Relationship between synoptic scale weather systems and column averaged atmospheric CO2
Abstract
Analysis of the atmospheric CO2 observations with transport models contributes to the understanding of the geographical distributions of CO2 sources and sinks. Space-borne sensors could be advantageous for CO2 measurements as they can provide wider spatial and temporal coverage. Inversion studies have suggested requirement of better than 1% precision for the space-borne observations. Since sources and sinks are inferred from spatial and temporal gradients in CO2, the space-borne observations must have no significant geographically varying biases. To study the dynamical biases in column CO2 due to possible correlation between clouds and atmospheric CO2 at synoptic scale, we have made simulations of CO2 (1988-2003) using NIES tracer transport model. Model resolution is 2.5o x 2.5o in horizontal and it has 15 vertical sigma-layers. Fluxes for (1) fossil fuels, (2) terrestrial biosphere (CASA NEP), (3) the oceans, and (4) inverse model derived monthly regional fluxes from 11 land and 11 ocean regions are used. SVD truncation is used to filter out noise in the inverse model flux time series. Model reproduces fairly well CO2 global trend and observed time series at monitoring sites around the globe. Lower column CO2 concentration is simulated inside cyclonic systems in summer over North hemispheric continental areas. Surface pressure is used as a proxy for dynamics and it is demonstrated that anomalies in column averaged CO2 has fairly good correlation with the anomalies in surface pressure. Positive correlation, as high as 0.7, has been estimated over parts of Siberia and N. America in summer time. Our explanation is based on that the low-pressure system is associated the upward motion, which leads to lower column CO2 values over these regions due to lifting of CO2-depleted summertime PBL air, and higher column CO2 over source areas. A sensitivity study without inverse model fluxes shows same correlation. The low-pressure systems' induced negative biases are 0.4-0.6 ppmv in summer over Siberia. Therefore it is essential to consider this bias due to covariance with vertical motion, while analyzing the column CO2 from space-borne observations together with in-situ observations, because most optical observations are not available under cloudy conditions typical for the low-pressure system.
- Publication:
-
AGU Fall Meeting Abstracts
- Pub Date:
- December 2005
- Bibcode:
- 2005AGUFM.A13G..07N
- Keywords:
-
- 0300 ATMOSPHERIC COMPOSITION AND STRUCTURE;
- 0315 Biosphere/atmosphere interactions (0426;
- 1610);
- 0322 Constituent sources and sinks;
- 1610 Atmosphere (0315;
- 0325);
- 1615 Biogeochemical cycles;
- processes;
- and modeling (0412;
- 0414;
- 0793;
- 4805;
- 4912)