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A Study of Large-Scale Surface Fluxes, Processes and Heavy Precipitation Associated with Land Falling Tropical Storm Lee over Gulf of Mexico using Remote Sensing and Satellite Data.

INTRODUCTION

A tropical cyclone (synonymous with hurricane) is an intense, low-level atmospheric warm-core vortex that originates over tropical oceans and is energetically driven principally by latent heat of evaporation from the ocean surface. Tropical cyclones are devastating natural disasters especially at the time of landfall. A tropical cyclone's sustained high winds, torrential rainfall and storm surge dramatically impact and alter coastal habitats, coastlines, man-made structures and cause loss of life. Over the decades, global research to forecast tropical cyclones through numerical simulation has grown. Now, spanning Global Circulation Models (GCM's), ensemble models such as ECMWF, NOGAPS, UKMET, GFDL and many others, has led to increased understanding of tropical cyclone behavior. However, many uncertainties exist particularly in terms of cyclogenesis, intensification potential and the prediction of both processes. One parameter of increasing interest for tropical cyclone intensification investigation is the ocean-atmosphere interface (OAI). At the state of current modeling techniques, the OAI is poorly understood and thus poorly represented in model simulations [10].

Limitations exist for reliable metrics to capture the amount of latent energy per unit area (e.g., satellite data correction, insufficient buoy coverage etc.,) in addition to computing reliable approximations of energy conversion-transfer values during any given tropical cyclone. We choose a case study, tropical storm Lee in the domain of the Gulf of Mexico, to examine fundamental parameters associated with tropical cyclone energy processes and surface fluxes with respect to the OIA. The following descriptive background was used as foundational criteria in our investigation of tropical storm Lee.

Tropical cyclone development

Regions and conditions. Each year on average, eleven tropical storms (of which six become tropical cyclones) develop over the Atlantic Ocean, Caribbean Sea, or Gulf of Mexico. The tropical cyclone season is generally during June-November and the 2011 season recorded 19 named systems [1]. Tropical cyclones usually develop between 5[degrees] to 30[degrees] north and south of latitudes--a region characterized by warm ocean waters with sea surface temperatures (SST) exceeding 26[degrees] C, as well as sufficient Coriolis acceleration. Energy is transferred to the storm via evaporation, where water vapor condenses and releases enormous amounts of latent heat to drive intensification. A mature tropical cyclone is structured of individual convective cells comprising regions of rising and sinking air parcels associated with small scale cumulus convection [2]. This convective activity produces intense thunderstorms that organize into clearly defined spiral bands.

Convective Available Potential Energy (CAPE). CAPE is a metric used to forecast large scale disturbances leading to severe weather [1]. CAPE is computed as the amount of buoyant energy available to accelerate an air parcel vertically, with maximum vertical speed estimates in units of Joules per kilogram (J [kg.sup.-1]). A higher CAPE value represents increasingly unstable atmospheric conditions to fuel storm growth and intensification. Although the current study focuses on CAPE values for intensification rates, CAPE values can be analyzed for pre-land fall effects of storm systems and contribute to early warning forecasts through predictive analysis [2].

Vertical motions. The uplift mechanism during energy transfer can be expressed in vertical wind velocities between the OAI. Associated velocities greater than 50 m [s.sup.-1] are observed during severe storm activity [3].

Precipitation. Tropical cyclones produce staggering amounts of rainfall, with maximum rates meeting or exceeding meters per day especially near the eyewall and when the storm becomes extra-tropical [3]. For this case study, we observe precipitation rates and total amounts as a function of CAPE energy and precipitable water content due to the energy transfer rate through the OAI.

Tropical cyclone mitigating processes

Mechanisms and features. Atmospheric and topographic processes and features can prohibit tropical cyclone development and intensification. Among those include (i) vertical wind shear, (ii) dry air intrusion, (iii) topographical obstructions (i.e., land masses and/or mountain ranges), (iv) sea surface temperatures less than 26[degrees] [C.sup.8] and (v) cold-water upwelling. We focus on parameters that impact the OIA: vertical wind shear, dry air intrusion and topography.

Vertical wind shear. Vertical wind shear is defined as the amount of change in wind direction and velocity with increasing altitude [5]. As wind speed increases with height, thunderstorms within a tropical cyclone become vertically slanted downwind and latent heat released by condensation is distributed over a larger area. Depending on wind shear magnitude and intensity, either a reduction or negation of intensification potential for tropical cyclone development will occur.

Dry air intrusion. Tropical cyclones require a constant supply of warm, moist air to support and sustain their powerful convective processes. The influx of dry air is extremely disruptive as it suppresses necessary convective uplift. Dry air infiltrates a storm, dispels latent heat through absorption and increases atmospheric stability.

Topography. Topography is considered when a tropical cyclone develops nearby, or passes over landmass during its track [2], cutting the storm off from the ocean-surface and disrupting the OIA. Topography type impacts tropical cyclones differently: 1) flat terrain will disrupt energy supply and 2) elevated, rugged terrain may disrupt storm structure altogether. Interestingly, the increased frictional force over land acts to decrease maximum sustained winds and also increase gusts felt at the surface, though these effects are most prominent with mountain ranges [9].

Case Study

Tropical storm Lee. Tropical storm Lee formed on September 2nd from a broad but disorganized tropical wave that entered the Western Caribbean in late August. The main center of circulation meandered inland on September 4th roughly 50 miles (80 km) southwest of Lafayette, LA and the squalls impacted the Gulf Coast as early as September 3rd. Tropical storm Lee's high moisture content and slow velocity promoted 24-hour rainfall totals in excess of 5 inches (127 mm) in most locations, including New Orleans Airport and Holden, LA where 11.05 inches (281 mm) and 15.43 inches (393 mm) fell, respectively [6]. Tropical storm Lee became post-tropical on September 5th, its remnants moving northeast to drench regions along the axis of the Appalachian Mountain range. Several locations set new 24-hour rainfall records; of noteworthy mention was Jackson, MS where 11.68 inches (297 mm) exceeding the previous record of 8.54 inches (217 mm) set in 1979; and Chattanooga, TN received 9.85 inches (250 mm), exceeding the previous 7.61 inches (193 mm) record set in 1886. Tropical storm Lee caused 21 fatalities, over 250 million USD in damages and spawned EF-0 and EF-1 tornadoes totaling 40 reports [6].

METHODS AND ANALYSIS

In the present study, we utilized satellite and remote sensing products to investigate the OAI components with respect to tropical storm Lee.

Remote Sensing products

GOES-8. To ascertain tropical storm Lee's geospatial domain, as well as its structure, we used visible-imagery from GOES-8 satellite instrument channels 1 through 5 (Figure 1).

GOES-13 East. We used GOES-13 East infrared (IR) cloud-top temperature remapped imagery (Figure 2) to investigate storm intensities, precipitation potential. Image spatial resolution is 4km, displayed at a Mercator projection and captured at ~11 [micro]m (3). GOES-13 East Geostationary Water Vapor imagery (Figure 3) was used to investigate low and relative upper-level moisture content and advection, regions of environmental forcing and dry- air content. Water vapor imagery was captured with a spectral weight near 6.7 [micro]m and displayed at 16km spatial resolution and Mercator projection [4].

Advanced Microwave Sounding Unit (AMSU). Wind shear (Figures 4 and 5), wind velocity (Figure 6) and minimal central pressure (Figure 7) were investigated using NHC best-track analysis and AMSU intensity estimates from the Cooperative Institute for Meteorological Satellite Studies. The Knaff-Zehr-Courtney (KZC P-W) values were obtained by applying the KZC P-W pressure-wind relationship to the best-track wind data. Estimates during the extra-tropical stage are partially based on analyses from the NOAA Hydrometeorological Prediction Center (HPC). Dashed vertical lines correspond to 0000 UTC and the solid vertical line corresponds to the time of landfall. [5] Aircraft observations have been adjusted for elevation using 90%, 80%, and 80% adjustment factors for observations from 700 mb, 850 mb, and 1500 ft, respectively [5].

Naval Coupled Ocean Data Assimilation system (NCODA). Daily Oceanic Heat Content (OHC) estimates (Figure 8) were obtained to investigate available energy in degrees Kelvin. OHC has been provided by J. Cummings of the Naval Research Lab and is calculated from fields generated by the Naval Coupled Ocean Data Assimilation system (NCODA; Cummings 2005) (7). The spatial grid spacing is 0.2 Latitude x 0.2 Longitude and the units of the estimates are given as kJ [cm.sup.-2].

Atmospheric Sounding products. Atmospheric Soundings were obtained from the University of Wyoming to investigate environmental instability during tropical storm Lee. The SKEW-T diagram from Slidell, LA station (Figure 9), though the only reliable measurement during tropical storm Lee, provided an index for instability. Height (in millibars and meters) is defined on y-axis and temperature (in degrees Celsius) on the x-axis. The thick black line to the right represents the environmental lapse rate (ELR); the thick black line to the left represents dew point and the thin black line to right of ELR is the Theoretical Air Parcel Plot (TAPP).

Computations

We derived computations for CAPE using an empirical model and C++ algorithm. CAPE provides a measure of the maximum possible kinetic energy that a statically unstable air parcel can acquire.

Therefore, it provides a guide to the strength of convection and instability in the atmosphere. Vertical velocity is calculated from CAPE at the Equilibrium Level (EL). The vertical velocity of an air parcel by buoyancy is given by:

[D.sub.w]/[D.sub.t] = g[T.sub.parcel] - [T.sub.env]/[T.sub.env] (eq. 1)

Where w is the vertical velocity, [T.sub.parcel] is the temperature of the air parcel, [T.sub.env] is the temperature of the environment and g is the acceleration due to gravity.

CAPE can be computed as:

[[integral].sup.EL.sub.LFC]g[[T.sub.parcel] - [T.sub.env]/[T.sub.env]]Dz (eq. 2)

We want an expression for computing the maximum vertical atmospheric velocity at the EL, [w.sub.max]. It can now be derived based upon CAPE. Note that the expression Dw/Dt in equation 1 can be written as:

([D.sub.w]/[D.sub.t]) = ([D.sub.w]/[D.sub.z]) X ([D.sub.z]/[D.sub.t]) (eq. 3)

Since [D.sub.z]/[D.sub.t] = w

[D.sub.w]/[D.sub.t] = w[D.sub.w]/[D.sub.z] (eq. 4)

If equation 4 is integrated vertically from the Level of Free Convection (LFC) to the EL following the motion of the parcel, the result is:

[w.sup.2]/2 = [[integral].sup.EL.sub.LFC]g([T.sub.parcel] - [T.sub.env]/[T.sub.env])Dz (eq. 5)

Note that the right hand side of equation 5 is just the definition of CAPE. Therefore, the expression for [w.sub.max] is

[w.sub.max] = [square root of 2 CAPE] (eq 6)

RESULTS AND DISCUSSION

Tropical storm Lee covered a generous area over the Gulf of Mexico. Available OHC ranging > 100 K, sea surface temperatures between 29[degrees] and 31[degrees] C, and lack of upper-level prevailing winds granted a favorable OAI environment for tropical storm Lee to develop and sequester large amounts of energy as CAPE values exceeded 1000 J [kg.sup.-1], peaking at 2045 J [kg.sup.-1] on September 4th. On average, CAPE values for severe storms are approximately 2300-3000 J [kg.sup.-1]. Thus, the CAPE values computed during tropical storm Lee translated to only moderate atmospheric instability, as shown from 175-850 mb atmospheric sounding height analysis at Slidell, LA. GOES-13 East IR imagery shows modestly organized and significant convective activity predominantly within tropical storm Lee's ESE and WNW quadrants. Tropical storm Lee reached its lowest central pressure of 986 mb and its peak vertical velocity of 63.95 m [s.sup.-1] on September 4th, coinciding with its peak CAPE. However, 250-800 hPa vertical layer analysis shows persistent WNW shear between approximately 11 and 33 knots from the period September 2nd through 5th. In addition, GOES-13 East water vapor imagery shows prominent dry-air intrusion within the WSW quadrant of the storm, disrupting the OAI energy exchange. Tropical storm Lee reached its 50 knot peak wind velocity on September 3rd, despite a 1024 J [kg.sup.-1] CAPE value. Tropical storm Lee obtained large quantities of moisture that contributed to the intense precipitation event upon the Gulf Coast region with maximum rainfall totals of 15.48" in Holden, LA, 13.55" in Florence, MS and 12.62" in Mobile, AL.

CONCLUSIONS

Strong vertical motions and OAI associated with moderate amounts of instability coupled with consistent CAPE values allowed tropical storm Lee to absorb massive amounts moisture, contributing to Intense precipitation. Moderate wind shear and a prominent dry-air intrusion prevented tropical storm Lee from intensifying further. Though these processes typically negatively affect tropical cyclone intensification, tropical storm Lee was impacted by an unusually powerful blocking high-pressure system positioned in the interior Midwest of the United States. We surmise the intensity of the dry air, as opposed to the presence of wind shear, played a greater role in mitigating intensification through disruption of the OAI. Interestingly, CAPE, vertical motions and central pressure peaked shortly after landfall. This behavior is unusual, as tropical cyclones typically lose energy exchange from the OAI by crossing over topography. We hypothesize this may exhibit a delayed energy conversion from latent heat to mechanical energy, however the energetic dynamics warrant further study especially with respect to OAI behavior. It is our goal to extend this case study with several more studies and develop a greater platform towards understanding the OAI.

ACKNOWLEDGEMENTS

This work was supported by NASA/NICE grant NNX10AB49A.

LITERATURE CITED

[1.] Emanual, K.A., 1986: An Air-Sea Interaction Theory for Tropical Cyclones, J.Atmos.Sci., 45, 1143-1155

[2.] Holton, James R. An Introduction to Dynamic Meteorology, 4th Edition. Academic Press Inc., San Diego, 1992, pp 370

[3.] Kantave Greene, Lail Hossain and Remata Reddy, A Study of Vertical Motion and Associated Thunderstorm Activity over the West Coast of Gulf of Mexico, NCUR 99 Proceedings, pp 1294-1298.

[4.] Cooperative Institute for Meteorological Satellite Studies (CIMSS) Tropical Cyclones http://tropic.ssec.wisc.edu/tropic.php [Accessed 3-8-2012] NOAA Satellites and Information; National Environmental Satellite, Data and Information Service; Regional and Mesoscale Meteorology Branch (RAMMB) http://rammb.cira.colostate.edu/products/tc realtime [Accessed 4-16-2012]

[5.] NOAA, National Weather Service (NWS) National Hurricane Center (NHC) http://www.nhc.noaa.gov/pastall.shtml [Accessed 5-23-2012]

[6.] UWYO, University of Wyoming Department of Atmospheric Science http://weather.uwyo.edu/upperair/soundin g.html [Accessed 4-16-2012]

[7.] Peng, M.S., Fu, B., Li, T., and Stevens, D.E., 2012: Developing versus Nondeveloping Disturbances for Tropical Cyclone Formation. Part I: North Atlantic. Mon. Wea. Rev., 140 1047-1066

[8.] Chang, S. W.J., 1982: The Orographic Effects Induced by an Island Mountain Range on Propagating Tropical Cyclones. Mon. Wea. Rev., Vol 110 1255--1270

[9.] Tallapragada, V., et al 2014: Hurricane Weather Research and Forecast (HWRF) Model 2014 Scientific Documentation. NOAA/NWS/NCEP

Warith Abdullah, Remata Reddy, Ezat Heydari, Wilbur Walters Jackson

State University, Jackson, Mississippi 39217

Corresponding Author: Warith Abdullah, email: nullexponent@gmail.com

Caption: Figure 1. GOES-8 visible satellite image of T.S. Lee.

Caption: Figure 2. GOES-13 Enhanced IR Imagery for Tropical Storm Lee, September 03, 2011

Caption: Figure 3. GOES-13 16 km Geostationary Water Vapory Imagery for Tropical Storm Lee, September 04, 2011

Caption: Figure 4. AMSU Area- Averaged Wind Shears and Layer Means at 250-800 hPa height for Tropical Storm Lee, 2-5 September 2011. Red horizontal-line corresponds to wind speed (kt), blue horizontal-line corresponds to wind direction (degrees).

Caption: Figure 5. AMSU Area- Averaged Wind Shears and Layer Means at 500-800 hPa for Tropical Storm Lee, 2-5 September 2011.
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Author:Abdullah, Warith; Reddy, Remata; Heydari, Ezat; Jackson, Wilbur Walters
Publication:Journal of the Mississippi Academy of Sciences
Date:Jul 1, 2017
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