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Last modified
7/28/2009 2:35:57 PM
Creation date
4/15/2008 2:39:24 PM
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Weather Modification
Title
Comparison of Cloud Model Predictions: A Case Study Analysis of One- and Two-Dimensional Models
Date
6/11/1975
Weather Modification - Doc Type
Report
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<br />Verification data requirements, listed <br />in general order of priority are: <br /> <br />a. Radar (preferably 10 cm) - Life history for <br />as many clouds as possible for each <br />experimental day. <br /> <br />(1) First echo height, base and top defined <br />by 10-20 dBz contour. <br /> <br />(2) Time - height (h) plot of average and <br />variance of reflectivity (Z) over <br />each cell, where a cell is defined <br />by about the 10-20 dBz contour. <br />(Exact contour to be determined <br />in preliminary analysis.) <br /> <br />(3) x-h cross-section versus time through <br />maximum reflectivity, preferably in <br />plane (x) of wind or direction of echo <br />movement. <br /> <br />(4) Maximum Z versus time. <br /> <br />(5) Maximum reflectivity for cell: time, x, <br />and h position. <br /> <br />(6) Areal distribution (x, y) of maximum <br />height of echo above 10-20 dBz <br />(contoured) and maximum echo reflec- <br />tivity every 30 minutes. <br /> <br />b. Aircraft <br /> <br />(1) Drop-size distribution at cloud base in <br />updraft during developing stage. <br /> <br />(2) Partitioning of water substance into <br />liquid and ice, averaged over the <br />updraft, for cloud-size particles <br />(r<lOO ~m) and precipitation-size <br />particles (r~IOO ~m) at the height <br />of maximum reflectivity of the first <br />radar echo. <br /> <br />(3) Temperature, rate of climb, and vapor in <br />updraft and downdraft. <br /> <br />(4) Average cloud drop distribution over <br />updraft and downdraft. <br /> <br />(5) Precipitation distribution at cloud base. <br /> <br />c. Surface rainfall and hail, maximum rain rate <br />over 5 minutes and total precipitation <br />from cell. <br /> <br />d. Rawinsonde, continued serial ascents, <br />monitoring the changes in environment. <br /> <br />e. Visual cloud characteristics: <br /> <br />(1) Time lapse. <br /> <br />(2) Satellite - areal distribution. <br /> <br />(3) Human observation. <br /> <br />NOTE: Appearance of first echo (10-20 dBz) is the <br />synchronization time between models and <br />observations. <br /> <br />.~ <br /> <br />4. <br /> <br />OBJECTIVE MODEL VERIFICATION CRITERIA <br /> <br />It was suggested that the verification <br />of models must be objective and allow for natural <br />variability between clouds on a given day, thus <br />leading to careful verification of intermediate <br />stages leading to precipitation. The sequence of <br />verifiable events must be identified for each <br />model. A figure-of-merit (FOM) test statistic was <br />recommended for model verification between <br />predicted (Pi) and observed (Oi) parameters, <br /> <br />FOM = <br /> <br />~wi <br />i <br /> <br />Pi_Oi 1 <br />Max(P /Oi)J <br />N <br /> <br />2 <br /> <br />where wi is a weighting factor that is proportional <br />to the parameters' certainty and/or importance and N <br />is the number of parameters considered. A <br />summation value of zero is a perfect score and <br />one is a perfect bust. <br /> <br />It was recognized that even i.f precise <br />initial conditions were known, the assumptions <br />required to make models physically and computation- <br />ally reasonable would preclude the exact duplica- <br />tion of the real cloud. However, a model can <br />provide insight into the characteristic nature and <br />time scale of clouds and precipitation that develop <br />in the air mass represented by the given sounding. <br />By making several runs with reasonable variations <br />in initial conditions, as indicated by observations, <br />it should be possible to describe the range of <br />cloud types that could be expected. <br /> <br />5. <br /> <br />CONCLUSIONS <br /> <br />The modeling workshop was an extremely <br />useful first step in narrowing the gap between <br />models and observations. It provided encouragement <br />to the modelers by showing the ability of most <br />models. to properly characterize cloud development <br />on the two test days. In no case were modelers <br />trying to predict the actions of a particular cloud. <br />They did, however, try to predict important precipi- <br />tation mechanisms, types, and regions, and the <br />detection in quantitative terms of the importance <br />of the ice process on August 10 and its unimportance <br />on August 17 is significant. <br /> <br />The workshop produced a list of obser- <br />vations for initializing and verifying models and <br />suggested objective verification criteri.a. In the <br />future, another workshop may be called to consider <br />a more complete data set t~hich is being collected <br />primarily for this purpose as part of Project <br />HIP LEX . <br /> <br />Computer-manpower resources expended in <br />conducting this workshop were considerable. The <br />value gained in building confidence in models, <br />defining problems, and discussing observations made <br />the effort worthwhile. <br /> <br />~ <br />
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