William A. Sprigg

Dust transport model validation using satellite- and ground-based methods in the southwestern United States

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.

Annual Patterns of Atmospheric Pollutions and Episodes over Cairo Egypt

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.

Public-health applications in remote sensing

Remote sensing of the environment is critical to warn of imminent, life-threatening dust storms and to reduce risk of exposure to desert dust and hitchhiking bacteria, molds, heavy metals, and other human-health concerns. Desert dust affects cardiovascular and respiratory illness. Respirable particulates result in health-care costs exceeding

Dust Storms, Human Health and a Global Early Warning System

11.5 billion annually, with an additional

Science requirements and required future measurements

4.6 billion for lost productivity.1 As part of the NASA-sponsored Public Health Applications in Remote Sensing (PHAiRS) project, data from NASA’s Terra satellite are assimilated into a numerical-dynamical model of dust generation and entrainment, DREAM (Dust Regional Atmospheric Model). Originally developed for the Mediterranean region2 and modified in PHAiRS for the southwestern United States,3 DREAM is driven by operational weather-forecast models of the US National Weather Service (the Nonhydrostatic Mesoscale Model, NMM, and the operational model it replaces, eta). The DREAM system simulates and predicts—up to three days in advance—the onset of dust storms and the 3D size-concentration characteristics of the resulting airborne-dust clouds. Current barren-ground input to the model consists of MOD12 classification (an International Geosphere-Biosphere Programme ecosystem descriptor of land-cover type and dynamics) condensed to a two-class product: bare ground=1 and all other classes=0. Using Moderate Resolution Imaging Spectroradiometer (MODIS) products to replace the bare-ground class from the Olson World Ecosystem Land Cover map—the model’s original design parameter (see Figure 1)—improved DREAM’s performance significantly (see Figure 2).4, 5 Working with New Mexico’s Environmental Public Health Tracking System, we developed a Web-based client server (see Figure 3) to assist asthma andmyocardial-infarction surveillance Figure 1. (left) Olson World Ecosystem ‘barren’ category. (right) MOD12 (land-cover type and dynamics)-classified ‘barren’ category.

Large particle diffusion from an elevated line source - a comparative evaluation of a theoretical model with field diffusion experiments

Arid regions, the source of most airborne mineral dusts, comprise a third of the Earth’s land surface, where some two billion people are exposed daily to the fine particles raised by wind. Crossing political borders and travelling on air currents around the world, these particles not only affect the health of local communities, but also put many other populations extant at risk for cardiovascular and respiratory illnesses and a host of other health problems. Risks of exposure are affected by climatic conditions and their local and regional weather characteristics. And today, because of advancements in science and technology we are at the threshold of significantly reducing these health problems. Examples of meningitis, asthma and Valley fever are used to illustrate how risks may be lowered through a Dust-Health Early Warning System. A little more than a half-century of dedicated measurements of particulate air quality and of environmental science enhanced by Earth-orbiting satellites reveal the truth of airborne dust extent, and much of its variability in time and space. These truths have been essential in advancing numerical, dynamical models of the atmosphere that mimic and predict weather systems that loft the airborne dusts that medical sciences and epidemiology are proving harmful. This union of scientific disciplines and services makes possible today a means to improve public health around the world through a Global Dust-Health Early Warning System.

Remote Sensing Observation of Annual Dust Cycles and Possible Causality of Kawasaki Disease Outbreaks in Japan

The role of solar variability in climate variability and change has been debated for a long time. Now, new results from various space experiments monitoring the radiative and particle emissions from the Sun together with detailed studies of their terrestrial impacts have opened an exciting new era in both solar and atmospheric physics. Being so close, the Sun is the only star where we have a chance to identify and study in detail the processes responsible for changes in irradiance on time scales from minutes to decades-the longest time scale over which high precision data are available. High-resolution spatial and temporal observations conducted in various space and ground-based experiments demonstrate that the surface of the Sun and its outer atmosphere are highly variable on almost all spatial scales, and that many of the observed changes are linked to interior processes taking place in the Suns convective zone or below. The broad collection of the material in this Monograph clearly shows that the variable solar energy output affects the Earths atmosphere and climate in many fundamental ways. However, a quantitative understanding of all the involved processes and their relationship to the climate system and its response remains elusive. Based on the current database and knowledge, it remains to be seen what role solar forcing will play in future climate.

Introduction: Extreme Weather, Health and Communities: Why Consider the Connections?

Abstract 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.

Refining the Process of Science Support for Communities Around Extreme Weather Events and Climate Impacts

Kawasaki disease (KD) is a rare vascular disease that, if left untreated, can result in irreparable cardiac damage in children. While the symptoms of KD are well-known, as are best practices for treatment, the etiology of the disease and the factors contributing to KD outbreaks remain puzzling to both medical practitioners and scientists alike. Recently, a fungus known as Candida, originating in the farmlands of China, has been blamed for outbreaks in China and Japan, with the hypothesis that it can be transported over long ranges via different wind mechanisms. This paper provides evidence to understand the transport mechanisms of dust at different geographic locations and the cause of the annual spike of KD in Japan. Candida is carried along with many other dusts, particles or aerosols, of various sizes in major seasonal wind currents. The evidence is based upon particle categorization using the Moderate Resolution Imaging Spectrometer (MODIS) Aerosol Optical Depth (AOD), Fine Mode Fraction (FMF) and Ångström Exponent (AE), the Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observation (CALIPSO) attenuated backscatter and aerosol subtype, and the Aerosol Robotic Network’s (AERONET) derived volume concentration. We found that seasonality associated with aerosol size distribution at different geographic locations plays a role in identifying dominant abundance at each location. Knowing the typical size of the Candida fungus, and analyzing aerosol characteristics using AERONET data reveals possible particle transport association with KD events at different locations. Thus, understanding transport mechanisms and accurate identification of aerosol sources is important in order to understand possible triggers to outbreaks of KD. This work provides future opportunities to leverage machine learning, including state-of-the-art deep architectures, to build predictive models of KD outbreaks, with the ultimate goal of early forecasting and intervention within a nascent global health early-warning system.

Modeling wind-blown desert dust in the southwestern United States for public health warning: A case study

This chapter introduces the importance of thinking about interdisciplinary approaches to examining extreme weather, health and communities. Weather extremes are a challenge. In sudden storms, long periods of drought, heat waves or cold spells, people either cope or suffer the consequences. World populations today are facing extreme weather in many forms, including excessive heat, mega-storms, tornados, floods and drought. This is weather that threatens the health, safety and wellbeing of rich and poor alike. Special challenges emerge for those who lack the wealth and social power to prepare for or move away from extreme weather threats. This chapter presents the rationale for the chapters that follow, and the detailed case studies of radical weather and the problems left behind: the people harmed, the physical environments altered and the lasting health issues. It explores the connections among them, the best practices in community response to them, and the successes of interdisciplinary tactics in dealing with them across various geographies, customs and cultures.