The NASA Goddard Space Flight Center (GSFC) Scanning Raman Lidar (SRL) participated in the International H2O Project (IHOP), which occurred in May and June 2002 in the midwestern part of the United States. The SRL received extensive optical modifications prior to and during the IHOP campaign that added new measurement capabilities and enabled unprecedented daytime water vapor measurements by a Raman lidar system. Improvements were also realized in nighttime upper-tropospheric water vapor measurements. The other new measurements that were added to the SRL for the IHOP deployment included rotational Raman temperature, depolarization, cloud liquid water, and cirrus cloud ice water content. In this first of two parts, the details of the operational configuration of the SRL during IHOP are provided along with a description of the analysis and calibration procedures for water vapor mixing ratio, aerosol depolarization, and cirrus cloud extinction-to-backscatter ratio. For the first time, a Raman water vapor lidar calibration is performed, taking full account of the temperature sensitivity of water vapor and nitrogen Raman scattering. Part II presents case studies that permit the daytime and nighttime error statistics to be quantified.

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

We have investigated a technique that allows for the independent determination of the water vapor mixing ratio calibration factor for a Raman lidar system. This technique utilizes a procedure whereby a light source of known spectral characteristics is scanned across the aperture of the lidar system's telescope and the overall optical efficiency of the system is determined. Direct analysis of the temperature-dependent differential scattering cross sections for vibration and vibration-rotation transitions (convolved with narrowband filters) along with the measured efficiency of the system, leads to a theoretical determination of the water vapor mixing ratio calibration factor. A calibration factor was also obtained experimentally from lidar measurements and radiosonde data. A comparison of the theoretical and experimentally determined values agrees within 5%. We report on the sensitivity of the water vapor mixing ratio calibration factor to uncertainties in parameters that characterize the narrowband transmission filters, the temperature-dependent differential scattering cross section, and the variability of the system efficiency ratios as the lamp is scanned across the aperture of the telescope used in the Howard University Raman Lidar system.

A semianalytic Monte Carlo radiative transfer model (SALMON) has been developed which is particularly well-suited for addressing oceanographic lidar systems. SALMON is based on the method of expected values in which an analytical estimate is made of the probability of collection by a remote receiver of scattered or emitted photons at appropriate points in the stochastically constructed underwater photon trajectory. Sample results indicate that a substantial reduction in both variance and computer resources can be realized by using SALMON, as compared with more conventional Monte Carlo approaches, to study radiative transfer mechanisms associated with lidar systems.

IntroductionWater vapor is an important constituent of the atmosphere. The vertical distribution of moisture is important in determining atmospheric stability. Water vapor is also the most radiatively active atmospheric trace gas in the infrared (Ramanathan 1988) and thus could produce strong forcing from feedback associated with anthropogenically driven climate change (Cess 1990). In addition, there is significant variability in the distribution of water vapor on temporal and spatial scales smaller than is currently being measured by the standard techniques Howard University Raman Lidar