1 / 9

OPERATIONAL HEAT POTENTIAL ESTIMATES FOR HURRICANE INTENSITY

OPERATIONAL HEAT POTENTIAL ESTIMATES FOR HURRICANE INTENSITY. Michelle Mainelli, Lynn K. Shay, S. D. Jacob, P.G. Black.

ipo
Télécharger la présentation

OPERATIONAL HEAT POTENTIAL ESTIMATES FOR HURRICANE INTENSITY

An Image/Link below is provided (as is) to download presentation Download Policy: Content on the Website is provided to you AS IS for your information and personal use and may not be sold / licensed / shared on other websites without getting consent from its author. Content is provided to you AS IS for your information and personal use only. Download presentation by click this link. While downloading, if for some reason you are not able to download a presentation, the publisher may have deleted the file from their server. During download, if you can't get a presentation, the file might be deleted by the publisher.

E N D

Presentation Transcript

  1. OPERATIONAL HEAT POTENTIAL ESTIMATES FOR HURRICANE INTENSITY Michelle Mainelli, Lynn K. Shay, S. D. Jacob, P.G. Black Goal: To combine radar altimeter data with climatological and in situ data to estimate heat potential in the western Atlantic Ocean Basin to relate to hurricane intensity change. Research support by NSF/NOAA.

  2. INTRODUCTION: • SSTs only reflect skin temperatures of the ocean. • As SSTs mix with ocean mixed layer during storm passage-depth of 26oC water and integrated heat potential are important parameters for the ocean’s influence on storms. • More stable indicator for possible storm intensity. • Satellite altimetry (from TOPEX and ERS-2) locate warm ocean features relative to storm tracks to aid intensity prediction .

  3. APPROACH: • Surface Height Anomaly field from blended altimeter (T/ERS-2) fields. • Objectively analyzed to a 0.5 o grid in western Atlantic Ocean Basin. • Combine data with hurricane climatology for depth of 20 and 26oC isotherms and SSTs. • Two-layer model to estimate these depths and the heat potential using a gradient method. • Delineate warm and cold ocean features, and assess differences between observed and satellite-inferred heat potential.

  4. OBJECTIVE ANALYSIS: Blended SHA fields from altimeters TOPEX/ERS-2. Mariano and Brown (1992) algorithms to analyze 2-D and 3-D snapshots of ocean fields. Use scales applied to hurricane Gilbert data (Shay et al., 1992). Comparison of fields to Barnes analysis to ocean OA-found much better resolution of ocean features. Comparison of TOPEX versus Blended Fields reduced mapping error.

  5. IMPROVEMENTS: Research • TOPEX/ERS-2/ to monitor Hurricane HP Globally (Build a data base). • Explore data assimilation schemes to ingest SHA/SST data into oceanic models- HYCOM. • Evaluate estimates of Heat Potential from profiling Floats, etc to improve algorithms. • Deploy AXCTDs/AXCPs/AXBTs along satellite tracks (Recon flights). • Relate atmospheric data (GPS) to HP Variability and its change.

  6. MICOM/HYCOM : • Quiescent, Climatological, Realistic Cases with Eddy Field-Based on OA SAIC CTD data. • OML Parameterizations: KT, PRT, Gaspar, and Deardorff. • Analytical/Real Wind Cases • Comparison to both OML temperatures and Velocities from AXCP/AXBTs. • High Levels of Correlation, Mean Current Differences 10 cm/s. • Deardorff overmixed OML.

  7. TOPEX /ERS-2 ANALYSES: Analyses From Several Storms Over Past Two Years Have Revealed: • Wind Speed Changes Lagged Heat Potential Change By 12-18 Hours. • Annual Climo and Hurricane Climo- High Correlation to heat Content, 20 and 26C isotherm depths from 1999 • Cross-Correlation Indices >0.7 for all cases Wind / Heat Potential Changes. • Related to Air-Sea Fluxes, Theta_e, Over Heat Potential Gradients.

  8. SUMMARY: • Explore/Improve Data Assimilation Techniques for SHA/SST and T,S,U,V (z) in Oceanic Models. • Evaluate uncoupled and coupled model performation with data (i.e. ocean mixing schemes under high winds). • Oceanic feature analysis provides an early warning to the forecaster that rapid or steady intensificaton may occur under neutral to favorable atmospheric conditions. • Improve forecasting for the public.

  9. TRANSITIONS: Approach using radar altimetry from satellites is now being transitioned. to improve the product: • Acquire high resolution ocean data-not a technology issue-rather a fiscal one; • Combine these 3-D snapshots through Objective Analysis Schemes; • Develop assimilation schemes for models; and. • Require forecasters and researchers to open a dialogue-push the frontier.

More Related