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Stephan Bojinski
,
Michel Verstraete
,
Thomas C. Peterson
,
Carolin Richter
,
Adrian Simmons
, and
Michael Zemp

Climate research, monitoring, prediction, and related services rely on accurate observations of the atmosphere, land, and ocean, adequately sampled globally and over sufficiently long time periods. The Global Climate Observing System, set up under the auspices of United Nations organizations and the International Council for Science to help ensure the availability of systematic observations of climate, developed the concept of essential climate variables (ECVs). ECV data records are intended to provide reliable, traceable, observation-based evidence for a range of applications, including monitoring, mitigating, adapting to, and attributing climate changes, as well as the empirical basis required to understand past, current, and possible future climate variability. The ECV concept has been broadly adopted worldwide as the guiding basis for observing climate, including by the United Nations Framework Convention on Climate Change (UNFCCC), WMO, and space agencies operating Earth observation satellites.

This paper describes the rationale for these ECVs and their current selection, based on the principles of feasibility, relevance, and cost effectiveness. It also provides a view of how the ECV concept could evolve as a guide for rational and evidence-based monitoring of climate and environment. Selected examples are discussed to highlight the benefits, limitations, and future evolution of this approach.

The article is intended to assist program managers to set priorities for climate observation, dataset generation and related research: for instance, within the emerging Global Framework for Climate Services (GFCS). It also helps the observation community and individual researchers to contribute to systematic climate observation, by promoting understanding of ECV choices and the opportunities to influence their evolution.

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Sarah J. Doherty
,
Stephan Bojinski
,
Ann Henderson-Sellers
,
Kevin Noone
,
David Goodrich
,
Nathaniel L. Bindoff
,
John A. Church
,
Kathy A. Hibbard
,
Thomas R. Karl
,
Lucka Kajfez-Bogataj
,
Amanda H. Lynch
,
David E. Parker
,
I. Colin Prentice
,
Venkatachalam Ramaswamy
,
Roger W. Saunders
,
Mark Stafford Smith
,
Konrad Steffen
,
Thomas F. Stocker
,
Peter W. Thorne
,
Kevin E. Trenberth
,
Michel M. Verstraete
, and
Francis W. Zwiers

The Fourth Assessment Report (AR4) of the Intergovernmental Panel on Climate Change (IPCC) concluded that global warming is “unequivocal” and that most of the observed increase since the mid-twentieth century is very likely due to the increase in anthropogenic greenhouse gas concentrations, with discernible human influences on ocean warming, continental-average temperatures, temperature extremes, wind patterns, and other physical and biological indicators, impacting both socioeconomic and ecological systems. It is now clear that we are committed to some level of global climate change, and it is imperative that this be considered when planning future climate research and observational strategies. The Global Climate Observing System program (GCOS), the World Climate Research Programme (WCRP), and the International Geosphere-Biosphere Programme (IGBP) therefore initiated a process to summarize the lessons learned through AR4 Working Groups I and II and to identify a set of high-priority modeling and observational needs. Two classes of recommendations emerged. First is the need to improve climate models, observational and climate monitoring systems, and our understanding of key processes. Second, the framework for climate research and observations must be extended to document impacts and to guide adaptation and mitigation efforts. Research and observational strategies specifically aimed at improving our ability to predict and understand impacts, adaptive capacity, and societal and ecosystem vulnerabilities will serve both purposes and are the subject of the specific recommendations made in this paper.

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Peter W. Thorne
,
Kate M. Willett
,
Rob J. Allan
,
Stephan Bojinski
,
John R. Christy
,
Nigel Fox
,
Simon Gilbert
,
Ian Jolliffe
,
John J. Kennedy
,
Elizabeth Kent
,
Albert Klein Tank
,
Jay Lawrimore
,
David E. Parker
,
Nick Rayner
,
Adrian Simmons
,
Lianchun Song
,
Peter A. Stott
, and
Blair Trewin

No abstract available.

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Paul Poli
,
Dick P. Dee
,
Roger Saunders
,
Viju O. John
,
Peter Rayer
,
Jörg Schulz
,
Kenneth Holmlund
,
Dorothee Coppens
,
Dieter Klaes
,
James E. Johnson
,
Asghar E. Esfandiari
,
Irina V. Gerasimov
,
Emily B. Zamkoff
,
Atheer F. Al-Jazrawi
,
David Santek
,
Mirko Albani
,
Pascal Brunel
,
Karsten Fennig
,
Marc Schröder
,
Shinya Kobayashi
,
Dieter Oertel
,
Wolfgang Döhler
,
Dietrich Spänkuch
, and
Stephan Bojinski

Abstract

To better understand the impacts of climate change, environmental monitoring capabilities must be enhanced by deploying additional and more accurate satellite- and ground-based (including in situ) sensors. In addition, reanalysis of observations collected decades ago but long forgotten can unlock precious information about the recent past. Historical, in situ observations mainly cover densely inhabited areas and frequently traveled routes. In contrast, large selections of early meteorological satellite data, waiting to be exploited today, provide information about remote areas unavailable from any other source. When initially collected, these satellite data posed great challenges to transmission and archiving facilities. As a result, data access was limited to the main teams of scientific investigators associated with the instruments. As archive media have aged, so have the mission scientists and other pioneers of satellite meteorology, who sometimes retired in possession of unique and unpublished information.

This paper presents examples of recently recovered satellite data records, including satellite imagery, early infrared hyperspectral soundings, and early microwave humidity soundings. Their value for climate applications today can be realized using methods and techniques that were not yet available when the data were first collected, including efficient and accurate observation simulators and data assimilation into reanalyses. Modern technical infrastructure allows serving entire mission datasets online, enabling easy access and exploration by a broad range of users, including new and old generations of climate scientists.

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