Dear community,
during the last years, we have gathered a lot of experience with SEAS5 in multiple projects. When we've calculated categorical forecasts, we simply related actual forecasts to some climatology. And this climatology was based on the combination of all 25 ensemble members from a particular issue month during a reference period (e.g., 1981 to 2010). Now, we need to shift our reference period to match WMOs new suggestion (i.e, 1991 to 2020, https://public.wmo.int/en/media/news/updated-30-year-reference-period-reflects-changing-climate). This means that we have to combine the forecasts before 2017 with 25 members with forecasts from 2017 with 51 members. Therefore, we can not simply merge the forecasts as the duplication of the ensemble size from 2017 would obviously lead to a bias towards the years 2017 to 2020.
Are there any "official" suggestions or approaches on this particular issue? Or is there probably a community solution about how to derive a forecast climatology from forecasts where the size of the ensemble changes over time?
Best regards and thank you very much in advance,
Christof Lorenz