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- Author or Editor: T. R. Osborn x
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Abstract
A method is developed for estimating the uncertainty (standard error) of observed regional, hemispheric, and global-mean surface temperature series due to incomplete spatial sampling. Standard errors estimated at the grid-box level [SE2 = S 2(1 − r̄)/(1 + (n − 1)r̄)] depend upon three parameters: the number of site records (n) within each box, the average interrecord correlation (r̄) between these sites, and the temporal variability (S 2) of each grid-box temperature time series. For boxes without data (n = 0), estimates are made using values of S 2 interpolated from neighboring grid boxes. Due to spatial correlation, large-scale standard errors in a regional-mean time series are not simply the average of the grid-box standard errors, but depend upon the effective number of independent sites (N eff) over the region.
A number of assumptions must be made in estimating the various parameters, and these are tested with observational data and complementary results from multicentury control integrations of three coupled general circulation models (GCMs). The globally complete GCMs enable some assumptions to be tested in a situation where there are no missing data; comparison of parameters computed from the observed and model datasets are also useful for assessing the performance of GCMs. As most of the parameters are timescale dependent, the resulting errors are likewise timescale dependent and must be calculated for each timescale of interest. The length of the observed record enables uncertainties to be estimated on the interannual and interdecadal timescales, with the longer GCM runs providing inferences about longer timescales. For mean annual observed data on the interannual timescale, the 95% confidence interval for estimates of the global-mean surface temperature since 1951 is ±0.12°C. Prior to 1900, the confidence interval widens to ±0.18°C. Equivalent values on the decadal timescale are smaller: ±0.10°C (1951–95) and ±0.16°C (1851–1900).
Abstract
A method is developed for estimating the uncertainty (standard error) of observed regional, hemispheric, and global-mean surface temperature series due to incomplete spatial sampling. Standard errors estimated at the grid-box level [SE2 = S 2(1 − r̄)/(1 + (n − 1)r̄)] depend upon three parameters: the number of site records (n) within each box, the average interrecord correlation (r̄) between these sites, and the temporal variability (S 2) of each grid-box temperature time series. For boxes without data (n = 0), estimates are made using values of S 2 interpolated from neighboring grid boxes. Due to spatial correlation, large-scale standard errors in a regional-mean time series are not simply the average of the grid-box standard errors, but depend upon the effective number of independent sites (N eff) over the region.
A number of assumptions must be made in estimating the various parameters, and these are tested with observational data and complementary results from multicentury control integrations of three coupled general circulation models (GCMs). The globally complete GCMs enable some assumptions to be tested in a situation where there are no missing data; comparison of parameters computed from the observed and model datasets are also useful for assessing the performance of GCMs. As most of the parameters are timescale dependent, the resulting errors are likewise timescale dependent and must be calculated for each timescale of interest. The length of the observed record enables uncertainties to be estimated on the interannual and interdecadal timescales, with the longer GCM runs providing inferences about longer timescales. For mean annual observed data on the interannual timescale, the 95% confidence interval for estimates of the global-mean surface temperature since 1951 is ±0.12°C. Prior to 1900, the confidence interval widens to ±0.18°C. Equivalent values on the decadal timescale are smaller: ±0.10°C (1951–95) and ±0.16°C (1851–1900).
Abstract
Maps of monthly self-calibrating Palmer Drought Severity Index (SC-PDSI) have been calculated for the period of 1901–2002 for Europe (35°–70°N, 10°W–60°E) with a spatial resolution of 0.5° × 0.5°. The recently introduced SC-PDSI is a convenient means of describing the spatial and temporal variability of moisture availability and is based on the more common Palmer Drought Severity Index. The SC-PDSI improves upon the PDSI by maintaining consistent behavior of the index over diverse climatological regions. This makes spatial comparisons of SC-PDSI values on continental scales more meaningful.
Over the region as a whole, the mid-1940s to early 1950s stand out as a persistent and exceptionally dry period, whereas the mid-1910s and late 1970s to early 1980s were very wet. The driest and wettest summers on record, in terms of the amplitude of the index averaged over Europe, were 1947 and 1915, respectively, while the years 1921 and 1981 saw over 11% and over 7% of Europe suffering from extreme dry or wet conditions, respectively.
Trends in summer moisture availability over Europe for the 1901–2002 period fail to be statistically significant, both in terms of spatial means of the drought index and in the area affected by drought. Moreover, evidence for widespread and unusual drying in European regions over the last few decades is not supported by the current work.
Abstract
Maps of monthly self-calibrating Palmer Drought Severity Index (SC-PDSI) have been calculated for the period of 1901–2002 for Europe (35°–70°N, 10°W–60°E) with a spatial resolution of 0.5° × 0.5°. The recently introduced SC-PDSI is a convenient means of describing the spatial and temporal variability of moisture availability and is based on the more common Palmer Drought Severity Index. The SC-PDSI improves upon the PDSI by maintaining consistent behavior of the index over diverse climatological regions. This makes spatial comparisons of SC-PDSI values on continental scales more meaningful.
Over the region as a whole, the mid-1940s to early 1950s stand out as a persistent and exceptionally dry period, whereas the mid-1910s and late 1970s to early 1980s were very wet. The driest and wettest summers on record, in terms of the amplitude of the index averaged over Europe, were 1947 and 1915, respectively, while the years 1921 and 1981 saw over 11% and over 7% of Europe suffering from extreme dry or wet conditions, respectively.
Trends in summer moisture availability over Europe for the 1901–2002 period fail to be statistically significant, both in terms of spatial means of the drought index and in the area affected by drought. Moreover, evidence for widespread and unusual drying in European regions over the last few decades is not supported by the current work.
Abstract
The climatically sensitive zone of the Arctic Ocean lies squarely within the domain of the North Atlantic oscillation (NAO), one of the most robust recurrent modes of atmospheric behavior. However, the specific response of the Arctic to annual and longer-period changes in the NAO is not well understood. Here that response is investigated using a wide range of datasets, but concentrating on the winter season when the forcing is maximal and on the postwar period, which includes the most comprehensive instrumental record. This period also contains the largest recorded low-frequency change in NAO activity—from its most persistent and extreme low index phase in the 1960s to its most persistent and extreme high index phase in the late 1980s/early 1990s. This long-period shift between contrasting NAO extrema was accompanied, among other changes, by an intensifying storm track through the Nordic Seas, a radical increase in the atmospheric moisture flux convergence and winter precipitation in this sector, an increase in the amount and temperature of the Atlantic water inflow to the Arctic Ocean via both inflow branches (Barents Sea Throughflow and West Spitsbergen Current), a decrease in the late-winter extent of sea ice throughout the European subarctic, and (temporarily at least) an increase in the annual volume flux of ice from the Fram Strait.
Abstract
The climatically sensitive zone of the Arctic Ocean lies squarely within the domain of the North Atlantic oscillation (NAO), one of the most robust recurrent modes of atmospheric behavior. However, the specific response of the Arctic to annual and longer-period changes in the NAO is not well understood. Here that response is investigated using a wide range of datasets, but concentrating on the winter season when the forcing is maximal and on the postwar period, which includes the most comprehensive instrumental record. This period also contains the largest recorded low-frequency change in NAO activity—from its most persistent and extreme low index phase in the 1960s to its most persistent and extreme high index phase in the late 1980s/early 1990s. This long-period shift between contrasting NAO extrema was accompanied, among other changes, by an intensifying storm track through the Nordic Seas, a radical increase in the atmospheric moisture flux convergence and winter precipitation in this sector, an increase in the amount and temperature of the Atlantic water inflow to the Arctic Ocean via both inflow branches (Barents Sea Throughflow and West Spitsbergen Current), a decrease in the late-winter extent of sea ice throughout the European subarctic, and (temporarily at least) an increase in the annual volume flux of ice from the Fram Strait.
Abstract
Results are presented from a set of experiments designed to investigate factors that may influence proxy-based reconstructions of large-scale temperature patterns in past centuries. The factors investigated include 1) the method used to assimilate proxy data into a climate reconstruction, 2) the proxy data network used, 3) the target season, and 4) the spatial domain of the reconstruction. Estimates of hemispheric-mean temperature are formed through spatial averaging of reconstructed temperature patterns that are based on either the local calibration of proxy and instrumental data or a more elaborate multivariate climate field reconstruction approach. The experiments compare results based on the global multiproxy dataset used by Mann and coworkers, with results obtained using the extratropical Northern Hemisphere (NH) maximum latewood tree-ring density set used by Briffa and coworkers. Mean temperature reconstructions are compared for the full NH (Tropics and extratropics, land and ocean) and extratropical continents only, withvarying target seasons (cold-season half year, warm-season half year, and annual mean). The comparisons demonstrate dependence of reconstructions on seasonal, spatial, and methodological considerations, emphasizing the primary importance of the target region and seasonal window of the reconstruction. The comparisons support the generally robust nature of several previously published estimates of NH mean temperature changes in past centuries and suggest that further improvements in reconstructive skill are most likely to arise from an emphasis on the quality, rather than quantity, of available proxy data.
Abstract
Results are presented from a set of experiments designed to investigate factors that may influence proxy-based reconstructions of large-scale temperature patterns in past centuries. The factors investigated include 1) the method used to assimilate proxy data into a climate reconstruction, 2) the proxy data network used, 3) the target season, and 4) the spatial domain of the reconstruction. Estimates of hemispheric-mean temperature are formed through spatial averaging of reconstructed temperature patterns that are based on either the local calibration of proxy and instrumental data or a more elaborate multivariate climate field reconstruction approach. The experiments compare results based on the global multiproxy dataset used by Mann and coworkers, with results obtained using the extratropical Northern Hemisphere (NH) maximum latewood tree-ring density set used by Briffa and coworkers. Mean temperature reconstructions are compared for the full NH (Tropics and extratropics, land and ocean) and extratropical continents only, withvarying target seasons (cold-season half year, warm-season half year, and annual mean). The comparisons demonstrate dependence of reconstructions on seasonal, spatial, and methodological considerations, emphasizing the primary importance of the target region and seasonal window of the reconstruction. The comparisons support the generally robust nature of several previously published estimates of NH mean temperature changes in past centuries and suggest that further improvements in reconstructive skill are most likely to arise from an emphasis on the quality, rather than quantity, of available proxy data.
