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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 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

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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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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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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Thomas M. Smith and Richard W. Reynolds

Abstract

An extended reconstruction of monthly mean oceanic historical sea level pressure (SLP) based on Comprehensive Ocean–Atmosphere Data Set (COADS) release-2 observations is produced for the 1854–1997 period. The COADS data are first screened using an adaptive quality-control procedure. Land SLP data from coastal and island stations are used to supplement the COADS data. The SLP anomalies are analyzed monthly to a 2° grid using statistics based on 20 yr of assimilated atmospheric reanalysis. A first-order correction is applied to the reconstruction to minimize variations associated with spurious long-term changes in the atmospheric mass over the oceans.

In the nineteenth century, the reconstruction appears to underestimate the SLP-anomaly amplitudes, and error estimates for the reconstruction are largest. After 1900 the reconstruction variance is stronger, although there are periods in the first half of the twentieth century when sampling is poor and the variance decreases. Spatial correlations between the reconstruction and several comparison analyses are highest in the second half of the twentieth century, suggesting greater reconstruction reliability after 1950.

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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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Thomas M. Smith and Richard W. Reynolds

Abstract

Because of changes in SST sampling methods in the 1940s and earlier, there are biases in the earlier period SSTs relative to the most recent 50 years. Published results from the Met Office have shown the need for historic bias correction and have developed several correction techniques. An independent bias-correction method is developed here from an analysis using nighttime marine air temperatures and SST observations from the Comprehensive Ocean–Atmosphere Data Set (COADS). Because this method is independent from methods proposed by the Met Office, the differences indicate uncertainties and similarities indicate where users may have more confidence in the bias correction.

The new method gives results that are broadly consistent with the latest Met Office bias estimates. However, this bias estimate has a stronger annual cycle of bias in the Northern Hemisphere in comparison with the Met Office estimate. Both estimates have midlatitude annual cycles, with the greatest bias in the cold season, and both have a small annual cycle in the Tropics. From the 1850s into the early twentieth century both bias estimates increase with time, although this estimate increases slightly less than the Met Office estimate over that period. Near-global average temperatures are not greatly affected by the choice of bias correction. However, the need for a bias correction in some periods may introduce greater uncertainty in the global averages. Differences in the bias corrections suggest that this bias-induced uncertainty in the near-global average may be 0.1°C in the nineteenth century, with less uncertainty in the early twentieth century.

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Steven K. Esbensen and Richard W. Reynolds

Abstract

Air-sea transfers of sensible heat, latent heat and momentum are computed from 25 years of middle-latitude and subtropical ocean weather ship data in the North Atlantic and North Pacific using the bulk aerodynamic method. The results show that monthly averaged wind speeds, temperatures and humidities can be used to estimate the monthly averaged sensible and latent heat fluxes from the bulk aero-dynamic equations to within a relative error of ∼10%. The estimates of monthly averaged wind stress under the assumption of neutral stability are shown to be within ∼5% of the monthly averaged non-neutral values.

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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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