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Basivi Radhakrishna
Frédéric Fabry
John J. Braun
, and
Teresa Van Hove


The variation of precipitable water vapor (PW) over the continental United States is examined at various time scales using spatial maps of a column-averaged mixing ratio (CAMR) that is derived from integrated column PW from both observations and reanalysis data. CAMR spatial maps are generated utilizing PW measurements obtained from a network of ground-based global positioning system (GPS) receivers and the North American Regional Reanalysis (NARR) over a time span of 4 yr (February 2009–January 2013). The effect of topography on PW is mitigated by vertically averaging the mixing ratio instead of integrating the absolute humidity. An ordinary kriging interpolation technique is used to generate spatial maps of CAMR. The observed and predicted PW derived by GPS and NARR correlate well with each other at annual and monthly scales. When focusing on its diurnal cycle, moisture peaks in the late afternoon over the Great Plains and late night over the Rockies. It is also found that atmospheric moisture within NARR generally increases in the second half of the UTC day and is adjusted significantly lower when external observations, such as radiosondes, are assimilated into the analysis system. These adjustments in the analysis introduce nonphysical offsets that are not present within the GPS-derived moisture fields. At meso-β and meso-α scales, GPS PW fields can be used as a precursor to forecast convection up to 3 h prior to initiation. As stated previously, the correlation between GPS and NARR is high (>0.98) at monthly and seasonal time scales, but there is poor correlation at time scales less than a day. This indicates that the water budget within NARR is not in proper balance over these short-term time scales. Over the continental United States, daily cycles of PW and precipitation are coupled differently in different areas.

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