slide 1© ecmwf assimilation of atovs radiances at ecmwf: bias correction and impact in nwp enza di...
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Slide 1 © ECMWF
Assimilation of ATOVS radiances at ECMWF: Bias correction and impact in NWP
Enza Di Tomaso* and Niels BormannECMWF
*EUMETSAT fellow
Slide 2 © ECMWF
Assimilation of ATOVS radiances at ECMWF: Bias correction and impact in NWP
Enza Di Tomaso* and Niels BormannECMWF
*EUMETSAT fellow
Slide 3 © ECMWF
Assimilated ATOVS radiances ●HIRS: channel 4-7, 11, 14, 15 over sea; 12 over sea + low orography only●AMSU-A: channels 5,6 over sea + low orography; 7-14 land+sea●AMSU-B/MHS: channel 5 over sea only; 3,4 sea+low orography
HIRS ( 3 used)
AMSU-A (5 used)
AMSU-B/MHS (3 used)
NOAA-15 no: unstable yes (not ch 6, 11, 14)
no: quality
NOAA-17 yes Instrument failed no (since Dec 09)
NOAA-18 no: unstable yes yes
NOAA-19 yes yes (not ch 8) yes (not ch 3)
AQUA n/a yes (not ch 5 & 7; 6 over sea only)
n/a
METOP-A yes yes(not ch 7)
yes
Slide 4 © ECMWF
Assimilated ATOVS radiances ●HIRS: channel 4-7, 11, 14, 15 over sea; 12 over sea + low orography only●AMSU-A: channels 5,6 over sea + low orography; 7-14 land+sea●AMSU-B/MHS: channel 5 over sea only; 3,4 sea+low orography
HIRS ( 3 used)
AMSU-A (5 used)
AMSU-B/MHS (3 used)
NOAA-15 no: unstable yes (not ch 6, 11, 14)
no: quality
NOAA-17 yes Instrument failed no (since Dec 09)
NOAA-18 no: unstable yes yes
NOAA-19 yes yes (not ch 8) yes (not ch 3)
AQUA n/a yes (not ch 5 & 7; 6 over sea only)
n/a
METOP-A yes yes(not ch 7)
yes
Slide 5 © ECMWF
Assimilated ATOVS radiances ●HIRS: channel 4-7, 11, 14, 15 over sea; 12 over sea + low orography only●AMSU-A: channels 5,6 over sea + low orography; 7-14 land+sea●AMSU-B/MHS: channel 5 over sea only; 3,4 sea+low orography
HIRS ( 3 used)
AMSU-A (5 used)
AMSU-B/MHS (3 used)
NOAA-15 no: unstable yes (not ch 6, 11, 14)
no: quality
NOAA-17 yes Instrument failed no (since Dec 09)
NOAA-18 no: unstable yes yes
NOAA-19 yes yes (not ch 8) yes (not ch 3)
AQUA n/a yes (not ch 5 & 7; 6 over sea only)
n/a
METOP-A yes yes(not ch 7)
yes
Part 1
Slide 6 © ECMWF
Assimilated ATOVS radiances ●HIRS: channel 4-7, 11, 14, 15 over sea; 12 over sea + low orography only●AMSU-A: channels 5,6 over sea + low orography; 7-14 land+sea●AMSU-B/MHS: channel 5 over sea only; 3,4 sea+low orography
HIRS ( 3 used)
AMSU-A (5 used)
AMSU-B/MHS (3 used)
NOAA-15 no: unstable yes (not ch 6, 11, 14)
no: quality
NOAA-17 yes Instrument failed no (since Dec 09)
NOAA-18 no: unstable yes yes
NOAA-19 yes yes (not ch 8) yes (not ch 3)
AQUA n/a yes (not ch 5 & 7; 6 over sea only)
n/a
METOP-A yes yes(not ch 7)
yes
Part 1
Part 2
Slide 7 © ECMWF
Assimilated ATOVS radiances ●HIRS: channel 4-7, 11, 14, 15 over sea; 12 over sea + low orography only●AMSU-A: channels 5,6 over sea + low orography; 7-14 land+sea●AMSU-B/MHS: channel 5 over sea only; 3,4 sea+low orography
HIRS ( 3 used)
AMSU-A (5 used)
AMSU-B/MHS (3 used)
NOAA-15 no: unstable yes (not ch 6, 11, 14)
no: quality
NOAA-17 yes Instrument failed no (since Dec 09)
NOAA-18 no: unstable yes yes
NOAA-19 yes yes (not ch 8) yes (not ch 3)
AQUA n/a yes (not ch 5 & 7; 6 over sea only)
n/a
METOP-A yes yes(not ch 7)
yes
Part 1
Part 2
Slide 8 © ECMWF
Assimilation of ATOVS radiances at ECMWF: Bias correction and impact in NWP
(Part 1) .
Enza Di Tomaso* and Niels BormannECMWF
*EUMETSAT fellow
Slide 9 © ECMWF
Part 1: revision of AMSU-A bias correction
Bias correction of ch12 & ch14 (Part 1a)
AMSU/A(from http://disc.sci.gsfc.nasa.gov/AIRS/documentation/)
Slide 10 © ECMWF
Part 1: revision of AMSU-A bias correction
Bias correction of ch12 & ch14 (Part 1a)
Bias correction of ch5 to 8 (Part 1b, ongoing work)
AMSU/A(from http://disc.sci.gsfc.nasa.gov/AIRS/documentation/)
Slide 11 © ECMWF
Part 1: revision of AMSU-A bias correction
Bias correction of ch12 & ch14 (Part 1a)
Bias correction of ch5 to 8 (Part 1b, ongoing work)
Assimilation of surface-sensitive channels (future work)
(by Tom Greenwald)AMSU/A
(from http://disc.sci.gsfc.nasa.gov/AIRS/documentation/)
Slide 12 © ECMWF
Bias correction of ch 12 & 14: interaction between forecast model error and bias correction
T511 experiment (black) versus T255 experiment(red)
T1279 experiment (black) versus T255 experiment(red)
Issues with high spatial model resolution: radiosondes show resolution-dependent temperature biases in the stratosphere
Radiosonde T
RadiosondeT
N.Hemis
N.Hemis
Slide 13 © ECMWF
Experiment description●Revision of the bias correction of AMSU-A stratospheric channels peaking
where the forecast model error is particularly significant
– “noBC experiment”: no bias correction applied to AMSU-A ch12 and ch14
– “sBC experiment”: scan bias correction (polynomial in the scan angle and with no constant) applied to AMSU-A ch12 and ch14
– “N19 anchor experiment”: ● scan bias correction (with no constant) applied to AMSU-A ch12 and
ch14 on NOAA-19 ● scan bias and offset correction applied to AMSU-A ch12 and ch14 on
other satellites
Experiments were run over ‘summer’ (20 Jul – 31 Oct 2009) and ‘winter’ (6 Dec – 31 Mar 2010) at T511 resolution
Slide 14 © ECMWF
Experiment description●Revision of the bias correction of AMSU-A stratospheric channels peaking
where the forecast model error is particularly significant
– “noBC experiment”: no bias correction applied to AMSU-A ch12 and ch14
– “sBC experiment”: scan bias correction (polynomial in the scan angle and with no constant) applied to AMSU-A ch12 and ch14
– “N19 anchor experiment”: ● scan bias correction (with no constant) applied to AMSU-A ch12 and
ch14 on NOAA-19 ● scan bias and offset correction applied to AMSU-A ch12 and ch14 on
other satellites
Experiments were run over ‘summer’ (20 Jul – 31 Oct 2009) and ‘winter’ (6 Dec – 31 Mar 2010) at T511 resolution
Slide 15 © ECMWF
Departure statistics of the first guess and analysis
Radiosonde T
MetOp AMSU-A TB
N.Hemis
No bias correction of AMSU-A ch12 ad ch14 improves the fit to temperature observations
“noBC experiment” (black) versus control (red)“noBC experiment” BC (pink) versus control BC (green)
Slide 16 © ECMWF
Comparison with the SPARC climatology“noBC experiment” minus control control minus climate
Slide 17 © ECMWF
“noBC experiment” RMSE – control RMSE
Forecast impact“noBC experiment” versus control (verified against observations), summer
controlGOOD
“noBC experiment”
GOOD
The impact for the forecast of the 50hPa geopotential of the “noBC experiment” is positive in the extra-Tropics
Slide 18 © ECMWF
“noBC experiment” RMSE – control RMSE
Forecast impact“noBC experiment” versus control (verified against observations), winter
controlGOOD
“noBC experiment”
GOOD
The impact for the forecast of the 50hPa geopotential of the “noBC experiment” is positive in the extra-Tropics
Slide 19 © ECMWF
“noBC experiment” RMSE – control RMSE
Forecast impact“noBC experiment” versus control (verified against own-analysis), summer
controlGOOD
“noBC experiment”
GOOD
The impact for the forecast of the 500hPa geopotential of the “noBC experiment” is slightly negative in the Southern Hemisphere
Slide 20 © ECMWF
“noBC experiment” RMSE – control RMSE
Forecast impact“noBC experiment” versus control (verified against own-analysis), winter
controlGOOD
“noBC experiment”
GOOD
The impact for the forecast of the 500hPa geopotential of the “noBC experiment” is slightly negative in the Northern Hemisphere
Slide 21 © ECMWF
Experiment description●Revision of the bias correction of AMSU-A stratospheric channels peaking
where the forecast model error is particularly significant
– “noBC experiment”: no bias correction applied to AMSU-A ch12 and ch14
– “sBC experiment”: scan bias correction (polynomial in the scan angle and with no constant) applied to AMSU-A ch12 and ch14
– “N19 anchor experiment”: ● scan bias correction (with no constant) applied to AMSU-A ch12 and
ch14 on NOAA-19 ● scan bias and offset correction applied to AMSU-A ch12 and ch14 on
other satellites
Experiments were run over ‘summer’ (20 Jul – 31 Oct 2009) and ‘winter’ (6 Dec – 31 Mar 2010) at T511 resolution
Slide 22 © ECMWF
Departure statistics of the first guess and analysis
MetOp-A AMSU-A TB
NOAA-18 AMSU-A TB
S.Hemis
S.Hemis
The bias correction of AMSU-A ch12 (and ch14) onboard NOAA-18 is not adequately correcting the scan bias, as it tries to correct forinter-satellite biases
“sBC experiment” (black) versus “noBC experiment” (red)“sBC experiment” BC (pink) versus “noBC experiment” BC (green)
Slide 23 © ECMWF
Experiment description●Revision of the bias correction of AMSU-A stratospheric channels peaking
where the forecast model error is particularly significant
– “noBC experiment”: no bias correction applied to AMSU-A ch12 and ch14
– “sBC experiment”: scan bias correction (polynomial in the scan angle and with no constant) applied to AMSU-A ch12 and ch14
– “N19 anchor experiment”: ● scan bias correction (with no constant) applied to AMSU-A ch12 and
ch14 on NOAA-19 ● scan bias and offset correction applied to AMSU-A ch12 and ch14 on
other satellites
Experiments were run over ‘summer’ (20 Jul – 31 Oct 2009) and ‘winter’ (6 Dec – 31 Mar 2010) at T511 resolution
Slide 24 © ECMWF
“noBC experiment” RMSE – control RMSE
Forecast impact“N19 anchor experiment” versus control (verified against own-analysis), summer
controlGOOD
“noBC experiment”
GOOD
The impact for the forecast of the 500hPa geopotential of the “noBC experiment” is neutral also in the Southern Hemisphere
Slide 25 © ECMWF
“noBC experiment” RMSE – control RMSE
Forecast impact“N19 anchor experiment” versus control (verified against own-analysis), winter
controlGOOD
“noBC experiment”
GOOD
The impact for the forecast of the 500hPa geopotential of the “noBC experiment” is neutral also in the Northern Hemisphere
Slide 26 © ECMWF
Departure statistics of the first guess and analysis
MetOp-A AMSU-A TB
NOAA-18 AMSU-A TB
S.Hemis
S.Hemis
The bias correction of AMSU-A ch12 (and ch14) onboard NOAA-18 is now adequately correcting the scan bias
“N19 anchor experiment” (black) versus “noBC experiment” (red)“N19 anchor exp.” BC (pink) versus “noBC experiment” BC (green)
Slide 27 © ECMWF
Conclusions of part 1a
●We considered a revision of the bias correction of high stratospheric channels because of the interaction between the variational bias correction scheme (VarBC) and large forecast model biases in the upper atmosphere
– no bias correction of channels 12 and 14 has some negative forecast impact
– scan bias correction alone is affected by inter-satellite biases
– using one satellite as anchor for the others offers improvements to the previous solutions
Slide 28 © ECMWF
Bias correction of ch5 to 8: gamma-delta correction
●The observed bias is modelled with a constant fractional error in the optical depth (gamma) and a global constant (delta):
Bias = offset + bias due to errors in the channel transmittance
●Gamma coefficients are currently used in the radiative transfer up to NOAA-18 (not for NOAA-19 and MetOp-A), (work by P. Watts & A. McNally)
●Sources of error in the channel transmittance (not necessarily constant): – errors in the assumed gas concentration – errors in the absorption coefficient – inaccurate channel spectral response function
Slide 29 © ECMWF
Mean first guess departures with different gamma values control experiment (gamma = 1)
“gamma experiment” (gamma = 1.05)
Slide 30 © ECMWF
Conclusions of part 1b
●Values of gamma have been estimated for AMSU-A channels 5 to 8
●Experiments are running to show
– the impact of the updated gamma values for all AMSU-A
– whether gamma can correct air-mass dependent biases without the need of specific predictors in VarBC for channels 5 to 8
Slide 31 © ECMWF
Assimilation of ATOVS radiances at ECMWF: Bias correction and impact in NWP
(Part 2)
Enza Di Tomaso* and Niels BormannECMWF
*EUMETSAT fellow
Thanks to Alan Geer for the IVER package
Slide 32 © ECMWF
Part 2: orbit constellation OSEs●characterise the benefit for NWP of having ATOVS data from three evenly-spaced
orbits versus data from a less optimal coverage●assess the benefit for NWP of assimilating ATOVS data from more than three satellites
MetOp-A
NOAA-18 NOAA-19 Aqua
NOAA-15
NOAA-16
NOAA-17
Satellite equatorial crossing times (local)
Ti
me
Slide 33 © ECMWF
Data coverage
“two-satellite experiment”* MetOp-A * NOAA-18
“NOAA-15 experiment”* MetOp-A * NOAA-18 * NOAA-15
“NOAA-19 experiment”* MetOp-A * NOAA-18 * NOAA-19
Sample coverage from a 6-hour period around 0Z
Slide 34 © ECMWF
Experiment description●“no-MW sounder experiment”: no AMSU-A and AMSU-B/MHS were assimilated
●“two-satellite experiment”: AMSU-A and AMSU-B/MHS on MetOp-A and NOAA-18 were assimilated
●“three-satellite experiments”:– “NOAA-15 experiment”: AMSU-A data were added from a third satellite NOAA-15– “NOAA-19 experiment”: AMSU-A data were added from a third satellite NOAA-19
●“all-satellite experiment”: all available ATOVS observations were assimilated
●The above set of experiments was run also in the case in which the advanced sounder instruments IASI and AIRS were denied
●Experiments were run over more than three months (14 April 2009 to 4 August 2009) at T255 resolution
Slide 35 © ECMWF
Departure statistics of the first guess and analysis
Both NOAA-15 and NOAA-19 bring some small improvement to the fit to temperature observations
Departure statistics for MetOp-A AMSU-A show some benefits from assimilating observations from NOAA-15 rather than NOAA-19
MetOp AMSU-A TB
Tropics
“three-satellite experiment” (black) versus “two-satellite experiment” (red)
“NOAA-15 experiment” (black) versus “NOAA-19 experiment” (red)
Radiosonde T
Slide 36 © ECMWF
Forecast impact
When averaged over the extra-Tropics the impact for the forecast of the geopotential of “NOAA-15 experiment” versus “NOAA-19 experiment” is neutral to slightly positive
“NOAA-15 exp” RMSE – “NOAA-19 exp” RMSE
“NOAA-19 experiment”
GOOD
“NOAA-15 experiment”
GOOD
Slide 37 © ECMWF
Forecast impact
Both the assimilations of NOAA-15 and NOAA-19 data have a clearly positive forecast impact in the Southern Hemisphere compared to the use of two satellites only
Having ATOVS-like data from more than three satellites adds further benefit in terms of the forecast impact
“no-MW sounder experiment”
GOOD
“two-”, “three-”, “all-satellite
experiment” GOOD
“two-satellite” RMSE – “no-Mw sounder” RMSE “three-satellite” RMSE – “no-Mw sounder” RMSE “all-satellite” RMSE – “no-Mw sounder” RMSE
Slide 38 © ECMWF
Forecast impact
When IASI and AIRS are denied, the results show in general a stronger positive impact when additional ATOVS data are assimilated into the NWP system
“no-MW sounder experiment”
GOOD
“two-”, “three-”, “all-satellite
experiment” GOOD
“two-satellite” RMSE – “no-Mw sounder” RMSE “three-satellite” RMSE – “no-Mw sounder” RMSE “all-satellite” RMSE – “no-Mw sounder” RMSE
Slide 39 © ECMWF
Less thinning of data
●Comparing “three-satellite experiments” with a new “two-satellite experiment” where less data are removed
– less thinning of AMSU-A data
– additional field of view on each side of the scan
Slide 40 © ECMWF
Forecast impact“three-satellite experiment” versus “two-satellite experiment (less thinning)”
(verified against operational analysis)
“NOAA-15 exp” RMSE – “two-satellite (less thinning)” RMSE
“NOAA-15 experiment”
GOOD
“two-satellite experiment
(less thinning)”GOOD
There is still some advantage in using three AMSU-A rather than two
Slide 41 © ECMWF
Conclusions of part 2
●ATOVS data in a more evenly-spaced orbit configuration give slightly better results in terms of forecast impact in the Southern Hemisphere than data from a less optimal coverage
●Both the assimilations of NOAA-15 and NOAA-19 observations have a positive forecast impact in the Southern Hemisphere in comparison to the use of just two satellites, and there is a clear advantage in assimilating all available ATOVS data
●The benefit of evenly-spaced orbits is expected to be stronger in limited area systems where the coverage plays a more crucial role
Slide 42 © ECMWF
Danke und Frohe Weihnachten!
Slide 43 © ECMWF
Additional slides:gamma-delta correction
Watts and McNally
Slide 44 © ECMWF
Modelling absorption coefficient errors
Slide 45 © ECMWF
Estimating gamma
Slide 46 © ECMWF
Additional slides: variational bias correction (VarBC)
Dick Dee and Niels Bormann
Slide 47 © ECMWF
Variational analysis and bias correction:A brief review of variational data assimilation
h(x)yRh(x)yx)(xBx)(xJ(x) 1Tb
1Tb Minimise
background constraint (Jb)observational constraint (Jo)
The input xb represents past information propagated by the forecast model(the model background)
The input [y – h(xb)] represents the new information entering the system(the background departures - sometimes called the innovation)
The function h(x) represents a model for simulating observations(the observation operator)
Minimising the cost function J(x) produces an adjustment to the model background based on all used observations
(the analysis)
Slide 48 © ECMWF
Variational analysis and bias correction:Error sources in the input data
h(x)yRh(x)yx)(xBx)(xJ(x) 1Tb
1Tb Minimise
background constraint (Jb)observational constraint (Jo)
Errors in the input [y – h(xb)] arise from: errors in the actual observations errors in the model background errors in the observation operator
There is no general method for separating these different error sources we only have data about differences there is no true reference in the real world
The analysis does not respond well to contradictory input information A lot of work is done to remove biases prior to assimilation:
ideally by removing the cause in practise by careful comparison against other data
Slide 49 © ECMWF
Scan bias and air-mass dependent bias for each sensor/channel were estimated off-line from background departures, and stored on files (Harris and Kelly 2001)
Past* scheme for radiance bias correction at ECMWF
errorn observatio random
positionscan latitude,
)(
)(
10
obs
i
N
i iair
scanscan
e
xpb
bb
obsairscan exbbxhy )()(
)()( xbbxhy airscanb
Error model for brightness temperature data:
where
Periodically estimate scan bias and predictor coefficients: typically 2 weeks of background departures 2-step regression procedure careful masking and data selection
Average the background departures:
*Replaced in operations September 2006 by VarBC (Variational Bias Correction)
Predictors, for instance: 1000-300 hPa thickness 200-50 hPa thickness surface skin temperature total precipitable water
Slide 50 © ECMWF
The need for an adaptive bias correction system
The observing system is increasingly complex and constantly changingIt is dominated by satellite radiance data:
biases are flow-dependent, and may change with time they are different for different sensors they are different for different channels
0
5
10
15
20
25
30
35
40
45
50
55
No. of sources
1996 1997 1998 1999 2000 2001 2002 2003 2004 2005 2006 2007 2008 2009
Year
Number of satellite sources used at ECMWF
AEOLUSSMOSTRMMCHAMP/GRACECOSMICMETOPMTSAT radMTSAT windsJASONGOES radMETEOSAT radGMS windsGOES windsMETEOSAT windsAQUATERRAQSCATENVISATERSDMSPNOAA
How can we manage the bias corrections for all these different components?This requires a consistent approach and a flexible, automated system
Slide 51 © ECMWF
The bias in a given instrument/channel is described by (a few) bias parameters:typically, these are functions of air-mass and scan-position (the predictors)
These parameters can be estimated in a variational analysis along with the model state(Derber and Wu, 1998 at NCEP, USA)
Variational bias correction:The general idea
The standard variational analysis minimizes
Modify the observation operator to account for bias:
]βx[z TTT Include the bias parameters in the control vector:
Minimize instead (z)]h[yR(z)]h[yz)(zBz)(zJ(z) Tbz
Tb
~~ 11
h(x)][yRh(x)][yx)(xBx)(xJ(x) Tbx
Tb 11
),(~
)(~ xhzh
What is needed to implement this:
1. The modified operator and its TL + adjoint 2. A cycling scheme for updating the bias parameter estimates3. An effective preconditioner for the joint minimization
problem
),(~ xh
Slide 52 © ECMWF
Variational bias correction: The modified analysis problem
Jb: background constraint
Jo: observation constraint
h(x)yRh(x)yx)(xBx)(x(x) 1Tb
1Tb J
The original problem:
h(x)β)(x,byRh(x)β)(x,by
β)(βBβ)(βx)(xBx)(xβ)J(x,
o1T
o
b1β
Tbb
1x
Tb
Jb: background constraint for x J: background constraint for
Jo: bias-corrected observation constraint
The modified problem:
Parameter estimatefrom previous analysis
Slide 53 © ECMWF
Limitations of VarBC:Interaction with model bias
h(x)β)b(x,yRh(x)β)b(x,y
β)(βBβ)(βx)(xBx)(xβ)J(x,
1T
b1β
Tbb
1x
Tb
VarBC introduces some extra degrees of freedom in the analysis, to help improve the fit to the (bias-corrected) observations:
This may lead to undesired effects wheremodel bias is present, andfew observations are available, oronly observations with VarBC are present.VarBC will, over time, force agreement with the model background.
model
observations
VarBC may wrongly attribute model bias to the observations
This works well where the analysis is well-constrained by observations, and“anchoring” observations are available (e.g.,
radiosondes, GPSRO data).VarBC will correct any biased observations and produce a consistent consensus analysis.
model
abundant observations