Reinitialised versus continuous regional climate simulations using ALARO-0 coupled to the land surface model SURFEX

Abstract. The potential of the implementation of the land surface model SURFEX in the atmospheric ALARO-0 model configuration of the ALADIN system is tested in a continuous regional climate simulation. This contribution is evaluated with respect to the regional climate simulated by the original setup of ALARO-0 with ISBA. Next, an assessment has been performed to evaluate the continuous setup with an upper air daily reinitialised setup, where the surface is kept in a freely continuous mode. The results show that the introduction of SURFEX improves or has a neutral impact on the 2 m temperature and the daily total precipitation. More importantly, the use of an upper air daily reinitialised atmosphere outperforms the setup with a continuous atmosphere, for the 2 m temperature in winter and summer, and for the summer daily total precipitation. The differences between the two downscaling setups in the 2 m temperature and precipitation interact with the soil moisture. This coupling is strong for the continental areas, which motivates the use of a coupled land-atmosphere model to optimise the representation of the climate.

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Land surface model influence on the simulated climatologies of temperature and precipitation extremes in the WRF v3.9 model over North America

Geoscientific Model Development ◽

10.5194/gmd-13-5345-2020 ◽

2020 ◽

Vol 13 (11) ◽

pp. 5345-5366

Author(s):

Almudena García-García ◽

Francisco José Cuesta-Valero ◽

Hugo Beltrami ◽

Fidel González-Rouco ◽

Elena García-Bustamante ◽

...

Keyword(s):

Land Surface ◽

Climate Model ◽

Regional Climate ◽

Extreme Temperature ◽

Wrf Model ◽

Land Surface Model ◽

Surface Model ◽

Temperature And Precipitation ◽

Model Ensembles ◽

Precipitation Events

Abstract. The representation and projection of extreme temperature and precipitation events in regional and global climate models are of major importance for the study of climate change impacts. However, state-of-the-art global and regional climate model simulations yield a broad inter-model range of intensity, duration and frequency of these extremes. Here, we present a modeling experiment using the Weather Research and Forecasting (WRF) model to determine the influence of the land surface model (LSM) component on uncertainties associated with extreme events. First, we analyze land–atmosphere interactions within four simulations performed by the WRF model from 1980 to 2012 over North America, using three different LSMs. Results show LSM-dependent differences at regional scales in the frequency of occurrence of events when surface conditions are altered by atmospheric forcing or land processes. The inter-model range of extreme statistics across the WRF simulations is large, particularly for indices related to the intensity and duration of temperature and precipitation extremes. Our results show that the WRF simulation of the climatology of heat extremes can be 5 ∘C warmer and 6 d longer depending on the employed LSM component, and similarly for cold extremes and heavy precipitation events. Areas showing large uncertainty in WRF-simulated extreme events are also identified in a model ensemble from three different regional climate model (RCM) simulations participating in the Coordinated Regional Climate Downscaling Experiment (CORDEX) project, revealing the implications of these results for other model ensembles. Thus, studies based on multi-model ensembles and reanalyses should include a variety of LSM configurations to account for the uncertainty arising from this model component or to test the performance of the selected LSM component before running the whole simulation. This study illustrates the importance of the LSM choice in climate simulations, supporting the development of new modeling studies using different LSM components to understand inter-model differences in simulating extreme temperature and precipitation events, which in turn will help to reduce uncertainties in climate model projections.

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Land Surface Model influence on the simulated climatologies of temperature and precipitation extremes in the WRF v.3.9 model over North America

10.5194/gmd-2020-86 ◽

2020 ◽

Author(s):

Almudena García-García ◽

Francisco José Cuesta-Valero ◽

Hugo Beltrami ◽

J. Fidel González-Rouco ◽

Elena García-Bustamante ◽

...

Keyword(s):

North America ◽

Regional Climate Model ◽

Extreme Events ◽

Land Surface ◽

Climate Model ◽

Regional Climate ◽

Wrf Model ◽

Land Surface Model ◽

Surface Model ◽

Temperature And Precipitation

Abstract. The representation and projection of extreme temperature and precipitation events in regional and global climate models are of major importance for the study of climate change impacts. However, state-of-the-art global and regional climate model simulations yield a broad inter-model range of intensity, duration and frequency of these extremes. Here, we present a modeling experiment using the Weather Research and Forecasting (WRF) model to determine the influence of the land surface model (LSM) component on uncertainties associated with extreme events. First, we evaluate land-atmosphere interactions within four simulations performed by the WRF model using three different LSMs from 1980 to 2012 over North America. Results show LSM-dependent differences at regional scales in the frequency of occurrence of events when surface conditions are altered by atmospheric forcing or land processes. The inter-model range of extreme statistics across the WRF simulations is large, particularly for indices related to the intensity and duration of temperature and precipitation extremes. Areas showing large uncertainty in WRF simulated extreme events are also identified in a model ensemble from three different Regional Climate Model (RCM) simulations participating in the Coordinated Regional Climate Downscaling Experiment (CORDEX) project, revealing the implications of these results for other model ensembles. This study illustrates the importance of the LSM choice in climate simulations, supporting the development of new modeling studies using different LSM components to understand inter-model differences in simulating temperature and precipitation extreme events, which in turn will help to reduce uncertainties in climate model projections.

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Land Surface Model influence on the simulated climatologies of extreme temperature and precipitation events within the WRF model over North America

10.5194/egusphere-egu2020-3151 ◽

2020 ◽

Author(s):

Almudena García-García ◽

Francisco José Cuesta-Valero ◽

Hugo Beltrami ◽

J. Fidel González-Rouco ◽

Elena García-Bustamante ◽

...

Keyword(s):

Land Surface ◽

Climate Model ◽

Regional Climate ◽

Extreme Temperature ◽

Wrf Model ◽

Land Surface Model ◽

Surface Model ◽

Model Simulations ◽

Temperature And Precipitation ◽

Precipitation Events

The representation and projection of extreme temperature and precipitation events in climate models are of major importance for developing polices to build communities&#8217; resilience in the face of climate change. However, state-of-the-art global and regional climate model simulations yield a broad inter-model range of intensities, durations and frequencies of these extremes. Here, we present a modeling experiment using the Weather Research and Forecasting (WRF) Regional Climate Model (RCM) to determine the influence of the choice of land surface model (LSM) component on the uncertainty in the simulation of extreme event statistics. First, we evaluate land-atmosphere interactions within four simulations performed with the WRF model coupled to three different LSMs from 1980 to 2012 over North America. Results show regional differences among simulations for the frequency of events when surface conditions are altered by atmospheric forcing or by land surface processes. Second, we find a large inter-model range of extreme statistics across the ensemble of WRF-LSM simulations. This is particularly the case for indices related to the intensity and duration of temperature and precipitation extremes. Regions displaying large uncertainty in the WRF simulation of extreme events are also identified in a model ensemble experiment carried out with three different RCMs participating in the Coordinated Regional Climate Downscaling Experiment (CORDEX) project. This agreement between the model simulations performed in this work and the set of CORDEX simulations suggests that the implications of our results are valid for other model ensembles. This study illustrates the importance of supporting the development of new multi-LSM modeling studies to understand inter-model differences in simulating extreme events, ultimately helping to narrow down the range across climate model projections.

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Interactive comment on “Reinitialised versus continuous regional climate simulations using ALARO-0 coupled to the land surface model SURFEX” by Julie Berckmans et al.

10.5194/gmd-2016-154-rc2 ◽

2016 ◽

Author(s):

Anonymous

Keyword(s):

Land Surface ◽

Regional Climate ◽

Land Surface Model ◽

Surface Model ◽

Climate Simulations

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Executive Editor Comment on "Reinitialised versus continuous regional climate simulations using ALARO-0 coupled to the land surface model SURFEX"

10.5194/gmd-2016-154-sc1 ◽

2016 ◽

Author(s):

Astrid Kerkweg

Keyword(s):

Land Surface ◽

Regional Climate ◽

Land Surface Model ◽

Surface Model ◽

Editor Comment ◽

Executive Editor ◽

Climate Simulations

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The Met Office Unified Model Global Atmosphere 4.0 and JULES Global Land 4.0 configurations

Geoscientific Model Development ◽

10.5194/gmd-7-361-2014 ◽

2014 ◽

Vol 7 (1) ◽

pp. 361-386 ◽

Cited By ~ 121

Author(s):

D. N. Walters ◽

K. D. Williams ◽

I. A. Boutle ◽

A. C. Bushell ◽

J. M. Edwards ◽

...

Keyword(s):

Land Surface ◽

Weather Prediction ◽

Regional Climate ◽

Land Surface Model ◽

Unified Model ◽

Surface Model ◽

Development Cycle ◽

Global Land ◽

Overall Performance ◽

Ongoing Development

Abstract. We describe Global Atmosphere 4.0 (GA4.0) and Global Land 4.0 (GL4.0): configurations of the Met Office Unified Model and JULES (Joint UK Land Environment Simulator) community land surface model developed for use in global and regional climate research and weather prediction activities. GA4.0 and GL4.0 are based on the previous GA3.0 and GL3.0 configurations, with the inclusion of developments made by the Met Office and its collaborators during its annual development cycle. This paper provides a comprehensive technical and scientific description of GA4.0 and GL4.0 as well as details of how these differ from their predecessors. We also present the results of some initial evaluations of their performance. Overall, performance is comparable with that of GA3.0/GL3.0; the updated configurations include improvements to the science of several parametrisation schemes, however, and will form a baseline for further ongoing development.

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Evaluation of Temperature Simulation over Northern Thailand from Regional Climate Model Coupled with Land Surface Model

Applied Mechanics and Materials ◽

10.4028/www.scientific.net/amm.866.108 ◽

2017 ◽

Vol 866 ◽

pp. 108-111

Author(s):

Theerapan Saesong ◽

Pakpoom Ratjiranukool ◽

Sujittra Ratjiranukool

Keyword(s):

Regional Climate Model ◽

Land Surface ◽

Climate Model ◽

Global Analysis ◽

Regional Climate ◽

Land Surface Model ◽

Analysis Data ◽

Surface Model ◽

Northern Thailand ◽

Weather Model

Numerical Weather Model called The Weather Research and Forecasting model, WRF, developed by National Center for Atmospheric Research (NCAR) is adapted to be regional climate model. The model is run to perform the daily mean air surface temperatures over northern Thailand in 2010. Boundery dataset provided by National Centers for Environmental Prediction, NCEP FNL, (Final) Operational Global Analysis data which are on 10 x 10. The simulated temperatures by WRF with four land surface options, i.e., no land surface scheme (option 0), thermal diffusion (option 1), Noah land-surface (option 2) and RUC land-surface (option 3) were compared against observational data from Thai Meteorological Department (TMD). Preliminary analysis indicated WRF simulations with Noah scheme were able to reproduce the most reliable daily mean temperatures over northern Thailand.

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Assessment of WRF Land Surface Model Performance over West Africa

Advances in Meteorology ◽

10.1155/2020/6205308 ◽

2020 ◽

Vol 2020 ◽

pp. 1-30

Author(s):

Ifeanyi C. Achugbu ◽

Jimy Dudhia ◽

Ayorinde A. Olufayo ◽

Ifeoluwa A. Balogun ◽

Elijah A. Adefisan ◽

...

Keyword(s):

West Africa ◽

Land Surface ◽

Model Performance ◽

Wrf Model ◽

Land Surface Model ◽

Surface Model ◽

Reanalysis Dataset ◽

The North ◽

Temperature And Precipitation ◽

Moisture Advection

Simulations with four land surface models (LSMs) (i.e., Noah, Noah-MP, Noah-MP with ground water GW option, and CLM4) using the Weather Research and Forecasting (WRF) model at 12 km horizontal grid resolution were carried out as two sets for 3 months (December–February 2011/2012 and July–September 2012) over West Africa. The objective is to assess the performance of WRF LSMs in simulating meteorological parameters over West Africa. The model precipitation was assessed against TRMM while surface temperature was compared with the ERA-Interim reanalysis dataset. Results show that the LSMs performed differently for different variables in different land-surface conditions. Based on precipitation and temperature, Noah-MP GW is overall the best for all the variables and seasons in combination, while Noah came last. Specifically, Noah-MP GW performed best for JAS temperature and precipitation; CLM4 was the best in simulating DJF precipitation, while Noah was the best in simulating DJF temperature. Noah-MP GW has the wettest Sahel while Noah has the driest one. The strength of the Tropical Easterly Jet (TEJ) is strongest in Noah-MP GW and Noah-MP compared with that in CLM4 and Noah. The core of the African Easterly Jet (AEJ) lies around 12°N in Noah and 15°N for Noah-MP GW. Noah-MP GW and Noah-MP simulations have stronger influx of moisture advection from the southwesterly monsoonal wind than the CLM4 and Noah with Noah showing the least influx. Also, analysis of the evaporative fraction shows sharp gradient for Noah-MP GW and Noah-MP with wetter Sahel further to the north and further to the south for Noah. Noah-MP-GW has the highest amount of soil moisture, while the CLM4 has the least for both the JAS and DJF seasons. The CLM4 has the highest LH for both DJF and JAS seasons but however has the least SH for both DJF and JAS seasons. The principal difference between the LSMs is in the vegetation representation, description, and parameterization of the soil water column; hence, improvement is recommended in this regard.

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