marco gai, piera raspollini, flavio barbara, simone ceccherini, … · 2016. 6. 22. ·...

/ Identification of outliers MIPAS QWG #40 Firenze, 2-4 November 2015

STATISTICAL ANALYSIS OF ML2PP V7 DATASET AND COMPARISON WITH V6 DATASET

TOWARDS THE IDENTIFICATION OF POSSIBLE

APPROACHES FOR FLAGGING PROFILES

Marco Gai, Piera Raspollini, Flavio Barbara, Simone Ceccherini, Nicola Zoppetti

IFAC-CNR

November-2015


Conclusions from QWG #39

The conclusion of the preliminary study was: 1. Screening

For some species (like O3 and HNO3) the current screening (convergence/marquardt flags and CHI-square ) seems to be able to remove all outliers in the products For other species (like CH4, N2O and NO2), the current screening is not able to filter out all outliers.

2. New possible quantifier The distributions of the Profile Oscillation Quantifier, random errors and difference with the climatology can be used in order to identify the remaining product outliers.

Random error is a good candidate to be used to filter out the outliers

We analyzed the statistical distribution of some quantifiers of the retrieval • Chi-square, POQ2, Retrieval Error, Difference wrt climatology.


1. The analysis will be repeated on full mission reprocessing V.7, for both Full and Optimised Resolution measurements.

We performed the analysis for the year 2003 (FR) and 2009 (OR), both for v. 6 and v 7.02 reprocessing

We present some results of comparison between v.7 and v.6

1. Other retrieval parameter could be considered: for example the vertical

resolution.

We investigated the vertical resolution [in progress]

1. Proper thresholds have to be optimised.

We analyzed the threshold set for Chi-square on the 2003 and 2009 datasets

Outlook from QWG #39 (and summary)


[Chi-square] OR (year 2009) v 7.03

Distribution of Chi-square for all species Automatic scale: different scales for each sub-panel


Distribution of Chi-square Comparison between v. 7 and v. 6

[Chi-square] OR (year 2009) v6 .vs. v7


[OR 2009] ML2PP v 7.02

spec mean stdv Nsamples filtered out

p T 1.616 0.334 337129 0.07%

h2o 1.282 0.169 337227 0.07%

o3 2.452 0.612 337011 0.03%

hno3 1.32 0.258 334727 0.08%

ch4 1.789 0.462 336858 0.01%

no2 1.399 0.266 324858 0.14%

n2o 1.791 0.417 336814 3.68%

hcn 2.528 0.701 280186 0.16%

f11 1.215 0.137 334686 0.63%

f12 1.232 0.12 334691 0.02%

f14 1.88 0.553 328361 0.00%

f22 1.494 0.289 334448 0.55%

n2o5 1.357 0.225 334512 0.09%

cof2 1.714 0.364 333765 0.07%

clno 1.829 0.394 332821 0.22%

ccl4 3.269 1.181 332276 0.46%

[Chi-square] OR (year 2009) v. 6 and v. 7

The tables summarize the statistics in case of applying the Chi-square filter. The percentage of “filtered-out” is computed with respect to the converged retrievals [iconv=0]

Filter thresholds

[OR 2009] ML2PP v 6


p T 1.751 0.442 332339 0.21%

h2o 1.297 0.171 332964 0.21%

o3 2.536 0.631 331332 0.03%

hno3 1.334 0.279 328046 0.39%

ch4 1.788 0.475 328266 0.72%

no2 1.275 0.137 332854 1.35%

n2o 1.801 0.433 328410 0.06%

f11 1.356 0.263 328359 1.39%

f12 1.262 0.16 328476 0.59%

n2o5 1.364 0.22 325140 0.59%

clno 2.194 0.46 320810 1.61%


[Chi-square] FR (year 2003) v 7.03

Distribution of Chi-square Automatic scale: different scales for each sub-panel


Distribution of Chi-square Comparison between v. 7 and v. 6 differences can be explained with the different set of MW used for v. 7 and v. 6

[Chi-square] FR (year 2003) v6 .vs. v7


[FR 2003] ML2PP v 7.02


p T 1.576 0.391 289487 0.19%

h2o 1.402 0.226 284326 0.19%

o3 1.926 0.353 289090 1.96%

hno3 1.495 0.301 282341 0.30%

ch4 1.189 0.177 289695 2.31%

no2 1.084 0.086 277704 0.11%

n2o 1.145 0.101 273940 4.06%

hcn 1.438 0.244 277715 5.55%

f11 1.134 0.086 286470 4.15%

f12 1.153 0.093 277203 0.83%

f14 1.24 0.251 280158 4.10%

f22 1.466 0.346 282350 3.30%

n2o5 1.092 0.058 276052 2.27%

cof2 1.303 0.168 273910 4.47%

clno 1.628 0.232 278742 5.14%

ccl4 1.824 0.366 281394 3.57%

The table summarizes the statistics in case of applying the Chi-square filter. The percentage of “filtered-out” is computed with respect to the converged retrievals [iconv=0]

[Chi-square] FR (year 2003) v. 6 and v. 7

[FR 2003] ML2PP v 6


p T 1.93 0.463 288774 0.18%

h2o 1.031 0.182 288425 0.18%

o3 1.331 0.216 288530 0.30%

hno3 1.334 0.262 287348 0.17%

ch4 1.11 0.103 289244 0.66%

no2 0.995 0.077 288842 0.02%

n2o 1.135 0.104 281325 0.15%

f11 1.225 0.133 280416 2.75%

f12 1.202 0.106 284486 3.04%

n2o5 1.165 0.077 244459 1.66%

clno 1.69 0.279 263175 15.49%

Filter thresholds


[Retrieval Error] FR (year 2003) v 7.03

Distribution of Retrieval Error Outliers remaining after Chi-square filtering


[Retrieval Error] FR (year 2003) v 7.03

Distribution of Retrieval Error Automatic scale: different scales for each sub-panel


Distribution of Retrieval Error Comparison between v. 7 and v. 6

[Retrieval Error] FR (year 2003) v6 .vs. v7


[FR 2003] ML2PP v 7.02


p T 0.761 0.119 289484 0.20%

h2o 1.3 2.111 279739 0.19%

o3 0.06 0.015 289075 3.54%

hno3 0.129 0.059 282334 0.30%

ch4 0.055 0.039 288504 2.31%

no2 2.765 1.41 277300 0.52%

n2o 0.011 0.006 272978 4.20%

hcn 0.881 0.292 277623 5.88%

f11 0.032 0.014 286470 4.18%

f12 0.037 0.016 277203 0.83%

f14 0.026 0.013 241335 4.10%

f22 0.053 0.02 282350 16.70%

n2o5 0.13 0.077 275811 2.27%

cof2 0.047 0.015 273908 4.56%

clno 0.134 0.057 278725 5.15%

ccl4 0.013 0.004 281394 3.58%

[FR 2003] ML2PP v 6


p T 1.237 0.204 288714 0.23%

h2o 4.712 5.907 270259 0.20%

o3 0.126 0.033 266997 6.58%

hno3 0.167 0.078 287106 7.62%

ch4 0.115 0.047 287811 0.74%

no2 1.726 1.639 288835 0.51%

n2o 0.013 0.008 279602 0.16%

f11 0.013 0.008 280383 3.35%

f12 0.022 0.014 284260 3.06%

n2o5 0.093 0.051 244457 1.73%

clno 0.087 0.041 263174 15.49%

The tables summarize the statistics in case of applying filter on (Chi-square) (POQ2) (ESD). The percentage of “filtered-out” is computed with respect to the converged retrievals [iconv=0]

[Retrieval Error] FR (year 2003) v. 7 and v. 6


Distribution of Retrieval Error Comparison between v. 7 and v. 6 Differences between v.6 and v7 should be better investigated

[Retrieval Error] OR (year 2009) v6 .vs. v7


[Vertical resolution - trace of the AKM]

In addition to the Chi-square, POQ2 and Retrieval error we analyzed:

The vertical resolution

(maximum of the vertical resolution for each profile)

The trace of the Averaging Kernel

(ratio between the AKM-dimension and AKM-trace)

The analysis of these quantifiers is still in progress

The investigation is important but these parameters seem not be useful to flag the outliers


FR (year 2003) v. 7.03 Statistics on convergence

[FR 2003] ML2PP v 7.02 (convergence analysis)

spec iconv=0

[OK] iconv=1 iconv=2 iconv=3 iconv=4 iconv=5

pT [96.76%] [0.08%] [0.00%] [0.00%] [3.15%] [0.00%]

H2O [96.75%] [0.00%] [0.00%] [0.00%] [3.24%] [0.00%]

O3 [96.73%] [0.00%] [0.02%] [0.00%] [3.24%] [0.00%]

HNO3 [96.41%] [0.02%] [0.01%] [0.00%] [3.56%] [0.00%]

CH4 [96.75%] [0.00%] [0.00%] [0.00%] [3.24%] [0.01%]

N2O [96.75%] [0.00%] [0.00%] [0.00%] [3.24%] [0.01%]

NO2 [96.57%] [0.00%] [0.12%] [0.00%] [3.24%] [0.08%]

F11 [96.36%] [0.01%] [0.00%] [0.00%] [3.60%] [0.02%]

CLNO [96.44%] [0.00%] [0.00%] [0.00%] [3.56%] [0.00%]

N2O5 [96.41%] [0.01%] [0.01%] [0.00%] [3.58%] [0.00%]

F12 [96.43%] [0.00%] [0.00%] [0.00%] [3.57%] [0.00%]

convergence

flag reason

iconv=0 convergence OK

iconv=1 Max Gauss iteration exceeded

iconv=2 Max Marquardt iteration exceeded

iconv=3 Max Time exceeded

iconv=4 Retrieval crashed

iconv=5 Singular Covariance Matrix

The table summarizes the statistics of convergence for FR retrieval, year 2003 The percentages are computed with respect to the total retrieval analyzed


FR (year 2003) v. 6 Statistics on convergence

convergence

flag reason

iconv=0 convergence OK

iconv=1 Max Gauss iteration exceeded

iconv=2 Max Marquardt iteration exceeded

iconv=3

iconv=4 Retrieval crashed

iconv=5

The table summarizes the statistics of convergence for FR retrieval, year 2003 The percentages are computed with respect to the total retrieval analyzed

[FR 2003] ML2PP v 6 (convergence analysis)

spec iconv=0

[OK] iconv=1 iconv=2 iconv=3 iconv=4 iconv=5

p T [96.90%] [0.00%] [0.01%] [0.00%] [3.08] [0.00%]

H2O [96.90%] [0.00%] [0.00%] [0.00%] [3.10] [0.00%]

O3 [96.81%] [0.07%] [0.02%] [0.00%] [3.10] [0.00%]

HNO3 [96.89%] [0.01%] [0.00%] [0.00%] [3.11] [0.00%]

CH4 [96.90%] [0.00%] [0.00%] [0.00%] [3.10] [0.00%]

N2O [96.89%] [0.00%] [0.00%] [0.00%] [3.10] [0.00%]

NO2 [96.90%] [0.00%] [0.00%] [0.00%] [3.10] [0.00%]

F11 [96.87%] [0.02%] [0.00%] [0.00%] [3.11] [0.00%]

CLNO [95.77%] [0.00%] [0.02%] [0.00%] [4.21] [0.00%]

N2O5 [96.89%] [0.00%] [0.00%] [0.00%] [3.11] [0.00%]

F12 [96.89%] [0.00%] [0.00%] [0.00%] [3.11] [0.00%]


FR (year 2003) Statistics on convergence In blue: histogram of the total scans classified for latitude bands In red (superimposed): histogram of scans having bad convergence flag (conv_id>0)

The peaks of conv_id>0 are not nominal scans.

The scans with conv_id=4 are related to

particular commanded activities, planned

during the whole Full Resolution mission.

Both events (latitude re-alignment strategy and

WCC calibration) have been stopped since

2004.

This problem does not affect the Optimized

Resolution mission.

The peak is located near latitude 6 deg, corresponding to scans 6 & 7.


Conclusions

1. Retrieval quantifiers for outliers detection The analysis repeated on one year FR and one year OR dataset, both for v.7 and v. 6 processing, confirms that the Retrieval Error could be used as outlier detector, in addition to the Chi-square. Threshold have to be optimized.

2. Comparison between v.7 and v.6 processing CHI-Square: • OR no significant differences • FR improvement for pT, CFC11, CFC12, N2O5; degradation for H2O, O3, HNO3, NO2 differences are to be better investigated Retrieval Error (max value of the error of each profile): • OR no significant differences for pT;

improvement for H2O only • FR improvement for the main targets (but NO2); degradation for CFC11, CFC12, N2O5, ClNO differences are to be better investigated


Example of Time series Difference between v.7 and v.6


Time series [T]


Time series [O3]


Time series [CH4]

marco gai, piera raspollini, flavio barbara, simone ceccherini, … · 2016. 6. 22. ·...

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