goceplustheme3 finalreport with atbd and validation · ESA AO/1-6367/10/NL/AF “GOCE+ Theme 3: Air...

ESA AO/1-6367/10/NL/AF

“GOCE+ Theme 3: Air density and wind retrieval using GOCE data”

Validation Report

Sean Bruinsma

Version 1.1 - 3 June 2013

Validation report

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Contents

Contents .................................................................................................................................... 2

1. Introduction ...................................................................................................................... 5

2. Comparison with densities computed with GINS ...................................................... 7

3. Comparison with model densities ................................................................................. 9

4. Comparison of GOCE and CHAMP density profiles ............................................... 17

5. Comparison with model winds ................................................................................... 19

6. Wind in latitude bins ..................................................................................................... 20

7. Conclusion ...................................................................................................................... 22

References .............................................................................................................................. 23

WP2100: Present approved models of air density

3

1. Introduction

The validation of the GOCE densities is done using three approaches:

1. By comparing to densities derived with the CNES GINS orbit determination program [1], which computes the drag force in a different way, in particular by means of a satellite macro-model and a simplified model for the drag coefficients;

2.1 By comparing to models that have and have not assimilated CHAMP and GRACE density data, DTM2012 [2], and MSIS00 [3] and JB2008 [4], respectively;

2.2 By comparing to the HASDM model (High Accuracy Satellite Drag Model [5]), which is the near real time data assimilation model of the US Air Force;

3. By directly comparing GOCE density profiles, after altitude normalization, to CHAMP densities for a period that both satellites are coplanar.

The first validation approach is done using GOCE data of November 2009. The GINS software only used the ion propulsion data as input, i.e. the densities were derived without taking the accelerometer measurements into account. This simplification is justified due to the high level of drag compensation achieved by the DFAC system, and secondly because this test is used only to compare density averaged over a revolution or longer.

The comparison to model predictions (item 2) serves two purposes: a significant scale difference and errors in the GOCE densities can be detected, and secondly, the models are evaluated in an altitude range for which few observations are available. A user, if needed for model consistency, can subsequently correct for the scale. The HASDM model, which is expected to give nearly unbiased results for altitudes below 300 km, provides densities that contain a large part of the day-to-day variability (space weather) thanks to its data assimilation scheme. It is used as the reference for the density scale.

The third validation procedure consists in comparing density profiles of GOCE and CHAMP when the orbit planes are coplanar (i.e., the same solar local times are observed simultaneously) and the altitude difference not too large. The densities must be normalized to a mean altitude using a model. Because the altitude difference is rather small, the normalization error is small too.

The validation of the estimated winds will be done in 3 stages, but wind will not be derived at CNES because a simplified procedure causes very large wind errors.

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The first wind validation approach is done using days for which the geomagnetic activity is very weak. The models are most accurate under those conditions, and therefore best suited for the validation. The second approach is to detect potentially outlying observations. The third approach has not been completed yet as the CHAMP winds are being recomputed.

NB: the work presented next is still not a complete wind validation because of the lack of pertinent data and models, but it is an ongoing effort requiring international collaboration.

WP2100: Present approved models of air density 7

2. Comparison with densities computed with GINS

The proprietary GINS orbit determination software is used by CNES for the European Gravity Gradient consortium (EGGc) High-level Processing Facility (HPF) to process GOCE data and to elaborate gravity field models, for the processing of the GPS constellation data as an IGS Analysis Center, and to compute atmospheric densities using either accelerometer data or through classical orbit perturbation analysis.

A basic macro model of GOCE was implemented in order to derive densities. The dimensions, the frontal area in particular, were taken from a study by HTG (personal communication). Figure 1 is an illustration of the macro model used. The drag coefficient is computed using the Sentman model [7] for flat plates. The macro model is correctly oriented in inertial space thanks to the level-1b attitude quaternion product GO_CONS_EGG_IAQ_2C. The mass of the spacecraft is known from the Mass Reports sent regularly from ESOC/Flight Dynamics. The orbit positions, to geo-locate the thruster data, are given in the level-2 GOCE Precise Science Orbit products GO_CONS_SST_PKI_2. Finally, the GOCE thruster data GO_OPER_AUX_NOM_1b was used to compute the drag acceleration.

Fig. 1. The GOCE macro model used in GINS. The flight direction is along the X-axis.

Densities for the month November 2009 were computed and compared to two preliminary density products, the first set computed using the Alenia panel model (in January 2012), and a second set computed with the Angara software (in September 2012). The Angara model is the most accurate representation of the spacecraft and the interactions of its panels with the ambient atmosphere, and it is expected to give accurate results. The Alenia panel model has a more realistic realization of GOCE, and with respect to the GINS macro model it has a larger frontal area of 0.87 m2 (nb: derived densities will thus be smaller). These preliminary products were computed using both the thruster and the accelerometer data and are therefore more precise than the GINS-GOCE densities. The HASDM densities are also available for this month (courtesy Bruce Bowman, US Air Force Space

Frontal panel: 0.7 m2

(X)

(Y)

10.77 m2

5.90 m2

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Command) and these observations are the most accurate reference available in the validation. The average densities for the entire month are listed below:

GOCE-GINS 1.84E-14 g/cm3

GOCE-Alenia 1.57E-14 g/cm3

GOCE-Angara 1.86E-14 g/cm3

HASDM@GOCE 1.88E-14 g/cm3

The mean difference between GOCE-Angara and HASDM densities is 1%, and the GOCE-GINS densities are (fortuitously) very close too; the absolute values of the densities are consistent. When the density is inspected more in detail, larger differences are however visible. This is shown in Figure 2, which shows about five orbits of GOCE densities.

21856.0 21856.1 21856.2 21856.3

1.0.10–14

1.5.10–14

2.0.10–14

2.5.10–14

3.0.10–14

–80

–60

–40

–20

0

20

40

60

80

days since 1/1950 (3 November 2009)

(g/c

m3)

Densities: GOCE-GINS (black) / GOCE-Angara (orange) / GOCE-HASDM (dark blue)

(thrusternoise)

latitud

e (grey)

Fig. 2. Densities along the GOCE orbit for a period of 5 revolutions on 3 November

2009.

The differences are up to plus or minus 10%, the GOCE-Angara densities being smaller at high latitudes. The HASDM data is well centered on average and does not show specific biases. Figure 2 also reveals that the GOCE densities appear to be affected by noise in a specific density interval around 2.0E-14 g/cm3; this will be elaborated in a following section.

In summary: The preliminary GOCE-Angara densities are comparable with densities computed independently with GINS, as well as with HASDM densities.


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3. Comparison with model densities

Only the GOCE-Angara densities are tested hereafter, the GOCE-Alenia densities were clearly too small and these were in reality only computed in expectation of the completion of the Angara model for GOCE. In the following, the version_1_1 densities were scaled to HASDM using the constant factor 1.29, which is assumed to provide the correct scale. The scale factor between version_1 and version_1_1 is 1.30, and this is solely due to using different parameters in the aerodynamic model.

The models (Fortran source codes) and the solar and geomagnetic indices required to drive them are available either via the internet (NRLMSISE-00, JB2008) or in-house (DTM2012). These simple semi-empirical thermosphere models predict density for a specific position (i.e. given by the GOCE orbit) and time (through the time-dependence of the indices). The proprietary genere software is used to construct the DTM models since the early nineties. It is also used to compare and analyze observed with modeled densities; the above-listed models are already implemented. The software computes mean and RMS of the observed-minus-modeled residuals (O-C; absolute quantity) and of the observed-to-modeled ratios (O/C ratios; relative quantity), and the correlation coefficient. The O/C ratios are binned as a function of spatial (altitude, latitude, local time) and solar/geomagnetic activity parameters to facilitate analysis.

In the first series of comparisons the GOCE densities are analyzed, per month, by means of computing the relative precisions. Figure 3 presents the mean of the O/C ratios of the 3 statistical models DTM2012, JB2008 and NRLMSISE-00 computed with the GOCE densities (left frames) and the HASDM densities along the GOCE orbit (right frames). The overall mean of the DTM2012 and NRLMSISE-00 models is almost one, which means that the GOCE densities are perfectly consistent with these models. JB2008 on the other hand is on average 12% smaller than the GOCE densities. The HASDM O/C ratios confirm that JB2008 is underestimating density whereas both other models are nearly unbiased. The seasonal variation of the ratios in the left and right columns is very similar, which is in fact a sign that HASDM is indeed correcting the background model at least at the monthly scales. Note that the time series with HASDM cannot be identical to GOCE for two reasons: the HASDM near real time corrections do not have the same temporal and spatial resolution as the GOCE densities, nor the accuracy, and secondly, the HASDM data are complete whereas the GOCE densities have data gaps. The scale of the HASDM and GOCE densities is indistinguishable with an uncertainty of few percent.

Figure 4 displays the mean RMS of the O/C ratios, which is a measure of the models’ capability to reproduce the observed densities of GOCE, or the pseudo observations of HASDM. For the best and unbiased model, DTM2012, the RMS is between 0.10-0.17. This number can be compared with the RMS of CHAMP observations with DTM2012 in 2010, which is 0.22.

Figure 5 shows the correlation coefficients per month. The overall correlation is very high for all models, but for certain months the correlation drops significantly, for example September 2010 and GOCE densities. This is very likely due to the small number of days of data in that month, about a week; compared to the complete month of HASDM data the correlations are high again.

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0 4 8 12 16 20 24 280.85

0.90

0.95

1.00

1.05

1.10

months since 1/2010

DTM2012 compared with GOCEx1.29 (black) and HASDM (red)monthly mean observed-to-model ratios

0 4 8 12 16 20 24 28

1.0

1.1

1.2

1.3

months since 1/2010

JB2008 compared with GOCEx1.29 (black) and HASDM (red)monthly mean observed-to-model ratios

0 4 8 12 16 20 24 280.9

1.0

1.1

1.2

months since 1/2010

NRLMSISE-00 compared with GOCEx1.29 (black) and HASDM (red)monthly mean observed-to-model ratios

Fig.3. The O/C ratios of DTM2012 (top), JB2008 (middle) and NRLMSISE-00 (bottom) computed with scaled GOCE densities version_1_1 (black) and HASDM pseudo observations (red).


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0 4 8 12 16 20 24 280.08

0.10

0.12

0.14

0.16

months since 1/2010

DTM2012 compared with GOCEx1.29 (black) and HASDM (red)monthly mean RMS of observed-to-model ratios

0 4 8 12 16 20 24 28

0.10

0.20

0.30

months since 1/2010

JB2008 compared with GOCEx1.29 (black) and HASDM (red)monthly mean RMS of observed-to-model ratios

0 4 8 12 16 20 24 28

0.12

0.16

0.20

months since 1/2010

NRLMSISE-00 compared with GOCEx1.29 (black) and HASDM (red)monthly mean RMS of observed-to-model ratios

Fig.4. The mean RMS of the O/C ratios of DTM2012 (top), JB2008 (middle) and NRLMSISE-00 (bottom) computed with scaled GOCE densities version_1_1 (black) and HASDM pseudo observations (red).

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0 4 8 12 16 20 24 28

0.85

0.90

0.95

1.00

months since 1/2010

DTM2012 compared with GOCEx1.29 (black) and HASDM (red)monthly mean correlation coefficients

0 4 8 12 16 20 24 28

0.8

0.9

1.0

months since 1/2010

JB2008 compared with GOCEx1.29 (black) and HASDM (red)monthly mean correlation coefficients

0 4 8 12 16 20 24 28

0.85

0.90

0.95

1.00

months since 1/2010

NRLMSISE-00 compared with GOCEx1.29 (black) and HASDM (red)monthly mean correlation coefficients

Fig.5. Correlation coefficients of DTM2012 (top), JB2008 (middle) and NRLMSISE-00 (bottom) computed with scaled GOCE densities version_1_1 (black) and HASDM pseudo observations (red).


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A final test by means of model comparisons is done in order to verify that there is no systematic difference in ascending and descending arcs. Sorting the O/C ratios per month in a dawn and dusk bin does this, the result of which is displayed in Figure 6. Only NRLMSISE-00 has a significant bias, which, in view of the DTM2012 and JB2008 results for which no significant offset between dawn and dusk is seen, is a modeling error and not a systematic error in the GOCE densities.

1 2 3 4 5 6 7 8 9 10 11 120.90

0.95

1.00

1.05

month

DTM2012 compared with GOCE: monthly mean observed-to-model ratiosOpen symbols: Dawn side / Solid: Dusk side - dark blue: 2010 / blue: 2011

1 2 3 4 5 6 7 8 9 10 11 12

0.90

0.95

1.00

1.05

month

DTM2012 compared with HASDM: monthly mean observed-to-model ratiosOpen symbols: Dawn side / Solid: Dusk side - dark blue: 2010 / blue: 2011

1 2 3 4 5 6 7 8 9 10 11 120.95

1.00

1.05

1.10

1.15

1.20

month

JB2008 compared with GOCE: monthly mean observed-to-model ratiosOpen symbols: Dawn side / Solid: Dusk side - dark blue: 2010 / blue: 2011

1 2 3 4 5 6 7 8 9 10 11 12

0.95

1.00

1.05

1.10

1.15

1.20

1.25

month

JB2008 compared with HASDM: monthly mean observed-to-model ratiosOpen symbols: Dawn side / Solid: Dusk side - dark blue: 2010 / blue: 2011

1 2 3 4 5 6 7 8 9 10 11 12

0.90

0.95

1.00

1.05

1.10

1.15

month

NRLMSISE-00 compared with GOCE: monthly mean observed-to-model ratiosOpen symbols: Dawn side / Solid: Dusk side - dark blue: 2010 / blue: 2011

1 2 3 4 5 6 7 8 9 10 11 12

0.90

0.95

1.00

1.05

1.10

1.15

month

NRLMSISE-00 compared with HASDM: monthly mean observed-to-model ratiosOpen symbols: Dawn side / Solid: Dusk side - dark blue: 2010 / blue: 2011

Fig.6. The O/C ratios of DTM2012 (top), JB2008 (middle) and NRLMSISE-00 (bottom) computed with GOCE densities (left frames) and HASDM pseudo observations (right) in dawn and dusk bins.

The question of noise in the densities was raised in Section 2, Figure 2. The noise is in the thruster data and due to a changing flow regime in the ion propulsion, and therefore only present for a specific interval in the thrust range. Figure 7 shows the

Validation report

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effect visible in the densities, and it appears to be in the range of approximately 1.75-2.25E-14 g/cm3.

21854.00 21854.02 21854.04 21854.06

1.0.10–14

2.0.10–14

3.0.10–14


(g/c

m3)

GOCE (black), DTM2012 (blue), JB2008 (green), NRLMSISE-00 (red) densities

Thruster noise?

21878.00 21878.02 21878.041.0.10–14

2.0.10–14

3.0.10–14

4.0.10–14

–80

–60

–40

–20

0

20

40

60

80

days since 1/1950 (24-25 November 2009)

(g/c

m3)


latitude (grey)

Thruster noise?

22230.00 22230.02 22230.04 22230.06

1.5.10–14

2.5.10–14

3.5.10–14

4.5.10–14

5.5.10–14

–80

–60

–40

–20

0

20

40

60

80


(g/c

m3)


latitude (grey)

Thruster noise?

Fig. 7. Examples of GOCE and model densities for three dates and increasing density.

In order to quantify the noise, residuals are computed by detrending the data using a 150-second moving average window, which approximately acts as a high-pass filter that suppresses variations that are larger than 600 km.


15

21854.0 21854.2 21854.4 21854.6 21854.8 21855.0

–0.10

–0.05

0.00

0.05

0.10

0.15

Days since 1/1950 (1 November 2009)

Relative density variations (scales < 600 km) for: 0.5e-14 < GOCE density < 1.75e-14 g/cm3

RMS=0.025

21854.0 21854.2 21854.4 21854.6 21854.8 21855.0

–80

–60

–40

–20

0

20

40

60

80


latit

ude

Latitudes for: 0.5e-14 < GOCE density < 1.75e-14 g/cm3

21854.0 21854.2 21854.4 21854.6 21854.8 21855.0

–0.10

–0.05

0.00

0.05

0.10

0.15



RMS=0.039

21854.0 21854.2 21854.4 21854.6 21854.8 21855.0

–80

–60

–40

–20

0

20

40

60

80


latit

iude


Observations at low-mid latitudesRMS relative variations=0.035 -> This is thruster noise

observations in auroral zoneRMS relative variations=0.041

21854.0 21854.2 21854.4 21854.6 21854.8 21855.0

–0.10

–0.05

0.00

0.05

0.10

0.15



RMS=0.012

21854.0 21854.2 21854.4 21854.6 21854.8 21855.0

–80

–60

–40

–20

0

20

40

60

80


latit

ude


Fig.8. Relative density variations (left) and latitudes (right) for three density intervals.

Relative variations are subsequently calculated by taking the residual-to-trend ratios. These are shown in Figure 8 for 1 November 2009 sorted along with three density intervals: below, (approximately) within, and above the thruster noise band. The RMS of the relative variations is calculated for each bin and the value is given in the top left corners of the frames on the left. The RMS (0.039) is largest by far within the noise band (middle frame), but the latitudes plotted in the middle right frame show that these data are for a large part within the northern auroral zone. The natural

Validation report

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variability is highest there, and therefore the RMS of the relative variations has been computed separately for high and low-mid latitudes. The RMS’ are 0.041 and 0.035, respectively. The low density interval is at high southern latitudes mainly and has an RMS of 0.025. The low and mid latitude data are above the thruster noise band, and the RMS in that case is 0.012. The noise due to the thruster thus multiplies this natural noise by about three. The noise can be suppressed by smoothing the data, at the cost of a smaller spatial resolution.

In summary: The preliminary GOCE-Angara densities are comparable and consistent with densities predicted by models, as well as with HASDM densities. Scale difference between GOCE-Angara and HASDM cannot be determined. Thruster noise is visible in a specific density interval and the relative effect is of the order of 3-4% RMS.

4. Comparison of GOCE and CHAMP density profiles

This final test consists in directly comparing the latitude profiles of high-resolution densities inferred from the CHAMP accelerometer with the GOCE densities to verify that, under identical conditions, the same density structure is observed. This can be done when data are compared when CHAMP and GRACE are in the same orbital plane (with respect to the Sun), and after normalizing the data to a mean altitude (CHAMP orbits higher than GOCE most of the time). Co-planar events have occurred twice, but only the 24 January 2010 case can be analyzed. The second co-planar event took place during the GOCE outage in the summer of 2010. Figure 9 displays 6 revolutions of GOCE and CHAMP normalized to 300 km on 24 January 2010. The CHAMP data required no scaling to agree with GOCE, which is due to applying the same processing standards in the computation of the densities. This analysis pertains to the latitude structure, and figure 9 reveals that, although co-planar, CHAMP and GOCE orbit in opposite directions.

21938.00 21938.10 21938.20 21938.30 21938.405.0.10–15

6.0.10–15

7.0.10–15

8.0.10–15

9.0.10–15

1.0.10–14

days since 1/1950 (24 January 2010)

(g/c

m3)

CHAMP (blue) and GOCE v_1_1 (red) normalized to 300 km

Fig. 9. CHAMP and GOCE densities normalized to the mean altitude of 300 km for

the 24 January 2010 co-planar event.

The (mirrored) profiles are very similar. This is demonstrated in Figure 10, which shows the densities of first orbit of the day but now versus latitude. The profiles are nearly identical, and differences are 5% maximum. Note that a very small error is due to normalization, the GOCE orbit inclination is not the same as CHAMP (96° vs 87°), and that the same locations are passed with a time difference of about 30 minutes; therefore results cannot be strictly identical.

Validation report

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–80 –60 –40 –20 0 20 40 60 805.0.10–15

6.0.10–15

7.0.10–15

8.0.10–15

9.0.10–15

1.0.10–14

latitude

(g/c

m3)

CHAMP (blue) and GOCE v_1_1 (red) densities normalized to 300 km - 24/01/2010

latitude 0°: +5%

Identical mean density

latitude 0°: +3%

Fig.10. The CHAMP and GOCE densities for the dawn and dusk profiles of the first

revolution on 24 January 2010.

In summary: The preliminary GOCE-Angara and CHAMP densities are fully consistent.


19

5. Comparison with model winds

The comparison with TIMEGCM and HWM07 winds was done for two selected days in November 2009, for which the geomagnetic activity was very weak: Kp was 1- for 17 November, and 1+ for 28 November. Under such conditions, the winds deviate least from the statistical mean seasonal winds. The results of the comparisons are satisfactory. Figure 11 shows the GOCE-inferred winds and those predicted by the model TIMEGCM and HWM07 versus latitude for the two test days. Both models and the GOCE winds are consistent for the two days, i.e. their latitude structures are nearly identical.

–80 –70 –60 –50 –40 –30 –20 –10 0 10 20 30 40 50 60 70 80 90

–200

0

200

latitude

(m/s

)

Zonal wind 17 November 2009 (Red = TIMEGCM / Green = HWM07 / Blue = GOCE)

–80 –70 –60 –50 –40 –30 –20 –10 0 10 20 30 40 50 60 70 80 90

–200

–100

0

100

200

300

latitude

(m/s

)

Zonal wind 28 November 2009 (Red = TIMEGCM / Green = HWM07 / Blue = GOCE)

–80 –70 –60 –50 –40 –30 –20 –10 0 10 20 30 40 50 60 70 80 90

0

100

200

latitude

(m/s

)

Meridional wind 17 November 2009 (Red = TIMEGCM / Green = HWM07 / Blue = GOCE)

–80 –70 –60 –50 –40 –30 –20 –10 0 10 20 30 40 50 60 70 80 90

–100

0

100

200

300

latitude

(m/s

)

Meridional wind 28 November 2009 (Red = TIMEGCM / Green = HWM07 / Blue = GOCE)

Figure 11. Observed (GOCE; blue) and modeled (TIMEGCM=red; HWM07=green) winds for two geomagnetically quiet days.

Validation report

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6. Wind in latitude bins

The GOCE wind data for November 2009 have been selected next at three latitudes, 60°S, 0°, and 60°N, separately for the dawn and dusk sides. The data were not averaged over longitude, which explains part of the scatter visible in Figure 12. On the dusk side at 60°N and 60°S the perturbing effect of the magnetic poles can be seen, whereas this effect is not visible in the dawn profiles. The meridional winds are always blowing north with small amplitude of 0-50 m/s; as can be seen in Figure 11, structure is absent from 60°S through 60°N. Much more cannot be gleaned from this figure, except maybe that some suspicious data are detected in the zonal winds at the equator (observations with opposite sign, i.e., winds blowing opposite the mean direction). Otherwise no unexplainable discontinuities are detected.

–180 –150 –120 –90 –60 –30 0 30 60 90 120 150 180

–150

–100

–50

0

50

100

longitude

(m/s

)

GOCE winds November 2009 <59.7°, 60.3°> (Red = zonal/ Blue = meridional)

(dawn side)

–180 –150 –120 –90 –60 –30 0 30 60 90 120 150 180

–200

–100

0

100

200

300

longitude

(m/s

)

GOCE winds November 2009 <59.7°, 60.3°> (Red = zonal/ Blue = meridional)

(dusk side)

–180 –150 –120 –90 –60 –30 0 30 60 90 120 150 180

–100

–50

0

50

longitude

(m/s

)

GOCE winds November 2009 <-0.3°, 0.3°> (Red = zonal/ Blue = meridional)

(dawn side)

–180 –150 –120 –90 –60 –30 0 30 60 90 120 150 180

0

50

100

150

longitude

(m/s

)

GOCE winds November 2009 <-0.3°, 0.3°> (Red = zonal/ Blue = meridional)

(dusk side)


21

–180 –150 –120 –90 –60 –30 0 30 60 90 120 150 180

–300

–200

–100

0

100

longitude

(m/s

)

GOCE winds November 2009 <-60.3°,-59.7°> (Red = zonal/ Blue = meridional)

(dawn side)

–180 –150 –120 –90 –60 –30 0 30 60 90 120 150 180

–200

–100

0

100

200

300

longitude

(m/s

)

GOCE winds November 2009 <-60.3°,-59.7°> (Red = zonal/ Blue = meridional)

(dusk side)

Figure 12. Observed winds at three latitudes (60°N, 0°, 60°S from top to bottom), displayed separately for the dawn (left frames) and dusk sides.

Preliminary conclusion: GOCE horizontal wind data agree well on average with TIMEGCM and HWM07 for geomagnetic quiet days. Some data points were detected that may be erroneous.

Validation report

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7. Conclusion

The GOCE-Angara v_1_1 densities are comparable and consistent with densities predicted by the CIRA models JB2008 and NRLMSISE-00, and the more recent DTM2012, as well as with HASDM densities. Scale difference between GOCE-Angara and HASDM cannot be determined for version_1 of the densities, and is 1.29 (constant) for version_1_1. This scale offset is due to the selected aerodynamic model only, for which no standard exists presently. Consequently the complete GOCE data processing chain is validated.

Thruster noise is visible in a specific density interval and the relative effect is of the order of 3-4% RMS. The only remedy is smoothing, but at the cost of diminished resolution.

The GOCE horizontal wind data are comparable to HWM07 and TIMEGCM for geomagnetic quiet days.


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References

[1] S. Loyer, F. Perosanz, F. Mercier, H. Capdeville, J.C. Marty, “Zero-difference GPS ambiguity resolution at CNES–CLS IGS Analysis Center”, J. Geod., DOI 10.1007/s00190-012-0559-2, 2012

[2] www.atmop.eu

[3] J.M. Picone, A.E. Hedin, D.P. Drob, A.C. Aikin, “NRLMSISE-00 empirical model of the atmosphere: statistical comparisons and scientific issues,” J. Geophys. Res. 107 (A12),1468, 2002

[4] B.R Bowman, W.K. Tobiska, F.A. Marcos, C.Y. Huang, C.S. Lin, W.J. Burke, “A New Empirical Thermospheric Density Model JB2008 Using New Solar and Geomagnetic Indices”, AIAA/AAS Astrodynamics Specialist Conference, Honolulu, Ha, August, 2008

[5] M.F. Storz, et al., “High accuracy satellite drag model (HASDM),” AIAA 2002-4886, AIAA/AAS Astrodynamics Specialist Conference, Monterey, Ca, August, 2002

[6] D.P. Drob, et al., “An empirical model of the Earth’s horizontal wind fields: HWM07”, J. Geophys. Res., doi:10.1029/2008JA013668, 2008

[7] L.H. Sentman, “Comparison of the exact and approximate methods for predicting free molecule aerodynamic coefficients”, ARS J., 31, 1576 -1579, 1961

goceplustheme3 finalreport with atbd and validation · ESA AO/1-6367/10/NL/AF “GOCE+ Theme 3: Air...

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Transcript of goceplustheme3 finalreport with atbd and validation · ESA AO/1-6367/10/NL/AF “GOCE+ Theme 3: Air...