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Marine heatwaves (MHWs) are becoming increasingly common, with devastating ecosystem impacts. However, MHW understanding has almost exclusively relied on sea surface temperature with limited knowledge about their subsurface characteristics. Here we estimate global MHWs from the surface to 2,000 m depth, covering the period 1993–2019, and explore biodiversity exposure to their effects. We find that MHWs are typically more intense in the subsurface at 50–200 m and their duration increases up to twofold with depth, although with large spatial variability linked to different oceanographic conditions. Cumulative intensity (a thermal stress proxy) was highest in the upper 250 m, exposing subsurface biodiversity to MHW effects. This can be particularly concerning for up to 22% of the ocean, where high cumulative intensity overlapped the warm range edge of species distributions, thus being more sensitive to thermal stress. Subsurface MHWs can hence drive biodiversity patterns, with consequent effects on ecological interactions and ecosystem processes.The authors estimate the intensity, duration and number of global marine heatwaves from 1993 to 2019, from the surface to 2,000 m. They show generally higher intensity of marine heatwaves at 50–200 m, but increased duration with depth, and predict ocean regions of higher biodiversity exposure.

Recent mass loss from ice sheets and ice shelves is now persistent and prolonged enough that it impacts downstream oceanographic conditions. To demonstrate this, we use an ensemble of coupled GISS‐E2.1‐G simulations forced with historical estimates of anomalous freshwater, in addition to other climate forcings, from 1990 through 2019. There are detectable differences in zonal‐mean sea surface temperatures (SST) and sea ice in the Southern Ocean, and in regional sea level around Antarctica and in the western North Atlantic. These impacts mostly improve the model's representation of historical changes, including reversing the forced trends in Antarctic sea ice. The changes in SST may have implications for estimates of the SST pattern effect on climate sensitivity and for cloud feedbacks. We conclude that the changes are sufficiently large that model groups should strive to include more accurate estimates of these drivers in all‐forcing historical simulations in future coupled model intercomparisons. Plain Language Summary Simulations of recent historical periods are a key test of climate model reliability and skill. These model simulations require an accounting of all the drivers of climate change. We show that the impact of historical changes in freshwater fluxes from ice sheets and ice shelves on the ocean (through changes in salinity and stratification) are detectable in sea surface temperature and sea ice trends, and help improve the match between the modeled climate changes and observations. We recommend that more accurate estimates of these drivers be included in all climate simulations that do not explicitly model ice sheets and ice shelves. Key Points The response to anomalous meltwater from ice sheets and shelves is large enough for it to be a forcing in historical climate simulations When the GISS model includes these drivers, Southern Ocean SST and sea ice trends better match observations Steric and dynamic impacts on regional sea level in parts of the North Atlantic and coastal Antarctica are significant

Bull kelp, Nereocystis luetkeana , is an iconic kelp forest species of the Northeast Pacific that provides a wide range of ecosystem services to coastal marine species and society. In northern California, U.S.A., Nereocystis abundance declined sharply in 2014 and has yet to recover. While abiotic and biotic stressors were present prior to 2014, the population collapse highlights the need for a better understanding of how environmental conditions impact Nereocystis . In this study, we used a newly-developed, satellite-based dataset of bull kelp abundance, proxied by canopy cover over 20 years, to test the hypothesis that winter oceanographic conditions determine summer Nereocystis canopy cover. For the years before the collapse (1991 through 2013), wintertime ocean conditions, synthesized in a Multivariate Ocean Climate Indicator (MOCI), were indeed a good predictor of summer Nereocystis canopy cover (R 2 = 0.40 to 0.87). We attribute this relationship to the effects of upwelling and/or temperature on nutrient availability. South of Point Arena, California, winter ocean conditions had slightly lower explanatory power than north of Point Arena, also reflective of spring upwelling-driven nutrient entrainment. Results suggest that the Nereocystis gametophytes and/or early sporophytes are sensitive to winter oceanographic conditions. Furthermore, environmental conditions in winter 2014 could have been used to predict the Nereocystis collapse in summer 2014, and for kelp north of Point Arena, a further decline in 2015. Importantly, environmental models do not predict changes in kelp after 2015, suggesting biotic factors suppressed kelp recovery, most likely extreme sea urchin herbivory. Conditions during winter, a season that is often overlooked in studies of biophysical interactions, are useful for predicting summer Nereocystis kelp forest canopy cover, and will be useful in supporting kelp restoration actions in California and perhaps elsewhere in the world.

Species distribution models (SDMs) are increasingly applied in conservation management to predict suitable habitat for poorly known populations. High predictive performance of SDMs is evident in validations performed within the model calibration area (interpolation), but few studies have assessed SDM transferability to novel areas (extrapolation), particularly across large spatial scales or pelagic ecosystems. We performed rigorous SDM validation tests on distribution data from three populations of a long-ranging marine predator, the grey petrel Procellaria cinerea, to assess model transferability across the Southern Hemisphere (25-65°S). Oceanographic data were combined with tracks of grey petrels from two remote sub-Antarctic islands (Antipodes and Kerguelen) using boosted regression trees to generate three SDMs: one for each island population, and a combined model. The predictive performance of these models was assessed using withheld tracking data from within the model calibration areas (interpolation), and from a third population, Marion Island (extrapolation). Predictive performance was assessed using k-fold cross validation and point biserial correlation. The two population-specific SDMs included the same predictor variables and suggested birds responded to the same broad-scale oceanographic influences. However, all model validation tests, including of the combined model, determined strong interpolation but weak extrapolation capabilities. These results indicate that habitat use reflects both its availability and bird preferences, such that the realized distribution patterns differ for each population. The spatial predictions by the three SDMs were compared with tracking data and fishing effort to demonstrate the conservation pitfalls of extrapolating SDMs outside calibration regions. This exercise revealed that SDM predictions would have led to an underestimate of overlap with fishing effort and potentially misinformed bycatch mitigation efforts. Although SDMs can elucidate potential distribution patterns relative to large-scale climatic and oceanographic conditions, knowledge of local habitat availability and preferences is necessary to understand and successfully predict region-specific realized distribution patterns.

Holocene temperature evolution remains poorly understood. Proxies in the early and mid‐Holocene suggest a Holocene Thermal Maximum (HTM) where temperatures exceed the pre‐industrial, whereas climate models generally simulate monotonic warming. This discrepancy may reflect proxy seasonality biases or errors in climate model internal feedbacks or dynamics. Using seasonally unbiased ice core reconstructions at NEEM, NGRIP, and Greenland Ice Sheet Project 2, we identify a Greenland HTM of ∼2°C above pre‐industrial, in agreement with other Northern Hemisphere proxy reconstructions. The firn‐based reconstructions are verified through borehole thermometry, producing a multi‐core, multi‐proxy reconstruction of Greenland climate from the last glacial to pre‐industrial. HTM timing across Greenland is heterogenous, occurring earlier at high elevations. Total air content measurements suggest a temperature contribution from elevation changes; regional oceanographic conditions, a weakened polar lapse rate, or variable near‐surface inversions may also be important sensitivities. Our reconstructions support climate simulations with dynamic Holocene vegetation, highlighting the importance of vegetation feedbacks. Plain Language Summary Climate change during the Holocene, the current geological time period, is important to understand. This period began ∼11.7 thousand years ago and contains the transition from the last ice age to today. Simulations of this transition suggest that global climate continued to warm across this whole period. Proxy evidence, however, tends to suggest that warmer‐than‐modern temperatures were reached at the start of the Holocene, followed by gradual cooling. Resolving this dispute in our recent climatological past is important to verify climate model behavior, and understand nuances in proxy records. Using ice core reconstructions of Greenland climate, which broadly follows northern high‐latitude climate, we lend further support to a warm period in the early Holocene. These new records are spread across Greenland, allowing for the spatial fingerprint of this warm period to be identified. Key Points We identify a Holocene Thermal Maximum (HTM) across three Greenland ice cores of 1.6–2.6°C above pre‐industrial The HTM has a south‐to‐north difference in timing, beginning earlier at Greenland Ice Sheet Project 2 in the south (9.9 ka) and later at NEEM in the north (6.85 ka) Total air content suggests that deglacial elevation change contributes to this timing difference, but cannot fully explain observed trends

The cold temperate and subtropical marine faunas of the Northeastern Pacific meet within California as part of one of the few eastern boundary upwelling ecosystems in the world. Traditionally, it is believed that Point Conception is the precise site of turnover between these two faunas due to sharp changes in oceanographic conditions. However, evidence from intraspecific phylogeography and species range terminals do not support this view, finding stronger biogeographic breaks elsewhere along the coast. Here I develop a new application of historical biogeographic approaches to uncover sites of transition between faunas without needing an a priori hypothesis of where these occur. I used this approach to determine whether the point of transition between northern and southern temperate faunas occurs at Point Conception or elsewhere within California. I also examined expert-vetted latitudinal range data of California fish species from the 1970s and the 2020s to assess how biogeography could change with the backdrop of climate change. The site of turnover was found to occur near Point Conception, in concordance with the traditional view. I suggest that recent species- and population-level processes could be expected to give signals of different events from historical biogeography, possibly explaining the discrepancy across studies. Species richness of California has increased since the 1970s, mostly due to species’s ranges expanding northward from Baja California (Mexico). Range shifts under warming conditions seem to be increasing the disparity between northern and southern faunas of California, creating a more divergent biogeography.

Antarctic ice shelves control the flow of ice into the ocean, affecting the rate of sea level rise. This flow is regulated by ice‐shelf thickness, which depends on tributary flux across the grounding line and the balance between surface accumulation and ocean‐induced melting. Consequently, ice shelves that are tributary‐sustained will be more susceptible to dynamic changes upstream of the grounding line. In contrast, atmospherically sustained ice shelves will be more susceptible to changing local atmospheric and oceanographic conditions. Our results differentiate between these internal and external regimes by mapping which ice shelves are tributary‐ and which are atmospherically sustained and we compare these findings with published estimates of local ice‐shelf buttressing strength. This approach identifies buttressing relevant areas, particularly near pinning points, in West Antarctica and the Peninsula, which are highly dependent on surface accumulation and therefore vulnerable to the predicted decline of coastal snowfall through the end of the century.

The California Current System (CCS) is a biologically productive Eastern Boundary Upwelling System that experiences considerable environmental variability on seasonal and interannual timescales. Given that this variability drives changes in ecologically and economically important living marine resources, predictive skill for regional oceanographic conditions is highly desirable. Here, we assess the skill of seasonal sea surface temperature (SST) forecasts in the CCS using output from Global Climate Forecast Systems in the North American Multi-Model Ensemble (NMME), and describe mechanisms that underlie SST predictability. A simple persistence forecast provides considerable skill for lead times up to ~4 months, while skill above persistence is mostly confined to forecasts of late winter/spring and derives primarily from predictable evolution of ENSO-related variability. Specifically, anomalously weak (strong) equatorward winds are skillfully forecast during El Niño (La Niña) events, and drive negative (positive) upwelling anomalies and consequently warm (cold) temperature anomalies. This mechanism prevails during moderate to strong ENSO events, while years of ENSO-neutral conditions are not associated with significant forecast skill in the wind or significant skill above persistence in SST. We find also a strong latitudinal gradient in predictability within the CCS; SST forecast skill is highest off the Washington/Oregon coast and lowest off southern California, consistent with variable wind forcing being the dominant driver of SST predictability. These findings have direct implications for regional downscaling of seasonal forecasts and for short-term management of living marine resources.

Potential intensity (PI) is the maximum speed limit of a tropical cyclone found by modeling the storm as a thermal heat engine. Because there are significant correlations between PI and actual storm wind speeds, PI is a useful diagnostic for evaluating or predicting tropical cyclone intensity climatology and variability. Previous studies have calculated PI given a set of atmospheric and oceanographic conditions, but although a PI algorithm – originally developed by Kerry Emanuel – is in widespread use, it remains under-documented. The Tropical Cyclone Potential Intensity Calculations in Python (pyPI, v1.3) package develops the PI algorithm in Python and for the first time details the full background and algorithm (line by line) used to compute tropical cyclone potential intensity constrained by thermodynamics. The pyPI package (1) provides a freely available, flexible, validated Python PI algorithm, (2) carefully documents the PI algorithm and its Python implementation, and (3) demonstrates and encourages the use of PI theory in tropical cyclone analyses. Validation shows pyPI output is nearly identical to the previous potential intensity computation but is an improvement on the algorithm's consistency and handling of missing data. Example calculations with reanalyses data demonstrate pyPI's usefulness in climatological and meteorological research. Planned future improvements will improve on pyPI's assumptions, flexibility, and range of applications and tropical cyclone thermodynamic calculations.

Over the vast area of present‐day Europe, the Tithonian–Berriasian transition was a time of climate aridization, which was supposedly related to the more general trend of the latest Jurassic–earliest Cretaceous cooling and restrictions in atmospheric circulation. Recent studies suggest that such conditions affected also some other paleoenvironmental processes such as monsoonal upwellings, seafloor ventilation and circulation of nutrients within the water column. In order to test this model, the uppermost Jurassic–lowermost Cretaceous sedimentary succession of the Slovenian Basin was correlated with a reference data from the Bakony Basin (Transdanubian Range, Hungary). Stratigraphic calibration was ensured by integrated stratigraphy, utilizing bio‐ (calpionellids, calcareous dinocysts) and chemostratigraphic tools (δ13C stratigraphy) as well as regional correlations of magnetic susceptibility and terrigenous input. Paleoclimate, paleoredox and paleoproductivity conditions were evaluated based on various geochemical proxies. Both the Slovenian and the Bakony basin sections were found to document late Tithonian–early Berriasian climate aridization as well as related signals of seafloor hypoxia and elevated accumulations of micronutrients. Significant geochemical contrast between the basal (lower Tithonian) radiolarites and overlying upper Tithonian–Berriasian carbonates evidences the inverse relation between the surface productivity and the amount of nutrient‐type trace metals buried in sediments. The rhythm of paleoclimatically controlled environmental changes, with relatively humid early Tithonian, arid late Tithonian–early Berriasian, and again humid late Berriasian, correlates with those estimated for Vocontian Basin (SE France) and the Sub‐Boreal domain of Western and Central Europe. This indicates that climatic stratigraphy is a useful tool for global correlation of the Jurassic/Cretaceous boundary interval. Plain Language Summary During the Mesozoic, much of the present‐day Alpine orogenic belt (Alps–Carpathians–Dinarides) constituted the westernmost part of the so‐called Neotethys Ocean. Recent studies suggest that the gradual cooling during the Jurassic/Cretaceous transition affected this area by weakening of monsoons, what caused significant aridization. In addition, changes in atmospheric circulation are thought to have had an impact also on oceanographic conditions and the intensity of (wind‐induced) upwelling currents among others. In this study, we attempt to test the above model by comparing the geochemical signals obtained from sedimentary successions of western Slovenia (Slovenian Basin) and western Hungary (Transdanubian Range). Our study confirms the hypothesis that late Tithonian–early Berriasian (ca. 145–140 Ma) climate aridization was associated with less intense mixing of the water column. This, in turn, limited the availability of oxygen at the seafloor on one hand, and increased the burial of nutrients on the other. Accordingly, the results of this study not only provide new data on the latest Jurassic–earliest Cretaceous sedimentary trends and events but also contribute to our understanding of a complex relationships between the state of atmosphere (climate) and its impact on marine environments and support the global definition of the Jurassic/Cretaceous boundary. Key Points Geochemical contrast between radiolarites and limestones evidences the inverse relation between surface productivity and nutrient burial Arid climate of the Tithonian–Berriasian transition was associated with seafloor hypoxia and elevated accumulations of micronutrients A minor, but well pronounced peak in δ13C is characteristic for the lower/upper Berriasian boundary interval