Joseph K. Vaughan

Regional Environmental Prediction Over the Pacific Northwest

Abstract This paper examines the potential of regional environmental prediction by focusing on the local forecasting effort in the Pacific Northwest. A consortium of federal, state, and local agencies have funded the development and operation of a multifaceted numerical prediction system centered at the University of Washington that includes atmospheric, hydrologic, and air quality models, the collection of real-time regional weather data sources, and a number of realtime applications using both observations and model output. The manuscript reviews northwest modeling and data collection systems, describes the funding and management system established to support and guide the effort, provides some examples of regional real-time applications, and examines the national implications of regional environmental prediction.

A Numerical Daily Air Quality Forecast System for The Pacific Northwest

Abstract A real-time photochemical air quality forecast system has been implemented for the Puget Sound region to support public awareness of air quality issues. The Air Indicator Report for Public Access and Community Tracking (AIRPACT) forecast system uses daily numerical weather forecasts from the fifth-generation Pennsylvania State University (PSU)–National Center for Atmospheric Research (NCAR) Mesoscale Model (MM5) to drive the California Meteorological Model (CALMET)/California photochemistry grid model (CALGRID) Eulerian photochemical modeling suite. Hourly forecasts of ozone and other pollutant concentrations, including primary particulate emissions from diesel sources, are produced for urban Seattle and environs within a gridded domain consisting of 62 × 67 grid cells (4 km × 4 km) with 13 vertical layers. Detailed gridded emission inventories are adjusted dynamically for time of day, day of the week, month, and gridded ambient temperatures to generate requisite emissions. The forecast system al...

April 1998 Asian dust event over the Columbia Plateau

Surface-based radiometers can be used to assess the atmospheric aerosol burden. During 1998, two multifilter rotating shadow-band radiometers (MFRSRs), operated by Washington State University (WSU) and by the USDA UV-B program, were used to collect data on the Columbia Plateau atmosphere. Analysis of these data by an automated Langley algorithm provided retrievals for total optical thickness, allowing for calculation of aerosol optical thickness (AOT) and the top-of-atmosphere (TOA) instrument signal. Statistical evaluation of the TOA signal permitted recalculation of optical thickness using the Bouguer-Lambert-Beer law and resulted in improved estimates of aerosol optical thickness (AOT). Results for AOT and the associated Angstrom parameters are presented here for an April 1998 dust event for two colocated Columbia Plateau sites. AOT at 500 nm went from background levels (seasonally dominated by regional windblown dust) of ∼0.2 to more than 0.4 during the event maximum on April 27, not returning to normal levels until April 30. Comparison of 500-nm AOT between the two MFRSR showed a root-mean-square (RMS) difference of 0.016. The Angstrom exponent α reached a minimum of ∼0.2, and the β coefficient reached a maximum of ∼0.35, both on April 27, coincident with the AOT maximum. Contemporaneous aerosol sampling in Spokane, Washington, provided (1) elemental data that strongly support our interpretation of this event as an influx of Asian dust without significant sulfur enrichment and (2) event maximum PM10 measurements ∼80 μg/m3 consistent with Pullman event maximum AOT results, assuming a 3–4 km thick dust layer.

BioEarth: Envisioning and developing a new regional earth system model to inform natural and agricultural resource management

As managers of agricultural and natural resources are confronted with uncertainties in global change impacts, the complexities associated with the interconnected cycling of nitrogen, carbon, and water present daunting management challenges. Existing models provide detailed information on specific sub-systems (e.g., land, air, water, and economics). An increasing awareness of the unintended consequences of management decisions resulting from interconnectedness of these sub-systems, however, necessitates coupled regional earth system models (EaSMs). Decision makers’ needs and priorities can be integrated into the model design and development processes to enhance decision-making relevance and “usability” of EaSMs. BioEarth is a research initiative currently under development with a focus on the U.S. Pacific Northwest region that explores the coupling of multiple stand-alone EaSMs to generate usable information for resource decision-making. Direct engagement between model developers and non-academic stakeholders involved in resource and environmental management decisions throughout the model development process is a critical component of this effort. BioEarth utilizes a bottom-up approach for its land surface model that preserves fine spatial-scale sensitivities and lateral hydrologic connectivity, which makes it unique among many regional EaSMs. This paper describes the BioEarth initiative and highlights opportunities and challenges associated with coupling multiple stand-alone models to generate usable information for agricultural and natural resource decision-making.

Application of the Wind Erosion Prediction System in the AIRPACT Regional Air Quality Modeling Framework

Abstract. Wind erosion of soil is a major concern of the agricultural community, as it removes the most fertile part of the soil and thus degrades soil productivity. Furthermore, dust emissions due to wind erosion degrade air quality, reduce visibility, and cause perturbations to regional radiation budgets. PM 10 emitted from the soil surface can travel hundreds of kilometers downwind before being deposited back to the surface. Thus, it is necessary to address agricultural air pollutant sources within a regional air quality modeling system in order to forecast regional dust storms and to understand the impact of agricultural activities and land-management practices on air quality in a changing climate. The Wind Erosion Prediction System (WEPS) is a new tool in regional air quality modeling for simulating erosion from agricultural fields. WEPS represents a significant improvement, in comparison to existing empirical windblown dust modeling algorithms used for air quality simulations, by using a more process-based modeling approach. This is in contrast with the empirical approaches used in previous models, which could only be used reliably when soil, surface, and ambient conditions are similar to those from which the parameterizations were derived. WEPS was originally intended for soil conservation applications and designed to simulate conditions of a single field over multiple years. In this work, we used the EROSION submodel from WEPS as a PM 10 emission module for regional modeling by extending it to cover a large region divided into Euclidean grid cells. The new PM 10 emission module was then employed within a regional weather and chemical transport modeling framework commonly used for comprehensive simulations of a wide range of pollutants to evaluate overall air quality conditions. This framework employs the Weather Research and Forecasting (WRF) weather model along with the Community Multi-scale Air Quality (CMAQ) model to treat ozone, particulate matter, and other air pollutants. To demonstrate the capabilities of the WRF/EROSION/CMAQ dust modeling framework, we present here results from simulations of dust storms that occurred in central and eastern Washington during 4 October 2009 and 26 August 2010. Comparison of model results with observations indicates that the modeling framework performs well in predicting the onset and timing of the dust storms and the spatial extent of their dust plumes. The regional dust modeling framework is able to predict elevated PM 10 concentrations hundreds of kilometers downwind of erosion source regions associated with the windblown dust, although the magnitude of the PM 10 concentrations are extremely sensitive to the assumption of surface soil moisture and model wind speeds. Future work will include incorporating the full WEPS model into the regional modeling framework and targeting field measurements to evaluate the modeling framework more extensively.

Spatial Application of WEPS for Estimating Wind Erosion in the Pacific Northwest

Abstract. The Wind Erosion Prediction System (WEPS) is used to simulate soil erosion by wind on cropland and was originally designed to run simulations on a field scale. This study extended WEPS to run on multiple fields (grid cells) independently to cover a large region and conducted an initial investigation to assess how well WEPS performed in that environment by comparing simulations for two historical dust events with field observations and satellite images in the Columbia Plateau region of Washington. We modified the WEPS source code to allow it not only to run on multiple grid cells but also to save the state of the simulation so that it can be re-initiated from that state in future runs, allowing the model to be started and then stepped through time incrementally under various future climate or forecast weather scenarios. We initially ran WEPS on the entire state of Washington, with the entire Pacific Northwest region as our ultimate target area, to provide PM 10 and eventually PM 2.5 emissions from wind erosion events as input to the chemical transport model CMAQ, which is used by the AIRPACT regional air quality modeling system for the Pacific Northwest. Three principal inputs to WEPS are meteorological data, soil data, and crop management practices. These data, at a 1 km A— 1 km grid cell resolution, are the basic input data for running the spatially distributed model. The climatic data from a three-year period were stochastically generated based on statistical representations of past meteorological measurements from stations in the region and were used for initializing WEPS, and then a three-day set of meteorological data corresponding with historical dust storm events were selected for simulation by WEPS of wind erosion of cropland in the state of Washington. The crop management data were selected based on the land use and USDA Natural Resources Conservation Service (NRCS) crop management zones, and the soil data were derived from the NRCS SSURGO database. We aggregated the outputs from 1 km A— 1 km grid cells into 12 km A— 12 km grid cells for easier visualization and then mapped the total surface soil erosion, suspension, and PM 10 emissions for each 12 km A— 12 km grid cell. This study shows that WEPS can be successfully extended to run from one field grid cell to multiple field grid cells, and the model can identify regions with high potential for soil erosion by wind. It also demonstrates that WEPS can be used for real-time monitoring of soil erosion and air quality in a large region if actual and forecast weather inputs are available.

Chapter 22 Regional Real-Time Smoke Prediction Systems

Abstract Several real-time smoke prediction systems have been developed worldwide to help land managers, farmers, and air quality regulators balance land management needs against smoke impacts. Profiled here are four systems that are currently operational for regional domains for North America and Australia, providing forecasts to a well-developed user community. The systems link fire activity data, fuels information, and consumption and emissions models, with weather forecasts and dispersion models to produce a prediction of smoke concentrations from prescribed fires, wildfires, or agricultural fires across a region. The USDA Forest Services BlueSky system is operational for regional domains across the United States and obtains prescribed burn information and wildfire information from databases compiled by various agencies along with satellite fire detections. The U.S. National Oceanic and Atmospheric Administration (NOAA) smoke prediction system is initialized with satellite fire detections and is operational across North America. Washington State Universitys ClearSky agricultural smoke prediction system is operational in the states of Idaho and Washington, and burn location information is input via a secure Web site by regulators in those states. The Australian Bureau of Meteorology smoke prediction system is operational for regional domains across Australia for wildfires and prescribed burning. Operational uses of these systems are emphasized as well as the approaches to evaluate their performance given the uncertainties associated with each systems subcomponents. These real-time smoke prediction systems are providing a point of interagency understanding between land managers and air regulators from which to negotiate the conflicting needs of ecological fire use while minimizing air quality health impacts.

Design and Implementation of Kepler Workflows for BioEarth

Abstract BioEarth is an ongoing research initiative for the development of a regional-scale Ea rth S ystem M odel (EaSM) for the U.S. Pacific Northwest. Our project seeks to couple and integrate multiple stand-alone EaSMs developed through independent efforts for capturing natural and human processes in various realms of the biosphere: atmosphere (weather and air quality), terrestrial biota (crop, rangeland, and forest agro-ecosystems) and aquatic (river flows, water quality, and reservoirs); hydrology links all these realms. Due to the need to manage numerous complex simulations,an application of automated workflows was essential. In this paper, we present a case study of workflow design for the BioEarth project using the Kepler system to manage applications of the R egional H ydro- E cologic S imulation Sys tem (RHESSys) model. In particular, we report on the design of Kepler workflows to support: 1) standalone executions of the RHESSys model under serial and parallel applications, and 2) a more complex case of performing calibration runs involving multiple preprocessing modules, iterative exploration of parameters and parallel RHESSys executions. We exploited various Kepler features including a user-friendly design interface and support for parallel execution on a cluster. Our experiments show a performance speedup between 7–12x, using 16 cores of a Linux cluster, and demonstrate the general effectiveness of our Kepler workflows in managing RHESSys runs. This study shows the potential of Kepler to serve as the primary integration platform for the BioEarth project, with implications for other data- and compute-intensive Earth systems modeling projects.

Impacts of prescribed fires and benefits from their reduction for air quality, health and visibility in the Pacific Northwest of the United States

ABSTRACT Using a WRF-SMOKE-CMAQ modeling framework, we investigate the impacts of smoke from prescribed fires on model performance, regional and loc al air quality, health impacts, and visibility in protected natural environments using three different prescribed fire emission scenarios: 100% fire, no fire, and 30% fire. The 30% fire case reflects a 70% reduction in fire activities due to harvesting of logging residues for use as a feedstock for a potential aviation biofuel supply chain. Overall model performance improves for several performance metrics when fire emissions are included, especially for organic carbon, irrespective of the model goals and criteria used. This effect on model performance is more pronounced for the rural and remote IMPROVE sites for organic carbon and total PM2.5. A reduction in prescribed fire emissions (30% fire case) results in significant improvement in air quality in areas in western Oregon, northern Idaho, and western Montana, where most prescribed fires occur. Prescribed burning contributes to visibility impairment, and a relatively large portion of protected class I areas will benefit from a reduced emission scenario. For the haziest 20% days, prescribed burning is an important source of visibility impairment, and approximately 50% of IMPROVE sites in the model domain show a significant improvement in visibility for the reduced fire case. Using BenMAP, a health impact assessment tool, we show that several hundred additional deaths, several thousand upper and lower respiratory symptom cases, several hundred bronchitis cases, and more than 35,000 workday losses can be attributed to prescribed fires, and these health impacts decrease by 25–30% when a 30% fire emission scenario is considered. Implications: This study assesses the potential regional and local air quality, public health, and visibility impacts from prescribed burning activities, as well as benefits that can be achieved by a potential reduction in emissions for a scenario where biomass is harvested for conversion to biofuel. As prescribed burning activities become more frequent, they can be more detrimental for air quality and health. Forest residue-based biofuel industry can be source of cleaner fuel with co-benefits of improved air quality, reduction in health impacts, and improved visibility.

Incorporating the Wind Erosion Prediction System (WEPS) for Dust into a Regional Air Quality Modeling System

Wind erosion of soil is a major concern of the agricultural community as it removes the most fertile part of the soil and thus degrades soil productivity. Furthermore, suspension of eroded soil particles results in dust emissions into the atmosphere, contributing to poor air quality, reduced visibility, and perturbations to regional radiation budgets. An important aspect of understanding the impact of agricultural activities is the ability to model windblown dust emissions within the framework of a regional air-quality system that considers atmospheric constituents from a variety of sources. The Wind Erosion Prediction System (WEPS) is a new tool for treating erosion from agricultural fields. As a process-based model, WEPS represents a significant improvement in comparison to existing empirical windblown dust modeling algorithms. WEPS includes several submodels to account for the effects of crop growth, crop management practices, soil conditions and surface cover. WEPS was originally intended for soil conservation applications and designed to simulate conditions of a single field over multiple years. In this work, WEPS has been modified so that it can be incorporated into a gridded regional air quality forecasting system. The modified WEPS model is incorporated into the WRF/CMAQ modeling framework to study the impact of windblown dust on air quality in the state of Washington (Figure 1). Preliminary results indicate that the modeling framework performs well in predicting the onset of dust storm events although the exact timing of events is off by as much as several hours and the framework appear to underestimate atmospheric PM10 concentrations. Future work will include more quantitative and comprehensive evaluation to improve the modeling framework.