Use Of AMSU data in the UK Mesoscale
Model
Brett Candy
Steven English, Richard Renshaw & Bruce Macpherson
Satellite Applications & Data Assimilation,
Met Office
ITSC-X111, Sainte Adele, Canada
© Crown copyright
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
„
ITSC X111 Slide 2
Future Work
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 timeliness
„
Initial tests of assimilating radiance data in the UK Mes
encouraging
– Information retained in the short-range
„
But…..objectives are different.
– Key forecast parameters cloud cover, precip and surface
temp
ITSC X111 Slide 3
UK Mesoscale Model 1
Model
Model Domain
Domain
(Grid
(Grid resolution=12km)
resolution=12km)
Background: Full Resolution AMSUB Imagery 89 GHz
ITSC X111 Slide 4
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)
ITSC X111 Slide 5
Data Acquisition
Washington
West Freugh
Local Passes
NESDIS
HRPT
1b data
AAPP
AAPP
1d data on HIRS
grid
UK Mes
NWP
ITSC X111 Slide 6
Comparisons for
quality monitoring
1d data on HIRS
grid
Global
NWP
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.
ITSC X111 Slide 7
Tuning AMSU Observation Errors
NOAA17
NOAA16
Global R Matrix
4.5
4
AMSUB
humidity
errors
3.5
RMS (o-b) K
3
Reduced to
2K
2.5
2
1.5
1
0.5
0
4
5
6
7
8
9
10
AMSU channels
ITSC X111 Slide 8
11
18
19
20
Mid-lat Cyclone Case Study
AVHRR IR image
AMSU data screening
green: lwp yellow: precip
red: AMSUB cirrus
ITSC X111 Slide 9
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 negligible
instrument 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
ITSC X111 Slide 10
Bias Correction 2
AMSU channels Mean O-B Difference (K) over Mesoscale Domain
Uncorrected
Radiances
Corrected
Radiances
ITSC X111 Slide 11
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
ITSC X111 Slide 12
Convective Event 1
Observations Used
Channel 19
Situation: Warm moist air
moving northwards, mixing
with cooler air at higher
latitudes
ITSC X111 Slide 13
dark colours
indicate
Negative o-b
model too dry
Channel 20
Convective Event 2
Integrated Water Vapour Analysis
AMSU
No AMSU
region >
30kgm-2-2
T+6 rainrate forecast
Radar
ITSC X111 Slide 14
AMSU
No AMSU
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
Hourly Precip, 0z 26th August 2001 T+6
Verifying
Radar
ITSC X111 Slide 15
Control
+AMSU
AMSU Impact on Cloud
T+6 Cloud Cover
AMSU
Clear
low
medium
high
ITSC X111 Slide 16
No AMSU
Validation: vis image
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
ITSC X111 Slide 17
Additional Slides
ITSC X111 Slide 18
Local – Global BT Difference
Channel 16
HIRS
Channel 15
~0.5 K
AMSU
Channel 5
ITSC X111 Slide 19
Channel 6
~0.02 K
Initialisation of the Mesoscale Model: Weights given to Var & MOPs data
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
T-3
ITSC X111 Slide 20
T-2
T-1
T+0
T+1
T+2
T+3