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Two ocean climatologies of temperature and salinity, the Generalized Digital Environmental Model (GDEM) and the Climatological Atlas of the World Ocean, are compared. Dynamic height fields are computed by season from each climatology for the North Atlantic, North Pacific, and Indian oceans and are compared on a 1 ø latitude-longitude grid. Large-scale oceanographic features are generally found to be similarly represented in both climatologies. GDEM appears to render better representations of seasonal variability and regions of high current shear, such as the Gulf Stream, because of a different smoothing method and a finer grid spacing. Maps of dynamic heights from both climatologies are presented, and their similarities and differences are discussed. The methodology for the construction of GDEM is also described in detail. 1. tation of data fields in an atlas format on seasonal time scales. Oceanographic atlases, consisting of specific data fields on map bases, are the predecessors to climatologies. An outstanding early atlas is the Meteor Atlas [Wt;ist and Defant, 1936]. Other important past atlases include the Robinson-Bauer atlases [Robinson et al., 1979; Robinson, 1976], Fuglister's atlas of the Atlantic Ocean [Fuglister, 1960], Worthington's North Atlantic atlas [Worthington and Wright, 1970], and Wyrtki's atlas of the Indian Ocean This paper is not subject to U.S. copyright. Published in 1990 by the American Geophysical Union. Paper number 89JC03682. [Wyrtki, 1971]. A catalogue of oceanographic atlases prepared by Stommel and Fieux [1978] shows no data sets in the form of global climatologies before the two being compared here. Levitus [1982] published the first worldwide climatology, The Climatological Atlas of the World Ocean (hereafter referred to as LC), basing it on objectively analyzed, gridded sets of temperature, salinity, and oxygen fields. LC provides a synthesis of all temperature, salinity and oxygen data that were available from the National Oceanographic Data Center (NODC), Washington, D.C., through 1977. The data were analyzed on annual, seasonal, and monthly time scales and were gridded in 1 ø latitude-longitude cells at standard oceanographic levels between the ocean surface and bottom (maximum depth 5500 m). The other climatology being considered here, the Generalized Digital Environmental Model (GDEM) [Davis et al., 1986] had its beginnings at the Naval Oceanographic Office (NAVOCEANO) in 1975. GDEM is a four-dimensional (latitude, longitude, depth, and time) digital model of temperature and salinity for the North and South Atlantic, and Pacific north of the equator, the Indian Ocean north of 40øS, the Arctic Ocean, the Mediterranean Sea, and the Black Sea. The South Pacific model is expected to be finished by October 1989. GDEM consists of coefficients of mathematical expressions describing vertical profiles of temperature lo and salinity on a 5 latitude-longitude grid for seasonal and annual time frames. Profiles of temperature and salinity are generated from equations using the stored ...

The Modular Ocean Data Assimilation System (MODAS) is used by the U.S. Navy for depiction of threedimensional fields of temperature and salinity over the global ocean. MODAS includes both a static climatology and a dynamic climatology. While the static climatology represents the historical averages, the dynamic climatology assimilates near-real-time observations of sea surface height and sea surface temperature and provides improved temperature and salinity fields. The methodology for the construction of the MODAS climatology is described here. MODAS is compared with Levitus and Generalized Digital Environmental Model climatologies and with temperature and salinity profiles measured by SeaSoar in the Japan/East Sea to illustrate MODAS capabilities. MODAS with assimilated remotely sensed data is able to portray time-varying dynamical features that cannot be represented by static climatologies.

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Abstract. The capability of spaceborne altimeters to provide precise measurement of significant wave height and wind speed has been demonstrated repeatedly. It is shown in this paper that in addition to the significant wave height and wind speed, the wave period can be calculated from the semiempirical functions established from earlier wave research. The calculated characteristic wave period using the altimeter-derived wind speed and wave height are found to be in excellent agreement with the peak wave period and average wave period from the ocean buoy measurements in the Gulf of Mexico. Also, with the long time series of collocated data set, it is possible to compare altimeter output of wind and wave parameters with ocean buoy measurements taking into consideration the spatial lags between the buoy locations and the altimeter footprints, and the temporal lags between the two sensor systems. It is found that when the spatial lags are less than 10 km, the RMS difference of the significant wave height is approximately 0.1 m, which is the digitization resolution of the output from both altimeter and ocean buoy. For the wind speed, the RMS difference approaches 1.2 m/s in the Gulf of Mexico using the empirical algorithms. The wind speed agreement is significantly improved to 0.8 m/s when the tilting effect on the altimeter cross section is accounted for. In contrast to the spatial lags, temporal lags of up to 1 hour do not appear to produce significant difference in the statistics of comparison based on this study.