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Abstract
The NOAA ¼° daily optimum interpolation sea surface temperature analysis (DOISST) is available either as a 31-yr (from 1981 onward) time series based on Advanced Very High Resolution Radiometer (AVHRR) observations or as a 9-yr (2002–11) time series that incorporates additional data from the Advanced Microwave Scanning Radiometer (AMSR) on the Earth Observing System (EOS) platform. In October 2011, AVHRR+AMSR DOISST production was discontinued when the AMSR instrument lost its capability to collect daily, global-coverage data. Sea surface temperatures from the follow-up AMSR2 instrument will not be available until mid-2013. To ensure an uninterrupted consistent long-term microwave-based DOISST time series, this study tested the feasibility of bridging the gap between AMSR and AMSR2 using WindSat Polarimetric Radiometer (WSAT) data. Comparison of WSAT and AMSR SST data during their period of overlap from 2004 to 2011 showed temporal gaps were common for WSAT, especially before 2009. The WSAT daily spatial coverage was slightly inferior to AMSR but still far superior to AVHRR. When satellite SSTs were bias adjusted with respect to in situ data, the resulting AMSR- and WSAT-only analyses were very similar. Monthly zonal averages agreed to within 0.1 K, except when WSAT data were continuously missing for over three weeks. However, if satellite SSTs were not bias adjusted prior to analysis, seasonally varying zonal average differences were observed, with maxima of ~0.3 K occurring at midlatitudes. Thus, WSAT can be used to continue the microwave-based DOISST time series because the methodology compensates for the different equatorial crossing times of the two satellites.
Abstract
The NOAA ¼° daily optimum interpolation sea surface temperature analysis (DOISST) is available either as a 31-yr (from 1981 onward) time series based on Advanced Very High Resolution Radiometer (AVHRR) observations or as a 9-yr (2002–11) time series that incorporates additional data from the Advanced Microwave Scanning Radiometer (AMSR) on the Earth Observing System (EOS) platform. In October 2011, AVHRR+AMSR DOISST production was discontinued when the AMSR instrument lost its capability to collect daily, global-coverage data. Sea surface temperatures from the follow-up AMSR2 instrument will not be available until mid-2013. To ensure an uninterrupted consistent long-term microwave-based DOISST time series, this study tested the feasibility of bridging the gap between AMSR and AMSR2 using WindSat Polarimetric Radiometer (WSAT) data. Comparison of WSAT and AMSR SST data during their period of overlap from 2004 to 2011 showed temporal gaps were common for WSAT, especially before 2009. The WSAT daily spatial coverage was slightly inferior to AMSR but still far superior to AVHRR. When satellite SSTs were bias adjusted with respect to in situ data, the resulting AMSR- and WSAT-only analyses were very similar. Monthly zonal averages agreed to within 0.1 K, except when WSAT data were continuously missing for over three weeks. However, if satellite SSTs were not bias adjusted prior to analysis, seasonally varying zonal average differences were observed, with maxima of ~0.3 K occurring at midlatitudes. Thus, WSAT can be used to continue the microwave-based DOISST time series because the methodology compensates for the different equatorial crossing times of the two satellites.
Abstract
An improved SST reconstruction for the 1854–1997 period is developed. Compared to the version 1 analysis, in the western tropical Pacific, the tropical Atlantic, and Indian Oceans, more variance is resolved in the new analysis. This improved analysis also uses sea ice concentrations to improve the high-latitude SST analysis and a modified historical bias correction for the 1939–41 period. In addition, the new analysis includes an improved error estimate. Analysis uncertainty is largest in the nineteenth century and during the two world wars due to sparse sampling. The near-global average SST in the new analysis is consistent with the version 1 reconstruction. The 95% confidence uncertainty for the near-global average is 0.4°C or more in the nineteenth century, near 0.2°C for the first half of the twentieth century, and 0.1°C or less after 1950.
Abstract
An improved SST reconstruction for the 1854–1997 period is developed. Compared to the version 1 analysis, in the western tropical Pacific, the tropical Atlantic, and Indian Oceans, more variance is resolved in the new analysis. This improved analysis also uses sea ice concentrations to improve the high-latitude SST analysis and a modified historical bias correction for the 1939–41 period. In addition, the new analysis includes an improved error estimate. Analysis uncertainty is largest in the nineteenth century and during the two world wars due to sparse sampling. The near-global average SST in the new analysis is consistent with the version 1 reconstruction. The 95% confidence uncertainty for the near-global average is 0.4°C or more in the nineteenth century, near 0.2°C for the first half of the twentieth century, and 0.1°C or less after 1950.
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.
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.
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.
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.
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.
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.
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.
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.
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.
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.
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.
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.
Abstract
In this study, two sets of Pacific Ocean analyses for 1993–96 were analyzed. Both analyses were produced with the assimilation of subsurface temperature data from expendable bathythermographs and tropical atmosphere–ocean moorings. In addition one analysis also assimilated sea level data from TOPEX/Poseidon. Sea level variability in the two analyses agreed well with each other, and both agree with tide gauge and altimetry data for 1993–95. However, beginning in late 1995 through 1996, large sea level differences of 5–8 cm were found in the tropical western Pacific between the two analyses. Furthermore, large sea level discrepancies were also found between dynamic height estimated from TAO temperatures and tide gauge–altimetry observations in the same region during 1996. These discrepancies are consistent with the sea level differences between the two model based analyses.
Historical conductivity–temperature–depth data along 165°E near the equator were also analyzed and it was found that salinity variability on interannual timescale can result in a sea level variability of at least −5 dyn cm to +6 dyn cm. These results suggest that the sea level discrepancy in 1996 is likely due to inadequate salinity information both in estimating dynamic height from TAO temperature and in the data assimilation system used here, which corrects only temperature field.
The sea level error that resulted from inadequate salinity variability has a significant projection onto the second sea level anomaly EOF, which is linked to the onset phase of ENSO. This suggests that the error in the ocean initial conditions due to underestimate of interannual salinity variations in 1996 could impact the accuracy of ENSO prediction. Results from a twin experiment that uses two summer 1996 ocean initial conditions to hindcast for winter 1996/97 equatorial Pacific SST anomalies appear to support this hypothesis.
The results also pointed to a weakness of the present univariate assimilation system, which corrects only temperature. The improved sea level variability comes at the expense of reduced accuracy in temperature. A better solution would be a bivariate data assimilation system, which corrects both salinity and temperature, producing more accurate and consistent ocean initial conditions for ENSO prediction.
Abstract
In this study, two sets of Pacific Ocean analyses for 1993–96 were analyzed. Both analyses were produced with the assimilation of subsurface temperature data from expendable bathythermographs and tropical atmosphere–ocean moorings. In addition one analysis also assimilated sea level data from TOPEX/Poseidon. Sea level variability in the two analyses agreed well with each other, and both agree with tide gauge and altimetry data for 1993–95. However, beginning in late 1995 through 1996, large sea level differences of 5–8 cm were found in the tropical western Pacific between the two analyses. Furthermore, large sea level discrepancies were also found between dynamic height estimated from TAO temperatures and tide gauge–altimetry observations in the same region during 1996. These discrepancies are consistent with the sea level differences between the two model based analyses.
Historical conductivity–temperature–depth data along 165°E near the equator were also analyzed and it was found that salinity variability on interannual timescale can result in a sea level variability of at least −5 dyn cm to +6 dyn cm. These results suggest that the sea level discrepancy in 1996 is likely due to inadequate salinity information both in estimating dynamic height from TAO temperature and in the data assimilation system used here, which corrects only temperature field.
The sea level error that resulted from inadequate salinity variability has a significant projection onto the second sea level anomaly EOF, which is linked to the onset phase of ENSO. This suggests that the error in the ocean initial conditions due to underestimate of interannual salinity variations in 1996 could impact the accuracy of ENSO prediction. Results from a twin experiment that uses two summer 1996 ocean initial conditions to hindcast for winter 1996/97 equatorial Pacific SST anomalies appear to support this hypothesis.
The results also pointed to a weakness of the present univariate assimilation system, which corrects only temperature. The improved sea level variability comes at the expense of reduced accuracy in temperature. A better solution would be a bivariate data assimilation system, which corrects both salinity and temperature, producing more accurate and consistent ocean initial conditions for ENSO prediction.
Abstract
The purpose of this paper is to investigate two satellite instruments for SST: the infrared (IR) Advanced Along Track Scanning Radiometer (AATSR) and the microwave (MW) Tropical Rainfall Measuring Mission (TRMM) Microwave Imager (TMI). Because of its dual view, AATSR has a potential for lower biases than other IR products such as the Advanced Very High Resolution Radiometer (AVHRR), while the tropical TMI record was available for a longer period of time than the global MW instrument, the Advanced Microwave Scanning Radiometer (AMSR).
The results show that the AATSR IR retrievals are good quality with biases lower than or as low as other satellite retrievals between 50°S and 50°N. Furthermore, the dual-view algorithm reduces the influence of aerosol contamination. However, the AATSR coverage is roughly half that of AVHRR. North of 50°N there appear to be biases and high variability in summer daytime retrievals, with smaller but consistent biases observed below 50°S. TMI data can significantly improve coverage offshore in regions where IR retrievals are reduced by cloud cover. However, TMI data have small-scale biases from land contamination that should be removed by modifying the land–sea mask to remove more coastal regions.
Abstract
The purpose of this paper is to investigate two satellite instruments for SST: the infrared (IR) Advanced Along Track Scanning Radiometer (AATSR) and the microwave (MW) Tropical Rainfall Measuring Mission (TRMM) Microwave Imager (TMI). Because of its dual view, AATSR has a potential for lower biases than other IR products such as the Advanced Very High Resolution Radiometer (AVHRR), while the tropical TMI record was available for a longer period of time than the global MW instrument, the Advanced Microwave Scanning Radiometer (AMSR).
The results show that the AATSR IR retrievals are good quality with biases lower than or as low as other satellite retrievals between 50°S and 50°N. Furthermore, the dual-view algorithm reduces the influence of aerosol contamination. However, the AATSR coverage is roughly half that of AVHRR. North of 50°N there appear to be biases and high variability in summer daytime retrievals, with smaller but consistent biases observed below 50°S. TMI data can significantly improve coverage offshore in regions where IR retrievals are reduced by cloud cover. However, TMI data have small-scale biases from land contamination that should be removed by modifying the land–sea mask to remove more coastal regions.
