Adaptation of Advanced Weather Forecast Verification tools to Climate Problems: Opportunities and Challenges
Slowly, conditional considerations and performance evaluations are making their way into the benchmarking and performance measurement domain of climate models. While model developers can certainly come up with a host of conditional links between fields, they often lack salience. Bringing in user perspectives, however, offers interesting and tested ways of identifying different ways to quantify the effects of good or poor performance across two or more variables. Users therefore indirectly know from their daily operations what the consequences are of a suite of conditional process links.
Here we use advanced weather forecast verification tools to capture the probabilistic nature of some climate problems. Object-based evaluations also provide good instruments to tackle different questions than what is traditionally done. When combined with conditional settings, then multi-variate context becomes an active part in the verification. In fact, some of the most integrated factors arise from such conditions, many of which might even remain unknown. Yet, they allow for more integrated insight into the processes that are to be captured and measured in their joint behavior. We demonstrate opportunities and challenges that emerged in the effort to adapt the weather forecast verification tools to climate problems when working with the water sector. It is investigated if not also new and creative tools could emerge for the climate domain.