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 Report To Regional Response T 
 
 Coastal Region II 
 
 Third Coast Guard District 
 
 
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 A Climatological Oil Spi 
 Planning Guide 
 
 No.1 The New York Bight 
 
 February 1980 
 
 U.S. DEPARTMENT OF COMMERCE 
 
 National Oceanic and Atmospheric Administration 
 
 Environmental Data and Information Service 
 
gS fi BBte» 
 
 ^S,fTc5^ 
 
 Report To Regional Response Team 
 
 Coastal Region II 
 
 Third Coast Guard District 
 
 A Climatologies! Oil Spill 
 Planning Guide 
 
 No,1 The New York Bight 
 
 Compiled by: Joseph M. Bishop 
 
 Center for Environmental Assessment Services 
 Marine Environmental Assessment Division 
 
 Washington, D.C. 
 February 1980 
 
 U.S. DEPARTMENT OF COMMERCE 
 Philip M. Kiutznick, Secretary 
 
 National Oceanic and Atmospheric Administration 
 
 Richard A. Frank, Administrator 
 
 Environmental Data and Information Service 
 
 £» Thomas D. Potter, Director 
 
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CONTENTS 
 
 Page 
 
 1 . INTRODUCTION 1 
 
 2 . PATE OP OIL AT SEA 2 
 
 2 .1 Introduction 2 
 
 2.2 Spreading 3 
 
 2.3 Advection 4 
 
 2 . 4 Turbulent Diffusion 4 
 
 2 .5 Emulsion Formation 4 
 
 2.6 Photochemical Oxidation 4 
 
 2.7 Solution and Dispersion 6 
 
 2.8 Microbiological Action 6 
 
 2 .9 Evaporation 6 
 
 2.10 Oil Spill Modeling 6 
 
 2.10.1 Oil Pate Models 7 
 
 2.10.2 Oil Pate and Effect Models 7 
 
 2.10.3 Single Event Models 7 
 
 2.10.4 Climatological Models 7 
 
 2.10.5 Risk Assessment Models 8 
 
 2.11 Rule of Thumb Techniques 8 
 
 3 . ENVIRONMENTAL DATA 10 
 
 3 . 1 The Surface Wind Field 10 
 
 3.2 Wind Waves 17 
 
 3 . 3 Water Temperature 33 
 
 3.3.1 Temperature Distribution 33 
 
 3.3.2 Sea-Surface Temperature 46 
 
 3.4 Salinity 49 
 
 3.5 Density Distribution 49 
 
 3 .6 Vertical Mixing 51 
 
 3.7 Ocean Fronts, Meanders, and Eddies 59 
 
 3.8 Mean Coastal Currents 65 
 
 3.9 A Simulated Oil Drift Experiment 68 
 
 3.10 Location of Biological and Recreational Resources . 68 
 
 3.11 Calculated Climatological Relative Risk Ellipses 
 
 of the New York Bight 70 
 
 4. DATA AND SUPPORT FOR ACTUAL SPILLS OR SPILL PLANNING 
 
 (NOAA) 120 
 
 5. ACKNOWLEDGEMENT 121 
 
 6. References 122 
 
 ii 
 
1 . INTRODUCTION 
 
 Oil spills are a major concern associated with both offshore 
 oil production and movement of oil through the Mid-Atlantic Bight 
 area. This report summarizes appropriate environmental data, 
 discusses the movement of oil at sea, and attempts to predict the 
 effects of oil spills for the New York Bight, a region lying 
 between Montauk Point, N.Y., and Cape May, N.J. The concept that 
 a report of this type should be available was initially developed 
 during the grounding of the Argo Merchant . At that time, and 
 even to the present, there is no source of key environmental data 
 available related to oil spills for regional response planning. 
 The objective of this study is to provide this information in a 
 format that can be both understood and used by decision makers 
 for oil spill contingency planning and for scientific support 
 personnel during spills. 
 
2. PATE OP OIL AT SEA 
 
 2.1 Introduction 
 
 Environmental factors determine the fate of oil spilled at 
 sea. Initially, the oil starts to spread. This process is at 
 first rapid but slows (except for some oil fractions) until after 
 some hours a slick of semi-solid consistency is formed. Wind and 
 waves tend to break up the slick into patches. These patches are 
 eventually advected and diffused from the spill site. In 
 general, the primary factors concerning oil fate, as illustrated 
 in figure 1, are: 
 
 Spreading 
 Advection 
 
 Turbulent diffusion 
 Emulsion formation 
 Photochemical oxidation 
 Solution and dispersion 
 Microbiological action 
 Evaporation 
 
 Trace of Bottom 
 Deposited Oil 
 
 Trace of Sinking Oil 
 Plume on Sea Floor 
 
 Figure 1. — Block diagram showing the fate of an oil 
 slick (after Kolpack and Plutchak, 1976) 
 
2.2 Spreading 
 
 Attempts to describe theoretically the spreading of an oil 
 slick have been simple and are generally considered to be of 
 limited practical value for use at sea. The commonly used Fay 
 (1969) Theory states that oil spreads in three stages as shown in 
 figure 2. This type of information might be useful in helping 
 one make a decision on the amount of clean up resources required 
 by giving estimates of spill size. 
 
 10 7 
 
 10 6 - 
 
 I 10 5 
 
 10« 
 
 10- 
 
 I 
 
 1 1 
 
 1 
 
 jy 
 
 — 
 
 Gravity-Viscous 
 
 m* 
 
 1 
 
 1 1 
 
 ' 
 
 10' 
 
 10* 
 
 10* 
 
 10 s 
 
 10 6 
 
 10' 
 
 Time (sec) 
 
 Figure 2.— The size (diameter) of an oil slick as a 
 function of time for a 10,000 ton spill 
 (after Fay, 1969) 
 
2.3 Advection 
 
 The steady or residual movement of an oil slick is 
 critical. To determine this advection one must first consider 
 the appropriate averaging interval, because currents that occur 
 at intervals equal to or less than that time may cause either no 
 net movement (if they are periodic) or a diffusive effect (if 
 they are random). In general, for oil spill advection estimates 
 one usually uses the currents as depicted in an available atlas 
 that have been averaged for periods on the order of a month for 
 many years of observations. For this interval tidal currents are 
 periodic and transient wind-driven currents have strong random 
 nonadvective components. One must be careful here in that if the 
 oil is, for example, near the coast both the tidal current and/or 
 "random" wind-drift may drive the oil slicks on shore over a 
 shorter than advective time scale. 
 
 2.4 Turbulent Diffusion 
 
 Under favorable environmental conditions oil slicks tend to 
 break up into patches. These patches are generally advected with 
 the mean current but they are also subjected to random eddies in 
 the current field which spread the patches over a large area. 
 The rate of lateral spreading of these patches can be roughly 
 estimated using figure 3 over various time and space scales. 
 
 2.5 Emulsion Formation 
 
 In a short time after the spill the heavier fractions at 
 times take on a highly viscous consistency caused by the 
 formation of a water-in-oil emulsion termed "mousse" because of 
 its color and consistency. In this form oil may persist for 
 months and be advected to distant shorelines. An oil-in-water 
 emulsion can also exist with the oil in suspension. 
 
 2.6 Photochemical Oxidation 
 
 The less volatile fractions of oil are hydrocarbons whose 
 solubility in water is slight. Under the influence of sunlight, 
 however, these fractions can react with atmospheric oxygen to 
 produce more soluble compounds. This effect is small and could 
 only become important when oil is spread in a thin film over a 
 large area. Thus, photochemical oxidation may become a factor in 
 breaking down slicks a few microns thick. 
 
10 
 
 ,14 
 
 10 1 
 
 10 1 
 
 10' 
 
 (cm 2 ) 
 
 10 10 
 
 A North Sea 
 • Off Cape Kennedy 
 A New York Bight 
 O Off California 
 ■ Banana River 
 □ Manokin River 
 
 Figure 3. — Surface dye patch size,07, as a function 
 of time (after Okubo, 1962) 
 
2.7 Solution and Dispersion 
 
 A certain amount of the oil slick may actually pass into 
 solution in seawater. Although most probably a small effect, it 
 may constitute a pollution hazard because this is the easiest 
 state for interaction with marine organisms. Solubility 
 decreases rapidly with molecular weight and is usually small when 
 compared to the amount of oil dispersed as fine droplets. 
 Dispersion and solubility are processes that move oil from the 
 slick to the water column. Sea state (wave height) is the most 
 important environmental parameter governing dispersion. This 
 process could lead to concentrations of oil of 10 ppm to depths 
 of a few meters below a slick. Dispersed oil can easily be 
 ingested by marine organisms. 
 
 2.8 Microbiological Action 
 
 Many species of bacteria, molds, and yeasts, capable of 
 attaching oil, exist in seawater. These organisms are more 
 numerous in coastal waters. They use the hydrocarbons as an 
 energy source, but their activity depends on a plentiful supply 
 of nutrients. Under the most favorable conditions it seems that 
 a period of months is required to remove a large portion of a 
 slick. 
 
 2.9 Evaporation 
 
 A surface oil slick will lose mass due to surface 
 evaporation (vaporation) . The amount of loss is directly related 
 to the carbon number of the oil fraction in question. It also 
 depends on environmental factors such as wind speed and the 
 amount of wind-wave whitecapping. For the slick as a whole, 
 evaporation rates decline with time. Evaporation is usually 
 predicted using the single step approach in which the evaporated 
 fraction of the slick is removed as a step function. 
 
 2.10 Oil Spill Modeling 
 
 Knowledge of the movement of a surface oil slick is 
 important to give warning of possible shoreline pollution and 
 application of clean-up counter measures. Oil spill modeling 
 techniques have been developed to predict the movement of an oil 
 spill under actual or hypothetical conditions. Some of the 
 commonly used modeling techniques include: 
 
 Oil fate models 
 Oil fate and effect models 
 Single event models 
 Climatological models 
 Risk assessment models 
 
2.10.1 Oil Pate Models 
 
 The oil fate model is used to estimate the concentration, 
 distribution, and residence time of various fractions of oil into 
 various environmental sinks. An attempt is made to trace the 
 pathways that oil takes as it comes into contact with the 
 biota. The resulting computer calculations include all known 
 processes and parameters and their variable reaction rates. This 
 approach is probably the most advanced scientifically, but 
 because of the detailed environmental data inputs required, has 
 limited operational use. 
 
 2.10.2 Oil Fate and Effects Models 
 
 The oil fate and effect model is similar to the fate 
 model. It extends this type of calculation by using the output 
 of a fate model as input to a biological effect model. It also 
 requires detailed environmental data but, in general, is less 
 sophisticated in its physical and chemical parameterizations than 
 the fate model. This is a useful research tool but to date is 
 also not considered to be an operational tool that can be used 
 under actual spill conditions. 
 
 2.10.3 Single Event Models 
 
 The single event model is probably the best tool decision 
 makers have at their disposal for an actual spill, providing that 
 limited environmental data is available to a modeling support 
 group. It generally attempts to incorporate the most important 
 physical processes such as advection, diffusion, and spreading. 
 This type of model attempts to calculate future locations of oil 
 based on input parameters such as wind conditions and the ambient 
 current patterns, but it is limited by data inputs and thus 
 calculated trajectories are only as good as the sometimes 
 questionable inputs. 
 
 2.10.4 Climatological Models 
 
 The climatological modeling technique is based on archived 
 environmental data. It uses first order calculations of currents 
 to estimate oil advection. Usually advection is dominant over 
 other environmental factors and thus results have been useful in 
 such spills as that of the Argo Merchant . The "permanent" 
 current (derived from available atlas presentations) and a 
 transient wind-driven current (derived from local wind records 
 using the 3 percent rule) are added to produce a trajectory. The 
 trajectory is tracted in 3-hour intervals using a computer 
 simulation from the hypothetical spill site. Additional 
 trajectories are traced until relative risk diagrams can be drawn 
 that indicate the major direction of oil movement and its spread 
 
around this axis. The advantage of this calculation is that it 
 can be done calmly before the spill occurs and kept available in, 
 for example, an atlas for a specific location. The disadvantage 
 is that it is an approximation under actual conditions that is 
 only as good as the simple model assumptions. Also, this type of 
 model is limited by the assumption that conditions at spill time 
 are close to the climatological mean. This last approximation 
 may not be a poor one if the distance to an impact point is 
 large. 
 
 In section 3.11, relative risk diagrams are presented for 
 the New York Bight using a climatological computer simulation as 
 explained in Bishop (1976). These relative risk diagrams for 
 summer and winter are considered appropriate for all regions in 
 the New York Bight. The relative risk charts are moved to the 
 position of the hypothetical spill and adjusted to the mean 
 advection current axis. In this manner, one can estimate the 
 relative risk of various regions to impact. 
 
 2.10.5 Risk Assessment Models 
 
 A risk assessment model combines the trajectory of oil 
 movement with its biological and economic impact to arrive at a 
 decision on the possible deployment of the available limited 
 resources to reduce damage. It also can be used before the fact 
 to make decisions about locating oil facilities. 
 
 Summer and winter risk assessment charts for the New York 
 Bight were constructed by overlaying resource charts with the 
 climatological relative risk diagrams (fig. 57-105). In general, 
 winter spills tend seaward and possibly endanger offshore fishing 
 resources, while summer spills tend to impact the south shore of 
 Long Island more than any other region. 
 
 2.11 Rule of Thumb Techniques 
 
 Under certain circumstances, the person charged with making 
 a timely decision that requires an estimate of the fate of 
 spilled oil must act before qualified scientific advice can be 
 rendered. In this case, climatological estimated trajectories 
 might be helpful, but it seems a few common sense "rules of 
 thumb" are needed to help in making decisions. Consider the 
 following first-order approximations for advection. 
 
 In the absence of a strong permanent current, both empirical 
 and theoretical studies have shown that an oil slick on the ocean 
 surface travels at about 3 percent of the wind speed directed at 
 a slight angle (about 15° to the right) of the downwind 
 direction. 
 
In regions where strong permanent currents exist, such as 
 the Gulf Stream, available atlas presentations or satellite data 
 should be consulted. In general, the Gulf Stream is visible on 
 the IR photograph as a dark region about 100 km wide with the 
 core about 30 km from the shoreward boundary. A peak current of 
 about 150 cm/sec can be assumed for the core. The advection can 
 be approximated as the vectoral sum of wind driven current and 
 permanent current. If the oil spill is within a tidal excursion 
 to the impact point, an estimate of tidal current may also be 
 added to the current vector. 
 
 Another important operational consideration is the distance 
 between impact and spill site and how this relates through 
 various environmental processes to the time of impact. Figure 4 
 Indicates these relationships by plotting the important 
 environmental processes on a space-time chart. One need only 
 estimate the distance to the impact points and the advection 
 velocity toward impact. The diagram indicates impact time and 
 the various physical processes of importance for those length and 
 time scales. For example, a consideration of tidal currents is 
 only needed at a distance of 10-* to 10 m from spill to impact. 
 
 Time (sec) 
 
 a = nearshore spill 
 L = 10 3 m 
 1 T jmpact = 10 4 sec (U = 10 cm sec "' ] 
 
 10 cm sec' ) 
 
 Advection Velocity (cm sec -1 ) 
 
 Figure 4. — Time-length scales connected with oil 
 spills of various distance from shore 
 (after Stolzenbach et. al., 1977) 
 
3. ENVIRONMENTAL DATA 
 
 3.1 Surface Wind Field 
 
 An oil spill at sea is influenced by weather conditions. 
 Surface wind conditions produce wind waves and wind-driven 
 currents. Wind waves mix the oil both into the water column and 
 horizontally. Also, in theory, wave height is related to a 
 downwind wave driven current. Surface wind driven currents, in 
 theory, flow at 45° to the right of the wind. The combined oil 
 advection due to waves and wind-drift has been observed to be 
 about 3 percent of the wind magnitude directed about 15° to the 
 right of the wind. Other meteorological factors such as the 
 movement and location of major weather systems and atmospheric 
 fronts are important due to shifting wind conditions associated 
 with such disturbances. 
 
 The surface wind field is of prime importance in judging the 
 movement and thus the fate of oil spilled at sea. During the 
 winter, the wind in the New York Bight, related to a most 
 probable climatological pollutant trajectory, is from the WNW-NW 
 at 5 to 10 kt. During the summer the mean wind is directed from 
 the southwest at 3 to 4 kt. Figures 5 to 10 show calculated mean 
 wind vectors for various regions during specific months. Based 
 on this data, mean surface wind driven oil trajectories have a 
 higher probability of moving offshore during the winter months, 
 with the summer trajectories having a higher onshore tendency. 
 
 The mean wind field as presented can be explained by the 
 winter dominance of the Icelandic Low pressure system 
 (producing WNW-NW flow) and the summer dominance of the Bermuda 
 high pressure system (producing SSW-SW flow). 
 
 The constancy of the surface wind in the New York Bight has 
 been calculated by Williams and Godshall (1977). Winter and 
 summer constancy (about 50 percent and 40 percent, respectively) 
 is relatively high as compared to spring (about 15 percent) and 
 
 fall (about 25 percent) . 
 
 The above information concerning the mean wind and its 
 constancy can be interpreted in terms of oil spill trajectory 
 estimates in the following manner. In regions that are far 
 enough from the impact point (for example, outside one tidal 
 excursion) , the most probable impact would occur more frequently 
 along the mean wind direction. This type of climatological 
 projection, based on wind-driven currents, is most accurate 
 during seasons of high wind consistency and will be modified in 
 the presence of the prevailing permanent current. The constancy 
 can be interpreted in the context of the spread of oil spill 
 trajectories starting from a common point. The climatological 
 
 10 
 
FEBRUARY 
 
 Figure 5. — Monthly mean wind vectors in knots (after 
 Lettau, Bernhard, and Bower, 1976) 
 11 
 
Figure 6. — Monthly mean wind vectors in knots (after Lettau, 
 Bernhard, and Bower, 1976) 
 
 12 
 
?- MAY 
 
 ?S°00' 74°00' 73* 
 
 oo' 
 
 72°00' 
 
 
 
 18 
 
 1 
 
 - JUNE 
 
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 'y^X. 
 
 ft ">) 
 
 i<?7 
 
 
 8' 
 
 
 
 
 
 
 
 
 WESTHAMPTMp7Y-J»^ 
 
 
 
 
 
 
 NEWARK^-// 
 
 f ^iKENfEDY ~-—^~M ^^"•" - 
 
 
 
 
 
 
 
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 ^' ' 
 
 
 
 
 
 
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 VI ' / 
 
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 / 
 
 
 
 
 
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 S 
 
 
 
 
 
 
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 ATLANTIC OTY (Mpr 
 
 /"/ 
 
 /r 
 
 
 
 
 
 
 
 / / 
 
 f / 
 
 
 
 
 5: 
 
 1 
 
 / / V 
 
 j 
 
 
 TB 
 
 OO' M°0O 73 
 
 00 
 
 rj'oo 
 
 
 
 Figure 7. — Monthly mean wind vectors in knots (after Lettau, 
 Bernhard, and Bower, 1976) 
 
 13 
 
•I- JULY- 
 
 AUGUST 
 
 Figure 8. — Monthly mean wind vectors in knots (after Lettau, 
 Bernhard, and Bower, 1976) 
 
 14 
 
SEPTEMBER 
 
 y&***?^ > 
 
 Figure 9. — Monthly mean wind vectors in knots (after Lettau, 
 Bernhard, and Bower, 1976) 
 
 15 
 
; !- NOVEMBER 
 
 Figure 10. — Monthly mean wind vectors in knots (after Lettau, 
 Bernhard, and Bower, 1976) 
 
 16 
 
presentation depicting wind variability is the wind rose. 
 Figures 11 to 22 show surface wind roses for the study region in 
 which winter and summer roses indicate more of this 
 unidirectional tendency than spring and fall. This tendency 
 generally agrees with the calculations of constancy given by 
 Williams and Godshall (1977). Hence, oil spills in winter and 
 summer can be expected to be advected with a higher probability 
 in the mean wind direction than in spring and fall. 
 
 3.2 Wind Waves 
 
 Ocean waves have important effects on the eventual fate of 
 spilled oil at sea. Wind waves provide surface turbulence which 
 mixes a surface slick into the water column. Also, due to 
 exponential decay of wave particle velocity with depth, particles 
 on wave crests move slightly forward compared to those at the 
 trough, resulting in a slight wave-induced drift (about 1 percent 
 of the wind speed) in the down wind direction. For the purpose 
 of oceanographic analysis, the ocean area has been partitioned as 
 in Williams and Godshall (1977) into various ocean regions as 
 illustrated in figure 23. 
 
 Area 6 has a depth on the order of 50 m. Because of the 
 coastline, it is fetch-limited to the west and north; thus, for a 
 given duration, maximum waves would not be expected when the wind 
 is from these directions. Monthly wave roses for winter 
 (November to April) and summer (May to October) in this area are 
 shown in figure 24. Seas are higher in winter, and the 
 predominant wave direction for November and February is from west 
 to northwest. The highest waves, from 6 to 7.5 m, are observed 
 in December, January, and February, but for only a very small 
 percentage of the time. For 30 percent of the time, the waves 
 propagate from a westerly direction and are less than 1.5 m in 
 height. In June and July, the waves are almost exclusively from 
 the southwest and south and less than 1.5 m high. The winter and 
 summer height-period histograms for area 6 indicate that waves as 
 high as 9 m have been observed in winter, although rarely, 
 whereas in summer the maximum is 5 m (fig. 25). 
 
 
 17 
 
•Monthly surface wind roses for the New 
 York Bight (after the Naval Weather 
 Service Detachment, 1976) 
 
 18 
 
Figure 12. — Monthly surface wind roses for the New 
 York Bight (after the Naval Weather 
 Service Detachment, 1976) 
 
 19 
 
Figure 13. — Monthly surface wind roses for the New 
 York Bight (after the Naval Weather 
 Service Detachment, 1976) 
 
 20 
 

 Figure 14. — Monthly surface wind roses for the New 
 York Bight (after the Naval Weather 
 Service Detachment, 1976) 
 
 21 
 
-Monthly surface wind roses for the New 
 York Bight (after the Naval Weather 
 Service Detachment, 1976) 
 
 22 
 

 Figure 16. — Monthly surface wind roses for the New 
 York Bight (after the Naval Weather 
 Service Detachment, 1976) 
 
 23 
 
Figure 17. — Monthly surface wind roses for the New 
 York Bight (after the Naval Weather 
 Service Detachment, 1976) 
 
 24 
 
Figure 18. — Monthly surface wind roses for the New 
 York Bight (after the Naval Weather 
 Service Detachment, 1976) 
 
 25 
 
Figure 19. — Monthly surface wind roses for the New 
 York Bight (after the Naval Weather 
 Service Detachment, 1976) 
 
 26 
 
I OCTOBER 
 
 SURFACE WIND ROSE 
 
 DIRECTION FREQUENCY: 
 BARS, EACH CIRCLE = 20% 
 
 25% OF ALU WINDS 
 WERE FROM NORTH- % 
 EAST. 
 
 MEAN SPEED (KNOTS) 
 IS INDICATED BY THE 
 PRINTED NUMBER AT 
 THE END OF EACH M. 
 BAR. 
 
 73° 
 
 T 
 
 ■Monthly surface wind roses for the New 
 York Bight (after the Naval Weather 
 Service Detachment, 1976) 
 
 27 
 
Figure 21. — Monthly surface wind roses for the New 
 York Bight (after the Naval Weather 
 Service Detachment, 1976) 
 
 28 
 

 Figure 22. — Monthly surface wind roses for the New 
 York Bight (after the Naval Weather 
 Service Detachment, 1976) 
 
 29 
 
Figure 23. — Areas used for summaries of oceanographic 
 data (after Williams and Godshall, 1977) 
 
 30 
 
i- 
 
 NOV. 
 
 B*. 
 
 DEC. 
 
 JAN. 
 
 FEB 
 
 MAR. 
 
 APR. 
 
 MAY 
 
 JUNE 
 
 AUG. 
 
 SEPT. 
 
 OCT 
 
 % CALMS 
 
 l.mli.nl 
 
 J I 
 
 5 10 20 30 40 50 
 FREQUENCY % 
 
 HEIGHT (m) 
 3 .5 1 15™ 5 
 
 NO OF OBSERVATIONS 
 
 Figure 24. — Wave roses for winter (top) and summer 
 (bottom) (after Williams and Godshall, 
 1977) 
 
 31 
 
60 
 
 50 — 
 
 40 
 
 5? 30 
 
 20 
 
 WINTER 
 
 WAVE PERIOD(S) 
 
 6-9 
 
 >10 
 ALL 
 
 10 - ,- "Vs 
 
 
 0-.5 1-1.5 2-2.5 3-3.5 4-5.5 6-7.5 8-9.5 
 
 HEIGHT (m) 
 
 > 10 
 
 60 
 
 50 
 
 40 
 
 30 
 
 20 
 
 10 
 
 
 
 SUMMER 
 
 WAVEPERIOD(S) 
 
 ...... 6-9 
 
 >10 
 ALL 
 
 0-.5 1-1.5 2-2.5 3-3.5 4-5.5 6-7.5 8-9.5 > 10 
 
 Figure 25.' 
 
 HEIGHT (m) 
 
 •Wave height-period histograms, area 6 
 (after Williams and Godshall, 1977) 
 
 32 
 

 3.3 Water Temperature 
 
 3.3.1 Temperature Distribution 
 
 The mixing rate of oil in the water is related to water 
 temperature in that higher temperatures increase mixing. Also, 
 because of the relationship between water temperature and 
 circulation features, temperature gradients usually coincide with 
 circulation boundries. 
 
 Because of increased wind mixing in the winter, a vertically 
 constant temperature is observed throughout the water column, 
 with the coldest water near shore increasing toward the 200 m 
 isobath. 
 
 A rapid vertical change of temperature ( thermocline) appears 
 in May and continues to intensify to a maximum temperature 
 difference of about 17° in early September. Thus, during the 
 summer the water column is a point of minimum mixing ability 
 (maximum stability). Figures 26 to 37 show the mean monthly 
 temperature distribution for the New York Bight. 
 
 
 
 
 33 
 
1 :2, 750.000 
 10 10 20 
 
 Kilomatan 
 10 10 20 
 
 72° 
 
 JANUARY 
 
 41° 75° 
 
 25m 
 
 TSm 
 
 , 125m 
 
 Figure 26. — Mean monthly temperature distribution in the New York 
 Bight. Map pairs show bottom contours (top), surface 
 
 and vertical contours (bottom) 
 (after Bowman and Lewis, 1977) 
 
 Units are 
 
 34 
 
FEBRUARY 
 
 41»78° 
 
 . 100m 
 
 Figure 27. — Mean monthly temperature distribution in the New York 
 Bight. Map pairs show bottom contours (topK surface 
 
 and vertical contours (bottom) . Units are 
 (after Bowman and Lewis, 197 7) 
 
 35 
 
Figure 28. — Mean monthly temperature distribution in the New York 
 Bight. Map pairs show bottom contours (top), surface 
 and vertical contours (bottom). Units are C. 
 (after Bowman and Lewis, 1977) 
 
 36 
 

 41*73 
 
 50m , 
 
 APRIL 
 
 50m 
 
 100 m 
 
 Figure 29. — Mean monthly temperature distribution in the New York 
 Bight. Map pairs show bottom contours (top), surface 
 and vertical contours (bottom). Units are C. 
 (after Bowman and Lewis, 1977) 
 
 37 
 
MAY 
 
 41° 75° 
 
 Figure 30. — Mean monthly temperature distribution in the New York 
 Bight. Map pairs show bottom contours (top), surface 
 and vertical contours (bottom). Units are C. 
 (after Bowman and Lewis, 1977) 
 
 38 
 
1:2.730,000 
 
 10 10 20 
 
 > i,,l I 
 
 Statuta mil** 
 10 10 20 
 
 41°« 
 
 75m fc 
 
 JUNE 
 
 
 ( 100m 
 
 200m 
 
 Figure 31. — Mean monthly temperature distribution in the New York 
 Bight. Map pairs show bottom contours (top), surface 
 
 and vertical contours (bottom), 
 (after Bowman and Lewis, 1977) 
 
 Units are 
 
 39 
 
1 :2. 750.000 
 
 10 10 20 
 
 1 i ■ 
 Statute mil«j 
 
 10 10 20 
 
 i i i i 
 Kilomatan 
 1 10 I 
 Nautical mttas 
 
 41° 75" 
 
 JULY 
 
 2Sm 
 
 50m , 
 
 „ 125m 
 
 150m 
 
 200m 
 
 Figure 32. — Mean monthly temperature distribution in the New York 
 Bight. Map pairs show bottom contours (top), surface 
 and vertical contours (bottom). Units are C. 
 (after Bowman and Lewis, 1977) 
 
 40 
 

 41° 75° 
 
 72" 
 
 AUGUST 
 
 
 Figure 33. — Mean monthly temperature distribution in the New York 
 Bight. Map pairs show bottom contours (top), surface 
 and vertical contours (bottom). Units are C. 
 (after Bowman and Lewis, 1977) 
 
 41 
 
SEPTEMBER 
 
 41°75" 
 
 100m , 
 
 175m * 
 
 Figure 3^. — Mean monthly temperature distribution in the New York 
 
 Bight. Map pairs show bottom contours (top), 
 and vertical contours (bottom) . Units are C 
 (after Bowman and Lewis, 1977) 
 
 surface 
 
 42 
 
41° 73° 
 
 2Sm 
 
 Mm , 
 
 72" 
 
 OCTOBER 
 
 . 25m 
 
 5 , 150m 
 
 Figure 35. — Mean monthly temperature distribution in the New York 
 Bight. Map pairs show bottom contours (top), surface 
 and vertical contours (bottom). Units are C. 
 (after Bowman and Lewis, 1977) 
 
 43 
 
NOVEMBER 
 
 41° 7S° 
 
 50m 
 
 , 100m 
 
 1S0m 
 
 200m 
 
 Figure 36. — Mean monthly temperature distribution in the New York 
 Bight. Map pairs show bottom contours (top), surface 
 and vertical contours (bottom). Units are °C . 
 (after Bowman and Lewis, 1977) 
 
 44 
 
DECEMBER 
 
 41° 76° 
 
 75m » 
 
 150m , 
 
 „ 125m 
 
 Figure 37. — Mean monthly temperature distribution in the New York 
 Bight. Map pairs show bottom contours (top), surface 
 and vertical contours (bottom). Units are °C . 
 (after Bowman and Lewis, 1977) 
 
 45 
 
3.3.2 Sea-Surface Temperature (remote sensing techniques) 
 
 The "average" picture of water temperatures presented in the 
 previous section is clearly an oversimplification that tends to 
 smooth out the convoluted fronts and sharp gradients which may 
 exist. The complexity of the sea surface temperature structure 
 in this region has been confirmed by high resolution satellite 
 imagery. 
 
 One operational product based on these satellite images is 
 the analysis which has been produced weekly by the USCG 
 Oceanographic Unit, the U.S. Navy, and NOAA. Each analysis, 
 based on several days of observation, shows the positions of the 
 major thermal fronts in schematic form and the locations of cold 
 and warm eddies, and identifies the different water masses. Two 
 of these analyses (figs. 38 and 39) show, for example, that 
 conditions can range from the relatively simple to the 
 complicated; both are for the same month (April) but two 
 different years. These analyses may be obtained by writing to: 
 
 NOAA/NESS S132 
 
 Director, Environmental Products Br. 
 World Weather Bldg. , Room 510 
 Washington, DC 20233 
 
 Satellites are extremely valuable tools to map large scale 
 circulation features such as permanent currents, water mass 
 boundaries, and large eddies, but they do have limitations. 
 
 1. At best, they record only the skin temperature of the 
 ocean, as opposed to the bulk temperature measured by 
 ordinary, immersed thermometers. Except during periods of 
 unusual calm, the normal stirring by waves eliminates this 
 as a serious problem. However, even bulk surface 
 temperatures are not reliable indicators of deeper 
 temperature patterns. 
 
 2. More serious is the effect of water vapor in the 
 intervening atmosphere on satellite measurements. These 
 errors can be corrected to some extent by using an assumed 
 water vapor profile from a model atmosphere. A better 
 solution will be possible with the forthcoming advances 
 which will have two infrared bands that respond quite 
 differently to water vapor. The differences in measured 
 radiance can be used to determine the atmospheric 
 correction. It is expected that absolute temperatures 
 should be accurate to about 1°C. (Research Institute of the 
 Gulf of Maine, 1974). 
 
 46 
 
Figure 38.- 
 
 -Experimental Gulf Stream analysis 
 produced by NOAA satellite monitoring 
 (after the Research Institute of the 
 Gulf of Maine, 1974) 
 
 47 
 
Figure 39. — Experimental Gulf Stream analysis 
 
 produced by NOAA satellite monitoring 
 (after the Research Institute of the 
 Gulf of Maine, 1974) 
 
 48 
 
3. Cloud cover is a serious limitation to satellite 
 mapping, since sea-surface temperatures can be observed only 
 when the satellite pass happens to coincide with a cloud- 
 free period. Oceanic phenomena change more slowly than 
 those in the atmosphere, so that the continually improving 
 coverage in time will eliminate much of this problem, except 
 for periods of extended cloud cover. 
 
 A second technique for mapping sea-surface temperatures is 
 the use of air-borne radiation thermometry (ART). This technique 
 is useful in locating the region of sharp gradients, such as 
 those that occur near major current boundaries and large scale 
 eddies (fig. 40). Except for special studies, ART data should be 
 supplemented by satellite imagery which provides broader coverage 
 and is more nearly instantaneous over a large area. 
 
 For climatological purposes, the best regular reports on 
 sea-surface temperature are provided by "Gulf stream" , a monthly 
 publication of the National Weather Service. The reports are 
 based on all available information from ships, aircraft, and 
 satellites. Each issue includes a schematic drawing of the 
 locations of the oceanic fronts and eddies, a selection of 
 bathythermograms (BTs) and charts giving the mean surface 
 temperature for the month, anomaly from the 100-year mean for the 
 month, and the change from the previous month, all on a one- 
 degree grid from 25 to 45°N and 55° to 85°W. 
 
 3.4 Salinity Distribution 
 
 The observed salinity distribution is a result of the 
 balance between river runoff, evaporation minus precipitation, 
 advection, and mixing. Salinity is at a maximum at the end of 
 winter (due to subfreezing conditions on the continent) and at a 
 minimum in early summer (due to spring runoff). Although the 
 salinity field is critical in the determination of the density 
 distribution, salinity charts are not presented here, since there 
 is no presently accepted link between this parameter and oil 
 spill processes. 
 
 3.5 Density Distribution 
 
 In the New York Bight region the water reaches its maximum 
 density during the winter months because of the annual minimum in 
 temperature and maximum in salinity. In the spring, vernal 
 warming of the suface water coupled with a large increase in 
 runoff produce a marked vertical and horizontal stratification of 
 the water column. The resulting cross-shelf horizontal 
 stratification drives a southward directed coastal flow that 
 increases in magnitude (i.e., 10-15 cm/sec) into late summer. 
 This mean baroclinic (density driven) current may be important in 
 
 49 
 
Figure 40. — Sea-surface temperature through U.S. Coast 
 Guard Airborne Radiation Thermometer (after 
 the Research Institute of the Gulf of 
 Maine, 197*0 
 
 50 
 
the long-term advection of an oil spill at sea during calm 
 periods. The vertical stratification and development of a sharp 
 density change (pycnocline) starts (as does the thermocline) in 
 May and continues to increase in intensity to a maximum in 
 September. This condition will lead to a tendency for oil 
 spilled in the upper 10-15 m mixed layer to be trapped above the 
 strong pycnocline at 15-30 m. Figures 41 to 45 show the mean 
 density distribution for the New York Bight. Figure 46 shows 
 typical vertical density profiles. 
 
 3.6 Vertical Mixing 
 
 Vertical mixing of oil in the ocean can occur by convective 
 processes, by mechanical stirring such as surface wind-wave 
 mixing, by tidal current mixing, or by diffusion. Vertical 
 mixing is therefore a function of the density stratification and 
 of the vertical turbulence. 
 
 Implications regarding the extent of vertical mixing are 
 drawn from the analysis of water "stability," E, defined by 
 Hesselberg and Sverdrup (1914) to be the vertical density 
 gradient. Large positive values of E imply strong vertical 
 stratification, which inhibits vertical mixing; small positive 
 values of E imply deep vertical mixing, as caused, for example, 
 by strong winter winds. Here, E will be closely 
 approximated by A<T£ /AZ. , the vertical gradient of 
 sigma- t[ 0^ = (density-1 )1000] , to provide a convenient numerical 
 range. 
 
 Values of stability for areas 5, 6, 8, 9, and 12 are given 
 in table 1 for all seasons. 
 
 Winter . In mid-shelf areas 5, 6, and 8, stability is low 
 and variability is high. The water column for area 6 in winter, 
 shown in figure 46 is nearly homogeneous with only a slight 
 increase in density from surface to bottom. This is associated 
 with strong wind mixing and surface cooling. The offshore areas 
 9 and 12 show similar characteristics in the first 100 m, but 
 stability below 100 m decreases smoothly to near zero in the 
 bottom layers. During winter, density increases very gradually 
 with depth, and mixing occurs throughout the water column on the 
 shelf and down to the depth of penetration of seasonal influence 
 on the slope (>200 m) . These conditions lead to enhanced mixing 
 of a surface oil spill throughout the water column. 
 
 Spring . Warmer temperatures and river runoff in the surface 
 layers combine to decrease density in the surface layers and thus 
 increase stability. There is a decrease in density on both the 
 shelf and the slope. Table 1 shows the slight increase in 
 stability. Under these conditions, vertical mixing will not be 
 
 51 
 
73" 72" 
 
 JANUARY-MARCH 
 
 41»7B" 
 
 Figure 41. — Seasonal mean density distribution. Map pairs show 
 bottom contours (top), surface and vertical contours 
 (bottom). Units are sigma-t. (after Bowman and 
 Lewis, 1977) 
 
 52 
 
APRIL-MAY 
 
 41° 75° 
 
 200m 
 
 150m 
 
 Figure 42. — Seasonal mean density distribution. Map pairs show 
 bottom contours (top), surface and vertical contours 
 (bottom). Units are sigma-t. (after Bowman and 
 Lewis, 1977) 
 
 53 
 
50m 
 
 73° 72" 
 
 JUNE-AUGUST 
 
 41° ?5 D 
 
 , 25m 
 
 , 'Mm 
 
 Figure 43. — 
 
 Seasonal mean density distribution. Map pairs show 
 bottom contours (top), surface and vertical contours 
 (bottom). Units are sigma-t. (after Bowman and 
 Lewis, 1977) 
 
 54 
 
73° 72° 
 
 SEPTEMBER-OCTOBER 
 
 41°7S U 
 
 75m , 
 
 200m 
 
 179m 
 
 Figure 44. — Seasonal mean density distribution. Map pairs show 
 bottom contours (top), surface and vertical contours 
 (bottom). Units are sigma-t. (after Bowman and 
 Lewis, 1977) 
 
 55 
 
1 :2. 750.000 
 
 10 10 20 
 
 i i l [ 
 Sututa itoIm 
 
 10 10 20 
 
 ■ • ' I 
 
 Kilonwtan 
 10 10 
 
 50m 
 
 150m . 
 
 73° 72" 
 
 NOVEMBER-DECEMBER 
 
 41°75° 
 
 Figure 45. — Seasonal mean density distribution. Map pairs show 
 bottom contours (top), surface and vertical contours 
 (bottom). Units are sigma-t. (after Bowman and 
 Lewis, 1977) 
 
 56 
 
DENSITY (a t ) 
 
 SFC 
 
 
 21.0 22.0 23.0 
 
 24.0 25.0 
 
 26.0 
 
 
 
 III I 
 
 ;l / I 
 
 
 
 
 ! 
 
 
 
 
 
 \ 
 
 
 10 
 
 
 
 ^l 
 
 
 20 
 
 — 
 
 
 
 
 
 
 ^<v \ 
 
 
 
 
 
 V\ ^ •• 
 
 
 
 
 
 \\ \ : 
 
 
 ~30 
 
 B 
 
 ^ 
 
 
 Y\ \ : 
 
 
 X 
 
 I- 
 
 
 
 M ^ 
 
 
 a. 
 
 HI 
 
 a 
 
 
 
 v\ \ 
 
 
 40 
 
 
 
 •A \ 
 
 • i * 
 
 • 1 
 
 
 50 
 
 
 SPRING 
 
 
 
 
 
 \ 
 
 • 
 
 \ 
 
 • 
 
 
 
 
 
 — . — — FALL 
 
 
 
 60 
 7n 
 
 
 
 \ 
 
 
 
 Figure 46. — Mean vertical density profiles for area 6 (after 
 Williams and Godshall, 1977) 
 
 57 
 
Table 1.— Vertical stability E = (A(£/dZ) x 10 3 (after 
 Williams and Godshall, 1977) 
 
 
 Winter 
 
 Spring 
 
 Summer 
 
 Pall 
 
 Depth 
 
 Mean 
 
 Stand. 
 
 Mean 
 
 Stand. 
 
 Mean 
 
 Stand. 
 
 Mean 
 
 Stand 
 
 (m) 
 
 
 dev. 
 
 
 dev. 
 Area 5 
 
 
 dev. 
 
 
 dev. 
 
 10 
 
 9.1 
 
 20.6 
 
 54.1 
 
 51.5 
 
 100.0 
 
 43.4 
 
 8.0 
 
 13.0 
 
 20 
 
 15.2 
 
 3.2 
 
 49.3 
 
 36.7 
 
 92.8 
 
 41.6 
 
 6.2 
 
 13.8 
 
 30 
 
 2.2 
 
 6.7 
 
 23.5 
 
 14.6 
 
 61.5 
 
 22.9 
 
 6.3 
 
 8.3 
 
 40 
 
 1.7 
 
 2.8 
 
 14.4 
 
 8.4 
 
 33.2 
 
 16.7 
 
 13.0 
 
 12.1 
 
 50 
 
 
 
 
 Area 6 
 
 30.0 
 
 7.1 
 
 
 
 10 
 
 5.3 
 
 20.5 
 
 74.5 
 
 108.8 
 
 167.0 
 
 123.2 
 
 16.1 
 
 28.6 
 
 20 
 
 17.4 
 
 36.2 
 
 74.5 
 
 85.6 
 
 125.4 
 
 81.1 
 
 44.1 
 
 68.8 
 
 30 
 
 6.2 
 
 14.2 
 
 29.0 
 
 42.1 
 
 65.3 
 
 45.3 
 
 26.6 
 
 32.1 
 
 40 
 
 2.0 
 
 6.0 
 
 9.6 
 
 10.1 
 Area 8 
 
 31.6 
 
 19.5 
 
 38.4 
 
 13.1 
 
 10 
 
 24.7 
 
 74.5 
 
 147.9 
 
 164.7 
 
 226.4 
 
 225.5 
 
 50.2 
 
 104.7 
 
 20 
 
 2.6 
 
 5.8 
 
 38.4 
 
 45.9 
 Area 9 
 
 119.8 
 
 102.0 
 
 14.8 
 
 27.2 
 
 10 
 
 2.5 
 
 4.8 
 
 5.0 
 
 28.9 
 
 50.2 
 
 49.2 
 
 9.5 
 
 29.3 
 
 20 
 
 3.1 
 
 5.0 
 
 30.0 
 
 19.6 
 
 64.4 
 
 36.4 
 
 10.9 
 
 19.5 
 
 30 
 
 4.3 
 
 6.3 
 
 22.3 
 
 23.4 
 
 63.8 
 
 19.8 
 
 15.2 
 
 19.7 
 
 40 
 
 4.3 
 
 5.3 
 
 19.8 
 
 9.6 
 
 48.6 
 
 17.3 
 
 16.8 
 
 18.0 
 
 50 
 
 4.0 
 
 4.3 
 
 14.3 
 
 7.2 
 
 32.8 
 
 11.2 
 
 16.7 
 
 13.8 
 
 60 
 
 3.5 
 
 4.0 
 
 8.3 
 
 13.7 
 
 23.0 
 
 8.3 
 
 16.8 
 
 12.6 
 
 70 
 
 3.6 
 
 3.6 
 
 8.9 
 
 12.1 
 
 16.5 
 
 6.5 
 
 14.5 
 
 9.4 
 
 80 
 
 3.6 
 
 4.5 
 
 6.7 
 
 8.5 
 
 12.8 
 
 5.3 
 
 12.9 
 
 10.0 
 
 90 
 
 3.7 
 
 4.1 
 
 7.3 
 
 6.6 
 
 9.6 
 
 4.3 
 
 11.5 
 
 7.8 
 
 100 
 
 3.2 
 
 3.2 
 
 7.1 
 
 8.2 
 Area 12 
 
 7.6 
 
 3.6 
 
 10.1 
 
 5.1 
 
 10 
 
 0.1 
 
 13.8 
 
 53.3 
 
 84.2 
 
 123.6 
 
 148.7 
 
 26.3 
 
 52.5 
 
 20 
 
 2.5 
 
 5.7 
 
 36.6 
 
 35.4 
 
 130.3 
 
 95.0 
 
 26.6 
 
 31.0 
 
 30 
 
 2.8 
 
 7.2 
 
 19.3 
 
 22.0 
 
 58.2 
 
 50.4 
 
 34.9 
 
 28.0 
 
 40 
 
 2.5 
 
 4.4 
 
 18.4 
 
 15.3 
 
 36.1 
 
 24.8 
 
 29.6 
 
 22.4 
 
 50 
 
 1.9 
 
 2.8 
 
 15.0 
 
 11.5 
 
 25.8 
 
 17.8 
 
 22.9 
 
 17.8 
 
 60 
 
 2.6 
 
 4.2 
 
 13.0 
 
 9.6 
 
 18.2 
 
 16.3 
 
 18.4 
 
 17.4 
 
 70 
 
 2.9 
 
 2.9 
 
 10.3 
 
 8.3 
 
 15.8 
 
 14.6 
 
 18.5 
 
 12.2 
 
 80 
 
 3.4 
 
 2.7 
 
 9.0 
 
 6.8 
 
 16.0 
 
 11.4 
 
 20.7 
 
 17.5 
 
 90 
 
 3.5 
 
 3.9 
 
 8.2 
 
 5.5 
 
 11.9 
 
 7.3 
 
 14.9 
 
 8.5 
 
 100 
 
 3.8 
 
 4.8 
 
 6.6 
 
 4.5 
 
 8.1 
 
 5.4 
 
 11.4 
 
 8.1 
 
 58 
 
as strong as during winter, but there is no "barrier" to vertical 
 mixing, as occurs in the summer when a strong pycnocline 
 develops . 
 
 Summer . Surface heating and inflow of river water are 
 associated with a further increase in the near-surface stability 
 on the shelf (fig. 46). Stability is also high in the top 30 m 
 on the slope, as seen in table 1, with increasing values toward 
 the south. Area 9 shows evidence of a definable mean mixed layer 
 15 m deep. During this season, a surface oil spill will most 
 probably be trapped in the upper mixed layer due to the 
 development of the strong pycnocline. 
 
 Fall . Surface cooling and evaporation increase density both 
 on the shelf and on the slope, resulting in lowered stability of 
 both shelf and slope water (table 1). Autumn convective overturn 
 on the shelf in the fall, with subsequent return to winter 
 conditions, can be quite rapid (within a week) and dramatic, as 
 has been shown by Shonting et al. (1966). 
 
 3.7 Ocean Fronts, Meanders, and Eddies 
 
 The boundary between coastal (shelf) water and slope water 
 is delineated by a sharp front at about the 200 m isobath (fig. 
 47). Surface temperature differences across the winter front are 
 about 2° to 4°C to a maximum of 8°C. Salinity differences are on 
 the order 1 to 2 ppt over 10-15 km horizontally and 20 to 40 m 
 vertically. Meanders of the frontal surface of +_ 75 Km (toward 
 land or sea) have been observed to propagate southwest (the 
 opposite of Gulf Stream meanders). The strong horizontal 
 stratification and velocity shears in the frontal region would 
 tend to trap an oil spill in this region. 
 
 Anticyclonic eddies that break off from the Gulf Stream are 
 an important mechanism for transferring properties (heat, 
 momentum, salt) from the Gulf Stream to the slope water. They 
 form when a large, inshore Gulf Stream meander detaches to form a 
 clockwise vortex (fig. 48). The strong currents and 
 stratification also make eddy location important in the 
 predictions of oil spill advection. 
 
 The meanders of the Gulf Stream occasionally become 
 elongated and pinched off to form separate rings of current that 
 retain their identity for long periods of time. The rings, which 
 break off in the Sargasso Sea, rotate in the counterclockwise, or 
 cyclonic, sense and enclose slope water, which at any depth is 
 colder than the surrounding Sargasso Sea water (fig. 49). 
 Therefore, they are called cyclonic or cold-core rings or 
 eddies. Conversely, those which break off in the slope water 
 
 59 
 
stationary front 
 
 Figure 47. — Slope front and Gulf Stream, March 31, 
 1970 (after Bowman, 1977) 
 
 60 
 
Figure 48. — Drift of anticycfonic eddy (after Bowman, 
 1977) 
 
 61 
 
rotate clockwise and contain water that is anomalously warmer; 
 they are known as anti-cyclonic or warm core rings or eddies 
 (fig. 50). 
 
 The cyclonic rings, five to eight yearly, move off through 
 the Sargasso Sea and either dissipate after about a year or are 
 reassimilated within the Gulf Stream. They are associated with 
 the slope water only as a mechanism for transferring slope water 
 across the Gulf Stream. In contrast, the warmer core rings which 
 bring Sargasso and Gulf Stream water into the slope water are 
 much more important because of the limited area of the slope 
 water and because of the significant role they are believed to 
 play in determining its character and circulation. 
 
 The occurrence and movement of warm core rings are being 
 documented by both satellite imagery and ART aircraft flights and 
 the monthly "Gulfstream" summaries now regularly show their shape 
 and position. Most warm-core rings appear to develop in the 
 region of large Gulf Stream meanders east of 66°W, but some are 
 formed in the western slope water. At the same time that the 
 ring is moving, it is also rotating with speeds near the outer 
 edge ranging up to about 1 kt (50 cm/sec). From satellite 
 observations, it appears that the rotating rings entrain surface 
 shelf water along the shelf slope boundary and draw it out into 
 the slope water in long, narrow filaments. Warm-core rings begin 
 to decay shortly after formation; first the surface cools to the 
 temperature of the surrounding slope water, then the warm water 
 begins to mix away around the circumference. The lifetime of a 
 ring is estimated at 6 months to a year, but many appear to be 
 re-absorbed by the Gulf Stream before they lose their identity. 
 
 An eddy normally has an elongated shape and, when newly 
 formed, its long axis is oriented east-west. This axis rotates 
 with time, and has a general north-south orientation when the 
 eddy reaches 70° to 71°W. At this point, the eddy shape becomes 
 more rounded and the elongation is not as pronounced. 
 
 The diameter of an eddy varies from about 100 to 200 km at 
 the surface, as determined by airborne radiation thermometer 
 observations and temperature gradients. At the 200 m depth (an 
 eddy normally being located by the 15°C isotherm at this depth), 
 the diameter is 70 to 120 km. There is a tendency for an eddy to 
 decrease somewhat in size once it crosses 70°W. 
 
 62 
 
SCALE 
 50 100 150 
 
 NAUTICAL MILES 
 
 SLOPE WATER 
 
 SARGASSO WATER 
 
 SARGASSO WATER 
 
 SLOPE WATER 
 
 SLOPE WATER 
 
 SARGASSO WATER 
 
 . Gulf Stream y 
 \ Water ^ ' 
 
 SARGASSO WATER 
 
 Figure 49. — Diagram of ring formation from meander development to 
 separation of the Stream. Solid lines represent the 
 position of the 15°C isotherm at 200 m. Dashed lines 
 represent the approximate limit of the Sargasso sea 
 and the Gulf Stream, (after the Research Institute of 
 the Gulf of Maine, 1974) 
 
 63 
 
Figure 50. — Surface current speed (Kt) and direction of 
 circulation (after Williams and Godshall, 
 1977) 
 
 64 
 
3 .8 Mean Coastal Currents 
 
 A large amount of evidence indicates that the "permanent" 
 average flow in the coastal region of the New York Bight is 
 southwest at all depths. Extensive studies by Bumpus (1973) of 
 the permanent flow inshore of the 100 m isobath indicate a mean 
 flow on the order of 0.1 kt (5 cm/sec) southwest from Nantucket 
 Shoals to Cape Hatteras. During periods of prolonged southwest 
 winds and low runoff, surface currents have been observed flowing 
 northward in summer near the coast. Bottom currents appear to be 
 much weaker (0.008-0.02 kt; 0.4-1.0 cm/sec) than surface currents 
 and flow south and southwest. A weak seasonal fluctuation in the 
 permanent coastal current results from variations in wind stress 
 and runoff. 
 
 Ship drift is the result of the surface current and the 
 action of the wind on the ship's superstructure. Ship-drift data 
 represent a major source of information on large-scale flow in 
 the New York Bight and have been examined in some detail. 
 Williams and Godshall (1977) prepared ship drift charts for this 
 region. 
 
 Seasonal surface current vectors are presented in figures 51 
 to 54. They clearly show the well-documented mean southwest flow 
 over the shelf, the turn to seaward just north of Cape Hatteras, 
 and the northward flow seaward of the 200 m isobath along the 
 northern edge of the Gulf Stream. The typical mean speed is 0.1 
 kt (5 cm/sec). 
 
 A striking feature is the lack of strong seasonal 
 variability in currents, except near the mouths of estuaries. In 
 winter the primary driving force is the wind stress from the 
 northwest, while in summer it is the cross-shelf pressure 
 gradient generated by the outflow of low-salinity water from the 
 mouths of estuaries. 
 
 In summer, slight seasonal decrease in current strength 
 inferred from the ship-drift data is probably because the 
 prevailing southwest winds oppose the "coastal circulation" 
 created by the distribution of the mass field. 
 
 The constancy is the ratio, in percent, of the speed 
 associated with the mean vector of the current velocities to the 
 mean scalar average of the speed; i.e., a current that always 
 flows in the same direction would have a constancy approaching 
 1. The areas of highest constancy were calculated in the 
 southeastern part of the region along the northern edge of the 
 Gulf Stream, and in the midshelf region, especially in the 
 southern half of the area. Along the shelf break is an area of 
 low constancy, i.e., high variability in current direction. 
 There is little apparent seasonal variation in constancy. 
 
 65 
 
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3.9 Simulated Oil Drift Experiment 
 
 A field experiment designed to simulate the movement of oil 
 spills in the New York Bight was conducted by the Marine Sciences 
 Center, State University of New York at Stony Brook (Hardy, 
 Baylor, and Moskowitz 1976). More than 21,000 plastic driftcards 
 were released at 24 release points (figs. 55 and 56) between 
 January 23 and September 16, 1974. The results were summarized 
 in terms of summer and winter periods as follows: 
 
 The prevailing wind for the five-month period 
 November to March was west to northwest which 
 imparted a general seaward drift away from Long 
 Island's south shore. In the open outer 
 continental shelf the sea surface motion was 
 generally deflected to the right of the wind by 0° 
 to 10° so that prevailing winds from the west and 
 northwest set up a drift which was seaward from 
 Long Island. The prevailing onshore winds of 
 summer (112° to 147° T) blow toward Long Island. 
 However, the boundary conditions imposed by the 
 land mass of Long Island interfer with the simple 
 downwind transport. This deflects advection more 
 parallel to the shoreline. In these cases, the 
 release-recovery paths of drift cards may appear 
 to be deflected from the wind direction by large 
 angles. The southwest wind appeared to cause the 
 surface layer to move easterly or parallel to the 
 shoreline without converging on Long Island. 
 
 3.10 Location of Biological and Recreational Resources 
 
 In making an analysis of oil spill impact one must 
 not only consider the trajectory of the oil and the 
 important environmental parameters, but also the 
 resources of the potential impact regions. The following 
 diagrams give the location of selected biological and 
 recreational resources, (figs. 58-105). Relative impact 
 charts (fig. 57) based on the climatological oil 
 trajectory model, as explained in section 3.11, can be 
 combined with such data to estimate relative risk of 
 impact from spills at various locations. These 
 climatological relative risk charts can be used as an 
 overlay on the resource charts (fig. 58-105) to estimate 
 locations of high risk areas. 
 
 68 
 
1 1— 
 
 NAUTICAL MILES 
 10 20 30 
 
 10 20 30 40 50 
 KILOMETERS 
 
 T Z7 57 T7 — r 
 
 ■£> 
 
 <^. 
 
 RELEASE STATIONS 
 A BICOUNTY 
 • NOAA-MESA 
 
 _L 
 
 Figure 55. — Percent probability contours that some fraction of oil 
 spills will strand within 10 days on Long Island in 
 winter (January-March) 197^. Based on drift card return 
 frequencies per station (Hardy et al. , 1975) 
 
 NAUTICAL MILES 
 10 20 30 
 
 10 20 30 40 50 
 KILOMETERS 
 
 r Zr T Tr 
 
 7sr 
 
 <z 
 
 RELEASE STATIONS 
 A BICOUNTY 
 • NOAA-MESA 
 
 Figure 56. — Percent probability contours that some fraction of oil 
 spills will strand within 10 days on Long Island in 
 summer (April-September) 1974. Based on drift card return 
 frequencies per station (Hardy el al., 1975) 
 
 69 
 
3*11 Calculated Climatological Relative Risk 
 Ellipses of the New York Bight 
 
 To obtain a first-order estimate of the most probable path 
 an oil spill will take, a climatological approach was used. This 
 technique is based on the assumption that advection of the oil 
 slick by wind-driven currents is the most important factor. With 
 this approach, wind drift was given as 3 percent of the hourly 
 wind speed directed 15° to the right of the wind. Trajectories 
 were started from a hypothetical spill site and tracked on an 
 area geographic chart by computer for 10 nautical miles by 10 
 nautical mile areas. The climatological wind record for Kennedy 
 Airport was obtained from the National Climatic Center at 
 Asheville, N.C., and thousands of trajectories were tracted for 
 the summer and winter seasons. The resulting area impacts were 
 divided by the total trajectories, and relative risk ellipses 
 were formed. 
 
 These ellipses (fig. 57), will be assumed appropriate for 
 the whole New York Bight region. The ellipses, mirror the 
 statistics of the wind field since the winter mean wind is toward 
 the southeast and wind variability is relatively low. Thus the 
 risk calculations show a northwest/southeast elliptical 
 distribution. In the summer, when the mean wind is toward the 
 northeast and variability is high, a more circular distribution 
 is calculated. The use of these ellipses as an overlay on the 
 resource charts is a novel and important technique to estimate 
 spill impact from selected spill sites. Such a use would be 
 essential in pre-spill contingency planning. 
 
 70 
 
Figure 57. — Relative risk ellipses. 
 
 71 
 
Figure 58. — Natural resource chart for silver and red 
 hake spawning areas (after Smith, Slack, 
 and Davis, 1976) 
 
 72 
 
Figure 59- — Natural resource chart for harbor seal 
 whelping areas (after Smith, Slack, and 
 Davis, 1976) 
 
 73 
 
42° 
 
 41° — 
 
 -Natural resource chart for hard clam 
 grounds (after Slack and Wyant, 1978) 
 
 74 
 
Figure 61. — Natural resource chart for soft clam 
 grounds (after Slack and Wyant, 1978) 
 
 75 
 
Figure 62. — Natural resource chart for bay scallop 
 areas (after Slack and Wyant) 
 
 76 
 
Figure 63. — Natural resource chart for grey seal 
 areas (after Slack and Wyant, 1978) 
 
 77 
 
Figure 64. — Natural resource chart for surf clams 
 (after Gusey, 1976) 
 
 78 
 
37° 
 
 36° 
 
 35" 
 
 F 
 
 S" 
 
 AREA OF GREATER ABUNDANCE 
 
 37° 
 
 36° 
 
 76 c 
 
 75° 
 
 74 c 
 
 73 c 
 
 72 c 
 
 71< 
 
 70° 
 
 Figure 65. — Natural resource chart for Atlantic cod 
 (after Gusey, 1976) 
 
 79 
 
Figure 66. — Natural resource chart for bluefish 
 (after Gusey, 1976) 
 
 80 
 
Figure 67. — Natural resource chart for Atlantic 
 mackerel (fall) (after Gusey, 1976) 
 
 81 
 
-Natural resource chart for Atlantic 
 mackerel (spring) (after Gusey, 1976) 
 
 82 
 
Figure 69. — Natural resource chart for Atlantic 
 herring (fall) (after Gusey, 1976) 
 
 83 
 
Figure 70. — Natural resource chart for Atlantic 
 herring (spring) (after Gusey, 1976) 
 
 84 
 
Figure 71. — Natural resource chart for red hake 
 (fall) (after Gusey, 1976) 
 
 85 
 
Figure 72. — Natural resource chart for red hake 
 (spring) (after Gusey, 1976) 
 
 86 
 
Figure 73. — Natural resource chart for winter 
 
 flounder (fall) (after Gusey, 1976) 
 
 87 
 
Figure 74. — Natural resource chart for winter 
 
 flounder (spring) (after Gusey, 1976) 
 
 88 
 
Figure 75. — Natural resource chart for yellowtail 
 flounder (fall) (after Gusey, 1976) 
 
 89 
 
42 c 
 
 76° 
 
 75° 
 
 74° 
 
 73° 
 
 72° 
 
 70° 
 
 o 
 
 
 
 • o-rltj.o'-o.gA,''.! 
 
 dK9aW<\ 
 
 cty AREA OF GREATER ABUNDANCE 
 
 - 39° 
 
 38° 
 
 37° 
 
 36° 
 
 35° 
 
 73 c 
 
 72 c 
 
 71< 
 
 70° 
 
 Figure 76. — Natural resource chart for yellowtail 
 flounder (spring) (after Gusey, 1976) 
 
 90 
 
1970 
 
 O LOCATIONS NEAR BREEDING AREAS 
 M GENERAL DISTRIBUTION (SEASONAL) 
 
 Figure 77. — Natural resource chart for American shad 
 (after Marine Experimental Station, 
 U.R.I. , 1973) 
 
 91 
 
Figure 78. — Natural resource chart for striped bass 
 (after Marine Experimental Station, 
 U.R.I. , 1973) 
 
 92 
 
MAJOR 
 
 SPORT FISHING 
 
 AREAS 
 
 
 SPRING TO FALL 
 WINTER TO SPRING 
 
 35° 
 70° 
 
 
 Figure 79. — Natural resource chart for summer 
 
 flounder (after Marine Experimental 
 Station, U.R.I. , 1973) 
 
 93 
 
Figure 80. — Natural resource chart for menhaden 
 (after Marine Experimental Station, 
 U.R.I. , 1973) 
 
 94 
 
76 c 
 42° m 
 
 75° 
 
 41 c 
 
 40 c 
 
 39° 
 
 38° 
 
 
 o*«s!& - > 
 
 
 oO 
 
 J^K 
 
 j;o^:??' 
 
 ).o.o.o- 
 
 n5* 
 
 lo: 
 
 m^tmm 
 
 f.o^° 
 
 40° 
 
 ■9 >" 
 
 HUDSON 
 CANYON 
 
 39° 
 
 .0:< 
 
 M 
 
 O'o' 
 
 ■o.^s:-.Q-. 
 
 o.":o-J 
 
 VOO o-O.Q.' 
 
 38° 
 
 ' • • . • o • */ a 
 
 or 
 
 37° 
 
 INSHORE FISHERY 
 OFFSHORE FISHERY 
 
 - 36 e 
 
 35° 
 70° 
 
 74 c 
 
 73° 
 
 72 c 
 
 71 c 
 
 Figure 81. — Natural resource chart for lobster 
 (after Marine Experimental Station, 
 U.R.I. , 1973) 
 
 95 
 
•Natural resource chart for sea scallops 
 and calico scallops (after Marine 
 Experimental Station, U.R.I. , 1973) 
 
 96 
 

 T-r 
 \V 
 
 YELLOWTAIL 
 SILVER HAKE 
 RED HAKE 
 
 Figure 83. — Natural resource chart for yellow tail 
 silver hake, and red hake (fall) (after 
 Hennemuth, 1976) 
 
 97 
 
Figure 84. — Natural resource chart for squid, yellow 
 tail, silver hake, and red hake (spring) 
 (after Hennemuth, 1976) 
 
 98 
 
RED CRAB 
 SEA SCALLOPS 
 
 Figure 85. — Natural resource chart for sea scallops 
 and red crab (after Hennemuth, 1976) 
 
 99 
 
Figure 86. — Natural resource chart for wading birds 
 (after Slack and Wyant, 1978) 
 
 100 
 
Figure 87. — Natural resource chart for sea ducks 
 (after Slack and Wyant, 1978) 
 
 101 
 
Figure 88.- 
 
 -Natural resource chart for osprey (after 
 Slack and Wyant, 1978) 
 
 102 
 
Figure 89. — Natural resource chart for the bald eagle 
 (after Slack and Wyant, 1978) 
 
 103 
 
Figure 90.— 
 
 •Natural resource chart for peregrine 
 falcon nesting areas (after Slack and 
 Wyant, 1978) 
 
 104 
 
Figure 91. — Natural resource chart for peregrine 
 
 falcon migratory points (after Slack and 
 Wyant, 1978) 
 
 105 
 
42° 
 
 Figure 92. — Natural resource chart for birds with 
 limited distribution (after Marine 
 Experimental Station, U.R.I. , 1973) 
 
 106 
 
IPSWICH SPARROW 
 BROWN PELICAN 
 % ESKIMO CURLEW 
 
 - 36° 
 
 Figure 93. — Natural resource chart for birds with 
 limited distribution (after Marine 
 Experimental Station, U.R.I. , 1973) 
 
 107 
 
76° 75° 
 
 Figure 94 
 
 74 
 
 73° 
 
 72° 
 
 71 c 
 
 70° 
 
 ■Natural resource chart for birds with 
 limited breeding distribution (after 
 Marine Experimental Station, U.R.I. , 
 1973) 
 
 108 
 
Figure 95. — Natural resource chart showing selected 
 major breeding areas (after Marine 
 Experimental Station, U.R.I. , 1973) 
 
 109 
 
Figure 96. — Natural resource chart showing migration 
 points (after Marine Experimental 
 Station, U.R.I. , 1973) 
 
 110 
 
Figure 97. — Natural resource chart for sandy beaches 
 (after Slack and Wyant, 1978) 
 
 111 
 
■Natural resource chart for coastal marshes 
 (after Slack and Wyant, 1978) 
 
 112 
 
Figure 99. — Natural resource chart for areal extent 
 of national parks, seashores, and 
 recreation areas (after Slack and Wyant, 
 1978) 
 
 113 
 
Figure 100. — Natural resource chart for areal extent of 
 local and state parks and seashores 
 (after Slack and Wyant, 1978) 
 
 114 
 
Figure 101. — Natural resource chart for areal extent of 
 national wildlife refuges (after Slack 
 and Wyant, 1978) . 
 
 115 
 
Figure 102. — Natural resource chart for areal extent of 
 state wildlife and natural areas (after 
 Slack and Wyant, 1978) 
 
 116 
 
76° 75° 
 
 Figure 103 
 
 74 
 
 73 c 
 
 72 c 
 
 71< 
 
 70° 
 
 ■Natural resource chart for areal extent of 
 state marine sanctuaries (after Slack 
 and Wyant, 1978) 
 
 117 
 
-Natural resource chart for areal extent of 
 nongovernment wildlife and natural areas 
 (after Slack and Wyant, 1978) 
 
 118 
 
42° 
 
 76° 
 
 75° 
 
 41° 
 
 • GENERAL LOCATION OF COASTAL WETLANDS 
 o 10,000 ACRES OF PRIMARY IMPORTANCE 
 
 • 10,000 ACRES OF LESSER IMPORTANCE 
 
 40° 
 
 39° 
 
 38° 
 
 37° 
 
 36° 
 
 35° 
 
 73 c 
 
 72 c 
 
 71" 
 
 Figure 105. — Natural resource chart for wetlands 
 (after Gusey, 1976) 
 
 70° 
 
 119 
 
4. DATA AND SUPPORT FOR ACTUAL SPILLS OR OIL SPILL 
 
 PLANNING (NOAA) 
 
 a. Climatological Modeling 
 
 Chief, Marine Environmental Assessment Division 
 
 NOAA/EDIS/CEAS, D23 
 
 3300 Whitehaven St., N.W. 
 
 Washington, D.C. 20235 
 
 202/634-7381 
 
 b. Oceanographic Data Archives 
 Director, National Oceanographic Data Center 
 NOAA/EDIS/NODC, D7 
 
 2001 Wisconsin Avenue, N.W. 
 Washington, D.C. 20235 
 202/634-7232 
 
 c. Meteorological Data Archives 
 Director, National Climatic Center 
 NOAA/EDIS/NCC, D5 
 
 Federal Bldg. 
 Asheville, NC 28801 
 704/258-2850 
 
 d. Operational Marine Forecasts (including 
 oil spills) 
 
 Director, Techniques Development Lab. 
 
 NOAA/NWS/TDL, W42 
 
 Gramax Building 
 
 8060 13th Street 
 
 Silver Spring, MD 20910 
 
 301/427-7613 
 
 e. Single Event Modeling, Advice and 
 Forecasts 
 
 Chief, Oil Spill Scientific Support Team 
 
 7600 Sand Point Way, NE 
 
 Building 264 SW 
 
 Seattle, Washington 98115 
 
 (FTS) 399-5919 
 
 f . Marine Ocean Forecasts 
 Chief, Ocean Services Division 
 Gramax Building 
 
 8060 13th Street 
 
 Silver Spring, MD 20910 
 
 301/427-7778 
 
 120 
 
5. ACKNOWLEDGEMENT 
 
 This report was conceived and written by Joseph M. Bishop, 
 staff oceanographer, Marine Environmental Assessment Division Mr. 
 Edward Ridley, Division Chief, Center for Environmental 
 Assessment Services Dr. Kenneth Hadeen, Deputy Director, 
 EDIS/NOAA. Thanks goes to Donna Harrigan for her detailed 
 editing and technical assistance. The report was reviewed for 
 technical merit by Dr. Dave Amstutz of the Department of 
 Interior, Lt. Cdr. W. P. Holt U.S. Coast Guard, Drs . Dean Parsons 
 and Neeland McNaulty of the National Marine Fisheries Service 
 (NOAA) and Dr. Kurt Hess National Weather Service (NOAA). 
 
 121 
 
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 126 
 

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