Slide: 12nd SALGEE Training Workshop,Antalya, 4 – 7 April 2011 SEVIRI Active Fire products...

Slide: 1 2nd SALGEE Training Workshop ,Antalya, 4 – 7 April 2011

SEVIRI Active Fire products

Hans-Joachim LutzHans-Joachim [email protected]

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2nd SALGEE Training Workshop ,Antalya, 4 – 7 April 2011

•Introduction•Description of the algorithm•Results•Some critical issues•Future plans•MTG•Summary and Conclusions

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Description of the algorithm

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The active fire detection algorithm is based on a simple threshold test technique, using SEVIRI channels 4 (3.9

μm) and 9 (10.8 μm).

The algorithm is applied for all SEVIRI repeat cycles (15 Minutes) and for all land surface pixels, excluding desert/bare soil surface pixels and coastal pixels.

The algorithm does not need any cloud masking as an input. However it uses SEVIRI channel 1 (0.6 μm) to

eliminate (low) clouds with a high reflectance.

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StdDev3.9 15 Jan 2009, 12 UTC StdDev3.9-StdDev10.8

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BTD(3.9-10.8) 15 Jan 2009, 12 UTC StdDev3.9-StdDev10.8

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The setting of the thresholds is crucial for the fire detection !!!

In our scheme we use:

Forecast data and RTTOV for tests 1 and 5

Static thresholds (corrected for viewing angle) for tests 2, 3, and 4.

HOWEVER:

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Emissivity plays an important rôle

• Emissivity more variable near 3.9 m

• Sandy areas appear 5-10 K cooler at IR3.9 than at IR10.8 (at night, dry atmosphere)

IR3.9 IR10.8Dry sand: 0.8 0.95

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Emissivity map channel 4 (3.9 µm) for January

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1. Use RTM output (RTTOV) with the following parameter: TOA clear sky radiance (ε=1)Surface skin radiance (ε=1)Downward radiance at surface levelTotal Transmittance

2. Interpolate the gridded data to pixel location

3. Calculate the atmospheric contribution to the TOA radiance

4. Calculate the correct surface skin radiance using the emissivity, the reflected downward radiance at surface level and the reflected solar radiance (at daytime)

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rTOA = B(Ts). s . s

+ rdown. (1- s). s

+ rsolar . s . (1- s). s

+ rATM

please note:s has been calculated for the satellite viewing angle and is not corrected for the solar zenith angle. that no bi-directional effects are included (1- s)

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The following threshold tests are used:

1. Brightness temperature IR3.92. Standard Deviation difference (StdDev3.9–StdDev10.8)3. Brightness temperature difference (IR3.9-IR10.8)4. Standard Deviation IR10.8

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TB

(3.

9 m

) -

TB

(10

.8

m)

• Its strong sensitivity to sub-pixel "hot areas" makes the IR3.9 channel very useful in fire detection.

• If only 5% of the pixel is at 500 K, the IR3.9 channel measures 360 K, while the IR10.8 measures less than 320 K.

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BTD (3.9 - 10.8)

15 Jan 2009, 12 UTC

For fire (and most clouds)

BT3.9 >> BT10.8

For most other surfaces

BT3.9 ≈ BT10.8

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Results of test 5 (BTD of ch. 4 and 9)for possible fire

15 January 200912 UTC

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StdDev3.9-StdDev10.8

15 Jan 2009, 12 UTC

For fire

StdDev3.9 >> StdDev10.8

For clouds/cloud edges

StdDev3.9 ≤ StdDev10.8

For other surfaces

StdDev3.9 ≈ StdDev10.8

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Results of test 4 (Standard Dev. Diff. of ch. 4 and 9) added to test 5for possible fire


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Results of test 2 and 3 (Standard Dev. of ch. 4 and 9) added to tests 4 and 5 for possible fire


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BT 3.9

15 Jan 2009, 12 UTC

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Results of test 1 (BT of ch. 4) added to tests 2 - 5for possible fire


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Results of test 5 (BTD of ch. 4 and 9)for probable fire


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Results of test 4 (Standard Dev. Diff. of ch. 4 and 9) added to test 5for probable fire


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Results of test 2 and 3 (Standard Dev. of ch. 4 and 9) added to tests 4 and 5 for probable fire


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Results of test 1 (BT of ch. 4) added to tests 2 - 5for probable fire


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Final results combining all possible andprobable fires


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Diurnal cycle of number of fires for 15 January 2009

FIR-proto

0

500

1000

1500

2000

2500

3000

3500

4000

4500

020

040

060

080

010

0012

0014

0016

0018

0020

0022

00

Time (UTC)

Nu

mb

er

of

fire

s

FIR-proto

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Some critical issues

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Artefacts coming from Digital Filter

MSG-1, 7 August 2006, IR3.9 Channel (inverted)

18:00 18:15

18:30 18:45

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Impact of Sunglint

• There is very strong reflection of solar radiation at 3.9 m (sunglint)

• Features such as rivers in sunglint are obvious, but “illuminated” lakes could take on the appearance of fires

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Midday sun glint over the Congo riverMSG-1, 24 March 2004, 09:00 UTC, Channel 04 (3.9 m)

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Frequency of

Saturated IR3.9 Pixels

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Working without cloud mask – “hot clouds”


Low-level water clouds are relatively warm

They have a high reflectance in ch. 4 (3.9 µm)

These clouds appear as “hot spots” in ch. 4

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Working without cloud mask – “hot clouds”


The BTD ch.4 (3.9 µm) – ch.9 (10.8 µm)These clouds appear as “hot

spots” in ch. 4

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(Not really)Working without

cloud mask – “hot clouds”


Using channel VIS0.6, helps to filter out all “hot clouds”

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Future plans

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1. Use the improved ECMWF forecast modelThe operational algorithm works with a 1º / 6-hourly forecastThe prototype algorithm uses a 0.25º / 3-hourly forecastIn the near future ECMWF will provide a 0.125º forecast grid

2. Include solar transmittance The transmittance calculation for channel 4 is only done with the viewingangle, but needs also to be done with the solar zenith angle for the downwelling solar part.

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3. Create a MSG emissivity mapThere are plans to create a “MSG” emissivity map instead of using a mapderived from other sources and then interpolated in space and spectrato the MSG channels

4. Make use of the temporal filteringCurrently the algorithm is not using temporal filtering for both the diurnalcycle of the temperatures and the tracking of fires for a single pixelthroughout the day

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MTG

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The imager mission (FCI) of the third generation ofMeteosat (MTG) will have 16 channels which are

scanning the full disk every 10 minutes. The channels will be located at the

following wavelengths:

MTG Imager - Full Disk Mission

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MTG Imagery Band

Central Wavel. (µm)

Spatial resolution (km)

Objective

FDHSI-1 0.440 1 Aerosol optical depth, aerosol particle size, volcanic ash concentration

FDHSI-2 0.510 1 Aerosol optical depth, aerosol particle size, volcanic ash concentration

FDHSI-3 0.645 1 Cloud detection, AMV, cloud type, cloud optical depth, snow cover, vegetation stress, smoke detection, volcanic ash detection, volcanic ash concentration

FDHSI-4 0.860 1 Cloud detection, AMV, cloud type, cloud phase, cloud optical depth, cloud microphysics, snow cover, vegetation stress, smoke detection, volcanic ash detection, volcanic ash concentration

FDHSI-5 0.91 1 Total column humidity

FDHSI-6 1.375 1 Cirrus detection, water vapour imagery

FDHSI-7 1.61 1 Cloud phase, cloud microphysics, cloud detection, cloud type, snow cover, vegetation stress, smoke detection

FDHSI-8 2.26 1 Cloud microphysics

FDHSI-9 3.80 2 Cloud detection, cloud type, AMV, LST/SST, cloud phase, cloud microphysics, snow cover, sea ice temperature, fire detection/monitoring, volcanic ash detection, volcanic ash concentration

FDHSI-10

6.30 2 AMV, tracer heights, instability (grad T/Hu), column humidities

FDHSI-11

7.35 2 AMV, tracer heights, instability (grad T/Hu), column humidities

FDHSI-12

8.70 2 Cloud detection, cloud type, cloud top height, LST/SST, cloud phase, cloud drop size, instability (grad T/Hu), sea ice temperature, volcanic SO2 detection, sand/dust storm detection

FDHSI-13

9.66 2 Total Column ozone

FDHSI-14

10.5 2 Cloud detection, cloud type, cloud top height, AMV, tracer heights, LST/SST, instability (grad T/Hu), total column humidity, sea ice temperature, fire detection/monitoring, volcanic ash detection, volcanic ash concentration, sand/dust storm detection

FDHSI-15

12.3 2 Cloud detection, cloud type, cloud top height, AMV, tracer heights, LST/SST, instability (grad T/Hu), total column humidity, sea ice temperature, volcanic ash detection, volcanic ash concentration, sand/dust storm detection

FDHSI-16

13.3 2 Cloud top height, tracer heights, instability (grad T/Hu), volcanic ash detection


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0

0.2

0.4

0.6

0.8

1 0

0.2

0.4

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0.8

11 1.5 2 2.5 3 3.5 4

MSG

Spe

ctra

l R

espo

nse

Fun

ctio

ns Atm

ospheric transmission

[m]

1 32 4

CO2

True Color 1 km

Vertical integrierter Wassrdampf über Land 1 kmExtrem dünne Zirrusbewölkung 1 km

Wolkenteilchengröße und Phase 0.5 km


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0

0.2

0.4

0.6

0.8

1 0

0.2

0.4

0.6

0.8

14 5 6 7 8 9 10 11 12 13 14

MSG

Spe

ctra

l R

espo

nse

Fun

ctio

ns Atm

ospheric transmission

[m]

4 5 6 7 8 9 10 11

CO2

CO2

O3

H2O

MTG hat die gleichen Kanäle wie MSG im thermischen Bereich2 km nominale Auflösung1 km Auflösung für 3.8µm and 10.5 mm Kanäle (rapid scan)

MTG Imager Full Disk Mission

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It will be possible to setup a high resolution rapid scanning for the northern 25% of the disk (Europe)

at 4 channels which are scanning the area every 2.5 minutes.

These channels will be located at the following wavelengths:

MTG Imager - High Resolution Mission

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MTG ImageryBand

Central Wavel. (µm)

Spatial resolution (km)

Objective

HRFI-1 0.645 0.5 Cloud detection, AMV

HRFI-2 2.26 0.5 Cloud microphysics

HRFI-3 3.80 1 Cloud detection, cloud microphysics, (fire detection/monitoring)

HRFI-4 10.5 1 Cloud detection, cloud top height, AMV, (fire detection/monitoring)

MTG Imager - High Resolution Mission

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MODISch. 7 (2.1 µm) 1 km resolution(28 Aug 2007, 11:10 UTC)

Similar to the planned MTG ch. FDHSI-8at 2.26 µm

The hot spots appear already at 2.1 m

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But the main (big) points of the MTG Imagerfor the fire community are:

• The “fire channel” centered at 3.8 µm avoiding the CO2 absorption

• The temporal and spatial resolution will be higher (10 minutes and 2 km)

• The dynamic range of the 3.8 µm channel will be extended to 450 K

MTG Imager

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Summary and Conclusions

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Active Fire detection considers:

• Spectral signals and its spatial distribution (channels IR3.9, IR10.8, IR3.9-IR10.8 )

• Uses ECMWF Forecast data to derive thresholds

• Uses channel VIS0.6 to eliminate “hot clouds”

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Problems still to be solved are:

• Sunglint areas

• Better forecast/emissivity information

• Use of temporal signals (temporal filtering)

Slide: 12nd SALGEE Training Workshop,Antalya, 4 – 7 April 2011 SEVIRI Active Fire products...

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