AMPS Update June 2014

Transcription

1 AMPS Update June th Antarc*c Meteorological Observa*ons, Modeling, and Forecas*ng Workshop June 2014 Charleston, SC Kevin W. Manning Jordan G. Powers Mesoscale and Microscale Meteorology Division NCAR Earth System Laboratory NaKonal Center for Atmospheric Research Boulder, CO NCAR is sponsored by the NaKonal Science FoundaKon

2 The AntarcKc Mesoscale PredicKon System Provides customized NWP support for AntarcKc forecasters Forecast model is the Weather Research and ForecasKng Model (WRF ARW), tuned for the AntarcKc environment Funded by the NaKonal Science FoundaKon CollaboraKon between NaKonal Center for Atmospheric Research/ Mesoscale and Microscale Meteorology Division and Ohio State University/Byrd Polar Research Center Primary goals are to support USAP forecasters and ackvikes, and to support research and educakon efforts in AntarcKc meteorology Real Kme forecasts running since October 2000, through many updates Real Kme products disseminated primarily through the AMPS web page ( and the AntarcKc IDD network 2

3 30 km 3.3 km 10 km 1.1 km 3.3 km 3

4 AddiKonal Grids WAISD and PIG grids run as one way nests driven by output from the AMPS 10 km ConKnental grid. New Zealand and Palmer grids run as twoway nests of an independent 27 km grid similar in coverage to the AMPS 30 km grid. 3.3 km WAIS Divide 8 km New Zealand 3.3 km Pine Island Glacier 9 km Palmer Drake Passage 4

5 h]p:// h]p://amps backup.ucar.edu 5

6 New in the past year Layer average winds over Pole ` ` 6

7 Tests WRF version w/polar adaptakons currently running w/polar adaptakons RRTMG Shortwave parameterizakon currently running Goddard SW Thompson Microphysics parameterizakon Currently running WSM5 PotenKal effect on cloud deficit? Temperature/Warming issues Increase snow albedo Use GFS subsurface temperatures Ensemble forecasts 7

8 Ensemble Forecasts See Powers talk 8

9 WRF version tests ExecuKve summary: No compelling reason to upgrade from version at this Kme By most measures, verifies slightly worse than Temperature diurnal cycle differences 9

10 WRF vs. WRF Ross Ice Shelf error stakskcs Jan 2013 Temperature error stakskcs Wind speed error stakskcs K m s 1 K m s 1 Forecast Hour Forecast Hour 10

11 WRF vs. WRF East AntarcKc Plateau error stakskcs Jan 2013 Temperature error stakskcs Wind speed error stakskcs K m s 1 K m s 1 Forecast Hour Forecast Hour 11

12 RRTMG SW tests ExecuKve Summary: No compelling reason to switch to RRTMG SW (from Goddard SW) Surface temperature scores a li]le worse Surface wind speed scores are similar, possibly slightly be]er 12

13 WRF vs. WRF vs. WRF RRTMG Ross Ice Shelf error stakskcs Jan 2013 Temperature error stakskcs Wind speed error stakskcs K m s 1 K m s 1 Forecast Hour Forecast Hour 13

14 WRF vs. WRF vs. WRF RRTMG East AntarcKc Plateau error stakskcs Jan 2013 Temperature error stakskcs Wind speed error stakskcs K m s 1 K m s 1 Forecast Hour Forecast Hour 14

15 Thompson Microphysics What does Thompson offer? Two moment scheme: Thompson predicts number concentrakons as well as mixing rakos, allowing for be]er representakon of parkcle size distribukons Under ackve development More computakonally intensive Exploratory teskng in AMPS SuggesKon of more cloud in some areas Seems to reduce cloud ice, increase low level cloud water, increase snow as a microphysical species Several other microphysics schemes in WRF may merit teskng 15

16 WRF vs. WRF vs. WRF Thompson Ross Ice Shelf error stakskcs Jan 2013 Temperature error stakskcs Wind speed error stakskcs K m s 1 K m s 1 Forecast Hour Forecast Hour 16

17 WRF vs. WRF vs. WRF Thompson East AntarcKc Plateau error stakskcs Jan 2013 Temperature error stakskcs Wind speed error stakskcs K m s 1 K m s 1 Forecast Hour Forecast Hour 17

18 Mean microphysical profiles Jan 2013 Oceanic Ross Ice Shelf Plateau > 3000m Significantly more low level Cloud Water in Thompson Cloud Ice in WSM5 becomes Snow in Thompson Solid Lines: Thompson Microphysics Dashed Lines: WSM6 Microphysics Cloud Ice: Cloud Water: Snow: Rain: Graupel: 18

19 Warming issues Exploratory teskng Effect of subsurface temperature inikalizakon Effect of changes to snow albedo 19

20 Surface temperature error stakskcs as a funckon of forecast hour East AntarcKc plateau stakons; Jan 2014 AMPS configurakon: Snow albedo = 80% Subsurface temperatures cycled 20

21 AMPS configurakon: Snow albedo = 80% Subsurface temperatures cycled GFS subsurface temperatures 21

22 AMPS configurakon: Snow albedo = 80% Subsurface temperatures cycled GFS subsurface temperatures Snow albedo = 83 % 22

23 Mean subsurface T forecast as a funckon of forecast hour over East AntarcKc Plateau (topography > 3000 m) for Jan 2014 IniKalized by cycling subsurface T from previous forecast IniKalized with GFS subsurface T Albedo = 83 % 2 m Air Temperature Skin Temperature Layer 2: m Layer 2: m Layer 3: m Layer 4: m 23

24 Where To Next? Ferret out source of the diurnal signal of model error in newer WRF versions Further explore growth of temperature bias Pursue ensemble forecasts Data assimilakon methods: Cycling off of AMPS forecasts? Ensemble DA? 24