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McFarlane, S

Publications and source records attributed to McFarlane, S.

4 records
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DOE OSTI2011

ARM Climate Research Facility Spectral Surface Albedo Value-Added Product (VAP) Report

This document describes the input requirements, output data products, and methodology for the Spectral Surface Albedo (SURFSPECALB) value-added product (VAP). The SURFSPECALB VAP produces a best-estimate near-continuous high spectral resolution albedo data product using measurements from multifilter radiometers (MFRs). The VAP first identifies best estimates for the MFR downwelling and upwelling shortwave irradiance values, and then calculates narrowband spectral albedo from these best-estimate irradiance values. The methodology for finding the best-estimate values is based on a simple process of screening suspect data and backfilling screened and missing data with estimated values when possible. The resulting best-estimate MFR narrowband spectral albedos are used to determine a daily surface type (snow, 100% vegetation, partial vegetation, or 0% vegetation). For non-snow surfaces, a piecewise continuous function is used to estimate a high spectral resolution albedo at 1 min temporal and 10 cm-1 spectral resolution.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2011

Radiatively Important Parameters Best Estimate (RIPBE): An ARM Value-Added Product

The Radiatively Important Parameters Best Estimate (RIPBE) VAP was developed to create a complete set of clearly identified set of parameters on a uniform vertical and temporal grid to use as input to a radiative transfer model. One of the main drivers for RIPBE was as input to the Broadband Heating Rate Profile (BBHRP) VAP, but we also envision using RIPBE files for user-run radiative transfer codes, as part of cloud/aerosol retrieval testbeds, and as input to averaged datastreams for model evaluation.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2011

ARM MJO Investigation Experiment on Gan Island (AMIE-Gan) Science Plan

The overarching campaign, which includes the ARM Mobile Facility 2 (AMF2) deployment in conjunction with the Dynamics of the Madden-Julian Oscillation (DYNAMO) and the Cooperative Indian Ocean experiment on intraseasonal variability in the Year 2011 (CINDY2011) campaigns, is designed to test several current hypotheses regarding the mechanisms responsible for Madden-Julian Oscillation (MJO) initiation and propagation in the Indian Ocean area. The synergy between the proposed AMF2 deployment with DYNAMO/CINDY2011, and the corresponding funded experiment on Manus, combine for an overarching ARM MJO Investigation Experiment (AMIE) with two components: AMF2 on Gan Island in the Indian Ocean (AMIE-Gan), where the MJO initiates and starts its eastward propagation; and the ARM Manus site (AMIE-Manus), which is in the general area where the MJO usually starts to weaken in climate models. AMIE-Gan will provide measurements of particular interest to Atmospheric System Research (ASR) researchers relevant to improving the representation of MJO initiation in climate models. The framework of DYNAMO/CINDY2011 includes two proposed island-based sites and two ship-based locations forming a square pattern with sonde profiles and scanning precipitation and cloud radars at both island and ship sites. These data will be used to produce a Variational Analysis data set coinciding with the one produced for AMIE-Manus. The synergy between AMIE-Manus and AMIE-Gan will allow studies of the initiation, propagation, and evolution of the convective cloud population within the framework of the MJO. As with AMIE-Manus, AMIE-Gan/DYNAMO also includes a significant modeling component geared toward improving the representation of MJO initiation and propagation in climate and forecast models. This campaign involves the deployment of the second, marine-capable, AMF; all of the included measurement systems; and especially the scanning and vertically pointing radars. The campaign will include sonde launches at a rate of eight per day for the duration of the deployment. The increased sonde launches for the entire period matches that of the AMIE-Manus campaign and makes possible a far more robust Variational Analysis forcing data set product for the entire campaign, and thus better capabilities for modeling studies and synergistic research using the data from both AMIE sites.

54 ENVIRONMENTAL SCIENCES↗