Research
Wind-Wave Relation during Hurricane Wilma and Its Applications for Marine Science and Engineering
Analysis of datasets available from the literature indicates that, during tropical cyclones at sea, the barometric pressure is approximately negatively linearly related to the wind speed as well as to the wave height. During Hurricane Wilma in 2005, simultaneous meteorological-oceanographic (met-ocean) measurements were made by the National Data Buoy Center (NDBC) at the Data Buoy Station 42056 in the northwestern Caribbean Sea. Further analysis of these datasets showed that, when U10≥ 9 m s -1 during wind seas (when Hs/Lp≥ 0.020), Hs = 0.43 U10 – 2. Here, parameter Hs is the significant wave height (in meters), U10 is the wind speed (in m s -1 )at 10 m, Lp (= 1.56 T p 2 ) is the dominant wave length (in meters), and Tp is the peak wave period (in seconds). Applications of this proposed formula were successful during Hurricane Jose in 2017, Typhoon Russ in 1990 by NDBC Buoy 52009 near Guam, Typhoon Krosa in 2007 by a data buoy near Taiwan, and Typhoon Soudelor in 2015 by Jason -2 altimeter satellite. Also, its applications to rapid estimations of peak wave period, sea-surface currents and storm surge potentials were presented.
Measurements of Wind-Stress Induced Positive and Negative Storm Surges during Hurricane Isaac
When Hurricane Isaac in 2012 was over the coastal regions of Louisiana, USA, simultaneous measurements of both positive and negative storm surges were made by the U. S. National Ocean Service. Analysis of these datasets including wind speed and direction indicates that 93% of the positive surge and 74% of the negative surge can be explained by the windstress forcing, respectively. It is also found that the ratio of wind stress to either positive or negative surge is approximately 1:1.5, meaning that one pascal (1 N m -2) wind stress can generate 1.5 meters of water-level increase or decrease. This ratio may be used for forecasting or hind-casting purpose.
Relation between Overwater Friction Velocityand Wind Speed at 10m during Hurricane Rita
On the basis of pertinent in-situ measurements in the North Sea during extra-tropical cyclones and in the Gulf of Mexico during Hurricane Rita, a power law relation between overwater friction velocity and the wind speed at 10m is found and presented. Since the coefficient of determination exceeds 94 per cent, this power law is recommended for use in air-sea interaction studies.
Overwater Turbulence Intensity during Hurricane Katrina and Typhoon Russ
Abstract- When Hurricane Katrina was over the Gulf of Mexico in 2005 an unprecedented significant wave height (ð‘¯ð‘¯ð’”ð’”) of 17 m was measured at the National Data Buoy Center (NDBC) station 42040. Using this extreme ð‘¯ð‘¯ð’”ð’” value and those from NDBC Buoy 42003 in the Gulf of Mexico during Katrina and Buoy 52009 during Typhoon Russ near Guam in the Pacific in 1990, it is found that approximately 85% of the variation in turbulence intensity (TI) over the wind seas can be explained by the variation in ð‘¯ð‘¯ð’”ð’”. Application of this relation between TI and ð‘¯ð‘¯ð’”ð’” shows that the estimated drift velocity is in excellent(over 95%) agreement with that measured during Hurricane Ivan.
Applied Physics of Air-Sea-Land Interaction during Hurricane Katrina
A decade ago in August 2005 Hurricane Katrina devastated north-central Gulf of Mexico and southeastern Louisiana and Mississippi Gulf Coast. Although nearly all anemometers in the affected areas were destroyed by Katrina, few wind and wave measurement stations did survive the storm and provide some data to advance our understanding of the physics of air-sealand interaction. Analyses of these measurements indicate that : 1. On the basis of upper-air measurements made at Key West, FL, and Slidell, LA, the power-law wind profile is verified in the atmospheric surface boundary layer (up to 300m) where the friction dominants; 2. The cyclostrophic equation, which is the balance between centrifugal force and pressure gradient force, is validated so that the wind speed at 10m over the water, U10 = 6.3(1013 - Pmin) ^ (1/2), where Pmin is the minimum sea-level pressure; 3.The significant wave height (Hs) and its dominant wave period (Tp) can be normalized by using U*, which is the friction velocity (= (Ï„/Ï) ^ (1/2), where Ï„ is the wind stress and Ï is the air density).
Relations between Sea Surface Roughness, Wind Speed at 10m, and Wave Parametersduring a Tropical Cyclone
Measurements of wind and wave parameters during Hurricanes Kate and Lili and Typhoons Man-Yi and Krosa are analyzed. It is found that the wave characteristics are similar in both hurricane and typhoon. Relations amongst sea surface roughness, wind speed at 10m, and wave parameters are also formulated and presented for engineering applications.
Estimating Hurricane-Induced Drift Velocity: A Case Study during Ivan
During a tropical cyclone such as a hurricane, meteorological and oceanographic (met-ocean) conditions are severe. Estimates of these met-ocean parameters including winds, waves, current and storm surges are needed before and after the storm. Using Hurricane Ivan in 2004 as a case study, it is found that near surface wind measurements cannot be used to estimate waves and currents. An alternative method is proposed to estimate the wind drift velocity, i.e., Usea = 21 Hs^2/Tp^3, where Hs is the significant wave height and Tp the dominant wave period, both parameters are available routinely online from the National Data Buoy Center. Application of this Usea formula during Ivan shows that it is consistent with the near surface current measurements, particular the peak velocity.
Rapid Estimations of Air-Sea-Land Interaction Parameters during a Tropical Cyclone
Hurricane Ivan in 2004 and Hurricanes Katrina and Rita in 2005 devastated northern Gulf of Mexico and its coastal regions with catastrophic impacts in some regions. On the basis of applied physics of air-sea-land interaction, following formulas are derived and validated using the minimum sealevel pressure (Po in mb) as the most important input. They are: (1) Maximum wind speed (in m/s)= 6.3 (1013 - Po) 0.5; (2) Max significant wave height (in m) = 0.20 (1013 – Po); (3) Max wave setup (in feet)= 0.11 (1013 – Po); (4) Max surface drift velocity (in m/s) = 0.22 (1013 – Po) 0.5; (5) Most probable shoaling depth (in m) = (1013 – Po); (6) Max storm surge (in feet) = 0.23*(1010 – Po)*Fs*Fm, where Fs is a shoaling factor (not the shoaling depth) and Fm is a correction factor for storm motion; And(7) Max bottom (seabed) stress (in N/m^2) = 0.016 (1013 – Po). Examples for the applications of these formulas are provided.
Validating Wind Profile Equations during Tropical Storm Debby in 2012
Comparisons of logarithmic and power-law wind profiles are made for offshore conditions during Tropical Storm Debby in 2012 over the Gulf of Mexico. It is found that both laws are validated up to 122m and that the power law is as good as the log law statistically. For practical applications, the exponent of power law can be determined from the gust factor measurement available routinely from National Data Buoy Center (NDBC) buoys.
Engineering Applications of the Newly Available Roughness-Length Measurements by AOML at 213 ASOS Stations
Most recently, the Hurricane Research Division of the U. S. Atlantic Oceanographic and Meteorological Laboratory (AOML) has made extensive surveys of the roughness length (Zo) in each of the 213 Automated Surface Observation Stations (ASOS) located in tropical-cyclone prone regions. The original 8 values of Zo for each of the 45 degree segments within the 360 degree compass in each ASOS station are averaged geometrically to obtain one typical value for each of these 213 ASOS stations. Six ASOS stations are verified independently by the gust factor method during 5 hurricanes. Since the difference is within the 10 % composite accuracy for field measurements in wind speed, the computed geometric mean Zo values for each of the 213 ASOS stations are recommended for practical use. Applications of the proposed geometric mean Zo value to estimate the 3-second gust, peak gust, and peak factor during Hurricane Katrina are also provided for engineers as an example.
