scatterometers at knmi; towards increased resolution [email protected] hans bonekamp marcos...
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Scatterometers at KNMI;Towards Increased
Resolution
[email protected] BonekampMarcos Portabella
http://www.knmi.nl/scatterometer
Isabel
Miami Workshop 8-10 Feb ‘05 2
Overview Scatterometer
winds contain mesoscale detail not captured by NWP fields, but also noise
Mesoscale information is useful for nowcasting
MSS: an effective way of controling the noise
Spatial analysis in progress
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Spectral tail
Spectral response is used in engineering for design of noise properties
Ene
rgy
dens
ity
Ideal
Noisy
Truncated
Wave number
Being used now to increase SeaWinds resolution at KNMI
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Bad rainy case
Nadir noisy
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Broad Wind Direction Minima
Pro
bab i
lit y
of
Wind direction ()
Local minima
Local minima do not represent solution P
Solution bands
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A wide range of probable solutions exists in nadir(of 144 solutions per WVC)
Locally, 100-km product is pretty Unique(P threshold is 10-7)
Broad Minima
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Spatial filter: Mass
conservation Continuity
equation
0U = 0
Vertical motions < horizontal motion
Little divergence Mostly rotation
(extratropics)
Meteorological balance (2D-VAR)
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100 kmMultiple Solution
Scheme
1. Full use of solution probability info
2. Meteorological balance in Ambiguity Removal (2D-VAR)
(Portabella&Stoffelen, 2003)
Smooth solution
exists@100
km
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Standard scheme: < 4 solutions
Erratic at low wind speeds
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Multiple Solution Scheme
Smooth representation
Mesoscale detail kept
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ECMWF Position error
ECMWF First Guess ECMWF First Guess
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General MSS performance @100 km
Mean vector RMS difference with ECMWF FGAT (m/s)
Swath region Standard procedure
MSS NCEP
Sweet 2.48 2.23 2.85
Nadir 2.98 2.45 2.96
MSS better than 4-solution standard, in particular at nadir NCEP background for 2DVAR much worse
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NOAA MSS @ 25 km
Improved coldfront
BetterAroundrain
50 kmPlots !
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NOAA MSS @ 25 km
Improved inflow
BetterAroundrain
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MSS @ 25 km
NOAA
Improved inflow
NCEP
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SummarySummary
- The use of more wind retrieval information in MSS allows consistent mesoscale features in the 25-km product
- A balanced spatial filter such as 2D-VAR is effective in removing noise and keeping meteorology, direction or vector uniformity constraints are less effective
- At 100-km the background wind used for ambiguity removal appears irrelevant, but this needs checking at 25 km
- The spectral behaviour of 2D-Var at 25-km needs to be evaluated
- Verification against buoys is underway
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Further ReferencesFurther ReferencesFor scatterometer-related papers, documentation,
and wind products of the SAFs please refer to
http://www.knmi.nl/scatterometer
We look forward to sharing- Our scatterometer processing software- Our ERS and QuikScat products - Our new wind stress products- Our experience
We fund visiting scientists
E-mail: [email protected]
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DIRTH (NOAA product)JPL’s Direction Interval Retrieval Threshold Nudging
DIRTH TN removes noise in 25-km product, but at some expenseUnnormalised notion of P (WVC and speed dependence)P segments exclude probable solutions (T=0.8; 0.2 left out)Medium filter ignores P within segmentNo meteorological balance constraints
DIRTH results inVery smooth fields (> 100 km)Loss of meteorological detail
KNMI proposes Multiple Solution Scheme
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Scatterometer Data Processor
Observations Inversion Ambiguity Removal
Wind Field
OUTPUTOcean Surface Radar Backscatter Observations
Inversion Ambiguity Removal
Quality Control
Pre- Process
Wind Field
INPUTOUTPUT
Quality Monitor
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Ambiguity Probability
Quadratic inner loop approximation?
IFS experiments from KNMI + some visits
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http://www.knmi.nl/scatterometer
QuikSCAT
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NWP Impact @ 100 km
Storm near
HIRLAM misses wave;SeaWinds should bebeneficial!
29 10 2002
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Satellite Application Facilities
Scatterometer sea surface wind R&D Quality control, rain and ice screening Spatial averaging (100 km 25 km) Inversion: Computation of wind solutions and associated
probabilities from measurement information Determination of information content; Observation
operatorAmbiguity removal (spatial filter to determine unique field)
Active monitoring and control (of instrument and processing)
Web site (visualisation) and product distribution
Product enhancement Preparation for ASCAT wind production (METOP; 2006)
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Detail in 100-km product
KNMI 100km
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Product Verification with ECMWF Winds
SD KNMI NOAA Speed 1.31 1.64Direction
13.58 14.58
U 1.60 1.96 V 1.58 1.80 Comparison for a set of triple KNMI-NOAA-ECMWF points
KNMI 100-km product better for NWP assimilation than NOAA NOAA wind speed score relatively bad due to
wind direction spatial filter KNMI rejects less high wind points (Portabella &, 2000)