the value of very high resolution weather forecasts ......thejefferson project atlakegeorge...

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The Jefferson Project at Lake George The Jefferson Project is a research endeavor at Lake George, NY by IBM Research, Rensselaer Polytechnic Institute (RPI) and The FUND for Lake George. Lake George is a dimictic, oligotrophic lake and The Jefferson Project is working to understand, predict and enable a healthy Lake George ecosystem. An modeling system is being developed to provide data on the physical, chemical and biological parameters that drive ecosystem function. This includes a weather model that drives simulations of the watershed hydrology and lake circulation (and eventually the food web dynamics). Weather Modeling: How high is too high? - WRF-ARW Core V3.6.1 - Daily 36-hr forecasts at 00Z (May 21 2016 – present) - Assimilation of local and regional weather obs using WRF 3DVar - 39 vertical levels (11 below 1 km) - Thompson double-momentmicrophysics - MYNN surface and boundary layer / RRTMG radiation / Noah LSM Towards this end, we consider two questions: 1) Does model resolution impact simulated wind stress at the lake surface? 2) What is the impact on precipitation within the watershed? For wind stress, we find the lake-wide average converges at higher resolution despite more extreme values emerging. Do these regions of higher/lower wind stress have a material effect on lake circulation? For precipitation, the long-term average is similar across model resolutions although larger maximums emerge at Δ0.33 km. Whether this difference is important probably depends on user need (e.g., long-term hydrology studies vs. flash flood prediction). d01 – 9km | d02 – 3km | d03 – 1km | d04 – 0.33km The value of very high resolution weather forecasts? Experiences from The Jefferson Project at Lake George Campbell D. Watson*, James P. Cipriani, Mukul Tewari, Anthony P. Praino, Lloyd A. Treinish, Michael Henderson, Harry R. Kolar IBM T. J. Watson Research Center, Yorktown Heights, NY *[email protected] Effect of resolution on lake wind stress Surface winds drive lake circulation by applying stress at the surface. Surface winds are strongly controlled by topography, which is more realistically resolved at higher resolution. Following Xiao et al (2013), we compute the wind stress, τ , as follows: Over 7.5 months, the average wind stress on the lake converges as model resolution increases. However, variation in wind stress increases at higher resolution (i.e., higher highs, lower lows). Are these differences important? Next step: quantify the importance of these differences by using a lake circulation model. τ=ρ $ C & u ( C &)*+ =k ( / ln z/z * ( Units: kg m /) s /( or Nm /( ρ $ is air density C &)*1 is the drag coefficient u is wind speed k is von Karmen constant z is height above ground z * is surface roughness Δ 0.33 km Δ 1 km Δ 3 km 12 cells 119 cells Number of grid cells over Lake George at each resolution 1042 cells May 21 – Dec 31 2016: The average wind stress (N m -2 ) on Lake George Wind Stress (N m -2 ) 3 km (d02) 1 km (d03) 0.33 km (d04) Average 0.048 0.052 0.051 Average Minimum 0.017 0.005 0.002 Average Maximum 0.091 0.152 0.195 Effect of resolution on precipitation The watershed hydrology is driven by precipitation. Accurately simulating the amount and location of precipitation inside each watershed is crucial to understanding the physical system. The difference in average daily precipitation across domain resolutions for each (sub)watershed never exceeds 10%. However, like with wind stress, variations increase at higher resolution (e.g., differences in maximum precipitation are larger). Are these differences important? Next step: identify precipitation events where differences in maximum precipitation are largest across domains and quantify the impact on surface hydrology using a land surface model and runoff model. May 21 – Dec 31 2016: The average daily precipitation (mm) Δ 0.33 km Δ 1 km Δ 3 km Daily Precip (mm) 3 km (d02) 1 km (d03) 0.33 km (d04) Average 2.86 2.72 2.81 Average Maximum 5.97 6.75 7.66 Full Watershed (black line) Finkle Brook (orange line) Northwest Bay Brook (red line) Daily Precip (mm) 3 km (d02) 1 km (d03) 0.33 km (d04) Average 2.83 2.66 2.85 Average Maximum 2.83 3.18 3.55 Daily Precip (mm) 3 km (d02) 1 km (d03) 0.33 km (d04) Average 2.93 2.73 2.76 Average Maximum 3.69 4.13 4.35 ~50 km Xiao, W., Liu, S., Wang, W., Yang, D., Xu, J.,Cao, C., Li, H and Lee, X. 2013. Transfer Coefficients of Momentum, Heat and Water Vapour in the Atmospheric Surface Layer of a Large Freshwater Lake. Boundary-Layer Meteorol. 148: 479-494 Terrain height at 100 m intervals (as resolved by the model) shown by black contours; thick black line shows the extent of the Lake George watershed; red and orange lines show Northwest Bay and Finkle Brook subwatersheds, respectively; blue line shows the lake.

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Page 1: The value of very high resolution weather forecasts ......TheJefferson Project atLakeGeorge TheJeffersonProject isa research endeavorat Lake George, NY by IBM Research, Rensselaer

The Jefferson Project at Lake GeorgeThe Jefferson Project is a research endeavor at Lake George, NY by IBM Research,Rensselaer Polytechnic Institute (RPI) and The FUND for Lake George. Lake Georgeis a dimictic, oligotrophic lake and The Jefferson Project is working to understand,predict and enable a healthy Lake George ecosystem.

An modeling system is being developed to provide data on the physical, chemicaland biological parameters that drive ecosystem function. This includes a weathermodel that drives simulations of the watershed hydrology and lake circulation(and eventually the foodweb dynamics).

Weather Modeling: How high is too high?

- WRF-ARW Core V3.6.1- Daily 36-hr forecasts at 00Z (May 21 2016 – present)- Assimilation of local and regional weather obs usingWRF 3DVar- 39 vertical levels (11 below1 km)- Thompson double-momentmicrophysics- MYNN surface and boundary layer / RRTMG radiation / Noah LSM

Towards this end, we consider two questions:

1) Does model resolution impact simulated wind stress at the lake surface?2) What is the impact on precipitation within the watershed?

For wind stress, we find the lake-wide average converges at higher resolutiondespite more extreme values emerging. Do these regions of higher/lower windstress have a material effect on lake circulation?

For precipitation, the long-term average is similar across model resolutionsalthough larger maximums emerge at Δ0.33 km. Whether this difference isimportant probably depends on user need (e.g., long-term hydrology studies vs.flash flood prediction).

d01– 9km|d02– 3km|d03– 1km|d04– 0.33km

The value of very high resolution weather forecasts? Experiences from The Jefferson Project at Lake George Campbell D. Watson*, James P. Cipriani, Mukul Tewari, Anthony P. Praino, Lloyd A. Treinish, Michael Henderson, Harry R. Kolar

IBM T. J. Watson Research Center, Yorktown Heights, NY *[email protected]

Effect of resolution on lake wind stressSurface winds drive lake circulation by applying stress at the surface. Surface winds arestrongly controlledby topography,which is more realistically resolved at higher resolution.

FollowingXiao et al (2013), we compute the wind stress, τ, as follows:

Over 7.5 months, the average wind stress on the lake converges as model resolutionincreases. However, variation in wind stress increases at higher resolution (i.e., higherhighs, lower lows). Are these differences important?

Next step: quantify the importance of these differences by using a lake circulationmodel.

τ = ρ$C&u(

C&)*+ = k(/ ln z/z* (

Units:kgm/)s/( orNm/(

ρ$ isairdensityC&)*1 isthedragcoefficientu iswindspeedk isvonKarmenconstantz isheightabovegroundz* issurfaceroughness

Δ 0.33kmΔ 1kmΔ 3km

12cells 119cellsNumberofgridcellsoverLakeGeorgeateachresolution

1042cells

May21– Dec312016:Theaveragewindstress(Nm-2)onLakeGeorge

WindStress(Nm-2) 3km(d02) 1km(d03) 0.33km(d04)

Average 0.048 0.052 0.051AverageMinimum 0.017 0.005 0.002AverageMaximum 0.091 0.152 0.195

Effect of resolution on precipitationThe watershed hydrology is driven by precipitation. Accurately simulating the amount and location of precipitationinside each watershed is crucial to understanding the physical system. The difference in average daily precipitationacross domain resolutions for each (sub)watershed never exceeds 10%. However, like with wind stress, variationsincrease at higher resolution (e.g., differences in maximum precipitation are larger). Are these differencesimportant?

Next step: identify precipitation events where differences in maximum precipitation are largest across domains andquantify the impact on surface hydrologyusing a land surface model and runoff model.

May21– Dec312016:Theaveragedailyprecipitation(mm)Δ 0.33kmΔ 1kmΔ 3km

Daily Precip (mm) 3km(d02) 1km(d03) 0.33km(d04)

Average 2.86 2.72 2.81AverageMaximum 5.97 6.75 7.66

FullWatershed(blackline)

Finkle Brook(orangeline)

NorthwestBayBrook(redline)

Daily Precip (mm) 3km(d02) 1km(d03) 0.33km(d04)

Average 2.83 2.66 2.85AverageMaximum 2.83 3.18 3.55

Daily Precip (mm) 3km(d02) 1km(d03) 0.33km(d04)

Average 2.93 2.73 2.76AverageMaximum 3.69 4.13 4.35

~50km

Xiao,W.,Liu,S.,Wang,W.,Yang,D.,Xu,J.,Cao,C.,Li,HandLee,X.2013.TransferCoefficients ofMomentum,HeatandWaterVapour intheAtmosphericSurfaceLayerofaLargeFreshwaterLake.Boundary-LayerMeteorol.148:479-494

Terrainheightat100mintervals(asresolvedbythemodel)shownbyblackcontours;thickblacklineshowstheextentoftheLakeGeorgewatershed;redandorangelinesshowNorthwestBayandFinkle Brooksubwatersheds,respectively;bluelineshowsthelake.