Thursday, 7 January 2016

Interesting EGU sessions and conferences in 2016

Just a quick post to advertise some interesting (new) EGU sessions and conferences this year.

At EGU there will be four interesting sessions that fit to the topic of this blog. The abstract deadline is already next Wednesday, the 13th of January at 13 CET. The conference is half April in Vienna, Austria.

Climate Data Homogenization and Climate Trend and Variability Assessment
The main session for all things homogenization.

Taking the temperature of Earth: Variability, trends and applications of observed surface temperature data across all domains of Earth's surface
On measuring temperatures: surface itself (skin temperature), surface air over land, see surface temperature, marine air temperature. With a large range of observational methods, including satellites.

Transition into the Anthropocene-causes of climate change in the 19th and 20th century
A session on climate change in the very challenging early instrumental period, where the variability of station observations has large uncertainties. This session is new, as far as I can see. But EGU is big, I hope I did not miss it last year.

Historical Climatology
Even further back in time is the session on historical climatology where people mainly look at non-instrumental evidence of climatic changes and their importance for human society.

Also this year there will be an EMS conference. Like every second year, in 2016 it will be combined with the European Conference on Applied Climatology (ECAC) and thus has more climate goodies than average. This year it will be half September in Trieste, Italy.

The main session for fans of homogenization is: Climate monitoring; data rescue, management, quality and homogenization.

Fans of variability may like the session on Spatial Climatology.

A conference I really enjoyed the last two times I was there is the International Meeting on Statistical Climatology. Its audience is half statisticians and half climatologists. Everyone loves beautiful statistical and methodological questions. Great!! This year is will be in June in Canmore, Alberta, Canada.

It also has a session on homogenization: Climate data homogenization and climate trends/variability assessment.

If I missed any interesting sessions or conferences do let us know in the comments (also if it is your own).




Descriptions

Climate Data Homogenization and Climate Trend and Variability Assessment
Convener: Xiaolan L. Wang
Co-Conveners: Enric Aguilar, Rob Roebeling, and Petr Stepanek

The accuracy and homogeneity of climate data are indispensable for many aspects of climate research. In particular, a realistic and reliable assessment of historical climate trends and variability is hardly possible without a long-term, homogeneous time series of climate data. Accurate and homogeneous climate data are also indispensable for the calculation of related statistics that are needed and used to define the state of climate and climate extremes. Unfortunately, many kinds of changes (such as instrument and/or observer changes, and changes in station location and environment, observing practices and procedure, etc.) that took place in the period of data record could cause non-climatic changes (artificial shifts) in the data time series. Such artificial shifts could have huge impacts on the results of climate analysis, especially those of climate trend analysis. Therefore, artificial changes shall be eliminated, to the extent possible, from the time series prior to its application, especially its application in climate trends assessment.

This session calls for contributions that are related to bias correction and homogenization of climate data, including bias correction and validation of various climate data from satellite observations and from GCM and RCM simulations, as well as quality control/assurance of observations of various variables in the Earth system. It also calls for contributions that use high quality, homogeneous climate data to assess climate trends and variability and to analyze climate extremes, including the use of bias-corrected GCM or RCM simulations in statistical downscaling. This session will include studies that inter-compare different techniques and/or propose new techniques/algorithms for bias-correction and homogenization of climate data, for assessing climate trends and variability and analysis of climate extremes (including all aspects of time series analysis), as well as studies that explore the applicability of techniques/algorithms to data of different temporal resolutions (annual, monthly, daily) and of different climate elements (temperature, precipitation, pressure, wind, etc) from different observing network characteristics/densities, including various satellite observing systems.



Transition into the Anthropocene-causes of climate change in the 19th and 20th century
Convener: Gabriele Hegerl
Co-Convener: Stefan Brönnimann

This session focuses on the long view of climate variability and change as available from long records, reconstructions, reanalysis efforts and modelling, and we welcome analysis of temperature, precipitation, extreme events, sea ice, and ocean. Contributions are welcome that evaluate changes from historical data on the scale of large regions to the globe, analyse particular unusual climatic events, estimate interdecadal climate variability and climate system properties from long records, attribute causes to early observed changes and model or data assimilate this period. We anticipate that bringing observational, modelling and analysis results together will improve understanding and prediction of the interplay of climate variability and change. "



Taking the temperature of Earth: Variability, trends and applications of observed surface temperature data across all domains of Earth's surface
See also their homepage.
Convener: Darren Ghent
Co-Conveners: Nick Rayner, Stephan Matthiesen, Simon Hook, G.C. Hulley, Janette Bessembinder


Surface temperature (ST) is a critical variable for studying the energy and water balances of the Earth surface, and underpinning many aspects of climate research and services. The overarching motivation for this session is the need for better understanding of in-situ measurements and satellite observations to quantify ST. The term "surface temperature" encompasses several distinct temperatures that differently characterize even a single place and time on Earth’s surface, as well as encompassing different domains of Earth’s surface (surface air, sea, land, lakes and ice). Different surface temperatures play inter-connected yet distinct roles in the Earth’s surface system, and are observed with different complementary techniques.

The EarthTemp network was established in 2012 to stimulate new international collaboration in measuring and better understanding ST across all domains of the Earth’s surface including air, land, sea, lakes, ice. New and existing international projects and products have evolved from network collaboration (e.g. ESA Climate Change Initiative SST project, EUSTACE, FIDUCEO, International Surface Temperature Initiative, ESA GlobTemperature, HadISST, CRUTEM and HadCRUT). Knowledge gained during this EarthTemp session will be documented and published as part of the user requirements exercises for such projects and will thus benefit the wider community. A focus of this session is the use of ST's for assessing variability and long-term trends in the Earth system. In addition there will be opportunity for users of surface temperature over any surface of Earth on all space and timescales to showcase their use of the data and their results, to learn from each others' practice and to communicate their needs for improvements to developers of surface temperature products. Suggested contributions can include, but are not limited to, topics like:

* The application of ST in climate science
* How to improve remote sensing of ST in different environments
* Challenges from changes of in-situ observing networks over time
* Current understanding of how different types of ST inter-¬relate
* Nature of errors and uncertainties in ST observations
* Mutual/integrated quality control between satellite and in-situ observing systems.
* What do users of surface temperature data require in practical applications?



Historical Climatology
Convener: Stefan Grab
Co-Conveners: Rudolf Brazdil, David Nash, Georgina Endfield


Historical Climatology has gained momentum and worldwide recognition over the last couple of decades, particularly in the light of rapid global climate and environmental change. It is now well recognized that in order to better project future changes and be prepared for those changes, one should look to, and learn from, the past. To this end, historical documentary sources, in many cases spanning back several hundred years and far beyond instrumental weather records, offer detailed descriptive (qualitative) accounts on past weather and climate. Such documentary sources typically include, amongst others: weather diaries, ship log books, missionary reports and letters, historical newspapers, chronicles, accounting and government documents etc. Such proxies have particular advantages in that they in most cases offer details on the specific timing and placement of an event. In addition, valuable insights may be gained on environmental and anthropogenic consequences and responses to specific weather events and climate anomaly. Similarly, oral history records, based on people’s personal accounts and experiences of past weather offer important insights on perceptions of climate change, and details on past and sometimes ‘forgotten’ weather events and their consequences.

This session welcomes all studies using documentary, historical instrumental and oral history based approaches to: produce historical climate chronologies (multi-decadal to centennial scale), gain insights into past climatic periods or specific weather events, detail environmental and human consequences to past climate and weather, share people’s experiences and perceptions of past climate, weather events and climate change, and reflect on lessons learnt (coping and adaptation) from past climate and weather events. Whilst welcoming contributions from all global regions, we particularly appeal for contributions from Asia and the Middle East.



Climate monitoring; data rescue, management, quality and homogenization
Convener: Manola Brunet-India
Co-Conveners: Hermann Mächel, Victor Venema, Ingeborg Auer, Dan Hollis


Robust and reliable climatic studies, particularly those assessments dealing with climate variability and change, greatly depend on availability and accessibility to high-quality/high-resolution and long-term instrumental climate data. At present, a restricted availability and accessibility to long-term and high-quality climate records and datasets is still limiting our ability to better understand, detect, predict and respond to climate variability and change at lower spatial scales than global. In addition, the need for providing reliable, opportune and timely climate services deeply relies on the availability and accessibility to high-quality and high-resolution climate data, which also requires further research and innovative applications in the areas of data rescue techniques and procedures, data management systems, climate monitoring, climate time-series quality control and homogenisation.

In this session, we welcome contributions (oral and poster) in the following major topics:

• Climate monitoring , including early warning systems and improvements in the quality of the observational meteorological networks

• More efficient transfer of the data rescued into the digital format by means of improving the current state-of-the-art on image enhancement, image segmentation and post-correction techniques, innovating on adaptive Optical Character Recognition and Speech Recognition technologies and their application to transfer data, defining best practices about the operational context for digitisation, improving techniques for inventorying, organising, identifying and validating the data rescued, exploring crowd-sourcing approaches or engaging citizen scientist volunteers, conserving, imaging, inventorying and archiving historical documents containing weather records

• Climate data and metadata processing, including climate data flow management systems, from improved database models to better data extraction, development of relational metadata databases and data exchange platforms and networks interoperability

• Innovative, improved and extended climate data quality controls (QC), including both near real-time and time-series QCs: from gross-errors and tolerance checks to temporal and spatial coherence tests, statistical derivation and machine learning of QC rules, and extending tailored QC application to monthly, daily and sub-daily data and to all essential climate variables

• Improvements to the current state-of-the-art of climate data homogeneity and homogenisation methods, including methods intercomparison and evaluation, along with other topics such as climate time-series inhomogeneities detection and correction techniques/algorithms (either absolute or relative approaches), using parallel measurements to study inhomogeneities and extending approaches to detect/adjust monthly and, especially, daily and sub-daily time-series and to homogenise all essential climate variables

• Fostering evaluation of the uncertainty budget in reconstructed time-series, including the influence of the various data processes steps, and analytical work and numerical estimates using realistic benchmarking datasets



Spatial Climatology
Convener: Ole Einar Tveito
Co-Conveners: Mojca Dolinar, Christoph Frei


Gridded representation of past and future weather and climate with high spatial and temporal resolution is getting more and more important for assessing the variability of and impact of weather and climate on various environmental and social phenomena. They are also indispensable as validation and calibration input for climate models. This increased demand requires new efficient methods and approaches for estimating spatially distributed climate data as well as new efficient applications for managing and analyzing climatological and meteorological information at different temporal and spatial scales. This session addresses topics related to generation and application of gridded climate data with an emphasis on statistical methods for spatial analysis and spatial interpolation applied on observational data.

An important aspect in this respect is the creation and further use of reference climatologies. The new figures calculated for the latest normal period 1981-2010 are now recommended as reference period for assessments of regional and local climatologies. For this period new observation types (e.g. satellite and radar data) are available, and contributions taking advantage of multiple data sources are encouraged.

Spatial analysis using e.g. GIS is a very strong tool for visualizing and disseminating climate information. Examples showing developments, application and products of such analysis for climate services are particularly welcome.

The session intends to bring together experts, scientists and other interested people analyzing spatio-temporal characteristics of climatological elements, including spatial interpolation and GIS modeling within meteorology, climatology and other related environmental sciences.



Climate data homogenization and climate trends/variability assessment
Convener: Xiaolan Wang, Lucie Vincent, Markus Donat and Lisa Alexander

The accuracy and homogeneity of climate data are indispensable for many aspects of climate research. In particular, a realistic and reliable assessment of historical climate trends and variability is hardly possible without a long-term, homogeneous time series of climate data. Accurate and homogeneous climate data are also indispensable for the calculation of related statistics that are needed and used to define the state of climate and climate extremes. Unfortunately, many kinds of changes (such as instrument and/or observer changes, and changes in station location and exposure, observing practices and procedure, etc.) that took place in the period of data record could cause non-climatic sudden changes (artificial shifts) in the data time series. Such artificial shifts could have huge impacts on the results of climate analysis, especially those of climate trend analysis. Therefore, artificial changes shall be eliminated, to the extent possible, from the time series prior to its application, especially its application in climate trends assessment.

This session calls for contributions that are related to bias correction and homogenization of climate data, including bias correction and validation of various climate data from satellite observations and from GCM and RCM simulations, as well as quality control/assurance of observations of various variables in the Earth system. It also calls for contributions that use high quality, homogeneous climate data to assess climate trends and variability and to analyze climate extremes, including the use of bias-corrected GCM or RCM simulations in statistical downscaling.

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