This white paper summarizes the background, the need, and proposed implementation strategy for a national multi-model ensemble (NMME) system for operational intra-seasonal to interannual (ISI) climate prediction. The proposed strategy includes implementation of an experimental NMME protocol and designing and testing a future protocol for operational NMME prediction system. The protocols will le...

Improving water management in water stressed-regions requires reliable seasonal precipitation predication, which remains a grand challenge. Numerous statistical and dynamical model simulations have been developed for predicting precipitation. However, both types of models offer limited seasonal predictability. This study outlines a hybrid statistical-dynamical modeling framework for predicting ...

Abstract Ten years, 16 fully coupled global models, and hundreds of research papers later, the North American Multimodel Ensemble (NMME) monthly-to-seasonal prediction system is looking ahead to its second decade. The NMME comprises both real-time, initialized predictions a substantial database; retrospective real-time forecasts are archived freely available for development. Many U.S.-based int...

The Atlantic Niño/Niña, one of the dominant interannual variability in equatorial Atlantic, exerts prominent influence on Earth’s climate, but its prediction skill shown previously was unsatisfactory and limited to two three months. By diagnosing recently released North American Multimodel Ensemble (NMME) models, we find that Niño/Niña skills are improved, with multi-model ensemble (MME) reachi...

Abstract During the summer when an El Niño event is transitioning to a La Niña event, extratropical teleconnections exert robust warming anomalies over U.S. Midwest threatening agricultural production. This study assesses performance of current climate models in capturing prominent observed responses North America during summer, based on atmospheric general circulation model experiments and cou...

A Linear Inverse Model (LIM) is constructed to evaluate predictability of seasonal sea surface temperature (SST) and height (SSH) anomalies over the ice-free global ocean. Its ensemble-mean hindcast skill also compared that North American Multi-Model Ensemble (NMME) for 1982–2010. Both have similar dominant modes SST variability, but regional NMME somewhat higher in many locations. However, LIM...

The occurrence of high temperature and heavy rain events during the monsoon season are a major climate risk affecting aquaculture production in Bangladesh. Despite advances seasonal forecasting, development operational tools remains challenge. This work presents forecasting approach to predict number warm days (NWD) (NHRD) tailored two locations Bangladesh (Sylhet Khulna). is based on use meteo...