Mark DeMaria

Dr. Mark DeMaria


Research Focus & Metrics

Academic Career Length

24Years (2003-Present)

(Calculated once Scilit publication data is synced: current year − year of first publication + 1)

Representative Publications

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1 August 2005 in Weather and Forecasting
Verified
Journal Article
Closed access
MDMark DeMaria
Mark DeMaria
MMMichelle Mainelli
Michelle Mainelli
LSLynn K. Shay
Lynn K. Shay
JKJohn Knaff
John Knaff
JKJohn Kaplan
John Kaplan
Modifications to the Atlantic and east Pacific versions of the operational Statistical Hurricane Intensity Prediction Scheme (SHIPS) for each year from 1997 to 2003 are described. Major changes include the addition of a method to account for the storm decay over land in 2000, the extension of the forecasts from 3 to 5 days in 2001, and the use of an operational global model for the evaluation of the atmospheric predictors instead of a simple dry-adiabatic model beginning in 2001. A verification of the SHIPS operational intensity forecasts is presented. Results show that the 1997–2003 SHIPS forecasts had statistically significant skill (relative to climatology and persistence) out to 72 h in the Atlantic, and at 48 and 72 h in the east Pacific. The inclusion of the land effects reduced the intensity errors by up to 15% in the Atlantic, and up to 3% in the east Pacific, primarily for the shorter-range forecasts. The inclusion of land effects did not significantly degrade the forecasts at any time period. Results also showed that the 4–5-day forecasts that began in 2001 did not have skill in the Atlantic, but had some skill in the east Pacific. An experimental version of SHIPS that included satellite observations was tested during the 2002 and 2003 seasons. New predictors included brightness temperature information from Geostationary Operational Environmental Satellite (GOES) channel 4 (10.7 μm) imagery, and oceanic heat content (OHC) estimates inferred from satellite altimetry observations. The OHC estimates were only available for the Atlantic basin. The GOES data significantly improved the east Pacific forecasts by up to 7% at 12–72 h. The combination of GOES and satellite altimetry improved the Atlantic forecasts by up to 3.5% through 72 h for those storms west of 50°W.

1 March 2014 in Bulletin of the American Meteorological Society
Verified
Journal Article
Closed access
MDMark DeMaria
Mark DeMaria
CSCharles R. Sampson
Charles R. Sampson
JKJohn Knaff
John Knaff
KMKate D. Musgrave
Kate D. Musgrave
The mean absolute error of the official tropical cyclone (TC) intensity forecasts from the National Hurricane Center (NHC) and the Joint Typhoon Warning Center (JTWC) shows limited evidence of improvement over the past two decades. This result has sometimes erroneously been used to conclude that little or no progress has been made in the TC intensity guidance models. This article documents statistically significant improvements in operational TC intensity guidance over the past 24 years (1989–2012) in four tropical cyclone basins (Atlantic, eastern North Pacific, western North Pacific, and Southern Hemisphere). Errors from the best available model have decreased at 1%–2% yr−1 at 24–72 h, with faster improvement rates at 96 and 120 h. Although these rates are only about one-third to one-half of the rates of reduction of the track forecast models, most are statistically significant at the 95% level. These error reductions resulted from improvements in statistical–dynamical intensity models and consensus techniques that combine information from statistical–dynamical and dynamical models. The reason that the official NHC and JTWC intensity forecast errors have decreased slower than the guidance errors is because in the first half of the analyzed period, their subjective forecasts were more accurate than any of the available guidance. It is only in the last decade that the objective intensity guidance has become accurate enough to influence the NHC and JTWC forecast errors.

1 January 2009 in Monthly Weather Review
Verified
Journal Article
Closed access
MDMark DeMaria
Mark DeMaria
A simplified dynamical system for tropical cyclone intensity prediction based on a logistic growth equation (LGE) is developed. The time tendency of the maximum sustained surface winds is proportional to the sum of two terms: a growth term and a term that limits the maximum wind to an upper bound. The maximum wind evolution over land is determined by an empirical inland wind decay formula. The LGE contains four free parameters, which are the time-dependent growth rate and maximum potential intensity (MPI), and two constants that determine how quickly the intensity relaxes toward the MPI. The MPI is estimated from an empirical formula as a function of sea surface temperature and storm translational speed. The adjoint of the LGE provides a method for finding the other three free parameters to make the predictions as close as possible to the National Hurricane Center best-track intensities. The growth rate is assumed to be a linear function of the vertical shear (S), a convective instability parameter (C) determined from an entraining plume, and their product, where both S and C use global model fields as input. This assumption reduces the parameter estimation problem to the selection of six constants. Results show that the LGE optimized for the full life cycle of individual storms can very accurately simulate the intensity variations out to as long as 15 days. For intensity prediction, single values of the six constants are found by fitting the model to more than 2400 Atlantic forecasts from 2001 to 2006. Results show that the observed intensity variations can be fit more accurately with the LGE than with the linear Statistical Hurricane Intensity Prediction Scheme (SHIPS) formulation, and with a much smaller number of constants. Results also show that LGE model solution (and some properties of real storms) can be explained by the evolution in the two-dimensional S–C phase space. Forecast and other applications of the LGE model are discussed.

1 February 2004 in Journal of Applied Meteorology and Climatology
Verified
Journal Article
Closed access
PDF file
JDJulie L. Demuth
Julie L. Demuth
MDMark DeMaria
Mark DeMaria
JKJohn A. Knaff
John A. Knaff
THThomas H. Vonder Haar
Thomas H. Vonder Haar
Advanced Microwave Sounding Unit (AMSU) data are used to provide objective estimates of 1-min maximum sustained surface winds, minimum sea level pressure, and the radii of 34-, 50-, and 64-kt (1 kt ≡ 0.5144 m s−1) winds in the northeast, southeast, southwest, and northwest quadrants of tropical cyclones. The algorithms are derived from AMSU temperature, pressure, and wind retrievals from all tropical cyclones in the Atlantic and east Pacific basins during 1999–2001. National Hurricane Center best-track intensity and operational radii estimates are used as dependent variables in a multiple-regression approach. The intensity algorithms are evaluated for the developmental sample using a jackknife procedure and independent cases from the 2002 hurricane season. Jackknife results for the maximum winds and minimum sea level pressure estimates are mean absolute errors (MAE) of 11.0 kt and 6.7 hPa, respectively, and rmse of 14.1 kt and 9.3 hPa, respectively. For cases with corresponding reconnaissance dat... Abstract Advanced Microwave Sounding Unit (AMSU) data are used to provide objective estimates of 1-min maximum sustained surface winds, minimum sea level pressure, and the radii of 34-, 50-, and 64-kt (1 kt ≡ 0.5144 m s−1) winds in the northeast, southeast, southwest, and northwest quadrants of tropical cyclones. The algorithms are derived from AMSU temperature, pressure, and wind retrievals from all tropical cyclones in the Atlantic and east Pacific basins during 1999–2001. National Hurricane Center best-track intensity and operational radii estimates are used as dependent variables in a multiple-regression approach. The intensity algorithms are evaluated for the developmental sample using a jackknife procedure and independent cases from the 2002 hurricane season. Jackknife results for the maximum winds and minimum sea level pressure estimates are mean absolute errors (MAE) of 11.0 kt and 6.7 hPa, respectively, and rmse of 14.1 kt and 9.3 hPa, respectively. For cases with corresponding reconnaissance dat...

1 February 2003 in Weather and Forecasting
Verified
Journal Article
Closed access
JKJohn Knaff
John Knaff
MDMark DeMaria
Mark DeMaria
CSCharles R. Sampson
Charles R. Sampson
JGJames M. Gross
James M. Gross
Tropical cyclone track forecasting has improved recently to the point at which extending the official forecasts of both track and intensity to 5 days is being considered at the National Hurricane Center and the Joint Typhoon Warning Center. Current verification procedures at both of these operational centers utilize a suite of control models, derived from the “climatology” and “persistence” techniques, that make forecasts out to 3 days. To evaluate and verify 5-day forecasts, the current suite of control forecasts needs to be redeveloped to extend the forecasts from 72 to 120 h. This paper describes the development of 5-day tropical cyclone intensity forecast models derived from climatology and persistence for the Atlantic, the eastern North Pacific, and the western North Pacific Oceans. Results using independent input data show that these new models possess similar error and bias characteristics when compared with their predecessors in the North Atlantic and eastern North Pacific but that the west Pacific model shows a statistically significant improvement when compared with its forerunner. Errors associated with these tropical cyclone intensity forecast models are also shown to level off beyond 3 days in all of the basins studied.

26 May 2021 in Atmosphere
Verified
Journal Article
Open access
PDF file
MDMark DeMaria
Mark DeMaria
JFJames L. Franklin
James L. Franklin
MOMatthew J. Onderlinde
Matthew J. Onderlinde
JKJohn Kaplan
John Kaplan
Although some recent progress has been made in operational tropical cyclone (TC) intensity forecasting, the prediction of rapid intensification (RI) remains a challenging problem. To document RI forecast progress, deterministic and probabilistic operational intensity models used by the National Hurricane Center (NHC) are briefly reviewed. Results show that none of the deterministic models had RI utility from 1991 to about 2015 due to very low probability of detection, very high false alarm ratio, or both. Some ability to forecast RI has emerged since 2015, with dynamical models being the best guidance for the Atlantic and statistical models the best RI guidance for the eastern North Pacific. The first probabilistic RI guidance became available in 2001, with several upgrades since then leading to modest skill in recent years. A tool introduced in 2018 (DTOPS) is currently the most skillful among NHC’s probabilistic RI guidance. To measure programmatic progress in forecasting RI, the Hurricane Forecast Improvement Program has introduced a new RI metric that uses the traditional mean absolute error but restricts the sample to only those cases where RI occurred in the verifying best track or was forecast. By this metric, RI forecasts have improved by ~20–25% since the 2015–2017 baseline period.