The Greenhouse Effect is a natural phenomenon that warms up the earth. It works on the same principles as the ordinary garden glasshouse, which allows the light to get in, but does not allow the heat to get out. The earth is surrounded by a shield of atmospheric gases primarily nitrogen (78 %), and oxygen (21%). The remainder of the air composition is made up of what are called as “trace gases,” which include carbon dioxide (CO₂), methane (CH₄) etc. The earth maintains its temperature through insulation with a 'thermal blanket' of greenhouse gases which allow penetration of the sun's rays but prevent some heat radiating back into space. Light from the sun penetrates the atmosphere and reaches the earth surface, warming it up.

The remote sensing of CO₂ from satellites is an exciting new and rapidly developing field in carbon cycle research. Satellite sensors have the potential to provide a wealth of information on atmospheric CO₂, covering many regions that are scarsely monitored the ground based observational networks. Satellite measurements could significantly strengthen the power of inverse modelling computations in tracing sources and sinks of CO₂. The main challenge, however, is to reach the measurement accuracy needed to resolve the important CO₂ concentration gradients. The current generation of satellite instruments from which CO₂ can be retrieved is expected to meet the requirements only partly, as the instruments were not originally designed to measure CO₂. Nevertheless interesting results come out as we will show for the Sciamachy instrument. A particularly difficult aspect is the determination of the airmass factor, which is needed to translate the observed optical thickness into a column averaged dry air mixing ratio. The airmass factor is influenced by e.g. clouds, aerosols, air pressure, and orography. So far the uncertainty assessments have mainly relied on theoretical investigations and ground-based measurements. The measurements from Sciamachy allow us to verify these studies, and some of the methods that have been proposed to reduce or eliminate the errors. We will demonstrate this with the main focus on aerosols. Error assessments using in-flight data will be indispensable for improving future instruments.

We consider the ability of an inverse model framework and observations from the Cooperative Air Sampling Network to resolve fluxes at various scales over a 20-year period. During this time the observational network underwent a significant expansion. We calculate the resolution kernel to determine which continental/ocean basin scale fluxes may be resolved, and which spatial aggregations of fluxes are well resolved. In addition, the resolution kernel is used to obtain insights into how source regions are constrained by individual measurement sites.

Greenhouse gases Observing SATellite (GOSAT) of Japan is planned to be launched in 2008. GOSAT will be equipped with a FTS to monitor CO₂ column density globally. The FTS has three near infrared bands which cover 0.76 µm, 1.6 µm, and 2.0 µm spectral regions, respectively. Retrieval algorithms to estimate CO₂ and CH₄ column densities from these bands data are now being developed. We have investigated retrieval algorithms under the non-clear sky conditions. As one of these cases, a cirrus cloud parameter estimation was researched. The cirrus vertical profile (i.e., existing height) is estimated from the 0.76 µm band data. Strong water vapor absorption area is included in the 2.0 µm spectral band, so that the reflected radiance from a ground surface is absorbed completely by H₂O in this area. Thus the signal in this area is considered as path radiance caused by the cirrus clouds reflection, because there is little water vapor above the cirrus cloud top. By using this signal, the cirrus optical depth can be estimated, and then column densities of CO₂, CH₄ and H₂O are retrieved precisely.

Accurate estimates of the spatial distribution of pre-industrial and anthropogenic air-sea carbon fluxes are crucial to understanding the processes driving ocean carbon uptake. We present regional anthropogenic and pre-industrial air-sea fluxes estimated separately from their reconstructed concentrations and Ocean General Circulation Models (OGCM). The ocean interior carbon transports required to explain these fluxes are calculated and their implications for the global carbon cycle are discussed. 

A one-dimensional (1d) physical-biological-chemical model was developed and tested by Antoine and Morel [1995, AM95 hereafter], with the aim of assessing upper ocean carbon fluxes. This model was specifically designed to be driven by satellite data, and it was used to evaluate the upper ocean CO₂ fluxes at station P in the NE Pacific. Another validation of this model has been carried out at the DYFAMED station (NW Mediterranean), where time series of biological and physical observations are available. This validation is a first step before the basin-scale application to the Mediterranean Sea, as presented here for the period 1998-2000.

The ocean margins form the transition zone between terrestrial and open ocean areas and represent up to 30% of total ocean productivity, yet their role in the global carbon cycle is ill quantified. In order to address this issue, a bi-weekly time-series program was established in Santa Monica Bay in January 2003 to measure the seasonal evolution of the upper ocean carbon cycle at this coastal site. Our measurements reveal a strong seasonal cycle with an amplitude in salinity normalized dissolved inorganic carbon (DIC) reaching nearly 200 µmol/kg and pCO₂ changes of more than 200 µatm. The seasonal cycle of DIC is characterized by a maximum in late winter/early spring, which is caused by upwelling bringing high DIC concentrations from the upper thermocline during this time of the year. The concomitant supply of high levels of nutrients fuels an intense bloom, whose strength varies from year to year in response to large interannual variations in upwelling. In 2003 and 2004, substantial surface DIC decreases were observed under nitrate depleted conditions i) right after the occurrence of upwelling, and i) about three months after upwelling. This implies that during these times, either organic matter production occurred with a very high stoichiometric C:N ratio and/or an additional source of new nitrogen existed that supplied nitrogen without supplying DIC. The seasonal cycle of pCO₂ follows that of DIC with a late winter/early spring maximum, whose levels far exceed that of the atmosphere, and a summer-time minimum with undersaturated pCO₂ values. Annually, Santa Monica Bay acts as a weak to moderate sink for atmospheric CO₂. We suggest that this is mainly due to biological production and in part driven by the uptake of anthropogenic CO₂.

We estimate the natural and anthropogenic components of the air-sea flux of CO₂ in the Indian Ocean. The increase in atmospheric CO₂ driven by human activity has caused the air-sea CO₂ flux, to increase significantly over the industrial era. We estimate the flux in the year 1780 to be approximately 0.2Gt/yr, increasing by 0.26Gt/yr to 0.5Gt/yr in 2000. The estimate of the natural (preindustrial) flux is highly sensitive to uncertainties in modern-day CO₂ disequilibrium measurements. By contrast, the estimate of the anthropogenic flux is only weakly sensitive to these measurements. Our anthropogenic estimate is smaller than other studies due to the removal in our methodology of the widely made weak-mixing and constant-disequilibrium assumptions, both of which cause positive bias.