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Land and Hydrology modeling in NCEP Weather and Climate Prediction Models Ken Mitchell Environmental Modeling Center National Centers for Environmental Prediction – PowerPoint PPT presentation

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Title: Land and Hydrology modeling in


1
Land and Hydrology modeling in NCEP Weather and
Climate Prediction Models

Ken Mitchell
Environmental Modeling Center National Centers
for Environmental Prediction
NOAA Science Advisory Board November 6, 2001
NCEP Where America's Climate and Weather
Services Begin
2
OVERARCHING THEMES
Linkages between weather, water, and climate
predictions Multiple disciplines of
meteorology, hydrology, oceanography Dynamical
model predictions at multiple time and space
scales Fundamental importance of vast computer
power Ensemble prediction and probabilistic
forecasts An emerging community modeling
approach Central role of data assimilation for
atmosphere, land, ocean Partnerships to infuse
science and technology into operations
3
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6
NCEP Dynamical Model Prediction Suite
1 - Ocean seasonal forecast model coupled
ocean/atmosphere -- predict tropical
Pacific SST (issued monthly out to 11 months)
-- GFDL MOM ocean model (order 50-150 km
resolution) 2 - Atmospheric seasonal forecast
model (SFM) coupled atmosphere/land --
predict global atmospheric state (issued monthly
out to 7 months) -- NCEP global climate
model (order 200 km resolution) 3 - Atmospheric
medium-range forecast model (MRF) coupled
atmosphere/land -- predict global
atmospheric state (issued daily out to 15 days)
-- NCEP global medium-range model (order 75 km
resolution) 4 - Atmospheric short-range forecast
model (ETA) coupled atmosphere/land --
predict N. American atmospheric state (4 times
daily out to 2.5 to 3.5 days) -- NCEP
regional short-range model (order 22 km
resolution) 5 - Atmospheric nested short-range
forecast model (N-ETA) coupled atmos/land
-- predict regional atmospheric state, (4 times
daily out to 2 days) -- NCEP regional
short-range forecast model (order 10 km
resolution) 6 - Hurricane forecast model (GFDL)
and RUC model (FSL).
7
Community Weather and Climate Models NCEP
partnerships
1 - Community global weather and climate model
Earth System Model framework
Atmosphere, Ocean, and Land modules
Partners NCEP, NASA, NCAR, GFDL, DOE, MIT,
others 2 - Community Weather Research and
Forecast (WRF) regional model
Ultra-high 1-km spatial resolution for
national/regional domains Resolve
individual thunderstorm cells Partners
NCEP, NCAR, FSL, AFWA, others
8
Relocatable Eta Nests
  • High-resolution regional Eta forecasts "nested"
    inside of the parent Eta (22km/50 lev resolution)
  • Six nested domains are being run.
  • Hawaii and Puerto Rico twice per day
  • Alaska, East, West, Central U.S. once per day
  • Output available on NCEP ftp
  • server

9
Homeland Defense Initiative
  • NCEP Eta weather model
  • is linked with NOAA/ARL radiological dispersion
    model known as HYSPLIT.
  • This linked pair of models is executed at
    ultra-high spatial resolution of 4-km over any of
    the domains at right.

10
High Performance Computer
IBM SP at Bowie Computer Center in Bowie, MD
  • Ingests over 3.9 million observation reports
    daily
  • Produces 100 gigabytes of information daily
  • NCEP transmits 174,314 products each day
  • Second most powerful weather supercomputer in the
    world !
  • ( 46X Faster than the Cray C90, 3.0 tflops peak
    performance )
  • 584 nodes with four 375 MHz CPUs each (2336
    processors)

NCEP Central Operations, Oct 2001
11
IBM SUPERCOMPUTER Operational December
1999 Follow-on NCEP Modeling Advances
1 - Seasonal Forecast Model Nov 01 --
transitioned to operations on IBM (from former
demo platform) -- first formally operational
seasonal forecast system in the world 2 - Global
Medium-Range Model Jan 00 -- resolution
increase from 105-km/28-layers to
75-km/42-layers 3 - Eta Regional Short-Range
Model -- increase resolution from
33-km/45-layers to 22-km/50-layers Sep 00
-- increase resolution from 22-km/50-layers to
12-km/60-layers Nov 01 Also improvements in
several NCEP models in cloud microphysics,
precipitation assimilation, ingest of new radar
and satellite observations, improved land surface
physics, new tropical cyclone initialization.   Ne
xt Slide Example of impact of Eta Model
resolution increase from 22-km to 12-km on a
heavy convective precipitation event in Texas.
12
Impact of Resolution on Model Precipitation
Forecast
22 km Operational Meso Eta
10 km Experimental Threats Meso Eta
2.2
4.3 Better location Better intensity
Observed
7.0 5.7
13
Hydrological Applications Need Probabilistic
Precipitation Forecasts
Eta model-based 24-hour forecast valid 19 May 01
24HR PQPF OF .25
14
Ensemble Forecasting
Schematic example of ensemble predictions (used
for derivation of probabilistic forecasts
and measures of predictability).
15
Example of 8-day PQPF Probabilistic Quantitative
Precipitation Forecast (calibrated to remove bias)
16
NWS Office of Hydrologic Development
(OHD) Ensemble Forecast Strategy for Water
Management
17
Realistic soil moisture in coupled land-atmosphere
climate models improves seasonal predictability
of precipitation in the warm season
18
Improving Weather and Climate Prediction Becoming
a Complete Earth System Endeavor
1 - ATMOSPHERE troposphere, stratosphere -
initial conditions require atmosphere data
assimilation 2 - OCEAN deep ocean, seas,
coastal ocean, sea ice - initial conditions
require ocean data assimilation 3 -
LAND soil, snowpack, vegetation, runoff -
initial conditions require land data
assimilation
19
GAPP GEWEX Americas Prediction Project (NOAA
Office of Global Programs)
Improving weather and climate prediction
by bringing together meteorologists and
hydrologists in (A) coupled land-atmosphere
modeling (B) land data assimilation (C) water
resource applications of weather and
climate forecasts
20
The GAPP model development strategy
21
GAPP-strategy for research infusion to operations
22
Collaborators
23
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24
NCEP Eta model forecast during July
1998 Texas/Oklahoma drought, 24-hour forecast
valid 00Z 27 July 1998
In late July 1998, after nearly two months of
self-cycling the land states in the EDAS, the Eta
model successfully captured the extremely dry
soil moisture (upper left) and warm soil
temps (upper right) over the Texas/Oklahoma region
, yielding forecasts of high 2-m air temps
(lower left) and deep, dry, hot boundary
layers that verified well against raobs
(e.g., at Norman, OK lower right).
soil moisture availability (1-m)
soil temperature (5-cm)
air temperature (2-meter)
Norman, OK sonde (obssolid, modeldashed)
25
Eta model Oct 2001 end-of-month soil moisture
states and monthly observed total precipitation.
26
Monthly OBSERVED PRECIPITATION accumulations Inter
annual variability of North American Monsoon -
interior Southwest
July 1999
July 2000
total precipitation (mm)
dry
moist
departure from normal (mm)
Monthly observed precipitation accumulation based
on 0.25 deg lat/lon gridded analysis of
daily total gage-only data (Higgins, R.W., W. Shi
and E. Yarosh, 2000 Improved United States
Precipitation Quality Control System and
Analysis. NCEP/Climate Prediction Center ATLAS
No. 7, 40 pp).
27
NORTH AMERICAN MONSOON Eta model captures
interannual variability of daytime maximum
temperature and model soil moisture
July 1999
July 2000
Eta model end-of-month 2nd layer volumetric soil
moisture
relatively moist
relatively dry
Eta model monthly- mean 2-m (C) air temperature
vs obs interior Southwest
interior Southwest
28
NOAH LAND-SURFACE MODEL UPGRADES
cold season processes (Koren et al 1999) -
patchy snowcover - frozen soil (new state
variable) - snow density/snow depth (new
state variable) bare soil evaporation
refinements - parameterize upper sfc crust cap
on evap soil heat flux - new soil thermal
conductivity (Peters-Lidard et al 1998) -
under snowpack (Lunardini, 1981) - vegetation
reduction of thermal cond. (Peters-Lidard et
al 1997) surface characterization- maximum snow
albedo database (Robinson Kukla 1985)-
dynamic thermal roughness length refinements
vegetation - deeper rooting depth in forests -
canopy resistance refinements
NOAH LSM tested in various land-model intercompari
son projects, e.g. PILPS, GSWP, and (near-future)
DMIP.
29
NOAH LSM soil thermodynamics tested successfully
by OHD in Sacramento soil water accounting model
(SAC-SWA). Example below observed air
temperature (top), and observed (white) and
modelled (red) soil temperature at 20 cm, 40 cm,
and 80 cm at Valdai, Russia (Oct 71-Sep 72).
30
NOAH LSM performs well in U. Arizona multi-criteri
a objective calibration system. NOAH LSM chosen
as one of several land models to be used in their
NSF Science and Tech Center.
31
Major Recent Multi-Institution Initiative LDAS
Land Data Assimilation System
GOAL provide soil moisture/temperature initial
conditions Superior to present EDAS METHOD
drive stand-alone uncoupled land-surface
models with observed gage/radar precipitation and
satellite-derived surface solar insolation. -
bypass atmospheric model precipitation and
radiation biases ADDITIONS assimilate
satellite-derived soil moisture and skin
temperature - test land-data assimilation tools
(e.g. adjoint models, variational methods, Kalman
filtering, surface emissivity models)
32
Real-time National LDAS Demonstration (Hosted by
NCEP/EMC Partners NWS/OHD, NESDIS/ORA,
NASA/GSFC, Princeton U., U. Washington, Rutgers
U., U. Maryland, others)
U.S. domain at 1/8 deg. executed from Apr
1999 to present (ongoing) - hosted on NCEP
SGI-platform - website hosted at NASA/GSFC
- retrospective runs back to Sep 1996 nearly
complete (NASA-provided forcing) hourly surface
forcing - precipitation, incoming solar,
downward longwave, air temperature,
humidity, wind speed 4 land-models executing in
parallel - NOAH (NCEP), VIC (Princeton),
MOSAIC (NASA), SAC-SWA(NWS-OHD) - 15 to 60
minute time steps common outputs - soil
moisture temperature, snowpack, surface fluxes
of water and energy, snowmelt, runoff
common streamflow connectivity and routing model
- provided by Univ. Washington and Princeton
33
NWS/OHD provided soil classes on LDAS domain
Soils classification map as derived by NWS/OHD
for the LDAS project for the 1/8-deg LDAS grid,
using the 11-layer, 16-texture 1-km Penn
State STATSGO data base (D. Miller, GAPP PI) and
5-minute ARS FAO data.
34
NOAH LSM 4-layer soil moisture from
National-LDAS (valid 29 Feb 2000, 12Z)
35
The 188 basins chosen for LDAS-project streamflow
validation using the respective USGS streamflow
gaging stations. (Example time series for the
two labeled basins are shown in next figure.)
36
NOAH LSM LDAS streamflow validation at two USGS
gaging stations Upper Susquehanna (station No.
01503000 42.0353N - 75.8033W) and South
Fork Shenandoah (station No. 01631000 38.9139N -
78.2111W) for the period 21 June to 08 December
2000.
37
Future directions
Propagate/unify NOAH LSM in all NCEP global and
regional, weather and climate models Extend
national LDAS demonstration to global domain -
in collaboration with NASA/GSFC (now underway)
Demonstrate impact of land-surface initial
conditions and physics on seasonal climate
predictability - especially warm season
Demonstrate impact of regional climate models on
seasonal climate predictability
38
Issues for NOAAs Science Advisory Board
1 - Expand research into methods to account for
weather and climate model forecast precipitation
biases in hydrological models and water resource
applications. 2 - Increase emphasis on improving
forecast model physical parameterizations of
precipitation and water cycle processes cloud
microphysics, deep convection, cloud-radiation
feedbacks, PBL fluxes and land-surface
processes. 3 - Stay the course on developing
community weather and climate models, and the
linkages between weather and climate prediction.
4 - Sustain momentum towards aggressive expansion
of supercomputer power and mass-storage systems.
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