William A Sprigg
Recent Research & Project Management
Nature’s Aerosols & Air Quality: Detecting & Monitoring Sources and Simulating & Forecasting Emissions,Dispersal and Consequences
Co-principal investigator for NASA-sponsored projects: (a) Public Health Applications in Remote Sensing, Integrating Airborne Dust Concentration Into Public Health Decision Support Systems (2004 - 2010); (b) Adding NASA Earth Science Results into Public Health Tracking Systems (2008-2011); (c) Rapid Prototyping for Model Interoperability and High-Performance Computing (2008); (d) Rapid Prototyping to Test Pollen Modeling Applied to Public Health (2008-2009) and (e) Integration of Airborne Dust Prediction Systems and Vegetation Phenology to Track Pollen for Asthma Alerts in Public Health Decision Support Systems (2009-2014). Principal investigator for U.S. Centers for Disease Control and Prevention (CDC) and NASA: Airborne Dust Models, A Tool in Environmental Health Tracking (2012). An Arizona haboob in July 2011 became an opportunity to demonstrate that dust storm forecasts today can provide timely alerts of hazardous conditions for public health and safety (Sprigg, et al., 2012, 2014; Vukovic, et al., 2014).
International Concerns of Windblown Dust
Forty Nations Asked the World Meteorological Organization to Help Reduce Risks Associated With Windblown Desert Dust
As consultant (2008) to the World Meteorological Organization (WMO) and International Chair (2009-2010) for the WMO Implementation Plan Drafting Group, “Sand & Dust Storm Warning Advisory & Assessment System” (a) provided historical & technical background and professional network; (b) provided focus and articulated long-term needs, resources and international strategies for addressing the global, chronic problem of airborne dust from the world’s arid lands; and (c) initiated Pan-America sector collaboration and its role as a global information and enabling resource to address public health consequences of windblown dust.
National & International Science Policy Concerning Climate Variability & Change
Architect: U.S. National Climate Program -- incorporating ocean, land, ice, atmosphere and solar sciences, human resources, supporting infrastructures and management systems into missions and goals to understand and predict Earth’s climate system and the consequences of change. Of critical consequence, ensured that the Program’s “climate time scales” began at two weeks (the theoretical outer limit of weather forecasting) and would embrace El Nino as well as “greenhouse” warming. The Program plan reaffirmed that climate and its consequences were global and solutions would ultimately be international. Founded the Program on academic, private sector, government and scientific society participation through unique bottom-up/top-down/matrix management strategies. Formed the National Oceanic and Atmospheric Administration’s Climate Program -- initiating the Nation’s Experimental Climate Forecast Program and the Annual Climate Diagnostics Workshops (the 39th in 2014), forming the Nation’s Regional Climate Centers, and raising priority of the National Weather Service’s Climate Prediction Center.
- Ph.D. Atmospheric Science
- Yale University, New Haven, Connecticut, USA
- An Experimental Study of the Attenuation of the Solar Beam by Pollution in the Boundary Layer of an Urban Atmosphere
- M.Phil. Atmospheric Science
- Yale University, New Haven, Connecticut, USA
- M.S. Atmospheric Science
- Rutgers, The State University of New Jersey, New Brunswick, New Jersey, USA
- Particle Diffusion from an Infinite Continuous Line Source
- B.S. Meteorology and Atmospheric Science
- Florida State University, Tallahassee, Florida, USA
- Public Health Institute (2014 - Ongoing)
- Chapman University, Orange, California (2010 - 2014)
- The University of Arizona, Tucson, Arizona (2003 - Ongoing)
- The University of Arizona (1998 - 2003)
- National Academy of Sciences (1990 - 1998)
- National Oceanic & Atmospheric Administration (1989 - 1990)
- National Oceanic & Atmospheric Administration (1987 - 1989)
- National Oceanic & Atmospheric Administration (1987 - 1989)
- National Oceanic & Atmospheric Administration (1983 - 1987)
- National Oceanic & Atmospheric Administration (1979 - 1987)
- National Oceanic & Atmospheric Administration (1978 - 1983)
- National Oceanic & Atmospheric Administration (1976 - 1978)
- National Oceanic & Atmospheric Administration (1972 - 1976)
- U.S. Army Signal Center & School (1961 - 1963)
Working with undergraduate and graduate students participating in contemporary, environmental research for hands-on experience, learning from project conceptualization, funding and proposal processes, research team building, project management and reporting. Students working with Prof. Sprigg are exposed to an holistic view of why and how national and international science policy and research interests affect even the smallest of environmental research projects.
With ultimate aims to improve public health and safety through environmental research, Dr. Sprigg’s team has created an international-verified, research-tested and operational-ready dust forecast capability, demonstrating how risks of Valley Fever and other respiratory and cardiovascular illnesses can be reduced. A pollen-forecast system, offspring of dust modeling, is under test. Both systems may be used to examine potential air quality and public health and safety consequences of climate variability. Professor Sprigg has long been interested in furthering interdisciplinary research and science policy – from integrating all the scientific disciplines necessary to understand and adapt in a variable climate, to assembling international experts in such diverse fields as physical, environmental and medical science, and in energy, agriculture, urban planning, economics, education and public policy to further science in decision making.
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- Vukovic, A., Vujadinovic, M., Pejanovic, G., Andric, J., Kumjian, M. R., Djurdjevic, V., Dacic, M., Prasad, A. K., El-Askary, H., Paris, B. C., Petkovic, S., Nickovic, S., & Sprigg, W. A. (2014). Numerical simulation of "an American haboob". Atmospheric Chemistry and Physics, 14(7), 3211-3230.More infoAbstract: A dust storm of fearful proportions hit Phoenix in the early evening hours of 5 July 2011. This storm, an American haboob, was predicted hours in advance because numerical, land-atmosphere modeling, computing power and remote sensing of dust events have improved greatly over the past decade. High-resolution numerical models are required for accurate simulation of the small scales of the haboob process, with high velocity surface winds produced by strong convection and severe downbursts. Dust productive areas in this region consist mainly of agricultural fields, with soil surfaces disturbed by plowing and tracks of land in the high Sonoran Desert laid barren by ongoing draught. Model simulation of the 5 July 2011 dust storm uses the coupled atmospheric-dust model NMME-DREAM (Non-hydrostatic Mesoscale Model on E grid, Janjic et al., 2001; Dust REgional Atmospheric Model, Nickovic et al., 2001; Pérez et al., 2006) with 4 km horizontal resolution. A mask of the potentially dust productive regions is obtained from the land cover and the normalized difference vegetation index (NDVI) data from the Moderate Resolution Imaging Spectroradiometer (MODIS). The scope of this paper is validation of the dust model performance, and not use of the model as a tool to investigate mechanisms related to the storm. Results demonstrate the potential technical capacity and availability of the relevant data to build an operational system for dust storm forecasting as a part of a warning system. Model results are compared with radar and other satellite-based images and surface meteorological and PM10 observations. The atmospheric model successfully hindcasted the position of the front in space and time, with about 1 h late arrival in Phoenix. The dust model predicted the rapid uptake of dust and high values of dust concentration in the ensuing storm. South of Phoenix, over the closest source regions (~25 km), the model PM10 surface dust concentration reached ~2500 μg mg-3, but underestimated the values measured by the PM10 stations within the city. Model results are also validated by the MODIS aerosol optical depth (AOD), employing deep blue (DB) algorithms for aerosol loadings. Model validation included Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observation (CALIPSO), equipped with the lidar instrument, to disclose the vertical structure of dust aerosols as well as aerosol subtypes. Promising results encourage further research and application of high-resolution modeling and satellite-based remote sensing to warn of approaching severe dust events and reduce risks for safety and health.
- Fetouh, Y. A., Askary, H. E., Raey, M. E., Allali, M., Sprigg, W. A., & Kafatos, M. (2013). Annual patterns of atmospheric pollutions and episodes over cairo Egypt. Advances in Meteorology, 2013.More infoAbstract: The Nile Delta major cities, particularly Cairo, experienced stagnant air pollution episodes, known as Black Cloud, every year over the past decade during autumn. Low-elevated thermal inversion layers play a crucial role in intensifying pollution impacts. Carbon monoxide, ozone, atmospheric temperature, water vapor, and methane measurements from the tropospheric emission spectrometer (TES) on board the Aura have been used to assess the dominant component below the inversion layer. In this study, time series analysis, autocorrelations, and cross correlations are performed to gain a better understanding of the connections between those parameters and their local effect. Satellite-based data were obtained for the years 2005-2010. The parameters mentioned were investigated throughout the whole year in order to study the possible episodes that take place in addition to their change from year to year. Ozone and carbon monoxide were the two major indicators to the most basic episodes that occur over Cairo and the Delta region. © 2013 Y. Aboel Fetouh et al.
- Luvall, J. C., Sprigg, W. A., Levetin, E., Huete, A., Nickovic, S., Pejanovic, G. A., Vukovic, A., Van, P., Myers, O. B., Budge, A. M., Zelicoff, A. P., Bunderson, L., & Crimmins, T. M. (2011). Use of MODIS satellite images and an atmospheric dust transport model to evaluate juniperus spp. Pollen phenology and dispersal. 34th International Symposium on Remote Sensing of Environment - The GEOSS Era: Towards Operational Environmental Monitoring.More infoAbstract: Pollen can be transported great distances. Van de Water et. al., 2003 reported Juniperus spp. pollen was transported 200-600 km. Hence local observations of plant phenology may not be consistent with the timing and source of pollen collected by pollen sampling instruments. The DREAM (Dust REgional Atmospheric Model, Nickovic et al. 2001) is a verified model for atmospheric dust transport modeling using MODIS data products to identify source regions and quantities of dust. We are modifying the DREAM model to incorporate pollen transport. Pollen release will be estimated based on MODIS derived phenology of Juniperus spp. communities. Ground based observational records of pollen release timing and quantities will be used as verification. This information will be used to support the Centers for Disease Control and Prevention's National Environmental Public Health Tracking Program and the State of New Mexico environmental public health decision support for asthma and allergies alerts.
- Yin, D., Nickovic, S., & Sprigg, W. A. (2007). The impact of using different land cover data on wind-blown desert dust modeling results in the southwestern United States. Atmospheric Environment, 41(10), 2214-2224.More infoAbstract: Olson World Ecosystem (OWE) land cover data based on data sources of the 1970s and 1980s with a 10-min spatial resolution, and up-to-date Moderate Resolution Imaging Spectroradiometer (MODIS) land cover data with a 30-s resolution, were used, respectively, in modeling wind-blown desert dust in the southwest United States. The model using different land cover data sets preformed similarly in modeling meteorological field patterns, vertical profiles and surface wind and temperature, in comparisons against observations. The differences of wind and temperature at a specific time and location can be big. Compared against satellite and ground measurements, modeled dust spatial distributions using MODIS land cover data were considerably better than those using OWE land cover. Site against site comparisons of modeled and observed surface PM2.5 concentration time series showed that model performance improved significantly using MODIS land cover data. Modeled surface PM2.5 contour distributions using MODIS land cover data compared more favorably against observations. The performance statistics for modeled PM2.5 concentrations at 40 surface sites increased from 0.15 using OWE data, to 0.58 using MODIS data. This demonstrates that the survey updates and spatial resolution of land cover data are critical in correctly predicting dust events and dust concentrations. Using land cover data such as MODIS data from satellite remote sensing is promising in improving wind-blown dust modeling and forecasting. © 2006 Elsevier Ltd. All rights reserved.
- Mahler, A., Thome, K., Yin, D., & Sprigg, W. A. (2006). Dust transport model validation using satellite- And ground-based methods in the southwestern United States. Proceedings of SPIE - The International Society for Optical Engineering, 6299.More infoAbstract: Dust is known to aggravate respiratory diseases. This is an issue in the desert southwestern United States, where windblown dust events are common. The Public Health Applications in Remote Sensing (PHAiRS) project aims to address this problem by using remote-sensing products to assist in public health decision support. As part of PHAiRS, a model for simulating desert dust cycles, the Dust Regional Atmospheric Modeling (DREAM) system is employed to forecast dust events in the southwestern US. Thus far, DREAM has been validated in the southwestern US only in the lower part of the atmosphere by comparison with measurement and analysis products from surface synoptic, surface Meteorological Aerodrome Report (METAR), and upper-air radiosonde. This study examines the validity of the DREAM algorithm dust load prediction in the desert southwestern United States by comparison with satellite-based MODIS level 2 and MODIS Deep Blue aerosol products, and ground-based observations from the AERONET network of sunphotometers. Results indicate that there are difficulties obtaining MODIS L2 aerosol optical thickness (AOT) data in the desert southwest due to low AOT algorithm performance over areas with high surface reflectances. MODIS Deep Blue aerosol products show improvement, but the temporal and vertical resolution of MODIS data limit its utility for DREAM evaluation. AERONET AOT data show low correlation to DREAM dust load predictions. The potential contribution of space- or ground-based lidar to the PHAiRS project is also examined.
- Hudspeth, W., Nickovic, S., Yin, D., Chandy, B., Barbaris, B., Budge, A., Budge, T., Baros, S., Benedict, K., Bales, C., Catrall, C., Morain, S., Sanchez, G., Sprigg, W., & Thome, K. (2005). PHAiRS - A public health decision support system: Initial results. Proceedings, 31st International Symposium on Remote Sensing of Environment, ISRSE 2005: Global Monitoring for Sustainability and Security.More infoAbstract: Respiratory diseases caused or aggravated by dust or smoke (PM10 and PM2.5) are of concern to health officials in arid and semiarid regions where windblown dust constitutes a serious threat to public health. This paper presents early results of work on Public Health Applications in Remote Sensing (PHAiRS), a project that seeks to integrate NASA remote-sensing products into an existing public health decision-support system. With the goal of forecasting dust events, the project relies on outputs from the Dust Regional Atmospheric Model (DREAM). To characterize and establish baseline model behavior prior to the anticipated substitution of specified model parameters with NASA Earth Science data, a point-by-point comparison between in-situ observations and baseline DREAM model output is performed across reporting stations from north-central New Mexico to the Texas gulf coast for the two-day dust event of December 15-16, 2003.
- Morain, S., Budge, A., Budge, T., Baros, S., Benedict, K., Hudspeth, W., Bales, C., Sanchez, G., Sprigg, W., Yin, D., Barbaris, B., Chandy, B., Nickovic, S., Caskey, S., Speer, J., & Bradbury, J. (2005). Modeling atmospheric dust for a public health decision support system. Proceedings, 31st International Symposium on Remote Sensing of Environment, ISRSE 2005: Global Monitoring for Sustainability and Security.More infoAbstract: Environmental health and public health are often linked in the scientific and popular literature even though they require different scientific skill sets, technologies, and models for their study. Environmental health includes not only the health and sustainability of natural ecosystems, but the environments of built landscapes, home and building environments, and of the Earth system processes that promote or retard environmental change. To study them, one needs education in atmospheric physics and chemistry, water chemistry, geophysics, and biology. Public health is related in large measure to degraded environmental parameters (mostly induced by modern economic, social, and human pressures on landscapes). To study public health, one needs medical training and an appreciation of those processes that impact environments and that may in turn influence populations whose health might be at risk. Using satellite-acquired data and imagery to study environmental health has many immediate attractions; however, the extension of these studies for better understanding public health patterns and outcomes lags far behind, and does not yet embrace medical communities. This paper describes an engineering system for linking atmospheric dust episodes to specific public health outcomes that can be verified and validated in medical terms. It requires forging new scientific partnerships from the environmental and medical professions.
- Yin, D., Nickovic, S., Barbaris, B., Chandy, B., & Sprigg, W. A. (2005). Modeling wind-blown desert dust in the southwestern United States for public health warning: A case study. Atmospheric Environment, 39(33), 6243-6254.More infoAbstract: A model for simulating desert dust cycle was adapted and applied for a dust storm case in the southwest United States (US). This is an initial test of the model's capability as part of a future public health early warning system. The modeled meteorological fields, which drive a dust storm, were evaluated against surface and upper-air measurement data. The modeled dust fields were compared with satellite images, in situ surface PM2.5 and PM10 data, and visibility data in the areas affected by the dust event. The model predicted meteorological fields reasonably well. The modeled surface and upper-air field patterns were in agreement with the measured ones. The vertical profiles of wind, temperature, and humidity followed closely with the observed profiles. Statistical analyses of modeled and observed meteorological variables at surface sites showed fairly good model performance. The modeled dust spatial distributions were comparable with the satellite-observed dust clouds and the reduced visibility patterns. Most encouragingly, the model-predicted and observed PM2.5 peak hours matched reasonably well. The model produced better PM2.5 peak hours than PM10 peak hours. The temporal varying trends of daily and hourly PM2.5 and PM10 concentrations at most of the measurement sites were similar to those observed. Discrepancies between the values of the modeled and the measured surface PM2.5 and PM10 concentrations differed with time and location. Sometimes the modeled and measured concentrations can have one order of magnitude differences. These revealed there were possible deficiencies in the simulation of the dust production strength and location, and the representation of dust particle size in the modeling. Better land surface data and size representation of the dust production are expected to further improve model performance. © 2005 Elsevier Ltd. All rights reserved.
- Colwell, R., Epstein, P., Gubler, D., Hall, M., Reiter, P., Shukla, J., Sprigg, W., Takafuji, E., & Trtanj, J. (1998). Global climate change and infectious diseases. Emerging Infectious Diseases, 4(3), 451-452.More infoPMID: 9716968;PMCID: PMC2640270;
- Sprigg, W. A. (1996). Doctors watch the forecasts. Nature, 379(6566), 582-583.More infoPMID: 8628390;
- SPRIGG, W. A. (1973). LARGE PARTICLE DIFFUSION FROM AN ELEVATED LINE SOURCE - A COMPARATIVE EVALUATION OF A THEORETICAL MODEL WITH FIELD DIFFUSION EXPERIMENTS.. AGRIC. MET., 12(3), DECEMBER, 1973.More infoAbstract: A THEORETICAL MODEL OF ATMOSPHERIC DIFFUSION OF A POLYDISPERSED MATERIAL FROM AN ELEVATED LINE SOURCE IS USED TO PREDICT DOWNWIND DEPOSITION OF LARGE PARTICLES (NOMINALLY 100GM DIAMETER) RELEASED DURING SIX SEPARATE FIELD DIFFUSION EXPERIMENTS.TWO EQUATIONS ARE USED.ONE, WHERE DIFFUSION IS DEPENDENT ON THE DISTRIBUTION OF PARTICLES AS ADVECTED IN A STEADY-STATE CONDITION.THE SECOND INCLUDES FACTORS TO ACCOUNT FOR ATMOSPHERIC TURBULENCE AND DIFFUSION.WHEN THE CORRECT EQUATION IS CHOSEN FOR A GIVEN TURBULENCE CONDITION, IN ALL BUT TWO OF THE DIFFUSION DRIALS THE MODEL IS WITHIN 5 M OF PREDICTING THE POINT OF MAXIMUM DEPOSITION; IN ALL SIX TRIALS THE GREATES DISCREPENCY IS 15M.THE MODEL IS REASONABLY CAPABLE OF PREDICTING VALUES OF DOWNWIND DEPOSITION.WIND PROFILE FITTING TERMS ARE SHOWN TO BE MOST ACCURATE UNDER THERMALLY STABLE ATMOSPHERIC CONDITIONS.(A)
- Sprigg, W. A. (1973). Large particle diffusion from an elevated line source - a comparative evaluation of a theoretical model with field diffusion experiments. Agricultural Meteorology, 12(C), 425-439.More infoAbstract: A theoretical model of atmospheric diffusion of a polydispersed material from an elevated line source is used to predict downwind deposition of large particles (nominally 100 μ diameter) released during six separate field diffusion experiments. Two equations are used. One, where diffusion is dependent on the distribution of particles as advected in a steady-state condition. The second includes factors to account for atmospheric turbulence and diffusion. When the correct equation is chosen for a given turbulence condition, in all but two of the diffusion trials the model is within 5 m of predicting the point of maximum deposition; in all six trials the greatest discrepancy is 15 m. The model is reasonably capable of predicting values of downwind deposition. Wind profile fitting terms are shown to be most accurate under thermally stable atmospheric conditions. © 1973.