Search Results
You are looking at 1 - 5 of 5 items for :
- Author or Editor: Richard W. Reynolds x
- Journal of Atmospheric and Oceanic Technology x
- Refine by Access: All Content x
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.
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.
Abstract
Equatorial Pacific current and temperature fields were simulated with and without assimilation of subsurface temperature measurements for April 1992–March 1995 and compared with moored buoy and research vessel current measurements. Data assimilation intensified the mean east–west slope of the thermocline along the equator in the eastern Pacific, shifted eastward the longitude of the mean Equatorial Undercurrent (EUC) maximum speed 800 km to 125°W, and produced a 25% stronger mean EUC core speed in the eastern Pacific. In the eastern Pacific the mean EUC core speed simulated with data assimilation was slightly more representative of observations compared to that computed without data assimilated; in the western Pacific the data assimilation had no impact on mean EUC simulations.
Data assimilation intensified the north–south slope of the thermocline south of the equator in the western Pacific to produce a thicker and more intense westward-flowing South Equatorial Current (SEC) in the western Pacific. In the western Pacific the mean SEC transport per unit width simulated with data assimilation was more representative of observations compared to that computed without data assimilation. However, large differences remained between the observed SEC transport per unit width and that simulated with data assimilation. In the eastern Pacific, the data assimilation had no impact on mean SEC simulations.
The temporal variability of monthly mean EUC core speeds and SEC transports per unit width were increased significantly by data assimilation. It also increased the representativeness of monthly mean SEC transports per unit width to the observations. However, the data representativeness of monthly mean EUC core speeds was decreased. Results could be explained by the coupling between zonal gradient of temperature and EUC and between meridional gradient of temperature and SEC. Longitudinal variations along the Pacific equator of the impact of data assimilation on the EUC and SEC precludes the choice of a single site to evaluate the effectiveness of data assimilation schemes.
Abstract
Equatorial Pacific current and temperature fields were simulated with and without assimilation of subsurface temperature measurements for April 1992–March 1995 and compared with moored buoy and research vessel current measurements. Data assimilation intensified the mean east–west slope of the thermocline along the equator in the eastern Pacific, shifted eastward the longitude of the mean Equatorial Undercurrent (EUC) maximum speed 800 km to 125°W, and produced a 25% stronger mean EUC core speed in the eastern Pacific. In the eastern Pacific the mean EUC core speed simulated with data assimilation was slightly more representative of observations compared to that computed without data assimilated; in the western Pacific the data assimilation had no impact on mean EUC simulations.
Data assimilation intensified the north–south slope of the thermocline south of the equator in the western Pacific to produce a thicker and more intense westward-flowing South Equatorial Current (SEC) in the western Pacific. In the western Pacific the mean SEC transport per unit width simulated with data assimilation was more representative of observations compared to that computed without data assimilation. However, large differences remained between the observed SEC transport per unit width and that simulated with data assimilation. In the eastern Pacific, the data assimilation had no impact on mean SEC simulations.
The temporal variability of monthly mean EUC core speeds and SEC transports per unit width were increased significantly by data assimilation. It also increased the representativeness of monthly mean SEC transports per unit width to the observations. However, the data representativeness of monthly mean EUC core speeds was decreased. Results could be explained by the coupling between zonal gradient of temperature and EUC and between meridional gradient of temperature and SEC. Longitudinal variations along the Pacific equator of the impact of data assimilation on the EUC and SEC precludes the choice of a single site to evaluate the effectiveness of data assimilation schemes.
Abstract
Empirical orthogonal functions of the combined variability of temperature and salinity have been used as basis functions for the indirect reconstruction of salinity from observations of temperature alone. The method employs a weighted least squares procedure that minimizes the misfit between the reconstructed temperature and the observed temperature, but also constrains the variability of the reconstructed salinity to remain within specified bounds.
The method has been tested by fitting to temperature profiles from the Tropical Atmosphere Ocean array along 165°E in the western equatorial Pacific Ocean (8°N–8°S) for the 1986–97 period. Comparisons of the reconstructed salinity field with sea surface salinity and conductivity–temperature–depth data and of the reconstructed dynamic height with TOPEX/Poseidon observations of sea level demonstrate the reliability of the method. The reconstructed data successfully capture the upper-ocean variability at annual to ENSO timescales. The impact of neglecting salinity variability on the dynamic height anomaly in the western tropical Pacific Ocean is addressed.
Abstract
Empirical orthogonal functions of the combined variability of temperature and salinity have been used as basis functions for the indirect reconstruction of salinity from observations of temperature alone. The method employs a weighted least squares procedure that minimizes the misfit between the reconstructed temperature and the observed temperature, but also constrains the variability of the reconstructed salinity to remain within specified bounds.
The method has been tested by fitting to temperature profiles from the Tropical Atmosphere Ocean array along 165°E in the western equatorial Pacific Ocean (8°N–8°S) for the 1986–97 period. Comparisons of the reconstructed salinity field with sea surface salinity and conductivity–temperature–depth data and of the reconstructed dynamic height with TOPEX/Poseidon observations of sea level demonstrate the reliability of the method. The reconstructed data successfully capture the upper-ocean variability at annual to ENSO timescales. The impact of neglecting salinity variability on the dynamic height anomaly in the western tropical Pacific Ocean is addressed.
Abstract
The equatorial sea level analysis of the National Centers for Environmental Predictions deviates by as much as 8 cm from independent TOPEX/Poseidon (T/P) observations. This may be due to the model’s underestimation of salinity variability. Therefore, methods are developed to improve the model’s salinity field through T/P data assimilation and use of sea surface salinity (SSS) observations.
In regions where temperature is well known, salinity estimates are made with the use of climatological temperature–salinity (T–S) correlations. These estimates are improved by combining T–S with SSS observations and corrected with dynamic height, which provides information on salinity variability. Tests with independent conductivity temperature depth data show that the combination of T–S with SSS significantly improves salinity estimates. In the western Pacific, the maximum root-mean-square (rms) estimation error of 0.55 psu is reduced to 0.42 psu by the use of SSS in the salinity estimate. Correction with dynamic height reduces this rms to 0.22 psu. Also in other parts of the tropical Pacific Ocean the salinity estimation errors are reduced by a factor of 2 by combination of the T–S estimate with SSS and dynamic height. This study provides the first step toward an assimilation scheme in which salinity is corrected with the use of T/P sea level observations.
Abstract
The equatorial sea level analysis of the National Centers for Environmental Predictions deviates by as much as 8 cm from independent TOPEX/Poseidon (T/P) observations. This may be due to the model’s underestimation of salinity variability. Therefore, methods are developed to improve the model’s salinity field through T/P data assimilation and use of sea surface salinity (SSS) observations.
In regions where temperature is well known, salinity estimates are made with the use of climatological temperature–salinity (T–S) correlations. These estimates are improved by combining T–S with SSS observations and corrected with dynamic height, which provides information on salinity variability. Tests with independent conductivity temperature depth data show that the combination of T–S with SSS significantly improves salinity estimates. In the western Pacific, the maximum root-mean-square (rms) estimation error of 0.55 psu is reduced to 0.42 psu by the use of SSS in the salinity estimate. Correction with dynamic height reduces this rms to 0.22 psu. Also in other parts of the tropical Pacific Ocean the salinity estimation errors are reduced by a factor of 2 by combination of the T–S estimate with SSS and dynamic height. This study provides the first step toward an assimilation scheme in which salinity is corrected with the use of T/P sea level observations.
Abstract
A method is presented to evaluate the adequacy of the recent in situ network for climate sea surface temperature (SST) analyses using both in situ and satellite observations. Satellite observations provide superior spatiotemporal coverage, but with biases; in situ data are needed to correct the satellite biases. Recent NOAA/U.S. Navy operational Advanced Very High Resolution Radiometer (AVHRR) satellite SST biases were analyzed to extract typical bias patterns and scales. Occasional biases of 2°C were found during large volcano eruptions and near the end of the satellite instruments’ lifetime. Because future biases could not be predicted, the in situ network was designed to reduce the large biases that have occurred to a required accuracy. Simulations with different buoy density were used to examine their ability to correct the satellite biases and to define the residual bias as a potential satellite bias error (PSBE).
The PSBE and buoy density (BD) relationship was found to be nearly exponential, resulting in an optimal BD range of 2–3 per 10° × 10° box for efficient PSBE reduction. A BD of two buoys per 10° × 10° box reduces a 2°C maximum bias to below 0.5°C and reduces a 1°C maximum bias to about 0.3°C. The present in situ SST observing system was evaluated to define an equivalent buoy density (EBD), allowing ships to be used along with buoys according to their random errors. Seasonally averaged monthly EBD maps were computed to determine where additional buoys are needed for future deployments. Additionally, a PSBE was computed from the present EBD to assess the in situ system’s adequacy to remove potential future satellite biases.
Abstract
A method is presented to evaluate the adequacy of the recent in situ network for climate sea surface temperature (SST) analyses using both in situ and satellite observations. Satellite observations provide superior spatiotemporal coverage, but with biases; in situ data are needed to correct the satellite biases. Recent NOAA/U.S. Navy operational Advanced Very High Resolution Radiometer (AVHRR) satellite SST biases were analyzed to extract typical bias patterns and scales. Occasional biases of 2°C were found during large volcano eruptions and near the end of the satellite instruments’ lifetime. Because future biases could not be predicted, the in situ network was designed to reduce the large biases that have occurred to a required accuracy. Simulations with different buoy density were used to examine their ability to correct the satellite biases and to define the residual bias as a potential satellite bias error (PSBE).
The PSBE and buoy density (BD) relationship was found to be nearly exponential, resulting in an optimal BD range of 2–3 per 10° × 10° box for efficient PSBE reduction. A BD of two buoys per 10° × 10° box reduces a 2°C maximum bias to below 0.5°C and reduces a 1°C maximum bias to about 0.3°C. The present in situ SST observing system was evaluated to define an equivalent buoy density (EBD), allowing ships to be used along with buoys according to their random errors. Seasonally averaged monthly EBD maps were computed to determine where additional buoys are needed for future deployments. Additionally, a PSBE was computed from the present EBD to assess the in situ system’s adequacy to remove potential future satellite biases.
