climate data records – a maturity model and research-operation transitions john bates noaa’s...

Climate Data Records –A Maturity Model and

Research-Operation Transitions

John BatesNOAA’s National Climatic Data

Center

Workshop on the Applications of GPS Radio Occultation to Climate17 March 2008

Notional View of GPS-RO


GPS-RO Neumonic Device

Steve Martin demonstrates GPS-RO bending angle


Outline

Climate Data Records (CDRs) and Principles of Scientific Data Stewardship (SDS)

CDR Example – Upper-Tropospheric Water Vapor (UTWV or UTH)

The NASA-NOAA model for research-operations transitions of CDRs

Assessing the maturity of COSMIC GPS-RO

CDRs

UTWV

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COSMIC


Principles of Scientific Data Stewardship

Develop archive stewardship to preserve information content of raw data stream,

Process large volumes of satellite data extending up to decades in length to account for systematic errors and to eliminate artifacts in the raw data (referred to as fundamental climate data records, FCDRs),

Generate retrieved geophysical parameters from the FCDRs (referred to as thematic climate data records TCDRs) including combining observations from all sources,

Conduct monitoring and research by analyzing data sets to conduct climate science and applied research – Toward a National Climate Service– Climate variability and change, global water, energy,

carbon cycles– Societal Applications – GEOSS benefit areas – Climate

Information Records (CIRs)

CDRs


Sensor DataRecords (SDRs)

Data (Direct & Remotely Sensed)

Fundamental Climate Data

Records (FCDRs)

Thematic Climate Data Records

(TCDRs)

Climate Data Records or Homogenized Time Series

Homogenization and Calibration

Time-tagged Geo-Referenced

Converted to Bio-Geophysical

Variables

EnvironmentalData Records

(EDRs)

Converted to Bio-Geophysical

Variables

Defining CDRsClimate Data Records

CDRs


Upper Tropospheric Water Vapor CDR

Upper tropospheric water vapor (UTWV or UTH) channel has flown operationally since 1979

UTWV was originally dismissed (until 1990)– Didn’t compare well with radiosondes– Spectroscopy of WV uncertain

Lindzen’s 1990 BAMS paper ‘Some coolness concerning global warming’ spurred new attention

Water vapor feedback accounts for ½ to 2/3 of total global warming in model projections

UTWV


UTWV Long-term Intercalibration

246

246.5

247

247.5

248

248.5

249

1980 1984 1988 1992 1996 2000 2004

30S - 30N

N06N07

N08N09

N10N11

N12N14

N15N16

N17

Year

238

240

242

244

246

248

1980 1984 1988 1992 1996 2000 2004

30S - 30N

N06N07N08N09N10N11N12N14N15N16N17

Year

UTWV

Before

After


Becoming a CDR ‘Benchmark’

An objective benchmark may be determined by maturity assessment

A subjective benchmark is determined by independent application of a data set to climate monitoring, forcings, or feedbacks

Evidence for Strengthening of the Tropical General Circulation in the 1990s by Chen, Carlson and Del Genio

UTWV


Thoughts on Benchmark Concept The term Benchmark (Goody, 2001) carries particular

importance in the context of long-term climate monitoring and with respect to testing the veracity of climate model predictions. The central elements in the definition of a climate Benchmark are:– Accuracy that extends over decades, or indefinitely;– Variable critical to defining long-term climate change that is

observed on the global scale;– A measurement that is tied to irrefutable standards, usually

with a broad laboratory base;– Observation strategy designed to reveal systematic errors

through independent cross-checks, open inspection, and continuous interrogation;

– Limited number of carefully selected observables, with highly confined objectives defining (a) climate forcings, (b) climate response.

Just as the concept of ‘truth’, as in ‘ground truth’ is perhaps more a religious concept, so may be the concept of benchmark

A better definition may be in the combined objective maturity measures (as above) combined with the quintessential hallmark of the scientific process – independent peer review

UTWV


EVOLUTION OF A CLIMATE DATA RECORD (CDR)

Develop Joint Model of CDR Process

Develop a "Generic" Budget

Develop a list of Candidate CDRs focusing on the NPOESS

C1 Mission

Assess the Maturity and Cost Complexity of each Candidate

CDR

Priortize the Candidate CDRs for order of implementation

Develop a schedule of implementation with a gradual

start

Develop the accompanying budget

Planning Development Path

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Core Activities in CDR Evolution

Sensor calibration and characterization Algorithm development and refinement

– Continuing incubation of algorithm alternatives that may eventual replace previous “standard”

Product (Re-)Processing– Research & Operational agencies co-generate

Maturity Level 3-4 products as part of transition

– Assures transition readiness Product validation and use-driven

evaluation Archive, Distribution, Documentation

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Notional Evolution of a CDR(From NASA-NOAA Climate Science Working

Group)


Notional Evolution of GPS-RO(From Anthes et al.)

Need to map this into NASA-NOAA notional CDR evolution Gantt chart

Do we restore GPS-RO to NPOESS?

Activity Name Start Date Finish Date 2004 2005 2006 2007 2008 2009 2010 2011 2012 2013 2014 2015

2004 2005 2006 2007 2008 2009 2010 2011 2012 2013 2014 2015

Launch of COSMIC 10/4/05

Operation of COSMIC 10/18/05 10/17/10

Planning for COSMIC II 10/1/04 9/30/06

Development of COSMIC II 10/1/06 10/18/09

Launch of COSMIC II 10/18/09

Operation of COSMIC II 10/18/09 10/17/14

Planning for COSMIC III 10/1/09 9/30/10

Development of COSMIC III 10/1/10 10/17/13

Launch of COSMIC III 10/18/13

Operation of COSMIC III 10/18/13 10/17/18

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Operational Climate Data Records –Prioritization, Production, & Productivity

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CRD Maturity Research-Operations

NO

AA

LE

AD

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Cost Estimation Approach

1. Notional CDR lifecycle provides schedule and activity breakdown– NASA historical cost data estimates cost/activity– Separate Research and Operational cost profiles

2. Algorithm maturity* determines relative year in notional CDR lifecycle

3. Production complexity* determines multiplier of notional cost profile

4. CDR “ramp-up” rate treated as independent variable– Required CDR prioritization straw man

*Maturity and complexity estimates from joint agency sensor expert teams (names provided in April Panel brief)

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Complexity Serves As Multiplier of Notional Cost Profile

Factors:

1) Number, quality & diversity of input streams

2) Resolutions (vertical, horizontal, temporal, spectral)

3) Algorithm complexity4) Algorithm outputs (#CDRs)5) Cal/Val complexity and cost

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NOAA GPS-RO Work (NOAA Industry Day; Courtesy J. Yo)

NWP– On-going 3-yr Joint Center for Satellite Data Assimilation

(JCSDA) development program to assimilate GPS-RO data into National Weather Service’s operational Global Forecast System (GFS)

– Developed, tested, and implemented the necessary components to assimilate GPS-RO observations (refractivity and bending angle) in GFS

Forward models to simulate the observations from analysis variables, and tangent linear and adjoint models

Quality control algorithms Error characterization models Data handling and decoding procedures

– Verification and impact evaluation procedures

Climate – Funded SDS proposal & AMS meetings– Ben Ho - UCAR Validation and Calibration of MSU/AMSU

Measurements and Radiosonde Observations using GPS RO Data for Improving Stratospheric and Tropospheric Temperature Trends Analysis

NOAA GPS-RO Industry Day – January 2008

COSMIC


Meeting Future Needs (NOAA Industry Day; Courtesy J. Yo)

Continuity of COSMIC Mission after 2011– Maintain gain realized for global NWP– Maintain stable calibration/validation source for Climate

Data Records– Provide dense ionospheric soundings for Space WX– NWP Latency requirement drives downlink needs– Constellation Approach– Number/density of soundings ~ proportional to number of

receivers Multiple Global Navigation Satellite System Sources

– GALILEO, GLONASS – also increases number of soundings– Complementing radiometric satellite soundings

Recognize that GPR-RO is a KEY PART of the solution, not the whole

COSMIC


Summary from Industry Day (NOAA Industry Day; Courtesy J. Yo)

GSP-RO becoming established as data source for– Numerical weather prediction– Climate– Ionospheric sounding– COSMIC demonstrating benefits of small-

satellite Constellation approach to GPS-RO

– Now is the time to consider how to maintain constellation capability for GPSRO after 2011

– NRC’s Decadal Survey published in early 2007; recommended follow-on GPS Radio Occultation satellite mission

New potential may exist for CDRs and climate sensors in NOAA

COSMIC


Conclusions The foundations of research-

operations transition of satellite CDRs has begun within NOAA and NASA

NSF and NOAA should consider that work as a template for a potential GPS-RO transition

COSMIC should adopt a maturity model, assess progress on a regular basis, and encourage independent applications

How does GPS-RO ultimately fit in?


Backup Slides


CDR Maturity MatrixMaturit

y Sensor UseAlgorith

m stability

Metadata & QA Documentation Validation Public

ReleaseScience &

Applications

1 Research MissionSignificant

changes likely

Incomplete Draft ATBD Minimal

Limited data availability to

develop familiarity

Little or none

2 Research MissionSome

changes expected

Research grade (extensive)

ATBD Version 1+Uncertainty estimated

for select locations/times

Data available but of unknown

accuracy; caveats

required for use.

Limited or ongoing

3 Research MissionsMinimal changes expected

Research grade (extensive);

Meets international

standards

Public ATBD; Peer-reviewed algorithm and

product descriptions

Uncertainty estimated over widely distribute

times/location by multiple investigators;

Differences understood.


accuracy; caveats

required for use.

Provisionally used in

applications and assessments

demonstrating positive value.

4 Operational MissionMinimal changes expected

Stable, Allows provenance tracking and

reproducibility; Meets

international standards

Public ATBD; Draft Operational Algorithm

Description (OAD); Peer-reviewed algorithm and

product descriptions

Uncertainty estimated over widely distribute

times/location by multiple investigators;

Differences understood.


accuracy; caveats

required for use.

Provisionally used in

applications and assessments

demonstrating positive value.

5

All relevant research and operational

missions; unified and coherent record

demonstrated across different sensors

Stable and reproducible


reproducibility; Meeting


Public ATBD, Operational Algorithm Description (OAD) and Validation Plan; Peer-reviewed algorithm,

product and validation articles

Consistent uncertainties estimated over most

environmental conditions by multiple

investigators

Multi-mission record is publicly

available with associated uncertainty

estimate

Used in various published

applications and assessments by

different investigators

6

All relevant research and operational

missions; unified and coherent record over

complete series; record is considered

scientifically irrefutable following

extensive scrutiny

Stable and reproducible

; homogeneou

s and published

error budget


reproducibility; Meeting


Product, algorithm, validation, processing and

metadata described in peer-reviewed literature

Observation strategy designed to reveal systematic errors

through independent cross-checks, open

inspection, and continuous

interrogation

Multi-mission record is publicly

available from Long-Term

archive

Used in various published

applications and assessments by

different investigators

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climate data records – a maturity model and research-operation transitions john bates noaa’s...

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