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- Author or Editor: James A. Renwick x
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Abstract
Interannual variability in the frequency of atmospheric blocking events over the southern Pacific Ocean is analyzed in terms of variations in the El Niño–Southern Oscillation (ENSO) cycle, using a 16-yr record of Southern Hemisphere 500-hPa height fields. The number of days of blocking tends to increase on average during the warm phase of the ENSO cycle, particularly over the southeast Pacific during the southern spring and summer. Over the southeast Pacific between September and February, more than twice as many days of blocking are observed on average during El Niño events than during neutral or La Niña conditions. Changes in the frequency of days of blocking are found to be related to changes in the mean circulation and more strongly to changes in the variance of circulation over the South Pacific.
Abstract
Interannual variability in the frequency of atmospheric blocking events over the southern Pacific Ocean is analyzed in terms of variations in the El Niño–Southern Oscillation (ENSO) cycle, using a 16-yr record of Southern Hemisphere 500-hPa height fields. The number of days of blocking tends to increase on average during the warm phase of the ENSO cycle, particularly over the southeast Pacific during the southern spring and summer. Over the southeast Pacific between September and February, more than twice as many days of blocking are observed on average during El Niño events than during neutral or La Niña conditions. Changes in the frequency of days of blocking are found to be related to changes in the mean circulation and more strongly to changes in the variance of circulation over the South Pacific.
Abstract
Long time series of reanalyses, from NCEP–NCAR and from ECMWF, are used to investigate the occurrence of persistent positive anomalies (PPAs) in the 500-hPa geopotential height field over the Southern Hemisphere extratropics during 1958–2001. Defining persistent anomalies as those of at least 100 m in magnitude lasting for at least 5 days, it is found that the region of most frequent occurrence is over the South Pacific. A cluster analysis of monthly PPA counts shows two distinct patterns, one a zonal wavenumber-1 (ZW1) pattern centered over the southeast Pacific near 60°S and the other a zonal wavenumber-3 (ZW3) pattern with centers near New Zealand and over the southern Atlantic and Indian Oceans. Results were insensitive to the choice of dataset, and to the removal of a linear trend from the daily height fields. The southeast Pacific PPA region is strongly modulated by ENSO, while the ZW3 pattern appears only weakly related to ENSO variability. A strong upward trend is apparent in occurrence of the ZW3 cluster, related to a matching trend in the variance of the height fields, particularly those from ECMWF. Such trends are at least in part a consequence of changes in the observing system, particularly the introduction of satellite soundings in the late 1970s.
Abstract
Long time series of reanalyses, from NCEP–NCAR and from ECMWF, are used to investigate the occurrence of persistent positive anomalies (PPAs) in the 500-hPa geopotential height field over the Southern Hemisphere extratropics during 1958–2001. Defining persistent anomalies as those of at least 100 m in magnitude lasting for at least 5 days, it is found that the region of most frequent occurrence is over the South Pacific. A cluster analysis of monthly PPA counts shows two distinct patterns, one a zonal wavenumber-1 (ZW1) pattern centered over the southeast Pacific near 60°S and the other a zonal wavenumber-3 (ZW3) pattern with centers near New Zealand and over the southern Atlantic and Indian Oceans. Results were insensitive to the choice of dataset, and to the removal of a linear trend from the daily height fields. The southeast Pacific PPA region is strongly modulated by ENSO, while the ZW3 pattern appears only weakly related to ENSO variability. A strong upward trend is apparent in occurrence of the ZW3 cluster, related to a matching trend in the variance of the height fields, particularly those from ECMWF. Such trends are at least in part a consequence of changes in the observing system, particularly the introduction of satellite soundings in the late 1970s.
Abstract
Relationships on the seasonal timescale between Southern Hemisphere 500-hPa height, sea surface temperature, and Antarctic sea ice variability have been investigated using NCEP–NCAR reanalyses, NCEP sea surface temperatures, and Met Office sea surface temperature and sea ice data. The dominant region of interannual variability in the Southern Hemisphere circulation, over the southeast Pacific Ocean, is found to be related to ENSO variability in tropical Pacific sea temperatures, as shown in a number of earlier papers. It is also related to Antarctic sea ice variability, where an out-of-phase relationship is found between sea ice extent in the central Pacific and in the southwest Atlantic Ocean. Sea ice extent is enhanced in one region when the atmospheric flow anomaly is equatorward, presumably through a combination of anomalous heat flux and direct advection. At the same time, the atmospheric flow anomaly in the other region tends to be poleward, resulting in a poleward retreat in the sea ice edge. Such an interaction accounted for 63% of the total squared covariance between hemispheric 500-hPa height and sea ice edge anomalies.
Averaged over the full data series used, no strong lag relationships were found, suggesting that circulation, sea ice, and sea surface temperatures respond to one another on intraseasonal timescales. However, a composite analysis with respect to the times of maxima or minima in Pacific sea ice extent did show apparently nonlinear lag behavior. The negative height anomalies over the southeast Pacific associated with maxima in Pacific sea ice tend to precede the ice maximum, or at least show no tendency to persist after the time of the ice maximum. However, positive height anomalies over the southeast Pacific associated with minima in Pacific sea ice tend to persist for some months after the ice minimum. The latter effect may be related to anomalous surface heat fluxes associated with the upstream reduction in sea ice.
Abstract
Relationships on the seasonal timescale between Southern Hemisphere 500-hPa height, sea surface temperature, and Antarctic sea ice variability have been investigated using NCEP–NCAR reanalyses, NCEP sea surface temperatures, and Met Office sea surface temperature and sea ice data. The dominant region of interannual variability in the Southern Hemisphere circulation, over the southeast Pacific Ocean, is found to be related to ENSO variability in tropical Pacific sea temperatures, as shown in a number of earlier papers. It is also related to Antarctic sea ice variability, where an out-of-phase relationship is found between sea ice extent in the central Pacific and in the southwest Atlantic Ocean. Sea ice extent is enhanced in one region when the atmospheric flow anomaly is equatorward, presumably through a combination of anomalous heat flux and direct advection. At the same time, the atmospheric flow anomaly in the other region tends to be poleward, resulting in a poleward retreat in the sea ice edge. Such an interaction accounted for 63% of the total squared covariance between hemispheric 500-hPa height and sea ice edge anomalies.
Averaged over the full data series used, no strong lag relationships were found, suggesting that circulation, sea ice, and sea surface temperatures respond to one another on intraseasonal timescales. However, a composite analysis with respect to the times of maxima or minima in Pacific sea ice extent did show apparently nonlinear lag behavior. The negative height anomalies over the southeast Pacific associated with maxima in Pacific sea ice tend to precede the ice maximum, or at least show no tendency to persist after the time of the ice maximum. However, positive height anomalies over the southeast Pacific associated with minima in Pacific sea ice tend to persist for some months after the ice minimum. The latter effect may be related to anomalous surface heat fluxes associated with the upstream reduction in sea ice.
Abstract
Technique for identification of well-predicted spatial patterns in numerical weather prediction model output are outlined and applied to a 14-winter set of Northern Hemisphere 500-mb geopotential height analyses and 1–10-day forecasts produced by the ECMWF operational model. Three approaches are investigated: canonical correlation analysis (CCA), singular value decomposition analysis, and predictable component analysis, the products of which are related to the optimization of forecast-analysis correlation, covariance, and rms error, respectively. In confirmation of earlier results, the most predictable anomaly pattern identified by all three methods is found to be similar to the leading empirical orthogonal function of the analyzed 500-mb height anomaly field, which is dominated by the Pacific-North American pattern. The time series of forecast and verifying analysis projections onto the leading pattern have temporal correlations of at least 0.75 at all forecast intervals out to 10 days and greater than 0.85 for 5-day averages of 6–10-day forecasts and analyses. The leading pattern displays strong temporal persistence and is prominent on the interannual timescale. CCA is found to be the most desirable technique for identification of such patterns.
When CCA is applied to the first seven winters' data (as a dependent sample), the amplitude of the leading pattern is well predicted in either polarity and the skill of the full forecast field is shown to increase as the amplitude of the leading pattern increases, regardless of the polarity. However, when the analyzed and predicted fields from the second seven winters of the dataset (an independent sample) are projected onto the patterns derived from the first seven winters, the skill of the full forecast field does not appear to be well related to the amplitude of the leading predictable pattern. Slight decreases in rms error were achieved by statistically correcting the independent data, but only at the expense of a considerable damping of forecast amplitude. It is concluded that continuing model improvements make such approaches to skill prediction and statistical correction of little value in an operational setting.
Abstract
Technique for identification of well-predicted spatial patterns in numerical weather prediction model output are outlined and applied to a 14-winter set of Northern Hemisphere 500-mb geopotential height analyses and 1–10-day forecasts produced by the ECMWF operational model. Three approaches are investigated: canonical correlation analysis (CCA), singular value decomposition analysis, and predictable component analysis, the products of which are related to the optimization of forecast-analysis correlation, covariance, and rms error, respectively. In confirmation of earlier results, the most predictable anomaly pattern identified by all three methods is found to be similar to the leading empirical orthogonal function of the analyzed 500-mb height anomaly field, which is dominated by the Pacific-North American pattern. The time series of forecast and verifying analysis projections onto the leading pattern have temporal correlations of at least 0.75 at all forecast intervals out to 10 days and greater than 0.85 for 5-day averages of 6–10-day forecasts and analyses. The leading pattern displays strong temporal persistence and is prominent on the interannual timescale. CCA is found to be the most desirable technique for identification of such patterns.
When CCA is applied to the first seven winters' data (as a dependent sample), the amplitude of the leading pattern is well predicted in either polarity and the skill of the full forecast field is shown to increase as the amplitude of the leading pattern increases, regardless of the polarity. However, when the analyzed and predicted fields from the second seven winters of the dataset (an independent sample) are projected onto the patterns derived from the first seven winters, the skill of the full forecast field does not appear to be well related to the amplitude of the leading predictable pattern. Slight decreases in rms error were achieved by statistically correcting the independent data, but only at the expense of a considerable damping of forecast amplitude. It is concluded that continuing model improvements make such approaches to skill prediction and statistical correction of little value in an operational setting.
Abstract
The robustness of relationships between forecast model output and forecast skill is tested using a 14-winter set of Northern Hemisphere 500-mb geopotential height analyses and forecasts produced by the European Centre for Medium-Range Weather Forecasts operational model. During the period of record, model skill improved substantially at the medium range, as the model itself went through many upgrade cycles. It is found, through independent trials using subsamples of the full 14-winter record, that apparently useful forecast correction and skill prediction relationships are sensitive to sampling variability and are of limited use in an operational setting. Interannual variability and nonstationarity in the time series of forecasts both appear to contribute to the lack of robustness. The occurrence or nonoccurrence of El Niño conditions appears to have a large effect on the form of many of the results.
The amplitude of mean errors associated with the day-10 forecast shows no dependence on the initial analysis polarity of the Pacific–North American (PNA) pattern, and the day-10 forecast amplitude of the PNA pattern appears to be of little use in the prediction of forecast skill. One relatively stable result is found: errors in predicting upper-level ridges or blocks over the Alaskan region are influential in determining the hemispherically integrated rms errors at the medium range, throughout the entire period of record. Some implications of these results for the reanalysis and possible reprediction of meteorological fields at global forecasting centers are discussed.
Abstract
The robustness of relationships between forecast model output and forecast skill is tested using a 14-winter set of Northern Hemisphere 500-mb geopotential height analyses and forecasts produced by the European Centre for Medium-Range Weather Forecasts operational model. During the period of record, model skill improved substantially at the medium range, as the model itself went through many upgrade cycles. It is found, through independent trials using subsamples of the full 14-winter record, that apparently useful forecast correction and skill prediction relationships are sensitive to sampling variability and are of limited use in an operational setting. Interannual variability and nonstationarity in the time series of forecasts both appear to contribute to the lack of robustness. The occurrence or nonoccurrence of El Niño conditions appears to have a large effect on the form of many of the results.
The amplitude of mean errors associated with the day-10 forecast shows no dependence on the initial analysis polarity of the Pacific–North American (PNA) pattern, and the day-10 forecast amplitude of the PNA pattern appears to be of little use in the prediction of forecast skill. One relatively stable result is found: errors in predicting upper-level ridges or blocks over the Alaskan region are influential in determining the hemispherically integrated rms errors at the medium range, throughout the entire period of record. Some implications of these results for the reanalysis and possible reprediction of meteorological fields at global forecasting centers are discussed.
Abstract
The frequency of persistent high-latitude ridging events (commonly referred to as blocking) over the North Pacific–Alaskan region is investigated using a 44-winter record of daily 500-mb height fields. The winters are stratified in accordance with the phase of the El Niño–Southern Oscillation (ENSO) cycle and according to the sign of the seasonally averaged PNA index. It is found that the occurrence of blocking in the Bering Strait region is sensitive to the averaged polarity of the PNA pattern but is even more sensitive to the phase of the ENSO cycle. Sixty-nine percent more days of blocking are observed during winters occurring during the cool phase of ENSO, compared to those occurring during the warm phase. ENSO-related differences in blocking frequency are found to be associated with changes to both the mean and variance of the circulation over the North Pacific. The variance of geopotential heights on timescales corresponding to the lifetime of blocking events is found to be higher over the Bering Strait region in the cool phase of the ENSO cycle.
Abstract
The frequency of persistent high-latitude ridging events (commonly referred to as blocking) over the North Pacific–Alaskan region is investigated using a 44-winter record of daily 500-mb height fields. The winters are stratified in accordance with the phase of the El Niño–Southern Oscillation (ENSO) cycle and according to the sign of the seasonally averaged PNA index. It is found that the occurrence of blocking in the Bering Strait region is sensitive to the averaged polarity of the PNA pattern but is even more sensitive to the phase of the ENSO cycle. Sixty-nine percent more days of blocking are observed during winters occurring during the cool phase of ENSO, compared to those occurring during the warm phase. ENSO-related differences in blocking frequency are found to be associated with changes to both the mean and variance of the circulation over the North Pacific. The variance of geopotential heights on timescales corresponding to the lifetime of blocking events is found to be higher over the Bering Strait region in the cool phase of the ENSO cycle.
Abstract
Atmospheric blocking events over the South Pacific are investigated using a 39-yr record of 500-hPa height fields from the NCEP–NCAR reanalysis dataset. The analysis extends earlier work using a 16-yr record and confirms that the occurrence of blocking over the southeast Pacific is strongly modulated by the ENSO cycle during austral spring and summer. Comparison of results at 500 hPa with the 300-hPa meridional wind component showed that blocking events are associated with large-scale wave trains lying across the South Pacific from the region of Australia to southern South America. Similar wave trains are evident in both hemispheres in singular value decomposition analyses between 300-hPa meridional wind components and tropical Pacific outgoing longwave radiation (OLR) anomalies.
The hypothesis that the divergence associated with tropical OLR anomalies forces an extratropical wave response that results in enhanced blocking over the southeast Pacific was tested using a linearized, barotropic vorticity equation (BVE) model. Observed 300-hPa mean flow fields and divergence forcing that matched the anomalous OLR were used to drive the BVE model. The resulting pattern of meridional wind and streamfunction anomalies agrees closely with observations. When the tropical OLR anomaly is given an eastward phase speed of 5° per day, the extratropical response agrees even better with observations. This suggests that linear Rossby wave propagation provides an important link between anomalous convection in the Tropics and the occurrence of blocking over the southeast Pacific Ocean.
Abstract
Atmospheric blocking events over the South Pacific are investigated using a 39-yr record of 500-hPa height fields from the NCEP–NCAR reanalysis dataset. The analysis extends earlier work using a 16-yr record and confirms that the occurrence of blocking over the southeast Pacific is strongly modulated by the ENSO cycle during austral spring and summer. Comparison of results at 500 hPa with the 300-hPa meridional wind component showed that blocking events are associated with large-scale wave trains lying across the South Pacific from the region of Australia to southern South America. Similar wave trains are evident in both hemispheres in singular value decomposition analyses between 300-hPa meridional wind components and tropical Pacific outgoing longwave radiation (OLR) anomalies.
The hypothesis that the divergence associated with tropical OLR anomalies forces an extratropical wave response that results in enhanced blocking over the southeast Pacific was tested using a linearized, barotropic vorticity equation (BVE) model. Observed 300-hPa mean flow fields and divergence forcing that matched the anomalous OLR were used to drive the BVE model. The resulting pattern of meridional wind and streamfunction anomalies agrees closely with observations. When the tropical OLR anomaly is given an eastward phase speed of 5° per day, the extratropical response agrees even better with observations. This suggests that linear Rossby wave propagation provides an important link between anomalous convection in the Tropics and the occurrence of blocking over the southeast Pacific Ocean.
Abstract
The skill of two global numerical weather prediction models, the National Centers for Environmental Prediction (NCEP) medium-range forecast model and the European Centre for Medium-Range Weather Forecasts (ECMWF) operational model, has been assessed over the Southern Hemisphere extratropics for much of the 1990s. Forecast skill and circulation predictability are calculated in terms of predicted and observed 500-hPa height fields. The skill of both the NCEP and ECMWF models has increased steadily through the decade. The useful forecast range (mean anomaly correlation at least 0.6) extended out to about day 6 during the late 1990s compared to day 5 in the early 1990s. The ECMWF model generally performed best out to the useful forecast limit, but scores were insignificantly different beyond that. ECMWF forecasts show a gradual increase in variance with forecast interval, while NCEP forecasts show a decrease.
For both models, the most predictable wintertime circulation pattern, defined by a singular value decomposition analysis, is associated with wave propagation across the South Pacific and southern Atlantic Oceans, the so-called Pacific–South American pattern, analogous to results found for the Northern Hemisphere. At day 10, the predicted amplitude of the leading pattern correlates at 0.6 with the analysis amplitude, while average hemispheric anomaly correlations are less than 0.3. For the leading singular mode pair, the spatial patterns and summary statistics compare closely between models. The spatial pattern of the leading singular mode is very similar in form to the leading analysis EOF from either model. A study of forecast errors reveals that a pattern related to the “high-latitude mode” or Antarctic oscillation, associated with a zonally symmetric exchange of mass between mid- and high latitudes, is weakly associated with large forecast errors. Large errors tend to be associated with positive height anomalies over the Pole and weak westerlies near 55°S. The more predictable patterns exhibit stronger temporal persistence than do the least predictable. Applications of these results to operational forecasting are discussed.
Abstract
The skill of two global numerical weather prediction models, the National Centers for Environmental Prediction (NCEP) medium-range forecast model and the European Centre for Medium-Range Weather Forecasts (ECMWF) operational model, has been assessed over the Southern Hemisphere extratropics for much of the 1990s. Forecast skill and circulation predictability are calculated in terms of predicted and observed 500-hPa height fields. The skill of both the NCEP and ECMWF models has increased steadily through the decade. The useful forecast range (mean anomaly correlation at least 0.6) extended out to about day 6 during the late 1990s compared to day 5 in the early 1990s. The ECMWF model generally performed best out to the useful forecast limit, but scores were insignificantly different beyond that. ECMWF forecasts show a gradual increase in variance with forecast interval, while NCEP forecasts show a decrease.
For both models, the most predictable wintertime circulation pattern, defined by a singular value decomposition analysis, is associated with wave propagation across the South Pacific and southern Atlantic Oceans, the so-called Pacific–South American pattern, analogous to results found for the Northern Hemisphere. At day 10, the predicted amplitude of the leading pattern correlates at 0.6 with the analysis amplitude, while average hemispheric anomaly correlations are less than 0.3. For the leading singular mode pair, the spatial patterns and summary statistics compare closely between models. The spatial pattern of the leading singular mode is very similar in form to the leading analysis EOF from either model. A study of forecast errors reveals that a pattern related to the “high-latitude mode” or Antarctic oscillation, associated with a zonally symmetric exchange of mass between mid- and high latitudes, is weakly associated with large forecast errors. Large errors tend to be associated with positive height anomalies over the Pole and weak westerlies near 55°S. The more predictable patterns exhibit stronger temporal persistence than do the least predictable. Applications of these results to operational forecasting are discussed.
Abstract
In terms of the effects of future climate change upon society, some of the most important parameters to estimate are associated with changing risks of extreme rainfall events, both floods and droughts. However, such aspects of the climate system are hard to estimate well using general circulation models (GCMs)—in particular, for a small mountainous landmass such as New Zealand. This paper describes a downscaling technique using broad-scale changes simulated by GCMs to select past analogs of future climate. The analog samples are assumed to represent an unbiased sample of future rainfall and are used to develop detailed descriptions of rainfall statistics using hidden semi-Markov models of rainfall breakpoint information. Such models are used to simulate long synthetic rainfall time series for comparison with the historical record. Results for three New Zealand sites show overall increases in rainfall with climate change, brought about largely by an increased frequency of rainfall events rather than an increase in rainfall intensity. There was little evidence for significant increases in high-intensity short-duration rainfalls at any site. Such results suggest that, although regional increases of rainfall are consistent with expected future climate changes, it may be that circulation changes, rather than temperature (and vapor pressure) changes, will be the more important determinant of future rainfall distributions, at least for the coming few decades.
Abstract
In terms of the effects of future climate change upon society, some of the most important parameters to estimate are associated with changing risks of extreme rainfall events, both floods and droughts. However, such aspects of the climate system are hard to estimate well using general circulation models (GCMs)—in particular, for a small mountainous landmass such as New Zealand. This paper describes a downscaling technique using broad-scale changes simulated by GCMs to select past analogs of future climate. The analog samples are assumed to represent an unbiased sample of future rainfall and are used to develop detailed descriptions of rainfall statistics using hidden semi-Markov models of rainfall breakpoint information. Such models are used to simulate long synthetic rainfall time series for comparison with the historical record. Results for three New Zealand sites show overall increases in rainfall with climate change, brought about largely by an increased frequency of rainfall events rather than an increase in rainfall intensity. There was little evidence for significant increases in high-intensity short-duration rainfalls at any site. Such results suggest that, although regional increases of rainfall are consistent with expected future climate changes, it may be that circulation changes, rather than temperature (and vapor pressure) changes, will be the more important determinant of future rainfall distributions, at least for the coming few decades.
