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

(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.

GPM Ground Validation: Strategy and Efforts

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 D 0 ), 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.

D 0 Z + Core Satellite Quality Assessment

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.

Radiometer Validation Satellite Overpass Core Satellite Retrieval Synthetic Radiometer Synthetic Retrieval Rain Gauge Network Comparisons

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).

Error Modeling

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 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.

R, D 0 88D Dual Pol. Rain Gauge Disdrometer Profiler X-band Tb CRM Validation

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 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

Land Surface Validation

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 Previous 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.

Integrated Validation Plan Surface Feedback Processes Cloud Parameterizations Water Budget Closure Rainfall Properties Cloud Microphysics

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.