CL5.02
Climate Data Homogenization and Analysis of Climate Variability, Trends and Extremes
Convener: Cesar Azorin-Molina | Co-conveners: Enric Aguilar, Rob Roebeling, Xiaolan Wang
Orals
| Tue, 09 Apr, 08:30–10:15, 10:45–12:30, 14:00–15:45
 
Room 0.14
Posters
| Attendance Mon, 08 Apr, 10:45–12:30
 
Hall X5

Accurate and homogeneous long-term data records (i.e., 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 needs accurate and homogenized/harmonized data records (i.e., data records in which the unique nature of each sensor is maintained). Temporal changes, such as degradation of instruments, changes of instruments, changes of observation practices, or changes of station location and exposure, cause artificial non-climatic sudden or gradual changes in data records. The magnitude and uncertainty of these changes impact the results of climate trend analyses. Therefore, data intended for applications, such as making a realistic and reliable assessment of historical climate trends and variability, require to be homogenized or harmonized consistently so as to obtain well calibrated data records including measurement uncertainties.

The above described factors influence the quality of different essential climate variables, including atmospheric (e.g., air temperature, precipitation, wind speed), oceanic (e.g., sea surface temperature), and terrestrial (e.g., albedo, snow cover) variables from in-situ observing networks, satellite observing systems, and climate/earth-system model simulations. Our session calls for contributions related to the:

• Calibration, quality control, homogenization/harmonisation and validation of either fundamental or essential climate data records.

• 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. In particular, we encourage wind studies dealing with the observed slowdown (termed “stilling”) of near-surface winds in the last 30-50 years.