US GPM Ground Validation: Strategy and Efforts

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(US) GPM Ground Validation Strategy and Efforts
A summary of the NASA sponsored White Paper on
a validation strategy for GPM
Christian Kummerow Colorado State
University Walter Petersen University of
Alabama, Huntsville
3rd IPWG Workshop Melbourne, Australia October
23-27, 2006
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(US) GPM Ground Validation Strategy and Efforts

• Starting with meetings in August 2005 and
  February of 2006, a GPM panel was charged with
  developing a strategy for validating rainfall
  products from the core and constellation
  satellites.
• This resulted in a finished White Paper
  dated Sept. 27, 2006 Edited by C. Kummerow and W.
  Petersen.
• The GV white paper represents the NASA concept
  for rainfall validation. NASA thought it
  important to outline its own strategy and
  efforts before proceeding with in-depth
  discussions with potential partners.
• The White Paper was constructed with the
  idea in mind that many different partners would
  be able to contribute assets of different
  maturity and could fully participate - helping
  both the GV effort as well as their own
  scientific and application interests.

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GPM Ground Validation Strategy and Efforts
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Objective 1 GPR Core Satellite Quality
Assessment
Background Validation implies a comparison
against a higher truth. The core satellite is
near the top of the measurement system hierarchy
where such comparisons become difficult. While
it is possible to instrument a ground site
sufficiently to establish a higher truth, the
narrow swath of DPR will limit the useful
statistics to perhaps to no more than a few
raining events per months. The user
community, correctly or incorrectly, still uses
rain gauges as truth (even when networks are
sparse) and the core satellite quality should be
assessed against this reference to give users
confidence in the satellite products. It does
not matter if one is assessing Radar-only or
Radar Radiometer products. Both will use the
same fundamental radar remote sensing principles.
Adding radiometer data to the dual-frequency
radar will merely constrain one or more of the
radar variables. Approach Using physical
validation principles, the quality assessment is
broken into two parts. Validating the parameters
that can be observed by the satellite (Z profile
and D0), and then relating these to the
uncertainty in the surface rainfall. Ground
based polarimetric radars are used to provide the
link between satellite and rainfall gauges.
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Core Satellite Quality Assessment
D0 Z

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Objective 2 Constellation Radiometer Validation
Background GPM was designed to use the Core
satellite as the intercalibration and validation
standard. Direct overpass statistics can be used
if properly accounting for differences in spatial
resolution. The core satellite is designed to
create an a-priori database for Bayesian
inversions that is physically consistent with
each of the GMI radiances. The a-priori database
is used (via radiative transfer computations) to
construct a-priori databases for each of the
constellation radiometers. These database also
represent synthetic radiances for each of the
constellation radiometers and their retrieval
capabilities can be assessed directly against
this database. Direct and synthetic
comparisons with the core spacecraft can yield a
wealth of information regarding radiometer
rainfall estimates under various meteorological
conditions but rainfall accumulation errors are
difficult due to space/time correlation of
rainfall itself. Approach Use a combination
of coincident overpasses, synthetic retrievals
and existing in-situ networks to assess
instantaneous errors as well as rainfall
accumulation errors.
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Radiometer Validation
Synthetic Retrieval
Satellite Overpass
Rain Gauge Network Comparisons
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Objective 3 Error Modeling (a.k.a. physical
validation)
Background We must develop a framework to derive
uncertainties based upon first principles (rather
than comparisons against equally uncertain
measurements). Such models are based upon the
uncertainty in observations, radiative transfer
models, assumed cloud properties and inversion
theory. The largest source of uncertainty is the
uncertainty in the assumed cloud parameters.
Obtaining robust statistics for assumed
parameters (e.g. raindrop DSD, cloud water,
shape, density and PSD of ice particles,
characteristics of melting particles and surface
properties) is very difficult - requiring a
combination of surface as well as airborne
in-situ and remotely sensed observations. Need
creativity and support for new instrumentation
that shows promise The approach is parallel to
the Core Satellite Quality Assessment and
provides an independent means of establishing
uncertainties that can be compared/ contrasted to
that effort. Approach Use aircraft in
conjunction with detailed surface observation.
Couple the activity with Cloud Resolving Models
as well as Land Surface models (needed to
establish uncertainties in surface emissivity
models).
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Error Modeling
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Objective 4 Cloud Resolving Model Validation
Background High fidelity Cloud Resolving model
simulations are seen as a vital component of
error model activity. Cloud Resolving Models
offer a dynamical basis for relating the remotely
sensed ice-scattering to the coincident surface
rainfall over land. Cloud Resolving Models must
be viewed as an integral part of any applications
paradigm that focuses on the 2010-2020 time
frame. Progress in data assimilation is already
expanding to these scales. Validating Cloud
Resolving Models requires only marginal
additional observations over those planned for
GPR Core Satellite Quality Assessment and Error
Modeling Approach Add rawinsondes, cloud
profilers and aerosol measurement capabilities to
a site with diverse meteorological regimes.
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CRM Validation
Tb
88D
Dual Pol.
R, D0
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Objective 5 Coupled Land Surface/Atmospheric
Model Validation
Background High fidelity Land Surface Model
simulations are seen as a vital part to improving
our understanding of emissivity models that must
ultimately become part of physical radiometer
algorithms over land. Coupled Land
Surface/Cloud Resolving Models must be viewed as
an integral part of any applications paradigm
that focuses on the 2010-2020 time frame.
Progress in data assimilation is already
expanding to these scales. Land Surface
hydrologic models offer a unique validation
perspective that allows the regional closure of
the water/energy cycle to be studied. Together
with the CRM validation and the infrastructure
needed for it, this offers a new and integrated
look at rainfall validation that complements the
more direct comparisons. Validating land
Surface models requires only marginal additional
observations over those planned for GPR Core
Satellite Quality Assessment, Error Modeling and
CRM validation Approach Add surface flux,
soil moisture/temperature profiles and run-off
observations to the validation site
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Land Surface Validation
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Synergy between activities
Background The five objectives defined in the
White paper each have a constituency prepared to
work on these issues. The overlap between these
direct objectives naturally leads to larger
science questions being faced by the
precipitation community. (e.g. 3-hourly
rainfall validation and Land Surface model
validation addresses the question of water budget
closure that are highly relevant to broader
objectives as defined by GEWEX) Approach Previ
ous approaches stressed in-situ measurements and
comparisons to the satellite. The current
approach stresses broader science questions with
greater science team participation and validation
as a consistency among various different
approaches. Continued science involvement can
be fostered through reports that focus on each
of the 5 activities and the broader questions
that can be explored in their synergy.
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Integrated Validation Plan
Rainfall Properties
Cloud Microphysics
Cloud Parameterizations
Water Budget Closure
Surface Feedback Processes
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International Collaboration
Approach Now that NASA has defined its own
approach, it will facilitate cooperation and
coordination with potential partners.
Partnerships are possible at many levels - from
rain gauge networks, to dual polarizations
radars, to a subset of the activities outlined
here to a full fledged parallel effort in a
distinct climate regime. Cold regions (i..e.
snow dominated) and orographic regimes are of
particular interest but all regimes and, more
importantly, all research with existing and or
new data sets is welcome.