Regional high -frequency signals in atmospheric and oceanic excitation of polar motion

Pergamon

0 2002 COSPAR.

Adv. Space Res. Vol. 30, No. 2, pp. 369374, 2002 Published by Elsevier Science Ltd. All rights reserved Printed in Great Britain 0273-1177/02 $22.00 + 0.00

PII: SO273-1177(02)00309-5

REGIONAL HIGH -FREQUENCY SIGNALS IN ATMOSPHERIC AND OCEANIC EXCITATION OF POLAR MOTION J. Nastula’, R. M. Ponte’, and D. A. Salstein’ ‘Space Research Centre of the PAS, Bartycka 184 00-716 Warsaw, Poland 2Atmospheric and Environmental Research, Inc., 131 Hartwell Avenue, Lexington, MA 02421, USA

ABSTRACT Atmospheric and oceanic variability have been shown to play a role in the excitation of polar motion at periods longer than about 5 days, but there is still a large drop in coherence between combined oceanic-atmospheric and geodetic series at about 8 or 9 days. Improving the agreement at these high frequencies will require better estimates of oceanic angular momentum (OAM) and atmospheric angular momentum (AAM). Determining which regions are the most important for excitation of polar motion may provide clues to the present quality of AAM and OAM estimates and ways to improve them. For this purpose regional patterns of the standard deviation of atmospheric and oceanic excitation with periods shorter than 10 days are analysed and compared. The role of regional mass (oceanic bottom pressure and atmospheric surface pressure) and motion (currents and winds) signals in contributing to global polar motion excitation is also examined by computing the fractional covariance between local and global time series. Midlatitude regions were found to be places of strong local oceanic and atmospheric signals. Important oceanic excitation signals include circulation and mass fluxes associated with subtropical and higher latitude regions. 0 2002 COSPAR. Published by Elsevier Science Ltd. All rights reserved.

INTRODUCTION The importance of atmospheric angular momentum (AAM) and oceanic angular momentum (OAM) signals for polar motion excitation at periods longer than approximately 10 days is fairly well established (Eubanks, 1993; Nastula and Ponte, 1999; Ponte et al., 1998). Although the combined AAM and OAM signals do not explain all of the observed polar motion at these periods, their coherence is large and statistically significant (Ponte et al. 1998; Nastula and Ponte, 1999). However, at periods shorter than 10 days, there is a marked drop in coherence between observed polar motion and geophysical excitation inferred Tom available OAM and AAM series (e.g., Nastula and Ponte, 1999). At the same time, there is apparently no deficit in excitation power compared to that observed. Thus, uncertainties in some or all of the time series, rather than missing sources of excitation, may be the reason for the poor coherence at the highest frequencies (Ponte, 1997; Nastula and Ponte, 1999). To better understand the nature of the high frequency AAM and OAM signals and to try to reduce the uncertainties in their estimated values, it is useful to analyse their regional variability characteristics and to measure how different regions may contribute to the globally-integrated values. Regional analysis of AAM and OAM signals have been performed for monthly and longer periods (Salstein and Rosen, 1989; Nastula and Salstein, 1999; Nastula et al., 2000; Ponte and Stammer, 1999) and have revealed the importance of specific areas (e.g. North Pacific and Southern Oceans for OAM signals, Eurasia for AAM signals) for polar motion excitation. AAM and OAM signals associated with pressure terms were found to be of the same order of magnitude while signals associated with winds were substantially larger then those associated with ocean currents (Nastula et al., 2OGO).The regional characteristics of atmospheric and oceanic polar motion excitation at the shortest periods have not been considered, however. Here we analyse regional OAM and AAM values at periods ranging from 2 to 10 days. Our goals are to determine the regions in the ocean and atmosphere that can act as important sources of polar motion excitation, to quantify the relative role of mass and motion terms in this excitation, and to understand the processes that need to be resolved in order to capture the excitation signals at these high frequency bands.

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ATMOSPHERIC AND OCEANIC MEASUREMENTS Oceanic and atmospheric excitation of polar motion occurs by means of an exchange of angular momentum

with the solid Earth in the equatorial plane. The components of this momentum available for transfer to the solid Earth can be expressed as so called polar motion excitation functions, ~1, ~2 (Barnes et al., 1983), which represent polar motion excitation about the equatorial axes pointing to the Greenwich and 90 E meridians, respectively. The atmospheric or oceanic excitation functions can be compared with the equivalent geodetic excitations, determined from the observed positions of the Earths pole of rotation. For this study we use two data sets of regional values of atmospheric and oceanic excitation functions. OAM: Oceanic excitation functions for polar motion x1,2’ are calculated from output of the near global (75” S 66” N) barotropic ocean model of Ponte (1997), which was run on a 1.125 degree horizontal grid and driven by 6-hourly surface wind stress and atmospheric pressure from the U.S. National Centers for Environmental Prediction / National Center for Atmospheric Research (NCEP/NCAR) reanalysis, for the period January 1993 to December 1995. Full details of the model run and output used here are given in Ponte and Gaspar (1999) and references therein. In this work, we adopt the approach of Ponte (1997) and calculate ocean pressure terms based on sea level adjusted for an inverted barometer (IB) oceanic response to overlying air pressure. The approach is consistent with using the IB-corrected atmospheric x terms. The regional series are given at one-day intervals and they are useful for examining high frequency signals. These oceanic data were averaged spatially into 144 sectors over 15.75 by 21.5 degree boxes to focus on large-scale signals as it was done in the case of atmospheric data. Oceanic pressure terms are calculated separately. x1,*o(p)and velocity x1,20(V) AAM: Atmospheric excitation functions X~,~*are computed regionally by Nastula and Salstein (1999) from the NCEP/NCAR reanalysis system (Salstein et al., 1993). These basic data include atmospheric surface pressure and the vertical distribution of the horizontal components of wind velocity at each 2.5” x 2.5” latitude - longitude grid point for the last 50 years. To sample regional variability giving the same weight to all areas, we divide the globe into 108 equal-area sectors, placing meridional boundaries every 30” of longitude and zonal boundaries at 6.4, 19.5, 33.7, 51.1” and 90” N and S. Regional atmospheric excitation functions were then averaged from four-time to daily frequency over the period from January 1993 to December 1995. The atmospheric data contain terms related to and wind x~.~*~. pressure XQ*(~), pressure with the IB correction applied over oceans x~,z*‘~‘~~‘, METHOD

To quantify the relation between regional and global excitation functions we compute here the amplitude of the fractional covariance defined as:

5 (x f

cov

=

k=l

-

ii” xx L -

x )*

&t xl’ k

-

where * is the complex conjugate. Here N is number of points in the time series, overbars represent time averaging, superscript R denotes regional values, terms without superscript are global values of excitation functions, and x denotes either the real-valued functions x1 and ~2 or the complex-valued function x1 + ix2. The quantity in Eq.1 is a measure of the contribution of local signals to the variance in global series and by definition, fractional covariances over all grid boxes sum up to unity. We calculate latitude-longitude maps of the fractional covariance amplitudes from the two above mentioned data sets that have been filtered using the band-pass Butterworth filter (Otnes and Enochson, 1972) to include periods ranging from 2 to 10 days. REGIONAL ANALYSIS OF OCEANIC AND ATMOSPHERIC EXCITATION Figures 1 a-f, 2 a-f and 3 a-c show maps of the amplitude of fractional covariance between global and regional excitation functions for polar motion. To complement the information we present in Figures 1 g-h, 2 g-h and 3d maps of standard deviation (SDV) of complex-valued x values, For the ocean excitation, in the case of ~1”” (Figure la) the largest positive covariance can be seen over the southern mid-latitude arm centred at 180’ longitude. Weaker covariance maxima for x1’(‘) are found in the midlatitude North Pacific and North Atlantic and over the southern mid-latitude areas centred near 30” and 330* longitude. The largest covariance for x2’(‘) (Figure lc) is also found in the southern mid-latitudes, in the Indian and

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Pacific. For the complex-valued xqp’ (Figure le) the largest covariance is found over the southern midlatitudes areas centred near 60 “, 180 ‘, 270 ’ and 330 ’ longitude, weaker covariance maxima are also found in the mid-latitude North Pacific and North Atlantic. Maps of fractional covariances for ~1~) (Figure lb) show maximum in the Indian Ocean in area west of Australia centred near 30” S . For the case of xzW) (Figure Id) the fractional covariance pattern is dominated by the maximum in the area east of Australia centred near 20% with weaker maxima in regions east of South America and south-west of Africa. A map of fractional covariance amplitude for xW’ (Figure If) repeats the x2o(v)covariance maxima pattern. A maximum of covariance is also found in the Indian Ocean and tropical Atlantic. Turning to computations of AAM, it is known that with the IB correction, the atmosphere does not provide enough power to excite rapid polar motion. So, although the OAM model used here is consistent with using the IBcorrected atmospheric pressure data, we compute here fractional covariance also for the non-IB pressure case. eastern

(a)

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Fig. 1. (a-f> Maps of the amplitude of fractional covariance between global and regional values of polar motion oceanic excitation function for pressure and velocity terms; (g-h) maps of standard deviation of polar motion oceanic complex-valued excitation function for pressure and velocity terms.

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The fractional covariance for pressure term ~i*(~)(Figure 2a) of atmospheric excitation is dominated by maxima over the mid-latitude North Pacific, and over the area from the western region of the North Atlantic to eastern Europe. In the mid-latitude Southern Ocean (Figure 2a) one can see three maxima over longitudes corresponding to those for maxima in the Northern Hemisphere. The largest maxima in x2*(P)(Figure 2c) are seen however over Asia and western and eastern regions of North America. Enhanced covariance is found also in southern mid-latitudes over areas southwest of Australia and west of the southern tip of South America. The fractional covariance amplitude for complex xACP’(Figure 2e) ha s a spatial pattern with maxima in mid-latitude North Pacific, North Atlantic and Europe and over the South Pacific. Applying the IB correction to the atmospheric pressure term results in the dominance of Eurasia and North maxima of covariance are connected with America instead (Figures 2b and 2d). It is worth noting that for xiACP+IB’

(a)

Cov. x

,A(pressure)

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x ,A(pressure+lB) cl..=

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Onas)

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,V.

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2 .Z ‘ii

-10

-I

-40 -70 Longitude

Fig. 2. (a-f) Maps of amplitude of fractional covariance between global and regional values of polar motion atmospheric excitation function for pressure and pressure + IB term; (g-h) maps of standard deviation of polar motion atmospheric complex-valued excitation function for pressure and pressure + IB terms.

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Asia and North America seem to be more important. Europe, west Asia and the Gulf of Alaska, while for ~2A(P+ra) The spatial pattern of largest maxima of covariance for complex-valued ~*‘~+i~‘isdominated by that of x2A(P+IB). Maps of fractional covariance amplitudes for xiA O, ~2” o andXAm have complicated patterns, much different from the patterns for pressure terms (Figures 3a-c). This behaviour is likely due to the meridional wind terms being rather noisy or out of phase regionally. It is worth noting that generally all the regions with maximum covariance of oceanic and atmospheric pressure terms are similar to regions with maximum of standard deviation (Figures 1 g-h, 2 g-h and 3d). For the atmospheric wind term and the ocean currents term one can see some differences between maps of SDV and maps of fractional covariance.

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o.re

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Fig. 3. (a-c) Maps of amplitude of fractional covariance between global and regional values of polar motion atmospheric excitation function for wind term; (d) maps of standard deviation of polar motion atmospheric complex-valued excitation function for wind term. DISCUSSION AND CLOSING REMARKS We have explored the ways in which different regions contribute to oceanic and atmospheric excitation at periods of 2-10 days. In comparing the patterns here with those of earlier papers, regional characteristics of short period excitation are generally in agreement with those obtained from analyses performed for signals at monthly and longer periods (Nastula et al., 2000). The strongest polar motion excitation due to variability of atmospheric pressure, oceanic pressure and w ind terms is connected with areas over northern and southern midlatitudes. The spatial pattern of the pressure + IB term is dominated, however, by maxima over land areas with Eurasia and North America being especially important (Nastula and Salstein, 1999; Nastula et al., 2000). Oceanic excitation due to currents is strong in the North Pacific and the Southern Oceans. The patterns of variability and fractional covariance of AAM and OAM pressure terms reflect the spatial weights according to the definition of the excitation functions in Barnes et al. (1983) (see Ponte and Stammer, 1999 for a plot of the weighting factors) but are also modulated by the spatial patterns of atmospheric pressure and oceanic bottom pressure variability. In particular, high frequency variability in oceanic bottom pressure tends to be large in mid and high latitude regions (e.g., Fukumori et al., 1998), which also have large weighting factors, thus reinforcing the potential importance of those latitudes in exciting rapid polar motions. For ocean current terms, maxima in variability and fractional covariances do not strictly coincide, indicating that areas of large variability may not always contribute the most to the variability in the global ocean excitation functions. Comparison of regional amplitudes of AAM and OAM signals confirm that atmospheric and oceanic excitation are both likely to be important for polar motion excitation at periods of 2-10 days. Nastula and Ponte (1999)

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showed that there is a drop in coherence at about 8 or 9 days between the observed excitation of polar motion and that determined from the combination of atmospheric and oceanic estimates. Either a missing geophysical component, such as surface water, or limits to the accuracy of the data sets involved may be the causes. For the second case, we have highlighted here the regions contributing most to the excitation, and thus most important to assess carefully. Interestingly, covariance patterns are similar for both the high frequency signals studied here, as well as for the lower frequency signals shown elsewhere, so these particular locations in the atmosphere and ocean may be of fundamental importance in driving polar motion. ACKNOWLEGMENTS The research reported here was supported under the Polish State Committee for Scientific Research through project 152/T 12/97/13, and by the United States NASA Earth Observing System Program through NAG5-9989. The NSF International Division facilitated our cooperation through Grant INT-9807014. REFERENCES Barnes, R., T. H, R. Hide, A. A. White, and C. A. Wilson, Atmospheric angular momentum fluctuations, length-ofday changes and polar motion, Proc. R. Sot. Land., A387,31-73, 1983. Eubanks, T. M., Variations in the orientation of the Earth, in AGU Mono&?raDh,Contributions of Space Geodesv to Geodvnamics: Earth Dvnamics, Smith and Turcotte eds., Geodynamics Series, 24, pp. 1 -54,1993. Fukumori, I., R. Raghunath, and L.-L. Fu, Nature of global large - scale sea level variability in relation to atmospheric forcing, A modelling study, J. Geophys. Res., 103,5493--5512, 1998. Nastula, J., and R. M. Ponte, Further evidence or oceanic excitation of polar motion, Geophys. J. Int, 139, 123 - 130,1999. Nashua, J., R. M. Ponte , and D. A. Salstein, Regional signals in atmospheric and oceanic excitation of polar motion, in 1, Cagliari Sardlnia Italy, pp. 463-472,2000. Nashua, J., and D. A. Salstein, Regional atmospheric angular momentum contributions to polar motion excitation, J. Geophys. Res., 104,7347 - 7358, 1999. Otnes, R. K., and Enochson L., Digital Time Series Analvsis, John Wiley and Sons, New York, 1972. Ponte, R. M., Oceanic excitation of daily to seasonal signals in Earth rotation: Results from a constant-density numerical model, Geophys. J. Znt., 130,469 - 474, 1997. Ponte, R. M., and P. Gaspar, Regional analysis of the inverted barometer over the global ocean using TOPEX / POSEIDON data and model results, J. Geophys. Res., 104, 15587-15601,1999. Ponte, R. M., and D. Stammer, Role of ocean currents and bottom pressure variability on seasonal polar motion, J. Geophys. Res, 104, 23393 - 23409,1999. Ponte, R. M., D. Stammer and J. Marshall, Oceanic signals in observed motions of Earth’s pole of rotation, Nature, 391,476-479,1998. Salstein, D. A, and R. D. Rosen, Regional contributions to the atmospheric excitation of rapid polar motions, J. Geophys. Res., 94, 9971 - 9978, 1989. Salstein, D. A., D. M. Kann, A. J. Miller, and R. D. Rosen, The Sub-Bureau for Atmospheric Angular Momentum of the International Earth Rotation Service: a meteorological data center with geodetic applications, Bull. Amer. Meteor. Sot., 74, 67-80, 1993.