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This study evaluates the performance of 39 CMIP5 models participating in the Coordinated Ocean Wave Climate Project phase 2 (COWCLIP2.0) for simulating extreme significant wave height (SWH) indices in the Indian Ocean (IO) for the 26-year period from 1979 to 2005, using the ERA5 wave reanalysis as observation proxy. The multiple skill metrics of bias, root mean square error (RMSE), relative error (RE), interannual variability skill-score (IVS), comprehensive rating index (CRI), and total ranking (TR) are utilized to evaluate the CMIP5 models consisting of four clusters (ECCC(s), CSIRO, ECCC(d), and JRC) over the Northern IO (NIO), SouthernTropical IO (STIO), and Southern IO (SIO) sub-domains. The three extreme SWH indices are considered: rough wave days (HsRo), high wave days (HsHi), and top decile wave spell duration indicator (HHsDI). Climatology evaluation results indicate that the ECCC(s) cluster models and MME exhibit better agreements with the ERA5 reanalysis data (with smaller biases, RMSEs, and REs) than the other clusters over all sub-domains for HsRo and HsHi indices. Whereas most models display reasonable skills at simulating interannual variability of HsRo, HsHi is poorly captured by all clusters over the NIO and STIO, with a large inter-model spread in IVS values. HHsDI is found to be simulated well by all clusters regarding the climatology pattern and interannual variability, reflecting the characteristics of percentile-based indices. Integrated assessment based on CRI and TR analysis confirms the overall superiority of ECCC(s) cluster models in simulating mean and interannual variability of extreme SWH indices over all IO subdomains. [ABSTRACT FROM AUTHOR]

The El Niño-Southern Oscillation (ENSO) exerts significant influences on extreme significant wave height (SWH) but climate model capabilities in reproducing the observed ENSO impact on SWH have not been evaluated. This study assesses the performances of the Coupled Model Intercomparison Project phase 5 (CMIP5) models in term of extreme SWH responses to ENSO over the Indo-Pacific Ocean focusing on December-February (DJF). 18 CMIP5 models are evaluated using their historical simulations for 1950–2005 in view of the ERA-20C reanalysis. A non-stationary generalized extreme value (GEV) analysis is employed to fit DJF maxima of 6-hourly SWHs and obtain the extreme SWH response patterns to ENSO by incorporating Niño3.4 index as a covariate. Results show that CMIP5 models can on average capture the major observed mean and extreme SWH responses to ENSO, including the increased SWH over the northeastern North Pacific (NENP) and the decreased SWH over the Maritime Continent (MC) during El Niño. The inter-model relations between ENSO characteristics and SWH responses are further examined for the two hotspot regions (NENP and MC). It is found that ENSO intensity is a dominant factor determining simulated SWH over the NENP such that models with stronger ENSO simulate stronger SWH responses. In contrast, for the MC, the sea level pressure teleconnection pattern significantly affects the inter-model spread in SWH responses, also explaining the systematic underestimation of SWH responses over the region. Implication is that ENSO intensity and atmospheric teleconnection patterns need to be considered for better simulations and reliable predictions of extreme SWH variability. [ABSTRACT FROM AUTHOR]

In recent decades, wave power (WP) energy from the ocean is one of the cleanest renewable energy sources associated with oceanic warming. In Indo-Pacific Ocean, the WP is significantly influenced by natural climate variabilities, such as El Niño Southern Oscillation (ENSO), Indian Ocean Dipole (IOD), and Pacific Decadal Oscillation (PDO). In this study, the impact of major climate variability modes on seasonal extreme WP is examined over the period 1979–2019 using ERA5 reanalysis data and the non-stationary generalized extreme value analysis is applied to estimate the climatic extremes. Independent ENSO influence after removing the IOD impact (ENSO|IOD) on WP are evident over the northeast and central Pacific during December–February, and March–May, respectively, which subsequently shifts towards the western Pacific in June–August (JJA) and September–November (SON). The ENSO|PDO impact on WP exhibits similar yet weaker intensity year round compared to ENSO. Extreme WP responses due to the IOD|ENSO include widespread decreases over the tropical and eastern Indian Ocean, with localized increases only over South China and Philippine seas and Bay of Bengal during JJA, and the Arabian Sea during SON. Lastly, for the PDO|ENSO, the significant increases in WP are mostly confined to the Pacific, and most prominent in the North Pacific. Composite analysis of different phase combinations of PDO (IOD) with El Niño (La Niña) reveals stronger (weaker) influences year-round. The response patterns in significant wave height, peak wave period, sea surface temperatures, and sea level pressure help to explain the seasonal variations in WP. [ABSTRACT FROM AUTHOR]