E-WP0 - ECO: Module E COordination

ECO covers the coordination of the Module E; it integrates the individual evaluation efforts and organizes scientific exchanges with the other modules and WPs in MiKlip II. Stakeholder/end-user interaction required for the orientation of the evaluation system to end-user needs will be ensured in cooperation with module D, involving individual work packages as needed.

Beside the coordination of Module E, ECO has following scientific contributions:

As bias and drift correction become more relevant for all validation activities, ECO will implement a drift correction framework based on generalized linear models (GLMs). The framework includes a drift correction which is initialization time dependent. It shall be developed and implemented into the Central Evaluation System (CES). Together with WP E-6 DROUGHTCLIP, the GLM-based framework will be extended to skewed and positive variables, to be particularly suited for precipitation (WP E-2 DAPAGLOCO, WP E-5 PROMISA), humidity (WP E-1 MOSQUITO) or wind. Furthermore, calibration of probabilistic forecasts to increase reliability is an important issue in MiKlip II. Different calibration approaches will be developed in Module E within WP E-8 PROVESIMAC and WP E-9 CALIBRATION. Together with bias and drift correction, calibration of forecast will contribute to general post-processing methodologies which will be coordinated by ECO. Predictive skill is assumed not only to vary with lead time but also with season and/or with the phase of low-frequency climate modes, like Atlantic multidecadal variability (AMV), Atlantic meridional overturning circulation (AMOC), and Pacific decadal oscillation (PDO). Skill estimation stratified along these influences will be a valuable contribution to the general skill estimation but also for processoriented validation. Therefore ECO will implement CES plug-ins for stratified verification.

Goals

  • focusing end-user needs concerning the evaluation system for the transferof predictions towards a user-oriented operational system
  • development of bias and drift correction frameworks and coordination of calibration approaches of probabilistic forecasts
  • implementing frameworks for stratified verification