Download Sub-km External Surface Modeling to Improve Numerical Prediction

Sub-km External Surface Modeling to Improve
Numerical Prediction over Ecosystems, Cities, and
Water Surfaces
S. Bélair, M. Abrahamowicz,
S. Leroyer, N. Bernier, N. Gauthier,
V. Souvanlasy, A. Leroux, and
J.-P. Gauthier
Meteorological Research Division
Environment Canada
CMOS/AMS 2012 Congress, Montreal, June 1rst, 2012
ENVIRONMENT CANADA’s EXTERNAL SURFACE MODELING
SYSTEM
ATMOS
MODEL
LOW-RES MODEL or OBS or ANALYSES
ATMOSPHERIC FORCING at FIRST ATMOS. MODEL LEVEL (T, q, U, V)
ATMOSPHERIC FORCING at
SURFACE (RADIATION and
PRECIPITATION)
External
Surface
Models
With horizontal
resolution as high as
that of surface
databases (e.g., 100 m)
HIGH-RES
2D INTEGRATION
Computational cost of off-line surface modeling system is
much less than an integration of the atmospheric model
HIGH-RESOLUTION MODELING of the URBAN ENVIRONMENT
(120m)
Nocturnal 2m air temperature
(simulation, 120m)
§ 6 July, 01:00 LST
Montreal Island
°C
22
21
20
19
18
17
16
15
14
► UHI : 5-6 °C
(Leroyer et al. 2011)
HIGH-RESOLUTION MODELING OVER MOUNTAINS (VO2010)
100-m snow analyses
Great decrease of T2m errors (bias shown here)
(Bernier et al.
2011, 2012)
(Thanks to Juan Sebastian Fontecilla)
LAND SURFACE PARAMTERS
A VERY IMPORTANT ELEMENT of SUCCESS…
MODIS ALBEDO CLIM.
MODIS NDVI CLIM.
BIOME-BGC CLIM.
ALL DATABASES
GTOPO30
SRTM-DEM
ASTER-DEM
CDED1
GLCC
CCRS
GlobCover
LCC-2000
CanVec
Census
FAO
STATSGO
SMAP SM
HWSDB
GenPhysX /
UrbanX
Vegetation fractions
Urban parameters
Water fraction
Soil texture
Pre-Surf
Orographic parameters
Water fraction
GEM or
GEM-Surf
LEAF AREA INDEX
VEG. FRACTIONS
VEG. PARAMETERS
ALBEDOs
ROOT-ZONE DEPTH
SAND
CLAY
URBAN PARAMETERS
Building
Fraction (%)
60+
Q
50
40
Vegetation
(Various Types)
35
30
25
20
10
Pavement
Streets
è 100m Urban Fields over Toronto
Google Maps
DOWNSCALING LAI: SOURCES of INFORMATION
30m
200m
LCC-2000
Land Use /
Land Cover (types)
1km
10km
TARGET RESOLUTION
MODIS 10-year
NDVI climatology
Grass
Forests
(Belair et al., in preparation)
Biome-BGC
10-year Clim
from runs (LAI)
LAI OVER SOUTHERN ONTARIO and SOUTHERN QUEBEC
PRELIMINARY TESTSTOWARDS an IMPLEMENTATION over
CANADA: HIGH-RESOLUTION NUMERICAL PREDICTION of
LAND SURFACE TEMPERATURES
QUALITATIVE EVALUATION AGAINST MODIS SURFACE TEMPS
Spatial variability of
land surface
temperature depends
on …
Vegetation
Albedo
Emissivity
Soil texture
Soil moisture
Radiative forcing
PLANS for OPERATIONAL IMPLEMENTATION at MSC (2013)
è120 hr forecast run (every 6hr)
t=0
Best estimates of Hourly Forcing
SW, LW – REG-15 km, 6-12 hr. – at surface
UU,VV – REG-15km, 0-6 hr. – at screen lev. (10m)
P0 – REG-15km, 0-6 hr. – at surface
Hourly Forcing at 1st atmospheric level
From Reg-15km and Global-33km forecasts
(TT, HU, SW, LW,UU,VV,P0,PR )
Forcing is downscaled and adapted to Gem-Surf Resolution
PR –Canadian Precipitation Analysis (CaPA) – at surface
TT, HU – Optimal Interpolation (OI) – at screen lev. (2m)
Analysis
Analysis
t-6h
6h. Gem-Surf
Run
Pre-Processor of Geophysical Fields
èCoherence & Consistency tests for GenPhysx and
UrbanX variables
è Calculation of time-dependent variables (e.g,LAI,α)
t=0
120h. Gem-Surf Forecast
Provides best estimates of :
• Soil Moisture
• Surface Temp.
Pre-Processor • Snow charac. (density, depth,albedo)
• Urban charac. (roof, wall, road temp. etc.)
è Continuous (Analysis) Cycle
Hourly Forcing
Analysis
t-12h
t-6h
Pre-Processor
06 Z Forecast
t=0
Pre-Processor
t+6h
Pre-Processor
12 Z Forecast
18 Z Forecast
120hr
120hr
t+12h
Pre-Processor
00 Z Forecast
120hr
t-6h
Pre-Processor
06 Z Forecast
120hr
Pre-Processor
12 Z Forecast
120hr
18 Z Foreca