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CARIBBEAN METOCEAN CLIMATE STATISTICS (CARIMOS) Vincent J. Cardone, President Oceanweather Inc. Cos Cob, CT, USA Specification of the extreme and normal.

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Presentation on theme: "CARIBBEAN METOCEAN CLIMATE STATISTICS (CARIMOS) Vincent J. Cardone, President Oceanweather Inc. Cos Cob, CT, USA Specification of the extreme and normal."— Presentation transcript:

1 CARIBBEAN METOCEAN CLIMATE STATISTICS (CARIMOS) Vincent J. Cardone, President Oceanweather Inc. Cos Cob, CT, USA Specification of the extreme and normal wind and wave climate and basin scale storm surge and 2-D currents by a hindcast approach

2 CARIMOS Hindcast Approach Hindcast 109 tropical cyclones 1921 – 1999 Hindcast 15-continuous years 1981 – 1995 Winds and waves: triple nested approach to account for North Atlantic swell input, complex basin morphology, shallow water and island sheltering: 1.25°/.25°/.065° Basin storm surge with 2D hydro model:.25°

3 Tropical Cyclones NOAA National Hurricane Center HURDAT Tape. Tropical Cyclone Deck Aircraft Reconnaissance Data. Annual Tropical Storm Reports and Summaries. Published Accounts of Caribbean Storms. Continuous Wind Fields Northern Hemisphere Surface Analysis Final Analysis Series NOAA Tropical Strip surface analyses NOAA NCDC TDF-11 format ship report files Climatological summaries Gridded pressure fields (NCDC Global Historical Fields CD) Global so-called WMO 1000-mb wind fields Gridded digital products of the new NOAA NCEP Global Reanalysis Project, specifically the 6-hourly 1000 mb and 10m surface wind fields.

4 Hindcast Model Attributes Swell Grid GRIDSWELL

5 Coarse Grid GRIDCOARSE

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7 Fine Grid GRIDFINE

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9 Tracks of Tropical Cyclones

10 Tropical Wind Model (TC96) Diagnostic PE PBL Model Wind field snapshots Buoy/Rig comparisons show accuracy of +/- 20º in wind direction and +/- 2 m/s in wind speed Applied in worldwide tropical basins

11 Tropical Model Snapshot Inputs Speed and direction of vortex motion Equivalent geostrophic flow of the ambient PBL pressure field in which the vortex propagates Central Pressure Scale radius of exponential radial pressure profile Hollands profile peakedness parameter

12 Snapshot Solutions

13 Wind WorkStation (WWS) Graphical analysis tool for the analysis of marine surface wind fields Blending tropical wind field into synoptic scale Direct analysis of tropical winds

14 Wind Fields in Tropical Cyclones

15 Tropical Wind Field Methodology Model Inputs Tropical Model WWS Wave Model

16 Aircraft Reconnaissance North Atlantic 1944 – present Western North Pacific 1944-1986 Image Courtesy of TPC

17 Pressure Profile Fit to Aircraft Data

18 35/50 Knot Radii Image Courtesy of JTWC

19 Tropical Cyclone Snap Database Dp: 2 to 120 mb every 2 mb Rp 5 to 120 Nmi every 4 Nmi B 1 to 2.5 every.1 Maximum Surface Wind Radius of Maximum Wind Azimuthally Averaged Wind Speed in 5 Nmi Bins Radius of 35/50 Knots InputOutput

20 QUIKSCAT Scatterometer Winds

21 Possible Model Solutions for Dp=90, B=1.00

22 Sample QUIKSCAT Fit

23 Wind Analysis Distributed Application (HWind)

24 HWind vs. Tropical Model Winds Winds on Sept 15 th, 2000 15GMT HWind: 37.3 m/s NHC: 45.4 m/s TC96/QuikScat: 43.3 m/s TC96HWind

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26 Sample Workstation Rp Fit in CARIMOS Hurricane

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30 Sample CARIMOS Hurricane Wind Hindcast

31 Sample CARIMOS Wave Hindcast

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37 Continuous Wind Fields NOAA NCEP Reanalysis 10-m winds First iteration revealed biases Interactive Objective Kinematic Analysis (IOKA)

38 Validation Tropical Cyclones – rely on extensive prior validation in tropical regimes such as Gulf of Mexico, South China Sea… Continuous – utilize buoy and satellite altimeter measured winds and sea states

39 Model Validation - Buoy Data

40 Hindcast vs Buoy 41018

41 Wind and Wave Statistics for CARIMOS Operational Hindcast vs. Buoy 41018

42 Model Distributional Validation vs. Buoy

43 Model Validation - Altimeter Data

44 Model Distributional Validation - Altimeter

45 Wind and Wave Statistics for CARIMOS Operational Hindcast vs. Altimeter Data

46 Model Validation Altimeter

47 CARIMOS Derivative Products Continuous Hindcast - site specific Time series 15 years, 3-hourly Bivariate distributions (HS-TP, HS-VMD, WS-WD) Duration/persistence distributions Extremes Time series in storms, hourly Return period extremes of WS, HS, HM, HC, TP, Va, Sh 1 year to 100 years

48 CARIMOS Wind and Wave Fields Definitions FieldDescription Date Julian format (where Jan 1 1900 = 1, Jan 2 1900 = 2, etc.) Wind Direction From which the wind is blowing, clockwise from true north in degrees (meteorological convention). Wind Speed 1-hour average of the effective neutral wind at a height of 10 meters, units in meters/second.

49 Total Spectrum Wave Fields: Total Variance The sum of the variance components of the hindcast spectrum, over the 552 bins of the wave model, in meters squared. Significant Wave Height 4.000 times the square root of the total variance, in meters. Peak Spectral Period Peak period is the reciprocal of peak frequency, in seconds. Peak frequency is computed by taking the spectral density in each frequency bin, and fitting a parabola to the highest density and one neighbor on each side. If highest density is in the.32157 Hz bin, the peak period reported is the peak period of a Pierson-Moskowitz spectrum having the same total variance as the hindcast spectrum. Vector Mean Direction To which waves are traveling, clockwise from north in degrees (oceanographic convention).

50 First Spectral Moment Following Haring and Heideman (OTC 3280, 1978) the first and second moments contain powers of = 2 f; thus: where dS is a variance component and the double sum extend over 552 bins. Second Spectral Moment Following Haring and Heideman (OTC 3280, 1978) the first and second moments contain powers of = 2 f; thus: where dS is a variance component and the double sum extend over 552 bins. Dominant Direction Following Haring and Heideman, the dominant direction is the solution of the equations The angle is determined only to within 180 degrees. Haring and Heideman choose from the pair (, +180) the value closer to the peak direction.

51 Angular Spreading The angular spreading function (Gumbel, Greenwood & Durand) is the mean value, over the 552 bins, of cos( -VMD), weighted by the variance component in each bin. If the angular spectrum is uniformly distributed over 360 degrees, this statistic is zero; if uniformly distributed over 180 degrees, 2/ ; if all variance is concentrated at the VMD, 1. For the use of this statistic in fitting an exponential distribution to the angular spectrum, see Pearson & Hartley, Biometrika Tables for statisticians, 2:123 ff. Angular spreading (ANGSPR) is related to cos n spreading as follows: n = (2*ANGSPR)/(1-ANGSPR) In-Line Variance Ratio Directional spreading by Haring and Heideman, p 1542. Computed as: If spectral variance is uniformly distributed over the entire compass, or over a semicircle, Rat = 0.5; if variance is confined to one angular band, or to two band 180 degrees apart, Rat = 1.00. According to Haring and Heideman, cos^2 spreading corresponds to Rat = 0.75.

52 Wave Partition Fields (Sea/Swell): Total Variance of Sea Partition Peak Spectral Period of Sea Partition Vector Mean Direction of Sea Partition Total Variance of Swell Partition Peak Spectral Period of Swell Partition Vector Mean Direction of Swell Partition Explanation of sea/swell computation: The sum of the variance components of the hindcast spectrum, over the 552 bins of the wave model, in meters squared. To partition sea (primary) and swell (secondary) we compute a P-M (Pierson-Moskowitz) spectrum, with a cos 3 spreading, from the adopted wind speed and direction. For each of the 552 bins, the lesser of the hindcast variance component and P-M variance component is thrown into the sea partition; the excess, if any, of hindcast over P-M is thrown into the swell partition.

53 Sample Storm Peak Table Storm Peaks 23 Peaks found > 4 within a window of 72 hours. CS Gpt 3106, Lat 15.0n, Long 75.0w, Depth 4024.333m Defined Period: Storms Date Ranges: 9/8/1921 01:00 to 10/2/2000 18:00 CCYYMM DDHHmm WD WS ETOT TP VMD MO1 MO2 HS DMDIR ANGSPR INLINE HSUR CS CD MaxWAVE CREST W/HS C/HS deg m/s m^2 sec deg m^2/s m2/s2 m deg cm cm/s deg m m 195509 252300 80.9 26.93 4.863 11.742 258.1 3.457 2.837 8.821 264.5 0.8032 0.7198 10.9 0.2 282.6 15.101 8.358 1.7120 0.9476 195109 041500 316.3 19.98 4.370 12.223 200.6 3.089 2.567 8.362 213.1 0.7204 0.6252 16.1 0.3 180.6 14.552 8.028 1.7402 0.9601 199911 151700 165.0 22.58 4.237 11.753 27.1 3.037 2.537 8.234 40.3 0.6990 0.6007 28.2 0.2 22.5 14.162 7.830 1.7199 0.9510 194109 261300 49.7 23.15 4.211 11.552 244.1 3.024 2.510 8.209 250.0 0.7953 0.6994 8.2 0.3 233.0 14.654 8.135 1.7851 0.9910 194208 241200 254.0 21.04 3.259 11.768 177.3 2.417 2.112 7.221 208.7 0.6100 0.5681 12.4 0.5 147.3 12.860 7.105 1.7809 0.9839 193309 192100 223.2 16.67 2.798 12.663 189.0 2.029 1.782 6.691 219.7 0.5800 0.6305 8.0 0.4 131.5 11.855 6.528 1.7718 0.9756 196007 130300 337.4 12.84 2.479 11.439 209.8 1.889 1.693 6.297 218.8 0.7640 0.6685 9.1 0.1 147.8 11.030 6.085 1.7517 0.9664 196107 220300 58.0 18.37 2.409 10.859 250.3 1.868 1.705 6.208 256.3 0.7980 0.7000 1.2 0.1 254.6 11.080 6.143 1.7847 0.9896 198008 060100 288.9 7.49 2.183 15.563 226.9 1.367 1.108 5.910 238.2 0.7859 0.7633 6.1 0.1 127.7 10.556 5.807 1.7861 0.9826 198809 120900 224.1 13.68 1.778 14.382 193.5 1.422 1.428 5.334 230.8 0.3029 0.7310 1.8 0.2 120.8 9.777 5.335 1.8330 1.0002 194408 200400 276.1 11.65 1.707 13.778 195.0 1.261 1.170 5.227 218.4 0.6766 0.6707 2.9 0.3 139.7 9.742 5.361 1.8638 1.0256 193211 041800 44.5 16.05 1.596 10.357 250.8 1.332 1.295 5.054 255.7 0.7443 0.6334 1.6 0.2 218.1 9.687 5.396 1.9168 1.0677 196908 302100 156.2 8.24 1.546 10.026 230.6 1.273 1.216 4.974 237.4 0.7818 0.6863 10.1 0.0 222.7 8.731 4.833 1.7553 0.9716 197809 160000 53.9 16.07 1.425 9.660 248.2 1.233 1.235 4.775 253.2 0.8026 0.7042 2.8 0.1 248.2 8.737 4.851 1.8298 1.0159 193808 231300 159.6 17.91 1.277 9.414 236.4 1.129 1.147 4.520 243.8 0.7691 0.6784 11.8 0.1 285.6 7.829 4.332 1.7321 0.9584 197909 010000 38.3 6.23 1.236 16.425 239.0 0.815 0.706 4.447 242.5 0.8933 0.8501 0.7 0.1 97.8 8.246 4.510 1.8542 1.0141 195410 101100 102.7 19.92 1.194 8.139 283.8 1.140 1.213 4.371 283.3 0.8151 0.7283 4.5 0.4 265.5 8.310 4.635 1.9011 1.0605 197108 211800 86.5 7.04 1.190 11.861 227.4 0.960 0.935 4.363 233.9 0.8277 0.7494 1.1 0.1 105.3 7.715 4.235 1.7682 0.9707 193808 112300 193.3 8.65 1.176 11.520 215.1 0.901 0.837 4.338 228.2 0.6592 0.6869 1.1 0.2 123.2 7.647 4.220 1.7627 0.9729 197109 081400 65.1 15.12 1.175 8.943 253.4 1.063 1.112 4.336 258.3 0.8063 0.7073 1.5 0.1 267.5 7.845 4.357 1.8093 1.0049 193108 130900 250.5 12.18 1.164 10.660 208.0 1.009 1.040 4.315 226.9 0.6919 0.6768 3.8 0.2 133.5 7.587 4.173 1.7582 0.9672 193307 010100 73.6 15.24 1.143 8.956 261.2 1.039 1.084 4.277 264.7 0.8170 0.7199 2.9 0.1 297.1 7.997 4.451 1.8697 1.0407 195108 171700 227.1 3.90 1.100 12.848 230.7 0.726 0.575 4.196 234.4 0.8790 0.8235 0.7 0.2 120.9 7.566 4.189 1.8031 0.9984

54 Computation of Maximum Individual Wave Height in a Storm The program evaluates Borgman's (1973) integral: where H is the largest wave height; a 2 is the mean square height taken as a function of time, t; t a and t b are the beginning and end of the storm; and T(t) is the wave period, taken here is the significant wave period. Maximum Individual Wave Height (Forristall, 1978): T = M 0 /M 1

55 Computation of Maximum Individual Crest Height in a Storm Maximum Crest Height (Haring and Heideman, 1978): where h is elevation and d is water depth T =.74 TP TP is the reciprocal of fpeak, found by solving by inverse interpolation The median of the resulting distribution was taken as the maximum expected single peak in the storm.

56 Extremal Analysis Storm Peak Table Issues Peaks over threshold vs annual maximum Selection of distribution Selection of fitting threshold Site averaging

57 Algorithm - Return-Period Extremes Calculation of Return-Period Extremes The distributional assumptions used are: 1.Gumbel distribution of extremes: 2.Borgman distributions of extremes, i.e., Gumbel distribution of squared extremes: 3.Galton distribution of height, i.e. normal distribution of log heights: 4.Weibull distribution described in next section The fitting procedure of Gumbel (1958, pp. 34 - 36) was followed for Gumbel, Borgman and Galton, with plotting positions based in i/(n+1), often called Weibull plotting position., where

58 Climate Variability - Impact on Design Wave Criteria Cold Years 100-year Hs7.4m (Gumbel) 100-year Hs7.9m (Weibull) Warm Years 100-year Hs9.9m (Gumbel) 100-year Hs10.3m (Weibull) Overall 100-year Hs9.0m (Gumbel) 100-year Hs9.2m (Weibull)

59 Tropical Cyclone Variability (From Goldberg et al., Science, 293, 20 July, 2001)

60 Significant Wave Height Interannual Variability of Exceedence Value

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62 Conclusions Demonstration that CARIMOS provides a very skillful model for normal conditions Importance of due consideration to decadal climatic trends, 25% difference in extreme wave heights Importance of due consideration in inter- annual variability upto 100% difference in values of 90% and 99% exceedences

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