作者: T. Leblanc , T. D. Walsh , I. S. McDermid , G. C. Toon , J.-F. Blavier
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摘要: The Measurements of Humidity in the Atmosphere and Validation Experiment (MOHAVE) 2009 campaign took place on 11-27 October at JPL Table Mountain Facility California (TMF). main objectives were to (1) validate water vapor measurements several instruments, including, three Raman lidars, two microwave radiometers, Fourier-Transform spectrometers, GPS receivers (column water), (2) cover from ground mesopause without gaps, (3) study upper tropospheric humidity variability timescales varying a few minutes days. A total 58 radiosondes 20 Frost-Point hygrometer sondes launched. Two types used during campaign. Non negligible differences readings between radiosonde (Vaisala RS92 InterMet iMet-1) made small, but measurable impact derivation mixing ratio by hygrometers. As observed previous campaigns, remained within 5 % Frost-point lower mid-troposphere, too dry troposphere. Over 270 h lidars (JPL GSFC) compared RS92, CFH, NOAA-FPH. lidar profiles reached km when integrated all night, 15 for 1 h. Excellent agreement this frost-point hygrometers was found throughout measurement range, with only 3 (0.3 ppmv) mean wet bias troposphere stratosphere (UTLS). other provided satisfactory results mid-troposphere (2-5 over range 3-10 km), suffered contamination fluorescence (wet ranging 50 10 preventing their use as an independent UTLS. comparison available stratospheric sounders allowed identify largest biases, particular Water Vapor Millimeter-wave Spectrometer Aura-Microwave Limb Sounder. No large, or least statistically significant, biases could be observed. Total Precipitable (TPW) six different co-located instruments available. Several retrieval groups own TPW retrievals, resulting datasets. Agreement 7 (0.7 mm) Such good illustrates maturity these raises confidence levels alternate complementary source calibration lidars. Tropospheric ozone temperature also measurements, together advected potential vorticity high-resolution transport model MIMOSA, identification deep intrusion TMF. These observations demonstrated strong future long-term monitoring