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Richard W. Reynolds

Abstract

A numerical finite-difference model using the Laplace tidal equations on an f-plane was developed to predict how tidal motion is disturbed by an elliptic ridge. With the use of an open-ocean matching condition the model was used to study the effects of several generalized types of elliptic bottom topographies and to study the particular case of the Hawaiian Ridge.

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Richard W. Reynolds

Abstract

Six global and two regional Pacific monthly sea surface temperature climatologies were compared. The climatologies were based on either surface marine observations or oceanographic cast (surface plus subsurface temperatures) observations. Although the cast data is more accurate than the surface marine, the data density of the cast observations is much more sparse. In this study, the surface marine climatologies were generally found to be superior to the cast climatologies. The individual differences between the climatologies are described and evaluated.

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Richard W. Reynolds

Abstract

A global monthly sea surface temperature analysis is described which uses real-lime in situ (ship and buoy) and satellite data. The method combines the advantages of both types of data: the ground truth of in situ data and the improved coverage of satellite data. The technique also effectively eliminates most of the bias differences between the in situ and satellite data. Examples of the method are shown to illustrate these points.

Sea surface temperature (SST) data from quality-controlled drifting buoys are used to develop error statistics for a 24-month period from January 1985 through December 1986. The average rms monthly error is 0.78°C; the modulus of the monthly blasts (i.e., the average of the absolute value of the monthly biases) is 0.09°C.

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Richard W. Reynolds

Abstract

The June 1991 eruptions of Mount Pinatubo produced new stratospheric aerosols that were greater than the aerosols from the 1982 eruptions of El Chichón. These new aerosols strongly affected the advanced very high resolution radiometer (AVHRR) retrievals of sea surface temperature in the tropics where negative biases occurred with magnitudes greater than 1°C. The time dependence of these biases are shown. In addition, a method to correct these biases is discussed and integrated into the National Meteorological Center's optimum interpolation sea surface temperature analysis.

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Claude Frankignoul and Richard W. Reynolds

Abstract

A slab model of the oceanic mixed layer is used to predict the statistical characteristics of the sea surface temperature anomalies that are forced by day-to-day changes in air-sea fluxes in the presence of a mean current. Because of the short time scale of the atmospheric fields, the model validity can be tested without quantitative information on the atmospheric forcing. A procedure is developed for the case where the mean current is given. It is applied to sea surface temperature (SST) anomaly data from the North Pacific using ship drift data as estimates of the mean ocean currants. At the 95% level of significance the model is consistent with the data over more than 85% of the investigated region. The results indicate that the atmospheric forcing acts as a white noise forcing; in regions of large currents, advection effects are important at low frequencies. However, SST anomaly autospectra are equally well represented by a local model where advection is neglected.

The available meteorological data are then used to estimate the forcing due to heat flux and Ekman advection anomalies. This forcing compares well with the stochastic forcing estimated from the SST data over most of the North Pacific. It is found that heat flux anomalies play a more important role than advection by anomalous Ekman currents; direct wind forcing and the resulting mixed-layer depth variability seem important at high latitudes but could not he estimated here. Finally, the cross-correlations between the SST anomaly and the atmospheric forcing fields are consistent with the stochastic forcing model and suggest that heat exchanges also contribute to the SST anomaly damping, thereby acting as a negative feedback.

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Pearn P. Niller and Richard W. Reynolds

Abstract

The purpose of our study is to describe and compute the large-scale, three-dimensional circulation near the Subtropical Front in the eastern North Pacific along 31°N. This was accomplished through the use of four extensive hydrographic surveys, historical wind-stress data and also the movement of surface drifters. Our results indicate that, in wintertime, surface water sinks on the north side of the front and rises on its south side. During the summer, however, the subtropical salty surface water overflows the frontal area to the north. Potential vorticity and heat are best conserved in a vertical flow pattern where the annual mean Ekman convergence sinks to a depth of 300 m and water upwells throughout the main thermocline. The computed horizontal flow below 700 m amounts to less than 0.6 cm s−1; both strength and direction depend greatly on the treatment of noise within the data set and also on the conservation statement that is specified in addition to geostrophic and hydrostatic dynamics. A qualitatively consistent circulation pattern, with a horizontal and vertical spread of freshwater tongues, has been found above 500 m. However, as Coats noted in 1981, diffusion rates cannot be adequately determined because of the difficulty involved in establishing 1arge-scale property changes when eddy noise is present. Below 700 m potential vorticity is uniform, while water-mass properties exhibit gradients. The eddy kinetic energy, as determined from surface drifters, increases threefold from 40°N to 20°N.

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Thomas M. Smith and Richard W. Reynolds

Abstract

A monthly extended reconstruction of global SST (ERSST) is produced based on Comprehensive Ocean–Atmosphere Data Set (COADS) release 2 observations from the 1854–1997 period. Improvements come from the use of updated COADS observations with new quality control procedures and from improved reconstruction methods. In addition error estimates are computed, which include uncertainty from both sampling and analysis errors. Using this method, little global variance can be reconstructed before the 1880s because data are too sparse to resolve enough modes for that period. Error estimates indicate that except in the North Atlantic ERSST is of limited value before 1880, when the uncertainty of the near-global average is almost as large as the signal. In most regions, the uncertainty decreases through most of the period and is smallest after 1950.

The large-scale variations of ERSST are broadly consistent with those associated with the Hadley Centre Global Sea Ice and Sea Surface Temperature (HadISST) reconstruction produced by the Met Office. There are differences due to both the use of different historical bias corrections as well as different data and analysis procedures, but these differences do not change the overall character of the SST variations. Procedures used here produce a smoother analysis compared to HadISST. The smoother ERSST has the advantage of filtering out more noise at the possible cost of filtering out some real variations when sampling is sparse. A rotated EOF analysis of the ERSST anomalies shows that the dominant modes of variation include ENSO and modes associated with trends. Projection of the HadISST data onto the rotated eigenvectors produces time series similar to those for ERSST, indicating that the dominant modes of variation are consistent in both.

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Thomas M. Smith and Richard W. Reynolds

Abstract

A merged land–air–sea surface temperature reconstruction analysis is developed for monthly anomalies. The reconstruction is global and spatially complete. Reconstructed anomalies damp toward zero in regions with insufficient sampling. Error estimates account for the damping associated with sparse sampling, and also for bias uncertainty in both the land and sea observations. Averages of the reconstruction are similar to simple averages of the unanalyzed data for most of the analysis period. For the nineteenth century, when sampling is most sparse and the error estimates are largest, the differences between the averaged reconstruction and the simple averages are largest. Sampling is always sparse poleward of 60° latitude, and historic reconstructions for the polar regions should be used with caution.

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Nicholas R. Nalli and Richard W. Reynolds

Abstract

This paper describes daytime sea surface temperature (SST) climate analyses derived from 16 years (1985–2000) of reprocessed Advanced Very High Resolution Radiometer (AVHRR) Pathfinder Atmospheres (PATMOS) multichannel radiometric data. Two satellite bias correction methods are employed: the first being an aerosol correction, the second being an in situ correction of satellite biases. The aerosol bias correction is derived from observed statistical relationships between the slant-path aerosol optical depth and AVHRR multichannel SST (MCSST) depressions for elevated levels of tropospheric and stratospheric aerosol. Weekly analyses of SST are produced on a 1° equal-angle grid using optimum interpolation (OI) methodology. Four separate OI analyses are derived based on 1) MCSST without satellite bias correction, 2) MCSST with aerosol satellite bias correction, 3) MCSST with in situ correction of satellite biases, and 4) MCSST with both aerosol and in situ corrections of satellite biases. These analyses are compared against the Tropical Rainfall Measuring Mission (TRMM) Microwave Imager OI SST, along with the extended reconstruction SST in situ analysis product. The OI analysis 1 exhibits significant negative and positive biases. Analysis 2, derived exclusively from satellite data, reduces globally the negative bias associated with elevated atmospheric aerosol, and subsequently reveals pronounced variations in diurnal warming consistent with recently published works. Analyses 3 and 4, derived from in situ correction of satellite biases, alleviate biases (positive and negative) associated with both aerosol and diurnal warming, and also reduce the dispersion. The PATMOS OISST 1985–2000 daytime climate analyses presented here provide a high-resolution (1° weekly) empirical database for studying seasonal and interannual climate processes.

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Richard W. Reynolds and Diane C. Marsico

Abstract

The monthly global sea surface temperature (SST) analysis of Reynolds using real-time in situ and satellite SST data has now been improved by using sea ice data to simulate SSTs in ice-covered regions. The simulated SSTs now become the external boundary condition for the analysis solution. This technique eliminates any high-latitude satellite biases and extends the analysis to the ice edge. The analysis with the ice data has been computed for the period January 1982 to present.

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