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Abstract
The evolution of the Southern Oscillation (SO) is examined in the time domain by computing lagged cross correlations between sea level pressures at Darwin and sea level or surface pressures at selected stations. Also, in the Northern Hemisphere, the historical and U.S. Navy sea level pressure analyses are used. All monthly time series are low-pass filtered to retain periodicities greater than 20 months in order to highlight the interannual fluctuations which are primarily associated with the SO. A detailed analysis of the post-1941 period results in plotted maps of the phase (lead or lag) and magnitude of the maximum cross correlations with Darwin, in a manner analogous to a broadband coherence and phase spectrum. The relationships within the SO are further examined, where possible, back to 1882 using time series of running decadal cross covariances.
The dominant pattern reveals the two poles of the traditional standing oscillation or seesaw of the SO, with centers of opposite sign over Indonesia and the central South Pacific Ocean. But there are significant phase variations within each center and clear indications that changes over the South Pacific lead the opposite changes in the Indonesian pole by 1–2 seasons. Largest leads of three seasons begin near New Zealand but quickly spread over the subtropics of both hemispheres in the Pacific. Typically 1–3 seasons later, opposite anomalies begin over the Indian region and progress east and southeast into the western Pacific. Significant positive and negative lagged correlations occur only in the New Zealand area.
For the post-1950 period, which is the basis for most recent analyses of El Niño–SO events, the SO was dominated by a three-six year quasi-periodicity which leads to ambiguity in interpreting phase relationships. The pattern of leads and lags is consistent with a progression of anomalies from southeast Australia across New Zealand and into the Pacific about two years later. The progression is not very regular, often occurring in discrete jumps. Moreover, it requires reinterpretation of the negative correlations as positive correlations that are half a period (π radians) out of phase. Eastward propagation is likely to be exaggerated by the implied cyclicity imposed by analyses in the frequency domain. Over the longer term (1882–1984) the ambiguity is lessened and the two poles are seen to be more distinct. Systematic leads are still apparent over the subtropics of the Pacific but the evidence for an eastward-propagating component extending from Australia across the southwest Pacific is not consistent throughout the record. The results show that caution must be exercised in interpreting the post-1950 period as representative of the long-term mean behavior.
The importance of the tendency for changes over the South Pacific to lead the SO lies in the probable role of associated processes in setting up tropical sea surface temperature anomalies, especially during the onset stage of El Niño events. The South Pacific Convergence Zone (SPCZ) is regarded as a key feature, and the physical mechanisms likely to be important are discussed. It is noted that the SO and El Niño events do not always coincide. Tropical Pacific sea surface temperatures can be anomalously warm without a change in the SO, apparently provided that the SPCZ is not involved to any extent. However, global-scale atmospheric teleconnections are primarily associated with the SO.
Abstract
The evolution of the Southern Oscillation (SO) is examined in the time domain by computing lagged cross correlations between sea level pressures at Darwin and sea level or surface pressures at selected stations. Also, in the Northern Hemisphere, the historical and U.S. Navy sea level pressure analyses are used. All monthly time series are low-pass filtered to retain periodicities greater than 20 months in order to highlight the interannual fluctuations which are primarily associated with the SO. A detailed analysis of the post-1941 period results in plotted maps of the phase (lead or lag) and magnitude of the maximum cross correlations with Darwin, in a manner analogous to a broadband coherence and phase spectrum. The relationships within the SO are further examined, where possible, back to 1882 using time series of running decadal cross covariances.
The dominant pattern reveals the two poles of the traditional standing oscillation or seesaw of the SO, with centers of opposite sign over Indonesia and the central South Pacific Ocean. But there are significant phase variations within each center and clear indications that changes over the South Pacific lead the opposite changes in the Indonesian pole by 1–2 seasons. Largest leads of three seasons begin near New Zealand but quickly spread over the subtropics of both hemispheres in the Pacific. Typically 1–3 seasons later, opposite anomalies begin over the Indian region and progress east and southeast into the western Pacific. Significant positive and negative lagged correlations occur only in the New Zealand area.
For the post-1950 period, which is the basis for most recent analyses of El Niño–SO events, the SO was dominated by a three-six year quasi-periodicity which leads to ambiguity in interpreting phase relationships. The pattern of leads and lags is consistent with a progression of anomalies from southeast Australia across New Zealand and into the Pacific about two years later. The progression is not very regular, often occurring in discrete jumps. Moreover, it requires reinterpretation of the negative correlations as positive correlations that are half a period (π radians) out of phase. Eastward propagation is likely to be exaggerated by the implied cyclicity imposed by analyses in the frequency domain. Over the longer term (1882–1984) the ambiguity is lessened and the two poles are seen to be more distinct. Systematic leads are still apparent over the subtropics of the Pacific but the evidence for an eastward-propagating component extending from Australia across the southwest Pacific is not consistent throughout the record. The results show that caution must be exercised in interpreting the post-1950 period as representative of the long-term mean behavior.
The importance of the tendency for changes over the South Pacific to lead the SO lies in the probable role of associated processes in setting up tropical sea surface temperature anomalies, especially during the onset stage of El Niño events. The South Pacific Convergence Zone (SPCZ) is regarded as a key feature, and the physical mechanisms likely to be important are discussed. It is noted that the SO and El Niño events do not always coincide. Tropical Pacific sea surface temperatures can be anomalously warm without a change in the SO, apparently provided that the SPCZ is not involved to any extent. However, global-scale atmospheric teleconnections are primarily associated with the SO.
Abstract
Estimates of the natural variability of monthly mean temperature data from 107 U.S. stations are made. The natural variability of monthly means is defined as those interannual fluctuations that can be attributed to the effects of statistical sampling alone. It is variability resulting from the variance and autocorrelation associated with daily weather fluctuations. It does not indicate “climate change” but rather it is the variability within an “unchanging climate”; as such it is a measure of unpredictable “climatic noise”. Comparisons between the natural and actual interannual variability are discussed in the context of potential long-range predictability. The natural variability is proposed as a lower limit for the standard error of estimate for any long-range prediction. A characteristic time between independent estimates is computed.
Abstract
Estimates of the natural variability of monthly mean temperature data from 107 U.S. stations are made. The natural variability of monthly means is defined as those interannual fluctuations that can be attributed to the effects of statistical sampling alone. It is variability resulting from the variance and autocorrelation associated with daily weather fluctuations. It does not indicate “climate change” but rather it is the variability within an “unchanging climate”; as such it is a measure of unpredictable “climatic noise”. Comparisons between the natural and actual interannual variability are discussed in the context of potential long-range predictability. The natural variability is proposed as a lower limit for the standard error of estimate for any long-range prediction. A characteristic time between independent estimates is computed.
Abstract
Observational information from 533 radial flight legs executed by the National Hurricane Research Laboratory over a 13-year period (1957–69) is used to present the structural characteristics and the variability of the hurricane’s inner core region. Tangential and radial winds, D-values, and adjusted temperatures are composited with respect to the Radius of Maximum Wind (RMW) in order to construct a five-level mean symmetric storm and a five-level mean asymmetric storm. The slope of the RMW with height and the position of the RMW relative to the inner cloud wall are presented. Utilizing these results, an idealized, steady-state schematic model of the flow conditions in the inner hurricane core is presented. Storms are stratified by deepening and filling tendency, intensity and storm speed. Finally, the variations of the RMW with latitude, maximum wind, inner radar radius, central pressure, and other features are discussed.
Many significant features are noted: 1) storm inflow is confined almost exclusively to the lowest layer and occurs at radii larger than the RMW; 2) inside the RMW (i.e., in the eye) outflow is present; 3) the warmest cyclone temperatures result from subsidence and occur just inside the eye-wall cloud edge where the sinking is strongest; 4) the largest D-value and adjusted temperature gradients occur at and just outside the RMW; 5) the largest convergence occurs in the lowest layer at the RMW; 6) the slope of the RMW with height is small and appears to be a function of intensity; 7) the maximum winds occur within the eye wall cloud area; 8) inner core winds are shown to have a natural asymmetry beyond that induced by storm motion; 9) vertical wind shears in deepening storms are much smaller than in filling storms; 10) in intense storms the maximum winds occur closer to the center than in weaker storms; 11) faster moving storms were more intense than slower moving storms; and 12) at high latitudes the maximum winds occur further away from the storm center than at low latitudes. Other features are shown and discussed.
Abstract
Observational information from 533 radial flight legs executed by the National Hurricane Research Laboratory over a 13-year period (1957–69) is used to present the structural characteristics and the variability of the hurricane’s inner core region. Tangential and radial winds, D-values, and adjusted temperatures are composited with respect to the Radius of Maximum Wind (RMW) in order to construct a five-level mean symmetric storm and a five-level mean asymmetric storm. The slope of the RMW with height and the position of the RMW relative to the inner cloud wall are presented. Utilizing these results, an idealized, steady-state schematic model of the flow conditions in the inner hurricane core is presented. Storms are stratified by deepening and filling tendency, intensity and storm speed. Finally, the variations of the RMW with latitude, maximum wind, inner radar radius, central pressure, and other features are discussed.
Many significant features are noted: 1) storm inflow is confined almost exclusively to the lowest layer and occurs at radii larger than the RMW; 2) inside the RMW (i.e., in the eye) outflow is present; 3) the warmest cyclone temperatures result from subsidence and occur just inside the eye-wall cloud edge where the sinking is strongest; 4) the largest D-value and adjusted temperature gradients occur at and just outside the RMW; 5) the largest convergence occurs in the lowest layer at the RMW; 6) the slope of the RMW with height is small and appears to be a function of intensity; 7) the maximum winds occur within the eye wall cloud area; 8) inner core winds are shown to have a natural asymmetry beyond that induced by storm motion; 9) vertical wind shears in deepening storms are much smaller than in filling storms; 10) in intense storms the maximum winds occur closer to the center than in weaker storms; 11) faster moving storms were more intense than slower moving storms; and 12) at high latitudes the maximum winds occur further away from the storm center than at low latitudes. Other features are shown and discussed.
Abstract
This is the second (Paper II) of two papers on the characteristics of the hurricane’s inner core region as revealed by the research flight data of the National Hurricane Research Laboratory. This paper presents information on the thermal stability and the dynamic characteristics of the hurricane’s inner core region from information derived from Paper I. Discussion is given on the hurricane’s inner core vertical stability, divergence, vertical motion, heating mechanism, wind-pressure acceleration, thermal wind balances, and other features.
It is shown that large vertical moist instability is present in the eye-wall cloud. Large super-gradient winds are present at the radius of maximum winds. Substantial mixing occurs between eye and eye wall and the average hurricane eye ventilates itself by about half of its mass during the time it takes to move the distance of its eye diameter. Maximum heating does not occur at the radius of maximum updraft. Inner core heating comes from the sinking motion within the eye and not from heat diffusion from the cumulus updraft. Other features are discussed.
Abstract
This is the second (Paper II) of two papers on the characteristics of the hurricane’s inner core region as revealed by the research flight data of the National Hurricane Research Laboratory. This paper presents information on the thermal stability and the dynamic characteristics of the hurricane’s inner core region from information derived from Paper I. Discussion is given on the hurricane’s inner core vertical stability, divergence, vertical motion, heating mechanism, wind-pressure acceleration, thermal wind balances, and other features.
It is shown that large vertical moist instability is present in the eye-wall cloud. Large super-gradient winds are present at the radius of maximum winds. Substantial mixing occurs between eye and eye wall and the average hurricane eye ventilates itself by about half of its mass during the time it takes to move the distance of its eye diameter. Maximum heating does not occur at the radius of maximum updraft. Inner core heating comes from the sinking motion within the eye and not from heat diffusion from the cumulus updraft. Other features are discussed.
Abstract
Using more than three times as many stations and time series of daily data that am generally 1.5–3.0 times longer than those in a previous study, estimates of the natural variability, also known as climate noise, of surface air temperatures are extended over most North America. The potential for long-range prediction of monthly means is determined by comparing the actual interannual variability of monthly means with the climate noise that is assumed to be unpredictable at long range. The climate noise estimates am typically larger during winter than during the other seasons. Nonetheless, the potential for long-range prediction is, generally, greatest for January and least for April. During January, temperatures nearest the oceans am more predictable than those for the central portions of North America.
The low-frequency white-noise statistical model that is used to estimate the unpredictable climate noise is compared with time series of (near) surface temperatures from a general circulation model to confirm its credibility. The estimates of the potential for prediction are tested further to establish their sensitivities to a critical parameter of the statistical model and to spatial averaging.
Abstract
Using more than three times as many stations and time series of daily data that am generally 1.5–3.0 times longer than those in a previous study, estimates of the natural variability, also known as climate noise, of surface air temperatures are extended over most North America. The potential for long-range prediction of monthly means is determined by comparing the actual interannual variability of monthly means with the climate noise that is assumed to be unpredictable at long range. The climate noise estimates am typically larger during winter than during the other seasons. Nonetheless, the potential for long-range prediction is, generally, greatest for January and least for April. During January, temperatures nearest the oceans am more predictable than those for the central portions of North America.
The low-frequency white-noise statistical model that is used to estimate the unpredictable climate noise is compared with time series of (near) surface temperatures from a general circulation model to confirm its credibility. The estimates of the potential for prediction are tested further to establish their sensitivities to a critical parameter of the statistical model and to spatial averaging.
Abstract
A Bayesian fingerprinting methodology for assessing anthropogenic impacts on climate was developed. This analysis considers the effect of increased CO2 on near-surface temperatures. A spatial CO2 fingerprint based on control and forced model output from the National Center for Atmospheric Research Climate System Model was developed. The Bayesian approach is distinguished by several new facets. First, the prior model for the amplitude of the fingerprint is a mixture of two distributions: one reflects prior uncertainty in the anticipated value of the amplitude under the hypothesis of “no climate change.” The second reflects behavior assuming“climate change forced by CO2.” Second, within the Bayesian framework, a new formulation of detection and attribution analyses based on practical significance of impacts rather than traditional statistical significance was presented. Third, since Bayesian analyses can be very sensitive to prior inputs, a robust Bayesian approach, which investigates the ranges of posterior inferences as prior inputs are varied, was used. Following presentation of numerical results that enforce the claim of changes in temperature patterns due to anthropogenic CO2 forcing, the article concludes with a comparative analysis for another CO2 fingerprint and selected discussion.
Abstract
A Bayesian fingerprinting methodology for assessing anthropogenic impacts on climate was developed. This analysis considers the effect of increased CO2 on near-surface temperatures. A spatial CO2 fingerprint based on control and forced model output from the National Center for Atmospheric Research Climate System Model was developed. The Bayesian approach is distinguished by several new facets. First, the prior model for the amplitude of the fingerprint is a mixture of two distributions: one reflects prior uncertainty in the anticipated value of the amplitude under the hypothesis of “no climate change.” The second reflects behavior assuming“climate change forced by CO2.” Second, within the Bayesian framework, a new formulation of detection and attribution analyses based on practical significance of impacts rather than traditional statistical significance was presented. Third, since Bayesian analyses can be very sensitive to prior inputs, a robust Bayesian approach, which investigates the ranges of posterior inferences as prior inputs are varied, was used. Following presentation of numerical results that enforce the claim of changes in temperature patterns due to anthropogenic CO2 forcing, the article concludes with a comparative analysis for another CO2 fingerprint and selected discussion.
Abstract
A new global 2°×2° monthly sea surface temperature (SST) climatology, primarily derived from a 1950–1979-based SST climatology from the Climate Analysis Center (CAC), is presented and described. The CAC climatology has been modified by using data from the Comprehensive Ocean-Atmosphere Data Set to improve the SST estimates in the regions of the Kuroshio and the Gulf Stream. This results in considerably larger and more realistic SST gradients in these regions. This modified climatology is smoothed in time using a truncated Fourier series to eliminate mean annual cycle fluctuations of three months or less, and finally, some spatial smoothing is applied over the high-latitude southern oceans.
This new SST climatology, which we call the Shea-Trenberth-Reynolds (STR) climatology, is compared with the Alexander and Mobley (AM) SST climatology often used as a lower boundary condition by general circulation models. Significant differences are noted. Generally, the STR climatology is warmer in the Northern Hemisphere and in the subtropics of the Southern Hemisphere during the northern winter. It is often colder south of 45°S in all months. The largest differences are more than 5°C in the Kuroshio and Gulf Stream regions, and in the mid- to high-latitude southern oceans, the SSTs are often more than 2°C lower. In addition, the STR climatology is temporally and spatially less noisy than the AM SST climatology.
Global SST anomalies spanning the period 1982 to 1990 are discussed. The largest anomalies are associated with the El Niño (1982–83 and 1986–87) and La Niña (1988) events in the tropical Pacific. However, because of differences in procedures in producing the 1982–1990 SSTs compared with the CAC climatology, the anomalies in certain regions are really compensating for deficiencies in the climatology and should not be interpreted as true climate anomalies.
Abstract
A new global 2°×2° monthly sea surface temperature (SST) climatology, primarily derived from a 1950–1979-based SST climatology from the Climate Analysis Center (CAC), is presented and described. The CAC climatology has been modified by using data from the Comprehensive Ocean-Atmosphere Data Set to improve the SST estimates in the regions of the Kuroshio and the Gulf Stream. This results in considerably larger and more realistic SST gradients in these regions. This modified climatology is smoothed in time using a truncated Fourier series to eliminate mean annual cycle fluctuations of three months or less, and finally, some spatial smoothing is applied over the high-latitude southern oceans.
This new SST climatology, which we call the Shea-Trenberth-Reynolds (STR) climatology, is compared with the Alexander and Mobley (AM) SST climatology often used as a lower boundary condition by general circulation models. Significant differences are noted. Generally, the STR climatology is warmer in the Northern Hemisphere and in the subtropics of the Southern Hemisphere during the northern winter. It is often colder south of 45°S in all months. The largest differences are more than 5°C in the Kuroshio and Gulf Stream regions, and in the mid- to high-latitude southern oceans, the SSTs are often more than 2°C lower. In addition, the STR climatology is temporally and spatially less noisy than the AM SST climatology.
Global SST anomalies spanning the period 1982 to 1990 are discussed. The largest anomalies are associated with the El Niño (1982–83 and 1986–87) and La Niña (1988) events in the tropical Pacific. However, because of differences in procedures in producing the 1982–1990 SSTs compared with the CAC climatology, the anomalies in certain regions are really compensating for deficiencies in the climatology and should not be interpreted as true climate anomalies.
Abstract
A new surface boundary forcing dataset for uncoupled simulations with the Community Atmosphere Model is described. It is a merged product based on the monthly mean Hadley Centre sea ice and SST dataset version 1 (HadISST1) and version 2 of the National Oceanic and Atmospheric Administration (NOAA) weekly optimum interpolation (OI) SST analysis. These two source datasets were also used to supply ocean surface information to the 40-yr European Centre for Medium-Range Weather Forecasts Re-Analysis (ERA-40). The merged product provides monthly mean sea surface temperature and sea ice concentration data from 1870 to the present: it is updated monthly, and it is freely available for community use. The merging procedure was designed to take full advantage of the higher-resolution SST information inherent in the NOAA OI.v2 analysis.
Abstract
A new surface boundary forcing dataset for uncoupled simulations with the Community Atmosphere Model is described. It is a merged product based on the monthly mean Hadley Centre sea ice and SST dataset version 1 (HadISST1) and version 2 of the National Oceanic and Atmospheric Administration (NOAA) weekly optimum interpolation (OI) SST analysis. These two source datasets were also used to supply ocean surface information to the 40-yr European Centre for Medium-Range Weather Forecasts Re-Analysis (ERA-40). The merged product provides monthly mean sea surface temperature and sea ice concentration data from 1870 to the present: it is updated monthly, and it is freely available for community use. The merging procedure was designed to take full advantage of the higher-resolution SST information inherent in the NOAA OI.v2 analysis.
