Monthly mean pressure reconstructions for Europe for the 1780–1995 period

Jones, Phil; Davies, Trevor; Lister, David; Slonosky, Victoria; Jónsson, Trausti; Bärring, Lars; Jönsson, Peter; Maheras, P.; Kolyva-Machera, F.; Barriendos, Mariano; Martín‐Vide, Javier; Rodríguez, Roberto Fernández; Alcoforado, María João; Wanner, Heinz; Pfister, Christian; Luterbacher, Jürg; Rickli, Ralph; Schuepbach, E.; Kaas, Eigil; Schmith, Torben; Jacobeit, Jucundus; Beck, Christoph

doi:10.1002/(sici)1097-0088(19990330)19:4<347::aid-joc363>3.0.co;2-s

Cited by 117 publications

(138 citation statements)

References 10 publications

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“…After assessment we recalibrated over 1901±1995 in order to derive monthly (1659±1995) and seasonal (1500±1658) NAO indices. For a detailed mathematical treatment of the reconstruction method, the reader is referred to Jones et al (1999) and Luterbacher et al (2001).…”

Section: Methodsmentioning

confidence: 99%

Extending North Atlantic oscillation reconstructions back to 1500

Syroka

2001

Atmospheric Science Letters

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Monthly (1659±1995) and seasonal (1500±1658) North Atlantic Oscillation (NAO) indices were estimated using instrumental and documentary proxy predictors from Eurasia. Uncertainty estimates were calculated for the reconstructions, and the variability of the 500-year winter NAO has been assessed. The late twentieth century NAO extremes are within the range of variability during earlier centuries.*

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Section: Methodsmentioning

confidence: 99%

Extending North Atlantic oscillation reconstructions back to 1500

Syroka

2001

Atmospheric Science Letters

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“…These grid-point data are of good quality over our study region because of the dense observation network available (Jones et al, 1999). Circulation indices for the period 1780-1872 were derived from the MSLP dataset developed by Jones et al (1999), who used a network of 10 to 51 monthly pressure series as predictors, with the UKMO MSLP data being the predictand, to reconstruct gridded pressure data over the region 35-70°N, 30°W-40°E using orthogonal spatial regression. The explained variances in their analysis ranged from 90% in January to 70% in July around the entire European region when all 51 stations were available.…”

Section: Circulation Datamentioning

confidence: 99%

“…Although there has been a renewed interest in the early European records in the last decade (e.g. Jones et al, 1999;Böhm et al, 2001;Camuffo and Jones, 2002), there still remain This paper is organized as follows. Section 2 provides details of our reasons to doubt the warm summers before around 1860.…”

Section: Introductionmentioning

confidence: 99%

Were southern Swedish summer temperatures before 1860 as warm as measured?

Moberg

Alexandersson

Bergström

et al. 2003

Intl Journal of Climatology

102

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Temperature series from Stockholm and Uppsala in southern Sweden indicate that summers from the mid-18th century until around 1860 were, on average, warmer than the 1961-90 mean. The station histories suggest that the early observations could have been positively biased, for example because of insufficient radiation protection. We investigate if independent support for warm summers in the early period can be obtained from other climate variables. Using stepwise multiple regression analysis we investigate nine potential predictor variables: six air circulation indices, precipitation, air pressure and cloud amount. Three of these variables -cloud amount (the most important one), meridional geostrophic wind, and air pressure -together explain 65% of the June-August temperature variance in the calibration period 1873-2000. Application of the regression relationship back to 1780 shows that the model is equally successful in predicting year-toyear temperature variability before 1873 as it is in the calibration period, whereas the low-frequency component is poorly reconstructed in the early period. This reduced skill is primarily due to poorer data quality of the predictor variables in the early period, in particular the cloud amount series. The observed decadal mean temperatures during 1780-1860 are found to be above the upper limit of a 95% confidence interval that accounts for uncertainties both in the regression relationship and in the cloud amount series. We conclude that the observed temperatures before around 1860 are, therefore, most likely positively biased. The size of this bias cannot be accurately determined from the evidence used here, but seems to be about 0.7-0.8°C for both stations. A comparison with long instrumental temperature series from central Europe suggests a slightly smaller bias (0.5-0.6°C). For more accurate assessment of the Stockholm and Uppsala temperatures, we recommend that extensive homogeneity testing of other long northern European temperature series are undertaken.

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“…The classifications and indices are usually based on observed sea level pressure (SLP) data, sometimes in combination with geopotential heights or by the latter only. The observed pressure data are less affected by inhomogeneities than are other climate variables, which makes it possible to analyse long time series (Jones et al, 1999).…”

Section: Introductionmentioning

confidence: 99%

Objective classification of atmospheric circulation over southern Scandinavia

Linderson

2001

Intl Journal of Climatology

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A method for calculating circulation indices and weather types following the Lamb classification is applied to southern Scandinavia. The main objective is to test the ability of the method to describe the atmospheric circulation over the area, and to evaluate the extent to which the pressure patterns determine local precipitation and temperature in Scania, southernmost Sweden. The weather type classification method works well and produces distinct groups. However, the variability within the group is large with regard to the location of the low pressure centres, which may have implications for the precipitation over the area. The anticyclonic weather type dominates, together with the cyclonic and westerly types. This deviates partly from the general picture for Sweden and may be explained by the southerly location of the study area. The cyclonic type is most frequent in spring, although cloudiness and amount of rain are lowest during this season. This could be explained by the occurrence of weaker cyclones or low air humidity during this time of year. Local temperature and precipitation were modelled by stepwise regression for each season, designating weather types as independent variables. Only the winter season-modelled temperature and precipitation show a high and robust correspondence to the observed temperature and precipitation, even though B 60% of the precipitation variance is explained. In the other seasons, the connection between atmospheric circulation and the local temperature and precipitation is low. Other meteorological parameters may need to be taken into account. The time and space resolution of the mean sea level pressure (MSLP) grid may affect the results, as many important features might not be covered by the classification. Local physiography may also influence the local climate in a way that cannot be described by the atmospheric circulation pattern alone, stressing the importance of using more than one observation series.

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Monthly mean pressure reconstructions for Europe for the 1780–1995 period

Cited by 117 publications

References 10 publications

Extending North Atlantic oscillation reconstructions back to 1500

Extending North Atlantic oscillation reconstructions back to 1500

Were southern Swedish summer temperatures before 1860 as warm as measured?

Objective classification of atmospheric circulation over southern Scandinavia

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