High‐accuracy measurements of total column water vapor from the Orbiting Carbon Observatory‐2. Issue 23 (9th December 2016)

• Record Type: Journal Article
• Authors: Nelson, Robert R.; Crisp, David; Ott, Lesley E.; O'Dell, Christopher W.
• Is Part Of: Geophysical research letters. Volume 43:Issue 23(2016)
• Page Start: 12, 261
• Page End: 12, 269
• Publication Date: 2016-12-09
• Subjects: OCO‐2 -- water vapor -- TCWV -- remote sensing -- hyperspectral -- near‐infrared; Geophysics -- Periodicals; Planets -- Periodicals; Lunar geology -- Periodicals; 550
• DOI: 10.1002/2016GL071200
• Languages: English
• ISSNs: 0094-8276

Abstract

Abstract: Accurate knowledge of the distribution of water vapor in Earth's atmosphere is of critical importance to both weather and climate studies. Here we report on measurements of total column water vapor (TCWV) from hyperspectral observations of near‐infrared reflected sunlight over land and ocean surfaces from the Orbiting Carbon Observatory‐2 (OCO‐2). These measurements are an ancillary product of the retrieval algorithm used to measure atmospheric carbon dioxide concentrations, with information coming from three highly resolved spectral bands. Comparisons to high‐accuracy validation data, including ground‐based GPS and microwave radiometer data, demonstrate that OCO‐2 TCWV measurements have maximum root‐mean‐square deviations of 0.9–1.3mm. Our results indicate that OCO‐2 is the first space‐based sensor to accurately and precisely measure the two most important greenhouse gases, water vapor and carbon dioxide, at high spatial resolution (1.3 × 2.3 km 2 ) and that OCO‐2 TCWV measurements may be useful in improving numerical weather predictions and reanalysis products. Key Points: OCO‐2 can measure total column water vapor with high precision, accuracy, and spatial resolution over land and ocean surfaces OCO‐2 is the first space‐based sensor to accurately measure the two most important greenhouse gases, H2 O and CO2, at high spatial resolution OCO‐2 water vapor measurements may be useful in improving numerical weather predictions and acting as a validation source for other sensors