A Climatology of Precipitation Efficiency in the Central Appalachian Mountain Region

James MorrowNick Luchetti

• Precipitation Efficiency = Precipitation/Precipitable Water (i.e. moisture available through the depths of the atmosphere)

• Ratio represents the the fraction of available water vapor in the atmosphere that is translated into precipitation reaching the surface.

Factors that alter the ratio: Storm Motion, Moisture Convergence, Coverage of Precipitation, Amount of lifting and instability release.

Objectives: • Highlight any trends that may signal a recent

change in the regional climate– Drought concerns– Heavy precipitation event concerns

• Highlight the inter-annual variability in seasonal precipitation efficiency – Identify climate system controllers

• Create a climatological visual display for operational forecasters to use when issuing watches and warnings.

Study Area

• Varying degrees of elevation• Flash flooding susceptibility • 25 weather stations

Methods

• 1982-2012

• Daily Precipitation data extracted from the National Climatic Data Center’s weather station database.

• Precipitable water data were gathered for a 2.5° latitude x 2.5° longitude area centered on Blacksburg, Virginia (elevation 640 m)– Re-analysis data base of NOAA’s Earth Systems Research Laboratory.

• 31-year median ratios were spatially plotted using GIS(Inverse Distance tool)

• Inter-annual median ratios vs. Multivariate ENSO Index(MEI) values were plotted.

Spring Season(March-May)

March April May25% 11.8 9.0 6.7

Median 34.2 27.1 19.975% 80.6 64.1 46.2

Summer Season(June-August)

June July August 25% 4.8 4.3 4.2

Median 14.5 13.0 12.675% 37.7 34.2 33.8

Fall Season(September-November)

September October November25% 4.6025 6.06 9.2

Median 15.435 20.83 28.6775% 46.705 55.53 74.16

Winter Season(December-February)

December January February25% 10.7 13.0 13.9

Median 31.9 37.4 36.375% 85.7 87.7 80.1

Full Season(January-December)

Potential Controller-Orographic Lift• Atmospheric instability• Lower-atmospheric evaporation of

hydrometers R^2 = .0049

• ENSO phase change alters synoptic scale storm motion

• Most evident in winter months

Potential Controller- El Niño/La Niña Cycles

Potential Controller- El Niño/La Niña Cycles• MEI + indicate El Niño– Wetter and cooler conditions

• MEI – indicate La Niña– Dryer and warmer conditions

Winter Classic El Nino Events (1982-1983, 1991-1992, 1997-1998, 2002-2003, 2009-2010)

(1.2,42%)

(1.6,35%)

(2.5,38%)

(1.1,51%)

(1.2,45%)

Winter Classic La Niña Events(1989-1990,1999-2000, 2000-2001, 2010-2012)

(-1.2,26%)

(-.909,22%)(-.6,34%)

(-1.12,33%)

Conclusions and Continued Research• Variation is evident spatially and temporally• Visually, aspect may be a potential controller • Extreme ENSO Phases could be a potential

controller • Use SWAT model to cross reference high flood

risk areas • Look into other large scale circulations(North

Atlantic Oscillation, Artic Oscillation)