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FXHW01 KWNH 070800

PMDHI 



Hawaii Extended Forecast Discussion

NWS Weather Prediction Center College Park MD

359 AM EDT Sun Apr 07 2024



Valid 00Z Mon Apr 08 2024 - 00Z Mon Apr 15 2024



Models and ensembles remain consistent for the forecast from the

weekend into the first half of next week, and have finally come

into better agreement with the forecast evolution during the

latter half of the week. There are still some finer details to be

resolved in the late week/weekend time frame though.  Expect

trades to continue trending somewhat lighter early this week as

high pressure initially north of the state weakens and tracks into

the eastern Pacific.  A front approaching from the northwest by

midweek should then turn winds more southeasterly. 

Windward-focused showers, with a few possibly straying to leeward

areas, should be moderate as a weakness aloft persisting into

early Tuesday could enhance amounts but guidance shows

precipitable water values staying somewhat below normal into the

early part of the week.  By Wednesday-Thursday, guidance

clustering has dramatically improved versus previous days, showing

a deep upper low closing off to the northwest of the state.  The

upper low will most likely drift northward and open up from Friday

onward as upstream energy filters into the overall trough.  Based

on the current consensus, the front extending south from the

associated surface low should get close to the western islands and

serve as a focus for heavy rainfall over that part of the state,

within a broader pattern of southerly moisture flow that will

likely bring precipitable water values above 1.5 inches across the

area for multiple days.  Of course exact details will take

additional time to resolve.  Although the CMC from a couple days

ago led the trend for where the upper low appears destined to

close off, today's 00Z CMC strays to the amplified/eastern side

with the larger scale upper trough by next weekend, pushing the

surface front farther east than most other guidance including

recent ECMWF-initialized machine learning models.  Thus would

recommend a composite of the GFS/ECMWF and their ensemble means as

a starting point for the forecast.



Rausch



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