The Sea State CCI dataset v1: towards a sea state climate data record based on satellite observations

Sea state data are of major importance for climate studies, marine engineering, safety at sea and coastal management. However, long-term sea state datasets are sparse and not always consistent, and sea state data users still mostly rely on numerical wave models for research and engineering applications. Facing the urgent need for a sea state climate data record, the Global Climate Observing System has listed “Sea State” as an Essential Climate Variable (ECV), fostering the launch in 2018 of the Sea State Climate Change Initiative (CCI). The CCI is a programme of the European Space Agency, whose objective is to realise the full potential of global Earth observation archives established by ESA and its member states in order to contribute to the ECV database. This paper presents the implementation of the first release of the Sea State CCI dataset, the implementation and benefits of a high-level denoising method, its validation against in situ measurements and numerical model outputs, and the future developments considered within the Sea State CCI project. The Sea State CCI dataset v1 is freely available on the ESA CCI website (http://cci.esa.int/data, last access: 25 August 2020) at ftp://anon-ftp.ceda.ac.uk/neodc/esacci/sea_state/data/v1.1_release/ (last access: 25 August 2020). Three products are available: a multi-mission along-track L2P product (http://dx.doi.org/ 10.5285/f91cd3ee7b6243d5b7d41b9beaf397e1, Piollé et al., 2020a), a daily merged multi mission along-track L3 product (http://dx.doi.org/10.5285/3ef6a5a66e9947d39b356251909dc12b, Piollé et al., 2020b) and a multimission monthly gridded L4 product (http://dx.doi.org/10.5285/47140d618dcc40309e1edbca7e773478, Piollé et al., 2020c)

Observing Sea States

Sea state information is needed for many applications, ranging from safety at sea and on the coast, for which real time data are essential, to planning and design needs for infrastructure that require long time series. The definition of the wave climate and its possible evolution requires high resolution data, and knowledge on possible drift in the observing system. Sea state is also an important climate variable that enters in air-sea fluxes parameterizations. Finally, sea state patterns can reveal the intensity of storms and associated climate patterns at large scales, and the intensity of currents at small scales. A synthesis of user requirements leads to requests for spatial resolution at kilometer scales, and estimations of trends of a few centimeters per decade. Such requirements cannot be met by observations alone in the foreseeable future, and numerical wave models can be combined with in situ and remote sensing data to achieve the required resolution. As today's models are far from perfect, observations are critical in providing forcing data, namely winds, currents and ice, and validation data, in particular for frequency and direction information, and extreme wave heights. In situ and satellite observations are particularly critical for the correction and calibration of significant wave heights to ensure the stability of model time series. A number of developments are underway for extending the capabilities of satellites and in situ observing systems. These include the generalization of directional measurements, an easier exchange of moored buoy data, the measurement of waves on drifting buoys, the evolution of satellite altimeter technology, and the measurement of directional wave spectra from satellite radar instruments. For each of these observing systems, the stability of the data is a very important issue. The combination of the different data sources, including numerical models, can help better fulfill the needs of users

Jet production in charged current deep inelastic e⁺p scatteringat HERA

The production rates and substructure of jets have been studied in charged current deep inelastic e⁺p scattering for Q² > 200 GeV² with the ZEUS detector at HERA using an integrated luminosity of 110.5 pb⁻¹. Inclusive jet cross sections are presented for jets with transverse energies E_{T}^{jet} > 5 GeV. Measurements of the mean subjet multiplicity, 〈n_{sbj}〉, of the inclusive jet sample are presented. Predictions based on parton-shower Monte Carlo models and next-to-leading-order QCD calculations are compared to the measurements. The value of α_{s} (M_{z}), determined from 〈n_{sbj}〉 at y_{cut} = 10⁻² for jets with 25 < E_{T}^{jet} < 119 GeV, is α_{s} (M_{z}) = 0.1202 ± 0.0052 (stat.)_{-0.0019}^{+0.0060} (syst.)_{-0.0053}^{+0.0065} (th.). The mean subjet multiplicity as a function of Q² is found to be consistent with that measured in NC DIS

Multijet production in neutral current deep inelastic scattering at HERA and determination of α_{s}

Multijet production rates in neutral current deep inelastic scattering have been measured in the range of exchanged boson virtualities 10 5 GeV and –1 < η_{LAB}^{jet} < 2.5. Next-to-leading-order QCD calculations describe the data well. The value of the strong coupling constant α_{s} (M_{z}), determined from the ratio of the trijet to dijet cross sections, is α_{s} (M_{z}) = 0.1179 ± 0.0013 (stat.)_{-0.0046}^{+0.0028}(exp.)_{-0.0046}^{+0.0028}(th.)

Robustness and uncertainties in global multivariate wind-wave climate projections

Understanding climate-driven impacts on the multivariate global wind-wave climate is paramount to effective offshore/coastal climate adaptation planning. However, the use of single-method ensembles and variations arising from different methodologies has resulted in unquantified uncertainty amongst existing global wave climate projections. Here, assessing the first coherent, community-driven, multi-method ensemble of global wave climate projections, we demonstrate widespread ocean regions with robust changes in annual mean significant wave height and mean wave period of 5–15% and shifts in mean wave direction of 5–15°, under a high-emission scenario. Approximately 50% of the world’s coastline is at risk from wave climate change, with ~40% revealing robust changes in at least two variables. Furthermore, we find that uncertainty in current projections is dominated by climate model-driven uncertainty, and that single-method modelling studies are unable to capture up to ~50% of the total associated uncertainty

Beauty photoproduction measured using decays into muons in dijet events in ep collisions at s\sqrt{s}=318 GeV

The photoproduction of beauty quarks in events with two jets and a muon has been measured with the ZEUS detector at HERA using an integrated luminosity of 110 pb$^{- 1}$. The fraction of jets containing b quarks was extracted from the transverse momentum distribution of the muon relative to the closest jet. Differential cross sections for beauty production as a function of the transverse momentum and pseudorapidity of the muon, of the associated jet and of $x_{\gamma}^{jets}$, the fraction of the photon's momentum participating in the hard process, are compared with MC models and QCD predictions made at next-to-leading order. The latter give a good description of the data.Comment: 32 pages, 6 tables, 7 figures Table 6 and Figure 7 revised September 200

The dependence of dijet production on photon virtuality in ep collisions at HERA

The dependence of dijet production on the virtuality of the exchanged photon, Q^2, has been studied by measuring dijet cross sections in the range 0 < Q^2 < 2000 GeV^2 with the ZEUS detector at HERA using an integrated luminosity of 38.6 pb^-1. Dijet cross sections were measured for jets with transverse energy E_T^jet > 7.5 and 6.5 GeV and pseudorapidities in the photon-proton centre-of-mass frame in the range -3 < eta^jet <0. The variable xg^obs, a measure of the photon momentum entering the hard process, was used to enhance the sensitivity of the measurement to the photon structure. The Q^2 dependence of the ratio of low- to high-xg^obs events was measured. Next-to-leading-order QCD predictions were found to generally underestimate the low-xg^obs contribution relative to that at high xg^obs. Monte Carlo models based on leading-logarithmic parton-showers, using a partonic structure for the photon which falls smoothly with increasing Q^2, provide a qualitative description of the data.Comment: 35 pages, 6 eps figures, submitted to Eur.Phys.J.

Search for a narrow charmed baryonic state decaying to D^*+/- p^-/+ in ep collisions at HERA

A resonance search has been made in the D^*+/- p^-/+ invariant-mass spectrum with the ZEUS detector at HERA using an integrated luminosity of 126 pb^-1. The decay channels D^*+ -> D^0 pi^+_s -> (K^- pi^+) pi^+_s and D^*+ -> D^0 pi^+_s -> (K^- pi^+ pi^+ pi^-) pi^+_s (and the corresponding antiparticle decays) were used to identify D^*+/- mesons. No resonance structure was observed in the D^*+/- p^-/+ mass spectrum from more than 60000 reconstructed D^*+/- mesons. The results are not compatible with a report of the H1 Collaboration of a charmed pentaquark, Theta^0_c.Comment: 22 pages, 7 figures, 1 table; minor text revisions; 2 references adde

A recent increase in global wave power as a consequence of oceanic warming

Wind-generated ocean waves drive important coastal processes that determine flooding and erosion. Ocean warming has been one factor affecting waves globally. Most studies have focused on studying parameters such as wave heights, but a systematic, global and long-term signal of climate change in global wave behavior remains undetermined. Here we show that the global wave power, which is the transport of the energy transferred from the wind into sea-surface motion, has increased globally (0.4% per year) and by ocean basins since 1948. We also find long-term correlations and statistical dependency with sea surface temperatures, globally and by ocean sub-basins, particularly between the tropical Atlantic temperatures and the wave power in high south latitudes, the most energetic region globally. Results indicate the upper-ocean warming, a consequence of anthropogenic global warming, is changing the global wave climate, making waves stronger. This identifies wave power as a potentially valuable climate change indicator.Funding for this project was partly provided by RISKOADAPT (BIA2017-89401-R) Spanish Ministry of Science, Innovation and Universities and the ECLISEA project part of the Horizon 2020 ERANET ERA4CS (European Research Area for Climate Services) 2016 Call