Search Results

You are looking at 1 - 3 of 3 items for

  • Author or Editor: S. D. Underwood x
  • All content x
Clear All Modify Search
S. Jeffrey Underwood and Michael D. Schultz

Abstract

Flash flood and debris flow reports from Storm Data and the U.S. Geological Survey (USGS) are used to investigate the relationship between hazardous hydrological responses, convective rainfall, and cloud-to-ground (CG) lightning flash parameters. Basins burned by the Coal Seam and Missionary Ridge wildfires during the summer of 2002 in western Colorado were selected as primary study areas. The North American monsoon (NAM) air mass played a pivotal role in providing low-level moisture over much of Colorado during each of the 12 hydrological events identified. Surface θ e values as high as 354 K were calculated over western Colorado in a composite analysis that also saw a θ e ridge through 500 hPa extending northward into Nebraska and southern South Dakota. Storm-total CG flashes were as high as 718, and the median flash total for the population of events was 256. Mean 5-min CG flash intensity for the events was 18.1 flashes. The mean rainfall intensity associated with the 12 hydrological events was 10.5 mm h−1, and average storm-total rainfall was 14.2 mm. Continuous CG flash sequences (one or more flashes per sequential 5-min interval) were significantly correlated with rainfall intensity, total rainfall, and rainfall duration for events generating postwildfire flash floods and debris flows. Operational utility may be derived from the observation of the mean lag time from the first recorded CG flash in a 7850-km2 study area to the peak rainfall intensity, and the mean lag time from peak CG flash rate to peak rainfall at the hydrological event location. The mean lag times for the 12 events in the study were 165 and 41 min, respectively.

Full access
Michael D. Schultz, S. Jeffrey Underwood, and Premkrishnan Radhakrishnan

Abstract

Currently, no uniform method exists for determining the optimal areal unit to analyze National Lightning Detection Network (NLDN) data. To address this problem, this paper utilizes the capabilities of modern geographic information systems (GIS) software to develop a consistent method for identifying areal analysis units while considering the location accuracy of the NLDN. Five grid cells were created at spatial resolutions of 0.1°, 0.2°, 0.3°, 0.4°, and 0.5°. To create cloud-to-ground (CG) lightning strikes, random points were generated at nine densities ranging from 1 to 9 strikes per square kilometer. A buffer of 500 m was placed around each random point to account for the margin of error in NLDN location accuracy. Random points that, when buffered to 500 m, still remained completely within the study region were evaluated as a percentage of all of the strikes to determine accuracy. The greatest accuracy of 95.88% was observed in the 0.5° grid cell at a density of 9 strikes per square kilometer. The lowest accuracy of 80.59% occurred in the 0.1° grid cell at a density of 4 strikes per square kilometer. There was little variation between the accuracies in similar grid cells regardless of their density, suggesting that CG flash density will have little effect on accuracy when selecting spatial resolution. Gains in accuracy diminished as spatial resolution increased. Gains in accuracy between the 0.1° and the 0.2° grid cells are approximately 9%. Gains in accuracy between the 0.4° and the 0.5° grid cells are less than 1%. To achieve 95% accuracy, a spatial resolution of no less than 0.4° is required.

Full access
G. A. Vecchi, T. Delworth, R. Gudgel, S. Kapnick, A. Rosati, A. T. Wittenberg, F. Zeng, W. Anderson, V. Balaji, K. Dixon, L. Jia, H.-S. Kim, L. Krishnamurthy, R. Msadek, W. F. Stern, S. D. Underwood, G. Villarini, X. Yang, and S. Zhang

Abstract

Tropical cyclones (TCs) are a hazard to life and property and a prominent element of the global climate system; therefore, understanding and predicting TC location, intensity, and frequency is of both societal and scientific significance. Methodologies exist to predict basinwide, seasonally aggregated TC activity months, seasons, and even years in advance. It is shown that a newly developed high-resolution global climate model can produce skillful forecasts of seasonal TC activity on spatial scales finer than basinwide, from months and seasons in advance of the TC season. The climate model used here is targeted at predicting regional climate and the statistics of weather extremes on seasonal to decadal time scales, and comprises high-resolution (50 km × 50 km) atmosphere and land components as well as more moderate-resolution (~100 km) sea ice and ocean components. The simulation of TC climatology and interannual variations in this climate model is substantially improved by correcting systematic ocean biases through “flux adjustment.” A suite of 12-month duration retrospective forecasts is performed over the 1981–2012 period, after initializing the climate model to observationally constrained conditions at the start of each forecast period, using both the standard and flux-adjusted versions of the model. The standard and flux-adjusted forecasts exhibit equivalent skill at predicting Northern Hemisphere TC season sea surface temperature, but the flux-adjusted model exhibits substantially improved basinwide and regional TC activity forecasts, highlighting the role of systematic biases in limiting the quality of TC forecasts. These results suggest that dynamical forecasts of seasonally aggregated regional TC activity months in advance are feasible.

Full access