Parametrization of a lake water dynamics model MLake in the ISBA-CTRIP land surface system (SURFEX v8.1)

Abstract. Lakes are of fundamental importance in the Earth system as they support essential environmental and economic services, such as freshwater supply. Streamflow variability and temporal evolution are impacted by the presence of lakes in the river network; therefore, any change in the lake state can induce a modification of the regional hydrological regime. Despite the importance of the impact of lakes on hydrological fluxes and the water balance, a representation of the mass budget is generally not included in climate models and global-scale hydrological modeling platforms. The goal of this study is to introduce a new lake mass module, MLake (Mass-Lake model), into the river-routing model CTRIP to resolve the specific mass balance of open-water bodies. Based on the inherent CTRIP parameters, the development of the non-calibrated MLake model was introduced to examine the influence of such hydrological buffer areas on global-scale river-routing performance. In the current study, an offline evaluation was performed for four river networks using a set of state-of-the-art quality atmospheric forcings and a combination of in situ and satellite measurements for river discharge and lake level observations. The results reveal a general improvement in CTRIP-simulated discharge and its variability, while also generating realistic lake level variations. MLake produces more realistic streamflows both in terms of daily and seasonal correlation. Excluding the specific case of Lake Victoria having low performances, the mean skill score of Kling–Gupta efficiency (KGE) is 0.41 while the normalized information contribution (NIC) shows a mean improvement of 0.56 (ranging from 0.15 to 0.94). Streamflow results are spatially scale-dependent, with better scores associated with larger lakes and increased sensitivity to the width of the lake outlet. Regarding lake level variations, results indicate a good agreement between observations and simulations with a mean correlation of 0.56 (ranging from 0.07 to 0.92) which is linked to the capability of the model to retrieve seasonal variations. Discrepancies in the results are mainly explained by the anthropization of the selected lakes, which introduces high-frequency variations in both streamflows and lake levels that degraded the scores. Anthropization effects are prevalent in most of the lakes studied, but they are predominant for Lake Victoria and are the main cause for relatively low statistical scores for the Nile River However, results on the Angara and the Neva rivers also depend on the inherent gap of ISBA-CTRIP process representation, which relies on further development such as the partitioned energy budget between the snow and the canopy over a boreal zone. The study is a first step towards a global coupled land system that will help to qualitatively assess the evolution of future global water resources, leading to improvements in flood risk and drought forecasting.

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Parametrization of lakes water dynamics in the ISBA-CTRIP land surface system (SURFEX v8.1)

10.5194/gmd-2020-296 ◽

2020 ◽

Author(s):

Thibault Guinaldo ◽

Simon Munier ◽

Patrick Le Moigne ◽

Aaron Boone ◽

Bertrand Decharme ◽

...

Keyword(s):

Lake Level ◽

Hydrological Modeling ◽

Lake Victoria ◽

Open Water ◽

Global Scale ◽

Water Bodies ◽

Water Dynamics ◽

Lake Levels ◽

The Impact ◽

River Routing

Abstract. Lakes are of fundamental importance in the Earth system as they support essential environmental and economic services such as freshwater supply. They also modify the local hydro-meteorological continuum as a lower boundary of the atmosphere. Sentinels of climate change and anthropization, these open water bodies are facing disruptions of their equilibrium generally leading to a notable reduction of their levels worldwide. Stream-flow variability and temporal evolution are impacted by the presence of lakes in the river network, therefore any change in the lake state can induce a modification of the regional hydrological regime. Despite the importance of the impact of lakes on hydrological fluxes and the water balance, a representation of the mass budget is generally not included in climate models and global scale hydrological modeling platforms. The goal of this study is to introduce a new lake mass module, MLake (Mass-Lake model), into the river routing model CTRIP to resolve the specific mass-balance of open water bodies. Based on the inherent CTRIP parameters, the development of the non-calibrated MLake model was introduced to examine the influence of such hydrological buffer areas on the global scale river routing performances. In the current study, an off-line evaluation was performed for four river networks using a set of state-of-the-art quality atmospheric forcings and a combination of in situ and satellite measurements for river discharge and lake level observations. The results reveal a general improvement in CTRIP simulated discharge and its variability, while also generating realistic lake level variations. MLake produces more realistic streamflows both in terms of daily and seasonal correlation. Excluding the specific case of Lake Victoria having low performances, the mean skill score of Kling-Gupta Efficiency (KGE) is 0.41 while the Normalized Information Contribution (NIC) shows a mean improvement of 0.56 (ranging from 0.15 to 0.94). Streamflow results are spatially scale-dependent, with better scores associated with larger lakes, and increased sensitivity to the width of the lake outlet. Regarding lake levels variations, results indicate a good agreement between observations and simulations with a mean correlation of 0.56 (ranging from 0.07 to 0.92) which is linked to the capability of the model to retrieve seasonal variations. Discrepancies in the results are mainly explained by the anthropization of the selected lakes which introduces high-frequency variations in both streamflows and lake levels that degraded the scores. Anthropization effects are prevalent in most of the lakes studied, but they are predominant for Lake Victoria and are the main cause for relatively low statistical scores for this river. However, results on the Angara and the Neva rivers also depend on the inherent gap of ISBA-CTRIP processes representation which relies on further development such as the partitioned energy budget between the snow and the canopy over a Boreal zone. The study is a first step towards a global coupled land system that will help to qualitatively assess the evolution of future global water resources leading to improvements in flood risk and drought forecasting.

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The Impact of Error Accounting in a Bayesian Approach to Calibrating Modeled Turbulent Fluxes in an Open-Canopy Forest

Journal of Hydrometeorology ◽

10.1175/jhm-d-17-0030.1 ◽

2017 ◽

Vol 18 (7) ◽

pp. 2029-2042

Author(s):

Tony E. Wong ◽

William Kleiber ◽

David C. Noone

Keyword(s):

Markov Chain ◽

Land Surface ◽

Hydrological Modeling ◽

Soil Layer ◽

Turbulent Fluxes ◽

Surface Model ◽

Model Parameters ◽

Top Soil ◽

The Impact ◽

Calibration Approach

Abstract Land surface models are notorious for containing many parameters that control the exchange of heat and moisture between land and atmosphere. Properly modeling the partitioning of total evapotranspiration (ET) between transpiration and evaporation is critical for accurate hydrological modeling, but depends heavily on the treatment of turbulence within and above canopies. Previous work has constrained estimates of evapotranspiration and its partitioning using statistical approaches that calibrate land surface model parameters by assimilating in situ measurements. These studies, however, are silent on the impacts of the accounting of uncertainty within the statistical calibration framework. The present study calibrates the aerodynamic, leaf boundary layer, and stomatal resistance parameters, which partially control canopy turbulent exchange and thus the evapotranspiration flux partitioning. Using an adaptive Metropolis–Hastings algorithm to construct a Markov chain of draws from the joint posterior distribution of these resistance parameters, an ensemble of model realizations is generated, in which latent and sensible heat fluxes and top soil layer temperature are optimized. A set of five calibration experiments demonstrate that model performance is sensitive to the accounting of various sources of uncertainty in the field observations and model output and that it is critical to account for model structural uncertainty. After calibration, the modeled fluxes and top soil layer temperature are largely free from bias, and this calibration approach successfully informs and characterizes uncertainty in these parameters, which is essential for model improvement and development. The key points of this paper are 1) a Markov chain Monte Carlo calibration approach successfully improves modeled turbulent fluxes; 2) ET partitioning estimates hinge on the representation of uncertainties in the model and data; and 3) despite these inherent uncertainties, constrained posterior estimates of ET partitioning emerge.

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High-resolution fully-coupled atmospheric–hydrological modeling: a cross-compartment regional water and energy cycle evaluation

10.5194/egusphere-egu2020-17855 ◽

2020 ◽

Author(s):

Benjamin Fersch ◽

Alfonso Senatore ◽

Bianca Adler ◽

Joël Arnault ◽

Matthias Mauder ◽

...

Keyword(s):

Boundary Layer ◽

Land Surface ◽

Hydrological Modeling ◽

Weather Prediction ◽

Surface Model ◽

Near Surface ◽

Ground Heat Flux ◽

The Impact ◽

Fully Coupled ◽

Regional Water

The land surface and the atmospheric boundary layer are closely intertwined with respect to the exchange of water, trace gases and energy. Nonlinear feedback and scale dependent mechanisms are obvious by observations and theories. Modeling instead is often narrowed to single compartments of the terrestrial system or bound to traditional viewpoints of definite scientific disciplines. Coupled terrestrial hydrometeorological modeling systems attempt to overcome these limitations to achieve a better integration of the processes relevant for regional climate studies and local area weather prediction. We examine the ability of the hydrologically enhanced version of the Weather Research and Forecasting Model (WRF-Hydro) to reproduce the regional water cycle by means of a two-way coupled approach and assess the impact of hydrological coupling with respect to a traditional regional atmospheric model setting. It includes the observation-based calibration of the hydrological model component (offline WRF-Hydro) and a comparison of the classic WRF and the fully coupled WRF-Hydro models both with identical calibrated parameter settings for the land surface model (Noah-MP). The simulations are evaluated based on extensive observations at the pre-Alpine Terrestrial Environmental Observatory (TERENO Pre-Alpine) for the Ammer (600 km&#178;) and Rott (55 km&#178;) river catchments in southern Germany, covering a five month period (Jun&#8211;Oct 2016).The sensitivity of 7 land surface parameters is tested using the Latin-Hypercube One-factor-At-a-Time (LH-OAT) method and 6 sensitive parameters are subsequently optimized for 6 different subcatchments, using the Model-Independent Parameter Estimation and Uncertainty Analysis software (PEST).The calibration of the offline WRF-Hydro leads to Nash-Sutcliffe efficiencies between 0.56 and 0.64 and volumetric efficiencies between 0.46 and 0.81 for the six subcatchments. The comparison of classic WRF and fully coupled WRF-Hydro shows only tiny alterations for radiation and precipitation but considerable changes for moisture- and energy fluxes. By comparison with TERENO Pre-Alpine observations, the fully coupled model slightly outperforms the classic WRF with respect to evapotranspiration, sensible and ground heat flux, near surface mixing ratio, temperature, and boundary layer profiles of air temperature. The subcatchment-based water budgets show uniformly directed variations for evapotranspiration, infiltration excess and percolation whereas soil moisture and precipitation change randomly.

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Exploring how groundwater buffers the influence of heatwaves on vegetation function during multi-year droughts

Earth System Dynamics ◽

10.5194/esd-12-919-2021 ◽

2021 ◽

Vol 12 (3) ◽

pp. 919-938

Author(s):

Mengyuan Mu ◽

Martin G. De Kauwe ◽

Anna M. Ukkola ◽

Andy J. Pitman ◽

Weidong Guo ◽

...

Keyword(s):

Land Surface ◽

Forest Canopy ◽

Climate Models ◽

Root Zone ◽

Stomatal Closure ◽

Capillary Rise ◽

Vapour Pressure Deficit ◽

Global Climate Models ◽

Surface Model ◽

The Impact

Abstract. The co-occurrence of droughts and heatwaves can have significant impacts on many socioeconomic and environmental systems. Groundwater has the potential to moderate the impact of droughts and heatwaves by moistening the soil and enabling vegetation to maintain higher evaporation, thereby cooling the canopy. We use the Community Atmosphere Biosphere Land Exchange (CABLE) land surface model, coupled to a groundwater scheme, to examine how groundwater influences ecosystems under conditions of co-occurring droughts and heatwaves. We focus specifically on south-east Australia for the period 2000–2019, when two significant droughts and multiple extreme heatwave events occurred. We found groundwater plays an important role in helping vegetation maintain transpiration, particularly in the first 1–2 years of a multi-year drought. Groundwater impedes gravity-driven drainage and moistens the root zone via capillary rise. These mechanisms reduced forest canopy temperatures by up to 5 ∘C during individual heatwaves, particularly where the water table depth is shallow. The role of groundwater diminishes as the drought lengthens beyond 2 years and soil water reserves are depleted. Further, the lack of deep roots or stomatal closure caused by high vapour pressure deficit or high temperatures can reduce the additional transpiration induced by groundwater. The capacity of groundwater to moderate both water and heat stress on ecosystems during simultaneous droughts and heatwaves is not represented in most global climate models, suggesting that model projections may overestimate the risk of these events in the future.

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A simple approach to mimic the effect of active vegetation in hydrological models to better estimate hydrological variables under climate change

10.5194/egusphere-egu21-12025 ◽

2021 ◽

Author(s):

Thedini Asali Peiris ◽

Petra Döll

Keyword(s):

Climate Change ◽

Land Surface ◽

Climate Models ◽

Potential Evapotranspiration ◽

Global Climate ◽

Global Climate Models ◽

Hydrological Models ◽

Net Radiation ◽

Ensemble Mean ◽

The Impact

Unlike global climate models, hydrological models cannot simulate the feedbacks among atmospheric processes, vegetation, water, and energy exchange at the land surface. This severely limits their ability to quantify the impact of climate change and the concurrent increase of atmospheric CO2 concentrations on evapotranspiration and thus runoff. Hydrological models generally calculate actual evapotranspiration as a fraction of potential evapotranspiration (PET), which is computed as a function of temperature and net radiation and sometimes of humidity and wind speed. Almost no hydrological model takes into account that PET changes because the vegetation responds to changing CO2 and climate. This active vegetation response consists of three components. With higher CO2 concentrations, 1) plant stomata close, reducing transpiration (physiological effect) and 2) plants may grow better, with more leaves, increasing transpiration (structural effect), while 3) climatic changes lead to changes in plants growth and even biome shifts, changing evapotranspiration. Global climate models, which include dynamic vegetation models, simulate all these processes, albeit with a high uncertainty, and take into account the feedbacks to the atmosphere.Milly and Dunne (2016) (MD) found that in the case of RCP8.5 the change of PET (computed using the Penman-Monteith equation) between 1981- 2000 and 2081-2100 is much higher than the change of non-water-stressed evapotranspiration (NWSET) computed by an ensemble of global climate models. This overestimation is partially due to the neglect of active vegetation response and partially due to the neglected feedbacks between the atmosphere and the land surface.The objective of this paper is to present a simple approach for hydrological models that enables them to mimic the effect of active vegetation on potential evapotranspiration under climate change, thus improving computation of freshwater-related climate change hazards by hydrological models. MD proposed an alternative approach to estimate changes in PET for impact studies that is only a function of the changes in energy and not of temperature and achieves a good fit to the ensemble mean change of evapotranspiration computed by the ensemble of global climate models in months and grid cells without water stress. We developed an implementation of the MD idea for hydrological models using the Priestley-Taylor equation (PET-PT) to estimate PET as a function of net radiation and temperature. With PET-PT, an increasing temperature trend leads to strong increases in PET. Our proposed methodology (PET-MD) helps to remove this effect, retaining the impact of temperature on PET but not on long-term PET change.We implemented the PET-MD approach in the global hydrological model WaterGAP2.2d. and computed daily time series of PET between 1981 and 2099 using bias-adjusted climate data of four global climate models for RCP 8.5. We evaluated, computed PET-PT and PET-MD at the grid cell level and globally, comparing also to the results of the Milly-Dunne study. The global analysis suggests that the application of PET-MD reduces the PET change until the end of this century from 3.341 mm/day according to PET-PT to 3.087 mm/day (ensemble mean over the four global climate models).Milly, P.C.D., Dunne K.A. (2016). DOI:10.1038/nclimate3046.

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Evaluation of Future Climate and Potential Impact on Streamflow in the Upper Nan River Basin of Northern Thailand

Advances in Meteorology ◽

10.1155/2020/8881118 ◽

2020 ◽

Vol 2020 ◽

pp. 1-15

Author(s):

Miyuru B. Gunathilake ◽

Yasasna V. Amaratunga ◽

Anushka Perera ◽

Imiya M. Chathuranika ◽

Anura S. Gunathilake ◽

...

Keyword(s):

River Basin ◽

Minimum Temperature ◽

Climate Models ◽

Hydrological Modeling ◽

Winter Season ◽

Future Climate ◽

Maximum Temperature ◽

Monthly Precipitation ◽

Northern Thailand ◽

The Impact

Water resources in Northern Thailand have been less explored with regard to the impact on hydrology that the future climate would have. For this study, three regional climate models (RCMs) from the Coordinated Regional Downscaling Experiment (CORDEX) of Coupled Model Intercomparison Project 5 (CMIP5) were used to project future climate of the upper Nan River basin. Future climate data of ACCESS_CCAM, MPI_ESM_CCAM, and CNRM_CCAM under Representation Concentration Pathways RCP4.5 and RCP8.5 were bias-corrected by the linear scaling method and subsequently drove the Hydrological Engineering Center-Hydrological Modeling System (HEC-HMS) to simulate future streamflow. This study compared baseline (1988–2005) climate and streamflow values with future time scales during 2020–2039 (2030s), 2040–2069 (2050s), and 2070–2099 (2080s). The upper Nan River basin will become warmer in future with highest increases in the maximum temperature of 3.8°C/year for MPI_ESM and minimum temperature of 3.6°C/year for ACCESS_CCAM under RCP8.5 during 2080s. The magnitude of changes and directions in mean monthly precipitation varies, with the highest increase of 109 mm for ACESSS_CCAM under RCP 4.5 in September and highest decrease of 77 mm in July for CNRM, during 2080s. Average of RCM combinations shows that decreases will be in ranges of −5.5 to −48.9% for annual flows, −31 to −47% for rainy season flows, and −47 to −67% for winter season flows. Increases in summer seasonal flows will be between 14 and 58%. Projection of future temperature levels indicates that higher increases will be during the latter part of the 20th century, and in general, the increases in the minimum temperature will be higher than those in the maximum temperature. The results of this study will be useful for river basin planners and government agencies to develop sustainable water management strategies and adaptation options to offset negative impacts of future changes in climate. In addition, the results will also be valuable for agriculturists and hydropower planners.

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Impact of humidity biases on light precipitation occurrence: observations versus simulations

10.5194/acp-2018-624 ◽

2018 ◽

Cited By ~ 1

Author(s):

Sophie Bastin ◽

Philippe Drobinski ◽

Marjolaine Chiriaco ◽

Olivier Bock ◽

Romain Roehrig ◽

...

Keyword(s):

Land Surface ◽

Climate Models ◽

Regional Climate ◽

Strong Dependence ◽

Mediterranean Area ◽

Critical Value ◽

Critical Values ◽

Frequency Of Occurrence ◽

The Impact ◽

Light Precipitation

Abstract. This work uses a network of GPS stations over Europe from which a homogenised integrated water vapor (IWV) dataset has been retrieved, completed with colocated temperature and precipitation measurements over specific stations to i) estimate the biases of six regional climate models over Europe in terms of humidity; ii) understand their origins; iii) and finally assess the impact of these biases on the frequency of occurrence of precipitation. The evaluated simulations have been performed in the framework of HYMEX/Med-CORDEX programs and cover the Mediterranean area and part of Europe at horizontal resolutions of 50 to 12 km. The analysis shows that models tend to overestimate the low values of IWV and the use of the nudging technique reduces the differences between GPS and simulated IWV. Results suggest that physics of models mostly explain the mean biases, while dynamics affects the variability. The land surface/atmosphere exchanges affect the estimation of IWV over most part of Europe, especially in summer. The limitations of the models to represent these processes explain part of their baises in IWV. However, models correctly simulate the dependance between IWV and temperature, and specifically the deviation that this relationship experiences regarding the Clausius-Clapeyron law after a critical value of temperature (Tbreak). The high spatial variability of Tbreak indicates that it has a strong dependence on local processes which drive the local humidity sources. This explains why the maximum values of IWV are not necessarely observed over warmer area, that are often dry area. Finally, it is shown over SIRTA observatory (near Paris) that the frequency of occurrence of light precipitation is strongly conditioned by the biases in IWV and by the precision of the models to reproduce the distribution of IWV as a function of the temperature. The results of the models indicate that a similar dependence occurs in other areas of Europe, especially where precipitation has a predominantly convective character. According to the observations, for each range of temperature, there is a critical value of IWV from which precipitation picks up. The critical values and the probability to exceed them are simulated with a bias that depends on the model. Those models which present too often light precipitation generally show lower critical values and higher probability to exceed them.

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Detection of open water dynamics with ENVISAT ASAR in support of land surface modelling at high latitudes

Biogeosciences ◽

10.5194/bg-9-703-2012 ◽

2012 ◽

Vol 9 (2) ◽

pp. 703-714 ◽

Cited By ~ 49

Author(s):

A. Bartsch ◽

A. M. Trofaier ◽

G. Hayman ◽

D. Sabel ◽

S. Schlaffer ◽

...

Keyword(s):

Land Surface ◽

Climate Models ◽

Open Water ◽

Data Availability ◽

Water Dynamics ◽

Climate Modelling ◽

Study Region ◽

Water Fraction ◽

Envisat Asar ◽

Statistical Measures

Abstract. Wetlands are generally accepted as being the largest but least well quantified single source of methane (CH4). The extent of wetland or inundation is a key factor controlling methane emissions, both in nature and in the parameterisations used in large-scale land surface and climate models. Satellite-derived datasets of wetland extent are available on the global scale, but the resolution is rather coarse (>25 km). The purpose of the present study is to assess the capability of active microwave sensors to derive inundation dynamics for use in land surface and climate models of the boreal and tundra environments. The focus is on synthetic aperture radar (SAR) operating in C-band since, among microwave systems, it has comparably high spatial resolution and data availability, and long-term continuity is expected. C-band data from ENVISAT ASAR (Advanced SAR) operating in wide swath mode (150 m resolution) were investigated and an automated detection procedure for deriving open water fraction has been developed. More than 4000 samples (single acquisitions tiled onto 0.5° grid cells) have been analysed for July and August in 2007 and 2008 for a study region in Western Siberia. Simple classification algorithms were applied and found to be robust when the water surface was smooth. Modification of input parameters results in differences below 1 % open water fraction. The major issue to address was the frequent occurrence of waves due to wind and precipitation, which reduces the separability of the water class from other land cover classes. Statistical measures of the backscatter distribution were applied in order to retrieve suitable classification data. The Pearson correlation between each sample dataset and a location specific representation of the bimodal distribution was used. On average only 40 % of acquisitions allow a separation of the open water class. Although satellite data are available every 2–3 days over the Western Siberian study region, the irregular acquisition intervals and periods of unsuitable weather suggest that an update interval of 10 days is more realistic for this domain. SAR data availability is currently limited. Future satellite missions, however, which aim for operational services (such as Sentinel-1 with its C-band SAR instrument), may provide the basis for inundation monitoring for land surface and climate modelling applications.

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Simulating riverine nutrient transport on global scale

10.5194/egusphere-egu2020-8167 ◽

2020 ◽

Author(s):

Tobias Stacke ◽

Stefan Hagemann ◽

Gibran Romero-Mujalli ◽

Jens Hartmann ◽

Helmuth Thomas

Keyword(s):

Land Surface ◽

Large Scale ◽

Climate Models ◽

River Flow ◽

Climate Change Impacts ◽

Global Scale ◽

Nutrient Loads ◽

Input Dataset ◽

Ocean Models ◽

Energy And Momentum

The currently ongoing CMIP6 simulations feature Earth System Models with interactively coupled components for atmosphere, ocean and land surface. Water, energy and momentum between these components are exchanged conservatively. This is crucial to compute climate interactions and their feedbacks consistently. Currently, the representation of biogeochemical cycles in land surface and ocean models is advancing including not only a carbon cycle but also processes based on nutrients like nitrogen or phosphorus. Some land surface models (LSM) already compute leaching of such constituents from the soil, and some ocean models (OM) consider nutrient influx from the land for a number of processes, e.g. biological activity. However, the OMs usually use observed data as input instead of the nutrient loads computed by the LSMs. This setup cannot represent the effects of climate or land use change on nutrient availability and therefore limits the applications of ESMs in respect to climate change impacts.For this reason, we are extending our hydrological discharge model, the HDM, to not only transport water but also other constituents. The HDM is an established component of regional (GCOAST, ESM ROM, Reg-CM-ES) as well as global (MPI-ESM) climate models but also applicable as stand-alone model. In a first step, only inert transport is simulated without considering any chemical reactions or biological transformation during river flow. The transport is realized using the same linear cascade infrastructure as used for water transport. However, a successful offline validation of these new features does not only require a realistic routing scheme and consequently the representation of the most important reactions during transport, but also the generation of sensible input data either from large scale models or from observations. In our presentation, we will outline the state of this work together with the compiled input dataset.

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A Statistical–Dynamical Methodology to Downscale Regional Climate Projections to Urban Scale

Journal of Applied Meteorology and Climatology ◽

10.1175/jamc-d-19-0104.1 ◽

2020 ◽

Vol 59 (6) ◽

pp. 1109-1123 ◽

Cited By ~ 1

Author(s):

François DuchÊne ◽

Bert Van Schaeybroeck ◽

Steven Caluwaerts ◽

Rozemien De Troch ◽

Rafiq Hamdi ◽

...

Keyword(s):

Land Surface ◽

Climate Models ◽

Dynamical Downscaling ◽

Heat Waves ◽

Regional Climate ◽

Wave Number ◽

Surface Model ◽

Climate Projections ◽

Short Period ◽

The Impact

AbstractThe demand of city planners for quantitative information on the impact of climate change on the urban environment is increasing. However, such information is usually extracted from decadelong climate projections generated with global or regional climate models (RCMs). Because of their coarse resolution and unsuitable physical parameterization, however, their model output is not adequate to be used at city scale. A full dynamical downscaling to city level, on the other hand, is computationally too expensive for climatological time scales. A statistical–dynamical computationally inexpensive method is therefore proposed that approximates well the behavior of the full dynamical downscaling approach. The approach downscales RCM simulations using the combination of an RCM at high resolution (H-RES) and a land surface model (LSM). The method involves the setup of a database of urban signatures by running an H-RES RCM with and without urban parameterization for a relatively short period. Using an analog approach, these signatures are first selectively added to the long-term RCM data, which are then used as forcing for an LSM using an urban parameterization in a stand-alone mode. A comparison with a full dynamical downscaling approach is presented for the city of Brussels, Belgium, for 30 summers with the combined ALADIN–AROME model (ALARO-0) coupled to the Surface Externalisée model (SURFEX) as H-RES RCM and SURFEX as LSM. The average bias of the nocturnal urban heat island during heat waves is vanishingly small, and the RMSE is strongly reduced. Not only is the statistical–dynamical approach able to correct the heat-wave number and intensities, it can also improve intervariable correlations and multivariate and temporally correlated indices, such as Humidex.

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