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Over the first half of 2020, Siberia experienced the warmest period from January to June since records began and on the 20th of June the weather station at Verkhoyansk reported 38 °C, the highest daily maximum temperature recorded north of the Arctic Circle. We present a multi-model, multi-method analysis on how anthropogenic climate change affected the probability of these events occurring using both observational datasets and a large collection of climate models, including state-of-the-art higher-resolution simulations designed for attribution and many from the latest generation of coupled ocean-atmosphere models, CMIP6. Conscious that the impacts of heatwaves can span large differences in spatial and temporal scales, we focus on two measures of the extreme Siberian heat of 2020: January to June mean temperatures over a large Siberian region and maximum daily temperatures in the vicinity of the town of Verkhoyansk. We show that human-induced climate change has dramatically increased the probability of occurrence and magnitude of extremes in both of these (with lower confidence for the probability for Verkhoyansk) and that without human influence the temperatures widely experienced in Siberia in the first half of 2020 would have been practically impossible.

This paper describes version 3 of the Simple Ocean Data Assimilation (SODA3) ocean reanalysis with enhancements to model resolution, observation, and forcing datasets, and the addition of active sea ice. SODA3 relies on the ocean component of the NOAA/Geophysical Fluid Dynamics Laboratory CM2.5 coupled model with nominal ¼° resolution. A scheme has also been implemented to reduce bias in the surface fluxes. A 37-yr-long ocean reanalysis, SODA3.4.2, created using this new SODA3 system is compared to the previous generation of SODA (SODA2.2.4) as well as to the Hadley Centre EN4.1.1 no-model statistical objective analysis. The comparison is carried out in the tropics, the midlatitudes, and the Arctic and includes examinations of the meridional overturning circulation in the Atlantic. The comparison shows that SODA3.4.2 has reduced systematic errors to a level comparable to those of the no-model statistical objective analysis in the upper ocean. The accuracy of variability has been improved particularly poleward of the tropics, with the greatest improvements seen in the Arctic, accompanying a substantial reduction in surface net heat and freshwater flux bias. These improvements justify increasing use of ocean reanalysis for climate studies including the higher latitudes.

The Plankton, Aerosol, Cloud, ocean Ecosystem (PACE) mission represents the National Aeronautics and Space Administration’s (NASA) next investment in satellite ocean color and the study of Earth’s ocean–atmosphere system, enabling new insights into oceanographic and atmospheric responses to Earth’s changing climate. PACE objectives include extending systematic cloud, aerosol, and ocean biological and biogeochemical data records, making essential ocean color measurements to further understand marine carbon cycles, food-web processes, and ecosystem responses to a changing climate, and improving knowledge of how aerosols influence ocean ecosystems and, conversely, how ocean ecosystems and photochemical processes affect the atmosphere. PACE objectives also encompass management of fisheries, large freshwater bodies, and air and water quality and reducing uncertainties in climate and radiative forcing models of the Earth system. PACE observations will provide information on radiative properties of land surfaces and characterization of the vegetation and soils that dominate their ref lectance. The primary PACE instrument is a spectrometer that spans the ultraviolet to shortwave-infrared wavelengths, with a ground sample distance of 1 km at nadir. This payload is complemented by two multiangle polarimeters with spectral ranges that span the visible to near-infrared region. Scheduled for launch in late 2022 to early 2023, the PACE observatory will enable significant advances in the study of Earth’s biogeochemistry, carbon cycle, clouds, hydrosols, and aerosols in the ocean–atmosphere–land system. Here, we present an overview of the PACE mission, including its developmental history, science objectives, instrument payload, observatory characteristics, and data products.

In Part I of this study, the impact of Ural blocking (UB) on the warm Arctic–cold Eurasian (WACE) pattern associated with the winter (DJF) arctic sea ice loss during 1979–2013 is examined by dividing the arctic sea ice reduction region into two dominant subregions: the Barents and Kara Seas (BKS) and the North American high-latitude (NAH) region (Baffin and Hudson Bay, Davis Strait, and Labrador Sea). It is found that atmospheric response to arctic sea ice loss resembles a negative Arctic response oscillation with a dominant positive height anomaly over the Eurasian subarctic region. Regression analyses of the two subregions further show that the sea ice loss over the BKS corresponds to the UB pattern together with a positive North Atlantic Oscillation (NAO⁺) and is followed by a WACE anomaly, while the sea ice reduction in the NAH region corresponds to a negative NAO (NAO⁻) pattern with a cold anomaly over northern Eurasia. Further analyses reveal that the UB pattern is more persistent during the period 2000–13 (P2) than 1979–99 (P1) because of the reduced middle-to-high-latitude mean westerly winds over Eurasia associated with the intense BKS warming. During P2 the establishment of the UB becomes a slow process because of the role of the BKS warming, while its decay is slightly rapid. In the presence of the long-lived UB that often occurs with the NAO⁺, the BKS-warming-induced DJF-mean anticyclonic anomaly is intensified and widened and then expands southward during P2 to amplify the WACE pattern and induce the southward displacement of its cold anomaly and the further loss of the BKS sea ice. Thus, midlatitude Eurasian cold events should be more frequent as the sea ice loss continues over the BKS.

The ECMWF OCEAN5 system is a global ocean and sea-ice ensemble of reanalysis and real-time analysis. This paper gives a full description of the OCEAN5 system, with the focus on upgrades of system components with respect to its predecessors, ORAS4 and ORAP5. An important novelty in OCEAN5 is the ensemble generation strategy that includes perturbation of initial conditions and a generic perturbation scheme for observations and forcing fields. Other upgrades include revisions to the a priori bias correction scheme, observation quality control and assimilation method for sea-level anomalies. The OCEAN5 historical reconstruction of the ocean and sea-ice state is the ORAS5 reanalysis, which includes five ensemble members and covers the period from 1979 onwards. Updated versions of observation data sets are used in ORAS5 production, with special attention devoted to the consistency of sea surface temperature (SST) and sea-ice observations. Assessment of ORAS5 through sensitivity experiments suggests that all system components contribute to an improved fit to observation in reanalyses, with the most prominent contribution from direct assimilation of ocean in situ observations. Results of observing system experiments further suggest that the Argo float is the most influential observation type in our data assimilation system. Assessment of ORAS5 has also been carried out for several key ocean state variables and verified against reference climate data sets from the ESA CCI (European Space Agency Climate Change Initiative) project. With respect to ORAS4, ORAS5 has improved ocean climate state and variability in terms of SST and sea level, mostly due to increased model resolution and updates in assimilated observation data sets. In spite of the improvements, ORAS5 still underestimates the temporal variance of sea level and continues exhibiting large SST biases in the Gulf Stream and its extension regions which are possibly associated with misrepresentation of front positions. Overall, the SST and sea-ice uncertainties estimated using five ORAS5 ensemble members have spatial patterns consistent with those of analysis error. The ensemble spread of sea ice is commensurable with the sea-ice analysis error. On the contrary, the ensemble spread is under-dispersive for SST.

Three key issues of moisture supply and Indian summer monsoon rainfall (ISMR) variability are discussed in the present work: identification of the oceanic and terrestrial sources of moisture; the extent to which each source affects the ISMR; and their individual contributions to the interannual variability of ISMR. The modified Dynamic Recycling Model, based on a Lagrangian trajectory approach, is used to estimate the relative contributions from 27 terrestrial and oceanic moisture source regions to the monsoon during 1979–2013. ERA-Interim data are used for the study. The results show that the ISMR is strongly influenced by the land–ocean–atmosphere interactions, and a significant fraction of atmospheric moisture to the ISMR comes from five main moisture sources: the western Indian Ocean (WIO), central Indian Ocean (CIO), upper Indian Ocean (UIO), Ganges basin (GB), and Red Sea and the neighboring gulf (RDG). The moisture flux from WIO is very high during the initial period of monsoon seasons. From the mid-monsoon season, the contribution from this moisture source decays and land sources through evapotranspiration (ET) become more active. Early decay of moisture contributions from the WIO and the GB is observed during weak monsoon years. El Niño years are associated with low contributions of moisture from all sources, whereas warm Indian Ocean years are associated with low moisture flux from the major sources except WIO. ISMR is characterized by the prolonged and increasing moisture supply from WIO during the first half of the monsoon along with contributions from GB during the end of season. The results are consistent across several reanalyses (CFSR, ERA-Interim, and MERRA).

The ocean–atmosphere coupling in the North Atlantic is investigated during the twentieth century using maximum covariance analysis of sea surface temperature (SST) and 500-hPa geopotential height analyses and performing regressions on dynamical diagnostics such as Eady growth rate, wave activity flux, and velocity potential. The North Atlantic Oscillation (NAO) generates the so-called SST anomaly tripole. A rather similar SST anomaly tripole, with the subpolar anomaly displaced to the east and a more contracted subtropical anomaly, which is referred to as the North Atlantic horseshoe pattern, in turn influences the atmosphere. In the fall and early winter, the response is NAO like and primarily results from subpolar forcing centered over the Labrador Sea and off Newfoundland. In summer, the largest atmospheric response to SST resembles the east Atlantic pattern and results from a combination of subpolar and tropical forcing. To emphasize the interannual to multidecadal variability, the same analysis is repeated after low-pass filtering. The SST influence is dominated by the Atlantic multidecadal oscillation (AMO), which also has a horseshoe shape, but with larger amplitude in the subpolar basin. A warm AMO phase leads to an atmospheric warming limited to the lower troposphere in summer, while it leads to a negative phase of the NAO in winter. The winter influence of the AMO is suggested to be primarily forced by the Atlantic SSTs in the northern subtropics. Such influence of the AMO is found in winter instead of early winter because the winter SST anomalies have a larger persistence, presumably because of SST reemergence.

While significant improvements have been made in understanding how the El Niño–Southern Oscillation (ENSO) impacts both North American and Asian climate, its relationship with the North Atlantic Oscillation (NAO) remains less clear. Observations indicate that ENSO exhibits a highly complex relationship with the NAO-associated atmospheric circulation. One critical contribution to this ambiguous ENSO/NAO relationship originates from ENSO’s diversity in its spatial structure. In general, both eastern (EP) and central Pacific (CP) El Niño events tend to be accompanied by a negative NAO-like atmospheric response. However, for two different types of La Niña the NAO response is almost opposite. Thus, the NAO responses for the CP ENSO are mostly linear, while nonlinear NAO responses dominate for the EP ENSO. These contrasting extra-tropical atmospheric responses are mainly attributed to nonlinear air-sea interactions in the tropical eastern Pacific. The local atmospheric response to the CP ENSO sea surface temperature (SST) anomalies is highly linear since the air-sea action center is located within the Pacific warm pool, characterized by relatively high climatological SSTs. In contrast, the EP ENSO SST anomalies are located in an area of relatively low climatological SSTs in the eastern equatorial Pacific. Here only sufficiently high positive SST anomalies during EP El Niño events are able to overcome the SST threshold for deep convection, while hardly any anomalous convection is associated with EP La Niña SSTs that are below this threshold. This ENSO/NAO relationship has important implications for NAO seasonal prediction and places a higher requirement on models in reproducing the full diversity of ENSO.

Pelagic fauna is expected to be impacted under climate change according to ecosystem simulations. However, the direction and magnitude of the impact is still uncertain and still not corroborated by observation-based statistical studies. Here we compile a global underwater sonar database and 20 ocean climate projections to predict the future distribution of sound-scattering fauna around the world’s oceans. We show that global pelagic fauna will be seriously compromised by the end of the twenty-first century if we continue under the current greenhouse emission scenario. Low and mid latitudes are expected to lose from 3% to 22% of animal biomass due to the expansion of low-productive systems, while higher latitudes would be populated by present-day temperate fauna, supporting results from ecosystem simulations. We further show that strong mitigation measures to contain global warming below 2 °C would reduce these impacts to less than half.The authors compile an underwater sonar database to understand the current and future distribution of pelagic fauna in the world’s oceans. They show loss of 3–22% of these fauna in low and mid latitudes under high-emissions scenarios, with impact reduced to less than half if global warming is contained below 2 °C.

The El Niño of 2015/16 was among the strongest El Niño events observed since 1950 and took place almost two decades after the previous major event in 1997/98. Here, perspectives of the event are shared by scientists from three national meteorological or climate services that issue regular operational updates on the status and prediction of El Niño–Southern Oscillation (ENSO). Public advisories on the unfolding El Niño were issued in the first half of 2015. This was followed by significant growth in sea surface temperature (SST) anomalies, a peak during November 2015–January 2016, subsequent decay, and its demise during May 2016. The life cycle and magnitude of the 2015/16 El Niño was well predicted by most models used by national meteorological services, in contrast to the generally overexuberant model predictions made the previous year. The evolution of multiple atmospheric and oceanic measures demonstrates the rich complexity of ENSO, as a coupled ocean–atmosphere phenomenon with pronounced global impacts. While some aspects of the 2015/16 El Niño rivaled the events of 1982/83 and 1997/98, we show that it also differed in unique and important ways, with implications for the study and evaluation of past and future ENSO events. Unlike previous major El Niños, remarkably above-average SST anomalies occurred in the western and central equatorial Pacific but were milder near the coast of South America. While operational ENSO systems have progressed markedly over the past several decades, the 2015/16 El Niño highlights several challenges that will continue to test both the research and operational forecast communities.