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Abstract
A simple example of the steady motion of a rotating, stratified fluid is studied. The solution which is uniformly valid for all values of the stratification, σsδ = vαgDΔT/(κf 2 L 2), is presented. The transitions in the dynamics from the homogeneous limit to strong stratification are illustrated in detail. The motion is driven by a stress. Consequently, Ekman suction is weaker than in cases where the driving force is a moving boundary, and Ekman layers are important until a stratification of O(1) at which point they combine with Lineykin layers to form the thermal equivalent of the Stewartson E½ layer.
Abstract
A simple example of the steady motion of a rotating, stratified fluid is studied. The solution which is uniformly valid for all values of the stratification, σsδ = vαgDΔT/(κf 2 L 2), is presented. The transitions in the dynamics from the homogeneous limit to strong stratification are illustrated in detail. The motion is driven by a stress. Consequently, Ekman suction is weaker than in cases where the driving force is a moving boundary, and Ekman layers are important until a stratification of O(1) at which point they combine with Lineykin layers to form the thermal equivalent of the Stewartson E½ layer.
Abstract
The role of local heating in producing annual and interannual sea-surface temperature variations in the eastern tropical Pacific is studied. Removed from the eastern boundary (122°W), and off the equator, local heating plays a major role in producing annual temperature fluctuations. At the same longitudes from 10°N to 10°S interannual variations in the yearly-average temperature and the anomalous net heat input into the ocean are of the same sign and magnitude. During the 1969 and 1972 mean warmings there was increased heat input into the ocean. Closer to the eastern boundary, oceanic processes such as advection are as important as local heating. Results from a simple model incorporating local heating, offshore Ekman transports, and upwelling suggest the following scenario for the 1972–73 El Niño. During February and March 1972 enhanced local heating and reduced offshore advection were the main reasons for anomalously warm temperatures in the open ocean adjacent to Peruvian coastal waters. From April 1972 to March 1973 temperatures remained high because of offshore transport of anomalously warm inshore waters. Whether the latter were warm because of upwelling of warmer water or transport of warmer water from farther south is not clear.
Abstract
The role of local heating in producing annual and interannual sea-surface temperature variations in the eastern tropical Pacific is studied. Removed from the eastern boundary (122°W), and off the equator, local heating plays a major role in producing annual temperature fluctuations. At the same longitudes from 10°N to 10°S interannual variations in the yearly-average temperature and the anomalous net heat input into the ocean are of the same sign and magnitude. During the 1969 and 1972 mean warmings there was increased heat input into the ocean. Closer to the eastern boundary, oceanic processes such as advection are as important as local heating. Results from a simple model incorporating local heating, offshore Ekman transports, and upwelling suggest the following scenario for the 1972–73 El Niño. During February and March 1972 enhanced local heating and reduced offshore advection were the main reasons for anomalously warm temperatures in the open ocean adjacent to Peruvian coastal waters. From April 1972 to March 1973 temperatures remained high because of offshore transport of anomalously warm inshore waters. Whether the latter were warm because of upwelling of warmer water or transport of warmer water from farther south is not clear.
Abstract
In this study, the authors compare skills of forecasts of tropical Pacific sea surface temperatures from the National Centers for Environmental Prediction (NCEP) coupled general circulation model that were initiated using different sets of ocean initial conditions. These were produced with and without assimilation of observed subsurface upper-ocean temperature data from expendable bathythermographs (XBTs) and from the Tropical Ocean Global Atmosphere–Tropical Atmosphere Ocean (TOGA–TAO) buoys.
These experiments show that assimilation of observed subsurface temperature data in the determining of the initial conditions, especially for summer and fall starts, results in significantly improved forecasts for the NCEP coupled model. The assimilation compensates for errors in the forcing fields and inadequate physical parameterizations in the ocean model. Furthermore, additional skill improvements, over that provided by XBT assimilation, result from assimilation of subsurface temperature data collected by the TOGA–TAO buoys. This is a consequence of the current predominance of TAO data in the tropical Pacific in recent years.
Results suggest that in the presence of erroneous wind forcing and inadequate physical parameterizations in the ocean model ocean data assimilation can improve ocean initialization and thus can improve the skill of the forecasts. However, the need for assimilation can create imbalances between the mean states of the oceanic initial conditions and the coupled model. These imbalances and errors in the coupled model can be significant limiting factors to forecast skill, especially for forecasts initiated in the northern winter. These limiting factors cannot be avoided by using data assimilation and must be corrected by improving the models and the forcing fields.
Abstract
In this study, the authors compare skills of forecasts of tropical Pacific sea surface temperatures from the National Centers for Environmental Prediction (NCEP) coupled general circulation model that were initiated using different sets of ocean initial conditions. These were produced with and without assimilation of observed subsurface upper-ocean temperature data from expendable bathythermographs (XBTs) and from the Tropical Ocean Global Atmosphere–Tropical Atmosphere Ocean (TOGA–TAO) buoys.
These experiments show that assimilation of observed subsurface temperature data in the determining of the initial conditions, especially for summer and fall starts, results in significantly improved forecasts for the NCEP coupled model. The assimilation compensates for errors in the forcing fields and inadequate physical parameterizations in the ocean model. Furthermore, additional skill improvements, over that provided by XBT assimilation, result from assimilation of subsurface temperature data collected by the TOGA–TAO buoys. This is a consequence of the current predominance of TAO data in the tropical Pacific in recent years.
Results suggest that in the presence of erroneous wind forcing and inadequate physical parameterizations in the ocean model ocean data assimilation can improve ocean initialization and thus can improve the skill of the forecasts. However, the need for assimilation can create imbalances between the mean states of the oceanic initial conditions and the coupled model. These imbalances and errors in the coupled model can be significant limiting factors to forecast skill, especially for forecasts initiated in the northern winter. These limiting factors cannot be avoided by using data assimilation and must be corrected by improving the models and the forcing fields.
Abstract
The link between El Niño and the California wintertime rainfall has been reported in various studies. During the winter of 1994/95, warm sea surface temperature anomalies (SSTAs) were observed in the central Pacific, and widespread significant flooding occurred in California during January 1995 and March 1995. However, the El Niño–Southern Oscillation alone cannot explain the flooding. In March 1995 California suffered flooding after the warm SSTA over the central Pacific had weakened considerably. During November and December, in spite of El Niño conditions, California was not flooded, and more than two standard deviations above normal SSTA in the North Pacific were observed. A possible link between midlatitude warm SSTA and the timing of the onset of flooding is suspected within the seasonal forecasting community.
The climate condition during the northern winter of 1994/95 is described using the National Centers for Environmental Prediction–National Center for Atmospheric Research reanalysis data. Diagnostics show the typical El Niño pattern in the seasonal mean and the link between the position of the jet exit and the flooding over California on the intraseasonal timescale.
The relationship among California floods, the Pacific jet, tropical rainfall, and SSTA is inferred from results of general circulation model (GCM) experiments with various SSTAs. The results show that the rainfall over California is associated with an eastward extension of the Pacific jet, which itself is associated with enhanced tropical convection over the warm SSTA in the central Pacific. The GCM experiments also show that rainfall over the Indian Ocean can contribute to the weakening of the Pacific jet and to dryness over California. The GCM experiments did not show significant impact of North Pacific SSTA, either upon the Pacific jet or upon rainfall over California. The agreement with diagnostics results is discussed. GCM experiments suggest the link between the tropical intraseasonal oscillation (TIO) and the flooding in March in California, since there is a strong TIO component in rainfall over the Indian Ocean.
Abstract
The link between El Niño and the California wintertime rainfall has been reported in various studies. During the winter of 1994/95, warm sea surface temperature anomalies (SSTAs) were observed in the central Pacific, and widespread significant flooding occurred in California during January 1995 and March 1995. However, the El Niño–Southern Oscillation alone cannot explain the flooding. In March 1995 California suffered flooding after the warm SSTA over the central Pacific had weakened considerably. During November and December, in spite of El Niño conditions, California was not flooded, and more than two standard deviations above normal SSTA in the North Pacific were observed. A possible link between midlatitude warm SSTA and the timing of the onset of flooding is suspected within the seasonal forecasting community.
The climate condition during the northern winter of 1994/95 is described using the National Centers for Environmental Prediction–National Center for Atmospheric Research reanalysis data. Diagnostics show the typical El Niño pattern in the seasonal mean and the link between the position of the jet exit and the flooding over California on the intraseasonal timescale.
The relationship among California floods, the Pacific jet, tropical rainfall, and SSTA is inferred from results of general circulation model (GCM) experiments with various SSTAs. The results show that the rainfall over California is associated with an eastward extension of the Pacific jet, which itself is associated with enhanced tropical convection over the warm SSTA in the central Pacific. The GCM experiments also show that rainfall over the Indian Ocean can contribute to the weakening of the Pacific jet and to dryness over California. The GCM experiments did not show significant impact of North Pacific SSTA, either upon the Pacific jet or upon rainfall over California. The agreement with diagnostics results is discussed. GCM experiments suggest the link between the tropical intraseasonal oscillation (TIO) and the flooding in March in California, since there is a strong TIO component in rainfall over the Indian Ocean.
Abstract
Vertical profiles of current, temperature and salinity were taken in the upper ocean from 3°S to 2°N along 55°30′E in the Indian Ocean during February–June in 1975 and 1976. During both years a strong O(80 cm s−1) equatorial undercurrent was present throughout the measurement period in the vicinity of the equator. A second region of eastward flow above the thermocline was observed at 3°S. During May and June the undercurrent moved southward and merged with the southern region of eastward flow. The meridional flow field was dominated by transients that during strong events were antisymmetric about the equator and had a vertical wavelength of ∼180 m. The transient events strongly affected the zonal flow field; during strong events the undercurrent was almost eliminated. This is in contrast to the GATE observations where the undercurrent was advected back and forth across the equator.
Abstract
Vertical profiles of current, temperature and salinity were taken in the upper ocean from 3°S to 2°N along 55°30′E in the Indian Ocean during February–June in 1975 and 1976. During both years a strong O(80 cm s−1) equatorial undercurrent was present throughout the measurement period in the vicinity of the equator. A second region of eastward flow above the thermocline was observed at 3°S. During May and June the undercurrent moved southward and merged with the southern region of eastward flow. The meridional flow field was dominated by transients that during strong events were antisymmetric about the equator and had a vertical wavelength of ∼180 m. The transient events strongly affected the zonal flow field; during strong events the undercurrent was almost eliminated. This is in contrast to the GATE observations where the undercurrent was advected back and forth across the equator.
Abstract
A dynamical model-based ocean analysis system has been implemented at the National Meteorological Center (NMC). This is used to provide retrospective and routine weekly analyses for the Pacific and Atlantic Oceans. Retrospective analyses have been performed for the period mid-1982 to mid-1993. The analyses are used for diagnostics of past climatic variability, real-time climate monitoring, and as initial conditions for coupled multiseason forecasts. The assimilation system is based on optimal interpolation objective analysis solved using an equivalent variational formulation. Analysis errors are estimated by comparisons to independent datasets such as temperature data from moorings and sea level information from tide gauges. In the near equatorial zone rms errors in thermocline depth are of order of 6–15 m. Comparisons of sea level estimates from the reanalyses with the records from tide gauges indicate that the rms sea level errors for monthly analysis are of the order of 0.04–0.09 m. For the weekly analyses, which potentially have more accurate forcing fields, the rms sea level errors am about 0.02–0.06 m.
The analysis system can be used to infer the net heat flux at the air–sea interface on mean annual and interannual timescales. Examination of the dominant components to the oceanic heat budget shows that advection, storage changes, and the net surface heat flux can all be of the same order of magnitude; however, frequently the net surface heat flux is much smaller than the other components. The annual variations in the components are as large or larger than the interannual variability. In the equatorial region interannual changes are of the order of 50–100 W m−2 and act as a negative feedback to the anomalous SSTs. In the subtropics the interannual variability is only in the order of 5–10 W m−2.
Principal component analysis of the monthly analyzed ocean fields revealed an interannual sea level and SST empirical orthogonal function that has an intradecadal timescale. This mode is characterized by meridional adjustments of the thermal field. It is probably forced by the changes in the curl of the stress caused by changes in the intensity and location of the trade winds associated with the ENSO.
Abstract
A dynamical model-based ocean analysis system has been implemented at the National Meteorological Center (NMC). This is used to provide retrospective and routine weekly analyses for the Pacific and Atlantic Oceans. Retrospective analyses have been performed for the period mid-1982 to mid-1993. The analyses are used for diagnostics of past climatic variability, real-time climate monitoring, and as initial conditions for coupled multiseason forecasts. The assimilation system is based on optimal interpolation objective analysis solved using an equivalent variational formulation. Analysis errors are estimated by comparisons to independent datasets such as temperature data from moorings and sea level information from tide gauges. In the near equatorial zone rms errors in thermocline depth are of order of 6–15 m. Comparisons of sea level estimates from the reanalyses with the records from tide gauges indicate that the rms sea level errors for monthly analysis are of the order of 0.04–0.09 m. For the weekly analyses, which potentially have more accurate forcing fields, the rms sea level errors am about 0.02–0.06 m.
The analysis system can be used to infer the net heat flux at the air–sea interface on mean annual and interannual timescales. Examination of the dominant components to the oceanic heat budget shows that advection, storage changes, and the net surface heat flux can all be of the same order of magnitude; however, frequently the net surface heat flux is much smaller than the other components. The annual variations in the components are as large or larger than the interannual variability. In the equatorial region interannual changes are of the order of 50–100 W m−2 and act as a negative feedback to the anomalous SSTs. In the subtropics the interannual variability is only in the order of 5–10 W m−2.
Principal component analysis of the monthly analyzed ocean fields revealed an interannual sea level and SST empirical orthogonal function that has an intradecadal timescale. This mode is characterized by meridional adjustments of the thermal field. It is probably forced by the changes in the curl of the stress caused by changes in the intensity and location of the trade winds associated with the ENSO.
Abstract
The evolution of oceanic and atmospheric anomaly fields for the period prior to and during the 1986–87 El Niño/Southem Oscillation (ENSO) is presented. A comparison is made between the 1986–87 ENSO and other warm episodes that occurred during the last 20 yr. In addition, for the first time, an ocean general circulation model was run in a real-time diagnostic mode. The model output provided detailed information about the evolution of subsurface features throughout the Pacific basin.
A slow trend towards warm episode (ENSO) conditions in the Pacific was evident throughout the period 1985–86 in certain atmospheric and oceanic variables. Atmospheric and oceanic fields changed much more rapidly during late 1986 as enhanced atmospheric convection developed in the equatorial Pacific near the date line. Thermocline depths rapidly increased (decreased) in the eastern (western) equatorial Pacific as low-level westerlies developed in the western portion of the basin. A remote response to those westerlies was felt along the west coast of South America in early 1987 as sea surface temperatures (SSTs) increased 3°–5°C above normal. Conditions remained anomalous in the tropical Pacific throughout 1987, but began a rapid return towards normal late in the year as low-level easterlies increased in strength. By the northern spring 1988, below normal SSTs were observed throughout the equatorial Pacific east of the date line.
Abstract
The evolution of oceanic and atmospheric anomaly fields for the period prior to and during the 1986–87 El Niño/Southem Oscillation (ENSO) is presented. A comparison is made between the 1986–87 ENSO and other warm episodes that occurred during the last 20 yr. In addition, for the first time, an ocean general circulation model was run in a real-time diagnostic mode. The model output provided detailed information about the evolution of subsurface features throughout the Pacific basin.
A slow trend towards warm episode (ENSO) conditions in the Pacific was evident throughout the period 1985–86 in certain atmospheric and oceanic variables. Atmospheric and oceanic fields changed much more rapidly during late 1986 as enhanced atmospheric convection developed in the equatorial Pacific near the date line. Thermocline depths rapidly increased (decreased) in the eastern (western) equatorial Pacific as low-level westerlies developed in the western portion of the basin. A remote response to those westerlies was felt along the west coast of South America in early 1987 as sea surface temperatures (SSTs) increased 3°–5°C above normal. Conditions remained anomalous in the tropical Pacific throughout 1987, but began a rapid return towards normal late in the year as low-level easterlies increased in strength. By the northern spring 1988, below normal SSTs were observed throughout the equatorial Pacific east of the date line.
Abstract
A series of seasonally varying linear Markov models are constructed in a reduced multivariate empirical orthogonal function (MEOF) space of observed sea surface temperature, surface wind stress, and sea level analysis. The Markov models are trained in the 1980–95 period and are verified in the 1964–79 period. It is found that the Markov models that include seasonality fit to the data better in the training period and have a substantially higher skill in the independent period than the models without seasonality. The authors conclude that seasonality is an important component of ENSO and should be included in Markov models. This conclusion is consistent with that of statistical models that take seasonality into account using different methods.
The impact of each variable on the prediction skill of Markov models is investigated by varying the weightings among the three variables in the MEOF space. For the training period the Markov models that include sea level information fit the data better than the models without sea level information. For the independent 1964–79 period, the Markov models that include sea level information have a much higher skill than the Markov models without sea level information. The authors conclude that sea level contains the most essential information for ENSO since it contains the filtered response of the ocean to noisy wind forcing.
The prediction skill of the Markov model with three MEOFs is competitive for both the training and independent periods. This Markov model successfully predicted the 1997/98 El Niño and the 1998/99 La Niña.
Abstract
A series of seasonally varying linear Markov models are constructed in a reduced multivariate empirical orthogonal function (MEOF) space of observed sea surface temperature, surface wind stress, and sea level analysis. The Markov models are trained in the 1980–95 period and are verified in the 1964–79 period. It is found that the Markov models that include seasonality fit to the data better in the training period and have a substantially higher skill in the independent period than the models without seasonality. The authors conclude that seasonality is an important component of ENSO and should be included in Markov models. This conclusion is consistent with that of statistical models that take seasonality into account using different methods.
The impact of each variable on the prediction skill of Markov models is investigated by varying the weightings among the three variables in the MEOF space. For the training period the Markov models that include sea level information fit the data better than the models without sea level information. For the independent 1964–79 period, the Markov models that include sea level information have a much higher skill than the Markov models without sea level information. The authors conclude that sea level contains the most essential information for ENSO since it contains the filtered response of the ocean to noisy wind forcing.
The prediction skill of the Markov model with three MEOFs is competitive for both the training and independent periods. This Markov model successfully predicted the 1997/98 El Niño and the 1998/99 La Niña.
The Coupled Model Project was established at the National Meteorological Center (NMC) in January 1991 to develop a multiseason forecast system based on coupled ocean-atmosphere general circulation models. This provided a focus to combine expertise in near real-time ocean modeling and analyses situated in the Climate Analysis Center (CAC) with expertise in atmospheric modeling and data assimilation in the Development Division. Since the inception of the project, considerable progress has been made toward establishing a coupled forecast system. A T40 version of NMC's operational global medium-range forecast model (MRF) has been modified so as to have improved response to boundary forcing from the Tropics. In extended simulations, which are forced with observed historical global sea surface temperature (SST) fields, the model reproduces much of the observed tropical Pacific and North American rainfall and temperature variability. An ocean reanalysis has been performed for the Pacific basin starting from July 1982 to present and uses a dynamical model-based assimilation system. This also provides the ocean initial conditions for coupled forecast experiments. The current coupled forecast model consists of an active Pacific Ocean model coupled to the T40 version of the NMC's MRF. In the future, a global ocean model will be used to include climate information from the other ocean basins. The initial experiments focused on forecasting Northern Hemisphere winter SST anomalies in the tropical Pacific with a lead time of two seasons. The coupled model showed considerable skill during these experiments. Work is currently under way to quantify the skill in predicting climatic variability over North America.
The Coupled Model Project was established at the National Meteorological Center (NMC) in January 1991 to develop a multiseason forecast system based on coupled ocean-atmosphere general circulation models. This provided a focus to combine expertise in near real-time ocean modeling and analyses situated in the Climate Analysis Center (CAC) with expertise in atmospheric modeling and data assimilation in the Development Division. Since the inception of the project, considerable progress has been made toward establishing a coupled forecast system. A T40 version of NMC's operational global medium-range forecast model (MRF) has been modified so as to have improved response to boundary forcing from the Tropics. In extended simulations, which are forced with observed historical global sea surface temperature (SST) fields, the model reproduces much of the observed tropical Pacific and North American rainfall and temperature variability. An ocean reanalysis has been performed for the Pacific basin starting from July 1982 to present and uses a dynamical model-based assimilation system. This also provides the ocean initial conditions for coupled forecast experiments. The current coupled forecast model consists of an active Pacific Ocean model coupled to the T40 version of the NMC's MRF. In the future, a global ocean model will be used to include climate information from the other ocean basins. The initial experiments focused on forecasting Northern Hemisphere winter SST anomalies in the tropical Pacific with a lead time of two seasons. The coupled model showed considerable skill during these experiments. Work is currently under way to quantify the skill in predicting climatic variability over North America.
Abstract
In this study, the National Centers for Environmental Prediction (NCEP) Regional Spectral Model (RSM) has been evaluated as a means of enhancing the depiction of regional details beyond that which is capable in low-resolution global models. Three-month-long simulations driven by the NCEP–National Center for Atmospheric Research 40-yr reanalysis data are conducted with a horizontal resolution of about 50 km over the United States, for the two winters and summers. The selected winter cases are December–February (DJF) 1991/92 (warm eastern Pacific SST anomalies) and DJF 1992/93 (normal eastern Pacific SST anomalies). Summer cases are May–July (MJJ) 1988 (a drought in the Great Plains) and MJJ 1993 (a flooding).
Overall, the results from the model are very satisfactory in terms of the precipitation distribution for different seasons as well as the representation of large-scale features. Evaluation of simulated large-scale features reveals that the model does not exhibit a discernible synoptic-scale drift during the 3-month integration period, irrespective of the seasons. Surprisingly, the model simulation is found to correct some biases in the large-scale fields that exist in the reanalysis data. This bias reduction is attributed to the improved depiction of physical processes within the RSM. This finding indicates that one should take special care in the interpretation and validation of simulated results against the analyzed data.
Evaluation of the RSM simulated precipitation for the winter and summer cases generally agrees with results obtained from previous studies. For instance, the skill for simulated precipitation in the winter cases exceeds that of the summer cases by a factor of 2. Comparison of simulated precipitation with observations reveals the 3-month-long RSM simulated precipitation to be more skillful than that obtained from the reanalysis data (the 6-h forecast from the data assimilation system). In addition to seasonal variations in precipitation, daily variation in the simulated precipitation is quite good. However, detailed analysis points to the need for further RSM development, particularly in physics. In the summer cases the grid-resolvable precipitation physics simulate excessive precipitation over the northern United States. A more serious problem is found in the diurnal cycle of the simulation precipitation, in that the model initiates convection too early. Despite these deficiencies, it is concluded that the NCEP RSM is a very useful tool for regional climate studies.
Abstract
In this study, the National Centers for Environmental Prediction (NCEP) Regional Spectral Model (RSM) has been evaluated as a means of enhancing the depiction of regional details beyond that which is capable in low-resolution global models. Three-month-long simulations driven by the NCEP–National Center for Atmospheric Research 40-yr reanalysis data are conducted with a horizontal resolution of about 50 km over the United States, for the two winters and summers. The selected winter cases are December–February (DJF) 1991/92 (warm eastern Pacific SST anomalies) and DJF 1992/93 (normal eastern Pacific SST anomalies). Summer cases are May–July (MJJ) 1988 (a drought in the Great Plains) and MJJ 1993 (a flooding).
Overall, the results from the model are very satisfactory in terms of the precipitation distribution for different seasons as well as the representation of large-scale features. Evaluation of simulated large-scale features reveals that the model does not exhibit a discernible synoptic-scale drift during the 3-month integration period, irrespective of the seasons. Surprisingly, the model simulation is found to correct some biases in the large-scale fields that exist in the reanalysis data. This bias reduction is attributed to the improved depiction of physical processes within the RSM. This finding indicates that one should take special care in the interpretation and validation of simulated results against the analyzed data.
Evaluation of the RSM simulated precipitation for the winter and summer cases generally agrees with results obtained from previous studies. For instance, the skill for simulated precipitation in the winter cases exceeds that of the summer cases by a factor of 2. Comparison of simulated precipitation with observations reveals the 3-month-long RSM simulated precipitation to be more skillful than that obtained from the reanalysis data (the 6-h forecast from the data assimilation system). In addition to seasonal variations in precipitation, daily variation in the simulated precipitation is quite good. However, detailed analysis points to the need for further RSM development, particularly in physics. In the summer cases the grid-resolvable precipitation physics simulate excessive precipitation over the northern United States. A more serious problem is found in the diurnal cycle of the simulation precipitation, in that the model initiates convection too early. Despite these deficiencies, it is concluded that the NCEP RSM is a very useful tool for regional climate studies.
