improvement of short-term severe weather forecasting using high-resolution modis satellite data
DESCRIPTION
Study of MODIS Retrieved Total Precipitable Water (TPW) Data and their Impact on Severe Weather Simulations. Improvement of Short-term Severe Weather Forecasting Using high-resolution MODIS Satellite Data. S.-H. Chen 1 , A. Chen 1 , J. Haase 2 , Z. Zhao 1 , and F. Vandenberghe 3. - PowerPoint PPT PresentationTRANSCRIPT
Improvement of Short-term Severe Weather
Forecasting Using high-resolution MODIS Satellite
Data
Study of MODIS Retrieved Total Precipitable Water (TPW)
Data and their Impact on Severe Weather Simulations
S.-H. Chen1, A. Chen1, J. Haase2, Z. Zhao1, and F. Vandenberghe3
1 Department of Land, Air, and Water Resources, University of California, Davis, CA2 Department of Earth and Atmospheric Sciences, Purdue University, W. Lafayette, IN 3 National Center for Atmospheric Research, Boulder, CO
o Introduction
o Observations
o Experiments and Preliminary
Results
o Summary
Outline
MODIS Data
Moderate Resolution Imaging
Spectroradiometer
Aboard Terra (2000) and Aqua (2002)
36 spectral bands: 0.405-14.387 μm
Resolutions: 250m, 500m, 1000m
Sun-synchronous polar orbit
Mean altitude : 705 km (equator)
Width of swath : 2300 km (Terra), 2330 m
(Aqua)
Introduction
Retrieved MODIS Total Precipitalbe Water (TPW) Images
MODIS InfraRed (IR) TPW (cm). This image shows a 50%
retrieval rate.
MODIS near InfraRed (nIR) TPW (cm).
This image shows an 85% retrieval rate.
Introduction
Observations
00Z 01/04/04
MODIS swath & Radiosonde Stations
After CorrectionBefore Correction
y = 0.1606x - 0.7725
-20
-10
0
10
20
0 10 20 30 40 50 60
MODIS nIR TPW (mm)
MO
DIS
nIR
- R
adio
son
de
TP
W (
mm
)
RMS ~ 4 mm RMS ~ 2.5 mm
y = -5E-05x + 9E-06
-20
-10
0
10
20
0 10 20 30 40 50 60
MODIS nIR TPW (mm)
MO
DIS
nIR
- R
adio
son
de
TP
W (
mm
)
Observations
MODIS nIR TPW vs. Radiosonde TPW
MODIS – Radiosonde vs. Latitude
IRnIR
-20
-10
0
10
20
-50 -40 -30 -20 -10 0
latitude
nIR
- R
adio
son
de
TP
W (
mm
)
-30
-20
-10
0
10
20
30
-50 -40 -30 -20 -10 0
Latitude
IR-R
adis
onde
TP
W (
mm
)
Radiosonde Stations
Hail and Strong Wind reports(June 1 and 2 2004)
Severe thunderstorm activity on June 1 and 2, 2004 in Oklahoma, Texas, Arkansas and Louisiana. (Curtsey Storm Prediction Center NOAA)
experiments
Model Configuration
Weather Research and Forecast Model
18 UTC 1 June – 00 UTC 3 June 2004
Global Reanalysis: AVN 1o x 1o
Domain 1 - 30 km
2 - 10 km
Physic: Purdue microphysics
New Kain-Fritsch
RRTM long wave
Dudhia short wave
YSU PBL
(Initial Time: 1800 UTC 1 June 2004)
experiments
Hurricane Isidore(1800 UTC 17 – 0000 UTC 20 Sep 2002)
experiments
Global Reanalysis: AVN 1o x 1o
Domain 1 - 30 km
2 - 10 km
3 - 3.3 km
Physic: Purdue microphysics
New Kain-Fritsch
RRTM long wave
Dudhia short wave
YSU PBL
Model Configuration(Initial Time: 1800 UTC 17 Sep 2002)
experiments
Weather Research and Forecast Model
18 UTC Sep 17 – 00 UTC Sep 20, 2002
Experiments
Assimilated data Error
CNTL None
MOD Original MODIS nIR TPW
4 mm
MODC Corrected MODIS nIR TPW
2.5 mm
After CorrectionBefore Correction
y = 0.1606x - 0.7725
-20
-10
0
10
20
0 10 20 30 40 50 60
MODIS nIR TPW (mm)
MO
DIS
nIR
- R
adio
son
de
TP
W (
mm
)
RMS ~ 4 mm RMS ~ 2.5 mm
y = -5E-05x + 9E-06
-20
-10
0
10
20
0 10 20 30 40 50 60
MODIS nIR TPW (mm)
MO
DIS
nIR
- R
adio
son
de
TP
W (
mm
)
Rainfall (0 - 6h simulation)Isidore
Observation CNTL
MOD MODC
Rainfall (6 - 12h simulation)Isidore
Observation CNTL
MOD MODC
Rainfall (12 – 18h simulation)Isidore
Observation CNTL
MOD MODC
Isidore
IMOD IMODC
TPW Increment and 850 mb Wind
Maximum CAPE
ICNTL IMOD IMODC
965
975
985
995
1005
0 6 12 18 24 30 36 42 48 54Time (hr)
Sea
Lev
el P
ress
ure
(h
Pa)
OBS
ICNTL
IMOD
IMODC
Results - Isidore
Minimum Sea Level Pressure Maximum 10-m Wind Speed
10
20
30
40
50
0 6 12 18 24 30 36 42 48 54
Time (hr)
Max
imum
10-
m w
ind
(m s-1
)
OBS
ICNTL
IMOD
IMODC
Radar Reflectivity - Isidore
Radar Image (HRD,NOAA) ICNTL
IMOD IMODC
(2100 UTC 19 Sep 2002)
2-km Vertical Velocity (24h)
ICNTL IMOD
2-km Vertical Velocity (48h)
ICNTL IMOD
Summary o The retrieved MODIS TPW might have biases and the
RMS error is about 2-4 mm, which is comparable with that from
global reanalysis over land.
o The assimilation of MODIS TPW may not be able to
improve “now (i.e., at data assimilation time)” nowcasting
but may have a potential to improve “future (e.g., 12h later)” nowcasting!
o Preliminary results show that the assimilation of
MODIS TPW has slightly positive impact on sever weather
simulations (rainfall, storm intensity, etc.).