VALIDATION OF SATELLITE PRECIPITATION PRODUCTS WITH USE OF HYDROLOGICAL MODELS – EUMETSAT H-SAF ACTIVITIES Jerzy Niedbała Institute of Meteorology and Water Management Hydrological Forecasting Office, Kraków Bożena Łapeta, Piotr Struzik Institute of Meteorology and Water Management Satellite Remote Sensing Centre, Kraków Whole H-SAF Team contributed Institute of Meteorology and Water Management, POLAND, Krakow EUMETSAT H-SAF – Satellite Application Facility in Support to Operational Hydrology and Water Management
Transcript
VALIDATION OF SATELLITE PRECIPITATION PRODUCTS WITH USE OF HYDROLOGICAL MODELS –
EUMETSAT H-SAF ACTIVITIES
Jerzy NiedbałaInstitute of Meteorology and Water ManagementHydrological Forecasting Office, Kraków
Bożena Łapeta, Piotr StruzikInstitute of Meteorology and Water ManagementSatellite Remote Sensing Centre, Kraków
Whole H-SAF Team contributed
Institute of Meteorology and Water Management, POLAND, Krakow
EUMETSAT H-SAF –
Satellite Application Facility in Support to Operational Hydrology and Water Management
• EUMETSAT H-SAF activities (very shortly).
• H-SAF validation programme
• IMWM Poland –
H-SAF validation studies of precipitation products:
-
Conventional validation,
-
Hydrological impact studies.
• Conclusions
Presentation outline:
Institute of Meteorology and Water Management, Kraków, PolandHydrological Forecasting OfficeSatellite Remote Sensing Centre
EUMETSAT Satellite Application Facility in Support to Operational Hydrology and Water Management (H-SAF)
H-SAF activities officially started (15 Sept.2005) –
development phase 2005-2010,
12 European countries involved.
Poland coordinates Hydrological Validation and implementation cluster.
The main objectives of H-SAF :
a.
to provide new satellite-derived products
from existing and future satellites with sufficient time and space resolution to satisfy the needs of operational hydrology; identified products:
precipitation soil moisture snowb.
to perform independent validation of the usefulness of the new products
for fighting against floods, landslides, avalanches, and evaluating water resources.
EUMETSAT Satellite Application Facility in Support to Operational Hydrology and Water Management (H-SAF)
H-SAF bottom-up aproachRequirements driven by operational hydrology needs.
Creation of operational satellite products for:-Better spatialisation of conventional measurements,-To complement ground observations on the areas with sparse ground networks and/or not covered by radars,- Merging satellite products with other data sources,- Redundancy of information - useful in case of disaster situation (damage of measuring posts or data links)
Final assessment of satellite products to be done by Hydrological Impact Studies.
Demonstration and training on satellite products use, in real operational environment of State Hydrological Services
Impact studies
Hydrological cycle vs. satellite products
Precipitation ProductsProducts from H-SAF (quality figures refer to the Operational Phase (2010-2015)
Belgium, France, Germany, Italy, Poland, Slovakia, Turkey
At least 24 catchments, 14 operational models
Fig. 28 -
Composite image from all Polish radars.
8 radars
989 telemetric posts
IMWM
Poland
METEOSAT (7,8,9)
NOAA (all)FengYun 1D
Ready for Metop60 Synop
152 Climate
978 Raingauges
196 Snow obs. posts
Lightning detection
SAFIR
NWP:
LM-COSMO, ALADIN
••Variety of climatological conditionsVariety of climatological conditions••Variety of terrain conditionsVariety of terrain conditions••Variety of land coverVariety of land cover
RG data quality control – analysis of the measurements performed by each gauge (the posts are equipped with two gauges) in order to exclude the wrong data.
The time slots closest to satellite overpass were taken into consideration.
Validation method
For each satellite AMSU / NOAA pixels, the automatic rain gauges situated within that pixel were found.
Different pixel’s size was taken into account depending both on the direction (along and across track) and the pixel position in scanning line.
The pixel shape was assumed to be the rectangular.
If more than one rain gauge were found within one satellite pixel, the ground rain rate value was calculated as a mean of all rain gauges measurements.
H01, 2007-05-22 15.20 UTC H02 v.1.1, 2007-06-04 14.37 UTC H02 v.2.1, 2007-06-04 14:37 UTC
H03 v.1.0, 2007-06-04 14.27 UTC H05 v.1.0, 2007-06-04 15.00 UTC
Preliminary results
Three days with typical convective precipitation 05.2007 i 04-05.06.2007.All available precipitation products were analysed:
91%
2%
18,8 %
89,2 %7%
H03 v1.0
S‐NO D‐NO
S‐NO D‐YES
S‐YES i D‐YES
S‐YES i D‐NO
93% 3%
28 %
72 %
4%
H01 v1.0
S‐NO D‐NO
S‐NO D‐YES
S‐YES i D‐YES
S‐YES i D‐NO
90%
5%
37,6 %
62,4 %
5%
H02 v1.1
S‐NO D‐NO
S‐NO D‐YES
S‐YES i D‐YES
S‐YES i D‐NO
24,43 %
0,26 %7,7 %
92,3 %75,31 %
H02 v2.1
S‐NO D‐NO
S‐NO D‐YES
S‐YES i D‐YES
S‐YES i D‐NO
76%
10% 33,9 %
66,1 %
14%
H05 v1.0 ‐ suma 3‐godzinna opadu
S‐NO D‐NO
S‐NO D‐YES
S‐YES i D‐YES
S‐YES i D‐NO
H01 v1.0 H02 v1.1 H02 v2.1 H03 v1.0 H05 v1.0
Hit rate * 0.28 0.26 0.96 0.26 0.33
False-alarm rate
0.69 0.62 0.92 0.89 0.68
Odds ratio 13.37 11.13 7.73 4.92 4.00
Accuracy 0.94 0.92 0.30 0.91 0.81
Frequency Bias
0.89 0.7 12.49 2.4 1.06
* Strongly dependant on the rain/no rain class numbering
Results of the categorical (dichotomous) statistics obtained for H-SAF precipitation products
1
10
100
1000
10000
0 0,25 0,5 1 2 4 8 10 16 32 64
Num
ber o
f cas
es
Rain rate [mm/h]
Rain gauges H02 v21 H02 v11
1
10
100
1000
10000
0 0,25 0,5 1 2 4 8 10 16 32 64
Num
ber o
f cas
es
Rain rate [mm/h]
Rain gauges H01 v10
1
10
100
1000
10000
0 0,25 0,5 1 2 4 8 10 16 32 64
Num
ber o
f cas
es
3 hour accumulated precipitation [mm]
Rain gauges H05 v10
1
10
100
1000
10000
100000
1000000
Num
ber o
f cas
es
Rain rate [mm/h]
RG H03
H01 v1.0[mm/h]
H02 v1.1[mm/h]
H02 v2.1[mm/h]
H03 v1.0[mm/h]
H05 v1.0[mm]
Mean error -2.938 1.10 -0.82 -1.86 0.01
Mean absolute
error
4.14 2.69 1.25 4.35 1.35
RMSE 7.12 4.12 2.93 11.69 9.08
Multiplicative
Bias
0.4 1.43 0.48 0.57 1.00
Standard Deviation of diff.
6.62 4.00 2.82 11.55 9.09
Results of continuous statistics for H-SAF precipitation products obtained with the use of rain gauges data (in [mm/h] for H01-H03 and in [mm] for H05)
-60-40-20
020406080
100120140
0 10 20 30 40 50 60 70 80
Rai
n ra
te d
iff.
Sat-R
G [
mm
/h]
Rain rate form RG [mm/h]
H02 v1.1
August 2006 – August 2007
First conclusions:
• The obtained results showed that both, detection and estimation of intensity of convective rainfall is very difficult task. All rain rate products significantly underestimate high precipitation and overestimate low precipitation.
• For all products, except for H02 v21, the similar values of the hit rate, false alarm rate and accuracy were obtained. However, high value of odds ratio for H01 suggests that this product recognises the precipitation better than other.
• Both, dichotomous and continuous statistics, showed that rain rate products H02 v21 was too ‘rainy’, especially for the low precipitation categories (form 0 to 1 mm/h)
• The quality of H02 products depends on the pixel number: the closer to the ends of AMSU scan line, the lower quality.
• H03 products quality seems to be lower, with reasonably higher RMSE and lower correlation coefficient. This product has been preliminary validated with the use of hydrological model
Preparation of tool verification Preparation of tool verification --
the hydrological modelthe hydrological model
input data for hydrological models from manual and
automatic ground stations and experimental resarch
(*) - on basis Sarma P.B.S., Delleur J.W., Rao A.R., 1973, Comparison of rainfall - runoff models for urban areas, Journal of Hydrology 18(3/4), 329-347
(preliminary) CONCLUSION:
exchange of ground observations by satellite data don’t relapse results
of
hydrological
model
Conclusions:
1.
H-SAF is preparing operational structure for hydrology. Without acceptation of products and their quality (at least among EUMETSAT Member and Cooperationg States), this activity will be useless.
2.
First H-SAF products already available (inter SAF distribution).
3.
Preliminary validation is promising –
further studies required.
4.
Hydrological impact studies –
way forward to avoid problem with comparison of completely different data.
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