The sustainability of wave energy linked to the intra- and inter-annual variability in wave climate is crucial in wave resource assessment. In this study, we quantify the dependency of stability of wave energy flux (power) on long-term variability of wind and wave climate to detect a relationship between them. We used six decades of re-analysis wind and simulated wave climate in the entire globe and using two 30-yearly periods, we showed that not only the previously suggested minimum period of 10 years for wave energy assessment appears to be insufficient for detecting the influence of climate variability, but also the selection period for wave energy assessment can lead to an over/underestimation of about 25% for wave power. In addition, we quantified the dependency of rates of change of wave power, wind speed and wave parameters and showed that the change in wave power is mainly a function of change in swell wave climate globally. Finally, we redefined the suitability of global hotspots for wave energy extraction using intra-annual fluctuation, long-term change, and the available wave power for the period of six decades. The results highlight the importance of climate variability in resource assessment, sustainability, and prioritizing the hotspots for future development. 

https://www.nature.com/articles/s41598-022-18935-w.pdf

Linking the long-term variability in global wave energy to swell climate and redefining suitable coasts for energy exploitation

Abstract The rapid decline in Pacific cod ( Gadus macrocephalus , Gadidae) biomass following multiple Gulf of Alaska marine heatwaves (2014–2016 and 2019) may be one of the most dramatic documented changes in a sustainably managed marine fishery. As such, fisheries managers are exploring new recruitment paradigms for Pacific cod under novel environmental conditions. In this review, we address the challenges of managing and forecasting Pacific cod populations in the Eastern Pacific where thermal habitats for early life stages are undergoing varying rates of change across space and time. We use observational data to examine changes in distribution, abundance and demographics of the population from 1993 to 2020, and model contemporary and future changes of thermal habitat for both spawning success and age‐0 juvenile growth potential. Results indicate that reduced spawning habitat and early life stage abundance may be a precursor to regional population decline, but the recent apparent increases in size‐at‐age of pre‐recruits will have unknown impacts on future recruitment in these regions. We contend that continued monitoring of early life stages will be necessary to track changes in phenology and growth that likely determine size‐at‐age and the survival trajectories of year classes into the adult population. These include complex size‐ and temperature‐dependent energetics spanning seasonal habitats through the first winter. Climate‐ready management of Pacific cod will, therefore, require new process investigations beyond single‐season surveys focused on one‐life stage. 

Pacific cod in the Anthropocene: An early life history perspective under changing thermal habitats

Advances in satellite observation have improved our capacity to track changes in the ocean with numerous ecological and conservation applications, which are yet under-explored for coastal ecology. In this study, we assessed the spatio-temporal dynamics in invertebrate larval recruitment and the Seascape Pelagic Habitat Classification, a satellite remote-sensing product developed by the Marine Biodiversity Observation Network (MBON) and delivered by the US National Oceanic and Atmospheric Administration to monitor biodiversity globally. Our ultimate goal was to identify and predict changes in coastal benthic assemblages at tropical reefs in the SW Atlantic based on integrated pelagic conditions, testing the use of MBON Seascape categorization. Our results revealed that the pelagic Seascapes correlated with monthly and seasonal variations in recruitment rates and assemblage composition. Recruitment was strongly influenced by subtropical Seascapes and was reduced by the presence of warm waters with high-nutrient contents and phytoplankton blooms, which are likely to affect reef communities in the long term. Recruitment modeling indicates that Seascapes may be more efficient than sea surface temperature in predicting benthic larval dynamics. Based on historical Seascape patterns, we identified seven events that may have impacted benthic recruitment in this region during the last decades. These findings provide new insights into the application of novel satellite remote-sensing Seascape categorizations in benthic ecology and evidence how reef larval supply in the SW Atlantic could be impacted by recent and future ocean changes. 

/pdf/reef-larval-recruitment-in-response-to-seascape-dynamics-in-3iwh62va.pdf

Reef larval recruitment in response to seascape dynamics in the SW Atlantic

Linking multiple stressor science to policy opportunities through network modeling

Thailand is located in the Southeast Asian region, where the summer rainfall exhibits strong interannual variability, and the successful simulation of rainfall variation in Thailand by current climate models remains a challenge. Therefore, this paper evaluates the capability of the state-of-the-art Atmospheric GCM of the Institute of Atmospheric Physics (IAP-AGCM) in simulating summer rainfall over Thailand by comparing the model’s results with ground-truth observation during 1981–2012. Generally, the model shows a certain skill in reproducing the observed spatial distribution of the summer rainfall climatology and its interannual variability over Thailand, although the model underestimated both rainfall amount and its variability. Using Empirical Orthogonal Function (EOF) analysis, it is found that the IAP climate model reproduced creditably the spatial patterns of the first three dominant modes of summer rainfall in Thailand, whereas it underestimated the explained variance of the observed EOF-1 and overestimated the explained variance of the observed EOF-2 significantly. It was further found that the correlation between the observed rainfall anomalies in Thailand and the Niño3.4 index can be reproduced by the IAP model. However, the observed negative correlation is largely underestimated by the IAP climate model, and this could be the reason for the underestimation of explained variance of the EOF-1 by the IAP model. The evaluation results would be of great importance for further model improvement and thus potential application in seasonal prediction in the region.

/pdf/simulation-of-summer-rainfall-in-thailand-by-iap-agcm4-1-ttlzitwe.pdf

Simulation of Summer Rainfall in Thailand by IAP-AGCM4.1

Climate change is expected to warm, deoxygenate, and acidify ocean waters. Global climate models (GCMs) predict future conditions at large spatial scales, and these predictions are then often used to parameterize laboratory experiments designed to assess biological and ecological responses to future change. However, nearshore ecosystems are affected by a range of physical processes such as tides, local winds, and surface and internal waves, causing local variability in conditions that often exceeds global climate models. Predictions of future climatic conditions at local scales, the most relevant to ecological responses, are largely lacking. To fill this critical gap, we developed a 2D implementation of the Regional Ocean Modeling System (ROMS) to downscale global climate predictions across all Representative Concentration Pathway (RCP) scenarios to smaller spatial scales, in this case the scale of a temperate reef in the northeastern Pacific. To assess the potential biological impacts of local climate variability, we then used the results from different climate scenarios to estimate how climate change may affect the survival, growth, and fertilization of a representative marine benthic invertebrate, the red abalone Haliotis rufescens, to a highly varying multi-stressor environment. We found that high frequency variability in temperature, dissolved oxygen (DO), and pH increases as pCO2 increases in the atmosphere. Extreme temperature and pH conditions are generally not expected until RCP 4.5 or greater, while frequent exposure to low DO is already occurring. In the nearshore environment simulation, strong RCP scenarios can affect red abalone growth as well as reduce fertilization during extreme conditions when compared to global scale simulations.

/pdf/downscaling-global-ocean-climate-models-improves-estimates-o1qaouhaf1.pdf

Downscaling global ocean climate models improves estimates of exposure regimes in coastal environments

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Downscaling global ocean climate models improves estimates of exposure regimes in coastal environments