This experiment contains an instance of the analog weather generator unseen-awg (Version 1.0) and over 10,000 years of artificial time series generated with unseen-awg for European weather under present-day climate conditions. Long simulations of artificial weather data help studying the weather-related risks across many sectors.
The simulations are composed of 500 21-year-long daily time series and stored as look-up tables. They can be expanded into multivariate spatiotemporal data using the provided reforecast dataset of impact-relevant meteorological variables.
The provided unseen-awg generator instance uses default parameter settings. It can be loaded using the corresponding Python class. The instance includes a large dataset of pre-computed similarities. Compared to using unseen-awg without pre-computation, this enables substantially faster simulations.
Wider, Jonathan; Zscheischler, Jakob (2026). An instance of the analog weather generator unseen-awg with precomputed similarities and a large set of generated weather data. World Data Center for Climate (WDCC) at DKRZ. https://doi.org/10.26050/WDCC/unsawg_wg
SQA - Scientific Quality Assurance 'approved by author'
Result Date
2026-04-21
Technical Quality Assurance (TQA)
TQA - Technical Quality Assurance 'approved by WDCC'
Description
1. Number of data sets is correct and > 0: passed; 2. Size of every data set is > 0: passed; 3. The data sets and corresponding metadata are accessible: passed; 4. The data sizes are controlled and correct: passed; 5. The format is correct: passed; 6. Variable description and data are consistent: passed
Method
WDCC-TQA checklist
Method Description
Checks performed by WDCC. The list of TQA metrics are documented in the 'WDCC User Guide for Data Publication' Chapter 8.1.1