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- Author or Editor: Rong Zhang x
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Abstract
High-resolution space-based observations reveal significant two-way air–sea interactions associated with tropical instability waves (TIWs); their roles in budgets of heat, salt, momentum, and biogeochemical fields in the tropical oceans have been recently demonstrated. However, dynamical model-based simulations of the atmospheric response to TIW-induced sea surface temperature (SSTTIW) perturbations remain a great challenge because of the limitation in spatial resolution and realistic representations of the related processes in the atmospheric planetary boundary layer (PBL) and their interactions with the overlying free troposphere. Using microwave remote sensing data, an empirical model is derived to depict wind stress perturbations induced by TIW-related SST forcing in the eastern tropical Pacific Ocean. Wind data are based on space–time blending of Quick Scatterometer (QuikSCAT) Direction Interval Retrieval with Thresholded Nudging (DIRTH) satellite observations and NCEP analysis fields; SST data are from the Tropical Rainfall Measuring Mission (TRMM) Microwave Imager (TMI). These daily data are first subject to a spatial filter of 12° moving average in the zonal direction to extract TIW-related wind stress (τTIW) and SSTTIW perturbations. A combined singular value decomposition (SVD) analysis is then applied to these zonal high-pass-filtered τTIW and SSTTIW fields. It is demonstrated that the SVD-based analysis technique can effectively extract TIW-induced covariability patterns in the atmosphere and ocean, acting as a filter by passing wind signals that are directly related with the SSTTIW forcing over the TIW active regions. As a result, the empirical model can well represent TIW-induced wind stress responses as revealed directly from satellite measurements (e.g., the structure and phase), but the amplitude can be underestimated significantly. Validation and sensitivity experiments are performed to illustrate the robustness of the empirical τTIW model. Further applications are discussed for taking into account the TIW-induced wind responses and feedback effects that are missing in large-scale climate models and atmospheric reanalysis data, as well as for uncoupled ocean and coupled mesoscale and large-scale air–sea modeling studies.
Abstract
High-resolution space-based observations reveal significant two-way air–sea interactions associated with tropical instability waves (TIWs); their roles in budgets of heat, salt, momentum, and biogeochemical fields in the tropical oceans have been recently demonstrated. However, dynamical model-based simulations of the atmospheric response to TIW-induced sea surface temperature (SSTTIW) perturbations remain a great challenge because of the limitation in spatial resolution and realistic representations of the related processes in the atmospheric planetary boundary layer (PBL) and their interactions with the overlying free troposphere. Using microwave remote sensing data, an empirical model is derived to depict wind stress perturbations induced by TIW-related SST forcing in the eastern tropical Pacific Ocean. Wind data are based on space–time blending of Quick Scatterometer (QuikSCAT) Direction Interval Retrieval with Thresholded Nudging (DIRTH) satellite observations and NCEP analysis fields; SST data are from the Tropical Rainfall Measuring Mission (TRMM) Microwave Imager (TMI). These daily data are first subject to a spatial filter of 12° moving average in the zonal direction to extract TIW-related wind stress (τTIW) and SSTTIW perturbations. A combined singular value decomposition (SVD) analysis is then applied to these zonal high-pass-filtered τTIW and SSTTIW fields. It is demonstrated that the SVD-based analysis technique can effectively extract TIW-induced covariability patterns in the atmosphere and ocean, acting as a filter by passing wind signals that are directly related with the SSTTIW forcing over the TIW active regions. As a result, the empirical model can well represent TIW-induced wind stress responses as revealed directly from satellite measurements (e.g., the structure and phase), but the amplitude can be underestimated significantly. Validation and sensitivity experiments are performed to illustrate the robustness of the empirical τTIW model. Further applications are discussed for taking into account the TIW-induced wind responses and feedback effects that are missing in large-scale climate models and atmospheric reanalysis data, as well as for uncoupled ocean and coupled mesoscale and large-scale air–sea modeling studies.
Abstract
A new intermediate coupled model (ICM) is presented and employed to make retrospective predictions of tropical Pacific sea surface temperature (SST) anomalies. The ocean dynamics is an extension of the McCreary baroclinic modal model to include varying stratification and certain nonlinear effects. A standard configuration is chosen with 10 baroclinic modes plus two surface layers, which are governed by Ekman dynamics and simulate the combined effects of the higher baroclinic modes from 11 to 30. A nonlinear correction associated with vertical advection of zonal momentum is incorporated and applied (diagnostically) only within the two surface layers, forced by the linear part through nonlinear advection terms. As a result of these improvements, the model realistically simulates the mean equatorial circulation and its variability. The ocean thermodynamics include an SST anomaly model with an empirical parameterization for the temperature of subsurface water entrained into the mixed layer (Te ), which is optimally calculated in terms of sea surface height (SSH) anomalies using an empirical orthogonal function (EOF) analysis technique from historical data. The ocean model is then coupled to a statistical atmospheric model that estimates wind stress (τ) anomalies based on a singular value decomposition (SVD) analysis between SST anomalies observed and τ anomalies simulated from ECHAM4.5 (24-member ensemble mean). The coupled system exhibits realistic interannual variability associated with El Niño, including a predominant standing pattern of SST anomalies along the equator and coherent phase relationships among different atmosphere–ocean anomaly fields with a dominant 3-yr oscillation period.
Twelve-month hindcasts/forecasts are made during the period 1963–2002, starting each month. Only observed SST anomalies are used to initialize the coupled predictions. As compared to other prediction systems, this coupled model has relatively small systematic errors in the predicted SST anomalies, and its SST prediction skill is apparently competitive with that of most advanced coupled systems incorporating sophisticated ocean data assimilation. One striking feature is that the model skill surpasses that of persistence at all lead times over the central equatorial Pacific. Prediction skill is strongly dependent on the season, with the correlations attaining a minimum in spring and a maximum in fall. Cross-validation experiments are performed to examine the sensitivity of the prediction skill to the data periods selected for training the empirical Te model. It is demonstrated that the artificial skill introduced by using a dependently constructed Te model is not significant. Independent forecasts are made for the period 1997–2002 when no dependent data are included in constructing the two empirical models (Te and τ). The coupled model has reasonable success in predicting transition to warm phase and to cold phase in the spring of 1997 and 1998, respectively. Potential problems and further improvements are discussed with the new intermediate prediction system.
Abstract
A new intermediate coupled model (ICM) is presented and employed to make retrospective predictions of tropical Pacific sea surface temperature (SST) anomalies. The ocean dynamics is an extension of the McCreary baroclinic modal model to include varying stratification and certain nonlinear effects. A standard configuration is chosen with 10 baroclinic modes plus two surface layers, which are governed by Ekman dynamics and simulate the combined effects of the higher baroclinic modes from 11 to 30. A nonlinear correction associated with vertical advection of zonal momentum is incorporated and applied (diagnostically) only within the two surface layers, forced by the linear part through nonlinear advection terms. As a result of these improvements, the model realistically simulates the mean equatorial circulation and its variability. The ocean thermodynamics include an SST anomaly model with an empirical parameterization for the temperature of subsurface water entrained into the mixed layer (Te ), which is optimally calculated in terms of sea surface height (SSH) anomalies using an empirical orthogonal function (EOF) analysis technique from historical data. The ocean model is then coupled to a statistical atmospheric model that estimates wind stress (τ) anomalies based on a singular value decomposition (SVD) analysis between SST anomalies observed and τ anomalies simulated from ECHAM4.5 (24-member ensemble mean). The coupled system exhibits realistic interannual variability associated with El Niño, including a predominant standing pattern of SST anomalies along the equator and coherent phase relationships among different atmosphere–ocean anomaly fields with a dominant 3-yr oscillation period.
Twelve-month hindcasts/forecasts are made during the period 1963–2002, starting each month. Only observed SST anomalies are used to initialize the coupled predictions. As compared to other prediction systems, this coupled model has relatively small systematic errors in the predicted SST anomalies, and its SST prediction skill is apparently competitive with that of most advanced coupled systems incorporating sophisticated ocean data assimilation. One striking feature is that the model skill surpasses that of persistence at all lead times over the central equatorial Pacific. Prediction skill is strongly dependent on the season, with the correlations attaining a minimum in spring and a maximum in fall. Cross-validation experiments are performed to examine the sensitivity of the prediction skill to the data periods selected for training the empirical Te model. It is demonstrated that the artificial skill introduced by using a dependently constructed Te model is not significant. Independent forecasts are made for the period 1997–2002 when no dependent data are included in constructing the two empirical models (Te and τ). The coupled model has reasonable success in predicting transition to warm phase and to cold phase in the spring of 1997 and 1998, respectively. Potential problems and further improvements are discussed with the new intermediate prediction system.
Abstract
Freshwater flux (FWF) forcing–induced feedback has not been represented adequately in many coupled ocean–atmosphere models of the tropical Pacific. Previously, various approximations have been made in representing the FWF forcing in climate modeling. In this article, using a hybrid coupled model (HCM), sensitivity experiments are performed to examine the extent to which this forcing and related feedback effects can contribute to tropical biases in interannual simulations of the tropical Pacific. The total FWF into the ocean, represented by precipitation (P) minus evaporation (E), (P − E), is separated into its climatological part and interannual anomaly part: FWFTotal = (P − E)clim + FWFinter. The former can be prescribed (seasonally varying); the latter can be captured using an empirical model linking with large-scale sea surface temperature (SST) variability. Four cases are considered with different FWFinter specifications: interannual (P − E) forcing [FWFinter = (P − E)inter], interannual P forcing (FWFinter = P inter), interannual E forcing (FWFinter = −E inter), and climatological (P − E) forcing (FWFinter = 0.0), respectively. The HCM-based experiments indicate that different FWFinter approximations can modulate interannual variability in a substantial way. The HCM with the interannual (P − E) forcing, in which a positive SST − (P − E)inter feedback is included explicitly, has a reasonably realistic simulation of interannual variability. When FWFinter is approximated in some ways, the simulated interannual variability can be modulated significantly: it is weakened with the climatological (P − E) forcing and is even more damped with the interannual E forcing, but is exaggerated with the interannual P forcing. Quantitatively, taking the interannual (P − E) forcing run as a reference, the Niño-3 SST variance can be reduced by about 12% and 26% in the climatological (P − E) forcing run and interannual E forcing run, respectively, but overestimated by 11% in the P inter forcing run. It is demonstrated that FWF can be a clear bias source for coupled model simulations in the tropical Pacific.
Abstract
Freshwater flux (FWF) forcing–induced feedback has not been represented adequately in many coupled ocean–atmosphere models of the tropical Pacific. Previously, various approximations have been made in representing the FWF forcing in climate modeling. In this article, using a hybrid coupled model (HCM), sensitivity experiments are performed to examine the extent to which this forcing and related feedback effects can contribute to tropical biases in interannual simulations of the tropical Pacific. The total FWF into the ocean, represented by precipitation (P) minus evaporation (E), (P − E), is separated into its climatological part and interannual anomaly part: FWFTotal = (P − E)clim + FWFinter. The former can be prescribed (seasonally varying); the latter can be captured using an empirical model linking with large-scale sea surface temperature (SST) variability. Four cases are considered with different FWFinter specifications: interannual (P − E) forcing [FWFinter = (P − E)inter], interannual P forcing (FWFinter = P inter), interannual E forcing (FWFinter = −E inter), and climatological (P − E) forcing (FWFinter = 0.0), respectively. The HCM-based experiments indicate that different FWFinter approximations can modulate interannual variability in a substantial way. The HCM with the interannual (P − E) forcing, in which a positive SST − (P − E)inter feedback is included explicitly, has a reasonably realistic simulation of interannual variability. When FWFinter is approximated in some ways, the simulated interannual variability can be modulated significantly: it is weakened with the climatological (P − E) forcing and is even more damped with the interannual E forcing, but is exaggerated with the interannual P forcing. Quantitatively, taking the interannual (P − E) forcing run as a reference, the Niño-3 SST variance can be reduced by about 12% and 26% in the climatological (P − E) forcing run and interannual E forcing run, respectively, but overestimated by 11% in the P inter forcing run. It is demonstrated that FWF can be a clear bias source for coupled model simulations in the tropical Pacific.
