Search Results

You are looking at 1 - 5 of 5 items for :

  • Author or Editor: David A. Marks x
  • Weather and Forecasting x
  • All content x
Clear All Modify Search
David A. Short, James E. Sardonia, Winifred C. Lambert, and Mark M. Wheeler

Abstract

Electrified thunderstorm anvil clouds extend the threat of natural and triggered lightning to space launch and landing operations far beyond the immediate vicinity of thunderstorm cells. The deep convective updrafts of thunderstorms transport large amounts of water vapor, supercooled water droplets, and ice crystals into the upper troposphere, forming anvil clouds, which are then carried downstream by the prevailing winds in the anvil-formation layer. Electrified anvil clouds have been observed over the space launch and landing facilities of the John F. Kennedy Space Center and Cape Canaveral Air Force Station (CCAFS), emanating from thunderstorm activity more than 200 km away. Space launch commit criteria and flight rules require launch and landing vehicles to avoid penetration of the nontransparent portion of anvil clouds. The life cycles of 163 anvil clouds over the Florida peninsula and its coastal waters were documented using Geostationary Operational Environmental Satellite (GOES)-8 visible imagery on 49 anvil-case days during the months of May–July 2001. Anvil clouds were found to propagate at the speed and direction of upper-tropospheric winds in the layer from 300 to 150 hPa, approximately 9.4–14 km in altitude, with an effective average transport lifetime of approximately 2 h and a standard deviation of approximately 30 min. The effective lifetime refers to the time required for the nontransparent leading edge of an anvil cloud to reach its maximum extent before beginning to dissipate. The information about propagation and lifetime was incorporated into the design, construction, and implementation of an objective short-range anvil forecast tool based on upper-air observations, for use on the Meteorological Interactive Data Display System within the Range Weather Operations facility of the 45th Weather Squadron at CCAFS and the Spaceflight Meteorology Group at Johnson Space Center.

Full access
Charles R. Sampson, Andrea B. Schumacher, John A. Knaff, Mark DeMaria, Edward M. Fukada, Chris A. Sisko, David P. Roberts, Katherine A. Winters, and Harold M. Wilson

Abstract

The Department of Defense uses a Tropical Cyclone Conditions of Readiness (TC-CORs) system to prepare bases and evacuate assets and personnel in advance of adverse weather associated with tropical cyclones (TCs). TC-CORs are recommended by weather facilities either on base or at central sites and generally are related to the timing and potential for destructive (50 kt; 1 kt ≈ 0.5144 m s−1) sustained winds. Recommendations are then considered by base or area commanders along with other factors for setting the TC-CORs. Ideally, the TC-CORs are set sequentially, from TC-COR IV (destructive winds within 72 h), through TC-COR III (destructive winds within 48 h) and TC-COR II (destructive winds within 24 h), and finally to TC-COR I (destructive winds within 12 h), if needed. Each TC-COR, once set, initiates a series of preparations and actions. Preparations for TC-COR IV can be as unobtrusive as obtaining emergency supplies, while preparations and actions leading up to TC-COR I are generally far more costly, intrusive, and labor-intensive activities. The purpose of this paper is to describe an objective aid that provides TC-COR guidance for meteorologists to use when making recommendations to base commanders. The TC-COR guidance is based on wind probability thresholds from an operational wind probability product run at the U.S. tropical cyclone forecast centers. An analysis on 113 independent cases from various bases shows the skill of the objective aid and how well it compares with the operational TC-CORs. A sensitivity analysis is also performed to demonstrate some of the advantages and pitfalls of raising or lowering the wind probability thresholds used by this objective aid.

Full access
Anu Simon, Andrew B. Penny, Mark DeMaria, James L. Franklin, Richard J. Pasch, Edward N. Rappaport, and David A. Zelinsky

Abstract

This study discusses the development of the Hurricane Forecast Improvement Program (HFIP) Corrected Consensus Approach (HCCA) for tropical cyclone track and intensity forecasts. The HCCA technique relies on the forecasts of separate input models for both track and intensity and assigns unequal weighting coefficients based on a set of training forecasts. The HCCA track and intensity forecasts for 2015 were competitive with some of the best-performing operational guidance at the National Hurricane Center (NHC); HCCA was the most skillful model for Atlantic track forecasts through 48 h. Average track input model coefficients for the 2015 forecasts in both the Atlantic and eastern North Pacific basins were largest for the European Centre for Medium-Range Weather Forecasts (ECMWF) deterministic model and the National Centers for Environmental Prediction (NCEP) Global Forecast System (GFS) ensemble mean, but the relative magnitudes of the intensity coefficients were more varied. Input model sensitivity experiments conducted using retrospective HCCA forecasts from 2011 to 2015 indicate that the ECMWF deterministic model had the largest positive impact on the skill of the HCCA track forecasts in both basins. The most important input models for HCCA intensity forecasts are the Hurricane Weather Research and Forecasting (HWRF) Model and the Coupled Ocean–Atmosphere Mesoscale Prediction System-Tropical Cyclone (COAMPS-TC) model initialized from the GFS. Several updates were incorporated into the HCCA formulation prior to the 2016 season. Verification results indicate HCCA continued to be a skillful model, especially for short-range (12–48 h) track forecasts in both basins.

Full access
Mark DeMaria, John A. Knaff, Michael J. Brennan, Daniel Brown, Richard D. Knabb, Robert T. DeMaria, Andrea Schumacher, Christopher A. Lauer, David P. Roberts, Charles R. Sampson, Pablo Santos, David Sharp, and Katherine A. Winters

Abstract

The National Hurricane Center Hurricane Probability Program, which estimated the probability of a tropical cyclone passing within a specific distance of a selected set of coastal stations, was replaced by the more general Tropical Cyclone Surface Wind Speed Probabilities in 2006. A Monte Carlo (MC) method is used to estimate the probabilities of 34-, 50-, and 64-kt (1 kt = 0.51 m s−1) winds at multiple time periods through 120 h. Versions of the MC model are available for the Atlantic, the combined eastern and central North Pacific, and the western North Pacific. This paper presents a verification of the operational runs of the MC model for the period 2008–11 and describes model improvements since 2007. The most significant change occurred in 2010 with the inclusion of a method to take into account the uncertainty of the track forecasts on a case-by-case basis, which is estimated from the spread of a dynamical model ensemble and other parameters. The previous version represented the track uncertainty from the error distributions from the previous 5 yr of forecasts from the operational centers, with no case-to-case variability. Results show the MC model provides robust estimates of the wind speed probabilities using a number of standard verification metrics, and that the inclusion of the case-by-case measure of track uncertainty improved the probability estimates. Beginning in 2008, an older operational wind speed probability table product was modified to include information from the MC model. This development and a verification of the new version of the table are described.

Full access
David A. Lavers, N. Bruce Ingleby, Aneesh C. Subramanian, David S. Richardson, F. Martin Ralph, James D. Doyle, Carolyn A. Reynolds, Ryan D. Torn, Mark J. Rodwell, Vijay Tallapragada, and Florian Pappenberger

Abstract

A key aim of observational campaigns is to sample atmosphere–ocean phenomena to improve understanding of these phenomena, and in turn, numerical weather prediction. In early 2018 and 2019, the Atmospheric River Reconnaissance (AR Recon) campaign released dropsondes and radiosondes into atmospheric rivers (ARs) over the northeast Pacific Ocean to collect unique observations of temperature, winds, and moisture in ARs. These narrow regions of water vapor transport in the atmosphere—like rivers in the sky—can be associated with extreme precipitation and flooding events in the midlatitudes. This study uses the dropsonde observations collected during the AR Recon campaign and the European Centre for Medium-Range Weather Forecasts (ECMWF) Integrated Forecasting System (IFS) to evaluate forecasts of ARs. Results show that ECMWF IFS forecasts 1) were colder than observations by up to 0.6 K throughout the troposphere; 2) have a dry bias in the lower troposphere, which along with weaker winds below 950 hPa, resulted in weaker horizontal water vapor fluxes in the 950–1000-hPa layer; and 3) exhibit an underdispersiveness in the water vapor flux that largely arises from model representativeness errors associated with dropsondes. Four U.S. West Coast radiosonde sites confirm the IFS cold bias throughout winter. These issues are likely to affect the model’s hydrological cycle and hence precipitation forecasts.

Open access