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Land Component for Arctic System Reanalysis. Fei Chen and Michael Barlage Research Applications Laboratory (RAL) The Institute for Integrative and Multidisciplinary Earth Studies (TIIMES) National Center for Atmospheric Research. ASR components. Atmosphere component: WRF-ARW-3dvar

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land component for arctic system reanalysis

Land Component for Arctic System Reanalysis

Fei Chen and Michael Barlage

Research Applications Laboratory (RAL)

The Institute for Integrative and Multidisciplinary Earth Studies (TIIMES)

National Center for Atmospheric Research

Arctic System Reanalysis meeting, NCAR, Boulder,18 January 2008

asr components
ASR components
  • Atmosphere component: WRF-ARW-3dvar
  • Sea-ice component: Polar WRF sea-ice treatment
  • Greenland ice-sheet component: Polar WRF land-ice treatment
  • Land component: Noah and HRLDAS

Arctic System Reanalysis meeting, NCAR, Boulder,18 January 2008

outline
Outline
  • Overview of
    • Noah land surface model
    • High-resolution land data assimilation system (HRLDAS)
  • HRLDAS plan for ASR

Arctic System Reanalysis meeting, NCAR, Boulder,18 January 2008

why do we need land surface models in wrf
Why Do We Need Land Surface Models in WRF?
  • Need to account for subgrid-scale fluxes
  • The lower boundary is the only physical boundary for atmospheric models
  • LSM becomes increasingly important:
    • Cloud/cumulus schemes are sensitive to the PBL structures
      • The PBL growth over land is driven primarily by
        • Entrainment of warmer air from the free troposphere
        • Surface sensible and latent fluxes
    • WRF model increase grid-spacing (1-km and sub 1-km). Need to capture mesoscale circulations forced by surface variability in albedo, soil moisture/temperature, landuse, and snow
  • Challenge:
    • Land surface variability and complex land surface/hydrology processes
    • Initialization of soil moisture/temperature is a challenge

Arctic System Reanalysis meeting, NCAR, Boulder,18 January 2008

the advanced noah lsm for wrf
The Advanced Noah LSM for WRF
  • Multi-institutional collaborative effort among NCEP, NCAR, U.S. Air Force Weather Agency, NASA, and university community to develop the unified Noah LSM for numerical weather prediction community
  • Designed for high-resolution realtime weather forecast, air pollution, local and regional hydrologic applications
  • Noah implemented/tested in
    • Operational NCEP models:
      • NAM (12-km, 60-layer) regional model and data assimilation system
      • GFS global forecast model
      • GFDL hurricane model
    • 25-year Regional Reanalysis system (32-km, 60-layer)
    • Navy: operational COAMPS
  • Coupled WRF/Noah operational:
    • AFWA: WRF-ARW for operations July 2006
    • NCEP: WRF-NMM for operations June 2006
noah lsm in wrf v2 2 dec 2006
Noah LSM in WRF V2.2 (Dec 2006)
  • Improved Physics
    • Frozen-ground physics
    • Patchy snow cover, time-varying snow density and snow roughness length
    • Soil heat flux treatment under snow pack
    • Modified soil thermal conductivity
    • Seasonal surface emissivity
    • Simple treatment of urban landuse
  • Additional background fields
    • Monthly global climatology albedo (0.15 degree)
    • Global maximum snow albedo database
  • Import various sources of soil initial data
  • New single-layer urban canopy model

Arctic System Reanalysis meeting, NCAR, Boulder,18 January 2008

noah lsm includes
Noah LSM includes
  • Land ice (glacier)
  • Sea ice
    • The above two will be treated by components in Polar-WRF.
  • The routines in Noah to deal with these two processes will not be used for ASR
  • Land-vegetation
  • Land-bare soil

Arctic System Reanalysis meeting, NCAR, Boulder,18 January 2008

1 km global landuse map
1-km Global Landuse Map

determine Rc_min, and other vegetation parameters

Arctic System Reanalysis meeting, NCAR, Boulder,18 January 2008

slide9

Global Soil Texture Map

determine Kt, and other soil parameters

Arctic System Reanalysis meeting, NCAR, Boulder,18 January 2008

seasonality of vegetation based on monthly ndvi
Seasonality of vegetation Based on monthly NDVI

Arctic System Reanalysis meeting, NCAR, Boulder,18 January 2008

slide11

WRF/ Noah Snow Storm Case 18 March 2003

24-h snow water equivalent change valid at 00Z 19 March

Snow melted

too quickly in

the previous version

Of Noah

Obs 24-h SWE

change valid at

06Z 19 March

Arctic System Reanalysis meeting, NCAR, Boulder,18 January 2008

frozen ground physics in noah improve simulations of soil temperature soil moisture and runoff
Frozen-ground physics in Noah improve simulations of soil temperature, soil moisture, and runoff

Evaluation using Rosemount Field Experiment Data, Minnesota

freezing

rain+snow melt

thawing

Noah (OSU)

Noah (OSU)

Noah with frozen ground

Noah with frozen ground

observations

observations

Details see Koren, Schaake, Mitchell, Duan, Chen, Baker, 1999, JGR

slide13
New fix in the Noah Penman equation for snow-covered surface reduce low-level Q bias (WRF 3.0)2m-RH, 18Z, 6 March 2007

Modified

Difference (Modif-Orig)

Snow cover

motivation for hrldas
Motivation for HRLDAS
  • Mesoscale models need to capture PBL structures and motions resulted from surface forcing
  • No routine high-resolution soil observation network
  • Ultimate approach is to combine observation, modeling, and data assimilation
  • Alternatives: Using observed rainfall, analyzed downward solar radiation, and atmospheric analysis to drive LSMs in uncoupled mode
    • NCEP NLDAS: North America, 1/8 degree
    • AFWA ARGMET: global, 47-km, long-term archive
    • NCAR High-resolution land data assimilation system (HRLDAS)

Arctic System Reanalysis meeting, NCAR, Boulder,18 January 2008

ncar high resolution land data assimilation system hrldas concept
NCAR High-Resolution Land Data Assimilation System (HRLDAS) Concept

Run uncoupled LSM on the same grid as mesoscale NWP models

  • Using the same LSM as in coupled NWP model: same soil moisture climatology
  • No Mis-match of terrain, land use type, soil texture, physical parameters between sources of soil data and NWP models
  • No interpolation and soil moisture conversion

Arctic System Reanalysis meeting, NCAR, Boulder,18 January 2008

hrldas capturing small scale variability an example over conus
HRLDAS: Capturing Small-Scale VariabilityAn example over CONUS
  • Input:
    • 4-km hourly NCEP Stage-II rainfall
    • 1-km landuse type and soil texture maps
    • 0.5 degree hourly GOES downward solar radiation
    • 0.15 degree AVHRR vegetation fraction
    • T,q, u, v, from model based analysis
  • Output: long term evolution of multi-layer soil moisture and temperature, surface fluxes, and runoff

4-km HRLDAS surface soil moisture

in IHOP-2002 domain 12 Z May 29 2002

Arctic System Reanalysis meeting, NCAR, Boulder,18 January 2008

slide17

Spin-up of Soil Moisture (top 10 cm soil)

Initial time

From coarse resolution of EDAS field

46 days later

Heterogeneity was developed in the 4-km domain

Arctic System Reanalysis meeting, NCAR, Boulder,18 January 2008

spin up of soil moisture
Spin-up of Soil Moisture

Volumetric soil moisture

RMS difference (m3m-3)

0.02 <

0.1 <

0.02

0.1

1st layer soil moisture

3rd layer soil moisture

Coarse

soil

Medium

soil

Fine

soil

Chen et al., J. Appli. Meteorol. Climate, 2007

hrldas for asr
HRLDAS for ASR
  • Blending atmospheric and land-surface observations and land surface model
  • To provide land state variables for driving the coupled WRF/Noah-Polar modeling system
    • Soil moisture (liquid and solid phase)
    • Soil temperature
    • Snow water equivalent and depth
    • Canopy water content
    • Vegetation characteristics
  • To provide long-term evolution of the above variables plus surface hydrological cycle (runoff, evaporation) and energy cycle (surface heat flux, ground heat flux, upward long-wave radiation)

Arctic System Reanalysis meeting, NCAR, Boulder,18 January 2008

asr land modeling timeline
ASR Land Modeling Timeline

HRLDAS

Spin-up

HRLDAS and WRF coupled simulations

1998

2000

2010

Arctic System Reanalysis meeting, NCAR, Boulder,18 January 2008

asr land modeling timeline21
ASR Land Modeling Timeline

HRLDAS Spin-up

Forcing Data

1hr

1hr

Hourly Forcing Data

GLDAS: T,q,U,p,SW,LW

CMAP: precipitation

GDAS: SW, LW

GOES: SW,LW

Air Force: snow

1998

2000

Arctic System Reanalysis meeting, NCAR, Boulder,18 January 2008

asr land modeling timeline22
ASR Land Modeling Timeline

HRLDAS and WRF coupled simulations

HRLDAS communicates to WRF

3hr

1hr

1hr

1hr

2000

2010

Blended WRF Input to HRLDAS

Blended Hourly Forcing Data

WRF: T,q,U,SW,LW

CMAP: precipitation

GDAS: snow, SW, LW

Air Force: snow

GLDAS: SW, LW

Improved Land Surface States

Snow

Soil Moisture/Temperature

Land Surface Temperature

comparison of sw radiation inputs
Comparison of SW radiation inputs

Arctic System Reanalysis meeting, NCAR, Boulder,18 January 2008

satellite data modis avhrr
Satellite data - MODIS & AVHRR
  • fPAR/LAI: MODIS 8-day, 1km, 2000-current
  • Albedo: MODIS 8-day, 1km, 2000-current
  • Land Skin Temperature: MODIS 8-day and daily, 1km and 6km, 2000-current
  • Green Vegetation Fraction: MODIS-based, 1km, 16-day, 2000-current
  • Green Vegetation Fraction: AVHRR, weekly, 0.144deg, 1982-2005

Arctic System Reanalysis meeting, NCAR, Boulder,18 January 2008

improved surface spatial heterogeneity
Improved Surface Spatial Heterogeneity

Arctic System Reanalysis meeting, NCAR, Boulder,18 January 2008

wrf domain

600 x 600 cells

  • 20 km
  • polar projection
  • ref_lat = 90
  • ref_lon = 0
  • truelat = 70
  • stand_lon = -110
WRF domain

Arctic System Reanalysis meeting, NCAR, Boulder,18 January 2008

modis 1km vegetation data june 18 2002
MODIS 1km Vegetation DataJune 18, 2002

Arctic System Reanalysis meeting, NCAR, Boulder,18 January 2008

vegetation data modis vs wrf june 18 2002
Vegetation Data: MODIS vs WRFJune 18, 2002

Absolute difference

Relative difference

hrldas algorithm
HRLDAS Algorithm

Canopy water,

Snow, Tskin ,Tsoil,

Soil moisture

Forcing data:

GRIB format

SW, LW

T,q,ps,U,precip

WPS Metgrid

Interpolated

forcing data:

NetCDF format

Canopy water,

Snow, Tskin,Tsoil,

Soil moisture

SW, LW

T,q,ps,U,precip

Merged

IC file

Merged

forcing file

Static

input

WPS Geogrid

HRLDAS

….

MODIS

Arctic System Reanalysis meeting, NCAR, Boulder,18 January 2008

preliminary hrldas spin up july 1 1999
Preliminary HRLDAS Spin-up July 1, 1999

Downward Solar Radiation Incident at the Surface

Hourly GLDAS forcing data based on observed clouds and simple 3-layer radiation model

Arctic System Reanalysis meeting, NCAR, Boulder,18 January 2008

preliminary hrldas spin up july 1999
Preliminary HRLDAS Spin-up July 1999

Surface Skin Temperature

Hourly HRLDAS output plotted at 2Z every day for a month

Arctic System Reanalysis meeting, NCAR, Boulder,18 January 2008

preliminary hrldas spin up july 199932
Preliminary HRLDAS Spin-up July 1999

Soil Moisture 2nd Layer

Hourly HRLDAS output plotted at 2Z every day for a month

Arctic System Reanalysis meeting, NCAR, Boulder,18 January 2008

summary
Summary
  • HRLDAS will provide high-resolution on the same grid of WRF-3dvar
    • land-state variables to drive WRF/Noah for analysis phase
    • Long-term evolution of surface hydrological and energy budget components
  • The latest Noah (to be released in March 2008 in WRF 3.0) is used for HRLDAS for ASR
    • Possible enhancements: Noah model physics and data assimilation
  • Collection of atmospheric forcing and satellite data for use in HRLDAS is in progress
  • Need to coordinate with
    • “atmospheric” team
      • WRF configuration, duration of reanalysis, hourly WRF output
    • “evaluation” team
      • Data collection and verification approach

Arctic System Reanalysis meeting, NCAR, Boulder,18 January 2008