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Warming signals emerging from the analysis of daily changes in extreme temperature events over Pampas (Argentina)

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Abstract

Global warming and the intensification of extreme temperature events have been significant issues around the world in recent decades. The Pampas region in Argentina is one of the essential areas worldwide because of its agricultural productivity. Therefore, this study aimed to assess daily temperature events trends to identify warming signals during the last 6 decades. Thus, climatic information from 50 weather stations was analyzed to calculate cold and hot extreme events. Trends analysis was carried out with a Mann–Kendall test. As a result, we identified that maximum, minimum, and mean temperatures increased more than 1 °C in most of the Pampas from 1960 to 2018. The hot and cold extreme events demonstrated the existence of warming signals since warm days, warm nights, summer days, tropical nights, and both the coldest days and nights presented a significantly positive trend (2.3 °C, 0.7 °C, 43.6 days, 17.1 days, 0.9 °C, and 1.9 °C in the 59 years, respectively). Contrarily, frost days and cold nights and days had negative trends (12.3 days, 3.2 °C, and 2.4 °C in the 59 years, respectively). The results allow us to conclude that a high daily temperature variability characterizes the region. This knowledge is crucial for generating management policies focused on the sustainability of agricultural economic activities in Pampas.

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References

  • Abatan AA, Abiodun BJ, Lawal KA, Gutowski WJ (2015) Trends in extreme temperature over Nigeria from percentile-based threshold indices. Int J Climatol 6(6):2527–2540. https://doi.org/10.1002/joc.4510

    Article  Google Scholar 

  • Alexander LV, Zhang X, Peterson TC, Caesar J, Gleason B, Klein Tank AMG, Haylock M, Collins D, Trewin B, Rahimzadeh F, Tagipour A, Rupa Kumar K, Revadekar J, Griffiths G, Vincent L, Stephenson DB, Burn J, Aguilar E, Brunet M, Taylor M, New M, Zhai P, Rusticucci M, Vazquez-Aguirre JL (2006) Global observed changes in daily climate extremes of temperature and precipitation. J Geophys Res 111(5):1–22. https://doi.org/10.1029/2005JD006290

    Article  Google Scholar 

  • Alhaji UU, Yusuf AS, Edet CO, Oche CO, Agbo EP (2018) Trend analysis of temperature in Gombe state using mann kendall trend test. J Sci Res Rep 20(3):1–9

    Google Scholar 

  • Aliaga VS, Ferrelli F, Piccolo MC (2017) Regionalization of climate over the Argentine Pampas. Int J Climatol 37:1237–1247. https://doi.org/10.1002/joc.5079

    Article  Google Scholar 

  • Barros VR, Boninsegna JA, Camilloni IA, Chidiak M, Magrín GO, Rusticucci M (2015) Climate change in Argentina: trends, projections, impacts and adaptation. Wires Clim Change 6:151–169. https://doi.org/10.1002/wcc.316

    Article  Google Scholar 

  • Brendel AS, del Barrio RA, Mora F, León EAO, Flores JR, Campoy JA (2020) Current agro-climatic potential of Patagonia shaped by thermal and hydric patterns. Theor Appl Climatol 142(3):855–886. https://doi.org/10.1007/s00704-020-03350-w

    Article  Google Scholar 

  • Chen A, He X, Guan H, Cai Y (2017) Trends and periodicity of daily temperature and precipitation extremes during 1960–2013 in Hunan Province, central south China. Theor Appl Climatol 132:71–88. https://doi.org/10.1007/s00704-017-2069-x

    Article  Google Scholar 

  • Collins M, Knutti R, Arblaster J, Dufresne J-L, Fichefet T, Friedlingstein P, Gao X, Gutowski WJ, Johns T, Krinner G, Shongwe M, Tebaldi C, Weaver AJ, Wehner MF, Allen MR, Andrews T, Beyerle U, Bitz CM, Bony S, Booth BBB (2013) Long-term Climate Change: Projections, Commitments and Irreversibility. In: Stocker TF, Qin D, Plattner G-K, Tignor MMB, Allen SK, Boschung J, Nauels A, Xia Y, Bex V, Midgley PM (eds) Climate change 2013 - the physical science basis: contribution of working group i to the fifth assessment report of the intergovernmental panel on climate change. Intergovernmental Panel on Climate Change, Cambridge University Press, pp 1029–1136

  • Fernández-Long ME, Müller GV, Beltrán-Przekurat A, Scarpati OE (2013) Long-term and recent changes in temperature-based agroclimatic indices in Argentina. Int J Climatol 33(7):1673–1686. https://doi.org/10.1002/joc.3541

    Article  Google Scholar 

  • Ferrelli F, Brendel AS, Aliaga VS, Piccolo MC, Perillo GME (2019) Climate regionalization and trends based on daily temperature and precipitation extremes in the south of the Pampas (Argentina). Cuadernos De Investigación Geográfica 45(1):393–416. https://doi.org/10.18172/cig.3707

    Article  Google Scholar 

  • Fouillet A, Rey G, Laurent F, Pavillon G, Bellec S, Guihenneuc-Jouyaux C, Hémon D (2006) Excess mortality related to the August 2003 heat wave in France. Int Arch Occup Environ Health 80(1):16–24. https://doi.org/10.1007/s00420-006-0089-4

    Article  Google Scholar 

  • Garcia RA, Cabeza M, Rahbek C, Araújo MB (2014) Multiple dimensions of climate change and their implications for biodiversity. Science 344:486–496. https://doi.org/10.1126/science.1247579

    Article  Google Scholar 

  • Githeko AK, Lindsay SW, Confalonieri UE, Patz JA (2000) Climate change and vector-borne diseases: a regional analysis. Bull World Health Organ 78:1136–1147

    Google Scholar 

  • Grassini P, Thorburn J, Burr C, Cassman KG (2011) High-yield irrigated maize in the Western U.S. Corn Belt: I. On-farm yield, yield potential, and impact of agronomic practices. Field Crops Res 120:142–150. https://doi.org/10.1016/j.fcr.2010.09.012

    Article  Google Scholar 

  • Hamed KH (2008) Trend detection in hydrologic data: the Mann–Kendall trend test under the scaling hypothesis. J Hydrol 349(3–4):350–363. https://doi.org/10.1016/j.jhydrol.2007.11.009

  • Hartmann DL, Klein Tank AMG, Rusticucci M, Alexander LV, Brönnimann S, Rahman Charabi YA, Dentender FJ, Dlugokencky EJ, Easterling DR, Kaplan A, Soden BJ, Thorne PW, Wild M, Zhai P (2013) Observations: atmosphere and surface. In: 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, pp 159–254. https://doi.org/10.1017/CBO9781107415324.008

  • Hulme M, Sheard N (1999) Climate Change Scenarios for Argentina. Climatic Research Unit, Norwich, UK

    Google Scholar 

  • IPCC (2007) Summary for policymakers of climate change 2007: the physical science basis. Contribution of working group i to the fourth assessment report of the intergovernmental panel on climate change. Cambridge University Press, Cambridge, UK

    Google Scholar 

  • Kendall MR (1955) Rank correlation methods, 4th edn. Chareles Griffin, London

    Google Scholar 

  • Kondrashov D, Denton R, Shprits YY, Singer HJ (2014) Reconstruction of gaps in the past history of solar wind parameters. Geophys Res Lett 41(8):2702–2707. https://doi.org/10.1002/2014GL059741

    Article  Google Scholar 

  • Lim SS, Vos T, Flaxman AD, Danaei G, Shibuya K, Adair-Rohani H, Aryee M (2012) A comparative risk assessment of burden of disease and injury attributable to 67 risk factors and risk factor clusters in 21 regions, 1990–2010: a systematic analysis for the Global Burden of Disease Study 2010. The Lancet 380(9859):2224–2260

    Article  Google Scholar 

  • Mann HB (1945) Non-parametric tests against trend. Econométrica 13:245–259

    Article  Google Scholar 

  • Menzel A, Jakobi G, Ahas R, Scheifinger H, Estrella N (2003) Variations of the climatological growing season (1951–2000) in Germany compared with other countries. Int J Climatol 23:793–812. https://doi.org/10.1002/joc.915

    Article  Google Scholar 

  • Monzon JP, Sadras VO, Abbate PA, Caviglia OP (2007) Modelling management strategies for wheat–soybean double crops in the south-eastern Pampas. Field Crops Res 101(1):44–52. https://doi.org/10.1016/j.fcr.2006.09.007

  • Nasir MJ, Khan AS, Alam S (2018) Climate change and agriculture: an overview of farmers perception and adaptations in Balambat Tehsil, District Dir Lower, Pakistan. Sarhad J Agric 34(1):85–92. https://doi.org/10.17582/journal.sja/2018/34.1.85.92

    Article  Google Scholar 

  • Peterson T, Folland C, Gruza G, Hogg W, Mokssit A, Plummer N (2001) Report on the activities of the working group on climate change detection and related rapporteurs. World Meteorological Organization, Geneva, p 146

    Google Scholar 

  • Pohlert T (2016) Non-parametric trend tests and change-point detection. CC BY-ND, 4

  • Ruml M, Gregorić E, Vujadinović M, Radovanović S, Matović G, Vuković A, Pocuca V, Stojičić D (2017) Observed changes of temperature extremes in Serbia over the period 1961–2010. Atmos Res 183:26–41. https://doi.org/10.1016/j.atmosres.2016.08.01

    Article  Google Scholar 

  • Salman SA, Shahid S, Ismail T, Chung ES, Al-Abadi AM (2017) Long-term trends in daily temperature extremes in Iraq. Atmos Res 198:97–107

    Article  Google Scholar 

  • Sen PK (1968) Estimates of the regression coefficient based on Kendall's tau. J Am Stat Assoc 63(324):1379–1389

  • Scian BV, Pierini JO (2013) Variability and trends of extreme dry and wet seasonal precipitation in Argentina. A retrospective analysis. Atmósfera. https://doi.org/10.1016/S0187-6236

    Article  Google Scholar 

  • Scian B, Labraga JC, Reimers W, Frumento O (2006) Characteristics of large-scale atmospheric circulation related to extreme monthly rainfall anomalies in the Pampa Region, Argentina, under non-ENSO conditions. Theor Appl Climatol 85(1–2):89–106

    Article  Google Scholar 

  • Shrestha AB, Bajracharya SR, Sharma AR, Duo C, Kulkarni A (2017) Observed trends and changes in daily temperature and precipitation extremes over the Koshi river basin 1975–2010. Int J Climatol 37(2):1066–1083. https://doi.org/10.1002/joc.4761

    Article  Google Scholar 

  • Sun W, Song X, Mu X, Gao P, Wang F, Zhao G (2015) Spatiotemporal vegetation cover variations associated with climate change and ecological restoration in the Loess Plateau. Agric for Meteorol 209:87–99. https://doi.org/10.1016/j.agrformet.2015.05.002

    Article  Google Scholar 

  • Sun W, Mu X, Song X, Wu D, Cheng A, Qiu B (2016) Changes in extreme temperature and precipitation events in the Loess Plateau (China) during 1960–2013 under global warming. Atmos Res Lett 168:33–48. https://doi.org/10.1016/j.atmosres.2015.09.001

    Article  Google Scholar 

  • Taylor MH, Losch M, Wenzel M, Schröter J (2013) On the sensitivity of eld reconstruction and prediction using empirical orthogonal functions derived from Gappy data. J Clim 26(22):9194–9205. https://doi.org/10.1175/JCLI-D-13-00089.1

    Article  Google Scholar 

  • Thakuri S, Dahal S, Shrestha D, Guyennon N, Romano E, Colombo N, Salerno F (2019) Elevation-dependent warming of maximum air temperature in Nepal during 1976–2015. Atmos Res Lett 228:261–269. https://doi.org/10.1016/j.atmosres.2019.06.006

    Article  Google Scholar 

  • Tierney J, Smerdon J, Anchukaitis K, Seager R (2013) Multidecadal variability in East African hydroclimate controlled by the Indian Ocean. Nature 493:389–392. https://doi.org/10.1038/nature11785

    Article  Google Scholar 

  • Vincent LA, Mekis E (2006) Changes in daily and extreme temperature and precipitation indices for Canada over the twentieth century. Atmos Ocean 44(2):177–193. https://doi.org/10.3137/ao.440205

    Article  Google Scholar 

  • Wan L, Zhang XP, Ma Q, Zhang JJ, Ma TY, Sun YP (2014) Spatiotemporal characteristics of precipitation and extreme events on the Loess Plateau of China between 1957 and 2009. Hydrol Processes 28(18):4971–4983. https://doi.org/10.1002/hyp.9951

    Article  Google Scholar 

  • Wang XL (2008a) Penalized maximal F-test for detecting undocumented mean shifts without trend-change. J Atmos Oceanic Technol 25:368–384. https://doi.org/10.1175/2007JTECHA982.1

    Article  Google Scholar 

  • Wang XL (2008b) Accounting for autocorrelation in detecting mean-shifts in climate data series using the penalized maximal t or F test. J Atmos Oceanic Technol 47:2423–2444. https://doi.org/10.1175/2008JAMC1741.1

    Article  Google Scholar 

  • Wang XL, Wen QH, Wu Y (2007) Penalized maximal t test for detecting undocumented mean change in climate data series. J Appl Meteorol and Clim 46:916–931. https://doi.org/10.1175/JAM2504.1

    Article  Google Scholar 

  • Wang XL, Chen H, Wu Y, Feng Y, Pu Q (2010) New techniques for the detection and adjustment of shifts in daily precipitation data series. J Atmos Oceanic Technol 49(12):2416–2436. https://doi.org/10.1175/2010JAMC2376.1

    Article  Google Scholar 

  • Wang KY, Li QF, Yang Y, Zeng M, Li PC, Zhang JX (2015) Analysis of spatio-temporal evolution of droughts in Luanhe River Basin using different drought indices. Water Sci Eng 8(4):282–290. https://doi.org/10.1016/j.wse.2015.11.004

    Article  Google Scholar 

  • Worku G, Teferi E, Bantider A, Dile YT (2019) Observed changes in extremes of daily rainfall and temperature in Jemma sub-basin Upper Blue Nile Basin, Ethiopia. Appl Clim. https://doi.org/10.1007/s00704-018-2412-x

    Article  Google Scholar 

  • Zhang, X, Yang, F (2004) RClimDex (1.0) user manual. Climate Research Branch Environment Canada, 22

  • Zhang Q, Li J, Chen YD, Chen X (2011) Observed changes of temperature extremes during 1960–2005 in China: natural or human-induced variations? Theor Appl Climatol 106(3–4):417–431. https://doi.org/10.1007/s00704-011-0447-3

    Article  Google Scholar 

  • Zhou H, Aizen E, Aizen V (2018) Constructing a long-term monthly climate data set in central Asia. Int J Climatol 38 (3):1463–1475. https://doi.org/10.1002/joc.5259

  • Zilio MI, Alfonso MB, Ferrelli F, Perillo GME, Piccolo MC (2017) Ecosystem services provision, tourism and climate variability in shallow lakes: the case of La Salada, Buenos Aires, Argentina. Tour Manage 62:208–217. https://doi.org/10.1016/j.tourman.2017.04.008

    Article  Google Scholar 

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Acknowledgements

The authors are grateful to the Consejo Nacional de Investigaciones Científicas y Técnicas (CONICET, Argentina) and Universidad Nacional del Sur (UNS) for financial support. Moreover, we would like to thank the Instituto Nacional de Tecnología Agropecuaria (INTA), and Servicio Meteorológico Nacional (SMN) from Argentina for providing meteorological data.

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Author notes

  1. Federico Ferrelli and Andrea Soledad Brendel have equally contribute to this paper.

Authors and Affiliations

  1. Instituto Argentino de Oceanografía (IADO), Universidad Nacional del Sur (UNS)-CONICET, Florida 8000 (Camino La Carrindanga km 7,5) Complejo CCT CONICET, Edificio E1, B8000BFW, Bahía Blanca, Argentina

    Federico Ferrelli, Andrea Soledad Brendel, Gerardo Miguel Eduardo Perillo & María Cintia Piccolo

  2. Departamento de Geografía y Turismo, Universidad Nacional del Sur (UNS), 12 de Octubre 1198, B8000BFW, Bahía Blanca, Argentina

    Federico Ferrelli & María Cintia Piccolo

  3. Departamento de Agronomía, Universidad Nacional del Sur (UNS), San Andrés 800, B8000BFW, Bahía Blanca, Argentina

    Andrea Soledad Brendel

  4. Departamento de Geología, Universidad Nacional del Sur (UNS), Alem 1253, Cuerpo 2, B8000BFW, Bahía Blanca, Argentina

    Gerardo Miguel Eduardo Perillo

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  1. Federico Ferrelli
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  2. Andrea Soledad Brendel
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  3. Gerardo Miguel Eduardo Perillo
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Correspondence to Federico Ferrelli.

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Ferrelli, F., Brendel, A.S., Perillo, G.M.E. et al. Warming signals emerging from the analysis of daily changes in extreme temperature events over Pampas (Argentina). Environ Earth Sci 80, 422 (2021). https://doi.org/10.1007/s12665-021-09721-4

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