uses of satellite data for monitoring and forecasts of
TRANSCRIPT
Uses of Satellite Data for Monitoring and Forecasts of Hurricane and Coastal Precipitation
Fuzhong Weng NOAA/NESDIS/Center for Satellite Applications and Research
Xiaolei Zou
Florida State University
Vijay Tallapragada and Andrew Collard NOAA/NWS/Environmental Modeling Center
And
STAR/EMC Satellite Data Assimilation Team Members (Ben Zhang, Lin Lin, In-Hyuk Kwon, and Haixia Liu)
Impacts of Satellite Data on Global Medium-Range Weather Forecasts
0 2 4 6 8 10 12 14 16 18
O3: Ozone from satellites METEOSAT IR Rad (T,H)
MTSATIMG: Japanese geostationary sat vis and IR imagery GOES IR rad (T,H)
MODIS: Moderate Resolution Imaging Spectroradiometer (winds) GMS: Japanese geostationary satellite winds
SSMI: Special Sensor MW Imager (H and sfc winds) AMSRE: MW imager radiances (clouds and precip)
MHS: MW humidity sounder on NOAA POES and METOP (H) MSG: METEOSAT 2nd Generation IR rad (T,H)
HIRS: High-Resol IR Sounder on NOAA POES (T,H) PILOT: Pilot balloons and wind profilers (winds)
Ocean buoys (Sfc P, H and winds) METEOSAT winds
GOES winds AMSU-B: Adv MW Sounder B on NOAA POES
SYNOP: Sfc P over land and oceans,H, and winds over oceans QuikSCAT: sfc winds over oceans
TEMP: Radiosonde T, H, and winds GPSRO: RO bending angles from COSMIC, METOP
AIREP: Aircraft T, H, and winds AIRS: Atmos IR Sounder on Aqua (T,H)
IASI: IR Atmos Interferometer on METOP (T,H) AMSU-A: Adv MW Sounder A on Aqua and NOAA POES (T)
Forecast error reduction contribution (%)
2009 2010 2004 2005 2006 2007 2008 2011 2012 2013 2014 2015 2016 2017 2018
2019 2020
PM Orbit
Mid-AM Orbit
Early-AM Orbit
DMSP 17 DMSP 19
DMSP 20
METOP-B METOP-C
METOP-A
DMSP 16 DMSP 18
NOAA 18
NOAA 19
NPP
JPSS-1
DMSP: SSMI/S
METOP: AVHRR HIRS IASI AMSU-A MHS GOME-2 ASCAT GRAS
NOAA: AVHRR HIRS AMSU-A MHS SBUV/2
NPP: VIIRS, ATMS, OMPS, CrIS
C1:VIIRS, ATMS, OMPS, CrIS
NOAA/METOP/DMSP Satellite System
Suomi NPP Instruments NPP/JPSS Instrument! Measurement !
ATMS - Advanced Technology Microwave Sounder !
ATMS and CrIS together provide high ver4cal resolu4on temperature and water vapor informa.on needed to maintain and improve forecast skill out to 5 to 7 days in advance for extreme weather events, including hurricanes and severe weather outbreaks
CrIS - Cross-track Infrared Sounder !
VIIRS – Visible Infrared Imager Radiometer Suite!
VIIRS provides many cri.cal imagery products including snow/ice cover, clouds, fog, aerosols, fire, smoke plumes, vegeta4on health, phytoplankton abundance/chlorophyll
OMPS - Ozone Mapping and Profiler Suite!!
Ozone spectrometers for monitoring ozone hole and recovery of stratospheric ozone and for UV index forecasts
CERES - Clouds and the Earthʼs Radiant Energy System!!
Scanning radiometer which supports studies of Earth Radiation Budget!
The First ATMS Image at 183GHz
6 1
48
96
49
Scan angle Beam width
ATMS Scan Angle and Beam Width
Channel Nadir Resolution (km) Outmost FOV size (km)
ATMS AMSU ATMS AMSU Cross-track Along-track
ATMS AMSU ATMS AMSU
1-2 1-2 74.8 48.6 323.1 155.2 141.8 85.6
3-16 3-15 31.6 48.6 136.7 155.2 60.0 85.6
17-22 16-20 15.8 16.2 68.4 58.9 30.0 29.4
7
Comparison of Spatial Temperature Structure between ATMS and AMSU-A (CH2)
NPP ATMS and VIIRS Imager and Products
Warm Core Cross section along 26.0 N VIIRS 0.64 µm visible and 11.45 µm IR images at 18:33 UTC, 28 Aug 2012
METAR, MSL Pressure, and Buoys information included
Hurricane Sandy Warm Core Anomaly Ascending 1730 UTC, 29 October 2012
Cross section along Longitude 72.9 W Cross section along Latitude 38.1 N
At 1800 UTC Oct 29 Max Wind: 90 MPH, Min Pressure: 940 hPa
Sandy Max Wind, Warm Core and MSLP
The First Light CrIS Image
Spectral Coverage of Thermal Sounders (Example BT’s for AIRS, IASI, & CrIS)
AIRS, 2378 Channels
CrIS 1305
IASI, 8401 Channels
CO2 CO2 O3 CO CH4
13
Example of T(p) & q(p) Channel Kernel Functions
AIRS 15 µm (650-800 cm-1) band
K = dR/dT
AIRS 6.7 µm (1200-1600 cm-1) band
K = dR/dq
14
CrIS Radiometric Calibration: Compared to AIRS and IASI
AIRS
CrIS
CrIS-AIRS
IASI
CrIS
CrIS-IASI
CrIS has about 0.2K warm bias wrt IASI and no bias wrt AIRS from SNO collocated data sets. In the analysis, IASI data was de-‐apodized to obtain the original interferogram data and are then resampled using CrIS spectrum resolu4on, and FFT back to get CrIS like radiances
Courtesy of Likun Wang, STAR
CrIS SDR Spectra and Global Coverage
FOV (~14km nadir) FOR (~50km, Nadir)
VSC
Window Channel Water vapor Channel
Total clear sky observa4on points ~400000
allFOVFOVi CRTMObsCRTMObsBIASi
)()( −−−=
Blue: a:er nonlinearity coefficient change but before spectral coefficient change
Black: before nonlinearity and spectral coefficient changes
Red: a:er nonlinearity coefficient and spectral coefficient changes
The achieved uniformity of the spectral and radiometric uncertain5es cross the 9 FOVs is important for NWP to maximize the use of the radiance data
CrIS Individual FOV Bias wrt NWP Simulations
Courtesy of Yong Chen, STAR
From Niels Bormann, ECMWF
Forecast Impact of CrIS in ECMWF
Radiance observa4ons from CrIS have only been available since 26 June 2012 and thus forecast impact experiments are not yet mature. However, preliminary results suggest that assimila4ng just 57 key temperature sounding channels from CrIS in addi.on to AIRS and IASI can improve forecasts compared to the control. Note that the orbit of NPP is on top of that of AQUA (13:30) so CrIS and AIRS data are used in close proximity – work con4nues to op4mise analysis weights.
Northern Hemisphere , Z 500 hPa; 2-‐month trial
CrIS good
CrIS bad
0 1 2 3 4 5 6 Forecast day
0.04
0.02
0.00
-0.02
0.06
MetOp Instruments
• AVHRR/3 - Advanced Very High Resolution Radiometer
• HIRS/4 - High Resolution Infrared Sounder
• AMSU-A - Advanced Microwave Sounding Units-A1/A2
• MHS - Microwave Humidity Sounder
• ASCAT - Advanced Scatterometer
• GOME-2 - Global Ozone Monitoring Experiment-2
• IASI - Infrared Atmospheric Sounding Interferometer
• GRAS - The GNSS (Global Navigation Satellite System) Receiver for Atmospheric Sounding (GRAS)
Highlighted instruments in red are the common ones which are also on board of NOAA satellites
Ozone Perturbation during Hurricane Event: An Example of METOP GOME-2
Metop-A Metop-A and Metop-B
GPSRO Measurements: Example Metop-B GRAS
Slide: 20
Metop-B: Validation in October 2012 (against COSMIC)
Radio occultation bending angle co-location statistics of GRAS on Metop-A, -B and COSMIC (within 300km, 3h). Otherwise as previous plot.
Surface Scatterometer Wind: METOP ASCAT L2 Winds
• ASCAT-A and –B winds very similar • Top: ASCAT-B in blue • Left: ASCAT-B statistics for wind speed,
direction and u/v components, with respect to ECMWF winds: wind quality already well within requirements
23
Passive Microwave Imager: an example of GCOM-W1 AMSR-2 Instrument
• Deployable main reflector system with 2.0m diameter.
• Frequency channel set is identical to that of AMSR-E except 7.3GHz channel for RFI mitigation.
• 2-point external calibration with the improved HTS (hot-load).
AMSR2 Channel Set Center Freq. [GHz]
Band width [MHz]
Polarization
Beam width [deg] (Ground res. [km])
Sampling interval
[km]
6.925/ 7.3 350
V and H
1.8 (35 x 62)
10
1.7 (34 x 58) 10.65 100 1.2 (24 x 42) 18.7 200 0.65 (14 x 22) 23.8 400 0.75 (15 x 26) 36.5 1000 0.35 (7 x 12) 89.0 3000 0.15 (3 x 5) 5
Stowed
AMSR2 characteristics
Scan Conical scan
Swath width 1450km Antenna 2.0m offset parabola Digitalization 12bit
Incidence angle nominal 55 degree
Polarization Vertical and Horizontal Dynamic range 2.7-340K
Deployed
GCOM-W AMSR-2 provides higher space resolutions compared its precursor on EOS-Aqua (AMSR-E) and better design for mitigating radio frequency interference in land remote sensing application
Information Content from GCOM-W1 AMSR2
Duration 9 - 21 February 2012 MSPD=115 mph MSLP=932 (hPa) JAXA launched GCOM-W1 on Oct 18, 2011 with AMSR2 on board and NESDIS is developing
NOAA unique AMSR2 products for user community.
AMSR-E Ocean Products: Theoretical Base
7095
120145170195220245270
0 1 2 3 4 5 6 7 8 9 10Liquid Water Path (mm)
T H (K
)
10.65 GHz 18.7 GHz 36.5 GHz
(b)
170
185
200
215
230
245
260
275
0 1 2 3 4 5 6 7 8 9 10
Liquid Water Path (mm)
T V (K
)
10.65 GHz 18.7 GHz 36.5 GHz
(a)
155
160
165
170
175
180
185
270 275 280 285 290 295 300 305 310
SST (K)
T V (K
)
6.925 GHz 10.65 GHz
(c)
70
80
90
100
110
120
130
140
0 3 6 9 12 15 18 21 24 27 30
SSW (m/s)
T H (K
)
6.925 GHz 10.65 GHz
(d)
Information Content from GCOM-W1 AMSR2 Hurricane Sandy-10-28-2012 06 UTC
Duration 9 - 21 February 2012 MSPD=115 mph MSLP=932 (hPa)
JAXA launched GCOM-W1 on Oct 18, 2011 with AMSR2 on board and NESDIS is developing NOAA unique AMSR2 products for user community.
SST SSW
Information Content from GCOM-W1 AMSR2 Hurricane Sandy-10-28-2012 06 UTC
Duration 9 - 21 February 2012 MSPD=115 mph MSLP=932 (hPa) JAXA launched GCOM-W1 on Oct 18, 2011 with AMSR2 on board and NESDIS is developing
NOAA unique AMSR2 products for user community.
TPW CLW
Forecasts of Hurricane Sandy without Polar satellites Tony McNally
ECMWF forecasts of Mean Sea Level Pressure, 5 days in advance of the 30th October 2012 for the landfall of Hurricane Sandy. Forecasts from an assimilation system with no polar satellites fail to predict the landfall of the storm on the US east coast.
NO POLAR SAT ECMWF OPS VERIFICATION
5 day forecast: Base time 2012-10-25-00z Valid Time: 2012-10-30-00z
Satellite Data Critical for Improving Hurricane and Coastal Precipitation Forecasts
• Satellite microwave sounding data – provide hurricane thermal/moisture structure for improving intensity forecast (SSMIS/AMSU-A/MHS/ATMS)
• Satellite infrared sounding data – provide environmental thermal and moisture structure for track and precipitation forecast (HIRS/CrIS/AIRS/IASI)
• Ocean surface wind and temperature from satellite scatterometer and passive microwave imager – provide surface energy flux and surface vortex (ASCAT/AMSR2/GMI)
• GPSRO refractivity and bending angle – provide tropical cyclonegenesis information (COSMIC/GRAS)
• Geostationary sounder and imager – provide real-time monitoring and tracking of all severe weather events with a high temporal and spatial resolutions (e.g. GOES etc).
Statement of Problems in GSI
• NCEP GSI (3DVar data assimilation system) is being used by community for both global and regional model analysis but its interface is not designed well for different model configurations
• In 2011 and 2012 version of Hurricane Weather Research Forecast (HWRF) model, most of satellite data are not used in HWRF analysis process due to its model top setup
• Analyses show GSI quality controls for satellite water vapor
sounding data are also problematic (lots of bad data sneak into the analysis process).
• Bias correction schemes for satellite data developed for the global model applications have not been fully vetted for regional model applications
STAR Baseline HWRF Model and Data Assimilation System
HWRF Model:
• 2012 NCEP-Trunk version 934
• Three telescoping domains: Outer domain: 27km: 75x75o; Inner domain: 9km ~11x10o Inner-most domain: 3km inner-most nest ~6x6o
Revised Model Level and Top:
• Vertical levels: 61
• Model top: 0.5 hPa
Data Assimilation System:
• GFS 6 hour forecasts
• GSI (3DVAR)
• The Hurricane Weather Research and Forecasting (HWRF) Model dynamical core is designed based on the WRF model using NCEP Non-Hydrostatic Mesoscale Model (NMM) core with a movable high-resolution nested grid (telescopic) • Regional-Scale, Moving Nest, Ocean-Atmosphere Coupled Modeling System. Horizontal resolution: 27 km outer grid, 9 km inner grid, 42 vertical levels • Non-Hydrostaticsystem of equations formulated on a rotated latitude-longitude, Arakawa E-grid and a vertical, pressure hybrid (sigma_p-P) coordinate. • Advanced HWRF 3D Variational analysis that includes vortex relocation, correction to winds, MSLP, temperature and moisture in the hurricane region and adjustment to actual storm intensity. • Uses SAS convection scheme, GFS/GFDL surface, boundary layer physics, GFDL/GFS radiation and Ferrier Microphysical Scheme. • Ocean coupled modeling system (POM/HYCOM).
Data Sets Used for STAR HWRF Assimilation
Conventional Data: Radiosondes, aircraft reports (AIREP/PIREP, RECCO, MDCRS-ACARS, TAMDAR, AMDAR), Surface ship and buoy observations , Surface observations over land, Pibal winds,Wind profilers, VAD wind, Dropsondes
Baseline Satellite Instrument Data:
• AMSU-A (channel 5-14) from NOAA-18,19 and METOP-A, METOP-B • HIRS from NOAA-19,METOP-A, METOP-B • AIRS from EOS Aqua • IASI from METOP-A and METOP-B • ASCAT from METOP-A and METOP-B • GPSRO from GRAS, COSMIC • CrIS/ATMS from Suomi NPP ( to be added) • SSMIS from F18 ( to be added) • AMSR2 from GCOM-W1 ( to be added)
Number of Satellite Data Assimilated in HWRF-L61F
Cycle
2218Z
2306Z 2318Z
2406Z 2418Z
2506Z
2518Z
2606Z
2618Z 2718Z
2806Z
2818Z
2918Z
Dat
a N
umbe
r
0
50000
100000
150000
200000
250000
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29
AMSU-A (N19)
HIRS4 (N19)
AMSU-A (Metop-A)
AMSU-A (N18)
AIRS (Aqua)
HIRS4 (Metop-A)
0
5000
10000
15000
20000
25000
30000
35000
1 3 5 7 9 11 13 15 17 19 21 23 25 27 29 0
10000
20000
30000
40000
50000
60000
1 3 5 7 9 11 13 15 17 19 21 23 25 27 29
0 5000
10000 15000 20000 25000 30000 35000 40000
1 3 5 7 9 11 13 15 17 19 21 23 25 27 29
Cycle Cycle
Cycle
AMSU-A (N18) AMSU-A (N19)
AMSU-A (Metop-A)
Dat
a N
umbe
r
Dat
a N
umbe
r
Dat
a N
umbe
r
Number of Satellite Data Assimilated in HWRF-L61F
0 1000 2000 3000 4000 5000 6000 7000 8000 9000
1 3 5 7 9 11 13 15 17 19 21 23 25 27 29 0
2000 4000 6000 8000
10000 12000 14000 16000
1 3 5 7 9 11 13 15 17 19 21 23 25 27 29
0
20000
40000
60000
80000
100000
120000
140000
1 3 5 7 9 11 13 15 17 19 21 23 25 27 29
Cycle Cycle
Cycle
HIRS4 (Metop-A) HIRS4 (N19)
AIRS (Aqua)
Dat
a N
umbe
r
Dat
a N
umbe
r
Dat
a N
umbe
r
Number of Satellite Data Assimilated in HWRF-L61F
HWRF GFS
Multiple Forecasts of Tracks
L61C L61F
Multiple Forecasts of Tracks
Multiple Forecasts of Max. Wind Speed GFS HWRF
L61F
38
L61C
Multiple Forecasts of Min. Surf. Pres.
GFS HWRF
L61F L61C
Summary and Conclusions
• NOAA, METOP, DMSP polar satellites provide critical information on atmospheric vertical temperature structure for hurricane monitoring and forecasts
• Suomi NPP ATMS is very unique for resolving hurricane warm core features through spatial oversampling and additional channel
• GCOM-W1 AMSR2 are new instrument and can provide surface wind speed and SST for hurricane applications
• METOP and FY-3 unique instruments ((e.g. GPSRO, scattterometer, ozone) provide more information for NWP and other environmental applications
• A baseline version of HWRF and satellite instruments is defined for our hurricane and typhoon research and applications.
• In 2012 hurricane and typhoon season, Our baseline HWRF/DA system in general improves the intensity forecasts for most of study cases including Hurricane Sandy