scholarly journals Exploring an Alternative Configuration of the Hydroclimatic Modeling Chain, Based on the Notion of Asynchronous Objective Functions

Water ◽  
2019 ◽  
Vol 11 (10) ◽  
pp. 2012 ◽  
Author(s):  
Simon Ricard ◽  
Jean-Daniel Sylvain ◽  
François Anctil
Keyword(s):  
Climate Model ◽  
Regional Climate ◽  
Hydrologic Model ◽  
Climate Variables ◽  
Objective Functions ◽  
Sequence Of Events ◽  
Simulated Climate ◽  
The Common ◽  
Meteorological Observations ◽  
Alternative Configuration

This study explores an alternative configuration of the hydroclimatic modeling chain around the notion of asynchronous objective-function (AOF). AOFs are calibration criteria purposely ignoring the correlation between observed and simulated variables. Within the suggested alternative configuration, the hydrologic model is being forced and calibrated with bias corrected climate variables over the reference period instead of historical meteorological observations. Consequently, the alternative configuration circumvent the redundant usage of climate observation operated within conventional configurations for statistical post-processing of simulated climate variables and calibration of the hydrologic model. AOFs optimize statistical properties of hydroclimatic projections, preserving the sequence of events imbedded within the forcing climate model. Both conventional and alternative configurations of the hydroclimatic modeling chain are implemented over a mid-size nivo-pluvial catchment located in the Saint-Lawrence Valley, Canada. The WaSiM-ETH hydrological model is forced with a bias-corrected member of the Canadian Regional Climate Model Large Ensemble (CRCM5-LE). Five AOFs are designed and compared to the common Kling-Gupta efficiency (KGE) metric. Forced with observations, AOFs tend to provide a hydrologic response comparable to KGE during the nival season and moderately degraded during the pluvial season. Using AOFs, the alternative configuration of the hydroclimatic modeling chain provides more coherent hydrologic projections relative to a conventional configuration.

scholarly journals Producing hydrologic scenarios from raw climate model outputs using an asynchronous modelling framework

2021 ◽  
Author(s):  
Simon Ricard ◽  
Philippe Lucas-Picher ◽  
François Anctil
Keyword(s):  
Climate Change ◽  
Climate Model ◽  
Water Discharge ◽  
Climate Change Impacts ◽  
Climate Variables ◽  
Post Processing ◽  
Hydrologic Models ◽  
Simulated Climate ◽  
Meteorological Observations ◽  
The Impact

Abstract. Statistical post-processing of climate model outputs is a common hydroclimatic modelling practice aiming to produce climate scenarios that better fit in-situ observations and to produce reliable stream flows forcing calibrated hydrologic models. Such practice is however criticized for disrupting the physical consistency between simulated climate variables and affecting the trends in climate change signals imbedded within raw climate simulations. It also requires abundant good-quality meteorological observations, which are not available for many regions in the world. A simplified hydroclimatic modelling workflow is proposed to quantify the impact of climate change on water discharge without resorting to meteorological observations, nor for statistical post-processing of climate model outputs, nor for calibrating hydrologic models. By combining asynchronous hydroclimatic modelling, an alternative framework designed to construct hydrologic scenarios without resorting to meteorological observations, and quantile perturbation applied to streamflow observations, the proposed workflow produces sound and plausible hydrologic scenarios considering: (1) they preserve trends and physical consistency between simulated climate variables, (2) are implemented from a modelling cascades despite observation scarcity, and (3) support the participation of end-users in producing and interpreting climate change impacts on water resources. The proposed modelling workflow is implemented over four subcatchments of the Chaudière River, Canada, using 9 North American CORDEX simulations and a pool of lumped conceptual hydrologic models. Forced with raw climate model outputs, hydrologic models are calibrated over the reference period according to a calibration metric designed to function with temporally uncorrelated observed and simulated streamflow values. Perturbation factors are defined by relating each simulated streamflow quantiles over both reference and future periods. Hydrologic scenarios are finally produced by applying perturbation factors to available streamflow observations.

scholarly journals Possible Increase of Vegetation Exposure to Spring Frost under Climate Change in Switzerland

Atmosphere ◽  
2020 ◽  
Vol 11 (4) ◽  
pp. 391 ◽  
Author(s):  
Ondřej Lhotka ◽  
Stefan Brönnimann
Keyword(s):  
Climate Model ◽  
Regional Climate ◽  
Data Set ◽  
Spring Frost ◽  
Frost Risk ◽  
Historical Climate ◽  
Rcp 8.5 ◽  
Swiss Plateau ◽  
Meteorological Observations ◽  
Near Future

We assessed future changes in spring frost risk for the Aare river catchment that comprises the Swiss Plateau, the most important agricultural region of Switzerland. An ensemble of 15 bias-corrected regional climate model (RCM) simulations from the EXAR data set forced by the RCP 4.5 and RCP 8.5 concentration pathways were analysed for two future periods. Correlating actual meteorological observations and Swiss phenological spring index, we proposed and tested an RCM-compatible methodology (based on temperature data only) for estimating a start of spring and severity of frost events. In the historical climate, a significant advancement in start of spring was observed and frost events were more frequent in those years in which spring started sooner. In 2021–2050, spring is projected to start eight (twelve) days earlier, considering the RCP 4.5 (8.5) scenario. Substantial changes were simulated for the 2070–2099 period under RCP 8.5, when the total severity of frost events was projected to be increased by a factor of 2.1 compared to the historical climate. The study revealed the possible future increase of vegetation exposure to spring frost in Switzerland and that this phenomenon is noticeable even in the near future under the ‘low concentration’ RCP 4.5 scenario.

scholarly journals A pragmatic approach for the downscaling and bias correction of regional climate simulations – evaluation in hydrological modeling

2011 ◽  
Vol 4 (1) ◽  
pp. 45-63 ◽  
Author(s):  
T. Marke ◽  
W. Mauser ◽  
A. Pfeiffer ◽  
G. Zängl
Keyword(s):  
Hydrological Modeling ◽  
Hydrological Model ◽  
Climate Model ◽  
Regional Climate ◽  
Model Performance ◽  
Reanalysis Data ◽  
Historical Period ◽  
Climate Simulations ◽  
Meteorological Observations ◽  
Climate Model Simulations

Abstract. The present study investigates a statistical approach for the downscaling of climate simulations focusing on those meteorological parameters most commonly required as input for climate change impact models (temperature, precipitation, air humidity and wind speed), including the option to correct biases in the climate model simulations. The approach is evaluated by the utilization of a hydrometeorological model chain consisting of (i) the regional climate model MM5 (driven by reanalysis data at the boundaries of the model domain), (ii) the downscaling and model interface SCALMET, and (iii) the hydrological model PROMET. The results of four hydrological model runs are compared to discharge recordings at the gauge of the Upper Danube Watershed (Central Europe) for the historical period of 1972–2000 on a daily time basis. The comparison reveals that the presented approaches allow for a more accurate simulation of discharge for the catchment of the Upper Danube Watershed and the considered gauge at the outlet in Achleiten. The correction for subgrid-scale variability is shown to reduce biases in simulated discharge compared to the utilization of bilinear interpolation. Further enhancements in model performance could be achieved by a correction of biases in the RCM data within the downscaling process. Although the presented downscaling approach strongly improves the performance of the hydrological model, deviations from the observed discharge conditions persist that are not found when driving the hydrological model with spatially distributed meteorological observations.

The coupling of the Common Land Model (CLM0) to a regional climate model (RegCM)

2005 ◽  
Vol 82 (3-4) ◽  
pp. 225-243 ◽  
Author(s):  
A. L. Steiner ◽  
J. S. Pal ◽  
F. Giorgi ◽  
R. E. Dickinson ◽  
W. L. Chameides
Keyword(s):  
Regional Climate Model ◽  
Climate Model ◽  
Regional Climate ◽  
Common Land Model ◽  
The Common

scholarly journals Spatial Interpolation of Daily Precipitation in a High Mountainous Watershed Based on Gauge Observations and a Regional Climate Model Simulation

2017 ◽  
Vol 18 (3) ◽  
pp. 845-862 ◽  
Author(s):  
Yuhan Wang ◽  
Hanbo Yang ◽  
Dawen Yang ◽  
Yue Qin ◽  
Bing Gao ◽  
...  
Keyword(s):  
Spatial Distribution ◽  
Regional Climate Model ◽  
Spatial Interpolation ◽  
Climate Model ◽  
Daily Precipitation ◽  
Regional Climate ◽  
Heihe River ◽  
Topographic Effects ◽  
Precipitation Data ◽  
Meteorological Observations

Abstract Precipitation is a primary climate forcing factor in catchment hydrology, and its spatial distribution is essential for understanding the spatial variability of ecohydrological processes in a catchment. In mountainous areas, meteorological stations are generally too sparse to represent the spatial distribution of precipitation. This study develops a spatial interpolation method that combines meteorological observations and regional climate model (RCM) outputs. The method considers the precipitation–elevation relationship in the mountain region and the topographic effects, especially the mountain blocking effect. Furthermore, using this method, this study produced a 3-km-resolution precipitation dataset from 1960 to 2014 in the middle and upper reaches of the Heihe River basin located on the northern slope of the Qilian Mountains in the northeastern Tibetan Plateau. Cross validation based on the station observations showed that this method is reasonable. The rationality of the interpolated precipitation data was also evaluated by the catchment water balances using the observed river discharge and the actual evapotranspiration based on remote sensing. The interpolated precipitation data were compared with the China Gauge-Based Daily Precipitation Analysis product and the RCM output and was shown to be optimal. The results showed that the proposed method effectively used the information from the meteorological observations and the RCM simulations and provided the spatial distributions of daily precipitations with reasonable accuracy and high resolution, which is important for a distributed hydrological simulation at the catchment scale.

scholarly journals Reducing Forecast Errors of a Regional Climate Model Using Adaptive Filters

2021 ◽  
Vol 11 (17) ◽  
pp. 8001
Author(s):  
Michel Pompeu Tcheou ◽  
Lisandro Lovisolo ◽  
Alexandre Ribeiro Freitas ◽  
Sin Chan Chou
Keyword(s):  
Regional Climate Model ◽  
Adaptive Filters ◽  
Climate Model ◽  
Learning Algorithm ◽  
Regional Climate ◽  
Absolute Error ◽  
Recursive Least Squares ◽  
Forecast Errors ◽  
Climate Variables ◽  
Seasonal Forecasts

In this work, the use of adaptive filters for reducing forecast errors produced by a Regional Climate Model (RCM) is investigated. Seasonal forecasts are compared against the reanalysis data provided by the National Centers for Environmental Prediction. The reanalysis is used to train adaptive filters based on the Recursive Least Squares algorithm in order to reduce the forecast error. The K-means unsupervised learning algorithm is used to obtain the number of filters to employ from the climate variables. The proposed approach is applied to some climate variables such as the meridional wind, zonal wind, and the geopotential height. The forecast is produced by the Eta RCM at 40-km resolution in a domain covering most of Brazil. Results show that the proposed approach is capable of reducing the forecast errors, according to evaluation metrics such as normalized mean square error, maximum absolute error, and maximum normalized absolute error, thus improving the seasonal climate forecasts.

scholarly journals Dynamical Downscaling with Reinitializations: A Method to Generate Finescale Climate Datasets Suitable for Impact Studies

2013 ◽  
Vol 14 (4) ◽  
pp. 1159-1174 ◽  
Author(s):  
Philippe Lucas-Picher ◽  
Fredrik Boberg ◽  
Jens H. Christensen ◽  
Peter Berg
Keyword(s):  
Climate Model ◽  
Dynamical Downscaling ◽  
Regional Climate ◽  
Temporal Correlation ◽  
Systematic Errors ◽  
Added Value ◽  
Driving Field ◽  
Continuous Simulation ◽  
Impact Studies ◽  
Sequence Of Events

Abstract To retain the sequence of events of a regional climate model (RCM) simulation driven by a reanalysis, a method that has not been widely adopted uses an RCM with frequent reinitializations toward its driving field. In this regard, this study highlights the benefits of an RCM simulation with frequent (daily) reinitializations compared to a standard continuous RCM simulation. Both simulations are carried out with the RCM HIRHAM5, driven with the European Centre for Medium-Range Weather Forecasts (ECMWF) Interim Re-Analysis (ERA-Interim) data, over the 12-km-resolution European Coordinated Regional Climate Downscaling Experiment (CORDEX) domain covering the period 1989–2009. The analysis of daily precipitation shows improvements in the sequence of events and the maintenance of the added value from the standard continuous RCM simulation. The validation of the two RCM simulations with observations reveals that the simulation with reinitializations indeed improves the temporal correlation. Furthermore, the RCM simulation with reinitializations has lower systematic errors compared to the continuous simulation, which has a tendency to be too wet. A comparison of the distribution of wet day precipitation intensities shows similar added value in the continuous and reinitialized simulations with higher variability and extremes compared to the driving field ERA-Interim. Overall, the results suggest that the finescale climate dataset of the RCM simulation with reinitializations better suits the needs of impact studies by providing a sequence of events matching closely the observations, while limiting systematic errors and generating reliable added value. Downsides of the method with reinitializations are increased computational costs and the introduction of temporal discontinuities that are similar to those of a reanalysis.

scholarly journals Hydroclimatology of the Nile: results from a regional climate model

2005 ◽  
Vol 2 (1) ◽  
pp. 319-364 ◽  
Author(s):  
Y. A. Mohamed ◽  
B. J. J. M. van den Hurk ◽  
H. H. G. Savenije ◽  
W. G. M. Bastiaanssen
Keyword(s):  
Land Surface ◽  
Climate Model ◽  
Water Cycle ◽  
Regional Climate ◽  
Hydrologic Model ◽  
Surface Fluxes ◽  
Monthly Precipitation ◽  
Moisture Recycling ◽  
White Nile ◽  
Regional Water

Abstract. This paper is the result of the first regional coupled climatic and hydrologic model of the Nile. For the first time the interaction between the climatic processes and the hydrological processes on the land surface have been fully coupled. The hydrological model is driven by the rainfall and the energy available for evaporation generated in the climate model, and the runoff generated in the catchment is again routed over the wetlands of the Nile to supply moisture for atmospheric feedback. The results obtained are surprisingly accurate given the extremely low runoff coefficients in the catchment. The paper presents model results over the sub-basins: Blue Nile, White Nile, Atbara river and the Main Nile for the period 1995 to 2000, but focuses on the Sudd swamp. Limitations in both the observational data and the model are discussed. It is concluded that the model provides a sound representation of the regional water cycle over the Nile. The model is used to describe the regional water cycle in the Nile basin in terms of atmospheric fluxes, land surface fluxes and land surface-climate feedbacks. The monthly moisture recycling ratio (i.e. locally generated/total precipitation) over the Nile varies between 8 and 14%, with an annual mean of 11%, which implies that 89% of the Nile water resources originates from outside the basin physical boundaries. The monthly precipitation efficiency varies between 12 and 53%, and the annual mean is 28%. The mean annual result of the Nile regional water cycle is compared to that of the Amazon and the Mississippi basins.

scholarly journals Intercomparison of surface meltwater routing models for the Greenland ice sheet and influence on subglacial effective pressures

2020 ◽  
Vol 14 (10) ◽  
pp. 3349-3365
Author(s):  
Kang Yang ◽  
Aleah Sommers ◽  
Lauren C. Andrews ◽  
Laurence C. Smith ◽  
Xin Lu ◽  
...  
Keyword(s):  
Climate Model ◽  
Regional Climate ◽  
Ice Sheet ◽  
Greenland Ice Sheet ◽  
Hydrologic Model ◽  
Effective Pressure ◽  
Time To Peak ◽  
Hydrologic Systems ◽  
Hydrologic System ◽  
Routing Models

Abstract. Each summer, large volumes of surface meltwater drain off the Greenland ice sheet (GrIS) surface through moulins to the bed, impacting subglacial hydrology and ice flow dynamics. Supraglacial surface routing delays may propagate to englacial and subglacial hydrologic systems, requiring accurate assessment to correctly estimate subglacial effective pressures. We compare hourly supraglacial moulin discharge simulations from three surface meltwater routing models – the synthetic unit hydrograph (SUH), the bare-ice component of surface routing and lake filling (SRLF), and the rescaled width function (RWF) – for four internally drained catchments on the southwestern Greenland ice sheet surface. The routing models are forced identically using surface runoff from the Modèle Atmosphérique Régionale regional climate model (RCM). For each catchment, simulated moulin hydrographs are input to the SHAKTI subglacial hydrologic model to simulate diurnally varying subglacial effective-pressure variations in the vicinity of a single moulin. Overall, all three routing models produce more realistic moulin discharges than simply using RCM runoff outputs without surface routing but produce significant differences in peak moulin discharge and time to peak. In particular, the RWF yields later, smaller peak moulin discharges than the SUH or SRLF due to its representation of slow interfluve flow between supraglacial meltwater channels, and it can readily accommodate the seasonal evolution of supraglacial stream and river networks. Differences among the three routing models are reflected in a series of simple idealized subglacial hydrology simulations that yield different diurnal effective-pressure amplitudes; however, the supraglacial hydrologic system acts as short-term storage for surface meltwater, and the temporal mean effective pressure is relatively consistent across routing models.

Sign in / Sign up

Export Citation Format

Share Document