Validation of HydroEstimator algorithm

1
Validation of Hydro-Estimator algorithm

• Nazario D. Ramirez
• Mayaguez, PR
• March 5, 2007

2
Objectives

• To validate and enhance high resolution
  multi-sensor (IRMW) algorithms over Puerto Rico.
  
• Hydro-estimator
• Self-Calibrating Multivariate Precipitation
  Retrieval
• Perform a radar validation.
• Improve the performance of HE and SCaMPR

3
Satellite retrieval rainfall algorithms

• Estimation algorithms
• Visible/Infrared (IR)-Based Algorithms
• Microwave (MW)-Based Algorithms
• Hydro-Estimator is IR-base algorithm
• SCaMPR is IRMW Combination Algorithms

4
Hydro-Estimator Basics

• Rainfall estimation techniques based on satellite
  cloud-top temperatures have existed for gt30 years
• The Auto-Estimator was the first-generation
  automated technique at NESDIS the
  Hydro-Estimator (HE) replaced it in 2002.
• AE and HE estimate rainfall rate based on the
  cloud-top temperature, (GOES channel 4 10.7-µm)
  
• Colder clouds are raining heavily
• Warmer clouds are raining lightly or not at all.

5
Rainfall rate and brightness temperature

• Vicente et al. 1995.
• 6800 observations of collected IR brightness
  temperature and radar rainfall rates from
  convective cores of mesoscale convective systems
  (March-June 1995).
• RR rainfall rate mm/h
• T10.7 in Kelvin

6
Illustration of the IR signal from different
rainfall intensities
Tb200 K
Tb212 K
Tb224 K
Tb230 K
200
250
290
T (K)
7
Exceptions to the Rule...
Cirrus Tb205 K
Cumulonimbus Tb200 K
Nimbostratus Tb240 K
290
200
250
T (K)
8
Analysis at each pixel
T_min
Pixel of interest
o

101 pixel
101 pixel
9
Rain rate calculation for convective or
non-convective core
If zlt0 RR0 If zgt0,
10
Hydro-Estimator Basics

• Satellite imagery alone does not contain all the
  information needed for evaluating rainfall.
  Numerous processes occur below the clouds,
  including
• Evaporation of raindrops
• Enhancement or reduction of rainfall by
  terrain-induced upslope / downslope
• Numerical Weather Prediction (NWP) model forecast
  fields are used to derive correction factors
• Precipitable water enhance rain rates in high-PW
  areas reduce in low-PW areas
• Relative humidity reduce rain rates in dry
  (low-RH) areas
• Convective equilibrium level temperature regions
  with values above 213 K have their rain rates
  enhanced
• 850-hPa winds interfaced with digital topography
  enhance rain rates in upslope regions and reduce
  them in downslope regions

11
Rain rate as a function of brightness temperature
and precipitable water in the Hydro-Estimator
Convective Core rainfall
12
Non-core rainfall
13
Reduction in rain rate as a function of relative
humidity in the Hydro-Estimator
14
Preparation for validation

• Since satellite estimates of rainfall provide
  instantaneous rates rather than accumulation over
  time, radar-based rainfall rates must be
  considered to be more appropriate calibration
  data set than the rain gauge data.

15
NEXRAD NEXt Generation RADar

• NEXRAD is used to warn people of the United
  States and Puerto Rico about weather.
• There are 158 operational NEXRAD radar systems
  deployed throughout the United States and at
  selected overseas locations.
• The maximum range of the NEXRAD radar is 250
  nautical miles.

16
NEXRAD Location Cayey P.R.
Latitude 18.118 N Longitude 66.079 W Radar
height 2907 ft Time per scans 6 to 10 minutes
17
Computer program

• Understand Level II and Level III data sets.
• Develop an algorithms that convert BINARY NEXRAD
  datasets into a MATLAB format.
• Compare Level II and Level III Reflectivity
  products read in NOAA Java products, with MATLAB
  products

18
Reflectivity level II
19
Reflectivity level III
20
Rain Gauges
21
Rain Gauge Stations
22
Accumulated Reflectivity vs Accumulated Rainfall
(18 Rain Gauges)
October 4th to 7th, 2005
23
Estimated vs Observed Reflectivity
for a562.56, b 1.7474
24
Observed vs estimated rainfall
for a562.56, b 1.7474
25
Accumulated Reflectivity of 18 Stations near
NEXRAD Radar Station and Accumulated Rainfall on
18 Rain Gauges.
Do not have any Radar Observations
January 1st to 31st, 2002
26
Seasonal Correction

• Two equations will be derived one for dry and one
  for wet season.
• Two sets of coefficients and for i1,2 and
  represents the wet and dry periods, respectively.

27
Earth curvature correction