Impact of Terrain Altitude and Cloud Height on Ozone Remote Sensing from Satellite

Abstract

Terrain and cloud height heavily impact ozone information despite ozone being concentrated in the stratosphere. The ozone weighting function (OWF) provides important information towards understanding the capabilities and limitations of a given channel. The factors that impact the OWF can be analyzed using radiative transfer theory and modeling. At the 9.6-mm infrared spectral region, both the OWF values and peaks are related to the surface temperature, terrain altitude, and cloud height. Warmer surface temperatures, lower terrain altitude, or lower cloud levels will give larger weighting function values, and the peak of the weighting function slightly increases with the increase in surface temperature, terrain altitude, or cloud height. For longer UV bands such as 306 and 318 nm, OWF shows smaller values for higher terrains, while showing larger values when clouds are present. However, in the shorter UV bands such as 274 and 288 nm, OWF has almost no relationship with the surface and clouds. Therefore, with satellite-based infrared ozone remote sensing, high terrain and cloud presence will reduce ozone sensitivity and information content. In addition, for UV bands, the effect is spectrally dependent: lower terrain altitude and the presence of clouds will increase the zone information content in the longer UV band, but they have no effect in the short UV band. A simulation of an ozone retrieval in the infrared band shows that higher terrain results in lower precision for colder emitting surface temperatures and less ozone absorption signal.

Evaluation of Environmental Moisture from NWP Models with Measurements from Advanced Geostationary Satellite Imager—A Case Study

“…The Jacobians denote the change of top-of-atmosphere (TOA) radiance in response to unit perturbation in atmosphere or surface, i.e., WV content in certain level. It is very important and useful in moisture profile retrieval and is able to reflect the remote sensing capability and limitation of the given spectral bands [15,19,20]. In Figure 2, the 6.25 µm band (AHI, channel 8) detects WV at a higher atmospheric level around 300 hPa; the 6.95 µm band (AHI, channel 9) peaks at a lower level around 350 hPa, whereas the 7.35 µm band (AHI, channel 10) peaks at a lowest level around 480 hPa.…”

Performance of AIRS ozone retrieval over the central Himalayas: use of ozonesonde and other satellite datasets

“…Very sparse in situ and ground-based observations in this region, along with inadequate information on the surface parameters, make it difficult to retrieve the atmospheric composition from space-borne instruments. This is because the ozone weighting function, a measure of the retrieval sensitivity and a fundamental retrieval component, depends upon various atmospheric parameters like surface temperature, surface emissivity, and terrain height (Rodgers, 1976(Rodgers, , 1990Bai et al, 2014), which is not uniform over the footprint size of the Atmospheric Infrared Sounder (AIRS; ∼ 13 km × 13 km) in the Himalayas. Usually, the ozone weighting function has a shorter integrating path over the elevated terrain regions, which follows a smaller weighting function and provides less sensitivity and more errors in the final retrievals (Coheur et al, 2005;Bai et al, 2014).…”

Performance of AIRS ozone retrieval over the central Himalayas: Case studies of biomass burning, downward ozone transport and radiative forcing using long-term observations

“…Here, the in-situ ground-based observations are very sparse and limited, and complex topography along with inadequate information on the surface parameters make it difficult to retrieve atmospheric composition from space-borne instruments. This is because ozone weighting function, a measure of the retrieval sensitivity and a fundamental retrieval component, depends upon various atmospheric parameters like surface temperature, surface emissivity, and terrain height (Rodgers et al, 1976(Rodgers et al, , 1990Bai et al, 2014), which is not uniform over the foot-print size of the AIRS (~ 13 km x 13 km) over the Himalayas. Usually, the ozone weighting function has a shorter integrating path over the elevated terrain regions, which follows a smaller weighting function and provides lesser sensitivity and higher errors in the final retrievals (Coheur et al, 2005;Bai et al, 2014).…”

“…This is because ozone weighting function, a measure of the retrieval sensitivity and a fundamental retrieval component, depends upon various atmospheric parameters like surface temperature, surface emissivity, and terrain height (Rodgers et al, 1976(Rodgers et al, , 1990Bai et al, 2014), which is not uniform over the foot-print size of the AIRS (~ 13 km x 13 km) over the Himalayas. Usually, the ozone weighting function has a shorter integrating path over the elevated terrain regions, which follows a smaller weighting function and provides lesser sensitivity and higher errors in the final retrievals (Coheur et al, 2005;Bai et al, 2014). Apart from the terrain height, retrieval also depends on other factors like surface emissivity, atmospheric input constituents, input error minimizing parameters, etc., whose accuracy matters, alters the retrieval processes abruptly, and introduces error in the final retrieval.…”