Looking over your opponent's shoulder An analysis of New Labour's political strategy, and a proposal for defeating it

SIGLEAvailable from British Library Document Supply Centre-DSC:m01/12852 / BLDSC - British Library Document Supply CentreGBUnited Kingdo

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

Monthly grid-point pressure data are reconstructed from station records of pressure for Europe since 1780. The region encompasses 35-70°N to 30°W-40°E. The reconstructions are based on a principal components regression technique, which relates surface pressure patterns to those of the station pressure data. The relationships are derived over a calibration period (1936-1995) and the results tested with independent data (the verification period, 1881-1935). The reconstructions are of excellent quality, although this is slightly lower for regions with poor station coverage in the early years, particularly during the summer months. The reconstructions are compared with other monthly mean pressure maps produced by Lamb and Johnson (1966) for the years 1780-1872 and by Kington (1980, 1988) for 1781-1785. Both of these map series show systematic biases relative to the present reconstructions

Monthly mean pressure reconstruction for the Late Maunder Minimum Period (AD 1675-1715)

The Late Maunder Minimum (LMM; 1675-1715) delineates a period with marked climate variability within the Little Ice Age in Europe. Gridded monthly mean surface pressure fields were reconstructed for this period for the eastern North Atlantic-European region (25°W-30°E and 35-70°N). These were based on continuous information drawn from proxy and instrumental data taken from several European data sites. The data include indexed temperature and rainfall values, sea ice conditions from northern Iceland and the Western Baltic. In addition, limited instrumental data, such as air temperature from central England (CET) and Paris, reduced mean sea level pressure (SLP) at Paris, and monthly mean wind direction in the Oresund (Denmark) are used. The reconstructions are based on a canonical correlation analysis (CCA), with the standardized station data as predictors and the SLP pressure fields as predictand. The CCA-based model was performed using data from the twentieth century. The period 1901-1960 was used to calibrate the statistical model, and the remaining 30 years (1961-1990) for the validation of the reconstructed monthly pressure fields. Assuming stationarity of the statistical relationships, the calibrated CCA model was then used to predict the monthly LMM SLP fields. The verification results illustrated that the regression equations developed for the majority of grid points contain good predictive skill. Nevertheless, there are seasonal and geographical limitations for which valid spatial SLP patterns can be reconstructed. Backward elimination techniques indicated that Paris station air pressure and temperature, CET, and the wind direction in the Oresund are the most important predictors, together sharing more than 65% of the total variance. The reconstructions are compared with additional data and subjectively reconstructed monthly pressure charts for the years 1675-1704. It is shown that there are differences between the two approaches. However, for extreme years the reconstructions are in good agreement

Forest resilience to drought varies across biomes

16 Pags.- 3 Tabls.- 5 Figs.Forecasted increase drought frequency and severity may drive worldwide declines in forest productivity. Species‐level responses to a drier world are likely to be influenced by their functional traits. Here, we analyse forest resilience to drought using an extensive network of tree‐ring width data and satellite imagery. We compiled proxies of forest growth and productivity (TRWi, absolutely dated ring‐width indices; NDVI, Normalized Difference Vegetation Index) for 11 tree species and 502 forests in Spain corresponding to Mediterranean, temperate, and continental biomes. Four different components of forest resilience to drought were calculated based on TRWi and NDVI data before, during, and after four major droughts (1986, 1994–1995, 1999, and 2005), and pointed out that TRWi data were more sensitive metrics of forest resilience to drought than NDVI data. Resilience was related to both drought severity and forest composition. Evergreen gymnosperms dominating semi‐arid Mediterranean forests showed the lowest resistance to drought, but higher recovery than deciduous angiosperms dominating humid temperate forests. Moreover, semi‐arid gymnosperm forests presented a negative temporal trend in the resistance to drought, but this pattern was absent in continental and temperate forests. Although gymnosperms in dry Mediterranean forests showed a faster recovery after drought, their recovery potential could be constrained if droughts become more frequent. Conversely, angiosperms and gymnosperms inhabiting temperate and continental sites might have problems to recover after more intense droughts since they resist drought but are less able to recover afterwards.This study was financially supported by the Spanish Ministry of Economy projects: CGL2015‐69186‐C2‐1‐R (Fundiver), CGL2015‐69985‐R (CLIMED), CGL2013‐48843‐C2‐1‐R (CoMo‐ReAdapt), AGL2014‐53822‐C2‐1‐R (SATIVA), XIRONO (BFU2010‐21451), CGL2014‐52135‐C03‐01, PCIN‐2015‐220, and CGL2016‐81706‐REDT (Ecometas Network). The study was also funded by IMDROFLOOD (Water Works 2014, EC) and INDECIS (European Research Areas for Climate Services) projects. This work also benefited from funding from Xunta de Galicia (PGIDIT06PXIB502262PR, GRC GI‐1809, ROCLIGAL‐10MDS291009PR), INIA (RTA2006‐00117), and Interreg V‐A POCTEFA (CANOPEE, 2014‐2020‐FEDER funds) projects. RSS and AG were supported by Postdoctoral grants (IJCI‐2015‐25845 and MINECO‐FPDI 2013‐16600; FEDER funds).Peer reviewe