Homogeneous long-term data records (i.e., well calibrated quality-controlled data that are forced to look like a common reference) are essential for researching, monitoring, or attenuating changes in climate, for example to describe the state of climate or to detect climate extremes. Likewise, reanalysis requires harmonized data records (i.e., well calibrated quality-controlled data that maintained the unique nature of each sensor). Climate data records need to be screened and cleared from artificial non-climatic temporal and/or spatial effects, such as gradual degradation of instruments, jumps due to instruments changes, jumps due to observation practices changes, or jumps due to changes of station location and exposure. The magnitude and uncertainty of these gradual and/or abrupt changes determines their suitability for climate trend analyses. Therefore, data intended for applications, such as making a realistic and reliable assessment of historical climate trends and variability, require consistently homogenized and/or harmonized data records including measurement uncertainties.
The above described artificial non-climatic effects influence the quality of different Essential Climate Variables (ECVs), including atmospheric (e.g., air temperature, precipitation, wind speed), oceanic (e.g., sea surface temperature), and terrestrial (e.g., albedo, snow cover) variables.
Our session calls for contributions, using data records from i) in-situ observing networks, ii) satellite observing systems, iii) reanalysis products, and/or iii) climate/earth-system model simulations based data records, on the:
• calibration, quality control, homogenization/harmonization and validation of either Fundamental Climate Data Records (FCDRs) and/or Essential Climate Variables data records (CDRs);
• development of new data records and their analysis (spatial and temporal characteristics, particularly of extremes);
• examination of observed trends and variability, as well as studies that explore the applicability of techniques/algorithms to data of different temporal resolutions (annual, seasonal, monthly, daily, and sub-daily);
• rescue and analysis of centennial meteorological observations, with focus on data prior to the 1960s, as a unique source to fill in the gap of knowledge of climate variability over century time-scales.