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C. M. HAYDEN

Abstract

The scale of cloud clusters occurring in the tropical North Pacific is objectively derived from vidicon data received from the ESSA satellites for July and October 1967 and January and April 1968. Attention is focused on the inter-tropical convergence zone, which is defined to be the 10° latitude strip with greatest average brightness. The predominant width of cloud clusters is found to range from 275 km in winter to 450 km in summer. The most frequent distances separating clusters are 6°–8° and 10°–12° (latitude) without seasonal variation. The results indicate that a grid size suitable for tropical analysis is about half that used by the National Meteorological Center for midlatitude analysis.

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C. M. HAYDEN

Abstract

Tropospheric height and thickness values derived from Nimbus 3 Satellite Infra-Red Spectrometer (SIRS) sounding data are compared with nearby radiosonde data to determine (a) the accuracy and compatibility of SIRS data relative to the radiosonde and (b) the utility of SIRS data relative to the radiosonde, for objective analysis. The study shows that both the relative accuracy and the utility of the SIRS data are strongly dependent on cloud conditions, pressure level, and instrument status. SIRS thickness values in the upper troposphere compare well with radiosonde data. Loss of the 714 cm−1 channel in November 1969 greatly reduced the quality of the SIRS data, especially at lower levels; but prior to the loss, clear-air soundings show approximate parity with radiosonde observations.

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J. M. Lewis, C. M. Hayden, R. T. Merrill, and J. M. Schneider

During February and March 1988, a limited field experiment was conducted over the Gulf of Mexico to gather data on two phenomena: air mass modification over the Loop Current, and return flow characteristics of modified polar air returning to the southern shores of the United States. Six-hourly radiosondes, special Cross- Chain LORAN (Long-Range Aid to Navigation) Atmospheric Sounding System (CLASS) soundings, and three P-3 flights including dropwindsondes and Airborne Expendable Bathythermograph (AXBT) measurements were taken. The experiment objectives and the data are described.

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Lindsey R. Barnes, David M. Schultz, Eve C. Gruntfest, Mary H. Hayden, and Charles C. Benight

Abstract

Two items need to be clarified from an earlier work of the authors. The first is that the layout of the 2 × 2 contingency table was reversed from standard practice, with the titles of “observed event” and “forecast” transposed. The second is that FAR should have represented “false alarm ratio,” not “false alarm rate.” Unfortunately, the terminology used in the atmospheric sciences is confusing, with authors as early as 1965 having used the terminology differently from currently accepted practice. More recent studies are not much better. A survey of peer-reviewed articles published in American Meteorological Society journals between 2001 and 2007 found that, of 26 articles using those terms, 10 (38%) used them inconsistently with the currently accepted definitions. This article recommends that authors make explicit how their verification statistics are calculated in their manuscripts and consider using the terms probability of false detection and probability of false alarm instead of false alarm rate and false alarm ratio.

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J. A. Zandlo, W. L. Smith, W. P. Menzel, and C. M. Hayden

Abstract

A method to depict quasi-continuous surface temperature features is presented. Half-hourly GOES window channel brightness temperature determinations are employed to monitor time changes in the surface temperature field. TIROS-N water vapor channel measurements, within 6 h of the GOES measurements, are used to generate water vapor absorption corrections to the window channel brightness temperatures. Two case studies are presented that show the resulting surface radiating temperature estimates to be accurate close to 1 K. In regions where conventional ground based measurements are sparse, this method is demonstrated to be most useful. The potential for using time sequences of these surface temperature fields as a diagnostic aid for forecasting severe weather is exhibited in one of the case studies.

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Lindsey R. Barnes, Eve C. Gruntfest, Mary H. Hayden, David M. Schultz, and Charles Benight

Abstract

The false alarm rate (FAR) measures the fraction of forecasted events that did not occur, and it remains one of the key metrics for verifying National Weather Service (NWS) weather warnings. The national FAR for tornado warnings in 2003 was 0.76, indicating that only one in four tornado warnings was verified. The NWS’s goal for 2010 is to reduce this value to 0.70. Conventional wisdom is that false alarms reduce the public’s willingness to respond to future events. This paper questions this conventional wisdom. In addition, this paper argues that the metrics used to evaluate false alarms do not accurately represent the numbers of actual false alarms or the forecasters’ abilities because current metrics categorize events as either a hit or a miss and do not give forecasters credit for close calls. Aspects discussed in this paper include how the NWS FAR is measured, how humans respond to warnings, and what are alternative approaches to measure FAR. A conceptual model is presented as a framework for a new perspective on false alarms that includes close calls, providing a more balanced view of forecast verification.

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David M. Schultz, Eve C. Gruntfest, Mary H. Hayden, Charles C. Benight, Sheldon Drobot, and Lindsey R. Barnes

Abstract

One of the goals of the Warning Project is to understand how people receive warnings of hazardous weather and subsequently use this information to make decisions. As part of the project, 519 surveys from Austin, Texas, floodplain residents were collected and analyzed. About 90% of respondents understood that a tornado warning represented a more serious and more likely threat than a tornado watch. Most respondents (86%) were not concerned about a limited number of false alarms or close calls reducing their confidence in future warnings, suggesting no cry-wolf effect. Most respondents reported safe decisions in two hypothetical scenarios: a tornado warning issued while the respondent was home and a tornado visible by the respondent while driving. However, nearly half the respondents indicated that they would seek shelter from a tornado under a highway overpass if they were driving. Despite the limitations of this study, these results suggest that more education is needed on the dangers of highway overpasses as shelter from severe weather.

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Benjamin F. Zaitchik, Mary H. Hayden, Daniel A. M. Villela, Cynthia C. Lord, Uriel D. Kitron, José Joaquín Carvajal, Daniel C. P. Câmara, and Izabel C. dos Reis
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Auwal F. Abdussalam, Andrew J. Monaghan, Vanja M. Dukić, Mary H. Hayden, Thomas M. Hopson, Gregor C. Leckebusch, and John E. Thornes

Abstract

Northwest Nigeria is a region with a high risk of meningitis. In this study, the influence of climate on monthly meningitis incidence was examined. Monthly counts of clinically diagnosed hospital-reported cases of meningitis were collected from three hospitals in northwest Nigeria for the 22-yr period spanning 1990–2011. Generalized additive models and generalized linear models were fitted to aggregated monthly meningitis counts. Explanatory variables included monthly time series of maximum and minimum temperature, humidity, rainfall, wind speed, sunshine, and dustiness from weather stations nearest to the hospitals, and the number of cases in the previous month. The effects of other unobserved seasonally varying climatic and nonclimatic risk factors that may be related to the disease were collectively accounted for as a flexible monthly varying smooth function of time in the generalized additive models, s(t). Results reveal that the most important explanatory climatic variables are the monthly means of daily maximum temperature, relative humidity, and sunshine with no lag; and dustiness with a 1-month lag. Accounting for s(t) in the generalized additive models explains more of the monthly variability of meningitis compared to those generalized linear models that do not account for the unobserved factors that s(t) represents. The skill score statistics of a model version with all explanatory variables lagged by 1 month suggest the potential to predict meningitis cases in northwest Nigeria up to a month in advance to aid decision makers.

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Auwal F. Abdussalam, Andrew J. Monaghan, Daniel F. Steinhoff, Vanja M. Dukic, Mary H. Hayden, Thomas M. Hopson, John E. Thornes, and Gregor C. Leckebusch

Abstract

Meningitis remains a major health burden throughout Sahelian Africa, especially in heavily populated northwest Nigeria with an annual incidence rate ranging from 18 to 200 per 100 000 people for 2000–11. Several studies have established that cases exhibit sensitivity to intra- and interannual climate variability, peaking during the hot and dry boreal spring months, raising concern that future climate change may increase the incidence of meningitis in the region. The impact of future climate change on meningitis risk in northwest Nigeria is assessed by forcing an empirical model of meningitis with monthly simulations of seven meteorological variables from an ensemble of 13 statistically downscaled global climate model projections from phase 5 of the Coupled Model Intercomparison Experiment (CMIP5) for representative concentration pathway (RCP) 2.6, 6.0, and 8.5 scenarios, with the numbers representing the globally averaged top-of-the-atmosphere radiative imbalance (in W m−2) in 2100. The results suggest future temperature increases due to climate change have the potential to significantly increase meningitis cases in both the early (2020–35) and late (2060–75) twenty-first century, and for the seasonal onset of meningitis to begin about a month earlier on average by late century, in October rather than November. Annual incidence may increase by 47% ± 8%, 64% ± 9%, and 99% ± 12% for the RCP 2.6, 6.0, and 8.5 scenarios, respectively, in 2060–75 with respect to 1990–2005. It is noteworthy that these results represent the climatological potential for increased cases due to climate change, as it is assumed that current prevention and treatment strategies will remain similar in the future.

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