非表示:
キーワード:
-
要旨:
This study presents results from the European Centre for Medium-RangeWeather Forecasts (ECMWF) carbon
dioxide (CO2) analysis system where the atmospheric
CO2 is controlled through the assimilation of columnaveraged
dry-air mole fractions of CO2 (XCO2) from the
Greenhouse gases Observing Satellite (GOSAT). The analysis
is compared to a free-run simulation (without assimilation
of XCO2), and they are both evaluated against XCO2
data from the Total Carbon Column Observing Network (TCCON).
We show that the assimilation of the GOSAT XCO2
product from the Bremen Optimal Estimation Differential
Optical Absorption Spectroscopy (BESD) algorithm during
the year 2013 provides XCO2 fields with an improved mean
absolute error of 0.6 parts per million (ppm) and an improved
station-to-station bias deviation of 0.7 ppm compared to the
free run (1.1 and 1.4 ppm, respectively) and an improved estimated
precision of 1 ppm compared to the GOSAT BESD
data (3.3 ppm). We also show that the analysis has skill for
synoptic situations in the vicinity of frontal systems, where
the GOSAT retrievals are sparse due to cloud contamination.
We finally computed the 10-day forecast from each analysis
at 00:00 UTC, and we demonstrate that the CO2 forecast
shows synoptic skill for the largest-scale weather patterns (of
the order of 1000 km) even up to day 5 compared to its own analysis.
