Long-period weather observations elsewhere in the British Isles and Europe

2019 ◽  
pp. 56-68
Author(s):  
Stephen Burt ◽  
Tim Burt
Keyword(s):  
Temperature Series ◽  
Daily Temperature ◽  
Continuous Series ◽  
British Isles ◽  
Long Period ◽  
Weather Observations ◽  
Central England Temperature ◽  
Weather Stations ◽  
Temperature Records

This chapter summarises other long-period weather observations from both the British Isles and Europe. The Radcliffe Observatory possesses the longest continuous series of weather records in Britain for one site: the first observations date from the mid-1760s, with unbroken daily temperature records since November 1813. It includes references to Gordon Manley’s Central England Temperature series. There are brief descriptions of the longest-running weather stations in Europe, including Uppsala and Stockholm in Sweden, Padua and Milan in Italy, Hohenpeissenberg in Germany, and the British observatories at Kew, Armagh and Durham, many (like Oxford) starting life as astronomical observatories in the eighteenth or early nineteenth centuries. The chapter ends with a brief comment as to why such long weather records remain important in the present day.

Mending and extending observational temperature series by linear and nonlinear regression

2021 ◽  
Author(s):  
Jiří Mikšovský ◽  
Petr Štěpánek
Keyword(s):  
Nonlinear Regression ◽  
Temperature Series ◽  
The Czech Republic ◽  
Improve Accuracy ◽  
Potential Benefits ◽  
Regression Techniques ◽  
Weather Stations ◽  
Temperature Records ◽  
Daily Temperature Series ◽  
Target Locations

<p>While time series of meteorological measurements from land-based weather stations still represent one of the basic types of data employed in climate research, it not uncommon for these records to be incomplete, interrupted by periods of missing or otherwise compromised values. Such gaps typically need to be filled before a subsequent analysis can be performed, and records from other nearby measuring sites are frequently used for this purpose. In this presentation, results of central European daily temperatures estimation from other concurrent measurements by various statistical methods are showcased, with a particular emphasis on assessing potential benefits of application of nonlinear regression techniques. Using multi-decadal daily temperature series originating from a dense network of weather stations covering the territory of the Czech Republic, we show that while nonlinear regression does not always outperform its linear counterpart, it can substantially improve accuracy of temperature estimates for some target locations. The gain is shown to be especially prominent for sites exhibiting atypical behavior compared to their local geographic neighborhood, such as isolated mountain-based stations. In addition to regression-based restoration of compromised segments in the temperature records, use of this methodology for extending the temperature records beyond their original period of measurements is also discussed, as well as its potential for homogeneity testing.</p>

scholarly journals Nonlinear correlations of daily temperature records over land

2006 ◽  
Vol 13 (5) ◽  
pp. 571-576 ◽  
Author(s):  
I. Bartos ◽  
I. M. Jánosi
Keyword(s):  
Daily Temperature ◽  
Fluctuation Analysis ◽  
Temperature Changes ◽  
Temporal Correlations ◽  
Temperature Records ◽  
Global Statistics ◽  
Correlation Properties ◽  
Nonlinear Correlations ◽  
Detrended Fluctuation ◽  
Temperature Time

Abstract. We present a near global statistics on the correlation properties of daily temperature records. Data from terrestrial meteorological stations in the Global Daily Climatology Network are analyzed by means of detrended fluctuation analysis. Long-range temporal correlations extending up to several years are detected for each station. In order to reveal nonlinearity, we evaluated the magnitude of daily temperature changes (volatility) by the same method. The results clearly indicate the presence of nonlinearities in temperature time series, furthemore the geographic distribution of correlation exponents exhibits well defined clustering.

scholarly journals The longest homogeneous series of grape harvest dates, Beaune 1354–2018, and its significance for the understanding of past and present climate

2019 ◽  
Vol 15 (4) ◽  
pp. 1485-1501 ◽  
Author(s):  
Thomas Labbé ◽  
Christian Pfister ◽  
Stefan Brönnimann ◽  
Daniel Rousseau ◽  
Jörg Franke ◽  
...  
Keyword(s):  
Temperature Series ◽  
Present Climate ◽  
Atmospheric Blocking ◽  
Central European ◽  
Phenological Data ◽  
Long Period ◽  
The Past ◽  
Harvest Dates ◽  
Early Harvest ◽  
July Temperature

Abstract. Records of grape harvest dates (GHDs) are the oldest and the longest continuous phenological data in Europe. However, many available series, including the well-known (Dijon) Burgundy series, are error prone because scholars so far have uncritically drawn the data from 19th century publications instead of going back to the archives. The GHDs from the famous vine region of Beaune (Burgundy) were entirely drawn from the archives and critically cross-checked with narrative evidence. In order to reconstruct temperature, the series was calibrated against the long Paris temperature series comprising the 360 years from 1659 to 2018. The 664-year-long Beaune series from 1354 to 2018 is also significantly correlated with tree-ring and documentary proxy evidence as well as with the central European temperature series (from 1500). The series is clearly subdivided into two parts. From 1354 to 1987 grapes were on average picked from 28 September on, whereby during the last 31-year-long period of rapid warming from 1988 to 2018 harvests began 13 d earlier. Early harvest dates are shown to be accompanied by high pressure over western–central Europe and atmospheric blocking over Denmark. The 33 extremely early harvests comprising the fifth percentile bracket of GHDs are unevenly distributed over time; 21 of them occurred between 1393 and 1719, while this is the case for just 5 years between 1720 and 2002. Since the hot summer of 2003, 8 out of 16 spring–summer periods were outstanding according to the statistics of the last 664 years, no less than 5 among them within the last 8 years. In the Paris temperature measurements since 1659, April-to-July temperature reached the highest value ever in 2018. In sum, the 664-year-long Beaune GHD series demonstrates that outstanding hot and dry years in the past were outliers, while they have become the norm since the transition to rapid warming in 1988.

A Comparison of Daily Temperature-Averaging Methods: Spatial Variability and Recent Change for the CONUS

2018 ◽  
Vol 31 (3) ◽  
pp. 979-996 ◽  
Author(s):  
Jase Bernhardt ◽  
Andrew M. Carleton ◽  
Chris LaMagna
Keyword(s):  
Spatial Variability ◽  
Daily Temperature ◽  
Maximum Temperature ◽  
Underlying Assumption ◽  
First Order ◽  
Daily Average ◽  
Hourly Temperature ◽  
Significant Difference ◽  
Weather Stations

Abstract Traditionally, the daily average air temperature at a weather station is computed by taking the mean of two values, the maximum temperature (Tmax) and the minimum temperature (Tmin), over a 24-h period. These values form the basis for numerous studies of long-term climatologies (e.g., 30-yr normals) and recent temperature trends and changes. However, many first-order weather stations—such as those at airports—also record hourly temperature data. Using an average of the 24 hourly temperature readings to compute daily average temperature has been shown to provide a more precise and representative estimate of a given day’s temperature. This study assesses the spatial variability of the differences in these two methods of daily temperature averaging [i.e., (Tmax + Tmin)/2; average of 24 hourly temperature values] for 215 first-order weather stations across the conterminous United States (CONUS) over the 30-yr period 1981–2010. A statistically significant difference is shown between the two methods, as well as consistent overestimation of temperature by the traditional method [(Tmax + Tmin)/2], particularly in southern and coastal portions of the CONUS. The explanation for the long-term difference between the two methods is the underlying assumption for the twice-daily method that the diurnal curve of temperature is symmetrical. Moreover, this paper demonstrates a spatially coherent pattern in the difference compared to the most recent part of the temperature record (2001–15). The spatial and temporal differences shown have implications for assessments of the physical factors influencing the diurnal temperature curve, as well as the exact magnitude of contemporary climate change.

Climate change and the adoption of agriculture in north-west Europe

2002 ◽  
Vol 5 (1) ◽  
pp. 9-23 ◽  
Author(s):  
Clive Bonsall ◽  
Mark G. Macklin ◽  
David E. Anderson ◽  
Robert W. Payton
Keyword(s):  
Climate Change ◽  
Agricultural Expansion ◽  
British Isles ◽  
Agricultural Frontier ◽  
North West ◽  
Long Period ◽  
Northern France ◽  
The North ◽  
Northern Poland ◽  
Southern Scandinavia

Farming can be shown to have spread very rapidly across the British Isles and southern Scandinavia around 6000 years ago, following a long period of stasis when the agricultural ‘frontier’ lay further south on the North European Plain between northern France and northern Poland. The reasons for the delay in the adoption of agriculture on the north-west fringe of Europe have been debated by archaeologists for decades. Here, we present fresh evidence that this renewed phase of agricultural expansion was triggered by a significant change in climate. This finding may also have implications for understanding the timing of the expansion of farming into some upland areas of southern and mid-latitude Europe.

Subarea characteristics of the long-range correlations and the index χ for daily temperature records over China

2012 ◽  
Vol 109 (1-2) ◽  
pp. 261-270 ◽  
Author(s):  
Lei Jiang ◽  
Naiming Yuan ◽  
Zuntao Fu ◽  
Dongxiao Wang ◽  
Xia Zhao ◽  
...  
Keyword(s):  
Long Range ◽  
Daily Temperature ◽  
Long Range Correlations ◽  
Temperature Records

scholarly journals Asymmetry of Daily Temperature Records

2008 ◽  
Vol 65 (10) ◽  
pp. 3327-3336 ◽  
Author(s):  
Yosef Ashkenazy ◽  
Yizhak Feliks ◽  
Hezi Gildor ◽  
Eli Tziperman
Keyword(s):  
Daily Temperature ◽  
High Latitudes ◽  
Atmospheric Conditions ◽  
Cyclone Activity ◽  
Radiative Relaxation ◽  
Cold Air ◽  
Cold Fronts ◽  
Mean Temperature ◽  
Temperature Records

The authors study the NCEP–NCAR reanalysis temperature records and find that surface daily mean temperature cools rapidly and warms gradually at the midlatitudes (around 40°N and 40°S). This “asymmetry” is partially related to the midlatitude cyclone activity, in which cold fronts are significantly faster and steeper than warm fronts, and to intrusions of cold air. The gradual warming may be attributed also to the radiative relaxation to average atmospheric conditions after the passage of cold fronts or other intrusions of cold air. At the high latitudes there is an opposite asymmetry with rapid warming and gradual cooling; this asymmetry may be attributed to the radiative relaxation to average cold atmospheric conditions after the passage of warm fronts or intrusions of warm air.

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