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Journal articles on the topic 'Calibration of climate model'

Author: Grafiati

Published: 25 May 2024

Last updated: 19 July 2025

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1

Kutschera, Ellynne, John B. Kim, G. Stephen Pitts, and Ray Drapek. "“What’s Past Is Prologue”: Vegetation Model Calibration with and without Future Climate." Land 12, no. 6 (2023): 1121. http://dx.doi.org/10.3390/land12061121.

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Many models are designed to generate future predictions under climate-change scenarios. Such models are typically calibrated for a study area with climate data that represent historical conditions. However, future projections of the model may include outputs for which the model has not been calibrated. Ideally, a climate-change-impacts model would be calibrated for recent conditions and also for possible future climate conditions. We demonstrate an approach, where a vegetation model is subjected to two calibrations: conventionally to the study area and separately to the study area plus additio

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Lee, Jeonghoon, Jeonghyeon Choi, Jiyu Seo, Jeongeun Won, and Sangdan Kim. "Exploring Climate Sensitivity in Hydrological Model Calibration." Water 15, no. 23 (2023): 4094. http://dx.doi.org/10.3390/w15234094.

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In the context of hydrological model calibration, observational data play a central role in refining and evaluating model performance and uncertainty. Among the critical factors, the length of the data records and the associated climatic conditions are paramount. While there is ample research on data record length selection, the same cannot be said for the selection of data types, particularly when it comes to choosing the climatic conditions for calibration. Conceptual hydrological models inherently simplify the representation of hydrological processes, which can lead to structural limitation

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Tett, Simon F. B., Jonathan M. Gregory, Nicolas Freychet, Coralia Cartis, Michael J. Mineter, and Lindon Roberts. "Does Model Calibration Reduce Uncertainty in Climate Projections?" Journal of Climate 35, no. 8 (2022): 2585–602. http://dx.doi.org/10.1175/jcli-d-21-0434.1.

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Abstract Uncertainty in climate projections is large as shown by the likely uncertainty ranges in equilibrium climate sensitivity (ECS) of 2.5–4 K and in the transient climate response (TCR) of 1.4–2.2 K. Uncertainty in model projections could arise from the way in which unresolved processes are represented, the parameter values used, or the targets for model calibration. We show that, in two climate model ensembles that were objectively calibrated to minimize differences from observed large-scale atmospheric climatology, uncertainties in ECS and TCR are about 2–6 times smaller than in the CMI

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O'Reilly, Christopher H., Daniel J. Befort, and Antje Weisheimer. "Calibrating large-ensemble European climate projections using observational data." Earth System Dynamics 11, no. 4 (2020): 1033–49. http://dx.doi.org/10.5194/esd-11-1033-2020.

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Abstract. This study examines methods of calibrating projections of future regional climate for the next 40–50 years using large single-model ensembles (the Community Earth System Model (CESM) Large Ensemble and Max Planck Institute (MPI) Grand Ensemble), applied over Europe. The three calibration methods tested here are more commonly used for initialised forecasts from weeks up to seasonal timescales. The calibration techniques are applied to ensemble climate projections, fitting seasonal ensemble data to observations over a reference period (1920–2016). The calibration methods were tested an

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Kim, Daeha, Il Won Jung, and Jong Ahn Chun. "A comparative assessment of rainfall–runoff modelling against regional flow duration curves for ungauged catchments." Hydrology and Earth System Sciences 21, no. 11 (2017): 5647–61. http://dx.doi.org/10.5194/hess-21-5647-2017.

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Abstract. Rainfall–runoff modelling has long been a special subject in hydrological sciences, but identifying behavioural parameters in ungauged catchments is still challenging. In this study, we comparatively evaluated the performance of the local calibration of a rainfall–runoff model against regional flow duration curves (FDCs), which is a seemingly alternative method of classical parameter regionalisation for ungauged catchments. We used a parsimonious rainfall–runoff model over 45 South Korean catchments under semi-humid climate. The calibration against regional FDCs was compared with the

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Meinshausen, M., S. C. B. Raper, and T. M. L. Wigley. "Emulating coupled atmosphere-ocean and carbon cycle models with a simpler model, MAGICC6 – Part 1: Model description and calibration." Atmospheric Chemistry and Physics 11, no. 4 (2011): 1417–56. http://dx.doi.org/10.5194/acp-11-1417-2011.

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Abstract. Current scientific knowledge on the future response of the climate system to human-induced perturbations is comprehensively captured by various model intercomparison efforts. In the preparation of the Fourth Assessment Report (AR4) of the Intergovernmental Panel on Climate Change (IPCC), intercomparisons were organized for atmosphere-ocean general circulation models (AOGCMs) and carbon cycle models, named "CMIP3" and "C4MIP", respectively. Despite their tremendous value for the scientific community and policy makers alike, there are some difficulties in interpreting the results. For

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Beltran, Cesar, N. R. Edwards, A. B. Haurie, J. P. Vial, and D. S. Zachary. "Oracle-based optimization applied to climate model calibration." Environmental Modeling & Assessment 11, no. 1 (2005): 31–43. http://dx.doi.org/10.1007/s10666-005-9024-4.

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8

Koch, Julian, Mehmet Cüneyd Demirel, and Simon Stisen. "Climate Normalized Spatial Patterns of Evapotranspiration Enhance the Calibration of a Hydrological Model." Remote Sensing 14, no. 2 (2022): 315. http://dx.doi.org/10.3390/rs14020315.

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Spatial pattern-oriented evaluations of distributed hydrological models have contributed towards an improved realism of hydrological simulations. This advancement has been supported by the broad range of readily available satellite-based datasets of key hydrological variables, such as evapotranspiration (ET). At larger scale, spatial patterns of ET are often driven by underlying climate gradients, and with this study, we argue that gradient dominated patterns may hamper the potential of spatial pattern-oriented evaluation frameworks. We hypothesize that the climate control of spatial patterns

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Nguyen-Ky, Sy, and Katariina Penttilä. "Indoor Climate and Energy Model Calibration with Monitored Data of a Naturally Ventilated Dairy Barn in a Cold Climate." Applied Engineering in Agriculture 37, no. 5 (2021): 851–59. http://dx.doi.org/10.13031/aea.14280.

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HighlightsIndoor climate and energy model of a dairy barn is constructed and calibrated with collected data.Long-term monitoring of indoor conditions and electricity consumption greatly facilitates the model calibration process.Statistical benchmarks given by guidelines confirm the usability and reliability of the model.Abstract. This study demonstrates an application of ICE model calibration by using sensor building metrics in a naturally ventilated dairy house in a cold climate. The barn, at the time of the study, had 70 lactating cows and 30 calves with a total animal area of 1922 m2 and ot

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Urabe, Tomoyuki, Xiaoxiong Xiong, Taichiro Hashiguchi, Shigemasa Ando, Yoshihiko Okamura, and Kazuhiro Tanaka. "Radiometric Model and Inter-Comparison Results of the SGLI-VNR On-Board Calibration." Remote Sensing 12, no. 1 (2019): 69. http://dx.doi.org/10.3390/rs12010069.

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The Second Generation Global Imager (SGLI) on Global Change Observation Mission–Climate (GCOM-C) satellite empowers surface and atmospheric measurements related to the carbon cycle and radiation budget, with two radiometers of Visible and Near Infrared Radiometer (SGLI-VNR) and Infrared Scanning Radiometer (SGLI-IRS) that perform a wide-band (380 nm–12 µm) optical observation not only with as wide as a 1150–1400 km field of view (FOV), but also with as high as 0.25–0.5 km resolution. Additionally, polarization and along-track slant view observations are quite characteristic of SGLI. It is impo

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Guzmán-Cruz, R., R. Castañeda-Miranda, J. J. García-Escalante, A. Lara-Herrera, I. Serroukh, and L. O. Solis-Sánchez. "GENETIC ALGORITHMS FOR CALIBRATION OF A GREENHOUSE CLIMATE MODEL." Revista Chapingo Serie Horticultura XVI, no. 1 (2010): 23–30. http://dx.doi.org/10.5154/r.rchsh.2010.16.003.

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Steele, Katie, and Charlotte Werndl. "Climate Models, Calibration, and Confirmation." British Journal for the Philosophy of Science 64, no. 3 (2013): 609–35. http://dx.doi.org/10.1093/bjps/axs036.

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13

Sleziak, Patrik, Ladislav Holko, Michal Danko, and Juraj Parajka. "Uncertainty in the Number of Calibration Repetitions of a Hydrologic Model in Varying Climatic Conditions." Water 12, no. 9 (2020): 2362. http://dx.doi.org/10.3390/w12092362.

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The objective of this study is to examine the impact of the number of calibration repetitions on hydrologic model performance and parameter uncertainty in varying climatic conditions. The study is performed in a pristine alpine catchment in the Western Tatra Mountains (the Jalovecký Creek catchment, Slovakia) using daily data from the period 1989–2018. The entire data set has been divided into five 6-years long periods; the division was based on the wavelet analysis of precipitation, air temperature and runoff data. A lumped conceptual hydrologic model TUW (“Technische Universität Wien”) was c

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Schepen, Andrew, Yvette Everingham, and Quan J. Wang. "On the Joint Calibration of Multivariate Seasonal Climate Forecasts from GCMs." Monthly Weather Review 148, no. 1 (2020): 437–56. http://dx.doi.org/10.1175/mwr-d-19-0046.1.

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Abstract Multivariate seasonal climate forecasts are increasingly required for quantitative modeling in support of natural resources management and agriculture. GCM forecasts typically require postprocessing to reduce biases and improve reliability; however, current seasonal postprocessing methods often ignore multivariate dependence. In low-dimensional settings, fully parametric methods may sufficiently model intervariable covariance. On the other hand, empirical ensemble reordering techniques can inject desired multivariate dependence in ensembles from template data after univariate postproc

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Cakir, Roxelane, Mélanie Raimonet, Sabine Sauvage, et al. "Hydrological Alteration Index as an Indicator of the Calibration Complexity of Water Quantity and Quality Modeling in the Context of Global Change." Water 12, no. 1 (2019): 115. http://dx.doi.org/10.3390/w12010115.

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Modeling is a useful way to understand human and climate change impacts on the water resources of agricultural watersheds. Calibration and validation methodologies are crucial in forecasting assessments. This study explores the best calibration methodology depending on the level of hydrological alteration due to human-derived stressors. The Soil and Water Assessment Tool (SWAT) model is used to evaluate hydrology in South-West Europe in a context of intensive agriculture and water scarcity. The Index of Hydrological Alteration (IHA) is calculated using discharge observation data. A comparison

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Boulard, T., B. Draoui, and F. Neirac. "CALIBRATION AND VALIDATION OF A GREENHOUSE CLIMATE CONTROL MODEL." Acta Horticulturae, no. 406 (April 1996): 49–62. http://dx.doi.org/10.17660/actahortic.1996.406.4.

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Guzmán-Cruz, R., R. Castañeda-Miranda, J. J. García-Escalante, I. L. López-Cruz, A. Lara-Herrera, and J. I. de la Rosa. "Calibration of a greenhouse climate model using evolutionary algorithms." Biosystems Engineering 104, no. 1 (2009): 135–42. http://dx.doi.org/10.1016/j.biosystemseng.2009.06.006.

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18

Harp, D. R., A. L. Atchley, S. L. Painter, et al. "Effect of soil property uncertainties on permafrost thaw projections: a calibration-constrained analysis." Cryosphere Discussions 9, no. 3 (2015): 3351–404. http://dx.doi.org/10.5194/tcd-9-3351-2015.

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Abstract. The effect of soil property uncertainties on permafrost thaw projections are studied using a three-phase subsurface thermal hydrology model and calibration-constrained uncertainty analysis. The Null-Space Monte Carlo method is used to identify soil hydrothermal parameter combinations that are consistent with borehole temperature measurements at the study site, the Barrow Environmental Observatory. Each parameter combination is then used in a forward projection of permafrost conditions for the 21st century (from calendar year 2006 to 2100) using atmospheric forcings from the Community

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19

Jajarmizadeh, Milad, Lariyah Mohd Sidek, Sobri Harun, and Mohsen Salarpour. "Optimal Calibration and Uncertainty Analysis of SWAT for an Arid Climate." Air, Soil and Water Research 10 (January 1, 2017): 117862211773179. http://dx.doi.org/10.1177/1178622117731792.

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One of the major issues for semidistributed models is calibration of sensitive parameters. This study compared 3 scenarios for Soil and Water Assessment Tool (SWAT) model for calibration and uncertainty. Roodan watershed has been selected for simulation of daily flow in southern part of Iran with an area of 10 570 km2. After preparation of required data and implementation of the SWAT model, sensitivity analysis has been performed by Latin Hypercube One-factor-At-a-Time method on those parameters which are effective for flow simulation. Then, SWAT Calibration and Uncertainty Program (SWAT-CUP)

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20

Mendoza, Pablo A., Martyn P. Clark, Naoki Mizukami, et al. "Effects of Hydrologic Model Choice and Calibration on the Portrayal of Climate Change Impacts." Journal of Hydrometeorology 16, no. 2 (2015): 762–80. http://dx.doi.org/10.1175/jhm-d-14-0104.1.

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Abstract The assessment of climate change impacts on water resources involves several methodological decisions, including choices of global climate models (GCMs), emission scenarios, downscaling techniques, and hydrologic modeling approaches. Among these, hydrologic model structure selection and parameter calibration are particularly relevant and usually have a strong subjective component. The goal of this research is to improve understanding of the role of these decisions on the assessment of the effects of climate change on hydrologic processes. The study is conducted in three basins located

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21

Chang, Kai‐Lan, and Serge Guillas. "Computer model calibration with large non‐stationary spatial outputs: application to the calibration of a climate model." Journal of the Royal Statistical Society: Series C (Applied Statistics) 68, no. 1 (2018): 51–78. http://dx.doi.org/10.1111/rssc.12309.

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22

Melsen, Lieke Anna, and Björn Guse. "Climate change impacts model parameter sensitivity – implications for calibration strategy and model diagnostic evaluation." Hydrology and Earth System Sciences 25, no. 3 (2021): 1307–32. http://dx.doi.org/10.5194/hess-25-1307-2021.

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Abstract. Hydrological models are useful tools for exploring the impact of climate change. To prioritize parameters for calibration and to evaluate hydrological model functioning, sensitivity analysis can be conducted. Parameter sensitivity, however, varies over climate, and therefore climate change could influence parameter sensitivity. In this study we explore the change in parameter sensitivity for the mean discharge and the timing of the discharge, within a plausible climate change rate. We investigate whether changes in sensitivity propagate into the calibration strategy and diagnosticall

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Wi, S., Y. C. E. Yang, S. Steinschneider, A. Khalil, and C. M. Brown. "Calibration approaches for distributed hydrologic models using high performance computing: implication for streamflow projections under climate change." Hydrology and Earth System Sciences Discussions 11, no. 9 (2014): 10273–317. http://dx.doi.org/10.5194/hessd-11-10273-2014.

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Abstract. This study utilizes high performance computing to test the performance and uncertainty of calibration strategies for a spatially distributed hydrologic model in order to improve model simulation accuracy and understand prediction uncertainty at interior ungaged sites of a sparsely-gaged watershed. The study is conducted using a distributed version of the HYMOD hydrologic model (HYMOD_DS) applied to the Kabul River basin. Several calibration experiments are conducted to understand the benefits and costs associated with different calibration choices, including (1) whether multisite gag

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Khaki, Mehdi. "Land Surface Model Calibration Using Satellite Remote Sensing Data." Sensors 23, no. 4 (2023): 1848. http://dx.doi.org/10.3390/s23041848.

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Satellite remote sensing provides a unique opportunity for calibrating land surface models due to their direct measurements of various hydrological variables as well as extensive spatial and temporal coverage. This study aims to apply terrestrial water storage (TWS) estimated from the gravity recovery and climate experiment (GRACE) mission as well as soil moisture products from advanced microwave scanning radiometer–earth observing system (AMSR-E) to calibrate a land surface model using multi-objective evolutionary algorithms. For this purpose, the non-dominated sorting genetic algorithm (NSGA

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Huang, Shaochun, Harsh Shah, Bibi S. Naz, et al. "Impacts of hydrological model calibration on projected hydrological changes under climate change—a multi-model assessment in three large river basins." Climatic Change 163, no. 3 (2020): 1143–64. http://dx.doi.org/10.1007/s10584-020-02872-6.

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AbstractThis study aimed to investigate the influence of hydrological model calibration/validation on discharge projections for three large river basins (the Rhine, Upper Mississippi and Upper Yellow). Three hydrological models (HMs), which have been firstly calibrated against the monthly discharge at the outlet of each basin (simple calibration), were re-calibrated against the daily discharge at the outlet and intermediate gauges under contrast climate conditions simultaneously (enhanced calibration). In addition, the models were validated in terms of hydrological indicators of interest (medi

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Zeng, Qiang, Hua Chen, Chong-Yu Xu, Meng-Xuan Jie, and Yu-Kun Hou. "Feasibility and uncertainty of using conceptual rainfall-runoff models in design flood estimation." Hydrology Research 47, no. 4 (2015): 701–17. http://dx.doi.org/10.2166/nh.2015.069.

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Hydrological models are developed for different purposes including flood forecasting, design flood estimation, water resources assessment, and impact study of climate change and land use change, etc. In this study, applicability and uncertainty of two deterministic lumped models, the Xinanjiang (XAJ) model and the Hydrologiska Byråns Vattenbalansavdelning (HBV) model, in design flood estimation are evaluated in a data rich catchment in southern China. Uncertainties of the estimated design flood caused by model equifinality and calibration data period are then assessed using the generalized lik

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Yang, Qichun, Quan J. Wang, Andrew W. Western, Wenyan Wu, Yawen Shao, and Kirsti Hakala. "Reconstructing climate trends adds skills to seasonal reference crop evapotranspiration forecasting." Hydrology and Earth System Sciences 26, no. 4 (2022): 941–54. http://dx.doi.org/10.5194/hess-26-941-2022.

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Abstract. Evapotranspiration plays an important role in the terrestrial water cycle. Reference crop evapotranspiration (ETo) has been widely used to estimate water transfer from vegetation surface to the atmosphere. Seasonal ETo forecasting provides valuable information for effective water resource management and planning. Climate forecasts from general circulation models (GCMs) have been increasingly used to produce seasonal ETo forecasts. Statistical calibration plays a critical role in correcting bias and dispersion errors in GCM-based ETo forecasts. However, time-dependent errors resulting

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Bellprat, O., S. Kotlarski, D. Lüthi, and C. Schär. "Objective calibration of regional climate models." Journal of Geophysical Research: Atmospheres 117, no. D23 (2012): n/a. http://dx.doi.org/10.1029/2012jd018262.

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Coopersmith, E. J., B. S. Minsker, and M. Sivapalan. "Using similarity of soil texture and hydroclimate to enhance soil moisture estimation." Hydrology and Earth System Sciences 18, no. 8 (2014): 3095–107. http://dx.doi.org/10.5194/hess-18-3095-2014.

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Abstract. Estimating soil moisture typically involves calibrating models to sparse networks of in situ sensors, which introduces considerable error in locations where sensors are not available. We address this issue by calibrating parameters of a parsimonious soil moisture model, which requires only antecedent precipitation information, at gauged locations and then extrapolating these values to ungauged locations via a hydroclimatic classification system. Fifteen sites within the Soil Climate Analysis Network (SCAN) containing multiyear time series data for precipitation and soil moisture are

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Coopersmith, E. J., B. S. Minsker, and M. Sivapalan. "Using hydro-climatic and edaphic similarity to enhance soil moisture prediction." Hydrology and Earth System Sciences Discussions 11, no. 2 (2014): 2321–53. http://dx.doi.org/10.5194/hessd-11-2321-2014.

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Abstract. Estimating soil moisture typically involves calibrating models to sparse networks of in~situ sensors, which introduces considerable error in locations where sensors are not available. We address this issue by calibrating parameters of a parsimonious soil moisture model, which requires only antecedent precipitation information, at gauged locations and then extrapolating these values to ungauged locations via a hydro-climatic classification system. Fifteen sites within the soil climate analysis network (SCAN) containing multi-year time series data for precipitation and soil moisture ar

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Wi, S., Y. C. E. Yang, S. Steinschneider, A. Khalil, and C. M. Brown. "Calibration approaches for distributed hydrologic models in poorly gaged basins: implication for streamflow projections under climate change." Hydrology and Earth System Sciences 19, no. 2 (2015): 857–76. http://dx.doi.org/10.5194/hess-19-857-2015.

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Abstract. This study tests the performance and uncertainty of calibration strategies for a spatially distributed hydrologic model in order to improve model simulation accuracy and understand prediction uncertainty at interior ungaged sites of a sparsely gaged watershed. The study is conducted using a distributed version of the HYMOD hydrologic model (HYMOD_DS) applied to the Kabul River basin. Several calibration experiments are conducted to understand the benefits and costs associated with different calibration choices, including (1) whether multisite gaged data should be used simultaneously

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32

Erlandsen, Helene Birkelund, Kajsa M. Parding, Rasmus Benestad, Abdelkader Mezghani, and Marie Pontoppidan. "A Hybrid Downscaling Approach for Future Temperature and Precipitation Change." Journal of Applied Meteorology and Climatology 59, no. 11 (2020): 1793–807. http://dx.doi.org/10.1175/jamc-d-20-0013.1.

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AbstractWe used empirical–statistical downscaling in a pseudoreality context, in which both large-scale predictors and small-scale predictands were based on climate model results. The large-scale conditions were taken from a global climate model, and the small-scale conditions were taken from dynamical downscaling of the same global model with a convection-permitting regional climate model covering southern Norway. This hybrid downscaling approach, a “perfect model”–type experiment, provided 120 years of data under the CMIP5 high-emission scenario. Ample calibration samples made rigorous testi

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Yan, Bing, Yicheng Gu, En Li, Yi Xu, and Lingling Ni. "Runoff Prediction of Tunxi Basin under Projected Climate Changes Based on Lumped Hydrological Models with Various Model Parameter Optimization Strategies." Sustainability 16, no. 16 (2024): 6897. http://dx.doi.org/10.3390/su16166897.

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Runoff is greatly influenced by changes in climate conditions. Predicting runoff and analyzing its variations under future climates are crucial for ensuring water security, managing water resources effectively, and promoting sustainable development within the catchment area. As the key step in runoff modeling, the calibration of hydrological model parameters plays an important role in models’ performance. Identifying an efficient and reliable optimization algorithm and objective function continues to be a significant challenge in applying hydrological models. This study selected new algorithms

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Ba, Doudou, Jakub Langhammer, Petr Maca, and Ansoumana Bodian. "Testing sensitivity of BILAN and GR2M models to climate conditions in the Gambia River Basin." Journal of Hydrology and Hydromechanics 72, no. 1 (2024): 131–47. http://dx.doi.org/10.2478/johh-2023-0044.

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Abstract This study investigates the performance of two lumped hydrological models, BILAN and GR2M, in simulating runoff across six catchments in the Gambia River Basin (Senegal) over a 30-year period employing a 7-year sliding window under different climatic conditions. The results revealed differences in overall performance and variable sensitivity of the models to hydrological conditions and calibration period lengths, stemming from their different structure and complexity. In particular, the BILAN model, which is based on a more complex set of parameters, showed better overall results in s

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Ascanio-Villabona, Javier, N. Y. Castillo-Leon, Nicolas Orejarena Osorio, Brayan Eduardo Tarazona-Romero, and K. T. Jaimes-Quintero. "Simulation of the energy model of a rural house located in a cold climate using an in-situ monitoring system." Periodicals of Engineering and Natural Sciences (PEN) 12, no. 3 (2024): 595–603. https://doi.org/10.21533/pen.v12.i3.59.

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The energy simulation of buildings is presented as a tool to analyze the comfort, consumption and energy efficiency of buildings, however, the discrepancy between simulated models and real data has been a constant, for this reason, energy model calibrations are performed to increase the reliability of the predictions of the simulation. This research carried out the simulation and calibration of the energy model of a rural house, located in a cold climate at more than 3000 meters above sea level, the study was developed in three phases, starting with the monitoring of climatological variables,

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Felikson, Denis, Sophie Nowicki, Isabel Nias, et al. "Choice of observation type affects Bayesian calibration of Greenland Ice Sheet model simulations." Cryosphere 17, no. 11 (2023): 4661–73. http://dx.doi.org/10.5194/tc-17-4661-2023.

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Abstract. Determining reliable probability distributions for ice sheet mass change over the coming century is critical to refining uncertainties in sea-level rise projections. Bayesian calibration, a method for constraining projection uncertainty using observations, has been previously applied to ice sheet projections but the impact of the chosen observation type on the calibrated posterior probability distributions has not been quantified. Here, we perform three separate Bayesian calibrations to constrain uncertainty in Greenland Ice Sheet (GrIS) simulations of the committed mass loss in 2100

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Ismail, Muhammad Fraz, Bibi S. Naz, Michel Wortmann, Markus Disse, Laura C. Bowling, and Wolfgang Bogacki. "Comparison of two model calibration approaches and their influence on future projections under climate change in the Upper Indus Basin." Climatic Change 163, no. 3 (2020): 1227–46. http://dx.doi.org/10.1007/s10584-020-02902-3.

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AbstractThis study performs a comparison of two model calibration/validation approaches and their influence on future hydrological projections under climate change by employing two climate scenarios (RCP2.6 and 8.5) projected by four global climate models. Two hydrological models (HMs), snowmelt runoff model + glaciers and variable infiltration capacity model coupled with a glacier model, were used to simulate streamflow in the highly snow and glacier melt–driven Upper Indus Basin. In the first (conventional) calibration approach, the models were calibrated only at the basin outlet, while in t

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Bolin, David, Arnoldo Frigessi, Peter Guttorp, et al. "Calibrating regionally downscaled precipitation over Norway through quantile-based approaches." Advances in Statistical Climatology, Meteorology and Oceanography 2, no. 1 (2016): 39–47. http://dx.doi.org/10.5194/ascmo-2-39-2016.

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Abstract. Dynamical downscaling of earth system models is intended to produce high-resolution climate information at regional to local scales. Current models, while adequate for describing temperature distributions at relatively small scales, struggle when it comes to describing precipitation distributions. In order to better match the distribution of observed precipitation over Norway, we consider approaches to statistical adjustment of the output from a regional climate model when forced with ERA-40 reanalysis boundary conditions. As a second step, we try to correct downscalings of historica

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Zhang, Xujie, Martijn J. Booij, and Yue-Ping Xu. "Improved Simulation of Peak Flows under Climate Change: Postprocessing or Composite Objective Calibration?" Journal of Hydrometeorology 16, no. 5 (2015): 2187–208. http://dx.doi.org/10.1175/jhm-d-14-0218.1.

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Abstract Climate change is expected to have large impacts on peak flows. However, there may be bias in the simulation of peak flows by hydrological models. This study aims to improve the simulation of peak flows under climate change in Lanjiang catchment, east China, by comparing two approaches: postprocessing of peak flows and composite objective calibration. Two hydrological models [Soil and Water Assessment Tool (SWAT) and modèle du Génie Rural à 4 paramètres Journalier (GR4J)] are employed to simulate the daily flows, and the peaks-over-threshold method is used to extract peak flows from t

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Bhattarai, Shreeya, Prem B. Parajuli, and Filip To. "Comparison of Flood Frequency at Different Climatic Scenarios in Forested Coastal Watersheds." Climate 11, no. 2 (2023): 41. http://dx.doi.org/10.3390/cli11020041.

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Climate change-induced extreme precipitation causes coastal flooding. A streamflow simulation in coastal watersheds, Wolf River Watershed (WRW) and Jourdan River Watershed (JRW), was conducted using the Soil and Water Assessment Tool (SWAT) to compare variation in flow at different climates and to analyze the flood frequency. Baseline models were auto-calibrated with SWAT calibration and uncertainty programs (SWAT-CUP). Kling–Gupta efficiency (KGE), defined as the objective function in SWAT-CUP, ranged from 0.8 to 0.7 in WRW and from 0.55 to 0.68 in JRW during the calibration–validation proces

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Sandstad, Marit, Borgar Aamaas, Ane Nordlie Johansen, et al. "CICERO Simple Climate Model (CICERO-SCM v1.1.1) – an improved simple climate model with a parameter calibration tool." Geoscientific Model Development 17, no. 17 (2024): 6589–625. http://dx.doi.org/10.5194/gmd-17-6589-2024.

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Abstract. The CICERO Simple Climate Model (CICERO-SCM) is a lightweight, semi-empirical model of global climate. Here we present a new open-source Python port of the model for use in climate assessment and research. The new version of CICERO-SCM has the same scientific logic and functionality as the original Fortran version, but it is considerably more flexible and also open-source via GitHub. We describe the basic structure and improvements compared to the previous Fortran version, together with technical descriptions of the global thermal dynamics and carbon cycle components and the emission

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Majone, Bruno, Diego Avesani, Patrick Zulian, Aldo Fiori, and Alberto Bellin. "Analysis of high streamflow extremes in climate change studies: how do we calibrate hydrological models?" Hydrology and Earth System Sciences 26, no. 14 (2022): 3863–83. http://dx.doi.org/10.5194/hess-26-3863-2022.

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Abstract. Climate change impact studies on hydrological extremes often rely on hydrological models with parameters inferred through calibration procedures using observed meteorological data as input forcing. We show that this procedure can lead to a biased evaluation of the probability distribution of high streamflow extremes when climate models are used. As an alternative approach, we introduce a methodology, coined “Hydrological Calibration of eXtremes” (HyCoX), in which the calibration of the hydrological model, as driven by climate model output, is carried out by maximizing the probability

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Todorovic, Andrijana, and Jasna Plavsic. "The role of conceptual hydrologic model calibration in climate change impact on water resources assessment." Journal of Water and Climate Change 7, no. 1 (2015): 16–28. http://dx.doi.org/10.2166/wcc.2015.086.

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Assessment of climate change (CC) impact on hydrologic regime requires a calibrated rainfall-runoff model, defined by its structure and parameters. The parameter values depend, inter alia, on the calibration period. This paper investigates influence of the calibration period on parameter values, model efficiency and streamflow projections under CC. To this end, a conceptual HBV-light model of the Kolubara River catchment in Serbia is calibrated against flows observed within 5 consecutive wettest, driest, warmest and coldest years and in the complete record period. The optimised parameters reve

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Hundecha, Yeshewatesfa, Berit Arheimer, Peter Berg, et al. "Effect of model calibration strategy on climate projections of hydrological indicators at a continental scale." Climatic Change 163, no. 3 (2020): 1287–306. http://dx.doi.org/10.1007/s10584-020-02874-4.

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AbstractThe effect of model calibration on the projection of climate change impact on hydrological indicators was assessed by employing variants of a pan-European hydrological model driven by forcing data from an ensemble of climate models. The hydrological model was calibrated using three approaches: calibration at the outlets of major river basins, regionalization through calibration of smaller scale catchments with unique catchment characteristics, and building a model ensemble by sampling model parameters from the regionalized model. The large-scale patterns of the change signals projected

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Heaven, S., A. M. Salter, and D. Clarke. "Calibration of a simple model for waste stabilisation pond performance in seasonal climates." Water Science and Technology 64, no. 7 (2011): 1488–96. http://dx.doi.org/10.2166/wst.2011.550.

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The paper describes the calibration of a model for waste stabilisation pond (WSP) performance in seasonal climates, based on the use of readily available climate data sets. Calibration data were taken from a wide geographical area of Canada and the USA, including coastal and moderately seasonal sites. Good agreement with measured values was shown using a biochemical oxygen demand (BOD) decay constant of 0.3 day−1 for facultative ponds and 0.07–0.1 day−1 for storage/maturation ponds with a temperature-related Arrhenius constant of 1.05, and a fixed BOD decay constant of 0.007 day−1 at water tem

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Harp, D. R., A. L. Atchley, S. L. Painter, et al. "Effect of soil property uncertainties on permafrost thaw projections: a calibration-constrained analysis." Cryosphere 10, no. 1 (2016): 341–58. http://dx.doi.org/10.5194/tc-10-341-2016.

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Abstract. The effects of soil property uncertainties on permafrost thaw projections are studied using a three-phase subsurface thermal hydrology model and calibration-constrained uncertainty analysis. The null-space Monte Carlo method is used to identify soil hydrothermal parameter combinations that are consistent with borehole temperature measurements at the study site, the Barrow Environmental Observatory. Each parameter combination is then used in a forward projection of permafrost conditions for the 21st century (from calendar year 2006 to 2100) using atmospheric forcings from the Communit

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Chung, S. W., and J. K. Oh. "Calibration of CE-QUAL-W2 for a monomictic reservoir in a monsoon climate area." Water Science and Technology 54, no. 11-12 (2006): 29–37. http://dx.doi.org/10.2166/wst.2006.841.

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The impact of inflow mixing on reservoir stratification is significant for reservoirs situated in a monsoon climate area. It cause difficulty in the calibration of a two-dimensional hydrodynamic and water quality model, CE-QUAL-W2 that was recently adopted for a real-time turbidity monitoring and modelling system (RTMMS) for a reservoir in Korea. This paper presents a systematic calibration and verification processe of the model for the reservoir. A sensitivity analysis showed that wind sheltering, Chezy, and sediment heat exchange coefficients are most sensitive to stratification structure. I

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Giesen, R. H., and J. Oerlemans. "Calibration of a surface mass balance model for global-scale applications." Cryosphere 6, no. 6 (2012): 1463–81. http://dx.doi.org/10.5194/tc-6-1463-2012.

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Abstract. Global applications of surface mass balance models have large uncertainties, as a result of poor climate input data and limited availability of mass balance measurements. This study addresses several possible consequences of these limitations for the modelled mass balance. This is done by applying a simple surface mass balance model that only requires air temperature and precipitation as input data, to glaciers in different regions. In contrast to other models used in global applications, this model separately calculates the contributions of net solar radiation and the temperature-de

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Voudouri, Antigoni, Euripides Avgoustoglou, Izthak Carmona, et al. "Objective Calibration of Numerical Weather Prediction Model: Application on Fine Resolution COSMO Model over Switzerland." Atmosphere 12, no. 10 (2021): 1358. http://dx.doi.org/10.3390/atmos12101358.

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The objective calibration method originally performed on regional climate models is applied to a fine horizontal resolution Numerical Weather Prediction (NWP) model over a mainly continental domain covering the Alpine Arc. The method was implemented on the MeteoSwiss COSMO (consortium for a small-scale modeling) model with a resolution of 0.01° (approximately 1 km). For the model calibration, five tuning parameters of the parameterization schemes affecting turbulence, soil-surface exchange and radiation were chosen. A full year was simulated, with the history of the soil included (hindcast) to

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Peatier, Saloua, Benjamin M. Sanderson, and Laurent Terray. "Exploration of diverse solutions for the calibration of imperfect climate models." Earth System Dynamics 15, no. 4 (2024): 987–1014. http://dx.doi.org/10.5194/esd-15-987-2024.

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Abstract. The calibration of Earth system model parameters is subject to data, time, and computational constraints. The high dimensionality of this calibration problem, combined with errors arising from model structural assumptions, makes it impossible to find model versions fully consistent with historical observations. Therefore, the potential for multiple plausible configurations presenting different trade-offs between skills in various variables and spatial regions remains usually untested. In this study, we lay out a formalism for making different assumptions about how ensemble variabilit

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