Harold E. Brooks

Flash flood forecasting : An ingredients-based methodology

Abstract An approach to forecasting the potential for flash flood-producing storms is developed, using the notion of basic ingredients. Heavy precipitation is the result of sustained high rainfall rates. In turn, high rainfall rates involve the rapid ascent of air containing substantial water vapor and also depend on the precipitation efficiency. The duration of an event is associated with its speed of movement and the size of the system causing the event along the direction of system movement. This leads naturally to a consideration of the meteorological processes by which these basic ingredients are brought together. A description of those processes and of the types of heavy precipitation-producing storms suggests some of the variety of ways in which heavy precipitation occurs. Since the right mixture of these ingredients can be found in a wide variety of synoptic and mesoscale situations, it is necessary to know which of the ingredients is critical in any given case. By knowing which of the ingredients...

The spatial distribution of severe thunderstorm and tornado environments from global reanalysis data

Proximity sounding analysis has long been a tool to determine environmental conditions associated with different kinds of weather events and to discriminate between them. It has been limited, necessarily, by the spatial and temporal distribution of soundings. The recent development of reanalysis datasets that cover the globe with spatial grid spacing on the order of 200 km and temporal spacing every 6 h allows for the possibility of increasing the number of proximity soundings by creating ‘‘pseudo-soundings.’’ We have used the National Center for Atmospheric Research (NCAR)/United States National Centers for Environmental Prediction (NCEP) reanalysis system to create soundings and find environmental conditions associated with significant severe thunderstorms (hail at least 5 cm in diameter, wind gusts at least 120 km h � 1 , or a tornado of at least F2 damage) and to discriminate between significant tornadic and non-tornadic thunderstorm environments in the eastern United States for the period 1997–1999. Applying the relationships from that region to Europe and the rest of the globe, we have made estimates of the frequency of favorable conditions for significant severe thunderstorms. Southern Europe has the greatest frequency of significant severe thunderstorm environments, particularly over the Spanish plateau and the region east of the Adriatic Sea. Favorable significant tornadic environments are found in France and east of the Adriatic. Worldwide, favorable significant thunderstorm environments are concentrated in equatorial Africa, the central United States, southern Brazil and northern Argentina, and near the Himalayas. Tornadic environments are by far the most common in the central United States, with lesser areas in southern Brazil and northern Argentina. Published by Elsevier B.V.

On the Environments of Tornadic and Nontornadic Mesocyclones

Abstract The authors investigated differences in the environments associated with tornadic and nontornadic mesocyclones are investigated using proximity soundings. Questions about the definition of proximity are raised. As the environments of severe storms with high spatial and temporal resolution are observed, the operational meaning of proximity becomes less clear. Thus the exploration of the proximity dataset is subject to certain caveats that are presented in some detail. Results from this relatively small proximity dataset support a recently developed conceptual model of the development and maintenance of low-level mesocyclones within supercells. Three regimes of low-level mesocyclonic behavior are predicted by the conceptual model: (i) low-level mesocyclones are slow to develop, if at all, (ii) low-level mesocyclones form quickly but are short lived, and (iii) low-level mesocyclones develop slowly but have the potential to persist for hours. The model suggests that a balance is needed between the mi...

Monitoring and Understanding Changes in Heat Waves, Cold Waves, Floods, and Droughts in the United States: State of Knowledge

Weather and climate extremes have been varying and changing on many different time scales. In recent decades, heat waves have generally become more frequent across the United States, while cold waves have been decreasing. While this is in keeping with expectations in a warming climate, it turns out that decadal variations in the number of U.S. heat and cold waves do not correlate well with the observed U.S. warming during the last century. Annual peak flow data reveal that river flooding trends on the century scale do not show uniform changes across the country. While flood magnitudes in the Southwest have been decreasing, flood magnitudes in the Northeast and north-central United States have been increasing. Confounding the analysis of trends in river flooding is multiyear and even multidecadal variability likely caused by both large-scale atmospheric circulation changes and basin-scale “memory” in the form of soil moisture. Droughts also have long-term trends as well as multiyear and decadal variability...

Climatological Estimates of Local Daily Tornado Probability for the United States

Abstract An estimate is made of the probability of an occurrence of a tornado day near any location in the contiguous 48 states for any time during the year. Gaussian smoothers in space and time have been applied to the observed record of tornado days from 1980 to 1999 to produce daily maps and annual cycles at any point on an 80 km × 80 km grid. Many aspects of this climatological estimate have been identified in previous work, but the method allows one to consider the record in several new ways. The two regions of maximum tornado days in the United States are northeastern Colorado and peninsular Florida, but there is a large region between the Appalachian and Rocky Mountains that has at least 1 day on which a tornado touches down on the grid. The annual cycle of tornado days is of particular interest. The southeastern United States, outside of Florida, faces its maximum threat in April. Farther west and north, the threat is later in the year, with the northern United States and New England facing its ma...

Changes in severe thunderstorm environment frequency during the 21st century caused by anthropogenically enhanced global radiative forcing.

Severe thunderstorms comprise an extreme class of deep convective clouds and produce high-impact weather such as destructive surface winds, hail, and tornadoes. This study addresses the question of how severe thunderstorm frequency in the United States might change because of enhanced global radiative forcing associated with elevated greenhouse gas concentrations. We use global climate models and a high-resolution regional climate model to examine the larger-scale (or “environmental”) meteorological conditions that foster severe thunderstorm formation. Across this model suite, we find a net increase during the late 21st century in the number of days in which these severe thunderstorm environmental conditions (NDSEV) occur. Attributed primarily to increases in atmospheric water vapor within the planetary boundary layer, the largest increases in NDSEV are shown during the summer season, in proximity to the Gulf of Mexico and Atlantic coastal regions. For example, this analysis suggests a future increase in NDSEV of 100% or more in locations such as Atlanta, GA, and New York, NY. Any direct application of these results to the frequency of actual storms also must consider the storm initiation.

Using Ensembles for Short-Range Forecasting

Numerical forecasts from a pilot program on short-range ensemble forecasting at the National Centers for Environmental Prediction are examined. The ensemble consists of 10 forecasts made using the 80-km Eta Model and 5 forecasts from the regional spectral model. Results indicate that the accuracy of the ensemble mean is comparable to that from the 29-km Meso Eta Model for both mandatory level data and the 36-h forecast cyclone position. Calculations of spread indicate that at 36 and 48 h the spread from initial conditions created using the breeding of growing modes technique is larger than the spread from initial conditions created using different analyses. However, the accuracy of the forecast cyclone position from these two initialization techniques is nearly identical. Results further indicate that using two different numerical models assists in increasing the ensemble spread significantly. There is little correlation between the spread in the ensemble members and the accuracy of the ensemble mean for the prediction of cyclone location. Since information on forecast uncertainty is needed in many applications, and is one of the reasons to use an ensemble approach, the lack of a correlation between spread and forecast uncertainty presents a challenge to the production of short-range ensemble forecasts. Even though the ensemble dispersion is not found to be an indication of forecast uncertainty, significant spread can occur within the forecasts over a relatively short time period. Examples are shown to illustrate how small uncertainties in the model initial conditions can lead to large differences in numerical forecasts from an identical numerical model.

Evolution of the U.S. Tornado Database: 1954–2003

Abstract Over the last 50 yr, the number of tornadoes reported in the United States has doubled from about 600 per year in the 1950s to around 1200 in the 2000s. This doubling is likely not related to meteorological causes alone. To account for this increase a simple least squares linear regression was fitted to the annual number of tornado reports. A “big tornado day” is a single day when numerous tornadoes and/or many tornadoes exceeding a specified intensity threshold were reported anywhere in the country. By defining a big tornado day without considering the spatial distribution of the tornadoes, a big tornado day differs from previous definitions of outbreaks. To address the increase in the number of reports, the number of reports is compared to the expected number of reports in a year based on linear regression. In addition, the F1 and greater Fujita-scale record was used in determining a big tornado day because the F1 and greater series was more stationary over time as opposed to the F2 and greater...

Climatological Estimates of Daily Local Nontornadic Severe Thunderstorm Probability for the United States

Abstract The probability of nontornadic severe weather event reports near any location in the United States for any day of the year has been estimated. Gaussian smoothers in space and time have been applied to the observed record of severe thunderstorm occurrence from 1980 to 1994 to produce daily maps and annual cycles at any point. Many aspects of this climatology have been identified in previous work, but the method allows for the consideration of the record in several new ways. A review of the raw data, broken down in various ways, reveals that numerous nonmeteorological artifacts are present in the raw data. These are predominantly associated with the marginal nontornadic severe thunderstorm events, including an enormous growth in the number of severe weather reports since the mid-1950s. Much of this growth may be associated with a drive to improve warning verification scores. The smoothed spatial and temporal distributions of the probability of nontornadic severe thunderstorm events are presented in...

Precipitation forecasting using a neural network

A neural network, using input from the Eta Model and upper air soundings, has been developed for the probability of precipitation (PoP) and quantitative precipitation forecast (QPF) for the Dallas‐Fort Worth, Texas, area. Forecasts from two years were verified against a network of 36 rain gauges. The resulting forecasts were remarkably sharp, with over 70% of the PoP forecasts being less than 5% or greater than 95%. Of the 436 days with forecasts of less than 5% PoP, no rain occurred on 435 days. On the 111 days with forecasts of greater than 95% PoP, rain always occurred. The linear correlation between the forecast and observed precipitation amount was 0.95. Equitable threat scores for threshold precipitation amounts from 0.05 in. ( ;1 mm) to 1 in. (;25 mm) are 0.63 or higher, with maximum values over 0.86. Combining the PoP and QPF products indicates that for very high PoPs, the correlation between the QPF and observations is higher than for lower PoPs. In addition, 61 of the 70 observed rains of at least 0.5 in. (12.7 mm) are associated with PoPs greater than 85%. As a result, the system indicates a potential for more accurate precipitation forecasting.