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

EPA Science Inventory

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

A Comparison of Modeled Pollutant Profiles With MOZAIC Aircraft Measurements

EPA Science Inventory

In this study, we use measurements performed under the MOZAIC program to evaluate vertical profiles of meteorological parameters, CO, and ozone that were simulated for the year 2006 with several versions of the WRF/CMAQ modeling system. Model updates, including WRF nudging strate...

Simulation of Urban Heat Island Mitigation Strategies in Atlanta, GA Using High-Resolution Land Use/Land Cover Data Set to Enhance Meteorological Modeling

NASA Technical Reports Server (NTRS)

Crosson, William L.; Dembek, Scott; Estes, Maurice G., Jr.; Limaye, Ashutosh S.; Lapenta, William; Quattrochi, Dale A.; Johnson, Hoyt; Khan, Maudood

2006-01-01

The specification of land use/land cover (LULC) and associated land surface parameters in meteorological models at all scales has a major influence on modeled surface energy fluxes and boundary layer states. In urban areas, accurate representation of the land surface may be even more important than in undeveloped regions due to the large heterogeneity within the urban area. Deficiencies in the characterization of the land surface related to the spatial or temporal resolution of the data, the number of LULC classes defined, the accuracy with which they are defined, or the degree of heterogeneity of the land surface properties within each class may degrade the performance of the models. In this study, an experiment was conducted to test a new high-resolution LULC data set for meteorological simulations for the Atlanta, Georgia metropolitan area using a mesoscale meteorological model and to evaluate the effects of urban heat island (UHI) mitigation strategies on modeled meteorology for 2030. Simulation results showed that use of the new LULC data set reduced a major deficiency of the land use data used previously, specifically the poor representation of urban and suburban land use. Performance of the meteorological model improved substantially, with the overall daytime cold bias reduced by over 30%. UHI mitigation strategies were projected to offset much of a predicted urban warming between 2000 and 2030. In fact, for the urban core, the cooling due to UHI mitigation strategies was slightly greater than the warming associated with urbanization over this period. For the larger metropolitan area, cooling only partially offset the projected warming trend.

File Specification for the MERRA Aerosol Reanalysis (MERRAero): MODIS AOD Assimilation based on a MERRA Replay

NASA Technical Reports Server (NTRS)

Da Silva, A. M.; Randles, C. A.; Buchard, V.; Darmenov, A.; Colarco, P. R.; Govindaraju, R.

2015-01-01

This document describes the gridded output files produced by the Goddard Earth Observing System version 5 (GEOS-5) Goddard Aerosol Assimilation System (GAAS) from July 2002 through December 2014. The MERRA Aerosol Reanalysis (MERRAero) is produced with the hydrostatic version of the GEOS-5 Atmospheric Global Climate Model (AGCM). In addition to standard meteorological parameters (wind, temperature, moisture, surface pressure), this simulation includes 15 aerosol tracers (dust, sea-salt, sulfate, black and organic carbon), ozone, carbon monoxide and carbon dioxide. This model simulation is driven by prescribed sea-surface temperature and sea-ice, daily volcanic and biomass burning emissions, as well as high-resolution inventories of anthropogenic emission sources. Meteorology is replayed from the MERRA Reanalysis.

Development of Gridded Fields of Urban Canopy Parameters for Advanced Urban Meteorological and Air Quality Models

EPA Science Inventory

Urban dispersion and air quality simulation models applied at various horizontal scales require different levels of fidelity for specifying the characteristics of the underlying surfaces. As the modeling scales approach the neighborhood level (~1 km horizontal grid spacing), the...

Artificial neural network model for ozone concentration estimation and Monte Carlo analysis

NASA Astrophysics Data System (ADS)

Gao, Meng; Yin, Liting; Ning, Jicai

2018-07-01

Air pollution in urban atmosphere directly affects public-health; therefore, it is very essential to predict air pollutant concentrations. Air quality is a complex function of emissions, meteorology and topography, and artificial neural networks (ANNs) provide a sound framework for relating these variables. In this study, we investigated the feasibility of using ANN model with meteorological parameters as input variables to predict ozone concentration in the urban area of Jinan, a metropolis in Northern China. We firstly found that the architecture of network of neurons had little effect on the predicting capability of ANN model. A parsimonious ANN model with 6 routinely monitored meteorological parameters and one temporal covariate (the category of day, i.e. working day, legal holiday and regular weekend) as input variables was identified, where the 7 input variables were selected following the forward selection procedure. Compared with the benchmarking ANN model with 9 meteorological and photochemical parameters as input variables, the predicting capability of the parsimonious ANN model was acceptable. Its predicting capability was also verified in term of warming success ratio during the pollution episodes. Finally, uncertainty and sensitivity analysis were also performed based on Monte Carlo simulations (MCS). It was concluded that the ANN could properly predict the ambient ozone level. Maximum temperature, atmospheric pressure, sunshine duration and maximum wind speed were identified as the predominate input variables significantly influencing the prediction of ambient ozone concentrations.

Chemical Modeling for Studies of GeoTRACE Capabilities

NASA Technical Reports Server (NTRS)

2005-01-01

Geostationary measurements of tropospheric pollutants with high spatial and temporal resolution will revolutionize the understanding and predictions of the chemically linked global pollutants aerosols and ozone. However, the capabilities of proposed geostationary instruments, particularly GeoTRACE, have not been thoroughly studied with model simulations. Such model simulations are important to answer the questions and allay the concerns that have been expressed in the atmospheric sciences community about the feasibility of such measurements. We proposed a suite of chemical transport model simulations using the EPA Models 3 chemical transport model, which obtains its meteorology from the MM-5 mesoscale model. The model output consists of gridded abundances of chemical pollutants and meteorological parameters every 30-60 minutes for cases that have occurred in the Eastern United States. This output was intended to be used to test the GeoTRACE capability to retrieve the tropospheric columns of these pollutants.

An automated system to simulate the River discharge in Kyushu Island using the H08 model

NASA Astrophysics Data System (ADS)

Maji, A.; Jeon, J.; Seto, S.

2015-12-01

Kyushu Island is located in southwestern part of Japan, and it is often affected by typhoons and a Baiu front. There have been severe water-related disasters recorded in Kyushu Island. On the other hand, because of high population density and for crop growth, water resource is an important issue of Kyushu Island.The simulation of river discharge is important for water resource management and early warning of water-related disasters. This study attempts to apply H08 model to simulate river discharge in Kyushu Island. Geospatial meteorological and topographical data were obtained from Japanese Ministry of Land, Infrastructure, Transport and Tourism (MLIT) and Automated Meteorological Data Acquisition System (AMeDAS) of Japan Meteorological Agency (JMA). The number of the observation stations of AMeDAS is limited and is not quite satisfactory for the application of water resources models in Kyushu. It is necessary to spatially interpolate the point data to produce grid dataset. Meteorological grid dataset is produced by considering elevation dependence. Solar radiation is estimated from hourly sunshine duration by a conventional formula. We successfully improved the accuracy of interpolated data just by considering elevation dependence and found out that the bias is related to geographical location. The rain/snow classification is done by H08 model and is validated by comparing estimated and observed snow rate. The estimates tend to be larger than the corresponding observed values. A system to automatically produce daily meteorological grid dataset is being constructed.The geospatial river network data were produced by ArcGIS and they were utilized in the H08 model to simulate the river discharge. Firstly, this research is to compare simulated and measured specific discharge, which is the ratio of discharge to watershed area. Significant error between simulated and measured data were seen in some rivers. Secondly, the outputs by the coupled model including crop growth module and reservoir operation module were analyzed. However, there are differences between the simulated value and measured value. We need to improve dam operation, artificial water intake, and parameters such as depth of the soil and flow velocity in the river.

Selection of meteorological parameters affecting rainfall estimation using neuro-fuzzy computing methodology

NASA Astrophysics Data System (ADS)

Hashim, Roslan; Roy, Chandrabhushan; Motamedi, Shervin; Shamshirband, Shahaboddin; Petković, Dalibor; Gocic, Milan; Lee, Siew Cheng

2016-05-01

Rainfall is a complex atmospheric process that varies over time and space. Researchers have used various empirical and numerical methods to enhance estimation of rainfall intensity. We developed a novel prediction model in this study, with the emphasis on accuracy to identify the most significant meteorological parameters having effect on rainfall. For this, we used five input parameters: wet day frequency (dwet), vapor pressure (e̅a), and maximum and minimum air temperatures (Tmax and Tmin) as well as cloud cover (cc). The data were obtained from the Indian Meteorological Department for the Patna city, Bihar, India. Further, a type of soft-computing method, known as the adaptive-neuro-fuzzy inference system (ANFIS), was applied to the available data. In this respect, the observation data from 1901 to 2000 were employed for testing, validating, and estimating monthly rainfall via the simulated model. In addition, the ANFIS process for variable selection was implemented to detect the predominant variables affecting the rainfall prediction. Finally, the performance of the model was compared to other soft-computing approaches, including the artificial neural network (ANN), support vector machine (SVM), extreme learning machine (ELM), and genetic programming (GP). The results revealed that ANN, ELM, ANFIS, SVM, and GP had R2 of 0.9531, 0.9572, 0.9764, 0.9525, and 0.9526, respectively. Therefore, we conclude that the ANFIS is the best method among all to predict monthly rainfall. Moreover, dwet was found to be the most influential parameter for rainfall prediction, and the best predictor of accuracy. This study also identified sets of two and three meteorological parameters that show the best predictions.

Ensemble-based flash-flood modelling: Taking into account hydrodynamic parameters and initial soil moisture uncertainties

NASA Astrophysics Data System (ADS)

Edouard, Simon; Vincendon, Béatrice; Ducrocq, Véronique

2018-05-01

Intense precipitation events in the Mediterranean often lead to devastating flash floods (FF). FF modelling is affected by several kinds of uncertainties and Hydrological Ensemble Prediction Systems (HEPS) are designed to take those uncertainties into account. The major source of uncertainty comes from rainfall forcing and convective-scale meteorological ensemble prediction systems can manage it for forecasting purpose. But other sources are related to the hydrological modelling part of the HEPS. This study focuses on the uncertainties arising from the hydrological model parameters and initial soil moisture with aim to design an ensemble-based version of an hydrological model dedicated to Mediterranean fast responding rivers simulations, the ISBA-TOP coupled system. The first step consists in identifying the parameters that have the strongest influence on FF simulations by assuming perfect precipitation. A sensitivity study is carried out first using a synthetic framework and then for several real events and several catchments. Perturbation methods varying the most sensitive parameters as well as initial soil moisture allow designing an ensemble-based version of ISBA-TOP. The first results of this system on some real events are presented. The direct perspective of this work will be to drive this ensemble-based version with the members of a convective-scale meteorological ensemble prediction system to design a complete HEPS for FF forecasting.

A clustering approach for the analysis of solar energy yields: A case study for concentrating solar thermal power plants

NASA Astrophysics Data System (ADS)

Peruchena, Carlos M. Fernández; García-Barberena, Javier; Guisado, María Vicenta; Gastón, Martín

2016-05-01

The design of Concentrating Solar Thermal Power (CSTP) systems requires a detailed knowledge of the dynamic behavior of the meteorology at the site of interest. Meteorological series are often condensed into one representative year with the aim of data volume reduction and speeding-up of energy system simulations, defined as Typical Meteorological Year (TMY). This approach seems to be appropriate for rather detailed simulations of a specific plant; however, in previous stages of the design of a power plant, especially during the optimization of the large number of plant parameters before a final design is reached, a huge number of simulations are needed. Even with today's technology, the computational effort to simulate solar energy system performance with one year of data at high frequency (as 1-min) may become colossal if a multivariable optimization has to be performed. This work presents a simple and efficient methodology for selecting number of individual days able to represent the electrical production of the plant throughout the complete year. To achieve this objective, a new procedure for determining a reduced set of typical weather data in order to evaluate the long-term performance of a solar energy system is proposed. The proposed methodology is based on cluster analysis and permits to drastically reduce computational effort related to the calculation of a CSTP plant energy yield by simulating a reduced number of days from a high frequency TMY.

Atmospheric Model Evaluation Tool for meteorological and air quality simulations

EPA Pesticide Factsheets

The Atmospheric Model Evaluation Tool compares model predictions to observed data from various meteorological and air quality observation networks to help evaluate meteorological and air quality simulations.

Bayesian dynamic modeling of time series of dengue disease case counts.

PubMed

Martínez-Bello, Daniel Adyro; López-Quílez, Antonio; Torres-Prieto, Alexander

2017-07-01

The aim of this study is to model the association between weekly time series of dengue case counts and meteorological variables, in a high-incidence city of Colombia, applying Bayesian hierarchical dynamic generalized linear models over the period January 2008 to August 2015. Additionally, we evaluate the model's short-term performance for predicting dengue cases. The methodology shows dynamic Poisson log link models including constant or time-varying coefficients for the meteorological variables. Calendar effects were modeled using constant or first- or second-order random walk time-varying coefficients. The meteorological variables were modeled using constant coefficients and first-order random walk time-varying coefficients. We applied Markov Chain Monte Carlo simulations for parameter estimation, and deviance information criterion statistic (DIC) for model selection. We assessed the short-term predictive performance of the selected final model, at several time points within the study period using the mean absolute percentage error. The results showed the best model including first-order random walk time-varying coefficients for calendar trend and first-order random walk time-varying coefficients for the meteorological variables. Besides the computational challenges, interpreting the results implies a complete analysis of the time series of dengue with respect to the parameter estimates of the meteorological effects. We found small values of the mean absolute percentage errors at one or two weeks out-of-sample predictions for most prediction points, associated with low volatility periods in the dengue counts. We discuss the advantages and limitations of the dynamic Poisson models for studying the association between time series of dengue disease and meteorological variables. The key conclusion of the study is that dynamic Poisson models account for the dynamic nature of the variables involved in the modeling of time series of dengue disease, producing useful models for decision-making in public health.

Effects of climate change on aerosol concentrations in Europe

NASA Astrophysics Data System (ADS)

Megaritis, Athanasios G.; Fountoukis, Christos; Pandis, Spyros N.

2013-04-01

High concentrations of particulate matter less than 2.5 μm in size (PM2.5), ozone and other major constituents of air pollution, have adverse effects on human health, visibility and ecosystems (Seinfeld and Pandis, 2006), and are strongly influenced by meteorology. Emissions control policy is currently made assuming that climate will remain constant in the future. However, climate change over the next decades is expected to be significant (IPCC, 2007) and may impact local and regional air quality. Determining the sensitivity of the concentrations of air pollutants to climate change is an important step toward estimating future air quality. In this study we applied PMCAMx (Fountoukis et al., 2011), a three dimensional chemical transport model, over Europe, in order to quantify the individual effects of various meteorological parameters on fine particulate matter (PM2.5) concentrations. A suite of perturbations in various meteorological factors, such as temperature, wind speed, absolute humidity and precipitation were imposed separately on base case conditions to determine the sensitivities of PM2.5 concentrations and composition to these parameters. Different simulation periods (summer, autumn 2008 and winter 2009) are used to examine also the seasonal dependence of the air quality - climate interactions. The results of these sensitivity simulations suggest that there is an important link between changes in meteorology and PM2.5 levels. We quantify through separate sensitivity simulations the processes which are mainly responsible for the final predicted changes in PM2.5 concentration and composition. The predicted PM2.5 response to those meteorology perturbations was found to be quite variable in space and time. These results suggest that, the changes in concentrations caused by changes in climate should be taken into account in long-term air quality planning. References Fountoukis C., Racherla P. N., Denier van der Gon H. A. C., Polymeneas P., Charalampidis P. E., Pilinis C., Wiedensohler A., Dall'Osto M., O'Dowd C., and S. N. Pandis: Evaluation of a three-dimensional chemical transport model (PMCAMx) in the European domain during the EUCAARI May 2008 campaign, Atmos. Chem. Phys., 11, 10331-10347, 2011. Intergovernmental Panel on Climate Change (IPCC), Fourth Assessment Report: Summary for Policymakers, 2007. Seinfeld, J. H., and Pandis, S. N.: Atmospheric chemistry and physics: From air pollution to climate change, 2nd ed.; John Wiley and Sons, Hoboken, NJ, 2006.

Surveillance and Control of Malaria Transmission Using Remotely Sensed Meteorological and Environmental Parameters

NASA Technical Reports Server (NTRS)

Kiang, R.; Adimi, F.; Nigro, J.

2007-01-01

Meteorological and environmental parameters important to malaria transmission include temperature, relative humidity, precipitation, and vegetation conditions. These parameters can most conveniently be obtained using remote sensing. Selected provinces and districts in Thailand and Indonesia are used to illustrate how remotely sensed meteorological and environmental parameters may enhance the capabilities for malaria surveillance and control. Hindcastings based on these environmental parameters have shown good agreement to epidemiological records.

Processing TES Level-2 Data

NASA Technical Reports Server (NTRS)

Poosti, Sassaneh; Akopyan, Sirvard; Sakurai, Regina; Yun, Hyejung; Saha, Pranjit; Strickland, Irina; Croft, Kevin; Smith, Weldon; Hoffman, Rodney; Koffend, John;

1D-Var multilayer assimilation of X-band SAR data into a detailed snowpack model

NASA Astrophysics Data System (ADS)

Phan, X. V.; Ferro-Famil, L.; Gay, M.; Durand, Y.; Dumont, M.; Morin, S.; Allain, S.; D'Urso, G.; Girard, A.

2014-10-01

The structure and physical properties of a snowpack and their temporal evolution may be simulated using meteorological data and a snow metamorphism model. Such an approach may meet limitations related to potential divergences and accumulated errors, to a limited spatial resolution, to wind or topography-induced local modulations of the physical properties of a snow cover, etc. Exogenous data are then required in order to constrain the simulator and improve its performance over time. Synthetic-aperture radars (SARs) and, in particular, recent sensors provide reflectivity maps of snow-covered environments with high temporal and spatial resolutions. The radiometric properties of a snowpack measured at sufficiently high carrier frequencies are known to be tightly related to some of its main physical parameters, like its depth, snow grain size and density. SAR acquisitions may then be used, together with an electromagnetic backscattering model (EBM) able to simulate the reflectivity of a snowpack from a set of physical descriptors, in order to constrain a physical snowpack model. In this study, we introduce a variational data assimilation scheme coupling TerraSAR-X radiometric data into the snowpack evolution model Crocus. The physical properties of a snowpack, such as snow density and optical diameter of each layer, are simulated by Crocus, fed by the local reanalysis of meteorological data (SAFRAN) at a French Alpine location. These snowpack properties are used as inputs of an EBM based on dense media radiative transfer (DMRT) theory, which simulates the total backscattering coefficient of a dry snow medium at X and higher frequency bands. After evaluating the sensitivity of the EBM to snowpack parameters, a 1D-Var data assimilation scheme is implemented in order to minimize the discrepancies between EBM simulations and observations obtained from TerraSAR-X acquisitions by modifying the physical parameters of the Crocus-simulated snowpack. The algorithm then re-initializes Crocus with the modified snowpack physical parameters, allowing it to continue the simulation of snowpack evolution, with adjustments based on remote sensing information. This method is evaluated using multi-temporal TerraSAR-X images acquired over the specific site of the Argentière glacier (Mont-Blanc massif, French Alps) to constrain the evolution of Crocus. Results indicate that X-band SAR data can be taken into account to modify the evolution of snowpack simulated by Crocus.

Scaling up watershed model parameters: flow and load simulations of the Edisto River Basin, South Carolina, 2007-09

USGS Publications Warehouse

Feaster, Toby D.; Benedict, Stephen T.; Clark, Jimmy M.; Bradley, Paul M.; Conrads, Paul

2014-01-01

As part of an ongoing effort by the U.S. Geological Survey to expand the understanding of relations among hydrologic, geochemical, and ecological processes that affect fish-tissue mercury concentrations within the Edisto River Basin, analyses and simulations of the hydrology of the Edisto River Basin were made using the topography-based hydrological model (TOPMODEL). A primary focus of the investigation was to assess the potential for scaling up a previous application of TOPMODEL for the McTier Creek watershed, which is a small headwater catchment to the Edisto River Basin. Scaling up was done in a step-wise manner, beginning with applying the calibration parameters, meteorological data, and topographic-wetness-index data from the McTier Creek TOPMODEL to the Edisto River TOPMODEL. Additional changes were made for subsequent simulations, culminating in the best simulation, which included meteorological and topographic wetness index data from the Edisto River Basin and updated calibration parameters for some of the TOPMODEL calibration parameters. The scaling-up process resulted in nine simulations being made. Simulation 7 best matched the streamflows at station 02175000, Edisto River near Givhans, SC, which was the downstream limit for the TOPMODEL setup, and was obtained by adjusting the scaling factor, including streamflow routing, and using NEXRAD precipitation data for the Edisto River Basin. The Nash-Sutcliffe coefficient of model-fit efficiency and Pearson’s correlation coefficient for simulation 7 were 0.78 and 0.89, respectively. Comparison of goodness-of-fit statistics between measured and simulated daily mean streamflow for the McTier Creek and Edisto River models showed that with calibration, the Edisto River TOPMODEL produced slightly better results than the McTier Creek model, despite the substantial difference in the drainage-area size at the outlet locations for the two models (30.7 and 2,725 square miles, respectively). Along with the TOPMODEL hydrologic simulations, a visualization tool (the Edisto River Data Viewer) was developed to help assess trends and influencing variable in the stream ecosystem. Incorporated into the visualization tool were the water-quality load models TOPLOAD, TOPLOAD–H, and LOADEST. Because the focus of this investigation was on scaling up the models from McTier Creek, water-quality concentrations that were previously collected in the McTier Creek Basin were used in the water-quality load models.

Automated source term and wind parameter estimation for atmospheric transport and dispersion applications

NASA Astrophysics Data System (ADS)

Bieringer, Paul E.; Rodriguez, Luna M.; Vandenberghe, Francois; Hurst, Jonathan G.; Bieberbach, George; Sykes, Ian; Hannan, John R.; Zaragoza, Jake; Fry, Richard N.

2015-12-01

Accurate simulations of the atmospheric transport and dispersion (AT&D) of hazardous airborne materials rely heavily on the source term parameters necessary to characterize the initial release and meteorological conditions that drive the downwind dispersion. In many cases the source parameters are not known and consequently based on rudimentary assumptions. This is particularly true of accidental releases and the intentional releases associated with terrorist incidents. When available, meteorological observations are often not representative of the conditions at the location of the release and the use of these non-representative meteorological conditions can result in significant errors in the hazard assessments downwind of the sensors, even when the other source parameters are accurately characterized. Here, we describe a computationally efficient methodology to characterize both the release source parameters and the low-level winds (eg. winds near the surface) required to produce a refined downwind hazard. This methodology, known as the Variational Iterative Refinement Source Term Estimation (STE) Algorithm (VIRSA), consists of a combination of modeling systems. These systems include a back-trajectory based source inversion method, a forward Gaussian puff dispersion model, a variational refinement algorithm that uses both a simple forward AT&D model that is a surrogate for the more complex Gaussian puff model and a formal adjoint of this surrogate model. The back-trajectory based method is used to calculate a ;first guess; source estimate based on the available observations of the airborne contaminant plume and atmospheric conditions. The variational refinement algorithm is then used to iteratively refine the first guess STE parameters and meteorological variables. The algorithm has been evaluated across a wide range of scenarios of varying complexity. It has been shown to improve the source parameters for location by several hundred percent (normalized by the distance from source to the closest sampler), and improve mass estimates by several orders of magnitude. Furthermore, it also has the ability to operate in scenarios with inconsistencies between the wind and airborne contaminant sensor observations and adjust the wind to provide a better match between the hazard prediction and the observations.

Scaling up watershed model parameters--Flow and load simulations of the Edisto River Basin

USGS Publications Warehouse

Feaster, Toby D.; Benedict, Stephen T.; Clark, Jimmy M.; Bradley, Paul M.; Conrads, Paul

2014-01-01

The Edisto River is the longest and largest river system completely contained in South Carolina and is one of the longest free flowing blackwater rivers in the United States. The Edisto River basin also has fish-tissue mercury concentrations that are some of the highest recorded in the United States. As part of an effort by the U.S. Geological Survey to expand the understanding of relations among hydrologic, geochemical, and ecological processes that affect fish-tissue mercury concentrations within the Edisto River basin, analyses and simulations of the hydrology of the Edisto River basin were made with the topography-based hydrological model (TOPMODEL). The potential for scaling up a previous application of TOPMODEL for the McTier Creek watershed, which is a small headwater catchment to the Edisto River basin, was assessed. Scaling up was done in a step-wise process beginning with applying the calibration parameters, meteorological data, and topographic wetness index data from the McTier Creek TOPMODEL to the Edisto River TOPMODEL. Additional changes were made with subsequent simulations culminating in the best simulation, which included meteorological and topographic wetness index data from the Edisto River basin and updated calibration parameters for some of the TOPMODEL calibration parameters. Comparison of goodness-of-fit statistics between measured and simulated daily mean streamflow for the two models showed that with calibration, the Edisto River TOPMODEL produced slightly better results than the McTier Creek model, despite the significant difference in the drainage-area size at the outlet locations for the two models (30.7 and 2,725 square miles, respectively). Along with the TOPMODEL hydrologic simulations, a visualization tool (the Edisto River Data Viewer) was developed to help assess trends and influencing variables in the stream ecosystem. Incorporated into the visualization tool were the water-quality load models TOPLOAD, TOPLOAD-H, and LOADEST. Because the focus of this investigation was on scaling up the models from McTier Creek, water-quality concentrations that were previously collected in the McTier Creek basin were used in the water-quality load models.

Evaluation of the effects of climate and man intervention on ground waters and their dependent ecosystems using time series analysis

NASA Astrophysics Data System (ADS)

Gemitzi, Alexandra; Stefanopoulos, Kyriakos

2011-06-01

SummaryGroundwaters and their dependent ecosystems are affected both by the meteorological conditions as well as from human interventions, mainly in the form of groundwater abstractions for irrigation needs. This work aims at investigating the quantitative effects of meteorological conditions and man intervention on groundwater resources and their dependent ecosystems. Various seasonal Auto-Regressive Integrated Moving Average (ARIMA) models with external predictor variables were used in order to model the influence of meteorological conditions and man intervention on the groundwater level time series. Initially, a seasonal ARIMA model that simulates the abstraction time series using as external predictor variable temperature ( T) was prepared. Thereafter, seasonal ARIMA models were developed in order to simulate groundwater level time series in 8 monitoring locations, using the appropriate predictor variables determined for each individual case. The spatial component was introduced through the use of Geographical Information Systems (GIS). Application of the proposed methodology took place in the Neon Sidirochorion alluvial aquifer (Northern Greece), for which a 7-year long time series (i.e., 2003-2010) of piezometric and groundwater abstraction data exists. According to the developed ARIMA models, three distinct groups of groundwater level time series exist; the first one proves to be dependent only on the meteorological parameters, the second group demonstrates a mixed dependence both on meteorological conditions and on human intervention, whereas the third group shows a clear influence from man intervention. Moreover, there is evidence that groundwater abstraction has affected an important protected ecosystem.

Study of meteorological parameters over the central Himalayan region using balloon-borne sensor

NASA Astrophysics Data System (ADS)

Shrivastava, Rahul; Naja, Manish; Gwal, A. K.

2013-06-01

In the present paper we accumulate the recent advances in atmospheric research by analyzing meteorological data. We have calculated meteorological parameters over the central Himalayan region at Nainital (longitude 79.45□ E, latitude 29.35□N). It is a high altitude place (1951 meters) which is very useful for such type of measurement. We have done our work on meteorological parameters in GVAX (Ganges Valley Aerosol Experiment) project. It was an American-Indo project which was use to capture pre-monsoon to post-monsoon conditions to establish a comprehensive baseline for advancements in the study of the effects of Atmospheric conditions of the Ganges Valley. The Balloon Borne Sounding System (BBSS) technique was also used for in-situ measurements of meteorological parameters.

Role of meteorology in simulating methane seasonal cycle and growth rate

NASA Astrophysics Data System (ADS)

Ghosh, A.; Patra, P. K.; Ishijima, K.; Morimoto, S.; Aoki, S.; Nakazawa, T.

2012-12-01

Methane (CH4) is the second most important anthropogenically produced greenhouse gas whose radiative effect is comparable to that of carbon dioxide since the preindustrial time. Methane also contributes to formation of tropospheric ozone and water vapor in the stratosphere, further increasing its importance to the Earth's radiative balance. In the present study, model simulation of CH4 for three different emission scenarios has been conducted using the CCSR/NIES/FRCGC Atmospheric General Circulation Model (AGCM) based Chemistry Transport Model (ACTM) with and without nudging of meteorological parameters for the period of 1981-2011. The model simulations are compared with measurements at monthly timescale at surface monitoring stations. We show the overall trends in CH4 growth rate and seasonal cycle at most measurement sites can be fairly successfully modeled by using existing knowledge of CH4 flux trends and seasonality. Detailed analysis reveals the model simulation without nudging has greater seasonal cycle amplitude compared to observation as well as the model simulation with nudging. The growth rate is slightly overestimated for the model simulation without nudging. For better representation of regional/global flux distribution pattern and strength in the future, we are exploring various dynamical and chemical aspects in the forward model with and without nudging.

GEMPAK5 user's guide, version 5.0

NASA Technical Reports Server (NTRS)

Desjardins, Mary L.; Brill, Keith F.; Schotz, Steven S.

1991-01-01

GEMPAK is a general meteorological software package used to analyze and display conventional meteorological data as well as satellite derived parameters. The User's Guide describes the GEMPAK5 programs and input parameters and details the algorithms used for the meteorological computations.

Simulating gas and particulate pollution over the Middle East and the state of Qatar using a 3-D regional air quality modeling system

NASA Astrophysics Data System (ADS)

Fountoukis, Christos; Gladich, Ivan; Ayoub, Mohammed; Kais, Sabre; Ackermann, Luis; Skillern, Adam

2016-04-01

The rapid urbanization, industrialization and economic expansion in the Middle East have led to increased levels of atmospheric pollution with important implications for human health and climate. We applied the online-coupled meteorological and chemical transport Weather Research and Forecasting/Chemistry (WRF-Chem) model over the Middle Eastern domain, to simulate the concentration of gas and aerosols with a special focus over the state of Qatar. WRF-Chem was set to simulate pollutant concentrations along with the meteorology-chemistry interactions through the related direct, indirect and semi-direct feedback mechanisms. A triple-nested domain configuration was used with a high grid resolution (1x1 km2) over the region of Qatar. Model predictions are evaluated against intensive measurements of meteorological parameters (temperature, relative humidity and wind speed) as well as ozone and particulate matter taken from various measurement stations throughout Doha, Qatar during summer 2015. The ability of the model to capture the temporal and spatial variability of the observations is assessed and possible reasons for the model bias are explored through sensitivity tests. Emissions of both fine and coarse mode particles from construction activities in large urban Middle Eastern environments comprise a major pollution source that is unaccounted for in emission inventories used so far in large scale models for this part of the world.

THE VALUE OF NUDGING IN THE METEOROLOGY MODEL FOR RETROSPECTIVE CMAQ SIMULATIONS

EPA Science Inventory

Using a nudging-based data assimilation approach throughout a meteorology simulation (i.e., as a "dynamic analysis") is considered valuable because it can provide a better overall representation of the meteorology than a pure forecast. Dynamic analysis is often used in...

Observed and predicted sensitivities of extreme surface ozone to meteorological drivers in three US cities

NASA Astrophysics Data System (ADS)

Fix, Miranda J.; Cooley, Daniel; Hodzic, Alma; Gilleland, Eric; Russell, Brook T.; Porter, William C.; Pfister, Gabriele G.

2018-03-01

We conduct a case study of observed and simulated maximum daily 8-h average (MDA8) ozone (O3) in three US cities for summers during 1996-2005. The purpose of this study is to evaluate the ability of a high resolution atmospheric chemistry model to reproduce observed relationships between meteorology and high or extreme O3. We employ regional coupled chemistry-transport model simulations to make three types of comparisons between simulated and observational data, comparing (1) tails of the O3 response variable, (2) distributions of meteorological predictor variables, and (3) sensitivities of high and extreme O3 to meteorological predictors. This last comparison is made using two methods: quantile regression, for the 0.95 quantile of O3, and tail dependence optimization, which is used to investigate even higher O3 extremes. Across all three locations, we find substantial differences between simulations and observational data in both meteorology and meteorological sensitivities of high and extreme O3.

A Monte-Carlo Analysis of Organic Aerosol Volatility with Aerosol Microphysics

NASA Astrophysics Data System (ADS)

Gao, C. Y.; Tsigaridis, K.; Bauer, S. E.

2016-12-01

A newly developed box model scheme, MATRIX-VBS, includes the volatility-basis set (VBS) framework in an aerosol microphysical scheme MATRIX (Multiconfiguration Aerosol TRacker of mIXing state), which resolves aerosol mass and number concentrations and aerosol mixing state. The new scheme advanced the representation of organic aerosols in Earth system models by improving the traditional and simplistic treatment of organic aerosols as non-volatile and with a fixed size distribution. Further development includes adding the condensation of organics on coarse mode aerosols - dust and sea salt, thus making all organics in the system semi-volatile. To test and simplify the model, a Monte-Carlo analysis is performed to pin point which processes affect organics the most under which chemical and meteorological conditions. Since the model's parameterizations have the ability to capture a very wide range of conditions, from very clean to very polluted and for a wide range of meteorological conditions, all possible scenarios on Earth across the whole parameter space, including temperature, location, emissions and oxidant levels, are examined. The Monte-Carlo simulations provide quantitative information on the sensitivity of the newly developed model and help us understand how organics are affecting the size distribution, mixing state and volatility distribution at varying levels of meteorological conditions and pollution levels. In addition, these simulations give information on which parameters play a critical role in the aerosol distribution and evolution in the atmosphere and which do not, that will facilitate the simplification of the box model, an important step in its implementation in the global model.

Utility of an airframe referenced spatial auditory display for general aviation operations

NASA Astrophysics Data System (ADS)

Naqvi, M. Hassan; Wigdahl, Alan J.; Ranaudo, Richard J.

2009-05-01

The University of Tennessee Space Institute (UTSI) completed flight testing with an airframe-referenced localized audio cueing display. The purpose was to assess its affect on pilot performance, workload, and situational awareness in two scenarios simulating single-pilot general aviation operations under instrument meteorological conditions. Each scenario consisted of 12 test procedures conducted under simulated instrument meteorological conditions, half with the cue off, and half with the cue on. Simulated aircraft malfunctions were strategically inserted at critical times during each test procedure. Ten pilots participated in the study; half flew a moderate workload scenario consisting of point to point navigation and holding pattern operations and half flew a high workload scenario consisting of non precision approaches and missed approach procedures. Flight data consisted of aircraft and navigation state parameters, NASA Task Load Index (TLX) assessments, and post-flight questionnaires. With localized cues there was slightly better pilot technical performance, a reduction in workload, and a perceived improvement in situational awareness. Results indicate that an airframe-referenced auditory display has utility and pilot acceptance in general aviation operations.

Towards Data-Driven Simulations of Wildfire Spread using Ensemble-based Data Assimilation

NASA Astrophysics Data System (ADS)

Rochoux, M. C.; Bart, J.; Ricci, S. M.; Cuenot, B.; Trouvé, A.; Duchaine, F.; Morel, T.

2012-12-01

Real-time predictions of a propagating wildfire remain a challenging task because the problem involves both multi-physics and multi-scales. The propagation speed of wildfires, also called the rate of spread (ROS), is indeed determined by complex interactions between pyrolysis, combustion and flow dynamics, atmospheric dynamics occurring at vegetation, topographical and meteorological scales. Current operational fire spread models are mainly based on a semi-empirical parameterization of the ROS in terms of vegetation, topographical and meteorological properties. For the fire spread simulation to be predictive and compatible with operational applications, the uncertainty on the ROS model should be reduced. As recent progress made in remote sensing technology provides new ways to monitor the fire front position, a promising approach to overcome the difficulties found in wildfire spread simulations is to integrate fire modeling and fire sensing technologies using data assimilation (DA). For this purpose we have developed a prototype data-driven wildfire spread simulator in order to provide optimal estimates of poorly known model parameters [*]. The data-driven simulation capability is adapted for more realistic wildfire spread : it considers a regional-scale fire spread model that is informed by observations of the fire front location. An Ensemble Kalman Filter algorithm (EnKF) based on a parallel computing platform (OpenPALM) was implemented in order to perform a multi-parameter sequential estimation where wind magnitude and direction are in addition to vegetation properties (see attached figure). The EnKF algorithm shows its good ability to track a small-scale grassland fire experiment and ensures a good accounting for the sensitivity of the simulation outcomes to the control parameters. As a conclusion, it was shown that data assimilation is a promising approach to more accurately forecast time-varying wildfire spread conditions as new airborne-like observations of the fire front location get available. [*] Rochoux, M.C., Delmotte, B., Cuenot, B., Ricci, S., and Trouvé, A. (2012) "Regional-scale simulations of wildland fire spread informed by real-time flame front observations", Proc. Combust. Inst., 34, in press http://dx.doi.org/10.1016/j.proci.2012.06.090 EnKF-based tracking of small-scale grassland fire experiment, with estimation of wind and fuel parameters.

Physical Processes in Coastal Stratocumulus Clouds from Aircraft Measurements During UPPEF 2012

DTIC Science & Technology

2013-09-01

pressure, dew point, water vapor, absolute humidity, and carbon dioxide concentration. There were various upward and downward looking pyranometers ...Meteorological parameters IR Temperature -50 to +20 °C Up-looking modified Kipp & Zonen CM-22 pyranometer (CIRPAS/NRL) Meteorological parameters Down...welling Solar Irradiance 0-1400 W m -2 Down-looking modified Kipp & Zonen CM-22 pyranometer (CIRPAS/NRL) Meteorological parameters Up-welling Solar

Enviro-HIRLAM Applicability for Black Carbon Studies in Arctic

NASA Astrophysics Data System (ADS)

Nuterman, Roman; Mahura, Alexander; Baklanov, Alexander; Kurganskiy, Alexander; Amstrup, Bjarne; Kaas, Eigil

2015-04-01

One of the main aims of the Nordic CarboNord project ("Impact of black carbon on air quality and climate in Northern Europe and Arctic") is focused on providing new information on distribution and effects of black carbon in Northern Europe and Arctic. It can be done through assessing robustness of model predictions of long-range black carbon distribution and its relation to climate change and forcing. In our study, the online integrated meteorology-chemistry/aerosols model - Enviro-HIRLAM (Environment - HIgh Resolution Limited Area Model) - is used. This study, at first, is focused on adaptation (model setup, domain for the Northern Hemisphere and Arctic region, emissions, boundary conditions, refining aerosols microphysics and chemistry, cloud-aerosol interaction processes) of Enviro-HIRLAM model and selection of most unfavorable weather and air pollution episodes for the Arctic region. Simulations of interactions between black carbon and meteorological processes in northern conditions for selected episodes will be performed (at DMI's supercomputer HPC CRAY-XT5), and then long-term simulations at regional scale for selected winter vs. summer months. Modelling results will be compared on a diurnal cycle and monthly basis against observations for key meteorological parameters (such as air temperature, wind speed, relative humidity, and precipitation) as well as aerosol concentration. Finally, evaluation of black carbon atmospheric transport, dispersion, and deposition patterns at different spatio-temporal scales; physical-chemical processes and transformations of black carbon containing aerosols; and interactions and effects between black carbon and meteorological processes in Arctic weather conditions will be done.

Sensitivity of potential evapotranspiration and simulated flow to varying meteorological inputs, Salt Creek watershed, DuPage County, Illinois

USGS Publications Warehouse

Whitbeck, David E.

2006-01-01

The Lamoreux Potential Evapotranspiration (LXPET) Program computes potential evapotranspiration (PET) using inputs from four different meteorological sources: temperature, dewpoint, wind speed, and solar radiation. PET and the same four meteorological inputs are used with precipitation data in the Hydrological Simulation Program-Fortran (HSPF) to simulate streamflow in the Salt Creek watershed, DuPage County, Illinois. Streamflows from HSPF are routed with the Full Equations (FEQ) model to determine water-surface elevations. Consequently, variations in meteorological inputs have potential to propagate through many calculations. Sensitivity of PET to variation was simulated by increasing the meteorological input values by 20, 40, and 60 percent and evaluating the change in the calculated PET. Increases in temperatures produced the greatest percent changes, followed by increases in solar radiation, dewpoint, and then wind speed. Additional sensitivity of PET was considered for shifts in input temperatures and dewpoints by absolute differences of ?10, ?20, and ?30 degrees Fahrenheit (degF). Again, changes in input temperatures produced the greatest differences in PET. Sensitivity of streamflow simulated by HSPF was evaluated for 20-percent increases in meteorological inputs. These simulations showed that increases in temperature produced the greatest change in flow. Finally, peak water-surface elevations for nine storm events were compared among unmodified meteorological inputs and inputs with values predicted 6, 24, and 48 hours preceding the simulated peak. Results of this study can be applied to determine how errors specific to a hydrologic system will affect computations of system streamflow and water-surface elevations.

Relative performance of empirical and physical models in assessing the seasonal and annual glacier surface mass balance of Saint-Sorlin Glacier (French Alps)

NASA Astrophysics Data System (ADS)

Réveillet, Marion; Six, Delphine; Vincent, Christian; Rabatel, Antoine; Dumont, Marie; Lafaysse, Matthieu; Morin, Samuel; Vionnet, Vincent; Litt, Maxime

2018-04-01

This study focuses on simulations of the seasonal and annual surface mass balance (SMB) of Saint-Sorlin Glacier (French Alps) for the period 1996-2015 using the detailed SURFEX/ISBA-Crocus snowpack model. The model is forced by SAFRAN meteorological reanalysis data, adjusted with automatic weather station (AWS) measurements to ensure that simulations of all the energy balance components, in particular turbulent fluxes, are accurately represented with respect to the measured energy balance. Results indicate good model performance for the simulation of summer SMB when using meteorological forcing adjusted with in situ measurements. Model performance however strongly decreases without in situ meteorological measurements. The sensitivity of the model to meteorological forcing indicates a strong sensitivity to wind speed, higher than the sensitivity to ice albedo. Compared to an empirical approach, the model exhibited better performance for simulations of snow and firn melting in the accumulation area and similar performance in the ablation area when forced with meteorological data adjusted with nearby AWS measurements. When such measurements were not available close to the glacier, the empirical model performed better. Our results suggest that simulations of the evolution of future mass balance using an energy balance model require very accurate meteorological data. Given the uncertainties in the temporal evolution of the relevant meteorological variables and glacier surface properties in the future, empirical approaches based on temperature and precipitation could be more appropriate for simulations of glaciers in the future.

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

NASA Astrophysics Data System (ADS)

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

2015-12-01

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

Airline meteorological requirements

NASA Technical Reports Server (NTRS)

Chandler, C. L.; Pappas, J.

1985-01-01

A brief review of airline meteorological/flight planning is presented. The effects of variations in meteorological parameters upon flight and operational costs are reviewed. Flight path planning through the use of meteorological information is briefly discussed.

Bayesian dynamic modeling of time series of dengue disease case counts

PubMed Central

López-Quílez, Antonio; Torres-Prieto, Alexander

2017-01-01

The aim of this study is to model the association between weekly time series of dengue case counts and meteorological variables, in a high-incidence city of Colombia, applying Bayesian hierarchical dynamic generalized linear models over the period January 2008 to August 2015. Additionally, we evaluate the model’s short-term performance for predicting dengue cases. The methodology shows dynamic Poisson log link models including constant or time-varying coefficients for the meteorological variables. Calendar effects were modeled using constant or first- or second-order random walk time-varying coefficients. The meteorological variables were modeled using constant coefficients and first-order random walk time-varying coefficients. We applied Markov Chain Monte Carlo simulations for parameter estimation, and deviance information criterion statistic (DIC) for model selection. We assessed the short-term predictive performance of the selected final model, at several time points within the study period using the mean absolute percentage error. The results showed the best model including first-order random walk time-varying coefficients for calendar trend and first-order random walk time-varying coefficients for the meteorological variables. Besides the computational challenges, interpreting the results implies a complete analysis of the time series of dengue with respect to the parameter estimates of the meteorological effects. We found small values of the mean absolute percentage errors at one or two weeks out-of-sample predictions for most prediction points, associated with low volatility periods in the dengue counts. We discuss the advantages and limitations of the dynamic Poisson models for studying the association between time series of dengue disease and meteorological variables. The key conclusion of the study is that dynamic Poisson models account for the dynamic nature of the variables involved in the modeling of time series of dengue disease, producing useful models for decision-making in public health. PMID:28671941

A review of the meteorological parameters which affect aerial application

NASA Technical Reports Server (NTRS)

Christensen, L. S.; Frost, W.

1979-01-01

The ambient wind field and temperature gradient were found to be the most important parameters. Investigation results indicated that the majority of meteorological parameters affecting dispersion were interdependent and the exact mechanism by which these factors influence the particle dispersion was largely unknown. The types and approximately ranges of instrumented capabilities for a systematic study of the significant meteorological parameters influencing aerial applications were defined. Current mathematical dispersion models were also briefly reviewed. Unfortunately, a rigorous dispersion model which could be applied to aerial application was not available.

Identification of sensitive parameters in the modeling of SVOC reemission processes from soil to atmosphere.

PubMed

Loizeau, Vincent; Ciffroy, Philippe; Roustan, Yelva; Musson-Genon, Luc

2014-09-15

Semi-volatile organic compounds (SVOCs) are subject to Long-Range Atmospheric Transport because of transport-deposition-reemission successive processes. Several experimental data available in the literature suggest that soil is a non-negligible contributor of SVOCs to atmosphere. Then coupling soil and atmosphere in integrated coupled models and simulating reemission processes can be essential for estimating atmospheric concentration of several pollutants. However, the sources of uncertainty and variability are multiple (soil properties, meteorological conditions, chemical-specific parameters) and can significantly influence the determination of reemissions. In order to identify the key parameters in reemission modeling and their effect on global modeling uncertainty, we conducted a sensitivity analysis targeted on the 'reemission' output variable. Different parameters were tested, including soil properties, partition coefficients and meteorological conditions. We performed EFAST sensitivity analysis for four chemicals (benzo-a-pyrene, hexachlorobenzene, PCB-28 and lindane) and different spatial scenari (regional and continental scales). Partition coefficients between air, solid and water phases are influent, depending on the precision of data and global behavior of the chemical. Reemissions showed a lower variability to soil parameters (soil organic matter and water contents at field capacity and wilting point). A mapping of these parameters at a regional scale is sufficient to correctly estimate reemissions when compared to other sources of uncertainty. Copyright © 2014 Elsevier B.V. All rights reserved.

Data on the effect of geological and meteorological parameters on indoor radon and thoron level- case study: Kermanshah, Iran.

PubMed

Pirsaheb, Meghdad; Najafi, Farid; Hemati, Lida; Khosravi, Touba; Sharafi, Hooshmand

2018-06-01

The present study was aimed to evaluate the relationship between indoor radon and thoron concentrations, geological and meteorological parameters. The radon and thoron concentrations were determined in three hospitals in Kermanshah, the west part of Iran, using the RTM-1688-2 radon meter. Also, the type and porosity of the underlying soil and the meteorological parameters such as temperature, humidity, atmospheric pressure, rainfall and wind speed were studied and the obtained results analyzed using STATA-Ver.8. In this study the obtained radon concentration was furthered in buildings which constructed on the soil with clayey gravel and sand feature than the soil with clay characteristic and little pasty with a significant difference ( P < 0.05). While the lower coefficient about 1.3 was obtained in measured the thoron concentration and a significant difference was not observed. So the soil porosity can extremely effect on the indoor radon amount. Among all studied meteorological parameters, temperature has been determined as the most important meteorological parameter, influence the indoor radon and thoron concentrations.

Comparison of Malaria Simulations Driven by Meteorological Observations and Reanalysis Products in Senegal.

PubMed

Diouf, Ibrahima; Rodriguez-Fonseca, Belen; Deme, Abdoulaye; Caminade, Cyril; Morse, Andrew P; Cisse, Moustapha; Sy, Ibrahima; Dia, Ibrahima; Ermert, Volker; Ndione, Jacques-André; Gaye, Amadou Thierno

2017-09-25

The analysis of the spatial and temporal variability of climate parameters is crucial to study the impact of climate-sensitive vector-borne diseases such as malaria. The use of malaria models is an alternative way of producing potential malaria historical data for Senegal due to the lack of reliable observations for malaria outbreaks over a long time period. Consequently, here we use the Liverpool Malaria Model (LMM), driven by different climatic datasets, in order to study and validate simulated malaria parameters over Senegal. The findings confirm that the risk of malaria transmission is mainly linked to climate variables such as rainfall and temperature as well as specific landscape characteristics. For the whole of Senegal, a lag of two months is generally observed between the peak of rainfall in August and the maximum number of reported malaria cases in October. The malaria transmission season usually takes place from September to November, corresponding to the second peak of temperature occurring in October. Observed malaria data from the Programme National de Lutte contre le Paludisme (PNLP, National Malaria control Programme in Senegal) and outputs from the meteorological data used in this study were compared. The malaria model outputs present some consistencies with observed malaria dynamics over Senegal, and further allow the exploration of simulations performed with reanalysis data sets over a longer time period. The simulated malaria risk significantly decreased during the 1970s and 1980s over Senegal. This result is consistent with the observed decrease of malaria vectors and malaria cases reported by field entomologists and clinicians in the literature. The main differences between model outputs and observations regard amplitude, but can be related not only to reanalysis deficiencies but also to other environmental and socio-economic factors that are not included in this mechanistic malaria model framework. The present study can be considered as a validation of the reliability of reanalysis to be used as inputs for the calculation of malaria parameters in the Sahel using dynamical malaria models.

Computer simulations of space-borne meteorological systems on the CYBER 205

NASA Technical Reports Server (NTRS)

Halem, M.

1984-01-01

Because of the extreme expense involved in developing and flight testing meteorological instruments, an extensive series of numerical modeling experiments to simulate the performance of meteorological observing systems were performed on CYBER 205. The studies compare the relative importance of different global measurements of individual and composite systems of the meteorological variables needed to determine the state of the atmosphere. The assessments are made in terms of the systems ability to improve 12 hour global forecasts. Each experiment involves the daily assimilation of simulated data that is obtained from a data set called nature. This data is obtained from two sources: first, a long two-month general circulation integration with the GLAS 4th Order Forecast Model and second, global analysis prepared by the National Meteorological Center, NOAA, from the current observing systems twice daily.

Simulation of the Tornado Event of 22 March, 2013 over Brahmanbaria, Bangladesh using WRF Model with 3DVar DA techniques

NASA Astrophysics Data System (ADS)

Ahasan, M. N.; Alam, M. M.; Debsarma, S. K.

2015-02-01

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.

Contribution of rainfall, snow and ice melt to the hydrological regime of the Arve upper catchment and to severe flood events

NASA Astrophysics Data System (ADS)

Lecourt, Grégoire; Revuelto, Jesús; Morin, Samuel; Zin, Isabella; Lafaysse, Matthieu; Condom, Thomas; Six, Delphine; Vionnet, Vincent; Charrois, Luc; Dumont, Marie; Gottardi, Frédéric; Laarman, Olivier; Coulaud, Catherine; Esteves, Michel; Lebel, Thierry; Vincent, Christian

2016-04-01

In Alpine catchments, the hydrological response to meteorological events is highly influenced by the precipitation phase (liquid or solid) and by snow and ice melt. It is thus necessary to simulate accurately the snowpack evolution and its spatial distribution to perform relevant hydrological simulations. This work is focused on the upper Arve Valley (Western Alps). This 205 km2 catchment has large glaciated areas (roughly 32% of the study area) and covers a large range of elevations (1000-4500 m a.s.l.). Snow presence is significant year-round. The area is also characterized by steep terrain and strong vegetation heterogeneity. Modelling hydrological processes in such a complex catchment is therefore challenging. The detailed ISBA land surface model (including the Crocus snowpack scheme) has been applied to the study area using a topography based discretization (classifying terrain by aspect, elevation, slope and presence of glacier). The meteorological forcing used to run the simulations is the reanalysis issued from the SAFRAN model which assimilates meteorological observations from the Meteo-France networks. Conceptual reservoirs with calibrated values of emptying parameters are used to represent the underground water storage. This approach has been tested to simulate the discharge on the Arve catchment and three sub-catchments over 1990-2015. The simulations were evaluated with respect to observed water discharges for several headwaters with varying glaciated areas. They allow to quantify the relative contribution of rainfall, snow and ice melt to the hydrological regime of the basin. Additionally, we present a detailed analysis of several particular flood events. For these events, the ability of the model to correctly represent the catchment behaviour is investigated, looking particularly to the relevance of the simulated snowpack. Particularly, its spatial distribution is evaluated using MODIS snow cover maps, punctual snowpack observations and summer glacier mass balance estimations.

[Sensitivity analysis of AnnAGNPS model's hydrology and water quality parameters based on the perturbation analysis method].

PubMed

Xi, Qing; Li, Zhao-Fu; Luo, Chuan

2014-05-01

Sensitivity analysis of hydrology and water quality parameters has a great significance for integrated model's construction and application. Based on AnnAGNPS model's mechanism, terrain, hydrology and meteorology, field management, soil and other four major categories of 31 parameters were selected for the sensitivity analysis in Zhongtian river watershed which is a typical small watershed of hilly region in the Taihu Lake, and then used the perturbation method to evaluate the sensitivity of the parameters to the model's simulation results. The results showed that: in the 11 terrain parameters, LS was sensitive to all the model results, RMN, RS and RVC were generally sensitive and less sensitive to the output of sediment but insensitive to the remaining results. For hydrometeorological parameters, CN was more sensitive to runoff and sediment and relatively sensitive for the rest results. In field management, fertilizer and vegetation parameters, CCC, CRM and RR were less sensitive to sediment and particulate pollutants, the six fertilizer parameters (FR, FD, FID, FOD, FIP, FOP) were particularly sensitive for nitrogen and phosphorus nutrients. For soil parameters, K is quite sensitive to all the results except the runoff, the four parameters of the soil's nitrogen and phosphorus ratio (SONR, SINR, SOPR, SIPR) were less sensitive to the corresponding results. The simulation and verification results of runoff in Zhongtian watershed show a good accuracy with the deviation less than 10% during 2005- 2010. Research results have a direct reference value on AnnAGNPS model's parameter selection and calibration adjustment. The runoff simulation results of the study area also proved that the sensitivity analysis was practicable to the parameter's adjustment and showed the adaptability to the hydrology simulation in the Taihu Lake basin's hilly region and provide reference for the model's promotion in China.

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

EPA Science Inventory

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

Three-D Simulation of the Origin of the Pollutant Ozone Maxima in the Great African Plume: New Meteorology, New Chemistry for TRACE-A

NASA Technical Reports Server (NTRS)

Chatfeild, Robert; Vastano, John; Singh, Hanwant; Chan, K. Roland (Technical Monitor)

1996-01-01

Burning in South Central Africa is primarily responsible for the vast buildup of ozone in the mid-Atlantic noticeable in the Belem, Brazil, ozonesondes, and also visible in analyses using the Total Ozone Mapping Spectrometer (TOMS). We report on full-scale chemistry simulations for the SAFARI/TRACE-A field period of September-October, 1992. These observational programs provided a wealth of comparison data, including spectacular depictions of the vertical structure of ozone and particulate pollution over Africa, South America, and the Equatorial Atlantic [Browell JGR, 1996, submitted] above and below the NASA DC-8 airplane path. These depictions provide strict tests on the ability of a 3-d simulation and its controlling input parameters, most notably the biomass burning emissions strength. We use meteorology from MM5 used as a synoptic assimilation model and our own GRACES Global Regional Air Chemistry Event Simulator. This report will focus on the unique meteorology of the Equatorial Atmosphere around the Gulf of Guinea during the TRACE-A period, which we describe as "the opening of the gate," "the Great African Plume," and the "African Recirculatory System." We expect to assess whether the ozone observed is primarily "transported African smog," the standard view, or whether "re-$NO_[x)$-ification" of the Central Atlantic troposphere (reduction of nitric acid to active nitrogen oxides in clouds or aerosol) may be required for "extended intercontinental ozone production." A status report on a second nitrogen problem, "lower-tropospheric missing NO(y)," in which we find a serious imbalance in the $NO_ {x }$ and $NO_{y}$ budgets when compared with similar atmospheric tracers, will be given. An elaboration of the concepts set off by quotation marks in this abstract will be given in the talk.

Inter-annual variability of carbon fluxes in temperate forest ecosystems: effects of biotic and abiotic factors

NASA Astrophysics Data System (ADS)

Chen, M.; Keenan, T. F.; Hufkens, K.; Munger, J. W.; Bohrer, G.; Brzostek, E. R.; Richardson, A. D.

2014-12-01

Carbon dynamics in terrestrial ecosystems are influenced by both abiotic and biotic factors. Abiotic factors, such as variation in meteorological conditions, directly drive biophysical and biogeochemical processes; biotic factors, referring to the inherent properties of the ecosystem components, reflect the internal regulating effects including temporal dynamics and memory. The magnitude of the effect of abiotic and biotic factors on forest ecosystem carbon exchange has been suggested to vary at different time scales. In this study, we design and conduct a model-data fusion experiment to investigate the role and relative importance of the biotic and abiotic factors for inter-annual variability of the net ecosystem CO2 exchange (NEE) of temperate deciduous forest ecosystems in the Northeastern US. A process-based model (FöBAAR) is parameterized at four eddy-covariance sites using all available flux and biometric measurements. We conducted a "transplant" modeling experiment, that is, cross- site and parameter simulations with different combinations of site meteorology and parameters. Using wavelet analysis and variance partitioning techniques, analysis of model predictions identifies both spatial variant and spatially invariant parameters. Variability of NEE was primarily modulated by gross primary productivity (GPP), with relative contributions varying from hourly to yearly time scales. The inter-annual variability of GPP and NEE is more regulated by meteorological forcing, but spatial variability in certain model parameters (biotic response) has more substantial effects on the inter-annual variability of ecosystem respiration (Reco) through the effects on carbon pools. Both the biotic and abiotic factors play significant roles in modulating the spatial and temporal variability in terrestrial carbon cycling in the region. Together, our study quantifies the relative importance of both, and calls for better understanding of them to better predict regional CO2 exchanges.

Astronomical, physical, and meteorological parameters for planetary atmospheres

NASA Technical Reports Server (NTRS)

Allison, Michael; Travis, Larry D.

1986-01-01

A newly compiled table of astronomical, physical, and meteorological parameters for planetary atmospheres is presented. Formulae and explanatory notes for their application and a complete listing of sources are also given.

The impacts of urban surface characteristics on radiation balance and meteorological variables in the boundary layer around Beijing in summertime

NASA Astrophysics Data System (ADS)

Liu, Ruiting; Han, Zhiwei; Wu, Jian; Hu, Yonghong; Li, Jiawei

2017-11-01

In this study, some key geometric and thermal parameters derived from recent field and satellite observations in Beijing were collected and incorporated into WRF-UCM (Weather Research and Forecasting) model instead of previous default ones. A series of sensitivity model simulations were conducted to investigate the influences of these parameters on radiation balance, meteorological variables, turbulence kinetic energy (TKE), as well as planetary boundary layer height (PBLH) in regions around Beijing in summer 2014. Model validation demonstrated that the updated parameters represented urban surface characteristics more realistically and the simulations of meteorological variables were evidently improved to be closer to observations than the default parameters. The increase in building height tended to increase and slightly decrease surface air temperature at 2 m (T2) at night and around noon, respectively, and to reduce wind speed at 10 m (WS10) through a day. The increase in road width led to significant decreases in T2 and WS10 through the whole day, with the maximum changes in early morning and in evening, respectively. Both lower surface albedo and inclusion of anthropogenic heat (AH) resulted in increases in T2 and WS10 over the day, with stronger influence from AH. The vertical extension of the impact of urban surface parameters was mainly confined within 300 m at night and reached as high as 1600 m during daytime. The increase in building height tended to increase TKE and PBLH and the TKE increase was larger at night than during daytime due to enhancements of both mechanical and buoyant productions. The increase in road width generally reduced TKE and PBLH except for a few hours in the afternoon. The lower surface albedo and the presence of AH consistently resulted in increases of TKE and PBLH through both day and night. The increase in building height induced a slight divergence by day and a notable convergence at night, whereas the increase in road width led to a remarkable divergence through the entire day. Both AH and lower surface albedo induced a wind convergence over the day, which tended to strengthen nighttime mountain downslope wind and daytime southerly wind to the south of Beijing, but to weaken daytime upslope wind in mountain areas.

Selecting climate simulations for impact studies based on multivariate patterns of climate change.

PubMed

Mendlik, Thomas; Gobiet, Andreas

In climate change impact research it is crucial to carefully select the meteorological input for impact models. We present a method for model selection that enables the user to shrink the ensemble to a few representative members, conserving the model spread and accounting for model similarity. This is done in three steps: First, using principal component analysis for a multitude of meteorological parameters, to find common patterns of climate change within the multi-model ensemble. Second, detecting model similarities with regard to these multivariate patterns using cluster analysis. And third, sampling models from each cluster, to generate a subset of representative simulations. We present an application based on the ENSEMBLES regional multi-model ensemble with the aim to provide input for a variety of climate impact studies. We find that the two most dominant patterns of climate change relate to temperature and humidity patterns. The ensemble can be reduced from 25 to 5 simulations while still maintaining its essential characteristics. Having such a representative subset of simulations reduces computational costs for climate impact modeling and enhances the quality of the ensemble at the same time, as it prevents double-counting of dependent simulations that would lead to biased statistics. The online version of this article (doi:10.1007/s10584-015-1582-0) contains supplementary material, which is available to authorized users.

Mitigation of global cooling by stratospheric chemistry feedbacks in a simulation of the Last Glacial Maximum

NASA Astrophysics Data System (ADS)

Noda, S.; Kodera, K.; Deushi, M.; Kitoh, A.; Mizuta, R.; Yoshida, K.; Murakami, S.; Adachi, Y.; Yoden, S.

2017-12-01

A series of numerical simulations of the Last Glacial Maximum (21 kyr B.P.) climate are performed by using an Earth System Model of the Meteorological Research Institute of the Japan Meteorological Agency to investigate the impact of stratospheric ozone profile on the surface climate with decreased CO2 condition and different orbital parameters. The contribution of the interactive ozone chemistry reveals a significant anomaly of +0.5 K (approximately 20 %) in the tropics and up to +1.5 K in high-latitudes for the annual mean zonal mean surface air temperature compared with those of the corresponding experiments with a prescribed ozone profile for preindustrial simulation of the fifth Coupled Model Intercomparison Project (CMIP5). In the tropics, this mitigation of global cooling is related to longwave radiative feedbacks associated with circulation-driven increases in lower stratospheric ozone and related increase in stratospheric water vapor and related decrease in cirrus cloud. The relations are opposite signs to and consistent with those of a global warming simulation. In high-latitudes, the polar amplification of mitigation of cooling associated with the change of sea ice area that is the same sign to and consistent with our previous paleoclimate simulation in the mid-Holocene (6 kyr B.P.). We recommend that climate models include sea ice and ozone profile that are consistent with CO2 concentration.

Development of an Aircraft Approach and Departure Atmospheric Profile Generation Algorithm

NASA Technical Reports Server (NTRS)

Buck, Bill K.; Velotas, Steven G.; Rutishauser, David K. (Technical Monitor)

2004-01-01

In support of NASA Virtual Airspace Modeling and Simulation (VAMS) project, an effort was initiated to develop and test techniques for extracting meteorological data from landing and departing aircraft, and for building altitude based profiles for key meteorological parameters from these data. The generated atmospheric profiles will be used as inputs to NASA s Aircraft Vortex Spacing System (AVOLSS) Prediction Algorithm (APA) for benefits and trade analysis. A Wake Vortex Advisory System (WakeVAS) is being developed to apply weather and wake prediction and sensing technologies with procedures to reduce current wake separation criteria when safe and appropriate to increase airport operational efficiency. The purpose of this report is to document the initial theory and design of the Aircraft Approach Departure Atmospheric Profile Generation Algorithm.

Derivation of global vegetation biophysical parameters from EUMETSAT Polar System

NASA Astrophysics Data System (ADS)

García-Haro, Francisco Javier; Campos-Taberner, Manuel; Muñoz-Marí, Jordi; Laparra, Valero; Camacho, Fernando; Sánchez-Zapero, Jorge; Camps-Valls, Gustau

2018-05-01

This paper presents the algorithm developed in LSA-SAF (Satellite Application Facility for Land Surface Analysis) for the derivation of global vegetation parameters from the AVHRR (Advanced Very High Resolution Radiometer) sensor on board MetOp (Meteorological-Operational) satellites forming the EUMETSAT (European Organization for the Exploitation of Meteorological Satellites) Polar System (EPS). The suite of LSA-SAF EPS vegetation products includes the leaf area index (LAI), the fractional vegetation cover (FVC), and the fraction of absorbed photosynthetically active radiation (FAPAR). LAI, FAPAR, and FVC characterize the structure and the functioning of vegetation and are key parameters for a wide range of land-biosphere applications. The algorithm is based on a hybrid approach that blends the generalization capabilities offered by physical radiative transfer models with the accuracy and computational efficiency of machine learning methods. One major feature is the implementation of multi-output retrieval methods able to jointly and more consistently estimate all the biophysical parameters at the same time. We propose a multi-output Gaussian process regression (GPRmulti), which outperforms other considered methods over PROSAIL (coupling of PROSPECT and SAIL (Scattering by Arbitrary Inclined Leaves) radiative transfer models) EPS simulations. The global EPS products include uncertainty estimates taking into account the uncertainty captured by the retrieval method and input errors propagation. A sensitivity analysis is performed to assess several sources of uncertainties in retrievals and maximize the positive impact of modeling the noise in training simulations. The paper discusses initial validation studies and provides details about the characteristics and overall quality of the products, which can be of interest to assist the successful use of the data by a broad user's community. The consistent generation and distribution of the EPS vegetation products will constitute a valuable tool for monitoring of earth surface dynamic processes.

Can nudging be used to quantify model sensitivities in precipitation and cloud forcing?

NASA Astrophysics Data System (ADS)

Lin, Guangxing; Wan, Hui; Zhang, Kai; Qian, Yun; Ghan, Steven J.

2016-09-01

Efficient simulation strategies are crucial for the development and evaluation of high-resolution climate models. This paper evaluates simulations with constrained meteorology for the quantification of parametric sensitivities in the Community Atmosphere Model version 5 (CAM5). Two parameters are perturbed as illustrating examples: the convection relaxation time scale (TAU), and the threshold relative humidity for the formation of low-level stratiform clouds (rhminl). Results suggest that the fidelity of the constrained simulations depends on the detailed implementation of nudging and the mechanism through which the perturbed parameter affects precipitation and cloud. The relative computational costs of nudged and free-running simulations are determined by the magnitude of internal variability in the physical quantities of interest, as well as the magnitude of the parameter perturbation. In the case of a strong perturbation in convection, temperature, and/or wind nudging with a 6 h relaxation time scale leads to nonnegligible side effects due to the distorted interactions between resolved dynamics and parameterized convection, while 1 year free-running simulations can satisfactorily capture the annual mean precipitation and cloud forcing sensitivities. In the case of a relatively weak perturbation in the large-scale condensation scheme, results from 1 year free-running simulations are strongly affected by natural noise, while nudging winds effectively reduces the noise, and reasonably reproduces the sensitivities. These results indicate that caution is needed when using nudged simulations to assess precipitation and cloud forcing sensitivities to parameter changes in general circulation models. We also demonstrate that ensembles of short simulations are useful for understanding the evolution of model sensitivities.

SSE Data and Information

Atmospheric Science Data Center

2018-04-03

Surface meteorology and Solar Energy (SSE) Data and Information The Release 6.0 Surface meteorology and Solar Energy ( SSE ) data set contains parameters formulated for assessing and designing renewable energy systems. This latest release contains new parameters based on ...

Kalman filter data assimilation: targeting observations and parameter estimation.

PubMed

Bellsky, Thomas; Kostelich, Eric J; Mahalov, Alex

2014-06-01

This paper studies the effect of targeted observations on state and parameter estimates determined with Kalman filter data assimilation (DA) techniques. We first provide an analytical result demonstrating that targeting observations within the Kalman filter for a linear model can significantly reduce state estimation error as opposed to fixed or randomly located observations. We next conduct observing system simulation experiments for a chaotic model of meteorological interest, where we demonstrate that the local ensemble transform Kalman filter (LETKF) with targeted observations based on largest ensemble variance is skillful in providing more accurate state estimates than the LETKF with randomly located observations. Additionally, we find that a hybrid ensemble Kalman filter parameter estimation method accurately updates model parameters within the targeted observation context to further improve state estimation.

Kalman filter data assimilation: Targeting observations and parameter estimation

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

Bellsky, Thomas, E-mail: bellskyt@asu.edu; Kostelich, Eric J.; Mahalov, Alex

2014-06-15

This paper studies the effect of targeted observations on state and parameter estimates determined with Kalman filter data assimilation (DA) techniques. We first provide an analytical result demonstrating that targeting observations within the Kalman filter for a linear model can significantly reduce state estimation error as opposed to fixed or randomly located observations. We next conduct observing system simulation experiments for a chaotic model of meteorological interest, where we demonstrate that the local ensemble transform Kalman filter (LETKF) with targeted observations based on largest ensemble variance is skillful in providing more accurate state estimates than the LETKF with randomly locatedmore » observations. Additionally, we find that a hybrid ensemble Kalman filter parameter estimation method accurately updates model parameters within the targeted observation context to further improve state estimation.« less

Some Observational and Modeling Studies of the Atmospheric Boundary Layer at Mississippi Gulf Coast for Air Pollution Dispersion Assessment

PubMed Central

Yerramilli, Anjaneyulu; Challa, Venkata Srinivas; Indracanti, Jayakumar; Dasari, Hariprasad; Baham, Julius; Patrick, Chuck; Young, John; Hughes, Robert; White, Lorren D.; Hardy, Mark G.; Swanier, Shelton

2008-01-01

Coastal atmospheric conditions widely vary from those over inland due to the land-sea interface, temperature contrast and the consequent development of local circulations. In this study a field meteorological experiment was conducted to measure vertical structure of boundary layer during the period 25–29 June, 2007 at three locations Seabee base, Harrison and Wiggins sites in the Mississippi coast. A GPS Sonde along with slow ascent helium balloon and automated weather stations equipped with slow and fast response sensors were used in the experiment. GPS sonde were launched at three specific times (0700 LT, 1300 LT and 1800 LT) during the experiment days. The observations indicate shallow boundary layer near the coast which gradually develops inland. The weather research and forecasting (WRF) meso-scale atmospheric model and a Lagrangian particle dispersion model (HYSPLIT) are used to simulate the lower atmospheric flow and dispersion in a range of 100 km from the coast for 28–30 June, 2007. The simulated meteorological parameters were compared with the experimental observations. The meso-scale model results show significant temporal and spatial variations in the meteorological fields as a result of development of sea breeze flow, its coupling with the large scale flow field and the ensuing alteration in the mixing depth across the coast. Simulated ground-level concentrations of SO2 from four elevated point sources located along the coast indicate diurnal variation and impact of the local sea-land breeze on the direction of the plume. Model concentration levels were highest during the stable morning condition and during the sea-breeze time in the afternoon. The highest concentrations were found up to 40 km inland during sea breeze time. The study illustrates the application of field meteorological observations for the validation of WRF which is coupled to HYSPLIT for dispersion assessment in the coastal region. PMID:19151446

Intercomparison of microphysical datasets collected from CAIPEEX observations and WRF simulation

NASA Astrophysics Data System (ADS)

Pattnaik, S.; Goswami, B.; Kulkarni, J.

2009-12-01

In the first phase of ongoing Cloud Aerosol Interaction and Precipitation Enhancement Experiment (CAIPEEX) program of Indian Institute of Tropical Meteorology (IITM), intensive cloud microphysical datasets are collected over India during the May through September, 2009. This study is designed to evaluate the forecast skills of existing cloud microphysical parameterization schemes (i.e. single moment/double moments) within the WRF-ARW model (Version 3.1.1) during different intensive observation periods (IOP) over the targeted regions spreading all across India. Basic meteorological and cloud microphysical parameters obtained from the model simulations are validated against the observed data set collected during CAIPEEX program. For this study, we have considered three IOP phases (i.e. May 23-27, June 11-15, July 3-7) carried out over northern, central and western India respectively. This study emphasizes the thrust to understand the mechanism of evolution, intensification and distribution of simulated precipitation forecast upto day four (i.e. 96 hour forecast). Efforts have also been made to carryout few important microphysics sensitivity experiments within the explicit schemes to investigate their respective impact on the formation and distribution of vital cloud parameters (e.g. cloud liquid water, frozen hydrometeors) and model rainfall forecast over the IOP regions. The characteristic features of liquid and frozen hydrometers in the pre-monsoon and monsoon regimes are examined from model forecast as well as from CAIPEEX observation data set for different IOPs. The model is integrated in a triply nested fashion with an innermost nest explicitly resolved at a horizontal resolution of 4km.In this presentation preliminary results from aforementioned research initiatives will be introduced.

Trace Gas/Aerosol Interactions and GMI Modeling Support

NASA Technical Reports Server (NTRS)

Penner, Joyce E.; Liu, Xiaohong; Das, Bigyani; Bergmann, Dan; Rodriquez, Jose M.; Strahan, Susan; Wang, Minghuai; Feng, Yan

2005-01-01

Current global aerosol models use different physical and chemical schemes and parameters, different meteorological fields, and often different emission sources. Since the physical and chemical parameterization schemes are often tuned to obtain results that are consistent with observations, it is difficult to assess the true uncertainty due to meteorology alone. Under the framework of the NASA global modeling initiative (GMI), the differences and uncertainties in aerosol simulations (for sulfate, organic carbon, black carbon, dust and sea salt) solely due to different meteorological fields are analyzed and quantified. Three meteorological datasets available from the NASA DAO GCM, the GISS-II' GCM, and the NASA finite volume GCM (FVGCM) are used to drive the same aerosol model. The global sulfate and mineral dust burdens with FVGCM fields are 40% and 20% less than those with DAO and GISS fields, respectively due to its heavier rainfall. Meanwhile, the sea salt burden predicted with FVGCM fields is 56% and 43% higher than those with DAO and GISS, respectively, due to its stronger convection especially over the Southern Hemispheric Ocean. Sulfate concentrations at the surface in the Northern Hemisphere extratropics and in the middle to upper troposphere differ by more than a factor of 3 between the three meteorological datasets. The agreement between model calculated and observed aerosol concentrations in the industrial regions (e.g., North America and Europe) is quite similar for all three meteorological datasets. Away from the source regions, however, the comparisons with observations differ greatly for DAO, FVGCM and GISS, and the performance of the model using different datasets varies largely depending on sites and species. Global annual average aerosol optical depth at 550 nm is 0.120-0.131 for the three meteorological datasets.

Meteorological satellite accomplishments

NASA Technical Reports Server (NTRS)

Allison, L. J.; Arking, A.; Bandeen, W. R.; Shenk, W. E.; Wexler, R.

1974-01-01

The various types of meteorological satellites are enumerated. Vertical sounding, parameter extraction technique, and both macroscale and mesoscale meteorological phenomena are discussed. The heat budget of the earth-atmosphere system is considered, along with ocean surface and hydrology.

The Forecast Interpretation Tool—a Monte Carlo technique for blending climatic distributions with probabilistic forecasts

USGS Publications Warehouse

Husak, Gregory J.; Michaelsen, Joel; Kyriakidis, P.; Verdin, James P.; Funk, Chris; Galu, Gideon

2011-01-01

Probabilistic forecasts are produced from a variety of outlets to help predict rainfall, and other meteorological events, for periods of 1 month or more. Such forecasts are expressed as probabilities of a rainfall event, e.g. being in the upper, middle, or lower third of the relevant distribution of rainfall in the region. The impact of these forecasts on the expectation for the event is not always clear or easily conveyed. This article proposes a technique based on Monte Carlo simulation for adjusting existing climatologic statistical parameters to match forecast information, resulting in new parameters defining the probability of events for the forecast interval. The resulting parameters are shown to approximate the forecasts with reasonable accuracy. To show the value of the technique as an application for seasonal rainfall, it is used with consensus forecast developed for the Greater Horn of Africa for the 2009 March-April-May season. An alternative, analytical approach is also proposed, and discussed in comparison to the first simulation-based technique.

[Historical overview of medical meteorology - the new horizon in medical prevention].

PubMed

Boussoussou, Nora; Boussoussou, Melinda; Nemes, Attila

2017-02-01

The aim of this article is to draw attention to the medical meteorology from the perspective of the history of science. Unfortunately medical meteorology is not part of the daily medical practice. The climate change is a new challenge for health care worldwide. It concerns millions of people a higher morbidity and mortality rate. Knowing the effects of the meteorological parameters as risk factors can allow us to create new prevention strategies. These new strategies could help to decrease the negative health effects of the meteorological parameters. Nowadays on the field of the medical prevention the medical meteorology is a new horizon and in the future it could play an important role. Health care professionals have the most important role to fight against the negative effects of the global climate change. Orv. Hetil., 2017, 158(5), 187-191.

Statistical analysis of CSP plants by simulating extensive meteorological series

NASA Astrophysics Data System (ADS)

Pavón, Manuel; Fernández, Carlos M.; Silva, Manuel; Moreno, Sara; Guisado, María V.; Bernardos, Ana

2017-06-01

The feasibility analysis of any power plant project needs the estimation of the amount of energy it will be able to deliver to the grid during its lifetime. To achieve this, its feasibility study requires a precise knowledge of the solar resource over a long term period. In Concentrating Solar Power projects (CSP), financing institutions typically requires several statistical probability of exceedance scenarios of the expected electric energy output. Currently, the industry assumes a correlation between probabilities of exceedance of annual Direct Normal Irradiance (DNI) and energy yield. In this work, this assumption is tested by the simulation of the energy yield of CSP plants using as input a 34-year series of measured meteorological parameters and solar irradiance. The results of this work show that, even if some correspondence between the probabilities of exceedance of annual DNI values and energy yields is found, the intra-annual distribution of DNI may significantly affect this correlation. This result highlights the need of standardized procedures for the elaboration of representative DNI time series representative of a given probability of exceedance of annual DNI.

Processing of meteorological data with ultrasonic thermoanemometers

NASA Astrophysics Data System (ADS)

Telminov, A. E.; Bogushevich, A. Ya.; Korolkov, V. A.; Botygin, I. A.

2017-11-01

The article describes a software system intended for supporting scientific researches of the atmosphere during the processing of data gathered by multi-level ultrasonic complexes for automated monitoring of meteorological and turbulent parameters in the ground layer of the atmosphere. The system allows to process files containing data sets of temperature instantaneous values, three orthogonal components of wind speed, humidity and pressure. The processing task execution is done in multiple stages. During the first stage, the system executes researcher's query for meteorological parameters. At the second stage, the system computes series of standard statistical meteorological field properties, such as averages, dispersion, standard deviation, asymmetry coefficients, excess, correlation etc. The third stage is necessary to prepare for computing the parameters of atmospheric turbulence. The computation results are displayed to user and stored at hard drive.

SSE Data and Information Page

Atmospheric Science Data Center

2018-04-04

Surface meteorology and Solar Energy (SSE) Data and Information A new POWER home page ... The Release 6.0 Surface meteorology and Solar Energy (SSE) data set contains parameters formulated for assessing and designing renewable energy systems. This latest release contains new parameters based on ...

Contrastive Analysis of Meteorological Element Effect Simulated by parameterization schemes Land Surface Process of Noah and CLM4 over the Yellow River Source Region

NASA Astrophysics Data System (ADS)

Zhang, Y.; Wen, X.

2017-12-01

The Yellow River source region is situated in the northeast Tibetan Plateau, which is considered as a global climate change hot-spot and one of the most sensitive areas in terms of response to global warming in view of its fragile ecosystem. This region plays an irreplaceable role for downstream water supply of The Yellow River because of its unique topography and variable climate. The water energy cycle processes of the Yellow River source Region from July to September in 2015 were simulated by using the WRF mesoscale numerical model. The two groups respectively used Noah and CLM4 parameterization schemes of land surface process. Based on the observation data of GLDAS data set, ground automatic weather station and Zoige plateau wetland ecosystem research station, the simulated values of near surface meteorological elements and surface energy parameters of two different schemes were compared. The results showed that the daily variations about meteorological factors in Zoige station in September were simulated quite well by the model. The correlation coefficient between the simulated temperature and humidity of the CLM scheme were 0.88 and 0.83, the RMSE were 1.94 ° and 9.97%, and the deviation Bias were 0.04 ° and 3.30%, which was closer to the observation data than the Noah scheme. The correlation coefficients of net radiation, surface heat flux, upward short wave and upward longwave radiation were respectively 0.86, 0.81, 0.84 and 0.88, which corresponded better than the observation data. The sensible heat flux and latent heat flux distribution of the Noah scheme corresponded quite well to GLDAS. the distribution and magnitude of 2m relative humidity and soil moisture were closer to surface observation data because the CLM scheme described the photosynthesis and evapotranspiration of land surface vegetation more rationally. The simulating abilities of precipitation and downward longwave radiation need to be improved. This study provides a theoretical basis for the numerical simulation of water energy cycle in the source region over the Yellow River basin.

METEOROLOGICAL AND TRANSPORT MODELING

EPA Science Inventory

Advanced air quality simulation models, such as CMAQ, as well as other transport and dispersion models, require accurate and detailed meteorology fields. These meteorology fields include primary 3-dimensional dynamical and thermodynamical variables (e.g., winds, temperature, mo...

REGIONAL-SCALE WIND FIELD CLASSIFICATION EMPLOYING CLUSTER ANALYSIS

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

Glascoe, L G; Glaser, R E; Chin, H S

2004-06-17

The classification of time-varying multivariate regional-scale wind fields at a specific location can assist event planning as well as consequence and risk analysis. Further, wind field classification involves data transformation and inference techniques that effectively characterize stochastic wind field variation. Such a classification scheme is potentially useful for addressing overall atmospheric transport uncertainty and meteorological parameter sensitivity issues. Different methods to classify wind fields over a location include the principal component analysis of wind data (e.g., Hardy and Walton, 1978) and the use of cluster analysis for wind data (e.g., Green et al., 1992; Kaufmann and Weber, 1996). The goalmore » of this study is to use a clustering method to classify the winds of a gridded data set, i.e, from meteorological simulations generated by a forecast model.« less

Lack of evidence for meteorological effects on infradian dynamics of testosterone

NASA Astrophysics Data System (ADS)

Celec, Peter; Smreková, Lucia; Ostatníková, Daniela; Čabajová, Zlata; Hodosy, Július; Kúdela, Matúš

2009-09-01

Climatic factors are known to influence the endocrine system. Previous studies have shown that circannual seasonal variations of testosterone might be partly explained by changes in air temperature. Whether infradian variations are affected by meteorological factors is unknown. To analyze possible effects of meteorological parameters on infradian variations of salivary testosterone levels in both sexes, daily salivary testosterone levels were measured during 1 month in 14 men and 17 women. A correlation analysis between hormonal levels and selected meteorological parameters was performed. The results indicate that high testosterone levels are loosely associated with cold, sunny and dry weather in both sexes. However, only the correlations between testosterone and air temperature (men) and actual cloudiness (women) were statistically significant ( p < 0,05). Although some correlations reached the level of statistical significance, the effects of selected meteorological parameters on salivary testosterone levels remain unclear. Further longer-term studies concentrating on air temperature, cloudiness and average relative humidity in relation to the sex hormone axis are needed.

The Aggregate Description of Semi-Arid Vegetation with Precipitation-Generated Soil Moisture Heterogeneity

NASA Technical Reports Server (NTRS)

White, Cary B.; Houser, Paul R.; Arain, Altaf M.; Yang, Zong-Liang; Syed, Kamran; Shuttleworth, W. James

1997-01-01

Meteorological measurements in the Walnut Gulch catchment in Arizona were used to synthesize a distributed, hourly-average time series of data across a 26.9 by 12.5 km area with a grid resolution of 480 m for a continuous 18-month period which included two seasons of monsoonal rainfall. Coupled surface-atmosphere model runs established the acceptability (for modelling purposes) of assuming uniformity in all meteorological variables other than rainfall. Rainfall was interpolated onto the grid from an array of 82 recording rain gauges. These meteorological data were used as forcing variables for an equivalent array of stand-alone Biosphere-Atmosphere Transfer Scheme (BATS) models to describe the evolution of soil moisture and surface energy fluxes in response to the prevalent, heterogeneous pattern of convective precipitation. The calculated area-average behaviour was compared with that given by a single aggregate BATS simulation forced with area-average meteorological data. Heterogeneous rainfall gives rise to significant but partly compensating differences in the transpiration and the intercepted rainfall components of total evaporation during rain storms. However, the calculated area-average surface energy fluxes given by the two simulations in rain-free conditions with strong heterogeneity in soil moisture were always close to identical, a result which is independent of whether default or site-specific vegetation and soil parameters were used. Because the spatial variability in soil moisture throughout the catchment has the same order of magnitude as the amount of rain failing in a typical convective storm (commonly 10% of the vegetation's root zone saturation) in a semi-arid environment, non-linearitv in the relationship between transpiration and the soil moisture available to the vegetation has limited influence on area-average surface fluxes.

Statistical analysis and ANN modeling for predicting hydrological extremes under climate change scenarios: the example of a small Mediterranean agro-watershed.

PubMed

Kourgialas, Nektarios N; Dokou, Zoi; Karatzas, George P

2015-05-01

The purpose of this study was to create a modeling management tool for the simulation of extreme flow events under current and future climatic conditions. This tool is a combination of different components and can be applied in complex hydrogeological river basins, where frequent flood and drought phenomena occur. The first component is the statistical analysis of the available hydro-meteorological data. Specifically, principal components analysis was performed in order to quantify the importance of the hydro-meteorological parameters that affect the generation of extreme events. The second component is a prediction-forecasting artificial neural network (ANN) model that simulates, accurately and efficiently, river flow on an hourly basis. This model is based on a methodology that attempts to resolve a very difficult problem related to the accurate estimation of extreme flows. For this purpose, the available measurements (5 years of hourly data) were divided in two subsets: one for the dry and one for the wet periods of the hydrological year. This way, two ANNs were created, trained, tested and validated for a complex Mediterranean river basin in Crete, Greece. As part of the second management component a statistical downscaling tool was used for the creation of meteorological data according to the higher and lower emission climate change scenarios A2 and B1. These data are used as input in the ANN for the forecasting of river flow for the next two decades. The final component is the application of a meteorological index on the measured and forecasted precipitation and flow data, in order to assess the severity and duration of extreme events. Copyright © 2015 Elsevier Ltd. All rights reserved.

Sensitivity of desert dust emission modelling to horizontal resolution: the example of the Bodélé Depression

NASA Astrophysics Data System (ADS)

Bouet, Christel; Cautenet, Guy; Marticorena, Béatrice; Bergametti, Gilles; Minvielle, Fanny; Schmechtig, Catherine; Laurent, Benoit

2010-05-01

Atmospheric aerosols are known to play an important role in the Earth's climate system. However, the quantification of aerosol radiative impact on the Earth's radiative budget is very complex because of the high variability in space and time of aerosol mass and particle number concentrations, and optical properties as well. In many regions, like in desert regions, dust is the largest contribution to aerosol optical thickness [Tegen et al., 1997]. Consequently, it appears fundamental to well represent mineral dust emissions to reduce uncertainties concerning aerosol radiative impact on the Earth's radiative budget. Recently, several studies (e.g. Prospero et al. [2002]) underlined that the Bodélé depression, in northern Chad, is probably the most important source of mineral dust in the world. However many models fail in simulating these large dust emissions. Indeed, dust emission is a threshold phenomenon mainly driven by the intensity of surface wind velocity. Realistic estimates of dust emissions then rely on the quality and accuracy of the surface wind fields. Koren and Kaufman [2004] showed that the reanalysis data (NCEP), which can be used as input data in numerical models, underestimates surface wind velocity in the Bodélé Depression by up to 50%. Such an uncertainty on surface wind velocity cannot allow an accurate simulation of the dust emission. In mesoscale meteorological models, global reanalysis datasets are used to initialize and laterally nudge the models that compute meteorological parameters (like wind velocity) with a finer spatial and temporal resolutions. The question arises concerning the precision of the wind speeds calculated by these models. Using the Regional Atmospheric Modeling System (RAMS, Cotton et al. [2003]) coupled online with the dust production model developed by Marticorena and Bergametti [1995] and recently improved by Laurent et al. [2008] for Africa, the influence of the horizontal resolution of the mesoscale meteorological model on the simulation of dust emission in the Bodélé Depression is investigated. A one year simulation is run in order to test the capability of the model to represent the pronounced seasonal cycle of dust emission in this region. Routine measurements from meteorological stations as well as satellite imagery are used to evaluate the accuracy of the simulations.

Establishment and analysis of a High-Resolution Assimilation Dataset of the water-energy cycle in China

NASA Astrophysics Data System (ADS)

Wen, Xiaohang; Dong, Wenjie; Yuan, Wenping; Zheng, Zhiyuan

For better prediction and understanding of land-atmospheric interaction, in-situ observed meteorological data acquired from the China Meteorological Administration (CMA) were assimilated in the Weather Research and Forecasting (WRF) model and the monthly Green Vegetation Coverage (GVF) data, which was calculated using the Normalized Difference Vegetation Index (NDVI) of the Earth Observing System Moderate-Resolution Imaging Spectroradiometer (EOS-MODIS) and Digital Elevation Model (DEM) data of the Shuttle Radar Topography Mission (SRTM) system. Furthermore, the WRF model produced a High-Resolution Assimilation Dataset of the water-energy cycle in China (HRADC). This dataset has a horizontal resolution of 25 km for near surface meteorological data, such as air temperature, humidity, wind vectors and pressure (19 levels); soil temperature and moisture (four levels); surface temperature; downward/upward short/long radiation; 3-h latent heat flux; sensible heat flux; and ground heat flux. In this study, we 1) briefly introduce the cycling 3D-Var assimilation method and 2) compare results of meteorological elements, such as 2 m temperature and precipitation generated by the HRADC with the gridded observation data from CMA, and surface temperature and specific humidity with Global Land Data Assimilation System (GLDAS) output data from the National Aeronautics and Space Administration (NASA). We find that the simulated results of monthly 2 m temperature from HRADC is improved compared with the control simulation and has effectively reproduced the observed patterns. The simulated special distribution of ground surface temperature and specific humidity from HRADC are much closer to GLDAS outputs. The spatial distribution of root mean square errors (RMSE) and bias of 2 m temperature between observations and HRADC is reduced compared with the bias between observations and the control run. The monthly spatial distribution of surface temperature and specific humidity from HRADC is consistent with the GLDAS outputs over China. This study could improve the land surface parameters by utilizing remote sensing data and could further improve atmospheric elements with a data assimilation system. This work provides an effective attempt at combining multi-source data with different spatial and temporal scales into numerical simulations, and the simulated results could be used in further research on the long-term climatic effects and characteristics of the water-energy cycle over China.

Modeling uncertainties for tropospheric nitrogen dioxide columns affecting satellite-based inverse modeling of nitrogen oxides emissions

NASA Astrophysics Data System (ADS)

Lin, J.-T.; Liu, Z.; Zhang, Q.; Liu, H.; Mao, J.; Zhuang, G.

2012-12-01

Errors in chemical transport models (CTMs) interpreting the relation between space-retrieved tropospheric column densities of nitrogen dioxide (NO2) and emissions of nitrogen oxides (NOx) have important consequences on the inverse modeling. They are however difficult to quantify due to lack of adequate in situ measurements, particularly over China and other developing countries. This study proposes an alternate approach for model evaluation over East China, by analyzing the sensitivity of modeled NO2 columns to errors in meteorological and chemical parameters/processes important to the nitrogen abundance. As a demonstration, it evaluates the nested version of GEOS-Chem driven by the GEOS-5 meteorology and the INTEX-B anthropogenic emissions and used with retrievals from the Ozone Monitoring Instrument (OMI) to constrain emissions of NOx. The CTM has been used extensively for such applications. Errors are examined for a comprehensive set of meteorological and chemical parameters using measurements and/or uncertainty analysis based on current knowledge. Results are exploited then for sensitivity simulations perturbing the respective parameters, as the basis of the following post-model linearized and localized first-order modification. It is found that the model meteorology likely contains errors of various magnitudes in cloud optical depth, air temperature, water vapor, boundary layer height and many other parameters. Model errors also exist in gaseous and heterogeneous reactions, aerosol optical properties and emissions of non-nitrogen species affecting the nitrogen chemistry. Modifications accounting for quantified errors in 10 selected parameters increase the NO2 columns in most areas with an average positive impact of 18% in July and 8% in January, the most important factor being modified uptake of the hydroperoxyl radical (HO2) on aerosols. This suggests a possible systematic model bias such that the top-down emissions will be overestimated by the same magnitude if the model is used for emission inversion without corrections. The modifications however cannot eliminate the large model underestimates in cities and other extremely polluted areas (particularly in the north) as compared to satellite retrievals, likely pointing to underestimates of the a priori emission inventory in these places with important implications for understanding of atmospheric chemistry and air quality. Note that these modifications are simplified and should be interpreted with caution for error apportionment.

Simulations of Tropospheric NO2 by the Global Modeling Initiative (GMI) Model Utilizing Assimilated and Forecast Meteorological Fields: Comparison to Ozone Monitoring Instrument (OMI) Measurements

NASA Technical Reports Server (NTRS)

Rodriquez, J. M.; Yoshida, Y.; Duncan, B. N.; Bucsela, E. J.; Gleason, J. F.; Allen, D.; Pickering, K. E.

2007-01-01

We present simulations of the tropospheric composition for the years 2004 and 2005, carried out by the GMI Combined Stratosphere-Troposphere (Combo) model, at a resolution of 2degx2.5deg. The model includes a new parameterization of lightning sources of NO(x) which is coupled to the cloud mass fluxes in the adopted meteorological fields. These simulations use two different sets of input meteorological fields: a)late-look assimilated fields from the Global Modeling and Assimilation Office (GMAO), GEOS-4 system and b) 12-hour forecast fields initialized with the assimilated data. Comparison of the forecast to the assimilated fields indicates that the forecast fields exhibit less vigorous convection, and yield tropical precipitation fields in better agreement with observations. Since these simulations include a complete representation of the stratosphere, they provide realistic stratosphere-tropospheric fluxes of O3 and NO(y). Furthermore, the stratospheric contribution to total columns of different troposheric species can be subtracted in a consistent fashion, and the lightning production of NO(y) will depend on the adopted meteorological field. We concentrate here on the simulated tropospheric columns of NO2, and compare them to observations by the OM1 instrument for the years 2004 and 2005. The comparison is used to address these questions: a) is there a significant difference in the agreement/disagreement between simulations for these two different meteorological fields, and if so, what causes these differences?; b) how do the simulations compare to OMI observations, and does this comparison indicate an improvement in simulations with the forecast fields? c) what are the implications of these simulations for our understanding of the NO2 emissions over continental polluted regions?

Simulation of Malaria Transmission among Households in a Thai Village using Remotely Sensed Parameters

NASA Technical Reports Server (NTRS)

Kiang, Richard K.; Adimi, Farida; Zollner, Gabriela E.; Coleman, Russell E.

2007-01-01

We have used discrete-event simulation to model the malaria transmission in a Thailand village with approximately 700 residents. Specifically, we model the detailed interactions among the vector life cycle, sporogonic cycle and human infection cycle under the explicit influences of selected extrinsic and intrinsic factors. Some of the meteorological and environmental parameters used in the simulation are derived from Tropical Rainfall Measuring Mission and the Ikonos satellite data. Parameters used in the simulations reflect the realistic condition of the village, including the locations and sizes of the households, ages and estimated immunity of the residents, presence of farm animals, and locations of larval habitats. Larval habitats include the actual locations where larvae were collected and the probable locations based on satellite data. The output of the simulation includes the individual infection status and the quantities normally observed in field studies, such as mosquito biting rates, sporozoite infection rates, gametocyte prevalence and incidence. Simulated transmission under homogeneous environmental condition was compared with that predicted by a SEIR model. Sensitivity of the output with respect to some extrinsic and intrinsic factors was investigated. Results were compared with mosquito vector and human malaria data acquired over 4.5 years (June 1999 - January 2004) in Kong Mong Tha, a remote village in Kanchanaburi Province, western Thailand. The simulation method is useful for testing transmission hypotheses, estimating the efficacy of insecticide applications, assessing the impacts of nonimmune immigrants, and predicting the effects of socioeconomic, environmental and climatic changes.

Assimilation of remote sensing data into a process-based ecosystem model for monitoring changes of soil water content in croplands

NASA Astrophysics Data System (ADS)

Ju, Weimin; Gao, Ping; Wang, Jun; Li, Xianfeng; Chen, Shu

2008-10-01

Soil water content (SWC) is an important factor affecting photosynthesis, growth, and final yields of crops. The information on SWC is of importance for mitigating the reduction of crop yields caused by drought through proper agricultural water management. A variety of methodologies have been developed to estimate SWC at local and regional scales, including field sampling, remote sensing monitoring and model simulations. The reliability of regional SWC simulation depends largely on the accuracy of spatial input datasets, including vegetation parameters, soil and meteorological data. Remote sensing has been proved to be an effective technique for controlling uncertainties in vegetation parameters. In this study, the vegetation parameters (leaf area index and land cover type) derived from the Moderate Resolution Imaging Spectrometer (MODIS) were assimilated into a process-based ecosystem model BEPS for simulating the variations of SWC in croplands of Jiangsu province, China. Validation shows that the BEPS model is able to capture 81% and 83% of across-site variations of SWC at 10 and 20 cm depths during the period from September to December, 2006 when a serous autumn drought occurred. The simulated SWC responded the events of rainfall well at regional scale, demonstrating the usefulness of our methodology for SWC and practical agricultural water management at large scales.

Generation of Multivariate Surface Weather Series with Use of the Stochastic Weather Generator Linked to Regional Climate Model

NASA Astrophysics Data System (ADS)

Dubrovsky, M.; Farda, A.; Huth, R.

2012-12-01

The regional-scale simulations of weather-sensitive processes (e.g. hydrology, agriculture and forestry) for the present and/or future climate often require high resolution meteorological inputs in terms of the time series of selected surface weather characteristics (typically temperature, precipitation, solar radiation, humidity, wind) for a set of stations or on a regular grid. As even the latest Global and Regional Climate Models (GCMs and RCMs) do not provide realistic representation of statistical structure of the surface weather, the model outputs must be postprocessed (downscaled) to achieve the desired statistical structure of the weather data before being used as an input to the follow-up simulation models. One of the downscaling approaches, which is employed also here, is based on a weather generator (WG), which is calibrated using the observed weather series and then modified (in case of simulations for the future climate) according to the GCM- or RCM-based climate change scenarios. The present contribution uses the parametric daily weather generator M&Rfi to follow two aims: (1) Validation of the new simulations of the present climate (1961-1990) made by the ALADIN-Climate/CZ (v.2) Regional Climate Model at 25 km resolution. The WG parameters will be derived from the RCM-simulated surface weather series and compared to those derived from observational data in the Czech meteorological stations. The set of WG parameters will include selected statistics of the surface temperature and precipitation (characteristics of the mean, variability, interdiurnal variability and extremes). (2) Testing a potential of RCM output for calibration of the WG for the ungauged locations. The methodology being examined will consist in using the WG, whose parameters are interpolated from the surrounding stations and then corrected based on a RCM-simulated spatial variability. The quality of the weather series produced by the WG calibrated in this way will be assessed in terms of selected climatic characteristics focusing on extreme precipitation and temperature characteristics (including characteristics of dry/wet/hot/cold spells). Acknowledgements: The present experiment is made within the frame of projects ALARO (project P209/11/2405 sponsored by the Czech Science Foundation), WG4VALUE (project LD12029 sponsored by the Ministry of Education, Youth and Sports) and VALUE (COST ES 1102 action).

Retrieval of nonprecipitating liquid water cloud parameters from microwave data - A simulation study

NASA Technical Reports Server (NTRS)

Huang, Hung-Lung; Diak, George R.

1992-01-01

A new microwave algorithm, analogous to the IR 'radiance-ratioing' method of Eyre and Menzel (1989) is developed to retrieve the height and 'effective' fraction (defined as the product of the emissivity times the actual physical fractional coverage) of nonprecipitating water clouds using various pairs of the 20 microwave channels planned for the Advanced Microwave Sounding Unit (AMSU), an instrument slated to fly on polar-orbiting satellites beginning in 1994. The results of a simulation study are presented to provide some insights into the potentials of this technique using different AMSU channel combinations. This study suggests that the use of the oxygen channels 3 and 5 and water vapor channels 19 and 20 will produce the most accurate retrievals of liquid water cloud parameters and the highest percentage of good-quality retrievals over a range of meteorological and cloud conditions.

The impact of higher-order ionospheric effects on estimated tropospheric parameters in Precise Point Positioning

NASA Astrophysics Data System (ADS)

Zus, F.; Deng, Z.; Wickert, J.

2017-08-01

The impact of higher-order ionospheric effects on the estimated station coordinates and clocks in Global Navigation Satellite System (GNSS) Precise Point Positioning (PPP) is well documented in literature. Simulation studies reveal that higher-order ionospheric effects have a significant impact on the estimated tropospheric parameters as well. In particular, the tropospheric north-gradient component is most affected for low-latitude and midlatitude stations around noon. In a practical example we select a few hundred stations randomly distributed over the globe, in March 2012 (medium solar activity), and apply/do not apply ionospheric corrections in PPP. We compare the two sets of tropospheric parameters (ionospheric corrections applied/not applied) and find an overall good agreement with the prediction from the simulation study. The comparison of the tropospheric parameters with the tropospheric parameters derived from the ERA-Interim global atmospheric reanalysis shows that ionospheric corrections must be consistently applied in PPP and the orbit and clock generation. The inconsistent application results in an artificial station displacement which is accompanied by an artificial "tilting" of the troposphere. This finding is relevant in particular for those who consider advanced GNSS tropospheric products for meteorological studies.

Reconstructing the prevailing meteorological and optical environment during the time of the Titanic disaster

NASA Astrophysics Data System (ADS)

Basu, Sukanta; Nunalee, Christopher G.; He, Ping; Fiorino, Steven T.; Vorontsov, Mikhail A.

2014-10-01

In this paper, we reconstruct the meteorological and optical environment during the time of Titanic's disaster utilizing a state-of-the-art meteorological model, a ray-tracing code, and a unique public-domain dataset called the Twentieth Century Global Reanalysis. With high fidelity, our simulation captured the occurrence of an unusually high Arctic pressure system over the disaster site with calm wind. It also reproduced the movement of a polar cold front through the region bringing a rapid drop in air temperature. The simulated results also suggest that unusual meteorological conditions persisted several hours prior to the Titanic disaster which contributed to super-refraction and intermittent optical turbulence. However, according to the simulations, such anomalous conditions were not present at the time of the collision of Titanic with an iceberg.

Preliminary investigation of the effects of eruption source parameters on volcanic ash transport and dispersion modeling using HYSPLIT

NASA Astrophysics Data System (ADS)

Stunder, B.

2009-12-01

Atmospheric transport and dispersion (ATD) models are used in real-time at Volcanic Ash Advisory Centers to predict the location of airborne volcanic ash at a future time because of the hazardous nature of volcanic ash. Transport and dispersion models usually do not include eruption column physics, but start with an idealized eruption column. Eruption source parameters (ESP) input to the models typically include column top, eruption start time and duration, volcano latitude and longitude, ash particle size distribution, and total mass emission. An example based on the Okmok, Alaska, eruption of July 12-14, 2008, was used to qualitatively estimate the effect of various model inputs on transport and dispersion simulations using the NOAA HYSPLIT model. Variations included changing the ash column top and bottom, eruption start time and duration, particle size specifications, simulations with and without gravitational settling, and the effect of different meteorological model data. Graphical ATD model output of ash concentration from the various runs was qualitatively compared. Some parameters such as eruption duration and ash column depth had a large effect, while simulations using only small particles or changing the particle shape factor had much less of an effect. Some other variations such as using only large particles had a small effect for the first day or so after the eruption, then a larger effect on subsequent days. Example probabilistic output will be shown for an ensemble of dispersion model runs with various model inputs. Model output such as this may be useful as a means to account for some of the uncertainties in the model input. To improve volcanic ash ATD models, a reference database for volcanic eruptions is needed, covering many volcanoes. The database should include three major components: (1) eruption source, (2) ash observations, and (3) analyses meteorology. In addition, information on aggregation or other ash particle transformation processes would be useful.

Study of key factors influencing dust emission: An assessment of GEOS-Chem and DEAD simulations with observations

NASA Astrophysics Data System (ADS)

Bartlett, Kevin S.

Mineral dust aerosols can impact air quality, climate change, biological cycles, tropical cyclone development and flight operations due to reduced visibility. Dust emissions are primarily limited to the extensive arid regions of the world, yet can negatively impact local to global scales, and are extremely complex to model accurately. Within this dissertation, the Dust Entrainment And Deposition (DEAD) model was adapted to run, for the first known time, using high temporal (hourly) and spatial (0.3°x0.3°) resolution data to methodically interrogate the key parameters and factors influencing global dust emissions. The dependence of dust emissions on key parameters under various conditions has been quantified and it has been shown that dust emissions within DEAD are largely determined by wind speeds, vegetation extent, soil moisture and topographic depressions. Important findings were that grid degradation from 0.3ºx0.3º to 1ºx1º, 2ºx2.5º, and 4°x5° of key meteorological, soil, and surface input parameters greatly reduced emissions approximately 13% and 29% and 64% respectively, as a result of the loss of sub grid detail within these key parameters at coarse grids. After running high resolution DEAD emissions globally for 2 years, two severe dust emission cases were chosen for an in-depth investigation of the root causes of the events and evaluation of the 2°x2.5° Goddard Earth Observing System (GEOS)-Chem and 0.3°x0.3° DEAD model capabilities to simulate the events: one over South West Asia (SWA) in June 2008 and the other over the Middle East in July 2009. The 2 year lack of rain over SWA preceding June 2008 with a 43% decrease in mean rainfall, yielded less than normal plant growth, a 28% increase in Aerosol Optical Depth (AOD), and a 24% decrease in Meteorological Aerodrome Report (METAR) observed visibility (VSBY) compared to average years. GEOS-Chem captured the observed higher AOD over SWA in June 2008. More detailed comparisons of GEOS-Chem predicted AOD and visibility over SWA with those observed at surface stations and from satellites revealed overall success of the model, although substantial regional differences exist. Within the extended drought, the study area was zoomed into the Middle East (ME) for July 2009 where multi-grid DEAD dust emissions using hourly CFSR meteorological input were compared with observations. The high resolution input yielded the best spatial and temporal dust patterns compared with Defense Meteorological Satellite Program (DMSP), Moderate Resolution Imaging Spectroradiometer (MODIS) and METAR VSBY observations and definitively revealed Syria as a major dust source for the region. The coarse resolution dust emissions degraded or missed daily dust emissions entirely. This readily showed that the spatial scale degradation of the input data can significantly impair DEAD dust emissions and offers a strong argument for adapting higher resolution dust emission schemes into future global models for improvements of dust simulations.

Effect of spatial averaging on multifractal properties of meteorological time series

NASA Astrophysics Data System (ADS)

Hoffmann, Holger; Baranowski, Piotr; Krzyszczak, Jaromir; Zubik, Monika

2016-04-01

Introduction The process-based models for large-scale simulations require input of agro-meteorological quantities that are often in the form of time series of coarse spatial resolution. Therefore, the knowledge about their scaling properties is fundamental for transferring locally measured fluctuations to larger scales and vice-versa. However, the scaling analysis of these quantities is complicated due to the presence of localized trends and non-stationarities. Here we assess how spatially aggregating meteorological data to coarser resolutions affects the data's temporal scaling properties. While it is known that spatial aggregation may affect spatial data properties (Hoffmann et al., 2015), it is unknown how it affects temporal data properties. Therefore, the objective of this study was to characterize the aggregation effect (AE) with regard to both temporal and spatial input data properties considering scaling properties (i.e. statistical self-similarity) of the chosen agro-meteorological time series through multifractal detrended fluctuation analysis (MFDFA). Materials and Methods Time series coming from years 1982-2011 were spatially averaged from 1 to 10, 25, 50 and 100 km resolution to assess the impact of spatial aggregation. Daily minimum, mean and maximum air temperature (2 m), precipitation, global radiation, wind speed and relative humidity (Zhao et al., 2015) were used. To reveal the multifractal structure of the time series, we used the procedure described in Baranowski et al. (2015). The diversity of the studied multifractals was evaluated by the parameters of time series spectra. In order to analyse differences in multifractal properties to 1 km resolution grids, data of coarser resolutions was disaggregated to 1 km. Results and Conclusions Analysing the spatial averaging on multifractal properties we observed that spatial patterns of the multifractal spectrum (MS) of all meteorological variables differed from 1 km grids and MS-parameters were biased by -29.1 % (precipitation; width of MS) up to >4 % (min. Temperature, Radiation; asymmetry of MS). Also, the spatial variability of MS parameters was strongly affected at the highest aggregation (100 km). Obtained results confirm that spatial data aggregation may strongly affect temporal scaling properties. This should be taken into account when upscaling for large-scale studies. Acknowledgements The study was conducted within FACCE MACSUR. Please see Baranowski et al. (2015) for details on funding. References Baranowski, P., Krzyszczak, J., Sławiński, C. et al. (2015). Climate Research 65, 39-52. Hoffman, H., G. Zhao, L.G.J. Van Bussel et al. (2015). Climate Research 65, 53-69. Zhao, G., Siebert, S., Rezaei E. et al. (2015). Agricultural and Forest Meteorology 200, 156-171.

Sensitivity of polar ozone recovery predictions of the GMI 3D CTM to GCM and DAS dynamics

NASA Astrophysics Data System (ADS)

Considine, D.; Connell, P.; Strahan, S.; Douglass, A.; Rotman, D.

2003-04-01

The Global Modeling Initiative (GMI) 3-D chemistry and transport model has been used to generate 2 simulations of the 1995-2030 time period. The 36-year simulations both used the source gas and aerosol boundary conditions of the 2002 World Meteorological Organization assessment exercise MA2. The first simulation was based on a single year of meteorological data (winds, temperatures) generated by the new Goddard Space Flight Center "Finite Volume" General Circulation Model (FVGCM), repeated for each year of the simulation. The second simulation used a year of meteorological data generated by a new data assimilation system based on the FVGCM (FVDAS), using observations for July 1, 1999 - June 30, 2000. All other aspects of the two simulations were identical. The increase in vortex-averaged south polar springtime ozone concentrations in the lower stratosphere over the course of the simulations is more robust in the simulation driven by the GCM meteorological data than in the simulation driven by DAS winds. At the same time, the decrease in estimated chemical springtime ozone loss is similar. We thus attribute the differences between the two simulations to differences in the representations of polar dynamics which reduce the sensitivity of the simulation driven by DAS winds to changes in vortex chemistry. We also evaluate the representations in the two simulations of trace constituent distributions in the current polar lower stratosphere using various observations. In these comparisons the GCM-based simulation often is in better agreement with the observations than the DAS-based simulation.

Air quality modelling in the Berlin-Brandenburg region using WRF-Chem v3.7.1: sensitivity to resolution of model grid and input data

NASA Astrophysics Data System (ADS)

Kuik, Friderike; Lauer, Axel; Churkina, Galina; Denier van der Gon, Hugo A. C.; Fenner, Daniel; Mar, Kathleen A.; Butler, Tim M.

2016-12-01

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. NOx (NO + NO2) concentrations are simulated reasonably well on average, but nighttime concentrations are overestimated due to the model's underestimation of the mixing layer height, and urban daytime concentrations are underestimated. The daytime underestimation is improved when using downscaled, and thus locally higher emissions, suggesting that part of this bias is due to deficiencies in the emission input data and their resolution. The results further demonstrate that a horizontal resolution of 3 km improves the results and spatial representativeness of the model compared to a horizontal resolution of 15 km. With the input data (land use classes, emissions) at the level of detail of the base run of this study, we find that a horizontal resolution of 1 km does not improve the results compared to a resolution of 3 km. However, our results suggest that a 1 km horizontal model resolution could enable a detailed simulation of local pollution patterns in the Berlin-Brandenburg region if the urban land use classes, together with the respective input parameters to the urban canopy model, are specified with a higher level of detail and if urban emissions of higher spatial resolution are used.

Performance assessment of retrospective meteorological inputs for use in air quality modeling during TexAQS 2006

NASA Astrophysics Data System (ADS)

Ngan, Fong; Byun, Daewon; Kim, Hyuncheol; Lee, Daegyun; Rappenglück, Bernhard; Pour-Biazar, Arastoo

2012-07-01

To achieve more accurate meteorological inputs than was used in the daily forecast for studying the TexAQS 2006 air quality, retrospective simulations were conducted using objective analysis and 3D/surface analysis nudging with surface and upper observations. Model ozone using the assimilated meteorological fields with improved wind fields shows better agreement with the observation compared to the forecasting results. In the post-frontal conditions, important factors for ozone modeling in terms of wind patterns are the weak easterlies in the morning for bringing in industrial emissions to the city and the subsequent clockwise turning of the wind direction induced by the Coriolis force superimposing the sea breeze, which keeps pollutants in the urban area. Objective analysis and nudging employed in the retrospective simulation minimize the wind bias but are not able to compensate for the general flow pattern biases inherited from large scale inputs. By using an alternative analyses data for initializing the meteorological simulation, the model can re-produce the flow pattern and generate the ozone peak location closer to the reality. The inaccurate simulation of precipitation and cloudiness cause over-prediction of ozone occasionally. Since there are limitations in the meteorological model to simulate precipitation and cloudiness in the fine scale domain (less than 4-km grid), the satellite-based cloud is an alternative way to provide necessary inputs for the retrospective study of air quality.

Assessment of TMY generation methods for solar power production estimation

NASA Astrophysics Data System (ADS)

Zebner, H.

2010-09-01

This paper deals with the evaluation of different methods commonly employed in the solar power industry for the generation of representative data sets with solar resource information and further climate parameters. The quality of energy yield simulation data sets is defined by the accuracy of the data source (e. g. measurement device or calculation model) and its representativeness for the typical meteorological conditions at the location of the investigated power plant site. Supposing that data with high accuracy is available the next challenge is to prepare a best-possible input data set for the energy production simulation software. Such programs are often limited to the simulation of one-year data sets with hourly frequency (i. e. 8760 values). The data set shall therefore contain values which are most representative for each hour of the year and reflect the dynamical behaviour of the resource. As simple averaging of long-term data would not fulfil these requirements, certain methods for selecting such a typical meteorological year (TMY) have been developed in recent years. Presently, there are three to four different methods recommended in scientific literature or suggested by practitioners in the solar industry. The evaluation in this paper seeks to test the most commonly used methods with high precision data from the baseline surface radiation network (BSRN). From a long-term time series retrieved from a station in a region suitable for the development of solar power plants a TMY is created by utilizing different generation methods. The resulting data set is then compared to the average over all years in order to evaluate the general representativeness. As the plant operator is interested in the average production over the life time of a plant the result of an energy yield simulation performed with each of the different data set is then compared to the mean production gained by simulating the yield of for each single year and then averaging the results obtained for the individual years. As outcome of this evaluation information on the meteorological representativeness and suitability for energy production estimation of each method is achieved. This is regarded as an important step in assuring the validity of production forecasts based on TMYs in the context of solar power plant development - an area which is characterised by very specific needs for solar input values (e. g. DNI) and lack in the concurrent availability of additional parameters such as temperature and humidity.

Comparison of Malaria Simulations Driven by Meteorological Observations and Reanalysis Products in Senegal

PubMed Central

Diouf, Ibrahima; Rodriguez-Fonseca, Belen; Deme, Abdoulaye; Caminade, Cyril; Morse, Andrew P.; Cisse, Moustapha; Sy, Ibrahima; Dia, Ibrahima; Ermert, Volker; Ndione, Jacques-André; Gaye, Amadou Thierno

2017-01-01

The analysis of the spatial and temporal variability of climate parameters is crucial to study the impact of climate-sensitive vector-borne diseases such as malaria. The use of malaria models is an alternative way of producing potential malaria historical data for Senegal due to the lack of reliable observations for malaria outbreaks over a long time period. Consequently, here we use the Liverpool Malaria Model (LMM), driven by different climatic datasets, in order to study and validate simulated malaria parameters over Senegal. The findings confirm that the risk of malaria transmission is mainly linked to climate variables such as rainfall and temperature as well as specific landscape characteristics. For the whole of Senegal, a lag of two months is generally observed between the peak of rainfall in August and the maximum number of reported malaria cases in October. The malaria transmission season usually takes place from September to November, corresponding to the second peak of temperature occurring in October. Observed malaria data from the Programme National de Lutte contre le Paludisme (PNLP, National Malaria control Programme in Senegal) and outputs from the meteorological data used in this study were compared. The malaria model outputs present some consistencies with observed malaria dynamics over Senegal, and further allow the exploration of simulations performed with reanalysis data sets over a longer time period. The simulated malaria risk significantly decreased during the 1970s and 1980s over Senegal. This result is consistent with the observed decrease of malaria vectors and malaria cases reported by field entomologists and clinicians in the literature. The main differences between model outputs and observations regard amplitude, but can be related not only to reanalysis deficiencies but also to other environmental and socio-economic factors that are not included in this mechanistic malaria model framework. The present study can be considered as a validation of the reliability of reanalysis to be used as inputs for the calculation of malaria parameters in the Sahel using dynamical malaria models. PMID:28946705

Impacts of a Stochastic Ice Mass-Size Relationship on Squall Line Ensemble Simulations

NASA Astrophysics Data System (ADS)

Stanford, M.; Varble, A.; Morrison, H.; Grabowski, W.; McFarquhar, G. M.; Wu, W.

2017-12-01

Cloud and precipitation structure, evolution, and cloud radiative forcing of simulated mesoscale convective systems (MCSs) are significantly impacted by ice microphysics parameterizations. Most microphysics schemes assume power law relationships with constant parameters for ice particle mass, area, and terminal fallspeed relationships as a function of size, despite observations showing that these relationships vary in both time and space. To account for such natural variability, a stochastic representation of ice microphysical parameters was developed using the Predicted Particle Properties (P3) microphysics scheme in the Weather Research and Forecasting model, guided by in situ aircraft measurements from a number of field campaigns. Here, the stochastic framework is applied to the "a" and "b" parameters of the unrimed ice mass-size (m-D) relationship (m=aDb) with co-varying "a" and "b" values constrained by observational distributions tested over a range of spatiotemporal autocorrelation scales. Diagnostically altering a-b pairs in three-dimensional (3D) simulations of the 20 May 2011 Midlatitude Continental Convective Clouds Experiment (MC3E) squall line suggests that these parameters impact many important characteristics of the simulated squall line, including reflectivity structure (particularly in the anvil region), surface rain rates, surface and top of atmosphere radiative fluxes, buoyancy and latent cooling distributions, and system propagation speed. The stochastic a-b P3 scheme is tested using two frameworks: (1) a large ensemble of two-dimensional idealized squall line simulations and (2) a smaller ensemble of 3D simulations of the 20 May 2011 squall line, for which simulations are evaluated using observed radar reflectivity and radial velocity at multiple wavelengths, surface meteorology, and surface and satellite measured longwave and shortwave radiative fluxes. Ensemble spreads are characterized and compared against initial condition ensemble spreads for a range of variables.

Simulation of radioactive tracer transport using IsoRSM and uncertainty analysis

NASA Astrophysics Data System (ADS)

SAYA, A.; Chang, E.; Yoshimura, K.; Oki, T.

2013-12-01

Due to the massive earthquakes and tsunami on March 11 2011 in Eastern Japan, Fukushima Daiichi nuclear power plant was severely damaged and some reactors were exploded. To know how the radioactive materials were spread and how much they were deposited into the land, it is important to enhance the accuracy of radioactive transport simulation model. However, there are uncertainties in the models including dry and wet deposition process in the models, meteorological field and release amount of radioactive materials. In this study we analyzed these uncertainties aiming for higher accuracy in the simulation. We modified the stable isotope mode of Regional Spectral Model (IsoRSM, Yoshimura et al., 2009) to enable to simulate the transport of the radioactive tracers, namely iodine 131 and cesium 137, by including the dry and wet deposition processes. With this model, we conducted a set of sensitivity experiments using different parameters in the deposition processes, different diffusivity in advection processes, and different domain sizes. The control experiment with 10km resolution covering most of Japan and surrounding oceans (132.7oE-151.5oE &28.3oN-46.7oN) and the emission estimated by Chino et al. (2011) showed reasonable temporal results for Toukatsu area (eastern part of Tokyo metropolis and western part of Chiba prefecture where low-level contamination was occurred), i.e., on 22 March, the tracers from Fukushima were reached and precipitated in a significant amount as wet deposition. Thus we conducted 4 experimental simulations to analyze the simulation uncertainty due to 1) different meteorological pattern, different parameters for 2) wet and 3) dry deposition and 4) diffusion. Though the temporal patterns of deposition of radioactive particles were somewhat similar each other in all experiments, we revealed that the impacts to the area mean deposition were large. Results of the simulations with different diffusivity and different domain size showed that the patterns of precipitation amount and distribution, and deposition amount were affected. The new transport scheme, semi-lagrangian scheme could show some improvement in the simulated meteorological field. Furthermore, we have begun the inversion estimation combined with IsoRSM and the monitoring data from the Nuclear regulation Agency. Preliminary results with consecutive two week simulations starting every day with daily unit release will be shown at the conference. References 1. Yoshimura, K., Kanamitsu. M. and Dettinger. M.: Regional downscaling for stable water isotopes: A case study of an atmospheric river event, Journal of geophysical research, Vol.15, D18114, doi:10.1029/2010JD014032, 2010 2. Chino, M., Nakayama. H., Nagai. H., Terada. H., Katata. G. and Yamazawa. H.: Preliminary estimation of release amounts of 131I and 137Cs accidentally discharged from the Fukushima Daiichi Nuclear Power Plant into the atmosphere, Journal of Nuclear Science and Technology, Vol.48, No.7, p.1129-1134, 2011

Meteorology drives ambient air quality in a valley: a case of Sukinda chromite mine, one among the ten most polluted areas in the world.

PubMed

Mishra, Soumya Ranjan; Pradhan, Rudra Pratap; Prusty, B Anjan Kumar; Sahu, Sanjat Kumar

2016-07-01

The ambient air quality (AAQ) assessment was undertaken in Sukinda Valley, the chromite hub of India. The possible correlations of meteorological variables with different air quality parameters (PM10, PM2.5, SO2, NO2 and CO) were examined. Being the fourth most polluted area in the globe, Sukinda Valley has always been under attention of researchers, for hexavalent chromium contamination of water. The monitoring was carried out from December 2013 through May 2014 at six strategic locations in the residential and commercial areas around the mining cluster of Sukinda Valley considering the guidelines of Central Pollution Control Board (CPCB). In addition, meteorological parameters viz., temperature, relative humidity, wind speed, wind direction and rainfall, were also monitored. The air quality data were subjected to a general linear model (GLM) coupled with one-way analysis of variance (ANOVA) test for testing the significant difference in the concentration of various parameters among seasons and stations. Further, a two-tailed Pearson's correlation test helped in understanding the influence of meteorological parameters on dispersion of pollutants in the area. All the monitored air quality parameters varied significantly among the monitoring stations suggesting (i) the distance of sampling location to the mine site and other allied activities, (ii) landscape features and topography and (iii) meteorological parameters to be the forcing functions. The area was highly polluted with particulate matters, and in most of the cases, the PM level exceeded the National Ambient Air Quality Standards (NAAQS). The meteorological parameters seemed to play a major role in the dispersion of pollutants around the mine clusters. The role of wind direction, wind speed and temperature was apparent in dispersion of the particulate matters from their source of generation to the surrounding residential and commercial areas of the mine.

A satellite simulator for TRMM PR applied to climate model simulations

NASA Astrophysics Data System (ADS)

Spangehl, T.; Schroeder, M.; Bodas-Salcedo, A.; Hollmann, R.; Riley Dellaripa, E. M.; Schumacher, C.

2017-12-01

Climate model simulations have to be compared against observation based datasets in order to assess their skill in representing precipitation characteristics. Here we use a satellite simulator for TRMM PR in order to evaluate simulations performed with MPI-ESM (Earth system model of the Max Planck Institute for Meteorology in Hamburg, Germany) performed within the MiKlip project (https://www.fona-miklip.de/, funded by Federal Ministry of Education and Research in Germany). While classical evaluation methods focus on geophysical parameters such as precipitation amounts, the application of the satellite simulator enables an evaluation in the instrument's parameter space thereby reducing uncertainties on the reference side. The CFMIP Observation Simulator Package (COSP) provides a framework for the application of satellite simulators to climate model simulations. The approach requires the introduction of sub-grid cloud and precipitation variability. Radar reflectivities are obtained by applying Mie theory, with the microphysical assumptions being chosen to match the atmosphere component of MPI-ESM (ECHAM6). The results are found to be sensitive to the methods used to distribute the convective precipitation over the sub-grid boxes. Simple parameterization methods are used to introduce sub-grid variability of convective clouds and precipitation. In order to constrain uncertainties a comprehensive comparison with sub-grid scale convective precipitation variability which is deduced from TRMM PR observations is carried out.

Electronic simulation of a barometric pressure sensor for the meteorological monitor assembly

NASA Technical Reports Server (NTRS)

Guiar, C. N.; Duff, L. W.

1982-01-01

An analysis of the electronic simulation of barometric pressure used to self-test the counter electronics of the digital barometer is presented. The barometer is part of the Meteorological Monitor Assembly that supports navigation in deep space communication. The theory of operation of the digital barometer, the design details, and the verification procedure used with the barometric pressure simulator are presented.

A Monte-Carlo Analysis of Organic Volatility with Aerosol Microphysics

NASA Astrophysics Data System (ADS)

Gao, Chloe; Tsigaridis, Kostas; Bauer, Susanne E.

2017-04-01

A newly developed box model, MATRIX-VBS, includes the volatility-basis set (VBS) framework in an aerosol microphysical scheme MATRIX (Multiconfiguration Aerosol TRacker of mIXing state), which resolves aerosol mass and number concentrations and aerosol mixing state. The new scheme advanced the representation of organic aerosols in models by improving the traditional and simplistic treatment of organic aerosols as non-volatile and with a fixed size distribution. Further development includes adding the condensation of organics on coarse mode aerosols - dust and sea salt, thus making all organics in the system semi-volatile. To test and simplify the model, a Monte-Carlo analysis is performed to pin point which processes affect organics the most under varied chemical and meteorological conditions. Since the model's parameterizations have the ability to capture a very wide range of conditions, all possible scenarios on Earth across the whole parameter space, including temperature, humidity, location, emissions and oxidant levels, are examined. The Monte-Carlo simulations provide quantitative information on the sensitivity of the newly developed model and help us understand how organics are affecting the size distribution, mixing state and volatility distribution at varying levels of meteorological conditions and pollution levels. In addition, these simulations give information on which parameters play a critical role in the aerosol distribution and evolution in the atmosphere and which do not, that will facilitate the simplification of the box model, an important step in its implementation in the global model GISS ModelE as a module.

Uncertainties in Past and Future Global Water Availability

NASA Astrophysics Data System (ADS)

Sheffield, J.; Kam, J.

2014-12-01

Understanding how water availability changes on inter-annual to decadal time scales and how it may change in the future under climate change are a key part of understanding future stresses on water and food security. Historic evaluations of water availability on regional to global scales are generally based on large-scale model simulations with their associated uncertainties, in particular for long-term changes. Uncertainties are due to model errors and missing processes, parameter uncertainty, and errors in meteorological forcing data. Recent multi-model inter-comparisons and impact studies have highlighted large differences for past reconstructions, due to different simplifying assumptions in the models or the inclusion of physical processes such as CO2 fertilization. Modeling of direct anthropogenic factors such as water and land management also carry large uncertainties in their physical representation and from lack of socio-economic data. Furthermore, there is little understanding of the impact of uncertainties in the meteorological forcings that underpin these historic simulations. Similarly, future changes in water availability are highly uncertain due to climate model diversity, natural variability and scenario uncertainty, each of which dominates at different time scales. In particular, natural climate variability is expected to dominate any externally forced signal over the next several decades. We present results from multi-land surface model simulations of the historic global availability of water in the context of natural variability (droughts) and long-term changes (drying). The simulations take into account the impact of uncertainties in the meteorological forcings and the incorporation of water management in the form of reservoirs and irrigation. The results indicate that model uncertainty is important for short-term drought events, and forcing uncertainty is particularly important for long-term changes, especially uncertainty in precipitation due to reduced gauge density in recent years. We also discuss uncertainties in future projections from these models as driven by bias-corrected and downscaled CMIP5 climate projections, in the context of the balance between climate model robustness and climate model diversity.

Impacts of weather versus climate and driver uncertainty on multi-centennial ecosystem model simulations

NASA Astrophysics Data System (ADS)

Rollinson, C.; Simkins, J.; Fer, I.; Desai, A. R.; Dietze, M.

2017-12-01

Simulations of ecosystem dynamics and comparisons with empirical data require accurate, continuous, and often sub-daily meteorology records that are spatially aligned to the scale of the empirical data. A wealth of meteorology data for the past, present, and future is available through site-specific observations, modern reanalysis products, and gridded GCM simulations. However, these products are mismatched in spatial and temporal resolution, often with both different means and seasonal patterns. We have designed and implemented a two-step meteorological downscaling and ensemble generation method that combines multiple meteorology data products through debiasing and temporal downscaling protocols. Our methodology is designed to preserve the covariance among seven meteorological variables for use as drivers in ecosystem model simulations: temperature, precipitation, short- and longwave radiation, surface pressure, humidity, and wind. Furthermore, our method propagates uncertainty through the downscaling process and results in ensembles of meteorology that can be compared to paleoclimate reconstructions and used to analyze the effects of both high- and low-frequency climate anomalies on ecosystem dynamics. Using a multiple linear regression approach, we have combined hourly, 0.125-degree gridded data from the NLDAS (1980-present) with CRUNCEP (1901-2010) and CMIP5 historical (1850-2005), past millennium (850-1849), and future (1950-2100) GCM simulations. This has resulted in an ensemble of continuous, hourly-resolved meteorology from from the paleo era into the future with variability in weather events as well as low-frequency climatic changes. We investigate the influence of extreme sub-daily weather phenomena versus long-term climatic changes in an ensemble of ecosystem models that range in atmospheric and biological complexity. Through data assimilation with paleoclimate reconstructions of past climate, we can improve data-model comparisons using observations of vegetation change from the past 1200 years. Accounting for driver uncertainty in model evaluation can help determine the relative influence of structural versus parameterization errors in ecosystem modelings.

Regionalization of post-processed ensemble runoff forecasts

NASA Astrophysics Data System (ADS)

Olav Skøien, Jon; Bogner, Konrad; Salamon, Peter; Smith, Paul; Pappenberger, Florian

2016-05-01

For many years, meteorological models have been run with perturbated initial conditions or parameters to produce ensemble forecasts that are used as a proxy of the uncertainty of the forecasts. However, the ensembles are usually both biased (the mean is systematically too high or too low, compared with the observed weather), and has dispersion errors (the ensemble variance indicates a too low or too high confidence in the forecast, compared with the observed weather). The ensembles are therefore commonly post-processed to correct for these shortcomings. Here we look at one of these techniques, referred to as Ensemble Model Output Statistics (EMOS) (Gneiting et al., 2005). Originally, the post-processing parameters were identified as a fixed set of parameters for a region. The application of our work is the European Flood Awareness System (http://www.efas.eu), where a distributed model is run with meteorological ensembles as input. We are therefore dealing with a considerably larger data set than previous analyses. We also want to regionalize the parameters themselves for other locations than the calibration gauges. The post-processing parameters are therefore estimated for each calibration station, but with a spatial penalty for deviations from neighbouring stations, depending on the expected semivariance between the calibration catchment and these stations. The estimated post-processed parameters can then be used for regionalization of the postprocessing parameters also for uncalibrated locations using top-kriging in the rtop-package (Skøien et al., 2006, 2014). We will show results from cross-validation of the methodology and although our interest is mainly in identifying exceedance probabilities for certain return levels, we will also show how the rtop package can be used for creating a set of post-processed ensembles through simulations.

Simulation of the interannual variations of biogenic emissions of volatile organic compounds in China: Impacts on tropospheric ozone and secondary organic aerosol

NASA Astrophysics Data System (ADS)

Fu, Y.; Liao, H.

2012-12-01

We use the MEGAN (Model of emissions of Gases and Aerosols from Nature) module embedded within the global three-dimensional Goddard Earth Observing System chemical transport model (GEOS-Chem) to simulate the interannual variations in biogenic volatile organic compound (BVOC) emissions and concentrations of ozone and secondary organic aerosols (SOA) in China over years 2001-2006. To have better representation of biogenic emissions, we have updated in the model the land cover and leaf area index in China using Moderate Resolution Imaging Spectroradiometer (MODIS) satellite measurements, and we have developed a new classification of vegetation with 21 plant functional types. Estimated annual BVOC emission in China averaged over 2001-2006 is 18.85 Tg C yr-1, in which emissions of isoprene, monoterpenes, and other reactive volatile organic compounds account for 50.9%, 15.0%, and 34.1%, respectively. The simulated BVOC emissions in China have large interannual variations. The values of regionally averaged absolute percent departure from the mean (APDM) of isoprene emissions are in the range of 21-42% in January and 15-28% in July. The APDM values of monoterpene emissions are 14-32% in January and 10-21% in July, which are generally smaller than those of isoprene emissions. Model results indicate that the interannual variations in isoprene emissions are more dependent on variations in meteorological fields, whereas the interannual variations in monoterpene emissions are more sensitive to changes in vegetation parameters. With fixed anthropogenic emissions, as a result of the variations in both meteorological parameters and vegetation, simulated O3 concentrations show interannual variations of 0.8-5 ppbv (or largest APDM values of 4-15%), and simulated SOA shows APDM values of 5-15% in southwestern China in January as well as 10-25% in southeastern and 20-35% in northeastern China in July. On a regional mean basis, the interannual variations in BVOCs alone can lead to 2-5% differences in simulated O3 and SOA in summer.

Simulation of the interannual variations of biogenic emissions of volatile organic compounds in China: Impacts on tropospheric ozone and secondary organic aerosol

NASA Astrophysics Data System (ADS)

Fu, Yu; Liao, Hong

2012-11-01

We use the MEGAN (Model of emissions of Gases and Aerosols from Nature) module embedded within the global three-dimensional Goddard Earth Observing System chemical transport model (GEOS-Chem) to simulate the interannual variations in biogenic volatile organic compound (BVOC) emissions and concentrations of ozone and secondary organic aerosols (SOA) in China over years 2001-2006. To have better representation of biogenic emissions, we have updated in the model the land cover and leaf area index in China using Moderate Resolution Imaging Spectroradiometer (MODIS) satellite measurements, and we have developed a new classification of vegetation with 21 plant functional types. Estimated annual BVOC emission in China averaged over 2001-2006 is 18.85 Tg C yr-1, in which emissions of isoprene, monoterpenes, and other reactive volatile organic compounds account for 50.9%, 15.0%, and 34.1%, respectively. The simulated BVOC emissions in China have large interannual variations. The values of regionally averaged absolute percent departure from the mean (APDM) of isoprene emissions are in the range of 21-42% in January and 15-28% in July. The APDM values of monoterpene emissions are 14-32% in January and 10-21% in July, which are generally smaller than those of isoprene emissions. Model results indicate that the interannual variations in isoprene emissions are more dependent on variations in meteorological fields, whereas the interannual variations in monoterpene emissions are more sensitive to changes in vegetation parameters. With fixed anthropogenic emissions, as a result of the variations in both meteorological parameters and vegetation, simulated O3 concentrations show interannual variations of 0.8-5 ppbv (or largest APDM values of 4-15%), and simulated SOA shows APDM values of 5-15% in southwestern China in January as well as 10-25% in southeastern and 20-35% in northeastern China in July. On a regional mean basis, the interannual variations in BVOCs alone can lead to 2-5% differences in simulated O3 and SOA in summer.

A statistical retrieval of cloud parameters for the millimeter wave Ice Cloud Imager on board MetOp-SG

NASA Astrophysics Data System (ADS)

Prigent, Catherine; Wang, Die; Aires, Filipe; Jimenez, Carlos

2017-04-01

The meteorological observations from satellites in the microwave domain are currently limited to below 190 GHz. However, the next generation of European Organisation for the Exploitation of Meteorological Satellites (EUMETSAT) Polar System-Second Generation-EPS-SG will carry an instrument, the Ice Cloud Imager (ICI), with frequencies up to 664 GHz, to improve the characterization of the cloud frozen phase. In this paper, a statistical retrieval of cloud parameters for ICI is developed, trained on a synthetic database derived from the coupling of a mesoscale cloud model and radiative transfer calculations. The hydrometeor profiles simulated with the Weather Research and Forecasting model (WRF) for twelve diverse European mid-latitude situations are used to simulate the brightness temperatures with the Atmospheric Radiative Transfer Simulator (ARTS) to prepare the retrieval database. The WRF+ARTS simulations have been compared to the Special Sensor Microwave Imager/Sounder (SSMIS) observations up to 190 GHz: this successful evaluation gives us confidence in the simulations at the ICI channels from 183 to 664 GHz. Statistical analyses have been performed on this simulated retrieval database, showing that it is not only physically realistic but also statistically satisfactory for retrieval purposes. A first Neural Network (NN) classifier is used to detect the cloud presence. A second NN is developed to retrieve the liquid and ice integrated cloud quantities over sea and land separately. The detection and retrieval of the hydrometeor quantities (i.e., ice, snow, graupel, rain, and liquid cloud) are performed with ICI-only, and with ICI combined with observations from the MicroWave Imager (MWI, with frequencies from 19 to 190 GHz, also on board MetOp-SG). The ICI channels have been optimized for the detection and quantification of the cloud frozen phases: adding the MWI channels improves the performance of the vertically integrated hydrometeor contents, especially for the cloud liquid phases. The relative error for the retrieved integrated frozen water content (FWP, i.e., ice+snow+graupel) is below 40% for 0.1kg/m2 < FWP < 0.5kg/m2 and below 20% for FWP > 0.5 kg/m2.

Analysis of the WRF-Chem simulations contributing to the AQMEII-Phase II exercise with respect to aerosol impact on precipitation

NASA Astrophysics Data System (ADS)

Werhahn, Johannes; Balzarini, Allessandra; Baró, Roccio; Curci, Gabriele; Forkel, Renate; Hirtl, Marcus; Honzak, Luka; Jiménez-Guerrero, Pedro; Langer, Matthias; Lorenz, Christof; Pérez, Juan L.; Pirovano, Guido; San José, Roberto; Tuccella, Paolo; Žabkar, Rahela

2014-05-01

Simulated feedback effects between aerosol concentrations and meteorological variables and on pollutant distributions are expected to depend on model configuration and the meteorological situation. In order to quantity these effects the second phase of the AQMEII (Air Quality Model Evaluation International Initiative; http://aqmeii.jrc.ec.europa.eu/) model inter-comparison exercise focused on online coupled meteorology-chemistry models. Among others, seven of the participating groups contributed simulations with WRF-Chem (Grell et al., 2005) for Europe. According to the common simulation strategy for AQMEII phase 2, the entire year 2010 was simulated as a sequence of 2-day time slices. For better comparability, the seven groups using WRF-Chem applied the same grid spacing of 23 km and shared common processing of initial and boundary conditions as well as anthropogenic and fire emissions. The simulations differ by the chosen chemistry option, aerosol module, cloud microphysics, and by the degree of aerosol-meteorology feedback that was considered. Results from this small ensemble are analyzed with respect to the effect of the different degrees of aerosol-meteorology feedback, i.e. no aerosol feedback, direct aerosol effect, and direct plus indirect aerosol effect, on large scale precipitation. Simulated precipitation fields were compared against daily precipitation observations as given by E-OBS 25 km resolution gridded dataset from the EU-FP6 project ENSEMBLES (http://ensembles-eu.metoffice.com) and the data providers in the ECA&D project (http://www.ecad.eu). As expected, a first analysis confirms that the average impact of aerosol feedback is only very small on the considered spatial and temporal scale, i.e. due to the fact that initial meteorological conditions were taken every 3rd day from a one day non-feedback spin-up run. However, the analysis of the correlations between simulation and observations for the first and the second day indicates for some particular situations and regions a slightly better correlation when the aerosol indirect effect is accounted for.

TEMPORAL FEATURES IN OBSERVED AND SIMULATED METEOROLOGY AND AIR QUALITY OVER THE EASTERN UNITED STATES

EPA Science Inventory

In this study, temporal scale analysis is applied as a technique to evaluate an annual simulation of meteorology, O₃, and PM_2.5 and its chemical components over the continental U.S. utilizing two modeling systems. It is illustrated that correlations were ins...

Tropospheric transport differences between models using the same large-scale meteorological fields

NASA Astrophysics Data System (ADS)

Orbe, Clara; Waugh, Darryn W.; Yang, Huang; Lamarque, Jean-Francois; Tilmes, Simone; Kinnison, Douglas E.

2017-01-01

The transport of chemicals is a major uncertainty in the modeling of tropospheric composition. A common approach is to transport gases using the winds from meteorological analyses, either using them directly in a chemical transport model or by constraining the flow in a general circulation model. Here we compare the transport of idealized tracers in several different models that use the same meteorological fields taken from Modern-Era Retrospective analysis for Research and Applications (MERRA). We show that, even though the models use the same meteorological fields, there are substantial differences in their global-scale tropospheric transport related to large differences in parameterized convection between the simulations. Furthermore, we find that the transport differences between simulations constrained with the same-large scale flow are larger than differences between free-running simulations, which have differing large-scale flow but much more similar convective mass fluxes. Our results indicate that more attention needs to be paid to convective parameterizations in order to understand large-scale tropospheric transport in models, particularly in simulations constrained with analyzed winds.

Integration of Ground, Buoys, Satellite and Model data to map the Changes in Meteorological Parameters Associated with Harvey Hurricane

NASA Astrophysics Data System (ADS)

Chauhan, A.; Sarkar, S.; Singh, R. P.

2017-12-01

The coastal areas have dense onshore and marine observation network and are also routinely monitored by constellation of satellites. The monitoring of ocean, land and atmosphere through a range of meteorological parameters, provides information about the land and ocean surface. Satellite data also provide information at different pressure levels that help to access the development of tropical storms and formation of hurricanes at different categories. Integration of ground, buoys, satellite and model data showing the changes in meteorological parameters during the landfall stages of hurricane Harvey will be discussed. Hurricane Harvey was one of the deadliest hurricanes at the Gulf coast which caused intense flooding from the precipitation. The various observation networks helped city administrators to evacuate the coastal areas, that minimized the loss of lives compared to the Galveston hurricane of 1900 which took 10,000 lives. Comparison of meteorological parameters derived from buoys, ground stations and satellites associated with Harvey and 2005 Katrina hurricane present some of the interesting features of the two hurricanes.

Preliminary Evaluation of the DUSTRAN Modeling Suite for Modeling Atmospheric Chloride Transport

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

Jensen, Philip; Tran, Tracy; Fritz, Bradley

2016-05-03

This study investigates the potential of DUSTRAN, a dust dispersion modeling system developed by Pacific Northwest National Laboratory, to model the transport of sea salt aerosols (SSA). Results from DUSTRAN simulations run with historical meteorological data were compared against privately-measured chloride data at the near coastal Maine Yankee Nuclear Power Plant (NPP) and the Environmental Protection Agency-measured CASTNET data from Acadia National Park (NP). The comparisons have provided both encouragement as to the practical value of DUSTRAN’s CALPUFF model and suggestions for further software development opportunities. All modeled concentrations were within one order of magnitude of those measured and amore » few test cases showed excellent agreement between modeled and measured concentrations. However, there is a lack of consistency in discrepancy which may be due to inaccurate extrapolation of meteorological data, underlying model physics, and the source term. Future research will refine the software to better capture physical phenomena. Overall, results indicate that with parameter refinement, DUSTRAN has the potential to simulate atmospheric chloride transport from known sources to inland sites for the purpose of determining the corrosion susceptibility of various structures, systems, and components at the site.« less

The NASA-Langley Wake Vortex Modelling Effort in Support of an Operational Aircraft Spacing System

NASA Technical Reports Server (NTRS)

Proctor, Fred H.

1998-01-01

Two numerical modelling efforts, one using a large eddy simulation model and the other a numerical weather prediction model, are underway in support of NASA's Terminal Area Productivity program. The large-eddy simulation model (LES) has a meteorological framework and permits the interaction of wake vortices with environments characterized by crosswind shear, stratification, humidity, and atmospheric turbulence. Results from the numerical simulations are being used to assist in the development of algorithms for an operational wake-vortex aircraft spacing system. A mesoscale weather forecast model is being adapted for providing operational forecast of winds, temperature, and turbulence parameters to be used in the terminal area. This paper describes the goals and modelling approach, as well as achievements obtained to date. Simulation results will be presented from the LES model for both two and three dimensions. The 2-D model is found to be generally valid for studying wake vortex transport, while the 3-D approach is necessary for realistic treatment of decay via interaction of wake vortices and atmospheric boundary layer turbulence. Meteorology is shown to have an important affect on vortex transport and decay. Presented are results showing that wake vortex transport is unaffected by uniform fog or rain, but wake vortex transport can be strongly affected by nonlinear vertical change in the ambient crosswind. Both simulation and observations show that atmospheric vortices decay from the outside with minimal expansion of the core. Vortex decay and the onset three-dimensional instabilities are found to be enhanced by the presence of ambient turbulence.

Performance of WRF for Simulation of Mesoscale Meteorological Characteristics for Air Quality Assessment over Tropical Coastal City, Chennai

NASA Astrophysics Data System (ADS)

Madala, Srikanth; Srinivas, C. V.; Satyanarayana, A. N. V.

2018-01-01

The land-sea breezes (LSBs) play an important role in transporting air pollution from urban areas on the coast. In this study, the Advanced Research WRF (ARW) mesoscale model is used for predicting boundary layer features to understand the transport of pollution in different seasons over the coastal region of Chennai in Southern India. Sensitivity experiments are conducted with two non-local [Yonsei University (YSU) and Asymmetric Convective Model version 2 (ACM2)] and three turbulence kinetic energy (TKE) closure [Mellor-Yamada-Nakanishi and Niino Level 2.5 (MYNN2) and Mellor-Yamada-Janjic (MYJ) and quasi-normal scale elimination (QNSE)], planetary boundary layer (PBL) parameterization schemes for simulating the thermodynamic structure, and low-level atmospheric flow in different seasons. Comparison of simulations with observations from a global positioning system (GPS) radiosonde, meteorological tower, automated weather stations, and Doppler weather radar (DWR)-derived wind data reveals that the characteristics of LSBs vary widely in different seasons and are more prominent during the pre-monsoon and monsoon seasons (March-September) with large horizontal and vertical extents compared to the post-monsoon and winter seasons. The qualitative and quantitative results indicate that simulations with ACM2 followed by MYNN2 and YSU produced various features of the LSBs, boundary layer parameters and the thermo-dynamical structure in better agreement with observations than other tested physical parameterization schemes. Simulations revealed seasonal variation of onset time, vertical extent of LSBs, and mixed layer depth, which would influence the air pollution dispersion in different seasons over the study region.

What is the sensitivity of the mineral dust cycle at the regional scale to surface wind speed? First insights from the DRUMS project.

NASA Astrophysics Data System (ADS)

Bouet, Christel; Siour, Guillaume; Poulet, David; Bergametti, Gilles; Laurent, Benoit; Brocheton, Fabien; Forêt, Gilles; Xu, Yiwen; Marticorena, Béatrice

2017-04-01

Modelling of the mineral dust cycle is still a challenging issue both at the global and regional scales: during the last decade, several exercises of model intercomparison highlighted the wide variability of the existing dust models to estimate dust emission fluxes and atmospheric load at both scales. For instance, within the framework of the international AEROCOM Project (http://aerocom.met.no/), 15 different global dust models provide a range of possible dust emission fluxes from 400 to 2200 Tg yr-1 for North Africa and from 26 to 526 Tg yr-1 for the Middle East, i.e. still a factor of 5 and 20 respectively (Huneeus et al., 2011). Whatever the scale, a critical aspect for any dust model is the sensitivity to the meteorological fields used to compute dust emission fluxes (external forcing or simulated by the coupled meteorological or climatic model). Indeed, the intensity of dust emission varies as a power 3 of the surface wind speed, and the number of dust emission events is the number of times the surface wind speed exceeds the wind erosion threshold. As a result, the simulations of dust emissions are extremely sensitive to the way the surface wind speeds are accounted for both in global and regional models. In this context, the aim of the DRUMS (DeseRt dUst Modeling: performance and Sensitivity evaluation) project was to investigate the sensitivity of a regional dust model (CHIMERE) to this parameter. This sensitivity study was conducted for 3 years from 2006 to 2008 over the North of Africa (45°N-0°N; 45°W-55°E), where dust emissions are the most intense. Emission fluxes can be simulated there with the most relevant data set of surface properties controlling dust emissions and accounting for the heterogeneity of land surfaces (surface roughness, soil size distribution and texture) of desert regions (Laurent et al., 2008). Meteorological products (forecasts and re-analysis) provided by the most recognized international meteorological centres (US NCEP and ECMWF), and thus the most widely used for the simulations of the mineral dust cycle, were tested. In addition, the benefit provided by the use of the WRF model to downscale the meteorological forcing was evaluated. The estimation of the performance of the CHIMERE model forced by the different meteorological fields was conducted using a unique validation data set compiled during the project by analysing and evaluating (i) the large number of experimental data resulting from the AMMA (African Monsoon Multidisciplinary Analysis) field campaigns, (ii) long-term aerosol monitoring over West Africa (Sahelian Dust Transect) and downwind the Sahara/Sahel region (AERONET), and (iii) recent satellite aerosol products (SeaWIFS AOD). This dataset allowed to validate the main characteristics of the dust cycle (emission, transport, and deposit).

Comparative analysis of meteorological performance of coupled chemistry-meteorology models in the context of AQMEII phase 2

EPA Science Inventory

Air pollution simulations critically depend on the quality of the underlying meteorology. In phase 2 of the Air Quality Model Evaluation International Initiative (AQMEII-2), thirteen modeling groups from Europe and four groups from North America operating eight different regional...

Meteorology, Emissions, and Grid Resolution: Effects on Discrete and Probabilistic Model Performance

EPA Science Inventory

In this study, we analyze the impacts of perturbations in meteorology and emissions and variations in grid resolution on air quality forecast simulations. The meteorological perturbations con-sidered in this study introduce a typical variability of ~1°C, 250 - 500 m, 1 m/s, and 1...

WRF-CMAQ Two-way Coupled System with Aerosol Feedback: Software Development and Preliminary Results

EPA Science Inventory

Air quality models such as the EPA Community Multiscale Air Quality (CMAQ) require meteorological data as part of the input to drive the chemistry and transport simulation. The Meteorology-Chemistry Interface Processor (MCIP) is used to convert meteorological data into CMAQ-ready...

A study to define meteorological uses and performance requirements for the Synchronous Earth Observatory Satellite

NASA Technical Reports Server (NTRS)

Suomi, V. E.; Krauss, R. J.; Barber, D.; Levanon, N.; Martin, D. W.; Mclellan, D. W.; Sikdar, D. N.; Sromovsky, L. A.; Branch, D.; Heinricy, D.

1973-01-01

The potential meteorological uses of the Synchronous Earth Observatory Satellite (SEOS) were studied for detecting and predicting hazards to life, property, or the quality of the environment. Mesoscale meteorological phenonmena, and the observations requirements for SEOS are discussed along with the sensor parameters.

Atmospherical simulations of the OMEGA/MEX observations

NASA Astrophysics Data System (ADS)

Melchiorri, R.; Drossart, P.; Combes, M.; Encrenaz, T.; Fouchet, T.; Forget, F.; Bibring, J. P.; Ignatiev, N.; Moroz, V.; OMEGA Team

The modelization of the atmospheric contribution in the martian spectrum is an important step for the OMEGA data analysis.A full line by line radiative transfer calculation is made for the gas absorption; the dust opacity component, in a first approximation, is calculated as an optically thin additive component.Due to the large number of parameters needed in the calculations, the building of a huge data base to be interpolated is not envisageable, for each observed OMEGA spectrum with calculation for all the involved parameters (atmospheric pressure, water abundance, CO abundance, dust opacity and geometric angles of observation). The simulation of the observations allows us to fix all the orbital parameters and leave the unknown parameters as the only variables.Starting from the predictions of the current meteorological models of Mars we build a smaller data base corresponding on each observation. We present here a first order simulation, which consists in retrieving atmospheric contribution from the solar reflected component as a multiplicative (for gas absorption) and an additive component (for suspended dust contribution); although a fully consistent approach will require to include surface and atmosphere contributions together in synthetic calculations, this approach is sufficient for retrieving mineralogic information cleaned from atmospheric absorption at first order.First comparison to OMEGA spectra will be presented, with first order retrieval of CO2 pressure, CO and H2O abundance, and dust opacity.

Radiation environment study of near space in China area

NASA Astrophysics Data System (ADS)

Fan, Dongdong; Chen, Xingfeng; Li, Zhengqiang; Mei, Xiaodong

2015-10-01

Aerospace activity becomes research hotspot for worldwide aviation big countries. Solar radiation study is the prerequisite for aerospace activity to carry out, but lack of observation in near space layer becomes the barrier. Based on reanalysis data, input key parameters are determined and simulation experiments are tried separately to simulate downward solar radiation and ultraviolet radiation transfer process of near space in China area. Results show that atmospheric influence on the solar radiation and ultraviolet radiation transfer process has regional characteristic. As key factors such as ozone are affected by atmospheric action both on its density, horizontal and vertical distribution, meteorological data of stratosphere needs to been considered and near space in China area is divided by its activity feature. Simulated results show that solar and ultraviolet radiation is time, latitude and ozone density-variant and has complicated variation characteristics.

A Reduced Form Model for Ozone Based on Two Decades of ...

EPA Pesticide Factsheets

A Reduced Form Model (RFM) is a mathematical relationship between the inputs and outputs of an air quality model, permitting estimation of additional modeling without costly new regional-scale simulations. A 21-year Community Multiscale Air Quality (CMAQ) simulation for the continental United States provided the basis for the RFM developed in this study. Predictors included the principal component scores (PCS) of emissions and meteorological variables, while the predictand was the monthly mean of daily maximum 8-hour CMAQ ozone for the ozone season at each model grid. The PCS form an orthogonal basis for RFM inputs. A few PCS incorporate most of the variability of emissions and meteorology, thereby reducing the dimensionality of the source-receptor problem. Stochastic kriging was used to estimate the model. The RFM was used to separate the effects of emissions and meteorology on ozone concentrations. by running the RFM with emissions constant (ozone dependent on meteorology), or constant meteorology (ozone dependent on emissions). Years with ozone-conducive meteorology were identified, and meteorological variables best explaining meteorology-dependent ozone were identified. Meteorology accounted for 19% to 55% of ozone variability in the eastern US, and 39% to 92% in the western US. Temporal trends estimated for original CMAQ ozone data and emission-dependent ozone were mostly negative, but the confidence intervals for emission-dependent ozone are much

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

NASA Astrophysics Data System (ADS)

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

2013-12-01

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

Evaluation of a simple, point-scale hydrologic model in simulating soil moisture using the Delaware environmental observing system

NASA Astrophysics Data System (ADS)

Legates, David R.; Junghenn, Katherine T.

2018-04-01

Many local weather station networks that measure a number of meteorological variables (i.e. , mesonetworks) have recently been established, with soil moisture occasionally being part of the suite of measured variables. These mesonetworks provide data from which detailed estimates of various hydrological parameters, such as precipitation and reference evapotranspiration, can be made which, when coupled with simple surface characteristics available from soil surveys, can be used to obtain estimates of soil moisture. The question is Can meteorological data be used with a simple hydrologic model to estimate accurately daily soil moisture at a mesonetwork site? Using a state-of-the-art mesonetwork that also includes soil moisture measurements across the US State of Delaware, the efficacy of a simple, modified Thornthwaite/Mather-based daily water balance model based on these mesonetwork observations to estimate site-specific soil moisture is determined. Results suggest that the model works reasonably well for most well-drained sites and provides good qualitative estimates of measured soil moisture, often near the accuracy of the soil moisture instrumentation. The model exhibits particular trouble in that it cannot properly simulate the slow drainage that occurs in poorly drained soils after heavy rains and interception loss, resulting from grass not being short cropped as expected also adversely affects the simulation. However, the model could be tuned to accommodate some non-standard siting characteristics.

A Research Study of Tropospheric Ozone and Meteorological Parameters to Introduce High School Students to Scientific Procedures

ERIC Educational Resources Information Center

Diaz-de-Mera, Yolanda; Notario, Alberto; Aranda, Alfonso; Adame, Jose Antonio; Parra, Alfonso; Romero, Eugenio; Parra, Jesus; Munoz, Fernando

2011-01-01

An environmental research project was carried out by a consortium established among scientists and university lecturers in collaboration with two high schools. High school students participated in a long-term study of the local temporal profiles of tropospheric ozone and the relationship to pollution and meteorological parameters. Low-cost…

The role of meteorological conditions and pollution control strategies in reducing air pollution in Beijing during APEC 2014 and Victory Parade 2015

NASA Astrophysics Data System (ADS)

Liang, Pengfei; Zhu, Tong; Fang, Yanhua; Li, Yingruo; Han, Yiqun; Wu, Yusheng; Hu, Min; Wang, Junxia

2017-11-01

To control severe air pollution in China, comprehensive pollution control strategies have been implemented throughout the country in recent years. To evaluate the effectiveness of these strategies, the influence of meteorological conditions on levels of air pollution needs to be determined. Using the intensive air pollution control strategies implemented during the Asia-Pacific Economic Cooperation Forum in 2014 (APEC 2014) and the 2015 China Victory Day Parade (Victory Parade 2015) as examples, we estimated the role of meteorological conditions and pollution control strategies in reducing air pollution levels in Beijing. Atmospheric particulate matter of aerodynamic diameter ≤ 2.5 µm (PM2.5) samples were collected and gaseous pollutants (SO2, NO, NOx, and O3) were measured online at a site in Peking University (PKU). To determine the influence of meteorological conditions on the levels of air pollution, we first compared the air pollutant concentrations during days with stable meteorological conditions. However, there were few days with stable meteorological conditions during the Victory Parade. As such, we were unable to estimate the level of emission reduction efforts during this period. Finally, a generalized linear regression model (GLM) based only on meteorological parameters was built to predict air pollutant concentrations, which could explain more than 70 % of the variation in air pollutant concentration levels, after incorporating the nonlinear relationships between certain meteorological parameters and the concentrations of air pollutants. Evaluation of the GLM performance revealed that the GLM, even based only on meteorological parameters, could be satisfactory to estimate the contribution of meteorological conditions in reducing air pollution and, hence, the contribution of control strategies in reducing air pollution. Using the GLM, we found that the meteorological conditions and pollution control strategies contributed 30 and 28 % to the reduction of the PM2.5 concentration during APEC and 38 and 25 % during the Victory Parade, respectively, based on the assumption that the concentrations of air pollutants are only determined by meteorological conditions and emission intensities. We also estimated the contribution of meteorological conditions and control strategies in reducing the concentrations of gaseous pollutants and PM2.5 components with the GLMs, revealing the effective control of anthropogenic emissions.

Results of meteorological monitoring in Gorny Altai before and after the Chuya earthquake in 2003

NASA Astrophysics Data System (ADS)

Aptikaeva, O. I.; Shitov, A. V.

2014-12-01

We consider the dynamics of some meteorological parameters in Gorny Altai from 2000 to 2011. We analyzed the variations in the meteorological parameters related to the strong Chuya earthquake (September 27, 2003). A number of anomalies were revealed in the time series. Before this strong earthquake, the winter temperatures at the nearest meteorological station to the earthquake source increased by 8-10°C (by 2009 they returned to the mean values), while the air humidity in winter decreased. In the winter of 2002, we observed a long negative anomaly in the time series of the atmospheric pressure. At the same time, the decrease in the released seismic energy was replaced by the tendency to its increase. Using wavelet analysis we revealed the synchronism in the dynamics of the atmospheric parameters, variations in the solar and geomagnetic activities, and geodynamic processes. We also discuss the relationship of the atmospheric and geodynamic processes and the comfort conditions of the population in the climate analyzed here.

Remote sensing of tropospheric turbulence using GPS radio occultation

NASA Astrophysics Data System (ADS)

Shume, Esayas; Ao, Chi

2016-07-01

Radio occultation (RO) measurements are sensitive to the small-scale irregularities in the atmosphere. In this study, we present a new technique to estimate tropospheric turbulence strength (namely, scintillation index) by analyzing RO amplitude fluctuations in impact parameter domain. GPS RO observations from the COSMIC (Constellation Observing System for Meteorology, Ionosphere, and Climate) satellites enabled us to calculate global maps of scintillation measures, revealing the seasonal, latitudinal, and longitudinal characteristics of the turbulent troposphere. Such information are both difficult and expensive to obtain especially over the oceans. To verify our approach, simulation experiments using the multiple phase screen (MPS) method were conducted. The results show that scintillation indices inferred from the MPS simulations are in good agreement with scintillation measures estimated from COSMIC observations.

One multi-media environmental system with linkage between meteorology/ hydrology/ air quality models and water quality model

NASA Astrophysics Data System (ADS)

Tang, C.; Lynch, J. A.; Dennis, R. L.

2016-12-01

The biogeochemical processing of nitrogen and associated pollutants is driven by meteorological and hydrological processes in conjunction with pollutant loading. There are feedbacks between meteorology and hydrology that will be affected by land-use change and climate change. Changes in meteorology will affect pollutant deposition. It is important to account for those feedbacks and produce internally consistent simulations of meteorology, hydrology, and pollutant loading to drive the (watershed/water quality) biogeochemical models. In this study, the ecological response to emission reductions in streams in the Potomac watershed was evaluated. Firstly, we simulated the deposition by using the fully coupled Weather Research & Forecasting (WRF) model and the Community Multiscale Air Quality (CAMQ) model; secondly, we created the hydrological data by the offline linked Variable Infiltration Capacity (VIC) model and the WRF model. Lastly, we investigated the water quality by one comprehensive/environment model, namely the linkage of CMAQ, WRF, VIC and the Model of Acidification of Groundwater In Catchment (MAGIC) model from 2002 to 2010.The simulated results (such as NO3, SO4, and SBC) fit well to the observed values. The linkage provides a generally accurate, well-tested tool for evaluating sensitivities to varying meteorology and environmental changes on acidification and other biogeochemical processes, with capability to comprehensively explore strategic policy and management design.

WRF model for precipitation simulation and its application in real-time flood forecasting in the Jinshajiang River Basin, China

NASA Astrophysics Data System (ADS)

Zhou, Jianzhong; Zhang, Hairong; Zhang, Jianyun; Zeng, Xiaofan; Ye, Lei; Liu, Yi; Tayyab, Muhammad; Chen, Yufan

2017-07-01

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.

[Adaptability of APSIM model in Southwestern China: A case study of winter wheat in Chongqing City].

PubMed

Dai, Tong; Wang, Jing; He, Di; Zhang, Jian-ping; Wang, Na

2015-04-01

Field experimental data of winter wheat and parallel daily meteorological data at four typical stations in Chongqing City were used to calibrate and validate APSIM-wheat model and determine the genetic parameters for 12 varieties of winter wheat. The results showed that there was a good agreement between the simulated and observed growth periods from sowing to emergence, flowering and maturity of wheat. Root mean squared errors (RMSEs) between simulated and observed emergence, flowering and maturity were 0-3, 1-8, and 0-8 d, respectively. Normalized root mean squared errors (NRMSEs) between simulated and observed above-ground biomass for 12 study varieties were less than 30%. NRMSE between simulated and observed yields for 10 varieties out of 12 study varieties were less than 30%. APSIM-wheat model performed well in simulating phenology, aboveground biomass and yield of winter wheat in Chongqing City, which could provide a foundational support for assessing the impact of climate change on wheat production in the study area based on the model.

Oceanic influence on seasonal malaria outbreaks over Senegal and Sahel

NASA Astrophysics Data System (ADS)

Diouf, Ibrahima; Rodríguez de Fonseca, Belen; Deme, Abdoulaye; Cisse Cisse, Moustapha; Ndione Ndione, Jaques-Andre; Gaye, Amadou T.; Suarez, Roberto

2015-04-01

Beyond assessment and analysis of observed and simulated malaria parameters, this study is furthermore undertaken in the framework of predictability of malaria outbreaks in Senegal and remote regions in Sahel, which are found to take place two months after the rainy season. The predictors are the sea surface temperature anomalous patterns at different ocean basins mainly over the Pacific and Atlantic as they are related to changes in air temperature, humidity, rainfall and wind. A relationship between El Niño and anomalous malaria parameters is found. The malaria parameters are calculated with the Liverpool Malaria Model (LMM) using meteorological datasets from different reanalysis products. A hindcast of these parameters is performed using the Sea Surface temperature based Statistical Seasonal ForeCAST (S4CAST) model developed at UCM in order to predict malaria parameters some months in advance. The results of this work will be useful for decision makers to better access to climate forecasts and application on malaria transmission risk.

Modeling the impacts of green infrastructure land use changes on air quality and meteorology case study and sensitivity analysis in Kansas City

EPA Science Inventory

Changes in vegetation cover associated with urban planning efforts may affect regional meteorology and air quality. Here we use a comprehensive coupled meteorology-air quality model (WRF-CMAQ) to simulate the influence of planned land use changes from green infrastructure impleme...

Instantaneous-to-daily GPP upscaling schemes based on a coupled photosynthesis-stomatal conductance model: correcting the overestimation of GPP by directly using daily average meteorological inputs.

PubMed

Wang, Fumin; Gonsamo, Alemu; Chen, Jing M; Black, T Andrew; Zhou, Bin

2014-11-01

Daily canopy photosynthesis is usually temporally upscaled from instantaneous (i.e., seconds) photosynthesis rate. The nonlinear response of photosynthesis to meteorological variables makes the temporal scaling a significant challenge. In this study, two temporal upscaling schemes of daily photosynthesis, the integrated daily model (IDM) and the segmented daily model (SDM), are presented by considering the diurnal variations of meteorological variables based on a coupled photosynthesis-stomatal conductance model. The two models, as well as a simple average daily model (SADM) with daily average meteorological inputs, were validated using the tower-derived gross primary production (GPP) to assess their abilities in simulating daily photosynthesis. The results showed IDM closely followed the seasonal trend of the tower-derived GPP with an average RMSE of 1.63 g C m(-2) day(-1), and an average Nash-Sutcliffe model efficiency coefficient (E) of 0.87. SDM performed similarly to IDM in GPP simulation but decreased the computation time by >66%. SADM overestimated daily GPP by about 15% during the growing season compared to IDM. Both IDM and SDM greatly decreased the overestimation by SADM, and improved the simulation of daily GPP by reducing the RMSE by 34 and 30%, respectively. The results indicated that IDM and SDM are useful temporal upscaling approaches, and both are superior to SADM in daily GPP simulation because they take into account the diurnally varying responses of photosynthesis to meteorological variables. SDM is computationally more efficient, and therefore more suitable for long-term and large-scale GPP simulations.

Assessment of NASA's Physiographic and Meteorological Datasets as Input to HSPF and SWAT Hydrological Models

NASA Technical Reports Server (NTRS)

Alacron, Vladimir J.; Nigro, Joseph D.; McAnally, William H.; OHara, Charles G.; Engman, Edwin Ted; Toll, David

2011-01-01

This paper documents the use of simulated Moderate Resolution Imaging Spectroradiometer land use/land cover (MODIS-LULC), NASA-LIS generated precipitation and evapo-transpiration (ET), and Shuttle Radar Topography Mission (SRTM) datasets (in conjunction with standard land use, topographical and meteorological datasets) as input to hydrological models routinely used by the watershed hydrology modeling community. The study is focused in coastal watersheds in the Mississippi Gulf Coast although one of the test cases focuses in an inland watershed located in northeastern State of Mississippi, USA. The decision support tools (DSTs) into which the NASA datasets were assimilated were the Soil Water & Assessment Tool (SWAT) and the Hydrological Simulation Program FORTRAN (HSPF). These DSTs are endorsed by several US government agencies (EPA, FEMA, USGS) for water resources management strategies. These models use physiographic and meteorological data extensively. Precipitation gages and USGS gage stations in the region were used to calibrate several HSPF and SWAT model applications. Land use and topographical datasets were swapped to assess model output sensitivities. NASA-LIS meteorological data were introduced in the calibrated model applications for simulation of watershed hydrology for a time period in which no weather data were available (1997-2006). The performance of the NASA datasets in the context of hydrological modeling was assessed through comparison of measured and model-simulated hydrographs. Overall, NASA datasets were as useful as standard land use, topographical , and meteorological datasets. Moreover, NASA datasets were used for performing analyses that the standard datasets could not made possible, e.g., introduction of land use dynamics into hydrological simulations

Simulation of meteorological satellite (METSAT) data using LANDSAT data

NASA Technical Reports Server (NTRS)

Austin, W. W.; Ryland, W. E.

1983-01-01

The information content which can be expected from the advanced very high resolution radiometer system, AVHRR, on the NOAA-6 satellite was assessed, and systematic techniques of data interpretation for use with meteorological satellite data were defined. In-house data from LANDSAT 2 and 3 were used to simulate the spatial, spectral, and sampling methods of the NOAA-6 satellite data.

Feedbacks between Air-Quality, Meteorology, and the Forest Environment

NASA Astrophysics Data System (ADS)

Makar, Paul; Akingunola, Ayodeji; Stroud, Craig; Zhang, Junhua; Gong, Wanmin; Moran, Michael; Zheng, Qiong; Brook, Jeffrey; Sills, David

2017-04-01

The outcome of air quality forecasts depend in part on how the local environment surrounding the emissions regions influences chemical reaction rates and transport from those regions to the larger spatial scales. Forested areas alter atmospheric chemistry through reducing photolysis rates and vertical diffusivities within the forest canopy. The emitted pollutants, and their reaction products, are in turn capable of altering meteorology, through the well-known direct and indirect effects of particulate matter on radiative transfer. The combination of these factors was examined using version 2 of the Global Environmental Multiscale - Modelling Air-quality and CHemistry (GEM-MACH) on-line air pollution model. The model configuration used for this study included 12 aerosol size bins, eight aerosol species, homogeneous core Mie scattering, the Milbrandt-Yao two-moment cloud microphysics scheme with cloud condensation nuclei generated from model aerosols using the scheme of Abdul-Razzak and Ghan, and a new parameterization for forest canopy shading and turbulence. The model was nested to 2.5km resolution for a domain encompassing the lower Great Lakes, for simulations of a period in August of 2015 during the Pan American Games, held in Toronto, Canada. Four scenarios were carried out: (1) a "Base Case" scenario (the original model, in which coupling between chemistry and weather is not permitted; instead, the meteorological model's internal climatologies for aerosol optical and cloud condensation properties are used for direct and indirect effect calculations); (2) a "Feedback" scenario (the aerosol properties were derived from the internally simulated chemistry, and coupled to the meteorological model's radiative transfer and cloud formation modules); (3) a "Forest" scenario (canopy shading and turbulence were added to the Base Case); (4) a "Combined" scenario (including both direct and indirect effect coupling between meteorology and chemistry, as well as the forest canopy parameterization). The simulations suggest that the feedbacks between simulated aerosols and meteorology may strengthen the existing lake breeze circulation, modifying the resulting meteorological and air-quality forecasts, while the forest canopy's influence may extend throughout the planetary boundary layer, and may also influence the weather. The simulations will be compared to available observations, in order to determine their relative impact on model performance.

Modeling of meteorology, tracer transport and chemistry for the Uintah Basin Winter Ozone Studies 2012 and 2013

NASA Astrophysics Data System (ADS)

Ahmadov, R.; McKeen, S. A.; Angevine, W. M.; Frost, G. J.; Roberts, J. M.; De Gouw, J. A.; Warneke, C.; Peischl, J.; Brown, S. S.; Edwards, P. M.; Wild, R. J.; Pichugina, Y. L.; Banta, R. M.; Brewer, A.; Senff, C. J.; Langford, A. O.; Petron, G.; Karion, A.; Sweeney, C.; Schnell, R. C.; Johnson, B.; Zamora, R. J.; Helmig, D.; Park, J.; Evans, J.; Stephens, C. R.; Olson, J. B.; Trainer, M.

2013-12-01

The Uintah Basin Winter Ozone Studies (UBWOS) field campaigns took place during winter of 2012 and 2013 in the Uintah Basin, Utah. The studies were aimed at characterizing meteorology, emissions of atmospheric constituents and air chemistry in a region abundant with oil and gas production, with associated emissions of various volatile organic compounds (VOCs) and NOx. High ozone pollution events were observed throughout the Uintah Basin during the winter of 2013, but not during the winter of 2012. A clear understanding of the processes leading to high ozone events is still lacking. We present here high spatiotemporal resolution simulations of meteorology, tracer transport and gas chemistry over the basin during January-February, 2012 and 2013 using the WRF/Chem regional photochemical model. Correctly characterizing the meteorology poses unique challenges due to complex terrain, cold-pool conditions, and shallow inversion layers observed during the winter of 2013. We discuss the approach taken to adequately simulate the meteorology over the basin and present evaluations of the modeled meteorology using surface, lidar and tethersonde measurements. Initial simulations use a passive tracer within the model as a surrogate for CH4 released from oil and gas wells. These tracer transport simulations show that concentrations of inert, emitted species near the surface in 2013 were 4-8 times higher than 2012 due to much shallower boundary layers and reduced winds in 2013. This is supported by in-situ measurements of CH4 made at the Horse Pool surface station during the field campaigns. Full photochemical simulations are forced by VOC and NOx emissions that are determined in a top-down approach, using observed emission ratios of VOC and NOx relative to CH4, along with available information of active wells, compressors, and processing plants. We focus on differences in meteorology, temperature, and radiation between the two winters in determining ozone concentrations in the basin. The model is then used diagnostically to assess first-order sensitivities of basin-wide ozone to NOx or VOC emissions, and how they depend on the environmental differences between the winters of 2012 and 2013.

Black carbon and trace gases over South Asia: Measurements and Regional Climate model simulations

NASA Astrophysics Data System (ADS)

Bhuyan, Pradip; Pathak, Binita; Parottil, Ajay

2016-07-01

Trace gases and aerosols are simulated with 50 km spatial resolution over South Asian CORDEX domain enclosing the Indian sub-continent and North-East India for the year 2012 using two regional climate models RegCM4 coupled with CLM4.5 and WRF-Chem 3.5. Both models are found to capture the seasonality in the simulated O3 and its precursors, NOx and CO and black carbon concentrations together with the meteorological variables over the Indian Subcontinent as well as over the sub-Himalayan North-Eastern region of India including Bangladesh. The model simulations are compared with the measurements made at Dibrugarh (27.3°N, 94.6°E, 111 m amsl). Both the models are found to capture the observed diurnal and seasonal variations in O3 concentrations with maximum in spring and minimum in monsoon, the correlation being better for WRF-Chem (R~0.77) than RegCM (R~0.54). Simulated NOx and CO is underestimated in all the seasons by both the models, the performance being better in the case of WRF-Chem. The observed difference may be contributed by the bias in the estimation of the O3 precursors NOx and CO in the emission inventories or the error in the simulation of the meteorological variables which influences O3 concentration in both the models. For example, in the pre-monsoon and winter season, the WRF-Chem model simulated shortwave flux overestimates the observation by ~500 Wm-2 while in the monsoon and post monsoon season, simulated shortwave flux is equivalent to the observation. The model predicts higher wind speed in all the seasons especially during night-time. In the post-monsoon and winter season, the simulated wind pattern is reverse to observation with daytime low and night-time high values. Rainfall is overestimated in all the seasons. RegCM-CLM4.5 is found to underestimate rainfall and other meteorological parameters. The WRF-Chem model closely captured the observed values of black carbon mass concentrations during pre-monsoon and summer monsoon seasons, but deviated significantly during the winter season. On the other hand RegCM-CLM4.5 underestimates BC throughout the year. This may be attributed to the inaccuracy in the emission inventories, where the small scale local burnings those generating black carbon over this region is not accounted for either by the satellite (due to detection limit) as well as in the emission inventories considered in the model. Thus further improvement in the emission inventories is recommended in RegCM-CLM4.5.

Linking the Weather Generator with Regional Climate Model: Effect of Higher Resolution

NASA Astrophysics Data System (ADS)

Dubrovsky, Martin; Huth, Radan; Farda, Ales; Skalak, Petr

2014-05-01

This contribution builds on our last year EGU contribution, which followed two aims: (i) validation of the simulations of the present climate made by the ALADIN-Climate Regional Climate Model (RCM) at 25 km resolution, and (ii) presenting a methodology for linking the parametric weather generator (WG) with RCM output (aiming to calibrate a gridded WG capable of producing realistic synthetic multivariate weather series for weather-ungauged locations). Now we have available new higher-resolution (6.25 km) simulations with the same RCM. The main topic of this contribution is an anser to a following question: What is an effect of using a higher spatial resolution on a quality of simulating the surface weather characteristics? In the first part, the high resolution RCM simulation of the present climate will be validated in terms of selected WG parameters, which are derived from the RCM-simulated surface weather series and compared to those derived from weather series observed in 125 Czech meteorological stations. The set of WG parameters will include statistics of the surface temperature and precipitation series. When comparing the WG parameters from the two sources (RCM vs observations), we interpolate the RCM-based parameters into the station locations while accounting for the effect of altitude. In the second part, we will discuss an effect of using the higher resolution: the results of the validation tests will be compared with those obtained with the lower-resolution RCM. Acknowledgements: The present experiment is made within the frame of projects ALARO-Climate (project P209/11/2405 sponsored by the Czech Science Foundation), WG4VALUE (project LD12029 sponsored by the Ministry of Education, Youth and Sports of CR) and VALUE (COST ES 1102 action).

Evaluation of a Mesoscale Atmospheric Dispersion Modeling System with Observations from the 1980 Great Plains Mesoscale Tracer Field Experiment. Part I: Datasets and Meteorological Simulations.

NASA Astrophysics Data System (ADS)

Moran, Michael D.; Pielke, Roger A.

1996-03-01

The Colorado State University mesoscale atmospheric dispersion (MAD) numerical modeling system, which consists of a prognostic mesoscale meteorological model coupled to a mesoscale Lagrangian particle dispersion model, has been used to simulate the transport and diffusion of a perfluorocarbon tracer-gas cloud for one afternoon surface release during the July 1980 Great Plains mesoscale tracer field experiment. Ground-level concentration (GLC) measurements taken along arcs of samplers 100 and 600 km downwind of the release site at Norman, Oklahoma, up to three days after the tracer release were available for comparison. Quantitative measures of a number of significant dispersion characteristics obtained from analysis of the observed tracer cloud's moving GLC `footprint' have been used to evaluate the modeling system's skill in simulating this MAD case.MAD is more dependent upon the spatial and temporal structure of the transport wind field than is short-range atmospheric dispersion. For the Great Plains mesoscale tracer experiment, the observations suggest that the Great Plains nocturnal low-level jet played an important role in transporting and deforming the tracer cloud. A suite of ten two- and three-dimensional numerical meteorological experiments was devised to investigate the relative contributions of topography, other surface inhomogeneities, atmospheric baroclinicity, synoptic-scale flow evolution, and meteorological model initialization time to the structure and evolution of the low-level mesoscale flow field and thus to MAD. Results from the ten mesoscale meteorological simulations are compared in this part of the paper. The predicted wind fields display significant differences, which give rise in turn to significant differences in predicted low-level transport. The presence of an oscillatory ageostrophic component in the observed synoptic low-level winds for this case is shown to complicate initialization of the meteorological model considerably and is the likely cause of directional errors in the predicted mean tracer transport. A companion paper describes the results from the associated dispersion simulations.

NASA Cold Land Processes Experiment (CLPX 2002/03): Ground-based and near-surface meteorological observations

Treesearch

Kelly Elder; Don Cline; Angus Goodbody; Paul Houser; Glen E. Liston; Larry Mahrt; Nick Rutter

2009-01-01

A short-term meteorological database has been developed for the Cold Land Processes Experiment (CLPX). This database includes meteorological observations from stations designed and deployed exclusively for CLPXas well as observations available from other sources located in the small regional study area (SRSA) in north-central Colorado. The measured weather parameters...

Winter wheat yield estimation of remote sensing research based on WOFOST crop model and leaf area index assimilation

NASA Astrophysics Data System (ADS)

Chen, Yanling; Gong, Adu; Li, Jing; Wang, Jingmei

2017-04-01

Accurate crop growth monitoring and yield predictive information are significant to improve the sustainable development of agriculture and ensure the security of national food. Remote sensing observation and crop growth simulation models are two new technologies, which have highly potential applications in crop growth monitoring and yield forecasting in recent years. However, both of them have limitations in mechanism or regional application respectively. Remote sensing information can not reveal crop growth and development, inner mechanism of yield formation and the affection of environmental meteorological conditions. Crop growth simulation models have difficulties in obtaining data and parameterization from single-point to regional application. In order to make good use of the advantages of these two technologies, the coupling technique of remote sensing information and crop growth simulation models has been studied. Filtering and optimizing model parameters are key to yield estimation by remote sensing and crop model based on regional crop assimilation. Winter wheat of GaoCheng was selected as the experiment object in this paper. And then the essential data was collected, such as biochemical data and farmland environmental data and meteorological data about several critical growing periods. Meanwhile, the image of environmental mitigation small satellite HJ-CCD was obtained. In this paper, research work and major conclusions are as follows. (1) Seven vegetation indexes were selected to retrieve LAI, and then linear regression model was built up between each of these indexes and the measured LAI. The result shows that the accuracy of EVI model was the highest (R2=0.964 at anthesis stage and R2=0.920 at filling stage). Thus, EVI as the most optimal vegetation index to predict LAI in this paper. (2) EFAST method was adopted in this paper to conduct the sensitive analysis to the 26 initial parameters of the WOFOST model and then a sensitivity index was constructed to evaluate the influence of each parameter mentioned above on the winter wheat yield formation. Finally, six parameters that sensitivity index more than 0.1 as sensitivity factors were chose, which are TSUM1, SLATB1, SLATB2, SPAN, EFFTB3 and TMPF4. To other parameters, we confirmed them via practical measurement and calculation, available literature or WOFOST default. Eventually, we completed the regulation of WOFOST parameters. (3) Look-up table algorithm was used to realize single-point yield estimation through the assimilation of the WOFOST model and the retrieval LAI. This simulation achieved a high accuracy which perfectly meet the purpose of assimilation (R2=0.941 and RMSE=194.58kg/hm2). In this paper, the optimum value of sensitivity parameters were confirmed and the estimation of single-point yield were finished. Key words: yield estimation of winter wheat, LAI, WOFOST crop growth model, assimilation

PHOTOCHEMICAL AIR POLLUTION IN THE NORTH OF PORTUGAL: A HIGH TROPOSHERIC OZONE EPISODE

NASA Astrophysics Data System (ADS)

Monteiro, A.; Carvalho, A.; Tchepel, O.; Ferreira, J.; Martins, H.; Miranda, A.; Borrego, C.; Saavedra, S.; Rodríguez, A.; Souto, J. A.

2009-12-01

Very high concentrations of ozone are continuously measured at the monitoring station at Lamas d’Olo, located at the North of Portugal,. A particular high photochemical episode occurred between 11 and 13 of July 2005, registering ozone hourly maximum values above 350 µg.m-3. This ozone-rich episode is investigated in this paper, in order to identify its origin and formation. Besides the analysis of both meteorological and air quality monitoring datasets, a numerical modelling approach, based on MM5-CAMx system, was used to simulate the dispersion and transport (horizontal and vertical) of the photochemical pollutants and its precursors. A cross spectrum analysis of the meteorological and air quality time series was performed, in the frequency domain, to establish the relationships between ozone data measured at Lamas d’Olo with air quality data from neighbourhood stations and meteorological parameters. Results point out different behaviour/contribution between the analysed sites. Moreover, different contributions of the u and v wind component on the ozone concentration fluctuations were found suggesting the presence a mountain breeze circulation and a north synoptic transport. The preliminary modelling results pointed out that the vertical transport of pollutants are responsible for the measured high concentrations, combined with particular meteorological conditions, related to the planetary boundary layer (PBL) development. The pollutants transported and existent at high vertical levels are captured/trapped when the PBL height reaches its daily maximum, and extremely high ozone ground level concentrations are consequently measured.

Estimation of Secondary Compounds Concentrations Contributed by Biogenic VOC With Chemical Transport Model in the Central Area of Japan

NASA Astrophysics Data System (ADS)

Yamamoto, K.; Kanemaru, A.; Okumura, M.; Tohno, S.

2008-12-01

Biogenic VOC (BVOC) has comparably large contribution to generation of secondary air pollutants, such as photochemical oxidant or urban aerosol. In this study a BVOC emission inventory in the Kansai area, which is located in the central part of Japan, based on the field observation was developed. Some validations of the inventory were conducted by estimating the concentration distribution of oxidants with this developed and an existing BVOC emission inventory in Kansai area by meteorological model MM5 and atmospheric chemical transport model CMAQ. In the development of BVOC emission, the vegetation map by the Biodiversity Center of Japan which had been arranged as basic information on natural environmental preservation in a regional standard mesh (the third mesh) in 1999 was used. In this study isoprene and the mono-terpene were taken up as BVOC. Quercus crispula and Quercus serrata were selected as the source of isoprene, and Cryptomeria japonica, Chamaecyparis obtuse, Quercus phillyraeoides, Pinus densiflora, and Pinus thunbergii were selected as sources of mono-terpene. The parameter of the basic emission rate included in the model was decided by arranging the result of the observation in Kansai Research Center of Forestry and Forest Products Research Institute in each season. This emission flux from each species were calculated by G93 model by Guenther et al. and meteorological fields for the model, such as temperatures and sunlight intensities, were renewed hour by hour, therefore, this emission inventory has a high time resolution according to the season and time. In calculating meteorological fields, meteorological model MM5 Ver.3.7 was conducted in Japanese standard mesh in the selected five days of April, July, and October in 2004, and January 2005 respectively, and taking out the result of wind velocities and temperatures for substituting to the G93 model. Then atmospheric chemical transport model CMAQ Ver.4.6 with the emission inventories and meteorological fields was used for estimating secondary produced compounds concentration in the Kansai region. While the emission amount data of BVOC is also included in the EAGrid-Japan database, constructed by A. Kannari et al., another simulation with this existing BVOC emission inventory was conducted. As for other emission inventories of precursors, EAGrid-Japan was also used in both simulations. According to the result of estimation of BVOC emission, the total amount of BVOC is almost same as that of EAGrid-Japan, however, the ratio of isoprene to total BVOC emission is quite low in our estimation, due to the used vegetation map in this study, and the configuration of basic emission parameter in Autumn and Winter which is set to zero. According to the result of atmospheric chemical transport simulation with this developed BVOC inventory, oxidant concentrations are lower than observed values. This result suggests that the amount of isoprene emission strongly affected on the concentrations of oxidants, therefore, more accurate vegetation map data as a basis of BVOC emissions should be developed.

Quantification of the impact of hydrology on agricultural production as a result of too dry, too wet or too saline conditions

NASA Astrophysics Data System (ADS)

Hack-ten Broeke, Mirjam J. D.; Kroes, Joop G.; Bartholomeus, Ruud P.; van Dam, Jos C.; de Wit, Allard J. W.; Supit, Iwan; Walvoort, Dennis J. J.; van Bakel, P. Jan T.; Ruijtenberg, Rob

2016-08-01

For calculating the effects of hydrological measures on agricultural production in the Netherlands a new comprehensive and climate proof method is being developed: WaterVision Agriculture (in Dutch: Waterwijzer Landbouw). End users have asked for a method that considers current and future climate, that can quantify the differences between years and also the effects of extreme weather events. Furthermore they would like a method that considers current farm management and that can distinguish three different causes of crop yield reduction: drought, saline conditions or too wet conditions causing oxygen shortage in the root zone. WaterVision Agriculture is based on the hydrological simulation model SWAP and the crop growth model WOFOST. SWAP simulates water transport in the unsaturated zone using meteorological data, boundary conditions (like groundwater level or drainage) and soil parameters. WOFOST simulates crop growth as a function of meteorological conditions and crop parameters. Using the combination of these process-based models we have derived a meta-model, i.e. a set of easily applicable simplified relations for assessing crop growth as a function of soil type and groundwater level. These relations are based on multiple model runs for at least 72 soil units and the possible groundwater regimes in the Netherlands. So far, we parameterized the model for the crops silage maize and grassland. For the assessment, the soil characteristics (soil water retention and hydraulic conductivity) are very important input parameters for all soil layers of these 72 soil units. These 72 soil units cover all soils in the Netherlands. This paper describes (i) the setup and examples of application of the process-based model SWAP-WOFOST, (ii) the development of the simplified relations based on this model and (iii) how WaterVision Agriculture can be used by farmers, regional government, water boards and others to assess crop yield reduction as a function of groundwater characteristics or as a function of the salt concentration in the root zone for the various soil types.

A Regional-Scale Evaluation on Environmental Stability Conditions for Convective Rain under Climate Change from Super-High-Resolution GCM Simulations

NASA Astrophysics Data System (ADS)

Takemi, T.; Nomura, S.; Oku, Y.; Ishikawa, H.

2011-12-01

Understanding and forecasting of convective rain due to intense thunderstorms, which develop under conditions both with and without significant synoptic-scale and/or mesoscale forcings, are critical in dealing with disaster prevention/mitigation and developing urban planning appropriate for disaster management. Thunderstorms rapidly develop even during the daytimes of fair weather conditions without any external forcings, and sometimes become strong enough to induce local-scale meteorological disasters such as torrential rain, flush flooding, high winds, and tornadoes/gusts. With the growing interests in climate change, future changes in the behavior of such convectively generated extreme events have gained scientific and societal interests. This study conducted the regional-scale evaluations on the environmental stability conditions for convective rain that develops under synoptically undisturbed, summertime conditions by using the outputs of super-high-resolution AGCM simulations, at a 20-km resolution, for the present, the near-future, and the future climates under global warming with IPCC A1B emission scenario. The GCM, MRI-AGCM3.2S, was developed by Meteorological Research Institute of Japan Meteorological Agency under the KAKUSHIN program funded by the Ministry of Education, Culture, Sports, Science, and Technology of Japan. The climate simulation outputs that were used in this study corresponded to three 25-year periods: 1980-2004 for the present climate; 2020-2044 for the near-future climate; and 2075-2099 for the future climate. The Kanto Plain that includes the Tokyo metropolitan area was chosen as the study area, since the Tokyo metropolitan area is one of the largest metropolises in the world and is vulnerable to extreme weather events. Therefore, one of the purposes of this study was to examine how regional-scale evaluations are performed from the super-high-resolution GCM outputs. After verifying the usefulness of the GCM present-climate outputs with observations and operational mesoscale analyses, we examined, as another purpose of this study, the future changes in the environmental stability for convective rain. To diagnose the environmental conditions, some of the commonly used stability parameters and indices were examined. In the future climates, temperature lapse rate decreased in the lower troposphere, while water vapor mixing ratio increased throughout the deep troposphere. The changes in the temperature and moisture profiles resulted in the increase in both precipitable water vapor and convective available potential energy. These projected changes will be enhanced with the future period. Furthermore, the statistical analyses for the differences of the stability parameters between no-rain and rain days under the synoptically undisturbed condition in each simulated climate period indicated that the environmental conditions in terms of the stability parameters that distinguish no-rain and rain events are basically unchanged between the present and the future climates. This result suggests that the environmental characteristics favorable for afternoon rain events in the synoptically undisturbed environments will not change under global warming.

Development and evaluation of the Screening Trajectory Ozone Prediction System (STOPS, version 1.0)

NASA Astrophysics Data System (ADS)

Czader, B. H.; Percell, P.; Byun, D.; Choi, Y.

2014-11-01

A hybrid Lagrangian-Eulerian modeling tool has been developed using the Eulerian framework of the Community Multiscale Air Quality (CMAQ) model. It is a moving nest that utilizes saved original CMAQ simulation results to provide boundary conditions, initial conditions, as well as emissions and meteorological parameters necessary for a simulation. Given that these file are available, this tool can run independently from the CMAQ whole domain simulation and it is designed to simulate source - receptor relationship upon changes in emissions. In this tool, the original CMAQ's horizontal domain is reduced to a small sub-domain that follows a trajectory defined by the mean mixed-layer wind. It has the same vertical structure and physical and chemical interactions as CMAQ except advection calculation. The advantage of this tool compared to other Lagrangian models is its capability of utilizing realistic boundary conditions that change with space and time as well as detailed chemistry treatment. The correctness of the algorithms and the overall performance was evaluated against CMAQ simulation results. Its performance depends on the atmospheric conditions occurring during the simulation period with the comparisons being most similar to CMAQ results under uniform wind conditions. The mean bias varies between -0.03 and -0.78 and the slope is between 0.99 and 1.01 for different analyzed cases. For complicated meteorological condition, such as wind circulation, the simulated mixing ratios deviate from CMAQ values as a result of Lagrangian approach of using mean wind for its movement, but are still close, with the mean varying between 0.07 and -4.29 and slope varying between 0.95 and 1.063 for different analyzed cases. For historical reasons this hybrid Lagrangian - Eulerian tool is named the Screening Trajectory Ozone Prediction System (STOPS) but its use is not limited to ozone prediction as similarly to CMAQ it can simulate concentrations of many species, including particulate matter and some toxic compounds, such as formaldehyde and 1,3-butadiene.

Evaluation of meteorological and epidemiological characteristics of fatal pulmonary embolism

NASA Astrophysics Data System (ADS)

Törő, Klára; Pongrácz, Rita; Bartholy, Judit; Váradi-T, Aletta; Marcsa, Boglárka; Szilágyi, Brigitta; Lovas, Attila; Dunay, György; Sótonyi, Péter

2016-03-01

The objective of the present study was to identify risk factors among epidemiological factors and meteorological conditions in connection with fatal pulmonary embolism. Information was collected from forensic autopsy records in sudden unexpected death cases where pulmonary embolism was the exact cause of death between 2001 and 2010 in Budapest. Meteorological parameters were detected during the investigated period. Gender, age, manner of death, cause of death, place of death, post-mortem pathomorphological changes and daily meteorological conditions (i.e. daily mean temperature and atmospheric pressure) were examined. We detected that the number of registered pulmonary embolism (No 467, 211 male) follows power law in time regardless of the manner of death. We first described that the number of registered fatal pulmonary embolism up to the nth day can be expressed as Y( n) = α ṡ n β where Y denotes the number of fatal pulmonary embolisms up to the nth day and α > 0 and β > 1 are model parameters. We found that there is a definite link between the cold temperature and the increasing incidence of fatal pulmonary embolism. Cold temperature and the change of air pressure appear to be predisposing factors for fatal pulmonary embolism. Meteorological parameters should have provided additional information about the predisposing factors of thromboembolism.

GIS-Based Noise Simulation Open Source Software: N-GNOIS

NASA Astrophysics Data System (ADS)

Vijay, Ritesh; Sharma, A.; Kumar, M.; Shende, V.; Chakrabarti, T.; Gupta, Rajesh

2015-12-01

Geographical information system (GIS)-based noise simulation software (N-GNOIS) has been developed to simulate the noise scenario due to point and mobile sources considering the impact of geographical features and meteorological parameters. These have been addressed in the software through attenuation modules of atmosphere, vegetation and barrier. N-GNOIS is a user friendly, platform-independent and open geospatial consortia (OGC) compliant software. It has been developed using open source technology (QGIS) and open source language (Python). N-GNOIS has unique features like cumulative impact of point and mobile sources, building structure and honking due to traffic. Honking is the most common phenomenon in developing countries and is frequently observed on any type of roads. N-GNOIS also helps in designing physical barrier and vegetation cover to check the propagation of noise and acts as a decision making tool for planning and management of noise component in environmental impact assessment (EIA) studies.

Coupled carbon-nitrogen land surface modelling for UK agricultural landscapes using JULES and JULES-ECOSSE-FUN (JEF)

NASA Astrophysics Data System (ADS)

Comyn-Platt, Edward; Clark, Douglas; Blyth, Eleanor

2016-04-01

The UK is required to provide accurate estimates of the UK greenhouse gas (GHG; CO2, CH4 and N2O) emissions for the UNFCCC (United Nations Framework Convention on Climate Change). Process based land surface models (LSMs), such as the Joint UK Land Environment Simulator (JULES), attempt to provide such estimates based on environmental (e.g. land use and soil type) and meteorological conditions. The standard release of JULES focusses on the water and carbon cycles, however, it has long been suggested that a coupled carbon-nitrogen scheme could enhance simulations. This is of particular importance when estimating agricultural emission inventories where the carbon cycle is effectively managed via the human application of nitrogen based fertilizers. JULES-ECOSSE-FUN (JEF) links JULES with the Estimation of Carbon in Organic Soils - Sequestration and Emission (ECOSSE) model and the Fixation and Uptake of Nitrogen (FUN) model as a means of simulating C:N coupling. This work presents simulations from the standard release of JULES and the most recent incarnation of the JEF coupled system at the point and field scale. Various configurations of JULES and JEF were calibrated and fine-tuned based on comparisons with observations from three UK field campaigns (Crichton, Harwood Forest and Brattleby) specifically chosen to represent the managed vegetation types that cover the UK. The campaigns included flux tower and chamber measurements of CO2, CH4 and N2O amongst other meteorological parameters and records of land management such as application of fertilizer and harvest date at the agricultural sites. Based on the results of these comparisons, JULES and/or JEF will be used to provide simulations on the regional and national scales in order to provide improved estimates of the total UK emission inventory.

Air Modeling - Observational Meteorological Data

EPA Pesticide Factsheets

Observed meteorological data for use in air quality modeling consist of physical parameters that are measured directly by instrumentation, and include temperature, dew point, wind direction, wind speed, cloud cover, cloud layer(s), ceiling height,

Meteorological Drivers of Extreme Air Pollution Events

NASA Astrophysics Data System (ADS)

Horton, D. E.; Schnell, J.; Callahan, C. W.; Suo, Y.

2017-12-01

The accumulation of pollutants in the near-surface atmosphere has been shown to have deleterious consequences for public health, agricultural productivity, and economic vitality. Natural and anthropogenic emissions of ozone and particulate matter can accumulate to hazardous concentrations when atmospheric conditions are favorable, and can reach extreme levels when such conditions persist. Favorable atmospheric conditions for pollutant accumulation include optimal temperatures for photochemical reaction rates, circulation patterns conducive to pollutant advection, and a lack of ventilation, dispersion, and scavenging in the local environment. Given our changing climate system and the dual ingredients of poor air quality - pollutants and the atmospheric conditions favorable to their accumulation - it is important to characterize recent changes in favorable meteorological conditions, and quantify their potential contribution to recent extreme air pollution events. To facilitate our characterization, this study employs the recently updated Schnell et al (2015) 1°×1° gridded observed surface ozone and particulate matter datasets for the period of 1998 to 2015, in conjunction with reanalysis and climate model simulation data. We identify extreme air pollution episodes in the observational record and assess the meteorological factors of primary support at local and synoptic scales. We then assess (i) the contribution of observed meteorological trends (if extant) to the magnitude of the event, (ii) the return interval of the meteorological event in the observational record, simulated historical climate, and simulated pre-industrial climate, as well as (iii) the probability of the observed meteorological trend in historical and pre-industrial climates.

Cloud physics laboratory project science and applications working group

NASA Technical Reports Server (NTRS)

Hung, R. J.

1977-01-01

The conditions of the expansion chamber under zero gravity environment were simulated. The following three branches of fluid mechanics simulation under low gravity environment were accomplished: (1) oscillation of the water droplet which characterizes the nuclear oscillation in nuclear physics, bubble oscillation of two phase flow in chemical engineering, and water drop oscillation in meteorology; (2) rotation of the droplet which characterizes nuclear fission in nuclear physics, formation of binary stars and rotating stars in astrophysics, and breakup of the water droplet in meteorology; and (3) collision and coalescence of the water droplets which characterizes nuclear fusion in nuclear physics and processes of rain formation in meteorology.

Chemistry Simulations Using MERRA-2 Reanalysis with the GMI CTM and Replay in Support of the Atmospheric Composition Community

NASA Technical Reports Server (NTRS)

Oman, Luke D.; Strahan, Susan E.

2016-01-01

Simulations using reanalyzed meteorological conditions have been long used to understand causes of atmospheric composition change over the recent past. Using the new Modern-Era Retrospective analysis for Research and Applications, version 2 (MERRA-2) meteorology, chemistry simulations are being conducted to create products covering 1980-2016 for the atmospheric composition community. These simulations use the Global Modeling Initiative (GMI) chemical mechanism in two different models: the GMI Chemical Transport Model (CTM) and the GEOS-5 model developed Replay mode. Replay mode means an integration of the GEOS-5 general circulation model that is incrementally adjusted each time step toward the MERRA-2 analysis. The GMI CTM is a 1 x 1.25 simulation and the MERRA-2 GMI Replay simulation uses the native MERRA-2 approximately horizontal resolution on the cubed sphere. The Replay simulations is driven by the online use of key MERRA-2 meteorological variables (i.e. U, V, T, and surface pressure) with all other variables calculated in response to those variables. A specialized set of transport diagnostics is included in both runs to better understand trace gas transport and changes over the recent past.

Errors and improvements in the use of archived meteorological data for chemical transport modeling: an analysis using GEOS-Chem v11-01 driven by GEOS-5 meteorology

NASA Astrophysics Data System (ADS)

Yu, Karen; Keller, Christoph A.; Jacob, Daniel J.; Molod, Andrea M.; Eastham, Sebastian D.; Long, Michael S.

2018-01-01

Global simulations of atmospheric chemistry are commonly conducted with off-line chemical transport models (CTMs) driven by archived meteorological data from general circulation models (GCMs). The off-line approach has the advantages of simplicity and expediency, but it incurs errors due to temporal averaging in the meteorological archive and the inability to reproduce the GCM transport algorithms exactly. The CTM simulation is also often conducted at coarser grid resolution than the parent GCM. Here we investigate this cascade of CTM errors by using 222Rn-210Pb-7Be chemical tracer simulations off-line in the GEOS-Chem CTM at rectilinear 0.25° × 0.3125° (≈ 25 km) and 2° × 2.5° (≈ 200 km) resolutions and online in the parent GEOS-5 GCM at cubed-sphere c360 (≈ 25 km) and c48 (≈ 200 km) horizontal resolutions. The c360 GEOS-5 GCM meteorological archive, updated every 3 h and remapped to 0.25° × 0.3125°, is the standard operational product generated by the NASA Global Modeling and Assimilation Office (GMAO) and used as input by GEOS-Chem. We find that the GEOS-Chem 222Rn simulation at native 0.25° × 0.3125° resolution is affected by vertical transport errors of up to 20 % relative to the GEOS-5 c360 online simulation, in part due to loss of transient organized vertical motions in the GCM (resolved convection) that are temporally averaged out in the 3 h meteorological archive. There is also significant error caused by operational remapping of the meteorological archive from a cubed-sphere to a rectilinear grid. Decreasing the GEOS-Chem resolution from 0.25° × 0.3125° to 2° × 2.5° induces further weakening of vertical transport as transient vertical motions are averaged out spatially and temporally. The resulting 222Rn concentrations simulated by the coarse-resolution GEOS-Chem are overestimated by up to 40 % in surface air relative to the online c360 simulations and underestimated by up to 40 % in the upper troposphere, while the tropospheric lifetimes of 210Pb and 7Be against aerosol deposition are affected by 5-10 %. The lost vertical transport in the coarse-resolution GEOS-Chem simulation can be partly restored by recomputing the convective mass fluxes at the appropriate resolution to replace the archived convective mass fluxes and by correcting for bias in the spatial averaging of boundary layer mixing depths.

Sensitivity of modeled estuarine circulation to spatial and temporal resolution of input meteorological forcing of a cold frontal passage

NASA Astrophysics Data System (ADS)

Weaver, Robert J.; Taeb, Peyman; Lazarus, Steven; Splitt, Michael; Holman, Bryan P.; Colvin, Jeffrey

2016-12-01

In this study, a four member ensemble of meteorological forcing is generated using the Weather Research and Forecasting (WRF) model in order to simulate a frontal passage event that impacted the Indian River Lagoon (IRL) during March 2015. The WRF model is run to provide high and low, spatial (0.005° and 0.1°) and temporal (30 min and 6 h) input wind and pressure fields. The four member ensemble is used to force the Advanced Circulation model (ADCIRC) coupled with Simulating Waves Nearshore (SWAN) and compute the hydrodynamic and wave response. Results indicate that increasing the spatial resolution of the meteorological forcing has a greater impact on the results than increasing the temporal resolution in coastal systems like the IRL where the length scales are smaller than the resolution of the operational meteorological model being used to generate the forecast. Changes in predicted water elevations are due in part to the upwind and downwind behavior of the input wind forcing. The significant wave height is more sensitive to the meteorological forcing, exhibited by greater ensemble spread throughout the simulation. It is important that the land mask, seen by the meteorological model, is representative of the geography of the coastal estuary as resolved by the hydrodynamic model. As long as the temporal resolution of the wind field captures the bulk characteristics of the frontal passage, computational resources should be focused so as to ensure that the meteorological model resolves the spatial complexities, such as the land-water interface, that drive the land use responsible for dynamic downscaling of the winds.

Technology Needs Assessment of an Atmospheric Observation System for Multidisciplinary Air Quality/Meteorology Missions, Part 2

NASA Technical Reports Server (NTRS)

Alvarado, U. R.; Bortner, M. H.; Grenda, R. N.; Brehm, W. F.; Frippel, G. G.; Alyea, F.; Kraiman, H.; Folder, P.; Krowitz, L.

1982-01-01

The technology advancements that will be necessary to implement the atmospheric observation systems are considered. Upper and lower atmospheric air quality and meteorological parameters necessary to support the air quality investigations were included. The technology needs were found predominantly in areas related to sensors and measurements of air quality and meteorological measurements.

Gsflow-py: An integrated hydrologic model development tool

NASA Astrophysics Data System (ADS)

Gardner, M.; Niswonger, R. G.; Morton, C.; Henson, W.; Huntington, J. L.

2017-12-01

Integrated hydrologic modeling encompasses a vast number of processes and specifications, variable in time and space, and development of model datasets can be arduous. Model input construction techniques have not been formalized or made easily reproducible. Creating the input files for integrated hydrologic models (IHM) requires complex GIS processing of raster and vector datasets from various sources. Developing stream network topology that is consistent with the model resolution digital elevation model is important for robust simulation of surface water and groundwater exchanges. Distribution of meteorologic parameters over the model domain is difficult in complex terrain at the model resolution scale, but is necessary to drive realistic simulations. Historically, development of input data for IHM models has required extensive GIS and computer programming expertise which has restricted the use of IHMs to research groups with available financial, human, and technical resources. Here we present a series of Python scripts that provide a formalized technique for the parameterization and development of integrated hydrologic model inputs for GSFLOW. With some modifications, this process could be applied to any regular grid hydrologic model. This Python toolkit automates many of the necessary and laborious processes of parameterization, including stream network development and cascade routing, land coverages, and meteorological distribution over the model domain.

Refractivity variations and propagation at Ultra High Frequency

NASA Astrophysics Data System (ADS)

Alam, I.; Najam-Ul-Islam, M.; Mujahid, U.; Shah, S. A. A.; Ul Haq, Rizwan

Present framework is established to deal with the refractivity variations normally affected the radio waves propagation at different frequencies, ranges and different environments. To deal such kind of effects, many researchers proposed several methodologies. One method is to use the parameters from meteorology to investigate these effects of variations in refractivity on propagation. These variations are region specific and we have selected a region of one kilometer height over the English Channel. We have constructed different modified refractivity profiles based on the local meteorological data. We have recorded more than 48 million received signal strength from a communication links of 50 km operating at 2015 MHz in the Ultra High Frequency band giving path loss between transmitting and receiving stations of the experimental setup. We have used parabolic wave equation method to simulate an hourly value of signal strength and compared the obtained simulated loss to the experimental loss. The analysis is made to compute refractivity distribution of standard (STD) and ITU (International Telecommunication Union) refractivity profiles for various evaporation ducts. It is found that a standard refractivity profile is better than the ITU refractivity profiles for the region at 2015 MHz. Further, it is inferred from the analysis of results that 10 m evaporation duct height is the dominant among all evaporation duct heights considered in the research.

Research on the semi-distributed monthly rainfall runoff model at the Lancang River basin based on DEM

NASA Astrophysics Data System (ADS)

Liu, Gang; Zhao, Rong; Liu, Jiping; Zhang, Qingpu

2007-06-01

The Lancang River Basin is so narrow and its hydrological and meteorological information are so flexible. The Rainfall, evaporation, glacial melt water and groundwater affect the runoff whose replenishment forms changing notable with the season in different areas at the basin. Characters of different kind of distributed model and conceptual hydrological model are analyzed. A semi-distributed hydrological model of relation between monthly runoff and rainfall, temperate and soil type has been built in Changdu County based on Visual Basic and ArcObject. The way of discretization of distributed hydrological model was used in the model, and principles of conceptual model are taken into account. The sub-catchment of Changdu is divided into regular cells, and all kinds of hydrological and meteorological information and land use classes and slope extracted from 1:250000 digital elevation models are distributed in each cell. The model does not think of the rainfall-runoff hydro-physical process but use the conceptual model to simulate the whole contributes to the runoff of the area. The affection of evapotranspiration loss and underground water is taken into account at the same time. The spatial distribute characteristics of the monthly runoff in the area are simulated and analyzed with a few parameters.

Influence of local parameters on the dispersion of traffic-related pollutants within street canyons

NASA Astrophysics Data System (ADS)

Karra, Styliani; Malki-Epshtein, Liora; Martin Hyde Collaboration

2011-11-01

Ventilation within urban cities and street canyons and the associated air quality is a problem of increasing interest in the last decades. It is important for to minimise exposure of the population to traffic-related pollutants at street level. The residence time of pollutants within the street canyons depends on the meteorological conditions such as wind speed and direction, geometry layout and local parameters (position of traffic lane within the street). An experimental study was carried out to investigate the influence of traffic lane position on the dispersion of traffic-related pollutants within different street canyons geometries: symmetrical (equal building heights on both sides of the street), non-symmetrical (uniform building heights but lower on one side of the street) and heterogeneous (non-uniform building heights on both sides of the street) under constant meteorological conditions. Laboratory experiments were carried out within a water channel and simultaneous measurements of velocity field and concentration scalar levels within and above the street canyons using PIV and PLIF techniques. Traffic -related emissions were simulated using a line emission source. Two positions were examined for all street geometries: line emission source was placed in the centre of the street canyon; line emission source was placed off the centre of the street. TSI Incorporated.

Space Shuttle Pad Exposure Period Meteorological Parameters STS-1 Through STS-107

NASA Technical Reports Server (NTRS)

Overbey, B. G.; Roberts, B. C.

2005-01-01

During the 113 missions of the Space Transportation System (STS) to date, the Space Shuttle fleet has been exposed to the elements on the launch pad for approx. 4,195 days. The Natural Environments Branch at Marshall Space Flight Center archives atmospheric environments to which the Space Shuttle vehicles are exposed. This Technical Memorandum (TM) provides a summary of the historical record of the meteorological conditions encountered by the Space Shuttle fleet during the pad exposure period. Parameters included in this TM are temperature, relative humidity, wind speed, wind direction, sea level pressure, and precipitation. Extremes for each of these parameters for each mission are also summarized. Sources for the data include meteorological towers and hourly surface observations. Data are provided from the first launch of the STS in 1981 through the launch of STS-107 in 2003.

Spherical Harmonics Functions Modelling of Meteorological Parameters in PWV Estimation

NASA Astrophysics Data System (ADS)

Deniz, Ilke; Mekik, Cetin; Gurbuz, Gokhan

2016-08-01

Aim of this study is to derive temperature, pressure and humidity observations using spherical harmonics modelling and to interpolate for the derivation of precipitable water vapor (PWV) of TUSAGA-Active stations in the test area encompassing 38.0°-42.0° northern latitudes and 28.0°-34.0° eastern longitudes of Turkey. In conclusion, the meteorological parameters computed by using GNSS observations for the study area have been modelled with a precision of ±1.74 K in temperature, ±0.95 hPa in pressure and ±14.88 % in humidity. Considering studies on the interpolation of meteorological parameters, the precision of temperature and pressure models provide adequate solutions. This study funded by the Scientific and Technological Research Council of Turkey (TUBITAK) (The Estimation of Atmospheric Water Vapour with GPS Project, Project No: 112Y350).

Lagrangian transport simulations of volcanic sulfur dioxide emissions: impact of meteorological data products

NASA Astrophysics Data System (ADS)

Hoffmann, Lars; Rößler, Thomas; Griessbach, Sabine; Heng, Yi; Stein, Olaf

2017-04-01

Sulfur dioxide (SO2) emissions from strong volcanic eruptions are an important natural cause for climate variations. We applied our new Lagrangian transport model Massive-Parallel Trajectory Calculations (MPTRAC) to perform simulations for three case studies of volcanic eruption events. The case studies cover the eruptions of Grímsvötn, Iceland, Puyehue-Cordón Caulle, Chile, and Nabro, Eritrea, in May and June 2011. We used SO2 observations of the Atmospheric Infrared Sounder (AIRS/Aqua) and a backward trajectory approach to initialize the simulations. Besides validation of the new model, the main goal of our study was a comparison of simulations with different meteorological data products. We considered three reanalyses (ERA-Interim, MERRA, and NCAR/NCEP) and the European Centre for Medium-Range Weather Forecasts (ECMWF) operational analysis. Qualitatively, the SO2 distributions from the simulations compare well with the AIRS data, but also with Cloud-Aerosol Lidar with Orthogonal Polarization (CALIOP) and Michelson Interferometer for Passive Atmospheric Sounding (MIPAS) aerosol observations. Transport deviations and the critical success index (CSI) are analyzed to evaluate the simulations quantitatively. During the first 5 or 10 days after the eruptions we found the best performance for the ECMWF analysis (CSI range of 0.25 - 0.31), followed by ERA-Interim (0.25 - 0.29), MERRA (0.23 - 0.27), and NCAR/NCEP (0.21 - 0.23). High temporal and spatial resolution of the meteorological data does lead to improved performance of Lagrangian transport simulations of volcanic emissions in the upper troposphere and lower stratosphere. Reference: Hoffmann L., Rößler, T., Griessbach, S., Heng, Y., and Stein, O., Lagrangian transport simulations of volcanic sulfur dioxide emissions: impact of meteorological data products, J. Geophys. Res., 121(9), 4651-4673, doi:10.1002/2015JD023749, 2016.

Simulation and analysis of atmospheric transmission performance in airborne Terahertz communication

NASA Astrophysics Data System (ADS)

Pan, Chengsheng; Shi, Xin; Liu, Chengyang; Wang, Xue; Ding, Yuanming

2018-02-01

For the special meteorological condition of high altitude transmission; first the influence of atmospheric turbulence on the Terahertz wireless communication is analyzed, and the atmospheric constants model with increase in height is given. On this basis, the relationship between the flicker index and the high altitude horizon transmission distance of the Terahertz wave is analyzed by simulation. Then, through the analysis of high altitude path loss and noise, the high altitude wireless link model is built. Finally, the link loss budget is given according to the current Terahertz device parameters, and bit error rate (BER) performance of on-off keyed modulation (OOK) and pulse position modulation (PPM) in four Terahertz frequency bands is compared and analyzed. All these above provided theoretical reference for high-altitude Terahertz wireless communication transmission.

Comparative Evaluation of the Impact of WRF/NMM and WRF/ARW Meteorology on CMAQ Simulations for PM2.5 and its Related Precursors during the 2006 TexAQS/GoMACCS Study

EPA Science Inventory

This study presents a comparative evaluation of the impact of WRF-NMM and WRF-ARW meteorology on CMAQ simulations of PM_2.5, its composition and related precursors over the eastern United States with the intensive observations obtained by aircraft (NOAA WP-3), ship and ...

Evaluation of near surface ozone and particulate matter in air ...

EPA Pesticide Factsheets

In this study, techniques typically used for future air quality projections are applied to a historical 11-year period to assess the performance of the modeling system when the driving meteorological conditions are obtained using dynamical downscaling of coarse-scale fields without correcting toward higher-resolution observations. The Weather Research and Forecasting model and the Community Multiscale Air Quality model are used to simulate regional climate and air quality over the contiguous United States for 2000–2010. The air quality simulations for that historical period are then compared to observations from four national networks. Comparisons are drawn between defined performance metrics and other published modeling results for predicted ozone, fine particulate matter, and speciated fine particulate matter. The results indicate that the historical air quality simulations driven by dynamically downscaled meteorology are typically within defined modeling performance benchmarks and are consistent with results from other published modeling studies using finer-resolution meteorology. This indicates that the regional climate and air quality modeling framework utilized here does not introduce substantial bias, which provides confidence in the method’s use for future air quality projections. This paper shows that if emissions inputs and coarse-scale meteorological inputs are reasonably accurate, then air quality can be simulated with acceptable accuracy even wi

A COMPREHENSIVE EVALUATION OF THE ETA-CMAQ FORECAST MODEL PERFORMANCE FOR O3, ITS RELATED PRECURSORS, AND METEOROLOGICAL PARAMETERS DURING THE 2004 ICARTT STUDY

EPA Science Inventory

In this study, the ability of the Eta-CMAQ forecast model to represent the vertical profiles of O3, related chemical species (CO, NO, NO₂, H₂O₂, CH₂O, HNO₃, SO₂, PAN, isoprene, toluene), and meteorological paramete...

Investigating malaria risk in the northern region of Nigeria using satellite imagery

NASA Astrophysics Data System (ADS)

Emetere, M. E.; Nikouravan, Bijan; Olawole, O. F.

2015-08-01

The dynamics of infectious diseases are dependent on salient environment and climate factors which are directly proportional to its transmission. Malaria is a common disease of typical tropics of the West African sub-region. The influences of malaria transmission via meteorological and environmental parameters were examined. Remotely sensed parameters i.e. skin temperature, sensible heat flux, latent heat flux and total precipitation were obtained from the NASA-MERRA. The results show that the meteorological and environmental parameters of northern Nigeria favour the long malaria dominance.

The effect of changes in space shuttle parameters on the NASA/MSFC multilayer diffusion model predictions of surface HCl concentrations

NASA Technical Reports Server (NTRS)

Glasser, M. E.; Rundel, R. D.

1978-01-01

A method for formulating these changes into the model input parameters using a preprocessor program run on a programed data processor was implemented. The results indicate that any changes in the input parameters are small enough to be negligible in comparison to meteorological inputs and the limitations of the model and that such changes will not substantially increase the number of meteorological cases for which the model will predict surface hydrogen chloride concentrations exceeding public safety levels.

Monitoring, modeling and mitigating impacts of wind farms on local meteorology

NASA Astrophysics Data System (ADS)

Baidya Roy, Somnath; Traiteur, Justin; Kelley, Neil

2010-05-01

Wind power is one of the fastest growing sources of energy. Most of the growth is in the industrial sector comprising of large utility-scale wind farms. Recent modeling studies have suggested that such wind farms can significantly affect local and regional weather and climate. In this work, we present observational evidence of the impact of wind farms on near-surface air temperatures. Data from perhaps the only meteorological field campaign in an operational wind farm shows that downwind temperatures are lower during the daytime and higher at night compared to the upwind environment. Corresponding radiosonde profiles at the nearby Edwards Air Force Base WMO meteorological station show that the diurnal environment is unstable while the nocturnal environment is stable during the field campaign. This behavior is consistent with the hypothesis proposed by Baidya Roy et al. (JGR 2004) that states that turbulence generated in the wake of rotors enhance vertical mixing leading to a warming/cooling under positive/negative potential temperature lapse rates. We conducted a set of 306 simulations with the Regional Atmospheric Modeling System (RAMS) to test if regional climate models can capture the thermal effects of wind farms. We represented wind turbines with a subgrid parameterization that assumes rotors to be sinks of momentum and sources of turbulence. The simulated wind farms consistently generated a localized warming/cooling under positive/negative lapse rates as hypothesized. We found that these impacts are inversely correlated with background atmospheric boundary layer turbulence. Thus, if the background turbulence is high due to natural processes, the effects of additional turbulence generated by wind turbine rotors are likely to be small. We propose the following strategies to minimize impacts of wind farms: • Engineering solution: design rotors that generate less turbulence in their wakes. Sensitivity simulations show that these turbines also increase the productivity of wind farms and reduce damages to downwind rotors. • Siting solution: develop wind farms in regions where ABL turbulence is naturally high. Since, turbulence data is not widely recorded, we use surface KE dissipation rate as a proxy for ABL turbulence. Indeed, in our simulations, these 2 parameters are strongly positively correlated (P<0.99). Using the JRA25 dataset, comprising of 25-year long 6-hourly global meteorological data, we identify such regions in the world. These regions that include the Midwest and Great Plains as well as large parts of northern Europe and western China are appropriate sites for low-impact wind farms.

A statistical investigation into the relationship between meteorological parameters and suicide

NASA Astrophysics Data System (ADS)

Dixon, Keith W.; Shulman, Mark D.

1983-06-01

Many previous studies of relationships between weather and suicides have been inconclusive and contradictory. This study investigated the relationship between suicide frequency and meteorological conditions in people who are psychologically predisposed to commit suicide. Linear regressions of diurnal temperature change, departure of temperature from the climatic norm, mean daytime sky cover, and the number of hours of precipitation for each day were performed on daily suicide totals using standard computer methods. Statistical analyses of suicide data for days with and without frontal passages were also performed. Days with five or more suicides (clusterdays) were isolated, and their weather parameters compared with those of nonclusterdays. Results show that neither suicide totals nor clusterday occurrence can be predicted using these meteorological parameters, since statistically significant relationships were not found. Although the data hinted that frontal passages and large daily temperature changes may occur on days with above average suicide totals, it was concluded that the influence of the weather parameters used, on the suicide rate, is a minor one, if indeed one exists.

Evaluate dry deposition velocity of the nitrogen oxides using Noah-MP physics ensemble simulations for the Dinghushan Forest, Southern China

NASA Astrophysics Data System (ADS)

Zhang, Qi; Chang, Ming; Zhou, Shengzhen; Chen, Weihua; Wang, Xuemei; Liao, Wenhui; Dai, Jianing; Wu, ZhiYong

2017-11-01

There has been a rapid growth of reactive nitrogen (Nr) deposition over the world in the past decades. The Pearl River Delta region is one of the areas with high loading of nitrogen deposition. But there are still large uncertainties in the study of dry deposition because of its complex processes of physical chemistry and vegetation physiology. At present, the forest canopy parameterization scheme used in WRF-Chem model is a single-layer "big leaf" model, and the simulation of radiation transmission and energy balance in forest canopy is not detailed and accurate. Noah-MP land surface model (Noah-MP) is based on the Noah land surface model (Noah LSM) and has multiple parametric options to simulate the energy, momentum, and material interactions of the vegetation-soil-atmosphere system. Therefore, to investigate the improvement of the simulation results of WRF-Chem on the nitrogen deposition in forest area after coupled with Noah-MP model and to reduce the influence of meteorological simulation biases on the dry deposition velocity simulation, a dry deposition single-point model coupled by Noah- MP and the WRF-Chem dry deposition module (WDDM) was used to simulate the deposition velocity (Vd). The model was driven by the micro-meteorological observation of the Dinghushan Forest Ecosystem Location Station. And a series of numerical experiments were carried out to identify the key processes influencing the calculation of dry deposition velocity, and the effects of various surface physical and plant physiological processes on dry deposition were discussed. The model captured the observed Vd well, but still underestimated the Vd. The self-defect of Wesely scheme applied by WDDM, and the inaccuracy of built-in parameters in WDDM and input data for Noah-MP (e.g. LAI) were the key factors that cause the underestimation of Vd. Therefore, future work is needed to improve model mechanisms and parameterization.

Preliminary Evaluation of Air Quality Model Performance Utilizing Measurements at the University of Houston Moody Tower and others during the TexAQS-II

NASA Astrophysics Data System (ADS)

Byun, D. W.; Rappenglueck, B.; Lefer, B.

2007-12-01

Accurate meteorological and photochemical modeling efforts are necessary to understand the measurements made during the Texas Air Quality Study (TexAQS-II). The main objective of the study is to understand the meteorological and chemical processes of high ozone and regional haze events in the Eastern Texas, including the Houston-Galveston metropolitan area. Real-time and retrospective meteorological and photochemical model simulations were performed to study key physical and chemical processes in the Houston Galveston Area. In particular, the Vertical Mixing Experiment (VME) at the University of Houston campus was performed on selected days during the TexAQS-II. Results of the MM5 meteorological model and CMAQ air quality model simulations were compared with the VME and other TexAQS-II measurements to understand the interaction of the boundary layer dynamics and photochemical evolution affecting Houston air quality.

Long-term weather predictability: Ural case study

NASA Astrophysics Data System (ADS)

Kubyshen, Alexander; Shopin, Sergey

2016-04-01

The accuracy of the state-of-the-art long-term meteorological forecast (at the seasonal level) is still low. Here it is presented approach (RAMES method) realizing different forecasting methodology. It provides prediction horizon of up to 19-22 years under equal probabilities of determination of parameters in every analyzed period [1]. Basic statements of the method are the following. 1. Long-term forecast on the basis of numerical modeling of the global meteorological process is principally impossible. Extension of long-term prediction horizon could be obtained only by the revealing and using a periodicity of meteorological situations at one point of observation. 2. Conventional calendar is unsuitable for generalization of meteorological data and revealing of cyclicity of meteorological processes. RAMES method uses natural time intervals: one day, synodic month and one year. It was developed a set of special calendars using these natural periods and the Metonic cycle. 3. Long-term time series of meteorological data is not a uniform universal set, it is a sequence of 28 universal sets appropriately superseding each other in time. The specifics of the method are: 1. Usage of the original research toolkit consisting of - a set of calendars based on the Metonic cycle; - a set of charts (coordinate systems) for the construction of sequence diagrams (of daily variability of a meteorological parameter during the analyzed year; of daily variability of a meteorological parameter using long-term dynamical time series of periods-analogues; of monthly and yearly variability of accumulated value of meteorological parameter). 2. Identification and usage of new virtual meteorological objects having several degrees of generalization appropriately located in the used coordinate systems. 3. All calculations are integrated into the single technological scheme providing comparison and mutual verification of calculation results. During the prolonged testing in the Ural region, it was proved the efficiency of the method for forecasting the following meteorological parameters: ­- air temperature (minimum, maximum, daily mean, diurnal variation, last spring and first autumn freeze); - periods of winds with speeds of >5m/s and the maximal expected wind speed; - precipitation periods and amount of precipitations; -­ relative humidity; - atmospheric pressure. Atmospheric events (thunderstorms, fog) and hydrometeors also occupy the appropriate positions at the sequence diagrams that provides a possibility of long-term forecasting also for these events. Accuracy of forecasts was tested in 2006-2009 years. The difference between the forecasted monthly mean temperature and actual values was <0.5°C in 40.9% of cases, between 0.5°C and 1°C in 18.2% of cases, between 1°C and 1.5°C in 18.2% of cases, <2°C in 86% of cases. The RAMES method provides the toolkit to successfully forecast the weather conditions in advance of several years. 1. A.F. Kubyshen, "RAMES method: revealing the periodicity of meteorological processes and it usage for long-term forecast [Metodika «RAMES»: vyjavlenie periodichnosti meteorologicheskih processov i ee ispol'zovanie dlja dolgosrochnogo prognozirovanija]", in A.E. Fedorov (ed.), Sistema «Planeta Zemlja»: 200 let so dnja rozhdenija Izmaila Ivanovicha Sreznevskogo. 100 let so dnja izdanija ego slovarja drevnerusskogo jazyka. LENAND. Moscow. pp. 305-311. (In Russian)

Lessons from a low-order coupled chemistry meteorology model and applications to a high-dimensional chemical transport model

NASA Astrophysics Data System (ADS)

Haussaire, Jean-Matthieu; Bocquet, Marc

2016-04-01

Atmospheric chemistry models are becoming increasingly complex, with multiphasic chemistry, size-resolved particulate matter, and possibly coupled to numerical weather prediction models. In the meantime, data assimilation methods have also become more sophisticated. Hence, it will become increasingly difficult to disentangle the merits of data assimilation schemes, of models, and of their numerical implementation in a successful high-dimensional data assimilation study. That is why we believe that the increasing variety of problems encountered in the field of atmospheric chemistry data assimilation puts forward the need for simple low-order models, albeit complex enough to capture the relevant dynamics, physics and chemistry that could impact the performance of data assimilation schemes. Following this analysis, we developped a low-order coupled chemistry meteorology model named L95-GRS [1]. The advective wind is simulated by the Lorenz-95 model, while the chemistry is made of 6 reactive species and simulates ozone concentrations. With this model, we carried out data assimilation experiments to estimate the state of the system as well as the forcing parameter of the wind and the emissions of chemical compounds. This model proved to be a powerful playground giving insights on the hardships of online and offline estimation of atmospheric pollution. Building on the results on this low-order model, we test advanced data assimilation methods on a state-of-the-art chemical transport model to check if the conclusions obtained with our low-order model still stand. References [1] Haussaire, J.-M. and Bocquet, M.: A low-order coupled chemistry meteorology model for testing online and offline data assimilation schemes, Geosci. Model Dev. Discuss., 8, 7347-7394, doi:10.5194/gmdd-8-7347-2015, 2015.

Vertical wind velocity measurements using a five-hole probe with remotely piloted aircraft to study aerosol-cloud interactions

NASA Astrophysics Data System (ADS)

Calmer, Radiance; Roberts, Gregory C.; Preissler, Jana; Sanchez, Kevin J.; Derrien, Solène; O'Dowd, Colin

2018-05-01

The importance of vertical wind velocities (in particular positive vertical wind velocities or updrafts) in atmospheric science has motivated the need to deploy multi-hole probes developed for manned aircraft in small remotely piloted aircraft (RPA). In atmospheric research, lightweight RPAs ( < 2.5 kg) are now able to accurately measure atmospheric wind vectors, even in a cloud, which provides essential observing tools for understanding aerosol-cloud interactions. The European project BACCHUS (impact of Biogenic versus Anthropogenic emissions on Clouds and Climate: towards a Holistic UnderStanding) focuses on these specific interactions. In particular, vertical wind velocity at cloud base is a key parameter for studying aerosol-cloud interactions. To measure the three components of wind, a RPA is equipped with a five-hole probe, pressure sensors, and an inertial navigation system (INS). The five-hole probe is calibrated on a multi-axis platform, and the probe-INS system is validated in a wind tunnel. Once mounted on a RPA, power spectral density (PSD) functions and turbulent kinetic energy (TKE) derived from the five-hole probe are compared with sonic anemometers on a meteorological mast. During a BACCHUS field campaign at Mace Head Atmospheric Research Station (Ireland), a fleet of RPAs was deployed to profile the atmosphere and complement ground-based and satellite observations of physical and chemical properties of aerosols, clouds, and meteorological state parameters. The five-hole probe was flown on straight-and-level legs to measure vertical wind velocities within clouds. The vertical velocity measurements from the RPA are validated with vertical velocities derived from a ground-based cloud radar by showing that both measurements yield model-simulated cloud droplet number concentrations within 10 %. The updraft velocity distributions illustrate distinct relationships between vertical cloud fields in different meteorological conditions.

Spatial and temporal variability of reference evapotranspiration and influenced meteorological factors in the Jialing River Basin, China

NASA Astrophysics Data System (ADS)

Herath, Imali Kaushalya; Ye, Xuchun; Wang, Jianli; Bouraima, Abdel-Kabirou

2018-02-01

Reference evapotranspiration (ETr) is one of the important parameters in the hydrological cycle. The spatio-temporal variation of ETr and other meteorological parameters that influence ETr were investigated in the Jialing River Basin (JRB), China. The ETr was estimated using the CROPWAT 8.0 computer model based on the Penman-Montieth equation for the period 1964-2014. Mean temperature (MT), relative humidity (RH), sunshine duration (SD), and wind speed (WS) were the main input parameters of CROPWAT while 12 meteorological stations were evaluated. Linear regression and Mann-Kendall methods were applied to study the spatio-temporal trends while the inverse distance weighted (IDW) method was used to identify the spatial distribution of ETr. Stepwise regression and partial correlation methods were used to identify the meteorological variables that most significantly influenced the changes in ETr. The highest annual ETr was found in the northern part of the basin, whereas the lowest rate was recorded in the western part. In the autumn, the highest ETr was recorded in the southeast part of JRB. The annual ETr reflected neither significant increasing nor decreasing trends. Except for the summer, ETr is slightly increasing in other seasons. The MT significantly increased whereas SD and RH were significantly decreased during the 50-year period. Partial correlation and stepwise regression methods found that the impact of meteorological parameters on ETr varies on an annual and seasonal basis while SD, MT, and RH contributed to the changes of annual and seasonal ETr in the JRB.

Describing the direct and indirect radiative effects of atmospheric aerosols over Europe by using coupled meteorology-chemistry simulations: a contribution from the AQMEII-Phase II exercise

NASA Astrophysics Data System (ADS)

Jimenez-Guerrero, Pedro; Balzarini, Alessandra; Baró, Rocío; Curci, Gabriele; Forkel, Renate; Hirtl, Marcus; Honzak, Luka; Langer, Matthias; Pérez, Juan L.; Pirovano, Guido; San José, Roberto; Tuccella, Paolo; Werhahn, Johannes; Zabkar, Rahela

2014-05-01

The study of the response of the aerosol levels in the atmosphere to a changing climate and how this affects the radiative budget of the Earth (direct, semi-direct and indirect effects) is an essential topic to build confidence on climate science, since these feedbacks involve the largest uncertainties nowadays. Air quality-climate interactions (AQCI) are, therefore, a key, but uncertain contributor to the anthropogenic forcing that remains poorly understood. To build confidence in the AQCI studies, regional-scale integrated meteorology-atmospheric chemistry models (i.e., models with on-line chemistry) that include detailed treatment of aerosol life cycle and aerosol impacts on radiation (direct effects) and clouds (indirect effects) are in demand. In this context, the main objective of this contribution is the study and definition of the uncertainties in the climate-chemistry-aerosol-cloud-radiation system associated to the direct radiative forcing and the indirect effect caused by aerosols over Europe, using an ensemble of fully-coupled meteorology-chemistry model simulations with the WRF-Chem model run under the umbrella of AQMEII-Phase 2 international initiative. Simulations were performed for Europe for the entire year 2010. According to the common simulation strategy, the year was simulated as a sequence of 2-day time slices. For better comparability, the seven groups applied the same grid spacing of 23 km and shared common processing of initial and boundary conditions as well as anthropogenic and fire emissions. With exception of a simulation with different cloud microphysics, identical physics options were chosen while the chemistry options were varied. Two model set-ups will be considered here: one sub-ensemble of simulations not taking into account any aerosol feedbacks (the baseline case) and another sub-ensemble of simulations which differs from the former by the inclusion of aerosol-radiation feedback. The existing differences for meteorological variables (mainly 2-m temperature and precipitation) and air quality levels (mainly ozone an PM10) between both sub-ensembles of WRF-Chem simulations have been characterized. In the case of ozone and PM10, an increase in solar radiation and temperature has generally resulted in an enhanced photochemical activity and therefore a negative feedback (areas with low aerosol concentrations present more than 50 W m-2 higher global radiation for cloudy conditions). However, simulated feedback effects between aerosol concentrations and meteorological variables and on pollutant distributions strongly depend on the model configuration and the meteorological situation. These results will help providing improved science-based foundations to better assess the impacts of climate variability, support the development of effective climate change policies and optimize private decision-making.

Sensitivity of the interannual variability of mineral aerosol simulations to meteorological forcing dataset

DOE PAGES

Smith, Molly B.; Mahowald, Natalie M.; Albani, Samuel; ...

2017-03-07

Interannual variability in desert dust is widely observed and simulated, yet the sensitivity of these desert dust simulations to a particular meteorological dataset, as well as a particular model construction, is not well known. Here we use version 4 of the Community Atmospheric Model (CAM4) with the Community Earth System Model (CESM) to simulate dust forced by three different reanalysis meteorological datasets for the period 1990–2005. We then contrast the results of these simulations with dust simulated using online winds dynamically generated from sea surface temperatures, as well as with simulations conducted using other modeling frameworks but the same meteorological forcings, in order tomore » determine the sensitivity of climate model output to the specific reanalysis dataset used. For the seven cases considered in our study, the different model configurations are able to simulate the annual mean of the global dust cycle, seasonality and interannual variability approximately equally well (or poorly) at the limited observational sites available. Altogether, aerosol dust-source strength has remained fairly constant during the time period from 1990 to 2005, although there is strong seasonal and some interannual variability simulated in the models and seen in the observations over this time period. Model interannual variability comparisons to observations, as well as comparisons between models, suggest that interannual variability in dust is still difficult to simulate accurately, with averaged correlation coefficients of 0.1 to 0.6. Because of the large variability, at least 1 year of observations at most sites are needed to correctly observe the mean, but in some regions, particularly the remote oceans of the Southern Hemisphere, where interannual variability may be larger than in the Northern Hemisphere, 2–3 years of data are likely to be needed.« less

Surface meteorology and Solar Energy

NASA Technical Reports Server (NTRS)

Stackhouse, Paul W. (Principal Investigator)

The Release 5.1 Surface meteorology and Solar Energy (SSE) data contains parameters formulated for assessing and designing renewable energy systems. Parameters fall under 11 categories including: Solar cooking, solar thermal applications, solar geometry, tilted solar panels, energy storage systems, surplus product storage systems, cloud information, temperature, wind, other meteorological factors, and supporting information. This latest release contains new parameters based on recommendations by the renewable energy industry and it is more accurate than previous releases. On-line plotting capabilities allow quick evaluation of potential renewable energy projects for any region of the world. The SSE data set is formulated from NASA satellite- and reanalysis-derived insolation and meteorological data for the 10-year period July 1983 through June 1993. Results are provided for 1 degree latitude by 1 degree longitude grid cells over the globe. Average daily and monthly measurements for 1195 World Radiation Data Centre ground sites are also available. [Mission Objectives] The SSE project contains insolation and meteorology data intended to aid in the development of renewable energy systems. Collaboration between SSE and technology industries such as the Hybrid Optimization Model for Electric Renewables ( HOMER ) may aid in designing electric power systems that employ some combination of wind turbines, photovoltaic panels, or diesel generators to produce electricity. [Temporal_Coverage: Start_Date=1983-07-01; Stop_Date=1993-06-30] [Spatial_Coverage: Southernmost_Latitude=-90; Northernmost_Latitude=90; Westernmost_Longitude=-180; Easternmost_Longitude=180].

A protocol for a systematic literature review: comparing the impact of seasonal and meteorological parameters on acute respiratory infections in Indigenous and non-Indigenous peoples.

PubMed

Bishop-Williams, Katherine E; Sargeant, Jan M; Berrang-Ford, Lea; Edge, Victoria L; Cunsolo, Ashlee; Harper, Sherilee L

2017-01-26

Acute respiratory infections (ARI) are a leading cause of morbidity and mortality globally, and are often linked to seasonal and/or meteorological conditions. Globally, Indigenous peoples may experience a different burden of ARI compared to non-Indigenous peoples. This protocol outlines our process for conducting a systematic review to investigate whether associations between ARI and seasonal or meteorological parameters differ between Indigenous and non-Indigenous groups residing in the same geographical region. A search string will be used to search PubMed ® , CAB Abstracts/CAB Direct © , and Science Citation Index ® aggregator databases. Articles will be screened using inclusion/exclusion criteria applied first at the title and abstract level, and then at the full article level by two independent reviewers. Articles maintained after full article screening will undergo risk of bias assessment and data will be extracted. Heterogeneity tests, meta-analysis, and forest and funnel plots will be used to synthesize the results of eligible studies. This protocol paper describes our systematic review methods to identify and analyze relevant ARI, season, and meteorological literature with robust reporting. The results are intended to improve our understanding of potential associations between seasonal and meteorological parameters and ARI and, if identified, whether this association varies by place, population, or other characteristics. The protocol is registered in the PROSPERO database (#38051).

Superduck Marine Meteorological Experiment Data Summary: Mean Values and Turbulence Parameters.

DTIC Science & Technology

1988-08-01

number) This report summarizes the Mean values and turbulence parameters Of Meteorological measurements made during an experiment at Duck, NC, during...Sept-Oct 1986. The measure- ments wore made to Calculate wind stress in the nearshore area. Wind stress is a primary forcing function for nearshore waves...measure. Only in recent years has technology made it possible to accurately measure its fluctuations. The krypton hygrometer is a recent development

Pollen Concentration in the Atmosphere of Abha City, Saudi Arabia and its Relationship with Meteorological Parameters

NASA Astrophysics Data System (ADS)

Alwadie, Hussein M.

A qualitative and quantitative evaluation of pollen concentration in the atmosphere of Abha city, Saudi Arabia with the relation to meteorological parameters is presented. Investigations were undertaken from January to December 2006 using a Burkard 7 day volumetric spore trap. A total of 6,492 pollen grains m-3 belonging to 50 pollen taxa was detected. Poaceae represented 55.1% of total pollen, Leguminosae (11.7%), Compositae (6.1%), Solanaceae (4.6%) and Cupressaceae (4.2%). Pollen grains were found throughout the year. July represented the highest peak of pollen number and also the highest pollen taxa. The monthly variation of pollen taxa and their relationship to meteorological parameters were investigated. It was found that the pollen concentration is positively correlated with temperature and negatively correlated with rainfall, relative humidity and wind velocity. May-September represented the months of highest pollen number (95% of total pollen).

BOREAS AES MARSII Surface Meteorological Data

NASA Technical Reports Server (NTRS)

Atkinson, G. Barrie; Funk, Barry; Hall, Forrest G. (Editor); Knapp, David E. (Editor)

2000-01-01

Canadian AES personnel collected several data sets related to surface and atmospheric meteorological conditions over the BOREAS region. This data set contains 15-minute meteorological data from six MARSII meteorology stations in the BOREAS region in Canada. Parameters include site, time, temperature, dewpoint, visibility, wind speed, wind gust, wind direction, two cloud groups, precipitation, and station pressure. Temporally, the data cover the period of May to September 1994. Geo-graphically, the stations are spread across the provinces of Saskatchewan and Manitoba. The data are provided in tabular ASCII files, and are classified as AFM-Staff data.

Exploring the relationship between meteorology and surface PM2.5 in Northern India

NASA Astrophysics Data System (ADS)

Schnell, J.; Naik, V.; Horowitz, L. W.; Paulot, F.; Ginoux, P. A.

2017-12-01

Northern India is one of the most polluted and densely populated regions in world. Accurately modeling pollution in the region is difficult due to the extreme conditions with respect to emissions, meteorology, and topography, but it is paramount in order to understand how future changes in emissions and climate may alter the region's pollution regime. We evaluate a developmental version of the new-generation NOAA GFDL Atmospheric Model, version 4 (AM4) in its ability to simulate observed wintertime PM2.5 and its relationship to meteorology over the Northern India (23°N-31°N, 68°E-90°E). We perform two simulations of the GFDL-AM4 nudged to observed meteorology for the period (1980-2016) with two emission inventories developed for CMIP5 and CMIP6 and compare results with observations from India's Central Pollution Control Board (CPCB) for the period 1 October 2015 - 31 March 2016. Overall, our results indicate that the simulation with CMIP6 emissions has substantially reduced the low model bias in the region. The AM4, albeit biased low, generally simulates the magnitude and daily variability in observed total PM2.5. Ammonium nitrate and ammonium sulfate are the primary components of PM2.5 in the model, and although not directly observed, correlations of total observed PM2.5 and meteorology with the modeled individual PM2.5 components suggest the same for the observations. The model correctly reproduces the shape and magnitude of the seasonal cycle of PM2.5; but for the diurnal cycle, it misses the early evening rise and secondary maximum found in the observations. Observed PM2.5 abundances within the densely populated Indo-Gangetic Plain are by far the highest and are closely related to boundary layer meteorology, specifically relative humidity, wind speed, boundary layer height, and inversion strength. The GFDL-AM4 reproduces the observed pollution gradient over Northern India as well as the strength of the meteorology-PM2.5 relationship in most locations.

Effect of climate variability and change on winter haze over eastern China in recent decades

NASA Astrophysics Data System (ADS)

Liao, Hong; Yang, Yang

2017-04-01

In recent years, eastern China has frequently experienced persistent and severe winter haze pollution episodes with high aerosol concentrations, which have affected half of the 1.3 billion people in China. In this work, the increases in wintertime aerosol concentrations and severe haze events in eastern China over 1985-2015 were quantified by using observed atmospheric visibility from the National Climatic Data Center Global Summary of Day database, observed PM2.5 concentrations from the network of China National Environmental Monitoring Centre (CNEMC), and simulated PM2.5 concentrations from the Goddard Earth-Observing System (GEOS) chemical transport model (GEOS-Chem). Observed winter haze days (defined as days with atmospheric visibility less than 10 km and relative humidity less than 80%) averaged over eastern China (105-122.5°E, 20-45°N) increased from 21 days in 1980 to 42 days in 2014. Observed severe haze days (defined as days with PM2.5 >150 μg m-3) occurred mainly over Northern China. Considering variations in both anthropogenic emissions and meteorological parameters, the GEOS-Chem model simulated an increasing trend in wintertime surface-layer PM2.5 concentrations of 10.5 (±6.2) μg m-3 decade-1 over eastern China in the past decades. Sensitivity studies showed that changes in anthropogenic emissions and in climate contributed 87% and 17% to this increasing trend, respectively. Wintertime severe haze events over eastern China showed large interannual variations, driven by climate variability. Process analyses were performed to identify the key meteorological parameters that determined the interannual variations of wintertime severe haze events.

In-flight calibration/validation of the ENVISAT/MWR

NASA Astrophysics Data System (ADS)

Tran, N.; Obligis, E.; Eymard, L.

2003-04-01

Retrieval algorithms for wet tropospheric correction, integrated vapor and liquid water contents, atmospheric attenuations of backscattering coefficients in Ku and S band, have been developed using a database of geophysical parameters from global analyses from a meteorological model and corresponding simulated brightness temperatures and backscattering cross-sections by a radiative transfer model. Meteorological data correspond to 12 hours predictions from the European Center for Medium range Weather Forecasts (ECMWF) model. Relationships between satellite measurements and geophysical parameters are determined using a statistical method. The quality of the retrieval algorithms depends therefore on the representativity of the database, the accuracy of the radiative transfer model used for the simulations and finally on the quality of the inversion model. The database has been built using the latest version of the ECMWF forecast model, which has been operationally run since November 2000. The 60 levels in the model allow a complete description of the troposphere/stratosphere profiles and the horizontal resolution is now half of a degree. The radiative transfer model is the emissivity model developed at the Université Catholique de Louvain [Lemaire, 1998], coupled to an atmospheric model [Liebe et al, 1993] for gaseous absorption. For the inversion, we have replaced the classical log-linear regression with a neural networks inversion. For Envisat, the backscattering coefficient in Ku band is used in the different algorithms to take into account the surface roughness as it is done with the 18 GHz channel for the TOPEX algorithms or an additional term in wind speed for ERS2 algorithms. The in-flight calibration/validation of the Envisat radiometer has been performed with the tuning of 3 internal parameters (the transmission coefficient of the reflector, the sky horn feed transmission coefficient and the main antenna transmission coefficient). First an adjustment of the ERS2 brightness temperatures to the simulations for the 2000/2001 version of the ECMWF model has been applied. Then, Envisat brightness temperatures have been calibrated on these adjusted ERS2 values. The advantages of this calibration approach are that : i) such a method provides the relative discrepancy with respect to the simulation chain. The results, obtained simultaneously for several radiometers (we repeat the same analyze with TOPEX and JASON radiometers), can be used to detect significant calibration problems, more than 2 3 K). ii) the retrieval algorithms have been developed using the same meteorological model (2000/2001 version of the ECMWF model), and the same radiative transfer model than the calibration process, insuring the consistency between calibration and retrieval processing. Retrieval parameters are then optimized. iii) the calibration of the Envisat brightness temperatures over the 2000/2001 version of the ECMWF model, as well as the recommendation to use the same model as a reference to correct ERS2 brightness temperatures, allow the use of the same retrieval algorithms for the two missions, providing the continuity between the two. iv) by comparison with other calibration methods (such as systematic calibration of an instrument or products by using respectively the ones from previous mission), this method is more satisfactory since improvements in terms of technology, modelisation, retrieval processing are taken into account. For the validation of the brightness temperatures, we use either a direct comparison with measurements provided by other instruments in similar channel, or the monitoring over stable areas (coldest ocean points, stable continental areas). The validation of the wet tropospheric correction can be also provided by comparison with other radiometer products, but the only real validation rely on the comparison between in-situ measurements (performed by radiosonding) and retrieved products in coincidence.

The Invigoration of Deep Convective Clouds Over the Atlantic: Aerosol Effect, Meteorology or Retrieval Artifact?

NASA Technical Reports Server (NTRS)

Koren, Ilan; Feingold, Graham; Remer, Lorraine A.

2010-01-01

Associations between cloud properties and aerosol loading are frequently observed in products derived from satellite measurements. These observed trends between clouds and aerosol optical depth suggest aerosol modification of cloud dynamics, yet there are uncertainties involved in satellite retrievals that have the potential to lead to incorrect conclusions. Two of the most challenging problems are addressed here: the potential for retrieved aerosol optical depth to be cloud-contaminated, and as a result, artificially correlated with cloud parameters; and the potential for correlations between aerosol and cloud parameters to be erroneously considered to be causal. Here these issues are tackled directly by studying the effects of the aerosol on convective clouds in the tropical Atlantic Ocean using satellite remote sensing, a chemical transport model, and a reanalysis of meteorological fields. Results show that there is a robust positive correlation between cloud fraction or cloud top height and the aerosol optical depth, regardless of whether a stringent filtering of aerosol measurements in the vicinity of clouds is applied, or not. These same positive correlations emerge when replacing the observed aerosol field with that derived from a chemical transport model. Model-reanalysis data is used to address the causality question by providing meteorological context for the satellite observations. A correlation exercise between the full suite of meteorological fields derived from model reanalysis and satellite-derived cloud fields shows that observed cloud top height and cloud fraction correlate best with model pressure updraft velocity and relative humidity. Observed aerosol optical depth does correlate with meteorological parameters but usually different parameters from those that correlate with observed cloud fields. The result is a near-orthogonal influence of aerosol and meteorological fields on cloud top height and cloud fraction. The results strengthen the case that the aerosol does play a role in invigorating convective clouds.

Different meteorological parameters influence metapneumovirus and respiratory syncytial virus activity.

PubMed

Darniot, Magali; Pitoiset, Cécile; Millière, Laurine; Aho-Glélé, Ludwig Serge; Florentin, Emmanuel; Bour, Jean-Baptiste; Manoha, Catherine

2018-05-05

Both human metapneumovirus (hMPV) and respiratory syncytial virus (RSV) cause epidemics during the cold season in temperate climates. The purpose of this study was to find out whether climatic factors are associated with RSV and hMPV epidemics. Our study was based on data from 4300 patients admitted to the Dijon University Hospital for acute respiratory infection (ARI) over three winter seasons chosen for their dissimilar meteorological and virological patterns. Cases of hMPV and RSV were correlated with meteorological parameters recorded in the Dijon area. The relationship between virus data and local meteorological conditions was analyzed by univariate and multivariate negative binomial regression analysis. RSV detection was inversely associated with temperature and positively with relative humidity and air pressure, whereas hMPV was inversely associated with temperature and positively with wind speed. The association among meteorological variables and weekly ARIs cases due to RSV and hMPV demonstrated the relevance of climate factors as contributors to both hMPV and RSV activities. Meteorological drivers of RSV and hMPV epidemics are different. Low temperatures influence both hMPV and RSV activity. Relative humidity is an important predictor of RSV activity, but it does not influence hMPV activity. Copyright © 2018 Elsevier B.V. All rights reserved.

THE ATMOSPHERIC MODEL EVALUATION (AMET): METEOROLOGY MODULE

EPA Science Inventory

An Atmospheric Model Evaluation Tool (AMET), composed of meteorological and air quality components, is being developed to examine the error and uncertainty in the model simulations. AMET matches observations with the corresponding model-estimated values in space and time, and the...

Meteorological Controls on Local and Regional Volcanic Ash Dispersal.

PubMed

Poulidis, Alexandros P; Phillips, Jeremy C; Renfrew, Ian A; Barclay, Jenni; Hogg, Andrew; Jenkins, Susanna F; Robertson, Richard; Pyle, David M

2018-05-02

Volcanic ash has the capacity to impact human health, livestock, crops and infrastructure, including international air traffic. For recent major eruptions, information on the volcanic ash plume has been combined with relatively coarse-resolution meteorological model output to provide simulations of regional ash dispersal, with reasonable success on the scale of hundreds of kilometres. However, to predict and mitigate these impacts locally, significant improvements in modelling capability are required. Here, we present results from a dynamic meteorological-ash-dispersion model configured with sufficient resolution to represent local topographic and convectively-forced flows. We focus on an archetypal volcanic setting, Soufrière, St Vincent, and use the exceptional historical records of the 1902 and 1979 eruptions to challenge our simulations. We find that the evolution and characteristics of ash deposition on St Vincent and nearby islands can be accurately simulated when the wind shear associated with the trade wind inversion and topographically-forced flows are represented. The wind shear plays a primary role and topographic flows a secondary role on ash distribution on local to regional scales. We propose a new explanation for the downwind ash deposition maxima, commonly observed in volcanic eruptions, as resulting from the detailed forcing of mesoscale meteorology on the ash plume.

Coupling the WRF model with a temperature index model based on remote sensing for snowmelt simulations in a river basin in the Altay Mountains, northwest China

NASA Astrophysics Data System (ADS)

Wu, X.; Shen, Y.; Wang, N.; Pan, X.; Zhang, W.; He, J.; Wang, G.

2017-12-01

Snowmelt water is an important freshwater resource in the Altay Mountains in northwest China, and it is also crucial for local ecological system, economic and social sustainable development; however, warming climate and rapid spring snowmelt can cause floods that endanger both eco-environment and public and personal property and safety. This study simulates snowmelt in the Kayiertesi River catchment using a temperature-index model based on remote sensing coupled with high-resolution meteorological data obtained from NCEP reanalysis fields that were downscaled using Weather Research Forecasting model, then bias-corrected using a statistical downscaled model. Validation of the forcing data revealed that the high-resolution meteorological fields derived from downscaled NCEP reanalysis were reliable for driving the snowmelt model. Parameters of temperature-index model based on remote sensing were calibrated for spring 2014, and model performance was validated using MODIS snow cover and snow observations from spring 2012. The results show that the temperature-index model based on remote sensing performed well, with a simulation mean relative error of 6.7% and a Nash-Sutchliffe efficiency of 0.98 in spring 2012 in the river of Altay Mountains. Based on the reliable distributed snow water equivalent simulation, daily snowmelt runoff was calculated for spring 2012 in the basin. In the study catchment, spring snowmelt runoff accounts for 72% of spring runoff and 21% of annual runoff. Snowmelt is the main source of runoff for the catchment and should be managed and utilized effectively. The results provide a basis for snowmelt runoff predictions, so as to prevent snowmelt-induced floods, and also provide a generalizable approach that can be applied to other remote locations where high-density, long-term observational data is lacking.

The Microphysical Properties of Convective Precipitation Over the Tibetan Plateau by a Subkilometer Resolution Cloud-Resolving Simulation

NASA Astrophysics Data System (ADS)

Gao, Wenhua; Liu, Liping; Li, Jian; Lu, Chunsong

2018-03-01

The microphysical properties of convective precipitation over the Tibetan Plateau are unique because of the extremely high topography and special atmospheric conditions. In this study, the ground-based cloud radar and disdrometer observations as well as high-resolution Weather Research and Forecasting simulations with the Chinese Academy of Meteorological Sciences microphysics and four other microphysical schemes are used to investigate the microphysics and precipitation mechanisms of a convection event on 24 July 2014. The Weather Research and Forecasting-Chinese Academy of Meteorological Sciences simulation reasonably reproduces the spatial distribution of 24-hr accumulated rainfall, yet the temporal evolution of rain rate has a delay of 1-3 hr. The model reflectivity shares the common features with the cloud radar observations. The simulated raindrop size distributions demonstrate more of small- and large-size raindrops produced with the increase of rain rate, suggesting that changeable shape parameter should be used in size distribution. Results show that abundant supercooled water exists through condensation of water vapor above the freezing layer. The prevailing ice crystal microphysical processes are depositional growth and autoconversion of ice crystal to snow. The dominant source term of snow/graupel is riming of supercooled water. Sedimentation of graupel can play a vital role in the formation of precipitation, but melting of snow is rather small and quite different from that in other regions. Furthermore, water vapor budgets suggest that surface moisture flux be the principal source of water vapor and self-circulation of moisture happen at the beginning of convection, while total moisture flux convergence determine condensation and precipitation during the convective process over the Tibetan Plateau.

Future aerosol concentrations in Europe: Effects of changing meteorology and emissions

NASA Astrophysics Data System (ADS)

Coleman, Liz; Martin, Damien; Radalescu, Razvan; O'Dowd, Colin

2013-05-01

The ambient particulate matter concentrations are assessed using annual simulations for model validation period 2006, and for future time-slice years 2030, 2050 and 2100 under RCP scenario 6.0. Meteorological initial and boundary conditions are procured from ECHAM5-HAMMOC global simulations. The contribution of natural and anthropogenic processes to aerosol concentrations are assessed with particular emphasis on accumulation mode sea salt, organic enrichment thereof and future levels of secondary organic aerosol from isoprene.

Dynamic evaluation of CMAQ part I: Separating the effects of ...

EPA Pesticide Factsheets

A dynamic evaluation of the Community Multiscale Air Quality (CMAQ) modeling system version 5.0.1 was conducted to evaluate the model's ability to predict changes in ozone levels between 2002 and 2005, a time period characterized by emission reductions associated with the EPA's Nitrogen Oxides State Implementation Plan as well as significant reductions in mobile source emissions. Model results for the summers of 2002 and 2005 were compared to simulations from a previous version of CMAQ to assess the impact of model updates on predicted pollutant response. Changes to the model treatment of emissions, meteorology and chemistry had substantial impacts on the simulated ozone concentrations. While the median bias for high summertime ozone decreased in both years compared to previous simulations, the observed decrease in ozone from 2002 to 2005 in the eastern US continued to be underestimated by the model. Additional “cross” simulations were used to decompose the model predicted change in ozone into the change due to emissions, the change due to meteorology and any remaining change not explained individually by these two components. The decomposition showed that the emission controls led to a decrease in modeled high summertime ozone close to twice as large as the decrease attributable to changes in meteorology alone. Quantifying the impact of retrospective emission controls by removing the impacts of meteorology during the control period can be a valuable approac

Improved meteorology from an updated WRF/CMAQ modeling ...

EPA Pesticide Factsheets

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 Quality model) that employs the Pleim-Xiu land surface model (PX LSM). Recently, PX LSM WRF/CMAQ has been updated in vegetation, soil, and boundary layer processes resulting in improved 2 m temperature (T) and mixing ratio (Q), 10 m wind speed, and surface ozone simulations across the domain compared to the previous version for a period around August 2006. Yearlong meteorology simulations with the updated system demonstrate that MODIS input helps reduce bias of the 2 m Q estimation during the growing season from April to September. Improvements follow the green-up in the southeast from April and move toward the west and north through August. From October to March, MODIS input does not have much influence on the system because vegetation is not as active. The greatest effects of MODIS input include more accurate phenology, better representation of leaf area index (LAI) for various forest ecosystems and agricultural areas, and realistically sparse vegetation coverage in the western drylands. Despite the improved meteorology, MODIS input causes higher bias for the surface O3 simulation in April, August, and October in areas where MODIS LAI is much less than the base LAI. Thus, improvement

The 1981 current research on aviation weather (bibliography)

NASA Technical Reports Server (NTRS)

Daniel, J.; Frost, W.

1982-01-01

Current and ongoing research programs related to various areas of aviation meteorology are presented. Literature searches of major abstract publications, were conducted. Research project managers of various government agencies involved in aviation meteorology research provided a list of current research project titles and managers, supporting organizations, performing organizations, the principal investigators, and the objectives. These are tabulated under the headings of advanced meteorological instruments, forecasting, icing, lightning and atmospheric electricity; fog, visibility, and ceilings; low level wind shear, storm hazards/severe storms, turbulence, winds, and ozone and other meteorological parameters. This information was reviewed and assembled into a bibliography providing a current readily useable source of information in the area of aviation meteorology.

Ensemble Simulation of the Atmospheric Radionuclides Discharged by the Fukushima Nuclear Accident

NASA Astrophysics Data System (ADS)

Sekiyama, Thomas; Kajino, Mizuo; Kunii, Masaru

2013-04-01

Enormous amounts of radionuclides were discharged into the atmosphere by a nuclear accident at the Fukushima Daiichi nuclear power plant (FDNPP) after the earthquake and tsunami on 11 March 2011. The radionuclides were dispersed from the power plant and deposited mainly over eastern Japan and the North Pacific Ocean. A lot of numerical simulations of the radionuclide dispersion and deposition had been attempted repeatedly since the nuclear accident. However, none of them were able to perfectly simulate the distribution of dose rates observed after the accident over eastern Japan. This was partly due to the error of the wind vectors and precipitations used in the numerical simulations; unfortunately, their deterministic simulations could not deal with the probability distribution of the simulation results and errors. Therefore, an ensemble simulation of the atmospheric radionuclides was performed using the ensemble Kalman filter (EnKF) data assimilation system coupled with the Japan Meteorological Agency (JMA) non-hydrostatic mesoscale model (NHM); this mesoscale model has been used operationally for daily weather forecasts by JMA. Meteorological observations were provided to the EnKF data assimilation system from the JMA operational-weather-forecast dataset. Through this ensemble data assimilation, twenty members of the meteorological analysis over eastern Japan from 11 to 31 March 2011 were successfully obtained. Using these meteorological ensemble analysis members, the radionuclide behavior in the atmosphere such as advection, convection, diffusion, dry deposition, and wet deposition was simulated. This ensemble simulation provided the multiple results of the radionuclide dispersion and distribution. Because a large ensemble deviation indicates the low accuracy of the numerical simulation, the probabilistic information is obtainable from the ensemble simulation results. For example, the uncertainty of precipitation triggered the uncertainty of wet deposition; the uncertainty of wet deposition triggered the uncertainty of atmospheric radionuclide amounts. Then the remained radionuclides were transported downwind; consequently the uncertainty signal of the radionuclide amounts was propagated downwind. The signal propagation was seen in the ensemble simulation by the tracking of the large deviation areas of radionuclide concentration and deposition. These statistics are able to provide information useful for the probabilistic prediction of radionuclides.

A numerical model simulation of the regional air pollution meteorology of the greater Chesapeake Bay area - Summer day case study

NASA Technical Reports Server (NTRS)

Segal, M.; Pielke, R. A.; Mcnider, R. T.; Mcdougal, D. S.

1982-01-01

The mesoscale numerical model of the University of Virginia (UVMM), has been applied to the greater Chesapeake Bay area in order to provide a detailed description of the air pollution meteorology during a typical summer day. This model provides state of the art simulations for land-sea thermally induced circulations. The model-predicted results agree favorably with available observed data. The effects of synoptic flow and sea breeze coupling on air pollution meteorological characteristics in this region, are demonstrated by a spatial and temporal presentation of various model predicted fields. A transport analysis based on predicted wind velocities indicated possible recirculation of pollutants back onto the Atlantic coast due to the sea breeze circulation.

Analysis of a Meteorological Database for London Heathrow in the Context of Wake Vortex Hazards

NASA Astrophysics Data System (ADS)

Agnew, P.; Ogden, D. J.; Hoad, D. J.

2003-04-01

A database of meteorological parameters collected by aircraft arriving at LHR has recently been compiled. We have used the recorded variation of temperature and wind with height to deduce the 'wake vortex behaviour class' (WVBC) along the glide slope, as experienced by each flight. The integrated state of the glide slope has been investigated, allowing us to estimate the proportion of time for which the wake vortex threat is reduced, due to either rapid decay or transport off the glide slope. A numerical weather prediction model was used to forecast the meteorological parameters for periods coinciding with the aircraft data. This allowed us to perform a comparison of forecast WVBC with those deduced from the aircraft measurements.

Temperature and solute-transport simulation in streamflow using a Lagrangian reference frame

USGS Publications Warehouse

Jobson, Harvey E.

1980-01-01

A computer program for simulating one-dimensional, unsteady temperature and solute transport in a river has been developed and documented for general use. The solution approach to the convective-diffusion equation uses a moving reference frame (Lagrangian) which greatly simplifies the mathematics of the solution procedure and dramatically reduces errors caused by numerical dispersion. The model documentation is presented as a series of four programs of increasing complexity. The conservative transport model can be used to route a single conservative substance. The simplified temperature model is used to predict water temperature in rivers when only temperature and windspeed data are available. The complete temperature model is highly accurate but requires rather complete meteorological data. Finally, the 10-parameter model can be used to route as many as 10 interacting constituents through a river reach. (USGS)

Tropical Cyclone Genesis: A Dynamician's Point of View

NASA Astrophysics Data System (ADS)

Bouali, Safieddine; Leys, Jos

The paper focuses the route to the maturity of a cyclone as a twist process of the Hadley cell. The approach is qualified by a "dynamician's viewpoint" since the aerologic mechanism of the cyclone genesis is replicated without the classical tools of the meteorological fluid framework. Indeed, we introduce a pure dynamical model of a 2D vertical rotor of an airparcel to emulate the Hadley cell. Twisted by an appropriate feedback to inject geophysical forcing, the simulation displays two stretched solenoid rolls with clockwise and anticlockwise paths representing the Hadley belts wrapping the Earth. When the forcing parameter is higher, computations simulate overlapped whirlwind funnels revealing strong similarities with the structure of cyclones, hurricanes, and typhoons described in the atmospheric science literature. We conjecture that ocean-atmosphere interactions separate and convert a "slice" of the Hadley rotor into a fully tropical cyclone.

Improved meteorology from an updated WRF/CMAQ modeling system with MODIS vegetation and albedo

EPA Science Inventory

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...

A FEDERATED PARTNERSHIP FOR URBAN METEOROLOGICAL AND AIR QUALITY MODELING

EPA Science Inventory

Recently, applications of urban meteorological and air quality models have been performed at resolutions on the order of km grid sizes. This necessitated development and incorporation of high resolution landcover data and additional boundary layer parameters that serve to descri...

GEMPAK5. Part 2: GEMPLT programmer's guide, version 5.0

NASA Technical Reports Server (NTRS)

Desjardins, Mary L.; Brill, Keith F.; Schotz, Steven S.

1991-01-01

GEMPAK is a general meteorological software package used to analyze and display conventional meteorological data as well as satellite derived parameters. The GEMPAK Programmer's Guide describes the subroutines which can be used in the GEMPAK graphics and transformation subsystem, GEMPLT.

Influence of long-range anthropogenic transport on arctic cloud phase transition

NASA Astrophysics Data System (ADS)

Riedi, J.; Coopman, Q.; Garrett, T. J.; Finch, D.

2016-12-01

A decrease in precipitation during winter allows polluted air parcels from mid-latitudes to reach the Arctic. Low vertical mixing in the region concentrates aerosols and decreases scavenging. Aerosol impacts on cloud microphysical parameters remain poorly understood. However, cloud properties and pollution concentrations also vary with meteorological state, which poses the challenge of how to disentangle the impact of aerosols on clouds from that of natural thermodynamic variability. In this study we combine measurements from satellite instruments POLDER-3 and MODIS to temporally and spatially co-locate cloud properties over 65º in latitude with carbon monoxide concentrations, passive tracer of aerosol content, from GEOS-Chem between 2005 and 2010. We also add ERA-I reanalysis of meteorological parameters to stratify meteorological parameters, such as specific humidity and lower tropospheric stability. The goal is to determine the extent to which differences in cloud phase can be attributed to differences in aerosol content and not in meteorological parameters.We evaluated the amount of supercooling ΔT50 that is required for 50% of a chosen ensemble of low-level clouds to be in the ice phase. Consistent with Rangno & Hobbs (2001), our results suggest that small droplet effective radii are related to high values of ΔT50. Also, anthropogenic pollution plumes lower the degree of supercooling by approximately 5°C, independent of the decrease in effective radius and change of meteorological regime. This effect of anthropogenic aerosol on the transition temperature to freezing has not been reported before to our knowledge and lacks clear explanation. Rangno, A. L., & Hobbs, P. V. (2001). Ice particles in stratiform clouds in the Arctic and possible mechanisms for the production of high ice concentrations. Journal of geophysical research, 106, 15.

Power estimation using simulations for air pollution time-series studies

PubMed Central

2012-01-01

Background Estimation of power to assess associations of interest can be challenging for time-series studies of the acute health effects of air pollution because there are two dimensions of sample size (time-series length and daily outcome counts), and because these studies often use generalized linear models to control for complex patterns of covariation between pollutants and time trends, meteorology and possibly other pollutants. In general, statistical software packages for power estimation rely on simplifying assumptions that may not adequately capture this complexity. Here we examine the impact of various factors affecting power using simulations, with comparison of power estimates obtained from simulations with those obtained using statistical software. Methods Power was estimated for various analyses within a time-series study of air pollution and emergency department visits using simulations for specified scenarios. Mean daily emergency department visit counts, model parameter value estimates and daily values for air pollution and meteorological variables from actual data (8/1/98 to 7/31/99 in Atlanta) were used to generate simulated daily outcome counts with specified temporal associations with air pollutants and randomly generated error based on a Poisson distribution. Power was estimated by conducting analyses of the association between simulated daily outcome counts and air pollution in 2000 data sets for each scenario. Power estimates from simulations and statistical software (G*Power and PASS) were compared. Results In the simulation results, increasing time-series length and average daily outcome counts both increased power to a similar extent. Our results also illustrate the low power that can result from using outcomes with low daily counts or short time series, and the reduction in power that can accompany use of multipollutant models. Power estimates obtained using standard statistical software were very similar to those from the simulations when properly implemented; implementation, however, was not straightforward. Conclusions These analyses demonstrate the similar impact on power of increasing time-series length versus increasing daily outcome counts, which has not previously been reported. Implementation of power software for these studies is discussed and guidance is provided. PMID:22995599

Power estimation using simulations for air pollution time-series studies.

PubMed

Winquist, Andrea; Klein, Mitchel; Tolbert, Paige; Sarnat, Stefanie Ebelt

2012-09-20

Estimation of power to assess associations of interest can be challenging for time-series studies of the acute health effects of air pollution because there are two dimensions of sample size (time-series length and daily outcome counts), and because these studies often use generalized linear models to control for complex patterns of covariation between pollutants and time trends, meteorology and possibly other pollutants. In general, statistical software packages for power estimation rely on simplifying assumptions that may not adequately capture this complexity. Here we examine the impact of various factors affecting power using simulations, with comparison of power estimates obtained from simulations with those obtained using statistical software. Power was estimated for various analyses within a time-series study of air pollution and emergency department visits using simulations for specified scenarios. Mean daily emergency department visit counts, model parameter value estimates and daily values for air pollution and meteorological variables from actual data (8/1/98 to 7/31/99 in Atlanta) were used to generate simulated daily outcome counts with specified temporal associations with air pollutants and randomly generated error based on a Poisson distribution. Power was estimated by conducting analyses of the association between simulated daily outcome counts and air pollution in 2000 data sets for each scenario. Power estimates from simulations and statistical software (G*Power and PASS) were compared. In the simulation results, increasing time-series length and average daily outcome counts both increased power to a similar extent. Our results also illustrate the low power that can result from using outcomes with low daily counts or short time series, and the reduction in power that can accompany use of multipollutant models. Power estimates obtained using standard statistical software were very similar to those from the simulations when properly implemented; implementation, however, was not straightforward. These analyses demonstrate the similar impact on power of increasing time-series length versus increasing daily outcome counts, which has not previously been reported. Implementation of power software for these studies is discussed and guidance is provided.

How much expert knowledge is it worth to put in conceptual hydrological models?

NASA Astrophysics Data System (ADS)

Antonetti, Manuel; Zappa, Massimiliano

2017-04-01

Both modellers and experimentalists agree on using expert knowledge to improve our conceptual hydrological simulations on ungauged basins. However, they use expert knowledge differently for both hydrologically mapping the landscape and parameterising a given hydrological model. Modellers use generally very simplified (e.g. topography-based) mapping approaches and put most of the knowledge for constraining the model by defining parameter and process relational rules. In contrast, experimentalists tend to invest all their detailed and qualitative knowledge about processes to obtain a spatial distribution of areas with different dominant runoff generation processes (DRPs) as realistic as possible, and for defining plausible narrow value ranges for each model parameter. Since, most of the times, the modelling goal is exclusively to simulate runoff at a specific site, even strongly simplified hydrological classifications can lead to satisfying results due to equifinality of hydrological models, overfitting problems and the numerous uncertainty sources affecting runoff simulations. Therefore, to test to which extent expert knowledge can improve simulation results under uncertainty, we applied a typical modellers' modelling framework relying on parameter and process constraints defined based on expert knowledge to several catchments on the Swiss Plateau. To map the spatial distribution of the DRPs, mapping approaches with increasing involvement of expert knowledge were used. Simulation results highlighted the potential added value of using all the expert knowledge available on a catchment. Also, combinations of event types and landscapes, where even a simplified mapping approach can lead to satisfying results, were identified. Finally, the uncertainty originated by the different mapping approaches was compared with the one linked to meteorological input data and catchment initial conditions.

Instantaneous Linkages between Clouds and Large-Scale Meteorology over the Southern Ocean in Observations and a Climate Model

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

Wall, Casey J.; Hartmann, Dennis L.; Ma, Po-Lun

Instantaneous, coincident, footprint-level satellite observations of cloud properties and radiation taken during austral summer over the Southern Ocean are used to study relationships between clouds and large-scale meteorology. Cloud properties are very sensitive to the strength of vertical motion in the middle-troposphere, and low-cloud properties are sensitive to estimated inversion strength, low-level temperature advection, and sea surface temperature. These relationships are quantified. An index for the meteorological anomalies associated with midlatitude cyclones is presented, and it is used to reveal the sensitivity of clouds to the meteorology within the warm- and cold-sector of cyclones. The observed relationships between clouds andmore » meteorology are compared to those in the Community Atmosphere Model version 5 (CAM5) using satellite simulators. Low-clouds simulated by CAM5 are too few, too bright, and contain too much ice, and low-clouds located in the cold-sector of cyclones are too sensitive to variations in the meteorology. The latter two biases are dramatically reduced when CAM5 is coupled with an updated boundary layer parameterization know as Cloud Layers Unified by Binormals (CLUBB). More generally, this study demonstrates that examining the instantaneous timescale is a powerful approach to understanding the physical processes that control clouds and how they are represented in climate models. Such an evaluation goes beyond the cloud climatology and exposes model bias under various meteorological conditions.« less

A new concept to study the effect of climate change on different flood types

NASA Astrophysics Data System (ADS)

Nissen, Katrin; Nied, Manuela; Pardowitz, Tobias; Ulbrich, Uwe; Merz, Bruno

2014-05-01

Flooding is triggered by the interaction of various processes. Especially important are the hydrological conditions prior to the event (e.g. soil saturation, snow cover) and the meteorological conditions during flood development (e.g. rainfall, temperature). Depending on these (pre-) conditions different flood types may develop such as long-rain floods, short-rain floods, flash floods, snowmelt floods and rain-on-snow floods. A new concept taking these factors into account is introduced and applied to flooding in the Elbe River basin. During the period September 1957 to August 2002, 82 flood events are identified and classified according to their flood type. The hydrological and meteorological conditions at each day during the analysis period are detemined. In case of the hydrological conditions, a soil moisture pattern classification is carried out. Soil moisture is simulated with a rainfall-runoff model driven by atmospheric observations. Days of similar soil moisture patterns are identified by a principle component analysis and a subsequent cluster analysis on the leading principal components. The meteorological conditions are identified by applying a cluster analysis to the geopotential height, temperature and humidity fields of the ERA40 reanalysis data set using the SANDRA cluster algorithm. We are able to identify specific pattern combinations of hydrological pre-conditions and meteorological conditions which favour different flood types. Based on these results it is possible to analyse the effect of climate change on different flood types. As an example we show first results obtained using an ensemble of climate scenario simulations of ECHAM5 MPIOM model, taking only the changes in the meteorological conditions into account. According to the simulations, the frequency of the meteorological patterns favouring long-rain, short-rain and flash floods will not change significantly under future climate conditions. A significant increase is, however, predicted for the amount of precipitation associated with many of the relevant meteorological patterns. The increase varies between 12 and 67% depending on the weather pattern.

Modeling & Simulation Education for the Acquisition and T&E Workforce: FY07 Deliverable Package

DTIC Science & Technology

2007-12-01

oceanography, meteorology, and near- earth space science) to represent how systems interact with and are influenced by their environment. E12.1 E12.2 E12.3 E12.4...fundamentals of terrestrial science (geology, oceanography, meteorology, and near- earth space science) to represent how systems interact with and...description: Describe the fundamentals of terrestrial science (geology, oceanography, meteorology, and near- earth space science) to represent how systems

Analysis of traffic and meteorology on airborne particulate matter in Münster, northwest Germany.

PubMed

Gietl, Johanna K; Klemm, Otto

2009-07-01

The importance of street traffic and meteorological conditions on the concentrations of particulate matter (PM) with an aerodynamic diameter smaller than 10 microm (PM10) was studied in the city of Münster in northwest Germany. The database consisted of meteorological data, data of PM10 mass concentrations and fine particle number (6-225 nm diameter) concentrations, and traffic intensity data as counted with tally hand counters at a four- to six-lane road. On working days, a significant correlation could be found between the diurnal mean PM10 mass concentration and vehicle number. The lower number of heavy-duty vehicles compared with passenger cars contributed more to the particle number concentration on working days than on weekend days. On weekends, when the vehicle number was very low, the correlation between PM10 mass concentration and vehicle number changed completely. Other sources of PM and the meteorology dominated the PM concentration. Independent of the weekday, by decreasing the traffic by approximately 99% during late-night hours, the PM10 concentration was reduced by 12% of the daily mean value. A correlation between PM10 and the particle number concentration was found for each weekday. In this study, meteorological parameters, including the atmospheric stability of the boundary layer, were also accounted for. The authors deployed artificial neural networks to achieve more information on the influence of various meteorological parameters, traffic, and the day of the week. A multilayer perceptron network showed the best results for predicting the PM10 concentration, with the correlation coefficient being 0.72. The influence of relative humidity, temperature, and wind was strong, whereas the influence of atmospheric stability and the traffic parameters was weak. Although traffic contributes a constant amount of particles in a daily and weekly cycle, it is the meteorology that drives most of the variability.

Introducing stochastics into the simulation of convective precipitation events

NASA Astrophysics Data System (ADS)

Pistotnik, Georg

2010-05-01

In a joint project, the Central Institute for Meteorology and Geodynamics (ZAMG) and the Vienna University of Technology aimed to characterize strong precipitation events and their impact in the Bucklige Welt region in Eastern Austria. Both the region's hydrological and meteorological characteristics, namely its composition of virtually countless small catchments with short response times and a high frequency of summertime convective storms, cause the occurrence of flooding to be strictly tied to convective rainfall events, which is why this study has been focused on this type of precipitation. The meteorological database consists of the ZAMG's high-resolution analysis and nowcasting system INCA ("Integrated Nowcasting through Comprehensive Analysis"), which provides a set of precipitation analyses generated by a statistically optimized combination of rain gauge measurements and radar data with a temporal resolution of 15 minutes and a spatial resolution of 1 kilometre. An intensity threshold of 3.8mm/15min has been used to classify any observed precipitation as a convective one, thus extracting 245 convection days with a total number of almost 1600 individual storm events over the project region out of the 5-year data set from 2003 to 2007. Consecutive analyses were used to compute the motion of these storms, a complex process that could not be completely automatized; due to the repeated occurrence of storm splits or coalescences, a manual control of the automatically provided "suggestion" of movement had to be performed in order to merge two or more precipitation maxima to a single storm if necessary, thus yielding the smoothest and most plausible storm tracks and ensuring a high quality of the database. In the first part of the project, distributions for all characteristic parameters have been derived, including the number of storms per day, their place and time of initiation, their motion, lifetime, maximum intensity and maximum "cell volume" (i.e. overall precipitation per time step). Both components of the mean motion as well as of its deviations could be approximated by normal distributions, whereas the number of storms per day, their lifetime, maximum intensity and maximum cell volume roughly followed exponential distributions. The shapes of the convective cells were approximated by Gaussian bells with the peak intensity and the cell volume as boundary conditions. The temporal courses of the peak intensities and cell volumes were assumed to follow parabolas which are symmetric with respect to the half of the lifetime. In the second part of the project, these distributions were used to drive a random generator that allows simulating an arbitrary number of convection days in order to obtain pseudo time series of convective precipitation for each grid point. An algorithm to create correlated samples of random numbers enabled to also account for the observed correlation between some of the parameters, i.e. lifetime and maximum intensity or maximum cell volume. The spatial structures of the return periods of simulated convective precipitation events may provide valuable additional information when being assimilated to the time series measured by the (unfortunately rather sparse) rain gauges in this region. Thus, further studies have to investigate to what extent the "convection simulator" is able to reproduce these time series. Some iterative fine-tuning of the parameters' distributions as well as an extension of the database to a longer time span may further improve the results and enable to simulate realistic spatio-temporal convection scenarios ("design storms") that have the potential to feed hydrological models and, together with vegetation and soil characteristics, hopefully enable to better assess and regionalize the torrent hazard over the project region.

The 1991 International Aerospace and Ground Conference on Lightning and Static Electricity, volume 1

NASA Technical Reports Server (NTRS)

1991-01-01

The proceedings of the 1991 International Aerospace and Ground Conference on Lightning and Static Electricity are reported. Some of the topics covered include: lightning, lightning suppression, aerospace vehicles, aircraft safety, flight safety, aviation meteorology, thunderstorms, atmospheric electricity, warning systems, weather forecasting, electromagnetic coupling, electrical measurement, electrostatics, aircraft hazards, flight hazards, meteorological parameters, cloud (meteorology), ground effect, electric currents, lightning equipment, electric fields, measuring instruments, electrical grounding, and aircraft instruments.

Drought Dynamics and Food Security in Ukraine

NASA Astrophysics Data System (ADS)

Kussul, N. M.; Kogan, F.; Adamenko, T. I.; Skakun, S. V.; Kravchenko, O. M.; Kryvobok, O. A.; Shelestov, A. Y.; Kolotii, A. V.; Kussul, O. M.; Lavrenyuk, A. M.

2012-12-01

In recent years food security became a problem of great importance at global, national and regional scale. Ukraine is one of the most developed agriculture countries and one of the biggest crop producers in the world. According to the 2011 statistics provided by the USDA FAS, Ukraine was the 8th largest exporter and 10th largest producer of wheat in the world. Therefore, identifying current and projecting future trends in climate and agriculture parameters is a key element in providing support to policy makers in food security. This paper combines remote sensing, meteorological, and modeling data to investigate dynamics of extreme events, such as droughts, and its impact on agriculture production in Ukraine. Two main problems have been considered in the study: investigation of drought dynamics in Ukraine and its impact on crop production; and investigation of crop growth models for yield and production forecasting and its comparison with empirical models that use as a predictor satellite-derived parameters and meteorological observations. Large-scale weather disasters in Ukraine such as drought were assessed using vegetation health index (VHI) derived from satellite data. The method is based on estimation of green canopy stress/no stress from indices, characterizing moisture and thermal conditions of vegetation canopy. These conditions are derived from the reflectance/emission in the red, near infrared and infrared parts of solar spectrum measured by the AVHRR flown on the NOAA afternoon polar-orbiting satellites since 1981. Droughts were categorized into exceptional, extreme, severe and moderate. Drought area (DA, in % from total Ukrainian area) was calculated for each category. It was found that maximum DA over past 20 years was 10% for exceptional droughts, 20% for extreme droughts, 50% for severe droughts, and 80% for moderate droughts. Also, it was shown that in general the drought intensity and area did not increase considerably over past 10 years. Analysis of interrelation between DA of different categories at oblast level with agriculture production will be discussed as well. A comparative study was carried out to assess three approaches to forecast winter wheat yield in Ukraine at oblast level: (i) empirical regression-based model that uses as a predictor 16-day NDVI composites derived from MODIS at the 250 m resolution, (ii) empirical regression-based model that uses as predictors meteorological parameters, and (iii) adapted for Ukraine Crop Growth Monitoring System (CGMS) that is based on WOFOST crop growth simulation model and meteorological parameters. These three approaches were calibrated for 2000-2009 and 2000-2010 data, and compared while performing forecasts on independent data for 2010 and 2011. For 2010, the best results in terms of root mean square error (RMSE, by oblast, deviation of predicted values from official statistics) were achieved using CGMS models: 0.3 t/ha. For NDVI and meteorological models RMSE values were 0.79 and 0.77 t/ha, respectively. When forecasting winter wheat yield for 2011, the following RMSE values were obtained: 0.58 t/ha for CGMS, 0.56 t/ha for meteorological model, and 0.62 t/ha for NDVI. In this case performance of all three approaches was relatively the same. Acknowledgements. This work was supported by the U.S. CRDF Grant "Analysis of climate change & food security based on remote sensing & in situ data sets" (UKB2-2972-KV-09).

Design criteria and eigensequence plots for satellite-computed tomography. [in meteorology

NASA Technical Reports Server (NTRS)

Wahba, G.

1985-01-01

The use of the degrees of freedom for signal is proposed as a design criteria for comparing different designs for satellite and other measuring systems. It is also proposed that certain eigensequence plots be examined at the design stage along with appropriate estimates of the parameter lambda playing the role of noise to signal ratio. The degrees of freedom for signal and the eigensequence plots may be determined using prior information in the spectral domain which is presently available along with a description of the system, and simulated data for estimating lambda. This work extends the 1972 work of Weinreb and Crosby.

Analysis of air quality management with emphasis on transportation sources

NASA Technical Reports Server (NTRS)

English, T. D.; Divita, E.; Lees, L.

1980-01-01

The current environment and practices of air quality management were examined for three regions: Denver, Phoenix, and the South Coast Air Basin of California. These regions were chosen because the majority of their air pollution emissions are related to mobile sources. The impact of auto exhaust on the air quality management process is characterized and assessed. An examination of the uncertainties in air pollutant measurements, emission inventories, meteorological parameters, atmospheric chemistry, and air quality simulation models is performed. The implications of these uncertainties to current air quality management practices is discussed. A set of corrective actions are recommended to reduce these uncertainties.

Constraints Pb-210 and Be-7 on Wet Deposition and Transport in a Global Three-Dimensional Chemical Tracer Model Driven by Assimilated Meteorological Fields

NASA Technical Reports Server (NTRS)

Liu, Hong-Yu; Jacob, Daniel J.; Bey, Isabelle; Yantosca, Robert M.

2001-01-01

The atmospheric distributions of the aerosol tracers Pb-210 and Be-7 are simulated with a global three-dimensional model driven by assimilated meteorological observations for 1991-1996 from the NASA Goddard Earth Observing System (GEOSl). The combination of terrigenic Pb-210 and cosmogenic Be-7 provides a sensitive test of wet deposition and vertical transport in the model. Our simulation of moist transport and removal includes scavenging in wet convective updrafts (40% scavenging efficiency per kilometer of updraft), midlevel entrainment and detrainment, first-order rainout and washout from both convective anvils and large-scale precipitation, and cirrus precipitation. Observations from surface sites in specific years are compared to model results for the corresponding meteorological years, and observations from aircraft missions over the Pacific are compared to model results for the days of the flights. Initial simulation of Be-7 showed that cross-tropopause transport in the GEOSl meteorological fields is too fast by a factor of 3-4. We adjusted the stratospheric Be-7 source to correct the tropospheric simulation. Including this correction, we find that the model gives a good simulation of observed Pb-210 and Be-7 concentrations and deposition fluxes at surface sites worldwide, with no significant global bias and with significant success in reproducing the observed latitudinal and seasonal distributions. We achieve several improvements over previous models; in particular, we reproduce the observed Be-7 minimum in the tropics and show that its simulation is sensitive to rainout from convective anvils. Comparisons with aircraft observations up to 12-km altitude suggest that cirrus precipitation could be important for explaining the low concentrations in the middle and upper troposphere.

Dynamics and transport in the stratosphere : Simulations with a general circulation mode

NASA Astrophysics Data System (ADS)

van Aalst, Maarten Krispijn

2005-01-01

The middle atmosphere is strongly affected by two of the world's most important environmental problems: global climate change and stratospheric ozone depletion, caused by anthropogenic emissions of greenhouse gases and chlorofluorocarbons (CFCs), respectively. General circulation models with coupled chemistry are a key tool to advance our understanding of the complex interplay between dynamics, chemistry and radiation in the middle atmosphere. A key problem of such models is that they generate their own meteorology, and thus cannot be used for comparisons with instantaneous measurements. This thesis presents the first application of a simple data assimilation method, Newtonian relaxation, to reproduce realistic synoptical conditions in a state-of-the-art middle atmosphere general circulation model, MA-ECHAM. By nudging the model's meteorology slightly towards analyzed observations from a weather forecasting system (ECMWF), we have simulated specific atmospheric processes during particular meteorological episodes, such as the 1999/2000 Arctic winter. The nudging technique is intended to interfere as little as possible with the model's own dynamics. In fact, we found that we could even limit the nudging to the troposphere, leaving the middle atmosphere entirely free. In that setup, the model realistically reproduced many aspects of the instantaneous meteorology of the middle atmosphere, such as the unusually early major warming and breakup of the 2002 Antarctic vortex. However, we found that this required careful interpolation of the nudging data, and a correct choice of nudging parameters. We obtained the best results when we first projected the nudging data onto the model's normal modes so that we could filter out the (spurious) fast components. In a four-year simulation, for which we also introduced an additional nudging of the stratospheric quasi-biennial oscillation, we found that the model reproduced much of the interannual variability throughout the stratosphere, including the Antarctic temperature minima crucial for polar ozone chemistry, but failed to capture the precise timing and evolution of Arctic stratospheric warmings. We also identified an important model deficiency regarding tracer transport in the lower polar stratosphere. The success of the runs with tropospheric nudging in simulating the right stratospheric conditions, including the model capability to forecast major stratospheric warming events, bodes well for the model's representation of the dynamic coupling between the troposphere and the stratosphere, an important element of realistic simulation of the future climate of the middle atmosphere (which will partly depend on a changing wave forcing from the troposphere). However, for some aspects of stratospheric dynamics, such as the quasi-biennial oscillation, a higher vertical resolution is required, which might also help to reduce some of the transport problems identified in the lower polar vortex. The nudging technique applied and developed in this thesis offers excellent prospects for applications in coupled-chemistry simulations of the middle atmosphere, including for the interpretation of instantaneous measurements. In particular, it can be used to test and improve the new MA-ECHAM5/MESSy/MECCA coupled chemistry climate model system, in preparation for more reliable simulations of past and future climates.

BOREAS AES READAC Surface Meteorological Data

NASA Technical Reports Server (NTRS)

Atkinson, G. Barrie; Funk, Barry; Hall, Forrest G. (Editor); Knapp, David E. (Editor)

2000-01-01

Canadian AES personnel collected and processed data related to surface atmospheric meteorological conditions over the BOREAS region. This data set contains 15-minute meteorological data from one READAC meteorology station in Hudson Bay, Saskatchewan. Parameters include day, time, type of report, sky condition, visibility, mean sea level pressure, temperature, dewpoint, wind, altimeter, opacity, minimum and maximum visibility, station pressure, minimum and maximum air temperature, a wind group, precipitation, and precipitation in the last hour. The data were collected non-continuously from 24-May-1994 to 20-Sep-1994. The data are provided in tabular ASCII files, and are classified as AFM-Staff data.

Techniques for Improved Retrospective Fine-scale Meteorology

EPA Science Inventory

Pleim-Xiu Land-Surface model (PX LSM) was developed for retrospective meteorological simulations to drive chemical transport models. One of the key features of the PX LSM is the indirect soil moisture and temperature nudging. The idea is to provide a three hourly 2-m temperature ...

GEMPAK5. Part 1: GEMPAK5 programmer's guide, version 5.0

NASA Technical Reports Server (NTRS)

Desjardins, Mary L.; Brill, Keith F.; Schotz, Steven S.

1991-01-01

GEMPAK is a general meteorological software package used to analyze and display conventional meteorological data as well as satellite derived parameters. The Programmer's Guide describes the subroutines which can be used to build new GEMPAK programs. Part 1 contains GEMPAK subroutines.

An investigation of the role of current and future remote sensing data systems in numerical meteorology

NASA Technical Reports Server (NTRS)

Diak, George R.; Smith, William L.

1992-01-01

A flexible system for performing observing system simulation experiments which made contributions to meteorology across all elements of the observing system simulation experiment (OSSE) components was developed. Future work will seek better understanding of the links between satellite-measured radiation and radiative transfer in the clear, cloudy and precipitating atmosphere and investigate how that understanding might be applied to improve the depiction of the initial state and the treatment of physical processes in forecast models of the atmosphere.

A program and data base for evaluating SMMR algorithms

NASA Technical Reports Server (NTRS)

1979-01-01

A program (PARAM) is described which enables a user to compare the values of meteorological parameters derived from data obtained by the scanning multichannel microwave radiometer (SMMR) instrument on NIMBUS 7 with surface observations made over the ocean. The input to this program is a data base, also described, which contains the surface observations and coincident SMMR data. The evaluation of meteorological parameters using SMMR data is done by a user supplied subroutine. Instruments are given for executing the program and writing the subroutine.

Design of extensible meteorological data acquisition system based on FPGA

NASA Astrophysics Data System (ADS)

Zhang, Wen; Liu, Yin-hua; Zhang, Hui-jun; Li, Xiao-hui

2015-02-01

In order to compensate the tropospheric refraction error generated in the process of satellite navigation and positioning. Temperature, humidity and air pressure had to be used in concerned models to calculate the value of this error. While FPGA XC6SLX16 was used as the core processor, the integrated silicon pressure sensor MPX4115A and digital temperature-humidity sensor SHT75 are used as the basic meteorological parameter detection devices. The core processer was used to control the real-time sampling of ADC AD7608 and to acquire the serial output data of SHT75. The data was stored in the BRAM of XC6SLX16 and used to generate standard meteorological parameters in NEMA format. The whole design was based on Altium hardware platform and ISE software platform. The system was described in the VHDL language and schematic diagram to realize the correct detection of temperature, humidity, air pressure. The 8-channel synchronous sampling characteristics of AD7608 and programmable external resources of FPGA laid the foundation for the increasing of analog or digital meteorological element signal. The designed meteorological data acquisition system featured low cost, high performance, multiple expansions.

Smoke Dispersion Modeling Over Complex Terrain Using High-Resolution Meteorological Data and Satellite Observations: The FireHub Platform

NASA Technical Reports Server (NTRS)

Solomos, S.; Amiridis, V.; Zanis, P.; Gerasopoulos, E.; Sofiou, F. I.; Herekakis, T.; Brioude, J.; Stohl, A.; Kahn, R. A.; Kontoes, C.

2015-01-01

A total number of 20,212 fire hot spots were recorded by the Moderate Resolution Imaging Spectroradiometer (MODIS) satellite instrument over Greece during the period 2002e2013. The Fire Radiative Power (FRP) of these events ranged from 10 up to 6000 MW at 1 km resolution, and many of these fire episodes resulted in long-range transport of smoke over distances up to several hundred kilometers. Three different smoke episodes over Greece are analyzed here using real time hot-spot observations from the Spinning Enhanced Visible and Infrared Imager (SEVIRI) satellite instrument as well as from MODIS hot-spots. Simulations of smoke dispersion are performed with the FLEXPART-WRF model and particulate matter emissions are calculated directly from the observed FRP. The modeled smoke plumes are compared with smoke stereo-heights from the Multiangle Imaging Spectroradiometer (MISR) instrument and the sensitivities to atmospheric and modeling parameters are examined. Driving the simulations with high resolution meteorology (4 4 km) and using geostationary satellite data to identify the hot spots allows the description of local scale features that govern smoke dispersion. The long-range transport of smoke is found to be favored over the complex coastline environment of Greece due to the abrupt changes between land and marine planetary boundary layers (PBL) and the decoupling of smoke layers from the surface.

Multifractal evaluation of simulated precipitation intensities from the COSMO NWP model

NASA Astrophysics Data System (ADS)

Wolfensberger, Daniel; Gires, Auguste; Tchiguirinskaia, Ioulia; Schertzer, Daniel; Berne, Alexis

2017-12-01

The framework of universal multifractals (UM) characterizes the spatio-temporal variability in geophysical data over a wide range of scales with only a limited number of scale-invariant parameters. This work aims to clarify the link between multifractals (MFs) and more conventional weather descriptors and to show how they can be used to perform a multi-scale evaluation of model data. The first part of this work focuses on a MF analysis of the climatology of precipitation intensities simulated by the COSMO numerical weather prediction model. Analysis of the spatial structure of the MF parameters, and their correlations with external meteorological and topographical descriptors, reveals that simulated precipitation tends to be smoother at higher altitudes, and that the mean intermittency is mostly influenced by the latitude. A hierarchical clustering was performed on the external descriptors, yielding three different clusters, which correspond roughly to Alpine/continental, Mediterranean and temperate regions. Distributions of MF parameters within these three clusters are shown to be statistically significantly different, indicating that the MF signature of rain is indeed geographically dependent. The second part of this work is event-based and focuses on the smaller scales. The MF parameters of precipitation intensities at the ground are compared with those obtained from the Swiss radar composite during three events corresponding to typical synoptic conditions over Switzerland. The results of this analysis show that the COSMO simulations exhibit spatial scaling breaks that are not present in the radar data, indicating that the model is not able to simulate the observed variability at all scales. A comparison of the operational one-moment microphysical parameterization scheme of COSMO with a more advanced two-moment scheme reveals that, while no scheme systematically outperforms the other, the two-moment scheme tends to produce larger extreme values and more discontinuous precipitation fields, which agree better with the radar composite.

A numerical forecast model for road meteorology

NASA Astrophysics Data System (ADS)

Meng, Chunlei

2017-05-01

A fine-scale numerical model for road surface parameters prediction (BJ-ROME) is developed based on the Common Land Model. The model is validated using in situ observation data measured by the ROSA road weather stations of Vaisala Company, Finland. BJ-ROME not only takes into account road surface factors, such as imperviousness, relatively low albedo, high heat capacity, and high heat conductivity, but also considers the influence of urban anthropogenic heat, impervious surface evaporation, and urban land-use/land-cover changes. The forecast time span and the update interval of BJ-ROME in vocational operation are 24 and 3 h, respectively. The validation results indicate that BJ-ROME can successfully simulate the diurnal variation of road surface temperature both under clear-sky and rainfall conditions. BJ-ROME can simulate road water and snow depth well if the artificial removing was considered. Road surface energy balance in rainy days is quite different from that in clear-sky conditions. Road evaporation could not be neglected in road surface water cycle research. The results of sensitivity analysis show solar radiation correction coefficient, asphalt depth, and asphalt heat conductivity are important parameters in road interface temperatures simulation. The prediction results could be used as a reference of maintenance decision support system to mitigate the traffic jam and urban water logging especially in large cities.

The WRF-CMAQ Integrated On-Line Modeling System: Development, Testing, and Initial Applications

EPA Science Inventory

Traditionally, atmospheric chemistry-transport and meteorology models have been applied in an off-line paradigm, in which archived output on the dynamical state of the atmosphere simulated using the meteorology model is used to drive transport and chemistry calculations of atmos...

Proceedings of the Automated Weather Support Technical Exchange Conference (6th). Held at the U.S. Naval Academy, Annapolis, Maryland on 21-24 September 1970.

DTIC Science & Technology

forecasting, Tailored meteorological support, Automated processing and application of satellite data, and Environmental simulation. The sixth and final session was devoted to a panel discussion on Automated meteorological support.

Development and evaluation of the Screening Trajectory Ozone Prediction System (STOPS, version 1.0)

NASA Astrophysics Data System (ADS)

Czader, B. H.; Percell, P.; Byun, D.; Kim, S.; Choi, Y.

2015-05-01

A hybrid Lagrangian-Eulerian based modeling tool has been developed using the Eulerian framework of the Community Multiscale Air Quality (CMAQ) model. It is a moving nest that utilizes saved original CMAQ simulation results to provide boundary conditions, initial conditions, as well as emissions and meteorological parameters necessary for a simulation. Given that these files are available, this tool can run independently of the CMAQ whole domain simulation, and it is designed to simulate source-receptor relationships upon changes in emissions. In this tool, the original CMAQ's horizontal domain is reduced to a small sub-domain that follows a trajectory defined by the mean mixed-layer wind. It has the same vertical structure and physical and chemical interactions as CMAQ except advection calculation. The advantage of this tool compared to other Lagrangian models is its capability of utilizing realistic boundary conditions that change with space and time as well as detailed chemistry treatment. The correctness of the algorithms and the overall performance was evaluated against CMAQ simulation results. Its performance depends on the atmospheric conditions occurring during the simulation period, with the comparisons being most similar to CMAQ results under uniform wind conditions. The mean bias for surface ozone mixing ratios varies between -0.03 and -0.78 ppbV and the slope is between 0.99 and 1.01 for different analyzed cases. For complicated meteorological conditions, such as wind circulation, the simulated mixing ratios deviate from CMAQ values as a result of the Lagrangian approach of using mean wind for its movement, but are still close, with the mean bias for ozone varying between 0.07 and -4.29 ppbV and the slope varying between 0.95 and 1.06 for different analyzed cases. For historical reasons, this hybrid Lagrangian-Eulerian based tool is named the Screening Trajectory Ozone Prediction System (STOPS), but its use is not limited to ozone prediction as, similarly to CMAQ, it can simulate concentrations of many species, including particulate matter and some toxic compounds, such as formaldehyde and 1,3-butadiene.

Evaluation of an assimilation scheme to estimate snow water equivalent in the High Atlas of Morocco.

NASA Astrophysics Data System (ADS)

Baba, W. M.; Baldo, E.; Gascoin, S.; Margulis, S. A.; Cortés, G.; Hanich, L.

2017-12-01

The snow melt from the Atlas mountains represents a crucial water resource for crop irrigation in Morocco. Due to the paucity of in situ measurements, and the high spatial variability of the snow cover in this semi-arid region, assimilation of snow cover area (SCA) from high resolution optical remote sensing into a snowpack energy-balance model is considered as a promising method to estimate the snow water equivalent (SWE) and snow melt at catchment scales. Here we present a preliminary evaluation of an uncalibrated particle batch smoother data assimilation scheme (Margulis et al., 2015, J. Hydrometeor., 16, 1752-1772) in the High-Atlas Rheraya pilot catchment (225 km2) over a snow season. This approach does not require in situ data since it is based on MERRA-2 reanalyses data and satellite fractional snow cover area data. We compared the output of this prior/posterior ensemble data assimilation system to output from the distributed snowpack evolution model SnowModel (Liston and Elder, 2006, J. Hydrometeor. 7, 1259-1276). SnowModel was forced with in situ meteorological data from five automatic weather stations (AWS) and some key parameters (precipitation correction factor and rain-snow phase transition parameters) were calibrated using a time series of 8-m resolution SCA maps from Formosat-2. The SnowModel simulation was validated using a continuous snow height record at one high elevation AWS. The results indicate that the open loop simulation was reasonably accurate (compared to SnowModel results) in spite of the coarse resolution of the MERRA-2 forcing. The assimilation of Formosat-2 SCA further improved the simulation in terms of the peak SWE and SWE evolution over the melt season. During the accumulation season, the differences between the modeled and estimated (posterior) SWE were more substantial. The differences appear to be due to some observed precipitation events not being captured in MERRA-2. Further investigation will determine whether additional improvement in the posterior estimates result from a calibration of uncertainty input parameters based on the in situ meteorological data. The positive preliminary results pave the way for a SWE reanalysis at the scale of the Atlas mountains using data from wide swath sensors such as Landsat and Sentinel-2.

Integration of Satellite, Global Reanalysis Data and Macroscale Hydrological Model for Drought Assessment in Sub-Tropical Region of India

NASA Astrophysics Data System (ADS)

Pandey, V.; Srivastava, P. K.

2018-04-01

Change in soil moisture regime is highly relevant for agricultural drought, which can be best analyzed in terms of Soil Moisture Deficit Index (SMDI). A macroscale hydrological model Variable Infiltration Capacity (VIC) was used to simulate the hydro-climatological fluxes including evapotranspiration, runoff, and soil moisture storage to reconstruct the severity and duration of agricultural drought over semi-arid region of India. The simulations in VIC were performed at 0.25° spatial resolution by using a set of meteorological forcing data, soil parameters and Land Use Land Cover (LULC) and vegetation parameters. For calibration and validation, soil parameters obtained from National Bureau of Soil Survey and Land Use Planning (NBSSLUP) and ESA's Climate Change Initiative soil moisture (CCI-SM) data respectively. The analysis of results demonstrates that most of the study regions (> 80 %) especially for central northern part are affected by drought condition. The year 2001, 2002, 2007, 2008 and 2009 was highly affected by agricultural drought. Due to high average and maximum temperature, we observed higher soil evaporation that reduces the surface soil moisture significantly as well as the high topographic variations; coarse soil texture and moderate to high wind speed enhanced the drying upper soil moisture layer that incorporate higher negative SMDI over the study area. These findings can also facilitate the archetype in terms of daily time step data, lengths of the simulation period, various hydro-climatological outputs and use of reasonable hydrological model.

Temporal dynamics of airborne fungi in Havana (Cuba) during dry and rainy seasons: influence of meteorological parameters

NASA Astrophysics Data System (ADS)

Almaguer, Michel; Aira, María-Jesús; Rodríguez-Rajo, F. Javier; Rojas, Teresa I.

2014-09-01

The aim of this paper was to determine for first time the influence of the main meteorological parameters on the atmospheric fungal spore concentration in Havana (Cuba). This city is characterized by a subtropical climate with two different marked annual rainfall seasons during the year: a "dry season" and a "rainy season". A nonviable volumetric methodology (Lanzoni VPPS-2000 sampler) was used to sample airborne spores. The total number of spores counted during the 2 years of study was 293,594, belonging to 30 different genera and five spore types. Relative humidity was the meteorological parameter most influencing the atmospheric concentration of the spores, mainly during the rainy season of the year. Winds coming from the SW direction also increased the spore concentration in the air. In terms of spore intradiurnal variation we found three different patterns: morning maximum values for Cladosporium, night peaks for Coprinus and Leptosphaeria, and uniform behavior throughout the whole day for Aspergillus/ Penicillium."

Assessing uncertainty in radar measurements on simplified meteorological scenarios

NASA Astrophysics Data System (ADS)

Molini, L.; Parodi, A.; Rebora, N.; Siccardi, F.

2006-02-01

A three-dimensional radar simulator model (RSM) developed by Haase (1998) is coupled with the nonhydrostatic mesoscale weather forecast model Lokal-Modell (LM). The radar simulator is able to model reflectivity measurements by using the following meteorological fields, generated by Lokal Modell, as inputs: temperature, pressure, water vapour content, cloud water content, cloud ice content, rain sedimentation flux and snow sedimentation flux. This work focuses on the assessment of some uncertainty sources associated with radar measurements: absorption by the atmospheric gases, e.g., molecular oxygen, water vapour, and nitrogen; attenuation due to the presence of a highly reflecting structure between the radar and a "target structure". RSM results for a simplified meteorological scenario, consisting of a humid updraft on a flat surface and four cells placed around it, are presented.

Impact of meteorological inflow uncertainty on tracer transport and source estimation in urban atmospheres

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

Lucas, Donald D.; Gowardhan, Akshay; Cameron-Smith, Philip

2015-08-08

Here, a computational Bayesian inverse technique is used to quantify the effects of meteorological inflow uncertainty on tracer transport and source estimation in a complex urban environment. We estimate a probability distribution of meteorological inflow by comparing wind observations to Monte Carlo simulations from the Aeolus model. Aeolus is a computational fluid dynamics model that simulates atmospheric and tracer flow around buildings and structures at meter-scale resolution. Uncertainty in the inflow is propagated through forward and backward Lagrangian dispersion calculations to determine the impact on tracer transport and the ability to estimate the release location of an unknown source. Ourmore » uncertainty methods are compared against measurements from an intensive observation period during the Joint Urban 2003 tracer release experiment conducted in Oklahoma City.« less

Implications and concerns of deep-seated disposal of hydrocarbon exploration produced water using three-dimensional contaminant transport model in Bhit Area, Dadu District of Southern Pakistan.

PubMed

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

2010-11-01

A three-dimensional contaminant transport model has been developed to simulate and monitor the migration of disposal of hydrocarbon exploration produced water in Injection well at 2,100 m depth in the Upper Cretaceous Pab sandstone, Bhit area in Dadu district of Southern Pakistan. The regional stratigraphic and structural geological framework of the area, landform characteristics, meteorological parameters, and hydrogeological milieu have been used in the model to generate the initial simulation of steady-state flow condition in the underlying aquifer's layers. The geometry of the shallow and deep-seated characteristics of the geological formations was obtained from the drilling data, electrical resistivity sounding surveys, and geophysical well-logging information. The modeling process comprised of steady-state simulation and transient simulation of the prolific groundwater system of contamination transport after 1, 10, 30 years of injection. The contaminant transport was evaluated from the bottom of the injection well, and its short- and long-term effects were determined on aquifer system lying in varying hydrogeological and geological conditions.

Numerical simulation of a meteorological regime of Pontic region

NASA Astrophysics Data System (ADS)

Toropov, P.; Silvestrova, K.

2012-04-01

The Black Sea Coast of Caucasus is one of priority in sense of meteorological researches. It is caused both strategic and economic importance of coast, and current development of an infrastructure for the winter Olympic Games «Sochi-2014». During the winter period at the Black Sea Coast of Caucasus often there are the synoptic conditions leading to occurrence of the dangerous phenomena of weather: «northeast», ice-storms, strong rains, etc. The Department of Meteorology (Moscow State University) throughout 8 years spends regular measurements on the basis of Southern Department of Institute of Oenology of the Russian Academy of Sciences in July and February. They include automatically measurements with the time resolution of 5 minutes in three points characterizing landscape or region (coast, steppe plain, top of the Markothsky ridge), measurements of flux of solar radiation, measurements an atmospheric precipitation in 8 points, which remoteness from each other - 2-3 km. The saved up material has allowed to reveal some features of a meteorological mode of coast. But an overall objective of measurements - an estimation of quality of the numerical forecast by means of «meso scale» models (for example - model WRF). The first of numerical experiments by WRF model were leaded in 2007 year and were devoted reproduction of a meteorological mode of the Black Sea coast. The second phase of experiments has been directed on reproduction the storm phenomena (Novorossiysk nord-ost). For estimation of the modeling data was choused area witch limited by coordinates 44,1 - 44,75 (latitude) and 37,6 - 39 (longitude). Estimations are spent for the basic meteorological parameters - for pressure, temperature, speed of a wind. As earlier it was marked, 8 meteorological stations are located in this territory. Their values are accepted for the standard. Errors are calculated for February 2005, 2006, 2008, 2011 years, because in these periods was marked a strong winds. As the initial data in WRF model are used FNL the analysis, pumped up each six hours. The data is in the open access (http://nomad3.ncep.noaa.gov/pub/) in a grib format. Spatial step FNL of the FNL analysis is 1 degree. In the experiment 1-3 February 2011, was made the assimilation of station data located within the territory or identified during our expeditions. It is shown that the model WRF successfully reproduces the meteorological regime the Black Sea coast. The average error of simulation n without learning station data is as follows: for a temperature of 1.5 s for wind speed - 2 m / sec. The maximum error for the temperature is 5 C, and for wind speed 10 m / sec. To experiment with the assimilation of station data the error is reduced by an average of 20%. The spatial structure of temperature and wind fields close to the actually observed. Thus, it can be argued that the model WRF can be successfully applied to numerical forecast a dangerous phenomenon, such as «Novorossiysk nord-ost». The work is done in Natural Risk Assessment Laboratory under contract G.34.31.0007.

Influence of meteorological parameters on air quality

NASA Astrophysics Data System (ADS)

Gioda, Adriana; Ventura, Luciana; Lima, Igor; Luna, Aderval

2013-04-01

The physical characterization representative of ambient air particle concentrations is becoming a topic of great interest for urban air quality monitoring and human exposure assessment. Human exposure to particulate matter of less than 2.5 µm in diameter (PM2.5) can result in a variety of adverse health impacts, including reduced lung function and premature mortality. Numerous studies have shown that fine airborne inhalable particulate matter particles (PM2.5) are more dangerous to human health than coarse particles, e.g. PM10. This study investigates meteorological parameter impacts on PM2.5 concentrations in the atmosphere of Rio de Janeiro, Brazil. Samples were collected during 24 h every six days using a high-volume sampler from six sites in the metropolitan area of Rio de Janeiro from January to December 2011. The particles mass was determined by Gravimetry. Meteorological parameters were obtained from automatic stations near the sampling sites. The average PM2.5 concentrations ranged from 9 to 32 µg/m3 for all sites, exceeding the suggested annual limit of WHO (10 µg/m3). The relationship between the effects of temperature, relative humidity, wind speed and direction and particle concentration was examined using a Principal Component Analysis (PCA) for the different sites and seasons. The results for each sampling point and season presented different principal component numbers, varying from 2 to 4, and extremely different relationships with the parameters. This clearly shows that changes in meteorological conditions exert a marked influence on air quality.

Atmospheric new particle formation at the research station Melpitz, Germany: connection with gaseous precursors and meteorological parameters

NASA Astrophysics Data System (ADS)

Größ, Johannes; Hamed, Amar; Sonntag, André; Spindler, Gerald; Elina Manninen, Hanna; Nieminen, Tuomo; Kulmala, Markku; Hõrrak, Urmas; Plass-Dülmer, Christian; Wiedensohler, Alfred; Birmili, Wolfram

2018-02-01

This paper revisits the atmospheric new particle formation (NPF) process in the polluted Central European troposphere, focusing on the connection with gas-phase precursors and meteorological parameters. Observations were made at the research station Melpitz (former East Germany) between 2008 and 2011 involving a neutral cluster and air ion spectrometer (NAIS). Particle formation events were classified by a new automated method based on the convolution integral of particle number concentration in the diameter interval 2-20 nm. To study the relevance of gaseous sulfuric acid as a precursor for nucleation, a proxy was derived on the basis of direct measurements during a 1-month campaign in May 2008. As a major result, the number concentration of freshly produced particles correlated significantly with the concentration of sulfur dioxide as the main precursor of sulfuric acid. The condensation sink, a factor potentially inhibiting NPF events, played a subordinate role only. The same held for experimentally determined ammonia concentrations. The analysis of meteorological parameters confirmed the absolute need for solar radiation to induce NPF events and demonstrated the presence of significant turbulence during those events. Due to its tight correlation with solar radiation, however, an independent effect of turbulence for NPF could not be established. Based on the diurnal evolution of aerosol, gas-phase, and meteorological parameters near the ground, we further conclude that the particle formation process is likely to start in elevated parts of the boundary layer rather than near ground level.

SIMULATION OF SULFATE AEROSOL IN EAST ASIA USING MODELS-3/CMAQ WITH RAMS METEOROLOGICAL DATA

EPA Science Inventory

The present study attempts to address a few challenges in utilizing the flexibility of the Models-3 Community Multiscale Air Quality (CMAQ) modeling system. We apply the CMAQ system with the meteorological data provided by the Regional Atmospheric Modeling System (RAMS) and to a...

USING MM5 VERSION 2 WITH CMAQ AND MODELS-3, A USER'S GUIDE AND TUTORIAL

EPA Science Inventory

Meteorological data are important in many of the processes simulated in the Community Multi-Scale Air Quality (CMAQ) model and the Models-3 framework. The first meteorology model that has been selected and evaluated with CMAQ is the Fifth-Generation Pennsylvania State University...

INTRODUCTION OF URBAN CANOPY PARAMETERIZATION INTO MM5 TO SIMULATE URBAN METEOROLOGY AT NEIGHBORHOOD SCALE

EPA Science Inventory

Since most of the primary atmospheric pollutants are emitted inside the roughness sub-layer (RSL) and consequently the first chemical reactions and dispersion occur in this layer, it is necessary to generate detailed meteorological fields inside the RSL to perform air quality m...

New York Bight Study. Report 1. Hydrodynamic Modeling

DTIC Science & Technology

1994-08-01

function of time. Values of these parameters, averaged daily, were computed from meteorological data recorded at the John F. Kennedy ( JFK ) Airport for...Island Sound "exchange coefficient values were obtained as before from meteorological data collected at the JFK Airport . They are shown in Figures 62-63

A Lagrangian particle model to predict the airborne spread of foot-and-mouth disease virus

NASA Astrophysics Data System (ADS)

Mayer, D.; Reiczigel, J.; Rubel, F.

Airborne spread of bioaerosols in the boundary layer over a complex terrain is simulated using a Lagrangian particle model, and applied to modelling the airborne spread of foot-and-mouth disease (FMD) virus. Two case studies are made with study domains located in a hilly region in the northwest of the Styrian capital Graz, the second largest town in Austria. Mountainous terrain as well as inhomogeneous and time varying meteorological conditions prevent from application of so far used Gaussian dispersion models, while the proposed model can handle these realistically. In the model, trajectories of several thousands of particles are computed and the distribution of virus concentration near the ground is calculated. This allows to assess risk of infection areas with respect to animal species of interest, such as cattle, swine or sheep. Meteorological input data like wind field and other variables necessary to compute turbulence were taken from the new pre-operational version of the non-hydrostatic numerical weather prediction model LMK ( Lokal-Modell-Kürzestfrist) running at the German weather service DWD ( Deutscher Wetterdienst). The LMK model provides meteorological parameters with a spatial resolution of about 2.8 km. To account for the spatial resolution of 400 m used by the Lagrangian particle model, the initial wind field is interpolated upon the finer grid by a mass consistent interpolation method. Case studies depict a significant influence of local wind systems on the spread of virus. Higher virus concentrations at the upwind side of the hills and marginal concentrations in the lee are well observable, as well as canalization effects by valleys. The study demonstrates that the Lagrangian particle model is an appropriate tool for risk assessment of airborne spread of virus by taking into account the realistic orographic and meteorological conditions.

Saskatchewan Forest Fire Control Centre Surface Meteorological Data

NASA Technical Reports Server (NTRS)

Hall, Forrest G. (Editor); Newcomer, Jeffrey A. (Editor); Funk, Barry; Strub, Richard

2000-01-01

The Saskatchewan Forest Fire Control Centre (SFFCC) provided surface meteorological data to BOREAS from its archive. This data set contains hourly surface meteorological data from 18 of the Meteorological stations located across Saskatchewan. Included in these data are parameters of date, time, temperature, relative humidity, wind direction, wind speed, and precipitation. Temporally, the data cover the period of May through September of 1994 and 1995. The data are provided in comma-delimited ASCII files, and are classified as AFM-Staff data. The data files are available on a CD-ROM (see document number 20010000884), or from the Oak Ridge National Laboratory (ORNL) Distributed Active Archive Center (DAAC).

On the monitoring and prediction of flash floods in small and medium-sized catchments - the EXTRUSO project

NASA Astrophysics Data System (ADS)

Wiemann, Stefan; Eltner, Anette; Sardemann, Hannes; Spieler, Diana; Singer, Thomas; Thanh Luong, Thi; Janabi, Firas Al; Schütze, Niels; Bernard, Lars; Bernhofer, Christian; Maas, Hans-Gerd

2017-04-01

Flash floods regularly cause severe socio-economic damage worldwide. In parallel, climate change is very likely to increase the number of such events, due to an increasing frequency of extreme precipitation events (EASAC 2013). Whereas recent work primarily addresses the resilience of large catchment areas, the major impact of hydro-meteorological extremes caused by heavy precipitation is on small areas. Those are very difficult to observe and predict, due to sparse monitoring networks and only few means for hydro-meteorological modelling, especially in small catchment areas. The objective of the EXTRUSO project is to identify and implement appropriate means to close this gap by an interdisciplinary approach, combining comprehensive research expertise from meteorology, hydrology, photogrammetry and geoinformatics. The project targets innovative techniques for achieving spatio-temporal densified monitoring and simulations for the analysis, prediction and warning of local hydro-meteorological extreme events. The following four aspects are of particular interest: 1. The monitoring, analysis and combination of relevant hydro-meteorological parameters from various sources, including existing monitoring networks, ground radar, specific low-cost sensors and crowdsourcing. 2. The determination of relevant hydro-morphological parameters from different photogrammetric sensors (e.g. camera, laser scanner) and sensor platforms (e.g. UAV (unmanned aerial vehicle) and UWV (unmanned water vehicle)). 3. The continuous hydro-meteorological modelling of precipitation, soil moisture and water flows by means of conceptual and data-driven modelling. 4. The development of a collaborative, web-based service infrastructure as an information and communication point, especially in the case of an extreme event. There are three major applications for the planned information system: First, the warning of local extreme events for the population in potentially affected areas, second, the support for decision makers and emergency responders in the case of an event and, third, the development of open, interoperable tools for other researchers to be applied and further developed. The test area of the project is the Free State of Saxony (Germany) with a number of small and medium catchment areas. However, the whole system, comprising models, tools and sensor setups, is planned to be transferred and tested in other areas, within and outside Europe, as well. The team working on the project consists of eight researchers, including five PhD students and three postdocs. The EXTRUSO project is funded by the European Social Fund (ESF grant nr. 100270097) with a project duration of three years until June 2019. EASAC (2013): Trends in extreme weather events in Europe: implications for national and European Union adaption strategies. European Academies Science Advisory Council. Policy report 22, November 2013 The EXTRUSO project is funded by the European Social Fund (ESF), grant nr. 100270097

Impact of assimilation of conventional and satellite meteorological observations on the numerical simulation of a Bay of Bengal Tropical Cyclone of November 2008 near Tamilnadu using WRF model

NASA Astrophysics Data System (ADS)

Srinivas, C. V.; Yesubabu, V.; Venkatesan, R.; Ramarkrishna, S. S. V. S.

2010-12-01

The objective of this study is to examine the impact of assimilation of conventional and satellite data on the prediction of a severe cyclonic storm that formed in the Bay of Bengal during November 2008 with the four-dimensional data assimilation (FDDA) technique. The Weather Research and Forecasting (WRF ARW) model was used to study the structure, evolution, and intensification of the storm. Five sets of numerical simulations were performed using the WRF. In the first one, called Control run, the National Centers for Environmental Prediction (NCEP) Final Analysis (FNL) was used for the initial and boundary conditions. In the remaining experiments available observations were used to obtain an improved analysis and FDDA grid nudging was performed for a pre-forecast period of 24 h. The second simulation (FDDAALL) was performed with all the data of the Quick Scatterometer (QSCAT), Special Sensor Microwave Imager (SSM/I) winds, conventional surface, and upper air meteorological observations. QSCAT wind alone was used in the third simulation (FDDAQSCAT), the SSM/I wind alone in the fourth (FDDASSMI) and the conventional observations alone in the fifth (FDDAAWS). The FDDAALL with assimilation of all observations, produced sea level pressure pattern closely agreeing with the analysis. Examination of various parameters indicated that the Control run over predicted the intensity of the storm with large error in its track and landfall position. The assimilation experiment with QSCAT winds performed marginally better than the one with SSM/I winds due to better representation of surface wind vectors. The FDDAALL outperformed all the simulations for the intensity, movement, and rainfall associated with the storm. Results suggest that the combination of land-based surface, upper air observations along with satellite winds for assimilation produced better prediction than the assimilation with individual data sets.

Evaluation and uncertainty analysis of regional-scale CLM4.5 net carbon flux estimates

NASA Astrophysics Data System (ADS)

Post, Hanna; Hendricks Franssen, Harrie-Jan; Han, Xujun; Baatz, Roland; Montzka, Carsten; Schmidt, Marius; Vereecken, Harry

2018-01-01

Modeling net ecosystem exchange (NEE) at the regional scale with land surface models (LSMs) is relevant for the estimation of regional carbon balances, but studies on it are very limited. Furthermore, it is essential to better understand and quantify the uncertainty of LSMs in order to improve them. An important key variable in this respect is the prognostic leaf area index (LAI), which is very sensitive to forcing data and strongly affects the modeled NEE. We applied the Community Land Model (CLM4.5-BGC) to the Rur catchment in western Germany and compared estimated and default ecological key parameters for modeling carbon fluxes and LAI. The parameter estimates were previously estimated with the Markov chain Monte Carlo (MCMC) approach DREAM(zs) for four of the most widespread plant functional types in the catchment. It was found that the catchment-scale annual NEE was strongly positive with default parameter values but negative (and closer to observations) with the estimated values. Thus, the estimation of CLM parameters with local NEE observations can be highly relevant when determining regional carbon balances. To obtain a more comprehensive picture of model uncertainty, CLM ensembles were set up with perturbed meteorological input and uncertain initial states in addition to uncertain parameters. C3 grass and C3 crops were particularly sensitive to the perturbed meteorological input, which resulted in a strong increase in the standard deviation of the annual NEE sum (σ ∑ NEE) for the different ensemble members from ˜ 2 to 3 g C m-2 yr-1 (with uncertain parameters) to ˜ 45 g C m-2 yr-1 (C3 grass) and ˜ 75 g C m-2 yr-1 (C3 crops) with perturbed forcings. This increase in uncertainty is related to the impact of the meteorological forcings on leaf onset and senescence, and enhanced/reduced drought stress related to perturbation of precipitation. The NEE uncertainty for the forest plant functional type (PFT) was considerably lower (σ ∑ NEE ˜ 4.0-13.5 g C m-2 yr-1 with perturbed parameters, meteorological forcings and initial states). We conclude that LAI and NEE uncertainty with CLM is clearly underestimated if uncertain meteorological forcings and initial states are not taken into account.

An Extreme Meteorological Events Analysis For Nuclear Power Plant (NPP) Siting Project at Bangka Island, Indonesia

NASA Astrophysics Data System (ADS)

Septiadi, Deni; S, Yarianto Sugeng B.; Sriyana; Anzhar, Kurnia; Suntoko, Hadi

2018-03-01

The potential sources of meteorological phenomena in Nuclear Power Plant (NPP) area of interest are identified and the extreme values of the possible resulting hazards associated which such phenomena are evaluated to derive the appropriate design bases for the NPP. The appropriate design bases shall be determined according to the Nuclear Energy Regulatory Agency (Bapeten) applicable regulations, which presently do not indicate quantitative criteria for purposes of determining the design bases for meteorological hazards. These meteorological investigations are also carried out to evaluate the regional and site specific meteorological parameters which affect the transport and dispersion of radioactive effluents on the environment of the region around the NPP site. The meteorological hazards are to be monitored and assessed periodically over the lifetime of the plant to ensure that consistency with the design assumptions is maintained throughout the full lifetime of the facility.

Use of a scenario-neutral approach to identify the key hydro-meteorological attributes that impact runoff from a natural catchment

NASA Astrophysics Data System (ADS)

Guo, Danlu; Westra, Seth; Maier, Holger R.

2017-11-01

Scenario-neutral approaches are being used increasingly for assessing the potential impact of climate change on water resource systems, as these approaches allow the performance of these systems to be evaluated independently of climate change projections. However, practical implementations of these approaches are still scarce, with a key limitation being the difficulty of generating a range of plausible future time series of hydro-meteorological data. In this study we apply a recently developed inverse stochastic generation approach to support the scenario-neutral analysis, and thus identify the key hydro-meteorological variables to which the system is most sensitive. The stochastic generator simulates synthetic hydro-meteorological time series that represent plausible future changes in (1) the average, extremes and seasonal patterns of rainfall; and (2) the average values of temperature (Ta), relative humidity (RH) and wind speed (uz) as variables that drive PET. These hydro-meteorological time series are then fed through a conceptual rainfall-runoff model to simulate the potential changes in runoff as a function of changes in the hydro-meteorological variables, and runoff sensitivity is assessed with both correlation and Sobol' sensitivity analyses. The method was applied to a case study catchment in South Australia, and the results showed that the most important hydro-meteorological attributes for runoff were winter rainfall followed by the annual average rainfall, while the PET-related meteorological variables had comparatively little impact. The high importance of winter rainfall can be related to the winter-dominated nature of both the rainfall and runoff regimes in this catchment. The approach illustrated in this study can greatly enhance our understanding of the key hydro-meteorological attributes and processes that are likely to drive catchment runoff under a changing climate, thus enabling the design of tailored climate impact assessments to specific water resource systems.

The Wake Vortex Prediction and Monitoring System WSVBS

NASA Astrophysics Data System (ADS)

Gerz, T.; Holzäpfel, F.

2009-09-01

Design and performance of the Wake Vortex Prediction and Monitoring System WSVBS are described. The WSVBS has been developed to tactically increase airport capacity for approach and landing on closely-spaced parallel runways. It is thought to dynamically adjust aircraft separations dependent on weather conditions and the resulting wake vortex behaviour without compromising safety. The WSVBS consists of components that consider meteorological conditions, aircraft glide path adherence, aircraft parameter combinations representing aircraft weight categories, the resulting wake-vortex behaviour, the surrounding safety areas, wake vortex monitoring, and the integration of the predictions into the arrival manager. The WSVBS has been designed and applied to Frankfurt Airport. However, its components are generic and can well be adjusted to any runway system and or airport location. The prediction horizon is larger than 45 min (as required by air traffic control) and updated every 10 minutes. It predicts the concepts of operations and procedures established by DFS and it further predicts additional temporal separations for in-trail traffic. A specific feature of the WSVBS is the usage of both measured and predicted meteorological quantities as input to wake vortex prediction. In ground proximity where the probability to encounter wake vortices is highest, the wake predictor employs measured environmental parameters that yield superior prediction results. For the less critical part aloft, which can not be monitored completely by instrumentation, the meteorological parameters are taken from dedicated numerical terminal weather predictions. The wake vortex model predicts envelopes for vortex position and strength which implicitly consider the quality of the meteorological input data. This feature is achieved by a training procedure which employs statistics of measured and predicted meteorological parameters and the resulting wake vortex behaviour. The WSVBS combines various conservative elements that presumably lead to a very high overall safety level of the WSVBS. The combination of these conservative measures certainly leads to a very high but currently unknown overall safety. Once the methodology of a comprehensive risk analysis will be established, it is planned to adjust all components to appropriate and consistent confidence levels. The WSVBS has demonstrated its functionality at Frankfurt airport during 66 days in the period from 18/12/06 until 28/02/07. The performance test indicates that (i) the system ran stable - no forecast breakdowns occurred, (ii) aircraft separations could have been reduced in 75% of the time compared to ICAO standards, (iii) reduced separation procedures could have been continuously applied for at least several tens of minutes and up to several hours occasionally, (iv) the predictions were correct as for about 1100 landings observed during 16 days no warnings occurred from the LIDAR. Fast-time simulations reveal that adapted concepts of operation yield significant reductions in delay and/or an increase in capacity to 3% taking into account the real traffic mix and operational constraints in the period of one month. Before the WSVBS can be handed over for final adaptations to become a customized fully operational system some further steps are planned. A risk analysis needs to be pursued to convince all stakeholders of the usefulness and capabilities of the system.

Correlation between isotopic and meteorological parameters in Italian wines: a local-scale approach.

PubMed

Aghemo, Costanza; Albertino, Andrea; Gobetto, Roberto; Spanna, Federico

2011-08-30

Since the beginning of the 1980s deuterium nuclear magnetic resonance and carbon-13 mass spectrometry have proved to be reliable techniques for detecting adulteration and for classifying natural products by their geographic origin. Scientific literature has so far mainly focused on data acquired at regional level where isotopic parameters are correlated to climatic mean data relative to large territories. Nebbiolo and Barbera wine samples of various vintages and from different areas within the Piedmont region (northern Italy) were analysed using SNIF-NMR and GC-C-IRMS and a large set of meteorological parameters were recorded by means of weather stations placed in fields where the grapes were grown. Correlations between isotopic ((2)H and (13)C) data and several climatic parameters at a local level (mean temperature, total rainfall, mean humidity and thermal sums) were attempted and some linear correlations were found. Mean temperature and total rainfall were found to be correlated to isotopic ((2)H and (13)C) abundance in linear direct and inverse proportions respectively. Lower or no correlations between deuterium and carbon-13 abundances and other meteorological parameters such as mean humidity and thermal sums were found. Moreover, wines produced from different grape varieties in the same grape field showed significantly different isotopic values. Copyright © 2011 Society of Chemical Industry.

Multivariate space - time analysis of PRE-STORM precipitation

NASA Technical Reports Server (NTRS)

Polyak, Ilya; North, Gerald R.; Valdes, Juan B.

1994-01-01

This paper presents the methodologies and results of the multivariate modeling and two-dimensional spectral and correlation analysis of PRE-STORM rainfall gauge data. Estimated parameters of the models for the specific spatial averages clearly indicate the eastward and southeastward wave propagation of rainfall fluctuations. A relationship between the coefficients of the diffusion equation and the parameters of the stochastic model of rainfall fluctuations is derived that leads directly to the exclusive use of rainfall data to estimate advection speed (about 12 m/s) as well as other coefficients of the diffusion equation of the corresponding fields. The statistical methodology developed here can be used for confirmation of physical models by comparison of the corresponding second-moment statistics of the observed and simulated data, for generating multiple samples of any size, for solving the inverse problem of the hydrodynamic equations, and for application in some other areas of meteorological and climatological data analysis and modeling.

Feedbacks between air pollution and weather, Part 1: Effects on weather

NASA Astrophysics Data System (ADS)

Makar, P. A.; Gong, W.; Milbrandt, J.; Hogrefe, C.; Zhang, Y.; Curci, G.; Žabkar, R.; Im, U.; Balzarini, A.; Baró, R.; Bianconi, R.; Cheung, P.; Forkel, R.; Gravel, S.; Hirtl, M.; Honzak, L.; Hou, A.; Jiménez-Guerrero, P.; Langer, M.; Moran, M. D.; Pabla, B.; Pérez, J. L.; Pirovano, G.; San José, R.; Tuccella, P.; Werhahn, J.; Zhang, J.; Galmarini, S.

2015-08-01

The meteorological predictions of fully coupled air-quality models running in ;feedback; versus ;no-feedback; simulations were compared against each other and observations as part of Phase 2 of the Air Quality Model Evaluation International Initiative. In the ;no-feedback; mode, the aerosol direct and indirect effects were disabled, with the models reverting to either climatologies of aerosol properties, or a no-aerosol weather simulation. In the ;feedback; mode, the model-generated aerosols were allowed to modify the radiative transfer and/or cloud formation parameterizations of the respective models. Annual simulations with and without feedbacks were conducted on domains over North America for the years 2006 and 2010, and over Europe for the year 2010. The incorporation of feedbacks was found to result in systematic changes to forecast predictions of meteorological variables, both in time and space, with the largest impacts occurring in the summer and near large sources of pollution. Models incorporating only the aerosol direct effect predicted feedback-induced reductions in temperature, surface downward and upward shortwave radiation, precipitation and PBL height, and increased upward shortwave radiation, in both Europe and North America. The feedback response of models incorporating both the aerosol direct and indirect effects varied across models, suggesting the details of implementation of the indirect effect have a large impact on model results, and hence should be a focus for future research. The feedback response of models incorporating both direct and indirect effects was also consistently larger in magnitude to that of models incorporating the direct effect alone, implying that the indirect effect may be the dominant process. Comparisons across modelling platforms suggested that direct and indirect effect feedbacks may often act in competition: the sign of residual changes associated with feedbacks often changed between those models incorporating the direct effect alone versus those incorporating both feedback processes. Model comparisons to observations for no-feedback and feedback implementations of the same model showed that differences in performance between models were larger than the performance changes associated with implementing feedbacks within a given model. However, feedback implementation was shown to result in improved forecasts of meteorological parameters such as the 2 m surface temperature and precipitation. These findings suggest that meteorological forecasts may be improved through the use of fully coupled feedback models, or through incorporation of improved climatologies of aerosol properties, the latter designed to include spatial, temporal and aerosol size and/or speciation variations.

Simulation of Atmospheric Dispersion of Elevated Releases from Point Sources in Mississippi Gulf Coast with Different Meteorological Data

PubMed Central

Yerramilli, Anjaneyulu; Srinivas, Challa Venkata; Dasari, Hari Prasad; Tuluri, Francis; White, Loren D.; Baham, Julius M.; Young, John H.; Hughes, Robert; Patrick, Chuck; Hardy, Mark G.; Swanier, Shelton J.

2009-01-01

Atmospheric dispersion calculations are made using the HYSPLIT Particle Dispersion Model for studying the transport and dispersion of air-borne releases from point elevated sources in the Mississippi Gulf coastal region. Simulations are performed separately with three meteorological data sets having different spatial and temporal resolution for a typical summer period in 1–3 June 2006 representing a weak synoptic condition. The first two data are the NCEP global and regional analyses (FNL, EDAS) while the third is a meso-scale simulation generated using the Weather Research and Forecasting model with nested domains at a fine resolution of 4 km. The meso-scale model results show significant temporal and spatial variations in the meteorological fields as a result of the combined influences of the land-sea breeze circulation, the large scale flow field and diurnal alteration in the mixing depth across the coast. The model predicted SO2 concentrations showed that the trajectory and the concentration distribution varied in the three cases of input data. While calculations with FNL data show an overall higher correlation, there is a significant positive bias during daytime and negative bias during night time. Calculations with EDAS fields are significantly below the observations during both daytime and night time though plume behavior follows the coastal circulation. The diurnal plume behavior and its distribution are better simulated using the mesoscale WRF meteorological fields in the coastal environment suggesting its suitability for pollution dispersion impact assessment in the local scale. Results of different cases of simulation, comparison with observations, correlation and bias in each case are presented. PMID:19440433

Temperature lapse rate as an adjunct to wind shear detection

NASA Technical Reports Server (NTRS)

Zweifil, Terry

1991-01-01

Several meteorological parameters were examined to determine if measurable atmospheric conditions can improve windshear detection devices. Lapse rate, the temperature change with altitude, shows promise as being an important parameter in the prediction of severe wind shears. It is easily measured from existing aircraft instrumentation, and it can be important indicator of convective activity including thunderstorms and microbursts. The meteorological theory behind lapse rate measurement is briefly reviewed, and and FAA certified system is described that is currently implemented in the Honeywell Wind Shear Detection and Guidance System.

Modeling Vegetation Growth Impact on Groundwater Recharge

NASA Astrophysics Data System (ADS)

Anurag, H.; Ng, G. H. C.; Tipping, R.

2017-12-01

Vegetation growth is affected by variability in climate and land-cover / land-use over a range of temporal and spatial scales. Vegetation also modifies water budget through interception and evapotranspiration and thus has a significant impact on groundwater recharge. Most groundwater recharge assessments represent vegetation using specified, static parameter, such as for leaf-area-index, but this neglects the effect of vegetation dynamics on recharge estimates. Our study addresses this gap by including vegetation growth in model simulations of recharge. We use NCAR's Community Land Model v4.5 with its BGC module (BGC is the new CLM4.5 biogeochemistry). It integrates prognostic vegetation growth with land-surface and subsurface hydrological processes and can thus capture the effect of vegetation on groundwater. A challenge, however, is the need to resolve uncertainties in model inputs ranging from vegetation growth parameters all the way down to the water table. We have compiled diverse data spanning meteorological inputs to subsurface geology and use these to implement ensemble model simulations to evaluate the possible effects of dynamic vegetation growth (versus specified, static vegetation parameterizations) on estimating groundwater recharge. We present preliminary results for select data-intensive test locations throughout the state of Minnesota (USA), which has a sharp east-west precipitation gradient that makes it an apt testbed for examining ecohydrologic relationships across different temperate climatic settings and ecosystems. Using the ensemble simulations, we examine the effect of seasonal to interannual variability of vegetation growth on recharge and water table depths, which has implications for predicting the combined impact of climate, vegetation, and geology on groundwater resources. Future work will include distributed model simulations over the entire state, as well as conditioning uncertain vegetation and subsurface parameters on remote sensing data and statewide water table records using data assimilation.

Evaluation of near surface ozone and particulate matter in air quality simulations driven by dynamically downscaled historical meteorological fields

EPA Science Inventory

In this study, techniques typically used for future air quality projections are applied to a historical 11-year period to assess the performance of the modeling system when the driving meteorological conditions are obtained using dynamical downscaling of coarse-scale fields witho...

Flight investigation of a vertical-velocity command system for VTOL aircraft

NASA Technical Reports Server (NTRS)

Kelly, J. R.; Niessen, F. R.; Yenni, K. R.; Person, L. H., Jr.

1977-01-01

A flight investigation was undertaken to assess the potential benefits afforded by a vertical-velocity command system (VVCS) for VTOL (vertical take-off and landing) aircraft. This augmentation system was conceived primarily as a means of lowering pilot workload during decelerating approaches to a hover and/or landing under category III instrument meteorological conditions. The scope of the investigation included a determination of acceptable system parameters, a visual flight evaluation, and an instrument flight evaluation which employed a 10 deg, decelerating, simulated instrument approach task. The results indicated that the VVCS, which decouples the pitch and vertical degrees of freedom, provides more accurate glide-path tracking and a lower pilot workload than does the unaugmented system.

Validation of Soil Water Content Estimation Method on Agricultural Regions in South Korea

NASA Astrophysics Data System (ADS)

Shin, Y.; Kim, M.

2016-12-01

The continuous water stress caused by decrease of soil water has a direct influence to the crop growth in a upland crop area. The agricultural drought is occured if water requirement is not supplied timely in crop growh process. It is more important to understand the soil characteristics for high accuracy soil moisture estimation because of the soil water contents largely depends on soil properties. The RDA(Rural Development Administration) has provided real-time soil moisture observations corrected for 71 points in the South Korea. In this study, we developed a soil water content estimation method that considered soil hydraulic parameters for the observation points of soil water content in agricultural regions operated by the RDA. SWAP(Soil-Water-Atmosphere-Plant) model was used in the estimation of soil water contents. The soil hydraulic parameters that is the input data of the SWAP model were estimated using the ROSETTA model developed by the U.S. Department of Agriculture(USDA). Meteorological data observed from AWS(Automatic Weather Station) were used including daily maximum temperature(°), daily minimum temperature(°), relative humidity(%), solar radiation, wind speed and precipitation data. We choosed 56 stations there are no missing of meteorological data and have soil physical properties. For the verification of soil water content estimation method, we used Haenam KoFlux observation data that are observed long-term soil water contents over 2009-2015(2014 missing) years. In the case of 2015, there are good reproducibility between observation of soil water contents and results of SWAP model simulation with R2=0.72, RMSE=0.026 and TCC=0.849. In the case of precipitation event, the simulation results were slightly overestimated more than observation. However there are good reproducibility in the case of soil water reduction due to continuous non-precipitation periods. We have simulated the soil water contents of the 56 stations that being operated in the RDA from 4 January 2015 to 31 October 2015 using the SWAP model. The environmental setting of SWAP modle according to the station applied it equally. The results showed a significant difference to the reproducibility according to the observation station.

Multi-Index Attribution of Beijing's 2013 "Airpocalypse"

NASA Astrophysics Data System (ADS)

Callahan, C.; Diffenbaugh, N. S.; Horton, D. E.

2017-12-01

Poor air quality causes 2 to 4 million premature deaths per year globally. Individual high-impact events, like Beijing's January 2013 "airpocalypse," have drawn significant attention, as they have demonstrated that short-lived air quality events can have outsized effects on public health and economic vitality. Poor air quality events are the result of emission of pollutants and the meteorological conditions favorable to their accumulation in the near-surface environment. Accumulation occurs when pollutants are not dispersed or scavenged from the atmosphere. The most important meteorological precursors of these conditions include lack of precipitation, low wind speeds, and vertical temperature inversions. Recent reports of extreme air quality, in conjunction with projected future changes in some meteorological air quality indices, raise the question: have the meteorological conditions that shape air quality changed in frequency, intensity, or duration over the observational era? Here we assess whether anthropogenic climate change has altered meteorological conditions conducive to poor air quality. To gain a more complete picture of the effect of anthropogenic change on air quality, we use three indices that quantify poor air quality: the Pollution Potential Index (Zou et al, 2017), which measures temperature inversions and surface wind speeds, the Haze Weather Index (Cai et al, 2017), which measures temperature inversions and mid-level wind speeds, and the Air Stagnation Index (Horton et al, 2014), which measures precipitation, surface wind speeds, and mid-level wind speeds. Drawing on the attribution methods of Diffenbaugh et al (2017), we assess the contribution of observed meteorological trends to the magnitude of air quality events, the return interval of events in the observational record, historical simulated climate, and pre-industrial simulated climate, and the probability of the observed trend in historical and pre-industrial simulated climates. Particular attention is paid to Beijing's January 2013 event, but we also analyze air quality meteorology on a global scale. This work provides a framework for both further understanding the role of climate change in particular air quality events and for expanding the scope of extreme event attribution beyond its current applications.

Verification of ECMWF System 4 for seasonal hydrological forecasting in a northern climate

NASA Astrophysics Data System (ADS)

Bazile, Rachel; Boucher, Marie-Amélie; Perreault, Luc; Leconte, Robert

2017-11-01

Hydropower production requires optimal dam and reservoir management to prevent flooding damage and avoid operation losses. In a northern climate, where spring freshet constitutes the main inflow volume, seasonal forecasts can help to establish a yearly strategy. Long-term hydrological forecasts often rely on past observations of streamflow or meteorological data. Another alternative is to use ensemble meteorological forecasts produced by climate models. In this paper, those produced by the ECMWF (European Centre for Medium-Range Forecast) System 4 are examined and bias is characterized. Bias correction, through the linear scaling method, improves the performance of the raw ensemble meteorological forecasts in terms of continuous ranked probability score (CRPS). Then, three seasonal ensemble hydrological forecasting systems are compared: (1) the climatology of simulated streamflow, (2) the ensemble hydrological forecasts based on climatology (ESP) and (3) the hydrological forecasts based on bias-corrected ensemble meteorological forecasts from System 4 (corr-DSP). Simulated streamflow computed using observed meteorological data is used as benchmark. Accounting for initial conditions is valuable even for long-term forecasts. ESP and corr-DSP both outperform the climatology of simulated streamflow for lead times from 1 to 5 months depending on the season and watershed. Integrating information about future meteorological conditions also improves monthly volume forecasts. For the 1-month lead time, a gain exists for almost all watersheds during winter, summer and fall. However, volume forecasts performance for spring varies from one watershed to another. For most of them, the performance is close to the performance of ESP. For longer lead times, the CRPS skill score is mostly in favour of ESP, even if for many watersheds, ESP and corr-DSP have comparable skill. Corr-DSP appears quite reliable but, in some cases, under-dispersion or bias is observed. A more complex bias-correction method should be further investigated to remedy this weakness and take more advantage of the ensemble forecasts produced by the climate model. Overall, in this study, bias-corrected ensemble meteorological forecasts appear to be an interesting source of information for hydrological forecasting for lead times up to 1 month. They could also complement ESP for longer lead times.

Radicals and Reservoirs in the GMI Chemistry and Transport Model: Comparison to Measurements

NASA Technical Reports Server (NTRS)

Douglass, Anne R.; Stolarski, Richard S.; Strahan, Susan E.; Connell, Peter S.

2004-01-01

We have used a three-dimensional chemistry and transport model (CTM), developed under the Global Modeling Initiative (GMI), to carry out two simulations of the composition of the stratosphere under changing halogen loading for 1995 through 2030. The two simulations differ only in that one uses meteorological fields from a general circulation model while the other uses meteorological fields from a data assimilation system. A single year's winds and temperatures are repeated for each 36-year simulation. We compare results from these two simulations with an extensive collection of data from satellite and ground-based measurements for 1993-2000. Comparisons of simulated fields with observations of radical and reservoir species for some of the major ozone-destroying compounds are of similar quality for both simulations. Differences in the upper stratosphere, caused by transport of total reactive nitrogen and methane, impact the balance among the ozone loss processes and the sensitivity of the two simulations to the change in composition.

Extended-Range High-Resolution Dynamical Downscaling over a Continental-Scale Domain

NASA Astrophysics Data System (ADS)

Husain, S. Z.; Separovic, L.; Yu, W.; Fernig, D.

2014-12-01

High-resolution mesoscale simulations, when applied for downscaling meteorological fields over large spatial domains and for extended time periods, can provide valuable information for many practical application scenarios including the weather-dependent renewable energy industry. In the present study, a strategy has been proposed to dynamically downscale coarse-resolution meteorological fields from Environment Canada's regional analyses for a period of multiple years over the entire Canadian territory. The study demonstrates that a continuous mesoscale simulation over the entire domain is the most suitable approach in this regard. Large-scale deviations in the different meteorological fields pose the biggest challenge for extended-range simulations over continental scale domains, and the enforcement of the lateral boundary conditions is not sufficient to restrict such deviations. A scheme has therefore been developed to spectrally nudge the simulated high-resolution meteorological fields at the different model vertical levels towards those embedded in the coarse-resolution driving fields derived from the regional analyses. A series of experiments were carried out to determine the optimal nudging strategy including the appropriate nudging length scales, nudging vertical profile and temporal relaxation. A forcing strategy based on grid nudging of the different surface fields, including surface temperature, soil-moisture, and snow conditions, towards their expected values obtained from a high-resolution offline surface scheme was also devised to limit any considerable deviation in the evolving surface fields due to extended-range temporal integrations. The study shows that ensuring large-scale atmospheric similarities helps to deliver near-surface statistical scores for temperature, dew point temperature and horizontal wind speed that are better or comparable to the operational regional forecasts issued by Environment Canada. Furthermore, the meteorological fields resulting from the proposed downscaling strategy have significantly improved spatiotemporal variance compared to those from the operational forecasts, and any time series generated from the downscaled fields do not suffer from discontinuities due to switching between the consecutive forecasts.

PREDICTIONS OF DISPERSION AND DEPOSITION OF FALLOUT FROM NUCLEAR TESTING USING THE NOAA-HYSPLIT METEOROLOGICAL MODEL

PubMed Central

Moroz, Brian E.; Beck, Harold L.; Bouville, André; Simon, Steven L.

2013-01-01

The NOAA Hybrid Single-Particle Lagrangian Integrated Trajectory Model (HYSPLIT) was evaluated as a research tool to simulate the dispersion and deposition of radioactive fallout from nuclear tests. Model-based estimates of fallout can be valuable for use in the reconstruction of past exposures from nuclear testing, particularly, where little historical fallout monitoring data is available. The ability to make reliable predictions about fallout deposition could also have significant importance for nuclear events in the future. We evaluated the accuracy of the HYSPLIT-predicted geographic patterns of deposition by comparing those predictions against known deposition patterns following specific nuclear tests with an emphasis on nuclear weapons tests conducted in the Marshall Islands. We evaluated the ability of the computer code to quantitatively predict the proportion of fallout particles of specific sizes deposited at specific locations as well as their time of transport. In our simulations of fallout from past nuclear tests, historical meteorological data were used from a reanalysis conducted jointly by the National Centers for Environmental Prediction (NCEP) and the National Center for Atmospheric Research (NCAR). We used a systematic approach in testing the HYSPLIT model by simulating the release of a range of particles sizes from a range of altitudes and evaluating the number and location of particles deposited. Our findings suggest that the quantity and quality of meteorological data are the most important factors for accurate fallout predictions and that when satisfactory meteorological input data are used, HYSPLIT can produce relatively accurate deposition patterns and fallout arrival times. Furthermore, when no other measurement data are available, HYSPLIT can be used to indicate whether or not fallout might have occurred at a given location and provide, at minimum, crude quantitative estimates of the magnitude of the deposited activity. A variety of simulations of the deposition of fallout from atmospheric nuclear tests conducted in the Marshall Islands, at the Nevada Test Site (USA), and at the Semipalatinsk Nuclear Test Site (Kazakhstan) were performed using reanalysis data composed of historic meteorological observations. The results of the Marshall Islands simulations were used in a limited fashion to support the dose reconstruction described in companion papers within this volume. PMID:20622555

A Comparison of Observed and Simulated 1990 – 2010 U.S. Ozone Trends

EPA Science Inventory

In this study, we analyze ozone concentrations from long-term (1990 – 2010) WRF-CMAQ simulations driven by year specific meteorology and emissions. These simulations allow us to compare observed and simulated ozone trends in order to evaluate the model’s ability to pr...

Effects of temperature on flood forecasting: analysis of an operative case study in Alpine basins

NASA Astrophysics Data System (ADS)

Ceppi, A.; Ravazzani, G.; Salandin, A.; Rabuffetti, D.; Montani, A.; Borgonovo, E.; Mancini, M.

2013-04-01

In recent years the interest in the forecast and prevention of natural hazards related to hydro-meteorological events has increased the challenge for numerical weather modelling, in particular for limited area models, to improve the quantitative precipitation forecasts (QPF) for hydrological purposes. After the encouraging results obtained in the MAP D-PHASE Project, we decided to devote further analyses to show recent improvements in the operational use of hydro-meteorological chains, and above all to better investigate the key role played by temperature during snowy precipitation. In this study we present a reanalysis simulation of one meteorological event, which occurred in November 2008 in the Piedmont Region. The attention is focused on the key role of air temperature, which is a crucial feature in determining the partitioning of precipitation in solid and liquid phase, influencing the quantitative discharge forecast (QDF) into the Alpine region. This is linked to the basin ipsographic curve and therefore by the total contributing area related to the snow line of the event. In order to assess hydrological predictions affected by meteorological forcing, a sensitivity analysis of the model output was carried out to evaluate different simulation scenarios, considering the forecast effects which can radically modify the discharge forecast. Results show how in real-time systems hydrological forecasters have to consider also the temperature uncertainty in forecasts in order to better understand the snow dynamics and its effect on runoff during a meteorological warning with a crucial snow line over the basin. The hydrological ensemble forecasts are based on the 16 members of the meteorological ensemble system COSMO-LEPS (developed by ARPA-SIMC) based on the non-hydrostatic model COSMO, while the hydrological model used to generate the runoff simulations is the rainfall-runoff distributed FEST-WB model, developed at Politecnico di Milano.

Parallel runway requirement analysis study. Volume 1: The analysis

NASA Technical Reports Server (NTRS)

Ebrahimi, Yaghoob S.

1993-01-01

The correlation of increased flight delays with the level of aviation activity is well recognized. A main contributor to these flight delays has been the capacity of airports. Though new airport and runway construction would significantly increase airport capacity, few programs of this type are currently underway, let alone planned, because of the high cost associated with such endeavors. Therefore, it is necessary to achieve the most efficient and cost effective use of existing fixed airport resources through better planning and control of traffic flows. In fact, during the past few years the FAA has initiated such an airport capacity program designed to provide additional capacity at existing airports. Some of the improvements that that program has generated thus far have been based on new Air Traffic Control procedures, terminal automation, additional Instrument Landing Systems, improved controller display aids, and improved utilization of multiple runways/Instrument Meteorological Conditions (IMC) approach procedures. A useful element to understanding potential operational capacity enhancements at high demand airports has been the development and use of an analysis tool called The PLAND_BLUNDER (PLB) Simulation Model. The objective for building this simulation was to develop a parametric model that could be used for analysis in determining the minimum safety level of parallel runway operations for various parameters representing the airplane, navigation, surveillance, and ATC system performance. This simulation is useful as: a quick and economical evaluation of existing environments that are experiencing IMC delays, an efficient way to study and validate proposed procedure modifications, an aid in evaluating requirements for new airports or new runways in old airports, a simple, parametric investigation of a wide range of issues and approaches, an ability to tradeoff air and ground technology and procedures contributions, and a way of considering probable blunder mechanisms and range of blunder scenarios. This study describes the steps of building the simulation and considers the input parameters, assumptions and limitations, and available outputs. Validation results and sensitivity analysis are addressed as well as outlining some IMC and Visual Meteorological Conditions (VMC) approaches to parallel runways. Also, present and future applicable technologies (e.g., Digital Autoland Systems, Traffic Collision and Avoidance System II, Enhanced Situational Awareness System, Global Positioning Systems for Landing, etc.) are assessed and recommendations made.

BOREAS AES Campbell Scientific Surface Meteorological Data

NASA Technical Reports Server (NTRS)

Atkinson, G. Barrie; Funk, Barrie; Knapp. David E. (Editor); Hall, Forrest G. (Editor)

2000-01-01

Canadian AES personnel collected data related to surface and atmospheric meteorological conditions over the BOREAS region. This data set contains 15-minute meteorological data from 14 automated meteorology stations located across the BOREAS region. Included in this data are parameters of date, time, mean sea level pressure, station pressure, temperature, dew point, wind speed, resultant wind speed, resultant wind direction, peak wind, precipitation, maximum temperature in the last hour, minimum temperature in the last hour, pressure tendency, liquid precipitation in the last hour, relative humidity, precipitation from a weighing gauge, and snow depth. Temporally, the data cover the period of August 1993 to December 1996. The data are provided in tabular ASCII files, and are classified as AFM-Staff data.

A conditional approach to determining the effect of anthropogenic climate change on very rare events.

NASA Astrophysics Data System (ADS)

Wehner, Michael; Pall, Pardeep; Zarzycki, Colin; Stone, Daithi

2016-04-01

Probabilistic extreme event attribution is especially difficult for weather events that are caused by extremely rare large-scale meteorological patterns. Traditional modeling techniques have involved using ensembles of climate models, either fully coupled or with prescribed ocean and sea ice. Ensemble sizes for the latter case ranges from several 100 to tens of thousand. However, even if the simulations are constrained by the observed ocean state, the requisite large-scale meteorological pattern may not occur frequently enough or even at all in free running climate model simulations. We present a method to ensure that simulated events similar to the observed event are modeled with enough fidelity that robust statistics can be determined given the large scale meteorological conditions. By initializing suitably constrained short term ensemble hindcasts of both the actual weather system and a counterfactual weather system where the human interference in the climate system is removed, the human contribution to the magnitude of the event can be determined. However, the change (if any) in the probability of an event of the observed magnitude is conditional not only on the state of the ocean/sea ice system but also on the prescribed initial conditions determined by the causal large scale meteorological pattern. We will discuss the implications of this technique through two examples; the 2013 Colorado flood and the 2014 Typhoon Haiyan.

A new approach for the estimation of phytoplankton cell counts associated with algal blooms.

PubMed

Nazeer, Majid; Wong, Man Sing; Nichol, Janet Elizabeth

2017-07-15

This study proposes a method for estimating phytoplankton cell counts associated with an algal bloom, using satellite images coincident with in situ and meteorological parameters. Satellite images from Landsat Thematic Mapper (TM), Enhanced Thematic Mapper Plus (ETM+), Operational Land Imager (OLI) and HJ-1 A/B Charge Couple Device (CCD) sensors were integrated with the meteorological observations to provide an estimate of phytoplankton cell counts. All images were atmospherically corrected using the Second Simulation of the Satellite Signal in the Solar Spectrum (6S) atmospheric correction method with a possible error of 1.2%, 2.6%, 1.4% and 2.3% for blue (450-520nm), green (520-600nm), red (630-690nm) and near infrared (NIR 760-900nm) wavelengths, respectively. Results showed that the developed Artificial Neural Network (ANN) model yields a correlation coefficient (R) of 0.95 with the in situ validation data with Sum of Squared Error (SSE) of 0.34cell/ml, Mean Relative Error (MRE) of 0.154cells/ml and a bias of -504.87. The integration of the meteorological parameters with remote sensing observations provided a promising estimation of the algal scum as compared to previous studies. The applicability of the ANN model was tested over Hong Kong as well as over Lake Kasumigaura, Japan and Lake Okeechobee, Florida USA, where algal blooms were also reported. Further, a 40-year (1975-2014) red tide occurrence map was developed and revealed that the eastern and southern waters of Hong Kong are more vulnerable to red tides. Over the 40 years, 66% of red tide incidents were associated with the Dinoflagellates group, while the remainder were associated with the Diatom group (14%) and several other minor groups (20%). The developed technology can be applied to other similar environments in an efficient and cost-saving manner. Copyright © 2017 Elsevier B.V. All rights reserved.

Coupling the Canadian Terrestrial Ecosystem Model (CTEM v. 2.0) to Environment and Climate Change Canada's greenhouse gas forecast model (v.107-glb)

NASA Astrophysics Data System (ADS)

Badawy, Bakr; Polavarapu, Saroja; Jones, Dylan B. A.; Deng, Feng; Neish, Michael; Melton, Joe R.; Nassar, Ray; Arora, Vivek K.

2018-02-01

The Canadian Land Surface Scheme and the Canadian Terrestrial Ecosystem Model (CLASS-CTEM) together form the land surface component in the family of Canadian Earth system models (CanESMs). Here, CLASS-CTEM is coupled to Environment and Climate Change Canada (ECCC)'s weather and greenhouse gas forecast model (GEM-MACH-GHG) to consistently model atmosphere-land exchange of CO2. The coupling between the land and the atmospheric transport model ensures consistency between meteorological forcing of CO2 fluxes and CO2 transport. The procedure used to spin up carbon pools for CLASS-CTEM for multi-decadal simulations needed to be significantly altered to deal with the limited availability of consistent meteorological information from a constantly changing operational environment in the GEM-MACH-GHG model. Despite the limitations in the spin-up procedure, the simulated fluxes obtained by driving the CLASS-CTEM model with meteorological forcing from GEM-MACH-GHG were comparable to those obtained from CLASS-CTEM when it is driven with standard meteorological forcing from the Climate Research Unit (CRU) combined with reanalysis fields from the National Centers for Environmental Prediction (NCEP) to form CRU-NCEP dataset. This is due to the similarity of the two meteorological datasets in terms of temperature and radiation. However, notable discrepancies in the seasonal variation and spatial patterns of precipitation estimates, especially in the tropics, were reflected in the estimated carbon fluxes, as they significantly affected the magnitude of the vegetation productivity and, to a lesser extent, the seasonal variations in carbon fluxes. Nevertheless, the simulated fluxes based on the meteorological forcing from the GEM-MACH-GHG model are consistent to some extent with other estimates from bottom-up or top-down approaches. Indeed, when simulated fluxes obtained by driving the CLASS-CTEM model with meteorological data from the GEM-MACH-GHG model are used as prior estimates for an atmospheric CO2 inversion analysis using the adjoint of the GEOS-Chem model, the retrieved CO2 flux estimates are comparable to those obtained from other systems in terms of the global budget and the total flux estimates for the northern extratropical regions, which have good observational coverage. In data-poor regions, as expected, differences in the retrieved fluxes due to the prior fluxes become apparent. Coupling CLASS-CTEM into the Environment Canada Carbon Assimilation System (EC-CAS) is considered an important step toward understanding how meteorological uncertainties affect both CO2 flux estimates and modeled atmospheric transport. Ultimately, such an approach will provide more direct feedback to the CLASS-CTEM developers and thus help to improve the performance of CLASS-CTEM by identifying the model limitations based on atmospheric constraints.

Selection of meteorological conditions to apply in an Ecotron facility

NASA Astrophysics Data System (ADS)

Leemans, Vincent; De Cruz, Lesley; Dumont, Benjamin; Hamdi, Rafiq; Delaplace, Pierre; Heinesh, Bernard; Garré, Sarah; Verheggen, François; Theodorakopoulos, Nicolas; Longdoz, Bernard

2017-04-01

This presentation aims to propose a generic method to produce meteorological input data that is useful for climate research infrastructures such as an Ecotron, where researchers will face the need to generate representative actual or future climatic conditions. Depending on the experimental objectives and the research purposes, typical conditions or more extreme values such as dry or wet climatic scenarios might be requested. Four variables were considered here, the near-surface air temperature, the near-surface relative humidity, the cloud cover and precipitation. The meteorological datasets, among which a specific meteorological year can be picked up, are produced by the ALARO-0 model from the RMIB (Royal Meteorological Institute of Belgium). Two future climate scenarios (RCP 4.5 and 8.5) and two time periods (2041-2070 and 2071-2100) were used as well as a historical run of the model (1981-2010) which is used as a reference. When the data from a historical run were compared to the observed historical data, biases were noticed. A linear correction was proposed for all the variables except for precipitation, for which a non-linear correction (using a power function) was chosen to maintain a zero-precipitation occurrences. These transformations were able to remove most of the differences between the observed and historical run of the model for the means and for the standard deviations. For the relative humidity, because of non-linearities, only one half of the average bias was corrected and a different path might have to be chosen. For the selection of a meteorological year, a position and a dispersion parameter have been proposed to characterise each meteorological year for each variable. For precipitation, a third parameter quantifying the importance of dry and wet periods has been defined. In order to select a specific climate, for each of these nine parameters the experimenter should provide a percentile and a weight to prioritize the importance of each variable in the process of a global climate selection. The proposed algorithm computed the weighted distance for each year between the parameters and the point representing the position of the percentile in the nine-dimensional space. The five closest values were then selected and represented in different graphs. The proposed method is able to provide a decision aid in the selection of the meteorological conditions to be generated within an Ecotron. However, with a limited number of years available in each case (thirty years for each RCP and each time period), there is no perfect match and the ultimate trade-off will be the responsibility of the researcher. For typical years, close to the median, the relative frequency is higher and the trade-off is more easy than for more extreme years where the relative frequency is low.

Simulation of trace metals and PAH atmospheric pollution over Greater Paris: Concentrations and deposition on urban surfaces

NASA Astrophysics Data System (ADS)

Thouron, L.; Seigneur, C.; Kim, Y.; Legorgeu, C.; Roustan, Y.; Bruge, B.

2017-10-01

Urban areas can be subject not only to poor air quality, but also to contamination of other environmental media by air pollutants. Here, we address the potential transfer of selected air pollutants (two metals and three PAH) to urban surfaces. To that end, we simulate meteorology and air pollution from Europe to a Paris suburban neighborhood, using a four-level one-way nesting approach. The meteorological and air quality simulations use urban canopy sub-models in order to better represent the effect of the urban morphology on the air flow, atmospheric dispersion, and deposition of air pollutants to urban surfaces. This modeling approach allows us to distinguish air pollutant deposition among various urban surfaces (roofs, roads, and walls). Meteorological model performance is satisfactory, showing improved results compared to earlier simulations, although precipitation amounts are underestimated. Concentration simulation results are also satisfactory for both metals, with a fractional bias <0.5. Concentrations of benzo[a]pyrene are overestimated, probably because continental emissions may be overestimated. Concentrations of benzo[b]fluoranthene and indeno[1,2,3,cd]pyrene are underestimated, in part because of null boundary conditions. PAH deposition fluxes are consistent with earlier measurements obtained in the Greater Paris region. The model simulation results suggest that both wet and dry deposition processes need to be considered when estimating the transfer of air pollutants to other environmental media. Dry deposition fluxes to various urban surfaces are mostly uniform for PAH, which are entirely present in fine particles. However, there is significantly less wall deposition compared to deposition to roofs and roads for trace metals, due to their coarse fraction. Meteorology, particle size distribution, and urban morphology are all important factors affecting air pollutant deposition. Future work should focus on the collection of data suitable to evaluate the performance of atmospheric models for both wet and dry deposition with fine spatial resolution.

User's guide for MAGIC-Meteorologic and hydrologic genscn (generate scenarios) input converter

USGS Publications Warehouse

Ortel, Terry W.; Martin, Angel

2010-01-01

Meteorologic and hydrologic data used in watershed modeling studies are collected by various agencies and organizations, and stored in various formats. Data may be in a raw, un-processed format with little or no quality control, or may be checked for validity before being made available. Flood-simulation systems require data in near real-time so that adequate flood warnings can be made. Additionally, forecasted data are needed to operate flood-control structures to potentially mitigate flood damages. Because real-time data are of a provisional nature, missing data may need to be estimated for use in floodsimulation systems. The Meteorologic and Hydrologic GenScn (Generate Scenarios) Input Converter (MAGIC) can be used to convert data from selected formats into the Hydrologic Simulation System-Fortran hourly-observations format for input to a Watershed Data Management database, for use in hydrologic modeling studies. MAGIC also can reformat the data to the Full Equations model time-series format, for use in hydraulic modeling studies. Examples of the application of MAGIC for use in the flood-simulation system for Salt Creek in northeastern Illinois are presented in this report.

Rectenna related atmospheric effects

NASA Technical Reports Server (NTRS)

Lee, J.

1980-01-01

Possible meteorological effects arising from the existence and operations of a solar power satellite (SPS) system rectenna are examined. Analysis and model simulations in some chosen site situations and meteorological conditions indicate that the meteorological effects of the construction and operation of a rectenna are small, particularly outside the boundary of the structure. From weather and climate points of view, installation of an SPS rectenna seems likely to have effects comparable with those due to other nonindustrial land use changes covering the same area. The absorption and scattering of microwave radiation in the troposphere would have negligible atmospheric effects.

The Australian Bureau of Meteorology Activities for the Regional Ionosphere Specification and Forcating

NASA Astrophysics Data System (ADS)

Bouya, Z.; Terkildsen, M.; Maher, P.

2016-12-01

Space Weather Services, Australian Bureau of Meteorology, Sydney, Australia Abstract:The Australian Bureau of Meteorology through its Space Weather Service (SWS) provides ionospheric products and services to a diverse group of customers. In this work, we present a regional approach to characterizing the Australian regional Total Electron Content (TEC) and an assimilative model to map the Ionospheric layer parameter foF2. Finally we outline the design of an Australian regional Ionospheric forecast model at SWS. Keywords: TEC, foF2, regional, data assimilation, forecast

Incorporation of the equilibrium temperature approach in a Soil and Water Assessment Tool hydroclimatological stream temperature model

NASA Astrophysics Data System (ADS)

Du, Xinzhong; Shrestha, Narayan Kumar; Ficklin, Darren L.; Wang, Junye

2018-04-01

Stream temperature is an important indicator for biodiversity and sustainability in aquatic ecosystems. The stream temperature model currently in the Soil and Water Assessment Tool (SWAT) only considers the impact of air temperature on stream temperature, while the hydroclimatological stream temperature model developed within the SWAT model considers hydrology and the impact of air temperature in simulating the water-air heat transfer process. In this study, we modified the hydroclimatological model by including the equilibrium temperature approach to model heat transfer processes at the water-air interface, which reflects the influences of air temperature, solar radiation, wind speed and streamflow conditions on the heat transfer process. The thermal capacity of the streamflow is modeled by the variation of the stream water depth. An advantage of this equilibrium temperature model is the simple parameterization, with only two parameters added to model the heat transfer processes. The equilibrium temperature model proposed in this study is applied and tested in the Athabasca River basin (ARB) in Alberta, Canada. The model is calibrated and validated at five stations throughout different parts of the ARB, where close to monthly samplings of stream temperatures are available. The results indicate that the equilibrium temperature model proposed in this study provided better and more consistent performances for the different regions of the ARB with the values of the Nash-Sutcliffe Efficiency coefficient (NSE) greater than those of the original SWAT model and the hydroclimatological model. To test the model performance for different hydrological and environmental conditions, the equilibrium temperature model was also applied to the North Fork Tolt River Watershed in Washington, United States. The results indicate a reasonable simulation of stream temperature using the model proposed in this study, with minimum relative error values compared to the other two models. However, the NSE values were lower than those of the hydroclimatological model, indicating that more model verification needs to be done. The equilibrium temperature model uses existing SWAT meteorological data as input, can be calibrated using fewer parameters and less effort and has an overall better performance in stream temperature simulation. Thus, it can be used as an effective tool for predicting the changes in stream temperature regimes under varying hydrological and meteorological conditions. In addition, the impact of the stream temperature simulations on chemical reaction rates and concentrations was tested. The results indicate that the improved performance of the stream temperature simulation could significantly affect chemical reaction rates and the simulated concentrations, and the equilibrium temperature model could be a potential tool to model stream temperature in water quality simulations.

Assesment of PM2.5 emission from corn stover burning determining in chamber combustion

NASA Astrophysics Data System (ADS)

Hafidawati; Lestari, P.; Sofyan, A.

2018-04-01

Chamber measurement were conducted to determine Particulate Matter (PM2.5) emission from open burning of corn straw at Garut District, West Java. The of this study is to estimate the concentration of PM2.5 for two types of corn (corncobs and cornstover) for five varieties (Bisma, P29, NK, Bisma, NW). Corn residues were collected and then burned in the chamber combustion. The chamber was designed to simulate the burning in the field, which was observed in the field experiment that meteorological condition was calm wind. The samples were collected using a minivol air sampler. The assessment results of PM2.5 concentrations (mg/m3) from open burning experiment in the chamber for five varieties of corn cobs (Bisma, P29, NK, Bisi, NW) was 9.187; 2.843; 7.409; 3.781; 1.895 respectively. Concentration for corn stover burn was 2.060; 5.283; 4.048; 5.306 and 5.697 respectively. Fluctuations in the value of concentration among these varieties reflect variations in combustion conditions (combustion efficiency) and other parameters including water content, biomass conditions and the meteorological conditions. The combustion efficiency (MCE) of the combustion chamber simulation of corncobs ia lower than the MCE of corn stover, that the concentration PM2.5 more emitted from the burning of corn stover. The results of this study presented provide useful information for the development of local emission factors for PM2.5 from open burning of corn stover in Indonesia.

Impact of aerosols on ice crystal size

NASA Astrophysics Data System (ADS)

Zhao, Bin; Liou, Kuo-Nan; Gu, Yu; Jiang, Jonathan H.; Li, Qinbin; Fu, Rong; Huang, Lei; Liu, Xiaohong; Shi, Xiangjun; Su, Hui; He, Cenlin

2018-01-01

The interactions between aerosols and ice clouds represent one of the largest uncertainties in global radiative forcing from pre-industrial time to the present. In particular, the impact of aerosols on ice crystal effective radius (Rei), which is a key parameter determining ice clouds' net radiative effect, is highly uncertain due to limited and conflicting observational evidence. Here we investigate the effects of aerosols on Rei under different meteorological conditions using 9-year satellite observations. We find that the responses of Rei to aerosol loadings are modulated by water vapor amount in conjunction with several other meteorological parameters. While there is a significant negative correlation between Rei and aerosol loading in moist conditions, consistent with the "Twomey effect" for liquid clouds, a strong positive correlation between the two occurs in dry conditions. Simulations based on a cloud parcel model suggest that water vapor modulates the relative importance of different ice nucleation modes, leading to the opposite aerosol impacts between moist and dry conditions. When ice clouds are decomposed into those generated from deep convection and formed in situ, the water vapor modulation remains in effect for both ice cloud types, although the sensitivities of Rei to aerosols differ noticeably between them due to distinct formation mechanisms. The water vapor modulation can largely explain the difference in the responses of Rei to aerosol loadings in various seasons. A proper representation of the water vapor modulation is essential for an accurate estimate of aerosol-cloud radiative forcing produced by ice clouds.

On the influence of meteorological input on photochemical modelling of a severe episode over a coastal area

NASA Astrophysics Data System (ADS)

Pirovano, G.; Coll, I.; Bedogni, M.; Alessandrini, S.; Costa, M. P.; Gabusi, V.; Lasry, F.; Menut, L.; Vautard, R.

The modelling reconstruction of the processes determining the transport and mixing of ozone and its precursors in complex terrain areas is a challenging task, particularly when local-scale circulations, such as sea breeze, take place. Within this frame, the ESCOMPTE European campaign took place in the vicinity of Marseille (south-east of France) in summer 2001. The main objectives of the field campaign were to document several photochemical episodes, as well as to constitute a detailed database for chemistry transport models intercomparison. CAMx model has been applied on the largest intense observation periods (IOP) (June 21-26, 2001) in order to evaluate the impacts of two state-of-the-art meteorological models, RAMS and MM5, on chemical model outputs. The meteorological models have been used as best as possible in analysis mode, thus allowing to identify the spread arising in pollutant concentrations as an indication of the intrinsic uncertainty associated to the meteorological input. Simulations have been deeply investigated and compared with a considerable subset of observations both at ground level and along vertical profiles. The analysis has shown that both models were able to reproduce the main circulation features of the IOP. The strongest discrepancies are confined to the Planetary Boundary Layer, consisting of a clear tendency to underestimate or overestimate wind speed over the whole domain. The photochemical simulations showed that variability in circulation intensity was crucial mainly for the representation of the ozone peaks and of the shape of ozone plumes at the ground that have been affected in the same way over the whole domain and all along the simulated period. As a consequence, such differences can be thought of as a possible indicator for the uncertainty related to the definition of meteorological fields in a complex terrain area.

Assessing the competing roles of model resolution and meteorological forcing fidelity in hyperresolution simulations of snowpack and streamflow in the southern Rocky Mountains

NASA Astrophysics Data System (ADS)

Gochis, D. J.; Dugger, A. L.; Karsten, L. R.; Barlage, M. J.; Sampson, K. M.; Yu, W.; Pan, L.; McCreight, J. L.; Howard, K.; Busto, J.; Deems, J. S.

2017-12-01

Hydrometeorological processes vary over comparatively short length scales in regions of complex terrain such as the southern Rocky Mountains. Changes in temperature, precipitation, wind and solar radiation can vary significantly across elevation gradients, terrain landform and land cover conditions throughout the region. Capturing such variability in hydrologic models can necessitate the utilization of so-called `hyper-resolution' spatial meshes with effective element spacings of less than 100m. However, it is often difficult to obtain meteorological forcings of high quality in such regions at those resolutions which can result in significant uncertainty in fundamental in hydrologic model inputs. In this study we examine the comparative influences of meteorological forcing data fidelity and spatial resolution on seasonal simulations of snowpack evolution, runoff and streamflow in a set of high mountain watersheds in southern Colorado. We utilize the operational, NOAA National Water Model configuration of the community WRF-Hydro system as a baseline and compare against it, additional model scenarios with differing specifications of meteorological forcing data, with and without topographic downscaling adjustments applied, with and without experimental high resolution radar derived precipitation estimates and with WRF-Hydro configurations of progressively finer spatial resolution. The results suggest significant influence from and importance of meteorological downscaling techniques in controlling spatial distributions of meltout and runoff timing. The use of radar derived precipitation exhibits clear sensitivity on hydrologic simulation skill compared with the use of coarser resolution, background precipitation analyses. Advantages and disadvantages of the utilization of progressively higher resolution model configurations both in terms of computational requirements and model fidelity are also discussed.

Using weather prediction data for simulation of mesoscale atmospheric processes

NASA Astrophysics Data System (ADS)

Bart, Andrey A.; Starchenko, Alexander V.

2015-11-01

The paper presents an approach to specify initial and boundary conditions from the output data of global model SLAV for mesoscale modelling of atmospheric processes in areas not covered by meteorological observations. From the data and the model equations for a homogeneous atmospheric boundary layer the meteorological and turbulent characteristics of the atmospheric boundary layer are calculated.

Sensitivity of Hydrologic Extremes to Spatial Resolution of Meteorological Forcings: A Case Study of the Conterminous United States

NASA Astrophysics Data System (ADS)

Kao, S. C.; Naz, B. S.; Gangrade, S.; Ashfaq, M.; Rastogi, D.

2016-12-01

The magnitude and frequency of hydroclimate extremes are projected to increase in the conterminous United States (CONUS) with significant implications for future water resource planning and flood risk management. Nevertheless, apart from the change of natural environment, the choice of model spatial resolution could also artificially influence the features of simulated extremes. To better understand how the spatial resolution of meteorological forcings may affect hydroclimate projections, we test the runoff sensitivity using the Variable Infiltration Capacity (VIC) model that was calibrated for each CONUS 8-digit hydrologic unit (HUC8) at 1/24° ( 4km) grid resolution. The 1980-2012 gridded Daymet and PRISM meteorological observations are used to conduct the 1/24° resolution control simulation. Comparative simulations are achieved by smoothing the 1/24° forcing into 1/12° and 1/8° resolutions which are then used to drive the VIC model for the CONUS. In addition, we also test how the simulated high and low runoff conditions would react to change in precipitation (±10%) and temperature (+1°C). The results are further analyzed for various types of hydroclimate extremes across different watersheds in the CONUS. This work helps us understand the sensitivity of simulated runoff to different spatial resolutions of climate forcings and also its sensitivity to different watershed sizes and characteristics of extreme events in the future climate conditions.

Characterisation of residual ionospheric errors in bending angles using GNSS RO end-to-end simulations

NASA Astrophysics Data System (ADS)

Liu, C. L.; Kirchengast, G.; Zhang, K. F.; Norman, R.; Li, Y.; Zhang, S. C.; Carter, B.; Fritzer, J.; Schwaerz, M.; Choy, S. L.; Wu, S. Q.; Tan, Z. X.

2013-09-01

Global Navigation Satellite System (GNSS) radio occultation (RO) is an innovative meteorological remote sensing technique for measuring atmospheric parameters such as refractivity, temperature, water vapour and pressure for the improvement of numerical weather prediction (NWP) and global climate monitoring (GCM). GNSS RO has many unique characteristics including global coverage, long-term stability of observations, as well as high accuracy and high vertical resolution of the derived atmospheric profiles. One of the main error sources in GNSS RO observations that significantly affect the accuracy of the derived atmospheric parameters in the stratosphere is the ionospheric error. In order to mitigate the effect of this error, the linear ionospheric correction approach for dual-frequency GNSS RO observations is commonly used. However, the residual ionospheric errors (RIEs) can be still significant, especially when large ionospheric disturbances occur and prevail such as during the periods of active space weather. In this study, the RIEs were investigated under different local time, propagation direction and solar activity conditions and their effects on RO bending angles are characterised using end-to-end simulations. A three-step simulation study was designed to investigate the characteristics of the RIEs through comparing the bending angles with and without the effects of the RIEs. This research forms an important step forward in improving the accuracy of the atmospheric profiles derived from the GNSS RO technique.

Applying a coupled hydrometeorological simulation system to flash flood forecasting over the Korean Peninsula

NASA Astrophysics Data System (ADS)

Ryu, Young; Lim, Yoon-Jin; Ji, Hee-Sook; Park, Hyun-Hee; Chang, Eun-Chul; Kim, Baek-Jo

2017-11-01

In flash flood forecasting, it is necessary to consider not only traditional meteorological variables such as precipitation, evapotranspiration, and soil moisture, but also hydrological components such as streamflow. To address this challenge, the application of high resolution coupled atmospheric-hydrological models is emerging as a promising alternative. This study demonstrates the feasibility of linking a coupled atmospheric-hydrological model (WRF/WRFHydro) with 150-m horizontal grid spacing for flash flood forecasting in Korea. The study area is the Namgang Dam basin in Southern Korea, a mountainous area located downstream of Jiri Mountain (1915 m in height). Under flash flood conditions, the simulated precipitation over the entire basin is comparable to the domain-averaged precipitation, but discharge data from WRF-Hydro shows some differences in the total available water and the temporal distribution of streamflow (given by the timing of the streamflow peak following precipitation), compared to observations. On the basis of sensitivity tests, the parameters controlling the infiltration of excess precipitation and channel roughness depending on stream order are refined and their influence on temporal distribution of streamflow is addressed with intent to apply WRF-Hydro to flash flood forecasting in the Namgang Dam basin. The simulation results from the WRF-Hydro model with optimized parameters demonstrate the potential utility of a coupled atmospheric-hydrological model for forecasting heavy rain-induced flash flooding over the Korean Peninsula.

Mapping the Martian Meteorology

NASA Technical Reports Server (NTRS)

Allison, Michael; Ross, J. D.; Soloman, N.

1999-01-01

The Mars-adapted version of the NASA/GISS general circulation model (GCM) has been applied to the hourly/daily simulation of the planet's meteorology over several seasonal orbits. The current running version of the model includes a diurnal solar cycle, CO2 sublimation, and a mature parameterization of upper level wave drag with a vertical domain extending from the surface up to the 6 micro b level. The benchmark simulations provide a four-dimensional archive for the comparative evaluation of various schemes for the retrieval of winds from anticipated polar orbiter measurements of temperatures by the Pressure Modulator Infrared Radiometer.

Numerical experiments on short-term meteorological effects on solar variability

NASA Technical Reports Server (NTRS)

Somerville, R. C. J.; Hansen, J. E.; Stone, P. H.; Quirk, W. J.; Lacis, A. A.

1975-01-01

A set of numerical experiments was conducted to test the short-range sensitivity of a large atmospheric general circulation model to changes in solar constant and ozone amount. On the basis of the results of 12-day sets of integrations with very large variations in these parameters, it is concluded that realistic variations would produce insignificant meteorological effects. Any causal relationships between solar variability and weather, for time scales of two weeks or less, rely upon changes in parameters other than solar constant or ozone amounts, or upon mechanisms not yet incorporated in the model.

Atmospheric environment for Space Shuttle (STS-3) launch

NASA Technical Reports Server (NTRS)

Johnson, D. L.; Brown, S. C.; Batts, G. W.

1982-01-01

Selected atmospheric conditions observed near Space Shuttle STS-3 launch time on March 22, 1982, at Kennedy Space Center, Florida are summarized. Values of ambient pressure, temperature, moisture, ground winds, visual observations (cloud), and winds aloft are included. The sequence of prlaunch Jimsphere measured vertical wind profiles and the wind and thermodynamic parameters measured at the surface and aloft in the SRB descent/impact ocean area are presented. Final meteorological tapes, which consist of wind and thermodynamic parameters versus altitude, for STS-3 vehicle ascent and SRB descent were constructed. The STS-3 ascent meteorological data tape is constructed.

Mesoscale acid deposition modeling studies

NASA Technical Reports Server (NTRS)

Kaplan, Michael L.; Proctor, F. H.; Zack, John W.; Karyampudi, V. Mohan; Price, P. E.; Bousquet, M. D.; Coats, G. D.

1989-01-01

The work performed in support of the EPA/DOE MADS (Mesoscale Acid Deposition) Project included the development of meteorological data bases for the initialization of chemistry models, the testing and implementation of new planetary boundary layer parameterization schemes in the MASS model, the simulation of transport and precipitation for MADS case studies employing the MASS model, and the use of the TASS model in the simulation of cloud statistics and the complex transport of conservative tracers within simulated cumuloform clouds. The work performed in support of the NASA/FAA Wind Shear Program included the use of the TASS model in the simulation of the dynamical processes within convective cloud systems, the analyses of the sensitivity of microburst intensity and general characteristics as a function of the atmospheric environment within which they are formed, comparisons of TASS model microburst simulation results to observed data sets, and the generation of simulated wind shear data bases for use by the aviation meteorological community in the evaluation of flight hazards caused by microbursts.

Change of flood risk under climate change based on Discharge Probability Index in Japan

NASA Astrophysics Data System (ADS)

Nitta, T.; Yoshimura, K.; Kanae, S.; Oki, T.

2010-12-01

Water-related disasters under the climate change have recently gained considerable interest, and there have been many studies referring to flood risk at the global scale (e.g. Milly et al., 2002; Hirabayashi et al., 2008). In order to build adaptive capacity, however, regional impact evaluation is needed. We thus focus on the flood risk over Japan in the present study. The output from the Regional Climate Model 20 (RCM20), which was developed by the Meteorological Research Institute, was used. The data was first compared with observed data based on Automated Meteorological Data Acquisition System and ground weather observations, and the model biases were corrected using the ratio and difference of the 20-year mean values. The bias-corrected RCM20 atmospheric data were then forced to run a land surface model and a river routing model (Yoshimura et al., 2007; Ngo-Duc, T. et al. 2007) to simulate river discharge during 1981-2000, 2031-2050, and 2081-2100. Simulated river discharge was converted to Discharge Probability Index (DPI), which was proposed by Yoshimura et al based on a statistical approach. The bias and uncertainty of the models are already taken into account in the concept of DPI, so that DPI serves as a good indicator of flood risk. We estimated the statistical parameters for DPI using the river discharge for 1981-2000 with an assumption that the parameters stay the same in the different climate periods. We then evaluated the occurrence of flood events corresponding to DPI categories in each 20 years and averaged them in 9 regions. The results indicate that low DPI flood events (return period of 2 years) will become more frequent in 2031-2050 and high DPI flood events (return period of 200 years) will become more frequent in 2081-2100 compared with the period of 1981-2000, though average precipitation will become larger during 2031-2050 than during 2081-2100 in most regions. It reflects the increased extreme precipitation during 2081-2100.

Towards a Better Understanding of Water Stores and Fluxes: Model Observation Synthesis in a Snowmelt Dominated Research Watershed

NASA Astrophysics Data System (ADS)

Ryken, A.; Gochis, D.; Carroll, R. W. H.; Bearup, L. A.; Williams, K. H.; Maxwell, R. M.

2017-12-01

The hydrology of high-elevation, mountainous regions is poorly represented in Earth Systems Models (ESMs). In addition to regulating downstream water delivery, these ecosystems play an important role in the storage and land-atmosphere exchange of carbon and water. Water balances are sensitive to the amount of water stored in the snowpack (SWE) and the amount of water leaving the system in the form of evapotranspiration—two pieces of the hydrologic cycle that are difficult to observe and model in heterogeneous mountainous regions due to spatially variant weather patterns. In an effort to resolve this hydrologic gap in ESMs, this study seeks to better understand the interactions between groundwater, carbon flux, and the lower atmosphere in these high-altitude environments through integration of field observations and model simulations. We compare model simulations to field observations to elucidate process performance combined with a sensitivity analysis to better understand parameter uncertainty. Observations from a meteorological station in the East River Basin are used to force an integrated single-column hydrologic model, ParFlow-CLM. This met station is co-located with an eddy covariance tower, which, along with snow surveys, is used to better constrain the water, carbon, and energy fluxes in the coupled land-atmosphere model to increase our understanding of high-altitude headwaters. Preliminary results suggest the model compares well to the eddy covariance tower and field observations, shown through both correct magnitude and timing of peak SWE along with similar magnitudes and diurnal patterns of heat and water fluxes. Initial sensitivity analysis results show that an increase in temperature leads to a decrease in peak SWE as well as an increase in latent heat revealing a sensitivity of the model to air temperature. Further sensitivity analysis will help us understand more parameter uncertainty. Through obtaining more accurate and higher resolution meteorological data and applying it to a coupled hydrologic model, this study can lead to better representation of mountainous environments in all ESMs.

Influence of meteorological parameters on the soil radon (Rn222) emanation in Kutch, Gujarat, India.

PubMed

Sahoo, Sushanta Ku; Katlamudi, Madhusudhanarao; Shaji, Jerin P; Murali Krishna, K S; Udaya Lakshmi, G

2018-02-02

The soil radon (Rn 222 ) and thoron (Rn 220 ) concentrations recorded at Badargadh and Desalpar observatories in the Kutch region of Gujarat, India, have been analyzed to study the sources of the radon emissions, earthquake precursors, and the influence of meteorological parameters on radon emission. Radon and meteorological parameters were recorded using Radon Monitor RMT 1688-2 at these two stations. We used the radon data during February 21, 2011 to June 8, 2011, for Badargadh and March 2, 2011 to May 19, 2011, for the Desalpar station with a sampling interval of 10 min. It is observed that the radon concentrations at Desalpar varies between 781 and 4320 Bq m -3 with an average value of 2499 Bq m -3 , whereas thoron varies between 191 and 2017 Bq m -3 with an average value of 1433.69 Bq m -3 . The radon concentration at Badargadh varies between 264 and 2221 Bq m -3 with an average value of 1135.4 Bq m -3 , whereas thoron varies between 97 and 556 Bq m -3 . To understand how the meteorological parameters influence radon emanation, the radon and other meteorological parameters were correlated with linear regression analysis. Here, it was observed that radon and temperature are negatively correlated whereas radon and other two parameters, i.e., humidity and pressure are positively correlated. The cross correlogram also ascertains similar relationships between radon and other parameters. Further, the ratio between radon and thoron has been analyzed to determine the deep or shallow source of the radon emanation in the study area. These results revealed that the ratio radon/thoron enhanced during this period which indicates the deeper source contribution is prominent. Incidentally, all the local earthquakes occurred with a focal depth of 18-25 km at the lower crust in this region. We observed the rise in the concentrations of radon and the ratio radon/thoron at Badargadh station before the occurrence of the local earthquakes on 29th March 2011 (M 3.7) and 17th May 2011 (M 4.2). We clearly observed the radon level crossing the mean + 2*sigma level before the occurrence of these events. We conclude that these enhanced radon emissions are linked with alteration of the crustal stress/strain in this region as this observing station is near the epicenters of the earthquakes. We did not observe considerable variations in radon at the Desalpar station which is far from the earthquake location.

Migration by soaring or flapping: numerical atmospheric simulations reveal that turbulence kinetic energy dictates bee-eater flight mode

PubMed Central

Sapir, Nir; Horvitz, Nir; Wikelski, Martin; Avissar, Roni; Mahrer, Yitzhak; Nathan, Ran

2011-01-01

Aerial migrants commonly face atmospheric dynamics that may affect their movement and behaviour. Specifically, bird flight mode has been suggested to depend on convective updraught availability and tailwind assistance. However, this has not been tested thus far since both bird tracks and meteorological conditions are difficult to measure in detail throughout extended migratory flyways. Here, we applied, to our knowledge, the first comprehensive numerical atmospheric simulations by mean of the Regional Atmospheric Modeling System (RAMS) to study how meteorological processes affect the flight behaviour of migrating birds. We followed European bee-eaters (Merops apiaster) over southern Israel using radio telemetry and contrasted bird flight mode (flapping, soaring–gliding or mixed flight) against explanatory meteorological variables estimated by RAMS simulations at a spatial grid resolution of 250 × 250 m2. We found that temperature and especially turbulence kinetic energy (TKE) determine bee-eater flight mode, whereas, unexpectedly, no effect of tailwind assistance was found. TKE during soaring–gliding was significantly higher and distinct from TKE during flapping. We propose that applying detailed atmospheric simulations over extended migratory flyways can elucidate the highly dynamic behaviour of air-borne organisms, help predict the abundance and distribution of migrating birds, and aid in mitigating hazardous implications of bird migration. PMID:21471116

Can Atmospheric Reanalysis Data Sets Be Used to Reproduce Flooding Over Large Scales?

NASA Astrophysics Data System (ADS)

Andreadis, Konstantinos M.; Schumann, Guy J.-P.; Stampoulis, Dimitrios; Bates, Paul D.; Brakenridge, G. Robert; Kettner, Albert J.

2017-10-01

Floods are costly to global economies and can be exceptionally lethal. The ability to produce consistent flood hazard maps over large areas could provide a significant contribution to reducing such losses, as the lack of knowledge concerning flood risk is a major factor in the transformation of river floods into flood disasters. In order to accurately reproduce flooding in river channels and floodplains, high spatial resolution hydrodynamic models are needed. Despite being computationally expensive, recent advances have made their continental to global implementation feasible, although inputs for long-term simulations may require the use of reanalysis meteorological products especially in data-poor regions. We employ a coupled hydrologic/hydrodynamic model cascade forced by the 20CRv2 reanalysis data set and evaluate its ability to reproduce flood inundation area and volume for Australia during the 1973-2012 period. Ensemble simulations using the reanalysis data were performed to account for uncertainty in the meteorology and compared with a validated benchmark simulation. Results show that the reanalysis ensemble capture the inundated areas and volumes relatively well, with correlations for the ensemble mean of 0.82 and 0.85 for area and volume, respectively, although the meteorological ensemble spread propagates in large uncertainty of the simulated flood characteristics.

Simulating and explaining passive air sampling rates for semi-volatile compounds on polyurethane foam passive samplers

PubMed Central

Petrich, Nicholas T.; Spak, Scott N.; Carmichael, Gregory R.; Hu, Dingfei; Martinez, Andres; Hornbuckle, Keri C.

2013-01-01

Passive air samplers (PAS) including polyurethane foam (PUF) are widely deployed as an inexpensive and practical way to sample semi-volatile pollutants. However, concentration estimates from PAS rely on constant empirical mass transfer rates, which add unquantified uncertainties to concentrations. Here we present a method for modeling hourly sampling rates for semi-volatile compounds from hourly meteorology using first-principle chemistry, physics, and fluid dynamics, calibrated from depuration experiments. This approach quantifies and explains observed effects of meteorology on variability in compound-specific sampling rates and analyte concentrations; simulates nonlinear PUF uptake; and recovers synthetic hourly concentrations at a reference temperature. Sampling rates are evaluated for polychlorinated biphenyl congeners at a network of Harner model samplers in Chicago, Illinois during 2008, finding simulated average sampling rates within analytical uncertainty of those determined from loss of depuration compounds, and confirming quasi-linear uptake. Results indicate hourly, daily and interannual variability in sampling rates, sensitivity to temporal resolution in meteorology, and predictable volatility-based relationships between congeners. We quantify importance of each simulated process to sampling rates and mass transfer and assess uncertainty contributed by advection, molecular diffusion, volatilization, and flow regime within the PAS, finding PAS chamber temperature contributes the greatest variability to total process uncertainty (7.3%). PMID:23837599

Dynamical Downscaling of Meteorology from a Global Model by WRF towards Resolving US PM2.5 Distributions for the Mid 21st Century

NASA Astrophysics Data System (ADS)

Kunwar, S.; Bowden, J.; Milly, G.; Previdi, M. J.; Fiore, A. M.; West, J. J.

2017-12-01

In the coming decades, anthropogenically induced climate change will likely impact PM2.5 through both changing meteorology and feedback in natural emissions. A major goal of our project is to assess changes in PM2.5 levels over the continental US due to climate variability and change for the period 2005-2065. We will achieve this by using regional models to dynamically downscale coarse resolution (20 × 20) meteorology and air chemistry from a global model to finer spatial resolution (12 km), improving air quality projections for regions and subregions of the US (NE, SE, SW, NW, Midwest, Intermountain West). We downscale from GFDL CM3 simulations of the RCP8.5 scenario for the years 2006-2100 with aerosol and ozone precursor emissions fixed at 2005 levels. We carefully select model years from the global simulations that sample the range of PM2.5 distributions for different US regions at mid 21st century (2050-2065). Here we will show results for the meteorological downscaling (using WRF version 3.8.1) for this project, including a performance evaluation for meteorological variables with respect to the global model. In the future, the downscaled meteorology presented here will be used to drive air quality downscaling in CMAQ (version 5.2). Analysis of the resulting PM2.5 statistics for US regions, as well as the drivers for PM2.5 changes, will be important in supporting informed policies for air quality (also health and visibility) planning for different US regions for the next five decades.

Sensitivity analysis of WRF model PBL schemes in simulating boundary-layer variables in southern Italy: An experimental campaign

NASA Astrophysics Data System (ADS)

Avolio, E.; Federico, S.; Miglietta, M. M.; Lo Feudo, T.; Calidonna, C. R.; Sempreviva, A. M.

2017-08-01

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.

Continuously on-­going regional climate hindcast simulations for impact applications

NASA Astrophysics Data System (ADS)

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

2017-04-01

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

Investigation of optical and radiative properties of aerosols during an intense dust storm: A regional climate modeling approach

NASA Astrophysics Data System (ADS)

Bran, Sherin Hassan; Jose, Subin; Srivastava, Rohit

2018-03-01

The dynamical and optical properties of aerosols during an intense dust storm event over the Arabian Sea have been studied using Weather Research and Forecasting model coupled with Chemistry (WRF-Chem) and space borne instruments such as MODIS, MISR, CALIPSO and CERES during the period 17 to 24 March, 2012. The model captures the spatio-temporal and vertical variations of meteorological and optical parameters, however an overestimation in simulated aerosol optical parameters are observed when compared to satellite retrievals. The correlation coefficients (R) between simulated and observed AOD from MODIS and MISR are found to be 0.54 and 0.32 respectively. Model simulated AOD on dusty days (20 and 21 March 2012) increased by 2-3 times compared to non-dusty days (17 and 24 March 2012) and the single scattering albedo (SSA) and the asymmetry parameter increased from 0.96 to 0.99 and from 0.56 to 0.66, respectively. The R between simulated shortwave (SW) radiation at top of the atmosphere (TOA) and TOA SW radiation obtained from CERES is found to be 0.43, however the model simulated SW radiation at the TOA showed an underestimation with respect to CERES. The shortwave aerosol radiative forcing (SWARF) during the event over surface and TOA are ∼ -19.3 and ∼ -14.2 Wm-2 respectively, which is about 2-5 times higher when compared to the respective forcing values during non-dust days. Estimated net radiative forcing was in the range of -13 to -21 Wm-2 at TOA and -12 to -20 Wm-2 at the surface. The heating rate during event days within the lower atmosphere near 850 hPa is found to 0.32 - 0.4 K day-1 and 0.18 - 0.22 K day-1 on dusty and non-dusty days, respectively. Results of this study may be useful for a better modeling of atmospheric aerosols and its optical and radiative properties over oceanic region.

Development of an aerosol microphysical module: Aerosol Two-dimensional bin module for foRmation and Aging Simulation (ATRAS)

NASA Astrophysics Data System (ADS)

Matsui, H.; Koike, M.; Kondo, Y.; Fast, J. D.; Takigawa, M.

2014-09-01

Number concentrations, size distributions, and mixing states of aerosols are essential parameters for accurate estimations of aerosol direct and indirect effects. In this study, we develop an aerosol module, designated the Aerosol Two-dimensional bin module for foRmation and Aging Simulation (ATRAS), that can explicitly represent these parameters by considering new particle formation (NPF), black carbon (BC) aging, and secondary organic aerosol (SOA) processes. A two-dimensional bin representation is used for particles with dry diameters from 40 nm to 10 μm to resolve both aerosol sizes (12 bins) and BC mixing states (10 bins) for a total of 120 bins. The particles with diameters between 1 and 40 nm are resolved using additional eight size bins to calculate NPF. The ATRAS module is implemented in the WRF-Chem model and applied to examine the sensitivity of simulated mass, number, size distributions, and optical and radiative parameters of aerosols to NPF, BC aging, and SOA processes over East Asia during the spring of 2009. The BC absorption enhancement by coating materials is about 50% over East Asia during the spring, and the contribution of SOA processes to the absorption enhancement is estimated to be 10-20% over northern East Asia and 20-35% over southern East Asia. A clear north-south contrast is also found between the impacts of NPF and SOA processes on cloud condensation nuclei (CCN) concentrations: NPF increases CCN concentrations at higher supersaturations (smaller particles) over northern East Asia, whereas SOA increases CCN concentrations at lower supersaturations (larger particles) over southern East Asia. The application of ATRAS in East Asia also shows that the impact of each process on each optical and radiative parameter depends strongly on the process and the parameter in question. The module can be used in the future as a benchmark model to evaluate the accuracy of simpler aerosol models and examine interactions between NPF, BC aging, and SOA processes under different meteorological conditions and emissions.

Cultures of simulations vs. cultures of calculations? The development of simulation practices in meteorology and astrophysics

NASA Astrophysics Data System (ADS)

Sundberg, Mikaela

While the distinction between theory and experiment is often used to discuss the place of simulation from a philosophical viewpoint, other distinctions are possible from a sociological perspective. Turkle (1995) distinguishes between cultures of calculation and cultures of simulation and relates these cultures to the distinction between modernity and postmodernity, respectively. What can we understand about contemporary simulation practices in science by looking at them from the point of view of these two computer cultures? What new questions does such an analysis raise for further studies? On the basis of two case studies, the present paper compares and discusses simulation activities in astrophysics and meteorology. It argues that simulation practices manifest aspects of both of these cultures simultaneously, but in different situations. By employing the dichotomies surface/depth, play/seriousness, and extreme/reasonable to characterize and operationalize cultures of calculation and cultures of simulation as sensitizing concepts, the analysis shows how simulation code work shifts from development to use, the importance of but also resistance towards too much visualizations, and how simulation modelers play with extreme values, yet also try to achieve reasonable results compared to observations.

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

NASA Astrophysics Data System (ADS)

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

2013-07-01

Comprehensive model evaluation and comparison of two 3-D air quality modeling systems (i.e., the Weather Research and Forecast model (WRF)/Polyphemus and WRF with chemistry and the Model of Aerosol Dynamics, Reaction, Ionization, and Dissolution (MADRID) (WRF/Chem-MADRID)) are conducted over Western Europe. Part 1 describes the background information for the model comparison and simulation design, the application of WRF for January and July 2001 over triple-nested domains in Western Europe at three horizontal grid resolutions: 0.5°, 0.125°, and 0.025°, and the effect of aerosol/meteorology interactions on meteorological predictions. Nine simulated meteorological variables (i.e., downward shortwave and longwave radiation fluxes (SWDOWN and LWDOWN), outgoing longwave radiation flux (OLR), temperature at 2 m (T2), specific humidity at 2 m (Q2), relative humidity at 2 m (RH2), wind speed at 10 m (WS10), wind direction at 10 m (WD10), and precipitation (Precip)) are evaluated using available observations in terms of spatial distribution, domainwide daily and site-specific hourly variations, and domainwide performance statistics. The vertical profiles of temperature, dew points, and wind speed/direction are also evaluated using sounding data. WRF demonstrates its capability in capturing diurnal/seasonal variations and spatial gradients and vertical profiles of major meteorological variables. While the domainwide performance of LWDOWN, OLR, T2, Q2, and RH2 at all three grid resolutions is satisfactory overall, large positive or negative biases occur in SWDOWN, WS10, and Precip even at 0.125° or 0.025° in both months and in WD10 in January. In addition, discrepancies between simulations and observations exist in T2, Q2, WS10, and Precip at mountain/high altitude sites and large urban center sites in both months, in particular, during snow events or thunderstorms. These results indicate the model's difficulty in capturing meteorological variables in complex terrain and 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 (e.g., shortwave radiation, cloud microphysics, cumulus parameterizations, and ice nucleation treatments) as well as limitations in surface heat and moisture budget parameterizations (e.g., snow-related processes, subgrid-scale surface roughness elements, and urban canopy/heat island treatments and CO2 domes). While the use of finer grid resolutions of 0.125° and 0.025° shows some improvements for WS10, WD10, Precip, and some mesoscale events (e.g., strong forced convection and heavy precipitation), it does not significantly improve the overall statistical performance for all meteorological variables except for Precip. The WRF/Chem simulations with and without aerosols show that aerosols lead to reduced net shortwave radiation fluxes, 2 m temperature, 10 m wind speed, planetary boundary layer (PBL) height, and precipitation and increase aerosol optical depth, cloud condensation nuclei, cloud optical depth, and cloud droplet number concentrations over most of the domain. These results indicate a need to further improve the model representations of the above parameterizations as well as aerosol-meteorology interactions at all scales.

Sensitivity of the Community Multiscale Air Quality (CMAQ) Model v4.7 Results for the Eastern United States to MM5 and WRF Meteorological Drivers

EPA Science Inventory

This paper presents a comparison of the operational performance of two Community Multiscale Air Quality (CMAQ) model v4.7 simulations that utilize input data from the 5th generation Mesoscale Model MM5 and the Weather Research and Forecasting (WRF) meteorological models.

Implications of climate variability for monitoring the effectiveness of global mercury policy

NASA Astrophysics Data System (ADS)

Giang, A.; Monier, E.; Couzo, E. A.; Pike-thackray, C.; Selin, N. E.

2016-12-01

We investigate how climate variability affects ability to detect policy-related anthropogenic changes in mercury emissions in wet deposition monitoring data using earth system and atmospheric chemistry modeling. The Minamata Convention, a multilateral environmental agreement that aims to protect human health and the environment from anthropogenic emissions and releases of mercury, includes provisions for monitoring treaty effectiveness. Because meteorology can affect mercury chemistry and transport, internal variability is an important contributor to uncertainty in how effective policy may be in reducing the amount of mercury entering ecosystems through wet deposition. We simulate mercury chemistry using the GEOS-Chem global transport model to assess the influence of meteorology in the context of other uncertainties in mercury cycling and policy. In these simulations, we find that interannual variability in meteorology may be a dominant contributor to the spatial pattern and magnitude of historical regional wet deposition trends. To further assess the influence of climate variability in the GEOS-Chem mercury simulation, we use a 5-member ensemble of meteorological fields from the MIT Integrated Global System Model under present and future climate. Each member involves randomly initialized 20 year simulations centered around 2000 and 2050 (under a no-policy and a climate stabilization scenario). Building on previous efforts to understand climate-air quality interactions for ground-level O3 and particulate matter, we estimate from the ensemble the range of trends in mercury wet deposition given natural variability, and, to extend our previous results on regions that are sensitive to near-source vs. remote anthropogenic signals, we identify geographic regions where mercury wet deposition is most sensitive to this variability. We discuss how an improved understanding of natural variability can inform the Conference of Parties on monitoring strategy and policy ambition.

Present and Future Projections of Habitat Suitability of the Asian Tiger Mosquito, a Vector of Viral Pathogens, from Global Climate Simulations.

NASA Astrophysics Data System (ADS)

Proestos, Y.; Christophides, G.; Erguler, K.; Tanarhte, M.; Waldock, J.; Lelieveld, J.

2014-12-01

Climate change can influence the transmission of vector borne diseases (VBDs) through altering the habitat suitability of insect vectors. Here we present global climate model simulations and evaluate the associated uncertainties in view of the main meteorological factors that may affect the distribution of the Asian Tiger mosquito (Aedes albopictus), which can transmit pathogens that cause Chikungunya, Dengue fever, yellow fever and various encephalitides. Using a general circulation model (GCM) at 50 km horizontal resolution to simulate mosquito survival variables including temperature, precipitation and relative humidity, we present both global and regional projections of the habitat suitability up to the middle of the 21st century. The model resolution of 50 km allows evaluation against previous projections for Europe and provides a basis for comparative analyses with other regions. Model uncertainties and performance are addressed in light of the recent CMIP5 ensemble climate model simulations for the RCP8.5 concentration pathway and using meteorological re-analysis data (ERA-Interim/ECMWF) for the recent past. Uncertainty ranges associated with the thresholds of meteorological variables that may affect the distribution of Ae. albopictus are diagnosed using fuzzy-logic methodology, notably to assess the influence of selected meteorological criteria and combinations of criteria that influence mosquito habitat suitability. From the climate projections for 2050, and adopting a habitat suitability index larger than 70%, we estimate that about 2.4 billion individuals in a land area of nearly 20 million square kilometres will potentially be exposed to Ae. albopictus. The synthesis of fuzzy-logic based on mosquito biology and climate change analysis provides new insights into the regional and global spreading of VBDs to support disease control and policy making.

Testing the Joint UK Land Environment Simulator (JULES) for flood forecasting

NASA Astrophysics Data System (ADS)

Batelis, Stamatios-Christos; Rosolem, Rafael; Han, Dawei; Rahman, Mostaquimur

2017-04-01

Land Surface Models (LSM) are based on physics principles and simulate the exchanges of energy, water and biogeochemical cycles between the land surface and lower atmosphere. Such models are typically applied for climate studies or effects of land use changes but as the resolution of LSMs and supporting observations are continuously increasing, its representation of hydrological processes need to be addressed adequately. For example, changes in climate and land use can alter the hydrology of a region, for instance, by altering its flooding regime. LSMs can be a powerful tool because of their ability to spatially represent a region with much finer resolution. However, despite such advantages, its performance has not been extensively assessed for flood forecasting simply because its representation of typical hydrological processes, such as overland flow and river routing, are still either ignored or roughly represented. In this study, we initially test the Joint UK Land Environment Simulator (JULES) as a flood forecast tool focusing on its river routing scheme. In particular, JULES river routing parameterization is based on the Rapid Flow Model (RFM) which relies on six prescribed parameters (two surface and two subsurface wave celerities, and two return flow fractions). Although this routing scheme is simple, the prescription of its six default parameters is still too generalized. Our aim is to understand the importance of each RFM parameter in a series of JULES simulations at a number of catchments in the UK for the 2006-2015 period. This is carried out, for instance, by making a number of assumptions of parameter behaviour (e.g., spatially uniform versus varying and/or temporally constant or time-varying parameters within each catchment). Hourly rainfall radar in combination with the CHESS (Climate, Hydrological and Ecological research Support System) meteorological daily data both at 1 km2 resolution are used. The evaluation of the model is based on hourly runoff data provided by the National River Flood Archive using a number of model performance metrics. We use a calibrated conceptually-based lumped model, more typically applied in flood studies, as a benchmark for our analysis.

Modelling the association of dengue fever cases with temperature and relative humidity in Jeddah, Saudi Arabia-A generalised linear model with break-point analysis.

PubMed

Alkhaldy, Ibrahim

2017-04-01

The aim of this study was to examine the role of environmental factors in the temporal distribution of dengue fever in Jeddah, Saudi Arabia. The relationship between dengue fever cases and climatic factors such as relative humidity and temperature was investigated during 2006-2009 to determine whether there is any relationship between dengue fever cases and climatic parameters in Jeddah City, Saudi Arabia. A generalised linear model (GLM) with a break-point was used to determine how different levels of temperature and relative humidity affected the distribution of the number of cases of dengue fever. Break-point analysis was performed to modelled the effect before and after a break-point (change point) in the explanatory parameters under various scenarios. Akaike information criterion (AIC) and cross validation (CV) were used to assess the performance of the models. The results showed that maximum temperature and mean relative humidity are most probably the better predictors of the number of dengue fever cases in Jeddah. In this study three scenarios were modelled: no time lag, 1-week lag and 2-weeks lag. Among these scenarios, the 1-week lag model using mean relative humidity as an explanatory variable showed better performance. This study showed a clear relationship between the meteorological variables and the number of dengue fever cases in Jeddah. The results also demonstrated that meteorological variables can be successfully used to estimate the number of dengue fever cases for a given period of time. Break-point analysis provides further insight into the association between meteorological parameters and dengue fever cases by dividing the meteorological parameters into certain break-points. Copyright © 2016 Elsevier B.V. All rights reserved.

Fundamental statistical relationships between monthly and daily meteorological variables: Temporal downscaling of weather based on a global observational dataset

NASA Astrophysics Data System (ADS)

Sommer, Philipp; Kaplan, Jed

2016-04-01

Accurate modelling of large-scale vegetation dynamics, hydrology, and other environmental processes requires meteorological forcing on daily timescales. While meteorological data with high temporal resolution is becoming increasingly available, simulations for the future or distant past are limited by lack of data and poor performance of climate models, e.g., in simulating daily precipitation. To overcome these limitations, we may temporally downscale monthly summary data to a daily time step using a weather generator. Parameterization of such statistical models has traditionally been based on a limited number of observations. Recent developments in the archiving, distribution, and analysis of "big data" datasets provide new opportunities for the parameterization of a temporal downscaling model that is applicable over a wide range of climates. Here we parameterize a WGEN-type weather generator using more than 50 million individual daily meteorological observations, from over 10'000 stations covering all continents, based on the Global Historical Climatology Network (GHCN) and Synoptic Cloud Reports (EECRA) databases. Using the resulting "universal" parameterization and driven by monthly summaries, we downscale mean temperature (minimum and maximum), cloud cover, and total precipitation, to daily estimates. We apply a hybrid gamma-generalized Pareto distribution to calculate daily precipitation amounts, which overcomes much of the inability of earlier weather generators to simulate high amounts of daily precipitation. Our globally parameterized weather generator has numerous applications, including vegetation and crop modelling for paleoenvironmental studies.

Effects of Meteorological Variability on the Thermosphere-Ionosphere System during the Moderate Geomagnetic Disturbed January 2013 Period As Simulated By Time-GCM

NASA Astrophysics Data System (ADS)

Maute, A. I.; Hagan, M. E.; Richmond, A. D.; Liu, H.; Yudin, V. A.

2014-12-01

The ionosphere-thermosphere system is affected by solar and magnetospheric processes and by meteorological variability. Ionospheric observations of total electron content during the current solar cycle have shown that variability associated with meteorological forcing is important during solar minimum, and can have significant ionospheric effects during solar medium to maximum conditions. Numerical models can be used to study the comparative importance of geomagnetic and meterological forcing.This study focuses on the January 2013 Stratospheric Sudden Warming (SSW) period, which is associated with a very disturbed middle atmosphere as well as with moderately disturbed solar geomagntic conditions. We employ the NCAR Thermosphere-Ionosphere-Mesosphere-Electrodynamics General Circulation Model (TIME-GCM) with a nudging scheme using Whole-Atmosphere-Community-Climate-Model-Extended (WACCM-X)/Goddard Earth Observing System Model, Version 5 (GEOS5) results to simulate the effects of the meteorological and solar wind forcing on the upper atmosphere. The model results are evaluated by comparing with observations e.g., TEC, NmF2, ion drifts. We study the effect of the SSW on the wave spectrum, and the associated changes in the low latitude vertical drifts. These changes are compared to the impact of the moderate geomagnetic forcing on the TI-system during the January 2013 time period by conducting numerical experiments. We will present select highlights from our study and elude to the comparative importance of the forcing from above and below as simulated by the TIME-GCM.

Meteorological Modeling of Wintertime Cold Air Pool Stagnation Episodes in the Uintah and Salt Lake Basins

NASA Astrophysics Data System (ADS)

Crosman, E.; Horel, J.; Blaylock, B. K.; Foster, C.

2014-12-01

High wintertime ozone concentrations in rural areas associated with oil and gas development and high particulate concentrations in urban areas have become topics of increasing concern in the Western United States, as both primary and secondary pollutants become trapped within stable wintertime boundary layers. While persistent cold air pools that enable such poor wintertime air quality are typically associated with high pressure aloft and light winds, the complex physical processes that contribute to the formation, maintenance, and decay of persistent wintertime temperature inversions are only partially understood. In addition, obtaining sufficiently accurate numerical weather forecasts and meteorological simulations of cold air pools for input into chemical models remains a challenge. This study examines the meteorological processes associated with several wintertime pollution episodes in Utah's Uintah and Salt Lake Basins using numerical Weather Research and Forecasting model simulations and observations collected from the Persistent Cold Air Pool and Uintah Basin Ozone Studies. The temperature, vertical structure, and winds within these cold air pools was found to vary as a function of snow cover, snow albedo, land use, cloud cover, large-scale synoptic flow, and episode duration. We evaluate the sensitivity of key atmospheric features such as stability, planetary boundary layer depth, local wind flow patterns and transport mechanisms to variations in surface forcing, clouds, and synoptic flow. Finally, noted deficiencies in the meteorological models of cold air pools and modifications to the model snow and microphysics treatment that have resulted in improved cold pool simulations will be presented.

Temporal modelling and forecasting of the airborne pollen of Cupressaceae on the southwestern Iberian Peninsula.

PubMed

Silva-Palacios, Inmaculada; Fernández-Rodríguez, Santiago; Durán-Barroso, Pablo; Tormo-Molina, Rafael; Maya-Manzano, José María; Gonzalo-Garijo, Ángela

2016-02-01

Cupressaceae includes species cultivated as ornamentals in the urban environment. This study aims to investigate airborne pollen data for Cupressaceae on the southwestern Iberian Peninsula over a 21-year period and to analyse the trends in these data and their relationship with meteorological parameters using time series analysis. Aerobiological sampling was conducted from 1993 to 2013 in Badajoz (SW Spain). The main pollen season for Cupressaceae lasted, on average, 58 days, ranging from 55 to 112 days, from 24 January to 22 March. Furthermore, a short-term forecasting model has been developed for daily pollen concentrations. The model proposed to forecast the airborne pollen concentration is described by one equation. This expression is composed of two terms: the first term represents the pollen concentration trend in the air according to the average concentration of the previous 10 days; the second term is obtained from considering the actual pollen concentration value, which is calculated based on the most representative meteorological parameters multiplied by a fitting coefficient. Temperature was the main meteorological factor by its influence over daily pollen forecast, being the rain the second most important factor. This model represents a good approach to a continuous balance model of Cupressaceae pollen concentration and is supported by a close agreement between the observed and predicted mean concentrations. The novelty of the proposed model is the analysis of meteorological parameters that are not frequently used in Aerobiology.

Evaluating WRF Simulations of Urban Boundary Layer Processes during DISCOVER-AQ

NASA Astrophysics Data System (ADS)

Hegarty, J. D.; Henderson, J.; Lewis, J. R.; McGrath-Spangler, E. L.; Scarino, A. J.; Ferrare, R. A.; DeCola, P.; Welton, E. J.

2015-12-01

The accurate representation of processes in the planetary boundary layer (PBL) in meteorological models is of prime importance to air quality and greenhouse gas simulations as it governs the depth to which surface emissions are vertically mixed and influences the efficiency by which they are transported downwind. In this work we evaluate high resolution (~1 km) WRF simulations of PBL processes in the Washington DC - Baltimore and Houston urban areas during the respective DISCOVER-AQ 2011 and 2013 field campaigns using MPLNET micro-pulse lidar (MPL), mini-MPL, airborne high spectral resolution lidar (HSRL), Doppler wind profiler and CALIPSO satellite measurements along with complimentary surface and aircraft measurements. We will discuss how well WRF simulates the spatiotemporal variability of the PBL height in the urban areas and the development of fine-scale meteorological features such as bay and sea breezes that influence the air quality of the urban areas studied.

A "simulation chain" to define a Multidisciplinary Decision Support System for landslide risk management in pyroclastic soils

NASA Astrophysics Data System (ADS)

Damiano, E.; Mercogliano, P.; Netti, N.; Olivares, L.

2012-04-01

This paper proposes a Multidisciplinary Decision Support System (MDSS) as an approach to manage rainfall-induced shallow landslides of the flow type (flowslides) in pyroclastic deposits. We stress the need to combine information from the fields of meteorology, geology, hydrology, geotechnics and economics to support the agencies engaged in land monitoring and management. The MDSS consists of a "simulation chain" to link rainfall to effects in terms of infiltration, slope stability and vulnerability. This "simulation chain" was developed at the Euro-Mediterranean Centre for Climate Change (CMCC) (meteorological aspects), at the Geotechnical Laboratory of the Second University of Naples (hydrological and geotechnical aspects) and at the Department of Economics of the University of Naples "Federico II" (economic aspects). The results obtained from the application of this simulation chain in the Cervinara area during eleven years of research allowed in-depth analysis of the mechanisms underlying a flowslide in pyroclastic soil.

Detection of mesoscale zones of atmospheric instabilities using remote sensing and weather forecasting model data

NASA Astrophysics Data System (ADS)

Winnicki, I.; Jasinski, J.; Kroszczynski, K.; Pietrek, S.

2009-04-01

The paper presents elements of research conducted in the Faculty of Civil Engineering and Geodesy of the Military University of Technology, Warsaw, Poland, concerning application of mesoscale models and remote sensing data to determining meteorological conditions of aircraft flight directly related with atmospheric instabilities. The quality of meteorological support of aviation depends on prompt and effective forecasting of weather conditions changes. The paper presents a computer module for detecting and monitoring zones of cloud cover, precipitation and turbulence along the aircraft flight route. It consists of programs and scripts for managing, processing and visualizing meteorological and remote sensing databases. The application was developed in Matlab® for Windows®. The module uses products of COAMPS (Coupled Ocean/Atmosphere Mesoscale Prediction System) mesoscale non-hydrostatic model of the atmosphere developed by the US Naval Research Laboratory, satellite images acquisition system from the MSG-2 (Meteosat Second Generation) of the European Organization for the Exploitation of Meteorological Satellites (EUMETSAT) and meteorological radars data acquired from the Institute of Meteorology and Water Management (IMGW), Warsaw, Poland. The satellite images acquisition system and the COAMPS model are run operationally in the Faculty of Civil Engineering and Geodesy. The mesoscale model is run on an IA64 Feniks multiprocessor 64-bit computer cluster. The basic task of the module is to enable a complex analysis of data sets of miscellaneous information structure and to verify COAMPS results using satellite and radar data. The research is conducted using uniform cartographic projection of all elements of the database. Satellite and radar images are transformed into the Lambert Conformal projection of COAMPS. This facilitates simultaneous interpretation and supports decision making process for safe execution of flights. Forecasts are based on horizontal distributions and vertical profiles of meteorological parameters produced by the module. Verification of forecasts includes research of spatial and temporal correlations of structures generated by the model, e.g.: cloudiness, meteorological phenomena (fogs, precipitation, turbulence) and structures identified on current satellite images. The developed module determines meteorological parameters fields for vertical profiles of the atmosphere. Interpolation procedures run at user selected standard (pressure) or height levels of the model enable to determine weather conditions along any route of aircraft. Basic parameters of the procedures determining e.g. flight safety include: cloud base, visibility, cloud cover, turbulence coefficient, icing and precipitation intensity. Determining icing and turbulence characteristics is based on standard and new methods (from other mesoscale models). The research includes also investigating new generation mesoscale models, especially remote sensing data assimilation. This is required by necessity to develop and introduce objective methods of forecasting weather conditions. Current research in the Faculty of Civil Engineering and Geodesy concerns validation of the mesoscale module performance.

60 years of UK visibility measurements: impact of meteorology and atmospheric pollutants on visibility

NASA Astrophysics Data System (ADS)

Singh, Ajit; Bloss, William J.; Pope, Francis D.

2017-02-01

Reduced visibility is an indicator of poor air quality. Moreover, degradation in visibility can be hazardous to human safety; for example, low visibility can lead to road, rail, sea and air accidents. In this paper, we explore the combined influence of atmospheric aerosol particle and gas characteristics, and meteorology, on long-term visibility. We use visibility data from eight meteorological stations, situated in the UK, which have been running since the 1950s. The site locations include urban, rural and marine environments. Most stations show a long-term trend of increasing visibility, which is indicative of reductions in air pollution, especially in urban areas. Additionally, the visibility at all sites shows a very clear dependence on relative humidity, indicating the importance of aerosol hygroscopicity on the ability of aerosol particles to scatter radiation. The dependence of visibility on other meteorological parameters, such as wind speed and wind direction, is also investigated. Most stations show long-term increases in temperature which can be ascribed to climate change, land-use changes (e.g. urban heat island effects) or a combination of both; the observed effect is greatest in urban areas. The impact of this temperature change upon local relative humidity is discussed. To explain the long-term visibility trends and their dependence on meteorological conditions, the measured data were fitted to a newly developed light-extinction model to generate predictions of historic aerosol and gas scattering and absorbing properties. In general, an excellent fit was achieved between measured and modelled visibility for all eight sites. The model incorporates parameterizations of aerosol hygroscopicity, particle concentration, particle scattering, and particle and gas absorption. This new model should be applicable and is easily transferrable to other data sets worldwide. Hence, historical visibility data can be used to assess trends in aerosol particle properties. This approach may help constrain global model simulations which attempt to generate aerosol fields for time periods when observational data are scarce or non-existent. Both the measured visibility and the modelled aerosol properties reported in this paper highlight the success of the UK's Clean Air Act, which was passed in 1956, in cleaning the atmosphere of visibility-reducing pollutants.

Vertical PM10 Characteristics and their Relation with Tropospheric Meteorology over Hong Kong

NASA Astrophysics Data System (ADS)

Hei Tong, Cheuk

2016-04-01

Small particulates or PM10, those with aerodynamic diameters less than 10 mm, can cause long term impairment to human health as they can penetrate deep and deposit on the wall of the respiratory system. Hong Kong receives significant concentration of cross-boundary particulates but at the same time produce domestic pollutants which altogether contribute to the total pollution problem. Recent research interest is paying more attention on the vertical characteristic of PM in the lower atmosphere as possible correlations exist along different altitude. Besides, there exists potential relationship between PM concentration aloft and the high-level weather condition. Yet, most studies focus only up to around 200 meters above sea level due to the proposed significance and the lack of technology. Undoubtedly, this is not enough in investigating the relation between vertical atmospheric profile and PM vertical characteristics. New technology development has allowed measuring PM concentration along the vertical atmospheric profile up to tropopause. This measurement relies on the Atmospheric Light Detection and Ranging (LiDAR) which operates using the radar principle to detect Rayleigh and Mie scattering from atmospheric gas and aerosols. The research involves (1) study of the seasonal vertical PM10 characteristics in five studying site of Hong Kong covering urban, suburban and rural area; (2) the relationship of the PM10 characteristics with meteorological parameters; (3) the vertical PM10 characteristics under the approach of tropical cyclones. A portable Micro Pulse Lidar (MPL) is adopted to collect PM data aloft while surface PM data is collected from ground stations. High-level meteorology data is received from Hong Kong Observatory. Statistical analyses are operated to investigate the correlation between weather conditions and PM concentration along the vertical profile. The research study is divided in phrases. The ultimate goal of the study is to develop models simulating high-level PM concentration under different meteorological conditions and predict the impacts under global and urban climate change. Keywords: PM10; High level meteorology; Seasonal variations; Tropical cyclone; Hong Kong; LiDAR

Simulating land-atmosphere feedbacks and response to widespread forest disturbance: The role of lower boundary configuration and dynamic water table in meteorological modeling

NASA Astrophysics Data System (ADS)

Forrester, M.; Maxwell, R. M.; Bearup, L. A.; Gochis, D.

2017-12-01

Numerical meteorological models are frequently used to diagnose land-atmosphere interactions and predict large-scale response to extreme or hazardous events, including widespread land disturbance or perturbations to near-surface moisture. However, few atmospheric modeling platforms consider the impact that dynamic groundwater storage, specifically 3D subsurface flow, has on land-atmosphere interactions. In this study, we use the Weather Research and Forecasting (WRF) mesoscale meteorological model to identify ecohydrologic and land-atmosphere feedbacks to disturbance by the mountain pine beetle (MPB) over the Colorado Headwaters region. Disturbance simulations are applied to WRF with various lower boundary configurations: Including default Noah land surface model soil moisture representation; a version of WRF coupled to ParFlow (PF), an integrated groundwater-surface water model that resolves variably saturated flow in the subsurface; and WRF coupled to PF in a static water table version, simulating only vertical and no lateral subsurface flow. Our results agree with previous literature showing MPB-induced reductions in canopy transpiration in all lower boundary scenarios, as well as energy repartitioning, higher water tables, and higher planetary boundary layer over infested regions. Simulations show that expanding from local to watershed scale results in significant damping of MPB signal as unforested and unimpacted regions are added; and, while deforestation appears to have secondary feedbacks to planetary boundary layer and convection, these slight perturbations to cumulative summer precipitation are insignificant in the context of ensemble methodologies. Notably, the results suggest that groundwater representation in atmospheric modeling affects the response intensity of a land disturbance event. In the WRF-PF case, energy and atmospheric processes are more sensitive to disturbance in regions with higher water tables. Also, when dynamic subsurface hydrology is removed, WRF simulates a greater response to MPB at the land-atmosphere interface, including greater changes to daytime skin temperature, Bowen ratio and near-surface humidity. These findings highlight lower boundary representations in computational meteorology and numerical land-atmosphere modeling.

Simulating large-scale crop yield by using perturbed-parameter ensemble method

NASA Astrophysics Data System (ADS)

Iizumi, T.; Yokozawa, M.; Sakurai, G.; Nishimori, M.

2010-12-01

Toshichika Iizumi, Masayuki Yokozawa, Gen Sakurai, Motoki Nishimori Agro-Meteorology Division, National Institute for Agro-Environmental Sciences, Japan Abstract One of concerning issues of food security under changing climate is to predict the inter-annual variation of crop production induced by climate extremes and modulated climate. To secure food supply for growing world population, methodology that can accurately predict crop yield on a large scale is needed. However, for developing a process-based large-scale crop model with a scale of general circulation models (GCMs), 100 km in latitude and longitude, researchers encounter the difficulties in spatial heterogeneity of available information on crop production such as cultivated cultivars and management. This study proposed an ensemble-based simulation method that uses a process-based crop model and systematic parameter perturbation procedure, taking maize in U.S., China, and Brazil as examples. The crop model was developed modifying the fundamental structure of the Soil and Water Assessment Tool (SWAT) to incorporate the effect of heat stress on yield. We called the new model PRYSBI: the Process-based Regional-scale Yield Simulator with Bayesian Inference. The posterior probability density function (PDF) of 17 parameters, which represents the crop- and grid-specific features of the crop and its uncertainty under given data, was estimated by the Bayesian inversion analysis. We then take 1500 ensemble members of simulated yield values based on the parameter sets sampled from the posterior PDF to describe yearly changes of the yield, i.e. perturbed-parameter ensemble method. The ensemble median for 27 years (1980-2006) was compared with the data aggregated from the county yield. On a country scale, the ensemble median of the simulated yield showed a good correspondence with the reported yield: the Pearson’s correlation coefficient is over 0.6 for all countries. In contrast, on a grid scale, the correspondence is still high in most grids regardless of the countries. However, the model showed comparatively low reproducibility in the slope areas, such as around the Rocky Mountains in South Dakota, around the Great Xing'anling Mountains in Heilongjiang, and around the Brazilian Plateau. As there is a wide-ranging local climate conditions in the complex terrain, such as the slope of mountain, the GCM grid-scale weather inputs is likely one of major sources of error. The results of this study highlight the benefits of the perturbed-parameter ensemble method in simulating crop yield on a GCM grid scale: (1) the posterior PDF of parameter could quantify the uncertainty of parameter value of the crop model associated with the local crop production aspects; (2) the method can explicitly account for the uncertainty of parameter value in the crop model simulations; (3) the method achieve a Monte Carlo approximation of probability of sub-grid scale yield, accounting for the nonlinear response of crop yield to weather and management; (4) the method is therefore appropriate to aggregate the simulated sub-grid scale yields to a grid-scale yield and it may be a reason for high performance of the model in capturing inter-annual variation of yield.

Status, trends, and changes in freshwater inflows to bay systems in the Corpus Christi Bay National Estuary Program study area

USGS Publications Warehouse

Asquith, W.H.; Mosier, J. G.; Bush, P.W.

1997-01-01

The watershed simulation model Hydrologic Simulation Program—Fortran (HSPF) was used to generate simulated flow (runoff) from the 13 watersheds to the six bay systems because adequate gaged streamflow data from which to estimate freshwater inflows are not available; only about 23 percent of the adjacent contributing watershed area is gaged. The model was calibrated for the gaged parts of three watersheds—that is, selected input parameters (meteorologic and hydrologic properties and conditions) that control runoff were adjusted in a series of simulations until an adequate match between model-generated flows and a set (time series) of gaged flows was achieved. The primary model input is rainfall and evaporation data and the model output is a time series of runoff volumes. After calibration, simulations driven by daily rainfall for a 26-year period (1968–93) were done for the 13 watersheds to obtain runoff under current (1983–93), predevelopment (pre-1940 streamflow and pre-urbanization), and future (2010) land-use conditions for estimating freshwater inflows and for comparing runoff under the three land-use conditions; and to obtain time series of runoff from which to estimate time series of freshwater inflows for trend analysis.

Study on wet scavenging of atmospheric pollutants in south Brazil

NASA Astrophysics Data System (ADS)

Wiegand, Flavio; Pereira, Felipe Norte; Teixeira, Elba Calesso

2011-09-01

The present paper presents the study of in-cloud and below-cloud SO 2 and SO 42-scavenging processes by applying numerical models in the Candiota region, located in the state of Rio Grande do Sul, South Brazil. The BRAMS (Brazilian Regional Atmospheric Modeling System) model was applied to simulate the vertical structure of the clouds, and the B.V.2 (Below-Cloud Beheng Version 2) scavenging model was applied to simulate in-cloud and below-cloud scavenging processes of the pollutants SO 2 and SO 42-. Five events in 2004 were selected for this study and were sampled at the Candiota Airport station. The concentrations of SO 2 and SO 42- sampled in the air and the simulated meteorological parameters of rainfall episodes were used as input data in the B.V.2, which simulates raindrop interactions associated with the scavenging process. Results for the Candiota region showed that in-cloud scavenging processes were more significant than below-cloud scavenging processes for two of the five events studied, with a contribution of approximately 90-100% of SO 2 and SO 42- concentrations in rainwater. A few adjustments to the original version of B.V.2 were made to allow simulation of scavenging processes in several types of clouds, not only cumulus humilis and cumulus congestus.

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

USGS Publications Warehouse

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

2003-01-01

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

Mapping the Martian Meteorology

NASA Technical Reports Server (NTRS)

Allison, M.; Ross, J. D.; Solomon, N.

1999-01-01

The Mars-adapted version of the NASA/GISS general circulation model (GCM) has been applied to the hourly/daily simulation of the planet's meteorology over several seasonal orbits. The current running version of the model includes a diurnal solar cycle, CO2 sublimation, and a mature parameterization of upper level wave drag with a vertical domain extending from the surface up to the 6microb level. The benchmark simulations provide a four-dimensional archive for the comparative evaluation of various schemes for the retrieval of winds from anticipated polar orbiter measurements of temperatures by the Pressure Modulator Infrared Radiometer. Additional information is contained in the original extended abstract.

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

Patnaik, P. C.

The SIGMET mesoscale meteorology simulation code represents an extension, in terms of physical modelling detail and numerical approach, of the work of Anthes (1972) and Anthes and Warner (1974). The code utilizes a finite difference technique to solve the so-called primitive equations which describe transient flow in the atmosphere. The SIGMET modelling contains all of the physics required to simulate the time dependent meteorology of a region with description of both the planetary boundary layer and upper level flow as they are affected by synoptic forcing and complex terrain. The mathematical formulation of the SIGMET model and the various physicalmore » effects incorporated into it are summarized.« less

Seltzer_et_al_2016

EPA Pesticide Factsheets

This dataset supports the modeling study of Seltzer et al. (2016) published in Atmospheric Environment. In this study, techniques typically used for future air quality projections are applied to a historical 11-year period to assess the performance of the modeling system when the driving meteorological conditions are obtained using dynamical downscaling of coarse-scale fields without correcting toward higher resolution observations. The Weather Research and Forecasting model and the Community Multiscale Air Quality model are used to simulate regional climate and air quality over the contiguous United States for 2000-2010. The air quality simulations for that historical period are then compared to observations from four national networks. Comparisons are drawn between defined performance metrics and other published modeling results for predicted ozone, fine particulate matter, and speciated fine particulate matter. The results indicate that the historical air quality simulations driven by dynamically downscaled meteorology are typically within defined modeling performance benchmarks and are consistent with results from other published modeling studies using finer-resolution meteorology. This indicates that the regional climate and air quality modeling framework utilized here does not introduce substantial bias, which provides confidence in the method??s use for future air quality projections.This dataset is associated with the following publication:Seltzer, K., C

Studies of vorticity imbalance and stability, moisture budget, atmospheric energetics, and gradients of meteorological parameters during AVE 3

NASA Technical Reports Server (NTRS)

Scoggins, J. R. (Editor)

1978-01-01

Four diagnostic studies of AVE 3. are presented. AVE 3 represents a high wind speed wintertime situation, while most AVE's analyzed previously represented springtime conditions with rather low wind speeds. The general areas of analysis include the examination of budgets of vorticity, moisture, kinetic energy, and potential energy and a synoptic and statistical study of the horizontal gradients of meteorological parameters. Conclusions are integrated with and compared to those obtained in previously analyzed experiments (mostly springtime weather situations) so as to establish a more definitive understanding of the structure and dynamics of the atmosphere under a wide range of synoptic conditions.

An analysis of the first two years of GASP data

NASA Technical Reports Server (NTRS)

Holdeman, J. D.; Nastrom, G. D.; Falconer, P. D.

1977-01-01

Distributions of mean ozone levels from the first two years of data from the NASA Global Atmospheric Sampling Program (GASP) show spatial and temporal variations in agreement with previous measurements. The standard deviations of these distributions reflect the large natural variability of ozone levels in the altitude range of the GASP measurements. Monthly mean levels of ozone below the tropopause show an annual cycle with a spring maximum which is believed to result from transport from the stratosphere. Correlations of ozone with independent meteorological parameters, and meteorological parameters obtained by the GASP systems show that this transport occurs primarily through cyclogenesis at mid-latitudes.

Relationships between stratospheric clear air turbulence and synoptic meteorological parameters over the western United States between 12-20 km altitude

NASA Technical Reports Server (NTRS)

Scoggins, J. R.; Clark, T. L.; Possiel, N. C.

1975-01-01

Procedures for forecasting clear air turbulence in the stratosphere over the western United States from rawinsonde data are described and results presented. Approaches taken to relate meteorological parameters to regions of turbulence and nonturbulence encountered by the XB-70 during 46 flights at altitudes between 12-20 km include: empirical probabilities, discriminant function analysis, and mountainwave theory. Results from these techniques were combined into a procedure to forecast regions of clear air turbulence with an accuracy of 70-80 percent. A computer program was developed to provide an objective forecast directly from the rawinsonde sounding data.

Impact of fugitive sources and meteorological parameters on vertical distribution of particulate matter over the industrial agglomeration.

PubMed

Štrbová, Kristína; Raclavská, Helena; Bílek, Jiří

2017-12-01

The aim of the study was to characterize vertical distribution of particulate matter, in an area well known by highest air pollution levels in Europe. A balloon filled with helium with measuring instrumentation was used for vertical observation of air pollution over the fugitive sources in Moravian-Silesian metropolitan area during spring and summer. Synchronously, selected meteorological parameters were recorded together with particulate matter for exploration its relationship with particulate matter. Concentrations of particulate matter in the vertical profile were significantly higher in the spring than in the summer. Significant effect of fugitive sources was observed up to the altitude ∼255 m (∼45 m above ground) in both seasons. The presence of inversion layer was observed at the altitude ∼350 m (120-135 m above ground) at locations with major source traffic load. Both particulate matter concentrations and number of particles for the selected particle sizes decreased with increasing height. Strong correlation of particulate matter with meteorological parameters was not observed. The study represents the first attempt to assess the vertical profile over the fugitive emission sources - old environmental burdens in industrial region. Copyright © 2017 Elsevier Ltd. All rights reserved.

Meteorological Simulations of Ozone Episode Case Days during the 1996 Paso del Norte Ozone Study

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

Brown, M.J.; Costigan, K.; Muller, C.

1999-02-01

Meteorological simulations centered around the border cities of El Paso and Ciudad Juarez have been performed during an ozone episode that occurred on Aug. 13,1996 during the 1996 Paso del Norte Ozone Study field campaign. Simulations were petiormed using the HOTMAC mesoscale meteorological model using a 1,2,4, and 8 km horizontal grid size nested mesh system. Investigation of the vertical structure and evolution of the atmospheric boundary layer for the Aug. 11-13 time period is emphasized in this paper. Comparison of model-produced wind speed profiles to rawirisonde and radar profiler measurements shows reasonable agreement. A persistent upper-level jet was capturedmore » in the model simulations through data assimilation. In the evening hours, the model was not able to produce the strong wind direction shear seen in the radar wind profiles. Based on virtual potential temperature profile comparisons, the model appears to correctly simulate the daytime growth of the convective mixed layer. However, the model underestimates the cooling of the surface layer at night. We found that the upper-level jet significantly impacted the turbulence structure of the boundary layer, leading to relatively high turbulent kinetic energy (tke) values aloft at night. The model indicates that these high tke values aloft enhance the mid-morning growth of the boundary layer. No upper-level turbulence measurements were available to verify this finding, however. Radar profiler-derived mixing heights do indicate relatively rapid morning growth of the mixed layer.« less

Assessing potential changes of chestnut productivity in Europe under future climate conditions

NASA Astrophysics Data System (ADS)

Calheiros, T.; Pereira, M. G.; Pinto, J. G.; Caramelo, L.; Gomes-Laranjo, J.; Dacamara, C. C.

2012-04-01

The European chestnut is cultivated for its nuts and wood. Several studies point to the dependency of chestnut productivity on specific soil and climate characteristics. For instance, this species dislikes chalky and poorly drained soils, appreciates sedimentary, siliceous and acidic to neutral soils. Chestnut trees also seems to appreciate annual mean values of sunlight spanning between 2400 and 2600 h, rainfall ranging between 600 and 1500 mm, mean annual temperature between 9 and 13°C, 27°C being the mean of the maximum temperature (Heiniger and Conedera, 1992; Gomes-Laranjo et al.,2008). The amount of heat between May and October must range between 1800°D and 2400°D (Dinis et al., 2011) . In Poland, the growing season is defined as the period of time when the mean 24-h temperature is greater than 5°C (Wilczynski and Podalski, 2007). In Portugal, maximum photosynthetic activity occurs at 24-28°C for adult trees, but exhibits more than 50% of termoinhibition when the air temperature is above 32°C, which is frequent during summer (Gomes- Laranjo et al., 2006, 2008). Recently Pereira et al (2011) identified a set of meteorological variables/parameters with high impact on chestnut productivity. The main purpose of this work is to assess the potential impacts of future climate change on chestnut productivity in Portugal as well as on European chestnut orchards. First, observed data from the European Climate assessment (ECA) and simulations with the Regional Circulation Model (RCM) COSMO-CLM for recent climate conditions are used to assess the ability of the RCM to model the actual meteorological conditions. Then, ensemble projections from the ECHAM5/COSMO-CLM model chain for two climate scenarios (A1B and B1) are used to estimate the values of relevant meteorological variables and parameters und future climate conditions. Simulated values are then compared with those obtained for present climate. Results point to changes in the spatial and temporal distribution of meteorological variables and parameters. In particular, more severe conditions during spring and summer are expected, especially in the Mediterranean area, with less precipitation and higher temperatures. All these changes will have impacts on chestnut fruits and wood in Europe. Dinis, L-T. J., Ferreira-Cardoso, J., Peixoto, F., Costa, R. e Gomes-Laranjo, J., 2011: Study of morphological and chemical diversity in chestnut trees (var. 'Judia') as a function of temperature sum. Cyta- Journal of food, 9(3): 192-199 Gomes-Laranjo et al., 2008: Differences in photosynthetic apparatus of leaves from different sides of chestnut canopy, Photosynthetica, 46, 63-72. Heiniger,U. And Conedera, M., 1992: Chestnut forests and chestnut cultivation in Switzerland. Proceedings of the International Chestnut Conference, West Virginia University, Morgantown, 10-14 July 1992, 175-178. Pereira, M.G., Caramelo, L., Gouveia, C., Gomes-Laranjo, J., Magalhães, M., 2011: Assessment of weather-related risk on chestnut productivity. Nat. Hazards Earth Syst. Sci., 11, 1-12, doi:10.5194/nhess-11-12-011. Wilczynski, S. And Podlaski, R, 2007: The effect of climate on radial growth of horse chestnut (Aesculus hippocastanum L.) in the Swietokrzki National Park in Central Poland, J.For.Res., 12, 24-23.

Ozone indices based on simple meteorological parameters: potentials and limitations of regression and neural network models

NASA Astrophysics Data System (ADS)

Soja, G.; Soja, A.-M.

This study tested the usefulness of extremely simple meteorological models for the prediction of ozone indices. The models were developed with the input parameters of daily maximum temperature and sunshine duration and are based on a data collection period of three years. For a rural environment in eastern Austria, the meteorological and ozone data of three summer periods have been used to develop functions to describe three ozone exposure indices (daily maximum, 7 h mean 9.00-16.00 h, accumulated ozone dose AOT40). Data sets for other years or stations not included in the development of the models were used as test data to validate the performance of the models. Generally, optimized regression models performed better than simplest linear models, especially in the case of AOT40. For the description of the summer period from May to September, the mean absolute daily differences between observed and calculated indices were 8±6 ppb for the maximum half hour mean value, 6±5 ppb for the 7 h mean and 41±40 ppb h for the AOT40. When the parameters were further optimized to describe individual months separately, the mean absolute residuals decreased by ⩽10%. Neural network models did not always perform better than the regression models. This is attributed to the low number of inputs in this comparison and to the simple architecture of these models (2-2-1). Further factorial analyses of those days when the residuals were higher than the mean plus one standard deviation should reveal possible reasons why the models did not perform well on certain days. It was observed that overestimations by the models mainly occurred on days with partly overcast, hazy or very windy conditions. Underestimations more frequently occurred on weekdays than on weekends. It is suggested that the application of this kind of meteorological model will be more successful in topographically homogeneous regions and in rural environments with relatively constant rates of emission and long-range transport of ozone precursors. Under conditions too demanding for advanced physico/chemical models, the presented models may offer useful alternatives to derive ecologically relevant ozone indices directly from meteorological parameters.

Development of a CSP plant energy yield calculation tool applying predictive models to analyze plant performance sensitivities

NASA Astrophysics Data System (ADS)

Haack, Lukas; Peniche, Ricardo; Sommer, Lutz; Kather, Alfons

2017-06-01

At early project stages, the main CSP plant design parameters such as turbine capacity, solar field size, and thermal storage capacity are varied during the techno-economic optimization to determine most suitable plant configurations. In general, a typical meteorological year with at least hourly time resolution is used to analyze each plant configuration. Different software tools are available to simulate the annual energy yield. Software tools offering a thermodynamic modeling approach of the power block and the CSP thermal cycle, such as EBSILONProfessional®, allow a flexible definition of plant topologies. In EBSILON, the thermodynamic equilibrium for each time step is calculated iteratively (quasi steady state), which requires approximately 45 minutes to process one year with hourly time resolution. For better presentation of gradients, 10 min time resolution is recommended, which increases processing time by a factor of 5. Therefore, analyzing a large number of plant sensitivities, as required during the techno-economic optimization procedure, the detailed thermodynamic simulation approach becomes impracticable. Suntrace has developed an in-house CSP-Simulation tool (CSPsim), based on EBSILON and applying predictive models, to approximate the CSP plant performance for central receiver and parabolic trough technology. CSPsim significantly increases the speed of energy yield calculations by factor ≥ 35 and has automated the simulation run of all predefined design configurations in sequential order during the optimization procedure. To develop the predictive models, multiple linear regression techniques and Design of Experiment methods are applied. The annual energy yield and derived LCOE calculated by the predictive model deviates less than ±1.5 % from the thermodynamic simulation in EBSILON and effectively identifies the optimal range of main design parameters for further, more specific analysis.

A Multialgorithm Approach to Land Surface Modeling of Suspended Sediment in the Colorado Front Range

PubMed Central

Stewart, J. R.; Kasprzyk, J. R.; Rajagopalan, B.; Minear, J. T.; Raseman, W. J.

2017-01-01

Abstract A new paradigm of simulating suspended sediment load (SSL) with a Land Surface Model (LSM) is presented here. Five erosion and SSL algorithms were applied within a common LSM framework to quantify uncertainties and evaluate predictability in two steep, forested catchments (>1,000 km2). The algorithms were chosen from among widely used sediment models, including empirically based: monovariate rating curve (MRC) and the Modified Universal Soil Loss Equation (MUSLE); stochastically based: the Load Estimator (LOADEST); conceptually based: the Hydrologic Simulation Program—Fortran (HSPF); and physically based: the Distributed Hydrology Soil Vegetation Model (DHSVM). The algorithms were driven by the hydrologic fluxes and meteorological inputs generated from the Variable Infiltration Capacity (VIC) LSM. A multiobjective calibration was applied to each algorithm and optimized parameter sets were validated over an excluded period, as well as in a transfer experiment to a nearby catchment to explore parameter robustness. Algorithm performance showed consistent decreases when parameter sets were applied to periods with greatly differing SSL variability relative to the calibration period. Of interest was a joint calibration of all sediment algorithm and streamflow parameters simultaneously, from which trade‐offs between streamflow performance and partitioning of runoff and base flow to optimize SSL timing were noted, decreasing the flexibility and robustness of the streamflow to adapt to different time periods. Parameter transferability to another catchment was most successful in more process‐oriented algorithms, the HSPF and the DHSVM. This first‐of‐its‐kind multialgorithm sediment scheme offers a unique capability to portray acute episodic loading while quantifying trade‐offs and uncertainties across a range of algorithm structures. PMID:29399268

Mapping Surface Cover Parameters Using Aggregation Rules and Remotely Sensed Cover Classes. Version 1.9

NASA Technical Reports Server (NTRS)

Arain, Altaf M.; Shuttleworth, W. James; Yang, Z-Liang; Michaud, Jene; Dolman, Johannes

1997-01-01

A coupled model, which combines the Biosphere-Atmosphere Transfer Scheme (BATS) with an advanced atmospheric boundary-layer model, was used to validate hypothetical aggregation rules for BATS-specific surface cover parameters. The model was initialized and tested with observations from the Anglo-Brazilian Amazonian Climate Observational Study and used to simulate surface fluxes for rain forest and pasture mixes at a site near Manaus in Brazil. The aggregation rules are shown to estimate parameters which give area-average surface fluxes similar to those calculated with explicit representation of forest and pasture patches for a range of meteorological and surface conditions relevant to this site, but the agreement deteriorates somewhat when there are large patch-to-patch differences in soil moisture. The aggregation rules, validated as above, were then applied to remotely sensed 1 km land cover data set to obtain grid-average values of BATS vegetation parameters for 2.8 deg x 2.8 deg and 1 deg x 1 deg grids within the conterminous United States. There are significant differences in key vegetation parameters (aerodynamic roughness length, albedo, leaf area index, and stomatal resistance) when aggregate parameters are compared to parameters for the single, dominant cover within the grid. However, the surface energy fluxes calculated by stand-alone BATS with the 2-year forcing, data from the International Satellite Land Surface Climatology Project (ISLSCP) CDROM were reasonably similar using aggregate-vegetation parameters and dominant-cover parameters, but there were some significant differences, particularly in the western USA.

Sabkha Trafficability,

DTIC Science & Technology

1981-01-01

Meteorological Parameters at Meteorological Station 1, 31 May 1980 ........................ 68 $24 Relationship of Jubai. Port Datum to Tide Table Datum. .70 25...around which was a circular weight with two handles. Once assembled, the device was nositioned vertically at the point to be sampled and manually...limited use for sampling very fluid or unconsolidated sand or shell. In the former case, the upper few centimeters of cohesive sediment became embedded

Quantifying energy and water fluxes in dry dune ecosystems of the Netherlands

NASA Astrophysics Data System (ADS)

Voortman, B. R.; Bartholomeus, R. P.; van der Zee, S. E. A. T. M.; Bierkens, M. F. P.; Witte, J. P. M.

2015-04-01

Coastal and inland dunes provide various ecosystem services that are related to groundwater, such as drinking water production and biodiversity. To manage groundwater in a sustainable manner, knowledge of actual evapotranspiration (ETa) for the various land covers in dunes is essential. Aiming at improving the parameterization of dune vegetation in hydro-meteorological models, this study explores the magnitude of energy and water fluxes in an inland dune ecosystem in the Netherlands. Hydro-meteorological measurements were used to parameterize the Penman-Monteith evapotranspiration model for four different surfaces: bare sand, moss, grass and heather. We found that the net longwave radiation (Rnl) was the largest energy flux for most surfaces during daytime. However, modelling this flux by a calibrated FAO-56 Rnl model for each surface and for hourly time steps was unsuccessful. Our Rnl model, with a novel sub-model using solar elevation angle and air temperature to describe the diurnal pattern in radiative surface temperature, improved Rnl simulations considerably. Model simulations of evaporation from moss surfaces showed that the modulating effect of mosses on the water balance is species dependent. We demonstrate that dense moss carpets (Campylopus introflexus) evaporate more (5%, +14 mm) than bare sand (total of 258 mm in 2013), while more open structured mosses (Hypnum cupressiforme) evaporate less (-30%, -76 mm) than bare sand. Additionally, we found that a drought event in the summer of 2013 showed a pronounced delayed signal on lysimeter measurements of ETa for the grass and heather surfaces respectively. Due to the desiccation of leaves after the drought event, and their feedback on the parameters of the Penman-Monteith equation, the potential evapotranspiration in the year 2013 dropped with 9% (-37mm) and 10% (-61 mm) for the grass and heather surfaces respectively, which subsequently led to lowered ETa of 8% (-29 mm) and 7% (-29 mm). These feedbacks are of importance to water resources, especially during a changing climate with increasing number of drought days. Therefore, such feedbacks need to be integrated into a coupled plant physiological and hydro-meteorological model to accurately simulate ETa. In addition, our study showed that groundwater recharge in dunes can be increased considerably by promoting moss vegetation, especially of open structured moss species.

Variation in aerosol nucleation and growth in coal-fired power plant plumes due to background aerosol, meteorology and emissions: sensitivity analysis and parameterization.

NASA Astrophysics Data System (ADS)

Stevens, R. G.; Lonsdale, C. L.; Brock, C. A.; Reed, M. K.; Crawford, J. H.; Holloway, J. S.; Ryerson, T. B.; Huey, L. G.; Nowak, J. B.; Pierce, J. R.

2012-04-01

New-particle formation in the plumes of coal-fired power plants and other anthropogenic sulphur sources may be an important source of particles in the atmosphere. It remains unclear, however, how best to reproduce this formation in global and regional aerosol models with grid-box lengths that are 10s of kilometres and larger. The predictive power of these models is thus limited by the resultant uncertainties in aerosol size distributions. In this presentation, we focus on sub-grid sulphate aerosol processes within coal-fired power plant plumes: the sub-grid oxidation of SO2 with condensation of H2SO4 onto newly-formed and pre-existing particles. Based on the results of the System for Atmospheric Modelling (SAM), a Large-Eddy Simulation/Cloud-Resolving Model (LES/CRM) with online TwO Moment Aerosol Sectional (TOMAS) microphysics, we develop a computationally efficient, but physically based, parameterization that predicts the characteristics of aerosol formed within coal-fired power plant plumes based on parameters commonly available in global and regional-scale models. Given large-scale mean meteorological parameters, emissions from the power plant, mean background condensation sink, and the desired distance from the source, the parameterization will predict the fraction of the emitted SO2 that is oxidized to H2SO4, the fraction of that H2SO4 that forms new particles instead of condensing onto preexisting particles, the median diameter of the newly-formed particles, and the number of newly-formed particles per kilogram SO2 emitted. We perform a sensitivity analysis of these characteristics of the aerosol size distribution to the meteorological parameters, the condensation sink, and the emissions. In general, new-particle formation and growth is greatly reduced during polluted conditions due to the large preexisting aerosol surface area for H2SO4 condensation and particle coagulation. The new-particle formation and growth rates are also a strong function of the amount of sunlight and NOx since both control OH concentrations. Decreases in NOx emissions without simultaneous decreases in SO2 emissions increase new-particle formation and growth due to increased oxidation of SO2. The parameterization we describe here should allow for more accurate predictions of aerosol size distributions and a greater confidence in the effects of aerosols in climate and health studies.

Evaluation of GCMs in the context of regional predictive climate impact studies.

NASA Astrophysics Data System (ADS)

Kokorev, Vasily; Anisimov, Oleg

2016-04-01

Significant improvements in the structure, complexity, and general performance of earth system models (ESMs) have been made in the recent decade. Despite these efforts, the range of uncertainty in predicting regional climate impacts remains large. The problem is two-fold. Firstly, there is an intrinsic conflict between the local and regional scales of climate impacts and adaptation strategies, on one hand, and larger scales, at which ESMs demonstrate better performance, on the other. Secondly, there is a growing understanding that majority of the impacts involve thresholds, and are thus driven by extreme climate events, whereas accent in climate projections is conventionally made on gradual changes in means. In this study we assess the uncertainty in projecting extreme climatic events within a region-specific and process-oriented context by examining the skills and ranking of ESMs. We developed a synthetic regionalization of Northern Eurasia that accounts for the spatial features of modern climatic changes and major environmental and socio-economical impacts. Elements of such fragmentation could be considered as natural focus regions that bridge the gap between the spatial scales adopted in climate-impacts studies and patterns of climate change simulated by ESMs. In each focus region we selected several target meteorological variables that govern the key regional impacts, and examined the ability of the models to replicate their seasonal and annual means and trends by testing them against observations. We performed a similar evaluation with regard to extremes and statistics of the target variables. And lastly, we used the results of these analyses to select sets of models that demonstrate the best performance at selected focus regions with regard to selected sets of target meteorological parameters. Ultimately, we ranked the models according to their skills, identified top-end models that "better than average" reproduce the behavior of climatic parameters, and eliminated the outliers. Since the criteria of selecting the "best" models are somewhat loose, we constructed several regional ensembles consisting of different number of high-ranked models and compared results from these optimized ensembles with observations and with the ensemble of all models. We tested our approach in specific regional application of the terrestrial Russian Arctic, considering permafrost and Artic biomes as key regional climate-dependent systems, and temperature and precipitation characteristics governing their state as target meteorological parameters. Results of this case study are deposited on the web portal www.permafrost.su/gcms

Roles of Meteorology in Changes of Air Pollutants Concentrations in China from 2010 to 2015

NASA Astrophysics Data System (ADS)

Wang, P.; Kota, S. H.; Hu, J.; Ying, Q.; Zhang, H.

2017-12-01

Tremendous efforts have been made to control the severe air pollution in China in recent years. However, no significant improvement was observed according to annual fine particulate matter (PM2.5) concentrations and the concentrations in severe air pollution events in winter. This is partially due to the role of meteorology, which affects the emission, transport, transformation, and deposition of air pollutants. In this study, simulation of air pollutants over China was conducted for six years from 2010 to 2015 with constant anthropogenic emissions to verify the changes of air pollutants due to meteorology changes only. Model performance was validated by comparing with meteorological observations and air pollutants measures from various sources. Four different regions/cities were selected to understand the changes in wind, mixing layer height, temperature, and relative humanity at different seasons. The changes in concentrations of pollutants including PM2.5 and its chemical components and ozone were analyzed and associated with meteorological changes. This study would provide information for designing effective control strategies in different areas with the consideration of meteorological and climate changes.

Comparing bias correction methods in downscaling meteorological variables for a hydrologic impact study in an arid area in China

NASA Astrophysics Data System (ADS)

Fang, G. H.; Yang, J.; Chen, Y. N.; Zammit, C.

2015-06-01

Water resources are essential to the ecosystem and social economy in the desert and oasis of the arid Tarim River basin, northwestern China, and expected to be vulnerable to climate change. It has been demonstrated that regional climate models (RCMs) provide more reliable results for a regional impact study of climate change (e.g., on water resources) than general circulation models (GCMs). However, due to their considerable bias it is still necessary to apply bias correction before they are used for water resources research. In this paper, after a sensitivity analysis on input meteorological variables based on the Sobol' method, we compared five precipitation correction methods and three temperature correction methods in downscaling RCM simulations applied over the Kaidu River basin, one of the headwaters of the Tarim River basin. Precipitation correction methods applied include linear scaling (LS), local intensity scaling (LOCI), power transformation (PT), distribution mapping (DM) and quantile mapping (QM), while temperature correction methods are LS, variance scaling (VARI) and DM. The corrected precipitation and temperature were compared to the observed meteorological data, prior to being used as meteorological inputs of a distributed hydrologic model to study their impacts on streamflow. The results show (1) streamflows are sensitive to precipitation, temperature and solar radiation but not to relative humidity and wind speed; (2) raw RCM simulations are heavily biased from observed meteorological data, and its use for streamflow simulations results in large biases from observed streamflow, and all bias correction methods effectively improved these simulations; (3) for precipitation, PT and QM methods performed equally best in correcting the frequency-based indices (e.g., standard deviation, percentile values) while the LOCI method performed best in terms of the time-series-based indices (e.g., Nash-Sutcliffe coefficient, R2); (4) for temperature, all correction methods performed equally well in correcting raw temperature; and (5) for simulated streamflow, precipitation correction methods have more significant influence than temperature correction methods and the performances of streamflow simulations are consistent with those of corrected precipitation; i.e., the PT and QM methods performed equally best in correcting flow duration curve and peak flow while the LOCI method performed best in terms of the time-series-based indices. The case study is for an arid area in China based on a specific RCM and hydrologic model, but the methodology and some results can be applied to other areas and models.

Statistical analysis of aerosol species, trace gasses, and meteorology in Chicago.

PubMed

Binaku, Katrina; O'Brien, Timothy; Schmeling, Martina; Fosco, Tinamarie

2013-09-01

Both canonical correlation analysis (CCA) and principal component analysis (PCA) were applied to atmospheric aerosol and trace gas concentrations and meteorological data collected in Chicago during the summer months of 2002, 2003, and 2004. Concentrations of ammonium, calcium, nitrate, sulfate, and oxalate particulate matter, as well as, meteorological parameters temperature, wind speed, wind direction, and humidity were subjected to CCA and PCA. Ozone and nitrogen oxide mixing ratios were also included in the data set. The purpose of statistical analysis was to determine the extent of existing linear relationship(s), or lack thereof, between meteorological parameters and pollutant concentrations in addition to reducing dimensionality of the original data to determine sources of pollutants. In CCA, the first three canonical variate pairs derived were statistically significant at the 0.05 level. Canonical correlation between the first canonical variate pair was 0.821, while correlations of the second and third canonical variate pairs were 0.562 and 0.461, respectively. The first canonical variate pair indicated that increasing temperatures resulted in high ozone mixing ratios, while the second canonical variate pair showed wind speed and humidity's influence on local ammonium concentrations. No new information was uncovered in the third variate pair. Canonical loadings were also interpreted for information regarding relationships between data sets. Four principal components (PCs), expressing 77.0 % of original data variance, were derived in PCA. Interpretation of PCs suggested significant production and/or transport of secondary aerosols in the region (PC1). Furthermore, photochemical production of ozone and wind speed's influence on pollutants were expressed (PC2) along with overall measure of local meteorology (PC3). In summary, CCA and PCA results combined were successful in uncovering linear relationships between meteorology and air pollutants in Chicago and aided in determining possible pollutant sources.

Assessing the impact of local meteorological variables on surface ozone in Hong Kong during 2000-2015 using quantile and multiple line regression models

NASA Astrophysics Data System (ADS)

Zhao, Wei; Fan, Shaojia; Guo, Hai; Gao, Bo; Sun, Jiaren; Chen, Laiguo

2016-11-01

The quantile regression (QR) method has been increasingly introduced to atmospheric environmental studies to explore the non-linear relationship between local meteorological conditions and ozone mixing ratios. In this study, we applied QR for the first time, together with multiple linear regression (MLR), to analyze the dominant meteorological parameters influencing the mean, 10th percentile, 90th percentile and 99th percentile of maximum daily 8-h average (MDA8) ozone concentrations in 2000-2015 in Hong Kong. The dominance analysis (DA) was used to assess the relative importance of meteorological variables in the regression models. Results showed that the MLR models worked better at suburban and rural sites than at urban sites, and worked better in winter than in summer. QR models performed better in summer for 99th and 90th percentiles and performed better in autumn and winter for 10th percentile. And QR models also performed better in suburban and rural areas for 10th percentile. The top 3 dominant variables associated with MDA8 ozone concentrations, changing with seasons and regions, were frequently associated with the six meteorological parameters: boundary layer height, humidity, wind direction, surface solar radiation, total cloud cover and sea level pressure. Temperature rarely became a significant variable in any season, which could partly explain the peak of monthly average ozone concentrations in October in Hong Kong. And we found the effect of solar radiation would be enhanced during extremely ozone pollution episodes (i.e., the 99th percentile). Finally, meteorological effects on MDA8 ozone had no significant changes before and after the 2010 Asian Games.

Assessment and prediction of short term hospital admissions: the case of Athens, Greece

NASA Astrophysics Data System (ADS)

Kassomenos, P.; Papaloukas, C.; Petrakis, M.; Karakitsios, S.

The contribution of air pollution on hospital admissions due to respiratory and heart diseases is a major issue in the health-environmental perspective. In the present study, an attempt was made to run down the relationships between air pollution levels and meteorological indexes, and corresponding hospital admissions in Athens, Greece. The available data referred to a period of eight years (1992-2000) including the daily number of hospital admissions due to respiratory and heart diseases, hourly mean concentrations of CO, NO 2, SO 2, O 3 and particulates in several monitoring stations, as well as, meteorological data (temperature, relative humidity, wind speed/direction). The relations among the above data were studied through widely used statistical techniques (multivariate stepwise analyses) and Artificial Neural Networks (ANNs). Both techniques revealed that elevated particulate concentrations are the dominant parameter related to hospital admissions (an increase of 10 μg m -3 leads to an increase of 10.2% in the number of admissions), followed by O 3 and the rest of the pollutants (CO, NO 2 and SO 2). Meteorological parameters also play a decisive role in the formation of air pollutant levels affecting public health. Consequently, increased/decreased daily hospital admissions are related to specific types of meteorological conditions that favor/do not favor the accumulation of pollutants in an urban complex. In general, the role of meteorological factors seems to be underestimated by stepwise analyses, while ANNs attribute to them a more important role. Comparison of the two models revealed that ANN adaptation in complicate environmental issues presents improved modeling results compared to a regression technique. Furthermore, the ANN technique provides a reliable model for the prediction of the daily hospital admissions based on air quality data and meteorological indices, undoubtedly useful for regulatory purposes.

Physically Based Mountain Hydrological Modelling using Reanalysis Data in Patagonia

NASA Astrophysics Data System (ADS)

Krogh, S.; Pomeroy, J. W.; McPhee, J. P.

2013-05-01

Remote regions in South America are often characterized by insufficient observations of meteorology for robust hydrological model operation. Yet water resources must be quantified, understood and predicted in order to develop effective water management policies. Here, we developed a physically based hydrological model for a major river in Patagonia using the modular Cold Regions Hydrological Modelling Platform (CRHM) in order to better understand hydrological processes leading to streamflow generation in this remote region. The Baker River -with the largest mean annual streamflow in Chile-, drains snowy mountains, glaciers, wet forests, peat and semi-arid pampas into a large lake. Meteorology over the basin is poorly monitored in that there are no high elevation weather stations and stations at low elevations are sparsely distributed, only measure temperature and rainfall and are poorly maintained. Streamflow in the basin is gauged at several points where there are high quality hydrometric stations. In order to quantify the impact of meteorological data scarcity on prediction, two additional data sources were used: the ERA-Interim (ECMWF Re-analyses) and CFSR (Climate Forecast System Reanalysis) atmospheric reanalyses. Precipitation temporal distribution and magnitude from the models and observations were compared and the reanalysis data was found to have about three times the number of days with precipitation than the observations did. Better synchronization between measured peak streamflows and modeled precipitation was found compared to observed precipitation. These differences are attributed to: (i) lack of any snowfall observations (so precipitation records does not consider snowfall events) and (ii) available rainfall observations are all located at low altitude (<500 m a.s.l), and miss the occurrence of high altitude precipitation events. CRHM parameterization was undertaken by using local physiographic and vegetation characteristics where available and transferring locally unknown hydrological process parameters from cold regions mountain environments in Canada. Some soil moisture parameters were calibrated from streamflow observations. Model performance was estimated through comparison with observed streamflow records. Simulations using observed precipitation had negligible representativeness of streamflow (Nash-Sutcliffe coefficient, NS ≈ 0.2), while those using any of the two reanalyses as forcing data had reasonable model performance (NS ≈ 0.7). In spite of the better spatial resolution of the CFSR, the ability to simulate streamflow were not significantly different using either CFSR or ERA-Interim. The modeled water balance shows that snowfall is about 30% of the total precipitation input, but snowmelt superficial runoff comprises about 10% of total runoff. About 75% of all precipitation is infiltrated, and approximately 15% of the losses are attributed to evapotranspiration from soil and lake evaporation.

A Flexible Approach for the Statistical Visualization of Ensemble Data

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

Potter, K.; Wilson, A.; Bremer, P.

2009-09-29

Scientists are increasingly moving towards ensemble data sets to explore relationships present in dynamic systems. Ensemble data sets combine spatio-temporal simulation results generated using multiple numerical models, sampled input conditions and perturbed parameters. While ensemble data sets are a powerful tool for mitigating uncertainty, they pose significant visualization and analysis challenges due to their complexity. We present a collection of overview and statistical displays linked through a high level of interactivity to provide a framework for gaining key scientific insight into the distribution of the simulation results as well as the uncertainty associated with the data. In contrast to methodsmore » that present large amounts of diverse information in a single display, we argue that combining multiple linked statistical displays yields a clearer presentation of the data and facilitates a greater level of visual data analysis. We demonstrate this approach using driving problems from climate modeling and meteorology and discuss generalizations to other fields.« less

Modelling the dispersion and transport of reactive pollutants in a deep urban street canyon: using large-eddy simulation.

PubMed

Zhong, Jian; Cai, Xiao-Ming; Bloss, William James

2015-05-01

This study investigates the dispersion and transport of reactive pollutants in a deep urban street canyon with an aspect ratio of 2 under neutral meteorological conditions using large-eddy simulation. The spatial variation of pollutants is significant due to the existence of two unsteady vortices. The deviation of species abundance from chemical equilibrium for the upper vortex is greater than that for the lower vortex. The interplay of dynamics and chemistry is investigated using two metrics: the photostationary state defect, and the inferred ozone production rate. The latter is found to be negative at all locations within the canyon, pointing to a systematic negative offset to ozone production rates inferred by analogous approaches in environments with incomplete mixing of emissions. This study demonstrates an approach to quantify parameters for a simplified two-box model, which could support traffic management and urban planning strategies and personal exposure assessment. Copyright © 2015 Elsevier Ltd. All rights reserved.

Effect of Downscaled Forcings and Soil Texture Properties on Hyperresolution Hydrologic Simulations in a Regional Basin in Northwest Mexico

NASA Astrophysics Data System (ADS)

Ko, A.; Mascaro, G.; Vivoni, E. R.

2017-12-01

Hyper-resolution (< 1 km) hydrological modeling is expected to support a range of studies related to the terrestrial water cycle. A critical need for increasing the utility of hyper-resolution modeling is the availability of meteorological forcings and land surface characteristics at high spatial resolution. Unfortunately, in many areas these datasets are only available at coarse (> 10 km) scales. In this study, we address some of the challenges by applying a parallel version of the Triangulated Irregular Network (TIN)-based Real Time Integrated Basin Simulator (tRIBS) to the Rio Sonora Basin (RSB) in northwest Mexico. The RSB is a large, semiarid watershed ( 21,000 km2) characterized by complex topography and a strong seasonality in vegetation conditions, due to the North American monsoon. We conducted simulations at an average spatial resolution of 88 m over a decadal (2004-2013) period using spatially-distributed forcings from remotely-sensed and reanalysis products. Meteorological forcings were derived from the North American Land Data Assimilation System (NLDAS) at the original resolution of 12 km and were downscaled at 1 km with techniques accounting for terrain effects. Two grids of soil properties were created from different sources, including: (i) CONABIO (Comisión Nacional para el Conocimiento y Uso de la Biodiversidad) at 6 km resolution; and (ii) ISRIC (International Soil Reference Information Centre) at 250 m. Time-varying vegetation parameters were derived from the Moderate Resolution Imaging Spectroradiometer (MODIS) composite products. The model was first calibrated and validated through distributed soil moisture data from a network of 20 soil moisture stations during the monsoon season. Next, hydrologic simulations were conducted with five different combinations of coarse and downscaled forcings and soil properties. Outputs in the different configurations were then compared with independent observations of soil moisture, and with estimates of land surface temperature (1 km, daily) and evapotranspiration (1 km, monthly) from MODIS. This study is expected to support the community involved in hyper-resolution hydrologic modeling by identifying the crucial factors that, if available at higher resolution, lead to the largest improvement of the simulation prognostic capability.

Modeling actual evapotranspiration with routine meteorological variables in the data-scarce region of the Tibetan Plateau: Comparisons and implications

NASA Astrophysics Data System (ADS)

Ma, Ning; Zhang, Yinsheng; Xu, Chong-Yu; Szilagyi, Jozsef

2015-08-01

Quantitative estimation of actual evapotranspiration (ETa) by in situ measurements and mathematical modeling is a fundamental task for physical understanding of ETa as well as the feedback mechanisms between land and the ambient atmosphere. However, the ETa information in the Tibetan Plateau (TP) has been greatly impeded by the extremely sparse ground observation network in the region. Approaches for estimating ETa solely from routine meteorological variables are therefore important for investigating spatiotemporal variations of ETa in the data-scarce region of the TP. Motivated by this need, the complementary relationship (CR) and Penman-Monteith approaches were evaluated against in situ measurements of ETa on a daily basis in an alpine steppe region of the TP. The former includes the Nonlinear Complementary Relationship (Nonlinear-CR) as well as the Complementary Relationship Areal Evapotranspiration (CRAE) models, while the latter involves the Katerji-Perrier and the Todorovic models. Results indicate that the Nonlinear-CR, CRAE, and Katerji-Perrier models are all capable of efficiently simulating daily ETa, provided their parameter values were appropriately calibrated. The Katerji-Perrier model performed best since its site-specific parameters take the soil water status into account. The Nonlinear-CR model also performed well with the advantage of not requiring the user to choose between a symmetric and asymmetric CR. The CRAE model, even with a relatively low Nash-Sutcliffe efficiency (NSE) value, is also an acceptable approach in this data-scarce region as it does not need information of wind speed and ground surface conditions. In contrast, application of the Todorovic model was found to be inappropriate in the dry regions of the TP due to its significant overestimation of ETa as it neglects the effect of water stress on the bulk surface resistance. Sensitivity analysis of the parameter values demonstrated the relative importance of each parameter in the corresponding model. Overall, the Nonlinear-CR model is recommended in the absence of measured ETa for local calibration of the model parameter values.

Simulation of the Transport and Dispersion of Perfluorocarbon Tracers Released in Texas Using multiple Assimilated Meteorological Wind Fields

NASA Astrophysics Data System (ADS)

Schichtel, B.; Barna, M.; Gebhart, K.; Green, M.

2002-12-01

The Big Bend Regional Aerosol and Visibility Observational Study (BRAVO) was designed to determine the causes of visibility impairment at Big Bend National Park, located in southwestern Texas. As part of BRAVO, an intensive field study was conducted during July-October 1999. Among the features of this study was the release of unique perfluorocarbon tracers from four sites within Texas, representative of industrial/urban locations. These tracers were monitored at 21 sites, throughout Texas. Other measurements collected during the field study included upper-level winds using radar profilers, and speciated fine-particulate mass concentrations. MM5 was used to simulate the regional meteorology during BRAVO, and was run in non-hydrostatic mode using a continental-scale 36km domain with nested 12km and 4km domains. MM5 employed observational nudging by incorporating the available measured wind data from the National Weather Service and data from the radar wind profilers. Meteorological data from the National Weather Service's Eta Data Assimilation System (EDAS), archived at 80km grid spacing, were also available. Several models are being used to evaluate airmass transport to Big Bend, including CMAQ, REMSAD, HYSPLIT and the CAPITA Monte Carlo Model. This combination of tracer data, meteorological data and deployment of four models provides a unique opportunity to assess the ability of the model/wind field combinations to properly simulate the regional scale atmospheric transport and dispersion of trace gases over distances of 100 to 800km. This paper will present the tracer simulations from REMSAD using the 36 and 12 km MM5 wind fields, and results from HYSPLIT and the Monte Carlo model driven by the 36km MM5 and 80km EDAS wind fields. Preliminary results from HYSPLIT and the Monte Carlo model driven by the EDAS wind fields shows that these models are able to account for the primary features of tracer concentrations patterns in the Big Bend area. However, at times the simulated concentration peaks proceeded or followed the actual measured concentrations by about at day and the duration of the simulated tracer impacts were shorter than those measured in the Big Bend area.

Atmospheric aerosols parameters behavior and its association with meteorological activities variables over western Indian tropical semi-urban site i.e., Udaipur

NASA Astrophysics Data System (ADS)

Vyas, B. M.; Saxenna, Abhishek; Panwar, Chhagan

2016-05-01

The present study has been focused to the identify the role of meteorological processes on changing the monthly variation of AOD at 550nm, Angstrom Exponent Coefficient (AEC, 440/670nm) and Cloud Effective Radius (CER, μm) measured during January, 2005 to December 2013 over western Indian location i.e., Udaipur (24.6° N, 73.7° E, 560 m amsl). The monthly variation of AOD 550nm, AEC and during entire study period have shown the strong combined influence of different local surface meteorological parameters in varying amplitude with different nature. The higher values of wind speed, ambient surface temperature, planetary boundary layer, and favorable wind direction coming from desert and oceanic region (W and SW) may be recognize as some of possible factor to exhibit the higher aerosols loading of bigger aerosol size particles in pre-monsoon. These meteorological factors seem also to be plausible responsible factors for drastically reducing the cloud effective radius in pre-monsoon season. In contrary to this, in winter, lower atmospheric aerosols burden and more abundance of fine size particles along with increasing the CER sizes also seem to be influenced and governed by the adverse nature of meteorological conditions such lowering the PBL, T, WS as well as with air pollutants transportation by wind from the N and NE region, of high aerosols loading of fine size particles as anthropogenic aerosols located far away to the observing site.

Estimation of open water evaporation using land-based meteorological data

NASA Astrophysics Data System (ADS)

Li, Fawen; Zhao, Yong

2017-10-01

Water surface evaporation is an important process in the hydrologic and energy cycles. Accurate simulation of water evaporation is important for the evaluation of water resources. In this paper, using meteorological data from the Aixinzhuang reservoir, the main factors affecting water surface evaporation were determined by the principal component analysis method. To illustrate the influence of these factors on water surface evaporation, the paper first adopted the Dalton model to simulate water surface evaporation. The results showed that the simulation precision was poor for the peak value zone. To improve the model simulation's precision, a modified Dalton model considering relative humidity was proposed. The results show that the 10-day average relative error is 17.2%, assessed as qualified; the monthly average relative error is 12.5%, assessed as qualified; and the yearly average relative error is 3.4%, assessed as excellent. To validate its applicability, the meteorological data of Kuancheng station in the Luan River basin were selected to test the modified model. The results show that the 10-day average relative error is 15.4%, assessed as qualified; the monthly average relative error is 13.3%, assessed as qualified; and the yearly average relative error is 6.0%, assessed as good. These results showed that the modified model had good applicability and versatility. The research results can provide technical support for the calculation of water surface evaporation in northern China or similar regions.

Assessment of a surface-layer parameterization scheme in an atmospheric model for varying meteorological conditions

NASA Astrophysics Data System (ADS)

Anurose, T. J.; Bala Subrahamanyam, D.

2014-06-01

The performance of a surface-layer parameterization scheme in a high-resolution regional model (HRM) is carried out by comparing the model-simulated sensible heat flux (H) with the concurrent in situ measurements recorded at Thiruvananthapuram (8.5° N, 76.9° E), a coastal station in India. With a view to examining the role of atmospheric stability in conjunction with the roughness lengths in the determination of heat exchange coefficient (CH) and H for varying meteorological conditions, the model simulations are repeated by assigning different values to the ratio of momentum and thermal roughness lengths (i.e. z0m/z0h) in three distinct configurations of the surface-layer scheme designed for the present study. These three configurations resulted in differential behaviour for the varying meteorological conditions, which is attributed to the sensitivity of CH to the bulk Richardson number (RiB) under extremely unstable, near-neutral and stable stratification of the atmosphere.

Contribution of ambient ozone to Scots pine defoliation and reduced growth in the Central European forests: a Lithuanian case study.

PubMed

Augustaitis, Algirdas; Bytnerowicz, Andrzej

2008-10-01

The study aimed to explore if changes in crown defoliation and stem growth of Scots pines (Pinus sylvestris L.) could be related to changes in ambient ozone (O(3)) concentration in central Europe. To meet this objective the study was performed in 3 Lithuanian national parks, close to the ICP integrated monitoring stations from which data on meteorology and pollution were provided. Contribution of peak O(3) concentrations to the integrated impact of acidifying compounds and meteorological parameters on pine stem growth was found to be more significant than its contribution to the integrated impact of acidifying compounds and meteorological parameters on pine defoliation. Findings of the study provide statistical evidence that peak concentrations of ambient O(3) can have a negative impact on pine tree crown defoliation and stem growth reduction under field conditions in central and northeastern Europe where the AOT40 values for forests are commonly below their phytotoxic levels.

Thirty-year survey on airborne pollen concentrations in Genoa, Italy: relationship with sensitizations, meteorological data, and air pollution.

PubMed

Negrini, Arsenio Corrado; Negrini, Simone; Giunta, Vania; Quaglini, Silvana; Ciprandi, Giorgio

2011-01-01

Pollen allergy represents a relevant health issue. Betulaceae sensitization significantly increased in Genoa, Italy, in the last decades. This study investigated possible relationships among pollen count, meteorological changes, air pollution, and sensitizations in this city during a 30-year period. Betulaceae, Urticaceae, Gramineae, and Oleaceae pollen counts were measured from 1981 to 2010 in Genoa. Sensitization to these pollens was also considered in large populations of allergic patients. Meteorological parameters and pollutants were also measured in the same area. Betulaceae sensitization increased over time. All pollen species significantly increased over this time. Pollen season advanced for Betulaceae and Urticaceae. Only Urticaceae season significantly increased. Temperature increased while rainfall decreased over the time. Pollutants significantly decreased. There were some relationships between pollen changes and climatic and air pollution parameters. This 30-year study conducted in an urbanized area provided evidence that Betulaceae sensitization significantly increased, pollen load significantly augmented, and climate and air pollution changed with a possible influence on pollen release.

Impacts of WRF lightning assimilation on offline CMAQ simulations

EPA Science Inventory

Deep convective clouds vertically redistribute trace gases and aerosols and also provide a source for scavenging, aqueous phase chemistry, and wet deposition, making them important to air quality.? Regional air quality simulations are typically driven by meteorological models tha...

The optical depth sensor (ODS) for column dust opacity measurements and cloud detection on martian atmosphere

NASA Astrophysics Data System (ADS)

Toledo, D.; Rannou, P.; Pommereau, J.-P.; Foujols, T.

2016-08-01

A lightweight and sophisticated optical depth sensor (ODS) able to measure alternatively scattered flux at zenith and the sum of the direct flux and the scattered flux in blue and red has been developed to work in martian environment. The principal goals of ODS are to perform measurements of the daily mean dust opacity and to retrieve the altitude and optical depth of high altitude clouds at twilight, crucial parameters in the understanding of martian meteorology. The retrieval procedure of dust opacity is based on the use of radiative transfer simulations reproducing observed changes in the solar flux during the day as a function of 4 free parameters: dust opacity in blue and red, and effective radius and effective width of dust size distribution. The detection of clouds is undertaken by looking at the time variation of the color index (CI), defined as the ratio between red and blue ODS channels, at twilight. The retrieval of altitude and optical depth of clouds is carried out using a radiative transfer model in spherical geometry to simulate the CI time variation at twilight. Here the different retrieval procedures to analyze ODS signals, as well as the results obtained in different sensitivity analysis are presented and discussed.

[Estimation of average traffic emission factor based on synchronized incremental traffic flow and air pollutant concentration].

PubMed

Li, Run-Kui; Zhao, Tong; Li, Zhi-Peng; Ding, Wen-Jun; Cui, Xiao-Yong; Xu, Qun; Song, Xian-Feng

2014-04-01

On-road vehicle emissions have become the main source of urban air pollution and attracted broad attentions. Vehicle emission factor is a basic parameter to reflect the status of vehicle emissions, but the measured emission factor is difficult to obtain, and the simulated emission factor is not localized in China. Based on the synchronized increments of traffic flow and concentration of air pollutants in the morning rush hour period, while meteorological condition and background air pollution concentration retain relatively stable, the relationship between the increase of traffic and the increase of air pollution concentration close to a road is established. Infinite line source Gaussian dispersion model was transformed for the inversion of average vehicle emission factors. A case study was conducted on a main road in Beijing. Traffic flow, meteorological data and carbon monoxide (CO) concentration were collected to estimate average vehicle emission factors of CO. The results were compared with simulated emission factors of COPERT4 model. Results showed that the average emission factors estimated by the proposed approach and COPERT4 in August were 2.0 g x km(-1) and 1.2 g x km(-1), respectively, and in December were 5.5 g x km(-1) and 5.2 g x km(-1), respectively. The emission factors from the proposed approach and COPERT4 showed close values and similar seasonal trends. The proposed method for average emission factor estimation eliminates the disturbance of background concentrations and potentially provides real-time access to vehicle fleet emission factors.

Model analysis of urbanization impacts on boundary layer meteorology under hot weather conditions: a case study of Nanjing, China

NASA Astrophysics Data System (ADS)

Chen, Lei; Zhang, Meigen; Wang, Yongwei

2016-08-01

The Weather Research and Forecasting (WRF) model, configured with a single-layer urban canopy model, was employed to investigate the influence of urbanization on boundary layer meteorological parameters during a long-lasting heat wave. This study was conducted over Nanjing city, East China, from 26 July to 4 August 2010. The impacts of urban expansion and anthropogenic heat (AH) release were simulated to quantify their effects on 2-m temperature, 2-m water vapor mixing ratio, and 10-m wind speed and heat stress index. Urban sprawl increased the daily 2-m temperature in urbanized areas by around 1.6 °C and decreased the urban diurnal temperature range (DTR) by 1.24 °C. The contribution of AH release to the atmospheric warming was nearly 22 %, but AH had little influence on the DTR. The urban regional mean surface wind speed decreased by about 0.4 m s-1, and this decrease was successfully simulated from the surface to 300 m. The influence of urbanization on 2-m water vapor mixing ratio was significant over highly urbanized areas with a decrease of 1.1-1.8 g kg-1. With increased urbanization ratio, the duration of the inversion layer was about 4 h shorter, and the lower atmospheric layer was less stable. Urban heat island (UHI) intensity was significantly enhanced when synthesizing both urban sprawl and AH release and the daily mean UHI intensity increased by 0.74 °C. Urbanization increased the time under extreme heat stress (about 40 %) and worsened the living environment in urban areas.

Effects of oligotrophication on primary production in peri-alpine lakes

NASA Astrophysics Data System (ADS)

Finger, David; Wüest, Alfred; Bossard, Peter

2013-08-01

During the second half of the 20th century untreated sewage released from housing and industry into natural waters led to a degradation of many freshwater lakes and reservoirs worldwide. In order to mitigate eutrophication, wastewater treatment plants, including Fe-induced phosphorus precipitation, were implemented throughout the industrialized world, leading to reoligotrophication in many freshwater lakes. To understand and assess the effects of reoligotrophication on primary productivity, we analyzed 28 years of 14C assimilation rates, as well as other biotic and abiotic parameters, such as global radiation, nutrient concentrations and plankton densities in peri-alpine Lake Lucerne, Switzerland. Using a simple productivity-light relationship, we estimated continuous primary production and discussed the relation between productivity and observed limnological parameters. Furthermore, we assessed the uncertainty of our modeling approach based on monthly 14C assimilation measurements using Monte Carlo simulations. Results confirm that monthly sampling of productivity is sufficient for identifying long-term trends in productivity and that conservation management has successfully improved water quality during the past three decades via reducing nutrients and primary production in the lake. However, even though nutrient concentrations have remained constant in recent years, annual primary production varies significantly from year to year. Despite the fact that nutrient concentrations have decreased by more than an order of magnitude, primary production has decreased only slightly. These results suggest that primary production correlates well to nutrients availability but meteorological conditions lead to interannual variability regardless of the trophic status of the lake. Accordingly, in oligotrophic freshwaters meteorological forcing may reduce productivity impacting on the entire food chain of the ecosystem.

Post Fukushima tsunami simulations for Malaysian coasts

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

Koh, Hock Lye, E-mail: kohhl@ucsiuniversity.edu.my; Teh, Su Yean, E-mail: syteh@usm.my; Abas, Mohd Rosaidi Che

The recent recurrences of mega tsunamis in the Asian region have rekindled concern regarding potential tsunamis that could inflict severe damage to affected coastal facilities and communities. The 11 March 2011 Fukushima tsunami that crippled nuclear power plants in Northern Japan has further raised the level of caution. The recent discovery of petroleum reserves in the coastal water surrounding Malaysia further ignites the concern regarding tsunami hazards to petroleum facilities located along affected coasts. Working in a group, federal government agencies seek to understand the dynamics of tsunami and their impacts under the coordination of the Malaysian National Centre formore » Tsunami Research, Malaysian Meteorological Department. Knowledge regarding the generation, propagation and runup of tsunami would provide the scientific basis to address safety issues. An in-house tsunami simulation models known as TUNA has been developed by the authors to assess tsunami hazards along affected beaches so that mitigation measures could be put in place. Capacity building on tsunami simulation plays a critical role in the development of tsunami resilience. This paper aims to first provide a simple introduction to tsunami simulation towards the achievement of tsunami simulation capacity building. The paper will also present several scenarios of tsunami dangers along affected Malaysia coastal regions via TUNA simulations to highlight tsunami threats. The choice of tsunami generation parameters reflects the concern following the Fukushima tsunami.« less

Sixth Annual Workshop on Meteorological and Environmental Inputs to Aviation Systems, 26-28 October 1982, Tullahoma, Tenn

NASA Technical Reports Server (NTRS)

Camp, D. W.; Frost, W.; Coons, F.; Evanich, P.; Sprinkle, C. H.

1984-01-01

The six workshops whose proceedings are presently reported considered the subject of meteorological and environmental information inputs to aviation, in order to satisfy workshop-sponsoring agencies' requirements for (1) greater knowledge of the interaction of the atmosphere with aircraft and airport operators, (2) a better definition and implementation of meteorological services to operators, and (3) the collection and interpretation of data useful in establishing operational criteria that relate the atmospheric science input to aviation community operations. Workshop topics included equipment and instrumentation, forecasts and information updates, training and simulation facilities, and severe weather, icing and wind shear.

Inherent uncertainties in meteorological parameters for wind turbine design

NASA Technical Reports Server (NTRS)

Doran, J. C.

1982-01-01

Major difficulties associated with meteorological measurments such as the inability to duplicate the experimental conditions from one day to the next are discussed. This lack of consistency is compounded by the stochastic nature of many of the meteorological variables of interest. Moreover, simple relationships derived in one location may be significantly altered by topographical or synoptic differences encountered at another. The effect of such factors is a degree of inherent uncertainty if an attempt is made to describe the atmosphere in terms of universal laws. Some of these uncertainties and their causes are examined, examples are presented and some implications for wind turbine design are suggested.

BOREAS AES Five-Day Averaged Surface Meteorological and Upper Air Data

NASA Technical Reports Server (NTRS)

Hall, Forrest G. (Editor); Strub, Richard; Newcomer, Jeffrey A.

2000-01-01

The Canadian Atmospheric Environment Service (AES) provided BOREAS with hourly and daily surface meteorological data from 23 of the AES meteorological stations located across Canada and upper air data from 1 station at The Pas, Manitoba. Due to copyright restrictions on the full resolution surface meteorological data, this data set contains 5-day average values for the surface parameters. The upper air data are provided in their full resolution form. The 5-day averaging was performed in order to create a data set that could be publicly distributed at no cost. Temporally, the surface meteorological data cover the period of January 1975 to December 1996 and the upper air data cover the period of January 1961 to November 1996. The data are provided in tabular ASCII files, and are classified as AFM-staff data. The data files are available on a CD-ROM (see document number 20010000884), or from the Oak Ridge National Laboratory (ORNL) Distributed Active Archive Center (DAAC).

Meteorological aspects associated with dust storms in the Sistan region, southeastern Iran

NASA Astrophysics Data System (ADS)

Kaskaoutis, D. G.; Rashki, A.; Houssos, E. E.; Mofidi, A.; Goto, D.; Bartzokas, A.; Francois, P.; Legrand, M.

2015-07-01

Dust storms are considered natural hazards that seriously affect atmospheric conditions, ecosystems and human health. A key requirement for investigating the dust life cycle is the analysis of the meteorological (synoptic and dynamic) processes that control dust emission, uplift and transport. The present work focuses on examining the synoptic and dynamic meteorological conditions associated with dust-storms in the Sistan region, southeastern Iran during the summer season (June-September) of the years 2001-2012. The dust-storm days (total number of 356) are related to visibility records below 1 km at Zabol meteorological station, located near to the dust source. RegCM4 model simulations indicate that the intense northern Levar wind, the high surface heating and the valley-like characteristics of the region strongly affect the meteorological dynamics and the formation of a low-level jet that are strongly linked with dust exposures. The intra-annual evolution of the dust storms does not seem to be significantly associated with El-Nino Southern Oscillation, despite the fact that most of the dust-storms are related to positive values of Oceanic Nino Index. National Center for Environmental Prediction/National Center for Atmospheric Research reanalysis suggests that the dust storms are associated with low sea-level pressure conditions over the whole south Asia, while at 700 hPa level a trough of low geopotential heights over India along with a ridge over Arabia and central Iran is the common scenario. A significant finding is that the dust storms over Sistan are found to be associated with a pronounced increase of the anticyclone over the Caspian Sea, enhancing the west-to-east pressure gradient and, therefore, the blowing of Levar. Infrared Difference Dust Index values highlight the intensity of the Sistan dust storms, while the SPRINTARS model simulates the dust loading and concentration reasonably well, since the dust storms are usually associated with peaks in model simulations.

Long-term visibility data in the UK - how does visibility vary with meteorological and pollutant parameters?

NASA Astrophysics Data System (ADS)

Singh, Ajit; Bloss, William J.; Pope, Francis D.

2016-04-01

Poor visibility can be an indicator of poor air quality. Moreover, degradation in visibility can be hazardous to human safety; for example, low visibility can lead to accidents particularly during winter when fogs are prevalent. The present quantitative analysis attempts to explain the influence of aerosol concentration and composition, and meteorology on long-term UK visibility. We use visibility data from eight UK meteorological stations which have been running since the 1950s. The site locations include urban, rural and marine environments. Overall, most stations show a long term trend of visibility increase, which is indicative of reductions in aerosol pollution, especially in urban areas. Additionally, results at all sites show a very clear dependence on relative humidity, indicating the importance of aerosol hygroscopicity on the ability of aerosols to scatter radiation and hence impact upon visibility. The dependence of visibility on other meteorological parameters (e.g. relative humidity, air temperature, wind speed & direction) is also investigated. To explain the long term visibility trends and their dependence on meteorological conditions, a light extinction model was constructed incorporating the concentrations and composition of historic aerosol. The lack of historic aerosol size distributions and aerosol composition data, which determine hygroscopicity and refractive index, leads to an under-constrained model. Aerosol measurements from the last 10 years are used to constrain these model parameters, and hence their historical variation can be estimated; sensitivity analyses are used to estimate errors for the time period before regular aerosol measurements are available. A good agreement is observed between modelled and measured visibility. This work has generated a unique 60 year data set with which to understand how aerosol concentration and composition has varied over the UK. The model is applicable and easily transferrable to other data sets worldwide. Hence, different clean air legislation can be assessed for its effectiveness in reducing aerosol pollution. The implications for the UK will be discussed.

60 years of visibility data in the UK - how does visibility vary with meteorological and pollutant parameters?

NASA Astrophysics Data System (ADS)

Singh, A.; Bloss, W.; Pope, F.

2015-12-01

Reduced visibility can be an indicator of poor air quality. Moreover, degradation in visibility can be hazardous to human safety; for example, low visibility can lead to accidents particularly during the winter season when fogs are prevalent. Here, we explore the combined influence of aerosol characteristics and meteorology on long-term visibility. We use visibility data from eight meteorological stations, situated in the UK, which have been running since the 1950s. The site locations include urban, rural and marine environments. Most stations show a long term trend of visibility increase, which is indicative of reductions in aerosol pollution, especially in urban areas. Additionally, results at all sites show a very clear dependence on relative humidity, indicating the importance of aerosol hygroscopicity on the ability of aerosols to scatter radiation and hence impact upon visibility. The dependence of visibility on other meteorological parameters (e.g. wind speed, wind direction) is also investigated. To explain the long term visibility trends and their dependence on meteorological conditions, a light extinction model was constructed incorporating the concentrations and composition of historic aerosol. The lack of historic aerosol size distributions and aerosol composition data, which determine hygroscopicity and refractive index, leads to an under-constrained model. Aerosol measurements from the last 10 years are used to constrain these model parameters, and hence their historical variation can be estimated; sensitivity analyses are used to estimate errors for the time period before regular aerosol measurements are available. This work has generated a unique 60 year data set with which to understand how aerosol concentration and composition has varied over the UK. The model is applicable and easily transferrable to other data sets worldwide. Hence, different clean air legislation can be assessed for its effectiveness in reducing aerosol pollution. The implications for the UK will be discussed.

Monitoring Building Energy Systems at NASA Centers Using NASA Earth Science data, CMIP5 climate data products and RETScreen Expert Clean Energy Tool

NASA Astrophysics Data System (ADS)

Stackhouse, P. W., Jr.; Ganoe, R. E.; Westberg, D. J.; Leng, G. J.; Teets, E.; Hughes, J. M.; De Young, R.; Carroll, M.; Liou, L. C.; Iraci, L. T.; Podolske, J. R.; Stefanov, W. L.; Chandler, W.

2016-12-01

The NASA Climate Adaptation Science Investigator team is devoted to building linkages between NASA Earth Science and those within NASA responsible for infrastructure assessment, upgrades and planning. One of the focus areas is assessing NASA center infrastructure for energy efficiency, planning to meet new energy portfolio standards, and assessing future energy needs. These topics intersect at the provision of current and predicted future weather and climate data. This presentation provides an overview of the multi-center effort to access current building energy usage using Earth science observations, including those from in situ measurements, satellite measurement analysis, and global model data products as inputs to the RETScreen Expert, a clean energy decision support tool. RETScreen® Expert, sponsored by Natural Resources Canada (NRCan), is a tool dedicated to developing and providing clean energy project analysis software for the feasibility design and assessment of a wide range of building projects that incorporate renewable energy technologies. RETScreen Expert requires daily average meteorological and solar parameters that are available within less than a month of real-time. A special temporal collection of meteorological parameters was compiled from near-by surface in situ measurements. These together with NASA data from the NASA CERES (Clouds and Earth's Radiance Energy System)/FLASHFlux (Fast Longwave and SHortwave radiative Fluxes) provides solar fluxes and the NASA GMAO (Global Modeling and Assimilation Office) GEOS (Goddard Earth Observing System) operational meteorological analysis are directly used for meteorological input parameters. Examples of energy analysis for a few select buildings at various NASA centers are presented in terms of the energy usage relationship that these buildings have with changes in their meteorological environment. The energy requirements of potential future climates are then surveyed for a range of changes using the most recent CMIP5 global climate model data output.

Predictability Analysis of PM10 Concentrations in Budapest

NASA Astrophysics Data System (ADS)

Ferenczi, Zita

2013-04-01

Climate, weather and air quality may have harmful effects on human health and environment. Over the past few hundred years we had to face the changes in climate in parallel with the changes in air quality. These observed changes in climate, weather and air quality continuously interact with each other: pollutants are changing the climate, thus changing the weather, but climate also has impacts on air quality. The increasing number of extreme weather situations may be a result of climate change, which could create favourable conditions for rising of pollutant concentrations. Air quality in Budapest is determined by domestic and traffic emissions combined with the meteorological conditions. In some cases, the effect of long-range transport could also be essential. While the time variability of the industrial and traffic emissions is not significant, the domestic emissions increase in winter season. In recent years, PM10 episodes have caused the most critical air quality problems in Budapest, especially in winter. In Budapest, an air quality network of 11 stations detects the concentration values of different pollutants hourly. The Hungarian Meteorological Service has developed an air quality prediction model system for the area of Budapest. The system forecasts the concentration of air pollutants (PM10, NO2, SO2 and O3) for two days in advance. In this work we used meteorological parameters and PM10 data detected by the stations of the air quality network, as well as the forecasted PM10 values of the air quality prediction model system. In this work we present the evaluation of PM10 predictions in the last two years and the most important meteorological parameters affecting PM10 concentration. The results of this analysis determine the effect of the meteorological parameters and the emission of aerosol particles on the PM10 concentration values as well as the limits of this prediction system.

Crop evapotranspiration estimation using remote sensing and the existing network of meteorological stations in Cyprus

NASA Astrophysics Data System (ADS)

Papadavid, G.; Hadjimitsis, D.; Michaelides, S.; Nisantzi, A.

2011-05-01

Cyprus is frequently confronted with severe droughts and the need for accurate and systematic data on crop evapotranspiration (ETc) is essential for decision making, regarding water irrigation management and scheduling. The aim of this paper is to highlight how data from meteorological stations in Cyprus can be used for monitoring and determining the country's irrigation demands. This paper shows how daily ETc can be estimated using FAO Penman-Monteith method adapted to satellite data and auxiliary meteorological parameters. This method is widely used in many countries for estimating crop evapotranspiration using auxiliary meteorological data (maximum and minimum temperatures, relative humidity, wind speed) as inputs. Two case studies were selected in order to determine evapotranspiration using meteorological and low resolution satellite data (MODIS - TERRA) and to compare it with the results of the reference method (FAO-56) which estimates the reference evapotranspiration (ETo) by using only meteorological data. The first approach corresponds to the FAO Penman-Monteith method adapted for using both meteorological and remotely sensed data. Furthermore, main automatic meteorological stations in Cyprus were mapped using Geographical Information System (GIS). All the agricultural areas of the island were categorized according to the nearest meteorological station which is considered as "representative" of the area. Thiessen polygons methodology was used for this purpose. The intended goal was to illustrate what can happen to a crop, in terms of water requirements, if meteorological data are retrieved from other than the representative stations. The use of inaccurate data can result in low yields or excessive irrigation which both lead to profit reduction. The results have shown that if inappropriate meteorological data are utilized, then deviations from correct ETc might be obtained, leading to water losses or crop water stress.

Diffusion from a line source

NASA Technical Reports Server (NTRS)

Burns, R. E.

1973-01-01

The problem with predicting pollutant diffusion from a line source of arbitrary geometry is treated. The concentration at the line source may be arbitrarily varied with time. Special attention is given to the meteorological inputs which act as boundary conditions for the problem, and a mixing layer of arbitrary depth is assumed. Numerical application of the derived theory indicates the combinations of meteorological parameters that may be expected to result in high pollution concentrations.

LES-based generation of high-frequency fluctuation in wind turbulence obtained by meteorological model

NASA Astrophysics Data System (ADS)

Tamura, Tetsuro; Kawaguchi, Masaharu; Kawai, Hidenori; Tao, Tao

2017-11-01

The connection between a meso-scale model and a micro-scale large eddy simulation (LES) is significant to simulate the micro-scale meteorological problem such as strong convective events due to the typhoon or the tornado using LES. In these problems the mean velocity profiles and the mean wind directions change with time according to the movement of the typhoons or tornadoes. Although, a fine grid micro-scale LES could not be connected to a coarse grid meso-scale WRF directly. In LES when the grid is suddenly refined at the interface of nested grids which is normal to the mean advection the resolved shear stresses decrease due to the interpolation errors and the delay of the generation of smaller scale turbulence that can be resolved on the finer mesh. For the estimation of wind gust disaster the peak wind acting on buildings and structures has to be correctly predicted. In the case of meteorological model the velocity fluctuations have a tendency of diffusive variation without the high frequency component due to the numerically filtering effects. In order to predict the peak value of wind velocity with good accuracy, this paper proposes a LES-based method for generating the higher frequency components of velocity and temperature fields obtained by meteorological model.

The complementary relationship (CR) approach aids evapotranspiration estimation in the data scarce region of Tibetan Plateau: symmetric and asymmetric perspectives

NASA Astrophysics Data System (ADS)

Ma, N.; Zhang, Y.; Szilagyi, J.; Xu, C. Y.

2015-12-01

While the land surface latent and sensible heat release in the Tibetan Plateau (TP) could greatly influence the Asian monsoon circulation, the actual evapotranspiration (ETa) information in the TP has been largely hindered by its extremely sparse ground observation network. Thus the complementary relationship (CR) theory lends great potential in estimating the ETa since it relies on solely routine meteorological observations. With the in-situ energy/water flux observation over the highest semiarid alpine steppe in the TP, the modifications of specific components within the CR were first implemented. We found that the symmetry of the CR could be achieved for dry regions of TP when (i) the Priestley-Taylor coefficient, (ii) the slope of the saturation vapor pressure curve and (iii) the wind function were locally calibrated by using the ETa observations in wet days, an estimate of the wet surface temperature and the Monin-Obukhov Similarity (MOS) theory, respectively. In this way, the error of the simulated ETa by the symmetric AA model could be decreased to a large extent. Besides, the asymmetric CR was confirmed in TP when the D20 above-ground and/or E601B sunken pan evaporation (Epan) were used as a proxy of the ETp. Thus daily ETa could also be estimated by coupling D20 above-ground and/or E601B sunken pans through CR. Additionally, to overcome the modification of the specific components in the CR, we also evaluated the Nonlinear-CR model and the Morton's CRAE model. The former does not need the pre-determination of the asymmetry of CR, while the latter does not require the wind speed data as input. We found that both models are also able to simulate the daily ETa well provided their parameter values have been locally calibrated. The sensitivity analysis shows that, if the measured ETa data are absence to calibrate the models' parameter values, the Nonlinear-CR model may be a particularly good way for estimating ETabecause of its mild sensitivity to the parameter values making possible to employ published parameter values derived under similar climatic and land cover conditions. The CRAE model should also be highlighted in the TP since the special topography make the wind speed data suffer large uncertainties when the advanced geo-statistical method was used to spatially interpolate the point-based meteorological records.

Meteorological and air quality impacts of increased urban albedo and vegetative cover in the Greater Toronto Area, Canada

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

Taha, Haider; Hammer, Hillel; Akbari, Hashem

2002-04-30

The study described in this report is part of a project sponsored by the Toronto Atmospheric Fund, performed at the Lawrence Berkeley National Laboratory, to assess the potential role of surface property modifications on energy, meteorology, and air quality in the Greater Toronto Area (GTA), Canada. Numerical models were used to establish the possible meteorological and ozone air-quality impacts of increased urban albedo and vegetative fraction, i.e., ''cool-city'' strategies that can mitigate the urban heat island (UHI), significantly reduce urban energy consumption, and improve thermal comfort, particularly during periods of hot weather in summer. Mitigation is even more important duringmore » critical heat wave periods with possible increased heat-related hospitalization and mortality. The evidence suggests that on an annual basis cool-city strategies are beneficial, and the implementation of such measures is currently being investigated in the U.S. and Canada. We simulated possible scenari os for urban heat-island mitigation in the GTA and investigated consequent meteorological changes, and also performed limited air-quality analysis to assess related impacts. The study was based on a combination of mesoscale meteorological modeling, Lagrangian (trajectory), and photochemical trajectory modeling to assess the potential meteorological and ozone air-quality impacts of cool-city strategies. As available air-quality and emissions data are incompatible with models currently in use at LBNL, our air-quality analysis was based on photochemical trajectory modeling. Because of questions as to the accuracy and appropriateness of this approach, in our opinion this aspect of the study can be improved in the future, and the air-quality results discussed in this report should be viewed as relatively qualitative. The MM5 meteorological model predicts a UHI in the order of 2 to 3 degrees C in locations of maxima, and about 1 degree C as a typical value over most of the urban area. Our si mulations suggest that cool-city strategies can typically reduce local urban air temperature by 0.5-1 degrees C; as more sporadic events, larger decreases (1.5 degrees C, 2.5-2.7 degrees C and 4-6 degrees C) were also simulated. With regard to ozone mixing ratios along the simulated trajectories, the effects of cool-city strategies appear to be on the order of 2 ppb, a typical decrease. The photochemical trajectory model (CIT) also simulates larger decreases (e.g., 4 to 8 ppb), but these are not taken as representative of the potential impacts in this report. A comparison with other simulations suggest very crudely that a decrease of this magnitude corresponds to significant ''equivalent'' decreases in both NOx and VOCs emissions in the region. Our preliminary results suggest that significant UHI control can be achieved with cool-cities strategies in the GTA and is therefore worth further study. We recommend that better input data and more accurate modeling schemes be used to carry out f uture studies in the same direction.« less

Multiyear applications of WRF/Chem over continental U.S.: Model evaluation, variation trend, and impacts of boundary conditions

NASA Astrophysics Data System (ADS)

Yahya, Khairunnisa; He, Jian; Zhang, Yang

2015-12-01

Multiyear applications of an online-coupled meteorology-chemistry model allow an assessment of the variation trends in simulated meteorology, air quality, and their interactions to changes in emissions and meteorology, as well as the impacts of initial and boundary conditions (ICONs/BCONs) on simulated aerosol-cloud-radiation interactions over a period of time. In this work, the Weather Research and Forecasting model with Chemistry version 3.4.1 (WRF/Chem v. 3.4.1) with the 2005 Carbon Bond mechanism coupled with the Volatility Basis Set module for secondary organic aerosol formation (WRF/Chem-CB05-VBS) is applied for multiple years (2001, 2006, and 2010) over continental U.S. This work also examines the changes in simulated air quality and meteorology due to changes in emissions and meteorology and the model's capability in reproducing the observed variation trends in species concentrations from 2001 to 2010. In addition, the impacts of the chemical ICONs/BCONs on model predictions are analyzed. ICONs/BCONs are downscaled from two global models, the modified Community Earth System Model/Community Atmosphere model version 5.1 (CESM/CAM v5.1) and the Monitoring Atmospheric Composition and Climate model (MACC). The evaluation of WRF/Chem-CB05-VBS simulations with the CESM ICONs/BCONs for 2001, 2006, and 2010 shows that temperature at 2 m (T2) is underpredicted for all three years likely due to inaccuracies in soil moisture and soil temperature, resulting in biases in surface relative humidity, wind speed, and precipitation. With the exception of cloud fraction, other aerosol-cloud variables including aerosol optical depth, cloud droplet number concentration, and cloud optical thickness are underpredicted for all three years, resulting in overpredictions of radiation variables. The model performs well for O3 and particulate matter with diameter less than or equal to 2.5 (PM2.5) for all three years comparable to other studies from literature. The model is able to reproduce observed annual average trends in O3 and PM2.5 concentrations from 2001 to 2006 and from 2006 to 2010 but is less skillful in simulating their observed seasonal trends. The 2006 and 2010 results using CESM and MACC ICONs/BCONs are compared to analyze the impact of ICONs/BCONs on model performance and their feedbacks to aerosol, clouds, and radiation. Comparing to the simulations with MACC ICONs/BCONs, the simulations with the CESM ICONs/BCONs improve the performance of O3 mixing ratios (e.g., the normalized mean bias for maximum 8 h O3 is reduced from -17% to -1% in 2010), PM2.5 in 2010, and sulfate in 2006 (despite a slightly larger normalized mean bias for PM2.5 in 2006). The impacts of different ICONs/BCONs on simulated aerosol-cloud-radiation variables are not negligible, with larger impacts in 2006 compared to 2010.

Application of stepwise multiple regression techniques to inversion of Nimbus 'IRIS' observations.

NASA Technical Reports Server (NTRS)

Ohring, G.

1972-01-01

Exploratory studies with Nimbus-3 infrared interferometer-spectrometer (IRIS) data indicate that, in addition to temperature, such meteorological parameters as geopotential heights of pressure surfaces, tropopause pressure, and tropopause temperature can be inferred from the observed spectra with the use of simple regression equations. The technique of screening the IRIS spectral data by means of stepwise regression to obtain the best radiation predictors of meteorological parameters is validated. The simplicity of application of the technique and the simplicity of the derived linear regression equations - which contain only a few terms - suggest usefulness for this approach. Based upon the results obtained, suggestions are made for further development and exploitation of the stepwise regression analysis technique.

Impact of WRF model PBL schemes on air quality simulations over Catalonia, Spain.

PubMed

Banks, R F; Baldasano, J M

2016-12-01

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.

Linking the Weather Generator with Regional Climate Model

NASA Astrophysics Data System (ADS)

Dubrovsky, Martin; Farda, Ales; Skalak, Petr; Huth, Radan

2013-04-01

One of the downscaling approaches, which transform the raw outputs from the climate models (GCMs or RCMs) into data with more realistic structure, is based on linking the stochastic weather generator with the climate model output. The present contribution, in which the parametric daily surface weather generator (WG) M&Rfi is linked to the RCM output, follows two aims: (1) Validation of the new simulations of the present climate (1961-1990) made by the ALADIN-Climate Regional Climate Model at 25 km resolution. The WG parameters are derived from the RCM-simulated surface weather series and compared to those derived from weather series observed in 125 Czech meteorological stations. The set of WG parameters will include statistics of the surface temperature and precipitation series (including probability of wet day occurrence). (2) Presenting a methodology for linking the WG with RCM output. This methodology, which is based on merging information from observations and RCM, may be interpreted as a downscaling procedure, whose product is a gridded WG capable of producing realistic synthetic multivariate weather series for weather-ungauged locations. In this procedure, WG is calibrated with RCM-simulated multi-variate weather series in the first step, and the grid specific WG parameters are then de-biased by spatially interpolated correction factors based on comparison of WG parameters calibrated with gridded RCM weather series and spatially scarcer observations. The quality of the weather series produced by the resultant gridded WG will be assessed in terms of selected climatic characteristics (focusing on characteristics related to variability and extremes of surface temperature and precipitation). Acknowledgements: The present experiment is made within the frame of projects ALARO-Climate (project P209/11/2405 sponsored by the Czech Science Foundation), WG4VALUE (project LD12029 sponsored by the Ministry of Education, Youth and Sports of CR) and VALUE (COST ES 1102 action).

Large-eddy simulations of surface roughness parameter sensitivity to canopy-structure characteristics

DOE PAGES

Maurer, K. D.; Bohrer, G.; Kenny, W. T.; ...

2015-04-30

Surface roughness parameters, namely the roughness length and displacement height, are an integral input used to model surface fluxes. However, most models assume these parameters to be a fixed property of plant functional type and disregard the governing structural heterogeneity and dynamics. In this study, we use large-eddy simulations to explore, in silico, the effects of canopy-structure characteristics on surface roughness parameters. We performed a virtual experiment to test the sensitivity of resolved surface roughness to four axes of canopy structure: (1) leaf area index, (2) the vertical profile of leaf density, (3) canopy height, and (4) canopy gap fraction.more » We found roughness parameters to be highly variable, but uncovered positive relationships between displacement height and maximum canopy height, aerodynamic canopy height and maximum canopy height and leaf area index, and eddy-penetration depth and gap fraction. We also found negative relationships between aerodynamic canopy height and gap fraction, as well as between eddy-penetration depth and maximum canopy height and leaf area index. We generalized our model results into a virtual "biometric" parameterization that relates roughness length and displacement height to canopy height, leaf area index, and gap fraction. Using a decade of wind and canopy-structure observations in a site in Michigan, we tested the effectiveness of our model-driven biometric parameterization approach in predicting the friction velocity over heterogeneous and disturbed canopies. We compared the accuracy of these predictions with the friction-velocity predictions obtained from the common simple approximation related to canopy height, the values calculated with large-eddy simulations of the explicit canopy structure as measured by airborne and ground-based lidar, two other parameterization approaches that utilize varying canopy-structure inputs, and the annual and decadal means of the surface roughness parameters at the site from meteorological observations. We found that the classical representation of constant roughness parameters (in space and time) as a fraction of canopy height performed relatively well. Nonetheless, of the approaches we tested, most of the empirical approaches that incorporate seasonal and interannual variation of roughness length and displacement height as a function of the dynamics of canopy structure produced more precise and less biased estimates for friction velocity than models with temporally invariable parameters.« less

Large-eddy simulations of surface roughness parameter sensitivity to canopy-structure characteristics

NASA Astrophysics Data System (ADS)

Maurer, K. D.; Bohrer, G.; Kenny, W. T.; Ivanov, V. Y.

2015-04-01

Surface roughness parameters, namely the roughness length and displacement height, are an integral input used to model surface fluxes. However, most models assume these parameters to be a fixed property of plant functional type and disregard the governing structural heterogeneity and dynamics. In this study, we use large-eddy simulations to explore, in silico, the effects of canopy-structure characteristics on surface roughness parameters. We performed a virtual experiment to test the sensitivity of resolved surface roughness to four axes of canopy structure: (1) leaf area index, (2) the vertical profile of leaf density, (3) canopy height, and (4) canopy gap fraction. We found roughness parameters to be highly variable, but uncovered positive relationships between displacement height and maximum canopy height, aerodynamic canopy height and maximum canopy height and leaf area index, and eddy-penetration depth and gap fraction. We also found negative relationships between aerodynamic canopy height and gap fraction, as well as between eddy-penetration depth and maximum canopy height and leaf area index. We generalized our model results into a virtual "biometric" parameterization that relates roughness length and displacement height to canopy height, leaf area index, and gap fraction. Using a decade of wind and canopy-structure observations in a site in Michigan, we tested the effectiveness of our model-driven biometric parameterization approach in predicting the friction velocity over heterogeneous and disturbed canopies. We compared the accuracy of these predictions with the friction-velocity predictions obtained from the common simple approximation related to canopy height, the values calculated with large-eddy simulations of the explicit canopy structure as measured by airborne and ground-based lidar, two other parameterization approaches that utilize varying canopy-structure inputs, and the annual and decadal means of the surface roughness parameters at the site from meteorological observations. We found that the classical representation of constant roughness parameters (in space and time) as a fraction of canopy height performed relatively well. Nonetheless, of the approaches we tested, most of the empirical approaches that incorporate seasonal and interannual variation of roughness length and displacement height as a function of the dynamics of canopy structure produced more precise and less biased estimates for friction velocity than models with temporally invariable parameters.

Application of troposphere model from NWP and GNSS data into real-time precise positioning

NASA Astrophysics Data System (ADS)

Wilgan, Karina; Hadas, Tomasz; Kazmierski, Kamil; Rohm, Witold; Bosy, Jaroslaw

2016-04-01

The tropospheric delay empirical models are usually functions of meteorological parameters (temperature, pressure and humidity). The application of standard atmosphere parameters or global models, such as GPT (global pressure/temperature) model or UNB3 (University of New Brunswick, version 3) model, may not be sufficient, especially for positioning in non-standard weather conditions. The possible solution is to use regional troposphere models based on real-time or near-real time measurements. We implement a regional troposphere model into the PPP (Precise Point Positioning) software GNSS-WARP (Wroclaw Algorithms for Real-time Positioning) developed at Wroclaw University of Environmental and Life Sciences. The software is capable of processing static and kinematic multi-GNSS data in real-time and post-processing mode and takes advantage of final IGS (International GNSS Service) products as well as IGS RTS (Real-Time Service) products. A shortcoming of PPP technique is the time required for the solution to converge. One of the reasons is the high correlation among the estimated parameters: troposphere delay, receiver clock offset and receiver height. To efficiently decorrelate these parameters, a significant change in satellite geometry is required. Alternative solution is to introduce the external high-quality regional troposphere delay model to constrain troposphere estimates. The proposed model consists of zenith total delays (ZTD) and mapping functions calculated from meteorological parameters from Numerical Weather Prediction model WRF (Weather Research and Forecasting) and ZTDs from ground-based GNSS stations using the least-squares collocation software COMEDIE (Collocation of Meteorological Data for Interpretation and Estimation of Tropospheric Pathdelays) developed at ETH Zurich.

A Model for the Formation and Melting of Ice on Surface Waters.

NASA Astrophysics Data System (ADS)

de Bruin, H. A. R.; Wessels, H. R. A.

1988-02-01

Ice covers have an important influence on the hydrology of surface waters. The growth of ice layer on stationary waters, such as lakes or canals, depends primarily on meteorological parameters like temperature and humidity of the air, windspeed and radiation balance. The more complicated ice formation in rapidly flowing rivers is not considered in this study. A model is described that simulates ice growth and melting utilizing observed or forecast weather data. The model includes situations with a snow cover. Special attention is given to the optimal estimation of the net radiation and to the role of the stability of the near-surface air. Since a major practical application in the Netherlands is the use of frozen waters for recreation skating, the model is extended to include artificial ice tracks.

SIMULATION OF SUMMER-TIME DIURNAL BACTERIAL DYNAMICS IN THE ATMOSPHERIC SURFACE LAYER

EPA Science Inventory

A model was prepared to simulate the observed concentration dynamics of culturable bacteria in the diurnal summer atmosphere at a Willamette River Valley, Oregon location. The meteorological and bacterial mechanisms included in a dynamic null-dimensional model with one-second tim...

The effect of aerosol optical depth on rainfall with reference to meteorology over metro cities in India.

PubMed

Gunaseelan, Indira; Bhaskar, B Vijay; Muthuchelian, K

2014-01-01

Rainfall is a key link in the global water cycle and a proxy for changing climate; therefore, proper assessment of the urban environment's impact on rainfall will be increasingly important in ongoing climate diagnostics and prediction. Aerosol optical depth (AOD) measurements on the monsoon seasons of the years 2008 to 2010 were made over four metro regional hotspots in India. The highest average of AOD was in the months of June and July for the four cities during 3 years and lowest was in September. Comparing the four regions, Kolkata was in the peak of aerosol contamination and Chennai was in least. Pearson correlation was made between AOD with climatic parameters. Some changes in the parameters were found during drought year. Temperature, cloud parameters, and humidity play an important role for the drought conditions. The role of aerosols, meteorological parameters, and their impacts towards the precipitation during the monsoon was studied.

Southern Greenland water vapour isotopic composition at the crossroads of Atlantic and Arctic moisture

NASA Astrophysics Data System (ADS)

Bonne, J. L.; Steen-Larsen, H. C.; Risi, C. M.; Werner, M.; Sodemann, H.; Lacour, J. L.; Fettweis, X.; Cesana, G.; Delmotte, M.; Cattani, O.; Clerbaux, C.; Sveinbjörnsdottir, A. E.; Masson-Delmotte, V.

2014-12-01

Since September 2011, a continuous water vapour isotopic composition monitoring instrument has been remotely operated in Ivittuut (61.21°N, 48.17°W), southern Greenland. Meteorological parameters are monitored and precipitation has been sampled and analysed for isotopic composition, suggesting equilibrium between surface vapour and precipitation. The data depict small summer diurnal variations. δ18O and deuterium excess (d-excess) are generally anti-correlated and show important seasonal variations (with respective amplitudes of 10 and 20 ‰), and large synoptic variations associated to low-pressure systems (typically +5‰ on δ18O and -15‰ on d-excess). The moisture sources, estimated based on Lagrangian back-trajectories, are primarily influenced by the western North Atlantic, and north-eastern American continent. Notable are important seasonal and synoptic shifts of the moisture sources, and sporadic influences of the Arctic or the eastern North Atlantic. Moisture sources variations can be related to changes in water vapour isotopic composition, and the isotopic fingerprints can be attributed to the areas of moisture origins. Isotopic enabled AGCMs nudged to meteorology (LMDZiso, ECHAM5-wiso), despite biases, correctly capture the δ18O changes, but underestimate the d-excess changes. They allow to identify a high correlation between the southern Greenland d-excess and the simulated relative humidity and d-excess in the moisture source region south of Greenland. An extreme high temperature event in July 2012 affecting all Greenland, similar to ice sheet melt events during the medieval periods and one event in 1889 documented by Greenland ice core records, has been analysed regarding water vapour isotopic composition, using remote sensing (IASI) and in situ observations from Bermuda to northern Greenland (NEEM station). Our southern Greenland observations allow to track the water vapour evolution during this event along the moisture transport path, depicting the northward propagation of an isotopic signal inherited from the meteorological conditions during evaporation. Overall, our observations provide valuable information for interpreting Greenland ice core records as well as for evaluating water vapour isotopic simulations in atmospheric models.

Current status of validating operational model forecasts at the DWD site Lindenberg

NASA Astrophysics Data System (ADS)

Beyrich, F.; Heret, C.; Vogel, G.

2009-09-01

Based on long experience in the measurement of atmospheric boundary layer parameters, the Meteorological Observatory Lindenberg / Richard - Aßmann-Observatory is well qualified to validate operational NWP results for this location. The validation activities cover a large range of time periods from single days or months up to several years and include much more quantities than generally used in areal verification techniques. They mainly focus on land surface and boundary layer processes which play an important role in the atmospheric forc-ing from the surface. Versatility and continuity of the database enable a comprehensive evaluation of the model behaviour under different meteorological conditions in order to esti-mate the accuracy of the physical parameterisations and to detect possible deficiencies in the predicted processes. The measurements from the boundary layer field site Falkenberg serve as reference data for various types of validation studies: 1. The operational boundary-layer measurements are used to identify and to document weather situations with large forecast errors which can then be analysed in more de-tail. Results from a case study will be presented where model deficiencies in the cor-rect simulation of the diurnal evolution of near-surface temperature under winter con-ditions over a closed snow cover where diagnosed. 2. Due to the synopsis of the boundary layer quantities based on monthly averaged di-urnal cycles systematic model deficiencies can be detected more clearly. Some dis-tinctive features found in the annual cycle (e.g. near-surface temperatures, turbulent heat fluxes and soil moisture) will be outlined. Further aspects are their different ap-pearance in the COSMO-EU and COSMO-DE models as well as the effects of start-ing time (00 or 12 UTC) on the prediction accuracy. 3. The evaluation of the model behaviour over several years provides additional insight into the impact of changes in the physical parameterisations, data assimilation or nu-merics on the meteorological quantities. The temporal development of the error char-acteristics of some near-surface weather parameters (temperature, dewpoint tem-perature, wind velocity) and of the energy fluxes at the surface will be discussed.

Modeling analysis of secondary inorganic aerosols over China: pollution characteristics, and meteorological and dust impacts.

PubMed

Fu, Xiao; Wang, Shuxiao; Chang, Xing; Cai, Siyi; Xing, Jia; Hao, Jiming

2016-10-26

Secondary inorganic aerosols (SIA) are the predominant components of fine particulate matter (PM 2.5 ) and have significant impacts on air quality, human health, and climate change. In this study, the Community Multiscale Air Quality modeling system (CMAQ) was modified to incorporate SO 2 heterogeneous reactions on the surface of dust particles. The revised model was then used to simulate the spatiotemporal characteristics of SIA over China and analyze the impacts of meteorological factors and dust on SIA formation. Including the effects of dust improved model performance for the simulation of SIA concentrations, particularly for sulfate. The simulated annual SIA concentration in China was approximately 10.1 μg/m 3 on domain average, with strong seasonal variation: highest in winter and lowest in summer. High SIA concentrations were concentrated in developed regions with high precursor emissions, such as the North China Plain, Yangtze River Delta, Sichuan Basin, and Pearl River Delta. Strong correlations between meteorological factors and SIA pollution levels suggested that heterogeneous reactions under high humidity played an important role on SIA formation, particularly during severe haze pollution periods. Acting as surfaces for heterogeneous reactions, dust particles significantly affected sulfate formation, suggesting the importance of reducing dust emissions for controlling SIA and PM 2.5 pollution.

Chemical transport model ozone simulations for spring 2001 over the western Pacific: Comparisons with TRACE-P lidar, ozonesondes, and Total Ozone Mapping Spectrometer columns

NASA Astrophysics Data System (ADS)

Wild, Oliver; Sundet, Jostein K.; Prather, Michael J.; Isaksen, Ivar S. A.; Akimoto, Hajime; Browell, Edward V.; Oltmans, Samuel J.

2003-11-01

Two closely related chemical transport models (CTMs) employing the same high-resolution meteorological data (˜180 km × ˜180 km × ˜600 m) from the European Centre for Medium-Range Weather Forecasts are used to simulate the ozone total column and tropospheric distribution over the western Pacific region that was explored by the NASA Transport and Chemical Evolution over the Pacific (TRACE-P) measurement campaign in February-April 2001. We make extensive comparisons with ozone measurements from the lidar instrument on the NASA DC-8, with ozonesondes taken during the period around the Pacific Rim, and with TOMS total column ozone. These demonstrate that within the uncertainties of the meteorological data and the constraints of model resolution, the two CTMs (FRSGC/UCI and Oslo CTM2) can simulate the observed tropospheric ozone and do particularly well when realistic stratospheric ozone photochemistry is included. The greatest differences between the models and observations occur in the polluted boundary layer, where problems related to the simplified chemical mechanism and inadequate horizontal resolution are likely to have caused the net overestimation of about 10 ppb mole fraction. In the upper troposphere, the large variability driven by stratospheric intrusions makes agreement very sensitive to the timing of meteorological features.

Modeling analysis of secondary inorganic aerosols over China: pollution characteristics, and meteorological and dust impacts

NASA Astrophysics Data System (ADS)

Fu, Xiao; Wang, Shuxiao; Chang, Xing; Cai, Siyi; Xing, Jia; Hao, Jiming

2016-10-01

Secondary inorganic aerosols (SIA) are the predominant components of fine particulate matter (PM2.5) and have significant impacts on air quality, human health, and climate change. In this study, the Community Multiscale Air Quality modeling system (CMAQ) was modified to incorporate SO2 heterogeneous reactions on the surface of dust particles. The revised model was then used to simulate the spatiotemporal characteristics of SIA over China and analyze the impacts of meteorological factors and dust on SIA formation. Including the effects of dust improved model performance for the simulation of SIA concentrations, particularly for sulfate. The simulated annual SIA concentration in China was approximately 10.1 μg/m3 on domain average, with strong seasonal variation: highest in winter and lowest in summer. High SIA concentrations were concentrated in developed regions with high precursor emissions, such as the North China Plain, Yangtze River Delta, Sichuan Basin, and Pearl River Delta. Strong correlations between meteorological factors and SIA pollution levels suggested that heterogeneous reactions under high humidity played an important role on SIA formation, particularly during severe haze pollution periods. Acting as surfaces for heterogeneous reactions, dust particles significantly affected sulfate formation, suggesting the importance of reducing dust emissions for controlling SIA and PM2.5 pollution.

Modeling analysis of secondary inorganic aerosols over China: pollution characteristics, and meteorological and dust impacts

PubMed Central

Fu, Xiao; Wang, Shuxiao; Chang, Xing; Cai, Siyi; Xing, Jia; Hao, Jiming

2016-01-01

Secondary inorganic aerosols (SIA) are the predominant components of fine particulate matter (PM2.5) and have significant impacts on air quality, human health, and climate change. In this study, the Community Multiscale Air Quality modeling system (CMAQ) was modified to incorporate SO2 heterogeneous reactions on the surface of dust particles. The revised model was then used to simulate the spatiotemporal characteristics of SIA over China and analyze the impacts of meteorological factors and dust on SIA formation. Including the effects of dust improved model performance for the simulation of SIA concentrations, particularly for sulfate. The simulated annual SIA concentration in China was approximately 10.1 μg/m3 on domain average, with strong seasonal variation: highest in winter and lowest in summer. High SIA concentrations were concentrated in developed regions with high precursor emissions, such as the North China Plain, Yangtze River Delta, Sichuan Basin, and Pearl River Delta. Strong correlations between meteorological factors and SIA pollution levels suggested that heterogeneous reactions under high humidity played an important role on SIA formation, particularly during severe haze pollution periods. Acting as surfaces for heterogeneous reactions, dust particles significantly affected sulfate formation, suggesting the importance of reducing dust emissions for controlling SIA and PM2.5 pollution. PMID:27782166

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

Park, R.; Hong, Seungkyu K.; Kwon, Hyoung-Ahn

We used a 3-D regional atmospheric chemistry transport model (WRF-Chem) to examine processes that determine O3 in East Asia; in particular, we focused on O3 dry deposition, which is an uncertain research area due to insufficient observation and numerical studies in East Asia. Here, we compare two widely used dry deposition parameterization schemes, Wesely and M3DRY, which are used in the WRF-Chem and CMAQ models, respectively. The O3 dry deposition velocities simulated using the two aforementioned schemes under identical meteorological conditions show considerable differences (a factor of 2) due to surface resistance parameterization discrepancies. The O3 concentration differed by upmore » to 10 ppbv for the monthly mean. The simulated and observed dry deposition velocities were compared, which showed that the Wesely scheme model is consistent with the observations and successfully reproduces the observed diurnal variation. We conduct several sensitivity simulations by changing the land use data, the surface resistance of the water and the model’s spatial resolution to examine the factors that affect O3 concentrations in East Asia. As shown, the model was considerably sensitive to the input parameters, which indicates a high uncertainty for such O3 dry deposition simulations. Observations are necessary to constrain the dry deposition parameterization and input data to improve the East Asia air quality models.« less

Evaluating the spatial distribution of water balance in a small watershed, Pennsylvania

NASA Astrophysics Data System (ADS)

Yu, Zhongbo; Gburek, W. J.; Schwartz, F. W.

2000-04-01

A conceptual water-balance model was modified from a point application to be distributed for evaluating the spatial distribution of watershed water balance based on daily precipitation, temperature and other hydrological parameters. The model was calibrated by comparing simulated daily variation in soil moisture with field observed data and results of another model that simulates the vertical soil moisture flow by numerically solving Richards' equation. The impacts of soil and land use on the hydrological components of the water balance, such as evapotranspiration, soil moisture deficit, runoff and subsurface drainage, were evaluated with the calibrated model in this study. Given the same meteorological conditions and land use, the soil moisture deficit, evapotranspiration and surface runoff increase, and subsurface drainage decreases, as the available water capacity of soil increases. Among various land uses, alfalfa produced high soil moisture deficit and evapotranspiration and lower surface runoff and subsurface drainage, whereas soybeans produced an opposite trend. The simulated distribution of various hydrological components shows the combined effect of soil and land use. Simulated hydrological components compare well with observed data. The study demonstrated that the distributed water balance approach is efficient and has advantages over the use of single average value of hydrological variables and the application at a single point in the traditional practice.

What Drives the Variability of the Mid-Latitude Ionosphere?

NASA Astrophysics Data System (ADS)

Goncharenko, L. P.; Zhang, S.; Erickson, P. J.; Harvey, L.; Spraggs, M. E.; Maute, A. I.

2016-12-01

The state of the ionosphere is determined by the superposition of the regular changes and stochastic variations of the ionospheric parameters. Regular variations are represented by diurnal, seasonal and solar cycle changes, and can be well described by empirical models. Short-term perturbations that vary from a few seconds to a few hours or days can be induced in the ionosphere by solar flares, changes in solar wind, coronal mass ejections, travelling ionospheric disturbances, or meteorological influences. We use over 40 years of observations by the Millstone Hill incoherent scatter radar (42.6oN, 288.5oE) to develop an updated empirical model of ionospheric parameters, and wintertime data collected in 2004-2016 to study variability in ionospheric parameters. We also use NASA MERRA2 atmospheric reanalysis data to examine possible connections between the state of the stratosphere & mesosphere and the upper atmosphere (250-400km). A case of major SSW of January 2013 is selected for in-depth study and reveals large anomalies in ionospheric parameters. Modeling with the NCAR Thermospheric-Ionospheric-Mesospheric-Electrodynamics general Circulation Model (TIME-GCM) nudged by WACCM-GEOS5 simulation indicates that during the 2013 SSW the neutral and ion temperature in the polar through mid-latitude region deviates from the seasonal behavior.

Land-Sea-Atmosphere Interaction and Their Association with Drought Conditions

NASA Astrophysics Data System (ADS)

Singh, R. P.; Nath, A.

2017-12-01

Detailed analysis of satellite data for the period 2002-2016 provides an understanding of the land-sea interaction and its association with the vegetation conditions over the Indian continent. The Indian Ocean dipole (IOD) phenomenon is also considered to understand the atmospheric dynamics and meteorological parameters. GPS water vapor and meteorological parameters (relative humidity and water vapor) from the Indian Institute of Science (IISC) Bangalore have been considered for meteorological data for the period 2008-2016. Atmospheric parameters (water vapor, precipitation rate, land temperature, total ozone column) have been considered using through NASA Giovanni portal and GPS water vapor through SoumiNet data to study relation between Sea Surface temperature (SST) from Indian Ocean, Bay of Bengal and Arabian Sea. Our detailed analysis shows that SST has strong impact on the NDVI at different locations, the maximum impact of SST is observed at lower latitudes. The NDVI over the central and northern India (Indo-Gangetic plains (IGP) is not affected. The SST and NDVI shows high correlation in the central and northern parts, whereas the correlation is poor in the southern parts i.e. close to the ocean. The detailed analysis of NDVI data provides progression of the drought conditions especially in the southern parts of India and also shows impact of the El Nino during 2015-2016.

The influence of meteorological conditions on the progress and dynamics of pollen phenophases of selected species.

NASA Astrophysics Data System (ADS)

Jatczak, K.; Linkowska, J.; Rapiejko, P.

2010-09-01

In Poland phenological data is used mainly as a natural indicator of the influence of climate changes on environment. In relation to the growing interest of phenology in scientific research, we substantially extended observation ranges, concentrating mainly on phenophases of selected species that are important for allergology. Phenological data application in complex analysis together with meteorological and aerobiological data, give an opportunity for drawing conclusions on variability of the starting date of pollen season and its dynamics in a meteorological aspect. Species have their regional phenological characteristics, however the characteristics depends on meteorological conditions in a particular year. Therefore, the calculation of pheno-meteorological parameters is important for pollen release prediction. Availability of phenological database can also be useful in the field of preventive health care, through phenological data application in different atmospheric models (NWP models, phenological models, pollen release models) for numerical forecasting of pollen concentration in the air. Genetic conditions, industrial development, increase of air pollution are regarded as the main determinants of allergic diseases. The results of pheno - aero- meteorological analysis enable the estimation of the influence of natural environmental changes on the increasing prevalence of allergic diseases in Poland.

Watershed Data Management (WDM) database for Salt Creek streamflow simulation, DuPage County, Illinois, water years 2005-11

USGS Publications Warehouse

Bera, Maitreyee

2014-01-01

The U.S. Geological Survey (USGS), in cooperation with DuPage County Stormwater Management Division, maintains a USGS database of hourly meteorologic and hydrologic data for use in a near real-time streamflow simulation system, which assists in the management and operation of reservoirs and other flood-control structures in the Salt Creek watershed in DuPage County, Illinois. Most of the precipitation data are collected from a tipping-bucket rain-gage network located in and near DuPage County. The other meteorologic data (wind speed, solar radiation, air temperature, and dewpoint temperature) are collected at Argonne National Laboratory in Argonne, Ill. Potential evapotranspiration is computed from the meteorologic data. The hydrologic data (discharge and stage) are collected at USGS streamflow-gaging stations in DuPage County. These data are stored in a Watershed Data Management (WDM) database. An earlier report describes in detail the WDM database development including the processing of data from January 1, 1997, through September 30, 2004, in SEP04.WDM database. SEP04.WDM is updated with the appended data from October 1, 2004, through September 30, 2011, water years 2005–11 and renamed as SEP11.WDM. This report details the processing of meteorologic and hydrologic data in SEP11.WDM. This report provides a record of snow affected periods and the data used to fill missing-record periods for each precipitation site during water years 2005–11. The meteorologic data filling methods are described in detail in Over and others (2010), and an update is provided in this report.

A Summary of the Naval Postgraduate School Research Program

DTIC Science & Technology

1988-08-30

Teh.(accepted). F. P. Kel lyr C.-F. Shih , D. L. Reinke, and T. H. Vonder Haart "Metric Statistical Comparison of Objective Cloud Detectors," Er...February 5, 1988, Anaheim, CAP American Meteorological Society# Boston, MA. 211 Publications: C.-F. Shih , M. Wentzel, and T. H. Yonder Haar, (cont... Shih , "Estimation of Meteorological Parameters Over Mesoscale Regions from Satel l ite and In Situ Data." Preprints, Third Conference DR Satellite

The Automatic Meteorological Station System AN/TMQ-30 ( ).

DTIC Science & Technology

1982-08-01

network, the station electronics initiate the above operating sequence. 3.2.1 Meteorological Parameters Vindspeed. Windspeed measurements are made over a...much like a pocket calculator. Provision has been made to enable the operator to set or read the clock of the master station and to * set, modify, or...conditions is occuring during a regular cycle period. A normal report is not made under these conditions. Control is passed to the read data module under

Satellite Power System (SPS) laser studies. Volume 2: Meteorological effects on laser beam propagation and direct solar pumped lasers for the SPS

NASA Technical Reports Server (NTRS)

Beverly, R. E., III

1980-01-01

The primary emphasis of this research activity was to investigate the effect of the environment on laser power transmission/reception from space to ground. Potential mitigation techniques to minimize the environment effect by a judicious choice of laser operating parameters was investigated. Using these techniques, the availability of power at selected sites was determined using statistical meteorological data for each site.

Determinants of Low Cloud Properties - An Artificial Neural Network Approach Using Observation Data Sets

NASA Astrophysics Data System (ADS)

Andersen, Hendrik; Cermak, Jan

2015-04-01

This contribution studies the determinants of low cloud properties based on the application of various global observation data sets in machine learning algorithms. Clouds play a crucial role in the climate system as their radiative properties and precipitation patterns significantly impact the Earth's energy balance. Cloud properties are determined by environmental conditions, as cloud formation requires the availability of water vapour ("precipitable water") and condensation nuclei in sufficiently saturated conditions. A main challenge in the research of aerosol-cloud interactions is the separation of aerosol effects from meteorological influence. To gain understanding of the processes that govern low cloud properties in order to increase accuracy of climate models and predictions of future changes in the climate system is thus of great importance. In this study, artificial neural networks are used to relate a selection of predictors (meteorological parameters, aerosol loading) to a set of predictands (cloud microphysical and optical properties). As meteorological parameters, wind direction and velocity, sea level pressure, static stability of the lower troposphere, atmospheric water vapour and temperature at the surface are used (re-analysis data by the European Centre for Medium-Range Weather Forecasts). In addition to meteorological conditions, aerosol loading is used as a predictor of cloud properties (MODIS collection 6 aerosol optical depth). The statistical model reveals significant relationships between predictors and predictands and is able to represent the aerosol-cloud-meteorology system better than frequently used bivariate relationships. The most important predictors can be identified by the additional error when excluding one predictor at a time. The sensitivity of each predictand to each of the predictors is analyzed.

Monitoring Supraglacial Streams over Three Months in Southwest Greenland

NASA Astrophysics Data System (ADS)

Muthyala, R.; Rennermalm, A.; Leidman, S. Z.; Cooper, M. G.; Cooley, S. W.; Smith, L. C.; van As, D.

2017-12-01

Supraglacial river networks are the most efficient conduits for evacuation of meltwater runoff produced on Greenland ice sheet. These rivers are prominent features on the ablation zone of southwest Greenland. However, little is known about the transport of meltwater through supraglacial stream network and most of the in-situ observations only capture a few days of streamflow. Here we report three months of observations of water level and discharge collected during summer of 2016, in two small supraglacial streams near the ice sheet margin in southwest Greenland. We also compare streamflow observations with meteorological data from a nearby automatic weather station. The two sites are very different, with the lower basin relatively steep, smooth and dark while the upper basin has rugged terrain and deeply incised stream channels. These catchment characteristics propagate to different relationships with meteorological parameters. For example, upper basin stream water levels show a strong covariance with surface temperature while the lower basin water levels do not. We also find differences in temporal variation of supraglacial stream water level, with the upper basin having two distinct peaks, in mid-June and mid-July, while the lower basin shows gradual decrease from June to August. Long-term supraglacial stream observations such as these will ultimately help assess how well surface mass balance models can simulate ice sheet runoff.

Does temperature nudging overwhelm aerosol radiative ...

EPA Pesticide Factsheets

For over two decades, data assimilation (popularly known as nudging) methods have been used for improving regional weather and climate simulations by reducing model biases in meteorological parameters and processes. Similar practice is also popular in many regional integrated meteorology-air quality models that include aerosol direct and indirect effects. However in such multi-modeling systems, temperature changes due to nudging can compete with temperature changes induced by radiatively active & hygroscopic short-lived tracers leading to interesting dilemmas: From weather and climate prediction’s (retrospective or future) point of view when nudging is continuously applied, is there any real added benefit of using such complex and computationally expensive regional integrated modeling systems? What are the relative sizes of these two competing forces? To address these intriguing questions, we convert temperature changes due to nudging into radiative fluxes (referred to as the pseudo radiative forcing, PRF) at the surface and troposphere, and compare the net PRF with the reported aerosol radiative forcing. Results indicate that the PRF at surface dominates PRF at top of the atmosphere (i.e., the net). Also, the net PRF is about 2-4 times larger than estimated aerosol radiative forcing at regional scales while it is significantly larger at local scales. These results also show large surface forcing errors at many polluted urban sites. Thus, operational c

Likelihood of achieving air quality targets under model uncertainties.

PubMed

Digar, Antara; Cohan, Daniel S; Cox, Dennis D; Kim, Byeong-Uk; Boylan, James W

2011-01-01

Regulatory attainment demonstrations in the United States typically apply a bright-line test to predict whether a control strategy is sufficient to attain an air quality standard. Photochemical models are the best tools available to project future pollutant levels and are a critical part of regulatory attainment demonstrations. However, because photochemical models are uncertain and future meteorology is unknowable, future pollutant levels cannot be predicted perfectly and attainment cannot be guaranteed. This paper introduces a computationally efficient methodology for estimating the likelihood that an emission control strategy will achieve an air quality objective in light of uncertainties in photochemical model input parameters (e.g., uncertain emission and reaction rates, deposition velocities, and boundary conditions). The method incorporates Monte Carlo simulations of a reduced form model representing pollutant-precursor response under parametric uncertainty to probabilistically predict the improvement in air quality due to emission control. The method is applied to recent 8-h ozone attainment modeling for Atlanta, Georgia, to assess the likelihood that additional controls would achieve fixed (well-defined) or flexible (due to meteorological variability and uncertain emission trends) targets of air pollution reduction. The results show that in certain instances ranking of the predicted effectiveness of control strategies may differ between probabilistic and deterministic analyses.

Continuously on-going hindcast simulations for impact applications

NASA Astrophysics Data System (ADS)

Anders, Ivonne; Geyer, Beate

2016-04-01

Observations for e.g. temperature, precipitation, radiation, or wind are often used as meteorological forcing for different impact models, like e.g. crop models, urban models, economic models and energy system models. To assess a climate signal, the time period covered by the observation is often too short, they have gaps in between, and are inhomogeneous over time, due to changes in the measurements itself or in the near surrounding. Thus output from global and regional climate models can close the gap and provide homogeneous and physically consistent time series of meteorological parameters. CORDEX evaluation runs performed for the IPCC-AR5 provide a good base for the regional scale. However, with respect to climate services, continuously on-going hindcast simulations are required for regularly updated applications. In this study two projects are presented where hindcast-simulations optimized for a region of interest are performed continuously. The hindcast simulation performed by HZG covering Europe includes the EURO-CORDEX domain with a wider extend to the north to cover the ice edge. The simulation under consideration of the coastDat-experiences is available for the period of 1979 - 2015, prolonged ongoing and fulfills the customer's needs with respect of output variables, levels, intervals and statistical measures. CoastDat - customers are dealing e.g. with naval architecture, renewable energies, offshore wind farming, shipping emissions, coastal flood risk and others. The evaluation of the hindcast is done for Europe by using the EVAL-tool of the CCLM community and by comparison with HYRAS - data for Germany and neighbouring countries. The Climate Research group at the national Austrian weather service, ZAMG, is focusing on high mountain regions and, especially on the Alps. The hindcast-simulation is forced by ERA-interim and optimized for the Alpine Region. One of the main tasks is to capture strong precipitation events which often occur during summer when low pressure systems develop over the Golf of Genoa, moving to the North-East. This leads to floods and landslide events in Austria, Czech Republic and Germany. Such events are not sufficiently represented in the CORDEX-evaluation runs. ZAMG use high quality gridded precipitation and temperature data for the Alpine Region (1-6km) to evaluate the model performance. Data is provided e.g. to hydrological modellers (high water, low water), but also to assess icing capability of infrastructure.

Modeling hydrodynamics, temperature and water quality in Henry Hagg Lake, Oregon, 2000-2003

USGS Publications Warehouse

Sullivan, Annette B.; Rounds, Stewart A.

2004-01-01

The two-dimensional model CE-QUAL-W2 was used to simulate hydrodynamics, temperature, and water quality in Henry Hagg Lake, Oregon, for the years 2000 through 2003. Input data included lake bathymetry, meteorologic conditions, tributary inflows, tributary temperature and water quality, and lake outflows. Calibrated constituents included lake hydrodynamics, water temperature, orthophosphate, total phosphorus, ammonia, algae, chlorophyll a, zooplankton, and dissolved oxygen. Other simulated constituents included nitrate, dissolved and particulate organic matter, dissolved solids, and suspended sediment. Two algal groups (blue-green algae, and all other algae) were included in the model to simulate the lakes algal communities. Measured lake stage data were used to calibrate the lakes water balance; calibration of water temperature and water quality relied upon vertical profile data taken in the deepest part of the lake near the dam. The model initially was calibrated with data from 200001 and tested with data from 200203. Sensitivity tests were performed to examine the response of the model to specific parameters and coefficients, including the light-extinction coefficient, wind speed, tributary inflows of phosphorus, nitrogen and organic matter, sediment oxygen demand, algal growth rates, and zooplankton feeding preference factors.

Validation of the RegCM4-Subgrid module for the high resolution climate simulation over Korea

NASA Astrophysics Data System (ADS)

Lee, C.; Im, E.; Chang, K.; Choi, Y.

2010-12-01

Given the discernable evidences of climate changes due to human activity, there is a growing demand for the reliable climate change scenario in response to future emission forcing. One of the most significant impacts of climate changes can be that on the hydrological process. Changes in the seasonality and the low and high rainfall extremes can influence the water balance of river basin, with several consequences for societies and ecosystems. In fact, recent studies have reported that East Asia including the Korean peninsula is regarded to be a highly vulnerability region under global warming, especially for water resources. As an attempt to accurately assess the impact of climate change over Korea, we developed the dynamical downscaling system using the RegCM4 with a mosaic-type parameterization of subgrid-scale topography and land use (Sub-BATS). The Sub-BATS system is composed of 20 km coarse-grid cell and 4 km sub-grid cell. Before a full climate change simulation is carried out, we performed the simulation spanning the 19-year periods (1989-2007) with the lateral boundary fields obtained from the ERA-Interim reanalysis. The Korean peninsula is characterized by narrow mountain systems surrounded by ocean, and covered by a relatively dense observational network (approximate 400 stations), which provides an excellent dataset to validate a finescale downscaled results over the region. The evaluation of simulated surface variables (e.g. temperature, precipitation, snow, runoff) shows the usefulness of the RegCM4-Subgrid module as a tool to produce fine scale climate information of surface processes for coupling with hydrological model over the Korean peninsula Acknowledgements This work was supported by the Korea Science and Engineering Foundation (KOSEF) grant funded by the Korea government(MEST) (No. 2009-0085533), and by the "Advanced research on industrial meteorology" and " Development of meteorological resources for green growth." of National Institute of Meteorological Research (NIMR), funded by the Korea Meteorological Administration(KMA).

Climate-driven uncertainties in modeling terrestrial gross primary production: a site level to global-scale analysis.

PubMed

Barman, Rahul; Jain, Atul K; Liang, Miaoling

2014-05-01

We used a land surface model to quantify the causes and extents of biases in terrestrial gross primary production (GPP) due to the use of meteorological reanalysis datasets. We first calibrated the model using meteorology and eddy covariance data from 25 flux tower sites ranging from the tropics to the northern high latitudes and subsequently repeated the site simulations using two reanalysis datasets: NCEP/NCAR and CRUNCEP. The results show that at most sites, the reanalysis-driven GPP bias was significantly positive with respect to the observed meteorology-driven simulations. Notably, the absolute GPP bias was highest at the tropical evergreen tree sites, averaging up to ca. 0.45 kg C m(-2)  yr(-1) across sites (ca. 15% of site level GPP). At the northern mid-/high-latitude broadleaf deciduous and the needleleaf evergreen tree sites, the corresponding annual GPP biases were up to 20%. For the nontree sites, average annual biases of up to ca. 20-30% were simulated within savanna, grassland, and shrubland vegetation types. At the tree sites, the biases in short-wave radiation and humidity strongly influenced the GPP biases, while the nontree sites were more affected by biases in factors controlling water stress (precipitation, humidity, and air temperature). In this study, we also discuss the influence of seasonal patterns of meteorological biases on GPP. Finally, using model simulations for the global land surface, we discuss the potential impacts of site-level reanalysis-driven biases on the global estimates of GPP. In a broader context, our results can have important consequences on other terrestrial ecosystem fluxes (e.g., net primary production, net ecosystem production, energy/water fluxes) and reservoirs (e.g., soil carbon stocks). In a complementary study (Barman et al., ), we extend the present analysis for latent and sensible heat fluxes, thus consistently integrating the analysis of climate-driven uncertainties in carbon, energy, and water fluxes using a single modeling framework. © 2013 John Wiley & Sons Ltd.

Quasi-decadal variations in total ozone content, wind velocity, temperature, and geopotential height over the Arosa station (Switzerland)

NASA Astrophysics Data System (ADS)

Visheratin, K. N.

2016-01-01

We present the results of the analysis of the phase relationships between the quasi-decadal variations (QDVs) (in the range from 8 to 13 years) in the total ozone content (TOC) at the Arosa station for 1932-2012 and a number of meteorological parameters: monthly mean values of temperature, meridional and zonal components of wind velocity, and geopotential heights for isobaric surfaces in the layer of 10-925 hPa over the Arosa station using the Fourier methods and composite and cross-wavelet analysis. It has been shown that the phase relationships of the QDVs in the TOC and meteorological parameters with an 11-year cycle of solar activity change in time and height; starting with cycle 24 of solar activity (2008-2010), the variations in the TOC and a number of meteorological parameters occur in almost counter phase with the variations in solar activity. The periods of the maximum growth rate of the temperature at isobaric surfaces 50-100 hPa nearly correspond to the TOC's maximum periods, and the periods of the maximum temperature correspond the periods of the decrease of the peak TOC rate. The highest correlation coefficients between the meridional wind velocity and temperature are observed at 50 hPa at positive and negative delays of ~27 months. The times of the maxima (minima) of the QDVs in the meridional wind velocity nearly correspond to the periods of the maximum amplification (attenuation) rate of the temperature of the QDVs. The QDVs in the geopotential heights of isobaric surfaces fall behind the variations in the TOC by an average of 1.5 years everywhere except in the lower troposphere. In general, the periods of variations in the TOC and meteorological parameters in the range of 8-13 years are smaller than the period of variations in the level of solar activity.

Characterizing near-road air pollution using local-scale emission and dispersion models and validation against in-situ measurements

NASA Astrophysics Data System (ADS)

Wang, An; Fallah-Shorshani, Masoud; Xu, Junshi; Hatzopoulou, Marianne

2016-10-01

Near-road concentrations of nitrogen dioxide (NO2), a known marker of traffic-related air pollution, were simulated along a busy urban corridor in Montreal, Quebec using a combination of microscopic traffic simulation, instantaneous emission modeling, and air pollution dispersion. In order to calibrate and validate the model, a data collection campaign was designed. For this purpose, measurements of NO2 were conducted mid-block along four segments of the corridor throughout a four-week campaign conducted between March and April 2015. The four segments were chosen to be consecutive and yet exhibiting variability in road configuration and built environment characteristics. Roadside NO2 measurements were also paired with on-site and fixed-station meteorological data. In addition, traffic volumes, composition, and routing decisions were collected using video-cameras located at upstream and downstream intersections. Dispersion of simulated emissions was conducted for eight time slots and under a range of meteorological conditions using three different models with vastly different dispersion algorithms (OSPM, CALINE 4, and SIRANE). The three models exhibited poor correlation with near-road NO2 concentrations and were better able to simulate average concentrations occurring along the roadways rather than the range of concentrations measured under diverse meteorological and traffic conditions. As hypothesized, the model SIRANE that can handle a street canyon configuration was the most sensitive to the built environment especially to the presence of tall buildings around the road. In contrast, CALINE exhibited the lowest sensitivity to the built environment.

Simulation of the outdoor energy efficiency of an autonomous solar kit based on meteorological data for a site in Central Europa

NASA Astrophysics Data System (ADS)

Bouzaki, Mohammed Moustafa; Chadel, Meriem; Benyoucef, Boumediene; Petit, Pierre; Aillerie, Michel

2016-07-01

This contribution analyzes the energy provided by a solar kit dedicated to autonomous usage and installed in Central Europa (Longitude 6.10°; Latitude 49.21° and Altitude 160 m) by using the simulation software PVSYST. We focused the analysis on the effect of temperature and solar irradiation on the I-V characteristic of a commercial PV panel. We also consider in this study the influence of charging and discharging the battery on the generator efficiency. Meteorological data are integrated into the simulation software. As expected, the solar kit provides an energy varying all along the year with a minimum in December. In the proposed approach, we consider this minimum as the lowest acceptable energy level to satisfy the use. Thus for the other months, a lost in the available renewable energy exists if no storage system is associated.

The effect of wind and eruption source parameter variations on tephra fallout hazard assessment: an example from Vesuvio (Italy)

NASA Astrophysics Data System (ADS)

Macedonio, Giovanni; Costa, Antonio; Scollo, Simona; Neri, Augusto

2015-04-01

Uncertainty in the tephra fallout hazard assessment may depend on different meteorological datasets and eruptive source parameters used in the modelling. We present a statistical study to analyze this uncertainty in the case of a sub-Plinian eruption of Vesuvius of VEI = 4, column height of 18 km and total erupted mass of 5 × 1011 kg. The hazard assessment for tephra fallout is performed using the advection-diffusion model Hazmap. Firstly, we analyze statistically different meteorological datasets: i) from the daily atmospheric soundings of the stations located in Brindisi (Italy) between 1962 and 1976 and between 1996 and 2012, and in Pratica di Mare (Rome, Italy) between 1996 and 2012; ii) from numerical weather prediction models of the National Oceanic and Atmospheric Administration and of the European Centre for Medium-Range Weather Forecasts. Furthermore, we modify the total mass, the total grain-size distribution, the eruption column height, and the diffusion coefficient. Then, we quantify the impact that different datasets and model input parameters have on the probability maps. Results shows that the parameter that mostly affects the tephra fallout probability maps, keeping constant the total mass, is the particle terminal settling velocity, which is a function of the total grain-size distribution, particle density and shape. Differently, the evaluation of the hazard assessment weakly depends on the use of different meteorological datasets, column height and diffusion coefficient.

An investigation of the key parameters for predicting PV soiling losses

DOE PAGES

Micheli, Leonardo; Muller, Matthew

2017-01-25

One hundred and two environmental and meteorological parameters have been investigated and compared with the performance of 20 soiling stations installed in the USA, in order to determine their ability to predict the soiling losses occurring on PV systems. The results of this investigation showed that the annual average of the daily mean particulate matter values recorded by monitoring stations deployed near the PV systems are the best soiling predictors, with coefficients of determination ( R 2) as high as 0.82. The precipitation pattern was also found to be relevant: among the different meteorological parameters, the average length of drymore » periods had the best correlation with the soiling ratio. Lastly, a preliminary investigation of two-variable regressions was attempted and resulted in an adjusted R 2 of 0.90 when a combination of PM 2.5 and a binary classification for the average length of the dry period was introduced.« less

The use of Meteonorm weather generator for climate change studies

NASA Astrophysics Data System (ADS)

Remund, J.; Müller, S. C.; Schilter, C.; Rihm, B.

2010-09-01

The global climatological database Meteonorm (www.meteonorm.com) is widely used as meteorological input for simulation of solar applications and buildings. It's a combination of a climate database, a spatial interpolation tool and a stochastic weather generator. Like this typical years with hourly or minute time resolution can be calculated for any site. The input of Meteonorm for global radiation is the Global Energy Balance Archive (GEBA, http://proto-geba.ethz.ch). All other meteorological parameters are taken from databases of WMO and NCDC (periods 1961-90 and 1996-2005). The stochastic generation of global radiation is based on a Markov chain model for daily values and an autoregressive model for hourly and minute values (Aguiar and Collares-Pereira, 1988 and 1992). The generation of temperature is based on global radiation and measured distribution of daily temperature values of approx. 5000 sites. Meteonorm generates also additional parameters like precipitation, wind speed or radiation parameters like diffuse and direct normal irradiance. Meteonorm can also be used for climate change studies. Instead of climate values, the results of IPCC AR4 results are used as input. From all 18 public models an average has been made at a resolution of 1°. The anomalies of the parameters temperature, precipitation and global radiation and the three scenarios B1, A1B and A2 have been included. With the combination of Meteonorm's current database 1961-90, the interpolation algorithms and the stochastic generation typical years can be calculated for any site, for different scenarios and for any period between 2010 and 2200. From the analysis of variations of year to year and month to month variations of temperature, precipitation and global radiation of the past ten years as well of climate model forecasts (from project prudence, http://prudence.dmi.dk) a simple autoregressive model has been formed which is used to generate realistic monthly time series of future periods. Meteonorm can therefore be used as a relatively simple method to enhance the spatial and temporal resolution instead of using complicated and time consuming downscaling methods based on regional climate models. The combination of Meteonorm, gridded historical (based on work of Luterbach et al.) and IPCC results has been used for studies of vegetation simulation between 1660 and 2600 (publication of first version based on IS92a scenario and limited time period 1950 - 2100: http://www.pbl.nl/images/H5_Part2_van%20CCE_opmaak%28def%29_tcm61-46625.pdf). It's also applicable for other adaptation studies for e.g. road surfaces or building simulation. In Meteonorm 6.1 one scenario (IS92a) and one climate model has been included (Hadley CM3). In the new Meteonorm 7 (coming spring 2011) the model averages of the three above mentioned scenarios of the IPCC AR4 will be included.

Predictions of dispersion and deposition of fallout from nuclear testing using the NOAA-HYSPLIT meteorological model.

PubMed

Moroz, Brian E; Beck, Harold L; Bouville, André; Simon, Steven L

2010-08-01

The NOAA Hybrid Single-Particle Lagrangian Integrated Trajectory Model (HYSPLIT) was evaluated as a research tool to simulate the dispersion and deposition of radioactive fallout from nuclear tests. Model-based estimates of fallout can be valuable for use in the reconstruction of past exposures from nuclear testing, particularly where little historical fallout monitoring data are available. The ability to make reliable predictions about fallout deposition could also have significant importance for nuclear events in the future. We evaluated the accuracy of the HYSPLIT-predicted geographic patterns of deposition by comparing those predictions against known deposition patterns following specific nuclear tests with an emphasis on nuclear weapons tests conducted in the Marshall Islands. We evaluated the ability of the computer code to quantitatively predict the proportion of fallout particles of specific sizes deposited at specific locations as well as their time of transport. In our simulations of fallout from past nuclear tests, historical meteorological data were used from a reanalysis conducted jointly by the National Centers for Environmental Prediction (NCEP) and the National Center for Atmospheric Research (NCAR). We used a systematic approach in testing the HYSPLIT model by simulating the release of a range of particle sizes from a range of altitudes and evaluating the number and location of particles deposited. Our findings suggest that the quantity and quality of meteorological data are the most important factors for accurate fallout predictions and that, when satisfactory meteorological input data are used, HYSPLIT can produce relatively accurate deposition patterns and fallout arrival times. Furthermore, when no other measurement data are available, HYSPLIT can be used to indicate whether or not fallout might have occurred at a given location and provide, at minimum, crude quantitative estimates of the magnitude of the deposited activity. A variety of simulations of the deposition of fallout from atmospheric nuclear tests conducted in the Marshall Islands (mid-Pacific), at the Nevada Test Site (U.S.), and at the Semipalatinsk Nuclear Test Site (Kazakhstan) were performed. The results of the Marshall Islands simulations were used in a limited fashion to support the dose reconstruction described in companion papers within this volume.

Establishment and analysis of a High-Resolution Assimilation Dataset of the water-energy cycle in China

NASA Astrophysics Data System (ADS)

Zhu, X.; Wen, X.; Zheng, Z.

2017-12-01

For better prediction and understanding of land-atmospheric interaction, in-situ observed meteorological data acquired from the China Meteorological Administration (CMA) were assimilated in the Weather Research and Forecasting (WRF) model and the monthly Green Vegetation Coverage (GVF) data, which was calculated using the Normalized Difference Vegetation Index (NDVI) of the Earth Observing System Moderate-Resolution Imaging Spectroradiometer (EOS-MODIS) and Digital Elevation Model (DEM) data of the Shuttle Radar Topography Mission (SRTM) system. Furthermore, the WRF model produced a High-Resolution Assimilation Dataset of the water-energy cycle in China (HRADC). This dataset has a horizontal resolution of 25 km for near surface meteorological data, such as air temperature, humidity, wind vectors and pressure (19 levels); soil temperature and moisture (four levels); surface temperature; downward/upward short/long radiation; 3-h latent heat flux; sensible heat flux; and ground heat flux. In this study, we 1) briefly introduce the cycling 3D-Var assimilation method and 2) compare results of meteorological elements, such as 2 m temperature and precipitation generated by the HRADC with the gridded observation data from CMA, and surface temperature and specific humidity with Global LandData Assimilation System (GLDAS) output data from the National Aeronautics and Space Administration (NASA). We found that the satellite-derived GVF from MODIS increased over southeast China compared with the default model over the whole year. The simulated results of soil temperature, net radiation and surface energy flux from the HRADC are improved compared with the control simulation and are close to GLDAS outputs. The values of net radiation from HRADC are higher than the GLDAS outputs, and the differences in the simulations are large in the east region but are smaller in northwest China and on the Qinghai-Tibet Plateau. The spatial distribution of the sensible heat flux and the ground heat flux from HRADC is consistent with the GLDAS outputs in summer. In general, the simulated results from HRADC are an improvement on the control simulation and can present the characteristics of the spatial and temporal variation of the water-energy cycle in China.

Surface Meteorology and Solar Energy (SSE) Data Release 5.1

NASA Technical Reports Server (NTRS)

Stackhouse, Paul W. (Principal Investigator)

The Surface meteorology and Solar Energy (SSE) data set contains over 200 parameters formulated for assessing and designing renewable energy systems.The SSE data set is formulated from NASA satellite- and reanalysis-derived insolation and meteorological data for the 10-year period July 1983 through June 1993. Results are provided for 1 degree latitude by 1 degree longitude grid cells over the globe. Average daily and monthly measurements for 1195 World Radiation Data Centre ground sites are also available. [Location=GLOBAL] [Temporal_Coverage: Start_Date=1983-07-01; Stop_Date=1993-06-30] [Spatial_Coverage: Southernmost_Latitude=-90; Northernmost_Latitude=90; Westernmost_Longitude=-180; Easternmost_Longitude=180] [Data_Resolution: Latitude_Resolution=1 degree; Longitude_Resolution=1 degree].

Calibration of the ER-2 meteorological measurement system

NASA Technical Reports Server (NTRS)

Bowen, Stuart W.; Chan, K. Roland; Bui, T. Paul

1991-01-01

The Meteorological Measurement System (MMS) on the high altitude ER-2 aircraft was developed specifically for atmospheric research. The MMS provides accurate measurements of pressure, temperature, wind vector, position (longitude, latitude, altitude), pitch, roll, heading, angle of attack, angle of sideslip, true airspeed, aircraft eastward velocity, northward velocity, vertical acceleration, and time, at a sample rate of 5/s. MMS data products are presented in the form of either 5 or 1 Hz time series. The 1 Hz data stream, generally used by ER-2 investigators, is obtained from the 5 Hz data stream by filtering and desampling. The method of measurement of the meteorological parameters is given and the results of their analyses are discussed.

An Urban Diffusion Simulation Model for Carbon Monoxide

ERIC Educational Resources Information Center

Johnson, W. B.; And Others

1973-01-01

A relatively simple Gaussian-type diffusion simulation model for calculating urban carbon (CO) concentrations as a function of local meteorology and the distribution of traffic is described. The model can be used in two ways: in the synoptic mode and in the climatological mode. (Author/BL)

Diagnostic Analysis of Ozone Concentrations Simulated by Two Regional-Scale Air Quality Models

EPA Science Inventory

Since the Community Multiscale Air Quality modeling system (CMAQ) and the Weather Research and Forecasting with Chemistry model (WRF/Chem) use different approaches to simulate the interaction of meteorology and chemistry, this study compares the CMAQ and WRF/Chem air quality simu...

ADVANCED URBANIZED METEOROLOGICAL MODELING AND AIR QUALITY SIMULATIONS WITH CMAQ AT NEIGHBORHOOD SCALES

EPA Science Inventory

We present results from a study testing the new boundary layer parameterization method, the canopy drag approach (DA) which is designed to explicitly simulate the effects of buildings, street and tree canopies on the dynamic, thermodynamic structure and dispersion fields in urban...

Feedbacks between Air Pollution and Weather, Part 1: Effects on Weather

EPA Science Inventory

The meteorological predictions of fully coupled air-quality models running in “feedback” versus “nofeedback” simulations were compared against each other as part of Phase 2 of the Air Quality Model Evaluation International Initiative. The model simulations included a “no-feedback...

Dynamic Evaluation of Long-Term Air Quality Model Simulations Over the Northeastern U.S.

EPA Science Inventory

Dynamic model evaluation assesses a modeling system's ability to reproduce changes in air quality induced by changes in meteorology and/or emissions. In this paper, we illustrate various approaches to dynamic mode evaluation utilizing 18 years of air quality simulations perform...

INDIRECT ESTIMATION OF CONVECTIVE BOUNDARY LAYER STRUCTURE FOR USE IN ROUTINE DISPERSION MODELS

EPA Science Inventory

Dispersion models of the convectively driven atmospheric boundary layer (ABL) often require as input meteorological parameters that are not routinely measured. These parameters usually include (but are not limited to) the surface heat and momentum fluxes, the height of the cappin...

Assessment of ozone variations and meteorological effects in an urban area in the Mediterranean Coast.

PubMed

Dueñas, C; Fernández, M C; Cañete, S; Carretero, J; Liger, E

2002-11-01

Ozone concentrations are valuable indicators of possible health and environmental impacts. However, they are also used to monitor changes and trends in the sources of both ozone and its precursors. For this purpose, the influence of meteorological variables is a confusing factor. This study presents an analysis of a year of ozone concentrations measured in a coastal Spanish city. Firstly, the aim of this study was to perceive the daily, monthly and seasonal variation patterns of ozone concentrations. Diurnal cycles are presented by season and the fit of the data to a normal distribution is tested. In order to assess ozone behaviour under temperate weather conditions, local meteorological variables (wind direction and speed, temperature, relative humidity, pressure and rainfall) were monitored together with ozone concentrations. The main relationships we could observe in these analyses were then used to obtain a regression equation linking diurnal ozone concentrations in summer with meteorological parameters.

An integrated model for the assessment of global water resources Part 2: Applications and assessments

NASA Astrophysics Data System (ADS)

Hanasaki, N.; Kanae, S.; Oki, T.; Masuda, K.; Motoya, K.; Shirakawa, N.; Shen, Y.; Tanaka, K.

2008-07-01

To assess global water resources from the perspective of subannual variation in water availability and water use, an integrated water resources model was developed. In a companion report, we presented the global meteorological forcing input used to drive the model and six modules, namely, the land surface hydrology module, the river routing module, the crop growth module, the reservoir operation module, the environmental flow requirement module, and the anthropogenic withdrawal module. Here, we present the results of the model application and global water resources assessments. First, the timing and volume of simulated agriculture water use were examined because agricultural use composes approximately 85% of total consumptive water withdrawal in the world. The estimated crop calendar showed good agreement with earlier reports for wheat, maize, and rice in major countries of production. In major countries, the error in the planting date was ±1 mo, but there were some exceptional cases. The estimated irrigation water withdrawal also showed fair agreement with country statistics, but tended to be underestimated in countries in the Asian monsoon region. The results indicate the validity of the model and the input meteorological forcing because site-specific parameter tuning was not used in the series of simulations. Finally, global water resources were assessed on a subannual basis using a newly devised index. This index located water-stressed regions that were undetected in earlier studies. These regions, which are indicated by a gap in the subannual distribution of water availability and water use, include the Sahel, the Asian monsoon region, and southern Africa. The simulation results show that the reservoir operations of major reservoirs (>1 km3) and the allocation of environmental flow requirements can alter the population under high water stress by approximately -11% to +5% globally. The integrated model is applicable to assessments of various global environmental projections such as climate change.

Impact of climate change on groundwater resources in Southern Austria

NASA Astrophysics Data System (ADS)

Reszler, C.; Harum, T.; Poltnig, W.; Saccon, P.; Reichl, P.; Ruch, C.; Kopeinig, C.; Freundl, G.; Schlamberger, J.; Zessar, H.; Suette, G.

2012-04-01

Groundwater is the most important source for drinking water in Austria. In some parts of Southern Austria water resources already are very vulnerable to unfavourable climate conditions. This paper summarizes case studies of estimating the impact of climate change on groundwater recharge and groundwater flow in Southern Austria in the frame of the ETC-Alpine Space project ALP-WATER-SCARCE. In several pilot regions a distributed hydrological model was set up to simulate groundwater recharge and groundwater flow for a period of 10 to 30 years. The pilot sites range from mountainous catchments with steep hillslopes to Alpine valleys and flatlands with pore aquifers. In the model period comprehensive land data and meteorological data were used, and the models were calibrated to available stream gauge data. Additional low flow monitoring in the frame of the project also allowed for a more detailed regional analysis in some catchments. The simulations were firstly used to extend runoff and groundwater recharge depths on an annual basis up to 200 years into the past by regression analysis with long time meteorological parameters (HISTALP). The historical view shows that groundwater flow and recharge in most of the pilot regions decreased since the beginning of the 20th century, which is mainly the effect of climate change. Changes of land use are of minor relevance in most of the regions. Second, by the calibrated model scenarios were simulated to quantify the impact of a possible future change in the climatic conditions on water resources. The scenarios were generated by altering the model input by a "Delta-Change", under consideration of the historical development. These scenarios can be interpreted as "what if"-scenarios to quantify the sensitivity of the hydrological systems on these climatic variables. The results are compared with actual and projected water uses as a basis for regional water resources management.

Longitudinal modelling of respiratory symptoms in children

NASA Astrophysics Data System (ADS)

Schlink, Uwe; Fritz, Gisela; Herbarth, Olf; Richter, Matthias

2002-08-01

A panel of 277 children, aged 3-7 years, was used to study the association between air pollution (O3, SO2, NO2, and total suspended particles), meteorological factors (global radiation, maximum daytime temperature, daily averages of vapour pressure and air humidity) and respiratory symptoms. For 759 days the symptoms were recorded in a diary and modelling was based on a modification of the method proposed by Korn and Whittemore (Biometrics 35: 795-798, 1979). This approach (1) comprises an extension using environmental parameters at different time scales, (2) addresses the suitability of using the daily fraction of symptomatic individuals to account for inter-individual interactions and (3) enables the most significant weather effects to be identified. The resulting model consisted of (1) an individual specific intercept that takes account of the population's heterogeneity, (2) the individual's health status the day before, (3) a long-term meteorological effect, which may be either the squared temperature or global radiation in interaction with temperature, (4) the short-term effect of sulfur dioxide, and (5) the short-term effect of an 8-h ozone concentration above 60 µg/m3. Using the estimated parameters as input to a simulation study, we checked the quality of the model and demonstrate that the annual cycle of the prevalence of respiratory symptoms is associated to atmospheric covariates. Individuals suffering from allergy have been identified as a group of a particular susceptibility to ozone. The duration of respiratory symptoms appears to be free of scale and follows an exponential distribution function, which confirms that the symptom record of each individual follows a Poisson point-process. This supports the assumption that not only respiratory diseases, but also respiratory symptoms can be considered an independent measure for the health status of a population sample. Since a point process is described by only one parameter (namely the intensity of the point process), it is appropriate for records of respiratory symptoms to identify only one model which covers both the occurrence and duration of symptoms.

DIFFUSION IN THE VICINITY OF STANDARD-DESIGN NUCLEAR POWER PLANTS-I. WIND-TUNNEL EVALUATION OF DIFFUSIVE CHARACTERISTICS OF A SIMULATED SUBURBAN NEUTRAL ATMOSPHERIC BOUNDARY LAYER

EPA Science Inventory

A large meteorological wind tunnel was used to simulate a suburban atmospheric boundary layer. The model-prototype scale was 1:300 and the roughness length was approximately 1.0 m full scale. The model boundary layer simulated full scale dispersion from ground-level and elevated ...

Evaluation and comparison of different RCMs simulations of the Mediterranean climate: a view on the impact of model resolution and Mediterranean sea coupling.

NASA Astrophysics Data System (ADS)

Panthou, Gérémy; Vrac, Mathieu; Drobinski, Philippe; Bastin, Sophie; Somot, Samuel; Li, Laurent

2015-04-01

As regularly stated by numerous authors, the Mediterranean climate is considered as one major climate 'hot spot'. At least, three reasons may explain this statement. First, this region is known for being regularly affected by extreme hydro-meteorological events (heavy precipitation and flash-floods during the autumn season; droughts and heat waves during spring and summer). Second, the vulnerability of populations in regard of these extreme events is expected to increase during the XXIst century (at least due to the projected population growth in this region). At last, Global Circulation Models project that this regional climate will be highly sensitive to climate change. Moreover, global warming is expected to intensify the hydrological cycle and thus to increase the frequency of extreme hydro-meteorological events. In order to propose adaptation strategies, the robust estimation of the future evolution of the Mediterranean climate and the associated extreme hydro-meteorological events (in terms of intensity/frequency) is of great relevance. However, these projections are characterized by large uncertainties. Many components of the simulation chain can explain these large uncertainties : (i) uncertainties concerning the emission scenario; (ii) climate model simulations suffer of parametrization errors and uncertainties concerning the initial state of the climate; and (iii) the additional uncertainties given by the (dynamical or statistical) downscaling techniques and the impact model. Narrowing (as fine as possible) these uncertainties is a major challenge of the actual climate research. One way for that is to reduce the uncertainties associated with each component. In this study, we are interested in evaluating the potential improvement of : (i) coupled RCM simulations (with the Mediterranean Sea) in comparison with atmosphere only (stand-alone) RCM simulations and (ii) RCM simulations at a finer resolution in comparison with larger resolution. For that, three different RCMs (WRF, ALADIN, LMDZ4) were run, forced by ERA-Interim reanalyses, within the MED-CORDEX experiment. For each RCM, different versions (coupled/stand-alone, high/low resolution) were realized. A large set of scores was developed and applied in order to evaluate the performances of these different RCMs simulations. These scores were applied for three variables (daily precipitation amount, mean daily air temperature and the dry spell lengths). A particular attention was given to the RCM capability to reproduce the seasonal and spatial pattern of extreme statistics. Results show that the differences between coupled and stand-alone RCMs are localized very near the Mediterranean sea and that the model resolution has a slight impact on the scores obtained. Globally, the main differences between the RCM simulations come from the RCM used. Keywords: Mediterranean climate, extreme hydro-meteorological events, RCM simulations, evaluation of climate simulations

Implications of the methodological choices for hydrologic portrayals of climate change over the contiguous United States: Statistically downscaled forcing data and hydrologic models

USGS Publications Warehouse

Mizukami, Naoki; Clark, Martyn P.; Gutmann, Ethan D.; Mendoza, Pablo A.; Newman, Andrew J.; Nijssen, Bart; Livneh, Ben; Hay, Lauren E.; Arnold, Jeffrey R.; Brekke, Levi D.

2016-01-01

Continental-domain assessments of climate change impacts on water resources typically rely on statistically downscaled climate model outputs to force hydrologic models at a finer spatial resolution. This study examines the effects of four statistical downscaling methods [bias-corrected constructed analog (BCCA), bias-corrected spatial disaggregation applied at daily (BCSDd) and monthly scales (BCSDm), and asynchronous regression (AR)] on retrospective hydrologic simulations using three hydrologic models with their default parameters (the Community Land Model, version 4.0; the Variable Infiltration Capacity model, version 4.1.2; and the Precipitation–Runoff Modeling System, version 3.0.4) over the contiguous United States (CONUS). Biases of hydrologic simulations forced by statistically downscaled climate data relative to the simulation with observation-based gridded data are presented. Each statistical downscaling method produces different meteorological portrayals including precipitation amount, wet-day frequency, and the energy input (i.e., shortwave radiation), and their interplay affects estimations of precipitation partitioning between evapotranspiration and runoff, extreme runoff, and hydrologic states (i.e., snow and soil moisture). The analyses show that BCCA underestimates annual precipitation by as much as −250 mm, leading to unreasonable hydrologic portrayals over the CONUS for all models. Although the other three statistical downscaling methods produce a comparable precipitation bias ranging from −10 to 8 mm across the CONUS, BCSDd severely overestimates the wet-day fraction by up to 0.25, leading to different precipitation partitioning compared to the simulations with other downscaled data. Overall, the choice of downscaling method contributes to less spread in runoff estimates (by a factor of 1.5–3) than the choice of hydrologic model with use of the default parameters if BCCA is excluded.

Comparison of model performance and simulated water balance using NASIM and SWAT for the Wupper River Basin, Germany

NASA Astrophysics Data System (ADS)

Lorza, Paula; Nottebohm, Martin; Scheibel, Marc; aus der Beek, Tim

2017-04-01

Under the framework of the Horizon 2020 project BINGO (Bringing INnovation to onGOing water management), climate change impacts on the water cycle in the Wupper catchment area are being studied. With this purpose, a set of hydrological models in NASIM and SWAT have been set up, calibrated, and validated for past conditions using available data. NASIM is a physically-based, lumped, hydrological model based on the water balance equation. For the upper part of the Dhünn catchment area - Wupper River's main tributary - a SWAT model was also implemented. Observed and simulated discharge by NASIM and SWAT for the drainage area upstream of Neumühle hydrometric station (close to Große Dhünn reservoir's inlet) are compared. Comparison of simulated water balance for several hydrological years between the two models is also carried out. While NASIM offers high level of detail for modelling of complex urban areas and the possibility of entering precipitation time series at fine temporal resolution (e.g. minutely data), SWAT enables to study long-term impacts offering a huge variety of input and output variables including different soil properties, vegetation and land management practices. Beside runoff, also sediment and nutrient transport can be simulated. For most calculations, SWAT operates on a daily time step. The objective of this and future work is to determine catchment responses on different meteorological events and to study parameter sensitivity of stationary inputs such as soil parameters, vegetation or land use. Model performance is assessed with different statistical metrics (relative volume error, coefficient of determination, and Nash-Sutcliffe Efficiency).

Exploring the impact of forcing error characteristics on physically based snow simulations within a global sensitivity analysis framework

NASA Astrophysics Data System (ADS)

Raleigh, M. S.; Lundquist, J. D.; Clark, M. P.

2015-07-01

Physically based models provide insights into key hydrologic processes but are associated with uncertainties due to deficiencies in forcing data, model parameters, and model structure. Forcing uncertainty is enhanced in snow-affected catchments, where weather stations are scarce and prone to measurement errors, and meteorological variables exhibit high variability. Hence, there is limited understanding of how forcing error characteristics affect simulations of cold region hydrology and which error characteristics are most important. Here we employ global sensitivity analysis to explore how (1) different error types (i.e., bias, random errors), (2) different error probability distributions, and (3) different error magnitudes influence physically based simulations of four snow variables (snow water equivalent, ablation rates, snow disappearance, and sublimation). We use the Sobol' global sensitivity analysis, which is typically used for model parameters but adapted here for testing model sensitivity to coexisting errors in all forcings. We quantify the Utah Energy Balance model's sensitivity to forcing errors with 1 840 000 Monte Carlo simulations across four sites and five different scenarios. Model outputs were (1) consistently more sensitive to forcing biases than random errors, (2) generally less sensitive to forcing error distributions, and (3) critically sensitive to different forcings depending on the relative magnitude of errors. For typical error magnitudes found in areas with drifting snow, precipitation bias was the most important factor for snow water equivalent, ablation rates, and snow disappearance timing, but other forcings had a more dominant impact when precipitation uncertainty was due solely to gauge undercatch. Additionally, the relative importance of forcing errors depended on the model output of interest. Sensitivity analysis can reveal which forcing error characteristics matter most for hydrologic modeling.

Sensitivity Analysis of Delft3d Simulations at Duck, NC, USA

NASA Astrophysics Data System (ADS)

Penko, A.; Boggs, S.; Palmsten, M.

2017-12-01

Our objective is to set up and test Delft3D, a high-resolution coupled wave and circulation model, to provide real-time nowcasts of hydrodynamics at Duck, NC, USA. Here, we test the sensitivity of the model to various parameters and boundary conditions. In order to validate the model simulations we compared the results to observational data. Duck, NC was chosen as our test site due to the extensive array of observational oceanographic, bathymetric, and meteorological data collected by the Army Corps of Engineers Field Research Facility (FRF). Observations were recorded with Acoustic Wave and Current meters (AWAC) at 6-m and 11-m depths as well as a 17-m depth Waverider buoy. The model is set up with an outer and inner nested domain. The outer grid extends 12-km in the along-shore and 3.5-km in the cross-shore with a 50-m resolution and a maximum depth of 17-m. Spectral wave measurements from the 17-m Waverider buoy drove Delft3D-WAVE in the outer grid. We compared the results of five outer grid simulations to wave and current observations collected at the FRF. The model simulations are then compared to the wave and current measurements collected at the 6-m and 11-m AWACs. To determine the best parameters and boundary conditions for the model set up at Duck, we calculated the root mean square error (RMSE) between the simulation results and the observations. Several conclusions were made: 1) The addition of astronomic tides have a significant effect on the circulation magnitude and direction, 2) incorporating an updated bathymetry in the bottom boundary condition has a small effect in shallower (<8-m) depths, 3) decreasing the wave bed friction by 50% did not affect the wave predictions and 4) the accuracy of the simulated wave heights improved as wind and wave forcing at the lateral boundaries were included.

Scalability of grid- and subbasin-based land surface modeling approaches for hydrologic simulations

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

Tesfa, Teklu K.; Ruby Leung, L.; Huang, Maoyi

2014-03-27

This paper investigates the relative merits of grid- and subbasin-based land surface modeling approaches for hydrologic simulations, with a focus on their scalability (i.e., abilities to perform consistently across a range of spatial resolutions) in simulating runoff generation. Simulations produced by the grid- and subbasin-based configurations of the Community Land Model (CLM) are compared at four spatial resolutions (0.125o, 0.25o, 0.5o and 1o) over the topographically diverse region of the U.S. Pacific Northwest. Using the 0.125o resolution simulation as the “reference”, statistical skill metrics are calculated and compared across simulations at 0.25o, 0.5o and 1o spatial resolutions of each modelingmore » approach at basin and topographic region levels. Results suggest significant scalability advantage for the subbasin-based approach compared to the grid-based approach for runoff generation. Basin level annual average relative errors of surface runoff at 0.25o, 0.5o, and 1o compared to 0.125o are 3%, 4%, and 6% for the subbasin-based configuration and 4%, 7%, and 11% for the grid-based configuration, respectively. The scalability advantages of the subbasin-based approach are more pronounced during winter/spring and over mountainous regions. The source of runoff scalability is found to be related to the scalability of major meteorological and land surface parameters of runoff generation. More specifically, the subbasin-based approach is more consistent across spatial scales than the grid-based approach in snowfall/rainfall partitioning, which is related to air temperature and surface elevation. Scalability of a topographic parameter used in the runoff parameterization also contributes to improved scalability of the rain driven saturated surface runoff component, particularly during winter. Hence this study demonstrates the importance of spatial structure for multi-scale modeling of hydrological processes, with implications to surface heat fluxes in coupled land-atmosphere modeling.« less

Modeling of meteorology, chemistry and aerosol for the 2017 Utah Winter Fine Particle Study

NASA Astrophysics Data System (ADS)

McKeen, S. A.; Angevine, W. M.; McDonald, B.; Ahmadov, R.; Franchin, A.; Middlebrook, A. M.; Fibiger, D. L.; McDuffie, E. E.; Womack, C.; Brown, S. S.; Moravek, A.; Murphy, J. G.; Trainer, M.

2017-12-01

The Utah Winter Fine Particle Study (UWFPS-17) field project took place during January and February of 2017 within the populated region of the Great Salt Lake, Utah. The study focused on understanding the meteorology and chemistry associated with high particulate matter (PM) levels often observed near Salt Lake City during stable wintertime conditions. Detailed composition and meteorological observations were taken from the NOAA Twin-Otter aircraft and several surface sites during the study period, and extremely high aerosol conditions were encountered for two cold-pool episodes occurring in the last 2 weeks of January. A clear understanding of the photochemical and aerosol processes leading to these high PM events is still lacking. Here we present high spatiotemporal resolution simulations of meteorology, PM and chemistry over Utah from January 13 to February 1, 2017 using the WRF/Chem photochemical model. Correctly characterizing the meteorology is difficult due to the complex terrain and shallow inversion layers. We discuss the approach and limitations of the simulated meteorology, and evaluate low-level pollutant mixing using vertical profiles from missed airport approaches by the NOAA Twin-Otter performed routinely during each flight. Full photochemical simulations are calculated using NOx, ammonia and VOC emissions from the U.S. EPA NEI-2011 emissions inventory. Comparisons of the observed vertical column amounts of NOx, ammonia, aerosol nitrate and ammonium with model results shows the inventory estimates for ammonia emissions are low by a factor of four and NOx emissions are low by nearly a factor of two. The partitioning of both nitrate and NH3 between gas and particle phase depends strongly on the NH3 and NOx emissions to the model and calculated NOx to nitrate conversion rates. These rates are underestimated by gas-phase chemistry alone, even though surface snow albedo increases photolysis rates by nearly a factor of two. Several additional conversion mechanisms are added and evaluated in the model, including: heterogeneous nitrate to aerosol formation, catalytic conversion of NO2 to HONO and HNO3 at the snow surface, and direct HONO emissions from vehicles. Each mechanism contributes to the model matching observed NOx and total nitrate levels within 25% for median statistics over the study period.

Towards a Comprehensive Dynamic-chemistry Assimilation for Eos-Chem: Plans and Status in NASA's Data Assimilation Office

NASA Technical Reports Server (NTRS)

Pawson, Steven; Lin, Shian-Jiann; Rood, Richard B.; Stajner, Ivanka; Nebuda, Sharon; Nielsen, J. Eric; Douglass, Anne R.

2000-01-01

In order to support the EOS-Chem project, a comprehensive assimilation package for the coupled chemical-dynamical system is being developed by the Data Assimilation Office at NASA GSFC. This involves development of a coupled chemistry/meteorology model and of data assimilation techniques for trace species and meteorology. The model is being developed using the flux-form semi-Lagrangian dynamical core of Lin and Rood, the physical parameterizations from the NCAR Community Climate Model, and atmospheric chemistry modules from the Atmospheric Chemistry and Dynamics branch at NASA GSFC. To date the following results have been obtained: (i) multi-annual simulations with the dynamics-radiation model show the credibility of the package for atmospheric simulations; (ii) initial simulations including a limited number of middle atmospheric trace gases reveal the realistic nature of transport mechanisms, although there is still a need for some improvements. Samples of these results will be shown. A meteorological assimilation system is currently being constructed using the model; this will form the basis for the proposed meteorological/chemical assimilation package. The latter part of the presentation will focus on areas targeted for development in the near and far terms, with the objective of Providing a comprehensive assimilation package for the EOS-Chem science experiment. The first stage will target ozone assimilation. The plans also encompass a reanalysis (ReSTS) for the 1991-1995 period, which includes the Mt. Pinatubo eruption and the time when a large number of UARS observations were available. One of the most challenging aspects of future developments will be to couple theoretical advances in tracer assimilation with the practical considerations of a real environment and eventually a near-real-time assimilation system.

Winter ambient training conditions are associated with increased bronchial hyperreactivity and with shifts in serum innate immunity proteins in young competitive speed skaters.

PubMed

Kurowski, Marcin; Jurczyk, Janusz; Moskwa, Sylwia; Jarzębska, Marzanna; Krysztofiak, Hubert; Kowalski, Marek L

2018-01-01

Regular training modulates airway inflammation and modifies susceptibility to respiratory infections. The impact of exercise and ambient conditions on airway hyperreactivity and innate immunity has not been well studied. We aimed to assess exercise-related symptoms, lung function, airway hyperresponsiveness and innate immunity proteins in relation to meteorological conditions and exercise load in competitive athletes. Thirty-six speed skaters were assessed during winter (WTP) and summer (STP) periods. The control group comprised 22 non-exercising subjects. An allergy questionnaire for athletes (AQUA) and IPAQ (International Physical Activity Questionnaire) were used to assess symptoms and exercise. Meteorological parameters were acquired from World Meteorological Organization resources. Serum innate immunity proteins were measured by ELISA. Exercise-associated respiratory symptoms were reported by 79.4% of skaters. Despite similar exercise load and lung parameters during both periods, positive methacholine challenge was more frequent during winter ( p = 0.04). Heat shock protein HSPA1 and IL-1RA were significantly decreased during STP compared to WTP and controls. During WTP, IL-1RA was elevated in skaters reporting exercise-induced symptoms ( p = 0.007). sCD14 was elevated in athletes versus controls in both periods ( p < 0.05). HSPA1 was significantly higher in WTP compared to STP irrespective of presence of respiratory tract infections (RTIs). IL-1RA in WTP was elevated versus STP ( p = 0.004) only in RTI-negative athletes. Serum IL-1RA negatively correlated with most meteorological parameters during WTP. Ambient training conditions, but not training load, influence bronchial hyperreactivity and the innate immune response in competitive athletes assessed during winter. The protective effect of regular exercise against respiratory infections is associated with a shift in serum innate immunity proteins.

A comparison of selected models for estimating cable icing

NASA Astrophysics Data System (ADS)

McComber, Pierre; Druez, Jacques; Laflamme, Jean

In many cold climate countries, it is becoming increasingly important to monitor transmission line icing. Indeed, by knowing in advance of localized danger for icing overloads, electric utilities can take measures in time to prevent generalized failure of the power transmission network. Recently in Canada, a study was made to compare the estimation of a few icing models working from meteorological data in estimating ice loads for freezing rain events. The models tested were using only standard meteorological parameters, i.e. wind speed and direction, temperature and precipitation rate. This study has shown that standard meteorological parameters can only achieve very limited accuracy, especially for longer icing events. However, with the help of an additional instrument monitoring the icing rate intensity, a significant improvement in model prediction might be achieved. The icing rate meter (IRM) which counts icing and de-icing cycles per unit time on a standard probe can be used to estimate the icing intensity. A cable icing estimation is then made by taking into consideration the accretion size, temperature, wind speed and direction, and precipitation rate. In this paper, a comparison is made between the predictions of two previously tested models (one obtained and the other reconstructed from their description in the public literature) and of a model based on the icing rate meter readings. The models are tested against nineteen events recorded on an icing test line at Mt. Valin, Canada, during the winter season 1991-1992. These events are mostly rime resulting from in-cloud icing. However, freezing rain and wet snow events were also recorded. Results indicate that a significant improvement in the estimation is attained by using the icing rate meter data together with the other standard meteorological parameters.

Characteristics of Fine Particles in an Urban Atmosphere-Relationships with Meteorological Parameters and Trace Gases.

PubMed

Zhang, Tianhao; Zhu, Zhongmin; Gong, Wei; Xiang, Hao; Fang, Ruimin

2016-08-10

Atmospheric fine particles (diameter < 1 μm) attract a growing global health concern and have increased in urban areas that have a strong link to nucleation, traffic emissions, and industrial emissions. To reveal the characteristics of fine particles in an industrial city of a developing country, two-year measurements of particle number size distribution (15.1 nm-661 nm), meteorological parameters, and trace gases were made in the city of Wuhan located in central China from June 2012 to May 2014. The annual average particle number concentrations in the nucleation mode (15.1 nm-30 nm), Aitken mode (30 nm-100 nm), and accumulation mode (100 nm-661 nm) reached 4923 cm(-3), 12193 cm(-3) and 4801 cm(-3), respectively. Based on Pearson coefficients between particle number concentrations and meteorological parameters, precipitation and temperature both had significantly negative relationships with particle number concentrations, whereas atmospheric pressure was positively correlated with the particle number concentrations. The diurnal variation of number concentration in nucleation mode particles correlated closely with photochemical processes in all four seasons. At the same time, distinct growth of particles from nucleation mode to Aitken mode was only found in spring, summer, and autumn. The two peaks of Aitken mode and accumulation mode particles in morning and evening corresponded obviously to traffic exhaust emissions peaks. A phenomenon of "repeated, short-lived" nucleation events have been created to explain the durability of high particle concentrations, which was instigated by exogenous pollutants, during winter in a case analysis of Wuhan. Measurements of hourly trace gases and segmental meteorological factors were applied as proxies for complex chemical reactions and dense industrial activities. The results of this study offer reasonable estimations of particle impacts and provide references for emissions control strategies in industrial cities of developing countries.

Developing of the database of meteorological and radiation fields for Moscow region (urban reanalysis) for 1981-2014 period with high spatial and temporal resolution. Strategy and first results.

NASA Astrophysics Data System (ADS)

Konstantinov, Pavel; Varentsov, Mikhail; Platonov, Vladimir; Samsonov, Timofey; Zhdanova, Ekaterina; Chubarova, Natalia

2017-04-01

The main goal of this investigation is to develop a kind of "urban reanalysis" - the database of meteorological and radiation fields under Moscow megalopolis for period 1981-2014 with high spatial resolution. Main meteorological fields for Moscow region are reproduced with COSMO_CLM regional model (including urban parameters) with horizontal resolution 1x1 km. Time resolution of output fields is 1 hour. For radiation fields is quite useful to calculate SVF (Sky View Factor) for obtaining losses of UV radiation in complex urban conditions. Usually, the raster-based SVF analysis the shadow-casting algorithm proposed by Richens (1997) is popular (see Ratti and Richens 2004, Gal et al. 2008, for example). SVF image is obtained by combining shadow images obtained from different directions. An alternative is to use raster-based SVF calculation similar to vector approach using digital elevation model of urban relief. Output radiation field includes UV-radiation with horizontal resolution 1x1 km This study was financially supported by the Russian Foundation for Basic Research within the framework of the scientific project no. 15-35-21129 _mol_a_ved and project no 15-35-70006 mol_a_mos References: 1. Gal, T., Lindberg, F., and Unger, J., 2008. Computing continuous sky view factors using 3D urban raster and vector databases: comparison and application to urban climate. Theoretical and applied climatology, 95 (1-2), 111-123. 2. Richens, P., 1997. Image processing for urban scale environmental modelling. In: J.D. Spitler and J.L.M. Hensen, eds. th Intemational IBPSA Conference Building Simulation, Prague. 3. Ratti, C. and Richens, P., 2004. Raster analysis of urban form. Environment and Planning B: Planning and Design, 31 (2), 297-309.

Mars Pathfinder meteorological observations on the basis of results of an atmospheric global circulation model

NASA Technical Reports Server (NTRS)

Forget, Francois; Hourdin, F.; Talagrand, O.

1994-01-01

The Mars Pathfinder Meteorological Package (ASI/MET) will measure the local pressure, temperature, and winds at its future landing site, somewhere between the latitudes 0 deg N and 30 deg N. Comparable measurements have already been obtained at the surface of Mars by the Viking Landers at 22 deg N (VL1) and 48 deg N (VL2), providing much useful information on the martian atmosphere. In particular the pressure measurements contain very instructive information on the global atmospheric circulation. At the Laboratoire de Meteorologie Dynamique (LMD), we have analyzed and simulated these measurements with a martian atmospheric global circulation model (GCM), which was the first to simulate the martian atmospheric circulation over more than 1 year. The model is able to reproduce rather accurately many observed features of the martian atmosphere, including the long- and short-period oscillations of the surface pressure observed by the Viking landers. From a meteorological point of view, we think that a landing site located near or at the equator would be an interesting choice.

Influence of ozone and meteorological parameters on levels of polycyclic aromatic hydrocarbons in the air

NASA Astrophysics Data System (ADS)

Pehnec, Gordana; Jakovljević, Ivana; Šišović, Anica; Bešlić, Ivan; Vađić, Vladimira

2016-04-01

Concentrations of ten polycyclic aromatic hydrocarbons (PAHs) in the PM10 particle fraction were measured together with ozone and meteorological parameters at an urban site (Zagreb, Croatia) over a one-year period. Data were subjected to regression analysis in order to determine the relationship between the measured pollutants and selected meteorological variables. All of the PAHs showed seasonal variations with high concentrations in winter and autumn and very low concentrations during summer and spring. All of the ten PAHs concentrations also correlated well with each other. A statistically significant negative correlation was found between the concentrations of PAHs and ozone concentrations and concentrations of PAHs and temperature, as well as a positive correlation between concentrations of PAHs and PM10 mass concentration and relative humidity. Multiple regression analysis showed that concentrations of PM10 and ozone, temperature, relative humidity and pressure accounted for 43-70% of PAHs variability. Concentrations of PM10 and temperature were significant variables for all of the measured PAH's concentrations in all seasons. Ozone concentrations were significant for only some of the PAHs, particularly 6-ring PAHs.

Additional applications and related topics, chapter 4, part B

NASA Technical Reports Server (NTRS)

1975-01-01

Satellite mounted microwave instruments and their use to measure surface pressure are investigated. Data cover instrument accuracy, atmospheric transmission, and meteorological parameter determinations.

Trans-Pacific transport and evolution of aerosols and trace gases from Asia during the INTEX-B field campaign

NASA Astrophysics Data System (ADS)

Adhikary, B.; Carmichael, G. R.; Kulkarni, S.; Wei, C.; Tang, Y.; Dallura, A.; Mena-Carrasco, M.; Streets, D. G.; Zhang, Q.; Pierce, R. B.; Al-Saadi, J. A.; Emmons, L. K.; Pfister, G. G.; Avery, M. A.; Barrick, J. D.; Blake, D. R.; Brune, W. H.; Cohen, R. C.; Dibb, J. E.; Fried, A.; Heikes, B. G.; Huey, L. G.; O'Sullivan, D. W.; Sachse, G. W.; Shetter, R. E.; Singh, H. B.; Campos, T. L.; Cantrell, C. A.; Flocke, F. M.; Dunlea, E. J.; Jimenez, J. L.; Weinheimer, A. J.; Crounse, J. D.; Wennberg, P. O.; Schauer, J. J.; Stone, E. A.; Jaffe, D. A.; Reidmiller, D. R.

2009-08-01

The Sulfur Transport and dEposition Model (STEM) developed at the University of Iowa is applied to the analysis of observations obtained during the Intercontinental Chemical Transport Experiment-Phase B (INTEX-B), conducted over the Pacific Ocean during the 2006 North American spring season. This paper reports on the model performance of meteorological parameters, trace gases, aerosols and photolysis rate (J-values) predictions with the NASA DC-8 and NSF/NCAR C-130 airborne measurements along with observations from three surface sites Mt. Bachelor, Trinidad Head and Kathmandu, Nepal. In general the model shows appreciable skill in predicting many of the important aspects of the observed distributions. The major meteorological parameters driving long range transport are accurately predicted by the WRF simulations used in this study. Furthermore, the STEM model predicts aerosols and trace gases concentrations within a standard deviation of most of the observed mean values. The results also point towards areas where model improvements are needed; e.g., the STEM model underestimates CO (15% for the DC8 and 6% for the C-130), whereas it overpredicts PAN (by a factor of two for both aircraft). The errors in the model calculations are attributed to uncertainty in emissions estimates and uncertainty in the top and lateral boundary conditions. Results from a series of sensitivity simulations examining the impact of the growth of emissions in Asia from 2000 to 2006, the importance of biomass burning, the effect of using boundary conditions from different global models, and the role of heterogeneous chemistry on the predictions are also presented. The impacts of heterogeneous reactions at specific times during dust transport episodes can be significant, and in the presence of dust both sulfate and nitrate aerosol production is increased and gas phase nitric acid levels are reduced appreciably (~50%). The aging of the air masses during the long range transport over the Pacific and the impact of various sources (source regions as well as energy and biomass burning) on targeted observations are analyzed using back-trajectories and tagged CO-tracer analysis.

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

NASA Technical Reports Server (NTRS)

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

2012-01-01

The Short-term Prediction Research and Transition Center (SPoRT) is a collaborative partnership between NASA and operational forecasting entities, including a number of National Weather Service offices. SPoRT transitions real-time NASA products and capabilities to its partners to address specific operational forecast challenges. One challenge that forecasters face is applying convection-allowing numerical models to predict mesoscale convective weather. In order to address this specific forecast challenge, SPoRT produces real-time mesoscale model forecasts using the Weather Research and Forecasting (WRF) model that includes unique NASA products and capabilities. Currently, the SPoRT configuration of the WRF model (SPoRT-WRF) incorporates the 4-km Land Information System (LIS) land surface data, 1-km SPoRT sea surface temperature analysis and 1-km Moderate resolution Imaging Spectroradiometer (MODIS) greenness vegetation fraction (GVF) analysis, and retrieved thermodynamic profiles from the Atmospheric Infrared Sounder (AIRS). The LIS, SST, and GVF data are all integrated into the SPoRT-WRF through adjustments to the initial and boundary conditions, and the AIRS data are assimilated into a 9-hour SPoRT WRF forecast each day at 0900 UTC. This study dissects the overall impact of the NASA datasets and the individual surface and atmospheric component datasets on daily mesoscale forecasts. A case study covering the super tornado outbreak across the Ce ntral and Southeastern United States during 25-27 April 2011 is examined. Three different forecasts are analyzed including the SPoRT-WRF (NASA surface and atmospheric data), the SPoRT WRF without AIRS (NASA surface data only), and the operational National Severe Storms Laboratory (NSSL) WRF (control with no NASA data). The forecasts are compared qualitatively by examining simulated versus observed radar reflectivity. Differences between the simulated reflectivity are further investigated using convective parameters along with model soundings to determine the impacts of the various NASA datasets. Additionally, quantitative evaluation of select meteorological parameters is performed using the Meteorological Evaluation Tools model verification package to compare forecasts to in situ surface and upper air observations.

Construction of a Distributed-network Digital Watershed Management System with B/S Techniques

NASA Astrophysics Data System (ADS)

Zhang, W. C.; Liu, Y. M.; Fang, J.

2017-07-01

Integrated watershed assessment tools for supporting land management and hydrologic research are becoming established tools in both basic and applied research. The core of these tools are mainly spatially distributed hydrologic models as they can provide a mechanism for investigating interactions among climate, topography, vegetation, and soil. However, the extensive data requirements and the difficult task of building input parameter files for driving these distributed models, have long been an obstacle to the timely and cost-effective use of such complex models by watershed managers and policy-makers. Recently, a web based geographic information system (GIS) tool to facilitate this process has been developed for a large watersheds of Jinghe and Weihe catchments located in the loess plateau of the Huanghe River basin in north-western China. A web-based GIS provides the framework within which spatially distributed data are collected and used to prepare model input files of these two watersheds and evaluate model results as well as to provide the various clients for watershed information inquiring, visualizing and assessment analysis. This Web-based Automated Geospatial Watershed Assessment GIS (WAGWA-GIS) tool uses widely available standardized spatial datasets that can be obtained via the internet oracle databank designed with association of Map Guide platform to develop input parameter files for online simulation at different spatial and temporal scales with Xing’anjiang and TOPMODEL that integrated with web-based digital watershed. WAGWA-GIS automates the process of transforming both digital data including remote sensing data, DEM, Land use/cover, soil digital maps and meteorological and hydrological station geo-location digital maps and text files containing meteorological and hydrological data obtained from stations of the watershed into hydrological models for online simulation and geo-spatial analysis and provides a visualization tool to help the user interpret results. The utility of WAGWA-GIS in jointing hydrologic and ecological investigations has been demonstrated on such diverse landscapes as Jinhe and Weihe watersheds, and will be extended to be utilized in the other watersheds in China step by step in coming years

Regional Air Quality forecAST (RAQAST) Over the U.S

NASA Astrophysics Data System (ADS)

Yoshida, Y.; Choi, Y.; Zeng, T.; Wang, Y.

2005-12-01

A regional chemistry and transport modeling system is used to provide 48-hour forecast of the concentrations of ozone and its precursors over the United States. Meteorological forecast is conducted using the NCAR/Penn State MM5 model. The regional chemistry and transport model simulates the sources, transport, chemistry, and deposition of 24 chemical tracers. The lateral and upper boundary conditions of trace gas concentrations are specified using the monthly mean output from the global GEOS-CHEM model. The initial and boundary conditions for meteorological fields are taken from the NOAA AVN forecast. The forecast has been operational since August, 2003. Model simulations are evaluated using surface, aircraft, and satellite measurements in the A'hindcast' mode. The next step is an automated forecast evaluation system.

Calibrating a Soil-Vegetation-Atmosphere system with a genetical algorithm

NASA Astrophysics Data System (ADS)

Schneider, S.; Jacques, D.; Mallants, D.

2009-04-01

Accuracy of model prediction is well known for being very sensitive to the quality of the calibration of the model. It is also known that quantifying soil hydraulic parameters in a Soil-Vegetation-Atmosphere (SVA) system is a highly non-linear parameter estimation problem, and that robust methods are needed to avoid the optimization process to lead to non-optimal parameters. Evolutionary algorithms and specifically genetic algorithms (GAs) are very well suited for those complex parameter optimization problems. The SVA system in this study concerns a pine stand on a heterogeneous sandy soil (podzol) in the north of Belgium (Campine region). Throughfall and other meteorological data and water contents at different soil depths have been recorded during one year at a daily time step. The water table level, which is varying between 95 and 170 cm, has been recorded with a frequency of 0.5 hours. Based on the profile description, four soil layers have been distinguished in the podzol and used for the numerical simulation with the hydrus1D model (Simunek and al., 2005). For the inversion procedure the MYGA program (Yedder, 2002), which is an elitism GA, was used. Optimization was based on the water content measurements realized at the depths of 10, 20, 40, 50, 60, 70, 90, 110, and 120 cm to estimate parameters describing the unsaturated hydraulic soil properties of the different soil layers. Comparison between the modeled and measured water contents shows a good similarity during the simulated year. Impacts of short and intensive events (rainfall) on the water content of the soil are also well reproduced. Errors on predictions are on average equal to 5%, which is considered as a good result. A. Ben Haj Yedder. Numerical optimization and optimal control : (molecular chemistry applications). PhD thesis, Ecole Nationale des Ponts et Chaussées, 2002. Šimůnek, J., M. Th. van Genuchten, and M. Šejna, The HYDRUS-1D software package for simulating the one-dimensional movement of water, heat, and multiple solutes in variably saturated media. Version 3.0, HYDRUS Software Series 1, Department of Environmental Sciences, University of California Riverside, Riverside, CA, 270 pp., 2005.

Development of an aerosol microphysical module: Aerosol Two-dimensional bin module for foRmation and Aging Simulation (ATRAS)

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

Matsui, H.; Koike, Makoto; Kondo, Yutaka

2014-09-30

Number concentrations, size distributions, and mixing states of aerosols are essential parameters for accurate estimation of aerosol direct and indirect effects. In this study, we developed an aerosol module, designated Aerosol Two-dimensional bin module for foRmation and Aging Simulation (ATRAS), that can represent these parameters explicitly by considering new particle formation (NPF), black carbon (BC) aging, and secondary organic aerosol (SOA) processes. A two-dimensional bin representation is used for particles with dry diameters from 40 nm to 10 µm to resolve both aerosol size (12 bins) and BC mixing state (10 bins) for a total of 120 bins. The particlesmore » with diameters from 1 to 40 nm are resolved using an additional 8 size bins to calculate NPF. The ATRAS module was implemented in the WRF-chem model and applied to examine the sensitivity of simulated mass, number, size distributions, and optical and radiative parameters of aerosols to NPF, BC aging and SOA processes over East Asia during the spring of 2009. BC absorption enhancement by coating materials was about 50% over East Asia during the spring, and the contribution of SOA processes to the absorption enhancement was estimated to be 10 – 20% over northern East Asia and 20 – 35% over southern East Asia. A clear north-south contrast was also found between the impacts of NPF and SOA processes on cloud condensation nuclei (CCN) concentrations: NPF increased CCN concentrations at higher supersaturations (smaller particles) over northern East Asia, whereas SOA increased CCN concentrations at lower supersaturations (larger particles) over southern East Asia. Application of ATRAS to East Asia also showed that the impact of each process on each optical and radiative parameter depended strongly on the process and the parameter in question. The module can be used in the future as a benchmark model to evaluate the accuracy of simpler aerosol models and examine interactions between NPF, BC aging, and SOA processes under different meteorological conditions and emissions.« less

In situ sensors for measurements in the global trosposphere

NASA Technical Reports Server (NTRS)

Saeger, M. L.; Eaton, W. C.; Wright, R. S.; White, J. H.; Tommerdahl, J. B.

1981-01-01

Current techniques available for the in situ measurement of ambient trace gas species, particulate composition, and particulate size distribution are reviewed. The operational specifications of the various techniques are described. Most of the techniques described are those that have been used in airborne applications or show promise of being adaptable to airborne applications. Some of the instruments described are specialty items that are not commercially-available. In situ measurement techniques for several meteorological parameters important in the study of the distribution and transport of ambient air pollutants are discussed. Some remote measurement techniques for meteorological parameters are also discussed. State-of-the-art measurement capabilities are compared with a list of capabilities and specifications desired by NASA for ambient measurements in the global troposphere.

A Summary of Meteorological Parameters During Space Shuttle Pad Exposure Periods

NASA Technical Reports Server (NTRS)

Overbey, Glenn; Roberts, Barry C.

2005-01-01

During the 113 missions of the Space Transportation System (STS), the Space Shuffle fleet has been exposed to the elements on the launch pad for a total of 4195 days. The Natural Environments Branch at Marshall Space Flight Center archives atmospheric environments to which the Space Shuttle vehicles are exposed. This paper provides a summary of the historical record of the meteorological conditions encountered by the Space Shuttle fleet during the pad exposure period. Sources of the surface parameters, including temperature, dew point temperature, relative humidity, wind speed, wind direction, sea level pressure and precipitation are presented. Data is provided from the first launch of the STS in 1981 through the launch of STS-107 in 2003.

Application of WRF/Chem over the Continental U.S. under the AQMEII Phase II: Part 2. Evaluation of 2010 Application and Responses of Air Quality and Meteorology-Chemistry Interactions to Changes in Emissions and Meteorology from 2006 to 2010

EPA Science Inventory

The Weather Research and Forecasting model with Chemistry (WRF/Chem) simulation with the 2005 Carbon Bond (CB05) gas-phase mechanism coupled to the Modal for Aerosol Dynamics for Europe (MADE) and the Volatility Basis Set (VBS) approach for secondary organic aerosol (SOA) (MADE/V...

Numerical Simulations and Diagnostic Studies Relating Meteorology To Atmospheric Chemistry during TRACE-P

NASA Technical Reports Server (NTRS)

Fuelberg, Henry E.

2003-01-01

The Florida State University (FSU) team participated extensively in the pre-mission planning for TRACE-P through meetings, telephone calls, and e-mails. During Spring 2001, Prof. Fuelberg served as DC-8 Mission Meteorologist during the field campaign. He prepared meteorological guidance for each flight of the DC-8 and flew on each mission. After the field phase, FSU prepared various meteorological products, included backward air trajectories, for each flight of the DC-8 and P-3B. These were posted on the FSU and NASA-GTE web sites for use by all the Science Team. During the two-year post mission period, FSU conducted research relating meteorology to atmospheric chemistry during TRACE-P. This led to three journal articles in the Journal of Geophysical Research. FSU personnel were the lead authors on each of these articles. Abstracts of these articles are attached. In addition, the FSU team collaborated with other members of the TRACE-P Science Team to incorporate meteorological factors into their research. A list of publications resulting from these interactions is included.

THE NEW YORK MIDTOWN DISPERSION STUDY (MID-05) METEOROLOGICAL DATA REPORT.

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

REYNOLDS,R.M.; SULLIVAN, T.M.; SMITH, S.

2007-01-01

The New York City midtown dispersion program, MID05, examined atmospheric transport in the deep urban canyons near Rockefeller Center. Little is known about air flow and hazardous gas dispersion under such conditions, since previous urban field experiments have focused on small to medium sized cities with much smaller street canyons and examined response over a much larger area. During August, 2005, a series of six gas tracer tests were conducted and sampling was conducted over a 2 km grid. A critical component of understanding gas movement in these studies is detailed wind and meteorological information in the study zone. Tomore » support data interpretation and modeling, several meteorological stations were installed at street level and on roof tops in Manhattan. In addition, meteorological data from airports and other weather instrumentation around New York City were collected. This document describes the meteorological component of the project and provides an outline of data file formats for the different instruments. These data provide enough detail to support highly-resolved computational simulations of gas transport in the study zone.« less

Refinement and testing of analysis nudging in MPAS-A ...

EPA Pesticide Factsheets

The Model for Prediction Across Scales - Atmosphere (MPAS-A) is being adapted to serve as the meteorological driver for EPA’s “next-generation” air-quality model. To serve that purpose, it must be able to function in a diagnostic mode where past meteorological conditions are represented in greater detail and accuracy than can be provided by available observational data and meteorological reanalysis products. MPAS-A has been modified to allow four dimensional data assimilation (FDDA) by the nudging of temperature, humidity and wind toward target values predefined on the MPAS-A computational mesh. The technique of “analysis nudging” developed for the Penn State / NCAR Mesoscale Model – Version 4 (MM4), and later applied in the Weather Research and Forecasting model (WRF), is applied here in MPAS-A with adaptations for the unstructured Voronoi mesh used in MPAS-A. Test simulations for the periods of January and July 2013, with and without FDDA, are compared to target fields at various vertical levels and to surface-level meteorological observations. The results show the ability to follow target fields with high fidelity while still maintaining conservation of mass as in the original model. The results also show model errors relative to observations continue to be constrained throughout the simulations using FDDA and even show some error reduction during the first few days that could be attributable to the finer resolution of the 92-25 km computa

Evaluating the accuracy of VEMAP daily weather data for application in crop simulations on a regional scale

USDA-ARS?s Scientific Manuscript database

Weather plays a critical role in eco-environmental and agricultural systems. Limited availability of meteorological records often constrains the applications of simulation models and related decision support tools. The Vegetation/Ecosystem Modeling and Analysis Project (VEMAP) provides daily weather...

Over-fitting Time Series Models of Air Pollution Health Effects: Smoothing Tends to Bias Non-Null Associations Towards the Null.

EPA Science Inventory

Background: Simulation studies have previously demonstrated that time-series analyses using smoothing splines correctly model null health-air pollution associations. Methods: We repeatedly simulated season, meteorology and air quality for the metropolitan area of Atlanta from cyc...

AQMEII3 evaluation of regional NA/EU simulations and analysis of scale, boundary conditions and emissions error-dependence

EPA Science Inventory

Through the comparison of several regional-scale chemistry transport modelling systems that simulate meteorology and air quality over the European and American continents, this study aims at i) apportioning the error to the responsible processes using time-scale analysis, ii) hel...

Dynamic Evaluation of Two Decades of CMAQ Simulations over the Continental United States

EPA Science Inventory

This presentation focuses on the dynamic evaluation of the CMAQ model over the continental United States using multi-decadal simulations for the period from 1990 to 2010 to examine how well the changes in observed ozone air quality induced by variations in meteorology and/or emis...

Meteorology for public

NASA Astrophysics Data System (ADS)

Špoler Čanić, Kornelija; Rasol, Dubravka; Milković, Janja

2013-04-01

The Meteorological and Hydrological Service in Croatia (MHSC) is, as a public service, open to and concentrated on public. The organization of visits to the MHSC for groups started in 1986. The GLOBE program in Croatia started in 1995 and after that interest for the group tours at the MHSC has increased. The majority of visitors are school and kindergarten children, students and groups of teachers. For each group tour we try to prepare the content that is suitable for the age and interest of a group. Majority of groups prefer to visit the meteorological station where they can see meteorological instruments and learn how they work. It is organized as a little workshop, where visitors can ask questions and discuss with a guide not only about the meteorological measurements but also about weather and climate phenomena they are interested in. Undoubtedly the highlight of a visit is the forecaster's room where visitors can talk to the forecasters (whom they can also see giving a weather forecast on the national TV station) and learn how weather forecasts are made. Sometimes we offer to visitors to make some meteorological experiments but that is still not in a regular program of the group tours due to the lack of performing space. Therefore we give them the instructions for making instruments and simulations of meteorological phenomena from household items. Visits guides are meteorologists with profound experience in the popularization of science.

Meteorological Decision Assistance.

DTIC Science & Technology

1981-08-01

500 for labor and materials. The most economical course of action can be determined by computing the cost/loss ratio (C/L) and comparing it to the...interest, a clima - tology of these parameters, the impact of these parameters on the customer’s mission, and the techniques for assessing the probability of

Evaluation of urban surface parameterizations in the WRF model using measurements during the Texas Air Quality Study 2006 field campaign

NASA Astrophysics Data System (ADS)

Lee, S.-H.; Kim, S.-W.; Angevine, W. M.; Bianco, L.; McKeen, S. A.; Senff, C. J.; Trainer, M.; Tucker, S. C.; Zamora, R. J.

2010-10-01

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 conditions when nocturnal low-level jets exist and a thermal internal boundary layer over water forms.

The Ozone Budget in the Upper Troposphere from Global Modeling Initiative (GMI)Simulations

NASA Technical Reports Server (NTRS)

Rodriquez, J.; Duncan, Bryan N.; Logan, Jennifer A.

2006-01-01

Ozone concentrations in the upper troposphere are influenced by in-situ production, long-range tropospheric transport, and influx of stratospheric ozone, as well as by photochemical removal. Since ozone is an important greenhouse gas in this region, it is particularly important to understand how it will respond to changes in anthropogenic emissions and changes in stratospheric ozone fluxes.. This response will be determined by the relative balance of the different production, loss and transport processes. Ozone concentrations calculated by models will differ depending on the adopted meteorological fields, their chemical scheme, anthropogenic emissions, and treatment of the stratospheric influx. We performed simulations using the chemical-transport model from the Global Modeling Initiative (GMI) with meteorological fields from (It)h e NASA Goddard Institute for Space Studies (GISS) general circulation model (GCM), (2) the atmospheric GCM from NASA's Global Modeling and Assimilation Office(GMAO), and (3) assimilated winds from GMAO . These simulations adopt the same chemical mechanism and emissions, and adopt the Synthetic Ozone (SYNOZ) approach for treating the influx of stratospheric ozone -. In addition, we also performed simulations for a coupled troposphere-stratosphere model with a subset of the same winds. Simulations were done for both 4degx5deg and 2degx2.5deg resolution. Model results are being tested through comparison with a suite of atmospheric observations. In this presentation, we diagnose the ozone budget in the upper troposphere utilizing the suite of GMI simulations, to address the sensitivity of this budget to: a) the different meteorological fields used; b) the adoption of the SYNOZ boundary condition versus inclusion of a full stratosphere; c) model horizontal resolution. Model results are compared to observations to determine biases in particular simulations; by examining these comparisons in conjunction with the derived budgets, we may pinpoint deficiencies in the representation of chemical/dynamical processes.

Calibration of a distributed hydrologic model using observed spatial patterns from MODIS data

NASA Astrophysics Data System (ADS)

Demirel, Mehmet C.; González, Gorka M.; Mai, Juliane; Stisen, Simon

2016-04-01

Distributed hydrologic models are typically calibrated against streamflow observations at the outlet of the basin. Along with these observations from gauging stations, satellite based estimates offer independent evaluation data such as remotely sensed actual evapotranspiration (aET) and land surface temperature. The primary objective of the study is to compare model calibrations against traditional downstream discharge measurements with calibrations against simulated spatial patterns and combinations of both types of observations. While the discharge based model calibration typically improves the temporal dynamics of the model, it seems to give rise to minimum improvement of the simulated spatial patterns. In contrast, objective functions specifically targeting the spatial pattern performance could potentially increase the spatial model performance. However, most modeling studies, including the model formulations and parameterization, are not designed to actually change the simulated spatial pattern during calibration. This study investigates the potential benefits of incorporating spatial patterns from MODIS data to calibrate the mesoscale hydrologic model (mHM). This model is selected as it allows for a change in the spatial distribution of key soil parameters through the optimization of pedo-transfer function parameters and includes options for using fully distributed daily Leaf Area Index (LAI) values directly as input. In addition the simulated aET can be estimated at a spatial resolution suitable for comparison to the spatial patterns observed with MODIS data. To increase our control on spatial calibration we introduced three additional parameters to the model. These new parameters are part of an empirical equation to the calculate crop coefficient (Kc) from daily LAI maps and used to update potential evapotranspiration (PET) as model inputs. This is done instead of correcting/updating PET with just a uniform (or aspect driven) factor used in the mHM model (version 5.3). We selected the 20 most important parameters out of 53 mHM parameters based on a comprehensive sensitivity analysis (Cuntz et al., 2015). We calibrated 1km-daily mHM for the Skjern basin in Denmark using the Shuffled Complex Evolution (SCE) algorithm and inputs at different spatial scales i.e. meteorological data at 10km and morphological data at 250 meters. We used correlation coefficients between observed monthly (summer months only) MODIS data calculated from cloud free days over the calibration period from 2001 to 2008 and simulated aET from mHM over the same period. Similarly other metrics, e.g mapcurves and fraction skill-score, are also included in our objective function to assess the co-location of the grid-cells. The preliminary results show that multi-objective calibration of mHM against observed streamflow and spatial patterns together does not significantly reduce the spatial errors in aET while it improves the streamflow simulations. This is a strong signal for further investigation of the multi parameter regionalization affecting spatial aET patterns and weighting the spatial metrics in the objective function relative to the streamflow metrics.

Spatial interpolation of GPS PWV and meteorological variables over the west coast of Peninsular Malaysia during 2013 Klang Valley Flash Flood

NASA Astrophysics Data System (ADS)

Suparta, Wayan; Rahman, Rosnani

2016-02-01

Global Positioning System (GPS) receivers are widely installed throughout the Peninsular Malaysia, but the implementation for monitoring weather hazard system such as flash flood is still not optimal. To increase the benefit for meteorological applications, the GPS system should be installed in collocation with meteorological sensors so the precipitable water vapor (PWV) can be measured. The distribution of PWV is a key element to the Earth's climate for quantitative precipitation improvement as well as flash flood forecasts. The accuracy of this parameter depends on a large extent on the number of GPS receiver installations and meteorological sensors in the targeted area. Due to cost constraints, a spatial interpolation method is proposed to address these issues. In this paper, we investigated spatial distribution of GPS PWV and meteorological variables (surface temperature, relative humidity, and rainfall) by using thin plate spline (tps) and ordinary kriging (Krig) interpolation techniques over the Klang Valley in Peninsular Malaysia (longitude: 99.5°-102.5°E and latitude: 2.0°-6.5°N). Three flash flood cases in September, October, and December 2013 were studied. The analysis was performed using mean absolute error (MAE), root mean square error (RMSE), and coefficient of determination (R2) to determine the accuracy and reliability of the interpolation techniques. Results at different phases (pre, onset, and post) that were evaluated showed that tps interpolation technique is more accurate, reliable, and highly correlated in estimating GPS PWV and relative humidity, whereas Krig is more reliable for predicting temperature and rainfall during pre-flash flood events. During the onset of flash flood events, both methods showed good interpolation in estimating all meteorological parameters with high accuracy and reliability. The finding suggests that the proposed method of spatial interpolation techniques are capable of handling limited data sources with high accuracy, which in turn can be used to predict future floods.

Advances in snow cover distributed modelling via ensemble simulations and assimilation of satellite data

NASA Astrophysics Data System (ADS)

Revuelto, J.; Dumont, M.; Tuzet, F.; Vionnet, V.; Lafaysse, M.; Lecourt, G.; Vernay, M.; Morin, S.; Cosme, E.; Six, D.; Rabatel, A.

2017-12-01

Nowadays snowpack models show a good capability in simulating the evolution of snow in mountain areas. However singular deviations of meteorological forcing and shortcomings in the modelling of snow physical processes, when accumulated on time along a snow season, could produce large deviations from real snowpack state. The evaluation of these deviations is usually assessed with on-site observations from automatic weather stations. Nevertheless the location of these stations could strongly influence the results of these evaluations since local topography may have a marked influence on snowpack evolution. Despite the evaluation of snowpack models with automatic weather stations usually reveal good results, there exist a lack of large scale evaluations of simulations results on heterogeneous alpine terrain subjected to local topographic effects.This work firstly presents a complete evaluation of the detailed snowpack model Crocus over an extended mountain area, the Arve upper catchment (western European Alps). This catchment has a wide elevation range with a large area above 2000m a.s.l. and/or glaciated. The evaluation compares results obtained with distributed and semi-distributed simulations (the latter nowadays used on the operational forecasting). Daily observations of the snow covered area from MODIS satellite sensor, seasonal glacier surface mass balance evolution measured in more than 65 locations and the galciers annual equilibrium line altitude from Landsat/Spot/Aster satellites, have been used for model evaluation. Additionally the latest advances in producing ensemble snowpack simulations for assimilating satellite reflectance data over extended areas will be presented. These advances comprises the generation of an ensemble of downscaled high-resolution meteorological forcing from meso-scale meteorological models and the application of a particle filter scheme for assimilating satellite observations. Despite the results are prefatory, they show a good potential improving snowpack forecasting capabilities.

Assessment of PM10 enhancement by yellow sand on the air quality of Taipei, Taiwan in 2001.

PubMed

Chang, Shuenn-Chin; Lee, Chung-Te

2007-09-01

The impact of long-range transport of yellow sand from Asian Continent to the Taipei Metropolitan Area (Taipei) not only deteriorates air quality but also poses health risks to all, especially the children and the elderly. As such, it is important to assess the enhancement of PM(10) during yellow sand periods. In order to estimate PM(10) enhancement, we adopted factor analysis to distinguish the yellow-sand (YS) periods from non-yellow-sand (NYS) periods based on air quality monitoring records. Eight YS events were identified using factor analysis coupling with an independent validation procedure by checking background site values, examining meteorological conditions, and modeling air mass trajectory from January 2001 to May 2001. The duration of each event varied from 11 to 132 h, which was identified from the time when the PM(10) level was high, and the CO and NOx levels were low. Subsequently, we used the artificial neural network (ANN) to simulate local PM(10) levels from related parameters including local gas pollutants and meteorological factors during the NYS periods. The PM(10) enhancement during the YS periods is then calculated by subtracting the simulated PM(10) from the observed PM(10) levels. Based on our calculations, the PM(10) enhancement in the maximum hour of each event ranged from 51 to 82%. Moreover, in the eight events identified in 2001, it was estimated that a total amount of 7,210 tons of PM(10) were transported by yellow sand to Taipei. Thus, in this study, we demonstrate that an integration of factor analysis with ANN model could provide a very useful method in identifying YS periods and in determining PM(10) enhancement caused by yellow sand.

Effects of Land Use Change on Evapotranspiration and Water Yield in the Great Lakes Region

NASA Astrophysics Data System (ADS)

Mao, D.; Cherkauer, K. A.

2005-12-01

Human activities have affected the exchange of energy and water between atmosphere and land surface through land use change. Conversion of large regions of pre-settlement forest and grassland to a majority cropland cover in the Great Lakes region has resulted in regional scale changes to hydrologic responses. Understanding the impact of historic land use change is important for management of future resources. Effects of land use change on the water and energy cycle of three Great Lakes states: Minnesota, Wisconsin, and Michigan, are analyzed using the Variable Infiltration Capacity (VIC) model. Land Data Assimilation System (LDAS) meteorological and soil data as well as pre-settlement and modern vegetation data taken from the USGS Land Use History of North American (LUHNA) were used as model input. Default vegetation input parameters were adjusted for the region based on a review of published studies. Results from a single grid cell vegetation sensitivity test show that on an average annual basis, forests transpire more than cropland and cropland more than grassland due to seasonal variations in Leaf Area Index (LAI) and stomatal resistances of vegetations. The hydrologic impact of region wide land use change was then analyzed by comparing simulations using both pre-settlement and current vegetation cover but the same meteorological forcings. Simulated changes resulting from land cover change vary with season and vegetation types. Reduction in forest cover increases water yield by decreasing evapotranspiration. Conversion between forest types resulted only in small differences in evaporation and water fluxes response. The most significant hydrologic changes were located in the southern part of the region where land use change has been primarily forest converted to cropland.

SPITFIRE within the MPI Earth system model: Model development and evaluation

NASA Astrophysics Data System (ADS)

Lasslop, Gitta; Thonicke, Kirsten; Kloster, Silvia

2014-09-01

Quantification of the role of fire within the Earth system requires an adequate representation of fire as a climate-controlled process within an Earth system model. To be able to address questions on the interaction between fire and the Earth system, we implemented the mechanistic fire model SPITFIRE, in JSBACH, the land surface model of the MPI Earth system model. Here, we document the model implementation as well as model modifications. We evaluate our model results by comparing the simulation to the GFED version 3 satellite-based data set. In addition, we assess the sensitivity of the model to the meteorological forcing and to the spatial variability of a number of fire relevant model parameters. A first comparison of model results with burned area observations showed a strong correlation of the residuals with wind speed. Further analysis revealed that the response of the fire spread to wind speed was too strong for the application on global scale. Therefore, we developed an improved parametrization to account for this effect. The evaluation of the improved model shows that the model is able to capture the global gradients and the seasonality of burned area. Some areas of model-data mismatch can be explained by differences in vegetation cover compared to observations. We achieve benchmarking scores comparable to other state-of-the-art fire models. The global total burned area is sensitive to the meteorological forcing. Adjustment of parameters leads to similar model results for both forcing data sets with respect to spatial and seasonal patterns. This article was corrected on 29 SEP 2014. See the end of the full text for details.

Regional probability distribution of the annual reference evapotranspiration and its effective parameters in Iran

NASA Astrophysics Data System (ADS)

Khanmohammadi, Neda; Rezaie, Hossein; Montaseri, Majid; Behmanesh, Javad

2017-10-01

The reference evapotranspiration (ET0) plays an important role in water management plans in arid or semi-arid countries such as Iran. For this reason, the regional analysis of this parameter is important. But, ET0 process is affected by several meteorological parameters such as wind speed, solar radiation, temperature and relative humidity. Therefore, the effect of distribution type of effective meteorological variables on ET0 distribution was analyzed. For this purpose, the regional probability distribution of the annual ET0 and its effective parameters were selected. Used data in this research was recorded data at 30 synoptic stations of Iran during 1960-2014. Using the probability plot correlation coefficient (PPCC) test and the L-moment method, five common distributions were compared and the best distribution was selected. The results of PPCC test and L-moment diagram indicated that the Pearson type III distribution was the best probability distribution for fitting annual ET0 and its four effective parameters. The results of RMSE showed that the ability of the PPCC test and L-moment method for regional analysis of reference evapotranspiration and its effective parameters was similar. The results also showed that the distribution type of the parameters which affected ET0 values can affect the distribution of reference evapotranspiration.

EVALUATION OF METEOROLOGICAL ALERT CHAIN IN CASTILLA Y LEÓN (SPAIN): How can the meteorological risk managers help researchers?

NASA Astrophysics Data System (ADS)

López, Laura; Guerrero-Higueras, Ángel Manuel; Sánchez, José Luis; Matía, Pedro; Ortiz de Galisteo, José Pablo; Rodríguez, Vicente; Lorente, José Manuel; Merino, Andrés; Hermida, Lucía; García-Ortega, Eduardo; Fernández-Manso, Oscar

2013-04-01

Evaluating the meteorological alert chain, or, how information is transmitted from the meteorological forecasters to the final users, passing through risk managers, is a useful tool that benefits all the links of the chain, especially the meteorology researchers and forecasters. In fact, the risk managers can help significantly to improve meteorological forecasts in different ways. Firstly, by pointing out the most appropriate type of meteorological format, and its characteristics when representing the meteorological information, consequently improving the interpretation of the already-existing forecasts. Secondly, by pointing out the specific predictive needs in their workplaces related to the type of significant meteorological parameters, temporal or spatial range necessary, meteorological products "custom-made" for each type of risk manager, etc. In order to carry out an evaluation of the alert chain in Castilla y León, we opted for the creation of a Panel of Experts made up of personnel specialized in risk management (Responsible for Protection Civil, Responsible for Alert Services and Hydrological Planning of Hydrographical Confederations, Responsible for highway maintenance, and management of fires, fundamentally). In creating this panel, a total of twenty online questions were evaluated, and the majority of the questions were multiple choice or open-ended. Some of the results show how the risk managers think that it would be interesting, or very interesting, to carry out environmental educational campaigns about the meteorological risks in Castilla y León. Another result is the elevated importance that the risk managers provide to the observation data in real-time (real-time of wind, lightning, relative humidity, combined indices of risk of avalanches, snowslides, index of fires due to convective activity, etc.) Acknowledgements The authors would like to thank the Junta de Castilla y León for its financial support through the project LE220A11-2.

Evaluating the Credibility of Transport Processes in the Global Modeling Initiative 3D Model Simulations of Ozone Recovery

NASA Technical Reports Server (NTRS)

Strahan, Susan E.; Douglass, Anne R.

2003-01-01

The Global Modeling Initiative has integrated two 35-year simulations of an ozone recovery scenario with an offline chemistry and transport model using two different meteorological inputs. Physically based diagnostics, derived from satellite and aircraft data sets, are described and then used to evaluate the realism of temperature and transport processes in the simulations. Processes evaluated include barrier formation in the subtropics and polar regions, and extratropical wave-driven transport. Some diagnostics are especially relevant to simulation of lower stratospheric ozone, but most are applicable to any stratospheric simulation. The temperature evaluation, which is relevant to gas phase chemical reactions, showed that both sets of meteorological fields have near climatological values at all latitudes and seasons at 30 hPa and below. Both simulations showed weakness in upper stratospheric wave driving. The simulation using input from a general circulation model (GMI(sub GCM)) showed a very good residual circulation in the tropics and northern hemisphere. The simulation with input from a data assimilation system (GMI(sub DAS)) performed better in the midlatitudes than at high latitudes. Neither simulation forms a realistic barrier at the vortex edge, leading to uncertainty in the fate of ozone-depleted vortex air. Overall, tracer transport in the offline GMI(sub GCM) has greater fidelity throughout the stratosphere than the GMI(sub DAS).

Use of midlatitude soil moisture and meteorological observations to validate soil moisture simulations with biosphere and bucket models

NASA Technical Reports Server (NTRS)

Robock, Alan; Vinnikov, Konstantin YA.; Schlosser, C. Adam; Speranskaya, Nina A.; Xue, Yongkang

1995-01-01

Soil moisture observations in sites with natural vegetation were made for several decades in the former Soviet Union at hundreds of stations. In this paper, the authors use data from six of these stations from different climatic regimes, along with ancillary meteorological and actinometric data, to demonstrate a method to validate soil moisture simulations with biosphere and bucket models. Some early and current general circulation models (GCMs) use bucket models for soil hydrology calculations. More recently, the Simple Biosphere Model (SiB) was developed to incorporate the effects of vegetation on fluxes of moisture, momentum, and energy at the earth's surface into soil hydrology models. Until now, the bucket and SiB have been verified by comparison with actual soil moisture data only on a limited basis. In this study, a Simplified SiB (SSiB) soil hydrology model and a 15-cm bucket model are forced by observed meteorological and actinometric data every 3 h for 6-yr simulations at the six stations. The model calculations of soil moisture are compared to observations of soil moisture, literally 'ground truth,' snow cover, surface albedo, and net radiation, and with each other. For three of the stations, the SSiB and 15-cm bucket models produce good simulations of seasonal cycles and interannual variations of soil moisture. For the other three stations, there are large errors in the simulations by both models. Inconsistencies in specification of field capacity may be partly responsible. There is no evidence that the SSiB simulations are superior in simulating soil moisture variations. In fact, the models are quite similar since SSiB implicitly has a bucket embedded in it. One of the main differences between the models is in the treatment of runoff due to melting snow in the spring -- SSiB incorrectly puts all the snowmelt into runoff. While producing similar soil moisture simulations, the models produce very different surface latent and sensible heat fluxes, which would have large effects on GCM simulations.

Uncertainties in Episodic Ozone Modeling Stemming from Uncertainties in the Meteorological Fields.

NASA Astrophysics Data System (ADS)

Biswas, Jhumoor; Trivikrama Rao, S.

2001-02-01

This paper examines the uncertainty associated with photochemical modeling using the Variable-Grid Urban Airshed Model (UAM-V) with two different prognostic meteorological models. The meteorological fields for ozone episodes that occurred during 17-20 June, 12-15 July, and 30 July-2 August in the summer of 1995 were derived from two meteorological models, the Regional Atmospheric Modeling System (RAMS) and the Fifth-Generation Pennsylvania State University-National Center for Atmospheric Research Mesoscale Model (MM5). The simulated ozone concentrations from the two photochemical modeling systems, namely, RAMS/UAM-V and MM5/UAM-V, are compared with each other and with ozone observations from several monitoring sites in the eastern United States. The overall results indicate that neither modeling system performs significantly better than the other in reproducing the observed ozone concentrations. The results reveal that there is a significant variability, about 20% at the 95% level of confidence, in the modeled 1-h ozone concentration maxima from one modeling system to the other for a given episode. The model-to-model variability in the simulated ozone levels is for most part attributable to the unsystematic type of errors. The directionality for emission controls (i.e., NOx versus VOC sensitivity) is also evaluated with UAM-V using hypothetical emission reductions. The results reveal that not only the improvement in ozone but also the VOC-sensitive and NOx-sensitive regimes are influenced by the differences in the meteorological fields. Both modeling systems indicate that a large portion of the eastern United States is NOx limited, but there are model-to-model and episode-to-episode differences at individual grid cells regarding the efficacy of emission reductions.

Correction to "Influence of Dust and Black Carbon on the Snow Albedo in the NASA Goddard Earth Observing System Version 5 Land Surface Model"

NASA Technical Reports Server (NTRS)

Yasunari, Teppei J.; Koster, Randal D.; Kau, K. M.; Aoki, Teruo; Sud, Yogesh C.; Yamazaki, Takeshi; Motoyoshi, Hiroki; Kokdama, Yuji

2012-01-01

The website information describing the forcing meteorological data used for the land surface model (LSM) simulation, which were observed at an Automated Meteorological Station CAWS) at the Sapporo District Meteorological Observatory maintained by the Japan Meteorological Agency (JMA), was missing from the text. The 1-hourly data were obtained from the website of Kisyoutoukeijouhou (Information for available JMA-observed meteorological data in the past) on the website of JMA (in Japanese) (available at: http://www.jma.go.jpijmaimenulreport.html). The measurement height information of 59.5 m for the anemometer at the Sapporo Observatory was also obtained from the website of JMA (in Japanese) (available at: http://www.jma.go.jp/jma/menu/report.html). In addition, the converted 10-m wind speed, based on the AWS/JMA data, was further converted to a 2-m wind speed prior to its use with the land model as a usual treatment of off-line Catchment simulation. Please ignore the ice absorption data on the website mentioned in paragraph [15] which was not used for our calculations (but the data on the website was mostly the same as the estimated ice absorption coefficients by the following method because they partially used the same data by Warren [1984]). We calculated the ice absorption coefficients with the method mentioned in the same paragraph, for which some of the refractive index data by Warren [1984] were used and then interpolated between wavelengths, and also mentioned in paragraph [20] for the visible (VIS) and near-infrared (NIR) ranges. The optical data we used were interpolated between wavelengths as necessary.

Effect of horizontal resolution on meteorology and air-quality prediction with a regional scale model

NASA Astrophysics Data System (ADS)

Varghese, Saji; Langmann, Baerbel; Ceburnis, Darius; O'Dowd, Colin D.

2011-08-01

Horizontal resolution sensitivity can significantly contribute to the uncertainty in predictions of meteorology and air-quality from a regional climate model. In the study presented here, a state-of-the-art regional scale atmospheric climate-chemistry-aerosol model REMOTE is used to understand the influence of spatial model resolutions of 1.0°, 0.5° and 0.25° on predicted meteorological and aerosol parameters for June 2003 for the European domain comprising North-east Atlantic and Western Europe. Model precipitation appears to improve with resolution while wind speed has shown best results for 0.25° resolution for most of the stations compared with ECAD data. Low root mean square error and spatial bias for surface pressure, precipitation and surface temperature show that the model is very reliable. Spatial and temporal variation in black carbon, primary organic carbon, sea-salt and sulphate concentrations and their burden are presented. In most cases, chemical species concentrations at the surface show no particular trend or improvement with increase in resolution. There has been a pronounced influence of horizontal resolution on the vertical distribution pattern of some aerosol species. Some of these effects are due to the improvement in topographical details, flow characteristics and associated vertical and horizontal dynamic processes. The different sink processes have contributed very differently to the various aerosol species in terms of deposition (wet and dry) and sedimentation which are strongly linked to the meteorological processes. Overall, considering the performance of meteorological parameters and chemical species concentrations, a horizontal model resolution of 0.5° is suggested to achieve reasonable results within the limitations of this model.

Respiratory viral infections and effects of meteorological parameters and air pollution in adults with respiratory symptoms admitted to the emergency room

PubMed Central

Silva, Denise R; Viana, Vinícius P; Müller, Alice M; Livi, Fernando P; Dalcin, Paulo de Tarso R

2014-01-01

Background Respiratory viral infections (RVIs) are the most common causes of respiratory infections. The prevalence of respiratory viruses in adults is underestimated. Meteorological variations and air pollution are likely to play a role in these infections. Objectives The objectives of this study were to determine the number of emergency visits for influenza-like illness (ILI) and severe acute respiratory infection (SARI) and to evaluate the association between ILI/SARI, RVI prevalence, and meteorological factors/air pollution, in the city of Porto Alegre, Brazil, from November 2008 to October 2010. Methods Eleven thousand nine hundred and fifty-three hospitalizations (adults and children) for respiratory symptoms were correlated with meteorological parameters and air pollutants. In a subset of adults, nasopharyngeal aspirates were collected and analyzed through IFI test. The data were analyzed using time-series analysis. Results Influenza-like illness and SARI were diagnosed in 3698 (30·9%) and 2063 (17·7%) patients, respectively. Thirty-seven (9·0%) samples were positive by IFI and 93 of 410 (22·7%) were IFI and/or PCR positive. In a multivariate logistic regression model, IFI positivity was statistically associated with absolute humidity, use of air conditioning, and presence of mold in home. Sunshine duration was significantly associated with the frequency of ILI cases. For SARI cases, the variables mean temperature, sunshine duration, relative humidity, and mean concentration of pollutants were singnificant. Conclusions At least 22% of infections in adult patients admitted to ER with respiratory complaints were caused by RVI. The correlations among meteorological variables, air pollution, ILI/SARI cases, and respiratory viruses demonstrated the relevance of climate factors as significant underlying contributors to the prevalence of RVI. PMID:24034701

Implementation of an online chemical mechanism within a global-regional atmospheric model: design and initial steps

NASA Astrophysics Data System (ADS)

Jorba, O.; Pérez, C.; Baldasano, J. M.

2009-04-01

Chemical processes in air quality modelling systems are usually treated independently from the meteorological models. This approach is computationally attractive since off-line chemical transport simulations only require a single meteorological dataset to produce many chemical simulations. However, this separation of chemistry and meteorology produces a loss of important information about atmospheric processes and does not allow for feedbacks between chemistry and meteorology. To take into account such processes current models are evolving to an online coupling of chemistry and meteorology to produce consistent chemical weather predictions. The Earth Sciences Department of the Barcelona Supercomputing Center (BSC) develops the NMMB/BSC-DUST (Pérez et al., 2008), an online dust model within the global-regional NCEP/NMMB numerical weather prediction model (Janjic and Black, 2007) under development at National Centers for Environmental Prediction (NCEP). Current implementation is based on the well established regional dust model and forecast system DREAM (Nickovic et al., 2001). The most relevant characteristics of NMMB/BSC-DUST are its on-line coupling of the dust scheme with the meteorological driver, the wide range of applications from meso to global scales, and the inclusion of dust radiative effects allowing feedbacks between aerosols and meteorology. In order to complement such development, BSC works also in the implementation of a fully coupled online chemical mechanism within NMMB/BSC-DUST. The final objective is to develop a fully chemical weather prediction system able to resolve gas-aerosol-meteorology interactions from global to local scales. In this contribution we will present the design of the chemistry coupling and the current progress of its implementation. Following the NCEP/NMMB approach, the chemistry part will be coupled through the Earth System Modeling Framework (ESMF) as a pluggable component. The chemical mechanism and chemistry solver is based on the Kinetic PreProcessor KPP (Sandu and Sander, 2006) package with the main purpose to maintain a wide flexibility when configuring the model. Such approach will allow using a simple general chemical mechanism for global applications or a more complex mechanism for regional to local applications at higher resolution. REFERENCES Janjic, Z.I., and Black, T.L., 2007. An ESMF unified model for a broad range of spatial and temporal scales, Geophysical Research Abstracts, 9, 05025. Nickovic, S., Papadopoulos, A., Kakaliagou, O., and Kallos, G., 2001. Model for prediciton of desert dust cycle in the atmosphere. J. Geophys. Res., 106, 18113-18129. Pérez, C., Haustein, K., Janjic, Z.I., Jorba, O., Baldasano, J.M., Black, T.L., and Nickovic, S., 2008. An online dust model within the meso to global NMMB: current progress and plans. AGU Fall Meeting, San Francisco, A41K-03, 2008. Sandu, A., and Sander, R., 2006. Technical note:Simulating chemical systems in Fortran90 and Matlab with the Kinetic PreProcessor KPP-2.1. Atmos. Chem. and Phys., 6, 187-195.

Validation of scintillometer measurements over a heterogeneous landscape: The LITFASS-2009 Experiment

NASA Astrophysics Data System (ADS)

Beyrich, F.; Bange, J.; Hartogensis, O.; Raasch, S.

2009-09-01

The turbulent exchange of heat and water vapour are essential land surface - atmosphere interaction processes in the local, regional and global energy and water cycles. Scintillometry can be considered as the only technique presently available for the quasi-operational experimental determination of area-averaged turbulent fluxes needed to validate the fluxes simulated by regional atmospheric models or derived from satellite images at a horizontal scale of a few kilometres. While scintillometry has found increasing application over the last years, some fundamental issues related to its use still need further investigation. In particular, no studies are known so far to reproduce the path-averaged structure parameters measured by scintillometers by independent measurements or modelling techniques. The LITFASS-2009 field experiment has been performed in the area around the Meteorological Observatory Lindenberg / Richard-Aßmann-Observatory in Germany during summer 2009. It was designed to investigate the spatial (horizontal and vertical) and temporal variability of structure parameters (underlying the scintillometer principle) over moderately heterogeneous terrain. The experiment essentially relied on a coupling of eddy-covariance measurements, scintillometry and airborne measurements with an unmanned autonomous aircraft able to strictly fly along the scintillometer path. Data interpretation will be supported by numerical modelling using a large-eddy simulation (LES) model. The paper will describe the design of the experiment. First preliminary results from the measurements will be presented.

Impact of global climate change on ozone, particulate matter, and secondary organic aerosol concentrations in California: A model perturbation analysis

NASA Astrophysics Data System (ADS)

Horne, Jeremy R.; Dabdub, Donald

2017-03-01

Air quality simulations are performed to determine the impact of changes in future climate and emissions on regional air quality in the South Coast Air Basin (SoCAB) of California. The perturbation parameters considered in this study include (1) temperature, (2) absolute humidity, (3) biogenic VOC emissions due to temperature changes, and (4) boundary conditions. All parameters are first perturbed individually. In addition, the impact of simultaneously perturbing more than one parameter is analyzed. Air quality is simulated with meteorology representative of a summertime ozone pollution episode using both a baseline 2005 emissions inventory and a future emissions projection for the year 2023. Different locations within the modeling domain exhibit varying degrees of sensitivity to the perturbations considered. Afternoon domain wide average ozone concentrations are projected to increase by 13-18% as a result of changes in future climate and emissions. Afternoon increases at individual locations range from 10 to 36%. The change in afternoon particulate matter (PM) levels is a strong function of location in the basin, ranging from -7.1% to +4.7% when using 2005 emissions and -8.6% to +1.7% when using 2023 emissions. Afternoon secondary organic aerosol (SOA) concentrations for the entire domain are projected to decrease by over 15%, and the change in SOA levels is not a strong function of the emissions inventory utilized. Temperature increases play the dominant role in determining the overall impact on ozone, PM, and SOA concentrations in both the individual and combined perturbation scenarios.