MCS rainfall forecast accuracy as a function of large-scale forcing

dc.contributor.author Jankov, Isidora
dc.contributor.author Gallus, William
dc.contributor.author Gallus, William
dc.contributor.department Geological and Atmospheric Sciences
dc.date 2018-02-17T01:31:09.000
dc.date.accessioned 2020-06-30T04:04:41Z
dc.date.available 2020-06-30T04:04:41Z
dc.date.copyright Thu Jan 01 00:00:00 UTC 2004
dc.date.issued 2004-01-01
dc.description.abstract <p>The large-scale forcing associated with 20 mesoscale convective system (MCS) events has been evaluated to determine how the magnitude of that forcing influences the rainfall forecasts made with a 10-km grid spacing version of the Eta Model. Different convective parameterizations and initialization modifications were used to simulate these Upper Midwest events. Cases were simulated using both the Betts-Miller-Janjić (BMJ) and the Kain-Fritsch (KF) convective parameterizations, and three different techniques were used to improve the initialization of mesoscale features important to later MCS evolution. These techniques included a cold pool initialization, vertical assimilation of surface mesoscale observations, and an adjustment to initialized relative humidity based on radar echo coverage. As an additional aspect in this work, a morphology analysis of the 20 MCSs was included. Results suggest that the model using both schemes performs better when net large-scale forcing is strong, which typically is the case when a cold front moves across the domain. When net forcing is weak, which is often the case in midsummer situations north of a warm or stationary front, both versions of the model perform poorly. Runs with the BMJ scheme seem to be more affected by the magnitude of surface frontogenesis than the KF runs. Runs with the KF scheme are more sensitive to the CAPE amount than the BMJ runs. A fairly well-defined split in morphology was observed, with squall lines having trading stratiform regions likely in scenarios associated with higher equitable threat scores (ETSs) and nonlinear convective clusters strongly dominating the more poorly forecast weakly forced events.</p>
dc.description.comments <p>This article is from <em>Weather and Forecasting</em> 19 (2004): 428, doi: 1<a href="http://dx.doi.org/10.1175/1520-0434(2004)019<0428:MRFAAA>2.0.CO;2" target="_blank">0.1175/1520-0434(2004)019<0428:MRFAAA>2.0.CO;2</a>. Posted with permission.</p>
dc.format.mimetype application/pdf
dc.identifier archive/lib.dr.iastate.edu/ge_at_pubs/32/
dc.identifier.articleid 1035
dc.identifier.contextkey 7630225
dc.identifier.s3bucket isulib-bepress-aws-west
dc.identifier.submissionpath ge_at_pubs/32
dc.identifier.uri https://dr.lib.iastate.edu/handle/20.500.12876/38248
dc.language.iso en
dc.source.bitstream archive/lib.dr.iastate.edu/ge_at_pubs/32/2004_GallusWA_MCSRainfallForecast.pdf|||Fri Jan 14 23:33:55 UTC 2022
dc.source.uri 10.1175/1520-0434(2004)019<0428:MRFAAA>2.0.CO;2
dc.subject.disciplines Atmospheric Sciences
dc.subject.disciplines Geology
dc.subject.keywords atmospheric humidity
dc.subject.keywords atmospheric temperature
dc.subject.keywords computer simulation
dc.subject.keywords meteorology
dc.subject.keywords morphology
dc.subject.keywords radar equipment
dc.subject.keywords rain
dc.subject.keywords convective system
dc.subject.keywords stratiform
dc.subject.keywords weather forecasting
dc.subject.keywords accuracy assessment
dc.subject.keywords atmospheric forcing
dc.subject.keywords convective system
dc.subject.keywords forecasting method
dc.subject.keywords numerical model
dc.subject.keywords rainfall
dc.title MCS rainfall forecast accuracy as a function of large-scale forcing
dc.type article
dc.type.genre article
dspace.entity.type Publication
relation.isAuthorOfPublication 782ee936-54e9-45de-a7e6-2feb462aea2a
relation.isOrgUnitOfPublication 29272786-4c4a-4d63-98d6-e7b6d6730c45
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