Tropical Cyclone Forecasts
42
Tropical Cyclone Tropical Cyclone Forecasts Forecasts Dr. Richard J. Murnane Risk Prediction Initiative Bermuda Biological Station for Research, Inc.
description
Tropical Cyclone Forecasts. Dr. Richard J. Murnane Risk Prediction Initiative Bermuda Biological Station for Research, Inc. 2 1 0. Hurricane Landfall per Year. 19101930195019701990. Year. Cat 1&2. Cat 3, 4, 5. Hurricane Landfall in Miami and Dade County. Landsea, 1997. - PowerPoint PPT Presentation
Transcript of Tropical Cyclone Forecasts
Tropical Cyclone ForecastsTropical Cyclone Forecasts
Dr. Richard J. MurnaneRisk Prediction Initiative
Bermuda Biological Station for Research, Inc.
Hurricane Landfall in Miami Hurricane Landfall in Miami and Dade Countyand Dade County
Cat 1&2 Cat 3, 4, 5
1910 1930 1950 1970 1990
Hu
rric
an
e L
and
fall
per
Ye
ar 2
1
0
Year
Landsea, 1997
Tropical Cyclone Tropical Cyclone Seasonal Forecasting Seasonal Forecasting
StrategyStrategy Identify predictable global and Identify predictable global and
local features that drive climatelocal features that drive climate
Statistically relate features to Statistically relate features to tropical cyclone occurrencetropical cyclone occurrence
OutlineOutline Background on tropical cyclonesBackground on tropical cyclones
– Necessary conditionsNecessary conditions
– Forecast parametersForecast parameters
Seasonal forecastsSeasonal forecasts
– Basin-wideBasin-wide
– LandfallLandfall
Real-time hurricane intensity forecastsReal-time hurricane intensity forecasts
– Numerical predictionNumerical prediction
– Theoretical Maximum Potential IntensityTheoretical Maximum Potential Intensity
Necessary ConditionsNecessary Conditions Coriolis Effect
Unstable Atmosphere
Sea Surface Temperature > 26º C
Trigger
Little Vertical Wind Shear
High Relative Humidity
Major Climatic Features Affecting Major Climatic Features Affecting Atlantic Basin Hurricane ActivityAtlantic Basin Hurricane Activity
El NiEl Niño-Southern Oscillation (ENSO)
Quasi-biennial Oscillation
Sea Surface Temperature (SST)
West Africa Rainfall
Atmospheric Zonal Wind Anomalies
Sea Level Atmospheric Pressure
El Niño-Southern OscillationEl Niño-Southern Oscillation
Images from IRI web site
Normal
El Niño
US Hurricane Landfalls US Hurricane Landfalls Cat. Cat. 33
0.0
0.2
0.4
0.6
0.8
2 4 6 80
Pro
babi
lity
Number Landfalls Per Year
El Niño
Neutral
El Viejo
J. O’Brien & COAPS
0.0
0.2
0.4
0.6
0.8
1.0
Cat 1 Cat 2 Cat 3
El Niño
Neutral
El Viejo
Baroclinically InfluencedBaroclinically InfluencedAtlantic Storms:Atlantic Storms:
Hurricane Landfalls/yearHurricane Landfalls/year
# La
ndfa
lls/y
ear
Tropical Only Atlantic Storms:Tropical Only Atlantic Storms:Hurricane Landfalls/yearHurricane Landfalls/year
# La
ndfa
lls/y
ear
0.0
0.5
1.0
1.5
Cat 1 Cat 2 Cat 3
El Niño
Neutral
El Viejo
Quasi-Biennial Oscillation Quasi-Biennial Oscillation (QBO)(QBO)
Arrows show stratospheric wind direction
West Phase
Enhanced Atlantic Hurricane Formation
East Phase
Suppressed Atlantic Hurricane Formation
Sea Surface TemperatureSea Surface Temperature
Climate Prediction Center
Sea Surface Temperature AnomaliesSea Surface Temperature Anomalies
Climate Prediction Center
Seasonal Atlantic Hurricane Activity (1886-1991)
0
100
200May
June
July
Aug
Sept
Oct
Nov
Dec
Jan-Apr
West African RainfallWest African Rainfall
WesternSahel Region
Gulf of GuineaRegion
-2.00
-1.50
-1.00
-0.50
0.00
0.50
1.00
1.50
2.00
Sahel Rain (1899 – 1990)
1900 1920 1940 1960 1980
Sta
nd
ard
De
via
tion
Landsea et al., 1992
Year
2
1
0
-1
-2
1949 – 19901949 – 1990
0.64 IHD
7 Driest Sahel Years7 Driest Sahel Years 7 Wettest Sahel Years7 Wettest Sahel Years
14.43 IHD
Gray & Landsea, 1992
Intense Hurricanes vs. Sahel RainIntense Hurricanes vs. Sahel Rain
Long-term TrendsLong-term Trends
Year
Sta
nd
ard
Dev
iati
on
N. Atlantic SST AnomalyNE Atlantic SLP Anomaly (neg)Sahel RainIntense Hurricane Days
1950 1960 1970 1980 1990
2
1
0
-1
-2
Gray, 1998
Basin-Wide Seasonal Basin-Wide Seasonal ForecastsForecasts
Gray et al.’s Basin-wide ForecastsGray et al.’s Basin-wide Forecasts
Issued in: December, April, June, AugustIssued in: December, April, June, August
Forecast includes a variety of parameters:Forecast includes a variety of parameters:– Named StormsNamed Storms– HurricanesHurricanes, Hurricane Days, Hurricane Days– Intense HurricanesIntense Hurricanes, Intense Hurricane Days, Intense Hurricane Days– Hurricane Destruction PotentialHurricane Destruction Potential– Net Tropical Cyclone ActivityNet Tropical Cyclone Activity
Predictive Parameters Vary With ForecastPredictive Parameters Vary With Forecast
Gray et al.’s ‘98 Atlantic Gray et al.’s ‘98 Atlantic Basin ForecastsBasin Forecasts
1950-90 Average Dec April June Aug Total as of1 Oct 1998
Named Storms (9.3) 9 10 10 10 11
Hurricanes (5.8) 5 5 6 6 7
Intense Hurricanes (2.2) 2 2 2 2 2
Net Tropical CycloneActivity (100%)
90% 95% 100% 110% 121%
Landsea, 1997
Landsea, 1997
Elsner’s Atlantic Basin Elsner’s Atlantic Basin ForecastsForecasts
Uses subset of Gray variablesUses subset of Gray variables– Zonal windsZonal winds– West African rainfallWest African rainfall
Divides storms into tropical only and Divides storms into tropical only and baroclinically influencedbaroclinically influenced– assumes climatology for baroclinically assumes climatology for baroclinically
influenced storms (influenced storms (per year)per year)– Predicts tropical only storms using OLSPredicts tropical only storms using OLS
Calculates intense hurricanes using Calculates intense hurricanes using Poisson regressionPoisson regression
Elsner et al. Forecast 1998 Elsner et al. Forecast 1998 Atlantic Intense HurricanesAtlantic Intense Hurricanes
Elsner et al., 1998
0
0.1
0.2
0.3
0.4
0.5
1 2 3 4 5 6 7
Number of Storms
Pro
bab
ilit
y
0 1 2 3 4 5 6
August ‘98 ForecastsAugust ‘98 Forecasts
Mean1950-1990
Gray Elsner Observed8 Aug 98
Observed1 Oct 98
Named Storms
Hurricanes
9.3
5.8
10
6
-
3
5
3
11
7
Intense Hurricanes 2.3 2 1 1 2
Net TropicalCyclone Activity
100% 110% - 59% 121%
Seasonal Landfall and Seasonal Landfall and Location ForecastsLocation Forecasts
Gray Landfall Forecast Gray Landfall Forecast
Divides coast into separate sections Divides coast into separate sections
Uses Atlantic Basin seasonal forecast Uses Atlantic Basin seasonal forecast of “Net Tropical Cyclone Activity” (NTC) of “Net Tropical Cyclone Activity” (NTC) and SST anomalies to calculate total and SST anomalies to calculate total landfall probabilitylandfall probability
Distributes total probability along coast Distributes total probability along coast based on landfall climatologybased on landfall climatology
Cat 1&2 Hurricane LandfallsCat 1&2 Hurricane Landfalls
Gray, 1998
Intense Hurricane LandfallsIntense Hurricane Landfalls
Gray, 1998
1998 Landfall % Probability 1998 Landfall % Probability ForecastForecast
368
39
10.2 34
33
4
7
5
6 8
Gray, 1998
Elsner Landfall Elsner Landfall Probability ForecastsProbability Forecasts
Uses “Logistic Regression” for predictionsUses “Logistic Regression” for predictions
Predictors include:Predictors include:– Zonal wind anomaliesZonal wind anomalies– Sea level pressuresSea level pressures– QBOQBO– West African rainfallWest African rainfall
1998 Location Forecast1998 Location Forecast
IntenseHurricane in
the Gulf
IntenseHurricane in
the Caribbean
Hurricane Landfallon Southeast US
coast
Probability 0.189 0.107 0.469
Elsner et al., 1998
Hurricane Intensity Hurricane Intensity ForecastsForecasts
NHC Intensity Forecasts (1990-97)
25
20
15
10
5
Err
or
(kn
ots
)
1990 1991 1992 1993 1994 1995 1996 1997
72 hours
48 hours
24 hours
Avila, 1998
Year
Ginis et al.’s Hurricane Ginis et al.’s Hurricane ForecastsForecasts
Based on Coupled Ocean-Atmosphere Based on Coupled Ocean-Atmosphere ModelModel
Full Ocean Model Reproduces Air-Sea Full Ocean Model Reproduces Air-Sea Interactions and Improves Intensity Interactions and Improves Intensity ForecastsForecasts
Hurricane OpalHurricane Opal
Ginis, 1998
Maximum Potential Intensity Maximum Potential Intensity (MPI)(MPI)
Developed by Emanuel and BisterDeveloped by Emanuel and Bister
MPI Controlled by Environmental MPI Controlled by Environmental Factors, e.g.:Factors, e.g.:– Sea Surface TemperatureSea Surface Temperature
– Upper Atmosphere TemperatureUpper Atmosphere Temperature
– Relative HumidityRelative Humidity
Doesn’t account for forward motionDoesn’t account for forward motion
Contours of Maximum Contours of Maximum Wind Speed (m/s)Wind Speed (m/s)
Emanuel and Bister, 1998
Sea Surface Temperature (ºC)
Up
pe
r A
tmo
sp
he
re
Te
mp
era
ture
(ºC
)
15 20 25 30 35 40 45
-100
-75
-50
-25
Maximum Potential Maximum Potential Winds (m/s)Winds (m/s)
Emanuel and Bister, 1998
Maximum Potential Maximum Potential Wind (knots)Wind (knots)
Emanuel and Bister, 1998
ConclusionsConclusions Many of the seasonal forecast parameters Many of the seasonal forecast parameters
are related to the necessary conditions for are related to the necessary conditions for tropical cyclone formationtropical cyclone formation
Basin-wide seasonal forecasts are easier to Basin-wide seasonal forecasts are easier to make than landfall forecasts but they are of make than landfall forecasts but they are of less relevanceless relevance
Realistic representations of the ocean are Realistic representations of the ocean are needed to improve tropical cyclone intensity needed to improve tropical cyclone intensity forecastsforecasts
