J. Scott Greene

The Philadelphia Hot Weather–Health Watch/Warning System: Development and Application, Summer 1995

Abstract Last summer, Philadelphia, Pennsylvania, instituted a new Hot Weather-Health Watch/Warning System (PWWS) to alert the citys residents of potentially oppressive weather situations that could negatively affect health. In addition, the system was used by the Philadelphia Department of Public Health for guidance in the implementation of mitigation procedures during dangerous weather. The system is based on a synoptic climatological procedure that identifies “oppressive” air masses historically associated with increased human mortality. Airmass occurrence can be predicted up to 48 h in advance with use of model output statistics guidance forecast data. The development and statistical basis of the system are discussed, and an analysis of the procedures ability to forecast weather situations associated with elevated mortality counts is presented. The PWWS, through greater public awareness of excessive heat conditions, may have played an important role in reducing Philadelphias total heat-related deat...

A NEW SPATIAL SYNOPTIC CLASSIFICATION: APPLICATION TO AIR-MASS ANALYSIS

Despite recent advances in the classification of synoptic-scale events, there remains the need for development of a simple, automated, continental- scale air mass-based procedure. We present a new method of analysis to identify resident air masses at first-order weather stations to facilitate intersite comparison of daily air masses across a very large region. The ‘spatial synoptic classification’ (SSC) requires initial identification of the major air masses and their typical meteorological characteristics at each site. ‘Seed days’, which exhibit these typical characteristics for each air mass, are used as input for a linear discriminant function analysis, which produces a daily categorization of air masses with spatially continuous results. A second discriminant function analysis is used to determine whether a day is to be considered transitional between air masses. Using the SSC, air-mass frequencies were developed for winter across the USA east of the Rockies, and rates of modification were determined as each air mass traversed the region. The impact of snow cover on modification rates was determined by comparing two winter months with very different snow cover characteristics across the area. Keeping other factors constant, it appears that extended snow cover can reduce the temperature of a dry polar air mass by up to 11°C.

The impacts of weather and pollution on human mortality in Birmingham, Alabama and Philadelphia, Pennsylvania.

Past studies have examined how both extreme weather and atmospheric pollutants influence human mortality. However, the differential and/or synergistic impacts of weather and pollution on mortality are poorly understood. This relationship is particularly notable in summer, when both extreme weather and high pollution episodes are frequent. The goal of this study is to describe the relationship between atmospheric conditions (as characterized by weather and air pollution) and mortality in the summer season for Birmingham, Alabama and Philadelphia, Pennsylvania. To assess the health impacts of both weather and pollution (ozone and total suspended particulates, or TSP), we used a synoptic, or air mass-based, approach to take into account the entire weather situation, rather than individual weather elements. This method was used to identify ‘offensive’ air masses, which are associated with elevated mortality, and then to investigate which individual or combination of atmospheric conditions poses the greatest threat to human health in terms of acute (daily) mortality. In both cities, offensive weather events have a greater impact on acute mortality than high concentrations of TSP or ozone. The highest mortality levels occur when the hottest, but not the most polluted, air mass is present in each city. In Philadelphia, neither TSP nor ozone appear to contribute an ‘add on’ effect to weather-related mortality. Under non-offensive weather situations, pollution concentrations are associated with increased mortality in Philadelphia. Yet, regardless of pollution concentration, mortality levels are much lower for these air masses than for offensive events. Pollution appears to be more important for mortality in Birmingham. Although Birminghams high-mortality (offensive) air mass is not the most polluted, offensive air mass days with high pollution concentrations nonetheless exhibit higher mean mortality than offensive air mass days with low pollution concentrations. Also different from Philadelphia is a lack of a relationship in Birmingham between pollution levels and mortality on non-offensive air mass days. The relationship between summer weather and mortality is strong in both cities, while the role of pollution is less clear. This research underscores the imperative need for the development of a weather/health watch-warning system to alert the public that an offensive synoptic situation is imminent. Copyright

ANALOG EUROPEAN HEAT WAVES FOR U.S. CITIES TO ANALYZE IMPACTS ON HEAT-RELATED MORTALITY

Abstract Europe experienced an unprecedented excessive heat event (EHE) in 2003, raising the question: What if a similar EHE were experienced in U.S. cities? This study used an airmass-based meteorological method to develop analogs to the 2003 European EHE for five U.S. cities: Detroit, New York, Philadelphia, St. Louis, and Washington, D.C.; and calculated the potential excess mortality for these analogs. Analogs capture the 2003 EHEs characteristics by determining daily deviations from long-term averages for meteorological variables in Paris, France, expressed as a multiple of the standard deviation for each variables long-term average. The 2003 daily multiples of the standard deviation measured in Paris for 12 meteorological variables, and daily maximum and minimum temperatures, were transferred to each U.S. city, and multiplied by the corresponding standard deviation calculated for each variable, to produce analog meteorological variables. With these data, an airmass calendar for each city was devel...

Validation and Uncertainty Analysis of Satellite Rainfall Algorithms

Satellites, while offering excellent spatial coverage, determine precipitation indirectly, using algorithms that transform satellite-sensed radiance (either emitted or scattered) from clouds or raindrops into precipitation. A large uncertainty is associated with satellite precipitation estimates, stemming from unknown variation in space and time of the physical and statistical relationships between precipitation and satellite-sensed radiance. To mitigate this, satellite algorithms must be calibrated and verified using surface precipitation sampled from different climate regimes and seasons. Recently developed statistical techniques have been used effectively to reduce spatial sampling error associated with sparsely distributed raingages and thereby improve our understanding of satellite algorithm quality. This paper provides an example of satellite precipitation validation, including a description of the types of satellite data used to estimate precipitation, as well as the results from a major project (the Global Precipitation Climatology Project [GPCP]), to estimate global precipitation through a combination of satellite and raingage products. In addition, a recently developed procedure to investigate spatial averaging, scaling, and uncertainty analysis will be used to examine the GPCP product. Specifically, uncertainty analysis applied to comparisons between satellite monthly rainfall estimates and rainfall estimates constructed from Pacific atoll-sited raingauge sites will be discussed.

An Improved Method for Estimating the Wind Power Density Distribution Function

Abstract The wind power density (WPD) distribution curve is essential for wind power assessment and wind turbine engineering. The usual practice of estimating this curve from wind speed data is to first estimate the wind speed probability density function (PDF) using a nonparametric or parametric method. The density function is then multiplied by one-half the wind speed cubed times the air density. Unfortunately, this means that minor errors in the estimation of the wind speed PDF can result in large errors in the WPD distribution curve because the cubic term in the WPD function magnifies the error. To avoid this problem, this paper presents a new method of estimating the WPD distribution curve through a direct estimation of the curve using a Gauss–Hermite expansion. It is demonstrated that the proposed method provides a much more reliable estimate of the WPD distribution curve.

Estimated changes in wind speed and wind power density over the western High Plains, 1971–2000

This manuscript presents the results of research on the temporal patterns in wind speed and wind power density from 1971 to 2000. The study area is across the western High Plains states east of the Rocky Mountains in an area which has a proven wind power resource. Policies and economic analyses involving the rapidly expanding wind power industry have often assumed a constant in the wind resource; however, any temporal pattern or trend in wind speeds can have a meaningful impact on the reliability of wind power as an energy resource. Using data provided by the North American Regional Climate Change Assessment Program (NARCCAP) to analyze decadal and seasonal trends of wind data, this study shows that from 1971 to 2000 there were some notable changes in the NARCCAP simulated wind velocities over the study region. Wind speed trends across the central High Plains of the USA were most notable across the western portion of the study area along the higher terrain near the front range of the Rocky Mountains. The most significant changes occurred during winter and spring when a large portion of the study area experienced the most substantial decrease in wind speed, with a 20% reduction in wind power density during spring across the western portion of the study area. During summer and fall, the trends are less noticeable, with only very small changes in the summer. Fall was the only season that saw widespread increased values of wind power density from the 1970s to 1990s, with increases of nearly 10% in some southern areas of the study area. Based upon the analysis of the data and previous literature, it is theorized that these changes could be the result of changing synoptic patterns across the study region.

The Comprehensive Pacific Rainfall Database

Abstract This paper describes the Comprehensive Pacific Rainfall Database (PACRAIN), which contains daily and monthly precipitation records from the tropical Pacific basin. The database is a collection of observations from a variety of sources, including one, the Schools of the Pacific Rainfall Climate Experiment (SPaRCE), that is unique to PACRAIN. SPaRCE is a cooperative field project and involves schools from various Pacific island and atoll nations. Recent enhancements to the database, including improved quality control, observation and data entry standardization, expansion of the network, increased collaboration with local meteorological directors, and enhanced high-resolution data (e.g., on hourly or minute time scales), are discussed. This paper also outlines some of the internal data and Web-based access specifics of the database. To illustrate the potential usefulness of the data, two examples of research using the PACRAIN database are provided and discussed. The first is an analysis of temporal ...

The application of the European heat wave of 2003 to Korean cities to analyze impacts on heat-related mortality.

The goal of this research is to transpose the unprecedented 2003 European excessive heat event to six Korean cities and to develop meteorological analogs for each. Since this heat episode is not a model but an actual event, we can use a plausible analog to assess the risk of increasing heat on these cities instead of an analog that is dependent on general circulation (GCM) modeling or the development of arbitrary scenarios. Initially, the 2003 summer meteorological conditions from Paris are characterized statistically and these characteristics are transferred to the Korean cites. Next, the new meteorological dataset for each Korean city is converted into a daily air mass calendar. We can then determine the frequency and character of “offensive” air masses in the Korean cities that are historically associated with elevated heat-related mortality. One unexpected result is the comparative severity of the very hot summer of 1994 in Korea, which actually eclipsed the 2003 analog. The persistence of the offensive air masses is considerably greater for the summer of 1994, as were dew point temperatures for a majority of the Korean cities. For all the Korean cities but one, the summer of 1994 is associated with more heat-related deaths than the analog summer, in some cases yielding a sixfold increase over deaths in an average summer. The Korean cities appear less sensitive to heat-related mortality problems during very hot summers than do large eastern and Midwestern US cities, possibly due to a lesser summer climate variation and efficient social services available during extreme heat episodes.

An Isofactorial Change-of-Scale Model for the Wind Speed Probability Density Function

Abstract The wind speed probability density function (PDF) is used in a variety of applications in meteorology, oceanography, and climatology usually as a dataset comparison tool of a function of a quantity such as momentum flux or wind power density. The wind speed PDF is also a function of measurement scale and sampling error. Thus, quantities derived from a function of the wind PDF estimated from measurements taken at different scales may yield vastly different results. This is particularly true in the assessment of wind power density and studies of model subgrid-scale processes related to surface energy fluxes. This paper presents a method of estimating the PDF of wind speed representing a specific scale, whether that is in time, space, or time–space. The concepts used have been developed in the field of nonlinear geostatistics but have rarely been applied to meteorological problems. The method uses an expansion of orthogonal polynomials that incorporates a scaling parameter whose values can be found ...