use of amsu data in the uk mesoscale...
TRANSCRIPT
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ITSC-X111, Sainte Adele, Canada © Crown copyright
Use Of AMSU data in the UK MesoscaleModel
Brett Candy
Steven English, Richard Renshaw & Bruce Macpherson
Satellite Applications & Data Assimilation,
Met Office
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ITSC X111 Slide 2
Talk Outline
Background and Motivation
Limited Area Models at the Met Office
Data Usage in the Mesoscale model
– Source of observations
– Data screening
Bias Correction
Impact Assessment
– Method
– Some results
Future Work
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ITSC X111 Slide 3
Background
Contribution of ATOVS in global NWP is very important
To date effort has focused on assimilating satellite data in global NWP
– Some data types are currently precluded by timelinessInitial tests of assimilating radiance data in the UK Mesencouraging
– Information retained in the short-rangeBut…..objectives are different.
– Key forecast parameters cloud cover, precip and surface temp
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ITSC X111 Slide 4
UK Mesoscale Model 1 Model Domain
(Grid resolution=12km)
Model Domain
(Grid resolution=12km)
Background: Full Resolution AMSUB Imagery 89 GHz
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ITSC X111 Slide 5
UK Mesoscale Model 2
Assimilation system:
– incremental 3D-Var
– assimilation window ±1½ hours
– 2 hour data cutoff
Observations:
– radiosondes, air reps, wind profilers
– land station reps, including visibility
– satellite winds from Meteosat
Additionally cloud cover and surface rainrate information is assimilated via a different route (i.e. outside of Var)
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ITSC X111 Slide 6
Data Acquisition
Local PassesHRPT
West Freugh
AAPP AAPP
NESDIS
1b data
Washington
1d data on HIRS grid
1d data on HIRS grid
Comparisons for quality monitoring
UK MesNWP
Global NWP
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ITSC X111 Slide 7
ATOVS Data Use
HIRS data not used – calibration problems associated with partial super swath
AMSU data– Remapped to HIRS grid (allows use of same code as global)– AMSUB 183 GHz channels over sea only
AMSU data screening– Liquid water test in AAPP → reject channels 4,5 & 20– Ice test on 183 GHz channels → reject channels 19,20– Rain test in AAPP → reject channels 4-8 & 18-20
Data Thinning– 1 observation every 40 km. More weight given to clear &
microwave clear scenes.
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ITSC X111 Slide 8
AMSU channels
Tuning AMSU Observation Errors
AMSUB humidity
errors
Reduced to 2K
0
0.5
1
1.5
2
2.5
3
3.5
4
4.5
4 5 6 7 8 9 10 11 18 19 20
RM
S (o
-b) K
NOAA17 NOAA16 Global R Matrix
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ITSC X111 Slide 9
Mid-lat Cyclone Case StudyAVHRR IR image AMSU data screening
green: lwp yellow: precip
red: AMSUB cirrus
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ITSC X111 Slide 10
Bias Correction 1
Airmass dependent predictors (Eyre, 1992)
– problem in a LAM is to sample enough representative synoptic systems
– could monitor departures over a year, assuming negligibleinstrument drift
Current solution is to use global bias correction coefficients
– assumes global and LAM NWP are unbiased
– monitoring with sondes confirms this, at least for the troposphere
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ITSC X111 Slide 11
Bias Correction 2AMSU channels Mean O-B Difference (K) over Mesoscale Domain
Uncorrected
Radiances
Corrected
Radiances
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ITSC X111 Slide 12
Strategy for Assessing Impact
Case study for poor operational forecast.– Convection over S.W. Britain– Rain forecasts compared to radar
Set of cases containing range of weather situations observed over UK.– Chosen by forecaster– Subjective verification from station reports of 6 hour precip, surface
temp & cloud cover– NOAA15 & 16 assimilated
Extended Trial.– Ran for 1 month– Avoids spin-up problems– Near Real Time to get operational boundary conditions– Forecasts assessed by forecaster– NOAA16 & 17 assimilated
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ITSC X111 Slide 13
Convective Event 1Observations Used
Channel 19 Channel 20
Situation: Warm moist air moving northwards, mixing with cooler air at higher latitudes
dark colours indicate
Negative o-b model too dry
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ITSC X111 Slide 14
Convective Event 2Integrated Water Vapour Analysis
region > 30kgm-2-2
AMSU No AMSU
T+6 rainrate forecast
Radar AMSU No AMSU
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ITSC X111 Slide 15
Verification of Case Studies
6 cases improved, 6 cases worsened due to inclusion of
AMSU
Worse case highlights difficulties of using sparse verification sites for reporting precipitation
Control +AMSU
Hourly Precip, 0z 26th August 2001 T+6
Verifying Radar
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ITSC X111 Slide 16
AMSU Impact on Cloud
Validation: vis image
Clear
low
medium
high
AMSU
No AMSU
T+6 Cloud Cover
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ITSC X111 Slide 17
Conclusions
Operational in Mesoscale model from May 2003.– NRT trial positive for cloud & visibility. – Including a significant fog clearance case.
Similar approach adopted for European model.Future Work– AMSUB at full resolution.
» Issues for qc & bias correction.» Extend number of channels
– Assimilation in regions of significant LWP. » Total humidity control variable. » 1D Var» 3D Var
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ITSC X111 Slide 18
Additional Slides
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ITSC X111 Slide 19
Local – Global BT DifferenceChannel 15 Channel 16
~0.5 K
HIR
S
Channel 6Channel 5
~0.02 K
AM
SU
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ITSC X111 Slide 20
Initialisation of the Mesoscale Model: Weights given to Var & MOPs data
T-3 T-2 T-1 T+0 T+1 T+2 T+3
VAR incs
T-3 T-2 T-1 T+0 T+1 T+2 T+3
Cloud incs
T-3 T-2 T-1 T+0 T+1 T+2 T+3
RainRate incs -from hourly fields
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International TOVS Study Conference, 13th
, TOVS-13, Sainte Adele, Quebec, Canada, 29
October-4 November 2003. Madison, WI, University of Wisconsin-Madison, Space Science and
Engineering Center, Cooperative Institute for Meteorological Satellite Studies, 2003.