Developing a Reference Crop Evapotranspiration Climatology for the Southeastern U.S. using the FAO Penman-Monteith Estimation Heather Dinon*, Ryan Boyles,

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Presentation transcript:

Developing a Reference Crop Evapotranspiration Climatology for the Southeastern U.S. using the FAO Penman-Monteith Estimation Heather Dinon*, Ryan Boyles, Gail Wilkerson Carolinas and Virginia Climate Conference October 21, 2009 October 21, 2009 Wilmington, NC

Motivation NC Agriculture: –Annual $71B economy –19% of state income –Over 16% of work force (NCDA&CS 2008) Agriculture is largest consumer of water in US (NOAA 2002) Photo courtesy of Bridget Lassiter, of NCSU Crop Science Department Weather/Climate  Agriculture/Irrigation

What is this? Why do we need? Robust ET estimate: Efficient water use Maximize yields

Introduction ET provides guidance for crop managementET provides guidance for crop management Limited ET observationsLimited ET observations Solution: UN FAO Penman-Monteith method to estimate daily reference crop ETSolution: UN FAO Penman-Monteith method to estimate daily reference crop ET –Theoretical grass reference crop Height of 0.12mHeight of 0.12m Albedo of 0.23Albedo of 0.23 Surface resistance of 70s/mSurface resistance of 70s/m Weekly irrigation scheduleWeekly irrigation schedule –Min/Max Temp, Min/Max RH, Avg SR, Avg WS –Dependent on time of year & location (elev, lat)

Daily estimation Calculates RefET for stations on selected date of interest (YY-MM-DD)Calculates RefET for stations on selected date of interest (YY-MM-DD) –Date range: 01 Jan yesterday –ASOS, AWOS, ECONET, RAWS, USCRN –Virginia, Carolinas, Georgia, Florida, Alabama

Climatology product Years: Years: Daily average: 7-day moving averageDaily average: 7-day moving average –Annual time series for each station Average monthly totalsAverage monthly totals –Annual bar chart for each station  Both products require >80% of data, and data must pass QC checks

*Note: Upper and lower boundaries capture ~50% of the distribution. Only shown if 5 or more years of data.

Sensitivity analysis Sensitivity of inputs:Sensitivity of inputs: –min/max temp, min/max RH, avg SR, avg WS Case study:Case study: –Lake Wheeler Field Lab, Raleigh, NC Elevation: 382 feet above sea levelElevation: 382 feet above sea level Station type: ECONETStation type: ECONET –Average each parameter during July ( )

Summary - Tool Dataset of ET for assistance with crop management across Southeast USDataset of ET for assistance with crop management across Southeast US Daily estimate (2002 up to yesterday)Daily estimate (2002 up to yesterday) Climatology product (daily/monthly)Climatology product (daily/monthly) Spatial (maps) & temporal (graphs)Spatial (maps) & temporal (graphs)

Summary - Analysis Direct relationship: SR, temp, WSDirect relationship: SR, temp, WS Indirect relationship: RHIndirect relationship: RH SR main energy source for ETSR main energy source for ET

Future Work Analyze trends across the SoutheastAnalyze trends across the Southeast –Sensitivity analysis of inputs –Spatial variation (regional trends) –Temporal variation (seasonal trends)

Questions? Comments? Contact Information: Heather Dinon