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The snow level, or altitude in the atmosphere where snow melts to rain, is an important variable for hydrometeorological prediction in mountainous watersheds; yet, there is no operational performance measure associated with snow-level forecasts in the United States. To establish a performance measure, it is first necessary to establish the baseline performance associated with snow-level forecasts. Using data collected by vertically pointing Doppler radars, an automated algorithm has been developed to detect the altitude of maximum radar reflectivity in the radar bright band that results from the precipitation melting process. This altitude can be used as a proxy for the snow level, partly because it always exists below the freezing level, which is defined as the altitude of the 0°C isotherm. The skill of freezing-level forecasts produced by the California–Nevada River Forecast Center (CNRFC) is evaluated by comparing spatially interpolated and forecaster-adjusted numerical model freezing-level forecasts with observed freezing levels estimated by radars operating at 2875 MHz (S band). The freezing level was chosen instead of the snow level as the comparison parameter because the radar algorithm and the CNRFC have different interpretations of the snow level. The evaluation occurred at two sites: one in the coastal mountains north of San Francisco and the other in the Sierra Nevada. The evaluation was conducted for forecasts made during the winter wet season of 2005/06. Although the overall mean freezing-level forecast bias is small enough not to be hydrologically significant, about 15% of the forecasts had biases greater than 300 m (forecast too low). The largest forecast biases were associated with freezing levels above 2.3 km that were underforecasted by as much as 900 m. These high freezing-level events were accompanied by the heaviest precipitation intensities, exacerbating the flood threat and making the forecast even more challenging. [ABSTRACT FROM AUTHOR]

A robust and easily implemented verification procedure based on the column-integrated precipitable water (IPW) vapor estimates derived from a network of ground-based global positioning system (GPS) receivers has been used to assess the quality of the Atmospheric Infrared Sounder (AIRS) IPW retrievals over the contiguous United States. For a period of six months from April to October 2004, excellent agreement has been realized between GPS-derived IPW estimates and those determined from AIRS, showing small monthly bias values ranging from 0.5 to 1.5 mm and root-mean-square (rms) differences of 4 mm or less. When the spatial (latitude–longitude) window for the GPS and AIRS matchup observations is reduced from the initial ½° by ½° to ¼° by ¼°, the rms differences are reduced. Analysis revealed that the observed IPW biases between the instruments are strongly correlated to the reported surface pressure differences between the GPS and AIRS observational points. Adjusting the AIRS IPW values to account for the surface pressure discrepancies resulted in significant reductions of the bias between GPS and AIRS. A similar reduction can be obtained by comparing only (GPS–AIRS) match-up pairs for which the corresponding surface pressure differences are 0.5 mb or less. The comparisons also revealed that the AIRS IPW tends to be relatively dry in moist atmospheres (when IPW values >40 mm) but wetter in dry cases (when IPW values <10 mm). This is consistent with the documented bias of satellite measurements toward the first guess used in retrieval algorithms. However, additional study is needed to verify whether the AIRS water vapor retrieval process is the source of the discrepancies. It is shown that the IPW bias and rms differences have a seasonal dependency, with a maximum in summer (bias ∼ 1.2 mm, rms ∼ 4.14 mm) and minimum in winter (bias < -0.5 mm, rms ∼ 3 mm). [ABSTRACT FROM AUTHOR]

The primary weather forecast challenge at the Cape Canaveral Air Station and Kennedy Space Center is lightning. This paper describes a statistical approach that combines integrated precipitable water vapor (IPWV) data from a global positioning system (GPS) receiver site located at the Kennedy Space Center (KSC) with other meteorological data to develop a new GPS lightning index. The goal of this effort is to increase the forecasting skill and lead time for prediction of a first strike at the KSC. Statistical regression methods are used to identify predictors that contribute skill in forecasting a lightning event. Four predictors were identified out of a field of 23 predictors that were tested, determined using data from the 1999 summer thunderstorm season. They are maximum electric field mill values, GPS IPWV, 9-h change in IPWV, and K index. The GPS lightning index is a binary logistic regression model made up of coefficients multiplying the four predictors. When time series of the GPS lightning index are plotted, a common pattern emerges several hours prior to a lightning event. Whenever the GPS lightning index falls to 0.7 or below, lightning occurs within the next 12.5 h. An index threshold value of 0.7 was determined from the data for lightning prediction. Forecasting time constraints based on KSC weather notification requirements were incorporated into the verification. Forecast verification results obtained by using a contingency table revealed a 26.2% decrease from the KSC's previous-season false alarm rates for a nonindependent period and a 13.2% decrease in false alarm rates for an independent test season using the GPS lightning index. In addition, the index improved the KSC desired lead time by nearly 10%. Although the lightning strike window of 12 h is long, the GPS lightning index provides useful guidance to the forecaster in preparing lighting forecasts, when combined with other resources such as radar and satellite data. Future testing of the GPS... [ABSTRACT FROM AUTHOR]

Background: The impact of socioeconomic status (SES) has been described for screening and accessing treatment for colon cancer. However, little is known about the "downstream" effect in patients who receive guideline-concordant treatment. This study assessed the impact of SES on cancer-specific survival (CSS) and overall survival (OS) for stage III colon cancer patients., Methods: The SEER Census Tract-Level SES Dataset from 2004 to 2015 was used to identify stage III colon adenocarcinoma patients who received curative-intent surgery and adjuvant chemotherapy. The predictor variable was census tract SES. SES was analyzed as quintiles. The outcome variables were OR and CSS. Statistical analysis included chi square tests for association, Kaplan-Meier, Cox, Fine and Gray regression for survival analysis., Results: In total, 27,222 patients met inclusion criteria. Lower SES was associated with younger age, Black or Hispanic race/ethnicity, Medicaid/uninsured, higher T stage, and lower grade tumors. CSS at the 25th percentile was 54 months for the lowest SES quintile and 80 for the highest. Median OS was 113 months for the lowest SES quintile and not reached for highest. The 5-year CSS rate was 72.4% for the lowest SES quintile compared to 78.9% in the highest (p < 0.001). The 5-year OS rate was 66.5% for the lowest SES quintile and 74.6% in the highest (p < 0.001)., Conclusion: This is the first study to evaluate CSS and OS in an incidence-based cohort of stage III colon cancer patients using a granular, standardized measure of SES. Despite receipt of guideline-based treatment, SES was associated with disparities in CSS and OS., (© 2021 The Authors. Cancer Medicine published by John Wiley & Sons Ltd.)

Racial disparities in health are well-documented and represent a significant public health concern in the US. Racism-related factors contribute to poorer health and higher mortality rates among Blacks compared to other racial groups. However, methods to measure racism and monitor its associations with health at the population-level have remained elusive. In this study, we investigated the utility of a previously developed Internet search-based proxy of area racism as a predictor of Black mortality rates. Area racism was the proportion of Google searches containing the "N-word" in 196 designated market areas (DMAs). Negative binomial regression models were specified taking into account individual age, sex, year of death, and Census region and adjusted to the 2000 US standard population to examine the association between area racism and Black mortality rates, which were derived from death certificates and mid-year population counts collated by the National Center for Health Statistics (2004-2009). DMAs characterized by a one standard deviation greater level of area racism were associated with an 8.2% increase in the all-cause Black mortality rate, equivalent to over 30,000 deaths annually. The magnitude of this effect was attenuated to 5.7% after adjustment for DMA-level demographic and Black socioeconomic covariates. A model controlling for the White mortality rate was used to further adjust for unmeasured confounders that influence mortality overall in a geographic area, and to examine Black-White disparities in the mortality rate. Area racism remained significantly associated with the all-cause Black mortality rate (mortality rate ratio = 1.036; 95% confidence interval = 1.015, 1.057; p = 0.001). Models further examining cause-specific Black mortality rates revealed significant associations with heart disease, cancer, and stroke. These findings are congruent with studies documenting the deleterious impact of racism on health among Blacks. Our study contributes to evidence that racism shapes patterns in mortality and generates racial disparities in health.

Purpose: To determine whether chargemaster (a list of prices for common services and procedures set by individual hospitals) rates for diagnostic imaging were lower in states that cap awards for noneconomic damages (NED) than states with unlimited awards for medical negligence., Methods: We analyzed 2011 chargemaster data from the Centers for Medicare & Medicaid, pertaining to 6 ambulatory patient classifications specific to imaging. The dataset includes outpatient imaging facilities and hospitals in 49 states and the District of Columbia. The association between caps on NED and chargemaster rates for imaging in a sample of 15,218 data points was analyzed using linear regression and two-sample t tests assuming unequal variances., Results: In states that cap NED, the chargemaster rates were higher for the following modalities: Level II Echocardiogram without Contrast (mean charges: $2,015.60 versus $1,884.81, P = .0018); Level II Cardiac Imaging ($4,670.25 versus $4,398.58, P = .002); MRI & Magnetic Resonance Angiography without Contrast ($2,654.31 versus $2,526.74, P = .002); and Level III Diagnostic and Screening Ultrasound ($1,073.31 versus $1,027.32, P = .037). High charge-to-payment ratios were associated with states with the highest charges. There was a positive correlation between number of outpatient centers in the state and the average chargemaster rates for the state (mean chargemaster rate = 1727 + 0.79*Number of Outpatient Centers; R-squared = 0.23, P = .0004)., Conclusions: Chargemaster rates for select imaging services are not lower in states that have capped NED., (Copyright © 2014 American College of Radiology. Published by Elsevier Inc. All rights reserved.)

Background: Cirrhosis is known to be a significant risk factor for morbidity and mortality following trauma such that its presence is a requirement for trauma center transfer. The impact of trauma center level on post-injury survival in cirrhotic patients has not been well studied., Methods: The National Trauma Databank (version 7) was used to identify patients admitted with cirrhosis as a preexisting comorbidity. Patients who were dead on arrival, died in the emergency department, or had missing trauma center information were excluded. Our primary outcome measure was overall mortality stratified by admission trauma center level. Logistic regression analysis was used to derive adjusted mortality results., Results: A total of 3,395 patients met inclusion criteria (0.16% of all National Trauma Databank patients). Patients admitted to a Level I center were more likely to be younger and minorities, experience penetrating injuries, and require immediate operative intervention despite similar Injury Severity Scores (ISS). Overall mortality was lower at Level I centers compared with other centers (10.3% vs. 14.0%, p = 0.001). After logistic regression, Level I centers were associated with significantly lower mortality compared with non-Level I centers (adjusted odds ratio, 0.70; 95% confidence interval, 0.53-0.89; p = 0.004)., Conclusion: The mortality for cirrhotic patients admitted to a Level I trauma center was significantly less compared with those admitted to non-Level I centers. The etiology of this improved outcome needs to be identified and transmitted to non-Level I centers., Level of Evidence: Epidemiologic study, level III.