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dc.date.accessioned2022-05-09T00:50:05Z
dc.date.available2022-05-09T00:50:05Z
dc.date.copyright04 Feb 2022
dc.date.issued2022
dc.identifier.otherWAF-D-21-0104.1.pdf
dc.identifier.urihttp://yetl.yabesh.ir/yetl1/handle/yetl/4285608
dc.description.abstractIn-cloud icing is a major hazard for aviation traffic and forecasting of these events is an important task for weather agencies worldwide. A common tool utilized by aviation forecasters is an icing intensity index based on supercooled liquid water from numerical weather prediction models. We seek to validate the modified microphysics scheme, ICE-T, in the HARMONIE-AROME numerical weather prediction model with respect to aircraft icing. Icing intensities and supercooled liquid water derived from two 3-month winter season simulations with the original microphysics code, CTRL, and ICE-T are compared with pilot reports of icing and satellite retrieved values of liquid and ice water content from CloudSat–CALIPSO and liquid water path from AMSR-2. The results show increased supercooled liquid water and higher icing indices in ICE-T. Several different thresholds and sizes of neighborhood areas for icing forecasts were tested out, and ICE-T captures more of the reported icing events for all thresholds and nearly all neighborhood areas. With a higher frequency of forecasted icing, a higher false alarm ratio cannot be ruled out, but is not possible to quantify due to the lack of no-icing observations. The increased liquid water content in ICE-T shows a better match with the retrieved satellite observations, yet the values are still greatly underestimated at lower levels. Future studies should investigate this issue further, as liquid water content also has implications for downstream processes such as the cloud radiative effect, latent heat release, and precipitation.
dc.titleThe Ability of the ICE-T Microphysics Scheme in HARMONIE-AROME to Predict Aircraft Icing
dc.typeJournal Paper
dc.journal.volume37
dc.journal.issue2
dc.journal.titleWeather and Forecasting
dc.identifier.doi10.1175/WAF-D-21-0104.1
dc.page205–217
dc.treeWeather and Forecasting:;2022:;volume( 037 ):;issue: 002
dc.contenttypeFulltext


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