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Signals from the south; humpback whales carry messages of Antarctic sea‐ice ecosystem variability
John Wiley & Sons
2018
Signatures of climate tele-connection patterns in geophysical data series from Northern Scandinavia. NILU F
2003
2012
Simplified models for integrated air quality management in urban areas. NATO science for peace and security series
2008
Interdecadal change in the relationship between the East Asian winter monsoon (EAWM) and the Arctic Oscillation (AO) has been documented by many studies. This study, utilizing the model outputs from phase 5 of the Coupled Model Intercomparison Project (CMIP5), evaluates the ability of the coupled models in CMIP5 to capture the intensified relationship between the EAWM and winter AO since the 1980s, and further projects the evolution of the EAWM–AO relationship during the 21st century. It is found that the observed evolution of the EAWM–AO relationship can be reproduced well by some coupled models (e.g., GFDL-ESM2M, GISS-E2-H, and MPI-ESM-MR). The coupled models’ simulations indicate that the impact of winter AO on the EAWM-related circulation and East Asian winter temperature has strengthened since the 1980s. Such interdecadal change in the EAWM–AO relationship is attributed to the intensified propagation of stationary planetary waves associated with winter AO. Projections under the RCP4.5 and RCP8.5 scenarios suggest that the EAWM–AO relationship is significant before the 2030s and after the early 2070s, and insignificant during the 2060s, but uncertain from the 2030s to the 2050s.
Science Press
2018
2005
Simulating CH4 and CO2 over South and East Asia using the zoomed chemistry transport model LMDz-INCA
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.
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