Atmospheric Influences Physical oceanography Instructor: Dr. Cheng-Chien LiuCheng-Chien Liu Department of Earth Sciences National Cheng Kung University Last updated: 24 September 2003 Chapter 4

Driving forces  Sun Sunlight Evaporation Infrared emissions Sensible heating of the sea by warm or cold winds  Occur at constant moisture content with dry-bulb temperature of air  Geothermal heating  barely influence  Atmosphere Uneven distribution of heat  winds Evaporation  transfer heat  carry heat poleward  A coupled dynamic system (air-sea)

The Earth in space  The Earth’s orbit (Fig 4.1) Near circular with small eccentricity  Aphelion  Perihelion Inclination of rotating axis:  The vernal equinox (21 March)  The autumnal equinox (21 September)  The tropic of Cancer  The tropic of Capricorn Seasons  Averaged solar insolation  maximum in early January  If the insolation were rapidly and efficiently redistributed over Earth

Atmospheric wind systems  Fig 4.2 Annual wind speed and sea level pressure for 1989  Along the Equator: weak   Tropics: trade winds   Subtropics near 30 0 : weak winds  40 0 – 50 0 : roaring forties   50 0 – 60 0 : strong wind  Reasons of the strength and direction of winds  Uneven distribution of solar heating  Uneven distribution of land masses  Circulation of winds in a vertical plane The mean value of winds over the ocean: U 10 = 7.4 m/s

Atmospheric wind systems (cont.)  Fig 4.3 Distribution of winds in the atmosphere  The meridional cells in the atmosphere and the influence of Earth’s rotation on the winds  Cross section Seasonal influence  Fig 4.4  Asian monsoon  Winter   Summer 

The planetary boundary layer  Atmospheric boundary layer Definition Thickness Z i  Few tens of meters  weak wind, cold water  A kilometer  strong wind, warm water Exchange  Momentum  Heat Lowest part (  0.1 Z i )  Constant vertical fluxes of heat and momentum  Heat and momentum  log h  ∴ measure U 10

Measurement of wind  First: Maury (1847)  COADS NOAA  combined data back over a century For studying atmospheric forcing of the ocean

Measurement of wind (cont.)  Beaufort Scale Admiral Sir F. Beaufort (1806) Most common source of wind data (1990, 60%) Based on features (foam coverage, wave shape) Revision (1946): U 10 = 0.836B 3/2 Revision (1997): Table 4.1 Source of errors  Uneven distribution of ships (Fig 4.5)  Careless observers  Error coding  Accuracy > 10%

Measurement of wind (cont.)  Scatterometers Principles  Measure the scatter of centimeter-wavelength radio waves from small, centimeter-wavelength waves on the sea surface  Small wave amplitudes = fn(wind speed, wind direction) Limitation  Ambiguous direction  Can be removed by use of a few surface observations or numerical models Spaceborne platform  ERS-1, ERS-2 (1991-)  ADEOS (six months from 1996)  Error Accuracy:  1.3 m/s For V > 6 m/s, fewer than 3% has ambiguity error Spatial resolution: 25km

Measurement of wind (cont.)  Special Sensor Microwave/Imager SSM/I US Defense Meteorological Satellite program (1987 –) Principles  Microwave radiation emission = fn(wind speed, water vapor, water mass in cloud drops)  Limitation: ambiguous direction Accuracy:  Speed:  2 m/s  Direction:  22 0 (when combined with ECMWF 1000 mb wind analyses) Available data:  Global grid data: longitude  latitude  Since July 1987, every six hours

Measurement of wind (cont.)  Anemometers on ships Data  Read four times a day at GMT and report via radio Error  Sparse in time and space  May never be calibrated  Instantaneous rather than averaged values  Coding error

Measurement of wind (cont.)  Calibrated anemometer on ships Few ships Volunteer Observation Ship program Best accuracy:  2 m/s  Calibrated anemometers on weather buoys Few buoys (  100) Tropical Atmosphere Ocean (TAO) array Satellite links Accuracy  Speed:  1 m/s or 10%  Direction:  10 0

Measurement of wind (cont.)  Surface analysis from Numerical General Models Various observations  monthly averages (OK) Various observations  numerical model (problem)  Data assimilation (sequential estimation techniques)  Measurements are used to prepare initial conditions for the model, which is then integrated forward in time until further measurements are available. The model is thereupon reinitialized ECMWF data  European Centre for Medium-range Weather Forecasts  Surface fluxes, wind stress, heat flux, …  Every six hours on a 1 0  1 0 grid  Accuracy  Wind speed:  1.5 m/s  Direction:  18 0

Measurement of wind (cont.)  Reanalyzed output from numerical general circulation models Numerical models  continuous improved  calculated fluxes varied > inter-annual variability Use the best numerical models available  reanalyze data  uniform, internally consistent, surface analysis An example: offshore structure  Design  reanalyzed data  Operation  surface analysis and forecasts for every six hours

Measurement of wind (cont.)  Sources of reanalyzed data NCEP/NCAR ECMWF NASA

Sampling problem in Scatterometry  Sampling error Monthly maps  bands parallel to the satellite track Uneven distribution of samples Example: Fig 4.6  A weak storm  Catch in A but miss in B  6 m/s difference Sampling error 1 – 2 m/s in mid-latitudes

Wind stress  Wind stress The vertical transfer of horizontal momentum Our real interests T =  C D U 10 2   = 1.3 kg /m 3 : the density of air  C D : the drag coefficient  Fig 4.7: Correlation between T and U 10 2  C D  Dissipation method  1000C D = /U /U 10 2 (3  U 10  6 m/s) 1000C D = U 10 (6  U 10  26 m/s)

Important concepts  Driving source of energy  sunlight  Boundary layer Speed  height Fluxes of heat and momentum  constant  Measurements of wind Output from atmospheric circulation models  the most useful source of global wind velocity  Calculation of T