Slide 1 ECMWF Training Course - The Global Observing System - 06/2013 The Global Observing System...
-
Upload
miguel-mckinnon -
Category
Documents
-
view
213 -
download
0
Transcript of Slide 1 ECMWF Training Course - The Global Observing System - 06/2013 The Global Observing System...
Slide 1
ECMWF Training Course - The Global Observing System - 06/2013
The Global Observing System
Stephen English
With material kindly provided by Peter Bauer, Cristina Lupu, Tony McNally, Mohamed Dahoui, Erland Kallen, Enza di Tomaso, Niels
Bormann, Sabatino di Michele and Richard Engelen
European Centre for Medium-Range Weather Forecasts
Slide 2
ECMWF Training Course - The Global Observing System - 06/2013
Role of observations
RM
S e
rror
(m
)
Time (hours)
SEVIRI 6.2 µm
Every 12 hours we assimilate ~7,000,000 observations to correct the 100,000,000 variables that define the model’s virtual atmosphere.
We monitor an additional 12,000,000.
Observations limit error growth and make forecasting possible….
Slide 3
ECMWF Training Course - The Global Observing System - 06/2013
The state spaceMASS (temperature, pressure…)Radiosondes, surface observations, satellite sounders, aircraft
MOISTURE (humidity, clouds, precipitation…)Radiosondes, surface observations, satellite sounders and imagers, aircraft, radar, lidar
DYNAMICS (wind, vorticity, convergence…)Radiosondes, surface observations, satellite imagers, satellite scatterometer/radar/lidar, aircraft
COMPOSITION (ozone, aerosol…)Ozone sondes, surface observations, satellite sounders
SURFACE (surface type, temperature, moisture, homogeneity…)Satellite active and passive systems, surface observations
Slide 4
ECMWF Training Course - The Global Observing System - 06/2013
Profilers
RadiosondeSynopShip
AircraftBuoys
MoistureMass
Wind
Composition
Ozone sondesAir quality stations
Soil moistureRain gauge
Slide 5
ECMWF Training Course - The Global Observing System - 06/2013
Data sources: Conventional
Instrument Parameters Height
SYNOPSHIPMETAR
temperature, dew-point temperature, wind
Land: 2m, ships: 25m
BUOYS temperature, pressure, wind 2m
TEMPTEMPSHIPDROPSONDES
temperature, humidity,pressure, wind
Profiles
PROFILERS wind Profiles
Aircraft temperature, pressure wind
ProfilesFlight level data
Slide 6
ECMWF Training Course - The Global Observing System - 06/2013
What types of satellites are used in NWP?
Advantages Disadvantages
GEO - Regional coverage No global coverage by single satellite
- Temporal coverage
LEO - Global coverage with single satellite
Slide 7
ECMWF Training Course - The Global Observing System - 06/2013
Radio occultation
Geo IR and Polar MW Imagers
Feature tracking in imagery (e.g. cloud track winds), scatterometers and doppler winds
Geo IR Sounder
Radar andGPS total path delay
PolarIR + MWsounders
MoistureMass
Wind
Composition
Ultraviolet sensors
Sub-mm,and near IR plusVisible (e.g. Lidar)
IR = InfraRedMW = MicroWave
Slide 8
ECMWF Training Course - The Global Observing System - 06/2013
Metop
Slide 9
ECMWF Training Course - The Global Observing System - 06/2013
Metop
Slide 10
ECMWF Training Course - The Global Observing System - 06/2013
Example of conventional data coverage
Aircraft – AMDAR (note also have Airep and ACARs)
Surface (synop) - ship
Buoy
Balloon profiles e.g. radiosondes
Slide 11
ECMWF Training Course - The Global Observing System - 06/2013
LEO Sounders LEO Imagers
Scatterometers GEO imagers
Satellite Winds (AMVs)
GPS Radio Occultation
Example of 6-hourly satellite data coverage
30 March 2012 00 UTC
Slide 12
ECMWF Training Course - The Global Observing System - 06/2013
Slide 13
ECMWF Training Course - The Global Observing System - 06/2013
Combined impact of all satellite data
EUCOS Observing System Experiments (OSEs):
• 2007 ECMWF forecasting system,• winter & summer season,• different baseline systems:
• no satellite data (NOSAT),• NOSAT + AMVs,• NOSAT + 1 AMSU-A,
• general impact of satellites,• impact of individual systems,• all conventional observations.
500 hPa geopotential height anomaly correlation
3/4 day
3 days
Slide 14
ECMWF Training Course - The Global Observing System - 06/2013
User requirements and satellite data: OSCAR www.wmo-sat.info
• Vision for the GOS in 2025 adopted June 2009• GOS user guide WMO-No. 488 (2007)• Manual of the GOS WMO-No. 544 (2003) (updated for ET-SAT Geneva April 2012)
Slide 15
ECMWF Training Course - The Global Observing System - 06/2013
Using DA to help design the GOS
Examples questions we use Data Assimilation techniques to study:
•Would it be beneficial for the Chinese FY3 program to move to the “early morning orbit” with the Europeans occupying the “morning orbit” and the Americans the “afternoon orbit”?
•Preparation for future instruments such as lidar and radar (EarthCARE).
•Study using Ensemble of Data Assimilations to estimate the number of GPSRO soundings needed in future (discuss with Sean Healy if interested).
Slide 16
ECMWF Training Course - The Global Observing System - 06/2013
2009 ExperimentsEnza Di Tomaso* and Niels Bormann
MetOp-A
NOAA-18 NOAA-19 Aqua
NOAA-15
NOAA-16
NOAA-17
Ti
me
AM
Early AM
PM
Slide 17
ECMWF Training Course - The Global Observing System - 06/2013
FY3 orbit: what is the optimal orbit configuration?
“two-satellite experiment”* MetOp-A * NOAA-18
“NOAA-15 experiment”* MetOp-A * NOAA-18 * NOAA-15
“NOAA-19 experiment”* MetOp-A * NOAA-18 * NOAA-19
Slide 18
ECMWF Training Course - The Global Observing System - 06/2013
“no-MW sounder experiment”
GOOD
“two-”, “three-”, “all-satellite experiment”
GOOD
two-satellite RMSE – no-Mw sounder RMSE three-satellite RMSE – no-Mw sounder RMSE all-satellite RMSE – no-Mw sounder RMSE
Are 3 satellites better than 2?
YES
3.5 months 107 casesCY36R1 T511
Slide 19
ECMWF Training Course - The Global Observing System - 06/2013
RMS difference forecast – analysis for NOAA-15 and NOAA-19 experiments
NOAA-19 experiment
GOOD
NOAA-15 experiment
GOOD
Do orbital positions matter?
YES
Slide 21
ECMWF Training Course - The Global Observing System - 06/2013
2012 experiments
•Baseline 1: microwave only (NPP + METOP-A)
•Baseline 2: microwave + infrared (NPP + METOP-A)
Slide 22
ECMWF Training Course - The Global Observing System - 06/2013
NH NH
SH SH
Early am better
pm better
Microwave only baselineMicrowave + infrared baseline
3 months 90 casesCY38R1 T511
Slide 23
ECMWF Training Course - The Global Observing System - 06/2013
REF_AT
62 N 60 N 58 N 56 N 54 N 52 N 50 N 48 N 46 N 44 N 42 N 40 N 38 N 36 N 34 N 32 N 30 NLat
100W 99 W 98 W 97 W 96 W 95 W 94W 93 W 92 W 91 W 90 W 89W 88W 87 WLon
1.1
1.9
3.0
4.3
5.9
7.6
9.3
10.9
12.5
Hei
gh
t (k
m)
-24 - -21 -21 - -18 -18 - -15 -15 - -12 -12 - -9 -9 - -6 -6 - -3 -3 - 0 0 - 3 3 - 6 6 - 9 9 - 12 12 - 15 15 - 18Observation
REF_AT
62 N 60 N 58 N 56 N 54 N 52 N 50 N 48 N 46 N 44 N 42 N 40 N 38 N 36 N 34 N 32 N 30 NLat
100W 99 W 98 W 97 W 96 W 95 W 94W 93 W 92 W 91 W 90 W 89W 88W 87 WLon
1.1
1.9
3.0
4.3
5.9
7.6
9.3
10.9
12.5
Hei
gh
t (k
m)
-24 - -21 -21 - -18 -18 - -15 -15 - -12 -12 - -9 -9 - -6 -6 - -3 -3 - 0 0 - 3 3 - 6 6 - 9 9 - 12 12 - 15 15 - 18
REF_AT
62 N 60 N 58 N 56 N 54 N 52 N 50 N 48 N 46 N 44 N 42 N 40 N 38 N 36 N 34 N 32 N 30 NLat
100W 99 W 98 W 97 W 96 W 95 W 94W 93 W 92 W 91 W 90 W 89W 88W 87 WLon
1.1
1.9
3.0
4.3
5.9
7.6
9.3
10.9
12.5
Hei
gh
t (k
m)
-24 - -21 -21 - -18 -18 - -15 -15 - -12 -12 - -9 -9 - -6 -6 - -3 -3 - 0 0 - 3 3 - 6 6 - 9 9 - 12 12 - 15 15 - 18
15 – 18
REF_AT
62N
60N
58N
56N
54N
52N
50N
48N
46N
44N
42N
40N
38N
36N
34N
32N
30N
Lat100
W99
W98
W97
W96
W95
W94
W93
W92
W91
W90
W89
W88
W87
WLon
1.1
1.9
3.0
4.3
5.9
7.6
9.3
10.9
12.5Height (km)
-24 - -21-21 - -18
-18 - -15-15 - -12
-12 - -9-9 - -6
-6 - -3-3 - 0
0 - 33 - 6
6 - 99 - 12
12 - 1515 - 18
-24 – -21
-21 – -18
-18 – -16
-16 – -12
-12 – -9
-9 – -6
-6 – -3
-3 – 0
0 – 3
3 – 6
6 – 9
9 – 12
12 – 15
Model First-Guess
Analysis
1D-Var Assimilation of Cloudsat Radar Reflectivities (dBZ)
Preparing for future missions e.g. Aeolus and EarthCARE
23
Slide 24
ECMWF Training Course - The Global Observing System - 06/2013
Combining NWP with CTM models and data assimilation systems
New requirements in GOS for atmospheric composition
Slide 25
ECMWF Training Course - The Global Observing System - 06/2013
Monitoring of observations
•Webpages•Automatic warnings•Collaboration between users and providers
•J = ½(y-H(x))TR-1(y-H(x)) + Jb
•At beginning and end of minimisation, with and without QC, plus bias corrections.
Slide 26
ECMWF Training Course - The Global Observing System - 06/2013
Selected statistics are checked against an expected range.
E.g., global mean bias correction for GOES-12 (in blue):
Soft limits (mean ± 5 stdev being checked, calculated from past statistics over a period of 20 days, ending 2 days earlier)
Hard limits (fixed)
Email-alert
Data monitoring – automated warnings
(M. Dahoui & N. Bormann)
http://www.ecmwf.int/products/forecasts/satellite_check/
Email alert:
Slide 27
ECMWF Training Course - The Global Observing System - 06/2013
Data monitoring – automated warnings
Slide 28
ECMWF Training Course - The Global Observing System - 06/2013
Satellite data monitoringData monitoring – automated warnings
Slide 29
ECMWF Training Course - The Global Observing System - 06/2013
Global Observing System is essential to weather forecasting
Technology driven….a more integrated approach now?
Mass is well observed.
Moisture – satellite observations are data rich but poorly exploited. Radar and lidar will become more important.
Dynamics – even wind observations are scarce.
Composition – NWP techniques have been successfully extended to environmental analysis and prediction but more observations are needed.
Surface – DA for surface fields is being attempted.
Slide 30
ECMWF Training Course - The Global Observing System - 06/2013
Thank you for your attention
Thanks again to Peter Bauer, Cristina Lupu, Tony McNally, Mohamed Dahoui, Erland Kallen, Enza di Tomaso, Niels Bormann, Sabatino di Michele and Richard Engelen
Slide 31
ECMWF Training Course - The Global Observing System - 06/2013
Backup slidesDetailed list of instruments for NWP and atmospheric composition
(not shown but included for information)
Slide 32
ECMWF Training Course - The Global Observing System - 06/2013
Sun-Synchronous Polar SatellitesInstrument Early morning
orbitMorning orbit Afternoon orbit
High spectral resolution IR sounder
IASI Aqua AIRSNPP CrIS
Microwave T sounder
F16, 17 SSMIS Metop AMSU-AFY3A MWTSDMSP F18 SSMISMeteor-M N1 MTVZA
NOAA-15, 18, 19 AMSU-A Aqua AMSU-AFY3B MWTS, NPP ATMS
Microwave Q sounder + imagers
F16, 17 SSMIS Metop MHSDMSP F18 SSMISFY3A MWHS
NOAA-18, 19 MHSFY3B MWHS, NPP ATMS
Broadband IR sounder
Metop HIRSFY3A IRAS
NOAA-19 HIRSFY3B IRAS
IR Imagers Metop AVHRRMeteor-M N1 MSU-MR
Aqua+Terra MODISNOAA-15, 16, 18, 19 AVHRR
Composition(ozone etc).
NOAA-17 SBUV NOAA-18, 19 SBUVENVISAT GOMOSAURA OMI, MLSENVISAT SCIAMACHYGOSAT
Slide 33
ECMWF Training Course - The Global Observing System - 06/2013
Instrument High inclination (> 60°) Low inclination (<60°)
Radio occultation
GRAS, GRACE-A, COSMIC, TerraSarXC-NOFS, (SAC-C), ROSA
MW Imagers TRMM TMIMeghatropics SAFIRE MADRAS
Radar Altimeter ENVISAT RAJASON Cryosat
Sun-Synchronous Polar Satellites (2)Instrument Early morning
orbitMorning orbit Afternoon orbit
Scatterometer Metop ASCATCoriolis Windsat
Oceansat OSCAT
Radar CloudSat
Lidar Calipso
Visible reflectance
Parasol
L-band imagery
SMOSSAC-D/Aquarius
Non Sun-Synchronous Observations
Slide 34
ECMWF Training Course - The Global Observing System - 06/2013
Product Status
SEVIRI Clear sky radiance Assimilated
SEVIRI All sky radiance Being tested for overcast radiances, and cloud-free radiances in the ASR dataset
SEVIRI total column ozone Monitored
SEVIRI AMVs IR, Vis, WV-cloudy AMVs assimilated
GOES AMVs
MTSAT AMVs
Data sources: Geostationary Satellites