Transcript European Climate Assessment & Dataset

Warning:
What data do weno
require
for to
extremes
analysis
attempt
be
and what is available?
comprehensive;
bias
(an intro to the BOG
on towards
data)
land-atmosphere;
bias towards Europe
Albert Klein Tank
KNMI, The Netherlands
Outline
•
Russian heat wave (yes, one more time)
•
GCOS IP-2010
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Data Policy white paper from the Exeter workshop on
creating surface temperature datasets
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Other relevant initiatives
•
Further issues for BOG discussion
Example: Russian heat wave
July 2010
Example: Russian heat wave
July 2010
Enough data for
statistical modelling,
event attribution, or
studying physical
processes,
but…
Courtesy John Christy (top), Adrian Simmons (bottom)
Example: Russian heat wave
July 2010
Example: Russian heat wave
July 2010
31 days
with
Tx>25°C;
normal is
9.5 days
Data available from http://eca.knmi.nl
Example: Russian heat wave
July 2010
16 nights
with
Tn>20°C;
normal is
0.5 night
Data available from http://eca.knmi.nl
Example: Russian heat wave
July 2010
No 16 nights
significant
with
trend
at
Tn>20°C;
Moscow
normal is
0.5 night
Data available from http://eca.knmi.nl
Daily gridded
product (E-OBS)
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Based on station records
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Daily fields
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1950 – now
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0.25 deg resolution
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Matching RCM grids
•
Associated error fields
exist, but rarely used!
Haylock et al., J. Geophys. Res., 2008; data available from http://eca.knmi.nl
Daily gridded
product (E-OBS)
…but interpolation leads to reduction of extremes
•
Based on station records
•
Daily fields
•
1950 – now
•
0.25 deg resolution
•
Matching RCM grids
•
Associated error fields
exist, but rarely used!
precipitation
temperature
Haylock et al., J. Geophys. Res., 2008; data available from http://eca.knmi.nl
Traceability
•
About 60% is
“public”, i.e.
available from
the ECA&D
website
•
For the other
stations, only
the metadata
and derived
products can
be released
Data available from http://eca.knmi.nl
GCOS IP-10
GCOS IP-10
•
Observations are required for:
informed decisions on prevention, mitigation, and adaptation
strategies; to support research; to initialise predictions; to
develop the models; to assess social and economic
vulnerabilities
•
Observations are essential public goods:
benefits of global availability of data exceed any economic or
strategic value to individual countries from withholding
national data
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Observations underpin all efforts by Parties to the United
Nations Framework Convention on Climate Change (UNFCCC)
to mitigate, and adapt to, climate change
Some GCOS IP-10 issues
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Increasing need for local, high-frequency surface atmospheric
data on climate to characterise extremes
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Satellite remote-sensing systems become more important,
but surface-based and airborne in situ and remote-sensing
systems will always remain essential
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Metadata (i.e., information on where and how the
observations are taken) are absolutely essential
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Limited progress in developing countries, and support for
capacity-building is small in relation to needs
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Flow of data to the user community and to the international
data centres is inadequate
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Parties should produce national plans on their climate
observing system
Exeter workshop
Exeter workshop
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Several white papers, e.g. on Data Policy:
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Gap exists between theory (including GCOS and GEO
requirements) and practice
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Partly due to data policy, but not alone
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Also lack of engagement, lack of resources, and inadequate
data-system infrastructures
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Data policy issues are persistent and unlikely to go away in
the near future
See: http://www.surfacetemperatures.org
Exeter workshop
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Some recommendations:
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Accept trade off between traceability and data completeness
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Acknowledge that involvement of data providers from
countries throughout the world is essential
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Involves more than simply sending the data to an
international data centre
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Scientific community to deliver information to support local
climate services (= return of investment important in
particularly for developing countries)
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Support digitization of paper archives
Other relevant initiatives
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Global:
– coordinated inter-callibration (GSICS) and reprocessing
(SCOPE-CM) of satellite data
– ICOADS version 3 released (almost)
– several reanalyses datasets released (MERRA, CFSR, JRA)
– 20th Century reanalysis (based on surface pressure data only)
– new global reanalysis project by ECMWF (ERACLIM) with much
attention for improving reanalysis data input
– new project (CLIMDEX) for updating the global dataset of
extremes indices and developing global daily gridded datasets
(building on GHCN-Daily)
Other relevant initiatives
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Regional:
– regional reanalysis for North America (NARR)
and Europe (http://www.euro4m.eu )
More in:
– daily station collections
(+ daily gridded datasets) for Asia
(APHRODITE) and South America (CLARIS-LPB)
Meeting
Report
– several new WOAP4
national high
resolution
datasets
Hamburg, Germany
March 2010
GCOS Publication No. 142
Index for heavy falls
What about the
blank regions
in the map?
Alexander et al., JGR, 2006; also in IPCC-AR4
ETCCDI Regional Workshops
(complemented by APN)
Peterson and Manton, BAMS, 2008
Regional workshops
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Organised by the Expert Team on Climate Change Detection and
Indices (ETCCDI)
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ETCCDI is a group of scientists jointly sponsored by several
international agencies (WMO-CCl/WCRP-CLIVAR/JCOMM)
•
Environment Canada provides, maintains, and further develops the
R-based workshop software (freely available from
http://cccma.seos.uvic.ca/ETCCDI)
ETCCDI Regional Workshops
(complemented by APN)
Working together
GH Africa Workshop
(WCRP/World Bank)
04/2010
Central
Africa workshops:
Regional
(USA) 4/2007
successful concept,…
Mexico (UK)
03/2009
…but often no access to
original data!
West Indian
Ocean (France)
09/2009
Peterson and Manton, BAMS, 2008
Southeast
Asia (USA)
12/2007
Indonesia, Malaysia,
Thailand, Philippines
(NL) 12/2009
Further issues for BOG (1 of 2)
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Tension between traceability (access to the primary sources)
and data completeness (use whatever available)
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Need high density, high frequency, sharing, and long records
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Adaptive strategies for dealing with extreme events place even
higher demands on observations
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Datasets need continuous work, both for updating and improving
quality/homogeneity
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Including scientist developing datasets in research projects is a
good idea, e.g. in CMIP5 climate model evaluation
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Met Services are not keen if their only role is providing data;
application relevant products are a necessary return of investment
Further issues for BOG (2 of 2)
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Need to close the gap between rapid IT developments and actually
implementing modern distributed database management systems
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Reprocessing of data and reanalysis important
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Some (satellite) datasets are becoming so large that it is difficult
for many users to acquire them
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Users ask for products that meet their requirements, often
through integration of data from different sources (in situ,
satellite, reanalysis)
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Work needs to comply with WMO/GCOS/GEO ideas on
systems/standards, but in the end the actual delivered datasets
count rather than nice words
mailto: Albert.Klein.Tank @ KNMI.nl