[{"type":"journal_article","volume":94,"doi":"10.1016/j.advwatres.2016.05.001","publication_identifier":{"issn":["0309-1708"]},"month":"08","quality_controlled":"1","article_type":"original","author":[{"first_name":"M.","last_name":"Carenzo","full_name":"Carenzo, M."},{"last_name":"Pellicciotti","first_name":"Francesca","full_name":"Pellicciotti, Francesca","orcid":"0000-0002-5554-8087","id":"b28f055a-81ea-11ed-b70c-a9fe7f7b0e70"},{"first_name":"J.","last_name":"Mabillard","full_name":"Mabillard, J."},{"first_name":"T.","last_name":"Reid","full_name":"Reid, T."},{"full_name":"Brock, B.W.","first_name":"B.W.","last_name":"Brock"}],"user_id":"2DF688A6-F248-11E8-B48F-1D18A9856A87","publication":"Advances in Water Resources","language":[{"iso":"eng"}],"keyword":["Water Science and Technology"],"citation":{"mla":"Carenzo, M., et al. “An Enhanced Temperature Index Model for Debris-Covered Glaciers Accounting for Thickness Effect.” <i>Advances in Water Resources</i>, vol. 94, Elsevier, 2016, pp. 457–69, doi:<a href=\"https://doi.org/10.1016/j.advwatres.2016.05.001\">10.1016/j.advwatres.2016.05.001</a>.","apa":"Carenzo, M., Pellicciotti, F., Mabillard, J., Reid, T., &#38; Brock, B. W. (2016). An enhanced temperature index model for debris-covered glaciers accounting for thickness effect. <i>Advances in Water Resources</i>. Elsevier. <a href=\"https://doi.org/10.1016/j.advwatres.2016.05.001\">https://doi.org/10.1016/j.advwatres.2016.05.001</a>","short":"M. Carenzo, F. Pellicciotti, J. Mabillard, T. Reid, B.W. Brock, Advances in Water Resources 94 (2016) 457–469.","ama":"Carenzo M, Pellicciotti F, Mabillard J, Reid T, Brock BW. An enhanced temperature index model for debris-covered glaciers accounting for thickness effect. <i>Advances in Water Resources</i>. 2016;94:457-469. doi:<a href=\"https://doi.org/10.1016/j.advwatres.2016.05.001\">10.1016/j.advwatres.2016.05.001</a>","chicago":"Carenzo, M., Francesca Pellicciotti, J. Mabillard, T. Reid, and B.W. Brock. “An Enhanced Temperature Index Model for Debris-Covered Glaciers Accounting for Thickness Effect.” <i>Advances in Water Resources</i>. Elsevier, 2016. <a href=\"https://doi.org/10.1016/j.advwatres.2016.05.001\">https://doi.org/10.1016/j.advwatres.2016.05.001</a>.","ieee":"M. Carenzo, F. Pellicciotti, J. Mabillard, T. Reid, and B. W. Brock, “An enhanced temperature index model for debris-covered glaciers accounting for thickness effect,” <i>Advances in Water Resources</i>, vol. 94. Elsevier, pp. 457–469, 2016.","ista":"Carenzo M, Pellicciotti F, Mabillard J, Reid T, Brock BW. 2016. An enhanced temperature index model for debris-covered glaciers accounting for thickness effect. Advances in Water Resources. 94, 457–469."},"publisher":"Elsevier","intvolume":"        94","article_processing_charge":"No","day":"01","main_file_link":[{"open_access":"1","url":"https://doi.org/10.1016/j.advwatres.2016.05.001"}],"date_published":"2016-08-01T00:00:00Z","title":"An enhanced temperature index model for debris-covered glaciers accounting for thickness effect","status":"public","_id":"12620","date_created":"2023-02-20T08:15:11Z","oa":1,"abstract":[{"text":"Debris-covered glaciers are increasingly studied because it is assumed that debris cover extent and thickness could increase in a warming climate, with more regular rockfalls from the surrounding slopes and more englacial melt-out material. Debris energy-balance models have been developed to account for the melt rate enhancement/reduction due to a thin/thick debris layer, respectively. However, such models require a large amount of input data that are not often available, especially in remote mountain areas such as the Himalaya, and can be difficult to extrapolate. Due to their lower data requirements, empirical models have been used extensively in clean glacier melt modelling. For debris-covered glaciers, however, they generally simplify the debris effect by using a single melt-reduction factor which does not account for the influence of varying debris thickness on melt and prescribe a constant reduction for the entire melt across a glacier.\r\n\r\nIn this paper, we present a new temperature-index model that accounts for debris thickness in the computation of melt rates at the debris-ice interface. The model empirical parameters are optimized at the point scale for varying debris thicknesses against melt rates simulated by a physically-based debris energy balance model. The latter is validated against ablation stake readings and surface temperature measurements. Each parameter is then related to a plausible set of debris thickness values to provide a general and transferable parameterization. We develop the model on Miage Glacier, Italy, and then test its transferability on Haut Glacier d’Arolla, Switzerland.\r\n\r\nThe performance of the new debris temperature-index (DETI) model in simulating the glacier melt rate at the point scale is comparable to the one of the physically based approach, and the definition of model parameters as a function of debris thickness allows the simulation of the nonlinear relationship of melt rate to debris thickness, summarised by the Østrem curve. Its large number of parameters might be a limitation, but we show that the model is transferable in time and space to a second glacier with little loss of performance. We thus suggest that the new DETI model can be included in continuous mass balance models of debris-covered glaciers, because of its limited data requirements. As such, we expect its application to lead to an improvement in simulations of the debris-covered glacier response to climate in comparison with models that simply recalibrate empirical parameters to prescribe a constant across glacier reduction in melt.","lang":"eng"}],"extern":"1","scopus_import":"1","oa_version":"Published Version","date_updated":"2024-10-14T12:04:30Z","year":"2016","page":"457-469","publication_status":"published"},{"intvolume":"        92","citation":{"short":"J. Kim, M.C. Dwelle, S.K. Kampf, S. Fatichi, V.Y. Ivanov, Advances in Water Resources 92 (2016) 73–89.","ama":"Kim J, Dwelle MC, Kampf SK, Fatichi S, Ivanov VY. On the non-uniqueness of the hydro-geomorphic responses in a zero-order catchment with respect to soil moisture. <i>Advances in Water Resources</i>. 2016;92:73-89. doi:<a href=\"https://doi.org/10.1016/j.advwatres.2016.03.019\">10.1016/j.advwatres.2016.03.019</a>","ieee":"J. Kim, M. C. Dwelle, S. K. Kampf, S. Fatichi, and V. Y. Ivanov, “On the non-uniqueness of the hydro-geomorphic responses in a zero-order catchment with respect to soil moisture,” <i>Advances in Water Resources</i>, vol. 92. Elsevier, pp. 73–89, 2016.","ista":"Kim J, Dwelle MC, Kampf SK, Fatichi S, Ivanov VY. 2016. On the non-uniqueness of the hydro-geomorphic responses in a zero-order catchment with respect to soil moisture. Advances in Water Resources. 92, 73–89.","chicago":"Kim, Jongho, M. Chase Dwelle, Stephanie K. Kampf, Simone Fatichi, and Valeriy Y. Ivanov. “On the Non-Uniqueness of the Hydro-Geomorphic Responses in a Zero-Order Catchment with Respect to Soil Moisture.” <i>Advances in Water Resources</i>. Elsevier, 2016. <a href=\"https://doi.org/10.1016/j.advwatres.2016.03.019\">https://doi.org/10.1016/j.advwatres.2016.03.019</a>.","mla":"Kim, Jongho, et al. “On the Non-Uniqueness of the Hydro-Geomorphic Responses in a Zero-Order Catchment with Respect to Soil Moisture.” <i>Advances in Water Resources</i>, vol. 92, Elsevier, 2016, pp. 73–89, doi:<a href=\"https://doi.org/10.1016/j.advwatres.2016.03.019\">10.1016/j.advwatres.2016.03.019</a>.","apa":"Kim, J., Dwelle, M. C., Kampf, S. K., Fatichi, S., &#38; Ivanov, V. Y. (2016). On the non-uniqueness of the hydro-geomorphic responses in a zero-order catchment with respect to soil moisture. <i>Advances in Water Resources</i>. Elsevier. <a href=\"https://doi.org/10.1016/j.advwatres.2016.03.019\">https://doi.org/10.1016/j.advwatres.2016.03.019</a>"},"publisher":"Elsevier","article_processing_charge":"No","date_published":"2016-07-01T00:00:00Z","day":"01","author":[{"last_name":"Kim","first_name":"Jongho","full_name":"Kim, Jongho"},{"full_name":"Dwelle, M. Chase","last_name":"Dwelle","first_name":"M. Chase"},{"first_name":"Stephanie K.","last_name":"Kampf","full_name":"Kampf, Stephanie K."},{"full_name":"Fatichi, Simone","last_name":"Fatichi","first_name":"Simone","id":"cf8e546b-a9b0-11f0-a43b-aa89ed1b56d6"},{"full_name":"Ivanov, Valeriy Y.","last_name":"Ivanov","first_name":"Valeriy Y."}],"keyword":["Soil moisture","Spatial heterogeneity","Hydrological response","Geomorphic response","Non-uniqueness","Hydraulic connectivity"],"language":[{"iso":"eng"}],"user_id":"2DF688A6-F248-11E8-B48F-1D18A9856A87","publication":"Advances in Water Resources","publication_identifier":{"issn":["0309-1708"]},"article_type":"original","month":"07","quality_controlled":"1","type":"journal_article","volume":92,"doi":"10.1016/j.advwatres.2016.03.019","year":"2016","OA_type":"closed access","page":"73-89","publication_status":"published","oa_version":"None","scopus_import":"1","date_updated":"2026-08-06T07:50:36Z","status":"public","_id":"22510","title":"On the non-uniqueness of the hydro-geomorphic responses in a zero-order catchment with respect to soil moisture","extern":"1","date_created":"2026-07-27T12:30:24Z","abstract":[{"text":"This study advances mechanistic interpretation of predictability challenges in hydro-geomorphology related to the role of soil moisture spatial variability. Using model formulations describing the physics of overland flow, variably saturated subsurface flow, and erosion and sediment transport, this study explores (1) why a basin with the same mean soil moisture can exhibit distinctly different spatial moisture distributions, (2) whether these varying distributions lead to non-unique hydro-geomorphic responses, and (3) what controls non-uniqueness in relation to the response type. Two sets of numerical experiments are carried out with two physically-based models, HYDRUS and tRIBS+VEGGIE+FEaST, and their outputs are analyzed with respect to pre-storm moisture state. The results demonstrate that distinct spatial moisture distributions for the same mean wetness arise because near-surface soil moisture dynamics exhibit different degrees of coupling with deeper-soil moisture and the process of subsurface drainage. The consequences of such variations are different depending on the type of hydrological response. Specifically, if the predominant runoff response is of infiltration excess type, the degree of non-uniqueness is related to the spatial distribution of near-surface moisture. If runoff is governed by subsurface stormflow, the extent of deep moisture contributing area and its “readiness to drain” determine the response characteristics. Because the processes of erosion and sediment transport superimpose additional controls over factors governing runoff generation and overland flow, non-uniqueness of the geomorphic response can be highly dampened or enhanced. The explanation is sediment composed by multi-size particles can alternate states of mobilization or surface shielding and the transient behavior is inherently intertwined with the availability of mobile particles. We conclude that complex nonlinear dynamics of hydro-geomorphic processes are inherent expressions of physical interactions. As complete knowledge of watershed properties, states, or forcings will always present the ultimate, if ever resolvable, challenge, deterministic predictability will remain handicapped. Coupling of uncertainty quantification methods and space-time physics-based approaches will need to evolve to facilitate mechanistic interpretations and informed practical applications.","lang":"eng"}],"das_tickbox":"1"},{"scopus_import":"1","oa_version":"None","date_updated":"2023-02-24T09:28:04Z","year":"2015","publication_status":"published","page":"94-111","_id":"12630","status":"public","title":"Unraveling the hydrology of a Himalayan catchment through integration of high resolution in situ data and remote sensing with an advanced simulation model","extern":"1","abstract":[{"lang":"eng","text":"The hydrology of high-elevation watersheds of the Hindu Kush-Himalaya region (HKH) is poorly known. The correct representation of internal states and process dynamics in glacio-hydrological models can often not be verified due to missing in situ measurements. We use a new set of detailed ground data from the upper Langtang valley in Nepal to systematically guide a state-of-the art glacio-hydrological model through a parameter assigning process with the aim to understand the hydrology of the catchment and contribution of snow and ice processes to runoff. 14 parameters are directly calculated on the basis of local data, and 13 parameters are calibrated against 5 different datasets of in situ or remote sensing data. Spatial fields of debris thickness are reconstructed through a novel approach that employs data from an Unmanned Aerial Vehicle (UAV), energy balance modeling and statistical techniques. The model is validated against measured catchment runoff (Nash–Sutcliffe efficiency 0.87) and modeled snow cover is compared to Landsat snow cover. The advanced representation of processes allowed assessing the role played by avalanching for runoff for the first time for a Himalayan catchment (5% of annual water inputs to the hydrological system are due to snow redistribution) and to quantify the hydrological significance of sub-debris ice melt (9% of annual water inputs). Snowmelt is the most important contributor to total runoff during the hydrological year 2012/2013 (representing 40% of all sources), followed by rainfall (34%) and ice melt (26%). A sensitivity analysis is used to assess the efficiency of the monitoring network and identify the timing and location of field measurements that constrain model uncertainty. The methodology to set up a glacio-hydrological model in high-elevation regions presented in this study can be regarded as a benchmark for modelers in the HKH seeking to evaluate their calibration approach, their experimental setup and thus to reduce the predictive model uncertainty.\r\n\r\n"}],"date_created":"2023-02-20T08:16:21Z","author":[{"full_name":"Ragettli, S.","last_name":"Ragettli","first_name":"S."},{"id":"b28f055a-81ea-11ed-b70c-a9fe7f7b0e70","first_name":"Francesca","last_name":"Pellicciotti","full_name":"Pellicciotti, Francesca"},{"full_name":"Immerzeel, W.W.","first_name":"W.W.","last_name":"Immerzeel"},{"last_name":"Miles","first_name":"E.S.","full_name":"Miles, E.S."},{"full_name":"Petersen, L.","first_name":"L.","last_name":"Petersen"},{"full_name":"Heynen, M.","first_name":"M.","last_name":"Heynen"},{"full_name":"Shea, J.M.","first_name":"J.M.","last_name":"Shea"},{"full_name":"Stumm, D.","last_name":"Stumm","first_name":"D."},{"first_name":"S.","last_name":"Joshi","full_name":"Joshi, S."},{"first_name":"A.","last_name":"Shrestha","full_name":"Shrestha, A."}],"keyword":["Water Science and Technology"],"language":[{"iso":"eng"}],"publication":"Advances in Water Resources","user_id":"2DF688A6-F248-11E8-B48F-1D18A9856A87","issue":"4","intvolume":"        78","publisher":"Elsevier","citation":{"mla":"Ragettli, S., et al. “Unraveling the Hydrology of a Himalayan Catchment through Integration of High Resolution in Situ Data and Remote Sensing with an Advanced Simulation Model.” <i>Advances in Water Resources</i>, vol. 78, no. 4, Elsevier, 2015, pp. 94–111, doi:<a href=\"https://doi.org/10.1016/j.advwatres.2015.01.013\">10.1016/j.advwatres.2015.01.013</a>.","apa":"Ragettli, S., Pellicciotti, F., Immerzeel, W. W., Miles, E. S., Petersen, L., Heynen, M., … Shrestha, A. (2015). Unraveling the hydrology of a Himalayan catchment through integration of high resolution in situ data and remote sensing with an advanced simulation model. <i>Advances in Water Resources</i>. Elsevier. <a href=\"https://doi.org/10.1016/j.advwatres.2015.01.013\">https://doi.org/10.1016/j.advwatres.2015.01.013</a>","short":"S. Ragettli, F. Pellicciotti, W.W. Immerzeel, E.S. Miles, L. Petersen, M. Heynen, J.M. Shea, D. Stumm, S. Joshi, A. Shrestha, Advances in Water Resources 78 (2015) 94–111.","ama":"Ragettli S, Pellicciotti F, Immerzeel WW, et al. Unraveling the hydrology of a Himalayan catchment through integration of high resolution in situ data and remote sensing with an advanced simulation model. <i>Advances in Water Resources</i>. 2015;78(4):94-111. doi:<a href=\"https://doi.org/10.1016/j.advwatres.2015.01.013\">10.1016/j.advwatres.2015.01.013</a>","ista":"Ragettli S, Pellicciotti F, Immerzeel WW, Miles ES, Petersen L, Heynen M, Shea JM, Stumm D, Joshi S, Shrestha A. 2015. Unraveling the hydrology of a Himalayan catchment through integration of high resolution in situ data and remote sensing with an advanced simulation model. Advances in Water Resources. 78(4), 94–111.","ieee":"S. Ragettli <i>et al.</i>, “Unraveling the hydrology of a Himalayan catchment through integration of high resolution in situ data and remote sensing with an advanced simulation model,” <i>Advances in Water Resources</i>, vol. 78, no. 4. Elsevier, pp. 94–111, 2015.","chicago":"Ragettli, S., Francesca Pellicciotti, W.W. Immerzeel, E.S. Miles, L. Petersen, M. Heynen, J.M. Shea, D. Stumm, S. Joshi, and A. Shrestha. “Unraveling the Hydrology of a Himalayan Catchment through Integration of High Resolution in Situ Data and Remote Sensing with an Advanced Simulation Model.” <i>Advances in Water Resources</i>. Elsevier, 2015. <a href=\"https://doi.org/10.1016/j.advwatres.2015.01.013\">https://doi.org/10.1016/j.advwatres.2015.01.013</a>."},"date_published":"2015-04-01T00:00:00Z","day":"01","article_processing_charge":"No","type":"journal_article","doi":"10.1016/j.advwatres.2015.01.013","volume":78,"publication_identifier":{"issn":["0309-1708"]},"article_type":"original","quality_controlled":"1","month":"04"},{"doi":"10.1016/j.advwatres.2013.11.006","volume":63,"type":"journal_article","quality_controlled":"1","month":"01","article_type":"original","publication_identifier":{"issn":["0309-1708"]},"language":[{"iso":"eng"}],"user_id":"ba8df636-2132-11f1-aed0-ed93e2281fdd","publication":"Advances in Water Resources","keyword":["Stochastic rainfall models","Poisson cluster model","Multiplicative Random Cascade","Markov chain","Alternating renewal process"],"author":[{"full_name":"Paschalis, Athanasios","last_name":"Paschalis","first_name":"Athanasios"},{"last_name":"Molnar","first_name":"Peter","full_name":"Molnar, Peter"},{"full_name":"Fatichi, Simone","last_name":"Fatichi","first_name":"Simone","id":"cf8e546b-a9b0-11f0-a43b-aa89ed1b56d6"},{"first_name":"Paolo","last_name":"Burlando","full_name":"Burlando, Paolo"}],"day":"01","date_published":"2014-01-01T00:00:00Z","article_processing_charge":"No","publisher":"Elsevier","citation":{"short":"A. Paschalis, P. Molnar, S. Fatichi, P. Burlando, Advances in Water Resources 63 (2014) 152–166.","ama":"Paschalis A, Molnar P, Fatichi S, Burlando P. On temporal stochastic modeling of precipitation, nesting models across scales. <i>Advances in Water Resources</i>. 2014;63:152-166. doi:<a href=\"https://doi.org/10.1016/j.advwatres.2013.11.006\">10.1016/j.advwatres.2013.11.006</a>","ieee":"A. Paschalis, P. Molnar, S. Fatichi, and P. Burlando, “On temporal stochastic modeling of precipitation, nesting models across scales,” <i>Advances in Water Resources</i>, vol. 63. Elsevier, pp. 152–166, 2014.","ista":"Paschalis A, Molnar P, Fatichi S, Burlando P. 2014. On temporal stochastic modeling of precipitation, nesting models across scales. Advances in Water Resources. 63, 152–166.","chicago":"Paschalis, Athanasios, Peter Molnar, Simone Fatichi, and Paolo Burlando. “On Temporal Stochastic Modeling of Precipitation, Nesting Models across Scales.” <i>Advances in Water Resources</i>. Elsevier, 2014. <a href=\"https://doi.org/10.1016/j.advwatres.2013.11.006\">https://doi.org/10.1016/j.advwatres.2013.11.006</a>.","mla":"Paschalis, Athanasios, et al. “On Temporal Stochastic Modeling of Precipitation, Nesting Models across Scales.” <i>Advances in Water Resources</i>, vol. 63, Elsevier, 2014, pp. 152–66, doi:<a href=\"https://doi.org/10.1016/j.advwatres.2013.11.006\">10.1016/j.advwatres.2013.11.006</a>.","apa":"Paschalis, A., Molnar, P., Fatichi, S., &#38; Burlando, P. (2014). On temporal stochastic modeling of precipitation, nesting models across scales. <i>Advances in Water Resources</i>. Elsevier. <a href=\"https://doi.org/10.1016/j.advwatres.2013.11.006\">https://doi.org/10.1016/j.advwatres.2013.11.006</a>"},"intvolume":"        63","das_tickbox":"1","abstract":[{"text":"We analyze the performance of composite stochastic models of temporal precipitation which can satisfactorily reproduce precipitation properties across a wide range of temporal scales. The rationale is that a combination of stochastic precipitation models which are most appropriate for specific limited temporal scales leads to better overall performance across a wider range of scales than single models alone. We investigate different model combinations. For the coarse (daily) scale these are models based on Alternating renewal processes, Markov chains, and Poisson cluster models, which are then combined with a microcanonical Multiplicative Random Cascade model to disaggregate precipitation to finer (minute) scales. The composite models were tested on data at four sites in different climates. The results show that model combinations improve the performance in key statistics such as probability distributions of precipitation depth, autocorrelation structure, intermittency, reproduction of extremes, compared to single models. At the same time they remain reasonably parsimonious. No model combination was found to outperform the others at all sites and for all statistics, however we provide insight on the capabilities of specific model combinations. The results for the four different climates are similar, which suggests a degree of generality and wider applicability of the approach.","lang":"eng"}],"date_created":"2026-07-27T12:30:25Z","extern":"1","title":"On temporal stochastic modeling of precipitation, nesting models across scales","_id":"22575","status":"public","date_updated":"2026-08-10T11:55:17Z","oa_version":"None","scopus_import":"1","page":"152-166","publication_status":"published","OA_type":"closed access","year":"2014"},{"date_updated":"2026-08-12T14:11:56Z","oa_version":"None","scopus_import":"1","publication_status":"published","page":"159-175","OA_type":"closed access","year":"2014","das_tickbox":"1","extern":"1","abstract":[{"lang":"eng","text":"Regions of vegetation transitions (ecotones) are known to be highly sensitive to climate fluctuations. In this study, the Cellular-Automata Tree Grass Shrub Simulator (CATGraSS) has been modified, calibrated and used with downscaled future climate scenarios to examine the role of climate change on vegetation patterns in a steep mountainous catchment (1.3 km2) located in Sicily, Italy. In the catchment, north-facing slopes are mostly covered by trees and grass, and south-facing slopes by Indian Fig opuntia and grass, with grasses dominating as elevation grows. CATGraSS simulates solar radiation, evapotranspiration, and soil moisture in space and time. Each model cell can hold a single plant type or can be bare soil. Plant competition is modeled explicitly through mortality and the establishment of individual plants in open spaces. In this study, CATGraSS is modified to account for heterogeneity in soil thickness and tested in the study catchment using the historical climate of the region. Predicted vegetation patterns are compared with those obtained from satellite images. Results of model under current climate underscore the importance of solar irradiance and soil thickness, especially in the uplands where soil is shallow, in determining vegetation composition over complex terrain. A stochastic weather generator is used to generate future climate change scenarios for the catchment by downscaling GCM realizations in space and time. Future increase in atmospheric CO2 concentration was considered through modifying the vegetation water use efficiency and stomatal resistance for our study site. Model results suggest that vegetation pattern is highly sensitive to temperature and rainfall variations provided by climate scenarios (30% reduction of the annual precipitation and a 2.8 °C increase of the mean annual temperature). Future climate change is predicted to bring a considerable reorganization of the plant composition following topographic patterns, leading to a decrease of trees cover at the expenses of a grass expansion, which will cause loss of landscape vegetation diversity."}],"date_created":"2026-07-27T12:30:23Z","status":"public","_id":"22435","title":"Climate change and Ecotone boundaries: Insights from a cellular automata ecohydrology model in a Mediterranean catchment with topography controlled vegetation patterns","keyword":["CA model","Climate change","Ecohydrology","Topography"],"publication":"Advances in Water Resources","user_id":"ba8df636-2132-11f1-aed0-ed93e2281fdd","language":[{"iso":"eng"}],"author":[{"full_name":"Caracciolo, Domenico","first_name":"Domenico","last_name":"Caracciolo"},{"full_name":"Noto, Leonardo Valerio","last_name":"Noto","first_name":"Leonardo Valerio"},{"first_name":"Erkan","last_name":"Istanbulluoglu","full_name":"Istanbulluoglu, Erkan"},{"id":"cf8e546b-a9b0-11f0-a43b-aa89ed1b56d6","full_name":"Fatichi, Simone","first_name":"Simone","last_name":"Fatichi"},{"last_name":"Zhou","first_name":"Xiaochi","full_name":"Zhou, Xiaochi"}],"date_published":"2014-11-01T00:00:00Z","day":"01","article_processing_charge":"No","intvolume":"        73","publisher":"Elsevier","citation":{"short":"D. Caracciolo, L.V. Noto, E. Istanbulluoglu, S. Fatichi, X. Zhou, Advances in Water Resources 73 (2014) 159–175.","ama":"Caracciolo D, Noto LV, Istanbulluoglu E, Fatichi S, Zhou X. Climate change and Ecotone boundaries: Insights from a cellular automata ecohydrology model in a Mediterranean catchment with topography controlled vegetation patterns. <i>Advances in Water Resources</i>. 2014;73:159-175. doi:<a href=\"https://doi.org/10.1016/j.advwatres.2014.08.001\">10.1016/j.advwatres.2014.08.001</a>","chicago":"Caracciolo, Domenico, Leonardo Valerio Noto, Erkan Istanbulluoglu, Simone Fatichi, and Xiaochi Zhou. “Climate Change and Ecotone Boundaries: Insights from a Cellular Automata Ecohydrology Model in a Mediterranean Catchment with Topography Controlled Vegetation Patterns.” <i>Advances in Water Resources</i>. Elsevier, 2014. <a href=\"https://doi.org/10.1016/j.advwatres.2014.08.001\">https://doi.org/10.1016/j.advwatres.2014.08.001</a>.","ieee":"D. Caracciolo, L. V. Noto, E. Istanbulluoglu, S. Fatichi, and X. Zhou, “Climate change and Ecotone boundaries: Insights from a cellular automata ecohydrology model in a Mediterranean catchment with topography controlled vegetation patterns,” <i>Advances in Water Resources</i>, vol. 73. Elsevier, pp. 159–175, 2014.","ista":"Caracciolo D, Noto LV, Istanbulluoglu E, Fatichi S, Zhou X. 2014. Climate change and Ecotone boundaries: Insights from a cellular automata ecohydrology model in a Mediterranean catchment with topography controlled vegetation patterns. Advances in Water Resources. 73, 159–175.","mla":"Caracciolo, Domenico, et al. “Climate Change and Ecotone Boundaries: Insights from a Cellular Automata Ecohydrology Model in a Mediterranean Catchment with Topography Controlled Vegetation Patterns.” <i>Advances in Water Resources</i>, vol. 73, Elsevier, 2014, pp. 159–75, doi:<a href=\"https://doi.org/10.1016/j.advwatres.2014.08.001\">10.1016/j.advwatres.2014.08.001</a>.","apa":"Caracciolo, D., Noto, L. V., Istanbulluoglu, E., Fatichi, S., &#38; Zhou, X. (2014). Climate change and Ecotone boundaries: Insights from a cellular automata ecohydrology model in a Mediterranean catchment with topography controlled vegetation patterns. <i>Advances in Water Resources</i>. Elsevier. <a href=\"https://doi.org/10.1016/j.advwatres.2014.08.001\">https://doi.org/10.1016/j.advwatres.2014.08.001</a>"},"doi":"10.1016/j.advwatres.2014.08.001","volume":73,"type":"journal_article","article_type":"original","quality_controlled":"1","month":"11","publication_identifier":{"issn":["0309-1708"]}},{"oa_version":"None","scopus_import":"1","date_updated":"2026-08-06T10:13:12Z","year":"2011","OA_type":"closed access","publication_status":"published","page":"448-467","das_tickbox":"1","_id":"22556","status":"public","title":"Simulation of future climate scenarios with a weather generator","extern":"1","date_created":"2026-07-27T12:30:24Z","abstract":[{"text":"Numerous studies across multiple disciplines search for insights on the effects of climate change at local spatial scales and at fine time resolutions. This study presents an overall methodology of using a weather generator for downscaling an ensemble of climate model outputs. The downscaled predictions can explicitly include climate model uncertainty, which offers valuable information for making probabilistic inferences about climate impacts. The hourly weather generator that serves as the downscaling tool is briefly presented. The generator is designed to reproduce a set of meteorological variables that can serve as input to hydrological, ecological, geomorphological, and agricultural models. The generator is capable of reproducing a wide set of climate statistics over a range of temporal scales, from extremes, to low-frequency interannual variability; its performance for many climate variables and their statistics over different aggregation periods is highly satisfactory. The use of the weather generator in simulations of future climate scenarios, as inferred from climate models, is described in detail. Using a previously developed methodology based on a Bayesian approach, the stochastic downscaling procedure derives the frequency distribution functions of factors of change for several climate statistics from a multi-model ensemble of outputs of General Circulation Models. The factors of change are subsequently applied to the statistics derived from observations to re-evaluate the parameters of the weather generator. Using embedded causal and statistical relationships, the generator simulates future realizations of climate for a specific point location at the hourly scale. Uncertainties present in the climate model realizations and the multi-model ensemble predictions are discussed. An application of the weather generator in reproducing present (1961–2000) and forecasting future (2081–2100) climate conditions is illustrated for the location of Tucson (AZ). The stochastic downscaling is carried out using simulations of eight General Circulation Models adopted in the IPCC 4AR, A1B emission scenario.","lang":"eng"}],"author":[{"full_name":"Fatichi, Simone","last_name":"Fatichi","first_name":"Simone","id":"cf8e546b-a9b0-11f0-a43b-aa89ed1b56d6"},{"full_name":"Ivanov, Valeriy Y.","last_name":"Ivanov","first_name":"Valeriy Y."},{"first_name":"Enrica","last_name":"Caporali","full_name":"Caporali, Enrica"}],"keyword":["Weather generator","Stochastic downscaling","Climate change","Hydro-meteorology","Rainfall model"],"user_id":"ba8df636-2132-11f1-aed0-ed93e2281fdd","language":[{"iso":"eng"}],"publication":"Advances in Water Resources","intvolume":"        34","issue":"4","citation":{"mla":"Fatichi, Simone, et al. “Simulation of Future Climate Scenarios with a Weather Generator.” <i>Advances in Water Resources</i>, vol. 34, no. 4, Elsevier, 2011, pp. 448–67, doi:<a href=\"https://doi.org/10.1016/j.advwatres.2010.12.013\">10.1016/j.advwatres.2010.12.013</a>.","apa":"Fatichi, S., Ivanov, V. Y., &#38; Caporali, E. (2011). Simulation of future climate scenarios with a weather generator. <i>Advances in Water Resources</i>. Elsevier. <a href=\"https://doi.org/10.1016/j.advwatres.2010.12.013\">https://doi.org/10.1016/j.advwatres.2010.12.013</a>","ama":"Fatichi S, Ivanov VY, Caporali E. Simulation of future climate scenarios with a weather generator. <i>Advances in Water Resources</i>. 2011;34(4):448-467. doi:<a href=\"https://doi.org/10.1016/j.advwatres.2010.12.013\">10.1016/j.advwatres.2010.12.013</a>","ista":"Fatichi S, Ivanov VY, Caporali E. 2011. Simulation of future climate scenarios with a weather generator. Advances in Water Resources. 34(4), 448–467.","chicago":"Fatichi, Simone, Valeriy Y. Ivanov, and Enrica Caporali. “Simulation of Future Climate Scenarios with a Weather Generator.” <i>Advances in Water Resources</i>. Elsevier, 2011. <a href=\"https://doi.org/10.1016/j.advwatres.2010.12.013\">https://doi.org/10.1016/j.advwatres.2010.12.013</a>.","ieee":"S. Fatichi, V. Y. Ivanov, and E. Caporali, “Simulation of future climate scenarios with a weather generator,” <i>Advances in Water Resources</i>, vol. 34, no. 4. Elsevier, pp. 448–467, 2011.","short":"S. Fatichi, V.Y. Ivanov, E. Caporali, Advances in Water Resources 34 (2011) 448–467."},"publisher":"Elsevier","article_processing_charge":"No","day":"01","date_published":"2011-04-01T00:00:00Z","type":"journal_article","volume":34,"doi":"10.1016/j.advwatres.2010.12.013","publication_identifier":{"issn":["0309-1708"]},"article_type":"original","month":"04","quality_controlled":"1"}]