scholarly journals Improving the stomatal resistance, photosynthesis and two big leaf algorithms for grass in the regional climate model COSMO-CLM

2021 ◽  
Author(s):  
Evgenii Churiulin ◽  
Vladimir Kopeikin ◽  
Markus Übel ◽  
Jürgen Helmert ◽  
Jean-Maria Bettems ◽  
...  
Keyword(s):  
Regional Climate Model ◽  
Climate Model ◽  
Regional Climate ◽  
Stomatal Resistance ◽  
Day Length ◽  
Original Algorithm ◽  
Community Land Model ◽  
Reference Simulation ◽  
Meteorological Observations ◽  
New Algorithms

Abstract. Climatic changes towards warmer temperatures require the need to improve the simplified vegetation scheme of the regional climate model COSMO-CLM, which is not capable of modelling complex processes which depend on temperature, water availability, and day length. Thus, we have implemented the physically based Ball-Berry approach coupled with photosynthesis processes based on Farquhar and Collatz models for C3 and C4 plants in the regional climate model COSMO-CLM (CCLM v 5.16). The implementation of the new algorithms includes the replacement of the “one-big leaf” approach by a “two-big leaf” one. We performed single column simulations with COSMO-CLM over three observational sites with C3 grass plants in Germany for the period from 2010 to 2015 (Parc, Linden and Lindenberg domain). Hereby, we tested three alternative formulations of the new algorithms against a reference simulation (CCLMref) with no changes. The first formulation (CCLM3.5) adapts the algorithms for stomatal resistance from the Community Land Model (CLM v3.5), which depend on leaf photosynthesis, CO2 partial and vapor pressure and maximum stomatal resistance. The second one (CCLM4.5) includes a soil water stress function as in CLM v4.5. The third one (CCLM4.5e) is similar to CCLM4.5, but with adapted equations for dry leaf calculations. The results revealed major differences in the annual cycle of stomatal resistance compared to the original algorithm (CCLMref) of the reference simulation. The largest changes in stomatal resistance are observed from October to April when stomata are closed while summer values are generally less than control values that come closer to measured values. The results indicate that changes in stomatal resistance and photosynthesis algorithms can improve the accuracy of other parameters of the COSMO-CLM model (e.g.: transpiration rate or total evapotranspiration). These results were received by comparing COSMO-CLM parameters with FLUXNET data, meteorological observations at the sites, and GLEAM and HYRAS datasets.

scholarly journals Improving Climate Sensitivity of Deep Lakes within a Regional Climate Model and Its Impact on Simulated Climate

2014 ◽  
Vol 27 (8) ◽  
pp. 2886-2911 ◽  
Author(s):  
Val Bennington ◽  
Michael Notaro ◽  
Kathleen D. Holman
Keyword(s):  
Regional Climate Model ◽  
Interannual Variability ◽  
Climate Models ◽  
Climate Model ◽  
Regional Climate ◽  
Global Climate Models ◽  
Deep Lakes ◽  
Community Land Model ◽  
Lake Model ◽  
Lake Temperature

Abstract Regional climate models aim to improve local climate simulations by resolving topography, vegetation, and land use at a finer resolution than global climate models. Lakes, particularly large and deep lakes, are local features that significantly alter regional climate. The Hostetler lake model, a version of which is currently used in the Community Land Model, performs poorly in deep lakes when coupled to the regional climate of the International Centre for Theoretical Physics (ICTP) Regional Climate Model, version 4 (RegCM4). Within the default RegCM4 model, the lake fails to properly stratify, stifling the model’s ability to capture interannual variability in lake temperature and ice cover. Here, the authors improve modeled lake stratification and eddy diffusivity while correcting errors in the ice model. The resulting simulated lake shows improved stratification and interannual variability in lake ice and temperature. The lack of circulation and explicit mixing continues to stifle the model’s ability to simulate lake mixing events and variability in timing of stratification and destratification. The changes to modeled lake conditions alter seasonal means in sea level pressure, temperature, and low-level winds in the entire model domain, highlighting the importance of lake model selection and improvement for coupled simulations. Interestingly, changes to winter and spring snow cover and albedo impact spring warming. Unsurprisingly, regional climate variability is not significantly altered by an increase in lake temperature variability.

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 Impact of Environmental Conditions on Grass Phenology in the Regional Climate Model COSMO-CLM

Atmosphere ◽  
2020 ◽  
Vol 11 (12) ◽  
pp. 1364
Author(s):  
Eva Hartmann ◽  
Jan-Peter Schulz ◽  
Ruben Seibert ◽  
Marius Schmidt ◽  
Mingyue Zhang ◽  
...  
Keyword(s):  
Regional Climate Model ◽  
Environmental Conditions ◽  
Climate Model ◽  
Regional Climate ◽  
Growth Period ◽  
Day Length ◽  
Canopy Conductance ◽  
Area Index ◽  
Volatile Organic ◽  
New Evidence

Feedbacks of plant phenology to the regional climate system affect fluxes of energy, water, CO2, biogenic volatile organic compounds as well as canopy conductance, surface roughness length, and are influencing the seasonality of albedo. We performed simulations with the regional climate model COSMO-CLM (CCLM) at three locations in Germany covering the period 1999 to 2015 in order to study the sensitivity of grass phenology to different environmental conditions by implementing a new phenology module. We provide new evidence that the annually-recurring standard phenology of CCLM is improved by the new calculation of leaf area index (LAI) dependent upon surface temperature, day length, and water availability. Results with the new phenology implemented in the model show a significantly higher correlation with observations than simulations with the standard phenology. The interannual variability of LAI improves the representation of vegetation in years with extremely warm winter/spring (e.g., 2007) or extremely dry summer (e.g., 2003) and shows a more realistic growth period. The effect of the newly implemented phenology on atmospheric variables is small but tends to be positive. It should be used in future applications with an extension on more plant functional types.

scholarly journals The COSMO-CLM 4.8 regional climate model coupled to regional ocean, land surface and global earth system models using OASIS3-MCT: description and performance

2017 ◽  
Vol 10 (4) ◽  
pp. 1549-1586 ◽  
Author(s):  
Andreas Will ◽  
Naveed Akhtar ◽  
Jennifer Brauch ◽  
Marcus Breil ◽  
Edouard Davin ◽  
...  
Keyword(s):  
Regional Climate Model ◽  
Direct Cost ◽  
Land Surface ◽  
Climate Model ◽  
Regional Climate ◽  
Ocean Model ◽  
Earth System ◽  
Climate System Model ◽  
Community Land Model ◽  
Computational Performance

Abstract. We developed a coupled regional climate system model based on the CCLM regional climate model. Within this model system, using OASIS3-MCT as a coupler, CCLM can be coupled to two land surface models (the Community Land Model (CLM) and VEG3D), the NEMO-MED12 regional ocean model for the Mediterranean Sea, two ocean models for the North and Baltic seas (NEMO-NORDIC and TRIMNP+CICE) and the MPI-ESM Earth system model.We first present the different model components and the unified OASIS3-MCT interface which handles all couplings in a consistent way, minimising the model source code modifications and defining the physical and numerical aspects of the couplings. We also address specific coupling issues like the handling of different domains, multiple usage of the MCT library and exchange of 3-D fields.We analyse and compare the computational performance of the different couplings based on real-case simulations over Europe. The usage of the LUCIA tool implemented in OASIS3-MCT enables the quantification of the contributions of the coupled components to the overall coupling cost. These individual contributions are (1) cost of the model(s) coupled, (2) direct cost of coupling including horizontal interpolation and communication between the components, (3) load imbalance, (4) cost of different usage of processors by CCLM in coupled and stand-alone mode and (5) residual cost including i.a. CCLM additional computations.Finally a procedure for finding an optimum processor configuration for each of the couplings was developed considering the time to solution, computing cost and parallel efficiency of the simulation. The optimum configurations are presented for sequential, concurrent and mixed (sequential+concurrent) coupling layouts. The procedure applied can be regarded as independent of the specific coupling layout and coupling details.We found that the direct cost of coupling, i.e. communications and horizontal interpolation, in OASIS3-MCT remains below 7 % of the CCLM stand-alone cost for all couplings investigated. This is in particular true for the exchange of 450 2-D fields between CCLM and MPI-ESM. We identified remaining limitations in the coupling strategies and discuss possible future improvements of the computational efficiency.

Qinghai-Xizang (Tibetan) Plateau climate simulation using the regional climate model RegCM3

2013 ◽  
Vol 57 (3) ◽  
pp. 173-186 ◽  
Author(s):  
X Wang ◽  
M Yang ◽  
G Wan ◽  
X Chen ◽  
G Pang
Keyword(s):  
Tibetan Plateau ◽  
Regional Climate Model ◽  
Climate Model ◽  
Regional Climate ◽  
Climate Simulation

Evaluation of net shortwave radiation over China with a regional climate model

2020 ◽  
Vol 80 (2) ◽  
pp. 147-163
Author(s):  
X Liu ◽  
Y Kang ◽  
Q Liu ◽  
Z Guo ◽  
Y Chen ◽  
...  
Keyword(s):  
Regional Climate Model ◽  
Climate Model ◽  
Regional Climate ◽  
Radiant Energy ◽  
Energy System ◽  
Radiation Budget ◽  
Shortwave Radiation ◽  
Monsoon Region ◽  
Clear Sky ◽  
Sky Conditions

The regional climate model RegCM version 4.6, developed by the European Centre for Medium-Range Weather Forecasts Reanalysis, was used to simulate the radiation budget over China. Clouds and the Earth’s Radiant Energy System (CERES) satellite data were utilized to evaluate the simulation results based on 4 radiative components: net shortwave (NSW) radiation at the surface of the earth and top of the atmosphere (TOA) under all-sky and clear-sky conditions. The performance of the model for low-value areas of NSW was superior to that for high-value areas. NSW at the surface and TOA under all-sky conditions was significantly underestimated; the spatial distribution of the bias was negative in the north and positive in the south, bounded by 25°N for the annual and seasonal averaged difference maps. Compared with the all-sky condition, the simulation effect under clear-sky conditions was significantly better, which indicates that the cloud fraction is the key factor affecting the accuracy of the simulation. In particular, the bias of the TOA NSW under the clear-sky condition was <±10 W m-2 in the eastern areas. The performance of the model was better over the eastern monsoon region in winter and autumn for surface NSW under clear-sky conditions, which may be related to different levels of air pollution during each season. Among the 3 areas, the regional average biases overall were largest (negative) over the Qinghai-Tibet alpine region and smallest over the eastern monsoon region.

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