Lateral Boundary Conditions in Regional Climate Models: A Detailed Study of the Relaxation Procedure

Marbaix, Philippe; Gallée, Hubert; Brasseur, Olivier; Strihou, Jean-Pascal van Ypersele de

doi:10.1175/1520-0493(2003)131<0461:lbcirc>2.0.co;2

Cited by 102 publications

(61 citation statements)

References 22 publications

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“…The atmospheric variables are initialised and forced every 6 h at the lateral boundaries using the ERA-INTERIM reanalysis available at a resolution of about 80 km (Dee et al, 2011). Details of the boundary forcing can be found in Marbaix et al (2003). In all figures presented here, we show the entire domain of simulation to clearly visualize the buffer zone, which reaches approximately 100 to 200 km.…”

Section: Model Descriptionmentioning

confidence: 99%

Precipitation and snow cover in the Himalaya: from reanalysis to regional climate simulations

Ménégoz

Gallée

Jacobi

2013

Hydrol. Earth Syst. Sci.

128

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Abstract. We applied a Regional Climate Model (RCM) to simulate precipitation and snow cover over the Himalaya, between March 2000 and December 2002. Due to its higher resolution, our model simulates a more realistic spatial variability of wind and precipitation than those of the reanalysis of the European Centre of Medium range Weather Forecast (ECMWF) used as lateral boundaries. In this region, we found very large discrepancies between the estimations of precipitation provided by reanalysis, rain gauges networks, satellite observations, and our RCM simulation. Our model clearly underestimates precipitation at the foothills of the Himalaya and in its eastern part. However, our simulation provides a first estimation of liquid and solid precipitation in high altitude areas, where satellite and rain gauge networks are not very reliable. During the two years of simulation, our model resembles the snow cover extent and duration quite accurately in these areas. Both snow accumulation and snow cover duration differ widely along the Himalaya: snowfall can occur during the whole year in western Himalaya, due to both summer monsoon and mid-latitude low pressure systems bringing moisture into this region. In Central Himalaya and on the Tibetan Plateau, a much more marked dry season occurs from October to March. Snow cover does not have a pronounced seasonal cycle in these regions, since it depends both on the quite variable duration of the monsoon and on the rare but possible occurrence of snowfall during the extramonsoon period.

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Section: Model Descriptionmentioning

confidence: 99%

Precipitation and snow cover in the Himalaya: from reanalysis to regional climate simulations

Ménégoz

Gallée

Jacobi

2013

Hydrol. Earth Syst. Sci.

128

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“…Marbaix et al (2003) provide practical guidelines for choosing relaxation coefficients through sensitivity experiments. Orographic blending in the buffer zone, proposed by Jones et al (1995) and Hong and Juang (1998), is useful and effective in reducing systematic biases of the regional model influenced by dynamical uncertainty when steep orography appears in the buffer zone.…”

Section: Uncertainties In the Nested Rcmmentioning

confidence: 99%

Regional Climate Modeling: Progress, Challenges, and Prospects

Wang

Leung

McGregor

et al. 2004

Journal of the Meteorological Society of Japan

423

296

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Regional climate modeling using regional climate models (RCMs) has matured over the past decade to enable meaningful utilization in a broad spectrum of applications. In this paper, the latest progress in regional climate modeling studies is reviewed, including RCM development, applications of RCMs to Challenges and potential directions of future research in this important area are discussed, with focus on those that have received less attention previously, such as the importance of ensemble simulations, further development and improvement of the regional climate modeling approach, modeling extreme climate events and sub-daily variation of clouds and precipitation, model evaluation and diagnostics, applications of RCMs to climate process studies and seasonal predictions, and development of regional earth system models.It is believed that with the demonstrated credibility of RCMs in reproducing not only monthly to seasonal mean climate and interannual variability, but also the extreme climate events when driven by good quality reanalysis and continuous improvements in the skill of global general circulation models (GCMs) in simulating large-scale atmospheric circulation, regional climate modeling will remain an important dynamical downscaling tool for providing the needed information for assessing climate change impacts, and seasonal climate predictions, and a powerful tool for improving our understanding of regional climate processes. Internationally coordinated efforts can be developed to further advance regional climate modeling studies. It is also recognized that since the final quality of the results from nested RCMs depends in part on the realism of the large-scale forcing provided by GCMs, the reduction of errors and improvement in physics parameterizations in both GCMs and RCMs remain a priority for the climate modeling community.

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“…4). Dynamical inconsistencies can arise from the lack of well-posedness of the lateral boundary conditions (Oliger and Sundström (1978), Staniforth (1997)) and mismatch between the solution of the global and regional models in the nesting region (Davies (1976), Marbaix et al (2003), Harris and Durran (2010). These inconsistencies can result in the regional and global simulations diverging toward different climate states (Jones et al 1995).…”

Section: Introductionmentioning

confidence: 99%

Exploring a Multiresolution Modeling Approach within the Shallow-Water Equations

Ringler

Jacobsen

Gunzburger

et al. 2011

Monthly Weather Review

126

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The ability to solve the global shallow-water equations with a conforming, variable-resolution mesh is evaluated using standard shallow-water test cases. While our long-term motivation is the creation of a global climate modeling framework capable of resolving different spatial and temporal scales in different regions, we begin with an analysis of the shallow-water system in order to better understand the strengths and weaknesses of our approach. The multiresolution meshes are spherical centroidal Voronoi tessellations where a single, user-supplied density function determines the region(s) of fine-and coarse-mesh resolution. We explore the shallow-water system with a suite of meshes ranging from quasi-uniform resolution meshes, where grid spacing is globally uniform, to highly-variable resolution meshes, where grid spacing varies by a factor of 16 between the fine and coarse regions. We find that potential vorticity is conserved to within machine precision and total available energy is conserved to within time-truncation error. This finding holds for the full suite of meshes, ranging from quasi-uniform resolution and highly-variable resolution meshes. Using shallow-water test cases 2 and 5, we find that solution error is controlled primarily by the grid resolution in the coarsest part of the model domain. This finding is consistent with results obtained by others.When these variable resolution meshes are used for the simulation of an unstable zonal jet, we find that the core features of the growing instability are largely unchanged as the variation in mesh resolution increases. The main differences between the simulations occur outside the region of mesh refinement and these differences are attributed to the additional truncation error that accompanies increases in grid spacing. Overall, the results demonstrate support for this approach as a path toward multi-resolution climate system modeling.1

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Lateral Boundary Conditions in Regional Climate Models: A Detailed Study of the Relaxation Procedure

Cited by 102 publications

References 22 publications

Precipitation and snow cover in the Himalaya: from reanalysis to regional climate simulations

Precipitation and snow cover in the Himalaya: from reanalysis to regional climate simulations

Regional Climate Modeling: Progress, Challenges, and Prospects

Exploring a Multiresolution Modeling Approach within the Shallow-Water Equations

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