Optimization of a Hurricane Track Forecast Model with the Adjoint Model Equations

1993 ◽  
Vol 121 (6) ◽  
pp. 1730-1745 ◽  
Author(s):  
Mark Demaria ◽  
Robert W. Jones
Keyword(s):  
Forecast Model ◽  
Track Forecast ◽  
Adjoint Model ◽  
Hurricane Track ◽  
Model Equations

scholarly journals Perceptions of Hurricane-Track Forecasts in the United States

2020 ◽  
Vol 12 (1) ◽  
pp. 15-29 ◽  
Author(s):  
Jason Senkbeil ◽  
Jacob Reed ◽  
Jennifer Collins ◽  
Kimberly Brothers ◽  
Michelle Saunders ◽  
...  
Keyword(s):  
United States ◽  
The United States ◽  
Track Forecast ◽  
Wind Speeds ◽  
Home Location ◽  
Hurricane Track ◽  
The Difference ◽  
Storm Characteristics ◽  
Hurricane Tracks ◽  
Hurricane Irma

AbstractHurricanes Isaac (2012), Harvey (2017), and Irma (2017) were storms with different geophysical characteristics and track forecast consistencies. Despite the differences, common themes emerged from the perception of track forecasts from evacuees for each storm. Surveys with a mixture of closed and open-ended responses were conducted during the evacuations of each storm while the storm characteristics and decision-making were fresh in the minds of evacuees. Track perception accuracy for each evacuee was quantified by taking the difference between three metrics: perceived track and official track (PT − OT), perceived track and forecast track (PT − FT), and home location and perceived track (HL − PT). Evacuees from Hurricanes Isaac and Harvey displayed a tendency to perceive hurricane tracks as being closer to their home locations than what was forecast to occur and what actually occurred. The large sample collected for Hurricane Irma provided a chance to statistically verify some of the hypotheses generated from Isaac and Harvey. Results from Hurricane Irma confirmed that evacuees expected a storm to be closer to their home locations after controlling for regional influences. Furthermore, participants with greater previous hurricane experience perceived a track as being closer to their home locations, and participants residing in zip codes corresponding with nonmandatory evacuation zones also perceived tracks as being closer to their home locations. These findings suggest that most evacuees from hurricanes in the United States appear to perceive storms as being closer to their home locations than they are and overestimate wind speeds at their homes, thus overestimating the true danger from landfalling hurricanes in many storms.

scholarly journals Determination of Forecast Errors Arising from Different Components of Model Physics and Dynamics

2004 ◽  
Vol 132 (11) ◽  
pp. 2570-2594 ◽  
Author(s):  
T. N. Krishnamurti ◽  
J. Sanjay ◽  
A. K. Mitra ◽  
T. S. V. Vijaya Kumar
Keyword(s):  
Large Scale ◽  
Forecast Model ◽  
Regression Coefficients ◽  
Second Step ◽  
Cumulus Convection ◽  
Forecast Errors ◽  
Radiative Processes ◽  
Grid Points ◽  
Model Equations

Abstract This paper addresses a procedure to extract error estimates for the physical and dynamical components of a forecast model. This is a two-step process in which contributions to the forecast tendencies from individual terms of the model equations are first determined using an elaborate bookkeeping of the forecast. The second step regresses these estimates of tendencies from individual terms of the model equations against the observed total tendencies. This process is executed separately for the entire horizontal and vertical transform grid points of a global model. The summary of results based on the corrections to the physics and dynamics provided by the regression coefficients highlights the component errors of the model arising from its formulation. This study provides information on geographical and vertical distribution of forecast errors contributed by features such as nonlinear advective dynamics, the rest of the dynamics, deep cumulus convection, large-scale condensation physics, radiative processes, and the rest of physics. Several future possibilities from this work are also discussed in this paper.

scholarly journals Increasing vertical resolution in US models to improve track forecasts of Hurricane Joaquin with HWRF as an example

2016 ◽  
Vol 113 (42) ◽  
pp. 11765-11769 ◽  
Author(s):  
Banglin Zhang ◽  
Richard S. Lindzen ◽  
Vijay Tallapragada ◽  
Fuzhong Weng ◽  
Qingfu Liu ◽  
...  
Keyword(s):  
Tropical Cyclones ◽  
Forecast Model ◽  
Vertical Resolution ◽  
Global Forecast System ◽  
Forecast System ◽  
Atlantic Basin ◽  
Hurricane Track ◽  
Environmental Prediction ◽  
The Impact ◽  
Positive Impacts

The atmosphere−ocean coupled Hurricane Weather Research and Forecast model (HWRF) developed at the National Centers for Environmental Prediction (NCEP) is used as an example to illustrate the impact of model vertical resolution on track forecasts of tropical cyclones. A number of HWRF forecasting experiments were carried out at different vertical resolutions for Hurricane Joaquin, which occurred from September 27 to October 8, 2015, in the Atlantic Basin. The results show that the track prediction for Hurricane Joaquin is much more accurate with higher vertical resolution. The positive impacts of higher vertical resolution on hurricane track forecasts suggest that National Oceanic and Atmospheric Administration/NCEP should upgrade both HWRF and the Global Forecast System to have more vertical levels.

scholarly journals Targeting and Data Assimilation Studies during Hurricane Humberto (2001)

2006 ◽  
Vol 63 (1) ◽  
pp. 175-186 ◽  
Author(s):  
Sim D. Aberson ◽  
Brian J. Etherton
Keyword(s):  
Kalman Filter ◽  
Data Assimilation ◽  
Additional Data ◽  
Track Forecast ◽  
Barotropic Model ◽  
Forecast Models ◽  
Hurricane Track ◽  
Ensemble Transform Kalman Filter ◽  
Ensemble Transform

Abstract Two operational synoptic surveillance missions were conducted by the National Oceanic and Atmospheric Administration into Hurricane Humberto (2001). Forecasts from two leading dynamical hurricane track forecast models were improved substantially during the watch and warning period before a projected landfall by the assimilation of the additional dropwindsonde data. Feasibility tests with a barotropic model suggest that further improvements may be obtained by the use of the ensemble transform Kalman filter for assimilating these additional data into the model. This is the first effort to assimilate data into a hurricane model using the ensemble transform Kalman filter.

Impacts of Typhoon Track and Island Topography on the Heavy Rainfalls in Taiwan Associated with Morakot (2009)

2012 ◽  
Vol 140 (10) ◽  
pp. 3379-3394 ◽  
Author(s):  
Baoguo Xie ◽  
Fuqing Zhang
Keyword(s):  
Dominant Role ◽  
Forecast Model ◽  
Weather Research And Forecasting ◽  
Track Forecast ◽  
Typhoon Track ◽  
Flooding Event ◽  
Flow Transport ◽  
Monsoon Flow ◽  
Southern Taiwan ◽  
Heavy Rainfalls

Abstract Cloud-resolving ensemble simulations and sensitivity experiments utilizing the Weather Research and Forecasting model (WRF) are performed to investigate the dynamics and predictability of the record-breaking rainfall and flooding event in Taiwan induced by Typhoon Morakot (2009). It is found that a good rainfall forecast foremost requires a good track forecast during Morakot’s landfall. Given a good track forecast, interaction of the typhoon circulation with complex topography in southern Taiwan plays a dominant role in producing the observed heavy rainfalls. The terrain slope, strength of the horizontal winds, and mid–lower-tropospheric moisture content in the southwesterly upslope flow are the primary factors that determine the rainfall location and intensity, as elucidated by the idealized one-dimensional precipitation-rate forecast model. The typhoon circulation and the southwesterly monsoon flow transport abundant moisture into southern Taiwan, which produces the heavy rainfall through interactions with the complex high terrain in the area. In the meantime, as part of the south China monsoon, the southwesterly flow may be substantially enhanced by the typhoon circulation.

Assimilating Airborne Doppler Radar Observations with an Ensemble Kalman Filter for Convection-Permitting Hurricane Initialization and Prediction: Katrina (2005)

2012 ◽  
Vol 140 (3) ◽  
pp. 841-859 ◽  
Author(s):  
Yonghui Weng ◽  
Fuqing Zhang
Keyword(s):  
Kalman Filter ◽  
Hurricane Katrina ◽  
Ensemble Kalman Filter ◽  
Airborne Radar ◽  
Track Forecast ◽  
Forecast Errors ◽  
Radar Observations ◽  
Uncertainty Estimates ◽  
Hurricane Track ◽  
The Impact

Abstract Through a Weather Research and Forecasting model (WRF)-based ensemble Kalman filter (EnKF) data assimilation system, the impact of assimilating airborne radar observations for the convection-permitting analysis and prediction of Hurricane Katrina (2005) is examined in this study. A forecast initialized from EnKF analyses of airborne radar observations had substantially smaller hurricane track forecast errors than NOAA’s operational forecasts and a control forecast initialized from NCEP analysis data for lead times up to 120 h. Verifications against independent in situ and remotely sensed observations show that EnKF analyses successfully depict the inner-core structure of the hurricane vortex in terms of both dynamic (wind) and thermodynamic (temperature and moisture) fields. In addition to the improved analyses and deterministic forecast, an ensemble of forecasts initiated from the EnKF analyses also provided forecast uncertainty estimates for the hurricane track and intensity. Also documented here are the details of a series of data thinning and quality control procedures that were developed to generate superobservations from large volumes of airborne radial velocity measurements. These procedures have since been implemented operationally on the NOAA hurricane reconnaissance aircraft that allows for more efficient real-time transmission of airborne radar observations to the ground.

scholarly journals Long-term forecast model of spring runoff on the Belaya river

2019 ◽  
Vol 486 (6) ◽  
pp. 723-726
Author(s):  
D. Yu. Vasil’ev ◽  
V. V. Vodopyanov ◽  
G. S. Zayzeva ◽  
Sh. I. Zakirzyanov ◽  
V. V. Semenov ◽  
...  
Keyword(s):  
Water Balance ◽  
Forecast Model ◽  
Water Balance Model ◽  
Balance Model ◽  
Spring Runoff ◽  
Marquardt Algorithm ◽  
Long Term Forecasting ◽  
Model Equations ◽  
The Stability

This article presents the results of long-term forecasting of spring runoff in the Belaya River basin, based on the water balance model. To optimize the structure and parameters of the water balance model equations, the Levenberg-Marquardt algorithm was used to impose restrictions on the input data values. The obtained values of the equations’ coefficients were checked according to the criterion D/s adopted in the hydrometeorological service. The reliability of the predictive method used was assessed by statistical calculations of the stability of their parameters and test calculations on an independent sample. All equations obtained during the numerical experiment may be suitable to make forecasts.

Sign in / Sign up

Export Citation Format

Share Document