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2011 - Cooperative Institute for Research in Environmental Sciences ...

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PSD-16Ra<strong>in</strong>dropSizeDistributions<br />

FEDERAL LEAD: TIMOTHY SCHNEIDER<br />

CIRES LEAD: CHRISTOPHER WILLIAMS<br />

NOAA Goal 3: Weather and Water<br />

Project Goal: Improve ground-based, airborne and<br />

space-borne radar ra<strong>in</strong>fall estimates through <strong>in</strong>creased<br />

understand<strong>in</strong>g of the number and size of ra<strong>in</strong>drops <strong>in</strong><br />

precipitat<strong>in</strong>g cloud systems.<br />

Milestone 1. A vertical air motion estimation technique<br />

will be developed us<strong>in</strong>g collocated 50- and 920-MHz radar<br />

observations to isolate the vertical air motion resolved <strong>in</strong><br />

the 50-MHz radar observations. These columnar dual-frequency<br />

vertical air motion estimates will provide reference<br />

measurements <strong>for</strong> simultaneous dual-Doppler scann<strong>in</strong>g<br />

radar estimates.<br />

A dual-frequency profiler retrieval technique was developed<br />

that estimates the vertical air motion with<strong>in</strong> precipitat<strong>in</strong>g<br />

cloud systems. The technique relies on us<strong>in</strong>g the<br />

‘signal’ <strong>in</strong> one radar to mask out the ‘noise’ observed <strong>in</strong><br />

another. In particular, the 50-MHz profiler can simultaneously<br />

observe the vertical air motion and the ra<strong>in</strong>drop<br />

motion when precipitat<strong>in</strong>g clouds pass directly overhead.<br />

But the 920-MHz profiler is only sensitive to the ra<strong>in</strong>drop<br />

motion. By comb<strong>in</strong><strong>in</strong>g the two measurements, the 920-MHz<br />

profiler signal is used to mask out the ra<strong>in</strong>drop motion<br />

<strong>in</strong> the 50-MHz profiler observation. The result<strong>in</strong>g filtered<br />

50-MHz profiler observation conta<strong>in</strong>s only the vertical air<br />

motion <strong>in</strong><strong>for</strong>mation. The dual-frequency profiler retrieval<br />

technique was applied to observations collected dur<strong>in</strong>g<br />

the Tropical Warm Pool–International Cloud Experiment<br />

(TWP-ICE). The vertical air motions have been and are<br />

still be<strong>in</strong>g used by <strong>in</strong>ternational and domestic researchers<br />

study<strong>in</strong>g the dynamics of precipitat<strong>in</strong>g cloud systems.<br />

PSD-17<strong>Environmental</strong>Monitor<strong>in</strong>gandPrediction<br />

FEDERAL LEAD: GARY WICK<br />

CIRES LEAD: DARREN JACKSON<br />

NOAA Goal 3: Weather and Water<br />

Project Goal: Improve the per<strong>for</strong>mance of numerical weather<br />

and climate models through model process evaluation us<strong>in</strong>g<br />

data streams from focused observational campaigns and spaceborne<br />

measurements.<br />

Milestone 1. Assess the representation of water vapor content<br />

and transport <strong>in</strong> the new Flow-follow<strong>in</strong>g f<strong>in</strong>ite-volume<br />

Icosohedral Model dur<strong>in</strong>g w<strong>in</strong>tertime precipitation events<br />

along the U.S. West Coast us<strong>in</strong>g satellite observations, and<br />

compare with that of other operational models.<br />

Ef<strong>for</strong>ts have focused on the development and validation of<br />

methods to compare the representation of water vapor content<br />

and transport between observations and model analysis<br />

and <strong>for</strong>ecast fields. Atmospheric rivers are the primary<br />

manifestation of water vapor transport dur<strong>in</strong>g w<strong>in</strong>tertime<br />

precipitation events. An objective, automated tool <strong>for</strong> the<br />

identification and characterization of atmospheric river<br />

events <strong>in</strong> satellite observation and model <strong>for</strong>ecast fields has<br />

been developed. The functionality of the technique was<br />

validated by compar<strong>in</strong>g the objectively identified landfall<strong>in</strong>g<br />

atmospheric rivers over five w<strong>in</strong>ter seasons with those<br />

identified visually <strong>in</strong> a climatology of landfall<strong>in</strong>g events.<br />

The results demonstrated that the technique per<strong>for</strong>med extremely<br />

well with a critical success <strong>in</strong>dex of 92.8 percent <strong>in</strong><br />

identify<strong>in</strong>g events. A publication describ<strong>in</strong>g the technique<br />

is now be<strong>in</strong>g completed. Initial application of the technique<br />

to comparisons of the frequency and <strong>in</strong>tensity of atmospheric<br />

river events between observations and multiple<br />

<strong>for</strong>ecast models suggest that the models do a good job <strong>in</strong><br />

<strong>for</strong>ecast<strong>in</strong>g the occurrence of the events, but possibly overpredict<br />

their <strong>in</strong>fluence on land, particularly at longer lead<br />

times. Additional observations to directly assess the water<br />

vapor transport with<strong>in</strong> three atmospheric river events were<br />

collected from the unmanned Global Hawk aircraft as part<br />

of the NOAA-led W<strong>in</strong>ter Storms and Pacific Atmospheric<br />

Rivers (WISPAR) experiment.<br />

GSD-01NumericalWeatherPrediction<br />

FEDERAL LEAD: GEORG GRELL<br />

CIRES LEAD: CURTIS ALEXANDER<br />

NOAA Goal 3: Weather and Water<br />

Project Goal: Design and evaluate new approaches <strong>for</strong><br />

improv<strong>in</strong>g regional-scale numerical weather <strong>for</strong>ecasts,<br />

<strong>in</strong>clud<strong>in</strong>g <strong>for</strong>ecasts of severe weather events.<br />

Milestone 1. Conduct and evaluate a summer 2010 and <strong>2011</strong><br />

convection <strong>for</strong>ecast exercise with other Aviation Weather<br />

<strong>Research</strong> Product Development Teams (Convective Weather,<br />

<strong>in</strong> particular), <strong>in</strong> which the High Resolution Rapid Refresh<br />

(HRRR) run at convection-resolv<strong>in</strong>g resolution over the conterm<strong>in</strong>ous<br />

United States plays a dom<strong>in</strong>ant role. The goal of<br />

this exercise is to evaluate the potential effectiveness of the<br />

HRRR <strong>in</strong> predict<strong>in</strong>g high-impact aviation weather, particularly<br />

convection, 3–12 hours <strong>in</strong> advance.<br />

The HRRR model output was used as a key <strong>in</strong>put <strong>in</strong>to a<br />

real-time automated convective weather <strong>for</strong>ecast product<br />

known as CoSPA, which was used by the Federal Aviation<br />

Adm<strong>in</strong>istration (FAA). Dur<strong>in</strong>g the summers of 2010<br />

and <strong>2011</strong>, the FAA conducted an operational per<strong>for</strong>mance<br />

evaluation of CoSPA to assess its impact on air traffic management<br />

decision-mak<strong>in</strong>g. Additionally, the HRRR model<br />

<strong>for</strong>ecasts have been provided to the Aviation Weather Center<br />

(AWC) <strong>for</strong> guidance <strong>in</strong> the production of a Collaborative<br />

Convective Forecast Product (CCFP).<br />

Prior to the summer 2010 season, the HRRR <strong>for</strong>ecast<br />

doma<strong>in</strong> was expanded to <strong>in</strong>clude the entire conterm<strong>in</strong>ous<br />

United States; the underly<strong>in</strong>g Weather <strong>Research</strong> and<br />

Forecast<strong>in</strong>g (WRF) model version was updated to <strong>in</strong>clude<br />

the official version 3.2 release; and the <strong>for</strong>ecast period<br />

was extended from 12 to 15 hours. Reliability of HRRR<br />

model runs has been ma<strong>in</strong>ta<strong>in</strong>ed at about 95 percent <strong>for</strong><br />

2010/<strong>2011</strong>. Additional resources were implemented to<br />

improve the HRRR convective <strong>for</strong>ecast guidance <strong>in</strong>clud<strong>in</strong>g<br />

an <strong>in</strong>-house multi-scale verification system and a<br />

parallel (shadow) HRRR model whereby impacts of model<br />

changes are assessed <strong>in</strong> both real-time and thru retrospective<br />

<strong>for</strong>ecasts.<br />

Prior to the summer <strong>2011</strong> season, the parent <strong>for</strong>ecast<br />

model <strong>for</strong> HRRR <strong>in</strong>itialization was changed from the<br />

Rapid Update Cycle (RUC) to the Rapid Refresh (RR)<br />

and <strong>in</strong>cludes a more advanced data-assimilation system<br />

known as Gridpo<strong>in</strong>t Statistical Interpolation (GSI) along<br />

with a larger <strong>for</strong>ecast doma<strong>in</strong> cover<strong>in</strong>g North America.<br />

The larger doma<strong>in</strong> reduces the negative impact of lateral<br />

boundaries and additional observations are now <strong>in</strong>corporated<br />

<strong>in</strong>to the hourly RR analysis used by the HRRR.<br />

CIRES Annual Report <strong>2011</strong> 95

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