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Progress on the Use of Combined Analog and Photon Counting Detection for Raman Lidar

The Atmospheric Radiation Measurement (ARM) program Raman Lidar (CARL) was upgraded in 2004 with a new data system that provides simultaneous measurements of both the photomultiplier analog output voltage and photon counts. The so-called merge value added procedure (VAP) was developed to combine the analog and count-rate signals into a single signal with improved dynamic range. Earlier versions of this VAP tended to cause unacceptably large biases in the water vapor mixing ratio during the daytime as a result of improper matching between the analog and count-rate signals in the presence of elevated solar background levels. We recently identified several problems and tested a modified version of the merge VAP by comparing profiles of water vapor mixing ratio derived from CARL with simultaneous sonde data over a six month period. We show that the modified merge VAP significantly reduces the daytime bias, and results in mean differences that are within approximately 1% for both nighttime and daytime measurements.

Newsom, Rob↗

Satellite and Surface Data Synergy for Developing a 3D Cloud Structure and Properties Characterization Over the ARM SGP. Stage 1: Cloud Amounts, Optical Depths, and Cloud Heights Reconciliation

One of the primary Atmospheric Radiation Measurement (ARM) Program objectives is to obtain measurements applicable to the development of models for better understanding of radiative processes in the atmosphere. We address this goal by building a three-dimensional (3D) characterization of the cloud structure and properties over the ARM Southern Great Plains (SGP). We take the approach of juxtaposing the cloud properties as retrieved from independent satellite and ground-based retrievals, and looking at the statistics of the cloud field properties. Once these retrievals are well understood, they will be used to populate the 3D characterization database. As a first step we determine the relationship between surface fractional sky cover and satellite viewing angle dependent cloud fraction (CF). We elaborate on the agreement intercomparing optical depth (OD) datasets from satellite and ground using available retrieval algorithms with relation to the CF, cloud height, multi-layer cloud presence, and solar zenith angle (SZA). For the SGP Central Facility, where output from the active remote sensing cloud layer (ARSCL) valueadded product (VAP) is available, we study the uncertainty of satellite estimated cloud heights and evaluate the impact of this uncertainty for radiative studies.

Genkova, I.↗