Frequent rain observation from geostationary satellite by

Frequent rain observation from geostationary satellites
by millimetre-submillimetre-wave sounding
Bizzarro Bizzarri, CNR Istituto di Scienze dell’Atmosfera e del Clima, Italy
Albin Gasiewski, NOAA Environmental Technology Laboratory, USA
David Staelin, MIT Research Laboratory of Electronics, USA
Content
• Requirements for frequent precipitation observation
• Principle of MW precipitation observation from geostationary orbit
• GOMAS (Geostationary Observatory for MW Atmospheric Sounding)
WMO/CGMS 1st Internationl Precipitation Working Group Workshop, Madrid, 23-27 September 2002
1
WMO and EUMETSAT requirements for precipitation observation
Requirement
Global
Unit
WMO
NW P
RegIonal
EUM
WMO
NW P
Nowcas ting
EUM
WMO
EUM
Target
Threshold
Target
Threshold
Target
Threshold
Target
Threshold
Target
Threshold
Target
Threshold
x
km
50
100
5
100
10
50
3
50
5
50
1
5
r.m.s.
mm/h
0.1
1
0.1
1
0.1
1
0.1
1
0.1
1
1
10
t
h
1
12
1
12
0.5
6
0.5
3
0.08
1
0.03
0.3
delay
h
1
4
1
4
0.5
2
0.5
1
0.08
0.5
0.03
0.1
2
The problem of measuring precipitation
The most long-standing practise makes use of VIS/IR image sequences from GEO:
• The observing frequency is suitable (15 min with MSG)
• The measurement is strongly indirect (VIS/IR only “sees” the cloud top)
• The applicability is mostly addressing convective precipitation.
From LEO, MW images are used (from SSM/I, TRMM, in the near future GPM):
• The measurement is direct for low frequencies (10 GHz), less for high frequencies (90 GHz)
• The applicability is better for convective precipitation, but extends to all precipitation types
• The frequency, with GPM, will be around 3 hours
• Global scale will be served optimally, regional scale to a fair extent
• For the mesoscale, fusion between LEO MW images and GEO VIS/IR images will be attempted.
The ideal would be to extend the MW imagery technique to the geostationary orbit, but:
• The antenna diameter for a 10-km resolution is 15 m at 90 GHz, 35 m at 37 GHz, 70 m at 19 GHz
• Polarisation diversity is not practical from the geostationary orbit (large and variable z-angle).
GEO requires using higher frequencies and exploiting a different physical principle.
3
The physical principle for measuring precipitation from GEO
MW observation from LEO makes use of “atmospheric windows”:
• Most common frequencies: 6 GHz, 10 GHz, 19 GHz, 23 GHz, 37 GHz, 90 GHz, 150 GHz
• Dual polarisation for roughness effects (over the sea) and scattering from ice (over land).
The proposed principle for GEO exploits absorption bands:
•
•
•
•
•
Profiles of temperature and humidity are measured by more bands at different frequencies
Profiles observed exploiting bands of different frequencies are differently sensitive to clouds
Absorption bands at very high frequencies enable using antennas of affordable size
It is not necessary to differentiate polarisations
In absorption bands the measurement is equally effective over sea and land.
The precipitation measurement passes through the sounding one, therefore:
• Many more channels are needed, very narrow (< 1 ‰), with SNR > 100
• In exchange, one simultaneously gets:
- the temperature vertical profile (also inside clouds)
- the humidity vertical profile (also inside clouds)
- the columnar content (or gross profile) of liquid water in the cloud
- the columnar content (or gross profile) of ice water in the cloud
- the precipitation.
4
Multi-channel image from an airborne radiometer (Gasiewski et al, 1994). Note:
• In absorption bands (183 and 325 GHz) increasing cloud impact moving from the peak to
the window (from 183  1 to 183  3 and 183  7; and from 325  1 to 325  3 and 325  9);
• In windows (89, 150, 183  7, 220 e 325  9) increasing cloud impact with increasing
frequency.
5
Precipitation images from a cold front on October 7, 1998: NEXRAD precipitation map
smoothed to 15 km resolution (left image), and NOAA/AMSU precipitation map obtained
using a neural net retrieval technique (right image) (Staelin and Chen, 2000).
6
NOAA-15 AMSU-B 183+/-7 GHz 15-km resolution imagery of small
rain cells over the Eastern U.S on August 2, 2000 (from Staelin and
Chen, 2000).
7
Comparison between the 118/54 GHz profile ratio from the NAST-M microwave radiometer being flown on the
NASA ER-2 aircraft and simultaneous EDOP Doppler radar reflectivity observation. Hurricane Bonnie at 17
GMT on August 26, 1998 (Tsou et al, 2001). The ratio 118/54 is unit in the absence of precipitation or above
the precipitation cell, and reduces in the presence of precipitation because of higher attenuation from drops
and impact from ice scattering at the higher frequency. The agreement between the two vertical crosssections is striking. Horizontal maps of this information from GEO at 15 min intervals, will resemble a proxy
rain radar operating over continental field of view, particularly over oceans and mountainous terrain.
8
Atmospheric spectrum in the MW/Sub-mm range (Klein and Gasiewski, 2000).
Preferred bands - for O2 (temperature): 54 GHz, 118 GHz, 425 GHz; for H2O: 183 GHz, 380 GHz.
9
Incremental
Weighting
Functions (IWF) for the
selected channels in the
bands of oxygen (54, 118
and 425 GHz) and of water
vapour (183 and 380 GHz).
Note that the sensitivity of
380 and 425 GHz drastically
drops in lower troposphere
(Klein and Gasiewski, 2000).
10
Reference user requirements adopted for GOMAS
Geophysical
parameter
Temperature profile
Horizontal
resolution
Vertical
resolution
Accuracy
(r.m.s.)
Observing
cycle
Delay of
availability
30 km
2.0 km
1.5 K
1h
15 min
Humidity profile
20 km
2.0 km
20 %
1h
15 min
Cloud liquid/ice water
20 km
5.0 km
50 %
15 min
5 min
Precipitation rate
10 km
-
5 mm/h
15 min
5 min
Resolution v/s frequency and antenna diameter
Antenna Ø
54 GHz
118 GHz
183 GHz
380 GHz
425 GHz
1m
242 km
112 km
73 km
35 km
31 km
2m
121 km
56 km
36 km
18 km
16 km
3m
81 km
37 km
24 km
12 km
10 km
4m
60 km
28 km
18 km
8.8 km
7.8 km
11
GOMAS (Geostationary Observatory for MW Atmospheric Sounding)
European sector (1/12 of disk) scanned each 15 minutes
Temperature vertical profile, all-weather and inside clouds: resolution 30 km
Humidity vertical profile, all-weather and inside clouds: resolution 20 km
Columnar content or gross profile of liquid and ice water: resolution 20 km
Precipitation: resolution 10 km.
12
Radiometric performance assessment for 15 min observing cycle
Compliant
NET compliance code

(GHz)

(MHz)
56.325
Nearly compliant
Compliant on 2 x or 1 h
Required
NET (K)
Expected
NET (K)
Peak
of IWF

(GHz)

(MHz)
50
0.6
0.15
27 km
183.310  0.300
56.215
50
0.5
0.15
23 km
56.025
250
0.5
0.07
55.520
180
0.4
54.950
300
6 x 6 pixels
54.400
220
(60 km)
53.845
190
53.290
Product
resolution
IFOV
s.s.p.
Required
NET (K)
Expected
NE T (K)
Peak
of IWF
300
0.6
0.45
10 km
183.310  0.900
500
0.6
0.35
8.5 km
17 km
183.310  1.650
700
2 x 2 pixels
0.5
0.29
7 km
0.08
13 km
183.310  3.000
1000
(20 km)
0.3
0.24
6 km
0.4
0.06
10 km
183.310  5.000
2000
0.4
0.17
5 km
0.3
0.07
8 km
183.310  7.000
2000
0.6
0.17
4 km
0.3
0.08
5 km
183.310  17.000
4000
0.3
0.18
surface
360
0.3
0.06
3 km
380.197  0.045
30
0.3
2.36
15 km
52.825
300
0.2
0.06
2 km
380.197  0.400
200
0.5
0.91
13 km
51.760
400
0.1
0.05
1 km
380.197  1.500
500
2 x 2 pixels
0.5
0.58
11 km
50.300
180
0.1
0.08
surface
380.197  4.000
900
(20 km)
0.5
0.43
9 km
118.750  0.018
6
0.5
1.32
34 km
380.197  9.000
2000
0.4
0.29
7 km
118.750  0.035
12
0.6
0.93
29 km
380.197  18.000
2000
0.3
0.36
6 km
118.750  0.080
20
0.6
0.72
24 km
424.763  0.030
10
0.5
3.40
34 km
118.750  0.200
100
0.5
0.32
19 km
424.763  0.070
20
0.6
2.41
28 km
118.750  0.400
200
3 x 3 pixels
0.5
0.23
15 km
424.763  0.150
60
0.6
1.39
23 km
118.750  0.700
400
(30 km)
0.5
0.16
12 km
424.763  0.300
100
3 x 3 pixels
0.5
1.08
18 km
118.750  1.100
400
0.4
0.16
9 km
424.763  0.600
200
(30 km)
0.5
0.76
15 km
118.750  1.500
400
0.4
0.16
7 km
424.763  1.000
400
0.5
0.54
12 km
118.750  2.100
800
0.3
0.11
5 km
424.763  1.500
600
0.5
0.44
8 km
118.750  3.000
1000
0.2
0.10
3 km
424.763  4.000
1000
0.4
0.34
5 km
118.750  5.000
2000
0.1
0.07
surface
380.197  18.000
2000
1 pixel
12 km
1.0
0.72
6 km
424.763  4.000
1000
(10 km)
10 km
1.0
1.02
5 km
81 km
37 km
Product
resolution
IFOV
(s.s.p.)
Candidate to be dropped
24 km
12 km
10 km
13
3” Thick Composite Reflector
Nodding / Morphing
Subreflector
Space Calibration Tube
Receiver Package
50-430 GHz Feeds
Thin Struts
Elevation Motor
& Compensator
Azimuth Motor
& Compensator
Backup
Structure
The GOMAS instrument with its 3-m antenna
14
NORTH
DIRECTION
Solar Wing
Space
Calibration
Tube
The GOMAS
satellite
S-band
Antenna
for TT&C
3 -meter
Antenna
NADIR
S-Band Antenna
for TT&C
Star Sensors
S-band antenna
for LRIT
• Mass: 860 kg (“dry": 430 kg)
• Electrical power: 500 W
• Volume: 3.0 x 3.0 x 3.0 m3
• Data rate: 128 kbps (S-band,
compatible with MSG LRIT).
15
List of Proponents of GOMAS (undertaking to implement the scientific programme)
P.I.: Bizzarro BIZZARRI, for the CNR Istituto Scienze dell'Atmosfera e del Clima, Roma, Italy
Team leader
Institute
Team leader
Institute
Umberto AMATO
CNR Istituto Applicazioni della Matematica, Napoli, Italy
Paul MENZEL
NOAA/NESDIS Office of Research and Application, Madison Wis., USA
John BATES
NOAA/NESDIS, National Climatic Data Center, Asheville NC, USA
Jungang MIAO
Institute of Environmental Physics, University of Bremen, Germany
Wolfgang BENESCH
Deutscher Wetterdienst, Offenbach, Germany
Alberto MUGNAI
CNR Istituto Scienze dell'Atmosfera e del Clima, Roma, Italy
Stefan BÜHLER
Institute of Environmental Physics, University of Bremen, Germany
Paolo PAGANO
Servizio Meteorologico dell'Aeronautica, Roma, Italy
Massimo CAPALDO
Servizio Meteorologico dell'Aeronautica, Roma, Italy
Jean PAILLEUX
Météo France, Toulouse, France
Marco CERVINO
CNR Istituto Science dell'Atmosfera e del Clima, Bologna, Italy
Juan PARDO
Instituto de Estructura de la Materia, Madrid, Spain
Vincenzo CUOMO
CNR Istituto Metodologie Avanzate di Analisi Ambientale, Potenza, Italy
Federico PORCU'
Department of Physics, University of Ferrara, Italy
Luigi De LEONIBUS
Servizio Meteorologico dell'Aeronautica, Roma, Italy
Catherine PRIGENT
Dep.nt de Radioastronomie Millimetrique, Observatoire de Paris, France
Michel DESBOIS
CNRS Laboratoire de Météorologie Dynamique, Palaiseau, France
Franco PRODI
CNR Istituto Science dell'Atmosfera e del Clima, Bologna, Italy
Stefano DIETRICH
CNR Istituto Science dell'Atmosfera e del Clima, Roma, Italy
Rolando RIZZI
Department of Physics, University of Bologna, Italy
Frank EVANS
University of Colorado, Atmospheric & Oceanic Sciences, Boulder Co., USA
Guy ROCHARD
MétéoFrance, Centre de Météorologie Spatiale, Lannion, France
Laurence EYMARD
CNRS Centre études Environnement Terrestres et Planétaires, Vélizy, France
Hans Peter ROESLI
MétéoSuisse, Locarno-Monti, Switzerland
Albin GASIEWSKI
NOAA Environmental Technology Laboratory, Boulder Co., USA
Carmine SERIO
Dip.nto Ingegneria e Fisica Ambiente, University of Basilicata, Potenza, Italy
Nils GUSTAFSSON
Swedish Meteorological and Hydrological Institute, Norrköping, Sweden
William SMITH
NASA Langley Research Center, Hampton VA., USA
Georg HEYGSTER
Institute of Environmental Physics, University of Bremen, Germany
Antonio SPERANZA
Hydrographic and Mareographic Service, Roma, Italy
Marian KLEIN
NOAA Environmental Technology Laboratory, Boulder Co., USA
David STAELIN
MIT Research Laboratory of Electronics, Cambridge MA., USA
Klaus KÜNZI
Institute of Environmental Physics, University of Bremen, Germany
Alfonso SUTERA
Department of Physics, University of Roma, Italy
Vincenzo LEVIZZANI
CNR Istituto Science dell'Atmosfera e del Clima, Bologna, Italy
Jung-Jung TSOU
NASA Langley Research Center, Hampton VA., USA
Gian Luigi LIBERTI
CNR Istituto Science dell'Atmosfera e del Clima, Bologna, Italy
Chris VELDEN
Cooperative Institute for Meteorological Satellite Studies, Madison Wis.,USA
Ernesto LOPEZ-BAEZA
Dep.nt of Thermodynamics, Faculty of Physics, University of Valencia, Spain
Guido VISCONTI
Department of Physics, University of L'Aquila, Italy
16
Conclusions
• Strong requirements exist for frequent precipitation observation.
• From GEO, a new physical principle needs to be exploited.
• GOMAS is proposed as a demonstration mission.
• It would be a precursor for future operational applications.
• From the technical standpoint, and building on the studies
conducted in the U.S. on GEM, it is believed that no enabling
technology is currently missing.
• The GOMAS satellite could be developed in time for a launch in the
2007-2009 timeframe.
• It would provide simultaneous retrieval of:
- temperature profile (x  30 km)
- humidity profile (x  20 km)
- cloud liquid/ice water total column and gross profile (x  20 km)
- precipitation rate (x  10 km)
each 15 minutes ! over  1 / 12 of the disk covering sea and land !
17