Multisensor analysis of integrated atmospheric water vapor over Canada and Alaska



[1] Atmospheric water vapor is a key parameter for the analysis of climatic systems (greenhouse gas effect), in particular over high latitudes where water vapor displays an important seasonal variability. The sparse spatial and temporal sampling of atmospheric water vapor observations across Canada needs to be improved. A series of instruments and methods including a 940-nm solar absorption band radiometer (R) and radiosonde (S) analysis from a numerical weather prediction model and a ground-based bi-frequency Global Positioning System (GPS) were used to evaluate the integrated atmospheric water vapor (IWV) at various sites in Canada and Alaska from a multiyear database. The IWV-R measurements were collected within the framework of the North American Sun Radiometry network (AERONET/AEROCAN). Intercomparisons between [IWV-GPS and IWV-S], [IWV-R and IWV-GPS], and [IWV-R and IWV-S] show root mean square (RMS) differences of 1.8, 1.9, and 2.2 kg m−2, respectively. GPS meteorology appears to be the easiest approach to calibrate the solar radiometer water vapor band owing to its flexibility, and it allows us to overcome the Sun radiometry limitation in high-latitude areas like the Arctic. The sensitivity of the GPS retrieval to various parameters like GPS satellite constellation and meteorological data are discussed. The classical linear relationship between the surface temperature and the integrated weighted mean temperature profile needed for IWV-GPS retrieval may be significantly different for Arctic air masses compared with midlatitude air masses in the case of tropospheric temperature profile inversion. An ever-expanding multiyear (1994–2001) North American summer water vapor climatology, derived from AERONET/Canadian Sun Radiometer Network, is presented and analyzed, showing a mean value of 19.8 ± 6.1 kg m−2 and variations from 17 kg m−2 in Alaska to 23 kg m−2 in southeastern Canada. The results in Bonanza Creek, Alaska, show significant interannual variations with a peak in 1997, which may be linked to an El Niño event that occurred in the same year. Such a database may also be useful for climate model validation as shown for the Canadian Global Environmental Model (RMS difference of 3.4 kg m−2). In the end we show that, even if data are selected only for cloud-free atmospheres, there are no significant differences as compared with radiosonde climatology at Canadian Northwestern sites (≤3% relatively to Bonanza Creek summer mean value).