The Validation Network (VN) prototype for the Global Precipitation Measurement (GPM) Mission compares data from the Tropical Rainfall Measuring Mission (TRMM) satellite Precipitation Radar (PR) to similar measurements from U.S. and international operational weather radars. This prototype is a major component of the GPM Ground Validation System (GVS). The VN provides a means for the precipitation measurement community to identify and resolve significant discrepancies between the ground radar (GR) observations and similar satellite observations. The VN prototype is based on research results and computer code described by Anagnostou et al. (2001), Bolen and Chandrasekar (2000), and Liao et al. (2001), and has previously been described by Morris, et al. (2007). Morris and Schwaller (2009) describe the PR-GR volume-matching algorithm used to create the VN match-up data set used for the comparisons. This paper describes software tools that have been developed for visualization and statistical analysis of the original and volume matched PR and GR data

Morris, Kenneth R.

Schwaller, Mathew

NASA Technical Reports Server

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Remote Sensing: Global Vision for Local Action 
On behalf of the IEEE Geoscience and Remote Sensing Society and the IGARSS 2010 Organizing Committee, 
we are pleased to invite you to Honolulu for IGARSS 2010. We are thrilled to be returning to Hawaii to host 
IGARSS on its 30th anniversary! In the true spirit of an international event, we will continue our tradition of 
gathering world-class scientists, engineers, and educators engaged in the fields of geosciences and remote 
sensing from around the world. We anticipate well over one thousand participants to enjoy a week of technical 
sessions, tutorials, exhibits and social activities. 
For this 30th anniversary IGARSS we will celebrate our accomplishments over three decades of leadership in 
remote sensing instrumentation, techniques, and applications development. But perhaps more importantly we will 
look ahead to the future of our field with some fresh approaches and perspectives through our conference theme: 
Remote Sensing: Global Vision for Local Action. One such activity will be embodied in our plenary session, which 
will focus on the emerging field of We hope this plenary session, along with special 
tutorials and technical sessions, will inspire and excite our community for what is possible in the coming decade. 
We look forward to seeing you in Honolulu in July 201 O! 
Karen St.Germain and Paul Smits 
General Co-Chairs 
Abstract Submission 
Participation in IGARSS is open to all individuals interested in or working in the fields of geoscience and remote 
sensing. Abstracts received by the deadline will be considered for program placement under the standard peer 
review process. Late abstracts cannot be accepted due to the large number of submissions and short review 
schedule. The IEEE IGARSS 2010 Technical Program Committee will organize all accepted abstracts into either 
oral or interactive poster sessions based upon their potential contribution to the symposium and the composition 
of high-quality sessions. Session Co-chairs will be appointed as early as possible to help TPC setting the highest 
quality for oral and interactive sessions. Only accepted papers that are registered and presented at the 
symposium in Honolulu will be published in the symposium proceedings and be assigned an IEEE GRSS 
publication reference. The list of specialty projects and themes associated with community remote sensing will be 
soon available on the symposium website. 
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https://ntrs.nasa.gov/search.jsp?R=20100003126 2019-08-30T08:41:29+00:00Z
DATA VISUALIZATION AND ANALYSIS TOOLS FOR THE 
GLOBAL PRECIPITATION MEASUREMENT (GPM) VALIDATION NETWORK 
K. Robert Morris 
SAIC i NASA I Goddard Space Flight Center 
Mathew R. Schwaller ~ NASAiGSFC 
The Validation Network (VN) prototype for the Global Precipitation Measurement (GPM) mISSIOn 
compares data from the Tropical Rainfall Measuring Mission (TRMM) satellite Precipitation Radar (PR) 
to similar measurements from U.S. and international operational weather radars. This prototype is a 
major component of the GPM Ground Validation System (GVS). The VN provides a means for the 
precipitation measurement community to identify and resolve significant discrepancies between the 
ground radar (GR) observations and similar satellite observations. The VN prototype is based on research 
results and computer code described by Anagnostou et al. (2001), Bolen and Chandrasekar (2000), and 
Liao et al. (2001), and has previously been described by Morris, et al. (2007). Morris and Schwaller 
(2009) describe the PR-GR volume-matching algorithm used to create the VN match-up data set used for 
the comparisons. This paper describes software tools that have been developed for visualization and 
statistical analysis of the original and volume matched PR and GR data. 
Table 1. Mean difference between PR and original 
(GR) and frequency-corrected (GRKu) WSR-88D 
reflectivity for stratiform rain volumes above the 
bright band. Negative values indicate WSR-88D 
higher than TRMM PRo 
Radar 
10 
KJAX 
KLCH 
KMLB 
KMOB 
KTLH 
PR-GRKu 
Mean 
Difference 
0.03 
-0.76 
0.97 
2.63 
-0.72 
-1.34 
0.71 
1.00 
-1.62 
PR-GR PR Mean 
Mean Reflectivity Total 
Difference (dBZ) Samples 
dBZ' 
-0.49 2304 
-1.42 23.54 9071 
0.43 23.78 11910 
2.19 24.19 6871 
-1.33 22.95 4509 
-2.06 23.54 4071 
0.26 22.52 2787 
0.50 23.37 4772 
-2.34 23.37 3280 
The core VN dataset consists of volume-matched 
TRMM PR and quality-controlled, ground-based 
WSR-88D (Weather Surveillance Radar ~ 1988 
Doppler, or WSR-88D) radar reflectivity, for 21 
sites in the southeastern U.S. PR data include radar 
rcflectivity (both raw and attenuation corrected), 
near-surface rain rate, and other variables. Only 
reflectivity is analyzed for the GR. For cases when 
a PR/GR overlap event occurs with a significant 
(minimum ~ 1600 km2) total area of precipitation 
echoes within 100 km of the GR, the geometry-
matching component of the VN software suite performs a spatial match-up of the PR and GR data to 
common 3-D volumes by calculating PR and GR averages at the geometric intersection of the PR rays 
with the individual GR radar elevation sweeps. The along-ray PR data are averaged only in the vertical, 
between the top and bottom height of each GR elevation sweep intersected. The GR data are averaged 
only in the horizontal within the individual elevation sweep surfaees, over an area centered on each 
intersected PR ray. Match-up data are restricted to within a 100 km radius of the GR site, where the GR 
values have sufficient vertical resolution and GR overshooting of precipitation echoes is minimal. 
Three primary software tools have been written for analysis and visualization of the volume-matched PR 
and OR data: (l) bulk statistical analysis tool; (2) case study statistical analysis and display tool, and 3) 
the vertical cross section analysis tool. The bulk statistical analysis tool processes data for the entire VN 
match-up data set to produce PR-OR mean differences and related statistics for categories consisting of 
permutations of: OR site, date/time of the overpass, sample height (13 layers, 1.5 km deep, from 1.5 to 
19.5 km), rain type (convective, stratiform, other), proximity to the bright band (above, below, within), 
percent of volume above reflectivity thresholds, and range category from the OR (0-50 km, 50-100 km). 
Figure 1. PPI Animation Display of the VN Statistical Analysis and Display Tool, showing volume-matched PR 
(left) and GR (right) data. 
These split-out data are stored in a database table. Queries to the database allow the statistical data to be 
combined and recategorized in a flexible manner. For example, Table 1 presents the PR-OR mean 
difference in dBZ for individual VN WSR-88D radars, for both the original S-band OR reflectivity (OR) 
and the frequency-correeted OR reflectivity (ORKu), for all samples categorized as stratiform rain type, 
above the bright band, and where fewer than five percent of PR and OR bins were rejected as "below 
threshold" in the sample averages. In the same manner, the bulk data can be split out by site and date to 
produce time series of site-specific PR-OR mean reflectivity, or to analyze the results by region or season. 
The two primary visualization tools are the statistical analysis tool and the vertical cross section tool, 
which allow display and analysis of VN match-up data for individual site overpass events. For spatial 
orientation, the statistical analysis tool can display PPls of volume-matched data (Fig. 1) as an animation 
loop progressing from low to high elevation sweeps. The statistical analysis tool vertically stratifies the 
data to produce tabular and graphical displays, including vertical profiles of PR and OR reflectivity from 
data averaged over the constant height levels, and histograms of PR and OR for 
llHHI.i,,-e,U data stratified proximity to the bright band (Fig. scatter plots of PR vs. OR reflectivity 
Figure 2. Vertical profile (left) and histogram of volume-matched PR (green) and OR (red) reflectivity, by rain 
type. Only the histogram for the above-bright-band category is shown in this example. Example as shown 
represents the on-screen appearance of the program output. 
categorized by rain type and proximity to the bright band (Fig. 3); and tables of PR-GR mean difference 
broken out by rain type, for both the constant-height data levels and the levels defined as proximity to the 
bright band. The statistical analysis tool supports studies of calibration differences between the PR and 
GR as well as the evaluation of the quality of the TRMM PR attenuation correction algorithm. 
45 
c: 
.>2 
iii 
::l 
Iii 35 
~ 
0: 
a.. 25 ::a 
::a 
0: 
I-
15 25 35 45 55 65 
Radar, dBZ (Ku-adjusted) 
Figure 3. Scatter plot of PR VS. OR 
reflectivity for stratiform rain points above 
the bright band. 
The vertical cross-section tool generates cross sections of 
the PR and GR reflectivity match-up data (Fig. 4) and PR-
GR reflectivity difference (not shown) along a selected PR 
scan line. If the original 2A-25 TRMM PR product files are 
available, cross sections of full-vertical-resolution (250 m) 
PR data can also be displayed for comparison to the volume-
averaged PR match-up data. The cross-section tool was 
developed primarily to investigate differences seen between 
the PR and GR volume match data within and below the 
melting layer in stratiform rain, and to evaluate the quality 
of the PR attenuation correction algorithm in convective and 
heavy stratiform rain cases. Both tools provide the ability to 
adjustments 
apply the Liao/Meneghini S-band to Ku-band frequency 
and Meneghini, 2009) to the reflectivity data, and to filter the data volumes according 
to the ro~la~1'" percent above threshold criteria. 
These software tools are being made available as open source code via the NASA/GSFC Innovative 
Partnerships Program Office ,=~_~""-",,,"=~.c~~~==~J Information about the match-up data files 
and statistical products, including doeumentation and how to gain online access to them, can be found on 
the GPM gronnd validation web site ,=~~~"=~~===~,~~=~===~==/ 
REFERENCES 
Anagnostou, E.N., C.A. Morales, and T. Dinku, 2000: The 
use of TRMM Precipitation Radar observations in 
determining ground radar calibration biases. J. Atmos. 
Ocean. Tech., 18, 616-628. 
Bolen, S.M. and V. Chandrasekar, 2000: Quantitative 
cross validation of space-based and ground-based radar 
observations. J. Appl. Meteor., 39,2071-2079. 
Liao, L., R. Meneghini, and T. Iguichi, 2001: 
Comparisons of rain rate and reflectivity factor derived 
from the TRMM Precipitation Radar and the WSR-88D 
over the Melbourne, Florida, site. J. Atmos. Ocean. Tech., 
18,1959-1974. 
Liao, L., and R. Meneghini, 2009: Changes in the TRMM 
Version-5 and Version-6 Precipitation Radar Products due 
to Orbit Boost. J. Meteor. Soc. Japan. (Submitted) 
Morris, K.R, M.R. Schwaller, D.B. Wolff, and J.L. Pippitt, 
2007: A Global Precipitation Mission (GPM) validation 
network prototype. Preprints, 33rd Conference on Radar 
Meteorology of the AMS, Cairns, Australia, 5-10 August 
2007. 
Morris, K.R, and M.R. Schwaller, 2009: An enhanced 
Global Precipitation Mission (GPM) validation network 
prototype. Preprints, 34th Conference on Radar 
Meteorology of the AMS, Williamsburg, Virginia, 5-9 
October 2009. 
Figure 4. Vertical cross section of volume-
matched PR (top) and OR (bottom) data. 


Data Visualization and Analysis Tools for the Global Precipitation Measurement (GPM) Validation Network

The Validation Network (VN) prototype for the Global Precipitation Measurement (GPM) mission compares data from the Tropical Rainfall Measuring Mission (TRMM) satellite Precipitation Radar (PR) to similar measurements from U.S. and international operational weather radars. This prototype is a major component of the GPM Ground Validation System (GVS). The VN provides a means for the precipitation measurement community to identify and resolve significant discrepancies between the ground radar (GR) observations and similar satellite observations. The VN prototype is based on research results and computer code described by Anagnostou et al. (2001), Bolen and Chandrasekar (2000), and Liao et al. (2001), and has previously been described by Morris, et al. (2007). Morris and Schwaller (2009) describe the PR-GR volume-matching algorithm used to create the VN match-up data set used for the comparisons. This paper describes software tools that have been developed for visualization and statistical analysis of the original and volume matched PR and GR data

Schwaller, Mathew R.

Morris, K. Robert

DATA VISUALIZATION AND ANALYSIS TOOLS FOR THE
GLOBAL PRECIPITATION MEASUREMENT (GPM) VALIDATION NETWORK
K. Robert Morris
SAIC / NASA / Goddard Space Flight Center
Mathew R. Schwaller — NASA/GSFC
The Validation Network (VN) prototype for the Global Precipitation Measurement (GPM) mission
compares data from the Tropical Rainfall Measuring Mission (TRMM) satellite Precipitation Radar (PR)
to similar measurements from U.S. and international operational weather radars. This prototype is a
major component of the GPM Ground Validation System (GVS). The VN provides a means for the
precipitation measurement community to identify and resolve significant discrepancies between the
ground radar (GR) observations and similar satellite observations. The VN prototype is based on research
results and computer code described by Anagnostou et al. (2001), Bolen and Chandrasekar (2000), and
Liao et al. (2001), and has previously been described by Morris, et al. (2007). Morris and Schwaller
(2009) describe the PR-GR volume-matching algorithm used to create the VN match-up data set used for
the comparisons. This paper describes software tools that have been developed for visualization and
statistical analysis of the original and volume matched PR and GR data.
Table 1. Mean difference between PR and original
(GR) and frequency-corrected (GRO WSR-88D
reflectivity for stratiform rain volumes above the
bright band. Negative values indicate WSR-88D
higher than TRMM PR.
Radar
ID
PR-GRK.
Mean
Difference
qML_
PR-GR
Mean
Difference
z
—=Lq
PR Mean
Reflectivity(dBZ) TotalSamples
KAMIX 0.03 -0A9 22.65 2304KCLX -0.76 -1.42 23.54 9071KFWS 0.971 0.43 23.78 119101KGRK 2.631 2.19 24.19 6871KJAX -0.72 -133 22.95 4509KLCH -1.34 -2.06 23.54 4071KMLB 0.71 0.26 22.52 2787
M6FB 1.00 -0.50-23.37 4-772TLH -1.62 -2.34 2337 3280,
The core VN dataset consists of volume-matched
TRMM PR and quality-controlled, ground-based
WSR-88D (Weather Surveillance Radar — 1988
Doppler, or WSR-88D) radar reflectivity, for 21
sites in the southeastern U.S. PR data include radar
reflectivity (both raw and attenuation corrected),
neat-surface rain rate, and other variables. Only
reflectivity is analyzed for the GR. Geometric
matchup analyses are performed for cases when
there is "significant overlap" between the PR and
GR observations during periods of "significant
averaged only in the horizontal within the individual elevation sweep surfaces, over an area centered on
each intersected PR ray. Match-up data are restricted to within a 100 km radius of the GR site, where the
https://ntrs.nasa.gov/search.jsp?R=20100042502 2019-08-31T16:13:54+00:00Z
GR sample values have sufficient vertical resolution and GR overshooting of precipitation echoes is
minimal.
These split-out data are stored in a database table. Queries to the database allow the statistical data to be
combined and recategorized in a flexible manner. For example, Table I presents the PR-GR mean
difference in dBZ for individual VN WSR-88D radars, for both the original S-band GR reflectivity (GR)
and the frequency-corrected GR reflectivity (GRKu), for all samples categorized as stratiform rain type,
above the bright band, and where fewer than five percent of PR and GR bins were rejected as "below
threshold" in the sample averages. In the same manner, the bulk data can be split out by site and date to
produce time series of site-specific PR-GR mean reflectivity, or to analyze the results by region or season.
Figure 1. PPI Animation Display of the VN Statistical Analysis and Display Tool, showing volume-matched PR
(left) and GR (right) data.
The two primary visualization tools are the statistical analysis tool and the vertical cross section tool,
which allow display and analysis of VN match-up data for individual site overpass events. For spatial
orientation, the statistical analysis tool can display PPIs of volume-matched data (Fig. 1) as an animation
loop progressing from low to high elevation sweeps. The statistical analysis tool vertically stratifies the
data to produce tabular and graphical displays, including vertical profiles of PR and GR reflectivity from
match-up data averaged over the constant height levels, and histograms of PR and GR reflectivity for
match-up data stratified by proximity to the bright band (Fig. 2); scatter plots of PR vs. GR reflectivity
Figure 2. Vertical profile (left) and histogram of volume-matched PR (green) and GR (red) reflectivity, by rain
type. Only the histogram for the above-bright-band category is shown in this example. Example as shown
represents the on-screen appearance of the program output.
categorized by rain type and proximity to the bright band (Fig. 3); and tables of PR-GR mean difference
broken out by rain type, for both the constant-height data levels and the levels defined as proximity to the
bright band. The statistical analysis toot supports studies of calibration differences between the PR and
GR as well as the evaluation of the quality of the TRMM PR attenuation correction algorithm.
is
Is	 25	 35	 45	 55	 66
GV Radar, dBZ (Kwadjusted)
Figure 3. Scatter plot of PR vs. GR
reflectivity for stratiform rain points above
the bright band.
The vertical cross-section tool generates cross sections of
the PR and GR reflectivity match-up data (Fig. 4) and PR-
GR reflectivity difference (not shown) along a selected PR
scan line. If the original 2A-25 TRMM PR product files are
available, cross sections of full-vertical-resolution (250 m)
PR data can also be displayed for comparison to the volume-
averaged PR match-up data. The cross-section tool was
developed primarily to investigate differences seen between
the PR and GR volume match data within and below the
melting layer in stratiform rain, and to evaluate the quality
of the PR attenuation correction algorithm in convective and
heavy stratiform, rain cases. Both tools provide the ability to apply the Liao/Meneghini S-band to Ku-
band frequency adjustments (Liao and Meneghini, 2009) to the reflectivity data, and to filter the data
volumes according to the reflectivity percent above threshold criteria.
These software tools are being made available as open source code via the NASA/GSFC Innovative
Partnerships Program Office (htip..f/o ensour€,e. gsfc.nasa.gov). Information about the match-up data files
and statistical products, including documentation and how to gain online access to them, can be found on
the GPM ground validation web site (-hit / !'gVm.gs1c.nasa.&ov; g oundvalidation.html).
REFERENCES
Anagnostou, EX, C.A. Morales, and T. Dinku, 2000: The
use of TRNIM Precipitation Radar observations in
determining ground radar calibration biases. J Atmos.
Ocean. Tech., 18, 616-628.
Bolen, S.M. and V. Chandrasekar, 2000: Quantitative
cross validation of space-based and ground-based radar
observations. J AppL meteor., 39, 2071-2079.
Liao, L., R. Meneghini, and T. Iguichi, 2001:
Comparisons of rain rate and reflectivity factor derived
from the TRMM Precipitation Radar and the WSR-88D
over the Melbourne, Florida, site. J Annos. Ocean. Tech.,
18, 1959-1974.
Liao, L., and R. Meneghini, 2009: Changes in the TRMM
Version-5 and Version-6 Precipitation Radar Products due
to Orbit Boost. J Meteor. Soc. Japan. (Submitted)
Morris, K.R, M.R. Schwaller, D.B. Wolff, and J.L. Pippitt,
2007: A Global Precipitation Mission (GPM) validation
network prototype. Preprints, 33rd Conference on Radar
Meteorology of the AMS, Cairns, Australia, 5-10 August
2007.
Morris, K.R, and M.R. Schwaller, 2009: An enhanced
Global Precipitation Mission (GPM) validation network
prototype. Preprints, 34th Conference on Radar
Meteorology of the AMS, Williamsburg, Virginia, 5-9
October 2009.
Figure 4. Vertical cross section of volume
matched PR (top) and GR (bottom) data,


Data Visualization and Analysis Tools for the Global Precipitation Measurement (GPM) Validation Network

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