Modeling crop residue burning experiments and assessing the fire impacts on air quality

EPA Science Inventory

Prescribed burning is a common land management practice that results in ambient emissions of a variety of primary and secondary pollutants with negative health impacts. The community Multiscale Air Quality (CMAQ) model is used to conduct 2 km grid resolution simulations of prescr...

Air quality high resolution simulations of Italian urban areas with WRF-CHIMERE

NASA Astrophysics Data System (ADS)

Falasca, Serena; Curci, Gabriele

2017-04-01

The new European Directive on ambient air quality and cleaner air for Europe (2008/50/EC) encourages the use of modeling techniques to support the observations in the assessment and forecasting of air quality. The modelling system based on the combination of the WRF meteorological model and the CHIMERE chemistry-transport model is used to perform simulations at high resolution over the main Italian cities (e.g. Milan, Rome). Three domains covering Europe, Italy and the urban areas are nested with a decreasing grid size up to 1 km. Numerical results are produced for a winter month and a summer month of the year 2010 and are validated using ground-based observations (e.g. from the European air quality database AirBase). A sensitivity study is performed using different physics options, domain resolution and grid ratio; different urban parameterization schemes are tested using also characteristic morphology parameters for the cities considered. A spatial reallocation of anthropogenic emissions derived from international (e.g. EMEP, TNO, HTAP) and national (e.g. CTN-ACE) emissions inventories and based on the land cover datasets (Global Land Cover Facility and GlobCover) and the OpenStreetMap tool is also included. Preliminary results indicate that the introduction of the spatial redistribution at high-resolution allows a more realistic reproduction of the distribution of the emission flows and thus the concentrations of the pollutants, with significant advantages especially for the urban environments.

Microscale anthropogenic pollution modelling in a small tropical island during weak trade winds: Lagrangian particle dispersion simulations using real nested LES meteorological fields

NASA Astrophysics Data System (ADS)

Cécé, Raphaël; Bernard, Didier; Brioude, Jérome; Zahibo, Narcisse

2016-08-01

Tropical islands are characterized by thermal and orographical forcings which may generate microscale air mass circulations. The Lesser Antilles Arc includes small tropical islands (width lower than 50 km) where a total of one-and-a-half million people live. Air quality over this region is affected by anthropogenic and volcanic emissions, or saharan dust. To reduce risks for the population health, the atmospheric dispersion of emitted pollutants must be predicted. In this study, the dispersion of anthropogenic nitrogen oxides (NOx) is numerically modelled over the densely populated area of the Guadeloupe archipelago under weak trade winds, during a typical case of severe pollution. The main goal is to analyze how microscale resolutions affect air pollution in a small tropical island. Three resolutions of domain grid are selected: 1 km, 333 m and 111 m. The Weather Research and Forecasting model (WRF) is used to produce real nested microscale meteorological fields. Then the weather outputs initialize the Lagrangian Particle Dispersion Model (FLEXPART). The forward simulations of a power plant plume showed good ability to reproduce nocturnal peaks recorded by an urban air quality station. The increase in resolution resulted in an improvement of model sensitivity. The nesting to subkilometer grids helped to reduce an overestimation bias mainly because the LES domains better simulate the turbulent motions governing nocturnal flows. For peaks observed at two air quality stations, the backward sensitivity outputs identified realistic sources of NOx in the area. The increase in resolution produced a sharper inverse plume with a more accurate source area. This study showed the first application of the FLEXPART-WRF model to microscale resolutions. Overall, the coupling model WRF-LES-FLEXPART is useful to simulate the pollutant dispersion during a real case of calm wind regime over a complex terrain area. The forward and backward simulation results showed clearly that the subkilometer resolution of 333 m is necessary to reproduce realistic air pollution patterns in this case of short-range transport over a complex terrain area. Globally, this work contributes to enrich the sparsely documented domain of real nested microscale air pollution modelling. This study dealing with the determination of the proper resolution grid and proper turbulence scheme, is of significant interest to the near-source and complex terrain air quality research community.

A Variable-Resolution Stretched-Grid General Circulation Model and Data Assimilation System with Multiple Areas of Interest: Studying the Anomalous Regional Climate Events of 1998

NASA Technical Reports Server (NTRS)

Fox-Rabinovitz, Michael S.; Takacs, Lawrence; Govindaraju, Ravi C.; Atlas, Robert (Technical Monitor)

2002-01-01

The new stretched-grid design with multiple (four) areas of interest, one at each global quadrant, is implemented into both a stretched-grid GCM (general circulation model) and a stretched-grid data assimilation system (DAS). The four areas of interest include: the U.S./Northern Mexico, the El Nino area/Central South America, India/China, and the Eastern Indian Ocean/Australia. Both the stretched-grid GCM and DAS annual (November 1997 through December 1998) integrations are performed with 50 km regional resolution. The efficient regional down-scaling to mesoscales is obtained for each of the four areas of interest while the consistent interactions between regional and global scales and the high quality of global circulation, are preserved. This is the advantage of the stretched-grid approach. The global variable resolution DAS incorporating the stretched-grid GCM has been developed and tested as an efficient tool for producing regional analyses and diagnostics with enhanced mesoscale resolution. The anomalous regional climate events of 1998 that occurred over the U.S., Mexico, South America, China, India, African Sahel, and Australia are investigated in both simulation and data assimilation modes. Tree assimilated products are also used, along with gauge precipitation data, for validating the simulation results. The obtained results show that the stretched-grid GCM and DAS are capable of producing realistic high quality simulated and assimilated products at mesoscale resolution for regional climate studies and applications.

Research on the optimization of air quality monitoring station layout based on spatial grid statistical analysis method.

PubMed

Li, Tianxin; Zhou, Xing Chen; Ikhumhen, Harrison Odion; Difei, An

2018-05-01

In recent years, with the significant increase in urban development, it has become necessary to optimize the current air monitoring stations to reflect the quality of air in the environment. Highlighting the spatial representation of some air monitoring stations using Beijing's regional air monitoring station data from 2012 to 2014, the monthly mean particulate matter concentration (PM10) in the region was calculated and through the IDW interpolation method and spatial grid statistical method using GIS, the spatial distribution of PM10 concentration in the whole region was deduced. The spatial distribution variation of districts in Beijing using the gridding model was performed, and through the 3-year spatial analysis, PM10 concentration data including the variation and spatial overlay (1.5 km × 1.5 km cell resolution grid), the spatial distribution result obtained showed that the total PM10 concentration frequency variation exceeded the standard. It is very important to optimize the layout of the existing air monitoring stations by combining the concentration distribution of air pollutants with the spatial region using GIS.

Modelling the urban air quality in Hamburg with the new city-scale chemistry transport model CityChem

NASA Astrophysics Data System (ADS)

Karl, Matthias; Ramacher, Martin; Aulinger, Armin; Matthias, Volker; Quante, Markus

2017-04-01

Air quality modelling plays an important role by providing guidelines for efficient air pollution abatement measures. Currently, most urban dispersion models treat air pollutants as passive tracer substances or use highly simplified chemistry when simulating air pollutant concentrations on the city-scale. The newly developed urban chemistry-transport model CityChem has the capability of modelling the photochemical transformation of multiple pollutants along with atmospheric diffusion to produce pollutant concentration fields for the entire city on a horizontal resolution of 100 m or even finer and a vertical resolution of 24 layers up to 4000 m height. CityChem is based on the Eulerian urban dispersion model EPISODE of the Norwegian Institute for Air Research (NILU). CityChem treats the complex photochemistry in cities using detailed EMEP chemistry on an Eulerian 3-D grid, while using simple photo-stationary equilibrium on a much higher resolution grid (receptor grid), i.e. close to industrial point sources and traffic sources. The CityChem model takes into account that long-range transport contributes to urban pollutant concentrations. This is done by using 3-D boundary concentrations for the city domain derived from chemistry-transport simulations with the regional air quality model CMAQ. For the study of the air quality in Hamburg, CityChem was set-up with a main grid of 30×30 grid cells of 1×1 km2 each and a receptor grid of 300×300 grid cells of 100×100 m2. The CityChem model was driven with meteorological data generated by the prognostic meteorology component of the Australian chemistry-transport model TAPM. Bottom-up inventories of emissions from traffic, industry, households were based on data of the municipality of Hamburg. Shipping emissions for the port of Hamburg were taken from the Clean North Sea Shipping project. Episodes with elevated ozone (O3) were of specific interest for this study, as these are associated with exceedances of the World Health Organization (WHO) guideline concentration limits for O3 and of the regulatory limits for NO2. Model tests were performed with CityChem to study the ozone formation rate with simultaneous variation of emissions of nitrogen oxides (NOx) and volatile organic compounds (VOC). Emissions of VOC in urban areas are not well quantified as they may originate from various sources, including solvent usage, industry, combustion plants and vehicular traffic. The employed chemical mechanism contains large uncertainties with respect to ozone formation. Observed high-O3 episodes were analyzed by comparing modelled pollutant concentrations with concentration data from the Hamburg air quality surveillance network (http://luft.hamburg.de/). The analysis inspected possible reasons for too low modelled O3 in summer such as missing emissions of VOC from natural sources like green parks and the vertical exchange of O3 towards the surface.

A Multi-Resolution Assessment of the Community Multiscale Air Quality (CMAQ) Model v4.7 Wet Deposition Estimates for 2002 - 2006

EPA Science Inventory

This paper examines the operational performance of the Community Multiscale Air Quality (CMAQ) model simulations for 2002 - 2006 using both 36-km and 12-km horizontal grid spacing, with a primary focus on the performance of the CMAQ model in predicting wet deposition of sulfate (...

Effects of Grid Resolution on Modeled Air Pollutant Concentrations Due to Emissions from Large Point Sources: Case Study during KORUS-AQ 2016 Campaign

NASA Astrophysics Data System (ADS)

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

2017-12-01

Large point sources in the Chungnam area received a nation-wide attention in South Korea because the area is located southwest of the Seoul Metropolitan Area whose population is over 22 million and the summertime prevalent winds in the area is northeastward. Therefore, emissions from the large point sources in the Chungnam area were one of the major observation targets during the KORUS-AQ 2016 including aircraft measurements. In general, horizontal grid resolutions of eulerian photochemical models have profound effects on estimated air pollutant concentrations. It is due to the formulation of grid models; that is, emissions in a grid cell will be assumed to be mixed well under planetary boundary layers regardless of grid cell sizes. In this study, we performed series of simulations with the Comprehensive Air Quality Model with eXetension (CAMx). For 9-km and 3-km simulations, we used meteorological fields obtained from the Weather Research and Forecast model while utilizing the "Flexi-nesting" option in the CAMx for the 1-km simulation. In "Flexi-nesting" mode, CAMx interpolates or assigns model inputs from the immediate parent grid. We compared modeled concentrations with ground observation data as well as aircraft measurements to quantify variations of model bias and error depending on horizontal grid resolutions.

High resolution estimates of the corrosion risk for cultural heritage in Italy.

PubMed

De Marco, Alessandra; Screpanti, Augusto; Mircea, Mihaela; Piersanti, Antonio; Proietti, Chiara; Fornasier, M Francesca

2017-07-01

Air pollution plays a pivotal role in the deterioration of many materials used in buildings and cultural monuments causing an inestimable damage. This study aims to estimate the impacts of air pollution (SO 2 , HNO 3 , O 3 , PM 10 ) and meteorological conditions (temperature, precipitation, relative humidity) on limestone, copper and bronze based on high resolution air quality data-base produced with AMS-MINNI modelling system over the Italian territory over the time period 2003-2010. A comparison between high resolution data (AMS-MINNI grid, 4 × 4 km) and low resolution data (EMEP grid, 50 × 50 km) has been performed. Our results pointed out that the corrosion levels for limestone, copper and bronze are decreased in Italy from 2003 to 2010 in relation to decrease of pollutant concentrations. However, some problem related to air pollution persists especially in Northern and Southern Italy. In particular, PM 10 and HNO 3 are considered the main responsible for limestone corrosion. Moreover, the high resolution data (AMS-MINNI) allowed the identification of risk areas that are not visible with the low resolution data (EMEP modelling system) in all considered years and, especially, in the limestone case. Consequently, high resolution air quality simulations are suitable to provide concrete benefits in providing information for national effective policy against corrosion risk for cultural heritage, also in the context of climate changes that are affecting strongly Mediterranean basin. Copyright © 2017 Elsevier Ltd. All rights reserved.

Statistical Downscaling of WRF-Chem Model: An Air Quality Analysis over Bogota, Colombia

NASA Astrophysics Data System (ADS)

Kumar, Anikender; Rojas, Nestor

2015-04-01

Statistical downscaling is a technique that is used to extract high-resolution information from regional scale variables produced by coarse resolution models such as Chemical Transport Models (CTMs). The fully coupled WRF-Chem (Weather Research and Forecasting with Chemistry) model is used to simulate air quality over Bogota. Bogota is a tropical Andean megacity located over a high-altitude plateau in the middle of very complex terrain. The WRF-Chem model was adopted for simulating the hourly ozone concentrations. The computational domains were chosen of 120x120x32, 121x121x32 and 121x121x32 grid points with horizontal resolutions of 27, 9 and 3 km respectively. The model was initialized with real boundary conditions using NCAR-NCEP's Final Analysis (FNL) and a 1ox1o (~111 km x 111 km) resolution. Boundary conditions were updated every 6 hours using reanalysis data. The emission rates were obtained from global inventories, namely the REanalysis of the TROpospheric (RETRO) chemical composition and the Emission Database for Global Atmospheric Research (EDGAR). Multiple linear regression and artificial neural network techniques are used to downscale the model output at each monitoring stations. The results confirm that the statistically downscaled outputs reduce simulated errors by up to 25%. This study provides a general overview of statistical downscaling of chemical transport models and can constitute a reference for future air quality modeling exercises over Bogota and other Colombian cities.

Modeled Full-Flight Aircraft Emissions Impacts on Air Quality and Their Sensitivity to Grid Resolution

NASA Astrophysics Data System (ADS)

Vennam, L. P.; Vizuete, W.; Talgo, K.; Omary, M.; Binkowski, F. S.; Xing, J.; Mathur, R.; Arunachalam, S.

2017-12-01

Aviation is a unique anthropogenic source with four-dimensional varying emissions, peaking at cruise altitudes (9-12 km). Aircraft emission budgets in the upper troposphere lower stratosphere region and their potential impacts on upper troposphere and surface air quality are not well understood. Our key objective is to use chemical transport models (with prescribed meteorology) to predict aircraft emissions impacts on the troposphere and surface air quality. We quantified the importance of including full-flight intercontinental emissions and increased horizontal grid resolution. The full-flight aviation emissions in the Northern Hemisphere contributed 1.3% (mean, min-max: 0.46, 0.3-0.5 ppbv) and 0.2% (0.013, 0.004-0.02 μg/m3) of total O3 and PM2.5 concentrations at the surface, with Europe showing slightly higher impacts (1.9% (O3 0.69, 0.5-0.85 ppbv) and 0.5% (PM2.5 0.03, 0.01-0.05 μg/m3)) than North America (NA) and East Asia. We computed seasonal aviation-attributable mass flux vertical profiles and aviation perturbations along isentropic surfaces to quantify the transport of cruise altitude emissions at the hemispheric scale. The comparison of coarse (108 × 108 km2) and fine (36 × 36 km2) grid resolutions in NA showed 70 times and 13 times higher aviation impacts for O3 and PM2.5 in coarser domain. These differences are mainly due to the inability of the coarse resolution simulation to capture nonlinearities in chemical processes near airport locations and other urban areas. Future global studies quantifying aircraft contributions should consider model resolution and perhaps use finer scales near major aviation source regions.

Modeled Full-Flight Aircraft Emissions Impacts on Air Quality and Their Sensitivity to Grid Resolution

PubMed Central

Vennam, L. P.; Vizuete, W.; Talgo, K.; Omary, M.; Binkowski, F. S.; Xing, J.; Mathur, R.; Arunachalam, S.

2018-01-01

Aviation is a unique anthropogenic source with four-dimensional varying emissions, peaking at cruise altitudes (9–12 km). Aircraft emission budgets in the upper troposphere lower stratosphere region and their potential impacts on upper troposphere and surface air quality are not well understood. Our key objective is to use chemical transport models (with prescribed meteorology) to predict aircraft emissions impacts on the troposphere and surface air quality. We quantified the importance of including full-flight intercontinental emissions and increased horizontal grid resolution. The full-flight aviation emissions in the Northern Hemisphere contributed ~1.3% (mean, min–max: 0.46, 0.3–0.5 ppbv) and 0.2% (0.013, 0.004–0.02 μg/m3) of total O3 and PM2.5 concentrations at the surface, with Europe showing slightly higher impacts (1.9% (O3 0.69, 0.5–0.85 ppbv) and 0.5% (PM2.5 0.03, 0.01–0.05 μg/m3)) than North America (NA) and East Asia. We computed seasonal aviation-attributable mass flux vertical profiles and aviation perturbations along isentropic surfaces to quantify the transport of cruise altitude emissions at the hemispheric scale. The comparison of coarse (108 × 108 km2) and fine (36 × 36 km2) grid resolutions in NA showed ~70 times and ~13 times higher aviation impacts for O3 and PM2.5 in coarser domain. These differences are mainly due to the inability of the coarse resolution simulation to capture nonlinearities in chemical processes near airport locations and other urban areas. Future global studies quantifying aircraft contributions should consider model resolution and perhaps use finer scales near major aviation source regions. PMID:29707471

Modeled Full-Flight Aircraft Emissions Impacts on Air Quality and Their Sensitivity to Grid Resolution.

PubMed

Vennam, L P; Vizuete, W; Talgo, K; Omary, M; Binkowski, F S; Xing, J; Mathur, R; Arunachalam, S

2017-01-01

Aviation is a unique anthropogenic source with four-dimensional varying emissions, peaking at cruise altitudes (9-12 km). Aircraft emission budgets in the upper troposphere lower stratosphere region and their potential impacts on upper troposphere and surface air quality are not well understood. Our key objective is to use chemical transport models (with prescribed meteorology) to predict aircraft emissions impacts on the troposphere and surface air quality. We quantified the importance of including full-flight intercontinental emissions and increased horizontal grid resolution. The full-flight aviation emissions in the Northern Hemisphere contributed ~1.3% (mean, min-max: 0.46, 0.3-0.5 ppbv) and 0.2% (0.013, 0.004-0.02 μg/m 3 ) of total O 3 and PM 2.5 concentrations at the surface, with Europe showing slightly higher impacts (1.9% (O 3 0.69, 0.5-0.85 ppbv) and 0.5% (PM 2.5 0.03, 0.01-0.05 μg/m 3 )) than North America (NA) and East Asia. We computed seasonal aviation-attributable mass flux vertical profiles and aviation perturbations along isentropic surfaces to quantify the transport of cruise altitude emissions at the hemispheric scale. The comparison of coarse (108 × 108 km 2 ) and fine (36 × 36 km 2 ) grid resolutions in NA showed ~70 times and ~13 times higher aviation impacts for O 3 and PM 2.5 in coarser domain. These differences are mainly due to the inability of the coarse resolution simulation to capture nonlinearities in chemical processes near airport locations and other urban areas. Future global studies quantifying aircraft contributions should consider model resolution and perhaps use finer scales near major aviation source regions.

Fragmentation of urban forms and the environmental consequences: results from a high-spatial resolution model system

NASA Astrophysics Data System (ADS)

Tang, U. W.; Wang, Z. S.

2008-10-01

Each city has its unique urban form. The importance of urban form on sustainable development has been recognized in recent years. Traditionally, air quality modelling in a city is in a mesoscale with grid resolution of kilometers, regardless of its urban form. This paper introduces a GIS-based air quality and noise model system developed to study the built environment of highly compact urban forms. Compared with traditional mesoscale air quality model system, the present model system has a higher spatial resolution down to individual buildings along both sides of the street. Applying the developed model system in the Macao Peninsula with highly compact urban forms, the average spatial resolution of input and output data is as high as 174 receptor points per km2. Based on this input/output dataset with a high spatial resolution, this study shows that even the highly compact urban forms can be fragmented into a very small geographic scale of less than 3 km2. This is due to the significant temporal variation of urban development. The variation of urban form in each fragment in turn affects air dispersion, traffic condition, and thus air quality and noise in a measurable scale.

Regional Climate Simulation and Data Assimilation with Variable-Resolution GCMs

NASA Technical Reports Server (NTRS)

Fox-Rabinovitz, Michael S.

2002-01-01

Variable resolution GCMs using a global stretched grid (SG) with enhanced regional resolution over one or multiple areas of interest represents a viable new approach to regional climateklimate change and data assimilation studies and applications. The multiple areas of interest, at least one within each global quadrant, include the major global mountains and major global monsoonal circulations over North America, South America, India-China, and Australia. They also can include the polar domains, and the European and African regions. The SG-approach provides an efficient regional downscaling to mesoscales, and it is an ideal tool for representing consistent interactions of globaYlarge- and regionallmeso- scales while preserving the high quality of global circulation. Basically, the SG-GCM simulations are no different from those of the traditional uniform-grid GCM simulations besides using a variable-resolution grid. Several existing SG-GCMs developed by major centers and groups are briefly described. The major discussion is based on the GEOS (Goddard Earth Observing System) SG-GCM regional climate simulations.

Regional photochemical air quality modeling in the Mexico-US border area

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

Mendoza, A.; Russell, A.G.; Mejia, G.M.

1998-12-31

The Mexico-United States border area has become an increasingly important region due to its commercial, industrial and urban growth. As a result, environmental concerns have risen. Treaties like the North American Free Trade Agreement (NAFTA) have further motivated the development of environmental impact assessment in the area. Of particular concern are air quality, and how the activities on both sides of the border contribute to its degradation. This paper presents results of applying a three-dimensional photochemical airshed model to study air pollution dynamics along the Mexico-United States border. In addition, studies were conducted to assess how size resolution impacts themore » model performance. The model performed within acceptable statistic limits using 12.5 x 12.5 km{sup 2} grid cells, and the benefits using finer grids were limited. Results were further used to assess the influence of grid-cell size on the modeling of control strategies, where coarser grids lead to significant loss of information.« less

Application of OMI NO2 for Regional Air Quality Model Evaluation

NASA Astrophysics Data System (ADS)

Holloway, T.; Bickford, E.; Oberman, J.; Scotty, E.; Clifton, O. E.

2012-12-01

To support the application of satellite data for air quality analysis, we examine how column NO2 measurements from the Ozone Monitoring Instrument (OMI) aboard the NASA Aura satellite relate to ground-based and model estimates of NO2 and related species. Daily variability, monthly mean values, and spatial gradients in OMI NO2 from the Netherlands Royal Meteorological Institute (KNMI) are compared to ground-based measurements of NO2 from the EPA Air Quality System (AQS) database. Satellite data is gridded to two resolutions typical of regional air quality models - 36 km x 36 km over the continental U.S., and 12 km x 12 km over the Upper Midwestern U.S. Gridding is performed using the Wisconsin Horizontal Interpolation Program for Satellites (WHIPS), a publicly available software to support gridding of satellite data to model grids. Comparing daily OMI retrievals (13:45 daytime local overpass time) with ground-based measurements (13:00), we find January and July 2007 correlation coefficients (r-values) generally positive, with values higher in the winter (January) than summer (July) for most sites. Incidences of anti-correlation or low-correlation are evaluated with model simulations from the U.S. EPA Community Multiscale Air Quality Model version 4.7 (CMAQ). OMI NO2 is also used to evaluate CMAQ output, and to compare performance metrics for CMAQ relative to AQS measurements. We compare simulated NO2 across both the U.S. and Midwest study domains with both OMI NO2 (total column CMAQ values, weighted with the averaging kernel) and with ground-based observations (lowest model layer CMAQ values). 2007 CMAQ simulations employ emissions from the Lake Michigan Air Directors Consortium (LADCO) and meteorology from the Weather Research and Forecasting (WRF) model. Over most of the U.S., CMAQ is too high in January relative to OMI NO2, but too low in January relative to AQS NO2. In contrast, CMAQ is too low in July relative to OMI NO2, but too high relative to AQS NO2. These biases are used to evaluate emission sources (and the importance of missing sources, such as lightning NOx), and to explain model performance for related secondary species, especially nitrate aerosol and ozone.

STAMMEX high resolution gridded daily precipitation dataset over Germany: a new potential for regional precipitation climate research

NASA Astrophysics Data System (ADS)

Zolina, Olga; Simmer, Clemens; Kapala, Alice; Mächel, Hermann; Gulev, Sergey; Groisman, Pavel

2014-05-01

We present new high resolution precipitation daily grids developed at Meteorological Institute, University of Bonn and German Weather Service (DWD) under the STAMMEX project (Spatial and Temporal Scales and Mechanisms of Extreme Precipitation Events over Central Europe). Daily precipitation grids have been developed from the daily-observing precipitation network of DWD, which runs one of the World's densest rain gauge networks comprising more than 7500 stations. Several quality-controlled daily gridded products with homogenized sampling were developed covering the periods 1931-onwards (with 0.5 degree resolution), 1951-onwards (0.25 degree and 0.5 degree), and 1971-2000 (0.1 degree). Different methods were tested to select the best gridding methodology that minimizes errors of integral grid estimates over hilly terrain. Besides daily precipitation values with uncertainty estimates (which include standard estimates of the kriging uncertainty as well as error estimates derived by a bootstrapping algorithm), the STAMMEX data sets include a variety of statistics that characterize temporal and spatial dynamics of the precipitation distribution (quantiles, extremes, wet/dry spells, etc.). Comparisons with existing continental-scale daily precipitation grids (e.g., CRU, ECA E-OBS, GCOS) which include considerably less observations compared to those used in STAMMEX, demonstrate the added value of high-resolution grids for extreme rainfall analyses. These data exhibit spatial variability pattern and trends in precipitation extremes, which are missed or incorrectly reproduced over Central Europe from coarser resolution grids based on sparser networks. The STAMMEX dataset can be used for high-quality climate diagnostics of precipitation variability, as a reference for reanalyses and remotely-sensed precipitation products (including the upcoming Global Precipitation Mission products), and for input into regional climate and operational weather forecast models. We will present numerous application of the STAMMEX grids spanning from case studies of the major Central European floods to long-term changes in different precipitation statistics, including those accounting for the alternation of dry and wet periods and precipitation intensities associated with prolonged rainy episodes.

Signature of present and projected climate change at an urban scale: The case of Addis Ababa

NASA Astrophysics Data System (ADS)

Arsiso, Bisrat Kifle; Mengistu Tsidu, Gizaw; Stoffberg, Gerrit Hendrik

2018-06-01

Understanding climate change and variability at an urban scale is essential for water resource management, land use planning, development of adaption plans, mitigation of air and water pollution. However, there are serious challenges to meet these goals due to unavailability of observed and/or simulated high resolution spatial and temporal climate data. The statistical downscaling of general circulation climate model, for instance, is usually driven by sparse observational data hindering the use of downscaled data to investigate urban scale climate variability and change in the past. Recently, these challenges are partly resolved by concerted international effort to produce global and high spatial resolution climate data. In this study, the 1 km2 high resolution NIMR-HadGEM2-AO simulations for future projections under Representative Concentration Pathways (RCP4.5 and RCP8.5) scenarios and gridded observations provided by Worldclim data center are used to assess changes in rainfall, minimum and maximum temperature expected under the two scenarios over Addis Ababa city. The gridded 1 km2 observational data set for the base period (1950-2000) is compared to observation from a meteorological station in the city in order to assess its quality for use as a reference (baseline) data. The comparison revealed that the data set has a very good quality. The rainfall anomalies under RCPs scenarios are wet in the 2030s (2020-2039), 2050s (2040-2069) and 2080s (2070-2099). Both minimum and maximum temperature anomalies under RCPs are successively getting warmer during these periods. Thus, the projected changes under RCPs scenarios show a general increase in rainfall and temperatures with strong variabilities in rainfall during rainy season implying level of difficulty in water resource use and management as well as land use planning and management.

Evaluation of model-predicted hazardous air pollutants (HAPs) near a mid-sized U.S. airport

NASA Astrophysics Data System (ADS)

Vennam, Lakshmi Pradeepa; Vizuete, William; Arunachalam, Saravanan

2015-10-01

Accurate modeling of aircraft-emitted pollutants in the vicinity of airports is essential to study the impact on local air quality and to answer policy and health-impact related issues. To quantify air quality impacts of airport-related hazardous air pollutants (HAPs), we carried out a fine-scale (4 × 4 km horizontal resolution) Community Multiscale Air Quality model (CMAQ) model simulation at the T.F. Green airport in Providence (PVD), Rhode Island. We considered temporally and spatially resolved aircraft emissions from the new Aviation Environmental Design Tool (AEDT). These model predictions were then evaluated with observations from a field campaign focused on assessing HAPs near the PVD airport. The annual normalized mean error (NME) was in the range of 36-70% normalized mean error for all HAPs except for acrolein (>70%). The addition of highly resolved aircraft emissions showed only marginally incremental improvements in performance (1-2% decrease in NME) of some HAPs (formaldehyde, xylene). When compared to a coarser 36 × 36 km grid resolution, the 4 × 4 km grid resolution did improve performance by up to 5-20% NME for formaldehyde and acetaldehyde. The change in power setting (from traditional International Civil Aviation Organization (ICAO) 7% to observation studies based 4%) doubled the aircraft idling emissions of HAPs, but led to only a 2% decrease in NME. Overall modeled aircraft-attributable contributions are in the range of 0.5-28% near a mid-sized airport grid-cell with maximum impacts seen only within 4-16 km from the airport grid-cell. Comparison of CMAQ predictions with HAP estimates from EPA's National Air Toxics Assessment (NATA) did show similar annual mean concentrations and equally poor performance. Current estimates of HAPs for PVD are a challenge for modeling systems and refinements in our ability to simulate aircraft emissions have made only incremental improvements. Even with unrealistic increases in HAPs aviation emissions the model could not match observed concentrations near the runway airport site. Our results suggest other uncertainties in the modeling system such as meteorology, HAPs chemistry, or other emission sources require increased scrutiny.

Regional Data Assimilation Using a Stretched-Grid Approach and Ensemble Calculations

NASA Technical Reports Server (NTRS)

Fox-Rabinovitz, M. S.; Takacs, L. L.; Govindaraju, R. C.; Atlas, Robert (Technical Monitor)

2002-01-01

The global variable resolution stretched grid (SG) version of the Goddard Earth Observing System (GEOS) Data Assimilation System (DAS) incorporating the GEOS SG-GCM (Fox-Rabinovitz 2000, Fox-Rabinovitz et al. 2001a,b), has been developed and tested as an efficient tool for producing regional analyses and diagnostics with enhanced mesoscale resolution. The major area of interest with enhanced regional resolution used in different SG-DAS experiments includes a rectangle over the U.S. with 50 or 60 km horizontal resolution. The analyses and diagnostics are produced for all mandatory levels from the surface to 0.2 hPa. The assimilated regional mesoscale products are consistent with global scale circulation characteristics due to using the SG-approach. Both the stretched grid and basic uniform grid DASs use the same amount of global grid-points and are compared in terms of regional product quality.

Modeling Aircraft Emissions for Regional-scale Air Quality: Adapting a New Global Aircraft Emissions Database for the U.S

NASA Astrophysics Data System (ADS)

Arunachalam, S.; Baek, B. H.; Vennam, P. L.; Woody, M. C.; Omary, M.; Binkowski, F.; Fleming, G.

2012-12-01

Commercial aircraft emit substantial amounts of pollutants during their complete activity cycle that ranges from landing-and-takeoff (LTO) at airports to cruising in upper elevations of the atmosphere, and affect both air quality and climate. Since these emissions are not uniformly emitted over the earth, and have substantial temporal and spatial variability, it is vital to accurately evaluate and quantify the relative impacts of aviation emissions on ambient air quality. Regional-scale air quality modeling applications do not routinely include these aircraft emissions from all cycles. Federal Aviation Administration (FAA) has developed the Aviation Environmental Design Tool (AEDT), a software system that dynamically models aircraft performance in space and time to calculate fuel burn and emissions from gate-to-gate for all commercial aviation activity from all airports globally. To process in-flight aircraft emissions and to provide a realistic representation of these for treatment in grid-based air quality models, we have developed an interface processor called AEDTproc that accurately distributes full-flight chorded emissions in time and space to create gridded, hourly model-ready emissions input data. Unlike the traditional emissions modeling approach of treating aviation emissions as ground-level sources or processing emissions only from the LTO cycles in regional-scale air quality studies, AEDTproc distributes chorded inventories of aircraft emissions during LTO cycles and cruise activities into a time-variant 3-D gridded structure. We will present results of processed 2006 global emissions from AEDT over a continental U.S. modeling domain to support a national-scale air quality assessment of the incremental impacts of aircraft emissions on surface air quality. This includes about 13.6 million flights within the U.S. out of 31.2 million flights globally. We will focus on assessing spatio-temporal variability of these commercial aircraft emissions, and comparing upper tropospheric budgets of NOx from aircraft and lightning sources in the modeling domain.

GEM-AC, a stratospheric-tropospheric global and regional model for air quality and climate change: evaluation of gas phase properties

NASA Astrophysics Data System (ADS)

Kaminski, J. W.; Semeniuk, K.; McConnell, J. C.; Lupu, A.; Mamun, A.

2012-12-01

The Global Environmental Multiscale model for Air Quality and climate change (GEM-AC) is a global general circulation model based on the GEM model developed by the Meteorological Service of Canada for operational weather forecasting. It can be run with a global uniform (GU) grid or a global variable (GV) grid where the core has uniform grid spacing and the exterior grid expands. With a GV grid high resolution regional runs can be accomplished without a concern for boundary conditions. The work described here uses GEM version 3.3.2. The gas-phase chemistry consists in detailed reactions of Ox, NOx, HOx, CO, CH4, NMVOCs, halocarbons, ClOx and BrO. We have recently added elements of the Global Modal-aerosol eXtension (GMXe) scheme to address aerosol microphysics and gas-aerosol partitioning. The evaluation of the MESSY GMXe aerosol scheme is addressed in another poster. The Canadian aerosol module (CAM) is also available. Tracers are advected using the semi-Lagrangian scheme native to GEM. The vertical transport includes parameterized subgrid scale turbulence and large scale convection. Dry deposition is implemented as a flux boundary condition in the vertical diffusion equation. For climate runs the GHGs CO2, CH4, N2O, CFCs in the radiation scheme are adjusted to the scenario considered. In GV regional mode at high resolutions a lake model, FLAKE is also included. Wet removal comprises both in-cloud and below-cloud scavenging. With the gas phase chemistry the model has been run for a series of ten year time slices on a 3°×3° global grid with 77 hybrid levels from the surface to 0.15 hPa. The tropospheric and stratospheric gas phase results are compared with satellite measurements including, ACE, MIPAS, MOPITT, and OSIRIS. Current evaluations of the ozone field and other stratospheric fields are encouraging and tropospheric lifetimes for CH4 and CH3CCl3 are in reasonable accord with tropospheric models. We will present results for current and future climate conditions forced by SST for 2050.

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).

Allocating emissions to 4 km and 1 km horizontal spatial resolutions and its impact on simulated NOx and O3 in Houston, TX

NASA Astrophysics Data System (ADS)

Pan, Shuai; Choi, Yunsoo; Roy, Anirban; Jeon, Wonbae

2017-09-01

A WRF-SMOKE-CMAQ air quality modeling system was used to investigate the impact of horizontal spatial resolution on simulated nitrogen oxides (NOx) and ozone (O3) in the Greater Houston area (a non-attainment area for O3). We employed an approach recommended by the United States Environmental Protection Agency to allocate county-based emissions to model grid cells in 1 km and 4 km horizontal grid resolutions. The CMAQ Integrated Process Rate analyses showed a substantial difference in emissions contributions between 1 and 4 km grids but similar NOx and O3 concentrations over urban and industrial locations. For example, the peak NOx emissions at an industrial and urban site differed by a factor of 20 for the 1 km and 8 for the 4 km grid, but simulated NOx concentrations changed only by a factor of 1.2 in both cases. Hence, due to the interplay of the atmospheric processes, we cannot expect a similar level of reduction of the gas-phase air pollutants as the reduction of emissions. Both simulations reproduced the variability of NASA P-3B aircraft measurements of NOy and O3 in the lower atmosphere (from 90 m to 4.5 km). Both simulations provided similar reasonable predictions at surface, while 1 km case depicted more detailed features of emissions and concentrations in heavily polluted areas, such as highways, airports, and industrial regions, which are useful in understanding the major causes of O3 pollution in such regions, and to quantify transport of O3 to populated communities in urban areas. The Integrated Reaction Rate analyses indicated a distinctive difference of chemistry processes between the model surface layer and upper layers, implying that correcting the meteorological conditions at the surface may not help to enhance the O3 predictions. The model-observation O3 bias in our studies (e.g., large over-prediction during the nighttime or along Gulf of Mexico coastline), were due to uncertainties in meteorology, chemistry or other processes. Horizontal grid resolution is unlikely the major contributor to these biases.

HIGH-RESOLUTION DATASET OF URBAN CANOPY PARAMETERS FOR HOUSTON, TEXAS

EPA Science Inventory

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

On the feasibility of measuring urban air pollution by wireless distributed sensor networks.

PubMed

Moltchanov, Sharon; Levy, Ilan; Etzion, Yael; Lerner, Uri; Broday, David M; Fishbain, Barak

2015-01-01

Accurate evaluation of air pollution on human-wellbeing requires high-resolution measurements. Standard air quality monitoring stations provide accurate pollution levels but due to their sparse distribution they cannot capture the highly resolved spatial variations within cities. Similarly, dedicated field campaigns can use tens of measurement devices and obtain highly dense spatial coverage but normally deployment has been limited to short periods of no more than few weeks. Nowadays, advances in communication and sensory technologies enable the deployment of dense grids of wireless distributed air monitoring nodes, yet their sensor ability to capture the spatiotemporal pollutant variability at the sub-neighborhood scale has never been thoroughly tested. This study reports ambient measurements of gaseous air pollutants by a network of six wireless multi-sensor miniature nodes that have been deployed in three urban sites, about 150 m apart. We demonstrate the network's capability to capture spatiotemporal concentration variations at an exceptional fine resolution but highlight the need for a frequent in-situ calibration to maintain the consistency of some sensors. Accordingly, a procedure for a field calibration is proposed and shown to improve the system's performance. Overall, our results support the compatibility of wireless distributed sensor networks for measuring urban air pollution at a sub-neighborhood spatial resolution, which suits the requirement for highly spatiotemporal resolved measurements at the breathing-height when assessing exposure to urban air pollution. Copyright © 2014 Elsevier B.V. All rights reserved.

Assessing uncertain human exposure to ambient air pollution using environmental models in the Web

NASA Astrophysics Data System (ADS)

Gerharz, L. E.; Pebesma, E.; Denby, B.

2012-04-01

Ambient air quality can have significant impact on human health by causing respiratory and cardio-vascular diseases. Thereby, the pollutant concentration a person is exposed to can differ considerably between individuals depending on their daily routine and movement patterns. Using a straight forward approach this exposure can be estimated by integration of individual space-time paths and spatio-temporally resolved ambient air quality data. To allow a realistic exposure assessment, it is furthermore important to consider uncertainties due to input and model errors. In this work, we present a generic, web-based approach for estimating individual exposure by integration of uncertain position and air quality information implemented as a web service. Following the Model Web initiative envisioning an infrastructure for deploying, executing and chaining environmental models as services, existing models and data sources for e.g. air quality, can be used to assess exposure. Therefore, the service needs to deal with different formats, resolutions and uncertainty representations provided by model or data services. Potential mismatch can be accounted for by transformation of uncertainties and (dis-)aggregation of data under consideration of changes in the uncertainties using components developed in the UncertWeb project. In UncertWeb, the Model Web vision is extended to an Uncertainty-enabled Model Web, where services can process and communicate uncertainties in the data and models. The propagation of uncertainty to the exposure results is quantified using Monte Carlo simulation by combining different realisations of positions and ambient concentrations. Two case studies were used to evaluate the developed exposure assessment service. In a first study, GPS tracks with a positional uncertainty of a few meters, collected in the urban area of Münster, Germany were used to assess exposure to PM10 (particulate matter smaller 10 µm). Air quality data was provided by an uncertainty-enabled air quality model system which provided realisations of concentrations per hour on a 250 m x 250 m resolved grid over Münster. The second case study uses modelled human trajectories in Rotterdam, The Netherlands. The trajectories were provided as realisations in 15 min resolution per 4 digit postal code from an activity model. Air quality estimates were provided for different pollutants as ensembles by a coupled meteorology and air quality model system on a 1 km x 1 km grid with hourly resolution. Both case studies show the successful application of the service to different resolutions and uncertainty representations.

High-resolution grids of hourly meteorological variables for Germany

NASA Astrophysics Data System (ADS)

Krähenmann, S.; Walter, A.; Brienen, S.; Imbery, F.; Matzarakis, A.

2018-02-01

We present a 1-km2 gridded German dataset of hourly surface climate variables covering the period 1995 to 2012. The dataset comprises 12 variables including temperature, dew point, cloud cover, wind speed and direction, global and direct shortwave radiation, down- and up-welling longwave radiation, sea level pressure, relative humidity and vapour pressure. This dataset was constructed statistically from station data, satellite observations and model data. It is outstanding in terms of spatial and temporal resolution and in the number of climate variables. For each variable, we employed the most suitable gridding method and combined the best of several information sources, including station records, satellite-derived data and data from a regional climate model. A module to estimate urban heat island intensity was integrated for air and dew point temperature. Owing to the low density of available synop stations, the gridded dataset does not capture all variations that may occur at a resolution of 1 km2. This applies to areas of complex terrain (all the variables), and in particular to wind speed and the radiation parameters. To achieve maximum precision, we used all observational information when it was available. This, however, leads to inhomogeneities in station network density and affects the long-term consistency of the dataset. A first climate analysis for Germany was conducted. The Rhine River Valley, for example, exhibited more than 100 summer days in 2003, whereas in 1996, the number was low everywhere in Germany. The dataset is useful for applications in various climate-related studies, hazard management and for solar or wind energy applications and it is available via doi: 10.5676/DWD_CDC/TRY_Basis_v001.

Techniques and resources for storm-scale numerical weather prediction

NASA Technical Reports Server (NTRS)

Droegemeier, Kelvin; Grell, Georg; Doyle, James; Soong, Su-Tzai; Skamarock, William; Bacon, David; Staniforth, Andrew; Crook, Andrew; Wilhelmson, Robert

1993-01-01

The topics discussed include the following: multiscale application of the 5th-generation PSU/NCAR mesoscale model, the coupling of nonhydrostatic atmospheric and hydrostatic ocean models for air-sea interaction studies; a numerical simulation of cloud formation over complex topography; adaptive grid simulations of convection; an unstructured grid, nonhydrostatic meso/cloud scale model; efficient mesoscale modeling for multiple scales using variable resolution; initialization of cloud-scale models with Doppler radar data; and making effective use of future computing architectures, networks, and visualization software.

INITIAL APPL;ICATION OF THE ADAPTIVE GRID AIR POLLUTION MODEL

EPA Science Inventory

The paper discusses an adaptive-grid algorithm used in air pollution models. The algorithm reduces errors related to insufficient grid resolution by automatically refining the grid scales in regions of high interest. Meanwhile the grid scales are coarsened in other parts of the d...

A description and evaluation of an air quality model nested within global and regional composition-climate models using MetUM

NASA Astrophysics Data System (ADS)

Neal, Lucy S.; Dalvi, Mohit; Folberth, Gerd; McInnes, Rachel N.; Agnew, Paul; O'Connor, Fiona M.; Savage, Nicholas H.; Tilbee, Marie

2017-11-01

There is a clear need for the development of modelling frameworks for both climate change and air quality to help inform policies for addressing these issues simultaneously. This paper presents an initial attempt to develop a single modelling framework, by introducing a greater degree of consistency in the meteorological modelling framework by using a two-step, one-way nested configuration of models, from a global composition-climate model (GCCM) (140 km resolution) to a regional composition-climate model covering Europe (RCCM) (50 km resolution) and finally to a high (12 km) resolution model over the UK (AQUM). The latter model is used to produce routine air quality forecasts for the UK. All three models are based on the Met Office's Unified Model (MetUM). In order to better understand the impact of resolution on the downscaling of projections of future climate and air quality, we have used this nest of models to simulate a 5-year period using present-day emissions and under present-day climate conditions. We also consider the impact of running the higher-resolution model with higher spatial resolution emissions, rather than simply regridding emissions from the RCCM. We present an evaluation of the models compared to in situ air quality observations over the UK, plus a comparison against an independent 1 km resolution gridded dataset, derived from a combination of modelling and observations, effectively producing an analysis of annual mean surface pollutant concentrations. We show that using a high-resolution model over the UK has some benefits in improving air quality modelling, but that the use of higher spatial resolution emissions is important to capture local variations in concentrations, particularly for primary pollutants such as nitrogen dioxide and sulfur dioxide. For secondary pollutants such as ozone and the secondary component of PM10, the benefits of a higher-resolution nested model are more limited and reasons for this are discussed. This study highlights the point that the resolution of models is not the only factor in determining model performance - consistency between nested models is also important.

A variable resolution nonhydrostatic global atmospheric semi-implicit semi-Lagrangian model

NASA Astrophysics Data System (ADS)

Pouliot, George Antoine

2000-10-01

The objective of this project is to develop a variable-resolution finite difference adiabatic global nonhydrostatic semi-implicit semi-Lagrangian (SISL) model based on the fully compressible nonhydrostatic atmospheric equations. To achieve this goal, a three-dimensional variable resolution dynamical core was developed and tested. The main characteristics of the dynamical core can be summarized as follows: Spherical coordinates were used in a global domain. A hydrostatic/nonhydrostatic switch was incorporated into the dynamical equations to use the fully compressible atmospheric equations. A generalized horizontal variable resolution grid was developed and incorporated into the model. For a variable resolution grid, in contrast to a uniform resolution grid, the order of accuracy of finite difference approximations is formally lost but remains close to the order of accuracy associated with the uniform resolution grid provided the grid stretching is not too significant. The SISL numerical scheme was implemented for the fully compressible set of equations. In addition, the generalized minimum residual (GMRES) method with restart and preconditioner was used to solve the three-dimensional elliptic equation derived from the discretized system of equations. The three-dimensional momentum equation was integrated in vector-form to incorporate the metric terms in the calculations of the trajectories. Using global re-analysis data for a specific test case, the model was compared to similar SISL models previously developed. Reasonable agreement between the model and the other independently developed models was obtained. The Held-Suarez test for dynamical cores was used for a long integration and the model was successfully integrated for up to 1200 days. Idealized topography was used to test the variable resolution component of the model. Nonhydrostatic effects were simulated at grid spacings of 400 meters with idealized topography and uniform flow. Using a high-resolution topographic data set and the variable resolution grid, sets of experiments with increasing resolution were performed over specific regions of interest. Using realistic initial conditions derived from re-analysis fields, nonhydrostatic effects were significant for grid spacings on the order of 0.1 degrees with orographic forcing. If the model code was adapted for use in a message passing interface (MPI) on a parallel supercomputer today, it was estimated that a global grid spacing of 0.1 degrees would be achievable for a global model. In this case, nonhydrostatic effects would be significant for most areas. A variable resolution grid in a global model provides a unified and flexible approach to many climate and numerical weather prediction problems. The ability to configure the model from very fine to very coarse resolutions allows for the simulation of atmospheric phenomena at different scales using the same code. We have developed a dynamical core illustrating the feasibility of using a variable resolution in a global model.

A new multiscale air quality transport model (Fluidity, 4.1.9) using fully unstructured anisotropic adaptive mesh technology

NASA Astrophysics Data System (ADS)

Zheng, J.; Zhu, J.; Wang, Z.; Fang, F.; Pain, C. C.; Xiang, J.

2015-06-01

A new anisotropic hr-adaptive mesh technique has been applied to modelling of multiscale transport phenomena, which is based on a discontinuous Galerkin/control volume discretization on unstructured meshes. Over existing air quality models typically based on static-structured grids using a locally nesting technique, the advantage of the anisotropic hr-adaptive model has the ability to adapt the mesh according to the evolving pollutant distribution and flow features. That is, the mesh resolution can be adjusted dynamically to simulate the pollutant transport process accurately and effectively. To illustrate the capability of the anisotropic adaptive unstructured mesh model, three benchmark numerical experiments have been setup for two-dimensional (2-D) transport phenomena. Comparisons have been made between the results obtained using uniform resolution meshes and anisotropic adaptive resolution meshes.

Evaluation of the Global Land Data Assimilation System (GLDAS) air temperature data products

USGS Publications Warehouse

Ji, Lei; Senay, Gabriel B.; Verdin, James P.

2015-01-01

There is a high demand for agrohydrologic models to use gridded near-surface air temperature data as the model input for estimating regional and global water budgets and cycles. The Global Land Data Assimilation System (GLDAS) developed by combining simulation models with observations provides a long-term gridded meteorological dataset at the global scale. However, the GLDAS air temperature products have not been comprehensively evaluated, although the accuracy of the products was assessed in limited areas. In this study, the daily 0.25° resolution GLDAS air temperature data are compared with two reference datasets: 1) 1-km-resolution gridded Daymet data (2002 and 2010) for the conterminous United States and 2) global meteorological observations (2000–11) archived from the Global Historical Climatology Network (GHCN). The comparison of the GLDAS datasets with the GHCN datasets, including 13 511 weather stations, indicates a fairly high accuracy of the GLDAS data for daily temperature. The quality of the GLDAS air temperature data, however, is not always consistent in different regions of the world; for example, some areas in Africa and South America show relatively low accuracy. Spatial and temporal analyses reveal a high agreement between GLDAS and Daymet daily air temperature datasets, although spatial details in high mountainous areas are not sufficiently estimated by the GLDAS data. The evaluation of the GLDAS data demonstrates that the air temperature estimates are generally accurate, but caution should be taken when the data are used in mountainous areas or places with sparse weather stations.

Science Enabling Applications of Gridded Radiances and Products

NASA Astrophysics Data System (ADS)

Goldberg, M.; Wolf, W.; Zhou, L.

2005-12-01

New generations of hyperspectral sounders and imagers are not only providing vastly improved information to monitor, assess and predict the Earth's environment, they also provide tremendous volumes of data to manage. Key management challenges must include data processing, distribution, archive and utilization. At the NOAA/NESDIS Office of Research and Applications, we have started to address the challenge of utilizing high volume satellite by thinning observations and developing gridded datasets from the observations made from the NASA AIRS, AMSU and MODIS instrument. We have developed techniques for intelligent thinning of AIRS data for numerical weather prediction, by selecting the clearest AIRS 14 km field of view within a 3 x 3 array. The selection uses high spatial resolution 1 km MODIS data which are spatially convolved to the AIRS field of view. The MODIS cloud masks and AIRS cloud tests are used to select the clearest. During the real-time processing the data are thinned and gridded to support monitoring, validation and scientific studies. Products from AIRS, which includes profiles of temperature, water vapor and ozone and cloud-corrected infrared radiances for more than 2000 channels, are derived from a single AIRS/AMSU field of regard, which is a 3 x 3 array of AIRS footprints (each with a 14 km spatial resolution) collocated with a single AMSU footprint (42 km). One of our key gridded dataset is a daily 3 x 3 latitude/longitude projection which contains the nearest AIRS/AMSU field of regard with respect to the center of the 3 x 3 lat/lon grid. This particular gridded dataset is 1/40 the size of the full resolution data. This gridded dataset is the type of product request that can be used to support algorithm validation and improvements. It also provides for a very economical approach for reprocessing, testing and improving algorithms for climate studies without having to reprocess the full resolution data stored at the DAAC. For example, on a single CPU workstation, all the AIRS derived products can be derived from a single year of gridded data in 5 days. This relatively short turnaround time, which can be reduced considerably to 3 hours by using a cluster of 40 pc G5processors, allows for repeated reprocessing at the PIs home institution before substantial investments are made to reprocess the full resolution data sets archived at the DAAC. In other words, do not reprocess the full resolution data until the science community have tested and selected the optimal algorithm on the gridded data. Development and applications of gridded radiances and products will be discussed. The applications can be provided as part of a web-based service.

Towards a new multiscale air quality transport model using the fully unstructured anisotropic adaptive mesh technology of Fluidity (version 4.1.9)

NASA Astrophysics Data System (ADS)

Zheng, J.; Zhu, J.; Wang, Z.; Fang, F.; Pain, C. C.; Xiang, J.

2015-10-01

An integrated method of advanced anisotropic hr-adaptive mesh and discretization numerical techniques has been, for first time, applied to modelling of multiscale advection-diffusion problems, which is based on a discontinuous Galerkin/control volume discretization on unstructured meshes. Over existing air quality models typically based on static-structured grids using a locally nesting technique, the advantage of the anisotropic hr-adaptive model has the ability to adapt the mesh according to the evolving pollutant distribution and flow features. That is, the mesh resolution can be adjusted dynamically to simulate the pollutant transport process accurately and effectively. To illustrate the capability of the anisotropic adaptive unstructured mesh model, three benchmark numerical experiments have been set up for two-dimensional (2-D) advection phenomena. Comparisons have been made between the results obtained using uniform resolution meshes and anisotropic adaptive resolution meshes. Performance achieved in 3-D simulation of power plant plumes indicates that this new adaptive multiscale model has the potential to provide accurate air quality modelling solutions effectively.

InMAP: a new model for air pollution interventions

NASA Astrophysics Data System (ADS)

Tessum, C. W.; Hill, J. D.; Marshall, J. D.

2015-10-01

Mechanistic air pollution models are essential tools in air quality management. Widespread use of such models is hindered, however, by the extensive expertise or computational resources needed to run most models. Here, we present InMAP (Intervention Model for Air Pollution), which offers an alternative to comprehensive air quality models for estimating the air pollution health impacts of emission reductions and other potential interventions. InMAP estimates annual-average changes in primary and secondary fine particle (PM2.5) concentrations - the air pollution outcome generally causing the largest monetized health damages - attributable to annual changes in precursor emissions. InMAP leverages pre-processed physical and chemical information from the output of a state-of-the-science chemical transport model (WRF-Chem) within an Eulerian modeling framework, to perform simulations that are several orders of magnitude less computationally intensive than comprehensive model simulations. InMAP uses a variable resolution grid that focuses on human exposures by employing higher spatial resolution in urban areas and lower spatial resolution in rural and remote locations and in the upper atmosphere; and by directly calculating steady-state, annual average concentrations. In comparisons run here, InMAP recreates WRF-Chem predictions of changes in total PM2.5 concentrations with population-weighted mean fractional error (MFE) and bias (MFB) < 10 % and population-weighted R2 ~ 0.99. Among individual PM2.5 species, the best predictive performance is for primary PM2.5 (MFE: 16 %; MFB: 13 %) and the worst predictive performance is for particulate nitrate (MFE: 119 %; MFB: 106 %). Potential uses of InMAP include studying exposure, health, and environmental justice impacts of potential shifts in emissions for annual-average PM2.5. Features planned for future model releases include a larger spatial domain, more temporal information, and the ability to predict ground-level ozone (O3) concentrations. The InMAP model source code and input data are freely available online.

Comparison of alternative spatial resolutions in the application of a spatially distributed biogeochemical model over complex terrain

USGS Publications Warehouse

Turner, D.P.; Dodson, R.; Marks, D.

1996-01-01

Spatially distributed biogeochemical models may be applied over grids at a range of spatial resolutions, however, evaluation of potential errors and loss of information at relatively coarse resolutions is rare. In this study, a georeferenced database at the 1-km spatial resolution was developed to initialize and drive a process-based model (Forest-BGC) of water and carbon balance over a gridded 54976 km2 area covering two river basins in mountainous western Oregon. Corresponding data sets were also prepared at 10-km and 50-km spatial resolutions using commonly employed aggregation schemes. Estimates were made at each grid cell for climate variables including daily solar radiation, air temperature, humidity, and precipitation. The topographic structure, water holding capacity, vegetation type and leaf area index were likewise estimated for initial conditions. The daily time series for the climatic drivers was developed from interpolations of meteorological station data for the water year 1990 (1 October 1989-30 September 1990). Model outputs at the 1-km resolution showed good agreement with observed patterns in runoff and productivity. The ranges for model inputs at the 10-km and 50-km resolutions tended to contract because of the smoothed topography. Estimates for mean evapotranspiration and runoff were relatively insensitive to changing the spatial resolution of the grid whereas estimates of mean annual net primary production varied by 11%. The designation of a vegetation type and leaf area at the 50-km resolution often subsumed significant heterogeneity in vegetation, and this factor accounted for much of the difference in the mean values for the carbon flux variables. Although area wide means for model outputs were generally similar across resolutions, difference maps often revealed large areas of disagreement. Relatively high spatial resolution analyses of biogeochemical cycling are desirable from several perspectives and may be particularly important in the study of the potential impacts of climate change.

Suitability of satellite derived and gridded sea surface temperature data sets for calibrating high-resolution marine proxy records

NASA Astrophysics Data System (ADS)

Ouellette, G., Jr.; DeLong, K. L.

2016-02-01

High-resolution proxy records of sea surface temperature (SST) are increasingly being produced using trace element and isotope variability within the skeletal materials of marine organisms such as corals, mollusks, sclerosponges, and coralline algae. Translating the geochemical variations within these organisms into records of SST requires calibration with SST observations using linear regression methods, preferably with in situ SST records that span several years. However, locations with such records are sparse; therefore, calibration is often accomplished using gridded SST data products such as the Hadley Center's HADSST (5º) and interpolated HADISST (1º) data sets, NOAA's extended reconstructed SST data set (ERSST; 2º), optimum interpolation SST (OISST; 1º), and Kaplan SST data sets (5º). From these data products, the SST used for proxy calibration is obtained for a single grid cell that includes the proxy's study site. The gridded data sets are based on the International Comprehensive Ocean-Atmosphere Data Set (ICOADS) and each uses different methods of interpolation to produce the globally and temporally complete data products except for HadSST, which is not interpolated but quality controlled. This study compares SST for a single site from these gridded data products with a high-resolution satellite-based SST data set from NOAA (Pathfinder; 4 km) with in situ SST data and coral Sr/Ca variability for our study site in Haiti to assess differences between these SST records with a focus on seasonal variability. Our results indicate substantial differences in the seasonal variability captured for the same site among these data sets on the order of 1-3°C. This analysis suggests that of the data products, high-resolution satellite SST best captured seasonal variability at the study site. Unfortunately, satellite SST records are limited to the past few decades. If satellite SST are to be used to calibrate proxy records, collecting modern, living samples is desirable.

Impact of land-use on groundwater quality: GIS-based study from an alluvial aquifer in the western Ganges basin

NASA Astrophysics Data System (ADS)

Khan, Arina; Khan, Haris Hasan; Umar, Rashid

2017-12-01

In this study, groundwater quality of an alluvial aquifer in the western Ganges basin is assessed using a GIS-based groundwater quality index (GQI) concept that uses groundwater quality data from field survey and laboratory analysis. Groundwater samples were collected from 42 wells during pre-monsoon and post-monsoon periods of 2012 and analysed for pH, EC, TDS, Anions (Cl, SO4, NO3), and Cations (Ca, Mg, Na). To generate the index, several parameters were selected based on WHO recommendations. The spatially variable grids of each parameter were modified by normalizing with the WHO standards and finally integrated into a GQI grid. The mean GQI values for both the season suggest good groundwater quality. However, spatial variations exist and are represented by GQI map of both seasons. This spatial variability was compared with the existing land-use, prepared using high-resolution satellite imagery available in Google earth. The GQI grids were compared to the land-use map using an innovative GIS-based method. Results indicate that the spatial variability of groundwater quality in the region is not fully controlled by the land-use pattern. This probably reflects the diffuse nature of land-use classes, especially settlements and plantations.

Influence of high-resolution surface databases on the modeling of local atmospheric circulation systems

NASA Astrophysics Data System (ADS)

Paiva, L. M. S.; Bodstein, G. C. R.; Pimentel, L. C. G.

2013-12-01

Large-eddy simulations are performed using the Advanced Regional Prediction System (ARPS) code at horizontal grid resolutions as fine as 300 m to assess the influence of detailed and updated surface databases on the modeling of local atmospheric circulation systems of urban areas with complex terrain. Applications to air pollution and wind energy are sought. These databases are comprised of 3 arc-sec topographic data from the Shuttle Radar Topography Mission, 10 arc-sec vegetation type data from the European Space Agency (ESA) GlobCover Project, and 30 arc-sec Leaf Area Index and Fraction of Absorbed Photosynthetically Active Radiation data from the ESA GlobCarbon Project. Simulations are carried out for the Metropolitan Area of Rio de Janeiro using six one-way nested-grid domains that allow the choice of distinct parametric models and vertical resolutions associated to each grid. ARPS is initialized using the Global Forecasting System with 0.5°-resolution data from the National Center of Environmental Prediction, which is also used every 3 h as lateral boundary condition. Topographic shading is turned on and two soil layers with depths of 0.01 and 1.0 m are used to compute the soil temperature and moisture budgets in all runs. Results for two simulated runs covering the period from 6 to 7 September 2007 are compared to surface and upper-air observational data to explore the dependence of the simulations on initial and boundary conditions, topographic and land-use databases and grid resolution. Our comparisons show overall good agreement between simulated and observed data and also indicate that the low resolution of the 30 arc-sec soil database from United States Geological Survey, the soil moisture and skin temperature initial conditions assimilated from the GFS analyses and the synoptic forcing on the lateral boundaries of the finer grids may affect an adequate spatial description of the meteorological variables.

Evaluation of VIIRS, GOCI, and MODIS Collection 6 AOD Retrievals Against Ground Sunphotometer Observations Over East Asia

NASA Technical Reports Server (NTRS)

Xiao, Q.; Zhang, H.; Choi, M.; Li, S.; Kondragunta, S.; Kim, J.; Holben, B.; Levy, R. C.; Liu, Y.

2016-01-01

Persistent high aerosol loadings together with extremely high population densities have raised serious air quality and public health concerns in many urban centers in East Asia. However, ground-based air quality monitoring is relatively limited in this area. Recently, satellite-retrieved Aerosol Optical Depth (AOD) at high resolution has become a powerful tool to characterize aerosol patterns in space and time. Using ground AOD observations from the Aerosol Robotic Network (AERONET) and the Distributed Regional Aerosol Gridded Observation Networks (DRAGON)-Asia Campaign, as well as from handheld sunphotometers, we evaluated emerging aerosol products from the Visible Infrared Imaging Radiometer Suite (VIIRS) aboard the Suomi National Polar-orbiting Partnership (S-NPP), the Geostationary Ocean Color Imager (GOCI) aboard the Communication, Ocean, and Meteorology Satellite (COMS), and Terra and Aqua Moderate Resolution Imaging Spectroradiometer (MODIS) (Collection 6) in East Asia in 2012 and 2013. In the case study in Beijing, when compared with AOD observations from handheld sunphotometers, 51% of VIIRS Environmental Data Record (EDR) AOD, 37% of GOCI AOD, 33% of VIIRS Intermediate Product (IP) AOD, 26% of Terra MODIS C6 3km AOD, and 16% of Aqua MODIS C6 3km AOD fell within the reference expected error (EE) envelope (+/-0.05/+/- 0.15 AOD). Comparing against AERONET AOD over the JapanSouth Korea region, 64% of EDR, 37% of IP, 61% of GOCI, 39% of Terra MODIS, and 56% of Aqua MODIS C6 3km AOD fell within the EE. In general, satellite aerosol products performed better in tracking the day-to-day variability than tracking the spatial variability at high resolutions. The VIIRS EDR and GOCI products provided the most accurate AOD retrievals, while VIIRS IP and MODIS C6 3km products had positive biases.

Evaluation of VIIRS, GOCI, and MODIS Collection 6 AOD retrievals against ground sunphotometer observations over East Asia

NASA Astrophysics Data System (ADS)

Xiao, Q.; Zhang, H.; Choi, M.; Li, S.; Kondragunta, S.; Kim, J.; Holben, B.; Levy, R. C.; Liu, Y.

2016-02-01

Persistent high aerosol loadings together with extremely high population densities have raised serious air quality and public health concerns in many urban centers in East Asia. However, ground-based air quality monitoring is relatively limited in this area. Recently, satellite-retrieved Aerosol Optical Depth (AOD) at high resolution has become a powerful tool to characterize aerosol patterns in space and time. Using ground AOD observations from the Aerosol Robotic Network (AERONET) and the Distributed Regional Aerosol Gridded Observation Networks (DRAGON)-Asia Campaign, as well as from handheld sunphotometers, we evaluated emerging aerosol products from the Visible Infrared Imaging Radiometer Suite (VIIRS) aboard the Suomi National Polar-orbiting Partnership (S-NPP), the Geostationary Ocean Color Imager (GOCI) aboard the Communication, Ocean, and Meteorology Satellite (COMS), and Terra and Aqua Moderate Resolution Imaging Spectroradiometer (MODIS) (Collection 6) in East Asia in 2012 and 2013. In the case study in Beijing, when compared with AOD observations from handheld sunphotometers, 51 % of VIIRS Environmental Data Record (EDR) AOD, 37 % of GOCI AOD, 33 % of VIIRS Intermediate Product (IP) AOD, 26 % of Terra MODIS C6 3 km AOD, and 16 % of Aqua MODIS C6 3 km AOD fell within the reference expected error (EE) envelope (±0.05 ± 0.15 AOD). Comparing against AERONET AOD over the Japan-South Korea region, 64 % of EDR, 37 % of IP, 61 % of GOCI, 39 % of Terra MODIS, and 56 % of Aqua MODIS C6 3 km AOD fell within the EE. In general, satellite aerosol products performed better in tracking the day-to-day variability than tracking the spatial variability at high resolutions. The VIIRS EDR and GOCI products provided the most accurate AOD retrievals, while VIIRS IP and MODIS C6 3 km products had positive biases.

Mapping near-surface air temperature, pressure, relative humidity and wind speed over Mainland China with high spatiotemporal resolution

NASA Astrophysics Data System (ADS)

Li, Tao; Zheng, Xiaogu; Dai, Yongjiu; Yang, Chi; Chen, Zhuoqi; Zhang, Shupeng; Wu, Guocan; Wang, Zhonglei; Huang, Chengcheng; Shen, Yan; Liao, Rongwei

2014-09-01

As part of a joint effort to construct an atmospheric forcing dataset for mainland China with high spatiotemporal resolution, a new approach is proposed to construct gridded near-surface temperature, relative humidity, wind speed and surface pressure with a resolution of 1 km×1 km. The approach comprises two steps: (1) fit a partial thin-plate smoothing spline with orography and reanalysis data as explanatory variables to ground-based observations for estimating a trend surface; (2) apply a simple kriging procedure to the residual for trend surface correction. The proposed approach is applied to observations collected at approximately 700 stations over mainland China. The generated forcing fields are compared with the corresponding components of the National Centers for Environmental Prediction (NCEP) Climate Forecast System Reanalysis dataset and the Princeton meteorological forcing dataset. The comparison shows that, both within the station network and within the resolutions of the two gridded datasets, the interpolation errors of the proposed approach are markedly smaller than the two gridded datasets.

Comparison of Two Grid Refinement Approaches for High Resolution Regional Climate Modeling: MPAS vs WRF

NASA Astrophysics Data System (ADS)

Leung, L.; Hagos, S. M.; Rauscher, S.; Ringler, T.

2012-12-01

This study compares two grid refinement approaches using global variable resolution model and nesting for high-resolution regional climate modeling. The global variable resolution model, Model for Prediction Across Scales (MPAS), and the limited area model, Weather Research and Forecasting (WRF) model, are compared in an idealized aqua-planet context with a focus on the spatial and temporal characteristics of tropical precipitation simulated by the models using the same physics package from the Community Atmosphere Model (CAM4). For MPAS, simulations have been performed with a quasi-uniform resolution global domain at coarse (1 degree) and high (0.25 degree) resolution, and a variable resolution domain with a high-resolution region at 0.25 degree configured inside a coarse resolution global domain at 1 degree resolution. Similarly, WRF has been configured to run on a coarse (1 degree) and high (0.25 degree) resolution tropical channel domain as well as a nested domain with a high-resolution region at 0.25 degree nested two-way inside the coarse resolution (1 degree) tropical channel. The variable resolution or nested simulations are compared against the high-resolution simulations that serve as virtual reality. Both MPAS and WRF simulate 20-day Kelvin waves propagating through the high-resolution domains fairly unaffected by the change in resolution. In addition, both models respond to increased resolution with enhanced precipitation. Grid refinement induces zonal asymmetry in precipitation (heating), accompanied by zonal anomalous Walker like circulations and standing Rossby wave signals. However, there are important differences between the anomalous patterns in MPAS and WRF due to differences in the grid refinement approaches and sensitivity of model physics to grid resolution. This study highlights the need for "scale aware" parameterizations in variable resolution and nested regional models.

High Quality Data for Grid Integration Studies

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

Clifton, Andrew; Draxl, Caroline; Sengupta, Manajit

As variable renewable power penetration levels increase in power systems worldwide, renewable integration studies are crucial to ensure continued economic and reliable operation of the power grid. The existing electric grid infrastructure in the US in particular poses significant limitations on wind power expansion. In this presentation we will shed light on requirements for grid integration studies as far as wind and solar energy are concerned. Because wind and solar plants are strongly impacted by weather, high-resolution and high-quality weather data are required to drive power system simulations. Future data sets will have to push limits of numerical weather predictionmore » to yield these high-resolution data sets, and wind data will have to be time-synchronized with solar data. Current wind and solar integration data sets are presented. The Wind Integration National Dataset (WIND) Toolkit is the largest and most complete grid integration data set publicly available to date. A meteorological data set, wind power production time series, and simulated forecasts created using the Weather Research and Forecasting Model run on a 2-km grid over the continental United States at a 5-min resolution is now publicly available for more than 126,000 land-based and offshore wind power production sites. The National Solar Radiation Database (NSRDB) is a similar high temporal- and spatial resolution database of 18 years of solar resource data for North America and India. The need for high-resolution weather data pushes modeling towards finer scales and closer synchronization. We also present how we anticipate such datasets developing in the future, their benefits, and the challenges with using and disseminating such large amounts of data.« less

Estimating Biogenic Non-Methane Hydrocarbon Emissions for the Wasatch Front Through a High-Resolution. Gridded, Biogenic Vola Tile Organic Compound Emissions Inventory

DTIC Science & Technology

2002-01-01

1-hour and proposed 8-hour National Ambient Air Quality Standards. Reactive biogenic (natural) volatile organic compounds emitted from plants have...uncertainty in predicting plant species composition and frequency. Isoprene emissions computed for the study area from the project’s high-resolution...Landcover Database (BELD 2), while monoterpene and other reactive volatile organic compound emission rates were almost 26% and 28% lower, respectively

New Methods for Air Quality Model Evaluation with Satellite Data

NASA Astrophysics Data System (ADS)

Holloway, T.; Harkey, M.

2015-12-01

Despite major advances in the ability of satellites to detect gases and aerosols in the atmosphere, there remains significant, untapped potential to apply space-based data to air quality regulatory applications. Here, we showcase research findings geared toward increasing the relevance of satellite data to support operational air quality management, focused on model evaluation. Particular emphasis is given to nitrogen dioxide (NO2) and formaldehyde (HCHO) from the Ozone Monitoring Instrument aboard the NASA Aura satellite, and evaluation of simulations from the EPA Community Multiscale Air Quality (CMAQ) model. This work is part of the NASA Air Quality Applied Sciences Team (AQAST), and is motivated by ongoing dialog with state and federal air quality management agencies. We present the response of satellite-derived NO2 to meteorological conditions, satellite-derived HCHO:NO2 ratios as an indicator of ozone production regime, and the ability of models to capture these sensitivities over the continental U.S. In the case of NO2-weather sensitivities, we find boundary layer height, wind speed, temperature, and relative humidity to be the most important variables in determining near-surface NO2 variability. CMAQ agreed with relationships observed in satellite data, as well as in ground-based data, over most regions. However, we find that the southwest U.S. is a problem area for CMAQ, where modeled NO2 responses to insolation, boundary layer height, and other variables are at odds with the observations. Our analyses utilize a software developed by our team, the Wisconsin Horizontal Interpolation Program for Satellites (WHIPS): a free, open-source program designed to make satellite-derived air quality data more usable. WHIPS interpolates level 2 satellite retrievals onto a user-defined fixed grid, in effect creating custom-gridded level 3 satellite product. Currently, WHIPS can process the following data products: OMI NO2 (NASA retrieval); OMI NO2 (KNMI retrieval); OMI HCHO (NASA retrieval); MOPITT CO (NASA retrieval); MODIS AOD (NASA retrieval). More information at http://nelson.wisc.edu/sage/data-and-models/software.php.

Statistical modeling of urban air temperature distributions under different synoptic conditions

NASA Astrophysics Data System (ADS)

Beck, Christoph; Breitner, Susanne; Cyrys, Josef; Hald, Cornelius; Hartz, Uwe; Jacobeit, Jucundus; Richter, Katja; Schneider, Alexandra; Wolf, Kathrin

2015-04-01

Within urban areas air temperature may vary distinctly between different locations. These intra-urban air temperature variations partly reach magnitudes that are relevant with respect to human thermal comfort. Therefore and furthermore taking into account potential interrelations with other health related environmental factors (e.g. air quality) it is important to estimate spatial patterns of intra-urban air temperature distributions that may be incorporated into urban planning processes. In this contribution we present an approach to estimate spatial temperature distributions in the urban area of Augsburg (Germany) by means of statistical modeling. At 36 locations in the urban area of Augsburg air temperatures are measured with high temporal resolution (4 min.) since December 2012. These 36 locations represent different typical urban land use characteristics in terms of varying percentage coverages of different land cover categories (e.g. impervious, built-up, vegetated). Percentage coverages of these land cover categories have been extracted from different sources (Open Street Map, European Urban Atlas, Urban Morphological Zones) for regular grids of varying size (50, 100, 200 meter horizonal resolution) for the urban area of Augsburg. It is well known from numerous studies that land use characteristics have a distinct influence on air temperature and as well other climatic variables at a certain location. Therefore air temperatures at the 36 locations are modeled utilizing land use characteristics (percentage coverages of land cover categories) as predictor variables in Stepwise Multiple Regression models and in Random Forest based model approaches. After model evaluation via cross-validation appropriate statistical models are applied to gridded land use data to derive spatial urban air temperature distributions. Varying models are tested and applied for different seasons and times of the day and also for different synoptic conditions (e.g. clear and calm situations, cloudy and windy situations). Based on hourly air temperature data from our measurements in the urban area of Augsburg distinct temperature differences between locations with different urban land use characteristics are revealed. Under clear and calm weather conditions differences between mean hourly air temperatures reach values around 8°C. Whereas during cloudy and windy weather maximum differences in mean hourly air temperatures do not exceed 5°C. Differences appear usually slightly more pronounced in summer than in winter. First results from the application of statistical modeling approaches reveal promising skill of the models in terms of explained variances reaching up to 60% in leave-one-out cross-validation experiments. The contribution depicts the methodology of our approach and presents and discusses first results.

Urban Air Quality Modelling with AURORA: Prague and Bratislava

NASA Astrophysics Data System (ADS)

Veldeman, N.; Viaene, P.; De Ridder, K.; Peelaerts, W.; Lauwaet, D.; Muhammad, N.; Blyth, L.

2012-04-01

The European Commission, in its strategy to protect the health of the European citizens, states that in order to assess the impact of air pollution on public health, information on long-term exposure to air pollution should be available. Currently, indicators of air quality are often being generated using measured pollutant concentrations. While air quality monitoring stations data provide accurate time series information at specific locations, air quality models have the advantage of being able to assess the spatial variability of air quality (for different resolutions) and predict air quality in the future based on different scenarios. When running such air quality models at a high spatial and temporal resolution, one can simulate the actual situation as closely as possible, allowing for a detailed assessment of the risk of exposure to citizens from different pollutants. AURORA (Air quality modelling in Urban Regions using an Optimal Resolution Approach), a prognostic 3-dimensional Eulerian chemistry-transport model, is designed to simulate urban- to regional-scale atmospheric pollutant concentration and exposure fields. The AURORA model also allows to calculate the impact of changes in land use (e.g. planting of trees) or of emission reduction scenario's on air quality. AURORA is currently being applied within the ESA atmospheric GMES service, PASODOBLE (http://www.myair-eu.org), that delivers information on air quality, greenhouse gases, stratospheric ozone, … At present there are two operational AURORA services within PASODOBLE. Within the "Air quality forecast service" VITO delivers daily air quality forecasts for Belgium at a resolution of 5 km and for the major Belgian cities: Brussels, Ghent, Antwerp, Liege and Charleroi. Furthermore forecast services are provided for Prague, Czech Republic and Bratislava, Slovakia, both at a resolution of 1 km. The "Urban/regional air quality assessment service" provides urban- and regional-scale maps (hourly resolution) for air pollution and human exposure statistics for an entire year. So far we concentrated on Brussels, Belgium and the Rotterdam harbour area, The Netherlands. In this contribution we focus on the operational forecast services. Reference Lefebvre W. et al. (2011) Validation of the MIMOSA-AURORA-IFDM model chain for policy support: Modeling concentrations of elemental carbon in Flanders, Atmospheric Environment 45, 6705-6713

Simulation of Anomalous Regional Climate Events with a Variable Resolution Stretched Grid GCM

NASA Technical Reports Server (NTRS)

Fox-Rabinovitz, Michael S.

1999-01-01

The stretched-grid approach provides an efficient down-scaling and consistent interactions between global and regional scales due to using one variable-resolution model for integrations. It is a workable alternative to the widely used nested-grid approach introduced over a decade ago as a pioneering step in regional climate modeling. A variable-resolution General Circulation Model (GCM) employing a stretched grid, with enhanced resolution over the US as the area of interest, is used for simulating two anomalous regional climate events, the US summer drought of 1988 and flood of 1993. The special mode of integration using a stretched-grid GCM and data assimilation system is developed that allows for imitating the nested-grid framework. The mode is useful for inter-comparison purposes and for underlining the differences between these two approaches. The 1988 and 1993 integrations are performed for the two month period starting from mid May. Regional resolutions used in most of the experiments is 60 km. The major goal and the result of the study is obtaining the efficient down-scaling over the area of interest. The monthly mean prognostic regional fields for the stretched-grid integrations are remarkably close to those of the verifying analyses. Simulated precipitation patterns are successfully verified against gauge precipitation observations. The impact of finer 40 km regional resolution is investigated for the 1993 integration and an example of recovering subregional precipitation is presented. The obtained results show that the global variable-resolution stretched-grid approach is a viable candidate for regional and subregional climate studies and applications.

Insights into the physico-chemical evolution of pyrogenic organic carbon emissions from biomass burning using coupled Lagrangian-Eulerian simulations

NASA Astrophysics Data System (ADS)

Suciu, L. G.; Griffin, R. J.; Masiello, C. A.

2017-12-01

Wildfires and prescribed burning are important sources of particulate and gaseous pyrogenic organic carbon (PyOC) emissions to the atmosphere. These emissions impact atmospheric chemistry, air quality and climate, but the spatial and temporal variabilities of these impacts are poorly understood, primarily because small and fresh fire plumes are not well predicted by three-dimensional Eulerian chemical transport models due to their coarser grid size. Generally, this results in underestimation of downwind deposition of PyOC, hydroxyl radical reactivity, secondary organic aerosol formation and ozone (O3) production. However, such models are very good for simulation of multiple atmospheric processes that could affect the lifetimes of PyOC emissions over large spatiotemporal scales. Finer resolution models, such as Lagrangian reactive plumes models (or plume-in-grid), could be used to trace fresh emissions at the sub-grid level of the Eulerian model. Moreover, Lagrangian plume models need background chemistry predicted by the Eulerian models to accurately simulate the interactions of the plume material with the background air during plume aging. Therefore, by coupling the two models, the physico-chemical evolution of the biomass burning plumes can be tracked from local to regional scales. In this study, we focus on the physico-chemical changes of PyOC emissions from sub-grid to grid levels using an existing chemical mechanism. We hypothesize that finer scale Lagrangian-Eulerian simulations of several prescribed burns in the U.S. will allow more accurate downwind predictions (validated by airborne observations from smoke plumes) of PyOC emissions (i.e., submicron particulate matter, organic aerosols, refractory black carbon) as well as O3 and other trace gases. Simulation results could be used to optimize the implementation of additional PyOC speciation in the existing chemical mechanism.

A Variable Resolution Stretched Grid General Circulation Model: Regional Climate Simulation

NASA Technical Reports Server (NTRS)

Fox-Rabinovitz, Michael S.; Takacs, Lawrence L.; Govindaraju, Ravi C.; Suarez, Max J.

2000-01-01

The development of and results obtained with a variable resolution stretched-grid GCM for the regional climate simulation mode, are presented. A global variable resolution stretched- grid used in the study has enhanced horizontal resolution over the U.S. as the area of interest The stretched-grid approach is an ideal tool for representing regional to global scale interaction& It is an alternative to the widely used nested grid approach introduced over a decade ago as a pioneering step in regional climate modeling. The major results of the study are presented for the successful stretched-grid GCM simulation of the anomalous climate event of the 1988 U.S. summer drought- The straightforward (with no updates) two month simulation is performed with 60 km regional resolution- The major drought fields, patterns and characteristics such as the time averaged 500 hPa heights precipitation and the low level jet over the drought area. appear to be close to the verifying analyses for the stretched-grid simulation- In other words, the stretched-grid GCM provides an efficient down-scaling over the area of interest with enhanced horizontal resolution. It is also shown that the GCM skill is sustained throughout the simulation extended to one year. The developed and tested in a simulation mode stretched-grid GCM is a viable tool for regional and subregional climate studies and applications.

HPC Aspects of Variable-Resolution Global Climate Modeling using a Multi-scale Convection Parameterization

EPA Science Inventory

High performance computing (HPC) requirements for the new generation variable grid resolution (VGR) global climate models differ from that of traditional global models. A VGR global model with 15 km grids over the CONUS stretching to 60 km grids elsewhere will have about ~2.5 tim...

Modeling prescribed burning experiments and assessing the fire impacts on local to regional air quality

NASA Astrophysics Data System (ADS)

Zhou, L.; Baker, K. R.; Napelenok, S. L.; Elleman, R. A.; Urbanski, S. P.

2016-12-01

Biomass burning, including wildfires and prescribed burns, strongly impact the global carbon cycle and are of increasing concern due to the potential impacts on ambient air quality. This modelling study focuses on the evolution of carbonaceous compounds during a prescribed burning experiment and assesses the impacts of burning on local to regional air quality. The Community Multiscale Air Quality (CMAQ) model is used to conduct 4 and 2 km grid resolution simulations of prescribed burning experiments in southeast Washington state and western Idaho state in summer 2013. The ground and airborne measurements from the field experiment are used to evaluate the model performance in capturing surface and aloft impacts from the burning events. Phase partitioning of organic compounds in the plume are studied as it is a crucial step towards understanding the fate of carbonaceous compounds. The sensitivities of ambient concentrations and deposition to emissions are conducted for organic carbon, elemental carbon and ozone to estimate the impacts of fire on air quality.

Toward a Unified Representation of Atmospheric Convection in Variable-Resolution Climate Models

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

Walko, Robert

2016-11-07

The purpose of this project was to improve the representation of convection in atmospheric weather and climate models that employ computational grids with spatially-variable resolution. Specifically, our work targeted models whose grids are fine enough over selected regions that convection is resolved explicitly, while over other regions the grid is coarser and convection is represented as a subgrid-scale process. The working criterion for a successful scheme for representing convection over this range of grid resolution was that identical convective environments must produce very similar convective responses (i.e., the same precipitation amount, rate, and timing, and the same modification of themore » atmospheric profile) regardless of grid scale. The need for such a convective scheme has increased in recent years as more global weather and climate models have adopted variable resolution meshes that are often extended into the range of resolving convection in selected locations.« less

A variable resolution right TIN approach for gridded oceanographic data

NASA Astrophysics Data System (ADS)

Marks, David; Elmore, Paul; Blain, Cheryl Ann; Bourgeois, Brian; Petry, Frederick; Ferrini, Vicki

2017-12-01

Many oceanographic applications require multi resolution representation of gridded data such as for bathymetric data. Although triangular irregular networks (TINs) allow for variable resolution, they do not provide a gridded structure. Right TINs (RTINs) are compatible with a gridded structure. We explored the use of two approaches for RTINs termed top-down and bottom-up implementations. We illustrate why the latter is most appropriate for gridded data and describe for this technique how the data can be thinned. While both the top-down and bottom-up approaches accurately preserve the surface morphology of any given region, the top-down method of vertex placement can fail to match the actual vertex locations of the underlying grid in many instances, resulting in obscured topology/bathymetry. Finally we describe the use of the bottom-up approach and data thinning in two applications. The first is to provide thinned, variable resolution bathymetry data for tests of storm surge and inundation modeling, in particular hurricane Katrina. Secondly we consider the use of the approach for an application to an oceanographic data grid of 3-D ocean temperature.

Performance of European chemistry transport models as function of horizontal resolution

NASA Astrophysics Data System (ADS)

Schaap, M.; Cuvelier, C.; Hendriks, C.; Bessagnet, B.; Baldasano, J. M.; Colette, A.; Thunis, P.; Karam, D.; Fagerli, H.; Graff, A.; Kranenburg, R.; Nyiri, A.; Pay, M. T.; Rouïl, L.; Schulz, M.; Simpson, D.; Stern, R.; Terrenoire, E.; Wind, P.

2015-07-01

Air pollution causes adverse effects on human health as well as ecosystems and crop yield and also has an impact on climate change trough short-lived climate forcers. To design mitigation strategies for air pollution, 3D Chemistry Transport Models (CTMs) have been developed to support the decision process. Increases in model resolution may provide more accurate and detailed information, but will cubically increase computational costs and pose additional challenges concerning high resolution input data. The motivation for the present study was therefore to explore the impact of using finer horizontal grid resolution for policy support applications of the European Monitoring and Evaluation Programme (EMEP) model within the Long Range Transboundary Air Pollution (LRTAP) convention. The goal was to determine the "optimum resolution" at which additional computational efforts do not provide increased model performance using presently available input data. Five regional CTMs performed four runs for 2009 over Europe at different horizontal resolutions. The models' responses to an increase in resolution are broadly consistent for all models. The largest response was found for NO2 followed by PM10 and O3. Model resolution does not impact model performance for rural background conditions. However, increasing model resolution improves the model performance at stations in and near large conglomerations. The statistical evaluation showed that the increased resolution better reproduces the spatial gradients in pollution regimes, but does not help to improve significantly the model performance for reproducing observed temporal variability. This study clearly shows that increasing model resolution is advantageous, and that leaving a resolution of 50 km in favour of a resolution between 10 and 20 km is practical and worthwhile. As about 70% of the model response to grid resolution is determined by the difference in the spatial emission distribution, improved emission allocation procedures at high spatial and temporal resolution are a crucial factor for further model resolution improvements.

Development of high-resolution (250 m) historical daily gridded air temperature data using reanalysis and distributed sensor networks for the US northern Rocky Mountains

Treesearch

Zachary A. Holden; Alan Swanson; Anna E. Klene; John T. Abatzoglou; Solomon Z. Dobrowski; Samuel A. Cushman; John Squires; Gretchen G. Moisen; Jared W. Oyler

2016-01-01

Gridded temperature data sets are typically produced at spatial resolutions that cannot fully resolve fine-scale variation in surface air temperature in regions of complex topography. These data limitations have become increasingly important as scientists and managers attempt to understand and plan for potential climate change impacts. Here, we describe the...

High-Density, High-Resolution, Low-Cost Air Quality Sensor Networks for Urban Air Monitoring

NASA Astrophysics Data System (ADS)

Mead, M. I.; Popoola, O. A.; Stewart, G.; Bright, V.; Kaye, P.; Saffell, J.

2012-12-01

Monitoring air quality in highly granular environments such as urban areas which are spatially heterogeneous with variable emission sources, measurements need to be made at appropriate spatial and temporal scales. Current routine air quality monitoring networks generally are either composed of sparse expensive installations (incorporating e.g. chemiluminescence instruments) or higher density low time resolution systems (e.g. NO2 diffusion tubes). Either approach may not accurately capture important effects such as pollutant "hot spots" or adequately capture spatial (or temporal) variability. As a result, analysis based on data from traditional low spatial resolution networks, such as personal exposure, may be inaccurate. In this paper we present details of a sophisticated, low-cost, multi species (gas phase, speciated PM, meteorology) air quality measurement network methodology incorporating GPS and GPRS which has been developed for high resolution air quality measurements in urban areas. Sensor networks developed in the Centre for Atmospheric Science (University of Cambridge) incorporated electrochemical gas sensors configured for use in urban air quality studies operating at parts-per-billion (ppb) levels. It has been demonstrated that these sensors can be used to measure key air quality gases such as CO, NO and NO2 at the low ppb mixing ratios present in the urban environment (estimated detection limits <4ppb for CO and NO and <1ppb for NO2. Mead et al (submitted Aug., 2012)). Based on this work, a state of the art multi species instrument package for deployment in scalable sensor networks has been developed which has general applicability. This is currently being employed as part of a major 3 year UK program at London Heathrow airport (the Sensor Networks for Air Quality (SNAQ) Heathrow project). The main project outcome is the creation of a calibrated, high spatial and temporal resolution data set for O3, NO, NO2, SO2, CO, CO2, VOCstotal, size-speciated PM, temperature, relative humidity, wind speed and direction. The network incorporates existing GPRS infrastructures for real time sending of data with low overheads in terms of cost, effort and installation. In this paper we present data from the SNAQ Heathrow project as well as previous deployments showing measurement capability at the ppb level for NO, NO2 and CO. We show that variability can be observed and measured quantitatively using these sensor networks over widely differing time scales from individual emission events, diurnal variability associated with traffic and meteorological conditions, through to longer term synoptic weather conditions and seasonal behaviour. This work demonstrates a widely applicable generic capability to urban areas, airports as well as other complex emissions environments making this sensor system methodology valuable for scientific, policy and regulatory issues. We conclude that the low-cost high-density network philosophy has the potential to provide a more complete assessment of the high-granularity air quality structure generally observed in the environment. Further, when appropriately deployed, has the potential to offer a new paradigm in air quality quantification and monitoring.

InMAP: A model for air pollution interventions

DOE PAGES

Tessum, Christopher W.; Hill, Jason D.; Marshall, Julian D.; ...

2017-04-19

Mechanistic air pollution modeling is essential in air quality management, yet the extensive expertise and computational resources required to run most models prevent their use in many situations where their results would be useful. We present InMAP (Intervention Model for Air Pollution), which offers an alternative to comprehensive air quality models for estimating the air pollution health impacts of emission reductions and other potential interventions. InMAP estimates annual-average changes in primary and secondary fine particle (PM2.5) concentrations—the air pollution outcome generally causing the largest monetized health damages–attributable to annual changes in precursor emissions. InMAP leverages pre-processed physical and chemical informationmore » from the output of a state-of-the-science chemical transport model and a variable spatial resolution computational grid to perform simulations that are several orders of magnitude less computationally intensive than comprehensive model simulations. In comparisons we run, InMAP recreates comprehensive model predictions of changes in total PM2.5 concentrations with population-weighted mean fractional bias (MFB) of -17% and population-weighted R2 = 0.90. Although InMAP is not specifically designed to reproduce total observed concentrations, it is able to do so within published air quality model performance criteria for total PM2.5. Potential uses of InMAP include studying exposure, health, and environmental justice impacts of potential shifts in emissions for annual-average PM2.5. InMAP can be trained to run for any spatial and temporal domain given the availability of appropriate simulation output from a comprehensive model. The InMAP model source code and input data are freely available online under an open-source license.« less

InMAP: A model for air pollution interventions

PubMed Central

Hill, Jason D.; Marshall, Julian D.

2017-01-01

Mechanistic air pollution modeling is essential in air quality management, yet the extensive expertise and computational resources required to run most models prevent their use in many situations where their results would be useful. Here, we present InMAP (Intervention Model for Air Pollution), which offers an alternative to comprehensive air quality models for estimating the air pollution health impacts of emission reductions and other potential interventions. InMAP estimates annual-average changes in primary and secondary fine particle (PM2.5) concentrations—the air pollution outcome generally causing the largest monetized health damages–attributable to annual changes in precursor emissions. InMAP leverages pre-processed physical and chemical information from the output of a state-of-the-science chemical transport model and a variable spatial resolution computational grid to perform simulations that are several orders of magnitude less computationally intensive than comprehensive model simulations. In comparisons run here, InMAP recreates comprehensive model predictions of changes in total PM2.5 concentrations with population-weighted mean fractional bias (MFB) of −17% and population-weighted R2 = 0.90. Although InMAP is not specifically designed to reproduce total observed concentrations, it is able to do so within published air quality model performance criteria for total PM2.5. Potential uses of InMAP include studying exposure, health, and environmental justice impacts of potential shifts in emissions for annual-average PM2.5. InMAP can be trained to run for any spatial and temporal domain given the availability of appropriate simulation output from a comprehensive model. The InMAP model source code and input data are freely available online under an open-source license. PMID:28423049

InMAP: A model for air pollution interventions

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

Tessum, Christopher W.; Hill, Jason D.; Marshall, Julian D.

Mechanistic air pollution modeling is essential in air quality management, yet the extensive expertise and computational resources required to run most models prevent their use in many situations where their results would be useful. We present InMAP (Intervention Model for Air Pollution), which offers an alternative to comprehensive air quality models for estimating the air pollution health impacts of emission reductions and other potential interventions. InMAP estimates annual-average changes in primary and secondary fine particle (PM2.5) concentrations—the air pollution outcome generally causing the largest monetized health damages–attributable to annual changes in precursor emissions. InMAP leverages pre-processed physical and chemical informationmore » from the output of a state-of-the-science chemical transport model and a variable spatial resolution computational grid to perform simulations that are several orders of magnitude less computationally intensive than comprehensive model simulations. In comparisons we run, InMAP recreates comprehensive model predictions of changes in total PM2.5 concentrations with population-weighted mean fractional bias (MFB) of -17% and population-weighted R2 = 0.90. Although InMAP is not specifically designed to reproduce total observed concentrations, it is able to do so within published air quality model performance criteria for total PM2.5. Potential uses of InMAP include studying exposure, health, and environmental justice impacts of potential shifts in emissions for annual-average PM2.5. InMAP can be trained to run for any spatial and temporal domain given the availability of appropriate simulation output from a comprehensive model. The InMAP model source code and input data are freely available online under an open-source license.« less

Regional model simulations of New Zealand climate

NASA Astrophysics Data System (ADS)

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

1998-03-01

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

The Aeroflex: A Bicycle for Mobile Air Quality Measurements

PubMed Central

Elen, Bart; Peters, Jan; Van Poppel, Martine; Bleux, Nico; Theunis, Jan; Reggente, Matteo; Standaert, Arnout

2013-01-01

Fixed air quality stations have limitations when used to assess people's real life exposure to air pollutants. Their spatial coverage is too limited to capture the spatial variability in, e.g., an urban or industrial environment. Complementary mobile air quality measurements can be used as an additional tool to fill this void. In this publication we present the Aeroflex, a bicycle for mobile air quality monitoring. The Aeroflex is equipped with compact air quality measurement devices to monitor ultrafine particle number counts, particulate mass and black carbon concentrations at a high resolution (up to 1 second). Each measurement is automatically linked to its geographical location and time of acquisition using GPS and Internet time. Furthermore, the Aeroflex is equipped with automated data transmission, data pre-processing and data visualization. The Aeroflex is designed with adaptability, reliability and user friendliness in mind. Over the past years, the Aeroflex has been successfully used for high resolution air quality mapping, exposure assessment and hot spot identification. PMID:23262484

The Aeroflex: a bicycle for mobile air quality measurements.

PubMed

Elen, Bart; Peters, Jan; Poppel, Martine Van; Bleux, Nico; Theunis, Jan; Reggente, Matteo; Standaert, Arnout

2012-12-24

Fixed air quality stations have limitations when used to assess people's real life exposure to air pollutants. Their spatial coverage is too limited to capture the spatial variability in, e.g., an urban or industrial environment. Complementary mobile air quality measurements can be used as an additional tool to fill this void. In this publication we present the Aeroflex, a bicycle for mobile air quality monitoring. The Aeroflex is equipped with compact air quality measurement devices to monitor ultrafine particle number counts, particulate mass and black carbon concentrations at a high resolution (up to 1 second). Each measurement is automatically linked to its geographical location and time of acquisition using GPS and Internet time. Furthermore, the Aeroflex is equipped with automated data transmission, data pre-processing and data visualization. The Aeroflex is designed with adaptability, reliability and user friendliness in mind. Over the past years, the Aeroflex has been successfully used for high resolution air quality mapping, exposure assessment and hot spot identification. 

Modelled air pollution levels versus EC air quality legislation - results from high resolution simulation.

PubMed

Chervenkov, Hristo

2013-12-01

An appropriate method for evaluating the air quality of a certain area is to contrast the actual air pollution levels to the critical ones, prescribed in the legislative standards. The application of numerical simulation models for assessing the real air quality status is allowed by the legislation of the European Community (EC). This approach is preferable, especially when the area of interest is relatively big and/or the network of measurement stations is sparse, and the available observational data are scarce, respectively. Such method is very efficient for similar assessment studies due to continuous spatio-temporal coverage of the obtained results. In the study the values of the concentration of the harmful substances sulphur dioxide, (SO2), nitrogen dioxide (NO2), particulate matter - coarse (PM10) and fine (PM2.5) fraction, ozone (O3), carbon monoxide (CO) and ammonia (NH3) in the surface layer obtained from modelling simulations with resolution 10 km on hourly bases are taken to calculate the necessary statistical quantities which are used for comparison with the corresponding critical levels, prescribed in the EC directives. For part of them (PM2.5, CO and NH3) this is done for first time with such resolution. The computational grid covers Bulgaria entirely and some surrounding territories and the calculations are made for every year in the period 1991-2000. The averaged over the whole time slice results can be treated as representative for the air quality situation of the last decade of the former century.

Modeling emissions for three-dimensional atmospheric chemistry transport models.

PubMed

Matthias, Volker; Arndt, Jan A; Aulinger, Armin; Bieser, Johannes; Denier Van Der Gon, Hugo; Kranenburg, Richard; Kuenen, Jeroen; Neumann, Daniel; Pouliot, George; Quante, Markus

2018-01-24

Poor air quality is still a threat for human health in many parts of the world. In order to assess measures for emission reductions and improved air quality, three-dimensional atmospheric chemistry transport modeling systems are used in numerous research institutions and public authorities. These models need accurate emission data in appropriate spatial and temporal resolution as input. This paper reviews the most widely used emission inventories on global and regional scale and looks into the methods used to make the inventory data model ready. Shortcomings of using standard temporal profiles for each emission sector are discussed and new methods to improve the spatio-temporal distribution of the emissions are presented. These methods are often neither top-down nor bottom-up approaches but can be seen as hybrid methods that use detailed information about the emission process to derive spatially varying temporal emission profiles. These profiles are subsequently used to distribute bulk emissions like national totals on appropriate grids. The wide area of natural emissions is also summarized and the calculation methods are described. Almost all types of natural emissions depend on meteorological information, which is why they are highly variable in time and space and frequently calculated within the chemistry transport models themselves. The paper closes with an outlook for new ways to improve model ready emission data, for example by using external databases about road traffic flow or satellite data to determine actual land use or leaf area. In a world where emission patterns change rapidly, it seems appropriate to use new types of statistical and observational data to create detailed emission data sets and keep emission inventories up-to-date. Emission data is probably the most important input for chemistry transport model (CTM) systems. It needs to be provided in high temporal and spatial resolution and on a grid that is in agreement with the CTM grid. Simple methods to distribute the emissions in time and space need to be replaced by sophisticated emission models in order to improve the CTM results. New methods, e.g. for ammonia emissions, provide grid cell dependent temporal profiles. In the future, large data fields from traffic observations or satellite observations could be used for more detailed emission data.

Adaptive EAGLE dynamic solution adaptation and grid quality enhancement

NASA Technical Reports Server (NTRS)

Luong, Phu Vinh; Thompson, J. F.; Gatlin, B.; Mastin, C. W.; Kim, H. J.

1992-01-01

In the effort described here, the elliptic grid generation procedure in the EAGLE grid code was separated from the main code into a subroutine, and a new subroutine which evaluates several grid quality measures at each grid point was added. The elliptic grid routine can now be called, either by a computational fluid dynamics (CFD) code to generate a new adaptive grid based on flow variables and quality measures through multiple adaptation, or by the EAGLE main code to generate a grid based on quality measure variables through static adaptation. Arrays of flow variables can be read into the EAGLE grid code for use in static adaptation as well. These major changes in the EAGLE adaptive grid system make it easier to convert any CFD code that operates on a block-structured grid (or single-block grid) into a multiple adaptive code.

AIRS Observations Based Evaluation of Relative Climate Feedback Strengths on a GCM Grid-Scale

NASA Astrophysics Data System (ADS)

Molnar, G. I.; Susskind, J.

2012-12-01

Climate feedback strengths, especially those associated with moist processes, still have a rather wide range in GCMs, the primary tools to predict future climate changes associated with man's ever increasing influences on our planet. Here, we make use of the first 10 years of AIRS observations to evaluate interrelationships/correlations of atmospheric moist parameter anomalies computed from AIRS Version 5 Level-3 products, and demonstrate their usefulness to assess relative feedback strengths. Although one may argue about the possible usability of shorter-term, observed climate parameter anomalies for estimating the strength of various (mostly moist processes related) feedbacks, recent works, in particular analyses by Dessler [2008, 2010], have demonstrated their usefulness in assessing global water vapor and cloud feedbacks. First, we create AIRS-observed monthly anomaly time-series (ATs) of outgoing longwave radiation, water vapor, clouds and temperature profile over a 10-year long (Sept. 2002 through Aug. 2012) period using 1x1 degree resolution (a common GCM grid-scale). Next, we evaluate the interrelationships of ATs of the above parameters with the corresponding 1x1 degree, as well as global surface temperature ATs. The latter provides insight comparable with more traditional climate feedback definitions (e. g., Zelinka and Hartmann, 2012) whilst the former is related to a new definition of "local (in surface temperature too) feedback strengths" on a GCM grid-scale. Comparing the correlation maps generated provides valuable new information on the spatial distribution of relative climate feedback strengths. We argue that for GCMs to be trusted for predicting longer-term climate variability, they should be able to reproduce these observed relationships/metrics as closely as possible. For this time period the main climate "forcing" was associated with the El Niño/La Niña variability (e. g., Dessler, 2010), so these assessments may not be descriptive of longer-term climate feedbacks due to global warming, for example. Nevertheless, one should take more confidence of greenhouse warming predictions of those GCMs that reproduce the (high quality observations-based) shorter-term feedback-relationships the best.

The Monotonic Lagrangian Grid for Rapid Air-Traffic Evaluation

NASA Technical Reports Server (NTRS)

Kaplan, Carolyn; Dahm, Johann; Oran, Elaine; Alexandrov, Natalia; Boris, Jay

2010-01-01

The Air Traffic Monotonic Lagrangian Grid (ATMLG) is presented as a tool to evaluate new air traffic system concepts. The model, based on an algorithm called the Monotonic Lagrangian Grid (MLG), can quickly sort, track, and update positions of many aircraft, both on the ground (at airports) and in the air. The underlying data structure is based on the MLG, which is used for sorting and ordering positions and other data needed to describe N moving bodies and their interactions. Aircraft that are close to each other in physical space are always near neighbors in the MLG data arrays, resulting in a fast nearest-neighbor interaction algorithm that scales as N. Recent upgrades to ATMLG include adding blank place-holders within the MLG data structure, which makes it possible to dynamically change the MLG size and also improves the quality of the MLG grid. Additional upgrades include adding FAA flight plan data, such as way-points and arrival and departure times from the Enhanced Traffic Management System (ETMS), and combining the MLG with the state-of-the-art strategic and tactical conflict detection and resolution algorithms from the NASA-developed Stratway software. In this paper, we present results from our early efforts to couple ATMLG with the Stratway software, and we demonstrate that it can be used to quickly simulate air traffic flow for a very large ETMS dataset.

A hybrid modeling with data assimilation to evaluate human exposure level

NASA Astrophysics Data System (ADS)

Koo, Y. S.; Cheong, H. K.; Choi, D.; Kim, A. L.; Yun, H. Y.

2015-12-01

Exposure models are designed to better represent human contact with PM (Particulate Matter) and other air pollutants such as CO, SO2, O3, and NO2. The exposure concentrations of the air pollutants to human are determined by global and regional long range transport of global and regional scales from Europe and China as well as local emissions from urban and road vehicle sources. To assess the exposure level in detail, the multiple scale influence from background to local sources should be considered. A hybrid air quality modeling methodology combing a grid-based chemical transport model with a local plume dispersion model was used to provide spatially and temporally resolved air quality concentration for human exposure levels in Korea. In the hybrid modeling approach, concentrations from a grid-based chemical transport model and a local plume dispersion model are added to provide contributions from photochemical interactions, long-range (regional) transport and local-scale dispersion. The CAMx (Comprehensive Air quality Model with Extensions was used for the background concentrations from anthropogenic and natural emissions in East Asia including Korea while the road dispersion by vehicle emission was calculated by CALPUFF model. The total exposure level of the pollutants was finally assessed by summing the background and road contributions. In the hybrid modeling, the data assimilation method based on the optimal interpolation was applied to overcome the discrepancies between the model predicted concentrations and observations. The air quality data from the air quality monitoring stations in Korea. The spatial resolution of the hybrid model was 50m for the Seoul Metropolitan Ares. This example clearly demonstrates that the exposure level could be estimated to the fine scale for the exposure assessment by using the hybrid modeling approach with data assimilation.

File Specification for the 7-km GEOS-5 Nature Run, Ganymed Release Non-Hydrostatic 7-km Global Mesoscale Simulation

NASA Technical Reports Server (NTRS)

da Silva, Arlindo M.; Putman, William; Nattala, J.

2014-01-01

This document describes the gridded output files produced by a two-year global, non-hydrostatic mesoscale simulation for the period 2005-2006 produced with the non-hydrostatic version of GEOS-5 Atmospheric Global Climate Model (AGCM). In addition to standard meteorological parameters (wind, temperature, moisture, surface pressure), this simulation includes 15 aerosol tracers (dust, sea-salt, sulfate, black and organic carbon), O3, CO and CO2. This model simulation is driven by prescribed sea-surface temperature and sea-ice, daily volcanic and biomass burning emissions, as well as high-resolution inventories of anthropogenic sources. A description of the GEOS-5 model configuration used for this simulation can be found in Putman et al. (2014). The simulation is performed at a horizontal resolution of 7 km using a cubed-sphere horizontal grid with 72 vertical levels, extending up to to 0.01 hPa (approximately 80 km). For user convenience, all data products are generated on two logically rectangular longitude-latitude grids: a full-resolution 0.0625 deg grid that approximately matches the native cubed-sphere resolution, and another 0.5 deg reduced-resolution grid. The majority of the full-resolution data products are instantaneous with some fields being time-averaged. The reduced-resolution datasets are mostly time-averaged, with some fields being instantaneous. Hourly data intervals are used for the reduced-resolution datasets, while 30-minute intervals are used for the full-resolution products. All full-resolution output is on the model's native 72-layer hybrid sigma-pressure vertical grid, while the reduced-resolution output is given on native vertical levels and on 48 pressure surfaces extending up to 0.02 hPa. Section 4 presents additional details on horizontal and vertical grids. Information of the model surface representation can be found in Appendix B. The GEOS-5 product is organized into file collections that are described in detail in Appendix C. Additional details about variables listed in this file specification can be found in a separate document, the GEOS-5 File Specification Variable Definition Glossary. Documentation about the current access methods for products described in this document can be found on the GEOS-5 Nature Run portal: http://gmao.gsfc.nasa.gov/projects/G5NR. Information on the scientific quality of this simulation will appear in a forthcoming NASA Technical Report Series on Global Modeling and Data Assimilation to be available from http://gmao.gsfc.nasa.gov/pubs/tm/.

High-resolution daily gridded datasets of air temperature and wind speed for Europe

NASA Astrophysics Data System (ADS)

Brinckmann, S.; Krähenmann, S.; Bissolli, P.

2015-08-01

New high-resolution datasets for near surface daily air temperature (minimum, maximum and mean) and daily mean wind speed for Europe (the CORDEX domain) are provided for the period 2001-2010 for the purpose of regional model validation in the framework of DecReg, a sub-project of the German MiKlip project, which aims to develop decadal climate predictions. The main input data sources are hourly SYNOP observations, partly supplemented by station data from the ECA&D dataset (http://www.ecad.eu). These data are quality tested to eliminate erroneous data and various kinds of inhomogeneities. Grids in a resolution of 0.044° (5 km) are derived by spatial interpolation of these station data into the CORDEX area. For temperature interpolation a modified version of a regression kriging method developed by Krähenmann et al. (2011) is used. At first, predictor fields of altitude, continentality and zonal mean temperature are chosen for a regression applied to monthly station data. The residuals of the monthly regression and the deviations of the daily data from the monthly averages are interpolated using simple kriging in a second and third step. For wind speed a new method based on the concept used for temperature was developed, involving predictor fields of exposure, roughness length, coastal distance and ERA Interim reanalysis wind speed at 850 hPa. Interpolation uncertainty is estimated by means of the kriging variance and regression uncertainties. Furthermore, to assess the quality of the final daily grid data, cross validation is performed. Explained variance ranges from 70 to 90 % for monthly temperature and from 50 to 60 % for monthly wind speed. The resulting RMSE for the final daily grid data amounts to 1-2 °C and 1-1.5 m s-1 (depending on season and parameter) for daily temperature parameters and daily mean wind speed, respectively. The datasets presented in this article are published at http://dx.doi.org/10.5676/DWD_CDC/DECREG0110v1.

Frontiers in Atmospheric Chemistry Modelling

NASA Astrophysics Data System (ADS)

Colette, Augustin; Bessagnet, Bertrand; Meleux, Frederik; Rouïl, Laurence

2013-04-01

The first pan-European kilometre-scale atmospheric chemistry simulation is introduced. The continental-scale air pollution episode of January 2009 is modelled with the CHIMERE offline chemistry-transport model with a massive grid of 2 million horizontal points, performed on 2000 CPU of a high performance computing system hosted by the Research and Technology Computing Center at the French Alternative Energies and Atomic Energy Commission (CCRT/CEA). Besides the technical challenge, which demonstrated the robustness of the selected air quality model, we discuss the added value in terms of air pollution modelling and decision support. The comparison with in-situ observations shows that model biases are significantly improved despite some spurious added spatial variability attributed to shortcomings in the emission downscaling process and coarse resolution of the meteorological fields. The increased spatial resolution is clearly beneficial for the detection of exceedances and exposure modelling. We reveal small scale air pollution patterns that highlight the contribution of city plumes to background air pollution levels. Up to a factor 5 underestimation of the fraction of population exposed to detrimental levels of pollution can be obtained with a coarse simulation if subgrid scale correction such as urban increments are ignored. This experiment opens new perspectives for environmental decision making. After two decades of efforts to reduce air pollutant emissions across Europe, the challenge is now to find the optimal trade-off between national and local air quality management strategies. While the first approach is based on sectoral strategies and energy policies, the later builds upon new alternatives such as urban development. The strategies, the decision pathways and the involvement of individual citizen differ, and a compromise based on cost and efficiency must be found. We illustrated how high performance computing in atmospheric science can contribute to this aim. Although further developments are still needed to secure the results for routine policy use, the door is now open...

High-resolution surface analysis for extended-range downscaling with limited-area atmospheric models

NASA Astrophysics Data System (ADS)

Separovic, Leo; Husain, Syed Zahid; Yu, Wei; Fernig, David

2014-12-01

High-resolution limited-area model (LAM) simulations are frequently employed to downscale coarse-resolution objective analyses over a specified area of the globe using high-resolution computational grids. When LAMs are integrated over extended time frames, from months to years, they are prone to deviations in land surface variables that can be harmful to the quality of the simulated near-surface fields. Nudging of the prognostic surface fields toward a reference-gridded data set is therefore devised in order to prevent the atmospheric model from diverging from the expected values. This paper presents a method to generate high-resolution analyses of land-surface variables, such as surface canopy temperature, soil moisture, and snow conditions, to be used for the relaxation of lower boundary conditions in extended-range LAM simulations. The proposed method is based on performing offline simulations with an external surface model, forced with the near-surface meteorological fields derived from short-range forecast, operational analyses, and observed temperatures and humidity. Results show that the outputs of the surface model obtained in the present study have potential to improve the near-surface atmospheric fields in extended-range LAM integrations.

Relating health and climate impacts to grid-scale emissions using adjoint sensitivity modeling for the Climate and Clean Air Coalition

NASA Astrophysics Data System (ADS)

Henze, D. K.; Lacey, F.; Seltzer, M.; Vallack, H.; Kuylenstierna, J.; Bowman, K. W.; Anenberg, S.; Sasser, E.; Lee, C. J.; Martin, R.

2013-12-01

The Climate and Clean Air Coalition (CCAC) was initiated in 2012 to develop, understand and promote measures to reduce short lived climate forcers such as aerosol, ozone and methane. The Coalition now includes over 30 nations, and as a service to these nations is committed to providing a decision support toolkit that allows member nations to explore the benefits of a range of emissions mitigation measures in terms of the combined impacts on air quality and climate and so help in the development of their National Action Plans. Here we will present recent modeling work to support the development of the CCAC National Action Plans toolkit. Adjoint sensitivity analysis is presented as a means of efficiently relating air quality, climate and crop impacts back to changes in emissions from each species, sector and location at the grid-scale resolution of typical global air quality model applications. The GEOS-Chem adjoint model is used to estimate the damages per ton of emissions of PM2.5 related mortality, the impacts of ozone precursors on crops and ozone-related health effects, and the combined impacts of these species on regional surface temperature changes. We show how the benefits-per-emission vary spatially as a function of the surrounding environment, and how this impacts the overall benefit of sector-specific control strategies. We present initial findings for Bangladesh, as well as Mexico, Ghana and Colombia, some of the first countries to join the CCAC, and discuss general issues related to adjoint-based metrics for quantifying air quality and climate co-benefits.

Air quality modeling for the urban Jackson, Mississippi Region using a high resolution WRF/Chem model.

PubMed

Yerramilli, Anjaneyulu; Dodla, Venkata B; Desamsetti, Srinivas; Challa, Srinivas V; Young, John H; Patrick, Chuck; Baham, Julius M; Hughes, Robert L; Yerramilli, Sudha; Tuluri, Francis; Hardy, Mark G; Swanier, Shelton J

2011-06-01

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

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

EPA Science Inventory

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

Vorticity-divergence semi-Lagrangian global atmospheric model SL-AV20: dynamical core

NASA Astrophysics Data System (ADS)

Tolstykh, Mikhail; Shashkin, Vladimir; Fadeev, Rostislav; Goyman, Gordey

2017-05-01

SL-AV (semi-Lagrangian, based on the absolute vorticity equation) is a global hydrostatic atmospheric model. Its latest version, SL-AV20, provides global operational medium-range weather forecast with 20 km resolution over Russia. The lower-resolution configurations of SL-AV20 are being tested for seasonal prediction and climate modeling. The article presents the model dynamical core. Its main features are a vorticity-divergence formulation at the unstaggered grid, high-order finite-difference approximations, semi-Lagrangian semi-implicit discretization and the reduced latitude-longitude grid with variable resolution in latitude. The accuracy of SL-AV20 numerical solutions using a reduced lat-lon grid and the variable resolution in latitude is tested with two idealized test cases. Accuracy and stability of SL-AV20 in the presence of the orography forcing are tested using the mountain-induced Rossby wave test case. The results of all three tests are in good agreement with other published model solutions. It is shown that the use of the reduced grid does not significantly affect the accuracy up to the 25 % reduction in the number of grid points with respect to the regular grid. Variable resolution in latitude allows us to improve the accuracy of a solution in the region of interest.

Description of the F-16XL Geometry and Computational Grids Used in CAWAPI

NASA Technical Reports Server (NTRS)

Boelens, O. J.; Badcock, K. J.; Gortz, S.; Morton, S.; Fritz, W.; Karman, S. L., Jr.; Michal, T.; Lamar, J. E.

2009-01-01

The objective of the Cranked-Arrow Wing Aerodynamics Project International (CAWAPI) was to allow a comprehensive validation of Computational Fluid Dynamics methods against the CAWAP flight database. A major part of this work involved the generation of high-quality computational grids. Prior to the grid generation an IGES file containing the air-tight geometry of the F-16XL aircraft was generated by a cooperation of the CAWAPI partners. Based on this geometry description both structured and unstructured grids have been generated. The baseline structured (multi-block) grid (and a family of derived grids) has been generated by the National Aerospace Laboratory NLR. Although the algorithms used by NLR had become available just before CAWAPI and thus only a limited experience with their application to such a complex configuration had been gained, a grid of good quality was generated well within four weeks. This time compared favourably with that required to produce the unstructured grids in CAWAPI. The baseline all-tetrahedral and hybrid unstructured grids has been generated at NASA Langley Research Center and the USAFA, respectively. To provide more geometrical resolution, trimmed unstructured grids have been generated at EADS-MAS, the UTSimCenter, Boeing Phantom Works and KTH/FOI. All grids generated within the framework of CAWAPI will be discussed in the article. Both results obtained on the structured grids and the unstructured grids showed a significant improvement in agreement with flight test data in comparison with those obtained on the structured multi-block grid used during CAWAP.

A Variable Resolution Atmospheric General Circulation Model for a Megasite at the North Slope of Alaska

NASA Astrophysics Data System (ADS)

Dennis, L.; Roesler, E. L.; Guba, O.; Hillman, B. R.; McChesney, M.

2016-12-01

The Atmospheric Radiation Measurement (ARM) climate research facility has three siteslocated on the North Slope of Alaska (NSA): Barrrow, Oliktok, and Atqasuk. These sites, incombination with one other at Toolik Lake, have the potential to become a "megasite" whichwould combine observational data and high resolution modeling to produce high resolutiondata products for the climate community. Such a data product requires high resolutionmodeling over the area of the megasite. We present three variable resolution atmosphericgeneral circulation model (AGCM) configurations as potential alternatives to stand-alonehigh-resolution regional models. Each configuration is based on a global cubed-sphere gridwith effective resolution of 1 degree, with a refinement in resolution down to 1/8 degree overan area surrounding the ARM megasite. The three grids vary in the size of the refined areawith 13k, 9k, and 7k elements. SquadGen, NCL, and GIMP are used to create the grids.Grids vary based upon the selection of areas of refinement which capture climate andweather processes that may affect a proposed NSA megasite. A smaller area of highresolution may not fully resolve climate and weather processes before they reach the NSA,however grids with smaller areas of refinement have a significantly reduced computationalcost compared with grids with larger areas of refinement. Optimal size and shape of thearea of refinement for a variable resolution model at the NSA is investigated.

Validation of a new SAFRAN-based gridded precipitation product for Spain and comparisons to Spain02 and ERA-Interim

NASA Astrophysics Data System (ADS)

Quintana-Seguí, Pere; Turco, Marco; Herrera, Sixto; Miguez-Macho, Gonzalo

2017-04-01

Offline land surface model (LSM) simulations are useful for studying the continental hydrological cycle. Because of the nonlinearities in the models, the results are very sensitive to the quality of the meteorological forcing; thus, high-quality gridded datasets of screen-level meteorological variables are needed. Precipitation datasets are particularly difficult to produce due to the inherent spatial and temporal heterogeneity of that variable. They do, however, have a large impact on the simulations, and it is thus necessary to carefully evaluate their quality in great detail. This paper reports the quality of two high-resolution precipitation datasets for Spain at the daily time scale: the new SAFRAN-based dataset and Spain02. SAFRAN is a meteorological analysis system that was designed to force LSMs and has recently been extended to the entirety of Spain for a long period of time (1979/1980-2013/2014). Spain02 is a daily precipitation dataset for Spain and was created mainly to validate regional climate models. In addition, ERA-Interim is included in the comparison to show the differences between local high-resolution and global low-resolution products. The study compares the different precipitation analyses with rain gauge data and assesses their temporal and spatial similarities to the observations. The validation of SAFRAN with independent data shows that this is a robust product. SAFRAN and Spain02 have very similar scores, although the latter slightly surpasses the former. The scores are robust with altitude and throughout the year, save perhaps in summer when a diminished skill is observed. As expected, SAFRAN and Spain02 perform better than ERA-Interim, which has difficulty capturing the effects of the relief on precipitation due to its low resolution. However, ERA-Interim reproduces spells remarkably well in contrast to the low skill shown by the high-resolution products. The high-resolution gridded products overestimate the number of precipitation days, which is a problem that affects SAFRAN more than Spain02 and is likely caused by the interpolation method. Both SAFRAN and Spain02 underestimate high precipitation events, but SAFRAN does so more than Spain02. The overestimation of low precipitation events and the underestimation of intense episodes will probably have hydrological consequences once the data are used to force a land surface or hydrological model.

Atmospheric Boundary Layer Modeling for Combined Meteorology and Air Quality Systems

EPA Science Inventory

Atmospheric Eulerian grid models for mesoscale and larger applications require sub-grid models for turbulent vertical exchange processes, particularly within the Planetary Boundary Layer (PSL). In combined meteorology and air quality modeling systems consistent PSL modeling of wi...

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.

The influence of model grid resolution on estimation of national scale nitrogen deposition and exceedance of critical levels

NASA Astrophysics Data System (ADS)

Dore, A. J.; Kryza, M.; Hall, J. R.; Hallsworth, S.; Keller, V. J. D.; Vieno, M.; Sutton, M. A.

2011-12-01

The Fine Resolution Atmospheric Multi-pollutant Exchange model (FRAME) has been applied to model the spatial distribution of nitrogen deposition and air concentration over the UK at a 1 km spatial resolution. The modelled deposition and concentration data were gridded at resolutions of 1 km, 5 km and 50 km to test the sensitivity of calculations of the exceedance of critical loads for nitrogen deposition to the deposition data resolution. The modelled concentrations of NO2 were validated by comparison with measurements from the rural sites in the national monitoring network and were found to achieve better agreement with the high resolution 1 km data. High resolution plots were found to represent a more physically realistic distribution of nitrogen air concentrations and deposition resulting from use of 1 km resolution precipitation and emissions data as compared to 5 km resolution data. Summary statistics for national scale exceedance of the critical load for nitrogen deposition were not highly sensitive to the grid resolution of the deposition data but did show greater area exceedance with coarser grid resolution due to spatial averaging of high nitrogen deposition hot spots. Local scale deposition at individual Sites of Special Scientific Interest and high precipitation upland sites was sensitive to choice of grid resolution of deposition data. Use of high resolution data tended to generate lower deposition values in sink areas for nitrogen dry deposition (Sites of Scientific Interest) and higher values in high precipitation upland areas. In areas with generally low exceedance (Scotland) and for certain vegetation types (montane), the exceedance statistics were more sensitive to model data resolution.

The influence of model grid resolution on estimation of national scale nitrogen deposition and exceedance of critical loads

NASA Astrophysics Data System (ADS)

Dore, A. J.; Kryza, M.; Hall, J. R.; Hallsworth, S.; Keller, V. J. D.; Vieno, M.; Sutton, M. A.

2012-05-01

The Fine Resolution Atmospheric Multi-pollutant Exchange model (FRAME) was applied to model the spatial distribution of reactive nitrogen deposition and air concentration over the United Kingdom at a 1 km spatial resolution. The modelled deposition and concentration data were gridded at resolutions of 1 km, 5 km and 50 km to test the sensitivity of calculations of the exceedance of critical loads for nitrogen deposition to the deposition data resolution. The modelled concentrations of NO2 were validated by comparison with measurements from the rural sites in the national monitoring network and were found to achieve better agreement with the high resolution 1 km data. High resolution plots were found to represent a more physically realistic distribution of reactive nitrogen air concentrations and deposition resulting from use of 1 km resolution precipitation and emissions data as compared to 5 km resolution data. Summary statistics for national scale exceedance of the critical load for nitrogen deposition were not highly sensitive to the grid resolution of the deposition data but did show greater area exceedance with coarser grid resolution due to spatial averaging of high nitrogen deposition hot spots. Local scale deposition at individual Sites of Special Scientific Interest and high precipitation upland sites was sensitive to choice of grid resolution of deposition data. Use of high resolution data tended to generate lower deposition values in sink areas for nitrogen dry deposition (Sites of Scientific Interest) and higher values in high precipitation upland areas. In areas with generally low exceedance (Scotland) and for certain vegetation types (montane), the exceedance statistics were more sensitive to model data resolution.

Responses of future air quality to emission controls over North Carolina, Part I: Model evaluation for current-year simulations

NASA Astrophysics Data System (ADS)

Liu, Xiao-Huan; Zhang, Yang; Olsen, Kristen M.; Wang, Wen-Xing; Do, Bebhinn A.; Bridgers, George M.

2010-07-01

The prediction of future air quality and its responses to emission control strategies at national and state levels requires a reliable model that can replicate atmospheric observations. In this work, the Mesoscale Model (MM5) and the Community Multiscale Air Quality Modeling (CMAQ) system are applied at a 4-km horizontal grid resolution for four one-month periods, i.e., January, June, July, and August in 2002 to evaluate model performance and compare with that at 12-km. The evaluation shows skills of MM5/CMAQ that are overall consistent with current model performance. The large cold bias in temperature at 1.5 m is likely due to too cold soil initial temperatures and inappropriate snow treatments. The large overprediction in precipitation in July is due likely to too frequent afternoon convective rainfall and/or an overestimation in the rainfall intensity. The normalized mean biases and errors are -1.6% to 9.1% and 15.3-18.5% in January and -18.7% to -5.7% and 13.9-20.6% in July for max 1-h and 8-h O 3 mixing ratios, respectively, and those for 24-h average PM 2.5 concentrations are 8.3-25.9% and 27.6-38.5% in January and -57.8% to -45.4% and 46.1-59.3% in July. The large underprediction in PM 2.5 in summer is attributed mainly to overpredicted precipitation, inaccurate emissions, incomplete treatments for secondary organic aerosols, and model difficulties in resolving complex meteorology and geography. While O 3 prediction shows relatively less sensitivity to horizontal grid resolutions, PM 2.5 and its secondary components, visibility indices, and dry and wet deposition show a moderate to high sensitivity. These results have important implications for the regulatory applications of MM5/CMAQ for future air quality attainment.

Bridging the scales in a eulerian air quality model to assess megacity export of pollution

NASA Astrophysics Data System (ADS)

Siour, G.; Colette, A.; Menut, L.; Bessagnet, B.; Coll, I.; Meleux, F.

2013-08-01

In Chemistry Transport Models (CTMs), spatial scale interactions are often represented through off-line coupling between large and small scale models. However, those nested configurations cannot give account of the impact of the local scale on its surroundings. This issue can be critical in areas exposed to air mass recirculation (sea breeze cells) or around regions with sharp pollutant emission gradients (large cities). Such phenomena can still be captured by the mean of adaptive gridding, two-way nesting or using model nudging, but these approaches remain relatively costly. We present here the development and the results of a simple alternative multi-scale approach making use of a horizontal stretched grid, in the Eulerian CTM CHIMERE. This method, called "stretching" or "zooming", consists in the introduction of local zooms in a single chemistry-transport simulation. It allows bridging online the spatial scales from the city (∼1 km resolution) to the continental area (∼50 km resolution). The CHIMERE model was run over a continental European domain, zoomed over the BeNeLux (Belgium, Netherlands and Luxembourg) area. We demonstrate that, compared with one-way nesting, the zooming method allows the expression of a significant feedback of the refined domain towards the large scale: around the city cluster of BeNeLuX, NO2 and O3 scores are improved. NO2 variability around BeNeLux is also better accounted for, and the net primary pollutant flux transported back towards BeNeLux is reduced. Although the results could not be validated for ozone over BeNeLux, we show that the zooming approach provides a simple and immediate way to better represent scale interactions within a CTM, and constitutes a useful tool for apprehending the hot topic of megacities within their continental environment.

High-resolution mapping of vehicle emissions in China in 2008

NASA Astrophysics Data System (ADS)

Zheng, B.; Huo, H.; Zhang, Q.; Yao, Z. L.; Wang, X. T.; Yang, X. F.; Liu, H.; He, K. B.

2014-09-01

This study is the first in a series of papers that aim to develop high-resolution emission databases for different anthropogenic sources in China. Here we focus on on-road transportation. Because of the increasing impact of on-road transportation on regional air quality, developing an accurate and high-resolution vehicle emission inventory is important for both the research community and air quality management. This work proposes a new inventory methodology to improve the spatial and temporal accuracy and resolution of vehicle emissions in China. We calculate, for the first time, the monthly vehicle emissions for 2008 in 2364 counties (an administrative unit one level lower than city) by developing a set of approaches to estimate vehicle stock and monthly emission factors at county-level, and technology distribution at provincial level. We then introduce allocation weights for the vehicle kilometers traveled to assign the county-level emissions onto 0.05° × 0.05° grids based on the China Digital Road-network Map (CDRM). The new methodology overcomes the common shortcomings of previous inventory methods, including neglecting the geographical differences between key parameters and using surrogates that are weakly related to vehicle activities to allocate vehicle emissions. The new method has great advantages over previous methods in depicting the spatial distribution characteristics of vehicle activities and emissions. This work provides a better understanding of the spatial representation of vehicle emissions in China and can benefit both air quality modeling and management with improved spatial accuracy.

Effect of elevation resolution on evapotranspiration simulations using MODFLOW.

PubMed

Kambhammettu, B V N P; Schmid, Wolfgang; King, James P; Creel, Bobby J

2012-01-01

Surface elevations represented in MODFLOW head-dependent packages are usually derived from digital elevation models (DEMs) that are available at much high resolution. Conventional grid refinement techniques to simulate the model at DEM resolution increases computational time, input file size, and in many cases are not feasible for regional applications. This research aims at utilizing the increasingly available high resolution DEMs for effective simulation of evapotranspiration (ET) in MODFLOW as an alternative to grid refinement techniques. The source code of the evapotranspiration package is modified by considering for a fixed MODFLOW grid resolution and for different DEM resolutions, the effect of variability in elevation data on ET estimates. Piezometric head at each DEM cell location is corrected by considering the gradient along row and column directions. Applicability of the research is tested for the lower Rio Grande (LRG) Basin in southern New Mexico. The DEM at 10 m resolution is aggregated to resampled DEM grid resolutions which are integer multiples of MODFLOW grid resolution. Cumulative outflows and ET rates are compared at different coarse resolution grids. Results of the analysis conclude that variability in depth-to-groundwater within the MODFLOW cell is a major contributing parameter to ET outflows in shallow groundwater regions. DEM aggregation methods for the LRG Basin have resulted in decreased volumetric outflow due to the formation of a smoothing error, which lowered the position of water table to a level below the extinction depth. © 2011, The Author(s). Ground Water © 2011, National Ground Water Association.

The Impact of Varying the Physics Grid Resolution Relative to the Dynamical Core Resolution in CAM-SE-CSLAM

NASA Astrophysics Data System (ADS)

Herrington, A. R.; Lauritzen, P. H.; Reed, K. A.

2017-12-01

The spectral element dynamical core of the Community Atmosphere Model (CAM) has recently been coupled to an approximately isotropic, finite-volume grid per implementation of the conservative semi-Lagrangian multi-tracer transport scheme (CAM-SE-CSLAM; Lauritzen et al. 2017). In this framework, the semi-Lagrangian transport of tracers are computed on the finite-volume grid, while the adiabatic dynamics are solved using the spectral element grid. The physical parameterizations are evaluated on the finite-volume grid, as opposed to the unevenly spaced Gauss-Lobatto-Legendre nodes of the spectral element grid. Computing the physics on the finite-volume grid reduces numerical artifacts such as grid imprinting, possibly because the forcing terms are no longer computed at element boundaries where the resolved dynamics are least smooth. The separation of the physics grid and the dynamics grid allows for a unique opportunity to understand the resolution sensitivity in CAM-SE-CSLAM. The observed large sensitivity of CAM to horizontal resolution is a poorly understood impediment to improved simulations of regional climate using global, variable resolution grids. Here, a series of idealized moist simulations are presented in which the finite-volume grid resolution is varied relative to the spectral element grid resolution in CAM-SE-CSLAM. The simulations are carried out at multiple spectral element grid resolutions, in part to provide a companion set of simulations, in which the spectral element grid resolution is varied relative to the finite-volume grid resolution, but more generally to understand if the sensitivity to the finite-volume grid resolution is consistent across a wider spectrum of resolved scales. Results are interpreted in the context of prior ideas regarding resolution sensitivity of global atmospheric models.

Quantifying the impact of sub-grid surface wind variability on sea salt and dust emissions in CAM5

NASA Astrophysics Data System (ADS)

Zhang, Kai; Zhao, Chun; Wan, Hui; Qian, Yun; Easter, Richard C.; Ghan, Steven J.; Sakaguchi, Koichi; Liu, Xiaohong

2016-02-01

This paper evaluates the impact of sub-grid variability of surface wind on sea salt and dust emissions in the Community Atmosphere Model version 5 (CAM5). The basic strategy is to calculate emission fluxes multiple times, using different wind speed samples of a Weibull probability distribution derived from model-predicted grid-box mean quantities. In order to derive the Weibull distribution, the sub-grid standard deviation of surface wind speed is estimated by taking into account four mechanisms: turbulence under neutral and stable conditions, dry convective eddies, moist convective eddies over the ocean, and air motions induced by mesoscale systems and fine-scale topography over land. The contributions of turbulence and dry convective eddy are parameterized using schemes from the literature. Wind variabilities caused by moist convective eddies and fine-scale topography are estimated using empirical relationships derived from an operational weather analysis data set at 15 km resolution. The estimated sub-grid standard deviations of surface wind speed agree well with reference results derived from 1 year of global weather analysis at 15 km resolution and from two regional model simulations with 3 km grid spacing.The wind-distribution-based emission calculations are implemented in CAM5. In terms of computational cost, the increase in total simulation time turns out to be less than 3 %. Simulations at 2° resolution indicate that sub-grid wind variability has relatively small impacts (about 7 % increase) on the global annual mean emission of sea salt aerosols, but considerable influence on the emission of dust. Among the considered mechanisms, dry convective eddies and mesoscale flows associated with topography are major causes of dust emission enhancement. With all the four mechanisms included and without additional adjustment of uncertain parameters in the model, the simulated global and annual mean dust emission increase by about 50 % compared to the default model. By tuning the globally constant dust emission scale factor, the global annual mean dust emission, aerosol optical depth, and top-of-atmosphere radiative fluxes can be adjusted to the level of the default model, but the frequency distribution of dust emission changes, with more contribution from weaker wind events and less contribution from stronger wind events. In Africa and Asia, the overall frequencies of occurrence of dust emissions increase, and the seasonal variations are enhanced, while the geographical patterns of the emission frequency show little change.

Quantifying the impact of sub-grid surface wind variability on sea salt and dust emissions in CAM5

DOE PAGES

Zhang, Kai; Zhao, Chun; Wan, Hui; ...

2016-02-12

This paper evaluates the impact of sub-grid variability of surface wind on sea salt and dust emissions in the Community Atmosphere Model version 5 (CAM5). The basic strategy is to calculate emission fluxes multiple times, using different wind speed samples of a Weibull probability distribution derived from model-predicted grid-box mean quantities. In order to derive the Weibull distribution, the sub-grid standard deviation of surface wind speed is estimated by taking into account four mechanisms: turbulence under neutral and stable conditions, dry convective eddies, moist convective eddies over the ocean, and air motions induced by mesoscale systems and fine-scale topography overmore » land. The contributions of turbulence and dry convective eddy are parameterized using schemes from the literature. Wind variabilities caused by moist convective eddies and fine-scale topography are estimated using empirical relationships derived from an operational weather analysis data set at 15 km resolution. The estimated sub-grid standard deviations of surface wind speed agree well with reference results derived from 1 year of global weather analysis at 15 km resolution and from two regional model simulations with 3 km grid spacing.The wind-distribution-based emission calculations are implemented in CAM5. In terms of computational cost, the increase in total simulation time turns out to be less than 3 %. Simulations at 2° resolution indicate that sub-grid wind variability has relatively small impacts (about 7 % increase) on the global annual mean emission of sea salt aerosols, but considerable influence on the emission of dust. Among the considered mechanisms, dry convective eddies and mesoscale flows associated with topography are major causes of dust emission enhancement. With all the four mechanisms included and without additional adjustment of uncertain parameters in the model, the simulated global and annual mean dust emission increase by about 50 % compared to the default model. By tuning the globally constant dust emission scale factor, the global annual mean dust emission, aerosol optical depth, and top-of-atmosphere radiative fluxes can be adjusted to the level of the default model, but the frequency distribution of dust emission changes, with more contribution from weaker wind events and less contribution from stronger wind events. Lastly, in Africa and Asia, the overall frequencies of occurrence of dust emissions increase, and the seasonal variations are enhanced, while the geographical patterns of the emission frequency show little change.« less

Quantifying the impact of sub-grid surface wind variability on sea salt and dust emissions in CAM5

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

Zhang, Kai; Zhao, Chun; Wan, Hui

This paper evaluates the impact of sub-grid variability of surface wind on sea salt and dust emissions in the Community Atmosphere Model version 5 (CAM5). The basic strategy is to calculate emission fluxes multiple times, using different wind speed samples of a Weibull probability distribution derived from model-predicted grid-box mean quantities. In order to derive the Weibull distribution, the sub-grid standard deviation of surface wind speed is estimated by taking into account four mechanisms: turbulence under neutral and stable conditions, dry convective eddies, moist convective eddies over the ocean, and air motions induced by mesoscale systems and fine-scale topography overmore » land. The contributions of turbulence and dry convective eddy are parameterized using schemes from the literature. Wind variabilities caused by moist convective eddies and fine-scale topography are estimated using empirical relationships derived from an operational weather analysis data set at 15 km resolution. The estimated sub-grid standard deviations of surface wind speed agree well with reference results derived from 1 year of global weather analysis at 15 km resolution and from two regional model simulations with 3 km grid spacing.The wind-distribution-based emission calculations are implemented in CAM5. In terms of computational cost, the increase in total simulation time turns out to be less than 3 %. Simulations at 2° resolution indicate that sub-grid wind variability has relatively small impacts (about 7 % increase) on the global annual mean emission of sea salt aerosols, but considerable influence on the emission of dust. Among the considered mechanisms, dry convective eddies and mesoscale flows associated with topography are major causes of dust emission enhancement. With all the four mechanisms included and without additional adjustment of uncertain parameters in the model, the simulated global and annual mean dust emission increase by about 50 % compared to the default model. By tuning the globally constant dust emission scale factor, the global annual mean dust emission, aerosol optical depth, and top-of-atmosphere radiative fluxes can be adjusted to the level of the default model, but the frequency distribution of dust emission changes, with more contribution from weaker wind events and less contribution from stronger wind events. Lastly, in Africa and Asia, the overall frequencies of occurrence of dust emissions increase, and the seasonal variations are enhanced, while the geographical patterns of the emission frequency show little change.« less

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

PubMed Central

Yerramilli, Anjaneyulu; Dodla, Venkata B.; Desamsetti, Srinivas; Challa, Srinivas V.; Young, John H.; Patrick, Chuck; Baham, Julius M.; Hughes, Robert L.; Yerramilli, Sudha; Tuluri, Francis; Hardy, Mark G.; Swanier, Shelton J.

2011-01-01

In this study, an attempt was made to simulate the air quality with reference to ozone over the Jackson (Mississippi) region using an online WRF/Chem (Weather Research and Forecasting–Chemistry) model. The WRF/Chem model has the advantages of the integration of the meteorological and chemistry modules with the same computational grid and same physical parameterizations and includes the feedback between the atmospheric chemistry and physical processes. The model was designed to have three nested domains with the inner-most domain covering the study region with a resolution of 1 km. The model was integrated for 48 hours continuously starting from 0000 UTC of 6 June 2006 and the evolution of surface ozone and other precursor pollutants were analyzed. The model simulated atmospheric flow fields and distributions of NO2 and O3 were evaluated for each of the three different time periods. The GIS based spatial distribution maps for ozone, its precursors NO, NO2, CO and HONO and the back trajectories indicate that all the mobile sources in Jackson, Ridgeland and Madison contributing significantly for their formation. The present study demonstrates the applicability of WRF/Chem model to generate quantitative information at high spatial and temporal resolution for the development of decision support systems for air quality regulatory agencies and health administrators. PMID:21776240

A Structured-Grid Quality Measure for Simulated Hypersonic Flows

NASA Technical Reports Server (NTRS)

Alter, Stephen J.

2004-01-01

A structured-grid quality measure is proposed, combining three traditional measurements: intersection angles, stretching, and curvature. Quality assesses whether the grid generated provides the best possible tradeoffs in grid stretching and skewness that enable accurate flow predictions, whereas the grid density is assumed to be a constraint imposed by the available computational resources and the desired resolution of the flow field. The usefulness of this quality measure is assessed by comparing heat transfer predictions from grid convergence studies for grids of varying quality in the range of [0.6-0.8] on an 8'half-angle sphere-cone, at laminar, perfect gas, Mach 10 wind tunnel conditions.

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

EPA Science Inventory

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

Satellite-aided evaluation of population exposure to air pollution

USGS Publications Warehouse

Todd, William J.; George, Anthony J.; Bryant, Nevin A.

1979-01-01

The Clean Air Act Amendments of 1977 set schedules for states to implement regional, spatial assessments of air quality impacts. Accordingly, the U.S. Environmental Protection Agency recently published guidelines for quantifying population exposure to adverse air quality impact by using air quality and population data by census tracts. Our research complements the EPA guidelines in that it demonstrates the ability to determine population exposure to air pollution through computer processing that utilizes Landsat satellite-derived land use information. Three variables-a 1985 estimate of total suspended particulates for 2-km2 grid cells, Landsat-derived residential land cover data for 0.45-ha cells, and population totals for census tracts-were spatially registered and cross-tabulated to produce tabular and map products illustrating relative air quality exposure for residential population by 2-km2 cells. It would cost $20,000 to replicate our analysis for an area similar in size to the 4000-km2 Portland area. Once completed, the spatially fine, computer-compatible air quality and population data are amenable to the timely and efficient generation of population-at-risk tabular and map information on a continuous or periodic basis.

Constraints on the Profiles of Total Water PDF in AGCMs from AIRS and a High-Resolution Model

NASA Technical Reports Server (NTRS)

Molod, Andrea

2012-01-01

Atmospheric general circulation model (AGCM) cloud parameterizations generally include an assumption about the subgrid-scale probability distribution function (PDF) of total water and its vertical profile. In the present study, the Atmospheric Infrared Sounder (AIRS) monthly-mean cloud amount and relative humidity fields are used to compute a proxy for the second moment of an AGCM total water PDF called the RH01 diagnostic, which is the AIRS mean relative humidity for cloud fractions of 0.1 or less. The dependence of the second moment on horizontal grid resolution is analyzed using results from a high-resolution global model simulation.The AIRS-derived RH01 diagnostic is generally larger near the surface than aloft, indicating a narrower PDF near the surface, and varies with the type of underlying surface. High-resolution model results show that the vertical structure of profiles of the AGCM PDF second moment is unchanged as the grid resolution changes from 200 to 100 to 50 km, and that the second-moment profiles shift toward higher values with decreasing grid spacing.Several Goddard Earth Observing System, version 5 (GEOS-5), AGCM simulations were performed with several choices for the profile of the PDF second moment. The resulting cloud and relative humidity fields were shown to be quite sensitive to the prescribed profile, and the use of a profile based on the AIRS-derived proxy results in improvements relative to observational estimates. The AIRS-guided total water PDF profiles, including their dependence on underlying surface type and on horizontal resolution, have been implemented in the version of the GEOS-5 AGCM used for publicly released simulations.

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

NASA Astrophysics Data System (ADS)

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

2013-02-01

Comprehensive model evaluation and comparison of two 3-D air quality modeling systems (i.e. the Weather Research and Forecast model (WRF)/Polyphemus and WRF with chemistry and the Model of Aerosol Dynamics, Reaction, Ionization, and Dissolution (MADRID) (WRF/Chem-MADRID) are conducted over western Europe. Part 1 describes the background information for the model comparison and simulation design, as well as the application of WRF for January and July 2001 over triple-nested domains in western Europe at three horizontal grid resolutions: 0.5°, 0.125°, and 0.025°. Six simulated meteorological variables (i.e. temperature at 2 m (T2), specific humidity at 2 m (Q2), relative humidity at 2 m (RH2), wind speed at 10 m (WS10), wind direction at 10 m (WD10), and precipitation (Precip)) are evaluated using available observations in terms of spatial distribution, domainwide daily and site-specific hourly variations, and domainwide performance statistics. WRF demonstrates its capability in capturing diurnal/seasonal variations and spatial gradients of major meteorological variables. While the domainwide performance of T2, Q2, RH2, and WD10 at all three grid resolutions is satisfactory overall, large positive or negative biases occur in WS10 and Precip even at 0.025°. In addition, discrepancies between simulations and observations exist in T2, Q2, WS10, and Precip at mountain/high altitude sites and large urban center sites in both months, in particular, during snow events or thunderstorms. These results indicate the model's difficulty in capturing meteorological variables in complex terrain and subgrid-scale meteorological phenomena, due to inaccuracies in model initialization parameterization (e.g. lack of soil temperature and moisture nudging), limitations in the physical parameterizations of the planetary boundary layer (e.g. cloud microphysics, cumulus parameterizations, and ice nucleation treatments) as well as limitations in surface heat and moisture budget parameterizations (e.g. snow-related processes, subgrid-scale surface roughness elements, and urban canopy/heat island treatments and CO2 domes). While the use of finer grid resolutions of 0.125° and 0.025° shows some improvement for WS10, Precip, and some mesoscale events (e.g. strong forced convection and heavy precipitation), it does not significantly improve the overall statistical performance for all meteorological variables except for Precip. These results indicate a need to further improve the model representations of the above parameterizations at all scales.

High-quality weather data for grid integration studies

NASA Astrophysics Data System (ADS)

Draxl, C.

2016-12-01

As variable renewable power penetration levels increase in power systems worldwide, renewable integration studies are crucial to ensure continued economic and reliable operation of the power grid. In this talk we will shed light on requirements for grid integration studies as far as wind and solar energy are concerned. Because wind and solar plants are strongly impacted by weather, high-resolution and high-quality weather data are required to drive power system simulations. Future data sets will have to push limits of numerical weather prediction to yield these high-resolution data sets, and wind data will have to be time-synchronized with solar data. Current wind and solar integration data sets will be presented. The Wind Integration National Dataset (WIND) Toolkit is the largest and most complete grid integration data set publicly available to date. A meteorological data set, wind power production time series, and simulated forecasts created using the Weather Research and Forecasting Model run on a 2-km grid over the continental United States at a 5-min resolution is now publicly available for more than 126,000 land-based and offshore wind power production sites. The Solar Integration National Dataset (SIND) is available as time synchronized with the WIND Toolkit, and will allow for combined wind-solar grid integration studies. The National Solar Radiation Database (NSRDB) is a similar high temporal- and spatial resolution database of 18 years of solar resource data for North America and India. Grid integration studies are also carried out in various countries, which aim at increasing their wind and solar penetration through combined wind and solar integration data sets. We will present a multi-year effort to directly support India's 24x7 energy access goal through a suite of activities aimed at enabling large-scale deployment of clean energy and energy efficiency. Another current effort is the North-American-Renewable-Integration-Study, with the aim of providing a seamless data set across borders for a whole continent, to simulate and analyze the impacts of potential future large wind and solar power penetrations on bulk power system operations.

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.

A deep learning-based reconstruction of cosmic ray-induced air showers

NASA Astrophysics Data System (ADS)

Erdmann, M.; Glombitza, J.; Walz, D.

2018-01-01

We describe a method of reconstructing air showers induced by cosmic rays using deep learning techniques. We simulate an observatory consisting of ground-based particle detectors with fixed locations on a regular grid. The detector's responses to traversing shower particles are signal amplitudes as a function of time, which provide information on transverse and longitudinal shower properties. In order to take advantage of convolutional network techniques specialized in local pattern recognition, we convert all information to the image-like grid of the detectors. In this way, multiple features, such as arrival times of the first particles and optimized characterizations of time traces, are processed by the network. The reconstruction quality of the cosmic ray arrival direction turns out to be competitive with an analytic reconstruction algorithm. The reconstructed shower direction, energy and shower depth show the expected improvement in resolution for higher cosmic ray energy.

High-resolution daily gridded data sets of air temperature and wind speed for Europe

NASA Astrophysics Data System (ADS)

Brinckmann, Sven; Krähenmann, Stefan; Bissolli, Peter

2016-10-01

New high-resolution data sets for near-surface daily air temperature (minimum, maximum and mean) and daily mean wind speed for Europe (the CORDEX domain) are provided for the period 2001-2010 for the purpose of regional model validation in the framework of DecReg, a sub-project of the German MiKlip project, which aims to develop decadal climate predictions. The main input data sources are SYNOP observations, partly supplemented by station data from the ECA&D data set (http://www.ecad.eu). These data are quality tested to eliminate erroneous data. By spatial interpolation of these station observations, grid data in a resolution of 0.044° (≈ 5km) on a rotated grid with virtual North Pole at 39.25° N, 162° W are derived. For temperature interpolation a modified version of a regression kriging method developed by Krähenmann et al.(2011) is used. At first, predictor fields of altitude, continentality and zonal mean temperature are used for a regression applied to monthly station data. The residuals of the monthly regression and the deviations of the daily data from the monthly averages are interpolated using simple kriging in a second and third step. For wind speed a new method based on the concept used for temperature was developed, involving predictor fields of exposure, roughness length, coastal distance and ERA-Interim reanalysis wind speed at 850 hPa. Interpolation uncertainty is estimated by means of the kriging variance and regression uncertainties. Furthermore, to assess the quality of the final daily grid data, cross validation is performed. Variance explained by the regression ranges from 70 to 90 % for monthly temperature and from 50 to 60 % for monthly wind speed. The resulting RMSE for the final daily grid data amounts to 1-2 K and 1-1.5 ms-1 (depending on season and parameter) for daily temperature parameters and daily mean wind speed, respectively. The data sets presented in this article are published at doi:10.5676/DWD_CDC/DECREG0110v2.

Summarising climate and air quality (ozone) data on self-organising maps: a Sydney case study.

PubMed

Jiang, Ningbo; Betts, Alan; Riley, Matt

2016-02-01

This paper explores the classification and visualisation utility of the self-organising map (SOM) method in the context of New South Wales (NSW), Australia, using gridded NCEP/NCAR geopotential height reanalysis for east Australia, together with multi-site meteorological and air quality data for Sydney from the NSW Office of Environment and Heritage Air Quality Monitoring Network. A twice-daily synoptic classification has been derived for east Australia for the period of 1958-2012. The classification has not only reproduced the typical synoptic patterns previously identified in the literature but also provided an opportunity to visualise the subtle, non-linear change in the eastward-migrating synoptic systems influencing NSW (including Sydney). The summarisation of long-term, multi-site air quality/meteorological data from the Sydney basin on the SOM plane has identified a set of typical air pollution/meteorological spatial patterns in the region. Importantly, the examination of these patterns in relation to synoptic weather types has provided important visual insights into how local and synoptic meteorological conditions interact with each other and affect the variability of air quality in tandem. The study illustrates that while synoptic circulation types are influential, the within-type variability in mesoscale flows plays a critical role in determining local ozone levels in Sydney. These results indicate that the SOM can be a useful tool for assessing the impact of weather and climatic conditions on air quality in the regional airshed. This study further promotes the use of the SOM method in environmental research.

THE EMERGENCE OF NUMERICAL AIR QUALITY FORECASTING MODELS AND THEIR APPLICATION

EPA Science Inventory

In recent years the U.S. and other nations have begun programs for short-term local through regional air quality forecasting based upon numerical three-dimensional air quality grid models. These numerical air quality forecast (NAQF) models and systems have been developed and test...

THE EMERGENCE OF NUMERICAL AIR QUALITY FORCASTING MODELS AND THEIR APPLICATIONS

EPA Science Inventory

In recent years the U.S. and other nations have begun programs for short-term local through regional air quality forecasting based upon numerical three-dimensional air quality grid models. These numerical air quality forecast (NAQF) models and systems have been developed and test...

High-resolution mobile monitoring of carbon monoxide and ultrafine particle concentrations in a near-road environment

EPA Science Inventory

Assessment of near-road air quality is challenging in urban environments which have roadside structures or elevated or cut road sections that may impact the dispersion of emissions. Emissions from vehicles operating on arterial roads also contribute to air pollution variability i...

A new vehicle emission inventory for China with high spatial and temporal resolution

NASA Astrophysics Data System (ADS)

Zheng, B.; Huo, H.; Zhang, Q.; Yao, Z. L.; Wang, X. T.; Yang, X. F.; Liu, H.; He, K. B.

2013-12-01

This study is the first in a series of papers that aim to develop high-resolution emission databases for different anthropogenic sources in China. Here we focus on on-road transportation. Because of the increasing impact of on-road transportation on regional air quality, developing an accurate and high-resolution vehicle emission inventory is important for both the research community and air quality management. This work proposes a new inventory methodology to improve the spatial and temporal accuracy and resolution of vehicle emissions in China. We calculate, for the first time, the monthly vehicle emissions (CO, NMHC, NOx, and PM2.5) for 2008 in 2364 counties (an administrative unit one level lower than city) by developing a set of approaches to estimate vehicle stock and monthly emission factors at county-level, and technology distribution at provincial level. We then introduce allocation weights for the vehicle kilometers traveled to assign the county-level emissions onto 0.05° × 0.05° grids based on the China Digital Road-network Map (CDRM). The new methodology overcomes the common shortcomings of previous inventory methods, including neglecting the geographical differences between key parameters and using surrogates that are weakly related to vehicle activities to allocate vehicle emissions. The new method has great advantages over previous methods in depicting the spatial distribution characteristics of vehicle activities and emissions. This work provides a better understanding of the spatial representation of vehicle emissions in China and can benefit both air quality modeling and management with improved spatial accuracy.

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.

Particulate Matter and Ozone Prediction and Source Attribution for U.S. Air Quality Management in a Changing World

NASA Astrophysics Data System (ADS)

Sanyal, S.; Wuebbles, D. J.

2017-12-01

In this study, the focus is on how global changes in climate and emissions will affect the U.S. air quality, especially on fine particulate matter and ozone, projecting their future trends and quantifying key source attribution. We are conducting three primary experiments : (1) historical simulations for period 1994-2013 to establish the credibility of the system and refine process-level understanding of U.S. regional air quality; (2) projections for period 2041-2060 to quantify individual and combined impacts of global climate and emissions changes under multiple scenarios; (3) sensitivity analyses to determine future changes in pollution sources and their relative contributions from anthropogenic and natural emissions, long-range pollutant transport, and climate change effects. Here we will present the result from the first experiment with the global model CESM1.2 (with fully coupled chemistry using CAM-chem5) driven by NASA Modern-Era Retrospective analysis for Research and Applications (MERRA) reanalysis data at 0.9o x 1.25o resolution. We will present the comparison between the results from model simulation with observation data from EPA database. Since there is always a challenge in comparing gridded prediction from model data with point data from the observation databases, because the model simulations calculate the average outcome over a grid for a given set of conditions while the stochastic component (e.g. sub-grid variations) embedded in the observations are not accounted for, we are using extensive statistical measure to do the comparison. We will also determine relative contributions from multiscale (local, regional, global) processes, major source regions (Mexico, Canada, Asia, Africa) and types (natural, anthropogenic) and associated uncertainties (climate decadal oscillations/interannual variations, emissions and model structure errors).

Airborne High Spectral Resolution Lidar Aerosol Measurements during MILAGRO and TEXAQS/GOMACCS

NASA Technical Reports Server (NTRS)

Ferrare, Richard; Hostetler, Chris; Hair, John; Cook Anthony; Harper, David; Burton, Sharon; Clayton, Marian; Clarke, Antony; Russell, Phil; Redemann, Jens

2007-01-01

Two1 field experiments conducted during 2006 provided opportunities to investigate the variability of aerosol properties near cities and the impacts of these aerosols on air quality and radiative transfer. The Megacity Initiative: Local and Global Research Observations (MILAGRO) /Megacity Aerosol Experiment in Mexico City (MAX-MEX)/Intercontinental Chemical Transport Experiment-B (INTEX-B) joint experiment conducted during March 2006 investigated the evolution and transport of pollution from Mexico City. The Texas Air Quality Study (TEXAQS)/Gulf of Mexico Atmospheric Composition and Climate Study (GoMACCS) (http://www.al.noaa.gov/2006/) conducted during August and September 2006 investigated climate and air quality in the Houston/Gulf of Mexico region. During both missions, the new NASA Langley airborne High Spectral Resolution Lidar (HSRL) was deployed on the NASA Langley B200 King Air aircraft and measured profiles of aerosol extinction, backscattering, and depolarization to: 1) characterize the spatial and vertical distributions of aerosols, 2) quantify aerosol extinction and optical thickness contributed by various aerosol types, 3) investigate aerosol variability near clouds, 4) evaluate model simulations of aerosol transport, and 5) assess aerosol optical properties derived from a combination of surface, airborne, and satellite measurements.

Final Report: Closeout of the Award NO. DE-FG02-98ER62618 (M.S. Fox-Rabinovitz, P.I.)

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

Fox-Rabinovitz, M. S.

The final report describes the study aimed at exploring the variable-resolution stretched-grid (SG) approach to decadal regional climate modeling using advanced numerical techniques. The obtained results have shown that variable-resolution SG-GCMs using stretched grids with fine resolution over the area(s) of interest, is a viable established approach to regional climate modeling. The developed SG-GCMs have been extensively used for regional climate experimentation. The SG-GCM simulations are aimed at studying the U.S. regional climate variability with an emphasis on studying anomalous summer climate events, the U.S. droughts and floods.

Synoptic scale wind field properties from the SEASAT SASS

NASA Technical Reports Server (NTRS)

Pierson, W. J., Jr.; Sylvester, W. B.; Salfi, R. E.

1984-01-01

Dealiased SEASAT SEASAT A Scatterometer System SASS vector winds obtained during the Gulf Of Alaska SEASAT Experiment GOASEX program are processed to obtain superobservations centered on a one degree by one degree grid. The grid. The results provide values for the combined effects of mesoscale variability and communication noise on the individual SASS winds. These superobservations winds are then processed further to obtain estimates of synoptic scale vector winds stress fields, the horizontal divergence of the wind, the curl of the wind stress and the vertical velocity at 200 m above the sea surface, each with appropriate standard deviations of the estimates for each grid point value. They also explain the concentration of water vapor, liquid water and precipitation found by means of the SMMR Scanning Multichannel Microwave Radiometer at fronts and occlusions in terms of strong warm, moist air advection in the warm air sector accompanied by convergence in the friction layer. Their quality is far superior to that of analyses based on conventional data, which are shown to yield many inconsistencies.

Comparison of CMAQ Modeling Study with Discover-AQ 2014 Aircraft Measurements over Colorado

NASA Astrophysics Data System (ADS)

Tang, Y.; Pan, L.; Lee, P.; Tong, D.; Kim, H. C.; Artz, R. S.

2014-12-01

NASA and NCAR jointly led a recent multiple platform-based (space, air and ground) measurement intensive to study air quality and to validate satellite data. The Discover-AQ/FRAPPE field experiment took place along the Colorado Front Range in July and August, 2014. The air quality modeling team of the NOAA Air Resources Laboratory was one of the three teams that provided real-time air quality forecasting for the campaign. The U.S. EPA Community Multi-scale Air Quality (CMAQ) Model was used with emission inventories based on the data set used by the NOAA National Air Quality Forecasting Capacity (NAQFC). By analyzing the forecast results calculated using aircraft measurements, it was found that CO emissions tended to be overestimated, while ethane emissions were underestimated. Biogenic VOCs were also underpredicted. Due to their relatively high altitude, ozone concentrations in Denver and the surrounding areas are affected by both local emissions and transported ozone. The modeled ozone was highly dependent on the meteorological predictions over this region. The complex terrain over the Rocky Mountains also contributed to the model uncertainty. This study discussed the causes of model biases, the forecast performance under different meteorology, and results from using different model grid resolutions. Several data assimilation techniques were further tested to improve the "post-analysis" performance of the modeling system for the period.

Regional Climate Simulation with a Variable Resolution Stretched Grid GCM: The Regional Down-Scaling Effects

NASA Technical Reports Server (NTRS)

Fox-Rabinovitz, Michael S.; Takacs, Lawrence L.; Suarez, Max; Sawyer, William; Govindaraju, Ravi C.

1999-01-01

The results obtained with the variable resolution stretched grid (SG) GEOS GCM (Goddard Earth Observing System General Circulation Models) are discussed, with the emphasis on the regional down-scaling effects and their dependence on the stretched grid design and parameters. A variable resolution SG-GCM and SG-DAS using a global stretched grid with fine resolution over an area of interest, is a viable new approach to REGIONAL and subregional CLIMATE studies and applications. The stretched grid approach is an ideal tool for representing regional to global scale interactions. It is an alternative to the widely used nested grid approach introduced a decade ago as a pioneering step in regional climate modeling. The GEOS SG-GCM is used for simulations of the anomalous U.S. climate events of 1988 drought and 1993 flood, with enhanced regional resolution. The height low level jet, precipitation and other diagnostic patterns are successfully simulated and show the efficient down-scaling over the area of interest the U.S. An imitation of the nested grid approach is performed using the developed SG-DAS (Data Assimilation System) that incorporates the SG-GCM. The SG-DAS is run with withholding data over the area of interest. The design immitates the nested grid framework with boundary conditions provided from analyses. No boundary condition buffer is needed for the case due to the global domain of integration used for the SG-GCM and SG-DAS. The experiments based on the newly developed versions of the GEOS SG-GCM and SG-DAS, with finer 0.5 degree (and higher) regional resolution, are briefly discussed. The major aspects of parallelization of the SG-GCM code are outlined. The KEY OBJECTIVES of the study are: 1) obtaining an efficient DOWN-SCALING over the area of interest with fine and very fine resolution; 2) providing CONSISTENT interactions between regional and global scales including the consistent representation of regional ENERGY and WATER BALANCES; 3) providing a high computational efficiency for future SG-GCM and SG-DAS versions using PARALLEL codes.

DEM Based Modeling: Grid or TIN? The Answer Depends

NASA Astrophysics Data System (ADS)

Ogden, F. L.; Moreno, H. A.

2015-12-01

The availability of petascale supercomputing power has enabled process-based hydrological simulations on large watersheds and two-way coupling with mesoscale atmospheric models. Of course with increasing watershed scale come corresponding increases in watershed complexity, including wide ranging water management infrastructure and objectives, and ever increasing demands for forcing data. Simulations of large watersheds using grid-based models apply a fixed resolution over the entire watershed. In large watersheds, this means an enormous number of grids, or coarsening of the grid resolution to reduce memory requirements. One alternative to grid-based methods is the triangular irregular network (TIN) approach. TINs provide the flexibility of variable resolution, which allows optimization of computational resources by providing high resolution where necessary and low resolution elsewhere. TINs also increase required effort in model setup, parameter estimation, and coupling with forcing data which are often gridded. This presentation discusses the costs and benefits of the use of TINs compared to grid-based methods, in the context of large watershed simulations within the traditional gridded WRF-HYDRO framework and the new TIN-based ADHydro high performance computing watershed simulator.

Use of High Resolution Mobile Monitoring Techniques to Assess Near Road Air Quality Variability

EPA Science Inventory

This presentation provides a description of the techniques used to develop and conduct effective mobile monitoring studies. It also provides a summary of mobile monitoring assessment studies that have been used to assess near-road concentrations and the variability of pollutant l...

Use of High Resolution Mobile Monitoring Techniques to Assess Near-Road Air Quality Variability

EPA Science Inventory

This presentation provides a description of the techniques used to develop and conduct effective mobile monitoring studies. It also provides a summary of mobile monitoring assessment studies that have been used to assess near-road concentrations and the variability of pollutant l...

JIGSAW-GEO (1.0): Locally Orthogonal Staggered Unstructured Grid Generation for General Circulation Modelling on the Sphere

NASA Technical Reports Server (NTRS)

Engwirda, Darren

2017-01-01

An algorithm for the generation of non-uniform, locally orthogonal staggered unstructured spheroidal grids is described. This technique is designed to generate very high-quality staggered VoronoiDelaunay meshes appropriate for general circulation modelling on the sphere, including applications to atmospheric simulation, ocean-modelling and numerical weather prediction. Using a recently developed Frontal-Delaunay refinement technique, a method for the construction of high-quality unstructured spheroidal Delaunay triangulations is introduced. A locally orthogonal polygonal grid, derived from the associated Voronoi diagram, is computed as the staggered dual. It is shown that use of the Frontal-Delaunay refinement technique allows for the generation of very high-quality unstructured triangulations, satisfying a priori bounds on element size and shape. Grid quality is further improved through the application of hill-climbing-type optimisation techniques. Overall, the algorithm is shown to produce grids with very high element quality and smooth grading characteristics, while imposing relatively low computational expense. A selection of uniform and non-uniform spheroidal grids appropriate for high-resolution, multi-scale general circulation modelling are presented. These grids are shown to satisfy the geometric constraints associated with contemporary unstructured C-grid-type finite-volume models, including the Model for Prediction Across Scales (MPAS-O). The use of user-defined mesh-spacing functions to generate smoothly graded, non-uniform grids for multi-resolution-type studies is discussed in detail.

JIGSAW-GEO (1.0): locally orthogonal staggered unstructured grid generation for general circulation modelling on the sphere

NASA Astrophysics Data System (ADS)

Engwirda, Darren

2017-06-01

An algorithm for the generation of non-uniform, locally orthogonal staggered unstructured spheroidal grids is described. This technique is designed to generate very high-quality staggered Voronoi-Delaunay meshes appropriate for general circulation modelling on the sphere, including applications to atmospheric simulation, ocean-modelling and numerical weather prediction. Using a recently developed Frontal-Delaunay refinement technique, a method for the construction of high-quality unstructured spheroidal Delaunay triangulations is introduced. A locally orthogonal polygonal grid, derived from the associated Voronoi diagram, is computed as the staggered dual. It is shown that use of the Frontal-Delaunay refinement technique allows for the generation of very high-quality unstructured triangulations, satisfying a priori bounds on element size and shape. Grid quality is further improved through the application of hill-climbing-type optimisation techniques. Overall, the algorithm is shown to produce grids with very high element quality and smooth grading characteristics, while imposing relatively low computational expense. A selection of uniform and non-uniform spheroidal grids appropriate for high-resolution, multi-scale general circulation modelling are presented. These grids are shown to satisfy the geometric constraints associated with contemporary unstructured C-grid-type finite-volume models, including the Model for Prediction Across Scales (MPAS-O). The use of user-defined mesh-spacing functions to generate smoothly graded, non-uniform grids for multi-resolution-type studies is discussed in detail.

High-resolution integration of water, energy, and climate models to assess electricity grid vulnerabilities to climate change

NASA Astrophysics Data System (ADS)

Meng, M.; Macknick, J.; Tidwell, V. C.; Zagona, E. A.; Magee, T. M.; Bennett, K.; Middleton, R. S.

2017-12-01

The U.S. electricity sector depends on large amounts of water for hydropower generation and cooling thermoelectric power plants. Variability in water quantity and temperature due to climate change could reduce the performance and reliability of individual power plants and of the electric grid as a system. While studies have modeled water usage in power systems planning, few have linked grid operations with physical water constraints or with climate-induced changes in water resources to capture the role of the energy-water nexus in power systems flexibility and adequacy. In addition, many hydrologic and hydropower models have a limited representation of power sector water demands and grid interaction opportunities of demand response and ancillary services. A multi-model framework was developed to integrate and harmonize electricity, water, and climate models, allowing for high-resolution simulation of the spatial, temporal, and physical dynamics of these interacting systems. The San Juan River basin in the Southwestern U.S., which contains thermoelectric power plants, hydropower facilities, and multiple non-energy water demands, was chosen as a case study. Downscaled data from three global climate models and predicted regional water demand changes were implemented in the simulations. The Variable Infiltration Capacity hydrologic model was used to project inflows, ambient air temperature, and humidity in the San Juan River Basin. Resulting river operations, water deliveries, water shortage sharing agreements, new water demands, and hydroelectricity generation at the basin-scale were estimated with RiverWare. The impacts of water availability and temperature on electric grid dispatch, curtailment, cooling water usage, and electricity generation cost were modeled in PLEXOS. Lack of water availability resulting from climate, new water demands, and shortage sharing agreements will require thermoelectric generators to drastically decrease power production, as much as 50% during intensifying drought scenarios, which can have broader electricity sector system implications. Results relevant to stakeholder and power provider interests highlight the vulnerabilities in grid operations driven by water shortage agreements and changes in the climate.

Accurate finite difference methods for time-harmonic wave propagation

NASA Technical Reports Server (NTRS)

Harari, Isaac; Turkel, Eli

1994-01-01

Finite difference methods for solving problems of time-harmonic acoustics are developed and analyzed. Multidimensional inhomogeneous problems with variable, possibly discontinuous, coefficients are considered, accounting for the effects of employing nonuniform grids. A weighted-average representation is less sensitive to transition in wave resolution (due to variable wave numbers or nonuniform grids) than the standard pointwise representation. Further enhancement in method performance is obtained by basing the stencils on generalizations of Pade approximation, or generalized definitions of the derivative, reducing spurious dispersion, anisotropy and reflection, and by improving the representation of source terms. The resulting schemes have fourth-order accurate local truncation error on uniform grids and third order in the nonuniform case. Guidelines for discretization pertaining to grid orientation and resolution are presented.

Horizontal Residual Mean Circulation: Evaluation of Spatial Correlations in Coarse Resolution Ocean Models

NASA Astrophysics Data System (ADS)

Li, Y.; McDougall, T. J.

2016-02-01

Coarse resolution ocean models lack knowledge of spatial correlations between variables on scales smaller than the grid scale. Some researchers have shown that these spatial correlations play a role in the poleward heat flux. In order to evaluate the poleward transport induced by the spatial correlations at a fixed horizontal position, an equation is obtained to calculate the approximate transport from velocity gradients. The equation involves two terms that can be added to the quasi-Stokes streamfunction (based on temporal correlations) to incorporate the contribution of spatial correlations. Moreover, these new terms do not need to be parameterized and is ready to be evaluated by using model data directly. In this study, data from a high resolution ocean model have been used to estimate the accuracy of this HRM approach for improving the horizontal property fluxes in coarse-resolution ocean models. A coarse grid is formed by sub-sampling and box-car averaging the fine grid scale. The transport calculated on the coarse grid is then compared to the transport on original high resolution grid scale accumulated over a corresponding number of grid boxes. The preliminary results have shown that the estimate on coarse resolution grids roughly match the corresponding transports on high resolution grids.

Global Multi-Resolution Topography (GMRT) Synthesis - Recent Updates and Developments

NASA Astrophysics Data System (ADS)

Ferrini, V. L.; Morton, J. J.; Celnick, M.; McLain, K.; Nitsche, F. O.; Carbotte, S. M.; O'hara, S. H.

2017-12-01

The Global Multi-Resolution Topography (GMRT, http://gmrt.marine-geo.org) synthesis is a multi-resolution compilation of elevation data that is maintained in Mercator, South Polar, and North Polar Projections. GMRT consists of four independently curated elevation components: (1) quality controlled multibeam data ( 100m res.), (2) contributed high-resolution gridded bathymetric data (0.5-200 m res.), (3) ocean basemap data ( 500 m res.), and (4) variable resolution land elevation data (to 10-30 m res. in places). Each component is managed and updated as new content becomes available, with two scheduled releases each year. The ocean basemap content for GMRT includes the International Bathymetric Chart of the Arctic Ocean (IBCAO), the International Bathymetric Chart of the Southern Ocean (IBCSO), and the GEBCO 2014. Most curatorial effort for GMRT is focused on the swath bathymetry component, with an emphasis on data from the US Academic Research Fleet. As of July 2017, GMRT includes data processed and curated by the GMRT Team from 974 research cruises, covering over 29 million square kilometers ( 8%) of the seafloor at 100m resolution. The curated swath bathymetry data from GMRT is routinely contributed to international data synthesis efforts including GEBCO and IBCSO. Additional curatorial effort is associated with gridded data contributions from the international community and ensures that these data are well blended in the synthesis. Significant new additions to the gridded data component this year include the recently released data from the search for MH370 (Geoscience Australia) as well as a large high-resolution grid from the Gulf of Mexico derived from 3D seismic data (US Bureau of Ocean Energy Management). Recent developments in functionality include the deployment of a new Polar GMRT MapTool which enables users to export custom grids and map images in polar projection for their selected area of interest at the resolution of their choosing. Available for both the south and north polar regions, grids can be exported from GMRT in a variety of formats including ASCII, GeoTIFF and NetCDF to support use in common mapping software applications such as ArcGIS, GMT, Matlab, and Python. New web services have also been developed to enable programmatic access to grids and images in north and south polar projections.

Effects of temporal averaging on short-term irradiance variability under mixed sky conditions

NASA Astrophysics Data System (ADS)

Lohmann, Gerald M.; Monahan, Adam H.

2018-05-01

Characterizations of short-term variability in solar radiation are required to successfully integrate large numbers of photovoltaic power systems into the electrical grid. Previous studies have used ground-based irradiance observations with a range of different temporal resolutions and a systematic analysis of the effects of temporal averaging on the representation of variability is lacking. Using high-resolution surface irradiance data with original temporal resolutions between 0.01 and 1 s from six different locations in the Northern Hemisphere, we characterize the changes in representation of temporal variability resulting from time averaging. In this analysis, we condition all data to states of mixed skies, which are the most potentially problematic in terms of local PV power volatility. Statistics of clear-sky index k* and its increments Δk*τ (i.e., normalized surface irradiance and changes therein over specified intervals of time) are considered separately. Our results indicate that a temporal averaging time scale of around 1 s marks a transition in representing single-point irradiance variability, such that longer averages result in substantial underestimates of variability. Higher-resolution data increase the complexity of data management and quality control without appreciably improving the representation of variability. The results do not show any substantial discrepancies between locations or seasons.

A high-resolution open biomass burning emission inventory based on statistical data and MODIS observations in mainland China

NASA Astrophysics Data System (ADS)

Xu, Y.; Fan, M.; Huang, Z.; Zheng, J.; Chen, L.

2017-12-01

Open biomass burning which has adverse effects on air quality and human health is an important source of gas and particulate matter (PM) in China. Current emission estimations of open biomass burning are generally based on single source (alternative to statistical data and satellite-derived data) and thus contain large uncertainty due to the limitation of data. In this study, to quantify the 2015-based amount of open biomass burning, we established a new estimation method for open biomass burning activity levels by combining the bottom-up statistical data and top-down MODIS observations. And three sub-category sources which used different activity data were considered. For open crop residue burning, the "best estimate" of activity data was obtained by averaging the statistical data from China statistical yearbooks and satellite observations from MODIS burned area product MCD64A1 weighted by their uncertainties. For the forest and grassland fires, their activity levels were represented by the combination of statistical data and MODIS active fire product MCD14ML. Using the fire radiative power (FRP) which is considered as a better indicator of active fire level as the spatial allocation surrogate, coarse gridded emissions were reallocated into 3km ×3km grids to get a high-resolution emission inventory. Our results showed that emissions of CO, NOx, SO2, NH3, VOCs, PM2.5, PM10, BC and OC in mainland China were 6607, 427, 84, 79, 1262, 1198, 1222, 159 and 686 Gg/yr, respectively. Among all provinces of China, Henan, Shandong and Heilongjiang were the top three contributors to the total emissions. In this study, the developed open biomass burning emission inventory with a high-resolution could support air quality modeling and policy-making for pollution control.

Megacity and Air Pollution in the Eastern Mediterranean: Istanbul Case Study

NASA Astrophysics Data System (ADS)

Unal, Alper; Kindap, Tayfun; Im, Ulas; Markakis, Kostas; Mihalopoulos, Nikos; Gerasopoulos, Evangelos; Kocak, Mustafa; Mangir, Nizamettin; Kubilay, Nilgun; Kanakidou, Maria

2010-05-01

Turkey, with a population of 75 million, is located at the confluence of Europe and Asia. Istanbul is at the hearth of Turkey's fast economic growth. The city has an annual growth of 3.7% and, according to a study conducted by OECD, is ranked 12th among 45 OECD metro-regions. Istanbul generates 27% of Turkey's Gross Domestic Product (GDP); 40% of tax revenues; and 38% of total industrial output (OECD, 2008). As a result, Istanbul is facing a variety of challenging environmental problems affecting more than 15 million people. Observations show that the number of days exceeding the 24-hour limit value of 50 μgm-3 reached 157 in 2008, with a significant increase from previous years. The city is also a hot spot of pollutant emissions for the surrounding Eastern Mediterranean area. As part of the CityZEN project, in order to quantify the contribution of this megacity as a source of air pollution in the Eastern Mediterranean, a climatological trajectory analysis using a regional climate model output (RegCM3) and a high resolution regional modeling study were performed using the Models-3 WRF meteorological and CMAQ air quality models. Trajectory approach was used to identify the effects of Istanbul emissions on other cities in regional scale. A 30-year (1961-1990) period RegCM3 simulations were used to get a meaningful evaluation. The trajectories were computed according to a method described by Pettersen (1956) as a forward trajectory approach in a 27-km grid resolution. An air parcel was released once every 6h and a total of 42,368 air parcels (trajectories) were released during these 30 years. Long-term meteorological observations in Istanbul show northeasterly and southwesterly prevailing winds over the city. According to these prevailing winds, the distributions of trajectories were mainly observed from the north and south directions of the city. In order to run an air quality model, anthropogenic emission inventory was compiled from a number of different sources including high resolution emission inventories developed for Istanbul at 2km resolution and at 10 km resolution emission inventory of INERIS covering Europe. MOSESS model was used to process emissions data to provide CMAQ ready data (i.e., speciated and vertically and temporally distributed). Regional biogenic and dust emissions are calculated at each time step using the online MEGAN and GOCART modules of WRF-CHEM model. This paper focuses on the climatological and air quality model outputs to analyze the possible impacts of Istanbul emissions on regional air quality.

Impact of temporal upscaling and chemical transport model horizontal resolution on reducing ozone exposure misclassification

NASA Astrophysics Data System (ADS)

Xu, Yadong; Serre, Marc L.; Reyes, Jeanette M.; Vizuete, William

2017-10-01

We have developed a Bayesian Maximum Entropy (BME) framework that integrates observations from a surface monitoring network and predictions from a Chemical Transport Model (CTM) to create improved exposure estimates that can be resolved into any spatial and temporal resolution. The flexibility of the framework allows for input of data in any choice of time scales and CTM predictions of any spatial resolution with varying associated degrees of estimation error and cost in terms of implementation and computation. This study quantifies the impact on exposure estimation error due to these choices by first comparing estimations errors when BME relied on ozone concentration data either as an hourly average, the daily maximum 8-h average (DM8A), or the daily 24-h average (D24A). Our analysis found that the use of DM8A and D24A data, although less computationally intensive, reduced estimation error more when compared to the use of hourly data. This was primarily due to the poorer CTM model performance in the hourly average predicted ozone. Our second analysis compared spatial variability and estimation errors when BME relied on CTM predictions with a grid cell resolution of 12 × 12 km2 versus a coarser resolution of 36 × 36 km2. Our analysis found that integrating the finer grid resolution CTM predictions not only reduced estimation error, but also increased the spatial variability in daily ozone estimates by 5 times. This improvement was due to the improved spatial gradients and model performance found in the finer resolved CTM simulation. The integration of observational and model predictions that is permitted in a BME framework continues to be a powerful approach for improving exposure estimates of ambient air pollution. The results of this analysis demonstrate the importance of also understanding model performance variability and its implications on exposure error.

Air Quality Forecasts Using the NASA GEOS Model

NASA Technical Reports Server (NTRS)

Keller, Christoph A.; Knowland, K. Emma; Nielsen, Jon E.; Orbe, Clara; Ott, Lesley; Pawson, Steven; Saunders, Emily; Duncan, Bryan; Follette-Cook, Melanie; Liu, Junhua;

Comparison of pediatric radiation dose and vessel visibility on angiographic systems using piglets as a surrogate: antiscatter grid removal vs. lower detector air kerma settings with a grid — a preclinical investigation

PubMed Central

Racadio, John M.; Abruzzo, Todd A.; Johnson, Neil D.; Patel, Manish N.; Kukreja, Kamlesh U.; den Hartog, Mark. J. H.; Hoornaert, Bart P.A.; Nachabe, Rami A.

2015-01-01

The purpose of this study was to reduce pediatric doses while maintaining or improving image quality scores without removing the grid from X‐ray beam. This study was approved by the Institutional Animal Care and Use Committee. Three piglets (5, 14, and 20 kg) were imaged using six different selectable detector air kerma (Kair) per frame values (100%, 70%, 50%, 35%, 25%, 17.5%) with and without the grid. Number of distal branches visualized with diagnostic confidence relative to the injected vessel defined image quality score. Five pediatric interventional radiologists evaluated all images. Image quality score and piglet Kair were statistically compared using analysis of variance and receiver operating curve analysis to define the preferred dose setting and use of grid for a visibility of 2nd and 3rd order vessel branches. Grid removal reduced both dose to subject and imaging quality by 26%. Third order branches could only be visualized with the grid present; 100% detector Kair was required for smallest pig, while 70% detector Kair was adequate for the two larger pigs. Second order branches could be visualized with grid at 17.5% detector Kair for all three pig sizes. Without the grid, 50%, 35%, and 35% detector Kair were required for smallest to largest pig, respectively. Grid removal reduces both dose and image quality score. Image quality scores can be maintained with less dose to subject with the grid in the beam as opposed to removed. Smaller anatomy requires more dose to the detector to achieve the same image quality score. PACS numbers: 87.53.Bn, 87.57.N‐, 87.57.cj, 87.59.cf, 87.59.Dj PMID:26699297

Using NASA Environmental Data to Enhance Public Health Decision Making

NASA Technical Reports Server (NTRS)

Al-Hamdan, Mohammad; Crosson, William; Economou, Sigrid; Estes, Maurice, Jr.; Estes, Sue; Hemmings, Sarah; Kent, Shia; Puckett, Mark; Quattrochi, Dale; Wade, Gina;

[Air pollution in an urban area nearby the Rome-Ciampino city airport].

PubMed

Di Menno di Bucchianico, Alessandro; Cattani, Giorgio; Gaeta, Alessandra; Caricchia, Anna Maria; Troiano, Francesco; Sozzi, Roberto; Bolignano, Andrea; Sacco, Fabrizio; Damizia, Sesto; Barberini, Silvia; Caleprico, Roberta; Fabozzi, Tina; Ancona, Carla; Ancona, Laura; Cesaroni, Giulia; Forastiere, Francesco; Gobbi, Gian Paolo; Costabile, Francesca; Angelini, Federico; Barnaba, Francesca; Inglessis, Marco; Tancredi, Francesco; Palumbo, Lorenzo; Fontana, Luca; Bergamaschi, Antonio; Iavicoli, Ivo

2014-01-01

to assess air pollution spatial and temporal variability in the urban area nearby the Ciampino International Airport (Rome) and to investigate the airport-related emissions contribute. the study domain was a 64 km2 area around the airport. Two fifteen-day monitoring campaigns (late spring, winter) were carried out. Results were evaluated using several runs outputs of an airport-related sources Lagrangian particle model and a photochemical model (the Flexible Air quality Regional Model, FARM). both standard and high time resolution air pollutant concentrations measurements: CO, NO, NO2, C6H6, mass and number concentration of several PM fractions. 46 fixed points (spread over the study area) of NO2 and volatile organic compounds concentrations (fifteen days averages); deterministic models outputs. standard time resolution measurements, as well as model outputs, showed the airport contribution to air pollution levels being little compared to the main source in the area (i.e. vehicular traffic). However, using high time resolution measurements, peaks of particles associated with aircraft takeoff (total number concentration and soot mass concentration), and landing (coarse mass concentration) were observed, when the site measurement was downwind to the runway. the frequently observed transient spikes associated with aircraft movements could lead to a not negligible contribute to ultrafine, soot and coarse particles exposure of people living around the airport. Such contribute and its spatial and temporal variability should be investigated when assessing the airports air quality impact.

Using the HOMER Model in Air Quality Analysis

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

Not Available

2004-08-01

HOMER, the micropower optimization model created by the National Renewable Energy Laboratory (NREL), helps design and analyze off-grid and grid-connected power systems. One of HOMER's newest features is its enhanced ability to estimate air emissions for different micropower systems.

Episodic air quality impacts of plug-in electric vehicles

NASA Astrophysics Data System (ADS)

Razeghi, Ghazal; Carreras-Sospedra, Marc; Brown, Tim; Brouwer, Jack; Dabdub, Donald; Samuelsen, Scott

2016-07-01

In this paper, the Spatially and Temporally Resolved Energy and Environment Tool (STREET) is used in conjunction with University of California Irvine - California Institute of Technology (UCI-CIT) atmospheric chemistry and transport model to assess the impact of deploying plug-in electric vehicles and integrating wind energy into the electricity grid on urban air quality. STREET is used to generate emissions profiles associated with transportation and power generation sectors for different future cases. These profiles are then used as inputs to UCI-CIT to assess the impact of each case on urban air quality. The results show an overall improvement in 8-h averaged ozone and 24-h averaged particulate matter concentrations in the South Coast Air Basin (SoCAB) with localized increases in some cases. The most significant reductions occur northeast of the region where baseline concentrations are highest (up to 6 ppb decrease in 8-h-averaged ozone and 6 μg/m3 decrease in 24-h-averaged PM2.5). The results also indicate that, without integration of wind energy into the electricity grid, the temporal vehicle charging profile has very little to no effect on urban air quality. With the addition of wind energy to the grid mix, improvement in air quality is observed while charging at off-peak hours compared to the business as usual scenario.

Scales of variability of black carbon plumes and their dependence on resolution of ECHAM6-HAM

NASA Astrophysics Data System (ADS)

Weigum, Natalie; Stier, Philip; Schutgens, Nick; Kipling, Zak

2015-04-01

Prediction of the aerosol effect on climate depends on the ability of three-dimensional numerical models to accurately estimate aerosol properties. However, a limitation of traditional grid-based models is their inability to resolve variability on scales smaller than a grid box. Past research has shown that significant aerosol variability exists on scales smaller than these grid-boxes, which can lead to discrepancies between observations and aerosol models. The aim of this study is to understand how a global climate model's (GCM) inability to resolve sub-grid scale variability affects simulations of important aerosol features. This problem is addressed by comparing observed black carbon (BC) plume scales from the HIPPO aircraft campaign to those simulated by ECHAM-HAM GCM, and testing how model resolution affects these scales. This study additionally investigates how model resolution affects BC variability in remote and near-source regions. These issues are examined using three different approaches: comparison of observed and simulated along-flight-track plume scales, two-dimensional autocorrelation analysis, and 3-dimensional plume analysis. We find that the degree to which GCMs resolve variability can have a significant impact on the scales of BC plumes, and it is important for models to capture the scales of aerosol plume structures, which account for a large degree of aerosol variability. In this presentation, we will provide further results from the three analysis techniques along with a summary of the implication of these results on future aerosol model development.

Low-cost, high-density sensor network for urban emission monitoring: BEACO2N

NASA Astrophysics Data System (ADS)

Kim, J.; Shusterman, A.; Lieschke, K.; Newman, C.; Cohen, R. C.

2017-12-01

In urban environments, air quality is spatially and temporally heterogeneous as diverse emission sources create a high degree of variability even at the neighborhood scale. Conventional air quality monitoring relies on continuous measurements with limited spatial resolution or passive sampling with high-density and low temporal resolution. Either approach averages the air quality information over space or time and hinders our attempts to understand emissions, chemistry, and human exposure in the near-field of emission sources. To better capture the true spatio-temporal heterogeneity of urban conditions, we have deployed a low-cost, high-density air quality monitoring network in San Francisco Bay Area distributed at 2km horizontal spacing. The BErkeley Atmospheric CO2 Observation Network (BEACO2N) consists of approximately 50 sensor nodes, measuring CO2, CO, NO, NO2, O­3, and aerosol. Here we describe field-based calibration approaches that are consistent with the low-cost strategy of the monitoring network. Observations that allow inference of emission factors and identification of specific local emission sources will also be presented.

Photochemical model evaluation of 2013 California wild fire air quality impacts using surface, aircraft, and satellite data.

PubMed

Baker, K R; Woody, M C; Valin, L; Szykman, J; Yates, E L; Iraci, L T; Choi, H D; Soja, A J; Koplitz, S N; Zhou, L; Campuzano-Jost, Pedro; Jimenez, Jose L; Hair, J W

2018-10-01

The Rim Fire was one of the largest wildfires in California history, burning over 250,000 acres during August and September 2013 affecting air quality locally and regionally in the western U.S. Routine surface monitors, remotely sensed data, and aircraft based measurements were used to assess how well the Community Multiscale Air Quality (CMAQ) photochemical grid model applied at 4 and 12 km resolution represented regional plume transport and chemical evolution during this extreme wildland fire episode. Impacts were generally similar at both grid resolutions although notable differences were seen in some secondary pollutants (e.g., formaldehyde and peroxyacyl nitrate) near the Rim fire. The modeling system does well at capturing near-fire to regional scale smoke plume transport compared to remotely sensed aerosol optical depth (AOD) and aircraft transect measurements. Plume rise for the Rim fire was well characterized as the modeled plume top was consistent with remotely sensed data and the altitude of aircraft measurements, which were typically made at the top edge of the plume. Aircraft-based lidar suggests O 3 downwind in the Rim fire plume was vertically stratified and tended to be higher at the plume top, while CMAQ estimated a more uniformly mixed column of O 3 . Predicted wildfire ozone (O 3 ) was overestimated both at the plume top and at nearby rural and urban surface monitors. Photolysis rates were well characterized by the model compared with aircraft measurements meaning aerosol attenuation was reasonably estimated and unlikely contributing to O 3 overestimates at the top of the plume. Organic carbon was underestimated close to the Rim fire compared to aircraft data, but was consistent with nearby surface measurements. Periods of elevated surface PM 2.5 at rural monitors near the Rim fire were not usually coincident with elevated O 3 . Published by Elsevier B.V.

New Antarctic Gravity Anomaly Grid for Enhanced Geodetic and Geophysical Studies in Antarctica

NASA Technical Reports Server (NTRS)

Scheinert, M.; Ferraccioli, F.; Schwabe, J.; Bell, R.; Studinger, M.; Damaske, D.; Jokat, W.; Aleshkova, N.; Jordan, T.; Leitchenkov, G.;

Comparing Building and Neighborhood-Scale Variability of CO₂ and O₃ to Inform Deployment Considerations for Low-Cost Sensor System Use.

PubMed

Collier-Oxandale, Ashley; Coffey, Evan; Thorson, Jacob; Johnston, Jill; Hannigan, Michael

2018-04-26

The increased use of low-cost air quality sensor systems, particularly by communities, calls for the further development of best-practices to ensure these systems collect usable data. One area identified as requiring more attention is that of deployment logistics, that is, how to select deployment sites and how to strategically place sensors at these sites. Given that sensors are often placed at homes and businesses, ideal placement is not always possible. Considerations such as convenience, access, aesthetics, and safety are also important. To explore this issue, we placed multiple sensor systems at an existing field site allowing us to examine both neighborhood-level and building-level variability during a concurrent period for CO₂ (a primary pollutant) and O₃ (a secondary pollutant). In line with previous studies, we found that local and transported emissions as well as thermal differences in sensor systems drive variability, particularly for high-time resolution data. While this level of variability is unlikely to affect data on larger averaging scales, this variability could impact analysis if the user is interested in high-time resolution or examining local sources. However, with thoughtful placement and thorough documentation, high-time resolution data at the neighborhood level has the potential to provide us with entirely new information on local air quality trends and emissions.

Advanced Turbulence Modeling Concepts

NASA Technical Reports Server (NTRS)

Shih, Tsan-Hsing

2005-01-01

The ZCET program developed at NASA Glenn Research Center is to study hydrogen/air injection concepts for aircraft gas turbine engines that meet conventional gas turbine performance levels and provide low levels of harmful NOx emissions. A CFD study for ZCET program has been successfully carried out. It uses the most recently enhanced National combustion code (NCC) to perform CFD simulations for two configurations of hydrogen fuel injectors (GRC- and Sandia-injector). The results can be used to assist experimental studies to provide quick mixing, low emission and high performance fuel injector designs. The work started with the configuration of the single-hole injector. The computational models were taken from the experimental designs. For example, the GRC single-hole injector consists of one air tube (0.78 inches long and 0.265 inches in diameter) and two hydrogen tubes (0.3 inches long and 0.0226 inches in diameter opposed at 180 degree). The hydrogen tubes are located 0.3 inches upstream from the exit of the air element (the inlet location for the combustor). To do the simulation, the single-hole injector is connected to a combustor model (8.16 inches long and 0.5 inches in diameter). The inlet conditions for air and hydrogen elements are defined according to actual experimental designs. Two crossing jets of hydrogen/air are simulated in detail in the injector. The cold flow, reacting flow, flame temperature, combustor pressure and possible flashback phenomena are studied. Two grid resolutions of the numerical model have been adopted. The first computational grid contains 0.52 million elements, the second one contains over 1.3 million elements. The CFD results have shown only about 5% difference between the two grid resolutions. Therefore, the CFD result obtained from the model of 1.3-million grid resolution can be considered as a grid independent numerical solution. Turbulence models built in NCC are consolidated and well tested. They can handle both coarse and fine grids near the wall. They can model the effect of anisotropy of turbulent stresses and the effect of swirling. The chemical reactions of Magnusson model and ILDM method were both used in this study.

Simulating the Agulhas system in global ocean models - nesting vs. multi-resolution unstructured meshes

NASA Astrophysics Data System (ADS)

Biastoch, Arne; Sein, Dmitry; Durgadoo, Jonathan V.; Wang, Qiang; Danilov, Sergey

2018-01-01

Many questions in ocean and climate modelling require the combined use of high resolution, global coverage and multi-decadal integration length. For this combination, even modern resources limit the use of traditional structured-mesh grids. Here we compare two approaches: A high-resolution grid nested into a global model at coarser resolution (NEMO with AGRIF) and an unstructured-mesh grid (FESOM) which allows to variably enhance resolution where desired. The Agulhas system around South Africa is used as a testcase, providing an energetic interplay of a strong western boundary current and mesoscale dynamics. Its open setting into the horizontal and global overturning circulations also requires global coverage. Both model configurations simulate a reasonable large-scale circulation. Distribution and temporal variability of the wind-driven circulation are quite comparable due to the same atmospheric forcing. However, the overturning circulation differs, owing each model's ability to represent formation and spreading of deep water masses. In terms of regional, high-resolution dynamics, all elements of the Agulhas system are well represented. Owing to the strong nonlinearity in the system, Agulhas Current transports of both configurations and in comparison with observations differ in strength and temporal variability. Similar decadal trends in Agulhas Current transport and Agulhas leakage are linked to the trends in wind forcing.

Air quality modelling over the Eastern Mediterranean using the WRF/Chem model: Comparison of gas-phase chemistry and aerosol mechanisms

NASA Astrophysics Data System (ADS)

Georgiou, George K.; Christoudias, Theodoros; Proestos, Yiannis; Kushta, Jonilda; Hadjinicolaou, Panos; Lelieveld, Jos

2017-04-01

A comprehensive analysis of the performance of three coupled gas-phase chemistry and aerosol mechanisms included in the WRF/Chem model has been performed over the Eastern Mediterranean focusing on Cyprus during the CYPHEX campaign in 2014, using high temporal and spatial resolution. The model performance was evaluated by comparing calculations to measurements of gas phase species (O3, CO, NOx, SO2) and aerosols (PM10, PM2.5) from 13 ground stations. Initial results indicate that the calculated day-to-day and diurnal variations of the aforementioned species show good agreement with observations. The model was set up with three nested grids, downscaling to 4km over Cyprus. The meteorological boundary conditions were updated every 3 hours throughout the simulation using the Global Forecast System (GFS), while chemical boundary conditions were updated every 6 hours using the MOZART global chemical transport model. Biogenic emissions were calculated online by the the Model of Emissions of Gases and Aerosols from Nature version 2.1 (MEGAN2.1). Anthropogenic emissions were based on the EDGAR HTAP v2 global emission inventory, provided on a horizontal grid resolution of 0.1o × 0.1o. Three simulations were performed employing different chemistry and aerosol mechanisms; i) RADM2 chemical mechanism and MADE/SORGAM aerosols, ii) CBMZ chemical mechanism and MOSAIC aerosols, iii) MOZART chemical mechanism and MOSAIC aerosols. Results show that the WRF/Chem model satisfactorily estimates the trace gases relative concentrations at the background sites but not at the urban and traffic sites, while some differences appear between the simulated concentrations by the three mechanisms. The resulting discrepancies between the model outcome and measurements, especially at the urban and traffic sites, suggest that a higher resolution anthropogenic emission inventory might help improve fine resolution, regional air quality modelling. Differences in the simulated concentrations by the three chemical mechanisms are attributed to the different chemical species and reaction rate constants used.

Climate Signal Detection in Wine Quality Using Gridded vs. Station Data in North-East Hungary

NASA Astrophysics Data System (ADS)

Mika, Janos; Razsi, Andras; Gal, Lajos

2017-04-01

The grapevine is one of the oldest cultivated plants. Today's viticultural regions for quality wine production are located in relatively narrow geographical and therefore climatic niches. Our target area, the Matra Region in NE Hungary is fairly close to the edge of optimal wine production concerning its climate conditions. Fifty year (1961-2010) wine and quality (natural sugar content, in weight % of must) data are analysed and compared to parallel climate variables. Two sets of station-based monthly temperature, sunshine duration and precipitation data, taken from neighbouring stations, Eger-Kőlyuktető (1961-2010) and Kompolt (1976-2006) are used in 132 combinations, together with daily grid-point data provided by the CarpatClim Project (www.carpatclim-eu.org/pages/home). By now it is clear that (1) wine quality, is in significant negative correlation with the annual precipitation and in positive correlation with temperature and sunshine duration. (2) Applying a wide combination of monthly data we obtain even stronger correlations (higher significance according to t-tests) even from the station-based data, but it is difficult to select and optimum model from the many proper combinations differing in performance over the test sample just slightly. (3) The interpolated site-specific areal averages from the grid-point data provide even better results and stronger differences between the best models and the few other candidates. (4) Further improvement of statistical signal detection capacity of the above climate variables by using 5-day averages, point at the strong vulnerability of wine quality on climate anomalies of some key phenological phases of the investigated grapevine-mixes. Enhanced spatial and temporal resolution provides much better fit to the observed wine quality data. The study has been supported by the OTKA-113209 national project.

A Fleet of Low-Cost Sensor Based Air Quality Monitors Is Used to Measure Carbon Dioxide and Carbon Monoxide in Two Settings: In the Ambient Environment to Explore the Regional-Scale Spatial Variability of These Compounds Via a Distributed Network, and in Homes to Investigate How Heating during Winter Months can Impact Indoor Air Quality.

NASA Astrophysics Data System (ADS)

Casey, J. G.; Hannigan, M.; Collier, A. M.; Coffey, E.; Piedrahita, R.

2016-12-01

Affordable, small, portable, quiet tools to measure atmospheric trace gases and air quality enable novel experimental design and new findings. Members of the Hannigan Lab at the University of Colorado in Boulder have been working over the last few years to integrate emerging affordable gas sensors into such an air quality monitor. Presented here are carbon monoxide (CO) and carbon dioxide (CO2) measurements from two field experiments that utilized these tools. In the first experiment, ten air quality monitors were located northeast of Boulder throughout the Denver Julesburg oil and gas basin. The Colorado Department of Health and Environment has several air quality monitoring sites in this broader region, each in an Urban center. One goal of the experiment was to determine whether or not significant spatial variability of EPA criteria pollutants like CO, exists on a sub-regulatory monitoring grid scale. Another goal of the experiment was to compare rural sampling locations with urban sites. The monitors collected continuous data (sampling every 15 seconds) at each location over the course of several months. Our sensor calibration procedures are presented along with our observations and an analysis of the spatial and temporal variability in CO and CO2. In the second experiment, we used eight of our air quality monitors to better understand how home heating fuel type can impact indoor air quality in two communities on the Navajo Nation. We sought to compare air quality in homes using one of four different fuels for heat (wood, wood plus coal, pellet, and gas). There are many factors that contribute to indoor air quality and the impact of an emission source, like a woodstove, within a home. Having multiple, easily deployable, air quality monitors allowed us to account for many of these factors. We sampled four homes at a time, aiming for one home from each of our fuel groups in each sampling period. We sampled inside and outside of each home for a period of 3-4 days. In this way, we hoped to account for possible weather and outdoor air quality biases. CO and CO2 were measured and are put into context with acceptable levels. During periods when there were no emissions of CO and CO2, we used their rates of decay to calculate the home's air exchange rate via the tracer gas technique. The air exchange rate was then used to calculate emission rates for CO.

Sources and pathways of the upscale effects on the Southern Hemisphere jet in MPAS-CAM4 variable-resolution simulations

DOE PAGES

Sakaguchi, Koichi; Lu, Jian; Leung, L. Ruby; ...

2016-10-22

Impacts of regional grid refinement on large-scale circulations (“upscale effects”) were detected in a previous study that used the Model for Prediction Across Scales-Atmosphere coupled to the physics parameterizations of the Community Atmosphere Model version 4. The strongest upscale effect was identified in the Southern Hemisphere jet during austral winter. This study examines the detailed underlying processes by comparing two simulations at quasi-uniform resolutions of 30 and 120 km to three variable-resolution simulations in which the horizontal grids are regionally refined to 30 km in North America, South America, or Asia from 120 km elsewhere. In all the variable-resolution simulations,more » precipitation increases in convective areas inside the high-resolution domains, as in the reference quasi-uniform high-resolution simulation. With grid refinement encompassing the tropical Americas, the increased condensational heating expands the local divergent circulations (Hadley cell) meridionally such that their descending branch is shifted poleward, which also pushes the baroclinically unstable regions, momentum flux convergence, and the eddy-driven jet poleward. This teleconnection pathway is not found in the reference high-resolution simulation due to a strong resolution sensitivity of cloud radiative forcing that dominates the aforementioned teleconnection signals. The regional refinement over Asia enhances Rossby wave sources and strengthens the upper level southerly flow, both facilitating the cross-equatorial propagation of stationary waves. Evidence indicates that this teleconnection pathway is also found in the reference high-resolution simulation. Lastly, the result underlines the intricate diagnoses needed to understand the upscale effects in global variable-resolution simulations, with implications for science investigations using the computationally efficient modeling framework.« less

Sources and pathways of the upscale effects on the Southern Hemisphere jet in MPAS-CAM4 variable-resolution simulations

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

Sakaguchi, Koichi; Lu, Jian; Leung, L. Ruby

Impacts of regional grid refinement on large-scale circulations (“upscale effects”) were detected in a previous study that used the Model for Prediction Across Scales-Atmosphere coupled to the physics parameterizations of the Community Atmosphere Model version 4. The strongest upscale effect was identified in the Southern Hemisphere jet during austral winter. This study examines the detailed underlying processes by comparing two simulations at quasi-uniform resolutions of 30 and 120 km to three variable-resolution simulations in which the horizontal grids are regionally refined to 30 km in North America, South America, or Asia from 120 km elsewhere. In all the variable-resolution simulations,more » precipitation increases in convective areas inside the high-resolution domains, as in the reference quasi-uniform high-resolution simulation. With grid refinement encompassing the tropical Americas, the increased condensational heating expands the local divergent circulations (Hadley cell) meridionally such that their descending branch is shifted poleward, which also pushes the baroclinically unstable regions, momentum flux convergence, and the eddy-driven jet poleward. This teleconnection pathway is not found in the reference high-resolution simulation due to a strong resolution sensitivity of cloud radiative forcing that dominates the aforementioned teleconnection signals. The regional refinement over Asia enhances Rossby wave sources and strengthens the upper level southerly flow, both facilitating the cross-equatorial propagation of stationary waves. Evidence indicates that this teleconnection pathway is also found in the reference high-resolution simulation. Lastly, the result underlines the intricate diagnoses needed to understand the upscale effects in global variable-resolution simulations, with implications for science investigations using the computationally efficient modeling framework.« less

[Airports and air quality: a critical synthesis of the literature].

PubMed

Cattani, Giorgio; Di Menno di Bucchianico, Alessandro; Gaeta, Alessandra; Romani, Daniela; Fontana, Luca; Iavicoli, Ivo

2014-01-01

This work reviewed existing literature on airport related activities that could worsen surrounding air quality; its aim is to underline the progress coming from recent-year studies, the knowledge emerging from new approaches, the development of semi-empiric analytical methods as well as the questions still needing to be clarified. To estimate pollution levels, spatial and temporal variability, and the sources relative contributions integrated assessment, using both fixed point measurement and model outputs, are needed. The general picture emerging from the studies was a non-negligible and highly spatially variable (within 2-3 km from the fence line) airport contribution; even if it is often not dominant compared to other concomitant pollution sources. Results were highly airport-specific. Traffic volumes, landscape and meteorology were the key variables that drove the impacts. Results were thus hardly exportable to other contexts. Airport related pollutant sources were found to be characterized by unusual emission patterns (particularly ultrafine particles, black carbon and nitrogen oxides during take-off); high time-resolution measurements allow to depict the rapidly changing take-off effect on air quality that could not be adequately observed otherwise. Few studies used high time resolution data in a successful way as statistical models inputs to estimate the aircraft take-off contribution to the observed average levels. These findings should not be neglected when exposure of people living near airports is to be assessed.

Leveraging GeoTIFF Compatibility for Visualizing a New EASE-Grid 2.0 Global Satellite Passive Microwave Climate Record

NASA Astrophysics Data System (ADS)

Paget, A. C.; Brodzik, M. J.; Long, D. G.; Hardman, M.

2016-02-01

The historical record of satellite-derived passive microwave brightness temperatures comprises data from multiple imaging radiometers (SMMR, SSM/I-SSMIS, AMSR-E), spanning nearly 40 years of Earth observations from 1978 to the present. Passive microwave data are used to monitor time series of many climatological variables, including ocean wind speeds, cloud liquid water and sea ice concentrations and ice velocity. Gridded versions of passive microwave data have been produced using various map projections (polar stereographic, Lambert azimuthal equal-area, cylindrical equal-area, quarter-degree Platte-Carree) and data formats (flat binary, HDF). However, none of the currently available versions can be rendered in the common visualization standard, geoTIFF, without requiring cartographic reprojection. Furthermore, the reprojection details are complicated and often require expert knowledge of obscure software package options. We are producing a consistently calibrated, completely reprocessed data set of this valuable multi-sensor satellite record, using EASE-Grid 2.0, an improved equal-area projection definition that will require no reprojection for translation into geoTIFF. Our approach has been twofold: 1) define the projection ellipsoid to match the reference datum of the satellite data, and 2) include required file-level metadata for standard projection software to correctly render the data in the geoTIFF standard. The Calibrated, Enhanced Resolution Brightness Temperature (CETB) Earth System Data Record (ESDR), leverages image reconstruction techniques to enhance gridded spatial resolution to 3 km and uses newly available intersensor calibrations to improve the quality of derived geophysical products. We expect that our attention to easy geoTIFF compatibility will foster higher-quality analysis with the CETB product by enabling easy and correct intercomparison with other gridded and in situ data.

An operational air quality objective analysis of surface pollutants

NASA Astrophysics Data System (ADS)

Menard, R.; Robichaud, A.

2013-05-01

As of December 2012 a surface analysis of O3, PM2.5 at a resolution of 10 km over Canada and USA has become an operational product of Environment Canada. Analyses based an optimum interpolation scheme adapted to the variability of surface pollutant is run each hour. We will briefly discuss the specifics of the scheme, the technical implementation that lead to an operational implementation, a description and validation of the product as it stands today. An analysis of NO2 and a map of an air quality health index is also under way. We are now developing a high resolution analysis, 2.5 km over major cities over the Montreal-Toronto area and over the Oil sands region. The effect of state-dependent error covariance modeling will be present with some early results of the high resolutions analysis/assimilation.

Spatial and temporal variability of clouds and precipitation over Germany: multiscale simulations across the "gray zone"

NASA Astrophysics Data System (ADS)

Barthlott, C.; Hoose, C.

2015-11-01

This paper assesses the resolution dependance of clouds and precipitation over Germany by numerical simulations with the COnsortium for Small-scale MOdeling (COSMO) model. Six intensive observation periods of the HOPE (HD(CP)2 Observational Prototype Experiment) measurement campaign conducted in spring 2013 and 1 summer day of the same year are simulated. By means of a series of grid-refinement resolution tests (horizontal grid spacing 2.8, 1 km, 500, and 250 m), the applicability of the COSMO model to represent real weather events in the gray zone, i.e., the scale ranging between the mesoscale limit (no turbulence resolved) and the large-eddy simulation limit (energy-containing turbulence resolved), is tested. To the authors' knowledge, this paper presents the first non-idealized COSMO simulations in the peer-reviewed literature at the 250-500 m scale. It is found that the kinetic energy spectra derived from model output show the expected -5/3 slope, as well as a dependency on model resolution, and that the effective resolution lies between 6 and 7 times the nominal resolution. Although the representation of a number of processes is enhanced with resolution (e.g., boundary-layer thermals, low-level convergence zones, gravity waves), their influence on the temporal evolution of precipitation is rather weak. However, rain intensities vary with resolution, leading to differences in the total rain amount of up to +48 %. Furthermore, the location of rain is similar for the springtime cases with moderate and strong synoptic forcing, whereas significant differences are obtained for the summertime case with air mass convection. Domain-averaged liquid water paths and cloud condensate profiles are used to analyze the temporal and spatial variability of the simulated clouds. Finally, probability density functions of convection-related parameters are analyzed to investigate their dependance on model resolution and their impact on cloud formation and subsequent precipitation.

WegenerNet climate station network region Feldbach/Austria: From local measurements to weather and climate data products at 1 km-scale resolution

NASA Astrophysics Data System (ADS)

Kabas, T.; Leuprecht, A.; Bichler, C.; Kirchengast, G.

2010-12-01

South-eastern Austria is characteristic for experiencing a rich variety of weather and climate patterns. For this reason, the county of Feldbach was selected by the Wegener Center as a focus area for a pioneering observation experiment at very high resolution: The WegenerNet climate station network (in brief WegenerNet) comprises 151 meteorological stations within an area of about 20 km × 15 km (~ 1.4 km × 1.4 km station grid). All stations measure the main parameters temperature, humidity and precipitation with 5 minute sampling. Selected further stations include measurements of wind speed and direction completed by soil parameters as well as air pressure and net radiation. The collected data is integrated in an automatic processing system including data transfer, quality control, product generation, and visualization. Each station is equipped with an internet-attached data logger and the measurements are transferred as binary files via GPRS to the WegenerNet server in 1 hour intervals. The incoming raw data files of measured parameters as well as several operating values of the data logger are stored in a relational database (PostgreSQL). Next, the raw data pass the Quality Control System (QCS) in which the data are checked for its technical and physical plausibility (e.g., sensor specifications, temporal and spatial variability). In consideration of the data quality (quality flag), the Data Product Generator (DPG) results in weather and climate data products on various temporal scales (from 5 min to annual) for single stations and regular grids. Gridded data are derived by vertical scaling and squared inverse distance interpolation (1 km × 1 km and 0.01° × 0.01° grids). Both subsystems (QCS and DPG) are realized by the programming language Python. For application purposes the resulting data products are available via the bi-lingual (dt, en) WegenerNet data portal (www.wegenernet.org). At this time, the main interface is still online in a system in which MapServer is used to import spatial data by its database interface and to generate images of static geographic formats. However, a Java applet is additionally needed to display these images on the users local host. Furthermore, station data are visualized as time series by the scripting language PHP. Since February 2010, the visualization of gridded data products is a first step to a new data portal based on OpenLayers. In this GIS framework, all geographic information (e.g., OpenStreetMap) is displayed with MapServer. Furthermore, the visualization of all meteorological parameters are generated on the fly by a Python CGI script and transparently overlayed on the maps. Hence, station data and gridded data are visualized and further prepared for download in common data formats (csv, NetCDF). In conclusion, measured data and generated data products are provided with a data latency less than 1-2 hours in standard operation (near real time). Following an introduction of the processing system along the lines above, resulting data products are presented online at the WegenerNet data portal.

Air Quality Forecasts Using the NASA GEOS Model: A Unified Tool from Local to Global Scales

NASA Technical Reports Server (NTRS)

Knowland, E. Emma; Keller, Christoph; Nielsen, J. Eric; Orbe, Clara; Ott, Lesley; Pawson, Steven; Saunders, Emily; Duncan, Bryan; Cook, Melanie; Liu, Junhua;

Evaluation of multisectional and two-section particulate matter photochemical grid models in the Western United States.

PubMed

Morris, Ralph; Koo, Bonyoung; Yarwood, Greg

2005-11-01

Version 4.10s of the comprehensive air-quality model with extensions (CAMx) photochemical grid model has been developed, which includes two options for representing particulate matter (PM) size distribution: (1) a two-section representation that consists of fine (PM2.5) and coarse (PM2.5-10) modes that has no interactions between the sections and assumes all of the secondary PM is fine; and (2) a multisectional representation that divides the PM size distribution into N sections (e.g., N = 10) and simulates the mass transfer between sections because of coagulation, accumulation, evaporation, and other processes. The model was applied to Southern California using the two-section and multisection representation of PM size distribution, and we found that allowing secondary PM to grow into the coarse mode had a substantial effect on PM concentration estimates. CAMx was then applied to the Western United States for the 1996 annual period with a 36-km grid resolution using both the two-section and multisection PM representation. The Community Multiscale Air Quality (CMAQ) and Regional Modeling for Aerosol and Deposition (REMSAD) models were also applied to the 1996 annual period. Similar model performance was exhibited by the four models across the Interagency Monitoring of Protected Visual Environments (IMPROVE) and Clean Air Status and Trends Network monitoring networks. All four of the models exhibited fairly low annual bias for secondary PM sulfate and nitrate but with a winter overestimation and summer underestimation bias. The CAMx multisectional model estimated that coarse mode secondary sulfate and nitrate typically contribute <10% of the total sulfate and nitrate when averaged across the more rural IMPROVE monitoring network.

EVALUATING AND USING AIR QUALITY MODELS

EPA Science Inventory

Grid-based models are being used to assess the magnitude of the pollution problem and to design emission control strategies to achieve compliance with the relevant air quality standards in the United States.

Estimated tetrachloroethylene (C2Cl4) emissions for 1992 2014 in China and a high resolution gridded emission in 2010

NASA Astrophysics Data System (ADS)

Bie, P.; Li, Z.; Hu, J.

2016-12-01

Estimated tetrachloroethylene (C2Cl4) emissions for 1992 2014 in China and a high resolution gridded emission in 2010 Pengju Bie1, Zhifang Li1, Jianxin Hu1,*1Collaborative Innovation Center for Regional Environmental Quality, College of Environmental Sciences and Engineering, Peking University, Beijing 100871, China *Corresponding author E-mail: jianxin@pku.edu.cnTel: 86-10-62756593 Fax: 86-10-62760755 Evaluating the contribution from tetrachloroethylene (C2Cl4, PCE) to stratospheric halogen loading requires the knowledge of the spatial and temporal variability of emissions, and thus the tropospheric degradation and removal. And the short atmospheric lifetime (90 days) leads to a large regional variability. This study estimated the emissions of China from 1992 to 2014, based on emission functions and aggregated information given reasonable uncertainties. Results show that the emissions increased from 5.3(3.8 7.0) Gg to 176.9(131.2 232.1) Gg with a moderate growth rate of 17.3%/yr during 1992 2014. More than 97.3% of emissions stemmed from solvents sector. Considering the GDP data availability and the comparable estimate to that of top-down method in 2010, we developed a gridded emission inventory on a 0.5°×0.5° latitude-longitude grid of this year. Due to the more advanced social-economic conditions and more intensive industrial establishment, greater PCE emissions were observed to originate from East China, especially for Jiangsu and Zhejiang provinces, and Beijing-Tianjin-Hebei region and Pearl River Delta (PRD) region.

Downscaling a Global Climate Model to Simulate Climate Change Impacts on U.S. Regional and Urban Air Quality

NASA Technical Reports Server (NTRS)

Trail, M.; Tsimpidi, A. P.; Liu, P.; Tsigaridis, K.; Hu, Y.; Nenes, A.; Russell, A. G.

2013-01-01

Climate change can exacerbate future regional air pollution events by making conditions more favorable to form high levels of ozone. In this study, we use spectral nudging with WRF to downscale NASA earth system GISS modelE2 results during the years 2006 to 2010 and 2048 to 2052 over the continental United States in order to compare the resulting meteorological fields from the air quality perspective during the four seasons of five-year historic and future climatological periods. GISS results are used as initial and boundary conditions by the WRF RCM to produce hourly meteorological fields. The downscaling technique and choice of physics parameterizations used are evaluated by comparing them with in situ observations. This study investigates changes of similar regional climate conditions down to a 12km by 12km resolution, as well as the effect of evolving climate conditions on the air quality at major U.S. cities. The high resolution simulations produce somewhat different results than the coarse resolution simulations in some regions. Also, through the analysis of the meteorological variables that most strongly influence air quality, we find consistent changes in regional climate that would enhance ozone levels in four regions of the U.S. during fall (Western U.S., Texas, Northeastern, and Southeastern U.S), one region during summer (Texas), and one region where changes potentially would lead to better air quality during spring (Northeast). We also find that daily peak temperatures tend to increase in most major cities in the U.S. which would increase the risk of health problems associated with heat stress. Future work will address a more comprehensive assessment of emissions and chemistry involved in the formation and removal of air pollutants.

Spatio-temporal modelling for assessing air pollution in Santiago de Chile

NASA Astrophysics Data System (ADS)

Nicolis, Orietta; Camaño, Christian; Mařın, Julio C.; Sahu, Sujit K.

2017-01-01

In this work, we propose a space-time approach for studying the PM2.5 concentration in the city of Santiago de Chile. In particular, we apply the autoregressive hierarchical model proposed by [1] using the PM2.5 observations collected by a monitoring network as a response variable and numerical weather forecasts from the Weather Research and Forecasting (WRF) model as covariate together with spatial and temporal (periodic) components. The approach is able to provide short-term spatio-temporal predictions of PM2.5 concentrations on a fine spatial grid (at 1km × 1km horizontal resolution.)

A high-resolution European dataset for hydrologic modeling

NASA Astrophysics Data System (ADS)

Ntegeka, Victor; Salamon, Peter; Gomes, Goncalo; Sint, Hadewij; Lorini, Valerio; Thielen, Jutta

2013-04-01

There is an increasing demand for large scale hydrological models not only in the field of modeling the impact of climate change on water resources but also for disaster risk assessments and flood or drought early warning systems. These large scale models need to be calibrated and verified against large amounts of observations in order to judge their capabilities to predict the future. However, the creation of large scale datasets is challenging for it requires collection, harmonization, and quality checking of large amounts of observations. For this reason, only a limited number of such datasets exist. In this work, we present a pan European, high-resolution gridded dataset of meteorological observations (EFAS-Meteo) which was designed with the aim to drive a large scale hydrological model. Similar European and global gridded datasets already exist, such as the HadGHCND (Caesar et al., 2006), the JRC MARS-STAT database (van der Goot and Orlandi, 2003) and the E-OBS gridded dataset (Haylock et al., 2008). However, none of those provide similarly high spatial resolution and/or a complete set of variables to force a hydrologic model. EFAS-Meteo contains daily maps of precipitation, surface temperature (mean, minimum and maximum), wind speed and vapour pressure at a spatial grid resolution of 5 x 5 km for the time period 1 January 1990 - 31 December 2011. It furthermore contains calculated radiation, which is calculated by using a staggered approach depending on the availability of sunshine duration, cloud cover and minimum and maximum temperature, and evapotranspiration (potential evapotranspiration, bare soil and open water evapotranspiration). The potential evapotranspiration was calculated using the Penman-Monteith equation with the above-mentioned meteorological variables. The dataset was created as part of the development of the European Flood Awareness System (EFAS) and has been continuously updated throughout the last years. The dataset variables are used as inputs to the hydrological calibration and validation of EFAS as well as for establishing long-term discharge "proxy" climatologies which can then in turn be used for statistical analysis to derive return periods or other time series derivatives. In addition, this dataset will be used to assess climatological trends in Europe. Unfortunately, to date no baseline dataset at the European scale exists to test the quality of the herein presented data. Hence, a comparison against other existing datasets can therefore only be an indication of data quality. Due to availability, a comparison was made for precipitation and temperature only, arguably the most important meteorological drivers for hydrologic models. A variety of analyses was undertaken at country scale against data reported to EUROSTAT and E-OBS datasets. The comparison revealed that while the datasets showed overall similar temporal and spatial patterns, there were some differences in magnitudes especially for precipitation. It is not straightforward to define the specific cause for these differences. However, in most cases the comparatively low observation station density appears to be the principal reason for the differences in magnitude.

Indicators reflecting local and transboundary sources of PM2.5 and PMCOARSE in Rome - Impacts in air quality

NASA Astrophysics Data System (ADS)

Dimitriou, Konstantinos; Kassomenos, Pavlos

2014-10-01

The keystone of this paper was to calculate and interpret indicators reflecting sources and air quality impacts of PM2.5 and PMCOARSE (PM10-PM2.5) in Rome (Italy), focusing on potential exogenous influences. A backward atmospheric trajectory cluster analysis was implemented. The likelihood of daily PM10 exceedances was studied in conjunction with atmospheric patterns, whereas a Potential Source Contribution Function (PSCF) based on air mass residence time was deployed on a grid of a 0.5° × 0.5° resolution. Higher PM2.5 concentrations were associated with short/medium range airflows originated from Balkan Peninsula, whereas potential PMCOARSE sources were localized across the Mediterranean and coastal North Africa, due to dust and sea spray transportation. According to the outcome of a daily Pollution Index (PI), a slightly increased degradation of air quality is induced due to the additional quantity of exogenous PM but nevertheless, average levels of PI in all trajectory clusters belong in the low pollution category. Gaseous and particulate pollutants were also elaborated by a Principal Component Analysis (PCA), which produced 4 components: [Traffic], [photochemical], [residential] and [Secondary Coarse Aerosol], reflecting local sources of air pollution. PM2.5 levels were strongly associated with traffic, whereas PMCOARSE were produced autonomously by secondary sources.

Is there potential added value in COSMO-CLM forced by ERA reanalysis data?

NASA Astrophysics Data System (ADS)

Lenz, Claus-Jürgen; Früh, Barbara; Adalatpanah, Fatemeh Davary

2017-12-01

An application of the potential added value (PAV) concept suggested by Di Luca et al. (Clim Dyn 40:443-464, 2013a) is applied to ERA Interim driven runs of the regional climate model COSMO-CLM. They are performed for the time period 1979-2013 for the EURO-CORDEX domain at horizontal grid resolutions 0.11°, 0.22°, and 0.44° such that the higher resolved model grid fits into the next coarser grid. The concept of the potential added value is applied to annual, seasonal, and monthly means of the 2 m air temperature. Results show the highest potential added value at the run with the finest grid and generally increasing PAV with increasing resolution. The potential added value strongly depends on the season as well as the region of consideration. The gain of PAV is higher enhancing the resolution from 0.44° to 0.22° than from 0.22° to 0.11°. At grid aggregations to 0.88° and 1.76° the differences in PAV between the COSMO-CLM runs on the mentioned grid resolutions are maximal. They nearly vanish at aggregations to even coarser grids. In all cases the PAV is dominated by at least 80% by its stationary part.

An advanced stochastic weather generator for simulating 2-D high-resolution climate variables

NASA Astrophysics Data System (ADS)

Peleg, Nadav; Fatichi, Simone; Paschalis, Athanasios; Molnar, Peter; Burlando, Paolo

2017-07-01

A new stochastic weather generator, Advanced WEather GENerator for a two-dimensional grid (AWE-GEN-2d) is presented. The model combines physical and stochastic approaches to simulate key meteorological variables at high spatial and temporal resolution: 2 km × 2 km and 5 min for precipitation and cloud cover and 100 m × 100 m and 1 h for near-surface air temperature, solar radiation, vapor pressure, atmospheric pressure, and near-surface wind. The model requires spatially distributed data for the calibration process, which can nowadays be obtained by remote sensing devices (weather radar and satellites), reanalysis data sets and ground stations. AWE-GEN-2d is parsimonious in terms of computational demand and therefore is particularly suitable for studies where exploring internal climatic variability at multiple spatial and temporal scales is fundamental. Applications of the model include models of environmental systems, such as hydrological and geomorphological models, where high-resolution spatial and temporal meteorological forcing is crucial. The weather generator was calibrated and validated for the Engelberg region, an area with complex topography in the Swiss Alps. Model test shows that the climate variables are generated by AWE-GEN-2d with a level of accuracy that is sufficient for many practical applications.

High-Resolution Air Pollution Mapping with Google Street View Cars: Exploiting Big Data.

PubMed

Apte, Joshua S; Messier, Kyle P; Gani, Shahzad; Brauer, Michael; Kirchstetter, Thomas W; Lunden, Melissa M; Marshall, Julian D; Portier, Christopher J; Vermeulen, Roel C H; Hamburg, Steven P

2017-06-20

Air pollution affects billions of people worldwide, yet ambient pollution measurements are limited for much of the world. Urban air pollution concentrations vary sharply over short distances (≪1 km) owing to unevenly distributed emission sources, dilution, and physicochemical transformations. Accordingly, even where present, conventional fixed-site pollution monitoring methods lack the spatial resolution needed to characterize heterogeneous human exposures and localized pollution hotspots. Here, we demonstrate a measurement approach to reveal urban air pollution patterns at 4-5 orders of magnitude greater spatial precision than possible with current central-site ambient monitoring. We equipped Google Street View vehicles with a fast-response pollution measurement platform and repeatedly sampled every street in a 30-km 2 area of Oakland, CA, developing the largest urban air quality data set of its type. Resulting maps of annual daytime NO, NO 2 , and black carbon at 30 m-scale reveal stable, persistent pollution patterns with surprisingly sharp small-scale variability attributable to local sources, up to 5-8× within individual city blocks. Since local variation in air quality profoundly impacts public health and environmental equity, our results have important implications for how air pollution is measured and managed. If validated elsewhere, this readily scalable measurement approach could address major air quality data gaps worldwide.

A new Downscaling Approach for SMAP, SMOS and ASCAT by predicting sub-grid Soil Moisture Variability based on Soil Texture

NASA Astrophysics Data System (ADS)

Montzka, C.; Rötzer, K.; Bogena, H. R.; Vereecken, H.

2017-12-01

Improving the coarse spatial resolution of global soil moisture products from SMOS, SMAP and ASCAT is currently an up-to-date topic. Soil texture heterogeneity is known to be one of the main sources of soil moisture spatial variability. A method has been developed that predicts the soil moisture standard deviation as a function of the mean soil moisture based on soil texture information. It is a closed-form expression using stochastic analysis of 1D unsaturated gravitational flow in an infinitely long vertical profile based on the Mualem-van Genuchten model and first-order Taylor expansions. With the recent development of high resolution maps of basic soil properties such as soil texture and bulk density, relevant information to estimate soil moisture variability within a satellite product grid cell is available. Here, we predict for each SMOS, SMAP and ASCAT grid cell the sub-grid soil moisture variability based on the SoilGrids1km data set. We provide a look-up table that indicates the soil moisture standard deviation for any given soil moisture mean. The resulting data set provides important information for downscaling coarse soil moisture observations of the SMOS, SMAP and ASCAT missions. Downscaling SMAP data by a field capacity proxy indicates adequate accuracy of the sub-grid soil moisture patterns.

Running GCM physics and dynamics on different grids: Algorithm and tests

NASA Astrophysics Data System (ADS)

Molod, A.

2006-12-01

The major drawback in the use of sigma coordinates in atmospheric GCMs, namely the error in the pressure gradient term near sloping terrain, leaves the use of eta coordinates an important alternative. A central disadvantage of an eta coordinate, the inability to retain fine resolution in the vertical as the surface rises above sea level, is addressed here. An `alternate grid' technique is presented which allows the tendencies of state variables due to the physical parameterizations to be computed on a vertical grid (the `physics grid') which retains fine resolution near the surface, while the remaining terms in the equations of motion are computed using an eta coordinate (the `dynamics grid') with coarser vertical resolution. As a simple test of the technique a set of perpetual equinox experiments using a simplified lower boundary condition with no land and no topography were performed. The results show that for both low and high resolution alternate grid experiments, much of the benefit of increased vertical resolution for the near surface meridional wind (and mass streamfield) can be realized by enhancing the vertical resolution of the `physics grid' in the manner described here. In addition, approximately half of the increase in zonal jet strength seen with increased vertical resolution can be realized using the `alternate grid' technique. A pair of full GCM experiments with realistic lower boundary conditions and topography were also performed. It is concluded that the use of the `alternate grid' approach offers a promising way forward to alleviate a central problem associated with the use of the eta coordinate in atmospheric GCMs.

Quantification of marine aerosol subgrid variability and its correlation with clouds based on high-resolution regional modeling: Quantifying Aerosol Subgrid Variability

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

Lin, Guangxing; Qian, Yun; Yan, Huiping

One limitation of most global climate models (GCMs) is that with the horizontal resolutions they typically employ, they cannot resolve the subgrid variability (SGV) of clouds and aerosols, adding extra uncertainties to the aerosol radiative forcing estimation. To inform the development of an aerosol subgrid variability parameterization, here we analyze the aerosol SGV over the southern Pacific Ocean simulated by the high-resolution Weather Research and Forecasting model coupled to Chemistry. We find that within a typical GCM grid, the aerosol mass subgrid standard deviation is 15% of the grid-box mean mass near the surface on a 1 month mean basis.more » The fraction can increase to 50% in the free troposphere. The relationships between the sea-salt mass concentration, meteorological variables, and sea-salt emission rate are investigated in both the clear and cloudy portion. Under clear-sky conditions, marine aerosol subgrid standard deviation is highly correlated with the standard deviations of vertical velocity, cloud water mixing ratio, and sea-salt emission rates near the surface. It is also strongly connected to the grid box mean aerosol in the free troposphere (between 2 km and 4 km). In the cloudy area, interstitial sea-salt aerosol mass concentrations are smaller, but higher correlation is found between the subgrid standard deviations of aerosol mass and vertical velocity. Additionally, we find that decreasing the model grid resolution can reduce the marine aerosol SGV but strengthen the correlations between the aerosol SGV and the total water mixing ratio (sum of water vapor, cloud liquid, and cloud ice mixing ratios).« less

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

MODELING AIR TOXICS AND PM 2.5 CONCENTRATION FIELDS AS A MEANS FOR FACILITATING HUMAN EXPOSURE ASSESSMENTS

EPA Science Inventory

The capability of the US EPA Models-3/Community Multiscale Air Quality (CMAQ) modeling system is extended to provide gridded ambient air quality concentration fields at fine scales. These fields will drive human exposure to air toxics and fine particulate matter (PM2.5) models...

Impact of Variable SST on Simulated Warm Season Precipitation

NASA Astrophysics Data System (ADS)

Saleeby, S. M.; Cotton, W. R.

2007-05-01

The Colorado State University - Regional Atmospheric Modeling System (CSU-RAMS) is being used to examine the variability in monsoon-related warm season precipitation over Mexico and the United States due to variability in SST. Given recent improvements and increased resolution in satellite derived SSTs it is pertinent to examine the sensitivity of the RAMS model to the variety of SST data sources that are available. In particular, we are examining this dependence across continental scales over the full warm season, as well as across the regional scale centered around the Gulf of California on time scales of individual surge events. In this study we performed an ensemble of simulations that include the 2002, 2003, and 2004 warm seasons with use of the Climatology, Reynold's, AVHRR, and MODIS SSTs. From the seasonal 90-day simulations with 30km grid spacing, it was found that variations in surface latent heat flux are directly linked to differences in SST. Regions with cooler (warmer) SST have decreased (increased) moisture flux from the ocean which is in proportion to the magnitude of the SST difference. Over the eastern Pacific, differences in low-level horizontal moisture flux show a general trend toward reduced fluxes over cooler waters and very little inland impact. Over the Gulf of Mexico, however, there is substantial variability for each dataset comparison, despite having only limited variability among the SST data. Causes of this unexpected variability are not straight-forward. Precipitation impacts are greatest near the southern coast of Mexico and along the Sierra Madres. Precipitation variability over the CONUS is rather chaotic and is limited to areas impacted by the Gulf of Mexico or monsoon convection. Another unexpected outcome is the lack of variability in areas near the northern Gulf of California where SST and latent heat flux variability is a maximum. From the 7-day surge period simulations at 7km grid spacing, we found that SST differences on the higher resolution nested grid reveal fine scale variability that is otherwise smoothed out or unapparent on the coarser grid. Unlike the coarse grid, the latent heat flux, temperature, and moisture transport differences on the fine grid reveal an inland impact. This is likely due to fine scale variability in onshore moisture transport and sea- breeze circulations which may alter monsoonal convection and precipitation. However, only the largest SST differences (spatially and in magnitude) tend to invoke large, coherent responses in moisture flux. The SST variability at high resolution produces relatively large differences in precipitation that are focused along the slopes of the SMO, with a tendency toward greater variability along the western slope adjacent to the coast. The precipitation differences are of fine resolution, with variability of +/- 30 mm (over 5 days) along the length of the SMO. Variability on the fine grid also invokes precipitation changes over AZ/NM that are not resolved on the coarse grid. Vertical cross-sections examined along the GoC during the surge episode revealed variations in the moisture and temperature structure of the surge. The cooler SSTs in the climatological dataset produced the greatest variability compared to the other datasets. The surge produced from climatology SSTs was nearly 5g/kg drier and up to 4°C cooler compared to surges influenced by the SST datasets. The overall northward propagation of the surge appeared unaffected by the SSTs.

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

NASA Astrophysics Data System (ADS)

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

2012-12-01

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

The numerical modeling the sensitivity of coastal wind and ozone concentration to different SST forcing

NASA Astrophysics Data System (ADS)

Choi, Hyun-Jung; Lee, Hwa Woon; Jeon, Won-Bae; Lee, Soon-Hwan

2012-01-01

This study evaluated an atmospheric and air quality model of the spatial variability in low-level coastal winds and ozone concentration, which are affected by sea surface temperature (SST) forcing with different thermal gradients. Several numerical experiments examined the effect of sea surface SST forcing on the coastal atmosphere and air quality. In this study, the RAMS-CAMx model was used to estimate the sensitivity to two different resolutions of SST forcing during the episode day as well as to simulate the low-level coastal winds and ozone concentration over a complex coastal area. The regional model reproduced the qualitative effect of SST forcing and thermal gradients on the coastal flow. The high-resolution SST derived from NGSST-O (New Generation Sea Surface Temperature Open Ocean) forcing to resolve the warm SST appeared to enhance the mean response of low-level winds to coastal regions. These wind variations have important implications for coastal air quality. A higher ozone concentration was forecasted when SST data with a high resolution was used with the appropriate limitation of temperature, regional wind circulation, vertical mixing height and nocturnal boundary layer (NBL) near coastal areas.

High resolution simulations of a variable HH jet

NASA Astrophysics Data System (ADS)

Raga, A. C.; de Colle, F.; Kajdič, P.; Esquivel, A.; Cantó, J.

2007-04-01

Context: In many papers, the flows in Herbig-Haro (HH) jets have been modeled as collimated outflows with a time-dependent ejection. In particular, a supersonic variability of the ejection velocity leads to the production of "internal working surfaces" which (for appropriate forms of the time-variability) can produce emitting knots that resemble the chains of knots observed along HH jets. Aims: In this paper, we present axisymmetric simulations of an "internal working surface" in a radiative jet (produced by an ejection velocity variability). We concentrate on a given parameter set (i.e., on a jet with a constante ejection density, and a sinusoidal velocity variability with a 20 yr period and a 40 km s-1 half-amplitude), and carry out a study of the behaviour of the solution for increasing numerical resolutions. Methods: In our simulations, we solve the gasdynamic equations together with a 17-species atomic/ionic network, and we are therefore able to compute emission coefficients for different emission lines. Results: We compute 3 adaptive grid simulations, with 20, 163 and 1310 grid points (at the highest grid resolution) across the initial jet radius. From these simulations we see that successively more complex structures are obtained for increasing numerical resolutions. Such an effect is seen in the stratifications of the flow variables as well as in the predicted emission line intensity maps. Conclusions: .We find that while the detailed structure of an internal working surface depends on resolution, the predicted emission line luminosities (integrated over the volume of the working surface) are surprisingly stable. This is definitely good news for the future computation of predictions from radiative jet models for carrying out comparisons with observations of HH objects.

Influence of high-resolution surface databases on the modeling of local atmospheric circulation systems

NASA Astrophysics Data System (ADS)

Paiva, L. M. S.; Bodstein, G. C. R.; Pimentel, L. C. G.

2014-08-01

Large-eddy simulations are performed using the Advanced Regional Prediction System (ARPS) code at horizontal grid resolutions as fine as 300 m to assess the influence of detailed and updated surface databases on the modeling of local atmospheric circulation systems of urban areas with complex terrain. Applications to air pollution and wind energy are sought. These databases are comprised of 3 arc-sec topographic data from the Shuttle Radar Topography Mission, 10 arc-sec vegetation-type data from the European Space Agency (ESA) GlobCover project, and 30 arc-sec leaf area index and fraction of absorbed photosynthetically active radiation data from the ESA GlobCarbon project. Simulations are carried out for the metropolitan area of Rio de Janeiro using six one-way nested-grid domains that allow the choice of distinct parametric models and vertical resolutions associated to each grid. ARPS is initialized using the Global Forecasting System with 0.5°-resolution data from the National Center of Environmental Prediction, which is also used every 3 h as lateral boundary condition. Topographic shading is turned on and two soil layers are used to compute the soil temperature and moisture budgets in all runs. Results for two simulated runs covering three periods of time are compared to surface and upper-air observational data to explore the dependence of the simulations on initial and boundary conditions, grid resolution, topographic and land-use databases. Our comparisons show overall good agreement between simulated and observational data, mainly for the potential temperature and the wind speed fields, and clearly indicate that the use of high-resolution databases improves significantly our ability to predict the local atmospheric circulation.

Modelling two-way interactions between atmospheric pollution and weather using high-resolution GEM-MACH

NASA Astrophysics Data System (ADS)

Makar, Paul; Gong, Wanmin; Pabla, Balbir; Cheung, Philip; Milbrandt, Jason; Gravel, Sylvie; Moran, Michael; Gilbert, Samuel; Zhang, Junhua; Zheng, Qiong

2013-04-01

The Global Environmental Multiscale (GEM) model is the source of the Canadian government's operational numerical weather forecast guidance, and GEM-MACH is the Canadian operational air-quality forecast model. GEM-MACH comprises GEM and the 'Modelling Air-quality and Chemistry' module, a gas-phase, aqueous-phase and aerosol chemistry and microphysics subroutine package called from within GEM's physics module. The present operational GEM-MACH model is "on-line" (both chemistry and meteorology are part of the same modelling structure) but is not fully coupled (weather variables are provided as inputs to the chemistry, but the chemical variables are not used to modify the weather). In this work, we describe modifications made to GEM-MACH as part of the 2nd phase of the Air Quality Model Evaluation International Initiative, in order to bring the model to a fully coupled status and present the results of initial tests comparing uncoupled and coupled versions of the model to observations for a high-resolution forecasting system. Changes to GEM's cloud microphysics and radiative transfer packages were carried out to allow two-way coupling. The cloud microphysics package used here is the Milbrandt-Yau 2-moment (MY2) bulk microphysics scheme, which solves prognostic equations for the total droplet number concentration and the mass mixing ratios of six hydrometeor categories. Here, we have replaced the original cloud condensation nucleation parameterization of MY2 (empirically relating supersaturation and CCN number) with the aerosol activation scheme of Abdul-Razzak and Ghan (2002). The latter scheme makes use of the particle size and speciation distribution of GEM-MACH's chemistry code as well as meteorological inputs to predict the number of aerosol particles activated to form cloud droplets, which is then used in the MY2 microphysics. The radiative transfer routines of GEM assume a default constant concentration aerosol profile between the surface and 1500m, and a single set of optical properties for extinction, single scattering albedo, and asymmetry factor. Ozone in GEM is taken from a default 2D (latitude-height) monthly climatology. We have replaced the ozone below the model top with the ozone calculated from GEM-MACH's chemistry, and the default optical parameters associated with particulate matter have been replaced by those calculated with a Mie scattering algorithm. These changes were found to have a significant local impact on both weather and air-quality predictions for short-term test runs of 24 hours duration. In that particular case, the maximum number concentration of cloud droplets decreased by an order of magnitude, while the number of raindrops increased by an order of magnitude and changed in spatial distribution, but surface rainfall was found to decrease. The differences in meteorology had a profound effect on local pollutant plume concentrations at specific locations and times. We compare results over a longer time period, using two parallel forecast systems, one with feedbacks between meteorology and chemistry, one without. Both nest GEM-MACH from a North American domain (10 km horizontal grid spacing) to a 1535 x 1360 km, 2.5 km domain. These systems will be evaluated against monitoring networks within the high resolution domain.

Validation of WRF-Chem air quality simulations in the Netherlands at high resolution

NASA Astrophysics Data System (ADS)

Hilboll, A.; Lowe, D.; Kuenen, J. J. P.; Denier Van Der Gon, H.; Vrekoussis, M.

2017-12-01

Air pollution is the single most important environmental hazard for publichealth, and especially nitrogen dioxide (NO2) plays a key role in air qualityresearch. With the aim of improving the quality and reproducibility ofmeasurements of NO2 vertical distribution from MAX-DOAS instruments, theCINDI-2 campaign was held in Cabauw (NL) in September 2016.The measurement site was rural, but surrounded by several major pollutioncenters. Due to this spatial heterogeneity of emissions, as well as themeteorological conditions, high spatial and temporal variability in NO2 mixingratios were observed.Air quality models used in the analysis of the measured data must have highspatial resolution in order to resolve this fine spatial structure. Thisremains a challenge even today, mostly due to the uncertainties and largespatial heterogeneity of emission data, and the need to parameterize small-scaleprocesses.In this study, we use the state-of-the-art version 3.9 of the Weather Researchand Forecasting Model with Chemistry (WRF-Chem) to simulate air pollutantconcentrations over the Netherlands, to facilitate the analysis of the CINDI-2NO2 measurements. The model setup contains three nested domains withhorizontal resolutions of 15, 3, and 1 km. Anthropogenic emissions are takenfrom the TNO-MACC III inventory and, where available, from the Dutch PollutantRelease and Transfer Register (Emissieregistratie), at a spatial resolution of 7and 1 km, respectively. We use the Common Reactive Intermediates gas-phasechemical mechanism (CRIv2-R5) with the MOSAIC aerosol module.The high spatial resolution of model and emissions will allow us to resolve thestrong spatial gradients in the NO2 concentrations measured during theCINDI-2 campaign, allowing for an unprecedented level of detail in theanalysis of individual pollution sources.

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

NASA Astrophysics Data System (ADS)

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

2013-04-01

This paper reviews the results of recent observations and simulations on the thermal belt and cold air drainage, which are outstanding in local climatic phenomena in mountain areas. In a mountain valley, cold air pool and thermal belt were simulated with the Weather and Research Forecast (WRF) model and the Korea Local Analysis and Prediction System (KLAPS) to determine the impacts of planetary boundary layer (PBL) schemes and topography resolution on model performance. Using the KLAPS-WRF models, an information system was developed for 12 hour forecasting of cold air damage in orchard. This system was conducted on a three level nested grid from 1 km to 111 m horizontal resolution. Results of model runs were verified by the data from automated weather stations, which were installed at twelve sites in a valley at Yeonsuri, Yangpyeonggun, Gyeonggido to measure temperature and wind speed and direction during March to May 2012. The potential of the numerical model to simulate these local features was found to be dependent on the planetary boundary layer schemes. Statistical verification results indicate that Mellor-Yamada-Janjic (MYJ) PBL scheme was in good agreement with night time temperature, while the no-PBL scheme produced predictions similar to the day time temperature observation. Although the KLAPS-WRF system underestimates temperature in mountain areas and overestimates wind speed, it produced an accurate description of temperature, with an RMSE of 1.67 ˚C in clear daytime. Wind speed and direction were not forecasted well in precision (RMSE: 5.26 m/s and 10.12 degree). It might have been caused by the measurement uncertainty and spatial variability. Additionally, the performance of KLAPS-WRF was performed to evaluate for different terrain resolution: Topography data were improved from USGS (United States Geological Survey) 30" to NGII (National Geographic Information Institute) 10 m. The simulated results were quantitatively compared to observations and there was a significant improvement (RMSE: 2.06 ˚C -> 1.73 ˚C) in the temperature prediction in the study area. The results will provide useful guidance of grid size selection on high resolution simulation over the mountain regions in Korea.

High-Resolution Atmospheric Emission Inventory of the Argentine Enery Sector

NASA Astrophysics Data System (ADS)

Puliafito, Salvador Enrique; Castesana, Paula; Allende, David; Ruggeri, Florencia; Pinto, Sebastián; Pascual, Romina; Bolaño Ortiz, Tomás; Fernandez, Rafael Pedro

2017-04-01

This study presents a high-resolution spatially disaggregated inventory (2.5 km x 2.5 km), updated to 2014, of the main emissions from energy activities in Argentina. This inventory was created with the purpose of improving air quality regional models. The sub-sectors considered are public electricity and heat production, cement production, domestic aviation, road and rail transportation, inland navigation, residential and commercial, and fugitive emissions from refineries and fuel expenditure. The pollutants considered include greenhouse gases and ozone precursors: CO2, CH4, NOx, N2O VOC; and other gases specifically related to air quality including PM10, PM2.5, SOx, Pb and POPs. The uncertainty analysis of the inventories resulted in a variability of 3% for public electricity generation, 3-6% in the residential, commercial sector, 6-12% terrestrial transportation sector, 10-20% in oil refining and cement production according to the considered pollutant. Aviation and maritime navigation resulted in a higher variability reaching more than 60%. A comparison with the international emission inventory EDGAR shows disagreements in the spatial distribution of emissions, probably due to the finer resolution of the map presented here, particularly as a result of the use of new spatially disaggregated data of higher resolution that is currently available.

Sensitivity to grid resolution in the ability of a chemical transport model to simulate observed oxidant chemistry under high-isoprene conditions

NASA Astrophysics Data System (ADS)

Yu, Karen; Jacob, Daniel J.; Fisher, Jenny A.; Kim, Patrick S.; Marais, Eloise A.; Miller, Christopher C.; Travis, Katherine R.; Zhu, Lei; Yantosca, Robert M.; Sulprizio, Melissa P.; Cohen, Ron C.; Dibb, Jack E.; Fried, Alan; Mikoviny, Tomas; Ryerson, Thomas B.; Wennberg, Paul O.; Wisthaler, Armin

2016-04-01

Formation of ozone and organic aerosol in continental atmospheres depends on whether isoprene emitted by vegetation is oxidized by the high-NOx pathway (where peroxy radicals react with NO) or by low-NOx pathways (where peroxy radicals react by alternate channels, mostly with HO2). We used mixed layer observations from the SEAC4RS aircraft campaign over the Southeast US to test the ability of the GEOS-Chem chemical transport model at different grid resolutions (0.25° × 0.3125°, 2° × 2.5°, 4° × 5°) to simulate this chemistry under high-isoprene, variable-NOx conditions. Observations of isoprene and NOx over the Southeast US show a negative correlation, reflecting the spatial segregation of emissions; this negative correlation is captured in the model at 0.25° × 0.3125° resolution but not at coarser resolutions. As a result, less isoprene oxidation takes place by the high-NOx pathway in the model at 0.25° × 0.3125° resolution (54 %) than at coarser resolution (59 %). The cumulative probability distribution functions (CDFs) of NOx, isoprene, and ozone concentrations show little difference across model resolutions and good agreement with observations, while formaldehyde is overestimated at coarse resolution because excessive isoprene oxidation takes place by the high-NOx pathway with high formaldehyde yield. The good agreement of simulated and observed concentration variances implies that smaller-scale non-linearities (urban and power plant plumes) are not important on the regional scale. Correlations of simulated vs. observed concentrations do not improve with grid resolution because finer modes of variability are intrinsically more difficult to capture. Higher model resolution leads to decreased conversion of NOx to organic nitrates and increased conversion to nitric acid, with total reactive nitrogen oxides (NOy) changing little across model resolutions. Model concentrations in the lower free troposphere are also insensitive to grid resolution. The overall low sensitivity of modeled concentrations to grid resolution implies that coarse resolution is adequate when modeling continental boundary layer chemistry for global applications.

High-resolution precipitation database for the last two centuries in Italy: climatologies and anomalies

NASA Astrophysics Data System (ADS)

Crespi, Alice; Brunetti, Michele; Maugeri, Maurizio

2017-04-01

The availability of gridded high-resolution spatial climatologies and corresponding secular records has acquired an increasing importance in the recent years both to research purposes and as decision-support tools in the management of natural resources and economical activities. High-resolution monthly precipitation climatologies for Italy were computed by gridding on a 30-arc-second-resolution Digital Elevation Model (DEM) the precipitation normals (1961-1990) obtained from a quality-controlled dataset of about 6200 stations covering the Italian surface and part of the Northern neighbouring regions. Starting from the assumption that the precipitation distribution is strongly influenced by orography, especially elevation, a local weighted linear regression (LWLR) of precipitation versus elevation was performed at each DEM cell. The regression coefficients for each cell were estimated by selecting the stations with the highest weights in which the distances and the level of similarity between the station cells and the considered grid cell, in terms of orographic features, are taken into account. An optimisation procedure was then set up in order to define, for each month and for each grid cell, the most suitable decreasing coefficients for the weighting factors which enter in the LWLR scheme. The model was validated by the comparison with the results provided by inverse distance weighting (IDW) applied both to station normals and to the residuals of a global regression of station normals versus elevation. In both cases, the LWLR leave-one-out reconstructions show the best agreement with the observed station normals, especially when considering specific station clusters (high elevation sites for example). After producing the high-resolution precipitation climatological field, the temporal component on the high-resolution grid was obtained by following the anomaly method. It is based on the assumption that the spatio-temporal structure of the signal of a meteorological variable over a certain area can be described by the superimposition of two independent fields: the climatologies and the anomalies, i.e. the departures from the normal values. The secular precipitation anomaly records were thus estimated for each cell of the grid by averaging the anomaly values of neighbouring stations, by means of Gaussian weighting functions, taking into account both the distance and the elevation differences between the stations and the considered grid cell. The local secular precipitation records were then obtained by multiplying the local estimated anomalies for the corresponding 1961-1990 normals. To compute the anomaly field, a different dataset was used by selecting the stations with the longest series and extending them both to the past, retrieving data from non-digitised archives, and to the more recent decades. In particular, after a careful procedure of updating, quality-check and homogenisation of series, this methodology was applied on two Italian areas characterised by very different orography: Sardinia region and the Alpine areas within Adda basin.

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.

High resolution dynamical downscaling of air temperature and relative humidity: performance assessment of WRF for Portugal

NASA Astrophysics Data System (ADS)

Menezes, Isilda; Pereira, Mário; Moreira, Demerval; Carvalheiro, Luís; Bugalho, Lourdes; Corte-Real, João

2017-04-01

Air temperature and relative humidity are two of the atmospheric variables with higher impact on human and natural systems, contributing to define the stress/comfortable conditions, affecting the productivity and health of the individuals as well as diminishing the resilience to other environmental hazards. Atmospheric regional models, driven by large scale forecasts from global circulation models, are the best way to reproduce such environmental conditions in high space-time resolution. This study is focused on the performance assessment of the WRF mesoscale model to perform high resolution dynamical downscaling for Portugal with three two-way nested grids, at 60 km, 20 km and 5 km horizontal resolution. The simulations of WRF models were produced with different initial and boundary forcing conditions. The NCEP-FNL Operational Global Analysis data available on 1-degree by 1-degree grid every six hours and ERA-Interim reanalyses dataset were used to drive the models. Two alternative configurations of the WRF model, including planetary boundary, layer schemes, microphysics, land-surface models, radiation schemes, were used and tested within the 5 km spatial resolution domain. Simulations of air temperature and relative humidity were produced for January and July of 2016 and compared with the observed datasets provided by the Instituto Português do Mar e da Atmosfera (IPMA) for 83 weather stations. Different performance measures of bias, precision, and accuracy were used, namely normalized bias, standard deviation, mean absolute error, root mean square error, bias of root mean square error as well as correlation based measures (e.g., coefficient of determination) and goodness of fit measures (index of agreement). Main conclusions from the obtained results reveal: (i) great similarity between the spatial patterns of the simulated and observed fields; (ii) only small differences between simulations produced with ERA-Interim and NCEP-FNL, in spite of some differences between the input variables; (iii) the tested parametrizations do not force significantly different simulation patterns; (iv) observed and simulated hourly air temperature are very well correlated (91%), presenting similar variance and a low bias over the country. Obtained results are also in good agreement with other dynamical downscaling studies for Portugal supporting the use of WRF as a regional forecast model. Acknowledgements: This work was supported by: (i) the project Interact - Integrative Research in Environment,Agro-Chain and Technology, NORTE-01-0145-FEDER-000017, research line BEST, cofinanced by FEDER/NORTE 2020; (ii) the FIREXTR project, PTDC/ATP¬GEO/0462/2014; and, (iii) European Investment Funds by FEDER/COMPETE/POCI-Operacional Competitiveness and Internacionalization Programme, under Project POCI-01-0145-FEDER-006958 and National Funds by FCT - Portuguese Foundation for Science and Technology, under the project UID/AGR/04033.

Testing a high resolution CO2 and CO emission inventory against atmospheric observations in Salt Lake City, Utah for policy applications

NASA Astrophysics Data System (ADS)

Mendoza, D. L.; Lin, J. C.; Mitchell, L.; Gurney, K. R.; Patarasuk, R.; Mallia, D. V.; Fasoli, B.; Bares, R.; Catharine, D.; O'Keeffe, D.; Song, Y.; Huang, J.; Horel, J.; Crosman, E.; Hoch, S.; Ehleringer, J. R.

2016-12-01

We address the need for robust highly-resolved emissions and trace gas concentration data required for planning purposes and policy development aimed at managing pollutant sources. Adverse health effects resulting from urban pollution exposure are the result of proximity to emission sources and atmospheric mixing, necessitating models with high spatial and temporal resolution. As urban emission sources co-emit carbon dioxide (CO2) and criteria air pollutants (CAPs), efforts to reduce specific pollutants would synergistically reduce others. We present a contemporary (2010-2015) emissions inventory and modeled CO2 and carbon monoxide (CO) concentrations for Salt Lake County, Utah. We compare emissions transported by a dispersion model against stationary measurement data and present a systematic quantification of uncertainties. The emissions inventory for CO2 is based on the Hestia emissions data inventory that resolves emissions at hourly, building and road-link resolutions, as well as on an hourly gridded scale. The emissions were scaled using annual Energy Information Administration (EIA) fuel consumption data. We derived a CO emissions inventory using methods similar to Hestia, downscaling total county emissions from the 2011 Environmental Protection Agency's (EPA) National Emissions Inventory (NEI). The gridded CO emissions were compared against the Hestia CO2 gridded data to characterize spatial similarities and differences between them. Correlations were calculated at multiple scales of aggregation. The Stochastic Time-Inverted Lagrangian Trasport (STILT) dispersion model was used to transport emissions and estimate pollutant concentrations at an hourly resolution. Modeled results were compared against stationary measurements in the Salt Lake County area. This comparison highlights spatial locations and hours of high variability and uncertainty. Sensitivity to biological fluxes as well as to specific economic sectors was tested by varying their contributions to modeled concentrations and calibrating their emissions.

Verification of the NWP models operated at ICM, Poland

NASA Astrophysics Data System (ADS)

Melonek, Malgorzata

2010-05-01

Interdisciplinary Centre for Mathematical and Computational Modelling, University of Warsaw (ICM) started its activity in the field of NWP in May 1997. Since this time the numerical weather forecasts covering Central Europe have been routinely published on our publicly available website. First NWP model used in ICM was hydrostatic Unified Model developed by the UK Meteorological Office. It was a mesoscale version with horizontal resolution of 17 km and 31 levels in vertical. At present two NWP non-hydrostatic models are running in quasi-operational regime. The main new UM model with 4 km horizontal resolution, 38 levels in vertical and forecats range of 48 hours is running four times a day. Second, the COAMPS model (Coupled Ocean/Atmosphere Mesoscale Prediction System) developed by the US Naval Research Laboratory, configured with the three nested grids (with coresponding resolutions of 39km, 13km and 4.3km, 30 vertical levels) are running twice a day (for 00 and 12 UTC). The second grid covers Central Europe and has forecast range of 84 hours. Results of the both NWP models, ie. COAMPS computed on 13km mesh resolution and UM, are verified against observations from the Polish synoptic stations. Verification uses surface observations and nearest grid point forcasts. Following meteorological elements are verified: air temperature at 2m, mean sea level pressure, wind speed and wind direction at 10 m and 12 hours accumulated precipitation. There are presented different statistical indices. For continous variables Mean Error(ME), Mean Absolute Error (MAE) and Root Mean Squared Error (RMSE) in 6 hours intervals are computed. In case of precipitation the contingency tables for different thresholds are computed and some of the verification scores such as FBI, ETS, POD, FAR are graphically presented. The verification sample covers nearly one year.

Wireless Distributed Environmental Sensor Networks for Air Pollution Measurement-The Promise and the Current Reality.

PubMed

Broday, David M

2017-10-02

The evaluation of the effects of air pollution on public health and human-wellbeing requires reliable data. Standard air quality monitoring stations provide accurate measurements of airborne pollutant levels, but, due to their sparse distribution, they cannot capture accurately the spatial variability of air pollutant concentrations within cities. Dedicated in-depth field campaigns have dense spatial coverage of the measurements but are held for relatively short time periods. Hence, their representativeness is limited. Moreover, the oftentimes integrated measurements represent time-averaged records. Recent advances in communication and sensor technologies enable the deployment of dense grids of Wireless Distributed Environmental Sensor Networks for air quality monitoring, yet their capability to capture urban-scale spatiotemporal pollutant patterns has not been thoroughly examined to date. Here, we summarize our studies on the practicalities of using data streams from sensor nodes for air quality measurement and the required methods to tune the results to different stakeholders and applications. We summarize the results from eight cities across Europe, five sensor technologies-three stationary (with one tested also while moving) and two personal sensor platforms, and eight ambient pollutants. Overall, few sensors showed an exceptional and consistent performance, which can shed light on the fine spatiotemporal urban variability of pollutant concentrations. Stationary sensor nodes were more reliable than personal nodes. In general, the sensor measurements tend to suffer from the interference of various environmental factors and require frequent calibrations. This calls for the development of suitable field calibration procedures, and several such in situ field calibrations are presented.

Wireless Distributed Environmental Sensor Networks for Air Pollution Measurement—The Promise and the Current Reality

PubMed Central

2017-01-01

The evaluation of the effects of air pollution on public health and human-wellbeing requires reliable data. Standard air quality monitoring stations provide accurate measurements of airborne pollutant levels, but, due to their sparse distribution, they cannot capture accurately the spatial variability of air pollutant concentrations within cities. Dedicated in-depth field campaigns have dense spatial coverage of the measurements but are held for relatively short time periods. Hence, their representativeness is limited. Moreover, the oftentimes integrated measurements represent time-averaged records. Recent advances in communication and sensor technologies enable the deployment of dense grids of Wireless Distributed Environmental Sensor Networks for air quality monitoring, yet their capability to capture urban-scale spatiotemporal pollutant patterns has not been thoroughly examined to date. Here, we summarize our studies on the practicalities of using data streams from sensor nodes for air quality measurement and the required methods to tune the results to different stakeholders and applications. We summarize the results from eight cities across Europe, five sensor technologies-three stationary (with one tested also while moving) and two personal sensor platforms, and eight ambient pollutants. Overall, few sensors showed an exceptional and consistent performance, which can shed light on the fine spatiotemporal urban variability of pollutant concentrations. Stationary sensor nodes were more reliable than personal nodes. In general, the sensor measurements tend to suffer from the interference of various environmental factors and require frequent calibrations. This calls for the development of suitable field calibration procedures, and several such in situ field calibrations are presented. PMID:28974042

Improving spatio-temporal model estimation of satellite-derived PM2.5 concentrations: Implications for public health

NASA Astrophysics Data System (ADS)

Barik, M. G.; Al-Hamdan, M. Z.; Crosson, W. L.; Yang, C. A.; Coffield, S. R.

2017-12-01

Satellite-derived environmental data, available in a range of spatio-temporal scales, are contributing to the growing use of health impact assessments of air pollution in the public health sector. Models developed using correlation of Moderate Resolution Imaging Spectrometer (MODIS) Aerosol Optical Depth (AOD) with ground measurements of fine particulate matter less than 2.5 microns (PM2.5) are widely applied to measure PM2.5 spatial and temporal variability. In the public health sector, associations of PM2.5 with respiratory and cardiovascular diseases are often investigated to quantify air quality impacts on these health concerns. In order to improve predictability of PM2.5 estimation using correlation models, we have included meteorological variables, higher-resolution AOD products and instantaneous PM2.5 observations into statistical estimation models. Our results showed that incorporation of high-resolution (1-km) Multi-Angle Implementation of Atmospheric Correction (MAIAC)-generated MODIS AOD, meteorological variables and instantaneous PM2.5 observations improved model performance in various parts of California (CA), USA, where single variable AOD-based models showed relatively weak performance. In this study, we further asked whether these improved models actually would be more successful for exploring associations of public health outcomes with estimated PM2.5. To answer this question, we geospatially investigated model-estimated PM2.5's relationship with respiratory and cardiovascular diseases such as asthma, high blood pressure, coronary heart disease, heart attack and stroke in CA using health data from the Centers for Disease Control and Prevention (CDC)'s Wide-ranging Online Data for Epidemiologic Research (WONDER) and the Behavioral Risk Factor Surveillance System (BRFSS). PM2.5 estimation from these improved models have the potential to improve our understanding of associations between public health concerns and air quality.

File Specification for GEOS-5 FP (Forward Processing)

NASA Technical Reports Server (NTRS)

Lucchesi, R.

2013-01-01

The GEOS-5 FP Atmospheric Data Assimilation System (GEOS-5 ADAS) uses an analysis developed jointly with NOAA's National Centers for Environmental Prediction (NCEP), which allows the Global Modeling and Assimilation Office (GMAO) to take advantage of the developments at NCEP and the Joint Center for Satellite Data Assimilation (JCSDA). The GEOS-5 AGCM uses the finite-volume dynamics (Lin, 2004) integrated with various physics packages (e.g, Bacmeister et al., 2006), under the Earth System Modeling Framework (ESMF) including the Catchment Land Surface Model (CLSM) (e.g., Koster et al., 2000). The GSI analysis is a three-dimensional variational (3DVar) analysis applied in grid-point space to facilitate the implementation of anisotropic, inhomogeneous covariances (e.g., Wu et al., 2002; Derber et al., 2003). The GSI implementation for GEOS-5 FP incorporates a set of recursive filters that produce approximately Gaussian smoothing kernels and isotropic correlation functions. The GEOS-5 ADAS is documented in Rienecker et al. (2008). More recent updates to the model are presented in Molod et al. (2011). The GEOS-5 system actively assimilates roughly 2 × 10(exp 6) observations for each analysis, including about 7.5 × 10(exp 5) AIRS radiance data. The input stream is roughly twice this volume, but because of the large volume, the data are thinned commensurate with the analysis grid to reduce the computational burden. Data are also rejected from the analysis through quality control procedures designed to detect, for example, the presence of cloud. To minimize the spurious periodic perturbations of the analysis, GEOS-5 FP uses the Incremental Analysis Update (IAU) technique developed by Bloom et al. (1996). More details of this procedure are given in Appendix A. The assimilation is performed at a horizontal resolution of 0.3125-degree longitude by 0.25- degree latitude and at 72 levels, extending to 0.01 hPa. All products are generated at the native resolution of the horizontal grid. The majority of data products are time-averaged, but four instantaneous products are also available. Hourly data intervals are used for two-dimensional products, while 3-hourly intervals are used for three-dimensional products. These may be on the model's native 72-layer vertical grid or at 42 pressure surfaces extending to 0.1 hPa. This document describes the gridded output files produced by the GMAO near real-time operational FP, using the most recent version of the GEOS-5 assimilation system. Additional details about variables listed in this file specification can be found in a separate document, the GEOS-5 File Specification Variable Definition Glossary. Documentation about the current access methods for products described in this document can be found on the GMAO products page: http://gmao.gsfc.nasa.gov/products/.

File Specification for GEOS-5 FP-IT (Forward Processing for Instrument Teams)

NASA Technical Reports Server (NTRS)

Lucchesi, R.

2013-01-01

The GEOS-5 FP-IT Atmospheric Data Assimilation System (GEOS-5 ADAS) uses an analysis developed jointly with NOAA's National Centers for Environmental Prediction (NCEP), which allows the Global Modeling and Assimilation Office (GMAO) to take advantage of the developments at NCEP and the Joint Center for Satellite Data Assimilation (JCSDA). The GEOS-5 AGCM uses the finite-volume dynamics (Lin, 2004) integrated with various physics packages (e.g, Bacmeister et al., 2006), under the Earth System Modeling Framework (ESMF) including the Catchment Land Surface Model (CLSM) (e.g., Koster et al., 2000). The GSI analysis is a three-dimensional variational (3DVar) analysis applied in grid-point space to facilitate the implementation of anisotropic, inhomogeneous covariances (e.g., Wu et al., 2002; Derber et al., 2003). The GSI implementation for GEOS-5 FP-IT incorporates a set of recursive filters that produce approximately Gaussian smoothing kernels and isotropic correlation functions. The GEOS-5 ADAS is documented in Rienecker et al. (2008). More recent updates to the model are presented in Molod et al. (2011). The GEOS-5 system actively assimilates roughly 2 × 10(exp 6) observations for each analysis, including about 7.5 × 10(exp 5) AIRS radiance data. The input stream is roughly twice this volume, but because of the large volume, the data are thinned commensurate with the analysis grid to reduce the computational burden. Data are also rejected from the analysis through quality control procedures designed to detect, for example, the presence of cloud. To minimize the spurious periodic perturbations of the analysis, GEOS-5 FP-IT uses the Incremental Analysis Update (IAU) technique developed by Bloom et al. (1996). More details of this procedure are given in Appendix A. The analysis is performed at a horizontal resolution of 0.625-degree longitude by 0.5-degree latitude and at 72 levels, extending to 0.01 hPa. All products are generated at the native resolution of the horizontal grid. The majority of data products are time-averaged, but four instantaneous products are also available. Hourly data intervals are used for two-dimensional products, while 3-hourly intervals are used for three-dimensional products. These may be on the model's native 72-layer vertical grid or at 42 pressure surfaces extending to 0.1 hPa. This document describes the gridded output files produced by the GMAO near real-time operational GEOS-5 FP-IT processing in support of the EOS instrument teams. Additional details about variables listed in this file specification can be found in a separate document, the GEOS-5 File Specification Variable Definition Glossary.

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

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

He, Jian; Zhang, Yang; Wang, Kai

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

SIMULATION OF DISPERSION OF A POWER PLANT PLUME USING AN ADAPTIVE GRID ALGORITHM

EPA Science Inventory

A new dynamic adaptive grid algorithm has been developed for use in air quality modeling. This algorithm uses a higher order numerical scheme?the piecewise parabolic method (PPM)?for computing advective solution fields; a weight function capable of promoting grid node clustering ...

Mapping air quality zones for coastal urban centers.

PubMed

Freeman, Brian; Gharabaghi, Bahram; Thé, Jesse; Munshed, Mohammad; Faisal, Shah; Abdullah, Meshal; Al Aseed, Athari

2017-05-01

This study presents a new method that incorporates modern air dispersion models allowing local terrain and land-sea breeze effects to be considered along with political and natural boundaries for more accurate mapping of air quality zones (AQZs) for coastal urban centers. This method uses local coastal wind patterns and key urban air pollution sources in each zone to more accurately calculate air pollutant concentration statistics. The new approach distributes virtual air pollution sources within each small grid cell of an area of interest and analyzes a puff dispersion model for a full year's worth of 1-hr prognostic weather data. The difference of wind patterns in coastal and inland areas creates significantly different skewness (S) and kurtosis (K) statistics for the annually averaged pollutant concentrations at ground level receptor points for each grid cell. Plotting the S-K data highlights grouping of sources predominantly impacted by coastal winds versus inland winds. The application of the new method is demonstrated through a case study for the nation of Kuwait by developing new AQZs to support local air management programs. The zone boundaries established by the S-K method were validated by comparing MM5 and WRF prognostic meteorological weather data used in the air dispersion modeling, a support vector machine classifier was trained to compare results with the graphical classification method, and final zones were compared with data collected from Earth observation satellites to confirm locations of high-exposure-risk areas. The resulting AQZs are more accurate and support efficient management strategies for air quality compliance targets effected by local coastal microclimates. A novel method to determine air quality zones in coastal urban areas is introduced using skewness (S) and kurtosis (K) statistics calculated from grid concentrations results of air dispersion models. The method identifies land-sea breeze effects that can be used to manage local air quality in areas of similar microclimates.

How does mesoscale impact deep convection? Answers from ensemble Northwestern Mediterranean Sea simulations.

NASA Astrophysics Data System (ADS)

Waldman, Robin; Herrmann, Marine; Somot, Samuel; Arsouze, Thomas; Benshila, Rachid; Bosse, Anthony; Chanut, Jérôme; Giordani, Hervé; Pennel, Romain; Sevault, Florence; Testor, Pierre

2017-04-01

Ocean deep convection is a major process of interaction between surface and deep ocean. The Gulf of Lions is a well-documented deep convection area in the Mediterranean Sea, and mesoscale dynamics is a known factor impacting this phenomenon. However, previous modelling studies don't allow to address the robustness of its impact with respect to the physical configuration and ocean intrinsic variability. In this study, the impact of mesoscale on ocean deep convection in the Gulf of Lions is investigated using a multi-resolution ensemble simulation of the northwestern Mediterranean sea. The eddy-permitting Mediterranean model NEMOMED12 (6km resolution) is compared to its eddy-resolving counterpart with the 2-way grid refinement AGRIF in the northwestern Mediterranean (2km resolution). We focus on the well-documented 2012-2013 period and on the multidecadal timescale (1979-2013). The impact of mesoscale on deep convection is addressed in terms of its mean and variability, its impact on deep water transformations and on associated dynamical structures. Results are interpreted by diagnosing regional mean and eddy circulation and using buoyancy budgets. We find a mean inhibition of deep convection by mesoscale with large interannual variability. It is associated with a large impact on mean and transient circulation and a large air-sea flux feedback.

Monolayer-crystal streptavidin support films provide an internal standard of cryo-EM image quality

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

Han, Bong-Gyoon; Watson, Zoe; Cate, Jamie H. D.

Analysis of images of biotinylated Escherichia coli 70S ribosome particles, bound to streptavidin affinity grids, demonstrates that the image-quality of particles can be predicted by the image-quality of the monolayer crystalline support film. Also, the quality of the Thon rings is a good predictor of the image-quality of particles, but only when images of the streptavidin crystals extend to relatively high resolution. When the estimated resolution of streptavidin was 5 Å or worse, for example, the ribosomal density map obtained from 22,697 particles went to only 9.5 Å, while the resolution of the map reached 4.0 Å for the samemore » number of particles, when the estimated resolution of streptavidin crystal was 4 Å or better. It thus is easy to tell which images in a data set ought to be retained for further work, based on the highest resolution seen for Bragg peaks in the computed Fourier transforms of the streptavidin component. The refined density map obtained from 57,826 particles obtained in this way extended to 3.6 Å, a marked improvement over the value of 3.9 Å obtained previously from a subset of 52,433 particles obtained from the same initial data set of 101,213 particles after 3-D classification. These results are consistent with the hypothesis that interaction with the air-water interface can damage particles when the sample becomes too thin. Finally, streptavidin monolayer crystals appear to provide a good indication of when that is the case.« less

Distributional benefit analysis of a national air quality rule.

PubMed

Post, Ellen S; Belova, Anna; Huang, Jin

2011-06-01

Under Executive Order 12898, the U.S. Environmental Protection Agency (EPA) must perform environmental justice (EJ) reviews of its rules and regulations. EJ analyses address the hypothesis that environmental disamenities are experienced disproportionately by poor and/or minority subgroups. Such analyses typically use communities as the unit of analysis. While community-based approaches make sense when considering where polluting sources locate, they are less appropriate for national air quality rules affecting many sources and pollutants that can travel thousands of miles. We compare exposures and health risks of EJ-identified individuals rather than communities to analyze EPA's Heavy Duty Diesel (HDD) rule as an example national air quality rule. Air pollutant exposures are estimated within grid cells by air quality models; all individuals in the same grid cell are assigned the same exposure. Using an inequality index, we find that inequality within racial/ethnic subgroups far outweighs inequality between them. We find, moreover, that the HDD rule leaves between-subgroup inequality essentially unchanged. Changes in health risks depend also on subgroups' baseline incidence rates, which differ across subgroups. Thus, health risk reductions may not follow the same pattern as reductions in exposure. These results are likely representative of other national air quality rules as well.

Evaluation of arctic multibeam sonar data quality using nadir crossover error analysis and compilation of a full-resolution data product

NASA Astrophysics Data System (ADS)

Flinders, Ashton F.; Mayer, Larry A.; Calder, Brian A.; Armstrong, Andrew A.

2014-05-01

We document a new high-resolution multibeam bathymetry compilation for the Canada Basin and Chukchi Borderland in the Arctic Ocean - United States Arctic Multibeam Compilation (USAMBC Version 1.0). The compilation preserves the highest native resolution of the bathymetric data, allowing for more detailed interpretation of seafloor morphology than has been previously possible. The compilation was created from multibeam bathymetry data available through openly accessible government and academic repositories. Much of the new data was collected during dedicated mapping cruises in support of the United States effort to map extended continental shelf regions beyond the 200 nm Exclusive Economic Zone. Data quality was evaluated using nadir-beam crossover-error statistics, making it possible to assess the precision of multibeam depth soundings collected from a wide range of vessels and sonar systems. Data were compiled into a single high-resolution grid through a vertical stacking method, preserving the highest quality data source in any specific grid cell. The crossover-error analysis and method of data compilation can be applied to other multi-source multibeam data sets, and is particularly useful for government agencies targeting extended continental shelf regions but with limited hydrographic capabilities. Both the gridded compilation and an easily distributed geospatial PDF map are freely available through the University of New Hampshire's Center for Coastal and Ocean Mapping (ccom.unh.edu/theme/law-sea). The geospatial pdf is a full resolution, small file-size product that supports interpretation of Arctic seafloor morphology without the need for specialized gridding/visualization software.

Spatiotemporal comparison of highly-resolved emissions and concentrations of carbon dioxide and criteria pollutants in Salt Lake City, Utah for health and policy applications

NASA Astrophysics Data System (ADS)

Mendoza, D. L.; Lin, J. C.; Mitchell, L.; Gurney, K. R.; Patarasuk, R.; Fasoli, B.; Bares, R.; o'Keefe, D.; Song, T.; Huang, J.; Horel, J.; Crosman, E.; Ehleringer, J. R.

2015-12-01

This study addresses the need for robust highly-resolved emissions and concentration data required for planning purposes and policy development aimed at managing pollutant sources. Adverse health effects resulting from urban pollution exposure are dependent on proximity to emission sources and atmospheric mixing, necessitating models with high spatial and temporal resolution. As urban emission sources co-emit carbon dioxide (CO2) and criteria pollutants (CAPs), efforts to reduce specific pollutants would synergistically reduce others. We present emissions inventories and modeled concentrations for CO2 and CAPs: carbon monoxide (CO), lead (Pb), nitrogen oxides (NOx), particulate matter (PM2.5 and PM10), and sulfur oxides (SOx) for Salt Lake County, Utah. We compare the resulting concentrations against stationary and mobile measurement data and present a systematic quantification of uncertainties. The emissions inventory for CO2 is based on the Hestia emissions data inventory that resolves emissions at an hourly, building and road link resolution as well as hourly gridded emissions with a 0.002o x 0.002o spatial resolution. Two methods for deriving criteria pollutant emission inventories were compared. One was constructed using methods similar to Hestia but downscales total emissions based on the 2011 National Emissions Inventory (NEI). The other used Emission Modeling Clearinghouse spatial and temporal surrogates to downscale the NEI data from annual and county-level resolution to hourly and 0.002o x 0.002o grid cells. The gridded emissions from both criteria pollutant methods were compared against the Hestia CO2 gridded data to characterize spatial similarities and differences between them. Correlations were calculated at multiple scales of aggregation. The CALPUFF dispersion model was used to transport emissions and estimate air pollutant concentrations at an hourly 0.002o x 0.002o resolution. The resulting concentrations were spatially compared in the same manner as the emissions. Modeled results were compared against stationary measurements and from equipment mounted atop a light rail car in the Salt Lake City area. The comparison between both approaches to emissions estimation and resulting concentrations highlights spatial locations and hours of high variability and uncertainty.

Application and evaluation of two air quality models for particulate matter for a southeastern U.S. episode.

PubMed

Zhang, Yang; Pun, Betty; Wu, Shiang-Yuh; Vijayaraghavan, Krish; Seigneur, Christian

2004-12-01

The Models-3 Community Multiscale Air Quality (CMAQ) Modeling System and the Particulate Matter Comprehensive Air Quality Model with extensions (PMCAMx) were applied to simulate the period June 29-July 10, 1999, of the Southern Oxidants Study episode with two nested horizontal grid sizes: a coarse resolution of 32 km and a fine resolution of 8 km. The predicted spatial variations of ozone (O3), particulate matter with an aerodynamic diameter less than or equal to 2.5 microm (PM2.5), and particulate matter with an aerodynamic diameter less than or equal to 10 microm (PM10) by both models are similar in rural areas but differ from one another significantly over some urban/suburban areas in the eastern and southern United States, where PMCAMx tends to predict higher values of O3 and PM than CMAQ. Both models tend to predict O3 values that are higher than those observed. For observed O3 values above 60 ppb, O3 performance meets the U.S. Environmental Protection Agency's criteria for CMAQ with both grids and for PMCAMx with the fine grid only. It becomes unsatisfactory for PMCAMx and marginally satisfactory for CMAQ for observed O3 values above 40 ppb. Both models predict similar amounts of sulfate (SO4(2-)) and organic matter, and both predict SO4(2-) to be the largest contributor to PM2.5. PMCAMx generally predicts higher amounts of ammonium (NH4+), nitrate (NO3-), and black carbon (BC) than does CMAQ. PM performance for CMAQ is generally consistent with that of other PM models, whereas PMCAMx predicts higher concentrations of NO3-, NH4+, and BC than observed, which degrades its performance. For PM10 and PM2.5 predictions over the southeastern U.S. domain, the ranges of mean normalized gross errors (MNGEs) and mean normalized bias are 37-43% and -33-4% for CMAQ and 50-59% and 7-30% for PMCAMx. Both models predict the largest MNGEs for NO3- (98-104% for CMAQ 138-338% for PMCAMx). The inaccurate NO3- predictions by both models may be caused by the inaccuracies in the ammonia emission inventory and the uncertainties in the gas/particle partitioning under some conditions. In addition to these uncertainties, the significant PM overpredictions by PMCAMx may be attributed to the lack of wet removal for PM and a likely underprediction in the vertical mixing during the daytime.

Urban-rural variations in air quality and health impacts in northern India

NASA Astrophysics Data System (ADS)

Karambelas, A. N.; Holloway, T.; Fiore, A. M.; Kinney, P.; DeFries, R. S.; Kiesewetter, G.; Heyes, C.

2017-12-01

Ambient air pollution in India is a severe problem, contributing to negative health impacts and early death. Ground-based monitors often used to quantify health impacts are often located in urban regions, however approximately 70% of India's population resides in rural areas. We use high-resolution concentrations from the regional Community Multi-scale Air Quality (CMAQ) model over densely-populated northern India to estimate air quality and health impacts due to anthropogenic emission sectors separately for urban and rural regions. Modeled concentrations inform relative risk calculations and exposure estimates as performed in the Global Burden of Disease. Anthropogenic emissions from the International Institute for Applied Systems Analysis (IIASA) Greenhouse Gas-Air Pollution Interactions and Synergies (GAINS) model following version 5a of the Evaluating the Climate and Air Quality Impacts of Short-Lived Pollutants project gridding structure are updated to reflect urban- and rural-specific activity information for transportation and residential combustion, and industrial and electrical generating unit location and magnitude information. We estimate 314,000 (95% Confidence Interval: 304,000—323,000) and 58,000 (CI: 39,000—70,000) adults (25 years or older) die prematurely each year from PM2.5 and O3 respectively in northern India, with the greatest impacts along the Indo-Gangetic Plain. Using urban and rural population distributions, we estimate that the majority of premature deaths resulting from PM2.5 and O3 are in rural (292,000) as opposed to urban (79,000) regions. These findings indicate the need for designing monitoring networks and ground-based health studies in rural areas of India to more accurately quantify the true health implications of ambient air pollution, in addition to supporting model evaluation. Using this urban-versus-rural emissions framework, we are assessing anthropogenic contributions to regional air quality and health impacts, and examining mitigation strategies to reduce anthropogenic emissions, improve air quality, and reduce PM2.5 and O3 attributable premature death in the near-term.

Mapping Emissions that Contribute to Air Pollution Using Adjoint Sensitivity Analysis

NASA Astrophysics Data System (ADS)

Bastien, L. A. J.; Mcdonald, B. C.; Brown, N. J.; Harley, R.

2014-12-01

The adjoint of the Community Multiscale Air Quality model (CMAQ) is used to map emissions that contribute to air pollution at receptors of interest. Adjoint tools provide an efficient way to calculate the sensitivity of a model response to a large number of model inputs, a task that would require thousands of simulations using a more traditional forward sensitivity approach. Initial applications of this technique, demonstrated here, are to benzene and directly-emitted diesel particulate matter, for which atmospheric reactions are neglected. Emissions of these pollutants are strongly influenced by light-duty gasoline vehicles and heavy-duty diesel trucks, respectively. We study air quality responses in three receptor areas where populations have been identified as especially susceptible to, and adversely affected by air pollution. Population-weighted air basin-wide responses for each pollutant are also evaluated for the entire San Francisco Bay area. High-resolution (1 km horizontal grid) emission inventories have been developed for on-road motor vehicle emission sources, based on observed traffic count data. Emission estimates represent diurnal, day of week, and seasonal variations of on-road vehicle activity, with separate descriptions for gasoline and diesel sources. Emissions that contribute to air pollution at each receptor have been mapped in space and time using the adjoint method. Effects on air quality of both relative (multiplicative) and absolute (additive) perturbations to underlying emission inventories are analyzed. The contributions of local versus upwind sources to air quality in each receptor area are quantified, and weekday/weekend and seasonal variations in the influence of emissions from upwind areas are investigated. The contribution of local sources to the total air pollution burden within the receptor areas increases from about 40% in the summer to about 50% in the winter due to increased atmospheric stagnation. The effectiveness of control strategies based on region-wide exposure metrics is compared with strategies that focus on improving air quality at specific receptors.

40 CFR 93.152 - Definitions.

Code of Federal Regulations, 2011 CFR

2011-07-01

... official charged with direct responsibility for management of an area designated as Class I under the Act.... Areawide air quality modeling analysis means an assessment on a scale that includes the entire nonattainment or maintenance area using an air quality dispersion model or photochemical grid model to determine...

Global Gridded Emission Inventories of Pentabrominated Diphenyl Ether (PeBDE)

NASA Astrophysics Data System (ADS)

Li, Yi-Fan; Tian, Chongguo; Yang, Meng; Jia, Hongliang; Ma, Jianmin; Li, Dacheng

2010-05-01

Polybrominated diphenyl ethers (PBDEs) are flame retardants widely used in many everyday products such as cars, furniture, textiles, and other electronic equipment. The commercial PBDEs have three major technical mixtures: penta-(PeBDE), octa-(OBDE) and decabromodiphenyl ethers (DeBDE). PeBDE is a mixture of several BDE congeners, such as BDE-47, -99, and -100, and has been included as a new member of persistent organic pollutants (POPs) under the 2009 Stockholm Convention. In order to produce gridded emission inventories of PeBDE on a global scale, information of production, consumption, emission, and physiochemical properties of PeBDE have been searched for published papers, government reports, and internet publications. A methodology to estimate the emissions of PeBDE has been developed and global gridded emission inventories of 2 major congener in PeBDE mixture, BDE-47 and -99, on a 1 degree by 1degree latitude/longitude resolution for 2005 have been compiled. Using these emission inventories as input data, the Canadian Model for Environmental Transport of Organochlorine Pesticides (CanMETOP) model was used to simulate the transport of these chemicals and their concentrations in air were calculated for the year of 2005. The modeled air concentration of BDE-47 and -99 were compared with the monitoring air concentrations of these two congeners in the same year obtained from renowned international/national monitoring programs, such as Global Atmospheric Passive Sampling (GAPS), the Integrated Atmospheric Deposition Network (IADN), and the Chinese POPs Soil and Air Monitoring Program (SAMP), and significant correlations between the modeled results and the monitoring data were found, indicating the high quality of the produced emission inventories of BDE-47 and -99. Keywords: Pentabrominated Diphenyl Ether (PeBDE), Emission Inventories, Global, Model

Impact of ship emissions on air pollution and AOD over North Atlantic and European Arctic

NASA Astrophysics Data System (ADS)

Kaminski, Jacek W.; Struzewska, Joanna; Jefimow, Maciej; Durka, Pawel

2016-04-01

The iAREA project is combined of experimental and theoretical research in order to contribute to the new knowledge on the impact of absorbing aerosols on the climate system in the European Arctic (http://www.igf.fuw.edu.pl/iAREA). A tropospheric chemistry model GEM-AQ (Global Environmental Multiscale Air Quality) was used as a computational tool. The core of the model is based on a weather prediction model with environmental processes (chemistry and aerosols) implanted on-line and are interactive (i.e. providing feedback of chemistry on radiation and dynamics). The numerical grid covered the Euro-Atlantic region with the resolution of 50 km. Emissions developed by NILU in the ECLIPSE project was used (Klimont et al., 2013). The model was run for two 1-year scenarios. 2014 was chosen as a base year for simulations and analysis. Scenarios include a base run with most up-to-date emissions and a run without maritime emissions. The analysis will focus on the contribution of maritime emissions on levels of particulate matter and gaseous pollutants over the European Arctic, North Atlantic and coastal areas. The annual variability will be assessed based on monthly mean near-surface concentration fields. Analysis of shipping transport on near-surface air pollution over the Euro-Atlantic region will be assessed for ozone, NO2, SO2, CO, PM10, PM2.5. Also, a contribution of ship emissions to AOD will be analysed.

Online dynamical downscaling of temperature and precipitation within the iLOVECLIM model (version 1.1)

NASA Astrophysics Data System (ADS)

Quiquet, Aurélien; Roche, Didier M.; Dumas, Christophe; Paillard, Didier

2018-02-01

This paper presents the inclusion of an online dynamical downscaling of temperature and precipitation within the model of intermediate complexity iLOVECLIM v1.1. We describe the following methodology to generate temperature and precipitation fields on a 40 km × 40 km Cartesian grid of the Northern Hemisphere from the T21 native atmospheric model grid. Our scheme is not grid specific and conserves energy and moisture in the same way as the original climate model. We show that we are able to generate a high-resolution field which presents a spatial variability in better agreement with the observations compared to the standard model. Although the large-scale model biases are not corrected, for selected model parameters, the downscaling can induce a better overall performance compared to the standard version on both the high-resolution grid and on the native grid. Foreseen applications of this new model feature include the improvement of ice sheet model coupling and high-resolution land surface models.

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

NASA Astrophysics Data System (ADS)

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

2017-12-01

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

Variable Grid Traveltime Tomography for Near-surface Seismic Imaging

NASA Astrophysics Data System (ADS)

Cai, A.; Zhang, J.

2017-12-01

We present a new algorithm of traveltime tomography for imaging the subsurface with automated variable grids upon geological structures. The nonlinear traveltime tomography along with Tikhonov regularization using conjugate gradient method is a conventional method for near surface imaging. However, model regularization for any regular and even grids assumes uniform resolution. From geophysical point of view, long-wavelength and large scale structures can be reliably resolved, the details along geological boundaries are difficult to resolve. Therefore, we solve a traveltime tomography problem that automatically identifies large scale structures and aggregates grids within the structures for inversion. As a result, the number of velocity unknowns is reduced significantly, and inversion intends to resolve small-scale structures or the boundaries of large-scale structures. The approach is demonstrated by tests on both synthetic and field data. One synthetic model is a buried basalt model with one horizontal layer. Using the variable grid traveltime tomography, the resulted model is more accurate in top layer velocity, and basalt blocks, and leading to a less number of grids. The field data was collected in an oil field in China. The survey was performed in an area where the subsurface structures were predominantly layered. The data set includes 476 shots with a 10 meter spacing and 1735 receivers with a 10 meter spacing. The first-arrival traveltime of the seismogram is picked for tomography. The reciprocal errors of most shots are between 2ms and 6ms. The normal tomography results in fluctuations in layers and some artifacts in the velocity model. In comparison, the implementation of new method with proper threshold provides blocky model with resolved flat layer and less artifacts. Besides, the number of grids reduces from 205,656 to 4,930 and the inversion produces higher resolution due to less unknowns and relatively fine grids in small structures. The variable grid traveltime tomography provides an alternative imaging solution for blocky structures in the subsurface and builds a good starting model for waveform inversion and statics.

Multi-Resolution Unstructured Grid-Generation for Geophysical Applications on the Sphere

NASA Technical Reports Server (NTRS)

Engwirda, Darren

2015-01-01

An algorithm for the generation of non-uniform unstructured grids on ellipsoidal geometries is described. This technique is designed to generate high quality triangular and polygonal meshes appropriate for general circulation modelling on the sphere, including applications to atmospheric and ocean simulation, and numerical weather predication. Using a recently developed Frontal-Delaunay-refinement technique, a method for the construction of high-quality unstructured ellipsoidal Delaunay triangulations is introduced. A dual polygonal grid, derived from the associated Voronoi diagram, is also optionally generated as a by-product. Compared to existing techniques, it is shown that the Frontal-Delaunay approach typically produces grids with near-optimal element quality and smooth grading characteristics, while imposing relatively low computational expense. Initial results are presented for a selection of uniform and non-uniform ellipsoidal grids appropriate for large-scale geophysical applications. The use of user-defined mesh-sizing functions to generate smoothly graded, non-uniform grids is discussed.

Atmospheric Parameter Climatologies from AIRS: Monitoring Short-, and Longer-Term Climate Variabilities and 'Trends'

NASA Technical Reports Server (NTRS)

Molnar, Gyula; Susskind, Joel

2008-01-01

The AIRS instrument is currently the best space-based tool to simultaneously monitor the vertical distribution of key climatically important atmospheric parameters as well as surface properties, and has provided high quality data for more than 5 years. AIRS analysis results produced at the GODDARD/DAAC, based on Versions 4 & 5 of the AIRS retrieval algorithm, are currently available for public use. Here, first we present an assessment of interrelationships of anomalies (proxies of climate variability based on 5 full years, since Sept. 2002) of various climate parameters at different spatial scales. We also present AIRS-retrievals-based global, regional and 1x1 degree grid-scale "trend"-analyses of important atmospheric parameters for this 5-year period. Note that here "trend" simply means the linear fit to the anomaly (relative the mean seasonal cycle) time series of various parameters at the above-mentioned spatial scales, and we present these to illustrate the usefulness of continuing AIRS-based climate observations. Preliminary validation efforts, in terms of intercomparisons of interannual variabilities with other available satellite data analysis results, will also be addressed. For example, we show that the outgoing longwave radiation (OLR) interannual spatial variabilities from the available state-of-the-art CERES measurements and from the AIRS computations are in remarkably good agreement. Version 6 of the AIRS retrieval scheme (currently under development) promises to further improve bias agreements for the absolute values by implementing a more accurate radiative transfer model for the OLR computations and by improving surface emissivity retrievals.

Scaling effects on spring phenology detections from MODIS data at multiple spatial resolutions over the contiguous United States

NASA Astrophysics Data System (ADS)

Peng, Dailiang; Zhang, Xiaoyang; Zhang, Bing; Liu, Liangyun; Liu, Xinjie; Huete, Alfredo R.; Huang, Wenjiang; Wang, Siyuan; Luo, Shezhou; Zhang, Xiao; Zhang, Helin

2017-10-01

Land surface phenology (LSP) has been widely retrieved from satellite data at multiple spatial resolutions, but the spatial scaling effects on LSP detection are poorly understood. In this study, we collected enhanced vegetation index (EVI, 250 m) from collection 6 MOD13Q1 product over the contiguous United States (CONUS) in 2007 and 2008, and generated a set of multiple spatial resolution EVI data by resampling 250 m to 2 × 250 m and 3 × 250 m, 4 × 250 m, …, 35 × 250 m. These EVI time series were then used to detect the start of spring season (SOS) at various spatial resolutions. Further the SOS variation across scales was examined at each coarse resolution grid (35 × 250 m ≈ 8 km, refer to as reference grid) and ecoregion. Finally, the SOS scaling effects were associated with landscape fragment, proportion of primary land cover type, and spatial variability of seasonal greenness variation within each reference grid. The results revealed the influences of satellite spatial resolutions on SOS retrievals and the related impact factors. Specifically, SOS significantly varied lineally or logarithmically across scales although the relationship could be either positive or negative. The overall SOS values averaged from spatial resolutions between 250 m and 35 × 250 m at large ecosystem regions were generally similar with a difference less than 5 days, while the SOS values within the reference grid could differ greatly in some local areas. Moreover, the standard deviation of SOS across scales in the reference grid was less than 5 days in more than 70% of area over the CONUS, which was smaller in northeastern than in southern and western regions. The SOS scaling effect was significantly associated with heterogeneity of vegetation properties characterized using land landscape fragment, proportion of primary land cover type, and spatial variability of seasonal greenness variation, but the latter was the most important impact factor.

Evaluating the impact of chemical boundary conditions on near surface ozone in regional climate-air quality simulations over Europe

NASA Astrophysics Data System (ADS)

Akritidis, D.; Zanis, P.; Katragkou, E.; Schultz, M. G.; Tegoulias, I.; Poupkou, A.; Markakis, K.; Pytharoulis, I.; Karacostas, Th.

2013-12-01

A modeling system based on the air quality model CAMx driven off-line by the regional climate model RegCM3 is used for assessing the impact of chemical lateral boundary conditions (LBCs) on near surface ozone over Europe for the period 1996-2000. The RegCM3 and CAMx simulations were performed on a 50 km × 50 km grid over Europe with RegCM3 driven by the NCEP meteorological reanalysis fields and CAMx with chemical LBCs from ECHAM5/MOZART global model. The recent past period (1996-2000) was simulated in three experiments. The first simulation was forced using time and space invariant LBCs, the second was based on ECHAM5/MOZART chemical LBCs fixed for the year 1996 and the third was based on ECHAM5/MOZART chemical LBCs with interannual variability. Anthropogenic and biogenic emissions were kept identical for the three sensitivity runs.

AirNow Information Management System - Global Earth Observation System of Systems Data Processor for Real-Time Air Quality Data Products

NASA Astrophysics Data System (ADS)

Haderman, M.; Dye, T. S.; White, J. E.; Dickerson, P.; Pasch, A. N.; Miller, D. S.; Chan, A. C.

2012-12-01

Built upon the success of the U.S. Environmental Protection Agency's (EPA) AirNow program (www.AirNow.gov), the AirNow-International (AirNow-I) system contains an enhanced suite of software programs that process and quality control real-time air quality and environmental data and distribute customized maps, files, and data feeds. The goals of the AirNow-I program are similar to those of the successful U.S. program and include fostering the exchange of environmental data; making advances in air quality knowledge and applications; and building a community of people, organizations, and decision makers in environmental management. In 2010, Shanghai became the first city in China to run this state-of-the-art air quality data management and notification system. AirNow-I consists of a suite of modules (software programs and schedulers) centered on a database. One such module is the Information Management System (IMS), which can automatically produce maps and other data products through the use of GIS software to provide the most current air quality information to the public. Developed with Global Earth Observation System of Systems (GEOSS) interoperability in mind, IMS is based on non-proprietary standards, with preference to formal international standards. The system depends on data and information providers accepting and implementing a set of interoperability arrangements, including technical specifications for collecting, processing, storing, and disseminating shared data, metadata, and products. In particular, the specifications include standards for service-oriented architecture and web-based interfaces, such as a web mapping service (WMS), web coverage service (WCS), web feature service (WFS), sensor web services, and Really Simple Syndication (RSS) feeds. IMS is flexible, open, redundant, and modular. It also allows the merging of data grids to create complex grids that show comprehensive air quality conditions. For example, the AirNow Satellite Data Processor (ASDP) was recently developed to merge PM2.5 estimates from National Aeronautics and Space Administration (NASA) satellite data and AirNow observational data, creating more precise maps and gridded data products for under-monitored areas. The ASDP can easily incorporate other data feeds, including fire and smoke locations, to build enhanced real-time air quality data products. In this presentation, we provide an overview of the features and functions of IMS, an explanation of how data moves through IMS, the rationale of the system architecture, and highlights of the ASDP as an example of the modularity and scalability of IMS.

Canadian Operational Air Quality Forecasting Systems: Status, Recent Progress, and Challenges

NASA Astrophysics Data System (ADS)

Pavlovic, Radenko; Davignon, Didier; Ménard, Sylvain; Munoz-Alpizar, Rodrigo; Landry, Hugo; Beaulieu, Paul-André; Gilbert, Samuel; Moran, Michael; Chen, Jack

2017-04-01

ECCC's Canadian Meteorological Centre Operations (CMCO) division runs a number of operational air quality (AQ)-related systems that revolve around the Regional Air Quality Deterministic Prediction System (RAQDPS). The RAQDPS generates 48-hour AQ forecasts and outputs hourly concentration fields of O3, PM2.5, NO2, and other pollutants twice daily on a North-American domain with 10-km horizontal grid spacing and 80 vertical levels. A closely related AQ forecast system with near-real-time wildfire emissions, known as FireWork, has been run by CMCO during the Canadian wildfire season (April to October) since 2014. This system became operational in June 2016. The CMCO`s operational AQ forecast systems also benefit from several support systems, such as a statistical post-processing model called UMOS-AQ that is applied to enhance forecast reliability at point locations with AQ monitors. The Regional Deterministic Air Quality Analysis (RDAQA) system has also been connected to the RAQDPS since February 2013, and hourly surface objective analyses are now available for O3, PM2.5, NO2, PM10, SO2 and, indirectly, the Canadian Air Quality Health Index. As of June 2015, another version of the RDAQA has been connected to FireWork (RDAQA-FW). For verification purposes, CMCO developed a third support system called Verification for Air QUality Models (VAQUM), which has a geospatial relational database core and which enables continuous monitoring of the AQ forecast systems' performance. Urban environments are particularly subject to AQ pollution. In order to improve the services offered, ECCC has recently been investing efforts to develop a high resolution air quality prediction capability for urban areas in Canada. In this presentation, a comprehensive description of the ECCC AQ systems will be provided, along with a discussion on AQ systems performance. Recent improvements, current challenges, and future directions of the Canadian operational AQ program will also be discussed.

Vertical resolution of baroclinic modes in global ocean models

NASA Astrophysics Data System (ADS)

Stewart, K. D.; Hogg, A. McC.; Griffies, S. M.; Heerdegen, A. P.; Ward, M. L.; Spence, P.; England, M. H.

2017-05-01

Improvements in the horizontal resolution of global ocean models, motivated by the horizontal resolution requirements for specific flow features, has advanced modelling capabilities into the dynamical regime dominated by mesoscale variability. In contrast, the choice of the vertical grid remains a subjective choice, and it is not clear that efforts to improve vertical resolution adequately support their horizontal counterparts. Indeed, considering that the bulk of the vertical ocean dynamics (including convection) are parameterized, it is not immediately obvious what the vertical grid is supposed to resolve. Here, we propose that the primary purpose of the vertical grid in a hydrostatic ocean model is to resolve the vertical structure of horizontal flows, rather than to resolve vertical motion. With this principle we construct vertical grids based on their abilities to represent baroclinic modal structures commensurate with the theoretical capabilities of a given horizontal grid. This approach is designed to ensure that the vertical grids of global ocean models complement (and, importantly, to not undermine) the resolution capabilities of the horizontal grid. We find that for z-coordinate global ocean models, at least 50 well-positioned vertical levels are required to resolve the first baroclinic mode, with an additional 25 levels per subsequent mode. High-resolution ocean-sea ice simulations are used to illustrate some of the dynamical enhancements gained by improving the vertical resolution of a 1/10° global ocean model. These enhancements include substantial increases in the sea surface height variance (∼30% increase south of 40°S), the barotropic and baroclinic eddy kinetic energies (up to 200% increase on and surrounding the Antarctic continental shelf and slopes), and the overturning streamfunction in potential density space (near-tripling of the Antarctic Bottom Water cell at 65°S).

Evaluation of improved land use and canopy representation in ...

EPA Pesticide Factsheets

Biogenic volatile organic compounds (BVOC) participate in reactions that can lead to secondarily formed ozone and particulate matter (PM) impacting air quality and climate. BVOC emissions are important inputs to chemical transport models applied on local to global scales but considerable uncertainty remains in the representation of canopy parameterizations and emission algorithms from different vegetation species. The Biogenic Emission Inventory System (BEIS) has been used to support both scientific and regulatory model assessments for ozone and PM. Here we describe a new version of BEIS which includes updated input vegetation data and canopy model formulation for estimating leaf temperature and vegetation data on estimated BVOC. The Biogenic Emission Landuse Database (BELD) was revised to incorporate land use data from the Moderate Resolution Imaging Spectroradiometer (MODIS) land product and 2006 National Land Cover Database (NLCD) land coverage. Vegetation species data are based on the US Forest Service (USFS) Forest Inventory and Analysis (FIA) version 5.1 for 2002–2013 and US Department of Agriculture (USDA) 2007 census of agriculture data. This update results in generally higher BVOC emissions throughout California compared with the previous version of BEIS. Baseline and updated BVOC emission estimates are used in Community Multiscale Air Quality (CMAQ) Model simulations with 4 km grid resolution and evaluated with measurements of isoprene and monoterp

The Marine Geoscience Data System and the Global Multi-Resolution Topography Synthesis: Online Resources for Exploring Ocean Mapping Data

NASA Astrophysics Data System (ADS)

Ferrini, V. L.; Morton, J. J.; Carbotte, S. M.

2016-02-01

The Marine Geoscience Data System (MGDS: www.marine-geo.org) provides a suite of tools and services for free public access to data acquired throughout the global oceans including maps, grids, near-bottom photos, and geologic interpretations that are essential for habitat characterization and marine spatial planning. Users can explore, discover, and download data through a combination of APIs and front-end interfaces that include dynamic service-driven maps, a geospatially enabled search engine, and an easy to navigate user interface for browsing and discovering related data. MGDS offers domain-specific data curation with a team of scientists and data specialists who utilize a suite of back-end tools for introspection of data files and metadata assembly to verify data quality and ensure that data are well-documented for long-term preservation and re-use. Funded by the NSF as part of the multi-disciplinary IEDA Data Facility, MGDS also offers Data DOI registration and links between data and scientific publications. MGDS produces and curates the Global Multi-Resolution Topography Synthesis (GMRT: gmrt.marine-geo.org), a continuously updated Digital Elevation Model that seamlessly integrates multi-resolutional elevation data from a variety of sources including the GEBCO 2014 ( 1 km resolution) and International Bathymetric Chart of the Southern Ocean ( 500 m) compilations. A significant component of GMRT includes ship-based multibeam sonar data, publicly available through NOAA's National Centers for Environmental Information, that are cleaned and quality controlled by the MGDS Team and gridded at their full spatial resolution (typically 100 m resolution in the deep sea). Additional components include gridded bathymetry products contributed by individual scientists (up to meter scale resolution in places), publicly accessible regional bathymetry, and high-resolution terrestrial elevation data. New data are added to GMRT on an ongoing basis, with two scheduled releases per year. GMRT is available as both gridded data and images that can be viewed and downloaded directly through the Java application GeoMapApp (www.geomapapp.org) and the web-based GMRT MapTool. In addition, the GMRT GridServer API provides programmatic access to grids, imagery, profiles, and single point elevation values.

An attempt at estimating Paris area CO2 emissions from atmospheric concentration measurements

NASA Astrophysics Data System (ADS)

Bréon, F. M.; Broquet, G.; Puygrenier, V.; Chevallier, F.; Xueref-Remy, I.; Ramonet, M.; Dieudonné, E.; Lopez, M.; Schmidt, M.; Perrussel, O.; Ciais, P.

2015-02-01

Atmospheric concentration measurements are used to adjust the daily to monthly budget of fossil fuel CO2 emissions of the Paris urban area from the prior estimates established by the Airparif local air quality agency. Five atmospheric monitoring sites are available, including one at the top of the Eiffel Tower. The atmospheric inversion is based on a Bayesian approach, and relies on an atmospheric transport model with a spatial resolution of 2 km with boundary conditions from a global coarse grid transport model. The inversion adjusts prior knowledge about the anthropogenic and biogenic CO2 fluxes from the Airparif inventory and an ecosystem model, respectively, with corrections at a temporal resolution of 6 h, while keeping the spatial distribution from the emission inventory. These corrections are based on assumptions regarding the temporal autocorrelation of prior emissions uncertainties within the daily cycle, and from day to day. The comparison of the measurements against the atmospheric transport simulation driven by the a priori CO2 surface fluxes shows significant differences upwind of the Paris urban area, which suggests a large and uncertain contribution from distant sources and sinks to the CO2 concentration variability. This contribution advocates that the inversion should aim at minimising model-data misfits in upwind-downwind gradients rather than misfits in mole fractions at individual sites. Another conclusion of the direct model-measurement comparison is that the CO2 variability at the top of the Eiffel Tower is large and poorly represented by the model for most wind speeds and directions. The model's inability to reproduce the CO2 variability at the heart of the city makes such measurements ill-suited for the inversion. This and the need to constrain the budgets for the whole city suggests the assimilation of upwind-downwind mole fraction gradients between sites at the edge of the urban area only. The inversion significantly improves the agreement between measured and modelled concentration gradients. Realistic emissions are retrieved for two 30-day periods and suggest a significant overestimate by the AirParif inventory. Similar inversions over longer periods are necessary for a proper evaluation of the optimised CO2 emissions against independent data.

Evaluating Lightning-generated NOx (LNOx) Parameterization based on Cloud Top Height at Resolutions with Partially-resolved Convection for Upper Tropospheric Chemistry Studies

NASA Astrophysics Data System (ADS)

Wong, J.; Barth, M. C.; Noone, D. C.

2012-12-01

Lightning-generated nitrogen oxides (LNOx) is an important precursor to tropospheric ozone production. With a meteorological time-scale variability similar to that of the ozone chemical lifetime, it can nonlinearly perturb tropospheric ozone concentration. Coupled with upper-air circulation patterns, LNOx can accumulate in significant amount in the upper troposphere with other precursors, thus enhancing ozone production (see attached figure). While LNOx emission has been included and tuned extensively in global climate models, its inclusions in regional chemistry models are seldom tested. Here we present a study that evaluates the frequently used Price and Rind parameterization based on cloud-top height at resolutions that partially resolve deep convection using the Weather Research and Forecasting model with Chemistry (WRF-Chem) over the contiguous United States. With minor modifications, the parameterization is shown to generate integrated flash counts close to those observed. However, the modeled frequency distribution of cloud-to-ground flashes do not represent well for storms with high flash rates, bringing into question the applicability of the intra-cloud/ground partitioning (IC:CG) formulation of Price and Rind in some studies. Resolution dependency also requires attention when sub-grid cloud-tops are used instead of the originally intended grid-averaged cloud-top. LNOx passive tracers being gathered by monsoonal upper tropospheric anticyclone.

Climatological simulations of ozone and atmospheric aerosols in the Greater Cairo region

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

Steiner, A. L.; Tawfik, A. B.; Shalaby, A.

An integrated chemistry-climate model (RegCM4-CHEM) simulates present-day climate, ozone and tropospheric aerosols over Egypt with a focus on Greater Cairo (GC) region. The densley populated GC region is known for its severe air quality issues driven by high levels of anthropogenic pollution in conjuction with natural sources such as dust and agricultural burning events. We find that current global emission inventories underestimate key pollutants such as nitrogen oxides and anthropogenic aerosol species. In the GC region, average-ground-based NO2 observations of 40-60 ppb are substantially higher than modeled estimates (5-10 ppb), likely due to model grid resolution, improper boundary layer representation,more » and poor emissions inventories. Observed ozone concentrations range from 35 ppb (winter) to 80 ppb (summer). The model reproduces the seasonal cycle fairly well, but modeled summer ozone is understimated by approximately 15 ppb and exhibits little interannual variability. For aerosols, springtime dust events dominate the seasonal aerosol cycle. The chemistry-climate model captures the springtime peak aerosol optical depth (AOD) of 0.7-1 but is slightly greater than satellite-derived AOD. Observed AOD decreases in the summer and increases again in the fall due to agricultural burning events in the Nile Delta, yet the model underestimates this fall observed AOD peak, as standard emissions inventories underestimate this burning and the resulting aerosol emissions. Our comparison of modeled gas and particulate phase atmospheric chemistry in the GC region indicates that improved emissions inventories of mobile sources and other anthropogenic activities are needed to improve air quality simulations in this region.« less

Two decades [1992-2012] of surface wind analyses based on satellite scatterometer observations

NASA Astrophysics Data System (ADS)

Desbiolles, Fabien; Bentamy, Abderrahim; Blanke, Bruno; Roy, Claude; Mestas-Nuñez, Alberto M.; Grodsky, Semyon A.; Herbette, Steven; Cambon, Gildas; Maes, Christophe

2017-04-01

Surface winds (equivalent neutral wind velocities at 10 m) from scatterometer missions since 1992 have been used to build up a 20-year climate series. Optimal interpolation and kriging methods have been applied to continuously provide surface wind speed and direction estimates over the global ocean on a regular grid in space and time. The use of other data sources such as radiometer data (SSM/I) and atmospheric wind reanalyses (ERA-Interim) has allowed building a blended product available at 1/4° spatial resolution and every 6 h from 1992 to 2012. Sampling issues throughout the different missions (ERS-1, ERS-2, QuikSCAT, and ASCAT) and their possible impact on the homogeneity of the gridded product are discussed. In addition, we assess carefully the quality of the blended product in the absence of scatterometer data (1992 to 1999). Data selection experiments show that the description of the surface wind is significantly improved by including the scatterometer winds. The blended winds compare well with buoy winds (1992-2012) and they resolve finer spatial scales than atmospheric reanalyses, which make them suitable for studying air-sea interactions at mesoscale. The seasonal cycle and interannual variability of the product compare well with other long-term wind analyses. The product is used to calculate 20-year trends in wind speed, as well as in zonal and meridional wind components. These trends show an important asymmetry between the southern and northern hemispheres, which may be an important issue for climate studies.

Benefits of using enhanced air quality information in human health studies

EPA Science Inventory

The ability of four (4) enhancements of gridded PM_2.5 concentrations derived from observations and air quality models to detect the relative risk of long-term exposure to PM_2.5 are evaluated with a simulation study. The four enhancements include nearest-nei...

Air quality real-time forecast before and during the G-20 ...

EPA Pesticide Factsheets

The 2016 G-20 Hangzhou summit, the eleventh annual meeting of the G-20 heads of government, will be held during September 3-5, 2016 in Hangzhou, China. For a successful summit, it is important to ensure good air quality. To achieve this goal, governments of Hangzhou and its surrounding provinces will enforce a series of emission reductions, such as a forced closure of major highly-polluting industries and also limiting car and construction emissions in the cities and surroundings during the 2016 G-20 Hangzhou summit. Air quality forecast systems consisting of the two-way coupled WRF-CMAQ and online-coupled WRF-Chem have been applied to forecast air quality in Hangzhou regularly. This study will present the results of real-time forecasts of air quality over eastern China using 12-km grid spacing and for Hangzhou area using 4-km grid spacing with these two modeling systems using emission inventories for base and 2016 G-20 scenarios before and during the 2016 G-20 Hangzhou summit. Evaluations of models’ performance for both cases for PM2.5, PM10, O3, SO2, NO2, CO, air quality index (AQI), and aerosol optical depth (AOD) are carried out by comparing them with observations obtained from satellites, such as MODIS, and surface monitoring networks. The effects of the emission reduction efforts on expected air quality improvements during the2016 G-20 Hangzhou summit will be studied in depth. This study provides insights on how air quality will be improved by a plan

Grid Quality and Resolution Issues from the Drag Prediction Workshop Series

NASA Technical Reports Server (NTRS)

Mavriplis, Dimitri J.; Vassberg, John C.; Tinoco, Edward N.; Mani, Mori; Brodersen, Olaf P.; Eisfeld, Bernhard; Wahls, Richard A.; Morrison, Joseph H.; Zickuhr, Tom; Levy, David;

Modeling Spatial and Temporal Variability in Ammonia Emissions from Agricultural Fertilization

NASA Astrophysics Data System (ADS)

Balasubramanian, S.; Koloutsou-Vakakis, S.; Rood, M. J.

2013-12-01

Ammonia (NH3), is an important component of the reactive nitrogen cycle and a precursor to formation of atmospheric particulate matter (PM). Predicting regional PM concentrations and deposition of nitrogen species to ecosystems requires representative emission inventories. Emission inventories have traditionally been developed using top down approaches and more recently from data assimilation based on satellite and ground based ambient concentrations and wet deposition data. The National Emission Inventory (NEI) indicates agricultural fertilization as the predominant contributor (56%) to NH3 emissions in Midwest USA, in 2002. However, due to limited understanding of the complex interactions between fertilizer usage, farm practices, soil and meteorological conditions and absence of detailed statistical data, such emission estimates are currently based on generic emission factors, time-averaged temporal factors and coarse spatial resolution. Given the significance of this source, our study focuses on developing an improved NH3 emission inventory for agricultural fertilization at finer spatial and temporal scales for air quality modeling studies. Firstly, a high-spatial resolution 4 km x 4 km NH3 emission inventory for agricultural fertilization has been developed for Illinois by modifying spatial allocation of emissions based on combining crop-specific fertilization rates with cropland distribution in the Sparse Matrix Operator Kernel Emissions model. Net emission estimates of our method are within 2% of NEI, since both methods are constrained by fertilizer sales data. However, we identified localized crop-specific NH3 emission hotspots at sub-county resolutions absent in NEI. Secondly, we have adopted the use of the DeNitrification-DeComposition (DNDC) Biogeochemistry model to simulate the physical and chemical processes that control volatilization of nitrogen as NH3 to the atmosphere after fertilizer application and resolve the variability at the hourly scale. Representative temporal factors are being developed to capture crop-specific NH3 emission variability by combining knowledge of local crop management practices with high resolution cropland and soil maps. This improved spatially and temporally dependent NH3 emission inventory for agricultural fertilization is being prepared as a direct input to a state of the art air quality model to evaluate the effects of agricultural fertilization on regional air quality and atmospheric deposition of reactive nitrogen species.

Downscaling modelling system for multi-scale air quality forecasting

NASA Astrophysics Data System (ADS)

Nuterman, R.; Baklanov, A.; Mahura, A.; Amstrup, B.; Weismann, J.

2010-09-01

Urban modelling for real meteorological situations, in general, considers only a small part of the urban area in a micro-meteorological model, and urban heterogeneities outside a modelling domain affect micro-scale processes. Therefore, it is important to build a chain of models of different scales with nesting of higher resolution models into larger scale lower resolution models. Usually, the up-scaled city- or meso-scale models consider parameterisations of urban effects or statistical descriptions of the urban morphology, whereas the micro-scale (street canyon) models are obstacle-resolved and they consider a detailed geometry of the buildings and the urban canopy. The developed system consists of the meso-, urban- and street-scale models. First, it is the Numerical Weather Prediction (HIgh Resolution Limited Area Model) model combined with Atmospheric Chemistry Transport (the Comprehensive Air quality Model with extensions) model. Several levels of urban parameterisation are considered. They are chosen depending on selected scales and resolutions. For regional scale, the urban parameterisation is based on the roughness and flux corrections approach; for urban scale - building effects parameterisation. Modern methods of computational fluid dynamics allow solving environmental problems connected with atmospheric transport of pollutants within urban canopy in a presence of penetrable (vegetation) and impenetrable (buildings) obstacles. For local- and micro-scales nesting the Micro-scale Model for Urban Environment is applied. This is a comprehensive obstacle-resolved urban wind-flow and dispersion model based on the Reynolds averaged Navier-Stokes approach and several turbulent closures, i.e. k -ɛ linear eddy-viscosity model, k - ɛ non-linear eddy-viscosity model and Reynolds stress model. Boundary and initial conditions for the micro-scale model are used from the up-scaled models with corresponding interpolation conserving the mass. For the boundaries a kind of Dirichlet condition is chosen to provide the values based on interpolation from the coarse to the fine grid. When the roughness approach is changed to the obstacle-resolved one in the nested model, the interpolation procedure will increase the computational time (due to additional iterations) for meteorological/ chemical fields inside the urban sub-layer. In such situations, as a possible alternative, the perturbation approach can be applied. Here, the effects of main meteorological variables and chemical species are considered as a sum of two components: background (large-scale) values, described by the coarse-resolution model, and perturbations (micro-scale) features, obtained from the nested fine resolution model.

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

NASA Astrophysics Data System (ADS)

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

2017-12-01

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

Spatiotemporal Variability of Drought in Pakistan through High-Resolution Daily Gridded In-Situ Observations

NASA Astrophysics Data System (ADS)

Bashir, F.; Zeng, X.; Gupta, H. V.; Hazenberg, P.

2017-12-01

Drought as an extreme event may have far reaching socio-economic impacts on agriculture based economies like Pakistan. Effective assessment of drought requires high resolution spatiotemporally continuous hydrometeorological information. For this purpose, new in-situ daily observations based gridded analyses of precipitation, maximum, minimum and mean temperature and diurnal temperature range are developed, that covers whole Pakistan on 0.01º latitude-longitude for a 54-year period (1960-2013). The number of participating meteorological observatories used in these gridded analyses is 2 to 6 times greater than any other similar product available. This data set is used to identify extreme wet and dry periods and their spatial patterns across Pakistan using Palmer Drought Severity Index (PDSI) and Standardized Precipitation Index (SPI). Periodicity of extreme events is estimated at seasonal to decadal scales. Spatiotemporal signatures of drought incidence indicating its extent and longevity in different areas may help water resource managers and policy makers to mitigate the severity of the drought and its impact on food security through suitable adaptive techniques. Moreover, this high resolution gridded in-situ observations of precipitation and temperature is used to evaluate other coarser-resolution gridded products.

Using Analog Ensemble to generate spatially downscaled probabilistic wind power forecasts

NASA Astrophysics Data System (ADS)

Delle Monache, L.; Shahriari, M.; Cervone, G.

2017-12-01

We use the Analog Ensemble (AnEn) method to generate probabilistic 80-m wind power forecasts. We use data from the NCEP GFS ( 28 km resolution) and NCEP NAM (12 km resolution). We use forecasts data from NAM and GFS, and analysis data from NAM which enables us to: 1) use a lower-resolution model to create higher-resolution forecasts, and 2) use a higher-resolution model to create higher-resolution forecasts. The former essentially increases computing speed and the latter increases forecast accuracy. An aggregated model of the former can be compared against the latter to measure the accuracy of the AnEn spatial downscaling. The AnEn works by taking a deterministic future forecast and comparing it with past forecasts. The model searches for the best matching estimates within the past forecasts and selects the predictand value corresponding to these past forecasts as the ensemble prediction for the future forecast. Our study is based on predicting wind speed and air density at more than 13,000 grid points in the continental US. We run the AnEn model twice: 1) estimating 80-m wind speed by using predictor variables such as temperature, pressure, geopotential height, U-component and V-component of wind, 2) estimating air density by using predictors such as temperature, pressure, and relative humidity. We use the air density values to correct the standard wind power curves for different values of air density. The standard deviation of the ensemble members (i.e. ensemble spread) will be used as the degree of difficulty to predict wind power at different locations. The value of the correlation coefficient between the ensemble spread and the forecast error determines the appropriateness of this measure. This measure is prominent for wind farm developers as building wind farms in regions with higher predictability will reduce the real-time risks of operating in the electricity markets.

Challenges and opportunities in the design and construction of a GIS-based emission inventory infrastructure for the Niger Delta region of Nigeria.

PubMed

Fagbeja, Mofoluso A; Hill, Jennifer L; Chatterton, Tim J; Longhurst, James W S; Akpokodje, Joseph E; Agbaje, Ganiy I; Halilu, Shaba A

2017-03-01

Environmental monitoring in middle- and low-income countries is hampered by many factors which include enactment and enforcement of legislations; deficiencies in environmental data reporting and documentation; inconsistent, incomplete and unverifiable data; a lack of access to data; and technical expertise. This paper describes the processes undertaken and the major challenges encountered in the construction of the first Niger Delta Emission Inventory (NDEI) for criteria air pollutants and CO 2 released from the anthropogenic activities in the region. This study focused on using publicly available government and research data. The NDEI has been designed to provide a Geographic Information System-based component of an air quality and carbon management framework. The NDEI infrastructure was designed and constructed at 1-, 10- and 20-km grid resolutions for point, line and area sources using industry standard processes and emission factors derived from activities similar to those in the Niger Delta. Due to inadequate, incomplete, potentially inaccurate and unavailable data, the infrastructure was populated with data based on a series of best possible assumptions for key emission sources. This produces outputs with variable levels of certainty, which also highlights the critical challenges in the estimation of emissions from a developing country. However, the infrastructure is functional and has the ability to produce spatially resolved emission estimates.

Reprocessing the Historical Satellite Passive Microwave Record at Enhanced Spatial Resolutions using Image Reconstruction

NASA Astrophysics Data System (ADS)

Hardman, M.; Brodzik, M. J.; Long, D. G.; Paget, A. C.; Armstrong, R. L.

2015-12-01

Beginning in 1978, the satellite passive microwave data record has been a mainstay of remote sensing of the cryosphere, providing twice-daily, near-global spatial coverage for monitoring changes in hydrologic and cryospheric parameters that include precipitation, soil moisture, surface water, vegetation, snow water equivalent, sea ice concentration and sea ice motion. Currently available global gridded passive microwave data sets serve a diverse community of hundreds of data users, but do not meet many requirements of modern Earth System Data Records (ESDRs) or Climate Data Records (CDRs), most notably in the areas of intersensor calibration, quality-control, provenance and consistent processing methods. The original gridding techniques were relatively primitive and were produced on 25 km grids using the original EASE-Grid definition that is not easily accommodated in modern software packages. Further, since the first Level 3 data sets were produced, the Level 2 passive microwave data on which they were based have been reprocessed as Fundamental CDRs (FCDRs) with improved calibration and documentation. We are funded by NASA MEaSUREs to reprocess the historical gridded data sets as EASE-Grid 2.0 ESDRs, using the most mature available Level 2 satellite passive microwave (SMMR, SSM/I-SSMIS, AMSR-E) records from 1978 to the present. We have produced prototype data from SSM/I and AMSR-E for the year 2003, for review and feedback from our Early Adopter user community. The prototype data set includes conventional, low-resolution ("drop-in-the-bucket" 25 km) grids and enhanced-resolution grids derived from the two candidate image reconstruction techniques we are evaluating: 1) Backus-Gilbert (BG) interpolation and 2) a radiometer version of Scatterometer Image Reconstruction (SIR). We summarize our temporal subsetting technique, algorithm tuning parameters and computational costs, and include sample SSM/I images at enhanced resolutions of up to 3 km. We are actively working with our Early Adopters to finalize content and format of this new, consistently-processed high-quality satellite passive microwave ESDR.

Evaluation of tropical channel refinement using MPAS-A aquaplanet simulations

DOE PAGES

Martini, Matus N.; Gustafson, Jr., William I.; O'Brien, Travis A.; ...

2015-09-13

Climate models with variable-resolution grids offer a computationally less expensive way to provide more detailed information at regional scales and increased accuracy for processes that cannot be resolved by a coarser grid. This study uses the Model for Prediction Across Scales–Atmosphere (MPAS22A), consisting of a nonhydrostatic dynamical core and a subset of Advanced Research Weather Research and Forecasting (ARW-WRF) model atmospheric physics that have been modified to include the Community Atmosphere Model version 5 (CAM5) cloud fraction parameterization, to investigate the potential benefits of using increased resolution in an tropical channel. The simulations are performed with an idealized aquaplanet configurationmore » using two quasi-uniform grids, with 30 km and 240 km grid spacing, and two variable-resolution grids spanning the same grid spacing range; one with a narrow (20°S–20°N) and one with a wide (30°S–30°N) tropical channel refinement. Results show that increasing resolution in the tropics impacts both the tropical and extratropical circulation. Compared to the quasi-uniform coarse grid, the narrow-channel simulation exhibits stronger updrafts in the Ferrel cell as well as in the middle of the upward branch of the Hadley cell. The wider tropical channel has a closer correspondence to the 30 km quasi-uniform simulation. However, the total atmospheric poleward energy transports are similar in all simulations. The largest differences are in the low-level cloudiness. The refined channel simulations show improved tropical and extratropical precipitation relative to the global 240 km simulation when compared to the global 30 km simulation. All simulations have a single ITCZ. Furthermore, the relatively small differences in mean global and tropical precipitation rates among the simulations are a promising result, and the evidence points to the tropical channel being an effective method for avoiding the extraneous numerical artifacts seen in earlier studies that only refined portion of the tropics.« less

Spatial scaling of net primary productivity using subpixel landcover information

NASA Astrophysics Data System (ADS)

Chen, X. F.; Chen, Jing M.; Ju, Wei M.; Ren, L. L.

2008-10-01

Gridding the land surface into coarse homogeneous pixels may cause important biases on ecosystem model estimations of carbon budget components at local, regional and global scales. These biases result from overlooking subpixel variability of land surface characteristics. Vegetation heterogeneity is an important factor introducing biases in regional ecological modeling, especially when the modeling is made on large grids. This study suggests a simple algorithm that uses subpixel information on the spatial variability of land cover type to correct net primary productivity (NPP) estimates, made at coarse spatial resolutions where the land surface is considered as homogeneous within each pixel. The algorithm operates in such a way that NPP obtained from calculations made at coarse spatial resolutions are multiplied by simple functions that attempt to reproduce the effects of subpixel variability of land cover type on NPP. Its application to a carbon-hydrology coupled model(BEPS-TerrainLab model) estimates made at a 1-km resolution over a watershed (named Baohe River Basin) located in the southwestern part of Qinling Mountains, Shaanxi Province, China, improved estimates of average NPP as well as its spatial variability.

STEMS-Air: a simple GIS-based air pollution dispersion model for city-wide exposure assessment.

PubMed

Gulliver, John; Briggs, David

2011-05-15

Current methods of air pollution modelling do not readily meet the needs of air pollution mapping for short-term (i.e. daily) exposure studies. The main limiting factor is that for those few models that couple with a GIS there are insufficient tools for directly mapping air pollution both at high spatial resolution and over large areas (e.g. city wide). A simple GIS-based air pollution model (STEMS-Air) has been developed for PM(10) to meet these needs with the option to choose different exposure averaging periods (e.g. daily and annual). STEMS-Air uses the grid-based FOCALSUM function in ArcGIS in conjunction with a fine grid of emission sources and basic information on meteorology to implement a simple Gaussian plume model of air pollution dispersion. STEMS-Air was developed and validated in London, UK, using data on concentrations of PM(10) from routinely available monitoring data. Results from the validation study show that STEMS-Air performs well in predicting both daily (at four sites) and annual (at 30 sites) concentrations of PM(10). For daily modelling, STEMS-Air achieved r(2) values in the range 0.19-0.43 (p<0.001) based solely on traffic-related emissions and r(2) values in the range 0.41-0.63 (p<0.001) when adding information on 'background' levels of PM(10). For annual modelling of PM(10), the model returned r(2) in the range 0.67-0.77 (P<0.001) when compared with monitored concentrations. The model can thus be used for rapid production of daily or annual city-wide air pollution maps either as a screening process in urban air quality planning and management, or as the basis for health risk assessment and epidemiological studies. Crown Copyright © 2011. Published by Elsevier B.V. All rights reserved.

M-TraCE: a new tool for high-resolution computation and statistical elaboration of backward trajectories on the Italian domain

NASA Astrophysics Data System (ADS)

Vitali, Lina; Righini, Gaia; Piersanti, Antonio; Cremona, Giuseppe; Pace, Giandomenico; Ciancarella, Luisella

2017-12-01

Air backward trajectory calculations are commonly used in a variety of atmospheric analyses, in particular for source attribution evaluation. The accuracy of backward trajectory analysis is mainly determined by the quality and the spatial and temporal resolution of the underlying meteorological data set, especially in the cases of complex terrain. This work describes a new tool for the calculation and the statistical elaboration of backward trajectories. To take advantage of the high-resolution meteorological database of the Italian national air quality model MINNI, a dedicated set of procedures was implemented under the name of M-TraCE (MINNI module for Trajectories Calculation and statistical Elaboration) to calculate and process the backward trajectories of air masses reaching a site of interest. Some outcomes from the application of the developed methodology to the Italian Network of Special Purpose Monitoring Stations are shown to assess its strengths for the meteorological characterization of air quality monitoring stations. M-TraCE has demonstrated its capabilities to provide a detailed statistical assessment of transport patterns and region of influence of the site under investigation, which is fundamental for correctly interpreting pollutants measurements and ascertaining the official classification of the monitoring site based on meta-data information. Moreover, M-TraCE has shown its usefulness in supporting other assessments, i.e., spatial representativeness of a monitoring site, focussing specifically on the analysis of the effects due to meteorological variables.

A 12-year (1987-1998) Ensemble Simulation of the US Climate with a Variable Resolution Stretched Grid GCM

NASA Technical Reports Server (NTRS)

Fox-Rabinovitz, Michael S.; Takacs, Lawrence L.; Govindaraju, Ravi C.

2002-01-01

The variable-resolution stretched-grid (SG) GEOS (Goddard Earth Observing System) GCM has been used for limited ensemble integrations with a relatively coarse, 60 to 100 km, regional resolution over the U.S. The experiments have been run for the 12-year period, 1987-1998, that includes the recent ENSO cycles. Initial conditions 1-2 days apart are used for ensemble members. The goal of the experiments is analyzing the long-term SG-GCM ensemble integrations in terms of their potential in reducing the uncertainties of regional climate simulation while producing realistic mesoscales. The ensemble integration results are analyzed for both prognostic and diagnostic fields. A special attention is devoted to analyzing the variability of precipitation over the U.S. The internal variability of the SG-GCM has been assessed. The ensemble means appear to be closer to the verifying analyses than the individual ensemble members. The ensemble means capture realistic mesoscale patterns, especially those of induced by orography. Two ENSO cycles have been analyzed in terms their impact on the U.S. climate, especially on precipitation. The ability of the SG-GCM simulations to produce regional climate anomalies has been confirmed. However, the optimal size of the ensembles depending on fine regional resolution used, is still to be determined. The SG-GCM ensemble simulations are performed as a preparation or a preliminary stage for the international SGMIP (Stretched-Grid Model Intercomparison Project) that is under way with participation of the major centers and groups employing the SG-approach for regional climate modeling.

Regional Data Assimilation of AIRS Profiles and Radiances at the SPoRT Center

NASA Technical Reports Server (NTRS)

Zavodsky, Brad; Chou, Shih-hung; Jedlovec, Gary

2009-01-01

This slide presentation reviews the Short Term Prediction Research and Transition (SPoRT) Center's mission to improve short-term weather prediction at the regional and local scale. It includes information on the cold bias in Weather Research and Forcasting (WRF), troposphere recordings from the Atmospheric Infrared Sounder (AIRS), and vertical resolution of analysis grid.

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

NASA Astrophysics Data System (ADS)

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

2015-12-01

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

Mapping Atmospheric Moisture Climatologies across the Conterminous United States

PubMed Central

Daly, Christopher; Smith, Joseph I.; Olson, Keith V.

2015-01-01

Spatial climate datasets of 1981–2010 long-term mean monthly average dew point and minimum and maximum vapor pressure deficit were developed for the conterminous United States at 30-arcsec (~800m) resolution. Interpolation of long-term averages (twelve monthly values per variable) was performed using PRISM (Parameter-elevation Relationships on Independent Slopes Model). Surface stations available for analysis numbered only 4,000 for dew point and 3,500 for vapor pressure deficit, compared to 16,000 for previously-developed grids of 1981–2010 long-term mean monthly minimum and maximum temperature. Therefore, a form of Climatologically-Aided Interpolation (CAI) was used, in which the 1981–2010 temperature grids were used as predictor grids. For each grid cell, PRISM calculated a local regression function between the interpolated climate variable and the predictor grid. Nearby stations entering the regression were assigned weights based on the physiographic similarity of the station to the grid cell that included the effects of distance, elevation, coastal proximity, vertical atmospheric layer, and topographic position. Interpolation uncertainties were estimated using cross-validation exercises. Given that CAI interpolation was used, a new method was developed to allow uncertainties in predictor grids to be accounted for in estimating the total interpolation error. Local land use/land cover properties had noticeable effects on the spatial patterns of atmospheric moisture content and deficit. An example of this was relatively high dew points and low vapor pressure deficits at stations located in or near irrigated fields. The new grids, in combination with existing temperature grids, enable the user to derive a full suite of atmospheric moisture variables, such as minimum and maximum relative humidity, vapor pressure, and dew point depression, with accompanying assumptions. All of these grids are available online at http://prism.oregonstate.edu, and include 800-m and 4-km resolution data, images, metadata, pedigree information, and station inventory files. PMID:26485026

A NEW COMBINED LOCAL AND NON-LOCAL PBL MODEL FOR METEOROLOGY AND AIR QUALITY MODELING

EPA Science Inventory

A new version of the Asymmetric Convective Model (ACM) has been developed to describe sub-grid vertical turbulent transport in both meteorology models and air quality models. The new version (ACM2) combines the non-local convective mixing of the original ACM with local eddy diff...

Evaluation of the Monotonic Lagrangian Grid and Lat-Long Grid for Air Traffic Management

NASA Technical Reports Server (NTRS)

Kaplan, Carolyn; Dahm, Johann; Oran, Elaine; Alexandrov, Natalia; Boris, Jay

2011-01-01

The Air Traffic Monotonic Lagrangian Grid (ATMLG) is used to simulate a 24 hour period of air traffic flow in the National Airspace System (NAS). During this time period, there are 41,594 flights over the United States, and the flight plan information (departure and arrival airports and times, and waypoints along the way) are obtained from an Federal Aviation Administration (FAA) Enhanced Traffic Management System (ETMS) dataset. Two simulation procedures are tested and compared: one based on the Monotonic Lagrangian Grid (MLG), and the other based on the stationary Latitude-Longitude (Lat- Long) grid. Simulating one full day of air traffic over the United States required the following amounts of CPU time on a single processor of an SGI Altix: 88 s for the MLG method, and 163 s for the Lat-Long grid method. We present a discussion of the amount of CPU time required for each of the simulation processes (updating aircraft trajectories, sorting, conflict detection and resolution, etc.), and show that the main advantage of the MLG method is that it is a general sorting algorithm that can sort on multiple properties. We discuss how many MLG neighbors must be considered in the separation assurance procedure in order to ensure a five-mile separation buffer between aircraft, and we investigate the effect of removing waypoints from aircraft trajectories. When aircraft choose their own trajectory, there are more flights with shorter duration times and fewer CD&R maneuvers, resulting in significant fuel savings.

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

Impact of earthquake source complexity and land elevation data resolution on tsunami hazard assessment and fatality estimation

NASA Astrophysics Data System (ADS)

Muhammad, Ario; Goda, Katsuichiro

2018-03-01

This study investigates the impact of model complexity in source characterization and digital elevation model (DEM) resolution on the accuracy of tsunami hazard assessment and fatality estimation through a case study in Padang, Indonesia. Two types of earthquake source models, i.e. complex and uniform slip models, are adopted by considering three resolutions of DEMs, i.e. 150 m, 50 m, and 10 m. For each of the three grid resolutions, 300 complex source models are generated using new statistical prediction models of earthquake source parameters developed from extensive finite-fault models of past subduction earthquakes, whilst 100 uniform slip models are constructed with variable fault geometry without slip heterogeneity. The results highlight that significant changes to tsunami hazard and fatality estimates are observed with regard to earthquake source complexity and grid resolution. Coarse resolution (i.e. 150 m) leads to inaccurate tsunami hazard prediction and fatality estimation, whilst 50-m and 10-m resolutions produce similar results. However, velocity and momentum flux are sensitive to the grid resolution and hence, at least 10-m grid resolution needs to be implemented when considering flow-based parameters for tsunami hazard and risk assessments. In addition, the results indicate that the tsunami hazard parameters and fatality number are more sensitive to the complexity of earthquake source characterization than the grid resolution. Thus, the uniform models are not recommended for probabilistic tsunami hazard and risk assessments. Finally, the findings confirm that uncertainties of tsunami hazard level and fatality in terms of depth, velocity and momentum flux can be captured and visualized through the complex source modeling approach. From tsunami risk management perspectives, this indeed creates big data, which are useful for making effective and robust decisions.

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

Habte, Aron; Sengupta, Manajit; Lopez, Anthony

This paper validates the performance of the physics-based Physical Solar Model (PSM) data set in the National Solar Radiation Data Base (NSRDB) to quantify the accuracy of the magnitude and the spatial and temporal variability of the solar radiation data. Achieving higher penetrations of solar energy on the electric grid and reducing integration costs requires accurate knowledge of the available solar resource. Understanding the impacts of clouds and other meteorological constituents on the solar resource and quantifying intra-/inter-hour, seasonal, and interannual variability are essential for accurately designing utility-scale solar energy projects. Solar resource information can be obtained from ground-based measurementmore » stations and/or from modeled data sets. The availability of measurements is scarce, both temporally and spatially, because it is expensive to maintain a high-density solar radiation measurement network that collects good quality data for long periods of time. On the other hand, high temporal and spatial resolution gridded satellite data can be used to estimate surface radiation for long periods of time and is extremely useful for solar energy development. Because of the advantages of satellite-based solar resource assessment, the National Renewable Energy Laboratory developed the PSM. The PSM produced gridded solar irradiance -- global horizontal irradiance (GHI), direct normal irradiance (DNI), and diffuse horizontal irradiance -- for the NSRDB at a 4-km by 4-km spatial resolution and half-hourly temporal resolution covering the 18 years from 1998-2015. The NSRDB also contains additional ancillary meteorological data sets, such as temperature, relative humidity, surface pressure, dew point, and wind speed. Details of the model and data are available at https://nsrdb.nrel.gov. The results described in this paper show that the hourly-averaged satellite-derived data have a systematic (bias) error of approximately +5% for GHI and less than +10% for DNI; however, the scatter (root mean square error [RMSE]) difference is higher for the hourly averages.« less

Evaluation of the National Solar Radiation Database (NSRDB): 1998-2015

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

Habte, Aron; Sengupta, Manajit; Lopez, Anthony

This paper validates the performance of the physics-based Physical Solar Model (PSM) data set in the National Solar Radiation Data Base (NSRDB) to quantify the accuracy of the magnitude and the spatial and temporal variability of the solar radiation data. Achieving higher penetrations of solar energy on the electric grid and reducing integration costs requires accurate knowledge of the available solar resource. Understanding the impacts of clouds and other meteorological constituents on the solar resource and quantifying intra-/inter-hour, seasonal, and interannual variability are essential for accurately designing utility-scale solar energy projects. Solar resource information can be obtained from ground-based measurementmore » stations and/or from modeled data sets. The availability of measurements is scarce, both temporally and spatially, because it is expensive to maintain a high-density solar radiation measurement network that collects good quality data for long periods of time. On the other hand, high temporal and spatial resolution gridded satellite data can be used to estimate surface radiation for long periods of time and is extremely useful for solar energy development. Because of the advantages of satellite-based solar resource assessment, the National Renewable Energy Laboratory developed the PSM. The PSM produced gridded solar irradiance -- global horizontal irradiance (GHI), direct normal irradiance (DNI), and diffuse horizontal irradiance -- for the NSRDB at a 4-km by 4-km spatial resolution and half-hourly temporal resolution covering the 18 years from 1998-2015. The NSRDB also contains additional ancillary meteorological data sets, such as temperature, relative humidity, surface pressure, dew point, and wind speed. Details of the model and data are available at https://nsrdb.nrel.gov. The results described in this paper show that the hourly-averaged satellite-derived data have a systematic (bias) error of approximately +5% for GHI and less than +10% for DNI; however, the scatter (root mean square error [RMSE]) difference is higher for the hourly averages.« less

Sensitivity of U.S. summer precipitation to model resolution and convective parameterizations across gray zone resolutions

NASA Astrophysics Data System (ADS)

Gao, Yang; Leung, L. Ruby; Zhao, Chun; Hagos, Samson

2017-03-01

Simulating summer precipitation is a significant challenge for climate models that rely on cumulus parameterizations to represent moist convection processes. Motivated by recent advances in computing that support very high-resolution modeling, this study aims to systematically evaluate the effects of model resolution and convective parameterizations across the gray zone resolutions. Simulations using the Weather Research and Forecasting model were conducted at grid spacings of 36 km, 12 km, and 4 km for two summers over the conterminous U.S. The convection-permitting simulations at 4 km grid spacing are most skillful in reproducing the observed precipitation spatial distributions and diurnal variability. Notable differences are found between simulations with the traditional Kain-Fritsch (KF) and the scale-aware Grell-Freitas (GF) convection schemes, with the latter more skillful in capturing the nocturnal timing in the Great Plains and North American monsoon regions. The GF scheme also simulates a smoother transition from convective to large-scale precipitation as resolution increases, resulting in reduced sensitivity to model resolution compared to the KF scheme. Nonhydrostatic dynamics has a positive impact on precipitation over complex terrain even at 12 km and 36 km grid spacings. With nudging of the winds toward observations, we show that the conspicuous warm biases in the Southern Great Plains are related to precipitation biases induced by large-scale circulation biases, which are insensitive to model resolution. Overall, notable improvements in simulating summer rainfall and its diurnal variability through convection-permitting modeling and scale-aware parameterizations suggest promising venues for improving climate simulations of water cycle processes.

A Simple Algebraic Grid Adaptation Scheme with Applications to Two- and Three-dimensional Flow Problems

NASA Technical Reports Server (NTRS)

Hsu, Andrew T.; Lytle, John K.

1989-01-01

An algebraic adaptive grid scheme based on the concept of arc equidistribution is presented. The scheme locally adjusts the grid density based on gradients of selected flow variables from either finite difference or finite volume calculations. A user-prescribed grid stretching can be specified such that control of the grid spacing can be maintained in areas of known flowfield behavior. For example, the grid can be clustered near a wall for boundary layer resolution and made coarse near the outer boundary of an external flow. A grid smoothing technique is incorporated into the adaptive grid routine, which is found to be more robust and efficient than the weight function filtering technique employed by other researchers. Since the present algebraic scheme requires no iteration or solution of differential equations, the computer time needed for grid adaptation is trivial, making the scheme useful for three-dimensional flow problems. Applications to two- and three-dimensional flow problems show that a considerable improvement in flowfield resolution can be achieved by using the proposed adaptive grid scheme. Although the scheme was developed with steady flow in mind, it is a good candidate for unsteady flow computations because of its efficiency.

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.

Simulating smoke transport from wildland fires with a regional-scale air quality model: sensitivity to spatiotemporal allocation of fire emissions.

PubMed

Garcia-Menendez, Fernando; Hu, Yongtao; Odman, Mehmet T

2014-09-15

Air quality forecasts generated with chemical transport models can provide valuable information about the potential impacts of fires on pollutant levels. However, significant uncertainties are associated with fire-related emission estimates as well as their distribution on gridded modeling domains. In this study, we explore the sensitivity of fine particulate matter concentrations predicted by a regional-scale air quality model to the spatial and temporal allocation of fire emissions. The assessment was completed by simulating a fire-related smoke episode in which air quality throughout the Atlanta metropolitan area was affected on February 28, 2007. Sensitivity analyses were carried out to evaluate the significance of emission distribution among the model's vertical layers, along the horizontal plane, and into hourly inputs. Predicted PM2.5 concentrations were highly sensitive to emission injection altitude relative to planetary boundary layer height. Simulations were also responsive to the horizontal allocation of fire emissions and their distribution into single or multiple grid cells. Additionally, modeled concentrations were greatly sensitive to the temporal distribution of fire-related emissions. The analyses demonstrate that, in addition to adequate estimates of emitted mass, successfully modeling the impacts of fires on air quality depends on an accurate spatiotemporal allocation of emissions. Copyright © 2014 Elsevier B.V. All rights reserved.

A communication library for the parallelization of air quality models on structured grids

NASA Astrophysics Data System (ADS)

Miehe, Philipp; Sandu, Adrian; Carmichael, Gregory R.; Tang, Youhua; Dăescu, Dacian

PAQMSG is an MPI-based, Fortran 90 communication library for the parallelization of air quality models (AQMs) on structured grids. It consists of distribution, gathering and repartitioning routines for different domain decompositions implementing a master-worker strategy. The library is architecture and application independent and includes optimization strategies for different architectures. This paper presents the library from a user perspective. Results are shown from the parallelization of STEM-III on Beowulf clusters. The PAQMSG library is available on the web. The communication routines are easy to use, and should allow for an immediate parallelization of existing AQMs. PAQMSG can also be used for constructing new models.

A Low Cost High Density Sensor Network for Air Quality at London Heathrow Airport

NASA Astrophysics Data System (ADS)

Bright, V.; Mead, M. I.; Popoola, O. A.; Baron, R. P.; Saffell, J.; Stewart, G.; Kaye, P.; Jones, R.

2012-12-01

Atmospheric composition within urban areas has a direct effect on the air quality of an environment in which a large majority of people live and work. Atmospheric pollutants including ozone (O3), nitrogen dioxide (NO2), volatile organic compounds (VOCs) and particulate matter (PM) can have a significant effect on human health. As such it is important to determine the potential exposure of individuals to these atmospheric constituents and investigate the processes that lead to the degradation of air quality within the urban environment. Whilst modelled pollutant levels on the local scale often suggest high degrees of spatial and temporal variability, the relatively sparse fixed site automated urban networks only provide low spatial resolution data that do not appear adequate in detecting such small scale variability. In this paper we demonstrate that measurements can now be made using networks of low-cost sensors that utilise a variety of techniques, including electrochemical and optical, to measure concentrations of atmospheric species. Once equipped with GPS and GPRS to determine position and transmit data respectively, these networks have the potential to provide valuable insights into pollutant variability inherent on the local or micro-scale. The methodology has been demonstrated successfully in field campaigns carried out in cities including London and Valencia, and is now being deployed as part of the Sensor Networks for Air Quality currently deployed at London Heathrow airport (SNAQ-Heathrow) which is outlined in the partner paper presented by Mead et al. (this conference). The SNAQ-Heathrow network of 50 sensor nodes will provide an unprecedented data set that includes measurements of O3, NO, NO2, CO, CO2, SO2, total VOCs, size-speciated PM as well as meteorological variables that include temperature, relative humidity, wind speed and direction. This network will provide high temporal (20 second intervals) and spatial (50 sites within the airport area) resolution data over a 12 month period with data transmitted back to a server every 2 hours. In this paper we present the data capture and storage, data accessibility, data mining and visualisation techniques applied to the measurements of the SNAQ Heathrow high density sensor network, the preliminary results of which provide an insight into the potential use of such networks in characterising air quality, emissions and validating dispersion models on local scales. We also present a web based interface developed for the sensor network that allows users to access archived data and assess meteorological conditions, atmospheric dispersion, pollutant levels and emission rates.

Projections of Future Summertime Ozone over the U.S.

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

Pfister, G. G.; Walters, Stacy; Lamarque, J. F.

This study uses a regional fully coupled chemistry-transport model to assess changes in surface ozone over the summertime U.S. between present and a 2050 future time period at high spatial resolution (12 km grid spacing) under the SRES A2 climate and RCP8.5 anthropogenic pre-cursor emission scenario. The impact of predicted changes in climate and global background ozone is estimated to increase surface ozone over most of the U.S; the 5th - 95th percentile range for daily 8-hour maximum surface ozone increases from 31-79 ppbV to 30-87 ppbV between the present and future time periods. The analysis of a set ofmore » meteorological drivers suggests that these mostly will add to increasing ozone, but the set of simulations conducted does not allow to separate this effect from that through enhanced global background ozone. Statistically the most robust positive feedbacks are through increased temperature, biogenic emissions and solar radiation. Stringent emission controls can counteract these feedbacks and if considered, we estimate large reductions in surface ozone with the 5th-95th percentile reduced to 27-55 ppbV. A comparison of the high-resolution projections to global model projections shows that even though the global model is biased high in surface ozone compared to the regional model and compared to observations, both the global and the regional model predict similar changes in ozone between the present and future time periods. However, on smaller spatial scales, the regional predictions show more pronounced changes between urban and rural regimes that cannot be resolved at the coarse resolution of global model. In addition, the sign of the changes in overall ozone mixing ratios can be different between the global and the regional predictions in certain regions, such as the Western U.S. This study confirms the key role of emission control strategies in future air quality predictions and demonstrates the need for considering degradation of air quality with future climate change in emission policy making. It also illustrates the need for high resolution modeling when the objective is to address regional and local air quality or establish links to human health and society.« less

An approach to secure weather and climate models against hardware faults

NASA Astrophysics Data System (ADS)

Düben, Peter D.; Dawson, Andrew

2017-03-01

Enabling Earth System models to run efficiently on future supercomputers is a serious challenge for model development. Many publications study efficient parallelization to allow better scaling of performance on an increasing number of computing cores. However, one of the most alarming threats for weather and climate predictions on future high performance computing architectures is widely ignored: the presence of hardware faults that will frequently hit large applications as we approach exascale supercomputing. Changes in the structure of weather and climate models that would allow them to be resilient against hardware faults are hardly discussed in the model development community. In this paper, we present an approach to secure the dynamical core of weather and climate models against hardware faults using a backup system that stores coarse resolution copies of prognostic variables. Frequent checks of the model fields on the backup grid allow the detection of severe hardware faults, and prognostic variables that are changed by hardware faults on the model grid can be restored from the backup grid to continue model simulations with no significant delay. To justify the approach, we perform model simulations with a C-grid shallow water model in the presence of frequent hardware faults. As long as the backup system is used, simulations do not crash and a high level of model quality can be maintained. The overhead due to the backup system is reasonable and additional storage requirements are small. Runtime is increased by only 13 % for the shallow water model.

An approach to secure weather and climate models against hardware faults

NASA Astrophysics Data System (ADS)

Düben, Peter; Dawson, Andrew

2017-04-01

Enabling Earth System models to run efficiently on future supercomputers is a serious challenge for model development. Many publications study efficient parallelisation to allow better scaling of performance on an increasing number of computing cores. However, one of the most alarming threats for weather and climate predictions on future high performance computing architectures is widely ignored: the presence of hardware faults that will frequently hit large applications as we approach exascale supercomputing. Changes in the structure of weather and climate models that would allow them to be resilient against hardware faults are hardly discussed in the model development community. We present an approach to secure the dynamical core of weather and climate models against hardware faults using a backup system that stores coarse resolution copies of prognostic variables. Frequent checks of the model fields on the backup grid allow the detection of severe hardware faults, and prognostic variables that are changed by hardware faults on the model grid can be restored from the backup grid to continue model simulations with no significant delay. To justify the approach, we perform simulations with a C-grid shallow water model in the presence of frequent hardware faults. As long as the backup system is used, simulations do not crash and a high level of model quality can be maintained. The overhead due to the backup system is reasonable and additional storage requirements are small. Runtime is increased by only 13% for the shallow water model.

Validation of AIRS V6 Surface Temperature over Greenland with GCN and NOAA Stations

NASA Technical Reports Server (NTRS)

Lee, Jae N.; Hearty, Thomas; Cullather, Richard; Nowicki, Sophie; Susskind, Joel

2016-01-01

This work compares the temporal and spatial characteristics of the AIRSAMSU (Atmospheric Infrared Sounder Advanced Microwave Sounding Unit A) Version 6 and MODIS (Moderate resolution Imaging Spectroradiometer) Collection 5 derived surface temperatures over Greenland. To estimate uncertainties in space-based surface temperature measurements, we re-projected the MODIS Ice Surface Temperature (IST) to 0.5 by 0.5 degree spatial resolution. We also re-gridded AIRS Skin Temperature (Ts) into the same grid but classified with different cloud conditions and surface types. These co-located data sets make intercomparison between the two instruments relatively straightforward. Using this approach, the spatial comparison between the monthly mean AIRS Ts and MODIS IST is in good agreement with RMS 2K for May 2012. This approach also allows the detection of any long-term calibration drift and the careful examination of calibration consistency in the MODIS and AIRS temperature data record. The temporal correlations between temperature data are also compared with those from in-situ measurements from GC-Net (GCN) and NOAA stations. The coherent time series of surface temperature evident in the correlation between AIRS Ts and GCN temperatures suggest that at monthly time scales both observations capture the same climate signal over Greenland. It is also suggested that AIRS surface air temperature (Ta) can be used to estimate the boundary layer inversion.

New smoke predictions for Alaska in NOAA’s National Air Quality Forecast Capability

NASA Astrophysics Data System (ADS)

Davidson, P. M.; Ruminski, M.; Draxler, R.; Kondragunta, S.; Zeng, J.; Rolph, G.; Stajner, I.; Manikin, G.

2009-12-01

Smoke from wildfire is an important component of fine particle pollution, which is responsible for tens of thousands of premature deaths each year in the US. In Alaska, wildfire smoke is the leading cause of poor air quality in summer. Smoke forecast guidance helps air quality forecasters and the public take steps to limit exposure to airborne particulate matter. A new smoke forecast guidance tool, built by a cross-NOAA team, leverages efforts of NOAA’s partners at the USFS on wildfire emissions information, and with EPA, in coordinating with state/local air quality forecasters. Required operational deployment criteria, in categories of objective verification, subjective feedback, and production readiness, have been demonstrated in experimental testing during 2008-2009, for addition to the operational products in NOAA's National Air Quality Forecast Capability. The Alaska smoke forecast tool is an adaptation of NOAA’s smoke predictions implemented operationally for the lower 48 states (CONUS) in 2007. The tool integrates satellite information on location of wildfires with weather (North American mesoscale model) and smoke dispersion (HYSPLIT) models to produce daily predictions of smoke transport for Alaska, in binary and graphical formats. Hour-by hour predictions at 12km grid resolution of smoke at the surface and in the column are provided each day by 13 UTC, extending through midnight next day. Forecast accuracy and reliability are monitored against benchmark criteria for accuracy and reliability. While wildfire activity in the CONUS is year-round, the intense wildfire activity in AK is limited to the summer. Initial experimental testing during summer 2008 was hindered by unusually limited wildfire activity and very cloudy conditions. In contrast, heavier than average wildfire activity during summer 2009 provided a representative basis (more than 60 days of wildfire smoke) for demonstrating required prediction accuracy. A new satellite observation product was developed for routine near-real time verification of these predictions. The footprint of the predicted smoke from identified fires is verified with satellite observations of the spatial extent of smoke aerosols (5km resolution). Based on geostationary aerosol optical depth measurements that provide good time resolution of the horizontal spatial extent of the plumes, these observations do not yield quantitative concentrations of smoke particles at the surface. Predicted surface smoke concentrations are consistent with the limited number of in situ observations of total fine particle mass from all sources; however they are much higher than predicted for most CONUS fires. To assess uncertainty associated with fire emissions estimates, sensitivity analyses are in progress.

RESOLVING FINE SCALE IN AIR TOXICS MODELING AND THE IMPORTANCE OF ITS SUB-GRID VARIABILITY FOR EXPOSURE ESTIMATES

EPA Science Inventory

This presentation explains the importance of the fine-scale features for air toxics exposure modeling. The paper presents a new approach to combine local-scale and regional model results for the National Air Toxic Assessment. The technique has been evaluated with a chemical tra...

Experimental Determination of Demand Response Control Models and Cost of Control for Ensembles of Window-Mount Air Conditioners

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

Geller, Drew Adam; Backhaus, Scott N.

Control of consumer electrical devices for providing electrical grid services is expanding in both the scope and the diversity of loads that are engaged in control, but there are few experimentally-based models of these devices suitable for control designs and for assessing the cost of control. A laboratory-scale test system is developed to experimentally evaluate the use of a simple window-mount air conditioner for electrical grid regulation services. The experimental test bed is a single, isolated air conditioner embedded in a test system that both emulates the thermodynamics of an air conditioned room and also isolates the air conditioner frommore » the real-world external environmental and human variables that perturb the careful measurements required to capture a model that fully characterizes both the control response functions and the cost of control. The control response functions and cost of control are measured using harmonic perturbation of the temperature set point and a test protocol that further isolates the air conditioner from low frequency environmental variability.« less

SIMULATION OF A REACTING POLLUTANT PUFF USING AN ADAPTIVE GRID ALGORITHM

EPA Science Inventory

A new dynamic solution adaptive grid algorithm DSAGA-PPM, has been developed for use in air quality modeling. In this paper, this algorithm is described and evaluated with a test problem. Cone-shaped distributions of various chemical species undergoing chemical reactions are rota...

Usefulness of AIRS-Derived OLR, Temperature, Water Vapor and Cloudiness Anomaly Trends for GCM Validation

NASA Technical Reports Server (NTRS)

Molnar, Gyula I.; Susskind, Joel; Iredell, Lena F.

2010-01-01

Mainly due to their global nature, satellite observations can provide a very useful basis for GCM validations. In particular, satellite sounders such as AIRS provide 3-D spatial information (most useful for GCMs), so the question arises: can we use AIRS datasets for climate variability assessments? We show that the recent (September 2002 February 2010) CERES-observed negative trend in OLR of approx.-0.1 W/sq m/yr averaged over the globe is found in the AIRS OLR data as well. Most importantly, even minute details (down to 1 x 1 degree GCM-scale resolution) of spatial and temporal anomalies and trends of OLR as observed by CERES and computed based on AIRS-retrieved surface and atmospheric geophysical parameters over this time period are essentially the same. The correspondence can be seen even in the very large spatial variations of these trends with local values ranging from -2.6 W/sq m/yr to +3.0 W/sq m/yr in the tropics, for example. This essentially perfect agreement of OLR anomalies and trends derived from observations by two different instruments, in totally independent and different manners, implies that both sets of results must be highly accurate, and indirectly validates the anomalies and trends of other AIRS derived products as well. These products show that global and regional anomalies and trends of OLR, water vapor and cloud cover over the last 7+ years are strongly influenced by EI-Nino-La Nina cycles . We have created climate parameter anomaly datasets using AIRS retrievals which can be compared directly with coupled GCM climate variability assessments. Moreover, interrelationships of these anomalies and trends should also be similar between the observed and GCM-generated datasets, and, in cases of discrepancies, GCM parameterizations could be improved based on the relationships observed in the data. First, we assess spatial "trends" of variability of climatic parameter anomalies [since anomalies relative to the seasonal cycle are good proxies of climate variability] at the common 1x1 degree GCM grid-scale by creating spatial anomaly "trends" based on the first 7+ years of AIRS Version 5 Leve13 data. We suggest that modelers should compare these with their (coupled) GCM's performance covering the same period. We evaluate temporal variability and interrelations of climatic anomalies on global to regional e.g., deep Tropical Hovmoller diagrams, El-Nino-related variability scales, and show the effects of El-Nino-La Nina activity on tropical anomalies and trends of water vapor cloud cover and OLR. For GCMs to be trusted highly for long-term climate change predictions, they should be able to reproduce findings similar to these. In summary, the AIRS-based climate variability analyses provide high quality, informative and physically plausible interrelationships among OLR, temperature, humidity and cloud cover both on the spatial and temporal scales. GCM validations can use these results even directly, e. g., by creating 1x1 degree trendmaps for the same period in coupled climate simulations.

DEVELOPMENT OF MESOSCALE AIR QUALITY SIMULATION MODELS. VOLUME 1. COMPARATIVE SENSITIVITY STUDIES OF PUFF, PLUME, AND GRID MODELS FOR LONG DISTANCE DISPERSION

EPA Science Inventory

This report provides detailed comparisons and sensitivity analyses of three candidate models, MESOPLUME, MESOPUFF, and MESOGRID. This was not a validation study; there was no suitable regional air quality data base for the Four Corners area. Rather, the models have been evaluated...

USING MM5V3 WITH ETA ANALYSES FOR AIR-QUALITY MODELING AT THE EPA

EPA Science Inventory

Efforts have been underway since MM5v3 was released in July 1999 to set up air-quality simulations using Eta analyses as background fields. Our previous simulations used a one-way quadruple-nested set of domains with horizontal grid spacing of 108, 36, 12 and 4 km. With Eta a...

NCAR global model topography generation software for unstructured grids

NASA Astrophysics Data System (ADS)

Lauritzen, P. H.; Bacmeister, J. T.; Callaghan, P. F.; Taylor, M. A.

2015-06-01

It is the purpose of this paper to document the NCAR global model topography generation software for unstructured grids. Given a model grid, the software computes the fraction of the grid box covered by land, the gridbox mean elevation, and associated sub-grid scale variances commonly used for gravity wave and turbulent mountain stress parameterizations. The software supports regular latitude-longitude grids as well as unstructured grids; e.g. icosahedral, Voronoi, cubed-sphere and variable resolution grids. As an example application and in the spirit of documenting model development, exploratory simulations illustrating the impacts of topographic smoothing with the NCAR-DOE CESM (Community Earth System Model) CAM5.2-SE (Community Atmosphere Model version 5.2 - Spectral Elements dynamical core) are shown.

Significantly Reduced Health Burden from Ambient Air Pollution in the United States under Emission Reductions from 1990 to 2016

NASA Astrophysics Data System (ADS)

Zhang, Y.; West, J. J.; Mathur, R.; Xing, J.; Hogrefe, C.; Roselle, S. J.; Bash, J. O.; Pleim, J. E.; Gan, C. M.; Wong, D. C.; Tong, D.; van Donkelaar, A.; Martin, R.

2017-12-01

The 2015 Global Burden of Disease (GBD) study has listed air pollution as the fourth-ranking global mortality risk factor. Few studies have attempted to understand how these burdens change through time, especially in the United States (US). Here we aim to estimate air pollution-related mortality in the continental US for each year from 1990 to 2016, to understand the trend over this time period. We also analyze the relative contributions of changes in air pollutant concentrations, population, and baseline mortality to the overall trend and to the inter-annual variability in mortality estimates. To achieve this goal, we use a 21-year model simulation of PM2.5 and O3 concentrations from 1990 to 2010, with grid resolution of 36km×36km. We will also use two additional datasets informed by satellite observations: one from the North American Chemical Reanalysis project, which uses OMI NO2 and MODIS AOD observations for data assimilation to constrain ozone and PM2.5 between 2006-2016, and the other from satellite-derived estimates of ground-level PM2.5 using satellite AOD combined with the GEOS-Chem chemical transport model between 1998-2015. For the 21-year simulation, we find that the PM2.5-related mortality burden from ischemic heart disease, chronic obstructive pulmonary disease, lung cancer, and stroke, has steadily decreased, with a reduction of 51% from 1990 to 2010. The PM2.5 -related mortality burden would have decreased only by 27% if the PM2.5 concentrations had stayed at the 1990 level, due to decreases in baseline mortality rates for major diseases affected by PM2.5. The O3 mortality burden has smaller inter-annual variability than the PM2.5-related burden from 1990 to 2010, but the variability for the concentration-change only mortality burden is higher for O3 than for PM2.5. The O3-related mortality burden increased by 12% from 1990 to 2010, despite ozone decreases, mainly due to increases in the baseline mortality rates and population. The O3-related mortality burden would have increased by 61% if the O3 concentration had stayed at the 1990 level. Our preliminary results suggest that air quality improvements have significantly reduced the health burden over the past two decades.

Towards an operational high-resolution air quality forecasting system at ECCC

NASA Astrophysics Data System (ADS)

Munoz-Alpizar, Rodrigo; Stroud, Craig; Ren, Shuzhan; Belair, Stephane; Leroyer, Sylvie; Souvanlasy, Vanh; Spacek, Lubos; Pavlovic, Radenko; Davignon, Didier; Moran, Moran

2017-04-01

Urban environments are particularly sensitive to weather, air quality (AQ), and climatic conditions. Despite the efforts made in Canada to reduce pollution in urban areas, AQ continues to be a concern for the population, especially during short-term episodes that could lead to exceedances of daily air quality standards. Furthermore, urban air pollution has long been associated with significant adverse health effects. In Canada, the large percentage of the population living in urban areas ( 81%, according to the Canada's 2011 census) is exposed to elevated air pollution due to local emissions sources. Thus, in order to improve the services offered to the Canadian public, Environment and Climate Change Canada has launched an initiative to develop a high-resolution air quality prediction capacity for urban areas in Canada. This presentation will show observed pollution trends (2010-2016) for Canadian mega-cities along with some preliminary high-resolution air quality modelling results. Short-term and long-term plans for urban AQ forecasting in Canada will also be described.

The Role of Wave Cyclones in Transporting Boundary Layer Air to the Free Troposphere During the Spring 2001 NASA / TRACE-P Experiment

NASA Technical Reports Server (NTRS)

Fuelberg, Henry E.; Hannan, J. R.; Crawford, J. H.; Sachse, G. W.; Blake, D. R.

2003-01-01

Transport of boundary layer air to the free troposphere by cyclones during NASA's Transport and Chemical Evolution over the Pacific (TRACE-P) experiment is investigated. Airstreams responsible for boundary layer venting are diagnosed using results from a high-resolution meteorological model (MM5) together with in situ and remotely sensed chemical data. Hourly wind data from the MM5 are used to calculate three-dimensional grids of backward air trajectories. A reverse domain filling (RDF) technique then is employed to examine the characteristics of airstreams over the computational domain, and to isolate airstreams ascending from the boundary layer to the free troposphere during the previous 36 hours. Two cases are examined in detail. Results show that airstreams responsible for venting the boundary layer differ considerably from those described by classic conceptual models and in the recent literature. In addition, airstreams sampled by the TRACE-P aircraft are found to exhibit large variability in chemical concentrations. This variability is due to differences in the boundary layer histories of individual airstreams with respect to anthropogenic sources over continental Asia and Japan. Complex interactions between successive wave cyclones also are found to be important in determining the chemical composition of the airstreams. Particularly important is the process of post-cold frontal boundary layer air being rapidly transported offshore and recirculated into ascending airstreams of upstream cyclones.

An investigation of the impact of variations of DVH calculation algorithms on DVH dependant radiation therapy plan evaluation metrics

NASA Astrophysics Data System (ADS)

Kennedy, A. M.; Lane, J.; Ebert, M. A.

2014-03-01

Plan review systems often allow dose volume histogram (DVH) recalculation as part of a quality assurance process for trials. A review of the algorithms provided by a number of systems indicated that they are often very similar. One notable point of variation between implementations is in the location and frequency of dose sampling. This study explored the impact such variations can have on DVH based plan evaluation metrics (Normal Tissue Complication Probability (NTCP), min, mean and max dose), for a plan with small structures placed over areas of high dose gradient. Dose grids considered were exported from the original planning system at a range of resolutions. We found that for the CT based resolutions used in all but one plan review systems (CT and CT with guaranteed minimum number of sampling voxels in the x and y direction) results were very similar and changed in a similar manner with changes in the dose grid resolution despite the extreme conditions. Differences became noticeable however when resolution was increased in the axial (z) direction. Evaluation metrics also varied differently with changing dose grid for CT based resolutions compared to dose grid based resolutions. This suggests that if DVHs are being compared between systems that use a different basis for selecting sampling resolution it may become important to confirm that a similar resolution was used during calculation.

Quantifying Co-benefits of Renewable Energy through Integrated Electricity and Air Quality Modeling

NASA Astrophysics Data System (ADS)

Abel, D.

2016-12-01

This work focuses on the coordination of electricity sector changes with air quality and health improvement strategies through the integration of electricity and air quality models. Two energy models are used to calculate emission perturbations associated with changes in generation technology (20% generation from solar photovoltaics) and demand (future electricity use under a warmer climate). Impacts from increased solar PV penetration are simulated with the electricity model GridView, in collaboration with the National Renewable Energy Laboratory (NREL). Generation results are used to scale power plant emissions from an inventory developed by the Lake Michigan Air Directors Consortium (LADCO). Perturbed emissions and are used to calculate secondary particulate matter with the Community Multiscale Air Quality (CMAQ) model. We find that electricity NOx and SO2 emissions decrease at a rate similar to the total fraction of electricity supplied by solar. Across the Eastern U.S. region, average PM2.5 is reduced 5% over the summer, with highest reduction in regions and on days of greater PM2.5. A similar approach evaluates the air quality impacts of elevated electricity demand under a warmer climate. Meteorology is selected from the North American Regional Climate Change Assessment Program (NARCCAP) and input to a building energy model, eQUEST, to assess electricity demand as a function of ambient temperature. The associated generation and emissions are calculated on a plant-by-plant basis by the MyPower power sector model. These emissions are referenced to the 2011 National Emissions Inventory to be modeled in CMAQ for the Eastern U.S. and extended to health impact evaluation with the Environmental Benefits Mapping and Analysis Program (BenMAP). All results focus on the air quality and health consequences of energy system changes, considering grid-level changes to meet climate and air quality goals.

Linking Meteorology, Air Quality Models and Observations to ...

EPA Pesticide Factsheets

Epidemiologic studies are critical in establishing the association between exposure to air pollutants and adverse health effects. Results of epidemiologic studies are used by U.S. EPA in developing air quality standards to protect the public from the health effects of air pollutants. A major challenge in environmental epidemiology is adequate exposure characterization. Numerous health studies have used measurements from a few central-site ambient monitors to characterize air pollution exposures. Relying solely on central-site ambient monitors does not account for the spatial-heterogeneity of ambient air pollution patterns, the temporal variability in ambient concentrations, nor the influence of infiltration and indoor sources. Central-site monitoring becomes even more problematic for certain air pollutants that exhibit significant spatial heterogeneity. Statistical interpolation techniques and passive monitoring methods can provide additional spatial resolution in ambient concentration estimates. In addition, spatio-temporal models, which integrate GIS data and other factors, such as meteorology, have also been developed to produce more resolved estimates of ambient concentrations. Models, such as the Community Multi-Scale Air Quality (CMAQ) model, estimate ambient concentrations by combining information on meteorology, source emissions, and chemical-fate and transport. Hybrid modeling approaches, which integrate regional scale models with local scale dispersion

Developing high-resolution urban scale heavy-duty truck emission inventory using the data-driven truck activity model output

NASA Astrophysics Data System (ADS)

Perugu, Harikishan; Wei, Heng; Yao, Zhuo

2017-04-01

Air quality modelers often rely on regional travel demand models to estimate the vehicle activity data for emission models, however, most of the current travel demand models can only output reliable person travel activity rather than goods/service specific travel activity. This paper presents the successful application of data-driven, Spatial Regression and output optimization Truck model (SPARE-Truck) to develop truck-related activity inputs for the mobile emission model, and eventually to produce truck specific gridded emissions. To validate the proposed methodology, the Cincinnati metropolitan area in United States was selected as a case study site. From the results, it is found that the truck miles traveled predicted using traditional methods tend to underestimate - overall 32% less than proposed model- truck miles traveled. The coefficient of determination values for different truck types range between 0.82 and 0.97, except the motor homes which showed least model fit with 0.51. Consequently, the emission inventories calculated from the traditional methods were also underestimated i.e. -37% for NOx, -35% for SO2, -43% for VOC, -43% for BC, -47% for OC and - 49% for PM2.5. Further, the proposed method also predicted within ∼7% of the national emission inventory for all pollutants. The bottom-up gridding methodology used in this paper could allocate the emissions to grid cell where more truck activity is expected, and it is verified against regional land-use data. Most importantly, using proposed method it is easy to segregate gridded emission inventory by truck type, which is of particular interest for decision makers, since currently there is no reliable method to test different truck-category specific travel-demand management strategies for air pollution control.

Characterizing Intra-Urban Air Quality Gradients with a Spatially-Distributed Network

NASA Astrophysics Data System (ADS)

Zimmerman, N.; Ellis, A.; Schurman, M. I.; Gu, P.; Li, H.; Snell, L.; Gu, J.; Subramanian, R.; Robinson, A. L.; Apte, J.; Presto, A. A.

2016-12-01

City-wide air pollution measurements have typically relied on regulatory or research monitoring sites with low spatial density to assess population-scale exposure. However, air pollutant concentrations exhibit significant spatial variability depending on local sources and features of the built environment, which may not be well captured by the existing monitoring regime. To better understand urban spatial and temporal pollution gradients at 1 km resolution, a network of 12 real-time air quality monitoring stations was deployed beginning July 2016 in Pittsburgh, PA. The stations were deployed at sites along an urban-rural transect and in urban locations with a range of traffic, restaurant, and tall building densities to examine the impact of various modifiable factors. Measurements from the stationary monitoring stations were further supported by mobile monitoring, which provided higher spatial resolution pollutant measurements on nearby roadways and enabled routine calibration checks. The stationary monitoring measurements comprise ultrafine particle number (Aerosol Dynamics "MAGIC" CPC), PM2.5 (Met One Neighborhood PM Monitor), black carbon (Met One BC 1050), and a new low-cost air quality monitor, the Real-time Affordable Multi-Pollutant (RAMP) sensor package for measuring CO, NO2, SO2, O3, CO2, temperature and relative humidity. High time-resolution (sub-minute) measurements across the distributed monitoring network enable insight into dynamic pollutant behaviour. Our preliminary findings show that our instruments are sensitive to PM2.5 gradients exceeding 2 micro-grams per cubic meter and ultrafine particle gradients exceeding 1000 particles per cubic centimeter. Additionally, we have developed rigorous calibration protocols to characterize the RAMP sensor response and drift, as well as multiple linear regression models to convert sensor response into pollutant concentrations that are comparable to reference instrumentation.

Application and evaluation of high-resolution WRF-CMAQ with simple urban parameterization.

EPA Science Inventory

The 2-way coupled WRF-CMAQ meteorology and air quality modeling system is evaluated for high-resolution applications by comparing to a regional air quality field study (Discover-AQ). The model was modified to better account for the effects of urban environments. High-resolution...

Application and evaluation of high-resolution WRF-CMAQ with simple urban parameterization

EPA Science Inventory

The 2-way coupled WRF-CMAQ meteorology and air quality modeling system is evaluated for high-resolution applications by comparing to a regional air quality field study (Discover-AQ). The model was modified to better account for the effects of urban environments. High-resolution...

New Antarctic Gravity Anomaly Grid for Enhanced Geodetic and Geophysical Studies in Antarctica

PubMed Central

Scheinert, M.; Ferraccioli, F.; Schwabe, J.; Bell, R.; Studinger, M.; Damaske, D.; Jokat, W.; Aleshkova, N.; Jordan, T.; Leitchenkov, G.; Blankenship, D. D.; Damiani, T. M.; Young, D.; Cochran, J. R.; Richter, T. D.

2018-01-01

Gravity surveying is challenging in Antarctica because of its hostile environment and inaccessibility. Nevertheless, many ground-based, airborne and shipborne gravity campaigns have been completed by the geophysical and geodetic communities since the 1980s. We present the first modern Antarctic-wide gravity data compilation derived from 13 million data points covering an area of 10 million km2, which corresponds to 73% coverage of the continent. The remove-compute-restore technique was applied for gridding, which facilitated levelling of the different gravity datasets with respect to an Earth Gravity Model derived from satellite data alone. The resulting free-air and Bouguer gravity anomaly grids of 10 km resolution are publicly available. These grids will enable new high-resolution combined Earth Gravity Models to be derived and represent a major step forward towards solving the geodetic polar data gap problem. They provide a new tool to investigate continental-scale lithospheric structure and geological evolution of Antarctica. PMID:29326484

New Antarctic Gravity Anomaly Grid for Enhanced Geodetic and Geophysical Studies in Antarctica.

PubMed

Scheinert, M; Ferraccioli, F; Schwabe, J; Bell, R; Studinger, M; Damaske, D; Jokat, W; Aleshkova, N; Jordan, T; Leitchenkov, G; Blankenship, D D; Damiani, T M; Young, D; Cochran, J R; Richter, T D

2016-01-28

Gravity surveying is challenging in Antarctica because of its hostile environment and inaccessibility. Nevertheless, many ground-based, airborne and shipborne gravity campaigns have been completed by the geophysical and geodetic communities since the 1980s. We present the first modern Antarctic-wide gravity data compilation derived from 13 million data points covering an area of 10 million km 2 , which corresponds to 73% coverage of the continent. The remove-compute-restore technique was applied for gridding, which facilitated levelling of the different gravity datasets with respect to an Earth Gravity Model derived from satellite data alone. The resulting free-air and Bouguer gravity anomaly grids of 10 km resolution are publicly available. These grids will enable new high-resolution combined Earth Gravity Models to be derived and represent a major step forward towards solving the geodetic polar data gap problem. They provide a new tool to investigate continental-scale lithospheric structure and geological evolution of Antarctica.

SIMULATION OF DISPERSION OF A POWER PLANT PLUME USING AN ADAPTIVE GRID ALGORITHM. (R827028)

EPA Science Inventory

A new dynamic adaptive grid algorithm has been developed for use in air quality modeling. This algorithm uses a higher order numerical scheme––the piecewise parabolic method (PPM)––for computing advective solution fields; a weight function capable o...

CFD MODELING OF FINE SCALE FLOW AND TRANSPORT IN THE HOUSTON METROPOLITAN AREA, TEXAS

EPA Science Inventory

Fine scale modeling of flows and air quality in Houston, Texas is being performed; the use of computational fluid dynamics (CFD) modeling is being applied to investigate the influence of morphologic structures on the within-grid transport and dispersion of sources in grid models ...

Adding Four- Dimensional Data Assimilation (a.k.a. grid nudging) to MPAS

EPA Science Inventory

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 mod...

Population exposure to hazardous air quality due to the 2015 fires in Equatorial Asia.

PubMed

Crippa, P; Castruccio, S; Archer-Nicholls, S; Lebron, G B; Kuwata, M; Thota, A; Sumin, S; Butt, E; Wiedinmyer, C; Spracklen, D V

2016-11-16

Vegetation and peatland fires cause poor air quality and thousands of premature deaths across densely populated regions in Equatorial Asia. Strong El-Niño and positive Indian Ocean Dipole conditions are associated with an increase in the frequency and intensity of wildfires in Indonesia and Borneo, enhancing population exposure to hazardous concentrations of smoke and air pollutants. Here we investigate the impact on air quality and population exposure of wildfires in Equatorial Asia during Fall 2015, which were the largest over the past two decades. We performed high-resolution simulations using the Weather Research and Forecasting model with Chemistry based on a new fire emission product. The model captures the spatio-temporal variability of extreme pollution episodes relative to space- and ground-based observations and allows for identification of pollution sources and transport over Equatorial Asia. We calculate that high particulate matter concentrations from fires during Fall 2015 were responsible for persistent exposure of 69 million people to unhealthy air quality conditions. Short-term exposure to this pollution may have caused 11,880 (6,153-17,270) excess mortalities. Results from this research provide decision-relevant information to policy makers regarding the impact of land use changes and human driven deforestation on fire frequency and population exposure to degraded air quality.

Population exposure to hazardous air quality due to the 2015 fires in Equatorial Asia

PubMed Central

Crippa, P.; Castruccio, S.; Archer-Nicholls, S.; Lebron, G. B.; Kuwata, M.; Thota, A.; Sumin, S.; Butt, E.; Wiedinmyer, C.; Spracklen, D. V.

2016-01-01

Vegetation and peatland fires cause poor air quality and thousands of premature deaths across densely populated regions in Equatorial Asia. Strong El-Niño and positive Indian Ocean Dipole conditions are associated with an increase in the frequency and intensity of wildfires in Indonesia and Borneo, enhancing population exposure to hazardous concentrations of smoke and air pollutants. Here we investigate the impact on air quality and population exposure of wildfires in Equatorial Asia during Fall 2015, which were the largest over the past two decades. We performed high-resolution simulations using the Weather Research and Forecasting model with Chemistry based on a new fire emission product. The model captures the spatio-temporal variability of extreme pollution episodes relative to space- and ground-based observations and allows for identification of pollution sources and transport over Equatorial Asia. We calculate that high particulate matter concentrations from fires during Fall 2015 were responsible for persistent exposure of 69 million people to unhealthy air quality conditions. Short-term exposure to this pollution may have caused 11,880 (6,153–17,270) excess mortalities. Results from this research provide decision-relevant information to policy makers regarding the impact of land use changes and human driven deforestation on fire frequency and population exposure to degraded air quality. PMID:27848989

Performance characteristics of MM5-SMOKE-CMAQ for a summer photochemical episode in southeast England, United Kingdom

NASA Astrophysics Data System (ADS)

Yu, Y.; Sokhi, R. S.; Kitwiroon, N.; Middleton, D. R.; Fisher, B.

In this study a modelling system consisting of Mesoscale Model (MM5), Sparse Matrix Operator Kernel Emissions (SMOKE) and Community Multiscale Air Quality (CMAQ) model has been applied to a summer photochemical period in southeast England, UK. Ozone (O 3), nitrogen dioxide (NO 2) and particulate matter (PM 2.5) concentrations modelled with different horizontal grid resolutions (9 and 3 km) were evaluated against available ground-level observations from the UK Automatic Urban and Rural Network (AURN) and London Air Quality Network (LAQN) for the period of 24-28 June 2001 with a focus on O 3 predictions. This effort, which represents the first comprehensive performance evaluation of the modelling system over a UK domain, reveals that CMAQ's ability to reproduce surface O 3 observations varies with O 3 concentrations. It underpredicts O 3 mixing ratios on high-O 3 days and overpredicts the maximum and minimum hourly O 3 values for most low-O 3 days. Model sensitivity analysis with doubled anthropogenic NO x or volatile organic compounds (VOC) emissions and analysis of the daylight-averaged levels of OX (sum of O 3 and NO 2) as a function of NO x revealed that the undereprediction of peak O 3 concentrations on high-O 3 days is caused by the underprediction of regional contribution and to a lesser extent local production, which might be related to the underestimation of European emissions in EMEP inventory and the lacked reactivity of the modelled atmosphere. CMAQ systematically underpredicts hourly NO 2 mixing ratios but captures the temporal variations. The normalized mean bias for hourly NO 2, although much larger than that for O 3, falls well within the generally accepted range of -20% to -50%. CMAQ with both resolutions (9 and 3 km) significantly underpredicts PM 2.5 mass concentrations and fails to reproduce its temporal variations. While model performance for O 3 and PM 2.5 are not very sensitive to model grid resolutions, a better agreement between modelled and measured hourly NO 2 mixing ratios was achieved with higher resolution. Further investigation into the uncertainties in meteorological input, uncertainties in emissions, as well as representation of physical and chemical processes (e.g. chemical mechanism) in the model is needed to identify the causes for the discrepancies between observations and predictions.

Endosulfan in China 2-emissions and residues.

PubMed

Jia, Hongliang; Sun, Yeqing; Li, Yi-Fan; Tian, Chongguo; Wang, Degao; Yang, Meng; Ding, Yongshen; Ma, Jianmin

2009-05-01

Endosulfan is one of the organochlorine pesticides (OCPs) and also a candidate to be included in a group of new persistent organic pollutants (UNEP 2007). The first national endosulfan usage inventories in China with 1/4 degrees longitude by 1/6 degrees latitude resolution has been reported in an accompanying paper. In the second part of the paper, we compiled the gridded historical emissions and soil residues of endosulfan in China from the usage inventories. Based on the residue/emission data, gridded concentrations of endosulfan in Chinese soil and air have been calculated. These inventories will provide valuable data for the further study of endosulfan. Emission and residue of endosulfan were calculated from endosulfan usage by using a simplified gridded pesticide emission and residue model-SGPERM, which is an integrated modeling system combining mathematical model, database management system, and geographic information system. By using the emission and residue inventories, annual air and soil concentrations of endosulfan in each cell were determined. Historical gridded emission and residue inventories of alpha- and beta-endosulfan in agricultural soil in China with 1/4 degrees longitude by 1/6 degrees latitude resolution have been created. Total emissions were around 10,800 t, with alpha-endosulfan at 7,400 t and beta-endosulfan at 3,400 t from 1994 to 2004. The highest residues were 140 t for alpha-endosulfan and 390 t for beta-endosulfan, and the lowest residues were 0.7 t for alpha-endosulfan and 170 t for beta-endosulfan in 2004 in Chinese agricultural soil where endosulfan was applied. Based on the emission and residue inventories, concentrations of alpha- and beta-endosulfan in Chinese air and agricultural surface soil were also calculated for each grid cell. We have estimated annual averaged air concentrations and the annual minimum and maximum soil concentrations across China. The real concentrations will be different from season to season. Although our model does not consider the transport of the insecticide in the atmosphere, which could be very important in some areas during some special time, the estimated concentrations of endosulfan in Chinese air and soil derived from the endosulfan emission and residue inventories are in general consistent with the published monitoring data. To our knowledge, this work is the first inventory of this kind for endosulfan published on a national scale. Concentrations of the chemical in Chinese air and agricultural surface soil were calculated for each grid cell. Results show that the estimated concentrations of endosulfan in Chinese air and soil agree reasonably well with the monitoring data in general. The gridded endosulfan emission/residue inventories and also the air and soil concentration inventories created in this study will be updated upon availability of new information, including usage and monitoring data. The establishment of these inventories for the OCP is important for both scientific communities and policy makers.

Measuring Methane from Cars, Ships, Airplanes, Helicopters and Drones Using High-Speed Open-Path Technology

NASA Astrophysics Data System (ADS)

Burba, George; Anderson, Tyler; Biraud, Sebastien; Caulton, Dana; von Fischer, Joe; Gioli, Beniamino; Hanson, Chad; Ham, Jay; Kohnert, Katrin; Larmanou, Eric; Levy, Peter; Polidori, Andrea; Pikelnaya, Olga; Sachs, Torsten; Serafimovich, Andrei; Zaldei, Alessandro; Zondlo, Mark; Zulueta, Rommel

2017-04-01

Methane plays a critical role in the radiation balance, chemistry of the atmosphere, and air quality. The major anthropogenic sources of methane include oil and gas development sites, natural gas distribution networks, landfill emissions, and agricultural production. The majority of oil and gas and urban methane emission occurs via variable-rate point sources or diffused spots in topographically challenging terrains (e.g., street tunnels, elevated locations at water treatment plants, vents, etc.). Locating and measuring such methane emissions is challenging when using traditional micrometeorological techniques, and requires development of novel approaches. Landfill methane emissions traditionally assessed at monthly or longer time intervals are subject to large uncertainties because of the snapshot nature of the measurements and the barometric pumping phenomenon. The majority of agricultural and natural methane production occurs in areas with little infrastructure or easily available grid power (e.g., rice fields, arctic and boreal wetlands, tropical mangroves, etc.). A lightweight, high-speed, high-resolution, open-path technology was recently developed for eddy covariance measurements of methane flux, with power consumption 30-150 times below other available technologies. It was designed to run on solar panels or a small generator and be placed in the middle of the methane-producing ecosystem without a need for grid power. Lately, this instrumentation has been utilized increasingly more frequently outside of the traditional use on stationary flux towers. These novel approaches include measurements from various moving platforms, such as cars, aircraft, and ships. Projects included mapping of concentrations and vertical profiles, leak detection and quantification, mobile emission detection from natural gas-powered cars, soil methane flux surveys, etc. This presentation will describe the latest state of the key projects utilizing the novel lightweight low-power high-resolution open-path technology, and will highlight several novel approaches where such instrumentation was used in mobile deployments in urban, agricultural and natural environments by academic institutions, regulatory agencies and industry.

Mobile Measurements of Methane Using High-Speed Open-Path Technology

NASA Astrophysics Data System (ADS)

Burba, G. G.; Anderson, T.; Ediger, K.; von Fischer, J.; Gioli, B.; Ham, J. M.; Hupp, J. R.; Kohnert, K.; Levy, P. E.; Polidori, A.; Pikelnaya, O.; Price, E.; Sachs, T.; Serafimovich, A.; Zondlo, M. A.; Zulueta, R. C.

2016-12-01

Methane plays a critical role in the radiation balance, chemistry of the atmosphere, and air quality. The major anthropogenic sources of CH4 include oil and gas development sites, natural gas distribution networks, landfill emissions, and agricultural production. The majority of oil and gas and urban CH4 emission occurs via variable-rate point sources or diffused spots in topographically challenging terrains (e.g., street tunnels, elevated locations at water treatment plants, vents, etc.). Locating and measuring such CH4 emissions is challenging when using traditional micrometeorological techniques, and requires development of novel approaches. Landfill CH4 emissions traditionally assessed at monthly or longer time intervals are subject to large uncertainties because of the snapshot nature of the measurements and the barometric pumping phenomenon. The majority of agricultural and natural CH4 production occurs in areas with little infrastructure or easily available grid power (e.g., rice fields, arctic and boreal wetlands, tropical mangroves, etc.). A lightweight, high-speed, high-resolution, open-path technology was recently developed for eddy covariance measurements of CH4 flux, with power consumption 30-150 times below other available technologies. It was designed to run on solar panels or a small generator and be placed in the middle of the methane-producing ecosystem without a need for grid power. Lately, this instrumentation has been utilized increasingly more frequently outside of the traditional use on stationary flux towers. These novel approaches include measurements from various moving platforms, such as cars, aircraft, and ships. Projects included mapping of concentrations and vertical profiles, leak detection and quantification, mobile emission detection from natural gas-powered cars, soil CH4 flux surveys, etc. This presentation will describe key projects utilizing the novel lightweight low-power high-resolution open-path technology, and will highlight several novel approaches where such instrumentation was used in mobile deployments in urban, agricultural and natural environments by academic institutions, regulatory agencies and industry.

Gasdynamic model of turbulent combustion in an explosion

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

Kuhl, A.L.; Ferguson, R.E.; Chien, K.Y.

1994-08-31

Proposed here is a gasdynamic model of turbulent combustion in explosions. It is used to investigate turbulent mixing aspects of afterburning found in TNT charges detonated in air. Evolution of the turbulent velocity field was calculated by a high-order Godunov solution of the gasdynamic equations. Adaptive Mesh Refinement (AMR) was used to follow convective-mixing processes on the computational grid. Combustion was then taken into account by a simplified sub-grid model, demonstrating that it was controlled by turbulent mixing. The rate of fuel consumption decayed inversely with time, and was shown to be insensitive to grid resolution.

A High-Resolution Merged Wind Dataset for DYNAMO: Progress and Future Plans

NASA Technical Reports Server (NTRS)

Lang, Timothy J.; Mecikalski, John; Li, Xuanli; Chronis, Themis; Castillo, Tyler; Hoover, Kacie; Brewer, Alan; Churnside, James; McCarty, Brandi; Hein, Paul;

A new vertical grid nesting capability in the Weather Research and Forecasting (WRF) Model

DOE PAGES

Daniels, Megan H.; Lundquist, Katherine A.; Mirocha, Jeffrey D.; ...

2016-09-16

Mesoscale atmospheric models are increasingly used for high-resolution (<3 km) simulations to better resolve smaller-scale flow details. Increased resolution is achieved using mesh refinement via grid nesting, a procedure where multiple computational domains are integrated either concurrently or in series. A constraint in the concurrent nesting framework offered by the Weather Research and Forecasting (WRF) Model is that mesh refinement is restricted to the horizontal dimensions. This limitation prevents control of the grid aspect ratio, leading to numerical errors due to poor grid quality and preventing grid optimization. Here, a procedure permitting vertical nesting for one-way concurrent simulation is developedmore » and validated through idealized cases. The benefits of vertical nesting are demonstrated using both mesoscale and large-eddy simulations (LES). Mesoscale simulations of the Terrain-Induced Rotor Experiment (T-REX) show that vertical grid nesting can alleviate numerical errors due to large aspect ratios on coarse grids, while allowing for higher vertical resolution on fine grids. Furthermore, the coarsening of the parent domain does not result in a significant loss of accuracy on the nested domain. LES of neutral boundary layer flow shows that, by permitting optimal grid aspect ratios on both parent and nested domains, use of vertical nesting yields improved agreement with the theoretical logarithmic velocity profile on both domains. Lastly, vertical grid nesting in WRF opens the path forward for multiscale simulations, allowing more accurate simulations spanning a wider range of scales than previously possible.« less

A new vertical grid nesting capability in the Weather Research and Forecasting (WRF) Model

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

Daniels, Megan H.; Lundquist, Katherine A.; Mirocha, Jeffrey D.

Mesoscale atmospheric models are increasingly used for high-resolution (<3 km) simulations to better resolve smaller-scale flow details. Increased resolution is achieved using mesh refinement via grid nesting, a procedure where multiple computational domains are integrated either concurrently or in series. A constraint in the concurrent nesting framework offered by the Weather Research and Forecasting (WRF) Model is that mesh refinement is restricted to the horizontal dimensions. This limitation prevents control of the grid aspect ratio, leading to numerical errors due to poor grid quality and preventing grid optimization. Here, a procedure permitting vertical nesting for one-way concurrent simulation is developedmore » and validated through idealized cases. The benefits of vertical nesting are demonstrated using both mesoscale and large-eddy simulations (LES). Mesoscale simulations of the Terrain-Induced Rotor Experiment (T-REX) show that vertical grid nesting can alleviate numerical errors due to large aspect ratios on coarse grids, while allowing for higher vertical resolution on fine grids. Furthermore, the coarsening of the parent domain does not result in a significant loss of accuracy on the nested domain. LES of neutral boundary layer flow shows that, by permitting optimal grid aspect ratios on both parent and nested domains, use of vertical nesting yields improved agreement with the theoretical logarithmic velocity profile on both domains. Lastly, vertical grid nesting in WRF opens the path forward for multiscale simulations, allowing more accurate simulations spanning a wider range of scales than previously possible.« less

Assembling Large, Multi-Sensor Climate Datasets Using the SciFlo Grid Workflow System

NASA Astrophysics Data System (ADS)

Wilson, B. D.; Manipon, G.; Xing, Z.; Fetzer, E.

2008-12-01

NASA's Earth Observing System (EOS) is the world's most ambitious facility for studying global climate change. The mandate now is to combine measurements from the instruments on the A-Train platforms (AIRS, AMSR-E, MODIS, MISR, MLS, and CloudSat) and other Earth probes to enable large-scale studies of climate change over periods of years to decades. However, moving from predominantly single-instrument studies to a multi-sensor, measurement-based model for long-duration analysis of important climate variables presents serious challenges for large-scale data mining and data fusion. For example, one might want to compare temperature and water vapor retrievals from one instrument (AIRS) to another instrument (MODIS), and to a model (ECMWF), stratify the comparisons using a classification of the cloud scenes from CloudSat, and repeat the entire analysis over years of AIRS data. To perform such an analysis, one must discover & access multiple datasets from remote sites, find the space/time matchups between instruments swaths and model grids, understand the quality flags and uncertainties for retrieved physical variables, and assemble merged datasets for further scientific and statistical analysis. To meet these large-scale challenges, we are utilizing a Grid computing and dataflow framework, named SciFlo, in which we are deploying a set of versatile and reusable operators for data query, access, subsetting, co-registration, mining, fusion, and advanced statistical analysis. SciFlo is a semantically-enabled ("smart") Grid Workflow system that ties together a peer-to-peer network of computers into an efficient engine for distributed computation. The SciFlo workflow engine enables scientists to do multi-instrument Earth Science by assembling remotely-invokable Web Services (SOAP or http GET URLs), native executables, command-line scripts, and Python codes into a distributed computing flow. A scientist visually authors the graph of operation in the VizFlow GUI, or uses a text editor to modify the simple XML workflow documents. The SciFlo client & server engines optimize the execution of such distributed workflows and allow the user to transparently find and use datasets and operators without worrying about the actual location of the Grid resources. The engine transparently moves data to the operators, and moves operators to the data (on the dozen trusted SciFlo nodes). SciFlo also deploys a variety of Data Grid services to: query datasets in space and time, locate & retrieve on-line data granules, provide on-the-fly variable and spatial subsetting, and perform pairwise instrument matchups for A-Train datasets. These services are combined into efficient workflows to assemble the desired large-scale, merged climate datasets. SciFlo is currently being applied in several large climate studies: comparisons of aerosol optical depth between MODIS, MISR, AERONET ground network, and U. Michigan's IMPACT aerosol transport model; characterization of long-term biases in microwave and infrared instruments (AIRS, MLS) by comparisons to GPS temperature retrievals accurate to 0.1 degrees Kelvin; and construction of a decade-long, multi-sensor water vapor climatology stratified by classified cloud scene by bringing together datasets from AIRS/AMSU, AMSR-E, MLS, MODIS, and CloudSat (NASA MEASUREs grant, Fetzer PI). The presentation will discuss the SciFlo technologies, their application in these distributed workflows, and the many challenges encountered in assembling and analyzing these massive datasets.

Assembling Large, Multi-Sensor Climate Datasets Using the SciFlo Grid Workflow System

NASA Astrophysics Data System (ADS)

Wilson, B.; Manipon, G.; Xing, Z.; Fetzer, E.

2009-04-01

NASA's Earth Observing System (EOS) is an ambitious facility for studying global climate change. The mandate now is to combine measurements from the instruments on the "A-Train" platforms (AIRS, AMSR-E, MODIS, MISR, MLS, and CloudSat) and other Earth probes to enable large-scale studies of climate change over periods of years to decades. However, moving from predominantly single-instrument studies to a multi-sensor, measurement-based model for long-duration analysis of important climate variables presents serious challenges for large-scale data mining and data fusion. For example, one might want to compare temperature and water vapor retrievals from one instrument (AIRS) to another instrument (MODIS), and to a model (ECMWF), stratify the comparisons using a classification of the "cloud scenes" from CloudSat, and repeat the entire analysis over years of AIRS data. To perform such an analysis, one must discover & access multiple datasets from remote sites, find the space/time "matchups" between instruments swaths and model grids, understand the quality flags and uncertainties for retrieved physical variables, assemble merged datasets, and compute fused products for further scientific and statistical analysis. To meet these large-scale challenges, we are utilizing a Grid computing and dataflow framework, named SciFlo, in which we are deploying a set of versatile and reusable operators for data query, access, subsetting, co-registration, mining, fusion, and advanced statistical analysis. SciFlo is a semantically-enabled ("smart") Grid Workflow system that ties together a peer-to-peer network of computers into an efficient engine for distributed computation. The SciFlo workflow engine enables scientists to do multi-instrument Earth Science by assembling remotely-invokable Web Services (SOAP or http GET URLs), native executables, command-line scripts, and Python codes into a distributed computing flow. A scientist visually authors the graph of operation in the VizFlow GUI, or uses a text editor to modify the simple XML workflow documents. The SciFlo client & server engines optimize the execution of such distributed workflows and allow the user to transparently find and use datasets and operators without worrying about the actual location of the Grid resources. The engine transparently moves data to the operators, and moves operators to the data (on the dozen trusted SciFlo nodes). SciFlo also deploys a variety of Data Grid services to: query datasets in space and time, locate & retrieve on-line data granules, provide on-the-fly variable and spatial subsetting, perform pairwise instrument matchups for A-Train datasets, and compute fused products. These services are combined into efficient workflows to assemble the desired large-scale, merged climate datasets. SciFlo is currently being applied in several large climate studies: comparisons of aerosol optical depth between MODIS, MISR, AERONET ground network, and U. Michigan's IMPACT aerosol transport model; characterization of long-term biases in microwave and infrared instruments (AIRS, MLS) by comparisons to GPS temperature retrievals accurate to 0.1 degrees Kelvin; and construction of a decade-long, multi-sensor water vapor climatology stratified by classified cloud scene by bringing together datasets from AIRS/AMSU, AMSR-E, MLS, MODIS, and CloudSat (NASA MEASUREs grant, Fetzer PI). The presentation will discuss the SciFlo technologies, their application in these distributed workflows, and the many challenges encountered in assembling and analyzing these massive datasets.

Assessment of extreme value distributions for maximum temperature in the Mediterranean area

NASA Astrophysics Data System (ADS)

Beck, Alexander; Hertig, Elke; Jacobeit, Jucundus

2015-04-01

Extreme maximum temperatures highly affect the natural as well as the societal environment Heat stress has great effects on flora, fauna and humans and culminates in heat related morbidity and mortality. Agriculture and different industries are severely affected by extreme air temperatures. Even more under climate change conditions, it is necessary to detect potential hazards which arise from changes in the distributional parameters of extreme values, and this is especially relevant for the Mediterranean region which is characterized as a climate change hot spot. Therefore statistical approaches are developed to estimate these parameters with a focus on non-stationarities emerging in the relationship between regional climate variables and their large-scale predictors like sea level pressure, geopotential heights, atmospheric temperatures and relative humidity. Gridded maximum temperature data from the daily E-OBS dataset (Haylock et al., 2008) with a spatial resolution of 0.25° x 0.25° from January 1950 until December 2012 are the predictands for the present analyses. A s-mode principal component analysis (PCA) has been performed in order to reduce data dimension and to retain different regions of similar maximum temperature variability. The grid box with the highest PC-loading represents the corresponding principal component. A central part of the analyses is the model development for temperature extremes under the use of extreme value statistics. A combined model is derived consisting of a Generalized Pareto Distribution (GPD) model and a quantile regression (QR) model which determines the GPD location parameters. The QR model as well as the scale parameters of the GPD model are conditioned by various large-scale predictor variables. In order to account for potential non-stationarities in the predictors-temperature relationships, a special calibration and validation scheme is applied, respectively. Haylock, M. R., N. Hofstra, A. M. G. Klein Tank, E. J. Klok, P. D. Jones, and M. New (2008), A European daily high-resolution gridded data set of surface temperature and precipitation for 1950 - 2006, J. Geophys. Res., 113, D20119, doi:10.1029/2008JD010201.

Color visualization for fluid flow prediction

NASA Technical Reports Server (NTRS)

Smith, R. E.; Speray, D. E.

1982-01-01

High-resolution raster scan color graphics allow variables to be presented as a continuum, in a color-coded picture that is referenced to a geometry such as a flow field grid or a boundary surface. Software is used to map a scalar variable such as pressure or temperature, defined on a two-dimensional slice of a flow field. The geometric shape is preserved in the resulting picture, and the relative magnitude of the variable is color-coded onto the geometric shape. The primary numerical process for color coding is an efficient search along a raster scan line to locate the quadrilteral block in the grid that bounds each pixel on the line. Tension spline interpolation is performed relative to the grid for specific values of the scalar variable, which is then color coded. When all pixels for the field of view are color-defined, a picture is played back from a memory device onto a television screen.

A new synoptic scale resolving global climate simulation using the Community Earth System Model

NASA Astrophysics Data System (ADS)

Small, R. Justin; Bacmeister, Julio; Bailey, David; Baker, Allison; Bishop, Stuart; Bryan, Frank; Caron, Julie; Dennis, John; Gent, Peter; Hsu, Hsiao-ming; Jochum, Markus; Lawrence, David; Muñoz, Ernesto; diNezio, Pedro; Scheitlin, Tim; Tomas, Robert; Tribbia, Joseph; Tseng, Yu-heng; Vertenstein, Mariana

2014-12-01

High-resolution global climate modeling holds the promise of capturing planetary-scale climate modes and small-scale (regional and sometimes extreme) features simultaneously, including their mutual interaction. This paper discusses a new state-of-the-art high-resolution Community Earth System Model (CESM) simulation that was performed with these goals in mind. The atmospheric component was at 0.25° grid spacing, and ocean component at 0.1°. One hundred years of "present-day" simulation were completed. Major results were that annual mean sea surface temperature (SST) in the equatorial Pacific and El-Niño Southern Oscillation variability were well simulated compared to standard resolution models. Tropical and southern Atlantic SST also had much reduced bias compared to previous versions of the model. In addition, the high resolution of the model enabled small-scale features of the climate system to be represented, such as air-sea interaction over ocean frontal zones, mesoscale systems generated by the Rockies, and Tropical Cyclones. Associated single component runs and standard resolution coupled runs are used to help attribute the strengths and weaknesses of the fully coupled run. The high-resolution run employed 23,404 cores, costing 250 thousand processor-hours per simulated year and made about two simulated years per day on the NCAR-Wyoming supercomputer "Yellowstone."

Performance Summary of the 2006 Community Multiscale Air Quality (CMAQ) Simulation for the AQMEII Project: North American Application

EPA Science Inventory

The CMAQ modeling system has been used to simulate the CONUS using 12-km by 12-km horizontal grid spacing for the entire year of 2006 as part of the Air Quality Model Evaluation International initiative (AQMEII). The operational model performance for O₃ and PM_2.5<...

Uncertainties in estimates of mortality attributable to ambient PM2.5 in Europe

NASA Astrophysics Data System (ADS)

Kushta, Jonilda; Pozzer, Andrea; Lelieveld, Jos

2018-06-01

The assessment of health impacts associated with airborne particulate matter smaller than 2.5 μm in diameter (PM2.5) relies on aerosol concentrations derived either from monitoring networks, satellite observations, numerical models, or a combination thereof. When global chemistry-transport models are used for estimating PM2.5, their relatively coarse resolution has been implied to lead to underestimation of health impacts in densely populated and industrialized areas. In this study the role of spatial resolution and of vertical layering of a regional air quality model, used to compute PM2.5 impacts on public health and mortality, is investigated. We utilize grid spacings of 100 km and 20 km to calculate annual mean PM2.5 concentrations over Europe, which are in turn applied to the estimation of premature mortality by cardiovascular and respiratory diseases. Using model results at a 100 km grid resolution yields about 535 000 annual premature deaths over the extended European domain (242 000 within the EU-28), while numbers approximately 2.4% higher are derived by using the 20 km resolution. Using the surface (i.e. lowest) layer of the model for PM2.5 yields about 0.6% higher mortality rates compared with PM2.5 averaged over the first 200 m above ground. Further, the calculation of relative risks (RR) from PM2.5, using 0.1 μg m‑3 size resolution bins compared to the commonly used 1 μg m‑3, is associated with ±0.8% uncertainty in estimated deaths. We conclude that model uncertainties contribute a small part of the overall uncertainty expressed by the 95% confidence intervals, which are of the order of ±30%, mostly related to the RR calculations based on epidemiological data.

Evaluation of a Mesoscale Convective System in Variable-Resolution CESM

NASA Astrophysics Data System (ADS)

Payne, A. E.; Jablonowski, C.

2017-12-01

Warm season precipitation over the Southern Great Plains (SGP) follows a well observed diurnal pattern of variability, peaking at night-time, due to the eastward propagation of mesoscale convection systems that develop over the eastern slopes of the Rockies in the late afternoon. While most climate models are unable to adequately capture the organization of convection and characteristic pattern of precipitation over this region, models with high enough resolution to explicitly resolve convection show improvement. However, high resolution simulations are computationally expensive and, in the case of regional climate models, are subject to boundary conditions. Newly developed variable resolution global climate models strike a balance between the benefits of high-resolution regional climate models and the large-scale dynamics of global climate models and low computational cost. Recently developed parameterizations that are insensitive to the model grid scale provide a way to improve model performance. Here, we present an evaluation of the newly available Cloud Layers Unified by Binormals (CLUBB) parameterization scheme in a suite of variable-resolution CESM simulations with resolutions ranging from 110 km to 7 km within a regionally refined region centered over the SGP Atmospheric Radiation Measurement (ARM) site. Simulations utilize the hindcast approach developed by the Department of Energy's Cloud-Associated Parameterizations Testbed (CAPT) for the assessment of climate models. We limit our evaluation to a single mesoscale convective system that passed over the region on May 24, 2008. The effects of grid-resolution on the timing and intensity of precipitation, as well as, on the transition from shallow to deep convection are assessed against ground-based observations from the SGP ARM site, satellite observations and ERA-Interim reanalysis.

Studies of Inviscid Flux Schemes for Acoustics and Turbulence Problems

NASA Technical Reports Server (NTRS)

Morris, Chris

2013-01-01

Five different central difference schemes, based on a conservative differencing form of the Kennedy and Gruber skew-symmetric scheme, were compared with six different upwind schemes based on primitive variable reconstruction and the Roe flux. These eleven schemes were tested on a one-dimensional acoustic standing wave problem, the Taylor-Green vortex problem and a turbulent channel flow problem. The central schemes were generally very accurate and stable, provided the grid stretching rate was kept below 10%. As near-DNS grid resolutions, the results were comparable to reference DNS calculations. At coarser grid resolutions, the need for an LES SGS model became apparent. There was a noticeable improvement moving from CD-2 to CD-4, and higher-order schemes appear to yield clear benefits on coarser grids. The UB-7 and CU-5 upwind schemes also performed very well at near-DNS grid resolutions. The UB-5 upwind scheme does not do as well, but does appear to be suitable for well-resolved DNS. The UF-2 and UB-3 upwind schemes, which have significant dissipation over a wide spectral range, appear to be poorly suited for DNS or LES.

Weather Observation Systems and Efficiency of Fighting Forest Fires

NASA Astrophysics Data System (ADS)

Khabarov, N.; Moltchanova, E.; Obersteiner, M.

2007-12-01

Weather observation is an essential component of modern forest fire management systems. Satellite and in-situ based weather observation systems might help to reduce forest loss, human casualties and destruction of economic capital. In this paper, we develop and apply a methodology to assess the benefits of various weather observation systems on reductions of burned area due to early fire detection. In particular, we consider a model where the air patrolling schedule is determined by a fire hazard index. The index is computed from gridded daily weather data for the area covering parts Spain and Portugal. We conduct a number of simulation experiments. First, the resolution of the original data set is artificially reduced. The reduction of the total forest burned area associated with air patrolling based on a finer weather grid indicates the benefit of using higher spatially resolved weather observations. Second, we consider a stochastic model to simulate forest fires and explore the sensitivity of the model with respect to the quality of input data. The analysis of combination of satellite and ground monitoring reveals potential cost saving due to a "system of systems effect" and substantial reduction in burned area. Finally, we estimate the marginal improvement schedule for loss of life and economic capital as a function of the improved fire observing system.

A physically based analytical spatial air temperature and humidity model

NASA Astrophysics Data System (ADS)

Yang, Yang; Endreny, Theodore A.; Nowak, David J.

2013-09-01

Spatial variation of urban surface air temperature and humidity influences human thermal comfort, the settling rate of atmospheric pollutants, and plant physiology and growth. Given the lack of observations, we developed a Physically based Analytical Spatial Air Temperature and Humidity (PASATH) model. The PASATH model calculates spatial solar radiation and heat storage based on semiempirical functions and generates spatially distributed estimates based on inputs of topography, land cover, and the weather data measured at a reference site. The model assumes that for all grids under the same mesoscale climate, grid air temperature and humidity are modified by local variation in absorbed solar radiation and the partitioning of sensible and latent heat. The model uses a reference grid site for time series meteorological data and the air temperature and humidity of any other grid can be obtained by solving the heat flux network equations. PASATH was coupled with the USDA iTree-Hydro water balance model to obtain evapotranspiration terms and run from 20 to 29 August 2010 at a 360 m by 360 m grid scale and hourly time step across a 285 km2 watershed including the urban area of Syracuse, NY. PASATH predictions were tested at nine urban weather stations representing variability in urban topography and land cover. The PASATH model predictive efficiency R2 ranged from 0.81 to 0.99 for air temperature and 0.77 to 0.97 for dew point temperature. PASATH is expected to have broad applications on environmental and ecological models.

A dynamic urban air pollution population exposure assessment study using model and population density data derived by mobile phone traffic

NASA Astrophysics Data System (ADS)

Gariazzo, Claudio; Pelliccioni, Armando; Bolignano, Andrea

2016-04-01

A dynamic city-wide air pollution exposure assessment study has been carried out for the urban population of Rome, Italy, by using time resolved population distribution maps, derived by mobile phone traffic data, and modelled air pollutants (NO2, O3 and PM2.5) concentrations obtained by an integrated air dispersion modelling system. More than a million of persons were tracked during two months (March and April 2015) for their position within the city and its surroundings areas, with a time resolution of 15 min and mapped over an irregular grid system with a minimum resolution of 0.26 × 0.34 Km2. In addition, demographics information (as gender and age ranges) were available in a separated dataset not connected with the total population one. Such BigData were matched in time and space with air pollution model results and then used to produce hourly and daily resolved cumulative population exposures during the studied period. A significant mobility of population was identified with higher population densities in downtown areas during daytime increasing of up to 1000 people/Km2 with respect to nigh-time one, likely produced by commuters, tourists and working age population. Strong variability (up to ±50% for NO2) of population exposures were detected as an effect of both mobility and time/spatial changing in pollutants concentrations. A comparison with the correspondent stationary approach based on National Census data, allows detecting the inability of latter in estimating the actual variability of population exposure. Significant underestimations of the amount of population exposed to daily PM2.5 WHO guideline was identified for the Census approach. Very small differences (up to a few μg/m3) on exposure were detected for gender and age ranges population classes.

Assimilation of Quality Controlled AIRS Temperature Profiles using the NCEP GFS

NASA Technical Reports Server (NTRS)

Susskind, Joel; Reale, Oreste; Iredell, Lena; Rosenberg, Robert

2013-01-01

We have previously conducted a number of data assimilation experiments using AIRS Version-5 quality controlled temperature profiles as a step toward finding an optimum balance of spatial coverage and sounding accuracy with regard to improving forecast skill. The data assimilation and forecast system we used was the Goddard Earth Observing System Model , Version-5 (GEOS-5) Data Assimilation System (DAS), which represents a combination of the NASA GEOS-5 forecast model with the National Centers for Environmental Prediction (NCEP) operational Grid Point Statistical Interpolation (GSI) global analysis scheme. All analyses and forecasts were run at a 0.5deg x 0.625deg spatial resolution. Data assimilation experiments were conducted in four different seasons, each in a different year. Three different sets of data assimilation experiments were run during each time period: Control; AIRS T(p); and AIRS Radiance. In the "Control" analysis, all the data used operationally by NCEP was assimilated, but no AIRS data was assimilated. Radiances from the Aqua AMSU-A instrument were also assimilated operationally by NCEP and are included in the "Control". The AIRS Radiance assimilation adds AIRS observed radiance observations for a select set of channels to the data set being assimilated, as done operationally by NCEP. In the AIRS T(p) assimilation, all information used in the Control was assimilated as well as Quality Controlled AIRS Version-5 temperature profiles, i.e., AIRS T(p) information was substituted for AIRS radiance information. The AIRS Version-5 temperature profiles were presented to the GSI analysis as rawinsonde profiles, assimilated down to a case-by-case appropriate pressure level p(sub best) determined using the Quality Control procedure. Version-5 also determines case-by-case, level-by-level error estimates of the temperature profiles, which were used as the uncertainty of each temperature measurement. These experiments using GEOS-5 have shown that forecasts resulting from analyses using the AIRS T(p) assimilation system were superior to those from the Radiance assimilation system, both with regard to global 7 day forecast skill and also the ability to predict storm tracks and intensity.

Development of a high-resolution emission inventory and its evaluation and application through air quality modeling for Jiangsu Province, China

NASA Astrophysics Data System (ADS)

Zhao, Yu; Zhou, Yaduan; Mao, Pan; Zhang, Jie

2017-04-01

Improved emission inventories combining detailed source information are crucial for better understanding the atmospheric chemistry and effectively making emission control policies using air quality simulation, particularly at regional or local scales. With the downscaled inventories directly applied, chemical transport model might not be able to reproduce the authentic evolution of atmospheric pollution processes at small spatial scales. Using the bottom-up approach, a high-resolution emission inventory was developed for Jiangsu China, including SO2, NOx, CO, NH3, volatile organic compounds (VOCs), total suspended particulates (TSP), PM10, PM2.5, black carbon (BC), organic carbon (OC), and CO2. The key parameters relevant to emission estimation for over 6000 industrial sources were investigated, compiled and revised at plant level based on various data sources and on-site survey. As a result, the emission fractions of point sources were significantly elevated for most species. The improvement of this provincial inventory was evaluated through comparisons with other inventories at larger spatial scales, using satellite observation and air quality modeling. Compared to the downscaled Multi-resolution Emission Inventory for China (MEIC), the spatial distribution of NOX emissions in our provincial inventory was more consistent with summer tropospheric NO2 VCDs observed from OMI, particularly for the grids with moderate emission levels, implying the improved emission estimation for small and medium industrial plants by this work. Three inventories (national, regional, and provincial by this work) were applied in the Models-3/Community Multi-scale Air Quality (CMAQ) system for southern Jiangsu October 2012, to evaluate the model performances with different emission inputs. The best agreement between available ground observation and simulation was found when the provincial inventory was applied, indicated by the smallest normalized mean bias (NMB) and normalized mean errors (NME) for all the concerned species SO2, NO2, O3 and PM2.5. The result thus implied the advantage of improved emission inventory at local scale for high resolution air quality modeling. Under the unfavorable meteorology in which horizontal and vertical movement of atmosphere was limited, the simulated SO2 concentrations at downtown Nanjing (the capital city of Jiangsu) using the regional or national inventories were much higher than observation, implying the overestimated urban emissions when economy or population densities were applied to downscale or allocate the emissions. With more accurate spatial distribution of emissions at city level, the simulated concentrations using the provincial inventory were much closer to observation. Sensitivity analysis of PM2.5 and O3 formation was conducted using the improved provincial inventory through the Brute Force method. Iron & steel and cement plants were identified as important contributors to the PM2.5 concentrations in Nanjing. The O3 formation was VOCs-limited in southern Jiangsu, and the concentrations were negatively correlated with NOX emissions in urban areas owing to the accumulated NOx from transportation. More evaluations are further suggested for the impacts of speciation and temporal and vertical distribution of emissions on air quality modeling at regional or local scales in China.

Development of a high-resolution emission inventory and its evaluation and application through air quality modeling for Jiangsu Province, China

NASA Astrophysics Data System (ADS)

Zhou, Yaduan; Zhao, Yu; Mao, Pan; Zhang, Qiang; Zhang, Jie; Qiu, Liping; Yang, Yang

2017-01-01

Improved emission inventories combining detailed source information are crucial for better understanding of the atmospheric chemistry and effectively making emission control policies using air quality simulation, particularly at regional or local scales. With the downscaled inventories directly applied, chemical transport models might not be able to reproduce the authentic evolution of atmospheric pollution processes at small spatial scales. Using the bottom-up approach, a high-resolution emission inventory was developed for Jiangsu China, including SO2, NOx, CO, NH3, volatile organic compounds (VOCs), total suspended particulates (TSP), PM10, PM2.5, black carbon (BC), organic carbon (OC), and CO2. The key parameters relevant to emission estimation for over 6000 industrial sources were investigated, compiled, and revised at plant level based on various data sources and on-site surveys. As a result, the emission fractions of point sources were significantly elevated for most species. The improvement of this provincial inventory was evaluated through comparisons with other inventories at larger spatial scales, using satellite observation and air quality modeling. Compared to the downscaled Multi-resolution Emission Inventory for China (MEIC), the spatial distribution of NOx emissions in our provincial inventory was more consistent with summer tropospheric NO2 VCDs observed from OMI, particularly for the grids with moderate emission levels, implying the improved emission estimation for small and medium industrial plants by this work. Three inventories (national, regional, and provincial by this work) were applied in the Models-3 Community Multi-scale Air Quality (CMAQ) system for southern Jiangsu October 2012, to evaluate the model performances with different emission inputs. The best agreement between available ground observation and simulation was found when the provincial inventory was applied, indicated by the smallest normalized mean bias (NMB) and normalized mean errors (NME) for all the concerned species SO2, NO2, O3, and PM2.5. The result thus implied the advantage of improved emission inventory at local scale for high-resolution air quality modeling. Under the unfavorable meteorology in which horizontal and vertical movement of atmosphere was limited, the simulated SO2 concentrations at downtown Nanjing (the capital city of Jiangsu) using the regional or national inventories were much higher than those observed, implying that the urban emissions were overestimated when economy or population densities were applied to downscale or allocate the emissions. With more accurate spatial distribution of emissions at city level, the simulated concentrations using the provincial inventory were much closer to observation. Sensitivity analysis of PM2.5 and O3 formation was conducted using the improved provincial inventory through the brute force method. Iron and steel plants and cement plants were identified as important contributors to the PM2.5 concentrations in Nanjing. The O3 formation was VOC-limited in southern Jiangsu, and the concentrations were negatively correlated with NOx emissions in urban areas owing to the accumulated NOx from transportation. More evaluations are further suggested for the impacts of speciation and temporal and vertical distribution of emissions on air quality modeling at regional or local scales in China.

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

NASA Astrophysics Data System (ADS)

Komurcu, M.; Huber, M.

2016-12-01

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

Automated Approach to Very High-Order Aeroacoustic Computations. Revision

NASA Technical Reports Server (NTRS)

Dyson, Rodger W.; Goodrich, John W.

2001-01-01

Computational aeroacoustics requires efficient, high-resolution simulation tools. For smooth problems, this is best accomplished with very high-order in space and time methods on small stencils. However, the complexity of highly accurate numerical methods can inhibit their practical application, especially in irregular geometries. This complexity is reduced by using a special form of Hermite divided-difference spatial interpolation on Cartesian grids, and a Cauchy-Kowalewski recursion procedure for time advancement. In addition, a stencil constraint tree reduces the complexity of interpolating grid points that am located near wall boundaries. These procedures are used to develop automatically and to implement very high-order methods (> 15) for solving the linearized Euler equations that can achieve less than one grid point per wavelength resolution away from boundaries by including spatial derivatives of the primitive variables at each grid point. The accuracy of stable surface treatments is currently limited to 11th order for grid aligned boundaries and to 2nd order for irregular boundaries.

An Automated Approach to Very High Order Aeroacoustic Computations in Complex Geometries

NASA Technical Reports Server (NTRS)

Dyson, Rodger W.; Goodrich, John W.

2000-01-01

Computational aeroacoustics requires efficient, high-resolution simulation tools. And for smooth problems, this is best accomplished with very high order in space and time methods on small stencils. But the complexity of highly accurate numerical methods can inhibit their practical application, especially in irregular geometries. This complexity is reduced by using a special form of Hermite divided-difference spatial interpolation on Cartesian grids, and a Cauchy-Kowalewslci recursion procedure for time advancement. In addition, a stencil constraint tree reduces the complexity of interpolating grid points that are located near wall boundaries. These procedures are used to automatically develop and implement very high order methods (>15) for solving the linearized Euler equations that can achieve less than one grid point per wavelength resolution away from boundaries by including spatial derivatives of the primitive variables at each grid point. The accuracy of stable surface treatments is currently limited to 11th order for grid aligned boundaries and to 2nd order for irregular boundaries.

Monthly fractional green vegetation cover associated with land cover classes of the conterminous USA

USGS Publications Warehouse

Gallo, Kevin P.; Tarpley, Dan; Mitchell, Ken; Csiszar, Ivan; Owen, Timothy W.; Reed, Bradley C.

2001-01-01

The land cover classes developed under the coordination of the International Geosphere-Biosphere Programme Data and Information System (IGBP-DIS) have been analyzed for a study area that includes the Conterminous United States and portions of Mexico and Canada. The 1-km resolution data have been analyzed to produce a gridded data set that includes within each 20-km grid cell: 1) the three most dominant land cover classes, 2) the fractional area associated with each of the three dominant classes, and 3) the fractional area covered by water. Additionally, the monthly fraction of green vegetation cover (fgreen) associated with each of the three dominant land cover classes per grid cell was derived from a 5-year climatology of 1-km resolution NOAA-AVHRR data. The variables derived in this study provide a potential improvement over the use of monthly fgreen linked to a single land cover class per model grid cell.

Evaluation of decadal hindcasts using satellite simulators

NASA Astrophysics Data System (ADS)

Spangehl, Thomas; Mazurkiewicz, Alex; Schröder, Marc

2013-04-01

The evaluation of dynamical ensemble forecast systems requires a solid validation of basic processes such as the global atmospheric water and energy cycle. The value of any validation approach strongly depends on the quality of the observational data records used. Current approaches utilize in situ measurements, remote sensing data and reanalyses. Related data records are subject to a number of uncertainties and limitations such as representativeness, spatial and temporal resolution and homogeneity. However, recently several climate data records with known and sufficient quality became available. In particular, the satellite data records offer the opportunity to obtain reference information on global scales including the oceans. Here we consider the simulation of satellite radiances from the climate model output enabling an evaluation in the instrument's parameter space to avoid uncertainties stemming from the application of retrieval schemes in order to minimise uncertainties on the reference side. Utilizing the CFMIP Observation Simulator Package (COSP) we develop satellite simulators for the Tropical Rainfall Measuring Mission precipitation radar (TRMM PR) and the Infrared Atmospheric Sounding Interferometer (IASI). The simulators are applied within the MiKlip project funded by BMBF (German Federal Ministry of Education and Research) to evaluate decadal climate predictions performed with the MPI-ESM developed at the Max Planck Institute for Meteorology. While TRMM PR enables the evaluation of the vertical structure of precipitation over tropical and sub-tropical areas, IASI is used to support the global evaluation of clouds and radiation. In a first step the reliability of the developed simulators needs to be explored. The simulation of radiances in the instrument space requires the generation of sub-grid scale variability from the climate model output. Furthermore, assumptions are made to simulate radiances such as, for example, the distribution of different hydrometeor types. Therefore, testing is performed to determine the extent to which the quality of the simulator results depends on the applied methods used to generate sub-grid variability (e.g. sub-grid resolution). Moreover, the sensitivity of results to the choice of different distributions of hydrometeors is explored. The model evaluation is carried out in a statistical manner using histograms of radar reflectivities (TRMM PR) and brightness temperatures (IASI). Finally, methods to deduce data suitable for probabilistic evaluation of decadal hindcasts such as simple indices are discussed.

Energy dependent features of X-ray signals in a GridPix detector

NASA Astrophysics Data System (ADS)

Krieger, C.; Kaminski, J.; Vafeiadis, T.; Desch, K.

2018-06-01

We report on the calibration of an argon/isobutane (97.7%/2.3%)-filled GridPix detector with soft X-rays (277 eV to 8 keV) using the variable energy X-ray source of the CAST Detector Lab at CERN. We study the linearity and energy resolution of the detector using both the number of pixels hit and the total measured charge as energy measures. For the latter, the energy resolution σE / E is better than 10% (20%) for energies above 2 keV (0.5 keV). Several characteristics of the recorded events are studied.

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

NASA Astrophysics Data System (ADS)

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

2013-07-01

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

Simulating air quality in the Netherlands with WRF-Chem 3.8.1 at high resolution

NASA Astrophysics Data System (ADS)

Hilboll, Andreas; Kuenen, Jeroen; Denier van der Gon, Hugo; Vrekoussis, Mihalis

2017-04-01

Air pollution is the single most important environmental hazard for public health. Especially nitrogen dioxide (NO(2)) plays a key role in air quality research, both due to its immediate importance for the production of tropospheric ozone and acid rain, and as a general indicator of fossil fuel burning. To improve the quality and reproducibility of measurements of NO(2) vertical distribution from MAX-DOAS instruments, the CINDI-2 campaign was held in Cabauw (NL) in September 2016, featuring instruments from many of the leading atmospheric research institutions in the world. The measurement site in Cabauw is located in a rather rural region, surrounded by several major pollution centers (Utrecht, Rotterdam, Amsterdam). Since the instruments measure in several azimuthal directions, the measurements are able to provide information about the high spatial and temporal variability in pollutant concentrations, caused by both the spatial heterogeneity of emissions and meteorological conditions. When using air quality models in the analysis of the measured data to identify pollution sources, this mandates high spatial resolution in order to resolve the expected fine spatial structure in NO(2) concentrations. In spite of constant advances in computing power, this remains a challenge, mostly due to the uncertainties and large spatial heterogeneity of emissions and the need to parameterize small-scale processes. In this study, we use the most recent version 3.8.1 of the Weather Research and Forecasting Model with Chemistry (WRF-Chem) to simulate air pollutant concentrations over the Netherlands, to facilitate the analysis of the CINDI-2 NO(2}) measurements. The model setup contains three nested domains with horizontal resolutions of 15, 3, and 1 km. Anthropogenic emissions are taken from the TNO-MACC III inventory and, where available, from the Dutch Pollutant Release and Transfer Register (Emissieregistratie), at a spatial resolution of 7 and 1 km, respectively. We use the Common Reactive Intermediates gas-phase chemical mechanism (CRIv2-R5) with the MOSAIC aerosol module. The high spatial resolution of model and emissions will allow us to resolve the strong spatial gradients in the NO(2) concentrations measured during the CINDI-2 campaign, allowing for an unprecedented level of detail in the analysis of individual pollution sources.

An Overview of Numerical Weather Prediction on Various Scales

NASA Astrophysics Data System (ADS)

Bao, J.-W.

2009-04-01

The increasing public need for detailed weather forecasts, along with the advances in computer technology, has motivated many research institutes and national weather forecasting centers to develop and run global as well as regional numerical weather prediction (NWP) models at high resolutions (i.e., with horizontal resolutions of ~10 km or higher for global models and 1 km or higher for regional models, and with ~60 vertical levels or higher). The need for running NWP models at high horizontal and vertical resolutions requires the implementation of non-hydrostatic dynamic core with a choice of horizontal grid configurations and vertical coordinates that are appropriate for high resolutions. Development of advanced numerics will also be needed for high resolution global and regional models, in particular, when the models are applied to transport problems and air quality applications. In addition to the challenges in numerics, the NWP community is also facing the challenges of developing physics parameterizations that are well suited for high-resolution NWP models. For example, when NWP models are run at resolutions of ~5 km or higher, the use of much more detailed microphysics parameterizations than those currently used in NWP model will become important. Another example is that regional NWP models at ~1 km or higher only partially resolve convective energy containing eddies in the lower troposphere. Parameterizations to account for the subgrid diffusion associated with unresolved turbulence still need to be developed. Further, physically sound parameterizations for air-sea interaction will be a critical component for tropical NWP models, particularly for hurricane predictions models. In this review presentation, the above issues will be elaborated on and the approaches to address them will be discussed.

Seasonal and interannual variability of the Arctic sea ice: A comparison between AO-FVCOM and observations

NASA Astrophysics Data System (ADS)

Zhang, Yu; Chen, Changsheng; Beardsley, Robert C.; Gao, Guoping; Qi, Jianhua; Lin, Huichan

2016-11-01

A high-resolution (up to 2 km), unstructured-grid, fully ice-sea coupled Arctic Ocean Finite-Volume Community Ocean Model (AO-FVCOM) was used to simulate the sea ice in the Arctic over the period 1978-2014. The spatial-varying horizontal model resolution was designed to better resolve both topographic and baroclinic dynamics scales over the Arctic slope and narrow straits. The model-simulated sea ice was in good agreement with available observed sea ice extent, concentration, drift velocity and thickness, not only in seasonal and interannual variability but also in spatial distribution. Compared with six other Arctic Ocean models (ECCO2, GSFC, INMOM, ORCA, NAME, and UW), the AO-FVCOM-simulated ice thickness showed a higher mean correlation coefficient of ˜0.63 and a smaller residual with observations. Model-produced ice drift speed and direction errors varied with wind speed: the speed and direction errors increased and decreased as the wind speed increased, respectively. Efforts were made to examine the influences of parameterizations of air-ice external and ice-water interfacial stresses on the model-produced bias. The ice drift direction was more sensitive to air-ice drag coefficients and turning angles than the ice drift speed. Increasing or decreasing either 10% in water-ice drag coefficient or 10° in water-ice turning angle did not show a significant influence on the ice drift velocity simulation results although the sea ice drift speed was more sensitive to these two parameters than the sea ice drift direction. Using the COARE 4.0-derived parameterization of air-water drag coefficient for wind stress did not significantly influence the ice drift velocity simulation.

PDF added value of a high resolution climate simulation for precipitation

NASA Astrophysics Data System (ADS)

Soares, Pedro M. M.; Cardoso, Rita M.

2015-04-01

General Circulation Models (GCMs) are models suitable to study the global atmospheric system, its evolution and response to changes in external forcing, namely to increasing emissions of CO2. However, the resolution of GCMs, of the order of 1o, is not sufficient to reproduce finer scale features of the atmospheric flow related to complex topography, coastal processes and boundary layer processes, and higher resolution models are needed to describe observed weather and climate. The latter are known as Regional Climate Models (RCMs) and are widely used to downscale GCMs results for many regions of the globe and are able to capture physically consistent regional and local circulations. Most of the RCMs evaluations rely on the comparison of its results with observations, either from weather stations networks or regular gridded datasets, revealing the ability of RCMs to describe local climatic properties, and assuming most of the times its higher performance in comparison with the forcing GCMs. The additional climatic details given by RCMs when compared with the results of the driving models is usually named as added value, and it's evaluation is still scarce and controversial in the literuature. Recently, some studies have proposed different methodologies to different applications and processes to characterize the added value of specific RCMs. A number of examples reveal that some RCMs do add value to GCMs in some properties or regions, and also the opposite, elighnening that RCMs may add value to GCM resuls, but improvements depend basically on the type of application, model setup, atmospheric property and location. The precipitation can be characterized by histograms of daily precipitation, or also known as probability density functions (PDFs). There are different strategies to evaluate the quality of both GCMs and RCMs in describing the precipitation PDFs when compared to observations. Here, we present a new method to measure the PDF added value obtained from dynamical downscaling, based on simple PDF skill scores. The measure can assess the full quality of the PDFs and at the same time integrates a flexible manner to weight differently the PDF tails. In this study we apply the referred method to characaterize the PDF added value of a high resolution simulation with the WRF model. Results from a WRF climate simulation centred at the Iberian Penisnula with two nested grids, a larger one at 27km and a smaller one at 9km. This simulation is forced by ERA-Interim. The observational data used covers from rain gauges precipitation records to observational regular grids of daily precipitation. Two regular gridded precipitation datasets are used. A Portuguese grid precipitation dataset developed at 0.2°× 0.2°, from observed rain gauges daily precipitation. A second one corresponding to the ENSEMBLES observational gridded dataset for Europe, which includes daily precipitation values at 0.25°. The analisys shows an important PDF added value from the higher resolution simulation, regarding the full PDF and the extremes. This method shows higher potential to be applied to other simulation exercises and to evaluate other variables.

High Spatial Resolution of Atmospheric Particle Mixing State and Its Links to Particle Evolution in a Metropolitan Area

NASA Astrophysics Data System (ADS)

Ye, Q.; Gu, P.; Li, H.; Robinson, E. S.; Apte, J.; Sullivan, R. C.; Robinson, A. L.; Presto, A. A.; Donahue, N.

2017-12-01

Traditional air quality studies in urban areas have mostly relied on very few monitoring locations either at urban background sites or at roadside sites.However, air pollution is highly complex and dynamic and will undergo complicated transformations. Therefore, results from one or two monitoring sites may not be sufficient to address the spatial gradients of pollutants and their evolution after atmosphere processing on a local scale. Our study, as part of the Center for Air, Climate, and Energy Solutions, performed stratified mobile sampling of atmospheric particulate matter with high spatial resolution to address intra-city variability of atmospheric particle composition and mixing state. A suite of comprehensive real-time instrumentations including a state-of-the-art aerosol mass spectrometer with single particle measurement capability are deployed on the mobile platform. Our sampling locations covered a wide variety of places with substantial differences in emissions and land use types including tunnels, inter-state highways, commercial areas, residential neighborhood, parks, as well as locations upwind and downwind of the city center. Our results show that particles from traffic emissions and restaurant cookings are two major contributors to fresh particles in the urban environment. In addition, there are large spatial variabilities of source-specific particles and we identify the relevant physicochemical processes governing transformation of particle composition, size and mixing state. We also combine our results with demographic data to study population exposure to particles of specific sources. This work will help evaluate the performance of existing modeling tools for air quality and population exposure studies.

Multiscale predictions of aviation-attributable PM2.5 for U.S. airports modeled using CMAQ with plume-in-grid and an aircraft-specific 1-D emission model

EPA Science Inventory

Aviation activities represent an important and unique mode of transportation, but also impact air quality. In this study, we aim to quantify the impact of aircraft on air quality, focusing on aviation-attributable PM2.5 at scales ranging from local (a few kilometers) to continent...

Air Quality Research and Applications Using AURA OMi Data

NASA Technical Reports Server (NTRS)

Bhartia, P.K.; Gleason, J.F.; Torres, O.; Levelt, P.; Liu, X.; Ziemke, J.; Chandra, S.; Krotkov, N.

2007-01-01

The Ozone Monitoring Instrument (OMI) on EOS Aura is a new generation of satellite remote sensing instrument designed to measure trace gas and aerosol absorption at the UV and blue wavelengths. These measurements are made globally at urban scale resolution with no inter-orbital gaps that make them potentially very useful for air quality research, such as the determination of the sources and processes that affect global and regional air quality, and to develop applications such as air quality forecast. However, the use of satellite data for such applications is not as straight forward as satellite data have been for stratospheric research. There is a need for close interaction between the satellite product developers, in-situ measurement programs, and the air quality research community to overcome some of the inherent difficulties in interpreting data from satellite-based remote sensing instruments. In this talk we will discuss the challenges and opportunities in using OMI products for air quality research and applications. A key conclusion of this work is that to realize the full potential of OMI measurements it will be necessary to combine OMI data with data from instruments such as MLS, MODIS, AIRS, and CALIPSO that are currently flying in the "A-train" satellite constellation. In addition similar data taken by satellites crossing the earth at different local times than the A-train (e.g., the recently MetOp satellite) would need to be processed in a consistent manner to study diurnal variability, and to capture the effects on air quality of rapidly changing events such as wild fires.

GSOD Based Daily Global Mean Surface Temperature and Mean Sea Level Air Pressure (1982-2011)

DOE Data Explorer

Xuan Shi, Dali Wang

2014-05-05

This data product contains all the gridded data set at 1/4 degree resolution in ASCII format. Both mean temperature and mean sea level air pressure data are available. It also contains the GSOD data (1982-2011) from NOAA site, contains station number, location, temperature and pressures (sea level and station level). The data package also contains information related to the data processing methods

Rapid, High-Resolution Detection of Environmental Change over Continental Scales from Satellite Data - the Earth Observation Data Cube

NASA Technical Reports Server (NTRS)

Lewis, Adam; Lymburner, Leo; Purss, Matthew B. J.; Brooke, Brendan; Evans, Ben; Ip, Alex; Dekker, Arnold G.; Irons, James R.; Minchin, Stuart; Mueller, Norman

2015-01-01

The effort and cost required to convert satellite Earth Observation (EO) data into meaningful geophysical variables has prevented the systematic analysis of all available observations. To overcome these problems, we utilise an integrated High Performance Computing and Data environment to rapidly process, restructure and analyse the Australian Landsat data archive. In this approach, the EO data are assigned to a common grid framework that spans the full geospatial and temporal extent of the observations - the EO Data Cube. This approach is pixel-based and incorporates geometric and spectral calibration and quality assurance of each Earth surface reflectance measurement. We demonstrate the utility of the approach with rapid time-series mapping of surface water across the entire Australian continent using 27 years of continuous, 25 m resolution observations. Our preliminary analysis of the Landsat archive shows how the EO Data Cube can effectively liberate high-resolution EO data from their complex sensor-specific data structures and revolutionise our ability to measure environmental change.

Geostatistical uncertainty of assessing air quality using high-spatial-resolution lichen data: A health study in the urban area of Sines, Portugal.

PubMed

Ribeiro, Manuel C; Pinho, P; Branquinho, C; Llop, Esteve; Pereira, Maria J

2016-08-15

In most studies correlating health outcomes with air pollution, personal exposure assignments are based on measurements collected at air-quality monitoring stations not coinciding with health data locations. In such cases, interpolators are needed to predict air quality in unsampled locations and to assign personal exposures. Moreover, a measure of the spatial uncertainty of exposures should be incorporated, especially in urban areas where concentrations vary at short distances due to changes in land use and pollution intensity. These studies are limited by the lack of literature comparing exposure uncertainty derived from distinct spatial interpolators. Here, we addressed these issues with two interpolation methods: regression Kriging (RK) and ordinary Kriging (OK). These methods were used to generate air-quality simulations with a geostatistical algorithm. For each method, the geostatistical uncertainty was drawn from generalized linear model (GLM) analysis. We analyzed the association between air quality and birth weight. Personal health data (n=227) and exposure data were collected in Sines (Portugal) during 2007-2010. Because air-quality monitoring stations in the city do not offer high-spatial-resolution measurements (n=1), we used lichen data as an ecological indicator of air quality (n=83). We found no significant difference in the fit of GLMs with any of the geostatistical methods. With RK, however, the models tended to fit better more often and worse less often. Moreover, the geostatistical uncertainty results showed a marginally higher mean and precision with RK. Combined with lichen data and land-use data of high spatial resolution, RK is a more effective geostatistical method for relating health outcomes with air quality in urban areas. This is particularly important in small cities, which generally do not have expensive air-quality monitoring stations with high spatial resolution. Further, alternative ways of linking human activities with their environment are needed to improve human well-being. Copyright © 2016 Elsevier B.V. All rights reserved.

High-resolution spatial modeling of daily weather elements for a catchment in the Oregon Cascade Mountains, United States

Treesearch

Christopher Daly; Jonathan W. Smith; Joseph I. Smith; Robert B. McKane

2007-01-01

High-quality daily meteorological data at high spatial resolution are essential for a variety of hydrologic and ecological modeling applications that support environmental risk assessments and decisionmaking. This paper describes the development. application. and assessment of methods to construct daily high resolution (~50-m cell size) meteorological grids for the...

The Ozone Monitoring Instrument (OMI): towards a 14 Year Data Record and Applications in the Air Quality and Climate Domain

NASA Astrophysics Data System (ADS)

Levelt, P.; Joiner, J.; Tamminen, J.; Veefkind, P.; Bhartia, P. K.; Court, A. J.; Vlemmix, T.

2017-12-01

Keywords: emission monitoring, air quality, climate, atmospheric composition The Ozone Monitoring Instrument (OMI), launched on board of NASA's EOS-Aura spacecraft on July 15, 2004, provides unique contributions to the monitoring of the ozone layer, air quality and climate from space. With a data record of 13 years, OMI provides the longest NO2 and SO2 record from space, which is essential to understand the changes to emissions globally. The combination of urban scale resolution (13 x 24 km2 in nadir) and daily global coverage proved to be key features for the air quality community. Due to the operational Very Fast Delivery (VFD / direct readout) and Near Real Time (NRT) availability of the data, OMI also plays an important role in the early developments of operational services in the atmospheric chemistry domain. For example, OMI data is currently used operationally for improving air quality forecasts, for inverting high-resolution emission maps, the UV forecast and for volcanic plume warning systems for aviation. An overview of air quality applications, emission inventory inversions and trend analyses based on the OMI data record will be presented. An outlook will be given on the potentials of augmenting this record with the high resolution air quality measurements of TROPOMI (3,5 x 7 km2) and new satellite instrumentation entering the imaging domain, such as the TROPOLITE instrument ( 1 x 1 km2). Potential of imaging type of NO2 measurements in the the climate and air quality domain will be given, most notably on the use of high resolution NO2 measurements for pin-pointing anthropogenic CO2 emissions.

Changes in Pacific Northwest Heat Waves and Associated Synoptic/Mesoscale Drivers Under Anthropogenic Global Warming

NASA Astrophysics Data System (ADS)

Brewer, M.; Mass, C.

2014-12-01

Though western Oregon and Washington summers are typically mild due to the influence of the nearby Pacific Ocean, this region occasionally experiences heat waves with temperatures in excess of 35ºC. These heat waves can have a substantial impact on this highly populated region, particularly since the population is unaccustomed to and generally unprepared for such conditions. A comprehensive evaluation is needed of past and future heat wave trends in frequency, intensity, and duration. Furthermore, it is important to understand the physical mechanisms of Northwest heat waves and how such mechanisms might change under anthropogenic global warming. Lower-tropospheric heat waves over the west coast of North America are the result of both synoptic and mesoscale factors, the latter requiring high-resolution models (roughly 12-15 km grid spacing) to simulate. Synoptic factors include large-scale warming due to horizontal advection and subsidence, as well as reductions in large-scale cloudiness. An important mesoscale factor is the occurrence of offshore (easterly) flow, resulting in an adiabatically warmed continental air mass spreading over the western lowlands rather than the more usual cool, marine air influence. To fully understand how heat waves will change under AGW, it is necessary to determine the combined impacts of both synoptic and mesoscale effects in a warming world. General Circulation Models (GCM) are generally are too coarse to simulate mesoscale effects realistically and thus may provide unreliable estimates of the frequency and magnitudes of West Coast heat waves. Therefore, to determine the regional implications of global warming, this work made use of long-term, high-resolution WRF simulations, at 36- and 12-km resolution, produced by dynamically downscaling GCM grids. This talk will examine the predicted trends in Pacific Northwest heat wave intensity, duration, and frequency during the 21st century (through 2100). The spatial distribution in the trends in heat waves, and the variability of these trends at different resolutions and among different models will also be described. Finally, changes in the synoptic and mesoscale configurations that drive Pacific Northwest heat waves and the modulating effects of local terrain and land/water contrast will be discussed.

Influence of model grid size on the simulation of PM2.5 and the related excess mortality in Japan

NASA Astrophysics Data System (ADS)

Goto, D.; Ueda, K.; Ng, C. F.; Takami, A.; Ariga, T.; Matsuhashi, K.; Nakajima, T.

2016-12-01

Aerosols, especially PM2.5, can affect air pollution, climate change, and human health. The estimation of health impacts due to PM2.5 is often performed using global and regional aerosol transport models with various horizontal resolutions. To investigate the dependence of the simulated PM2.5 on model grid sizes, we executed two simulations using a high-resolution model ( 10km; HRM) and a low-resolution model ( 100km; LRM, which is a typical value for general circulation models). In this study, we used a global-to-regional atmospheric transport model to simulate PM2.5 in Japan with a stretched grid system in HRM and a uniform grid system in LRM for the present (the 2000) and the future (the 2030, as proposed by the Representative Concentrations Pathway 4.5, RCP4.5). These calculations were performed by nudging meteorological fields obtained from an atmosphere-ocean coupled model and providing emission inventories used in the coupled model. After correcting for bias, we calculated the excess mortality due to long-term exposure to PM2.5 for the elderly. Results showed the LRM underestimated by approximately 30 % (of PM2.5 concentrations in the 2000 and 2030), approximately 60 % (excess mortality in the 2000) and approximately 90 % (excess mortality in 2030) compared to the HRM results. The estimation of excess mortality therefore performed better with high-resolution grid sizes. In addition, we also found that our nesting method could be a useful tool to obtain better estimation results.

Regional inverse modeling for high reactive species with PYVAR-CHIMERE

NASA Astrophysics Data System (ADS)

Fortems-Cheiney, A.; Pison, I.; Dufour, G.; Broquet, G.; Costantino, L.

2017-12-01

The degradation of air quality is a worldwide environmental problem: according to the World Health Organization WHO, 92% of the world's population breathe polluted air in 2016. A number of air pollutants associated with respiratory disease and shortened life expectancy play a particularly important role in global outdoor air pollution. In addition to threatening both human health and ecosystems, these gaseous air pollutants including nitrogen oxides (NOx=NO+NO2), sulfur dioxide (SO2), ammonia (NH3), and volatile organic compounds (VOCs) could be precursors of ozone (O3) and Particulate Matter (PM). Without a strong scientific back-up to determine their different sources, the necessary regulations to improve air quality will not be efficient. To date, only chemistry-transport models (CTM) are able to describe pollutant concentrations at any location in the world and their evolution in the atmosphere. Consequently, they have become essential tools for studying air quality. However, CTM are hampered by incomplete information on gaseous precursors and one of the large shortcoming for simulating the gaseous pollutants budgets is the lack of high spatio-temporal variability for the emission estimations provided as inputs for chemistry-transport models. For all these reasons, an inverse system called PYVAR-CHIMERE has been developed, operating in synergy between a CTM and atmospheric observations, and being adjust for the highly reactive species of interest here, as NO2. We present here the first results of this Bayesian variational inverse method for the quantification of NO2 emissions both over Europe (in March 2011) and over China (in January 2015), with a spatial resolution of 0.5°x0.5° and at a weekly temporal resolution, constrained by surface measurements and OMI NO2 satellite observations.

Comparison of SeaWinds Backscatter Imaging Algorithms

PubMed Central

Long, David G.

2017-01-01

This paper compares the performance and tradeoffs of various backscatter imaging algorithms for the SeaWinds scatterometer when multiple passes over a target are available. Reconstruction methods are compared with conventional gridding algorithms. In particular, the performance and tradeoffs in conventional ‘drop in the bucket’ (DIB) gridding at the intrinsic sensor resolution are compared to high-spatial-resolution imaging algorithms such as fine-resolution DIB and the scatterometer image reconstruction (SIR) that generate enhanced-resolution backscatter images. Various options for each algorithm are explored, including considering both linear and dB computation. The effects of sampling density and reconstruction quality versus time are explored. Both simulated and actual data results are considered. The results demonstrate the effectiveness of high-resolution reconstruction using SIR as well as its limitations and the limitations of DIB and fDIB. PMID:28828143

Signal to Noise Ratio for Different Gridded Rainfall Products of Indian Monsoon

NASA Astrophysics Data System (ADS)

Nehra, P.; Shastri, H. K.; Ghosh, S.; Mishra, V.; Murtugudde, R. G.

2014-12-01

Gridded rainfall datasets provide useful information of spatial and temporal distribution of precipitation over a region. For India, there are 3 gridded rainfall data products available from India Meteorological Department (IMD), Tropical Rainfall Measurement Mission (TRMM) and Asian Precipitation - Highly Resolved Observational Data Integration towards Evaluation of Water Resources (APHRODITE), these compile precipitation information obtained through satellite based measurement and ground station based data. The gridded rainfall data from IMD is available at spatial resolution of 1°, 0.5° and 0.25° where as TRMM and APHRODITE is available at 0.25°. Here, we employ 7 years (1998-2004) of common time period amongst the 3 data products for the south-west monsoon season, i.e., the months June to September. We examine temporal mean and standard deviation of these 3 products to observe substantial variation amongst them at 1° resolution whereas for 0.25° resolution, all the data types are nearly identical. We determine the Signal to Noise Ratio (SNR) of the 3 products at 1° and 0.25° resolution based on noise separation technique adopting horizontal separation of the power spectrum generated with the Fast Fourier Transformation (FFT). A methodology is developed for threshold based separation of signal and noise from the power spectrum, treating the noise as white. The variance of signal to that of noise is computed to obtain SNR. Determination of SNR for different regions over the country shows the highest SNR with APHRODITE at 0.25° resolution. It is observed that the eastern part of India has the highest SNR in all cases considered whereas the northern and southern most Indian regions have lowest SNR. An incremental linear trend is observed among the SNR values and the spatial variance of corresponding region. Relationship between the computed SNR values and the interpolation method used with the dataset is analyzed. The SNR analysis provides an effective tool to evaluate the gridded precipitation data products. However detailed analysis is needed to determine the processes that lead to these SNR distributions so that the quality of the gridded rainfall data products can be further improved and transferability of the gridding algorithms can be explored to produce a unified high-quality rainfall dataset.

Validation of Land-Surface Mosaic Heterogeneity in the GEOS DAS

NASA Technical Reports Server (NTRS)

Bosilovich, Michael G.; Molod, Andrea; Houser, Paul R.; Schubert, Siegfried

1999-01-01

The Mosaic Land-surface Model (LSM) has been included into the current GEOS Data Assimilation System (DAS). The LSM uses a more advanced representation of physical processes than previous versions of the GEOS DAS, including the representation of sub-grid heterogeneity of the land-surface through the Mosaic approach. As a first approximation, Mosaic assumes that all similar surface types within a grid-cell can be lumped together as a single'tile'. Within one GCM grid-cell, there might be 1 - 5 different tiles or surface types. All tiles are subjected to the grid-scale forcing (radiation, air temperature and specific humidity, and precipitation), and the sub-grid variability is a function of the tile characteristics. In this paper, we validate the LSM sub-grid scale variability (tiles) using a variety of surface observing stations from the Southern Great Plains (SGP) site of the Atmospheric Radiation Measurement (ARM) Program. One of the primary goals of SGP ARM is to study the variability of atmospheric radiation within a G,CM grid-cell. Enough surface data has been collected by ARM to extend this goal to sub-grid variability of the land-surface energy and water budgets. The time period of this study is the Summer of 1998 (June I - September 1). The ARM site data consists of surface meteorology, energy flux (eddy correlation and bowen ratio), soil water observations spread over an area similar to the size of a G-CM grid-cell. Various ARM stations are described as wheat and alfalfa crops, pasture and range land. The LSM tiles considered at the grid-space (2 x 2.5) nearest the ARM site include, grassland, deciduous forests, bare soil and dwarf trees. Surface energy and water balances for each tile type are compared with observations. Furthermore, we will discuss the land-surface sub-grid variability of both the ARM observations and the DAS.

Simulating the dispersion of NOx and CO2 in the city of Zurich at building resolving scale

NASA Astrophysics Data System (ADS)

Brunner, Dominik; Berchet, Antoine; Emmenegger, Lukas; Henne, Stephan; Müller, Michael

2017-04-01

Cities are emission hotspots for both greenhouse gases and air pollutants. They contribute about 70% of global greenhouse gas emissions and are home to a growing number of people potentially suffering from poor air quality in the urban environment. High-resolution atmospheric transport modelling of greenhouse gases and air pollutants at the city scale has, therefore, several important applications such as air pollutant exposure assessment, air quality forecasting, or urban planning and management. When combined with observations, it also has the potential to quantify emissions and monitor their long-term trends, which is the main motivation for the deployment of urban greenhouse gas monitoring networks. We have developed a comprehensive atmospheric modeling model system for the city of Zurich, Switzerland ( 600,000 inhabitants including suburbs), which is composed of the mesoscale model GRAMM simulating the flow in a larger domain around Zurich at 100 m resolution, and the nested high-resolution model GRAL simulating the flow and air pollutant dispersion in the city at building resolving (5-10 m) scale. Based on an extremely detailed emission inventory provided by the municipality of Zurich, we have simulated two years of hourly NOx and CO2 concentration fields across the entire city. Here, we present a detailed evaluation of the simulations against a comprehensive network of continuous monitoring sites and passive samplers for NOx and analyze the sensitivity of the results to the temporal variability of the emissions. Furthermore, we present first simulations of CO2 and investigate the challenges associated with CO2 sources not covered by the inventory such as human respiration and exchange fluxes with urban vegetation.

The impact of horizontal resolution on the representation of air-sea interaction over North Atlantic open ocean convection sites

NASA Astrophysics Data System (ADS)

Moore, Kent; Renfrew, Ian; Bromwich, David; Wilson, Aaron; Vage, Kjetil; Bai, Lesheng

2017-04-01

Open ocean convection, where a loss of surface buoyancy leads to an overturning of the water column, occurs in four distinct regions of the North Atlantic and is an integral component of the Atlantic Meridional Overturning Circulation (AMOC). The overturning typically occurs during cold air outbreaks characterized by large surface turbulent heat fluxes and convective roll cloud development. Here we compare the statistics of the air-sea interaction over these convection sites as represented in three reanalyses with horizontal grid sizes ranging from 80km to 15km. We show that increasing the resolution increases the magnitude and frequency of the most extreme total turbulent heat fluxes, as well as displacing the maxima downstream away from the ice edges. We argue that these changes are a result of the higher resolution reanalysis being better able to represent mesoscale processes that occur within the atmospheric boundary layer during cold air outbreaks.

A novel hybrid approach with multidimensional-like effects for compressible flow computations

NASA Astrophysics Data System (ADS)

Kalita, Paragmoni; Dass, Anoop K.

2017-07-01

A multidimensional scheme achieves good resolution of strong and weak shocks irrespective of whether the discontinuities are aligned with or inclined to the grid. However, these schemes are computationally expensive. This paper achieves similar effects by hybridizing two schemes, namely, AUSM and DRLLF and coupling them through a novel shock switch that operates - unlike existing switches - on the gradient of the Mach number across the cell-interface. The schemes that are hybridized have contrasting properties. The AUSM scheme captures grid-aligned (and strong) shocks crisply but it is not so good for non-grid-aligned weaker shocks, whereas the DRLLF scheme achieves sharp resolution of non-grid-aligned weaker shocks, but is not as good for grid-aligned strong shocks. It is our experience that if conventional shock switches based on variables like density, pressure or Mach number are used to combine the schemes, the desired effect of crisp resolution of grid-aligned and non-grid-aligned discontinuities are not obtained. To circumvent this problem we design a shock switch based - for the first time - on the gradient of the cell-interface Mach number with very impressive results. Thus the strategy of hybridizing two carefully selected schemes together with the innovative design of the shock switch that couples them, affords a method that produces the effects of a multidimensional scheme with a lower computational cost. It is further seen that hybridization of the AUSM scheme with the recently developed DRLLFV scheme using the present shock switch gives another scheme that provides crisp resolution for both shocks and boundary layers. Merits of the scheme are established through a carefully selected set of numerical experiments.

Analysis of UK and European NOx and VOC emission scenarios in the Defra model intercomparison exercise

NASA Astrophysics Data System (ADS)

Derwent, Richard; Beevers, Sean; Chemel, Charles; Cooke, Sally; Francis, Xavier; Fraser, Andrea; Heal, Mathew R.; Kitwiroon, Nutthida; Lingard, Justin; Redington, Alison; Sokhi, Ranjeet; Vieno, Massimo

2014-09-01

Simple emission scenarios have been implemented in eight United Kingdom air quality models with the aim of assessing how these models compared when addressing whether photochemical ozone formation in southern England was NOx- or VOC-sensitive and whether ozone precursor sources in the UK or in the Rest of Europe (RoE) were the most important during July 2006. The suite of models included three Eulerian-grid models (three implementations of one of these models), a Lagrangian atmospheric dispersion model and two moving box air parcel models. The assignments as to NOx- or VOC-sensitive and to UK- versus RoE-dominant, turned out to be highly variable and often contradictory between the individual models. However, when the assignments were filtered by model performance on each day, many of the contradictions could be eliminated. Nevertheless, no one model was found to be the 'best' model on all days, indicating that no single air quality model could currently be relied upon to inform policymakers robustly in terms of NOx- versus VOC-sensitivity and UK- versus RoE-dominance on each day. It is important to maintain a diversity in model approaches.

Dual-resolution dose assessments for proton beamlet using MCNPX 2.6.0

NASA Astrophysics Data System (ADS)

Chao, T. C.; Wei, S. C.; Wu, S. W.; Tung, C. J.; Tu, S. J.; Cheng, H. W.; Lee, C. C.

2015-11-01

The purpose of this study is to access proton dose distribution in dual resolution phantoms using MCNPX 2.6.0. The dual resolution phantom uses higher resolution in Bragg peak, area near large dose gradient, or heterogeneous interface and lower resolution in the rest. MCNPX 2.6.0 was installed in Ubuntu 10.04 with MPI for parallel computing. FMesh1 tallies were utilized to record the energy deposition which is a special designed tally for voxel phantoms that converts dose deposition from fluence. 60 and 120 MeV narrow proton beam were incident into Coarse, Dual and Fine resolution phantoms with pure water, water-bone-water and water-air-water setups. The doses in coarse resolution phantoms are underestimated owing to partial volume effect. The dose distributions in dual or high resolution phantoms agreed well with each other and dual resolution phantoms were at least 10 times more efficient than fine resolution one. Because the secondary particle range is much longer in air than in water, the dose of low density region may be under-estimated if the resolution or calculation grid is not small enough.

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.

Deriving a sea surface climatology of CO2 fugacity in support of air-sea gas flux studies

NASA Astrophysics Data System (ADS)

Goddijn-Murphy, L. M.; Woolf, D. K.; Land, P. E.; Shutler, J. D.; Donlon, C.

2014-07-01

Climatologies, or long-term averages, of essential climate variables are useful for evaluating models and providing a baseline for studying anomalies. The Surface Ocean Carbon Dioxide (CO2) Atlas (SOCAT) has made millions of global underway sea surface measurements of CO2 publicly available, all in a uniform format and presented as fugacity, fCO2. fCO2 is highly sensitive to temperature and the measurements are only valid for the instantaneous sea surface temperature (SST) that is measured concurrent with the in-water CO2 measurement. To create a climatology of fCO2 data suitable for calculating air-sea CO2 fluxes it is therefore desirable to calculate fCO2 valid for climate quality SST. This paper presents a method for creating such a climatology. We recomputed SOCAT's fCO2 values for their respective measurement month and year using climate quality SST data from satellite Earth observation and then extrapolated the resulting fCO2 values to reference year 2010. The data were then spatially interpolated onto a 1° × 1° grid of the global oceans to produce 12 monthly fCO2 distributions for 2010. The partial pressure of CO2 (pCO2) is also provided for those who prefer to use pCO2. The CO2 concentration difference between ocean and atmosphere is the thermodynamic driving force of the air-sea CO2 flux, and hence the presented fCO2 distributions can be used in air-sea gas flux calculations together with climatologies of other climate variables.

A meteorological distribution system for high-resolution terrestrial modeling (MicroMet)

Treesearch

Glen E. Liston; Kelly Elder

2006-01-01

An intermediate-complexity, quasi-physically based, meteorological model (MicroMet) has been developed to produce high-resolution (e.g., 30-m to 1-km horizontal grid increment) atmospheric forcings required to run spatially distributed terrestrial models over a wide variety of landscapes. The following eight variables, required to run most terrestrial models, are...

Using NASA Remotely Sensed Data to Help Characterize Environmental Risk Factors for National Public Health Applications

NASA Technical Reports Server (NTRS)

Al-Hamdan, Mohammad; Crosson, William; Economou, Sigrid; Estes,Maurice, Jr.; Estes, Sue; Hemmings, Sarah; Kent, Shia; Puckett, Mark; Quattrochi, Dale; Wade, Gina;

Using NASA Remotely Sensed Data to Help Characterize Environmental Risk Factors for National Public Health Applications

NASA Astrophysics Data System (ADS)

Al-Hamdan, M. Z.; Crosson, W. L.; Economou, S.; Estes, M., Jr.; Estes, S. M.; Hemmings, S. N.; Kent, S.; Loop, M.; Puckett, M.; Quattrochi, D. A.; Wade, G.; McClure, L.

2012-12-01

The overall goal of this study is to address issues of environmental health and enhance public health decision making by using NASA remotely sensed data and products. This study is a collaboration between NASA Marshall Space Flight Center, Universities Space Research Association (USRA), the University of Alabama at Birmingham (UAB) School of Public Health and the Centers for Disease Control and Prevention (CDC) Office of Surveillance, Epidemiology and Laboratory Services. The objectives of this study are to develop high-quality spatial data sets of environmental variables, link these with public health data from a national cohort study, and deliver the environmental data sets and associated public health analyses to local, state and federal end-user groups. Three daily environmental data sets were developed for the conterminous U.S. on different spatial resolutions for the period 2003-2008: (1) spatial surfaces of estimated fine particulate matter (PM2.5) on a 10-km grid using US Environmental Protection Agency (EPA) ground observations and NASA's MODerate-resolution Imaging Spectroradiometer (MODIS) data; (2) a 1-km grid of MODIS Land Surface Temperature (LST); and (3) a 12-km grid of daily incoming solar radiation and maximum and minimum air temperature using the North American Land Data Assimilation System (NLDAS) data. These environmental datasets were linked with public health data from the UAB REasons for Geographic and Racial Differences in Stroke (REGARDS) national cohort study to determine whether exposures to these environmental risk factors are related to cognitive decline, stroke and other health outcomes. These environmental national datasets will also be made available to public health professionals, researchers and the general public via the CDC Wide-ranging Online Data for Epidemiologic Research (WONDER) system, where they can be aggregated to the county-level, state-level, or regional-level as per users' need and downloaded in tabular, graphical, and map formats. This provides a significant addition to the CDC WONDER online system, allowing public health researchers and policy makers to better include environmental exposure data in the context of other health data available in CDC WONDER. It also substantially expands public access to NASA data, making their use by a wide range of decision-makers feasible.

Linking NASA Environmental Data with a National Public Health Cohort Study and a CDC On-Line System to Enhance Public Health Decision Making

NASA Technical Reports Server (NTRS)

Al-Hamdan, Mohammad; Crosson, William; Economou, Sigrid; Estes, Maurice, Jr.; Estes, Sue; Hemmings, Sarah; Kent, Shia; Puckett, Mark; Quattrochi, Dale; Wade, Gina;

An emission processing system for air quality modelling in the Mexico City metropolitan area: Evaluation and comparison of the MOBILE6.2-Mexico and MOVES-Mexico traffic emissions.

PubMed

Guevara, M; Tena, C; Soret, A; Serradell, K; Guzmán, D; Retama, A; Camacho, P; Jaimes-Palomera, M; Mediavilla, A

2017-04-15

This article describes the High-Elective Resolution Modelling Emission System for Mexico (HERMES-Mex) model, an emission processing tool developed to transform the official Mexico City Metropolitan Area (MCMA) emission inventory into hourly, gridded (up to 1km 2 ) and speciated emissions used to drive mesoscale air quality simulations with the Community Multi-scale Air Quality (CMAQ) model. The methods and ancillary information used for the spatial and temporal disaggregation and speciation of the emissions are presented and discussed. The resulting emission system is evaluated, and a case study on CO, NO 2 , O 3 , VOC and PM 2.5 concentrations is conducted to demonstrate its applicability. Moreover, resulting traffic emissions from the Mobile Source Emission Factor Model for Mexico (MOBILE6.2-Mexico) and the MOtor Vehicle Emission Simulator for Mexico (MOVES-Mexico) models are integrated in the tool to assess and compare their performance. NO x and VOC total emissions modelled are reduced by 37% and 26% in the MCMA when replacing MOBILE6.2-Mexico for MOVES-Mexico traffic emissions. In terms of air quality, the system composed by the Weather Research and Forecasting model (WRF) coupled with the HERMES-Mex and CMAQ models properly reproduces the pollutant levels and patterns measured in the MCMA. The system's performance clearly improves in urban stations with a strong influence of traffic sources when applying MOVES-Mexico emissions. Despite reducing estimations of modelled precursor emissions, O 3 peak averages are increased in the MCMA core urban area (up to 30ppb) when using MOVES-Mexico mobile emissions due to its VOC-limited regime, while concentrations in the surrounding suburban/rural areas decrease or increase depending on the meteorological conditions of the day. The results obtained suggest that the HERMES-Mex model can be used to provide model-ready emissions for air quality modelling in the MCMA. Copyright © 2017 Elsevier B.V. All rights reserved.

Representing the Effects of Long-Range Transport and Lateral Boundary Conditions in Regional Air Pollution Models

EPA Science Inventory

The Community Multiscale Air Quality (CMAQ) modeling system was applied to a domain covering the northern hemisphere; meteorological information was derived from the Weather Research and Forecasting (WRF) model run on identical grid and projection configuration, while the emissio...

Air Quality Science and Regulatory Efforts Require Geostationary Satellite Measurements

NASA Technical Reports Server (NTRS)

Pickering, Kenneth E.; Allen, D. J.; Stehr, J. W.

2006-01-01

Air quality scientists and regulatory agencies would benefit from the high spatial and temporal resolution trace gas and aerosol data that could be provided by instruments on a geostationary platform. More detailed time-resolved data from a geostationary platform could be used in tracking regional transport and in evaluating mesoscale air quality model performance in terms of photochemical evolution throughout the day. The diurnal cycle of photochemical pollutants is currently missing from the data provided by the current generation of atmospheric chemistry satellites which provide only one measurement per day. Often peak surface ozone mixing ratios are reached much earlier in the day during major regional pollution episodes than during local episodes due to downward mixing of ozone that had been transported above the boundary layer overnight. The regional air quality models often do not simulate this downward mixing well enough and underestimate surface ozone in regional episodes. Having high time-resolution geostationary data will make it possible to determine the magnitude of this lower-and mid-tropospheric transport that contributes to peak eight-hour average ozone and 24-hour average PM2.5 concentrations. We will show ozone and PM(sub 2.5) episodes from the CMAQ model and suggest ways in which geostationary satellite data would improve air quality forecasting. Current regulatory modeling is typically being performed at 12 km horizontal resolution. State and regional air quality regulators in regions with complex topography and/or land-sea breezes are anxious to move to 4-km or finer resolution simulations. Geostationary data at these or finer resolutions will be useful in evaluating such models.

Air Quality Improvements of Increased Integration of Renewables: Solar Photovoltaics Penetration Scenarios

NASA Astrophysics Data System (ADS)

Duran, P.; Holloway, T.; Brinkman, G.; Denholm, P.; Littlefield, C. M.

2011-12-01

Solar photovoltaics (PV) are an attractive technology because they can be locally deployed and tend to yield high production during periods of peak electric demand. These characteristics can reduce the need for conventional large-scale electricity generation, thereby reducing emissions of criteria air pollutants (CAPs) and improving ambient air quality with regard to such pollutants as nitrogen oxides, sulfur oxides and fine particulates. Such effects depend on the local climate, time-of-day emissions, available solar resources, the structure of the electric grid, and existing electricity production among other factors. This study examines the air quality impacts of distributed PV across the United States Eastern Interconnection. In order to accurately model the air quality impact of distributed PV in space and time, we used the National Renewable Energy Lab's (NREL) Regional Energy Deployment System (ReEDS) model to form three unique PV penetration scenarios in which new PV construction is distributed spatially based upon economic drivers and natural solar resources. Those scenarios are 2006 Eastern Interconnection business as usual, 10% PV penetration, and 20% PV penetration. With the GridView (ABB, Inc) dispatch model, we used historical load data from 2006 to model electricity production and distribution for each of the three scenarios. Solar PV electric output was estimated using historical weather data from 2006. To bridge the gap between dispatch and air quality modeling, we will create emission profiles for electricity generating units (EGUs) in the Eastern Interconnection from historical Continuous Emissions Monitoring System (CEMS) data. Via those emissions profiles, we will create hourly emission data for EGUs in the Eastern Interconnect for each scenario during 2006. Those data will be incorporated in the Community Multi-scale Air Quality (CMAQ) model using the Sparse Matrix Operator Kernel Emissions (SMOKE) model. Initial results indicate that PV penetration significantly reduces conventional peak electricity production and that, due to reduced emissions during periods of extremely active photochemistry, air quality could see benefits.

Characteristics of the ocean simulations in the Max Planck Institute Ocean Model (MPIOM) the ocean component of the MPI-Earth system model

NASA Astrophysics Data System (ADS)

Jungclaus, J. H.; Fischer, N.; Haak, H.; Lohmann, K.; Marotzke, J.; Matei, D.; Mikolajewicz, U.; Notz, D.; von Storch, J. S.

2013-06-01

MPI-ESM is a new version of the global Earth system model developed at the Max Planck Institute for Meteorology. This paper describes the ocean state and circulation as well as basic aspects of variability in simulations contributing to the fifth phase of the Coupled Model Intercomparison Project (CMIP5). The performance of the ocean/sea-ice model MPIOM, coupled to a new version of the atmosphere model ECHAM6 and modules for land surface and ocean biogeochemistry, is assessed for two model versions with different grid resolution in the ocean. The low-resolution configuration has a nominal resolution of 1.5°, whereas the higher resolution version features a quasiuniform, eddy-permitting global resolution of 0.4°. The paper focuses on important oceanic features, such as surface temperature and salinity, water mass distribution, large-scale circulation, and heat and freshwater transports. In general, these integral quantities are simulated well in comparison with observational estimates, and improvements in comparison with the predecessor system are documented; for example, for tropical variability and sea ice representation. Introducing an eddy-permitting grid configuration in the ocean leads to improvements, in particular, in the representation of interior water mass properties in the Atlantic and in the representation of important ocean currents, such as the Agulhas and Equatorial current systems. In general, however, there are more similarities than differences between the two grid configurations, and several shortcomings, known from earlier versions of the coupled model, prevail.

Empirical downscaling of atmospheric key variables above a tropical glacier surface (Cordillera Blanca, Peru)

NASA Astrophysics Data System (ADS)

Hofer, M.; Kaser, G.; Mölg, T.; Juen, I.; Wagnon, P.

2009-04-01

Glaciers in the outer tropical Cordillera Blanca (Peru, South America) are of major socio-economic importance, since glacier runoff represents the primary water source during the dry season, when little or no rainfall occurs. Due to their location at high elevations, the glaciers moreover provide important information about climate change in the tropical troposphere, where measurements are sparse. This study targets the local reconstruction of air temperature, specific humidity and wind speed above the surface of an outer tropical glacier from NCEP/NCAR reanalysis data as large scale predictors. Since a farther scope is to provide input data for process based glacier mass balance modelling, the reconstruction pursues a high temporal resolution. Hence an empirical downscaling scheme is developed, based on a few years' time series of hourly observations from automatic weather stations, located at the glacier Artesonraju and nearby moraines (Northern Cordillera Blanca). Principal component and multiple regression analyses are applied to define the appropriate spatial downscaling domain, suitable predictor variables, and the statistical transfer functions. The model performance is verified using an independent data set. The best predictors are lower tropospheric air temperature and specific humidity, at reanalysis model grid points that represent the Bolivian Altiplano, located in the South of the Cordillera Blanca. The developed downscaling model explaines a considerable portion (more than 60%) of the diurnal variance of air temperature and specific humidity at the moraine stations, and air temperature above the glacier surface. Specific humidity above the glacier surface, however, can be reconstructed well in the seasonal, but not in the required diurnal time resolution. Wind speed can only be poorly determined by the large scale predictors (r² lower than 0.3) at both sites. We assume a complex local interaction between valley and glacier wind system to be the main cause for the differences between model and observations.

Connecting spatial and temporal scales of tropical precipitation in observations and the MetUM-GA6

NASA Astrophysics Data System (ADS)

Martin, Gill M.; Klingaman, Nicholas P.; Moise, Aurel F.

2017-01-01

This study analyses tropical rainfall variability (on a range of temporal and spatial scales) in a set of parallel Met Office Unified Model (MetUM) simulations at a range of horizontal resolutions, which are compared with two satellite-derived rainfall datasets. We focus on the shorter scales, i.e. from the native grid and time step of the model through sub-daily to seasonal, since previous studies have paid relatively little attention to sub-daily rainfall variability and how this feeds through to longer scales. We find that the behaviour of the deep convection parametrization in this model on the native grid and time step is largely independent of the grid-box size and time step length over which it operates. There is also little difference in the rainfall variability on larger/longer spatial/temporal scales. Tropical convection in the model on the native grid/time step is spatially and temporally intermittent, producing very large rainfall amounts interspersed with grid boxes/time steps of little or no rain. In contrast, switching off the deep convection parametrization, albeit at an unrealistic resolution for resolving tropical convection, results in very persistent (for limited periods), but very sporadic, rainfall. In both cases, spatial and temporal averaging smoothes out this intermittency. On the ˜ 100 km scale, for oceanic regions, the spectra of 3-hourly and daily mean rainfall in the configurations with parametrized convection agree fairly well with those from satellite-derived rainfall estimates, while at ˜ 10-day timescales the averages are overestimated, indicating a lack of intra-seasonal variability. Over tropical land the results are more varied, but the model often underestimates the daily mean rainfall (partly as a result of a poor diurnal cycle) but still lacks variability on intra-seasonal timescales. Ultimately, such work will shed light on how uncertainties in modelling small-/short-scale processes relate to uncertainty in climate change projections of rainfall distribution and variability, with a view to reducing such uncertainty through improved modelling of small-/short-scale processes.

Optimisation of an idealised primitive equation ocean model using stochastic parameterization

NASA Astrophysics Data System (ADS)

Cooper, Fenwick C.

2017-05-01

Using a simple parameterization, an idealised low resolution (biharmonic viscosity coefficient of 5 × 1012 m4s-1 , 128 × 128 grid) primitive equation baroclinic ocean gyre model is optimised to have a much more accurate climatological mean, variance and response to forcing, in all model variables, with respect to a high resolution (biharmonic viscosity coefficient of 8 × 1010 m4s-1 , 512 × 512 grid) equivalent. For example, the change in the climatological mean due to a small change in the boundary conditions is more accurate in the model with parameterization. Both the low resolution and high resolution models are strongly chaotic. We also find that long timescales in the model temperature auto-correlation at depth are controlled by the vertical temperature diffusion parameter and time mean vertical advection and are caused by short timescale random forcing near the surface. This paper extends earlier work that considered a shallow water barotropic gyre. Here the analysis is extended to a more turbulent multi-layer primitive equation model that includes temperature as a prognostic variable. The parameterization consists of a constant forcing, applied to the velocity and temperature equations at each grid point, which is optimised to obtain a model with an accurate climatological mean, and a linear stochastic forcing, that is optimised to also obtain an accurate climatological variance and 5 day lag auto-covariance. A linear relaxation (nudging) is not used. Conservation of energy and momentum is discussed in an appendix.

Exploration of exposure conditions with a novel wireless detector for bedside digital radiography

NASA Astrophysics Data System (ADS)

Bosmans, Hilde; Nens, Joris; Delzenne, Louis; Marshall, Nicholas; Pauwels, Herman; De Wever, Walter; Oyen, Raymond

2012-03-01

We propose, apply and validate an optimization scheme for a new wireless CsI based DR detector in combination with a regular mobile X-ray system for bedside imaging applications. Three different grids were tested in this combination. Signal-difference-to-noise was investigated in two ways, using a 1mm Cu piece in combination with different thicknesses of PMMA and by means of the CDRAD phantom using 10 images per condition and an automated evaluation method. A Figure of Merit (FOM), namely SDNR2/Imparted Energy, was calculated for a large range of exposure conditions, without and with grid in place. Misalignment of the grids was evaluated via the same FOMs. This optimization study was validated with comparative X-ray acquisitions performed on dead bodies. An experienced radiologist scored the quality of several specific aspects for all these exposures. Signal difference to noise ratios measured with the Cu method correlated well with the threshold contrasts from the CDRAD analysis (R2 > 0.9). The analysis showed optimal FOM with detector air kerma rates as typically used in clinical practice. Lower tube voltages provide higher FOM than the higher values but their practical use depends on the limitations of X-ray tubes, linked to patient motion artefacts. The use of high resolution grids should be encouraged, as the FOM increases with 47% at 75kV. These scores from the Visual grading study confirmed the results obtained with the FOM. The switch to (wireless) DR technology for bedside imaging could benefit from devices to improve grid positioning or any scatter reduction technique.

Simultaneous statistical bias correction of multiplePM2.5 species from a regional photochemical grid model

EPA Science Inventory

In recent years environmental epidemiologists have begun utilizing regionalscale air quality computer models to predict ambient air pollution concentrations in health studies instead of or in addition to monitoring data from central sites. The advantages of using such models i...

Modeling Dynamics of South American Rangelands to Climate Variability and Human Impact

NASA Astrophysics Data System (ADS)

Stanimirova, R.; Arevalo, P. A.; Kaufmann, R.; Maus, V.; Lesiv, M.; Havlik, P.; Friedl, M. A.

2017-12-01

The combined pressures of climate change and shifting dietary preferences are creating an urgent need to improve understanding of how climate and land management are jointly affecting the sustainability of rangelands. In particular, our ability to effectively manage rangelands in a manner that satisfies increasing demand for meat and dairy while reducing environmental impact depends on the sensitivity of rangelands to perturbations from both climate (e.g., drought) and land use (e.g., grazing). To characterize the sensitivity of rangeland vegetation to variation in climate, we analyzed gridded time series of satellite and climate data at 0.5-degree spatial resolution from 2003 to 2016 for rangeland ecosystems in South America. We used panel regression and canonical correlation to analyze the relationship between time series of enhanced vegetation index (EVI) derived from NASA's Moderate Spatial Resolution Imaging Spectroradiometer (MODIS) and gridded precipitation and air temperature data from the University of East Anglia's Climate Research Unit. To quantify the degree to which livestock management explains geographic variation of EVI, we used global livestock distribution (FAO) and feed requirements data from the Global Biosphere Management Model (GLOBIOM). Because rangeland ecosystems are sensitive to changes in meteorological variables at different time scales, we evaluated the strength of coupling between anomalies in EVI and anomalies in temperature and standardized precipitation index (SPI) data at 1-6 month lags. Our results show statistically significant relationships between EVI and precipitation during summer, fall, and winter in both tropical and subtropical agroecological zones of South America. Further, lagged precipitation effects, which reflect memory in the system, explain significant variance in winter EVI anomalies. While precipitation emerges as the dominant driver of variability in rangeland greenness, we find evidence of a management-induced signal as well. Our modeling framework integrates satellite observation, meteorological data sets, and land use/cover change information to improve our capability to monitor and manage the long-term sustainability of rangelands.

Variability in lateral carbon export from four major tributaries in the Upper Mississippi River Basin

NASA Astrophysics Data System (ADS)

Stanimirova, R.; Arevalo, P. A.; Kaufmann, R.; Maus, V.; Lesiv, M.; Havlik, P.; Friedl, M. A.

2016-12-01

The combined pressures of climate change and shifting dietary preferences are creating an urgent need to improve understanding of how climate and land management are jointly affecting the sustainability of rangelands. In particular, our ability to effectively manage rangelands in a manner that satisfies increasing demand for meat and dairy while reducing environmental impact depends on the sensitivity of rangelands to perturbations from both climate (e.g., drought) and land use (e.g., grazing). To characterize the sensitivity of rangeland vegetation to variation in climate, we analyzed gridded time series of satellite and climate data at 0.5-degree spatial resolution from 2003 to 2016 for rangeland ecosystems in South America. We used panel regression and canonical correlation to analyze the relationship between time series of enhanced vegetation index (EVI) derived from NASA's Moderate Spatial Resolution Imaging Spectroradiometer (MODIS) and gridded precipitation and air temperature data from the University of East Anglia's Climate Research Unit. To quantify the degree to which livestock management explains geographic variation of EVI, we used global livestock distribution (FAO) and feed requirements data from the Global Biosphere Management Model (GLOBIOM). Because rangeland ecosystems are sensitive to changes in meteorological variables at different time scales, we evaluated the strength of coupling between anomalies in EVI and anomalies in temperature and standardized precipitation index (SPI) data at 1-6 month lags. Our results show statistically significant relationships between EVI and precipitation during summer, fall, and winter in both tropical and subtropical agroecological zones of South America. Further, lagged precipitation effects, which reflect memory in the system, explain significant variance in winter EVI anomalies. While precipitation emerges as the dominant driver of variability in rangeland greenness, we find evidence of a management-induced signal as well. Our modeling framework integrates satellite observation, meteorological data sets, and land use/cover change information to improve our capability to monitor and manage the long-term sustainability of rangelands.

Regionalisation of statistical model outputs creating gridded data sets for Germany

NASA Astrophysics Data System (ADS)

Höpp, Simona Andrea; Rauthe, Monika; Deutschländer, Thomas

2016-04-01

The goal of the German research program ReKliEs-De (regional climate projection ensembles for Germany, http://.reklies.hlug.de) is to distribute robust information about the range and the extremes of future climate for Germany and its neighbouring river catchment areas. This joint research project is supported by the German Federal Ministry of Education and Research (BMBF) and was initiated by the German Federal States. The Project results are meant to support the development of adaptation strategies to mitigate the impacts of future climate change. The aim of our part of the project is to adapt and transfer the regionalisation methods of the gridded hydrological data set (HYRAS) from daily station data to the station based statistical regional climate model output of WETTREG (regionalisation method based on weather patterns). The WETTREG model output covers the period of 1951 to 2100 with a daily temporal resolution. For this, we generate a gridded data set of the WETTREG output for precipitation, air temperature and relative humidity with a spatial resolution of 12.5 km x 12.5 km, which is common for regional climate models. Thus, this regionalisation allows comparing statistical to dynamical climate model outputs. The HYRAS data set was developed by the German Meteorological Service within the German research program KLIWAS (www.kliwas.de) and consists of daily gridded data for Germany and its neighbouring river catchment areas. It has a spatial resolution of 5 km x 5 km for the entire domain for the hydro-meteorological elements precipitation, air temperature and relative humidity and covers the period of 1951 to 2006. After conservative remapping the HYRAS data set is also convenient for the validation of climate models. The presentation will consist of two parts to present the actual state of the adaptation of the HYRAS regionalisation methods to the statistical regional climate model WETTREG: First, an overview of the HYRAS data set and the regionalisation methods for precipitation (REGNIE method based on a combination of multiple linear regression with 5 predictors and inverse distance weighting), air temperature and relative humidity (optimal interpolation) will be given. Finally, results of the regionalisation of WETTREG model output will be shown.

Tropical Cyclone Activity in the High-Resolution Community Earth System Model and the Impact of Ocean Coupling

NASA Astrophysics Data System (ADS)

Li, Hui; Sriver, Ryan L.

2018-01-01

High-resolution Atmosphere General Circulation Models (AGCMs) are capable of directly simulating realistic tropical cyclone (TC) statistics, providing a promising approach for TC-climate studies. Active air-sea coupling in a coupled model framework is essential to capturing TC-ocean interactions, which can influence TC-climate connections on interannual to decadal time scales. Here we investigate how the choices of ocean coupling can affect the directly simulated TCs using high-resolution configurations of the Community Earth System Model (CESM). We performed a suite of high-resolution, multidecadal, global-scale CESM simulations in which the atmosphere (˜0.25° grid spacing) is configured with three different levels of ocean coupling: prescribed climatological sea surface temperature (SST) (ATM), mixed layer ocean (SLAB), and dynamic ocean (CPL). We find that different levels of ocean coupling can influence simulated TC frequency, geographical distributions, and storm intensity. ATM simulates more storms and higher overall storm intensity than the coupled simulations. It also simulates higher TC track density over the eastern Pacific and the North Atlantic, while TC tracks are relatively sparse within CPL and SLAB for these regions. Storm intensification and the maximum wind speed are sensitive to the representations of local surface flux feedbacks in different coupling configurations. Key differences in storm number and distribution can be attributed to variations in the modeled large-scale climate mean state and variability that arise from the combined effect of intrinsic model biases and air-sea interactions. Results help to improve our understanding about the representation of TCs in high-resolution coupled Earth system models, with important implications for TC-climate applications.

Impact of land cover data on the simulation of urban heat island for Berlin using WRF coupled with bulk approach of Noah-LSM

NASA Astrophysics Data System (ADS)

Li, Huidong; Wolter, Michael; Wang, Xun; Sodoudi, Sahar

2017-09-01

Urban-rural difference of land cover is the key determinant of urban heat island (UHI). In order to evaluate the impact of land cover data on the simulation of UHI, a comparative study between up-to-date CORINE land cover (CLC) and Urban Atlas (UA) with fine resolution (100 and 10 m) and old US Geological Survey (USGS) data with coarse resolution (30 s) was conducted using the Weather Research and Forecasting model (WRF) coupled with bulk approach of Noah-LSM for Berlin. The comparison between old data and new data partly reveals the effect of urbanization on UHI and the historical evolution of UHI, while the comparison between different resolution data reveals the impact of resolution of land cover on the simulation of UHI. Given the high heterogeneity of urban surface and the fine-resolution land cover data, the mosaic approach was implemented in this study to calculate the sub-grid variability in land cover compositions. Results showed that the simulations using UA and CLC data perform better than that using USGS data for both air and land surface temperatures. USGS-based simulation underestimates the temperature, especially in rural areas. The longitudinal variations of both temperature and land surface temperature show good agreement with urban fraction for all the three simulations. To better study the comprehensive characteristic of UHI over Berlin, the UHI curves (UHIC) are developed for all the three simulations based on the relationship between temperature and urban fraction. CLC- and UA-based simulations show smoother UHICs than USGS-based simulation. The simulation with old USGS data obviously underestimates the extent of UHI, while the up-to-date CLC and UA data better reflect the real urbanization and simulate the spatial distribution of UHI more accurately. However, the intensity of UHI simulated by CLC and UA data is not higher than that simulated by USGS data. The simulated air temperature is not dominated by the land cover as much as the land surface temperature, as air temperature is also affected by air advection.

Improving the City-scale Emission Inventory of Anthropogenic Air Pollutants: A Case Study of Nanjing

NASA Astrophysics Data System (ADS)

Qiu, L.; Zhao, Y.; Xu, R.; Xie, F.; Wang, H.; Qin, H.; Wu, X.; Zhang, J.

2014-12-01

To evaluate the improvement of city-scale emission inventory, a high-resolution emission inventory of air pollutants for Nanjing is first developed combining detailed source information, and then justified through quantitative analysis with observations. The best available domestic emission factors and unit-/facility-based activity level data were compiled based on a thorough field survey on major emission sources. Totally 1089 individual emission sources were identified as point sources and all the emission-related parameters including burner type, combustion technology, fuel quality, and removal efficiency of pollution control devices, are carefully investigated and analyzed. Some new data such as detailed information of city fueling-gas stations, construction sites, monthly activity level, data from continuous emission monitoring systems and traffic flow information were combined to improve spatiotemporal distribution of this inventory. For SO2, NOX and CO, good spatial correlations were found between ground observation (9 state controlling air sampling sites in Nanjing) and city-scale emission inventory (R2=0.34, 0.38 and 0.74, respectively). For TSP, PM10 and PM2.5, however, poorer correlation was found due to relatively weaker accuracy in emission estimation and spatial distribution of road dust. The mixing ratios between specific pollutants including OC/EC, BC/CO and CO2/CO, are well correlated between those from ground observation and emission. Compared to MEIC (Multi-resolution Emission Inventory for China), there is a better spatial consistence between this city-scale emission inventory and NO2 measured by OMI (Ozone Monitoring Instrument). In particular, the city-scale emission inventory still correlated well with satellite observations (R2=0.28) while the regional emission inventory showed little correlation with satellite observations (R2=0.09) when grids containing power plants are excluded. It thus confirms the improvement of city-scale emission inventory on industrial and transportation sources other than big power plants. Through the inventory evaluation, the necessity to develop high-resolution emission inventory with comprehensive emission source information is revealed for atmospheric science studies and air quality improvement at local scale.

Evolution of aerosol downwind of a major highway

NASA Astrophysics Data System (ADS)

Liggio, J.; Staebler, R. M.; Brook, J.; Li, S.; Vlasenko, A. L.; Sjostedt, S. J.; Gordon, M.; Makar, P.; Mihele, C.; Evans, G. J.; Jeong, C.; Wentzell, J. J.; Lu, G.; Lee, P.

2010-12-01

Primary aerosol from traffic emissions can have a considerable impact local and regional scale air quality. In order to assess the effect of these emissions and of future emissions scenarios, air quality models are required which utilize emissions representative of real world conditions. Often, the emissions processing systems which provide emissions input for the air quality models rely on laboratory testing of individual vehicles under non-ambient conditions. However, on the sub-grid scale particle evolution may lead to changes in the primary emitted size distribution and gas-particle partitioning that are not properly considered when the emissions are ‘instantly mixed’ within the grid volume. The affect of this modeling convention on model results is not well understood. In particular, changes in organic gas/particle partitioning may result in particle evaporation or condensation onto pre-existing aerosol. The result is a change in the particle distribution and/or an increase in the organic mass available for subsequent gas-phase oxidation. These effects may be missing from air-quality models, and a careful analysis of field data is necessary to quantify their impact. A study of the sub-grid evolution of aerosols (FEVER; Fast Evolution of Vehicle Emissions from Roadways) was conducted in the Toronto area in the summer of 2010. The study included mobile measurements of particle size distributions with a Fast mobility particle sizer (FMPS), aerosol composition with an Aerodyne aerosol mass spectrometer (AMS), black carbon (SP2, PA, LII), VOCs (PTR-MS) and other trace gases. The mobile laboratory was used to measure the concentration gradient of the emissions at perpendicular distances from the highway as well as the physical and chemical evolution of the aerosol. Stationary sites at perpendicular distances and upwind from the highway also monitored the particle size distribution. In addition, sonic anemometers mounted on the mobile lab provided measurements of turbulent dispersion as a function of distance from the highway, and a traffic camera was used to determine traffic density, composition and speed. These measurements differ from previous studies in that turbulence is measured under realistic conditions and hence the relationship of the aerosol evolution to atmospheric stability and mixing will also be quantified. Preliminary results suggest that aerosol size and composition does change on the sub-grid scale, and sub-grid scale parameterizations of turbulence and particle chemistry should be included in models to accurately represent these effects.

Recent Advances in High-Resolution Regional Climate Modeling at the U.S. Environmental Protection Agency

NASA Astrophysics Data System (ADS)

Alapaty, Kiran; Bullock, O. Russell; Herwehe, Jerold; Spero, Tanya; Nolte, Christopher; Mallard, Megan

2014-05-01

The Regional Climate Modeling Team at the U.S. Environmental Protection Agency has been improving the quality of regional climate fields generated by the Weather Research and Forecasting (WRF) model. Active areas of research include improving core physics within the WRF model and adapting the physics for regional climate applications, improving the representation of inland lakes that are unresolved by the driving fields, evaluating nudging strategies, and devising techniques to demonstrate value added by dynamical downscaling. These research efforts have been conducted using reanalysis data as driving fields, and then their results have been applied to downscale data from global climate models. The goals of this work are to equip environmental managers and policy/decision makers in the U.S. with science, tools, and data to inform decisions related to adapting to and mitigating the potential impacts of climate change on air quality, ecosystems, and human health. Our presentation will focus mainly on one area of the Team's research: Development and testing of a seamless convection parameterization scheme. For the continental U.S., one of the impediments to high-resolution (~3 to 15 km) climate modeling is related to the lack of a seamless convection parameterization that works across many scales. Since many convection schemes are not developed to work at those "gray scales", they often lead to excessive precipitation during warm periods (e.g., summer). The Kain-Fritsch (KF) convection parameterization in the WRF model has been updated such that it can be used seamlessly across spatial scales down to ~1 km grid spacing. First, we introduced subgrid-scale cloud and radiation interactions that had not been previously considered in the KF scheme. Then, a scaling parameter was developed to introduce scale-dependency in the KF scheme for use with various processes. In addition, we developed new formulations for: (1) convective adjustment timescale; (2) entrainment of environmental air; (3) impacts of convective updraft on grid-scale vertical velocity; (4) convective cloud microphysics; (5) stabilizing capacity; (6) elimination of double counting of precipitation; and (7) estimation of updraft mass flux at the lifting condensation level. Some of these scale-dependent formulations make the KF scheme operable at all scales up to about sub-kilometer grid resolution. In this presentation, regional climate simulations using the WRF model will be presented to demonstrate the effects of these changes to the KF scheme. Additionally, we briefly present results obtained from the improved representation of inland lakes, various nudging strategies, and added value of dynamical downscaling of regional climate. Requesting for a plenary talk for the session: "Regional climate modeling, including CORDEX" (session number CL6.4) at the EGU 2014 General Assembly, to be held 27 April - 2 May 2014 in Vienna, Austria.

Effect of grid resolution on large eddy simulation of wall-bounded turbulence

NASA Astrophysics Data System (ADS)

Rezaeiravesh, S.; Liefvendahl, M.

2018-05-01

The effect of grid resolution on a large eddy simulation (LES) of a wall-bounded turbulent flow is investigated. A channel flow simulation campaign involving a systematic variation of the streamwise (Δx) and spanwise (Δz) grid resolution is used for this purpose. The main friction-velocity-based Reynolds number investigated is 300. Near the walls, the grid cell size is determined by the frictional scaling, Δx+ and Δz+, and strongly anisotropic cells, with first Δy+ ˜ 1, thus aiming for the wall-resolving LES. Results are compared to direct numerical simulations, and several quality measures are investigated, including the error in the predicted mean friction velocity and the error in cross-channel profiles of flow statistics. To reduce the total number of channel flow simulations, techniques from the framework of uncertainty quantification are employed. In particular, a generalized polynomial chaos expansion (gPCE) is used to create metamodels for the errors over the allowed parameter ranges. The differing behavior of the different quality measures is demonstrated and analyzed. It is shown that friction velocity and profiles of the velocity and Reynolds stress tensor are most sensitive to Δz+, while the error in the turbulent kinetic energy is mostly influenced by Δx+. Recommendations for grid resolution requirements are given, together with the quantification of the resulting predictive accuracy. The sensitivity of the results to the subgrid-scale (SGS) model and varying Reynolds number is also investigated. All simulations are carried out with second-order accurate finite-volume-based solver OpenFOAM. It is shown that the choice of numerical scheme for the convective term significantly influences the error portraits. It is emphasized that the proposed methodology, involving the gPCE, can be applied to other modeling approaches, i.e., other numerical methods and the choice of SGS model.

Progress on Implementing Additional Physics Schemes into ...

EPA Pesticide Factsheets

The U.S. Environmental Protection Agency (USEPA) has a team of scientists developing a next generation air quality modeling system employing the Model for Prediction Across Scales – Atmosphere (MPAS-A) as its meteorological foundation. Several preferred physics schemes and options available in the Weather Research and Forecasting (WRF) model are regularly used by the USEPA with the Community Multiscale Air Quality (CMAQ) model to conduct retrospective air quality simulations. These include the Pleim surface layer, the Pleim-Xiu (PX) land surface model with fractional land use for a 40-class National Land Cover Database (NLCD40), the Asymmetric Convective Model 2 (ACM2) planetary boundary layer scheme, the Kain-Fritsch (KF) convective parameterization with subgrid-scale cloud feedback to the radiation schemes and a scale-aware convective time scale, and analysis nudging four-dimensional data assimilation (FDDA). All of these physics modules and options have already been implemented by the USEPA into MPAS-A v4.0, tested, and evaluated (please see the presentations of R. Gilliam and R. Bullock at this workshop). Since the release of MPAS v5.1 in May 2017, work has been under way to implement these preferred physics options into the MPAS-A v5.1 code. Test simulations of a summer month are being conducted on a global variable resolution mesh with the higher resolution cells centered over the contiguous United States. Driving fields for the FDDA and soil nudging are

Techno-economic assessment of the need for bulk energy storage in low-carbon electricity systems with a focus on compressed air storage (CAES)

NASA Astrophysics Data System (ADS)

Safaei Mohamadabadi, Hossein

Increasing electrification of the economy while decarbonizing the electricity supply is among the most effective strategies for cutting greenhouse gas (GHG) emissions in order to abate climate change. This thesis offers insights into the role of bulk energy storage (BES) systems to cut GHG emissions from the electricity sector. Wind and solar energies can supply large volumes of low-carbon electricity. Nevertheless, large penetration of these resources poses serious reliability concerns to the grid, mainly because of their intermittency. This thesis evaluates the performance of BES systems - especially compressed air energy storage (CAES) technology - for integration of wind energy from engineering and economic aspects. Analytical thermodynamic analysis of Distributed CAES (D-CAES) and Adiabatic CAES (A-CAES) suggest high roundtrip storage efficiencies ( 80% and 70%) compared to conventional CAES ( 50%). Using hydrogen to fuel CAES plants - instead of natural gas - yields a low overall efficiency ( 35%), despite its negligible GHG emissions. The techno-economic study of D-CAES shows that exporting compression heat to low-temperature loads (e.g. space heating) can enhance both the economic and emissions performance of compressed air storage plants. A case study for Alberta, Canada reveals that the abatement cost of replacing a conventional CAES with D-CAES plant practicing electricity arbitrage can be negative (-$40 per tCO2e, when the heat load is 50 km away from the air storage site). A green-field simulation finds that reducing the capital cost of BES - even drastically below current levels - does not substantially impact the cost of low-carbon electricity. At a 70% reduction in the GHG emissions intensity of the grid, gas turbines remain three times more cost-efficient in managing the wind variability compared to BES (in the best case and with a 15-minute resolution). Wind and solar thus, do not need to wait for availability of cheap BES systems to cost-effectively decarbonize the grid. The prospects of A-CAES seem to be stronger compared to other BES systems due to its low energy-specific capital cost.

California's Snow Gun and its implications for mass balance predictions under greenhouse warming

NASA Astrophysics Data System (ADS)

Howat, I.; Snyder, M.; Tulaczyk, S.; Sloan, L.

2003-12-01

Precipitation has received limited treatment in glacier and snowpack mass balance models, largely due to the poor resolution and confidence of precipitation predictions relative to temperature predictions derived from atmospheric models. Most snow and glacier mass balance models rely on statistical or lapse rate-based downscaling of general or regional circulation models (GCM's and RCM's), essentially decoupling sub-grid scale, orographically-driven evolution of atmospheric heat and moisture. Such models invariably predict large losses in the snow and ice volume under greenhouse warming. However, positive trends in the mass balance of glaciers in some warming maritime climates, as well as at high elevations of the Greenland Ice Sheet, suggest that increased precipitation may play an important role in snow- and glacier-climate interactions. Here, we present a half century of April snowpack data from the Sierra Nevada and Cascade mountains of California, USA. This high-density network of snow-course data indicates that a gain in winter snow accumulation at higher elevations has compensated loss in snow volume at lower elevations by over 50% and has led to glacier expansion on Mt. Shasta. These trends are concurrent with a region-wide increase in winter temperatures up to 2° C. They result from the orographic lifting and saturation of warmer, more humid air leading to increased precipitation at higher elevations. Previous studies have invoked such a "Snow Gun" effect to explain contemporaneous records of Tertiary ocean warming and rapid glacial expansion. A climatological context of the California's "snow gun" effect is elucidated by correlation between the elevation distribution of April SWE observations and the phase of the Pacific Decadal Oscillation and the El Nino Southern Oscillation, both controlling the heat and moisture delivered to the U.S. Pacific coast. The existence of a significant "Snow Gun" effect presents two challenges to snow and glacier mass balance modeling. Firstly, the link between amplification of orographic precipitation and the temporal evolution of ocean-climate oscillations indicates that prediction of future mass balance trends requires consideration of the timing and amplitude of such oscillations. Only recently have ocean-atmosphere models begun to realistically produce such temporal variability. Secondly, the steepening snow mass-balance elevation-gradient associated with the "Snow Gun" implies greater spatial variability in balance with warming. In a warming climate, orographic processes at a scale finer that the highest resolution RCM (>20km grid) become increasingly important and predictions based on lower elevations become increasingly inaccurate for higher elevations. Therefore, thermodynamic interaction between atmospheric heat, moisture and topography must be included in downscaling techniques. In order to demonstrate the importance of the thermodynamic downscaling in mass balance predictions, we nest a high-resolution (100m grid), coupled Orographic Precipitation and Surface Energy balance Model (OPSEM) into the RegC2.5 RCM (40 km grid) and compare results. We apply this nesting technique to Mt. Shasta, California, an area of high topography (~4000m) relative to its RegCM2.5 grid elevation (1289m). These models compute average April snow volume under present and doubled-present Atmospheric CO2 concentrations. While the RegCM2.5 regional model predicts an 83% decrease in April SWE, OPSEM predicts a 16% increase. These results indicate that thermodynamic interactions between the atmosphere and topography at sub- RCM grid resolution must be considered in mass balance models.

An Experimental High-Resolution Forecast System During the Vancouver 2010 Winter Olympic and Paralympic Games

NASA Astrophysics Data System (ADS)

Mailhot, J.; Milbrandt, J. A.; Giguère, A.; McTaggart-Cowan, R.; Erfani, A.; Denis, B.; Glazer, A.; Vallée, M.

2014-01-01

Environment Canada ran an experimental numerical weather prediction (NWP) system during the Vancouver 2010 Winter Olympic and Paralympic Games, consisting of nested high-resolution (down to 1-km horizontal grid-spacing) configurations of the GEM-LAM model, with improved geophysical fields, cloud microphysics and radiative transfer schemes, and several new diagnostic products such as density of falling snow, visibility, and peak wind gust strength. The performance of this experimental NWP system has been evaluated in these winter conditions over complex terrain using the enhanced mesoscale observing network in place during the Olympics. As compared to the forecasts from the operational regional 15-km GEM model, objective verification generally indicated significant added value of the higher-resolution models for near-surface meteorological variables (wind speed, air temperature, and dewpoint temperature) with the 1-km model providing the best forecast accuracy. Appreciable errors were noted in all models for the forecasts of wind direction and humidity near the surface. Subjective assessment of several cases also indicated that the experimental Olympic system was skillful at forecasting meteorological phenomena at high-resolution, both spatially and temporally, and provided enhanced guidance to the Olympic forecasters in terms of better timing of precipitation phase change, squall line passage, wind flow channeling, and visibility reduction due to fog and snow.

Evaluation of the National Solar Radiation Database (NSRDB) Using Ground-Based Measurements

NASA Astrophysics Data System (ADS)

Xie, Y.; Sengupta, M.; Habte, A.; Lopez, A.

2017-12-01

Solar resource is essential for a wide spectrum of applications including renewable energy, climate studies, and solar forecasting. Solar resource information can be obtained from ground-based measurement stations and/or from modeled data sets. While measurements provide data for the development and validation of solar resource models and other applications modeled data expands the ability to address the needs for increased accuracy and spatial and temporal resolution. The National Renewable Energy Laboratory (NREL) has developed and regular updates modeled solar resource through the National Solar Radiation Database (NSRDB). The recent NSRDB dataset was developed using the physics-based Physical Solar Model (PSM) and provides gridded solar irradiance (global horizontal irradiance (GHI), direct normal irradiance (DNI), and diffuse horizontal irradiance) at a 4-km by 4-km spatial and half-hourly temporal resolution covering 18 years from 1998-2015. A comprehensive validation of the performance of the NSRDB (1998-2015) was conducted to quantify the accuracy of the spatial and temporal variability of the solar radiation data. Further, the study assessed the ability of NSRDB (1998-2015) to accurately capture inter-annual variability, which is essential information for solar energy conversion projects and grid integration studies. Comparisons of the NSRDB (1998-2015) with nine selected ground-measured data were conducted under both clear- and cloudy-sky conditions. These locations provide a high quality data covering a variety of geographical locations and climates. The comparison of the NSRDB to the ground-based data demonstrated that biases were within +/- 5% for GHI and +/-10% for DNI. A comprehensive uncertainty estimation methodology was established to analyze the performance of the gridded NSRDB and includes all sources of uncertainty at various time-averaged periods, a method that is not often used in model evaluation. Further, the study analyzed the inter-annual and mean-anomaly of the 18 years of solar radiation data. This presentation will outline the validation methodology and provide detailed results of the comparison.

78 FR 67327 - Approval and Promulgation of Air Quality Implementation Plans; State of Colorado; Revised...

Federal Register 2010, 2011, 2012, 2013, 2014

2013-11-12

... shall include procedures for interagency consultation, conflict resolution, and public consultation... Determinations by the public, Air Quality Control Commission, and resolution of conflicts''. (2) 40 CFR 93.122(a... of 93.105(d) require specific procedures for resolving conflicts, and the provisions of 93.105(e...

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...

Optimal Design of Air Quality Monitoring Network and its Application in an Oil Refinery Plant: An Approach to Keep Health Status of Workers.

PubMed

ZoroufchiBenis, Khaled; Fatehifar, Esmaeil; Ahmadi, Javad; Rouhi, Alireza

2015-01-01

Industrial air pollution is a growing challenge to humane health, especially in developing countries, where there is no systematic monitoring of air pollution. Given the importance of the availability of valid information on population exposure to air pollutants, it is important to design an optimal Air Quality Monitoring Network (AQMN) for assessing population exposure to air pollution and predicting the magnitude of the health risks to the population. A multi-pollutant method (implemented as a MATLAB program) was explored for configur-ing an AQMN to detect the highest level of pollution around an oil refinery plant. The method ranks potential monitoring sites (grids) according to their ability to represent the ambient concentration. The term of cluster of contiguous grids that exceed a threshold value was used to calculate the Station Dosage. Selection of the best configuration of AQMN was done based on the ratio of a sta-tion's dosage to the total dosage in the network. Six monitoring stations were needed to detect the pollutants concentrations around the study area for estimating the level and distribution of exposure in the population with total network efficiency of about 99%. An analysis of the design procedure showed that wind regimes have greatest effect on the location of monitoring stations. The optimal AQMN enables authorities to implement an effective program of air quality management for protecting human health.

Optimal Design of Air Quality Monitoring Network and its Application in an Oil Refinery Plant: An Approach to Keep Health Status of Workers

PubMed Central

ZoroufchiBenis, Khaled; Fatehifar, Esmaeil; Ahmadi, Javad; Rouhi, Alireza

2015-01-01

Background: Industrial air pollution is a growing challenge to humane health, especially in developing countries, where there is no systematic monitoring of air pollution. Given the importance of the availability of valid information on population exposure to air pollutants, it is important to design an optimal Air Quality Monitoring Network (AQMN) for assessing population exposure to air pollution and predicting the magnitude of the health risks to the population. Methods: A multi-pollutant method (implemented as a MATLAB program) was explored for configur­ing an AQMN to detect the highest level of pollution around an oil refinery plant. The method ranks potential monitoring sites (grids) according to their ability to represent the ambient concentration. The term of cluster of contiguous grids that exceed a threshold value was used to calculate the Station Dosage. Selection of the best configuration of AQMN was done based on the ratio of a sta­tion’s dosage to the total dosage in the network. Results: Six monitoring stations were needed to detect the pollutants concentrations around the study area for estimating the level and distribution of exposure in the population with total network efficiency of about 99%. An analysis of the design procedure showed that wind regimes have greatest effect on the location of monitoring stations. Conclusion: The optimal AQMN enables authorities to implement an effective program of air quality management for protecting human health. PMID:26933646

Utilizing NASA DISCOVER-AQ Data to Examine Spatial Gradients in Complex Emission Environments

NASA Astrophysics Data System (ADS)

Buzanowicz, M. E.; Moore, W.; Crawford, J. H.; Schroeder, J.

2017-12-01

Although many regulations have been enacted with the goal of improving air quality, many parts of the US are still classified as `non-attainment areas' because they frequently violate federal air quality standards. Adequately monitoring the spatial distribution of pollutants both within and outside of non-attainment areas has been an ongoing challenge for regulators. Observations of near-surface pollution from space-based platforms would provide an unprecedented view of the spatial distribution of pollution, but this goal has not yet been realized due to fundamental limitations of satellites, specifically because the footprint size of satellite measurements may not be sufficiently small enough to capture true gradients in pollution, and rather represents an average over a large area. NASA's DISCOVER-AQ was a multi-year field campaign aimed at improving our understanding of the role that remote sensing, including satellite-based remote sensing, could play in air quality monitoring systems. DISCOVER-AQ data will be utilized to create a metric to examine spatial gradients and how satellites can capture those gradients in areas with complex emission environments. Examining horizontal variability within a vertical column is critical to understanding mixing within the atmosphere. Aircraft spirals conducted during DISCOVER-AQ were divided into octants, and averages of a given a species were calculated, with certain points receiving a flag. These flags were determined by calculating gradients between subsequent octants. Initial calculations have shown that over areas with large point source emissions, such as Platteville and Denver-La Casa in Colorado, and Essex, Maryland, satellite retrievals may not adequately capture spatial variability in the atmosphere, thus complicating satellite inversion techniques and limiting our ability to understand human exposure on sub-grid scales. Further calculations at other locations and for other trace gases are necessary to determine the effects of vertical variability within the atmosphere.

Ensuring Safety of Navigation: A Three-Tiered Approach

NASA Astrophysics Data System (ADS)

Johnson, S. D.; Thompson, M.; Brazier, D.

2014-12-01

The primary responsibility of the Hydrographic Department at the Naval Oceanographic Office (NAVOCEANO) is to support US Navy surface and sub-surface Safety of Navigation (SoN) requirements. These requirements are interpreted, surveys are conducted, and accurate products are compiled and archived for future exploitation. For a number of years NAVOCEANO has employed a two-tiered data-basing structure to support SoN. The first tier (Data Warehouse, or DWH) provides access to the full-resolution sonar and lidar data. DWH preserves the original data such that any scale product can be built. The second tier (Digital Bathymetric Database - Variable resolution, or DBDB-V) served as the final archive for SoN chart scale, gridded products compiled from source bathymetry. DBDB-V has been incorporated into numerous DoD tactical decision aids and serves as the foundation bathymetry for ocean modeling. With the evolution of higher density survey systems and the addition of high-resolution gridded bathymetry product requirements, a two-tiered model did not provide an efficient solution for SoN. The two-tiered approach required scientists to exploit full-resolution data in order to build any higher resolution product. A new perspective on the archival and exploitation of source data was required. This new perspective has taken the form of a third tier, the Navigation Surface Database (NSDB). NSDB is an SQLite relational database populated with International Hydrographic Organization (IHO), S-102 compliant Bathymetric Attributed Grids (BAGs). BAGs archived within NSDB are developed at the highest resolution that the collection sensor system can support and contain nodal estimates for depth, uncertainty, separation values and metadata. Gridded surface analysis efforts culminate in the generation of the source resolution BAG files and their storage within NSDB. Exploitation of these resources eliminates the time and effort needed to re-grid and re-analyze native source file formats.

AIRS Version 6 Products and Data Services at NASA GES DISC

NASA Astrophysics Data System (ADS)

Ding, F.; Savtchenko, A. K.; Hearty, T. J.; Theobald, M. L.; Vollmer, B.; Esfandiari, E.

2013-12-01

The NASA Goddard Earth Sciences Data and Information Services Center (GES DISC) is the home of processing, archiving, and distribution services for data from the Atmospheric Infrared Sounder (AIRS) mission. The AIRS mission is entering its 11th year of global observations of the atmospheric state, including temperature and humidity profiles, outgoing longwave radiation, cloud properties, and trace gases. The GES DISC, in collaboration with the AIRS Project, released data from the Version 6 algorithm in early 2013. The new algorithm represents a significant improvement over previous versions in terms of greater stability, yield, and quality of products. Among the most substantial advances are: improved soundings of Tropospheric and Sea Surface Temperatures; larger improvements with increasing cloud cover; improved retrievals of surface spectral emissivity; near-complete removal of spurious temperature bias trends seen in earlier versions; substantially improved retrieval yield (i.e., number of soundings accepted for output) for climate studies; AIRS-Only retrievals with comparable accuracy to AIRS+AMSU (Advanced Microwave Sounding Unit) retrievals; and more realistic hemispheric seasonal variability and global distribution of carbon monoxide. The GES DISC is working to bring the distribution services up-to-date with these new developments. Our focus is on popular services, like variable subsetting and quality screening, which are impacted by the new elements in Version 6. Other developments in visualization services, such as Giovanni, Near-Real Time imagery, and a granule-map viewer, are progressing along with the introduction of the new data; each service presents its own challenge. This presentation will demonstrate the most significant improvements in Version 6 AIRS products, such as newly added variables (higher resolution outgoing longwave radiation, new cloud property products, etc.), the new quality control schema, and improved retrieval yields. We will also demonstrate the various distribution and visualization services for AIRS data products. The cloud properties, model physics, and water and energy cycles research communities are invited to take advantage of the improvements in Version 6 AIRS products and the various services at GES DISC which provide them.

PAH concentrations simulated with the AURAMS-PAH chemical transport model over Canada and the USA

NASA Astrophysics Data System (ADS)

Galarneau, E.; Makar, P. A.; Zheng, Q.; Narayan, J.; Zhang, J.; Moran, M. D.; Bari, M. A.; Pathela, S.; Chen, A.; Chlumsky, R.

2014-04-01

The offline Eulerian AURAMS (A Unified Regional Air quality Modelling System) chemical transport model was adapted to simulate airborne concentrations of seven PAHs (polycyclic aromatic hydrocarbons): phenanthrene, anthracene, fluoranthene, pyrene, benz[a]anthracene, chrysene + triphenylene, and benzo[a]pyrene. The model was then run for the year 2002 with hourly output on a grid covering southern Canada and the continental USA with 42 km horizontal grid spacing. Model predictions were compared to ~5000 24 h-average PAH measurements from 45 sites, most of which were located in urban or industrial areas. Eight of the measurement sites also provided data on particle/gas partitioning which had been modelled using two alternative schemes. This is the first known regional modelling study for PAHs over a North American domain and the first modelling study at any scale to compare alternative particle/gas partitioning schemes against paired field measurements. The goal of the study was to provide output concentration maps of use to assessing human inhalation exposure to PAHs in ambient air. Annual average modelled total (gas + particle) concentrations were statistically indistinguishable from measured values for fluoranthene, pyrene and benz[a]anthracene whereas the model underestimated concentrations of phenanthrene, anthracene and chrysene + triphenylene. Significance for benzo[a]pyrene performance was close to the statistical threshold and depended on the particle/gas partitioning scheme employed. On a day-to-day basis, the model simulated total PAH concentrations to the correct order of magnitude the majority of the time. The model showed seasonal differences in prediction quality for volatile species which suggests that a missing emission source such as air-surface exchange should be included in future versions. Model performance differed substantially between measurement locations and the limited available evidence suggests that the model's spatial resolution was too coarse to capture the distribution of concentrations in densely populated areas. A more detailed analysis of the factors influencing modelled particle/gas partitioning is warranted based on the findings in this study.

Tabulations of ambient ozone data obtained by GASP (Global Air Sampling Program) airliners, March 1975 to July 1979

NASA Technical Reports Server (NTRS)

Jasperson, W. H.; Holdeman, J. D.

1984-01-01

Tabulations are given of GASP ambient ozone mean, standard deviation, median, 84th percentile, and 98th percentile values, by month, flight level, and geographical region. These data are tabulated to conform to the temporal and spatial resolution required by FAA Advisory Circular 120-38 (monthly by 2000 ft in altitude by 5 deg in latitude) for climatological data used to show compliance with cabin ozone regulations. In addition seasonal x 10 deg latitude tabulations are included which are directly comparable to and supersede the interim GASP ambient ozone tabulations given in appendix B of FAA-EE-80-43 (NASA TM-81528). Selected probability variations are highlighted to illustrate the spatial and temporal variability of ambient ozone and to compare results from the coarse and fine grid analyses.

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...

Impact of High Resolution Land-Use Data in Meteorology and Air Quality Modeling Systems

EPA Science Inventory

Accurate land use information is important in meteorology for land surface exchanges, in emission modeling for emission spatial allocation, and in air quality modeling for chemical surface fluxes. Currently, meteorology, emission, and air quality models often use outdated USGS Gl...

Evaluation of Urban Air Quality By Passive Sampling Technique

NASA Astrophysics Data System (ADS)

Nunes, T. V.; Miranda, A. I.; Duarte, S.; Lima, M. J.

Aveiro is a flat small city in the centre of Portugal, close to the Atlantic coast. In the last two decades an intensive development of demographic, traffic and industry growth in the region was observed which was reflected on the air quality degrada- tion. In order to evaluate the urban air quality in Aveiro, a field-monitoring network by passive sampling with high space resolution was implemented. Twenty-four field places were distributed in a area of 3x3 Km2 and ozone and NO2 concentrations were measured. The site distribution density was higher in the centre, 250x250 m2 than in periphery where a 500x500 m2 grid was used. The selection of field places took into consideration the choice criteria recommendation by United Kingdom environmental authorities, and three tubes and a blank tube for each pollutant were used at each site. The sampling system was mounted at 3m from the ground usually profiting the street lampposts. Concerning NO2 acrylic tubes were used with 85 mm of length and an in- ternal diameter of 12mm, where in one of the extremities three steel grids impregnated with a solution of TEA were placed and fixed with a polyethylene end cup (Heal et al., 1999); PFA Teflon tube with 53 mm of length and 9 mm of internal diameter and three impregnated glass filters impregnated with DPE solution fixed by a teflon end cup was used for ozone sampling (Monn and Hargartner, 1990). The passive sampling method for ozone and nitrogen dioxide was compared with continuous measurements, but the amount of measurements wasnSt enough for an accurate calibration and validation of the method. Although this constraint the field observations (June to August 2001) for these two pollutants assign interesting information about the air quality in the urban area. A krigger method of interpolation (Surfer- Golden Software-2000) was applied to field data to obtain isolines distribution of NO2 and ozone concentration for the studied area. Even the used passive sampling method has many limitations it is possi- ble to say that the NO2 concentrations were strictly related with traffic intensity and in the centre 3 to 10 times higher values were observed than the incoming air to the city; on the contrary the ozone seems to be consumed where we observe the highest NO2 concentrations. Heal, M. R.; O'Donoghue, M. A. and Cape, J. N., Overestimation of Urban Nitrogen Dioxide by Passive Sampling Tubes: a comparative exposure and model study, Atmo- spheric Environment, Vol 33, pp 513-524, 1999 Monn, Ch., Hangartner, M., Passive Sampling for Ozone, J. of Air and Waste Management Association, Vol. 40, Nz 3, 1990

Scalability of grid- and subbasin-based land surface modeling approaches for hydrologic simulations

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

Tesfa, Teklu K.; Ruby Leung, L.; Huang, Maoyi

2014-03-27

This paper investigates the relative merits of grid- and subbasin-based land surface modeling approaches for hydrologic simulations, with a focus on their scalability (i.e., abilities to perform consistently across a range of spatial resolutions) in simulating runoff generation. Simulations produced by the grid- and subbasin-based configurations of the Community Land Model (CLM) are compared at four spatial resolutions (0.125o, 0.25o, 0.5o and 1o) over the topographically diverse region of the U.S. Pacific Northwest. Using the 0.125o resolution simulation as the “reference”, statistical skill metrics are calculated and compared across simulations at 0.25o, 0.5o and 1o spatial resolutions of each modelingmore » approach at basin and topographic region levels. Results suggest significant scalability advantage for the subbasin-based approach compared to the grid-based approach for runoff generation. Basin level annual average relative errors of surface runoff at 0.25o, 0.5o, and 1o compared to 0.125o are 3%, 4%, and 6% for the subbasin-based configuration and 4%, 7%, and 11% for the grid-based configuration, respectively. The scalability advantages of the subbasin-based approach are more pronounced during winter/spring and over mountainous regions. The source of runoff scalability is found to be related to the scalability of major meteorological and land surface parameters of runoff generation. More specifically, the subbasin-based approach is more consistent across spatial scales than the grid-based approach in snowfall/rainfall partitioning, which is related to air temperature and surface elevation. Scalability of a topographic parameter used in the runoff parameterization also contributes to improved scalability of the rain driven saturated surface runoff component, particularly during winter. Hence this study demonstrates the importance of spatial structure for multi-scale modeling of hydrological processes, with implications to surface heat fluxes in coupled land-atmosphere modeling.« less

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

EPA Pesticide Factsheets

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

Using NASA Remotely Sensed Data to Help Characterize Environmental Risk Factors for National Public Health Applications

NASA Technical Reports Server (NTRS)

Al-Hamdan, Mohammad; Crosson, William; Economou, Sigrid; Estes, Maurice, Jr.; Estes, Sue; Hemmings, Sarah; Kent, Shia; Quattrochi, Dale; Wade, Gina; McClure, Leslie

2011-01-01

NASA Marshall Space Flight Center is collaborating with the University of Alabama at Birmingham (UAB) School of Public Health and the Centers for Disease Control and Prevention (CDC) National Center for Public Health Informatics to address issues of environmental health and enhance public health decision making by utilizing NASA remotely sensed data and products. The objectives of this study are to develop high-quality spatial data sets of environmental variables, link these with public health data from a national cohort study, and deliver the linked data sets and associated analyses to local, state and federal end-user groups. Three daily environmental data sets will be developed for the conterminous U.S. on different spatial resolutions for the period 2003-2008: (1) spatial surfaces of estimated fine particulate matter (PM2.5) exposures on a 10-km grid utilizing the US Environmental Protection Agency (EPA) ground observations and NASA's MODerate-resolution Imaging Spectroradiometer (MODIS) data; (2) a 1-km grid of Land Surface Temperature (LST) using MODIS data; and (3) a 12-km grid of daily Solar Insolation (SI) using the North American Land Data Assimilation System (NLDAS) forcing data. These environmental data sets will be linked with public health data from the UAB REasons for Geographic And Racial Differences in Stroke (REGARDS) national cohort study to determine whether exposures to these environmental risk factors are related to cognitive decline and other health outcomes. These environmental datasets and public health linkage analyses will be disseminated to end-users for decision making through the CDC Wide-ranging Online Data for Epidemiologic Research (WONDER) system.

Increased tree-ring network density reveals more precise estimations of sub-regional hydroclimate variability and climate dynamics in the Midwest, USA

NASA Astrophysics Data System (ADS)

Maxwell, Justin T.; Harley, Grant L.

2017-08-01

Understanding the historic variability in the hydroclimate provides important information on possible extreme dry or wet periods that in turn inform water management plans. Tree rings have long provided historical context of hydroclimate variability of the U.S. However, the tree-ring network used to create these countrywide gridded reconstructions is sparse in certain locations, such as the Midwest. Here, we increase ( n = 20) the spatial resolution of the tree-ring network in southern Indiana and compare a summer (June-August) Palmer Drought Severity Index (PDSI) reconstruction to existing gridded reconstructions of PDSI for this region. We find both droughts and pluvials that were previously unknown that rival the most intense PDSI values during the instrumental period. Additionally, historical drought occurred in Indiana that eclipsed instrumental conditions with regard to severity and duration. During the period 1962-2004 CE, we find that teleconnections of drought conditions through the Atlantic Meridional Overturning Circulation have a strong influence ( r = -0.60, p < 0.01) on secondary tree growth in this region for the late spring-early summer season. These findings highlight the importance of continuing to increase the spatial resolution of the tree-ring network used to infer past climate dynamics to capture the sub-regional spatial variability. Increasing the spatial resolution of the tree-ring network for a given region can better identify sub-regional variability, improve the accuracy of regional tree-ring PDSI reconstructions, and provide better information for climatic teleconnections.

High-resolution two-dimensional and three-dimensional modeling of wire grid polarizers and micropolarizer arrays

NASA Astrophysics Data System (ADS)

Vorobiev, Dmitry; Ninkov, Zoran

2017-11-01

Recent advances in photolithography allowed the fabrication of high-quality wire grid polarizers for the visible and near-infrared regimes. In turn, micropolarizer arrays (MPAs) based on wire grid polarizers have been developed and used to construct compact, versatile imaging polarimeters. However, the contrast and throughput of these polarimeters are significantly worse than one might expect based on the performance of large area wire grid polarizers or MPAs, alone. We investigate the parameters that affect the performance of wire grid polarizers and MPAs, using high-resolution two-dimensional and three-dimensional (3-D) finite-difference time-domain simulations. We pay special attention to numerical errors and other challenges that arise in models of these and other subwavelength optical devices. Our tests show that simulations of these structures in the visible and near-IR begin to converge numerically when the mesh size is smaller than ˜4 nm. The performance of wire grid polarizers is very sensitive to the shape, spacing, and conductivity of the metal wires. Using 3-D simulations of micropolarizer "superpixels," we directly study the cross talk due to diffraction at the edges of each micropolarizer, which decreases the contrast of MPAs to ˜200∶1.

Improving Technology for Vascular Imaging

NASA Astrophysics Data System (ADS)

Rana, Raman

Neuro-endovascular image guided interventions (Neuro-EIGIs) is a minimally invasive procedure that require micro catheters and endovascular devices be inserted into the vasculature via an incision near the femoral artery and guided under low dose fluoroscopy to the vasculature of the head and neck. However, the endovascular devices used for the purpose are of very small size (stents are of the order of 50mum to 100mum) and the success of these EIGIs depends a lot on the accurate placement of these devices. In order to accurately place these devices inside the patient, the interventionalist should be able to see them clearly. Hence, high resolution capabilities are of immense importance in neuro-EIGIs. The high-resolution detectors, MAF-CCD and MAF-CMOS, at the Toshiba Stroke and Vascular Research Center at the University at Buffalo are capable of presenting improved images for better patient care. Focal spot of an x-ray tube plays an important role in performance of these high resolution detectors. The finite size of the focal spot results into the blurriness around the edges of the image of the object resulting in reduced spatial resolution. Hence, knowledge of accurate size of the focal spot of the x-ray tube is very essential for the evaluation of the total system performance. Importance of magnification and image detector blur deconvolution was demonstrated to carry out the more accurate measurement of x-ray focal spot using a pinhole camera. A 30 micron pinhole was used to obtain the focal spot images using flat panel detector (FPD) and different source to image distances (SIDs) were used to achieve different magnifications (3.16, 2.66 and 2.16). These focal spot images were deconvolved with a 2-D modulation transfer function (MTF), obtained using noise response (NR) method, to remove the detector blur present in the images. Using these corrected images, the accurate size of all the three focal spots were obtained and it was also established that effect of detector blur can be reduced significantly by using a higher magnification. As discussed earlier, interventionalist need higher resolution capabilities during EIGIs for more confident and successful treatment of the patient. An experimental MAF-CCD enabled with a Control, Acquisition, Processing, Image Display and Storage (CAPIDS) system was installed and aligned on a detector changer attached to the C-arm of a clinical angiographic unit. The CAPIDS system was developed and implemented using LabVIEW software and provides a user-friendly interface that enables control of several clinical radiographic imaging modes of the MAF including: fluoroscopy, roadmap, radiography, and digital-subtraction-angiography (DSA). Whenever the higher resolution is needed, the MAD-CCD detector can be moved in front of the FPD. A particular set of steps were needed to deploy the MAF in front of the FPD and to transfer the controls to CAPIDS from the Toshiba Systems. In order to minimize any possible negative impact of using two different detectors during a procedure, a well-designed workflow was developed that enables smooth deployment of the MAF at critical stages of clinical procedures. The images obtained using MAF-CCD detector demonstrated the advantages the high resolution imagers have over FPDs. Scatter is inevitable in x-ray imaging as it reduces the image quality. The benefit of removing the scatter is that it improves contrast and also increases the signal-to-Noise (SNR). There are various scatter reduction methods like air-gap techniques, collimation, moving anti-scatter grids, stationary anti-scatter grids. Stationary anti-scatter grids is a preferred choice in dynamic imaging because of its compact design and ease to use. However, when these anti-scatter grids are used with high resolution detector, there will be anti-scatter grid-line pattern present in the image, as structure noise. Because of presence of this anti-scatter grid artifact, the contrast-to-Noise (CNR) of the image decreases when grid is used with high resolution detector. In order to address this issue, grid-line artifact minimization method for high resolution detectors is developed. (Abstract shortened by ProQuest.).

Variable-Resolution Ensemble Climatology Modeling of Sierra Nevada Snowpack within the Community Earth System Model (CESM)

NASA Astrophysics Data System (ADS)

Rhoades, A.; Ullrich, P. A.; Zarzycki, C. M.; Levy, M.; Taylor, M.

2014-12-01

Snowpack is crucial for the western USA, providing around 75% of the total fresh water supply (Cayan et al., 1996) and buffering against seasonal aridity impacts on agricultural, ecosystem, and urban water demands. The resilience of the California water system is largely dependent on natural stores provided by snowpack. This resilience has shown vulnerabilities due to anthropogenic global climate change. Historically, the northern Sierras showed a net decline of 50-75% in snow water equivalent (SWE) while the southern Sierras showed a net accumulation of 30% (Mote et al., 2005). Future trends of SWE highlight that western USA SWE may decline by 40-70% (Pierce and Cayan, 2013), snowfall may decrease by 25-40% (Pierce and Cayan, 2013), and more winter storms may tend towards rain rather than snow (Bales et al., 2006). The volatility of Sierran snowpack presents a need for scientific tools to help water managers and policy makers assess current and future trends. A burgeoning tool to analyze these trends comes in the form of variable-resolution global climate modeling (VRGCM). VRGCMs serve as a bridge between regional and global models and provide added resolution in areas of need, eliminate lateral boundary forcings, provide model runtime speed up, and utilize a common dynamical core, physics scheme and sub-grid scale parameterization package. A cubed-sphere variable-resolution grid with 25 km horizontal resolution over the western USA was developed for use in the Community Atmosphere Model (CAM) within the Community Earth System Model (CESM). A 25-year three-member ensemble climatology (1980-2005) is presented and major snowpack metrics such as SWE, snow depth, snow cover, and two-meter surface temperature are assessed. The ensemble simulation is also compared to observational, reanalysis, and WRF model datasets. The variable-resolution model provides a mechanism for reaching towards non-hydrostatic scales and simulations are currently being developed with refined nests of 12.5km resolution over California.

Calibrated, Enhanced-Resolution Brightness Temperature Earth System Data Record: A New Era for Gridded Passive Microwave Data

NASA Astrophysics Data System (ADS)

Hardman, M.; Brodzik, M. J.; Long, D. G.

2017-12-01

Since 1978, the satellite passive microwave data record has been a mainstay of remote sensing of the cryosphere, providing twice-daily, near-global spatial coverage for monitoring changes in hydrologic and cryospheric parameters that include precipitation, soil moisture, surface water, vegetation, snow water equivalent, sea ice concentration and sea ice motion. Up until recently, the available global gridded passive microwave data sets have not been produced consistently. Various projections (equal-area, polar stereographic), a number of different gridding techniques were used, along with various temporal sampling as well as a mix of Level 2 source data versions. In addition, not all data from all sensors have been processed completely and they have not been processed in any one consistent way. Furthermore, the original gridding techniques were relatively primitive and were produced on 25 km grids using the original EASE-Grid definition that is not easily accommodated in modern software packages. As part of NASA MEaSUREs, we have re-processed all data from SMMR, all SSM/I-SSMIS and AMSR-E instruments, using the most mature Level 2 data. The Calibrated, Enhanced-Resolution Brightness Temperature (CETB) Earth System Data Record (ESDR) gridded data are now available from the NSIDC DAAC. The data are distributed as netCDF files that comply with CF-1.6 and ACDD-1.3 conventions. The data have been produced on EASE 2.0 projections at smoothed, 25 kilometer resolution and spatially-enhanced resolutions, up to 3.125 km depending on channel frequency, using the radiometer version of the Scatterometer Image Reconstruction (rSIR) method. We expect this newly produced data set to enable scientists to better analyze trends in coastal regions, marginal ice zones and in mountainous terrain that were not possible with the previous gridded passive microwave data. The use of the EASE-Grid 2.0 definition and netCDF-CF formatting allows users to extract compliant geotiff images and provides for easy importing and correct reprojection interoperability in many standard packages. As a consistently-processed, high-quality satellite passive microwave ESDR, we expect this data set to replace earlier gridded passive microwave data sets, and to pave the way for new insights from higher-resolution derived geophysical products.

A Comparison of Statistical Techniques for Combining Modeled and Observed Concentrations to Create High-Resolution Ozone Air Quality Surfaces

EPA Science Inventory

Air quality surfaces representing pollutant concentrations across space and time are needed for many applications, including tracking trends and relating air quality to human and ecosystem health. The spatial and temporal characteristics of these surfaces may reveal new informat...

Quantifying public health benefits of environmental strategy of PM2.5 air quality management in Beijing-Tianjin-Hebei region, China.

PubMed

Chen, Li; Shi, Mengshuang; Li, Suhuan; Gao, Shuang; Zhang, Hui; Sun, Yanling; Mao, Jian; Bai, Zhipeng; Wang, Zhongliang; Zhou, Jiang

2017-07-01

In 2013, China issued "Air Pollution Prevention and Control Action Plan (Action Plan)" to improve air quality. To assess the benefits of this program in Beijing-Tianjin-Hebei (BTH) region, where the density of population and emissions vary greatly, we simulated the air quality benefit based on BenMAP to satisfy the Action Plan. In this study, we estimate PM 2.5 concentration using Voronoi spatial interpolation method on a grid with a spatial resolution of 1×1km 2 . Combined with the exposure-response function between PM 2.5 concentration and health endpoints, health effects of PM 2.5 exposure are analyzed. The economic loss is assessed by using the willingness to pay (WTP) method and human capital (HC) method. When the PM 2.5 concentration falls by 25% in BTH and reached 60μg/m 3 in Beijing, the avoiding deaths will be in the range of 3175 to 14051 based on different functions each year. Of the estimated mortality attributable to all causes, 3117 annual deaths were due to lung cancer, 1924 - 6318 annual deaths were due to cardiovascular, and 343 - 1697 annual deaths were due to respiratory. Based on WTP, the estimated monetary values for the avoided cases of all cause mortality, cardiovascular mortality, respiratory mortality and lung cancer ranged from 1110 to 29632, 673 to 13325, 120 to 3579, 1091 to 6574 million yuan, respectively. Based on HC, the corresponding values for the avoided cases of these four mortalities were 267 to 1178, 161 to 529, 29 to 143 and 261 million yuan, respectively. Copyright © 2016. Published by Elsevier B.V.

Evaluation of Observation-Fused Regional Air Quality Model Results for Population Air Pollution Exposure Estimation

PubMed Central

Chen, Gang; Li, Jingyi; Ying, Qi; Sherman, Seth; Perkins, Neil; Rajeshwari, Sundaram; Mendola, Pauline

2014-01-01

In this study, Community Multiscale Air Quality (CMAQ) model was applied to predict ambient gaseous and particulate concentrations during 2001 to 2010 in 15 hospital referral regions (HRRs) using a 36-km horizontal resolution domain. An inverse distance weighting based method was applied to produce exposure estimates based on observation-fused regional pollutant concentration fields using the differences between observations and predictions at grid cells where air quality monitors were located. Although the raw CMAQ model is capable of producing satisfying results for O3 and PM2.5 based on EPA guidelines, using the observation data fusing technique to correct CMAQ predictions leads to significant improvement of model performance for all gaseous and particulate pollutants. Regional average concentrations were calculated using five different methods: 1) inverse distance weighting of observation data alone, 2) raw CMAQ results, 3) observation-fused CMAQ results, 4) population-averaged raw CMAQ results and 5) population-averaged fused CMAQ results. It shows that while O3 (as well as NOx) monitoring networks in the HRR regions are dense enough to provide consistent regional average exposure estimation based on monitoring data alone, PM2.5 observation sites (as well as monitors for CO, SO2, PM10 and PM2.5 components) are usually sparse and the difference between the average concentrations estimated by the inverse distance interpolated observations, raw CMAQ and fused CMAQ results can be significantly different. Population-weighted average should be used to account spatial variation in pollutant concentration and population density. Using raw CMAQ results or observations alone might lead to significant biases in health outcome analyses. PMID:24747248

Intercomparison of Downscaling Methods on Hydrological Impact for Earth System Model of NE United States

NASA Astrophysics Data System (ADS)

Yang, P.; Fekete, B. M.; Rosenzweig, B.; Lengyel, F.; Vorosmarty, C. J.

2012-12-01

Atmospheric dynamics are essential inputs to Regional-scale Earth System Models (RESMs). Variables including surface air temperature, total precipitation, solar radiation, wind speed and humidity must be downscaled from coarse-resolution, global General Circulation Models (GCMs) to the high temporal and spatial resolution required for regional modeling. However, this downscaling procedure can be challenging due to the need to correct for bias from the GCM and to capture the spatiotemporal heterogeneity of the regional dynamics. In this study, the results obtained using several downscaling techniques and observational datasets were compared for a RESM of the Northeast Corridor of the United States. Previous efforts have enhanced GCM model outputs through bias correction using novel techniques. For example, the Climate Impact Research at Potsdam Institute developed a series of bias-corrected GCMs towards the next generation climate change scenarios (Schiermeier, 2012; Moss et al., 2010). Techniques to better represent the heterogeneity of climate variables have also been improved using statistical approaches (Maurer, 2008; Abatzoglou, 2011). For this study, four downscaling approaches to transform bias-corrected HADGEM2-ES Model output (daily at .5 x .5 degree) to the 3'*3'(longitude*latitude) daily and monthly resolution required for the Northeast RESM were compared: 1) Bilinear Interpolation, 2) Daily bias-corrected spatial downscaling (D-BCSD) with Gridded Meteorological Datasets (developed by Abazoglou 2011), 3) Monthly bias-corrected spatial disaggregation (M-BCSD) with CRU(Climate Research Unit) and 4) Dynamic Downscaling based on Weather Research and Forecast (WRF) model. Spatio-temporal analysis of the variability in precipitation was conducted over the study domain. Validation of the variables of different downscaling methods against observational datasets was carried out for assessment of the downscaled climate model outputs. The effects of using the different approaches to downscale atmospheric variables (specifically air temperature and precipitation) for use as inputs to the Water Balance Model (WBMPlus, Vorosmarty et al., 1998;Wisser et al., 2008) for simulation of daily discharge and monthly stream flow in the Northeast US for a 100-year period in the 21st century were also assessed. Statistical techniques especially monthly bias-corrected spatial disaggregation (M-BCSD) showed potential advantage among other methods for the daily discharge and monthly stream flow simulation. However, Dynamic Downscaling will provide important complements to the statistical approaches tested.

On the impact of the resolution on the surface and subsurface Eastern Tropical Atlantic warm bias

NASA Astrophysics Data System (ADS)

Martín-Rey, Marta; Lazar, Alban

2016-04-01

The tropical variability has a great importance for the climate of adjacent areas. Its sea surface temperature anomalies (SSTA) affect in particular the Brazilian Nordeste and the Sahelian region, as well as the tropical Pacific or the Euro-Atlantic sector. Nevertheless, the state-of the art climate models exhibits very large systematic errors in reproducing the seasonal cycle and inter-annual variability in the equatorial and coastal Africa upwelling zones (up to several °C for SST). Theses biases exist already, in smaller proportions though, in forced ocean models (several 1/10th of °C), and affect not only the mixed layer but also the whole thermocline. Here, we present an analysis of the impact of horizontal and vertical resolution changes on these biases. Three different DRAKKAR NEMO OGCM simulations have been analysed, associated to the same forcing set (DFS4.4) with different grid resolutions: "REF" for reference (1/4°, 46 vertical levels), "HH" with a finer horizontal grid (1/12°, 46 v.l.) and "HV" with a finer vertical grid (1/4°, 75 v.l.). At the surface, a more realistic seasonal SST cycle is produced in HH in the three upwellings, where the warm bias decreases (by 10% - 20%) during boreal spring and summer. A notable result is that increasing vertical resolution in HV causes a shift (in advance) of the upwelling SST seasonal cycles. In order to better understand these results, we estimate the three upwelling subsurface temperature errors, using various in-situ datasets, and provide thus a three-dimensional view of the biases.

Wetland inventory and variability over the last two decades at a global scale

NASA Astrophysics Data System (ADS)

Prigent, C.; Papa, F.; Aires, F.; Rossow, W. B.; Matthews, E.

2011-12-01

Remote sensing techniques employing visible, infrared, and microwave observations offer varying success in estimating wetlands and inundation extent and in monitoring their natural and anthropogenic variations. Low spatial resolution (e.g., 30 km) limits detection to large wetlands but has the advantage of frequent coverage. High spatial resolution (e.g., 100 m), while providing more environmental information, suffers from poor temporal resolution, with observations for just high/low water or warm/cold seasons. Most existing wetland data sets are limited to a few regions, for specific times in the year. The only global inventories of wetland dynamics over a long period of time is derived from a remote-sensing technique employing a suite of complementary satellite observations: it uses passive microwave land-surface microwave emissivities, scatterometer responses, and visible and near infrared reflectances. Combining observations from different instruments makes it possible to capitalize on their complementary strengths, and to extract maximum information about inundation characteristics. The technique is globally applicable without any tuning for particular environments. The satellite data are used to calculate monthly-mean inundated fractions of equal-area grid cells (0.25°x0.25° at the equator), taking into account the contribution of vegetation to the passive microwave signal (Prigent et al., 2001, 2007). Several adjustments to the initial technique have been applied to account for changes in satellite instruments (Papa et al., 2010). The resulting data set now covers 1993-2008 and has been carefully evaluated. We will present the inter-annual variability of the water surface extents under different environments, and relate these variations to other hydrological variables such as river height, precipitation, water runoff, or Grace data. Natural wetlands are the world's largest methane source and dominate the inter-annual variability of atmospheric methane concentrations, with up to 90% of the global methane flux anomalies related to variations in the wetland extent from some estimation. Our data set quantifying inundation dynamics throughout the world's natural wetlands provides a unique opportunity to reduce uncertainties in the role of natural wetlands in the inter-annual variability of the growth rate of atmospheric methane. Papa, F., C. Prigent, C. Jimenez, F. Aires, and W. B. Rossow, Interannual variability of surface water extent at global scale, 1993-2004, JGR, 115, D12111, doi:10.1029/2009JD012674, 2010. Prigent, C., F. Papa, F. Aires, W. B. Rossow, and E. Matthews, Global inundation dynamics inferred from multiple satellite observations, 1993-2000, JGR, 112, D12107, doi:10.1029/2006JD007847, 2007. Prigent, C., E. Matthews, F. Aires, and W. B. Rossow, Remote sensing of global wetland dynamics with multiple satellite data sets, GRL, 28 , 4631-4634, 2001.

Spatial interpolation of monthly mean air temperature data for Latvia

NASA Astrophysics Data System (ADS)

Aniskevich, Svetlana

2016-04-01

Temperature data with high spatial resolution are essential for appropriate and qualitative local characteristics analysis. Nowadays the surface observation station network in Latvia consists of 22 stations recording daily air temperature, thus in order to analyze very specific and local features in the spatial distribution of temperature values in the whole Latvia, a high quality spatial interpolation method is required. Until now inverse distance weighted interpolation was used for the interpolation of air temperature data at the meteorological and climatological service of the Latvian Environment, Geology and Meteorology Centre, and no additional topographical information was taken into account. This method made it almost impossible to reasonably assess the actual temperature gradient and distribution between the observation points. During this project a new interpolation method was applied and tested, considering auxiliary explanatory parameters. In order to spatially interpolate monthly mean temperature values, kriging with external drift was used over a grid of 1 km resolution, which contains parameters such as 5 km mean elevation, continentality, distance from the Gulf of Riga and the Baltic Sea, biggest lakes and rivers, population density. As the most appropriate of these parameters, based on a complex situation analysis, mean elevation and continentality was chosen. In order to validate interpolation results, several statistical indicators of the differences between predicted values and the values actually observed were used. Overall, the introduced model visually and statistically outperforms the previous interpolation method and provides a meteorologically reasonable result, taking into account factors that influence the spatial distribution of the monthly mean temperature.

Spatial Representativeness of PM2.5 Concentrations Obtained Using Observations From Network Stations

NASA Astrophysics Data System (ADS)

Shi, Xiaoqin; Zhao, Chuanfeng; Jiang, Jonathan H.; Wang, Chunying; Yang, Xin; Yung, Yuk L.

2018-03-01

Haze has been a focused air pollution phenomenon in China, and its characterization is highly desired. Aerosol properties obtained from a single station are frequently used to represent the haze condition over a large domain, such as tens of kilometers, which could result in high uncertainties due to their spatial variation. Using a high-resolution network observation over an urban city in North China from November 2015 to February 2016, this study examines the spatial representativeness of ground station observations of particulate matter with diameters less than 2.5 μm (PM2.5). We developed a new method to determine the representative area of PM2.5 measurements from limited stations. The key idea is to determine the PM2.5 spatial representative area using its spatial variability and temporal correlation. We also determine stations with large representative area using two grid networks with different resolutions. Based on the high spatial resolution measurements, the representative area of PM2.5 at one station can be determined from the grids with high correlations and small differences of PM2.5. The representative area for a single station in the study period ranges from 0.25 to 16.25 km2 but is less than 3 km2 for more than half of the stations. The representative area varies with locations, and observation at 10 optimal stations would have a good representativeness of those obtained from 169 stations for the 4 month time scale studied. Both evaluations with an empirical orthogonal function analysis and with independent data set corroborate the validity of the results found in this study.

The impact of past and future climate change on global human mortality due to ozone and PM2.5 outdoor air pollution

NASA Astrophysics Data System (ADS)

Silva, R.; West, J.; Anenberg, S.; Lamarque, J.; Shindell, D. T.; Bergmann, D. J.; Berntsen, T.; Cameron-Smith, P. J.; Collins, B.; Ghan, S. J.; Josse, B.; Nagashima, T.; Naik, V.; Plummer, D.; Rodriguez, J. M.; Szopa, S.; Zeng, G.

2012-12-01

Climate change can adversely affect air quality, through changes in meteorology, atmospheric chemistry, and emissions. Future changes in air pollutant emissions will also profoundly influence air quality. These changes in air quality can affect human health, as exposure to ground-level ozone and fine particulate matter (PM2.5) has been associated with premature human mortality. Here we will quantify the global mortality impacts of past and future climate change, considering the effects of climate change on air quality isolated from emission changes. The Atmospheric Chemistry and Climate Model Intercomparison Project (ACCMIP) has simulated the past and future surface concentrations of ozone and PM2.5 from each of several GCMs, for emissions from 1850 ("preindustrial") to 2000 ("present-day"), and for the IPCC AR5 Representative Concentration Pathways (RCPs) scenarios to 2100. We will use ozone and PM2.5 concentrations from simulations from five or more global models of atmospheric dynamics and chemistry, for a base year (present-day), pre-industrial conditions, and future scenarios, considering changes in climate and emissions. We will assess the mortality impacts of past climate change by using one simulation ensemble with present emissions and climate and one with present emissions but 1850 climate. We will similarly quantify the potential impacts of future climate change under the four RCP scenarios in 2030, 2050 and 2100. All model outputs will be regridded to the same resolution to estimate multi-model medians and range in each grid cell. Resulting premature deaths will be calculated using these medians along with epidemiologically-derived concentration-response functions, and present-day or future projections of population and baseline mortality rates, considering aging and transitioning disease rates over time. The spatial distributions of current and future global premature mortalities due to ozone and PM2.5 outdoor air pollution will be presented separately. These results will strengthen our understanding of the impacts of climate change today, and in future years considering different plausible scenarios.

PBSM3D: A finite volume, scalar-transport blowing snow model for use with variable resolution meshes

NASA Astrophysics Data System (ADS)

Marsh, C.; Wayand, N. E.; Pomeroy, J. W.; Wheater, H. S.; Spiteri, R. J.

2017-12-01

Blowing snow redistribution results in heterogeneous snowcovers that are ubiquitous in cold, windswept environments. Capturing this spatial and temporal variability is important for melt and runoff simulations. Point scale blowing snow transport models are difficult to apply in fully distributed hydrological models due to landscape heterogeneity and complex wind fields. Many existing distributed snow transport models have empirical wind flow and/or simplified wind direction algorithms that perform poorly in calculating snow redistribution where there are divergent wind flows, sharp topography, and over large spatial extents. Herein, a steady-state scalar transport model is discretized using the finite volume method (FVM), using parameterizations from the Prairie Blowing Snow Model (PBSM). PBSM has been applied in hydrological response units and grids to prairie, arctic, glacier, and alpine terrain and shows a good capability to represent snow redistribution over complex terrain. The FVM discretization takes advantage of the variable resolution mesh in the Canadian Hydrological Model (CHM) to ensure efficient calculations over small and large spatial extents. Variable resolution unstructured meshes preserve surface heterogeneity but result in fewer computational elements versus high-resolution structured (raster) grids. Snowpack, soil moisture, and streamflow observations were used to evaluate CHM-modelled outputs in a sub-arctic and an alpine basin. Newly developed remotely sensed snowcover indices allowed for validation over large basins. CHM simulations of snow hydrology were improved by inclusion of the blowing snow model. The results demonstrate the key role of snow transport processes in creating pre-melt snowcover heterogeneity and therefore governing post-melt soil moisture and runoff generation dynamics.

SoilGrids250m: Global gridded soil information based on machine learning

PubMed Central

Mendes de Jesus, Jorge; Heuvelink, Gerard B. M.; Ruiperez Gonzalez, Maria; Kilibarda, Milan; Blagotić, Aleksandar; Shangguan, Wei; Wright, Marvin N.; Geng, Xiaoyuan; Bauer-Marschallinger, Bernhard; Guevara, Mario Antonio; Vargas, Rodrigo; MacMillan, Robert A.; Batjes, Niels H.; Leenaars, Johan G. B.; Ribeiro, Eloi; Wheeler, Ichsani; Mantel, Stephan; Kempen, Bas

2017-01-01

This paper describes the technical development and accuracy assessment of the most recent and improved version of the SoilGrids system at 250m resolution (June 2016 update). SoilGrids provides global predictions for standard numeric soil properties (organic carbon, bulk density, Cation Exchange Capacity (CEC), pH, soil texture fractions and coarse fragments) at seven standard depths (0, 5, 15, 30, 60, 100 and 200 cm), in addition to predictions of depth to bedrock and distribution of soil classes based on the World Reference Base (WRB) and USDA classification systems (ca. 280 raster layers in total). Predictions were based on ca. 150,000 soil profiles used for training and a stack of 158 remote sensing-based soil covariates (primarily derived from MODIS land products, SRTM DEM derivatives, climatic images and global landform and lithology maps), which were used to fit an ensemble of machine learning methods—random forest and gradient boosting and/or multinomial logistic regression—as implemented in the R packages ranger, xgboost, nnet and caret. The results of 10–fold cross-validation show that the ensemble models explain between 56% (coarse fragments) and 83% (pH) of variation with an overall average of 61%. Improvements in the relative accuracy considering the amount of variation explained, in comparison to the previous version of SoilGrids at 1 km spatial resolution, range from 60 to 230%. Improvements can be attributed to: (1) the use of machine learning instead of linear regression, (2) to considerable investments in preparing finer resolution covariate layers and (3) to insertion of additional soil profiles. Further development of SoilGrids could include refinement of methods to incorporate input uncertainties and derivation of posterior probability distributions (per pixel), and further automation of spatial modeling so that soil maps can be generated for potentially hundreds of soil variables. Another area of future research is the development of methods for multiscale merging of SoilGrids predictions with local and/or national gridded soil products (e.g. up to 50 m spatial resolution) so that increasingly more accurate, complete and consistent global soil information can be produced. SoilGrids are available under the Open Data Base License. PMID:28207752

SoilGrids250m: Global gridded soil information based on machine learning.

PubMed

Hengl, Tomislav; Mendes de Jesus, Jorge; Heuvelink, Gerard B M; Ruiperez Gonzalez, Maria; Kilibarda, Milan; Blagotić, Aleksandar; Shangguan, Wei; Wright, Marvin N; Geng, Xiaoyuan; Bauer-Marschallinger, Bernhard; Guevara, Mario Antonio; Vargas, Rodrigo; MacMillan, Robert A; Batjes, Niels H; Leenaars, Johan G B; Ribeiro, Eloi; Wheeler, Ichsani; Mantel, Stephan; Kempen, Bas

2017-01-01

This paper describes the technical development and accuracy assessment of the most recent and improved version of the SoilGrids system at 250m resolution (June 2016 update). SoilGrids provides global predictions for standard numeric soil properties (organic carbon, bulk density, Cation Exchange Capacity (CEC), pH, soil texture fractions and coarse fragments) at seven standard depths (0, 5, 15, 30, 60, 100 and 200 cm), in addition to predictions of depth to bedrock and distribution of soil classes based on the World Reference Base (WRB) and USDA classification systems (ca. 280 raster layers in total). Predictions were based on ca. 150,000 soil profiles used for training and a stack of 158 remote sensing-based soil covariates (primarily derived from MODIS land products, SRTM DEM derivatives, climatic images and global landform and lithology maps), which were used to fit an ensemble of machine learning methods-random forest and gradient boosting and/or multinomial logistic regression-as implemented in the R packages ranger, xgboost, nnet and caret. The results of 10-fold cross-validation show that the ensemble models explain between 56% (coarse fragments) and 83% (pH) of variation with an overall average of 61%. Improvements in the relative accuracy considering the amount of variation explained, in comparison to the previous version of SoilGrids at 1 km spatial resolution, range from 60 to 230%. Improvements can be attributed to: (1) the use of machine learning instead of linear regression, (2) to considerable investments in preparing finer resolution covariate layers and (3) to insertion of additional soil profiles. Further development of SoilGrids could include refinement of methods to incorporate input uncertainties and derivation of posterior probability distributions (per pixel), and further automation of spatial modeling so that soil maps can be generated for potentially hundreds of soil variables. Another area of future research is the development of methods for multiscale merging of SoilGrids predictions with local and/or national gridded soil products (e.g. up to 50 m spatial resolution) so that increasingly more accurate, complete and consistent global soil information can be produced. SoilGrids are available under the Open Data Base License.

The Improvement of Spatial-Temporal PM2.5 Resolution in Taiwan by Using Data Assimilation Method

NASA Astrophysics Data System (ADS)

Lin, Yong-Qing; Lin, Yuan-Chien

2017-04-01

Forecasting air pollution concentration, e.g., the concentration of PM2.5, is of great significance to protect human health and the environment. Accurate prediction of PM2.5 concentrations is limited in number and the data quality of air quality monitoring stations. The spatial and temporal variations of PM2.5 concentrations are measured by 76 National Air Quality Monitoring Stations (built by the TW-EPA) in Taiwan. The National Air Quality Monitoring Stations are costly and scarce because of the highly precise instrument and their size. Therefore, many places still out of the range of National Air Quality Monitoring Stations. Recently, there are an enormous number of portable air quality sensors called "AirBox" developed jointly by the Taiwan government and a private company. By virtue of its price and portative, the AirBox can provide higher resolution of space-time PM2.5 measurement. However, the spatiotemporal distribution and data quality are different between AirBox and National Air Quality Monitoring Stations. To integrate the heterogeneous PM2.5 data, the data assimilation method should be performed before further analysis. In this study, we propose a data assimilation method based on Ensemble Kalman Filter (EnKF), which is a variant of classic Kalman Filter, can be used to combine additional heterogeneous data from different source while modeling to improve the estimation of spatial-temporal PM2.5 concentration. The assimilation procedure uses the advantages of the two kinds of heterogeneous data and merges them to produce the final estimation. The results have shown that by combining AirBox PM2.5 data as additional information in our model based EnKF can bring the better estimation of spatial-temporal PM2.5 concentration and improve the it's space-time resolution. Under the approach proposed in this study, higher spatial-temporal resoultion could provide a very useful information for a better spatial-temporal data analysis and further environmental management, such as air pollution source localization and micro-scale air pollution analysis. Keywords: PM2.5, Data Assimilation, Ensemble Kalman Filter, Air Quality

Using Satellite Aerosol Retrievals to Monitor Surface Particulate Air Quality

NASA Technical Reports Server (NTRS)

Levy, Robert C.; Remer, Lorraine A.; Kahn, Ralph A.; Chu, D. Allen; Mattoo, Shana; Holben, Brent N.; Schafer, Joel S.

2011-01-01

The MODIS and MISR aerosol products were designed nearly two decades ago for the purpose of climate applications. Since launch of Terra in 1999, these two sensors have provided global, quantitative information about column-integrated aerosol properties, including aerosol optical depth (AOD) and relative aerosol type parameters (such as Angstrom exponent). Although primarily designed for climate, the air quality (AQ) community quickly recognized that passive satellite products could be used for particulate air quality monitoring and forecasting. However, AOD and particulate matter (PM) concentrations have different units, and represent aerosol conditions in different layers of the atmosphere. Also, due to low visible contrast over brighter surface conditions, satellite-derived aerosol retrievals tend to have larger uncertainty in urban or populated regions. Nonetheless, the AQ community has made significant progress in relating column-integrated AOD at ambient relative humidity (RH) to surface PM concentrations at dried RH. Knowledge of aerosol optical and microphysical properties, ambient meteorological conditions, and especially vertical profile, are critical for physically relating AOD and PM. To make urban-scale maps of PM, we also must account for spatial variability. Since surface PM may vary on a finer spatial scale than the resolution of standard MODIS (10 km) and MISR (17km) products, we test higher-resolution versions of MODIS (3km) and MISR (1km research mode) retrievals. The recent (July 2011) DISCOVER-AQ campaign in the mid-Atlantic offers a comprehensive network of sun photometers (DRAGON) and other data that we use for validating the higher resolution satellite data. In the future, we expect that the wealth of aircraft and ground-based measurements, collected during DISCOVER-AQ, will help us quantitatively link remote sensed and ground-based measurements in the urban region.

Establishing the common patterns of future tropospheric ozone under diverse climate change scenarios

NASA Astrophysics Data System (ADS)

Jimenez-Guerrero, Pedro; Gómez-Navarro, Juan J.; Jerez, Sonia; Lorente-Plazas, Raquel; Baro, Rocio; Montávez, Juan P.

2013-04-01

The impacts of climate change on air quality may affect long-term air quality planning. However, the policies aimed at improving air quality in the EU directives have not accounted for the variations in the climate. Climate change alone influences future air quality through modifications of gas-phase chemistry, transport, removal, and natural emissions. As such, the aim of this work is to check whether the projected changes in gas-phase air pollution over Europe depends on the scenario driving the regional simulation. For this purpose, two full-transient regional climate change-air quality projections for the first half of the XXI century (1991-2050) have been carried out with MM5+CHIMERE system, including A2 and B2 SRES scenarios. Experiments span the periods 1971-2000, as a reference, and 2071-2100, as future enhanced greenhouse gas and aerosol scenarios (SRES A2 and B2). The atmospheric simulations have a horizontal resolution of 25 km and 23 vertical layers up to 100 mb, and were driven by ECHO-G global climate model outputs. The analysis focuses on the connection between meteorological and air quality variables. Our simulations suggest that the modes of variability for tropospheric ozone and their main precursors hardly change under different SRES scenarios. The effect of changing scenarios has to be sought in the intensity of the changing signal, rather than in the spatial structure of the variation patterns, since the correlation between the spatial patterns of variability in A2 and B2 simulation is r > 0.75 for all gas-phase pollutants included in this study. In both cases, full-transient simulations indicate an enhanced enhanced chemical activity under future scenarios. The causes for tropospheric ozone variations have to be sought in a multiplicity of climate factors, such as increased temperature, different distribution of precipitation patterns across Europe, increased photolysis of primary and secondary pollutants due to lower cloudiness, etc. Nonetheless, according to the results of this work future ozone is conditioned by the dependence of biogenic emissions on the climatological patterns of variability. In this sense, ozone over Europe is mainly driven by the warming-induced increase in biogenic emitting activity (vegetation is kept invariable in the simulations, but estimations of these emissions strongly depends on shortwave radiation and temperature, which are substantially modified in climatic simulations). Moreover, one of the most important drivers for ozone increase is the decrease of cloudiness (related to stronger solar radiation) mostly over southern Europe at the first half of the XXI century. However, given the large uncertainty isoprene sensitivity to climate change and the large uncertainties associated to the cloudiness projections, these results should be carefully considered.

Seltzer_et_al_2016

EPA Pesticide Factsheets

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

Scaling between reanalyses and high-resolution land-surface modelling in mountainous areas - enabling better application and testing of reanalyses in heterogeneous environments

NASA Astrophysics Data System (ADS)

Gruber, S.; Fiddes, J.

2013-12-01

In mountainous topography, the difference in scale between atmospheric reanalyses (typically tens of kilometres) and relevant processes and phenomena near the Earth surface, such as permafrost or snow cover (meters to tens of meters) is most obvious. This contrast of scales is one of the major obstacles to using reanalysis data for the simulation of surface phenomena and to confronting reanalyses with independent observation. At the example of modelling permafrost in mountain areas (but simple to generalise to other phenomena and heterogeneous environments), we present and test methods against measurements for (A) scaling atmospheric data from the reanalysis to the ground level and (B) smart sampling of the heterogeneous landscape in order to set up a lumped model simulation that represents the high-resolution land surface. TopoSCALE (Part A, see http://dx.doi.org/10.5194/gmdd-6-3381-2013) is a scheme, which scales coarse-grid climate fields to fine-grid topography using pressure level data. In addition, it applies necessary topographic corrections e.g. those variables required for computation of radiation fields. This provides the necessary driving fields to the LSM. Tested against independent ground data, this scheme has been shown to improve the scaling and distribution of meteorological parameters in complex terrain, as compared to conventional methods, e.g. lapse rate based approaches. TopoSUB (Part B, see http://dx.doi.org/10.5194/gmd-5-1245-2012) is a surface pre-processor designed to sample a fine-grid domain (defined by a digital elevation model) along important topographical (or other) dimensions through a clustering scheme. This allows constructing a lumped model representing the main sources of fine-grid variability and applying a 1D LSM efficiently over large areas. Results can processed to derive (i) summary statistics at coarse-scale re-analysis grid resolution, (ii) high-resolution data fields spatialized to e.g., the fine-scale digital elevation model grid, or (iii) validation products for locations at which measurements exist, only. The ability of TopoSUB to approximate results simulated by a 2D distributed numerical LSM at a factor of ~10,000 less computations is demonstrated by comparison of 2D and lumped simulations. Successful application of the combined scheme in the European Alps is reported and based on its results, open issues for future research are outlined.

Spatial and Temporal Variability of Trace Gas Columns Derived from WRF/Chem Regional Model Output: Planning for Geostationary Observations of Atmospheric Composition

NASA Technical Reports Server (NTRS)

Follette-Cook, M. B.; Pickering, K.; Crawford, J.; Duncan, B.; Loughner, C.; Diskin, G.; Fried, A.; Weinheimer, A.

2015-01-01

We quantify both the spatial and temporal variability of column integrated O3, NO2, CO, SO2, and HCHO over the Baltimore / Washington, DC area using output from the Weather Research and Forecasting model with on-line chemistry (WRF/Chem) for the entire month of July 2011, coinciding with the first deployment of the NASA Earth Venture program mission Deriving Information on Surface conditions from Column and Vertically Resolved Observations Relevant to Air Quality (DISCOVER-AQ). Using structure function analyses, we find that the model reproduces the spatial variability observed during the campaign reasonably well, especially for O3. The Tropospheric Emissions: Monitoring of Pollution (TEMPO) instrument will be the first NASA mission to make atmospheric composition observations from geostationary orbit and partially fulfills the goals of the Geostationary Coastal and Air Pollution Events (GEO-CAPE) mission. We relate the simulated variability to the precision requirements defined by the science traceability matrices of these space-borne missions. Results for O3 from 0- 2 km altitude indicate that the TEMPO instrument would be able to observe O3 air quality events over the Mid-Atlantic area, even on days when the violations of the air quality standard are not widespread. The results further indicated that horizontal gradients in CO from 0-2 km would be observable over moderate distances (= 20 km). The spatial and temporal results for tropospheric column NO2 indicate that TEMPO would be able to observe not only the large urban plumes at times of peak production, but also the weaker gradients between rush hours. This suggests that the proposed spatial and temporal resolutions for these satellites as well as their prospective precision requirements are sufficient to answer the science questions they are tasked to address.

Globally-Gridded Interpolated Night-Time Marine Air Temperatures 1900-2014

NASA Astrophysics Data System (ADS)

Junod, R.; Christy, J. R.

2016-12-01

Over the past century, climate records have pointed to an increase in global near-surface average temperature. Near-surface air temperature over the oceans is a relatively unused parameter in understanding the current state of climate, but is useful as an independent temperature metric over the oceans and serves as a geographical and physical complement to near-surface air temperature over land. Though versions of this dataset exist (i.e. HadMAT1 and HadNMAT2), it has been strongly recommended that various groups generate climate records independently. This University of Alabama in Huntsville (UAH) study began with the construction of monthly night-time marine air temperature (UAHNMAT) values from the early-twentieth century through to the present era. Data from the International Comprehensive Ocean and Atmosphere Data Set (ICOADS) were used to compile a time series of gridded UAHNMAT, (20S-70N). This time series was homogenized to correct for the many biases such as increasing ship height, solar deck heating, etc. The time series of UAHNMAT, once adjusted to a standard reference height, is gridded to 1.25° pentad grid boxes and interpolated using the kriging interpolation technique. This study will present results which quantify the variability and trends and compare to current trends of other related datasets that include HadNMAT2 and sea-surface temperatures (HadISST & ERSSTv4).

Diviner lunar radiometer gridded brightness temperatures from geodesic binning of modeled fields of view

NASA Astrophysics Data System (ADS)

Sefton-Nash, E.; Williams, J.-P.; Greenhagen, B. T.; Aye, K.-M.; Paige, D. A.

2017-12-01

An approach is presented to efficiently produce high quality gridded data records from the large, global point-based dataset returned by the Diviner Lunar Radiometer Experiment aboard NASA's Lunar Reconnaissance Orbiter. The need to minimize data volume and processing time in production of science-ready map products is increasingly important with the growth in data volume of planetary datasets. Diviner makes on average >1400 observations per second of radiance that is reflected and emitted from the lunar surface, using 189 detectors divided into 9 spectral channels. Data management and processing bottlenecks are amplified by modeling every observation as a probability distribution function over the field of view, which can increase the required processing time by 2-3 orders of magnitude. Geometric corrections, such as projection of data points onto a digital elevation model, are numerically intensive and therefore it is desirable to perform them only once. Our approach reduces bottlenecks through parallel binning and efficient storage of a pre-processed database of observations. Database construction is via subdivision of a geodesic icosahedral grid, with a spatial resolution that can be tailored to suit the field of view of the observing instrument. Global geodesic grids with high spatial resolution are normally impractically memory intensive. We therefore demonstrate a minimum storage and highly parallel method to bin very large numbers of data points onto such a grid. A database of the pre-processed and binned points is then used for production of mapped data products that is significantly faster than if unprocessed points were used. We explore quality controls in the production of gridded data records by conditional interpolation, allowed only where data density is sufficient. The resultant effects on the spatial continuity and uncertainty in maps of lunar brightness temperatures is illustrated. We identify four binning regimes based on trades between the spatial resolution of the grid, the size of the FOV and the on-target spacing of observations. Our approach may be applicable and beneficial for many existing and future point-based planetary datasets.

An Air-Ocean Coupled Nowcast/Forecast System for the East Asian Marginal Seas

DTIC Science & Technology

2000-09-12

external factors affecting the regional oceanogra- phy. We use a rectilinear grid with horizontal spacing of 0.25° by 0.25° and 23 nonuniform vertical a ... levels . The model uses realistic bathymetry data from the Naval Oceanographic Office Digit~ Bathymetry Data Base with 5 minute resolution (DBDB5). 2.1.2

Group for High Resolution Sea Surface Temperature (GHRSST) analysis fields inter-comparisons—Part 2: Near real time web-based level 4 SST Quality Monitor (L4-SQUAM)

NASA Astrophysics Data System (ADS)

Dash, Prasanjit; Ignatov, Alexander; Martin, Matthew; Donlon, Craig; Brasnett, Bruce; Reynolds, Richard W.; Banzon, Viva; Beggs, Helen; Cayula, Jean-Francois; Chao, Yi; Grumbine, Robert; Maturi, Eileen; Harris, Andy; Mittaz, Jonathan; Sapper, John; Chin, Toshio M.; Vazquez-Cuervo, Jorge; Armstrong, Edward M.; Gentemann, Chelle; Cummings, James; Piollé, Jean-François; Autret, Emmanuelle; Roberts-Jones, Jonah; Ishizaki, Shiro; Høyer, Jacob L.; Poulter, Dave

2012-11-01

There are a growing number of level 4 (L4; gap-free gridded) sea surface temperature (SST) products generated by blending SST data from various sources which are available for use in a wide variety of operational and scientific applications. In most cases, each product has been developed for a specific user community with specific requirements guiding the design of the product. Consequently differences between products are implicit. In addition, anomalous atmospheric conditions, satellite operations and production anomalies may occur which can introduce additional differences. This paper describes a new web-based system called the L4 SST Quality Monitor (L4-SQUAM) developed to monitor the quality of L4 SST products. L4-SQUAM intercompares thirteen L4 products with 1-day latency in an operational environment serving the needs of both L4 SST product users and producers. Relative differences between products are computed and visualized using maps, histograms, time series plots and Hovmöller diagrams, for all combinations of products. In addition, products are compared to quality controlled in situ SST data (available from the in situ SST Quality Monitor, iQUAM, companion system) in a consistent manner. A full history of products statistics is retained in L4-SQUAM for time series analysis. L4-SQUAM complements the two other Group for High Resolution SST (GHRSST) tools, the GHRSST Multi Product Ensemble (GMPE) and the High Resolution Diagnostic Data Set (HRDDS) systems, documented in part 1 of this paper and elsewhere, respectively. Our results reveal significant differences between SST products in coastal and open ocean areas. Differences of >2 °C are often observed at high latitudes partly due to different treatment of the sea-ice transition zone. Thus when an ice flag is available, the intercomparisons are performed in two ways: including and excluding ice-flagged grid points. Such differences are significant and call for a community effort to understand their root cause and ensure consistency between SST products. Future work focuses on including the remaining daily L4 SST products, accommodating for newer L4 SSTs which resolve the diurnal variability and evaluating retrospectively regenerated L4 SSTs to support satellite data reprocessing efforts aimed at generating improved SST Climate Data Records.

A photosynthesis-based two-leaf canopy stomatal conductance model for meteorology and air quality modeling with WRF/CMAQ PX LSM

NASA Astrophysics Data System (ADS)

Ran, Limei; Pleim, Jonathan; Song, Conghe; Band, Larry; Walker, John T.; Binkowski, Francis S.

2017-02-01

A coupled photosynthesis-stomatal conductance model with single-layer sunlit and shaded leaf canopy scaling is implemented and evaluated in a diagnostic box model with the Pleim-Xiu land surface model (PX LSM) and ozone deposition model components taken directly from the meteorology and air quality modeling system - WRF/CMAQ (Weather Research and Forecast model and Community Multiscale Air Quality model). The photosynthesis-based model for PX LSM (PX PSN) is evaluated at a FLUXNET site for implementation against different parameterizations and the current PX LSM approach with a simple Jarvis function (PX Jarvis). Latent heat flux (LH) from PX PSN is further evaluated at five FLUXNET sites with different vegetation types and landscape characteristics. Simulated ozone deposition and flux from PX PSN are evaluated at one of the sites with ozone flux measurements. Overall, the PX PSN simulates LH as well as the PX Jarvis approach. The PX PSN, however, shows distinct advantages over the PX Jarvis approach for grassland that likely result from its treatment of C3 and C4 plants for CO2 assimilation. Simulations using Moderate Resolution Imaging Spectroradiometer (MODIS) leaf area index (LAI) rather than LAI measured at each site assess how the model would perform with grid averaged data used in WRF/CMAQ. MODIS LAI estimates degrade model performance at all sites but one site having exceptionally old and tall trees. Ozone deposition velocity and ozone flux along with LH are simulated especially well by the PX PSN compared to significant overestimation by the PX Jarvis for a grassland site.

Derivation of a New Smoke Emissions Inventory using Remote Sensing, and Its Implications for Near Real-Time Air Quality Applications

NASA Technical Reports Server (NTRS)

Ellison, Luke; Ichoku, Charles

2012-01-01

A new emissions inventory of particulate matter (PM) is being derived mainly from remote sensing data using fire radiative power (FRP) and aerosol optical depth (AOD) retrievals from the Moderate Resolution Imaging Spectroradiometer (MODIS) instrument, as well as wind data from the Modern Era Retrospective-Analysis for Research and Applications (MERRA) reanalysis dataset, which spans the satellite era. This product is generated using a coefficient of emission, C(sub e), that has been produced on a 1x1 degree global grid such that, when it is multiplied with satellite measurements of FRP or its time-integrated equivalent fire radiative energy (FRE) retrieved over a given area and time period, the corresponding PM emissions are estimated. This methodology of using C(sub e) to derive PM emissions is relatively new and advantageous for near real-time air quality applications compared to current methods based on post-fire burned area that may not provide emissions in a timely manner. Furthermore, by using FRP to characterize a fire s output, it will represent better accuracy than the use of raw fire pixel counts, since fires in individual pixels can differ in size and strength by orders of magnitude, resulting in similar differences in emission rates. Here we will show examples of this effect and how this new emission inventory can properly account for the differing emission rates from fires of varying strengths. We also describe the characteristics of the new emissions inventory, and propose the process chain of incorporating it into models for air quality applications.

Statistical Properties of Differences between Low and High Resolution CMAQ Runs with Matched Initial and Boundary Conditions

EPA Science Inventory

The difficulty in assessing errors in numerical models of air quality is a major obstacle to improving their ability to predict and retrospectively map air quality. In this paper, using simulation outputs from the Community Multi-scale Air Quality Model (CMAQ), the statistic...

The impact of the resolution of meteorological datasets on catchment-scale drought studies

NASA Astrophysics Data System (ADS)

Hellwig, Jost; Stahl, Kerstin

2017-04-01

Gridded meteorological datasets provide the basis to study drought at a range of scales, including catchment scale drought studies in hydrology. They are readily available to study past weather conditions and often serve real time monitoring as well. As these datasets differ in spatial/temporal coverage and spatial/temporal resolution, for most studies there is a tradeoff between these features. Our investigation examines whether biases occur when studying drought on catchment scale with low resolution input data. For that, a comparison among the datasets HYRAS (covering Central Europe, 1x1 km grid, daily data, 1951 - 2005), E-OBS (Europe, 0.25° grid, daily data, 1950-2015) and GPCC (whole world, 0.5° grid, monthly data, 1901 - 2013) is carried out. Generally, biases in precipitation increase with decreasing resolution. Most important variations are found during summer. In low mountain range of Central Europe the datasets of sparse resolution (E-OBS, GPCC) overestimate dry days and underestimate total precipitation since they are not able to describe high spatial variability. However, relative measures like the correlation coefficient reveal good consistencies of dry and wet periods, both for absolute precipitation values and standardized indices like the Standardized Precipitation Index (SPI) or Standardized Precipitation Evaporation Index (SPEI). Particularly the most severe droughts derived from the different datasets match very well. These results indicate that absolute values of sparse resolution datasets applied to catchment scale might be critical to use for an assessment of the hydrological drought at catchment scale, whereas relative measures for determining periods of drought are more trustworthy. Therefore, studies on drought, that downscale meteorological data, should carefully consider their data needs and focus on relative measures for dry periods if sufficient for the task.

Using ERA-Interim reanalysis for creating datasets of energy-relevant climate variables

NASA Astrophysics Data System (ADS)

Jones, Philip D.; Harpham, Colin; Troccoli, Alberto; Gschwind, Benoit; Ranchin, Thierry; Wald, Lucien; Goodess, Clare M.; Dorling, Stephen

2017-07-01

The construction of a bias-adjusted dataset of climate variables at the near surface using ERA-Interim reanalysis is presented. A number of different, variable-dependent, bias-adjustment approaches have been proposed. Here we modify the parameters of different distributions (depending on the variable), adjusting ERA-Interim based on gridded station or direct station observations. The variables are air temperature, dewpoint temperature, precipitation (daily only), solar radiation, wind speed, and relative humidity. These are available on either 3 or 6 h timescales over the period 1979-2016. The resulting bias-adjusted dataset is available through the Climate Data Store (CDS) of the Copernicus Climate Change Data Store (C3S) and can be accessed at present from ftp://ecem.climate.copernicus.eu. The benefit of performing bias adjustment is demonstrated by comparing initial and bias-adjusted ERA-Interim data against gridded observational fields.

A gridded hourly rainfall dataset for the UK applied to a national physically-based modelling system

NASA Astrophysics Data System (ADS)

Lewis, Elizabeth; Blenkinsop, Stephen; Quinn, Niall; Freer, Jim; Coxon, Gemma; Woods, Ross; Bates, Paul; Fowler, Hayley

2016-04-01

An hourly gridded rainfall product has great potential for use in many hydrological applications that require high temporal resolution meteorological data. One important example of this is flood risk management, with flooding in the UK highly dependent on sub-daily rainfall intensities amongst other factors. Knowledge of sub-daily rainfall intensities is therefore critical to designing hydraulic structures or flood defences to appropriate levels of service. Sub-daily rainfall rates are also essential inputs for flood forecasting, allowing for estimates of peak flows and stage for flood warning and response. In addition, an hourly gridded rainfall dataset has significant potential for practical applications such as better representation of extremes and pluvial flash flooding, validation of high resolution climate models and improving the representation of sub-daily rainfall in weather generators. A new 1km gridded hourly rainfall dataset for the UK has been created by disaggregating the daily Gridded Estimates of Areal Rainfall (CEH-GEAR) dataset using comprehensively quality-controlled hourly rain gauge data from over 1300 observation stations across the country. Quality control measures include identification of frequent tips, daily accumulations and dry spells, comparison of daily totals against the CEH-GEAR daily dataset, and nearest neighbour checks. The quality control procedure was validated against historic extreme rainfall events and the UKCP09 5km daily rainfall dataset. General use of the dataset has been demonstrated by testing the sensitivity of a physically-based hydrological modelling system for Great Britain to the distribution and rates of rainfall and potential evapotranspiration. Of the sensitivity tests undertaken, the largest improvements in model performance were seen when an hourly gridded rainfall dataset was combined with potential evapotranspiration disaggregated to hourly intervals, with 61% of catchments showing an increase in NSE between observed and simulated streamflows as a result of more realistic sub-daily meteorological forcing.

MODIS Snow-Cover Products

NASA Technical Reports Server (NTRS)

Hall, Dorothy K.; Riggs, George A.; Salomonson, Vinvent V.; DiGirolamo, Nicolo; Bayr, Klaus J.; Houser, Paul (Technical Monitor)

2001-01-01

On December 18, 1999, the Terra satellite was launched with a complement of five instruments including the Moderate Resolution Imaging Spectroradiometer (MODIS). Many geophysical products are derived from MODIS data including global snow-cover products. These products have been available through the National Snow and Ice Data Center (NSIDC) Distributed Active Archive Center (DAAC) since September 13, 2000. MODIS snow-cover products represent potential improvement to the currently available operation products mainly because the MODIS products are global and 500-m resolution, and have the capability to separate most snow and clouds. Also the snow-mapping algorithms are automated which means that a consistent data set is generated for long-term climates studies that require snow-cover information. Extensive quality assurance (QA) information is stored with the product. The snow product suite starts with a 500-m resolution swath snow-cover map which is gridded to the Integerized Sinusoidal Grid to produce daily and eight-day composite tile products. The sequence then proceeds to a climate-modeling grid product at 5-km spatial resolution, with both daily and eight-day composite products. A case study from March 6, 2000, involving MODIS data and field and aircraft measurements, is presented. Near-term enhancements include daily snow albedo and fractional snow cover.

Observed and modelled “chemical weather” during ESCOMPTE

NASA Astrophysics Data System (ADS)

Dufour, A.; Amodei, M.; Ancellet, G.; Peuch, V.-H.

2005-03-01

The new MOdèle de Chimie Atmosphérique à Grande Echelle (MOCAGE) three-dimensional multiscale chemistry and transport model (CTM) has been applied to study heavy pollution episodes observed during the ESCOMPTE experiment. The model considers the troposphere and lower stratosphere, and allows the possibility of zooming from the planetary scale down to the regional scale over limited area subdomains. Like this, it generates its own time-dependent chemical boundary conditions in the vertical and in the horizontal. This paper focuses on the evaluation and quantification of uncertainties related to chemical and transport modelling during two intensive observing periods, IOP2 and IOP4 (June 20-26 and July 10-14, 2001, respectively). Simulations are compared to the database of four-dimensional observations, which includes ground-based sites and aircraft measurements, radiosoundings, and quasi-continuous measurements of ozone by LIDARs. Thereby, the observed and modelled day-to-day variabilities in air composition both at the surface and in the vertical have been assessed. Then, three sensitivity studies are conducted concerning boundary conditions, accuracy of the emission dataset, and representation of chemistry. Firstly, to go further in the analysis of chemical boundary conditions, results from the standard grid nesting set-up and altered configurations, relying on climatologies, are compared. Along with other recent studies, this work advocates the systematic coupling of limited-area models with global CTMs, even for regional air quality studies or forecasts. Next, we evaluate the benefits of using the detailed high-resolution emissions inventory of ESCOMPTE: improvements are noticeable both on ozone reactivity and on the concentrations of various species of the ozone photochemical cycle especially primary ones. Finally, we provide some insights on the comparison of two simulations differing only by the parameterisation of chemistry and using two state-of-the-art chemical schemes for regional photochemical modelling. Regional air quality modelling is found to be highly sensitive to the emission inventory dataset and also to the vertical and horizontal boundary conditions and detailed representation of chemistry. Interestingly enough, they infer the same range of errors compared to total model errors.

Stratospheric Intrusion-Influenced Ozone Air Quality Exceedences Investigated in MERRA-2

NASA Technical Reports Server (NTRS)

Knowland, K. Emma; Ott, Lesley; Duncan, Bryan; Wargan, Krzysztof

2017-01-01

Ozone near the surface is harmful to human health and is a result of the photochemical reaction with both man-made and natural precursor pollutant sources. Therefore, in order to reduce near surface ozone concentrations, communities must reduce anthropogenic pollution sources. However, the injection of stratospheric ozone into the troposphere, known as a stratospheric intrusion, can also lead to concentrations of ground-level ozone exceeding air quality standards. Stratospheric intrusions are dynamical atmospheric features, however, these intrusions have been misrepresented in models and reanalyses until recently, as the features of a stratospheric intrusion are best identified in horizontal resolutions of approximately 50 km or smaller. NASA's Modern-Era Retrospective Analysis for Research and Applications Version-2 (MERRA-2) reanalysis is a publicly-available high-resolution dataset (50 km) with assimilated ozone that characterizes stratospheric ozone on the same spatiotemporal resolution as the meteorology. We show that stratospheric intrusions that impact surface air quality are well represented in the MERRA-2 reanalysis. This is demonstrated through a case study analysis of stratospheric intrusion events which were identified by the United States Environmental Protection Agency (EPA) to impact surface ozone air quality in spring 2012 in Colorado. The stratospheric intrusions are identified in MERRA-2 by the folding of the dynamical tropopause under the jet stream and subsequent isentropic descent of dry, O3-rich stratospheric air towards the surface where ozone air quality exceedences were observed. The MERRA-2 reanalysis can support air quality agencies for more rapid identification of the impact of stratospheric air on ground-level ozone.

Improved Satellite Retrievals of NO2 and SO2 over the Canadian Oil Sands and Comparisons with Surface Measurements

NASA Technical Reports Server (NTRS)

McLinden, C. A.; Fioletov, V.; Boersma, K. F.; Kharol, S. K.; Krotkov, N.; Lamsal, L.; Makar, P. A.; Martin, R. V.; Veefkind, J. P.; Yang, K.

2014-01-01

Satellite remote sensing is increasingly being used to monitor air quality over localized sources such as the Canadian oil sands. Following an initial study, significantly low biases have been identified in current NO2 and SO2 retrieval products from the Ozone Monitoring Instrument (OMI) satellite sensor over this location resulting from a combination of its rapid development and small spatial scale. Air mass factors (AMFs) used to convert line-of-sight "slant" columns to vertical columns were re-calculated for this region based on updated and higher resolution input information including absorber profiles from a regional-scale (15 km × 15 km resolution) air quality model, higher spatial and temporal resolution surface reflectivity, and an improved treatment of snow. The overall impact of these new Environment Canada (EC) AMFs led to substantial increases in the peak NO2 and SO2 average vertical column density (VCD), occurring over an area of intensive surface mining, by factors of 2 and 1.4, respectively, relative to estimates made with previous AMFs. Comparisons are made with long-term averages of NO2 and SO2 (2005-2011) from in situ surface monitors by using the air quality model to map the OMI VCDs to surface concentrations. This new OMI-EC product is able to capture the spatial distribution of the in situ instruments (slopes of 0.65 to 1.0, correlation coefficients of greater than 0.9). The concentration absolute values from surface network observations were in reasonable agreement, with OMI-EC NO2 and SO2 biased low by roughly 30%. Several complications were addressed including correction for the interference effect in the surface NO2 instruments and smoothing and clear-sky biases in the OMI measurements. Overall these results highlight the importance of using input information that accounts for the spatial and temporal variability of the location of interest when performing retrievals.

Empirical-statistical downscaling of reanalysis data to high-resolution air temperature and specific humidity above a glacier surface (Cordillera Blanca, Peru)

NASA Astrophysics Data System (ADS)

Hofer, Marlis; MöLg, Thomas; Marzeion, Ben; Kaser, Georg

2010-06-01

Recently initiated observation networks in the Cordillera Blanca (Peru) provide temporally high-resolution, yet short-term, atmospheric data. The aim of this study is to extend the existing time series into the past. We present an empirical-statistical downscaling (ESD) model that links 6-hourly National Centers for Environmental Prediction (NCEP)/National Center for Atmospheric Research (NCAR) reanalysis data to air temperature and specific humidity, measured at the tropical glacier Artesonraju (northern Cordillera Blanca). The ESD modeling procedure includes combined empirical orthogonal function and multiple regression analyses and a double cross-validation scheme for model evaluation. Apart from the selection of predictor fields, the modeling procedure is automated and does not include subjective choices. We assess the ESD model sensitivity to the predictor choice using both single-field and mixed-field predictors. Statistical transfer functions are derived individually for different months and times of day. The forecast skill largely depends on month and time of day, ranging from 0 to 0.8. The mixed-field predictors perform better than the single-field predictors. The ESD model shows added value, at all time scales, against simpler reference models (e.g., the direct use of reanalysis grid point values). The ESD model forecast 1960-2008 clearly reflects interannual variability related to the El Niño/Southern Oscillation but is sensitive to the chosen predictor type.

Comparison of High-Frequency Solar Irradiance: Ground Measured vs. Satellite-Derived

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

Lave, Matthew; Weekley, Andrew

2016-11-21

High-frequency solar variability is an important to grid integration studies, but ground measurements are scarce. The high resolution irradiance algorithm (HRIA) has the ability to produce 4-sceond resolution global horizontal irradiance (GHI) samples, at locations across North America. However, the HRIA has not been extensively validated. In this work, we evaluate the HRIA against a database of 10 high-frequency ground-based measurements of irradiance. The evaluation focuses on variability-based metrics. This results in a greater understanding of the errors in the HRIA as well as suggestions for improvement to the HRIA.

Grist : grid-based data mining for astronomy

NASA Technical Reports Server (NTRS)

Jacob, Joseph C.; Katz, Daniel S.; Miller, Craig D.; Walia, Harshpreet; Williams, Roy; Djorgovski, S. George; Graham, Matthew J.; Mahabal, Ashish; Babu, Jogesh; Berk, Daniel E. Vanden;

Grist: Grid-based Data Mining for Astronomy

NASA Astrophysics Data System (ADS)

Jacob, J. C.; Katz, D. S.; Miller, C. D.; Walia, H.; Williams, R. D.; Djorgovski, S. G.; Graham, M. J.; Mahabal, A. A.; Babu, G. J.; vanden Berk, D. E.; Nichol, R.

2005-12-01

The Grist project is developing a grid-technology based system as a research environment for astronomy with massive and complex datasets. This knowledge extraction system will consist of a library of distributed grid services controlled by a workflow system, compliant with standards emerging from the grid computing, web services, and virtual observatory communities. This new technology is being used to find high redshift quasars, study peculiar variable objects, search for transients in real time, and fit SDSS QSO spectra to measure black hole masses. Grist services are also a component of the ``hyperatlas'' project to serve high-resolution multi-wavelength imagery over the Internet. In support of these science and outreach objectives, the Grist framework will provide the enabling fabric to tie together distributed grid services in the areas of data access, federation, mining, subsetting, source extraction, image mosaicking, statistics, and visualization.

Photochemical Grid Modelling Study to Assess Potential Air Quality Impacts Associated with Energy Development in Colorado and Northern New Mexico.

NASA Astrophysics Data System (ADS)

Parker, L. K.; Morris, R. E.; Zapert, J.; Cook, F.; Koo, B.; Rasmussen, D.; Jung, J.; Grant, J.; Johnson, J.; Shah, T.; Pavlovic, T.

2015-12-01

The Colorado Air Resource Management Modeling Study (CARMMS) was funded by the Bureau of Land Management (BLM) to predict the impacts from future federal and non-federal energy development in Colorado and Northern New Mexico. The study used the Comprehensive Air Quality Model with extensions (CAMx) photochemical grid model (PGM) to quantify potential impacts from energy development from BLM field office planning areas. CAMx source apportionment technology was used to track the impacts from multiple (14) different emissions source regions (i.e. field office areas) within one simulation, as well as to assess the cumulative impact of emissions from all source regions combined. The energy development emissions estimates were for the year 2021 for three different development scenarios: (1) low; (2) high; (3) high with emissions mitigation. Impacts on air quality (AQ) including ozone, PM2.5, PM10, NO2, SO2, and air quality related values (AQRVs) such as atmospheric deposition, regional haze and changes in Acid Neutralizing Capacity (ANC) of lakes were quantified, and compared to establish threshold levels. In this presentation, we present a brief summary of the how the emission scenarios were developed, we compare the emission totals for each scenario, and then focus on the ozone impacts for each scenario to assess: (1). the difference in potential ozone impacts under the different development scenarios and (2). to establish the sensitivity of the ozone impacts to different emissions levels. Region-wide ozone impacts will be presented as well as impacts at specific locations with ozone monitors.

DRAGON Grid: A Three-Dimensional Hybrid Grid Generation Code Developed

NASA Technical Reports Server (NTRS)

Liou, Meng-Sing

2000-01-01

Because grid generation can consume 70 percent of the total analysis time for a typical three-dimensional viscous flow simulation for a practical engineering device, payoffs from research and development could reduce costs and increase throughputs considerably. In this study, researchers at the NASA Glenn Research Center at Lewis Field developed a new hybrid grid approach with the advantages of flexibility, high-quality grids suitable for an accurate resolution of viscous regions, and a low memory requirement. These advantages will, in turn, reduce analysis time and increase accuracy. They result from an innovative combination of structured and unstructured grids to represent the geometry and the computation domain. The present approach makes use of the respective strengths of both the structured and unstructured grid methods, while minimizing their weaknesses. First, the Chimera grid generates high-quality, mostly orthogonal meshes around individual components. This process is flexible and can be done easily. Normally, these individual grids are required overlap each other so that the solution on one grid can communicate with another. However, when this communication is carried out via a nonconservative interpolation procedure, a spurious solution can result. Current research is aimed at entirely eliminating this undesired interpolation by directly replacing arbitrary grid overlapping with a nonstructured grid called a DRAGON grid, which uses the same set of conservation laws over the entire region, thus ensuring conservation everywhere. The DRAGON grid is shown for a typical film-cooled turbine vane with 33 holes and 3 plenum compartments. There are structured grids around each geometrical entity and unstructured grids connecting them. In fiscal year 1999, Glenn researchers developed and tested the three-dimensional DRAGON grid-generation tools. A flow solver suitable for the DRAGON grid has been developed, and a series of validation tests are underway.

Computation of Flow Over a Drag Prediction Workshop Wing/Body Transport Configuration Using CFL3D

NASA Technical Reports Server (NTRS)

Rumsey, Christopher L.; Biedron, Robert T.

2001-01-01

A Drag Prediction Workshop was held in conjunction with the 19th AIAA Applied Aerodynamics Conference in June 2001. The purpose of the workshop was to assess the prediction of drag by computational methods for a wing/body configuration (DLR-F4) representative of subsonic transport aircraft. This report details computed results submitted to this workshop using the Reynolds-averaged Navier-Stokes code CFL3D. Two supplied grids were used: a point-matched 1-to-1 multi-block grid, and an overset multi-block grid. The 1-to-1 grid, generally of much poorer quality and with less streamwise resolution than the overset grid, is found to be too coarse to adequately resolve the surface pressures. However, the global forces and moments are nonetheless similar to those computed using the overset grid. The effect of three different turbulence models is assessed using the 1-to-1 grid. Surface pressures are very similar overall, and the drag variation due to turbulence model is 18 drag counts. Most of this drag variation is in the friction component, and is attributed in part to insufficient grid resolution of the 1-to-1 grid. The misnomer of 'fully turbulent' computations is discussed; comparisons are made using different transition locations and their effects on the global forces and moments are quantified. Finally, the effect of two different versions of a widely used one-equation turbulence model is explored.

Mapping of the Tropospheric NO2 Spatial Distribution at City-scale Based on Airborne APEX Hyperspectral Imaging

NASA Astrophysics Data System (ADS)

Tack, F. M.; Merlaud, A.; Danckaert, T.; Yu, H.; Fayt, C.; Iordache, D.; Meuleman, K.; Fierens, F.; Deutsch, F.; Van Roozendael, M.

2016-12-01

NO2 is a key pollutant with highly variable concentrations in space and time. Quantitative information about its spatial variability at high resolution is currently scarce, but very valuable for (air quality) studies at the urban scale. APEX is a pushbroom hyperspectral imager with high spatial (60 by 80 m2) and spectral (2.8-3.3 nm) resolution. APEX flights were conducted over (1) the city and port of Antwerp, Belgium on April 14, 2015 and July 19, 2016, (2) Brussels, Belgium on June 30, 2015 (BUMBA project), and (3) Berlin, Germany on April 21, 2016 (AROMAT and AROMAPEX projects). APEX was operated from a DLR DO-228 plane at 6.1 km altitude. Over Berlin, two additional imagers, AirMAP (IUP Bremen) and SWING (BIRA-IASB), were simultaneously operated from a FUB Cessna at 3 km for intercomparison purposes. NO2 vertical column densities (VCDs) are retrieved based on (1) the DOAS analysis of the observed spectra in the visible region (470 nm - 510 nm), and (2) air mass factor calculations with the RTM VLIDORT 2.6. Results show that APEX is suitable (1) to detect the fast varying spectral signatures of a trace gas like NO2 and (2) to identify small scale gradients in the NO2 field and to resolve individual emission sources. Main NOx sources in the Antwerp area are related to (petro)chemical industry, while traffic emissions are dominant in Brussels. Over Berlin, 2 large industrial NO2 plumes are detected by all three imaging systems, crossing the city from west to east. The NO2 VCD levels range between 0.2 and 3.5 x 1016 molec cm-2. The typical detection limit for the APEX instrument is around 1.7 to 2.2 x 1015 molec cm-2. Correlation coefficients of 0.85 and slopes close to unity are obtained when compared to coincident car mobile-DOAS measurements. The NO2 retrieval algorithm, campaign results, and ongoing research concerning the comparison of the VCDs with in-situ surface concentrations and a high resolution (25 m) air quality model, i.e. RIO-IFDM, will be discussed.

Climate, air quality and human health benefits of various solar photovoltaic deployment scenarios in China in 2030

NASA Astrophysics Data System (ADS)

Yang, Junnan; Li, Xiaoyuan; Peng, Wei; Wagner, Fabian; Mauzerall, Denise L.

2018-06-01

Solar photovoltaic (PV) electricity generation can greatly reduce both air pollutant and greenhouse gas emissions compared to fossil fuel electricity generation. The Chinese government plans to greatly scale up solar PV installation between now and 2030. However, different PV development pathways will influence the range of air quality and climate benefits. Benefits depend on how much electricity generated from PV is integrated into power grids and the type of power plant displaced. Using a coal-intensive power sector projection as the base case, we estimate the climate, air quality, and related human health benefits of various 2030 PV deployment scenarios. We use the 2030 government goal of 400 GW installed capacity but vary the location of PV installation and the extent of inter-provincial PV electricity transmission. We find that deploying distributed PV in the east with inter-provincial transmission maximizes potential CO2 reductions and air quality-related health benefits (4.2% and 1.2% decrease in national total CO2 emissions and air pollution-related premature deaths compared to the base case, respectively). Deployment in the east with inter-provincial transmission results in the largest benefits because it maximizes displacement of the dirtiest coal-fired power plants and minimizes PV curtailment, which is more likely to occur without inter-provincial transmission. We further find that the maximum co-benefits achieved with deploying PV in the east and enabling inter-provincial transmission are robust under various maximum PV penetration levels in both provincial and regional grids. We find large potential benefits of policies that encourage distributed PV deployment and facilitate inter-provincial PV electricity transmission in China.

Finely Resolved On-Road PM2.5 and Estimated Premature Mortality in Central North Carolina.

PubMed

Chang, Shih Ying; Vizuete, William; Serre, Marc; Vennam, Lakshmi Pradeepa; Omary, Mohammad; Isakov, Vlad; Breen, Michael; Arunachalam, Saravanan

2017-12-01

To quantify the on-road PM 2.5 -related premature mortality at a national scale, previous approaches to estimate concentrations at a 12-km × 12-km or larger grid cell resolution may not fully characterize concentration hotspots that occur near roadways and thus the areas of highest risk. Spatially resolved concentration estimates from on-road emissions to capture these hotspots may improve characterization of the associated risk, but are rarely used for estimating premature mortality. In this study, we compared the on-road PM 2.5 -related premature mortality in central North Carolina with two different concentration estimation approaches-(i) using the Community Multiscale Air Quality (CMAQ) model to model concentration at a coarser resolution of a 36-km × 36-km grid resolution, and (ii) using a hybrid of a Gaussian dispersion model, CMAQ, and a space-time interpolation technique to provide annual average PM 2.5 concentrations at a Census-block level (∼105,000 Census blocks). The hybrid modeling approach estimated 24% more on-road PM 2.5 -related premature mortality than CMAQ. The major difference is from the primary on-road PM 2.5 where the hybrid approach estimated 2.5 times more primary on-road PM 2.5 -related premature mortality than CMAQ due to predicted exposure hotspots near roadways that coincide with high population areas. The results show that 72% of primary on-road PM 2.5 premature mortality occurs within 1,000 m from roadways where 50% of the total population resides, highlighting the importance to characterize near-road primary PM 2.5 and suggesting that previous studies may have underestimated premature mortality due to PM 2.5 from traffic-related emissions. © 2017 Society for Risk Analysis.

The Impact of ARM on Climate Modeling. Chapter 26

NASA Technical Reports Server (NTRS)

Randall, David A.; Del Genio, Anthony D.; Donner, Leo J.; Collins, William D.; Klein, Stephen A.

2016-01-01

Climate models are among humanity's most ambitious and elaborate creations. They are designed to simulate the interactions of the atmosphere, ocean, land surface, and cryosphere on time scales far beyond the limits of deterministic predictability, and including the effects of time-dependent external forcings. The processes involved include radiative transfer, fluid dynamics, microphysics, and some aspects of geochemistry, biology, and ecology. The models explicitly simulate processes on spatial scales ranging from the circumference of the Earth down to one hundred kilometers or smaller, and implicitly include the effects of processes on even smaller scales down to a micron or so. The atmospheric component of a climate model can be called an atmospheric global circulation model (AGCM). In an AGCM, calculations are done on a three-dimensional grid, which in some of today's climate models consists of several million grid cells. For each grid cell, about a dozen variables are time-stepped as the model integrates forward from its initial conditions. These so-called prognostic variables have special importance because they are the only things that a model remembers from one time step to the next; everything else is recreated on each time step by starting from the prognostic variables and the boundary conditions. The prognostic variables typically include information about the mass of dry air, the temperature, the wind components, water vapor, various condensed-water species, and at least a few chemical species such as ozone. A good way to understand how climate models work is to consider the lengthy and complex process used to develop one. Lets imagine that a new AGCM is to be created, starting from a blank piece of paper. The model may be intended for a particular class of applications, e.g., high-resolution simulations on time scales of a few decades. Before a single line of code is written, the conceptual foundation of the model must be designed through a creative envisioning that starts from the intended application and is based on current understanding of how the atmosphere works and the inventory of mathematical methods available.

Environmental Assessment for Clear AFS Grid Tie-in and Heat Plant, Clear Air Force Station, Alaska

DTIC Science & Technology

2013-07-01

greenhouse gases are presented in this section. 3.3.2.1 Air Quality Standards All stationary and mobile sources of air pollutants within a...These inventories provide estimates of criteria pollutant emissions associated with industrial sources, residential wood burning, mobile sources...larger, more mobile wildlife species are expected to vacate the project area, whereas individuals of less mobile species (i.e., small mammals,) could

Scale Issues in Air Quality Modeling

EPA Science Inventory

This presentation reviews past model evaluation studies investigating the impact of horizontal grid spacing on model performance. It also presents several examples of using a spectral decomposition technique to separate the forcings from processes operating on different time scal...

Visual Environment for Rich Data Interpretation (VERDI) program for environmental modeling systems

EPA Pesticide Factsheets

VERDI is a flexible, modular, Java-based program used for visualizing multivariate gridded meteorology, emissions and air quality modeling data created by environmental modeling systems such as the CMAQ model and WRF.

Experimental High-Resolution Land Surface Prediction System for the Vancouver 2010 Winter Olympic Games

NASA Astrophysics Data System (ADS)

Belair, S.; Bernier, N.; Tong, L.; Mailhot, J.

2008-05-01

The 2010 Winter Olympic and Paralympic Games will take place in Vancouver, Canada, from 12 to 28 February 2010 and from 12 to 21 March 2010, respectively. In order to provide the best possible guidance achievable with current state-of-the-art science and technology, Environment Canada is currently setting up an experimental numerical prediction system for these special events. This system consists of a 1-km limited-area atmospheric model that will be integrated for 16h, twice a day, with improved microphysics compared with the system currently operational at the Canadian Meteorological Centre. In addition, several new and original tools will be used to adapt and refine predictions near and at the surface. Very high-resolution two-dimensional surface systems, with 100-m and 20-m grid size, will cover the Vancouver Olympic area. Using adaptation methods to improve the forcing from the lower-resolution atmospheric models, these 2D surface models better represent surface processes, and thus lead to better predictions of snow conditions and near-surface air temperature. Based on a similar strategy, a single-point model will be implemented to better predict surface characteristics at each station of an observing network especially installed for the 2010 events. The main advantage of this single-point system is that surface observations are used as forcing for the land surface models, and can even be assimilated (although this is not expected in the first version of this new tool) to improve initial conditions of surface variables such as snow depth and surface temperatures. Another adaptation tool, based on 2D stationnary solutions of a simple dynamical system, will be used to produce near-surface winds on the 100-m grid, coherent with the high- resolution orography. The configuration of the experimental numerical prediction system will be presented at the conference, together with preliminary results for winter 2007-2008.

Bathymetric terrain model of the Atlantic margin for marine geological investigations

USGS Publications Warehouse

Andrews, Brian D.; Chaytor, Jason D.; ten Brink, Uri S.; Brothers, Daniel S.; Gardner, James V.; Lobecker, Elizabeth A.; Calder, Brian R.

2016-01-01

A bathymetric terrain model of the Atlantic margin covering almost 725,000 square kilometers of seafloor from the New England Seamounts in the north to the Blake Basin in the south is compiled from existing multibeam bathymetric data for marine geological investigations. Although other terrain models of the same area are extant, they are produced from either satellite-derived bathymetry at coarse resolution (ETOPO1), or use older bathymetric data collected by using a combination of single beam and multibeam sonars (Coastal Relief Model). The new multibeam data used to produce this terrain model have been edited by using hydrographic data processing software to maximize the quality, usability, and cartographic presentation of the combined 100-meter resolution grid. The final grid provides the largest high-resolution, seamless terrain model of the Atlantic margin..

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.

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

NASA Astrophysics Data System (ADS)

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

2016-04-01

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

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.

Aerosol indirect effect on the grid-scale clouds in the two-way coupled WRF–CMAQ: model description, development, evaluation and regional analysis

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

Yu, S.; Mathur, R.; Pleim, J.

This study implemented first, second and glaciation aerosol indirect effects (AIE) on resolved clouds in the two-way coupled Weather Research and Forecasting Community Multiscale Air Quality (WRF–CMAQ) modeling system by including parameterizations for both cloud drop and ice number concentrations on the basis of CMAQ-predicted aerosol distributions and WRF meteorological conditions. The performance of the newly developed WRF–CMAQ model, with alternate Community Atmospheric Model (CAM) and Rapid Radiative Transfer Model for GCMs (RRTMG) radiation schemes, was evaluated with observations from the Clouds and the See http://ceres.larc.nasa.gov/. Earth's Radiant Energy System (CERES) satellite and surface monitoring networks (AQS, IMPROVE, CASTNET, STN,more » and PRISM) over the continental US (CONUS) (12 km resolution) and eastern Texas (4 km resolution) during August and September of 2006. The results at the Air Quality System (AQS) surface sites show that in August, the normalized mean bias (NMB) values for PM 2.5 over the eastern US (EUS) and the western US (WUS) are 5.3% (-0.1%) and 0.4% (-5.2%) for WRF–CMAQ/CAM (WRF–CMAQ/RRTMG), respectively. The evaluation of PM 2.5 chemical composition reveals that in August, WRF–CMAQ/CAM (WRF–CMAQ/RRTMG) consistently underestimated the observed SO 4 2- by -23.0% (-27.7%), -12.5% (-18.9%) and -7.9% (-14.8%) over the EUS at the Clean Air Status Trends Network (CASTNET), Interagency Monitoring of Protected Visual Environments (IMPROVE) and Speciated Trends Network (STN) sites, respectively. Both configurations (WRF–CMAQ/CAM, WRF–CMAQ/RRTMG) overestimated the observed mean organic carbon (OC), elemental carbon (EC) and and total carbon (TC) concentrations over the EUS in August at the IMPROVE sites. Both configurations generally underestimated the cloud field (shortwave cloud forcing, SWCF) over the CONUS in August due to the fact that the AIE on the subgrid convective clouds was not considered when the model simulations were run at the 12 km resolution. This is in agreement with the fact that both configurations captured SWCF and longwave cloud forcing (LWCF) very well for the 4 km simulation over eastern Texas, when all clouds were resolved by the finer resolution domain. The simulations of WRF–CMAQ/CAM and WRF–CMAQ/RRTMG show dramatic improvements for SWCF, LWCF, cloud optical depth (COD), cloud fractions and precipitation over the ocean relative to those of WRF default cases in August. The model performance in September is similar to that in August, except for a greater overestimation of PM 2.5 due to the overestimations of SO 4 2-, NH 4 +, NO 3 -, and TC over the EUS, less underestimation of clouds (SWCF) over the land areas due to the lower SWCF values, and fewer convective clouds in September. Finally, this work shows that inclusion of indirect aerosol effect treatments in WRF–CMAQ represents a significant advancement and milestone in air quality modeling and the development of integrated emissions control strategies for air quality management and climate change mitigation.« less

Circulation and multiple-scale variability in the Southern California Bight

NASA Astrophysics Data System (ADS)

Dong, Changming; Idica, Eileen Y.; McWilliams, James C.

2009-09-01

The oceanic circulation in the Southern California Bight (SCB) is influenced by the large-scale California Current offshore, tropical remote forcing through the coastal wave guide alongshore, and local atmospheric forcing. The region is characterized by local complexity in the topography and coastline. All these factors engender variability in the circulation on interannual, seasonal, and intraseasonal time scales. This study applies the Regional Oceanic Modeling System (ROMS) to the SCB circulation and its multiple-scale variability. The model is configured in three levels of nested grids with the parent grid covering the whole US West Coast. The first child grid covers a large southern domain, and the third grid zooms in on the SCB region. The three horizontal grid resolutions are 20 km, 6.7 km, and 1 km, respectively. The external forcings are momentum, heat, and freshwater flux at the surface and adaptive nudging to gyre-scale SODA reanalysis fields at the boundaries. The momentum flux is from a three-hourly reanalysis mesoscale MM5 wind with a 6 km resolution for the finest grid in the SCB. The oceanic model starts in an equilibrium state from a multiple-year cyclical climatology run, and then it is integrated from years 1996 through 2003. In this paper, the 8-year simulation at the 1 km resolution is analyzed and assessed against extensive observational data: High-Frequency (HF) radar data, current meters, Acoustic Doppler Current Profilers (ADCP) data, hydrographic measurements, tide gauges, drifters, altimeters, and radiometers. The simulation shows that the domain-scale surface circulation in the SCB is characterized by the Southern California Cyclonic Gyre, comprised of the offshore equatorward California Current System and the onshore poleward Southern California Countercurrent. The simulation also exhibits three subdomain-scale, persistent ( i.e., standing), cyclonic eddies related to the local topography and wind forcing: the Santa Barbara Channel Eddy, the Central-SCB Eddy, and the Catalina-Clemente Eddy. Comparisons with observational data reveal that ROMS reproduces a realistic mean state of the SCB oceanic circulation, as well as its interannual (mainly as a local manifestation of an ENSO event), seasonal, and intraseasonal (eddy-scale) variations. We find high correlations of the wind curl with both the alongshore pressure gradient (APG) and the eddy kinetic energy level in their variations on time scales of seasons and longer. The geostrophic currents are much stronger than the wind-driven Ekman flows at the surface. The model exhibits intrinsic eddy variability with strong topographically related heterogeneity, westward-propagating Rossby waves, and poleward-propagating coastally-trapped waves (albeit with smaller amplitude than observed due to missing high-frequency variations in the southern boundary conditions).

Grid vs Mesh: The case of Hyper-resolution Modeling in Urban Landscapes

NASA Astrophysics Data System (ADS)

Grimley, L. E.; Tijerina, D.; Khanam, M.; Tiernan, E. D.; Frazier, N.; Ogden, F. L.; Steinke, R. C.; Maxwell, R. M.; Cohen, S.

2017-12-01

In this study, the relative performance of ADHydro and GSSHA was analyzed for a small and large rainfall event in an urban watershed called Dead Run near Baltimore, Maryland. ADHydro is a physics-based, distributed, hydrologic model that uses an unstructured mesh and operates in a high performance computing environment. The Gridded Surface/Subsurface Hydrological Analysis (GSSHA) model, which is maintained by the US Army Corps of Engineers, is a physics-based, distributed, hydrologic model that incorporates subsurface utilities and uses a structured mesh. A large portion of the work served as alpha-testing of ADHydro, which is under development by the CI-WATER modeling team at the University of Wyoming. Triangular meshes at variable resolutions were created to assess the sensitivity of ADHydro to changes in resolution and test the model's ability to handle a complicated urban routing network with structures present. ADHydro was compared with GSSHA which does not have the flexibility of an unstructured grid but does incorporate the storm drainage network. The modelled runoff hydrographs were compared to observed United States Geological Survey (USGS) stream gage data. The objective of this study was to analyze the effects of mesh type and resolution using ADHydro and GSSHA in simulations of an urban watershed.

Integrating bathymetric and topographic data

NASA Astrophysics Data System (ADS)

Teh, Su Yean; Koh, Hock Lye; Lim, Yong Hui; Tan, Wai Kiat

2017-11-01

The quality of bathymetric and topographic resolution significantly affect the accuracy of tsunami run-up and inundation simulation. However, high resolution gridded bathymetric and topographic data sets for Malaysia are not freely available online. It is desirable to have seamless integration of high resolution bathymetric and topographic data. The bathymetric data available from the National Hydrographic Centre (NHC) of the Royal Malaysian Navy are in scattered form; while the topographic data from the Department of Survey and Mapping Malaysia (JUPEM) are given in regularly spaced grid systems. Hence, interpolation is required to integrate the bathymetric and topographic data into regularly-spaced grid systems for tsunami simulation. The objective of this research is to analyze the most suitable interpolation methods for integrating bathymetric and topographic data with minimal errors. We analyze four commonly used interpolation methods for generating gridded topographic and bathymetric surfaces, namely (i) Kriging, (ii) Multiquadric (MQ), (iii) Thin Plate Spline (TPS) and (iv) Inverse Distance to Power (IDP). Based upon the bathymetric and topographic data for the southern part of Penang Island, our study concluded, via qualitative visual comparison and Root Mean Square Error (RMSE) assessment, that the Kriging interpolation method produces an interpolated bathymetric and topographic surface that best approximate the admiralty nautical chart of south Penang Island.

Algebraic dynamic multilevel method for compositional flow in heterogeneous porous media

NASA Astrophysics Data System (ADS)

Cusini, Matteo; Fryer, Barnaby; van Kruijsdijk, Cor; Hajibeygi, Hadi

2018-02-01

This paper presents the algebraic dynamic multilevel method (ADM) for compositional flow in three dimensional heterogeneous porous media in presence of capillary and gravitational effects. As a significant advancement compared to the ADM for immiscible flows (Cusini et al., 2016) [33], here, mass conservation equations are solved along with k-value based thermodynamic equilibrium equations using a fully-implicit (FIM) coupling strategy. Two different fine-scale compositional formulations are considered: (1) the natural variables and (2) the overall-compositions formulation. At each Newton's iteration the fine-scale FIM Jacobian system is mapped to a dynamically defined (in space and time) multilevel nested grid. The appropriate grid resolution is chosen based on the contrast of user-defined fluid properties and on the presence of specific features (e.g., well source terms). Consistent mapping between different resolutions is performed by the means of sequences of restriction and prolongation operators. While finite-volume restriction operators are employed to ensure mass conservation at all resolutions, various prolongation operators are considered. In particular, different interpolation strategies can be used for the different primary variables, and multiscale basis functions are chosen as pressure interpolators so that fine scale heterogeneities are accurately accounted for across different resolutions. Several numerical experiments are conducted to analyse the accuracy, efficiency and robustness of the method for both 2D and 3D domains. Results show that ADM provides accurate solutions by employing only a fraction of the number of grid-cells employed in fine-scale simulations. As such, it presents a promising approach for large-scale simulations of multiphase flow in heterogeneous reservoirs with complex non-linear fluid physics.

Downscaling reanalysis data to high-resolution variables above a glacier surface (Cordillera Blanca, Peru)

NASA Astrophysics Data System (ADS)

Hofer, Marlis; Mölg, Thomas; Marzeion, Ben; Kaser, Georg

2010-05-01

Recently initiated observation networks in the Cordillera Blanca provide temporally high-resolution, yet short-term atmospheric data. The aim of this study is to extend the existing time series into the past. We present an empirical-statistical downscaling (ESD) model that links 6-hourly NCEP/NCAR reanalysis data to the local target variables, measured at the tropical glacier Artesonraju (Northern Cordillera Blanca). The approach is particular in the context of ESD for two reasons. First, the observational time series for model calibration are short (only about two years). Second, unlike most ESD studies in climate research, we focus on variables at a high temporal resolution (i.e., six-hourly values). Our target variables are two important drivers in the surface energy balance of tropical glaciers; air temperature and specific humidity. The selection of predictor fields from the reanalysis data is based on regression analyses and climatologic considerations. The ESD modelling procedure includes combined empirical orthogonal function and multiple regression analyses. Principal component screening is based on cross-validation using the Akaike Information Criterion as model selection criterion. Double cross-validation is applied for model evaluation. Potential autocorrelation in the time series is considered by defining the block length in the resampling procedure. Apart from the selection of predictor fields, the modelling procedure is automated and does not include subjective choices. We assess the ESD model sensitivity to the predictor choice by using both single- and mixed-field predictors of the variables air temperature (1000 hPa), specific humidity (1000 hPa), and zonal wind speed (500 hPa). The chosen downscaling domain ranges from 80 to 50 degrees west and from 0 to 20 degrees south. Statistical transfer functions are derived individually for different months and times of day (month/hour-models). The forecast skill of the month/hour-models largely depends on month and time of day, ranging from 0 to 0.8, but the mixed-field predictors generally perform better than the single-field predictors. At all time scales, the ESD model shows added value against two simple reference models; (i) the direct use of reanalysis grid point values, and (ii) mean diurnal and seasonal cycles over the calibration period. The ESD model forecast 1960 to 2008 clearly reflects interannual variability related to the El Niño/Southern Oscillation, but is sensitive to the chosen predictor type. So far, we have not assessed the performance of NCEP/NCAR reanalysis data against other reanalysis products. The developed ESD model is computationally cheap and applicable wherever measurements are available for model calibration.

A downscaling scheme for atmospheric variables to drive soil-vegetation-atmosphere transfer models

NASA Astrophysics Data System (ADS)

Schomburg, A.; Venema, V.; Lindau, R.; Ament, F.; Simmer, C.

2010-09-01

For driving soil-vegetation-transfer models or hydrological models, high-resolution atmospheric forcing data is needed. For most applications the resolution of atmospheric model output is too coarse. To avoid biases due to the non-linear processes, a downscaling system should predict the unresolved variability of the atmospheric forcing. For this purpose we derived a disaggregation system consisting of three steps: (1) a bi-quadratic spline-interpolation of the low-resolution data, (2) a so-called `deterministic' part, based on statistical rules between high-resolution surface variables and the desired atmospheric near-surface variables and (3) an autoregressive noise-generation step. The disaggregation system has been developed and tested based on high-resolution model output (400m horizontal grid spacing). A novel automatic search-algorithm has been developed for deriving the deterministic downscaling rules of step 2. When applied to the atmospheric variables of the lowest layer of the atmospheric COSMO-model, the disaggregation is able to adequately reconstruct the reference fields. Applying downscaling step 1 and 2, root mean square errors are decreased. Step 3 finally leads to a close match of the subgrid variability and temporal autocorrelation with the reference fields. The scheme can be applied to the output of atmospheric models, both for stand-alone offline simulations, and a fully coupled model system.

Flexible Energy Scheduling Tool for Integrating Variable Generation | Grid

Science.gov Websites

, security-constrained economic dispatch, and automatic generation control programs. DOWNLOAD PAPER Electric commitment, security-constrained economic dispatch, and automatic generation control sub-models. Each sub resolutions and operating strategies can be explored. FESTIV produces not only economic metrics but also

Evaluating Multipollutant Exposure and Urban Air Quality: Pollutant Interrelationships, Neighborhood Variability, and Nitrogen Dioxide as a Proxy Pollutant

PubMed Central

Levy, Ilan; Mihele, Cristian; Lu, Gang; Narayan, Julie; Brook, Jeffrey R.

2013-01-01

Background: Although urban air pollution is a complex mix containing multiple constituents, studies of the health effects of long-term exposure often focus on a single pollutant as a proxy for the entire mixture. A better understanding of the component pollutant concentrations and interrelationships would be useful in epidemiological studies that exploit spatial differences in exposure by clarifying the extent to which measures of individual pollutants, particularly nitrogen dioxide (NO2), represent spatial patterns in the multipollutant mixture. Objectives: We examined air pollutant concentrations and interrelationships at the intraurban scale to obtain insight into the nature of the urban mixture of air pollutants. Methods: Mobile measurements of 23 air pollutants were taken systematically at high resolution in Montreal, Quebec, Canada, over 34 days in the winter, summer, and autumn of 2009. Results: We observed variability in pollution levels and in the statistical correlations between different pollutants according to season and neighborhood. Nitrogen oxide species (nitric oxide, NO2, nitrogen oxides, and total oxidized nitrogen species) had the highest overall spatial correlations with the suite of pollutants measured. Ultrafine particles and hydrocarbon-like organic aerosol concentration, a derived measure used as a specific indicator of traffic particles, also had very high correlations. Conclusions: Our findings indicate that the multipollutant mix varies considerably throughout the city, both in time and in space, and thus, no single pollutant would be a perfect proxy measure for the entire mix under all circumstances. However, based on overall average spatial correlations with the suite of pollutants measured, nitrogen oxide species appeared to be the best available indicators of spatial variation in exposure to the outdoor urban air pollutant mixture. Citation: Levy I, Mihele C, Lu G, Narayan J, Brook JR. 2014. Evaluating multipollutant exposure and urban air quality: pollutant interrelationships, neighborhood variability, and nitrogen dioxide as a proxy pollutant. Environ Health Perspect 122:65–72; http://dx.doi.org/10.1289/ehp.1306518 PMID:24225648

High Electricity Demand in the Northeast U.S.: PJM Reliability Network and Peaking Unit Impacts on Air Quality.

PubMed

Farkas, Caroline M; Moeller, Michael D; Felder, Frank A; Henderson, Barron H; Carlton, Annmarie G

2016-08-02

On high electricity demand days, when air quality is often poor, regional transmission organizations (RTOs), such as PJM Interconnection, ensure reliability of the grid by employing peak-use electric generating units (EGUs). These "peaking units" are exempt from some federal and state air quality rules. We identify RTO assignment and peaking unit classification for EGUs in the Eastern U.S. and estimate air quality for four emission scenarios with the Community Multiscale Air Quality (CMAQ) model during the July 2006 heat wave. Further, we population-weight ambient values as a surrogate for potential population exposure. Emissions from electricity reliability networks negatively impact air quality in their own region and in neighboring geographic areas. Monitored and controlled PJM peaking units are generally located in economically depressed areas and can contribute up to 87% of hourly maximum PM2.5 mass locally. Potential population exposure to peaking unit PM2.5 mass is highest in the model domain's most populated cities. Average daily temperature and national gross domestic product steer peaking unit heat input. Air quality planning that capitalizes on a priori knowledge of local electricity demand and economics may provide a more holistic approach to protect human health within the context of growing energy needs in a changing world.

GRID3D-v2: An updated version of the GRID2D/3D computer program for generating grid systems in complex-shaped three-dimensional spatial domains

NASA Technical Reports Server (NTRS)

Steinthorsson, E.; Shih, T. I-P.; Roelke, R. J.

1991-01-01

In order to generate good quality systems for complicated three-dimensional spatial domains, the grid-generation method used must be able to exert rather precise controls over grid-point distributions. Several techniques are presented that enhance control of grid-point distribution for a class of algebraic grid-generation methods known as the two-, four-, and six-boundary methods. These techniques include variable stretching functions from bilinear interpolation, interpolating functions based on tension splines, and normalized K-factors. The techniques developed in this study were incorporated into a new version of GRID3D called GRID3D-v2. The usefulness of GRID3D-v2 was demonstrated by using it to generate a three-dimensional grid system in the coolent passage of a radial turbine blade with serpentine channels and pin fins.

A Satellite-Derived Climate-Quality Data Record of the Clear-Sky Surface Temperature of the Greenland Ice Sheet

NASA Technical Reports Server (NTRS)

Hall, Dorothy K.; Comiso, Josefino C.; DiGirolamo, Nikolo E.; Shuman, Christopher A.; Key, Jeffrey R.; Koenig, Lora S.

2012-01-01

We have developed a climate-quality data record of the clear-sky surface temperature of the Greenland Ice Sheet using the Moderate-Resolution Imaging Spectroradiometer (MODIS) ice-surface temperature (1ST) algorithm. A climate-data record (CDR) is a time series of measurements of sufficient length, consistency, and continuity to determine climate variability and change. We present daily and monthly MODIS ISTs of the Greenland Ice Sheet beginning on 1 March 2000 and continuing through 31 December 2010 at 6.25-km spatial resolution on a polar stereographic grid. This record will be elevated in status to a CDR when at least nine more years of data become available either from MODIS Terra or Aqua, or from the Visible Infrared Imager Radiometer Suite (VIIRS) to be launched in October 2011. Our ultimate goal is to develop a CDR that starts in 1981 with the Advanced Very High Resolution (AVHRR) Polar Pathfinder (APP) dataset and continues with MODIS data from 2000 to the present, and into the VIIRS era. Differences in the APP and MODIS cloud masks have so far precluded the current 1ST records from spanning both the APP and MODIS time series in a seamless manner though this will be revisited when the APP dataset has been reprocessed. The complete MODIS 1ST daily and monthly data record is available online.

Extraction and Analysis of Regional Emission and Absorption Events of Greenhouse Gases with GOSAT and OCO-2

NASA Astrophysics Data System (ADS)

Kasai, K.; Shiomi, K.; Konno, A.; Tadono, T.; Hori, M.

2016-12-01

Global observation of greenhouse gases such as carbon dioxide (CO2) and methane (CH4) with high spatio-temporal resolution and accurate estimation of sources and sinks are important to understand greenhouse gases dynamics. Greenhouse Gases Observing Satellite (GOSAT) has observed column-averaged dry-air mole fractions of CO2 (XCO2) and CH4 (XCH4) over 7 years since January 2009 with wide swath but sparse pointing. Orbiting Carbon Observatory-2 (OCO-2) has observed XCO2 jointly on orbit since July 2014 with narrow swath but high resolution. We use two retrieved datasets as GOSAT observation data. One is ACOS GOSAT/TANSO-FTS Level 2 Full Product by NASA/JPL, and the other is NIES TANSO-FTS L2 column amount (SWIR). By using these GOSAT datasets and OCO-2 L2 Full Product, the biases among datasets, local sources and sinks, and temporal variability of greenhouse gases are clarified. In addition, CarbonTracker, which is a global model of atmospheric CO2 and CH4 developed by NOAA/ESRL, are also analyzed for comparing between satellite observation data and atmospheric model data. Before analyzing these datasets, outliers are screened by using quality flag, outcome flag, and warn level in land or sea parts. Time series data of XCO2 and XCH4 are obtained globally from satellite observation and atmospheric model datasets, and functions which express typical inter-annual and seasonal variation are fitted to each spatial grid. Consequently, anomalous events of XCO2 and XCH4 are extracted by the difference between each time series dataset and the fitted function. Regional emission and absorption events are analyzed by time series variation of satellite observation data and by comparing with atmospheric model data.

The Atlanta Urban Heat Island Mitigation and Air Quality Modeling Project: How High-Resoution Remote Sensing Data Can Improve Air Quality Models

NASA Technical Reports Server (NTRS)

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

2006-01-01

The Atlanta Urban Heat Island and Air Quality Project had its genesis in Project ATLANTA (ATlanta Land use Analysis: Temperature and Air quality) that began in 1996. Project ATLANTA examined how high-spatial resolution thermal remote sensing data could be used to derive better measurements of the Urban Heat Island effect over Atlanta. We have explored how these thermal remote sensing, as well as other imaged datasets, can be used to better characterize the urban landscape for improved air quality modeling over the Atlanta area. For the air quality modeling project, the National Land Cover Dataset and the local scale Landpro99 dataset at 30m spatial resolutions have been used to derive land use/land cover characteristics for input into the MM5 mesoscale meteorological model that is one of the foundations for the Community Multiscale Air Quality (CMAQ) model to assess how these data can improve output from CMAQ. Additionally, land use changes to 2030 have been predicted using a Spatial Growth Model (SGM). SGM simulates growth around a region using population, employment and travel demand forecasts. Air quality modeling simulations were conducted using both current and future land cover. Meteorological modeling simulations indicate a 0.5 C increase in daily maximum air temperatures by 2030. Air quality modeling simulations show substantial differences in relative contributions of individual atmospheric pollutant constituents as a result of land cover change. Enhanced boundary layer mixing over the city tends to offset the increase in ozone concentration expected due to higher surface temperatures as a result of urbanization.

The indoor air we breathe.

PubMed Central

Oliver, L C; Shackleton, B W

1998-01-01

Increasingly recognized as a potential public health problem since the outbreak of Legionnaire's disease in Philadelphia in 1976, polluted indoor air has been associated with health problems that include asthma, sick building syndrome, multiple chemical sensitivity, and hypersensitivity pneumonitis. Symptoms are often nonspecific and include headache, eye and throat irritation, chest tightness and shortness of breath, and fatigue. Air-borne contaminants include commonly used chemicals, vehicular exhaust, microbial organisms, fibrous glass particles, and dust. Identified causes include defective building design and construction, aging of buildings and their ventilation systems, poor climate control, inattention to building maintenance. A major contributory factor is the explosion in the use of chemicals in building construction and furnishing materials over the past four decades. Organizational issues and psychological variables often contribute to the problem and hinder its resolution. This article describes the health problems related to poor indoor air quality and offers solutions. Images p398-a p399-a PMID:9769764

High Resolution Regional Climate Modeling for Lebanon, Eastern Mediterranean Coast

NASA Astrophysics Data System (ADS)

Katurji, Marwan; Soltanzadeh, Iman; Kuhnlein, Meike; Zawar-Reza, Peyman

2013-04-01

The Eastern Mediterranean coast consists of Lebanon, Palestine, Syria, Israel and a small part of southern Turkey. The region lies between latitudes 30 degrees S and 40 degrees N, which makes its climate affected by westerly propagating wintertime cyclones spinning off mid-latitude troughs (December, January and February), while during summer (June, July and August) the area is strongly affected by the sub-tropical anti-cyclonic belt as a result of the descending air of the Hadley cell circulation system. The area is considered to be in a transitional zone between tropical to mid-latitude climate regimes, and having a coastal topography up to 3000 m in elevation (like in the Western Ranges of Lebanon), which emphasizes the complexity of climate variability in this area under future predictions of climate change. This research incorporates both regional climate numerical simulations, Tropical Rainfall Measuring Mission (TRMM) satellite derived and surface rain gauge rainfall data to evaluate the Regional Climate Model (RegCM) version 4 ability to represent both the mean and variance of observed precipitation in the Eastern Mediterranean Region, with emphasis on the Lebanese coastal terrain and mountain ranges. The adopted methodology involves dynamically down scaling climate data from reanalysis synoptic files through a double nesting procedure. The retrospective analysis of 13 years with both 50 and 10 km spatial resolution allows for the assessment of the model results on both a climate scale and specific high intensity precipitating events. The spatial averaged mean bias error in precipitation rate for the rainy season predicted by RegCM 50 and 10 km resolution grids was 0.13 and 0.004 mm hr-1 respectively. When correlating RegCM and TRMM precipitation rate for the domain covering Lebanon's coastal mountains, the root mean square error (RMSE) for the mean quantities over the 13-year period was only 0.03, while the RMSE for the standard deviation was higher by one order of magnitude. Initial results showed good spatial variability agreement for precipitation with the satellite-derived data with improved results for the 10 km grid resolution setup. Also, results show a larger uncertainty within RegCM for predicting extreme precipitation events. Future work will investigate the ability of RegCM to simulate these extreme deviations in precipitation. The results from this research can be helpful for the better design of future regional climate down scaling predictions under climate change scenarios.

Arctic storms simulated in atmospheric general circulation models under uniform high, uniform low, and variable resolutions

NASA Astrophysics Data System (ADS)

Roesler, E. L.; Bosler, P. A.; Taylor, M.

2016-12-01

The impact of strong extratropical storms on coastal communities is large, and the extent to which storms will change with a warming Arctic is unknown. Understanding storms in reanalysis and in climate models is important for future predictions. We know that the number of detected Arctic storms in reanalysis is sensitive to grid resolution. To understand Arctic storm sensitivity to resolution in climate models, we describe simulations designed to identify and compare Arctic storms at uniform low resolution (1 degree), at uniform high resolution (1/8 degree), and at variable resolution (1 degree to 1/8 degree). High-resolution simulations resolve more fine-scale structure and extremes, such as storms, in the atmosphere than a uniform low-resolution simulation. However, the computational cost of running a globally uniform high-resolution simulation is often prohibitive. The variable resolution tool in atmospheric general circulation models permits regional high-resolution solutions at a fraction of the computational cost. The storms are identified using the open-source search algorithm, Stride Search. The uniform high-resolution simulation has over 50% more storms than the uniform low-resolution and over 25% more storms than the variable resolution simulations. Storm statistics from each of the simulations is presented and compared with reanalysis. We propose variable resolution as a cost-effective means of investigating physics/dynamics coupling in the Arctic environment. Future work will include comparisons with observed storms to investigate tuning parameters for high resolution models. Sandia National Laboratories is a multi-program laboratory managed and operated by Sandia Corporation, a wholly owned subsidiary of Lockheed Martin Corporation, for the U.S. Department of Energy's National Nuclear Security Administration under contract DE-AC04-94AL85000. SAND2016-7402 A

Seasonal and spatial variation in broadleaf forest model parameters

NASA Astrophysics Data System (ADS)

Groenendijk, M.; van der Molen, M. K.; Dolman, A. J.

2009-04-01

Process based, coupled ecosystem carbon, energy and water cycle models are used with the ultimate goal to project the effect of future climate change on the terrestrial carbon cycle. A typical dilemma in such exercises is how much detail the model must be given to describe the observations reasonably realistic while also be general. We use a simple vegetation model (5PM) with five model parameters to study the variability of the parameters. These parameters are derived from the observed carbon and water fluxes from the FLUXNET database. For 15 broadleaf forests the model parameters were derived for different time resolutions. It appears that in general for all forests, the correlation coefficient between observed and simulated carbon and water fluxes improves with a higher parameter time resolution. The quality of the simulations is thus always better when a higher time resolution is used. These results show that annual parameters are not capable of properly describing weather effects on ecosystem fluxes, and that two day time resolution yields the best results. A first indication of the climate constraints can be found by the seasonal variation of the covariance between Jm, which describes the maximum electron transport for photosynthesis, and climate variables. A general seasonality we found is that during winter the covariance with all climate variables is zero. Jm increases rapidly after initial spring warming, resulting in a large covariance with air temperature and global radiation. During summer Jm is less variable, but co-varies negatively with air temperature and vapour pressure deficit and positively with soil water content. A temperature response appears during spring and autumn for broadleaf forests. This shows that an annual model parameter cannot be representative for the entire year. And relations with mean annual temperature are not possible. During summer the photosynthesis parameters are constrained by water availability, soil water content and vapour pressure deficit.

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

Sakaguchi, Koichi; Leung, Lai-Yung R.; Zhao, Chun

This study presents a diagnosis of a multi-resolution approach using the Model for Prediction Across Scales - Atmosphere (MPAS-A) for simulating regional climate. Four AMIP experiments are conducted for 1999-2009. In the first two experiments, MPAS-A is configured using global quasi-uniform grids at 120 km and 30 km grid spacing. In the other two experiments, MPAS-A is configured using variable-resolution (VR) mesh with local refinement at 30 km over North America and South America embedded inside a quasi-uniform domain at 120 km elsewhere. Precipitation and related fields in the four simulations are examined to determine how well the VR simulationsmore » reproduce the features simulated by the globally high-resolution model in the refined domain. In previous analyses of idealized aqua-planet simulations, the characteristics of the global high-resolution simulation in moist processes only developed near the boundary of the refined region. In contrast, the AMIP simulations with VR grids are able to reproduce the high-resolution characteristics across the refined domain, particularly in South America. This indicates the importance of finely resolved lower-boundary forcing such as topography and surface heterogeneity for the regional climate, and demonstrates the ability of the MPAS-A VR to replicate the large-scale moisture transport as simulated in the quasi-uniform high-resolution model. Outside of the refined domain, some upscale effects are detected through large-scale circulation but the overall climatic signals are not significant at regional scales. Our results provide support for the multi-resolution approach as a computationally efficient and physically consistent method for modeling regional climate.« less

Optimal resolution in maximum entropy image reconstruction from projections with multigrid acceleration

NASA Technical Reports Server (NTRS)

Limber, Mark A.; Manteuffel, Thomas A.; Mccormick, Stephen F.; Sholl, David S.

1993-01-01

We consider the problem of image reconstruction from a finite number of projections over the space L(sup 1)(Omega), where Omega is a compact subset of the set of Real numbers (exp 2). We prove that, given a discretization of the projection space, the function that generates the correct projection data and maximizes the Boltzmann-Shannon entropy is piecewise constant on a certain discretization of Omega, which we call the 'optimal grid'. It is on this grid that one obtains the maximum resolution given the problem setup. The size of this grid grows very quickly as the number of projections and number of cells per projection grow, indicating fast computational methods are essential to make its use feasible. We use a Fenchel duality formulation of the problem to keep the number of variables small while still using the optimal discretization, and propose a multilevel scheme to improve convergence of a simple cyclic maximization scheme applied to the dual problem.

High resolution modeling of the upper troposphere and lower stratosphere region over the Arctic - GEM-AC simulations for the future climate with and without aviation emissions.

NASA Astrophysics Data System (ADS)

Porebska, Magdalena; Struzewska, Joanna; Kaminski, Jacek W.

2016-04-01

Upper troposphere and lower stratosphere (UTLS) region is a layer around the tropopause. Perturbation of the chemical composition in the UTLS region can impact physical and dynamical processes that can lead to changes in cloudiness, precipitation, radiative forcing, stratosphere-troposphere exchange and zonal flow. The objective of this study is to investigate the potential impacts of aviation emissions on the upper troposphere and lower stratosphere. In order to assess the impact of the aviation emissions we will focus on changes in atmospheric dynamic due to changes in chemical composition in the UTLS over the Arctic. Specifically, we will assess perturbations in the distribution of the wind, temperature and pressure fields in the UTLS region. Our study will be based on simulations using a high resolution chemical weather model for four scenarios of current (2006) and future (2050) climate: with and without aircraft emissions. The tool that we use is the GEM-AC (Global Environmental Multiscale with Atmospheric Chemistry) chemical weather model where air quality, free tropospheric and stratospheric chemistry processes are on-line and interactive in an operational weather forecast model of Environment Canada. In vertical, the model domain is defined on 70 hybrid levels with model top at 0.1 mb. The gas-phase chemistry includes detailed reactions of Ox, NOx, HOx, CO, CH4, ClOx and BrO. Also, the model can address aerosol microphysics and gas-aerosol partitioning. Aircraft emissions are from the AEDT 2006 database developed by the Federal Aviation Administration (USA) and the future climate simulations are based on RCP8.5 projection presented by the IPCC in the fifth Assessment Report AR5. Results from model simulations on a global variable grid with 0.5o x 0.5o uniform resolution over the Arctic will be presented.

The Impact of Future Emissions Changes on Air Pollution Concentrations and Related Human Health Effects

NASA Astrophysics Data System (ADS)

Mikolajczyk, U.; Suppan, P.; Williams, M.

2015-12-01

Quantification of potential health benefits of reductions in air pollution on the local scale is becoming increasingly important. The aim of this study is to conduct health impact assessment (HIA) by utilizing regionally and spatially specific data in order to assess the influence of future emission scenarios on human health. In the first stage of this investigation, a modeling study was carried out using the Weather Research and Forecasting (WRF) model coupled with Chemistry to estimate ambient concentrations of air pollutants for the baseline year 2009, and for the future emission scenarios in southern Germany. Anthropogenic emissions for the baseline year 2009 are derived from the emission inventory provided by the Netherlands Organization of Applied Scientific Research (TNO) (Denier van der Gon et al., 2010). For Germany, the TNO emissions were replaced by gridded emission data with a high spatial resolution of 1/64 x 1/64 degrees. Future air quality simulations are carried out under different emission scenarios, which reflect possible energy and climate measures in year 2030. The model set-up included a nesting approach, where three domains with horizontal resolution of 18 km, 6 km and 2 km were defined. The simulation results for the baseline year 2009 are used to quantify present-day health burdens. Concentration-response functions (CRFs) for PM2.5 and NO2 from the WHO Health risks of air Pollution in Europe (HRAPIE) project were applied to population-weighted mean concentrations to estimate relative risks and hence to determine numbers of attributable deaths and associated life-years lost. In the next step, future health impacts of projected concentrations were calculated taking into account different emissions scenarios. The health benefits that we assume with air pollution reductions can be used to provide options for future policy decisions to protect public health.

Improving the quality of marine geophysical track line data: Along-track analysis

NASA Astrophysics Data System (ADS)

Chandler, Michael T.; Wessel, Paul

2008-02-01

We have examined 4918 track line geophysics cruises archived at the U.S. National Geophysical Data Center (NGDC) using comprehensive error checking methods. Each cruise was checked for observation outliers, excessive gradients, metadata consistency, and general agreement with satellite altimetry-derived gravity and predicted bathymetry grids. Thresholds for error checking were determined empirically through inspection of histograms for all geophysical values, gradients, and differences with gridded data sampled along ship tracks. Robust regression was used to detect systematic scale and offset errors found by comparing ship bathymetry and free-air anomalies to the corresponding values from global grids. We found many recurring error types in the NGDC archive, including poor navigation, inappropriately scaled or offset data, excessive gradients, and extended offsets in depth and gravity when compared to global grids. While ˜5-10% of bathymetry and free-air gravity records fail our conservative tests, residual magnetic errors may exceed twice this proportion. These errors hinder the effective use of the data and may lead to mistakes in interpretation. To enable the removal of gross errors without over-writing original cruise data, we developed an errata system that concisely reports all errors encountered in a cruise. With such errata files, scientists may share cruise corrections, thereby preventing redundant processing. We have implemented these quality control methods in the modified MGD77 supplement to the Generic Mapping Tools software suite.

Potential air quality benefits from increased solar photovoltaic electricity generation in the Eastern United States

NASA Astrophysics Data System (ADS)

Abel, David; Holloway, Tracey; Harkey, Monica; Rrushaj, Arber; Brinkman, Greg; Duran, Phillip; Janssen, Mark; Denholm, Paul

2018-02-01

We evaluate how fine particulate matter (PM2.5) and precursor emissions could be reduced if 17% of electricity generation was replaced with solar photovoltaics (PV) in the Eastern United States. Electricity generation is simulated using GridView, then used to scale electricity-sector emissions of sulfur dioxide (SO2) and nitrogen oxides (NOX) from an existing gridded inventory of air emissions. This approach offers a novel method to leverage advanced electricity simulations with state-of-the-art emissions inventories, without necessitating recalculation of emissions for each facility. The baseline and perturbed emissions are input to the Community Multiscale Air Quality Model (CMAQ version 4.7.1) for a full accounting of time- and space-varying air quality changes associated with the 17% PV scenario. These results offer a high-value opportunity to evaluate the reduced-form AVoided Emissions and geneRation Tool (AVERT), while using AVERT to test the sensitivity of results to changing base-years and levels of solar integration. We find that average NOX and SO2 emissions across the region decrease 20% and 15%, respectively. PM2.5 concentrations decreased on average 4.7% across the Eastern U.S., with nitrate (NO3-) PM2.5 decreasing 3.7% and sulfate (SO42-) PM2.5 decreasing 9.1%. In the five largest cities in the region, we find that the most polluted days show the most significant PM2.5 decrease under the 17% PV generation scenario, and that the greatest benefits are accrued to cities in or near the Ohio River Valley. We find summer health benefits from reduced PM2.5 exposure estimated as 1424 avoided premature deaths (95% Confidence Interval (CI): 284 deaths, 2 732 deaths) or a health savings of 13.1 billion (95% CI: 0.6 billion, 43.9 billion) These results highlight the potential for renewable energy as a tool for air quality managers to support current and future health-based air quality regulations.

An Updating System for the Gridded Population Database of China Based on Remote Sensing, GIS and Spatial Database Technologies.

PubMed

Yang, Xiaohuan; Huang, Yaohuan; Dong, Pinliang; Jiang, Dong; Liu, Honghui

2009-01-01

The spatial distribution of population is closely related to land use and land cover (LULC) patterns on both regional and global scales. Population can be redistributed onto geo-referenced square grids according to this relation. In the past decades, various approaches to monitoring LULC using remote sensing and Geographic Information Systems (GIS) have been developed, which makes it possible for efficient updating of geo-referenced population data. A Spatial Population Updating System (SPUS) is developed for updating the gridded population database of China based on remote sensing, GIS and spatial database technologies, with a spatial resolution of 1 km by 1 km. The SPUS can process standard Moderate Resolution Imaging Spectroradiometer (MODIS L1B) data integrated with a Pattern Decomposition Method (PDM) and an LULC-Conversion Model to obtain patterns of land use and land cover, and provide input parameters for a Population Spatialization Model (PSM). The PSM embedded in SPUS is used for generating 1 km by 1 km gridded population data in each population distribution region based on natural and socio-economic variables. Validation results from finer township-level census data of Yishui County suggest that the gridded population database produced by the SPUS is reliable.

Power Quality Control and Design of Power Converter for Variable-Speed Wind Energy Conversion System with Permanent-Magnet Synchronous Generator

PubMed Central

Oğuz, Yüksel; Güney, İrfan; Çalık, Hüseyin

2013-01-01

The control strategy and design of an AC/DC/AC IGBT-PMW power converter for PMSG-based variable-speed wind energy conversion systems (VSWECS) operation in grid/load-connected mode are presented. VSWECS consists of a PMSG connected to a AC-DC IGBT-based PWM rectifier and a DC/AC IGBT-based PWM inverter with LCL filter. In VSWECS, AC/DC/AC power converter is employed to convert the variable frequency variable speed generator output to the fixed frequency fixed voltage grid. The DC/AC power conversion has been managed out using adaptive neurofuzzy controlled inverter located at the output of controlled AC/DC IGBT-based PWM rectifier. In this study, the dynamic performance and power quality of the proposed power converter connected to the grid/load by output LCL filter is focused on. Dynamic modeling and control of the VSWECS with the proposed power converter is performed by using MATLAB/Simulink. Simulation results show that the output voltage, power, and frequency of VSWECS reach to desirable operation values in a very short time. In addition, when PMSG based VSWECS works continuously with the 4.5 kHz switching frequency, the THD rate of voltage in the load terminal is 0.00672%. PMID:24453905

Power quality control and design of power converter for variable-speed wind energy conversion system with permanent-magnet synchronous generator.

PubMed

Oğuz, Yüksel; Güney, İrfan; Çalık, Hüseyin

2013-01-01

The control strategy and design of an AC/DC/AC IGBT-PMW power converter for PMSG-based variable-speed wind energy conversion systems (VSWECS) operation in grid/load-connected mode are presented. VSWECS consists of a PMSG connected to a AC-DC IGBT-based PWM rectifier and a DC/AC IGBT-based PWM inverter with LCL filter. In VSWECS, AC/DC/AC power converter is employed to convert the variable frequency variable speed generator output to the fixed frequency fixed voltage grid. The DC/AC power conversion has been managed out using adaptive neurofuzzy controlled inverter located at the output of controlled AC/DC IGBT-based PWM rectifier. In this study, the dynamic performance and power quality of the proposed power converter connected to the grid/load by output LCL filter is focused on. Dynamic modeling and control of the VSWECS with the proposed power converter is performed by using MATLAB/Simulink. Simulation results show that the output voltage, power, and frequency of VSWECS reach to desirable operation values in a very short time. In addition, when PMSG based VSWECS works continuously with the 4.5 kHz switching frequency, the THD rate of voltage in the load terminal is 0.00672%.

Simulation of population-based commuter exposure to NO₂ using different air pollution models.

PubMed

Ragettli, Martina S; Tsai, Ming-Yi; Braun-Fahrländer, Charlotte; de Nazelle, Audrey; Schindler, Christian; Ineichen, Alex; Ducret-Stich, Regina E; Perez, Laura; Probst-Hensch, Nicole; Künzli, Nino; Phuleria, Harish C

2014-05-12

We simulated commuter routes and long-term exposure to traffic-related air pollution during commute in a representative population sample in Basel (Switzerland), and evaluated three air pollution models with different spatial resolution for estimating commute exposures to nitrogen dioxide (NO2) as a marker of long-term exposure to traffic-related air pollution. Our approach includes spatially and temporally resolved data on actual commuter routes, travel modes and three air pollution models. Annual mean NO2 commuter exposures were similar between models. However, we found more within-city and within-subject variability in annual mean (±SD) NO2 commuter exposure with a high resolution dispersion model (40 ± 7 µg m(-3), range: 21-61) than with a dispersion model with a lower resolution (39 ± 5 µg m(-3); range: 24-51), and a land use regression model (41 ± 5 µg m(-3); range: 24-54). Highest median cumulative exposures were calculated along motorized transport and bicycle routes, and the lowest for walking. For estimating commuter exposure within a city and being interested also in small-scale variability between roads, a model with a high resolution is recommended. For larger scale epidemiological health assessment studies, models with a coarser spatial resolution are likely sufficient, especially when study areas include suburban and rural areas.

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

NASA Astrophysics Data System (ADS)

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

2016-04-01

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

A New Integrated Weighted Model in SNOW-V10: Verification of Categorical Variables

NASA Astrophysics Data System (ADS)

Huang, Laura X.; Isaac, George A.; Sheng, Grant

2014-01-01

This paper presents the verification results for nowcasts of seven categorical variables from an integrated weighted model (INTW) and the underlying numerical weather prediction (NWP) models. Nowcasting, or short range forecasting (0-6 h), over complex terrain with sufficient accuracy is highly desirable but a very challenging task. A weighting, evaluation, bias correction and integration system (WEBIS) for generating nowcasts by integrating NWP forecasts and high frequency observations was used during the Vancouver 2010 Olympic and Paralympic Winter Games as part of the Science of Nowcasting Olympic Weather for Vancouver 2010 (SNOW-V10) project. Forecast data from Canadian high-resolution deterministic NWP system with three nested grids (at 15-, 2.5- and 1-km horizontal grid-spacing) were selected as background gridded data for generating the integrated nowcasts. Seven forecast variables of temperature, relative humidity, wind speed, wind gust, visibility, ceiling and precipitation rate are treated as categorical variables for verifying the integrated weighted forecasts. By analyzing the verification of forecasts from INTW and the NWP models among 15 sites, the integrated weighted model was found to produce more accurate forecasts for the 7 selected forecast variables, regardless of location. This is based on the multi-categorical Heidke skill scores for the test period 12 February to 21 March 2010.

A global data set of soil hydraulic properties and sub-grid variability of soil water retention and hydraulic conductivity curves

NASA Astrophysics Data System (ADS)

Montzka, Carsten; Herbst, Michael; Weihermüller, Lutz; Verhoef, Anne; Vereecken, Harry

2017-07-01

Agroecosystem models, regional and global climate models, and numerical weather prediction models require adequate parameterization of soil hydraulic properties. These properties are fundamental for describing and predicting water and energy exchange processes at the transition zone between solid earth and atmosphere, and regulate evapotranspiration, infiltration and runoff generation. Hydraulic parameters describing the soil water retention (WRC) and hydraulic conductivity (HCC) curves are typically derived from soil texture via pedotransfer functions (PTFs). Resampling of those parameters for specific model grids is typically performed by different aggregation approaches such a spatial averaging and the use of dominant textural properties or soil classes. These aggregation approaches introduce uncertainty, bias and parameter inconsistencies throughout spatial scales due to nonlinear relationships between hydraulic parameters and soil texture. Therefore, we present a method to scale hydraulic parameters to individual model grids and provide a global data set that overcomes the mentioned problems. The approach is based on Miller-Miller scaling in the relaxed form by Warrick, that fits the parameters of the WRC through all sub-grid WRCs to provide an effective parameterization for the grid cell at model resolution; at the same time it preserves the information of sub-grid variability of the water retention curve by deriving local scaling parameters. Based on the Mualem-van Genuchten approach we also derive the unsaturated hydraulic conductivity from the water retention functions, thereby assuming that the local parameters are also valid for this function. In addition, via the Warrick scaling parameter λ, information on global sub-grid scaling variance is given that enables modellers to improve dynamical downscaling of (regional) climate models or to perturb hydraulic parameters for model ensemble output generation. The present analysis is based on the ROSETTA PTF of Schaap et al. (2001) applied to the SoilGrids1km data set of Hengl et al. (2014). The example data set is provided at a global resolution of 0.25° at https://doi.org/10.1594/PANGAEA.870605.

Investigation of Multi-decadal Trends in Aerosol Direct Radiative Effects over North America using a Coupled Meteorology-Chemistry Model

NASA Astrophysics Data System (ADS)

Mathur, R.; Pleim, J.; Wong, D.; Wei, C.; Xing, J.; Gan, M.; Yu, S.; Binkowski, F.

2012-12-01

While aerosol radiative effects have been recognized as some of the largest sources of uncertainty among the forcers of climate change, there has been little effort devoted to verification of the spatial and temporal variability of the magnitude and directionality of aerosol radiative forcing. A comprehensive investigation of the processes regulating aerosol distributions, their optical properties, and their radiative effects and verification of their simulated effects for past conditions relative to measurements is needed in order to build confidence in the estimates of the projected impacts arising from changes in both anthropogenic forcing and climate change. This study aims at addressing this issue through a systematic investigation of changes in anthropogenic emissions of SO2 and NOx over the past two decades in the United States, their impacts on anthropogenic aerosol loading in the North American troposphere, and subsequent impacts on regional radiation budgets. A newly developed 2-way coupled meteorology and air pollution model composed of the Weather Research and Forecasting (WRF) model and the Community Multiscale Air Quality (CMAQ) model is being run for 20 years (1990 - 2010) on a 12 km resolution grid that covers most of North America including the entire conterminous US. During this period US emissions of SO2 and NOx have been reduced by about 66% and 50%, respectively, mainly due to Title IV of the U.S. Clean Air Act Amendments (CAA) that aimed to reduce emissions that contribute to acid deposition. A methodology is developed to consistently estimate emission inventories for the 20-year period accounting for air quality regulations as well as population trends, economic conditions, and technology changes in motor vehicles and electric power generation. The coupled WRF-CMAQ model includes detailed treatment of direct effects of aerosols on photolysis rates as well as on shortwave radiation and the direct effects of tropospheric ozone on the long-wave. New algorithms for the calculation of aerosol optical properties and radiation have been developed by considering both computational efficiency and more realistic aerosol states. Additionally, treatment of aerosol indirect effects on clouds has also recently been implemented. Analysis of measurements of aerosol composition, radiation, and associated variables, over the past two decades will be presented which indicate significant reductions in the tropospheric aerosol burden as well as an increase in down-welling shortwave radiation at numerous sites across the U.S. Initial applications of the coupled WRF-CMAQ model for time-periods pre and post the implementation of Title IV of the CAA will be discussed and comparisons with measurements to assess the model's ability to capture trends in aerosol burden, composition, and direct aerosol effects on surface shortwave radiation will be presented.

Investigating the use of an antiscatter grid in chest radiography for average adults with a computed radiography imaging system

PubMed Central

Wood, T J; Avery, G; Balcam, S; Needler, L; Smith, A; Saunderson, J R; Beavis, A W

2015-01-01

Objective: The aim of this study was to investigate via simulation a proposed change to clinical practice for chest radiography. The validity of using a scatter rejection grid across the diagnostic energy range (60–125 kVp), in conjunction with appropriate tube current–time product (mAs) for imaging with a computed radiography (CR) system was investigated. Methods: A digitally reconstructed radiograph algorithm was used, which was capable of simulating CR chest radiographs with various tube voltages, receptor doses and scatter rejection methods. Four experienced image evaluators graded images with a grid (n = 80) at tube voltages across the diagnostic energy range and varying detector air kermas. These were scored against corresponding images reconstructed without a grid, as per current clinical protocol. Results: For all patients, diagnostic image quality improved with the use of a grid, without the need to increase tube mAs (and therefore patient dose), irrespective of the tube voltage used. Increasing tube mAs by an amount determined by the Bucky factor made little difference to image quality. Conclusion: A virtual clinical trial has been performed with simulated chest CR images. Results indicate that the use of a grid improves diagnostic image quality for average adults, without the need to increase tube mAs, even at low tube voltages. Advances in knowledge: Validated with images containing realistic anatomical noise, it is possible to improve image quality by utilizing grids for chest radiography with CR systems without increasing patient exposure. Increasing tube mAs by an amount determined by the Bucky factor is not justified. PMID:25571914

Multidecadal simulation of coastal fog with a regional climate model

NASA Astrophysics Data System (ADS)

O'Brien, Travis A.; Sloan, Lisa C.; Chuang, Patrick Y.; Faloona, Ian C.; Johnstone, James A.

2013-06-01

In order to model stratocumulus clouds and coastal fog, we have coupled the University of Washington boundary layer model to the regional climate model, RegCM (RegCM-UW). By comparing fog occurrences observed at various coastal airports in the western United States, we show that RegCM-UW has success at modeling the spatial and temporal (diurnal, seasonal, and interannual) climatology of northern California coastal fog. The quality of the modeled fog estimate depends on whether coast-adjacent ocean or land grid cells are used; for the model runs shown here, the oceanic grid cells seem to be most appropriate. The interannual variability of oceanic northern California summertime fog, from a multi-decadal simulation, has a high and statistically significant correlation with the observed interannual variability ( r = 0.72), which indicates that RegCM-UW is capable of investigating the response of fog to long-term climatological forcing. While RegCM-UW has a number of aspects that would benefit from further investigation and development, RegCM-UW is a new tool for investigating the climatology of coastal fog and the physical processes that govern it. We expect that with appropriate physical parameterizations and moderate horizontal resolution, other climate models should be capable of simulating coastal fog. The source code for RegCM-UW is publicly available, under the GNU license, through the International Centre for Theoretical Physics.

A Satellite-Derived Climate-Quality Data Record of the Clear-Sky Surface Temperature of the Greenland Ice Sheet

NASA Technical Reports Server (NTRS)

Hall, Dorothy K.; Comiso, Josefino C.; DiGirolamo, Nicolo E.; Shuman, Christopher A.; Key, Jeffrey R.; Koenig, Lora S.

2011-01-01

We have developed a climate-quality data record of the clear-sky surface temperature of the Greenland Ice Sheet using the Moderate-Resolution Imaging Spectroradiometer (MODIS) Terra ice-surface temperature (1ST) algorithm. A climate-data record (CDR) is a time series of measurements of sufficient length, consistency, and continuity to determine climate variability and change. We present daily and monthly Terra MODIS ISTs of the Greenland Ice Sheet beginning on 1 March 2000 and continuing through 31 December 2010 at 6.25-km spatial resolution on a polar stereographic grid within +/-3 hours of 17:00Z or 2:00 PM Local Solar Time. Preliminary validation of the ISTs at Summit Camp, Greenland, during the 2008-09 winter, shows that there is a cold bias using the MODIS IST which underestimates the measured surface temperature by approximately 3 C when temperatures range from approximately -50 C to approximately -35 C. The ultimate goal is to develop a CDR that starts in 1981 with the Advanced Very High Resolution (AVHRR) Polar Pathfinder (APP) dataset and continues with MODIS data from 2000 to the present. Differences in the APP and MODIS cloud masks have so far precluded the current IST records from spanning both the APP and MODIS IST time series in a seamless manner though this will be revisited when the APP dataset has been reprocessed. The Greenland IST climate-quality data record is suitable for continuation using future Visible Infrared Imager Radiometer Suite (VIIRS) data and will be elevated in status to a CDR when at least 9 more years of climate-quality data become available either from MODIS Terra or Aqua, or from the VIIRS. The complete MODIS IST data record will be available online in the summer of 2011.

Evaluation of downscaled, gridded climate data for the conterminous United States

USGS Publications Warehouse

Robert J. Behnke,; Stephen J. Vavrus,; Andrew Allstadt,; Thomas P. Albright,; Thogmartin, Wayne E.; Volker C. Radeloff,

2016-01-01

Weather and climate affect many ecological processes, making spatially continuous yet fine-resolution weather data desirable for ecological research and predictions. Numerous downscaled weather data sets exist, but little attempt has been made to evaluate them systematically. Here we address this shortcoming by focusing on four major questions: (1) How accurate are downscaled, gridded climate data sets in terms of temperature and precipitation estimates?, (2) Are there significant regional differences in accuracy among data sets?, (3) How accurate are their mean values compared with extremes?, and (4) Does their accuracy depend on spatial resolution? We compared eight widely used downscaled data sets that provide gridded daily weather data for recent decades across the United States. We found considerable differences among data sets and between downscaled and weather station data. Temperature is represented more accurately than precipitation, and climate averages are more accurate than weather extremes. The data set exhibiting the best agreement with station data varies among ecoregions. Surprisingly, the accuracy of the data sets does not depend on spatial resolution. Although some inherent differences among data sets and weather station data are to be expected, our findings highlight how much different interpolation methods affect downscaled weather data, even for local comparisons with nearby weather stations located inside a grid cell. More broadly, our results highlight the need for careful consideration among different available data sets in terms of which variables they describe best, where they perform best, and their resolution, when selecting a downscaled weather data set for a given ecological application.

Assessing the impacts of seasonal and vertical atmospheric conditions on air quality over the Pearl River Delta region

NASA Astrophysics Data System (ADS)

Tong, Cheuk Hei Marcus; Yim, Steve Hung Lam; Rothenberg, Daniel; Wang, Chien; Lin, Chuan-Yao; Chen, Yongqin David; Lau, Ngar Cheung

2018-05-01

Air pollution is an increasingly concerning problem in many metropolitan areas due to its adverse public health and environmental impacts. Vertical atmospheric conditions have strong effects on vertical mixing of air pollutants, which directly affects surface air quality. The characteristics and magnitude of how vertical atmospheric conditions affect surface air quality, which are critical to future air quality projections, have not yet been fully understood. This study aims to enhance understanding of the annual and seasonal sensitivities of air pollution to both surface and vertical atmospheric conditions. Based on both surface and vertical meteorological characteristics provided by 1994-2003 monthly dynamic downscaling data from the Weather and Research Forecast Model, we develop generalized linear models (GLMs) to study the relationships between surface air pollutants (ozone, respirable suspended particulates, and sulfur dioxide) and atmospheric conditions in the Pearl River Delta (PRD) region. Applying Principal Component Regression (PCR) to address multi-collinearity, we study the contributions of various meteorological variables to pollutants' concentration levels based on the loading and model coefficient of major principal components. Our results show that relatively high pollutant concentration occurs under relatively low mid-level troposphere temperature gradients, low relative humidity, weak southerly wind (or strong northerly wind) and weak westerly wind (or strong easterly wind). Moreover, the correlations vary among pollutant species, seasons, and meteorological variables at various altitudes. In general, pollutant sensitivity to meteorological variables is found to be greater in winter than in other seasons, and the sensitivity of ozone to meteorology differs from that of the other two pollutants. Applying our GLMs to anomalous air pollution episodes, we find that meteorological variables up to mid troposphere (∼700 mb) play an important role in influencing surface air quality, pinpointing the significant and unique associations between meteorological variables at higher altitudes and surface air quality.

Impact of Model Resolution and Snow Cover Modification on the Performance of Weather Forecasting and Research (WRF) Models of Winter Conditions that Contribute to Ozone Pollution in the Uintah Basin, Eastern Utah, Winter 2013. Trang T. Tran, Marc Mansfield and Seth Lyman Bingham Research Center, Utah State University

NASA Astrophysics Data System (ADS)

Tran, T. T.; Mansfield, M. L.; Lyman, S.

2013-12-01

The Uintah Basin of Eastern Utah, USA, has experienced winter ozone pollution events with ozone concentrations exceeding the National Ambient Air Quality Standard of 75 ppb. With a total of four winter seasons of ozone sampling, winter 2013 is the worst on record for ozone pollution in the basin. Emissions of volatile organic compounds (VOCs) and nitrogen oxides (NOx) from oil and gas industries and other activities provide the precursors for ozone formation. The chemical mechanism of ozone formation is non-linear and complicated depending on the availability of VOCs and NOx. Moreover, meteorological conditions also play an important role in triggering ozone pollution. In the Uintah Basin, high albedo due to snow cover, a 'bowl-shaped' terrain, and strong inversions that trap precursors within the boundary layer are important factors contributing to ozone pollution. However, these local meteorological phenomena have been misrepresented by recent numerical modeling studies, probably due to misrepresenting the snow cover and complex terrain of the basin. In this study, Weather Research and Forecasting (WRF) simulations are performed on a model domain covering the entire Uintah Basin for winter 2013 (Dec 2012 - Mar 2013) to test the impacts of several grid resolutions (e.g., 4000, 1300 and 800m) and snow cover modification on performance of models of the local weather conditions of the basin. These sensitivity tests help to determine the best model configurations to produce appropriate meteorological input for air-quality simulations.

Development of Spatiotemporal Bias-Correction Techniques for Downscaling GCM Predictions

NASA Astrophysics Data System (ADS)

Hwang, S.; Graham, W. D.; Geurink, J.; Adams, A.; Martinez, C. J.

2010-12-01

Accurately representing the spatial variability of precipitation is an important factor for predicting watershed response to climatic forcing, particularly in small, low-relief watersheds affected by convective storm systems. Although Global Circulation Models (GCMs) generally preserve spatial relationships between large-scale and local-scale mean precipitation trends, most GCM downscaling techniques focus on preserving only observed temporal variability on point by point basis, not spatial patterns of events. Downscaled GCM results (e.g., CMIP3 ensembles) have been widely used to predict hydrologic implications of climate variability and climate change in large snow-dominated river basins in the western United States (Diffenbaugh et al., 2008; Adam et al., 2009). However fewer applications to smaller rain-driven river basins in the southeastern US (where preserving spatial variability of rainfall patterns may be more important) have been reported. In this study a new method was developed to bias-correct GCMs to preserve both the long term temporal mean and variance of the precipitation data, and the spatial structure of daily precipitation fields. Forty-year retrospective simulations (1960-1999) from 16 GCMs were collected (IPCC, 2007; WCRP CMIP3 multi-model database: https://esg.llnl.gov:8443/), and the daily precipitation data at coarse resolution (i.e., 280km) were interpolated to 12km spatial resolution and bias corrected using gridded observations over the state of Florida (Maurer et al., 2002; Wood et al, 2002; Wood et al, 2004). In this method spatial random fields which preserved the observed spatial correlation structure of the historic gridded observations and the spatial mean corresponding to the coarse scale GCM daily rainfall were generated. The spatiotemporal variability of the spatio-temporally bias-corrected GCMs were evaluated against gridded observations, and compared to the original temporally bias-corrected and downscaled CMIP3 data for the central Florida. The hydrologic response of two southwest Florida watersheds to the gridded observation data, the original bias corrected CMIP3 data, and the new spatiotemporally corrected CMIP3 predictions was compared using an integrated surface-subsurface hydrologic model developed by Tampa Bay Water.

Uncertainty in air quality observations using low-cost sensors

NASA Astrophysics Data System (ADS)

Castell, Nuria; Dauge, Franck R.; Dongol, Rozina; Vogt, Matthias; Schneider, Philipp

2016-04-01

Air pollution poses a threat to human health, and the WHO has classified air pollution as the world's largest single environmental health risk. In Europe, the majority of the population lives in areas where air quality levels frequently exceed WHO's ambient air quality guidelines. The emergence of low-cost, user-friendly and very compact air pollution platforms allowing observations at high spatial resolution in near real-time, provides us with new opportunities to simultaneously enhance existing monitoring systems as well as enable citizens to engage in more active environmental monitoring (citizen science). However the data sets generated by low-cost sensors show often questionable data quality. For many sensors, neither their error characteristics nor how their measurement capability holds up over time or through a range of environmental conditions, have been evaluated. We have conducted an exhaustive evaluation of the commercial low-cost platform AQMesh (measuring NO, NO2, CO, O3, PM10 and PM2.5) in laboratory and in real-world conditions in the city of Oslo (Norway). Co-locations in field of 24 platforms were conducted over a 6 month period (April to September 2015) allowing to characterize the temporal variability in the performance. Additionally, the field performance included the characterization on different monitoring urban monitoring sites characteristic of both traffic and background conditions. All the evaluations have been conducted against CEN reference method analyzers maintained according to the Norwegian National Reference Laboratory quality system. The results show clearly that a good performance in laboratory does not imply similar performance in real-world outdoor conditions. Moreover, laboratory calibration is not suitable for subsequent measurements in urban environments. In order to reduce the errors, sensors require on-site field calibration. Even after such field calibration, the platforms show a significant variability in the performance due to changes in the environmental conditions. Currently there is a lack of testing to ensure adequate sensor performance prior to marketing such instruments. Even when manufacturers provide detailed specification sheets, there is little guarantee that the specifications can actually be met in real-world conditions. Data quality is a pertinent concern, especially when citizens are collecting and interpreting the data by themselves. Poor or unknown data quality can lead to incorrect or inappropriate decisions. We present the experiences gained within the EU project CITI-SENSE, where low-cost sensors are one of the tools employed to empower citizens in air quality issues.

Numerical simulations of the transport and diffusion during the 1991 Winter Validation Study along the front range in Colorado

NASA Astrophysics Data System (ADS)

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

An important aspect of the U.S. Department of Energy's Atmospheric Studies in Complex Terrain (ASCOT) program is the development and evaluation of numerical models that predict transport and diffusion of pollutants in complex terrain. Operational mesoscale modeling of the transport of pollutants in complex terrain will become increasingly practical as computational costs decrease and additional data from high-resolution remote sensing instrumentation networks become available during the 1990s. Four-dimensional data assimilation (4DDA) techniques are receiving a great deal of attention recently not only to improve the initial conditions of mesoscale forecast models, but to create high-quality four-dimensional mesoscale analysis fields that can be used as input to air-quality models. In this study, a four-dimensional data assimilation technique based on Newtonian relaxation is incorporated into the Colorado State University (CSU) Regional Atmospheric Modeling System (RAMS) and evaluated using data taken from one experiment of the 1991 ASCOT field study along the front range of the Rockies in Colorado. The main objective of this study is to compare the observed surface concentrations with those predicted by a Lagrangian particle dispersion model and to demonstrate the effect of data assimilation on the simulated plume. In contrast to previous studies in which the smallest horizontal grid spacing was 10 km (Stauffer and Seaman, 1991) and 8 km (Yamada and Hermi, 1991), data assimilation is applied in this study to domains with a horizontal grid spacing as small as 1 km.

Evaluating DEM conditioning techniques, elevation source data, and grid resolution for field-scale hydrological parameter extraction

NASA Astrophysics Data System (ADS)

Woodrow, Kathryn; Lindsay, John B.; Berg, Aaron A.

2016-09-01

Although digital elevation models (DEMs) prove useful for a number of hydrological applications, they are often the end result of numerous processing steps that each contains uncertainty. These uncertainties have the potential to greatly influence DEM quality and to further propagate to DEM-derived attributes including derived surface and near-surface drainage patterns. This research examines the impacts of DEM grid resolution, elevation source data, and conditioning techniques on the spatial and statistical distribution of field-scale hydrological attributes for a 12,000 ha watershed of an agricultural area within southwestern Ontario, Canada. Three conditioning techniques, including depression filling (DF), depression breaching (DB), and stream burning (SB), were examined. The catchments draining to each boundary of 7933 agricultural fields were delineated using the surface drainage patterns modeled from LiDAR data, interpolated to a 1 m, 5 m, and 10 m resolution DEMs, and from a 10 m resolution photogrammetric DEM. The results showed that variation in DEM grid resolution resulted in significant differences in the spatial and statistical distributions of contributing areas and the distributions of downslope flowpath length. Degrading the grid resolution of the LiDAR data from 1 m to 10 m resulted in a disagreement in mapped contributing areas of between 29.4% and 37.3% of the study area, depending on the DEM conditioning technique. The disagreements among the field-scale contributing areas mapped from the 10 m LiDAR DEM and photogrammetric DEM were large, with nearly half of the study area draining to alternate field boundaries. Differences in derived contributing areas and flowpaths among various conditioning techniques increased substantially at finer grid resolutions, with the largest disagreement among mapped contributing areas occurring between the 1 m resolution DB DEM and the SB DEM (37% disagreement) and the DB-DF comparison (36.5% disagreement in mapped areas). These results demonstrate that the decision to use one DEM conditioning technique over another, and the constraints of available DEM data resolution and source, can greatly impact the modeled surface drainage patterns at the scale of individual fields. This work has significance for applications that attempt to optimize best-management practices (BMPs) for reducing soil erosion and runoff contamination within agricultural watersheds.

Spatio-temporal variability of soil water content on the local scale in a Mediterranean mountain area (Vallcebre, North Eastern Spain). How different spatio-temporal scales reflect mean soil water content

NASA Astrophysics Data System (ADS)

Molina, Antonio J.; Latron, Jérôme; Rubio, Carles M.; Gallart, Francesc; Llorens, Pilar

2014-08-01

As a result of complex human-land interactions and topographic variability, many Mediterranean mountain catchments are covered by agricultural terraces that have locally modified the soil water content dynamic. Understanding these local-scale dynamics helps us grasp better how hydrology behaves on the catchment scale. Thus, this study examined soil water content variability in the upper 30 cm of the soil on a Mediterranean abandoned terrace in north-east Spain. Using a dataset of high spatial (regular grid of 128 automatic TDR probes at 2.5 m intervals) and temporal (20-min time step) resolution, gathered throughout a 84-day period, the spatio-temporal variability of soil water content at the local scale and the way that different spatio-temporal scales reflect the mean soil water content were investigated. Soil water content spatial variability and its relation to wetness conditions were examined, along with the spatial structuring of the soil water content within the terrace. Then, the ability of single probes and of different combinations of spatial measurements (transects and grids) to provide a good estimate of mean soil water content on the terrace scale was explored by means of temporal stability analyses. Finally, the effect of monitoring frequency on the magnitude of detectable daily soil water content variations was studied. Results showed that soil water content spatial variability followed a bimodal pattern of increasing absolute variability with increasing soil water content. In addition, a linear trend of decreasing soil water content as the distance from the inner part of the terrace increased was identified. Once this trend was subtracted, resulting semi-variograms suggested that the spatial resolution examined was too high to appreciate spatial structuring in the data. Thus, the spatial pattern should be considered as random. Of all the spatial designs tested, the 10 × 10 m mesh grid (9 probes) was considered the most suitable option for a good, time-stable estimate of mean soil water content, as no improvement was obtained with the 5 × 5 m mesh grid (30 probes). Finally, the results of temporal aggregation showed that decreasing the monitoring frequency down to 8 h during wetting-up periods and to 1 day during drying-down ones did not result in a loss of information on daily soil water content variations.

MAX-DOAS tropospheric nitrogen dioxide column measurements compared with the Lotos-Euros air quality model

NASA Astrophysics Data System (ADS)

Vlemmix, T.; Eskes, H. J.; Piters, A. J. M.; Schaap, M.; Sauter, F. J.; Kelder, H.; Levelt, P. F.

2015-02-01

A 14-month data set of MAX-DOAS (Multi-Axis Differential Optical Absorption Spectroscopy) tropospheric NO2 column observations in De Bilt, the Netherlands, has been compared with the regional air quality model Lotos-Euros. The model was run on a 7×7 km2 grid, the same resolution as the emission inventory used. A study was performed to assess the effect of clouds on the retrieval accuracy of the MAX-DOAS observations. Good agreement was found between modeled and measured tropospheric NO2 columns, with an average difference of less than 1% of the average tropospheric column (14.5 · 1015 molec cm-2). The comparisons show little cloud cover dependence after cloud corrections for which ceilometer data were used. Hourly differences between observations and model show a Gaussian behavior with a standard deviation (σ) of 5.5 · 1015 molec cm-2. For daily averages of tropospheric NO2 columns, a correlation of 0.72 was found for all observations, and 0.79 for cloud free conditions. The measured and modeled tropospheric NO2 columns have an almost identical distribution over the wind direction. A significant difference between model and measurements was found for the average weekly cycle, which shows a much stronger decrease during the weekend for the observations; for the diurnal cycle, the observed range is about twice as large as the modeled range. The results of the comparison demonstrate that averaged over a long time period, the tropospheric NO2 column observations are representative for a large spatial area despite the fact that they were obtained in an urban region. This makes the MAX-DOAS technique especially suitable for validation of satellite observations and air quality models in urban regions.

Interpolated Sounding and Gridded Sounding Value-Added Products

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

Toto, T.; Jensen, M.

Standard Atmospheric Radiation Measurement (ARM) Climate Research Facility sounding files provide atmospheric state data in one dimension of increasing time and height per sonde launch. Many applications require a quick estimate of the atmospheric state at higher time resolution. The INTERPOLATEDSONDE (i.e., Interpolated Sounding) Value-Added Product (VAP) transforms sounding data into continuous daily files on a fixed time-height grid, at 1-minute time resolution, on 332 levels, from the surface up to a limit of approximately 40 km. The grid extends that high so the full height of soundings can be captured; however, most soundings terminate at an altitude between 25more » and 30 km, above which no data is provided. Between soundings, the VAP linearly interpolates atmospheric state variables in time for each height level. In addition, INTERPOLATEDSONDE provides relative humidity scaled to microwave radiometer (MWR) observations.The INTERPOLATEDSONDE VAP, a continuous time-height grid of relative humidity-corrected sounding data, is intended to provide input to higher-order products, such as the Merged Soundings (MERGESONDE; Troyan 2012) VAP, which extends INTERPOLATEDSONDE by incorporating model data. The INTERPOLATEDSONDE VAP also is used to correct gaseous attenuation of radar reflectivity in products such as the KAZRCOR VAP.« less

Trends in soil moisture and real evapotranspiration in Douro River for the period 1980-2010

NASA Astrophysics Data System (ADS)

García-Valdecasas-Ojeda, Matilde; de Franciscis, Sebastiano; Raquel Gámiz-Fortis, Sonia; Castro-Díez, Yolanda; Jesús Esteban-Parra, María

2017-04-01

This study analyzes the evolution of different hydrological variables, such as soil moisture and real evapotranspiration, for the last 30 years, in the Douro Basin, the most extensive basin in the Iberian Peninsula. The different components of the real evaporation, connected to the soil moisture content, can be important when analyzing the intensity of droughts and heat waves, and particularly relevant for the study of the climate change impacts. The real evapotranspiration and soil moisture data are provided by simulations obtained using the Variable Infiltration Capacity (VIC) hydrological model. This model is a large-scale hydrologic model and allows estimates of different variables in the hydrological system of a basin. Land surface is modeled as a grid of large and uniform cells with sub-grid heterogeneity (e.g. land cover), while water influx is local, only depending from the interaction between grid cells and local atmosphere environment. Observational data of temperature and precipitation from Spain02 dataset are used as input variables for VIC model. The simulations have a spatial resolution of about 9 km, and the analysis is carried out on a seasonal time-scale. Additionally, we compare these results with those obtained from a dynamical downscaling driven by ERA-Interim data using the Weather Research and Forecasting (WRF) model, with the same spatial resolution. The results obtained from Spain02 data show a decrease in soil moisture at different parts of the basin during spring and summer, meanwhile soil moisture seems to be increased for autumn. No significant changes are found for real evapotranspiration. Keywords: real evapotranspiration, soil moisture, Douro Basin, trends, VIC, WRF. Acknowledgements: This work has been financed by the projects P11-RNM-7941 (Junta de Andalucía-Spain) and CGL2013-48539-R (MINECO-Spain, FEDER).