Showing papers by "Peter Bergamaschi published in 2006"

Satellite chartography of atmospheric methane from SCIAMACHY on board ENVISAT: Analysis of the years 2003 and 2004

Abstract: The UV/Vis/near infrared spectrometer SCIAMACHY on board the European ENVISAT satellite enables total column retrieval of atmospheric methane with high sensitivity to the lower troposphere. The vertical column density of methane is converted to column averaged mixing ratio by using carbon dioxide retrievals as proxy for the probed atmospheric column. For this purpose, we apply concurrent total column measurements of CO_2 in combination with modeled column-averaged CO_2 mixing ratios. Possible systematic errors are discussed in detail while the precision error is 1.8% on average. This paper focuses on methane retrievals from January 2003 through December 2004. The measurements with global coverage over continents are compared with model results from the chemistry–transport model TM4. In the retrievals, the north-south gradient as well as regions with enhanced methane levels can be clearly identified. The highest abundances are found in the Red Basin of China, followed by northern South America, the Gangetic plains of India and central parts of Africa. Especially the abundances in northern South America and the Red Basin are generally higher than modeled. Further, we present the seasonal variations within the investigated time period. Peak values in Asia due to rice emissions are observed from August through October. We expand earlier investigations that suggest underestimated emissions in the tropics. It is shown that these underestimations show a seasonal behavior that peaks from August through December. The global measurements may be used for inverse modeling and are thus an important step towards better quantification of the methane budget.

Atmospheric carbon gases retrieved from SCIAMACHY by WFM-DOAS: version 0.5 CO and CH 4 and impact of calibration improvements on CO 2 retrieval

Abstract: . The three carbon gases carbon monoxide (CO), carbon dioxide (CO2), and methane (CH4) are important atmospheric constituents affecting air quality and climate. The near-infrared nadir spectra measured by SCIAMACHY on ENVISAT contain information on the vertical columns of these gases which we retrieve using a modified DOAS algorithm (WFM-DOAS or WFMD). Our main data products are CO vertical columns and dry-air column averaged mixing ratios of methane (CH4) and CO2 (denoted XCH4 and XCO2). For CO and CH4 we present new results for the year 2003 obtained with an improved version of WFM-DOAS (WFMDv0.5) retrieved from Level 1 version 4 (Lv1v4) spectra. This data set has recently been compared with a network of ground based FTIR stations. Here we describe the WFMDv0.5 algorithm, present global and regional maps, and comparisons with global reference data. We show that major problems of the previous versions (v0.4 and v0.41) related to the varying ice-layer on the SCIAMACHY channel 8 detector have been solved. Compared to MOPITT the SCIAMACHY CO columns are on average higher by about 10–20%. Regionally, however, especially over central South America, differences can be much larger. For methane we present global and regional maps which are compared to TM5 model simulations performed using standard methane emission inventories. We show that methane source regions can be clearly detected with SCIAMACHY. We also show that the methane data product can be significantly further improved using Lv1v5 spectra with improved calibration. For CO2 we present three years of SCIAMACHY CO2 measurements over Park Falls, Wisconsin, USA, retrieved from Lv1v5. We show that the quality of CO2 retrieved from these spectra is significantly higher compared to WFMDv0.4 XCO2 retrieved from Lv1v4.

Atmospheric carbon gases retrieved from SCIAMACHY by WFM-DOAS: improved global CO and CH 4 and initial verification of CO 2 over Park Falls (46° N, 90° W)

Abstract: The three carbon gases carbon monoxide (CO), carbon dioxide (CO 2 ), and methane (CH 4 ) are important atmospheric constituents affecting air quality and climate. The nadir spectra of reflected and scattered solar radiation in the near-infrared region, as observed by SCIAMACHY/ENVISAT, contain information on the vertical columns of these gases. A modified DOAS algorithm (WFM-DOAS) has been developed to retrieve this information. The main SCIAMACHY/WFM-DOAS data products are CO vertical columns and dry-air column averaged mixing ratios of methane and CO 2 , denoted XCH 4 and XCO 2 , respectively. For CO and methane we present new results obtained with an improved version of WFM-DOAS (v0.5). The SCIAMACHY data products have been compared with global reference data (MOPITT for CO, TM5 model simulations for XCH 4 ). The comparisons indicate that major problems of the previous version of WFM-DOAS (v0.4x) related to the varying ice-layer on the SCIAMACHY channel 8 detector have been solved. On average, the SCIAMACHY CO agrees within 10% (standard deviation 30%) with MOPITT but regionally, especially over northern South America, large differences have been found (up to about 80%). For methane we present global and regional maps which are compared to TM5 model simulations performed using standard emission inventories. Overall, there is good agreement but regionally there are substantial differences, e.g., due to limitations of current methane emission inventories. It still needs to be assessed by how much emission inventories can be improved by using the SCIAMACHY data. Concerning CO 2 we present a comparison of SCIAMACHY XCO 2 (WFM-DOAS v0.4) with TM3 model simulations over Park Falls, Wisconsin, USA. The peak-to-peak XCO 2 variability as measured by SCIAMACHY (seasonal cycle of year 2003?2005 data) is ~13 ppmv, in good agreement with preliminary analysis of ground-based Fourier Transform Spectrometer (FTS) measurements, which is a factor of 2.3 larger than the XCO 2 variability of TM3 model simulation for 2003. Park Falls is one of the few FTS ground stations which measure column averaged CO 2 and detailed comparison with these measurements (after data release) will help identifying the reason for the observed differences between SCIAMACHY and global (atmospheric) carbon models such as TM3 as reported here and in previous studies. For all three carbon gases we present regional results including seasonal variation focusing on China.