Issue 10 Volume 41 May 16, 2003

20030036993 Pacific Northwest National Lab., Richland, WA
Best Estimate Radiation Flux Value Added Product: Algorithm Operational Details and Explanations
Shi, Y.; Long, C. N.; Oct. 2002; In English
Report No.(s): PB2003-102677; ARM-TR-008; No Copyright; Avail: National Technical Information Service (NTIS)
This document describes some specifics of the algorithm for best estimate evaluation of radiation fluxes at Southern Great
Plains (SGP) Central Facility (CF). It uses the data available from the three co-located surface radiometer platforms at the SGP
CF to automatically determine the best estimate of the irradiance measurements available. The Best Estimate Flux (BEFlux)
value added product (VAP) was previously named Best Estimate ShortWave (BESW) VAP, which included all of the
broadband and spectral shortwave (SW) measurements for the SGP CF. In BESW, multiple measurements of the same
quantities, were handled simply by designating one as the primary measurement and using all others to merely fill in any gaps.
Thus, this BESW is better termed most continuous, since no additional quality assessment was applied. We modified the
algorithm in BESW to use the average of the closest two measurements as the best estimate when possible, if these
measurements pass all quality assessment criteria.
NTIS
Algorithms; Remote Sensing; Radiometers; Climatology; Heat Flux; Short Wave Radiation
20030036996 Pennsylvania State Univ., University Park, Brookhaven National Lab., Upton, NY, Pacific Northwest National
Lab., Richland, WA
ARM Millimeter Wave Cloud Radars (MMCRs) and the Active Remote Sensing of Clouds (ARSCL) Value Added
Product (VAP)
Clothiaux, E. E.; Miller, M. A.; Perez, R. C.; Turner, D. D.; Moran, K. P.; Mar. 04, 2001; 60 pp.; In English
Report No.(s): PB2003-102678; DOE/TM-ARM-VAP-002-1; No Copyright; Avail: CASI; A04, Hardcopy
The Millimeter Wave Cloud Radars (MMCRs) are designed as a remote sensing tool that can accurately detect almost all
of the hydrometeors present in the atmosphere. To illustrate the difficulty of this task, the various types of hydrometeors that
can occur in the atmosphere are considered in the context of detection by the MMCRs. Having outlined the nature of the
remote sensing problem, a discussion ensues of the NOAA Environmental Technology Laboratory (ETL) design of the
MMCR. Next, we present the operational modes of the MMCRs and discuss them in some detail to illustrate the nature of
the cloud products that are, and will be, derived from the MMCRs on a continuous basis.
NTIS
Remote Sensing; Clouds (Meteorology)
20030037179 Lawrence Livermore National Lab., Livermore, CA
Intercomparison of Climate Data Sets as a Measure of Observational Uncertainty
Feb. 22, 2002; In English
Report No.(s): DE2002-15002142; UCRL-ID-147371; No Copyright; Avail: National Technical Information Service (NTIS)
Uncertainties in climate observations are revealed when alternate observationally based data sets are compared. General
circulation model-based ‘reanalyses’ of meteorological observations will yield different results from different models, even if
identical sets of raw unanalyzed data form their starting points. We have examined 25 longitude-latitude fields (including
selected levels for three-dimensional quantities) encompassing atmospheric climate variables for which the PCMDI
observational data base contains two or more high-quality sources. For the most part we compare ECMWF with NCEP
reanalysis. In some cases, we compare in situ and/or satellite-derived data with reanalysis. To obtain an overview of the
differences for all 25 fields, we use a graphical technique developed for climate model diagnosis: a ‘portrait diagram’
displaying root-mean-square differences between the alternate data sources. With a few exceptions (arising from the
requirement that RMS differences be normalized to accommodate different units of variables) the portrait diagrams indicate
areas of agreement and disagreement that can be confirmed by examining traditional graphics such as zonal mean plots. In
accord with conventional wisdom, the greatest agreement between alternate data sets - hence the smallest implied
observational uncertainty - occurs for upper tropospheric zonal wind. We also find fairly good agreement between reanalysis
and more direct measures of precipitation, suggesting that modern observational systems are resolving some longstanding
problems with its measurement.
NTIS
Climate Models; Data Processing
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