Seasonal variation of carbon monoxide in northern Japan: Fourier transform IR measurements and source-labeled model calculations

Tropospheric carbon monoxide (CO) was measured throughout 2001 using groundbased Fourier transform IR (FTIR) spectrometers at Moshiri 44.4N and Rikubetsu 43.5N) observatories in northern Japan, which are separated by 150 km. Seasonal and day-to-day variations of CO are studied using these data, and contributions from various CO sources are evaluated using three-dimensional global chemistry transport model (GEOS-CHEM) calculations. Seasonal maximum and minimum FTIR-derived tropospheric CO amounts occurred in April and September, respectively. The ratio of partial column amounts between the 0–4 and 0–12 km altitude ranges is found to be slightly greater in early spring. The GEOS-CHEM model calculations generally reproduce these observed features. Source-labeled CO model calculations suggest that the observed seasonal variation is caused by seasonal contributions from various sources, in addition to a seasonal change in chemical CO loss by OH. Changes in meteorological fields largely control the relative importance of various source contributions. The contributions from fossil fuel (FF) combustion in Asia and photochemical CO production have the greatest yearly averaged contribution at 1 km among the CO sources (31% each). The Asian FF contribution increases from winter to summer, because weak southwesterly wind in summer brings more Asian pollutants to the observation sites. The seasonal variation from photochemical CO production is small (±17% at 1 km), likely because of concurrent increases (decreases) of photochemical production and loss rates in summer (winter), with the largest contribution between August and December. The contribution from intercontinental transport of European FF combustion CO is found to be comparable to that of Asian FF sources in winter. Northwesterly wind around the Siberian high in this season brings pollutants from Europe directly to Japan, in addition to southward transport of accumulated pollution from higher latitudes. The influences are generally greater at lower altitudes, resulting in a vertical gradient in the CO profile during winter. The model underestimates total CO by 12–14% between March and June. Satellite-derived fire-count data and the relationship between FTIR-derived HCN and CO amounts are generally consistent with biomass burning influences, which could have been underestimated by the model calculations

Atmospheric carbon dioxide retrieved from the Greenhouse gases Observing SATellite (GOSAT): Comparison with ground-based TCCON observations and GEOS-Chem model calculations

We retrieved column-averaged dry air mole fractions of atmospheric carbon dioxide (X_CO_2) from backscattered short-wave infrared (SWIR) sunlight measured by the Japanese Greenhouse gases Observing SATellite (GOSAT). Over two years of X_CO_2 retrieved from GOSAT is compared with X_CO_2 inferred from collocated SWIR measurements by seven ground-based Total Carbon Column Observing Network (TCCON) stations. The average difference between GOSAT and TCCON X_CO_2 for individual TCCON sites ranges from −0.87 ppm to 0.77 ppm with a mean value of 0.1 ppm and standard deviation of 0.56 ppm. We find an average bias between all GOSAT and TCCON X_CO_2 retrievals of −0.20 ppm with a standard deviation of 2.26 ppm and a correlation coefficient of 0.75. One year of XCO2 was retrieved from GOSAT globally, which was compared to global 3-D GEOS-Chem chemistry transport model calculations. We find that the latitudinal gradient, seasonal cycles, and spatial variability of GOSAT and GEOS-Chem agree well in general with a correlation coefficient of 0.61. Regional differences between GEOS-Chem model calculations and GOSAT observations are typically less than 1 ppm except for the Sahara and central Asia where a mean difference between 2 to 3 ppm is observed, indicating regional biases in the GOSAT X_CO_2 retrievals unobserved by the current TCCON network. Using a bias correction scheme based on linear regression these regional biases are significantly reduced, approaching the required accuracy for surface flux inversions

An intercomparison and evaluation of aircraft-derived and simulated CO from seven chemical transport models during the TRACE-P experiment

Four global scale and three regional scale chemical transport models are intercompared and evaluated during NASA's Transport and Chemical Evolution over the Pacific (TRACE-P) experiment. Model simulated and measured CO are statistically analyzed along aircraft flight tracks. Results for the combination of 11 flights show an overall negative bias in simulated CO. Biases are most pronounced during large CO events. Statistical agreements vary greatly among the individual flights. Those flights with the greatest range of CO values tend to be the worst simulated. However, for each given flight, the models generally provide similar relative results. The models exhibit difficulties simulating intense CO plumes. CO error is found to be greatest in the lower troposphere. Convective mass flux is shown to be very important, particularly near emissions source regions. Occasionally meteorological lift associated with excessive model-calculated mass fluxes leads to an overestimation of middle and upper tropospheric mixing ratios. Planetary Boundary Layer (PBL) depth is found to play an important role in simulating intense CO plumes. PBL depth is shown to cap plumes, confining heavy pollution to the very lowest levels