Simulating CH4 and CO2 over South and East Asia using the zoomed chemistry transport model LMDz-INCA
Authors: Lin Xin , Ciais Philippe , Bousquet Philippe , Ramonet Michel , Yin Yi , Balkanski Yves , Cozic Anne , Delmotte Marc , Evangeliou Nikolaos , Indira Nuggehalli K. , Locatelli Robin , Peng Shushi , Piao Shilong , Saunois Marielle , Swathi Panangady S. , Wang Rong , Yver-Kwok Camille , Tiwari Yogesh K. , Zhou Lingxi 
Published: July 2018

Abstract. The increasing availability of atmospheric measurements of
greenhouse gases (GHGs) from surface stations can improve the
retrieval of their fluxes at higher spatial and temporal resolutions
by inversions, provided that transport models are able to properly
represent the variability of concentrations observed at different
stations. South and East Asia (SEA; the study area in this paper including the regions of
South Asia and East Asia)
is a region with large and very
uncertain emissions of carbon dioxide (CO2) and methane
(CH4), the most potent anthropogenic GHGs. Monitoring
networks have expanded greatly during the past decade in this
region, which should contribute to reducing uncertainties in
estimates of regional GHG budgets. In this study, we simulate
concentrations of CH4 and CO2 using zoomed versions
(abbreviated as “ZAs”) of the global chemistry transport model
LMDz-INCA, which have fine horizontal resolutions of ∼0.66∘ in longitude and ∼0.51∘ in latitude
over SEA and coarser resolutions elsewhere. The concentrations of
CH4 and CO2 simulated from ZAs are compared to those
from the same model but with standard model grids of 2.50∘
in longitude and 1.27∘ in latitude (abbreviated as “STs”),
both prescribed with the same natural and anthropogenic
fluxes. Model performance is evaluated for each model version at
multi-annual, seasonal, synoptic and diurnal scales, against
a unique observation dataset including 39 global and regional
stations over SEA and around the world. Results show that ZAs
improve the overall representation of CH4 annual gradients
between stations in SEA, with reduction of RMSE by 16–20 %
compared to STs. The model improvement mainly results from reduction
in representation error at finer horizontal resolutions and thus
better characterization of the CH4 concentration gradients
related to scattered distributed emission sources. However, the
performance of ZAs at a specific station as compared to STs is more
sensitive to errors in meteorological forcings and surface fluxes,
especially when short-term variabilities or stations close to source
regions are examined. This highlights the importance of accurate
a priori CH4 surface fluxes in high-resolution transport
modeling and inverse studies, particularly regarding locations and
magnitudes of emission hotspots. Model performance for CO2
suggests that the CO2 surface fluxes have not been
prescribed with sufficient accuracy and resolution, especially the
spatiotemporally varying carbon exchange between land surface and
atmosphere. In addition, the representation of the CH4 and
CO2 short-term variabilities is also limited by model's
ability to simulate boundary layer mixing and mesoscale transport in
complex terrains, emphasizing the need to improve sub-grid physical
parameterizations in addition to refinement of model resolutions.