Scott Greene

Predicting key malaria transmission factors, biting and entomological inoculation rates, using modelled soil moisture in Kenya

While malaria transmission varies seasonally, large inter‐annual heterogeneity of malaria incidence occurs. Variability in entomological parameters, biting rates and entomological inoculation rates (EIR) have been strongly associated with attack rates in children. The goal of this study was to assess the weathers impact on weekly biting and EIR in the endemic area of Kisian, Kenya. Entomological data collected by the U.S. Army from March 1986 through June 1988 at Kisian, Kenya was analysed with concurrent weather data from nearby Kisumu airport. A soil moisture model of surface‐water availability was used to combine multiple weather parameters with landcover and soil features to improve disease prediction. Modelling soil moisture substantially improved prediction of biting rates compared to rainfall; soil moisture lagged two weeks explained up to 45% of An. gambiae biting variability, compared to 8% for raw precipitation. For An. funestus, soil moisture explained 32% variability, peaking after a 4‐week lag. The interspecies difference in response to soil moisture was significant (P < 0.00001). A satellite normalized differential vegetation index (NDVI) of the study site yielded a similar correlation (r2= 0.42 An. gambiae). Modelled soil moisture accounted for up to 56% variability of An. gambiae EIR, peaking at a lag of six weeks. The relationship between temperature and An. gambiae biting rates was less robust; maximum temperature r2=−0.20, and minimum temperature r2= 0.12 after lagging one week. Benefits of hydrological modelling are compared to raw weather parameters and to satellite NDVI. These findings can improve both current malaria risk assessments and those based on El Niño forecasts or global climate change model projections.

Climate Change, Heat Waves, and Mortality Projections for Chicago

ABSTRACT Over the coming century, climate change is projected to increase both mean and extreme temperatures as heat waves become more frequent, intense, and long-lived. The city of Chicago has already experienced a number of severe heat waves, with a 1995 event estimated to be responsible for nearly 800 deaths. Here, future projections under SRES higher (A1FI) and lower (B1) emission scenarios are used to estimate the frequency of 1995-like heat wave events in terms of both meteorological characteristics and impacts on heat-related mortality. Before end of century, 1995-like heat waves could occur every other year on average under lower emissions and as frequently as three times per year under higher. Annual average mortality rates are projected to equal those of 1995 under lower emissions and reach twice 1995 levels under higher. An “analog city” analysis, transposing the weather conditions from the European Heat Wave of 2003 (responsible for 70,000 deaths across Europe) to the city of Chicago, estimates that if a similar heat wave were to occur over Chicago, more than ten times the annual average number of heat-related deaths could occur in just a few weeks. Climate projections indicate that an EHW-type heat wave could occur in Chicago by mid-century. Between mid- and end-of-century, there could be as many as five such events under lower, and twenty-five under higher emissions. These results highlight the importance of both preventive mitigation and responsive adaptation strategies in reducing the vulnerability of Chicagos population to climate change-induced increases in extreme heat.

An Examination of Climate Change on Extreme Heat Events and Climate–Mortality Relationships in Large U.S. Cities

This study examines the impact of a changing climate on heat-related mortality in 40 large cities in the United States. A synoptic climatological procedure, the spatial synoptic classification, is used to evaluate present climate‐mortality relationships and project how potential climate changes might affect these values. Specifically,the synopticclassificationis combinedwithdownscaledfutureclimateprojectionsforthedecadal periods of 2020‐29, 2045‐55, and 2090‐99 from a coupled atmospheric‐oceanic general circulation model. The results show an increase in excessive heat event (EHE) days and increased heat-attributable mortality across the study cities with the most pronounced increases projected to occur in the Southeast and Northeast. This increase becomes more dramatic toward the end of the twenty-first century as the anticipated impact of climate change intensifies. The health impact associated with different emissions scenarios is also examined. These results suggest that a ‘‘business as usual’’ approach to greenhouse gas emissions mitigation could result in twice as many heat-related deaths by the end of the century than a lower emissions scenario. Finally, a comparison of future estimates of heat-related mortality during EHEs is presented using algorithms developed during two different, although overlapping, time periods, one that includes some recent large-scale significant EHE intervention strategies (1975‐2004), and one without (1975‐95). The results suggest these public health responses can significantly decrease heat-related mortality.

Analysis of vertical wind shear in the Southern Great Plains and potential impacts on estimation of wind energy production

This paper describes the analysis of near-surface wind speeds in Western Oklahoma. The goals of this research are to characterise the nocturnal low-level jet (LLJ) in the region, and to assess the impact wind variability, vertical shear and the LLJ on wind energy calculations. Results show the seasonal variability in wind characteristics as well as in the vertical wind shear, and also illustrate the errors associated with traditional estimates of wind power density in locations with a decoupled wind field. A comparison of projected energy output from three standard commercial turbines shows that traditional density estimations significantly underestimated power yield. The mean wind power density estimated via traditional means is significantly less than a more complete determination incorporating the LLJ. This difference illustrates the need to acquire accurate information regarding 50-150 m wind variability to produce improved estimates of wind energy resources.

A SYNOPTIC CLIMATOLOGICAL ANALYSIS OF SUMMERTIME PRECIPITATION INTENSITY IN THE EASTERN UNITED STATES

The spatial patterns of precipitation frequency and intensity over the eastern United States for summer from 1961 to 1990 are analyzed using a recently developed continental-scale air mass-based synoptic classification. This procedure, the spatial synoptic classification (SSC), is based on “seed” day identification of synoptic events and discriminant analysis to group together days that are within the same air-mass type. Results show differences in the types of precipitation associated with different air masses. Two air masses in particular-Moist Tropical and Moist Temperate-appear to be highly correlated with a majority of the precipitation, particularly in the southeast. The synoptic characteristics, daily intensity of rainfall, and radiosonde soundings during prevalence of these two air masses suggest that convective rainfall is common during Moist Tropical, and stratiform-type rainfall occurs during Moist Temperate. A simple stratification scheme based upon a synoptic-based air-mass delineation may be...

Advanced Wind Resource Characterization and Stationarity analysis for Improved Wind Farm Siting

A fundamental question of interest is “What are the geographic patterns of the renewable wind resources?” Knowledge of the location of local wind capacity remains vital to the industry, yet commercially viable renewable-related geospatial products that meet the needs of the wind and weather science industries are often suspect. There are three stages involved with wind power project planning and operations during which accurate characterization of the wind plays a critical role: • Prospecting (Siting): uses historical data, retrospective forecasts, and statistical methods to identify potential sites for wind power projects; • Site Assessment (Micrositing): determines the placement of a wind power project; and, • Operations: uses wind forecasts to determine available power output for hour-ahead and day-ahead time frames. The most critical of these is the first – identifying and characterizing the resource. This chapter will discuss this first stage in detail, outlining the state of the art in understanding the wind resource, and discussing the strengths and weaknesses of existing methods. For example, appropriate statistical and modeling methods to compute the wind speed probability density function (PDF) will be described and critically examined. In addition, although there has been an increasing awareness of renewable energy as a viable energy supply source, there has not been a concomitant increase in the awareness of the impacts that any spatial and temporal trends in the resource (e.g., in the wind speeds themselves) may have on long-term production, use, and implementation of renewable energy and renewable energy policy. Thus, potential changes of the wind field under a changing climate will also be discussed. As will be described in more detail below, the main topics under examination in this paper are: 1) accurate portrayal of the resource; and 2) potential implications of climate change on the wind resource of the future. The overall result will be an improved understanding of how the siting process works.

Ground Validation for the Global Precipitation Climatology Project

This paper discusses the role of the Surface Reference Data Center (SRDC) and the activities associated with data collection, error characterization, and validation associated with the Global Precipitation Climatology Project (GPCP). Housed in the Environmental Verification and Analysis Center (EVAC) at the University of Oklahoma, the EVAC/SRDC has built upon work from past NOAA-supported projects to become a unique location for scientists to obtain scarce rain gauge data and to conduct research into verification activities. These data are continually analyzed to produce error-assessed rainfall products. Scientists need only to access the EVAC/SRDC web site (http://www.evac.ou.edu/ srdc) to obtain critical global rain gauge data sets. Many of these data sets are impossible to obtain elsewhere. In this paper we will discuss the data collection, analysis, and validation methodology activities of the SRDC.