A Global Ocean Wind Stress Climatology Based on Ecmwf Analyses

Home , Wind stress

NCAR/TN-338+STR NCAR TECHNICAL NOTE - August 1989

A GLOBAL OCEAN WIND STRESS CLIMATOLOGY BASED ON ECMWF ANALYSES

KEVIN E. TRENBERTH JERRY G. OLSON WILLIAM G. LARGE

T (ANNUAL)

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CLIMATE AND GLOBAL DYNAMICS DIVISION I NATIONAL CENTER FOR ATMOSPHERIC RESEARCH BOULDER. COLORADO

Table of Contents Preface ...... v Acknowledgments ...... v 1. Introduction ...... 1 2. D ata ...... 6 3. The drag coefficient ...... 8 4. Mean annual cycle ...... 13 4.1 Monthly mean wind stress ...... 13 4.2 Monthly mean wind stress curl ...... 18 4.3 Sverdrup transports ...... 23 4.4 Results in tropics ...... 30 5. Comparisons with Hellerman and Rosenstein ...... 34 5.1 Differences in wind stress ...... 34 5.2 Changes in the atmospheric circulation ...... 47 6. Interannual variations ...... 55 7. Conclusions ...... 68 References ...... 70 Appendix I ECMWF surface winds ...... 75 Appendix II Curl of the wind stress ...... 81 Appendix III Stability fields ...... 83

iii

Preface

Computations of the surface wind stress over the global oceans have been made using surface winds from the European Centre for Medium Range Weather Forecasts (ECMWF) for seven years. The drag coefficient is a function of wind speed and atmospheric stability, and the density is computed for each observation. Seven year climatologies of wind stress, wind stress curl and Sverdrup transport are computed and compared with those of other studies. The interannual variability of these quantities over the seven years is presented. Results for the long term and individual monthly means are archived and available at NCAR. It is anticipated that these fields will be useful for driving ocean general circulation models.

The wind stress statistics over the southern oceans are believed to be the most reliable available because of the paucity of direct wind observations. The main shortcomings with the current results are in the tropics. The wind stress is shown to vary considerably from year to year and the mean values for the climatology (1980-86) differ significantly from those of previous periods. In the Northern Hemisphere, there is good reason to believe that these changes are mostly real and represent climate variations on interannual and decadal time scales that have major implications for the circulation of the oceans.

Acknowledgments

Special thanks go to Dennis Shea for preparing the air-sea temperature differences and surface relative humidity values from COADS that are presented in Appendix III. We thank P. D. Jones for providing Fig. 32, and Jerry Meehl and Frank Bryan for comments. The research of Trenberth and Olson is partiall y the Tropical Oceans Global Atmosphere Project Office under grant NA86AANRG0100. The data used were provided by ECMWF.

v 1. Introduction

Progress in understanding our climate system is increasingly dependent on improved understanding of the interactions among the various subsystems, of which the atmosphere and the oceans are the most active. The thermal and mechanical coupling between the atmosphere and the underlying oceans not only plays an important role in determining the atmospheric circulation, but also serves as the primary driving for surface ocean currents. In this paper the main focus is on the surface momentum flux, or wind stress, by which the atmospheric winds drive oceanic currents, with the ocean acting as a sink for atmospheric momentum. Fluxes of heat and moisture are also important, and all three fluxes depend greatly upon the surface winds.

Because the total angular momentum of the earth system is conserved, exchanges of momentum between the atmosphere and oceans and the solid earth result in changes in the length of day (e.g. Barnes et al., 1983; Rosen and Salstein, 1983). In the atmosphere the primary torques arise from pressure gradients across mountain ranges, the so-called mountain torque, plus the surface wind stress giving rise to the frictional torque. The latter is complex and not well understood over land even though there are plentiful observations. The ocean surface wind stress is better understood, but the observational data base is often inadequate to properly define the field. Somewhat recent studies of the atmospheric torques have been made by Wahr and Oort (1984) and Swinbank (1985). The latter finds that short-term variations are mainly caused by changes in mountain torque.

For the oceans, the momentum flux from the atmosphere is arguably the most important forcing for the upper ocean through the driving of the surface ocean currents. Ocean circulation models require the surface wind stress as a specified boundary condition. Cli- matological wind stress fields are commonly used to force ocean circulation models that are tested against our knowledge of the mean state of the oceans. The detailed evolution of the wind stress fields is needed for examining interannual variations, such as El Nino, for four-dimensional data assimilation to produce reliable estimates of the state of the ocean at any given time, and to provide a basis for future predictions (e.g. Kousky and Leetmaa,

1 1989). Substantial differences that occur in different wind stress analyses become reflected in substantial differences in oceanic behavior (e.g. Harrison et al., 1989).

Of interest then, are not only climatologies of the mean annual cycle of surface wind stress, but also multiyear time series.

The exchanges of momentum, and of heat and moisture, are most commonly pa- rameterized using bulk aerodynamic formulae. For the surface wind stress r the bulk formulation is

r= (r-,ry) = PCDV(, V) (1) where the surface wind (nominally at 10 m) is assumed to be parallel to the stress vector, with components (u, v) and magnitude V (= wind speed). The density of surface air is p, and the drag coefficient CD depends on the height of the wind measurement. Halpern (1988b) has noted that on the equator, where the mean wind speeds are -4 m s- 1 and the ocean currents can reach 0.5 m s - 1, the neglect of the ocean current can affect the bulk wind stress by 10-20%. However, the surface ocean current velocity is neglected in (1) because observations are not readily available and it is usually small compared with the wind speed.

From (1) the magnitude of the stress is Ir| = PCDV2 , which serves as a useful definition of CD. There have been many estimates of CD, for instance, computed as the ratio of the directly measured Reynolds stress to the square of the wind speed (e.g., Large and Pond, 1981). Often, through averaging, a single constant drag coefficient has been determined, which has the advantage of simplicity. But it is apparent from both theory and observations that CD in fact depends on wind speed and atmospheric stability (Liu et al., 1979; Large and Pond, 1981, 1982). The equivalent neutral drag coefficient, CN(V), is therefore commonly formulated as a function of wind speed:

CD = CD(V,) = CN(V)f(a) (2) where f(a) is a semi-empirical function of the stability parameter a (see Large and Pond, 1982). Nevertheless, the experimental measurements are always difficult to obtain and a scatter exists in most experimental results that compute CN(V), leaving considerable uncertainty as to its true values as a function of the bulk parameters.

2 In the past, even given (1), wind stress fields have been estimated using various methods and with a wide variety of drag coefficients. A difficulty has always been to obtain adequate spatial and temporal sampling of the surface winds to reliably estimate the stress. This is less a problem, but still significant, if only the long-term means are required since then all data can be composited together, but there are greater difficulties if individual monthly means are required, and interannual variability is still more problematical.

In the tropics, Luther and Harrison (1984) used Monte Carlo sampling of complete wind records to show that the 3 to 5 observations per month typically available there were insufficient for reliably assessing month-to-month variability. For wind stress, they find that at least 32 3-hourly observations are needed to reliably estimate the monthly variations. Halpern (1988a) used similar methods to analyse the records from moored buoys along the equator and found that to estimate the monthly mean wind speed with 95% confidence to within ±1 m s-1 the numbers of observations required were 10 and 8 for u and v, respectively. To reduce the errors to 0.5 m s- 1 requires about four times as many observations. Because both studies used data from the tropics where the data requirements are presumably less stringent because of the greater wind directional steadiness there, these values are probably conservative for higher latitudes. For example, at ocean weather station P (50°N 145°W) measurements are required at intervals of 2 days or less in order to estimate wind stress (Fissel et al., 1977).

Other studies have taken frequently sampled data and looked at effects of various averaging techniques on subsequent climatological stress estimates. Although monthly mean wind speeds can be used to compute the heat fluxes (Esbensen and Reynolds, 1981), unbiased wind stresses are produced only if the contributions of the wind fluctuations are somehow accounted for. Artificially inflated drag coefficients are sometimes used to partially compensate when only monthly mean wind speeds are available, for instance Hastenrath and Lamb (1977, 1978, 1979) used a CD of 2.8x10-3 (cf Fig. 1) in their computations of wind stress. Wright and Thompson (1983) derived a time-averaged form of (1) that includes both the mean wind vector and the wind variance. When vector averages are used, the empirical corrections determined by Marsden and Pond (1983) at

3 the Northern Hemisphere weather ships can be used.

By constructing wind roses with both direction and speed categories from frequently sampled weather data, Fissel et al., and Esbensen and Reynolds both produced accurate wind stresses. In the extremely data sparse high southern latitudes Hellerman (1967) employed such wind roses as published by the U.S. Navy Hydrographic Office (1955) to (1963) in several atlases. However, it is probable that these were not formed from sufficient data to allow reliable stresses to be computed. Esbensen and Reynolds show that if wind roses with only average winds for each direction are used, errors can be as large as 25%.

Bunker (1976) introduced North Atlantic results from surface fluxes based upon the full processing of individual ship observations; computations that included the transient wind components. His drag coefficient included wind speed and stability factors, see section 3. Wyrtki and Meyers (1976) similarly computed climatological surface wind stress calculations for the tropical Pacific Ocean. Hellerman and Rosenstein (1983) (henceforth H&R) published global estimates of surface wind stress based on individual ship observations using a drag coefficient that was essentially that of Bunker. More recently, Harrison (1989) similarly processed global ship data to recompute wind stresses in the same manner as H&R but used the rather different drag coefficient formulation of Large and Pond (1982). Further discussion of the different drag coefficients and their anticipated effects on the resulting stresses is given in section 3.

The purpose of the above wind stress climatologies was to obtain the long-term mean annual cycle. But even using all available data, there are some regions of the globe where there are insufficient observations, in particular, south of about 35°0 S, where H&R estimate standard errors in their mean stresses of over 0.25 dynes cm 2 . Problems in these areas are readily apparent from the lack of spatial coherence in the results. Han and Lee (1983) attempted to overcome this by using monthly mean wind and variance data plus an assumed Gaussian distribution model. In data sparse areas geostrophic winds were substituted from sea level pressure data. They were able to obtain improved spatial coverage and thus global monthly mean wind stress fields although with some questions remaining about the absolute accuracy. Again, the lack of sufficient data is much more a

4 problem when monthly mean time series of the wind stress are needed.

Further evidence for the shortcomings in currently available climatologies of wind stress over the southern oceans comes from Large and van Loon (1989) who examined the ocean circulation during the First GARP Global Experiment in 1979 using trajectories of drifting buoys and the associated wind fields. They conclude that while analyzed surface pressure fields contain basic features explaining the observed annual cycle in surface currents, wind climatologies based upon ship observations do not.

The approach in this is tostudyuseto twice-daily globally analyzed wind fields from a four-dimensional data assimilation system. This has the strong advantages of global coverage with regular 12-hour sampling, removing temporal sampling as an issue, even for individual months. The disadvantage is that results depend entirely on the veracity of the analysis system in reproducing the true wind fields. This aspect is discussed in section 2. The wind stress is computed only over the oceans using the drag coefficient formulation and method given in section 3. Areas climatologically covered with sea ice are excluded.

5 2. Data

Seven years (1980-86) of monthly mean wind stresses have been computed on a 2.5 ° x 2.5° grid based upon twice-daily 1000 mb wind analyses from the European Centre for Medium Range Weather Forecasts (ECMWF). These analyses are from the so-called WMO archive (Trenberth and Olson, 1988b) and do not include sea surface temperatures or surface fluxes.

As noted above, the analyses provide much better coverage and temporal sampling over much of the world's oceans, especially in the Southern Hemisphere (SH), than conven- tional ship data alone. Since the analysis method uses four-dimensional data assimilation, the surface wind analysis fully incesinall the sea level pressure measurements, for instance from buoys and island stations, through a sophisticated variant of the geostrophic relation. The analyses also include relevant past information that has been effectively carried forward in time using the numerical weather prediction (NWP) model and the prediction then provides the first guess for the new analysis.

An evaluation of the ECMWF analyses and intercomparisons with analyses from the U.S. National Meteorological Center (NMC) by Trenberth and Olson (1988a, b, c) have shown that the ECMWF fields are more suitable globally owing principally to better analyses over the SH and a more complete set of analyses (i.e. without the problems of missing fields and occasional corrupted fields that have plagued the NMC analyses). Nevertheless, there are day-to-day variations in the analyses from the two centers which result, for instance, in rms differences in wind speed exceeding 5 m s-1 over the Northern Hemisphere (NH) oceans in winter from 40 to 50°N and over the southern oceans south of 35°S year round. Such uncertainties could impact the surface wind stress by as much as 25%. Over the southern oceans, much of the discrepancy could be traced to problems in the NMC analyses. However, a case study (Trenberth and Olson, 1988c) of a rapidly developing low pressure system over the South Pacific Ocean in 1985 revealed that the ECMWF analyses tend to be quite conservative. The low was systematically analyzed to be slower to develop and not as deep as could verified from ships in the area, indicating that too much weight is placed on the first guess field from the NWP model. As a result, it is

6 expected that the variance of the winds over the open oceans is likely to be underestimated and this should be reflected in underestimates of the wind stress magnitude.

Other problems are apparent in the tropics. ECMWF and NMC rms differences in both pressure and wind fields were unacceptably large near the equator through 1984. Differences in the zonal mean u field exceeded 1 m s - 1, a value that can be compared with mean trade winds in the same area of ~4 m s - 1. Again part of these differences can be traced to problems at NMC. Reynolds et al. (1989) have compared near equatorial winds from NMC, ECMWF and the United Kingdom Meteorological Office global analyses with independent wind observations from six buoys in the tropical Pacific for six months in 1987. The analyzed values all agree more with each other than the real observations and the zonal winds are better analyzed than the meridional component, but none of the analyzed products was clearly superior or contained small enough differences to provide confidence in the analyses within 10 degrees of the equator. It appears that a major part of the difficulty in analyzing the winds in the tropics relates to the depiction of the divergent part of the wind. In section 4.4 we show for the ECMWF analyses that the monthly mean wind convergence near the equator fails to agree with that expected from satellite observed outgoing long wave radiation (which is an index of convective activity).

We used the 1000 mb level wind data, which is generally not expected to be the same as that at the surface. However, the manner of analysis of ship wind data at ECMWF prior to 9 September 1986 meant that the ship winds were effectively assigned to the 1000 mb level and the 1000 mb winds are considered to be the most appropriate ECMWF "surface" wind product prior to that date. This aspect is discussed in Appendix I and, as shown there, at ocean weather ship Lima (57°N 20°W) the ECMWF 1000 mb and observed wind speeds were correlated 0.87 with rms differences of 2.7 m s - 1 during the first part of 1982 (Bottger, 1982). We have assumed that the 1000 mb winds are in fact 10 m winds. Because of the methodology change in September 1986, only data up till that date have been included in the climatology compiled here.

The curl of the wind stress (section 4.2) and associated Sverdrup stream functions were computed as outlined in Appendix II.

7 3. The Drag Coefficient

The 10 m neutral drag coefficient formulation over the ocean

10 3 CN = 0.49 + 0.065V for V > 10 m s-1

=1.14 for3

=0.62 + 1.56V - 1 forV <3mss 1 is based upon Large and Pond (1982) for V > 3 m s- 1. The lowest wind speed portion is an empirical fit to Dittmer (1977) and Schacher et al. (1981) at V = 2 m s-1 merged with the Large and Pond results at V = 3 m s - 1 plus the notion that CN should tend to oo as

V - 0. In applications of this formula a lower limit on V of 1 m s-1 was set in computing

CN.

A stability dependence was also included to determine CD from (2). Spatially varying climatological mean monthly values of air-sea temperature and humidity differences were computed using the Comprehensive Ocean-Atmosphere Data Set (COADS) and varied monthly but fixed within each month and from year to year. The details and the relevant fields are presented in Appendix III. These variables, together with the ECMWF winds, were used2 in the formula in Large and Pond (1982) to give the stability parameter a at each grid point and every analysis time. At all NH weather ships, Esbensen and Reynolds (1981) found errors of less than a few percent in monthly averaged wind stress computed using monthly mean air-sea temperature and humidity differences. The air density was computed for each data point and time using the ECMWF temperature, pressure and humidity data.

Ignoring a small dependence on relative humidity, the variation in drag coefficient as a function of wind speed and air-sea temperature difference is shown in Fig. 1. The most important point from Fig. 1 is that changes in CD with wind speed, coupled with the temporal variations in stability and density, interfere with any simple relationship that might be expected linking stress to winds. Fig. 2 shows a comparison of the neutral drag

2 Monthly mean temperature and humidity differences were used because the ECMWF analyses do not include sea surface temperatures.

8 6.00

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Fig. 1. Drag coefficient (x10 3 ) as a function of wind speed (m s -~) for various sea-air temperature differences. Light solid lines, AT < 0; dark solid line AT = 0; dashed lines, AT> 0.

9 3.00

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Fig. 2. Neutral drag coefficient from different studies.

10 coefficient as a function of wind speed used in the current study versus those from several previous studies. Those by Smith and Banke (1975), Kondo (1975) and Garratt (1977) are discussed by Liu et al. (1979). Aside from the Kondo values, the others all show a similar increase in drag coefficient with wind speed but start from a different datum. The Large and Pond values are lower than most for wind speeds above 7 m s - 1.

A deceptively simple relationship using the drag coefficient is with the pseudostress P, given by

p = (PZ, PY) = V(u,v) (3) see Goldenberg and O'Brien (1981) and Servain and Legler (1986), for example. This has the apparent advantage of postponing specification of CD and has also been justified because it has been claimed that for low frequency fluctuations (periods > 10 days) CD = constant (Willebrand, 1978; Goldenberg and O'Brien, 1981). Note that IPI = V 2 . The implicit assumptions are that surface air density is reasonably constant and that an effective drag coefficient CD can then be used to convert P into r, i.e.,

PoCDP = r (4) where po is a constant density, often assigned 1.2 kg m- 3 . For individual observations CD differs from CD by the factor p/po which varies from . 0.97 at 30°C to 1.08 at 0°C. The main applications of pseudostress occur when it is averaged, but then additional complications arise. In particular, the effective drag coefficient should not be a global constant fixed in time, but should vary considerably geographically and with time of year. This aspect and other shortcomings associated with the pseudostress concept are documented by Trenberth et al. (1989), who examined the impact of the variations in drag coefficient on the resultant wind stress by computing the effective drag coefficient needed to convert the pseudostress into a stress.

The Large-Pond formulation gives drag coefficients that are considerably lower than used in most applications (e.g. Fig. 2). At wind speeds of 20 m s- 1 Bunker (1976), and Hellerman and Rosenstein (1983) use CD 2.3 x 10-3 versus 1.8 x 10- 3 for Large and Pond. In the tropics, it has been common to assume values of CD 1.5 x 10- 3 (Wyrtki

11 and Meyers, 1976; Goldenberg and O'Brien, 1981; Busalacchi and O'Brien, 1980, 1981; O'Brien and Goldenberg, 1982) or 1.4 x 10-3 (Philander et al., 1987), values that are 20 to 30% larger than those estimated by Trenberth et al.. Clearly, the selection of the drag coefficient formulation has a profound effect on the resulting wind stress climatology. Harrison (1989) consequently found his wind stresses to be 20 to 30% less than H&R owing to his use of the Large and Pond formulation versus the Bunker formulation. This difference is accounted for simply by the differences in drag coefficient. However, as shown later, we find differences with H&R to be less, apparently because of compensating effects of the different temporal and spatial sampling arising from the use of the ECMWF analyses.

12 4. Mean Annual Cycle

4.1. Monthly Mean Wind Stress

The annual mean wind stress is shown in vectorial form in Fig. 3 for the global oceans and Fig. 4 shows the same quantity but for only the tropical regions, actually ±35° latitude, with the size of the vectors quadrupled. The individual components are presented in contour form in Fig. 5. In Fig. 3 the main features that stand out are the subtropical anticyclonic gyres in the North and South Pacific, North and South Atlantic and Indian Oceans plus the very strong westerly wind dominated stresses over the Southern Oceans. In Fig. 4 the trade winds become emphasized but with an interesting small scale feature apparently disrupting the otherwise coherent pattern near the Hawaiian Islands. This feature will become clearer in the curl of the wind stress field and appears to be real. Also apparent in Fig. 4 is the convergence of the arrows in certain areas. Although the convergence in the Atlantic and western tropical Pacific is not unreasonable, the convergence south of the equator in the eastern tropical Pacific is not expected, either from cloud imagery from satellites or from comparisons with previous climatologies (e.g. O'Brien and Goldenberg, 1982; Legler and O'Brien, 1984). Further analysis in section 4d shows that this is mostly not real and results from difficulties in analyzing the divergent component of the wind field in low latitudes.

Fig. 6 presents three-month seasonal mean vectors over the global oceans and reveals the seasonality of the atmospheric circulation primarily in the NH, with the strong cyclonic circulations in the North Atlantic and North Pacific in December-February and the greatly expanded subtropical highs in the northern summer. The Indian monsoon is also apparent in June-August. Over the SH, seasonal changes in the wind stress driving the Antarctic circumpolar current appear smaller simply because the values are always large and average about 2 dynes cm - 2 for the annual mean zonal component, values much larger than found in previous climatologies. Locally, over the southern Indian Ocean, annual mean zonal wind stress values exceed 3 dynes cm - 2.

The annual cycle of the stresses exhibit several interesting characteristics. The zonally-averaged mean annual cycle of the oceanic wind stress components and magni-

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Fig. 3. Annual mean wind stress over the global oceans depicted as vectors. The arrow at bottom right corresponds to 10 dynes cm - 2.

r (ANNUAL) 0 30E 60E 90E 120E 150E 180 150W 120W 90W 60W 30W 0 90N 90N

...... ~~~~~~~~~~~~~vI. ..

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0 0

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Fig. 5. Annual mean wind stress over the global oceans for the two components. The contour interval is 0.2 dynes cm- 2 . Negative (westward or southward) values are dashed.

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Fig. 6. Mean wind stress over the oceans for c) June-August, and d) September-November seasons. The arrow at bottom right corresponds to 10 dynes cm- 2. 17 tude are shown as latitude-time sections in Fig. 7. Figures 8 and 9 present the same results but with the zonal averages confined to just the Pacific and Atlantic Oceans. The NH exhibits a strong annual cycle while the SH has a distinct semiannual cycle in the zonal component. The zonal stress is stronger in the SH (a maximum of >2 dynes cm- 2 ) than in the NH (1.35 dynes cm- 2 ), although when the meridional component is also considered in the total magnitude, the maxima are over 3 dynes cm -2 in both hemispheres. A comparison of the Pacific (Fig. 8) and Atlantic (Fig. 9) basins reveals that the maxima in the Atlantic (both NH and SH) lead those of the Pacific by approximately one month. For the total magnitude of the stress the NH annual cycle is much stronger than that in the SH and the NH Atlantic basin has a stronger maximum (4 dynes cm- 2 ) than the Pacific (3 dynes cm- 2 ). The fairly low stress values in the tropical regions (Fig. 7), approaching -0.3 dynes cm- 2 , are in a region where the analyzed winds cannot be trusted.

4.2. Monthly Mean Wind Stress Curl

The curl of the stress field (Fig. 10) provides insight into various aspects of the internal ocean dynamics, not just surface currents. If the equation of motion (including pressure gradient forces) is integrated over the depth of the ocean with some simplifying assumptions we obtain the Sverdrup equation between surface stresses and the north-south mass transport over the depth of the ocean

M = curl(r) (5) where My = fh pW vwdz and pw,,is the density of water, v, is the north-south velocity of the ocean flow, j3 is the gradient of the Coriolis parameter with latitude, and h is the depth of the ocean. Furthermore, we can define a horizontal streamfunction based upon this mass transport such that M, = therefore

=M- L curl(r)d (6) with the boundary condition that .b(xE)= 0 on the eastern boundary of ocean basins. Note in Fig. 10 how the small irregularity in the wind stress field near Hawaii becomes

18 - 2 [T. 1 (dv cm ) GLOBLOCANS (ANNUALCYCLE) t 1 ( cGLA C N ( L L 90 I .

60O

30 : {; :?iiii! i}i iiii i i!1ii i ? '.*...... _...... ' '...... "" " .. " ...... ' ok...... 0 ~:......

-30 -- '~- . l - _

...... -60 7= .

-90 i F mA i i A 0 N D

2 [Try (dy cm- ) GLOBAL OCEANS (ANNUAL CYCLE) .~~~~~~~~~I 90 -1 , , , ...... _ . · .

...... _ ...... 60 - ...... :-.....,...... ~i' . . "...... : -":.- .... ~~~~~~~...... _~~...." ~ -...... 30 -

'0 ~~~~~~~...... 0 ...... -.'---''....'.....-..'...... ':.,. -3 ...... ,·q6Z -30

-60

_ -U-cn IL- ! I F MH H i J A S 0 N D J

6) la -3 .4-) to

Months

Fig. 7: Mean annual cycle latitude-time sections of the zonally averaged wind stress a) eastward component, b) northward component, and c) magnitude averaged zonally over all the oceans in dynes cm- 2 . Negative values are stippled in a and b, and values >2 dynes cm - 2 are stippled in c. 19 C)

..] .6-i-3 St

TY I (dy cm2 ) PACIFIC OCEAN (ANNUAL CYCLE) 90 -

· ;5'- : ' ': '? : i ' """ 4' .' i . . :...... -...... 60-

...... 30 - : .. ; ...... : ...... :: : -:...... :...: . .. .-...... )(U ...... 1...... la , 0- ... .: ..:... i::::xW~iW%%~i~i~iiiii:~i~:;ii!%:i%::...... i-...... O...... -30 -30 - :: ::: ...... : .:: ....:: : :.:.. ..; ......

-60 - ' " :',':,:'...... ,, : ',:: .

-90 J F F{ M . J F{ 5 0 N 0 I

4) :: ,4.a (.-,,

Months Fig. 8: Mean annual cycle latitude-time sections of the zonally averaged wind stress a) eastward component, b) northward component, and c) magnitude averaged zonally over the Pacific in dynes cm- 2. Negative values are stippled in a and b, and values >2 dynes cm - 2 are stippled in c. 20 - I ATLANTIC OCEAN (ANNUAL CYCLE) r, 1 (dy cm-' ) I... --I --.- ---- i 90 F r . * i I I - .- ( C

.,.,,..... : -::......

~~~~~~~~~......

-30

-60

. -90 I . I rI . I -r i F N A J J RA S 0 N D J

ATC ICA -T (ANA CYCLLI - L1 a..~ r-fr"2 ~~I jju--) ATANTIC CEAN-- (NNUAL CYCLE) T- I i t c 1 - - nir .. 90

60I .425

30- :,,,,..::·.:. ::·:;::-: :-.::,:,:: :-:·:· · : '·:.::..::======. ':':' .::;::.::': ' .::::' : ::.'.;:::..:::.

...... ". . :. . "~'-~:':::::::...... 0 - H .428

-30 ,-,. : ...... -...... :::::i::::::......

-60

-90 I .I I I J-r- F 1 1A J J R 5 0 N D

-3

Months Fig. 9: Mean annual cycle latitude-time sections of the zonally averaged wind stress a) eastward component, b) northward component, and c) magnitude averaged zonally over the Atlantic Ocean in dynes cm - 2 . Negative values are stippled in a and b, and values >2 dynes cm - 2 are stippled in c.

21 CURL (dy cm- 3 X 10 9 ) ANNUAL 60W 30W 0 150W 120W 90W a 0 30E 60E 90E 120E 150E 180 AS I 9UNhtf%, 90N

60N 60N

30N 30N

0 0

30S 30S

605 60S onr 90S I 0 30E 60E 90E 120E 150E 180 150w 120W 90N 60N 30N 0

Fig. 10: Annual mean curl of the wind stress over the global oceans. The contour interval is 10 dynes cm 3 x 109 . Negative values are stippled.

22 quite pronounced, with a high positive region north of a local minimum, forming a dipole structure which is also found in the Harrison (1989) results based solely on ship winds.

Figure 11 presents the corresponding wind stress curl for the four seasons. Again, seasonal variations are strongest in the NH. The dipole feature near Hawaii is present in all seasons but weakest in winter.

4.3. Sverdrup transports

It is easier to interpret the implications of the wind stress curl through the Sverdrup mass transport. Figure 12 presents the annual mean and Fig. 13 gives the corresponding results for the four seasons, assuming implicitly that a steady state was reached for each seasonal forcing. Mass transport is parallel to contours of the streamfunction. The circulation inferred from the 4b,-field in the NH subtropics gives rise to the Kuroshio (Pacific) and Gulf Stream (Atlantic) as the return flow boundary currents 3.

Results are in general agreement with Harrison (1989) and H&R, although, as expected from the different drag coefficients, the values are slightly less than the latter. The maximum annual mean circulation is over 50 Sverdrups (1 Sverdrup = 1 x 1012 g s' 1) in the subtropical North Pacific and -25 Sverdrups in the corresponding North Atlantic. This is also less than found by Leetmaa and Bunker (1977), no doubt because of the smaller drag coefficient used. Also, the maximum for the Greenland-Iceland region is less than in the above-mentioned studies. In the SH, south of about 40°S, or 30°S in the Atlantic, the concept of a gyre circulation and the computed Sverdrup transport has less meaning, and these regions have mostly been blanked out (see Baker, 1982).

The seasonal variations in the wind stress would change the strength of the subtropical gyres substantially. To examine the total transport in the subtropical gyres we present in Fig. 14 the integrated Sverdrup transport streamfunction value at the western boundary for the Pacific and Atlantic. In the North Pacific, at 29°N, seasonal variations

3 The actual boundary currents include considerable local recirculation and are therefore much stronger and, in addition, more turbulent and complex than implied by the Sverdrup transport (see for instance Fig. 42 of Worthington, 1976, for the Gulf Stream).

23 - 3 CURL (dy cm X 109 )

0 30E 60E 90E 120E 150E 180 150N 120W 90W 60W 30W 0 90N . 90N -..'J---...... '. ~~~~~~~~~~~~~~~~~~ -~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~K..... ~~~~~~~~~~~~~~~~~~~~~~~ ...... -~~~~~~~~~...... 6ON~~~~~~~~~~~~~~~~~~~~~~~~~~ ...... 60N }

30N 30N

0 0

305 ...... 30S

60S ...... 605 DEC- FEB 90S . . .II I - ...... 90S 0 30E 60E 90E 120E I50E 180 150W 120W 90W 60W 30W 0

CURL (dy cm - 3 X 109) 0 30E 60E 90E 120E 150E 180 150W 120W 90W 60W 30W 0 ...... 90N . 90N

...... :9. ~~~r...... '¶3i.i ~~~~~~~~~~~~~~~~~~~-...... 60N ...... 60N

30N 30N

0 0

305 305

60S 60S

90S 90S 0 30E 60E 90E 120E 150E 180 150W 120W 90W 60W 30W 0

Fig. 11: Seasonal mean curl of the wind stress over the global oceans for a) December- February, and b) March-May. The contour interval is 10 dynes cm- 3 x 109 . Negative values are stippled. 24 CURL (dy cm 3 X 10 9 )

0 30E 60E 90E 120E 150E 180 150W 120N 90W 60W 30W 0 90N 90N

60N 60N

30N 30N ...... y ...

0 0

305 30S

60S 60S

90S 90S 0 .30E 60E 90E 120E 150E 180 150W 120W 90W 60W 30W 0

CURL (dy cm 3 X 10 9 ) 0 30E 60E 90E 120E 150E 180 150w 1201W 90W 60W 30W 0 ...... - . .- - I I -- 90NSON . . I . 90N

0.1 60N ..... ~ ..... ~ ~ ~ ~ ~ ~ >%.,, 60N

30N 30N

n 0 w

30S 305

60S 60S

90S 90S 0 30E 60E 90E 120E 150E 180 150W 120W 90W 60W 30W 0

Fig. 11: Seasonal mean curl of the wind stress over the global oceans for c) June- August, and d) September-November. The contour interval is 10 dynes cm- 3 x 109. Negative values are stippled.

25 's (gm s-' X 10-12) ANNUAL 90W 60W 30W 0 0 30E 60E 90E 120E 150E 180 150W 120W nurAKi 90N 'UN

...... ~~ ~~~~~ ~ ~~~~~~~~~~~ 60N 60N ... ..

...~~ ~ ~ ~ ~ ~ ~ ~ ~ ~ ~ ~ ~ ~ ~ ~ ~~~~~~~~~~~~~..... 30N 30N

...... 0 0 ...... ,...... ~ ~ ~ ......

30S 30S

60S 60S

one 90S II 0 30E 60E 90E 120E 150E 180 150NW 120W 90W 60W 30W 0

Fig. 12. Annual mean Sverdrup mass transport stream function over the global oceans. Negative values are stippled. Units are in Sverdrups.

26 is (gm s- 1 X 10-2 )

0 30E 60E 90E 120E 150E 180 150W 120W 90W 60W 30W 0 I ~~ ~ ~ ~ ~ 90N I 90N

..~~~~~~~~~~~~~~~~~~~~~~~~~~~...... 6ON 60N

3ON 3ON

0 0

305 30S

60S 605

90S 905 0 30E 60E 90E 120E 150E 180 150W 120W 90w 60W 30W 0

, s (gin s X 10-12) 0 30E 60E 90E 120E 150E 180 150W 120W 90W 60W 30W 0 90N 1 · ~~~~~~~~~~~~~~~~~~~~~~~~1 I , I ~~I I I 90N

...... , . 60N 60N d#-9X'I r

JON 30N

:-7' ·· T-''-'',, · 30N 0

305 30S

60S 60S MAR - MAY ...... 90S I w IF I I I I T I I I I I I I II I I 90S (0 30E 60E 90E 120E 150E 180 150W 120N 90W 60W 30W 0

Fig. 13. Seasonal mean Sverdrup mass transport stream function over the global oceans for a) December-February, and b) March-May. Negative values are stippled. Units are in Sverdrups.

27 is (gin s - 1 X 10-12 ) 0 30E 60E 90E 120E 150E 180 150 120W 90W 60W 30W 0 9ON - . -1 .-- . 9ON ..,-~.."' , ......

.. ~~ ~ ~ ~ ~ ~ ~ ~ ~ ~ ~ ~ . . 6ON - , "0%, 6ON

. Z' ...: ...... :, .": 4... 3ON - 3ON

...... IM 0 - 0 I

Z. -,--~... 305 - 305

605 - 605 ...... JUN: - A U G......

I I I I1 I II I I I I I I T I I I I I I I I T 1 - -T--- , I I I I I I I I I I I 90S I I I I I I I I I 90S 0 30E 60E 90E 120E ISOE 180 Isow 12OW 90W 6OW 3OW 0

-1 x 1 -12 (g m s 0 0 30E 60E 90E 120E ISOE 180 15OW 12OW 9OW 6OW 3OW 0 ...... 9ON ...... VML N 6ON

...... 3ON

......

0 0

30S

1 60S ...... 'T...... SEP NOV...... I I w I I I 90S 0 0 0 0 2E 10 8 5W 1O 0 O 0 0

Fig. 13. Seasonal mean Sverdrup mass transport stream function over the global oceans 90

-30

-60

-90 J F M R M J J R S 0 N D J

90 ., I , I I . . I 's AT WESTERN BOUNDARY OF ATLANTIC BASIN (m s-1 X 10-2) ANNUAL CYCLE 60 - ..__...... :.,...... :.....:.,::.:....:. , ...... -...... ' " .'-'-.-'-""'".

_~~~~~~~~~~~~~~~~~~~ _ 30 - -~~~~~~~~~~~~~~~~~~~~~~

.-.- .... - ~~~~~~~~.... V...... *,, P) ...... " 3-...... : ...... : ...... !i~~ii~~ii~::::::::::::.::..:...... : ~i!.. :...... :...:..;:.:::.....::..:..::::::.::...:..:..::..:::::::::::::::::::' ...... ::: :::::...:::::::::::::::: -A - ... ,...... o

,.-2 0- ! ...... I.' I..... _I .

...... :; ...... F...... ;.: ;.;.;.::::::Q:::::::::::::; ...... ; ;.::;:;:_,,; .; ...... : ...... -.::-:-:.; ...... ------...... --...... ,...... -...... ,...... ,..,,.,,.. ,, ' -- . ..v .. -30 -

-60 - , .,

-90 MI F 0 U I I 0 1; nl .JN J rl i n ,J I n u i11 u, JI Months

Fig. 14: Latitude-time section of the mean annual cycle of the integrated Sverdrup mass transport stream function at the western boundary of a) the Pacific and b) the At- lantic. Units are in Sverdrups. 29 range from over 100 to 30 Sverdrups, and in the North Atlantic, at 30°N, from over 40 to 20 Sverdrups. In the South Pacific, the subtropical gyre involving the East Australian current is always stronger than 40 Sverdrups but there is an implied southward shift in the southern summer. South of 30°S Fig. 14 has been cut off because the western boundary becomes complicated by the presence of New Zealand.

4.4. Results in the tropics

In the tropics, the divergent component of the atmospheric wind field assumes much greater importance than in higher latitudes, but tends to be exceedingly noisy on a day- by-day basis because of its link with convection, and thus is very difficult to measure and analyze reliably. In the operational analyses at major centers, the four-dimensional data assimilation schemes used to produce the atmospheric analyses have always encountered difficulty in getting the analyzed divergence field into a reasonable form. Initialization procedures are invoked to bring the pressure and wind fields into a dynamical balance that represents the slower varying Rossby modes, but not the fast gravitational modes. In the tropics, the distinction in frequency between the fast and slow modes is less clear, and the diabatic heating must be taken into account. Consequently, it is difficult to obtain a consistent divergent flow field, although the reasonableness can often be judged by comparing results with those from the simulations with the NWP model. Often there is a "spin up" to stronger divergence fields in the tropics.

Over the years, research has substantially improved the divergence field produced in this way, but with the result that there are major inhomogeneities with time. Trenberth and Olson (1988d) and Bengtsson and Shukla (1988) have documented the effects of operational changes at ECMWF with time and noted the substantial increase in the divergent winds, as analyzed, with time over the 1980-1986 period. As a consequence, the surface winds in the tropics have also been greatly affected and, as noted in section 2, are still not verifying well there when compared with observations.

To illustrate the nature of the problem as it affects the surface winds and how they have changed with time, we present the surface wind divergence from the ECMWF analyses for March to May for 1982 (Fig. 15) and 1986 (Fig. 16). Also shown for comparison are the

30 DIVERGENCE OF WIND FIELD X 106 0 30E 60E 90E 120E 150E 180 150W 120N 90W 60W 30W 0 90N 90N

...... 60N ...... 60N

1w. ''4'.' 30N 30N

··· 0 0 * / ·· ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~k" I-

305 MAR82-MAY82~~~~~~...... '~~~~~~~~~~~~~~~~~..... 30S

60S 60S

90S Ai I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I 90S I0 30E 60E 90E 120E 150E 180 150 120W 90W 60W 30W 0

TIME AVERAGED OLR (Wm 2 )

I0 30E 60E 90E 120E 150E 180 150W 120W 90W 60W 30W 0 ----- . 90N Ii , ...... iIf 90N ...... '"'··.. ······· ...... ~~~~~~~~~~~~~~~~,.. ` .... 6ON t 60N

30N 30N

0 0

30S 30S

.. ._ ..,...... 60S ...... 60S ......

AR ,,,,, - MAY ...... · :.... MAR 8 2 MAY 8 2 ...... 90S 905 0 30E 60E 90E 120E 150E 180 150W 120W 90W 60W 30W 0

Fig. 15: a) Divergence of the surface wind field from the ECMWF analyses for March- May 1982 in the tropics. The contour interval is 2x10- 6 s- 1 and negative values (convergence) are stippled. b) Mean Outgoing Longwave Radiation for March-May 1982. The contour interval is 20 W m - 2 and values less than 240 W m - 2 are stippled. 31 DIVERGENCE OF WIND FIELD X 10 6

0 30E 60E 90E--- 120E 150E 180 150W 120W 90W 60W 30W 0 90N ) L I 1 I I 1 · 1 90N

60N 60N ...... ~ ~ ~ ~ '"

30N 30N .1I

0 '.4.

I I . I. 30S 30S ...... · ......

60S 605 ...... ,...... _...... ,:...... MAR 86 MAY 86 m"%/- . 90S I .I .I .I .I IF , I , UD3 I 0 30E 60E 90E 120E 150E 180 1W 120W 90W 60W 30W 0

TIME AVERAGED OLR (Wm- 2 ) 150E SOW 120W 90W 60W 30W 0 0 30E 60E 90E 120E 180 n^L 90N 9UN

60N 60N

30N 30N

0 0

305 30S

60S 605

:::. 8 6. ."""""""""""^"""^ M A R 86 --R 8 M6 .A AYA ...... Y 86...... 90S 90S 0 30E 60E 90E 120E 150E 180 150W 120W 90W 60W 30W 0 Fig. 16: a) Divergence of the surface wind field from the ECMWF analyses for March- May 1986 in the tropics. The contour interval is 2x10 - 6 s 1 and negative values (convergence) are stippled. b) Mean Outgoing Longwave Radiation for March-May 1986, in W m - 2 . The contour interval is 20 W m - 2 and values less than 240 W m - 2 are stippled. 32 outgoing longwave radiation (OLR) fields for the same seasons. In the tropics, the latter mainly depend on the height of the cloud tops and thus are a good proxy for depicting regions of convection. We therefore expect regions of tropical surface wind convergence to correspond with low values of OLR.

In 1982 (Fig. 15) a fairly distinctive intertropical convergence zone (ITCZ) can be seen in both the Atlantic and Pacific between 5 and 15°N by the OLR values less than 240 W m- 2 in Fig. 15b. Note also the distinctive South Pacific Convergence Zone (SPCZ). In contrast, the ECMWF surface wind convergence field is much more chaotic, with most convergence south of the equator. Neither the ITCZs nor the SPCZ are well depicted.

In 1986 (Fig. 16) the same features are prominent in the OLR, but now there is a more coherent ECMWF surface wind convergence pattern that corresponds better with that expected. There still appears to be too much surface convergence south of the equator in the Pacific, although some convergence, often associated with a double ITCZ, is occasionally found. In the western Pacific, the fairly weak surface convergence is not unexpected because it is thought that much of the convergence there occurs through a much deeper layer.

Therefore while it appears that there has been some improvement with time, the surface wind field is not considered to be sufficiently reliable for wind stress calculations within the tropics.

33 5. Comparisons with Hellerman and Rosenstein

5.1. Differences in wind stress

Annual mean wind stress from both ECMWF and H&R along with the vector differences are shown in Fig. 17. Differences in the eastward and northward components and the wind stress curl are given in Fig. 18. Immediately apparent are the huge differences over the southern oceans and in the North Atlantic and North Pacific. Over the Southern Oceans differences were expected because of the scanty and inadequate sampling there in the H&R record, but the magnitude of the differences is nevertheless surprising. The large differences in the North Atlantic and North Pacific are quite unexpected however, because sampling is not a problem there. Moreover, the very distinctive pattern to the differences there is worth examining further. Before doing this, we first present the differences and their seasonal variations in more detail.

Because the wind stress depends on the wind speed raised to more than a power of 2, annual mean results tend to reflect those of the winter half year. Figures 19 and 20 show the total fields and their differences for January and July. In January, note the much stronger southerly component over the eastern North Pacific and North Atlantic. In July (Fig. 20) these differences are much less, although they are still from the southwest in the North Atlantic. The southwest monsoon is weaker and the southern westerlies much stronger in the ECMWF versus the H&R fields.

Some idea of the annual cycle of the differences can be gained from time sections of the annual cycle of zonal averages across all the oceans (Fig. 21) and from Fig. 22, which shows the annual, January and July zonal averages from ECMWF and H&R together. Dif- ferences turn out to be somewhat systematic so that the January and July maps are fairly representative of those seasons. Over the Southern Oceans differences exceed 1 dyne cm - 2 in the winter half year and stresses are 70% stronger in the ECMWF results. Elsewhere, however, the zonal average differences of the eastward component (see Fig. 21) are in fact remarkably small over most of the oceans, with the ECMWF stresses slightly smaller. This shows that in spite of the expected reduction in wind stress due to the use of a drag coefficient that is about 25% smaller, the added variance captured by the ECMWF analyses has

34 TECMWF (ANNUAL) 0 30E 60E 90E 120E 150E 180 15OW 120W 90W 60W 30 0 90N......

,90N. ----- _------.->...... , e3

' \~~~s ;>;~~~ . "**'':-'~..^ 'r~ -t '.. __ ** *. .. * II '

: r ; ; ; c i;; ^- O^ -' SON ^,; * . . ~., .., *... V?^ ^ t .s . .4 . .*. -..;; ;,: ^...... ·:: ...... :...... ON605 -- --...... -- -,- -- 60 60N

? 0 " .*. . ..-* ...... ------' .. .. .t_...... y ...... , ' ..- -

^ > ; ,. -"... |,.-^ :" M U^ ^UUU~~~~~~~~~~~j·. .'»,

- ...... ' **... *'...... ' " . . .'.'' ..... ,,...... ''-.. *-....."" ...... 90S\. . v ...... ^ , ^ _ _ _ _ _ ._ _. v. v, v. s. \,. . -^ . , s. , ...... X...... ^ v 0 30E 60E 90E 120E 150E 180 150W 120W 90M 60W 3OW 0

TH&R (ANNUAL) 0 30E 60E 90E 120E 150E 180 150W 120W 90W 60W 30W 0

9...... 60N ::"."' :... , 60N ,,..' ' ' :>. '.,1::'~.'..., ..

~.. %... K ... --- --.- -. --.- . .. .- .-

30 '30N '"\...60N ..a... |.'' ,' . " "... ~L**r. ''..- C-...... : :. :^..-0 ...... N 90S::::::.. *.* .. : . * . , . * ,, .....- 90S ,.,"* " " ' ' " :-" ' " ' " * ** :. : . ^ _ ,... . , ...... ^...... --*** 0 30E 60E 90E 120E 150E . 180...... 15W 12W 9W W 0 ...... 0... 30S605 .--- ' "',, ::: ...... 0... .::E.80.50W:::::::::::: .... .120W.90W..6W 30 60S

905 ...... S

T H&R (ANNUAL) 'TI:'CMdWfTECMWF - 'T'HR-- (ANNUAL) 0 30E[ 60E 90E I120E 1506 1801501 120w 9 60W 3 0 90N YUN

...... C . it C C - C I . 60N 60N

30N 30N h'.~~~~~~~~~~...... - ... .-

0 - ...... 0

C J,.7. 7 '...... % 30S 305

60S 60S ...... ,...

90S 90S5/!s I r4r rnr nrn mr I rri IAn *u lv)nu Cnu Cgnu AU A U JUt Oult YU 1 CUt 1 IU1 OOU - IDU 1 U V" Dv/un au" u

Fig. 17: Annual mean wind stress over the global oceans depicted as vectors from a) ECMWF b) H&R; the arrow at bottom right corresponds to 10 dynes cm- 2 , and c) differences depicted as vectors. The arrow at bottom right represents 5 dynes cm - 2. 35 2 TX (ECMWF) - Tx (H&R) (dy cm ) ANNUAL 90E 120E 150E 180 150W 120W 90W 60W 30W 0 0 30E 60E 90N 90N

60N 60N ":,. . · ...... ,,r"., . " . . ." . -. . . . C. 30N 30N : '" ... -:'-

0 0

30S 305

Hill# -Car"- 60S 60S

905 905 ,1 "__ ...... --..-- I .0 30E 60E 90E 120E 150E 180180 150W, , 120W 90W90 , 60W , 30W 0

m 2 Ty (ECMWF) - Ty (H&R) (dy c ) ANNUAL 120E 150E 180 150W 120W 90W 60W 30W C) 0 30E 60E 90E ...... 90N 90N

- 60N 60NI

30N 30N ...... 0 0

305 305 I -C~~~~~~~~~~~~~~~~~~~~~~~~~- 605I 60S

- - ...... , , I . . I .r- 905 905 i 1 I I I . I ~I ~ ~ ·~ I ~ . I . I I I I I I I . . I Ai 'AF OnF 12AF I'AFS iR I Sow 120W 9OW 6OW 30W u JJ=. .·..&». ~AF Ul- ZUL a1uV A· V v--. . --. --..

- 3 9 CURLECMWF - CURLH&R (dy cm X 10 ) ANNUAL 0 30E 60E 90E 120E 150E 180 150WSO120W 90W 60W 30W 0 ...... ^ Q9NI...... 90N ...... ;. . ...': i# :.m .-..' I-"-. I

60N 60N

30N 30N

...... -~~~~~~~~ 0 ~~~~~?r~~~~~~~~~~~~' 0

30S 30S

...... 60S I60S

I . . . . q_ 19I onA(I ------. - ...... I...... I .. . I ...... j %r j 3:UO 1 ., , 0 30E 60E 90E 120E 15OE 180 150W 120W 90W 60W 30W 0

Fig. 18: Differences in the annual mean wind stress over the global oceans between the current study and H&R, a) eastward and b) northward components; the contour interval is 0.2 dynes cm - 2 and, c) differences in the annual mean curl of the wind stress The contour interval is 5 dynes cm- 3 x 109 and the zero line is omitted.

36 TECMWF 0 30E 60E 90E 120E 150E 180 150W 120W 90W 60W 30W 0 90N 90N

60N 60N

30N 30N

0 0

305 ~. ~~ ~ ~ ~ ~ ., ...... 30S

60S 60S

JAN . 90S IOIn - - . . . I . . . I . . . I . I . . I ...... I . I I . I I 30E 60E 90E 120E 150E 180 150W 120W 90W 60W 30W 0 ------.-- . --.. .------.. --..

T H&R 0 30E 60E 90E 120E 150E 180 150W 120W 90W 60W 30W 9ON 90N

60N 60N

*,%..~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 30N 30N ,.d,~ ~~ ~ ~ ...... - 0 *0

*..,~~~~~-. .- ...... ______: 2~~~~~~~. 30S 305

60S .-.-.---...... -...--.-..-~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~...... 605

JAN. * 90S 905 ( 30E 60E 90E 120E 150E 180 150W 120W 90W 60W 30W 0

TECMWF - TH&R

A 24AF AM apAflr i n i.w an r-nu. fu nu CL M IL JVC Out !jut IzUt I IJt I Ou I WN I MMV UIJM bU1 31 U I --.. n^k ------.------. .. *~* ...... 90N

60N 60N

30N 30N .~~~~~~~~~~~~~~~~~~~~0.

I..~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 0 *0

305 30S

60S 60S ...-.~~~~~~~.-....-----...-~~ ~ ~~ ~~ ~ ~~ ~ ~ ~ ~ ~ ~ ~ ~...... '4 *I I ' - JAN --- I I 90S . . . . I . I . . I . . . . . . . . I . . I I I . . I . . . . :;Z4 I90S % 12fir c /%C ftrl . N^rl .rl^rl . ^^ .- . . --. . --. . --. . --. . U 3Ut GE 90E~U 120EJ A SOEU lU8 15UW 12OW 9OW 6OW 30W 0

Fig. 19: January mean wind stress over the global oceans depicted as vectors from a) ECMWF and b) H&R. The arrow at bottom right corresponds to 10 dynes cm 2. c) Differences in the January mean wind stress over the global oceans between the current study and H&R, depicted as vectors. The arrow at bottom right represents 5 dynes cmc- 22. 37 T ECMWF

60E 90E 120E 150E 180 150W 120 90W .0.0 60W.0 .0 30W 0 0 30E ...... t'ifNLI ' ' ' '. . '.. ' 90N 3lUNI ------

...... I. ...I. -.. . .4- 60NW 60N

30N 30N 4 4..4''4~ ~ '.4i: ~ ~ ..· l.444· ~

4 . -.'-...... -..---.. - 0 0- · cl ...... 5 9 r~~~~~~~~~~...... JUL~~~~~~~~~~~~~~~~~~~ %% ...... 305 30S 4. ~ ~~~~~~~~~~~~~~.I - ·4· -· 4L- .---. - - - -'- - '4 _ _ _ .-- .- --4 .4- - .4- 60S ______60S

___ crn< ------. I ·. . . 905 ~I ~ ~ I =vw~ C 30E 60E 90E 120E 150E 180 150W 120W 90W 60W 3OW 0

'H&R

0 30E 60E 90E 120E 150E 180 150W 120W 90W 60W 30W 0 90N 90N *90N. , - ...,, ...... - ...... r , | 'f. ;...... '-..

.. N .. . ;., . · ...... ; 6-.-0N-.·

,k < ^S^. 4 , ,. 6. 0 :''S ...... -...... , , : · ., ... 60N ; 30S ...... … " . .. :' ......

I- - 60 5 ' -.. .. :*...""...'...... - F,,-'. ' : ...... 605...... 30' , ...... '"' . . . --. ..-. . . . "" ' ' ' 30S ...... 'W Y I ...... ' ...... JUL ,. JUL...... , ,,, x- or3&2E. ,0 8.~ ,. ~000 0 TE-~ r·.~)?irrr-- "tHO R .~~~~CMW 4· \\

0 30E 60E 90E 120E 150E 180 150W 120W 90W 60W 3OW 0

T ECMWF - TH&R 180 150W 120W 90W 60W 30W 0 0 30E 60E 90E 120E 150E I -pl. 9ON 90N 4·· .L.:.."' ...... ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~...... - ...... 4 60N 60N ...... i-i.ui I~1L~i?. ~~~~~~· -555 '"" ""~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~.0A 30N 30N

0 0

4 . 4 . * ~'d.4.4 4. F . 4 . . 4 ...... 305 30S

60S 60S

4 J U L ...... Qcq .I ...... I . -1 I . - . . I- . . . I . . ;:31U ...... I . I I I - I . -.- I I . . . . . 90u 0 30E 60E 90E 120E 150E 180 150W 120W 90W 60W 30W 0 Fig. 20: July mean wind stress over the global oceans depicted as vectors from a) ECMWF and b) H&R. The arrow at bottom right represents 10 dynes cm- 2. c) Differences in the July mean wind stress over the global oceans between the current study and H&R, depicted as vectors. The bottom right arrow represents 5 dynes cm- 2 38 [TX ]ECMWF - [Tx ]H&R (dy cm-2 )

GLOBAL OCEANS (ANNUAL CYCT.RE - 90 IL ft I I I

...... _,"- : :~...... _.,.'.'~~ iii.':::-: ,, ,'::...:.' 60 r :::::::::::::::::~ : _._...... _..· ·...... ".":,,,',',, .272 30

L .000 .-_ a) (0 H CI· i ' i: ::::. !.:.::::-; .' ....''.o. -30 -e- .031

-60

-90 -~ I I II - I r · rU · · --- r I I I I I I I J M F M J J R S 0 N O J Months

Fig. 21: Latitude-time sections for the mean annual cycle differences in zonal mean wind stress eastward component over the global oceans. Negative values are stippled. The contour interval is 0.25 dynes cm 2.

39 3.00

2.50

2.00

1.50

cv E 1.00

C 0.50 O.0 0.00

-0.50

-1.00

-1.50

3.00

2.50

2.00

1.50

c 1.00

C 0.50 - I0 0.00

-0.50

-1.00

-1.50

3.00

2.50

2.00

1.50

E 1.00

C 0.50

0.00

-0.50

-1.00

-1.50 I LATITUDE

Fig. 22: Zonal mean annual eastward component of the wind stress over the global oceans for ECMWF (solid) and H&R (dashed); a) annual, b) January, and c) July.

40 evidently compensated to some extent. However, in the NH, the differences are primarily in the meridional wind stress component and are mostly confined to the winter half year.

To emphasize the differences at certain locations, Figs. 23 and 24 present the mean annual cycles from the ECMWF and H&R climatologies at 90°E 50°S in the southern Indian Ocean, 150°E 55°S south of Tasmania, and 100°W 45°S west of Chile, all in Fig. 23, and 155°W 45°N in the North Pacific, 45 0 W 50°N in the North Atlantic, and 150 0E 45°N just east of Japan in Fig. 24. In the southern Indian Ocean the differences reside in the westerly component with the ECMWF stress almost double that of H&R. Those differences are also seen south of Tasmania, although somewhat less in summer, but now with a much stronger northerly component to the ECMWF stresses. West of Chile, differences are greatest in the meridional stress component. Substantial differences are evident in both components throughout the year in the North Pacific but it is mainly the meridional component in the North Atlantic from December through July that large differences exist. Off Japan, the differences are mainly in winter in the eastward component, and may be related to the stability factor in the drag coefficient. The sea-air temperature differences are large (Appendix III) and act to increase the drag coefficient at that time of year. However, H&R also included a stability dependence in their computations.

These differences have implications for the associated oceanic circulation, as can be seen from the differences in the Sverdrup mass transport streamfunction, shown in Fig. 25 for the annual mean. Here the mass transport has been computed from the curl in the wind stress and is defined such that positive values indicate stronger subtropical gyres in the NH. The H&R Sverdrup transports have been computed from the wind stresses using identical procedures to those used for the ECMWF data. The differences in Fig. 25 indicate a stronger Kuroshio current off Japan and a stronger Gulf Stream in the Atlantic. The ECMWF fields also give a stronger subpolar gyre in the North Pacific, and a very different transport south of 40°S.

Figures 26 and 27 present the integrated Sverdrup streamfunction values at the western boundary for the Pacific and Atlantic as direct measures of the differences in the strength of the gyres. As seen from Fig. 25, because differences are larger away from the

41 90.00 LONG, -50.0 LAT I 5.00 . I I I I .1 I I I L 4.50 TZ tgcuvrl 4.00 TV (UNWIP 3.50 3.00 Tg IS&*,~~~~~~ TV 2.50 N 2.00 10~~~~~~ E 1.50 1.00 > 0.50

0.00 - · -0.50 -1.00 -1.50 -2.00

-2.50 IEB R I~~~~~~I I I I I I I JFN FEB APR ..MA r -JUAN JLJUL AlUJ r. Dxrc;FP OCT NOv DC Ji

150.00 LONG, -55.0° LAT 5.00 T 4.50 - YVX I I(.Mor) 4.00 . . r...x.. m.) .. . .( 3.50 3.00 2.50 -2.00 E 1.50 1.00 0 - .50 0.00 -0.50 -1.00 ~.~.-.~----.-..~ `.~.... -.~~~-·~.~-~ ~~`/. -1.50 -2.00 -2.50 i I I I I I I I I I t N FEB MR APR HAY JUN JUL RUG 5EP On17 Nv rr Au

-100.0° LONG, -45.0 LAT I I I I 5.00 iI I -- . I . --- . ----I 4.50 T1Iy (W...)(WNW?) 4.00 TX (EkE) 3.50 3.00 2.50 " 2.00 Kxt~r E 1.50 1.00 S 0.50 rrrK 0.00 -0.50 -1.00 -1.50 -2.00

-2.50 I I- . I I I I I I I I cmU Fo m v o ul&I LiH. _r _r . " . ._- ___ . Jr r o" Fto r rn mir JUN JUL HU, SE OCU NOV ULE JRN MONTHS Fig. 23: Annual cycle of mean wind stress components from ECMWF (solid) and H&R (dashed) at selected SH locations; a) at 90 0E 500 S in the southern Indian Ocean; b) at 150°E 55°S south of Tasmania; and c) 1000 W 450 S in the South Pacific Ocean. 42 -155.0° LONG, 45.0° LAT 5.00 4.50 4.00 3.50 3.00 2.50

NI 2.00 E 1.50 1.00 > 0.50 0.00 -0.50 -1.00 -1.50 -2.00 -2.50 FEB MAR PR MAY JUN JUL AUG SEP OCT NOV DEC

-45.0° LONG, 50.0° LAT 5.00 4.50 4.00 3.50 3.00 2.50

Nf 2.00 E i.so1.50 C) 1.00 , 0.50 0.00 -0.50 -1.00 -1.50 -2.00 -2.50 FEB MAR APR MAH JUN JUL RUG SEP OCT NOV DEC

0 150.00 LONG, 45.0 LAT 5.00 I I I i . A I. I

' tl uC 4.50 1 r)

4.00 ...... T,r (*I)) *** - (&S| 3.50 3.00 2.50

N 2.00 E 1.50

C) 1.00 · > 0.50 0.00 I~~~~~~~~~~~~~~ I -0.50

-1.00 I I I I I I I - . I~~~~r -1.50s I -2.00 -2.50 . I I -- - I I rn.ott Unt W n M JUN JUL HUl 5P OC NOV OEC JAN MONTHS Fig. 24: Annual cycle of mean wind stress components from ECMWF (solid) and H&R (dashed) at selected NH locations; a) at 155°W 45°N in the North Pacific Ocean; b) at 45°W 50°N in the North Atlantic; and c) 150°E 45°N near northern Japan. 43 1 'S (ECMWF) (gm s- X 10-12) ANNUAL 0 30E 60E 90E 120E 150E 180 15OW 120W 90W 60W 30W 0 nfAl 90N SUNI, .. .. .

··''--· , 'r·'·~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~-.. ,5, 60NSON 60N

30N 30N

0 0

305 305

605 605

otc; iVJ 90S kF 0 30E 60E 90E 120E 150E 180 150W 120W 90W 60W 30w U

- l +S (H&R) (gm s X 10-12) ANNUAL 150E 180 150W 120W 90W 60W 30W 0 0 30E 60E 90E 120E ...... hA', ·. . ·.. -. . . . . -. -. . --. . - .- . . .- 1UiN SinnLiJNI - "' """''ii .. '1·b, I .--r.,.....=···T· .. '.·r ·- ... ··- ...,·· -... " I=;\ ·· LI: d, ·'· *' : 60N )N,%&I

3( 30N N 0 0

30S OS

6(3S 60S

90S 905 0 30E 60E 90E 120E 150E 180 150w 120W 90w 60O 30Jw J

1 'S (ECMWF) - s5 (H&R) (gn s- X 10-12) ANNUAL 0 30E 60E 90E-- 120E 150E 180 1SOW 120W 90W 60W 30W 0 f%^&. ------UON. v90N r~~~~~~~~~~~~~~~~~~~~~~~~~hi

A... 60N 60N

...... 30N ;c~~~t·-· ~ ~ ~ '' ':-·'9'..;*-··(.121'·.~~~~~~~~~~~~~:1...... 30N

...... -.. 0 .. `~ "~~~~~r' ~~*2: ...... ·..r ·1-:1.· ·...kv I 0 ......

...... I 30S 30S

60S 60S

.... ,...- .- ...... I I . . . . tU3 ------. 90S . % r!,^t q IAI n1 .anE iru I 3Or I Ar---nr -- Ir.---"I IcnLc. --- sulAnrl' 1 i8 /1nI 11 ll l Ih,w UI Jut bDt %ut I z t Z)Ut IO I 53'V 5 Ir =%M UV" liv %I) Fig. 25. Annual mean Sverdrup mass transport stream function over the global oceans from a) the current study and b) H&R. Negative values are stippled. Contour interval is 10 Sverdrups. c) Difference between the two studies. Negative values are dashed. The contour interval is 5 Sverdrups. 44 - 2 *s AT WESTERN BOUNDARY OF PACIFIC BASIN (cm s' X 10 ) 100 . . . . , . . , ...... (ECIcwF) ANNUAL 80 --- + (HR)

40 CV) 0.4 20

0 U) w -20

-40

-60

-80

-100 90 60 30 0 -30 01.4 -60 -90

100

40 U) 20

co 0 WU) 04 -20

-40

-60

-80

-100

10C

6C60

40 U)

U) W 9=) -20

-40

-60

-80

-100

LATITUDE

Fig. 26: Meridional profiles of Sverdrup mass transport stream function along the western boundary of the Pacific for a) annual, b) January and, c) July. 45 1 2 +s AT WESTERN BOUNDARY OF ATLANTIC BASIN (im s- X 10-' ) 10(

C. 2C :D 3: a ( 1t: > -2C C/) -4q

-60

-80

-100

100

cn CL 20

o 0

> -20 Cf) -40

-60

-80

-100

10(

U) 0, 2C

C -

U) -40

-60

-80

-100

LATITUDE Fig. 27: Meridional profiles of Sverdrup mass transport stream function along the western boundary of the Atlantic for a) annual, b) January and, c) July. 46 coast, these are not the best measure. However they do show a remarkable resemblance overall, although with biggest differences from 40-50°N in the North Pacific subpolar cyclonic gyre involving the Oyashio current.

5.2. Changes in the atmospheric circulation

To further investigate the differences in the North Atlantic and North Pacific we use sea level pressure (SLP) fields. For SLP monthly mean fields based on daily historical analyses dating from 1899 are available. Discussion of the quality and problems with this set is given by Trenberth and Paolino (1980). The worst problems occur before 1924 and there are big discontinuities over high orography owing to changes with time in procedures to correct surface pressures to sea level.

A comparison has therefore been made between the SLP fields for the 1980-86 period versus means of the 1945-1977 (Figs. 28 and 29) or 1924-1977 (Fig. 30) periods, which were taken as possibly representative of the period of ship data going into the H&R analyses. Both of these reveal a statistically significant change in the atmospheric circulation over the oceans. Statistical significance was tested using a t test based upon the monthly standard deviations within each data set. Both Figs. 29 and 30 show the same pattern, with pressures 7 to 9 mb lower in the Aleutian low and about 6 mb higher in the North Atlantic in the recent seven year period for January. Both the changes in SLPs and in surface wind stress are consistent with what would be expected from the geostrophic relation.

The other large and statistically significant changes in SLP over land mostly signal the changes in procedure associated with corrections to sea level, and should be ignored.

The changes in SLP are remarkably consistent from November through March. In the North Pacific, maximum differences lie from 40 to 50N of -4.5, -6.2, -8.9, -7.5, and -7.9 mb in November to March, respectively. The pattern is more varied in the North Atlantic. The overall difference averaged from November through March is shown in Fig. 31. This serves to emphasize the deeper, by -5 mb, and more extensive Aleutian low but with a now fairly indistinct pattern in the North Atlantic. The annual mean SLP differences (not shown) continue to show pressures lower in the Pacific (with high statistical significance)

47 SLPCcumw (1980-1986) JAN

180 I

SLPaCMIA (1945-1977)

I I

Fig. 28: Mean sea level pressures for January a) 1980-86 and b) 1945-77 in mb (minus 1000 mb). 48 SLPccuMr - SLPAaCu.vc 1977 1986

ASLP (NORMALIZED)

Fig. 29: Differences in mean sea level pressures for January from 1980-86 versus 1945-77 a) total in mb, negative values are stippled; and b) t values, based on the monthly mean standard deviation, magnitudes greater than 2 are stippled and are statistically significant at about the 5% level. 49 SLPECMWF - SLPARCHIVE 1977 1986

ASLP (NORMALIZED)

Fig. 30: Differences in mean sea level pressures for January from 1980-86 versus 1924-77 a) total in mb, negative values are stippled; and b) t values, based on the monthly mean standard deviation, magnitudes greater than 2 are stippled and are statistically significant at about the 5% level. 50 SLPEcMwF - SLPARCHIVE 1977 1986

ASLP (NORMALIZED) 1977 1986

180

Fig. 31: Differences in mean sea level pressures for Nov-Mar from 1980-86 versus 1945-77 a) total in mb, negative values are stippled; and b) t values, based on the monthly mean standard deviation, magnitudes greater than 2 are stippled and are statistically significant at about the 5% level. 51 and the departures are about one annual standard deviation (-2.2 mb) below normal, but the pattern in the Atlantic is indistinct.

Of course the apparent consistency of the changes in SLP raise the question of whether they might simply be due to increased data and more sophisticated analysis techniques in recent years. We have performed similar analyses with the NMC products with the same results. Nevertheless, we suspect that some, but not all, of the differences may be accounted for by the different methods and data. Further evidence for the reality of the differences is the essentially independent but consistent change in the wind stress field. Note that because of the nonlinear nature of the surface stress, the changes in wind in the winter half year, as indicated geostrophically by the gradient in SLP, dominate the annual wind stress changes.

Further evidence to be factored into the apparent change in circulation comes from independent surface temperature analyses which show both the North Pacific and North Atlantic annual mean values to be persistently anomalously low in recent years (Jones et al., 1988), see Fig. 32. Over the oceans the surface temperatures have been replaced with SSTs. Of interest are the changes in surface temperatures and how they relate to what would be expected from changes in temperature advection, and perhaps vertical mixing over the oceans, by the anomalous winds.

Results from all three data sets are essentially based upon independent data and methods of analysis, and provide especially strong evidence that the Aleutian low is significantly deeper and extends farther east in the recent period. The pattern of change of SSTs is consistent. The general pattern around the North Pacific basin, notably the warming trend along western North America and the strong cooling between Japan and 160°W in mid-latitudes is consistent with the expected anomalous advection patterns associated with the change in circulation (see van Loon and Williams, 1976; 1977). In addition, increased mixing in the ocean and stronger heat fluxes into the atmosphere would help account for the recent persistently cold SSTs in the North Pacific.

52 TEMPERATURE CHANGE (1980- 1986)-(1945-1977) °C

0 180

Fig. 32: Change in annual mean surface temperatures (°C) 1980-86 minus 1945-77 over the NH. The contour interval is 0.25°C, values greater than 0.250°C are stippled and less than -0.25°C are hatched. (Courtesy of P. D. Jones).

53 Further investigation shows that the deeper Aleutian low regime extends from 1977 to 1988, a period when there were three El Ninio (warm) events in the tropical Pacific but no compensating La Ninia (cold) events, so that the tropical Pacific has experienced above normal sea surface temperatures. Modeling studies (e.g. Blackmon et al., 1983) confirm the teleconnection link between sea surface temperatures in the tropics and the North Pacific circulation. But the results obtained here are not simply due to the 1982-83 and 1986-87 El Ninos; the Aleutian low was also much deeper than normal in the winter of 1980-81. The possible role of teleconnections from the tropical Indian Ocean and Asia, and the influence of circulation changes near the Himalayan-Tibetan Plateau complex, which are also known to affect the Aleutian low, need to be explored to fully establish the reasons for the circulation changes.

In the North Atlantic, although there has been an increased southerly component to the wind stress in recent years, the pattern of change in SLP and thus in the winds themselves varies sufficiently from month to month that changes in advection are not a factor for the annual mean. Overall, the changes in circulation do not explain the apparent cooling trend in the North Atlantic area.

54 6. Interannual variations

Latitude-time series of the monthly mean zonally-averaged eastward component of the stress, both total and anomalies, are given in Fig. 33 for the total oceans. Fig. 34 presents the zonally-averaged northward stress, the stress magnitude, and the vertically integrated Sverdrup transport (see Eq. 5) My. The latter is the average Sverdrup transport, and is related to the maximum streamfunction on the western side of the ocean but is normalized by the distance across the ocean. Corresponding values for the Pacific and Atlantic are given in Figs. 35 and 36, and 37 and 38, respectively, except My is replaced by the value of pt/ at the western boundary, as a direct measure of the strength of the forcing of the individual ocean gyres.

The most striking feature shows up in the eastward stress component time series (Fig. 33) which reveals the maxima associated with the El Nino events of 1982-1983 and 1986-1987, although these are much more distinctive in zonal averages over the Pacific basin (Fig. 35). A much deeper Aleutian low pressure system in the northern winter of 1982-83 would have resulted in a much stronger Kuroshio current across the Pacific (Fig. 36c). Also, there was a reversal of the tropical Pacific easterlies during the 1982-83 El Ninio event.

However, largest wind stress anomalies, exceeding 2 dynes cm-2, are seen in the North Atlantic (Figs. 37 and 38), and apparently arise from big changes in the strength of the eastward stress as well as meridional displacements in the region of strongest values. The wind stresses experienced in the northern winters of 1981-82 and 1984-85 were notice- ably weaker, both in the eastward component and the total magnitude. Variations in the Icelandic low, often associated with the North Atlantic Oscillation, are the main source of this variability.

Although interannual variations over the Southern Oceans do not appear to be as large, they cover a much greater extent in the zonal average; the presentation in Figs. 33 to 38 tend to exaggerate the variations over the oceans of smaller east-west extent. Therefore, to examine the interannual variations without zonal averaging, we have selected meridions

55 90

O0 .4-

-30

-60

-90

0O ._. 0

-30

-60

-90

Months Fig. 33: Latitude-time sections of the monthly mean wind stress from 1980-86 eastward component zonally averaged for the global oceans; a) total, contour 0.5 dynes cm - 2, and b) departures from the mean annual cycle, contour 0.25 dynes cm- 2. Negative values are stippled. 56 I 7W. 1 ,4, - -2 .1TY j1 uy cm - ) GLOBAL OCEANS

I1k. c- )

......

-O

H H H ...... ~·::- ~·:-::· . .ff~·..·. ... - ·. : . .:. .·:.-:... ·- ·. . :·; · :~:: : -30 .370 .H08 ...... q8 :: :':.509 :: .521 3 0 __ +< 7

-60 -

-90- .-... ioauOsAn Iroio9 192i 1983 1984 1985 1986

r_ 1 i, -

CO la 0

tz -3-.4

CO 10

tt -3-.4

Months Fig. 34: Latitude-time sections of the monthly mean wind stress from 1980-86 for the global oceans zonally averaged: a) northward component; negative values are stippled, b) wind stress magnitude; magnitudes greater than 2 are stippled; contour 0.5 dynes cm 2 and, c) monthly mean zonally averaged Sverdrup mass transport; negative values are stippled and contour of 50 g cm- 1 s - x 10- 3 .

57 90

()

-30

-60

-90

-.- 0

-30

-60

-90 1980 1981 1982 1983 1984 1985 1986 Months Fig. 35: Latitude-time sections of the monthly mean wind stress from 1980-86 eastward component zonally averaged for the Pacific Ocean; a) total, contour 0.5 dynes cm - 2, and b) departures from the mean annual cycle, contour 0.25 dynes cm - 2. Negative values are stippled. 58 [Ty ] (dy cm- ) PACIFIC OCEAN , . 2 ------ORAN----- ·· 90 (dy cm I . . . I ...... PACIFIC I-L

... . 7 ·. r 60 o yn) o ) ' c

30 ...... 35 ......

.a 0

.-1 :::'::::::::::::'::'::.::::': ..: :;::::::: ::::::::: ::::::::::::::::'7:::::::-~:: '. :.. ::. :::"; '..: . *315...... 479 ...... 413 -30

...... :...... ; ...... -60 -

-90 . . I I I I I I I I I I I I I I I --- . . I . . I I . . I I 1- 1980 1981 1982 1983 1984 1985 1986

-30

-60

-90

1980 1981 1982 1983 1984 1985 1986 Months Fig. 36: Latitude-time sections of the monthly mean wind stress from 1980-86 for the Pacific Ocean zonally averaged: a) northward component; negative values are stippled, b) wind stress magnitude; magnitudes greater than 2 are stippled; contour 0.5 dynes 2 cm and, c) monthly mean integrated Sverdrup mass transport stream function along the western boundary; negative values are stippled and contour of 20 Sverdrups. 59 TX ] (dy cm-2 ) 90

0) "o *f,= ,--. CQ

-30

-60

-90

O .-.(o3 -30

-30

-60

-90

Months

Fig. 37: Latitude-time sections of the monthly mean wind stress from 1980-86 eastward component zonally averaged for the Atlantic Ocean; a) total, contour 0.5 dynes - 2 cm , and b) departures from the mean annual cycle, contour 0.25 dynes cm - 2 . Nega- tive values are stippled. 60 2 T'., J.i N.(dy cm-.... )I ..ATIANTIC I. _.,..` _ OCEAN__ 90 4.- . 1 (d .... m ... ~ - ATLNTI ACFAN--I-L

H H 447 .440 .9...... 494 ...... 483 .... -30 - ...... i : lllM^^^^^^^^^^ ...... , .': ^ .- .' A. .. .."".44^...... ' ' ' .48 A:' i'-;i : . :1:: : : T ~ ...... ::. r' ...... C·...... :::::::.... -^ · -60 ^--': .i.. ..ii.jpp ..

-o_ I I . -- i -9ll) I . . I . I . g I' · · · · · · I I ·-* - - -T 1980 1981 1982 1983 1984 1985 1986 .

-6--3

90 *s AT WESTERN BOUNDARY OF ATLANTIC BASIN (gimn ' X 10-O)

','I ' Zu2HK ., 0

30 - ...... ,.,,L,,,'ts ......

...... 0- ...... ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~·:::~f··

...... :if~f:~ ~ -· -30 -

-60 -

-go 4 - - 1980 1981 1982 1983 1984 1985 1986 Months

Fig. 38: Latitude-time sections of the monthly mean wind stress from 1980-86 for the Atlantic ocean zonally averaged: a) northward component; negative values are stippled, b) wind stress magnitude; magnitudes greater than 2 are stippled; contour 0.5 dynes cm- 2 and, c) monthly mean integrated Sverdrup mass transport stream function along the western boundary; negative values are stippled and contour of 20 Sverdrups.

61 in the center of the two major oceans. Figs. 39 and 40 present latitude-time cross sections along 150°W, down the Pacific Ocean, and 35°W, down the Atlantic. Shown are the two stress components, the magnitude, and the Sverdrup transport, My, at that longtitude.

In the Pacific, the 1982-83 northern winter anomaly again is prominent in the north, but enormous variations are seen in the South Pacific too. At 55 0S, the eastward wind stress values commonly exceed 2 dynes cm - 2 , but reverse in 1986 to about -1 dynes cm - 2 , probably in association with a major blocking event. In addition, the meridional stress was especially strong (<-2 dynes cm- 2 ) in 1981 (Fig 39). In the Atlantic at 35°W (Fig. 40), the variations are similar to those in Figs. 37 and 38 for the ocean as a whole.

To gain an appreciation of the interannual variations across the ocean basins and to better measure the changes in the subtropical gyres, we show several longitude-time cross-sections in Figs. 41-43, for the equator, and 30°N and 30°S. Although we have shown that the tropical, and especially equatorial, winds are unreliable, they nevertheless contain a large part of the El Ninio signal of the 1982-83 event (Harrison et al., 1989), and this can be seen in Fig. 41 for rz. Corresponding changes in the wind stress curl and Sverdrup streamfunction can also be seen.

In the subtropical gyres at 300 N (Fig. 42), the increase in strength of the curl and the Sverdrup streamfunction are again seen in the Pacific, with values ranging from as little as 60 Sverdrups in 1985 to over 140 Sverdrups in 1983. At 30°S (Fig. 43), the annual cycle in the curl is less distinctive in all three oceans, but the annual cycle in /k is fairly clear, especially in the Indian Ocean. Variations in the Pacific are again the largest, with Sverdrup transports implied in the East Australian current ranging from about 20 to 50 Sverdrups in the southern summer and 50 to 60 Sverdrups in winter. Interannual variations in the Atlantic are also notable (30 to 60 Sverdrups) and peak in 1982.

62 - 2 Ty (dy cm ) ...... I 1500 W 90 I . I~ I -~ ~ ~ ~ ~ ~ ~ _ I

...... ~ ~~~~~~~~~~~~~~~~~~~~~~~~...... 0 ...... '''' ··. ·.· :::· · · :::·:::· ·· ···

6~~I~.B ...... ~ t ~ -30 ...... H

...... 25 -60

-90 I ' . I· I I I I . . 1980 1981 1982 1983 1984 1985 1986 Months Months

a) 0 3 '^so

-30

-60

-90

Months Months JAN 80 - DEC 86 RN 80 - DEC 86

Fig. 39: Latitude-time sections of the monthly mean wind stress from 1980-86 for 1500 W; a) eastward component b) northward component c) magnitude, and d) Sverdrup mass transport

63 - 2 yv (dy cm ) 35° W 90 ...... 0

.:o: :v §,s~- 60

......

· 0 .- ...... J iji.j, i~~:i ~:~~~ii .:.~...... ~~~~~~~~~~~~~~~~~~~~~Lr~i i i·~ ~ ...... iin ltil~:iiiti~r~~'

...... -30 -60 II -90 l 1980 1981 1982 1983 1984 1985 1986 Months Months

- 1 - - 3 . iv ,.-2 ) , 35°W '-UU ( Cem s 1 X 10 ) 3iO W ' TOTAL \ I , ,/. '4nT 'kg ...... I .... 90

60 -na. a

i0...... ::iii:..O;:'""iii ' .. 30 .~~::i-:.i~:-~· : :- :.:©2:?; - _..j~::. ~ ,.: : '"0

n~~~O3CDm , 3.·:· _ _

· ,···,·i :·· , ·, · · ,· · · ,···

-60 " ·- ·· sT· w sw

-90 1 1980 1981 1982 1983 1984 1985 1986 1980 1981 1982 1983 1984 1985 1988 Months Months JN 80 - DEC 86 JRN 80 - DEC86

Fig. 40: Latitude-time sections of the monthly mean wind stress from 1980-86 for 350 W; a) eastward component b) northward component c) magnitude, and d) Sverdrup mass transport

64 1980

1981

1982

- 1983 0

V 1984 E

1985

1986

1987 60E 120E 180 120W 60W 0 Longitude

CURL (dy cm - 3 X 10 9 ) LAT= 0.0° I ng2 i I . I I I I I . I i I . . Iaou , k p - . . _ / ) :

1981 2Do 7 oC)) 6.74 ~Do '., : 1982 o/ -*:; 1 3 0 ! l en D6 : . ,,a(vs , ,,-^ ,,/', g 1983- ,.- 0 *'1 r ee 0 *- * o :s V 1984 - r,. . r E .. . . w J ,:; 1985

: ' ^ -- .^

,- 1986 .. , iF,' ) i: .-:, ,,1'1 i

I .I 1987 60E 120E 180 120W 60W 0 Longitude Longitude Fig. 41: Longitude-time sections, 1980-86, along the equator of a) the monthly mean wind stress eastward component, contour 0.2 dynes cm - 2 . Negative values are stippled, b) wind stress curl, contour interval 5 dynes cm - 3 x 109 and c) Sverdrup stream function, contour interval 5 Sverdrups. Negative values are dashed. Stippling is used to show the larger magnitudes. 65 - 3 9 ICURL (dy cm X 10 ) LAT= 30.00 ' I ! I I I I iI I I i I II I 1980 ...... -.. L-- .'-- , I - I ·\ ,I (· I\ t -c-·r--,Y: r\\ \ I ,I ( r r r., \'·r , '`C· r' 1981 I:'' :·:·Lr'·\·` rI ,Il -·-'' ,·. · '' r·i 1. \r ,, r \rr. f I C\ ) r , ('I r IL · \,r 1982 (·.:·:'·''" -·.t· ·;*· rl\r( r' )· c-,rl I rI (/n \ r r ed :: r rr rT-) O r -'1983 Crrr r;r. ·II( ,, i ·.·.·.·· 2 k r ed ··.-'j'Ek'i·-;;c' 4 0 Q) r r ,, ·c3 , v·y r I ( r ( v, r \· E r I, ... r (d c '= ,, V 1984 (· I 3 :t , I ---) Il W r\ *- ,· r i E- f C r 6.95 ' \r( O ,· --· .· ::: z r r ,,,, 'i·:\.· 1985 br·,·\ ,\u r r4 r r ·, :-b II ,, 1 , "·--,r I \,,, r r,- r J H ,-,, I I· I ,· rC· . 1986 - r 03'r c r ·, , `· 0: r r r r ,t r\ I ,cl " r \ I ,t \ r II I t rr r,,·.r · ·` rri 1987 - I I I I I I I t- 60E 120E 180 120W 60W 0

1980

1981

1982

V) - 1983 0

V 1984

1985

1986

1987

Longitude Fig. 42: Longitude-time sections from 1980-86 of the monthly mean for 30°N, a) wind stress curl, contour interval 10 dynes cm- 3 x 109 and b) Sverdrup stream function, contour interval 10 Sverdrups. Negative values are dashed. Stippling is used to show the larger magnitudes. 66 1980

1981

1982

" 1983 0

O 1984

1985

1986

1987

I 1980

1981

1982

t 1983 0

c) 1984 E

1985

1986

1987 60E 120E 180 120W 60W 0 Longitude

Fig. 43: Longitude-time sections from 1980-86 of the monthly mean for 30°S, a) wind stress curl, contour interval 10 dynes cm - 3 x 109 and b) Sverdrup stream function, contour interval 10 Sverdrups. Negative values are dashed. Stippling is used to show the larger magnitudes. 67 7. Conclusions

We have prepared a new climatology of surface wind stress over the oceans which has the advantage that it also features month-by-month mean fields for nearly seven years. It is anticipated that these fields will be useful for driving ocean general circulation models. All the results, including long term and individual monthly means, are archived and available at NCAR.

The wind stress statistics over the southern oceans are believed to be the most reliable available and there are quantitative differences from previous results elsewhere. The main shortcomings with the current results appear to be in the tropics. Also of note is the use of the Large and Pond formulation of the drag coefficient which has significant differences from several used previously.

The new climatology has significantly different features than in Hellerman and Rosen- stein (1983) and the independent analysis of sea level pressures supports the view that many of the differences in the NH are due to real climate variations on a decadal time scale. As well as indicating the need for caution in using any fields in the ECMWF climatology, such changes have strong implications for the oceans because the two climatologies would result in quite different Gulf Stream and Kuroshio circulations (Fig. 25). Although the oceanic adjustment time-scales are fairly long, significant changes would occur over a decade and call into question any assumptions of an oceanic steady state, such as is implied in some of the World Ocean Circulation Experiment strategies for sampling the ocean.

The highly significant and strong changes in the NH winter in the winds and pressures also have implications for interpreting trends in surface temperatures, which are of considerable interest because of the prospect of global warming associated with the buildup in greenhouse gases in the atmosphere. The results emphasize once more the conclusions of van Loon and Williams (1976, 1977) concerning the important role of the planetary scale waves in the NH and the spatial unevenness of the changes, as warming is apt to occur in the regions of increased southerlies and cooling in regions of increased northerlies. At the same time, there are added complications from mixing in the oceans and the additional

68 heat storage (as manifest as positive or negative SST anomalies) compared with the land. The depth of the mixing plus the heat capacity of the oceans means that the anomalies may persist long after the conditions that created them have ceased. Inevitably, these factors will complicate any interpretation of the surface temperature changes in terms of global warming.

We have further shown that the wind stress varies considerably from year to year. Strong variations associated with the 1982-1983 and 1986-1987 El Ninio events are evident in the tropical Pacific and NH, and the North Pacific in particular. In the SH interannual variations are not as large but still significant.

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74 Appendix I ECMWF Surface Winds

Much of what is contained in this appendix is based upon telephone conversations with Tony Hollingsworth 6/1/88, 6/10/88.

1. There was a major change on 9 September 1986 in the analysis. Prior to then the analysis was on standard pressure levels. Since then it has been on model sigma levels with the 1000 mb values produced by the post processor. Another substantial change occurred 7 April 1987.

2. Prior to September 1986:

* Ship data were assumed to be 10 m winds.

* A value at 1000 mb from the forecast is used as the first guess. The exchange of information between model and analysis levels was by interpolating "increments" (after 10 Dec. 1980). Thus the (forecast - analysis) increments are computed and a cubic spline fit to all levels in a and resulting values at the p levels added to the previous analysis to produce the first guess.

* The difference between the first guess wind and the ship wind at each observation point is computed as a new increment.

* This increment is used unadjusted at the nearest standard pressure level as if it had been observed at that level to update the analysis at that level.

* A reverse spline interpolation procedure p -+ a is used on the analysis changes to revise the analysis in a coordinates. The surface (lowest sigma) level wind resulting from this is assumed to be a 30 m wind.

* The 10 m wind is then derived from the 30 m wind assuming a neutral boundary layer and logarithic wind profile.

It appears that all ship data, regardless of surface pressure, over the oceans would be assigned to the 1000 mb level. Wave modelers at ECMWF preferred the 1000 mb wind over the nominal 10 m wind until late 1986. They tried the 10 m winds, the 1000 mb winds and modified versions of each and found the 1000 mb winds to be best for predicting ocean

75 waves.

3. After September 1986:

* The surface pressure is analyzed multivariately to define p, and thus the a levels.

* The surface (10 m) winds are not shifted but are used at the p, level (first sigma level) to update the analysis on a coordinates. However, there may be a boundary layer model involved in this since the lowest wind in the model is a 30 m wind.

* The 1000 mb values are interpolated/extrapolated from the a levels. For winds below the ground (i.e., p. < 1000 mb) it is believed that the winds are carried down constant at the surface value (but this is not true, see Table 1).

* A logarithmic wind profile is used somewhere in this process, presumably if 1000 mb < p.

* The 10 m wind is derived from the 30 m wind assuming a neutral boundary layer until 7 April 1987 and, after 7 April 1987, assuming a stability dependent boundary layer with the stability coming from the mode.

* The wave modelers insisted on the changes on 7 April 1987 and since then have been using the archived 10 m wind and not the 1000 mb wind. Between September 1986 and April 1987 neither the 10 m nor the 1000 mb worked very well.

4. Table 1.1 shows the archived winds at two locations in the Himalayan region where the 1000, 850 and 700 mb levels are below ground. While changes below the ground are small, the winds there bear no obvious relation to the first significant level wind above ground.

5. Further information from Bottger (1982) is reproduced in Figs. I.1 and I.2. These deal with verifications from January to May 1982 of so-called 10 m and 1000 mb winds at ocean weather ship Lima. Bttger (1982) also presents the mean and rms error using the 1000 mb wind analysis and the derived 10 m wind field from the

76 ECMWF analyses. The figures show the actual day-to-day values. The mean error of the 10 m wind is -1.3 m s- 1 versus 0.8 m s- 1 for the 1000 mb wind. The respective rms errors are 2.8 and 2.7 m s - 1 and the correlations are 0.88 and 0.87, respectively. Accordingly, these results show a slight advantage in using the 1000 mb wind analyzed product.

77 Table I.1. Values of u and v at 33.30 N 97.5 0 E (left) and 900 E (right) where the heights of the surface are 5124 and 5144 m, respectively; i.e., 1000, 850 and 700 mb levels are below ground, in m s-1.

Date Level u v u v

1/11/80 1000 13.37 5.93 11.47 -1.88 850 13.30 5.83 11.39 -2.22 700 13.44 5.79 11.57 -2.46 500 15.69 3.65 12.24 -2.43

1/11/82 1000 -1.48 0.85 3.40 2.29 850 -1.38 0.84 3.49 2.21 700 -1.47 0.58 3.56 2.33 500 7.56 6.98 6.38 -0.21

1/11/84 1000 6.79 5.36 8.07 -2.20 850 6.92 5.37 8.34 -2.10 700 7.02 5.19 8.96 -2.24 500 11.35 3.10 11.29 -2.40

1/12/86 1000 2.97 5.34 -4.60 -0.20 850 3.00 5.66 -4.35 0.17 700 3.41 5.14 -3.66 0.52 500 4.87 4.06 -1.31 2.38

12/1/86 1000 10.35 6.93 10.32 -4.30 850 10.20 6.86 10.28 -4.10 700 10.62 7.24 11.32 -3.79 500 15.33 4.25 16.52 -6.14

78 30 ......

28 ...... ·I .I ...... ~_ _ .r· .· ....

26 r...... ·r ~ · · ·...... ~·-· · .. .. l ...... _.,.A.,..,*.,._ 24 22 20 18 16 14 12 10 8 II

6 it 4 2 0 I event 20 40 60 80 100 1

Fig. I.1. Windspeed at 10 m above the surface, observed (full line) and analyzed (broken line) at OWS Lima for each 12Z observation (event) received between 15 January and 25 May 1982. From Bottger (1982).

ms-1 30 ......

26 ...... ,...... ·····1··· 24 ...~ .· ···.·· · ' ·· ···· ··.·· ( ...... ··-... ···...

22 """""""""~~' "I'""'"'~ ~ '' 1""" ...... ,...... 20 18 16 14 12 10 8 6 4 2 0 event

Fig. 1.2. As Fig. I.1, but the dashed line is here the ECMWF model analysis of windspeed at 1000 mb (instead of 10 m). From Bottger (1982).

Appendix II Curl of the wind stress

The curl of the wind stress was computed by making use of the expression

= curl,(r) - dl dA where curl.(r) is the average over the area dA, and the line integral of the tangential stress component is completed over the perimeter of the area. We define the area as being each 21° latitude-longitude box, and the resulting value is assigned to the center of the box. These raw results are archived.

For plotting purposes, the average of the values of curlz(r) at the four points ±14° of latitude and longitude removed, surrounding each original grid point, was taken, so that values were obtained on the original grid. This procedure introduces some weak but desir- able smoothing (because it removes two grid-length noise arising from the finite difference procedure) into the final values.

In computing the Sverdrup transport streamfunction from (6), the raw values of the curl were used, and values from ±1t° of latitude were averaged for plotting on the original grid.

Appendix III Stability Fields

The lowest level of data from ECMWF available is from 1000 mb and although we have argued that the 1000 mb wind is the most appropriate surface wind for use in the surface stress computations, the same cannot be said for 1000 mb temperature and humidity. For surface stability estimates, the most critical parameter is the air- sea temperature difference and large errors are likely to be incurred if the two fields are analyzed independently, especially in data sparse regions. Therefore, because the ECMWF analyses do not include SSTs and since the humidity fields are seriously in error (Trenberth and Olson, 1988d), we have had to abandon any thoughts of incorporating a full day-to-day variability of stability in the drag coefficient.

Instead, we have used mean COADS fields of air-sea temperature differences, air and sea temperatures separately and surface relative humidity, as a function of time of year to obtain global fields over the oceans. The first attempt to obtain these fields used the atlas results from Shea (1986) which analyzed air and sea temperatures separately for the 1950- 1979 period. The analysis method is discussed in Shea (1986) and is a modified Cressman objective analysis technique which has some tunable smoothing parameters built into it. In regions of dense data coverage the results are not sensitive to the "first guess" fields or the analysis method but in data sparse areas the results are quite sensitive to these factors.

Because of the analysis procedure and differences in gradients in each field, when the air-sea temperature differences are computed, results can be unreliable. Accordingly, we subsequently analyzed in the same way the actual air-sea temperature differences themselves which avoids the incompatibility problem at the cost of fewer available data. Some differences between the two methods were found in regions of strong gradient, such as near the Gulf Stream off the east coast of North America. These results were considered more reliable where data are adequate. However, there were extensive areas over the southern oceans where there are insufficient data.

Although it is recognized that there are numerous problems with marine air temperature (MAT) and SST over the years (see Folland et al., 1984; Barnett, 1984) the problems

83 are reduced after 1945. Folland et al. suggest that only nighttime MAT should be used because of daytime heating of the ship although Barnett used both. Prior to 1940 there appears to be a low bias in SSTs of -0.3°C which is blamed on bucket measurements versus the predominant intake SST measurements in more recent years. But Barnett finds a mix of bucket and intake measurements throughout.

In order to obtain MAT-SST differences and relative humidities over the southern oceans, it was decided to extend the data window to be from 1900 to 1979 as observations over the southern oceans were more plentiful, although still inadequate, in earlier years. Elsewhere, because of the smaller numbers of observations prior to World War II, the effects of the additional data are small (a few tenths of a degree C at most).-Even then, special procedures were necessary south of 60°S.

Thus the following method was used. Objective analysis of the COADS air-sea temperature differences and relative humidity for 1900-1979 were first performed. To fill the region south of 60°S, separate analyses of SST and MAT were made using all COADS data for the same period but with Antarctic station observations to define the surface coastal air temperatures, and for SST, the sea ice was specified from Alexander and Mobley (1976) and assumed to correspond to a value of-2.0°C.

These two analyses were then differenced to obtain a new set of air-sea temperature differences and values used to fill in the regions of missing data at high southern latitudes, with adjustments to the new values to ensure that they blended with the previous analysis at 60°S.

Because there remained some small scale structure to the results south of 450S, structure that clearly depended on the data distribution and was almost certainly spurious, additional smoothing in the east-west direction was implemented using Fourier analysis. Values at each latitude were replaced with the zonal mean (of the ocean points only) plus the first three harmonics.

Although the fields that result from these analyses have uncertainties of a few tenths of °C, it has little effect on the drag coefficient (see Fig. 1) which depends more on the wind speed variations. Sensitivity to the air-sea temperature differences occur only at

84 wind speeds of less than 5 m s-, but the contribution of these winds to the total stress is small.

Fig. III.1 presents the sea minus air temperature differences for each month. Values greater than 1°C in magnitude are stippled but are mostly positive and thus show areas where the surface atmosphere is unstable and CD is enhanced. These areas are in the NH in December-February off the east coasts of continents where cold continental air flows over warm water such as the Gulf Stream and Kuroshio currents. In June-August, similar unstable regions occur off of Antarctica in the SH. Over most of the oceans most of the time, with the main exception being the higher latitudes of the summer hemisphere, the sea temperature is higher than the air temperature.

Fig. III.2 presents the relative humidity fields over the oceans. Values typically range from 70 to 85% with lower values occurring in the regions of the persistent subtropical anticyclones.

85 TSEA - TAIR

.I 90N 90N

SON60N 60NSON

30N 30N

0 0

30S 30S ...... 60S 60S ....~...... ~ ~ ~_~~...... ~: 905 tU3a,5e I JAN 0 30E 60E 90E 120E 150E 180 150W 120W 90W 60W 30W 0 90N onu.060 _'*'''''''''' 0r .

' ;:...... ' 60N . .,,'~. ' ::,.s ':::..... · - · -' , 3 0N ...... - ..... 30N -0N -- o:

-'0 --..- ' " ' '.. 30S

60S

******* '.* ***** ' "' ** ..._ . _ .--...... -F .... 90S.....-I ... .'..... ~905· · -·- -· · -··-~~~~17 __1 ~~?...· ...... ,.v ---. p~r-. --- i ekt% t E'fLl t,=,f% r V'ilurui rn 0 30E 60E 90E 120E 150E 180 15iuw Zuw uuw oWvn v FEB 180 150W 120W 90W 60W 30W 0 %Jn 30 60E 90E 120E 150E · · 90N 90NSON - .-A · · · It --- ·4..... r C·-... ,__...... r ...'""'".....-..·.. ···.. ··r·. z F' .·····r;···· ··1 ·Y r ··(······ 60N 60N \ ·· .....-.·)..'· L.'L'I ,· ii·· r? ',·'';?= ::-: C ;··· C.r.. ·"':i ?·::. ··'...... ·. · ' ...... -.5 ri C-^..Y; 30N 30N r- r" '· rCi* rr, ..-1: it .. t?· .C'·/i: B ··· ·i - 0 0 f c-·--.. i 7·· '3,c' O i .r I: : : Jv6-Ins 30S

60S 60S . :.. ."', ...... ,,. . iS" ...... , ,,-.- ...... -...... nnrc VJt 90Si · ~~ ~ ~ ~ ~ ~ ~, ~ ~ ~ ~ ~ r~ n\ 0 30E 60E 90E 120E ISOE 180 150W 120W 90W 6bum 3 u MAR

Fig. III.1. Mean sea minus air temperature difference. Values greater than 1°C in magnitude are stippled. 86 TSEA -TAIR 0 30E 60E 90E 120E 1SOE 180 150W 120W 90W 60W 30W 0 ** ' '**...... 90N 90N . . ~~.90N...... 6 0 S 0 . . ' . r. .= `"i ii: 0~~ .. ..- -. 6 0

'"': . ':...f :.... '.-...

.-'. ' -'' .T' * 3 - ..-. '..5 .. - .. .. ': 305.

905. 90S

0 30E 60E 90E 120E 150E 180 150W 120W 90W 60W 30W 0 APR 0 30E 60E 90E 120E 1SOE 180 150W 120W 90W 60W 30W C 90N 90N

~~~~·..~~~~~~~~~~~~~~~~~~~~~~~~·-- .... ~~~~~~~""'... 60N 60N

30N ...... 30N ...... ~ r. ~ ·: -

0 ...... 0

30S 30S

60S 60S

90S o90 0 30E 60E 90E 120E 150E 180 150W 120W 90W 60 30W 0 MAY 0 30E 60E 90E 120E 150E 180 150W 120W 90W 60W 30W 0 90N ...... 0N 60...... -...... -. .... :';. "...... -...... ,-" ON .. . x.--'' : ': 60N

30N ... 30N 9 0 ~ 0 ':,, "1 o- ...· i b~i· O...... · 0 ... : ...... ;os~ ', ...... :::=:::::=:-:===:=---.-===.=-===;= .... 30S -.:.::.:.:...... :::...... :::.:.: .... ~ ~ ·· · · · 1··- : 30S ...... ~ ~~~~...... :~~"~"'-'"'...... '--'--'.... ~~~~~~··.~:~!?·· ·. !'::i:iii::i?:'~::::~j · · · · ,Z \

60S r_= ...... - ...... 60S ...... ::.. _,· ·--~...r~...... 90S .0...... ,.QE... i:0E...... , . . .. , . . .. 90S 0 30E 60E 90E 120E 150E 180 150W 120W 90W 60W 30M 0 JUN

Fig. III.1 (continued). Mean sea minus air temperature difference. Values greater than 1°C in magnitude are stippled.

87 TSEA -TAIR

0 30E 60E 90E 120E 150E-- 180- 150W 120W 90W 60W 30W 0 ----~ ----- ...... aQfr 9IUNn%^L ...... -,. ,., ..._-.~...... - ......

60N

30N 30N

, :. ' , ..... - ......

0 0 .... - ' f. < * *,...... ^ y r ..

30S 30S

. V** --- :.I.....- '* * * .--...... , ...... 60S 60S

.w w . . . I . . . nfK ------. - . 90S YU3i a I . . . . . I . . . .7 - I 0 30E 60E 90E 120E 150E 180 150W 120W 90W 60W 30W 0 JUL n onc ncr lF 1 nF I tnF 1R 1cSO 120W 90W 60W 30W 0 .VLU UL 'JVL .Jv ·- . 90N

...::'..' ··.-'"" ' ..*^-.*...^*...,....- .U ...... ; ' .... .-...:':~:: . ... .;... . .:..:.. . · · ..... ' - 60N 60N ..^ ...y "." ....." ";';*- .:";", "."..J '"**:. 60N ...... ~ ...... 305 130 30N6ON : :. ;. ...; '. 30N...... -'. 0 ' __..;.~__. Q,, '...... 60.S''. 305

60S

A --.,,. T IY0n - -, , . I, I, , , , , , . ' ' ' I -.- . . , . , ...... -. 0 30E 60E 90E 120E 150E 180 150W 120W 90W 60W 30W 0 AUG 0 30E 60E 90E 120E 150E 180 150W 120W 90W 60W 30W 0 90N 9.. ,------.-" _ ', ; ...... ,.. --- -"-" -...... -.-...... ' ...... ' '...' '':-'-e . . 6ON

30N

60590 .' - .. , . . . 0

30S

605

90S 0 30E 60E 90E 120E 150E 180 150W 120W 90W 60W 30W 0 SEP

Fig. III.1 (continued). Mean sea minus air temperature difference. Values greater than 1°C in magnitude are stippled. 88 TSEA '-TAIR 0 30E 60E 90E 120E- 150E 180 150W. 120W 90W 60W 30W 0 ...... ,...... 90N 90N

.. N t..^.**..^., , <.3 o-,.;- . -...... · ...... 60N

30N

30os -. . ..*...* . . . . ' ...... ":...... ON

96 . 0 5 ~ ...... 0 30W 60N ~\. ' ~' :~~~~~~~~~~...... : iir... .'" . ~'S. -. ,:...... ,.---, ,,..,--- ,-,. .. ~.--.. .- , , ,...... , 30S < .....t e ':'"~' .·.^?" v :' c,,c^

60S

90S 0 30E 60E 90E 120E 150E 180 150W 120W 90W 60W 30W 0 OCT 0 30E 60E 90E 120E 150E 180 150W 120W 90W 60W 30W 0 - - -- ...... ---. ----.---- . . 90N - 9ON

...... 60N 6'ON

"- ·,·· · .. ...·r·~~~~~~~~~~. ..

30N 3 ON *·...... -r) ..1.·~~~~~~~~~~. 0 0ON ......

30S 3

60S 6iOS

anc ------lU., - zIOS i;OW 120W 90W I vzva30F uvWv60E 0F 120F 150F a18R -,%.,- A _- __ _ NOV 0 30E 60E 90E 120E 150E 180 150W 120W 90W 60W 30W 0 1 1 1 K)N 90N 9 .. ** -* * - *· : . ' ...... ·...~xc ..::4:...... ~...'~~ ..... *.*.....-...... :'.:" .. ,.- "'·' ·- :...... '= ...... , : 90S90E 1 30EI 20E 6 I SOE"...... ; 180 ...... 6ON 60WN ^ W h.LR I'.) E/ '"' ' .. .. -.... 30N

630 . , ...... ,

60 0 - ...... :...... ' "'...... ''...... 30S .60"-3, -":'9E 120E 15E,. ... 80...... 150..... :.." 0. :~~~~~~~~~~~~~~~~0.60t4 30,0 " 60S 90S . '.I ' ' ' . I . .o I , , . _-....-- 90S 0 30E 60E 90E 120E 150E 180 15OW 120W 90W 60W 30W 0 DEC

Fig. III.1 (continued). Mean sea minus air temperature difference. Values greater than 1°C in magnitude are stippled. 89 RH

I ON 90N

ON 60N I ION 30N

1 0 0

30S 30S

60S 60S

90S 905 0 30E 60E 90 1U0EZtl uut iu un . . .J. . vv -- JAN 90E 120E 150E 180 150W 120W 90W 60W 301 0 0 30E 60E --.. - - . - . 6 . 0 Wi 90N 9N~

--`t-4;-...... ,.· 60N i r 60N j· c

"; 3ON 30N i.·\.C "': ...',..... :5- ... ·· . 0 0 L ,· ·)·.3r.

305 30S

134* 605 60S

L __ I 90S Qns 0 3 .6 90 I 0 1 1u . . .1 I u 30E 60E 90E 120E 150E 180 150W IZOWHSyW ouw a v FEB 0 30E 60E 90E 120E 150E 180 1501 120W 90W 60W 30W 0 90N . [ 9 w ~ .....-..- L,- . .... "; ...... · '-, ",,2 ...... , .·. '... .-- %----'' , ","" -- -'_I .. O i ·:· ir .;O , ... . 60tN i *" .. 2- r ,.... 30N 3ON r· I' r i 5- < :.· i 0 '·1 'r 0 0O r ·e i s,i.. 305 30S j

60S 605 ·' '···--· ·- ···""""""CII'"'"'"""'

9U0 I 1. 90S 4 ·r I I I~ 1 9OW 6ow 3OW 0 3 30E 60E 90E 120E ISOE 180 15OW 12OW MAR

is 2%. Fig. IH.2Z. Mean relative humidity fields in percent. The contour interval

90 RH _ ------. ___._ 0 30E 60E I 90N ...... I 30N n .wLI··· .....,. I 60N .iic"-··· (I6ON :.··' ·· ...... -. ·T 7 I " 30N 30N

0 I30

30S (30S SI" I 60S 60S

90S 90S 0 30E 60E I APR 0 30E 60E 90E 120E 150E 180 15OW 120W 90W 60W 30W 0 90N C 90N ""~YCC~ ~~ ~ ~ ~ ~ ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~...... ~...... P' .....~~~~······~~~~.... ··...... ·,·... ,·. ·'· ...... -······c~~~~~...... '... i. , "·(....·;~~~~~~~~~~~~~~~~~~~~~~~~~~...... 60N f 60N ...... '\ ~ 'k . ...

30N I ...... 30N J a 1

0 0

30SI 30S L 60Si 60S

...... ,,. :. ······ .f; , ...· .. ······...... ·...... 90SI 90S I MAY 0 30E 60E 90E 120E 1SOE 180 150W 120W 90W 60W 30W 0 ...... 90N 90N ------...... ········,····...... ""'~"""'······..·..†... ~-~i~I·~F;:...... · , -··~·r~'' t !':J'...... t 60N ON

30h ON

305 OS

60Si- OS

90S lOS ( JUN

Fig. III.2 (continued). Mean relative humidity fields in percent. The contour interval is 2%.

91 RH

I50E 180 150W 120W 90W' 60W 30W 0 0 30E 60E: 90E 120E Qnm 90N

60N 60N

30ON 30N

0 0

30S 30S

60S 60S

.ngs .91%f~ 905 I JUL 150H 120W 90W 60W 30W 0 0 30E 60E 90E 120E 150E 180 90N 90N F' ...... , .-.. -. ::.:.¥, .. :...... , .,':.:._.;,:'*:,... :-* , 60N .. :;

30N 30N

0 0

305 305

60S 60S

90S 90S --- A 'lr ---rr U JUt. DU. U:LUC l U- l.v » -w,- .a...... AUG 0 30E 60E 90E 120E 150E 180 150W 120W 90W 90N

c ...... J - s,- ....- ...... *?. .:>...... ^...... -.. <·'...... r~~~~~~~~~~~~~~~~nN~ ~ ~ ""···~.-·· . 60N

30N 30N i 0 0

b. 1-1 30S 30S

60S 60S

onA 90S .UJ miJ I)I 0 30E 60E 90E 1ZLOE 1wt iLOU LVW I£Vn JrrUV ULM uv·· SEP

Fig. 111.2 (continued). Mean relative humidity fields in percent. The contour interval is 2%. 92 RH 150W 120W 90W 60W 30W 0 ---- 0 30E 60E 90E 120E 150E 180 A% 90N 9ON ""''`"~ Z~:>*~e. ·. %*~ .. ' 60N 6iON mm

'r. .-.. ···,····u~...3 .. ,3 ··- r ~. f lN· 30N A%B Y Q ·--- -· ION

0 C)

30S 3OS

605 60S

905 .30S OCT

4 90N 90N

60N 60N

30N 30N

0 0

30S 30S ~~~~~~~·~~~~~~·-~ ..r ~ ~ ~ ...... ~~~~~·-"·--~~~~~~~~~~~ ...... 60S 60S

nrec Ua3 I90S 0 30E 60E 90E 120E 1SOE 180 150OW 120W 90W 60W 30W 0 NOV 0 30E 60E 90E 120E 150E 180 150W 12 90W 60W 3OW 90N 1 * " - 90N

'r "*·- ·; . >. ..-- -...... - .....- 60N 6ON60*str-~ ' wt w~ ^ .c~-·~cvn>^ -,' t i {o.~~·,L ^ -^)

30N 30N

0 0

30S 30S

60S 605

90S 90S~rr I. . . . . n I., 0 30E 60E 90E 120E 15OE 180 150W 1zow 9uM bOW Jw u DEC

Fig. III.2 (continued). Mean relative humidity fields in percent. The contour interval is 2%. 93