Incorporating Meteosat Second Generation Products

in Season Monitoring

Blessing SiwelaSADC Regional Remote Sensing Unit

November 15 2005

Outline

METEOSAT introduction METEOSAT data

Access to data Data format(s)

METEOSAT-7 vs METEOSAT-8 METEOSAT-8 products (current and

potential) for season monitoring

METEOSAT

Geo-stationary 36 000 km altitude Spatial Resolution 3km x 3km visible, thermal infra-red and water

vapour channels 42% of Earth covered 7 year design lifetime

Access to METEOSAT-8 data

Data available in XPIF format on PUMA receiver(s)

All historic MSG data (older than 24 hours) available in the EUMETSAT archive via an online ordering interface on the EUMETSAT Web site;

METEOSAT-8 data format

8-bit XPIF data, [0-255] Visible data [0 - 255] grey levels Temperature [-128 – 127]

degrees C Information in XPIF header

indicates data format, projection, geo-referencing parameters

METEOSAT-8 data format

Original data 10-bit [0..1024] but rescaled to 8-bit by 2-met software on PUMA receiver

Temperature

Visible

-128[ ……..]127

0[ ……..]255

0[ ……..]255

1, -128

Transformation

METEOSAT-8 data

Grid Size(X) 0.0206825708, (Y) 0.0212385622 (degrees)

610 east, 44.50 south

00 East, 6.340 North Projection: Platt-Carree (Latitude /

Longitude)

METEOSAT-7 vs METEOSAT-8

3 channels 5km IR, WV;

2.5km VIS 30 minutes

temporal resolution

12 channels 1km HRV;

3km other 15 minutes

temporal resolution

METEOSAT-7 vs METEOSAT-8

IDA (WinDisp)

Data Conversion Tools

XPIF

CHIPSWindows BMP

Other [ERDAS, ESRI

BIL, etc]

MSG Receive

r

Cold Cloud Duration from TIR data

Cold Cloud Duration from TIR data

hh00

hh30

hh15

hh45ccd1 ccd2

ccd = (ccd1 + ccd2) / 2

Cold Cloud Duration from TIR data

October 11-20 2005

Cold Cloud Duration from TIR data

CCD from METEOSAT-8 and METEOSAT-7 compare well; Historic M-7 data can be used for comparison of current CCD with average

METEOSAT-7

METEOSAT-8

October 11-20 2005

Rainfall Estimation from TIR data

CCD -> RFE Refine using

rain gauge or other data sources

WMO-GTS Radar data

Percentage cumulative rainfall received

Monitoring Rainfall Activity• Rainfall Estimate (RFE) images.

Rainfall Estimates Applications

Water Balance ModelsWater Requirements Satisfaction Index (WRSI)

Standardized Precipitation IndexStatistical method for measuring drought

Hydrological modelling Stream flow model

METEOSAT-8 RGB Composites

Channel X

Channel Y

Channel Z

METEOSAT-8 RGB Composites

Channel X

Channel Y

Channel Z

NIR1.6

ice clouds are dark, water clouds are bright

VIS0.6 and VIS0.8

All (“thick”) clouds are white

RGB composite can separate ice clouds from water clouds

Red: Cloud depth and amount of cloud water and ice.Day: Visible reflectance at 0.6 m. Night: Optical depth, approximated by 12.0-10.8 m channels.

Green: Cloud particle size and phase.Day: Approximated by 1.6 m or 3.9 m solar reflectance component. Night: Approximated by 10.8 –3.9 m brightness temperature.Day & Night: Water clouds have larger 10.8-8.7 m temperature difference than ice clouds. No skill for drop size discrimination.

Blue: Temperature is provided by 10.8 m day and night.

RGB Composites and interpretation of clouds

RGB - 149

1 1

3 4

6

7

89

4

5

3

1 .Multilayer mature cloud. Low cirrus above Low Cu+Sc. Little or no rain. Dark red above yellow-white.

2 .Thunderstorms. Orange tint on red.

3 .Mature rain cloud, moderate rain. Dark red + magenta.

4 .Sc+Cu. no-precip. Yellow-white.

5 .Local heavy rain shower. Bright Red.

6 .Light warm rain under multi-layer clouds. Bright Magenta.

7 .High level shield, raining on the east side. Orange riding over red.

8 .Mid-level orographic clouds. No rain. Intense yellos.

9 .Ciro-cumulus. No rain. Dirty yellow.

2

NIR

NIR

Vegetation Monitoring

Normalized Difference Vegetation Index: (NIR – Red) / (NIR + Red) Possible values -1 to 1 dense vegetation has higher

values (0.4 - 0.8), lightly vegetated regions have low values (0.1 - 0.2)

Vegetation Monitoring

METEOSAT-8 channels: VIS008, VIS006 IR108 , IR120 for cloud masking

NDVI = (VIS008 – VIS006) / (VIS008 + VIS006)

Values [ 0.0 … 0.5]

Difference between VIS008 and VIS006 gives good indication of vegetation density

Vegetation Monitoring

Vegetation MonitoringMETEOSAT-8 NDVI

Vegetation Monitoring

Cloud interference

sometimes limits use of NDVI

Vegetation Monitoring

Time series NDVI for

selected zones

Vegetation Monitoring

NDVI image comparison with normal / average or other

Thermal infrared radiation to monitor surface temperature of the crops can also be used to get information on crop health.

The more transpiration from crops, the cooler the leaves; warmer leaf temperature may suggest water stress.

Vegetation Monitoring

Vegetation Condition Index 100*(NDVI – NDVIMin) /(NDVImax – NDVImin)

Temperature Condition Index 100*(BTemp– BTempMin) /(BTempmax –

BTempmin) Combination used for monitoring drought and

vegetation stress due to excessive wetness Requires a long term dataset MSG provides a number of temperature channels,

notably IR039

Vegetation Monitoring

Vegetation Productivity Index A measure of the difference between the

current season vegetation response and the local norms as the statistical probability of having a worse case - this characterizes the severity of the deviation from the local normal

Current NDVI referenced against the NDVI percentile-images of the historical year, and classified in different frequency groups

Requires a long term NDVI dataset

Vegetation Monitoring

Weather hazard monitoring

15 minute updates

More channels used as RGB composites

Summary

MSG provides more than just a continuation of the service from the MFG

MSG data can be used for applications other than meteorological eg monitoring land surface parameters