Synergizing High-Resolution Satellite Data and Radar Data to Assess Trade Wind Cloud Precipitation

1
Synergizing High-Resolution Satellite Data and
Radar Data to Assess Trade Wind Cloud
Precipitation

• Eric Snodgrass
• Dept. Atmospheric Sciences, UIUC

2
Acknowledgements
Larry Di Girolamo Bob Rauber Guangyu
Zhao Lusheng Liang UIUC RICO Group NSF ATM
03-46172
3
Characteristics of the tropical atmosphere
The Hadley Cell in tropical latitudes
Increasing sea-surface temperature
4
(No Transcript)
5
The Hadley Cell in tropical latitudes
Trade inversion
Increasing sea-surface temperature
Recreated from Kerry Emmanuels American
Scientist article
6
The Hadley Cell in tropical latitudes
Trade-wind inversion
ITCZ
Sub-cloud layer
Increasing Sea Surface Temperatures
Trade wind clouds role - Supply and modify
moisture content in boundary layer as the trade
winds converge to feed the ITCZ.
Borrowed from Kerry Emmanuels American Scientist
article
7
Do these clouds precipitate?
and how much?
Courtesy of Bjorn Stevens
8
Tropical ocean precipitation measurement
Method

• Thermal IR Brightness Temperature
• GOES, MODIS, AVHRR
• Passive Microwave
• SSM/I
• Active Microwave
• Spaceborne Precip Radars
• TRMM

9
Project Goal The objective of RICO in the
broadest sense is to characterize and understand
the properties of trade wind cumulus at all
scales, with particular emphasis on determining
the importance of precipitation.
http//www.lib.utexas.edu/maps/americas/camericaca
ribbean.jpg
10
typical trade wind clouds
Modes of Organization
Wind-parallel bands
Outflow bands
Clusters
11
typical trade wind cumulus
Top of boundary layer
1000m
500m
700m
Ocean Surface
Wind-parallel bands
Outflow bands
Clusters
12
S-POLKa
Location Barbuda Wavelength 10cm (S-Band) Dual
Polarization Range resolution 145km Range gate
width 150m Beam width .833 Source of
Measurement for Precipitation
S-band dish
Ka-band dish
Donkey
Make shift toilet
13
Multi-angle Imaging SpectroRadiometer Attributes
400 km swath 443, 550, 670, 865 nm channels
275 m 1.1 km sampling 7 minutes to view the
same scene from all 9 cameras
14
Assess trade-wind cloud precipitation through the
synergy of high resolution satellite data and
S-band radar data.
MISR RGB
S-POLKa 0.5 Scan
15
ASTER (15m)
Reflectivity on ASTER grid
MISR (275m)
Reflectivity on MISR grid
16
Collocating the datasets
Find the path of the beam along the Earths
surface
Assign a latitude and longitude to the center of
each radar pixel
Shift the location of each pixel according to
time differences and background flow
Use a nearest-neighbor algorithm to assign each
MISR pixel a reflectivity value
17
(No Transcript)
18
2.1km
2.5km
LCL
18km ? same width as MISR pixel 50km ? 2.6 times
as wide 100km ? 5.3 times as wide 150km ? 8
times as wide Range resolution is always
smaller!
150km
130km
110km
90km
70km
50km
30km
10km
5km
19
Collocating the datasets
Find the path of the beam along the Earths
surface
Assign a latitude and longitude to the center of
each radar pixel
Shift the location of each radar pixel according
to time difference with MISR and the background
flow
Use a nearest-neighbor algorithm to assign each
MISR pixel a reflectivity value
20
?T(tR - tM2)
21
Example MISR time is later than radar pixel time
N
Wind dir. 45 Wind speed 12 ms-1
?Lat A / 111.12km
?Long B / 111.12kmCOS( original lat )
?Long
E
W
Original Radar Pixel (lat, long)
A 12?TSIN(270-45)
?Lat
B 12?TCOS(270-45)
S
Shift Radar Pixel (lat, long)
22
Collocating the datasets
Find the path of the beam along the Earths
surface
Assign a latitude and longitude to the center of
each radar pixel
Shift the location of each pixel according to
time differences and background flow
Use a nearest-neighbor algorithm to assign each
MISR pixel a reflectivity value
23
Nearest neighbor technique
24
(No Transcript)
25
(No Transcript)
26
(No Transcript)
27
(No Transcript)
28
(No Transcript)
29
Pre-processing
Radial Velocity
dBZ
30
(No Transcript)
31
ZDR Filter
32
Pre-processing
Radial Velocity
dBZ
33
Long line of birds
birds
34
Filtering Noise and Islands
Bad beams
Noise
Islands
Noise power return (DM) lt -115.6dB Island
removed manually with soloii
35
Rayleigh scattering off particles
http//ceos.cnes.fr8100/cdrom-98/ceos1/science/dg
/fig18.gif
Rayleigh Scattering for 10cm radars occurs for
particles smaller than 2cm (which includes all
rain drops)
36
Clear Air Echoes
The mechanism of scattering, Bragg scattering,
depends on diffraction of electromagnetic waves
caused by perturbations in the refractive index
on a scale of half the wavelength of the radar
Coherent wave reflection caused by objects spaced
at half the wavelength of impinging wave
Water wave
Diffraction pattern caused by single object
37
(No Transcript)
38
Radar Reflectivity (dBZ)
Barbuda
MISR NIR Reflectance
39
Reiterative slide
Courtesy of Bjorn Stevens
40
Data

• 12 overlapping scenes from Nov. 28th through Jan.
  24th
• Average surface wind was from 73 at 10.5ms-1
• Average LCL 773m (930mb)
• Max/Min time difference 150/0s

41
Characteristics of trade wind clouds from MISR
42
(No Transcript)
43
(No Transcript)
44
Accepted
Cloudy
45
Clear
Majority of the cloudy pixels have very weak
reflectivity suggesting that most are not
precipitating
Cloudy
46
(No Transcript)
47
(No Transcript)
48
(No Transcript)
49
Outflow Dominated

50
Cluster Dominated

51
Wind Parallel Dominated

52
Z260R1.7
(7dBZ)
(24dBZ)
(41dBZ)
53
Preliminary Values
Average precipitation rate for this region is
0.75mmd-1
LHF to atmos. from rain in this region is
22.77Wm-2 Chou et al (1995),found the ocean
surface LHF during February over this region to
be between 160-200Wm-2. Therefore, these clouds
are between 11-15 efficient at returning
evaporated water to the ocean through
precipitation.
54
Conclusions
Killing Frigate birds is my new favorite pastime
At 5dBZ Rayleigh scattering dominates return
signal
7.5 of cloudy pixels had rainfall rates to
0.1mmhr-1 (7dBZ)
2 of cloudy pixels rainfall rates 1mmhr-1
(24dBZ)
Average precipitation rate for this region is
0.75mmd-1
LHF to atmos. from rain in this region is
22.77Wm-2 (11-15 efficient at returning water
to the ocean surface)
55
Future work

• Make RICO Z-R relationship
• Processing the entire data set for average daily
  precipitation rate
• Develop metrics from MISR for global tropical
  application

56
Best Jerk Chicken in Antigua
57
IR Brightness Temperature Technique
PROBLEMS Indirect BT1 BT2 SST 4km to 2.5
x 2.5 horiz. res. Two similar clouds one may
rain and the other may not
BT2
Ocean Surface
4km
GPI 3f?t f fraction of area colder than
threshold temp ?t time over which f
applies Use a look up table to relate GPI to
rainfall depth per area
58
Active and Passive Microwave and Precipitation
Radars
59
Putting the radar on the north pole
60
Finding the lat and long of each pixel
61
Difficult targets for ground-based precipitation
radars
Shallow (have stats on cloud heights
Guangyu) Small (stats on cloud area Guangyu) Weak
reflectivity REMOVE this slide put the info at
the end
62
(No Transcript)
63
5cm
1
10cm
2
64
1
2
3
65
1
1
2
3
66
1
1
1
2
3
4
67
1
1
1
2
2
1
3
4
Constructive interference
68
1
1
2
1
2
3
1
2
4
Constructive interference
5
69
(No Transcript)
70
(No Transcript)
71
(No Transcript)
72
(No Transcript)
73
(No Transcript)