Articles | Volume 29, issue 12
https://doi.org/10.5194/hess-29-2727-2025
© Author(s) 2025. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/hess-29-2727-2025
© Author(s) 2025. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Research article
| 
01 Jul 2025
Research article |
| 01 Jul 2025
| 01 Jul 2025
A novel framework for analyzing rainy season dynamics in semi-arid environments: a case study in the Peruvian Rio Santa basin
Lorenz Hänchen
CORRESPONDING AUTHOR
Universität Innsbruck, Institut für Ökologie, Innsbruck, Austria
Emily Potter
University of Sheffield, School of Geography and Planning, Sheffield, UK
Cornelia Klein
UK Centre for Ecology and Hydrology, Wallingford, UK
Pierluigi Calanca
Climate and Agriculture, Agroscope Reckenholz, Zurich, Switzerland
Fabien Maussion
University of Bristol, School of Geographical Sciences, Bristol, UK
Wolfgang Gurgiser
Universität Innsbruck, Institut für Atmosphären- und Kryosphärenwissenschaften, Innsbruck, Austria
Georg Wohlfahrt
Universität Innsbruck, Institut für Ökologie, Innsbruck, Austria
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Larissa van der Laan, Anouk Vlug, Adam A. Scaife, Fabien Maussion, and Kristian Förster
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Usually, glacier models are supplied with climate information from long (e.g. 100 year) simulations by global climate models. In this paper, we test the feasibility of supplying glacier models with shorter simulations, to get more accurate information on 5–10 year time scales. Reliable information on these time scales is very important, especially for water management experts to know how much meltwater to expect, for rivers, agriculture and drinking water.
Jordi Bolibar, Facundo Sapienza, Fabien Maussion, Redouane Lguensat, Bert Wouters, and Fernando Pérez
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We developed a new modelling framework combining numerical methods with machine learning. Using this approach, we focused on understanding how ice moves within glaciers, and we successfully learnt a prescribed law describing ice movement for 17 glaciers worldwide as a proof of concept. Our framework has the potential to discover important laws governing glacier processes, aiding our understanding of glacier physics and their contribution to water resources and sea-level rise.
Francis Nkrumah, Cornelia Klein, Kwesi Akumenyi Quagraine, Rebecca Berkoh-Oforiwaa, Nana Ama Browne Klutse, Patrick Essien, Gandomè Mayeul Leger Davy Quenum, and Hubert Azoda Koffi
Weather Clim. Dynam., 4, 773–788, https://doi.org/10.5194/wcd-4-773-2023, https://doi.org/10.5194/wcd-4-773-2023, 2023
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It is not yet clear which variations in broader atmospheric conditions of the West African monsoon may lead to mesoscale convective system (MCS) occurrences in southern West Africa (SWA). In this study, we identified nine different weather patterns and categorized them as dry-, transition-, or monsoon-season types using a method called self-organizing maps (SOMs). It was revealed that a warmer Sahel region can create favourable conditions for MCS formation in SWA.
Julia Crook, Cornelia Klein, Sonja Folwell, Christopher M. Taylor, Douglas J. Parker, Adama Bamba, and Kouakou Kouadio
Weather Clim. Dynam., 4, 229–248, https://doi.org/10.5194/wcd-4-229-2023, https://doi.org/10.5194/wcd-4-229-2023, 2023
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Georg Wohlfahrt, Albin Hammerle, Felix M. Spielmann, Florian Kitz, and Chuixiang Yi
Biogeosciences, 20, 589–596, https://doi.org/10.5194/bg-20-589-2023, https://doi.org/10.5194/bg-20-589-2023, 2023
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Nidheesh Gangadharan, Hugues Goosse, David Parkes, Heiko Goelzer, Fabien Maussion, and Ben Marzeion
Earth Syst. Dynam., 13, 1417–1435, https://doi.org/10.5194/esd-13-1417-2022, https://doi.org/10.5194/esd-13-1417-2022, 2022
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We describe the contributions of ocean thermal expansion and land-ice melting (ice sheets and glaciers) to global-mean sea-level (GMSL) changes in the Common Era. The mass contributions are the major sources of GMSL changes in the pre-industrial Common Era and glaciers are the largest contributor. The paper also describes the current state of climate modelling, uncertainties and knowledge gaps along with the potential implications of the past variabilities in the contemporary sea-level rise.
Camille Abadie, Fabienne Maignan, Marine Remaud, Jérôme Ogée, J. Elliott Campbell, Mary E. Whelan, Florian Kitz, Felix M. Spielmann, Georg Wohlfahrt, Richard Wehr, Wu Sun, Nina Raoult, Ulli Seibt, Didier Hauglustaine, Sinikka T. Lennartz, Sauveur Belviso, David Montagne, and Philippe Peylin
Biogeosciences, 19, 2427–2463, https://doi.org/10.5194/bg-19-2427-2022, https://doi.org/10.5194/bg-19-2427-2022, 2022
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A better constraint of the components of the carbonyl sulfide (COS) global budget is needed to exploit its potential as a proxy of gross primary productivity. In this study, we compare two representations of oxic soil COS fluxes, and we develop an approach to represent anoxic soil COS fluxes in a land surface model. We show the importance of atmospheric COS concentration variations on oxic soil COS fluxes and provide new estimates for oxic and anoxic soil contributions to the COS global budget.
Lisa Kaser, Arianna Peron, Martin Graus, Marcus Striednig, Georg Wohlfahrt, Stanislav Juráň, and Thomas Karl
Atmos. Chem. Phys., 22, 5603–5618, https://doi.org/10.5194/acp-22-5603-2022, https://doi.org/10.5194/acp-22-5603-2022, 2022
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Biogenic volatile organic compounds (e.g., terpenoids) play an essential role in atmospheric chemistry. Urban greening activities need to consider the ozone- and aerosol-forming potential of these compounds released from vegetation. NMVOC emissions in urban environments are complex, and the biogenic component remains poorly quantified. For summer conditions biogenic emissions dominate terpene emissions and heat waves can significantly modulate urban biogenic terpenoid emissions.
Lorenz Hänchen, Cornelia Klein, Fabien Maussion, Wolfgang Gurgiser, Pierluigi Calanca, and Georg Wohlfahrt
Earth Syst. Dynam., 13, 595–611, https://doi.org/10.5194/esd-13-595-2022, https://doi.org/10.5194/esd-13-595-2022, 2022
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Linda M. J. Kooijmans, Ara Cho, Jin Ma, Aleya Kaushik, Katherine D. Haynes, Ian Baker, Ingrid T. Luijkx, Mathijs Groenink, Wouter Peters, John B. Miller, Joseph A. Berry, Jerome Ogée, Laura K. Meredith, Wu Sun, Kukka-Maaria Kohonen, Timo Vesala, Ivan Mammarella, Huilin Chen, Felix M. Spielmann, Georg Wohlfahrt, Max Berkelhammer, Mary E. Whelan, Kadmiel Maseyk, Ulli Seibt, Roisin Commane, Richard Wehr, and Maarten Krol
Biogeosciences, 18, 6547–6565, https://doi.org/10.5194/bg-18-6547-2021, https://doi.org/10.5194/bg-18-6547-2021, 2021
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The gas carbonyl sulfide (COS) can be used to estimate photosynthesis. To adopt this approach on regional and global scales, we need biosphere models that can simulate COS exchange. So far, such models have not been evaluated against observations. We evaluate the COS biosphere exchange of the SiB4 model against COS flux observations. We find that the model is capable of simulating key processes in COS biosphere exchange. Still, we give recommendations for further improvement of the model.
Kyle B. Delwiche, Sara Helen Knox, Avni Malhotra, Etienne Fluet-Chouinard, Gavin McNicol, Sarah Feron, Zutao Ouyang, Dario Papale, Carlo Trotta, Eleonora Canfora, You-Wei Cheah, Danielle Christianson, Ma. Carmelita R. Alberto, Pavel Alekseychik, Mika Aurela, Dennis Baldocchi, Sheel Bansal, David P. Billesbach, Gil Bohrer, Rosvel Bracho, Nina Buchmann, David I. Campbell, Gerardo Celis, Jiquan Chen, Weinan Chen, Housen Chu, Higo J. Dalmagro, Sigrid Dengel, Ankur R. Desai, Matteo Detto, Han Dolman, Elke Eichelmann, Eugenie Euskirchen, Daniela Famulari, Kathrin Fuchs, Mathias Goeckede, Sébastien Gogo, Mangaliso J. Gondwe, Jordan P. Goodrich, Pia Gottschalk, Scott L. Graham, Martin Heimann, Manuel Helbig, Carole Helfter, Kyle S. Hemes, Takashi Hirano, David Hollinger, Lukas Hörtnagl, Hiroki Iwata, Adrien Jacotot, Gerald Jurasinski, Minseok Kang, Kuno Kasak, John King, Janina Klatt, Franziska Koebsch, Ken W. Krauss, Derrick Y. F. Lai, Annalea Lohila, Ivan Mammarella, Luca Belelli Marchesini, Giovanni Manca, Jaclyn Hatala Matthes, Trofim Maximov, Lutz Merbold, Bhaskar Mitra, Timothy H. Morin, Eiko Nemitz, Mats B. Nilsson, Shuli Niu, Walter C. Oechel, Patricia Y. Oikawa, Keisuke Ono, Matthias Peichl, Olli Peltola, Michele L. Reba, Andrew D. Richardson, William Riley, Benjamin R. K. Runkle, Youngryel Ryu, Torsten Sachs, Ayaka Sakabe, Camilo Rey Sanchez, Edward A. Schuur, Karina V. R. Schäfer, Oliver Sonnentag, Jed P. Sparks, Ellen Stuart-Haëntjens, Cove Sturtevant, Ryan C. Sullivan, Daphne J. Szutu, Jonathan E. Thom, Margaret S. Torn, Eeva-Stiina Tuittila, Jessica Turner, Masahito Ueyama, Alex C. Valach, Rodrigo Vargas, Andrej Varlagin, Alma Vazquez-Lule, Joseph G. Verfaillie, Timo Vesala, George L. Vourlitis, Eric J. Ward, Christian Wille, Georg Wohlfahrt, Guan Xhuan Wong, Zhen Zhang, Donatella Zona, Lisamarie Windham-Myers, Benjamin Poulter, and Robert B. Jackson
Earth Syst. Sci. Data, 13, 3607–3689, https://doi.org/10.5194/essd-13-3607-2021, https://doi.org/10.5194/essd-13-3607-2021, 2021
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Methane is an important greenhouse gas, yet we lack knowledge about its global emissions and drivers. We present FLUXNET-CH4, a new global collection of methane measurements and a critical resource for the research community. We use FLUXNET-CH4 data to quantify the seasonality of methane emissions from freshwater wetlands, finding that methane seasonality varies strongly with latitude. Our new database and analysis will improve wetland model accuracy and inform greenhouse gas budgets.
Anna B. Harper, Karina E. Williams, Patrick C. McGuire, Maria Carolina Duran Rojas, Debbie Hemming, Anne Verhoef, Chris Huntingford, Lucy Rowland, Toby Marthews, Cleiton Breder Eller, Camilla Mathison, Rodolfo L. B. Nobrega, Nicola Gedney, Pier Luigi Vidale, Fred Otu-Larbi, Divya Pandey, Sebastien Garrigues, Azin Wright, Darren Slevin, Martin G. De Kauwe, Eleanor Blyth, Jonas Ardö, Andrew Black, Damien Bonal, Nina Buchmann, Benoit Burban, Kathrin Fuchs, Agnès de Grandcourt, Ivan Mammarella, Lutz Merbold, Leonardo Montagnani, Yann Nouvellon, Natalia Restrepo-Coupe, and Georg Wohlfahrt
Geosci. Model Dev., 14, 3269–3294, https://doi.org/10.5194/gmd-14-3269-2021, https://doi.org/10.5194/gmd-14-3269-2021, 2021
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We evaluated 10 representations of soil moisture stress in the JULES land surface model against site observations of GPP and latent heat flux. Increasing the soil depth and plant access to deep soil moisture improved many aspects of the simulations, and we recommend these settings in future work using JULES. In addition, using soil matric potential presents the opportunity to include parameters specific to plant functional type to further improve modeled fluxes.
Arianna Peron, Lisa Kaser, Anne Charlott Fitzky, Martin Graus, Heidi Halbwirth, Jürgen Greiner, Georg Wohlfahrt, Boris Rewald, Hans Sandén, and Thomas Karl
Biogeosciences, 18, 535–556, https://doi.org/10.5194/bg-18-535-2021, https://doi.org/10.5194/bg-18-535-2021, 2021
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Drought events are expected to become more frequent with climate change. Along with these events atmospheric ozone is also expected to increase. Both can stress plants. Here we investigate to what extent these factors modulate the emission of volatile organic compounds (VOCs) from oak plants. We find an antagonistic effect between drought stress and ozone, impacting the emission of different BVOCs, which is indirectly controlled by stomatal opening, allowing plants to control their water budget.
Lilian Schuster, Fabien Maussion, Lukas Langhamer, and Gina E. Moseley
Weather Clim. Dynam., 2, 1–17, https://doi.org/10.5194/wcd-2-1-2021, https://doi.org/10.5194/wcd-2-1-2021, 2021
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Precipitation and moisture sources over an arid region in northeast Greenland are investigated from 1979 to 2017 by a Lagrangian moisture source diagnostic driven by reanalysis data. Dominant winter moisture sources are the North Atlantic above 45° N. In summer local and north Eurasian continental sources dominate. In positive phases of the North Atlantic Oscillation, evaporation and moisture transport from the Norwegian Sea are stronger, resulting in more precipitation.
Yuan Zhang, Ana Bastos, Fabienne Maignan, Daniel Goll, Olivier Boucher, Laurent Li, Alessandro Cescatti, Nicolas Vuichard, Xiuzhi Chen, Christof Ammann, M. Altaf Arain, T. Andrew Black, Bogdan Chojnicki, Tomomichi Kato, Ivan Mammarella, Leonardo Montagnani, Olivier Roupsard, Maria J. Sanz, Lukas Siebicke, Marek Urbaniak, Francesco Primo Vaccari, Georg Wohlfahrt, Will Woodgate, and Philippe Ciais
Geosci. Model Dev., 13, 5401–5423, https://doi.org/10.5194/gmd-13-5401-2020, https://doi.org/10.5194/gmd-13-5401-2020, 2020
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We improved the ORCHIDEE LSM by distinguishing diffuse and direct light in canopy and evaluated the new model with observations from 159 sites. Compared with the old model, the new model has better sunny GPP and reproduced the diffuse light fertilization effect observed at flux sites. Our simulations also indicate different mechanisms causing the observed GPP enhancement under cloudy conditions at different times. The new model has the potential to study large-scale impacts of aerosol changes.
Cited articles
Belda, S., Pipia, L., Morcillo-Pallares, P., Rivera-Caicedo, J. P., Amin, E., De Grave, C., and Verrelst, J.: DATimeS: A machine learning time series GUI toolbox for gap-filling and vegetation phenology trends detection, Environ. Model. Softw., 127, 104666, https://doi.org/10.1016/j.envsoft.2020.104666, 2020. a
Bombardi, R. J. and Carvalho, L. M. V.: IPCC global coupled model simulations of the South America monsoon system, Clim. Dynam., 33, 893–916, https://doi.org/10.1007/s00382-008-0488-1, 2008. a
Bombardi, R. J., Kinter, J. L., and Frauenfeld, O. W.: A Global Gridded Dataset of the Characteristics of the Rainy And Dry Seasons, B. Am. Meteorol. Soc., 100, 1315–1328, https://doi.org/10.1175/bams-d-18-0177.1, 2019a. a
Bombardi, R. J., Moron, V., and Goodnight, J. S.: Detection, variability, and predictability of monsoon onset and withdrawal dates: A review, Int. J. Climatol., 40, 641–667, https://doi.org/10.1002/joc.6264, 2019b. a, b
Bury, J. T., Mark, B. G., McKenzie, J. M., French, A., Baraer, M., Huh, K. I., Zapata Luyo, M. A., and Gómez López, R. J.: Glacier recession and human vulnerability in the Yanamarey watershed of the Cordillera Blanca, Peru, Climatic Change, 105, 179–206, https://doi.org/10.1007/s10584-010-9870-1, 2010. a
Cai, W., Ng, B., Geng, T., Jia, F., Wu, L., Wang, G., Liu, Y., Gan, B., Yang, K., Santoso, A., Lin, X., Li, Z., Liu, Y., Yang, Y., Jin, F.-F., Collins, M., and McPhaden, M. J.: Anthropogenic impacts on twentieth-century ENSO variability changes, Nature Reviews Earth & Environment, 4, 407–418, https://doi.org/10.1038/s43017-023-00427-8, 2023. a
Camberlin, P. and Diop, M.: Application of daily rainfall principal component analysis to the assessment of the rainy season characteristics in Senegal, Clim. Res., 23, 159–169, https://doi.org/10.3354/cr023159, 2003. a
Caparros-Santiago, J. A., Rodriguez-Galiano, V., and Dash, J.: Land surface phenology as indicator of global terrestrial ecosystem dynamics: A systematic review, ISPRS J. Photogramm., 171, 330–347, https://doi.org/10.1016/j.isprsjprs.2020.11.019, 2021. a
Cook, B. I. and Buckley, B. M.: Objective determination of monsoon season onset, withdrawal, and length, J. Geophys. Res.-Atmos., 114, D23109, https://doi.org/10.1029/2009jd012795, 2009. a, b, c, d
De la Cruz, G., Huerta, A., Espinoza, J.-C., and Lavado-Casimiro, W.: Present Variability and Future Change in Onset and Cessation of the Rainy Season Over Peru, Int. J. Climatol., 45, e8700, https://doi.org/10.1002/joc.8700, 2025. a, b, c, d
Dextre, R. M., Eschenhagen, M. L., Camacho Hernández, M., Rangecroft, S., Clason, C., Couldrick, L., and Morera, S.: Payment for ecosystem services in Peru: Assessing the socio-ecological dimension of water services in the upper Santa River basin, Ecosyst. Serv., 56, 101454, https://doi.org/10.1016/j.ecoser.2022.101454, 2022. a
Didan, K.: MOD13Q1 MODIS/Terra vegetation indices 16-day L3 global 250m SIN grid V006, NASA Land Processes Distributed Active Archive Center (LP DAAC) [data set], https://doi.org/10.5067/MODIS/MOD13Q1.006, 2015a. a, b
Didan, K.: MYD13Q1 MODIS/Terra vegetation indices 16-day L3 global 250m SIN grid V006, NASA Land Processes Distributed Active Archive Center (LP DAAC) [data set], https://doi.org/10.5067/MODIS/MYD13Q1.006, 2015b. a, b
Drenkhan, F., Carey, M., Huggel, C., Seidel, J., and Oré, M. T.: The changing water cycle: climatic and socioeconomic drivers of water-related changes in the Andes of Peru, WIREs Water, 2, 715–733, https://doi.org/10.1002/wat2.1105, 2015. a
Drenkhan, F., Buytaert, W., Mackay, J. D., Barrand, N. E., Hannah, D. M., and Huggel, C.: Looking beyond glaciers to understand mountain water security, Nature Sustainability, 6, 130–138, https://doi.org/10.1038/s41893-022-00996-4, 2022. a
Dunning, C. M., Black, E. C. L., and Allan, R. P.: The onset and cessation of seasonal rainfall over Africa, J. Geophys. Res.-Atmos., 121, 11405–11424, https://doi.org/10.1002/2016jd025428, 2016. a, b
Espinoza, J. C., Garreaud, R., Poveda, G., Arias, P. A., Molina-Carpio, J., Masiokas, M., Viale, M., and Scaff, L.: Hydroclimate of the Andes Part I: Main Climatic Features, Front. Earth Sci., 8, 64, https://doi.org/10.3389/feart.2020.00064, 2020. a
Ferijal, T., Batelaan, O., Shanafield, M., and Alfahmi, F.: Determination of rainy season onset and cessation based on a flexible driest period, Theor. Appl. Climatol., 148, 91–104, https://doi.org/10.1007/s00704-021-03917-1, 2022. a, b
Fitzpatrick, R. G. J., Bain, C. L., Knippertz, P., Marsham, J. H., and Parker, D. J.: The West African Monsoon Onset: A Concise Comparison of Definitions, J. Climate, 28, 8673–8694, https://doi.org/10.1175/jcli-d-15-0265.1, 2015. a, b, c
Freedman, D. and Diaconis, P.: On the histogram as a density estimator: L2 theory, Z. Wahrscheinlichkeit., 57, 453–476, https://doi.org/10.1007/BF01025868, 1981. a
Funk, C., Peterson, P., Landsfeld, M., Pedreros, D., Verdin, J., Shukla, S., Husak, G., Rowland, J., Harrison, L., Hoell, A., and Michaelsen, J.: The climate hazards infrared precipitation with stations – a new environmental record for monitoring extremes, Sci. Data, 2, 150066, https://doi.org/10.1038/sdata.2015.66, 2015 (data available at: https://data.chc.ucsb.edu/products/CHIRPS-2.0/, last access: 16 November 2020). a, b, c
Fyffe, C. L., Potter, E., Fugger, S., Orr, A., Fatichi, S., Loarte, E., Medina, K., Hellström, R. Ã., Bernat, M., Aubry-Wake, C., Gurgiser, W., Perry, L. B., Suarez, W., Quincey, D. J., and Pellicciotti, F.: The Energy and Mass Balance of Peruvian Glaciers, J. Geophys. Res.-Atmos., 126, e2021JD034911, https://doi.org/10.1029/2021jd034911, 2021. a
Garcia, M., Raes, D., Jacobsen, S. E., and Michel, T.: Agroclimatic constraints for rainfed agriculture in the Bolivian Altiplano, J. Arid Environ., 71, 109–121, https://doi.org/10.1016/j.jaridenv.2007.02.005, 2007. a, b, c
Garreaud, R. D.: The Andes climate and weather, Adv. Geosci., 22, 3–11, https://doi.org/10.5194/adgeo-22-3-2009, 2009. a
Giràldez, L., Silva, Y., Zubieta, R., and Sulca, J.: Change of the Rainfall Seasonality Over Central Peruvian Andes: Onset, End, Duration and Its Relationship With Large-Scale Atmospheric Circulation, Climate, 8, 23, https://doi.org/10.3390/cli8020023, 2020. a, b, c
Gurgiser, W., Juen, I., Singer, K., Neuburger, M., Schauwecker, S., Hofer, M., and Kaser, G.: Comparing peasants' perceptions of precipitation change with precipitation records in the tropical Callejón de Huaylas, Peru, Earth Syst. Dynam., 7, 499–515, https://doi.org/10.5194/esd-7-499-2016, 2016. a, b, c, d
Gutierrez, R. A., Junquas, C., Armijos, E., Sörensson, A. A., and Espinoza, J.-C.: Performance of Regional Climate Model Precipitation Simulations Over the Terrain-Complex Andes-Amazon Transition Region, J. Geophys. Res.-Atmos., 129, e2023JD038618, https://doi.org/10.1029/2023JD038618, 2024. a
Harris, C. R., Millman, K. J., van der Walt, S. J., Gommers, R., Virtanen, P., Cournapeau, D., Wieser, E., Taylor, J., Berg, S., Smith, N. J., Kern, R., Picus, M., Hoyer, S., van Kerkwijk, M. H., Brett, M., Haldane, A., Del Rio, J. F., Wiebe, M., Peterson, P., Gerard-Marchant, P., Sheppard, K., Reddy, T., Weckesser, W., Abbasi, H., Gohlke, C., and Oliphant, T. E.: Array programming with NumPy, Nature, 585, 357–362, https://doi.org/10.1038/s41586-020-2649-2, 2020. a
Hoyer, S. and Hamman, J.: xarray: N-D labeled Arrays and Datasets in Python, Journal of Open Research Software, 5, 10, https://doi.org/10.5334/jors.148, 2017. a
Hunziker, S., Gubler, S., Calle, J., Moreno, I., Andrade, M., Velarde, F., Ticona, L., Carrasco, G., Castellón, Y., Oria, C., Croci-Maspoli, M., Konzelmann, T., Rohrer, M., and Brönnimann, S.: Identifying, attributing, and overcoming common data quality issues of manned station observations, Int. J. Climatol., 37, 4131–4145, https://doi.org/10.1002/joc.5037, 2017. a
Hänchen, L., Klein, C., Maussion, F., Gurgiser, W., Calanca, P., and Wohlfahrt, G.: Widespread greening suggests increased dry-season plant water availability in the Rio Santa valley, Peruvian Andes, Earth Syst. Dynam., 13, 595–611, https://doi.org/10.5194/esd-13-595-2022, 2022. a, b, c, d, e, f, g, h, i
Hänchen L., Potter, E., Klein, C., Calanca, P., Maussion, F., Gurgiser, W., and Wohlfahrt, G.: Code to recreate the analysis and figures of: “A Novel Framework for Analyzing Rainy Season Dynamics in semi-arid environments: A case study for the Peruvian Rio Santa Basin” (v1.0), Zenodo [code], https://doi.org/10.5281/zenodo.13952139, 2024. a
Jolliffe, I. T. and Sarria-dodd, D. E.: Early detection of the start of the wet season in tropical climates, Int. J. Climatol., 14, 71–76, https://doi.org/10.1002/joc.3370140106, 1994. a, b
Jones, C. and Carvalho, L. M. V.: Climate Change in the South American Monsoon System: Present Climate and CMIP5 Projections, J. Climate, 26, 6660–6678, https://doi.org/10.1175/jcli-d-12-00412.1, 2013. a
Kidd, C., Becker, A., Huffman, G. J., Muller, C. L., Joe, P., Skofronick-Jackson, G., and Kirschbaum, D. B.: So, how much of the Earth's surface is covered by rain gauges?, B. Am. Meteorol. Soc., 98, 69–78, https://doi.org/10.1175/BAMS-D-14-00283.1, 2017. a
Klein, C., Hänchen, L., Potter, E. R., Junquas, C., Harris, B. L., and Maussion, F.: Untangling the importance of dynamic and thermodynamic drivers for wet and dry spells across the Tropical Andes, Environ. Res. Lett., 18, 034002, https://doi.org/10.1088/1748-9326/acb72b, 2023a. a
Klein, C., Potter, E. R., Zauner, C., Gurgiser, W., Cruz Encarnación, R., Cochachín Rapre, A., and Maussion, F.: Farmers' first rain: investigating dry season rainfall characteristics in the Peruvian Andes, Environmental Research Communications, 5, 071004, https://doi.org/10.1088/2515-7620/ace516, 2023b. a
Laux, P., Kunstmann, H., and Bárdossy, A.: Predicting the regional onset of the rainy season in West Africa, Int. J. Climatol., 28, 329–342, https://doi.org/10.1002/joc.1542, 2008. a
Liebmann, B. and Marengo, J.: Interannual Variability of the Rainy Season and Rainfall in the Brazilian Amazon Basin, J. Climate, 14, 4308–4318, https://doi.org/10.1175/1520-0442(2001)014<4308:Ivotrs>2.0.Co;2, 2001. a, b, c
Liebmann, B., Camargo, S. J., Seth, A., Marengo, J. A., Carvalho, L. M. V., Allured, D., Fu, R., and Vera, C. S.: Onset and End of the Rainy Season in South America in Observations and the ECHAM 4.5 Atmospheric General Circulation Model, J. Climate, 20, 2037–2050, https://doi.org/10.1175/JCLI4122.1, 2007. a
MacLeod, D.: Seasonal predictability of onset and cessation of the east African rains, Weather and Climate Extremes, 21, 27–35, https://doi.org/10.1016/j.wace.2018.05.003, 2018. a
Marengo, J. A., Liebmann, B., Kousky, V. E., Filizola, N. P., and Wainer, I. C.: Onset and End of the Rainy Season in the Brazilian Amazon Basin, J. Climate, 14, 833–852, https://doi.org/10.1175/1520-0442(2001)014<0833:Oaeotr>2.0.Co;2, 2001. a
Mateo, E. I., Mark, B. G., Hellström, R. Å., Baraer, M., McKenzie, J. M., Condom, T., Rapre, A. C., Gonzales, G., Gómez, J. Q., and Encarnación, R. C. C.: High-temporal-resolution hydrometeorological data collected in the tropical Cordillera Blanca, Peru (2004–2020), Earth Syst. Sci. Data, 14, 2865–2882, https://doi.org/10.5194/essd-14-2865-2022, 2022. a
Maussion, F., Gurgiser, W., Großhauser, M., Kaser, G., and Marzeion, B.: ENSO influence on surface energy and mass balance at Shallap Glacier, Cordillera Blanca, Peru, The Cryosphere, 9, 1663–1683, https://doi.org/10.5194/tc-9-1663-2015, 2015. a, b
Maussion, F., Rothenpieler, T., Bell, R., Li, F., Landmann, J., Dusch, M., Sun, T., hannah, paolodeidda, and tbridel: fmaussion/salem: v0.3.9 (v0.3.9). Zenodo [code], https://doi.org/10.5281/zenodo.7554820, 2023. a
McKinney, W.: Data structures for statistical computing in python, in: Proceedings of the 9th Python in Science Conference, Austin, TX, 445, 51–56, https://doi.org/10.25080/Majora-92bf1922-00a, 2010. a
Olmo, M. E., Espinoza, J.-C., Bettolli, M. L., Sierra, J. P., Junquas, C., Arias, P., Moron, V., and Balmaceda-Huarte, R.: Circulation patterns and associated rainfall over south tropical South America: GCMs evaluation during the dry-to-wet transition season, J. Geophys. Res.-Atmos., 127, e2022JD036468, https://doi.org/10.1029/2022JD036468, 2022. a
Pollock, M. D., O'Donnell, G., Quinn, P., Dutton, M., Black, A., Wilkinson, M. E., Colli, M., Stagnaro, M., Lanza, L. G., Lewis, E., Kilsby, C. G., and O'Connell, P. E.: Quantifying and Mitigating Wind-Induced Undercatch in Rainfall Measurements, Water Resour. Res., 54, 3863–3875, https://doi.org/10.1029/2017wr022421, 2018. a
Potter, E. R., Fyffe, C. L., Orr, A., Quincey, D. J., Ross, A. N., Rangecroft, S., Medina, K., Burns, H., Llacza, A., Jacome, G., Hellström, R. Å., Castro, J., Cochachin, A., Montoya, N., Loarte, E., and Pellicciotti, F.: A future of extreme precipitation and droughts in the Peruvian Andes, npj Climate and Atmospheric Science, 6, 96, https://doi.org/10.1038/s41612-023-00409-z, 2023a. a, b, c, d, e, f, g, h, i, j, k, l
Potter, E., Fyffe, C., Orr, A., Quincey, D., Ross, A., Rangecroft, S., Medina, K., Burns, H., Llacza, A., Jacome, G., Hellstrom, R., Castro, J., Cochachin, A., Montoya, N., Loarte, E., and Pellicciotti, F.: Bias-corrected temperature and precipitation data from the WRF regional climate model output, Cordillera Blanca and Vilcanota-Urubamba regions, Peru, from 1980 to 2018 (Version 1.0), NERC EDS UK Polar Data Centre [data set], https://doi.org/10.5285/2cf25580-9b79-440f-8505-6230dd377877, 2023b. a
Potter, E., Fyffe, C., Orr, A., Quincey, D., Ross, A., Rangecroft, S., Medina, K., Burns, H., Llacza, A., Jacome, G., Hellstrom, R., Castro, J., Cochachin, A., Montoya, N., Loarte, E., and Pellicciotti, F.: Precipitation and temperature data from statistically downscaled CMIP5 models, Cordillera Blanca and Vilcanota-Urubamba regions, Peru, from 2019 to 2100 (Version 1.0), NERC EDS UK Polar Data Centre [data set], https://doi.org/10.5285/67ceb7c8-218c-46e1-9927-cfef2dd95526, 2023c. a
Potter, E., Fyffe, C., Orr, A., Quincey, D., Ross, A., Rangecroft, S., Medina, K., Burns, H., Llacza, A., Jacome, G., Hellstrom, R., Castro, J., Cochachin, A., Montoya, N., Loarte, E., and Pellicciotti, F.: Precipitation and temperature climate change indices calculated from WRF data and statistically downscaled CMIP5 models, Cordillera Blanca and Vilcanota-Urubamba regions, Peru, from 1980 to 2100 (Version 1.0), NERC EDS UK Polar Data Centre [data set], https://doi.org/10.5285/b56d30e8-edaa-4225-96d7-fcc689e930c7, 2023d. a
Quiroz, R., Yarlequé, C., Posadas, A., Mares, V., and Immerzeel, W. W.: Improving daily rainfall estimation from NDVI using a wavelet transform, Environ. Modell. Softw., 26, 201–209, https://doi.org/10.1016/j.envsoft.2010.07.006, 2011. a
Rangecroft, S., Dextre, R. M., Richter, I., Grados Bueno, C. V., Kelly, C., Turin, C., Fuentealba, B., Hernandez, M. C., Morera, S., Martin, J., Guy, A., and Clason, C.: Unravelling and understanding local perceptions of water quality in the Santa basin, Peru, J. Hydrol., 625, 129949, https://doi.org/10.1016/j.jhydrol.2023.129949, 2023. a
Rouse Jr., J. W., Haas, R. H., Schell, J., and Deering, D.: Monitoring the vernal advancement and retrogradation (green wave effect) of natural vegetation, Tech. rep., NASA-CR-132982, 1974. a
Sedlmeier, K., Imfeld, N., Gubler, S., Spirig, C., Caiña, K. Q., Escajadillo, Y., Rohrer, M., and Schwierz, C.: The rainy season in the Southern Peruvian Andes: A climatological analysis based on the new Climandes index, Int. J. Climatol., 43, 3005–3022, https://doi.org/10.1002/joc.8013, 2023. a, b, c, d, e, f, g
Servicio Nacional de Meteorología e Hidrología del Perú (SENAMHI): Plataforma de Datos de Estaciones Meteorológicas, https://www.senamhi.gob.pe/?p=estaciones, last access: 25 June 2025. a
Seregina, L. S., Fink, A. H., van der Linden, R., Elagib, N. A., and Pinto, J. G.: A new and flexible rainy season definition: Validation for the Greater Horn of Africa and application to rainfall trends, Int. J. Climatol., 39, 989–1012, https://doi.org/10.1002/joc.5856, 2018. a
Stern, R., Dennett, M., and Garbutt, D.: The start of the rains in West Africa, J. Climatol., 1, 59–68, 1981. a
Storn, R. and Price, K.: Differential Evolution – A Simple and Efficient Heuristic for global Optimization over Continuous Spaces, J. Global Optim., 11, 341–359, https://doi.org/10.1023/a:1008202821328, 1997. a
USGS EROS Archive: Digital Elevation – Shuttle Radar Topography Mission (SRTM) 1 Arc-second Global, uSGS EROS Archive [data set], https://www.usgs.gov/centers/eros (last access: 15 January 2021), 2021. a
Virtanen, P., Gommers, R., Oliphant, T. E., Haberland, M., Reddy, T., Cournapeau, D., Burovski, E., Peterson, P., Weckesser, W., Bright, J., van der Walt, S. J., Brett, M., Wilson, J., Millman, K. J., Mayorov, N., Nelson, A. R. J., Jones, E., Kern, R., Larson, E., Carey, C. J., Polat, I., Feng, Y., Moore, E. W., VanderPlas, J., Laxalde, D., Perktold, J., Cimrman, R., Henriksen, I., Quintero, E. A., Harris, C. R., Archibald, A. M., Ribeiro, A. H., Pedregosa, F., van Mulbregt, P., and SciPy, C.: SciPy 1.0: fundamental algorithms for scientific computing in Python, Nat. Methods, 17, 261–272, https://doi.org/10.1038/s41592-019-0686-2, 2020. a
Vuille, M., Kaser, G., and Juen, I.: Glacier mass balance variability in the Cordillera Blanca, Peru and its relationship with climate and the large-scale circulation, Global Planet. Change, 62, 14–28, https://doi.org/10.1016/j.gloplacha.2007.11.003, 2008. a
Warner, K., Afifi, T., Henry, K., Rawe, T., Smith, C., and De Sherbinin, A.: Where the Rain Falls : Climate Change, food and Livelihood Security, and Migration, Global Policy Report of the Where the Rain Falls Project, CARE France and UNU-EHS, Bonn, ISBN 978-3-939923-88-6, eISBN 978-3-939923-89-3, 2012. a
Yarleque, C., Vuille, M., Hardy, D. R., Posadas, A., and Quiroz, R.: Multiscale assessment of spatial precipitation variability over complex mountain terrain using a high-resolution spatiotemporal wavelet reconstruction method, J. Geophys. Res.-Atmos., 121, 12198–12216, https://doi.org/10.1002/2016jd025647, 2016. a
Zampieri, M., Toreti, A., Meroni, M., Bojovic, D., Octenjak, S., Marcos-Matamoros, R., Materia, S., Chang'a, L., Merchades, M., del Mar Chaves Montero, M., Rembold, F., Troccoli, A., Roy, I., and Hoteit, I.: Seasonal forecasts of the rainy season onset over Africa: Preliminary results from the FOCUS-Africa project, Climate Services, 32, 100417, https://doi.org/10.1016/j.cliser.2023.100417, 2023. a
Zhang, X. B., Alexander, L., Hegerl, G. C., Jones, P., Tank, A. K., Peterson, T. C., Trewin, B., and Zwiers, F. W.: Indices for monitoring changes in extremes based on daily temperature and precipitation data, Wiley Interdisciplinary Reviews-Climate Change, 2, 851–870, https://doi.org/10.1002/wcc.147, 2011. a
Short summary
In semi-arid regions, the timing and duration of the rainy season are crucial for agriculture. This study introduces a new framework for improving estimations of the onset and end of the rainy season by testing how well they fit local vegetation data. We improve the performance of existing methods and present a new one with higher performance. Our findings can help us to make informed decisions about water usage, and the framework can be applied to other regions as well.
In semi-arid regions, the timing and duration of the rainy season are crucial for agriculture....
