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The important role of: continuity of observations and data products for IPCC. Critical role for GCOS and WCRP. Kevin Trenberth NCAR. Climate Observations. Process studies : atmosphere, ocean, land, cryosphere and their interactions Sustained observations : the climate record

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slide1

The important role of:

continuity of observations and data products for IPCC

Critical role for GCOS and WCRP

Kevin Trenberth

NCAR

climate observations
Climate Observations
  • Process studies: atmosphere, ocean, land, cryosphere and their interactions
  • Sustained observations: the climate record
  • Enhanced monitoring
  • Analysis, assimilation and data products
  • Data stewardship, data access, QC
                • JSC 2010:
                • Observations white paper
slide3

WOAP: Key climate issues

  • Climate data records
    • Continuity, continuity, continuity;
    • The need for reprocessing and reanalysis of past data and coordination of these activities among agencies and variables;
    • Includes evaluation and assessment or results
    • Importance of calibration, accuracy, benchmarks,
    • Space and in situ observations;
  • Reanalysis to produce global gridded fields

GRUAN, GPS RO,

CLARREO

slide4

WOAP-1

Reprocessing: assess variables for need and readiness, and commitments. Include in GEOSS.

5 Principles for Re-Processing Climate Data Records

For climate, the value of an observational record increases with time, provided that the record is continuous and homogeneous.

As datasets are used, characteristics of the data and problems are exposed, and often solutions to problems or algorithm improvements are proposed, especially for satellite measurements.

Accordingly, re-processing of the record should be an integral part of the process of creating a climate data record.

slide5

WCRP/GCOS

WOAP workshop: ESRIN, Frascati 18-20 April 2011

Evaluation of satellite climate datasets

identification of best practices in evaluating and inter-comparing global climate datasets, especially where there is more than one data set for a given parameter (e.g., surface temperature, sea ice concentrations, etc.).

Pentad

Available Global GEWEX+ Datasets

Daily

3 – 6 hrs

TIME

1979

1985

1990

1995

2000

2005

2010

Parameter

Clouds

WaterVapor

50 km

Precipitation

250 km

100 km

TOARadiation

100 km

SRF Radiation

100 km

Evaporation

50 km

AtmosphericCirculation

50 km

large disparities among different analyses
Large disparities among different analyses

Daily SST (1 Jan 2007)

Reynolds and Chelton 2010 JC

Sea Level OHC

Palmer et al 2010

OceanObs’09

total sea ice area 2007 and 2008
Total sea ice area, 2007 and 2008

NASA Team

NASA Team 2

SSM/I Bootstrap

AMSR Bootstrap

ASI

Cal/Val (York)

Bristol

Norsex

Avg. of 8 algorithms

& ±1 st. dev. range

No single algorithm clearly superior

2007

2008

The largest factor for ice concentration/extent consistency is intercalibration of the products through transitions through different generations of satellite-borne sensors.

slide8

ISCCP

MODIS-ST

HCA (%)

PATMOS-x

MODIS-CE

ISCCP

TOVS Path-B

CALIPSO

CALIPSO (t > 0.1)

AIRS_LMD

CALIPSO

AIRS-LMD

(%)

High Cloud Amount (July)

absolute values depend on

instrument sensitivity

& method,

but distributions similar

reanalysis

Reanalysis

Reanalysis is an essential part of climate services, especially in monitoring, attribution and prediction

Major problems remain from the changing observing system

There is not a problem with lack of reanalyses, but: 

lack of an end to end program with adequate vetting and evaluation of products (and the funding for that), and

Reanalysis is all done in a research domain and not sustained, so that key personnel can be lost. 

Lack of adequate vetting and diagnosis

slide11

Atmospheric Reanalyses

Current atmosphericreanalyses, with the horizontal resolution (latitude; T159 is equivalent to about 0.8 ), the starting and ending dates, the approximate vintage of the model and analysis system, and current status.

slide12

Satellite Data Streams assimilated

TIROS-N

Dec

Feb

NOAA-6

TOVS

Jul

Apr

Nov

Oct

NOAA-7

Sep

Feb

NOAA-8

May

Jun

Jul Oct

NOAA-9

Jan

Nov

NOAA-10

Dec

Sep

NOAA-11

Nov

Jan

Sep

Sep

NOAA-12

Sep

Jun

NOAA-14

Jan

Dec

NOAA-15

Sep

ATOVS

NOAA-16

Nov

NOAA-17

Jul

NOAA-18

Nov

EOS Aqua

EOS Aqua

Oct

GOES-08

GOES

Sounders

Apr

Jul

GOES-10

Apr

Jun

F08

GOES-12

Jul

Jul

Dec

F10

SSM/I

Dec

Nov

F11

Dec

Dec

F13

May

F14

May

Dec

Aug

F15

78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 95 96 97 98 99 00 01 02 03 04 05 06 07 08

the changing observing system
The Changing Observing System
      • 1973 77k/6h 1987 550k
  • 1979 324k 2006 4,220k

1973 – 77K Obs every 6hrs

1987 – 550K Obs every 6hrs

1979 – 325K Obs every 6hrs

2006 – 4.2M Obs every 6hrs

slide14

NWP Forecast skill scores continue to improve

Reanalysis

Extratropical NH and SH forecasts: 12 month means plotted at last month. Updated from Simmons and Hollingsworth 2002

SH skill became comparable to NH after about 2002!

future needs observations and analysis
Future needs: Observations and Analysis
  • Observations: in situ and from space (that satisfy the climate observing principles);
  • A performance tracking system;
  • Climate Data Records (CDRs)
  • The ingest, archival, stewardship of data, data management;
  • Access to data
  • Data (re)processing and analysis
  • The analysis and reanalysis of the observations and derivation of products,
  • Data assimilation and model initialization
future needs models
Future needs: Models
  • Data assimilation and model initialization
  • Better, more complete models
  • Assessment of what has happened and why (attribution) including likely impacts on human and eco-systems;
  • Prediction of near-term climate change over several decades: ensembles
  • Statistical models: applications
  • Downscaling, regional information
  • Responsiveness to decision makers and users.
slide20

Role of WCRP

  • The coordinated collection, analysis and reanalysis of climate observations is required to describe the structure and variability of the climate system.
    • Observations give the basis for evaluating and improving models, and models providing the framework and impetus for deciding what observations to take.
    • Special efforts required to obtain, analyse and assimilate data from the new generation of environmental satellites.
  • Enables the generation of descriptions of states of the coupled climate system consistent with all variables and the physical framework provided by models, both for prediction and for documenting the climate record.
slide21

Role of WCRP

  • Advocate improved observations and analysis suitable for climate (satisfying the GCOS Climate Monitoring Principles to ensure continuity of record). This especially includes those from space.
  • Data set development: evaluating observations and promoting global reprocessing and reanalysis. Develop new products and datasets, analytical and diagnostic techniques, high level derived products: for use in understanding and analyzing climate variability and change, and for evaluating models.
  • Mechanisms and modes of variability in climate anomalies; operational attribution, numerical experimentation in near real time to allow reliable statements to be made not only about what the state of the climate is, but also why it is the way it is and the mechanisms involved.
slide22

Role of WCRP

    • Data assimilation and analysis: initializing of coupled models for prediction.
  • Provide advice on best datasets for various purposes (climatologies and time series) and their merits and limitations. (Error bars are greatly needed.)
  • High priority needs are to have assessments of datasets for use in evaluating climate models, and specifically those used in the AR5 IPCC report that will participate in the CMIP5 activity
slide23

Role of WCRP

  • Help improve and promote sound data stewardship, including data archiving, management, and access. This includes making sure that climate-related data variables are reaching data archives, and that standards are set for archiving new types of data.
  • Help make data accessible and available e.g., through the internet. Promote shared efforts for data quality control.
climate information system

WCRP

Climate Information System

Trenberth, 2008 WMO Bull

imperative a climate information system
Imperative:A climate information system
  • Observations: forcings,atmosphere, ocean, land
  • Analysis: comprehensive, integrated, products
  • Assimilation: model based, initialization
  • Attribution: understanding, causes
  • Assessment: global, regions, impacts, planning
  • Predictions: multiple time scales
  • Decision Making: impacts, adaptation

An Integrated Earth System Information System

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