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...
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...
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...
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...
Janice L. Coen; Marques Cameron; John Michalakes; Edward G. Patton; Philip J. Riggan; Kara M. Yedinak
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...
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,...
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)...
Full Text Available A new coupled system of aerosol HAM model and the Weather, Research and Forecasting (WRF model is presented in this paper. Unlike the current aerosol schemes used in WRF model, the HAM is using a "pseudomodal" approach for the representation of the particle size distribution. The aerosol components considered are sulfate, black carbon, particulate organic matter, sea salt and mineral dust. The preliminary model results are presented for two different 6-day simulation periods from 22 to 28 February 2006 as a winter period and 6 to 12 May 2006 as a mild period. The mean shortwave radiation and thermal forcing were calculated from the model simulations with and without aerosols feedback for two simulation periods. A negative radiative forcing and cooling of the atmosphere were found mainly over the regions of high emission of mineral dust. The absorption of shortwave radiation by black carbon caused warming effects in some regions with positive radiative forcing. The simulated daily mean sulfate mass concentration showed a rather good agreement with the measurements in the European EMEP network. The diurnal variation of the simulated hourly PM10 mass concentration at Tehran was also qualitatively close to the observations in both simulation periods. The model captured diurnal cycle and the magnitude of the observed PM10 concentration during most of the simulation periods. The differences between the observed and simulated PM10 concentration resulted mostly from limitation of the model in simulating the clouds and precipitation, transport errors and uncertainties in the particulate emission rates. The inclusion of aerosols feedback in shortwave radiation scheme improved the simulated daily mean shortwave radiation fluxes in Tehran for both simulation periods.
High-resolution weather forecasting is affected by many aspects, i.e. model initial conditions, subgrid-scale cumulus convection and cloud microphysics schemes. Recent 12km grid studies using the Weather Research and Forecasting (WRF) model have identified the importance of inco...
Burns, R.; Zhou, S.; Syed, R.
The NASA Unified Weather Research and Forecasting (NU-WRF) Model is an effort to unify several WRF variants developed at NASA and bring together NASA's existing earth science models and assimilation systems that simulate the interaction among clouds, aerosols, atmospheric gases, precipitation, and land surfaces. By developing NU-WRF, the NASA modeling community expects to: (1) facilitate better use of WRF for scientific research, (2) reduce redundancy in major WRF development, (3) prolong the serviceable life span of WRF, and (4) allow better use of NASA high-resolution satellite data for short term climate and weather research. This project involves multiple teams from different organizations and the research goals are still evolving. As a result, software engineering best practices are needed for software life-cycle management and testing, and to ensure reliability of the data being generated. NASA software engineers and scientists have worked together to develop software requirements, scientific use cases, automated regression tests, software release plans, and a revision control system. Nightly automated regression tests are being used on scaled-down versions of the use cases to test if any code changes have unintentionally changed the science results or made the software unstable. Revision control management is needed to track software changes that are made by the many developers involved in the project. The release planning helps to guide the release of NU-WRF versions to the NASA community and allows for making strategic changes in delivery dates and software features as needed. The team of software engineers and scientists have also worked on optimizing, generalizing, and testing existing model preprocessing codes and run scripts for the various models. Finally, the team developed model coupling tools to link WRF with NASA earth science models. NU-WRF 1.0 was based on WRF3.1.1 and was released to the NASA community in July 2010, providing the researchers
Hou, Tuanjie; Lei, Hengchi; Yang, Jiefan; Hu, Zhaoxia; Feng, Qiujuan
In this study, we investigated stratiform precipitation associated with an upper-level westerly trough and a cold front over northern China between 30 Apr. and 1 May 2009. We employed the Weather Research and Forecasting (WRF) model (version 3.4.1) to perform high-resolution numerical simulations of rainfall. We also conducted simulations with two microphysics schemes and sensitivity experiments without riming of snow and changing cloud droplet number concentrations (CDNCs) to determine the effect of snow riming on cloud structure and precipitation. Then we compared our results with CloudSat, Doppler radar and rain gauge observations. The comparison with the Doppler radar observations suggested that the WRF model was quite successful in capturing the timing and location of the stratiform precipitation region. Further comparisons with the CloudSat retrievals suggested that both microphysics schemes overestimated ice and liquid water contents. The sensitivity experiments without riming of snow suggested that the presence or absence of riming significantly influenced the precipitation distribution, but only slightly affected total accumulated precipitation. Without riming of snow, the changes of updrafts from the two microphysics schemes were different due to a different consideration of ice particle capacitance and latent heat effect of riming on deposition. While sensitivity experiments with three different CDNC values of 100, 250 and 1000 cm- 3 suggested variations in snow riming rates, changing CDNC had little impact on precipitation.
Chen, F.; Barlage, M. J.
The Weather Research and Forecasting (WRF) model has been widely used with high-resolution configuration in the weather and regional climate communities, and hence demands its land-surface models to treat not only fast-response processes, such as plant evapotranspiration that are important for numerical weather prediction but also slow-evolving processes such as snow hydrology and interactions between surface soil water and deep aquifer. Correctly representing urbanization, which has been traditionally ignored in coarse-resolution modeling, is critical for applying WRF to air quality and public health research. To meet these demands, numerous efforts have been undertaken to improve land-surface models (LSM) in WRF, including the recent implementation of the Noah-MP (Noah Multiple-Physics). Noah-MP uses multiple options for key sub-grid land-atmosphere interaction processes (Niu et al., 2011; Yang et al., 2011), and contains a separate vegetation canopy representing within- and under-canopy radiation and turbulent processes, a multilayer physically-based snow model, and a photosynthesis canopy resistance parameterization with a dynamic vegetation model. This paper will focus on the interactions between fast and slow land processes through: 1) a benchmarking of the Noah-MP performance, in comparison to five widely-used land-surface models, in simulating and diagnosing snow evolution for complex terrain forested regions, and 2) the effects of interactions between shallow and deep aquifers on regional weather and climate. Moreover, we will provide an overview of recent improvements of the integrated WRF-Urban modeling system, especially its hydrological enhancements that takes into account the effects of lawn irrigation, urban oasis, evaporation from pavements, anthropogenic moisture sources, and a green-roof parameterization.
Gibbs, J.A.; Fedorovich, E.; Eijk, A.M.J. van
Weather Research and Forecasting (WRF) model predictions using different boundary layer schemes and horizontal grid spacings were compared with observational and numerical large-eddy simulation data for conditions corresponding to a dry atmospheric convective boundary layer (CBL) over the southern
Warrach-Sagi, Kirsten; Schwitalla, Thomas; Wulfmeyer, Volker
Extreme events like the heat wave in summer 2003 in Central Europe and in August 2010 in Russia (which was associated with floodings of the Odra an in Pakistan) and severe floodings in Germany were caused by persistent so-called omega and blocking Vb weather situations in Europe. They are caused when quasi-stationary, quasi-resonant enhanced and quasi-resonant Rossby waves develop in mid-latitudes. To simulate quasi-stationary Rossby waves in numerical weather prediction and climate models at least a resolution of 20 km is required, however, to simulate the associated extremes the simulations need to be convection permitting. Further the high resolution allows the small scale structures to feed back to the large scale systems. Most of the current limited area, high-resolution models apply a domain which is centered over the region of interest. Such limited area model applications may suffer from a deterioration of synoptic features like low pressure systems due to effects in the boundary relaxation zone when downscaling reanalysis or global model simulation data. For Europe this is mainly caused by the longitudinal boundaries. A way to overcome these types of difficulties is to run a latitude belt simulation model. We applied the Weather Research and Forecasting (WRF) model with 3 km horizontal resolution for July and August 2013 forcing the model 6-hourly with ECMWF analyses data at 20°N and 65°N and with daily sea surface temperature data from the OSTIA project of the UK Met Office at 6 km resolution. The model domain encompasses 12000*1500*57 grid cells. First results of this so far unique simulation will be presented.
Klein, C.; Hoffmann, P.; Priesack, E.
Climate change causes altering distributions of meteorological factors influencing plant growth and its interactions between the land surface and the atmosphere. Recent studies show, that uncertainties in regional and global climate simulations are also caused by lacking descriptions of the soil-plant-atmosphere system. Therefore, we couple a mechanistic soil-plant model to a regional climate and forecast model. The detailed simulation of the water and energy exchanges, especially the transpiration of grassland and forests stands, are the key features of the modelling framework. The Weather Research and Forecasting model (WRF) (Skamarock 2008) is an open source mesoscale numerical weather prediction model. The WRF model was modified in a way, to either choose its native, static land surface model NOAH or the mechanistic eco-system model Expert-N 5.0 individually for every single grid point within the simulation domain. The Expert-N 5.0 modelling framework provides a highly modular structure, enabling the development and use of a large variety of different plant and soil models, including heat transfer, nitrogen uptake/turnover/transport as well as water uptake/transport and crop management. To represent the key landuse types grassland and forest, we selected two mechanistic plant models: The Hurley Pasture model (Thornley 1998) and a modified TREEDYN3 forest simulation model (Bossel 1996). The models simulate plant growth, water, nitrogen and carbon flows for grassland and forest stands. A mosaic approach enables Expert-N to use high resolution land use data e.g. CORINE Land Cover data (CLC, 2006) for the simulation, making it possible to simulate different land use distributions within a single grid cell. The coupling results are analyzed for plausibility and compared with the results of the default land surface model NOAH (Fei Chen and Jimy Dudhia 2010). We show differences between the mechanistic and the static model coupling, with focus on the feedback effects
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)
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.
Khandakar Md Habib Al Razi, Moritomi Hiroshi
Full Text Available 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.
Khandakar Md Habib Al Razi, Moritomi Hiroshi
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 u...
Iacono, Michael J. [Atmospheric and Environmental Research, Lexington, MA (United States)
The objective of this research has been to evaluate and implement enhancements to the computational performance of the RRTMG radiative transfer option in the Advanced Research version of the Weather Research and Forecasting (WRF) model. Efficiency is as essential as accuracy for effective numerical weather prediction, and radiative transfer is a relatively time-consuming component of dynamical models, taking up to 30-50 percent of the total model simulation time. To address this concern, this research has implemented and tested a version of RRTMG that utilizes graphics processing unit (GPU) technology (hereinafter RRTMGPU) to greatly improve its computational performance; thereby permitting either more frequent simulation of radiative effects or other model enhancements. During the early stages of this project the development of RRTMGPU was completed at AER under separate NASA funding to accelerate the code for use in the Goddard Space Flight Center (GSFC) Goddard Earth Observing System GEOS-5 global model. It should be noted that this final report describes results related to the funded portion of the originally proposed work concerning the acceleration of RRTMG with GPUs in WRF. As a k-distribution model, RRTMG is especially well suited to this modification due to its relatively large internal pseudo-spectral (g-point) dimension that, when combined with the horizontal grid vector in the dynamical model, can take great advantage of the GPU capability. Thorough testing under several model configurations has been performed to ensure that RRTMGPU improves WRF model run time while having no significant impact on calculated radiative fluxes and heating rates or on dynamical model fields relative to the RRTMG radiation. The RRTMGPU codes have been provided to NCAR for possible application to the next public release of the WRF forecast model.
Alfred M. Klausmann
Full Text Available Hurricane Irene caused widespread and significant impacts along the U.S. east coast during 27–29 August 2011. During this period, the storm moved across eastern North Carolina and then tracked northward crossing into Long Island and western New England. Impacts included severe flooding from the mid-Atlantic states into eastern New York and western New England, widespread wind damage and power outages across a large portion of southern and central New England, and a major storm surge along portions of the Long Island coast. The objective of this study was to conduct retrospective simulations using the Advanced Research Weather Research and Forecast (WRF-ARW model in an effort to reconstruct the storm’s surface wind field during the period of 27–29 August 2011. The goal was to evaluate how to use the WRF modeling system as a tool for reconstructing the surface wind field from historical storm events to support storm surge studies. The results suggest that, with even modest data assimilation applied to these simulations, the model was able to resolve the detailed structure of the storm, the storm track, and the spatial surface wind field pattern very well. The WRF model shows real potential for being used as a tool to analyze historical storm events to support storm surge studies.
Pour Biazar, Arastoo; White, Andrew; McNider, Richard; Khan, Maudood; Dornblaser, Bright; Wu, Yuling
Clouds have a significant role in air quality simulations as they modulate biogenic hydrocarbon emissions and photolysis rates, impact boundary-layer development, lead to deep vertical mixing of pollutants and precursors, and induce aqueous phase chemistry. Unfortunately, numerical meteorological models still have difficulty in creating clouds in the right place and time compared to observed clouds. This is especially the case when synoptic-scale forcing is weak, as often is the case during air pollution episodes in the Southeast United States. Thus, poor representation of clouds impacts the photochemical model's ability in simulating the air quality. However, since satellites provide the best observational platform for defining the formation and location of clouds, satellite observations can be of great value in retrospective simulations. Here, we present results from a recent activity in which the Geostationary Operational Environmental Satellite (GOES) derived cloud fields are assimilated within Weather Research and Forecasting (WRF) model to improve simulated clouds. The assimilation technique dynamically support cloud formation/dissipation within WRF based on GOES observations. The technique uses observations to identify model cloud errors, estimates a target vertical velocity and moisture to create/remove clouds, and adjust the flow field accordingly. The technique was implemented and tested in WRF for a month-long simulation during August 2006, and was tested in an air quality simulation over the period of August-September 2013 (NASA's Discover-AQ field campaign). The cloud assimilation on the average improved model cloud simulation by 15%. The cloud correction not only improved the spatial and temporal distribution of clouds, it also improved boundary layer temperature, humidity, and wind speed. These improvements in meteorological fields directly impacted the air quality simulations and altered trace gas concentrations. For air quality simulations, WRF
Marjanovic, N.; Mirocha, J. D.; Chow, F. K.
In this work, we examine the performance of a generalized actuator disk (GAD) model embedded within the Weather Research and Forecasting (WRF) atmospheric model to study wake effects on successive rows of turbines at a North American wind farm. These wake effects are of interest as they can drastically reduce down-wind energy extraction and increase turbulence intensity. The GAD, which is designed for turbulence-resolving simulations, is used within downscaled large-eddy simulations (LES) forced with mesoscale simulations and WRF's grid nesting capability. The GAD represents the effects of thrust and torque created by a wind turbine on the atmosphere within a disk representing the rotor swept area. The lift and drag forces acting on the turbine blades are parameterized using blade-element theory and the aerodynamic properties of the blades. Our implementation permits simulation of turbine wake effects and turbine/airflow interactions within a realistic atmospheric boundary layer flow field, including resolved turbulence, time-evolving mesoscale forcing, and real topography. The GAD includes real-time yaw and pitch control to respond realistically to changing flow conditions. Simulation results are compared to SODAR data from operating wind turbines and an already existing WRF mesoscale turbine drag parameterization to validate the GAD parameterization.
Olatinwo, Rabiu O; Prabha, Thara V; Paz, Joel O; Hoogenboom, Gerrit
Early leaf spot of peanut (Arachis hypogaea L.), a disease caused by Cercospora arachidicola S. Hori, is responsible for an annual crop loss of several million dollars in the southeastern United States alone. The development of early leaf spot on peanut and subsequent spread of the spores of C. arachidicola relies on favorable weather conditions. Accurate spatio-temporal weather information is crucial for monitoring the progression of favorable conditions and determining the potential threat of the disease. Therefore, the development of a prediction model for mitigating the risk of early leaf spot in peanut production is important. The specific objective of this study was to demonstrate the application of the high-resolution Weather Research and Forecasting (WRF) model for management of early leaf spot in peanut. We coupled high-resolution weather output of the WRF, i.e. relative humidity and temperature, with the Oklahoma peanut leaf spot advisory model in predicting favorable conditions for early leaf spot infection over Georgia in 2007. Results showed a more favorable infection condition in the southeastern coastline of Georgia where the infection threshold were met sooner compared to the southwestern and central part of Georgia where the disease risk was lower. A newly introduced infection threat index indicates that the leaf spot threat threshold was met sooner at Alma, GA, compared to Tifton and Cordele, GA. The short-term prediction of weather parameters and their use in the management of peanut diseases is a viable and promising technique, which could help growers make accurate management decisions, and lower disease impact through optimum timing of fungicide applications.
Olatinwo, Rabiu O.; Prabha, Thara V.; Paz, Joel O.; Hoogenboom, Gerrit
Early leaf spot of peanut ( Arachis hypogaea L.), a disease caused by Cercospora arachidicola S. Hori, is responsible for an annual crop loss of several million dollars in the southeastern United States alone. The development of early leaf spot on peanut and subsequent spread of the spores of C. arachidicola relies on favorable weather conditions. Accurate spatio-temporal weather information is crucial for monitoring the progression of favorable conditions and determining the potential threat of the disease. Therefore, the development of a prediction model for mitigating the risk of early leaf spot in peanut production is important. The specific objective of this study was to demonstrate the application of the high-resolution Weather Research and Forecasting (WRF) model for management of early leaf spot in peanut. We coupled high-resolution weather output of the WRF, i.e. relative humidity and temperature, with the Oklahoma peanut leaf spot advisory model in predicting favorable conditions for early leaf spot infection over Georgia in 2007. Results showed a more favorable infection condition in the southeastern coastline of Georgia where the infection threshold were met sooner compared to the southwestern and central part of Georgia where the disease risk was lower. A newly introduced infection threat index indicates that the leaf spot threat threshold was met sooner at Alma, GA, compared to Tifton and Cordele, GA. The short-term prediction of weather parameters and their use in the management of peanut diseases is a viable and promising technique, which could help growers make accurate management decisions, and lower disease impact through optimum timing of fungicide applications.
Deli, Meriem; Mkhinini, Nadia; Sadok Guellouz, Mohamed; Benjabrallah, Sadok
Tunisia is a country situated in the south of the mediterannen basin. This region undergoes direct and indirect effects of climate change. Actually, we notice that summer temperatures have risen during the last decades. Nevertheless research on the tunisian climate are not well developed and are mainly based on observations; short and mid term forecast are not available for the tunisian case. In this context we have studied the climate properties of Tunisia over the last 30 years using Weather Research and Forecasting model WRF. Afterwards we compared our results to the observations that we have obteined on behalf of the National Institute of Meteorology. Results were then used to calculate different climate indices related to the air temperature such as extreme values during a specific period exceeding specific limits (Percentile), warm and cold spell duration and growing season length. We admit that we have created a reliable database for the Tunisian climate.
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...
Cosgrove, B.; Gochis, D.; Clark, E. P.; Cui, Z.; Dugger, A. L.; Fall, G. M.; Feng, X.; Fresch, M. A.; Gourley, J. J.; Khan, S.; Kitzmiller, D.; Lee, H. S.; Liu, Y.; McCreight, J. L.; Newman, A. J.; Oubeidillah, A.; Pan, L.; Pham, C.; Salas, F.; Sampson, K. M.; Smith, M.; Sood, G.; Wood, A.; Yates, D. N.; Yu, W.; Zhang, Y.
The National Weather Service (NWS) National Water Center(NWC) is collaborating with the NWS National Centers for Environmental Prediction (NCEP) and the National Center for Atmospheric Research (NCAR) to implement a first-of-its-kind operational instance of the Weather Research and Forecasting (WRF)-Hydro model over the Continental United States (CONUS) and contributing drainage areas on the NWS Weather and Climate Operational Supercomputing System (WCOSS) supercomputer. The system will provide seamless, high-resolution, continuously cycling forecasts of streamflow and other hydrologic outputs of value from both deterministic- and ensemble-type runs. WRF-Hydro will form the core of the NWC national water modeling strategy, supporting NWS hydrologic forecast operations along with emergency response and water management efforts of partner agencies. Input and output from the system will be comprehensively verified via the NWC Water Resource Evaluation Service. Hydrologic events occur on a wide range of temporal scales, from fast acting flash floods, to long-term flow events impacting water supply. In order to capture this range of events, the initial operational WRF-Hydro configuration will feature 1) hourly analysis runs, 2) short-and medium-range deterministic forecasts out to two day and ten day horizons and 3) long-range ensemble forecasts out to 30 days. All three of these configurations are underpinned by a 1km execution of the NoahMP land surface model, with channel routing taking place on 2.67 million NHDPlusV2 catchments covering the CONUS and contributing areas. Additionally, the short- and medium-range forecasts runs will feature surface and sub-surface routing on a 250m grid, while the hourly analyses will feature this same 250m routing in addition to nudging-based assimilation of US Geological Survey (USGS) streamflow observations. A limited number of major reservoirs will be configured within the model to begin to represent the first-order impacts of
Zeng, X.-M.; Wang, B.; Zhang, Y.; Song, S.; Huang, X.; Zheng, Y.; Chen, C.; Wang, G.
Using a succession of 24 h Weather Research and Forecasting model (WRF) simulations, we investigate the sensitivity to initial soil moisture of a short-range high-temperature weather event that occurred in late July 2003 in East China. The initial soil moisture (SMOIS) in the Noah land surface scheme is adjusted (relative to the control run, CTL) for four groups of simulations: DRY25 (-25%), DRY50 (-50%), WET25 (+25%) and WET50 (+50%). Ten 24 h integrations are performed in each group. We focus on 2 m surface air temperature (SAT) greater than 35 °C (the threshold of "high-temperature" events in China) at 06:00 UTC (roughly 14:00 LT in the study domain) to analyse the occurrence of the high-temperature event. The 10-day mean results show that the 06:00 UTC SAT (SAT06) is sensitive to the SMOIS change; specifically, SAT06 exhibits an apparent increase with the SMOIS decrease (e.g. compared with CTL, DRY25 generally results in a 1 °C SAT06 increase over the land surface of East China), areas with 35 °C or higher SAT06 are the most affected, and the simulations are more sensitive to the SMOIS decrease than to the SMOIS increase, which suggests that hot weather can be amplified under low soil moisture conditions. Regarding the mechanism underlying the extremely high SAT06, sensible heat flux has been shown to directly heat the lower atmosphere, and latent heat flux has been found to be more sensitive to the SMOIS change, resulting in an overall increase in surface net radiation due to the increased greenhouse effect (e.g. with the SMOIS increase from DRY25 to CTL, the 10-day mean net radiation increases by 5 W m-2). Additionally, due to the unique and dynamic nature of the western Pacific subtropical high, negative feedback occurs between the regional atmospheric circulation and the air temperature in the lower atmosphere while positive feedback occurs in the mid-troposphere. Using a method based on an analogous temperature relationship, a detailed analysis of the
Zeng, X.-M.; Wang, B.; Zhang, Y.; Song, S.; Huang, X.; Zheng, Y.; Chen, C.; Wang, G.
Using the Weather Research and Forecasting model (WRF), we investigate the sensitivity of simulated short-range high-temperature weather to initial soil moisture for the East China extremely hot event in late July 2003 via a succession of 24 h simulations. The initial soil moisture (SMOIS) in the Noah land surface scheme is prescribed for five groups of designed simulations, i.e., relative to the control run (CTL), SMOIS is changed by -25, -50, +25 and +50% in the DRY25, DRY50, WET25 and WET50 groups, respectively, with ten 24 h-long integrations performed in each group. We focus on above-35 °C (standard of so-called "high-temperature" event in China) 2 m surface air temperature (SAT) at 06:00 UTC (roughly 12:00 LT in the study domain) to analyze the occurrence of the high-temperature event. Ten-day mean results show that the 06:00 UTC SAT (SAT06) is sensitive to the SMOIS change, i.e., SAT06 exhibits an apparent rising with the SMOIS decrease (e.g., compared with CTL, DRY25 results in a 1 °C SAT06 rising in general over land surface of East China), areas with above-35 °C SAT06 are most affected, and the simulations are found to be more sensitive to the SMOIS decrease than to the SMOIS increase, suggesting that hot weather can be amplified under low soil moisture conditions. With regard to the mechanism of influencing the extreme high SAT06, sensible heat flux shows to directly heat the lower atmosphere, latent heat flux is found to be more sensitive to the SMOIS change and results in the overall increase of surface net radiation due to the increased greenhouse effect (e.g., with the SMOIS increase of 25% from DRY25 to CTL, the ten-day mean net radiation is increased by 5 W m-2), and a negative (positive) feedback is found between regional atmospheric circulation and air temperature in the lower atmosphere (mid-troposphere) due to the unique dynamic nature of the western Pacific subtropical high. Using a method based on an analogous temperature relationship, a
Grell, Georg; Fast, Jerome D.; Gustafson, William I.; Peckham, Steven E.; McKeen, Stuart A.; Salzmann, Marc; Freitas, Saulo
This is a conference proceeding that is now being put together as a book. This is chapter 2 of the book: "INTEGRATED SYSTEMS OF MESO-METEOROLOGICAL AND CHEMICAL TRANSPORT MODELS" published by Springer. The chapter title is "On-line Chemistry within WRF: Description and Evaluation of a State-of-the-Art Multiscale Air Quality and Weather Prediction Model." The original conference was the COST-728/NetFAM workshop on Integrated systems of meso-meteorological and chemical transport models, Danish Meteorological Institute, Copenhagen, May 21-23, 2007.
Tolentino, Jerome T.; Rejuso, Ma. Victoria; Inocencio, Loureal Camille; Ang, Ma. Rosario Concepcion; Bagtasa, Gerry
Wind energy is one of the best options for renewable energy such that, many researchers work on wind resource assessment, specifically using numerical weather prediction (NWP) model to forecast atmospheric behavior on a given domain. In addition, every combination of parameterization configuration influences wind assessment. At the same time, choosing the optimum vertical and horizontal resolution may affect its output and processing time. Regardless of available researches, most of them focuses on mid-latitude area but not in tropical areas like the Philippines. In the study, sensitivity analysis of Weather Research and Forecasting (WRF) model version 3.6.1 with 4 configurations was performed. The duration of the simulation was from January 1, 2014 00:00 to December 31, 2014 23:00. The parameters involved were horizontal resolution and vertical levels. Also, meteorological input data from NCEP Final Analysis with 1 degree resolution every 6 hours was used. For validation, wind speed measurements at 10 m height from NOAA Integrated Surface Database (ISD) were utilized, of which, the 3 weather stations are located in Manila, Science Garden and Ninoy Aquino International Airport (NAIA). The results show that increasing horizontal resolution from 4 km to 1 km have no significant increase to wind speed accuracy. In majority, higher vertical levels tend to increase its accuracy. Moreover, the model has higher accuracy during the rainy season and months of April and May. Overall, the model overestimated the observed wind speed but the diurnal cycle of wind speed follows all the simulation.
horizontal grid spacing inner domain centered near San Diego, California. The San Diego area contains a mixture of urban , suburban, agricultural, and...Global Forecast System (GFS) model (Environmental Modeling Center 2003). The WRE–N is envisioned to be a rapid-update cycling application of WRF–ARW...surface– hydrology model with the Penn State-NCAR MM5 modeling system. Part I: Model implementation and sensitivity. Monthly Weather Review. 2001a
Full Text Available 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
Hyde, Peter; Mahalov, Alex; Li, Jialun
Nine dust storms in south-central Arizona, USA were simulated with the Weather Research and Forecasting with Chemistry model (WRF-Chem) at 2-km resolution. The windblown dust emission algorithm was the Air Force Weather Agency model. In comparison with ground-based PM10 observations, the model unevenly reproduces the dust storm events. The model adequately estimates the location and timing of the events, but it is unable to precisely replicate the magnitude and timing of the elevated hourly concentrations of particles 10 microns and smaller ([PM10]).Furthermore, the model under-estimated [PM10] in highly agricultural Pinal County because it under-estimated surface wind speeds and because the model's erodible fractions of the land surface data were too coarse to effectively resolve the active and abandoned agricultural lands. In contrast, the model over-estimated [PM10] in western Arizona along the Colorado River because it generated daytime sea breezes (from the nearby Gulf of California) whose surface-layer speeds were too strong. In Phoenix the model's performance depended on the event, with both under- and over-estimations partly due to incorrect representation of urban features. Sensitivity tests indicate that [PM10] highly rely on meteorological forcing. Increasing the fraction of erodible surfaces in the Pinal County agricultural areas improved the simulation of [PM10] in that region. Both 24-hr and 1-hr measured [PM10] were, for the most part, and especially in Pinal County, extremely elevated, with the former exceeding the health standard by as much as tenfold and the latter exceeding health-based guidelines by as much as seventy-fold. Monsoonal thunderstorms not only produce elevated [PM10], but also cause flash floods and disrupt water resource deliveries. Given the severity and frequency of these dust storms, and conceding that the modeling system applied in this work did not produce the desired agreement between simulations and observations, additional
Zhang, Hongliang; Chen, Gang; Hu, Jianlin; Chen, Shu-Hua; Wiedinmyer, Christine; Kleeman, Michael; Ying, Qi
The performance of the Weather Research and Forecasting (WRF)/Community Multi-scale Air Quality (CMAQ) system in the eastern United States is analyzed based on results from a seven-year modeling study with a 4-km spatial resolution. For 2-m temperature, the monthly averaged mean bias (MB) and gross error (GE) values are generally within the recommended performance criteria, although temperature is over-predicted with MB values up to 2K. Water vapor at 2-m is well-predicted but significant biases (>2 g kg(-1)) were observed in wintertime. Predictions for wind speed are satisfactory but biased towards over-prediction with 0
Cofino, Antonio S.; Fernández Quiruelas, Valvanuz; García Díez, Markel; Blanco Real, Jose C.; Fernández, Jesús
demonstrate the ability of Grid infrastructures in solving a scientific problem with interest and relevance on the meteorology area (implying a high computational cost) we will perform a high resolution hindcast on Southwestern Europe with ERA-Interim re-analysis as boundary and initial conditions. The production of an atmospheric hindcast at high resolution, will provide an appropriate assessment of the possibilities and uncertainties of the WRF model for the evaluation and forecasting of weather, energy and natural hazards.  http://www.meteo.unican.es/software/wrf4g
Realistic vegetation characteristics and phenology from the Moderate Resolution Imaging Spectroradiometer (MODIS) products improve the simulation for the meteorology and air quality modeling system WRF/CMAQ (Weather Research and Forecasting model and Community Multiscale Air Qual...
The four-dimensional data assimilation (FDDA) technique in the Weather Research and Forecasting (WRF) meteorological model has recently undergone an important update from the original version. Previous evaluation results have demonstrated that the updated FDDA approach in WRF pr...
This study evaluates interior nudging techniques using the Weather Research and Forecasting (WRF) model for regional climate modeling over the conterminous United States (CONUS) using a two-way nested configuration. NCEP–Department of Energy Atmospheric Model Intercomparison Pro...
Fredj, Erick; Givati, Amir
More accurate simulation of precipitation and streamflow is a challenge that can be addressed by using the Weather Research and Forecasting Model (WRF) in conjunction with the hydrological model coupling extension package (WRF-Hydro).This is demonstrated for the country of Israel and surrounding regions. Simulations from the coupled WRF/WRF-Hydro system were verified against measurements from rain gauges and hydrometric stations in the domain for the 2012-2013 and 2013-2014 winters (wet seasons). These periods were characterized by many punctuated hydrometeorological and hydroclimatic events, including both severe drought and extreme floods events. The WRF model simulations were initialized with 0.5 degree NOAA/NCEP GFS model data. The model domain was set up with 3 domains, up to 3km grid spacing resolution. The model configuration used here constitutes a fully distributed, 3-dimensional, variably-saturated surface and subsurface flow model. Application of terrain routing and, subsequently, channel and reservoir routing functions, to the uni-dimensional NOAA land surface model was motivated by the need to account for increased complexity in land surface states and fluxes and to provide a more physically-realistic conceptualization of terrestrial hydrologic processes. The simulation results indicated a good agreement with actual peak discharges for extreme flood events and for full hydrographs. Specifically the coupled WRF/WRF-Hydro model as configured in this study shows improvement in simulated precipitation over one way WRF precipitation simulations. The correlation between the observed and the simulated precipitation using the fully coupled WRF/WRF-Hydro system was higher than the standalone WRF model, especially for convective precipitation events that affect arid regions in the domain. The results suggest that the coupled WRF/WRF-Hydro system has potential for flood forecasting and flood warning purposes at 0-72 hour lead times for large cool season storm
Anupam Kumar; S K Roy Bhowmik; Ananda K Das
India Meteorological Department has implemented Polar WRF model for the Maitri (lat. 70° 45′S, long. 11° 44′E) region at the horizontal resolution of 15 km using initial and boundary conditions of the Global Forecast System (GFS T-382) operational at the India Meteorological Department (IMD). Main objective of this paper is to examine the performance skill of the model in the short-range time scale over the Maitri region. An inter-comparison of the time series of daily mean sea level pressure and surface winds of Maitri for the 24 hours and 48 hours forecast against the corresponding observed fields has been made using 90 days data for the period from 1 December 2010 to 28 February 2011. The result reveals that the performance of the Polar WRF is reasonable, good and superior to that of IMD GFS forecasts. GFS shows an underestimation of mean sea level pressure of the order of 16–17 hPa with root mean square errors (RMSE) of order 21 hPa, whereas Polar WRF shows an overestimation of the order of 3–4 hPa with RMSE of 4 hPa. For the surface wind, GFS shows an overestimation of 1.9 knots at 24 hours forecast and an underestimation of 3.7 knots at 48 hours forecast with RMSE ranging between 8 and 11 knots. Whereas Polar WRF shows underestimation of 1.4 knots and 1.2 knots at 24 hours and 48 hours forecast with RMSE of 5 knots. The results of a case study illustrated in this paper, reveal that the model is capable of capturing synoptic weather features of Antarctic region. The performance of the model is found to be comparable with that of Antarctic Meso-scale Prediction System (AMPS) products.
Emmanouil, George; Vlachogiannis, Diamanto; Sfetsos, Athanasios; Karozis, Stelios; Tasopoulou, Antonia
The accurate simulation of weather conditions is becoming more and more an issue of increased research interest and public demand. Because of the uncertainty in forecasting such phenomena, the investigation of the choice of a proper model configuration to simulate in a satisfactory way usual weather conditions, as well as extreme events is of crucial importance. In the framework of providing reliable weather forecasting, the WRF atmospheric model was employed to simulate the weather conditions during a usual for the area low pressure system that passed over the Greek peninsula during 2015 (September, 18-24). NCEP FNL analysis data were used for model input. The model configuration was setup to include three nested domains with increasing horizontal resolution inwards (11km, 2km and 0.5km respectively), centered in Attica area. The model parameterization was concluded following a number of sensitivity tests, previously carried out for other weather events including extremes in the same area, such as the Cleopatra cyclone. The main meteorological variables were analyzed and evaluation of the results was performed against in-situ measurements by the network of the Hellenic National Meteorological Service stations. The comparison of the September low-pressure event and the Cleopatra case study model results in temperature showed good agreement with the observations in both cases. Study of the precipitation fields yielded significant improvement compared to the analysis data of the NCEP FNL and the comparison between the model results and observed values was found to be good locally at some stations. The overall conclusion was that the model parameterization and applied methodology proved to be an efficient and useful tool for studying and forecasting such events.
Havens, S.; Marks, D. G.; Watson, K. A.; Masarik, M.; Flores, A. N.; Kormos, P.; Hedrick, A. R.
Traditional operational modeling tools used by water managers in the west are challenged by more frequently occurring uncharacteristic stream flow patterns caused by climate change. Water managers are now turning to new models based on the physical processes within a watershed to combat the increasing number of events that do not follow the historical patterns. The USDA-ARS has provided near real time snow water equivalent (SWE) maps using iSnobal since WY2012 for the Boise River Basin in southwest Idaho and since WY2013 for the Tuolumne Basin in California that feeds the Hetch Hetchy reservoir. The goal of these projects is to not only provide current snowpack estimates but to use the Weather Research and Forecasting (WRF) model to drive iSnobal in order to produce a forecasted stream flow when coupled to a hydrology model. The first step is to develop methods on how to create snow model forcing data from WRF outputs. Using a reanalysis 1km WRF dataset from WY2009 over the Boise River Basin, WRF model results like surface air temperature, relative humidity, wind, precipitation, cloud cover, and incoming long wave radiation must be downscaled for use in iSnobal. iSnobal results forced with WRF output are validated at point locations throughout the basin, as well as compared with iSnobal results forced with traditional weather station data. The presentation will explore the differences in forcing data derived from WRF outputs and weather stations and how this affects the snowpack distribution.
Impact Analysis of Climate Change on Snow over a Complex Mountainous Region Using Weather Research and Forecast Model (WRF Simulation and Moderate Resolution Imaging Spectroradiometer Data (MODIS-Terra Fractional Snow Cover Products
Full Text Available Climate change has a complex effect on snow at the regional scale. The change in snow patterns under climate change remains unknown for certain regions. Here, we used high spatiotemporal resolution snow-related variables simulated by a weather research and forecast model (WRF including snowfall, snow water equivalent and snow depth along with fractional snow cover (FSC data extracted from Moderate Resolution Imaging Spectroradiometer Data (MODIS-Terra to evaluate the effects of climate change on snow over the Heihe River Basin (HRB, a typical inland river basin in arid northwestern China from 2000 to 2013. We utilized Empirical Orthogonal Function (EOF analysis and Mann-Kendall/Theil-Sen trend analysis to evaluate the results. The results are as follows: (1 FSC, snow water equivalent, and snow depth across the entire HRB region decreased, especially at elevations over 4500 m; however, snowfall increased at mid-altitude ranges in the upstream area of the HRB. (2 Total snowfall also increased in the upstream area of the HRB; however, the number of snowfall days decreased. Therefore, the number of extreme snow events in the upstream area of the HRB may have increased. (3 Snowfall over the downstream area of the HRB decreased. Thus, ground stations, WRF simulations and remote sensing products can be used to effectively explore the effect of climate change on snow at the watershed scale.
Nicholls, Stephen D.; Decker, Steven G.; Tao, Wei-Kuo; Lang, Stephen E.; Shi, Jainn J.; Mohr, Karen I.
This study evaluated the impact of five single- or double-moment bulk microphysics schemes (BMPSs) on Weather Research and Forecasting model (WRF) simulations of seven intense wintertime cyclones impacting the mid-Atlantic United States; 5-day long WRF simulations were initialized roughly 24 h prior to the onset of coastal cyclogenesis off the North Carolina coastline. In all, 35 model simulations (five BMPSs and seven cases) were run and their associated microphysics-related storm properties (hydrometer mixing ratios, precipitation, and radar reflectivity) were evaluated against model analysis and available gridded radar and ground-based precipitation products. Inter-BMPS comparisons of column-integrated mixing ratios and mixing ratio profiles reveal little variability in non-frozen hydrometeor species due to their shared programming heritage, yet their assumptions concerning snow and graupel intercepts, ice supersaturation, snow and graupel density maps, and terminal velocities led to considerable variability in both simulated frozen hydrometeor species and radar reflectivity. WRF-simulated precipitation fields exhibit minor spatiotemporal variability amongst BMPSs, yet their spatial extent is largely conserved. Compared to ground-based precipitation data, WRF simulations demonstrate low-to-moderate (0.217-0.414) threat scores and a rainfall distribution shifted toward higher values. Finally, an analysis of WRF and gridded radar reflectivity data via contoured frequency with altitude diagrams (CFADs) reveals notable variability amongst BMPSs, where better performing schemes favored lower graupel mixing ratios and better underlying aggregation assumptions.
Diagne, Hadja Maïmouna; David, Mathieu; Boland, John; Schmutz, Nicolas; Lauret, Philippe
International audience; An efficient use of solar energy production requires reliable forecast information on surface solar irradiance. This article aims at providing a model output statistics (MOS) method of improving solar irradiance forecasts from Weather Research and Forecasting (WRF) Model.The WRF model was used to produce one year of day ahead solar irradiance forecasts covering Reunion Island with an horizontal resolution of 3 km. These forecasts are refined with a Kalman filter using ...
Kochanski, Adam K; Mandel, Jan; Kim, Minjeong
We describe two recent additions to WRF coupled with a fire spread model. Fire propagation is strongly dependent on fuel moisture, which in turn depends on the history of the atmosphere. We have implemented a equilibrium time-lag model of fuel moisture driven by WRF variables. The code allows the user to specify fuel parameters, with the defaults calibrated to the Canadian fire danger rating system for 10-hour fuel. The moisture model can run coupled with the atmosphere-fire model, or offline from WRF output to equilibrate the moisture over a period of time and to provide initial moisture conditions for a coupled atmosphere-fire-moisture simulation. The fire model also inserts smoke tracers into WRF-Chem to model the transport of fire emissions. The coupled model is available from OpenWFM.org. An earlier version of the fire model coupled with atmosphere is a part of WRF release.
Mielikainen, Jarno; Huang, Bormin; Huang, Allen H.
Next-generation mesoscale numerical weather prediction system, the Weather Research and Forecasting (WRF) model, is a designed for dual use for forecasting and research. WRF offers multiple physics options that can be combined in any way. One of the physics options is radiance computation. The major source for energy for the earth's climate is solar radiation. Thus, it is imperative to accurately model horizontal and vertical distribution of the heating. Goddard solar radiative transfer model includes the absorption duo to water vapor,ozone, ozygen, carbon dioxide, clouds and aerosols. The model computes the interactions among the absorption and scattering by clouds, aerosols, molecules and surface. Finally, fluxes are integrated over the entire longwave spectrum.In this paper, we present our results of optimizing the Goddard longwave radiative transfer 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 coprocessor supports all important Intel development tools. Thus, the development environment is familiar one 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 discusses in this paper. The optimizations improved the performance of the original Goddard longwave radiative transfer scheme on Xeon Phi 7120P by a factor of 2.2x. Furthermore, the same optimizations improved the performance of the Goddard longwave radiative transfer scheme on a dual socket configuration of eight core Intel Xeon E5-2670 CPUs by a factor of 2.1x compared to the original Goddard longwave radiative transfer scheme code.
Unal, E.; Ramirez, J. A.
Abstract. Flash floods are one of the most damaging natural disasters producing large socio-economic losses. Projected impacts of climate change include increases in the magnitude and the frequency of flash floods all around the world. Therefore, it is important to understand the physical processes of flash flooding to enhance our capacity for prediction, prevention, risk management, and recovery. However, understanding these processes is ambitious because of small spatial scale and sudden nature of flash floods, interactions with complex topography and land use, difficulty in defining initial soil moisture conditions, non-linearity of catchment response, and high space-time variability of storm characteristics. Thus, detailed regional case studies are needed, especially with respect to the interactions between the land surface and the atmosphere. One such flash flood event occurred recently in the Front Range of the Rocky Mountains of Colorado during September 9-15, 2013 causing 10 fatalities and $3B cost in damages. An unexpected persistent and moist weather pattern located over the mountains and produced seven-day extreme rainfall fed by moisture input from the Gulf of Mexico. We used a coupled WRF-WRF-Hydro modeling system to simulate this event for better understanding of the physical process and of the sensitivity of the hydrologic response to storm characteristics, initial soil moisture conditions, and watershed characteristics.
Nielsen, Joakim Refslund
-ments are still needed in the representation of the land surface variability and of some key land surface processes. This thesis explores two possibilities for improving the near-surface model predictions using the mesoscale Weather Research and Forecasting (WRF) model. In the _rst approach, data from satellite......For accurate predictions of weather and climate, it is important that the land surface and its processes are well represented. In a mesoscale model the land surface processes are calculated in a land surface model (LSM). These pro-cesses include exchanges of energy, water and momentum between...... the land surface components, such as vegetation and soil, and their interactions with the atmosphere. The land surface processes are complex and vary in time and space. Signi_cant e_ort by the land surface community has therefore been invested in improving the LSMs over the recent decades. However, improve...
Tulich, S. N.
This paper describes a general method for the treatment of convective momentum transport (CMT) in large-scale dynamical solvers that use a cyclic, two-dimensional (2-D) cloud-resolving model (CRM) as a "superparameterization" of convective-system-scale processes. The approach is similar in concept to traditional parameterizations of CMT, but with the distinction that both the scalar transport and diagnostic pressure gradient force are calculated using information provided by the 2-D CRM. No assumptions are therefore made concerning the role of convection-induced pressure gradient forces in producing up or down-gradient CMT. The proposed method is evaluated using a new superparameterized version of the Weather Research and Forecast model (SP-WRF) that is described herein for the first time. Results show that the net effect of the formulation is to modestly reduce the overall strength of the large-scale circulation, via "cumulus friction." This statement holds true for idealized simulations of two types of mesoscale convective systems, a squall line, and a tropical cyclone, in addition to real-world global simulations of seasonal (1 June to 31 August) climate. In the case of the latter, inclusion of the formulation is found to improve the depiction of key synoptic modes of tropical wave variability, in addition to some aspects of the simulated time-mean climate. The choice of CRM orientation is also found to importantly affect the simulated time-mean climate, apparently due to changes in the explicit representation of wide-spread shallow convective regions.
Udina, Mireia; Sun, Jielun; Kosović, Branko; Soler, Maria Rosa
Following Sun et al. (J Atmos Sci 69(1):338-351, 2012), vertical variations of turbulent mixing in stably stratified and neutral environments as functions of wind speed are investigated using the large-eddy simulation capability in the Weather Research and Forecasting model. The simulations with a surface cooling rate for the stable boundary layer (SBL) and a range of geostrophic winds for both stable and neutral boundary layers are compared with observations from the Cooperative Atmosphere-Surface Exchange Study 1999 (CASES-99). To avoid the uncertainty of the subgrid scheme, the investigation focuses on the vertical domain when the ratio between the subgrid and the resolved turbulence is small. The results qualitatively capture the observed dependence of turbulence intensity on wind speed under neutral conditions; however, its vertical variation is affected by the damping layer used in absorbing undesirable numerical waves at the top of the domain as a result of relatively large neutral turbulent eddies. The simulated SBL fails to capture the observed temperature variance with wind speed and the observed transition from the SBL to the near-neutral atmosphere with increasing wind speed, although the vertical temperature profile of the simulated SBL resembles the observed profile. The study suggests that molecular thermal conduction responsible for the thermal coupling between the surface and atmosphere cannot be parameterized through the Monin-Obukhov bulk relation for turbulent heat transfer by applying the surface radiation temperature, as is common practice when modelling air-surface interactions.
Mejia-Estrada, Iskra; Bates, Paul; Ángel Rico-Ramírez, Miguel
Understanding the natural processes that precede the occurrence of flash floods is crucial to improve the future flood projections in a changing climate. Using numerical weather prediction tools allows to determine one of the triggering conditions for these particularly dangerous events, difficult to forecast due to their short lead-time. However, simulating the spatial and temporal evolution of the rainfall that leads to a rapid rise in river levels requires determining the best model configuration without compromising the computational efficiency. The current research involves the results of the first part of a cascade modeling approach, where the Weather Research and Forecasting (WRF) model is used to simulate the heavy rainfall in the east of the UK in June 2012 when stationary thunderstorms caused 2-hour accumulated values to match those expected in the whole month of June over the city of Newcastle. The optimum model set-up was obtained after extensive testing regarding physics parameterizations, spin-up times, datasets used as initial conditions and model resolution and nesting, hence determining its sensitivity to reproduce localised events of short duration. The outputs were qualitatively and quantitatively assessed using information from the national weather radar network as well as interpolated rainfall values from gauges, respectively. Statistical and skill score values show that the model is able to produce reliable accumulated precipitation values while explicitly solving the atmospheric equations in high resolution domains as long as several hydrometeors are considered with a spin-up time that allows the model to assimilate the initial conditions without going too far back in time from the event of interest. The results from the WRF model will serve as input to run a semi-distributed hydrological model to determine the rainfall-runoff relationship within an uncertainty assessment framework that will allow evaluating the implications of assumptions at
Hahmann, Andrea N.; Vincent, Claire Louise; Peña, Alfredo
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......High-quality tall mast and wind lidar measurements over the North and Baltic Seas are used to validate the wind climatology produced from winds simulated by the Weather, Research and Forecasting (WRF) model in analysis mode. Biases in annual mean wind speed between model and observations at heights...... around 100m are smaller than 3.2% at offshore sites, except for those that are affected by the wake of a wind farm or the coastline. These biases are smaller than those obtained by using winds directly from the reanalysis. We study the sensitivity of the WRF-simulated wind climatology to various model...
Kochanski, Adam K; Mandel, Jan; Clements, Craig B
Atmospheric pollution regulations have emerged as a dominant obstacle to prescribed burns. Thus, forecasting the pollution caused by wildland fires has acquired high importance. WRF and SFIRE model wildland fire spread in a two-way interaction with the atmosphere. The surface heat flux from the fire causes strong updrafts, which in turn change the winds and affect the fire spread. Fire emissions, estimated from the burning organic matter, are inserted in every time step into WRF-Chem tracers at the lowest atmospheric layer. The buoyancy caused by the fire then naturally simulates plume dynamics, and the chemical transport in WRF-Chem provides a forecast of the pollution spread. We discuss the choice of wood burning models and compatible chemical transport models in WRF-Chem, and demonstrate the results on case studies.
Boxe, C.; Hafsa, U.; Blue, S.; Emmanuel, S.; Griffith, E.; Moore, J.; Tam, J.; Khan, I.; Cai, Z.; Bocolod, B.; Zhao, J.; Ahsan, S.; Gurung, D.; Tang, N.; Bartholomew, J.; Rafi, R.; Caltenco, K.; Rivas, M.; Ditta, H.; Alawlaqi, H.; Rowley, N.; Khatim, F.; Ketema, N.; Strothers, J.; Diallo, I.; Owens, C.; Radosavljevic, J.; Austin, S. A.; Johnson, L. P.; Zavala-Gutierrez, R.; Breary, N.; Saint-Hilaire, D.; Skeete, D.; Stock, J.; Salako, O.
WRF-Chem is the Weather Research and Forecasting (WRF) model coupled with Chemistry. The model simulates the emission, transport, mixing, and chemical transformation of trace gases and aerosols simultaneously with the meteorology. The model is used for investigation of regional-scale air quality, field program analysis, and cloud-scale interactions between clouds and chemistry. The development of WRF-Chem is a collaborative effort among the community led by NOAA/ESRL scientists. The Official WRF-Chem web page is located at the NOAA web site. Our model development is closely linked with both NOAA/ESRL and DOE/PNNL efforts. Description of PNNL WRF-Chem model development is located at the PNNL web site as well as the PNNL Aerosol Modeling Testbed. High school and undergraduate students, representative of academic institutions throughout USA's Tri-State Area (New York, New Jersey, Connecticut), set up WRF-Chem on CUNY CSI's High Performance Computing Center. Students learned the back-end coding that governs WRF-Chems structure and the front-end coding that displays visually specified weather simulations and forecasts. Students also investigated the impact, to select baseline simulations/forecasts, due to the reaction, NO2 + OH + M → HOONO + M (k = 9.2 × 10-12 cm3 molecule-1 s-1, Mollner et al. 2010). The reaction of OH and NO2 to form gaseous nitric acid (HONO2) is among the most influential and in atmospheric chemistry. Till a few years prior, its rate coefficient remained poorly determined under tropospheric conditions because of difficulties in making laboratory measurements at 760 torr. These activities fosters student coding competencies and deep insights into weather forecast and air quality.
Raghavan, S. V.; Vu, M. T.; Liong, S. Y.
We present an analysis of the present-day (1961-1990) regional climate simulations over Vietnam. The regional climate model Weather Research and Forecasting (WRF) was driven by the global reanalysis ERA40. The performance of the regional climate model in simulating the observed climate is evaluated with a main focus on precipitation and temperature. The regional climate model was able to reproduce the observed spatial patterns of the climate, although with some biases. The model also performed better in reproducing the extreme precipitation and the interannual variability. Overall, the WRF model was able to simulate the main regional signatures of climate variables, seasonal cycles, and frequency distributions. This study is an evaluation of the present-day climate simulations of a regional climate model at a resolution of 25 km. Given that dynamical downscaling has become common for studying climate change and its impacts, the study highlights that much more improvements in modeling might be necessary to yield realistic simulations of climate at high resolutions before they can be used for impact studies at a local scale. The need for a dense network of observations is also realized as observations at high resolutions are needed when it comes to evaluations and validations of models at sub-regional and local scales.
Full Text Available Among the parameters that must be considered for an offshore wind farm development, the stability conditions of the marine atmospheric boundary layer (MABL are of significant importance. Atmospheric stability is a vital parameter in wind resource assessment (WRA due to its direct relation to wind and turbulence profiles. A better understanding of the stability conditions occurring offshore and of the interaction between MABL and wind turbines is needed. Accurate simulations of the offshore wind and stability conditions using mesoscale modelling techniques can lead to a more precise WRA. However, the use of any mesoscale model for wind energy applications requires a proper validation process to understand the accuracy and limitations of the model. For this validation process, the weather research and forecasting (WRF model has been applied over the North Sea during March 2005. The sensitivity of the WRF model performance to the use of different horizontal resolutions, input datasets, PBL parameterisations, and nesting options was examined. Comparison of the model results with other modelling studies and with high quality observations recorded at the offshore measurement platform FINO1 showed that the ERA-Interim reanalysis data in combination with the 2.5-level MYNN PBL scheme satisfactorily simulate the MABL over the North Sea.
Steeneveld, G. J.; Tolk, L. F.; Moene, A. F.; Hartogensis, O. K.; Peters, W.; Holtslag, A. A. M.
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 (Net
Wang, Hongshuai; Yao, Yongqiang; Liu, Liyong; Qian, Xuan; Yin, Jia
Atmospheric optical turbulence modeling and forecast for astronomy is a relatively recent discipline, but has played important roles in site survey, optimization of large telescope observing tables, and in the applications of adaptive optics technique. The numerical approach, by using of meteorological parameters and parameterization of optical turbulence, can provide all the optical turbulence parameters related, such as C2n profile, coherent length, wavefront coherent time, seeing, isoplanatic angle, and so on. This is particularly interesting for searching new sites without the long and expensive site testing campaigns with instruments. Earlier site survey results by the site survey team of National Astronomical Observatories of China imply that the south-west Tibet, Ali, is one of the world best IR and sub-mm site. For searching the best site in Ali area, numerical approach by Weather and Research Forecasting (WRF) model had been used to evaluate the climatology of the optical turbulence. The WRF model is configured over a domain 200km×200km with 1km horizontal resolution and 65 vertical levels from ground to the model top(10millibars) in 2010. The initial and boundary conditions for the model are provided by the 1° × 1° Global Final Analysis data from NCEP. The distribution and seasonal variation of optical turbulence parameters over this area are presented.
Wiersema, D. J.; Lundquist, K. A.; Martien, P. T.; Rivard, T.; Chow, F. K.
Urban air quality modeling at the neighborhood scale has potential to become an important tool for long term exposure studies, regulation, and urban planning. Current generation models for urban flow or air quality are limited by laborious mesh creation, terrain slope restrictions due to coordinate transformations, lack of atmospheric physics, and/or omission of regional meteorological effects. To avoid these limitations we have extended the functionality of an existing model, IBM-WRF, a modified version of the Weather Research and Forecasting model (WRF) which uses an immersed boundary method (IBM) (Lundquist et al. 2010, 2012). The immersed boundary method used in our model allows for the evaluation of flow over complex urban geometries including vertical surfaces, sharp corners, and local topographic variations. Lateral boundaries in IBM-WRF can be prescribed using output from the standard WRF model, allowing for realistic meteorological input. IBM-WRF is being used to investigate transport and trapping of vehicle emissions around a proposed affordable housing development located adjacent to a major freeway which transports 250,000+ vehicles per day. Urban topography is created using high-resolution airborne LIDAR building data combined with ground elevation data. Emission locations and strengths are assigned using data provided by the Bay Area Air Quality Management District. Development is underway to allow for meteorological input to be created using the WRF model configured to use nested domains. This will allow for synoptic scale phenomena to affect the neighborhood scale IBM-WRF domain, which has a horizontal resolution on the order of one meter. Initial results from IBM-WRF are presented here and will ultimately be used to assist planning efforts to reduce local air pollution exposure and minimize related associated adverse health effects. Lundquist, K., F. Chow, and J. Lundquist, 2010: An immersed boundary method for the weather research and forecasting
Zhang, Xu; Bao, Jian-Wen; Chen, Baode
A new three-dimensional (3D) turbulent kinetic energy (TKE) subgrid mixing model is developed to address the problem of simulating the convective boundary layer (CBL) across the terra incognita in the Advanced Research version of the Weather Research and Forecasting Model (ARW-WRF). The new model combines the horizontal and vertical subgrid turbulent mixing into a single energetically consistent framework, in contrast to the convectional one-dimensional (1D) planetary boundary layer (PBL) schemes. The transition between large-eddy simulation (LES) and mesoscale limit is accomplished in the new scale-adaptive model. A series of dry CBL and real-time simulations using the WRF model are carried out, in which the newly-developed, scale-adaptive, more general and energetically consistent TKE-based model is compared with the conventional 1D TKE-based PBL schemes for parameterizing vertical subgrid turbulent mixing against the WRF LES dataset and observations. The characteristics of the WRF-simulated results using the new and conventional schemes are compared. The importance of including the nonlocal component in the vertical buoyancy specification in the newly-developed general TKE-based scheme is illustrated. The improvements of the new scheme over convectional PBL schemes across the terra incognita can be seen in the partitioning of vertical flux profiles. Through comparing the results from the simulations against the WRF LES dataset and observations, we will show the feasibility of using the new scheme in the WRF model in the lieu of the conventional PBL parameterization schemes.
Vincent, Claire Louise; Liu, Yubao
The increasing penetration of wind energy into national electricity markets has increased the demand for accurate surface layer wind forecasts. There has recently been a focus on forecasting the wind at wind farm sites using both statistical models and numerical weather prediction (NWP) models. Recent advances in computing capacity and non-hydrostatic NWP models means that it is possible to nest mesoscale models down to Large Eddy Simulation (LES) scales over the spatial area of a typical wind farm. For example, the WRF model (Skamarock 2008) has been run at a resolution of 123 m over a wind farm site in complex terrain in Colorado (Liu et al. 2009). Although these modelling attempts indicate a great hope for applying such models for detailed wind forecasts over wind farms, one of the obvious challenges of running the model at this resolution is that while some boundary layer structures are expected to be modelled explicitly, boundary layer eddies into the inertial sub-range can only be partly captured. Therefore, the amount and nature of sub-grid-scale mixing that is required is uncertain. Analysis of Liu et al. (2009) modelling results in comparison to wind farm observations indicates that unrealistic wind speed fluctuations with a period of around 1 hour occasionally occurred during the two day modelling period. The problem was addressed by re-running the same modelling system with a) a modified diffusion constant and b) two-way nesting between the high resolution model and its parent domain. The model, which was run with horizontal grid spacing of 370 m, had dimensions of 505 grid points in the east-west direction and 490 points in the north-south direction. It received boundary conditions from a mesoscale model of resolution 1111 m. Both models had 37 levels in the vertical. The mesoscale model was run with a non-local-mixing planetary boundary layer scheme, while the 370 m model was run with no planetary boundary layer scheme. It was found that increasing the
Wang, Z.; yang, J.
Rapid urbanization has emerged as the source of many adverse effects that challenge the environmental sustainability of cities under changing climatic patterns. One essential key to address these challenges is to physically resolve the dynamics of urban-land-atmospheric interactions. To investigate the impact of urbanization on regional climate, physically-based single layer urban canopy model (SLUCM) has been developed and implemented into the Weather Research and Forecasting (WRF) platform. However, due to the lack of realistic representation of urban hydrological processes, simulation of urban climatology by current coupled WRF-SLUCM is inevitably inadequate. Aiming at improving the accuracy of simulations, recently we implemented urban hydrological processes into the model, including (1) anthropogenic latent heat, (2) urban irrigation, (3) evaporation over impervious surface, and (4) urban oasis effect. In addition, we couple the green roof system into the model to verify its capacity in alleviating urban heat island effect at regional scale. Driven by different meteorological forcings, offline tests show that the enhanced model is more accurate in predicting turbulent fluxes arising from built terrains. Though the coupled WRF-SLUCM has been extensively tested against various field measurement datasets, accurate input parameter space needs to be specified for good model performance. As realistic measurements of all input parameters to the modeling framework are rarely possible, understanding the model sensitivity to individual parameters is essential to determine the relative importance of parameter uncertainty to model performance. Thus we further use an advanced Monte Carlo approach to quantify relative sensitivity of input parameters of the hydrological model. In particular, performance of two widely used soil hydraulic models, namely the van Genuchten model (based on generic soil physics) and an empirical model (viz. the CHC model currently adopted in WRF
Obsgrid) that creates input data for the Advanced Research version of the Weather Research and Forecasting model (WRF-ARW) is modified to perform a...Configuration The Advanced Research version of the Weather Research and Forecasting model (WRF-ARW) V3.6.1 (Skamarock et al. 2008) is applied with 56 vertical...those with more benign weather. On 7 February a trough moved onshore and led to widespread precipitation in the region . More quiescent weather was in
Tan, Qian; Santanello, Joseph A., Jr.; Zhou, Shujia; Tao, Zhining; Peters-Lidard, Christa d.; Chn, Mian
Land-Atmosphere coupling is typically designed and implemented independently for physical (e.g. water and energy) and chemical (e.g. biogenic emissions and surface depositions)-based models and applications. Differences in scale, data requirements, and physics thus limit the ability of Earth System models to be fully coupled in a consistent manner. In order for the physical-chemical-biological coupling to be complete, treatment of the land in terms of surface classification, condition, fluxes, and emissions must be considered simultaneously and coherently across all components. In this study, we investigate a coupling strategy for the NASA-Unified Weather Research and Forecasting (NU-WRF) model that incorporates the traditionally disparate fluxes of water and energy through NASA's LIS (Land Information System) and biogenic emissions through BEIS (Biogenic Emissions Inventory System) and MEGAN (Model of Emissions of Gases and Aerosols from Nature) into the atmosphere. In doing so, inconsistencies across model inputs and parameter data are resolved such that the emissions from a particular plant species are consistent with the heat and moisture fluxes calculated for that land cover type. In turn, the response of the atmospheric turbulence and mixing in the planetary boundary layer (PBL) acts on the identical surface type, fluxes, and emissions for each. In addition, the coupling of dust emission within the NU-WRF system is performed in order to ensure consistency and to maximize the benefit of high-resolution land representation in LIS. The impacts of those self-consistent components on' the simulation of atmospheric aerosols are then evaluated through the WRF-Chem-GOCART (Goddard Chemistry Aerosol Radiation and Transport) model. Overall, this ambitious project highlights the current difficulties and future potential of fully coupled. components. in Earth System models, and underscores the importance of the iLEAPS community in supporting improved knowledge of
Quan, Jiping; Di, Zhenhua; Duan, Qingyun; Gong, Wei; Wang, Chen
Tuning model parameters to match model simulations with observations can be an effective way to enhance the performance of numerical weather prediction (NWP) models such as Weather Research and Forecasting (WRF) model. However, this is a very complicated process as a typical NWP model involves many model parameters and many output variables. One must take a multi-objective approach to ensure all of the major simulated model outputs are satisfactory. This talk presents the results of an investigation of multi-objective parameter sensitivity analysis of the WRF model to different model outputs, including conventional surface meteorological variables such as precipitation, surface temperature, humidity and wind speed, as well as atmospheric variables such as total precipitable water, cloud cover, boundary layer height and outgoing long radiation at the top of the atmosphere. The goal of this study is to identify the most important parameters that affect the predictive skill of short-range meteorological forecasts by the WRF model. The study was performed over the Greater Beijing Region of China. A total of 23 adjustable parameters from seven different physical parameterization schemes were considered. Using a multi-objective global sensitivity analysis method, we examined the WRF model parameter sensitivities to the 5-day simulations of the aforementioned model outputs. The results show that parameter sensitivities vary with different model outputs. But three to four of the parameters are shown to be sensitive to all model outputs considered. The sensitivity results from this research can be the basis for future model parameter optimization of the WRF model.
Full Text Available Quantitative precipitation estimation and forecasting (QPE and QPF are among the most challenging tasks in atmospheric sciences. In this work, QPE based on numerical modelling and data assimilation is investigated. Key components are the Weather Research and Forecasting (WRF model in combination with its 3D variational assimilation scheme, applied on the convection-permitting scale with sophisticated model physics over central Europe. The system is operated in a 1-hour rapid update cycle and processes a large set of in situ observations, data from French radar systems, the European GPS network and satellite sensors. Additionally, a free forecast driven by the ECMWF operational analysis is included as a reference run representing current operational precipitation forecasting. The verification is done both qualitatively and quantitatively by comparisons of reflectivity, accumulated precipitation fields and derived verification scores for a complex synoptic situation that developed on 26 and 27 September 2012. The investigation shows that even the downscaling from ECMWF represents the synoptic situation reasonably well. However, significant improvements are seen in the results of the WRF QPE setup, especially when the French radar data are assimilated. The frontal structure is more defined and the timing of the frontal movement is improved compared with observations. Even mesoscale band-like precipitation structures on the rear side of the cold front are reproduced, as seen by radar. The improvement in performance is also confirmed by a quantitative comparison of the 24-hourly accumulated precipitation over Germany. The mean correlation of the model simulations with observations improved from 0.2 in the downscaling experiment and 0.29 in the assimilation experiment without radar data to 0.56 in the WRF QPE experiment including the assimilation of French radar data.
Hirtl, Marcus; Mantovani, Simone; Krüger, Bernd C.; Flandorfer, Claudia; Langer, Matthias
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
Dekić, L.; Mihalović, A.; Jovičić, I.; Vladiković, D.; Jerinić, J.; Ivković, M.
This paper examines two episodes of heavy rainfall and significantly increased water levels. The first case relates to the period including the beginning and the end of the third decade of June 2010 at the Kolubara river basin, where extreme rainfall led to two big flood waves on the Kolubara river, whereat water levels exceeded both regular and extraordinary flood defence and approached their historical maximum. The second case relates to the period including the end of November and the beginning of December 2010 at the Jadar river basin, where heavier precipitation caused the water levels of the basin to reach and surpass the occurrence limit (warning level). The HBV (Hydrological Bureau Waterbalance-section) rainfall/snowmelt - runoff model installed at the RHMSS uses gridded quantitative precipitation and air temperature forecast for 72 hours in advance based on meteorological weather forecast WRF-NMM mesoscale model. Nonhydrostatic Mesoscale Model (NMM) core of the Weather Research and Forecasting (WRF) system is flexible state-of-the-art numerical weather prediction model capable to describe and estimate powerful nonhydrostatic mechanism in convective clouds that cause heavy rain. The HBV model is a semi-distributed conceptual catchment model in which the spatial structure of a catchment area is not explicitly modelled. Instead, the sub-basin represents a primary modelling unit while the basin is characterised by area-elevation distribution and classification of vegetation cover and land use distributed by height zone. WRF-NMM forecast shows very good agreement with observations in terms of timing, location and amount of precipitation. They are used as input for HBV model, forecasted discharges at the output profile of the selected river basin represent model output for consideration. 1 Republic Hydrometeorological Service of Serbia
Full Text Available We describe the physical model, numerical algorithms, and software structure of a model consisting of the Weather Research and Forecasting (WRF model, coupled with the fire-spread model (SFIRE module. In every time step, the fire model inputs the surface wind, which drives the fire, and outputs the heat flux from the fire into the atmosphere, which in turn influences the atmosphere. SFIRE is implemented by the level set method, which allows a submesh representation of the burning region and a flexible implementation of various kinds of ignition. The coupled model is capable of running on a cluster faster than real time even with fine resolution in dekameters. It is available as a part of the Open Wildland Fire Modeling (OpenWFM environment at http://openwfm.org, which contains also utilities for visualization, diagnostics, and data processing, including an extended version of the WRF Preprocessing System (WPS. The SFIRE code with a subset of the features is distributed with WRF 3.3 as WRF-Fire.
Khandakar Md Habib Al Razi
Full Text Available The fully coupled WRF/Chem (Weather Research and Forecasting/Chemistry model is used to simulate air quality over the Sea of Japan coastal area. Anthropogenic surface emissions database used as input for this model are mainly based on Global hourly emissions data (dust, sea salt, biomass burning, RETRO (REanalysis of the TROpospheric chemical composition, GEIA (Global Emissions Inventory Activity and POET (Precursors of ozone and their Effects in the Troposphere. Climatologic concentrations of particulate matters derived from Regional acid Deposition Model (RADM2 chemical mechanism and Secondary Organic Aerosol Model (MADE/SORGAM with aqueous reaction were used to deduce the corresponding aerosols fluxes for input to the WRF/Chem. The model was firstly integrated for 48 hours continuously starting from 00:00 UTC of 14 March 2008 to evaluate ozone concentrations and other precursor pollutants were analyzed. WPS meteorological data were used for the simulation of WRF/Chem model in this study. Despite the low resolution of the area global emissions and the weak density of the local point emissions, it has been found that WRF/Chem simulates quite well with the diurnal variation of the chemical species concentrations over the Sea of Japan coastal area. The simulations conducted in this study showed that due to the geographical and climatologically characteristics, it is still environmentally friendly by the transported pollutants in this region.
Decadal application of WRF/Chem for regional air quality and climate modeling over the U.S. under the representative concentration pathways scenarios. Part 1: Model evaluation and impact of downscaling
Yahya, Khairunnisa; Wang, Kai; Campbell, Patrick; Chen, Ying; Glotfelty, Timothy; He, Jian; Pirhalla, Michael; Zhang, Yang
An advanced online-coupled meteorology-chemistry model, i.e., the Weather Research and Forecasting Model with Chemistry (WRF/Chem), is applied for current (2001-2010) and future (2046-2055) decades under the representative concentration pathways (RCP) 4.5 and 8.5 scenarios to examine changes in future climate, air quality, and their interactions. In this Part I paper, a comprehensive model evaluation is carried out for current decade to assess the performance of WRF/Chem and WRF under both scenarios and the benefits of downscaling the North Carolina State University's (NCSU) version of the Community Earth System Model (CESM_NCSU) using WRF/Chem. The evaluation of WRF/Chem shows an overall good performance for most meteorological and chemical variables on a decadal scale. Temperature at 2-m is overpredicted by WRF (by ∼0.2-0.3 °C) but underpredicted by WRF/Chem (by ∼0.3-0.4 °C), due to higher radiation from WRF. Both WRF and WRF/Chem show large overpredictions for precipitation, indicating limitations in their microphysics or convective parameterizations. WRF/Chem with prognostic chemical concentrations, however, performs much better than WRF with prescribed chemical concentrations for radiation variables, illustrating the benefit of predicting gases and aerosols and representing their feedbacks into meteorology in WRF/Chem. WRF/Chem performs much better than CESM_NCSU for most surface meteorological variables and O3 hourly mixing ratios. In addition, WRF/Chem better captures observed temporal and spatial variations than CESM_NCSU. CESM_NCSU performance for radiation variables is comparable to or better than WRF/Chem performance because of the model tuning in CESM_NCSU that is routinely made in global models.
Dobrinkova, Nina; Jordanov, Georgi; Mandel, Jan
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.
Richardson, Mark I.; Lee, Christopher; Lian, Yuan; Mischna, Michael A.; Newman, Claire E.; Toigo, Anthony
planetWRF is based upon the NCAR Weather Research and Forecasting (WRF) model and has been applied to Mars, Titan and Pluto. planetWRF offers global-scale, two-way interactive nested mesoscale, and microscale LES simulation of planetary atmospheres using a rectangular grid.Recently, a fully-coupled dust and water cycle aerosol scheme has been introduced based on Morrison and Gettelman [Lee et al., this conference]. The scheme treats both dust and water ice as two-moment distributions. Significantly, the scheme treats all processes (nucleation, growth, advection, sedimentation, radiation) using the two-moment distributions, with no lossy conversion between spectral and radius-bin representation.The LES modeing capability has been augmented with the ability to import HiRISE DTMs to allow simulation of small-scale flow over topography including the first order effects of local slope and shadowing. Simulations of Victoria crater (visited by Opportunity) show dramatic variations of surface temperature on scales of a few meters during the morning and distinct changes in the patterns of wind stress as the crater interior is coupled and decoupled from boundary layer convection at different times. The LES has also been augmented to run with dynamically and radiatively interactive dust.planetMPAS is based upon the NCAR Model for Prediction Across Scales (MPAS), an unstructured mesh model that allows for far more uniform resolution of the whole globe, uses a fully compressible nonhydrostatic dynamical core, and an advanced terrain-following coordinate system. The MPAS model been designed to use WRF physics routines. As such, planetMPAS and planetWRF are alternate dynamical cores within the same modeling system. planetMPAS has major advantages over WRF for certain kinds of global simulations: high-precision tracer problems, e.g. Argon transport on Mars; uniform resolution of polar regions, e.g. water ice cap interactions with the martian global water cycle; and convection
Sterk, H.A.M.; Steeneveld, G.J.; Vihma, T.; Anderson, P.S.; Bosveld, F.C.; Holtslag, A.A.M.
In this paper we evaluated the Weather Research and Forecasting (WRF) mesoscale meteorological model for stable conditions at clear skies with low wind speeds. Three contrasting terrains with snow covered surfaces are considered, namely Cabauw (Netherlands, snow over grass), Sodankylä (Finland, snow
Brioude, J.; Arnold, D.; Stohl, A.; Cassiani, M.; Morton, Don; Seibert, P.; Angevine, W. M.; Evan, S.; Dingwell, A.; Fast, Jerome D.; Easter, Richard C.; Pisso, I.; Bukhart, J.; Wotawa, G.
The Lagrangian particle dispersion model FLEXPART was originally designed for cal- culating long-range and mesoscale dispersion of air pollutants from point sources, such as after an accident in a nuclear power plant. In the meantime FLEXPART has evolved into a comprehensive tool for atmospheric transport modeling and analysis at different scales. This multiscale need from the modeler community has encouraged new developments in FLEXPART. In this document, we present a version that works with the Weather Research and Forecasting (WRF) mesoscale meteoro- logical model. Simple procedures on how to run FLEXPART-WRF are presented along with special options and features that differ from its predecessor versions. In addition, test case data, the source code and visualization tools are provided to the reader as supplementary material.
Norris, Jesse; Carvalho, Leila M. V.; Jones, Charles; Cannon, Forest; Bookhagen, Bodo; Palazzi, Elisa; Tahir, Adnan Ahmad
The Weather Research and Forecasting (WRF) model is used to simulate the spatiotemporal distribution of precipitation over central Asia over the year April 2005 through March 2006. Experiments are performed at 6.7 km horizontal grid spacing, with an emphasis on winter and summer precipitation over the Himalaya. The model and the Tropical Rainfall Measuring Mission show a similar inter-seasonal cycle of precipitation, from extratropical cyclones to monsoon precipitation, with agreement also in the diurnal cycle of monsoon precipitation. In winter months, WRF compares better in timeseries of daily precipitation to stations below than above 3-km elevation, likely due to inferior measurement of snow than rain by the stations, highlighting the need for reliable snowfall measurements at high elevations in winter. In summer months, the nocturnal precipitation cycle in the foothills and valleys of the Himalaya is captured by this 6.7-km WRF simulation, while coarser simulations with convective parameterization show near zero nocturnal precipitation. In winter months, higher resolution is less important, serving only to slightly increase precipitation magnitudes due to steeper slopes. However, even in the 6.7-km simulation, afternoon precipitation is overestimated at high elevations, which can be reduced by even higher-resolution (2.2-km) simulations. These results indicate that WRF provides skillful simulations of precipitation relevant for studies of water resources over the complex terrain in the Himalaya.
Gochis, D. J.; Yu, W.; Dugger, A. L.; McCreight, J. L.; Yates, D. N.; Clark, M. P.; Wood, A. W.; Sampson, K. M.; Rasmussen, R.
The translation of weather and climate forcing through complex landscapes to drive terrestrial hydrologic processes is a true multi-scale problem. Model architectures that attempt to capture these processes and feedbacks in a physically realistic way must be able to bridge spatial scales from meters to kilometers. To represent these processes across continental domains modeling systems must fully embrace high performance computing. Also, because there are both scientific and computational trade-offs in modeling many terrestrial hydrologic and land-atmosphere exchange processes, it is often highly advantageous to support multiple physics options in order to test competing hypotheses and apply scale-appropriate parameterizations for different prediction problems. In this talk we provide an update of new developments to the WRF-Hydro system in meeting these needs from both a process representation and high performance computing perspective. A key feature of these developments centers on new multi-scale modeling capabilities recently added to WRF-Hydro. We will discuss prediction and computational performance metrics for several recent large river basin and continental scale applications of the WRF-Hydro system over the coterminous U.S. and over Mexico in modes both coupled and uncoupled to the Weather Research and Forecasting (WRF) model. We will also provide updates on new developments to the WRF-Hydro system in the areas of water management applications and hydrologic data assimilation.
A. J. Litta
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.
Volker, Patrick; Badger, Jake; Hahmann, Andrea N.
The project’s objective is to investigate and develop methods for prediction of mesoscale climate, wake effects and atmospheric feedbacks, for scenarios where large portions of the sea are covered with wind farms. The atmospheric flow is simulated with the WRF mesoscale model, since it has signif...
Papa Rao, G.; Rajasekhar, M.; Pushpa Saroja, R.; Sreeshna, T.; Rajeevan, M.; Ramakrishna, S. S. V. S.
Operational short range prediction of Meso-scale thunderstorms for Sriharikota(13.7°N ,80.18°E) has been performed using two nested domains 27 & 9Km configuration of Weather Research & Forecasting-Advanced Research Weather Model (WRF- ARW V3.4).Thunderstorm is a Mesoscale system with spatial scale of few kilometers to a couple of 100 kilometers and time scale of less than an one hour to several hours, which produces heavy rain, lightning, thunder, surface wind squalls and down-bursts. Numerical study of Thunderstorms at Sriharikota and its neighborhood have been discussed with its antecedent thermodynamic stability indices and Parameters that are usually favorable for the development of convective instability based on WRF ARW model predictions. Instability is a prerequisite for the occurrence of severe weather, the greater the instability, the greater will be the potential of thunderstorm. In the present study, K Index, Total totals Index (TTI), Convective Available Potential Energy (CAPE), Convective Inhibition Energy (CINE), Lifted Index (LI), Precipitable Water (PW), etc. are the instability indices used for the short range prediction of thunderstorms. In this study we have made an attempt to estimate the skill of WRF ARW predictability and diagnosed three thunderstorms that occurred during the late evening to late night of 31st July, 20th September and 2nd October of 2015 over Sriharikota Island which are validated with Local Electric Field Mill (EFM), rainfall observations and Chennai Doppler Weather Radar products. The model predicted thermodynamic indices (CAPE, CINE, K Index, LI, TTI and PW) over Sriharikota which act as good indicators for severe thunderstorm activity.
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.
A J Litta; U C Mohanty; Sumam Mary Idicula
Thunderstorm, resulting from vigorous convective activity, is one of the most spectacular weather phenomena in the atmosphere. A common feature of the weather during the pre-monsoon season over the Indo-Gangetic Plain and northeast India is the outburst of severe local convective storms, commonly known as ‘Nor’westers’(as they move from northwest to southeast). The severe thunderstorms associated with thunder, squall lines, lightning and hail cause extensive losses in agricultural, damage to structure and also loss of life. In this paper, sensitivity experiments have been conducted with the Non-hydrostatic Mesoscale Model (NMM) to test the impact of three microphysical schemes in capturing the severe thunderstorm event occurred over Kolkata on 15 May 2009. The results show that the WRF-NMM model with Ferrier microphysical scheme appears to reproduce the cloud and precipitation processes more realistically than other schemes. Also, we have made an attempt to diagnose four severe thunderstorms that occurred during pre-monsoon seasons of 2006, 2007 and 2008 through the simulated radar reflectivity fields from NMM model with Ferrier microphysics scheme and validated the model results with Kolkata Doppler Weather Radar (DWR) observations. Composite radar reflectivity simulated by WRF-NMM model clearly shows the severe thunderstorm movement as observed by DWR imageries, but failed to capture the intensity as in observations. The results of these analyses demonstrated the capability of high resolution WRF-NMM model in the simulation of severe thunderstorm events and determined that the 3 km model improve upon current abilities when it comes to simulating severe thunderstorms over east Indian region.
Brioude, J.; Arnold, D.; Stohl, A.; Cassiani, M.; Morton, D.; Seibert, P.; Angevine, W.; Evan, S.; Dingwell, A.; Fast, J. D.; Easter, R. C.; Pisso, I.; Burkhart, J.; Wotawa, G.
The Lagrangian particle dispersion model FLEXPART was originally designed for calculating long-range and mesoscale dispersion of air pollutants from point sources, such that occurring after an accident in a nuclear power plant. In the meantime, FLEXPART has evolved into a comprehensive tool for atmospheric transport modeling and analysis at different scales. A need for further multiscale modeling and analysis has encouraged new developments in FLEXPART. In this paper, we present a FLEXPART version that works with the Weather Research and Forecasting (WRF) mesoscale meteorological model. We explain how to run this new model and present special options and features that differ from those of the preceding versions. For instance, a novel turbulence scheme for the convective boundary layer has been included that considers both the skewness of turbulence in the vertical velocity as well as the vertical gradient in the air density. To our knowledge, FLEXPART is the first model for which such a scheme has been developed. On a more technical level, FLEXPART-WRF now offers effective parallelization, and details on computational performance are presented here. FLEXPART-WRF output can either be in binary or Network Common Data Form (NetCDF) format, both of which have efficient data compression. In addition, test case data and the source code are provided to the reader as a Supplement. This material and future developments will be accessible at http://www.flexpart.eu.
Bugaets, Andrey; Gonchukov, Leonid
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
Kuznetsova, Alexandra; Troitskaya, Yuliya; Kandaurov, Alexander; Baydakov, Georgy; Vdovin, Maxim; Papko, Vladislav; Sergeev, Daniil
Simulation of ocean and sea waves is an accepted instrument for the improvement of the weather forecasts. Wave modelling, coupled models modelling is applied to open seas  and is less developed for moderate and small inland water reservoirs and lakes, though being of considerable interest for inland navigation. Our goal is to tune the WAVEWATCH III model to the conditions of the inland reservoir and to carry out the simulations of surface wind waves with coupled WRF (Weather Research and Forecasting) and WAVEWATCH III models. Gorky Reservoir, an artificial lake in the central part of the Volga River formed by a hydroelectric dam, was considered as an example of inland reservoir. Comparing to  where moderate constant winds (u10 is up to 9 m/s) of different directions blowing steadily all over the surface of the reservoir were considered, here we apply atmospheric model WRF to get wind input to WAVEWATCH III. WRF computations were held on the Yellowstone supercomputer for 4 nested domains with minimum scale of 1 km. WAVEWATCH III model was tuned for the conditions of the Gorky Reservoir. Satellite topographic data on altitudes ranged from 56,6° N to 57,5° N and from 42.9° E to 43.5° E with increments 0,00833 ° in both directions was used. 31 frequencies ranged from 0,2 Hz to 4 Hz and 30 directions were considered. The minimal significant wave height was changed to the lower one. The waves in the model were developing from some initial seeding spectral distribution (Gaussian in frequency and space, cosine in direction). The range of the observed significant wave height in the numerical experiment was from less than 1 cm up to 30 cm. The field experiments were carried out in the south part of the Gorky reservoir from the boat [2, 3]. 1-D spectra of the field experiment were compared with those obtained in the numerical experiments with different parameterizations of flux provided in WAVEWATCH III both with constant wind input and WRF wind input. For all the
Endo, S.; Liu, Y.; Lin, W.; Liu, G.
Cloud-resolving Models (CRM) and large-eddy simulations (LES) have been demonstrated to be an effective tool in evaluation and development of parameterizations of various fast processes in climate models, including microphysics and turbulence. The DOE FAst-physics System TEstbed and Research (FASTER) project proposes to utilize the Weather Research and Forecasting (WRF) model as a CRM/LES in model evaluation against ARM observations. Here we reconfigure the WRF-LES that uses doubly periodic lateral boundaries to implement additional functions for this purpose, including prescription of time-varying large-scale and surface forcings. This framework allows us to perform (1) cloud resolving simulations using large-scale forcings, (2) conventional CRM simulations with planetary boundary layer scheme, as well as (3) one-dimensional single column simulations with full parameterizations, under the same forcings. We will report results of using the newly configured WRF-CRM to simulate the well-tested continental cumulus case in GCSS model inter-comparison studies described in Brown et al (2002), and the cases collected during the ARM March 2000 Cloud IOP at the Southern Great Plains (SGP) site.
Full Text Available The Lagrangian particle dispersion model FLEXPART was originally designed for calculating long-range and mesoscale dispersion of air pollutants from point sources, such as after an accident in a nuclear power plant. In the meantime FLEXPART has evolved into a comprehensive tool for atmospheric transport modeling and analysis at different scales. This multiscale need has encouraged new developments in FLEXPART. In this document, we present a FLEXPART version that works with the Weather Research and Forecasting (WRF mesoscale meteorological model. We explain how to run and present special options and features that differ from its predecessor versions. For instance, a novel turbulence scheme for the convective boundary layer has been included that considers both the skewness of turbulence in the vertical velocity as well as the vertical gradient in the air density. To our knowledge, FLEXPART is the first model for which such a scheme has been developed. On a more technical level, FLEXPART-WRF now offers effective parallelization and details on computational performance are presented here. FLEXPART-WRF output can either be in binary or Network Common Data Form (NetCDF format with efficient data compression. In addition, test case data and the source code are provided to the reader as Supplement. This material and future developments will be accessible at http://www.flexpart.eu.
Brioude, J.; Arnold, D.; Stohl, A.; Cassiani, M.; Morton, D.; Seibert, P.; Angevine, W.; Evan, S.; Dingwell, A.; Fast, J. D.; Easter, R. C.; Pisso, I.; Burkhart, J.; Wotawa, G.
The Lagrangian particle dispersion model FLEXPART was originally designed for calculating long-range and mesoscale dispersion of air pollutants from point sources, such as after an accident in a nuclear power plant. In the meantime FLEXPART has evolved into a comprehensive tool for atmospheric transport modeling and analysis at different scales. This multiscale need has encouraged new developments in FLEXPART. In this document, we present a FLEXPART version that works with the Weather Research and Forecasting (WRF) mesoscale meteorological model. We explain how to run and present special options and features that differ from its predecessor versions. For instance, a novel turbulence scheme for the convective boundary layer has been included that considers both the skewness of turbulence in the vertical velocity as well as the vertical gradient in the air density. To our knowledge, FLEXPART is the first model for which such a scheme has been developed. On a more technical level, FLEXPART-WRF now offers effective parallelization and details on computational performance are presented here. FLEXPART-WRF output can either be in binary or Network Common Data Form (NetCDF) format with efficient data compression. In addition, test case data and the source code are provided to the reader as Supplement. This material and future developments will be accessible at http://www.flexpart.eu.
Lee, Junhong; Hong, Jinkyu
Canopy height is closely related to biomass and aerodynamic properties, which regulate turbulent transfer of energy and mass at the soil-vegetation-atmosphere continuum. However, this key information has been prescribed as a constant value in a fixed plant functional type in atmospheric models. This paper is the first to report impacts of using realistic forest canopy height, retrieved from spaceborne lidar, on regional climate simulation by using the canopy height data in the Weather Research and Forecasting (WRF) model's land surface model. Numerical simulations were conducted over the Amazon Basin during summer season. Over this region, the lidar-retrieved canopy heights were higher than the default values used in the WRF, which are dependent only on plant functional type. By modifying roughness length and zero-plane displacement height, the change of canopy height resulted in changes in surface energy balance by regulating aerodynamic conductances and vertical temperature gradient, thus modifying the lifting condensation level and equivalent potential temperature in the atmospheric boundary layer. Our analysis also showed that the WRF model better reproduced the observed precipitation when lidar-retrieved canopy height was used over the Amazon Basin.
Lee, Junhong; Hong, Jinkyu
Canopy height is closely related to biomass and aerodynamic properties, which regulate turbulent transfer of energy and mass at the soil-vegetation-atmosphere continuum. However, this key information has been prescribed as a constant value in a fixed plant functional type in atmospheric models. This presentation reports impacts of using realistic forest canopy height, retrieved from spaceborne LiDAR, on regional climate simulation in the Weather Research and Forecasting (WRF) model's land surface model. Numerical simulations were conducted over the Amazon Basin and East Asia during summer season. Over these regions, the LiDAR-retrieved canopy heights were higher than the default values used in the WRF,which are dependent only on plant functional type. By modifying roughness length and zero-plane displacement height, the change of canopy height resulted in changes in surface energy balance by regulating aerodynamic conductances and vertical temperature gradient, thus modifying the lifting condensation level and equivalent potential temperature in the atmospheric boundary layer. Our analysis also showed that the WRF model better reproduced the observed precipitation when LiDAR-retrieved canopy height was used over the Amazon Basin.
Listowski, Constantino; Lachlan-Cope, Tom
The first intercomparisons of cloud microphysics schemes implemented in the Weather Research and Forecasting (WRF) mesoscale atmospheric model (version 3.5.1) are performed on the Antarctic Peninsula using the polar version of WRF (Polar WRF) at 5 km resolution, along with comparisons to the British Antarctic Survey's aircraft measurements (presented in part 1 of this work; Lachlan-Cope et al., 2016). This study follows previous works suggesting the misrepresentation of the cloud thermodynamic phase in order to explain large radiative biases derived at the surface in Polar WRF continent-wide (at 15 km or coarser horizontal resolution) and in the Polar WRF-based operational forecast model Antarctic Mesoscale Prediction System (AMPS) over the Larsen C Ice Shelf at 5 km horizontal resolution. Five cloud microphysics schemes are investigated: the WRF single-moment five-class scheme (WSM5), the WRF double-moment six-class scheme (WDM6), the Morrison double-moment scheme, the Thompson scheme, and the Milbrandt-Yau double-moment seven-class scheme. WSM5 (used in AMPS) and WDM6 (an upgrade version of WSM5) lead to the largest biases in observed supercooled liquid phase and surface radiative biases. The schemes simulating clouds in closest agreement to the observations are the Morrison, Thompson, and Milbrandt schemes for their better average prediction of occurrences of clouds and cloud phase. Interestingly, those three schemes are also the ones allowing for significant reduction of the longwave surface radiative bias over the Larsen C Ice Shelf (eastern side of the peninsula). This is important for surface energy budget consideration with Polar WRF since the cloud radiative effect is more pronounced in the infrared over icy surfaces. Overall, the Morrison scheme compares better to the cloud observation and radiation measurements. The fact that WSM5 and WDM6 are single-moment parameterizations for the ice crystals is responsible for their lesser ability to model the
Case, Jonathan L.; Blankenship, Clay B.; Zavodsky, Bradley T.; Srikishen, Jayanthi; Berndt, Emily B.
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.
Q. Li; J. Chen
It is found from statistical analysis that urban effects have great impact on climate change in South China, especially in recent year with the fast economic development in China. Minimum temperature and precipitation tend to be greater in urban area than in rural region. This study tends to prove this urban effect in South China, especially the Pearl River Delta region by using Weather Research and Forecasting model (WRF). In this study, we use two land use data of Pearl River Delta in 1980 ...
The Carbonaceous Aerosols and Radiative Effects Study (CARES), a field campaign held in central California in June 2010, provides a unique opportunity to assess the aerosol optics modeling component of the two-way coupled Weather Research and Forecasting (WRF) – Community Multisc...
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, 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
Banks, R F; Baldasano, J M
Here we analyze the impact of four planetary boundary-layer (PBL) parametrization schemes from the Weather Research and Forecasting (WRF) numerical weather prediction model on simulations of meteorological variables and predicted pollutant concentrations from an air quality forecast system (AQFS). The current setup of the Spanish operational AQFS, CALIOPE, is composed of the WRF-ARW V3.5.1 meteorological model tied to the Yonsei University (YSU) PBL scheme, HERMES v2 emissions model, CMAQ V5.0.2 chemical transport model, and dust outputs from BSC-DREAM8bv2. We test the performance of the YSU scheme against the Assymetric Convective Model Version 2 (ACM2), Mellor-Yamada-Janjic (MYJ), and Bougeault-Lacarrère (BouLac) schemes. The one-day diagnostic case study is selected to represent the most frequent synoptic condition in the northeast Iberian Peninsula during spring 2015; regional recirculations. It is shown that the ACM2 PBL scheme performs well with daytime PBL height, as validated against estimates retrieved using a micro-pulse lidar system (mean bias=-0.11km). In turn, the BouLac scheme showed WRF-simulated air and dew point temperature closer to METAR surface meteorological observations. Results are more ambiguous when simulated pollutant concentrations from CMAQ are validated against network urban, suburban, and rural background stations. The ACM2 scheme showed the lowest mean bias (-0.96μgm(-3)) with respect to surface ozone at urban stations, while the YSU scheme performed best with simulated nitrogen dioxide (-6.48μgm(-3)). The poorest results were with simulated particulate matter, with similar results found with all schemes tested. Copyright © 2016 The Authors. Published by Elsevier B.V. All rights reserved.
Cofino, A. S.; Fernández Quiruelas, V.; Blanco Real, J. C.; García Díez, M.; Fernández, J.
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 WRF4G project objective 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 used by many groups, in the climate research community, to carry on downscaling simulations. Therefore this 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 simulations and the data. Thus,another objective of theWRF4G project consists on the development of a generic adaptation of WRF to DCIs. It should simplify the access to the DCIs for the researchers, and also to free them from the technical and computational aspects of the use of theses DCI. Finally, in order to demonstrate the ability of WRF4G solving actual scientific challenges with interest and relevance on the climate science (implying a high computational cost) we will shown results from different kind of downscaling experiments, like ERA-Interim re-analysis, CMIP5 models
A recently published meteorology and air quality modeling study has several serious deficiencies deserving comment. The study uses the weather research and forecasting/chemistry (WRF/Chem) model to compare and evaluate boundary layer and land surface modeling options. The most se...
Zhang, Zhenyu; Arnault, Joel; Wagner, Sven; Kunstmann, Harald
The upper Heihe river basin (10,020 km2) is situated in the alpine region of northwestern China, where gauge coverage is poor. Water-related activity is essential for the human economy in this region, which requires detailed knowledge of the available water resources. However, the lack of hydro-meteorological data makes any water balance investigation challenging. The use of regional atmospheric models can compensate this lack of data. The aim of this study is to investigate which improvement can be gained by enhancing the hydrological parameterization in atmospheric models. For this purpose, we employ the Weather Research and Forecasting model (WRF) and its coupled atmospheric-hydrological version (WRF-Hydro). In comparison to WRF, WRF-Hydro integrates horizontal terrestrial water transport at the land surface and subsurface. Atmospheric processes are downscaled from ECMWF operational analysis to 4 km resolution, and lateral terrestrial water flows are resolved on a sub-grid at 400 m. The study period is 2008-2009, during which observed discharge is available at three gauge stations. The joint terrestrial-atmospheric water budget is investigated in both WRF and WRF-Hydro. In WRF-Hydro, overland flow and re-infiltration increase the soil water storage, consequently increasing evapotranspiration and decreasing river runoff. This change in evapotranspiration influences moisture convergence in the atmosphere, and slightly changes precipitation patterns. Comparing model results with in-situ and gridded datasets (ITP-CAS forcing data, FLUXNET-MTE), WRF-Hydro shows improvement on precipitation and evapotranspiration simulation. The ability of WRF-Hydro to reproduce observed streamflow is also demonstrated.
Yan, Huiping; Qian, Yun; Lin, Guang; Leung, Lai-Yung R.; Yang, Ben; Fu, Q.
Convective parameterizations used in weather and climate models all display sensitivity to model resolution and variable skill in different climatic regimes. Although parameters in convective schemes can be calibrated using observations to reduce model errors, it is not clear if the optimal parameters calibrated based on regional data can robustly improve model skill across different model resolutions and climatic regimes. In this study, this issue is investigated using a regional modeling framework based on the Weather Research and Forecasting (WRF) model. To quantify the response and sensitivity of model performance to model parameters, we identified five key input parameters and specified their ranges in the Kain-Fritsch (KF) convection scheme in WRF and calibrated them across different spatial resolutions, climatic regimes, and radiation schemes using observed precipitation data. Results show that the optimal values for the five input parameters in the KF scheme are close and model sensitivity and error exhibit similar dependence on the input parameters for all experiments conducted in this study despite differences in the precipitation climatology. We found that the model overall performances in simulating precipitation are more sensitive to the coefficients of downdraft (Pd) and entrainment (Pe) mass flux and starting height of downdraft (Ph). However, we found that rainfall biases, which are probably more related to structural errors, still exist over some regions in the simulation even with the optimal parameters, suggesting further studies are needed to identify the sources of uncertainties and reduce the model biases or structural errors associated with missed or misrepresented physical processes and/or potential problems with the modeling framework.
Nedbor-Gross, R.; Henderson, B. H.; Pachon, J. E.; Davis, J. R.; Baublitz, C. B.; Rincón, A.
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
Mallard, M.; Bullock, R.; Nolte, C. G.; Alapaty, K.; Otte, T.; Gula, J.
Lakes can play a significant role in regional climate by modifying air masses through fluxes of heat and moisture and by modulating inland extremes in temperature. Representing these effects becomes more important as regional climate modeling efforts employ finer grid spacing in order to simulate smaller scales. The Weather Research and Forecasting (WRF) model does not simulate lakes explicitly. Instead, lake points are treated as ocean points, with sea surface temperatures (SSTs) interpolated from the nearest neighboring ocean point in the driving coarse-scale fields. This can result in substantial errors for inland lakes such as the Great Lakes. Although prescribed lake surface temperatures (LSTs) can be used for retrospective modeling applications, this may not be desirable for applications involving downscaling future climate scenarios from a global climate model (GCM). In such downscaling simulations, lakes that impact the regional climate in the area of interest may not be resolved by the coarser global input fields. Explicitly simulating the LST would allow WRF to better represent interannual variability in regions significantly affected by lakes, and the influence of such variability on temperature and precipitation patterns. Therefore, coupling a lake model to WRF may lead to more reliable assessments of the impacts of extreme events on human health and the environment. We employ a version of WRF coupled to the Freshwater Lake model, FLake (Gula and Peltier 2012). FLake is a 1D bulk lake model which provides updated LSTs and ice coverage throughout the integration. This two-layer model uses a temperature-depth profile which includes a homogeneous mixed layer at the surface and a thermocline below. The shape of the thermocline is assumed, based on past theoretical and observational studies. Therefore, additional variables required for FLake to run are minimal, and it does not require tuning for individual lakes. These characteristics are advantageous for a
Fita, Lluís; Hourdin, Frédéric; Fairhead, Laurent; Drobinski, Phlippe
Nowadays advances in climatological sciences, pose different challenges for the current global climate models (GCM). One of them is related to the resolution. In some exercises, GCMs are started to be used to that resolutions to which they were not designed for, or in advance of future uses, they have to be tested in order to know their limitations. With the mid term perspective in mind of future uses of the Laboratorie de Météorologie Dynamique Zoom (LMDZ) model, a framework has been designed in order to use the physical parameterizations of the LMDZ model coupled to the dynamical core of Weather Research and Forecasting (WRF) model. This framework will allow the analysis of different aspects such as: resolution thresholds of the LMDZ physics set, skill of LMDZ physics in comparison with cloud resolving simulations, impact of the primitive equations fully compressible dynamics from WRF in global runs among others. The design and implementation of the framework keeps almost all the original capabilities of both models. As a first step, results of an ensemble of 1-year low-resolution global aqua-planet runs performed with the original models using different physical configurations, and the new framework will be presented. These initial results show the correct performance of the new framework, and the sensitivity of the global circulation due to different dynamical atmospheric cores and physical parameterizations.
Case, Jonathan; Blottman, Pete; Hoeth, Brian; Oram, Timothy
The Weather Research and Forecasting (WRF) model is the next generation community mesoscale model designed to enhance collaboration between the research and operational sectors. The NM'S as a whole has begun a transition toward WRF as the mesoscale model of choice to use as a tool in making local forecasts. Currently, both the National Weather Service in Melbourne, FL (NWS MLB) and the Spaceflight Meteorology Group (SMG) are running the Advanced Regional Prediction System (AIRPS) Data Analysis System (ADAS) every 15 minutes over the Florida peninsula to produce high-resolution diagnostics supporting their daily operations. In addition, the NWS MLB and SMG have used ADAS to provide initial conditions for short-range forecasts from the ARPS numerical weather prediction (NWP) model. Both NM'S MLB and SMG have derived great benefit from the maturity of ADAS, and would like to use ADAS for providing initial conditions to WRF. In order to assist in this WRF transition effort, the Applied Meteorology Unit (AMU) was tasked to configure and implement an operational version of WRF that uses output from ADAS for the model initial conditions. Both agencies asked the AMU to develop a framework that allows the ADAS initial conditions to be incorporated into the WRF Environmental Modeling System (EMS) software. Developed by the NM'S Science Operations Officer (S00) Science and Training Resource Center (STRC), the EMS is a complete, full physics, NWP package that incorporates dynamical cores from both the National Center for Atmospheric Research's Advanced Research WRF (ARW) and the National Centers for Environmental Prediction's Non-Hydrostatic Mesoscale Model (NMM) into a single end-to-end forecasting system. The EMS performs nearly all pre- and postprocessing and can be run automatically to obtain external grid data for WRF boundary conditions, run the model, and convert the data into a format that can be readily viewed within the Advanced Weather Interactive Processing System
Yang, Jiachuan; Wang, Zhi-hua; Chen, Fei; Miao, Shiguang; Tewari, Mukul; Georgescu, Matei
To meet the demand of the ever-increasing urbanized global population, substantial conversion of natural landscapes to urban terrains is expected in the next few decades. The landscape modification will emerge as the source of many adverse effects that challenge the environmental sustainability of cities under changing climatic patterns. To address these adverse effects and to develop corresponding adaptation/mitigation strategies, physically-based single layer urban canopy model (SLUCM) has been developed and implemented into the Weather Research and Forecasting (WRF) platform. However, due to the lack of realistic representation of urban hydrological processes, simulation of urban climatology by current coupled WRF/SLUCM is inevitably inadequate. Aiming at improving the accuracy of simulations, in this study we implement physically-based parameterization of urban hydrological processes into the model, including (1) anthropogenic latent heat, (2) urban irrigation, (3) evaporation over water-holding engineered pavements, (4) urban oasis effect, and (5) green roof. In addition, we use an advanced Monte Carlo approach to quantify the sensitivity of urban hydrological modeling to parameter uncertainties. Evaluated against field observations at four major metropolitan areas, results show that the enhanced model is significantly improved in accurately predicting turbulent fluxes arising from built surfaces, especially the latent heat flux. Case studies show that green roof is capable of reducing urban surface temperature and sensible heat flux effectively, and modifying local and regional hydroclimate. Meanwhile, it is efficient in decreasing energy loading of buildings, not only cooling demand in summers but also heating demand in winters, through the combined evaporative cooling and insulation effect. Effectiveness of green roof is found to be limited by availability of water resources and highly sensitive to surface roughness heights. The enhanced WRF/SLUCM model
GAO Wenhua; ZHAO Fengsheng; HU Zhijin; FENG Xua
The Chinese Academy of Meteorological Sciences (CAMS) two-moment bulk microphysics scheme was adopted in this study to investigate the representation of cloud and precipitation processes under different environmental conditions.The scheme predicts the mixing ratio of water vapor as well as the mixing ratios and nnmber concentrations of cloud droplets,rain,ice,snow,and graupel.A new parameterization approach to simulate heterogeneous droplet activation was developed in this scheme.Furthermore,the improved CAMS scheme was coupled with the Weather Research and Forecasting model (WRF v3.1),which made it possible to simulate the microphysics of clouds and precipitation as well as the cloud-aerosol interactions in selected atmospheric condition.The rain event occurring on 27 28 December 2008 in eastern China was simulated using the CAMS scheme and three sophisticated microphysics schemes in the WRF model.Results showed that the simulated 36-h accumulated precipitations were generally agreed with observation data,and the CAMS scheme performed well in the southern area of the nested donain.The radar reflectivity,the averaged precipitation intensity,and the hydrometeor mixing ratios simulated by the CAMS scheme were generally consistent with those from other microphysics schemes.The hydrometeor number concentrations simulated by the CAMS scheme were also close to the experiential values in stratus clouds.The model results suggest that the CAMS scheme performs reasonably well in describing the microphysics of clouds and precipitation in the mesoscale WRF model.
Case, Jonathan L.; Jedlove, Gary J.; Santos, Pablo; Medlin, Jeffrey M.; Rozumalski, Robert A.
The NASA Short-term Prediction Research and Transition (SPoRT) Center has developed a Moderate Resolution Imaging Spectroradiometer (MODIS) sea surface temperature (SST) composite at 2-km resolution that has been implemented in version 3 of the National Weather Service (NWS) Weather Research and Forecasting (WRF) Environmental Modeling System (EMS). The WRF EMS is a complete, full physics numerical weather prediction package that incorporates dynamical cores from both the Advanced Research WRF (ARW) and the Non-hydrostatic Mesoscale Model (NMM). The installation, configuration, and execution of either the ARW or NMM models is greatly simplified by the WRF EMS to encourage its use by NWS Weather Forecast Offices (WFOs) and the university community. The WRF EMS is easy to run on most Linux workstations and clusters without the need for compilers. Version 3 of the WRF EMS contains the most recent public release of the WRF-NMM and ARW modeling system (version 3 of the ARW is described in Skamarock et al. 2008), the WRF Pre-processing System (WPS) utilities, and the WRF Post-Processing program. The system is developed and maintained by the NWS National Science Operations Officer Science and Training Resource Coordinator. To initialize the WRF EMS with high-resolution MODIS SSTs, SPoRT developed the composite product consisting of MODIS SSTs over oceans and large lakes with the NCEP Real-Time Global (RTG) filling data over land points. Filling the land points is required due to minor inconsistencies between the WRF land-sea mask and that used to generate the MODIS SST composites. This methodology ensures a continuous field that adequately initializes all appropriate arrays in WRF. MODIS composites covering the Gulf of Mexico, western Atlantic Ocean and the Caribbean are generated daily at 0400, 0700, 1600, and 1900 UTC corresponding to overpass times of the NASA Aqua and Terra polar orbiting satellites. The MODIS SST product is output in gridded binary-1 (GRIB-1) data
Unal, E.; Tan, E.; Mentes, S. S.; Caglar, F.; Turkmen, M.; Unal, Y. S.; Onol, B.; Ozdemir, E. T.
Although discontinuous behavior of wind field makes energy production more difficult, wind energy is the fastest growing renewable energy sector in Turkey which is the 6th largest electricity market in Europe. Short-term prediction systems, which capture the dynamical and statistical nature of the wind field in spatial and time scales, need to be advanced in order to increase the wind power prediction accuracy by using appropriate numerical weather forecast models. Therefore, in this study, performances of the next generation mesoscale Numerical Weather Forecasting model, WRF, and The Fifth-Generation NCAR/Penn State Mesoscale Model, MM5, have been compared for the Western Part of Turkey. MM5 has been widely used by Turkish State Meteorological Service from which MM5 results were also obtained. Two wind farms of the West Turkey have been analyzed for the model comparisons by using two different model domain structures. Each model domain has been constructed by 3 nested domains downscaling from 9km to 1km resolution by the ratio of 3. Since WRF and MM5 models have no exactly common boundary layer, cumulus, and microphysics schemes, the similar physics schemes have been chosen for these two models in order to have reasonable comparisons. The preliminary results show us that, depending on the location of the wind farms, MM5 wind speed RMSE values are 1 to 2 m/s greater than that of WRF values. Since 1 to 2 m/s errors can be amplified when wind speed is converted to wind power; it is decided that the WRF model results are going to be used for the rest of the project.
Full Text Available The prediction of fog onset remains difficult despite the progress in numerical weather prediction. It is a complex process and requires adequate representation of the local perturbations in weather prediction models. It mainly depends upon microphysical and mesoscale processes that act within the boundary layer. This study utilizes a multirule based diagnostic (MRD approach using postprocessing of the model simulations for fog predictions. The empiricism involved in this approach is mainly to bridge the gap between mesoscale and microscale variables, which are related to mechanism of the fog formation. Fog occurrence is a common phenomenon during winter season over Delhi, India, with the passage of the western disturbances across northwestern part of the country accompanied with significant amount of moisture. This study implements the above cited approach for the prediction of occurrences of fog and its onset time over Delhi. For this purpose, a high resolution weather research and forecasting (WRF model is used for fog simulations. The study involves depiction of model validation and postprocessing of the model simulations for MRD approach and its subsequent application to fog predictions. Through this approach model identified foggy and nonfoggy days successfully 94% of the time. Further, the onset of fog events is well captured within an accuracy of 30–90 minutes. This study demonstrates that the multirule based postprocessing approach is a useful and highly promising tool in improving the fog predictions.
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
A. Montornès; B. Codina; J. W. Zack
Although ozone is an atmospheric gas with high spatial and temporal variability, mesoscale numerical weather prediction (NWP) models simplify the specification of ozone concentrations used in their shortwave schemes by using a few ozone profiles. In this paper, a two-part study is presented: (i) an assessment of the quality of the ozone profiles provided for use with the shortwave schemes in the Advanced Research version of the Weather Research and Forecasting (WRF-AR...
Full Text Available For wind resource assessment projects, it is common practice to use a power-law relationship (U(z ~ zα and a fixed shear exponent (α = 1=7 to extrapolate the observed wind speed from a low measurement level to high turbine hub-heights. However, recent studies using tall-tower observations have found that the annual average shear exponents at several locations over the United States Great Plains (USGP are significantly higher than 1=7. These findings highlight the critical need for detailed spatio-temporal characterizations of wind shear climatology over the USGP, where numerous large wind farms will be constructed in the foreseeable future. In this paper, a new generation numerical weather prediction model—the Weather Research and Forecasting (WRF model, a fast and relatively inexpensive alternative to time-consuming and costly tall-tower projects, is utilized to determine whether it can reliably estimate the shear exponent and the magnitude of the directional shear at any arbitrary location over the USGP. Our results indicate that the WRF model qualitatively captures several low-level wind shear characteristics. However, there is definitely room for physics parameterization improvements for the WRF model to reliably represent the lower part of the atmospheric boundary layer.
Muller, Omar; Lovino, Miguel; Berbery, E. Hugo
Weather forecasting and monitoring systems based on regional models are becoming increasingly relevant for decision support in agriculture and water management. This work evaluates the predictive and monitoring capabilities of a system based on WRF model simulations at 15 km grid spacing over a domain that encompasses La Plata Basin (LPB) in southern South America, where agriculture and water resources are essential. The model's skill up to a lead-time of 7 days is evaluated with daily precipitation and 2m temperature in-situ observations. Results show high prediction performance with 7 days lead-time throughout the domain and particularly over LPB, where about 70% of rain and no-rain days are correctly predicted. The scores tend to be better over humid climates than over arid-to-semiarid climates. Compared to the arid-semiarid climate, the humid climate has a higher probability of detection and less false alarms. The ranges of the skill scores are similar to those found over the United States, suggesting that proper choice of parameterizations lead to no loss of performance of the model. Daily mean, minimum and maximum forecast temperatures are highly correlated with observations up to 7 day lead time. The best performance is for daily mean temperature, followed by minimum temperature and a slightly weaker performance for maximum temperature over arid regions. The usefulness of WRF products for hydroclimate monitoring was tested for an unprecedented drought in southern Brazil and for a slightly above normal precipitation season in northeastern Argentina. In both cases the model products reproduce the observed precipitation conditions with consistent impacts on soil moisture, evapotranspiration and runoff. This evaluation validates the model's usefulness to fore-cast weather up to one week and to monitor climate conditions in real time. The scores suggest that the forecast lead-time can be extended into week two, while bias correction methods can reduce part of the
Bhati, Shweta; Mohan, Manju
Urban heat island effect in Delhi has been assessed using Weather Research and Forecasting (WRF v3.5) coupled with urban canopy model (UCM) focusing on air temperature and surface skin temperature. The estimated heat island intensities for different land use/land cover (LULC) have been compared with those derived from in situ and satellite observations. The model performs reasonably well for urban heat island intensity (UHI) estimation and is able to reproduce trend of UHI for urban areas. There is a significant improvement in model performance with inclusion of UCM which results in reduction in root mean-squared errors (RMSE) for temperatures from 1.63 °C (2.89 °C) to 1.13 °C (2.75 °C) for urban (non-urban) areas. Modification of LULC also improves performance for non-urban areas. High UHI zones and top 3 hotspots are captured well by the model. The relevance of selecting a reference point at the periphery of the city away from populated and built-up areas for UHI estimation is examined in the context of rapidly growing cities where rural areas are transforming fast into built-up areas, and reference site may not be appropriate for future years. UHI estimated by WRF model (with and without UCM) with respect to reference rural site compares well with the UHI based on observed in situ data. An alternative methodology is explored using a green area with minimum temperature within the city as a reference site. This alternative methodology works well with observed UHIs and WRF-UCM-simulated UHIs but has poor performance for WRF-simulated UHIs. It is concluded that WRF model can be applied for UHI estimation with classical methodology based on rural reference site. In general, many times WRF model performs satisfactorily, though WRF-UCM always shows a better performance. Hence, inclusion of appropriate representation of urban canopies and land use-land cover is important for improving predictive capabilities of the mesoscale models.
Bacmeister, Julio T.
Awareness of weather and concern about weather in the proximate future certainly must have accompanied the emergence of human self-consciousness. Although weather is a basic idea in human existence, it is difficult to define precisely.
Rodrigues, M. A.; Rocha, A.; Monteiro, A.; Quénol, H.; de Freitas, J. R.
In viticulture where the quality of the wine, the selection of the grapevines or even the characteristics of the farming soil, also depending from local soil features like topography, proximity of a river or water body, will act locally on the weather. Frosts are of significant concern to growers of many cultures crops such as winegrapes. Because of their high latitude and some altitude, the vineyards of the Demarcated Douro Region (DDR) are subjected to the frost, which cause serious damages. But the hazards of vineyard don't confine to the incidents of the fortuitous and meteorological character. The illnesses and plagues affect frequently the vineyards of Demarcated Douro Region due, namely to the weather, to the high power of the regional stocks, to the dense vegetation badly drained and favourable to the setting of numberless fungi, viruses and/or poisonous insects. In the case of DDR it is worth noticing the meteorological conditions due to the weather characteristics. Although there are several illnesses and plagues the most important enemies for the vine in the DDR are the mildew, oidium, grey rottenness, grape moth,. . . , if the climatic conditions favour their appearance and development. For this study, we selected some months for different periods, at the 16 weather stations of the Region of Douro. We use the Weather Research and Forecast Model (WRF) to study and possibly predict the occurrence of risk and plagues (mildew) episodes. The model is first validated with the meteorological data obtained at the weather stations. The knowledge of frost and plagues occurrence allows one to decrease its risks not only by selecting the cultural species and varieties but also the places of growth and the planting and sowing dates.
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)
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.
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
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.
Falk, M.; Pyles, R. D.; Marras, S.; Spano, D.; Snyder, R. L.; Paw U, K.
The number of urban metabolism studies has increased in recent years, due to the important impact that energy, water and carbon exchange over urban areas have on climate change. Urban modeling is therefore crucial in the future design and management of cities. This study presents the ACASA model coupled to the Weather Research and Forecasting (WRF-ARW) mesoscale model to simulate urban fluxes at a horizontal resolution of 200 meters for urban areas of roughly 10 by 10 km. As part of the European Project “BRIDGE”, these regional simulations were used in combination with remotely sensed data to provide constraints on the land surface types and the exchange of carbon and energy fluxes from urban centers.Surface-atmosphere exchanges of mass and energy were simulated using the Advanced Canopy Atmosphere Soil Algorithm (ACASA). ACASA is a multi-layer high-order closure model, recently modified to work over natural, agricultural as well as urban environments. In particular, improvements were made to account for the anthropogenic contribution to heat and carbon production. In order to more accurately simulate the mass and energy exchanges across larger urban regions, ACASA was coupled with a mesoscale weather model (WRF). Here we present ACASA-WRF simulations of mass and energy fluxes over over two different urban regions: a high latitude city, Helsinki (Finland) and an historic European city, Florence (Italy). Helsinki is characterized by recent, rapid urbanization that requires a substantial amount of energy for heating, while Florence is representative of cities in lower latitudes, with substantial cultural heritage, a huge tourist flow, and an architectural footprint that remains comparatively constant in time. The in-situ ACASA model was tested over the urban environment at local point scale with very promising results when validated against urban flux measurements. This study shows the application of this methodology at a regional scale with high spatial
Prince, Alyssa; Trout, Joseph; di Mercurio, Alexis
The Weather Research and Forecasting (WRF) Model is a nested-grid, mesoscale numerical weather prediction system maintained by the Developmental Testbed Center. The model simulates the atmosphere by integrating partial differential equations, which use the conservation of horizontal momentum, conservation of thermal energy, and conservation of mass along with the ideal gas law. This research investigated the possible use of WRF in investigating the effects of weather on wing tip wake turbulence. This poster shows the results of an investigation into the accuracy of WRF using different grid resolutions. Several atmospheric conditions were modeled using different grid resolutions. In general, the higher the grid resolution, the better the simulation, but the longer the model run time. This research was supported by Dr. Manuel A. Rios, Ph.D. (FAA) and the grant ``A Pilot Project to Investigate Wake Vortex Patterns and Weather Patterns at the Atlantic City Airport by the Richard Stockton College of NJ and the FAA'' (13-G-006). Dr. Manuel A. Rios, Ph.D. (FAA), and the grant ``A Pilot Project to Investigate Wake Vortex Patterns and Weather Patterns at the Atlantic City Airport by the Richard Stockton College of NJ and the FAA''
Montornes, Alex; Codina, Bernat; Zack, John W.; Sola, Yolanda
Solar eclipses are predictable astronomical events that abruptly reduce the incoming solar radiation into the Earth's atmosphere, which frequently results in non-negligible changes in meteorological fields. The meteorological impacts of these events have been analyzed in many studies since the late 1960s. The recent growth in the solar energy industry has greatly increased the interest in providing more detail in the modeling of solar radiation variations in numerical weather prediction (NWP) models for the use in solar resource assessment and forecasting applications. The significant impact of the recent partial and total solar eclipses that occurred in the USA (23 October 2014) and Europe (20 March 2015) on solar power generation have provided additional motivation and interest for including these astronomical events in the current solar parameterizations.Although some studies added solar eclipse episodes within NWP codes in the 1990s and 2000s, they used eclipse parameterizations designed for a particular case study. In contrast to these earlier implementations, this paper documents a new package for the Weather Research and Forecasting-Advanced Research WRF (WRF-ARW) model that can simulate any partial, total or hybrid solar eclipse for the period 1950 to 2050 and is also extensible to a longer period. The algorithm analytically computes the trajectory of the Moon's shadow and the degree of obscuration of the solar disk at each grid point of the domain based on Bessel's method and the Five Millennium Catalog of Solar Eclipses provided by NASA, with a negligible computational time. Then, the incoming radiation is modified accordingly at each grid point of the domain.This contribution is divided in three parts. First, the implementation of Bessel's method is validated for solar eclipses in the period 1950-2050, by comparing the shadow trajectory with values provided by NASA. Latitude and longitude are determined with a bias lower than 5 x 10-3 degrees (i
Dodla, Venkata B.
Tropical cyclone prediction, in terms of intensification and movement, is important for disaster management and mitigation. Hitherto, research studies were focused on this issue that lead to improvement in numerical models, initial data with data assimilation, physical parameterizations and application of ensemble prediction. Weather Research and Forecasting (WRF) model is the state-of-art model for cyclone prediction. In the present study, prediction of tropical cyclone (Phailin, 2013) that formed in the North Indian Ocean (NIO) with and without data assimilation using WRF model has been made to assess impacts of data assimilation. WRF model was designed to have nested two domains of 15 and 5 km resolutions. In the present study, numerical experiments are made without and with the assimilation of scatterometer winds, and radiances from ATOVS and ATMS. The model performance was assessed in respect to the movement and intensification of cyclone. ATOVS data assimilation experiment had produced the best prediction with least errors less than 100 km up to 60 hours and producing pre-deepening and deepening periods accurately. The Control and SCAT wind assimilation experiments have shown good track but the errors were 150-200 km and gradual deepening from the beginning itself instead of sudden deepening.
gochis, David; rasmussen, Roy; Yu, Wei; Ikeda, Kyoko
Modeling of extreme weather events often require very finely resolved treatment of atmospheric circulation structures in order to produce and localize large magnitudes of moisture fluxes that result in extreme precipitation. This is particularly true for cool season orographic precipitation processes where the representation of landform can significantly influence vertical velocity profiles and cloud moisture entrainment rates. In this work we report on recent progress in high resolution regional climate modeling of the Colorado Headwaters region using an updated version of the Weather Research and Forecasting (WRF) model and a hydrological extension package called WRF-Hydro. Previous work has shown that the WRF-Hydro modeling system forced by high resolution WRF model output can produce credible depictions of winter orographic precipitation and resultant monthly and annual river flows. Here we present results from a detailed study of an extreme springtime snowfall event that occurred along the Colorado Front Range in March of 2003. First an analysis of the simulated streamflows resulting from the melt out of that event are presented followed by an analysis of projected streamflows from the event where the atmospheric forcing in the WRF model is perturbed using the Psuedo-Global-Warming (PGW) perturbation methodology. Results from the impact of warming on total precipitation, snow-rain partitioning and surface hydrological fluxes (evapotranspiration and runoff) will be discussed in the context of how potential changes in temperature impact the amount of precipitation, the phase of precipitation (rain vs. snow) and the timing and amplitude of streamflow responses. It is shown that under the assumptions of the PGW method, intense precipitation rates increase during the event and, more importantly, that more precipitation falls as rain versus snow which significantly amplifies the runoff response from one where runoff is produced gradually to where runoff is more
gochis, David; Parodi, Antonio; Hooper, Rick; Jha, Shantenu; Zaslavsky, Ilya
The need for improved assessments and predictions of many key environmental variables is driving a multitude of model development efforts in the geosciences. The proliferation of weather and climate impacts research is driving a host of new environmental prediction model development efforts as society seeks to understand how climate does and will impact key societal activities and resources and, in turn, how human activities influence climate and the environment. This surge in model development has highlighted the role of model coupling as a fundamental activity itself and, at times, a significant bottleneck in weather and climate impacts research. This talk explores some of the recent activities and progress that has been made in assessing the attributes of various approaches to the coupling of physics-based process models for hydrometeorology. One example modeling system that is emerging from these efforts is the community 'WRF-Hydro' modeling system which is based on the modeling architecture of the Weather Research and Forecasting (WRF). An overview of the structural components of WRF-Hydro will be presented as will results from several recent applications which include the prediction of flash flooding events in the Rocky Mountain Front Range region of the U.S. and along the Ligurian coastline in the northern Mediterranean. Efficient integration of the coupled modeling system with distributed infrastructure for collecting and sharing hydrometeorological observations is one of core themes of the work. Specifically, we aim to demonstrate how data management infrastructures used in the US and Europe, in particular data sharing technologies developed within the CUAHSI Hydrologic Information System and UNIDATA, can interoperate based on international standards for data discovery and exchange, such as standards developed by the Open Geospatial Consortium and adopted by GEOSS. The data system we envision will help manage WRF-Hydro prediction model data flows, enabling
Full Text Available The first intercomparisons of cloud microphysics schemes implemented in the Weather Research and Forecasting (WRF mesoscale atmospheric model (version 3.5.1 are performed on the Antarctic Peninsula using the polar version of WRF (Polar WRF at 5 km resolution, along with comparisons to the British Antarctic Survey's aircraft measurements (presented in part 1 of this work; Lachlan-Cope et al., 2016. This study follows previous works suggesting the misrepresentation of the cloud thermodynamic phase in order to explain large radiative biases derived at the surface in Polar WRF continent-wide (at 15 km or coarser horizontal resolution and in the Polar WRF-based operational forecast model Antarctic Mesoscale Prediction System (AMPS over the Larsen C Ice Shelf at 5 km horizontal resolution. Five cloud microphysics schemes are investigated: the WRF single-moment five-class scheme (WSM5, the WRF double-moment six-class scheme (WDM6, the Morrison double-moment scheme, the Thompson scheme, and the Milbrandt–Yau double-moment seven-class scheme. WSM5 (used in AMPS and WDM6 (an upgrade version of WSM5 lead to the largest biases in observed supercooled liquid phase and surface radiative biases. The schemes simulating clouds in closest agreement to the observations are the Morrison, Thompson, and Milbrandt schemes for their better average prediction of occurrences of clouds and cloud phase. Interestingly, those three schemes are also the ones allowing for significant reduction of the longwave surface radiative bias over the Larsen C Ice Shelf (eastern side of the peninsula. This is important for surface energy budget consideration with Polar WRF since the cloud radiative effect is more pronounced in the infrared over icy surfaces. Overall, the Morrison scheme compares better to the cloud observation and radiation measurements. The fact that WSM5 and WDM6 are single-moment parameterizations for the ice crystals is responsible for their lesser
Srivastava, Prashant K.; Han, Dawei; Rico-Ramirez, Miguel A.; O'Neill, Peggy; Islam, Tanvir; Gupta, Manika; Dai, Qiang
This study explores the performance of soil moisture data from the global European Centre for Medium Range Weather Forecasts (ECMWF) ERA interim reanalysis datasets using the Weather Research and Forecasting (WRF) mesoscale numerical weather model coupled with the Noah Land surface model for hydrological applications. For evaluating the performance of WRF for soil moisture estimation, three domains are taken into account. The domain with best performance is used for estimating the soil moisture deficit (SMD). Further, several approaches are presented in this study to evaluate the efficiency of WRF simulated soil moisture for SMD estimation and compared against Soil Moisture and Ocean Salinity (SMOS) downscaled and non-downscaled soil moisture. In this study, the first approach is based on the empirical relationship between WRF soil moisture and the SMD on a continuous time series basis, while the second approach is focused on the vegetation cover impact on SMD retrieval, depicted in terms of growing and non-growing seasons. The linear growing and non-growing seasonal model in combination performs well with the NSE = 0.79, RMSE = 0.011 m; Bias = 0.24 m, in comparison to linear model (NSE = 0.70, RMSE = 0.013 m; Bias = 0.01 m). The performance obtained using WRF soil moisture is comparable to SMOS level 2 product but lower than the downscaled SMOS datasets. The results indicate that methodologies could be useful for modelers working in the field of soil moisture information system and SMD estimation at a catchment scale. The study could be useful for ungauged basins that pose a challenge to hydrological modeling due to unavailability of datasets for proper model calibration and validation.
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 that 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.
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.
Gunwani, Preeti; Mohan, Manju
In the present work sensitivity of Weather Research Forecasting (WRF) Model has been carried out using five planetary boundary layer (PBL) schemes - Yonsei University Scheme (YSU), Mellor-Yamada-Janjić scheme (MYJ), Aymmetric Convective Model version 2 (ACM2), Quasi Normal Scale Elimination scheme (QNSE), Mellor-Yamada-Nakanishi-Niino scheme (MYNN) in different climatic zones over India namely Tropical, Temperate and Arid for surface meteorological parameters, upper air variables and planetary boundary layer height during summer and winter season. The model outputs have been compared with observations through standard statistical measures. The aim is to study the relative performance of these schemes, selecting the best option climatic zone-wise and thereby minimizing uncertainty in model predictions. WRF model performance evaluation shows better agreement for temperature and relative humidity compared to wind speed. Overall for India, ACM2, QNSE show good performance for temperature and relative humidity whereas ACM2, MYNN show better performance for wind speed though these may vary for different climatic zones. Geopotential height and wind over 850 hPa is well simulated by ACM2 and MYNN over India. For PBL height ACM2, MYNN and MYJ works best for Chennai, New Delhi and Kolkata respectively during summer period. However, for winter period MYJ works best for Chennai while, QNSE works best for New Delhi and Kolkata. Considering all meteorological parameters together, it is seen that for arid zone ACM2, QNSE and MYJ schemes work reasonably well. For temperate zone, ACM2, QNSE and MYNN schemes show better results. For tropical zone all PBL schemes work closely. Hence, depending on the application, parameter and climate zone, this study provides suitable recommendations for choosing PBL schemes appropriately for each zone and parameter separately for the Indian region.
Pena Diaz, Alfredo; Hahmann, Andrea N.
Direct estimations of turbulent fluxes and atmospheric stability were performed from a sonic anemometer at 50 m height on a meteorological mast at the Horns Rev wind farm in the North Sea. The stability and flux estimations from the sonic measurements are compared with bulk results from a cup...... 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...
Stec, Magdalena; Szymanowski, Mariusz; Kryza, Maciej
Wildfires are one of the main ecosystems' disturbances for forested, seminatural and agricultural areas. They generate significant economic loss, especially in forest management and agriculture. Forest fire risk modeling is therefore essential e.g. for forestry administration. In August 2015 a new method of forest fire risk forecasting entered into force in Poland. The method allows to predict a fire risk level in a 4-degree scale (0 - no risk, 3 - highest risk) and consists of a set of linearized regression equations. Meteorological information is used as predictors in regression equations, with air temperature, relative humidity, average wind speed, cloudiness and rainfall. The equations include also pine litter humidity as a measure of potential fuel characteristics. All these parameters are measured routinely in Poland at 42 basic and 94 auxiliary sites. The fire risk level is estimated for a current (basing on morning measurements) or next day (basing on midday measurements). Entire country is divided into 42 prognostic zones, and fire risk level for each zone is taken from the closest measuring site. The first goal of this work is to assess if the measurements needed for fire risk forecasting may be replaced by the data from mesoscale meteorological model. Additionally, the use of a meteorological model would allow to take into account much more realistic spatial differentiation of weather elements determining the fire risk level instead of discrete point-made measurements. Meteorological data have been calculated using the Weather Research and Forecasting model (WRF). For the purpose of this study the WRF model is run in the reanalysis mode allowing to estimate all required meteorological data in a 5-kilometers grid. The only parameter that cannot be directly calculated using WRF is the litter humidity, which has been estimated using empirical formula developed by Sakowska (2007). The experiments are carried out for two selected years: 2010 and 2012. The
Zhou, Jianzhong; Zhang, Hairong; Zhang, Jianyun; Zeng, Xiaofan; Ye, Lei; Liu, Yi; Tayyab, Muhammad; Chen, Yufan
An accurate flood forecasting with long lead time can be of great value for flood prevention and utilization. This paper develops a one-way coupled hydro-meteorological modeling system consisting of the mesoscale numerical weather model Weather Research and Forecasting (WRF) model and the Chinese Xinanjiang hydrological model to extend flood forecasting lead time in the Jinshajiang River Basin, which is the largest hydropower base in China. Focusing on four typical precipitation events includes: first, the combinations and mode structures of parameterization schemes of WRF suitable for simulating precipitation in the Jinshajiang River Basin were investigated. Then, the Xinanjiang model was established after calibration and validation to make up the hydro-meteorological system. It was found that the selection of the cloud microphysics scheme and boundary layer scheme has a great impact on precipitation simulation, and only a proper combination of the two schemes could yield accurate simulation effects in the Jinshajiang River Basin and the hydro-meteorological system can provide instructive flood forecasts with long lead time. On the whole, the one-way coupled hydro-meteorological model could be used for precipitation simulation and flood prediction in the Jinshajiang River Basin because of its relatively high precision and long lead time.
Eiserloh, Arthur J., Jr.
In this study, data assimilation methods of 3-D variational analysis (3DVAR), observation nudging, and analysis (grid) nudging were evaluated in the Weather Research and Forecasting (WRF) model for a high-impact, multi-episode landfalling atmospheric river (AR) event for Northern California from 28 November to 3 December, 2012. Eight experiments were designed to explore various combinations of the data assimilation methods and different initial conditions. The short-to-medium range quantitative precipitation forecast (QPF) performances were tested for each experiment. Surface observations from the National Oceanic and Atmospheric Administration's (NOAA) Hydrometeorology Network (HMT), National Weather Service (NWS) radiosondes, and GPS Radio Occultation (RO) vertical profiles from the Constellation Observing System for Meteorology Ionosphere and Climate (COSMIC) satellites were used for assimilation. Model results 2.5 days into the forecast showed slower timing of the 2nd AR episode by a few hours and an underestimation in AR strength. For the entire event forecasts, the non-grid-nudging experiments showed the lowest mean absolute error (MAE) for rainfall accumulations, especially those with 3DVAR. Higher-resolution initial conditions showed more realistic coastal QPFs. Also, a 3-h nudging time interval and time window for observation nudging and 3DVAR, respectively, may be too large for this type of event, and it did not show skill until 60-66 h into the forecast.
Muller, B. M.; Herbster, C. G.; Mosher, F. R.
It is not unusual to observe atmospheric eddies in satellite imagery of the marine stratus and stratocumulus clouds that characterize the summertime weather of the California coastal region and near-shore oceanic environment. The winds of the marine atmospheric boundary layer (MABL) over the ocean interact with the high terrain of prominent headlands and islands to create order-10 km scale areas of swirling air that can contain a cloud-free eye, 180-degree wind reversals at the surface over a period of minutes, and may be associated with mixing and turbulence between the high-humidity air of the MABL and the much warmer and drier inversion layer air above. However, synoptic and even subsynoptic surface weather measurements, and the synoptic upper-air observing network are inadequate, or in some cases, completely unable, to detect and characterize the formation, movement, and even the existence of the eddies. They can literally slip between land-based surface observation locations, or stay over the near-shore ocean environment where there may be no surface meteorological measurements. This study presents Weather Research and Forecasting (WRF) Model simulations of these small-scale, terrain-driven, atmospheric features in the MABL from cases detected in GOES satellite imagery. The purpose is to use model output to diagnose the formation mechanisms, sources of vorticity, and the air flow in and around the eddies. Satellite imagery is compared to simulated atmospheric variables to validate features generated within the model atmosphere, and model output is employed as a surrogate atmosphere to better understand the atmospheric characteristics of the eddies. Model air parcel trajectories are estimated to trace the movement and sources of the air contained in and around these often-observed, but seldom-measured features.
Arnault, Joel; Rummler, Thomas; Kunstmann, Harald
Soil moisture plays a crucial role in land-atmosphere interactions. Land-atmosphere feedbacks are expected to be strongest in transition zones between wet and dry land surfaces. It is therefore questionable whether a physically-enhanced description of soil moisture variability in a numerical model would improve the realism of the simulated atmosphere. This question is investigated here for a two-year period in Germany, including a one-year spinup time, using the hydrologically enhanced version of the Weather Research and Forecasting WRF model, namely WRF-Hydro. The simulated domain covers Germany and neighboring areas. Atmospheric processes are resolved on a 4km resolution grid with explicit convection, whereas hydrological processes, namely overland flow, subsurface lateral flow and river flow, are resolved on a subgrid at 400 m resolution. This WRF-Hydro setup is run for several values of the surface infiltration parameter, in order to evaluate model result uncertainty originating from uncertainty in the description of terrestrial hydrological processes. Soil moisture variability deduced from this WRF-Hydro ensemble is compared with that deduced from a WRF-standalone ensemble. WRF and WRF-Hydro results are validated with daily gridded E-OBS datasets of precipitation and temperature from the European Climate Assessment & Dataset, and daily discharge data from the Global Runoff Data Center GRDC. The impact of the physically-enhanced description of soil moisture variability in WRF-Hydro is finally investigated with the concept of soil moisture memory.
García-Valdecasas Ojeda, Matilde; De Franciscis, Sebastiano; Raquel Gámiz-Fortis, Sonia; Castro-Díez, Yolanda; Esteban-Parra, María Jesus
Variable Infiltration Capacity (VIC) model is a large-scale, semi-distributed hydrologic model . Its most important properties are related to the land surface, modeled as a grid of large and uniform cells with sub-grid heterogeneity (e.g. land cover), as well as to the local water influx (i.e. water can only enter a grid cell via the atmosphere and the channel flow between grid cells is ignored). The portions of surface and subsurface water runoff that reach the local channel network, are assumed to stay in the channel, and cannot flow back into the soil. In a second step, routing of streamflow is performed separately from the land surface simulation, using a separate model, the Routing Model, described in . The final goal of our research consists into set an optimal hydrological and climate model to study the evolution of the streamflow of Guadalquivir Basin with different future land use, land cover and climate scenarios. In this work we study the coupling between VIC model, Routing model and Weather Research and Forecasting (WRF) model in order to perform the evolution of the streamflow for the Guadalquivir Basin (Spain). For this end, a calibration of the most relevant VIC model parameters using real streamflow daily time series, obtained from CEDEX (Centro de Estudios y Experimentación de Obras Públicas, Spain) database  was performed. In the time period under study, i.e. the decades 1988-1997 (calibration step) and 1998-2007 (verification step), the VIC model has been coupled with observational climate data, obtained from SPAIN02 database . Additionally, we carried out a sensitivity analysis of WRF model to different parameterizations using different cumulus, microphysics and surface/planetary boundary layer schemes for the period 1995-1996. WRF runs were carried over a domain encompassing the Iberian Peninsula and nested in the coarser EURO-CORDEX domain . The optimal parameters set resulting from such analysis have been used to obtain a
Barlage, M.; Zeng, X.; Mitchell, K.
Several input surface datasets currently used in operational weather forecasting are outdated and based on low resolution original datasets. Using higher resolution MODIS and AVHRR satellite data, the datasets of green vegetation fraction(GVF) and maximum snow albedo(MSA) are calculated and updated. The MSA dataset is obtained from 0.05 degree albedo and reflectance from the MODIS instrument onboard Terra and Aqua. Datasets of GVF are calculated from 1km and 2km MODIS, and 0.144 degree AVHRR NDVI data. The new datasets are tested and validated in the operational version of WRF used at NCEP. The use of this higher resolution input data provides an increased land surface heterogeneity needed at the current operational model resolution. It also progresses toward real-time updating of land surface states in operational forecasting. The goals of this work are to 1) improve near-surface temperature prediction in snow-covered regions and 2) derive the algorithm to provide real-time inclusion of satellite-derived NDVI into current operational weather forecasts.
Pu, Zhaoxia; Chachere, Catherine N.; Hoch, Sebastian W.; Pardyjak, Eric; Gultepe, Ismail
A field campaign to study cold season fog in complex terrain was conducted as a component of the Mountain Terrain Atmospheric Modeling and Observations (MATERHORN) Program from 07 January to 01 February 2015 in Salt Lake City and Heber City, Utah, United States. To support the field campaign, an advanced research version of the Weather Research and Forecasting (WRF) model was used to produce real-time forecasts and model evaluation. This paper summarizes the model performance and preliminary evaluation of the model against the observations. Results indicate that accurately forecasting fog is challenging for the WRF model, which produces large errors in the near-surface variables, such as relative humidity, temperature, and wind fields in the model forecasts. Specifically, compared with observations, the WRF model overpredicted fog events with extended duration in Salt Lake City because it produced higher moisture, lower wind speeds, and colder temperatures near the surface. In contrast, the WRF model missed all fog events in Heber City, as it reproduced lower moisture, higher wind speeds, and warmer temperatures against observations at the near-surface level. The inability of the model to produce proper levels of near-surface atmospheric conditions under fog conditions reflects uncertainties in model physical parameterizations, such as the surface layer, boundary layer, and microphysical schemes.
difficulty of making accurate fallout predictions. 2.2.1 Fireball In the first few instants following a nuclear explosion, fireball temperatures can...exceed 107 K, and the resulting gradient between the atmospheric and the fireball temperatures will cause the fireball to rise . The temperature...will decrease initially through radiative cooling, but as toroidal motion of the fireball begins to dominate, entrainment of cold air will result in
Ghotbi, Saba; Sotoudeheian, Saeed; Arhami, Mohammad
Satellite remote sensing products of AOD from MODIS along with appropriate meteorological parameters were used to develop statistical models and estimate ground-level PM10. Most of previous studies obtained meteorological data from synoptic weather stations, with rather sparse spatial distribution, and used it along with 10 km AOD product to develop statistical models, applicable for PM variations in regional scale (resolution of ≥10 km). In the current study, meteorological parameters were simulated with 3 km resolution using WRF model and used along with the rather new 3 km AOD product (launched in 2014). The resulting PM statistical models were assessed for a polluted and largely variable urban area, Tehran, Iran. Despite the critical particulate pollution problem, very few PM studies were conducted in this area. The issue of rather poor direct PM-AOD associations existed, due to different factors such as variations in particles optical properties, in addition to bright background issue for satellite data, as the studied area located in the semi-arid areas of Middle East. Statistical approach of linear mixed effect (LME) was used, and three types of statistical models including single variable LME model (using AOD as independent variable) and multiple variables LME model by using meteorological data from two sources, WRF model and synoptic stations, were examined. Meteorological simulations were performed using a multiscale approach and creating an appropriate physic for the studied region, and the results showed rather good agreements with recordings of the synoptic stations. The single variable LME model was able to explain about 61%-73% of daily PM10 variations, reflecting a rather acceptable performance. Statistical models performance improved through using multivariable LME and incorporating meteorological data as auxiliary variables, particularly by using fine resolution outputs from WRF (R2 = 0.73-0.81). In addition, rather fine resolution for PM
Watson, Leela R.; Bauman, William H., III
NASA prefers to land the space shuttle at Kennedy Space Center (KSC). When weather conditions violate Flight Rules at KSC, NASA will usually divert the shuttle landing to Edwards Air Force Base (EAFB) in Southern California. But forecasting surface winds at EAFB is a challenge for the Spaceflight Meteorology Group (SMG) forecasters due to the complex terrain that surrounds EAFB, One particular phenomena identified by SMG is that makes it difficult to forecast the EAFB surface winds is called "wind cycling". This occurs when wind speeds and directions oscillate among towers near the EAFB runway leading to a challenging deorbit bum forecast for shuttle landings. The large-scale numerical weather prediction models cannot properly resolve the wind field due to their coarse horizontal resolutions, so a properly tuned high-resolution mesoscale model is needed. The Weather Research and Forecasting (WRF) model meets this requirement. The AMU assessed the different WRF model options to determine which configuration best predicted surface wind speed and direction at EAFB, To do so, the AMU compared the WRF model performance using two hot start initializations with the Advanced Research WRF and Non-hydrostatic Mesoscale Model dynamical cores and compared model performance while varying the physics options.
Full Text Available We use measurements by the 52 MHz wind-profiling radar ESRAD, situated near Kiruna in Arctic Sweden, and simulations using the Advanced Research and Weather Forecasting model, WRF, to study vertical winds and turbulence in the troposphere in mountain-wave conditions on 23 , 24 and 25 January 2003. We find that WRF can accurately match the vertical wind signatures at the radar site when the spatial resolution for the simulations is 1 km. The horizontal and vertical wavelengths of the dominating mountain-waves are ∼10–20 km and the amplitudes in vertical wind 1–2 m/s. Turbulence below 5500 m height, is seen by ESRAD about 40% of the time. This is a much higher rate than WRF predictions for conditions of Richardson number (Ri >1 but similar to WRF predictions of Ri>2. WRF predicts that air crossing the 100 km wide model domain centred on ESRAD has a ∼10% chance of encountering convective instabilities (Ri>0. somewhere along the path. The cause of low Ri is a combination of wind-shear at synoptic upper-level fronts and perturbations in static stability due to the mountain-waves. Comparison with radiosondes suggests that WRF underestimates wind-shear and the occurrence of thin layers with very low static stability, so that vertical mixing by turbulence associated with mountain waves may be significantly more than suggested by the model.
Newton, Richard; Vaughan, Geraint; Chemel, Charles
The CAST campaign, along with sister campaigns CONTRAST and ATTREX, was an aircraft and field campaign based in Guam and Manus Island, Papua New Guinea between January and March 2014. The field campaign in Manus Island consisted of ground measurements and ozonesonde launches. One of the observations from the ozonesonde data was a low-ozone event in the tropical tropopause layer on 21 - 23 February, which was traced to the outflow from a marine convective system that pumped ozone-deficient air into the tropopause region. This air was advected by an easterly jet over Manus Island, where it was measured by the ozonesondes. This low-ozone event has prompted further investigation using the Weather Research and Forecasting (WRF) model. The model has been run for the period between 17 - 23 February to investigate its ability to reproduce the conditions that produced the low-ozone event. The model output was compared with the ground measurements and ozonesonde measurements from Manus, and tracers were used to understand how efficient the convective systems are at lifting air from the surface or lower troposphere into the tropopause. Furthermore, the sensitivity of particular physics options to the experiment was investigated. Future work will be focused on finding other instances of the low-ozone phenomenon in the tropopause layer in order to determine their typical frequency, size and longevity.
Full Text Available 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, denominated "modified BMJ" scheme, where the humidity reference profile is more moist, was developed and 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 dataset, 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.
Full Text Available The Weather Research and Forecasting (WRF model coupled with an Urban Canopy Model (UCM was used for studying urban environmental issues. Because land use data employed in the WRF model do not agree with the current situation around Guangzhou, China, the performance of WRF/UCM with new land-use data extracted from Remote Sensing (RS data was evaluated in early August 2012. Results from simulations reveal that experiments with the extracted data are capable of reasonable reproductions of the majority of the observed temporal characteristics of the 2-m temperature, and can capture the characteristics of Urban Heat Island (UHI. The “UCM_12” simulation, which employed the extracted land-use data with the WRF/UCM model, provided the best reproduction of the 2-m temperature data evolution and the smallest minimum absolute average error when compared with the other two experiments without coupled UCM. The contributions of various factors to the UHI effect were analyzed by comparing the energy equilibrium processes of “UCM_12” in urban and suburban areas. Analysis revealed that energy equilibrium processes with new land use data can explain the diurnal character of the UHI intensity variation. Furthermore, land use data extracted from RS can be used to simulate the UHI.
Srabanti Ballav; Prabir K Patra; Yousuke Sawa; Hidekazu Matsueda; Ahoro Adachi; Shigeru Onogi; Masayuki Takigawa; Utpal K De
Simulation of carbon dioxide (CO2) at hourly/weekly intervals and fine vertical resolution at the continental or coastal sites is challenging because of coarse horizontal resolution of global transport models. Here the regional Weather Research and Forecasting (WRF) model coupled with atmospheric chemistry is adopted for simulating atmospheric CO2 (hereinafter WRF-CO2) in nonreactive chemical tracer mode. Model results at horizontal resolution of 27 × 27 km and 31 vertical levels are compared with hourly CO2 measurements from Tsukuba, Japan (36.05°N, 140.13°E) at tower heights of 25 and 200 m for the entire year 2002. Using the wind rose analysis, we find that the fossil fuel emission signal from the megacity Tokyo dominates the diurnal, synoptic and seasonal variations observed at Tsukuba. Contribution of terrestrial biosphere fluxes is of secondary importance for CO2 concentration variability. The phase of synoptic scale variability in CO2 at both heights are remarkably well simulated the observed data (correlation coefficient >0.70) for the entire year. The simulations of monthly mean diurnal cycles are in better agreement with the measurements at lower height compared to that at the upper height. The modelled vertical CO2 gradients are generally greater than the observed vertical gradient. Sensitivity studies show that the simulation of observed vertical gradient can be improved by increasing the number of vertical levels from 31 in the model WRF to 37 (4 below 200 m) and using the Mellor–Yamada–Janjic planetary boundary scheme. These results have large implications for improving transport model simulation of CO2 over the continental sites.
S K Deb; T P Srivastava; C M Kishtawal
The summer monsoon season of the year 2006 was highlighted by an unprecedented number of monsoon lows over the central and the western parts of India,particularly giving widespread rainfall over Gujarat and Rajasthan.Ahmedabad had received 540.2 mm of rainfall in the month of August 2006 against the climatological mean of 219.8 mm.The two spells of very heavy rainfall of 108.4 mm and 97.7 mm were recorded on 8 and 12 August 2006 respectively.Due to meteorological complexities involved in replicating the rainfall occurrences over a region,the Weather Research and Forecast (WRF –ARW version)modeling system with two different cumulus schemes in a nested con ﬁguration is chosen for simulating these events.The spatial distributions of large-scale circulation and moisture ﬁelds have been simulated reasonably well in this model,though there are some spatial biases in the simulated rainfall pattern.The rainfall amount over Ahmedabad has been underestimated by both the cumulus parameterization schemes.The quantitative validation of the simulated rainfall is done by calculating the categorical skill scores like frequency bias,threat scores (TS)and equitable threat scores (ETS).In this case the KF scheme has outperformed the GD scheme for the low precipitation threshold.
A. de Meij
Full Text Available The objective of this study is to evaluate the impact of meteorological input data on calculated gas and aerosol concentrations. We use two different meteorological models (MM5 and WRF together with the chemistry transport model CHIMERE. We focus on the Po valley area (Italy for January and June 2005.
Firstly we evaluate the meteorological parameters with observations. The analysis shows that the performance of both models is similar, however some small differences are still noticeable.
Secondly, we analyze the impact of using MM5 and WRF on calculated PM10 and O3 concentrations. In general CHIMERE/MM5 and CHIMERE/WRF underestimate the PM10 concentrations for January. The difference in PM10 concentrations for January between CHIMERE/MM5 and CHIMERE/WRF is around a factor 1.6 (PM10 higher for CHIMERE/MM5. This difference and the larger underestimation in PM10 concentrations by CHIMERE/WRF are related to the differences in heat fluxes and the resulting PBL heights calculated by WRF. In general the PBL height by WRF meteorology is a factor 2.8 higher at noon in January than calculated by MM5. This study showed that the difference in microphysics scheme has an impact on the profile of cloud liquid water (CLW calculated by the meteorological driver and therefore on the production of SO4 aerosol.
A sensitivity analysis shows that changing the Noah Land Surface Model (LSM for the 5-layer soil temperature model, the calculated monthly mean PM10 concentrations increase by 30%, due to the change in the heat fluxes and the resulting PBL heights.
For June, PM10 calculated concentrations by CHIMERE/MM5 and CHIMERE/WRF are similar and agree with the observations. Calculated O3 values for June are in general overestimated by a factor 1.3 by CHIMERE/MM5 and CHIMRE/WRF. The reason for this is that daytime NO2
Lundquist, Katherine Ann [Univ. of California, Berkeley, CA (United States)
Accurate simulations of atmospheric boundary layer flow are vital for predicting dispersion of contaminant releases, particularly in densely populated urban regions where first responders must react within minutes and the consequences of forecast errors are potentially disastrous. Current mesoscale models do not account for urban effects, and conversely urban scale models do not account for mesoscale weather features or atmospheric physics. The ultimate goal of this research is to develop and implement an immersed boundary method (IBM) along with a surface roughness parameterization into the mesoscale Weather Research and Forecasting (WRF) model. IBM will be used in WRF to represent the complex boundary conditions imposed by urban landscapes, while still including forcing from regional weather patterns and atmospheric physics. This document details preliminary results of this research, including the details of three distinct implementations of the immersed boundary method. Results for the three methods are presented for the case of a rotation influenced neutral atmospheric boundary layer over flat terrain.
native features of HTML. WRFEE is based on the model-view-controller ( MVC ) paradigm whereby the model controls program flow (see figure 1), the view is...modifications are outlined later in this report. 3 3. Background WRFEE is based on the MVC paradigm whereby the model handles data and the business logic...Wrfendtoend Java Bean The WRFEE bean represents the “model” portion of the MVC system, as it steps through each of the requisite processes
GAO Hao; JIA Gensuo
As more satellite-derived land cover products used in the study of global change,especially climate modeling,assessing their quality has become vitally important.In this study,we developed a distance metric based on the parameters used in weather research and forecasting (WRF) to characterize the degree of disagreement among land cover products and to identify the tolerance for misclassification within the International Geosphere Biosphere Programme (IGBP) classification scheme.We determined the spatial degree of disagreement and then created maps of misclassification of Moderate Resolution Imaging Spectoradiometer (MODIS) products,and we calculated overall and class-specific accuracy and fuzzy agreement in a WRF model.Our results show a high level of agreement and high tolerance of misclassification in the WRF model between large-scale homogeneous landscapes,while a low level of agreement and tolerance of misclassification appeared in heterogeneous landscapes.The degree of disagreement varied significantly among seven regions of China.The class-specific accuracy and fuzzy agreement in MODIS Collection 4 and 5 products varied significantly.High accuracy and fuzzy agreement occurred in the following classes:water,grassland,cropland,and barren or sparsely vegetated.Misclassification mainly occurred among specific classes with similar plant functional types and low discriminative spectro-temporal signals.Some classes need to be improved further; the quality of MODIS land cover products across China still does not meet the common requirements of climate modeling.Our findings may have important implications for improving land surface parameterization for simulating climate and for better understanding the influence of the land cover change on climate.
Full Text Available Yunnan province is the core region of the drought in the Southwest China, which makes the region become the hot spot in the meteorological research. However, among the various influencing factors of the drought in Yunnan province, the influence of the land use/cover change (LUCC on the drought has not been quantitatively analyzed. The LUCC in recent decades was first quantitatively analyzed in this study. Given the fact that severe drought in Yunnan province is mainly due to much-less-than-normal precipitation and much-warmer-than-normal surface temperature, this study focused on the future spatiotemporal heterogeneity of the temperature and precipitation, which have great impacts on the drought. Finally, the influencing factors of drought in Yunnan province were simulated with the Weather Research and Forecasting (WRF model, and the risk of drought was spatially analyzed with the meteorological drought composite index. The results indicate that the large-area forest plays a more important role in alleviating the risk of drought than other vegetation types do. Besides, the changes of the landscape structure resulting from the urban expansion play a significant role in intensifying the risk of drought.
Full Text Available The meteorological model WRF-ARW (Weather Research and Forecasting - Advanced Research WRF is a new generation model that has a worldwide growing community of users. In the framework of a project that studies the feasibility of implementing it operationally at the Meteorological Service of Catalonia, a verification of the forecasts produced by the model in several cases of precipitation observed over Catalonia has been carried out. Indeed, given the importance of precipitation forecasts in this area, one of the main objectives was to study the sensitivity of the model in different configurations of its parameterizations of convection and cloud microphysics. In this paper, we present the results of this verification for two domains, a 36-km grid size and one of 12 km grid size, unidirectionally nested to the previous one. In the external domain, the evaluation was based on the analysis of the main statistical parameters (ME and RMSE for temperature, relative humidity, geopotential and wind, and it has been determined that the combination using the Kain-Fritsch convective scheme with the WSM5 microphysical scheme has provided the best results. Then, with this configuration set for the external domain, some forecasts at the nested domain have been done, by combining different convection and cloud microphysics schemes, leading to the conclusion that the most accurate configuration is the one combining the convective parameterization of Kain-Fritsch and the Thompson microphysics scheme.
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.
Lian, Lishu; Li, Baofu; Chen, Yaning; Chu, Cuicui; Qin, Yanhua
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 < 0.001) between the modeled and measured values. The model simulates precipitation less well, with correlation coefficients of 0.41-0.91, but they are all at statistically significant levels, with p < 0.05. During the 20-year period, the LUCCs in the study area consisted mainly of conversions from dry land to urbanized land (747.3 km(2)) and bare/sparse vegetation (132.4 km(2)). The LUCCs caused a 0.16 °C temperature increase in January and October and 0.01 and 0.18 °C temperature decreases in April and July, respectively. The range of temperature changes over mixed forest and water bodies due to the LUCCs was wide (0.39-1.31 °C) and was narrower over deciduous broadleaf forest and wetland (0.01 to 0.06 °C). The LUCCs did not change the precipitation greatly in January, April, and October but did affect the precipitation in July substantially, causing a decrease of 23.71 mm. The LUCCs did not affect 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.
Wilgan, K. I.; Rohm, W.; Bosy, J.; Geiger, A.; Hurter, F.
The GNSS (Global Navigation Satellite Systems) signal propagation delay in neutral atmosphere can be described in terms of total refractivity which depends on the atmospheric parameters: air pressure, temperature and water vapor partial pressure. In this study we have reconstructed the total refractivity profiles over Poland using the least-squares collocation software COMEDIE (Collocation of Meteorological Data for Interpretation and Estimation of Tropospheric Pathdelays). Profiles were calculated from different combinations of data sets from following sources: meteorological parameters from Numerical Weather Prediction Model WRF (Weather Research and Forecasting) or EUREF Permanent Network (EPN) stations and zenith total delay (ZTD) from ground-based GNSS products on ASG-EUPOS stations. The combinations of data sets included into this study are: 'WRF only', 'WRF/GNSS', 'WRF/GNSS/EPN' and 'GNSS only'. To find the data set with the best accuracy, profiles were compared with the reference radiosonde observations. The data set with the best accuracy is the combined 'WRF/GNSS' with mean bias close to 0 and standard deviation of 3 ppm. The data set 'WRF/GNSS/EPN' shows very similar accuracy so, there is no need to include the additional ground-based meteorological information from EPN stations. The data set 'GNSS only' shows much worse accuracy with the discrepancies at lower altitudes even at the level of -30 ppm. The data set 'WRF only' shows as good agreement with reference data as 'WRF/GNSS' in term of total refractivity, but when we calculated ZTD from all sets, we found that standard deviations from residuals are almost two times larger for the 'WRF only' dataset. We continue advancing the collocation algorithms, so the ZTD from the model can be useful as a priori troposphere information for example in PPP (Precise Point Positioning) technique.
Ragi, A. R.; Sharan, Maithili; Haddad, Z. S.
This study examines the influence of Purdue-Lin microphysical parameterization scheme (Lin et al.,1983) on quantitative precipitation for pre-monsoon/monsoon conditions over southern peninsular India in the Weather Research and Forecasting (WRF) model. An ideal microphysical scheme has to describe the formation, growth of cloud droplets and ice crystals and fall out as precipitation. Microphysics schemes can be broadly categorized into two types: bin and bulk particle size distribution (Morrison, 2010). Bulk schemes predict one or more bulk quantities and assume some functional form for the particle size distribution. For better parameterization, proper interpretation of these hydrometeors (Cloud Droplets, Raindrops, Ice Crystals and Aggregates, Rimed Ice Particles, Graupel, Hail) and non-hydrometeors (Aerosols vs. Condensation Nuclei vs. Cloud Condensation Nuclei vs. Ice Nuclei) is very important. The Purdue-Lin scheme is a commonly used microphysics scheme in WRF model utilizing the "bulk" particle size distribution, meaning that a particle size distribution is assumed. The intercept parameter (N0) is, in fact, turns out to be independent of the density. However, in situ observations suggest (Haddad et al., 1996, 1997) that the mass weighted mean diameter is correlated with water content per unit volume (q), leading to the fact that N0 depends on it. Here, in order to analyze the correlation of droplet size distribution with the convection, we have carried out simulations by implementing a consistent methodology to enforce a correlation between N0 and q in the Purdue-Lin microphysics scheme in WRF model. The effect of particles in Indian Summer Monsoon has been examined using frequency distribution of rainfall at surface, daily rainfall over the domain and convective available potential energy and convective inhibition. The simulations are conducted by analyzing the maximum rainfall days in the pre-monsoon/monsoon seasons using Tropical Rainfall Measuring Mission
Avolio, E.; Federico, S.; Miglietta, M.
The sensitivity of boundary layer variables to five (two non-local and three local) planetary boundary-layer (PBL) parameterization schemes, available in the Weather Research and Forecasting (WRF) mesoscale meteorological model, is evaluated in an experimental site in Calabria region (southern...... Italy), in an area characterized by a complex orography near the sea. Results of 1kmÃ—1km grid spacing simulations are compared with the data collected during a measurement campaign in summer 2009, considering hourly model outputs. Measurements from several instruments are taken into account...... the surface, where the model uncertainties are, usually, smaller than at the surface. A general anticlockwise rotation of the simulated flow with height is found at all levels. The mixing height is overestimated by all schemes and a possible role of the simulated sensible heat fluxes for this mismatching...
Chin, H S; Caldwell, P M; Bader, D C
The Weather and Research Forecast (WRF) model version 3.0.1 is used to explore California wintertime model wet bias. In this study, two wintertime storms are selected from each of four major types of large-scale conditions; Pineapple Express, El Nino, La Nina, and synoptic cyclones. We test the impacts of several model configurations on precipitation bias through comparison with three sets of gridded surface observations; one from the National Oceanographic and Atmospheric Administration, and two variations from the University of Washington (without and with long-term trend adjustment; UW1 and UW2, respectively). To simplify validation, California is divided into 4 regions (Coast, Central Valley, Mountains, and Southern California). Simulations are driven by North American Regional Reanalysis data to minimize large-scale forcing error. Control simulations are conducted with 12-km grid spacing (low resolution) but additional experiments are performed at 2-km (high) resolution to evaluate the robustness of microphysics and cumulus parameterizations to resolution changes. We find that the choice of validation dataset has a significant impact on the model wet bias, and the forecast skill of model precipitation depends strongly on geographic location and storm type. Simulations with right physics options agree better with UW1 observations. In 12-km resolution simulations, the Lin microphysics and the Kain-Fritsch cumulus scheme have better forecast skill in the coastal region while Goddard, Thompson, and Morrison microphysics, and the Grell-Devenyi cumulus scheme perform better in the rest of California. The effect of planetary boundary layer, soil-layer, and radiation physics on model precipitation is weaker than that of microphysics and cumulus processes for short- to medium-range low-resolution simulations. Comparison of 2-km and 12-km resolution runs suggests a need for improvement of cumulus schemes, and supports the use of microphysics schemes in coarser
Fischer, E. V.; Ford, B.; Lassman, W.; Pierce, J. R.; Pfister, G.; Volckens, J.; Magzamen, S.; Gan, R.
Exposure to high concentrations of particulate matter (PM) present during acute pollution events is associated with adverse health effects. While many anthropogenic pollution sources are regulated in the United States, emissions from wildfires are difficult to characterize and control. With wildfire frequency and intensity in the western U.S. projected to increase, it is important to more precisely determine the effect that wildfire emissions have on human health, and whether improved forecasts of these air pollution events can mitigate the health risks associated with wildfires. One of the challenges associated with determining health risks associated with wildfire emissions is that the low spatial resolution of surface monitors means that surface measurements may not be representative of a population's exposure, due to steep concentration gradients. To obtain better estimates of ambient exposure levels for health studies, a chemical transport model (CTM) can be used to simulate the evolution of a wildfire plume as it travels over populated regions downwind. Improving the performance of a CTM would allow the development of a new forecasting framework that could better help decision makers estimate and potentially mitigate future health impacts. We use the Weather Research and Forecasting model with online chemistry (WRF-Chem) to simulate wildfire plume evolution. By varying the model resolution, meteorology reanalysis initial conditions, and biomass burning inventories, we are able to explore the sensitivity of model simulations to these various parameters. Satellite observations are used first to evaluate model skill, and then to constrain the model results. These data are then used to estimate population-level exposure, with the aim of better characterizing the effects that wildfire emissions have on human health.
Rocha, M. J.; Dutra, E.; Vieira, G.; Miranda, P.; Fragoso, M.; Ramos, M.
Permafrost is central to the carbon cycle and to the climate system and is recognized by the WCRP/WMO as a key element of the Earth System in which research efforts should focus. Compared with the Arctic, very little is known about the distribution, thickness, and properties of permafrost in the Antarctic. The main reason for this is the scarce network of permafrost temperature monitoring boreholes, as well as the short number of active layer monitoring sites. According to the IPCC in the last decades regions underlain by permafrost have been reduced in extent, and a warming of the ground has been observed in many areas. This study focus on Livingston and Deception Islands (South Shetlands), located in the Antarctic Peninsula region, one of the Earth's regions where warming has been more significant in the last 50 years. Our work is integrated in a project focusing on studying the influence of climate change on permafrost temperatures, which includes systematic and long-term terrain monitoring and also modeling using mesoscale meteorological models. A significant contribution will be the evaluation of the possibilities for using the mesoscale modeling approaches to other areas of the Antarctic Peninsula where no data exist on permafrost temperatures. Climate variability of the Antarctic Peninsula region was studied using the new reanalysis product from ECMWF Era-Interim and observational data from meteorological monitoring sites and boreholes run by our group. Monthly and annual cycles of near surface climate variables are compared. The modeling approach includes the H-TESSEL (Hydrology Tiled ECMWF Scheme for Surface Exchanges over Land) and the WRF (Weather Research and Forecasting), both forced with ERA-Interim for modeling ground temperatures in the study region. Simulations of both land surface and mesoscale models are compared with the observational data of soil temperatures. Preliminary results are presented and show that our approach can provide a good tool
Varentsov, Mikhail; Verezemskaya, Polina; Baranyuk, Anastasia; Zabolotskikh, Elizaveta; Repina, Irina
Polar lows (PL), high latitude marine mesoscale cyclones, are an enigmatic atmospheric phenomenon, which could result in windstorm damage of shipping and infrastructure in high latitudes. Because of their small spatial scales, short life times and their tendency to develop in remote data sparse regions (Zahn, Strorch, 2008), our knowledge of their behavior and climatology lags behind that of synoptic-scale cyclones. In case of continuing global warming (IPCC, 2013) and prospects of the intensification of economic activity and marine traffic in Arctic region, the problem of relevant simulation of this phenomenon by numerical models of the atmosphere, which could be used for weather and climate prediction, is especially important. The focus of this paper is researching the ability to simulate polar lows by two modern nonhydrostatic mesoscale numerical models, driven by realistic lateral boundary conditions from ERA-Interim reanalysis: regional climate model COSMO-CLM (Böhm et. al., 2009) and weather prediction and research model (WRF). Fields of wind, pressure and cloudiness, simulated by models, were compared with remote sensing data and ground meteorological observations for several cases, when polar lows were observed, in Norwegian, Kara and Laptev seas. Several types of satellite data were used: atmospheric water vapor, cloud liquid water content and surface wind fields were resampled by examining AMSR-E and AMSR-2 microwave radiometer data (MODIS Aqua, GCOM-W1), and wind fields were additionally extracted from QuickSCAT scatterometer. Infrared and visible pictures of cloud cover were obtained from MODIS (Aqua). Completed comparison shown that COSMO-CLM and WRF models could successfully reproduce evolution of polar lows and their most important characteristics such as size and wind speed in short experiments with WRF model and longer (up to half-year) experiments with COSMO-CLM model. Improvement of the quality of polar lows reproduction by these models in
Mizzi, A. P.
A regional hybrid GSI/ETKF data assimilation scheme for the WRF/ARW model Arthur P. Mizzi National Center for Atmospheric Research Boulder, CO 80307 303-497-8987 firstname.lastname@example.org Recently, there has been increased interest in hybrid variational data assimilation due to its ability to improve numerical weather forecast accuracy by incorporating ensemble error information into the data assimilation process (Buehner, 2010a, b; Wang 2010). In this paper, we introduce a GSI/ETKF regional hybrid (Mizzi, 2011). The GSI/ETKF regional hybrid uses a modified version of NOAA/EMC's GSI global hybrid (Wang, 2010) for the ensemble mean analysis and an ETKF (Bishop, et. al., 2001) to update the ensemble perturbations. We tested the GSI/ETKF regional hybrid by applying it to cycling experiments with WRF/ARW on a coarse-resolution domain covering the continental United States (CONUS) that: (i) compared different ETKF schemes, and (ii) reduced and held the number of ETKF observations constant. The results from those experiments showed that: (i) the ETKF scheme requiring the least amount of inflation provided the lowest 12-hr forecast RMSEs (ii) holding the number of ETKF observations constant removed the oscillation in the posterior ETKF ensemble spread noted by Bowler et al., (2008), and (iii) reducing the number of ETKF observations lowered the 12-hr forecast RMSEs. Presently, we are extending this work to a comparison of the GSI/ETKF regional hybrid with a GSI/LETKF regional hybrid based on the LETKF of Ott, et. al., (2004) and a GSI/EnKF regional hybrid based on the DART EnKF (Anderson et. al., 2009). Generally, the GSI/LETKF and GSI/EnKF schemes require less ensemble spread inflation compared to the GSI/ETKF scheme. Consequently, we expect the GSI/LETKF and GSI/EnKF schemes to provide lower 12-hr forecast RMSEs compared to the GSI/ETKF results. Our preliminary results are consistent with that supposition.
Hima Bindu, H.; Venkat Ratnam, M.; Yesubabu, V.; Narayana Rao, T.; Kesarkar, Amit; Naidu, C. V.
Characteristics of gravity waves (GWs) generated due to tropical cyclone (TC) Phailin (2013) that occurred over Bay of Bengal are investigated using the Weather Research and Forecast (WRF) model simulations from its depression stage to weakening stage (10-14 October 2013). Two types of numerical experiments are conducted with and without assimilating conventional and satellite observations using the 3-Dimentional Variational (3DVAR) technique. The results show that the experiment without assimilating any observations (control) has produced a large difference in terms of track and intensity with observed best track estimates of IMD. Similar features are noticed also in winds, reflectivity and independent GPS Radio Occultation (temperature) and radiosonde (temperature and winds) profiles. The experiment with assimilation significantly reduced the observed differences in all the above mentioned parameters. A close match of the assimilated outputs with observations prompted us to use it to identify the TC generated GW characteristics. GW perturbation components are extracted from the three day mean (4-7 October 2013) calm background atmosphere prior to the formation of depression. When compared to the control run, assimilated outputs show a clear increase in all the gravity wave parameters except the amplitudes where control run wave amplitudes are found to be stronger than the assimilated outputs. Fast Fourier transform (FFT) analysis in the time domain revealed dominance of GWs with periods of 2-4 h. Band pass filtered vertical velocity perturbations for these periods showed clear downward phase propagation (0.05-0.07 ms- 1) in the upper troposphere and lower stratosphere (UTLS) at different latitude/longitude positions away from the centre of the TC revealing an upward energy propagation of generated GWs. Interestingly, an increase in GW activity during the landfall of the TC is found. FFT in the vertical domain revealed vertical wavelengths ranging from 3 to 8 km
Sati, A. P.
The continuous population growth and the subsequent economic expansion over centuries have been the primary drivers of land use /land cover (LULC) changes resulting in the environmental changes across the globe. Most of the urban areas being developed today are on the expense of agricultural or barren lands and the changes result from various practices such as deforestation, changing agriculture practices, rapid expansion of urban centers etc.For modeling applications, classification of land use is important and periodic updates of land cover are necessary to capture change due to LULC changes.Updated land cover and land use data derived from satellites offer the possibility of consistent and regularly collected information on LULC. In this study we explore the application of Landsat based LULC classification inWeather Research and Forecasting (WRF) model in predicting the meteorology over Delhi, India. The supervised classification of Landsat 8 imagery over Delhi region is performed which update the urban extent as well as other Land use for the region. WRF model simulations are performed using LULC classification from Landsat data, United States Geological Survey (USGS) and Moderate Resolution Imaging Spectroradiometer (MODIS) for various meteorological parameters. Modifications in LULC showed a significant effect on various surface meteorological parameters such as temperature, humidity, wind circulations and other underlying surface parameters. There is a considerable improvement in the spatial distribution of the surface meteorological parameters with correction in input LULC. The study demonstrates the improved LULC classification from Landsat data than currently in vogue and their potential to improve numerical weather simulations especially for expanding urban areas.The continuous population growth and the subsequent economic expansion over centuries have been the primary drivers of land use /land cover (LULC) changes resulting in the environmental changes
Balan Sobhana, Sandeepan; Nayak, Sashikant; Panchang, Vijay
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
Sharma, Sumit; Chatani, Satoru; Mahtta, Richa; Goel, Anju; Kumar, Atul
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. Sector-
Full Text Available Tropopause folds are one of the mechanisms of stratosphere–troposphere exchange, which can bring ozone rich stratospheric air to low altitudes in the extra-tropical regions. They have been widely studied at northern mid- or high latitudes, but so far almost no studies have been made at mid- or high southern latitudes. The Moveable Atmospheric Radar for Antarctica (MARA, a 54.5 MHz wind-profiler radar, has operated at the Swedish summer station Wasa, Antarctica (73° S, 13.5° W during austral summer seasons from 2007 to 2011 and has observed on several occasions signatures similar to those caused by tropopause folds at comparable Arctic latitudes. Here a case study is presented of one of these events when an ozonesonde successfully sampled the fold. Analysis from European Center for Medium Range Weather Forecasting (ECMWF is used to study the circumstances surrounding the event, and as boundary conditions for a mesoscale simulation using the Weather Research and Forecasting (WRF model. The fold is well resolved by the WRF simulation, and occurs on the poleward side of the polar jet stream. However, MARA resolves fine-scale layering associated with the fold better than the WRF simulation.
Mihalikova, M.; Kirkwood, S.; Arnault, J.; Mikhaylova, D.
Tropopause folds are one of the mechanisms of stratosphere-troposphere exchange, which can bring ozone rich stratospheric air to low altitudes in the extra-tropical regions. They have been widely studied at northern mid- or high latitudes, but so far almost no studies have been made at mid- or high southern latitudes. The Moveable Atmospheric Radar for Antarctica (MARA), a 54.5 MHz wind-profiler radar, has operated at the Swedish summer station Wasa, Antarctica (73° S, 13.5° W) during austral summer seasons from 2007 to 2011 and has observed on several occasions signatures similar to those caused by tropopause folds at comparable Arctic latitudes. Here a case study is presented of one of these events when an ozonesonde successfully sampled the fold. Analysis from European Center for Medium Range Weather Forecasting (ECMWF) is used to study the circumstances surrounding the event, and as boundary conditions for a mesoscale simulation using the Weather Research and Forecasting (WRF) model. The fold is well resolved by the WRF simulation, and occurs on the poleward side of the polar jet stream. However, MARA resolves fine-scale layering associated with the fold better than the WRF simulation.
Rantanen, Mika; Räisänen, Jouni; Lento, Juha; Stepanyuk, Oleg; Räty, Olle; Sinclair, Victoria A.; Järvinen, Heikki
A software package (OZO, Omega-Zwack-Okossi) was developed to diagnose the processes that affect vertical motions and geopotential height tendencies in weather systems simulated by the Weather Research and Forecasting (WRF) model. First, this software solves a generalised omega equation to calculate the vertical motions associated with different physical forcings: vorticity advection, thermal advection, friction, diabatic heating, and an imbalance term between vorticity and temperature tendencies. After this, the corresponding height tendencies are calculated with the Zwack-Okossi tendency equation. The resulting height tendency components thus contain both the direct effect from the forcing itself and the indirect effects (related to the vertical motion induced by the same forcing) of each physical mechanism. This approach has an advantage compared with previous studies with the Zwack-Okossi equation, in which vertical motions were used as an independent forcing but were typically found to compensate the effects of other forcings.The software is currently tailored to use input from WRF simulations with Cartesian geometry. As an illustration, results for an idealised 10-day baroclinic wave simulation are presented. An excellent agreement is found between OZO and the direct WRF output for both the vertical motion and the height tendency fields. The individual vertical motion and height tendency components demonstrate the importance of both adiabatic and diabatic processes for the simulated cyclone. OZO is an open-source tool for both research and education, and the distribution of the software will be supported by the authors.
gochis, David; hooper, Rick; parodi, Antonio; Jha, Shantenu; Yu, Wei; Zaslavsky, Ilya; Ganapati, Dinesh
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.
Mandal, M.; Singh, K. S.; Balaji, M.; Mohapatra, M.
This study examines the performance of the Advanced Research core of Weather Research and Forecasting (ARW-WRF) model in prediction of the Bay of Bengal cyclone `Phailin'. The two-way interactive double-nested model at 27 and 9-km resolutions customized at Indian Institute of Technology Kharagpur (IITKGP) is used to predict the storm on real-time basis and five predictions are made with five different initial conditions. The initial and boundary conditions for the model are derived from the Global Forecasting System (GFS) analysis and forecast respectively. The track of storm is well predicted in all the five forecasts. In particular, the forecast with less initial positional error led to more accurate track and landfall prediction. It is observed that the predicted peak intensity and translation speed of the storm depends strongly on initial intensity error, vertical wind shear and vertical distribution of maximum potential vorticity. The trend of intensification and dissipation of the storm is well predicted by the model in terms of central sea level pressure (CSLP). The intensity in terms of maximum surface wind (MSW) is under-predicted by the model and it is suggested that the MSW estimated from predicted pressure drop may be used as prediction guideline. The storm intensified rapidly during its passage over the high Tropical Cyclone Heat Potential zone and is reasonably well predicted by the model. Though the magnitude of the precipitation is not well predicted, distribution of precipitation is fairly well predicted by the model. The track and intensity of the storm predicted by the customized WRF-ARW is better than that of other NWP models. The landfall (time and position) is also better predicted by the model compared to other NWP models if initialized at cyclonic storm stage. The results indicate that the customized model have good potential for real-time prediction of Bay of Bengal cyclones and encourage further investigation with larger number of cyclones.
Heikkilä, Ulla; Gómez Navarro, Juan Jose; Franke, Jörg; Brönnimann, Stefan; Cattin, Réne
Switzerland has experienced a number of severe precipitation events during the last few decades, such as during the 14-16 November of 2002 or during the 21-22 August of 2005. Both events, and subsequent extreme floods, caused fatalities and severe financial losses, and have been well studied both in terms of atmospheric conditions leading to extreme precipitation, and their consequences [e.g. Hohenegger et al., 2008, Stucki et al., 2012]. These examples highlight the need to better characterise the frequency and severity of flooding in the Alpine area. In a larger framework we will ultimately produce a high-resolution data set covering the entire 20th century to be used for detailed hydrological studies including all atmospheric parameters relevant for flooding events. In a first step, we downscale the aforementioned two events of 2002 and 2005 to assess the model performance regarding precipitation extremes. The complexity of the topography in the Alpine area demands high resolution datasets. To achieve a sufficient detail in resolution we employ the Weather Research and Forecasting regional climate model (WRF). A set of 4 nested domains is used with a 2-km resolution horizontal resolution over Switzerland. The NCAR 20th century reanalysis (20CR) with a horizontal resolution of 2.5° serves as boundary condition [Compo et al., 2011]. First results of the downscaling the 2002 and 2005 extreme precipitation events show that, compared to station observations provided by the Swiss Meteorological Office MeteoSwiss, the model strongly underestimates the strength of these events. This is mainly due to the coarse resolution of the 20CR data, which underestimates the moisture fluxes during these events. We tested driving WRF with the higher-resolved NCEP reanalysis and found a significant improvement in the amount of precipitation of the 2005 event. In a next step we will downscale the precipitation and wind fields during a 6-year period 2002-2007 to investigate and
Zhang, Xuezhen; Xiong, Zhe; Zheng, Jingyun; Ge, Quansheng
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.
Wharton, Sonia [Lawrence Livermore National Lab. (LLNL), Livermore, CA (United States); Simpson, Matthew [Lawrence Livermore National Lab. (LLNL), Livermore, CA (United States); Osuna, Jessica [Lawrence Livermore National Lab. (LLNL), Livermore, CA (United States); Newman, Jennifer [National Renewable Energy Lab. (NREL), Golden, CO (United States); Biraud, Sebastien [Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States)
The Weather Research and Forecasting (WRF) model is used to investigate choice of land surface model (LSM) on the near-surface wind profile, including heights reached by multi-megawatt wind turbines. Simulations of wind profiles and surface energy fluxes were made using five LSMs of varying degrees of sophistication in dealing with soil-plant-atmosphere feedbacks for the U.S. Department of Energy (DOE) Atmospheric Radiation Measurement (ARM) Climate Research Facility’s Southern Great Plains (SGP) Central Facility in Oklahoma. Surface-flux and wind-profile measurements were available for validation. The WRF model was run for three two-week periods during which varying canopy and meteorological conditions existed. The LSMs predicted a wide range of energy-flux and wind-shear magnitudes even during the cool autumn period when we expected less variability. Simulations of energy fluxes varied in accuracy by model sophistication, whereby LSMs with very simple or no soil-plant-atmosphere feedbacks were the least accurate; however, the most complex models did not consistently produce more accurate results. Errors in wind shear also were sensitive to LSM choice and were partially related to the accuracy of energy flux data. The variability of LSM performance was relatively high, suggesting that LSM representation of energy fluxes in the WRF model remains a significant source of uncertainty for simulating wind turbine inflow conditions.
Full Text Available We present simulations of atmospheric CO2 concentrations provided by two modeling systems, run at high spatial resolution: the Eulerian-based Weather Research Forecasting (WRF model and the Lagrangian-based Stochastic Time-Inverted Lagrangian Transport (STILT model, both of which are coupled to a diagnostic biospheric model, the Vegetation Photosynthesis and Respiration Model (VPRM. The consistency of the simulations is assessed with special attention paid to the details of horizontal as well as vertical transport and mixing of CO2 concentrations in the atmosphere. The dependence of model mismatch (Eulerian vs. Lagrangian on models' spatial resolution is further investigated. A case study using airborne measurements during which both models showed large deviations from each other is analyzed in detail as an extreme case. Using aircraft observations and pulse release simulations, we identified differences in the representation of details in the interaction between turbulent mixing and advection through wind shear as the main cause of discrepancies between WRF and STILT transport at a spatial resolution such as 2 and 6 km. Based on observations and inter-model comparisons of atmospheric CO2 concentrations, we show that a refinement of the parameterization of turbulent velocity variance and Lagrangian time-scale in STILT is needed to achieve a better match between the Eulerian and the Lagrangian transport at such a high spatial resolution (e.g. 2 and 6 km. Nevertheless, the inter-model differences in simulated CO2 time series for a tall tower observatory at Ochsenkopf in Germany are about a factor of two smaller than the model-data mismatch and about a factor of three smaller than the mismatch between the current global model simulations and the data. Thus suggests that it is reasonable to use STILT as an adjoint model of WRF atmospheric transport.
Wong, David; Yang, Cheng-en; Mathur, Rohit; Pleim, Jonathan; Fu, Joshua; Wong, Kwai; Gao, Yang
I/O is part of a scientific model and it takes up a significant portion of the simulation. There is no exception for the newly developed WRF-CMAQ two-way coupled model at US EPA. This two-way coupled meteorology and air quality model is composed of the Weather Research and Forecasting (WRF) model and the Community Multiscale Air Quality (CMAQ) model. We are using this two-way model to evaluate how accurate it simulates the effects of aerosol loading on radiative forcing between 1990 and 2010 when there were substantial aerosol emissions such as SO2 and NOx, reduction in North America and Europe. The I/O scheme in the current model does not make use of any parallel file system or parallel I/O approach. In addition the I/O takes about 15% - 28% of the entire simulation. Our novel approach not only utilizes pnetCDF parallel I/O technique but goes one step further to aggregate the data locally, i.e. along column dimension or row dimension in the spatial domain. This approach not only reduces the I/O traffic contention but also aggregated data enhances the I/O efficiency. In terms of I/O time, we have shown this method is about 6 to 10 times faster than the current existing I/O scheme in the model and about 20% - 3 times faster than strict application of pnetCDF. We are currently running the model on a Cray XE6 machine and finding ways to reduce the overall simulation time is crucial to the success to achieve our objective.
J. T. M. Lenaerts
Full Text Available A shallow cumulus over land redistributes heat and moisture in the boundary layer, but is also important on larger scales, because it can trigger severe convection events. Due to its small (100 - 1000 m spatial scale, this feature is defined as a sub-grid process in mesoscale models. The goal of this research is to examine the representation of shallow cumulus clouds in the mesoscale model WRF by reproducing a shallow cumulus situation observed over land. In particular, we focus on the role of the convection parameterisation in the characteristic vertical energy transport in the boundary layer. The analysis focusses on the thermodynamic structure of the boundary layer and on the cloud properties derived from a simple parcel method theory. This numerical experiment is designed to be as close as possible to the Large-Eddy Simulations (LES model intercomparison study of Brown et al. (2002. They concentrated on the representation of shallow cumulus clouds over land in LES, using data from the American Southern Great Plains of 21st June 1997. To imitate the dynamic structure of LES, we have designed a Multiple Single Column version of WRF. Using identical surface forcing and initial thermodynamic profiles, WRF boundary layer structure shows good agreement with the LES results. However, the parcel method indicates that a larger inversion and the absence of a conditionally unstable layer suppress shallow cumulus clouds development by WRF. In addition, WRF does not show any cloud development in terms of cloud liquid water. We show also that a convective parameterisation is necessary to represent the enhanced boundary layer vertical transport by shallow cumulus clouds. Different convective parameterisation schemes are analyzed and compared.
Härer, Stefan; Bernhardt, Matthias; Gutmann, Ethan; Bauer, Hans-Stefan; Schulz, Karsten
Until recently, a large gap existed in the atmospheric downscaling strategies. On the one hand, computationally efficient statistical approaches are widely used, on the other hand, dynamic but CPU-intensive numeric atmospheric models like the weather research and forecast (WRF) model exist. The intermediate complex atmospheric research (ICAR) model developed at NCAR (Boulder, Colorado, USA) addresses this gap by combining the strengths of both approaches: the process-based structure of a dynamic model and its applicability in a changing climate as well as the speed of a parsimonious modelling approach which facilitates the modelling of ensembles and a straightforward way to test new parametrization schemes as well as various input data sources. However, the ICAR model has not been tested in Europe and on slightly undulated terrain yet. This study now evaluates for the first time the ICAR model to WRF model runs in Central Europe comparing a complete year of model results in the mesoscale Attert catchment (Luxembourg). In addition to these modelling results, we also describe the first implementation of ICAR on an Intel Phi architecture and consequently perform speed tests between the Vienna cluster, a standard workstation and the use of an Intel Phi coprocessor. Finally, the study gives an outlook on sensitivity studies using slightly different input data sources.
Yao, Yao; Huang, Jianbin; Luo, Yong; Zhao, Zongci
Sea ice plays an important role in the air-ice-ocean interaction, but it is often represented simply in many regional atmospheric models. The Noah sea ice scheme, which is the only option in the current Weather Research and Forecasting (WRF) model (version 3.6.1), has a problem of energy imbalance due to its simplification in snow processes and lack of ablation and accretion processes in ice. Validated against the Surface Heat Budget of the Arctic Ocean (SHEBA) in situ observations, Noah underestimates the sea ice temperature which can reach -10 °C in winter. Sensitivity tests show that this bias is mainly attributed to the simulation within the ice when a time-dependent ice thickness is specified. Compared with the Noah sea ice model, the high-resolution thermodynamic snow and ice model (HIGHTSI) uses more realistic thermodynamics for snow and ice. Most importantly, HIGHTSI includes the ablation and accretion processes of sea ice and uses an interpolation method which can ensure the heat conservation during its integration. These allow the HIGHTSI to better resolve the energy balance in the sea ice, and the bias in sea ice temperature is reduced considerably. When HIGHTSI is coupled with the WRF model, the simulation of sea ice temperature by the original Polar WRF is greatly improved. Considering the bias with reference to SHEBA observations, WRF-HIGHTSI improves the simulation of surface temperature, 2 m air temperature and surface upward long-wave radiation flux in winter by 6, 5 °C and 20 W m-2, respectively. A discussion on the impact of specifying sea ice thickness in the WRF model is presented. Consistent with previous research, prescribing the sea ice thickness with observational information results in the best simulation among the available methods. If no observational information is available, we present a new method in which the sea ice thickness is initialized from empirical estimation and its further change is predicted by a complex thermodynamic
Kushta, Jonilda; Proestos, Yiannis; Georgiou, George; Christoudias, Theodoros; Lelieveld, Jos
The fully coupled WRF-Chem (Weather Research and Forecasting with Chemistry) model is used to simulate air quality over Cyprus. Cyprus is an island country with complex topography, located in the eastern corner of East Mediterranean region, affected year-long by local, regional and long range transported pollution. An extensive sensitivity analysis of the model performance has been performed over the area of interest with three domains of respective grid spacing of 40, 8 and 2 km. Different configurations have been deployed regarding horizontal resolution, simulation timestep, boundary conditions, NOx emissions and speciation method of emitted NMVOCs (Non Methane Volatile Organic Compounds). The WRF-Chem model simulated hourly concentrations of air pollutants for a month-long period (July 2014) during which measurements are available over 13 stations (4 of which background stations, 1 industrial and 8 urban/traffic stations). The model was initialized with meteorological initial and boundary conditions (ICBC) using NCAR-NCEP's F Global Forecast System output (GFS) at a 1o x1o spatial resolution. The ICBC for the chemical species are derived from the MOZART global model results (2.5o x 2.5o). Both ICBCs datasets are updated every 6 hours. The emission inventory used in the study is the EDGAR-HTAP v2 dataset with a horizontal grid resolution of 0.1o × 0.1o, while an additional dataset with speciated NMVOCs (instead of summed volatile species) is also tested. The diurnal cycle of the atmospheric concentrations of ozone averaged over the island, exhibits a maximum of 114 μg/m3 when the boundary conditions are derived from MOZART and 94 μg/m3 when the boundary conditions are not included (local background and production), suggesting a constant inflow of ozone from long range transport of about 20 μg/m3. The contribution of pollution from regional sources is more pronounced at the western border due to the characteristic summer time north-northeasterly etesian flow
M N Ahasan; M M Alam; S K Debsarma
A severe thunderstorm produced a tornado (F2 on the enhanced Fujita–Pearson scale), which affected the Brahmanbaria district of Bangladesh during 1100–1130 UTC of 22 March, 2013. The tornado consumed 38, injured 388 and caused a huge loss of property. The total length travelled by the tornado was about 12–15 km and about 1728 households were affected. An attempt has been made to simulate this rare event using the Weather Research and Forecasting (WRF) model. The model was run in a single domain at 9 km resolution for a period of 24 hrs, starting at 0000 UTC on 22 March, 2013. The meteorological conditions that led to form this tornado have been analyzed. The model simulated meteorological conditions are compared with that of a ‘no severe thunderstorm observed day’ on 22 March, 2012. Thus, the model also ran in the same domain at same resolution for 24 hrs, starting at 0000 UTC on 22 March, 2012. The model simulated meteorological parameters are consistent with each other, and all are in good agreement with the observation in terms of the region of occurrence of the tornado activity. The model has efficiently captured the common favourable synoptic conditions for the occurrence of severe tornadoes though there are some spatial and temporal biases in the simulation. The wind speed is not in good agreement with the observation as it has shown the strongest wind of only 15–20 ms−1, against the estimated wind speed of about 55 ms−1. The spatial distributions as well as intensity of rainfall are also in good agreement with the observation. The results of these analyses demonstrated the capability of high-resolution WRF model with 3DVar Data Assimilation (DA) techniques in simulation of tornado over Brahmanbaria, Bangladesh.
Gabriel, M. C.; Knightes, C. D.; Cooter, E. J.; Dennis, R. L.
Watershed fate and transport models are widely used within the US Environmental Protection Agency's (USEPA) Office of Research and Development (ORD) as tools to forecast ecosystem services and evaluate future scenarios associated with land use, climate change and emissions regulation. A critical step in applying fate and transport models is understanding model sensitivity and function, particularly as new and innovative methods become available to apply forcing function data, e.g. precipitation data. Currently, multiple precipitation data sources are available for use in watershed modeling, two of which include National Climactic Data Center (NCDC) and Weather Research and Forecasting (WRF) data. As there are clear distinctions in how precipitation is determined for these precipitation sources (gauge vs. model simulated), there can also exist significant differences in precipitation frequency on a site-by-site basis. These differences may translate to large contrasts in nitrogen transport due to the sensitivity of surface biogeochemical processes to precipitation characteristics, namely those influenced by soil moisture content. The objective of this study is to investigate potential differences in the fate and transport of reactive nitrogen for two watersheds in the Neuse Basin, North Carolina, USA, after separately applying NCDC and WRF precipitation data sources into the Soil and Water Assessment Tool (SWAT) watershed model. The spatiotemporal variation of several nitrogen transport processes will be compared, e.g. reactive nitrogen fixation, plant uptake, overland delivery to streams, denitrification. Results from this research will advance exposure science by providing a greater understanding of the operation and function of watershed fate and transport models, which are primary tools used to assess ecosystem exposure.
Case, Jonathan L.; Bell, Jordan R.; LaFontaine, Frank J.; Peters-Lidard, Christa D.
The NASA Short-term Prediction Research and Transition (SPoRT) Center has developed a Greenness Vegetation Fraction (GVF) dataset, which is updated daily using swaths of Normalized Difference Vegetation Index data from the Moderate Resolution Imaging Spectroradiometer (MODIS) data aboard the NASA-EOS Aqua and Terra satellites. NASA SPoRT started generating daily real-time GVF composites at 1-km resolution over the Continental United States beginning 1 June 2010. A companion poster presentation (Bell et al.) primarily focuses on impact results in an offline configuration of the Noah land surface model (LSM) for the 2010 warm season, comparing the SPoRT/MODIS GVF dataset to the current operational monthly climatology GVF available within the National Centers for Environmental Prediction (NCEP) and Weather Research and Forecasting (WRF) models. This paper/presentation primarily focuses on individual case studies of severe weather events to determine the impacts and possible improvements by using the real-time, high-resolution SPoRT-MODIS GVFs in place of the coarser-resolution NCEP climatological GVFs in model simulations. The NASA-Unified WRF (NU-WRF) modeling system is employed to conduct the sensitivity simulations of individual events. The NU-WRF is an integrated modeling system based on the Advanced Research WRF dynamical core that is designed to represents aerosol, cloud, precipitation, and land processes at satellite-resolved scales in a coupled simulation environment. For this experiment, the coupling between the NASA Land Information System (LIS) and the WRF model is utilized to measure the impacts of the daily SPoRT/MODIS versus the monthly NCEP climatology GVFs. First, a spin-up run of the LIS is integrated for two years using the Noah LSM to ensure that the land surface fields reach an equilibrium state on the 4-km grid mesh used. Next, the spin-up LIS is run in two separate modes beginning on 1 June 2010, one continuing with the climatology GVFs while the
Chiswell, S.; Buckley, R.
During the year 2008, the United States National Weather Service (NWS) completed an eight fold increase in sampling capability for weather radars to 250 m resolution. This increase is expected to improve warning lead times by detecting small scale features sooner with increased reliability; however, current NWS operational model domains utilize grid spacing an order of magnitude larger than the radar data resolution, and therefore the added resolution of radar data is not fully exploited. The assimilation of radar reflectivity and velocity data into high resolution numerical weather model forecasts where grid spacing is comparable to the radar data resolution was investigated under a Laboratory Directed Research and Development (LDRD) 'quick hit' grant to determine the impact of improved data resolution on model predictions with specific initial proof of concept application to daily Savannah River Site operations and emergency response. Development of software to process NWS radar reflectivity and radial velocity data was undertaken for assimilation of observations into numerical models. Data values within the radar data volume undergo automated quality control (QC) analysis routines developed in support of this project to eliminate empty/missing data points, decrease anomalous propagation values, and determine error thresholds by utilizing the calculated variances among data values. The Weather Research and Forecasting model (WRF) three dimensional variational data assimilation package (WRF-3DVAR) was used to incorporate the QC'ed radar data into input and boundary conditions. The lack of observational data in the vicinity of SRS available to NWS operational models signifies an important data void where radar observations can provide significant input. These observations greatly enhance the knowledge of storm structures and the environmental conditions which influence their development. As the increase in computational power and availability has
Yang, Jiachuan; Wang, Zhi-Hua; Chen, Fei; Miao, Shiguang; Tewari, Mukul; Voogt, James A.; Myint, Soe
Urbanization modifies surface energy and water budgets, and has significant impacts on local and regional hydroclimate. In recent decades, a number of urban canopy models have been developed and implemented into the Weather Research and Forecasting (WRF) model to capture urban land-surface processes. Most of these models are inadequate due to the lack of realistic representation of urban hydrological processes. Here, we implement physically-based parametrizations of urban hydrological processes into the single layer urban canopy model in the WRF model. The new single-layer urban canopy model features the integration of, (1) anthropogenic latent heat, (2) urban irrigation, (3) evaporation from paved surfaces, and (4) the urban oasis effect. The new WRF-urban modelling system is evaluated against field measurements for four different cities; results show that the model performance is substantially improved as compared to the current schemes, especially for latent heat flux. In particular, to evaluate the performance of green roofs as an urban heat island mitigation strategy, we integrate in the urban canopy model a multilayer green roof system, enabled by the physical urban hydrological schemes. Simulations show that green roofs are capable of reducing surface temperature and sensible heat flux as well as enhancing building energy efficiency.
Kumar, Prashant; Gopalan, Kaushik; Shukla, Bipasha Paul; Shyam, Abhineet
Specifying physically consistent and accurate initial conditions is one of the major challenges of numerical weather prediction (NWP) models. In this study, ground-based global positioning system (GPS) integrated water vapor (IWV) measurements available from the International Global Navigation Satellite Systems (GNSS) Service (IGS) station in Bangalore, India, are used to assess the impact of GPS data on NWP model forecasts over southern India. Two experiments are performed with and without assimilation of GPS-retrieved IWV observations during the Indian winter monsoon period (November-December, 2012) using a four-dimensional variational (4D-Var) data assimilation method. Assimilation of GPS data improved the model IWV analysis as well as the subsequent forecasts. There is a positive impact of ˜10 % over Bangalore and nearby regions. The Weather Research and Forecasting (WRF) model-predicted 24-h surface temperature forecasts have also improved when compared with observations. Small but significant improvements were found in the rainfall forecasts compared to control experiments.
Zavodsky, Bradley; Case, Jonathan L.; Gotway, John H.; White, Kristopher; Medlin, Jeffrey; Wood, Lance; Radell, Dave
Local modeling with a customized configuration is conducted at National Weather Service (NWS) Weather Forecast Offices (WFOs) to produce high-resolution numerical forecasts that can better simulate local weather phenomena and complement larger scale global and regional models. The advent of the Environmental Modeling System (EMS), which provides a pre-compiled version of the Weather Research and Forecasting (WRF) model and wrapper Perl scripts, has enabled forecasters to easily configure and execute the WRF model on local workstations. NWS WFOs often use EMS output to help in forecasting highly localized, mesoscale features such as convective initiation, the timing and inland extent of lake effect snow bands, lake and sea breezes, and topographically-modified winds. However, quantitatively evaluating model performance to determine errors and biases still proves to be one of the challenges in running a local model. Developed at the National Center for Atmospheric Research (NCAR), the Model Evaluation Tools (MET) verification software makes performing these types of quantitative analyses easier, but operational forecasters do not generally have time to familiarize themselves with navigating the sometimes complex configurations associated with the MET tools. To assist forecasters in running a subset of MET programs and capabilities, the Short-term Prediction Research and Transition (SPoRT) Center has developed and transitioned a set of dynamic, easily configurable Perl scripts to collaborating NWS WFOs. The objective of these scripts is to provide SPoRT collaborating partners in the NWS with the ability to evaluate the skill of their local EMS model runs in near real time with little prior knowledge of the MET package. The ultimate goal is to make these verification scripts available to the broader NWS community in a future version of the EMS software. This paper provides an overview of the SPoRT MET scripts, instructions for how the scripts are run, and example use
Du, Tien Duc; Ngo-Duc, Thanh; Kieu, Chanh
This study presents an approach to assimilate tropical cyclone (TC) real-time reports and the University of Wisconsin-Cooperative Institute for Meteorological Satellite Studies (CIMSS) Atmospheric Motion Vectors (AMV) data into the Weather Research and Forecasting (WRF) model for TC forecast applications. Unlike current methods in which TC real-time reports are used to either generate a bogus vortex or spin up a model initial vortex, the proposed approach ingests the TC real-time reports through blending a dynamically consistent synthetic vortex structure with the CIMSS-AMV data. The blended dataset is then assimilated into the WRF initial condition, using the local ensemble transform Kalman filter (LETKF) algorithm. Retrospective experiments for a number of TC cases in the northwestern Pacific basin during 2013-2014 demonstrate that this approach could effectively increase both the TC circulation and enhance the large-scale environment that the TCs are embedded in. Further evaluation of track and intensity forecast errors shows that track forecasts benefit more from improvement in the large-scale flow at 4-5-day lead times, whereas the intensity improvement is minimal. While the difference between the track and intensity improvement could be due to a specific model configuration, this result appears to be consistent with the recent reports of insignificant impacts of inner core data assimilation in operational TC models at the long range of 4-5 days. The new approach will be most beneficial for future regional TC models that are directly initialized from very high-resolution global models whose storm initial locations are sufficiently accurate at the initial analysis that there is no need to carry out any artificial vortex removal or filtering steps.
Pereira, E. B.; Lima, F. J. L.; Martins, F. R.
Solar energy is referred to as variable generation sources because their electricity production varies based on the availability of sun irradiance. To accommodate this variability, electricity grid operators use a variety of tools to maintain a reliable electricity supply, one of them is to forecast solar irradiation, and to adjust other electricity sources as needed. This work reports an approach to forecast solar irradiation in the Brazilian Northeastern region (NEB) by using statistically post-processing data from mesoscale model outputs. The method assimilates the diversity of climate characteristics occurring in the region presenting the largest solar energy potentials in Brazil. Untreated solar irradiance forecasts for 24h in advance were obtained using the WRF model runs. Cluster analysis technique was employed to find out areas presenting similar climate characteristics and to reduce uncertainties. Comparison analysis between WRF model outputs and site-specific measured data were performed to evaluate the model skill in forecasting the surface solar irradiation. After that, post-processing of WRF outputs using artificial neural networks (ANNs) and multiple regression methods refined the short-term solar irradiation forecasts. A set of pre-selected variables of the WRF model outputs representing the forecasted atmospheric conditions were used as predictors by the ANNs. Several predictors were tested in the adjustment and simulation of the ANNs. We found the best ANNs architecture and a group of 10 predictors, with which more in-depth analyzes were carried out, including performance evaluation for fall and spring of 2011 (rainy and dry season in NEB). The site-specific measured solar radiation data came from 110 stations distributed throughout the NEB. Data for the rainy season were acquired from March to May, and for the dry season from September to November. We concluded that the untreated numerical forecasts of solar irradiation provided by WRF exhibited a
Anggoro, Adityo Mega; Putra, Agie Wandala; Hutasoit, Budi Saritua
Indonesia is one of the countries known as a one of the world lungs because it has a large forest and varied species. Besides that Indonesia has frequently hit by wildfires a year, one in 2015 yesterday which was hotly discussed because of the impact of forest fires that disrupt transport activity for flights resulting from interruption of smoke from fires. Therefore, it is important to be able to model the behavior of forest fires to disaster mitigation. In this study simulated forest fires in the region of South Sumatra on September 23, 2015 by the coordinates of fires 3,17°S and 106,03°E, this information is obtained from observation satellite imagery LANDSAT8 and hotspot distribution information from LAPAN. WRF-Fire is a combination model of Weather Research and Forecasting (WRF) with dynamic ARW core with fire semi-empirical models, based on the level set method. Methods of data analysis using descriptive analysis, comparative and spatial. The results showed that the distribution pattern of the fire resulting models have similarities with observation, the fire along with the smoke moving toward the northwest, then from the simulation results of surface winds and the invasion of fire has a correlation value of 0.62. WRF-Fire models able to simulate the extent of wildland fire even though it has few results overestimate is 1.725 ha and observations is 1.709 ha, this shows that the WRF-Fire models able be used to help mitigate the catastrophic wildland fire in Indonesia.
Tateo, Andrea; Marcello Miglietta, Mario; Fedele, Francesca; Menegotto, Micaela; Monaco, Alfonso; Bellotti, Roberto
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
Bartolomeu, S.; Carvalho, M. J.; Marta-Almeida, M.; Melo-Gonçalves, P.; Rocha, A.
Spatial and temporal distributions of the trends of extreme precipitation indices were analysed between 1986 and 2005, over the Iberian Peninsula (IP). The knowledge of the patterns of extreme precipitation is important for impacts assessment, development of adaptation and mitigation strategies. As such, there is a growing need for a more detailed knowledge of precipitation climate change. This analysis was performed for Portuguese and Spanish observational datasets and results performed by the Weather Research and Forecast (WRF) model forced by the ERA-Interim reanalysis. Extreme precipitation indices recommended by the Expert Team for Climate Change Detection Monitoring and Indices were computed, by year and season. Then, annual and seasonal trends of the indices were estimated by Theil-Sen method and their significance was tested by the Mann-Kendal test. Additionally, a second simulation forced by the Max Planck Institute Earth System Model (MPI-ESM), was considered. This second modelling configuration was created in order to assess its performance when simulating extremes of precipitation. The annual trends estimated for the 1986-2005, from the observational datasets and from the ERA-driven simulation reveal: 1) negative statistically significant trends of the CWD index in the Galicia and in the centre of the IP; 2) positive statistically significant trends of the CDD index over the south of the IP and negative statistically significant trends in Galicia, north and centre of Portugal; 3) positive statistically significant trends of the R75p index in some regions of the north of the IP; 4) positive statistically significant trends in the R95pTOT index in the Central Mountains Chain, Leon Mountains and in the north of Portugal. Seasonally, negative statistically significant trends of the CWD index were found in Galicia, in winter and in the south of the IP, in summer. Positive statistically significant trends of the CWD index were identified in the Leon Mountains
Gochis, D. J.; Cosgrove, B.; Yu, W.; Clark, E. P.; Yates, D. N.; Dugger, A. L.; McCreight, J. L.; Pan, L.; Zhang, Y.; rafeei-Nasab, A.; Karsten, L. R.; Cline, D. W.; Sampson, K. M.; Newman, A. J.; Wood, A.; Win-Gildenmeister, M.
Operational flood, flash flood and water supply forecasting is typically conducted using a host of different observational and modeling tools that range widely in process complexity, spatial resolution andobservational data sources. While such tailored approaches can provide significant skill in specific water forecasting applications, the lack of a more coordinated general approach can result in inconsistency between various forecast products and can inhibit transfer of information, methodologies between forecast systems. With the aim of improving the timeliness, consistency and spatial fidelity hydrologic prediction products, the U.S. National Weather Service has initiated an effort to provide street-level, water prediction services for the nation. This effort seeks to incorporate advances in hydrometeorological observing capabilities, new hydrologic data assimilation methodologies, improvements in hydrographic and geospatial information and advances in the ulitizion of high performance computers for process-based hydrologic modeling. This talk will summarize the proposed Initial Operating Capability (IOC) for national water prediction using the community WRF-Hydro modeling system, scheduled for operational execution during late spring of 2016. Four different configurations of the WRF-Hydro system are planned including an Analysis and Data Assimilation configuration, Short Range (0-2 day) and Medium Range (0-10 day) deterministic configurations and a Long Range (0-30 day) enesmble configuration. Streamflow analyses and forecasts from each model configurations will be produced on 2.7 million river reaches of the NHDPlusv2 hydrographic dataset. This presentation summarizes results from a number of different model development and benchmarking activities conducted as part of the IOC effort. Results from prototype real-time forecasting activities conducted during the 2015 National Flood Interoperability Experiment (NFIE) will be presented as will retrospective
Pattanayak, Sujata; Mohanty, U C; Osuri, Krishna K
The present study is carried out to investigate the performance of different cumulus convection, planetary boundary layer, land surface processes, and microphysics parameterization schemes in the simulation of a very severe cyclonic storm (VSCS) Nargis (2008), developed in the central Bay of Bengal on 27 April 2008. For this purpose, the nonhydrostatic mesoscale model (NMM) dynamic core of weather research and forecasting (WRF) system is used. Model-simulated track positions and intensity in terms of minimum central mean sea level pressure (MSLP), maximum surface wind (10 m), and precipitation are verified with observations as provided by the India Meteorological Department (IMD) and Tropical Rainfall Measurement Mission (TRMM). The estimated optimum combination is reinvestigated with six different initial conditions of the same case to have better conclusion on the performance of WRF-NMM. A few more diagnostic fields like vertical velocity, vorticity, and heat fluxes are also evaluated. The results indicate that cumulus convection play an important role in the movement of the cyclone, and PBL has a crucial role in the intensification of the storm. The combination of Simplified Arakawa Schubert (SAS) convection, Yonsei University (YSU) PBL, NMM land surface, and Ferrier microphysics parameterization schemes in WRF-NMM give better track and intensity forecast with minimum vector displacement error.
Soltanzadeh, Iman; Bonnardot, Valérie; Sturman, Andrew; Quénol, Hervé; Zawar-Reza, Peyman
Global warming has implications for thermal stress for grapevines during ripening, so that wine producers need to adapt their viticultural practices to ensure optimum physiological response to environmental conditions in order to maintain wine quality. The aim of this paper is to assess the ability of the Weather Research and Forecasting (WRF) model to accurately represent atmospheric processes at high resolution (500 m) during two events during the grapevine ripening period in the Stellenbosch Wine of Origin district of South Africa. Two case studies were selected to identify areas of potentially high daytime heat stress when grapevine photosynthesis and grape composition were expected to be affected. The results of high-resolution atmospheric model simulations were compared to observations obtained from an automatic weather station (AWS) network in the vineyard region. Statistical analysis was performed to assess the ability of the WRF model to reproduce spatial and temporal variations of meteorological parameters at 500-m resolution. The model represented the spatial and temporal variation of meteorological variables very well, with an average model air temperature bias of 0.1 °C, while that for relative humidity was -5.0 % and that for wind speed 0.6 m s-1. Variation in model performance varied between AWS and with time of day, as WRF was not always able to accurately represent effects of nocturnal cooling within the complex terrain. Variations in performance between the two case studies resulted from effects of atmospheric boundary layer processes in complex terrain under the influence of the different synoptic conditions prevailing during the two periods.
Soltanzadeh, Iman; Bonnardot, Valérie; Sturman, Andrew; Quénol, Hervé; Zawar-Reza, Peyman
Global warming has implications for thermal stress for grapevines during ripening, so that wine producers need to adapt their viticultural practices to ensure optimum physiological response to environmental conditions in order to maintain wine quality. The aim of this paper is to assess the ability of the Weather Research and Forecasting (WRF) model to accurately represent atmospheric processes at high resolution (500 m) during two events during the grapevine ripening period in the Stellenbosch Wine of Origin district of South Africa. Two case studies were selected to identify areas of potentially high daytime heat stress when grapevine photosynthesis and grape composition were expected to be affected. The results of high-resolution atmospheric model simulations were compared to observations obtained from an automatic weather station (AWS) network in the vineyard region. Statistical analysis was performed to assess the ability of the WRF model to reproduce spatial and temporal variations of meteorological parameters at 500-m resolution. The model represented the spatial and temporal variation of meteorological variables very well, with an average model air temperature bias of 0.1 °C, while that for relative humidity was -5.0 % and that for wind speed 0.6 m s-1. Variation in model performance varied between AWS and with time of day, as WRF was not always able to accurately represent effects of nocturnal cooling within the complex terrain. Variations in performance between the two case studies resulted from effects of atmospheric boundary layer processes in complex terrain under the influence of the different synoptic conditions prevailing during the two periods.
Full Text Available This work discusses the sources of model biases in reconstructing the Planetary Boundary Layer (PBL height among five commonly used PBL parameterizations. The Weather Research and Forecasting (WRF Model was applied over the critical area of Northern Italy with 5 km of horizontal resolution, and compared against a wide set of experimental data for February 2008. Three non-local closure PBL schemes (Asymmetrical Convective Model version 2, ACM2; Medium Range Forecast, MRF; Yonsei University, YSU and two local closure parameterizations (Mellor Yamada Janjic, MYJ; University of Washington Moist Turbulence, UW were selected for the analysis. Vertical profiles of aerosol number concentrations and Lidar backscatter profiles were collected in the metropolitan area of Milan in order to derive the PBL hourly evolution. Moreover, radio-soundings of Milano Linate airport as well as surface temperature, mixing ratio and wind speed of several meteorological stations were considered too. Results show that all five parameterizations produce similar performances in terms of temperature, mixing ratio and wind speed in the city of Milan, implying some systematic errors in all simulations. However, UW and ACM2 use the same local closure during nighttime conditions, allowing smaller mean biases (MB of temperature (ACM2 MB = 0.606 K, UW MB = 0.209 K, and wind speed (ACM2 MB = 0.699 m s−1, UW MB = 0.918 m s−1. All schemes have the same variations of the diurnal PBL height, since over predictions of temperature and wind speed are found to cause a general overestimation of mixing during its development in winter. In particular, temperature estimates seem to impact the early evolution of the PBL height, while entrainment fluxes parameterizations have major influence on the afternoon development. MRF, MYJ and ACM2 use the same approach in reconstructing the entrainment process, producing the largest overestimations of PBL height (MB ranges from 85.51–179.10 m. On
Balzarini, A.; Angelini, F.; Ferrero, L.; Moscatelli, M.; Perrone, M. G.; Pirovano, G.; Riva, G. M.; Sangiorgi, G.; Toppetti, A. M.; Gobbi, G. P.; Bolzacchini, E.
This work discusses the sources of model biases in reconstructing the Planetary Boundary Layer (PBL) height among five commonly used PBL parameterizations. The Weather Research and Forecasting (WRF) Model was applied over the critical area of Northern Italy with 5 km of horizontal resolution, and compared against a wide set of experimental data for February 2008. Three non-local closure PBL schemes (Asymmetrical Convective Model version 2, ACM2; Medium Range Forecast, MRF; Yonsei University, YSU) and two local closure parameterizations (Mellor Yamada Janjic, MYJ; University of Washington Moist Turbulence, UW) were selected for the analysis. Vertical profiles of aerosol number concentrations and Lidar backscatter profiles were collected in the metropolitan area of Milan in order to derive the PBL hourly evolution. Moreover, radio-soundings of Milano Linate airport as well as surface temperature, mixing ratio and wind speed of several meteorological stations were considered too. Results show that all five parameterizations produce similar performances in terms of temperature, mixing ratio and wind speed in the city of Milan, implying some systematic errors in all simulations. However, UW and ACM2 use the same local closure during nighttime conditions, allowing smaller mean biases (MB) of temperature (ACM2 MB = 0.606 K, UW MB = 0.209 K), and wind speed (ACM2 MB = 0.699 m s-1, UW MB = 0.918 m s-1). All schemes have the same variations of the diurnal PBL height, since over predictions of temperature and wind speed are found to cause a general overestimation of mixing during its development in winter. In particular, temperature estimates seem to impact the early evolution of the PBL height, while entrainment fluxes parameterizations have major influence on the afternoon development. MRF, MYJ and ACM2 use the same approach in reconstructing the entrainment process, producing the largest overestimations of PBL height (MB ranges from 85.51-179.10 m). On the contrary, the
Watson, Leela R.; Bauman, William H., III; Hoeth, Brian
This abstract describes work that will be done by the Applied Meteorology Unit (AMU) in assessing the success of different model configurations in predicting "wind cycling" cases at Edwards Air Force Base, CA (EAFB), in which the wind speeds and directions oscillate among towers near the EAFB runway. The Weather Research and Forecasting (WRF) model allows users to choose among two dynamical cores - the Advanced Research WRF (ARW) and the Non-hydrostatic Mesoscale Model (NMM). There are also data assimilation analysis packages available for the initialization of the WRF model - the Local Analysis and Prediction System (LAPS) and the Advanced Regional Prediction System (ARPS) Data Analysis System (ADAS). Having a series of initialization options and WRF cores, as well as many options within each core, creates challenges for local forecasters, such as determining which configuration options are best to address specific forecast concerns. The goal of this project is to assess the different configurations available and determine which configuration will best predict surface wind speed and direction at EAFB.
Banks, Robert F.; Tiana-Alsina, Jordi; Baldasano, José María; Rocadenbosch, Francesc; Papayannis, Alexandros; Solomos, Stavros; Tzanis, Chris G.
Air quality forecast systems need reliable and accurate representations of the planetary boundary layer (PBL) to perform well. An important question is how accurately numerical weather prediction models can reproduce conditions in diverse synoptic flow types. Here, observations from the summer 2014 HygrA-CD (Hygroscopic Aerosols to Cloud Droplets) experimental campaign are used to validate simulations from the Weather Research and Forecasting (WRF) model over the complex, urban terrain of the Greater Athens Area. Three typical atmospheric flow types were identified during the 39-day campaign based on 2-day backward trajectories: Continental, Etesians, and Saharan. It is shown that the numerical model simulations differ dramatically depending on the PBL scheme, atmospheric dynamics, and meteorological parameter (e.g., 2-m air temperature). Eight PBL schemes from WRF version 3.4 are tested with daily simulations on an inner domain at 1-km grid spacing. Near-surface observations of 2-m air temperature and relative humidity and 10-m wind speed are collected from multiple meteorological stations. Estimates of the PBL height come from measurements using a multiwavelength Raman lidar, with an adaptive extended Kalman filter technique. Vertical profiles of atmospheric variables are obtained from radiosonde launches, along with PBL heights calculated using bulk Richardson number. Daytime maximum PBL heights ranged from 2.57 km during Etesian flows, to as low as 0.37 km during Saharan flows. The largest differences between model and observations are found with simulated PBL height during Saharan synoptic flows. During the daytime, campaign-averaged near-surface variables show WRF tended to have a cool, moist bias with higher simulated wind speeds than the observations, especially near the coast. It is determined that non-local PBL schemes give the most agreeable solutions when compared with observations.
Qian, Y.; Yang, B.; Lin, G.; Leung, R.; Zhang, Y.
The current tuning process of parameters in global climate models is often performed subjectively or treated as an optimization procedure to minimize model biases based on observations. The latter approach may provide more plausible values for a set of tunable parameters to approximate the observed climate, the system could be forced to an unrealistic physical state or improper balance of budgets through compensating errors over different regions of the globe. In this study, the Weather Research and Forecasting (WRF) model was used to provide a more flexible framework to investigate a number of issues related uncertainty quantification (UQ) and parameter tuning. The WRF model was constrained by reanalysis of data over the Southern Great Plains (SGP), where abundant observational data from various sources was available for calibration of the input parameters and validation of the model results. Focusing on five key input parameters in the new Kain-Fritsch (KF) convective parameterization scheme used in WRF as an example, the purpose of this study was to explore the utility of high-resolution observations for improving simulations of regional patterns and evaluate the transferability of UQ and parameter tuning across physical processes, spatial scales, and climatic regimes, which have important implications to UQ and parameter tuning in global and regional models. A stochastic important-sampling algorithm, Multiple Very Fast Simulated Annealing (MVFSA) was employed to efficiently sample the input parameters in the KF scheme based on a skill score so that the algorithm progressively moved toward regions of the parameter space that minimize model errors. The results based on the WRF simulations with 25-km grid spacing over the SGP showed that the precipitation bias in the model could be significantly reduced when five optimal parameters identified by the MVFSA algorithm were used. The model performance was found to be sensitive to downdraft- and entrainment
Yucel, I.; Onen, A.; Yilmaz, K. K.; Gochis, D. J.
A fully-distributed, multi-physics, multi-scale hydrologic and hydraulic modeling system, WRF-Hydro, is used to assess the potential for skillful flood forecasting based on precipitation inputs derived from the Weather Research and Forecasting (WRF) model and the EUMETSAT Multi-sensor Precipitation Estimates (MPEs). Similar to past studies it was found that WRF model precipitation forecast errors related to model initial conditions are reduced when the three dimensional atmospheric data assimilation (3DVAR) scheme in the WRF model simulations is used. A comparative evaluation of the impact of MPE versus WRF precipitation estimates, both with and without data assimilation, in driving WRF-Hydro simulated streamflow is then made. The ten rainfall-runoff events that occurred in the Black Sea Region were used for testing and evaluation. With the availability of streamflow data across rainfall-runoff events, the calibration is only performed on the Bartin sub-basin using two events and the calibrated parameters are then transferred to other neighboring three ungauged sub-basins in the study area. The rest of the events from all sub-basins are then used to evaluate the performance of the WRF-Hydro system with the calibrated parameters. Following model calibration, the WRF-Hydro system was capable of skillfully reproducing observed flood hydrographs in terms of the volume of the runoff produced and the overall shape of the hydrograph. Streamflow simulation skill was significantly improved for those WRF model simulations where storm precipitation was accurately depicted with respect to timing, location and amount. Accurate streamflow simulations were more evident in WRF model simulations where the 3DVAR scheme was used compared to when it was not used. Because of substantial dry bias feature of MPE, as compared with surface rain gauges, streamflow derived using this precipitation product is in general very poor. Overall, root mean squared errors for runoff were reduced by
Fallmann, Joachim; Suppan, Peter; Emeis, Stefan
Cities are warmer than their surroundings (called urban heat island, UHI). UHI influence urban atmospheric circulation, air quality, and ecological conditions. UHI leads to upward motion and compensating near-surface inflow from the surroundings which import rural trace substances. Chemical and aerosol formation processes are modified due to increased temperature, reduced humidity and modified urban-rural trace substance mixtures. UHIs produce enhanced heat stress for humans, animals and plants, less water availability and modified air quality. Growing cities and Climate Change will aggravate the UHI and its effects and urgently require adaptation and mitigation strategies. Prior to this, UHI properties must be assessed by surface observations, ground- and satellite-based vertical remote sensing and numerical modelling. The Weather Research and Forecasting Model (WRF) is an instrument to simulate and assess this phenomenon based on boundary conditions from observations and global climate models. Three urbanization schemes are available with WRF, which are tested during this study for different weather conditions in central Europe and will be enhanced if necessary. High resolution land use maps are used for this modeling effort. In situ measurements and Landsat thermal images are employed for validation of the results. The study will focus on the city of Stuttgart located in the south western part of Germany that is situated in a caldera-like orographic feature. This municipality has a long tradition in urban climate research and thus is well equipped with climatologic measurement stations. By using Geographical Information Systems (GIS), it is possible to simulate several scenarios for different surface properties. By increasing the albedo of roof and wall layers in the urban canopy model or by replacing urban land use by natural vegetation, simple urban planning strategies can be tested and the effect on urban heat island formation and air quality can be
Nelson, Matthew A.; Brown, Michael J.; Halverson, Scot A.; Bieringer, Paul E.; Annunzio, Andrew; Bieberbach, George; Meech, Scott
The Quick Urban & Industrial Complex (QUIC) atmospheric transport, and dispersion modelling, system was evaluated against the Joint Urban 2003 tracer-gas measurements. This was done using the wind and turbulence fields computed by the Weather Research and Forecasting (WRF) model. We compare the simulated and observed plume transport when using WRF-model-simulated wind fields, and local on-site wind measurements. Degradation of the WRF-model-based plume simulations was cased by errors in the simulated wind direction, and limitations in reproducing the small-scale wind-field variability. We explore two methods for importing turbulence from the WRF model simulations into the QUIC system. The first method uses parametrized turbulence profiles computed from WRF-model-computed boundary-layer similarity parameters; and the second method directly imports turbulent kinetic energy from the WRF model. Using the WRF model's Mellor-Yamada-Janjic boundary-layer scheme, the parametrized turbulence profiles and the direct import of turbulent kinetic energy were found to overpredict and underpredict the observed turbulence quantities, respectively. Near-source building effects were found to propagate several km downwind. These building effects and the temporal/spatial variations in the observed wind field were often found to have a stronger influence over the lateral and vertical plume spread than the intensity of turbulence. Correcting the WRF model wind directions using a single observational location improved the performance of the WRF-model-based simulations, but using the spatially-varying flow fields generated from multiple observation profiles generally provided the best performance.
Full Text Available Wind speed forecasting is difficult not only because of the influence of atmospheric dynamics but also for the impossibility of providing an accurate prediction with traditional statistical forecasting models that work by discovering an inner relationship within historical records. This paper develops a self-adaptive (SA auto-regressive integrated moving average with exogenous variables (ARIMAX model that is optimized very-short-term by the chaotic particle swarm optimization (CPSO algorithm, known as the SA-ARIMA-CPSO approach, for wind speed prediction. The ARIMAX model chooses the wind speed result from the Weather Research and Forecasting (WRF simulation as an exogenous input variable. Further, an SA strategy is applied to the ARIMAX process. When new information is available, the model process can be updated adaptively with parameters optimized by the CPSO algorithm. The proposed SA-ARIMA-CPSO approach enables the forecasting process to update training information and model parameters intelligently and adaptively. As tested using the 15-min wind speed data collected from a wind farm in Northern China, the improved method has the best performance compared with several other models.
Kirova-Galabova, Hristina; Batchvarova, Ekaterina; Gryning, Sven-Erik
We examined the features of the Arctic boundary layer during winter (land and sea covered by snow/ice) and summer (sea covered by sea ice) using Weather Research and Forecasting (WRF) model version 3.4.1 and radiosounding data collected at Station Nord (81.65N, 16.65W) . The dataset consist...
Li, X.; Tao, W.; Shi, J. J.; Matsui, T.
A snow band formed over Japan Sea during the “Winter MCSs Observation over the Japan Sea -2001 (WMO-01)” on January 14, 2001 was simulated using triple-nested WRF model. The simulation captured the formation and propagation of the intense snow band over a 24-hour period. Comparisons between the WRF simulation and the surface C-band radar observation show good agreements on snow band structure and cloud streaks formed at its down wind shear side. In order to study the aerosol impact on snow fall, as well as details in microphysics in the snow band, a 12-hour simulation from the inner domain of the WRF model are used as forcing to drive a 2-D cloud-resolving model, the Goddard Cumulus Ensemble (GCE) model, with an explicit spectral bin microphysical scheme. The WRF simulated surface fluxes are also applied in the cloud-resolving model. The GCE model simulated ice- and water- phase hydrometeors are compared with the WRF simulation, as well as with airplane and satellite observations using multi-sensor satellite simulator. This work shows the potential of combining simulations of both realistic storm dynamics and detailed microphysics to study snowfall events. Accurate hydrometeor profiles in a 3-D cloud system are vital in remote sensing retrievals, especially for space-borne instruments. While WRF model can provide more realistic, 3-D spatial and temporal variations of the snow band, simplified bulk microphysical scheme in WRF are not very informative in detailed size distributions of various hydrometeor species, especially in ice-phase. On the other hand, GCE model with detailed microphysics scheme has severe computational limitations. The purpose of this study is to bridge these two approaches and obtain meaningful statistics of hydrometeors’ vertical profiles, as well as mechanism of aerosol impact on a snow band formation.
Subin, Z.M.; Riley, W.J.; Kueppers, L.M.; Jin, J.; Christianson, D.S.; Torn, M.S.
A regional atmosphere model [Weather Research and Forecasting model version 3 (WRF3)] and a land surface model [Community Land Model, version 3.5 (CLM3.5)] were coupled to study the interactions between the atmosphere and possible future California land-cover changes. The impact was evaluated on California's climate of changes in natural vegetation under climate change and of intentional afforestation. The ability of WRF3 to simulate California's climate was assessed by comparing simulations by WRF3-CLM3.5 and WRF3-Noah to observations from 1982 to 1991. Using WRF3-CLM3.5, the authors performed six 13-yr experiments using historical and future large-scale climate boundary conditions from the Geophysical Fluid Dynamics Laboratory Climate Model version 2.1 (GFDL CM2.1). The land-cover scenarios included historical and future natural vegetation from the Mapped Atmosphere-Plant-Soil System-Century 1 (MC1) dynamic vegetation model, in addition to a future 8-million-ha California afforestation scenario. Natural vegetation changes alone caused summer daily-mean 2-m air temperature changes of -0.7 to +1 C in regions without persistent snow cover, depending on the location and the type of vegetation change. Vegetation temperature changes were much larger than the 2-m air temperature changes because of the finescale spatial heterogeneity of the imposed vegetation change. Up to 30% of the magnitude of the summer daily-mean 2-m air temperature increase and 70% of the magnitude of the 1600 local time (LT) vegetation temperature increase projected under future climate change were attributable to the climate-driven shift in land cover. The authors projected that afforestation could cause local 0.2-1.2 C reductions in summer daily-mean 2-m air temperature and 2.0-3.7 C reductions in 1600 LT vegetation temperature for snow-free regions, primarily because of increased evapotranspiration. Because some of these temperature changes are of comparable magnitude to those
Hahmann, Andrea N.; Pena Diaz, Alfredo; Hansen, Jens Carsten
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 covers the preliminary validation of the WRF simulations against tall mast observations....
Teixeira, J. C.; Carvalho, A. C.; Carvalho, M. J.; Luna, T.; Rocha, A.
The advances in satellite technology in recent years have made feasible the acquisition of high-resolution information on the Earth's surface. Examples of such information include elevation and land use, which have become more detailed. Including this information in numerical atmospheric models can improve their results in simulating lower boundary forced events, by providing detailed information on their characteristics. Consequently, this work aims to study the sensitivity of the weather research and forecast (WRF) model to different topography as well as land-use simulations in an extreme precipitation event. The test case focused on a topographically driven precipitation event over the island of Madeira, which triggered flash floods and mudslides in the southern parts of the island. Difference fields between simulations were computed, showing that the change in the data sets produced statistically significant changes to the flow, the planetary boundary layer structure and precipitation patterns. Moreover, model results show an improvement in model skill in the windward region for precipitation and in the leeward region for wind, in spite of the non-significant enhancement in the overall results with higher-resolution data sets of topography and land use.
Machineni, Nehru; Veldore, Vidyunmala; Mesquita, Michel d. S.
Accuracy in predicting tropical cyclones over low lying coastal regions is pivotal for understanding storm tracks and their subsequent impacts. The present study highlights the challenges in predicting the Bay of Bengal (BOB) cyclone "AILA" (during 23rd to 25th May 2009) using the Weather Research and Forecast model, Advanced research core module (WRF-ARW). The model configuration uses a two-way interactive nested domain with 10 km resolution over BOB. Its initial and boundary conditions are driven from the NCEP FNL operational global analysis data at every 6 hours. A total of 74 sensitivity experiments were conducted to test the following factors and levels: a) parametrization schemes: two microphysics and two cumulus physics schemes used to select appropriate combination over study region, b) model domain:including/excluding Himalayas, c) vertical resolution: eight various increasing/decreasing vertical levels have been carried out to evaluate the storm track dependencies on these factors, d) domain size: and increasing (decreasing) the grid points of model domain in east-west direction shows that approximately 50-100 km track difference for every two points. Our results show that, the experiments including the Himalayas provide a better representation of cyclone track and speed. In order to reduce the computational time required to do such tremendous amount of experiment, we hypothesize to use statistical tools of experimental design which can involve all the factors that determine the cyclone tracks. A proper experimental design might provide unbiased results and also we might need less number of experiments.
Rafieei Nasab, A.; Gochis, D.; Dugger, A. L.; Pan, L.; McCreight, J. L.; Yu, W.; Zhang, Y.; Yates, D. N.; Somos-Valenzuela, M. A.; Salas, F. R.; Maidment, D. R.
A fully-distributed WRF-Hydro modeling system developed at National Center of Atmospheric Research (NCAR) will serve the initial operational nationwide streamflow forecasting needs of the National Water Center (NWC). This paper presents a multi-faceted evaluation of the WRF-hydro modeling system in preparation for operational national streamflow prediction. The testing period encompasses the 2015 warm season which included the National Flood Interoperability Experiment (NFIE) where WRF-Hydro and the RAPID channel routing model were driven by the Multi-Radar Multi-Sensor (MRMS) estimates as the real-time precipitation estimate product and the High Resolution Rapid Refresh (HRRR) for the short term forecast. Here, we validate the MRMS estimates and HRRR precipitation forecasts at national scale using daily precipitation observations from the Global Historical Climatology Network (GHCN). Because WRF-Hydro has several physics options such as surface overland flow, saturated subsurface flow, channel routing as well as conceptual deep groundwater base flow also conducted additional simulations to evaluate WRF-Hydro performance under different processes configurations. Streamflow verification data for model simulations and predictions was completed for a subset of GAGES-II reference basins. Multi-temporal and spatial scale verification is performed in order to test the robustness and skill improvement in WRF-Hydro streamflow simulations under different configuration over a wide range of basins sizes and from short-term (hourly) to longer-term (monthly) flow simulations. Evaluation will be also carried out based on various geographic regions to relate the skill improvement to dominant controls on flow based on the actual physical and climatic properties of the basins. The goal is to inform WRF-Hydro model configuration for the initial operating capabilities (IOC) project and target processes and parameter estimates for improvement.
Bravo-Aranda, Juan Antonio; de Arruda Moreira, Gregori; Navas-Guzmán, Francisco; José Granados-Muñoz, María; Guerrero-Rascado, Juan Luis; Pozo-Vázquez, David; Arbizu-Barrena, Clara; José Olmo Reyes, Francisco; Mallet, Marc; Alados Arboledas, Lucas
The automatic and non-supervised detection of the planetary boundary layer height (zPBL) by means of lidar measurements was widely investigated during the last several years. Despite considerable advances, the experimental detection still presents difficulties such as advected aerosol layers coupled to the planetary boundary layer (PBL) which usually produces an overestimation of the zPBL. To improve the detection of the zPBL in these complex atmospheric situations, we present a new algorithm, called POLARIS (PBL height estimation based on lidar depolarisation). POLARIS applies the wavelet covariance transform (WCT) to the range-corrected signal (RCS) and to the perpendicular-to-parallel signal ratio (δ) profiles. Different candidates for zPBL are chosen and the selection is done based on the WCT applied to the RCS and δ. We use two ChArMEx (Chemistry-Aerosol Mediterranean Experiment) campaigns with lidar and microwave radiometer (MWR) measurements, conducted in 2012 and 2013, for the POLARIS' adjustment and validation. POLARIS improves the zPBL detection compared to previous methods based on lidar measurements, especially when an aerosol layer is coupled to the PBL. We also compare the zPBL provided by the Weather Research and Forecasting (WRF) numerical weather prediction (NWP) model with respect to the zPBL determined with POLARIS and the MWR under Saharan dust events. WRF underestimates the zPBL during daytime but agrees with the MWR during night-time. The zPBL provided by WRF shows a better temporal evolution compared to the MWR during daytime than during night-time.
Asong, Z. E.
Lack of accurate estimates of precipitation are an important limitation for hydrological and earth systems modelling in Canada. Ground-based measurements are inevitably limited, given the large land area and small population density, fail to capture the effects of mountain topography in important runoff-producing areas and suffer from gross inaccuracies associated with cold climate precipitation processes. The capability of the current generation of atmospheric models to represent precipitation is therefore of major interest for hydrological practice. The skill of a high-resolution 4-km convection resolving regional climate model (RCM)―Weather Research and Forecasting (WRF) in capturing the statistics of daily-scale precipitation (P) and temperature (T) over western Canada within the period 2002 - 2013, using observational data sets for comparison is evaluated in this study. We analyze not only the mean pattern of P and T distributions, but also the inter-annual variability and trends in higher order climate statistics such as wet-dry day frequency, spell lengths, 95th percentile daily maximum T, 5th percentile daily minimum T, and 95th percentile daily P are evaluated against ground observations. This preliminary assessment should enable more informed application of high-resolution RCMs for the investigation of current and future changes in socio-economic and environmentally relevant hydro-climatic characteristics over this topographically complex region of western Canada.
U.S. Environmental Protection Agency — Box Photosynthesis model simulations for latent heat and ozone at 6 different FLUXNET sites. This dataset is associated with the following publication: Ran, L., J....
Full Text Available We present simulations of atmospheric CO2 concentrations provided by two modeling systems, run at high spatial resolution: the Eulerian-based Weather Research Forecasting (WRF model and the Lagrangian-based Stochastic Time-Inverted Lagrangian Transport (STILT model, both of which are coupled to a diagnostic biospheric model, the Vegetation Photosynthesis and Respiration Model (VPRM. The consistency of the simulations is assessed with special attention paid to the details of horizontal as well as vertical transport and mixing of CO2 concentrations in the atmosphere. The dependence of model mismatch (Eulerian vs. Lagrangian on models' spatial resolution is further investigated. A case study using airborne measurements during which two models showed large deviations from each other is analyzed in detail as an extreme case. Using aircraft observations and pulse release simulations, we identified differences in the representation of details in the interaction between turbulent mixing and advection through wind shear as the main cause of discrepancies between WRF and STILT transport at a spatial resolution such as 2 and 6 km. Based on observations and inter-model comparisons of atmospheric CO2 concentrations, we show that a refinement of the parameterization of turbulent velocity variance and Lagrangian time-scale in STILT is needed to achieve a better match between the Eulerian and the Lagrangian transport at such a high spatial resolution (e.g. 2 and 6 km. Nevertheless, the inter-model differences in simulated CO2 time series for a tall tower observatory at Ochsenkopf in Germany are about a factor of two smaller than the model-data mismatch and about a factor of three smaller than the mismatch between the current global model simulations and the data.
Cuchiara, G. C.; Carvalho, J.
One of the main problems related to air pollution in urban areas is caused by photochemical oxidants, particularly troposphere ozone (O3), which is considered a harmful substance. The O3 precursors (carbon monoxide CO, nitrogen oxides NOx and hydrocarbons HCs) are predominantly of anthropogenic origin in these areas, and vehicles are the main emission sources. Due to the increased urbanization and industrial development in recent decades, air pollutant emissions have increased likewise, mainly by mobile sources in the highly urbanized and developed areas, such as the Metropolitan Area of Porto Alegre-RS (MAPA). According to legal regulations implemented in Brazil in 2005, which aimed at increasing the fraction of biofuels in the national energy matrix, 2% biodiesel were supposed to be added to the fuel mixture within three years, and up to 5% after eight years of implementation of these regulations. Our work performs an analysis of surface concentrations for O3, NOx, CO, and HCs through numerical simulations with WRF/Chem (Weather Research and Forecasting model with Chemistry). The model is validated against observational data obtained from the local urban air quality network for the period from January 5 to 9, 2009 (96 hours). One part of the study focused on the comparison of simulated meteorological variables, to observational data from two stations in MAPA. The results showed that the model simulates well the diurnal evolution of pressure and temperature at the surface, but is much less accurate for wind speed. Another part included the evaluation of model results of WRF/Chem for O3 versus observed data at air quality stations Esteio and Porto Alegre. Comparisons between simulated and observed O3 revealed that the model simulates well the evolution of the observed values, but on many occasions the model did not reproduce well the maximum and minimum concentrations. Finally, a preliminary quantitative sensitivity study on the impact of biofuel on the
GU Jianfeng; Qingnong XIAO; Ying-Hwa KUO; Dale M. BARKER; XUE Jishan; MA Xiaoxing
Using the recently developed Weather Research and Forecasting (WRF) 3DVAR and the WRF model, numerical experiments are conducted for the initialization and simulation of typhoon Rusa (2002).The observational data used in the WRF 3DVAR are conventional Global Telecommunications System (GTS) data and Korean Automatic Weather Station (AWS) surface observations. The Background Error Statistics (BES) via the National Meteorological Center (NMC) method has two different resolutions, that is, a 210-km horizontal grid space from the NCEP global model and a 10-kn horizontal resolution from Korean operational forecasts. To improve the performance of the WRF simulation initialized from the WRF 3DVAR analyses, the scale-lengths used in the horizontal background error covariances via recursive filter are tuned in terms of the WRF 3DVAR control variables, streamfunction, velocity potential, unbalanced pressure and specific humidity. The experiments with respect to different background error statistics and different observational data indicate that the subsequent 24-h the WRF model forecasts of typhoon Rusa's track and precipitation are significantly impacted upon the initial fields. Assimilation of the AWS data with the tuned background error statistics obtains improved predictions of the typhoon track and its precipitation.
Lara Fanego, Vicente; Ruiz Arias, Jose Antonio; Pozo Vazquez, Antonio David; Santos Alamillos, Francisco Javier; Tovar Pescador, Joaquin [Jaen Univ. (Spain). Dept. of Physics; Quesada Ruiz, Samuel [Jaen Univ. (Spain). Dept. of Computer Engineering
In this work, we evaluate the reliability of GHI and DNI forecast based on the WRF mesoscale atmospheric model in Andalusia (Southern Spain). Particularly, the role of the spatial resolution of the model set up and the use of a spatial-averaging post-processing step was analyzed. To this end, a set of two-days-ahead one-year-length integrations, with different spatial resolutions (1, 3, 9 and 27 km) were evaluated. Results showed, firstly, that an increment in the spatial resolution does not enhance the reliability of the model forecasts, except under clear sky conditions. Secondly, that, in general, an spatial averaging of the solar forecasts corresponding to the grid points surrounding the location of interest provides a notable improvement in the forecasting skills. The most significant improvement is found when forecasts corresponding to an area of about 100 by 100 km are averaged. The role of the WRF model cloud representation in the former results is discussed. (orig.)
Falk, M.; Pyles, R. D.; Marras, S.; Spano, D.; Paw U, K. T.
The number of urban metabolism studies has increased in recent years, due to the important impact that energy, water and carbon exchange over urban areas have on climate change. Urban modeling is therefore crucial in the future design and management of cities. This study presents the ACASA model coupled to the Weather Research and Forecasting (WRF-ARW) mesoscale model to simulate urban fluxes at a horizontal resolution of 200 meters for urban areas of roughly 100 km^2. As part of the European Project "BRIDGE", these regional simulations were used in combination with remotely sensed data to provide constraints on the land surface types and the exchange of carbon and energy fluxes from urban centers. Surface-atmosphere exchanges of mass and energy were simulated using the Advanced Canopy Atmosphere Soil Algorithm (ACASA). ACASA is a multi-layer high-order closure model, recently modified to work over natural, agricultural as well as urban environments. In particular, improvements were made to account for the anthropogenic contribution to heat and carbon production. For two cities four climate change and four urban planning scenarios were simulated: The climate change scenarios include a base scenario (Sc0: 2008 Commit in IPCC), a medium emission scenario (Sc1: IPCC A2), a worst case emission scenario (Sce2: IPCC A1F1) and finally a best case emission scenario (Sce3: IPCC B1). The urban planning scenarios include different development scenarios such as smart growth. The two cities are a high latitude city, Helsinki (Finland) and an historic city, Florence (Italy). Helsinki is characterized by recent, rapid urbanization that requires a substantial amount of energy for heating, while Florence is representative of cities in lower latitudes, with substantial cultural heritage and a comparatively constant architectural footprint over time. In general, simulated fluxes matched the point observations well and showed consistent improvement in the energy partitioning over
Full Text Available Land use/cover change (LUCC has become one of the most important factors for the global climate change. As one of the major types of LUCC, cultivated land reclamation also has impacts on regional climate change. Most of the previous studies focused on the correlation and simulation analysis of historical LUCC and climate change, with few explorations for the impacts of future LUCC on regional climate, especially impacts of the cultivated land reclamation. This study used the Weather Research and Forecasting (WRF model to forecast the changes of energy flux and temperature based on the future cultivated land reclamation in India and then analyzed the impacts of cultivated land reclamation on climate change. The results show that cultivated land reclamation will lead to a large amount of land conversions, which will overall result in the increase in latent heat flux of regional surface as well as the decrease in sensible heat flux and further lead to changes of regional average temperature. Furthermore, the impact on climate change is seasonally different. The cultivated land reclamation mainly leads to a temperature decrease in the summer, while it leads to a temperature increase in the winter.
Full Text Available The influence of sea surface temperature (SST anomalies on the hurricane characteristics are investigated in a set of sensitivity experiments employing the Weather Research and Forecasting (WRF model. The idealised experiments are performed for the case of Hurricane Katrina in 2005. The first set of sensitivity experiments with basin-wide changes of the SST magnitude shows that the intensity goes along with changes in the SST, i.e., an increase in SST leads to an intensification of Katrina. Additionally, the trajectory is shifted to the west (east, with increasing (decreasing SSTs. The main reason is a strengthening of the background flow. The second set of experiments investigates the influence of Loop Current eddies idealised by localised SST anomalies. The intensity of Hurricane Katrina is enhanced with increasing SSTs close to the core of a tropical cyclone. Negative nearby SST anomalies reduce the intensity. The trajectory only changes if positive SST anomalies are located west or north of the hurricane centre. In this case the hurricane is attracted by the SST anomaly which causes an additional moisture source and increased vertical winds.
Vejmelka, Martin; Mandel, Jan
Fuel moisture is a major influence on the behavior of wildland fires and an important underlying factor in fire risk. We present a method to assimilate spatially sparse fuel moisture observations from remote automatic weather stations (RAWS) into the moisture model in WRF-SFIRE. WRF-SFIRE is a coupled atmospheric and fire behavior model which simulates the evolution of fuel moisture in idealized fuel species based on atmospheric state. The proposed method uses a modified trend surface model to estimate the fuel moisture field and its uncertainty based on currently available observations. At each grid point of WRF-SFIRE, this information is combined with the model forecast using a nonlinear Kalman filter, leading to an updated estimate of fuel moisture. We demonstrate the effectiveness of the method with tests in two real-world situations: a region in Southern California, where two large Santa Ana fires occurred recently, and on a domain enclosing Colorado.
Full Text Available To improve the simulation performance of mesoscale models in the northeastern Tibetan Plateau, two reanalysis initial datasets (NCEP FNL and ERA-Interim and two MODIS (Moderate-Resolution Imaging Spectroradiometer land-use datasets (from 2001 and 2010 are used in WRF (Weather Research and Forecasting modeling. The model can reproduce the variations of 2 m temperature (T2 and 2 m relative humidity (RH2, but T2 is overestimated and RH2 is underestimated in the control experiment. After using the new initial drive and land use data, the simulation precision in T2 is improved by the correction of overestimated net energy flux at surface and the RH2 is improved due to the lower T2 and larger soil moisture. Due to systematic bias in WRF modeling for wind speed, we design another experiment that includes the Jimenez subgrid-scale orography scheme, which reduces the frequency of low wind speed and increases the frequency of high wind speed and that is more consistent with the observation. Meanwhile, the new drive and land-use data lead to lower boundary layer height and influence the potential temperature and wind speed in both the lower atmosphere and the upper layer, while the impact on water vapor mixing ratio is primarily concentrated in the lower atmosphere.
At the 12th Annual CMAS Conference initial results from the application of the coupled WRF-CMAQ modeling system to the 2011 Baltimore-Washington D.C. DISCOVER-AQ campaign were presented, with the focus on updates and new methods applied to the WRF modeling for fine-scale applicat...
Santoni, G. W.; Xiang, B.; Kort, E. A.; Daube, B.; Andrews, A. E.; Sweeney, C.; Wecht, K.; Peischl, J.; Ryerson, T. B.; Angevine, W. M.; Trainer, M.; Nehrkorn, T.; Eluszkiewicz, J.; Wofsy, S. C.
We present constraints on California emission inventories of methane (CH4) using atmospheric observations from nine NOAA P-3 flights during the California Nexus (CalNex) campaign in May and June of 2010. Measurements were made using a quantum cascade laser spectrometer (QCLS) and a cavity ring-down spectrometer (CRDS) and calibrated to NOAA standards in-flight. Five flights sampled above the northern and southern central valley and an additional four flights probed the south coast air basin, quantifying emissions from the Los Angeles basin. The data show large (>100 ppb) CH4 enhancements associated with point and area sources such as cattle and manure management, landfills, wastewater treatment, gas production and distribution infrastructure, and rice agriculture. We compare aircraft observations to modeled CH4 distributions by accounting for a) transport using the Stochastic Time-Inverted Lagrangian Transport (STILT) model driven by Weather Research and Forecasting (WRF) meteorology, b) emissions from inventories such as EDGAR and ones constructed from California-specific state and county databases, each gridded to 0.1° x 0.1° resolution, and c) spatially and temporally evolving boundary conditions such as GEOS-Chem and a NOAA aircraft profile measurement derived curtain imposed at the edge of the WRF domain. After accounting for errors associated with transport, planetary boundary layer height, lateral boundary conditions, seasonality of emissions, and the spatial resolution of surface emission prior estimates, we find that the California Air Resources Board (CARB) CH4 budget is a factor of 1.64 too low. Using a Bayesian inversion to the flight data, we estimate California's CH4 budget to be 2.5 TgCH4/yr, with emissions from cattle and manure management, landfills, rice, and natural gas infrastructure, representing roughly 82%, 26%, 9% and 32% (sum = 149% with other sources accounting for the additional 15%) of the current CARB CH4 budget estimate of 1.52 TgCH4
Molthan, Andrew L.; Jedlovec, Gary J.; Lapenta, William M.
The CloudSat Mission, part of the NASA A-Train, is providing the first global survey of cloud profiles and cloud physical properties, observing seasonal and geographical variations that are pertinent to evaluating the way clouds are parameterized in weather and climate forecast models. CloudSat measures the vertical structure of clouds and precipitation from space through the Cloud Profiling Radar (CPR), a 94 GHz nadir-looking radar measuring the power backscattered by clouds as a function of distance from the radar. One of the goals of the CloudSat mission is to evaluate the representation of clouds in forecast models, thereby contributing to improved predictions of weather, climate and the cloud-climate feedback problem. This paper highlights potential limitations in cloud microphysical schemes currently employed in the Weather Research and Forecast (WRF) modeling system. The horizontal and vertical structure of explicitly simulated cloud fields produced by the WRF model at 4-km resolution are being evaluated using CloudSat observations in concert with products derived from MODIS and AIRS. A radiative transfer model is used to produce simulated profiles of radar reflectivity given WRF input profiles of hydrometeor mixing ratios and ambient atmospheric conditions. The preliminary results presented in the paper will compare simulated and observed reflectivity fields corresponding to horizontal and vertical cloud structures associated with midlatitude cyclone events.
Wang, Yi; Long, Charles N.; Leung, Lai-Yung R.; Dudhia, Jimy; McFarlane, Sally A.; Mather, James H.; Ghan, Steven J.; Liu, Xiaodong
Data from the Tropical Warm Pool I5 nternational Cloud Experiment (TWPICE) were used to evaluate two suites of high-resolution (4-7 km, convection-resolving) simulations of the Advanced Research Weather Research and Forecasting (WRF) model with a focus on the performance of different cloud microphysics (MP) schemes. The major difference between these two suites of simulations is with and without the reinitializing process. Whenreinitialized every three days, the four cloud MP schemes evaluated can capture the general profiles of cloud fraction, temperature, water vapor, winds, and cloud liquid and ice water content (LWC and IWC, respectively). However, compared with surface measurements of radiative and moisture fluxes and satellite retrieval of top-of-the-atmosphere (TOA) fluxes, disagreements do exist. Large discrepancies with observed LWC and IWC and derived radiative heating profiles can be attributed to both the limitations of the cloud property retrievals and model performance. The simulated precipitation also shows a wide range of uncertainty as compared with observations, which could be caused by the cloud MP schemes, complexity of land-sea configuration, and the high temporal and spatial variability. In general, our result indicates the importance of large-scale initial and lateral boundary conditions in re-producing basic features of cloudiness and its vertical structures. Based on our case study, we find overall the six-hydrometer single-moment MP scheme(WSM6) [Hong and Lim, 2006] in the WRF model si25 mulates the best agree- ment with the TWPICE observational analysis.
Lee, Junhong; Shin, Hyeyum Hailey; Hong, Song-You; Jiménez, Pedro A.; Dudhia, Jimy; Hong, Jinkyu
paper reports on the first attempt to investigate whether excessive precipitation over mountainous areas, which is a common problem in model simulations, could be remedied by the implementation of a more realistic surface wind field in the high-resolution Weather Research and Forecasting (WRF) model. A series of 48 h short-range forecasts was conducted for the month of July 2006 within the triple-nested WRF configuration, for which the highest resolution of 3 km was focused on areas with complex orography over East Asian monsoonal regions. For accurate surface wind simulations, the subgrid-scale (SGS) orography parameterization scheme was employed. It was found that the simulated surface wind showed negative (positive) bias over mountainous (flat) regions when the SGS orography parameterization was excluded. After inclusion of the SGS orography parameterization, wind speed over mountainous (flat) regions increased (decreased), implying that the bias was mitigated. Moisture divergence (convergence) over the mountains (on the leeward side of the mountains) was induced, and surface latent heat flux increased along the mountain ranges following the improvement in the representation of the surface wind by the inclusion of the SGS orography parameterization. Eventually, excessive precipitation simulated over mountainous areas of East Asia, which is a feature commonly observed in numerical model studies, was alleviated because of the moisture divergence and increased surface latent heat flux.
Full Text Available A source-oriented representation of airborne particulate matter was added to the Weather Research & Forecasting (WRF model with chemistry (WRF/Chem. The source-oriented aerosol separately tracks primary particles with different hygroscopic properties rather than instantaneously combining them into an internal mixture. The source-oriented approach avoids artificially mixing light absorbing black + brown carbon particles with materials such as sulfate that would encourage the formation of additional coatings. Source-oriented particles undergo coagulation and gas-particle conversion, but these processes are considered in a dynamic framework that realistically "ages" primary particles over hours and days in the atmosphere. The source-oriented WRF/Chem model more accurately predicts radiative feedbacks from anthropogenic aerosols compared to models that make internal mixing or other artificial mixing assumptions. A three-week stagnation episode (15 December 2000 to 6 January 2001 during the California Regional PM10/PM2.5 Air Quality Study (CRPAQS was chosen for the initial application of the new modeling system. Emissions were obtained from the California Air Resources Board. Gas-phase reactions were modeled with the SAPRC90 photochemical mechanism. Gas-particle conversion was modeled as a dynamic process with semi-volatile vapor pressures at the particle surface calculated using ISORROPIA. Source oriented calculations were performed for 8 particle size fractions ranging from 0.01–10 μm particle diameters with a spatial resolution of 4 km and hourly time resolution. Primary particles emitted from diesel engines, wood smoke, high sulfur fuel combustion, food cooking, and other anthropogenic sources were tracked separately throughout the simulation as they aged in the atmosphere. Results show that the source-oriented representation of particles with meteorological feedbacks in WRF/Chem changes the aerosol extinction coefficients, downward shortwave
Hu, Jianlin; Chen, Jianjun; Ying, Qi; Zhang, Hongliang
China has been experiencing severe air pollution in recent decades. Although an ambient air quality monitoring network for criteria pollutants has been constructed in over 100 cities since 2013 in China, the temporal and spatial characteristics of some important pollutants, such as particulate matter (PM) components, remain unknown, limiting further studies investigating potential air pollution control strategies to improve air quality and associating human health outcomes with air pollution exposure. In this study, a yearlong (2013) air quality simulation using the Weather Research and Forecasting (WRF) model and the Community Multi-scale Air Quality (CMAQ) model was conducted to provide detailed temporal and spatial information of ozone (O3), total PM2.5, and chemical components. Multi-resolution Emission Inventory for China (MEIC) was used for anthropogenic emissions and observation data obtained from the national air quality monitoring network were collected to validate model performance. The model successfully reproduces the O3 and PM2.5 concentrations at most cities for most months, with model performance statistics meeting the performance criteria. However, overprediction of O3 generally occurs at low concentration range while underprediction of PM2.5 happens at low concentration range in summer. Spatially, the model has better performance in southern China than in northern China, central China, and Sichuan Basin. Strong seasonal variations of PM2.5 exist and wind speed and direction play important roles in high PM2.5 events. Secondary components have more boarder distribution than primary components. Sulfate (SO42-), nitrate (NO3-), ammonium (NH4+), and primary organic aerosol (POA) are the most important PM2.5 components. All components have the highest concentrations in winter except secondary organic aerosol (SOA). This study proves the ability of the CMAQ model to reproduce severe air pollution in China, identifies the directions where improvements are
Katinka Petersen, Anna; Kumar, Rajesh; Brasseur, Guy; Granier, Claire
The degradation of air quality in Asia resulting from the intensification of human activities, and the related impacts on the health of billions of people have become an urgent matter of concern. The World Health Organization states that each year nearly 3.3 million people die worldwide prematurely because of air pollution. The situation is particularly acute in Asia. Improving air quality over the Asian continent has become a major challenge for national, regional and local authorities. A prerequisite for air quality improvement is the development of a reliable monitoring system with surface instrumentation and space platforms as well as an analysis and prediction system based on an advanced chemical-meteorological model. The aim is to use the WRF-Chem model for the prediction of daily air quality for the Asian continent with spatial resolution that will be increased in densely populated areas by grid nesting. The modeling system covers a nearly the entire Asian continent so that transport processes of chemical compounds within the continent are simulated and analyzed. To additionally account for the long-range effects and assess their relative importance against regional emissions, the regional chemical transport modeling system uses information from a global modeling system as boundary conditions. The first steps towards a forecasting system over Asia are to test the model performance over this large model domain and the different emissions inventories available for Asia. In this study, the WRF-Chem model was run for a domain covering 60°E to 150°E, 5°S to 50°N at a resolution of 60 km x 60 km for January 2006 with three alternative emission inventories available for Asia (MACCITY, INTEX-B and REAS). We present an intercomparison of the three different simulations and evaluate the simulations with satellite and in situ observations, with focus on ozone, particulate matter, nitrogen oxides and carbon monoxide. The differences between the simulations using
Phoenix, D. B.; Homeyer, C. R.
Tropopause-penetrating convection is capable of rapidly transporting air from the lower troposphere to the upper troposphere and lower stratosphere (UTLS). Since the vertical redistribution of gases in the atmosphere by convection can have important impacts on the chemistry of the UTLS, the radiative budget, and climate, it has become a recent focus of observational and modeling studies. Despite being otherwise limited in space and time, recent aircraft observations from field campaigns such as the Deep Convective Clouds and Chemistry (DC3) experiment have provided new high-resolution observations of convective transport. Modeling studies, on the other hand, offer the advantage of providing output related to the physical, dynamical, and chemical characteristics of storms and their environments at fine spatial and temporal scales. Since these characteristics of simulated convection depend on the chosen model design, we examine the sensitivity of simulated convective transport to the choice of physical and chemical parameterizations in the Weather Research and Forecasting model coupled with Chemistry (WRF-Chem) for several DC3 cases in this study. In particular, we conduct sensitivity tests for the choice of 1) bulk microphysics parameterization, 2) planetary boundary layer parameterization, and 3) chemical mechanism. Model output is evaluated using ground-based radar observations of each storm and in situ trace gas observations from two aircraft operated during the DC3 experiment. Model results show measurable sensitivity of the physical characteristics of a storm and the transport of water vapor and additional trace gases into the UTLS to the choice of microphysics parameterization. The physical characteristics of the storm and transport of insoluble trace gases are largely insensitive to choice of PBL scheme and chemical mechanism, though several soluble trace gases (e.g., SO2, CH2O, NH3) exhibit some measurable sensitivity.
Full Text Available The impact of urban surface parameterizations in the WRF (Weather Research and Forecasting model on the simulation of local meteorological fields is investigated. The Noah land surface model (LSM, a modified LSM, and a single-layer urban canopy model (UCM have been compared, focusing on urban patches. The model simulations were performed for 6 days from 12 August to 17 August during the Texas Air Quality Study 2006 field campaign. Analysis was focused on the Houston-Galveston metropolitan area. The model simulated temperature, wind, and atmospheric boundary layer (ABL height were compared with observations from surface meteorological stations (Continuous Ambient Monitoring Stations, CAMS, wind profilers, the NOAA Twin Otter aircraft, and the NOAA Research Vessel Ronald H. Brown. The UCM simulation showed better results in the comparison of ABL height and surface temperature than the LSM simulations, whereas the original LSM overestimated both the surface temperature and ABL height significantly in urban areas. The modified LSM, which activates hydrological processes associated with urban vegetation mainly through transpiration, slightly reduced warm and high biases in surface temperature and ABL height. A comparison of surface energy balance fluxes in an urban area indicated the UCM reproduces a realistic partitioning of sensible heat and latent heat fluxes, consequently improving the simulation of urban boundary layer. However, the LSMs have a higher Bowen ratio than the observation due to significant suppression of latent heat flux. The comparison results suggest that the subgrid heterogeneity by urban vegetation and urban morphological characteristics should be taken into account along with the associated physical parameterizations for accurate simulation of urban boundary layer if the region of interest has a large fraction of vegetation within the urban patch. Model showed significant discrepancies in the specific meteorological
Kerandi, Noah Misati; Laux, Patrick; Arnault, Joel; Kunstmann, Harald
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.
To improve the weather forecasting over the Beijing area for the 2008 Olympic Games,a triple-nested(27/9/3km) WRFVar/WRF system with 3-h update cycle was established.Experiments have been done for a convective event that occurred on August 1,2006.The results showed that the high-resolution rapid update cycle gave a good precipitation forecast;the tunings of background error statistics(BES) and observation-error statistics in WRFVar improved the skill of the precipitation forecast;the BES for the fine domain(3 km) obtained by interpolation from its parent domain(9 km) can be used in 3 km WRFVar as a reasonable approximation.The user can now save a great deal of work related to the derivation of the fine mesh BES from the forecast over a period of time;the rapid update cycle with 3-h frequency has satisfied the forecast,and the update cycle with 1-h frequency was not necessary.
Jin, J.; Miller, N.
The Community Land Model version 3 (CLM3) developed by the National Center for Atmospheric Research (NCAR) was coupled into the Weather Research and Forecasting (WRF) Model version 2.2. The performance of WRF-CLM3 in predicting regional climate was quantitatively compared with that of WRF coupled to the soil thermal diffusion (STD), Rapid Update Cycle, and NOAH Land Surface Schemes. These land surface schemes represent a range of complexity within land-surface schemes. CLM3 is the most sophisticated model, with detailed snow and vegetation processes. The STD scheme is oversimplified, which only calculates soil temperature and neglects vegetation and snow physics. The RUC and NOAH schemes are intermediate in the detail, and the major deference between them is that RUC has a multi-layer snow scheme, and Noah has a single snow layer lumped with the topmost soil layer. WRF was driven by the National Centers for Environmental Prediction Reanalysis data II with each of these land surface schemes for one-year simulations over the period, 1 October 1995 to 30 September 1996, resulting in four one-year simulations for intercomparison. Each simulation has 30km-10km two-way nested domains. The 30 km domain includes the western U.S. and eastern Pacific, and the inner domain includes California and parts of Nevada, Oregon, and the eastern Pacific. Our analysis shows that WRF-CLM3 outperforms WRF-RUC, WRF-NOAH, and WRF-STD in simulating temperature and snow when compared with observations. The WRF-STD scheme, which does not include snow and vegetation processes resulted in the poorest results, with a dramatic overestimation of surface air temperature. However, regardless of the land surface scheme chosen, WRF reasonably well reproduces the winter precipitation, a major water resource for California, suggesting that the linkage between land surface processes and precipitation is not explicit. In general, land surface schemes play a significant role in the simulation of regional
Kukkonen, J.; Balk, T.; Schultz, D.M.; Baklanov, A.; Klein, T.; Miranda, A.I.; Monteiro, A.; Hirtl, M.; Tarvainen, V.; Boy, M.; Peuch, V.H.; Poupkou, A.; Kioutsioukis, I.; Finardi, S.; Sofiev, M.; Sokhi, R.; Lehtinen, K.; Karatzas, K.; San José, R.; Astitha, M.; Kallos, G.; Schaap, M.; Reimer, E.; Jakobs, H.; Eben, K.
Numerical models that combine weather forecasting and atmospheric chemistry are here referred to as chemical weather forecasting models. Eighteen operational chemical weather forecasting models on regional and continental scales in Europe are described and compared in this article. Topics discussed
Zhang, Y.; Enomoto, H.; Ohata, T.; Kitabata, H.; Kadota, T.; Hirabayashi, Y.
Glacier mass balance forms a vital link between climate change and glacier dynamics and hydrology, and its variation is the best way to infer climate change from glaciers. The Altai Mountains are located in the southern periphery of the Asian Arctic basin and the most northern periphery of the central Asia mountain system, which contains 1280 glaciers covering an area of 1191 km2. These glaciers are at the headwaters of many prominent rivers, which affects the water discharge of large rivers such as the Ob and Yenisey rivers. Although several studies have been proposed for glacier changes in this region based on satellite data, so far no study focuses on glacier mass change in the whole Altai Mountains. Therefore, we implement a temperature-index-based glacier model that considers the glacier area evolution and the refreezing of meltwater, to reconstruct glacier mass balance of the Altai Mountains, forcing the model by a Weather Research and Forecasting (WRF) model simulations with 5-km resolution and glacier inventory data. Compared to available observed mass balances on three glaciers of this region, the model can reproduce reasonably well the decadal glacier mass changes. According to our calculations, the glaciers in the whole region show a mean annual balance of -0.8 m water equivalent per year over the period 1988-2012. Most Altai glaciers have experienced negative net surface mass balance over the study period, especially in the western part of the Altai Mountains. In addition to rising temperature, decreased precipitation in the western part of the Altai Mountains and increasing precipitation in the eastern part is probably driving these systematic differences.
Viterbo, Francesca; Parodi, Antonio; Molini, Luca; Provenzale, Antonello; von Hardenberg, Jost; Palazzi, Elisa
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.
Qing, Chun; Wu, Xiaoqing; Li, Xuebin; Zhu, Wenyue; Qiao, Chunhong; Rao, Ruizhong; Mei, Haipin
The methods to obtain atmospheric refractive index structure constant (Cn2) by instrument measurement are limited spatially and temporally and they are more difficult and expensive over the ocean. It is useful to forecast Cn2 effectively from Weather Research and Forecasting Model (WRF) outputs. This paper introduces a method that WRF Model is used to forecast the routine meteorological parameters firstly, and then Cn2 is calculated based on these parameters by the Bulk model from the Monin-Obukhov similarity theory (MOST) over the ocean near-surface. The corresponding Cn2 values measured by the micro-thermometer which is placed on the ship are compared with the ones forecasted by WRF model to determine how this method performs. The result shows that the forecasted Cn2 is consistent with the measured Cn2 in trend and the order of magnitude as a whole, as well as the correlation coefficient is up to 77.57%. This method can forecast some essential aspects of Cn2 and almost always captures the correct magnitude of Cn2, which experiences fluctuations of two orders of magnitude. Thus, it seems to be a feasible and meaningful method that using WRF model to forecast near-surface Cn2 value over the ocean.
Yucel, Ismail; Onen, Alper; Yilmaz, Koray; Gochis, David
A fully-distributed, multi-physics, multi-scale hydrologic and hydraulic modeling system, WRF-Hydro, is used to assess the potential for skillful flood forecasting based on precipitation inputs derived from the Weather Research and Forecasting (WRF) model and the EUMETSAT Multi-sensor Precipitation Estimates (MPEs). Similar to past studies it was found that WRF model precipitation forecast errors related to model initial conditions are reduced when the three dimensional atmospheric data assimilation (3DVAR) scheme in the WRF model simulations is used. A comparative evaluation of the impact of MPE versus WRF precipitation estimates, both with and without data assimilation, in driving WRF-Hydro simulated streamflow is then made. The ten rainfall-runoff events that occurred in the Black Sea Region were used for testing and evaluation. With the availability of streamflow data across rainfall-runoff events, the cal- ibration is only performed on the Bartin sub-basin using two events and the calibrated parameters are then transferred to other neighboring three ungauged sub-basins in the study area. The rest of the events from all sub-basins are then used to evaluate the performance of the WRF-Hydro system with the cali- brated parameters. Following model calibration, the WRF-Hydro system was capable of skillfully repro- ducing observed flood hydrographs in terms of the volume of the runoff produced and the overall shape of the hydrograph. Streamflow simulation skill was significantly improved for those WRF model simula- tions where storm precipitation was accurately depicted with respect to timing, location and amount. Accurate streamflow simulations were more evident in WRF model simulations where the 3DVAR scheme was used compared to when it was not used. Because of substantial dry bias feature of MPE, as compared with surface rain gauges, streamflow derived using this precipitation product is in general very poor. Overall, root mean squared errors for runoff were
Full Text Available During the Convective and Orographically induced Precipitation Study (COPS, a scanning Doppler lidar was deployed at Achern, Baden-Wüttemberg, Germany from 13th June to 16th August 2007. Vertical velocity profiles ('rays' through the boundary layer were measured every 3 seconds with vertical profiles of horizontal wind velocity being derived from performing azimuth scans every 30 minutes. During Intense Observation Periods radiosondes were launched from the site. In this paper, a case study of convective boundary layer development on 15th July 2007 is investigated. Estimates of eddy dissipation rate are made from the vertically pointing lidar data and used as one input to the velocity-temperature co-variance equation to estimate sensible heat flux. The sensible heat flux values calculated from Doppler lidar data are compared with a surface based energy balance station and output from the Weather Research and Forecasting (WRF model.
Avolio, E.; Federico, S.; Miglietta, M. M.; Lo Feudo, T.; Calidonna, C. R.; Sempreviva, A. M.
The sensitivity of boundary layer variables to five (two non-local and three local) planetary boundary-layer (PBL) parameterization schemes, available in the Weather Research and Forecasting (WRF) mesoscale meteorological model, is evaluated in an experimental site in Calabria region (southern Italy), in an area characterized by a complex orography near the sea. Results of 1 km × 1 km grid spacing simulations are compared with the data collected during a measurement campaign in summer 2009, considering hourly model outputs. Measurements from several instruments are taken into account for the performance evaluation: near surface variables (2 m temperature and relative humidity, downward shortwave radiation, 10 m wind speed and direction) from a surface station and a meteorological mast; vertical wind profiles from Lidar and Sodar; also, the aerosol backscattering from a ceilometer to estimate the PBL height. Results covering the whole measurement campaign show a cold and moist bias near the surface, mostly during daytime, for all schemes, as well as an overestimation of the downward shortwave radiation and wind speed. Wind speed and direction are also verified at vertical levels above the surface, where the model uncertainties are, usually, smaller than at the surface. A general anticlockwise rotation of the simulated flow with height is found at all levels. The mixing height is overestimated by all schemes and a possible role of the simulated sensible heat fluxes for this mismatching is investigated. On a single-case basis, significantly better results are obtained when the atmospheric conditions near the measurement site are dominated by synoptic forcing rather than by local circulations. From this study, it follows that the two first order non-local schemes, ACM2 and YSU, are the schemes with the best performance in representing parameters near the surface and in the boundary layer during the analyzed campaign.
Liu, Y.; Cheng, W.; Liu, Y. W.; Wiener, G.; Frehlich, R.; Mahoney, W.; Warner, T.; Himelic, J.; Parks, K.; Early, S.
In collaboration with Xcel Energy and Vasaila Inc., the National Center for Atmospheric Research (NCAR) conducts modeling study to evaluate the existing and the enhanced intensive observation systems for wind power nowcasting and short-range forecasting at a northern Colorado wind farm. The NCAR WRF (Weather Research and Forecasting model) based Real-Time Four-Dimensional Data Assimilation (RTFDDA) and forecasting system, which has been employed to support Xcel Energy operational wind forecast, was used in this study. The observational data include ten met-towers, a 915Hz wind profiler, a sodar and a Windcube Doppler lidar, besides the in-farm met-towers and wind speed and power reports from more than 300 of wind turbines. The WRF-RTFDDA 4-dimensioanl data assimilation algorithm allows to spread and propagate observation information in the WRF model space (x, y, z and time) with weighting functions built according to the observation location and time. The WRF-RTFDDA was set up to run with four nested domains with grid increments of 30, 10, 3.333 and 1.111km respectively. The standard and diverse non-conventional observations are assimilated on coarse grid domains along with the special wind farm observations. In this study, we investigate a) spread of surface observations in PBL according to PBL depth and regimes, b) optimization of horizontal influence radii and steep-terrain adjustment, and c) impact of different observation platforms and data types on 0 - 12 h wind prediction . It is found that PBL mixing and thermodynamic structures are greatly influenced by the PBL parameterization formulation. The range of the data assimilation effect on forecasts relies on weather and PBL regimes. In most cases, assimilation of in-farm and near-farm observations improves up to 12-hour wind power prediction and assimilation of in-farm data can significantly improves 0 - 6 hour forecasts.
Wang, N; Guo, H; Jiang, F; Ling, Z H; Wang, T
Field measurements were simultaneously conducted at a mountain (Mt.) site (Tai Mao Shan, TMS) and an urban site (Tsuen Wan, TW) at the foot of the Mt. TMS in Hong Kong. An interesting event with consecutive high-ozone (O₃) days from 08:00 on 28 Oct. to 23:00 on 03 Nov., 2010 was observed at Mt. TMS, while no such polluted event was found at the foot of the mountain. The Weather Research and Forecasting (WRF)-Community Multiscale Air Quality (CMAQ) models were used to understand this event. Model performance evaluation showed that the simulated meteorological parameters and air pollutants were well in agreement with the observations. The index of agreement (IOA) of temperature, relative humidity, wind direction and wind speed were 0.93, 0.83, 0.46 and 0.60, respectively. The multi-day high O₃ episode at Mt. TMS was also reasonably reproduced (IOA=0.68). Horizontally, the photochemical processes determined the O₃ levels in southwestern Pearl River Delta (PRD) and the Pearl River Estuary (PRE), while in eastern and northern PRD, the O₃ destruction was over the production during the event. Vertically, higher O₃ values at higher levels were found at both Mt. TMS and TW, indicating a vertical O₃ gradient over Hong Kong. With the aid of the process analysis module, we found positive contribution of vertical transport including advection and diffusion to O₃ mixing ratios at the two sites, suggesting that O₃ values at lower locations could be affected by O₃ at higher locations via vertical advection and diffusion over Hong Kong.
Molthan, Andrew L.; Case, Jonathan L.; Venner, Jason; Moreno-Madrinan, Max. J.; Delgado, Francisco
Over the past two years, scientists in the Earth Science Office at NASA fs Marshall Space Flight Center (MSFC) have explored opportunities to apply cloud computing concepts to support near real ]time weather forecast modeling via the Weather Research and Forecasting (WRF) model. Collaborators at NASA fs Short ]term Prediction Research and Transition (SPoRT) Center and the SERVIR project at Marshall Space Flight Center have established a framework that provides high resolution, daily weather forecasts over Mesoamerica through use of the NASA Nebula Cloud Computing Platform at Ames Research Center. Supported by experts at Ames, staff at SPoRT and SERVIR have established daily forecasts complete with web graphics and a user interface that allows SERVIR partners access to high resolution depictions of weather in the next 48 hours, useful for monitoring and mitigating meteorological hazards such as thunderstorms, heavy precipitation, and tropical weather that can lead to other disasters such as flooding and landslides. This presentation will describe the framework for establishing and providing WRF forecasts, example applications of output provided via the SERVIR web portal, and early results of forecast model verification against available surface ] and satellite ]based observations.
Zhong, D.; Feng, X.
The need for a software toolkit that integrates space weather models and data is one of many challenges we are facing with when applying the models to space weather forecasting. To meet this challenge, we have developed Space Weather Integrated Modeling (SWIM) that is capable of analysis and visualizations of the results from a diverse set of space weather models. SWIM has a modular design and is written in Python, by using NumPy, matplotlib, and the Visualization ToolKit (VTK). SWIM provides data management module to read a variety of spacecraft data products and a specific data format of Solar-Interplanetary Conservation Element/Solution Element MHD model (SIP-CESE MHD model) for the study of solar-terrestrial phenomena. Data analysis, visualization and graphic user interface modules are also presented in a user-friendly way to run the integrated models and visualize the 2-D and 3-D data sets interactively. With these tools we can locally or remotely analysis the model result rapidly, such as extraction of data on specific location in time-sequence data sets, plotting interplanetary magnetic field lines, multi-slicing of solar wind speed, volume rendering of solar wind density, animation of time-sequence data sets, comparing between model result and observational data. To speed-up the analysis, an in-situ visualization interface is used to support visualizing the data 'on-the-fly'. We also modified some critical time-consuming analysis and visualization methods with the aid of GPU and multi-core CPU. We have used this tool to visualize the data of SIP-CESE MHD model in real time, and integrated the Database Model of shock arrival, Shock Propagation Model, Dst forecasting model and SIP-CESE MHD model developed by SIGMA Weather Group at State Key Laboratory of Space Weather/CAS.
Tariku, Tebikachew Betru; Gan, Thian Yew
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
Syrakov, D.; Prodanova, M.; Georgieva, E.
The air quality modelling system WRF-CMAQ running at the National Institute of Meteorology and Hydrology (NIMH) in Sofia was applied to the European domain for the year 2010 in the frame of the Air Quality Model Evaluation International Initiative (AQMEII), Phase 2. The model system was set up for a domain of 5000x5000 km2 size with horizontal resolution of 25 km. The models options used and the emission input are briefly outlined. The model performance was investigated based on graphical plots and statistical indexes obtained by the web-based model evaluation platform ENSEMBLE. A preliminary operational model evaluation for ozone and particulate matter was conducted, comparing simulated and observed concentrations at ground level in three sub-domains of Europe. The analysis shows model overestimation for ozone and model underestimation for particulate matter. The best statistical indicators are for ozone concentrations during summer, when comparing data for EMEP stations in the EU domain. The worse results are for PM10 winter concentration in the region of the Balkan countries. (Author)
Syrakov, M.; Prodanova, M.; Georgieva, E.
The air quality modelling system WRF-CMAQ running at the National Institute of Meteorology and Hydrology (NIMH) in Sofia was applied to the European domain for the year 2010 in the frame of the Air Quality Model Evaluation International Initiative (AQMEII), Phase 2. The model system was set up for a domain of 5000x5000 km2 size with horizontal resolution of 25 km. The models’ options used and the emission input are briefly outlined. The model performance was investigated based on graphical plots and statistical indexes obtained by the web-based model evaluation platform ENSEMBLE. A preliminary operational model evaluation for ozone and particulate matter was conducted, comparing simulated and observed concentrations at ground level in three sub-domains of Europe. The analysis shows model overestimation for ozone and model underestimation for particulate matter. The best statistical indicators are for ozone concentrations during summer, when comparing data for EMEP stations in the EU domain. The worse results are for PM10 winter concentration in the region of the Balkan countries. (Author)
of nacelle wind speeds and turbine yaws as a new set of observations to be assimilated into the Weather Research and Forecasting (WRF) Model. We present two assimilation strategies and their impact on 0-6 h forecasts for the large Danish offshore wind farm Horns Rev I. These strategies include nudging (Four...
Full Text Available The impacts of the urban heat island (UHI phenomenon on energy consumption, air quality, and human health have been widely studied and described. Mitigation strategies have been developed to fight the UHI and its detrimental consequences. A potential countermeasure is the increase of urban albedo by using cool materials. Cool materials are highly reflective materials that can maintain lower surface temperatures and thus can present an effective solution to mitigate the UHI. Terni’s proven record of high temperatures along with related environmental and comfort issues in its urban areas have reflected the local consequences of global warming. On the other hand, it promoted integrated actions by the government and research institutes to investigate solutions to mitigate the UHI effects. In this study, the main goal is to investigate the effectiveness of albedo increase as a strategy to tackle the UHI, by using the Weather Research and Forecasting (WRF mesoscale model to simulate the urban climate of Terni (Italy. Three different scenarios through a summer heat wave in the summer of 2015 are analyzed. The Base Scenario, which simulates the actual conditions of the urban area, is the control case. In the Albedo Scenario (ALB Scenario, the albedo of the roof, walls and road of the whole urban area is increased. In the Albedo-Industrial Scenario (ALB-IND Scenario, the albedo of the roof, walls and road of the area occupied by the main industrial site of Terni, located in close proximity to the city center, is increased. The simulation results show that the UHI is decreased up to 2 °C both at daytime and at nighttime in the ALB and in ALB-IND Scenarios. Peak temperatures in the urban area can be decreased by 1 °C at daytime, and by about 2 °C at nighttime. Albedo increase in the area of interest might thus represent an opportunity to decrease the UHI effect and its consequences.
Yang, Ben; Qian, Yun; Lin, Guang; Leung, Lai-Yung R.; Zhang, Yaocun
The current tuning process of parameters in global climate models is often performed subjectively, or treated as an optimization procedure to minimize the difference between model fields and observations. The later approach may be generating a set of tunable parameters that approximate the observed climate but via an unrealistic balance of physical processes and/or compensating errors over different regions in the globe. In this study, we run the Weather Research and Forecasting (WRF) regional model constrained by the reanalysis data over the Southern Great Plains (SGP) where abundant observational data from various resources are available for calibration of the input parameters and validation of the model results. Our goal is to quantify the uncertainty ranges and identify the optimal values of five key input parameters in a new Kain-Frisch (KF) convective parameterization scheme incorporated in the WRF model. A stochastic sampling algorithm, Multiple Very Fast Simulated Annealing (MVFSA), is employed to efficiently sample the input parameters in KF scheme based on the skill score so that the algorithm progressively moves toward regions of the parameter space that minimize model errors. The results based on the WRF simulations with 25-km grid spacing over the SGP show that the model bias for precipitation can be significantly reduced by using five optimal parameters identified by the MVFSA algorithm. The model performance is very sensitive to downdraft and entrainment related parameters and consumption time of Convective Available Potential Energy (CAPE). Simulated convective precipitation decreases as the ratio of downdraft to updraft flux increases. Larger CAPE consumption time results in less convective but more stratiform precipitation. The simulation using optimal parameters obtained by only constraining precipitation generates positive impact on the other output variables, such as temperature and wind. By using the optimal parameters obtained at 25 km
The goal of this study is to assess the sensitivity of regional climate simulations run with the Weather Research and Forecasting (WRF) model to the choice of datasets representing land use and land cover (LULC). Within a regional climate modeling application, an accurate repres...
Nielsen, Joakim Refslund; Dellwik, Ebba; Hahmann, Andrea N.
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...... to a control run using the default GVF data and their performances are quantified against gridded data. The verification includes 2-m temperature and precipitation. The results show that although the simulation using the new GYP product performs well, it does not significantly improve performance compared...
Wilmot, C.-S. M.; Rappenglück, B.; Li, X.; Cuchiara, G.
Air quality forecasting requires atmospheric weather models to generate accurate meteorological conditions, one of which is the development of the planetary boundary layer (PBL). An important contributor to the development of the PBL is the land-air exchange captured in the energy budget as well as turbulence parameters. Standard and surface energy variables were modeled using the fifth-generation Penn State/National Center for Atmospheric Research mesoscale model (MM5), version 3.6.1, and the Weather Research and Forecasting (WRF) model, version 3.5.1, and compared to measurements for a southeastern Texas coastal region. The study period was 28 August-1 September 2006. It also included a frontal passage. The results of the study are ambiguous. Although WRF does not perform as well as MM5 in predicting PBL heights, it better simulates energy budget and most of the general variables. Both models overestimate incoming solar radiation, which implies a surplus of energy that could be redistributed in either the partitioning of the surface energy variables or in some other aspect of the meteorological modeling not examined here. The MM5 model consistently had much drier conditions than the WRF model, which could lead to more energy available to other parts of the meteorological system. On the clearest day of the study period, MM5 had increased latent heat flux, which could lead to higher evaporation rates and lower moisture in the model. However, this latent heat disparity between the two models is not visible during any other part of the study. The observed frontal passage affected the performance of most of the variables, including the radiation, flux, and turbulence variables, at times creating dramatic differences in the r2 values.
Wilmot, C.-S. M.; Rappenglück, B.; Li, X.
Air quality forecasting requires atmospheric weather models to generate accurate meteorological conditions, one of which is the development of the planetary boundary layer (PBL). An important contributor to the development of the PBL is the land-air exchange captured in the energy budget as well as turbulence parameters. Standard and surface energy variables were modeled using the fifth-generation Penn State/National Center for Atmospheric Research mesoscale model (MM5), version 3.6.1, and the Weather Research and Forecasting (WRF) model, version 3.2.1, and compared to measurements for a southeastern Texas coastal region. The study period was 28 August-1 September 2006. It also included a frontal passage. The results of the study are ambiguous. Although WRF does not perform as well as MM5 in predicting PBL heights, it better simulates most of the general and energy budget variables. Both models overestimate incoming solar radiation, which implies a surplus of energy that could be redistributed in either the partitioning of the surface energy variables or in some other aspect of the meteorological modeling not examined here. The MM5 model consistently had much drier conditions than the WRF model, which could lead to more energy available to other parts of the meteorological system. On the clearest day of the study period MM5 had increased latent heat flux, which could lead to higher evaporation rates and lower moisture in the model. However, this latent heat disparity between the two models is not visible during any other part of the study. The observed frontal passage affected the performance of most of the variables, including the radiation, flux, and turbulence variables, at times creating dramatic differences in the r2 values.
Full Text Available This paper deals with the evaluation of parameterization schemes in the WRF model for estimation of mixing height. Numerical experiments were performed using various combinations of parameterization schemes and the results were compared with the mixing height estimated using the radiosonde observations taken by the India Meteorological Department (IMD at Mangalore site for selected days of the warm and cold season in the years 2004–2007. The results indicate that there is a large variation in the mixing heights estimated by the model using various combinations of parameterization schemes. It was seen that the physics option consisting of Mellor Yamada Janjic (Eta as the PBL scheme, Monin Obukhov Janjic (Eta as the surface layer scheme, and Noah land surface model performs reasonably well in reproducing the observed mixing height at this site for both the seasons as compared to the other combinations tested. This study also showed that the choice of the land surface model can have a significant impact on the simulation of mixing height by a prognostic model.
Lundquist, J; Glascoe, L; Obrecht, J
Accurate short-term forecasts of wind resources are required for efficient wind farm operation and ultimately for the integration of large amounts of wind-generated power into electrical grids. Siemens Energy Inc. and Lawrence Livermore National Laboratory, with the University of Colorado at Boulder, are collaborating on the design of an operational forecasting system for large wind farms. The basis of the system is the numerical weather prediction tool, the Weather Research and Forecasting (WRF) model; large-eddy simulations and data assimilation approaches are used to refine and tailor the forecasting system. Representation of the atmospheric boundary layer is modified, based on high-resolution large-eddy simulations of the atmospheric boundary. These large-eddy simulations incorporate wake effects from upwind turbines on downwind turbines as well as represent complex atmospheric variability due to complex terrain and surface features as well as atmospheric stability. Real-time hub-height wind speed and other meteorological data streams from existing wind farms are incorporated into the modeling system to enable uncertainty quantification through probabilistic forecasts. A companion investigation has identified optimal boundary-layer physics options for low-level forecasts in complex terrain, toward employing decadal WRF simulations to anticipate large-scale changes in wind resource availability due to global climate change.
Dey, Sharadia; Gupta, Srimanta; Sibanda, Precious; Chakraborty, Arun
The present study focuses on the spatio-temporal variation of nitrogen dioxide (NO2) during June 2013 to May 2015 and its futuristic emission scenario over an urban area (Durgapur) of eastern India. The concentration of ambient NO2 shows seasonal as well as site specific characteristics. The site with high vehicular density (Muchipara) shows highest NO2 concentration followed by industrial site (DVC- DTPS Colony) and the residential site (B Zone), respectively. The seasonal variation of ambient NO2 over the study area is portrayed by means of Geographical Information System based Digital Elevation Model. Out of the total urban area under consideration (114.982 km2), the concentration of NO2 exceeded the National Ambient Air Quality Standard (NAAQS) permissible limit over an area of 5.000 km2, 0.786 km2 and 0.653 km2 in post monsoon, winter and pre monsoon, respectively. Wind rose diagrams, correlation and regression analyses show that meteorology plays a crucial role in dilution and dispersion of NO2 near the earth’s surface. Principal component analysis identifies vehicular source as the major source of NO2 in all the seasons over the urban region. Coupled AMS/EPA Regulatory Model (AERMOD)–Weather Research and Forecasting (WRF) model is used for predicting the concentration of NO2. Comparison of the observed and simulated data shows that the model overestimates the concentration of NO2 in all the seasons (except winter). The results show that coupled AERMOD–WRF model can overcome the unavailability of hourly surface as well as upper air meteorological data required for predicting the pollutant concentration, but improvement of emission inventory along with better understanding of the sinks and sources of ambient NO2 is essential for capturing the more realistic scenario. PMID:28141866
Dey, Sharadia; Gupta, Srimanta; Sibanda, Precious; Chakraborty, Arun
The present study focuses on the spatio-temporal variation of nitrogen dioxide (NO2) during June 2013 to May 2015 and its futuristic emission scenario over an urban area (Durgapur) of eastern India. The concentration of ambient NO2 shows seasonal as well as site specific characteristics. The site with high vehicular density (Muchipara) shows highest NO2 concentration followed by industrial site (DVC- DTPS Colony) and the residential site (B Zone), respectively. The seasonal variation of ambient NO2 over the study area is portrayed by means of Geographical Information System based Digital Elevation Model. Out of the total urban area under consideration (114.982 km2), the concentration of NO2 exceeded the National Ambient Air Quality Standard (NAAQS) permissible limit over an area of 5.000 km2, 0.786 km2 and 0.653 km2 in post monsoon, winter and pre monsoon, respectively. Wind rose diagrams, correlation and regression analyses show that meteorology plays a crucial role in dilution and dispersion of NO2 near the earth's surface. Principal component analysis identifies vehicular source as the major source of NO2 in all the seasons over the urban region. Coupled AMS/EPA Regulatory Model (AERMOD)-Weather Research and Forecasting (WRF) model is used for predicting the concentration of NO2. Comparison of the observed and simulated data shows that the model overestimates the concentration of NO2 in all the seasons (except winter). The results show that coupled AERMOD-WRF model can overcome the unavailability of hourly surface as well as upper air meteorological data required for predicting the pollutant concentration, but improvement of emission inventory along with better understanding of the sinks and sources of ambient NO2 is essential for capturing the more realistic scenario.
Tsai, T. C.; Chen, J. P.; Dearden, C.
The wide variety of ice crystal shapes and growth habits makes it a complicated issue in cloud models. This study developed the bulk ice adaptive habit parameterization based on the theoretical approach of Chen and Lamb (1994) and introduced a 6-class hydrometeors double-moment (mass and number) bulk microphysics scheme with gamma-type size distribution function. Both the proposed schemes have been implemented into the Weather Research and Forecasting model (WRF) model forming a new multi-moment bulk microphysics scheme. Two new moments of ice crystal shape and volume are included for tracking pristine ice's adaptive habit and apparent density. A closure technique is developed to solve the time evolution of the bulk moments. For the verification of the bulk ice habit parameterization, some parcel-type (zero-dimension) calculations were conducted and compared with binned numerical calculations. The results showed that: a flexible size spectrum is important in numerical accuracy, the ice shape can significantly enhance the diffusional growth, and it is important to consider the memory of growth habit (adaptive growth) under varying environmental conditions. Also, the derived results with the 3-moment method were much closer to the binned calculations. A field campaign of DIAMET was selected to simulate in the WRF model for real-case studies. The simulations were performed with the traditional spherical ice and the new adaptive shape schemes to evaluate the effect of crystal habits. Some main features of narrow rain band, as well as the embedded precipitation cells, in the cold front case were well captured by the model. Furthermore, the simulations produced a good agreement in the microphysics against the aircraft observations in ice particle number concentration, ice crystal aspect ratio, and deposition heating rate especially within the temperature region of ice secondary multiplication production.
Full Text Available One of the dominant uncertainties in inverse estimates of regional CO2 surface-atmosphere fluxes is related to model errors in vertical transport within the planetary boundary layer (PBL. In this study we present the results from a synthetic experiment using the atmospheric model WRF-VPRM to realistically simulate transport of CO2 for large parts of the European continent at 10 km spatial resolution. To elucidate the impact of vertical mixing error on modeled CO2 mixing ratios we simulated a month during the growing season (August 2006 with different commonly used parameterizations of the PBL (Mellor-Yamada-Janjić (MYJ and Yonsei-University (YSU scheme. To isolate the effect of transport errors we prescribed the same CO2 surface fluxes for both simulations. Differences in simulated CO2 mixing ratios (model bias were on the order of 3 ppm during daytime with larger values at night. We present a simple method to reduce this bias by 70–80% when the true height of the mixed layer is known.
Foster, J. H.; Cossu, F.; Amelung, F.; Businger, S.; Cherubini, T.
The complex spatial and temporal changes in the atmospheric propagation delay of the radar signal remain the single biggest factor limiting Interferometric Synthetic Aperture Radar's (InSAR) potential for hazard monitoring and mitigation. A new generation of InSAR systems is being built and launched, and optimizing the science and hazard applications of these systems requires advanced methodologies to mitigate tropospheric noise. We present preliminary results from an investigation into the application of GPS and numerical weather models for generating tropospheric correction fields. We use the Weather Research and Forecasting (WRF) model to generate a 900 m spatial resolution atmospheric model covering the Big Island of Hawaii and an even higher, 300 m resolution grid over Mauna Loa and Kilauea volcanoes. By comparing a range of approaches, from the simplest, using reanalyses based on typically available meteorological observations, through to the "kitchen-sink" approach of assimilating all relevant data sets into our custom analyses, we examine the impact of the additional data sets on the atmospheric models and their effectiveness in correcting InSAR data. We focus particularly on the assimilation of information from the more than 60 GPS sites in the island. We ingest zenith tropospheric delay estimates from these sites directly into the WRF analyses, and also perform double-difference tomography using the phase residuals from the GPS processing to robustly incorporate information on atmospheric heterogeneity from the GPS data into the models. We assess our performance through comparisons of our atmospheric models with external observations not ingested into the model, and through the effectiveness of the derived phase screens in reducing InSAR variance. This work will produce best-practice recommendations for the use of weather models for InSAR correction, and inform efforts to design a global strategy for the NISAR mission, for both low-latency and definitive
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
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 an overview of the measurements conducted for this study. In addition to 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 difference between the model calculation and the measurement are mostly smaller than 30%, except the calculations of HONO at PD (Pudong and CO 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-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-limited condition. The threshold value is strongly dependent on the emission ratio of NOx/VOCs. When the ratio is about 0.4, the Shanghai region is under a strong VOC-limited condition over the
Hernández-Ceballos, M. A.; Adame, J. A.; Bolívar, J. P.; De la Morena, B. A.
Located in the southwest of the Iberian Peninsula, the Guadalquivir valley is a site of frequent problems related to air pollution. The atmospheric dynamics of this region is poorly characterised but is fundamental to understanding the chemical and photochemical processes that contribute to the pollution problems. In this work, the atmospheric mesoscale Weather Research and Forecasting (WRF-ARW) model was used to study the horizontal and vertical development of the two sea-land breeze patterns (pure and non-pure) that are identified in the coastal area as being responsible for many of the air pollution events. In addition, data from five meteorological stations within the valley were used to validate and compare the model results. The FNL archives were used to define the initial and boundary conditions of the model. Four domains with a grid resolution of 81, 27, 9 and 3 km and 40 sigma pressure levels in each domain were defined. The Medium Range and Forecast (MRF) parameterisation scheme was used with new values for both the bulk critical Richardson number and the coefficient of proportionality. This new configuration was obtained from the sensitivity exercises. Several periods were modelled for both breeze patterns, focusing on the wind, the potential temperatures and the specific humidity fields. For the pure breeze, the horizontal movement along the valley was conditioned by the arrival of a Mediterranean flow in the Guadalquivir valley that limits the horizontal extension of the breeze to 20-40 km inland. In contrast, the non-pure pattern was only identified in the coastal area; although motivated by the entrance of southwestern flows, a marine air mass transport along the valley was detected and reached inland areas located approximately 200 km from the coast line. In both cases, the model results indicated the formation of a thermal internal boundary layer with a vertical development of less than 500 m for the pure sea breeze while for the non-pure breeze
Morin, C.; Quattrochi, D. A.; Zavodsky, B.; Case, J.
Dengue fever (DF) is an important mosquito transmitted disease that is strongly influenced by meteorological and environmental conditions. Recent research has focused on forecasting DF case numbers based on meteorological data. However, these forecasting tools have generally relied on empirical models that require long DF time series to train. Additionally, their accuracy has been tested retrospectively, using past meteorological data. Consequently, the operational utility of the forecasts are still in question because the error associated with weather and climate forecasts are not reflected in the results. Using up-to-date weekly dengue case numbers for model parameterization and weather forecast data as meteorological input, we produced weekly forecasts of DF cases in San Juan, Puerto Rico. Each week, the past weeks' case counts were used to re-parameterize a process-based DF model driven with updated weather forecast data to generate forecasts of DF case numbers. Real-time weather forecast data was produced using the Weather Research and Forecasting (WRF) numerical weather prediction (NWP) system enhanced using additional high-resolution NASA satellite data. This methodology was conducted in a weekly iterative process with each DF forecast being evaluated using county-level DF cases reported by the Puerto Rico Department of Health. The one week DF forecasts were accurate especially considering the two sources of model error. First, weather forecasts were sometimes inaccurate and generally produced lower than observed temperatures. Second, the DF model was often overly influenced by the previous weeks DF case numbers, though this phenomenon could be lessened by increasing the number of simulations included in the forecast. Although these results are promising, we would like to develop a methodology to produce longer range forecasts so that public health workers can better prepare for dengue epidemics.
Kerandi, Noah; Arnault, Joel; Laux, Patrick; Wagner, Sven; Kitheka, Johnson; Kunstmann, Harald
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.
Iguchi, T.; Matsui, T.; Li, X.; Shi, J. J.; Tao, W.
The next-generation Global Precipitation Measurement (GPM) mission will offer a global view of precipitation systems including over middle and high latitudes and enable accurate measurement of frozen precipitation and light rainfall. The project of a synthetic GPM simulator was proposed to offer a vitual cloud libraty (VCL) to support development of the retrieval algorithm. The VCL is composed of ground validation (GV)-constrained 3D database of cloud resolving model (CRM) output and simulated GPM L1 product. The satellite retrieval algorithm can be cross-checked with a physical-based approach by using the VCL as a priori database. The first experiment for making VCL is planned for a snowfall event during the Canadian CloudSAT/CALIPSO Validation Project (C3VP) field campaign. This campaign was took place at the site located between the Lakes Huron and Ontario in south central Ontario, Canada. A cold wind passing over the lakes causes a snowstorm specific to areas over the lee side during winter season. Shi et al.  showed a numerical simulation of the lake-effect snowstorm on Jan. 20, 2007 using the Weather and Research Forecasting (WRF) model with newly implemented the Goddard microphysics scheme (1-moment bulk for 2-water, 3-ice classes). The simulation reasonably represented the locally intensive frozen precipitation in agreement with King-city C-band radar observation. The structures of ice clouds were generally consistent with those in CloudSat and AMSU-B observations also. This study is aimed at a follow-up study of their research using the WRF in conjunction with the spectral bin microphysics for clouds (WRF-SBM), especially targeted to cloud microphysics of the snowfall event. This SBM (1-moment 33 bins for 1-water, 6-ice classes) is based on the Hebrew University Cloud Model (HUCM) [e.g., Khain et al., 2000; Iguchi et al., 2008, Appendix A]. We will offer a discussion of ice cloud microphysics on a lake-effect snowstorm with sensitivity tests to
Full Text Available 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.
Kirova, Hristina; Batchvarova, Ekaterina; Gryning, Sven-Erik
The boundary-layer processes in High Arctic area are studied based on consecutive radiosoundings and numerical simulations with Weather Research and Forecasting (WRF) model version 3.3.1 during a late winter period. The measurements consist of about 30 radiosondings performed every 12 hours...
VinodKumar, K.; Soumya, M.; Tkalich, P.; Vethamony, P.
Cyclone `Thane` developed over the southeast Bay of Bengal (BoB) at 88.5 degree E, 8.5degree N during 25-31 December 2011.Simulations have been carried out using Weather Research and Forecasting (WRF) model to generate fine resolution winds...
Full Text Available The Amazon region as a large source of methane (CH4 contributes significantly to the global annual CH4 budget. For the first time in the Amazon region, 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 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 map with inundated area changing in time represents 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 of the Amazon lowland region 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
Carotenuto, Federico; Gioli, Beniamino; Toscano, Piero; Gualtieri, Giovanni; Miglietta, Franco; Wohlfahrt, Georg
An intensive aerial campaign was flown in the context of the CARBIUS project (Maselli et al., 2010) between July 2004 and December 2005. The flights covered, over more than 240 Km, a target area in central Italy (between the regions of Lazio and Tuscany) characterized by various land uses and topography, ranging from coastal zones to mountainous landscapes (Colline Metallifere, Tuscany). The aerial vector (Sky Arrow 650 ERA) was equipped for high frequency (50 Hz) measurements of the three components of mean wind and turbulence, as well as air temperature, CO2 and H2O concentrations. While the aim of the CARBIUS campaign was focused on GHG fluxes, the dataset is used in the present work as a benchmark to assess the capability of mesoscale models to correctly simulate transport fields. A first assessment has been done by comparing the dataset to a coupled WRF-NMM-CALMET system (Gioli et al., 2014), but the aim of the present work is to expand on those foundations by comparing the data to higher resolution WRF-ARW simulations. WRF-ARW outputs are, in fact, frequently used as inputs to multiple dispersion models and any misrepresentation of the "real" situation is therefore propagated through the modelling chain. Our aim is to assess these potential errors keeping into account different topographic situations and seasons thanks to the existent aerial dataset. Moreover the sensitivity of the WRF-ARW model to different initial and boundary conditions (ECMWF vs. CFSR) is explored, since also the initial forcing may influence the representation of the transport field. Results show that the model is generally capable of reproducing the main features of the mean wind field independently from the choice of the initial forcing. Terrain features still show an impact on the model outputs (especially on wind directions), moreover the performance of the model is also influenced by seasonal effects. Gioli B., Gualtieri G., Busillo C., Calastrini F., Gozzini B., Miglietta F. (2014
Full Text Available A WRF-CMAQ modeling system is used to assess the impact of emission control strategies and weather conditions on haze pollution in Zhongshan, Guangdong Province, China. One-month simulations for January 2014 are completed and evaluated with the observational data. The simulations show reasonable agreement with the observations. Several sensitivity studies are completed to quantify the percentage contributions of local emissions versus regional emissions to the PM2.5 concentrations under different weather conditions. The results indicate that the contributions from local emission is higher than those of the emissions from regional transport when there is no intrusion of cold front (i.e., 58% contribution from local emission versus 42% contribution from the regional transport. The contribution of regional transport is increased to 76% when a strong cold front appears. Furthermore, the sensitivity study demonstrates that PM2.5 concentrations on the first, second, and third days are reduced by 47%, 52%, and 58%, respectively, after the local emissions are turned off when there is no intrusion of cold front. Finally, a case study shows that industrial, residential, and mobile emissions account for 24%, 22%, and 15% of the change of PM2.5, respectively, during a heavy haze pollution event in Zhongshan.
Yahya, Khairunnisa; Campbell, Patrick; Zhang, Yang
Following a comprehensive model evaluation, this Part II paper presents projected changes in future (2046-2055) climate, air quality, and their interactions under the RCP4.5 and RCP8.5 scenarios using the Weather, Research and Forecasting model with Chemistry (WRF/Chem). In general, both WRF/Chem RCP4.5 and RCP8.5 simulations predict similar increases on average (∼2 °C) for 2-m temperature (T2) but different spatial distributions of the projected changes in T2, 2-m relative humidity, 10-m wind speed, precipitation, and planetary boundary layer height, due to differences in the spatial distributions of projected emissions, and their feedbacks into climate. Future O3 mixing ratios will decrease for most parts of the U.S. under the RCP4.5 scenario but increase for all areas under the RCP8.5 scenario due to higher projected temperature, greenhouse gas concentrations and biogenic volatile organic compounds (VOC) emissions, higher O3 values for boundary conditions, and disbenefit of NOx reduction and decreased NO titration over VOC-limited O3 chemistry regions. Future PM2.5 concentrations will decrease for both RCP4.5 and RCP8.5 scenarios with different trends in projected concentrations of individual PM species. Total cloud amounts decrease under both scenarios in the future due to decreases in PM and cloud droplet number concentration thus increased radiation. Those results illustrate the impacts of carbon policies with different degrees of emission reductions on future climate and air quality. The WRF/Chem and WRF simulations show different spatial patterns for projected changes in T2 for future decade, indicating different impacts of prognostic and prescribed gas/aerosol concentrations, respectively, on climate change.
C. A. Klich
Full Text Available We use the Weather Research and Forecasting with Chemistry (WRF-Chem online chemical transport model to simulate a middle latitude cyclone in East Asia at three different horizontal resolutions (45, 15, and 5 km grid spacing. The cyclone contains a typical warm conveyor belt (WCB with an embedded squall line that passes through an area having large surface concentrations (>400 ppbv of carbon monoxide (CO. Model output from WRF-Chem is used to compare differences between the large-scale CO vertical transport by the WCB (the 45 km simulation with the smaller-scale transport due to its convection (the 5 km simulation. Forward trajectories are calculated from WRF-Chem output using HYSPLIT. At 45 km grid spacing, the WCB exhibits gradual ascent, lofting surface CO to 6–7 km. Upon reaching the warm front, the WCB and associated CO ascend more rapidly and later turn eastward over the Pacific Ocean. Convective transport at 5 km resolution with explicitly resolved convection occurs much more rapidly, with surface CO lofted to altitudes greater than 10 km in 1 h or less. We also compute CO vertical mass fluxes to compare differences in transport due to the different grid spacings. Upward CO flux exceeds 110 000 t h−1 in the domain with explicit convection when the squall line is at peak intensity, while fluxes from the two coarser resolutions are an order of magnitude smaller. Specific areas of interest within the 5 km domain are defined to compare the magnitude of convective transport to that within the entire 5 km region. Although convection encompasses only a small portion of the 5 km domain, it is responsible for ~40% of the upward CO transport. We also examine the vertical transport due to a short wave trough and its associated area of convection, not related to the cyclone, that lofts CO to the upper troposphere. Results indicate that fine-scale resolution with explicitly resolved convection is important when assessing the vertical transport of
Yang, B.; Qian, Y.; Lin, G.; Leung, R.; Zhang, Y.
The current tuning process of parameters in global climate models is often performed subjectively or treated as an optimization procedure to minimize model biases based on observations. While the latter approach may provide more plausible values for a set of tunable parameters to approximate the observed climate, the system could be forced to an unrealistic physical state or improper balance of budgets through compensating errors over different regions of the globe. In this study, the Weather Research and Forecasting (WRF) model was used to provide a more flexible framework to investigate a number of issues related uncertainty quantification (UQ) and parameter tuning. The WRF model was constrained by reanalysis of data over the Southern Great Plains (SGP), where abundant observational data from various sources was available for calibration of the input parameters and validation of the model results. Focusing on five key input parameters in the new Kain-Fritsch (KF) convective parameterization scheme used in WRF as an example, the purpose of this study was to explore the utility of high-resolution observations for improving simulations of regional patterns and evaluate the transferability of UQ and parameter tuning across physical processes, spatial scales, and climatic regimes, which have important implications to UQ and parameter tuning in global and regional models. A stochastic importance sampling algorithm, Multiple Very Fast Simulated Annealing (MVFSA) was employed to efficiently sample the input parameters in the KF scheme based on a skill score so that the algorithm progressively moved toward regions of the parameter space that minimize model errors. The results based on the WRF simulations with 25-km grid spacing over the SGP showed that the precipitation bias in the model could be significantly reduced when five optimal parameters identified by the MVFSA algorithm were used. The model performance was found to be sensitive to downdraft- and entrainment
Full Text Available The current tuning process of parameters in global climate models is often performed subjectively or treated as an optimization procedure to minimize model biases based on observations. While the latter approach may provide more plausible values for a set of tunable parameters to approximate the observed climate, the system could be forced to an unrealistic physical state or improper balance of budgets through compensating errors over different regions of the globe. In this study, the Weather Research and Forecasting (WRF model was used to provide a more flexible framework to investigate a number of issues related uncertainty quantification (UQ and parameter tuning. The WRF model was constrained by reanalysis of data over the Southern Great Plains (SGP, where abundant observational data from various sources was available for calibration of the input parameters and validation of the model results. Focusing on five key input parameters in the new Kain-Fritsch (KF convective parameterization scheme used in WRF as an example, the purpose of this study was to explore the utility of high-resolution observations for improving simulations of regional patterns and evaluate the transferability of UQ and parameter tuning across physical processes, spatial scales, and climatic regimes, which have important implications to UQ and parameter tuning in global and regional models. A stochastic importance sampling algorithm, Multiple Very Fast Simulated Annealing (MVFSA was employed to efficiently sample the input parameters in the KF scheme based on a skill score so that the algorithm progressively moved toward regions of the parameter space that minimize model errors.
The results based on the WRF simulations with 25-km grid spacing over the SGP showed that the precipitation bias in the model could be significantly reduced when five optimal parameters identified by the MVFSA algorithm were used. The model performance was found to be sensitive to
Full Text Available The current tuning process of parameters in global climate models is often performed subjectively or treated as an optimization procedure to minimize model biases based on observations. While the latter approach may provide more plausible values for a set of tunable parameters to approximate the observed climate, the system could be forced to an unrealistic physical state or improper balance of budgets through compensating errors over different regions of the globe. In this study, the Weather Research and Forecasting (WRF model was used to provide a more flexible framework to investigate a number of issues related uncertainty quantification (UQ and parameter tuning. The WRF model was constrained by reanalysis of data over the Southern Great Plains (SGP, where abundant observational data from various sources was available for calibration of the input parameters and validation of the model results. Focusing on five key input parameters in the new Kain-Fritsch (KF convective parameterization scheme used in WRF as an example, the purpose of this study was to explore the utility of high-resolution observations for improving simulations of regional patterns and evaluate the transferability of UQ and parameter tuning across physical processes, spatial scales, and climatic regimes, which have important implications to UQ and parameter tuning in global and regional models. A stochastic important-sampling algorithm, Multiple Very Fast Simulated Annealing (MVFSA was employed to efficiently sample the input parameters in the KF scheme based on a skill score so that the algorithm progressively moved toward regions of the parameter space that minimize model errors.
The results based on the WRF simulations with 25-km grid spacing over the SGP showed that the precipitation bias in the model could be significantly reduced when five optimal parameters identified by the MVFSA algorithm were used. The model performance was found to be sensitive to
Full Text Available In this study, a regional coupled climate–chemistry modeling system using the dynamical downscaling technique was established by linking the global Community Earth System Model (CESM and the regional two-way coupled Weather Research and Forecasting – Community Multi-scale Air Quality (WRF-CMAQ model for the purpose of comprehensive assessments of regional climate change and air quality and their interactions within one modeling framework. The modeling system was applied over east Asia for a multi-year climatological application during 2006–2010, driven with CESM downscaling data under Representative Concentration Pathways 4.5 (RCP4.5, along with a short-term air quality application in representative months in 2013 that was driven with a reanalysis dataset. A comprehensive model evaluation was conducted against observations from surface networks and satellite observations to assess the model's performance. This study presents the first application and evaluation of the two-way coupled WRF-CMAQ model for climatological simulations using the dynamical downscaling technique. The model was able to satisfactorily predict major meteorological variables. The improved statistical performance for the 2 m temperature (T2 in this study (with a mean bias of −0.6 °C compared with the Coupled Model Intercomparison Project Phase 5 (CMIP5 multi-models might be related to the use of the regional model WRF and the bias-correction technique applied for CESM downscaling. The model showed good ability to predict PM2. 5 in winter (with a normalized mean bias (NMB of 6.4 % in 2013 and O3 in summer (with an NMB of 18.2 % in 2013 in terms of statistical performance and spatial distributions. Compared with global models that tend to underpredict PM2. 5 concentrations in China, WRF-CMAQ was able to capture the high PM2. 5 concentrations in urban areas. In general, the two-way coupled WRF-CMAQ model performed well for both climatological and air
Hong, Chaopeng; Zhang, Qiang; Zhang, Yang; Tang, Youhua; Tong, Daniel; He, Kebin
In this study, a regional coupled climate-chemistry modeling system using the dynamical downscaling technique was established by linking the global Community Earth System Model (CESM) and the regional two-way coupled Weather Research and Forecasting - Community Multi-scale Air Quality (WRF-CMAQ) model for the purpose of comprehensive assessments of regional climate change and air quality and their interactions within one modeling framework. The modeling system was applied over east Asia for a multi-year climatological application during 2006-2010, driven with CESM downscaling data under Representative Concentration Pathways 4.5 (RCP4.5), along with a short-term air quality application in representative months in 2013 that was driven with a reanalysis dataset. A comprehensive model evaluation was conducted against observations from surface networks and satellite observations to assess the model's performance. This study presents the first application and evaluation of the two-way coupled WRF-CMAQ model for climatological simulations using the dynamical downscaling technique. The model was able to satisfactorily predict major meteorological variables. The improved statistical performance for the 2 m temperature (T2) in this study (with a mean bias of -0.6 °C) compared with the Coupled Model Intercomparison Project Phase 5 (CMIP5) multi-models might be related to the use of the regional model WRF and the bias-correction technique applied for CESM downscaling. The model showed good ability to predict PM2. 5 in winter (with a normalized mean bias (NMB) of 6.4 % in 2013) and O3 in summer (with an NMB of 18.2 % in 2013) in terms of statistical performance and spatial distributions. Compared with global models that tend to underpredict PM2. 5 concentrations in China, WRF-CMAQ was able to capture the high PM2. 5 concentrations in urban areas. In general, the two-way coupled WRF-CMAQ model performed well for both climatological and air quality applications. The coupled
Hildebrand, E. P.
The Air Force Weather Agency (AFWA) is responsible for running and maintaining the Diagnostic Cloud Forecast (DCF) model to support DoD missions and those of their external partners. The DCF model generates three-dimensional cloud forecasts for global and regional domains at various resolutions. Regional domains are chosen based on Air Force mission needs. DCF is purely a statistical model that can be appended to any numerical weather prediction (NWP) model. Operationally, AFWA runs the DCF model deterministically using GFS data from NCEP and WRF data that are created in-house. In addition, AFWA also runs an ensemble version of the DCF model using the Mesoscale Ensemble Prediction System (MEPS). The deterministic DCF uses predictor variables from the WRF or GFS models, depending on whether the domain is regional or global, and statistically relates them to observed cloud cover from the World-Wide Merged Cloud Analysis (WWMCA). The forecast process of the model uses an ordinal logistic regression to predict membership in one of 101 groups (every 1% from 0-100%). The predicted group membership then is translated into a cloud amount. This is performed on 21 pressure levels ranging from 1000 hPa to 100 hPa. Cloud amount forecasts on these 21 levels are used along with the NWP geopotential height forecasts to estimate the base and top heights of cloud layers in the vertical. DCF also includes routines to estimate the amount and type of cloud within each layer. Forecasts of total cloud amount are verified using the WWMCA, as well as independent sources of cloud data. This presentation will include an overview of the DCF model and its use at AFWA. Results will be presented to show that DCF adds value over the raw cloud forecasts from NWP models. Ideas for future work also will be addressed.
Soares, Pedro M. M.; Cardoso, Rita M.; Lima, Daniela C. A.; Miranda, Pedro M. A.
Portugal, which is located in the west limit of the Mediterranean subtropics, is a small region with a complex orography with large precipitation gradients and interannual variability. In this study, the newer and higher resolution regional climate simulations, covering Portugal, are evaluated in present climate and used to investigate the rainfall projections for the end of the twenty-first century, following the RCP4.5 and RCP8.5 emission scenarios. The EURO-CORDEX historical simulations, at 0.11° and at 0.44° resolution, are evaluated against gridded observations of precipitation, which allows the assembly of four multi-model ensembles. An extra simulation, at even higher resolution (9 km) with WRF is also analysed. In present climate, the models are able to describe the precipitation temporal and spatial patterns as well its distributions, although there is a large spread and an overestimation of larger rainfall quantiles. The multi-model ensembles show that selecting the best performing models adds quality to the overall representation of rainfall. The high-resolution simulations augment the spatial details of precipitation, but objectively do not seem to add value with respect to the coarse resolution. Regarding the RCP8.5 scenario, WRF and the multi-model ensembles consistently predict important losses of precipitation in Portugal in spring, summer and autumn, ranging from -10% and -50%. For all seasons, the changes are more severe in the southern basins. The precipitation distributions show, for all models, important reductions of the contribution from low to moderate/high precipitation bins and augments of days with strong rainfall. Furthermore, a prominent growth of high-ranking percentiles is predicted reaching values over 70% in some regions. Generally, the changes associated with the RCP4.5 scenario have the same signal and features, but with smaller magnitudes.
Salvador, Nadir; Reis, Neyval Costa; Santos, Jane Meri; Albuquerque, Taciana Toledo de Almeida; Loriato, Ayres Geraldo; Delbarre, Hervé; Augustin, Patrick; Sokolov, Anton; Moreira, Davidson Martins
Three atmospheric boundary layer (ABL) schemes and two land surface models that are used in the Weather Research and Forecasting (WRF) model, version 3.4.1, were evaluated with numerical simulations by using data from the north coast of France (Dunkerque). The ABL schemes YSU (Yonsei University), ACM2 (Asymmetric Convective Model version 2), and MYJ (Mellor-Yamada-Janjic) were combined with two land surface models, Noah and RUC (Rapid Update Cycle), in order to determine the performances under sea-breeze conditions. Particular attention is given in the determination of the thermal internal boundary layer (TIBL), which is very important in air pollution scenarios. The other physics parameterizations used in the model were consistent for all simulations. The predictions of the sea-breeze dynamics output from the WRF model were compared with observations taken from sonic detection and ranging, light detection and ranging systems and a meteorological surface station to verify that the model had reasonable accuracy in predicting the behavior of local circulations. The temporal comparisons of the vertical and horizontal wind speeds and wind directions predicted by the WRF model showed that all runs detected the passage of the sea-breeze front. However, except for the combination of MYJ and Noah, all runs had a time delay compared with the frontal passage measured by the instruments. The proposed study shows that the synoptic wind attenuated the intensity and penetration of the sea breeze. This provided changes in the vertical mixing in a short period of time and on soil temperature that could not be detected by the WRF model simulations with the computational grid used. Additionally, among the tested schemes, the combination of the localclosure MYJ scheme with the land surface Noah scheme was able to produce the most accurate ABL height compared with observations, and it was also able to capture the TIBL.
ElSaadani, M.; Quintero, F.; Goska, R.; Krajewski, W. F.; Lahmers, T.; Small, S.; Gochis, D. J.
This study examines the performance of different Hydrologic models in estimating peak flows over the state of Iowa. In this study I will compare the output of the Iowa Flood Center (IFC) hydrologic model and WRF-Hydro (NFIE configuration) to the observed flows at the USGS stream gauges. During the National Flood Interoperability Experiment I explored the performance of WRF-Hydro over the state of Iowa using different rainfall products and the resulting hydrographs showed a "flashy" behavior of the model output due to lack of calibration and bad initial flows due to short model spin period. I would like to expand this study by including a second well established hydrologic model and include more rain gauge vs. radar rainfall direct comparisons. The IFC model is expected to outperform WRF-Hydro's out of the box results, however, I will test different calibration options for both the Noah-MP land surface model and RAPID, which is the routing component of the NFIE-Hydro configuration, to see if this will improve the model results. This study will explore the statistical structure of model output uncertainties across scales (as a function of drainage areas and/or stream orders). I will also evaluate the performance of different radar-based Quantitative Precipitation Estimation (QPE) products (e.g. Stage IV, MRMS and IFC's NEXRAD based radar rainfall product. Different basins will be evaluated in this study and they will be selected based on size, amount of rainfall received over the basin area and location. Basin location will be an important factor in this study due to our prior knowledge of the performance of different NEXRAD radars that cover the region, this will help observe the effect of rainfall biases on stream flows. Another possible addition to this study is to apply controlled spatial error fields to rainfall inputs and observer the propagation of these errors through the stream network.
Floors, Rogier; Pena Diaz, Alfredo; Vincent, Claire Louise;
in the amount of observed low level jet. The wind speed predicted by WRF does not improve when a higher resolution is used. Therefore, both the inhomogeneous (westerly) and homogeneous (easterly) flow contribute to a large negative bias in the mean wind speed profile at heights between 100 and 200 m....
Göndöcs, Júlia; Breuer, Hajnalka; Pongrácz, Rita; Bartholy, Judit
The population of Earth is continuously growing, and due to urbanisation it is quite concentrated in metropolitan areas. Overall, cities cover almost 2% of the global surface causing several environmental and social issues. These artificial surface covers significantly modify the surface energy exchange processes through modification of naturally covered lands resulting in altered local wind and temperature patterns because of the presence of buildings. The architectures' three-dimensional extensions certainly affect the incoming radiation, the sky-view factors as well, as the 3D wind fields, resulting in specific local microclimate at each metropolitan area. The increased temperature in the central built-up areas and the cooler surrounding of the cities lead to the urban heat island phenomenon, which is widely studied both with observations and numerical models. The Weather Research and Forecasting (WRF) mesoscale model coupled to multilayer urban canopy parameterisation is used to investigate this phenomenon for Budapest and its surroundings. Before starting the simulations, the detailed surface has to be set up according to the actual conditions, for which CORINE and OpenStreetMap databases are used, both including buildings, different land use categories, and waterbodies. The new land use distribution serving as input for WRF runs distinguishes three urban categories: (i) low-intensity residential, (ii) high-intensity residential, and (iii) commercial/industrial. For the simulations the initial meteorological fields are derived from the publicly available GFS (Global Forecast System) outputs. Simulations are completed for one-week-long periods in summer and winter in 2015, for which we selected periods with the atmospheric conditions of weak wind and clear sky. In order to keep the stability of the simulations, the entire downscaling is carried out in several steps using gradually smaller domains embedded to each other. Thus, three embedded target areas have
WANG Shu-chang; HUANG Si-xun; ZHANG Wei-min; ZHU Xiao-qian; CAO Xiao-qun; LI Yi
Initialization and initial imbalance problem were discussed in the context of a three-dimensional variational data assimilation system of the new generation "Weather Research and Forecasting Model". Severaloptions of digital filter initialization have been tested with a rain storm case. It is shown that digital filter initialization, especially diabatic digital filter initialization and twice digital filter initialization, have effectively removed spurious high frequency noise from initial data for numerical weather prediction and produced balanced initial conditions. For six consecutive intermittent data assimilation cycles covering a 3-day period, mean initialization increments and impact on forecast variables are studied. DFI has been demonstrated to provide better adjustment of the hydrometeors and vertical velocity, reduced spin-up time, and improved forecast variables quantity.
Toth, Gabor; vanderHolst, Bart; Sokolov, Igor V.; DeZeeuw, Darren; Gombosi, Tamas I.; Fang, Fang; Manchester, Ward B.; Meng, Xing; Nakib, Dalal; Powell, Kenneth G.; Stout, Quentin F.; Glocer, Alex; Ma, Ying-Juan; Opher, Merav
Space weather describes the various processes in the Sun-Earth system that present danger to human health and technology. The goal of space weather forecasting is to provide an opportunity to mitigate these negative effects. Physics-based space weather modeling is characterized by disparate temporal and spatial scales as well as by different physics in different domains. A multi-physics system can be modeled by a software framework comprising of several components. Each component corresponds to a physics domain, and each component is represented by one or more numerical models. The publicly available Space Weather Modeling Framework (SWMF) can execute and couple together several components distributed over a parallel machine in a flexible and efficient manner. The framework also allows resolving disparate spatial and temporal scales with independent spatial and temporal discretizations in the various models. Several of the computationally most expensive domains of the framework are modeled by the Block-Adaptive Tree Solar wind Roe Upwind Scheme (BATS-R-US) code that can solve various forms of the magnetohydrodynamics (MHD) equations, including Hall, semi-relativistic, multi-species and multi-fluid MHD, anisotropic pressure, radiative transport and heat conduction. Modeling disparate scales within BATS-R-US is achieved by a block-adaptive mesh both in Cartesian and generalized coordinates. Most recently we have created a new core for BATS-R-US: the Block-Adaptive Tree Library (BATL) that provides a general toolkit for creating, load balancing and message passing in a 1, 2 or 3 dimensional block-adaptive grid. We describe the algorithms of BATL and demonstrate its efficiency and scaling properties for various problems. BATS-R-US uses several time-integration schemes to address multiple time-scales: explicit time stepping with fixed or local time steps, partially steady-state evolution, point-implicit, semi-implicit, explicit/implicit, and fully implicit numerical
Yu, Lingxue; Liu, Tingxiang; Bu, Kun; Yang, Jiuchun; Chang, Liping; Zhang, Shuwen
The snow cover extent in mid-high latitude areas of the Northern Hemisphere has significantly declined corresponding to the global warming, especially since the 1970s. Snow-climate feedbacks play a critical role in regulating the global radiation balance and influencing surface heat flux exchange. However, the degree to which snow cover changes affect the radiation budget and energy balance on a regional scale and the difference between snow-climate and land use/cover change (LUCC)-climate feedbacks have been rarely studied. In this paper, we selected Heilongjiang Basin, where the snow cover has changed obviously, as our study area and used the WRF model to simulate the influences of snow cover changes on the surface radiation budget and heat balance. In the scenario simulation, the localized surface parameter data improved the accuracy by 10 % compared with the control group. The spatial and temporal analysis of the surface variables showed that the net surface radiation, sensible heat flux, Bowen ratio, temperature and percentage of snow cover were negatively correlated and that the ground heat flux and latent heat flux were positively correlated with the percentage of snow cover. The spatial analysis also showed that a significant relationship existed between the surface variables and land cover types, which was not obviously as that for snow cover changes. Finally, six typical study areas were selected to quantitatively analyse the influence of land cover types beneath the snow cover on heat absorption and transfer, which showed that when the land was snow covered, the conversion of forest to farmland can dramatically influence the net radiation and other surface variables, whereas the snow-free land showed significantly reduced influence. Furthermore, compared with typical land cover changes, e.g., the conversion of forest into farmland, the influence of snow cover changes on net radiation and sensible heat flux were 60 % higher than that of land cover changes
Barrera, Y.; Nehrkorn, T.; Hegarty, J. D.; Wofsy, S. C.; Gottlieb, E.; Sargent, M. R.; Decola, P.; Jones, T.
Simulation of the planetary boundary layer (PBL) and residual layer (RL) are key requirements for forecasting air quality in cities and detecting transboundary air pollution events. This study combines information from a network of Mini Micropulse Lidar (MPL) instruments, the CALIOP satellite, meteorological and air pollution measuring sensors, and a particle-transport model to critically test mesoscale transport models at the regional level. Aerosol backscattering measurements were continuously taken with MPL units in various locations within the Northeastern U.S., between September 2012 to August 2015. Data is analyzed using wavelet covariance transforms and image processing techniques. Initial results for the city of Boston show a PBL growth rate between approx. 150 and 300 meters per hour, in the morning to early afternoon (~12-19 UTC). The RL was present throughout the night and day at approx. 1.3 to 2.0 km. Transboundary air pollution events were detected and quantified, and variations in concentrations of greenhouse gases and aerosols were also evaluated. Results were compared to information retrieved from Weather and Research Forecasting (WRF) model and the Stochastic Time-Inverted Lagrangian Transport (STILT) model.
Arnault, Joel; Rummler, Thomas; Baur, Florian; Lerch, Sebastian; Wagner, Sven; Fersch, Benjamin; Zhang, Zhenyu; Kerandi, Noah; Keil, Christian; Kunstmann, Harald
Precipitation predictability can be assessed by the spread within an ensemble of atmospheric simulations being perturbed in the initial, lateral boundary conditions and/or modeled processes within a range of uncertainty. Surface-related processes are more likely to change precipitation when synoptic forcing is weak. This study investigates the effect of uncertainty in the representation of terrestrial water flows on precipitation predictability. The tools used for this investigation are the Weather Research and Forecasting (WRF) model and its hydrologically-enhanced version WRF-Hydro, applied over Central Europe during April-October 2008. The WRF grid is that of COSMO-DE, with a resolution of 2.8 km. In WRF-Hydro, the WRF grid is coupled with a sub-grid at 280 m resolution to resolve lateral terrestrial water flows. Vertical flow uncertainty is considered by modifying the parameter controlling the partitioning between surface runoff and infiltration in WRF, and horizontal flow uncertainty is considered by comparing WRF with WRF-Hydro. Precipitation predictability is deduced from the spread of an ensemble based on three turbulence parameterizations. Model results are validated with E-OBS precipitation and surface temperature, ESA-CCI soil moisture, FLUXNET-MTE surface evaporation and GRDC discharge. It is found that the uncertainty in the representation of terrestrial water flows is more likely to significantly affect precipitation predictability when surface flux spatial variability is high. In comparison to the WRF ensemble, WRF-Hydro slightly improves the adjusted continuous ranked probability score of daily precipitation. The reproduction of observed daily discharge with Nash-Sutcliffe model efficiency coefficients up to 0.91 demonstrates the potential of WRF-Hydro for flood forecasting.
Saba, Tanzila; Rehman, Amjad; AlGhamdi, Jarallah S.
Making deductions and expectations about climate has been a challenge all through mankind's history. Challenges with exact meteorological directions assist to foresee and handle problems well in time. Different strategies have been investigated using various machine learning techniques in reported forecasting systems. Current research investigates climate as a major challenge for machine information mining and deduction. Accordingly, this paper presents a hybrid neural model (MLP and RBF) to enhance the accuracy of weather forecasting. Proposed hybrid model ensure precise forecasting due to the specialty of climate anticipating frameworks. The study concentrates on the data representing Saudi Arabia weather forecasting. The main input features employed to train individual and hybrid neural networks that include average dew point, minimum temperature, maximum temperature, mean temperature, average relative moistness, precipitation, normal wind speed, high wind speed and average cloudiness. The output layer composed of two neurons to represent rainy and dry weathers. Moreover, trial and error approach is adopted to select an appropriate number of inputs to the hybrid neural network. Correlation coefficient, RMSE and scatter index are the standard yard sticks adopted for forecast accuracy measurement. On individual standing MLP forecasting results are better than RBF, however, the proposed simplified hybrid neural model comes out with better forecasting accuracy as compared to both individual networks. Additionally, results are better than reported in the state of art, using a simple neural structure that reduces training time and complexity.
Tao, Wei-Kuo; Wu, Di; Matsui, Toshi; Li, Xiaowen; Zeng, Xiping; Peter-Lidard, Christa; Hou, Arthur
One of major CRM approaches to studying precipitation processes is sometimes referred to as "cloud ensemble modeling". This approach allows many clouds of various sizes and stages of their lifecycles to be present at any given simulation time. Large-scale effects derived from observations are imposed into CRMs as forcing, and cyclic lateral boundaries are used. The advantage of this approach is that model results in terms of rainfall and QI and Q2 usually are in good agreement with observations. In addition, the model results provide cloud statistics that represent different types of clouds/cloud systems during their lifetime (life cycle). The large-scale forcing derived from MC3EI will be used to drive GCE model simulations. The model-simulated results will be compared with observations from MC3E. These GCE model-simulated datasets are especially valuable for LH algorithm developers. In addition, the regional scale model with very high-resolution, NASA Unified WRF is also used to real time forecast during the MC3E campaign to ensure that the precipitation and other meteorological forecasts are available to the flight planning team and to interpret the forecast results in terms of proposed flight scenarios. Post Mission simulations are conducted to examine the sensitivity of initial and lateral boundary conditions to cloud and precipitation processes and rainfall. We will compare model results in terms of precipitation and surface rainfall using GCE model and NU-WRF
Bilal, M.; Solbakken, K.; Birkelund, Y.
In this study, the performance of the mesoscale meteorological Weather Research and Forecast (WRF) model coupled with the microscale computational fluid dynamics based model WindSim is investigated and compared to the performance of WRF alone. The two model set-ups, WRF and WRF-WindSim, have been tested on three high-wind events in February, June and October, over a complex terrain at the Nygårdsfjell wind park in Norway. The wind speeds and wind directions are compared to measurements and the results are evaluated based on root mean square error, bias and standard deviation error. Both model set-ups are able to reproduce the high wind events. For the winter month February the WRF-WindSim performed better than WRF alone, with the root mean square error (RMSE) decreasing from 2.86 to 2.38 and standard deviation error (STDE) decreasing from 2.69 to 2.37. For the two other months no such improvements were found. The best model performance was found in October where the WRF had a RMSE of 1.76 and STDE of 1.68. For June, both model set-ups underestimate the wind speed. Overall, the adopted coupling method of using WRF outputs as virtual climatology for coupling WRF and WindSim did not offer a significant improvement over the complex terrain of Nygårdsfjell. However, the proposed coupling method offers high degree of simplicity when it comes to its application. Further testing is recommended over larger number of test cases to make a significant conclusion.
Dasari, Hari Prasad
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
Gyongyosi, A. Z.; Andre, K.; Salavec, P.; Horanyi, A.; Szepszo, G.; Mille, M.; Tasnadi, P.; Weidiger, T.
. Numerical modeling became a common tool in the daily practice of weather experts forecasters due to the i) increasing user demands for weather data by the costumers, ii) the growth in computer resources, iii) numerical weather prediction systems available for integration on affordable, off the shelf computers and iv) available input data (from ECMWF or NCEP) for model integrations. Beside learning the theoretical basis, since the last year. Students in their MSc or BSc Thesis Research or in Student's Research ProjectsStudent's Research Projects h have the opportunity to run numerical models and to analyze the outputs for different purposes including wind energy estimation, simulation of the dynamics of a polar low, and subtropical cyclones, analysis of the isentropic potential vorticity field, examination of coupled atmospheric dispersion models, etc. A special course in the application of numerical modeling has been held (is being announced for the upcoming semester) (is being announced for the upcoming semester) for our students in order to improve their skills on this field. Several numerical model (NRIPR ETA and WRF) systems have been adapted in the University and integrated WRF have been tested and used for the geographical region of the Carpathian Basin (NRIPR, ETA and WRF). Recently ALADIN/CHAPEAU the academic version of the ARPEGE ALADIN cy33t1 meso-scale numerical weather prediction model system (which is the operational forecasting tool of our National Weather Service) has been installed at our Institute. ALADIN is the operational forecasting model of the Hungarian Meteorological Service and developed in the framework of the international ALADIN co-operation. Our main objectives are i) the analysis of different typical weather situations, ii) fine tuning of parameterization schemes and the iii) comparison of the ALADIN/CHAPEAU and WRF model outputs based on case studies. The necessary hardware and software innovations has have been done. In the presentation the
Full Text Available Over the Mediterranean region, elevated tropospheric ozone (O3 values are recorded, especially in summer. We use the Infrared Atmospheric Sounding Interferometer (IASI and the Weather Research and Forecasting Model with Chemistry (WRF-Chem to understand and interpret the factors and emission sources responsible for the high O3 concentrations observed in the Mediterranean troposphere. Six years of IASI data have been analyzed and show consistent maxima during summer, with an increase of up to 22% in the [0–8] km O3 column in the eastern part of the basin compared to the middle of the basin. We analyze 2010 as an example year to investigate the processes that contribute to these summer maxima. Using two modeled O3 tracers (inflow to the model domain and local anthropogenic emissions, we show that between the surface and 2 km, O3 is mostly formed from anthropogenic emissions and above 4 km, is mostly transported from outside the domain. Evidence of stratosphere to troposphere exchanges (STE in the eastern part of the basin is shown, and corresponds with low relative humidity and high potential vorticity.
Mirocha, J. D. [Lawrence Livermore National Lab. (LLNL), Livermore, CA (United States); Kosovic, B. [National Center for Atmospheric Research, Boulder, CO (United States); Aitken, M. L. [Univ. of Colorado, Boulder, CO (United States); Lundquist, J. K. [Univ. of Colorado, Boulder, CO (United States); National Renewable Energy Lab., Golden, CO (United States)
A generalized actuator disk (GAD) wind turbine parameterization designed for large-eddy simulation (LES) applications was implemented into the Weather Research and Forecasting (WRF) model. WRF-LES with the GAD model enables numerical investigation of the effects of an operating wind turbine on and interactions with a broad range of atmospheric boundary layer phenomena. Numerical simulations using WRF-LES with the GAD model were compared with measurements obtained from the Turbine Wake and Inflow Characterization Study (TWICS-2011), the goal of which was to measure both the inflow to and wake from a 2.3-MW wind turbine. Data from a meteorological tower and two light-detection and ranging (lidar) systems, one vertically profiling and another operated over a variety of scanning modes, were utilized to obtain forcing for the simulations, and to evaluate characteristics of the simulated wakes. Simulations produced wakes with physically consistent rotation and velocity deficits. Two surface heat flux values of 20 W m–2 and 100 W m–2 were used to examine the sensitivity of the simulated wakes to convective instability. Simulations using the smaller heat flux values showed good agreement with wake deficits observed during TWICS-2011, whereas those using the larger value showed enhanced spreading and more-rapid attenuation. This study demonstrates the utility of actuator models implemented within atmospheric LES to address a range of atmospheric science and engineering applications. In conclusion, validated implementation of the GAD in a numerical weather prediction code such as WRF will enable a wide range of studies related to the interaction of wind turbines with the atmosphere and surface.
Full Text Available Although ozone is an atmospheric gas with high spatial and temporal variability, mesoscale numerical weather prediction (NWP models simplify the specification of ozone concentrations used in their shortwave schemes by using a few ozone profiles. In this paper, a two-part study is presented: (i an assessment of the quality of the ozone profiles provided for use with the shortwave schemes in the Advanced Research version of the Weather Research and Forecasting (WRF-ARW model and (ii the impact of deficiencies in those profiles on the performance of model simulations of direct solar radiation. The first part compares simplified datasets used to specify the total ozone column in five schemes (i.e. Goddard, New Goddard, RRTMG, CAM and Fu–Liou–Gu with the Multi-Sensor Reanalysis dataset during the period 1979–2008 examining the latitudinal, longitudinal and seasonal limitations in the ozone modeling of each parameterization. The results indicate that the maximum deviations are over the poles due to the Brewer–Dobson circulation and there are prominent longitudinal patterns in the departures due to quasi-stationary features forced by the land–sea distribution. In the second part, the bias in the simulated direct solar radiation due to these deviations from the simplified spatial and temporal representation of the ozone distribution is analyzed for the New Goddard and CAM schemes using the Beer–Lambert–Bouger law. For radiative applications those simplifications introduce spatial and temporal biases with near-zero departures over the tropics during all the year and increasing poleward with a maximum in the high middle latitudes during the winter of each hemisphere.
Full Text Available The Hong Kong Observatory (HKO is planning to implement a fine-resolution Numerical Weather Prediction (NWP model for supporting the aviation weather applications at the Hong Kong International Airport (HKIA. This new NWP model system, called Aviation Model (AVM, is configured at a horizontal grid spacing of 600 m and 200 m. It is based on the WRF-ARW (Advance Research WRF model that can have sufficient computation efficiency in order to produce hourly updated forecasts up to 9 hours ahead on a future high performance computer system with theoretical peak performance of around 10 TFLOPS. AVM will be nested inside the operational mesoscale NWP model of HKO with horizontal resolution of 2 km. In this paper, initial numerical experiment results in forecast of windshear events due to seabreeze and terrain effect are discussed. The simulation of sea-breeze-related windshear is quite successful, and the headwind change observed from flight data could be reproduced in the model forecast. Some impacts of physical processes on generating the fine-scale wind circulation and development of significant convection are illustrated. The paper also discusses the limitations in the current model setup and proposes methods for the future development of AVM.
Full Text Available Although ozone is an atmospheric gas with high spatial and temporal variability, mesoscale numerical weather prediction (NWP models simplify the specification of ozone concentrations used in their shortwave schemes by using a few ozone profiles. In this paper, a two-part study is presented: (i an evaluation of the quality of the ozone profiles provided for use with the shortwave schemes in the Advanced Research version of the Weather Research and Forecasting (WRF-ARW model and (ii an assessment of the impact of deficiencies in those profiles on the performance of model simulations of direct solar radiation. The first part compares simplified data sets used to specify the total ozone column in six schemes (i.e., Goddard, New Goddard, RRTMG, CAM, GFDL and Fu–Liou–Gu with the Multi-Sensor Reanalysis data set during the period 1979–2008 examining the latitudinal, longitudinal and seasonal limitations in the ozone profile specifications of each parameterization. The results indicate that the maximum deviations are over the poles and show prominent longitudinal patterns in the departures due to the lack of representation of the patterns associated with the Brewer–Dobson circulation and the quasi-stationary features forced by the land–sea distribution, respectively. In the second part, the bias in the simulated direct solar radiation due to these deviations from the simplified spatial and temporal representation of the ozone distribution is analyzed for the New Goddard and CAM schemes using the Beer–Lambert–Bouguer law and for the GFDL using empirical equations. For radiative applications those simplifications introduce spatial and temporal biases with near-zero departures over the tropics throughout the year and increasing poleward with a maximum in the high middle latitudes during the winter of each hemisphere.
Gochis, D. J.; Yu, W.
Prediction of heavy rainfall and associated streamflow responses remain as critical hydrometeorological challenges and require improved understanding of the linkages between atmospheric and land surface processes. Streamflow prediction skill is intrinsically liked to quantitative precipitation forecast skill, which emphasizes the need to produce mesoscale predictions of rainfall of high fidelity. However, in many cases land surface parameters can also exert significant control on the runoff response to heavy rainfall and on the formation or localization of heavy rainfall as well. A new generation of integrated atmospheric-hydrologic modeling systems is emerging from different groups around the world to meet the challenge of integrated water cycle predictions. In this talk the community WRF-Hydro modeling system will be presented. After a brief reviewing the architectural features of the WRF-Hydro system short-term forecasting and regional hydroclimate prediction applications of the model from western North America will be presented. In these applications, analyses will present results from observation-validated prediction experiments where atmospheric and terrestrial hydrologic model components are run in both a fully coupled mode and separately without two-way interactions. Emphasis is placed on illustrating an assessment framework using an initial state perturbation methodology to quantify the role of land-atmosphere energy and moisture flux partitioning in controlling precipitation and runoff forecast skill. Issues related to experimental design of fully-coupled model prediction experiments will also be discussed as will issues related to computational performance.
Czernecki, Bartosz; Kryza, Maciej; Migała, Krzysztof; Kolendowicz, Leszek
High frequency of stable atmospheric conditions in Polar regions makes it a very challenging region to accurately downscale local meteorological phenomena. Keeping that in mind authors decided to evaluate the robustness of dynamical downscaling techniques with the use of the Polar Weather Research and Forecasting (Polar WRF) model version 3.7.1 for the area of Svalbard. The Weather Research and Forecasting (WRF) model is often used as a tool for dynamical downscaling. However, its application for relatively complex topography in polar regions like over the area of investigation are sparse. This study introduces some preliminary results of the research project, funded by the Polish National Science Centre, focused on application of the Polar WRF model for the Svalbard area at high spatial and temporal resolution. We show the sensitivity of the surface wind speed, air temperature and sea level pressure calculated by the Polar WRF model for three different parameterizations of the planetary boundary layer. Two-way nested domains were applied with the finest horizontal resolution of 3 km for the smallest domain. June 2008 and January 2009 are selected for tests of the WRF model with the GFS FNL data used as initial and boundary conditions. The results of simulations are compared with in-situ meteorological data measured at synoptic stations running in the nested model domains. Three independent simulations let to evaluate the sensitivity of downscaling results in each of nested domains and assess the role of chosen PBL schemes for model's accuracy. The results allow to quantify the role of different Polar WRF's PBL settings, which may be useful for long-term climatological mesoscale simulations as a tool for recognition of local aspects of Svalbard's climate. The long-term climatological simulations are the further aims of this project.
Zavodsky, Bradley; Kozlowski, Danielle; Case, Jonathan; Molthan, Andrew
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
Bhandari, Mahabir S. [Oak Ridge National Lab. (ORNL), Oak Ridge, TN (United States)
In anticipation of emerging global urbanization and its impact on microclimate, a need exists to better understand and quantify microclimate effects on building energy use. Satisfaction of this need will require coordinated research of microclimate impacts on and from “human systems.” The Urban Microclimate and Energy Tool (Urban-MET) project seeks to address this need by quantifying and analyzing the relationships among climatic conditions, urban morphology, land cover, and energy use; and using these relationships to inform energy-efficient urban development and planning. Initial research will focus on analysis of measured and modeled energy efficiency of various building types in selected urban areas and temporal variations in energy use for different urban morphologies under different microclimatic conditions. In this report, we analyze the differences between microclimate weather data sets for the Oak Ridge National Laboratory campus produced by ENVI-met and Weather Research Forecast (WRF) models, the ASHRAE clear sky which defines the maximum amounts of solar radiation that can be expected, and measured data from a weather station on campus. Errors with climate variables and their impact on building energy consumption will be shown for the microclimate simulations to help prioritize future improvement for use in microclimate simulation impacts to energy use of buildings.
The challenges of monitoring and forecasting flash-flood-producing storm events in data-sparse and arid regions are explored using the Weather Research and Forecasting (WRF) Model (version 3.5) in conjunction with a range of available satellite, in situ, and reanalysis data. Here, we focus on characterizing the initial synoptic features and examining the impact of model parameterization and resolution on the reproduction of a number of flood-producing rainfall events that occurred over the western Saudi Arabian city of Jeddah. Analysis from the European Centre for Medium-Range Weather Forecasts (ECMWF) interim reanalysis (ERA-Interim) data suggests that mesoscale convective systems associated with strong moisture convergence ahead of a trough were the major initial features for the occurrence of these intense rain events. The WRF Model was able to simulate the heavy rainfall, with driving convective processes well characterized by a high-resolution cloud-resolving model. The use of higher (1 km vs 5 km) resolution along the Jeddah coastline favors the simulation of local convective systems and adds value to the simulation of heavy rainfall, especially for deep-convection-related extreme values. At the 5-km resolution, corresponding to an intermediate study domain, simulation without a cumulus scheme led to the formation of deeper convective systems and enhanced rainfall around Jeddah, illustrating the need for careful model scheme selection in this transition resolution. In analysis of multiple nested WRF simulations (25, 5, and 1 km), localized volume and intensity of heavy rainfall together with the duration of rainstorms within the Jeddah catchment area were captured reasonably well, although there was evidence of some displacements of rainstorm events.
Yes No No Obs-nudge rad 90,45,20 No Yes No Obs-nudge rad 120,60,20 No No Yes MYJ– PBL Scheme (modified) Yes Yes Yes WRF, sgl-moment, 5-class mp Yes...Environmental Prediction NOFDDA “no FDDA” NWP Numerical Weather Prediction PBL planetary boundary layer RH relative humidity RMSE root-mean
Ross, Robert S.; Krishnamurti, T. N.; Chaney, Kirsten M.
The Weather Research and Forecasting (WRF) Model 5-day simulations of Major Hurricane Julia (2010) and Tropical Storm Florence (2012), both of which developed from African easterly waves, are used to conduct a complete energetics study to explain why one storm became a major hurricane while the other weakened to a wave. The disparate intensity outcomes are caused by significant differences in the energetics of the two systems that emerge in their storm stages due to differences in the impact of the Saharan air layer (SAL). In their wave stages both waves exhibit a convectively driven energy production cycle, in which the regions of positive barotropic and baroclinic energy conversion and of diabatic heating and rainfall are all superimposed. Convection induces barotropic instability which then enhances the baroclinic overturning through a resonance of the two instabilities, which together produce the eddy kinetic energy. Diabatic heating in the convection generates eddy available potential energy which, along with the eddy kinetic energy, defines the total eddy energy of the system. Florence loses the convectively driven energy production cycle in the storm stage and begins to weaken, while Julia maintains this cycle and becomes a major hurricane. The disruption of the convection in Florence is due to the drying, stabilizing, and vertical shearing effects of an expansive SAL to the north of the storm, effects not present in the Julia case. Consideration is given to the different effects of the SAL on 6-10 day waves (Florence wave) versus 3-5 day waves (Julia wave).
M. S. Mallard
Full Text Available The Weather Research and Forecasting (WRF model is commonly used to make high resolution future projections of regional climate by downscaling global climate model (GCM outputs. Because the GCM fields are typically at a much coarser spatial resolution than the target regional downscaled fields, inland lakes are often poorly resolved in the driving global fields, if they are resolved at all. In such an application, using WRF's default interpolation methods can result in unrealistic lake temperatures and ice cover at inland water points. Prior studies have shown that lake temperatures and ice cover impact the simulation of other surface variables, such as air temperatures and precipitation, two fields that are often used in regional climate applications to understand the impacts of climate change on human health and the environment. Here, alternative methods for setting lake surface variables in WRF for downscaling simulations are presented and contrasted.
Shepherd, Tristan J.; Walsh, Kevin J.
This study investigates the effect of the choice of convective parameterization (CP) scheme on the simulated tracks of three intense tropical cyclones (TCs), using the Weather Research and Forecasting (WRF) model. We focus on diagnosing the competing influences of large-scale steering flow, beta drift and convectively induced changes in track, as represented by four different CP schemes (Kain-Fritsch (KF), Betts-Miller-Janjic (BMJ), Grell-3D (G-3), and the Tiedtke (TD) scheme). The sensitivity of the results to initial conditions, model domain size and shallow convection is also tested. We employ a diagnostic technique by Chan et al. (J Atmos Sci 59:1317-1336, 2002) that separates the influence of the large-scale steering flow, beta drift and the modifications of the steering flow by the storm-scale convection. The combined effect of the steering flow and the beta drift causes TCs typically to move in the direction of the wavenumber-1 (WN-1) cyclonic potential vorticity tendency (PVT). In instances of asymmetrical TCs, the simulated TC motion does not necessarily match the motion expected from the WN-1 PVT due to changes in the convective pattern. In the present study, we test this concept in the WRF simulations and investigate whether if the diagnosed motion from the WN-1 PVT and the TC motion do not match, this can be related to the emerging evolution of changes in convective structure. Several systematic results are found across the three cyclone cases. The sensitivity of TC track to initial conditions (the initialisation time and model domain size) is less than the sensitivity of TC track to changing the CP scheme. The simulated track is not overly sensitive to shallow convection in the KF, BMJ, and TD schemes, compared to the track difference between CP schemes. The G3 scheme, however, is highly sensitive to shallow convection being used. Furthermore, while agreement between the simulated TC track direction and the WN-1 diagnostic is usually good, there are
Vara-Vela, A.; Andrade, M. F.; Kumar, P.; Ynoue, R. Y.; Muñoz, A. G.
The objective of this work is to evaluate the impact of vehicular emissions on the formation of fine particles (PM2.5; ≤ 2.5 µm in diameter) in the Sao Paulo Metropolitan Area (SPMA) in Brazil, where ethanol is used intensively as a fuel in road vehicles. The Weather Research and Forecasting with Chemistry (WRF-Chem) model, which simulates feedbacks between meteorological variables and chemical species, is used as a photochemical modelling tool to describe the physico-chemical processes leading to the evolution of number and mass size distribution of particles through gas-to-particle conversion. A vehicular emission model based on statistical information of vehicular activity is applied to simulate vehicular emissions over the studied area. The simulation has been performed for a 1-month period (7 August-6 September 2012) to cover the availability of experimental data from the NUANCE-SPS (Narrowing the Uncertainties on Aerosol and Climate Changes in Sao Paulo State) project that aims to characterize emissions of atmospheric aerosols in the SPMA. The availability of experimental measurements of atmospheric aerosols and the application of the WRF-Chem model made it possible to represent some of the most important properties of fine particles in the SPMA such as the mass size distribution and chemical composition, besides allowing us to evaluate its formation potential through the gas-to-particle conversion processes. Results show that the emission of primary gases, mostly from vehicles, led to a production of secondary particles between 20 and 30 % in relation to the total mass concentration of PM2.5 in the downtown SPMA. Each of PM2.5 and primary natural aerosol (dust and sea salt) contributed with 40-50 % of the total PM10 (i.e. those ≤ 10 µm in diameter) concentration. Over 40 % of the formation of fine particles, by mass, was due to the emission of hydrocarbons, mainly aromatics. Furthermore, an increase in the number of small particles impaired the
Shepherd, Tristan J.; Walsh, Kevin J.
This study investigates the effect of the choice of convective parameterization (CP) scheme on the simulated tracks of three intense tropical cyclones (TCs), using the Weather Research and Forecasting (WRF) model. We focus on diagnosing the competing influences of large-scale steering flow, beta drift and convectively induced changes in track, as represented by four different CP schemes (Kain-Fritsch (KF), Betts-Miller-Janjic (BMJ), Grell-3D (G-3), and the Tiedtke (TD) scheme). The sensitivity of the results to initial conditions, model domain size and shallow convection is also tested. We employ a diagnostic technique by Chan et al. (J Atmos Sci 59:1317-1336, 2002) that separates the influence of the large-scale steering flow, beta drift and the modifications of the steering flow by the storm-scale convection. The combined effect of the steering flow and the beta drift causes TCs typically to move in the direction of the wavenumber-1 (WN-1) cyclonic potential vorticity tendency (PVT). In instances of asymmetrical TCs, the simulated TC motion does not necessarily match the motion expected from the WN-1 PVT due to changes in the convective pattern. In the present study, we test this concept in the WRF simulations and investigate whether if the diagnosed motion from the WN-1 PVT and the TC motion do not match, this can be related to the emerging evolution of changes in convective structure. Several systematic results are found across the three cyclone cases. The sensitivity of TC track to initial conditions (the initialisation time and model domain size) is less than the sensitivity of TC track to changing the CP scheme. The simulated track is not overly sensitive to shallow convection in the KF, BMJ, and TD schemes, compared to the track difference between CP schemes. The G3 scheme, however, is highly sensitive to shallow convection being used. Furthermore, while agreement between the simulated TC track direction and the WN-1 diagnostic is usually good, there are
Hiramatsu, Akio; Huynh, Van-Nam; Nakamori, Yoshiteru
The quality of weather forecast has gradually improved, but weather information such as precipitation forecast is still uncertainty. Meteorologists have studied the use and economic value of weather information, and users have to translate weather information into their most desirable action. To maximize the economic value of users, the decision maker should select the optimum course of action for his company or project, based on an appropriate decision strategy under uncertain situations. In...
Andersen, Ove; Torp, Kristian
for storing and map-matching GPS data, and integrating this data with detailed weather data. The model is generic in the sense that it can be used anywhere GPS data and weather data is available. Next, we analyze the correlation between travel time and the weather classes dry, fog, rain, and snow along...
Govett, Mark; Middlecoff, Jacques; Henderson, Tom; Rosinski, James
The Non-hydrostatic Icosahedral Model (NIM) is a global weather prediction model being developed to run on the GPU and MIC fine-grain architectures. The model dynamics, written in Fortran, was initially parallelized for GPUs in 2009 using the F2C-ACC compiler and demonstrated good results running on a single GPU. Subsequent efforts have focused on (1) running efficiently on multiple GPUs, (2) parallelization of NIM for Intel-MIC using openMP, (3) assessing commercial Fortran GPU compilers now available from Cray, PGI and CAPS, (4) keeping the model up to date with the latest scientific development while maintaining a single source performance portable code, and (5) parallelization of two physics packages used in the NIM: the operational Global Forecast System (GFS) used operationally, and the widely used Weather Research and Forecast (WRF) model physics. The presentation will touch on each of these efforts, but highlight improvements in parallel performance of the NIM running on the Titan GPU cluster at ORNL, the ongong parallelization of model physics, and a recent evaluation of commercial GPU compilers using the F2C-ACC compiler as the baseline.
Dreher, Joseph G.
For expedience in delivering dispersion guidance in the diversity of operational situations, National Weather Service Melbourne (MLB) and Spaceflight Meteorology Group (SMG) are becoming increasingly reliant on the PC-based version of the HYSPLIT model run through a graphical user interface (GUI). While the GUI offers unique advantages when compared to traditional methods, it is difficult for forecasters to run and manage in an operational environment. To alleviate the difficulty in providing scheduled real-time trajectory and concentration guidance, the Applied Meteorology Unit (AMU) configured a Linux version of the Hybrid Single-Particle Lagrangian Integrated Trajectory (HYSPLIT) (HYSPLIT) model that ingests the National Centers for Environmental Prediction (NCEP) guidance, such as the North American Mesoscale (NAM) and the Rapid Update Cycle (RUC) models. The AMU configured the HYSPLIT system to automatically download the NCEP model products, convert the meteorological grids into HYSPLIT binary format, run the model from several pre-selected latitude/longitude sites, and post-process the data to create output graphics. In addition, the AMU configured several software programs to convert local Weather Research and Forecast (WRF) model output into HYSPLIT format.
Lian, Yuan; Newman, Claire E.; Richardson, Mark I.
We use the TitanWRF and Titan MITgcm to simulate the formation of stratospheric superrotation on Titan. The stratospheric wind speed reaches 180 m/s around both solstices. The MITgcm results appear similar to those from Titan WRF (Newman et al., 2011). However, despite the similar physics parameterizations such as radiative transfer and PBL mixing, the MITgcm produces a consistent minimum (about 5 to 15m/s depending on the season) near 50km above the surface. This result is comparable to the wind profile obtained by Huygens, though the observed wind minimum was between 75km and 80km above the surface. Attempts have been made to investigate what produces the wind minimum, e.g., turning off the diurnal cycle and removing surface thermal inertia. The wind minimum persists despite the effort, suggesting the feature may originate from interactions between zonal wind and downward propagating waves. We further examine the effect of topography on the wind structure. The stratospheric superrotation in these simulations is significantly slower than that in the simulations without topography, with maximum speed of 110m/s as opposed to previously simulated 180m/s. The wind minimum near 50km, however, still exists in the MITgcm. Also, results suggest that the near surface winds are primarily guided by topography, and are less affected by solar heating on the surface. Another distinct result, compared to the cases without topography in both TitanWRF and the MITgcm, is that the near surface winds in the equatorial region exhibit strong eastward components, which may help to explain the combination of dune orientations and transport directions inferred from imaging. Lastly, we introduce an active methane cycle using a simplified Betts-Miller scheme (similar to Mitchell et al, 2009) to represent moist convection associated with the methane cycle in the troposphere. We will explore the impact of the new scheme on the methane cycle, and compare its realism to that of the large
Yahya, Khairunnisa; Glotfelty, Timothy; Wang, Kai; Zhang, Yang; Nenes, Athanasios
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
García-Valdecasas Ojeda, Matilde; Quishpe-Vásquez, César; Raquel Gámiz-Fortis, Sonia; Castro-Díez, Yolanda; Jesús Esteban-Parra, María
Regional Climate Models (RCM) has been widely used as a tool to perform high resolution climate fields in areas with high climate variability such as Spain. However, the outputs provided by downscaling techniques have many sources of uncertainty associated at different aspects. In this study, the ability of the Weather Research and Forecasting (WRF) model to capture drought conditions has been analyzed. The WRF simulation was carried out for a period that spanned from 1980 to 2010 over a domain centered in the Iberian Peninsula with a spatial resolution of 0.088°, and nested in the coarser EURO-CORDEX domain (0.44° spatial resolution). To investigate the spatiotemporal drought variability, the Standardized Precipitation Index (SPI) and the Standardized Precipitation Evapotranspiration Index (SPEI) has been computed at two different timescales: 3- and 12-months due to its suitability to study agricultural and hydrological droughts. The drought indices computed from WRF outputs were compared with those obtained from the observational (MOTEDAS and MOPREDAS) datasets. In order to assess the added value provided by downscaled fields, these indices were also computed from the ERA-Interim Re-Analysis database, which provides the lateral and boundary conditions of the WRF simulations. Results from this study indicate that WRF provides a noticeable benefit with respect to ERA-Interim for many regions in Spain in terms of drought indices, greater for SPI than for SPEI. The improvement offered by WRF depends on the region, index and timescale analyzed, being greater at longer timescales. These findings prove the reliability of the downscaled fields to detect drought events and, therefore, it is a remarkable source of knowledge for a suitable decision making related to water-resource management. Keywords: Drought, added value, Regional Climate Models, WRF, SPEI, SPI. Acknowledgements: This work has been financed by the projects P11-RNM-7941 (Junta de Andalucía-Spain) and
Full Text Available This article is based on the study of the seasonal and interannual variability of carbon monoxide (CO and ozone (O3 at different altitudes of the troposphere over Hyderabad, India, during 2006–2010 using Measurement of OZone and water vapour by Airbus In-Service Aircraft (MOZAIC and observation from Tropospheric Emission Spectrometer (TES aboard NASA's Aura satellite. The MOZAIC observations show maximum seasonal variability in both CO and O3 during winter and pre-monsoon season, with CO in the range (100–200±13 ppbv and O3 in the range (50–70±9 ppbv. The time-series of MOZAIC data shows a significant increase of 4.2±1.3 % in the surface CO and 6.7±1.3 % in the surface O3 during 2006–2010 in Hyderabad. From MOZAIC observations, we identify CO and O3 profiles that are anomalous with respect to the monthly mean and compare those with Weather Research Forecast model coupled with Chemistry (WRF-Chem and Model for OZone and Related Tracers, version 4 profiles for the same day. The anomalous profiles of WRF-Chem are simulated using three convection schemes. The goodness of comparison depends on the convection scheme and the altitude region of the troposphere.
San Jose, R.; Perez, J. L.; Gonzalez, R. M.
Urban metabolism modeling has advanced substantially during the last years due to the increased detail in mesoscale urban parameterization in meteorological mesoscale models and CFD numerical tools. Recently the implementation of the “urban canopy model” (UCM) into the WRF mesoscale meteorological model has produced a substantial advance on the understanding of the urban atmospheric heat flux exchanges in the urban canopy. The need to optimize the use of heat energy in urban environment has produced a substantial increase in the detailed investigation of the urban heat flux exchanges. In this contribution we will show the performance of using a tool called MICROSYS (MICRO scale CFD modelling SYStem) which is an adaptation of the classical urban canopy model but on a high resolution environment by using a classical CFD approach. The energy balance in the urban system can be determined in a micrometeorologicl sense by considering the energy flows in and out of a control volume. For such a control volume reaching from ground to a certain height above buildings, the energy balance equation includes the net radiation, the anthropogenic heat flux, the turbulent sensible heat flux, the turbulent latent heat flux, the net storage change within the control volume, the net advected flux and other sources and sinks. We have applied the MICROSYS model to an area of 5 km x 5 km with 200 m spatial resolution by using the WRF-UCM (adapted and the MICROSYS CFD model. The anthropogenic heat flux has been estimated by using the Flanner M.G. (2009) database and detailed GIS information (50 m resolution) of Madrid city. The Storage energy has been estimated by calculating the energy balance according to the UCM procedure and implementing it into the MICROSYS tool. Results show that MICROSYS can be used as an energy efficient tool to estimate the energy balance of different urban areas and buildings.
Voudouri, A.; Khain, P.; Carmona, I.; Bellprat, O.; Grazzini, F.; Avgoustoglou, E.; Bettems, J. M.; Kaufmann, P.
Numerical weather prediction (NWP) and climate models use parameterization schemes for physical processes, which often include free or poorly confined parameters. Model developers normally calibrate the values of these parameters subjectively to improve the agreement of forecasts with available observations, a procedure referred as expert tuning. A practicable objective multi-variate calibration method build on a quadratic meta-model (MM), that has been applied for a regional climate model (RCM) has shown to be at least as good as expert tuning. Based on these results, an approach to implement the methodology to an NWP model is presented in this study. Challenges in transferring the methodology from RCM to NWP are not only restricted to the use of higher resolution and different time scales. The sensitivity of the NWP model quality with respect to the model parameter space has to be clarified, as well as optimize the overall procedure, in terms of required amount of computing resources for the calibration of an NWP model. Three free model parameters affecting mainly turbulence parameterization schemes were originally selected with respect to their influence on the variables associated to daily forecasts such as daily minimum and maximum 2 m temperature as well as 24 h accumulated precipitation. Preliminary results indicate that it is both affordable in terms of computer resources and meaningful in terms of improved forecast quality. In addition, the proposed methodology has the advantage of being a replicable procedure that can be applied when an updated model version is launched and/or customize the same model implementation over different climatological areas.
Bøvith, Thomas; Nielsen, Allan Aasbjerg; Hansen, Lars Kai
A method for detecting clutter in weather radar images by information fusion is presented. Radar data, satellite images, and output from a numerical weather prediction model are combined and the radar echoes are classified using supervised classification. The presented method uses indirect...... information on precipitation in the atmosphere from Meteosat-8 multispectral images and near-surface temperature estimates from the DMI-HIRLAM-S05 numerical weather prediction model. Alternatively, an operational nowcasting product called 'Precipitating Clouds' based on Meteosat-8 input is used. A scale...
Tewari, M.; Mittal, R.; Radhakrishnan, C.; Cipriani, J.; Watson, C.
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).
Full Text Available This work attempts to validate two modified Kalman gain algorithms by assimilating a single radar simulation data set into the Weather Research and Forecasting model using an Ensemble Square Root Filter. Emphasis is placed on the comparison of assimilation performance between the two modified algorithms against the classical Kalman gain algorithm when the measurement operator is non-linear. Three ideal storm-scale experiments, which are configured identically except for the different Kalman gain algorithms, are designed in parallel for this purpose. The results show that the first modified algorithm can result in a better simulation of a storm, as measured by the root mean square error (RMSE. The second algorithm can also, to some extent, reduce the RMSE of the simulation of some state vectors, but with little improvement of the estimation of storm intensity. Overall, our preliminary experiments indicate that the two modified Kalman gain algorithms can benefit the assimilation of complex numerical models when the measurement operators are non-linear, confirming the earlier theoretical analysis and the results of simple models. Further work is needed to evaluate the impact of the modified Kalman gain algorithms on the assimilation performance of ensemble-based methods.
Ojrzyńska, Hanna; Kryza, Maciej; Wałaszek, Kinga; Szymanowski, Mariusz; Werner, Małgorzata; Dore, Anthony J.
This paper presents the application of the high-resolution WRF model data for the automatic classification of the atmospheric circulation types and the evaluation of the model results for daily rainfall and air temperatures. The WRF model evaluation is performed by comparison with measurements and gridded data (E-OBS). The study is focused on the area of Poland and covers the 1981-2010 period, for which the WRF model has been run using three nested domains with spatial resolution of 45 km × 45 km, 15 km × 15 km and 5 km × 5 km. For the model evaluation, we have used the data from the innermost domain, and data from the second domain were used for circulation typology. According to the circulation type analysis, the anticyclonic types (AAD and AAW) are the most frequent. The WRF model is able to reproduce the daily air temperatures and the error statistics are better, compared with the interpolation-based gridded dataset. The high-resolution WRF model shows a higher spatial variability of both air temperature and rainfall, compared with the E-OBS dataset. For the rainfall, the WRF model, in general, overestimates the measured values. The model performance shows a seasonal pattern and is also dependent on the atmospheric circulation type, especially for daily rainfall.
Dubois, Caroline; Goderniaux, Pascal; Deceuster, John; Poulain, Angélique; Kaufmann, Olivier
'Ghost-rock' karst aquifer has recently been highlighted. In this particular type of aquifer, the karst is not expressed as open conduits but consists in zones where the limestone is weathered. The in-situ weathering of limestone leaves a soft porous material called 'alterite'. The hydro-mechanical properties of this material differs significantly from those of the host rock: the weathering enhances the storage capacity and the conductivity of the rock. This type of weathered karst aquifer has never been studied from a hydrogeological point of view. In this study, we present the hydraulic characterization of such weathered zones. We also present a modelling approach derived from the common Equivalent Porous Medium (EPM) approach, but including the spatial distribution of hydrogeological properties through the weathered features, from the hard rock to the alterite, according to a weathering index. Unlike the Discrete Fracture Network (DFN) approaches, which enable to take into account a limited number of fractures, this new approach allows creating models including thousands of weathered features. As the properties of the alterite have to be considered at a centimeter scale, it is necessary to upscale these properties to carry out simulations over large areas. Therefore, an upscaling method was developed, taking into account the anisotropy of the weathered features. Synthetic models are built, upscaled and different hydrogeological simulations are run to validate the method. This methodology is finally tested on a real case study: the modelling of the dewatering drainage flow of an exploited quarry in a weathered karst aquifer in Belgium.
Zhu, Jiang; Stevens, E.; Zavodsky, B. T.; Zhang, X.; Heinrichs, T.; Broderson, D.
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.
Chang, Rui; Rong, Zhu; Badger, Merete
Using accurate inputs of wind speed is crucial in wind resource assessment, as predicted power is proportional to the wind speed cubed. This study outlines a methodology for combining multiple ocean satellite winds and winds from WRF simulations in order to acquire the accurate reconstructed...... offshore winds which can be used for offshore wind resource assessment. First, wind speeds retrieved from Synthetic Aperture Radar (SAR) and Scatterometer ASCAT images were validated against in situ measurements from seven coastal meteorological stations in South China Sea (SCS). The wind roses from...... (SD) of 2.09 m/s (1.83 m/s) and correlation coefficient of R 0.75 (0.80). When the offshore winds (i.e., winds directed from land to sea) are excluded, the comparison results for wind speeds show an improvement of SD and R, indicating that the satellite data are more credible over the open ocean...
García-Valdecasas Ojeda, Matilde; Gámiz-Fortis, Sonia R.; Castro-Díez, Yolanda; Esteban-Parra, María. Jesús
The Weather Research and Forecasting (WRF) model has been used to show the benefits provided by downscaled fields to detect and analyze wet and dry periods over a region with high precipitation variability such as Spain. We have analyzed the spatiotemporal behavior of two widely used drought indices: the Standardized Precipitation Index (SPI) and the Standardized Precipitation Evapotranspiration Index (SPEI), computed at 3 and 12 month time scales, which provide important information in an agricultural and water-resource context. These two indices were computed from WRF outputs and compared with those calculated from observational (monthly precipitation and temperature databases of Spain, MOPREDAS and MOTEDAS) and from the European Centre for Medium-Range Weather Forecasts Interim Re-Analysis (ERA-Interim) data sets. This evaluation was made by using a regional scale and a multistep regionalization method and by comparison of individual grid points. In general, results indicate that the drought indices obtained by using WRF outputs provide a noticeable improvement regarding those computed by using ERA-Interim, higher at longer time scales. Although results show no significant differences between drought indices analyzed, the improvement offered by WRF is greater for SPI than for SPEI. In terms of averaged duration, magnitude, and severity of drought, the benefits provided by WRF are not so evident, presenting better agreement with the observational data at 12 month time scale, being clearer for the intensity. These findings evidence the benefit of using WRF climate fields to monitor, analyze, and detect drought events, being a valuable source of knowledge for a suitable decision making, especially for water-resource management.
Eluszkiewicz, Janusz; Nehrkorn, Thomas; Wofsy, Steven C.; Matross, Daniel; Gerbig, Christoph; Lin, John C.; Freitas, Saulo; Longo, Marcos; Andrews, Arlyn E.; Peters, Wouter
This paper evaluates simulations of atmospheric CO2 measured in 2004 at continental surface and airborne receptors, intended to test the capability to use data with high temporal and spatial resolution for analyses of carbon sources and sinks at regional and continental scales. The simulations were performed using the Stochastic Time-Inverted Lagrangian Transport (STILT) model driven by the Weather Forecast and Research (WRF) model, and linked to surface fluxes from the satellite-driven Vegetation Photosynthesis and Respiration Model (VPRM). The simulations provide detailed representations of hourly CO2 tower data and reproduce the shapes of airborne vertical profiles with high fidelity. WRF meteorology gives superior model performance compared with standard meteorological products, and the impact of including WRF convective mass fluxes in the STILT trajectory calculations is significant in individual cases. Important biases in the simulation are associated with the nighttime CO2 build-up and subsequent morning transition to convective conditions, and with errors in the advected lateral boundary condition. Comparison of STILT simulations driven by the WRF model against those driven by the Brazilian variant of the Regional Atmospheric Modeling System (BRAMS) shows that model-to-model differences are smaller than between an individual transport model and observations, pointing to systematic errors in the simulated transport. Future developments in the WRF model s data assimilation capabilities, basic research into the fundamental aspects of trajectory calculations, and intercomparison studies involving other transport models, are possible venues for reducing these errors. Overall, the STILT/WRF/VPRM offers a powerful tool for continental and regional scale carbon flux estimates.
Gao, Wenhua; Fan, Jiwen; Easter, R. C.; Yang, Qing; Zhao, Chun; Ghan, Steven J.
Aerosol-cloud interaction processes can be represented more physically with bin cloud microphysics relative to bulk microphysical parameterizations. However, due to computational power limitations in the past, bin cloud microphysics was often run with very simple aerosol treatments. The purpose of this study is to represent better aerosol-cloud interaction processes in the Chemistry version of Weather Research and Forecast model (WRF-Chem) at convection-permitting scales by coupling spectral-bin cloud microphysics (SBM) with the MOSAIC sectional aerosol model. A flexible interface is built that exchanges cloud and aerosol information between them. The interface contains a new bin aerosol activation approach, which replaces the treatments in the original SBM. It also includes the modified aerosol resuspension and in-cloud wet removal processes with the droplet loss tendencies and precipitation fluxes from SBM. The newly coupled system is evaluated for two marine stratocumulus cases over the Southeast Pacific Ocean with either a simplified aerosol setup or full-chemistry. We compare the aerosol activation process in the newly coupled SBM-MOSAIC against the SBM simulation without chemistry using a simplified aerosol setup, and the results show consistent activation rates. A longer time simulation reinforces that aerosol resuspension through cloud drop evaporation plays an important role in replenishing aerosols and impacts cloud and precipitation in marine stratocumulus clouds. Evaluation of the coupled SBM-MOSAIC with full-chemistry using aircraft measurements suggests that the new model works realistically for the marine stratocumulus clouds, and improves the simulation of cloud microphysical properties compared to a simulation using MOSAIC coupled with the Morrison two-moment microphysics.
Gao, Wenhua; Fan, Jiwen; Easter, Richard C.; Yang, Qing; Zhao, Chun; Ghan, Steven J.
Aerosol-cloud interaction processes can be represented more physically with bin cloud microphysics relative to bulk microphysical parameterizations. However, due to computational power limitations in the past, bin cloud microphysics was often run with very simple aerosol treatments. The purpose of this study is to represent better aerosol-cloud interaction processes in the Chemistry version of Weather Research and Forecast model (WRF-Chem) at convection-permitting scales by coupling spectral-bin cloud microphysics (SBM) with the MOSAIC sectional aerosol model. A flexible interface is built that exchanges cloud and aerosol information between them. The interface contains a new bin aerosol activation approach, which replaces the treatments in the original SBM. It also includes the modified aerosol resuspension and in-cloud wet removal processes with the droplet loss tendencies and precipitation fluxes from SBM. The newly coupled system is evaluated for two marine stratocumulus cases over the Southeast Pacific Ocean with either a simplified aerosol setup or full-chemistry. We compare the aerosol activation process in the newly-coupled SBM-MOSAIC against the SBM simulation without chemistry using a simplified aerosol setup, and the results show consistent activation rates. A longer time simulation reinforces that aerosol resuspension through cloud drop evaporation plays an important role in replenishing aerosols and impacts cloud and precipitation in marine stratocumulus clouds. Evaluation of the coupled SBM-MOSAIC with full-chemistry using aircraft measurements suggests that the new model works realistically for the marine stratocumulus clouds, and improves the simulation of cloud microphysical properties compared to a simulation using MOSAIC coupled with the Morrison two-moment microphysics.
Rios-Entenza, A.; Miguez-Macho, G.
Land-atmosphere water exchanges and heat fluxes play an important role in climate and particularly in controlling precipitation in water-limited regions. One of such regions is the Iberian Peninsula, and in this study we examine the relevance of water recycling in convective precipitation regimes of the Fall and Spring there, when rainfall is critical for agriculture and many other human activities. We conducted simulations with WRF-ARW model at 5 km horizontal resolution, using a 1500 km x 1500 km nested grid that covers the Iberian Peninsula, with a parent domain that uses spectral nudging in order to avoid the distortion of the large-scale circulation caused by the interaction of the modeled flow with the lateral boundaries of the nested grid. For land-surface interactions we coupled WRF with the LEAF-HYDRO land surface model, which includes water table dynamics. We use therefore a tool that simulates the entire water cycle, including the water table, which has been reported to be critical for soil moisture dynamics in semi-arid regions like the Iberian Peninsula. For each one of the events that we selected, we performed two simulations: a control one, where all land-atmosphere feedbacks are taken into account, and the experiment, where infiltration of the precipitated water into the soil was suppressed. In this manner we explore the role of upward latent and sensible heat fluxes and evapotranspiration in precipitation dynamics. Preliminary results suggest that water recycling is a key factor in extending convective precipitation during several days, and that the total new water added in the area as a whole is only a fraction of the total measured rainfall. An estimation of this fraction is very important to better understanding the water budget and for hydrological planning in this water-stressed region.
Validação de poluentes fotoquímicos e inclusão do inventário de emissões no modelo de qualidade do ar WRF/CHEM, para a região metropolitana de São Paulo Prediction of photochemical pollutants in metropolitan area of São Paulo using air quality model (WRF/CHEM and the CETESP pollutants emmission inventory
Rosiberto Salustiano da Silva Junior
the results of an approximation and transformation made on the Sao Paulo Metropolitan Region (SPMR pollutant emission inventory, required to be used as input data on the WRF/Chem model ("Weather Research This paper shows the results of an approximation and transformation made on the Sao Paulo Metropolitan Region (SPMR pollutant emission inventory, required to be used as input data on the WRF/Chem model ("Weather Research and Forecasting / CHEMistry". Therefore, the purpose is to evaluate the efficiency of the WRF/Chem model to simulate photochemical pollutants on the SPMR, using as parameters the inclusion of the emission inventory and measurements of carbon monoxide (CO and tropospheric ozone (O3 concentrations. The WRF/Chem is a forecast, weather climate and air quality model, which solves simultaneously the meteorology and chemistry modules. SPMR is considered one of the largest cities in the world, and like other big cities suffer with atmospheric pollution. Researches made in SPMR show that vehicles are the main sources of Carbon monoxide (CO, Hydrocarbon (HC and Nitrogen oxide (NOx. When it comes to Sulphur oxides (SOx and inhalable particles (PM10 the main sources of emission fundamentally are industries and vehicles. Another crucial factor is the resuspension of particles from the ground (soil and the formation of secondary aerosols. A 2006 Companhia Ambiental do Estado de São Paulo (CETESB inventory of emissions will be used as input data to the WRF/CHEM model. Since the annual CETESB inventory of emissions integrates the whole SPMR some approximation is required to match the model input data format. It was proposed some approximation methods in which the inventory of annual emissions was representatively distributed in time and space as required by the model. The results show that these methods improved the forecasting of the ozone (O3 and of CO concentration by approximately 25%, reaching a correlation coefficients of 0,79% for the ozone and 0,49% for
Burakowski, E. A.; Chen, M.; Birkel, S. D.; Wake, C. P.; Dibb, J. E.
When colonists arrived in the New England region of the United States (US) in the 1600's, more than 90% of land area was forested. By the mid-1800's, half of the land area was deforested having been cleared extensively for timber, pasture, and to heat homes. Today, New Hampshire is one of the most forested states in the US, yet little is known about the local climate impacts resulting from reforestation. We hypothesize that the removal of forests in 1850 had a strong impact on wintertime climate through changes in surface albedo, roughness length, and other biogeophysical surface properties. This study investigates the climate impacts of historical deforestation on New England winter climate using the Weather, Research, and Forecasting model. The WRF simulations presented here utilize a triple-nested approach, with the innermost 4-km domain centered on the New England states for two land cover scenarios, (2) an historical 1850 deforested scenario derived from the History Database of the Global Environment (HYDE3) land cover dataset and (2) present-day reforested scenario derived from MODerate Resolution Imaging Spectroradiometer (MODIS) land cover data. ERA-Interim lateral boundary conditions are used to drive the model and results are compared for an above average snowfall winter (November 2008 through April 2009) and a below-average snowfall winter (November 2001 through April 2002). Simulations are ongoing but analysis of observational data suggests that nocturnal cooling is a dominant response to deforestation compared to forested areas. The results from the WRF modeling efforts in this study will help inform future land use decisions in the future.
Nielsen, Joakim Refslund; Dellwik, Ebba; Hahmann, Andrea N.
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 a green vegetation fraction (GVF) climatology to represent the seasonal...... or changes in management practice since it is derived more than twenty years ago. In this study, a new high resolution, high quality GVF product is applied in a WRF climate simulation over Denmark during the 2006 heat wave year. The new GVF product reflects the year 2006 and it was previously tested...... in a climate run at low spatial resolution showing good performance. The new simulations are carried out at higher resolution and the performance is quantified against (1) a control run using the default GVF data and (2) two gridded data sets (E-OBS and DMI Climate grid) at lower resolution for which...
It is well known that crop production and hydrologic variation on watersheds is weather related. Rarely, however, is meteorological data quality checks reported for agricultural systems model research. We present quality assurance procedures for agricultural system model weather data input. Problems...
Follette-Cook, M. B.; Pickering, K.; Crawford, J.; Duncan, B.; Loughner, C.; Diskin, G.; Fried, A.; Weinheimer, A.
We quantify both the spatial and temporal variability of column integrated O3, NO2, CO, SO2, and HCHO over the Baltimore / Washington, DC area using output from the Weather Research and Forecasting model with on-line chemistry (WRF/Chem) for the entire month of July 2011, coinciding with the first deployment of the NASA Earth Venture program mission Deriving Information on Surface conditions from Column and Vertically Resolved Observations Relevant to Air Quality (DISCOVER-AQ). Using structure function analyses, we find that the model reproduces the spatial variability observed during the campaign reasonably well, especially for O3. The Tropospheric Emissions: Monitoring of Pollution (TEMPO) instrument will be the first NASA mission to make atmospheric composition observations from geostationary orbit and partially fulfills the goals of the Geostationary Coastal and Air Pollution Events (GEO-CAPE) mission. We relate the simulated variability to the precision requirements defined by the science traceability matrices of these space-borne missions. Results for O3 from 0- 2 km altitude indicate that the TEMPO instrument would be able to observe O3 air quality events over the Mid-Atlantic area, even on days when the violations of the air quality standard are not widespread. The results further indicated that horizontal gradients in CO from 0-2 km would be observable over moderate distances (= 20 km). The spatial and temporal results for tropospheric column NO2 indicate that TEMPO would be able to observe not only the large urban plumes at times of peak production, but also the weaker gradients between rush hours. This suggests that the proposed spatial and temporal resolutions for these satellites as well as their prospective precision requirements are sufficient to answer the science questions they are tasked to address.
Kryza, Maciej; Wałaszek, Kinga; Ojrzyńska, Hanna; Szymanowski, Mariusz; Werner, Małgorzata; Dore, Anthony J.
In this work, we present the results of high-resolution dynamical downscaling of air temperature, relative humidity, wind speed and direction, for the area of Poland, with the Weather Research and Forecasting (WRF) model. The model is configured using three nested domains, with spatial resolution of 45 km × 45 km, 15 km × 15 km and 5 km × 5 km. The ERA-Interim database is used for boundary conditions. The results are evaluated by comparison with station measurements for the period 1981-2010. The model is capable of reproducing the main climatological features of the study area. The results are in very close agreement with the measurements, especially for the air temperature. For all four meteorological variables, the model performance captures seasonal and daily cycles. For the air temperature and winter season, the model underestimates the measurements. For summer, the model shows higher values, compared with the measurements. The opposite is the case for relative humidity. There is a strong diurnal pattern in mean error, which changes seasonally. The agreement with the measurements is worse for the seashore and mountain areas, which suggests that the 5 km × 5 km grid might still have an insufficient spatial resolution. There is no statistically significant temporal trend in the model performance. The larger year-to-year changes in the model performance, e.g. for the years 1982 and 2010 for the air temperature should therefore be linked with the natural variability of meteorological conditions.
Hayes, P.; Trigg, J. L.; Stauffer, D.; Hunter, G.; McQueen, J.
modelers on the meteorology team. Some of the Olympic venues were located in the mountains to the west of Torino, while the rest were located on the relatively flat plain in and around the cities of Pinerolo and Torino to the east. DTRA partners at Pennsylvania State University (PSU) and the U.S. National Center for Atmospheric Research (NCAR) established data collection and assimilation, and forecast modeling processes that used special weather station observations provided by the Area Previsione e Monitoraggio Ambientale of Italy's ARPA Piemonte. At PSU a version of the MM5 was especially prepared to use observation data to forecast weather in a four-nest configuration. Two other DTRA partners provided independent weather forecast models against which the PSU model data were compared. The U.S. Air Force Weather Agency provided its MM5 forecast model data and the U.S. National Oceanic and Atmospheric Administration's National Centers for Environmental Prediction provided data from a special version of their WRF model. The project produced many opportunities to improve the modeling and forecasting capability at DTRA. DTRA and its partners plan to expand upon this experience during upcoming field tests, and to further improve and expand the capability to provide accurate high-resolution weather forecast information to hazard and consequence assessment operations.
Kosovic, B.; Jimenez, P. A.
Advances in high performance computational resources and frameworks now make possible the use of Numerical Weather Predication (NWP) models for high-resolution simulations of atmospheric flows. In order to develop best practices, standards, and procedures for multi-scale simulations, we need to carry out extensive validation of NWP models across unprecedented range of scales from hundreds of kilometers to tens of meters. However, there are limited observational data available for evaluating high-resolution models. Recently, Nunalee et al (2015) validated large-eddy simulations (LES) using WRF for flow and dispersion based on the Cinder Cone Butte experiment carried out in Idaho in 1982. This study involved moderately complex terrain. We now extend the study to a significantly more complex terrain based on a more recent field study in Idaho. This field study include two experiments: the first one carried out in 2010 and centered on the Big Southern Butte (BSB) and the second in 2011 centered on the Salmon River Canyon both in Idaho (Butler et al., 2015). As a first step, here we focus on using the observations from the BSB experiment to validate multi-scale simulations using the WRF model. We carry out both mesoscale simulations and large-eddy simulations (LES). Nested mesoscale simulations are carried out using the innermost nest with grid cell size of 300m while nested WRF-LES are carried with grid cell size of ~50m. We analyze the performance of PBL scheme in mesoscale simulations and the resulting interplay between subgrid parameterization and numerical advection scheme in LES. The results of this analysis are used to assess performance of PBL schemes in complex terrain where the assumption of horizontal homogeneity on which these schemes are based are violated and to suggest the modifications to PBL scheme to account for the effect of heterogeneity.
Ahn, Joong-Bae; Im, Eun-Soon; Jo, Sera
This study assesses the regional climate projection newly projected within the framework of the national downscaling project in South Korea. The fine-scale climate information (12.5 km) is produced by dynamical downscaling of the HadGEM2-AO global projections forced by the representative concentration pathway (RCP4.5 and 8.5) scenarios using the Weather Research and Forecasting (WRF) modeling system. Changes in temperature and precipitation in terms of long-term trends, daily characteristics and extremes are presented by comparing two 30 yr periods (2041-2070 vs. 2071-2100). The temperature increase presents a relevant trend, but the degree of warming varies in different periods and emission scenarios. While the temperature distribution from the RCP8.5 projection is continuously shifted toward warmer conditions by the end of the 21st century, the RCP4.5 projection appears to stabilize warming in accordance with emission forcing. This shift in distribution directly affects the magnitude of extremes, which enhances extreme hot days but reduces extreme cold days. Precipitation changes, however, do not respond monotonically to emission forcing, as they exhibit less sensitivity to different emission scenarios. An enhancement of high intensity precipitation and a reduction of weak intensity precipitation are discernible, implying an intensified hydrologic cycle. Changes in return levels of annual maximum precipitation suggest an increased probability of extreme precipitation with 20 yr and 50 yr return periods. Acknowledgement : This work was funded by the Korea Meteorological Administration Research and Development Program under grant KMIPA 2015-2081
Vahmani, P.; Ban-Weiss, G. A.
Modeling the climate of urban areas is of interest for studying urban heat islands (UHIs). Reliable assessment of the primary causes of UHIs and the efficacy of various heat mitigation strategies requires accurate prediction of urban temperatures and realistic representation of land surface physical characteristics in models. In this study, we expand the capabilities of the Weather Research and Forecasting (WRF) model by implementing high-resolution, real-time satellite observations of green vegetation fraction (GVF) and albedo. Satellite-based GVF and albedo replace constant values that are assumed for urban pixels in the default version of WRF. Simulations of urban meteorology in Los Angeles using the improved model show marked improvements relative to the default model. The largest improvements are for nocturnal air temperatures, with a reduction in root-mean-square deviation between simulations and observations from 3.8 to 1.9°C. Utilizing the improved model, we quantify relationships between surface and 2 m air temperatures versus urban fraction, GVF, albedo, distance from the ocean, and elevation. Distance from the ocean is found to be the main contributor to variations in temperatures around Los Angeles. After conditionally sampling pixels to minimize the influence of distance from the ocean and elevation, we find that variations in GVF and urban fraction are responsible for up to 58 and 27% of the variance in temperatures. The satellite-supported meteorological modeling framework reported here can be used for studying UHIs in other cities and can serve as a foundation for testing the efficacy of various heat mitigation strategies.
García-Valdecasas-Ojeda, Matilde; De Franciscis, Sebastiano; Raquel Gámiz-Fortis, Sonia; Castro-Díez, Yolanda; Esteban-Parra, María Jesus
Meteorological inputs play an essential role in predicting the potential effects of climate change on water resources. Consequently, this study is focused on evaluating the skill of Weather Research and Forecasting (WRF) model to simulate present climate characteristics in term of different variables used for hydrological modeling. For the 35-yr period (1980-2014), high-resolution simulations have been performed with a spatial resolution of 0.088° over a domain encompassing the Iberian Peninsula, and nested in the coarser EURO-CORDEX domain (0.44° resolution). WRF model was driven by the global bias-corrected climate model output data from version 1 of NCAR's Community Earth System Model (CESM1). In addition, other simulation forced by the European Centre for Medium-Range Weather Forecasts (ECMWF) Interim Reanalysis (ERA-Interim) as "perfect boundary conditions" was also run. For validation purposes, WRF outputs were compared for Spain and Portugal independently, using two observational data sources: the Spain02 version 4 daily precipitation and (maximum and minimum) temperature gridded datasets, and the PT02 daily gridded precipitation data. The study was carried out at different time scales in order to evaluate the model ability to capture long-term mean values (from annual to monthly) and high-order statistics (extreme events) by directly comparing grid-points. Furthermore, the observational gridded data were grouped using a multistep regionalization to facilitate the comparison in term of several parameters such as the monthly annual cycle or the percentiles of daily values. The main result is that WRF provides useful information at regional scale, with significant improvement in complex terrain areas such as Iberian Peninsula. Although considerable errors are still observed, the model is able to capture the main precipitation and temperature patterns. The major benefits of using WRF are related to the better representation of extreme events that are an
Nielsen, Joakim Refslund; Dellwik, Ebba; Hahmann, Andrea N.
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 a green vegetation fraction (GVF) climatology to represent the seasonal......Climate studies show that the frequency of heat wave events and above-average high temperatures during the summer months over Europe will increase in the coming decades. Such climatic changes and long-term meteorological conditions will impact the seasonal development of vegetation and ultimately...
Full Text Available Weather and climate modelling require dedicated computer infrastructure in order to generate high-resolution, large ensemble, various models with different configurations, etc. in order to optimise operational forecasts and climate projections. High...
Raman, A.; Arellano, A. F.
Prediction of local to regional scale dust events is challenging due to the complex nature of key processes driving emission, transport, and deposition of mineral dust. In particular, it is difficult to map precisely the sources of mineral dust across heterogeneous land surface properties and land-use changes. This is especially true for Arizona haboobs. These dust storm events are typically driven by thunderstorms and down-bursts over arid regions generating high atmospheric loading of dust in the order of hundreds to thousands of microgram per cubic meter. Modeling and prediction of these events are further complicated by the limitations in satellite-derived and in-situ measurements of dust and related geophysical variables. Here, we investigate the capability of a coupled weather-chemistry model in predicting Arizona haboobs. In particular, this research focuses on the simulation of July 5, 2011 Phoenix haboob using Weather Research and Forecasting model coupled with Chemistry (WRF-Chem) and Goddard Chemistry Aerosol Radiation and Transport Model (GOCART) dust scheme. We evaluate the ability of WRF-Chem in simulating the haboob using satellite retrievals of aerosol extinction properties and mass concentrations from Moderate Resolution Imaging Spectroradiometer (MODIS), Cloud-Aerosol Lidar and Infrared Pathfinder Satellite (CALIPSO) and high resolution SEVIRI false color dust product, in conjunction with in-situ PM10 and PM2.5 measurements. The study uses a nested modeling domain covering Utah, California and Arizona at a horizontal resolution of 5.4 km (outer) and 1.8 km (inner). Boundary conditions for the model are obtained from NOAA Global Forecasting System six-hourly forecast. We present results illustrating the key features of the haboobs, such as the cold pools and surface wind speeds driving the horizontal and vertical structure of the dust, as well as the patterns of dust transport and deposition. Although the spatio-temporal patterns of the haboob
Full Text Available The fully coupled WRF/Chem (Weather Research and Forecasting/Chemistry model is used to simulate air quality over coastal areas of the Sea of Japan. The anthropogenic surface emissions database used as input for this model was based primarily on global hourly emissions data (dust, sea salt, and biomass burning, RETRO (REanalysis of the TROpospheric chemical composition, GEIA (Global Emissions Inventory Activity, and POET (Precursors of Ozone and their Effects in the Troposphere. Climatologic concentrations of particulate matter derived from the Regional Acid Deposition Model (RADM2, chemical mechanism, and the Secondary Organic Aerosol Model (MADE/SORGAM with aqueous reactions were used to deduce the corresponding aerosol fluxes for input to the WRF/Chem model. The model was first integrated continuously over 48 hours, starting from 00:00 UTC on 14 March 2008, to evaluate ozone concentrations and other precursor pollutants. WPS meteorological data were used for the WRF/Chem model simulation in this study. Despite the low resolution of global emissions and the weak density of the local point emissions, it was found that the WRF/Chem model simulates the diurnal variation of the chemical species concentrations over the coastal areas of the Sea of Japan quite well. The Air Quality Management Division of the Ministry of the Environment in Japan selected the maximum level of the air quality standard for ozone, which is 60 ppb. In this study, the atmospheric concentrations of ozone over the coastal area of the Sea of Japan were calculated to be 30–55 ppb during the simulation period, which was lower than the Japanese air quality standard for ozone.
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...
Dynamic evaluation of two decades of ozone simulations performed with the fully coupled Weather Research and Forecasting (WRF)–Community Multi-scale Air Quality (CMAQ) model over the contiguous United States is conducted to assess how well the changes in observed ozone air ...
Bell, Jordan R.; Case, Jonathan L.; LaFontaine, Frank J.; Kumar, Sujay V.
The NASA Short-term Prediction Research and Transition (SPoRT) Center has developed a Greenness Vegetation Fraction (GVF) dataset, which is updated daily using swaths of Normalized Difference Vegetation Index data from the Moderate Resolution Imaging Spectroradiometer (MODIS) data aboard the NASA EOS Aqua and Terra satellites. NASA SPoRT began generating daily real-time GVF composites at 1-km resolution over the Continental United States (CONUS) on 1 June 2010. The purpose of this study is to compare the National Centers for Environmental Prediction (NCEP) climatology GVF product (currently used in operational weather models) to the SPoRT-MODIS GVF during June to October 2010. The NASA Land Information System (LIS) was employed to study the impacts of the SPoRT-MODIS GVF dataset on a land surface model (LSM) apart from a full numerical weather prediction (NWP) model. For the 2010 warm season, the SPoRT GVF in the western portion of the CONUS was generally higher than the NCEP climatology. The eastern CONUS GVF had variations both above and below the climatology during the period of study. These variations in GVF led to direct impacts on the rates of heating and evaporation from the land surface. In the West, higher latent heat fluxes prevailed, which enhanced the rates of evapotranspiration and soil moisture depletion in the LSM. By late Summer and Autumn, both the average sensible and latent heat fluxes increased in the West as a result of the more rapid soil drying and higher coverage of GVF. The impacts of the SPoRT GVF dataset on NWP was also examined for a single severe weather case study using the Weather Research and Forecasting (WRF) model. Two separate coupled LIS/WRF model simulations were made for the 17 July 2010 severe weather event in the Upper Midwest using the NCEP and SPoRT GVFs, with all other model parameters remaining the same. Based on the sensitivity results, regions with higher GVF in the SPoRT model runs had higher evapotranspiration and
Jin, J.; Wen, L.; Subin, Z. M.; Miller, N. L.
The Community Land Model version 3.5 (CLM3.5) developed by the National Center for Atmospheric Research (NCAR) was coupled into the Weather Research and Forecasting (WRF) Model version 3.0. The performance of WRF3.0-CLM3.5 in simulating snowpack was extensively evaluated with in-situ observations from a mountainous site called Col de Porte, located in northern Alps region of France, and the Columbia River Basin, located in the northwestern United States. CLM3.5 was configured with a five-layer snow scheme, and includes snow compaction and liquid water transfer processes, and a sophisticated snow albedo scheme. WRF3.0-CLM3.5 was forced with the National Center for Atmospheric Research/National Centers for Environmental Prediction Reanalysis data to simulate for the 1988-1989 snow season for the Col de Porte site and the 2001-2002 season for the Columbia River Basin, with 60km-20km two-way nested domains. The initial simulations show that WRF3.0-CLM3.5 significantly improves snow simulations when compared to those produced with the WRF3.0 coupled to the Noah land surface scheme at the both study sites. However, WRF3.0-CLM3.5 still tends to underestimate the observed snowpack. Calibration with the observed data from the Col de Porte site indicates that the snow water content bias mainly results from stronger, high elevation incoming solar radiation. An adjustment for the radiation scheme in WRF3.0 was made to reduce the incoming radiation to better fit with the observations. This adjustment improves snow simulations at both Col de Porte site and the Columbia River Basin. Additional offline snow simulations with CLM3.5 driven with observed forcing data were performed at the Col de Porte site. These offline simulations are compared to the results produced with the coupled WRF3.0-CLM3.5. Through this comparison, snow-atmosphere interactions are quantitatively indentified. The improved snow simulations in WRF3.0-CLM3.5 will benefit regional hydro-climate research and
Zhang, Yang [Department of Marine, Earth, and Atmospheric Sciences, North Carolina State University, Raleigh North Carolina USA; Collaborative Innovation Center for Regional Environmental Quality, Beijing China; Zhang, Xin [Department of Marine, Earth, and Atmospheric Sciences, North Carolina State University, Raleigh North Carolina USA; Wang, Kai [Department of Marine, Earth, and Atmospheric Sciences, North Carolina State University, Raleigh North Carolina USA; He, Jian [Department of Marine, Earth, and Atmospheric Sciences, North Carolina State University, Raleigh North Carolina USA; Leung, L. Ruby [Pacific Northwest National Laboratory, Richland Washington USA; Fan, Jiwen [Pacific Northwest National Laboratory, Richland Washington USA; Nenes, Athanasios [School of Earth and Atmospheric Sciences, Georgia Institute of Technology, Atlanta Georgia USA; School of Chemical and Biomolecular Engineering, Georgia Institute of Technology, Atlanta Georgia USA
Aerosol activation into cloud droplets is an important process that governs aerosol indirect effects. The advanced treatment of aerosol activation by Fountoukis and Nenes (2005) and its recent updates, collectively called the FN series, have been incorporated into a newly developed regional coupled climate-air quality model based on the Weather Research and Forecasting model with the physics package of the Community Atmosphere Model version 5 (WRF-CAM5) to simulate aerosol-cloud interactions in both resolved and convective clouds. The model is applied to East Asia for two full years of 2005 and 2010. A comprehensive model evaluation is performed for model predictions of meteorological, radiative, and cloud variables, chemical concentrations, and column mass abundances against satellite data and surface observations from air quality monitoring sites across East Asia. The model performs overall well for major meteorological variables including near-surface temperature, specific humidity, wind speed, precipitation, cloud fraction, precipitable water, downward shortwave and longwave radiation, and column mass abundances of CO, SO2, NO2, HCHO, and O3 in terms of both magnitudes and spatial distributions. Larger biases exist in the predictions of surface concentrations of CO and NOx at all sites and SO2, O3, PM2.5, and PM10 concentrations at some sites, aerosol optical depth, cloud condensation nuclei over ocean, cloud droplet number concentration (CDNC), cloud liquid and ice water path, and cloud optical thickness. Compared with the default Abdul-Razzack Ghan (2000) parameterization, simulations with the FN series produce ~107–113% higher CDNC, with half of the difference attributable to the higher aerosol activation fraction by the FN series and the remaining half due to feedbacks in subsequent cloud microphysical processes. With the higher CDNC, the FN series are more skillful in simulating cloud water path, cloud optical thickness, downward shortwave radiation
Li, Qinyi; Zhang, Li; Wang, Tao; Tham, Yee Jun; Ahmadov, Ravan; Xue, Likun; Zhang, Qiang; Zheng, Junyu
The uptake of dinitrogen pentoxide (N2O5) on aerosol surfaces and the subsequent production of nitryl chloride (ClNO2) can have a significant impact on the oxidising capability and thus on secondary pollutants such as ozone. The range of such an impact, however, has not been well quantified in different geographical regions. In this study, we applied the Weather Research and Forecasting coupled with Chemistry (WRF-Chem) model to investigate the impact of the N2O5 uptake processes in the Hong Kong-Pearl River Delta (HK-PRD) region, where the highest ever reported N2O5 and ClNO2 concentrations were observed in our recent field study. We first incorporated into the WRF-Chem an aerosol thermodynamics model (ISORROPIA II), recent parameterisations for N2O5 heterogeneous uptake and ClNO2 production and gas-phase chlorine chemistry. The revised model was then used to simulate the spatiotemporal distribution of N2O5 and ClNO2 over the HK-PRD region and the impact of N2O5 uptake and Cl activation on ozone and reactive nitrogen in the planetary boundary layer (PBL). The updated model can generally capture the temporal variation of N2O5 and ClNO2 observed at a mountaintop site in Hong Kong, but it overestimates N2O5 uptake and ClNO2 production. The model results suggest that under average conditions, elevated levels of ClNO2 (> 0.25 ppb within the PBL) are present in the south-western PRD, with the highest values (> 1.00 ppb) predicted near the ground surface (0-200 m above ground level; a.g.l.). In contrast, during the night when very high levels of ClNO2 and N2O5 were measured in well-processed plumes from the PRD, ClNO2 is mostly concentrated within the residual layer ( ˜ 300 m a.g.l.). The addition of N2O5 heterogeneous uptake and Cl activation reduces the NO and NO2 levels by as much as 1.93 ppb ( ˜ 7.4 %) and 4.73 ppb ( ˜ 16.2 %), respectively, and it increases the total nitrate and ozone concentrations by up to 13.45 µg m-3 ( ˜ 57.4 %) and 7.23 ppb ( ˜ 16
Hanna, Steven R.; Reen, Brian; Hendrick, Elizabeth; Santos, Lynne; Stauffer, David; Deng, Aijun; McQueen, Jeffrey; Tsidulko, Marina; Janjic, Zavisa; Jovic, Dusan; Sykes, R. Ian
The objective of the study is to evaluate operational mesoscale meteorological model atmospheric boundary-layer (ABL) outputs for use in the Hazard Prediction Assessment Capability (HPAC)/Second-Order Closure Integrated Puff (SCIPUFF) transport and dispersion model. HPAC uses the meteorological models’ routine simulations of surface buoyancy flux, winds, and mixing depth to derive the profiles of ABL turbulence. The Fifth-Generation Pennsylvania State University/National Center for Atmospheric Research Mesoscale Model (MM5) and the Weather Research and Forecast-Nonhydrostatic Mesoscale Model (WRF-NMM) ABL outputs and the HPAC ABL parameterisations are compared with observations during the International H2O Project (IHOP). The meteorological models’ configurations are not specially designed research versions for this study but rather are intended to be representative of what may be used operationally and thus have relatively coarse lowest vertical layer thicknesses of 59 and 36 m, respectively. The meteorological models’ simulations of mixing depth are in good agreement (±20%) with observations on most afternoons. Wind speed errors of 1 or 2 ms-1 are found, typical of those found in other studies, with larger errors occurring when the simulated centre of a low-pressure system is misplaced in time or space. The hourly variation of turbulent kinetic energy (TKE) is well-simulated during the daytime, although there is a meteorological model underprediction bias of about 20-40%. At night, WRF-NMM shows fair agreement with observations, and MM5 sometimes produces a very small default TKE value because of the stable boundary-layer parameterisation that is used. The HPAC TKE parameterisation is usually a factor of 5-10 high at night, primarily due to the fact that the meteorological model wind-speed output is at a height of 30 m for MM5 and 18 m for WRF-NMM, which is often well above the stable mixing depth. It is concluded that, before meteorological model TKE
Kuik, Friderike; Lauer, Axel; Churkina, Galina; Denier van der Gon, Hugo A. C.; Fenner, Daniel; Mar, Kathleen A.; Butler, Tim M.
Air pollution is the number one environmental cause of premature deaths in Europe. Despite extensive regulations, air pollution remains a challenge, especially in urban areas. For studying summertime air quality in the Berlin-Brandenburg region of Germany, the Weather Research and Forecasting Model with Chemistry (WRF-Chem) is set up and evaluated against meteorological and air quality observations from monitoring stations as well as from a field campaign conducted in 2014. The objective is to assess which resolution and level of detail in the input data is needed for simulating urban background air pollutant concentrations and their spatial distribution in the Berlin-Brandenburg area. The model setup includes three nested domains with horizontal resolutions of 15, 3 and 1 km and anthropogenic emissions from the TNO-MACC III inventory. We use RADM2 chemistry and the MADE/SORGAM aerosol scheme. Three sensitivity simulations are conducted updating input parameters to the single-layer urban canopy model based on structural data for Berlin, specifying land use classes on a sub-grid scale (mosaic option) and downscaling the original emissions to a resolution of ca. 1 km × 1 km for Berlin based on proxy data including traffic density and population density. The results show that the model simulates meteorology well, though urban 2 m temperature and urban wind speeds are biased high and nighttime mixing layer height is biased low in the base run with the settings described above. We show that the simulation of urban meteorology can be improved when specifying the input parameters to the urban model, and to a lesser extent when using the mosaic option. On average, ozone is simulated reasonably well, but maximum daily 8 h mean concentrations are underestimated, which is consistent with the results from previous modelling studies using the RADM2 chemical mechanism. Particulate matter is underestimated, which is partly due to an underestimation of secondary organic aerosols
National Aeronautics and Space Administration — Facilitate use of Goddard Cumulus Ensemble (GCE), Weather Research and Forecasting Model (WRF), and Goddard Multi-scale Modeling Framework (MMF) with bin...
Kukkonen, J.; Olsson, T.; Schultz, D.M.; Baklanov, A.; Klein, T.; Miranda, A.I.; Monteiro, A.; Hirtl, M.; Tarvainen, V.; Boy, M.; Peuch, V.-H.; Poupkou, A.; Kioutsioukis, I.; Finardi, S.; Sofiev, M.; Sokhi, R.; Lehtinen, K.E.J.; Karatzas, K.; San José, R.; Astitha, M.; Kallos, G.; Schaap, M.; Reimer, E.; Jakobs, H.; Eben, K.
Numerical models that combine weather forecasting and atmospheric chemistry are here referred to as chemical weather forecasting models. Eighteen operational chemical weather forecasting models on regional and continental scales in Europe are described and compared in this article. Topics discussed
Cai, Changjie; Zhang, Xin; Wang, Kai; Zhang, Yang; Wang, Litao; Zhang, Qiang; Duan, Fengkui; He, Kebin; Yu, Shao-Cai
New particle formation (NPF) provides an important source of aerosol particles and cloud condensation nuclei, which may result in enhanced cloud droplet number concentration (CDNC) and cloud shortwave albedo. In this work, several nucleation parameterizations and one particle early growth parameterization are implemented into the online-coupled Weather Research and Forecasting model coupled with chemistry (WRF/Chem) to improve the model's capability in simulating NPF and early growth of ultrafine particles over East Asia. The default 8-bin over the size range of 39 nm-10 μm used in the Model for Simulating Aerosol Interactions and Chemistry aerosol module is expanded to the 12-bin over 1 nm-10 μm to explicitly track the formation and evolution of new particles. Although model biases remain in simulating H2SO4, condensation sink, growth rate, and formation rate, the evaluation of July 2008 simulation identifies a combination of three nucleation parameterizations (i.e., COMB) that can best represent the atmospheric nucleation processes in terms of both surface nucleation events and the resulting vertical distribution of ultrafine particle concentrations. COMB consists of a power law of Wang et al. (2011) based on activation theory for urban areas in planetary boundary layer (PBL), a power law of Boy et al. (2008) based on activation theory for non-urban areas in PBL, and the ion-mediated nucleation parameterization of YU10 for above PBL. The application and evaluation of the improved model with 12-bin and the COMB nucleation parameterization in East Asia during January, April, July, and October in 2001 show that the model has an overall reasonably good skill in reproducing most observed meteorological variables and surface and column chemical concentrations. Relatively large biases in simulated precipitation and wind speeds are due to inaccurate surface roughness and limitations in model treatments of cloud formation and aerosol-cloud-precipitation interactions
El-Samra, R.; Bou-Zeid, E.; Bangalath, H. K.; Stenchikov, G.; El-Fadel, M.
A set of ten downscaling simulations at high spatial resolution (3 km horizontally) were performed using the Weather Research and Forecasting (WRF) model to generate future climate projections of annual and seasonal temperature and precipitation changes over the Eastern Mediterranean (with a focus on Lebanon). The model was driven with the High Resolution Atmospheric Model (HiRAM), running over the whole globe at a resolution of 25 km, under the conditions of two Representative Concentration Pathways (RCP) (4.5 and 8.5). Each downscaling simulation spanned one year. Two past years (2003 and 2008), also forced by HiRAM without data assimilation, were simulated to evaluate the model's ability to capture the cold and wet (2003) and hot and dry (2008) extremes. The downscaled data were in the range of recent observed climatic variability, and therefore corrected for the cold bias of HiRAM. Eight future years were then selected based on an anomaly score that relies on the mean annual temperature and accumulated precipitation to identify the worst year per decade from a water resources perspective. One hot and dry year per decade, from 2011 to 2050, and per scenario was simulated and compared to the historic 2008 reference. The results indicate that hot and dry future extreme years will be exacerbated and the study area might be exposed to a significant decrease in annual precipitation (rain and snow), reaching up to 30% relative to the current extreme conditions.
to deterministic models. Results from ensemble weather input into operational risk management ( ORM ) destruction of enemy air defense simulations...growth during the analysis period (Toth and Kalnay, 1993; Toth and Kalnay, 1997). From this framework the ensemble transform bred vector, ensemble...features. Each of its 10 members is run independently using different configurations in the framework of the Weather Research and Forecasting (WRF
Application of an Online-Coupled Regional Climate Model, WRF-CAM5, over East Asia for Examination of Ice Nucleation Schemes: Part I. Comprehensive Model Evaluation and Trend Analysis for 2006 and 2011
Chen, Ying; Zhang, Yang; Fan, Jiwen; Leung, Lai-Yung; Zhang, Qiang; He, Kebin
Online-coupled climate and chemistry models are necessary to realistically represent the interactions between climate variables and chemical species and accurately simulate aerosol direct and indirect effects on cloud, precipitation, and radiation. In this Part I of a two-part paper, simulations from the Weather Research and Forecasting model coupled with the physics package of Community Atmosphere Model (WRF-CAM5) are conducted with the default heterogeneous ice nucleation parameterization over East Asia for two full years: 2006 and 2011. A comprehensive model evaluation is performed using satellite and surface observations. The model shows an overall acceptable performance for major meteorological variables at the surface and in the boundary layer, as well as column variables (e.g., precipitation, cloud fraction, precipitating water vapor, downward longwave and shortwave radiation). Moderate to large biases exist for cloud condensation nuclei over oceanic areas, cloud variables (e.g., cloud droplet number concentration, cloud liquid and ice water paths, cloud optical depth, longwave and shortwave cloud forcing). These biases indicate a need to improve the model treatments for cloud processes, especially cloud droplets and ice nucleation, as well as to reduce uncertainty in the satellite retrievals. The model simulates well the column abundances of chemical species except for column SO2 but relatively poor for surface concentrations of several species such as CO, NO2, SO2, PM2.5, and PM10. Several reasons could contribute to the underestimation of major chemical species in East Asia including underestimations of anthropogenic emissions and natural dust emissions, uncertainties in the spatial and vertical distributions of the anthropogenic emissions, as well as biases in meteorological, radiative, and cloud predictions. Despite moderate to large biases in the chemical predictions, the model performance is generally consistent with
Application of an Online-Coupled Regional Climate Model, WRF-CAM5, over East Asia for Examination of Ice Nucleation Schemes: Part I. Comprehensive Model Evaluation and Trend Analysis for 2006 and 2011
Full Text Available Online-coupled climate and chemistry models are necessary to realistically represent the interactions between climate variables and chemical species and accurately simulate aerosol direct and indirect effects on cloud, precipitation, and radiation. In this Part I of a two-part paper, simulations from the Weather Research and Forecasting model coupled with the physics package of Community Atmosphere Model (WRF-CAM5 are conducted with the default heterogeneous ice nucleation parameterization over East Asia for two full years: 2006 and 2011. A comprehensive model evaluation is performed using satellite and surface observations. The model shows an overall acceptable performance for major meteorological variables at the surface and in the boundary layer, as well as column variables (e.g., precipitation, cloud fraction, precipitating water vapor, downward longwave and shortwave radiation. Moderate to large biases exist for cloud condensation nuclei over oceanic areas, cloud variables (e.g., cloud droplet number concentration, cloud liquid and ice water paths, cloud optical depth, longwave and shortwave cloud forcing. These biases indicate a need to improve the model treatments for cloud processes, especially cloud droplets and ice nucleation, as well as to reduce uncertainty in the satellite retrievals. The model simulates well the column abundances of chemical species except for column SO2 but relatively poor for surface concentrations of several species such as CO, NO2, SO2, PM2.5, and PM10. Several reasons could contribute to the underestimation of major chemical species in East Asia including underestimations of anthropogenic emissions and natural dust emissions, uncertainties in the spatial and vertical distributions of the anthropogenic emissions, as well as biases in meteorological, radiative, and cloud predictions. Despite moderate to large biases in the chemical predictions, the model performance is generally consistent with or even better
孙银川; 白永清; 左河疆
为了开展西北地区宁夏太阳能光伏发电气象预报服务,基于本地化WRF模式产品及当地光伏电站提供的发电功率资料,提出了EOF分析结合MOS预报的技术方法,进行模式辐射预报的统计订正研究,建立逐时光伏发电功率预测模型,得到较为理想的结果。通过EOF-MOS方法进行辐射预报订正,可使辐照度平均绝对百分比误差（MAPE）由原来24%左右降低到15%左右,模型预测发电功率MAPE稳定在22%左右。尤其是对于转折性天气趋势把握,具有较高的参考价值。%In order to carry out solar photovoltaic power generation forecast service in Ningxia of northwestern China,we used the combination of EOF analysis and MOS forecast method to correct the shortwave radiation WRF model based on the localized WRF model and power generation data from the local photovoltaic power station,and established an hourly photovoltaic power prediction model.Forecast revised by the EOF-MOS method could cause the mean absolute percentage error(MAPE) in solar irradiance forecast reduced from 24% to 15%,and the MAPE in photovoltaic power forecast be stable around 22%.The forecast method presents a good prediction result,especially for the forecast in frequently variable weather.
Wang, N.; Ferraro, R. R.; Gopalan, K.; Tao, W.; Shi, J. J.
As we move from the TRMM to GPM era, more emphasis will be placed on a larger regime of precipitation in mid- and high-latitudes, including light rain, mixed-phase precipitation and snowfall. In these areas, a large and highly variable portion of the total annual precipitation is snow. There is a wealth of observational evidence of brightness temperature depression from frozen hydrometeor scattering at the high frequency from aircraft and spacecraft microwave instruments. Research on the development of snowfall retrieval over land has become increasing important in the last few years (Chen and Staelin, 2003; Kongoli et al., 2004; Skofronick-Jackson et al., 2004, Noh et al., 2006; Aonashi et al., 2007; Liu, 2008; Grecu and Olson, 2008; Kim et al., 2008). However, there is still a considerable amount of work that needs to be done to develop global snowfall detection and retrieval algorithms. This paper describes the development and testing of snowfall models and retrieval algorithms using WRF snowfall simulations and high frequency radiative transfer models for snowfall events took place in January 2007 over Ontario, Canada.
A set of ten downscaling simulations at high spatial resolution (3 km horizontally) were performed using the Weather Research and Forecasting (WRF) model to generate future climate projections of annual and seasonal temperature and precipitation changes over the Eastern Mediterranean (with a focus on Lebanon). The model was driven with the High Resolution Atmospheric Model (HiRAM), running over the whole globe at a resolution of 25 km, under the conditions of two Representative Concentration Pathways (RCP) (4.5 and 8.5). Each downscaling simulation spanned one year. Two past years (2003 and 2008), also forced by HiRAM without data assimilation, were simulated to evaluate the model’s ability to capture the cold and wet (2003) and hot and dry (2008) extremes. The downscaled data were in the range of recent observed climatic variability, and therefore corrected for the cold bias of HiRAM. Eight future years were then selected based on an anomaly score that relies on the mean annual temperature and accumulated precipitation to identify the worst year per decade from a water resources perspective. One hot and dry year per decade, from 2011 to 2050, and per scenario was simulated and compared to the historic 2008 reference. The results indicate that hot and dry future extreme years will be exacerbated and the study area might be exposed to a significant decrease in annual precipitation (rain and snow), reaching up to 30% relative to the current extreme conditions.
Trenhaile, Alan S.
A mathematical, wave-erosional model was modified to study the additional effect of weathering by wetting and drying and salt weathering on the development of shore platforms in macro- to mesotidal environments. Model rates of downwearing by these processes, at different tidal elevations, were based on data obtained from a series of laboratory experiments on sandstones from eastern Canada. Backwearing by mechanical wave erosion was calculated using basic wave equations. There were several types of run which were designed to determine the effect of: weathering and the production of fine-grained sediment; the periodic accumulation of debris on weathering in the upper intertidal zone; and weathering in reducing rock resistance and facilitating wave quarrying. The results implied that, compared to mechanical wave erosion, the direct effect of weathering and fine-grained sediment production makes only a small contribution to the long-term development of shore platforms. The relationship between cliff-foot debris occurrence and platform development and morphology was inconsistent because of the negative feedback relationship between erosion rates, surface gradients, and rates of wave attenuation. The model suggested that weathering can play an important, indirect role in assisting wave quarrying of joint blocks and other rock fragments.
Modeling flash flood events in arid environments is a difficult but important task that has impacts on both water resource related issues and also emergency management and response. The challenge is often related to adequately describing the precursor intense rainfall events that cause these flood responses, as they are generally poorly simulated and forecast. Jeddah, the second largest city in the Kingdom of Saudi Arabia, has suffered from a number of flash floods over the last decade, following short-intense rainfall events. The research presented here focuses on examining four historic Jeddah flash floods (Nov. 25-26 2009, Dec. 29-30 2010, Jan. 14-15 2011 and Jan. 25-26 2011) and investigates the feasibility of using numerical weather prediction models to achieve a more realistic simulation of these flood-producing rainfall events. The Weather Research and Forecasting (WRF) model (version 3.5) is used to simulate precipitation and meteorological conditions via a high-resolution inner domain (1-km) around Jeddah. A range of different convective closure and microphysics parameterization, together with high-resolution (4-km) sea surface temperature data are employed. Through examining comparisons between the WRF model output and in-situ, radar and satellite data, the characteristics and mechanism producing the extreme rainfall events are discussed and the capacity of the WRF model to accurately forecast these rainstorms is evaluated.
Fay, D; Ringwood, John; Condon, M.
Weather information is an important factor in load forecasting models. This weather information usually takes the form of actual weather readings. However, online operation of load forecasting models requires the use of weather forecasts, with associated weather forecast errors. A technique is proposed to model weather forecast errors to reflect current accuracy. A load forecasting model is then proposed which combines the forecasts of several load forecasting models. This approach allows the...
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
Tolosana-Delgado, R.; Soret, A.; Jorba, O.; Baldasano, J. M.; Sánchez-Arcilla, A.
Meteorological models, like WRF, usually describe the earth surface characteristics by tables that are function of land-use. The roughness length (z0) is an example of such approach. However, over sea z0 is modeled by the Charnock (1955) relation, linking the surface friction velocity u*2 with the roughness length z0 of turbulent air flow, z0 = α-u2* g The Charnock coefficient α may be considered a measure of roughness. For the sea surface, WRF considers a constant roughness α = 0.0185. However, there is evidence that sea surface roughness should depend on wave energy (Donelan, 1982). Spectral wave models like WAM, model the evolution and propagation of wave energy as a function of wind, and include a richer sea surface roughness description. Coupling WRF and WAM is thus a common way to improve the sea surface roughness description of WRF. WAM is a third generation wave model, solving the equation of advection of wave energy subject to input/output terms of: wind growth, energy dissipation and resonant non-linear wave-wave interactions. Third generation models work on the spectral domain. WAM considers the Charnock coefficient α a complex yet known function of the total wind input term, which depends on the wind velocity and on the Charnock coefficient again. This is solved iteratively (Janssen et al., 1990). Coupling of meteorological and wave models through a common Charnock coefficient is operationally done in medium-range met forecasting systems (e.g., at ECMWF) though the impact of coupling for smaller domains is not yet clearly assessed (Warner et al, 2010). It is unclear to which extent the additional effort of coupling improves the local wind and wave fields, in comparison to the effects of other factors, like e.g. a better bathymetry and relief resolution, or a better circulation information which might have its influence on local-scale meteorological processes (local wind jets, local convection, daily marine wind regimes, etc.). This work, within the
McCreight, J. L.; Wu, Y.; Gochis, D.; Rafieeinasab, A.; Dugger, A. L.; Yu, W.; Cosgrove, B.; Cui, Z.; Oubeidillah, A.; Briar, D.
The streamflow (discharge) data assimilation capability in version 1 of the National Water Model (NWM; a WRF-Hydro configuration) is applied and evaluated in a 5-year (2011-2015) retrospective study using NLDAS2 forcing data over CONUS. This talk will describe the NWM V1 operational nudging (continuous-time) streamflow data assimilation approach, its motivation, and its relationship to this retrospective evaluation. Results from this study will provide a an analysis-based (not forecast-based) benchmark for streamflow DA in the NWM. The goal of the assimilation is to reduce discharge bias and improve channel initial conditions for discharge forecasting (though forecasts are not considered here). The nudging method assimilates discharge observations at nearly 7,000 USGS gages (at frequency up to 1/15 minutes) to produce a (univariate) discharge reanalysis (i.e. this is the only variable affected by the assimilation). By withholding 14% nested gages throughout CONUS in a separate validation run, we evaluate the downstream impact of assimilation at upstream gages. Based on this sample, we estimate the skill of the streamflow reanalysis at ungaged locations and examine factors governing the skill of the assimilation. Comparison of assimilation and open-loop runs is presented. Performance of DA under both high and low flow regimes and selected flooding events is examined. Preliminary evaluation of nudging parameter sensitivity and its relationship to flow regime will be presented.
Lorente-Plazas, Raquel; García-Díez, Markel; Jimenez-Guerrero, Pedro; Fernández, Jesús; Montavez, Juan Pedro
The assessment of the climate variability over Africa has recently attracted the interest of the regional climate downscaling research community. The main reasons are not only because Africa is a climate change hot-spot, but also due to the low capacity of this region for the adaptation and mitigation under negative impacts and its direct dependency on its socio-economic sustainability of the climate variability. Therefore, improvements in the understanding of the African climate could help the governments in decision-making. Under this umbrella, regional climate models (RCMs) are promising tools to assess the African regional climate. The main advantage of the RCMs, with respect to global reanalysis datasets, is the higher detail provided by the increased resolution which implies a better representation of land-surface interactions and atmospheric processes. However, the confidence on the RCMs strongly depends on the reduction/bounding of uncertainties. One of these sources of uncertainties is associated with the selection of the boundary conditions for driving the regional models. In this work, two identical CORDEX-compliant simulations have been performed over Africa with the unique difference of being driven by two different reanalyses. The reanalyses used were the European Centre for Medium Range Weather Forecasts Interim reanalysis (ERA-I) and the Japanese 25-year reanalysis (JRA-25) by the Japanese Meteorological Service. Both reanalyses have identical temporal resolution (6-hr) but different spatial grid resolution, 0.75 and 1.25 degrees, respectively. The regional model used was the Weather Research and Forecasting Model (WRF). The numerical experiments encompass the period 1989-2010 covering the Africa-CORDEX domain with a 50 km horizontal spatial resolution and 28 vertical levels up to 50 hPa. The WRF simulations are compared between them and against observations. For the mean and maximum temperature the CRU monthly time series (0.25deg) from Climatic
Full Text Available The planetary boundary layer (PBL is the lowest part of the atmosphere and where its character is directly affected by its contact with the underlying planetary surface. The PBL is responsible for vertical sub-grid-scale fluxes due to eddy transport in the whole atmospheric column. It determines the flux profiles within the well-mixed boundary layer and the more stable layer above. It thus provides an evolutionary model of atmospheric temperature, moisture (including clouds, and horizontal momentum in the entire atmospheric column. For such purposes, several PBL models have been proposed and employed in the weather research and forecasting (WRF model of which the Yonsei University (YSU scheme is one. To expedite weather research and prediction, we have put tremendous effort into developing an accelerated implementation of the entire WRF model using graphics processing unit (GPU massive parallel computing architecture whilst maintaining its accuracy as compared to its central processing unit (CPU-based implementation. This paper presents our efficient GPU-based design on a WRF YSU PBL scheme. Using one NVIDIA Tesla K40 GPU, the GPU-based YSU PBL scheme achieves a speedup of 193× with respect to its CPU counterpart running on one CPU core, whereas the speedup for one CPU socket (4 cores with respect to 1 CPU core is only 3.5×. We can even boost the speedup to 360× with respect to 1 CPU core as two K40 GPUs are applied.
Huang, M.; Mielikainen, J.; Huang, B.; Chen, H.; Huang, H.-L. A.; Goldberg, M. D.
The planetary boundary layer (PBL) is the lowest part of the atmosphere and where its character is directly affected by its contact with the underlying planetary surface. The PBL is responsible for vertical sub-grid-scale fluxes due to eddy transport in the whole atmospheric column. It determines the flux profiles within the well-mixed boundary layer and the more stable layer above. It thus provides an evolutionary model of atmospheric temperature, moisture (including clouds), and horizontal momentum in the entire atmospheric column. For such purposes, several PBL models have been proposed and employed in the weather research and forecasting (WRF) model of which the Yonsei University (YSU) scheme is one. To expedite weather research and prediction, we have put tremendous effort into developing an accelerated implementation of the entire WRF model using graphics processing unit (GPU) massive parallel computing architecture whilst maintaining its accuracy as compared to its central processing unit (CPU)-based implementation. This paper presents our efficient GPU-based design on a WRF YSU PBL scheme. Using one NVIDIA Tesla K40 GPU, the GPU-based YSU PBL scheme achieves a speedup of 193× with respect to its CPU counterpart running on one CPU core, whereas the speedup for one CPU socket (4 cores) with respect to 1 CPU core is only 3.5×. We can even boost the speedup to 360× with respect to 1 CPU core as two K40 GPUs are applied.
Full Text Available The planetary boundary layer (PBL is the lowest part of the atmosphere and where its character is directly affected by its contact with the underlying planetary surface. The PBL is responsible for vertical sub-grid-scale fluxes due to eddy transport in the whole atmospheric column. It determines the flux profiles within the well-mixed boundary layer and the more stable layer above. It thus provides an evolutionary model of atmospheric temperature, moisture (including clouds, and horizontal momentum in the entire atmospheric column. For such purposes, several PBL models have been proposed and employed in the weather research and forecasting (WRF model of which the Yonsei University (YSU scheme is one. To expedite weather research and prediction, we have put tremendous effort into developing an accelerated implementation of the entire WRF model using Graphics Processing Unit (GPU massive parallel computing architecture whilst maintaining its accuracy as compared to its CPU-based implementation. This paper presents our efficient GPU-based design on WRF YSU PBL scheme. Using one NVIDIA Tesla K40 GPU, the GPU-based YSU PBL scheme achieves a speedup of 193× with respect to its Central Processing Unit (CPU counterpart running on one CPU core, whereas the speedup for one CPU socket (4 cores with respect to one CPU core is only 3.5×. We can even boost the speedup to 360× with respect to one CPU core as two K40 GPUs are applied.
Del Genio, A. D.; Domagal-Goldman, S. D.; Kiang, N. Y.; Kopparapu, R. K.; Schmidt, G. A.; Sohl, L. E.
Modeling of planetary climate and weather has followed the development of tools for studying Earth, with lags of a few years. Early Earth climate studies were performed with 1-dimensionalradiative-convective models, which were soon fol-lowed by similar models for the climates of Mars and Venus and eventually by similar models for exoplan-ets. 3-dimensional general circulation models (GCMs) became common in Earth science soon after and within several years were applied to the meteorology of Mars, but it was several decades before a GCM was used to simulate extrasolar planets. Recent trends in Earth weather and and climate modeling serve as a useful guide to how modeling of Solar System and exoplanet weather and climate will evolve in the coming decade.
Integrated modelling of physical, chemical and biological weather has been widely considered during the recent decades. Such modelling includes interactions of atmospheric physics and chemical/biological aerosol concentrations. Emitted aerosols are subject to atmospheric transport, dispersion...... and deposition, but in turn they impact the radiation as well as cloud and precipitation formation. The present study focuses on birch pollen modelling as well as on physical and chemical weather with emphasis on black carbon (BC) aerosol modelling. The Enviro-HIRLAM model has been used for the study...
Arnault, Joel; Wagner, Seven; Rummler, Thomas; Fersch, Benjamin; Bliefernicht, Jan; Andresen, Sabine; Kunstmann, Harald
The analysis of land-atmosphere feedbacks requires detailed representation of land processes in atmospheric models. Our focus here is on runoff-infiltration partitioning and resolved overland flow. In the standard version of WRF, runoff-infiltration partitioning is described as a purely vertical process. In WRF-Hydro, runoff is enhanced with lateral water flows. The study region is the Sissili catchment (12800 km2) in West Africa and the study period March 2003 - February 2004. Our WRF setup includes an outer and inner domain at 10 and 2 km resolution covering the West African and Sissili region, respectively. In our WRF-Hydro setup the inner domain is coupled with a sub-grid at 500 m resolution to compute overland and river flow. Model results are compared with TRMM precipitation, MTE evapotranspiration, CCI soil moisture, CRU temperature, and streamflow observation. The role of runoff infiltration partitioning and resolved overland flow on land-atmosphere feedbacks is addressed with a sensitivity analysis of WRF results to the runoff-infiltration partitioning parameter and a comparison between WRF and WRF-Hydro results, respectively. In the outer domain, precipitation is sensitive to runoff-infiltration partitioning at the scale of the Sissili area (~100x100 km2), but not of area A (500x2500 km2). In the inner domain, where precipitation patterns are mainly prescribed by lateral boundary conditions, sensitivity is small, but additionally resolved overland flow here clearly increases infiltration and evapotranspiration at the beginning of the wet season when soils are still dry. Our WRF-Hydro setup shows potential for joint atmospheric and terrestrial water balance studies, and reproduces observed daily discharge with a Nash-Sutcliffe model efficiency coefficient of 0.43.
Nielsen, Joakim Refslund; Dellwik, Ebba; Hahmann, Andrea N.
A method is presented for development of satellite green vegetation fraction (GVF) time series for use in the Weather Research and Forecasting (WRF) model. The GVF data is in the WRF model used to describe the temporal evolution of many land surface parameters, in addition to the evolution...
Temimi, Marouane; Chaouch, Naira; Weston, Michael; Ghedira, Hosni
This study covers five fog events reported in 2014 at Abu Dhabi International Airport in the United Arab Emirates (UAE). We assess the performance of WRF-ARW model during fog conditions and we intercompare seven different PBL schemes and assess their impact on the performance of the simulations. Seven PBL schemes, namely, Yonsei University (YSU), Mellor-Yamada-Janjic (MYJ), Moller-Yamada Nakanishi and Niino (MYNN) level 2.5, Quasi-Normal Scale Elimination (QNSE-EDMF), Asymmetric Convective Model (ACM2), Grenier-Bretherton-McCaa (GBM) and MYNN level 3 were tested. Radiosonde data from the Abu Dhabi International Airport and surface measurements of relative humidity (RH), dew point temperature, wind speed, and temperature profiles were used to assess the performance of the model. All PBL schemes showed comparable skills with relatively higher performance with the QNSE scheme. The average RH Root Mean Square Error (RMSE) and BIAS for all PBLs were 15.75 % and -9.07 %, respectively, whereas the obtained RMSE and BIAS when QNSE was used were 14.65 % and -6.3 % respectively. Comparable skills were obtained for the rest of the variables. Local PBL schemes showed better performance than non-local schemes. Discrepancies between simulated and observed values were higher at the surface level compared to high altitude values. The sensitivity to lead time showed that best simulation performances were obtained when the lead time varies between 12 and 18 hours. In addition, the results of the simulations show that better performance is obtained when the starting condition is dry.
Georgiou, George K.; Christoudias, Theodoros; Proestos, Yiannis; Kushta, Jonilda; Hadjinicolaou, Panos; Lelieveld, Jos
A comprehensive analysis of the performance of three coupled gas-phase chemistry and aerosol mechanisms included in the WRF/Chem model has been performed over the Eastern Mediterranean focusing on Cyprus during the CYPHEX campaign in 2014, using high temporal and spatial resolution. The model performance was evaluated by comparing calculations to measurements of gas phase species (O3, CO, NOx, SO2) and aerosols (PM10, PM2.5) from 13 ground stations. Initial results indicate that the calculated day-to-day and diurnal variations of the aforementioned species show good agreement with observations. The model was set up with three nested grids, downscaling to 4km over Cyprus. The meteorological boundary conditions were updated every 3 hours throughout the simulation using the Global Forecast System (GFS), while chemical boundary conditions were updated every 6 hours using the MOZART global chemical transport model. Biogenic emissions were calculated online by the the Model of Emissions of Gases and Aerosols from Nature version 2.1 (MEGAN2.1). Anthropogenic emissions were based on the EDGAR HTAP v2 global emission inventory, provided on a horizontal grid resolution of 0.1o × 0.1o. Three simulations were performed employing different chemistry and aerosol mechanisms; i) RADM2 chemical mechanism and MADE/SORGAM aerosols, ii) CBMZ chemical mechanism and MOSAIC aerosols, iii) MOZART chemical mechanism and MOSAIC aerosols. Results show that the WRF/Chem model satisfactorily estimates the trace gases relative concentrations at the background sites but not at the urban and traffic sites, while some differences appear between the simulated concentrations by the three mechanisms. The resulting discrepancies between the model outcome and measurements, especially at the urban and traffic sites, suggest that a higher resolution anthropogenic emission inventory might help improve fine resolution, regional air quality modelling. Differences in the simulated concentrations by the
Case. Jonathan; Mungai, John; Sakwa, Vincent; Kabuchanga, Eric; Zavodsky, Bradley T.; Limaye, Ashutosh S.
Flooding and drought are two key forecasting challenges for the Kenya Meteorological Department (KMD). Atmospheric processes leading to excessive precipitation and/or prolonged drought can be quite sensitive to the state of the land surface, which interacts with the boundary layer of the atmosphere providing a source of heat and moisture. 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. Enhanced regional modeling capabilities have the potential to improve forecast guidance in support of daily operations and high-end events over east Africa. KMD currently runs a configuration of the Weather Research and Forecasting (WRF) model in real time to support its daily forecasting operations, invoking the Nonhydrostatic 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. Two organizations at the National Aeronautics and Space Administration Marshall Space Flight Center in Huntsville, AL, SERVIR and the Short-term Prediction Research and Transition (SPoRT) Center, have established a working partnership with KMD for enhancing its regional modeling capabilities. To accomplish this goal, SPoRT and SERVIR will provide experimental land surface initialization datasets and model verification capabilities to KMD. To produce a land-surface initialization more consistent with the resolution of the KMD-WRF runs, the NASA Land Information System (LIS
Kniffka, Anke; Benedetti, Angela; Knippertz, Peter; Stanelle, Tanja; Brooks, Malcolm; Deetz, Konrad; Maranan, Marlon; Rosenberg, Philip; Pante, Gregor; Allan, Richard; Hill, Peter; Adler, Bianca; Fink, Andreas; Kalthoff, Norbert; Chiu, Christine; Vogel, Bernhard; Field, Paul; Marsham, John
DACCIWA (Dynamics-Aerosol-Chemistry-Cloud Interactions in West Africa) is an EU-funded project that aims to determine the influence of anthropogenic and natural emissions on the atmospheric composition, air quality, weather and climate over southern West Africa. DACCIWA organised a major international field campaign in June-July 2016 and involves a wide range of modelling activities. Here we report about the coordinated model evaluation performed in the framework of DACCIWA focusing on meteorological fields. This activity consists of two elements: (a) the quality of numerical weather prediction during the field campaign, (b) the ability of seasonal and climate models to represent the mean state and its variability. For the first element, the extensive observations from the main field campaign in West Africa in June-July 2016 (ground supersites, radiosondes, aircraft measurements) will be combined with conventional data (synoptic stations, satellites data from various sensors) to evaluate models against. The forecasts include operational products from centres such as the ECMWF, UK MetOffice and the German Weather Service and runs specifically conducted for the planning and the post-analysis of the field campaign using higher resolutions (e.g., WRF, COSMO). The forecast and the observations are analysed in a concerted way to assess the ability of the models to represent the southern West African weather systems and secondly to provide a comprehensive synoptic overview of the state of the atmosphere. In a second step the process will be extended to long-term modelling periods. This includes both seasonal and climate models, respectively. In this case, the observational dataset contains long-term satellite observations and station data, some of which were digitised from written records in the framework of DACCIWA. Parameter choice and spatial averaging will build directly on the weather forecasting evaluation to allow an assessment of the impact of short-term errors on
Angevine, W. M.; Brioude, J.; McKeen, S.; Holloway, J. S.
Lagrangian particle dispersion models require meteorological fields as input. Uncertainty in the driving meteorology is one of the major uncertainties in the results. The propagation of uncertainty through the system is not simple, and it has not been thoroughly explored. Here, we take an ensemble approach. Six different configurations of the Weather Research and Forecast (WRF) model drive otherwise identical simulations with FLEXPART-WRF for 49 days over eastern North America. The ensemble spreads of wind speed, mixing height, and tracer concentration are presented. Uncertainty of tracer concentrations due solely to meteorological uncertainty is 30-40%. Spatial and temporal averaging reduces the uncertainty marginally. Tracer age uncertainty due solely to meteorological uncertainty is 15-20%. These are lower bounds on the uncertainty, because a number of processes are not accounted for in the analysis.
© 2015. American Geophysical Union. All Rights Reserved. Two extreme snowfall events associated with extratropical cyclones, one interacting with the western and one with the central Himalaya, are simulated with the Weather Research and Forecasting (WRF) model over 8 days. One event in January 1999 was driven by a longwave trough over west Asia, with the cyclone becoming terrain-locked in the western Himalayan notch. Another event in March 2006 was driven by a trough further south and east, f...
Imran, H. M.; Kala, J.; Ng, A. W. M.; Muthukumaran, S.
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.
E. G. Chapman
Full Text Available The local and regional influence of elevated point sources on summertime aerosol forcing and cloud-aerosol interactions in northeastern North America was investigated using the WRF-Chem community model. The direct effects of aerosols on incoming solar radiation were simulated using existing modules to relate aerosol sizes and chemical composition to aerosol optical properties. Indirect effects were simulated by adding a prognostic treatment of cloud droplet number and adding modules that activate aerosol particles to form cloud droplets, simulate aqueous-phase chemistry, and tie a two-moment treatment of cloud water (cloud water mass and cloud droplet number to an existing radiation scheme. Fully interactive feedbacks thus were created within the modified model, with aerosols affecting cloud droplet number and cloud radiative properties, and clouds altering aerosol size and composition via aqueous processes, wet scavenging, and gas-phase-related photolytic processes. Comparisons of a baseline simulation with observations show that the model captured the general temporal cycle of aerosol optical depths (AODs and produced clouds of comparable thickness to observations at approximately the proper times and places. The model overpredicted SO2 mixing ratios and PM2.5 mass, but reproduced the range of observed SO2 to sulfate aerosol ratios, suggesting that atmospheric oxidation processes leading to aerosol sulfate formation are captured in the model. The baseline simulation was compared to a sensitivity simulation in which all emissions at model levels above the surface layer were set to zero, thus removing stack emissions. Instantaneous, site-specific differences for aerosol and cloud related properties between the two simulations could be quite large, as removing above-surface emission sources influenced when and where clouds formed within the modeling domain. When summed spatially over the finest resolution model
Soares, Pedro; Cardoso, Rita; Lima, Daniela; Miranda, Pedro
Portugal, which is located in the west limit of the Mediterranean subtropics, is a small region with a complex orography with large precipitation gradients and interannual variability. In this study, the newer and higher resolution regional climate simulations, covering Portugal, are evaluated in present climate and used to investigate the rainfall projections for the end of the 21st century, following the RCP4.5 and RCP8.5 emission scenarios. The EURO-CORDEX historical simulations, at 0.11o and at 0.44o resolution, are evaluated against gridded observations of precipitation, which allows the assembly of four multi-model ensembles. An extra simulation, at even higher resolution (9km) with WRF is also analysed. In present climate, the models are able to describe the precipitation temporal and spatial patterns as well its distributions, although there is a large spread and an overestimation of larger rainfall quantiles. The multi-model ensembles show that selecting the best performing models adds quality to the overall representation of rainfall. The high-resolution simulations augment the spatial details of precipitation, but objectively do not seem to add value with respect to the coarse resolution. Regarding the RCP8.5 scenario, WRF and the multi-model ensembles consistently predict important losses of precipitation in Portugal in spring, summer and autumn, ranging from -10% and -50%. For all seasons, the changes are more severe in the southern basins. The precipitation distributions show, for all models, important reductions of the contribution from low to moderate/high precipitation bins and augments of days with strong rainfall. Furthermore, a prominent growth of high-ranking percentiles is predicted reaching values over 70% in some regions. Generally, the changes associated with the RCP4.5 scenario have the same signal and features, but with smaller magnitudes. Acknowledgments The authors wish to acknowledge SOLAR (PTDC/GEOMET/7078/2014) and FCT UID/GEO/50019
Lompar, Miloš; Ćurić, Mladjen; Romanic, Djordje
Despite an important role the aerosols play in all stages of cloud lifecycle, their representation in numerical weather prediction models is often rather crude. This paper investigates the effects the explicit versus implicit inclusion of aerosols in a microphysics parameterization scheme in Weather Research and Forecasting (WRF) - Advanced Research WRF (WRF-ARW) model has on cloud dynamics and microphysics. The testbed selected for this study is a severe mesoscale convective system with supercells that struck west and central parts of Serbia in the afternoon of July 21, 2014. Numerical products of two model runs, i.e. one with aerosols explicitly (WRF-AE) included and another with aerosols implicitly (WRF-AI) assumed, are compared against precipitation measurements from surface network of rain gauges, as well as against radar and satellite observations. The WRF-AE model accurately captured the transportation of dust from the north Africa over the Mediterranean and to the Balkan region. On smaller scales, both models displaced the locations of clouds situated above west and central Serbia towards southeast and under-predicted the maximum values of composite radar reflectivity. Similar to satellite images, WRF-AE shows the mesoscale convective system as a merged cluster of cumulonimbus clouds. Both models over-predicted the precipitation amounts; WRF-AE over-predictions are particularly pronounced in the zones of light rain, while WRF-AI gave larger outliers. Unlike WRF-AI, the WRF-AE approach enables the modelling of time evolution and influx of aerosols into the cloud which could be of practical importance in weather forecasting and weather modification. Several likely causes for discrepancies between models and observations are discussed and prospects for further research in this field are outlined.
Full Text Available Chemical modelling studies have been conducted over north-western Europe in summer conditions, showing that night-time dinitrogen pentoxide (N2O5 heterogeneous reactive uptake is important regionally in modulating particulate nitrate and has a~modest influence on oxidative chemistry. Results from Weather Research and Forecasting model with Chemistry (WRF-Chem model simulations, run with a detailed volatile organic compound (VOC gas-phase chemistry scheme and the Model for Simulating Aerosol Interactions and Chemistry (MOSAIC sectional aerosol scheme, were compared with a series of airborne gas and particulate measurements made over the UK in July 2010. Modelled mixing ratios of key gas-phase species were reasonably accurate (correlations with measurements of 0.7–0.9 for NO2 and O3. However modelled loadings of particulate species were less accurate (correlation with measurements for particulate sulfate and ammonium were between 0.0 and 0.6. Sulfate mass loadings were particularly low (modelled means of 0.5–0.7 μg kg−1air, compared with measurements of 1.0–1.5 μg kg−1air. Two flights from the campaign were used as test cases – one with low relative humidity (RH (60–70%, the other with high RH (80–90%. N2O5 heterogeneous chemistry was found to not be important in the low-RH test case; but in the high-RH test case it had a strong effect and significantly improved the agreement between modelled and measured NO3 and N2O5. When the model failed to capture atmospheric RH correctly, the modelled NO3 and N2O5 mixing ratios for these flights differed significantly from the measurements. This demonstrates that, for regional modelling which involves heterogeneous processes, it is essential to capture the ambient temperature and water vapour profiles. The night-time NO3 oxidation of VOCs across the whole region was found to be 100–300 times slower than the daytime OH oxidation of these compounds. The difference in contribution was less
Hahmann, Andrea N.; Casso, P.; Campmany, E.
We present a method for generalizing wind climatologies generated from mesoscale model output (e.g. the Weather, Research and Forecasting (WRF) model.) The generalization procedure is based on Wind Atlas framework of WAsP and KAMM/WAsP, and been extensively in wind resources assessment in DTU Wind...... generalized wind climatologies estimated by the microscale model WAsP and the methodology presented here. For the Danish wind measurements the mean absolute error in the ‘raw’ wind speeds is 9.2%, while the mean absolute error in the generalized wind speeds is 4.1%. The generalization procedure has been...... installed and automated in the Vortex downscaling chain for the MAPS calculation, which are computed at 3 km horizontal resolution grid. For the MAPS-derived wind speeds the mean absolute error in the ‘raw’ wind speeds is 17.3%, while the mean absolute error in the generalized winds is 10.7%....
Oglesby, R. J.; Rowe, C. M.; Hays, C.
Mesoamerica (the countries from Mexico to Colombia) has been identified by IPCC as a low-latitude, developing region at considerable risk to climate change. Furthermore, the complex topography of the region, and interactions with adjacent tropical oceans, makes understanding of potential climate change from global climate models alone very problematic. Statistical downscaling techniques for the region are not very robust, largely due to the lack of sufficient observations upon which to base the large-scale to small-scale relationships. Therefore, we have used the WRF regional climate model to dynamically downscale global results from a NCAR CCSM simulation employing the A2 emission scenario that was made for IPCC AR4. All of Mesoamerica is covered with a domain with a spatial resolution of 12 km, with selected high elevation regions of Mexico, Colombia, and Peru also covered by 4 km domains. A three-year simulation was made forced by NCEP reanalyses for the years 1991, 1992, and 1993. This run has been evaluated using actual station observations in addition to gridded datasets, in order to identify model strengths and weaknesses (biases) for this region. This comparison clearly demonstrated the need to properly resolve elevation, including both topographic heights and valleys. It also showed the difficulty that the model has in simulating extreme precipitation events, as it usually underestimates the actual amount. Additional five-year simulations were made forced with CCSM output for 2000-2004 (present-day control) and 2050-2054 (climate change scenario for the A2 emission scenario) to investigate potential climate change for the region. Summarizing key results, all land regions, except for a narrow strip along the Pacific coast of Mexico, showed a warming. This warming was largest (up to 3-4 deg C) in the highland regions and the Amazonian basin. The warming was less (generally 1-2 deg C) in the lowland and intermountain regions. Changes in precipitation strongly
Full Text Available The main purpose of this paper is to present a feasible model for the daily average temperature on the area of Zhengzhou and apply it to weather derivatives pricing. We start by exploring the background of weather derivatives market and then use the 62 years of daily historical data to apply the mean-reverting Ornstein-Uhlenbeck process to describe the evolution of the temperature. Finally, Monte Carlo simulations are used to price heating degree day (HDD call option for this city, and the slow convergence of the price of the HDD call can be found through taking 100,000 simulations. The methods of the research will provide a frame work for modeling temperature and pricing weather derivatives in other similar places in China.
Gilmore, James B.; Evans, Jason P.; Sherwood, Steven C.; Ekström, Marie; Ji, Fei
In the context of regional downscaling, we study the representation of extreme precipitation in the Weather Research and Forecasting (WRF) model, focusing on a major event that occurred on the 8th of June 2007 along the coast of eastern Australia (abbreviated "Newy"). This was one of the strongest extra-tropical low-pressure systems off eastern Australia in the last 30 years and was one of several storms comprising a test bed for the WRF ensemble that underpins the regional climate change projections for eastern Australia (New South Wales/Australian Capital Territory Regional Climate Modelling Project, NARCliM). Newy provides an informative case study for examining precipitation extremes as simulated by WRF set up for regional downscaling. Here, simulations from the NARCliM physics ensemble of Newy available at ˜10 km grid spacing are used. Extremes and spatio-temporal characteristics are examined using land-based daily and hourly precipitation totals, with a particular focus on hourly accumulations. Of the different physics schemes assessed, the cumulus and the boundary layer schemes cause the largest differences. Although the Betts-Miller-Janjic cumulus scheme produces better rainfall totals over the entire storm, the Kain-Fritsch cumulus scheme promotes higher and more realistic hourly extreme precipitation totals. Analysis indicates the Kain-Fritsch runs are correlated with larger resolved grid-scale vertical moisture fluxes, which are produced through the influence of parameterized convection on the larger-scale circulation and the subsequent convergence and ascent of moisture. Results show that WRF qualitatively reproduces spatial precipitation patterns during the storm, albeit with some errors in timing. This case study indicates that whilst regional climate simulations of an extreme event such as Newy in WRF may be well represented at daily scales irrespective of the physics scheme used, the representation at hourly scales is likely to be physics scheme
Full Text Available The numerical weather forecast model Weather Research and Forecasting (WRF has a range of applications because it offers multiple physical options, enabling the users to optimizing WRF for specific scales, geographical locations and applications. Summer rainfall cannot be predicted well in North West of Iran (NWI. Most of them are convective. Sometimes rainfall is heavy, so that it causes flash flood. In this research, some configurations of WRF were tested with four summer rainfall events in NWI to find the best configuration. Five cumulus, four planetary boundary layers (PBL and two microphysical schemes were combined. Twenty-six different configurations (models were implemented at two resolutions of 5 and 15 km for duration of 48 h. Four events, with over 20 mm convective daily rainfall total, were selected at NWI during summer season between 2010 and 2015. These events were tested by developing 26 unique models. Results were verified using several methods. The aim was to find the best results during the first 24 h. Although no single configuration can be introduced for all times, thresholds, and atmospheric system to provide reliable and accurate forecast, the best configuration for WRF can be identified. Kain-Fritsch (new Eta, Betts-Miller-Janjic, Modified Kain-Fritsch, Multi-scale Kain-Fritsch and newer Tiedtke cumulus schemes and Mellor-Yamada-Janjic, Shin-Hong ‘scale-aware’, Medium Range Forecast (MRF and Yonsei University (YSU Planetary Boundary Layer schemes and Kessler, WRF Single Moment 3 class simple ice (WSM3 microphysics schemes were selected. The result show that Cumulus schemes are the most sensitive and Microphysics schemes are the less sensitive. The comparison of 15 km and 5 km resolution simulations do not show obvious advantages in downscaling the results. Configuration with newer Tiedtke cumulus, Mellor-Yamada-Janjic PBL, WSM3 and Kessler microphysics schemes give the best results for the 5 and 15 km resolutions. The
Davis, J. R.; Paramygin, V. A.; Figueiredo, R.; Sheng, Y.
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
Tian, Jiyang; Liu, Jia; Wang, Jianhua; Li, Chuanzhe; Yu, Fuliang; Chu, Zhigang
Mesoscale Numerical Weather Prediction systems can provide rainfall products at high resolutions in space and time, playing an increasingly more important role in water management and flood forecasting. The Weather Research and Forecasting (WRF) model is one of the most popular mesoscale systems and has been extensively used in research and practice. However, for hydrologists, an unsolved question must be addressed before each model application in a different target area. That is, how are the most appropriate combinations of physical parameterisations from the vast WRF library selected to provide the best downscaled rainfall? In this study, the WRF model was applied with 12 designed parameterisation schemes with different combinations of physical parameterisations, including microphysics, radiation, planetary boundary layer (PBL), land-surface model (LSM) and cumulus parameterisations. The selected study areas are two semi-humid and semi-arid catchments located in the Daqinghe River basin, Northern China. The performance of WRF with different parameterisation schemes is tested for simulating eight typical 24-h storm events with different evenness in space and time. In addition to the cumulative rainfall amount, the spatial and temporal patterns of the simulated rainfall are evaluated based on a two-dimensional composed verification statistic. Among the 12 parameterisation schemes, Scheme 4 outperforms the other schemes with the best average performance in simulating rainfall totals and temporal patterns; in contrast, Scheme 6 is generally a good choice for simulations of spatial rainfall distributions. Regarding the individual parameterisations, Single-Moment 6 (WSM6), Yonsei University (YSU), Kain-Fritsch (KF) and Grell-Devenyi (GD) are better choices for