Abstract
In time series of essential climatological variables, many discontinuities are created not by climate factors but changes in the measuring system, including relocations, changes in instrumentation, exposure or even observation practices. Some of these changes occur due to reorganization, cost-efficiency or innovation. In the last few decades, station movements have often been accompanied by the introduction of an automatic weather station (AWS). Our study identifies the biases in daily maximum and minimum temperatures using parallel records of manual and automated observations. They are selected to minimize the differences in surrounding environment, exposition, distance and difference in elevation. Therefore, the type of instrumentation is the most important biasing factor between both measurements. The pairs of weather stations are located in Piedmont, a region of Italy, and in Gaspé Peninsula, a region of Canada. They have 6 years of overlapping period on average, and 5110 daily values. The approach implemented for the comparison is divided in four main parts: a statistical characterization of the daily temperature series; a comparison between the daily series; a comparison between the types of events, heat wave, cold wave and normal events; and a verification of the homogeneity of the difference series. Our results show a higher frequency of warm (+ 10%) and extremely warm (+ 35%) days in the automated system, compared with the parallel manual record. Consequently, the use of a composite record could significantly bias the calculation of extreme events.
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Data availability
Supplementary data and the program source code associated with this article can be found at https://github.com/UniToDSTGruppoClima/CoTemp (Guenzi et al. in press).
References
Acquaotta F, Fratianni S, Cassardo C, Cremonini R (2009) On the continuity and climatic variability of meteorological stations in Torino, Asti, Vercelli and Oropa. Met Atmos Phys 103:279–287
Acquaotta F, Fratianni S, Garzena D (2015) Temperature changes in the North-Western Italian Alps from 1961 to 2010. Theor Appl Climatol 122:619–634
Acquaotta F, Fratianni S, Venema V (2016) Assessment of parallel precipitation measurements networks in Piedmont, Italy. Int J Climatol 36(12):3963–3974
Alexander L, Herold N (2015) ClimPACTv2 indices and software. A document prepared on behalf of the Commission for Climatology (CCl) Expert Team on Sector-Specific Climate Indices (ET-SCI), Sydney
Alexandersson H, Moberg A (1997) Homogenization of Swedish temperature data. Part I : homogeneity test for linear trends. Int J Climatol 14:25–34
Auer I, Bohm R, Jurkovic A, Lipa W et al (2007) HISTALP: historical instrumental climatological surface time series of the Greater Alpine Region. Int J Climatol 27:17–46. https://doi.org/10.1002/joc.1377
Baronetti A, Acquaotta F, Fratianni S (2018) Rainfall variability from a dense rain gauge network in North -West Italy. Clim Res 75(3):201–213
Bertiglia F, Lopardo G, Merlone A, Roggero G, Cat Berro D, Mercalli L, Gilabert A, Brunet M (2014) Traceability of ground-based air-temperature measurements: a case study on the Meteorological Observatory of Moncalieri (Italy). Int J Thermodyn. https://doi.org/10.1007/s10765-014-1806-y
Biancotti A, Destefanis E, Fratianni S, Masciocco L (2005) On precipitation and hydrology of Susa Valley (Western Alps). Geogr Fis Dinam Quat VII:51–58
Brohan P, Kennedy JJ, Harris I, Tett SF, Jones PD (2006) Uncertainty estimates in regional and global observed temperature changes: a new data set from 1850. J Geophys Res Atm 111(D12):1–21
Capers RS, Kimball KD, McFarland KP, Jones MT, Lloyd AH, Munroe JS, Fortin G, Mattrick C, Goren J, Sperduto DD, Paradis R (2013) Establishing alpine research priorities in northeastern North America. Northeast Nat 20(4):559–577
Changnon SA, Kunkel KE (2006) Changes in instruments and sites affecting historical weather records: a case study. J Atm Ocean Technol 23:825–828
Davey CA, Pielke RA (2005) Microclimate exposures of surface based weather stations. Bull Am Met Soc 86:497–504
Della-Marta P, Wanner H (2006) A method of homogenizing the extremes and mean of daily temperature measurements. J Clim 19:4179–4197. https://doi.org/10.1175/JCLI3855.1
Dodson R, Marks D (1997) Daily air temperature interpolated at high spatial resolution over a large mountainous region. Clim Res 8:1–20
Environment Canada (2018) Canadian climate normals 1981–2010. http://ftp.tor.ec.gc.ca/Pub/Documentation_Canadian_Climate_Normals/1981_2010/Canadian_Climate_Normals_1981_2010_Calculation_Information.pdf
Esper J, Cook ER, Schweingruber FH (2002) Low-frequency signals in long tree-ring chronologies for reconstructing past temperature variability. Science 295(5563):2250–2253
Fazzini M, Fratianni S, Biancotti A, Billi P (2004) Skiability conditions in several skiing complexes on Piedmontese and Dolomitic Alps. Meteorol Z 13(3):253–258
Fiebrich CA, Crawford KC (2009) Automation: a step toward improving the equality of daily temperature data produced by climate observing networks. J Atmos Ocean Technol 26:1246–1260
Fortin G, Acquaotta F, Fratianni S (2017) The evolution of temperature extremes in the Gaspé Peninsula, Quebec, Canada (1974-2013). Theor Appl Climatol 130(1–2):163–172
Fratianni S, Acquaotta F (2017) The climate of Italy. In: Marchetti M, Soldati M (eds) Landscapes and landforms of Italy. Springer Cham, pp 29–38
Fratianni S, Cassardo C, Cremonini R (2009) Climatic characterization of foehn episodes in Piedmont, Italy. Geogr Fis Dinam Quat 22:15–22
Gallo KP (2005) Evaluation of temperature differences for paired stations of the U. S. Climate Reference Network. J Clim Notes and Correspondence 18:1629–1636
Giaccone E, Colombo N, Acquaotta F, Paro L, Fratianni S (2015) Climate variations in a high altitude Alpine basin and their effects on a glacial environment (Italian Western Alps). Atmosfera 28:117–128
Grykalowska A, Kowal A, Szmyrka-Grzebyk A (2015) The basics of calibration procedure and estimation of uncertainty budget for meteorological temperature sensors. Met Apps 22:867–872
Guenzi D, Acquaotta F, Garzena D, Fratianni S (2017) CoRain: a free and open source software for rain series comparison. Earth Sci Inform 10(3):405–416
Guenzi D, Acquaotta F, Garzena D, Baronetti A, Fratianni S (in press) An algorithm for daily temperature comparison: co. temp - comparing series of temperature. Earth Sci Inform
Hausfather Z, Cowtan K, Menne MJ, Claude NW (2016) Evaluating the impact of U.S. Historical Climatology Network homogenization using the U.S. Climate Reference Network. Geophys Res Lett:1695–1701
Hubbard KG, Lin X (2006) Reexamination of instrument change effects in the US Historical Climatology Network. Geophys Res Lett 33(15):1–4
Isotta F, Frei C, Weilguni V, Tadic M, Lassègues P, Rudolf B, Pavan V, Cacciamani C, Antolini G, Ratto S, Munari M, Micheletti S, Bonati V, Lussana C, Ronchi C, Panettieri E, Marigo G, Vertacnik G (2013) The climate of daily precipitation in the Alps: development and analysis of a high-resolution grid dataset from pan-Alpine rain-gauge data. Int J Climatol 34:1657–1675
Karl TR, Derr V, Easterling D, Folland C, Hofmann D, Levitus S, Nicholls N, Parker D, Withee G (1995) Critical issue for long term climate monitoring. Clim Chang 31:185–221
Karl TR, Arguez A, Huang B, Lawrimore JH, McMahon JR, Menne MJ, Peterson TC, Zhang HM (2015) Possible artifacts of data biases in the recent global surface warming hiatus. Science 348(6242):1469–1472
Leeper RD, Rennie J, Palecki MA (2015) Observational perspectives from U.S. Climate Reference Network (USCRN) and Cooperative Observer Program (COOP) Network: temperature and precipitation comparison. J Atm Ocean Technol 32:703–721
Lejeune Q, Davin EL, Guillod BP, Seneviratne SI (2015) Influence of Amazonian deforestation on the future evolution of regional surface fluxes, circulation, surface temperature and precipitation. Clim Dyn 44(9–10):2769–2786
Lepage MP, Bourgeois G (2011) Le réseau québécois de stations météorologiques et l’information générée pour le secteur agricole. Centre de référence en agriculture et agroalimentaire du Québec (CRAAQ), Québec http://www.agrometeo.org/help/le_reseau_quebecois_de_stations_meteo.pd f
Luterbacher J, Dietrich D, Xoplaki E, Grosjean M, Wanner H (2004) European seasonal and annual temperature variability, trends, and extremes since 1500. Science 303(5663):1499–1503
Mestre O, Gruber C, Prieur C, Caussinus H, Jourdain S (2011) SPLIDHOM: a method for homogenization of daily temperature observations. J Appl Meteorol Climatol 50:2343–2358
Milewska EJ, Vincent LA (2016) Preserving continuity of long-term daily maximum and minimum temperature observations with automation of reference climate stations using overlapping data and meteorological conditions. Atmos-Ocean 54(1):32–47
Ministry of Sustainable Development, Environment and Fight against Climate Change (MSDEFCC) (2017) Données du Programme de surveillance du climat, Direction générale du suivi de l’état de l’environnement, Québec
Nicholls N (1995) Long-term climate monitoring and extreme events. Clim Chang 31:231–245
Nigrelli G, Fratianni S, Zampollo A, Turconi L, Chiarle M (2018) The altitudinal temperature lapse rates applied to high elevation rock falls studies in the Western European Alps. Theor Appl Climatol 131(3–4):1479–1491
Pauli H, Gottfried M, Reiter K, Klettner C, Grabherr G (2007) Signals of range expansions and contractions of vascular plants in the high Alps: observations (1994–2004) at the GLORIA master site Schrankogel, Tyrol, Austria. Glob Chang Biol 13(1):147–156
Peterson TC (2003) Assessment of urban versus rural in situ surface temperatures in the contiguous United States: no difference found. J Clim 16:2941–2959
Peterson TC, Easterling DR, Karl TR, Groisman P, Nicholls N, Plummer N, Torok S, Auer I, Boehm R, Gullet D, Vincent L, Heino R, Tuomenvirta H, Mestre O, Szentimrey T, Salinger JF, Rland E, Alexandersson H, Jones P, Parker D (1998) Homogeneity adjustments of in situ atmospheric climate data : a review. Int J Climatol 18:1493–1517
Reynolds RW, Chelton DB (2010) Comparisons of daily sea surface temperature analyses for 2007–08. J Clim 23:3545–3562
Rolland C (2003) Spatial and seasonal variations of air temperature lapse rates in alpine regions. Journal of Climate 16:1032–1046
Squintu A, van der Schrier G, Brugnara Y, Klein Tank A (2019) Homogenization of daily temperature series in the European Climate Assessment & Dataset. Int J Climatol 39:1243–1261
Stocker T (Ed.), (2014) Climate change 2013: the physical science basis: Working Group I contribution to the Fifth assessment report of the Intergovernmental Panel on Climate Change. Cambridge University Press
Terzago S, Cremonini R, Cassardo C, Fratianni S (2012) Analysis of snow precipitation during the period 2000-09 and evaluation of a MSG/SEVIRI snow cover algorithm in SW Italian Alps. Geogr Fis Dinam Quat 35(1):91–99
Thorne PW, Menne MJ, Williams CN, Rennie JJ, Lawrimore JH, Vose RS, Peterson TC, Durre I, Davy R, Esau I, Klein-Tank AMG, Merlone A (2016) Reassessing changes in diurnal temperature range: a new data set and characterization of data biases. J Geophys Res Atmos. https://doi.org/10.1002/2015JD024583
Trewin BC (2005) A notable frost hollow at Coonabarabran, New South Wales. Aust Meteorol Mag 54:15–21
Trewin B (2010) Exposure, instrumentation, and observing practice effects on land temperature measurements. Wiley Interdiscip Rev Clim Chang 1(4):490–506
Trewin BC, Trevitt ACF (1996) The development of composite temperature records. Int J Climatol 16:1227–1242
Vincent LA, Mekis E (2009) Discontinuities due to joining precipitation station observations in Canada. J Appl Met Climatol 48(1):156–166
Vincent L, Milewska E, Wang X, Hartwell M (2018) Uncertainty in homogenized daily temperatures and derived indices of extremes illustrated using parallel observations in Canada. Int J Climatol 38:692–707
Wang XL (2008a) Penalized maximal F test for detecting undocumented mean shift without trend change. J Atmos Ocean Technol 25(3):368–384
Wang XL (2008b) Accounting for autocorrelation in detecting mean shifts in climate data series using the penalized maximal t or F test. J Appl Met Climatol 47(9):2423–2444
Wang XL and Feng Y (2013) RHtestsV4 User Manual. Climate Research Division, Atmospheric Science and Technology Directorate, Science and Technology Branch, Environment Canada. 28 pp. [Available online at http://etccdi.pacificclimate.org/software.shtml]
Wang XL, Wen QH, Wu Y (2007) Penalized maximal t test for detecting undocumented mean change in climate data series. J Appl Met Climatol 46(6):916–931
Willett K, Williams C, Jolliffe IT, Lund R, Alexander LV, Bronnimann S, Vincent LA, Easterbrook S, Venema VKC, Berry D, Warren RE, Lopardo G, Auchmann R, Aguilar E, Menne MJ, Gallagher C, Hausfather Z, Thorarinsdottir T, Thorne PW (2014) A framework for benchmarking homogenisation algorithm performance on the global scale. Geosci Instrum Method Data Syst 3:187–200. https://doi.org/10.5194/gi-3-187-2014
Williams CN, Menne MJ, Thorne PW (2012) Benchmarking the performance of pairwise homogenisation of surface temperatures in the United States. J Geophys Res Atmos 117:1–16
WMO (2007) Guidelines for managing changes in climate observation programmes. World Meteorological Organization, World Climate Data and Monitoring Programme series, WCDMP-No. 62, WMO-TD No. 1378, Geneva
Yue S, Pilon P, Phinney B, Cavadias G (2002) The influence of autocorrelation on the ability to detect trend in hydrological series. Hydrol Process 16:1807–1829
Zhang X, Yang F (2013) RClimDex (1.1) User Guide. Climate Research Branch Environment Canada: Downs view, Ontario
Acknowledgements
This research was developed in the framework of the project Nexdata_Nextsnow (national coordinator, V. Levizzani; unit scientific responsible, S. Fratianni). We greatly thank the Ministry of Sustainable Development, Environment and Fight against Climate Change (MSDEFCC) (Province of Quebec) for providing the weather data for the Gaspé Peninsula area. The authors would like to thank Jeremy Hayhoe and Elisabeth Marchand for proofreading assistance.
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Acquaotta, F., Fratianni, S., Aguilar, E. et al. Influence of instrumentation on long temperature time series. Climatic Change 156, 385–404 (2019). https://doi.org/10.1007/s10584-019-02545-z
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DOI: https://doi.org/10.1007/s10584-019-02545-z