First Review for the manuscript entitled « ICON in Climate Limited-area Mode (ICON Release Version 2.6.1) : a new regional climate model » by Van Pham et al.

Abstract The present work introduces a new and useful tool to quantify the lateral boundary forcing of a regional climate model (RCM). This tool, an aging tracer, computes the time the air parcels spend inside the limited-area domain of an RCM. The aging tracers are initialized to zero when the air parcels enter the domain and grow older during their migrations through the domain with each time step in the integration of the model. This technique was employed in a 10-member ensemble of 10-yr (1980–89) simulations with the Canadian RCM on a large domain covering North America. The residency time is treated and archived as the other simulated meteorological variables, therefore allowing computation of its climate diagnostics. These diagnostics show that the domain-averaged residency time is shorter in winter than in summer as a result of the faster winter atmospheric circulation. The residency time decreases with increasing height above the surface because of the faster atmospheric circulation at high levels dominated by the jet stream. Within the domain, the residency time increases from west to east according to the transportation of the aging tracer with the westerly general atmospheric circulation. A linear relation is found between the spatial distribution of the internal variability—computed with the variance between the ensemble members—and residency time. This relation indicates that the residency time can be used as a quantitative indicator to estimate the level of control exerted by the lateral boundary conditions on the RCM simulations.

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PERFORMA KONVERGENSI ANGIN PERMUKAAN DIURNAL MODEL REANALISIS ERA5 DI BENUA MARITIM INDONESIA

Jurnal Sains & Teknologi Modifikasi Cuaca ◽

10.29122/jstmc.v20i2.3795 ◽

2020 ◽

Vol 20 (2) ◽

pp. 59-65

Author(s):

Achmad Fahruddin Rais ◽

Soenardi Soenardi ◽

Zubaidi Fanani ◽

Pebri Surgiansyah

Keyword(s):

Finite Difference ◽

Regional Climate Model ◽

Climate Model ◽

Regional Climate ◽

Surface Wind ◽

Limited Area ◽

Surface Winds ◽

Limited Area Model ◽

Area Model ◽

Weather Research

IntisariPada penelitian ini, penulis mengkaji uji performa kualitatif konvergensi angin permukaan model reanalisis ERA5 di BMI yang dibandingkan dengan hasil penelitian menggunakan limited area model (LAM) oleh Qian, Im dan Eltahir serta Alfahmi et al. Konvergensi angin permukaan dan anomali angin permukaan dihitung dengan menggunakan finite difference. Hasil penelitian menunjukkan bahwa model reanalisis ERA5 mampu mensimulasikan konvergensi anomali angin permukaan dengan baik terhadap model regional climate model (RegCM) maupun The MIT regional climate model (MRCM) resolusi 27 km di Pulau Jawa dan sekitarnya serta BMI bagian barat dengan nilai konvergensi yang lebih tinggi. Sedangkan terhadap model weather research forecast (WRF) 9 km di BMI bagian timur, model reanalisis ERA5 juga dapat mensimulasikan konvergensi angin permukaan, tetapi dengan nilai yang lebih rendah. Selain itu, model reanalisis ERA5 mensimulasikan konvergensi angin permukaan lebih cepat 2 jam di BMI bagian barat dan timur dibandingkan MRCM27 dan WRF. AbstractIn this study, we discuss the qualitative performance testing of ERA5 surface wind convergence over the Indonesia maritime continent (BMI) compared with research based on limited area model (LAM) by Qian, Im, and Eltahir and also Alfahmi et al. Wind surface convergence and wind surface anomalies convergence is calculated using finite-difference. The results show that the ERA5 reanalysis model can simulate convergence of surface wind anomalies compared with both regional climate model (RegCM) and 27 km MIT regional climate model (MRCM) over Java and also western BMI with higher convergence values. While ERA5 reanalysis model can also simulate convergence of surface winds, but with lower values compared to 9 km weather research forecast (WRF) model over eastern BMI. Besides, the ERA5 reanalysis model simulates convergence of surface winds, which is 2 hours faster over western and eastern BMI compared to MRCM27 and WRF.

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Effects of coastal topography on climate: high-resolution simulation with a regional climate model

Climate Research ◽

10.3354/cr01077 ◽

2012 ◽

Vol 52 ◽

pp. 159-174 ◽

Cited By ~ 26

Author(s):

B Önol

Keyword(s):

High Resolution ◽

Regional Climate Model ◽

Climate Model ◽

Regional Climate ◽

Resolution Simulation ◽

Coastal Topography

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

Climate Research ◽

10.3354/cr01167 ◽

2013 ◽

Vol 57 (3) ◽

pp. 173-186 ◽

Cited By ~ 18

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

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

Climate Research ◽

10.3354/cr01598 ◽

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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