Attributing correlation skill of dynamical GCM precipitation forecasts to statistical ENSO teleconnection using a set-theory-based approach

Abstract. Climate teleconnections are essential for the verification of valuable precipitation forecasts generated by global climate models (GCMs). This paper develops a novel approach to attributing correlation skill dynamical GCM statistical El Niño–Southern Oscillation (ENSO) teleconnection using coefficient determination (R2). Specifically, observed is respectively regressed against forecasts, Niño3.4 and both them, then intersection operation implemented quantify overlapping R2 Niño3.4. The significance sign ENSO facilitate three cases attribution, i.e., significantly positive anomaly attributable teleconnection, negative not teleconnection. A case study devised Forecast System version 2 (CFSv2) seasonal precipitation. For grid cells around world, ratio (negative) 10.8 % (11.7 %) in December–January–February (DJF), 7.1 (7.3 March–April–May (MAM), 6.3 (7.4 June–July–August (JJA) 7.0 (14.3 September–October–November (SON). results only confirm prominent contributions but also present spatial plots regions where subject other than ENSO. Overall, proposed attribution can serve as an effective tool investigate sources predictability