A comprehensive estimation of the economic effects of meteorological services based on the input-output method.

PubMed

Wu, Xianhua; Wei, Guo; Yang, Lingjuan; Guo, Ji; Lu, Huaguo; Chen, Yunfeng; Sun, Jian

2014-01-01

Concentrating on consuming coefficient, partition coefficient, and Leontief inverse matrix, relevant concepts and algorithms are developed for estimating the impact of meteorological services including the associated (indirect, complete) economic effect. Subsequently, quantitative estimations are particularly obtained for the meteorological services in Jiangxi province by utilizing the input-output method. It is found that the economic effects are noticeably rescued by the preventive strategies developed from both the meteorological information and internal relevance (interdependency) in the industrial economic system. Another finding is that the ratio range of input in the complete economic effect on meteorological services is about 1 : 108.27-1 : 183.06, remarkably different from a previous estimation based on the Delphi method (1 : 30-1 : 51). Particularly, economic effects of meteorological services are higher for nontraditional users of manufacturing, wholesale and retail trades, services sector, tourism and culture, and art and lower for traditional users of agriculture, forestry, livestock, fishery, and construction industries.

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.

The Gaussian atmospheric transport model and its sensitivity to the joint frequency distribution and parametric variability.

PubMed

Hamby, D M

2002-01-01

Reconstructed meteorological data are often used in some form of long-term wind trajectory models for estimating the historical impacts of atmospheric emissions. Meteorological data for the straight-line Gaussian plume model are put into a joint frequency distribution, a three-dimensional array describing atmospheric wind direction, speed, and stability. Methods using the Gaussian model and joint frequency distribution inputs provide reasonable estimates of downwind concentration and have been shown to be accurate to within a factor of four. We have used multiple joint frequency distributions and probabilistic techniques to assess the Gaussian plume model and determine concentration-estimate uncertainty and model sensitivity. We examine the straight-line Gaussian model while calculating both sector-averaged and annual-averaged relative concentrations at various downwind distances. The sector-average concentration model was found to be most sensitive to wind speed, followed by horizontal dispersion (sigmaZ), the importance of which increases as stability increases. The Gaussian model is not sensitive to stack height uncertainty. Precision of the frequency data appears to be most important to meteorological inputs when calculations are made for near-field receptors, increasing as stack height increases.

Future directions of meteorology related to air-quality research.

PubMed

Seaman, Nelson L

2003-06-01

Meteorology is one of the major factors contributing to air-pollution episodes. More accurate representation of meteorological fields has been possible in recent years through the use of remote sensing systems, high-speed computers and fine-mesh meteorological models. Over the next 5-20 years, better meteorological inputs for air quality studies will depend on making better use of a wealth of new remotely sensed observations in more advanced data assimilation systems. However, for fine mesh models to be successful, parameterizations used to represent physical processes must be redesigned to be more precise and better adapted for the scales at which they will be applied. Candidates for significant overhaul include schemes to represent turbulence, deep convection, shallow clouds, and land-surface processes. Improvements in the meteorological observing systems, data assimilation and modeling, coupled with advancements in air-chemistry modeling, will soon lead to operational forecasting of air quality in the US. Predictive capabilities can be expected to grow rapidly over the next decade. This will open the way for a number of valuable new services and strategies, including better warnings of unhealthy atmospheric conditions, event-dependent emissions restrictions, and now casting support for homeland security in the event of toxic releases into the atmosphere.

A multiscale modelling methodology applicable for regulatory purposes taking into account effects of complex terrain and buildings on pollutant dispersion: a case study for an inner Alpine basin.

PubMed

Oettl, D

2015-11-01

Dispersion modelling in complex terrain always has been challenging for modellers. Although a large number of publications are dedicated to that field, candidate methods and models for usage in regulatory applications are scarce. This is all the more true when the combined effect of topography and obstacles on pollutant dispersion has to be taken into account. In Austria, largely situated in Alpine regions, such complex situations are quite frequent. This work deals with an approach, which is in principle capable of considering both buildings and topography in simulations by combining state-of-the-art wind field models at the micro- (<1 km) and mesoscale γ (2-20 km) with a Lagrangian particle model. In order to make such complex numerical models applicable for regulatory purposes, meteorological input data for the models need to be readily derived from routine observations. Here, use was made of the traditional way to bin meteorological data based on wind direction, speed, and stability class, formerly mainly used in conjunction with Gaussian-type models. It is demonstrated that this approach leads to reasonable agreements (fractional bias < 0.1) between observed and modelled annual average concentrations in an Alpine basin with frequent low-wind-speed conditions, temperature inversions, and quite complex flow patterns, while keeping the simulation times within the frame of possibility with regard to applications in licencing procedures. However, due to the simplifications in the derivation of meteorological input data as well as several ad hoc assumptions regarding the boundary conditions of the mesoscale wind field model, the methodology is not suited for computing detailed time and space variations of pollutant concentrations.

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.

Proceedings: Sixth Annual Workshop on Meteorological and Environmental Inputs to Aviation Systems

NASA Technical Reports Server (NTRS)

Frost, W. (Editor); Camp, D. W. (Editor); Hershman, L. W. (Editor)

1983-01-01

The topics of interaction of the atmosphere with aviation systems, the better definition and implementation of services to operators, and the collection and interpretation of data for establishing operational criteria relating the total meteorological inputs from the atmospheric sciences to the needs of aviation communities were addressed.

Meteorological and air pollution modeling for an urban airport

NASA Technical Reports Server (NTRS)

Swan, P. R.; Lee, I. Y.

1980-01-01

Results are presented of numerical experiments modeling meteorology, multiple pollutant sources, and nonlinear photochemical reactions for the case of an airport in a large urban area with complex terrain. A planetary boundary-layer model which predicts the mixing depth and generates wind, moisture, and temperature fields was used; it utilizes only surface and synoptic boundary conditions as input data. A version of the Hecht-Seinfeld-Dodge chemical kinetics model is integrated with a new, rapid numerical technique; both the San Francisco Bay Area Air Quality Management District source inventory and the San Jose Airport aircraft inventory are utilized. The air quality model results are presented in contour plots; the combined results illustrate that the highly nonlinear interactions which are present require that the chemistry and meteorology be considered simultaneously to make a valid assessment of the effects of individual sources on regional air quality.

Methodologies for evaluating performance and assessing uncertainty of atmospheric dispersion models

NASA Astrophysics Data System (ADS)

Chang, Joseph C.

This thesis describes methodologies to evaluate the performance and to assess the uncertainty of atmospheric dispersion models, tools that predict the fate of gases and aerosols upon their release into the atmosphere. Because of the large economic and public-health impacts often associated with the use of the dispersion model results, these models should be properly evaluated, and their uncertainty should be properly accounted for and understood. The CALPUFF, HPAC, and VLSTRACK dispersion modeling systems were applied to the Dipole Pride (DP26) field data (˜20 km in scale), in order to demonstrate the evaluation and uncertainty assessment methodologies. Dispersion model performance was found to be strongly dependent on the wind models used to generate gridded wind fields from observed station data. This is because, despite the fact that the test site was a flat area, the observed surface wind fields still showed considerable spatial variability, partly because of the surrounding mountains. It was found that the two components were comparable for the DP26 field data, with variability more important than uncertainty closer to the source, and less important farther away from the source. Therefore, reducing data errors for input meteorology may not necessarily increase model accuracy due to random turbulence. DP26 was a research-grade field experiment, where the source, meteorological, and concentration data were all well-measured. Another typical application of dispersion modeling is a forensic study where the data are usually quite scarce. An example would be the modeling of the alleged releases of chemical warfare agents during the 1991 Persian Gulf War, where the source data had to rely on intelligence reports, and where Iraq had stopped reporting weather data to the World Meteorological Organization since the 1981 Iran-Iraq-war. Therefore the meteorological fields inside Iraq must be estimated by models such as prognostic mesoscale meteorological models, based on observational data from areas outside of Iraq, and using the global fields simulated by the global meteorological models as the initial and boundary conditions for the mesoscale models. It was found that while comparing model predictions to observations in areas outside of Iraq, the predicted surface wind directions had errors between 30 to 90 deg, but the inter-model differences (or uncertainties) in the predicted surface wind directions inside Iraq, where there were no onsite data, were fairly constant at about 70 deg. (Abstract shortened by UMI.)

Dispersion modeling of accidental releases of toxic gases - utility for the fire brigades.

NASA Astrophysics Data System (ADS)

Stenzel, S.; Baumann-Stanzer, K.

2009-09-01

Several air dispersion models are available for prediction and simulation of the hazard areas associated with accidental releases of toxic gases. The most model packages (commercial or free of charge) include a chemical database, an intuitive graphical user interface (GUI) and automated graphical output for effective presentation of results. The models are designed especially for analyzing different accidental toxic release scenarios ("worst-case scenarios”), preparing emergency response plans and optimal countermeasures as well as for real-time risk assessment and management. The research project RETOMOD (reference scenarios calculations for toxic gas releases - model systems and their utility for the fire brigade) was conducted by the Central Institute for Meteorology and Geodynamics (ZAMG) in cooperation with the Viennese fire brigade, OMV Refining & Marketing GmbH and Synex Ries & Greßlehner GmbH. RETOMOD was funded by the KIRAS safety research program of the Austrian Ministry of Transport, Innovation and Technology (www.kiras.at). The main tasks of this project were 1. Sensitivity study and optimization of the meteorological input for modeling of the hazard areas (human exposure) during the accidental toxic releases. 2. Comparison of several model packages (based on reference scenarios) in order to estimate the utility for the fire brigades. For the purpose of our study the following models were tested and compared: ALOHA (Areal Location of Hazardous atmosphere, EPA), MEMPLEX (Keudel av-Technik GmbH), Trace (Safer System), Breeze (Trinity Consulting), SAM (Engineering office Lohmeyer). A set of reference scenarios for Chlorine, Ammoniac, Butane and Petrol were proceed, with the models above, in order to predict and estimate the human exposure during the event. Furthermore, the application of the observation-based analysis and forecasting system INCA, developed in the Central Institute for Meteorology and Geodynamics (ZAMG) in case of toxic release was investigated. INCA (Integrated Nowcasting through Comprehensive Analysis) data are calculated operationally with 1 km horizontal resolution and based on the weather forecast model ALADIN. The meteorological field's analysis with INCA include: Temperature, Humidity, Wind, Precipitation, Cloudiness and Global Radiation. In the frame of the project INCA data were compared with measurements from the meteorological observational network, conducted at traffic-near sites in Vienna. INCA analysis and very short term forecast fields (up to 6 hours) are found to be an advanced possibility to provide on-line meteorological input for the model package used by the fire brigade. Since the input requirements differ from model to model, and the outputs are based on unequal criteria for toxic area and exposure, a high degree of caution in the interpretation of the model results is required - especially in the case of slow wind speeds, stable atmospheric condition, and flow deflection by buildings in the urban area or by complex topography.

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.

Developing Predictive Models for Algal Bloom Occurrence and Identifying Factors Controlling their Occurrence in the Charlotte County and Surroundings

NASA Astrophysics Data System (ADS)

Karki, S.; Sultan, M.; Elkadiri, R.; Chouinard, K.

2017-12-01

Numerous occurrences of harmful algal blooms (Karenia Brevis) were reported from Southwest Florida along the coast of Charlotte County, Florida. We are developing data-driven (remote sensing, field, and meteorological data) models to accomplish the following: (1) identify the factors controlling bloom development, (2) forecast bloom occurrences, and (3) make recommendations for monitoring variables that are found to be most indicative of algal bloom occurrences and for identifying optimum locations for monitoring stations. To accomplish these three tasks we completed/are working on the following steps. Firstly, we developed an automatic system for downloading and processing of ocean color data acquired through MODIS Terra and MODIS Aqua products using SeaDAS ocean color processing software. Examples of extracted variables include: chlorophyll a (OC3M), chlorophyll a Generalized Inherent Optical Property (GIOP), chlorophyll a Garver-Siegel- Maritorena (GSM), sea surface temperature (SST), Secchi disk depth, euphotic depth, turbidity index, wind direction and speed, colored dissolved organic material (CDOM). Secondly we are developing a GIS database and a web-based GIS to host the generated remote sensing-based products in addition to relevant meteorological and field data. Examples of the meteorological and field inputs include: precipitation amount and rates, concentrations of nitrogen, phosphorous, fecal coliform and Dissolved Oxygen (DO). Thirdly, we are constructing and validating a multivariate regression model and an artificial neural network model to simulate past algal bloom occurrences using the compiled archival remote sensing, meteorological, and field data. The validated model will then be used to predict the timing and location of algal bloom occurrences. The developed system, upon completion, could enhance the decision making process, improve the citizen's quality of life, and strengthen the local economy.

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

EVALUATING THE USE OF OUTPUTS FROM COMPREHENSIVE METEOROLOGICAL MODELS IN AIR QUALITY MODELING APPLICATIONS

EPA Science Inventory

Currently used dispersion models, such as the AMS/EPA Regulatory Model (AERMOD), process routinely available meteorological observations to construct model inputs. Thus, model estimates of concentrations depend on the availability and quality of Meteorological observations, as we...

Propagation of hydro-meteorological uncertainty in a model cascade framework to inundation prediction

NASA Astrophysics Data System (ADS)

Rodríguez-Rincón, J. P.; Pedrozo-Acuña, A.; Breña-Naranjo, J. A.

2015-07-01

This investigation aims to study the propagation of meteorological uncertainty within a cascade modelling approach to flood prediction. The methodology was comprised of a numerical weather prediction (NWP) model, a distributed rainfall-runoff model and a 2-D hydrodynamic model. The uncertainty evaluation was carried out at the meteorological and hydrological levels of the model chain, which enabled the investigation of how errors that originated in the rainfall prediction interact at a catchment level and propagate to an estimated inundation area and depth. For this, a hindcast scenario is utilised removing non-behavioural ensemble members at each stage, based on the fit with observed data. At the hydrodynamic level, an uncertainty assessment was not incorporated; instead, the model was setup following guidelines for the best possible representation of the case study. The selected extreme event corresponds to a flood that took place in the southeast of Mexico during November 2009, for which field data (e.g. rain gauges; discharge) and satellite imagery were available. Uncertainty in the meteorological model was estimated by means of a multi-physics ensemble technique, which is designed to represent errors from our limited knowledge of the processes generating precipitation. In the hydrological model, a multi-response validation was implemented through the definition of six sets of plausible parameters from past flood events. Precipitation fields from the meteorological model were employed as input in a distributed hydrological model, and resulting flood hydrographs were used as forcing conditions in the 2-D hydrodynamic model. The evolution of skill within the model cascade shows a complex aggregation of errors between models, suggesting that in valley-filling events hydro-meteorological uncertainty has a larger effect on inundation depths than that observed in estimated flood inundation extents.

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.

Evaluation of a regional assimilation system coupled with the WRF-chem model

NASA Astrophysics Data System (ADS)

Liu, Yan-an; Gao, Wei; Huang, Hung-lung; Strabala, Kathleen; Liu, Chaoshun; Shi, Runhe

2013-09-01

Air quality has become a social issue that is causing great concern to humankind across the globe, but particularly in developing countries. Even though the Weather Research and Forecasting with Chemistry (WRF-Chem) model has been applied in many regions, the resolution for inputting meteorology field analysis still impacts the accuracy of forecast. This article describes the application of the CIMSS Regional Assimilation System (CRAS) in East China, and its capability to assimilate the direct broadcast (DB) satellite data for obtaining more detailed meteorological information, including cloud top pressure (CTP) and total precipitation water (TPW) from MODIS. Performance evaluation of CRAS is based on qualitative and quantitative analyses. Compared with data collected from ERA-Interim, Radiosonde, and the Tropical Rainfall Measuring Mission (TRMM) precipitation measurements using bias and Root Mean Square Error (RMSE), CRAS has a systematic error due to the impact of topography and other factors; however, the forecast accuracy of all elements in the model center area is higher at various levels. The bias computed with Radiosonde reveals that the temperature and geopotential height of CRAS are better than ERA-Interim at first guess. Moreover, the location of the 24 h accumulated precipitation forecast are highly consistent with the TRMM retrieval precipitation, which means that the performance of CRAS is excellent. In summation, the newly built Vtable can realize the function of inputting the meteorology field from CRAS output into WRF, which couples the CRAS with WRF-Chem. Therefore, this study not only provides for forecast accuracy of CRAS, but also increases the capability of running the WRF-Chem model at higher resolutions in the future.

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.

Improvement of Meteorological Inputs for TexAQS-II Air Quality Simulations

NASA Astrophysics Data System (ADS)

Ngan, F.; Byun, D.; Kim, H.; Cheng, F.; Kim, S.; Lee, D.

2008-12-01

An air quality forecasting system (UH-AQF) for Eastern Texas, which is in operation by the Institute for Multidimensional Air Quality Studies (IMAQS) at the University of Houston, uses the Fifth-Generation PSU/NCAR Mesoscale Model MM5 model as the meteorological driver for modeling air quality with the Community Multiscale Air Quality (CMAQ) model. While the forecasting system was successfully used for the planning and implementation of various measurement activities, evaluations of the forecasting results revealed a few systematic problems in the numerical simulations. From comparison with observations, we observe some times over-prediction of northerly winds caused by inaccurate synoptic inputs and other times too strong southerly winds caused by local sea breeze development. Discrepancies in maximum and minimum temperature are also seen for certain days. Precipitation events, as well as clouds, are simulated at the incorrect locations and times occasionally. Model simulatednrealistic thunderstorms are simulated, causing sometimes cause unrealistically strong outflows. To understand physical and chemical processes influencing air quality measures, a proper description of real world meteorological conditions is essential. The objective of this study is to generate better meteorological inputs than the AQF results to support the chemistry modeling. We utilized existing objective analysis and nudging tools in the MM5 system to develop the MUltiscale Nest-down Data Assimilation System (MUNDAS), which incorporates extensive meteorological observations available in the simulated domain for the retrospective simulation of the TexAQS-II period. With the re-simulated meteorological input, we are able to better predict ozone events during TexAQS-II period. In addition, base datasets in MM5 such as land use/land cover, vegetation fraction, soil type and sea surface temperature are updated by satellite data to represent the surface features more accurately. They are key physical parameters inputs affecting transfer of heat, momentum and soil moisture in land-surface process in MM5. Using base the accurate input datasets, we are able to have improved see the differences of predictions of ground temperatures, winds and even thunderstorm activities within boundary layer.

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...

Selecting Meteorological Input for the Global Modeling Initiative Assessments

NASA Technical Reports Server (NTRS)

Strahan, Susan; Douglass, Anne; Prather, Michael; Coy, Larry; Hall, Tim; Rasch, Phil; Sparling, Lynn

1999-01-01

The Global Modeling Initiative (GMI) science team has developed a three dimensional chemistry and transport model (CTM) to evaluate the impact of the exhaust of supersonic aircraft on the stratosphere. An important goal of the GMI is to test modules for numerical transport, photochemical integration, and model dynamics within a common framework. This work is focussed on the dependence of the overall assessment on the wind and temperature fields used by the CTM. Three meteorological data sets for the stratosphere were available to GMI: the National Center for Atmospheric Research Community Climate Model (CCM2), the Goddard Earth Observing System Data Assimilation System (GEOS-DAS), and the Goddard Institute for Space Studies general circulation model (GISS-2'). Objective criteria were established by the GMI team to evaluate which of these three data sets provided the best representation of trace gases in the stratosphere today. Tracer experiments were devised to test various aspects of model transport. Stratospheric measurements of long-lived trace gases were selected as a test of the CTM transport. This presentation describes the criteria used in grading the meteorological fields and the resulting choice of wind fields to be used in the GMI assessment. This type of objective model evaluation will lead to a higher level of confidence in these assessments. We suggest that the diagnostic tests shown here be used to augment traditional general circulation model evaluation methods.

Calculating distributed glacier mass balance for the Swiss Alps from RCM output: Development and testing of downscaling and validation methods

NASA Astrophysics Data System (ADS)

Machguth, H.; Paul, F.; Kotlarski, S.; Hoelzle, M.

2009-04-01

Climate model output has been applied in several studies on glacier mass balance calculation. Hereby, computation of mass balance has mostly been performed at the native resolution of the climate model output or data from individual cells were selected and statistically downscaled. Little attention has been given to the issue of downscaling entire fields of climate model output to a resolution fine enough to compute glacier mass balance in rugged high-mountain terrain. In this study we explore the use of gridded output from a regional climate model (RCM) to drive a distributed mass balance model for the perimeter of the Swiss Alps and the time frame 1979-2003. Our focus lies on the development and testing of downscaling and validation methods. The mass balance model runs at daily steps and 100 m spatial resolution while the RCM REMO provides daily grids (approx. 18 km resolution) of dynamically downscaled re-analysis data. Interpolation techniques and sub-grid parametrizations are combined to bridge the gap in spatial resolution and to obtain daily input fields of air temperature, global radiation and precipitation. The meteorological input fields are compared to measurements at 14 high-elevation weather stations. Computed mass balances are compared to various sets of direct measurements, including stake readings and mass balances for entire glaciers. The validation procedure is performed separately for annual, winter and summer balances. Time series of mass balances for entire glaciers obtained from the model run agree well with observed time series. On the one hand, summer melt measured at stakes on several glaciers is well reproduced by the model, on the other hand, observed accumulation is either over- or underestimated. It is shown that these shifts are systematic and correlated to regional biases in the meteorological input fields. We conclude that the gap in spatial resolution is not a large drawback, while biases in RCM output are a major limitation to model performance. The development and testing of methods to reduce regionally variable biases in entire fields of RCM output should be a focus of pursuing studies.

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

Meteorological Processors and Accessory Programs

EPA Pesticide Factsheets

Surface and upper air data, provided by NWS, are important inputs for air quality models. Before these data are used in some of the EPA dispersion models, meteorological processors are used to manipulate the data.

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).

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

Satellite data based approach for the estimation of anthropogenic heat flux over urban areas

NASA Astrophysics Data System (ADS)

Nitis, Theodoros; Tsegas, George; Moussiopoulos, Nicolas; Gounaridis, Dimitrios; Bliziotis, Dimitrios

2017-09-01

Anthropogenic effects in urban areas influence the thermal conditions in the environment and cause an increase of the atmospheric temperature. The cities are sources of heat and pollution, affecting the thermal structure of the atmosphere above them which results to the urban heat island effect. In order to analyze the urban heat island mechanism, it is important to estimate the anthropogenic heat flux which has a considerable impact on the urban energy budget. The anthropogenic heat flux is the result of man-made activities (i.e. traffic, industrial processes, heating/cooling) and thermal releases from the human body. Many studies have underlined the importance of the Anthropogenic Heat Flux to the calculation of the urban energy budget and subsequently, the estimation of mesoscale meteorological fields over urban areas. Therefore, spatially disaggregated anthropogenic heat flux data, at local and city scales, are of major importance for mesoscale meteorological models. The main objectives of the present work are to improve the quality of such data used as input for mesoscale meteorological models simulations and to enhance the application potential of GIS and remote sensing in the fields of climatology and meteorology. For this reason, the Urban Energy Budget concept is proposed as the foundation for an accurate determination of the anthropogenic heat discharge as a residual term in the surface energy balance. The methodology is applied to the cities of Athens and Paris using the Landsat ETM+ remote sensing data. The results will help to improve our knowledge on Anthropogenic Heat Flux, while the potential for further improvement of the methodology is also discussed.

Surface Meteorology, Barrow, Alaska, Area A, B, C and D, Ongoing from 2012

DOE Data Explorer

Bob Busey; Larry Hinzman; William Cable; Vladimir Romanovsky

2014-12-04

Meteorological data are being collected at several points within four intensive study areas in Barrow. These data assist in the calculation of the energy balance at the land surface and are also useful as inputs into modeling activities.

Determination of the optimal training principle and input variables in artificial neural network model for the biweekly chlorophyll-a prediction: a case study of the Yuqiao Reservoir, China.

PubMed

Liu, Yu; Xi, Du-Gang; Li, Zhao-Liang

2015-01-01

Predicting the levels of chlorophyll-a (Chl-a) is a vital component of water quality management, which ensures that urban drinking water is safe from harmful algal blooms. This study developed a model to predict Chl-a levels in the Yuqiao Reservoir (Tianjin, China) biweekly using water quality and meteorological data from 1999-2012. First, six artificial neural networks (ANNs) and two non-ANN methods (principal component analysis and the support vector regression model) were compared to determine the appropriate training principle. Subsequently, three predictors with different input variables were developed to examine the feasibility of incorporating meteorological factors into Chl-a prediction, which usually only uses water quality data. Finally, a sensitivity analysis was performed to examine how the Chl-a predictor reacts to changes in input variables. The results were as follows: first, ANN is a powerful predictive alternative to the traditional modeling techniques used for Chl-a prediction. The back program (BP) model yields slightly better results than all other ANNs, with the normalized mean square error (NMSE), the correlation coefficient (Corr), and the Nash-Sutcliffe coefficient of efficiency (NSE) at 0.003 mg/l, 0.880 and 0.754, respectively, in the testing period. Second, the incorporation of meteorological data greatly improved Chl-a prediction compared to models solely using water quality factors or meteorological data; the correlation coefficient increased from 0.574-0.686 to 0.880 when meteorological data were included. Finally, the Chl-a predictor is more sensitive to air pressure and pH compared to other water quality and meteorological variables.

Impact of inherent meteorology uncertainty on air quality model predictions

EPA Science Inventory

It is well established that there are a number of different classifications and sources of uncertainties in environmental modeling systems. Air quality models rely on two key inputs, namely, meteorology and emissions. When using air quality models for decision making, it is impor...

Human-model hybrid Korean air quality forecasting system.

PubMed

Chang, Lim-Seok; Cho, Ara; Park, Hyunju; Nam, Kipyo; Kim, Deokrae; Hong, Ji-Hyoung; Song, Chang-Keun

2016-09-01

The Korean national air quality forecasting system, consisting of the Weather Research and Forecasting, the Sparse Matrix Operator Kernel Emissions, and the Community Modeling and Analysis (CMAQ), commenced from August 31, 2013 with target pollutants of particulate matters (PM) and ozone. Factors contributing to PM forecasting accuracy include CMAQ inputs of meteorological field and emissions, forecasters' capacity, and inherent CMAQ limit. Four numerical experiments were conducted including two global meteorological inputs from the Global Forecast System (GFS) and the Unified Model (UM), two emissions from the Model Intercomparison Study Asia (MICS-Asia) and the Intercontinental Chemical Transport Experiment (INTEX-B) for the Northeast Asia with Clear Air Policy Support System (CAPSS) for South Korea, and data assimilation of the Monitoring Atmospheric Composition and Climate (MACC). Significant PM underpredictions by using both emissions were found for PM mass and major components (sulfate and organic carbon). CMAQ predicts PM2.5 much better than PM10 (NMB of PM2.5: -20~-25%, PM10: -43~-47%). Forecasters' error usually occurred at the next day of high PM event. Once CMAQ fails to predict high PM event the day before, forecasters are likely to dismiss the model predictions on the next day which turns out to be true. The best combination of CMAQ inputs is the set of UM global meteorological field, MICS-Asia and CAPSS 2010 emissions with the NMB of -12.3%, the RMSE of 16.6μ/m(3) and the R(2) of 0.68. By using MACC data as an initial and boundary condition, the performance skill of CMAQ would be improved, especially in the case of undefined coarse emission. A variety of methods such as ensemble and data assimilation are considered to improve further the accuracy of air quality forecasting, especially for high PM events to be comparable to for all cases. The growing utilization of the air quality forecast induced the public strongly to demand that the accuracy of the national forecasting be improved. In this study, we investigated the problems in the current forecasting as well as various alternatives to solve the problems. Such efforts to improve the accuracy of the forecast are expected to contribute to the protection of public health by increasing the availability of the forecast system.

Choosing Meteorological Input for the Global Modeling Initiative Assessment of High Speed Aircraft

NASA Technical Reports Server (NTRS)

Douglas, A. R.; Prather, M. P.; Hall, T. M.; Strahan, S. E.; Rasch, P. J.; Sparling, L. C.; Coy, L.; Rodriquez, J. M.

1998-01-01

The Global Modeling Initiative (GMI) science team is developing a three dimensional chemistry and transport model (CTM) to be used in assessment of the atmospheric effects of aviation. Requirements are that this model be documented, be validated against observations, use a realistic atmospheric circulation, and contain numerical transport and photochemical modules representing atmospheric processes. The model must also retain computational efficiency to be tractable to use for multiple scenarios and sensitivity studies. To meet these requirements, a facility model concept was developed in which the different components of the CTM are evaluated separately. The first use of the GMI model will be to evaluate the impact of the exhaust of supersonic aircraft on the stratosphere. The assessment calculations will depend strongly on the wind and temperature fields used by the CTM. Three meteorological data sets for the stratosphere are available to GMI: the National Center for Atmospheric Research Community Climate Model (CCM2), the Goddard Earth Observing System Data Assimilation System (GEOS DAS), and the Goddard Institute for Space Studies general circulation model (GISS). Objective criteria were established by the GMI team to identify the data set which provides the best representation of the stratosphere. Simulations of gases with simple chemical control were chosen to test various aspects of model transport. The three meteorological data sets were evaluated and graded based on their ability to simulate these aspects of stratospheric measurements. This paper describes the criteria used in grading the meteorological fields. The meteorological data set which has the highest score and therefore was selected for GMI is CCM2. This type of objective model evaluation establishes a physical basis for interpretation of differences between models and observations. Further, the method provides a quantitative basis for defining model errors, for discriminating between different models, and for ready re-evaluation of improved models. These in turn will lead to a higher level of confidence in assessment calculations.

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.

VALDRIFT 1.0: A valley atmospheric dispersion model with deposition

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

Allwine, K.J.; Bian, X.; Whiteman, C.D.

1995-05-01

VALDRIFT version 1.0 is an atmospheric transport and diffusion model for use in well-defined mountain valleys. It is designed to determine the extent of ddft from aedal pesticide spraying activities, but can also be applied to estimate the transport and diffusion of various air pollutants in valleys. The model is phenomenological -- that is, the dominant meteorological processes goveming the behavior of the valley atmosphere are formulated explicitly in the model, albeit in a highly parameterized fashion. The key meteorological processes treated are: (1) nonsteady and nonhomogeneous along-valley winds and turbulent diffusivities, (2) convective boundary layer growth, (3) inversion descent,more » (4) noctumal temperature inversion breakup, and (5) subsidence. The model is applicable under relatively cloud-free, undisturbed synoptic conditions and is configured to operate through one diumal cycle for a single valley. The inputs required are the valley topographical characteristics, pesticide release rate as a function of time and space, along-valley wind speed as a function of time and space, temperature inversion characteristics at sunrise, and sensible heat flux as a function of time following sunrise. Default values are provided for certain inputs in the absence of detailed observations. The outputs are three-dimensional air concentration and ground-level deposition fields as a function of time.« less

Proceedings: Third Annual Workshop on Meteorological and Environmental Inputs to Aviation Systems

NASA Technical Reports Server (NTRS)

Camp, D. W. (Editor); Frost, W. (Editor)

1979-01-01

The proceedings of a workshop on meteorological and environmental inputs to aviation systems are reported. The major objectives of the workshop are to satisfy such needs of the sponsoring agencies as the expansion of our understanding and knowledge of the interaction of the atmosphere with aviation systems, the better definition and implementation of services to operators, and the collection and interpretation of data for establishing operational criteria, relating the total meteorological inputs from the atmospheric sciences to the needs of aviation communities. The unique aspect of the workshop was the achievement of communication across the interface of the boundaries between pilots, meteorologists, training personnel, accident investigators, traffic controllers, flight operation personnel from military, civil, general aviation, and commercial interests alike. Representatives were in attendance from government, airlines, private agencies, aircraft manufacturers, Department of Defense, industries, research institutes, and universities. Full-length papers addressed the topics of training, flight operations, accident investigation, air traffic control, and airports. Winds and wind shear; icing and frost; atmospheric electricity and lightning; fog, visibility and ceilings; and turbulence were discussed.

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.

An Evaluation System for the Online Training Programs in Meteorology and Hydrology

ERIC Educational Resources Information Center

Wang, Yong; Zhi, Xiefei

2009-01-01

This paper studies the current evaluation system for the online training program in meteorology and hydrology. CIPP model that includes context evaluation, input evaluation, process evaluation and product evaluation differs from Kirkpatrick model including reactions evaluation, learning evaluation, transfer evaluation and results evaluation in…

NASA Earth Science Research Results for Improved Regional Crop Yield Prediction

NASA Astrophysics Data System (ADS)

Mali, P.; O'Hara, C. G.; Shrestha, B.; Sinclair, T. R.; G de Goncalves, L. G.; Salado Navarro, L. R.

2007-12-01

National agencies such as USDA Foreign Agricultural Service (FAS), Production Estimation and Crop Assessment Division (PECAD) work specifically to analyze and generate timely crop yield estimates that help define national as well as global food policies. The USDA/FAS/PECAD utilizes a Decision Support System (DSS) called CADRE (Crop Condition and Data Retrieval Evaluation) mainly through an automated database management system that integrates various meteorological datasets, crop and soil models, and remote sensing data; providing significant contribution to the national and international crop production estimates. The "Sinclair" soybean growth model has been used inside CADRE DSS as one of the crop models. This project uses Sinclair model (a semi-mechanistic crop growth model) for its potential to be effectively used in a geo-processing environment with remote-sensing-based inputs. The main objective of this proposed work is to verify, validate and benchmark current and future NASA earth science research results for the benefit in the operational decision making process of the PECAD/CADRE DSS. For this purpose, the NASA South American Land Data Assimilation System (SALDAS) meteorological dataset is tested for its applicability as a surrogate meteorological input in the Sinclair model meteorological input requirements. Similarly, NASA sensor MODIS products is tested for its applicability in the improvement of the crop yield prediction through improving precision of planting date estimation, plant vigor and growth monitoring. The project also analyzes simulated Visible/Infrared Imager/Radiometer Suite (VIIRS, a future NASA sensor) vegetation product for its applicability in crop growth prediction to accelerate the process of transition of VIIRS research results for the operational use of USDA/FAS/PECAD DSS. The research results will help in providing improved decision making capacity to the USDA/FAS/PECAD DSS through improved vegetation growth monitoring from high spatial and temporal resolution remote sensing datasets; improved time-series meteorological inputs required for crop growth models; and regional prediction capability through geo-processing-based yield modeling.

Improved assessment of gross and net primary productivity of Canada's landmass

NASA Astrophysics Data System (ADS)

Gonsamo, Alemu; Chen, Jing M.; Price, David T.; Kurz, Werner A.; Liu, Jane; Boisvenue, Céline; Hember, Robbie A.; Wu, Chaoyang; Chang, Kuo-Hsien

2013-12-01

assess Canada's gross primary productivity (GPP) and net primary productivity (NPP) using boreal ecosystem productivity simulator (BEPS) at 250 m spatial resolution with improved input parameter and driver fields and phenology and nutrient release parameterization schemes. BEPS is a process-based two-leaf enzyme kinetic terrestrial ecosystem model designed to simulate energy, water, and carbon (C) fluxes using spatial data sets of meteorology, remotely sensed land surface variables, soil properties, and photosynthesis and respiration rate parameters. Two improved key land surface variables, leaf area index (LAI) and land cover type, are derived at 250 m from Moderate Resolution Imaging Spectroradiometer sensor. For diagnostic error assessment, we use nine forest flux tower sites where all measured C flux, meteorology, and ancillary data sets are available. The errors due to input drivers and parameters are then independently corrected for Canada-wide GPP and NPP simulations. The optimized LAI use, for example, reduced the absolute bias in GPP from 20.7% to 1.1% for hourly BEPS simulations. Following the error diagnostics and corrections, daily GPP and NPP are simulated over Canada at 250 m spatial resolution, the highest resolution simulation yet for the country or any other comparable region. Total NPP (GPP) for Canada's land area was 1.27 (2.68) Pg C for 2008, with forests contributing 1.02 (2.2) Pg C. The annual comparisons between measured and simulated GPP show that the mean differences are not statistically significant (p > 0.05, paired t test). The main BEPS simulation error sources are from the driver fields.

How sensitive are estimates of carbon fixation in agricultural models to input data?

PubMed Central

2012-01-01

Background Process based vegetation models are central to understand the hydrological and carbon cycle. To achieve useful results at regional to global scales, such models require various input data from a wide range of earth observations. Since the geographical extent of these datasets varies from local to global scale, data quality and validity is of major interest when they are chosen for use. It is important to assess the effect of different input datasets in terms of quality to model outputs. In this article, we reflect on both: the uncertainty in input data and the reliability of model results. For our case study analysis we selected the Marchfeld region in Austria. We used independent meteorological datasets from the Central Institute for Meteorology and Geodynamics and the European Centre for Medium-Range Weather Forecasts (ECMWF). Land cover / land use information was taken from the GLC2000 and the CORINE 2000 products. Results For our case study analysis we selected two different process based models: the Environmental Policy Integrated Climate (EPIC) and the Biosphere Energy Transfer Hydrology (BETHY/DLR) model. Both process models show a congruent pattern to changes in input data. The annual variability of NPP reaches 36% for BETHY/DLR and 39% for EPIC when changing major input datasets. However, EPIC is less sensitive to meteorological input data than BETHY/DLR. The ECMWF maximum temperatures show a systematic pattern. Temperatures above 20°C are overestimated, whereas temperatures below 20°C are underestimated, resulting in an overall underestimation of NPP in both models. Besides, BETHY/DLR is sensitive to the choice and accuracy of the land cover product. Discussion This study shows that the impact of input data uncertainty on modelling results need to be assessed: whenever the models are applied under new conditions, local data should be used for both input and result comparison. PMID:22296931

DMSP observations of high latitude Poynting flux during magnetic storms

NASA Astrophysics Data System (ADS)

Huang, Cheryl Y.; Huang, Yanshi; Su, Yi-Jiun; Hairston, Marc R.; Sotirelis, Thomas

2017-11-01

Previous studies have demonstrated that energy can enter the high-latitude regions of the Ionosphere-Thermosphere (IT) system on open field lines. To assess the extent of high-latitude energy input, we have carried out a study of Poynting flux measured by the Defense Meteorological Satellite Program (DMSP) satellites during magnetic storms. We report sporadic intense Poynting fluxes measured by four DMSP satellites at polar latitudes during two moderate magnetic storms which occurred in August and September 2011. Comparisons with a widely used empirical model for energy input to the IT system show that the model does not adequately capture electromagnetic (EM) energy at very high latitudes during storms. We have extended this study to include more than 30 storm events and find that intense EM energy is frequently detected poleward of 75° magnetic latitude.

Improving fungal disease forecasts in winter wheat: a critical role of intra-day variations of meteorological conditions

USDA-ARS?s Scientific Manuscript database

Meteorological conditions are important factors in the development of fungal diseases in winter wheat and are the main inputs of the decision support systems used to forecast disease and thus determine timing for efficacious fungicide application. This study uses the Fourier transform method (FTM) t...

Improving of local ozone forecasting by integrated models.

PubMed

Gradišar, Dejan; Grašič, Boštjan; Božnar, Marija Zlata; Mlakar, Primož; Kocijan, Juš

2016-09-01

This paper discuss the problem of forecasting the maximum ozone concentrations in urban microlocations, where reliable alerting of the local population when thresholds have been surpassed is necessary. To improve the forecast, the methodology of integrated models is proposed. The model is based on multilayer perceptron neural networks that use as inputs all available information from QualeAria air-quality model, WRF numerical weather prediction model and onsite measurements of meteorology and air pollution. While air-quality and meteorological models cover large geographical 3-dimensional space, their local resolution is often not satisfactory. On the other hand, empirical methods have the advantage of good local forecasts. In this paper, integrated models are used for improved 1-day-ahead forecasting of the maximum hourly value of ozone within each day for representative locations in Slovenia. The WRF meteorological model is used for forecasting meteorological variables and the QualeAria air-quality model for gas concentrations. Their predictions, together with measurements from ground stations, are used as inputs to a neural network. The model validation results show that integrated models noticeably improve ozone forecasts and provide better alert systems.

Anvil Forecast Tool in the Advanced Weather Interactive Processing System, Phase II

NASA Technical Reports Server (NTRS)

Barrett, Joe H., III

2008-01-01

Meteorologists from the 45th Weather Squadron (45 WS) and Spaceflight Meteorology Group have identified anvil forecasting as one of their most challenging tasks when predicting the probability of violations of the Lightning Launch Commit Criteria and Space Light Rules. As a result, the Applied Meteorology Unit (AMU) created a graphical overlay tool for the Meteorological Interactive Data Display Systems (MIDDS) to indicate the threat of thunderstorm anvil clouds, using either observed or model forecast winds as input.

Spatial interpolation of hourly precipitation and dew point temperature for the identification of precipitation phase and hydrologic response in a mountainous catchment

NASA Astrophysics Data System (ADS)

Garen, D. C.; Kahl, A.; Marks, D. G.; Winstral, A. H.

2012-12-01

In mountainous catchments, it is well known that meteorological inputs, such as precipitation, air temperature, humidity, etc. vary greatly with elevation, spatial location, and time. Understanding and monitoring catchment inputs is necessary in characterizing and predicting hydrologic response to these inputs. This is true all of the time, but it is the most dramatically critical during large storms, when the input to the stream system due to rain and snowmelt creates the potential for flooding. Besides such crisis events, however, proper estimation of catchment inputs and their spatial distribution is also needed in more prosaic but no less important water and related resource management activities. The first objective of this study is to apply a geostatistical spatial interpolation technique (elevationally detrended kriging) to precipitation and dew point temperature on an hourly basis and explore its characteristics, accuracy, and other issues. The second objective is to use these spatial fields to determine precipitation phase (rain or snow) during a large, dynamic winter storm. The catchment studied is the data-rich Reynolds Creek Experimental Watershed near Boise, Idaho. As part of this analysis, precipitation-elevation lapse rates are examined for spatial and temporal consistency. A clear dependence of lapse rate on precipitation amount exists. Certain stations, however, are outliers from these relationships, showing that significant local effects can be present and raising the question of whether such stations should be used for spatial interpolation. Experiments with selecting subsets of stations demonstrate the importance of elevation range and spatial placement on the interpolated fields. Hourly spatial fields of precipitation and dew point temperature are used to distinguish precipitation phase during a large rain-on-snow storm in December 2005. This application demonstrates the feasibility of producing hourly spatial fields and the importance of doing so to support an accurate determination of precipitation phase for assessing catchment hydrologic response to the storm.

Quality assurance of weather data for agricultural system model input

USDA-ARS?s Scientific Manuscript database

It is well known that crop production and hydrologic variation on watersheds is weather related. Rarely, however, is meteorological data quality checks reported for agricultural systems model research. We present quality assurance procedures for agricultural system model weather data input. Problems...

A globally calibrated scheme for generating daily meteorology from monthly statistics: Global-WGEN (GWGEN) v1.0

NASA Astrophysics Data System (ADS)

Sommer, Philipp S.; Kaplan, Jed O.

2017-10-01

While a wide range of Earth system processes occur at daily and even subdaily timescales, many global vegetation and other terrestrial dynamics models historically used monthly meteorological forcing both to reduce computational demand and because global datasets were lacking. Recently, dynamic land surface modeling has moved towards resolving daily and subdaily processes, and global datasets containing daily and subdaily meteorology have become available. These meteorological datasets, however, cover only the instrumental era of the last approximately 120 years at best, are subject to considerable uncertainty, and represent extremely large data files with associated computational costs of data input/output and file transfer. For periods before the recent past or in the future, global meteorological forcing can be provided by climate model output, but the quality of these data at high temporal resolution is low, particularly for daily precipitation frequency and amount. Here, we present GWGEN, a globally applicable statistical weather generator for the temporal downscaling of monthly climatology to daily meteorology. Our weather generator is parameterized using a global meteorological database and simulates daily values of five common variables: minimum and maximum temperature, precipitation, cloud cover, and wind speed. GWGEN is lightweight, modular, and requires a minimal set of monthly mean variables as input. The weather generator may be used in a range of applications, for example, in global vegetation, crop, soil erosion, or hydrological models. While GWGEN does not currently perform spatially autocorrelated multi-point downscaling of daily weather, this additional functionality could be implemented in future versions.

Preliminary validation of WRF model in two Arctic fjords, Hornsund and Porsanger

NASA Astrophysics Data System (ADS)

Aniskiewicz, Paulina; Stramska, Małgorzata

2017-04-01

Our research is focused on development of efficient modeling system for arctic fjords. This tool should include high-resolution meteorological data derived using downscaling approach. In this presentation we have focused on modeling, with high spatial resolution, of the meteorological conditions in two Arctic fjords: Hornsund (H), located in the western part of Svalbard archipelago and Porsanger (P) located in the coastal waters of the Barents Sea. The atmospheric downscaling is based on The Weather Research and Forecasting Model (WRF, www.wrf-model.org) with polar stereographic projection. We have created two parent domains with grid point distances of about 3.2 km (P) and 3.0 km (H) and with nested domains (almost 5 times higher resolution than parent domains). We tested what is the impact of the spatial resolution of the model on derived meteorological quantities. For both fjords the input topography data resolution is 30 sec. To validate the results we have used meteorological data from the Norwegian Meteorological Institute for stations Lakselv (L) and Honningsvåg (Ho) located in the inner and outer parts of the Porsanger fjord as well as from station in the outer part of the Hornsund fjord. We have estimated coefficients of determination (r2), statistical errors (St) and systematic errors (Sy) between measured and modelled air temperature and wind speed at each station. This approach will allow us to create high resolution spatially variable meteorological fields that will serve as forcing for numerical models of the fjords. We will investigate the role of different meteorological quantities (e. g. wind, solar insolation, precipitation) on hydrohraphic processes in fjords. The project has been financed from the funds of the Leading National Research Centre (KNOW) received by the Centre for Polar Studies for the period 2014-2018. This work was also funded by the Norway Grants (NCBR contract No. 201985, project NORDFLUX). Partial support comes from the Institute of Oceanology (IO PAN).

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...

Sensitivity and uncertainty of input sensor accuracy for grass-based reference evapotranspiration

USDA-ARS?s Scientific Manuscript database

Quantification of evapotranspiration (ET) in agricultural environments is becoming of increasing importance throughout the world, thus understanding input variability of relevant sensors is of paramount importance as well. The Colorado Agricultural and Meteorological Network (CoAgMet) and the Florid...

Global meteorological data facility for real-time field experiments support and guidance

NASA Technical Reports Server (NTRS)

Shipham, Mark C.; Shipley, Scott T.; Trepte, Charles R.

1988-01-01

A Global Meteorological Data Facility (GMDF) has been constructed to provide economical real-time meteorological support to atmospheric field experiments. After collection and analysis of meteorological data sets at a central station, tailored meteorological products are transmitted to experiment field sites using conventional ground link or satellite communication techniques. The GMDF supported the Global Tropospheric Experiment Amazon Boundary Layer Experiment (GTE-ABLE II) based in Manaus, Brazil, during July and August 1985; an arctic airborne lidar survey mission for the Polar Stratospheric Clouds (PSC) experiment during January 1986; and the Genesis of Atlantic Lows Experiment (GALE) during January, February and March 1986. GMDF structure is similar to the UNIDATA concept, including meteorological data from the Zephyr Weather Transmission Service, a mode AAA GOES downlink, and dedicated processors for image manipulation, transmission and display. The GMDF improved field experiment operations in general, with the greatest benefits arising from the ability to communicate with field personnel in real time.

The model SIRANE for atmospheric urban pollutant dispersion. PART III: Validation against NO2 yearly concentration measurements in a large urban agglomeration

NASA Astrophysics Data System (ADS)

Soulhac, L.; Nguyen, C. V.; Volta, P.; Salizzoni, P.

2017-10-01

We present a validation study of an updated version of the SIRANE model, whose results have been systematically compared to concentrations of nitrogen dioxide collected over the whole urban agglomeration of Lyon. We model atmospheric dispersion of nitrogen oxides emitted by road traffic, industries and domestic heating. The meteorological wind field is computed by a pre-processor using data collected at a ground level monitoring station. Model results are compared with hourly concentrations measured at 15 monitoring stations over the whole year (2008). Further 75 passive diffusion samplers were used during 3 periods of 2 weeks to get a detailed spatial distribution over the west part of the city. An analysis of the model results depending on the variability of the meteorological input allows us to identify the causes for peculiar bad performances of the model and to identify possible improvements of the parameterisations implemented in it.

Utility of a Two-source Energy Balance Approach for Daily Mapping of Landsat-scale Fluxes Over Irrigated Agriculture in a Desert Environment

NASA Astrophysics Data System (ADS)

Houborg, R.; McCabe, M. F.; Rosas Aguilar, J.; Anderson, M. C.; Hain, C.

2014-12-01

The Middle East and North Africa (MENA) region is an area characterized by limited fresh water resources, an often inefficient use of these, and relatively poor in-situ monitoring as a result of sparse meteorological observations. Enhanced satellite-based monitoring systems are needed for aiding local water resource and agricultural management activities in these data poor arid environments. A multi-sensor and multi-scale land-surface flux monitoring capacity is being implemented over parts of MENA in order to provide meaningful decision support at relevant spatiotemporal scales. The integrated modeling system uses the Atmosphere-Land Exchange Inverse (ALEXI) model and associated flux disaggregation scheme (DisALEXI), and the Spatial and Temporal Adaptive Reflectance Fusion Model (STARFM) in conjunction with model reanalysis data and remotely sensed data from polar orbiting (Landsat and MODIS; MODerate resolution Imaging Spectroradiometer) and geostationary (MSG; Meteosat Second Generation) satellite platforms to facilitate daily estimates of land surface fluxes down to sub-field scale (i.e. 30 m). Within this modeling system, thermal infrared satellite data provide information about the sub-surface moisture status and plant stress, obviating the need for precipitation input and error-prone soil surface characterizations. In this study, the integrated ALEXI-DisALEXI-STARFM framework is applied over an irrigated agricultural region in Saudi Arabia, and the daily estimates of Landsat scale water, energy and carbon fluxes are evaluated against available flux tower observations and other independent in-situ and satellite-based records. The study addresses the challenges associated with time-continuous sub-field scale mapping of land-surface fluxes in a harsh desert environment, and looks into the optimization of model descriptions and parameterizations and meteorological forcing and vegetation inputs for application over these regions.

Sustainable management of agriculture activity on areas with soil vulnerability to compaction trough a developed decision support system (DSS)

NASA Astrophysics Data System (ADS)

Moretto, Johnny; Fantinato, Luciano; Rasera, Roberto

2017-04-01

One of the main environmental effects of agriculture is the negative impacts on areas with soil vulnerability to compaction and undersurface water derived from inputs and treatment distributions. A solution may represented from the "Precision Farming". Precision Farming refers to a management concept focusing on (near-real time) observation, measurement and responses to inter- and intra-variability in crops, fields and animals. Potential benefits may include increasing crop yields and animal performance, cost and labour reduction and optimisation of process inputs, all of which would increase profitability. At the same time, Precision Farming should increase work safety and reduce the environmental impacts of agriculture and farming practices, thus contributing to the sustainability of agricultural production. The concept has been made possible by the rapid development of ICT-based sensor technologies and procedures along with dedicated software that, in the case of arable farming, provides the link between spatially-distributed variables and appropriate farming practices such as tillage, seeding, fertilisation, herbicide and pesticide application, and harvesting. Much progress has been made in terms of technical solutions, but major steps are still required for the introduction of this approach over the common agricultural practices. There are currently a large number of sensors capable of collecting data for various applications (e.g. Index of vegetation vigor, soil moisture, Digital Elevation Models, meteorology, etc.). The resulting large volumes of data need to be standardised, processed and integrated using metadata analysis of spatial information, to generate useful input for decision-support systems. In this context, a user-friendly IT applications has been developed, for organizing and processing large volumes of data from different types of remote sensing and meteorological sensors, and for integrating these data into user-friendly farm management support systems able to support the farm manager. In this applications will be possible to implement numerical models to support the farm manager on the best time to work in field and/or the best trajectory to follow with a GPS navigation system on soil vulnerability to compaction. In addition to provide "as applied map" to indicate in each part of the field the exact needed quantity of inputs and treatments. This new working models for data management will allow to a most efficient resource usage contributing in a more sustainable agriculture both for a more economic benefits for the farmers and for reduction of environmental soil and undersurface water impacts.

Meteorological Influences on Nitrogen Dynamics of a Coastal Onsite Wastewater Treatment System

PubMed Central

O’Driscoll, M.A.; Humphrey, C. P.; Deal, N.E.; Lindbo, D.L.; Zarate-Bermudez, M.A.

2016-01-01

Onsite wastewater treatment systems (OWTS) can contribute nitrogen (N) to coastal waters. In coastal areas with shallow groundwater, OWTS are likely affected by meteorological events. However, the meteorological influences on temporal variability of N exports from OWTS are not well documented. Hydrogeological characterization and seasonal monitoring of wastewater and groundwater quality were conducted at a residence adjacent to the Pamlico River Estuary, North Carolina during a two-year field study (October 2009–2011). Rainfall was elevated during the first study year, relative to the annual mean. In the second year, drought was followed by extreme precipitation from Hurricane Irene. Recent meteorological conditions influenced N speciation and concentrations in groundwater. Groundwater total dissolved nitrogen (TDN) beneath the OWTS drainfield was dominated by nitrate during the drought; during wetter periods ammonium and organic N were common. Effective precipitation (P-ET) affected OWTS TDN exports because of its influence on groundwater recharge and discharge. Groundwater nitrate-N concentrations beneath the drainfield were typically higher than 10 mg/l when total bi-weekly precipitation was less than evapotranspiration (precipitation deficit: P15 m downgradient of the drainfield. Although OWTS nitrate inputs caused elevated groundwater nitrate concentrations between the drainfield and the estuary, the majority of nitrate was attenuated via denitrification between the OWTS and 48 m to the estuary. However, DON originating from the OWTS was mobile and contributed to elevated TDN concentrations along the groundwater flowpath to the estuary. PMID:25602204

The potential of different artificial neural network (ANN) techniques in daily global solar radiation modeling based on meteorological data

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

Behrang, M.A.; Assareh, E.; Ghanbarzadeh, A.

2010-08-15

The main objective of present study is to predict daily global solar radiation (GSR) on a horizontal surface, based on meteorological variables, using different artificial neural network (ANN) techniques. Daily mean air temperature, relative humidity, sunshine hours, evaporation, and wind speed values between 2002 and 2006 for Dezful city in Iran (32 16'N, 48 25'E), are used in this study. In order to consider the effect of each meteorological variable on daily GSR prediction, six following combinations of input variables are considered: (I)Day of the year, daily mean air temperature and relative humidity as inputs and daily GSR as output.more » (II)Day of the year, daily mean air temperature and sunshine hours as inputs and daily GSR as output. (III)Day of the year, daily mean air temperature, relative humidity and sunshine hours as inputs and daily GSR as output. (IV)Day of the year, daily mean air temperature, relative humidity, sunshine hours and evaporation as inputs and daily GSR as output. (V)Day of the year, daily mean air temperature, relative humidity, sunshine hours and wind speed as inputs and daily GSR as output. (VI)Day of the year, daily mean air temperature, relative humidity, sunshine hours, evaporation and wind speed as inputs and daily GSR as output. Multi-layer perceptron (MLP) and radial basis function (RBF) neural networks are applied for daily GSR modeling based on six proposed combinations. The measured data between 2002 and 2005 are used to train the neural networks while the data for 214 days from 2006 are used as testing data. The comparison of obtained results from ANNs and different conventional GSR prediction (CGSRP) models shows very good improvements (i.e. the predicted values of best ANN model (MLP-V) has a mean absolute percentage error (MAPE) about 5.21% versus 10.02% for best CGSRP model (CGSRP 5)). (author)« less

Evaluation of CMAQ and CAMx Ensemble Air Quality Forecasts during the 2015 MAPS-Seoul Field Campaign

NASA Astrophysics Data System (ADS)

Kim, E.; Kim, S.; Bae, C.; Kim, H. C.; Kim, B. U.

2015-12-01

The performance of Air quality forecasts during the 2015 MAPS-Seoul Field Campaign was evaluated. An forecast system has been operated to support the campaign's daily aircraft route decisions for airborne measurements to observe long-range transporting plume. We utilized two real-time ensemble systems based on the Weather Research and Forecasting (WRF)-Sparse Matrix Operator Kernel Emissions (SMOKE)-Comprehensive Air quality Model with extensions (CAMx) modeling framework and WRF-SMOKE- Community Multi_scale Air Quality (CMAQ) framework over northeastern Asia to simulate PM10 concentrations. Global Forecast System (GFS) from National Centers for Environmental Prediction (NCEP) was used to provide meteorological inputs for the forecasts. For an additional set of retrospective simulations, ERA Interim Reanalysis from European Centre for Medium-Range Weather Forecasts (ECMWF) was also utilized to access forecast uncertainties from the meteorological data used. Model Inter-Comparison Study for Asia (MICS-Asia) and National Institute of Environment Research (NIER) Clean Air Policy Support System (CAPSS) emission inventories are used for foreign and domestic emissions, respectively. In the study, we evaluate the CMAQ and CAMx model performance during the campaign by comparing the results to the airborne and surface measurements. Contributions of foreign and domestic emissions are estimated using a brute force method. Analyses on model performance and emissions will be utilized to improve air quality forecasts for the upcoming KORUS-AQ field campaign planned in 2016.

Forecast of Antarctic Sea Ice and Meteorological Fields

NASA Astrophysics Data System (ADS)

Barreira, S.; Orquera, F.

2017-12-01

Since 2001, we have been forecasting the climatic fields of the Antarctic sea ice (SI) and surface air temperature, surface pressure and precipitation anomalies for the Southern Hemisphere at the Meteorological Department of the Argentine Naval Hydrographic Service with different techniques that have evolved with the years. Forecast is based on the results of Principal Components Analysis applied to SI series (S-Mode) that gives patterns of temporal series with validity areas (these series are important to determine which areas in Antarctica will have positive or negative SI anomalies based on what happen in the atmosphere) and, on the other hand, to SI fields (T-Mode) that give us the form of the SI fields anomalies based on a classification of 16 patterns. Each T-Mode pattern has unique atmospheric fields associated to them. Therefore, it is possible to forecast whichever atmosphere variable we decide for the Southern Hemisphere. When the forecast is obtained, each pattern has a probability of occurrence and sometimes it is necessary to compose more than one of them to obtain the final result. S-Mode and T-Mode are monthly updated with new data, for that reason the forecasts improved with the increase of cases since 2001. We used the Monthly Polar Gridded Sea Ice Concentrations database derived from satellite information generated by NASA Team algorithm provided monthly by the National Snow and Ice Data Center of USA that begins in November 1978. Recently, we have been experimenting with multilayer Perceptron (neuronal network) with supervised learning and a back-propagation algorithm to improve the forecast. The Perceptron is the most common Artificial Neural Network topology dedicated to image pattern recognition. It was implemented through the use of temperature and pressure anomalies field images that were associated with a the different sea ice anomaly patterns. The variables analyzed included only composites of surface air temperature and pressure anomalies to simplify the density of input data and avoid a non-converging solution. Sea ice and atmospheric variables forecast can be checked every month at our web page http://www.hidro.gob.ar/smara/sb/sb.asp and at World Meteorological web page (Global Cryosphere Watch) http://globalcryospherewatch.org/state_of_cryo/seaice/.

Instantaneous and daily values of the surface energy balance over agricultural fields using remote sensing and a reference field in an arid environment

USGS Publications Warehouse

Kustas, William P.; Moran, M.S.; Jackson, R. D.; Gay, L.W.; Duell, L.F.W.; Kunkel, K.E.; Matthias, A.D.

1990-01-01

Remotely sensed surface temperature and reflectance in the visible and near infrared wavebands along with ancilliary meteorological data provide the capability of computing three of the four surface energy balance components (i.e., net radiation, soil heat flux, and sensible heat flux) at different spatial and temporal scales. As a result, under nonadvective conditions, this enables the estimation of the remaining term (i.e., the latent heat flux). One of the practical applications with this approach is to produce evapotranspiration (ET) maps for agricultural regions which consist of an array of fields containing different crops at varying stages of growth and soil moisture conditions. Such a situation exists in the semiarid southwest at the University of Arizona Maricopa Agricultural Center, south of Phoenix. For one day (14 June 1987), surface temperature and reflectance measurements from an aircraft 150 m above ground level (agl) were acquired over fields from zero to nearly full cover at four times between 1000 MST and 1130 MST. The diurnal pattern of the surface energy balance was measured over four fields, which included alfalfa at 60% cover, furrowed cotton at 20% and 30% cover, and partially plowed what stubble. Instantaneous and daily values of ET were estimated for a representative area around each flux site with an energy balance model that relies on a reference ET. This reference value was determined with remotely sensed data and several meteorological inputs. The reference ET was adjusted to account for the different surface conditions in the other fields using only remotely sensed variables. A comparison with the flux measurements suggests the model has difficulties with partial canopy conditions, especially related to the estimation of the sensible heat flux. The resulting errors for instantaneous ET were on the order of 100 W m-2 and for daily values of order 2 mm day-1. These findings suggest future research should involve development of methods to account for the variability of meteorological parameters brought about by changes in surface conditions and improvements in the modeling of sensible heat transfer across the surface-atmosphere interface for partial canopy conditions using remote sensing information. ?? 1990.

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.

Meteorological Input to General Aviation Pilot Training

NASA Technical Reports Server (NTRS)

Colomy, J. R.

1979-01-01

The meteorological education of general aviation pilots is discussed in terms of the definitions and concepts of learning and good educational procedures. The effectiveness of the metoeorological program in the training of general aviations pilots is questioned. It is suggested that flight instructors provide real experience during low ceilings and visibilities, and that every pilot receiving an instrument rating should experience real instrument flight.

Impact of inherent meteorology uncertainty on air quality ...

EPA Pesticide Factsheets

It is well established that there are a number of different classifications and sources of uncertainties in environmental modeling systems. Air quality models rely on two key inputs, namely, meteorology and emissions. When using air quality models for decision making, it is important to understand how uncertainties in these inputs affect the simulated concentrations. Ensembles are one method to explore how uncertainty in meteorology affects air pollution concentrations. Most studies explore this uncertainty by running different meteorological models or the same model with different physics options and in some cases combinations of different meteorological and air quality models. While these have been shown to be useful techniques in some cases, we present a technique that leverages the initial condition perturbations of a weather forecast ensemble, namely, the Short-Range Ensemble Forecast system to drive the four-dimensional data assimilation in the Weather Research and Forecasting (WRF)-Community Multiscale Air Quality (CMAQ) model with a key focus being the response of ozone chemistry and transport. Results confirm that a sizable spread in WRF solutions, including common weather variables of temperature, wind, boundary layer depth, clouds, and radiation, can cause a relatively large range of ozone-mixing ratios. Pollutant transport can be altered by hundreds of kilometers over several days. Ozone-mixing ratios of the ensemble can vary as much as 10–20 ppb

Modelling the meteorological forest fire niche in heterogeneous pyrologic conditions.

PubMed

De Angelis, Antonella; Ricotta, Carlo; Conedera, Marco; Pezzatti, Gianni Boris

2015-01-01

Fire regimes are strongly related to weather conditions that directly and indirectly influence fire ignition and propagation. Identifying the most important meteorological fire drivers is thus fundamental for daily fire risk forecasting. In this context, several fire weather indices have been developed focussing mainly on fire-related local weather conditions and fuel characteristics. The specificity of the conditions for which fire danger indices are developed makes its direct transfer and applicability problematic in different areas or with other fuel types. In this paper we used the low-to-intermediate fire-prone region of Canton Ticino as a case study to develop a new daily fire danger index by implementing a niche modelling approach (Maxent). In order to identify the most suitable weather conditions for fires, different combinations of input variables were tested (meteorological variables, existing fire danger indices or a combination of both). Our findings demonstrate that such combinations of input variables increase the predictive power of the resulting index and surprisingly even using meteorological variables only allows similar or better performances than using the complex Canadian Fire Weather Index (FWI). Furthermore, the niche modelling approach based on Maxent resulted in slightly improved model performance and in a reduced number of selected variables with respect to the classical logistic approach. Factors influencing final model robustness were the number of fire events considered and the specificity of the meteorological conditions leading to fire ignition.

Modelling the Meteorological Forest Fire Niche in Heterogeneous Pyrologic Conditions

PubMed Central

De Angelis, Antonella; Ricotta, Carlo; Conedera, Marco; Pezzatti, Gianni Boris

2015-01-01

Fire regimes are strongly related to weather conditions that directly and indirectly influence fire ignition and propagation. Identifying the most important meteorological fire drivers is thus fundamental for daily fire risk forecasting. In this context, several fire weather indices have been developed focussing mainly on fire-related local weather conditions and fuel characteristics. The specificity of the conditions for which fire danger indices are developed makes its direct transfer and applicability problematic in different areas or with other fuel types. In this paper we used the low-to-intermediate fire-prone region of Canton Ticino as a case study to develop a new daily fire danger index by implementing a niche modelling approach (Maxent). In order to identify the most suitable weather conditions for fires, different combinations of input variables were tested (meteorological variables, existing fire danger indices or a combination of both). Our findings demonstrate that such combinations of input variables increase the predictive power of the resulting index and surprisingly even using meteorological variables only allows similar or better performances than using the complex Canadian Fire Weather Index (FWI). Furthermore, the niche modelling approach based on Maxent resulted in slightly improved model performance and in a reduced number of selected variables with respect to the classical logistic approach. Factors influencing final model robustness were the number of fire events considered and the specificity of the meteorological conditions leading to fire ignition. PMID:25679957

A quantitative sensitivity analysis on the behaviour of common thermal indices under hot and windy conditions in Doha, Qatar

NASA Astrophysics Data System (ADS)

Fröhlich, Dominik; Matzarakis, Andreas

2016-04-01

Human thermal perception is best described through thermal indices. The most popular thermal indices applied in human bioclimatology are the perceived temperature (PT), the Universal Thermal Climate Index (UTCI), and the physiologically equivalent temperature (PET). They are analysed focusing on their sensitivity to single meteorological input parameters under the hot and windy meteorological conditions observed in Doha, Qatar. It can be noted, that the results for the three indices are distributed quite differently. Furthermore, they respond quite differently to modifications in the input conditions. All of them show particular limitations and shortcomings that have to be considered and discussed. While the results for PT are unevenly distributed, UTCI shows limitations concerning the input data accepted. PET seems to respond insufficiently to changes in vapour pressure. The indices should therefore be improved to be valid for several kinds of climates.

Proceedings of the 2nd Annual Workshop on Meteorological and Environmental Inputs to Aviation Systems

NASA Technical Reports Server (NTRS)

Frost, W. (Editor); Camp, D. W. (Editor); Durham, D. E. (Editor)

1978-01-01

The proceedings of a workshop held at the University of Tennessee Space Institute, Tullahoma, Tennessee, March 28-30, 1978, are reported. The workshop was jointly sponsored by NASA, NOAA, FAA, and brought together many disciplines of the aviation communities in round table discussions. The major objectives of the workshop are to satisfy such needs of the sponsoring agencies as the expansion of our understanding and knowledge of the interactions of the atmosphere with aviation systems, as the better definition and implementation of services to operators, and as the collection and interpretation of data for establishing operational criteria, relating the total meteorological inputs from the atmospheric sciences to the needs of aviation communities.

A study of the mechanism of internal gravity wave generation by quasigeostrophic meteorological motions

NASA Technical Reports Server (NTRS)

Medvedev, A. S.

1987-01-01

Numerous experiments on the detection of atmospheric waves in the frequency range from acoustic to planetary at meteor heights have revealed that important wave sources are meteorological processes in the troposphere (cyclones, atmospheric fronts, jet streams, etc.). A dynamical theory based on the others work include describing the adaptation of meteorological fields to the geostropic equilibrium state. According to this theory, wave motions appear as a result of constant competition between the maladjustment of the wind and pressure fields due to nonlinear effects and the tendency of the atmosphere to establish a quasi-geostrophic equilibrium of these fields. These meteorological fields are discussed.

A study of the mechanism of internal gravity wave generation by quasigeostrophic meteorological motions

NASA Astrophysics Data System (ADS)

Medvedev, A. S.

1987-08-01

Numerous experiments on the detection of atmospheric waves in the frequency range from acoustic to planetary at meteor heights have revealed that important wave sources are meteorological processes in the troposphere (cyclones, atmospheric fronts, jet streams, etc.). A dynamical theory based on the others work include describing the adaptation of meteorological fields to the geostropic equilibrium state. According to this theory, wave motions appear as a result of constant competition between the maladjustment of the wind and pressure fields due to nonlinear effects and the tendency of the atmosphere to establish a quasi-geostrophic equilibrium of these fields. These meteorological fields are discussed.

Measuring the vertical electrical field above an oceanic convection system using a meteorological sounding balloon

NASA Astrophysics Data System (ADS)

Chen, A. B.; Chiu, C.; Lai, S.; Chen, C.; Kuo, C.; Su, H.; Hsu, R.

2012-12-01

The vertical electric field above thundercloud plays an important role in the generation and modeling of transient luminous events. For example, Pasko [1995] proposed that the high quasi-static E-field following the positive cloud-to-ground lightning could accelerate and input energy to ambient electrons; as they collide and excite nitrogen and oxygen molecules in upper atmosphere, sprites may be induced. A series of balloon experiments led by Holzworth have investigated the temporal and spatial fluctuations of the electric field and conductivity in the upper atmosphere at different sites [Holzworth 2005, and references in]. But the strength and variation of the vertical electric field above thundercloud, especially oceanic ones, are not well documented so far. A lightweight, low-cost measurement system including an electric field meter and the associated aviation electronics are developed to carry out the in-situ measurement of the vertical electric field and the inter-cloud charge distribution. Our measuring system was first deployed using a meteorological sounding balloon from Taitung, Taiwan in May 2012. The measured electric field below 3km height shows an exponential decay and it is consistent with the expected potential gradient variation between ionosphere and the Earth surface. But the background strength of the measured E-field grows up exponentially and a violent fluctuations is also observed when the balloon flew over a developing oceanic convection cell. The preliminary results from this flight will be reported and discussed. This low-cost electric field meter is developed within one year. In the coming months, more flights will be performed with the aim to measure the rapid variation of the electric field above thundercloud as well as the E-field that may induce transient luminous events. Our ground campaigns show that the occurrence rates of blue and gigantic jet are relatively high in the vicinity of Taiwan. Our experiment can be used to diagnose the dynamics of the E-field associated with blue and gigantic jets.

A deep belief network approach using VDRAS data for nowcasting

NASA Astrophysics Data System (ADS)

Han, Lei; Dai, Jie; Zhang, Wei; Zhang, Changjiang; Feng, Hanlei

2018-04-01

Nowcasting or very short-term forecasting convective storms is still a challenging problem due to the high nonlinearity and insufficient observation of convective weather. As the understanding of the physical mechanism of convective weather is also insufficient, the numerical weather model cannot predict convective storms well. Machine learning approaches provide a potential way to nowcast convective storms using various meteorological data. In this study, a deep belief network (DBN) is proposed to nowcast convective storms using the real-time re-analysis meteorological data. The nowcasting problem is formulated as a classification problem. The 3D meteorological variables are fed directly to the DBN with dimension of input layer 6*6*80. Three hidden layers are used in the DBN and the dimension of output layer is two. A box-moving method is presented to provide the input features containing the temporal and spatial information. The results show that the DNB can generate reasonable prediction results of the movement and growth of convective storms.

Sensitivity analysis of the near-road dispersion model RLINE - An evaluation at Detroit, Michigan

NASA Astrophysics Data System (ADS)

Milando, Chad W.; Batterman, Stuart A.

2018-05-01

The development of accurate and appropriate exposure metrics for health effect studies of traffic-related air pollutants (TRAPs) remains challenging and important given that traffic has become the dominant urban exposure source and that exposure estimates can affect estimates of associated health risk. Exposure estimates obtained using dispersion models can overcome many of the limitations of monitoring data, and such estimates have been used in several recent health studies. This study examines the sensitivity of exposure estimates produced by dispersion models to meteorological, emission and traffic allocation inputs, focusing on applications to health studies examining near-road exposures to TRAP. Daily average concentrations of CO and NOx predicted using the Research Line source model (RLINE) and a spatially and temporally resolved mobile source emissions inventory are compared to ambient measurements at near-road monitoring sites in Detroit, MI, and are used to assess the potential for exposure measurement error in cohort and population-based studies. Sensitivity of exposure estimates is assessed by comparing nominal and alternative model inputs using statistical performance evaluation metrics and three sets of receptors. The analysis shows considerable sensitivity to meteorological inputs; generally the best performance was obtained using data specific to each monitoring site. An updated emission factor database provided some improvement, particularly at near-road sites, while the use of site-specific diurnal traffic allocations did not improve performance compared to simpler default profiles. Overall, this study highlights the need for appropriate inputs, especially meteorological inputs, to dispersion models aimed at estimating near-road concentrations of TRAPs. It also highlights the potential for systematic biases that might affect analyses that use concentration predictions as exposure measures in health studies.

Acceptance criteria for urban dispersion model evaluation

NASA Astrophysics Data System (ADS)

Hanna, Steven; Chang, Joseph

2012-05-01

The authors suggested acceptance criteria for rural dispersion models' performance measures in this journal in 2004. The current paper suggests modified values of acceptance criteria for urban applications and tests them with tracer data from four urban field experiments. For the arc-maximum concentrations, the fractional bias should have a magnitude <0.67 (i.e., the relative mean bias is less than a factor of 2); the normalized mean-square error should be <6 (i.e., the random scatter is less than about 2.4 times the mean); and the fraction of predictions that are within a factor of two of the observations (FAC2) should be >0.3. For all data paired in space, for which a threshold concentration must always be defined, the normalized absolute difference should be <0.50, when the threshold is three times the instrument's limit of quantification (LOQ). An overall criterion is then applied that the total set of acceptance criteria should be satisfied in at least half of the field experiments. These acceptance criteria are applied to evaluations of the US Department of Defense's Joint Effects Model (JEM) with tracer data from US urban field experiments in Salt Lake City (U2000), Oklahoma City (JU2003), and Manhattan (MSG05 and MID05). JEM includes the SCIPUFF dispersion model with the urban canopy option and the urban dispersion model (UDM) option. In each set of evaluations, three or four likely options are tested for meteorological inputs (e.g., a local building top wind speed, the closest National Weather Service airport observations, or outputs from numerical weather prediction models). It is found that, due to large natural variability in the urban data, there is not a large difference between the performance measures for the two model options and the three or four meteorological input options. The more detailed UDM and the state-of-the-art numerical weather models do provide a slight improvement over the other options. The proposed urban dispersion model acceptance criteria are satisfied at over half of the field experiments.

Numerical modeling of thermal regime in inland water bodies with field measurement data

NASA Astrophysics Data System (ADS)

Gladskikh, D.; Sergeev, D.; Baydakov, G.; Soustova, I.; Troitskaya, Yu.

2018-01-01

Modification of the program complex LAKE, which is intended to compute the thermal regimes of inland water bodies, and the results of its validation in accordance with the parameters of lake part of Gorky water reservoir are reviewed in the research. The modification caused changing the procedure of input temperature profile assignment and parameterization of surface stress on air-water boundary in accordance with the consideration of wind influence on mixing process. Also the innovation consists in combined methods of gathering meteorological parameters from files of global meteorological reanalysis and data of hydrometeorological station. Temperature profiles carried out with CTD-probe during expeditions in the period 2014-2017 were used for validation of the model. The comparison between the real data and the numerical results and its assessment based on time and temperature dependences in control points, correspondence of the forms of the profiles and standard deviation for all performed realizations are provided. It is demonstrated that the model reproduces the results of field measurement data for all observed conditions and seasons. The numerical results for the regimes with strong mixing are in the best quantitative and qualitative agreement with the real profiles. The accuracy of the forecast for the ones with strong stratification near the surface is lower but all specificities of the forms are correctly reproduced.

Activities of NASA's Global Modeling Initiative (GMI) in the Assessment of Subsonic Aircraft Impact

NASA Technical Reports Server (NTRS)

Rodriquez, J. M.; Logan, J. A.; Rotman, D. A.; Bergmann, D. J.; Baughcum, S. L.; Friedl, R. R.; Anderson, D. E.

2004-01-01

The Intergovernmental Panel on Climate Change estimated a peak increase in ozone ranging from 7-12 ppbv (zonal and annual average, and relative to a baseline with no aircraft), due to the subsonic aircraft in the year 2015, corresponding to aircraft emissions of 1.3 TgN/year. This range of values presumably reflects differences in model input (e.g., chemical mechanism, ground emission fluxes, and meteorological fields), and algorithms. The model implemented by the Global Modeling Initiative allows testing the impact of individual model components on the assessment calculations. We present results of the impact of doubling the 1995 aircraft emissions of NOx, corresponding to an extra 0.56 TgN/year, utilizing meteorological data from NASA's Data Assimilation Office (DAO), the Goddard Institute for Space Studies (GISS), and the Middle Atmosphere Community Climate Model, version 3 (MACCM3). Comparison of results to observations can be used to assess the model performance. Peak ozone perturbations ranging from 1.7 to 2.2 ppbv of ozone are calculated using the different fields. These correspond to increases in total tropospheric ozone ranging from 3.3 to 4.1 Tg/Os. These perturbations are consistent with the IPCC results, due to the difference in aircraft emissions. However, the range of values calculated is much smaller than in IPCC.

Meteorological and Environmental Inputs to Aviation Systems

NASA Technical Reports Server (NTRS)

Camp, Dennis W. (Editor); Frost, Walter (Editor)

1988-01-01

Reports on aviation meteorology, most of them informal, are presented by representatives of the National Weather Service, the Bracknell (England) Meteorological Office, the NOAA Wave Propagation Lab., the Fleet Numerical Oceanography Center, and the Aircraft Owners and Pilots Association. Additional presentations are included on aircraft/lidar turbulence comparison, lightning detection and locating systems, objective detection and forecasting of clear air turbulence, comparative verification between the Generalized Exponential Markov (GEM) Model and official aviation terminal forecasts, the evaluation of the Prototype Regional Observation and Forecast System (PROFS) mesoscale weather products, and the FAA/MIT Lincoln Lab. Doppler Weather Radar Program.

Meteorological and associated data collected over agricultural fields in Pinal County, Arizona, 1989 and 1990

USGS Publications Warehouse

Owen-Joyce, Sandra J.; Brown, Paul W.

1995-01-01

Data were collected at temporary meteorological stations installed in agricultural fields in Pinal County, Arizona, to evaluate the spatial and temporal variability of point data and to examine how station location affects ground-based meteorological data and the resulting values of evapotranspiration calculated using remotely sensed multispectral data from satellites. Time-specific data were collected to correspond with satellite overpasses from April to October 1989, and June 27-28, 1990. Meteorological data consisting of air temperature, relative humidity, wind speed, solar radiation, and net radiation were collected at each station during all periods of the project. Supplementary measurements of soil temperature, soil heat flux density, and surface or canopy temperature were obtained at some locations during certain periods of the project. Additional data include information on data-collection periods, station positions, instrumentation, sensor heights, and field dimensions. Other data, which correspond to the extensive field measurements made in con- junction with satellite overpasses in 1989 and 1990, include crop type, canopy cover, canopy height, irrigation, cultivation, and orientation of rows. Field boundaries and crop types were mapped in a 2- to 3-square-kilometer area surrounding each meteorological station. Field data are presented in tabular and graphic form. Meteorological and supplementary data are available, upon request, in digital form.

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.

A Methodological Inter-Comparison of Gridded Meteorological Products

NASA Astrophysics Data System (ADS)

Newman, A. J.; Clark, M. P.; Longman, R. J.; Giambelluca, T. W.; Arnold, J.

2017-12-01

Here we present a gridded meteorology inter-comparison using the state of Hawaíi as a testbed. This inter-comparison is motivated by two general goals: 1) the broad user community of gridded observation based meteorological fields should be aware of inter-product differences and the reasons they exist, which allows users to make informed choices on product selection to best meet their specific application(s); 2) we want to demonstrate the utility of inter-comparisons to meet the first goal, yet highlight that they are limited to mostly generic statements regarding attribution of differences that limits our understanding of these complex algorithms and obscures future research directions. Hawaíi is a useful testbed because it is a meteorologically complex region with well-known spatial features that are tied to specific physical processes (e.g. the trade wind inversion). From a practical standpoint, there are now several monthly climatological and daily precipitation and temperature datasets available that are being used for impact modeling. General conclusions that have emerged are: 1) differences in input station data significantly influence product differences; 2) prediction of precipitation occurrence is crucial across multiple metrics; 3) derived temperature statistics (e.g. diurnal temperature range) may have large spatial differences across products; and 4) attribution of differences to methodological choices is difficult and may limit the outcomes of these inter-comparisons, particularly from a development viewpoint. Thus, we want to continue to move the community towards frameworks that allow for multiple options throughout the product generation chain and allow for more systematic testing.

Reference evapotranspiration forecasting based on local meteorological and global climate information screened by partial mutual information

NASA Astrophysics Data System (ADS)

Fang, Wei; Huang, Shengzhi; Huang, Qiang; Huang, Guohe; Meng, Erhao; Luan, Jinkai

2018-06-01

In this study, reference evapotranspiration (ET0) forecasting models are developed for the least economically developed regions subject to meteorological data scarcity. Firstly, the partial mutual information (PMI) capable of capturing the linear and nonlinear dependence is investigated regarding its utility to identify relevant predictors and exclude those that are redundant through the comparison with partial linear correlation. An efficient input selection technique is crucial for decreasing model data requirements. Then, the interconnection between global climate indices and regional ET0 is identified. Relevant climatic indices are introduced as additional predictors to comprise information regarding ET0, which ought to be provided by meteorological data unavailable. The case study in the Jing River and Beiluo River basins, China, reveals that PMI outperforms the partial linear correlation in excluding the redundant information, favouring the yield of smaller predictor sets. The teleconnection analysis identifies the correlation between Nino 1 + 2 and regional ET0, indicating influences of ENSO events on the evapotranspiration process in the study area. Furthermore, introducing Nino 1 + 2 as predictors helps to yield more accurate ET0 forecasts. A model performance comparison also shows that non-linear stochastic models (SVR or RF with input selection through PMI) do not always outperform linear models (MLR with inputs screen by linear correlation). However, the former can offer quite comparable performance depending on smaller predictor sets. Therefore, efforts such as screening model inputs through PMI and incorporating global climatic indices interconnected with ET0 can benefit the development of ET0 forecasting models suitable for data-scarce regions.

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.

Climatological Downscaling and Evaluation of AGRMET Precipitation Analyses Over the Continental U.S.

NASA Astrophysics Data System (ADS)

Garcia, M.; Peters-Lidard, C. D.; Eylander, J. B.; Daly, C.; Tian, Y.; Zeng, J.

2007-05-01

The spatially distributed application of a land surface model (LSM) over a region of interest requires the application of similarly distributed precipitation fields that can be derived from various sources, including surface gauge networks, surface-based radar, and orbital platforms. The spatial variability of precipitation influences the spatial organization of soil temperature and moisture states and, consequently, the spatial variability of land- atmosphere fluxes. The accuracy of spatially-distributed precipitation fields can contribute significantly to the uncertainty of model-based hydrological states and fluxes at the land surface. Collaborations between the Air Force Weather Agency (AFWA), NASA, and Oregon State University have led to improvements in the processing of meteorological forcing inputs for the NASA-GSFC Land Information System (LIS; Kumar et al. 2006), a sophisticated framework for LSM operation and model coupling experiments. Efforts at AFWA toward the production of surface hydrometeorological products are currently in transition from the legacy Agricultural Meteorology modeling system (AGRMET) to use of the LIS framework and procedures. Recent enhancements to meteorological input processing for application to land surface models in LIS include the assimilation of climate-based information for the spatial interpolation and downscaling of precipitation fields. Climatological information included in the LIS-based downscaling procedure for North America is provided by a monthly high-resolution PRISM (Daly et al. 1994, 2002; Daly 2006) dataset based on a 30-year analysis period. The combination of these sources and methods attempts to address the strengths and weaknesses of available legacy products, objective interpolation methods, and the PRISM knowledge-based methodology. All of these efforts are oriented on an operational need for timely estimation of spatial precipitation fields at adequate spatial resolution for customer dissemination and near-real-time simulations in regions of interest. This work focuses on value added to the AGRMET precipitation product by the inclusion of high-quality climatological information on a monthly time scale. The AGRMET method uses microwave-based satellite precipitation estimates from various polar-orbiting platforms (NOAA POES and DMSP), infrared-based estimates from geostationary platforms (GOES, METEOSAT, etc.), related cloud analysis products, and surface gauge observations in a complex and hierarchical blending process. Results from processing of the legacy AGRMET precipitation products over the U.S. using LIS-based methods for downscaling, both with and without climatological factors, are evaluated against high-resolution monthly analyses using the PRISM knowledge- based method (Daly et al. 2002). It is demonstrated that the incorporation of climatological information in a downscaling procedure can significantly enhance the accuracy, and potential utility, of AFWA precipitation products for military and civilian customer applications.

Throughfall under a teak plantation in Thailand: a multifactorial analysis on the effects of canopy phenology and meteorological conditions

NASA Astrophysics Data System (ADS)

Tanaka, N.; Levia, D. F., Jr.; Igarashi, Y.; Nanko, K.; Yoshifuji, N.; Tanaka, K.; Chatchai, T.; Suzuki, M.; Kumagai, T.

2014-12-01

Teak (Tectona grandis Linn. f.) plantations cover vast areas throughout Southeast Asia and are of great economic importance. This study has sought to increase our understanding of throughfall inputs under teak by analyzing the abiotic and biotic factors governing throughfall amounts and throughfall ratios in relation to three canopy phenophases (leafless, leafing, and leafed). There is no rain during the brief leaf senescence phenophase. Daily data was available for both throughfall volumes and depths as well as leaf area index. Detailed meteorological data were available in situ every ten minutes. Leveraging this high-resolution field data, we employed boosted regression trees (BRT) analysis to identify the primary controls on throughfall amount and ratio during each of the three canopy phenophases. Whereas throughfall amounts were always dominated by the magnitude of rainfall (as expected), throughfall ratios were governed by a suite of predictor variables during each phenophase. The BRT analysis demonstrated that throughfall ratio in the leafless phase was most influenced (in descending order of importance) by air temperature, rainfall amount, maximum wind speed, and rainfall intensity. Throughfall ratio in the leafed phenophase was dominated by rainfall amount which exerted 54.0% of the relative influence. The leafing phenophase was an intermediate case where rainfall amount, air temperature, and vapor pressure deficit were most important. Our results highlight the fact that throughfall ratios are differentially influenced by a suite of meteorological variables during leafless, leafing, and leafed phenophases. Abiotic variables (rainfall amount, air temperature, vapor pressure deficit, and maximum wind speed) trumped leaf area index and stand density in their effect on throughfall ratio. The leafing phenophase, while transitional in nature and short in duration, has a detectable and unique impact on water inputs to teak plantations. Further work is clearly needed to better gauge the importance of the leaf emergence period to the stemflow hydrology and forest biogeochemistry of teak plantations.

Apollo: AN Automatic Procedure to Forecast Transport and Deposition of Tephra

NASA Astrophysics Data System (ADS)

Folch, A.; Costa, A.; Macedonio, G.

2007-05-01

Volcanic ash fallout represents a serious threat to communities around active volcanoes. Reliable short term predictions constitute a valuable support for to mitigate the effects of fallout on the surrounding area during an episode of crisis. We present a platform-independent automatic procedure aimed to daily forecast volcanic ash dispersal. The procedure builds on a series of programs and interfaces that allow an automatic data/results flow. Firstly the procedure downloads mesoscale meteorological forecasts for the region and period of interest, filters and converts data from its native format (typically GRIB format files), and sets up the CALMET diagnostic meteorological model to obtain hourly wind field and micro-meteorological variables on a finer mesh. Secondly a 1-D version of the buoyant plume equations assesses the distribution of mass along the eruptive column depending on the obtained wind field and on the conditions at the vent (granulometry, mass flow rate, etc.). All these data are used as input for the ash dispersion model(s). Any model able to face physical complexity and coupling processes with adequate solving times can be plugged into the system by means of an interface. Currently, the procedure contains the models HAZMAP, TEPHRA and FALL3D, the latter in both serial and parallel versions. Parallelization of FALL3D is done at two levels one for particle classes and one for spatial domain. The last step is to post-processes the model(s) outcomes to end up with homogeneous maps written on portable format files. Maps plot relevant quantities such as predicted ground load, expected deposit thickness or visual and flight safety concentration thresholds. Several applications are shown as examples.

Proceedings: Fourth Annual Workshop on Meteorological and Environmental Inputs to Aviation Systems

NASA Technical Reports Server (NTRS)

Frost, Walter (Editor); Camp, Dennis W. (Editor)

1980-01-01

The proceedings of a workshop on meteorological and environmental inputs to aviation systems held at The University of Tennessee Space Institute, Tullahoma, Tennessee, March 25-27, 1980, are reported. The workshop was jointly sponsored by NASA, NOAA, and FAA and brought together many disciplines of the aviation communities in round table discussions. The major objectives of the workshop are to satisfy such needs of the sponsoring agencies as the expansion of our understanding and knowledge of the interaction of the atmosphere with aviation systems, the better definition and implementation of services to operators, and the collection and interpretation of data for establishing operational criteria relating the total meteorological inputs from the atmospheric sciences to the needs of aviation communities. The unique aspects of the workshop were the diversity of the participants and the achievement of communication across the interface of the boundaries between pilots, meteorologists, training personnel, accident investigators, traffic controllers, flight operation personnel from military, civil, general aviation, and commercial interests alike. Representatives were in attendance from government, airlines, private agencies, aircraft manufacturers, Department of Defense, industries, research institutes, and universities. Full-length papers from invited speakers addressed topics on icing, turbulence, wind and wind shear, ceilings and visibility, lightning, and atmospheric electricity. These papers are contained in the proceedings together with the committee chairmen's reports on the results and conclusions of their efforts on similar subjects.

Adding Four- Dimensional Data Assimilation (aka grid ...

EPA Pesticide Factsheets

Adding four-dimensional data assimilation (a.k.a. grid nudging) to MPAS.The U.S. Environmental Protection Agency is investigating the use of MPAS as the meteorological driver for its next-generation air quality model. To function as such, MPAS needs to operate in a diagnostic mode in much the same manner as the current meteorological driver, the Weather Research and Forecasting (WRF) model. The WRF operates in diagnostic mode using Four-Dimensional Data Assimilation, also known as "grid nudging". MPAS version 4.0 has been modified with the addition of an FDDA routine to the standard physics drivers to nudge the state variables for wind, temperature and water vapor towards MPAS initialization fields defined at 6-hour intervals from GFS-derived data. The results to be shown demonstrate the ability to constrain MPAS simulations to known historical conditions and thus provide the U.S. EPA with a practical meteorological driver for global-scale air quality simulations. The National Exposure Research Laboratory (NERL) Computational Exposure Division (CED) develops and evaluates data, decision-support tools, and models to be applied to media-specific or receptor-specific problem areas. CED uses modeling-based approaches to characterize exposures, evaluate fate and transport, and support environmental diagnostics/forensics with input from multiple data sources. It also develops media- and receptor-specific models, process models, and decision support tools for use bo

Sensitivity of surface meteorological analyses to observation networks

NASA Astrophysics Data System (ADS)

Tyndall, Daniel Paul

A computationally efficient variational analysis system for two-dimensional meteorological fields is developed and described. This analysis approach is most efficient when the number of analysis grid points is much larger than the number of available observations, such as for large domain mesoscale analyses. The analysis system is developed using MATLAB software and can take advantage of multiple processors or processor cores. A version of the analysis system has been exported as a platform independent application (i.e., can be run on Windows, Linux, or Macintosh OS X desktop computers without a MATLAB license) with input/output operations handled by commonly available internet software combined with data archives at the University of Utah. The impact of observation networks on the meteorological analyses is assessed by utilizing a percentile ranking of individual observation sensitivity and impact, which is computed by using the adjoint of the variational surface assimilation system. This methodology is demonstrated using a case study of the analysis from 1400 UTC 27 October 2010 over the entire contiguous United States domain. The sensitivity of this approach to the dependence of the background error covariance on observation density is examined. Observation sensitivity and impact provide insight on the influence of observations from heterogeneous observing networks as well as serve as objective metrics for quality control procedures that may help to identify stations with significant siting, reporting, or representativeness issues.

Modeling Study for Tangier Island Jetties, Tangier Island, Virginia

DTIC Science & Technology

2015-03-01

meteorological and oceanographic (metocean) inputs used as forcing conditions. CENAO provided survey data available for Tangier Is- land from a...and 5 ft or 1.5 m). Wave direction is meteorological (e.g., direction waves coming from). Figure 55. Ten selected locations (black squares) in Alt...given in the previous sections. The Hud- son equation is well known and has been used for years to determine ar- mor stability ( Hudson 1959; Shore

What does industry need in the way of meteorology for air pollution problems

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

Crow, L.W.

1978-01-01

A discussion covers information which should be supplied to the consulting meteorologist; typical requests made by industrial concerns of various consultants; feeding meteorological data to models; the use of meteorological information in developing prevention of significant deterioration requirements; sources of error, e.g., assuming that digital values have a higher validity than the original analog records; the need for industrial concerns to develop sets of site-specific data; and the greater liability of air flow and stability frequencies estimated by professional meteorologists than transposed historical data from the nearest airport station for use as model input to make preliminary planning decisions.

Development and evaluation of climatologically-downscaled AFWA AGRMET precipitation products over the continental U.S.

NASA Astrophysics Data System (ADS)

Garcia, M.; Peters-Lidard, C. D.; Eylander, J. B.; Daly, C.; Gibson, W.; Tian, Y.; Zeng, J.; Kato, H.

2008-05-01

Collaborations between the Air Force Weather Agency (AFWA), the Hydrological Sciences Branch at NASA-GSFC, and the PRISM Group at Oregon State University have led to improvements in the processing of meteorological forcing inputs for the NASA-GSFC Land Information System (LIS; Kumar et al. 2006), a sophisticated framework for LSM operation and model coupling experiments. Efforts at AFWA toward the production of surface hydrometeorological products are currently in transition from the legacy Agricultural Meteorology modeling system (AGRMET) to use of the LIS framework and procedures. Recent enhancements to meteorological input processing for application to land surface models in LIS include the assimilation of climate-based information for the spatial interpolation and downscaling of precipitation fields. Climatological information included in the LIS- based downscaling procedure for North America is provided by a monthly high-resolution PRISM (Daly et al. 1994, 2002; Daly 2006) dataset based on a 30-year analysis period. The combination of these sources and methods attempts to address the strengths and weaknesses of available legacy products, objective interpolation methods, and the PRISM knowledge-based methodology. All of these efforts are oriented on an operational need for timely estimation of spatial precipitation fields at adequate spatial resolution for customer dissemination and near-real-time simulations in regions of interest. This work focuses on value added to the AGRMET precipitation product by the inclusion of high-quality climatological information on a monthly time scale. The AGRMET method uses microwave-based satellite precipitation estimates from various polar-orbiting platforms (NOAA POES and DMSP), infrared-based estimates from geostationary platforms (GOES, METEOSAT, etc.), related cloud analysis products, and surface gauge observations in a complex and hierarchical blending process. Results from processing of the legacy AGRMET precipitation products over the U.S. using LIS-based methods for downscaling, both with and without climatological factors, are evaluated against high-resolution monthly analyses using the PRISM knowledge- based method (Daly et al. 2002) over a 4-year period. It is demonstrated that the incorporation of climatological information in a downscaling procedure can significantly enhance the accuracy, and potential utility, of AFWA precipitation products for customer applications, especially over mountainous terrain as in the western U.S.

GEOS-5 Chemistry Transport Model User's Guide

NASA Technical Reports Server (NTRS)

Kouatchou, J.; Molod, A.; Nielsen, J. E.; Auer, B.; Putman, W.; Clune, T.

2015-01-01

The Goddard Earth Observing System version 5 (GEOS-5) General Circulation Model (GCM) makes use of the Earth System Modeling Framework (ESMF) to enable model configurations with many functions. One of the options of the GEOS-5 GCM is the GEOS-5 Chemistry Transport Model (GEOS-5 CTM), which is an offline simulation of chemistry and constituent transport driven by a specified meteorology and other model output fields. This document describes the basic components of the GEOS-5 CTM, and is a user's guide on to how to obtain and run simulations on the NCCS Discover platform. In addition, we provide information on how to change the model configuration input files to meet users' needs.

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

Uncertainty Evaluations of the CRCS In-orbit Field Radiometric Calibration Methods for Thermal Infrared Channels of FENGYUN Meteorological Satellites

NASA Astrophysics Data System (ADS)

Zhang, Y.; Rong, Z.; Min, M.; Hao, X.; Yang, H.

2017-12-01

Meteorological satellites have become an irreplaceable weather and ocean-observing tool in China. These satellites are used to monitor natural disasters and improve the efficiency of many sectors of Chinese national economy. It is impossible to ignore the space-derived data in the fields of meteorology, hydrology, and agriculture, as well as disaster monitoring in China, a large agricultural country. For this reason, China is making a sustained effort to build and enhance its meteorological observing system and application system. The first Chinese polar-orbiting weather satellite was launched in 1988. Since then China has launched 14 meteorological satellites, 7 of which are sun synchronous and 7 of which are geostationary satellites; China will continue its two types of meteorological satellite programs. In order to achieve the in-orbit absolute radiometric calibration of the operational meteorological satellites' thermal infrared channels, China radiometric calibration sites (CRCS) established a set of in-orbit field absolute radiometric calibration methods (FCM) for thermal infrared channels (TIR) and the uncertainty of this method was evaluated and analyzed based on TERRA/AQUA MODIS observations. Comparisons between the MODIS at pupil brightness temperatures (BTs) and the simulated BTs at the top of atmosphere using radiative transfer model (RTM) based on field measurements showed that the accuracy of the current in-orbit field absolute radiometric calibration methods was better than 1.00K (@300K, K=1) in thermal infrared channels. Therefore, the current CRCS field calibration method for TIR channels applied to Chinese metrological satellites was with favorable calibration accuracy: for 10.5-11.5µm channel was better than 0.75K (@300K, K=1) and for 11.5-12.5µm channel was better than 0.85K (@300K, K=1).

Analysis of Surface Electric Field Measurements from an Array of Electric Field Mills

NASA Astrophysics Data System (ADS)

Lucas, G.; Thayer, J. P.; Deierling, W.

2016-12-01

Kennedy Space Center (KSC) has operated an distributed array of over 30 electric field mills over the past 18 years, providing a unique data set of surface electric field measurements over a very long timespan. In addition to the electric field instruments there are many meteorological towers around KSC that monitor the local meteorological conditions. Utilizing these datasets we have investigated and found unique spatial and temporal signatures in the electric field data that are attributed to local meteorological effects and the global electric circuit. The local and global scale influences on the atmospheric electric field will be discussed including the generation of space charge from the ocean surf, local cloud cover, and a local enhancement in the electric field that is seen at sunrise.

National Atmospheric Release Advisory Center dispersion modeling of the Full-scale Radiological Dispersal device (FSRDD) field trials

DOE PAGES

Neuscamman, Stephanie J.; Yu, Kristen L.

2016-05-01

The results of the National Atmospheric Release Advisory Center (NARAC) model simulations are compared to measured data from the Full-Scale Radiological Dispersal Device (FSRDD) field trials. The series of explosive radiological dispersal device (RDD) experiments was conducted in 2012 by Defence Research and Development Canada (DRDC) and collaborating organizations. During the trials, a wealth of data was collected, including a variety of deposition and air concentration measurements. The experiments were conducted with one of the stated goals being to provide measurements to atmospheric dispersion modelers. These measurements can be used to facilitate important model validation studies. For this study, meteorologicalmore » observations recorded during the tests are input to the diagnostic meteorological model, ADAPT, which provides 3–D, time-varying mean wind and turbulence fields to the LODI dispersion model. LODI concentration and deposition results are compared to the measured data, and the sensitivity of the model results to changes in input conditions (such as the particle activity size distribution of the source) and model physics (such as the rise of the buoyant cloud of explosive products) is explored. The NARAC simulations predicted the experimentally measured deposition results reasonably well considering the complexity of the release. Lastly, changes to the activity size distribution of the modeled particles can improve the agreement of the model results to measurement.« less

Improved interpolation of meteorological forcings for hydrologic applications in a Swiss Alpine region

NASA Astrophysics Data System (ADS)

Tobin, Cara; Nicotina, Ludovico; Parlange, Marc B.; Berne, Alexis; Rinaldo, Andrea

2011-04-01

SummaryThis paper presents a comparative study on the mapping of temperature and precipitation fields in complex Alpine terrain. Its relevance hinges on the major impact that inadequate interpolations of meteorological forcings bear on the accuracy of hydrologic predictions regardless of the specifics of the models, particularly during flood events. Three flood events measured in the Swiss Alps are analyzed in detail to determine the interpolation methods which best capture the distribution of intense, orographically-induced precipitation. The interpolation techniques comparatively examined include: Inverse Distance Weighting (IDW), Ordinary Kriging (OK), and Kriging with External Drift (KED). Geostatistical methods rely on a robust anisotropic variogram for the definition of the spatial rainfall structure. Results indicate that IDW tends to significantly underestimate rainfall volumes whereas OK and KED methods capture spatial patterns and rainfall volumes induced by storm advection. Using numerical weather forecasts and elevation data as covariates for precipitation, we provide evidence for KED to outperform the other methods. Most significantly, the use of elevation as auxiliary information in KED of temperatures demonstrates minimal errors in estimated instantaneous rainfall volumes and provides instantaneous lapse rates which better capture snow/rainfall partitioning. Incorporation of the temperature and precipitation input fields into a hydrological model used for operational management was found to provide vastly improved outputs with respect to measured discharge volumes and flood peaks, with notable implications for flood modeling.

Diagnostics of sources of tropospheric ozone using data assimilation during the KORUS-AQ campaign

NASA Astrophysics Data System (ADS)

Gaubert, B.; Emmons, L. K.; Miyazaki, K.; Buchholz, R. R.; Tang, W.; Arellano, A. F., Jr.; Tilmes, S.; Barré, J.; Worden, H. M.; Raeder, K.; Anderson, J. L.; Edwards, D. P.

2017-12-01

Atmospheric oxidative capacity plays a crucial role in the fate of greenhouse gases and air pollutants as well as in the formation of secondary pollutants such as tropospheric ozone. The attribution of sources of tropospheric ozone is a difficult task because of biases in input parameters and forcings such as emissions and meteorology in addition to errors in chemical schemes. We assimilate satellite remote sensing observations of ozone precursors such as carbon monoxide (CO) and nitrogen dioxide (NO2) in the global coupled chemistry-transport model: Community Atmosphere Model with Chemistry (CAM-Chem). The assimilation is completed using an Ensemble Adjustment Kalman Filter (EAKF) in the Data Assimilation Research Testbed (DART) framework which allows estimates of unobserved parameters and potential constraints on secondary pollutants and emissions. The ensemble will be constructed using perturbations in chemical kinetics, different emission fields and by assimilating meteorological observations to fully assess uncertainties in the chemical fields of targeted species. We present a set of tools such as emission tags (CO and propane), combined with diagnostic analysis of chemical regimes and perturbation of emissions ratios to estimate a regional budget of primary and secondary pollutants in East Asia and their sensitivity to data assimilation. This study benefits from the large set of aircraft and ozonesonde in-situ observations from the Korea-United States Air Quality (KORUS-AQ) campaign that occurred in South Korea in May-June 2016.

The field campaigns of the European Tracer Experiment (ETEX). overview and results

NASA Astrophysics Data System (ADS)

Nodop, K.; Connolly, R.; Girardi, F.

As part of the European Tracer Experiment (ETEX) two successful atmospheric experiments were carried out in October and November, 1994. Perfluorocarbon (PFC) tracers were released into the atmosphere in Monterfil, Brittany, and air samples were taken at 168 stations in 17 European countries for 72 h after the release. Upper air tracer measurements were made from three aircraft. During the first experiment a westerly air flow transported the tracer plume north-eastwards across Europe. During the second release the flow was eastwards. The results from the ground sampling network allowed the determination of the cloud evolution as far as Sweden, Poland and Bulgaria. This demonstrated that the PFT technique can be successfully applied in long-range tracer experiments up to 2000 km. Typical background concentrations of the tracer used are around 5-7 fl ℓ -1 in ambient air. Concentrations in the plume ranged from 10 to above 200 fl/ℓ -1. The tracer release characteristics, the tracer concentrations at the ground and in upper air, the routine and additional meteorological observations at the ground level and in upper air, trajectories derived from constant-level balloons and the meteorological input fields for long-range transport models are assembled in the ETEX database. The ETEX database is accessible via the Internet. Here, an overview is given of the design of the experiment, the methods used and the data obtained.

Predicting Low Flow Conditions from Climatic Indices - Indicator-Based Modeling for Climate Change Impact Assessment

NASA Astrophysics Data System (ADS)

Fangmann, Anne; Haberlandt, Uwe

2014-05-01

In the face of climate change, the assessment of future hydrological regimes has become indispensable in the field of water resources management. Investigation of potential change is vital for proper planning, especially with regard to hydrological extremes. Commonly, projection of future streamflow is done applying process-based hydrological models, using climate model data as input, whose complex model structures generally require excessive amounts of time and effort for set-up and computation. This study aims at identifying practical alternatives to the employment of sophisticated models by considering simpler, yet sufficiently accurate methods for modeling rainfall-runoff relations with regard to hydrological extremes. The focus is thereby put on the prediction of low flow periods, which are, in contrast to flood events, characterized by extended durations and spatial dimensions. The models to be established in this study base on indicators, which characterize both meteorological and hydrological conditions within dry periods. This approach makes direct use of the coupling between atmospheric driving forces and streamflow response with the underlying presumption that low-precipitation and high-evaporation periods result in diminished flow, implying that relationships exist between the properties of both meteorological and hydrological events (duration, volume, severity etc.). Eventually, optimal combinations of meteorological indicators are sought that are suitable to predict various low flow characteristics with satisfactory accuracy. Two approaches for model specification are tested: a) multiple linear regression, and b) Fuzzy logic. The data used for this study are daily time series of mean discharge obtained from 294 gauges with variable record length situated in the federal state of Lower Saxony, Germany, as well as interpolated climate variables available for a period from 1951 to 2011. After extraction of a variety of indicators from the available discharge and climate time series on a bi-annual basis, regression and Fuzzy models are fit. Fitting is done in two variations: locally at each of the watersheds in the study area, and regionally, yielding one specific model expression for the entire study area. Models for the individual stations perform well using only the meteorological indicators as predictor variables, while the regional models require the additional input of catchment descriptors to account for the variability of the rainfall-runoff translation processes between the catchments.

Intercomparison of the community multiscale air quality model and CALGRID using process analysis.

PubMed

O'Neill, Susan M; Lamb, Brian K

2005-08-01

This study was designed to examine the similarities and differences between two advanced photochemical air quality modeling systems: EPA Models-3/CMAQ and CALGRID/CALMET. Both modeling systems were applied to an ozone episode that occurred along the I-5 urban corridor in western Washington and Oregon during July 11-14, 1996. Both models employed the same modeling domain and used the same detailed gridded emission inventory. The CMAQ model was run using both the CB-IV and RADM2 chemical mechanisms, while CALGRID was used with the SAPRC-97 chemical mechanism. Outputfrom the Mesoscale Meteorological Model (MM5) employed with observational nudging was used in both models. The two modeling systems, representing three chemical mechanisms and two sets of meteorological inputs, were evaluated in terms of statistical performance measures for both 1- and 8-h average observed ozone concentrations. The results showed that the different versions of the systems were more similar than different, and all versions performed well in the Portland region and downwind of Seattle but performed poorly in the more rural region north of Seattle. Improving the meteorological input into the CALGRID/CALMET system with planetary boundary layer (PBL) parameters from the Models-3/CMAQ meteorology preprocessor (MCIP) improved the performance of the CALGRID/CALMET system. The 8-h ensemble case was often the best performer of all the cases indicating that the models perform better over longer analysis periods. The 1-h ensemble case, derived from all runs, was not necessarily an improvement over the five individual cases, but the standard deviation about the mean provided a measure of overall modeling uncertainty. Process analysis was applied to examine the contribution of the individual processes to the species conservation equation. The process analysis results indicated that the two modeling systems arrive at similar solutions by very different means. Transport rates are faster and exhibit greater fluctuations in the CMAQ cases than in the CALGRID cases, which lead to different placement of the urban ozone plumes. The CALGRID cases, which rely on the SAPRC97 chemical mechanism, exhibited a greater diurnal production/loss cycle of ozone concentrations per hour compared to either the RADM2 or CBIV chemical mechanisms in the CMAQ cases. These results demonstrate the need for specialized process field measurements to confirm whether we are modeling ozone with valid processes.

Using self-organizing maps to infill missing data in hydro-meteorological time series from the Logone catchment, Lake Chad basin.

PubMed

Nkiaka, E; Nawaz, N R; Lovett, J C

2016-07-01

Hydro-meteorological data is an important asset that can enhance management of water resources. But existing data often contains gaps, leading to uncertainties and so compromising their use. Although many methods exist for infilling data gaps in hydro-meteorological time series, many of these methods require inputs from neighbouring stations, which are often not available, while other methods are computationally demanding. Computing techniques such as artificial intelligence can be used to address this challenge. Self-organizing maps (SOMs), which are a type of artificial neural network, were used for infilling gaps in a hydro-meteorological time series in a Sudano-Sahel catchment. The coefficients of determination obtained were all above 0.75 and 0.65 while the average topographic error was 0.008 and 0.02 for rainfall and river discharge time series, respectively. These results further indicate that SOMs are a robust and efficient method for infilling missing gaps in hydro-meteorological time series.

Overview of meteorological measurements for aerial spray modeling.

PubMed

Rafferty, J E; Biltoft, C A; Bowers, J F

1996-06-01

The routine meteorological observations made by the National Weather Service have a spatial resolution on the order of 1,000 km, whereas the resolution needed to conduct or model aerial spray applications is on the order of 1-10 km. Routinely available observations also do not include the detailed information on the turbulence and thermal structure of the boundary layer that is needed to predict the transport, dispersion, and deposition of aerial spray releases. This paper provides an overview of the information needed to develop the meteorological inputs for an aerial spray model such as the FSCBG and discusses the different types of instruments that are available to make the necessary measurements.

Filling the gaps in meteorological continuous data measured at FLUXNET sites with ERA-Interim reanalysis

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

Vuichard, N.; Papale, D.

In this study, exchanges of carbon, water and energy between the land surface and the atmosphere are monitored by eddy covariance technique at the ecosystem level. Currently, the FLUXNET database contains more than 500 registered sites, and up to 250 of them share data (free fair-use data set). Many modelling groups use the FLUXNET data set for evaluating ecosystem models' performance, but this requires uninterrupted time series for the meteorological variables used as input. Because original in situ data often contain gaps, from very short (few hours) up to relatively long (some months) ones, we develop a new and robustmore » method for filling the gaps in meteorological data measured at site level. Our approach has the benefit of making use of continuous data available globally (ERA-Interim) and a high temporal resolution spanning from 1989 to today. These data are, however, not measured at site level, and for this reason a method to downscale and correct the ERA-Interim data is needed. We apply this method to the level 4 data (L4) from the La Thuile collection, freely available after registration under a fair-use policy. The performance of the developed method varies across sites and is also function of the meteorological variable. On average over all sites, applying the bias correction method to the ERA-Interim data reduced the mismatch with the in situ data by 10 to 36 %, depending on the meteorological variable considered. In comparison to the internal variability of the in situ data, the root mean square error (RMSE) between the in situ data and the unbiased ERA-I (ERA-Interim) data remains relatively large (on average over all sites, from 27 to 76 % of the standard deviation of in situ data, depending on the meteorological variable considered). The performance of the method remains poor for the wind speed field, in particular regarding its capacity to conserve a standard deviation similar to the one measured at FLUXNET stations.« less

Filling the gaps in meteorological continuous data measured at FLUXNET sites with ERA-Interim reanalysis

DOE PAGES

Vuichard, N.; Papale, D.

2015-07-13

In this study, exchanges of carbon, water and energy between the land surface and the atmosphere are monitored by eddy covariance technique at the ecosystem level. Currently, the FLUXNET database contains more than 500 registered sites, and up to 250 of them share data (free fair-use data set). Many modelling groups use the FLUXNET data set for evaluating ecosystem models' performance, but this requires uninterrupted time series for the meteorological variables used as input. Because original in situ data often contain gaps, from very short (few hours) up to relatively long (some months) ones, we develop a new and robustmore » method for filling the gaps in meteorological data measured at site level. Our approach has the benefit of making use of continuous data available globally (ERA-Interim) and a high temporal resolution spanning from 1989 to today. These data are, however, not measured at site level, and for this reason a method to downscale and correct the ERA-Interim data is needed. We apply this method to the level 4 data (L4) from the La Thuile collection, freely available after registration under a fair-use policy. The performance of the developed method varies across sites and is also function of the meteorological variable. On average over all sites, applying the bias correction method to the ERA-Interim data reduced the mismatch with the in situ data by 10 to 36 %, depending on the meteorological variable considered. In comparison to the internal variability of the in situ data, the root mean square error (RMSE) between the in situ data and the unbiased ERA-I (ERA-Interim) data remains relatively large (on average over all sites, from 27 to 76 % of the standard deviation of in situ data, depending on the meteorological variable considered). The performance of the method remains poor for the wind speed field, in particular regarding its capacity to conserve a standard deviation similar to the one measured at FLUXNET stations.« less

A study on the uncertainty based on Meteorological fields on Source-receptor Relationships for Total Nitrate in the Northeast Asia

NASA Astrophysics Data System (ADS)

Sunwoo, Y.; Park, J.; Kim, S.; Ma, Y.; Chang, I.

2010-12-01

Northeast Asia hosts more than one third of world population and the emission of pollutants trends to increase rapidly, because of economic growth and the increase of the consumption in high energy intensity. In case of air pollutants, especially, its characteristics of emissions and transportation become issued nationally, in terms of not only environmental aspects, but also long-range transboundary transportation. In meteorological characteristics, westerlies area means what air pollutants that emitted from China can be delivered to South Korea. Therefore, considering meteorological factors can be important to understand air pollution phenomena. In this study, we used MM5(Fifth-Generation Mesoscale Model) and WRF(Weather Research and Forecasting Model) to produce the meteorological fields. We analyzed the feature of physics option in each model and the difference due to characteristic of WRF and MM5. We are trying to analyze the uncertainty of source-receptor relationships for total nitrate according to meteorological fields in the Northeast Asia. We produced the each meteorological fields that apply the same domain, same initial and boundary conditions, the best similar physics option. S-R relationships in terms of amount and fractional number for total nitrate (sum of N from HNO3, nitrate and PAN) were calculated by EMEP method 3.

Daily River Flow Forecasting with Hybrid Support Vector Machine – Particle Swarm Optimization

NASA Astrophysics Data System (ADS)

Zaini, N.; Malek, M. A.; Yusoff, M.; Mardi, N. H.; Norhisham, S.

2018-04-01

The application of artificial intelligence techniques for river flow forecasting can further improve the management of water resources and flood prevention. This study concerns the development of support vector machine (SVM) based model and its hybridization with particle swarm optimization (PSO) to forecast short term daily river flow at Upper Bertam Catchment located in Cameron Highland, Malaysia. Ten years duration of historical rainfall, antecedent river flow data and various meteorology parameters data from 2003 to 2012 are used in this study. Four SVM based models are proposed which are SVM1, SVM2, SVM-PSO1 and SVM-PSO2 to forecast 1 to 7 day ahead of river flow. SVM1 and SVM-PSO1 are the models with historical rainfall and antecedent river flow as its input, while SVM2 and SVM-PSO2 are the models with historical rainfall, antecedent river flow data and additional meteorological parameters as input. The performances of the proposed model are measured in term of RMSE and R2 . It is found that, SVM2 outperformed SVM1 and SVM-PSO2 outperformed SVM-PSO1 which meant the additional meteorology parameters used as input to the proposed models significantly affect the model performances. Hybrid models SVM-PSO1 and SVM-PSO2 yield higher performances as compared to SVM1 and SVM2. It is found that hybrid models are more effective in forecasting river flow at 1 to 7 day ahead at the study area.

Development and application of artificial neural network models to estimate values of a complex human thermal comfort index associated with urban heat and cool island patterns using air temperature data from a standard meteorological station

NASA Astrophysics Data System (ADS)

Moustris, Konstantinos; Tsiros, Ioannis X.; Tseliou, Areti; Nastos, Panagiotis

2018-04-01

The present study deals with the development and application of artificial neural network models (ANNs) to estimate the values of a complex human thermal comfort-discomfort index associated with urban heat and cool island conditions inside various urban clusters using as only inputs air temperature data from a standard meteorological station. The index used in the study is the Physiologically Equivalent Temperature (PET) index which requires as inputs, among others, air temperature, relative humidity, wind speed, and radiation (short- and long-wave components). For the estimation of PET hourly values, ANN models were developed, appropriately trained, and tested. Model results are compared to values calculated by the PET index based on field monitoring data for various urban clusters (street, square, park, courtyard, and gallery) in the city of Athens (Greece) during an extreme hot weather summer period. For the evaluation of the predictive ability of the developed ANN models, several statistical evaluation indices were applied: the mean bias error, the root mean square error, the index of agreement, the coefficient of determination, the true predictive rate, the false alarm rate, and the Success Index. According to the results, it seems that ANNs present a remarkable ability to estimate hourly PET values within various urban clusters using only hourly values of air temperature. This is very important in cases where the human thermal comfort-discomfort conditions have to be analyzed and the only available parameter is air temperature.

Development and application of artificial neural network models to estimate values of a complex human thermal comfort index associated with urban heat and cool island patterns using air temperature data from a standard meteorological station.

PubMed

Moustris, Konstantinos; Tsiros, Ioannis X; Tseliou, Areti; Nastos, Panagiotis

2018-04-11

The present study deals with the development and application of artificial neural network models (ANNs) to estimate the values of a complex human thermal comfort-discomfort index associated with urban heat and cool island conditions inside various urban clusters using as only inputs air temperature data from a standard meteorological station. The index used in the study is the Physiologically Equivalent Temperature (PET) index which requires as inputs, among others, air temperature, relative humidity, wind speed, and radiation (short- and long-wave components). For the estimation of PET hourly values, ANN models were developed, appropriately trained, and tested. Model results are compared to values calculated by the PET index based on field monitoring data for various urban clusters (street, square, park, courtyard, and gallery) in the city of Athens (Greece) during an extreme hot weather summer period. For the evaluation of the predictive ability of the developed ANN models, several statistical evaluation indices were applied: the mean bias error, the root mean square error, the index of agreement, the coefficient of determination, the true predictive rate, the false alarm rate, and the Success Index. According to the results, it seems that ANNs present a remarkable ability to estimate hourly PET values within various urban clusters using only hourly values of air temperature. This is very important in cases where the human thermal comfort-discomfort conditions have to be analyzed and the only available parameter is air temperature.

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.

Numerical Weather Prediction Models on Linux Boxes as tools in meteorological education in Hungary

NASA Astrophysics Data System (ADS)

Gyongyosi, A. Z.; Andre, K.; Salavec, P.; Horanyi, A.; Szepszo, G.; Mille, M.; Tasnadi, P.; Weidiger, T.

2012-04-01

Education of Meteorologist in Hungary - according to the Bologna Process - has three stages: BSc, MSc and PhD, and students graduating at each stage get the respective degree (BSc, MSc and PhD). The three year long base BSc course in Meteorology can be chosen by undergraduate students in the fields of Geosciences, Environmental Sciences and Physics. BasicsFundamentals in Mathematics (Calculus), Physics (General and Theoretical) Physics and Informatics are emphasized during their elementary education. The two year long MSc course - in which about 15 to 25 students are admitted each year - can be studied only at our the Eötvös Loránd uUniversity in the our country. Our aim is to give a basic education in all fields of Meteorology. Main topics are: Climatology, Atmospheric Physics, Atmospheric Chemistry, Dynamic and Synoptic Meteorology, Numerical Weather Prediction, modeling Modeling of surfaceSurface-atmosphere Iinteractions and Cclimate change. Education is performed in two branches: Climate Researcher and Forecaster. Education of Meteorologist in Hungary - according to the Bologna Process - has three stages: BSc, MSc and PhD, and students graduating at each stage get the respective degree. The three year long BSc course in Meteorology can be chosen by undergraduate students in the fields of Geosciences, Environmental Sciences and Physics. Fundamentals in Mathematics (Calculus), (General and Theoretical) Physics and Informatics are emphasized during their elementary education. The two year long MSc course - in which about 15 to 25 students are admitted each year - can be studied only at the Eötvös Loránd University in our country. Our aim is to give a basic education in all fields of Meteorology: Climatology, Atmospheric Physics, Atmospheric Chemistry, Dynamic and Synoptic Meteorology, Numerical Weather Prediction, Modeling of Surface-atmosphere Interactions and Climate change. Education is performed in two branches: Climate Researcher and Forecaster. Numerical modeling became a common tool in the daily practice of weather experts forecasters due to the i) increasing user demands for weather data by the costumers, ii) the growth in computer resources, iii) numerical weather prediction systems available for integration on affordable, off the shelf computers and iv) available input data (from ECMWF or NCEP) for model integrations. Beside learning the theoretical basis, since the last year. Students in their MSc or BSc Thesis Research or in Student's Research ProjectsStudent's Research Projects h have the opportunity to run numerical models and to analyze the outputs for different purposes including wind energy estimation, simulation of the dynamics of a polar low, and subtropical cyclones, analysis of the isentropic potential vorticity field, examination of coupled atmospheric dispersion models, etc. A special course in the application of numerical modeling has been held (is being announced for the upcoming semester) (is being announced for the upcoming semester) for our students in order to improve their skills on this field. Several numerical model (NRIPR ETA and WRF) systems have been adapted in the University and integrated WRF have been tested and used for the geographical region of the Carpathian Basin (NRIPR, ETA and WRF). Recently ALADIN/CHAPEAU the academic version of the ARPEGE ALADIN cy33t1 meso-scale numerical weather prediction model system (which is the operational forecasting tool of our National Weather Service) has been installed at our Institute. ALADIN is the operational forecasting model of the Hungarian Meteorological Service and developed in the framework of the international ALADIN co-operation. Our main objectives are i) the analysis of different typical weather situations, ii) fine tuning of parameterization schemes and the iii) comparison of the ALADIN/CHAPEAU and WRF model outputs based on case studies. The necessary hardware and software innovations has have been done. In the presentation the computer resources needed for the integration of both WRF and ALADIN/CHAPEAU models will be briefly described. The software developments performed for the evaluation and comparison of the different modeling systems will be demonstrated. The main objectives of the education program on the practical numerical weather modeling will be introduced, as well as its detailed thematics and the structure of the labs.

Exploring objective climate classification for the Himalayan arc and adjacent regions using gridded data sources

NASA Astrophysics Data System (ADS)

Forsythe, N.; Blenkinsop, S.; Fowler, H. J.

2015-05-01

A three-step climate classification was applied to a spatial domain covering the Himalayan arc and adjacent plains regions using input data from four global meteorological reanalyses. Input variables were selected based on an understanding of the climatic drivers of regional water resource variability and crop yields. Principal component analysis (PCA) of those variables and k-means clustering on the PCA outputs revealed a reanalysis ensemble consensus for eight macro-climate zones. Spatial statistics of input variables for each zone revealed consistent, distinct climatologies. This climate classification approach has potential for enhancing assessment of climatic influences on water resources and food security as well as for characterising the skill and bias of gridded data sets, both meteorological reanalyses and climate models, for reproducing subregional climatologies. Through their spatial descriptors (area, geographic centroid, elevation mean range), climate classifications also provide metrics, beyond simple changes in individual variables, with which to assess the magnitude of projected climate change. Such sophisticated metrics are of particular interest for regions, including mountainous areas, where natural and anthropogenic systems are expected to be sensitive to incremental climate shifts.

Forecasting volcanic ash dispersal and coeval resuspension during the April-May 2015 Calbuco eruption

NASA Astrophysics Data System (ADS)

Reckziegel, F.; Bustos, E.; Mingari, L.; Báez, W.; Villarosa, G.; Folch, A.; Collini, E.; Viramonte, J.; Romero, J.; Osores, S.

2016-07-01

Atmospheric dispersion of volcanic ash from explosive eruptions or from subsequent fallout deposit resuspension causes a range of impacts and disruptions on human activities and ecosystems. The April-May 2015 Calbuco eruption in Chile involved eruption and resuspension activities. We overview the chronology, effects, and products resulting from these events, in order to validate an operational forecast strategy for tephra dispersal. The modelling strategy builds on coupling the meteorological Weather Research and Forecasting (WRF/ARW) model with the FALL3D dispersal model for eruptive and resuspension processes. The eruption modelling considers two distinct particle granulometries, a preliminary first guess distribution used operationally when no field data was available yet, and a refined distribution based on field measurements. Volcanological inputs were inferred from eruption reports and results from an Argentina-Chilean ash sample data network, which performed in-situ sampling during the eruption. In order to validate the modelling strategy, results were compared with satellite retrievals and ground deposit measurements. Results indicate that the WRF-FALL3D modelling system can provide reasonable forecasts in both eruption and resuspension modes, particularly when the adjusted granulometry is considered. The study also highlights the importance of having dedicated datasets of active volcanoes furnishing first-guess model inputs during the early stages of an eruption.

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.

Interannual Variability in Intercontinental Transport

NASA Technical Reports Server (NTRS)

Gupta, Mohan; Douglass, Anne; Kawa, S. Randy; Pawson, Steven

2003-01-01

We have investigated the importance of intercontinental transport using source-receptor relationship. A global radon-like and seven regional tracers were used in three-dimensional model simulations to quantify their contributions to column burdens and vertical profiles at world-wide receptors. Sensitivity of these contributions to meteorological input was examined using different years of meteorology in two atmospheric simulations. Results show that Asian emission influences tracer distributions in its eastern downwind regions extending as far as Europe with major contributions in mid- and upper troposphere. On the western and eastern sides of the US, Asian contribution to annual average column burdens are 37% and 5% respectively with strong monthly variations. At an altitude of 10 km, these contributions are 75% and 25% respectively. North American emissions contribute more than 15% to annual average column burden and about 50% at 8 km altitude over the European region. Contributions from tropical African emissions are wide-spread in both the hemispheres. Differences in meteorological input cause non-uniform redistribution of tracer mass throughout the troposphere at all receptors. We also show that in model-model and model-data comparison, correlation analysis of tracer's spatial gradients provides an added measure of model's performance.

Innovations in Basic Flight Training for the Indonesian Air Force

DTIC Science & Technology

1990-12-01

microeconomic theory that could approximate the optimum mix of training hours between an aircraft and simulator, and therefore improve cost effectiveness...The microeconomic theory being used is normally employed when showing production with two variable inputs. An example of variable inputs would be labor...NAS Corpus Christi, Texas, Aerodynamics of the T-34C, 1989. 26. Naval Air Training Command, NAS Corpus Christi, Texas, Meteorological Theory Workbook

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.

Hourly predictive Levenberg-Marquardt ANN and multi linear regression models for predicting of dew point temperature

NASA Astrophysics Data System (ADS)

Zounemat-Kermani, Mohammad

2012-08-01

In this study, the ability of two models of multi linear regression (MLR) and Levenberg-Marquardt (LM) feed-forward neural network was examined to estimate the hourly dew point temperature. Dew point temperature is the temperature at which water vapor in the air condenses into liquid. This temperature can be useful in estimating meteorological variables such as fog, rain, snow, dew, and evapotranspiration and in investigating agronomical issues as stomatal closure in plants. The availability of hourly records of climatic data (air temperature, relative humidity and pressure) which could be used to predict dew point temperature initiated the practice of modeling. Additionally, the wind vector (wind speed magnitude and direction) and conceptual input of weather condition were employed as other input variables. The three quantitative standard statistical performance evaluation measures, i.e. the root mean squared error, mean absolute error, and absolute logarithmic Nash-Sutcliffe efficiency coefficient ( {| {{{Log}}({{NS}})} |} ) were employed to evaluate the performances of the developed models. The results showed that applying wind vector and weather condition as input vectors along with meteorological variables could slightly increase the ANN and MLR predictive accuracy. The results also revealed that LM-NN was superior to MLR model and the best performance was obtained by considering all potential input variables in terms of different evaluation criteria.

A site-specific screening comparison of modeled and monitored air dispersion and deposition for perfluorooctanoate.

PubMed

Barton, Catherine A; Zarzecki, Charles J; Russell, Mark H

2010-04-01

This work assessed the usefulness of a current air quality model (American Meteorological Society/Environmental Protection Agency Regulatory Model [AERMOD]) for predicting air concentrations and deposition of perfluorooctanoate (PFO) near a manufacturing facility. Air quality models play an important role in providing information for verifying permitting conditions and for exposure assessment purposes. It is important to ensure traditional modeling approaches are applicable to perfluorinated compounds, which are known to have unusual properties. Measured field data were compared with modeling predictions to show that AERMOD adequately located the maximum air concentration in the study area, provided representative or conservative air concentration estimates, and demonstrated bias and scatter not significantly different than that reported for other compounds. Surface soil/grass concentrations resulting from modeled deposition flux also showed acceptable bias and scatter compared with measured concentrations of PFO in soil/grass samples. Errors in predictions of air concentrations or deposition may be best explained by meteorological input uncertainty and conservatism in the PRIME algorithm used to account for building downwash. In general, AERMOD was found to be a useful screening tool for modeling the dispersion and deposition of PFO in air near a manufacturing facility.

Ozone levels in the Empty Quarter of Saudi Arabia--application of adaptive neuro-fuzzy model.

PubMed

Rahman, Syed Masiur; Khondaker, A N; Khan, Rouf Ahmad

2013-05-01

In arid regions, primary pollutants may contribute to the increase of ozone levels and cause negative effects on biotic health. This study investigates the use of adaptive neuro-fuzzy inference system (ANFIS) for ozone prediction. The initial fuzzy inference system is developed by using fuzzy C-means (FCM) and subtractive clustering (SC) algorithms, which determines the important rules, increases generalization capability of the fuzzy inference system, reduces computational needs, and ensures speedy model development. The study area is located in the Empty Quarter of Saudi Arabia, which is considered as a source of huge potential for oil and gas field development. The developed clustering algorithm-based ANFIS model used meteorological data and derived meteorological data, along with NO and NO₂ concentrations and their transformations, as inputs. The root mean square error and Willmott's index of agreement of the FCM- and SC-based ANFIS models are 3.5 ppbv and 0.99, and 8.9 ppbv and 0.95, respectively. Based on the analysis of the performance measures and regression error characteristic curves, it is concluded that the FCM-based ANFIS model outperforms the SC-based ANFIS model.

Simulating air temperature in an urban street canyon in all weather conditions using measured data at a reference meteorological station

NASA Astrophysics Data System (ADS)

Erell, E.; Williamson, T.

2006-10-01

A model is proposed that adapts data from a standard meteorological station to provide realistic site-specific air temperature in a city street exposed to the same meso-scale environment. In addition to a rudimentary description of the two sites, the canyon air temperature (CAT) model requires only inputs measured at standard weather stations; yet it is capable of accurately predicting the evolution of air temperature in all weather conditions for extended periods. It simulates the effect of urban geometry on radiant exchange; the effect of moisture availability on latent heat flux; energy stored in the ground and in building surfaces; air flow in the street based on wind above roof height; and the sensible heat flux from individual surfaces and from the street canyon as a whole. The CAT model has been tested on field data measured in a monitoring program carried out in Adelaide, Australia, in 2000-2001. After calibrating the model, predicted air temperature correlated well with measured data in all weather conditions over extended periods. The experimental validation provides additional evidence in support of a number of parameterisation schemes incorporated in the model to account for sensible heat and storage flux.

Air Quality and Meteorological Boundary Conditions during the MCMA-2003 Field Campaign

NASA Astrophysics Data System (ADS)

Sosa, G.; Arriaga, J.; Vega, E.; Magaña, V.; Caetano, E.; de Foy, B.; Molina, L. T.; Molina, M. J.; Ramos, R.; Retama, A.; Zaragoza, J.; Martínez, A. P.; Márquez, C.; Cárdenas, B.; Lamb, B.; Velasco, E.; Allwine, E.; Pressley, S.; Westberg, H.; Reyes, R.

2004-12-01

A comprehensive field campaign to characterize photochemical smog in the Mexico City Metropolitan Area (MCMA) was conducted during April 2003. An important number of equipment was deployed all around the urban core and its surroundings to measure gas and particles composition from the various sources and receptor sites. In addition to air quality measurements, meteorology variables were also taken by regular weather meteorological stations, tethered balloons, radiosondes, sodars and lidars. One important issue with regard to the field campaign was the characterization of the boundary conditions in order to feed meteorological and air quality models. Four boundary sites were selected to measure continuously criteria pollutants, VOC and meteorological variables at surface level. Vertical meteorological profiles were measured at three other sites : radiosondes in Tacubaya site were launched every six hours daily; tethered balloons were launched at CENICA and FES-Cuautitlan sites according to the weather conditions, and one sodar was deployed at UNAM site in the south of the city. Additionally to these measurements, two fixed meteorological monitoring networks deployed along the city were available to complement these measurements. In general, we observed that transport of pollutants from the city to the boundary sites changes every day, according to the coupling between synoptic and local winds. This effect were less important at elevated sites such as Cerro de la Catedral and ININ, where synoptic wind were more dominant during the field campaign. Also, local sources nearby boundary sites hide the influence of pollution coming from the city some days, particularly at the La Reforma site.

Carbonaceous aerosols and Impacts on regional climate over South Asia

NASA Astrophysics Data System (ADS)

Pathak, B.; Parottil, A.

2017-12-01

A comprehensive assessment on the effects of carbonaceous aerosols over regional climate of South Asia CORDEX Domain is carried out using the ICTP developed Regional climate model version 4 (RegCM 4.4). Five different simulations considering (a) Carbonaceous aerosols with feedback to meteorological field (EXP1), (b) Carbonaceous aerosols without feedback to meteorological field (c) only Black Carbon with feed back to meteorological field (EXP3) and (d) only Black Carbon without feed back to meteorological field (EXP4) and only meteorology simulation (CNTL) are performed. All the five experiments are integrated from 01 January 2008 to 01 January 2012 continuously with a horizontal resolution of 50 km with first one year as spin up time. The simulated meteorology for all the simulations is validated by comparing with observations. The influence of carbonaceous aerosols on Direct Radiative Forcing (DRF) at the top of the atmosphere (TOA) and within the atmosphere (ATM) over the South Asian region with focus on Indian subcontinent is carried out. The contribution of black carbon to the total DRF and its significance is analyzed. Modulation in precipitation and temperature with the aerosol-climate feedback is studied by comparing the meteorological parameters in CNTL with CARB/BC with and without feedback simulations. In general, black carbon is found to reduce the precipitation, wind over the region more strongly than total carbonaceous aerosols. Role of black carbon in warming the surface is investigated by comparing the RegCM simulation considering both biomass burning and anthropogenic emissions with simulations considering only anthropogenic simulations.

Department of Defense meteorological and environmental inputs to aviation systems

NASA Technical Reports Server (NTRS)

Try, P. D.

1983-01-01

Recommendations based on need, cost, and achievement of flight safety are offered, and the re-evaluation of weather parameters needed for safe landing operations that lead to reliable and consistent automated observation capabilities are considered.

What do you want to be in ten years? - Advising meteorology students in the post-Twister era

NASA Astrophysics Data System (ADS)

Snow, J. T.; Hempe, M.

2012-12-01

"What do you want to be in ten years?' This is a question we ask our students, freshmen and transfer, when they first arrive in the College student services center. Often the answer is "I don't know. I just want to be in meteorology." This response leads to a discussion of career opportunities in meteorology and related fields, including what might be called faux-careers, such as professional storm chasing and weather tour operations. (Students often have been misled by what they have seen in television shows.) Many students arrive on our doorstep with their heart set on a degree in meteorology, but lack knowledge of what the field is about or how challenging a meteorology degree program really is. We find ourselves spending a great deal of time convincing students that they need to explore the real opportunities in meteorology and related fields, which are many. Fortunately, because of the concentration of University and federal weather organizations in the National Weather Center and private sector weather companies in adjacent buildings, we are able to show concrete examples of real careers by means of tours, job shadowing, and introductions to alumni employed in these organizations. Also, as the students' progress in their studies, they discover the many opportunities for undergraduate employment, research experiences, and internships in these same organizations, through which they gain an appreciation for what constitutes a real career in modern meteorology. Further, many of today's careers in meteorology require a broad, global perspective. Unfortunately, many meteorology students have not traveled widely, but again have only seen what the media provides about distant lands and peoples. Accordingly, we encourage our undergraduate students to take advantage of our unique opportunities for overseas experiences in meteorology. Through arrangements with the met programs at the University of Reading (England), Monash University (Australia), and University of Hamburg (Germany), we are able to offer a one-semester international experience structured so that there are no delays in a participating student's graduation date. The student who takes advantage of this opportunity gains a broad perspective of the field and learns a great deal about themselves and the world.

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.

Uncertainty Quantification of Evapotranspiration and Infiltration from Modeling and Historic Time Series at the Savannah River F-Area

NASA Astrophysics Data System (ADS)

Faybishenko, B.; Flach, G. P.

2012-12-01

The objectives of this presentation are: (a) to illustrate the application of Monte Carlo and fuzzy-probabilistic approaches for uncertainty quantification (UQ) in predictions of potential evapotranspiration (PET), actual evapotranspiration (ET), and infiltration (I), using uncertain hydrological or meteorological time series data, and (b) to compare the results of these calculations with those from field measurements at the U.S. Department of Energy Savannah River Site (SRS), near Aiken, South Carolina, USA. The UQ calculations include the evaluation of aleatory (parameter uncertainty) and epistemic (model) uncertainties. The effect of aleatory uncertainty is expressed by assigning the probability distributions of input parameters, using historical monthly averaged data from the meteorological station at the SRS. The combined effect of aleatory and epistemic uncertainties on the UQ of PET, ET, and Iis then expressed by aggregating the results of calculations from multiple models using a p-box and fuzzy numbers. The uncertainty in PETis calculated using the Bair-Robertson, Blaney-Criddle, Caprio, Hargreaves-Samani, Hamon, Jensen-Haise, Linacre, Makkink, Priestly-Taylor, Penman, Penman-Monteith, Thornthwaite, and Turc models. Then, ET is calculated from the modified Budyko model, followed by calculations of I from the water balance equation. We show that probabilistic and fuzzy-probabilistic calculations using multiple models generate the PET, ET, and Idistributions, which are well within the range of field measurements. We also show that a selection of a subset of models can be used to constrain the uncertainty quantification of PET, ET, and I.

Aerosol physicochemical properties in relation to meteorology: Case studies in urban, marine, and arid settings

NASA Astrophysics Data System (ADS)

Wonaschuetz, Anna

Atmospheric aerosols are a highly relevant component of the climate system affecting atmospheric radiative transfer and the hydrological cycle. As opposed to other key atmospheric constituents with climatic relevance, atmospheric aerosol particles are highly heterogeneous in time and space with respect to their size, concentration, chemical composition and physical properties. Many aspects of their life cycle are not understood, making them difficult to represent in climate models and hard to control as a pollutant. Aerosol-cloud interactions in particular are infamous as a major source of uncertainty in future climate predictions. Field measurements are an important source of information for the modeling community and can lead to a better understanding of chemical and microphysical processes. In this study, field data from urban, marine, and arid settings are analyzed and the impact of meteorological conditions on the evolution of aerosol particles while in the atmosphere is investigated. Particular attention is given to organic aerosols, which are a poorly understood component of atmospheric aerosols. Local wind characteristics, solar radiation, relative humidity and the presence or absence of clouds and fog are found to be crucial factors in the transport and chemical evolution of aerosol particles. Organic aerosols in particular are found to be heavily impacted by processes in the liquid phase (cloud droplets and aerosol water). The reported measurements serve to improve the process-level understanding of aerosol evolution in different environments and to inform the modeling community by providing realistic values for input parameters and validation of model calculations.

Sensitivity analysis of radionuclides atmospheric dispersion following the Fukushima accident

NASA Astrophysics Data System (ADS)

Girard, Sylvain; Korsakissok, Irène; Mallet, Vivien

2014-05-01

Atmospheric dispersion models are used in response to accidental releases with two purposes: - minimising the population exposure during the accident; - complementing field measurements for the assessment of short and long term environmental and sanitary impacts. The predictions of these models are subject to considerable uncertainties of various origins. Notably, input data, such as meteorological fields or estimations of emitted quantities as function of time, are highly uncertain. The case studied here is the atmospheric release of radionuclides following the Fukushima Daiichi disaster. The model used in this study is Polyphemus/Polair3D, from which derives IRSN's operational long distance atmospheric dispersion model ldX. A sensitivity analysis was conducted in order to estimate the relative importance of a set of identified uncertainty sources. The complexity of this task was increased by four characteristics shared by most environmental models: - high dimensional inputs; - correlated inputs or inputs with complex structures; - high dimensional output; - multiplicity of purposes that require sophisticated and non-systematic post-processing of the output. The sensitivities of a set of outputs were estimated with the Morris screening method. The input ranking was highly dependent on the considered output. Yet, a few variables, such as horizontal diffusion coefficient or clouds thickness, were found to have a weak influence on most of them and could be discarded from further studies. The sensitivity analysis procedure was also applied to indicators of the model performance computed on a set of gamma dose rates observations. This original approach is of particular interest since observations could be used later to calibrate the input variables probability distributions. Indeed, only the variables that are influential on performance scores are likely to allow for calibration. An indicator based on emission peaks time matching was elaborated in order to complement classical statistical scores which were dominated by deposit dose rates and almost insensitive to lower atmosphere dose rates. The substantial sensitivity of these performance indicators is auspicious for future calibration attempts and indicates that the simple perturbations used here may be sufficient to represent an essential part of the overall uncertainty.

Analysis of source regions and meteorological factors for the variability of spring PM10 concentrations in Seoul, Korea

NASA Astrophysics Data System (ADS)

Lee, Jangho; Kim, Kwang-Yul

2018-02-01

CSEOF analysis is applied for the springtime (March, April, May) daily PM10 concentrations measured at 23 Ministry of Environment stations in Seoul, Korea for the period of 2003-2012. Six meteorological variables at 12 pressure levels are also acquired from the ERA Interim reanalysis datasets. CSEOF analysis is conducted for each meteorological variable over East Asia. Regression analysis is conducted in CSEOF space between the PM10 concentrations and individual meteorological variables to identify associated atmospheric conditions for each CSEOF mode. By adding the regressed loading vectors with the mean meteorological fields, the daily atmospheric conditions are obtained for the first five CSEOF modes. Then, HYSPLIT model is run with the atmospheric conditions for each CSEOF mode in order to back trace the air parcels and dust reaching Seoul. The K-means clustering algorithm is applied to identify major source regions for each CSEOF mode of the PM10 concentrations in Seoul. Three main source regions identified based on the mean fields are: (1) northern Taklamakan Desert (NTD), (2) Gobi Desert and (GD), and (3) East China industrial area (ECI). The main source regions for the mean meteorological fields are consistent with those of previous study; 41% of the source locations are located in GD followed by ECI (37%) and NTD (21%). Back trajectory calculations based on CSEOF analysis of meteorological variables identify distinct source characteristics associated with each CSEOF mode and greatly facilitate the interpretation of the PM10 variability in Seoul in terms of transportation route and meteorological conditions including the source area.

Final Report: Update of the Glossary of Meteorology, September 1, 1994 - August 3, 1999

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

American Meteorological Society

2000-01-24

The American Meteorological Society has updated the Glossary of Meteorology from the first addition which was published in 1959. The second edition contains over 12,000 entries in meteorology and related fields. The glossary will be made available in both book and CD-ROM formats. DOE was one of six federal agencies that provided support for this project.

Consequences of varied soil hydraulic and meteorological complexity on unsaturated zone time lag estimates.

PubMed

Vero, S E; Ibrahim, T G; Creamer, R E; Grant, J; Healy, M G; Henry, T; Kramers, G; Richards, K G; Fenton, O

2014-12-01

The true efficacy of a programme of agricultural mitigation measures within a catchment to improve water quality can be determined only after a certain hydrologic time lag period (subsequent to implementation) has elapsed. As the biophysical response to policy is not synchronous, accurate estimates of total time lag (unsaturated and saturated) become critical to manage the expectations of policy makers. The estimation of the vertical unsaturated zone component of time lag is vital as it indicates early trends (initial breakthrough), bulk (centre of mass) and total (Exit) travel times. Typically, estimation of time lag through the unsaturated zone is poor, due to the lack of site specific soil physical data, or by assuming saturated conditions. Numerical models (e.g. Hydrus 1D) enable estimates of time lag with varied levels of input data. The current study examines the consequences of varied soil hydraulic and meteorological complexity on unsaturated zone time lag estimates using simulated and actual soil profiles. Results indicated that: greater temporal resolution (from daily to hourly) of meteorological data was more critical as the saturated hydraulic conductivity of the soil decreased; high clay content soils failed to converge reflecting prevalence of lateral component as a contaminant pathway; elucidation of soil hydraulic properties was influenced by the complexity of soil physical data employed (textural menu, ROSETTA, full and partial soil water characteristic curves), which consequently affected time lag ranges; as the importance of the unsaturated zone increases with respect to total travel times the requirements for high complexity/resolution input data become greater. The methodology presented herein demonstrates that decisions made regarding input data and landscape position will have consequences for the estimated range of vertical travel times. Insufficiencies or inaccuracies regarding such input data can therefore mislead policy makers regarding the achievability of water quality targets. Copyright © 2014 Elsevier B.V. All rights reserved.

Global Surface Solar Energy Anomalies Including El Nino and La Nina Years

NASA Technical Reports Server (NTRS)

Whitlock, C. H.; Brown, D. E.; Chandler, W. S.; DiPasquale, R. C.; Ritchey, Nancy A.; Gupta, Shashi K.; Wilber, Anne C.; Kratz, David P.; Stackhouse, Paul W.

2001-01-01

This paper synthesizes past events in an attempt to define the general magnitude, duration, and location of large surface solar anomalies over the globe. Surface solar energy values are mostly a function of solar zenith angle, cloud conditions, column atmospheric water vapor, aerosols, and surface albedo. For this study, solar and meteorological parameters for the 10-yr period July 1983 through June 1993 are used. These data were generated as part of the Release 3 Surface meteorology and Solar Energy (SSE) activity under the NASA Earth Science Enterprise (ESE) effort. Release 3 SSE uses upgraded input data and methods relative to previous releases. Cloud conditions are based on recent NASA Version-D International Satellite Cloud Climatology Project (ISCCP) global satellite radiation and cloud data. Meteorological inputs are from Version-I Goddard Earth Observing System (GEOS) reanalysis data that uses both weather station and satellite information. Aerosol transmission for different regions and seasons are for an 'average' year based on historic solar energy data from over 1000 ground sites courtesy of Natural Resources Canada (NRCan). These data are input to a new Langley Parameterized Shortwave Algorithm (LPSA) that calculates surface albedo and surface solar energy. That algorithm is an upgraded version of the 'Staylor' algorithm. Calculations are performed for a 280X280 km equal-area grid system over the globe based on 3-hourly input data. A bi-linear interpolation process is used to estimate data output values on a 1 X 1 degree grid system over the globe. Maximum anomalies are examined relative to El Nino and La Nina events in the tropical Pacific Ocean. Maximum year-to-year anomalies over the globe are provided for a 10-year period. The data may assist in the design of systems with increased reliability. It may also allow for better planning for emergency assistance during some atypical events.

A Model-based Approach to Scaling GPP and NPP in Support of MODIS Land Product Validation

NASA Astrophysics Data System (ADS)

Turner, D. P.; Cohen, W. B.; Gower, S. T.; Ritts, W. D.

2003-12-01

Global products from the Earth-orbiting MODIS sensor include land cover, leaf area index (LAI), FPAR, 8-day gross primary production (GPP), and annual net primary production (NPP) at the 1 km spatial resolution. The BigFoot Project was designed specifically to validate MODIS land products, and has initiated ground measurements at 9 sites representing a wide array of vegetation types. An ecosystem process model (Biome-BGC) is used to generate estimates of GPP and NPP for each 5 km x 5 km BigFoot site. Model inputs include land cover and LAI (from Landsat ETM+), daily meteorological data (from a centrally located eddy covariance flux tower), and soil characteristics. Model derived outputs are validated against field-measured NPP and flux tower-derived GPP. The resulting GPP and NPP estimates are then aggregated to the 1 km resolution for direct spatial comparison with corresponding MODIS products. At the high latitude sites (tundra and boreal forest), the MODIS GPP phenology closely tracks the BigFoot GPP, but there is a high bias in the MODIS GPP. In the temperate zone sites, problems with the timing and magnitude of the MODIS FPAR introduce differences in MODIS GPP compared to the validation data at some sites. However, the MODIS LAI/FPAR data are currently being reprocessed (=Collection 4) and new comparisons will be made for 2002. The BigFoot scaling approach permits precise overlap in spatial and temporal resolution between the MODIS products and BigFoot products, and thus permits the evaluation of specific components of the MODIS NPP algorithm. These components include meteorological inputs from the NASA Data Assimilation Office, LAI and FPAR from other MODIS algorithms, and biome-specific parameters for base respiration rate and light use efficiency.

General description and operation of the agro-environmental system: Crop management modeling. [Virginia

NASA Technical Reports Server (NTRS)

Gross, E.; Scott, J. H., Jr.

1981-01-01

Input for a data management system to provide farmers with information to improve crop management practices in Virginia requires monitoring of control crops at field stations, crop surveys derived from remotely sensed aircraft data, meteorological data from synchronous satellites, and details of local agricultural conditions. Presently models are under development for determining pest problems, water balance in the soil, stages of plant maturity, and optimum planting date. The status of the Cerospora leafspot model for peanut crop management is considered. Other models under development planned relate to Cylindtocladium Blackrot and Sclerotinia blight of peanuts, cyst nematode (Globerdena solanacearum) of tobacco, and red crown rot of soybeans. A software for program for estimating precipitation and solar radiation on a statewise basis is also being developed.

A holistic approach for large-scale derived flood frequency analysis

NASA Astrophysics Data System (ADS)

Dung Nguyen, Viet; Apel, Heiko; Hundecha, Yeshewatesfa; Guse, Björn; Sergiy, Vorogushyn; Merz, Bruno

2017-04-01

Spatial consistency, which has been usually disregarded because of the reported methodological difficulties, is increasingly demanded in regional flood hazard (and risk) assessments. This study aims at developing a holistic approach for deriving flood frequency at large scale consistently. A large scale two-component model has been established for simulating very long-term multisite synthetic meteorological fields and flood flow at many gauged and ungauged locations hence reflecting the spatially inherent heterogeneity. The model has been applied for the region of nearly a half million km2 including Germany and parts of nearby countries. The model performance has been multi-objectively examined with a focus on extreme. By this continuous simulation approach, flood quantiles for the studied region have been derived successfully and provide useful input for a comprehensive flood risk study.

Ka-Band ARM Zenith Radar Corrections Value-Added Product

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

Johnson, Karen; Toto, Tami; Giangrande, Scott

The KAZRCOR Value -added Product (VAP) performs several corrections to the ingested KAZR moments and also creates a significant detection mask for each radar mode. The VAP computes gaseous attenuation as a function of time and radial distance from the radar antenna, based on ambient meteorological observations, and corrects observed reflectivities for that effect. KAZRCOR also dealiases mean Doppler velocities to correct velocities whose magnitudes exceed the radar’s Nyquist velocity. Input KAZR data fields are passed through into the KAZRCOR output files, in their native time and range coordinates. Complementary corrected reflectivity and velocity fields are provided, along with amore » mask of significant detections and a number of data quality flags. This report covers the KAZRCOR VAP as applied to the original KAZR radars and the upgraded KAZR2 radars. Currently there are two separate code bases for the different radar versions, but once KAZR and KAZR2 data formats are harmonized, only a single code base will be required.« less

MOM: A meteorological data checking expert system in CLIPS

NASA Technical Reports Server (NTRS)

Odonnell, Richard

1990-01-01

Meteorologists have long faced the problem of verifying the data they use. Experience shows that there is a sizable number of errors in the data reported by meteorological observers. This is unacceptable for computer forecast models, which depend on accurate data for accurate results. Most errors that occur in meteorological data are obvious to the meteorologist, but time constraints prevent hand-checking. For this reason, it is necessary to have a 'front end' to the computer model to ensure the accuracy of input. Various approaches to automatic data quality control have been developed by several groups. MOM is a rule-based system implemented in CLIPS and utilizing 'consistency checks' and 'range checks'. The system is generic in the sense that it knows some meteorological principles, regardless of specific station characteristics. Specific constraints kept as CLIPS facts in a separate file provide for system flexibility. Preliminary results show that the expert system has detected some inconsistencies not noticed by a local expert.

The design of 1-wire net meteorological observatory for 2.4 m telescope

NASA Astrophysics Data System (ADS)

Zhu, Gao-Feng; Wei, Ka-Ning; Fan, Yu-Feng; Xu, Jun; Qin, Wei

2005-03-01

The weather is an important factor to affect astronomical observations. The 2.4 m telescope can not work in Robotic Mode without the weather data input. Therefore it is necessary to build a meteorological observatory near the 2.4 m telescope. In this article, the design of the 1-wire net meteorological observatory, which includes hardware and software systems, is introduced. The hardware system is made up of some kinds of sensors and ADC. A suited power station system is also designed. The software system is based on Windows XP operating system and MySQL data management system, and a prototype system of browse/server model is developed by JAVA and JSP. After being tested, the meteorological observatory can register the immediate data of weather, such as raining, snowing, and wind speed. At last, the data will be stored for feature use. The product and the design can work well for the 2.4 m telescope.

A noise assessment and prediction system

NASA Technical Reports Server (NTRS)

Olsen, Robert O.; Noble, John M.

1990-01-01

A system has been designed to provide an assessment of noise levels that result from testing activities at Aberdeen Proving Ground, Md. The system receives meteorological data from surface stations and an upper air sounding system. The data from these systems are sent to a meteorological model, which provides forecasting conditions for up to three hours from the test time. The meteorological data are then used as input into an acoustic ray trace model which projects sound level contours onto a two-dimensional display of the surrounding area. This information is sent to the meteorological office for verification, as well as the range control office, and the environmental office. To evaluate the noise level predictions, a series of microphones are located off the reservation to receive the sound and transmit this information back to the central display unit. The computer models are modular allowing for a variety of models to be utilized and tested to achieve the best agreement with data. This technique of prediction and model validation will be used to improve the noise assessment system.

NASA Prediction of Worldwide Energy Resource High Resolution Meteorology Data For Sustainable Building Design

NASA Technical Reports Server (NTRS)

Chandler, William S.; Hoell, James M.; Westberg, David; Zhang, Taiping; Stackhouse, Paul W., Jr.

2013-01-01

A primary objective of NASA's Prediction of Worldwide Energy Resource (POWER) project is to adapt and infuse NASA's solar and meteorological data into the energy, agricultural, and architectural industries. Improvements are continuously incorporated when higher resolution and longer-term data inputs become available. Climatological data previously provided via POWER web applications were three-hourly and 1x1 degree latitude/longitude. The NASA Modern Era Retrospective-analysis for Research and Applications (MERRA) data set provides higher resolution data products (hourly and 1/2x1/2 degree) covering the entire globe. Currently POWER solar and meteorological data are available for more than 30 years on hourly (meteorological only), daily, monthly and annual time scales. These data may be useful to several renewable energy sectors: solar and wind power generation, agricultural crop modeling, and sustainable buildings. A recent focus has been working with ASHRAE to assess complementing weather station data with MERRA data. ASHRAE building design parameters being investigated include heating/cooling degree days and climate zones.

A comprehensive sensitivity analysis of the WRF model for air quality applications over the Iberian Peninsula

NASA Astrophysics Data System (ADS)

Borge, Rafael; Alexandrov, Vassil; José del Vas, Juan; Lumbreras, Julio; Rodríguez, Encarnacion

Meteorological inputs play a vital role on regional air quality modelling. An extensive sensitivity analysis of the Weather Research and Forecasting (WRF) model was performed, in the framework of the Integrated Assessment Modelling System for the Iberian Peninsula (SIMCA) project. Up to 23 alternative model configurations, including Planetary Boundary Layer schemes, Microphysics, Land-surface models, Radiation schemes, Sea Surface Temperature and Four-Dimensional Data Assimilation were tested in a 3 km spatial resolution domain. Model results for the most significant meteorological variables, were assessed through a series of common statistics. The physics options identified to produce better results (Yonsei University Planetary Boundary Layer, WRF Single-Moment 6-class microphysics, Noah Land-surface model, Eta Geophysical Fluid Dynamics Laboratory longwave radiation and MM5 shortwave radiation schemes) along with other relevant user settings (time-varying Sea Surface Temperature and combined grid-observational nudging) where included in a "best case" configuration. This setup was tested and found to produce more accurate estimation of temperature, wind and humidity fields at surface level than any other configuration for the two episodes simulated. Planetary Boundary Layer height predictions showed a reasonable agreement with estimations derived from routine atmospheric soundings. Although some seasonal and geographical differences were observed, the model showed an acceptable behaviour overall. Despite being useful to define the most appropriate setup of the WRF model for air quality modelling over the Iberian Peninsula, this study provides a general overview of WRF sensitivity and can constitute a reference for future mesoscale meteorological modelling exercises.

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...

Impact of Uncertainties in Meteorological Forcing Data and Land Surface Parameters on Global Estimates of Terrestrial Water Balance Components

NASA Astrophysics Data System (ADS)

Nasonova, O. N.; Gusev, Ye. M.; Kovalev, Ye. E.

2009-04-01

Global estimates of the components of terrestrial water balance depend on a technique of estimation and on the global observational data sets used for this purpose. Land surface modelling is an up-to-date and powerful tool for such estimates. However, the results of modelling are affected by the quality of both a model and input information (including meteorological forcing data and model parameters). The latter is based on available global data sets containing meteorological data, land-use information, and soil and vegetation characteristics. Now there are a lot of global data sets, which differ in spatial and temporal resolution, as well as in accuracy and reliability. Evidently, uncertainties in global data sets will influence the results of model simulations, but to which extent? The present work is an attempt to investigate this issue. The work is based on the land surface model SWAP (Soil Water - Atmosphere - Plants) and global 1-degree data sets on meteorological forcing data and the land surface parameters, provided within the framework of the Second Global Soil Wetness Project (GSWP-2). The 3-hourly near-surface meteorological data (for the period from 1 July 1982 to 31 December 1995) are based on reanalyses and gridded observational data used in the International Satellite Land-Surface Climatology Project (ISLSCP) Initiative II. Following the GSWP-2 strategy, we used a number of alternative global forcing data sets to perform different sensitivity experiments (with six alternative versions of precipitation, four versions of radiation, two pure reanalysis products and two fully hybridized products of meteorological data). To reveal the influence of model parameters on simulations, in addition to GSWP-2 parameter data sets, we produced two alternative global data sets with soil parameters on the basis of their relationships with the content of clay and sand in a soil. After this the sensitivity experiments with three different sets of parameters were performed. As a result, 16 variants of global annual estimates of water balance components were obtained. Application of alternative data sets on radiation, precipitation, and soil parameters allowed us to reveal the influence of uncertainties in input data on global estimates of water balance components.

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.

Multimodel hydrological ensemble forecasts for the Baskatong catchment in Canada using the TIGGE database.

NASA Astrophysics Data System (ADS)

Tito Arandia Martinez, Fabian

2014-05-01

Adequate uncertainty assessment is an important issue in hydrological modelling. An important issue for hydropower producers is to obtain ensemble forecasts which truly grasp the uncertainty linked to upcoming streamflows. If properly assessed, this uncertainty can lead to optimal reservoir management and energy production (ex. [1]). The meteorological inputs to the hydrological model accounts for an important part of the total uncertainty in streamflow forecasting. Since the creation of the THORPEX initiative and the TIGGE database, access to meteorological ensemble forecasts from nine agencies throughout the world have been made available. This allows for hydrological ensemble forecasts based on multiple meteorological ensemble forecasts. Consequently, both the uncertainty linked to the architecture of the meteorological model and the uncertainty linked to the initial condition of the atmosphere can be accounted for. The main objective of this work is to show that a weighted combination of meteorological ensemble forecasts based on different atmospheric models can lead to improved hydrological ensemble forecasts, for horizons from one to ten days. This experiment is performed for the Baskatong watershed, a head subcatchment of the Gatineau watershed in the province of Quebec, in Canada. Baskatong watershed is of great importance for hydro-power production, as it comprises the main reservoir for the Gatineau watershed, on which there are six hydropower plants managed by Hydro-Québec. Since the 70's, they have been using pseudo ensemble forecast based on deterministic meteorological forecasts to which variability derived from past forecasting errors is added. We use a combination of meteorological ensemble forecasts from different models (precipitation and temperature) as the main inputs for hydrological model HSAMI ([2]). The meteorological ensembles from eight of the nine agencies available through TIGGE are weighted according to their individual performance and combined to form a grand ensemble. Results show that the hydrological forecasts derived from the grand ensemble perform better than the pseudo ensemble forecasts actually used operationally at Hydro-Québec. References: [1] M. Verbunt, A. Walser, J. Gurtz et al., "Probabilistic flood forecasting with a limited-area ensemble prediction system: Selected case studies," Journal of Hydrometeorology, vol. 8, no. 4, pp. 897-909, Aug, 2007. [2] N. Evora, Valorisation des prévisions météorologiques d'ensemble, Institu de recherceh d'Hydro-Québec 2005. [3] V. Fortin, Le modèle météo-apport HSAMI: historique, théorie et application, Institut de recherche d'Hydro-Québec, 2000.

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.

Development of the TACOM (Tank Automotive Command) Thermal Imaging Model (TTIM). Volume 1. Technical Guide and User’s Manual.

DTIC Science & Technology

1984-12-01

BLOCK DATA Default values for variables input by menus. LIBR Interface with frame I/O routines. SNSR Interface with sensor routines. ATMOS Interface with...Routines Included in Frame I/O Interface Routine Description LIBR Selects options for input or output to a data library. FRREAD Reads frame from file and/or...Layer", Journal of Applied Meteorology 20, pp. 242-249, March 1981. 15 L.J. Harding, Numerical Analysis and Applications Software Abstracts, Computing

Code Description for Generation of Meteorological Height and Pressure Level and Layer Profiles

DTIC Science & Technology

2016-06-01

defined by user input height or pressure levels. It can process input profiles from sensing systems such as radiosonde, lidar, or wind profiling radar...nearly the same way, but the split between wind and temperature/humidity (TH) special levels leads to some changes to one other routine. If changes are...top of the sounding, sometimes the moisture, the thermal, both thermal and moisture, and/or the wind data are missing. Missing data items in the

Multivariate Statistical Postprocessing of Ensemble Forcasts of Precipitation and Temperature over four River Basins in California

NASA Astrophysics Data System (ADS)

Scheuerer, Michael; Hamill, Thomas M.; Whitin, Brett; He, Minxue; Henkel, Arthur

2017-04-01

Hydrological forecasts strongly rely on predictions of precipitation amounts and temperature as meteorological inputs to hydrological models. Ensemble weather predictions provide a number of different scenarios that reflect the uncertainty about these meteorological inputs, but are often biased and underdispersive, and therefore require statistical postprocessing. In hydrological applications it is crucial that spatial and temporal (i.e. between different forecast lead times) dependencies as well as dependence between the two weather variables is adequately represented by the recalibrated forecasts. We present a study with temperature and precipitation forecasts over four river basins over California that are postprocessed with a variant of the nonhomogeneous Gaussian regression method (Gneiting et al., 2005) and the censored, shifted gamma distribution approach (Scheuerer and Hamill, 2015) respectively. For modelling spatial, temporal and inter-variable dependence we propose a variant of the Schaake Shuffle (Clark et al., 2005) that uses spatio-temporal trajectories of observed temperture and precipitation as a dependence template, and chooses the historic dates in such a way that the divergence between the marginal distributions of these trajectories and the univariate forecast distributions is minimized. For the four river basins considered in our study, this new multivariate modelling technique consistently improves upon the Schaake Shuffle and yields reliable spatio-temporal forecast trajectories of temperature and precipitation that can be used to force hydrological forecast systems. References: Clark, M., Gangopadhyay, S., Hay, L., Rajagopalan, B., Wilby, R., 2004. The Schaake Shuffle: A method for reconstructing space-time variability in forecasted precipitation and temperature fields. Journal of Hydrometeorology, 5, pp.243-262. Gneiting, T., Raftery, A.E., Westveld, A.H., Goldman, T., 2005. Calibrated probabilistic forecasting using ensemble model output statistics and minimum CRPS. Monthly Weather Review, 133, pp.1098-1118. Scheuerer, M., Hamill, T.M., 2015. Statistical postprocessing of ensemble precipitation forecasts by fitting censored, shifted gamma distributions. Monthly Weather Review, 143, pp.4578-4596. Scheuerer, M., Hamill, T.M., Whitin, B., He, M., and Henkel, A., 2016: A method for preferential selection of dates in the Schaake shuffle approach to constructing spatio-temporal forecast fields of temperature and precipitation. Water Resources Research, submitted.

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.

Meteorological measurements. Chapter 3

Treesearch

David Y. Hollinger

2008-01-01

Environmental measurements are useful for detecting climatic trends, understanding how the environment influences biological processes, and as input to ecosystem models. Landscape-scale monitoring requires a suite of environmental measures for all of these purposes, including air and soil temperature, humidity, wind speed, precipitation and soil moisture, and different...

A Sensitivity Study of the Aircraft Vortex Spacing System (AVOSS) Wake Predictor Algorithm to the Resolution of Input Meteorological Profiles

NASA Technical Reports Server (NTRS)

Rutishauser, David K.; Butler, Patrick; Riggins, Jamie

2004-01-01

The AVOSS project demonstrated the feasibility of applying aircraft wake vortex sensing and prediction technologies to safe aircraft spacing for single runway arrivals. On average, AVOSS provided spacing recommendations that were less than the current FAA prescribed spacing rules, resulting in a potential airport efficiency gain. Subsequent efforts have included quantifying the operational specifications for future Wake Vortex Advisory Systems (WakeVAS). In support of these efforts, each of the candidate subsystems for a WakeVAS must be specified. The specifications represent a consensus between the high-level requirements and the capabilities of the candidate technologies. This report documents the beginnings of an effort to quantify the capabilities of the AVOSS Prediction Algorithm (APA). Specifically, the APA horizontal position and circulation strength output sensitivity to the resolution of its wind and turbulence inputs is examined. The results of this analysis have implications for the requirements of the meteorological sensing and prediction systems comprising a WakeVAS implementation.

Spatial regression test for ensuring temperature data quality in southern Spain

NASA Astrophysics Data System (ADS)

Estévez, J.; Gavilán, P.; García-Marín, A. P.

2018-01-01

Quality assurance of meteorological data is crucial for ensuring the reliability of applications and models that use such data as input variables, especially in the field of environmental sciences. Spatial validation of meteorological data is based on the application of quality control procedures using data from neighbouring stations to assess the validity of data from a candidate station (the station of interest). These kinds of tests, which are referred to in the literature as spatial consistency tests, take data from neighbouring stations in order to estimate the corresponding measurement at the candidate station. These estimations can be made by weighting values according to the distance between the stations or to the coefficient of correlation, among other methods. The test applied in this study relies on statistical decision-making and uses a weighting based on the standard error of the estimate. This paper summarizes the results of the application of this test to maximum, minimum and mean temperature data from the Agroclimatic Information Network of Andalusia (southern Spain). This quality control procedure includes a decision based on a factor f, the fraction of potential outliers for each station across the region. Using GIS techniques, the geographic distribution of the errors detected has been also analysed. Finally, the performance of the test was assessed by evaluating its effectiveness in detecting known errors.

SENSITIVITY OF THE NATIONAL OCEANIC AND ATMOSPHERIC ADMINISTRATION MULTILAYER MODEL TO INSTRUMENT ERROR AND PARAMETERIZATION UNCERTAINTY

EPA Science Inventory

The response of the National Oceanic and Atmospheric Administration multilayer inferential dry deposition velocity model (NOAA-MLM) to error in meteorological inputs and model parameterization is reported. Monte Carlo simulations were performed to assess the uncertainty in NOA...

Error characterization of microwave satellite soil moisture data sets using fourier analysis

USDA-ARS?s Scientific Manuscript database

Soil moisture is a key geophysical variable in hydrological and meteorological processes. Accurate and current observations of soil moisture over meso to global scales used as inputs to hydrological, weather and climate modelling will benefit the predictability and understanding of these processes. ...

Error characterization of microwave satellite soil moisture data sets using fourier analysis

USDA-ARS?s Scientific Manuscript database

Abstract: Soil moisture is a key geophysical variable in hydrological and meteorological processes. Accurate and current observations of soil moisture over mesoscale to global scales as inputs to hydrological, weather and climate modelling will benefit the predictability and understanding of these p...

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...

Temperature histories of commercial flights at severe conditions from GASP data

NASA Technical Reports Server (NTRS)

Jasperson, W. H.; Nastrom, G. D.

1983-01-01

The thermal environment of commercial aircraft from a data set gathered during the Global Atmospheric Sampling Program (GASP) is studied. The data set covers a four-year period of measurements. The report presents plots of airplane location and speed and atmospheric temperature as functions of elapsed time for 35 extreme-condition flights, selected by minimum values of several temperature parameters. One of these parameters, the severity factor, is an approximation of the in-flight wing-tank temperature. Representative low-severity-factor flight histories may be useful for actual temperature-profile inputs to design and research studies. Comparison of the GASP atmospheric temperatures to interpolated temperatures from National Meteorological Center and Global Weather Central analysis fields shows that the analysis temperatures are slightly biased toward warmer than actual temperatures, particularly over oceans and at extreme conditions.

Computer programs for producing single-event aircraft noise data for specific engine power and meteorological conditions for use with USAF (United States Air Force) community noise model (NOISEMAP)

NASA Astrophysics Data System (ADS)

Mohlman, H. T.

1983-04-01

The Air Force community noise prediction model (NOISEMAP) is used to describe the aircraft noise exposure around airbases and thereby aid airbase planners to minimize exposure and prevent community encroachment which could limit mission effectiveness of the installation. This report documents two computer programs (OMEGA 10 and OMEGA 11) which were developed to prepare aircraft flight and ground runup noise data for input to NOISEMAP. OMEGA 10 is for flight operations and OMEGA 11 is for aircraft ground runups. All routines in each program are documented at a level useful to a programmer working with the code or a reader interested in a general overview of what happens within a specific subroutine. Both programs input normalized, reference aircraft noise data; i.e., data at a standard reference distance from the aircraft, for several fixed engine power settings, a reference airspeed and standard day meteorological conditions. Both programs operate on these normalized, reference data in accordance with user-defined, non-reference conditions to derive single-event noise data for 22 distances (200 to 25,000 feet) in a variety of physical and psycho-acoustic metrics. These outputs are in formats ready for input to NOISEMAP.

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.

Development and validation of the European Cluster Assimilation Techniques run libraries

NASA Astrophysics Data System (ADS)

Facskó, G.; Gordeev, E.; Palmroth, M.; Honkonen, I.; Janhunen, P.; Sergeev, V.; Kauristie, K.; Milan, S.

2012-04-01

The European Commission funded the European Cluster Assimilation Techniques (ECLAT) project as a collaboration of five leader European universities and research institutes. A main contribution of the Finnish Meteorological Institute (FMI) is to provide a wide range global MHD runs with the Grand Unified Magnetosphere Ionosphere Coupling simulation (GUMICS). The runs are divided in two categories: Synthetic runs investigating the extent of solar wind drivers that can influence magnetospheric dynamics, as well as dynamic runs using measured solar wind data as input. Here we consider the first set of runs with synthetic solar wind input. The solar wind density, velocity and the interplanetary magnetic field had different magnitudes and orientations; furthermore two F10.7 flux values were selected for solar radiation minimum and maximum values. The solar wind parameter values were constant such that a constant stable solution was archived. All configurations were run several times with three different (-15°, 0°, +15°) tilt angles in the GSE X-Z plane. The result of the 192 simulations named so called "synthetic run library" were visualized and uploaded to the homepage of the FMI after validation. Here we present details of these runs.

Dune mobility in the St. Anthony Dune Field, Idaho, USA: Effects of meteorological variables and lag time

NASA Astrophysics Data System (ADS)

Hoover, R. H.; Gaylord, D. R.; Cooper, C. M.

2018-05-01

The St. Anthony Dune Field (SADF) is a 300 km2 expanse of active to stabilized transverse, barchan, barchanoid, and parabolic sand dunes located in a semi-arid climate in southeastern Idaho. The northeastern portion of the SADF, 16 km2, was investigated to examine meteorological influences on dune mobility. Understanding meteorological predictors of sand-dune migration for the SADF informs landscape evolution and impacts assessment of eolian activity on sensitive agricultural lands in the western United States, with implications for semi-arid environments globally. Archival aerial photos from 1954 to 2011 were used to calculate dune migration rates which were subsequently compared to regional meteorological data, including temperature, precipitation and wind speed. Observational analyses based on aerial photo imagery and meteorological data indicate that dune migration is influenced by weather for up to 5-10 years and therefore decadal weather patterns should be taken into account when using dune migration rates as proxies from climate fluctuation. Statistical examination of meteorological variables in this study indicates that 24% of the variation of sand dune migration rates is attributed to temperature, precipitation and wind speed, which is increased to 45% when incorporating lag time.

Impact of meteorology on air quality modeling over the Po valley in northern Italy

NASA Astrophysics Data System (ADS)

Pernigotti, D.; Georgieva, E.; Thunis, P.; Bessagnet, B.

2012-05-01

A series of sensitivity tests has been performed using both a mesoscale meteorological model (MM5) and a chemical transport model (CHIMERE) to better understand the reasons why all models underestimate particulate matter concentrations in the Po valley in winter. Different options are explored to nudge meteorological observations from regulatory networks into MM5 in order to improve model performances, especially during the low wind speed regimes frequently present in this area. The sensitivity of the CHIMERE modeled particulate matter concentrations to these different meteorological inputs are then evaluated for the January 2005 time period. A further analysis of the CHIMERE model results revealed the need of improving the parametrization of the in-cloud scavenging and vertical diffusivity schemes; such modifications are relevant especially when the model is applied under mist, fog and low stratus conditions, which frequently occur in the Po valley during winter. The sensitivity of modeled particulate matter concentrations to turbulence parameters, wind, temperature and cloud liquid water content in one of the most polluted and complex areas in Europe is finally discussed.

Introduction of the Mobile Platform for the Meteorological Observations in Seoul Metropolitan City of Korea

NASA Astrophysics Data System (ADS)

Baek, K. T.; Lee, S.; Kang, M.; Lee, G.

2016-12-01

Traffic accidents due to adverse weather such as fog, heavy rainfall, flooding and road surface freezing have been increasing in Korea. To reduce damages caused by the severe weather on the road, a forecast service of combined real-time road-wise weather and the traffic situation is required. Conventional stationary meteorological observations in sparse location system are limited to observe the detailed road environment. For this reason, a mobile meteorological observation platform has been coupled in Weather Information Service Engine (WISE) which is the prototype of urban-scale high resolution weather prediction system in Seoul metropolitan area of Korea in early August 2016. The instruments onboard are designed to measure 15 meteorological parameters; pressure, temperature, relative humidity, precipitation, up/down net radiation, up/down longwave radiation, up/down shortwave radiation, road surface condition, friction coefficient, water depth, wind direction and speed. The observations from mobile platform show a distinctive advantage of data collection in need for road conditions and inputs for the numerical forecast model. In this study, we introduce and examine the feasibility of mobile observations in urban weather prediction and applications.

The Chinese FY-1 Meteorological Satellite Application in Observation on Oceanic Environment

NASA Astrophysics Data System (ADS)

Weimin, S.

meteorological satellite is stated in this paper. exploration of the ocean resources has been a very important question of global strategy in the world. The exploration of the ocean resources includes following items: Making full use of oceanic resources and space, protecting oceanic environment. to observe the ocean is by using of satellite. In 1978, US successfully launched the first ocean observation satellite in the world --- Sea Satellite. It develops ancient oceanography in to advanced space-oceanography. FY-1 B and FY- IC respectively. High quality data were acquired at home and abroad. FY-1 is Chinese meteorological satellite, but with 0.43 ~ 0.48 μm ,0.48 ~ 0.53 μm and 0.53 ~ 0.58 μm three ocean color channels, actually it is a multipurpose remote sensing satellite of meteorology and oceanography. FY-1 satellite's capability of observation on ocean partly, thus the application field is expanded and the value is increased. With the addition of oceanic channels on FY-1, the design of the satellite is changed from the original with meteorological observation as its main purpose into remote sensing satellite possessing capability of observing meteorology and ocean as well. Thus, the social and economic benefit of FY-1 is increased. the social and economic benefit of the development of the satellite is the key technique in the system design of the satellite. technically feasible but also save the funds in researching and manufacturing of the satellite, quicken the tempo of researching and manufacturing satellite. the scanning radiometer for FY-1 is conducted an aviation experiment over Chinese ocean. This experiment was of vital importance to the addition of oceanic observation channel on FY-1. FY-1 oceanic channels design to be correct. detecting ocean color. This is the unique character of Chinese FY-1 meteorological satellite. meteorological remote sensing channel on FY-1 to form detecting capability of three visible channels: red, yellow and blue spectrum bands. Thus FY-1 satellite can be used for observation on ocean color experiment. This experiment is successful, a lot of data were acquired. Good application results were obtained in the field of oceanic science research. Therefore, it makes FY-1 a remote sensing satellite used for observation on meteorology and ocean. This is the unique character of Chinese FY-1 meteorological satellite, it is widely noticed all over the world. Chinese meteorological satellite has been realized the aim of using one satellite for multipurpose applications and brought more and more social and economic benefit. oceanic channel in Chinese meteorological satellites is also foreseen to expand the application field in Chinese meteorological satellites. Key Word : Meteorological Satellite Oceanic Remote Sensing

Small-Scale Tropopause Dynamics and TOMS Total Ozone

NASA Technical Reports Server (NTRS)

Stanford, John L.

2002-01-01

This project used Earth Probe Total Ozone Mapping Spectrometer (EP TOMS) along-track ozone retrievals, in conjunction with ancillary meteorological fields and modeling studies, for high resolution investigations of upper troposphere and lower stratosphere dynamics. Specifically, high resolution along-track (Level 2) EP TOMS data were used to investigate the beautiful fine-scale structure in constituent and meteorological fields prominent in the evolution of highly non-linear baroclinic storm systems. Comparison was made with high resolution meteorological models. The analyses provide internal consistency checks and validation of the EP TOMS data which are vital for monitoring ozone depletion in both polar and midlatitude regions.

Evaluation of satellite-based, modeled-derived daily solar radiation data for the continental U.S.

USDA-ARS?s Scientific Manuscript database

Many applications of simulation models and related decision support tools for agriculture and natural resource management require daily meteorological data as inputs. Availability and quality of such data, however, often constrain research and decision support activities that require use of these to...

Probabilistic Meteorological Characterization for Turbine Loads

NASA Astrophysics Data System (ADS)

Kelly, M.; Larsen, G.; Dimitrov, N. K.; Natarajan, A.

2014-06-01

Beyond the existing, limited IEC prescription to describe fatigue loads on wind turbines, we look towards probabilistic characterization of the loads via analogous characterization of the atmospheric flow, particularly for today's "taller" turbines with rotors well above the atmospheric surface layer. Based on both data from multiple sites as well as theoretical bases from boundary-layer meteorology and atmospheric turbulence, we offer probabilistic descriptions of shear and turbulence intensity, elucidating the connection of each to the other as well as to atmospheric stability and terrain. These are used as input to loads calculation, and with a statistical loads output description, they allow for improved design and loads calculations.

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.

International challenge to model the long-range transport of radioxenon released from medical isotope production to six Comprehensive Nuclear-Test-Ban Treaty monitoring stations

DOE PAGES

Maurer, Christian; Baré, Jonathan; Kusmierczyk-Michulec, Jolanta; ...

2018-03-08

After performing a first multi-model exercise in 2015 a comprehensive and technically more demanding atmospheric transport modelling challenge was organized in 2016. Release data were provided by the Australian Nuclear Science and Technology Organization radiopharmaceutical facility in Sydney (Australia) for a one month period. Measured samples for the same time frame were gathered from six International Monitoring System stations in the Southern Hemisphere with distances to the source ranging between 680 (Melbourne) and about 17,000 km (Tristan da Cunha). Participants were prompted to work with unit emissions in pre-defined emission intervals (daily, half-daily, 3-hourly and hourly emission segment lengths) andmore » in order to perform a blind test actual emission values were not provided to them. Despite the quite different settings of the two atmospheric transport modelling challenges there is common evidence that for long-range atmospheric transport using temporally highly resolved emissions and highly space-resolved meteorological input fields has no significant advantage compared to using lower resolved ones. As well an uncertainty of up to 20% in the daily stack emission data turns out to be acceptable for the purpose of a study like this. Model performance at individual stations is quite diverse depending largely on successfully capturing boundary layer processes. No single model-meteorology combination performs best for all stations. Moreover, the stations statistics do not depend on the distance between the source and the individual stations. Finally, it became more evident how future exercises need to be designed. Set-up parameters like the meteorological driver or the output grid resolution should be pre-scribed in order to enhance diversity as well as comparability among model runs.« less

ASI/CGS products and services in support of GNSS-meteorology

NASA Astrophysics Data System (ADS)

Pacione, Rosa; Pace, Brigida; Bianco, Giuseppe

2013-04-01

For more than a decade, ASI/CGS has supported ground-based GNSS meteorology in Europe participating in various projects such as MAGIC, COST-716, TOUGH, E-GVAP (phase I and II) and providing Zenith Tropospheric path Delays (ZTD) derived from a European network of GNSS stations covering mainly the central Mediterranean area. Working in close cooperation with the meteorological community, GNSS data are analyzed in order to provide ZTD with different latencies ranging from post-processing, useful for climate studies, to near-real time, for hourly assimilation into Numerical Weather Prediction (NWP) model. However advancements in NWP models (such as the Met Office UKV 1.5km model) with rapid update cycles require observations with improved timeliness and with greater spatial and temporal resolution than is currently available. To fulfil this requirement a sub-hourly PPP processing has been set-up, and is under evaluation, thanks to the availability of the IGS RT orbit and clock corrections. Moreover ZTD estimates are the input data for developing new and enhanced products: ZTD residuals fields and Integrated Water Vapour (IWV) maps. The former will be helpful in augmenting empirical tropospheric models for positioning applications. The latter are useful for nowcasting and severe weather monitoring since they let to follow IWV time evolution. We present an overview of the developed products and services; the new directions in support of NWP applications and the nowcasting and forecasting of severe weather events that emerge within E-GVAP phase III and the EU COST Action "Advanced Global Navigation Satellite Systems tropospheric products for monitoring Severe Weather Events and Climate" (GNSS4SWEC). Acknowledgements. This work has been carried out under ASI contract I-014-10-0.

Evaluating and improving the results of air quality models in Texas using TES, AIRS and other satellite data

NASA Astrophysics Data System (ADS)

Osterman, G.; Harper, C.; Estes, M.; Zhao, W.; Bowman, K.; Pierce, B.; Irion, B.; Kahn, B.; Al-Saadi, J.

2008-05-01

The Houston/Galveston/Brazoria (HGB) area of Texas has been classified as in moderate nonattainment of the Environmental Protection Agency (EPA) 8-hour standard for ground level ozone since April 30, 2004. The Texas Commission on Environmental Quality uses photochemical model results as one of its primary tools to develop strategies to bring the HGB area into attainment with the EPA standard. The state of Texas then includes the strategies into a revised version of its State Implementation Plan (SIP). We will discuss efforts that have been or soon will be underway to use satellite data to evaluate and improve the meteorological and photochemical modeling efforts at TCEQ. In particular we will show the use of GOES, AIRS and TES data to improve the ability to model, using the MM5 model, the meteorological conditions over Texas and the Gulf of Mexico. The meteorological fields are then used as one of the inputs to the CAMx air quality model used at TCEQ. We will discuss the use of chemical transport model results as initial and boundary conditions which are a key uncertainty in the modeling of the air above Houston. We will also discuss the use of TES data to assist in the evaluation of preliminary model results generated by TCEQ for time periods in 2005. The satellite data will provide key information on ozone and carbon monoxide concentrations away from surface monitors in the troposphere. We will show how satellite data is becoming a key tool in the effort to improve air quality in the HGB area and one that can easily applied for use in other regions of the country.

International challenge to model the long-range transport of radioxenon released from medical isotope production to six Comprehensive Nuclear-Test-Ban Treaty monitoring stations

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

Maurer, Christian; Baré, Jonathan; Kusmierczyk-Michulec, Jolanta

After performing a first multi-model exercise in 2015 a comprehensive and technically more demanding atmospheric transport modelling challenge was organized in 2016. Release data were provided by the Australian Nuclear Science and Technology Organization radiopharmaceutical facility in Sydney (Australia) for a one month period. Measured samples for the same time frame were gathered from six International Monitoring System stations in the Southern Hemisphere with distances to the source ranging between 680 (Melbourne) and about 17,000 km (Tristan da Cunha). Participants were prompted to work with unit emissions in pre-defined emission intervals (daily, half-daily, 3-hourly and hourly emission segment lengths) andmore » in order to perform a blind test actual emission values were not provided to them. Despite the quite different settings of the two atmospheric transport modelling challenges there is common evidence that for long-range atmospheric transport using temporally highly resolved emissions and highly space-resolved meteorological input fields has no significant advantage compared to using lower resolved ones. As well an uncertainty of up to 20% in the daily stack emission data turns out to be acceptable for the purpose of a study like this. Model performance at individual stations is quite diverse depending largely on successfully capturing boundary layer processes. No single model-meteorology combination performs best for all stations. Moreover, the stations statistics do not depend on the distance between the source and the individual stations. Finally, it became more evident how future exercises need to be designed. Set-up parameters like the meteorological driver or the output grid resolution should be pre-scribed in order to enhance diversity as well as comparability among model runs.« less

Assessment of Seasonal Water Balance Components over India Using Macroscale Hydrological Model

NASA Astrophysics Data System (ADS)

Joshi, S.; Raju, P. V.; Hakeem, K. A.; Rao, V. V.; Yadav, A.; Issac, A. M.; Diwakar, P. G.; Dadhwal, V. K.

2016-12-01

Hydrological models provide water balance components which are useful for water resources assessment and for capturing the seasonal changes and impact of anthropogenic interventions and climate change. The study under description is a national level modeling framework for country India using wide range of geo-spatial and hydro-meteorological data sets for estimating daily Water Balance Components (WBCs) at 0.15º grid resolution using Variable Infiltration Capacity model. The model parameters were optimized through calibration of model computed stream flow with field observed yielding Nash-Sutcliffe efficiency between 0.5 to 0.7. The state variables, evapotranspiration (ET) and soil moisture were also validated, obtaining R2 values of 0.57 and 0.69, respectively. Using long-term meteorological data sets, model computation were carried to capture hydrological extremities. During 2013, 2014 and 2015 monsoon seasons, WBCs were estimated and were published in web portal with 2-day time lag. In occurrence of disaster events, weather forecast was ingested, high surface runoff zones were identified for forewarning and disaster preparedness. Cumulative monsoon season rainfall of 2013, 2014 and 2015 were 105, 89 and 91% of long period average (LPA) respectively (Source: India Meteorological Department). Analysis of WBCs indicated that corresponding seasonal surface runoff was 116, 81 and 86% LPA and evapotranspiration was 109, 104 and 90% LPA. Using the grid-wise data, the spatial variation in WBCs among river basins/administrative regions was derived to capture the changes in surface runoff, ET between the years and in comparison with LPA. The model framework is operational and is providing periodic account of national level water balance fluxes which are useful for quantifying spatial and temporal variation in basin/sub-basin scale water resources, periodical water budgeting to form vital inputs for studies on water resources and climate change.

Validation of the DIFFAL, HPAC and HotSpot Dispersion Models Using the Full-Scale Radiological Dispersal Device (FSRDD) Field Trials Witness Plate Deposition Dataset.

PubMed

Purves, Murray; Parkes, David

2016-05-01

Three atmospheric dispersion models--DIFFAL, HPAC, and HotSpot--of differing complexities have been validated against the witness plate deposition dataset taken during the Full-Scale Radiological Dispersal Device (FSRDD) Field Trials. The small-scale nature of these trials in comparison to many other historical radiological dispersion trials provides a unique opportunity to evaluate the near-field performance of the models considered. This paper performs validation of these models using two graphical methods of comparison: deposition contour plots and hotline profile graphs. All of the models tested are assessed to perform well, especially considering that previous model developments and validations have been focused on larger-scale scenarios. Of the models, HPAC generally produced the most accurate results, especially at locations within ∼100 m of GZ. Features present within the observed data, such as hot spots, were not well modeled by any of the codes considered. Additionally, it was found that an increase in the complexity of the meteorological data input to the models did not necessarily lead to an improvement in model accuracy; this is potentially due to the small-scale nature of the trials.

The Nevada Rural Ozone Initiative: Field measurements of surface ozone in rural settings

NASA Astrophysics Data System (ADS)

Fine, R.; Gustin, M. S.; Weiss-Penzias, P. S.; Jaffe, D. A.; Peterson, C.

2011-12-01

The Nevada Rural Ozone Initiative (NVROI) focuses on measuring ozone and other parameters at rural sites across Nevada. The project was prompted by observations of elevated ozone concentrations at Great Basin National Park (GBNP), a remote location at the eastern boundary of the state. Past CASTNET data collected at GBNP demonstrated that the area will be out of attainment if the new ozone NAAQS are established at any values between 60 and 70 ppb. To examine the ozone sources we have augmented the CASTNET data at GBNP with measurements at additional sites. NVROI field sites are situated between 1390 and 2080 meters above sea level along transects consistent with the prevailing wind directions across the state. Data collection began in July 2011. Measurements indicate significant variability in the diel pattern of ozone concentrations between field sites suggesting that site specific physicochemical characteristics, free tropospheric inputs, and regional transport of air pollutants all influence observed values at these background sites. Ancillary gas, particulate matter, and meteorological parameters will be coupled with trajectory analyses to investigate the influence of local, regional, and long range sources on background ozone concentrations.

Rapid Debris Analysis Project Task 3 Final Report - Sensitivity of Fallout to Source Parameters, Near-Detonation Environment Material Properties, Topography, and Meteorology

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

Goldstein, Peter

2014-01-24

This report describes the sensitivity of predicted nuclear fallout to a variety of model input parameters, including yield, height of burst, particle and activity size distribution parameters, wind speed, wind direction, topography, and precipitation. We investigate sensitivity over a wide but plausible range of model input parameters. In addition, we investigate a specific example with a relatively narrow range to illustrate the potential for evaluating uncertainties in predictions when there are more precise constraints on model parameters.

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.

[Application of artificial neural networks in forecasting the number of circulatory system diseases death toll].

PubMed

Zhang, Ying; Shao, Yi; Shang, Kezheng; Wang, Shigong; Wang, Jinyan

2014-09-01

Set up the model of forecasting the number of circulatorys death toll based on back-propagation (BP) artificial neural networks discuss the relationship between the circulatory system diseases death toll meteorological factors and ambient air pollution. The data of tem deaths, meteorological factors, and ambient air pollution within the m 2004 to 2009 in Nanjing were collected. On the basis of analyzing the ficient between CSDDT meteorological factors and ambient air pollution, leutral network model of CSDDT was built for 2004 - 2008 based on factors and ambient air pollution within the same time, and the data of 2009 est the predictive power of the model. There was a closely system diseases relationship between meteorological factors, ambient air pollution and the circulatory system diseases death toll. The ANN model structure was 17 -16 -1, 17 input notes, 16 hidden notes and 1 output note. The training precision was 0. 005 and the final error was 0. 004 999 42 after 487 training steps. The results of forecast show that predict accuracy over 78. 62%. This method is easy to be finished with smaller error, and higher ability on circulatory system death toll on independent prediction, which can provide a new method for forecasting medical-meteorological forecast and have the value of further research.

Modeling and roles of meteorological factors in outbreaks of highly pathogenic avian influenza H5N1.

PubMed

Biswas, Paritosh K; Islam, Md Zohorul; Debnath, Nitish C; Yamage, Mat

2014-01-01

The highly pathogenic avian influenza A virus subtype H5N1 (HPAI H5N1) is a deadly zoonotic pathogen. Its persistence in poultry in several countries is a potential threat: a mutant or genetically reassorted progenitor might cause a human pandemic. Its world-wide eradication from poultry is important to protect public health. The global trend of outbreaks of influenza attributable to HPAI H5N1 shows a clear seasonality. Meteorological factors might be associated with such trend but have not been studied. For the first time, we analyze the role of meteorological factors in the occurrences of HPAI outbreaks in Bangladesh. We employed autoregressive integrated moving average (ARIMA) and multiplicative seasonal autoregressive integrated moving average (SARIMA) to assess the roles of different meteorological factors in outbreaks of HPAI. Outbreaks were modeled best when multiplicative seasonality was incorporated. Incorporation of any meteorological variable(s) as inputs did not improve the performance of any multivariable models, but relative humidity (RH) was a significant covariate in several ARIMA and SARIMA models with different autoregressive and moving average orders. The variable cloud cover was also a significant covariate in two SARIMA models, but air temperature along with RH might be a predictor when moving average (MA) order at lag 1 month is considered.

Spontaneous emergence of rogue waves in partially coherent waves: A quantitative experimental comparison between hydrodynamics and optics

NASA Astrophysics Data System (ADS)

El Koussaifi, R.; Tikan, A.; Toffoli, A.; Randoux, S.; Suret, P.; Onorato, M.

2018-01-01

Rogue waves are extreme and rare fluctuations of the wave field that have been discussed in many physical systems. Their presence substantially influences the statistical properties of a partially coherent wave field, i.e., a wave field characterized by a finite band spectrum with random Fourier phases. Their understanding is fundamental for the design of ships and offshore platforms. In many meteorological conditions waves in the ocean are characterized by the so-called Joint North Sea Wave Project (JONSWAP) spectrum. Here we compare two unique experimental results: the first one has been performed in a 270 m wave tank and the other in optical fibers. In both cases, waves characterized by a JONSWAP spectrum and random Fourier phases have been launched at the input of the experimental device. The quantitative comparison, based on an appropriate scaling of the two experiments, shows a very good agreement between the statistics in hydrodynamics and optics. Spontaneous emergence of heavy tails in the probability density function of the wave amplitude is observed in both systems. The results demonstrate the universal features of rogue waves and provide a fundamental and explicit bridge between two important fields of research. Numerical simulations are also compared with experimental results.

Spontaneous emergence of rogue waves in partially coherent waves: A quantitative experimental comparison between hydrodynamics and optics.

PubMed

El Koussaifi, R; Tikan, A; Toffoli, A; Randoux, S; Suret, P; Onorato, M

2018-01-01

Rogue waves are extreme and rare fluctuations of the wave field that have been discussed in many physical systems. Their presence substantially influences the statistical properties of a partially coherent wave field, i.e., a wave field characterized by a finite band spectrum with random Fourier phases. Their understanding is fundamental for the design of ships and offshore platforms. In many meteorological conditions waves in the ocean are characterized by the so-called Joint North Sea Wave Project (JONSWAP) spectrum. Here we compare two unique experimental results: the first one has been performed in a 270 m wave tank and the other in optical fibers. In both cases, waves characterized by a JONSWAP spectrum and random Fourier phases have been launched at the input of the experimental device. The quantitative comparison, based on an appropriate scaling of the two experiments, shows a very good agreement between the statistics in hydrodynamics and optics. Spontaneous emergence of heavy tails in the probability density function of the wave amplitude is observed in both systems. The results demonstrate the universal features of rogue waves and provide a fundamental and explicit bridge between two important fields of research. Numerical simulations are also compared with experimental results.

Measurement of Global Radiation using Photovoltaic Panels

NASA Astrophysics Data System (ADS)

Veroustraete, Frank; Bronders, Jan; Lefevre, Filip; Mensink, Clemens

2014-05-01

The Vito Unit - Environmental and Spatial Aspects (RMA) - for many of its models makes use of global solar radiation. From this viewpoint and also from the notion that this variable is seldom measured or available at the local scale and at high multi-temporal frequencies, it can be stated that many models are fed with low quality estimates of global solar radiation at the local to regional scales. A project was initiated called SUNSPIDER with the following objective. To make use of photovoltaic solar panels to measure solar radiation at the highest spatio-temporal resolution, from the local to the regional scales and from minutes to years. To integrate the measured solar fields in different application fields like, plant systems and agriculture, agro-meteorology and hydrology and last but not least solar energy applications. In Belgium about 250.000 PV installations have been built leading to about 6% electric power supply from photovoltaics on a yearly basis. Last year in June, the supply reached a peak of more than 20% of the total power input on the Belgian grid. A database of Belgian residential solar panel sites will be compiled. The database will serve as an input to an inverted PV model to be able to perform radiation calculations specifically for each of the validated panel sites based on minutely logged power data. Data acquisition for these sites will start each time a site is validated and hence imported in the database. Keywords: Photovoltaic Panels; PV modelling; Global Radiation.

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.

Meteorological Sensor Array (MSA)-Phase I. Volume 3 (Pre-Field Campaign Sensor Calibration)

DTIC Science & Technology

2015-07-01

turbulence impact of the WSMR solar array. 4) Designing , developing, testing , and evaluating integrated Data Acquisition System (DAS) hardware and...ARL-TR-7362 ● JULY 2015 US Army Research Laboratory Meteorological Sensor Array (MSA)–Phase I, Volume 3 (Pre-Field Campaign...NOTICES Disclaimers The findings in this report are not to be construed as an official Department of the Army position unless so designated by

Numerical simulations and observations of surface wave fields under an extreme tropical cyclone

USGS Publications Warehouse

Fan, Y.; Ginis, I.; Hara, T.; Wright, C.W.; Walsh, E.J.

2009-01-01

The performance of the wave model WAVEWATCH III under a very strong, category 5, tropical cyclone wind forcing is investigated with different drag coefficient parameterizations and ocean current inputs. The model results are compared with field observations of the surface wave spectra from an airborne scanning radar altimeter, National Data Buoy Center (NDBC) time series, and satellite altimeter measurements in Hurricane Ivan (2004). The results suggest that the model with the original drag coefficient parameterization tends to overestimate the significant wave height and the dominant wavelength and produces a wave spectrum with narrower directional spreading. When an improved drag parameterization is introduced and the wave-current interaction is included, the model yields an improved forecast of significant wave height, but underestimates the dominant wavelength. When the hurricane moves over a preexisting mesoscale ocean feature, such as the Loop Current in the Gulf of Mexico or a warm-and cold-core ring, the current associated with the feature can accelerate or decelerate the wave propagation and significantly modulate the wave spectrum. ?? 2009 American Meteorological Society.

Mesoscale landscape model of gypsy moth phenology

Treesearch

Joseph M. Russo; John G. W. Kelley; Andrew M. Liebhold

1991-01-01

A recently-developed high resolution climatological temperature data base was input into a gypsy moth phenology model. The high resolution data were created from a coupling of 30-year averages of station observations and digital elevation data. The resultant maximum and minimum temperatures have about a 1 km resolution which represents meteorologically the mesoscale....

NCEP-ECPC monthly to seasonal US fire danger forecasts

Treesearch

J. Roads; P. Tripp; H. Juang; J. Wang; F. Fujioka; S. Chen

2010-01-01

Five National Fire Danger Rating System indices (including the Ignition Component, Energy Release Component, Burning Index, Spread Component, and the Keetch–Byram Drought Index) and the Fosberg Fire Weather Index are used to characterise US fire danger. These fire danger indices and input meteorological variables, including temperature, relative humidity, precipitation...

TESTING PHYSICS AND CHEMISTRY SENSITIVITIES IN THE U.S. EPA COMMUNITY MULTISCALE AIR QUALITY MODELING SYSTEM (CMAQ)

EPA Science Inventory

Uncertainties in key elements of emissions and meteorology inputs to air quality models (AQMs) can range from 50 to 100% with some areas of emissions uncertainty even higher (Russell and Dennis, 2000). Uncertainties in the chemical mechanisms are thought to be smaller (Russell an...

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.

Appraisal of Weather Research and Forecasting Model Downscaling of Hydro-meteorological Variables and their Applicability for Discharge Prediction: Prognostic Approach for Ungauged Basin

NASA Astrophysics Data System (ADS)

Srivastava, P. K.; Han, D.; Rico-Ramirez, M. A.; Bray, M.; Islam, T.; Petropoulos, G.; Gupta, M.

2015-12-01

Hydro-meteorological variables such as Precipitation and Reference Evapotranspiration (ETo) are the most important variables for discharge prediction. However, it is not always possible to get access to them from ground based measurements, particularly in ungauged catchments. The mesoscale model WRF (Weather Research & Forecasting model) can be used for prediction of hydro-meteorological variables. However, hydro-meteorologists would like to know how well the downscaled global data products are as compared to ground based measurements and whether it is possible to use the downscaled data for ungauged catchments. Even with gauged catchments, most of the stations have only rain and flow gauges installed. Measurements of other weather hydro-meteorological variables such as solar radiation, wind speed, air temperature, and dew point are usually missing and thus complicate the problems. In this study, for downscaling the global datasets, the WRF model is setup over the Brue catchment with three nested domains (D1, D2 and D3) of horizontal grid spacing of 81 km, 27 km and 9 km are used. The hydro-meteorological variables are downscaled using the WRF model from the National Centers for Enviromental Prediction (NCEP) reanalysis datasets and subsequently used for the ETo estimation using the Penman Monteith equation. The analysis of weather variables and precipitation are compared against the ground based datasets, which indicate that the datasets are in agreement with the observed datasets for complete monitoring period as well as during the seasons except precipitation whose performance is poorer in comparison to the measured rainfall. After a comparison, the WRF estimated precipitation and ETo are then used as a input parameter in the Probability Distributed Model (PDM) for discharge prediction. The input data and model parameter sensitivity analysis and uncertainty estimation are also taken into account for the PDM calibration and prediction following the Generalised Likelihood Uncertainty Estimation (GLUE) approach. The overall analysis suggests that the uncertainty estimates in predicted discharge using WRF downscaled ETo have comparable performance to ground based observed datasets and hence is promising for discharge prediction in the absence of ground based measurements.

Assimilating concentration observations for transport and dispersion modeling in a meandering wind field

NASA Astrophysics Data System (ADS)

Haupt, Sue Ellen; Beyer-Lout, Anke; Long, Kerrie J.; Young, George S.

Assimilating concentration data into an atmospheric transport and dispersion model can provide information to improve downwind concentration forecasts. The forecast model is typically a one-way coupled set of equations: the meteorological equations impact the concentration, but the concentration does not generally affect the meteorological field. Thus, indirect methods of using concentration data to influence the meteorological variables are required. The problem studied here involves a simple wind field forcing Gaussian dispersion. Two methods of assimilating concentration data to infer the wind direction are demonstrated. The first method is Lagrangian in nature and treats the puff as an entity using feature extraction coupled with nudging. The second method is an Eulerian field approach akin to traditional variational approaches, but minimizes the error by using a genetic algorithm (GA) to directly optimize the match between observations and predictions. Both methods show success at inferring the wind field. The GA-variational method, however, is more accurate but requires more computational time. Dynamic assimilation of a continuous release modeled by a Gaussian plume is also demonstrated using the genetic algorithm approach.

Rugged, no-moving-parts windspeed and static pressure probe designs for measurements in planetary atmospheres

NASA Technical Reports Server (NTRS)

Bedard, A. J., Jr.; Nishiyama, R. T.

1993-01-01

Instruments developed for making meteorological observations under adverse conditions on Earth can be applied to systems designed for other planetary atmospheres. Specifically, a wind sensor developed for making measurements within tornados is capable of detecting induced pressure differences proportional to wind speed. Adding strain gauges to the sensor would provide wind direction. The device can be constructed in a rugged form for measuring high wind speeds in the presence of blowing dust that would clog bearings and plug passages of conventional wind speed sensors. Sensing static pressure in the lower boundary layer required development of an omnidirectional, tilt-insensitive static pressure probe. The probe provides pressure inputs to a sensor with minimum error and is inherently weather-protected. The wind sensor and static pressure probes have been used in a variety of field programs and can be adapted for use in different planetary atmospheres.

Hot limpets: predicting body temperature in a conductance-mediated thermal system.

PubMed

Denny, Mark W; Harley, Christopher D G

2006-07-01

Living at the interface between the marine and terrestrial environments, intertidal organisms may serve as a bellwether for environmental change and a test of our ability to predict its biological consequences. However, current models do not allow us to predict the body temperature of intertidal organisms whose heat budgets are strongly affected by conduction to and from the substratum. Here, we propose a simple heat-budget model of one such animal, the limpet Lottia gigantea, and test the model against measurements made in the field. Working solely from easily measured physical and meteorological inputs, the model predicts the daily maximal body temperatures of live limpets within a fraction of a degree, suggesting that it may be a useful tool for exploring the thermal biology of limpets and for predicting effects of climate change. The model can easily be adapted to predict the temperatures of chitons, acorn barnacles, keyhole limpets, and encrusting animals and plants.

Stochastic Watershed Models for Risk Based Decision Making

NASA Astrophysics Data System (ADS)

Vogel, R. M.

2017-12-01

Over half a century ago, the Harvard Water Program introduced the field of operational or synthetic hydrology providing stochastic streamflow models (SSMs), which could generate ensembles of synthetic streamflow traces useful for hydrologic risk management. The application of SSMs, based on streamflow observations alone, revolutionized water resources planning activities, yet has fallen out of favor due, in part, to their inability to account for the now nearly ubiquitous anthropogenic influences on streamflow. This commentary advances the modern equivalent of SSMs, termed `stochastic watershed models' (SWMs) useful as input to nearly all modern risk based water resource decision making approaches. SWMs are deterministic watershed models implemented using stochastic meteorological series, model parameters and model errors, to generate ensembles of streamflow traces that represent the variability in possible future streamflows. SWMs combine deterministic watershed models, which are ideally suited to accounting for anthropogenic influences, with recent developments in uncertainty analysis and principles of stochastic simulation

Estimating the volcanic emission rate and atmospheric lifetime of SO2 from space: a case study for Kīlauea volcano, Hawai'i

USGS Publications Warehouse

Beirle, Steffen; Hörmann, Christoph; Penning de Vries, Malouse; Dörner, Stefan; Kern, Christoph; Wagner, Thomas

2014-01-01

We present an analysis of SO2 column densities derived from GOME-2 satellite measurements for the Kīlauea volcano (Hawai`i) for 2007–2012. During a period of enhanced degassing activity in March–November 2008, monthly mean SO2 emission rates and effective SO2 lifetimes are determined simultaneously from the observed downwind plume evolution and meteorological wind fields, without further model input. Kīlauea is particularly suited for quantitative investigations from satellite observations owing to the absence of interfering sources, the clearly defined downwind plumes caused by steady trade winds, and generally low cloud fractions. For March–November 2008, the effective SO2 lifetime is 1–2 days, and Kīlauea SO2 emission rates are 9–21 kt day−1, which is about 3 times higher than initially reported from ground-based monitoring systems.

Phenology Atlas of Czechia in preparation - aim & content

NASA Astrophysics Data System (ADS)

Hajkova, L.; Nekovar, J.; Novak, M.; Richterova, D.

2009-09-01

The main task is to create Phenology Atlas of Czechia for the period 1991 - 2010 by using geographic information systems. The general outputs will be maps (average phenophase onset at different altitudes), graphs (evaluation of phenophase onset in time) and tables (statistical results) with text, picture and botanical specification. The publication will be divided into 6 main chapters (Introduction, Phenology in Czechia & Europe, Methodology of observation, Field crops & Fruit trees & Wild plants, Phenology regionalisation, Temporal and Spatial variability). The essantial emphasis will be enforced on wild plants especially allergology important plants and phenophases. CHMI phenological and meteorological data will be used as an input data. This publication will be allocated for general public, supposed size B4, 270 - 300 pages. The research project is proposed for 3 years (2009 - 2011). In the presentation will be given several examples of Atlas content (Norway Spruce and Birch phenophases from Transaction of CHMI Nr.50, 2007).

Effect of radar rainfall time resolution on the predictive capability of a distributed hydrologic model

NASA Astrophysics Data System (ADS)

Atencia, A.; Llasat, M. C.; Garrote, L.; Mediero, L.

2010-10-01

The performance of distributed hydrological models depends on the resolution, both spatial and temporal, of the rainfall surface data introduced. The estimation of quantitative precipitation from meteorological radar or satellite can improve hydrological model results, thanks to an indirect estimation at higher spatial and temporal resolution. In this work, composed radar data from a network of three C-band radars, with 6-minutal temporal and 2 × 2 km2 spatial resolution, provided by the Catalan Meteorological Service, is used to feed the RIBS distributed hydrological model. A Window Probability Matching Method (gage-adjustment method) is applied to four cases of heavy rainfall to improve the observed rainfall sub-estimation in both convective and stratiform Z/R relations used over Catalonia. Once the rainfall field has been adequately obtained, an advection correction, based on cross-correlation between two consecutive images, was introduced to get several time resolutions from 1 min to 30 min. Each different resolution is treated as an independent event, resulting in a probable range of input rainfall data. This ensemble of rainfall data is used, together with other sources of uncertainty, such as the initial basin state or the accuracy of discharge measurements, to calibrate the RIBS model using probabilistic methodology. A sensitivity analysis of time resolutions was implemented by comparing the various results with real values from stream-flow measurement stations.

Thermal bioaerosol cloud tracking with Bayesian classification

NASA Astrophysics Data System (ADS)

Smith, Christian W.; Dupuis, Julia R.; Schundler, Elizabeth C.; Marinelli, William J.

2017-05-01

The development of a wide area, bioaerosol early warning capability employing existing uncooled thermal imaging systems used for persistent perimeter surveillance is discussed. The capability exploits thermal imagers with other available data streams including meteorological data and employs a recursive Bayesian classifier to detect, track, and classify observed thermal objects with attributes consistent with a bioaerosol plume. Target detection is achieved based on similarity to a phenomenological model which predicts the scene-dependent thermal signature of bioaerosol plumes. Change detection in thermal sensor data is combined with local meteorological data to locate targets with the appropriate thermal characteristics. Target motion is tracked utilizing a Kalman filter and nearly constant velocity motion model for cloud state estimation. Track management is performed using a logic-based upkeep system, and data association is accomplished using a combinatorial optimization technique. Bioaerosol threat classification is determined using a recursive Bayesian classifier to quantify the threat probability of each tracked object. The classifier can accept additional inputs from visible imagers, acoustic sensors, and point biological sensors to improve classification confidence. This capability was successfully demonstrated for bioaerosol simulant releases during field testing at Dugway Proving Grounds. Standoff detection at a range of 700m was achieved for as little as 500g of anthrax simulant. Developmental test results will be reviewed for a range of simulant releases, and future development and transition plans for the bioaerosol early warning platform will be discussed.

A novel hybrid forecasting model for PM₁₀ and SO₂ daily concentrations.

PubMed

Wang, Ping; Liu, Yong; Qin, Zuodong; Zhang, Guisheng

2015-02-01

Air-quality forecasting in urban areas is difficult because of the uncertainties in describing both the emission and meteorological fields. The use of incomplete information in the training phase restricts practical air-quality forecasting. In this paper, we propose a hybrid artificial neural network and a hybrid support vector machine, which effectively enhance the forecasting accuracy of an artificial neural network (ANN) and support vector machine (SVM) by revising the error term of the traditional methods. The hybrid methodology can be described in two stages. First, we applied the ANN or SVM forecasting system with historical data and exogenous parameters, such as meteorological variables. Then, the forecasting target was revised by the Taylor expansion forecasting model using the residual information of the error term in the previous stage. The innovation involved in this approach is that it sufficiently and validly utilizes the useful residual information on an incomplete input variable condition. The proposed method was evaluated by experiments using a 2-year dataset of daily PM₁₀ (particles with a diameter of 10 μm or less) concentrations and SO₂ (sulfur dioxide) concentrations from four air pollution monitoring stations located in Taiyuan, China. The theoretical analysis and experimental results demonstrated that the forecasting accuracy of the proposed model is very promising. Copyright © 2014 Elsevier B.V. All rights reserved.

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

Schalk, W.W. III

Early actions of emergency responders during hazardous material releases are intended to assess contamination and potential public exposure. As measurements are collected, an integration of model calculations and measurements can assist to better understand the situation. This study applied a high resolution version of the operational 3-D numerical models used by Lawrence Livermore National Laboratory to a limited meteorological and tracer data set to assist in the interpretation of the dispersion pattern on a 140 km scale. The data set was collected from a tracer release during the morning surface inversion and transition period in the complex terrain of themore » Snake River Plain near Idaho Falls, Idaho in November 1993 by the United States Air Force. Sensitivity studies were conducted to determine model input parameters that best represented the study environment. These studies showed that mixing and boundary layer heights, atmospheric stability, and rawinsonde data are the most important model input parameters affecting wind field generation and tracer dispersion. Numerical models and limited measurement data were used to interpret dispersion patterns through the use of data analysis, model input determination, and sensitivity studies. Comparison of the best-estimate calculation to measurement data showed that model results compared well with the aircraft data, but had moderate success with the few surface measurements taken. The moderate success of the surface measurement comparison, may be due to limited downward mixing of the tracer as a result of the model resolution determined by the domain size selected to study the overall plume dispersion. 8 refs., 40 figs., 7 tabs.« less

Use of geostationary meteorological satellite images in convective rain estimation for flash-flood forecasting

NASA Astrophysics Data System (ADS)

Wardah, T.; Abu Bakar, S. H.; Bardossy, A.; Maznorizan, M.

2008-07-01

SummaryFrequent flash-floods causing immense devastation in the Klang River Basin of Malaysia necessitate an improvement in the real-time forecasting systems being used. The use of meteorological satellite images in estimating rainfall has become an attractive option for improving the performance of flood forecasting-and-warning systems. In this study, a rainfall estimation algorithm using the infrared (IR) information from the Geostationary Meteorological Satellite-5 (GMS-5) is developed for potential input in a flood forecasting system. Data from the records of GMS-5 IR images have been retrieved for selected convective cells to be trained with the radar rain rate in a back-propagation neural network. The selected data as inputs to the neural network, are five parameters having a significant correlation with the radar rain rate: namely, the cloud-top brightness-temperature of the pixel of interest, the mean and the standard deviation of the temperatures of the surrounding five by five pixels, the rate of temperature change, and the sobel operator that indicates the temperature gradient. In addition, three numerical weather prediction (NWP) products, namely the precipitable water content, relative humidity, and vertical wind, are also included as inputs. The algorithm is applied for the areal rainfall estimation in the upper Klang River Basin and compared with another technique that uses power-law regression between the cloud-top brightness-temperature and radar rain rate. Results from both techniques are validated against previously recorded Thiessen areal-averaged rainfall values with coefficient correlation values of 0.77 and 0.91 for the power-law regression and the artificial neural network (ANN) technique, respectively. An extra lead time of around 2 h is gained when the satellite-based ANN rainfall estimation is coupled with a rainfall-runoff model to forecast a flash-flood event in the upper Klang River Basin.

Estimating water temperatures in small streams in western Oregon using neural network models

USGS Publications Warehouse

Risley, John C.; Roehl, Edwin A.; Conrads, Paul

2003-01-01

Artificial neural network models were developed to estimate water temperatures in small streams using data collected at 148 sites throughout western Oregon from June to September 1999. The sites were located on 1st-, 2nd-, or 3rd-order streams having undisturbed or minimally disturbed conditions. Data collected at each site for model development included continuous hourly water temperature and description of riparian habitat. Additional data pertaining to the landscape characteristics of the basins upstream of the sites were assembled using geographic information system (GIS) techniques. Hourly meteorological time series data collected at 25 locations within the study region also were assembled. Clustering analysis was used to partition 142 sites into 3 groups. Separate models were developed for each group. The riparian habitat, basin characteristic, and meteorological time series data were independent variables and water temperature time series were dependent variables to the models, respectively. Approximately one-third of the data vectors were used for model training, and the remaining two-thirds were used for model testing. Critical input variables included riparian shade, site elevation, and percentage of forested area of the basin. Coefficient of determination and root mean square error for the models ranged from 0.88 to 0.99 and 0.05 to 0.59 oC, respectively. The models also were tested and validated using temperature time series, habitat, and basin landscape data from 6 sites that were separate from the 142 sites that were used to develop the models. The models are capable of estimating water temperatures at locations along 1st-, 2nd-, and 3rd-order streams in western Oregon. The model user must assemble riparian habitat and basin landscape characteristics data for a site of interest. These data, in addition to meteorological data, are model inputs. Output from the models include simulated hourly water temperatures for the June to September period. Adjustments can be made to the shade input data to simulate the effects of minimum or maximum shade on water temperatures.

TopoSCALE v.1.0: downscaling gridded climate data in complex terrain

NASA Astrophysics Data System (ADS)

Fiddes, J.; Gruber, S.

2014-02-01

Simulation of land surface processes is problematic in heterogeneous terrain due to the the high resolution required of model grids to capture strong lateral variability caused by, for example, topography, and the lack of accurate meteorological forcing data at the site or scale it is required. Gridded data products produced by atmospheric models can fill this gap, however, often not at an appropriate spatial resolution to drive land-surface simulations. In this study we describe a method that uses the well-resolved description of the atmospheric column provided by climate models, together with high-resolution digital elevation models (DEMs), to downscale coarse-grid climate variables to a fine-scale subgrid. The main aim of this approach is to provide high-resolution driving data for a land-surface model (LSM). The method makes use of an interpolation of pressure-level data according to topographic height of the subgrid. An elevation and topography correction is used to downscale short-wave radiation. Long-wave radiation is downscaled by deriving a cloud-component of all-sky emissivity at grid level and using downscaled temperature and relative humidity fields to describe variability with elevation. Precipitation is downscaled with a simple non-linear lapse and optionally disaggregated using a climatology approach. We test the method in comparison with unscaled grid-level data and a set of reference methods, against a large evaluation dataset (up to 210 stations per variable) in the Swiss Alps. We demonstrate that the method can be used to derive meteorological inputs in complex terrain, with most significant improvements (with respect to reference methods) seen in variables derived from pressure levels: air temperature, relative humidity, wind speed and incoming long-wave radiation. This method may be of use in improving inputs to numerical simulations in heterogeneous and/or remote terrain, especially when statistical methods are not possible, due to lack of observations (i.e. remote areas or future periods).

Effects of Land-use/Land-cover and Climate Changes on Water Quantity and Quality in Sub-basins near Major US Cities in the Great Lakes Region

NASA Astrophysics Data System (ADS)

Murphy, L.; Al-Hamdan, M. Z.; Crosson, W. L.; Barik, M.

2017-12-01

Land-cover change over time to urbanized, less permeable surfaces, leads to reduced water infiltration at the location of water input while simultaneously transporting sediments, nutrients and contaminants farther downstream. With an abundance of agricultural fields bordering the greater urban areas of Milwaukee, Detroit, and Chicago, water and nutrient transport is vital to the farming industry, wetlands, and communities that rely on water availability. Two USGS stream gages each located within a sub-basin near each of these Great Lakes Region cities were examined, one with primarily urban land-cover between 1992 and 2011, and one with primarily agriculture land-cover. ArcSWAT, a watershed model and soil and water assessment tool used in extension with ArcGIS, was used to develop hydrologic models that vary the land-covers to simulate surface runoff during a model run period from 2004 to 2008. Model inputs that include a digital elevation model (DEM), Landsat-derived land-use/land-cover (LULC) satellite images from 1992, 2001, and 2011, soil classification, and meteorological data were used to determine the effect of different land-covers on the water runoff, nutrients and sediments. The models were then calibrated and validated to USGS stream gage data measurements over time. Additionally, the watershed model was run based on meteorological data from an IPCC CMIP5 high emissions climate change scenario for 2050. Model outputs from the different LCLU scenarios were statistically evaluated and results showed that water runoff, nutrients and sediments were impacted by LULC change in four out of the six sub-basins. In the 2050 climate scenario, only one out of the six sub-basin's water quantity and quality was affected. These results contribute to the importance of developing hydrologic models as the dependence on the Great Lakes as a freshwater resource competes with the expansion of urbanization leading to the movement of runoff, nutrients, and sediments off the land.

Large-scale derived flood frequency analysis based on continuous simulation

NASA Astrophysics Data System (ADS)

Dung Nguyen, Viet; Hundecha, Yeshewatesfa; Guse, Björn; Vorogushyn, Sergiy; Merz, Bruno

2016-04-01

There is an increasing need for spatially consistent flood risk assessments at the regional scale (several 100.000 km2), in particular in the insurance industry and for national risk reduction strategies. However, most large-scale flood risk assessments are composed of smaller-scale assessments and show spatial inconsistencies. To overcome this deficit, a large-scale flood model composed of a weather generator and catchments models was developed reflecting the spatially inherent heterogeneity. The weather generator is a multisite and multivariate stochastic model capable of generating synthetic meteorological fields (precipitation, temperature, etc.) at daily resolution for the regional scale. These fields respect the observed autocorrelation, spatial correlation and co-variance between the variables. They are used as input into catchment models. A long-term simulation of this combined system enables to derive very long discharge series at many catchment locations serving as a basic for spatially consistent flood risk estimates at the regional scale. This combined model was set up and validated for major river catchments in Germany. The weather generator was trained by 53-year observation data at 528 stations covering not only the complete Germany but also parts of France, Switzerland, Czech Republic and Australia with the aggregated spatial scale of 443,931 km2. 10.000 years of daily meteorological fields for the study area were generated. Likewise, rainfall-runoff simulations with SWIM were performed for the entire Elbe, Rhine, Weser, Donau and Ems catchments. The validation results illustrate a good performance of the combined system, as the simulated flood magnitudes and frequencies agree well with the observed flood data. Based on continuous simulation this model chain is then used to estimate flood quantiles for the whole Germany including upstream headwater catchments in neighbouring countries. This continuous large scale approach overcomes the several drawbacks reported in traditional approaches for the derived flood frequency analysis and therefore is recommended for large scale flood risk case studies.

Urban impact on air quality in RegCM/CAMx couple for MEGAPOLI project - high resolution sensitivity study

NASA Astrophysics Data System (ADS)

Halenka, T.; Huszar, P.; Belda, M.

2010-09-01

Recent studies show considerable effect of atmospheric chemistry and aerosols on climate on regional and local scale. For the purpose of qualifying and quantifying the magnitude of climate forcing due to atmospheric chemistry/aerosols on regional scale, the development of coupling of regional climate model and chemistry/aerosol model was started on the Department of Meteorology and Environmental Protection, Charles University, Prague, for the EC FP6 Project QUANTIFY and EC FP6 Project CECILIA. For this coupling, existing regional climate model and chemistry transport model have been used at very high resolution of 10km grid. Climate is calculated using RegCM while chemistry is solved by CAMx. The experiments with the couple have been prepared for EC FP7 project MEGAPOLI assessing the impact of the megacities and industrialized areas on climate. Meteorological fields generated by RCM drive CAMx transport, chemistry and a dry/wet deposition. A preprocessor utility was developed for transforming RegCM provided fields to CAMx input fields and format. New domain have been settled for MEGAPOLI purpose in 10km resolution including all the European "megacities" regions, i.e. London metropolitan area, Paris region, industrialized Ruhr area, Po valley etc. There is critical issue of the emission inventories available for 10km resolution including the urban hot-spots, TNO emissions are adopted for this sensitivity study in 10km resolution for comparison of the results with the simulation based on merged TNO emissions, i.e. basically original EMEP emissions at 50 km grid. The sensitivity test to switch on/off Paris area emissions is analysed as well. Preliminary results for year 2005 are presented and discussed to reveal whether the concept of effective emission indices could help to parameterize the urban plume effects in lower resolution models. Interactive coupling is compared to study the potential of possible impact of urban air-pollution to the urban area climate.

Estimation of clear-sky insolation using satellite and ground meteorological data

NASA Technical Reports Server (NTRS)

Staylor, W. F.; Darnell, W. L.; Gupta, S. K.

1983-01-01

Ground based pyranometer measurements were combined with meteorological data from the Tiros N satellite in order to estimate clear-sky insolations at five U.S. sites for five weeks during the spring of 1979. The estimates were used to develop a semi-empirical model of clear-sky insolation for the interpretation of input data from the Tiros Operational Vertical Sounder (TOVS). Using only satellite data, the estimated standard errors in the model were about 2 percent. The introduction of ground based data reduced errors to around 1 percent. It is shown that although the errors in the model were reduced by only 1 percent, TOVS data products are still adequate for estimating clear-sky insolation.

[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.

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.

[Real-time irrigation forecast of cotton mulched with plastic film under drip irrigation based on meteorological date].

PubMed

Shen, Xiao-jun; Sun, Jing-sheng; Li, Ming-si; Zhang, Ji-yang; Wang, Jing-lei; Li, Dong-wei

2015-02-01

It is important to improve the real-time irrigation forecasting precision by predicting real-time water consumption of cotton mulched with plastic film under drip irrigation based on meteorological data and cotton growth status. The model parameters for calculating ET0 based on Hargreaves formula were determined using historical meteorological data from 1953 to 2008 in Shihezi reclamation area. According to the field experimental data of growing season in 2009-2010, the model of computing crop coefficient Kc was established based on accumulated temperature. On the basis of crop water requirement (ET0) and Kc, a real-time irrigation forecast model was finally constructed, and it was verified by the field experimental data in 2011. The results showed that the forecast model had high forecasting precision, and the average absolute values of relative error between the predicted value and measured value were about 3.7%, 2.4% and 1.6% during seedling, squaring and blossom-boll forming stages, respectively. The forecast model could be used to modify the predicted values in time according to the real-time meteorological data and to guide the water management in local film-mulched cotton field under drip irrigation.

URBAN MORPHOLOGICAL ANALYSIS FOR MESOSCALE METEOROLOGICAL AND DISPERSION MODELING APPLICATIONS: CURRENT ISSUES

EPA Science Inventory

Representing urban terrain characteristics in mesoscale meteorological and dispersion models is critical to produce accurate predictions of wind flow and temperature fields, air quality, and contaminant transport. A key component of the urban terrain representation is the charac...

Development of the ClearSky smoke dispersion forecast system for agricultural field burning in the Pacific Northwest

NASA Astrophysics Data System (ADS)

Jain, Rahul; Vaughan, Joseph; Heitkamp, Kyle; Ramos, Charleston; Claiborn, Candis; Schreuder, Maarten; Schaaf, Mark; Lamb, Brian

The post-harvest burning of agricultural fields is commonly used to dispose of crop residue and provide other desired services such as pest control. Despite careful regulation of burning, smoke plumes from field burning in the Pacific Northwest commonly degrade air quality, particularly for rural populations. In this paper, ClearSky, a numerical smoke dispersion forecast system for agricultural field burning that was developed to support smoke management in the Inland Pacific Northwest, is described. ClearSky began operation during the summer through fall burn season of 2002 and continues to the present. ClearSky utilizes Mesoscale Meteorological Model version 5 (MM5v3) forecasts from the University of Washington, data on agricultural fields, a web-based user interface for defining burn scenarios, the Lagrangian CALPUFF dispersion model and web-served animations of plume forecasts. The ClearSky system employs a unique hybrid source configuration, which treats the flaming portion of a field as a buoyant line source and the smoldering portion of the field as a buoyant area source. Limited field observations show that this hybrid approach yields reasonable plume rise estimates using source parameters derived from recent field burning emission field studies. The performance of this modeling system was evaluated for 2003 by comparing forecast meteorology against meteorological observations, and comparing model-predicted hourly averaged PM 2.5 concentrations against observations. Examples from this evaluation illustrate that while the ClearSky system can accurately predict PM 2.5 surface concentrations due to field burning, the overall model performance depends strongly on meteorological forecast error. Statistical evaluation of the meteorological forecast at seven surface stations indicates a strong relationship between topographical complexity near the station and absolute wind direction error with wind direction errors increasing from approximately 20° for sites in open areas to 70° or more for sites in very complex terrain. The analysis also showed some days with good forecast meteorology with absolute mean error in wind direction less than 30° when ClearSky correctly predicted PM 2.5 surface concentrations at receptors affected by field burns. On several other days with similar levels of wind direction error the model did not predict apparent plume impacts. In most of these cases, there were no reported burns in the vicinity of the monitor and, thus, it appeared that other, non-reported burns were responsible for the apparent plume impact at the monitoring site. These cases do not provide information on the performance of the model, but rather indicate that further work is needed to identify all burns and to improve burn reports in an accurate and timely manner. There were also a number of days with wind direction errors exceeding 70° when the forecast system did not correctly predict plume behavior.

Meteorological interpretation of transient LOD changes

NASA Astrophysics Data System (ADS)

Masaki, Y.

2008-04-01

The Earth’s spin rate is mainly changed by zonal winds. For example, seasonal changes in global atmospheric circulation and episodic changes accompanied with El Nĩ os are clearly detected n in the Length-of-day (LOD). Sub-global to regional meteorological phenomena can also change the wind field, however, their effects on the LOD are uncertain because such LOD signals are expected to be subtle and transient. In our previous study (Masaki, 2006), we introduced atmospheric pressure gradients in the upper atmosphere in order to obtain a rough picture of the meteorological features that can change the LOD. In this presentation, we compare one-year LOD data with meteorological elements (winds, temperature, pressure, etc.) and make an attempt to link transient LOD changes with sub-global meteorological phenomena.

PEM-West trajectory climatology and photochemical model sensitivity study prepared using retrospective meteorological data

NASA Technical Reports Server (NTRS)

Merrill, John T.; Rodriguez, Jose M.

1991-01-01

Trajectory and photochemical model calculations based on retrospective meteorological data for the operations areas of the NASA Pacific Exploratory Mission (PEM)-West mission are summarized. The trajectory climatology discussed here is intended to provide guidance for flight planning and initial data interpretation during the field phase of the expedition by indicating the most probable path air parcels are likely to take to reach various points in the area. The photochemical model calculations which are discussed indicate the sensitivity of the chemical environment to various initial chemical concentrations and to conditions along the trajectory. In the post-expedition analysis these calculations will be used to provide a climatological context for the meteorological conditions which are encountered in the field.

Coupling of WRF meteorological model to WAM spectral wave model through sea surface roughness at the Balearic Sea: impact on wind and wave forecasts

NASA Astrophysics Data System (ADS)

Tolosana-Delgado, R.; Soret, A.; Jorba, O.; Baldasano, J. M.; Sánchez-Arcilla, A.

2012-04-01

Meteorological models, like WRF, usually describe the earth surface characteristics by tables that are function of land-use. The roughness length (z0) is an example of such approach. However, over sea z0 is modeled by the Charnock (1955) relation, linking the surface friction velocity u*2 with the roughness length z0 of turbulent air flow, z0 = α-u2* g The Charnock coefficient α may be considered a measure of roughness. For the sea surface, WRF considers a constant roughness α = 0.0185. However, there is evidence that sea surface roughness should depend on wave energy (Donelan, 1982). Spectral wave models like WAM, model the evolution and propagation of wave energy as a function of wind, and include a richer sea surface roughness description. Coupling WRF and WAM is thus a common way to improve the sea surface roughness description of WRF. WAM is a third generation wave model, solving the equation of advection of wave energy subject to input/output terms of: wind growth, energy dissipation and resonant non-linear wave-wave interactions. Third generation models work on the spectral domain. WAM considers the Charnock coefficient α a complex yet known function of the total wind input term, which depends on the wind velocity and on the Charnock coefficient again. This is solved iteratively (Janssen et al., 1990). Coupling of meteorological and wave models through a common Charnock coefficient is operationally done in medium-range met forecasting systems (e.g., at ECMWF) though the impact of coupling for smaller domains is not yet clearly assessed (Warner et al, 2010). It is unclear to which extent the additional effort of coupling improves the local wind and wave fields, in comparison to the effects of other factors, like e.g. a better bathymetry and relief resolution, or a better circulation information which might have its influence on local-scale meteorological processes (local wind jets, local convection, daily marine wind regimes, etc.). This work, within the scope of the 7th EU FP Project FIELD_AC, assesses the impact of coupling WAM and WRF on wind and wave forecasts on the Balearic Sea, and compares it with other possible improvements, like using available high-resolution circulation information from MyOcean GMES core services, or assimilating altimeter data on the Western Mediterranean. This is done in an ordered fashion following statistical design rules, which allows to extract main effects of each of the factors considered (coupling, better circulation information, data assimilation following Lionello et al., 1992) as well as two-factor interactions. Moreover, the statistical significance of these improvements can be tested in the future, though this requires maximum likelihood ratio tests with correlated data. Charnock, H. (1955) Wind stress on a water surface. Quart.J. Row. Met. Soc. 81: 639-640 Donelan, M. (1982) The dependence of aerodynamic drag coefficient on wave parameters. Proc. 1st Int. Conf. on Meteorology and Air-Sea Interactions of teh Coastal Zone. The Hague (Netherlands). AMS. 381-387 Janssen, P.A.E.M., Doyle, J., Bidlot, J., Hansen, B., Isaksen, L. and Viterbo, P. (1990) The impact of oean waves on the atmosphere. Seminars of the ECMWF. Lionello, P., Günther, H., and Janssen P.A.E.M. (1992) Assimilation of altimeter data in a global third-generation wave model. Journal of Geophysical Research 97 (C9): 453-474. Warner, J., Armstrong, B., He, R. and Zambon, J.B. (2010) Development of a Coupled Ocean-Atmosphere-Wave-Sediment Transport (COAWST) Modeling System. Ocean Modelling 35: 230-244.

Urban and regional land use analysis: CARETS and census cities experiment package

NASA Technical Reports Server (NTRS)

Alexander, R. (Principal Investigator); Lins, H. F., Jr.; Gallagher, D. B.

1975-01-01

The author has identified the following significant results. Temperatures in degrees Celsius were derived from PCM counts using the Pease's modified gray window technique. The Outcalt simulator was setup on the USGS computer. The input data to the model are basically meteorological and geographical in nature. The output data is presented in three matrices.

A comparison between modeled and measured permafrost temperatures at Ritigraben borehole, Switzerland

NASA Astrophysics Data System (ADS)

Mitterer-Hoinkes, Susanna; Lehning, Michael; Phillips, Marcia; Sailer, Rudolf

2013-04-01

The area-wide distribution of permafrost is sparsely known in mountainous terrain (e.g. Alps). Permafrost monitoring can only be based on point or small scale measurements such as boreholes, active rock glaciers, BTS measurements or geophysical measurements. To get a better understanding of permafrost distribution, it is necessary to focus on modeling permafrost temperatures and permafrost distribution patterns. A lot of effort on these topics has been already expended using different kinds of models. In this study, the evolution of subsurface temperatures over successive years has been modeled at the location Ritigraben borehole (Mattertal, Switzerland) by using the one-dimensional snow cover model SNOWPACK. The model needs meteorological input and in our case information on subsurface properties. We used meteorological input variables of the automatic weather station Ritigraben (2630 m) in combination with the automatic weather station Saas Seetal (2480 m). Meteorological data between 2006 and 2011 on an hourly basis were used to drive the model. As former studies showed, the snow amount and the snow cover duration have a great influence on the thermal regime. Low snow heights allow for deeper penetration of low winter temperatures into the ground, strong winters with a high amount of snow attenuate this effect. In addition, variations in subsurface conditions highly influence the temperature regime. Therefore, we conducted sensitivity runs by defining a series of different subsurface properties. The modeled subsurface temperature profiles of Ritigraben were then compared to the measured temperatures in the Ritigraben borehole. This allows a validation of the influence of subsurface properties on the temperature regime. As expected, the influence of the snow cover is stronger than the influence of sub-surface material properties, which are significant, however. The validation presented here serves to prepare a larger spatial simulation with the complex hydro-meteorological 3-dimensional model Alpine 3D, which is based on a distributed application of SNOWPACK.

Statistical Approaches for Spatiotemporal Prediction of Low Flows

NASA Astrophysics Data System (ADS)

Fangmann, A.; Haberlandt, U.

2017-12-01

An adequate assessment of regional climate change impacts on streamflow requires the integration of various sources of information and modeling approaches. This study proposes simple statistical tools for inclusion into model ensembles, which are fast and straightforward in their application, yet able to yield accurate streamflow predictions in time and space. Target variables for all approaches are annual low flow indices derived from a data set of 51 records of average daily discharge for northwestern Germany. The models require input of climatic data in the form of meteorological drought indices, derived from observed daily climatic variables, averaged over the streamflow gauges' catchments areas. Four different modeling approaches are analyzed. Basis for all pose multiple linear regression models that estimate low flows as a function of a set of meteorological indices and/or physiographic and climatic catchment descriptors. For the first method, individual regression models are fitted at each station, predicting annual low flow values from a set of annual meteorological indices, which are subsequently regionalized using a set of catchment characteristics. The second method combines temporal and spatial prediction within a single panel data regression model, allowing estimation of annual low flow values from input of both annual meteorological indices and catchment descriptors. The third and fourth methods represent non-stationary low flow frequency analyses and require fitting of regional distribution functions. Method three is subject to a spatiotemporal prediction of an index value, method four to estimation of L-moments that adapt the regional frequency distribution to the at-site conditions. The results show that method two outperforms successive prediction in time and space. Method three also shows a high performance in the near future period, but since it relies on a stationary distribution, its application for prediction of far future changes may be problematic. Spatiotemporal prediction of L-moments appeared highly uncertain for higher-order moments resulting in unrealistic future low flow values. All in all, the results promote an inclusion of simple statistical methods in climate change impact assessment.

Development of an analysis tool for cloud base height and visibility

NASA Astrophysics Data System (ADS)

Umdasch, Sarah; Reinhold, Steinacker; Manfred, Dorninger; Markus, Kerschbaum; Wolfgang, Pöttschacher

2014-05-01

The meteorological variables cloud base height (CBH) and horizontal atmospheric visibility (VIS) at surface level are of vital importance for safety and effectiveness in aviation. Around 20% of all civil aviation accidents in the USA from 2003 to 2007 were due to weather related causes, around 18% of which were owing to decreased visibility or ceiling (main CBH). The aim of this study is to develop a system generating quality-controlled gridded analyses of the two parameters based on the integration of various kinds of observational data. Upon completion, the tool is planned to provide guidance for nowcasting during take-off and landing as well as for flights operated under visual flight rules. Primary input data consists of manual as well as instrumental observation of CBH and VIS. In Austria, restructuring of part of the standard meteorological stations from human observation to automatic measurement of VIS and CBH is currently in progress. As ancillary data, satellite derived products can add 2-dimensional information, e.g. Cloud Type by NWC SAF (Nowcasting Satellite Application Facilities) MSG (Meteosat Second Generation). Other useful available data are meteorological surface measurements (in particular of temperature, humidity, wind and precipitation), radiosonde, radar and high resolution topography data. A one-year data set is used to study the spatial and weather-dependent representativeness of the CBH and VIS measurements. The VERA (Vienna Enhanced Resolution Analysis) system of the Institute of Meteorology and Geophysics of the University of Vienna provides the framework for the analysis development. Its integrated "Fingerprint" technique allows the insertion of empirical prior knowledge and ancillary information in the form of spatial patterns. Prior to the analysis, a quality control of input data is performed. For CBH and VIS, quality control can consist of internal consistency checks between different data sources. The possibility of two-dimensional consistency checks has to be explored. First results in the development of quality control features and fingerprints will be shown.

Towards a Near Real-Time Satellite-Based Flux Monitoring System for the MENA Region

NASA Astrophysics Data System (ADS)

Ershadi, A.; Houborg, R.; McCabe, M. F.; Anderson, M. C.; Hain, C.

2013-12-01

Satellite remote sensing has the potential to offer spatially and temporally distributed information on land surface characteristics, which may be used as inputs and constraints for estimating land surface fluxes of carbon, water and energy. Enhanced satellite-based monitoring systems for aiding local water resource assessments and agricultural management activities are particularly needed for the Middle East and North Africa (MENA) region. The MENA region is an area characterized by limited fresh water resources, an often inefficient use of these, and relatively poor in-situ monitoring as a result of sparse meteorological observations. To address these issues, an integrated modeling approach for near real-time monitoring of land surface states and fluxes at fine spatio-temporal scales over the MENA region is presented. This approach is based on synergistic application of multiple sensors and wavebands in the visible to shortwave infrared and thermal infrared (TIR) domain. The multi-scale flux mapping and monitoring system uses the Atmosphere-Land Exchange Inverse (ALEXI) model and associated flux disaggregation scheme (DisALEXI), and the Spatial and Temporal Adaptive Reflectance Fusion Model (STARFM) in conjunction with model reanalysis data and multi-sensor remotely sensed data from polar orbiting (e.g. Landsat and MODerate resolution Imaging Spectroradiometer (MODIS)) and geostationary (MSG; Meteosat Second Generation) satellite platforms to facilitate time-continuous (i.e. daily) estimates of field-scale water, energy and carbon fluxes. Within this modeling system, TIR satellite data provide information about the sub-surface moisture status and plant stress, obviating the need for precipitation input and a detailed soil surface characterization (i.e. for prognostic modeling of soil transport processes). The STARFM fusion methodology blends aspects of high frequency (spatially coarse) and spatially fine resolution sensors and is applied directly to flux output fields to facilitate daily mapping of fluxes at sub-field scales. A complete processing infrastructure to automatically ingest and pre-process all required input data and to execute the integrated modeling system for near real-time agricultural monitoring purposes over targeted MENA sites is being developed, and initial results from this concerted effort will be discussed.

MODELED MESOSCALE METEOROLOGICAL FIELDS WITH FOUR-DIMENSIONAL DATA ASSIMILATION IN REGIONAL SCALE AIR QUALITY MODELS

EPA Science Inventory

This paper addresses the need to increase the temporal and spatial resolution of meteorological data currently used in air quality simulation models, AQSMs. ransport and diffusion parameters including mixing heights and stability used in regulatory air quality dispersion models a...

The role of the global electric circuit in solar and internal forcing of clouds and climate

NASA Astrophysics Data System (ADS)

Tinsley, Brian A.; Burns, G. B.; Zhou, Limin

Reports of a variety of short-term meteorological responses to changes in the global electric circuit associated with a set of disparate inputs are analyzed. The meteorological responses consist of changes in cloud cover, atmospheric temperature, pressure, or dynamics. All of these are found to be responding to changes in a key linking agent, that of the downward current density, Jz, that flows from the ionosphere through the troposphere to the surface (ocean and land). As it flows through layer clouds, Jz generates space charge in conductivity gradients at the upper and lower boundaries, and this electrical charge is capable of affecting the microphysical interactions between droplets and both ice-forming nuclei and condensation nuclei. Four short-term inputs to the global circuit are due to solar activity and consist of (1) Forbush decreases of the galactic cosmic ray flux; (2) solar energetic particle events; (3) relativistic electron precipitation changes; and (4) polar cap ionospheric convection potential changes. One input that is internal to the global circuit consists of (5) global ionospheric potential changes due to changes in the current output of the highly electrified clouds (mainly deep convective clouds at low latitudes) that act as generators for the circuit. The observed short-term meteorological responses to these five inputs are of small amplitude but high statistical significance for repeated Jz changes of order 5% for low latitudes increasing to 25-30% at high latitudes. On the timescales of multidecadal solar minima, such as the Maunder minimum, changes in tropospheric dynamics and climate related to Jz are also larger at high latitudes, and correlate with the lower energy component (˜1 GeV) of the cosmic ray flux increasing by as much as a factor of two relative to present values. Also, there are comparable cosmic ray flux changes and climate responses on millennial timescales. The persistence of the longer-term Jz changes for many decades to many centuries would produce an integrated effect on climate that could dominate over short-term weather and climate variations, and explain the observed correlations. Thus, we propose that mechanisms responding to Jz are a candidate for explanations of sun-weather-climate correlations on multidecadal to millenial timescales, as well as on the day-to-day timescales analyzed here.

Synoptic Meteorology during the SNOW-ONE-A Field Experiment.

DTIC Science & Technology

1983-05-01

AD ,34 888 SYNOPTIC METEOROLOGY DURING tHE SNOW-ONE A FIELD I EXPERIMENTIUP COLD REGIONS RESEARCH AND ENGINEERING LABHANOVER NN M A BILELLO MAY 83...PROGRAM ELEMENT. PROJECT. TASK U. S. Army Cold Regions Research and AREA & WORK UNIT NUMBERS Engineering Laboratory DA Project 4A762730AT42- Hanover, New...Hampshire 03755 B-El-5 It. CONTROLLING OFFICE NAME AND ADDRESS 12. REPORT DATE Office of the Ch ief of Engineers May 1983 Washington, D.C. 20314 13

Agricultural Meteorology in China.

NASA Astrophysics Data System (ADS)

Rosenberg, Norman J.

1982-03-01

During nearly five weeks in China (May-June 1981), the author visited scientific institutions and experiment stations engaged in agricultural meterology and climatology research and teaching. The facilities, studies, and research programs at each institution are described and the scientific work in these fields is evaluated. Agricultural meteorology and climatology are faced with some unique problems and opportunities in China and progress in these fields may be of critical importance to that nation in coming years. The author includes culinary notes and comments on protocol in China.

The added value of stochastic spatial disaggregation for short-term rainfall forecasts currently available in Canada

NASA Astrophysics Data System (ADS)

Gagnon, Patrick; Rousseau, Alain N.; Charron, Dominique; Fortin, Vincent; Audet, René

2017-11-01

Several businesses and industries rely on rainfall forecasts to support their day-to-day operations. To deal with the uncertainty associated with rainfall forecast, some meteorological organisations have developed products, such as ensemble forecasts. However, due to the intensive computational requirements of ensemble forecasts, the spatial resolution remains coarse. For example, Environment and Climate Change Canada's (ECCC) Global Ensemble Prediction System (GEPS) data is freely available on a 1-degree grid (about 100 km), while those of the so-called High Resolution Deterministic Prediction System (HRDPS) are available on a 2.5-km grid (about 40 times finer). Potential users are then left with the option of using either a high-resolution rainfall forecast without uncertainty estimation and/or an ensemble with a spectrum of plausible rainfall values, but at a coarser spatial scale. The objective of this study was to evaluate the added value of coupling the Gibbs Sampling Disaggregation Model (GSDM) with ECCC products to provide accurate, precise and consistent rainfall estimates at a fine spatial resolution (10-km) within a forecast framework (6-h). For 30, 6-h, rainfall events occurring within a 40,000-km2 area (Québec, Canada), results show that, using 100-km aggregated reference rainfall depths as input, statistics of the rainfall fields generated by GSDM were close to those of the 10-km reference field. However, in forecast mode, GSDM outcomes inherit of the ECCC forecast biases, resulting in a poor performance when GEPS data were used as input, mainly due to the inherent rainfall depth distribution of the latter product. Better performance was achieved when the Regional Deterministic Prediction System (RDPS), available on a 10-km grid and aggregated at 100-km, was used as input to GSDM. Nevertheless, most of the analyzed ensemble forecasts were weakly consistent. Some areas of improvement are identified herein.

Performance assessment of nitrate leaching models for highly vulnerable soils used in low-input farming based on lysimeter data.

PubMed

Groenendijk, Piet; Heinen, Marius; Klammler, Gernot; Fank, Johann; Kupfersberger, Hans; Pisinaras, Vassilios; Gemitzi, Alexandra; Peña-Haro, Salvador; García-Prats, Alberto; Pulido-Velazquez, Manuel; Perego, Alessia; Acutis, Marco; Trevisan, Marco

2014-11-15

The agricultural sector faces the challenge of ensuring food security without an excessive burden on the environment. Simulation models provide excellent instruments for researchers to gain more insight into relevant processes and best agricultural practices and provide tools for planners for decision making support. The extent to which models are capable of reliable extrapolation and prediction is important for exploring new farming systems or assessing the impacts of future land and climate changes. A performance assessment was conducted by testing six detailed state-of-the-art models for simulation of nitrate leaching (ARMOSA, COUPMODEL, DAISY, EPIC, SIMWASER/STOTRASIM, SWAP/ANIMO) for lysimeter data of the Wagna experimental field station in Eastern Austria, where the soil is highly vulnerable to nitrate leaching. Three consecutive phases were distinguished to gain insight in the predictive power of the models: 1) a blind test for 2005-2008 in which only soil hydraulic characteristics, meteorological data and information about the agricultural management were accessible; 2) a calibration for the same period in which essential information on field observations was additionally available to the modellers; and 3) a validation for 2009-2011 with the corresponding type of data available as for the blind test. A set of statistical metrics (mean absolute error, root mean squared error, index of agreement, model efficiency, root relative squared error, Pearson's linear correlation coefficient) was applied for testing the results and comparing the models. None of the models performed good for all of the statistical metrics. Models designed for nitrate leaching in high-input farming systems had difficulties in accurately predicting leaching in low-input farming systems that are strongly influenced by the retention of nitrogen in catch crops and nitrogen fixation by legumes. An accurate calibration does not guarantee a good predictive power of the model. Nevertheless all models were able to identify years and crops with high- and low-leaching rates. Copyright © 2014 Elsevier B.V. All rights reserved.

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.

Does a more skilful meteorological input lead to a more skilful flood forecast at seasonal timescales?

NASA Astrophysics Data System (ADS)

Neumann, Jessica; Arnal, Louise; Magnusson, Linus; Cloke, Hannah

2017-04-01

Seasonal river flow forecasts are important for many aspects of the water sector including flood forecasting, water supply, hydropower generation and navigation. In addition to short term predictions, seasonal forecasts have the potential to realise higher benefits through more optimal and consistent decisions. Their operational use however, remains a challenge due to uncertainties posed by the initial hydrologic conditions (e.g. soil moisture, groundwater levels) and seasonal climate forcings (mainly forecasts of precipitation and temperature), leading to a decrease in skill with increasing lead times. Here we present a stakeholder-led case study for the Thames catchment (UK), currently being undertaken as part of the H2020 IMPREX project. The winter of 2013-14 was the wettest on record in the UK; driven by 12 major Atlantic depressions, the Thames catchment was subject to compound (concurrent) flooding from fluvial and groundwater sources. Focusing on the 2013-14 floods, this study aims to see whether increased skill in meteorological input translates through to more accurate forecasting of compound flood events at seasonal timescales in the Thames catchment. An earlier analysis of the ECMWF System 4 (S4) seasonal meteorological forecasts revealed that it did not skilfully forecast the extreme event of winter 2013-14. This motivated the implementation of an atmospheric experiment by the ECMWF to force the S4 to more accurately represent the low-pressure weather conditions prevailing in winter 2013-14 [1]. Here, we used both the standard and the "improved" S4 seasonal meteorological forecasts to force the EFAS (European Flood Awareness System) LISFLOOD hydrological model. Both hydrological forecasts were started on the 1st of November 2013 and run for 4 months of lead time to capture the peak of the 2013-14 flood event. Comparing the seasonal hydrological forecasts produced with both meteorological forcing data will enable us to assess how the improved meteorology translates into skill in the hydrological forecast for this extreme compound event. As primary stakeholders involved in the study, the Environment Agency and Flood Forecasting Centre are responsible for managing flood risk in the UK. For them, the detection of a potential flood signal weeks or months in advance could be of great value in terms of operational practice, decision-making and early warning. [1] Rodwell, M.J., Ferranti, L., Magnusson, L., Weisheimer, A., Rabier, F. & Richardson, D. (2015) Diagnosis of northern hemispheric regime behaviour during winter 2013/14. ECMWF Technical Memoranda 769.

Machine Learning Classification of Heterogeneous Fields to Estimate Physical Responses

NASA Astrophysics Data System (ADS)

McKenna, S. A.; Akhriev, A.; Alzate, C.; Zhuk, S.

2017-12-01

The promise of machine learning to enhance physics-based simulation is examined here using the transient pressure response to a pumping well in a heterogeneous aquifer. 10,000 random fields of log10 hydraulic conductivity (K) are created and conditioned on a single K measurement at the pumping well. Each K-field is used as input to a forward simulation of drawdown (pressure decline). The differential equations governing groundwater flow to the well serve as a non-linear transform of the input K-field to an output drawdown field. The results are stored and the data set is split into training and testing sets for classification. A Euclidean distance measure between any two fields is calculated and the resulting distances between all pairs of fields define a similarity matrix. Similarity matrices are calculated for both input K-fields and the resulting drawdown fields at the end of the simulation. The similarity matrices are then used as input to spectral clustering to determine groupings of similar input and output fields. Additionally, the similarity matrix is used as input to multi-dimensional scaling to visualize the clustering of fields in lower dimensional spaces. We examine the ability to cluster both input K-fields and output drawdown fields separately with the goal of identifying K-fields that create similar drawdowns and, conversely, given a set of simulated drawdown fields, identify meaningful clusters of input K-fields. Feature extraction based on statistical parametric mapping provides insight into what features of the fields drive the classification results. The final goal is to successfully classify input K-fields into the correct output class, and also, given an output drawdown field, be able to infer the correct class of input field that created it.

Yield estimation of corn based on multitemporal LANDSAT-TM data as input for an agrometeorological model

NASA Astrophysics Data System (ADS)

Bach, Heike

1998-07-01

In order to test remote sensing data with advanced yield formation models for accuracy and timeliness of yield estimation of corn, a project was conducted for the State Ministry for Rural Environment, Food, and Forestry of Baden-Württemberg (Germany). This project was carried out during the course of the `Special Yield Estimation', a regular procedure conducted for the European Union, to more accurately estimate agricultural yield. The methodology employed uses field-based plant parameter estimation from atmospherically corrected multitemporal/multispectral LANDSAT-TM data. An agrometeorological plant-production-model is used for yield prediction. Based solely on four LANDSAT-derived estimates (between May and August) and daily meteorological data, the grain yield of corn fields was determined for 1995. The modelled yields were compared with results gathered independently within the Special Yield Estimation for 23 test fields in the upper Rhine valley. The agreement between LANDSAT-based estimates (six weeks before harvest) and Special Yield Estimation (at harvest) shows a relative error of 2.3%. The comparison of the results for single fields shows that six weeks before harvest, the grain yield of corn was estimated with a mean relative accuracy of 13% using satellite information. The presented methodology can be transferred to other crops and geographical regions. For future applications hyperspectral sensors show great potential to further enhance the results for yield prediction with remote sensing.

Gravitational Signal of Mass Redistribution Due to Interannual Meteorological Oscillations in Atmosphere and Ocean

NASA Technical Reports Server (NTRS)

Chao, B. F.; Au, A. Y.; Johnson, T.; Smith, David E. (Technical Monitor)

2001-01-01

Interannual meteorological oscillations (ENSO, QBO, NAO, etc.) have demonstrable influences on Earth's rotation. Here we study their effects on global gravitational field, whose temporal variations are being studied using SLR (satellite laser ranging) data and in anticipation of the new space mission GRACE. The meteorological oscillation modes are identified using the EOF (empirical orthogonal function)/PC (principal component) decomposition of surface fields (in which we take care of issues associated with the area-weighting and non-zero mean). We examine two fields, one for the global surface pressure field for the atmosphere obtained from the NCEP reanalysis (for the past 40 years), one for the surface topography field for the ocean from the Topex/Poseidon (T/P) data (for the past 8 years). We use monthly maps, and remove the mean-monthly ("climatology") values from each grid point, hence focusing only on non-seasonal signals. The T/P data were first subject to a steric correction where the steric contribution to the ocean surface topography was removed according to output of the numerical POCM model. The respective atmospheric and oceanic contributions to the gravitational variation, in terms of harmonic Stokes coefficients, are then combined mode-by-mode. Since the T/P data already contain the oceanic response to overlying atmospheric pressure, no regards to the inverted-barometer behavior for the ocean need be considered. Results for the lowest-degree Stokes coefficients can then be compared with space geodetic observations including the Earth's rotation and the SLR data mentioned above, to identify the importance of each meteorological oscillations in gravitational variation signals.

Proceedings of the NASA Workshop on Flight Deck Centered Parallel Runway Approaches in Instrument Meteorological Conditions

NASA Technical Reports Server (NTRS)

Waller, Marvin C. (Editor); Scanlon, Charles H. (Editor)

1996-01-01

A Government and Industry workshop on Flight-Deck-Centered Parallel Runway Approaches in Instrument Meteorological Conditions (IMC) was conducted October 29, 1996 at the NASA Langley Research Center. This document contains the slides and records of the proceedings of the workshop. The purpose of the workshop was to disclose to the National airspace community the status of ongoing NASA R&D to address the closely spaced parallel runway problem in IMC and to seek advice and input on direction of future work to assure an optimized research approach. The workshop also included a description of a Paired Approach Concept which is being studied at United Airlines for application at the San Francisco International Airport.

An Introduction to Air Chemistry.

ERIC Educational Resources Information Center

Butcher, Samuel S.; Charlson, Robert J.

Designed for those with no previous experience in the field, this book synthesizes the areas of chemistry and meteorology required to bring into focus some of the complex problems associated with the atmospheric environment. Subject matter moves from a review of the relevant chemical and meteorological principles to a discussion of the general…

Investigating the Impact on Modeled Ozone Concentrations Using Meteorological Fields From WRF With and Updated Four-Dimensional Data Assimilation Approach”

EPA Science Inventory

The four-dimensional data assimilation (FDDA) technique in the Weather Research and Forecasting (WRF) meteorological model has recently undergone an important update from the original version. Previous evaluation results have demonstrated that the updated FDDA approach in WRF pr...

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...

Pattern recognition of satellite cloud imagery for improved weather prediction

NASA Technical Reports Server (NTRS)

Gautier, Catherine; Somerville, Richard C. J.; Volfson, Leonid B.

1986-01-01

The major accomplishment was the successful development of a method for extracting time derivative information from geostationary meteorological satellite imagery. This research is a proof-of-concept study which demonstrates the feasibility of using pattern recognition techniques and a statistical cloud classification method to estimate time rate of change of large-scale meteorological fields from remote sensing data. The cloud classification methodology is based on typical shape function analysis of parameter sets characterizing the cloud fields. The three specific technical objectives, all of which were successfully achieved, are as follows: develop and test a cloud classification technique based on pattern recognition methods, suitable for the analysis of visible and infrared geostationary satellite VISSR imagery; develop and test a methodology for intercomparing successive images using the cloud classification technique, so as to obtain estimates of the time rate of change of meteorological fields; and implement this technique in a testbed system incorporating an interactive graphics terminal to determine the feasibility of extracting time derivative information suitable for comparison with numerical weather prediction products.

Potential sources of precipitation in Lake Baikal basin

NASA Astrophysics Data System (ADS)

Shukurov, K. A.; Mokhov, I. I.

2017-11-01

Based on the data of long-term measurements at 23 meteorological stations in the Russian part of the Lake Baikal basin the probabilities of daily precipitation with different intensity and their contribution to the total precipitation are estimated. Using the trajectory model HYSPLIT_4 for each meteorological station for the period 1948-2016 the 10-day backward trajectories of air parcels, the height of these trajectories and distribution of specific humidity along the trajectories are calculated. The average field of power of potential sources of daily precipitation (less than 10 mm) for all meteorological stations in the Russian part of the Lake Baikal basin was obtained using the CWT (concentration weighted trajectory) method. The areas have been identified from which within 10 days water vapor can be transported to the Lake Baikal basin, as well as regions of the most and least powerful potential sources. The fields of the mean height of air parcels trajectories and the mean specific humidity along the trajectories are compared with the field of mean power of potential sources.

Urban Landscape Characterization Using Remote Sensing Data For Input into Air Quality Modeling

NASA Technical Reports Server (NTRS)

Quattrochi, Dale A.; Estes, Maurice G., Jr.; Crosson, William; Khan, Maudood

2005-01-01

The urban landscape is inherently complex and this complexity is not adequately captured in air quality models that are used to assess whether urban areas are in attainment of EPA air quality standards, particularly for ground level ozone. This inadequacy of air quality models to sufficiently respond to the heterogeneous nature of the urban landscape can impact how well these models predict ozone pollutant levels over metropolitan areas and ultimately, whether cities exceed EPA ozone air quality standards. We are exploring the utility of high-resolution remote sensing data and urban growth projections as improved inputs to meteorological and air quality models focusing on the Atlanta, Georgia metropolitan area as a case study. The National Land Cover Dataset at 30m resolution is being used as the land use/land cover input and aggregated to the 4km scale for the MM5 mesoscale meteorological model and the Community Multiscale Air Quality (CMAQ) modeling schemes. Use of these data have been found to better characterize low density/suburban development as compared with USGS 1 km land use/land cover data that have traditionally been used in modeling. Air quality prediction for future scenarios to 2030 is being facilitated by land use projections using a spatial growth model. Land use projections were developed using the 2030 Regional Transportation Plan developed by the Atlanta Regional Commission. This allows the State Environmental Protection agency to evaluate how these transportation plans will affect future air quality.

Transport of a Power Plant Tracer Plume over Grand Canyon National Park.

NASA Astrophysics Data System (ADS)

Chen, Jun; Bornstein, Robert; Lindsey, Charles G.

1999-08-01

Meteorological and air-quality data, as well as surface tracer concentration values, were collected during 1990 to assess the impacts of Navajo Generating Station (NGS) emissions on Grand Canyon National Park (GCNP) air quality. These data have been used in the present investigation to determine between direct and indirect transport routes taken by the NGS plume to produce measured high-tracer concentration events at GCNP.The meteorological data were used as input into a three-dimensional mass-consistent wind model, whose output was used as input into a horizontal forward-trajectory model. Calculated polluted air locations were compared with observed surface-tracer concentration values.Results show that complex-terrain features affect local wind-flow patterns during winter in the Grand Canyon area. Local channeling, decoupled canyon winds, and slope and valley flows dominate in the region when synoptic systems are weak. Direct NGS plume transport to GCNP occurs with northeasterly plume-height winds, while indirect transport to the park is caused by wind direction shifts associated with passing synoptic systems. Calculated polluted airmass positions along the modeled streak lines match measured surface-tracer observations in both space and time.

Engineering description of the ascent/descent bet product

NASA Technical Reports Server (NTRS)

Seacord, A. W., II

1986-01-01

The Ascent/Descent output product is produced in the OPIP routine from three files which constitute its input. One of these, OPIP.IN, contains mission specific parameters. Meteorological data, such as atmospheric wind velocities, temperatures, and density, are obtained from the second file, the Corrected Meteorological Data File (METDATA). The third file is the TRJATTDATA file which contains the time-tagged state vectors that combine trajectory information from the Best Estimate of Trajectory (BET) filter, LBRET5, and Best Estimate of Attitude (BEA) derived from IMU telemetry. Each term in the two output data files (BETDATA and the Navigation Block, or NAVBLK) are defined. The description of the BETDATA file includes an outline of the algorithm used to calculate each term. To facilitate describing the algorithms, a nomenclature is defined. The description of the nomenclature includes a definition of the coordinate systems used. The NAVBLK file contains navigation input parameters. Each term in NAVBLK is defined and its source is listed. The production of NAVBLK requires only two computational algorithms. These two algorithms, which compute the terms DELTA and RSUBO, are described. Finally, the distribution of data in the NAVBLK records is listed.

The Langley Parameterized Shortwave Algorithm (LPSA) for Surface Radiation Budget Studies. 1.0

NASA Technical Reports Server (NTRS)

Gupta, Shashi K.; Kratz, David P.; Stackhouse, Paul W., Jr.; Wilber, Anne C.

2001-01-01

An efficient algorithm was developed during the late 1980's and early 1990's by W. F. Staylor at NASA/LaRC for the purpose of deriving shortwave surface radiation budget parameters on a global scale. While the algorithm produced results in good agreement with observations, the lack of proper documentation resulted in a weak acceptance by the science community. The primary purpose of this report is to develop detailed documentation of the algorithm. In the process, the algorithm was modified whenever discrepancies were found between the algorithm and its referenced literature sources. In some instances, assumptions made in the algorithm could not be justified and were replaced with those that were justifiable. The algorithm uses satellite and operational meteorological data for inputs. Most of the original data sources have been replaced by more recent, higher quality data sources, and fluxes are now computed on a higher spatial resolution. Many more changes to the basic radiation scheme and meteorological inputs have been proposed to improve the algorithm and make the product more useful for new research projects. Because of the many changes already in place and more planned for the future, the algorithm has been renamed the Langley Parameterized Shortwave Algorithm (LPSA).

Study on the medical meteorological forecast of the number of hypertension inpatient based on SVR

NASA Astrophysics Data System (ADS)

Zhai, Guangyu; Chai, Guorong; Zhang, Haifeng

2017-06-01

The purpose of this study is to build a hypertension prediction model by discussing the meteorological factors for hypertension incidence. The research method is selecting the standard data of relative humidity, air temperature, visibility, wind speed and air pressure of Lanzhou from 2010 to 2012(calculating the maximum, minimum and average value with 5 days as a unit ) as the input variables of Support Vector Regression(SVR) and the standard data of hypertension incidence of the same period as the output dependent variables to obtain the optimal prediction parameters by cross validation algorithm, then by SVR algorithm learning and training, a SVR forecast model for hypertension incidence is built. The result shows that the hypertension prediction model is composed of 15 input independent variables, the training accuracy is 0.005, the final error is 0.0026389. The forecast accuracy based on SVR model is 97.1429%, which is higher than statistical forecast equation and neural network prediction method. It is concluded that SVR model provides a new method for hypertension prediction with its simple calculation, small error as well as higher historical sample fitting and Independent sample forecast capability.

Po-Basin Atmospheric Composition during the Pegasos Field Campaign (summer 2012): Evaluation of ninfa/aodeM Simulation with In-Situ e Remote Sensing Observations

NASA Astrophysics Data System (ADS)

Landi, Tony C.; Bonafe, Giovanni; Stortini, Michele; Minguzzi, Enrico; Cristofanelli, Paolo; Marinoni, Angela; Giulianelli, Lara; Sandrini, Silvia; Gilardoni, Stefania; Rinaldi, Matteo; Ricciardelli, Isabella

2014-05-01

Within the EU project PEGASOS one of three field campaigns took place in the Po Valley during the summer of 2012. Photochemistry, particle formation, and particle properties related to diurnal evolution of the PBL were investigated through both in-situ and airborne measurements on board a Zeppelin NT air ship. In addition, 3-D air quality modeling systems were implemented over the Po valley for the summer 2012 to better characterize the atmospheric conditions, in terms of meteorological parameters and chemical composition. In this work, we present a comparison between atmospheric composition simulations carried out by the modeling system NINFA/AODEM with measurements performed during the PEGASOS field campaign for the period 13 June - 12 July 2012. NINFA (Stortini et al., 2007) is based on the chemical transport model CHIMERE (Bessagnet et al., 2008), driven by COSMO-I7, the meteorological Italian Limited Area Model, (Steppeler et al., 2003). Boundary conditions are provided by Prev'air data (www.prevair.org), and emission data input are based on regional, national and European inventory. Besides, a post-processing tool for aerosol optical properties calculation, called AODEM (Landi T. C. 2013) was implemented. Thus, predictions of Aerosol Optical Depth and aerosol extinction coefficient were also used for model comparison to vertical-resolved observations. For this experiment, NINFA/AODEM has been also evaluated by using measurements of size-segregated aerosol samples, number particles concentration and aerosol optical properties collected on hourly basis at the 3 different sampling sites representative of urban background (Bologna), rural background (San Pietro Capofiume) and remote high altitude station (Monte Cimone 2165 ma.s.l.). ). In addition, we focused on new particles formations events and long range transports from Northern Africa observed during the field campaign. References Bessagnet, Bertrand, Laurent Menut, Gabriele Curci, Alma Hodzic, Bruno Guillaume, Catherine Liousse, Sophie Moukhtar, Betty Pun, Christian Seigneur, and Michaël Schulz (2008). "Regional modeling of carbonaceous aerosols over europe-focus on secondary organic aerosols." Journal of Atmospheric Chemistry 61, no. 3 : 175-202. Landi Tony Christian (2013). AODEM: A post-processing tool for aerosol optical properties calculation in the Chemical Transport Models. Book published by LAP - Lambert Academic Publishing ISBN: 978-3-659-31802-3. Steppeler, J., G. Doms, U. Schättler, H. W. Bitzer, A. Gassmann, U. Damrath, and G. Gregoric (2003). "Meso-gamma scale forecasts using the nonhydrostatic model LM." Meteorology and Atmospheric Physics 82, no. 1-4 : 75-96. M. Stortini, M. Deserti, G. Bonafè, and E. Minguzzi. Long-term simulation and validation of ozone and aerosol in the Po Valley. In C.Borrego and E.Renner, editors, Developments in Environmental Sciences, volume 6, pages 768-770. Elsevier, 2007.

Meteorological Instrumentation and Measurements Open Resource Training Modules for Undergraduate and Graduate Education

NASA Astrophysics Data System (ADS)

Rockwell, A.; Clark, R. D.; Stevermer, A.

2017-12-01

The National Center for Atmospheric Research Earth Observing Laboratory, Millersville University and The COMET Program are collaborating to produce a series of nine online modules on the the topic of meteorological instrumentation and measurements. These interactive, multimedia educational modules can be integrated into undergraduate and graduate meteorology courses on instrumentation, measurement science, and observing systems to supplement traditional pedagogies and enhance blended instruction. These freely available and open-source training tools are designed to supplement traditional pedagogies and enhance blended instruction. Three of the modules are now available and address the theory and application of Instrument Performance Characteristics, Meteorological Temperature Instrumentation and Measurements, and Meteorological Pressure Instrumentation and Measurements. The content of these modules is of the highest caliber as it has been developed by scientists and engineers who are at the forefront of the field of observational science. Communicating the availability of these unique and influential educational resources with the community is of high priority. These modules will have a profound effect on the atmospheric observational sciences community by fulfilling a need for contemporary, interactive, multimedia guided education and training modules integrating the latest instructional design and assessment tools in observational science. Thousands of undergraduate and graduate students will benefit, while course instructors will value a set of high quality modules to use as supplements to their courses. The modules can serve as an alternative to observational research training and fill the void between field projects or assist those schools that lack the resources to stage a field- or laboratory-based instrumentation experience.

Usage of NASA's Near Real-Time Solar and Meteorological Data for Monitoring Building Energy Systems Using RETScreen International's Performance Analysis Module

NASA Technical Reports Server (NTRS)

Stackhouse, Paul W., Jr.; Charles, Robert W.; Chandler, William S.; Hoell, James M.; Westberg, David; Zhang, Taiping; Ziegler, Urban; Leng, Gregory J.; Meloche, Nathalie; Bourque, Kevin

2012-01-01

This paper describes building energy system production and usage monitoring using examples from the new RETScreen Performance Analysis Module, called RETScreen Plus. The module uses daily meteorological (i.e., temperature, humidity, wind and solar, etc.) over a period of time to derive a building system function that is used to monitor building performance. The new module can also be used to target building systems with enhanced technologies. If daily ambient meteorological and solar information are not available, these are obtained over the internet from NASA's near-term data products that provide global meteorological and solar information within 3-6 days of real-time. The accuracy of the NASA data are shown to be excellent for this purpose enabling RETScreen Plus to easily detect changes in the system function and efficiency. This is shown by several examples, one of which is a new building at the NASA Langley Research Center that uses solar panels to provide electrical energy for building energy and excess energy for other uses. The system shows steady performance within the uncertainties of the input data. The other example involves assessing the reduction in energy usage by an apartment building in Sweden before and after an energy efficiency upgrade. In this case, savings up to 16% are shown.

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.

Causes of Interannual Variability over the Southern Hemispheric Tropospheric Ozone Maximum

NASA Technical Reports Server (NTRS)

Liu, Junhua; Rodriguez, Jose M.; Steenrod, Stephen D.; Douglass, Anne R.; Logan, Jennifer A.; Olsen, Mark A.; Wargan, Krzysztog; Ziemke, Jerald R.

2017-01-01

We examine the relative contribution of processes controlling the interannual variability (IAV) of tropospheric ozone over four sub-regions of the southern hemispheric tropospheric ozone maximum (SHTOM) over a 20-year period. Our study is based on hindcast simulations from the National Aeronautics and Space Administration Global Modeling Initiative chemistry transport model (NASA GMI-CTM) of tropospheric and stratospheric chemistry, driven by assimilated Modern Era Retrospective Analysis for Research and Applications (MERRA) meteorological fields. Our analysis shows that over SHTOM region, the IAV of the stratospheric contribution is the most important factor driving the IAV of upper tropospheric ozone (270 hectopascals), where ozone has a strong radiative effect. Over the South Atlantic region, the contribution from surface emissions to the IAV of ozone exceeds that from stratospheric input at and below 430 hectopascals. Over the South Indian Ocean, the IAV of stratospheric ozone makes the largest contribution to the IAV of ozone with little or no influence from surface emissions at 270 and 430 hectopascals in austral winter. Over the tropical South Atlantic region, the contribution from IAV of stratospheric input dominates in austral winter at 270 hectopascals and drops to less than half but is still significant at 430 hectopascals. Emission contributions are not significant at these two levels. The IAV of lightning over this region also contributes to the IAV of ozone in September and December. Over the tropical southeastern Pacific, the contribution of the IAV of stratospheric input is significant at 270 and 430 hectopascals in austral winter, and emissions have little influence.

Causes of interannual variability over the southern hemispheric tropospheric ozone maximum

NASA Astrophysics Data System (ADS)

Liu, Junhua; Rodriguez, Jose M.; Steenrod, Stephen D.; Douglass, Anne R.; Logan, Jennifer A.; Olsen, Mark A.; Wargan, Krzysztof; Ziemke, Jerald R.

2017-03-01

We examine the relative contribution of processes controlling the interannual variability (IAV) of tropospheric ozone over four sub-regions of the southern hemispheric tropospheric ozone maximum (SHTOM) over a 20-year period. Our study is based on hindcast simulations from the National Aeronautics and Space Administration Global Modeling Initiative chemistry transport model (NASA GMI-CTM) of tropospheric and stratospheric chemistry, driven by assimilated Modern Era Retrospective Analysis for Research and Applications (MERRA) meteorological fields. Our analysis shows that over SHTOM region, the IAV of the stratospheric contribution is the most important factor driving the IAV of upper tropospheric ozone (270 hPa), where ozone has a strong radiative effect. Over the South Atlantic region, the contribution from surface emissions to the IAV of ozone exceeds that from stratospheric input at and below 430 hPa. Over the South Indian Ocean, the IAV of stratospheric ozone makes the largest contribution to the IAV of ozone with little or no influence from surface emissions at 270 and 430 hPa in austral winter. Over the tropical South Atlantic region, the contribution from IAV of stratospheric input dominates in austral winter at 270 hPa and drops to less than half but is still significant at 430 hPa. Emission contributions are not significant at these two levels. The IAV of lightning over this region also contributes to the IAV of ozone in September and December. Over the tropical southeastern Pacific, the contribution of the IAV of stratospheric input is significant at 270 and 430 hPa in austral winter, and emissions have little influence.

Spatial clustering and meteorological drivers of summer ozone in Europe

NASA Astrophysics Data System (ADS)

Carro-Calvo, Leopoldo; Ordóñez, Carlos; García-Herrera, Ricardo; Schnell, Jordan L.

2017-10-01

We have applied the k-means clustering technique on a maximum daily 8-h running average near-surface ozone (MDA8 O3) gridded dataset over Europe at 1° × 1° resolution for summer 1998-2012. This has resulted in a spatial division of nine regions where ozone presents coherent spatiotemporal patterns. The role of meteorology in the variability of ozone at different time scales has been investigated by using daily meteorological fields from the NCEP-NCAR meteorological reanalysis. In the five regions of central-southern Europe ozone extremes (exceedances of the summer 95th percentile) occur mostly under anticyclonic circulation or weak sea level pressure gradients which trigger elevated temperatures and the recirculation of air masses. In the four northern regions extremes are associated with high-latitude anticyclones that divert the typical westerly flow at those latitudes and cause the advection of aged air masses from the south. The impact of meteorology on the day-to-day variability of ozone has been assessed by means of two different types of multiple linear models. These include as predictors meteorological fields averaged within the regions (;region-based; approach) or synoptic indices indicating the degree of resemblance between the daily meteorological fields over a large domain (25°-70° N, 35° W - 35° E) and their corresponding composites for extreme ozone days (;index-based; approach). With the first approach, a reduced set of variables, always including daily maximum temperature within the region, explains 47-66% of the variability (adjusted R2) in central-southern Europe, while more complex models are needed to explain 27-49% of the variability in the northern regions. The index-based approach yields better results for the regions of northern Europe, with adjusted R2 = 40-57%. Finally, both methodologies have also been applied to reproduce the interannual variability of ozone, with the best models explaining 66-88% of the variance in central-southern Europe and 45-66% in the north. Thus, the regionalisation carried out in this work has allowed establishing clear distinctions between the meteorological drivers of ozone in northern Europe and in the rest of the continent. These drivers are consistent across the different time scales examined (extremes, day-to-day and interannual), which gives confidence in the robustness of the results.

GPS Water Vapor Tomography: First results from the ESCOMPTE Field Experiment

NASA Astrophysics Data System (ADS)

Masson, F.; Champollion, C.; Bouin, M.-N.; Walpersdorf, A.; van Baelen, J.; Doerflinger, E.; Bock, O.

2003-04-01

We develop a tomographic software to model the spatial distribution of the tropospheric water vapor from GPS data. First we present simulations based on a real GPS station distribution and simple tropospheric models, which prove the potentiality of the method. Second we apply the software to the ESCOMPTE data. During the ESCOMPTE field experiment, a dense network of 17 dual frequency GPS receivers has been operated for two weeks within a 20 km x 20 km area around Marseille (Southern France). The network extends from the sea level to the top of the Etoile chain (~700 m high). The input data are the slant delay values obtained by combining the estimated zenith delay values with the horizontal gradients. The effect of the initial tropospheric water vapor model, the number and thickness of the layers of the model, the a priori model and data covariance and some other parameters will be discussed. Simultaneously water vapor radiometer, solar spectrometer, Raman lidar and radiosondes have been deployed to get a data set usable for comparison with the tomographic inversion results and validation of the method. Comparison with meteorological models (MesoNH - Meteo-France) will be shown.

A comparison of measured and theoretical predictions for STS ascent and entry sonic booms

NASA Technical Reports Server (NTRS)

Garcia, F., Jr.; Jones, J. H.; Henderson, H. R.

1983-01-01

Sonic boom measurements have been obtained during the flights of STS-1 through 5. During STS-1, 2, and 4, entry sonic boom measurements were obtained and ascent measurements were made on STS-5. The objectives of this measurement program were (1) to define the sonic boom characteristics of the Space Transportation System (STS), (2) provide a realistic assessment of the validity of xisting theoretical prediction techniques, and (3) establish a level of confidence for predicting future STS configuration sonic boom environments. Detail evaluation and reporting of the results of this program are in progress. This paper will address only the significant results, mainly those data obtained during the entry of STS-1 at Edwards Air Force Base (EAFB), and the ascent of STS-5 from Kennedy Space Center (KSC). The theoretical prediction technique employed in this analysis is the so called Thomas Program. This prediction technique is a semi-empirical method that required definition of the near field signatures, detailed trajectory characteristics, and the prevailing meteorological characteristics as an input. This analytical procedure then extrapolates the near field signatures from the flight altitude to an altitude consistent with each measurement location.

The role of global cloud climatologies in validating numerical models

NASA Technical Reports Server (NTRS)

HARSHVARDHAN

1992-01-01

Global maps of the monthly mean net upward longwave radiation flux at the ocean surface were obtained for April, July, October 1985 and January 1986. These maps were produced by blending information obtained from a combination of general circulation model cloud radiative forcing fields, the top of the atmosphere cloud radiative forcing from ERBE and TOVS profiles and sea surface temperature on ISCCP C1 tapes. The fields are compatible with known meteorological regimes of atmospheric water vapor content and cloudiness. There is a vast area of high net upward longwave radiation flux (greater than 80/sq Wm) in the eastern Pacific Ocean throughout most of the year. Areas of low net upward longwave radiation flux ((less than 40/sq Wm) are the tropical convective regions and extra tropical regions that tend to have persistent low cloud cover.The technique used relies on General Circulation Model simulations and so is subject to some of the uncertainties associated with the model. However, all input information regarding temperature, moisture, and cloud cover is from satellite data having near global coverage. This feature of the procedure alone warrants its consideration for further use in compiling global maps of longwave radiation.

Grid-cell-based crop water accounting for the famine early warning system

USGS Publications Warehouse

Verdin, J.; Klaver, R.

2002-01-01

Rainfall monitoring is a regular activity of food security analysts for sub-Saharan Africa due to the potentially disastrous impact of drought. Crop water accounting schemes are used to track rainfall timing and amounts relative to phenological requirements, to infer water limitation impacts on yield. Unfortunately, many rain gauge reports are available only after significant delays, and the gauge locations leave large gaps in coverage. As an alternative, a grid-cell-based formulation for the water requirement satisfaction index (WRSI) was tested for maize in Southern Africa. Grids of input variables were obtained from remote sensing estimates of rainfall, meteorological models, and digital soil maps. The spatial WRSI was computed for the 1996–97 and 1997–98 growing seasons. Maize yields were estimated by regression and compared with a limited number of reports from the field for the 1996–97 season in Zimbabwe. Agreement at a useful level (r = 0·80) was observed. This is comparable to results from traditional analysis with station data. The findings demonstrate the complementary role that remote sensing, modelling, and geospatial analysis can play in an era when field data collection in sub-Saharan Africa is suffering an unfortunate decline.

FACILITATING ADVANCED URBAN METEOROLOGY AND AIR QUALITY MODELING CAPABILITIES WITH HIGH RESOLUTION URBAN DATABASE AND ACCESS PORTAL TOOLS

EPA Science Inventory

Information of urban morphological features at high resolution is needed to properly model and characterize the meteorological and air quality fields in urban areas. We describe a new project called National Urban Database with Access Portal Tool, (NUDAPT) that addresses this nee...

Modeling of microclimatic characteristics of highland area

NASA Astrophysics Data System (ADS)

Sitdikova, Iuliia; Rusin, Igor

2013-04-01

Microclimatic characteristics of highlands may vary considerably over distances of a few meters depending on slope and aspect. There is a problem of estimation of components of surface energy balance based on observation of single stations for description of microclimate highlands. The aim of this paper is to develop a method that would restore microclimatic characteristics of terrain, based on observations of the single station, by physical extrapolation. The input parameters to obtain the microclimatic characteristics are as follows: air temperature, relative humidity, and wind speed on two vertical levels, air pressure, surface temperature, direct and diffused solar radiation and surface albedo. The recent version of the Meteorological Radiation Model (MRM) has been used to calculate a solar radiation over the area and to estimate an influence of cloudiness amounts. The height, slope and aspect were accounted at each point with using a digital elevation model. Have been supposed that air temperature and specific humidity vary with altitude only. Net radiation was calculated at all points of the area. Supposed that the difference between the surface temperature and the air temperature is a linear function of net radiation. The empirical coefficient, which depends on wind speed with adjustment of given area. Latent and sensible fluxes are calculated by using the modified Bowen ratio, which varies on the area. Method was tested on field research in Krasnodar region (RF). The meteorological observations were made every three hour on actinometric and gradient sites. The editional gradient site with different orientation of the slope was organized from 400 meters of the main site. Topographic survey of area was made 1x1,3 km in size for a digital elevation model constructing. At all points of the area of radiation and heat balance were calculated. The results of researches are the maps of surface temperature, net radiation, latent and sensible fluxes. The calculations showed that the average value of components of heat balance by area differ significantly from the data observed on meteorological station.

Meteorological support to the West German-United States Barium Ion Cloud Project.

NASA Technical Reports Server (NTRS)

Westfall, R. R.; Chamberlain, L. W.

1972-01-01

The objective of the Barium Ion Cloud Project was to study a barium ionized cloud released at an altitude of 5 earth radii. Accurate forecasting of weather conditions to prevail during the experiment period was critical to the project success. Good seeing conditions were required at all optical sites during the experiment. All meteorological support was the responsibility of the National Weather Service at Wallops Station, Virginia. Preliminary results confirm the scientists' theories of the magnetic fields and the existence of electric fields in the magnetosphere.

Recommended Values of Meteorological Factors to Be Considered in the Design of Aircraft Ice-Prevention Equipment

NASA Technical Reports Server (NTRS)

Jones, Alun R; Lewis, William

1949-01-01

Meteorological conditions conducive to aircraft icing are arranged in four classifications: three are associated with cloud structure and the fourth with freezing rain. The range of possible meteorological factors for each classification is discussed and specific values recommended for consideration in the design of ice-prevention equipment for aircraft are selected and tabulated. The values selected are based upon a study of the available observational data and theoretical considerations where observations are lacking. Recommendations for future research in the field are presented.

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.

Impact of input field characteristics on vibrational femtosecond coherent anti-Stokes Raman scattering thermometry.

PubMed

Yang, Chao-Bo; He, Ping; Escofet-Martin, David; Peng, Jiang-Bo; Fan, Rong-Wei; Yu, Xin; Dunn-Rankin, Derek

2018-01-10

In this paper, three ultrashort-pulse coherent anti-Stokes Raman scattering (CARS) thermometry approaches are summarized with a theoretical time-domain model. The difference between the approaches can be attributed to variations in the input field characteristics of the time-domain model. That is, all three approaches of ultrashort-pulse (CARS) thermometry can be simulated with the unified model by only changing the input fields features. As a specific example, the hybrid femtosecond/picosecond CARS is assessed for its use in combustion flow diagnostics; thus, the examination of the input field has an impact on thermometry focuses on vibrational hybrid femtosecond/picosecond CARS. Beginning with the general model of ultrashort-pulse CARS, the spectra with different input field parameters are simulated. To analyze the temperature measurement error brought by the input field impacts, the spectra are fitted and compared to fits, with the model neglecting the influence introduced by the input fields. The results demonstrate that, however the input pulses are depicted, temperature errors still would be introduced during an experiment. With proper field characterization, however, the significance of the error can be reduced.

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

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.

Users' instructions for the NASA/MSFC cloud-rise preprocessor program, version 6, and the NASA/MSFC multilayer diffusion program, version 6: Research version for Univac 1108 system

NASA Technical Reports Server (NTRS)

Bjorklund, J. R.

1978-01-01

The cloud-rise preprocessor and multilayer diffusion computer programs were used by NASA in predicting concentrations and dosages downwind from normal and abnormal launches of rocket vehicles. These programs incorporated: (1) the latest data for the heat content and chemistry of rocket exhaust clouds; (2) provision for the automated calculation of surface water pH due to deposition of HCl from precipitation scavenging; (3) provision for automated calculation of concentration and dosage parameters at any level within the vertical grounds for which meteorological inputs have been specified; and (4) provision for execution of multiple cases of meteorological data. Procedures used to automatically calculate wind direction shear in a layer were updated.

Assessing the impacts of climate change in Mediterranean catchments under conditions of data scarcity

NASA Astrophysics Data System (ADS)

Meyer, Swen; Ludwig, Ralf

2013-04-01

According to current climate projections, Mediterranean countries are at high risk for an even pronounced susceptibility to changes in the hydrological budget and extremes. While there is scientific consensus that climate induced changes on the hydrology of Mediterranean regions are presently occurring and are projected to amplify in the future, very little knowledge is available about the quantification of these changes, which is hampered by a lack of suitable and cost effective hydrological monitoring and modeling systems. The European FP7-project CLIMB is aiming to analyze climate induced changes on the hydrology of the Mediterranean Basins by investigating 7 test sites located in the countries Italy, France, Turkey, Tunisia, Gaza and Egypt. CLIMB employs a combination of novel geophysical field monitoring concepts, remote sensing techniques and integrated hydrologic modeling to improve process descriptions and understanding and to quantify existing uncertainties in climate change impact analysis. The Rio Mannu Basin, located in Sardinia; Italy, is one test site of the CLIMB project. The catchment has a size of 472.5 km2, it ranges from 62 to 946 meters in elevation, at mean annual temperatures of 16°C and precipitation of about 700 mm, the annual runoff volume is about 200 mm. The physically based Water Simulation Model WaSiM Vers. 2 (Schulla & Jasper (1999)) was setup to model current and projected future hydrological conditions. The availability of measured meteorological and hydrological data is poor as common to many Mediterranean catchments. The lack of available measured input data hampers the calibration of the model setup and the validation of model outputs. State of the art remote sensing techniques and field measuring techniques were applied to improve the quality of hydrological input parameters. In a field campaign about 250 soil samples were collected and lab-analyzed. Different geostatistical regionalization methods were tested to improve the model setup. The soil parameterization of the model was tested against publically available soil data. Results show a significant improvement of modeled soil moisture outputs. To validate WaSiMs evapotranspiration (ETact) outputs, Landsat TM images were used to calculate the actual monthly mean ETact rates using the triangle method (Jiang and Islam, 1999). Simulated spatial ETact patterns and those derived from remote sensing show a good fit especially for the growing season. WaSiM was driven with the meteorological forcing taken from 4 different ENSEMBLES climate projections for a reference (1971-2000) and a future (2041-2070) times series. Output results were analyzed for climate induced changes on selected hydrological variables. While the climate projections reveal increased precipitation rates in the spring season, first simulation results show an earlier onset and an increased duration of the dry season, imposing an increased irrigation demand and higher vulnerability of agricultural productivity.

Can dust emission mechanisms be determined from field measurements?

NASA Astrophysics Data System (ADS)

Klose, Martina; Webb, Nicholas; Gill, Thomas E.; Van Pelt, Scott; Okin, Gregory

2017-04-01

Field observations are needed to develop and test theories on dust emission for use in dust modeling systems. The dust emission mechanism (aerodynamic entrainment, saltation bombardment, aggregate disintegration) as well as the amount and particle-size distribution of emitted dust may vary under sediment supply- and transport-limited conditions. This variability, which is caused by heterogeneity of the surface and the atmosphere, cannot be fully captured in either field measurements or models. However, uncertainty in dust emission modeling can be reduced through more detailed observational data on the dust emission mechanism itself. To date, most measurements do not provide enough information to allow for a determination of the mechanisms leading to dust emission and often focus on a small variety of soil and atmospheric settings. Additionally, data sets are often not directly comparable due to different measurement setups. As a consequence, the calibration of dust emission schemes has so far relied on a selective set of observations, which leads to an idealization of the emission process in models and thus affects dust budget estimates. Here, we will present results of a study which aims to decipher the dust emission mechanism from field measurements as an input for future model development. Detailed field measurements are conducted, which allow for a comparison of dust emission for different surface and atmospheric conditions. Measurements include monitoring of the surface, loose erodible material, transported sediment, and meteorological data, and are conducted in different environmental settings in the southwestern United States. Based on the field measurements, a method is developed to differentiate between the different dust emission mechanisms.

COST Action ES1206: Advanced GNSS Tropospheric Products for Monitoring Severe Weather Events and Climate (GNSS4SWEC)

NASA Astrophysics Data System (ADS)

Jones, Jonathan; Guerova, Guergana; Dousa, Jan; Dick, Galina; de Haan, Siebren; Pottiaux, Eric; Bock, Olivier; Pacione, Rosa

2017-04-01

GNSS is a well established atmospheric observing technique which can accurately sense atmospheric water vapour, the most abundant greenhouse gas, accounting for up to 70% of atmospheric warming. Water vapour is typically under-sampled in modern operational meteorological observing systems and obtaining and exploiting additional high-quality humidity observations is essential to improve weather forecasting and climate monitoring. COST Action ES1206 is a 4-year project, running from 2013 to 2017, which is coordinating the research activities and improved capabilities from concurrent developments in the GNSS, meteorological and climate communities. For the first time, the synergy of multi-GNSS constellations is used to develop new, more advanced tropospheric products, exploiting the full potential of multi-GNSS on a wide range of temporal and spatial scales - from real-time products monitoring and forecasting severe weather, to the highest quality post-processed products suitable for climate research. The Action also promotes the use of meteorological data as an input to real-time GNSS services and is stimulating the transfer of knowledge and data throughout Europe and beyond.

Weathering the empire: meteorological research in the early British Straits Settlements.

PubMed

Williamson, Fiona

2015-09-01

This article explores meteorological interest and experimentation in the early history of the Straits Settlements. It centres on the establishment of an observatory in 1840s Singapore and examines the channels that linked the observatory to a global community of scientists, colonial officers and a reading public. It will argue that, although the value of overseas meteorological investigation was recognized by the British government, investment was piecemeal and progress in the field often relied on the commitment and enthusiasm of individuals. In the Straits Settlements, as elsewhere, these individuals were drawn from military or medical backgrounds, rather than trained as dedicated scientists. Despite this, meteorology was increasingly recognized as of fundamental importance to imperial interests. Thus this article connects meteorology with the history of science and empire more fully and examines how research undertaken in British dependencies is revealing of the operation of transnational networks in the exchange of scientific knowledge.

Sulfate and Pb-210 Simulated in a Global Model Using Assimilated Meteorological Fields

NASA Technical Reports Server (NTRS)

Chin, Mian; Rood, Richard; Lin, S.-J.; Jacob, Daniel; Muller, Jean-Francois

1999-01-01

This report presents the results of distributions of tropospheric sulfate, Pb-210 and their precursors from a global 3-D model. This model is driven by assimilated meteorological fields generated by the Goddard Data Assimilation Office. Model results are compared with observations from surface sites and from multiplatform field campaigns of Pacific Exploratory Missions (PEM) and Advanced Composition Explorer (ACE). The model generally captures the seasonal variation of sulfate at the surface sites, and reproduces well the short-term in-situ observations. We will discuss the roles of various processes contributing to the sulfate levels in the troposphere, and the roles of sulfate aerosol in regional and global radiative forcing.

Mesoscale atmospheric modeling for emergency response

NASA Astrophysics Data System (ADS)

Osteen, B. L.; Fast, J. D.

Atmospheric transport models for emergency response have traditionally utilized meteorological fields interpolated from sparse data to predict contaminant transport. Often these fields are adjusted to satisfy constraints derived from the governing equations of geophysical fluid dynamics, e.g. mass continuity. Gaussian concentration distributions or stochastic models are then used to represent turbulent diffusion of a contaminant in the diagnosed meteorological fields. The popularity of these models derives from their relative simplicity, ability to make reasonable short-term predictions, and, most important, execution speed. The ability to generate a transport prediction for an accidental release from the Savannah River Site in a time frame which will allow protective action to be taken is essential in an emergency response operation.

Thundercloud electrification models in atmospheric electricity and meteorology

NASA Technical Reports Server (NTRS)

Parker, L. W.

1980-01-01

A survey is presented of presently-available theoretical models. The models are classified into three main groups: (1) convection models, (2) precipitation models, and (3) general models. The strengths and weaknesses of the models, their dimensionalities and degrees of sophistication, the nature of their inputs and outputs, and the various specific charging mechanisms treated by them, are considered. In results obtained to date, the convection models predict no significant electrification enhancement based on conductivity gradients and convection alone, with the assumed air circulation patterns. Results of the precipitation models show that the initial electrification can occur rapidly and stably through noninductive collision mechanisms involving ice, and breakdown-strength electric fields can relatively easily be achieved subsequently through the collisional-inductive mechanism. A critical difficulty of the collision mechanisms is imprecise knowledge of relaxation times versus contact times, which can easily lead to overestimates of electrification. The general model results tend to support those of the precipitation models in emphasizing the high potential effectiveness of the collisional-inductive mechanism.

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

Evaluation and prediction of solar radiation for energy management based on neural networks

NASA Astrophysics Data System (ADS)

Aldoshina, O. V.; Van Tai, Dinh

2017-08-01

Currently, there is a high rate of distribution of renewable energy sources and distributed power generation based on intelligent networks; therefore, meteorological forecasts are particularly useful for planning and managing the energy system in order to increase its overall efficiency and productivity. The application of artificial neural networks (ANN) in the field of photovoltaic energy is presented in this article. Implemented in this study, two periodically repeating dynamic ANS, that are the concentration of the time delay of a neural network (CTDNN) and the non-linear autoregression of a network with exogenous inputs of the NAEI, are used in the development of a model for estimating and daily forecasting of solar radiation. ANN show good productivity, as reliable and accurate models of daily solar radiation are obtained. This allows to successfully predict the photovoltaic output power for this installation. The potential of the proposed method for controlling the energy of the electrical network is shown using the example of the application of the NAEI network for predicting the electric load.

Effects of downscaled high-resolution meteorological data on the PSCF identification of emission sources

DOE PAGES

Cheng, Meng -Dawn; Kabela, Erik D.

2016-04-30

The Potential Source Contribution Function (PSCF) model has been successfully used for identifying regions of emission source at a long distance in this study, the PSCF model relies on backward trajectories calculated by the Hybrid Single-Particle Lagrangian Integrated Trajectory (HYSPLIT) model. In this study, we investigated the impacts of grid resolution and Planetary Boundary Layer (PBL) parameterization (e.g., turbulent transport of pollutants) on the PSCF analysis. The Mellor-Yamada-Janjic (MYJ) and Yonsei University (YUS) parameterization schemes were selected to model the turbulent transport in the PBL within the Weather Research and Forecasting (WRF version 3.6) model. Two separate domain grid sizesmore » (83 and 27 km) were chosen in the WRF downscaling in generating the wind data for driving the HYSPLIT calculation. The effects of grid size and PBL parameterization are important in incorporating the influ- ence of regional and local meteorological processes such as jet streaks, blocking patterns, Rossby waves, and terrain-induced convection on the transport of pollutants by a wind trajectory. We found high resolution PSCF did discover and locate source areas more precisely than that with lower resolution meteorological inputs. The lack of anticipated improvement could also be because a PBL scheme chosen to produce the WRF data was only a local parameterization and unable to faithfully duplicate the real atmosphere on a global scale. The MYJ scheme was able to replicate PSCF source identification by those using the Reanalysis and discover additional source areas that was not identified by the Reanalysis data. In conclusion, a potential benefit for using high-resolution wind data in the PSCF modeling is that it could discover new source location in addition to those identified by using the Reanalysis data input.« less

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.

Simplified methods for real-time prediction of storm surge uncertainty: The city of Venice case study

NASA Astrophysics Data System (ADS)

Mel, Riccardo; Viero, Daniele Pietro; Carniello, Luca; Defina, Andrea; D'Alpaos, Luigi

2014-09-01

Providing reliable and accurate storm surge forecasts is important for a wide range of problems related to coastal environments. In order to adequately support decision-making processes, it also become increasingly important to be able to estimate the uncertainty associated with the storm surge forecast. The procedure commonly adopted to do this uses the results of a hydrodynamic model forced by a set of different meteorological forecasts; however, this approach requires a considerable, if not prohibitive, computational cost for real-time application. In the present paper we present two simplified methods for estimating the uncertainty affecting storm surge prediction with moderate computational effort. In the first approach we use a computationally fast, statistical tidal model instead of a hydrodynamic numerical model to estimate storm surge uncertainty. The second approach is based on the observation that the uncertainty in the sea level forecast mainly stems from the uncertainty affecting the meteorological fields; this has led to the idea to estimate forecast uncertainty via a linear combination of suitable meteorological variances, directly extracted from the meteorological fields. The proposed methods were applied to estimate the uncertainty in the storm surge forecast in the Venice Lagoon. The results clearly show that the uncertainty estimated through a linear combination of suitable meteorological variances nicely matches the one obtained using the deterministic approach and overcomes some intrinsic limitations in the use of a statistical tidal model.

Correlation Between the "seeing FWHM" of Satellite Optical Observations and Meteorological Data at the OWL-Net Station, Mongolia

NASA Astrophysics Data System (ADS)

Bae, Young-Ho; Jo, Jung Hyun; Yim, Hong-Suh; Park, Young-Sik; Park, Sun-Youp; Moon, Hong Kyu; Choi, Young-Jun; Jang, Hyun-Jung; Roh, Dong-Goo; Choi, Jin; Park, Maru; Cho, Sungki; Kim, Myung-Jin; Choi, Eun-Jung; Park, Jang-Hyun

2016-06-01

The correlation between meteorological data collected at the optical wide-field patrol network (OWL-Net) Station No. 1 and the seeing of satellite optical observation data was analyzed. Meteorological data and satellite optical observation data from June 2014 to November 2015 were analyzed. The analyzed meteorological data were the outdoor air temperature, relative humidity, wind speed, and cloud index data, and the analyzed satellite optical observation data were the seeing full-width at half-maximum (FWHM) data. The annual meteorological pattern for Mongolia was analyzed by collecting meteorological data over four seasons, with data collection beginning after the installation and initial set-up of the OWL-Net Station No. 1 in Mongolia. A comparison of the meteorological data and the seeing of the satellite optical observation data showed that the seeing degrades as the wind strength increases and as the cloud cover decreases. This finding is explained by the bias effect, which is caused by the fact that the number of images taken on the less cloudy days was relatively small. The seeing FWHM showed no clear correlation with either temperature or relative humidity.

RAWINPROC: Computer program for decommutating, interpreting, and interpolating Rawinsonde meteorological balloon sounding data

NASA Technical Reports Server (NTRS)

Staffanson, F. L.

1981-01-01

The FORTRAN computer program RAWINPROC accepts output from NASA Wallops computer program METPASS1; and produces input for NASA computer program 3.0.0700 (ECC-PRD). The three parts together form a software system for the completely automatic reduction of standard RAWINSONDE sounding data. RAWINPROC pre-edits the 0.1-second data, including time-of-day, azimuth, elevation, and sonde-modulated tone frequency, condenses the data according to successive dwells of the tone frequency, decommutates the condensed data into the proper channels (temperature, relative humidity, high and low references), determines the running baroswitch contact number and computes the associated pressure altitudes, and interpolates the data appropriate for input to ACC-PRD.

Quantifying the changes in the High Mountain Asia snow hydrology

NASA Astrophysics Data System (ADS)

Yoon, Y.; Kumar, S.; Mocko, D. M.; Rosenberg, R. I.; Kwon, Y.; Forman, B. A.; Zaitchik, B. F.

2017-12-01

The melting of snow and glaciers in the High Mountain Asia (HMA) provides the water needs of approximately 1.3 billion people in the region. Increasing temperatures have large effects on the hydrologic cycle, influencing snowmelt, snowpack, stream flow, and water runoff, which can impact all aspects of water security, such as water allocation, conservation, efficiency and land-use planning. Most mountain regions, however, remain ungauged without in-situ measurement of precipitation or snowpack due to the complex terrain, and thus it is difficult to understand the regional water balance and assess how it might change in the future. In this study, we focus on characterizing the spatiotemporal patterns of snowpack states and fluxes over the last 30+ years (1980 - present) and assessing the relationship between snowmelt and runoff. The Noah land surface model with multi-parameterization options, version 3.6 (Noah-MP.3.6) in the NASA Land Information System (LIS) is used to establish a high resolution (1 km) modeling environment over the HMA. Combining information from satellite observations and the Modern-Era Retrospective analysis for Research and Applications, Version 2 (MERRA-2) is used to provide an effective way to develop spatially and temporally continuous estimates of changes. To improve the spatial representativeness of the precipitation field for modeling at 1km resolution, the input field is downscaled using a stochastic downscaling method with the monthly WorldClim data. The other meteorological inputs (e.g., air temperature, humidity, pressure, wind, and downward shortwave and longwave) are corrected for elevation through lapse-rate and slope-aspect methods. Evaluation of the model estimates is presented using satellite-derived data (e.g., MODIS and GRACE) and reanalysis products (e.g., CMC and ERA-interim).

An assessment of the feasibility of the use of satellite-only rainfall estimates for the hydrological monitoring in central Italy

NASA Astrophysics Data System (ADS)

Campo, Lorenzo; Caparrini, Francesca

2013-04-01

The need for accurate distributed hydrological modelling has constantly increased in last years for several purposes: agricultural applications, water resources management, hydrological balance at watershed scale, floods forecast. The main input for the hydrological numerical models is rainfall data that present, at the same time, a large availability of measures (in gauged regions, with respect to other micro-meteorological variables) and the most complex spatial patterns. While also in presence of densely gauged watersheds the spatial interpolation of the rainfall is a non-trivial problem, due to the spatial intermittence of the variable (especially at finer temporal scales), ungauged regions need an alternative source of rainfall data in order to perform the hydrological modelling. Such source can be constituted by the satellite-estimated rainfall fields, with reference to both geostationary and polar-orbit platforms. In this work the rainfall product obtained by the Aqua-AIRS sensor were used in order to assess the feasibility of the use of satellite-based rainfall as input for distributed hydrological modelling. The MOBIDIC (MOdello di BIlancio Distribuito e Continuo) model, developed at the Department of civil and Environmental Engineering of the University of Florence and operationally used by Tuscany Region and Umbria Region for flood prediction and management, was used for the experiments. In particular three experiments were carried on: a) hydrological simulation with the use of rain-gauges data, b) simulation with the use of satellite-only rainfall estimates, c) simulation with the combined use of the two sources of data in order to obtain an optimal estimate of the actual rainfall fields. The domain of the study was the central Italy. Several critical events occurred in the area were analyzed. A discussion of the results is provided.

Large scale snow water status monitoring: comparison of different snow water products in the upper Colorado basins

USGS Publications Warehouse

Artan, G.A.; Verdin, J.P.; Lietzow, R.

2013-01-01

We illustrate the ability to monitor the status of snowpack over large areas by using a~spatially distributed snow accumulation and ablation model in the Upper Colorado Basin. The model was forced with precipitation fields from the National Weather Service (NWS) Multi-sensor Precipitation Estimator (MPE) and the Tropical Rainfall Measuring Mission (TRMM) datasets; remaining meteorological model input data was from NOAA's Global Forecast System (GFS) model output fields. The simulated snow water equivalent (SWE) was compared to SWEs from the Snow Data Assimilation System (SNODAS) and SNOwpack TELemetry system (SNOTEL) over a~region of the Western United States that covers parts of the Upper Colorado Basin. We also compared the SWE product estimated from the Special Sensor Microwave Imager (SSM/I) and Scanning Multichannel Microwave Radiometer (SMMR) to the SNODAS and SNOTEL SWE datasets. Agreement between the spatial distribution of the simulated SWE with both SNODAS and SNOTEL was high for the two model runs for the entire snow accumulation period. Model-simulated SWEs, both with MPE and TRMM, were significantly correlated spatially on average with the SNODAS (r = 0.81 and r = 0.54; d.f. = 543) and the SNOTEL SWE (r = 0.85 and r = 0.55; d.f. = 543), when monthly basinwide simulated average SWE the correlation was also highly significant (r = 0.95 and r = 0.73; d.f. = 12). The SWE estimated from the passive microwave imagery was not correlated either with the SNODAS SWE or (r = 0.14, d.f. = 7) SNOTEL-reported SWE values (r = 0.08, d.f. = 7). The agreement between modeled SWE and the SWE recorded by SNODAS and SNOTEL weakened during the snowmelt period due to an underestimation bias of the air temperature that was used as model input forcing.

Testing efficacy of monthly forecast application in agrometeorology: Winter wheat phenology dynamic

NASA Astrophysics Data System (ADS)

Lalic, B.; Jankovic, D.; Dekic, Lj; Eitzinger, J.; Firanj Sremac, A.

2017-02-01

Use of monthly weather forecast as input meteorological data for agrometeorological forecasting, crop modelling and plant protection can foster promising applications in agricultural production. Operational use of monthly or seasonal weather forecast can help farmers to optimize field operations (fertilizing, irrigation) and protection measures against plant diseases and pests by taking full advantage of monthly forecast information in predicting plant development, pest and disease risks and yield potentials few weeks in advance. It can help producers to obtain stable or higher yield with the same inputs and to minimise losses caused by weather. In Central and South-Eastern Europe ongoing climate change lead to shifts of crops phenology dynamics (i.e. in Serbia 4-8 weeks earlier in 2016 than in previous years) and brings this subject in the front of agronomy science and practice. Objective of this study is to test efficacy of monthly forecast in predicting phenology dynamics of different winter wheat varieties, using phenological model developed by Forecasting and Warning Service of Serbia in plant protection. For that purpose, historical monthly forecast for four months (March 1, 2005 - June 30, 2005) was assimilated from ECMWF MARS archive for 50 ensemble members and control run. Impact of different agroecological conditions is tested by using observed and forecasted data for two locations - Rimski Sancevi (Serbia) and Groß-Enzersdorf (Austria).

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.

Improvement in the accuracy of back trajectories using WRF to identify pollen sources in southern Iberian Peninsula.

PubMed

Hernández-Ceballos, M A; Skjøth, C A; García-Mozo, H; Bolívar, J P; Galán, C

2014-12-01

Airborne pollen transport at micro-, meso-gamma and meso-beta scales must be studied by atmospheric models, having special relevance in complex terrain. In these cases, the accuracy of these models is mainly determined by the spatial resolution of the underlying meteorological dataset. This work examines how meteorological datasets determine the results obtained from atmospheric transport models used to describe pollen transport in the atmosphere. We investigate the effect of the spatial resolution when computing backward trajectories with the HYSPLIT model. We have used meteorological datasets from the WRF model with 27, 9 and 3 km resolutions and from the GDAS files with 1° resolution. This work allows characterizing atmospheric transport of Olea pollen in a region with complex flows. The results show that the complex terrain affects the trajectories and this effect varies with the different meteorological datasets. Overall, the change from GDAS to WRF-ARW inputs improves the analyses with the HYSPLIT model, thereby increasing the understanding the pollen episode. The results indicate that a spatial resolution of at least 9 km is needed to simulate atmospheric flows that are considerable affected by the relief of the landscape. The results suggest that the appropriate meteorological files should be considered when atmospheric models are used to characterize the atmospheric transport of pollen on micro-, meso-gamma and meso-beta scales. Furthermore, at these scales, the results are believed to be generally applicable for related areas such as the description of atmospheric transport of radionuclides or in the definition of nuclear-radioactivity emergency preparedness.

Improvement in the accuracy of back trajectories using WRF to identify pollen sources in southern Iberian Peninsula

NASA Astrophysics Data System (ADS)

Hernández-Ceballos, M. A.; Skjøth, C. A.; García-Mozo, H.; Bolívar, J. P.; Galán, C.

2014-12-01

Airborne pollen transport at micro-, meso-gamma and meso-beta scales must be studied by atmospheric models, having special relevance in complex terrain. In these cases, the accuracy of these models is mainly determined by the spatial resolution of the underlying meteorological dataset. This work examines how meteorological datasets determine the results obtained from atmospheric transport models used to describe pollen transport in the atmosphere. We investigate the effect of the spatial resolution when computing backward trajectories with the HYSPLIT model. We have used meteorological datasets from the WRF model with 27, 9 and 3 km resolutions and from the GDAS files with 1 ° resolution. This work allows characterizing atmospheric transport of Olea pollen in a region with complex flows. The results show that the complex terrain affects the trajectories and this effect varies with the different meteorological datasets. Overall, the change from GDAS to WRF-ARW inputs improves the analyses with the HYSPLIT model, thereby increasing the understanding the pollen episode. The results indicate that a spatial resolution of at least 9 km is needed to simulate atmospheric flows that are considerable affected by the relief of the landscape. The results suggest that the appropriate meteorological files should be considered when atmospheric models are used to characterize the atmospheric transport of pollen on micro-, meso-gamma and meso-beta scales. Furthermore, at these scales, the results are believed to be generally applicable for related areas such as the description of atmospheric transport of radionuclides or in the definition of nuclear-radioactivity emergency preparedness.

Assessing Fire Weather Index using statistical downscaling and spatial interpolation techniques in Greece

NASA Astrophysics Data System (ADS)

Karali, Anna; Giannakopoulos, Christos; Frias, Maria Dolores; Hatzaki, Maria; Roussos, Anargyros; Casanueva, Ana

2013-04-01

Forest fires have always been present in the Mediterranean ecosystems, thus they constitute a major ecological and socio-economic issue. The last few decades though, the number of forest fires has significantly increased, as well as their severity and impact on the environment. Local fire danger projections are often required when dealing with wild fire research. In the present study the application of statistical downscaling and spatial interpolation methods was performed to the Canadian Fire Weather Index (FWI), in order to assess forest fire risk in Greece. The FWI is used worldwide (including the Mediterranean basin) to estimate the fire danger in a generalized fuel type, based solely on weather observations. The meteorological inputs to the FWI System are noon values of dry-bulb temperature, air relative humidity, 10m wind speed and precipitation during the previous 24 hours. The statistical downscaling methods are based on a statistical model that takes into account empirical relationships between large scale variables (used as predictors) and local scale variables. In the framework of the current study the statistical downscaling portal developed by the Santander Meteorology Group (https://www.meteo.unican.es/downscaling) in the framework of the EU project CLIMRUN (www.climrun.eu) was used to downscale non standard parameters related to forest fire risk. In this study, two different approaches were adopted. Firstly, the analogue downscaling technique was directly performed to the FWI index values and secondly the same downscaling technique was performed indirectly through the meteorological inputs of the index. In both cases, the statistical downscaling portal was used considering the ERA-Interim reanalysis as predictands due to the lack of observations at noon. Additionally, a three-dimensional (3D) interpolation method of position and elevation, based on Thin Plate Splines (TPS) was used, to interpolate the ERA-Interim data used to calculate the index. Results from this method were compared with the statistical downscaling results obtained from the portal. Finally, FWI was computed using weather observations obtained from the Hellenic National Meteorological Service, mainly in the south continental part of Greece and a comparison with the previous results was performed.

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.

Atmospheric transport simulations in support of the Carbon in Arctic Reservoirs Vulnerability Experiment (CARVE)

NASA Astrophysics Data System (ADS)

Henderson, J. M.; Eluszkiewicz, J.; Mountain, M. E.; Nehrkorn, T.; Chang, R. Y.-W.; Karion, A.; Miller, J. B.; Sweeney, C.; Steiner, N.; Wofsy, S. C.; Miller, C. E.

2014-10-01

This paper describes the atmospheric modeling that underlies the Carbon in Arctic Reservoirs Vulnerability Experiment (CARVE) science analysis, including its meteorological and atmospheric transport components (Polar variant of the Weather Research and Forecasting (WRF) and Stochastic Time Inverted Lagrangian Transport (STILT) models), and provides WRF validation for May-October 2012 and March-November 2013 - the first two years of the aircraft field campaign. A triply nested computational domain for WRF was chosen so that the innermost domain with 3.3 km grid spacing encompasses the entire mainland of Alaska and enables the substantial orography of the state to be represented by the underlying high-resolution topographic input field. Summary statistics of the WRF model performance on the 3.3 km grid indicate good overall agreement with quality-controlled surface and radiosonde observations. Two-meter temperatures are generally too cold by approximately 1.4 K in 2012 and 1.1 K in 2013, while 2 m dewpoint temperatures are too low (dry) by 0.2 K in 2012 and too high (moist) by 0.6 K in 2013. Wind speeds are biased too low by 0.2 m s-1 in 2012 and 0.3 m s-1 in 2013. Model representation of upper level variables is very good. These measures are comparable to model performance metrics of similar model configurations found in the literature. The high quality of these fine-resolution WRF meteorological fields inspires confidence in their use to drive STILT for the purpose of computing surface influences ("footprints") at commensurably increased resolution. Indeed, footprints generated on a 0.1° grid show increased spatial detail compared with those on the more common 0.5° grid, lending itself better for convolution with flux models for carbon dioxide and methane across the heterogeneous Alaskan landscape. Ozone deposition rates computed using STILT footprints indicate good agreement with observations and exhibit realistic seasonal variability, further indicating that WRF-STILT footprints are of high quality and will support accurate estimates of CO2 and CH4 surface-atmosphere fluxes using CARVE observations.

Atmospheric transport simulations in support of the Carbon in Arctic Reservoirs Vulnerability Experiment (CARVE)

NASA Astrophysics Data System (ADS)

Henderson, J. M.; Eluszkiewicz, J.; Mountain, M. E.; Nehrkorn, T.; Chang, R. Y.-W.; Karion, A.; Miller, J. B.; Sweeney, C.; Steiner, N.; Wofsy, S. C.; Miller, C. E.

2015-04-01

This paper describes the atmospheric modeling that underlies the Carbon in Arctic Reservoirs Vulnerability Experiment (CARVE) science analysis, including its meteorological and atmospheric transport components (polar variant of the Weather Research and Forecasting (WRF) and Stochastic Time Inverted Lagrangian Transport (STILT) models), and provides WRF validation for May-October 2012 and March-November 2013 - the first 2 years of the aircraft field campaign. A triply nested computational domain for WRF was chosen so that the innermost domain with 3.3 km grid spacing encompasses the entire mainland of Alaska and enables the substantial orography of the state to be represented by the underlying high-resolution topographic input field. Summary statistics of the WRF model performance on the 3.3 km grid indicate good overall agreement with quality-controlled surface and radiosonde observations. Two-meter temperatures are generally too cold by approximately 1.4 K in 2012 and 1.1 K in 2013, while 2 m dewpoint temperatures are too low (dry) by 0.2 K in 2012 and too high (moist) by 0.6 K in 2013. Wind speeds are biased too low by 0.2 m s-1 in 2012 and 0.3 m s-1 in 2013. Model representation of upper level variables is very good. These measures are comparable to model performance metrics of similar model configurations found in the literature. The high quality of these fine-resolution WRF meteorological fields inspires confidence in their use to drive STILT for the purpose of computing surface influences ("footprints") at commensurably increased resolution. Indeed, footprints generated on a 0.1° grid show increased spatial detail compared with those on the more common 0.5° grid, better allowing for convolution with flux models for carbon dioxide and methane across the heterogeneous Alaskan landscape. Ozone deposition rates computed using STILT footprints indicate good agreement with observations and exhibit realistic seasonal variability, further indicating that WRF-STILT footprints are of high quality and will support accurate estimates of CO2 and CH4 surface-atmosphere fluxes using CARVE observations.

Climate scenarios for the Truckee-Carson River system

USGS Publications Warehouse

Dettinger, Michael; Sterle, Kelley; Simpson, Karen; Singletary, Loretta; Fitzgerald, Kelsey; McCarthy, Maureen

2017-01-01

In this study, the scenarios ultimately take the form of gridded, daily (maximum and minimum) temperatures and precipitation totals spanning the entire Truckee-Carson River System, from which meteorological inputs to various hydrologic, water-balance and watermanagement models can be extracted by other parts of the Water for the Seasons project and by other studies and stakeholders. Climate scenarios are constructed using: 1) survey data from interviews with 66 Truckee-Carson River System water-management and water-interest organizations to identify plausible drought and high-flow events that could stress the system irreparably; 2) input from the Stakeholder Affiliate Group and other modelers on the Water for the Seasons team to gain additional key stakeholder input with regard to organizational survey results and to identify the most pressing water-management issues being faced in the system; and 3) historical climate datasets used to simulate possible future conditions.

THE DEFINITION AND INTERPRETATION OF TERRESTRIAL ENVIRONMENT DESIGN INPUTS FOR VEHICLE DESIGN CONSIDERATIONS

NASA Technical Reports Server (NTRS)

Johnson, Dale L.; Keller, Vernon W.; Vaughan, William W.

2005-01-01

The description and interpretation of the terrestrial environment (0-90 km altitude) is an important driver of aerospace vehicle structural, control, and thermal system design. NASA is currently in the process of reviewing the meteorological information acquired over the past decade and producing an update to the 1993 Terrestrial Environment Guidelines for Aerospace Vehicle Design and Development handbook. This paper addresses the contents of this updated handbook, with special emphasis on new material being included in the areas of atmospheric thermodynamic models, wind dynamics, atmospheric composition, atmospheric electricity, cloud phenomena, atmospheric extremes, sea state, etc. In addition, the respective engineering design elements will be discussed relative to the importance and influence of terrestrial environment inputs that require consideration and interpretation for design applications. Specific lessons learned that have contributed to the advancements made in the acquisition, interpretation, application and awareness of terrestrial environment inputs for aerospace engineering applications are discussed.

Attributing Crop Production in the United States Using Artificial Neural Network

NASA Astrophysics Data System (ADS)

Ma, Y.; Zhang, Z.; Pan, B.

2017-12-01

Crop production plays key role in supporting life, economy and shaping environment. It is on one hand influenced by natural factors including precipitation, temperature, energy, and on the other hand shaped by the investment of fertilizers, pesticides and human power. Successful attributing of crop production to different factors can help optimize resources and improve productivity. Based on the meteorological records from National Center for Environmental Prediction and state-wise crop production related data provided by the United States Department of Agriculture Economic Research Service, an artificial neural network was constructed to connect crop production with precipitation and temperature anormlies, capital input, labor input, energy input, pesticide consumption and fertilizer consumption. Sensitivity analysis were carried out to attribute their specific influence on crop production for each grid. Results confirmed that the listed factors can generally determine the crop production. Different state response differently to the pertubation of predictands. Their spatial distribution is visulized and discussed.

Air-Quality and Climate Coupling in High Resolution for Urban Heat Island Study

NASA Astrophysics Data System (ADS)

Halenka, T.; Huszar, P.; Belda, M.

2012-04-01

Recent studies show considerable effect of atmospheric chemistry and aerosols on climate on regional and local scale. For the purpose of qualifying and quantifying the magnitude of climate forcing due to atmospheric chemistry/aerosols on regional scale and climate change effects on air-quality the regional climate model RegCM and chemistry/aerosol model CAMx was coupled. Climate change impacts on air-quality have been studied in high resolution of 10km with interactive two-way coupling of the effects of air-quality on climate. The experiments with the couple were performed for EC FP7 project MEGAPOLI assessing the impact of the megacities and industrialized areas on climate. New experiments in high resolution are prepared andsimulated for Urban Heat Island studies within the OP Central Europe Project UHI. Meteorological fields generated by RCM drive CAMx transport, chemistry and a dry/wet deposition. A preprocessor utility was developed for transforming RegCM provided fields to CAMx input fields and format. There is critical issue of the emission inventories available for 10km resolution including the urban hot-spots, TNO emissions are adopted for the experiments. Sensitivity tests switching on/off urban areas emissions are analysed as well. The results for year 2005 are presented and discussed, interactive coupling is compared to study the potential of possible impact of urban air-pollution to the urban area climate.

Comparison of different models for ground-level atmospheric turbulence strength (C(n)(2)) prediction with a new model according to local weather data for FSO applications.

PubMed

Arockia Bazil Raj, A; Arputha Vijaya Selvi, J; Durairaj, S

2015-02-01

Atmospheric parameters strongly affect the performance of free-space optical communication (FSOC) systems when the optical wave is propagating through the inhomogeneous turbulence transmission medium. Developing a model to get an accurate prediction of the atmospheric turbulence strength (C(n)(2)) according to meteorological parameters (weather data) becomes significant to understand the behavior of the FSOC channel during different seasons. The construction of a dedicated free-space optical link for the range of 0.5 km at an altitude of 15.25 m built at Thanjavur (Tamil Nadu) is described in this paper. The power level and beam centroid information of the received signal are measured continuously with weather data at the same time using an optoelectronic assembly and the developed weather station, respectively, and are recorded in a data-logging computer. Existing models that exhibit relatively fewer prediction errors are briefed and are selected for comparative analysis. Measured weather data (as input factors) and C(n)(2) (as a response factor) of size [177,147×4] are used for linear regression analysis and to design mathematical models more suitable in the test field. Along with the model formulation methodologies, we have presented the contributions of the input factors' individual and combined effects on the response surface and the coefficient of determination (R(2)) estimated using analysis of variance tools. An R(2) value of 98.93% is obtained using the new model, model equation V, from a confirmatory test conducted with a testing data set of size [2000×4]. In addition, the prediction accuracies of the selected and the new models are investigated during different seasons in a one-year period using the statistics of day, week-averaged, month-averaged, and seasonal-averaged diurnal Cn2 profiles, and are verified in terms of the sum of absolute error (SAE). A Cn2 prediction maximum average SAE of 2.3×10(-13)  m(-2/3) is achieved using the new model in a longer range of dynamic meteorological parameters during the different local seasons.

Development and testing of meteorology and air dispersion models for Mexico City

NASA Astrophysics Data System (ADS)

Williams, M. D.; Brown, M. J.; Cruz, X.; Sosa, G.; Streit, G.

Los Alamos National Laboratory and Instituto Mexicano del Petróleo are completing a joint study of options for improving air quality in Mexico City. We have modified a three-dimensional, prognostic, higher-order turbulence model for atmospheric circulation (HOTMAC) and a Monte Carlo dispersion and transport model (RAPTAD) to treat domains that include an urbanized area. We used the meteorological model to drive models which describe the photochemistry and air transport and dispersion. The photochemistry modeling is described in a separate paper. We tested the model against routine measurements and those of a major field program. During the field program, measurements included: (1) lidar measurements of aerosol transport and dispersion, (2) aircraft measurements of winds, turbulence, and chemical species aloft, (3) aircraft measurements of skin temperatures, and (4) Tethersonde measurements of winds and ozone. We modified the meteorological model to include provisions for time-varying synoptic-scale winds, adjustments for local wind effects, and detailed surface-coverage descriptions. We developed a new method to define mixing-layer heights based on model outputs. The meteorology and dispersion models were able to provide reasonable representations of the measurements and to define the sources of some of the major uncertainties in the model-measurement comparisons.

Development of Automated Objective Meteorological Techniques.

DTIC Science & Technology

1980-11-30

differences are due largely to the nature and spatial distribution of the atmospheric data chosen as input for the model . The data for initial values and...technique. This report fo,-uses on results of theoretical investigations and data analyses performed oy SASC during the period May, 1979 to June, 1980...the sampling period, at a given point in space, the various size particles composing the particle distribution ex- hibit different velocities from each

Continually Plastic Modeling of Non-Stationary Systems

DTIC Science & Technology

2016-09-01

ples, we had previously been unable to generate effective models of SWE. For Experiment Set I, therefore, air temperature was the only meteorological...input. Air temperature is known to be a highly effective predictor of melt rate because it is correlated with long- wave atmospheric radiation, the...us to compose datasets large enough for effective machine learning. However, the inclu- sion of air temperature did not have a significant impact on

National Guidebook for Application of Hydrogeomorphic Assessment to Tidal Fringe Wetlands

DTIC Science & Technology

1998-12-01

Wrighton Road Lothian, MD 20711 Ron Thorn Battele Marine Science Laboratory 1529 West Sequim Bay Road Sequim , WA 98382 Rena Weichenburg U.S. Army...This region includes the Delaware and Chesapeake Bay estuaries and, except for the exclusion of the microtidal Albemarle and Pamlico Sounds...Gulf (Pearl River, Mississippi, to Galveston Bay , Texas). Small tidal range (< 1 m), meteorologically dominated diurnal tides. Freshwater input

Proceedings: Annual Workshop on Meteorological and Environmental Inputs to Aviation Systems (4th), March 25-27, 1980.

DTIC Science & Technology

1980-03-01

Force -- 4 United States Navy -- 1 National Transportation Safety Board -- I PRIVATE SECTOR (43) University and Research -- 12 Georgia Institute of...States Air Force , Aeronautical Systems Division 6 *1 __________________________________________-our_ TABLE 4 IMPROMPTU PRESENTATIONS 񓟛 Clear Air...Propulsion Laboratory 7 concerning the Air New Zealand DC-10 accident at Mt. Erebus, Antarctica; and John Corbin of the U.S. Air Force Aeronautical

Calculated maximum Hl ground-level concentrations downwind from launch pad aborts of the space shuttle and Titan 3 C vehicles at Kennedy Space Center

NASA Technical Reports Server (NTRS)

Dumbauld, R. K.; Bjorklund, J. R.

1972-01-01

A quantitative assessment is described of the potential environmental hazard posed by the atmospheric release of HCl resulting from the burning of solid propellant during two hypothetical on-pad aborts of the Titan 3 C and space shuttle vehicles at Kennedy Space Center. In one pad-abort situation, it is assumed that the cases of the two solid-propellant engines are ruptured and the burning propellant falls to the ground in the immediate vicinity of the launch pad where it continues to burn for 5 minutes. In the other pad-abort situation considered, one of the two solid engines on each vehicle is assumed to ignite and burn at the normal rate while the vehicle remains on the launch pad. Calculations of maximum HCl ground-level concentration for the above on-pad abort situations were made using the computerized NASA/MSFC multilayer diffusion models in conjunction with appropriate meteorological and source inputs. Three meteorological regimes are considered-fall, spring, and afternoon sea-breeze. Source inputs for the hazard calculations were developed. The principal result of the calculations is that maximum ground-level HCl concentrations at distances greater than 1 kilometer from the launch pad are less than 3 parts per million in all cases considered.

A multidisciplinary system for monitoring and forecasting Etna volcanic plumes

NASA Astrophysics Data System (ADS)

Coltelli, Mauro; Prestifilippo, Michele; Spata, Gaetano; Scollo, Simona; Andronico, Daniele

2010-05-01

One of the most active volcanoes in the world is Mt. Etna, in Italy, characterized by frequent explosive activity from the central craters and from fractures opened along the volcano flanks which, during the last years, caused several damages to aviation and forced the closure of the Catania International Airport. To give precise warning to the aviation authorities and air traffic controller and to assist the work of VAACs, a novel system for monitoring and forecasting Etna volcanic plumes, was developed at the Istituto Nazionale di Geofisica e Vulcanologia, sezione di Catania, the managing institution for the surveillance of Etna volcano. Monitoring is carried out using multispectral infrared measurements from the Spin Enhanced Visible and Infrared Imager (SEVIRI) on board the Meteosat Second Generation geosynchronous satellite able to track the volcanic plume with a high time resolution, visual and thermal cameras used to monitor the explosive activity, three continuous wave X-band disdrometers which detect ash dispersal and fallout, sounding balloons used to evaluate the atmospheric fields, and finally field data collected after the end of the eruptive event needed to extrapolate important features of explosive activity. Forecasting is carried out daily using automatic procedures which download weather forecast data obtained by meteorological mesoscale models from the Italian Air Force national Meteorological Office and from the hydrometeorological service of ARPA-SIM; run four different tephra dispersal models using input parameters obtained by the analysis of the deposits collected after few hours since the eruptive event similar to 22 July 1998, 21-24 July 2001 and 2002-03 Etna eruptions; plot hazard maps on ground and in air and finally publish them on a web-site dedicated to the Italian Civil Protection. The system has been already tested successfully during several explosive events occurring at Etna in 2006, 2007 and 2008. These events produced eruption columns high up to several kilometers above sea level and, on the basis of parameters such as mass eruption rate and total grain-size distributions, showed different explosive style. The monitoring and forecasting system is going on developing through the installation of new instruments able to detect different features of the volcanic plumes (e.g. the dispersal and sedimentation processes) in order to reduce the uncertainty of the input parameters used in the modeling. This is crucial to perform a reliable forecasting. We show that multidisciplinary approaches can really give useful information on the presence of volcanic ash and consequently to prevent damages and airport disruptions.

Two-Dimensional Model Simulations of Interannual Variability in the Tropical Stratosphere

NASA Technical Reports Server (NTRS)

Fleming, Eric L.; Jackman, Charles H.; Considine, David B.; Rosenfeld, Joan; Bhartia, P. K. (Technical Monitor)

2001-01-01

Meteorological data from the United Kingdom Meteorological Office (UKMO) and constituent data from the Upper Atmospheric Research Satellite (UARS) are used to construct yearly zonal mean dynamical fields for the 1990s for use in the GSFC 2-D chemistry and transport model. This allows for interannual dynamical variability to be included in the model constituent simulations. In this study, we focus on the tropical stratosphere. We find that the phase of quasi-biennial oscillation (QBO) signals in equatorial CH4, and profile and total column 03 data is resolved quite well using this empirically- based 2-D model transport framework. However. the QBO amplitudes in the model constituents are systematically underestimated relative to the observations at most levels. This deficiency is probably due in part to the limited vertical resolutions of the 2-D model and the UKMO and UARS input data sets. We find that using different heating rate calculations in the model affects the interannual and QBO amplitudes in the constituent fields, but has little impact on the phase. Sensitivity tests reveal that the QBO in transport dominates the ozone interannual variability in the lower stratosphere. with the effect of the temperature QBO being dominant in the tipper stratosphere via the strong temperature dependence of the ozone loss reaction rates. We also find that the QBO in odd nitrogen radicals, which is caused by the QBO modulated transport of NOy, plays a significant but not dominant role in determining the ozone QBO variability in the middle stratosphere. The model mean age of air is in good overall agreement with that determined from tropical lower,middle stratospheric OMS balloon observations of SF6 and CO2. The interannual variability of tile equatorial mean age in the model increases with altitude and maximizes near 40 km, with a range, of 4-5 years over the 1993-2000 time period.

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.

Spoilt for choice - A comparison of downscaling approaches for hydrological impact studies

NASA Astrophysics Data System (ADS)

Rössler, Ole; Fischer, Andreas; Kotlarski, Sven; Keller, Denise; Liniger, Mark; Weingartner, Rolf

2017-04-01

With the increasing number of available climate downscaling approaches, users are often faced with the luxury problem of which downscaling method to apply in a climate change impact assessment study. In Switzerland, for instance, the new generation of local scale climate scenarios CH2018 will be based on quantile mapping (QM), replacing the previous delta change (DC) method. Parallel to those two methods, a multi-site weather generator (WG) was developed to meet specific user needs. The question poses which downscaling method is the most suitable for a given application. Here, we analyze the differences of the three approaches in terms of hydro-meteorological responses in the Swiss pre-Alps in terms of mean values as well as indices of extremes. The comparison of the three different approaches was carried out in the frame of a hydrological impact assessment study that focused on different runoff characteristics and their related meteorological indices in the meso-scale catchment of the river Thur ( 1700 km2), Switzerland. For this purpose, we set up the hydrological model WaSiM-ETH under present (1980-2009) and under future conditions (2070-2099), assuming the SRES A1B emission scenario. Input to the three downscaling approaches were 10 GCM-RCM simulations of the ENSEMBLES project, while eight meteorological station observations served as the reference. All station data, observed and downscaled, were interpolated to obtain meteorological fields of temperature and precipitation required by the hydrological model. For the present-day reference period we evaluated the ability of each downscaling method to reproduce today's hydro-meteorological patterns. In the scenario runs, we focused on the comparison of change signals for each hydro-meteorological parameter generated by the three downscaling techniques. The evaluation exercise reveals that QM and WG perform equally well in representing present day average conditions, but that QM outperforms WG in reproducing indices related to extreme conditions like the number of drought events or multi-day rain sums. In terms of mean monthly discharge changes, the three downscaling methods reveal notable differences: DC shows the strongest (in summer) and less pronounced (in winter) change signal. Regarding some extreme features of runoff like frequency of droughts and the low flow level, DC shows similar change signals compared to QM and WG. This was unexpected as DC is commonly reported to fail in terms of projecting extreme changes. In contrast, QM mostly shows the strongest change signals for the 10 different extreme related indices, due to its ability to pick up more features of the climate change signals from the RCM. This indicates that DC and also WG miss some aspects, especially for flood related indices. Hence, depending on the target variable of interest, DC and QM typically provide the full range of change signals, while WG mostly lies in between both method. However, it offers the great advantage of multiple realizations combined with inter-variable consistency.

GPS IPW as a Meteorological Parameter and Climate Global Change Indicator

NASA Astrophysics Data System (ADS)

Kruczyk, M.; Liwosz, T.

2011-12-01

Paper focuses on comprehensive investigation of the GPS derived IPW (Integrated Precipitable Water, also IWV) as a geophysical tool. GPS meteorology is now widely acknowledged indirect method of atmosphere sensing. First we demonstrate GPS IPW quality. Most thorough inter-technique comparisons of directly measured IPW are attainable only for some observatories (note modest percentage of GPS stations equipped with meteorological devices). Nonetheless we have managed to compare IPW series derived from GPS tropospheric solutions (ZTD mostly from IGS and EPN solutions) and some independent techniques. IPW values from meteorological sources we used are: radiosoundings, sun photometer and input fields of numerical weather prediction model. We can treat operational NWP models as meteorological database within which we can calculate IWV for all GPS stations independently from network of direct measurements (COSMO-LM model maintained by Polish Institute of Meteorology and Water Management was tried). Sunphotometer (CIMEL-318, Central Geophysical Observatory IGF PAS, Belsk, Poland) data seems the most genuine source - so we decided for direct collocation of GPS measurements and sunphotometer placing permanent GPS receiver on the roof of Belsk Observatory. Next we analyse IPW as geophysical parameter: IPW demonstrates some physical effects evoked by station location (height and series correlation coefficient as a function of distance) and weather patterns like dominant wind directions (in case of neighbouring stations). Deficiency of surface humidity data to model IPW is presented for different climates. This inadequacy and poor humidity data representation in NWP model extremely encourages investigating information exchange potential between Numerical Model and GPS network. The second and most important aspect of this study concerns long series of IPW (daily averaged) which can serve as climatological information indicator (water vapour role in climate system is hard to exaggerate). Especially intriguing are relatively unique shape of such series in different climates. Long lasting changes in weather conditions: 'dry' and 'wet' years are also visible. The longer and more uniform our series are the better chance to estimate the magnitude of climatological IWV changes. Homogenous ZTD solution during long period is great concern in this approach (problems with GPS strategy and reference system changes). In case of continental network (EUREF Permanent Network) reliable data we get only after reprocessing. Simple sinusoidal model has been adjusted to the IPW series (LS method) for selected stations (mainly Europe but also other continents - IGS stations), every year separately. Not only amplitudes but also phases of annual signal differ from year to year. Longer IPW series (up to 14 years) searched for some climatological signal sometimes reveal weak steady trend. Large number of GPS permanent stations, relative easiness of IPW derivation (only and surface meteo data needed apart from GPS solution) and water vapour significance in water cycle and global climate make this GPS IPW promising element of global environmental change monitoring.

Comprehensive modeling of monthly mean soil temperature using multivariate adaptive regression splines and support vector machine

NASA Astrophysics Data System (ADS)

Mehdizadeh, Saeid; Behmanesh, Javad; Khalili, Keivan

2017-07-01

Soil temperature (T s) and its thermal regime are the most important factors in plant growth, biological activities, and water movement in soil. Due to scarcity of the T s data, estimation of soil temperature is an important issue in different fields of sciences. The main objective of the present study is to investigate the accuracy of multivariate adaptive regression splines (MARS) and support vector machine (SVM) methods for estimating the T s. For this aim, the monthly mean data of the T s (at depths of 5, 10, 50, and 100 cm) and meteorological parameters of 30 synoptic stations in Iran were utilized. To develop the MARS and SVM models, various combinations of minimum, maximum, and mean air temperatures (T min, T max, T); actual and maximum possible sunshine duration; sunshine duration ratio (n, N, n/N); actual, net, and extraterrestrial solar radiation data (R s, R n, R a); precipitation (P); relative humidity (RH); wind speed at 2 m height (u 2); and water vapor pressure (Vp) were used as input variables. Three error statistics including root-mean-square-error (RMSE), mean absolute error (MAE), and determination coefficient (R 2) were used to check the performance of MARS and SVM models. The results indicated that the MARS was superior to the SVM at different depths. In the test and validation phases, the most accurate estimations for the MARS were obtained at the depth of 10 cm for T max, T min, T inputs (RMSE = 0.71 °C, MAE = 0.54 °C, and R 2 = 0.995) and for RH, V p, P, and u 2 inputs (RMSE = 0.80 °C, MAE = 0.61 °C, and R 2 = 0.996), respectively.

Neural network simulation of soil NO3 dynamic under potato crop system

NASA Astrophysics Data System (ADS)

Goulet-Fortin, Jérôme; Morais, Anne; Anctil, François; Parent, Léon-Étienne; Bolinder, Martin

2013-04-01

Nitrate leaching is a major issue in sandy soils intensively cropped to potato. Modelling could test and improve management practices, particularly as regard to the optimal N application rates. Lack of input data is an important barrier for the application of classical process-based models to predict soil NO3 content (SNOC) and NO3 leaching (NOL). Alternatively, data driven models such as neural networks (NN) could better take into account indicators of spatial soil heterogeneity and plant growth pattern such as the leaf area index (LAI), hence reducing the amount of soil information required. The first objective of this study was to evaluate NN and hybrid models to simulate SNOC in the 0-40 cm soil layer considering inter-annual variations, spatial soil heterogeneity and differential N application rates. The second objective was to evaluate the same methodology to simulate seasonal NOL dynamic at 1 m deep. To this aim, multilayer perceptrons with different combinations of driving meteorological variables, functions of the LAI and state variables of external deterministic models have been trained and evaluated. The state variables from external models were: drainage estimated by the CLASS model and the soil temperature estimated by an ICBM subroutine. Results of SNOC simulations were compared to field data collected between 2004 and 2011 at several experimental plots under potato cropping systems in Québec, Eastern Canada. Results of NOL simulation were compared to data obtained in 2012 from 11 suction lysimeters installed in 2 experimental plots under potato cropping systems in the same region. The most performing model for SNOC simulation was obtained using a 4-input hybrid model composed of 1) cumulative LAI, 2) cumulative drainage, 3) soil temperature and 4) day of year. The most performing model for NOL simulation was obtained using a 5-input NN model composed of 1) N fertilization rate at spring, 2) LAI, 3) cumulative rainfall, 4) the day of year and 5) the percentage of clay content. The MAE was 22% for SNOC simulation and 23% for NOL simulation. High sensitivity to LAI suggests that the model may take into account field and sub-field spatial variability and support N management. Further studies are needed to fully validate the method, particularly in the case of NOL simulation.

GUMICS4 Synthetic and Dynamic Simulations of the ECLAT Project

NASA Astrophysics Data System (ADS)

Facsko, G.; Palmroth, M. M.; Gordeev, E.; Hakkinen, L. V.; Honkonen, I. J.; Janhunen, P.; Sergeev, V. A.; Kauristie, K.; Milan, S. E.

2012-12-01

The European Commission funded the European Cluster Assimilation Techniques (ECLAT) project as a collaboration of five leader European universities and research institutes. A main contribution of the Finnish Meteorological Institute (FMI) is to provide a wide range of global MHD runs with the Grand Unified Magnetosphere Ionosphere Coupling simulation (GUMICS). The runs are divided in two categories: synthetic runs investigating the extent of solar wind drivers that can influence magnetospheric dynamics, as well as dynamic runs using measured solar wind data as input. Here we consider the first set of runs with synthetic solar wind input. The solar wind density, velocity and the interplanetary magnetic field had different magnitudes and orientations; furthermore two F10.7 flux values were selected for solar radiation minimum and maximum values. The solar wind parameter values were constant such that a constant stable solution was archived. All configurations were run several times with three different (-15°, 0°, +15°) tilt angles in the GSE X-Z plane. The Cray XT supercomputer of the FMI provides a unique opportunity in global magnetohydrodynamic simulation: running the GUMICS-4 based on one year real solar wind data. Solar wind magnetic field, density, temperature and velocity data based on Advanced Composition Explorer (ACE) and WIND measurements are downloaded from the OMNIWeb open database and a special input file is created for each Cluster orbit. All data gaps are replaced with linear interpolations between the last and first valid data values before and after the data gap. Minimum variance transformation is applied for the Interplanetary Magnetic Field data to clean and avoid the code of divergence. The Cluster orbits are divided into slices allowing parallel computation and each slice has an average tilt angle value. The file timestamps start one hour before the perigee to provide time for building up a magnetosphere in the simulation space. The real measurements were extrapolated into one minute intervals by the database and the time steps of the simulation result are shifted by 20-30 minutes calculated from the spacecraft position and the actual solar wind velocity. All simulation results are saved every 5th minutes (in calculation time). The result of the 162 simulations named so called "synthetic run library" were visualized and uploaded to the homepage of the FMI after validation as well as the year run savings. Here we present details of these runs.

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.

Validation of the MIMOSA-AURORA-IFDM model chain for policy support: Modeling concentrations of elemental carbon in Flanders

NASA Astrophysics Data System (ADS)

Lefebvre, Wouter; Vercauteren, Jordy; Schrooten, Liesbeth; Janssen, Stijn; Degraeuwe, Bart; Maenhaut, Willy; de Vlieger, Ina; Vankerkom, Jean; Cosemans, Guido; Mensink, Clemens; Veldeman, Nele; Deutsch, Felix; Van Looy, Stijn; Peelaerts, Wim; Lefebre, Filip

2011-12-01

The ability of a complex model chain to simulate elemental carbon (EC) concentrations was examined. The results of the model chain were compared to EC concentration measurements made at several locations, every sixth day. Two measurement campaigns were taken into account, one in 2006-2007 and one in 2008-2009. The model results compare very well for both periods, with an R2 of 0.74, a bias of 0.02 μg m -3 and a RMSE of 0.32 μg m -3. Sensitivity analyses to different meteorology inputs and changing emissions from year to year were performed. The differences between the two measurement periods were also investigated. It is shown that somewhat more than half of these differences is due to meteorology. However, emission changes also play an important role.

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

Lange, R.; Dickerson, M.A.; Peterson, K.R.

Two numerical models for the calculation of air concentration and ground deposition of airborne effluent releases are compared. The Particle-in-Cell (PIC) model and the Straight-Line Airflow Gaussian model were used for the simulation. Two sites were selected for comparison: the Hudson River Valley, New York, and the area around the Savannah River Plant, South Carolina. Input for the models was synthesized from meteorological data gathered in previous studies by various investigators. It was found that the PIC model more closely simulated the three-dimensional effects of the meteorology and topography. Overall, the Gaussian model calculated higher concentrations under stable conditions withmore » better agreement between the two methods during neutral to unstable conditions. In addition, because of its consideration of exposure from the returning plume after flow reversal, the PIC model calculated air concentrations over larger areas than did the Gaussian model.« less

Solar radiation over Egypt: Comparison of predicted and measured meteorological data

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

Kamel, M.A.; Shalaby, S.A.; Mostafa, S.S.

1993-06-01

Measurements of global solar irradiance on a horizontal surface at five meteorological stations in Egypt for three years 1987, 1988, and 1989 are compared with their corresponding values computed by two independent methods. The first method is based on the Angstrom formula, which correlates relative solar irradiance H/H[sub o] to corresponding relative duration of bright sunshine n/N. Regional regression coefficients are obtained and used for prediction of global solar irradiance. Good agreement with measurements is obtained. In the second method an empirical relation, in which sunshine duration and the noon altitude of the sun as inputs together with appropriate choicemore » of zone parameters, is employed. This gives good agreement with the measurements. Comparison shows that the first method gives better fitting with the experimental data.« less

Autonomous Aerial Sensors for Wind Power Meteorology

NASA Astrophysics Data System (ADS)

Giebel, Gregor; Schmidt Paulsen, Uwe; Reuder, Joachim; La Cour-Harbo, Anders; Thomsen, Carsten; Bange, Jens; Buschmann, Marco

2010-05-01

This poster describes a new approach for measurements in wind power meteorology using small unmanned flying platforms. During a week of flying a lighter-than-air vehicle, two small electrically powered aeroplanes and a larger helicopter at the Risø test station at Høvsøre, we will compare wind speed measurements with fixed mast and LIDAR measurements, investigate optimal flight patterns for each measurement task, and measure other interesting meteorological features like the air-sea boundary in the vicinity of the wind farm. In order to prepare the measurement campaign, a workshop is held, soliciting input from various communities. Large-scale wind farms, especially offshore, need an optimisation between installed wind power density and the losses in the wind farm due to wake effects between the turbines. While the wake structure behind single wind turbines onshore is fairly well understood, there are different problems offshore, thought to be due mainly to the low turbulence. Good measurements of the wake and wake structure are not easy to come by, as the use of a met mast is static and expensive, while the use of remote sensing instruments either needs significant access to the turbine to mount an instrument, or is complicated to use on a ship due to the ship's own movement. In any case, a good LIDAR or SODAR will cost many tens of thousands of euros. Another current problem in wind energy is the coming generation of wind turbines in the 10-12 MW class, with tip heights of over 200 m. Very few measurement masts exist to verify our knowledge of atmospheric physics - all that is known is that the boundary layer description we used so far is not valid any more. Here, automated Unmanned Aerial Vehicles (UAVs) could be used as either an extension of current high masts or to build a network of very high ‘masts' in a region of complex terrain or coastal flow conditions. In comparison to a multitude of high masts, UAVs could be quite cost-effective. In order to test this assumption and to test the limits of UAVs for wind power meteorology, this project assembles four different UAVs from four participating groups. Risø will build a lighter-than-air kite with a long tether, Bergen University flies a derivative of the Funjet, a pusher airplane below 1 kg total weight, Mavionics or TU Braunschweig flies the Carolo, a 2m wide two prop model with a pitot tube on the nose, and Aalborg University will use a helicopter for their part. All those platforms will be flown during one week at the Danish national test station for large wind turbines at Høvsøre. The site is strongly instrumented, with 6 masts reaching up to 167m. The comparison of wind speed measurements from planes and fixed masts should give an indication of the accuracy of the measured wind field. A workshop is planned as preparation, where everyone with an interest in the program can give input.

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.

Main field and secular variation modeling with Defense Meteorological Satellite Program magnetic measurements

NASA Astrophysics Data System (ADS)

Alken, P.; Olsen, N.; Finlay, C. C.; Chulliat, A.

2017-12-01

In order to investigate the spatial structure and development of rapid (sub-decadal) changes in the geomagnetic core field, including its secular variation and acceleration, global magnetic measurements from space play a crucial role. With the end of the CHAMP mission in September 2010, there has been a gap in high-quality satellite magnetic field measurements until the Swarm mission was launched in November 2013. Geomagnetic main field models during this period have relied on the global ground observatory network which, due to its sparse spatial configuration, has difficulty in resolving secular variation and acceleration at higher spherical harmonic degrees. In this presentation we will show new results in building main field models during this "gap period", based on vector magnetic measurements from four Defense Meteorological Satellite Program (DMSP) satellites. While the fluxgate instruments onboard DMSP were not designed for high-quality core field modeling, we find that the DMSP dataset can provide valuable information on secular variation and acceleration during the gap period.

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.

On quality control procedures for solar radiation and meteorological measures, from subhourly to montly average time periods

NASA Astrophysics Data System (ADS)

Espinar, B.; Blanc, P.; Wald, L.; Hoyer-Klick, C.; Schroedter-Homscheidt, M.; Wanderer, T.

2012-04-01

Meteorological data measured by ground stations are often a key element in the development and validation of methods exploiting satellite images. These data are considered as a reference against which satellite-derived estimates are compared. Long-term radiation and meteorological measurements are available from a large number of measuring stations. However, close examination of the data often reveals a lack of quality, often for extended periods of time. This lack of quality has been the reason, in many cases, of the rejection of large amount of available data. The quality data must be checked before their use in order to guarantee the inputs for the methods used in modelling, monitoring, forecast, etc. To control their quality, data should be submitted to several conditions or tests. After this checking, data that are not flagged by any of the test is released as a plausible data. In this work, it has been performed a bibliographical research of quality control tests for the common meteorological variables (ambient temperature, relative humidity and wind speed) and for the usual solar radiometrical variables (horizontal global and diffuse components of the solar radiation and the beam normal component). The different tests have been grouped according to the variable and the average time period (sub-hourly, hourly, daily and monthly averages). The quality test may be classified as follows: • Range checks: test that verify values are within a specific range. There are two types of range checks, those based on extrema and those based on rare observations. • Step check: test aimed at detecting unrealistic jumps or stagnation in the time series. • Consistency checks: test that verify the relationship between two or more time series. The gathered quality tests are applicable for all latitudes as they have not been optimized regionally nor seasonably with the aim of being generic. They have been applied to ground measurements in several geographic locations, what result in the detection of some control tests that are no longer adequate, due to different reasons. After the modification of some test, based in our experience, a set of quality control tests is now presented, updated according to technology advances and classified. The presented set of quality tests allows radiation and meteorological data to be tested in order to know their plausibility to be used as inputs in theoretical or empirical methods for scientific research. The research leading to those results has partly receive funding from the European Union's Seventh Framework Programme (FP7/2007-2013) under Grant Agreement no. 262892 (ENDORSE project).

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.

Effect of regional-scale transport on oxidants in the vicinity of Philadelphia during the 1999 NE-OPS field campaign

Treesearch

Jerome D. Fast; Rahul A. Zaveri; Xindi Bian; Elaine G. Chapman; Richard C. Easter

2002-01-01

A new meteorological-chemical model is used to determine the relative contribution of regional-scale transport and local photochemical production on air quality over Philadelphia. The model performance is evaluated using surface and airborne meteorological and chemical measurements made during a 30-day period in July and August of 1999 as part of the Northeast Oxidant...

Efforts to Overcome Difficulties in a Higher Education Meteorology Department Institution

NASA Astrophysics Data System (ADS)

Mota, G. V.; Souza, J. R.; Ribeiro, J. B.; Souza, E. B.; Gomes, N. V.; Oliveira, R. A.; Ameida, W. G.; Chagas, G. O.; Yoksas, T.; Spangler, T.; Cutrim, E.

2007-05-01

The development of cyberinfrastructure in higher education meteorology departments has become a key requirement to better qualify their students and develop scientific research. The authors present their efforts to overcome low budget, lack of personnel, and other difficulties in the Department of Meteorology, Universidade Federal do Pará (UFPA), to participate in international collaborations for sharing hydro-meteorological data, tools and technological systems. Some important steps towards a consolidated integration of the group with the international partnership are discussed, and three are highlighted: (a) the resources from the Unidata's Equipment Award (supported by the National Science Foundation - NSF) and equipment donated in cooperation with the COMET and Meteoforum projects; (b) the interaction of the local team making its project resources available to the community; and (c) the involvement of students with the programs and the cyberinfrastructure available locally. Some positive results can be observed, such as the ability for students of Synoptic Meteorology II class to not only see static meteorological fields on the web, but actually build themselves regional and real-time synoptic products from the data received through Unidata's Internet Data Distribution (IDD) system. Moreover, the UFPA's group intends to improve its infrastructure to expand the access of real-time data and products to other members of the local meteorological community.

Short perturbations of cosmic ray intensity and electric field in atmosphere

NASA Technical Reports Server (NTRS)

Alexeyenko, V. V.; Chudakov, A. E.; Sborshikov, V. G.; Tizengauzen, V. A.

1985-01-01

Short perturbations of cosmic ray intensity were found to be a common phenomenon. Its meteorological origin and correlation with electric field is established. The phenomenon can be explained by the electric field if the strength of this field at high altitudes is much bigger than the measured one at surface.

A Generalized Method for Vertical Profiles of Mean Layer Values of Meteorological Variables

DTIC Science & Technology

2015-09-01

NUMBER OF PAGES 62 19a. NAME OF RESPONSIBLE PERSON James Cogan a. REPORT Unclassified b. ABSTRACT Unclassified c . THIS PAGE...Message Zones, Primary Data Structure, and Sample METB3 Weighting Array 35 Appendix C . Samples of Input and Output 41 List of Symbols...39 Table C -1 Example of RAOB for Albuquerque, New Mexico. The first 3 mandatory levels are below the actual terrain surface and

Proceedings: Annual Workshop on Meteorological and Environmental Inputs to Aviation Systems (5th) Held on 31 March-2 April 1981.

DTIC Science & Technology

1981-12-01

STUDIES PROJECT MODIFICATION JFK JOHN F. KENNEDY AIRPORT PATWAS PILOT AUTOMATIC TELEPHONE WEATHER ANSWERING SERVICE JPL JET PROPULSION LABORATORY PDP...wing aircraft, helicopters, and cruise sorship directed at Atmospheric Electricity missiles. The AEHP concepts developed will apply Hazards Protection...atmospheric electricity simulators. 90 THE JOINT AIRPORT WEATHER STUDIES PROJECT John McCarthy National Center for Atmospheric Research Several people raised

Evaluation of data assimilation techniques for a mesoscale meteorological model and their effects on air quality model results

NASA Astrophysics Data System (ADS)

Amicarelli, A.; Gariazzo, C.; Finardi, S.; Pelliccioni, A.; Silibello, C.

2008-05-01

Data assimilation techniques are methods to limit the growth of errors in a dynamical model by allowing observations distributed in space and time to force (nudge) model solutions. They have become common for meteorological model applications in recent years, especially to enhance weather forecast and to support air-quality studies. In order to investigate the influence of different data assimilation techniques on the meteorological fields produced by RAMS model, and to evaluate their effects on the ozone and PM10 concentrations predicted by FARM model, several numeric experiments were conducted over the urban area of Rome, Italy, during a summer episode.

Upper-Tropospheric Winds Derived from Geostationary Satellite Water Vapor Observations

NASA Technical Reports Server (NTRS)

Velden, Christopher S.; Hayden, Christopher M.; Nieman, Steven J.; Menzel, W. Paul; Wanzong, Steven; Goerss, James S.

1997-01-01

The coverage and quality of remotely sensed upper-tropospheric moisture parameters have improved considerably with the deployment of a new generation of operational geostationary meteorological satellites: GOES-8/9 and GMS-5. The GOES-8/9 water vapor imaging capabilities have increased as a result of improved radiometric sensitivity and higher spatial resolution. The addition of a water vapor sensing channel on the latest GMS permits nearly global viewing of upper-tropospheric water vapor (when joined with GOES and Meteosat) and enhances the commonality of geostationary meteorological satellite observing capabilities. Upper-tropospheric motions derived from sequential water vapor imagery provided by these satellites can be objectively extracted by automated techniques. Wind fields can be deduced in both cloudy and cloud-free environments. In addition to the spatially coherent nature of these vector fields, the GOES-8/9 multispectral water vapor sensing capabilities allow for determination of wind fields over multiple tropospheric layers in cloud-free environments. This article provides an update on the latest efforts to extract water vapor motion displacements over meteorological scales ranging from subsynoptic to global. The potential applications of these data to impact operations, numerical assimilation and prediction, and research studies are discussed.

Improvement of Advanced Storm-scale Analysis and Prediction System (ASAPS) on Seoul Metropolitan Area, Korea

NASA Astrophysics Data System (ADS)

Park, Jeong-Gyun; Jee, Joon-Bum

2017-04-01

Dangerous weather such as severe rain, heavy snow, drought and heat wave caused by climate change make more damage in the urban area that dense populated and industry areas. Urban areas, unlike the rural area, have big population and transportation, dense the buildings and fuel consumption. Anthropogenic factors such as road energy balance, the flow of air in the urban is unique meteorological phenomena. However several researches are in process about prediction of urban meteorology. ASAPS (Advanced Storm-scale Analysis and Prediction System) predicts a severe weather with very short range (prediction with 6 hour) and high resolution (every hour with time and 1 km with space) on Seoul metropolitan area based on KLAPS (Korea Local Analysis and Prediction System) from KMA (Korea Meteorological Administration). This system configured three parts that make a background field (SUF5), analysis field (SU01) with observation and forecast field with high resolution (SUF1). In this study, we improve a high-resolution ASAPS model and perform a sensitivity test for the rainfall case. The improvement of ASAPS include model domain configuration, high resolution topographic data and data assimilation with WISE observation data.

New DMSP database of precipitating auroral electrons and ions

NASA Astrophysics Data System (ADS)

Redmon, Robert J.; Denig, William F.; Kilcommons, Liam M.; Knipp, Delores J.

2017-08-01

Since the mid-1970s, the Defense Meteorological Satellite Program (DMSP) spacecraft have operated instruments for monitoring the space environment from low Earth orbit. As the program evolved, so have the measurement capabilities such that modern DMSP spacecraft include a comprehensive suite of instruments providing estimates of precipitating electron and ion fluxes, cold/bulk plasma composition and moments, the geomagnetic field, and optical emissions in the far and extreme ultraviolet. We describe the creation of a new public database of precipitating electrons and ions from the Special Sensor J (SSJ) instrument, complete with original counts, calibrated differential fluxes adjusted for penetrating radiation, estimates of the total kinetic energy flux and characteristic energy, uncertainty estimates, and accurate ephemerides. These are provided in a common and self-describing format that covers 30+ years of DMSP spacecraft from F06 (launched in 1982) to F18 (launched in 2009). This new database is accessible at the National Centers for Environmental Information and the Coordinated Data Analysis Web. We describe how the new database is being applied to high-latitude studies of the colocation of kinetic and electromagnetic energy inputs, ionospheric conductivity variability, field-aligned currents, and auroral boundary identification. We anticipate that this new database will support a broad range of space science endeavors from single observatory studies to coordinated system science investigations.

Grid-cell-based crop water accounting for the famine early warning system

NASA Astrophysics Data System (ADS)

Verdin, James; Klaver, Robert

2002-06-01

Rainfall monitoring is a regular activity of food security analysts for sub-Saharan Africa due to the potentially disastrous impact of drought. Crop water accounting schemes are used to track rainfall timing and amounts relative to phenological requirements, to infer water limitation impacts on yield. Unfortunately, many rain gauge reports are available only after significant delays, and the gauge locations leave large gaps in coverage. As an alternative, a grid-cell-based formulation for the water requirement satisfaction index (WRSI) was tested for maize in Southern Africa. Grids of input variables were obtained from remote sensing estimates of rainfall, meteorological models, and digital soil maps. The spatial WRSI was computed for the 1996-97 and 1997-98 growing seasons. Maize yields were estimated by regression and compared with a limited number of reports from the field for the 1996-97 season in Zimbabwe. Agreement at a useful level (r = 0·80) was observed. This is comparable to results from traditional analysis with station data. The findings demonstrate the complementary role that remote sensing, modelling, and geospatial analysis can play in an era when field data collection in sub-Saharan Africa is suffering an unfortunate decline. Published in 2002 by John Wiley & Sons, Ltd.

Immersive Earth Science: Data Visualization in Virtual Reality

NASA Astrophysics Data System (ADS)

Skolnik, S.; Ramirez-Linan, R.

2017-12-01

Utilizing next generation technology, Navteca's exploration of 3D and volumetric temporal data in Virtual Reality (VR) takes advantage of immersive user experiences where stakeholders are literally inside the data. No longer restricted by the edges of a screen, VR provides an innovative way of viewing spatially distributed 2D and 3D data that leverages a 360 field of view and positional-tracking input, allowing users to see and experience data differently. These concepts are relevant to many sectors, industries, and fields of study, as real-time collaboration in VR can enhance understanding and mission with VR visualizations that display temporally-aware 3D, meteorological, and other volumetric datasets. The ability to view data that is traditionally "difficult" to visualize, such as subsurface features or air columns, is a particularly compelling use of the technology. Various development iterations have resulted in Navteca's proof of concept that imports and renders volumetric point-cloud data in the virtual reality environment by interfacing PC-based VR hardware to a back-end server and popular GIS software. The integration of the geo-located data in VR and subsequent display of changeable basemaps, overlaid datasets, and the ability to zoom, navigate, and select specific areas show the potential for immersive VR to revolutionize the way Earth data is viewed, analyzed, and communicated.

Cross-scale impact of climate temporal variability on ecosystem water and carbon fluxes

DOE PAGES

Paschalis, Athanasios; Fatichi, Simone; Katul, Gabriel G.; ...

2015-08-07

While the importance of ecosystem functioning is undisputed in the context of climate change and Earth system modeling, the role of short-scale temporal variability of hydrometeorological forcing (~1 h) on the related ecosystem processes remains to be fully understood. Additionally, various impacts of meteorological forcing variability on water and carbon fluxes across a range of scales are explored here using numerical simulations. Synthetic meteorological drivers that highlight dynamic features of the short temporal scale in series of precipitation, temperature, and radiation are constructed. These drivers force a mechanistic ecohydrological model that propagates information content into the dynamics of water andmore » carbon fluxes for an ensemble of representative ecosystems. The focus of the analysis is on a cross-scale effect of the short-scale forcing variability on the modeled evapotranspiration and ecosystem carbon assimilation. Interannual variability of water and carbon fluxes is emphasized in the analysis. The main study inferences are summarized as follows: (a) short-scale variability of meteorological input does affect water and carbon fluxes across a wide range of time scales, spanning from the hourly to the annual and longer scales; (b) different ecosystems respond to the various characteristics of the short-scale variability of the climate forcing in various ways, depending on dominant factors limiting system productivity; (c) whenever short-scale variability of meteorological forcing influences primarily fast processes such as photosynthesis, its impact on the slow-scale variability of water and carbon fluxes is small; and (d) whenever short-scale variability of the meteorological forcing impacts slow processes such as movement and storage of water in the soil, the effects of the variability can propagate to annual and longer time scales.« less

Cross-scale impact of climate temporal variability on ecosystem water and carbon fluxes

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

Paschalis, Athanasios; Fatichi, Simone; Katul, Gabriel G.

While the importance of ecosystem functioning is undisputed in the context of climate change and Earth system modeling, the role of short-scale temporal variability of hydrometeorological forcing (~1 h) on the related ecosystem processes remains to be fully understood. Additionally, various impacts of meteorological forcing variability on water and carbon fluxes across a range of scales are explored here using numerical simulations. Synthetic meteorological drivers that highlight dynamic features of the short temporal scale in series of precipitation, temperature, and radiation are constructed. These drivers force a mechanistic ecohydrological model that propagates information content into the dynamics of water andmore » carbon fluxes for an ensemble of representative ecosystems. The focus of the analysis is on a cross-scale effect of the short-scale forcing variability on the modeled evapotranspiration and ecosystem carbon assimilation. Interannual variability of water and carbon fluxes is emphasized in the analysis. The main study inferences are summarized as follows: (a) short-scale variability of meteorological input does affect water and carbon fluxes across a wide range of time scales, spanning from the hourly to the annual and longer scales; (b) different ecosystems respond to the various characteristics of the short-scale variability of the climate forcing in various ways, depending on dominant factors limiting system productivity; (c) whenever short-scale variability of meteorological forcing influences primarily fast processes such as photosynthesis, its impact on the slow-scale variability of water and carbon fluxes is small; and (d) whenever short-scale variability of the meteorological forcing impacts slow processes such as movement and storage of water in the soil, the effects of the variability can propagate to annual and longer time scales.« less

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.

The Current Status and Future of GNSS-Meteorology in Europe

NASA Astrophysics Data System (ADS)

Jones, J.; Guerova, G.; Dousa, J.; Dick, G.; Haan, de, S.; Pottiaux, E.; Bock, O.; Pacione, R.

2017-12-01

GNSS is a well established atmospheric observing system which can accurately sense water vapour, the most abundant greenhouse gas, accounting for 60-70% of atmospheric warming. Water vapour observations are currently under-sampled in operational meteorology and obtaining and exploiting additional high-quality humidity observations is essential to improve severe weather forecasting and climate monitoring. Inconsistencies introduced into long-term time series from improved GNSS processing algorithms make climate trend analysis challenging. Ongoing re-processing efforts using state-of-the-art models are underway which will provide consistent time series' of tropospheric data, using 15+ years of GNSS observations and from over 600 stations worldwide. These datasets will enable validation of systematic biases from a range of instrumentation, improve the knowledge of climatic trends of atmospheric water vapour, and will potentially be of great benefit to global and regional NWP reanalyses and climate model simulations (e.g. IPCC AR5) COST Action ES1206 is a 4-year project, running from 2013 to 2017, which has coordinated new and improved capabilities from concurrent developments in GNSS, meteorological and climate communities. For the first time, the synergy of multi-GNSS constellations has been used to develop new, more advanced tropospheric products, exploiting the full potential of multi-GNSS on a wide range of temporal and spatial scales - from real-time products monitoring and forecasting severe weather, to the highest quality post-processed products suitable for climate research. The Action has also promoted the use of meteorological data as an input to real-time GNSS positioning, navigation, and timing services and has stimulated knowledge and data transfer throughout Europe and beyond. This presentation will give an overview of COST Action ES1206 plus an overview of ground-based GNSS-meteorology in Europe in general, including current status and future opportunities.

Using Meteorological Analogues for Reordering Postprocessed Precipitation Ensembles in Hydrological Forecasting

NASA Astrophysics Data System (ADS)

Bellier, Joseph; Bontron, Guillaume; Zin, Isabella

2017-12-01

Meteorological ensemble forecasts are nowadays widely used as input of hydrological models for probabilistic streamflow forecasting. These forcings are frequently biased and have to be statistically postprocessed, using most of the time univariate techniques that apply independently to individual locations, lead times and weather variables. Postprocessed ensemble forecasts therefore need to be reordered so as to reconstruct suitable multivariate dependence structures. The Schaake shuffle and ensemble copula coupling are the two most popular methods for this purpose. This paper proposes two adaptations of them that make use of meteorological analogues for reconstructing spatiotemporal dependence structures of precipitation forecasts. Performances of the original and adapted techniques are compared through a multistep verification experiment using real forecasts from the European Centre for Medium-Range Weather Forecasts. This experiment evaluates not only multivariate precipitation forecasts but also the corresponding streamflow forecasts that derive from hydrological modeling. Results show that the relative performances of the different reordering methods vary depending on the verification step. In particular, the standard Schaake shuffle is found to perform poorly when evaluated on streamflow. This emphasizes the crucial role of the precipitation spatiotemporal dependence structure in hydrological ensemble forecasting.

Field gamma-ray spectrometer GS256: measurements stability

NASA Astrophysics Data System (ADS)

Mojzeš, Andrej

2009-01-01

The stability of in situ readings of the portable gamma-ray spectrometer GS256 during the field season of 2006 was studied. The instrument is an impulse detector of gamma rays based on NaI(Tl) 3" × 3" scintillation unit and 256-channel spectral analyzer which allows simultaneous assessment of up to 8 radioisotopes in rocks. It is commonly used in surface geophysical survey for the measurement of natural 40K, 238U and 232Th but also artificial 137Cs quantities. The statistical evaluation is given of both repeated measurements - in the laboratory and at several field control points in different survey areas. The variability of values shows both the instrument stability and also the relative influence of some meteorological factors, mainly rainfalls. The analysis shows an acceptable level of instrument measurements stability, the necessity to avoid measurement under unfavourable meteorological conditions and to keep detailed field book information about time, position and work conditions.

The Bering Sea ice cover during March 1979: Comparison of surface and satellite data with the Nimbus-7 SMMR

NASA Technical Reports Server (NTRS)

Martin, S.; Cavalieri, D. J.; Gloersen, P.; Mcnutt, S. L.

1982-01-01

During March 1979, field operations were carried out in the Marginal Ice Zone (MIZ) of the Bering Sea. The field measurements which included oceanographic, meteorological and sea ice observations were made nearly coincident with a number of Nimbus-7 and Tiros-N satellite observations. The results of a comparison between surface and aircraft observations, and images from the Tiros-N satellite, with ice concentrations derived from the microwave radiances of the Nimbus-7 Scanning Multichannel Microwave Radiometer (SMMR) are given. Following a brief discussion of the field operations, including a summary of the meteorological conditions during the experiment, the satellite data is described with emphasis on the Nimbus-7 SMMR and the physical basis of the algorithm used to retrieve ice concentrations.

On the impact of using downscaled reanalysis data instead of direct measurements for modeling the mass balance of a tropical glacier (Cordillera Blanca, Peru)

NASA Astrophysics Data System (ADS)

Galos, Stephan; Hofer, Marlis; Marzeion, Ben; Mölg, Thomas; Großhauser, Martin

2013-04-01

Due to their setting, tropical glaciers are sensitive indicators of mid-tropospheric meteorological variability and climate change. Furthermore these glaciers are of particular interest because they respond faster to climatic changes than glaciers located in mid- or high-latitudes. As long-term direct meteorological measurements in such remote environments are scarce, reanalysis data (e.g. ERA-Interim) provide a highly valuable source of information. Reanalysis datasets (i) enable a temporal extension of data records gained by direct measurements and (ii) provide information from regions where direct measurements are not available. In order to properly derive the physical exchange processes between glaciers and atmosphere from reanalysis data, downscaling procedures are required. In the present study we investigate if downscaled atmospheric variables (air temperature and relative humidity) from a reanalysis dataset can be used as input for a physically based, high resolution energy and mass balance model. We apply a well validated empirical-statistical downscaling model, fed with ERA-Interim data, to an automated weather station (AWS) on the surface of Glaciar Artesonraju (8.96° S | 77.63° W). The downscaled data is then used to replace measured air temperature and relative humidity in the input for the energy and mass balance model, which was calibrated using ablation data from stakes and a sonic ranger. In order to test the sensitivity of the modeled mass balance to the downscaled data, the results are compared to a reference model run driven solely with AWS data as model input. We finally discuss the results and present future perspectives for further developing this method.

The EMEP MSC-W chemical transport model - technical description

NASA Astrophysics Data System (ADS)

Simpson, D.; Benedictow, A.; Berge, H.; Bergström, R.; Emberson, L. D.; Fagerli, H.; Flechard, C. R.; Hayman, G. D.; Gauss, M.; Jonson, J. E.; Jenkin, M. E.; Nyíri, A.; Richter, C.; Semeena, V. S.; Tsyro, S.; Tuovinen, J.-P.; Valdebenito, Á.; Wind, P.

2012-08-01

The Meteorological Synthesizing Centre-West (MSC-W) of the European Monitoring and Evaluation Programme (EMEP) has been performing model calculations in support of the Convention on Long Range Transboundary Air Pollution (CLRTAP) for more than 30 years. The EMEP MSC-W chemical transport model is still one of the key tools within European air pollution policy assessments. Traditionally, the model has covered all of Europe with a resolution of about 50 km × 50 km, and extending vertically from ground level to the tropopause (100 hPa). The model has changed extensively over the last ten years, however, with flexible processing of chemical schemes, meteorological inputs, and with nesting capability: the code is now applied on scales ranging from local (ca. 5 km grid size) to global (with 1 degree resolution). The model is used to simulate photo-oxidants and both inorganic and organic aerosols. In 2008 the EMEP model was released for the first time as public domain code, along with all required input data for model runs for one year. The second release of the EMEP MSC-W model became available in mid 2011, and a new release is targeted for summer 2012. This publication is intended to document this third release of the EMEP MSC-W model. The model formulations are given, along with details of input data-sets which are used, and a brief background on some of the choices made in the formulation is presented. The model code itself is available at www.emep.int, along with the data required to run for a full year over Europe.

Applications of ISES for meteorology

NASA Technical Reports Server (NTRS)

Try, Paul D.

1990-01-01

The results are summarized from an initial assessment of the potential real-time meteorological requirements for the data from Eos systems. Eos research scientists associated with facility instruments, investigator instruments, and interdisciplinary groups with data related to meteorological support were contacted, along with those from the normal operational user and technique development groups. Two types of activities indicated the greatest need for real-time Eos data: technology transfer groups (e.g., NOAA's Forecasting System Laboratory and the DOD development laboratories), and field testing groups with airborne operations. A special concern was expressed by several non-U.S. participants who desire a direct downlink to be sure of rapid receipt of the data for their area of interest. Several potential experiments or demonstrations are recommended for ISES which include support for hurricane/typhoon forecasting, space shuttle reentry, severe weather forecasting (using microphysical cloud classification techniques), field testing, and quick reaction of instrumented aircraft to measure such events as polar stratospheric clouds and volcanic eruptions.

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.

AIRBORNE BACTERIA IN THE ATMOSPHERIC SURFACE LAYER: TEMPORAL DISTRIBUTION ABOVE A GRASS SEED FIELD

EPA Science Inventory

Temporal airborne bacterial concentrations and meteorological conditions were measured above a grass seed field in the Willamette River Valley, near Corvallis, Oregon, in the summer of 1993. he report describes the changes in the atmospheric surface layer over a grass seed field ...

MOVES-Matrix and distributed computing for microscale line source dispersion analysis.

PubMed

Liu, Haobing; Xu, Xiaodan; Rodgers, Michael O; Xu, Yanzhi Ann; Guensler, Randall L

2017-07-01

MOVES and AERMOD are the U.S. Environmental Protection Agency's recommended models for use in project-level transportation conformity and hot-spot analysis. However, the structure and algorithms involved in running MOVES make analyses cumbersome and time-consuming. Likewise, the modeling setup process, including extensive data requirements and required input formats, in AERMOD lead to a high potential for analysis error in dispersion modeling. This study presents a distributed computing method for line source dispersion modeling that integrates MOVES-Matrix, a high-performance emission modeling tool, with the microscale dispersion models CALINE4 and AERMOD. MOVES-Matrix was prepared by iteratively running MOVES across all possible iterations of vehicle source-type, fuel, operating conditions, and environmental parameters to create a huge multi-dimensional emission rate lookup matrix. AERMOD and CALINE4 are connected with MOVES-Matrix in a distributed computing cluster using a series of Python scripts. This streamlined system built on MOVES-Matrix generates exactly the same emission rates and concentration results as using MOVES with AERMOD and CALINE4, but the approach is more than 200 times faster than using the MOVES graphical user interface. Because AERMOD requires detailed meteorological input, which is difficult to obtain, this study also recommends using CALINE4 as a screening tool for identifying the potential area that may exceed air quality standards before using AERMOD (and identifying areas that are exceedingly unlikely to exceed air quality standards). CALINE4 worst case method yields consistently higher concentration results than AERMOD for all comparisons in this paper, as expected given the nature of the meteorological data employed. The paper demonstrates a distributed computing method for line source dispersion modeling that integrates MOVES-Matrix with the CALINE4 and AERMOD. This streamlined system generates exactly the same emission rates and concentration results as traditional way to use MOVES with AERMOD and CALINE4, which are regulatory models approved by the U.S. EPA for conformity analysis, but the approach is more than 200 times faster than implementing the MOVES model. We highlighted the potentially significant benefit of using CALINE4 as screening tool for identifying potential area that may exceeds air quality standards before using AERMOD, which requires much more meteorology input than CALINE4.

Assimilation of water temperature and discharge data for ensemble water temperature forecasting

NASA Astrophysics Data System (ADS)

Ouellet-Proulx, Sébastien; Chimi Chiadjeu, Olivier; Boucher, Marie-Amélie; St-Hilaire, André

2017-11-01

Recent work demonstrated the value of water temperature forecasts to improve water resources allocation and highlighted the importance of quantifying their uncertainty adequately. In this study, we perform a multisite cascading ensemble assimilation of discharge and water temperature on the Nechako River (Canada) using particle filters. Hydrological and thermal initial conditions were provided to a rainfall-runoff model, coupled to a thermal module, using ensemble meteorological forecasts as inputs to produce 5 day ensemble thermal forecasts. Results show good performances of the particle filters with improvements of the accuracy of initial conditions by more than 65% compared to simulations without data assimilation for both the hydrological and the thermal component. All thermal forecasts returned continuous ranked probability scores under 0.8 °C when using a set of 40 initial conditions and meteorological forecasts comprising 20 members. A greater contribution of the initial conditions to the total uncertainty of the system for 1-dayforecasts is observed (mean ensemble spread = 1.1 °C) compared to meteorological forcings (mean ensemble spread = 0.6 °C). The inclusion of meteorological uncertainty is critical to maintain reliable forecasts and proper ensemble spread for lead times of 2 days and more. This work demonstrates the ability of the particle filters to properly update the initial conditions of a coupled hydrological and thermal model and offers insights regarding the contribution of two major sources of uncertainty to the overall uncertainty in thermal forecasts.

Improvement of fog predictability in a coupled system of PAFOG and WRF

NASA Astrophysics Data System (ADS)

Kim, Wonheung; Yum, Seong Soo; Kim, Chang Ki

2017-04-01

Fog is difficult to predict because of the multi-scale nature of its formation mechanism: not only the synoptic conditions but also the local meteorological conditions crucially influence fog formation. Coarse vertical resolution and parameterization errors in fog prediction models are also critical reasons for low predictability. In this study, we use a coupled model system of a 3D mesoscale model (WRF) and a single column model with a fine vertical resolution (PAFOG, PArameterized FOG) to simulate fogs formed over the southern coastal region of the Korean Peninsula, where National Center for Intensive Observation of Severe Weather (NCIO) is located. NCIO is unique in that it has a 300 m meteorological tower built at the location to measure basic meteorological variables (temperature, dew point temperature and winds) at eleven different altitudes, and comprehensive atmospheric physics measurements are made with the various remote sensing instruments such as visibility meter, cloud radar, wind profiler, microwave radiometer, and ceilometer. These measurement data are used as input data to the model system and for evaluating the results. Particularly the data for initial and external forcings, which are tightly connected to the predictability of coupled model system, are derived from the tower measurement. This study aims at finding out the most important factors that influence fog predictability of the coupled system for NCIO. Nudging of meteorological tower data and soil moisture variability are found to be critically influencing fog predictability. Detailed results will be discussed at the conference.

Synoptic and meteorological drivers of extreme ozone concentrations over Europe

NASA Astrophysics Data System (ADS)

Otero, Noelia Felipe; Sillmann, Jana; Schnell, Jordan L.; Rust, Henning W.; Butler, Tim

2016-04-01

The present work assesses the relationship between local and synoptic meteorological conditions and surface ozone concentration over Europe in spring and summer months, during the period 1998-2012 using a new interpolated data set of observed surface ozone concentrations over the European domain. Along with local meteorological conditions, the influence of large-scale atmospheric circulation on surface ozone is addressed through a set of airflow indices computed with a novel implementation of a grid-by-grid weather type classification across Europe. Drivers of surface ozone over the full distribution of maximum daily 8-hour average values are investigated, along with drivers of the extreme high percentiles and exceedances or air quality guideline thresholds. Three different regression techniques are applied: multiple linear regression to assess the drivers of maximum daily ozone, logistic regression to assess the probability of threshold exceedances and quantile regression to estimate the meteorological influence on extreme values, as represented by the 95th percentile. The relative importance of the input parameters (predictors) is assessed by a backward stepwise regression procedure that allows the identification of the most important predictors in each model. Spatial patterns of model performance exhibit distinct variations between regions. The inclusion of the ozone persistence is particularly relevant over Southern Europe. In general, the best model performance is found over Central Europe, where the maximum temperature plays an important role as a driver of maximum daily ozone as well as its extreme values, especially during warmer months.

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.

NASA GISS Surface Temperature (GISTEMP) Analysis

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

Schmidt, G.; Ruedy, R.; Persin, A

The NASA GISS Surface Temperature (GISTEMP) analysis provides a measure of the changing global surface temperature with monthly resolution for the period since 1880, when a reasonably global distribution of meteorological stations was established. The input data that the GISTEMP Team use for the analysis, collected by many national meteorological services around the world, are the adjusted data of the Global Historical Climatology Network (GHCN) Vs. 3 (this represents a change from prior use of unadjusted Vs. 2 data) (Peterson and Vose, 1997 and 1998), United States Historical Climatology Network (USHCN) data, and SCAR (Scientific Committee on Antarctic Research) datamore » from Antarctic stations. Documentation of the basic analysis method is provided by Hansen et al. (1999), with several modifications described by Hansen et al. (2001). The GISS analysis is updated monthly, however CDIAC's presentation of the data here is updated annually.« less

Focused sunlight factor of forest fire danger assessment using Web-GIS and RS technologies

NASA Astrophysics Data System (ADS)

Baranovskiy, Nikolay V.; Sherstnyov, Vladislav S.; Yankovich, Elena P.; Engel, Marina V.; Belov, Vladimir V.

2016-08-01

Timiryazevskiy forestry of Tomsk region (Siberia, Russia) is a study area elaborated in current research. Forest fire danger assessment is based on unique technology using probabilistic criterion, statistical data on forest fires, meteorological conditions, forest sites classification and remote sensing data. MODIS products are used for estimating some meteorological conditions and current forest fire situation. Geonformation technologies are used for geospatial analysis of forest fire danger situation on controlled forested territories. GIS-engine provides opportunities to construct electronic maps with different levels of forest fire probability and support raster layer for satellite remote sensing data on current forest fires. Web-interface is used for data loading on specific web-site and for forest fire danger data representation via World Wide Web. Special web-forms provide interface for choosing of relevant input data in order to process the forest fire danger data and assess the forest fire probability.

Analysis/forecast experiments with a multivariate statistical analysis scheme using FGGE data

NASA Technical Reports Server (NTRS)

Baker, W. E.; Bloom, S. C.; Nestler, M. S.

1985-01-01

A three-dimensional, multivariate, statistical analysis method, optimal interpolation (OI) is described for modeling meteorological data from widely dispersed sites. The model was developed to analyze FGGE data at the NASA-Goddard Laboratory of Atmospherics. The model features a multivariate surface analysis over the oceans, including maintenance of the Ekman balance and a geographically dependent correlation function. Preliminary comparisons are made between the OI model and similar schemes employed at the European Center for Medium Range Weather Forecasts and the National Meteorological Center. The OI scheme is used to provide input to a GCM, and model error correlations are calculated for forecasts of 500 mb vertical water mixing ratios and the wind profiles. Comparisons are made between the predictions and measured data. The model is shown to be as accurate as a successive corrections model out to 4.5 days.

Modeling the wet bulb globe temperature using standard meteorological measurements.

PubMed

Liljegren, James C; Carhart, Richard A; Lawday, Philip; Tschopp, Stephen; Sharp, Robert

2008-10-01

The U.S. Army has a need for continuous, accurate estimates of the wet bulb globe temperature to protect soldiers and civilian workers from heat-related injuries, including those involved in the storage and destruction of aging chemical munitions at depots across the United States. At these depots, workers must don protective clothing that increases their risk of heat-related injury. Because of the difficulty in making continuous, accurate measurements of wet bulb globe temperature outdoors, the authors have developed a model of the wet bulb globe temperature that relies only on standard meteorological data available at each storage depot for input. The model is composed of separate submodels of the natural wet bulb and globe temperatures that are based on fundamental principles of heat and mass transfer, has no site-dependent parameters, and achieves an accuracy of better than 1 degree C based on comparisons with wet bulb globe temperature measurements at all depots.

Modelling the future distribution of ammonium nitrate concentrations in The Netherlands for 2020: The sensitivity to meteorological parameters

NASA Astrophysics Data System (ADS)

Williams, J. E.; van der Swaluw, E.; de Vries, W. J.; Sauter, F. J.; van Pul, W. A. J.; Hoogerbrugge, R.

2015-08-01

We present a parameterization developed to simulate Ammonium particle (NH4+) concentrations in the Operational Priority Substances (OPS) source-receptor model, without the necessity of using a detailed chemical scheme. By using the ratios of the main pre-cursor gases SO2, NO2 and NH3, and utilising calculations performed using a chemical box-model, we show that the parameterization can simulate annual mean NH4+ concentration fields to within ∼15% of measured values at locations throughout the Netherlands. Performing simulations for different decades, we find a strong correlation of simulated NH4+ distributions for both past (1993-1995) and present (2009-2012) time periods. Although the total concentration of NH4+ has decreased over the period, we find that the fraction of NH4+ transported into the Netherlands has increased from around 40% in the past to 50% for present-day. This is due to the variable efficiency of mitigation practises across economic sectors. Performing simulations for the year 2020 using associated emission estimates, we show that there are generally decreases of ∼8-25% compared to present day concentrations. By altering the meteorological fields applied in the future simulations, we show that a significant uncertainty of between ∼50 and 100% exists on this estimated NH4+ distribution as a result of variability in the temperature dependent emission terms and relative humidity. Therefore, any projections of future NH4+ distributions should be performed using well chosen meteorological fields representing recent meteorological situations.

Data analysis and archival

NASA Technical Reports Server (NTRS)

Danielsen, Edwin F.; Pfister, Leonhard; Hipskind, R. Stephen; Gaines, Steven E.

1990-01-01

The purpose of this task is the acquisition, distribution, archival, and analysis of data collected during and in support of the Upper Atmospheric Research Program (UARP) field experiments. Meteorological and U2 data from the 1984 Stratosphere-Troposphere Exchange Project (STEP) was analyzed to determine characteristics of internal atmospheric waves. CDROM's containing data from the 1987 STEP, 1987 Airborne Antarctic Ozone Expedition (AAOE), and the 1989 Airborne Arctic Stratospheric Expedition (AASE) were produced for archival and distribution of those data sets. The AASE CDROM contains preliminary data and a final release is planned for February 1990. Comparisons of data from the NASA ER-2 Meteorological Measurement System (MMS) with radar tracking and radiosonde data show good agreement. Planning for a Meteorological Support Facility continues. We are investigating existing and proposed hardware and software to receive, manipulate, and display satellite imagery and standard meteorological analyses, forecasts, and radiosonde data.

Assessing the impacts of climate change in Mediterranean catchments under conditions of data scarcity - The Gaza case study

NASA Astrophysics Data System (ADS)

Gampe, David; Ludwig, Ralf

2013-04-01

According to current climate projections, Mediterranean countries are at high risk for an even pronounced susceptibility to changes in the hydrological budget and extremes. While there is scientific consensus that climate induced changes on the hydrology of Mediterranean regions are presently occurring and are projected to amplify in the future, very little knowledge is available about the quantification of these changes, which is hampered by a lack of suitable and cost effective hydrological monitoring and modeling systems. The European FP7-project CLIMB is aiming to analyze climate induced changes on the hydrology of the Mediterranean Basins by investigating seven test sites located in the countries Italy, France, Turkey, Tunisia, Gaza and Egypt. CLIMB employs a combination of novel geophysical field monitoring concepts, remote sensing techniques and integrated hydrologic modeling to improve process descriptions and understanding and to quantify existing uncertainties in climate change impact analysis. One of those seven sites is the Gaza Strip, located in the Eastern Mediterranean and part of the Palestinian Autonomous Area, covers an area of 365km² with a length of 35km and 6 to 12km in width. Elevation ranges from sea level up to 104m in the East of the test site. Mean annual precipitation varies from 235mm in the South to 420mm in the North of the area. The inter annual variability of rainfall and the rapid population growth in an highly agricultural used area represent the major challenges in this area. The physically based Water Simulation Model WaSiM Vers. 2 (Schulla & Jasper (1999)) is setup to model current and projected future hydrological conditions. The availability of measured meteorological and hydrological data is poor as common to many Mediterranean catchments. The lack of available measured input data hampers the calibration of the model setup and the validation of model outputs. WaSiM was driven with meteorological forcing taken from 4 different ENSEMBLES climate projections for a reference (1971-2000) and a future (2041-2070) times series. State of the art remote sensing techniques and field measuring techniques were applied to improve the quality of hydrological input parameters. For the parameterization of the vegetation the Leaf Area Index (LAI) is a crucial component. However, the LAI is difficult to access at field scale, hence a simple remote sensing approach, using the Normalized Difference Vegetation Index (NDVI) and MODIS LAI information, was applied for the parameterization in WaSiM. As no permanent streams, hence no discharge measurements, exist in the Gaza Strip, the actual evapotranspiration (ETact) outputs of the model were used for model validation. Landsat TM images were applied to calculate the actual monthly mean ETact rates using the triangle method (Jiang and Islam, 1999). Simulated spatial ETact patterns and those derived from remote sensing show a good fit especially for the growing season.

Estimated winter wheat yield from crop growth predicted by LANDSAT

NASA Technical Reports Server (NTRS)

Kanemasu, E. T.

1977-01-01

An evapotranspiration and growth model for winter wheat is reported. The inputs are daily solar radiation, maximum temperature, minimum temperature, precipitation/irrigation and leaf area index. The meteorological data were obtained from National Weather Service while LAI was obtained from LANDSAT multispectral scanner. The output provides daily estimates of potential evapotranspiration, transpiration, evaporation, soil moisture (50 cm depth), percentage depletion, net photosynthesis and dry matter production. Winter wheat yields are correlated with transpiration and dry matter accumulation.

Latin American Network of students in Atmospheric Sciences and Meteorology

NASA Astrophysics Data System (ADS)

Cuellar-Ramirez, P.

2017-12-01

The Latin American Network of Students in Atmospheric Sciences and Meteorology (RedLAtM) is a civil nonprofit organization, organized by students from Mexico and some Latin- American countries. As a growing organization, providing human resources in the field of meteorology at regional level, the RedLAtM seeks to be a Latin American organization who helps the development of education and research in Atmospheric Sciences and Meteorology in order to engage and promote the integration of young people towards a common and imminent future: Facing the still unstudied various weather and climate events occurring in Latin America. The RedLAtM emerges from the analysis and observation/realization of a limited connection between Latin American countries around research in Atmospheric Sciences and Meteorology. The importance of its creation is based in cooperation, linking, research and development in Latin America and Mexico, in other words, to join efforts and stablish a regional scientific integration who leads to technological progress in the area of Atmospheric Sciences and Meteorology. As ultimate goal the RedLAtM pursuit to develop climatic and meteorological services for those countries unable to have their own programs, as well as projects linked with the governments of Latin American countries and private companies for the improvement of prevention strategies, research and decision making. All this conducing to enhance the quality of life of its inhabitants facing problems such as poverty and inequality.

Long-term hydrometeorological trends in the Midwest region based on a century long gridded hydrometeorological dataset and simulations from a macro-scale hydrology model

NASA Astrophysics Data System (ADS)

Chiu, C. M.; Hamlet, A. F.

2014-12-01

Climate change is likely to impact the Great Lakes region and Midwest region via changes in Great Lakes water levels, agricultural impacts, river flooding, urban stormwater impacts, drought, water temperature, and impacts to terrestrial and aquatic ecosystems. Self-consistent and temporally homogeneous long-term data sets of precipitation and temperature over the entire Great Lakes region and Midwest regions are needed to provide inputs to hydrologic models, assess historical trends in hydroclimatic variables, and downscale global and regional-scale climate models. To support these needs a new hybrid gridded meteorological forcing dataset at 1/16 degree resolution based on data from co-op station records, the U. S Historical Climatology Network (HCN) , the Historical Canadian Climate Database (HCCD), and Precipitation Regression on Independent Slopes Method (PRISM) has been assembled over the Great Lakes and Midwest region from 1915-2012 at daily time step. These data were then used as inputs to the macro-scale Variable Infiltration Capacity (VIC) hydrology model, implemented over the Midwest and Great Lakes region at 1/16 degree resolution, to produce simulated hydrologic variables that are amenable to long-term trend analysis. Trends in precipitation and temperature from the new meteorological driving data sets, as well as simulated hydrometeorological variables such as snowpack, soil moisture, runoff, and evaporation over the 20th century are presented and discussed.

Analysis of the precipitation and streamflow extremes in Northern Italy using high resolution reanalysis dataset Express-Hydro

NASA Astrophysics Data System (ADS)

Silvestro, Francesco; Parodi, Antonio; Campo, Lorenzo

2017-04-01

The characterization of the hydrometeorological extremes, both in terms of rainfall and streamflow, in a given region plays a key role in the environmental monitoring provided by the flood alert services. In last years meteorological simulations (both near real-time and historical reanalysis) were available at increasing spatial and temporal resolutions, making possible long-period hydrological reanalysis in which the meteo dataset is used as input in distributed hydrological models. In this work, a very high resolution meteorological reanalysis dataset, namely Express-Hydro (CIMA, ISAC-CNR, GAUSS Special Project PR45DE), was employed as input in the hydrological model Continuum in order to produce long time series of streamflows in the Liguria territory, located in the Northern part of Italy. The original dataset covers the whole Europe territory in the 1979-2008 period, at 4 km of spatial resolution and 3 hours of time resolution. Analyses in terms of comparison between the rainfall estimated by the dataset and the observations (available from the local raingauges network) were carried out, and a bias correction was also performed in order to better match the observed climatology. An extreme analysis was eventually carried on the streamflows time series obtained by the simulations, by comparing them with the results of the same hydrological model fed with the observed time series of rainfall. The results of the analysis are shown and discussed.

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.

The U.S. Geological Survey Monthly Water Balance Model Futures Portal

USGS Publications Warehouse

Bock, Andrew R.; Hay, Lauren E.; Markstrom, Steven L.; Emmerich, Christopher; Talbert, Marian

2017-05-03

The U.S. Geological Survey Monthly Water Balance Model Futures Portal (https://my.usgs.gov/mows/) is a user-friendly interface that summarizes monthly historical and simulated future conditions for seven hydrologic and meteorological variables (actual evapotranspiration, potential evapotranspiration, precipitation, runoff, snow water equivalent, atmospheric temperature, and streamflow) at locations across the conterminous United States (CONUS).The estimates of these hydrologic and meteorological variables were derived using a Monthly Water Balance Model (MWBM), a modular system that simulates monthly estimates of components of the hydrologic cycle using monthly precipitation and atmospheric temperature inputs. Precipitation and atmospheric temperature from 222 climate datasets spanning historical conditions (1952 through 2005) and simulated future conditions (2020 through 2099) were summarized for hydrographic features and used to drive the MWBM for the CONUS. The MWBM input and output variables were organized into an open-access database. An Open Geospatial Consortium, Inc., Web Feature Service allows the querying and identification of hydrographic features across the CONUS. To connect the Web Feature Service to the open-access database, a user interface—the Monthly Water Balance Model Futures Portal—was developed to allow the dynamic generation of summary files and plots  based on plot type, geographic location, specific climate datasets, period of record, MWBM variable, and other options. Both the plots and the data files are made available to the user for download 

Comparison of artificial intelligence methods and empirical equations to estimate daily solar radiation

NASA Astrophysics Data System (ADS)

Mehdizadeh, Saeid; Behmanesh, Javad; Khalili, Keivan

2016-08-01

In the present research, three artificial intelligence methods including Gene Expression Programming (GEP), Artificial Neural Networks (ANN) and Adaptive Neuro-Fuzzy Inference System (ANFIS) as well as, 48 empirical equations (10, 12 and 26 equations were temperature-based, sunshine-based and meteorological parameters-based, respectively) were used to estimate daily solar radiation in Kerman, Iran in the period of 1992-2009. To develop the GEP, ANN and ANFIS models, depending on the used empirical equations, various combinations of minimum air temperature, maximum air temperature, mean air temperature, extraterrestrial radiation, actual sunshine duration, maximum possible sunshine duration, sunshine duration ratio, relative humidity and precipitation were considered as inputs in the mentioned intelligent methods. To compare the accuracy of empirical equations and intelligent models, root mean square error (RMSE), mean absolute error (MAE), mean absolute relative error (MARE) and determination coefficient (R2) indices were used. The results showed that in general, sunshine-based and meteorological parameters-based scenarios in ANN and ANFIS models presented high accuracy than mentioned empirical equations. Moreover, the most accurate method in the studied region was ANN11 scenario with five inputs. The values of RMSE, MAE, MARE and R2 indices for the mentioned model were 1.850 MJ m-2 day-1, 1.184 MJ m-2 day-1, 9.58% and 0.935, respectively.

Describing Ecosystem Complexity through Integrated Catchment Modeling

NASA Astrophysics Data System (ADS)

Shope, C. L.; Tenhunen, J. D.; Peiffer, S.

2011-12-01

Land use and climate change have been implicated in reduced ecosystem services (ie: high quality water yield, biodiversity, and agricultural yield. The prediction of ecosystem services expected under future land use decisions and changing climate conditions has become increasingly important. Complex policy and management decisions require the integration of physical, economic, and social data over several scales to assess effects on water resources and ecology. Field-based meteorology, hydrology, soil physics, plant production, solute and sediment transport, economic, and social behavior data were measured in a South Korean catchment. A variety of models are being used to simulate plot and field scale experiments within the catchment. Results from each of the local-scale models provide identification of sensitive, local-scale parameters which are then used as inputs into a large-scale watershed model. We used the spatially distributed SWAT model to synthesize the experimental field data throughout the catchment. The approach of our study was that the range in local-scale model parameter results can be used to define the sensitivity and uncertainty in the large-scale watershed model. Further, this example shows how research can be structured for scientific results describing complex ecosystems and landscapes where cross-disciplinary linkages benefit the end result. The field-based and modeling framework described is being used to develop scenarios to examine spatial and temporal changes in land use practices and climatic effects on water quantity, water quality, and sediment transport. Development of accurate modeling scenarios requires understanding the social relationship between individual and policy driven land management practices and the value of sustainable resources to all shareholders.

Evaluating the Credibility of Transport Processes in Simulations of Ozone Recovery using the Global Modeling Initiative Three-dimensional Model

NASA Technical Reports Server (NTRS)

Strahan, Susan E.; Douglass, Anne R.

2004-01-01

The Global Modeling Initiative (GMI) has integrated two 36-year simulations of an ozone recovery scenario with an offline chemistry and tra nsport model using two different meteorological inputs. Physically ba sed diagnostics, derived from satellite and aircraft data sets, are d escribed and then used to evaluate the realism of temperature and transport processes in the simulations. Processes evaluated include barri er formation in the subtropics and polar regions, and extratropical w ave-driven transport. Some diagnostics are especially relevant to sim ulation of lower stratospheric ozone, but most are applicable to any stratospheric simulation. The global temperature evaluation, which is relevant to gas phase chemical reactions, showed that both sets of me teorological 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 g eneral circulation model (GMI(GCM)) showed a very good residual circulation in the tropics and Northern Hemisphere. The simulation with inp ut from a data assimilation system (GMI(DAS)) performed better in the midlatitudes than it did 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 GML(GCM) has greater fidelity throughout the stratosphere tha n it does in the GMI(DAS)

An Investigation of Turbulent Heat Exchange in the Subtropics

DTIC Science & Technology

2014-09-30

meteorological sensors aboard the research vessel the R/V Revelle during the DYNAMO field program. In situ meteorology and high-rate flux sensors operated...continuously while in the sampling period for DYNAMO Leg 3. This included all sensors operating during Leg 2 with the addition of a closed-path LI...stress; wave data; surface and near surface sea temperatures, salinity and currents; and other key variables specifically requested by DYNAMO /LASP PIs

Spatial optimization of an ideal wind energy system as a response to the intermittency of renewable energies?

NASA Astrophysics Data System (ADS)

Lassonde, Sylvain; Boucher, Olivier; Breon, François-Marie; Tobin, Isabelle; Vautard, Robert

2016-04-01

The share of renewable energies in the mix of electricity production is increasing worldwide. This trend is driven by environmental and economic policies aiming at a reduction of greenhouse gas emissions and an improvement of energy security. It is expected to continue in the forthcoming years and decades. Electricity production from renewables is related to weather and climate factors such as the diurnal and seasonal cycles of sunlight and wind, but is also linked to variability on all time scales. The intermittency in the renewable electricity production (solar, wind power) could eventually hinder their future deployment. Intermittency is indeed a challenge as demand and supply of electricity need to be balanced at any time. This challenge can be addressed by the deployment of an overcapacity in power generation (from renewable and/or thermal sources), a large-scale energy storage system and/or improved management of the demand. The main goal of this study is to optimize a hypothetical renewable energy system at the French and European scales in order to investigate if spatial diversity of the production (here electricity from wind energy) could be a response to the intermittency. We use ECMWF (European Centre for Medium-Range Weather Forecasts) ERA-interim meteorological reanalysis and meteorological fields from the Weather Research and Forecasts (WRF) model to estimate the potential for wind power generation. Electricity demand and production are provided by the French electricity network (RTE) at the scale of administrative regions for years 2013 and 2014. Firstly we will show how the simulated production of wind power compares against the measured production at the national and regional scale. Several modelling and bias correction methods of wind power production will be discussed. Secondly, we will present results from an optimization procedure that aims to minimize some measure of the intermittency of wind energy. For instance we estimate the optimal distribution between French regions (with or without cross-border inputs) that minimizes the impact of low-production periods computed in a running mean sense and its sensitivity to the period considered. We will also assess which meteorological situations are the most problematic over the 35-year ERA-interim climatology(1980-2015).

A climatological description of the Savannah River Site

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

Hunter, C.H.

1990-05-22

This report provides a general climatological description of the Savannah River Site. The description provides both regional and local scale climatology. The regional climatology includes a general regional climatic description and presents information on occurrence frequencies of the severe meteorological phenomena that are important considerations in the design and siting of a facility. These phenomena include tornadoes, thunderstorms, hurricanes, and ice/snow storms. Occurrence probabilities given for extreme tornado and non-tornado winds are based on previous site specific studies. Local climatological conditions that are significant with respect to the impact of facility operations on the environment are described using on-site ormore » near-site meteorological data. Summaries of wind speed, wind direction, and atmospheric stability are primarily based on the most recently generated five-year set of data collected from the onsite meteorological tower network (1982--86). Temperature, humidity, and precipitation summaries include data from SRL's standard meteorological instrument shelter and the Augusta National Weather Service office at Bush Field through 1986. A brief description of the onsite meteorological monitoring program is also provided. 24 refs., 15 figs., 22 tabs.« less

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

A Comparative Model of Field Investigations: Aligning School Science Inquiry with the Practices of Contemporary Science

ERIC Educational Resources Information Center

Windschitl, Mark; Dvornich, Karen; Ryken, Amy E.; Tudor, Margaret; Koehler, Gary

2007-01-01

Field investigations are not characterized by randomized and manipulated control group experiments; however, most school science and high-stakes tests recognize only this paradigm of investigation. Scientists in astronomy, genetics, field biology, oceanography, geology, and meteorology routinely select naturally occurring events and conditions and…

Three-dimensional aspects of radiative transfer in remote sensing of precipitation: Application to the 1986 COHMEX storm

NASA Technical Reports Server (NTRS)

Haferman, J. L.; Krajewski, W. F.; Smith, T. F.

1994-01-01

Several multifrequency techniques for passive microwave estimation of precipitation based on the absorption and scattering properties of hydrometers have been proposed in the literature. In the present study, plane-parallel limitations are overcome by using a model based on the discrete-ordinates method to solve the radiative transfer equation in three-dimensional rectangular domains. This effectively accounts for the complexity and variety of radiation problems encountered in the atmosphere. This investigation presents result for plane-parallel and three-dimensional radiative transfer for a precipitating system, discusses differences between these results, and suggests possible explanations for these differences. Microphysical properties were obtained from the Colorado State University Regional Atmospehric Modeling System and represent a hailstorm observed during the 1986 Cooperative Huntsville Meteorological Experiment. These properties are used as input to a three-dimensional radiative transfer model in order to simulate satellite observation of the storm. The model output consists of upwelling brightness temperatures at several of the frequencies on the Special Sensor Microwave/Imager. The radiative transfer model accounts for scattering and emission of atmospheric gases and hydrometers in liquid and ice phases. Brightness temperatures obtained from the three-dimensional model of this investigation indicate that horizontal inhomogeneities give rise to brightness temperature fields that can be quite different from fields obtained using plane-parallel radiative transfer theory. These differences are examined for various resolutions of the satellite sensor field of view. In adddition, the issue of boundary conditions for three-dimensional atmospheric radiative transfer is addressed.

An operational search and rescue model for the Norwegian Sea and the North Sea

NASA Astrophysics Data System (ADS)

Breivik, Øyvind; Allen, Arthur A.

A new operational, ensemble-based search and rescue model for the Norwegian Sea and the North Sea is presented. The stochastic trajectory model computes the net motion of a range of search and rescue objects. A new, robust formulation for the relation between the wind and the motion of the drifting object (termed the leeway of the object) is employed. Empirically derived coefficients for 63 categories of search objects compiled by the US Coast Guard are ingested to estimate the leeway of the drifting objects. A Monte Carlo technique is employed to generate an ensemble that accounts for the uncertainties in forcing fields (wind and current), leeway drift properties, and the initial position of the search object. The ensemble yields an estimate of the time-evolving probability density function of the location of the search object, and its envelope defines the search area. Forcing fields from the operational oceanic and atmospheric forecast system of The Norwegian Meteorological Institute are used as input to the trajectory model. This allows for the first time high-resolution wind and current fields to be used to forecast search areas up to 60 h into the future. A limited set of field exercises show good agreement between model trajectories, search areas, and observed trajectories for life rafts and other search objects. Comparison with older methods shows that search areas expand much more slowly using the new ensemble method with high resolution forcing fields and the new leeway formulation. It is found that going to higher-order stochastic trajectory models will not significantly improve the forecast skill and the rate of expansion of search areas.

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

Greenberg, Jim; Penuelas, J.; Guenther, Alex B.

To survey landscape-scale fluxes of biogenic gases, a100-meterTeflon tube was attached to a tethered balloon as a sampling inlet for a fast response Proton Transfer Reaction Mass Spectrometer (PTRMS). Along with meteorological instruments deployed on the tethered balloon and at 3-mand outputs from a regional weather model, these observations were used to estimate landscape scale biogenic volatile organic compound fluxes with two micrometeorological techniques: mixed layer variance and surface layer gradients. This highly mobile sampling system was deployed at four field sites near Barcelona to estimate landscape-scale BVOC emission factors in a relatively short period (3 weeks). The two micrometeorologicalmore » techniques agreed within the uncertainty of the flux measurements at all four sites even though the locations had considerable heterogeneity in species distribution and complex terrain. The observed fluxes were significantly different than emissions predicted with an emission model using site-specific emission factors and land-cover characteristics. Considering the wide range in reported BVOC emission factors of VOCs for individual vegetation species (more than an order of magnitude), this flux estimation technique is useful for constraining BVOC emission factors used as model inputs.« less

A Robust Kalman Framework with Resampling and Optimal Smoothing

PubMed Central

Kautz, Thomas; Eskofier, Bjoern M.

2015-01-01

The Kalman filter (KF) is an extremely powerful and versatile tool for signal processing that has been applied extensively in various fields. We introduce a novel Kalman-based analysis procedure that encompasses robustness towards outliers, Kalman smoothing and real-time conversion from non-uniformly sampled inputs to a constant output rate. These features have been mostly treated independently, so that not all of their benefits could be exploited at the same time. Here, we present a coherent analysis procedure that combines the aforementioned features and their benefits. To facilitate utilization of the proposed methodology and to ensure optimal performance, we also introduce a procedure to calculate all necessary parameters. Thereby, we substantially expand the versatility of one of the most widely-used filtering approaches, taking full advantage of its most prevalent extensions. The applicability and superior performance of the proposed methods are demonstrated using simulated and real data. The possible areas of applications for the presented analysis procedure range from movement analysis over medical imaging, brain-computer interfaces to robot navigation or meteorological studies. PMID:25734647

Energetics of the April 2000 magnetic superstorm observed by DMSP

NASA Astrophysics Data System (ADS)

Burke, William J.; Huang, Cheryl Y.; Rich, Frederick J.

2006-01-01

During the late main phase of the April 6, 2000 storm with Dst approaching -300 nT, four Defense Meteorological Satellite Program (DMSP) satellites encountered repeated episodes of intense field-aligned currents whose magnetic perturbations exceeded 1300 nT, corresponding to |J∥| > 1 A/m. They had relatively fast rise times (˜5 min) and lasted for ˜20 min. The large magnetic perturbations occurred within the expanded auroral oval at magnetic latitudes below 60°. From Poynting-flux calculations we estimate that during each event several hundred tera-Joules of energy that dissipates in the mid-latitude ionosphere and thermosphere. Ground magnetometers at auroral and middle latitudes detected weak fluctuations that were incommensurate with magnetic perturbations observations at DMSP altitudes. Observed discrepancies between ground and satellite magnetometer measurements suggest that under storm conditions operational models systematically underestimate the level of electromagnetic energy available to the ionosphere thermosphere. We demonstrate a transmission-line model for M-I coupling that allows calculations of this electromagnetic energy input with no a priori knowledge of ionospheric conductances.

What is the relative role of initial hydrological conditions and meteorological forcing to the seasonal hydrological forecasting skill? Analysis along Europe's hydro-climatic gradient

NASA Astrophysics Data System (ADS)

Pechlivanidis, Ilias; Crochemore, Louise

2017-04-01

Recent advances in understanding and forecasting of climate have led into skilful seasonal meteorological predictions, which can consequently increase the confidence of hydrological prognosis. The majority of seasonal impact modelling has commonly been conducted at only one or a limited number of basins limiting the potential to understand large systems. Nevertheless, there is a necessity to develop operational seasonal forecasting services at the pan-European scale, capable of addressing the end-user needs. The skill of such forecasting services is subject to a number of sources of uncertainty, i.e. model structure, parameters, and forcing input. In here, we complement the "deep" knowledge from basin based modelling by investigating the relative contributions of initial hydrological conditions (IHCs) and meteorological forcing (MF) to the skill of a seasonal pan-European hydrological forecasting system. We use the Ensemble Streamflow Prediction (ESP) and reverse ESP (revESP) procedure to show a proxy of hydrological forecasting uncertainty due to MF and IHC uncertainties respectively. We further calculate the critical lead time (CLT), as a proxy of the river memory, after which the importance of MFs surpasses the importance of IHCs. We analyze these results in the context of prevailing hydro-climatic conditions for about 35000 European basins. Both model state initialisation (level in surface water, i.e. reservoirs, lakes and wetlands, soil moisture, snow depth) and provision of climatology are based on forcing input derived from the WFDEI product for the period 1981-2010. The analysis shows that the contribution of ICs and MFs to the hydrological forecasting skill varies considerably according to location, season and lead time. This analysis allows clustering of basins in which hydrological forecasting skill may be improved by better estimation of IHCs, e.g. via data assimilation of in-situ and/or satellite observations; whereas in other basins skill improvement depends on better MFs.

Impact of meteorological data resolution on the forecasted ozone concentrations during the ESCOMPTE IOP2a and IOP2b

NASA Astrophysics Data System (ADS)

Menut, Laurent; Coll, Isabelle; Cautenet, Sylvie

2005-03-01

During the summer 2001, several photo-oxidant pollution episodes were documented around Marseilles-Fos-Berre in the South of France within the framework of the ESCOMPTE campaign. The site is composed of large cities (Marseilles, Aix, and Toulon), significant factories (Fos-Berre), a dense road network, and extensive rural area. Both biogenic and anthropogenic emissions are thus significative. Located close to the Mediterranean Sea and framed by the Pyrenees and the Alps Mountains, pollutant concentrations are under the influence of strong emissions as well as a complex meteorology. During the whole summer 2001, the chemistry-transport model CHIMERE was used to forecast pollutant concentrations. The ECMWF forecast meteorological fields were used as forcing, with a raw spatial and temporal resolution of 0.5° and 3 h, respectively. It was observed that even if the synoptic dynamic processes were correctly described, the resolution was not always able to detail small-scale dynamics (sea breezes and orographical winds). To estimate the impact of meteorological forcing on the modeled concentration accuracy, an intercomparison exercise has thus been carried out on the same episode but with two sets of meteorological data: ECMWF data (with horizontal and temporal resolution of 0.5° and 3 h) and data from the mesoscale model RAMS (3 km and 1 h). The two sets of meteorological data are compared and discussed in terms of raw differences as a function of time and location, and in terms of induced discrepancies between the modeled and observed ozone concentration fields. It was shown that even if the RAMS model provides a better description of land-sea breezes and nocturnal boundary layer processes, the simulated ozone time series are satisfactory with the two meteorological forcings. In the context of ozone forecast, the scores are better with ECMWF. This is attributed to the diffusive aspect of these data that will more easily catch localized peaks, while a small error in wind speed or direction in RAMS will misplace the ozone plume.

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.

Prediction of Chl-a concentrations in an eutrophic lake using ANN models with hybrid inputs

NASA Astrophysics Data System (ADS)

Aksoy, A.; Yuzugullu, O.

2017-12-01

Chlorophyll-a (Chl-a) concentrations in water bodies exhibit both spatial and temporal variations. As a result, frequent sampling is required with higher number of samples. This motivates the use of remote sensing as a monitoring tool. Yet, prediction performances of models that convert radiance values into Chl-a concentrations can be poor in shallow lakes. In this study, Chl-a concentrations in Lake Eymir, a shallow eutrophic lake in Ankara (Turkey), are determined using artificial neural network (ANN) models that use hybrid inputs composed of water quality and meteorological data as well as remotely sensed radiance values to improve prediction performance. Following a screening based on multi-collinearity and principal component analysis (PCA), dissolved-oxygen concentration (DO), pH, turbidity, and humidity were selected among several parameters as the constituents of the hybrid input dataset. Radiance values were obtained from QuickBird-2 satellite. Conversion of the hybrid input into Chl-a concentrations were studied for two different periods in the lake. ANN models were successful in predicting Chl-a concentrations. Yet, prediction performance declined for low Chl-a concentrations in the lake. In general, models with hybrid inputs were superior over the ones that solely used remotely sensed data.

Probabilistic estimation of residential air exchange rates for ...

EPA Pesticide Factsheets

Residential air exchange rates (AERs) are a key determinant in the infiltration of ambient air pollution indoors. Population-based human exposure models using probabilistic approaches to estimate personal exposure to air pollutants have relied on input distributions from AER measurements. An algorithm for probabilistically estimating AER was developed based on the Lawrence Berkley National Laboratory Infiltration model utilizing housing characteristics and meteorological data with adjustment for window opening behavior. The algorithm was evaluated by comparing modeled and measured AERs in four US cities (Los Angeles, CA; Detroit, MI; Elizabeth, NJ; and Houston, TX) inputting study-specific data. The impact on the modeled AER of using publically available housing data representative of the region for each city was also assessed. Finally, modeled AER based on region-specific inputs was compared with those estimated using literature-based distributions. While modeled AERs were similar in magnitude to the measured AER they were consistently lower for all cities except Houston. AERs estimated using region-specific inputs were lower than those using study-specific inputs due to differences in window opening probabilities. The algorithm produced more spatially and temporally variable AERs compared with literature-based distributions reflecting within- and between-city differences, helping reduce error in estimates of air pollutant exposure. Published in the Journal of

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.

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

Model study of meteorology and photochemical air pollution over un urban area in south-eastern France (ESCOMPTE campaign).

NASA Astrophysics Data System (ADS)

Taghavi, M.; Cautenet, S.

2003-04-01

The ESCOMPTE Campaign has been conducted over Southern France (Provence region including the Marseille, Aix and Toulon cities and the Fos-Berre industrial center) in June and July of 2001. In order to study the redistribution of the pollutants emitted by anthropic and biogenic emissions and their impact on the atmospheric chemistry, we used meso-scale modeling (RAMS model, paralleled version 4.3, coupled on line with chemical modules : MOCA2.2 (Poulet et al, 2002) including 29 gaseous species). The hourly high resolution emissions were obtained from ESCOMPTE database (Ponche et al, 2002). The model was coupled with the dry deposition scheme (Walmsley and Weseley,1996). In this particular case of complex circulation (sea breeze associated with topography), the processes involving peaks of pollution were strongly non linear, and the meso scale modeling coupled on line with chemistry module was an essential step for a realistic redistribution of chemical species. Two nested grids satisfactorily describe the synoptic dynamics and the sea breeze circulations. The ECMWF meteorological fields provide the initial and boundary conditions. Different events characterized by various meteorological situations were simulated. Meteorological fields retrieved by modeling, also Modeled ozone, NOx, CO and SO2 concentrations, were compared with balloons, lidars, aircrafts and surface stations measurements. The chemistry regimes were explained according to the distribution of plumes. The stratified layers were examined.

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

Modeling sulfur dioxide concentrations in Mt. Rainier area during prevent

NASA Astrophysics Data System (ADS)

Givati, Reuven; Flocchini, Robert G.; Cahill, Thomas A.

The MATHEW/ADPIC models (a diagnostic wind model and a particle model) which were developed at Lawrence Livermore National Laboratory, were used to compute SO 2 concentrations in the Mt Rainier area during PREVENT (Pacific Northwest Regional Visibility Experiment Using Natural Tracers, June to September 1990). The modeled concentrations were compared to measured concentrations at two sampling locations (Tahoma Woods and Paradise near Mt Rainier) which are located in a valley. The SO 2 sources considered are located along the Puget Sound (Everett, Seattle and Tacoma area) and south of it. New formulations were included in the models for the oxidation of SO 2 and the interpolation of the wind field. Because of the paucity of the meteorological data near the sampling points, an estimation was made of the wind values in the valley, based on the phenomena of wind channeling, mountain and valley winds, and historical wind observations near Mt Rainier. The models were run for several non-rainy days during the PREVENT period when large SO 2 concentrations were observed, and for other special cases. Out of 14 days for which the emissions of the previous night were taken into account, for 12 days the ratio of the modeled to the measured SO 2 concentrations at Tahoma Woods during the daytime, was in the interval 0.45-2.00, considered a good agreement. However, the agreement at Tahoma Woods during the night, and at Paradise during the day and the night, were not as good. It seems that the wind flow near Tahoma Woods under the stable conditions at night, and near the steep terrain of Paradise, were not modeled correctly, with the limited input of available meteorological observations.

Spatial variability in airborne bacterial communities across land-use types and their relationship to the bacterial communities of potential source environments

PubMed Central

Bowers, Robert M; McLetchie, Shawna; Knight, Rob; Fierer, Noah

2011-01-01

Although bacteria are ubiquitous in the near-surface atmosphere and they can have important effects on human health, airborne bacteria have received relatively little attention and their spatial dynamics remain poorly understood. Owing to differences in meteorological conditions and the potential sources of airborne bacteria, we would expect the atmosphere over different land-use types to harbor distinct bacterial communities. To test this hypothesis, we sampled the near-surface atmosphere above three distinct land-use types (agricultural fields, suburban areas and forests) across northern Colorado, USA, sampling five sites per land-use type. Microbial abundances were stable across land-use types, with ∼105–106 bacterial cells per m3 of air, but the concentrations of biological ice nuclei, determined using a droplet freezing assay, were on average two and eight times higher in samples from agricultural areas than in the other two land-use types. Likewise, the composition of the airborne bacterial communities, assessed via bar-coded pyrosequencing, was significantly related to land-use type and these differences were likely driven by shifts in the sources of bacteria to the atmosphere across the land-uses, not local meteorological conditions. A meta-analysis of previously published data shows that atmospheric bacterial communities differ from those in potential source environments (leaf surfaces and soils), and we demonstrate that we may be able to use this information to determine the relative inputs of bacteria from these source environments to the atmosphere. This work furthers our understanding of bacterial diversity in the atmosphere, the terrestrial controls on this diversity and potential approaches for source tracking of airborne bacteria. PMID:21048802

The Value of Humans in the Operational River Forecasting Enterprise

NASA Astrophysics Data System (ADS)

Pagano, T. C.

2012-04-01

The extent of human control over operational river forecasts, such as by adjusting model inputs and outputs, varies from nearly completely automated systems to those where forecasts are generated after discussion among a group of experts. Historical and realtime data availability, the complexity of hydrologic processes, forecast user needs, and forecasting institution support/resource availability (e.g. computing power, money for model maintenance) influence the character and effectiveness of operational forecasting systems. Automated data quality algorithms, if used at all, are typically very basic (e.g. checks for impossible values); substantial human effort is devoted to cleaning up forcing data using subjective methods. Similarly, although it is an active research topic, nearly all operational forecasting systems struggle to make quantitative use of Numerical Weather Prediction model-based precipitation forecasts, instead relying on the assessment of meteorologists. Conversely, while there is a strong tradition in meteorology of making raw model outputs available to forecast users via the Internet, this is rarely done in hydrology; Operational river forecasters express concerns about exposing users to raw guidance, due to the potential for misinterpretation and misuse. However, this limits the ability of users to build their confidence in operational products through their own value-added analyses. Forecasting agencies also struggle with provenance (i.e. documenting the production process and archiving the pieces that went into creating a forecast) although this is necessary for quantifying the benefits of human involvement in forecasting and diagnosing weak links in the forecasting chain. In hydrology, the space between model outputs and final operational products is nearly unstudied by the academic community, although some studies exist in other fields such as meteorology.

Estimating inter-annual diversity of seasonal agricultural area using multi-temporal resourcesat data.

PubMed

Sreenivas, K; Sekhar, N Seshadri; Saxena, Manoj; Paliwal, R; Pathak, S; Porwal, M C; Fyzee, M A; Rao, S V C Kameswara; Wadodkar, M; Anasuya, T; Murthy, M S R; Ravisankar, T; Dadhwal, V K

2015-09-15

The present study aims at analysis of spatial and temporal variability in agricultural land cover during 2005-6 and 2011-12 from an ongoing program of annual land use mapping using multidate Advanced Wide Field Sensor (AWiFS) data aboard Resourcesat-1 and 2. About 640-690 multi-temporal AWiFS quadrant data products per year (depending on cloud cover) were co-registered and radiometrically normalized to prepare state (administrative unit) mosaics. An 18-fold classification was adopted in this project. Rule-based techniques along with maximum-likelihood algorithm were employed to deriving land cover information as well as changes within agricultural land cover classes. The agricultural land cover classes include - kharif (June-October), rabi (November-April), zaid (April-June), area sown more than once, fallow lands and plantation crops. Mean kappa accuracy of these estimates varied from 0.87 to 0.96 for various classes. Standard error of estimate has been computed for each class annually and the area estimates were corrected using standard error of estimate. The corrected estimates range between 99 and 116 Mha for kharif and 77-91 Mha for rabi. The kharif, rabi and net sown area were aggregated at 10 km × 10 km grid on annual basis for entire India and CV was computed at each grid cell using temporal spatially-aggregated area as input. This spatial variability of agricultural land cover classes was analyzed across meteorological zones, irrigated command areas and administrative boundaries. The results indicate that out of various states/meteorological zones, Punjab was consistently cropped during kharif as well as rabi seasons. Out of all irrigated commands, Tawa irrigated command was consistently cropped during rabi season. Copyright © 2014 Elsevier Ltd. All rights reserved.

Data collection handbook to support modeling the impacts of radioactive material in soil

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

Yu, C.; Cheng, J.J.; Jones, L.G.

1993-04-01

A pathway analysis computer code called RESRAD has been developed for implementing US Department of Energy Residual Radioactive Material Guidelines. Hydrogeological, meteorological, geochemical, geometrical (size, area, depth), and material-related (soil, concrete) parameters are used in the RESRAD code. This handbook discusses parameter definitions, typical ranges, variations, measurement methodologies, and input screen locations. Although this handbook was developed primarily to support the application of RESRAD, the discussions and values are valid for other model applications.

Modeling Circulation along the Vietnamese Coast Influenced by Monsoon Variability in Meteorology, River Discharge and Interactions with the Vietnamese East Sea

DTIC Science & Technology

2012-09-30

input data and making choices on the configuration of the regional VES model. Details on the domain for the nested/ downscaled shelf model with follow...microwave satellite radiometer data (which are unaffected by cloud) blended with high resolution infrared imagery and found this a useful data set for...variational methods for the assimilation of satellite and in situ observations to achieve improved state estimation and subsequent forecast skill in real

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.

The FALL3D Ash Cloud Dispersion Model and its Implementation at the Buenos Aires VAAC

NASA Astrophysics Data System (ADS)

Folch, A.; Suaya, M.; Costa, A.; Viramonte, J.

2009-12-01

Airborne volcanic ash and aerosols threat aerial navigation and affect the quality of air at medium to large distances downwind from the volcano. Airplane re-routing and airport disruption carry important socioeconomic consequences at regional and national levels. Models to forecast volcanic ash clouds constitute, together with satellite imagery, a valuable predictive tool during a crisis. FALL3D is an Eulerian ash cloud dispersion model based on the advection-diffusion-sedimentation equation. The model runs at any scale, from regional to global. The dispersion model is off-line coupled with global (e.g. GFS, NMM-b) and mesoscalar (e.g. NMM-b, WRF, ETA) meteorological models and with re-analysis datasets. FALL3D has been recently installed at the Buenos Aires VAAC, depending on the Argentinean National Meteorological Service (SMN). In this presentation we summarize the characteristics of the model and its implementation at the VAAC, including the different domains, the meteorological forecast inputs (ETA or GFS) and the scenarios assumed for some critical volcanoes (Chaitén, Llaima, Lascar, etc.). Pre-defined scenarios are necessary to give an early first order prediction when data is poor or unavailable. This is particularly critical in Central Andes, were most active volcanoes are located in remote areas with poor or inexistent monitoring.

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.

Physical Processes Governing Atmospheric Trace Constituents Measured from an Aircraft on PEM-Tropics

NASA Technical Reports Server (NTRS)

Newell, Reginald E.; Hoell, James M., Jr. (Technical Monitor)

2001-01-01

Before the mission, the PI (principal investigator) was instrumental in securing real-time use of the new 51-level ECMWF (European Centre for Medium Range Weather Forecasts) meteorological data. During the mission, he provided flight planning and execution guidance as meteorologist for the P-3B. Mr. Yong Zhu computed and plotted meteorological forecast maps using the ECMWF data and transmitted them to the field from MIT (Massachusetts Institute of Technology). Dr. John Cho was in the field for the Christmas Island portion to extract data from the on-site NOAA (National Oceanic and Atmospheric Administration) radars for local wind profiles that were used at the flight planning meetings. When the power supply for the VHF radar failed, he assisted the NOAA engineer in its repair. After the mission, Mr. Zhu produced meteorological data memos, which were made available to the PEM (Pacific Exploratory Mission)-Tropics B science team on request. An undergraduate student, Ms. Danielle Morse, wrote memos annotating the cloud conditions seen on the aircraft external monitor video tapes. Dr. Cho and the PI circulated a memo regarding the status (and associated problems) of the meteorological measurement systems on the DC-8 and P-3B to the relevant people on the science team. Several papers by members of our project were completed and accepted by JGR (Journal of Geophysical Research) for the first special section on PEM-Tropics B. These papers included coverage of the following topics: 1) examination of boundary layer data; 2) water vapor transport; 3) tropospheric trace constituent layers; 4) summarizations of the meteorological background and events during PEM-Tropics B; 5) concomitant lidar measurements of ozone, water vapor, and aerosol.

A one-dimensional sectional aerosol model integrated with mesoscale meteorological data to study marine boundary layer aerosol dynamics

NASA Astrophysics Data System (ADS)

Caffrey, Peter F.; Hoppel, William A.; Shi, Jainn J.

2006-12-01

The dynamics of aerosols in the marine boundary layer are simulated with a one-dimensional, multicomponent, sectional aerosol model using vertical profiles of turbulence, relative humidity, temperature, vertical velocity, cloud cover, and precipitation provided by 3-D mesoscale meteorological model output. The Naval Research Laboratory's (NRL) sectional aerosol model MARBLES (Fitzgerald et al., 1998a) was adapted to use hourly meteorological input taken from NRL's Coupled Ocean-Atmosphere Prediction System (COAMPS). COAMPS-generated turbulent mixing coefficients and large-scale vertical velocities determine vertical exchange within the marine boundary layer and exchange with the free troposphere. Air mass back trajectories were used to define the air column history along which the meteorology was retrieved for use with the aerosol model. Details on the integration of these models are described here, as well as a description of improvements made to the aerosol model, including transport by large-scale vertical motions (such as subsidence and lifting), a revised sea-salt aerosol source function, and separate tracking of sulfate mass from each of the five sources (free tropospheric, nucleated, condensed from gas phase oxidation products, cloud-processed, and produced from heterogeneous oxidation of S(IV) on sea-salt aerosol). Results from modeling air masses arriving at Oahu, Hawaii, are presented, and the relative contribution of free-tropospheric sulfate particles versus sea-salt aerosol from the surface to CCN concentrations is discussed. Limitations and benefits of the method are presented, as are sensitivity analyses of the effect of large-scale vertical motions versus turbulent mixing.

Sampling errors in the estimation of empirical orthogonal functions. [for climatology studies

NASA Technical Reports Server (NTRS)

North, G. R.; Bell, T. L.; Cahalan, R. F.; Moeng, F. J.

1982-01-01

Empirical Orthogonal Functions (EOF's), eigenvectors of the spatial cross-covariance matrix of a meteorological field, are reviewed with special attention given to the necessary weighting factors for gridded data and the sampling errors incurred when too small a sample is available. The geographical shape of an EOF shows large intersample variability when its associated eigenvalue is 'close' to a neighboring one. A rule of thumb indicating when an EOF is likely to be subject to large sampling fluctuations is presented. An explicit example, based on the statistics of the 500 mb geopotential height field, displays large intersample variability in the EOF's for sample sizes of a few hundred independent realizations, a size seldom exceeded by meteorological data sets.

Fog Simulations Based on Multi-Model System: A Feasibility Study

NASA Astrophysics Data System (ADS)

Shi, Chune; Wang, Lei; Zhang, Hao; Zhang, Su; Deng, Xueliang; Li, Yaosun; Qiu, Mingyan

2012-05-01

Accurate forecasts of fog and visibility are very important to air and high way traffic, and are still a big challenge. A 1D fog model (PAFOG) is coupled to MM5 by obtaining the initial and boundary conditions (IC/BC) and some other necessary input parameters from MM5. Thus, PAFOG can be run for any area of interest. On the other hand, MM5 itself can be used to simulate fog events over a large domain. This paper presents evaluations of the fog predictability of these two systems for December of 2006 and December of 2007, with nine regional fog events observed in a field experiment, as well as over a large domain in eastern China. Among the simulations of the nine fog events by the two systems, two cases were investigated in detail. Daily results of ground level meteorology were validated against the routine observations at the CMA observational network. Daily fog occurrences for the two study periods was validated in Nanjing. General performance of the two models for the nine fog cases are presented by comparing with routine and field observational data. The results of MM5 and PAFOG for two typical fog cases are verified in detail against field observations. The verifications demonstrated that all methods tended to overestimate fog occurrence, especially for near-fog cases. In terms of TS/ETS, the LWC-only threshold with MM5 showed the best performance, while PAFOG showed the worst. MM5 performed better for advection-radiation fog than for radiation fog, and PAFOG could be an alternative tool for forecasting radiation fogs. PAFOG did show advantages over MM5 on the fog dissipation time. The performance of PAFOG highly depended on the quality of MM5 output. The sensitive runs of PAFOG with different IC/BC showed the capability of using MM5 output to run the 1D model and the high sensitivity of PAFOG on cloud cover. Future works should intensify the study of how to improve the quality of input data (e.g. cloud cover, advection, large scale subsidence) for the 1D model, particularly how to eliminate near-fog case in fog forecasting.

Operational Reconnaissance: Identifying the Right Problems in a Complex World

DTIC Science & Technology

2015-05-23

about the activities and resources of an enemy or rival, or to secure data concerning the meteorological , hydrographic, or geographic characteristics of...Information. Kansas City, KS: Hudson -Kimberly Publishing Co., 1896. War Department. Field Manual (FM) 1-20, Army Air Force Field Manual, Tactics and

Donald Baker | NREL

Science.gov Websites

-7162 Don assists with the installation and maintenance of the NWTC's field test turbines as well as with test article installations and testing in the Structural Testing Laboratory and both dynamometer facilities. He participates in the operation and maintenance of the field test sites and meteorological

Generation and evaluation of typical meteorological year datasets for greenhouse and external conditions on the Mediterranean coast.

PubMed

Fernández, M D; López, J C; Baeza, E; Céspedes, A; Meca, D E; Bailey, B

2015-08-01

A typical meteorological year (TMY) represents the typical meteorological conditions over many years but still contains the short term fluctuations which are absent from long-term averaged data. Meteorological data were measured at the Experimental Station of Cajamar 'Las Palmerillas' (Cajamar Foundation) in Almeria, Spain, over 19 years at the meteorological station and in a reference greenhouse which is typical of those used in the region. The two sets of measurements were subjected to quality control analysis and then used to create TMY datasets using three different methodologies proposed in the literature. Three TMY datasets were generated for the external conditions and two for the greenhouse. They were assessed by using each as input to seven horticultural models and comparing the model results with those obtained by experiment in practical trials. In addition, the models were used with the meteorological data recorded during the trials. A scoring system was used to identify the best performing TMY in each application and then rank them in overall performance. The best methodology was that of Argiriou for both greenhouse and external conditions. The average relative errors between the seasonal values estimated using the 19-year dataset and those using the Argiriou greenhouse TMY were 2.2 % (reference evapotranspiration), -0.45 % (pepper crop transpiration), 3.4 % (pepper crop nitrogen uptake) and 0.8 % (green bean yield). The values obtained using the Argiriou external TMY were 1.8 % (greenhouse reference evapotranspiration), 0.6 % (external reference evapotranspiration), 4.7 % (greenhouse heat requirement) and 0.9 % (loquat harvest date). Using the models with the 19 individual years in the historical dataset showed that the year to year weather variability gave results which differed from the average values by ± 15 %. By comparison with results from other greenhouses it was shown that the greenhouse TMY is applicable to greenhouses which have a solar radiation transmission of approximately 65 % and rely on manual control of ventilation which constitute the majority in the south-east of Spain and in most Mediterranean greenhouse areas.

Generation and evaluation of typical meteorological year datasets for greenhouse and external conditions on the Mediterranean coast

NASA Astrophysics Data System (ADS)

Fernández, M. D.; López, J. C.; Baeza, E.; Céspedes, A.; Meca, D. E.; Bailey, B.

2015-08-01

A typical meteorological year (TMY) represents the typical meteorological conditions over many years but still contains the short term fluctuations which are absent from long-term averaged data. Meteorological data were measured at the Experimental Station of Cajamar `Las Palmerillas' (Cajamar Foundation) in Almeria, Spain, over 19 years at the meteorological station and in a reference greenhouse which is typical of those used in the region. The two sets of measurements were subjected to quality control analysis and then used to create TMY datasets using three different methodologies proposed in the literature. Three TMY datasets were generated for the external conditions and two for the greenhouse. They were assessed by using each as input to seven horticultural models and comparing the model results with those obtained by experiment in practical trials. In addition, the models were used with the meteorological data recorded during the trials. A scoring system was used to identify the best performing TMY in each application and then rank them in overall performance. The best methodology was that of Argiriou for both greenhouse and external conditions. The average relative errors between the seasonal values estimated using the 19-year dataset and those using the Argiriou greenhouse TMY were 2.2 % (reference evapotranspiration), -0.45 % (pepper crop transpiration), 3.4 % (pepper crop nitrogen uptake) and 0.8 % (green bean yield). The values obtained using the Argiriou external TMY were 1.8 % (greenhouse reference evapotranspiration), 0.6 % (external reference evapotranspiration), 4.7 % (greenhouse heat requirement) and 0.9 % (loquat harvest date). Using the models with the 19 individual years in the historical dataset showed that the year to year weather variability gave results which differed from the average values by ± 15 %. By comparison with results from other greenhouses it was shown that the greenhouse TMY is applicable to greenhouses which have a solar radiation transmission of approximately 65 % and rely on manual control of ventilation which constitute the majority in the south-east of Spain and in most Mediterranean greenhouse areas.

Designing Input Fields for Non-Narrative Open-Ended Responses in Web Surveys

PubMed Central

Couper, Mick P.; Kennedy, Courtney; Conrad, Frederick G.; Tourangeau, Roger

2012-01-01

Web surveys often collect information such as frequencies, currency amounts, dates, or other items requiring short structured answers in an open-ended format, typically using text boxes for input. We report on several experiments exploring design features of such input fields. We find little effect of the size of the input field on whether frequency or dollar amount answers are well-formed or not. By contrast, the use of templates to guide formatting significantly improves the well-formedness of responses to questions eliciting currency amounts. For date questions (whether month/year or month/day/year), we find that separate input fields improve the quality of responses over single input fields, while drop boxes further reduce the proportion of ill-formed answers. Drop boxes also reduce completion time when the list of responses is short (e.g., months), but marginally increases completion time when the list is long (e.g., birth dates). These results suggest that non-narrative open questions can be designed to help guide respondents to provide answers in the desired format. PMID:23411468

Development and evaluation of an empirical diurnal sea surface temperature model

NASA Astrophysics Data System (ADS)

Weihs, R. R.; Bourassa, M. A.

2013-12-01

An innovative method is developed to determine the diurnal heating amplitude of sea surface temperatures (SSTs) using observations of high-quality satellite SST measurements and NWP atmospheric meteorological data. The diurnal cycle results from heating that develops at the surface of the ocean from low mechanical or shear produced turbulence and large solar radiation absorption. During these typically calm weather conditions, the absorption of solar radiation causes heating of the upper few meters of the ocean, which become buoyantly stable; this heating causes a temperature differential between the surface and the mixed [or bulk] layer on the order of a few degrees. It has been shown that capturing the diurnal cycle is important for a variety of applications, including surface heat flux estimates, which have been shown to be underestimated when neglecting diurnal warming, and satellite and buoy calibrations, which can be complicated because of the heating differential. An empirical algorithm using a pre-dawn sea surface temperature, peak solar radiation, and accumulated wind stress is used to estimate the cycle. The empirical algorithm is derived from a multistep process in which SSTs from MTG's SEVIRI SST experimental hourly data set are combined with hourly wind stress fields derived from a bulk flux algorithm. Inputs for the flux model are taken from NASA's MERRA reanalysis product. NWP inputs are necessary because the inputs need to incorporate diurnal and air-sea interactive processes, which are vital to the ocean surface dynamics, with a high enough temporal resolution. The MERRA winds are adjusted with CCMP winds to obtain more realistic spatial and variance characteristics and the other atmospheric inputs (air temperature, specific humidity) are further corrected on the basis of in situ comparisons. The SSTs are fitted to a Gaussian curve (using one or two peaks), forming a set of coefficients used to fit the data. The coefficient data are combined with accumulated wind stress and peak solar radiation to create an empirical relationship that approximates physical processes such as turbulence and heating memory (capacity) of the ocean. Weaknesses and strengths of the model, including potential spatial biases, will be discussed.

An Overview of the First International Satellite Land Surface Climatology Project (ISLSCP) Field Experiment (FIFE)

NASA Astrophysics Data System (ADS)

Sellers, P. J.; Hall, F. G.; Asrar, G.; Strebel, D. E.; Murphy, R. E.

1992-11-01

In the summer of 1983 a group of scientists working in the fields of meteorology, biology, and remote sensing met to discuss methods for modeling and observing land-surface—atmosphere interactions on regional and global scales. They concluded, first, that the existing climate models contained poor representations of the processes controlling the exchanges of energy, water, heat, and carbon between the land surface and the atmosphere and, second, that satellite remote sensing had been underutilized as a means of specifying global fields of the governing biophysical parameters. Accordingly, a multiscale, multidisciplinary experiment, FIFE, was initiated to address these two issues. The objectives of FIFE were specified as follows: (1) Upscale integration of models: The experiment was designed to test the soil-plant-atmosphere models developed by biometeorologists for small-scale applications (millimeters to meters) and to develop methods to apply them at the larger scales (kilometers) appropriate to atmospheric models and satellite remote sensing. (2) Application of satellite remote sensing: Even if the first goal were achieved to yield a "perfect" model of vegetation-atmosphere exchanges, it would have very limited applications without a global observing system for initialization and validation. As a result, the experiment was tasked with exploring methods for using satellite data to quantify important biophysical states and rates for model input. The experiment was centered on a 15 × 15 km grassland site near Manhattan, Kansas. This area became the focus for an extended monitoring program of satellite, meteorological, biophysical, and hydrological data acquisition from early 1987 through October 1989 and a series of 12- to 20-day intensive field campaigns (IFCs), four in 1987 and one in 1989. During the IFCs the fluxes of heat, moisture, carbon dioxide, and radiation were measured with surface and airborne equipment in coordination with measurements of surface and atmospheric parameters and satellite overpasses. The resulting data are held in a single integrated data base and continue to be analyzed by the participating scientists and others. The first two sections of this paper recount the history and scientific background leading up to FIFE; the third and fourth sections review the experiment design, the scientific teams and equipment involved, and the actual execution of the experiment; the fifth section provides an overview of the contents of this special issue; the sixth section summarizes the management and resources of the project; and the last section lists the acknowledgments.

Implementation of the Short-Term Ensemble Prediction System (STEPS) in Belgium and verification of case studies

NASA Astrophysics Data System (ADS)

Foresti, Loris; Reyniers, Maarten; Delobbe, Laurent

2014-05-01

The Short-Term Ensemble Prediction System (STEPS) is a probabilistic precipitation nowcasting scheme developed at the Australian Bureau of Meteorology in collaboration with the UK Met Office. In order to account for the multiscaling nature of rainfall structures, the radar field is decomposed into an 8 levels multiplicative cascade using a Fast Fourier Transform. The cascade is advected using the velocity field estimated with optical flow and evolves stochastically according to a hierarchy of auto-regressive processes. This allows reproducing the empirical observation that the rate of temporal evolution of the small scales is faster than the large scales. The uncertainty in radar rainfall measurement and the unknown future development of the velocity field are also considered by stochastic modelling in order to reflect their typical spatial and temporal variability. Recently, a 4 years national research program has been initiated by the University of Leuven, the Royal Meteorological Institute (RMI) of Belgium and 3 other partners: PLURISK ("forecasting and management of extreme rainfall induced risks in the urban environment"). The project deals with the nowcasting of rainfall and subsequent urban inundations, as well as socio-economic risk quantification, communication, warning and prevention. At the urban scale it is widely recognized that the uncertainty of hydrological and hydraulic models is largely driven by the input rainfall estimation and forecast uncertainty. In support to the PLURISK project the RMI aims at integrating STEPS in the current operational deterministic precipitation nowcasting system INCA-BE (Integrated Nowcasting through Comprehensive Analysis). This contribution will illustrate examples of STEPS ensemble and probabilistic nowcasts for a few selected case studies of stratiform and convective rain in Belgium. The paper focuses on the development of STEPS products for potential hydrological users and a preliminary verification of the nowcasts, especially to analyze the spatial distribution of forecast errors. The analysis of nowcast biases reveals the locations where the convective initiation, rainfall growth and decay processes significantly reduce the forecast accuracy, but also points out the need for improving the radar-based quantitative precipitation estimation product that is used both to generate and verify the nowcasts. The collection of fields of verification statistics is implemented using an online update strategy, which potentially enables the system to learn from forecast errors as the archive of nowcasts grows. The study of the spatial or temporal distribution of nowcast errors is a key step to convey to the users an overall estimation of the nowcast accuracy and to drive future model developments.

Solar UV dose patterns in Italy.

PubMed

Meloni, D; Casale, G R; Siani, A M; Palmieri, S; Cappellani, F

2000-06-01

Since 1992 solar ultraviolet (UV) spectral irradiance (290-325 nm) has been measured at two Italian stations of Rome (urban site) and Ispra (semirural site) using Brewer spectrophotometry. The data collected under all sky conditions, are compared with the output of a sophisticated radiative transfer model (System for Transfer of Atmospheric Radiation--STAR model). The STAR multiple scattering scheme is able to cope with all physical processes relevant to the UV transfer through the atmosphere. The experience so far acquired indicates that, in spite of the unavoidable uncertainties in the input parameters (ozone, aerosol, surface albedo, pressure, temperature, relative humidity, cloud cover), measured and computed clear sky iradiances are in reasonable agreement. The STAR model is applied to build up the solar UV geographic patterns in Italy: the daily dose in the range 290-325 nm is computed at about 70 sites where a thorough and homogeneous climatology is available. For each month the concept of an idealized "standard day" is introduced and the surface distribution of solar UV field determined. The map of solar UV patterns for Italy, available for the first time, meets the study requirements in the field of skin and eye epidemiology, as well as in other investigations dealing with the impact of UV on the biosphere. The results are interpreted in terms of atmospheric and meteorological parameters modulating UV radiation reaching the ground.

New DMSP Database of Precipitating Auroral Electrons and Ions.

PubMed

Redmon, Robert J; Denig, William F; Kilcommons, Liam M; Knipp, Delores J

2017-08-01

Since the mid 1970's, the Defense Meteorological Satellite Program (DMSP) spacecraft have operated instruments for monitoring the space environment from low earth orbit. As the program evolved, so to have the measurement capabilities such that modern DMSP spacecraft include a comprehensive suite of instruments providing estimates of precipitating electron and ion fluxes, cold/bulk plasma composition and moments, the geomagnetic field, and optical emissions in the far and extreme ultraviolet. We describe the creation of a new public database of precipitating electrons and ions from the Special Sensor J (SSJ) instrument, complete with original counts, calibrated differential fluxes adjusted for penetrating radiation, estimates of the total kinetic energy flux and characteristic energy, uncertainty estimates, and accurate ephemerides. These are provided in a common and self-describing format that covers 30+ years of DMSP spacecraft from F06 (launched in 1982) through F18 (launched in 2009). This new database is accessible at the National Centers for Environmental Information (NCEI) and the Coordinated Data Analysis Web (CDAWeb). We describe how the new database is being applied to high latitude studies of: the co-location of kinetic and electromagnetic energy inputs, ionospheric conductivity variability, field aligned currents and auroral boundary identification. We anticipate that this new database will support a broad range of space science endeavors from single observatory studies to coordinated system science investigations.

Evaluation of low wind modeling approaches for two tall-stack databases.

PubMed

Paine, Robert; Samani, Olga; Kaplan, Mary; Knipping, Eladio; Kumar, Naresh

2015-11-01

The performance of the AERMOD air dispersion model under low wind speed conditions, especially for applications with only one level of meteorological data and no direct turbulence measurements or vertical temperature gradient observations, is the focus of this study. The analysis documented in this paper addresses evaluations for low wind conditions involving tall stack releases for which multiple years of concurrent emissions, meteorological data, and monitoring data are available. AERMOD was tested on two field-study databases involving several SO2 monitors and hourly emissions data that had sub-hourly meteorological data (e.g., 10-min averages) available using several technical options: default mode, with various low wind speed beta options, and using the available sub-hourly meteorological data. These field study databases included (1) Mercer County, a North Dakota database featuring five SO2 monitors within 10 km of the Dakota Gasification Company's plant and the Antelope Valley Station power plant in an area of both flat and elevated terrain, and (2) a flat-terrain setting database with four SO2 monitors within 6 km of the Gibson Generating Station in southwest Indiana. Both sites featured regionally representative 10-m meteorological databases, with no significant terrain obstacles between the meteorological site and the emission sources. The low wind beta options show improvement in model performance helping to reduce some of the over-prediction biases currently present in AERMOD when run with regulatory default options. The overall findings with the low wind speed testing on these tall stack field-study databases indicate that AERMOD low wind speed options have a minor effect for flat terrain locations, but can have a significant effect for elevated terrain locations. The performance of AERMOD using low wind speed options leads to improved consistency of meteorological conditions associated with the highest observed and predicted concentration events. The available sub-hourly modeling results using the Sub-Hourly AERMOD Run Procedure (SHARP) are relatively unbiased and show that this alternative approach should be seriously considered to address situations dominated by low-wind meander conditions. AERMOD was evaluated with two tall stack databases (in North Dakota and Indiana) in areas of both flat and elevated terrain. AERMOD cases included the regulatory default mode, low wind speed beta options, and use of the Sub-Hourly AERMOD Run Procedure (SHARP). The low wind beta options show improvement in model performance (especially in higher terrain areas), helping to reduce some of the over-prediction biases currently present in regulatory default AERMOD. The SHARP results are relatively unbiased and show that this approach should be seriously considered to address situations dominated by low-wind meander conditions.

Towards a model-based inventory of soil organic carbon in agricultural soils for the Swiss greenhouse gas reporting

NASA Astrophysics Data System (ADS)

Staudt, K.; Leifeld, J.; Bretscher, D.; Fuhrer, J.

2012-04-01

The Swiss inventory submission under the United Nations Framework Convention on Climate Change (UNFCCC) reports on changes in soil organic carbon stocks under different land-uses and land-use changes. The approach currently employed for cropland and grassland soils combines Tier 1 and Tier 2 methods and is considered overly simplistic. As the UNFCC encourages countries to develop Tier 3 methods for national greenhouse gas reporting, we aim to build up a model-based inventory of soil organic carbon in agricultural soils in Switzerland. We conducted a literature research on currently employed higher-tier methods using process-based models in four countries: Denmark, Sweden, Finland and the USA. The applied models stem from two major groups differing in complexity - those belonging to the group of general ecosystem models that include a plant-growth submodel, e.g. Century, and those that simulate soil organic matter turnover but not plant-growth, e.g. ICBM. For the latter group, carbon inputs to the soil from plant residues and roots have to be determined separately. We will present some aspects of the development of a model-based inventory of soil organic carbon in agricultural soils in Switzerland. Criteria for model evaluation are, among others, modeled land-use classes and land-use changes, spatial and temporal resolution, and coverage of relevant processes. For model parameterization and model evaluation at the field scale, data from several long-term agricultural experiments and monitoring sites in Switzerland is available. A subsequent regional application of a model requires the preparation of regional input data for the whole country - among others spatio-temporal meteorological data, agricultural and soil data. Following the evaluation of possible models and of available data, preference for application in the Swiss inventory will be given to simpler model structures, i.e. models without a plant-growth module. Thus, we compared different allometric relations for the estimation of plant carbon inputs to the soil from yield data that are usually provided with the models. Calculated above- and below-ground carbon inputs vary substantially between methods and exhibit different sensitivities to yield data. As a benchmark, inputs to the soil from above- and below-ground crop residues are calculated with the IPCC default method. Furthermore, the suitability of these estimation methods for Swiss conditions is tested.

Geomagnetic main field modeling with DMSP

NASA Astrophysics Data System (ADS)

Alken, P.; Maus, S.; Lühr, H.; Redmon, R. J.; Rich, F.; Bowman, B.; O'Malley, S. M.

2014-05-01

The Defense Meteorological Satellite Program (DMSP) launches and maintains a network of satellites to monitor the meteorological, oceanographic, and solar-terrestrial physics environments. In the past decade, geomagnetic field modelers have focused much attention on magnetic measurements from missions such as CHAMP, Ørsted, and SAC-C. With the completion of the CHAMP mission in 2010, there has been a multiyear gap in satellite-based vector magnetic field measurements available for main field modeling. In this study, we calibrate the special sensor magnetometer instrument on board DMSP to create a data set suitable for main field modeling. These vector field measurements are calibrated to compute instrument timing shifts, scale factors, offsets, and nonorthogonality angles of the fluxgate magnetometer cores. Euler angles are then computed to determine the orientation of the vector magnetometer with respect to a local coordinate system. We fit a degree 15 main field model to the data set and compare with the World Magnetic Model and Ørsted scalar measurements. We call this model DMSP-MAG-1, and its coefficients and software are available for download at http://geomag.org/models/dmsp.html. Our results indicate that the DMSP data set will be a valuable source for main field modeling for the years between CHAMP and the recently launched Swarm mission.

A high-resolution regional reanalysis for the European CORDEX region

NASA Astrophysics Data System (ADS)

Bollmeyer, Christoph; Keller, Jan; Ohlwein, Christian; Wahl, Sabrina

2015-04-01

Within the Hans-Ertel-Centre for Weather Research (HErZ), the climate monitoring branch concentrates efforts on the assessment and analysis of regional climate in Germany and Europe. In joint cooperation with DWD (German Weather Service), a high-resolution reanalysis system based on the COSMO model has been developed. Reanalyses gain more and more importance as a source of meteorological information for many purposes and applications. Several global reanalyses projects (e.g., ERA, MERRA, CSFR, JMA9) produce and verify these data sets to provide time series as long as possible combined with a high data quality. Due to a spatial resolution down to 50-70km and 3-hourly temporal output, they are not suitable for small scale problems (e.g., regional climate assessment, meso-scale NWP verification, input for subsequent models such as river runoff simulations, renewable energy applications). The implementation of regional reanalyses based on a limited area model along with a data assimilation scheme is able to generate reanalysis data sets with high spatio-temporal resolution. The work presented here focuses on two regional reanalyses for Europe and Germany. The European reanalysis COSMO-REA6 matches the CORDEX EURO-11 specifications, albeit at a higher spatial resolution, i.e., 0.055° (6km) instead of 0.11° (12km). Nested into COSMO-REA6 is COSMO-REA2, a convective-scale reanalysis with 2km resolution for Germany. COSMO-REA6 comprises the assimilation of observational data using the existing nudging scheme of COSMO and is complemented by a special soil moisture analysis and boundary conditions given by ERA-Interim data. COSMO-REA2 also uses the nudging scheme complemented by a latent heat nudging of radar information. The reanalysis data set currently covers 17 years (1997-2013) for COSMO-REA6 and 4 years (2010-2013) for COSMO-REA2 with a very large set of output variables and a high temporal output step of hourly 3D-fields and quarter-hourly 2D-fields. The evaluation of the reanalyses is done using independent observations for the most important meteorological parameters with special emphasis on precipitation and high-impact weather situations.

Impact of Transpacific Aerosol on Air Quality over the United States: A Perspective from Aerosol-Cloud-Radiation Interactions

NASA Technical Reports Server (NTRS)

Tao, Zhining; Yu, Hongbin; Chin, Mian

2015-01-01

Observations have well established that aerosols from various sources in Asia, Europe, and Africa can travel across the Pacific and reach the contiguous United States (U.S.) at least on episodic bases throughout a year, with a maximum import in spring. The imported aerosol not only can serve as an additional source to regional air pollution (e.g., direct input), but also can influence regional air quality through the aerosol-cloud-radiation (ACR) interactions that change local and regional meteorology. This study assessed impacts of the transpacific aerosol on air quality, focusing on surface ozone and PM2.5, over the U.S. using the NASA Unified Weather Research Forecast model. Based on the results of 3- month (April to June of 2010) simulations, the impact of direct input (as an additional source) of transpacific aerosol caused an increase of surface PM2.5 concentration by approximately 1.5 micro-g/cu m over the west coast and about 0.5 micro-g/cu m over the east coast of the U.S. By influencing key meteorological processes through the ACR interactions, the transpacific aerosol exerted a significant effect on both surface PM2.5 (+/-6 micro-g/cu m3) and ozone (+/-12 ppbv) over the central and eastern U.S. This suggests that the transpacific transport of aerosol could either improve or deteriorate local air quality and complicate local effort toward the compliance with the U.S. National Ambient Air Quality Standards.

A framework for improving a seasonal hydrological forecasting system using sensitivity analysis

NASA Astrophysics Data System (ADS)

Arnal, Louise; Pappenberger, Florian; Smith, Paul; Cloke, Hannah

2017-04-01

Seasonal streamflow forecasts are of great value for the socio-economic sector, for applications such as navigation, flood and drought mitigation and reservoir management for hydropower generation and water allocation to agriculture and drinking water. However, as we speak, the performance of dynamical seasonal hydrological forecasting systems (systems based on running seasonal meteorological forecasts through a hydrological model to produce seasonal hydrological forecasts) is still limited in space and time. In this context, the ESP (Ensemble Streamflow Prediction) remains an attractive forecasting method for seasonal streamflow forecasting as it relies on forcing a hydrological model (starting from the latest observed or simulated initial hydrological conditions) with historical meteorological observations. This makes it cheaper to run than a standard dynamical seasonal hydrological forecasting system, for which the seasonal meteorological forecasts will first have to be produced, while still producing skilful forecasts. There is thus the need to focus resources and time towards improvements in dynamical seasonal hydrological forecasting systems which will eventually lead to significant improvements in the skill of the streamflow forecasts generated. Sensitivity analyses are a powerful tool that can be used to disentangle the relative contributions of the two main sources of errors in seasonal streamflow forecasts, namely the initial hydrological conditions (IHC; e.g., soil moisture, snow cover, initial streamflow, among others) and the meteorological forcing (MF; i.e., seasonal meteorological forecasts of precipitation and temperature, input to the hydrological model). Sensitivity analyses are however most useful if they inform and change current operational practices. To this end, we propose a method to improve the design of a seasonal hydrological forecasting system. This method is based on sensitivity analyses, informing the forecasters as to which element of the forecasting chain (i.e., IHC or MF) could potentially lead to the highest increase in seasonal hydrological forecasting performance, after each forecast update.

Predicted carbonation of existing concrete building based on the Indonesian tropical micro-climate

NASA Astrophysics Data System (ADS)

Hilmy, M.; Prabowo, H.

2018-03-01

This paper is aimed to predict the carbonation progress based on the previous mathematical model. It shortly explains the nature of carbonation including the processes and effects. Environmental humidity and temperature of the existing concrete building are measured and compared to data from local Meteorological, Climatological, and Geophysical Agency. The data gained are expressed in the form of annual hygrothermal values which will use as the input parameter in carbonation model. The physical properties of the observed building such as its location, dimensions, and structural material used are quantified. These data then utilized as an important input parameter for carbonation coefficients. The relationships between relative humidity and the rate of carbonation established. The results can provide a basis for repair and maintenance of existing concrete buildings and the sake of service life analysis of them.

COMPARISON OF SCIENTIFIC FINDINGS FROM MAJOR OZONE FIELD STUDIES IN NORTH AMERICA AND EUROPE

EPA Science Inventory

During the past decade, nearly 600 million dollars were invested in more than 30 major field studies in North America and Europe examining tropospheric ozone chemistry, meteorology, precursor emissions, and modeling. Most of these studies were undertaken to provide new or refin...

Monthly mean large-scale analyses of upper-tropospheric humidity and wind field divergence derived from three geostationary satellites

NASA Technical Reports Server (NTRS)

Schmetz, Johannes; Menzel, W. Paul; Velden, Christopher; Wu, Xiangqian; Vandeberg, Leo; Nieman, Steve; Hayden, Christopher; Holmlund, Kenneth; Geijo, Carlos

1995-01-01

This paper describes the results from a collaborative study between the European Space Operations Center, the European Organization for the Exploitation of Meteorological Satellites, the National Oceanic and Atmospheric Administration, and the Cooperative Institute for Meteorological Satellite Studies investigating the relationship between satellite-derived monthly mean fields of wind and humidity in the upper troposphere for March 1994. Three geostationary meteorological satellites GOES-7, Meteosat-3, and Meteosat-5 are used to cover an area from roughly 160 deg W to 50 deg E. The wind fields are derived from tracking features in successive images of upper-tropospheric water vapor (WV) as depicted in the 6.5-micron absorption band. The upper-tropospheric relative humidity (UTH) is inferred from measured water vapor radiances with a physical retrieval scheme based on radiative forward calculations. Quantitative information on large-scale circulation patterns in the upper-troposphere is possible with the dense spatial coverage of the WV wind vectors. The monthly mean wind field is used to estimate the large-scale divergence; values range between about-5 x 10(exp -6) and 5 x 10(exp 6)/s when averaged over a scale length of about 1000-2000 km. The spatial patterns of the UTH field and the divergence of the wind field closely resemble one another, suggesting that UTH patterns are principally determined by the large-scale circulation. Since the upper-tropospheric humidity absorbs upwelling radiation from lower-tropospheric levels and therefore contributes significantly to the atmospheric greenhouse effect, this work implies that studies on the climate relevance of water vapor should include three-dimensional modeling of the atmospheric dynamics. The fields of UTH and WV winds are useful parameters for a climate-monitoring system based on satellite data. The results from this 1-month analysis suggest the desirability of further GOES and Meteosat studies to characterize the changes in the upper-tropospheric moisture sources and sinks over the past decade.

Experience-dependent shaping of hippocampal CA1 intracellular activity in novel and familiar environments

PubMed Central

Cohen, Jeremy D; Bolstad, Mark; Lee, Albert K

2017-01-01

The hippocampus is critical for producing stable representations of familiar spaces. How these representations arise is poorly understood, largely because changes to hippocampal inputs have not been measured during spatial learning. Here, using intracellular recording, we monitored inputs and plasticity-inducing complex spikes (CSs) in CA1 neurons while mice explored novel and familiar virtual environments. Inputs driving place field spiking increased in amplitude – often suddenly – during novel environment exploration. However, these increases were not sustained in familiar environments. Rather, the spatial tuning of inputs became increasingly similar across repeated traversals of the environment with experience – both within fields and throughout the whole environment. In novel environments, CSs were not necessary for place field formation. Our findings support a model in which initial inhomogeneities in inputs are amplified to produce robust place field activity, then plasticity refines this representation into one with less strongly modulated, but more stable, inputs for long-term storage. DOI: http://dx.doi.org/10.7554/eLife.23040.001 PMID:28742496

PLS Road surface temperature forecast for susceptibility of ice occurrence

NASA Astrophysics Data System (ADS)

Marchetti, Mario; Khalifa, Abderrhamen; Bues, Michel

2014-05-01

Winter maintenance relies on many operational tools consisting in monitoring atmospheric and pavement physical parameters. Among them, road weather information systems (RWIS) and thermal mapping are mostly used by service in charge of managing infrastructure networks. The Data from RWIS and thermal mapping are considered as inputs for forecasting physical numerical models, commonly in place since the 80s. These numerical models do need an accurate description of the infrastructure, such as pavement layers and sub-layers, along with many meteorological parameters, such as air temperature and global and infrared radiation. The description is sometimes partially known, and meteorological data is only monitored on specific spot. On the other hand, thermal mapping is now an easy, reliable and cost effective way to monitor road surface temperature (RST), and many meteorological parameters all along routes of infrastructure networks, including with a whole fleet of vehicles in the specific cases of roads, or airports. The technique uses infrared thermometry to measure RST and an atmospheric probes for air temperature, relative humidity, wind speed and global radiation, both at a high resolution interval, to identify sections of the road network prone to ice occurrence. However, measurements are time-consuming, and the data from thermal mapping is one input among others to establish the forecast. The idea was to build a reliable forecast on the sole data from thermal mapping. Previous work has established the interest to use principal component analysis (PCA) on the basis of a reduced number of thermal fingerprints. The work presented here is a focus on the use of partial least-square regression (PLS) to build a RST forecast with air temperature measurements. Roads with various environments, weather conditions (clear, cloudy mainly) and seasons were monitored over several months to generate an appropriate number of samples. The study was conducted to determine the minimum number of samples to get a reliable forecast, considering inputs for numerical models do not exceed five thermal fingerprints. Results of PLS have shown that the PLS model could have a R² of 0.9562, a RMSEP of 1.34 and a bias of -0.66. The same model applied to establish a forecast on past event indicates an average difference between measurements and forecasts of 0.20 °C. The advantage of such approach is its potential application not only to winter events, but also the extreme summer ones for urban heat island.

Measuring progress of the global sea level observing system

NASA Astrophysics Data System (ADS)

Woodworth, Philip L.; Aarup, Thorkild; Merrifield, Mark; Mitchum, Gary T.; Le Provost, Christian

Sea level is such a fundamental parameter in the sciences of oceanography geophysics, and climate change, that in the mid-1980s, the Intergovernmental Oceanographic Commission (IOC) established the Global Sea Level Observing System (GLOSS). GLOSS was to improve the quantity and quality of data provided to the Permanent Service for Mean Sea Level (PSMSL), and thereby, data for input to studies of long-term sea level change by the Intergovernmental Panel on Climate Change (IPCC). It would also provide the key data needed for international programs, such as the World Ocean Circulation Experiment (WOCE) and later, the Climate Variability and Predictability Programme (CLIVAR).GLOSS is now one of the main observation components of the Joint Technical Commission for Oceanography and Marine Meteorology (JCOMM) of IOC and the World Meteorological Organization (WMO). Progress and deficiencies in GLOSS were presented in July to the 22nd IOC Assembly at UNESCO in Paris and are contained in the GLOSS Assessment Report (GAR) [IOC, 2003a].

Modelling NOX concentrations through CFD-RANS in an urban hot-spot using high resolution traffic emissions and meteorology from a mesoscale model

NASA Astrophysics Data System (ADS)

Sanchez, Beatriz; Santiago, Jose Luis; Martilli, Alberto; Martin, Fernando; Borge, Rafael; Quaassdorff, Christina; de la Paz, David

2017-08-01

Air quality management requires more detailed studies about air pollution at urban and local scale over long periods of time. This work focuses on obtaining the spatial distribution of NOx concentration averaged over several days in a heavily trafficked urban area in Madrid (Spain) using a computational fluid dynamics (CFD) model. A methodology based on weighted average of CFD simulations is applied computing the time evolution of NOx dispersion as a sequence of steady-state scenarios taking into account the actual atmospheric conditions. The inputs of emissions are estimated from the traffic emission model and the meteorological information used is derived from a mesoscale model. Finally, the computed concentration map correlates well with 72 passive samplers deployed in the research area. This work reveals the potential of using urban mesoscale simulations together with detailed traffic emissions so as to provide accurate maps of pollutant concentration at microscale using CFD simulations.

Response of winter and spring wheat grain yields to meteorological variation

NASA Technical Reports Server (NTRS)

Feyerherm, A. M.; Kanemasu, E. T.; Paulsen, G. M.

1977-01-01

Mathematical models which quantify the relation of wheat yield to selected weather-related variables are presented. Other sources of variation (amount of applied nitrogen, improved varieties, cultural practices) have been incorporated in the models to explain yield variation both singly and in combination with weather-related variables. Separate models were developed for fall-planted (winter) and spring-planted (spring) wheats. Meteorological variation is observed, basically, by daily measurements of minimum and maximum temperatures, precipitation, and tabled values of solar radiation at the edge of the atmosphere and daylength. Two different soil moisture budgets are suggested to compute simulated values of evapotranspiration; one uses the above-mentioned inputs, the other uses the measured temperatures and precipitation but replaces the tabled values (solar radiation and daylength) by measured solar radiation and satellite-derived multispectral scanner data to estimate leaf area index. Weather-related variables are defined by phenological stages, rather than calendar periods, to make the models more universally applicable.

Estimation water vapor content using the mixing ratio method and validated with the ANFIS PWV model

NASA Astrophysics Data System (ADS)

Suparta, W.; Alhasa, K. M.; Singh, M. S. J.

2017-05-01

This study reported the comparison between water vapor content, the surface meteorological data (pressure, temperature, and relative humidity), and precipitable water vapor (PWV) produced by PWV from adaptive neuro fuzzy inference system (ANFIS) for areas in the Universiti Kebangsaan Malaysia Bangi (UKMB) station. The water vapor content value was estimated with mixing ratio method and the surface meteorological data as the parameter inputs. The accuracy of water vapor content was validated with PWV from ANFIS PWV model for the period of 20-23 December 2016. The result showed that the water vapor content has a similar trend with the PWV which produced by ANFIS PWV model (r = 0.975 at the 99% confidence level). This indicates that the water vapor content that obtained with mixing ratio agreed very well with the ANFIS PWV model. In addition, this study also found, the pattern of water vapor content and PWV have more influenced by the relative humidity.

Cavity electromagnetically induced transparency with Rydberg atoms

NASA Astrophysics Data System (ADS)

Bakar Ali, Abu; Ziauddin

2018-02-01

Cavity electromagnetically induced transparency (EIT) is revisited via the input probe field intensity. A strongly interacting Rydberg atomic medium ensemble is considered in a cavity, where atoms behave as superatoms (SAs) under the dipole blockade mechanism. Each atom in the strongly interacting Rydberg atomic medium (87 Rb) follows a three-level cascade atomic configuration. A strong control and weak probe field are employed in the cavity with the ensemble of Rydberg atoms. The features of the reflected and transmitted probe light are studied under the influence of the input probe field intensity. A transparency peak (cavity EIT) is revealed at a resonance condition for small values of input probe field intensity. The manipulation of the cavity EIT is reported by tuning the strength of the input probe field intensity. Further, the phase and group delay of the transmitted and reflected probe light are studied. It is found that group delay and phase in the reflected light are negative, while for the transmitted light they are positive. The magnitude control of group delay in the transmitted and reflected light is investigated via the input probe field intensity.

Comparison of Mid-latitude Cyclones in Sea Level Pressure, Gepotential Height and Vorticity Fields

NASA Astrophysics Data System (ADS)

Raible, Christoph C.; Blender, Richard; Fraedrich, Klaus

2013-04-01

The mid-latitudes are dominated by diurnal variability, which is related to traveling high- and low-pressure systems. The lows or cyclones are a major source of natural hazards. This has led to growing interest in the scientific community to develop Eulerian and Lagrangian measures and to analyze the atmospheric high-frequency variability. One important issue is that there is no straight forward definition of cyclones resulting in a large variety of so-called cyclone detection and tracking methods. Each of these methods relies on different input fields which are related to specific features of a cyclone, e.g., sea level pressure (SLP), which specifically focuses on the mass aspect of the velocity field. Recently, the available methods have been compared with respect to climatology and life cycles using the ERA interim data set (Neu et al. 2013). Based on this study we investigate different fields as input for one specific method. We focus on the three mostly used input data, sea level pressure (SLP), 1000-hPa gepotential height (Z1000) and 850-hPa vorticity (850VOR). The cyclone detection and tracking method developed by Blender et al. (1997) is used and we apply it to ERA interim data in the 1.5 x 1.5 resolution. The method was mainly applied for Z1000 and the Northern Hemisphere (e.g., Blender et al. 1997; Raible et al. 2008). To compare the tracks and cyclone characteristics obtained from the different input data we need to adapt critical parameters of the method in such a way that comparable numbers of cyclone centers are identified in either field. The target is set to the number of cyclone centers in northern hemispheric winter. This enables us to assess the seasonal and hemispheric dependence. Preliminary results show that the agreement between cyclones based on SLP and Z1000 varies between roughly 70 to 80% depending on the season and the hemisphere. Spatially, most of the differences are found around orographic features like Greenland. An interesting finding is that the number of cyclones based on Z1000 is increased comparing the winter and summer season as the number of heat lows increases in summer. However, the behavior is vice versa for cyclones based on SLP. References: Blender R., K. Fraedrich, and F. Lunkeit, 1997: Identification of cyclone-track regimes in the North Atlantic. Quart. J. Roy. Meteor. Soc., 123, 727-741. Neu, U., M. G. Akperov, N. Bellenbaum, R. Benestad, R. Blender, R. Caballero, A. Cocozza, H. F. Dacre, Y. Feng, K. Fraedrich, J. Grieger, S. Gulev, J. Hanley, T. Hewson, M. Inatsu, K. Keay, S. F. Kew, I. Kindem, G. C. Leckebusch, M. L. R. Liberato, P. Lionello, I. I. Mokhov, J. G. Pinto, C. C. Raible, M. Reale, I. Rudeva, M. Schuster, I. Simmonds, M. Sinclair, M. Sprenger, N. D. Tilinina, I. F. Trigo, S. Ulbrich, U. Ulbrich, X. L. Wang, H. Wernli, 2012: IMILAST - a community effort to intercompare extratropical cyclone detection and tracking algorithms: assessing method-related uncertainties, Bulletin of the American Meteorological Society, in press. Raible, C. C., P. Della-Marta, C. Schwierz, H. Wernli, and R. Blender, 2008: Northern Hemisphere extratropical cyclones: A comparison of detection and tracking methods and different reanalyses, Mon. Wea. Rev., 136 880-897.

Cloud Intrusion Detection and Repair (CIDAR)

DTIC Science & Technology

2016-02-01

form for VLC , Swftools-png2swf, Swftools-jpeg2swf, Dillo and GIMP. The superscript indicates the bit width of each expression atom. “sext(v, w... challenges in input rectification is the need to deal with nested fields. In general, input formats are in tree structures containing arbitrarily...length indicator constraints is challeng - ing, because of the presence of nested fields in hierarchical input format. For example, an integer field may

The Lagrangian particle dispersion model FLEXPART version 10

NASA Astrophysics Data System (ADS)

Pisso, Ignacio; Sollum, Espen; Grythe, Henrik; Kristiansen, Nina; Cassiani, Massimo; Eckhardt, Sabine; Thompson, Rona; Groot Zwaaftnik, Christine; Evangeliou, Nikolaos; Hamburger, Thomas; Sodemann, Harald; Haimberger, Leopold; Henne, Stephan; Brunner, Dominik; Burkhart, John; Fouilloux, Anne; Fang, Xuekun; Phillip, Anne; Seibert, Petra; Stohl, Andreas

2017-04-01

The Lagrangian particle dispersion model FLEXPART was in its first original release in 1998 designed for calculating the long-range and mesoscale dispersion of air pollutants from point sources, such as after an accident in a nuclear power plant. The model has now evolved into a comprehensive tool for atmospheric transport modelling and analysis. Its application fields are extended to a range of atmospheric transport processes for both atmospheric gases and aerosols, e.g. greenhouse gases, short-lived climate forces like black carbon, volcanic ash and gases as well as studies of the water cycle. We present the newest release, FLEXPART version 10. Since the last publication fully describing FLEXPART (version 6.2), the model code has been parallelised in order to allow for the possibility to speed up computation. A new, more detailed gravitational settling parametrisation for aerosols was implemented, and the wet deposition scheme for aerosols has been heavily modified and updated to provide a more accurate representation of this physical process. In addition, an optional new turbulence scheme for the convective boundary layer is available, that considers the skewness in the vertical velocity distribution. Also, temporal variation and temperature dependence of the OH-reaction are included. Finally, user input files are updated to a more convenient and user-friendly namelist format, and the option to produce the output-files in netCDF-format instead of binary format is implemented. We present these new developments and show recent model applications. Moreover, we also introduce some tools for the preparation of the meteorological input data, as well as for the processing of FLEXPART output data.

Evaluation of WRF Parameterizations for Air Quality Applications over the Midwest USA

NASA Astrophysics Data System (ADS)

Zheng, Z.; Fu, K.; Balasubramanian, S.; Koloutsou-Vakakis, S.; McFarland, D. M.; Rood, M. J.

2017-12-01

Reliable predictions from Chemical Transport Models (CTMs) for air quality research require accurate gridded weather inputs. In this study, a sensitivity analysis of 17 Weather Research and Forecast (WRF) model runs was conducted to explore the optimum configuration in six physics categories (i.e., cumulus, surface layer, microphysics, land surface model, planetary boundary layer, and longwave/shortwave radiation) for the Midwest USA. WRF runs were initally conducted over four days in May 2011 for a 12 km x 12 km domain over contiguous USA and a nested 4 km x 4 km domain over the Midwest USA (i.e., Illinois and adjacent areas including Iowa, Indiana, and Missouri). Model outputs were evaluated statistically by comparison with meteorological observations (DS337.0, METAR data, and the Water and Atmospheric Resources Monitoring Network) and resulting statistics were compared to benchmark values from the literature. Identified optimum configurations of physics parametrizations were then evaluated for the whole months of May and October 2011 to evaluate WRF model performance for Midwestern spring and fall seasons. This study demonstrated that for the chosen physics options, WRF predicted well temperature (Index of Agreement (IOA) = 0.99), pressure (IOA = 0.99), relative humidity (IOA = 0.93), wind speed (IOA = 0.85), and wind direction (IOA = 0.97). However, WRF did not predict daily precipitation satisfactorily (IOA = 0.16). Developed gridded weather fields will be used as inputs to a CTM ensemble consisting of the Comprehensive Air Quality Model with Extensions to study impacts of chemical fertilizer usage on regional air quality in the Midwest USA.

Estimating Gross Primary Production in Cropland with High Spatial and Temporal Scale Remote Sensing Data

NASA Astrophysics Data System (ADS)

Lin, S.; Li, J.; Liu, Q.

2018-04-01

Satellite remote sensing data provide spatially continuous and temporally repetitive observations of land surfaces, and they have become increasingly important for monitoring large region of vegetation photosynthetic dynamic. But remote sensing data have their limitation on spatial and temporal scale, for example, higher spatial resolution data as Landsat data have 30-m spatial resolution but 16 days revisit period, while high temporal scale data such as geostationary data have 30-minute imaging period, which has lower spatial resolution (> 1 km). The objective of this study is to investigate whether combining high spatial and temporal resolution remote sensing data can improve the gross primary production (GPP) estimation accuracy in cropland. For this analysis we used three years (from 2010 to 2012) Landsat based NDVI data, MOD13 vegetation index product and Geostationary Operational Environmental Satellite (GOES) geostationary data as input parameters to estimate GPP in a small region cropland of Nebraska, US. Then we validated the remote sensing based GPP with the in-situ measurement carbon flux data. Results showed that: 1) the overall correlation between GOES visible band and in-situ measurement photosynthesis active radiation (PAR) is about 50 % (R2 = 0.52) and the European Center for Medium-Range Weather Forecasts ERA-Interim reanalysis data can explain 64 % of PAR variance (R2 = 0.64); 2) estimating GPP with Landsat 30-m spatial resolution data and ERA daily meteorology data has the highest accuracy(R2 = 0.85, RMSE < 3 gC/m2/day), which has better performance than using MODIS 1-km NDVI/EVI product import; 3) using daily meteorology data as input for GPP estimation in high spatial resolution data would have higher relevance than 8-day and 16-day input. Generally speaking, using the high spatial resolution and high frequency satellite based remote sensing data can improve GPP estimation accuracy in cropland.

Extending Integrate-and-Fire Model Neurons to Account for the Effects of Weak Electric Fields and Input Filtering Mediated by the Dendrite.

PubMed

Aspart, Florian; Ladenbauer, Josef; Obermayer, Klaus

2016-11-01

Transcranial brain stimulation and evidence of ephaptic coupling have recently sparked strong interests in understanding the effects of weak electric fields on the dynamics of brain networks and of coupled populations of neurons. The collective dynamics of large neuronal populations can be efficiently studied using single-compartment (point) model neurons of the integrate-and-fire (IF) type as their elements. These models, however, lack the dendritic morphology required to biophysically describe the effect of an extracellular electric field on the neuronal membrane voltage. Here, we extend the IF point neuron models to accurately reflect morphology dependent electric field effects extracted from a canonical spatial "ball-and-stick" (BS) neuron model. Even in the absence of an extracellular field, neuronal morphology by itself strongly affects the cellular response properties. We, therefore, derive additional components for leaky and nonlinear IF neuron models to reproduce the subthreshold voltage and spiking dynamics of the BS model exposed to both fluctuating somatic and dendritic inputs and an extracellular electric field. We show that an oscillatory electric field causes spike rate resonance, or equivalently, pronounced spike to field coherence. Its resonance frequency depends on the location of the synaptic background inputs. For somatic inputs the resonance appears in the beta and gamma frequency range, whereas for distal dendritic inputs it is shifted to even higher frequencies. Irrespective of an external electric field, the presence of a dendritic cable attenuates the subthreshold response at the soma to slowly-varying somatic inputs while implementing a low-pass filter for distal dendritic inputs. Our point neuron model extension is straightforward to implement and is computationally much more efficient compared to the original BS model. It is well suited for studying the dynamics of large populations of neurons with heterogeneous dendritic morphology with (and without) the influence of weak external electric fields.

Extending Integrate-and-Fire Model Neurons to Account for the Effects of Weak Electric Fields and Input Filtering Mediated by the Dendrite

PubMed Central

Obermayer, Klaus

2016-01-01

Transcranial brain stimulation and evidence of ephaptic coupling have recently sparked strong interests in understanding the effects of weak electric fields on the dynamics of brain networks and of coupled populations of neurons. The collective dynamics of large neuronal populations can be efficiently studied using single-compartment (point) model neurons of the integrate-and-fire (IF) type as their elements. These models, however, lack the dendritic morphology required to biophysically describe the effect of an extracellular electric field on the neuronal membrane voltage. Here, we extend the IF point neuron models to accurately reflect morphology dependent electric field effects extracted from a canonical spatial “ball-and-stick” (BS) neuron model. Even in the absence of an extracellular field, neuronal morphology by itself strongly affects the cellular response properties. We, therefore, derive additional components for leaky and nonlinear IF neuron models to reproduce the subthreshold voltage and spiking dynamics of the BS model exposed to both fluctuating somatic and dendritic inputs and an extracellular electric field. We show that an oscillatory electric field causes spike rate resonance, or equivalently, pronounced spike to field coherence. Its resonance frequency depends on the location of the synaptic background inputs. For somatic inputs the resonance appears in the beta and gamma frequency range, whereas for distal dendritic inputs it is shifted to even higher frequencies. Irrespective of an external electric field, the presence of a dendritic cable attenuates the subthreshold response at the soma to slowly-varying somatic inputs while implementing a low-pass filter for distal dendritic inputs. Our point neuron model extension is straightforward to implement and is computationally much more efficient compared to the original BS model. It is well suited for studying the dynamics of large populations of neurons with heterogeneous dendritic morphology with (and without) the influence of weak external electric fields. PMID:27893786

Numerical model of the circulation and dispersion in the east Adriatic coastal waters

NASA Astrophysics Data System (ADS)

Beg Paklar, Gordana; Dzoic, Tomislav; Koracin, Darko; Matijevic, Slavica; Grbec, Branka; Ivatek-Sahdan, Stjepan

2017-04-01

The Regional Ocean Modeling System (ROMS) was implemented to reproduce physical properties of the area around submarine outlet Stobrec in the middle Adriatic coastal area. ROMS model run was forced with realistic atmospheric fields obtained from meteorological model Aladin, climatological river discharges, tides and dynamics of the surrounding area imposed at the open boundaries. Atmospheric forcing included momentum, heat and water fluxes calculated interactively from the Aladin surface fields during ROMS model simulations. Simulated fields from the Adriatic and shelf scale models were used to prescribe the initial and open boundary conditions for fine resolution coastal domain. Model results were compared with available CTD measurements and discussed in the light of the climatological circulation and thermohaline properties of the middle Adriatic coastal area. Variability in the circulation is related to the prevailing atmospheric conditions, changes in the hydrological conditions and water mass exchange at the open boundaries. Basic features of the coastal circulation are well reproduced by the ROMS model, as well as temperatures and salinities which are within corresponding seasonal intervals, although with lower stratification than measured ones. In order to reproduce dispersion of the passive tracer the ROMS model was coupled with Lagrangian dispersion model. Multiyear monitoring of the physical, chemical and biological parameters around the sewage outlet was used to assess the quality of the dispersion model results. Among measured parameters, redox potential of the surface sediment layer was selected to be compared with model results as its negative values are direct consequence of increased organic matter input that can be attributed to the sewage system inflow.

Long-term solar UV radiation reconstructed by ANN modelling with emphasis on spatial characteristics of input data

NASA Astrophysics Data System (ADS)

Feister, U.; Junk, J.; Woldt, M.; Bais, A.; Helbig, A.; Janouch, M.; Josefsson, W.; Kazantzidis, A.; Lindfors, A.; den Outer, P. N.; Slaper, H.

2008-06-01

Artificial Neural Networks (ANN) are efficient tools to derive solar UV radiation from measured meteorological parameters such as global radiation, aerosol optical depths and atmospheric column ozone. The ANN model has been tested with different combinations of data from the two sites Potsdam and Lindenberg, and used to reconstruct solar UV radiation at eight European sites by more than 100 years into the past. Special emphasis will be given to the discussion of small-scale characteristics of input data to the ANN model. Annual totals of UV radiation derived from reconstructed daily UV values reflect interannual variations and long-term patterns that are compatible with variabilities and changes of measured input data, in particular global dimming by about 1980/1990, subsequent global brightening, volcanic eruption effects such as that of Mt. Pinatubo, and the long-term ozone decline since the 1970s. Patterns of annual erythemal UV radiation are very similar at sites located at latitudes close to each other, but different patterns occur between UV radiation at sites in different latitude regions.

Emulation and Sobol' sensitivity analysis of an atmospheric dispersion model applied to the Fukushima nuclear accident

NASA Astrophysics Data System (ADS)

Girard, Sylvain; Mallet, Vivien; Korsakissok, Irène; Mathieu, Anne

2016-04-01

Simulations of the atmospheric dispersion of radionuclides involve large uncertainties originating from the limited knowledge of meteorological input data, composition, amount and timing of emissions, and some model parameters. The estimation of these uncertainties is an essential complement to modeling for decision making in case of an accidental release. We have studied the relative influence of a set of uncertain inputs on several outputs from the Eulerian model Polyphemus/Polair3D on the Fukushima case. We chose to use the variance-based sensitivity analysis method of Sobol'. This method requires a large number of model evaluations which was not achievable directly due to the high computational cost of Polyphemus/Polair3D. To circumvent this issue, we built a mathematical approximation of the model using Gaussian process emulation. We observed that aggregated outputs are mainly driven by the amount of emitted radionuclides, while local outputs are mostly sensitive to wind perturbations. The release height is notably influential, but only in the vicinity of the source. Finally, averaging either spatially or temporally tends to cancel out interactions between uncertain inputs.

Fine-Scale Comparison of TOMS Total Ozone Data with Model Analysis of an Intense Midwestern Cyclone

NASA Technical Reports Server (NTRS)

Olsen, Mark A.; Gallus, William A., Jr.; Stanford, John L.; Brown, John M.

2000-01-01

High-resolution (approx. 40 km) along-track total column ozone data from the Total Ozone Mapping Spectrometer (TOMS) instrument are compared with a high-resolution mesoscale numerical model analysis of an intense cyclone in the Midwestern United States. Total ozone increased by 100 DU (nearly 38%) as the TOMS instrument passed over the associated tropopause fold region. Complex structure is seen in the meteorological fields and compares well with the total ozone observations. Ozone data support the meteorological analysis showing that stratospheric descent was confined to levels above approx. 600 hPa; significant positive potential vorticity at lower levels is attributable to diabetic processes. Likewise, meteorological fields show that two pronounced ozone streamers extending north and northeastward into Canada at high levels are not bands of stratospheric air feeding into the cyclone; one is a channel of exhaust downstream from the system, and the other apparently previously connected the main cyclonic circulation to a southward intrusion of polar stratospheric air and advected eastward as the cut-off cyclone evolved. Good agreement between small-scale features in the model output and total ozone data underscores the latter's potential usefulness in diagnosing upper tropospheric/lower stratospheric dynamics and kinematics.

Uncertainty in predictions of forest carbon dynamics: separating driver error from model error.

PubMed

Spadavecchia, L; Williams, M; Law, B E

2011-07-01

We present an analysis of the relative magnitude and contribution of parameter and driver uncertainty to the confidence intervals on estimates of net carbon fluxes. Model parameters may be difficult or impractical to measure, while driver fields are rarely complete, with data gaps due to sensor failure and sparse observational networks. Parameters are generally derived through some optimization method, while driver fields may be interpolated from available data sources. For this study, we used data from a young ponderosa pine stand at Metolius, Central Oregon, and a simple daily model of coupled carbon and water fluxes (DALEC). An ensemble of acceptable parameterizations was generated using an ensemble Kalman filter and eddy covariance measurements of net C exchange. Geostatistical simulations generated an ensemble of meteorological driving variables for the site, consistent with the spatiotemporal autocorrelations inherent in the observational data from 13 local weather stations. Simulated meteorological data were propagated through the model to derive the uncertainty on the CO2 flux resultant from driver uncertainty typical of spatially extensive modeling studies. Furthermore, the model uncertainty was partitioned between temperature and precipitation. With at least one meteorological station within 25 km of the study site, driver uncertainty was relatively small ( 10% of the total net flux), while parameterization uncertainty was larger, 50% of the total net flux. The largest source of driver uncertainty was due to temperature (8% of the total flux). The combined effect of parameter and driver uncertainty was 57% of the total net flux. However, when the nearest meteorological station was > 100 km from the study site, uncertainty in net ecosystem exchange (NEE) predictions introduced by meteorological drivers increased by 88%. Precipitation estimates were a larger source of bias in NEE estimates than were temperature estimates, although the biases partly compensated for each other. The time scales on which precipitation errors occurred in the simulations were shorter than the temporal scales over which drought developed in the model, so drought events were reasonably simulated. The approach outlined here provides a means to assess the uncertainty and bias introduced by meteorological drivers in regional-scale ecological forecasting.

Evolution of Field-Aligned Electron and Ion Densities From Whistler Mode Radio Soundings During Quiet to Moderately Active Period and Comparisons With SAMI2 Simulations

NASA Astrophysics Data System (ADS)

Reddy, A.; Sonwalkar, V. S.; Huba, J. D.

2018-02-01

Knowledge of field-aligned electron and ion distributions is necessary for understanding the physical processes causing variations in field-aligned electron and ion densities. Using whistler mode sounding by Radio Plasma Imager/Imager for Magnetopause-to-Aurora Global Exploration (RPI/IMAGE), we determined the evolution of dayside electron and ion densities along L ˜ 2 and L ˜ 3 (90-4,000 km) during a 7 day (21-27 November 2005) geomagnetically quiet to moderately active period. Over this period the O+/H+ transition height was ˜880 ± 60 km and ˜1000 ± 100 km, respectively, at L ˜ 2 and L ˜ 3. The electron density varied in a complex manner; it was different at L ˜ 2 and L ˜ 3 and below and above the O+/H+ transition height. The measured electron and ion densities are consistent with those from Challenging Minisatellite Payload (CHAMP) and Defense Meteorological Satellite Program (DMSP) and other past measurements, but they deviated from bottomside sounding and International Reference Ionosphere (IRI) 2012 empirical model results. Using SAMI2 (Naval Research Laboratory (NRL) ionosphere model) with reasonably adjusted values of inputs (neutral densities, winds, electric fields, and photoelectron heating), we simulated the evolution of O+/H+ transition height and field-aligned electron and ion densities so that a fair agreement was obtained between the simulation results and observations. Simulation studies indicated that reduced neutral densities (H and/or O) with time limited O+-H charge exchange process. This reduction in neutral densities combined with changes in neutral winds and plasma temperature led to the observed variations in the electron and ion densities. The observation/simulation method presented here can be extended to investigate the role of neutral densities and composition, disturbed winds, and prompt penetration electric fields in the storm time ionosphere/plasmasphere dynamics.

An Intercomparison of the Dynamical Cores of Global Atmospheric Circulation Models for Mars

NASA Technical Reports Server (NTRS)

Hollingsworth, Jeffery L.; Bridger, Alison F. C.; Haberle, Robert M.

1998-01-01

This is a Final Report for a Joint Research Interchange (JRI) between NASA Ames Research Center and San Jose State University, Department of Meteorology. The focus of this JRI has been to evaluate the dynamical 'cores' of two global atmospheric circulation models for Mars that are in operation at the NASA Ames Research Center. The two global circulation models in use are fundamentally different: one uses spherical harmonics in its horizontal representation of field variables; the other uses finite differences on a uniform longitude-latitude grid. Several simulations have been conducted to assess how the dynamical processors of each of these circulation models perform using identical 'simple physics' parameterizations. A variety of climate statistics (e.g., time-mean flows and eddy fields) have been compared for realistic solstitial mean basic states. Results of this research have demonstrated that the two Mars circulation models with completely different spatial representations and discretizations produce rather similar circulation statistics for first-order meteorological fields, suggestive of a tendency for convergence of numerical solutions. Second and higher-order fields can, however, vary significantly between the two models.

An Intercomparison of the Dynamical Cores of Global Atmospheric Circulation Models for Mars

NASA Technical Reports Server (NTRS)

Hollingsworth, Jeffery L.; Bridger, Alison F. C.; Haberle, Robert M.

1998-01-01

This is a Final Report for a Joint Research Interchange (JRI) between NASA Ames Research Cen- ter and San Jose State University, Department of Meteorology. The focus of this JRI has been to evaluate the dynamical "cores" of two global atmospheric circulation models for Mars that are in operation at the NASA Ames Research Center. ne two global circulation models in use are fundamentally different: one uses spherical harmonics in its horizontal representation of field variables; the other uses finite differences on a uniform longitude-latitude grid. Several simulations have been conducted to assess how the dynamical processors of each of these circulation models perform using identical "simple physics" parameterizations. A variety of climate statistics (e.g., time-mean flows and eddy fields) have been compared for realistic solstitial mean basic states. Results of this research have demonstrated that the two Mars circulation models with completely different spatial representations and discretizations produce rather similar circulation statistics for first-order meteorological fields, suggestive of a tendency for convergence of numerical solutions. Second and higher-order fields can, however, vary significantly between the two models.

Risk Quantification for Sustaining Coastal Military Installation Asset and Mission Capabilities (RC-1701)

DTIC Science & Technology

2014-06-06

al. 2012, and references therein). The world’s oceans have an en01m ous capacity to store this heat , but the result is ocean wruming and all the...TC96 wind model computes surface stress and average wind speed and direction in the PBL of a tropical cyclone. The model inputs are meteorological...is the effective earth elasticity factor; τs,winds and τs,waves are surface stresses due to winds and waves, respectively; τb is bottom stress ; M

Proceedings of the Workshop on Meteorological and Environmental Inputs to Aviation Systems (6th) Held at the University of Tennessee Space Institute on 26-28 October 1982,

DTIC Science & Technology

1983-04-01

it is mediocre information, as long 28 RESPOSE : Jim Sullivan data link can unload the voice channels. How- ever, this raises workload questions for...automa- This capability provides an alternative to tion program provides for pilot self -briefing voice communications. Where we’ve got crowded...etc., and various display-menu-product call-up 1983 use. and user-oriented self -help schemes. Additional PROFS products, including radar The Denver

An Estimation of Turbulent Kinetic Energy and Energy Dissipation Rate Based on Atmospheric Boundary Layer Similarity Theory

NASA Technical Reports Server (NTRS)

Han, Jongil; Arya, S. Pal; Shaohua, Shen; Lin, Yuh-Lang; Proctor, Fred H. (Technical Monitor)

2000-01-01

Algorithms are developed to extract atmospheric boundary layer profiles for turbulence kinetic energy (TKE) and energy dissipation rate (EDR), with data from a meteorological tower as input. The profiles are based on similarity theory and scalings for the atmospheric boundary layer. The calculated profiles of EDR and TKE are required to match the observed values at 5 and 40 m. The algorithms are coded for operational use and yield plausible profiles over the diurnal variation of the atmospheric boundary layer.

figure1.nc

EPA Pesticide Factsheets

NetCDF file of the SREF standard deviation of wind speed and direction that was used to inject variability in the FDDA input.variable U_NDG_OLD contains standard deviation of wind speed (m/s)variable V_NDG_OLD contains the standard deviation of wind direction (deg)This dataset is associated with the following publication:Gilliam , R., C. Hogrefe , J. Godowitch, S. Napelenok , R. Mathur , and S.T. Rao. Impact of inherent meteorology uncertainty on air quality model predictions. JOURNAL OF GEOPHYSICAL RESEARCH-ATMOSPHERES. American Geophysical Union, Washington, DC, USA, 120(23): 12,259–12,280, (2015).

An Operational Coastal Forecasting System in Galicia (NW Spain)

NASA Astrophysics Data System (ADS)

Balseiro, C. F.; Carracedo, P.; Pérez, E.; Pérez, V.; Taboada, J.; Venacio, A.; Vilasa, L.

2009-09-01

The Galician coast (NW Iberian Peninsula coast) and mainly the Rias Baixas (southern Galician rias) are one of the most productive ecosystems in the world, supporting a very active fishing and aquiculture industry. This high productivity lives together with a high human pressure and an intense maritime traffic, which means an important environmental risk. Besides that, Harmful Algae Blooms (HAB) are common in this area, producing important economical losses in aquiculture. In this context, the development of an Operational Hydrodynamic Ocean Forecast System is the first step to the development of a more sophisticated Ocean Integrated Decision Support Tool. A regional oceanographic forecasting system in the Galician Coast has been developed by MeteoGalicia (the Galician regional meteorological agency) inside ESEOO project to provide forecasts on currents, sea level, water temperature and salinity. This system is based on hydrodynamic model MOHID, forced with the operational meteorological model WRF, supported daily at MeteoGalicia . Two grid meshes are running nested at different scales, one of ~2km at the shelf scale and the other one with a resolution of 500 m at the rias scale. ESEOAT (Puertos del Estado) model provide salinity and temperature fields which are relaxed at all depth along the open boundary of the regional model (~6km). Temperature and salinity initial fields are also obtained from this application. Freshwater input from main rivers are included as forcing in MOHID model. Monthly mean discharge data from gauge station have been provided by Aguas de Galicia. Nowadays a coupling between an hydrological model (SWAT) and the hydrodynamic one are in development with the aim to verify the impact of the rivers discharges. The system runs operationally daily, providing two days of forecast. First model verifications had been performed against Puertos del Estado buoys and Xunta de Galicia buoys network along the Galician coast. High resolution model results were validated against a CTDs profiles campaign carried out during an oil spill exercise in the Ria de Vigo in April 2007. During EROCIPS INTERREG IIIB and EASY INTERREG IVB projects, a Galician oceanographic observation network were built. Three stations located inside the Rias Baixas allow to collect meteorological and oceanographic data at different depths to calibrate and validate the modelization of the rias. To complete this network and to create a common data platform a new project emerged (RAIA INTERREG IVA). It will provide MeteoGalicia more scientific data to improve the study of the rias. Furthermore, MeteoGalicia is also involved in DRIFTER AMPERA project which allows to improve the capability of modelling and monitoring the trajectory of hazardous substances and inerts.

Evaluating meteo marine climatic model inputs for the investigation of coastal hydrodynamics

NASA Astrophysics Data System (ADS)

Bellafiore, D.; Bucchignani, E.; Umgiesser, G.

2010-09-01

One of the major aspects discussed in the recent works on climate change is how to provide information from the global scale to the local one. In fact the influence of sea level rise and changes in the meteorological conditions due to climate change in strategic areas like the coastal zone is at the base of the well known mitigation and risk assessment plans. The investigation of the coastal zone hydrodynamics, from a modeling point of view, has been the field for the connection between hydraulic models and ocean models and, in terms of process studies, finite element models have demonstrated their suitability in the reproduction of complex coastal morphology and in the capability to reproduce different spatial scale hydrodynamic processes. In this work the connection between two different model families, the climate models and the hydrodynamic models usually implemented for process studies, is tested. Together, they can be the most suitable tool for the investigation of climate change on coastal systems. A finite element model, SHYFEM (Shallow water Hydrodynamic Finite Element Model), is implemented on the Adriatic Sea, to investigate the effect of wind forcing datasets produced by different downscaling from global climate models in terms of surge and its coastal effects. The wind datasets are produced by the regional climate model COSMO-CLM (CIRA), and by EBU-POM model (Belgrade University), both downscaling from ECHAM4. As a first step the downscaled wind datasets, that have different spatial resolutions, has been analyzed for the period 1960-1990 to compare what is their capability to reproduce the measured wind statistics in the coastal zone in front of the Venice Lagoon. The particularity of the Adriatic Sea meteo climate is connected with the influence of the orography in the strengthening of winds like Bora, from North-East. The increase in spatial resolution permits the more resolved wind dataset to better reproduce meteorology and to provide a more realistic forcing for hydrodynamic simulations. After this analysis, effects on water level variations, under different wind forcing, has been analyzed to define what is the local effect on sea level changes in the coastal area of the North Adriatic. Surge statistics produced from different climate model forcings for the IPCC A1B scenario have been studied to provide local information on climate change effects on coastal hydrodynamics due to meteorological effect. This typology of application has been considered a suitable tool for coastal management and can be considered a study field that will increase its importance in the more general investigation on scale interaction processes as the effects of global scale climate phenomena on local areas.

Modeled Forecasts of Dengue Fever in San Juan, Puerto Rico Using NASA Satellite Enhanced Weather Forecasts

NASA Astrophysics Data System (ADS)

Morin, C.; Quattrochi, D. A.; Zavodsky, B.; Case, J.

2015-12-01

Dengue fever (DF) is an important mosquito transmitted disease that is strongly influenced by meteorological and environmental conditions. Recent research has focused on forecasting DF case numbers based on meteorological data. However, these forecasting tools have generally relied on empirical models that require long DF time series to train. Additionally, their accuracy has been tested retrospectively, using past meteorological data. Consequently, the operational utility of the forecasts are still in question because the error associated with weather and climate forecasts are not reflected in the results. Using up-to-date weekly dengue case numbers for model parameterization and weather forecast data as meteorological input, we produced weekly forecasts of DF cases in San Juan, Puerto Rico. Each week, the past weeks' case counts were used to re-parameterize a process-based DF model driven with updated weather forecast data to generate forecasts of DF case numbers. Real-time weather forecast data was produced using the Weather Research and Forecasting (WRF) numerical weather prediction (NWP) system enhanced using additional high-resolution NASA satellite data. This methodology was conducted in a weekly iterative process with each DF forecast being evaluated using county-level DF cases reported by the Puerto Rico Department of Health. The one week DF forecasts were accurate especially considering the two sources of model error. First, weather forecasts were sometimes inaccurate and generally produced lower than observed temperatures. Second, the DF model was often overly influenced by the previous weeks DF case numbers, though this phenomenon could be lessened by increasing the number of simulations included in the forecast. Although these results are promising, we would like to develop a methodology to produce longer range forecasts so that public health workers can better prepare for dengue epidemics.

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.

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.

Meteorological conditions during the summer 1986 CITE 2 flight series

NASA Technical Reports Server (NTRS)

Shipham, Mark C.; Cahoon, Donald R.; Bachmeier, A. Scott

1990-01-01

An overview of meteorological conditions during the NASA Global Tropospheric Experiment/Chemical Instrumentation Testing and Evaluation (GTE/CITE 2) summer 1986 flight series is presented. Computer-generated isentropic trajectories are used to trace the history of air masses encountered along each aircraft flight path. The synoptic-scale wind fields are depicted based on Montgomery stream function analyses. Time series of aircraft-measured temperature, dew point, ozone, and altitude are shown to depict air mass variability. Observed differences between maritime tropical and maritime polar air masses are discussed.

A graphics package for meteorological data, version 1.5

NASA Technical Reports Server (NTRS)

Moorthi, Shrinivas; Suarez, Max; Phillips, Bill; Schemm, Jae-Kyung; Schubert, Siegfried

1989-01-01

A plotting package has been developed to simplify the task of plotting meteorological data. The calling sequences and examples of high level yet flexible routines which allow contouring, vectors and shading of cylindrical, polar, orthographic and Mollweide (egg) projections are given. Routines are also included for contouring pressure-latitude and pressure-longitude fields with linear or log scales in pressure (interpolation to fixed grid interval is done automatically). Also included is a fairly general line plotting routine. The present version (1.5) produces plots on WMS laser printers and uses graphics primitives from WOLFPLOT.

2D PWV monitoring of a wide and orographically complex area with a low dense GNSS network

NASA Astrophysics Data System (ADS)

Ferrando, Ilaria; Federici, Bianca; Sguerso, Domenico

2018-04-01

This study presents an innovative procedure to monitor the precipitable water vapor (PWV) content of a wide and orographically complex area with low-density networks. The procedure, termed G4M (global navigation satellite system, GNSS, for Meteorology), has been developed in a geographic information system (GIS) environment using the free and open source GRASS GIS software (https://grass.osgeo.org). The G4M input data are zenith total delay estimates obtained from GNSS permanent stations network adjustment and pressure ( P) and temperature ( T) observations using existing infrastructure networks with different geographic distributions in the study area. In spite of the wide sensor distribution, the procedure produces 2D maps with high spatiotemporal resolution (up to 250 m and 6 min) based on a simplified mathematical model including data interpolation, which was conceived by the authors to describe the atmosphere's physics. In addition to PWV maps, the procedure provides ΔPWV and heterogeneity index maps: the former represents PWV variations with respect to a "calm" moment, which are useful for monitoring the PWV evolution; and the latter are promising indicators to localize severe meteorological events in time and space. This innovative procedure is compared with meteorological simulations in this paper; in addition, an application to a severe event that occurred in Genoa (Italy) is presented.[Figure not available: see fulltext.

Modeling of episodic particulate matter events using a 3-D air quality model with fine grid: Applications to a pair of cities in the US/Mexico border

NASA Astrophysics Data System (ADS)

Choi, Yu-Jin; Hyde, Peter; Fernando, H. J. S.

High (episodic) particulate matter (PM) events over the sister cities of Douglas (AZ) and Agua Prieta (Sonora), located in the US-Mexico border, were simulated using the 3D Eulerian air quality model, MODELS-3/CMAQ. The best available input information was used for the simulations, with pollution inventory specified on a fine grid. In spite of inherent uncertainties associated with the emission inventory as well as the chemistry and meteorology of the air quality simulation tool, model evaluations showed acceptable PM predictions, while demonstrating the need for including the interaction between meteorology and emissions in an interactive mode in the model, a capability currently unavailable in MODELS-3/CMAQ when dealing with PM. Sensitivity studies on boundary influence indicate an insignificant regional (advection) contribution of PM to the study area. The contribution of secondary particles to the occurrence of high PM events was trivial. High PM episodes in the study area, therefore, are purely local events that largely depend on local meteorological conditions. The major PM emission sources were identified as vehicular activities on unpaved/paved roads and wind-blown dust. The results will be of immediate utility in devising PM mitigation strategies for the study area, which is one of the US EPA-designated non-attainment areas with respect to PM.

[Application of artificial neural networks on the prediction of surface ozone concentrations].

PubMed

Shen, Lu-Lu; Wang, Yu-Xuan; Duan, Lei

2011-08-01

Ozone is an important secondary air pollutant in the lower atmosphere. In order to predict the hourly maximum ozone one day in advance based on the meteorological variables for the Wanqingsha site in Guangzhou, Guangdong province, a neural network model (Multi-Layer Perceptron) and a multiple linear regression model were used and compared. Model inputs are meteorological parameters (wind speed, wind direction, air temperature, relative humidity, barometric pressure and solar radiation) of the next day and hourly maximum ozone concentration of the previous day. The OBS (optimal brain surgeon) was adopted to prune the neutral work, to reduce its complexity and to improve its generalization ability. We find that the pruned neural network has the capacity to predict the peak ozone, with an agreement index of 92.3%, the root mean square error of 0.0428 mg/m3, the R-square of 0.737 and the success index of threshold exceedance 77.0% (the threshold O3 mixing ratio of 0.20 mg/m3). When the neural classifier was added to the neural network model, the success index of threshold exceedance increased to 83.6%. Through comparison of the performance indices between the multiple linear regression model and the neural network model, we conclud that that neural network is a better choice to predict peak ozone from meteorological forecast, which may be applied to practical prediction of ozone concentration.

A dynamic aerodynamic resistance approach to calculate high resolution sensible heat fluxes in urban areas

NASA Astrophysics Data System (ADS)

Crawford, Ben; Grimmond, Sue; Kent, Christoph; Gabey, Andrew; Ward, Helen; Sun, Ting; Morrison, William

2017-04-01

Remotely sensed data from satellites have potential to enable high-resolution, automated calculation of urban surface energy balance terms and inform decisions about urban adaptations to environmental change. However, aerodynamic resistance methods to estimate sensible heat flux (QH) in cities using satellite-derived observations of surface temperature are difficult in part due to spatial and temporal variability of the thermal aerodynamic resistance term (rah). In this work, we extend an empirical function to estimate rah using observational data from several cities with a broad range of surface vegetation land cover properties. We then use this function to calculate spatially and temporally variable rah in London based on high-resolution (100 m) land cover datasets and in situ meteorological observations. In order to calculate high-resolution QH based on satellite-observed land surface temperatures, we also develop and employ novel methods to i) apply source area-weighted averaging of surface and meteorological variables across the study spatial domain, ii) calculate spatially variable, high-resolution meteorological variables (wind speed, friction velocity, and Obukhov length), iii) incorporate spatially interpolated urban air temperatures from a distributed sensor network, and iv) apply a modified Monte Carlo approach to assess uncertainties with our results, methods, and input variables. Modeled QH using the aerodynamic resistance method is then compared to in situ observations in central London from a unique network of scintillometers and eddy-covariance measurements.

Input Range Testing for the General Mission Analysis Tool (GMAT)

NASA Technical Reports Server (NTRS)

Hughes, Steven P.

2007-01-01

This document contains a test plan for testing input values to the General Mission Analysis Tool (GMAT). The plan includes four primary types of information, which rigorously define all tests that should be performed to validate that GMAT will accept allowable inputs and deny disallowed inputs. The first is a complete list of all allowed object fields in GMAT. The second type of information, is test input to be attempted for each field. The third type of information is allowable input values for all objects fields in GMAT. The final piece of information is how GMAT should respond to both valid and invalid information. It is VERY important to note that the tests below must be performed for both the Graphical User Interface and the script!! The examples are illustrated using a scripting perspective, because it is simpler to write up. However, the test must be performed for both interfaces to GMAT.

On The Design and Implementation of a New Electric-Field Meter with Reciprocating Shutter and Field-Change-Antenna Option

NASA Astrophysics Data System (ADS)

Swenson, J.; Byerley, L. G.; Bogoev, I.; Hinckley, A.; Beasley, W. H.

2003-12-01

The atmospheric electric field is a unique indicator of locally disturbed weather, local thunderstorms and local atmospheric electrical hazards. Yet, surprisingly, routine observations of ambient electric field have never been included in the canonical suite of measured meteorological variables. This notable omission may be a result of the historically high costs to acquire, install, and maintain conventional electric-field mills. To reduce costs and overcome limitations of traditional field meters, Campbell Scientific, Inc. has developed an electric-field meter (patent pending) with a reciprocating shutter that eliminates the problem of making electrical contact with a rotating shaft. The reciprocating action is under microprocessor control, so the sample rate can be varied in response to measured conditions. Between samples of electric field, the shutter can even be left open indefinitely, allowing the instrument to function as a field-change antenna. Since the shutter is closed before and after each measurement in field-meter mode, it is relatively easy to account for drift and offsets automatically, so that measurements can be made even if the electrode insulator becomes degraded by conductive deposits of the types likely to be encountered in severe outdoor environments. Because the motor is energized for only a small fraction of each measurement cycle, average power consumption is exceptionally low, making the new field meter especially suitable for solar-powered applications such as automated remote meteorological stations. Some preliminary observations demonstrate the capabilities of the instrument.

Desagregation des debits mensuels en debits journaliers

NASA Astrophysics Data System (ADS)

Ypou, Tanou Ya Kouassi

A good estimate of the historical natural flow of water in a water system, allows an appropriate management of reservoirs of hydroelectric plants. This management is a guarantee for efficient planning of hydropower production. The reconstruction of the real natural inputs with quality features for the periods before and after the impoundment of reservoirs is sought by HQ. The implementation of a good quality daily historical data from monthly data remains a major concern both for HQ and for the scientific community. Beyond the benefits of mastering simulations of the basin's hydrological behavior in water systems, this study allows the establishment of appropriate measures to protect the population and the various properties located in riparian areas of water systems. The main objective of the study is the breakdown of monthly flows in daily flows. This study is in the business context of HQ. To reconstruct the historical supply of water systems, HSAMI and HYDROTEL models are used. Different methods have been used by HQ to constitute the daily historical rates. So far, a good quality of the reconstituted daily data analysis illustrates the serious discrepancies and errors in those series. Several previous studies in the literature have attempted to reconstruct the daily flow rates from historical monthly series, but as explained in the report, these different approaches have results that do not represent the reality of HQ's water systems. Clearly the methods are not effective in the operational framework of Hydro-Quebec. This report presents an optimized use based on the approach HSAMI and HYDROTEL models in order to transform the flow of rain for the reconstruction of natural flow series. This approach is applied to Outardes's and Saint-Maurice's water systems with the weather and physical field data available. Input the hydrological data are validated by a process of analyzing data quality, specific flow and evaporation parameters. Input the metrological data has been analysis by Statistics, climate and water for weather series criteria. An automatic calibration of the two models is made with the Matlab software. The results of the calibration of Outardes's and Saint-Maurice's water systems are presented in this report. The modeling of ground conditions is made for input data needs of different models using the features included in the models are generally presented in this report and in particularly the model for HYDROTEL and PHYSITEL. The historical simulation flows is performed using meteorological data and physical field data on the periods of 1965 to 2014. Based on the quality of input data available and the goal of generating daily historical supply series using monthly series of natural inputs, the quality criteria have been defined to qualify the model to choose. Indeed, the quality criteria for comparing the two models are the criterion of NSE and KGE. Analysis of the results led to the conclusion that the HYDROTEL model is most appropriate in the operational framework of HQ to disaggregate monthly historical series of daily flows in series. The HYDROTEL model enabled to disaggregate monthly debits daily flows. The daily discharges simulated ponds Beaumont, Vermillion, La tuque are presented and analyzed in this report. Keywords: disaggregation, natural flow, HYDROTEL, HSAMI, data reconstruction .

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.

The latitude dependence of the variance of zonally averaged quantities. [in polar meteorology with attention to geometrical effects of earth

NASA Technical Reports Server (NTRS)

North, G. R.; Bell, T. L.; Cahalan, R. F.; Moeng, F. J.

1982-01-01

Geometric characteristics of the spherical earth are shown to be responsible for the increase of variance with latitude of zonally averaged meteorological statistics. An analytic model is constructed to display the effect of a spherical geometry on zonal averages, employing a sphere labeled with radial unit vectors in a real, stochastic field expanded in complex spherical harmonics. The variance of a zonally averaged field is found to be expressible in terms of the spectrum of the vector field of the spherical harmonics. A maximum variance is then located at the poles, and the ratio of the variance to the zonally averaged grid-point variance, weighted by the cosine of the latitude, yields the zonal correlation typical of the latitude. An example is provided for the 500 mb level in the Northern Hemisphere compared to 15 years of data. Variance is determined to increase north of 60 deg latitude.

Effective UV radiation from model calculations and measurements

NASA Technical Reports Server (NTRS)

Feister, Uwe; Grewe, Rolf

1994-01-01

Model calculations have been made to simulate the effect of atmospheric ozone and geographical as well as meteorological parameters on solar UV radiation reaching the ground. Total ozone values as measured by Dobson spectrophotometer and Brewer spectrometer as well as turbidity were used as input to the model calculation. The performance of the model was tested by spectroradiometric measurements of solar global UV radiation at Potsdam. There are small differences that can be explained by the uncertainty of the measurements, by the uncertainty of input data to the model and by the uncertainty of the radiative transfer algorithms of the model itself. Some effects of solar radiation to the biosphere and to air chemistry are discussed. Model calculations and spectroradiometric measurements can be used to study variations of the effective radiation in space in space time. The comparability of action spectra and their uncertainties are also addressed.

Integrated analysis of the effects of agricultural management on nitrogen fluxes at landscape scale.

PubMed

Kros, J; Frumau, K F A; Hensen, A; de Vries, W

2011-11-01

The integrated modelling system INITIATOR was applied to a landscape in the northern part of the Netherlands to assess current nitrogen fluxes to air and water and the impact of various agricultural measures on these fluxes, using spatially explicit input data on animal numbers, land use, agricultural management, meteorology and soil. Average model results on NH(3) deposition and N concentrations in surface water appear to be comparable to observations, but the deviation can be large at local scale, despite the use of high resolution data. Evaluated measures include: air scrubbers reducing NH(3) emissions from poultry and pig housing systems, low protein feeding, reduced fertilizer amounts and low-emission stables for cattle. Low protein feeding and restrictive fertilizer application had the largest effect on both N inputs and N losses, resulting in N deposition reductions on Natura 2000 sites of 10% and 12%, respectively. Copyright © 2011 Elsevier Ltd. All rights reserved.

Results of the GABLS3 diurnal-cycle benchmark for wind energy applications

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

Rodrigo, J. Sanz; Allaerts, D.; Avila, M.

We present results of the GABLS3 model intercomparison benchmark revisited for wind energy applications. The case consists of a diurnal cycle, measured at the 200-m tall Cabauw tower in the Netherlands, including a nocturnal low-level jet. The benchmark includes a sensitivity analysis of WRF simulations using two input meteorological databases and five planetary boundary-layer schemes. A reference set of mesoscale tendencies is used to drive microscale simulations using RANS k-ϵ and LES turbulence models. The validation is based on rotor-based quantities of interest. Cycle-integrated mean absolute errors are used to quantify model performance. The results of the benchmark are usedmore » to discuss input uncertainties from mesoscale modelling, different meso-micro coupling strategies (online vs offline) and consistency between RANS and LES codes when dealing with boundary-layer mean flow quantities. Altogether, all the microscale simulations produce a consistent coupling with mesoscale forcings.« less

Results of the GABLS3 diurnal-cycle benchmark for wind energy applications

DOE PAGES

Rodrigo, J. Sanz; Allaerts, D.; Avila, M.; ...

2017-06-13

We present results of the GABLS3 model intercomparison benchmark revisited for wind energy applications. The case consists of a diurnal cycle, measured at the 200-m tall Cabauw tower in the Netherlands, including a nocturnal low-level jet. The benchmark includes a sensitivity analysis of WRF simulations using two input meteorological databases and five planetary boundary-layer schemes. A reference set of mesoscale tendencies is used to drive microscale simulations using RANS k-ϵ and LES turbulence models. The validation is based on rotor-based quantities of interest. Cycle-integrated mean absolute errors are used to quantify model performance. The results of the benchmark are usedmore » to discuss input uncertainties from mesoscale modelling, different meso-micro coupling strategies (online vs offline) and consistency between RANS and LES codes when dealing with boundary-layer mean flow quantities. Altogether, all the microscale simulations produce a consistent coupling with mesoscale forcings.« less

NASA/GEWEX shortwave surface radiation budget: Integrated data product with reprocessed radiance, cloud, and meteorology inputs, and new surface albedo treatment

NASA Astrophysics Data System (ADS)

Cox, Stephen J.; Stackhouse, Paul W.; Gupta, Shashi K.; Mikovitz, J. Colleen; Zhang, Taiping

2017-02-01

The NASA/GEWEX Surface Radiation Budget (SRB) project produces shortwave and longwave surface and top of atmosphere radiative fluxes for the 1983-near present time period. Spatial resolution is 1 degree. The current Release 3.0 (available at gewex-srb.larc.nasa.gov) uses the International Satellite Cloud Climatology Project (ISCCP) DX product for pixel level radiance and cloud information. This product is subsampled to 30 km. ISCCP is currently recalibrating and recomputing their entire data series, to be released as the H product, at 10km resolution. The ninefold increase in pixel number will allow SRB a higher resolution gridded product (e.g. 0.5 degree), as well as the production of pixel-level fluxes. Other key input improvements include a detailed aerosol history using the Max Planck Institute Aerosol Climatology (MAC), and temperature and moisture profiles from nnHIRS.

Remote sensing-aided systems for snow qualification, evapotranspiration estimation, and their application in hydrologic models

NASA Technical Reports Server (NTRS)

Korram, S.

1977-01-01

The design of general remote sensing-aided methodologies was studied to provide the estimates of several important inputs to water yield forecast models. These input parameters are snow area extent, snow water content, and evapotranspiration. The study area is Feather River Watershed (780,000 hectares), Northern California. The general approach involved a stepwise sequence of identification of the required information, sample design, measurement/estimation, and evaluation of results. All the relevent and available information types needed in the estimation process are being defined. These include Landsat, meteorological satellite, and aircraft imagery, topographic and geologic data, ground truth data, and climatic data from ground stations. A cost-effective multistage sampling approach was employed in quantification of all the required parameters. The physical and statistical models for both snow quantification and evapotranspiration estimation was developed. These models use the information obtained by aerial and ground data through appropriate statistical sampling design.

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.

A multi-year data set on aerosol-cloud-precipitation-meteorology interactions for marine stratocumulus clouds.

PubMed

Sorooshian, Armin; MacDonald, Alexander B; Dadashazar, Hossein; Bates, Kelvin H; Coggon, Matthew M; Craven, Jill S; Crosbie, Ewan; Hersey, Scott P; Hodas, Natasha; Lin, Jack J; Negrón Marty, Arnaldo; Maudlin, Lindsay C; Metcalf, Andrew R; Murphy, Shane M; Padró, Luz T; Prabhakar, Gouri; Rissman, Tracey A; Shingler, Taylor; Varutbangkul, Varuntida; Wang, Zhen; Woods, Roy K; Chuang, Patrick Y; Nenes, Athanasios; Jonsson, Haflidi H; Flagan, Richard C; Seinfeld, John H

2018-02-27

Airborne measurements of meteorological, aerosol, and stratocumulus cloud properties have been harmonized from six field campaigns during July-August months between 2005 and 2016 off the California coast. A consistent set of core instruments was deployed on the Center for Interdisciplinary Remotely-Piloted Aircraft Studies Twin Otter for 113 flight days, amounting to 514 flight hours. A unique aspect of the compiled data set is detailed measurements of aerosol microphysical properties (size distribution, composition, bioaerosol detection, hygroscopicity, optical), cloud water composition, and different sampling inlets to distinguish between clear air aerosol, interstitial in-cloud aerosol, and droplet residual particles in cloud. Measurements and data analysis follow documented methods for quality assurance. The data set is suitable for studies associated with aerosol-cloud-precipitation-meteorology-radiation interactions, especially owing to sharp aerosol perturbations from ship traffic and biomass burning. The data set can be used for model initialization and synergistic application with meteorological models and remote sensing data to improve understanding of the very interactions that comprise the largest uncertainty in the effect of anthropogenic emissions on radiative forcing.

A multi-year data set on aerosol-cloud-precipitation-meteorology interactions for marine stratocumulus clouds

PubMed Central

Sorooshian, Armin; MacDonald, Alexander B.; Dadashazar, Hossein; Bates, Kelvin H.; Coggon, Matthew M.; Craven, Jill S.; Crosbie, Ewan; Hersey, Scott P.; Hodas, Natasha; Lin, Jack J.; Negrón Marty, Arnaldo; Maudlin, Lindsay C.; Metcalf, Andrew R.; Murphy, Shane M.; Padró, Luz T.; Prabhakar, Gouri; Rissman, Tracey A.; Shingler, Taylor; Varutbangkul, Varuntida; Wang, Zhen; Woods, Roy K.; Chuang, Patrick Y.; Nenes, Athanasios; Jonsson, Haflidi H.; Flagan, Richard C.; Seinfeld, John H.

2018-01-01

Airborne measurements of meteorological, aerosol, and stratocumulus cloud properties have been harmonized from six field campaigns during July-August months between 2005 and 2016 off the California coast. A consistent set of core instruments was deployed on the Center for Interdisciplinary Remotely-Piloted Aircraft Studies Twin Otter for 113 flight days, amounting to 514 flight hours. A unique aspect of the compiled data set is detailed measurements of aerosol microphysical properties (size distribution, composition, bioaerosol detection, hygroscopicity, optical), cloud water composition, and different sampling inlets to distinguish between clear air aerosol, interstitial in-cloud aerosol, and droplet residual particles in cloud. Measurements and data analysis follow documented methods for quality assurance. The data set is suitable for studies associated with aerosol-cloud-precipitation-meteorology-radiation interactions, especially owing to sharp aerosol perturbations from ship traffic and biomass burning. The data set can be used for model initialization and synergistic application with meteorological models and remote sensing data to improve understanding of the very interactions that comprise the largest uncertainty in the effect of anthropogenic emissions on radiative forcing. PMID:29485627

A multi-year data set on aerosol-cloud-precipitation-meteorology interactions for marine stratocumulus clouds

NASA Astrophysics Data System (ADS)

Sorooshian, Armin; MacDonald, Alexander B.; Dadashazar, Hossein; Bates, Kelvin H.; Coggon, Matthew M.; Craven, Jill S.; Crosbie, Ewan; Hersey, Scott P.; Hodas, Natasha; Lin, Jack J.; Negrón Marty, Arnaldo; Maudlin, Lindsay C.; Metcalf, Andrew R.; Murphy, Shane M.; Padró, Luz T.; Prabhakar, Gouri; Rissman, Tracey A.; Shingler, Taylor; Varutbangkul, Varuntida; Wang, Zhen; Woods, Roy K.; Chuang, Patrick Y.; Nenes, Athanasios; Jonsson, Haflidi H.; Flagan, Richard C.; Seinfeld, John H.

2018-02-01

Airborne measurements of meteorological, aerosol, and stratocumulus cloud properties have been harmonized from six field campaigns during July-August months between 2005 and 2016 off the California coast. A consistent set of core instruments was deployed on the Center for Interdisciplinary Remotely-Piloted Aircraft Studies Twin Otter for 113 flight days, amounting to 514 flight hours. A unique aspect of the compiled data set is detailed measurements of aerosol microphysical properties (size distribution, composition, bioaerosol detection, hygroscopicity, optical), cloud water composition, and different sampling inlets to distinguish between clear air aerosol, interstitial in-cloud aerosol, and droplet residual particles in cloud. Measurements and data analysis follow documented methods for quality assurance. The data set is suitable for studies associated with aerosol-cloud-precipitation-meteorology-radiation interactions, especially owing to sharp aerosol perturbations from ship traffic and biomass burning. The data set can be used for model initialization and synergistic application with meteorological models and remote sensing data to improve understanding of the very interactions that comprise the largest uncertainty in the effect of anthropogenic emissions on radiative forcing.

The effect of environmental uncertainty on morphological design and fluid balance in Sarracenia purpurea L.

PubMed

Kingsolver, Joel

1981-03-01

To explore principles of organismic design in fluctuating environments, morphological design of the leaf of the pitcher-plant, Sarracenia purpurea, was studied for a population in northern Michigan. The design criterion focused upon the leaf shape and minimum size which effectively avoids leaf desiccation (complete loss of fluid from the leaf cavity) in the face of fluctuating rainfall and meteorological conditions. Bowl- and pitcher-shaped leaves were considered. Simulations show that the pitcher geometry experiences less frequent desiccation than bowls of the same size. Desiccation frequency is inversely related to leaf size; the size distribution of pitcher leaves in the field shows that the majority of pitchers desiccate only 1-3 times per season on average, while smaller pitchers may average up to 8 times per season. A linear filter model of an organism in a fluctuating environment is presented, in which the organism selectively filters the temporal patterns of environmental input. General measures of rainfall predictability based upon information theory and spectral analysis are consistent with the model of a pitcher leaf as a low-pass (frequency) filter which avoids desiccation by eliminating high-frequency rainfall variability.

MONET: multidimensional radiative cloud scene model

NASA Astrophysics Data System (ADS)

Chervet, Patrick

1999-12-01

All cloud fields exhibit variable structures (bulge) and heterogeneities in water distributions. With the development of multidimensional radiative models by the atmospheric community, it is now possible to describe horizontal heterogeneities of the cloud medium, to study these influences on radiative quantities. We have developed a complete radiative cloud scene generator, called MONET (French acronym for: MOdelisation des Nuages En Tridim.) to compute radiative cloud scene from visible to infrared wavelengths for various viewing and solar conditions, different spatial scales, and various locations on the Earth. MONET is composed of two parts: a cloud medium generator (CSSM -- Cloud Scene Simulation Model) developed by the Air Force Research Laboratory, and a multidimensional radiative code (SHDOM -- Spherical Harmonic Discrete Ordinate Method) developed at the University of Colorado by Evans. MONET computes images for several scenario defined by user inputs: date, location, viewing angles, wavelength, spatial resolution, meteorological conditions (atmospheric profiles, cloud types)... For the same cloud scene, we can output different viewing conditions, or/and various wavelengths. Shadowing effects on clouds or grounds are taken into account. This code is useful to study heterogeneity effects on satellite data for various cloud types and spatial resolutions, and to determine specifications of new imaging sensor.

Cloud rise model for radiological dispersal devices events

NASA Astrophysics Data System (ADS)

Sharon, Avi; Halevy, Itzhak; Sattinger, Daniel; Yaar, Ilan

2012-07-01

As a part of the preparedness and response to possible radiological terror events, it is important to model the evolution of the radioactive cloud immediately after its formation, as a function of time, explosive quantity and local meteorological conditions. One of the major outputs of a cloud rise models is the evaluation of cloud top height, which is an essential input for most of the succeeding atmospheric dispersion models. This parameter strongly affects the radiological consequences of the event. Most of the cloud rise models used today, have been developed according to experiments were large quantities of explosives were used, within the range of hundreds of kilograms of TNT. The majority of these models, however, fail to address Radiological Dispersion Devices (RDD) events, which are typically characterized by smaller amounts of TNT. In this paper, a new, semi-empirical model that describes the vertical evolution of the cloud up to its effective height as a function of time, explosive quantity, atmospheric stability and horizontal wind speed, is presented. The database for this model is taken from five sets of experiments done in Israel during 2006-2009 under the "Green Field" (GF) project, using 0.25-100 kg of TNT.

Uncertainties of isoprene emissions in the MEGAN model estimated for a coniferous and broad-leaved mixed forest in Southern China

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

Situ, S.; Wang, Xuemei; Guenther, Alex B.

2014-12-01

Using local observed emission factor, meteorological data, vegetation 5 information and dynamic MODIS LAI, MEGANv2.1 was constrained to predict the isoprene emission from Dinghushan forest in the Pearl River Delta region during a field campaign in November 2008, and the uncertainties in isoprene emission estimates were quantified by the Monte Carlo approach. The results indicate that MEGAN can predict the isoprene emission reasonably during the campaign, and the mean value of isoprene emission is 2.35 mg m-2 h-1 in daytime. There are high uncertainties associated with the MEGAN inputs and calculated parameters, and the relative error can be as highmore » as -89 to 111% for a 95% confidence interval. The emission factor of broadleaf trees and the activity factor accounting for light and temperature dependence are the most important contributors to the uncertainties in isoprene emission estimated for the Dinghushan forest during the campaign. The results also emphasize the importance of accurate observed PAR and temperature to reduce the uncertainties in isoprene emission estimated by model, because the MEGAN model activity factor accounting for light and temperature dependence is highly sensitive to PAR and temperature.« less

Improvements to the gridding of precipitation data across Europe under the E-OBS scheme

NASA Astrophysics Data System (ADS)

Cornes, Richard; van den Besselaar, Else; Jones, Phil; van der Schrier, Gerard; Verver, Ge

2016-04-01

Gridded precipitation data are a valuable resource for analyzing past variations and trends in the hydroclimate. Such data also provide a reference against which model simulations may be driven, compared and/or adjusted. The E-OBS precipitation dataset is widely used for such analyses across Europe, and is particularly valuable since it provides a spatially complete, daily field across the European domain. In this analysis, improvements to the E-OBS precipitation dataset will be presented that aim to provide a more reliable estimate of grid-box precipitation values, particularly in mountainous areas and in regions with a relative sparsity of input station data. The established three-stage E-OBS gridding scheme is retained, whereby monthly precipitation totals are gridded using a thin-plate spline; daily anomalies are gridded using indicator kriging; and the final dataset is produced by multiplying the two grids. The current analysis focuses on improving the monthly thin-plate spline, which has overall control on the final daily dataset. The results from different techniques are compared and the influence on the final daily data is assessed by comparing the data against gridded country-wide datasets produced by various National Meteorological Services

New technique for ensemble dressing combining Multimodel SuperEnsemble and precipitation PDF

NASA Astrophysics Data System (ADS)

Cane, D.; Milelli, M.

2009-09-01

The Multimodel SuperEnsemble technique (Krishnamurti et al., Science 285, 1548-1550, 1999) is a postprocessing method for the estimation of weather forecast parameters reducing direct model output errors. It differs from other ensemble analysis techniques by the use of an adequate weighting of the input forecast models to obtain a combined estimation of meteorological parameters. Weights are calculated by least-square minimization of the difference between the model and the observed field during a so-called training period. Although it can be applied successfully on the continuous parameters like temperature, humidity, wind speed and mean sea level pressure (Cane and Milelli, Meteorologische Zeitschrift, 15, 2, 2006), the Multimodel SuperEnsemble gives good results also when applied on the precipitation, a parameter quite difficult to handle with standard post-processing methods. Here we present our methodology for the Multimodel precipitation forecasts applied on a wide spectrum of results over Piemonte very dense non-GTS weather station network. We will focus particularly on an accurate statistical method for bias correction and on the ensemble dressing in agreement with the observed precipitation forecast-conditioned PDF. Acknowledgement: this work is supported by the Italian Civil Defence Department.

Linking the M&Rfi Weather Generator with Agrometeorological Models

NASA Astrophysics Data System (ADS)

Dubrovsky, Martin; Trnka, Miroslav

2015-04-01

Realistic meteorological inputs (representing the present and/or future climates) for the agrometeorological model simulations are often produced by stochastic weather generators (WGs). This contribution presents some methodological issues and results obtained in our recent experiments. We also address selected questions raised in the synopsis of this session. The input meteorological time series for our experiments are produced by the parametric single site weather generator (WG) Marfi, which is calibrated from the available observational data (or interpolated from surrounding stations). To produce meteorological series representing the future climate, the WG parameters are modified by climate change scenarios, which are prepared by the pattern scaling method: the standardised scenarios derived from Global or Regional Climate Models are multiplied by the change in global mean temperature (ΔTG) determined by the simple climate model MAGICC. The presentation will address following questions: (i) The dependence of the quality of the synthetic weather series and impact results on the WG settings. An emphasis will be put on an effect of conditioning the daily WG on monthly WG (presently being one of our hot topics), which aims at improvement of the reproduction of the low-frequency weather variability. Comparison of results obtained with various WG settings is made in terms of climatic and agroclimatic indices (including extreme temperature and precipitation characteristics and drought indices). (ii) Our methodology accounts for the uncertainties coming from various sources. We will show how the climate change impact results are affected by 1. uncertainty in climate modelling, 2. uncertainty in ΔTG, and 3. uncertainty related to the complexity of the climate change scenario (focusing on an effect of inclusion of changes in variability into the climate change scenarios). Acknowledgements: This study was funded by project "Building up a multidisciplinary scientific team focused on drought" No. CZ.1.07/2.3.00/20.0248. The weather generator is being developed within the frame of WG4VALUE project (LD12029), which is supported by Ministry of Education, Youth and Sports and linked to the COST action ES1102 VALUE.

Operational applications of a process-based runoff generation module on the Swiss Plateau and Prealps

NASA Astrophysics Data System (ADS)

Horat, Christoph; Antonetti, Manuel; Wernli, Heini; Zappa, Massimiliano

2017-04-01

Flash floods evolve rapidly during and after heavy precipitation events and represent a risk for society, especially in mountainous areas. Knowledge on meteorological variables and their temporal development is often not sufficient to predict their occurrence. Therefore, information about the state of the hydrological system derived from hydrological models is used. These models rely however on strong simplifying assumptions and need therefore to be calibrated. This prevents their application on catchments, where no runoff data is available. Here we present a flash-flood forecasting chain including: (i) a nowcasting product which combines radar and rain gauge rainfall data (CombiPrecip), (ii) meteorological data from numerical weather prediction models at currently finest available resolution (COSMO-1, COSMO-E), (iii) operationally available soil moisture estimations from the PREVAH hydrological model, and (iv) a process-based runoff generation module with no need for calibration (RGM-PRO). This last component uses information on the spatial distribution of dominant runoff processes (DRPs) which can be derived with different mapping approaches, and is parameterised a priori based on expert knowledge. First, we compared the performance of RGM-PRO with the one of a traditional conceptual runoff generation module for several events on Swiss Emme catchment, as well as on their nested catchments. Different DRP-maps are furthermore tested to evaluate the sensitivity of the forecasting chain to the mapping approaches. Then, we benchmarked the new forecasting chain with the traditional chain used on the Swiss Verzasca catchment. The results show that RGM-PRO performs similarly or even better than the traditional calibrated conceptual module on the investigated catchments. The use of strongly simplified DRP mapping approaches still leads to satisfying results, due mainly to the fact that the largest uncertainty source is represented by the meteorological input data. On the Verzasca catchment, RGM-PRO outperformed the traditional forecast chain in terms of mean absolute error, independently from the lead time and threshold quantile, whereas the Brier Skill Score did not show any clear preference. Probabilistic input data led generally to better results compared with those obtained with deterministic forecasts.

Sensitivity of ocean model simulation in the coastal ocean to the resolution of the meteorological forcing

NASA Astrophysics Data System (ADS)

Chen, Feng; Shapiro, Georgy; Thain, Richard

2013-04-01

The quality of ocean simulations depends on a number of factors such as approximations in governing equations, errors introduced by the numerical scheme, uncertainties in input parameters, and atmospheric forcing. The identification of relations between the uncertainties in input and output data is still a challenge for the development of numerical models. The impacts of ocean variables on ocean models are still not well known (e.g., Kara et al., 2009). Given the considerable importance of the atmospheric forcing to the air-sea interaction, it is essential that researchers in ocean modelling work need a good understanding about how sensitive the atmospheric forcing is to variations of model results, which is beneficial to the development of ocean models. Also, it provides a proper way to choose the atmospheric forcing in ocean modelling applications. Our previous study (Shapiro et al, 2011) has shown that the basin-wide circulation pattern and the temperature structure in the Black Sea produced by the same model is significantly dependent on the source of the meteorological input, giving remarkably different responses. For the purpose of this study we have chosen the Celtic Sea where high resolution meteo data are available from the UK Met office since 2006. The Celtic Sea is tidally dominated water basin, with the tidal stream amplitude varying from 0.25m/s in the southwest to 2 m/s in the Bristol Channel. It is also filled with mesoscale eddies which contribute to the formation of the residual (tidally averaged) circulation pattern (Young et al, 2003). The sea is strongly stratified from April to November, which adds to the formation of density driven currents. In this paper we analyse how sensitive the model output is to variations in the spatial resolution of meteorological using low (1.6°) and high (0.11°) resolution meteo forcing, giving the quantitative relation between variations of met forcing and the resulted differences of model results, as well as identifying the causes. The length scales of most energetic dynamic features in both ocean and atmosphere are defined by the Rossby radius of deformation, which is about 1000 km (a typical size of a cyclone) in the atmosphere while only 10-20 km (a size of a mesoscale eddy) in a shallow sea. However sub-mesoscale atmospheric patterns such as patchiness in the cloud cover could result in smaller scale variations of both the wind and solar radiation hence creating a direct link of these smaller atmospheric features with the ocean mesoscale variability. The simulation has been performed using a version of POLCOMS numerical model (Enriquez et al, 2005). Tidal boundary conditions were taken from the Oregon State University European Shelf Tidal Model (Egbert et al, 2010) and the temperature/ salinity initial fields and boundary conditions were taken from the World Ocean Database (Boyer et al, 2004). The paper discusses what elements of the circulation and water column structure are mostly sensitive to the meteo-fields resolution. References Kara, A.B., Wallcraft, A.J., Hurlburt, H.E., Loh, W.-Y., 2009. Which surface atmospheric variable drives the seasonal cycle of sea surface temperature over the global ocean? Journal of Geophysical Research, Vol. 114, D05101. Boyer, .T, S. Levitus, H. Garcia, R. Locarnini, C. Stephens, and J. Antonov, T. Boyer, S. Levitus, H. Garcia, R. Locarnini, C. Stephens, and J. Antonov, 2004. Objective Analyses of Annual, Seasonal, and Monthly Temperature and Salinity for the World Ocean on a ¼ Grid. International Journal of Climatology, 25, 931-945. Egbert, G. D., S. Y. Erofeeva, and R. D. Ray, 2010. Assimilation of altimetry data for nonlinear shallow-water tides: quarter-diurnal tides of the Northwest European Shelf, Continental Shelf Research, 30, 668-679. Enriquez, C. E., G. I. Shapiro, A. J. Souza, and A. G. Zatsepin, 2005. Hydrodynamic modelling of mesoscale eddies in the Black Sea. Ocean Dyn., 55, 476-489. Georgy Shapiro, Dmitry Aleynik , Andrei Zatsepin , Valentina Khan, Valery Prostakishin , Tatiana Akivis , Vladimir Belokopytov , Anton Sviridov , and Vladimir Piotukh . 2011. Response of water temperature in the Black Sea to atmospheric forcing: the sensitivity study. Geophysical Research Abstracts. Vol. 13, EGU2011-933

Fast computation of derivative based sensitivities of PSHA models via algorithmic differentiation

NASA Astrophysics Data System (ADS)

Leövey, Hernan; Molkenthin, Christian; Scherbaum, Frank; Griewank, Andreas; Kuehn, Nicolas; Stafford, Peter

2015-04-01

Probabilistic seismic hazard analysis (PSHA) is the preferred tool for estimation of potential ground-shaking hazard due to future earthquakes at a site of interest. A modern PSHA represents a complex framework which combines different models with possible many inputs. Sensitivity analysis is a valuable tool for quantifying changes of a model output as inputs are perturbed, identifying critical input parameters and obtaining insight in the model behavior. Differential sensitivity analysis relies on calculating first-order partial derivatives of the model output with respect to its inputs. Moreover, derivative based global sensitivity measures (Sobol' & Kucherenko '09) can be practically used to detect non-essential inputs of the models, thus restricting the focus of attention to a possible much smaller set of inputs. Nevertheless, obtaining first-order partial derivatives of complex models with traditional approaches can be very challenging, and usually increases the computation complexity linearly with the number of inputs appearing in the models. In this study we show how Algorithmic Differentiation (AD) tools can be used in a complex framework such as PSHA to successfully estimate derivative based sensitivities, as is the case in various other domains such as meteorology or aerodynamics, without no significant increase in the computation complexity required for the original computations. First we demonstrate the feasibility of the AD methodology by comparing AD derived sensitivities to analytically derived sensitivities for a basic case of PSHA using a simple ground-motion prediction equation. In a second step, we derive sensitivities via AD for a more complex PSHA study using a ground motion attenuation relation based on a stochastic method to simulate strong motion. The presented approach is general enough to accommodate more advanced PSHA studies of higher complexity.

Long Island Sound Tropospheric Ozone Study (LISTOS) Fact Sheet

EPA Pesticide Factsheets

EPA scientists are collaborating on a multi-agency field study to investigate the complex interaction of emissions, chemistry and meteorological factors contributing to elevated ozone levels along the Long Island Sound shoreline.

Helicity in dynamic atmospheric processes

NASA Astrophysics Data System (ADS)

Kurgansky, M. V.

2017-03-01

An overview on the helicity of the velocity field and the role played by this concept in modern research in the field of geophysical fluid dynamics and dynamic meteorology is given. Different (both previously known in the literature and first presented) formulations of the equation of helicity balance in atmospheric motions (including those with allowance for effects of air compressibility and Earth's rotation) are brought together. Equations and relationships are given which are valid in different approximations accepted in dynamic meteorology: Boussinesq approximation, quasi-static approximation, and quasi-geostrophic approximation. Emphasis is placed on the analysis of helicity budget in large-scale quasi-geostrophic systems of motion; a formula for the helicity flux across the upper boundary of the nonlinear Ekman boundary layer is given, and this flux is shown to be exactly compensated for by the helicity destruction inside the Ekman boundary layer.

Impact of shade on outdoor thermal comfort—a seasonal field study in Tempe, Arizona

NASA Astrophysics Data System (ADS)

Middel, Ariane; Selover, Nancy; Hagen, Björn; Chhetri, Nalini

2016-12-01

Shade plays an important role in designing pedestrian-friendly outdoor spaces in hot desert cities. This study investigates the impact of photovoltaic canopy shade and tree shade on thermal comfort through meteorological observations and field surveys at a pedestrian mall on Arizona State University's Tempe campus. During the course of 1 year, on selected clear calm days representative of each season, we conducted hourly meteorological transects from 7:00 a.m. to 6:00 p.m. and surveyed 1284 people about their thermal perception, comfort, and preferences. Shade lowered thermal sensation votes by approximately 1 point on a semantic differential 9-point scale, increasing thermal comfort in all seasons except winter. Shade type (tree or solar canopy) did not significantly impact perceived comfort, suggesting that artificial and natural shades are equally efficient in hot dry climates. Globe temperature explained 51 % of the variance in thermal sensation votes and was the only statistically significant meteorological predictor. Important non-meteorological factors included adaptation, thermal comfort vote, thermal preference, gender, season, and time of day. A regression of subjective thermal sensation on physiological equivalent temperature yielded a neutral temperature of 28.6 °C. The acceptable comfort range was 19.1 °C-38.1 °C with a preferred temperature of 20.8 °C. Respondents exposed to above neutral temperature felt more comfortable if they had been in air-conditioning 5 min prior to the survey, indicating a lagged response to outdoor conditions. Our study highlights the importance of active solar access management in hot urban areas to reduce thermal stress.

Methods of Data Collection, Sample Processing, and Data Analysis for Edge-of-Field, Streamgaging, Subsurface-Tile, and Meteorological Stations at Discovery Farms and Pioneer Farm in Wisconsin, 2001-7

USGS Publications Warehouse

Stuntebeck, Todd D.; Komiskey, Matthew J.; Owens, David W.; Hall, David W.

2008-01-01

The University of Wisconsin (UW)-Madison Discovery Farms (Discovery Farms) and UW-Platteville Pioneer Farm (Pioneer Farm) programs were created in 2000 to help Wisconsin farmers meet environmental and economic challenges. As a partner with each program, and in cooperation with the Wisconsin Department of Natural Resources and the Sand County Foundation, the U.S. Geological Survey (USGS) Wisconsin Water Science Center (WWSC) installed, maintained, and operated equipment to collect water-quantity and water-quality data from 25 edge-offield, 6 streamgaging, and 5 subsurface-tile stations at 7 Discovery Farms and Pioneer Farm. The farms are located in the southern half of Wisconsin and represent a variety of landscape settings and crop- and animal-production enterprises common to Wisconsin agriculture. Meteorological stations were established at most farms to measure precipitation, wind speed and direction, air and soil temperature (in profile), relative humidity, solar radiation, and soil moisture (in profile). Data collection began in September 2001 and is continuing through the present (2008). This report describes methods used by USGS WWSC personnel to collect, process, and analyze water-quantity, water-quality, and meteorological data for edge-of-field, streamgaging, subsurface-tile, and meteorological stations at Discovery Farms and Pioneer Farm from September 2001 through October 2007. Information presented includes equipment used; event-monitoring and samplecollection procedures; station maintenance; sample handling and processing procedures; water-quantity, waterquality, and precipitation data analyses; and procedures for determining estimated constituent concentrations for unsampled runoff events.

Objective high Resolution Analysis over Complex Terrain with VERA

NASA Astrophysics Data System (ADS)

Mayer, D.; Steinacker, R.; Steiner, A.

2012-04-01

VERA (Vienna Enhanced Resolution Analysis) is a model independent, high resolution objective analysis of meteorological fields over complex terrain. This system consists of a special developed quality control procedure and a combination of an interpolation and a downscaling technique. Whereas the so called VERA-QC is presented at this conference in the contribution titled "VERA-QC, an approved Data Quality Control based on Self-Consistency" by Andrea Steiner, this presentation will focus on the method and the characteristics of the VERA interpolation scheme which enables one to compute grid point values of a meteorological field based on irregularly distributed observations and topography related aprior knowledge. Over a complex topography meteorological fields are not smooth in general. The roughness which is induced by the topography can be explained physically. The knowledge about this behavior is used to define the so called Fingerprints (e.g. a thermal Fingerprint reproducing heating or cooling over mountainous terrain or a dynamical Fingerprint reproducing positive pressure perturbation on the windward side of a ridge) under idealized conditions. If the VERA algorithm recognizes patterns of one or more Fingerprints at a few observation points, the corresponding patterns are used to downscale the meteorological information in a greater surrounding. This technique allows to achieve an analysis with a resolution much higher than the one of the observational network. The interpolation of irregularly distributed stations to a regular grid (in space and time) is based on a variational principle applied to first and second order spatial and temporal derivatives. Mathematically, this can be formulated as a cost function that is equivalent to the penalty function of a thin plate smoothing spline. After the analysis field has been divided into the Fingerprint components and the unexplained part respectively, the requirement of a smooth distribution is applied to the latter component only (the Fingerprint field is rough by definition). In order to obtain the final analysis field, the unexplained component has to be combined with the weighted Fingerprint patterns. Operationally, VERA is carried out at our Department on an hourly basis analyzing temperature measurements, pressure, wind and precipitation observations for several domains of the whole world. VERA analyses are used for nowcasting purposes, for establishing climate databases and model verification. Furthermore, VERA can be interesting for everyone who possesses a PC but does not have access to a complex data assimilation system which is in general only available at numerical weather prediction centers.

How do I know if my forecasts are better? Using benchmarks in hydrological ensemble prediction

NASA Astrophysics Data System (ADS)

Pappenberger, F.; Ramos, M. H.; Cloke, H. L.; Wetterhall, F.; Alfieri, L.; Bogner, K.; Mueller, A.; Salamon, P.

2015-03-01

The skill of a forecast can be assessed by comparing the relative proximity of both the forecast and a benchmark to the observations. Example benchmarks include climatology or a naïve forecast. Hydrological ensemble prediction systems (HEPS) are currently transforming the hydrological forecasting environment but in this new field there is little information to guide researchers and operational forecasters on how benchmarks can be best used to evaluate their probabilistic forecasts. In this study, it is identified that the forecast skill calculated can vary depending on the benchmark selected and that the selection of a benchmark for determining forecasting system skill is sensitive to a number of hydrological and system factors. A benchmark intercomparison experiment is then undertaken using the continuous ranked probability score (CRPS), a reference forecasting system and a suite of 23 different methods to derive benchmarks. The benchmarks are assessed within the operational set-up of the European Flood Awareness System (EFAS) to determine those that are 'toughest to beat' and so give the most robust discrimination of forecast skill, particularly for the spatial average fields that EFAS relies upon. Evaluating against an observed discharge proxy the benchmark that has most utility for EFAS and avoids the most naïve skill across different hydrological situations is found to be meteorological persistency. This benchmark uses the latest meteorological observations of precipitation and temperature to drive the hydrological model. Hydrological long term average benchmarks, which are currently used in EFAS, are very easily beaten by the forecasting system and the use of these produces much naïve skill. When decomposed into seasons, the advanced meteorological benchmarks, which make use of meteorological observations from the past 20 years at the same calendar date, have the most skill discrimination. They are also good at discriminating skill in low flows and for all catchment sizes. Simpler meteorological benchmarks are particularly useful for high flows. Recommendations for EFAS are to move to routine use of meteorological persistency, an advanced meteorological benchmark and a simple meteorological benchmark in order to provide a robust evaluation of forecast skill. This work provides the first comprehensive evidence on how benchmarks can be used in evaluation of skill in probabilistic hydrological forecasts and which benchmarks are most useful for skill discrimination and avoidance of naïve skill in a large scale HEPS. It is recommended that all HEPS use the evidence and methodology provided here to evaluate which benchmarks to employ; so forecasters can have trust in their skill evaluation and will have confidence that their forecasts are indeed better.