Abstract
A good climatic analysis requires accurate and homogeneous daily precipitation series; unluckily, inhomogeneity is frequently found and have to be considered, especially when it is due to non-climatic parameters. CoRain is a free and open source software written in R language that could greatly help analyzing inhomogeneity caused by rainfall measuring instruments. CoRain compares two parallel rain series (with an overlapping period) and tries to highlight overestimations and underestimations due to rain gauges in a specific condition, so that the user can consider it for future analysis. CoRain offers many information on the two analyzed series, starting with cleaning input data, comparing them and classifying rainy days by severity. CoRain is a cross-platform software, easily adaptable to different needs, that takes in input a single text file with daily information of the two rain series and outputs tables (in CSV format) and plots (as PNG images) that help in the interpretation of the data. Use of the program is very simple: the execution can be either interactive or non-interactive. CoRain code has been tested on different rain series in the Piedmont region (northwestern Italy), showing its importance in identifying climate variations and instrumentation errors.
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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. Meteorog Atmos Phys 103:279–287. doi:10.1007/s00703-008-0333-4
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. doi:10.1007/s00704-014-1316-7
Acquaotta F, Fratianni S, Venema V (2016) Assessment of parallel precipitation measurements networks in Piedmont, Italy Int J Climatol, doi: 10.1002/joc.4606
Aguilar E, Auer I, Brunet M, Peterson TC, Wieringa J. (2003) Guidelines on climate metadata and homogenization. WMO-TD No. 1186, WCDMP No. 53, World Meteorological Organization, Geneva (Switzerland) 52 pp
Baciu M, Copaciu V, Breza T, Cheval S, Pescaru IV (2005) Preliminary results obtained following the intercomparison of the meteorological parameters provided by automatic and classical stations in Romania. In WMO technical conference on meteorological and environmental instruments and methods of Observation (TECO-2005), Bucharest
Bodtmann W, Ruthroff C (1976) The measurement of 1 min rain rates from weighing raingage recording. J Appl Meteorol 15:1160–1166
Boroneant C, Baciu M, Orzan A (2006) On the statistical parameters calculated for the essential climatological variables during 2-years of parallel observations with automatic and classical stations in Romania. In 5th Seminar on Homogenization and Data Quality in the Climatological Databases, Budapest
Brunet M, Saladié O, Jones P, Sigrò J, Aguilar E, Moberg A, Lister D, Walther A, Lòpez D, Almarza C (2006) The development of a new daily adjusted temperature dataset for Spain (1850 – 2003). Int J Climatol 26:1777–1802. doi:10.1002/joc.1338
Forland EJ, Alexandersson H, Dahlstrom B, Drebs A, Frich P, Hanssen-Bauer I, Heino R, Helminen J, Jhonsson T, Nordli PO, Palsdottir T, Smith T, Tuomenvirta H, Tveito OE, Vedin H (1998) Reward: relating extreme weather to atmospheric circulation using a regionalized dataset, final report (1996–1998). DNMI Report 17/98 KLIMA
Free Software Foundation (2007) GNU general public license (GPL v3). Available online at http://www.gnu.org/licenses/gpl.html Accessed on 19 June 2016
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
Gilabert A (2016) Assessment of the bias introduced by the automatisation of climate record combining climatological and meteorological. Ph.D Thesis, Geography Department Centre for Climate Change, p 209
Göktürk OM, Bozkurt D, Şen OL, Karaca M (2008) Quality control and homogeneity of Turkish precipitation data. Hydrol Process 22(16):3210–3218. doi:10.1002/hyp.6915
Gonzalez-Rouco JF, Jimenez JF, Quesada V, Valero F (2001) Quality control and homogeneity of precipitation data in the southwest of Europe. J Clim 14:964–978
Goodison BE, Louie PYT, Yang D (1998) WMO solid precipitation measurement intercomparison - final report. WMO-TD No. 872, instruments and observing methods report No. 67, World Meteorological Organization, Geneva (Switzerland) 318 pp
Guenzi D, Fratianni S, Boraso R, Cremonini R (2016) CondMerg: an open source implementation in R language of conditional merging for weather radars and rain gauges observations. Earth Sci Inf. doi:10.1007/s12145-016-0278-y
Heino R (1994) Climate in Finland during the period of meteorological observations. Finnish Meteorological Institute Contributions, 12, 209
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. doi:10.1002/joc.3794
Karl TR, Williams C (1987) An approach to adjusting climatological time series for discontinuous inhomogeneities. J Clim Appl Meteorol 26:1744–1763
Lanza L, Stagi L (2012) Non-parametric error distribution analysis from the laboratory calibration of various rainfall intensity gauges. Water Sci Technol 65(10):1745–1752
Lanza L, Vuerich E (2009) The WMO field intercomparison of rain intensity gauges. Atmos Res 94:534–543
Mekis E, Vincent L (2011) An overview of the second generation adjusted daily precipitation dataset for trend analysis in Canada. Atmosphere-Ocean 2:163–177. doi:10.1080/07055900.2011.583910
Milewska E, Hogg WD (2002) Continuity of climatological observations with automation. Atmosphere-Ocean 40(3):333–359
Parker DE (1994) Effects of changing exposure of thermometers at land stations. Int J Climatol 14:1–31. doi:10.1002/joc.3370140102
Peleg N, Ben-Asher M, Morin E (2013) Radar subpixel-scale rainfall variability and uncertainty: lessons learned from observations of a dense rain-gauge network. Hydrol Earth Syst Sci 17:2195–2208. doi:10.5194/hess-17-2195-2013
Peterson TC, Easterling DR, Karl TR, Groisman P, Nicholls N, Plummer N, Torok S, Auer I, Boehm R, Gullett D, Vincent L, Heino R, Tuomenvirta H, Mestre O, Szentimrey T, Salingeri J, Førland EJ, Hanssen-Bauer I, Alexandersson H, Jones P, Parker D (1998) Homogeneity adjustments of in situ atmospheric climate data: a review. Int J Climatol 18:1493–1517. doi:10.1002/(SICI) 1097-0088(19981115)18:13<1493::AID-JOC329>3.0.CO;2-T
POST (2015) Parallel observations science Team. Available online at http://www.Surfacetemperatures.Org/databank/parallel_measurements Accessed on 19 June 2016
R Development Core Team (2011) The R project for statistical computing. Available online at https://www.r-project.org/ Accessed on 19 June 2016
Sen PK (1968) Estimates of the regression coefficient based on Kendall’s Tau. J Am Stat Assoc 63:1379–1389
Sevruk B, Klemm S (1989) Catalogue of national standard precipitation gauge. WMO-TD No. 313, instruments and observing methods report No. 39, World Meteorological Organization, Geneva (Switzerland) 24 pp
Sevruk B, Zahlavova L (1994) Classification system of precipitation gauge site exposure: evaluation and application. Int J Climatol 14:681–689
Sevruk B, Ondras M, Chvila B (2009) The WMO precipitation measurement intercomparisons. Atmos Res 92:376–380
Terzago S, Cassardo C, Cremonini R, Fratianni S (2010) Snow precipitation and snow cover climatic variability for the period 1971–2009 in the SouthWestern Italian Alps: the 2008–2009 snow season case study. Water 2:773–787. doi:10.3390/w2040773
Terzago S, Cremonini R, Cassardo C, Fratianni S (2012) Analysis of snow precipitation during the period 2000-09 and evaluation of a snow cover algorithm in SW Italian Alps. Geogr Fis Din Quat 35:91–99
Terzago S, Fratianni S, Cremonini R (2013) Winter precipitation in Western Italian Alps (1926–2010) trends and connections with the North Atlantic/Arctic Oscillation. Meteorog Atmos Phys 119:125–136. doi:10.1007/s00703-012-0231-7
Toreti A, Desiato F (2008) Changes in temperature extremes over Italy in the last 44 years. Int J Climatol 28:733–745. doi:10.1002/ joc.1576
Venema VKC, Mestre O, Aguilar E, Auer I, Guijarro JA, Domonkos P, Vertacnik G, Szentimrey T, Stepánek P, Zahradnicek P, Viarre J, Müller-Westermeier G, Lakatos M, Williams CN, Menne MJ, Lindau R, Rasol D, Rustemeier E, Kolokythas K, Marinova T, Andresen L, Acquaotta F, Fratianni S, Cheval S, Klancar M, Brunetti M, Gruber C, Prohom DM, Likso T, Esteban P, Brandsma T, Willet K (2013) Benchmarking homogenization algorithms for monthly data. AIP Conference Proceedings 1552(8):1060–1065. doi:10.1063/1.4819690
Vincent L, Mekis E (2009) Discontinuities due to joining precipitation station observations in Canada. J Appl Meteorol Climatol 48:156–166. doi:10.1175/2008JAMC2031.1
Wang X, Chen H, Wu Y, Feng Y, Pu Q (2010) New techniques for the detection and adjustment of shifts in daily precipitation data series. J Appl Meteorol Climatol 49:2416–2436. doi:10.1175/2010JAMC2376.1
WMO (2012) Medare initiative. Available online at http://www.omm.urv.cat/MEDARE/ Accessed on 19 June 2016
WMO-CIMO (2008) Guide to meteorological instruments and methods of observation. WMO-No. 8, 7th edition, World Meteorological Organization, Geneva (Switzerland) 681 pp
Zandonadi L, Acquaotta F, Fratianni S, Zavattini JA (2016) Changes in precipitation extremes in Brazil (Paraná River Basin). Theor Appl Climatol 123:741–756
Zhang X, Vincent LA, Hogg WD, Niitsoo A (2000) Temperature and precipitation trends in Canada during the 20th century. Atmosphere-Ocean 38:395–429
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Communicated by: H. A. Babaie
Electronic supplementary material
Supplementary data and the program source code associated with this article can be found both in the online version of the article and at https://github.com/UniToDSTGruppoClima/CoRain
Online Resource 1
file “Co.Rain.R”, containing the source code of the program discussed here (R 34 kb)
Online Resource 2
file “example1.txt”, containing both candidate and reference series used as example (TXT 75 kb)
Online Resource 3
file “example2.txt”, containing both candidate and reference series used as example; data is taken from Boves stations, Piedmont (NW Italy) (TXT 89 kb)
Online Resource 4
file “example3.txt”, containing both candidate and reference series used as example (TXT 82 kb)
Online Resource 5
file “example4.txt”, containing both candidate and reference series used as example (TXT 74 kb)
Online Resource 6
file “example5.txt”, containing both candidate and reference series used as example (TXT 43 kb)
Online Resource 7
file “example6.txt”, containing both candidate and reference series used as example (TXT 17 kb)
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Guenzi, D., Acquaotta, F., Garzena, D. et al. CoRain: A free and open source software for rain series comparison. Earth Sci Inform 10, 405–416 (2017). https://doi.org/10.1007/s12145-017-0301-y
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DOI: https://doi.org/10.1007/s12145-017-0301-y