Rainfall Mapping:
methods and accuracy
Lecture 4
February 5, 2009
Basics
• Precipitation? Types?
• Why precipitation observation?
• How to do?
– Rain gauge
– Remote sensing
1. In situ measurements
Rain gauge, direct measurement
Point measurement (1 m2)
High sampling frequency
Quality data
http://www.usatoday.com/weather/wtipgauge.htm
http://www.metoffice.com/education/secondary/images/es19_rain-gauge-illus.jpg
1 tip = 0.01 inch
If 10 tips in 1 minute, 0.1 inch total
(W 2 – W 1) / g
P=
Area
Problems of point measures
• Gauge itself: tipping, data logging, battery,…
• Accessibility,
• Rainfall spatial variability
Design high dense rain gauge to study the rainfall
spatial variability in a small area
6 pairs of double gauges
Quality Control by Double Gauges
(Our data collection started in May 2003)
Deep Well double gauges
All 6 pairs double gauges
Kriging interpolation of rainfall
Oct. 3, 2003
unit: mm
This is a complete weather system (CWS-1):
Standard:
Wind speed sensor
Wind direction sensor
Rain gauge
Temperature and humidity sensor
Optional:
Lightning rod
Solar radiation base
Barometric pressure sensor
Solar radiation sensor
2. Remote Sensing Precipitation
• Infrared
• Passive microwave
• Active microwave (radar)
2.1 Ground-based radar
• Single and multi-polarization
• Wavelength ranges: 3 cm (x-band), 5 cm (c-band),
10 cm (s-band)
• NEXRAD (WSR-88D): 10 cm (3 GHz)
• CASA-X band radar: 3 cm (10 GHz)
Radar hydrology
• What is it?
receiver
P0 = transmitted power [W]
Pr = backscattered power [W]
G = antenna gain (engineering term to enlarge signal return)
σ = Radar scattering of rain drop cross section [m2]
Rt = distance between radar and target [m]
λ = wavelength of radar [m]
• Backscatter reflectivity
N(D), number of rainfall drops
per unit volume at diameter
between D and D+dD,
D is the diameter if raindrop
• Precipitation rate (mm/h)
Z-R relationship
Next Generation Weather Radar
WSR-88D (NEXRAD)
First deployed
in 1988
Spectrum
Microwave (10cm)
Spatial
Resolution (km)
1, 2, 4
Temporal
Resolution
6-10 minutes
160 Radars
21 km
3km
Clear sky, 5 scans every 10 minutes
9 scans every 6 minutes
14 scans every 5 minutes
NEXRAD products
• NCDC level II and III
• RFC Stage I, II, III (MPE)
• Difference of the two products?
NEXRAD NCDC products
• Level II (base) data
– Reflectivity, mean radial velocity, and spectrum width
– 1 km x 1 degree
– 5 or 6 minutes in rain model and 10 minutes in clear sky
mode
• Level III products (total 41)
– DPA (4.7625 km HRAP grid, hourly, but every 5 or 6 minutes)
Product: http://lwf.ncdc.noaa.gov/oa/radar/radarproducts.html
Data viewer: http://www.ncdc.noaa.gov/oa/radar/jnx/
KEWX_DPA_20060120_2311
KEWX_DPA_20060117_0005
Use the level II reflectivity and convert to rainfall for ROIs and time period you need
NEXRAD RFC products
(4 km and hourly)
•
•
•
Stage I
- Hourly digital precipitation (HDP)
Stage II
- HDP merge with gauges
Stage III (or MPE)
- Mosaicked Stage II cover a RFC area
MPE since end of 2003 for the WGRFC.
Stage III archived at http://dipper.nws.noaa.gov/hdsb/data/nexrad/nexrad.html
Stage III real time at ftp://63.77.98.88/pub/
Stage III
in 13 RFCs
http://dipper.nws.noaa.gov/hdsb/data/nexrad/wgrfc_stageiii.html
Stage III/MPE process
• Compressed and multi-tarred binary file
• Hydrologic Rainfall Analysis Project (HRAP)
- Polar stereographic projection (earth-centered datum):
Radius: 6371.2 km, Longitude of 105° W, attitude of 50° N,
• Roughly 9,000 files (hourly) a year
Monthly
1
Daily
2
30
1
CPD-Hourly
30 x 24
3
Hourly
ASCII
30 x 24 =720
720
For Stage III
Reprojection
(720)
Define Projection
(720)
GIS (grid)
(720)
Each year = 12 x 720 = 8640,
It is impossible to manually finish this work.
Workflow of automated data conversion
Xie et al. 2005
Xie et al. 2005
CASA X-band radar
Additional slides about CASA
2.2 TRMM
•
•
•
The Tropical Rainfall Measuring Mission (TRMM) satellite is a joint project between
the United States (under the leadership of NASA's Goddard Space Flight Center) and
Japan (under the leadership of the National Space Development Agency, or NASDA).
The first spacecraft designed to monitor rain over the tropics, was successfully
launched from Tanegashima, Japan, on November 27, 1997, at 13:27pm Los Angeles
(California) time. TRMM travels between ± 35 degrees latitude in a low earth and low
inclination orbit.
TRMM is the first mission to measure precipitation quantitatively from space. It
includes the first precipitation radar (PR) to be flown in space, along with a 5-channel
SSM/I-like passive microwave imager (TMI), an AVHRR-like visible-infrared
radiometer (VIRS), a lightning sensor and a cloud sensor. The PR, TMI , and the VIRS
are designed to obtain rainfall and other relevant information (e.g. rain type, height of
the bright band, cloud type, cloud top height) individually.
TRMM is giving scientists a better understanding of what parts of a hurricane produce
rainfall and why, as well as possibly resolve the question of how much latent heat or
"fuel" hurricanes of differing strengths release into the atmosphere and whether they
affect overall weather circulation.
TRMM PR
• 13.796 and 13.802 GHz with horizontal polarization
• Measures the strength of backscatter, similar to NEXRAD
and CASA.
• TRMM 2A25, vertical rainfall rate profile for each radar
beam
• 3-D distribution of rainfall at 4 km x 4 km x 250m
• Estimated near-surface rainfall rate and average rainfall
rate between 2 and 4 km for each beam position.
Example of horizontal and vertical cross sections of rainfall rate measured
by TRMM PR for Typhoon #8 on 2 August 2000
TRMM Microwave Imager (TMI)
•
•
•
•
•
TMI has 10.7, 19.4, 21.3, 37, 85.5 GHz at altitude of 350 km, is based on
Special Sensor Microwave/Imager (SSM/I), except 10.7 channel of TMI
designed to provide a more-linear response for high rainfall rates common
in tropical rainfall.
Dual-polarized (except 21.3)
Products (TRMM 2A12)
– 10.7 GHz Sea surface temperature (clouds are nearly transparent at
10.7 GHz)
– 10.7 GHz 10 m wind speed
– 37 GHz 10 m wind speed
– 21.3 GHz columnar water vapor
– Columnar cloud water
– 19-37 GHz rain rate
Resolution of 0.25 degree or 25 km
Daily (ascending and descending)
How measures rainfall with
Microwaves
• Planck’s equation for brightness temperature
• Absorption-based: water surface only emit half of the microwave
energy, so Tb is only half of the real T. raindrops, however, appear
warm and offer a contrast against “cold” water surfaces. the more
drops, the warmer. (<= 37 GHz)
• Scattering-based: land surface appear ~90% of the real T, a little
contrast to “warm” raindrops, though certain properties of rainfall
still can be inferred. The 85.5 GHz are strongly scattered by ice
present in many raining clouds. This reduces the T offers a contrast
against the warm land background.
VIRS of TRMM
• 0.63, 1.6, 3.75, 10.80 and 12 microns, similar to
AVHRR
• Cloud coverage, type, top temperatures, and
precipitation at a horizontal resolution of 2.1 km
(nadir)
• Only level 1 calibrated radiances data available
now
TRMM Orbit Viewer
Software: ftp://disc2.nascom.nasa.gov/software/trmm_software/Orbit_Viewer/README.html
Data: http://disc.gsfc.nasa.gov/data/datapool/TRMM_DP/01_Data_Products/01_Orbital/index.html
Mission Index: ftp://ftp-tsdis.gsfc.nasa.gov/pub/TSDISorbitViewer/mission_index_gz/
TRMM climate products (level 3)
• 3A25 PR (monthly), 0.5 x 0.5 degree
• 3A12 TMI (Monthly), 5 x 5 degree
• 3A11 emission (monthly), 5 x 5 degree on ocean
only
• 3B31 combined PR/TMI (monthly),
• 3B42 TMI/GPI
• 3B43 3B42/gauges
TRMM Online Visualization and
Analysis System (TOVAS)
• http://lake.nascom.nasa.gov/tovas/
• TRMM-adjusted merged-infrared precipitation (3B42)
• The 3B42 dataset uses the TMI 2A12 rain estimates to
adjust high temporal resolution (3-hourly or higher) IR rain
rates over daily gridded 1x1 degree lat/lon boxes.
– 0.25 x 0.25 degree, 3-hours
• 3B43 is by combining the 3-hourly merged high-quality/IR
estimates (3B-42) with the monthly accumulated Climate
Assessment and Monitoring System (CAMS) or Global
Precipitation Climatology Centre (GPCC) rain gauge
analysis (3A-45).
– 0.25 x 0.25 degree, monthly
2.3
http://www.oso.noaa.gov/goesstatus/
GOES
PERSIANN
• http://www.chrs.web.uci.edu/research/satellite_precipitatio
n/activities00.html
• Precipitation Estimation from Remotely Sensed
Information using Artificial Neural Networks (PERSIANN)
• Based on GOES 15 minutes IR composites, combined
with TRMM 2A12 and others
• 30 minutes 4 km, then aggregated to 0.25° (25km) 6-hour
and others.
GOES precipitation index (GPI)
• Precipitation (mm) = 3 (mm/h) x Fc x t
– Fc is the mean fractional coverage of cloud colder than 235 k
(30N-30S) or 220k (30-50) in 1° x 1° up to 2.5° x 2.5° box
– T is the number of hours over the Fc was compiled
– Cloud top brightness temperature
• Daily product (1° x 1° )
• Data can be downloaded from
ftp://ftp.ncep.noaa.gov/pub/precip/gpi/.
Know detail about this algorithm, please read Arkin and Meisner (1987)
paper through webCT. (otherwise, this paper is not required to read)
3. What is the accuracy?
• Rain gauge-based rainfall accuracy
– Very good accuracy for the point
– Might experience different types of errors
• Remotely sensed rainfall accuracy
– Usually use raingauge rainfall as a ground truth
– Two ways to see remote sensing rainfall accuracy
• Rainfall events detection (POD)
• Rainfall amount (R2, bias, cv, mean relative difference)
–
–
–
–
–
–
5-6 minutes,
Hours,
Events,
Month,
Season,
Year
Validation Variables
Probability of precipitation detection (POD)
Pr  P( Rr  0 | Rr  0 or Rg  0) 
R _ Count
R _ Count  G _ Count  Pairs _ R _ G
Root Mean of Squared Difference (RMSD)
2
n
RMSD r  g  P( Rr  0 & Rg  0) 
 ( R (i)  R
i 1
r
g
(n  1)
Mean Relative Difference (Rd)
Rd  P( Rr  0 & Rg  0) 
RMSD
CM g
Correlation Coefficient (R)
Coefficient of Variance (CV)
(i ))
Sevilleta, New Mexico (1995-2001)
Rainfall events detection (POD)
Radar rainfall
hours
Gauge rainfall
hours
Trunc.
error
NonMonsoon
1143
4181
57-72%
Monsoon
3900
3540
NO
Xie et al. 2006
Stage III (1995-2001) in New Mexico
Monsoon
Non-Monsoon
Xie et al. 2006
Texas Hill Country, 2001 and 2004
Wang et al. 2008
Comparison: 2001 (Stage3) & 2004 (MPE)
Table 1. Statistic comparison between Stage III /MPE and gauge rainfall data in 2001/2004
All GBRA data in 2001
Gauge
All data
Stage 3
All GBRA data in 2004
Gauge
MPE
Rainfall Count (hrs)
8812
6769
19564
30525
Total Rainfall (mm)
17507
20266
50730
52989
1.9
2.9
2.6
1.7
Mean (mm)
Total Count (hrs)
34352
It indicates that Stage III11810
truncates the small
rainfall
events
but much overestimates
the rest 0.57
of rainfall0.89
POD
0.75
0.57
events.
The problem is fixed
in MPE.
Gauge_Radar Pairs
3771
15737
Total Rainfall (mm)
Gauge_Radar
pairs
13565
15124
48753
44803
Mean (mm)
3.6
4.0
3.1
2.8
RMSD (mm)
5.1 (143%)
2.9 (94%)
11.5%
-8.1%
0.68
0.79
Estimation Bias
R
R2 of MPE vs Gauge in 2004
Uniform events
CV<=0.8
Non-uniform events
CV>0.8
Extremely uniform and non-uniform events
40
80
y = 0.33x + 0.23
y = 0.83x + 0.32
R2 = 0.92
2
R = 0.30
30
MPE
MPE
60
40
20
20
10
0
0
0
A
20
40
60
Gauge (mm/hour)
CV<0.1
0
80
B
10
20
Gauge (mm/hour)
CV>1.0
30
40
Monthly and Accumulation of
Precipitation in 2004
EB=-7.2
EB=-22.5
Monthly accumulation of concurrent non-uniform gauge and
radar MPE precipitation in 2004
45000
Acc. P.(mm)
40000
35000
15000
3000
12500
2500
10000
30000
25000
7500
20000
5000
15000
10000
Acc. P.(mm)
G_month
MPE_month
G_Acc
MPE_Acc
Monthly P. (mm)
50000
2500
1200
G_month
MPE_month
G_Acc
MPE_Acc
2000
1000
800
1500
600
1000
400
500
200
5000
0
0
1
A
2
3
4
5
6
7
8
Month
Uniform events
9
0
10 11 12
0
1
B
2
3
4
5
6
7
8
9
10 11 12
Month
Non-uniform events
Monthly P. (mm)
Monthly accumulation of concurrent uniform gauge and radar
MPE precipitation in 2004
Monthly and Accumulation of
Precipitation in 2001
EB=19.5
EB=-23.5
Monthly accumulation of concurrent non-uniform
gauge and radar stage III precipitation in 2001
Acc. P. (mm)
20000
15000
5000
3000
4000
2500
3000
10000
2000
5000
1000
0
2
3
4
5
6
7
8
Uniform events
1000
800
1500
600
1000
400
500
200
0
9 10 11 12
Month
1200
G_Month
S_month
G_Acc
S_Acc
2000
0
1
A
Acc. P. (mm)
G_Month
S_month
G_Acc
S_Acc
Monthly P. (mm)
25000
0
1
B
2
3
4
5
6
7
8
9
10 11 12
Month
Non-uniform events
Monthly P. (mm)
Monthly accumulation of concurrent uniform
gauge and radar stage III precipitation in 2001
NEXRAD VS TRMM
August
APGI is 3B42
Merged is 3B43
West African
Nicholson et al., 2003
5-month season