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The recent advancements in climate modeling partially build on the improvement of horizontal resolution in different components of the simulating system. A higher resolution is expected to provide a better representation of the climate variability, and in this work we are particularly interested in the potential improvements in representing extreme events of high temperature and precipitation. The two versions of the Centro Euro-Mediterraneo sui Cambiamenti Climatici (CMCC-CM2) model used here adopt the highest horizontal resolutions available within the last family of the global coupled climate models developed at CMCC to participate in the Coupled Model Intercomparison Projects, Phase 6 (CMIP6) effort. The main aim of this study is to document the ability of the CMCC-CM2 models to represent the spatial distribution of extreme events of temperature and precipitation, under the historical period, comparing model results to observations, the European Centre for Medium-Range Weather Forecasts (ECMWF) reanalysis (ERA5), multi-source weighted-ensemble precipitation (MSWEP) and Climate Hazards Group infrared precipitation with station data (CHIRPS) observations. For a more detailed evaluation we use both 6-hourly and daily time series, to compute indices representative of intense and extreme conditions. In terms of mean climate, the two models are able to realistically reproduce the main patterns of temperature and precipitation. The high resolution version (1/4∘ horizontal resolution) of the atmospheric model provides better results than the standard resolution one (1°), not only in terms of means but also in terms of intense and extreme events of temperature defined at daily and 6-hourly frequencies. This is also the case of average and intense precipitation. On the other hand the extreme precipitation is not improved by the adoption of a higher horizontal resolution.

Syukuro Manabe was awarded the Nobel Prize in Physics in 2021 for his work on climate modeling. The Prize recognizes an exceptional career that pioneered a new area of the scientific enterprise revealing the power of numerical simulations and methods for advancing scientific discovery and producing new knowledge. Manabe contributed decisively to the creation of the modern scientific discipline of climate science through numerical modeling, stressing clarity of ideas and simplicity of approach. He described in no uncertain terms the role of greenhouse gases in the atmosphere and the impact of changes in the radiation balance of the atmosphere caused by the anthropogenic increase of such gases, and he revealed the role of water vapor in the greenhouse effect. He also understood the importance of including all the components of the climate system (the oceans, sea ice, and land surface) to reach a comprehensive treatment of the mechanisms of climate in a general circulation model, paving the way to the modern earth system models and the establishment of climate modeling as a leading scientific discipline.

The Mediterranean Forecasting Systems produces operational analyses, reanalyses and 10-day forecasts for many Essential Ocean Variables (EOVs), from currents, temperature to wind waves and pelagic biogeochemistry. The products are available at a horizontal resolution of 1/24 degrees (approximately 4 km) and 141 unevenly spaced vertical levels. The core of the Mediterranean Forecasting System is constituted by the physical (PHY), the biogeochemical (BIO) and the wave (WAV) components coupled offline, consisting of both numerical models and data assimilation modules. The 3 components together constitute the so-called Mediterranean Monitoring and Forecasting Center (Med-MFC) of the Copernicus Marine Service. Daily 10-day forecasts are produced by the PHY, BIO and WAV components as well as analyses, while reanalyses are produced for the past 30 years about every ~3 years and extended (yearly). The modelling systems, their coupling strategy and evolution is illustrated in detail. For the first time, the quality of the products is documented in terms of skill metrics evaluated on a common three-year period (2018–2020), giving the first complete assessment of uncertainties for all the Mediterranean environmental variable analyses.

In this work we show how it is possible to derive a new set of nudging equations, a tool still used in many data assimilation problems, starting from statistical physics considerations and availing ourselves of stochastic parameterizations that take into account unresolved interactions. The fluctuations used are thought of as Gaussian white noise with zero mean. The derivation is based on the conditioned Langevin dynamics technique. Exploiting the relation between the Fokker–Planck and the Langevin equations, the nudging equations are derived for a maximally observed system that converges towards the observations in finite time. The new nudging term found is the analog of the so called quantum potential of the Bohmian mechanics. In order to make the new nudging equations feasible for practical computations, two approximations are developed and used as bases from which extending this tool to non-perfectly observed systems. By means of a physical framework, in the zero noise limit, all the physical nudging parameters are fixed by the model under study and there is no need to tune other free ad-hoc variables. The limit of zero noise shows that also for the classical nudging equations it is necessary to use dynamical information to correct the typical relaxation term. A comparison of these approximations with a 3DVar scheme, that use a conjugate gradient minimization, is then shown in a series of four twin experiments that exploit low order chaotic models.

Italy and Germany are establishing a new bilateral cooperation in meteorology, climatology and related disciplines that will create a hub of excellence for cutting edge research and translate the findings into improving operational services and university education. The joint research and education network IDEA-S4S will harness expertise of universities, research institutes and operational services in both countries and foster scientific exchange and collaboration to improve weather, climate and environmental services.Within the new programme, the core areas of scientific expertise of both countries will be systematically brought together, activities will be streamlined and extended beyond basic research collaboration to form a holistic IDEA-S4S network of weather and climate science and education, extending from qualification of graduates to support for early career researchers to networking of senior scientists. The programme will cooperate with WMO and the European Meteorological Infrastructure (ECMWF, EUMETSAT, EUMETNET) and strengthen the scientific environment for the ECMWF sites in Bonn and Bologna. A Joint Steering Committee will oversee the cooperation and guide the overall scientific and strategic direction of the programme.Through four-year funding periods, the network aims to make substantial progress in seamless high-resolution probabilistic Earth system prediction, employing state-of-the-art observing systems and Earth system models. This requires improved understanding and application of coupled processes between the components of the Earth system (including atmosphere-ocean-ice-land-vegetation-rivers) as well as between the impacts of human activities and the Earth system. Such complex weather and climate prediction systems place high demands on high-performance computing infrastructure, generate extremely large data volumes and need to integrate observations seamlessly into the models.In this contribution, we will present the concept and roadmap of the IDEA-S4S network, which will focus on improving seamless weather and climate forecasts, in particular for high impact events such as floods and droughts. Both countries have experienced devastating impacts of such extreme events with unusual rainfall intensities, some of which even lead to the destruction of entire regions. Better understanding the complex structure and the numerous feedback processes in such events will improve the prediction of future events in support of a better prepared and resilient society.

The dominant modes of variability at the sub-seasonal to seasonal (S2S) time scales in the tropical atmosphere, with particular emphasis on the Madden-Julian oscillation (MJO), is investigated using the observed NOAA outgoing longwave radiation (OLR). This study focuses on the boreal winter season (November to April) of the period 1993-2016. The multi-channel singular spectral analysis (MSSA) method is introduced and used to isolate the dominant modes associated with the tropical boreal winter daily OLR anomalies. The results show that the dominant MSSA mode consists of an intraseasonal oscillation with a period of around 35-day and two seasonally persistent modes. The 35-day oscillation is related to the intraseasonal convective activity of the tropics with little contribution to the seasonal mean value, and the phase composites and propagation characteristics of the 35-day mode are almost identical to the MJO (referred to as the MJO mode). The seasonally persistent modes are characterized by large-scale patterns that prevail over most of the tropics with the same sign anomalies throughout the boreal winter season, which represent inter-annual variations and are related to the El Niño-Southern Oscillation (ENSO) pattern. In this work, the MSSA based analysis is applied to the fully coupled (atmosphere-ocean-land-cryosphere) Euro-Mediterranean Center on Climate Change (CMCC) seasonal prediction system to evaluate the model's performance in simulating observed dominant modes of the boreal winter tropical variability.

In this work we show how it is possible to derive a new set of nudging equations, a tool still used in many data assimilation problems, starting from statistical physics considerations and availing ourselves of stochastic parameterizations that take into account unresolved interactions. The fluctuations used are thought of as Gaussian white noise with zero mean. The derivation is based on the conditioned Langevin dynamics technique. Exploiting the relation between the Fokker–Planck and the Langevin equations, the nudging equations are derived for a maximally observed system that converges towards the observations in finite time. The new nudging term found is the analog of the so called quantum potential of the Bohmian mechanics. In order to make the new nudging equations feasible for practical computations, two approximations are developed and used as bases from which extending this tool to non-perfectly observed systems. By means of a physical framework, in the zero noise limit, all the physical nudging parameters are fixed by the model under study and there is no need to tune other free ad-hoc variables. The limit of zero noise shows that also for the classical nudging equations it is necessary to use dynamical information to correct the typical relaxation term. A comparison of these approximations with a 3DVar scheme, that use a conjugate gradient minimization, is then shown in a series of four twin experiments that exploit low order chaotic models.

Significance Much work has been done to quantify tropical cyclone (TC)-induced precipitation and its role in determining flood events. We identify the role of tropical cyclones in reducing precipitation over particular areas of the tropical domain. The significant reduction in the precipitation over the Maritime Continent when the TC season is particularly active is in line with the net reduction in westward water flow into the Maritime Continent atmosphere, induced by TC-associated circulation over the region., The Maritime Continent plays a role in the global circulation pattern, due to the energy released by convective condensation over the region which influences the global atmospheric circulation. We demonstrate that tropical cyclones contribute to drying the Maritime Continent atmosphere, influencing the definition of the onset of the dry season. The process was investigated using observational data and reanalysis. Our findings were confirmed by numerical experiments using low- and high-resolution versions of the CMCC-CM2 General Circulation Model contributing to the HighResMIP CMIP6 effort.

A short commentary on the role of systematic errors in climate simulations.

In the last years, ensemble methods have been widely popular in atmospheric, climate, and ocean dynamics investigations and forecasts as convenient methods to obtain statistical information on these systems. In many cases, ensembles have been used as an approximation to the probability distribution that has acquired more and more a central role, as the importance of a single trajectory, or member, was recognized as less informative. This paper shows that using results from the dynamical systems and more recent results from the machine learning and AI communities, we can arrive at a direct estimation of the probability distribution evolution and also at the formulation of predictor systems based on a nonlinear formulation. The paper introduces the theory and demonstrates its application to two examples. The first is a one-dimensional system based on the Niño-3 index; the second is a multidimensional case based on time series of monthly mean SST in the Pacific. We show that we can construct the probability distribution and set up a system to forecast its evolution and derive various quantities from it. The objective of the paper is not strict realism, but the introduction of these methods and the demonstration that they can be used also in the complex, multidimensional environment typical of atmosphere and ocean applications.

The recent advancements in climate modelling partially build on the improvement of horizontal resolution in different components of the simulating system. A higher resolution is expected to provide a better representation of the climate variability, and in this work we are particularly interested in the potential improvements in representing extreme events of high temperature and precipitation. The two versions of the CMCC-CM2 model used here, adopt the highest horizontal resolutions available within the last family of the global coupled climate models de¬veloped at CMCC to participate in the CMIP6 effort. The main aim of this study is to document the ability of the CMCC-CM2 models in representing the spatial distribution of extreme events of temperature and precipitation, under the historical period, comparing model results to observations (ERA5 Reanalysis and CHIRPS observations). For a more detailed evaluation we investigate both 6 hourly and daily time series for the definition of the extreme conditions. In terms of mean climate, the two models are able to realistically reproduce the main patterns of temperature and precipitation. The very-high resolution version (¼ degree horizontal resolution) of the atmospheric model provides better results than the high resolution one (one degree), not only in terms of means but also in terms of extreme events of temperature defined at daily and 6-hourly frequency. This is also the case of average precipitation. On the other hand the extreme precipitation is not improved by the adoption of a higher horizontal resolution.

The North Pacific Ocean is the most active region on our planet in terms of tropical cyclone (TC) activity. These storms are responsible for numerous fatalities and economic damages, affecting the livelihood of those living in the impacted areas. Historically the examination of TCs in the North Pacific Ocean has been performed separately for its two main sub-basins: the West North Pacific and the East North Pacific. Here, we consider the TC activity in the North Pacific as a single basin and examine the climate processes responsible for its number of TC days. We show that the Pacific Decadal Oscillation modulates the number of TC days in the North Pacific Ocean through its connection to the sea surface temperature. The insights from this work will advance the understanding of the climate processes responsible for these storms, and will provide valuable information toward our preparation and adaptation efforts on long timescales.

Tropical cyclones (TCs) in the North Pacific Ocean claim a major socio-economic toll on a yearly basis, and their impacts are projected to be exacerbated due to climate change and increased exposure and vulnerability. Recent examples of Typhoons Mangkhut (2018) and Hagibis (2019) are a reminder of the devastating impacts these storms can have. While the TC activity in the West North Pacific (WNP) and East North Pacific (ENP) has been the subject of intense investigation, these basins are generally treated separately, rather than considering the storm activity in the North Pacific as a single basin. The influence of climate processes, such as the Pacific Decadal Oscillation (PDO) , that operate across the entire North Pacific may not have been considered by focusing on the sub-basins, especially if we are interested in multi-annual and decadal changes. It is reasonable to hypothesize that a climate mode like the PDO could play an important role in terms of TC activity in this basin. However, there is limited evidence that connects these storms and the PDO. Our expectation is that the number of TC days is related to the PDO through the modulation of this climate mode of the SST in the regions where these storms develop. In particular, during the positive phase of the PDO, warm waters close to the equator would lead to conditions favorable to the development of longer-lasting storms compared to the negative PDO phase, which is characterized by lower SST values. We believe that this connection has not been sufficiently considered in the literature because the North Pacific Ocean was not considered as a single basin but broken up into WNP and ENP, confounding the detection of a potential PDO signal. Therefore, in this work we focus on the potential role of the PDO in modulating TC activity, with emphasis on the number of TC active days in the entire North Pacific Ocean. We have selected this metric because the number of TC days provides an integrated information about TC genesis, lifespan, and tracks, and because it exhibits substantial decadal-scale oscillations in TC activity compared to other metrics used to highlight TC activity. We aim to verify the effects of different SST patterns on the spatial distribution of TC genesis in the North Pacific leading to conditions that are more/less favorable for long-lasting TCs under positive/negative PDO phases. A larger number of TC days for storms that tend to develop along the tropics during the positive PDO phase is found. When we stratify the years according to the sign of the PDO phase, the years associated with the positive phase tend to have storms that form at a lower latitude and that last longer compared with the negative phase. On average, these storms tend to form around 14°N and to result in 240 TC days; during the negative PDO phase, TCs tend to form around 16°N, for a total of 160 TC days.

The outbreak of coronavirus disease 2019 (COVID-19) was identified in Wuhan, China, in December 2019. As of 17 April 2020, more than 2 million cases of COVID-19 have been reported worldwide. Northern Italy is one of the world&rsquo, s centers of active coronavirus cases. In this study, we predicted the spread of COVID-19 and its burden on hospital care under different conditions of social distancing in Lombardy and Emilia-Romagna, the two regions of Italy most affected by the epidemic. To do this, we used a Susceptible-Exposed-Infectious-Recovered (SEIR) deterministic model, which encompasses compartments relevant to public health interventions such as quarantine. A new compartment L was added to the model for isolated infected population, i.e., individuals tested positives that do not need hospital care. We found that in Lombardy restrictive containment measures should be prolonged at least until early July to avoid a resurgence of hospitalizations, on the other hand, in Emilia-Romagna the number of hospitalized cases could be kept under a reasonable amount with a higher contact rate. Our results suggest that territory-specific forecasts under different scenarios are crucial to enhance or take new containment measures during the epidemic.

Large-scale river routing schemes are essential to close the hydrological cycle in fully coupled Earth System Models (ESMs). The availability of a realistic water flow is a powerful instrument to evaluate modeled land surface, a crucial component of the global climate whose properties are often simplified by heavy parameterization, due to lack of process knowledge and validation data. We built up a new concept of river routing model, named HYDROS (HYdro-Dynamic ROuting Scheme), that replaces the present scheme embedded in the CMCC-CM2 global coupled model. The new scheme aims at overcoming one of the current major limitations, that is the use of time-independent flow velocities parameterized as a function of topography. Through the imposition of hydraulic equations, HYDROS defines a time-varying flow velocity associated with the amount of lateral runoff generated by the ESM's land component and the flow through the river system. Compared to the scheme currently in place, HYDROS show improvements in the simulation of mean annual discharge phase, especially for the Arctic rivers and the Amazon. In the Mississippi case, an extreme flood episode is better caught by the new representation, indicating that the improved flow velocity better catches the discharge peaks after extreme rainfalls. The new routing model is not able to improve the volumes of simulated river discharge, whose magnitude depends on the ability of the ESM land surface scheme to generate correct surface and sub-surface runoff. Once implemented in coupled mode, HYDROS will guarantee a plausible amount and timing of freshwater discharge into the global ocean, unveiling possible unresolved feedback mechanisms occurring in proximity of river mouths.

The current lack of a standardized approach to compute the coastal oil spill hazard due to maritime traffic accidental releases has hindered an accurate estimate of its global impact, which is paramount to manage and intercompare the associated risks. We propose here a hazard estimation approach that is based on ensemble simulations and the extraction of the relevant frequency distributions. We demonstrate that both open ocean and beached oil concentration distributions fit a Weibull curve, a two-parameter fat-tail probability distribution function. The simulation experiments are carried out in all the coastal areas of the Atlantic ocean basin. An indicator that quantify the coastal oil spill hazard is proposed and applied to the study areas.

ENSO is investigated here by considering it as a transition from different states. Transition probability matrices can be defined to describe the evolution of ENSO in this way. Sea surface temperature anomalies are classified into four categories, or states, and the probability to move from one state to another has been calculated for both observations and a simulation from a GCM. This could be useful for understanding and diagnosing general circulation models elucidating the mechanisms that govern ENSO in models. Furthermore, these matrices have been used to define a predictability index of ENSO based on the entropy concept introduced by Shannon. The index correctly identifies the emergence of the spring predictability barrier and the seasonal variations of the transition probabilities. The transition probability matrices could also be used to formulate a basic prediction model for ENSO that was tested here on a case study.

Reliable and timely information on the environmental conditions at sea is key to the safety of professional and recreational users as well as to the optimal execution of their activities. The possibility of users obtaining environmental information in due time and with adequate accuracy in the marine and coastal environment is defined as sea situational awareness (SSA). Without adequate information on the environmental meteorological and oceanographic conditions, users have a limited capacity to respond, which has led to loss of lives and to large environmental disasters with enormous consequent damage to the economy, society and ecosystems. Within the framework of the TESSA project, new SSA services for the Mediterranean Sea have been developed. In this paper we present SeaConditions, which is a web and mobile application for the provision of meteorological and oceanographic observation and forecasting products. Model forecasts and satellite products from operational services, such as ECMWF and CMEMS, can be visualized in SeaConditions. In addition, layers of information related to bathymetry, sea level and ocean-colour data (chl a and water transparency) are displayed. Ocean forecasts at high spatial resolutions are included in the version of SeaConditions presented here. SeaConditions provides a user-friendly experience with a fluid zoom capability, facilitating the appropriate display of data with different levels of detail. SeaConditions is a single point of access to interactive maps from different geophysical fields, providing high-quality information based on advanced oceanographic models. The SeaConditions services are available through both web and mobile applications. The web application is available at www.sea-conditions.com and is accessible and compatible with present-day browsers. Interoperability with GIS software is implemented. User feedback has been collected and taken into account in order to improve the service. The SeaConditions iOS and Android apps have been downloaded by more than 105000 users to date (May 2016), and more than 100000 users have visited the web version.

Through tropical cyclone (TC) activity the ocean and the atmosphere exchange a large amount of energy. In this work possible improvements introduced by a higher coupling frequency are tested between the two components of a climate model in the representation of TC intensity and TC–ocean feedbacks. The analysis is based on the new Centro Euro-Mediterraneo per I Cambiamenti Climatici Climate Model (CMCC-CM2-VHR), capable of representing realistic TCs up to category-5 storms. A significant role of the negative sea surface temperature (SST) feedback, leading to a weakening of the cyclone intensity, is made apparent by the improved representation of high-frequency coupled processes. The first part of this study demonstrates that a more realistic representation of strong TC count is obtained by coupling atmosphere and ocean components at hourly instead of daily frequency. Coherently, the positive bias of the annually averaged power dissipation index associated with TCs is reduced by one order of magnitude when coupling at the hourly frequency, compared to both forced mode and daily coupling frequency results. The second part of this work shows a case study (a modeled category-5 typhoon) analysis to verify the impact of a more realistic representation of the high-frequency coupling in representing the TC effect on the ocean; the theoretical subsurface warming induced by TCs is well represented when coupling the two components at the higher frequency. This work demonstrates that an increased horizontal resolution of model components is not sufficient to ensure a realistic representation of intense and fast-moving systems, such as tropical and extratropical cyclones, but a concurrent increase in coupling frequency is required.

Euro‐Mediterranean Centre on Climate Change coupled climate model (CMCC‐CM2) represents the new family of the global coupled climate models developed and used at CMCC. It is based on the atmospheric, land and sea ice components from the Community Earth System Model coupled with the global ocean model Nucleus for European Modeling of the Ocean. This study documents the model components, the coupling strategy, particularly for the oceanic, atmospheric, and sea ice components, and the overall model ability in reproducing the observed mean climate and main patterns of interannual variability. As a first step toward a more comprehensive, process‐oriented, validation of the model, this work analyzes a 200‐year simulation performed under constant forcing corresponding to present‐day climate conditions. In terms of mean climate, the model is able to realistically reproduce the main patterns of temperature, precipitation, and winds. Specifically, we report improvements in the representation of the sea surface temperature with respect to the previous version of the model. In terms of mean atmospheric circulation features, we notice a realistic simulation of upper tropospheric winds and midtroposphere geopotential eddies. The oceanic heat transport and the Atlantic meridional overturning circulation satisfactorily compare with present‐day observations and estimates from global ocean reanalyses. The sea ice patterns and associated seasonal variations are realistically reproduced in both hemispheres, with a better skill in winter. Main weaknesses of the simulated climate are related with the precipitation patterns, specifically in the tropical regions with large dry biases over the Amazon basin. Similarly, the seasonal precipitation associated with the monsoons, mostly over Asia, is weaker than observed. The main patterns of interannual variability in terms of dominant empirical orthogonal functions are faithfully reproduced, mostly in the Northern Hemisphere winter. In the tropics the main teleconnection patterns associated with El Niño–Southern Oscillation and with the Indian Ocean Dipole are also in good agreement with observations.

The term "monsoon-desert mechanism" indicates the relationship between the diabatic heating associated with the South Asian summer monsoon rainfall and the remote response in the western sub-tropics where long Rossby waves anchor strong descent with high subsidence. In CMIP5 twenty-first century climate scenarios, the precipitation over South Asia is projected to increase. This study investigates how this change could affect the summer climate projections in the Mediterranean region. In a linear framework the monsoon-desert mechanism in the context of climate change would imply that the change in subsidence over the Mediterranean should be strongly linked with the changes in South Asian monsoon precipitation. The steady-state solution from a linear model forced with CMIP5 model projected precipitation change over South Asia shows a broad region of descent in the Mediterranean, while the results from CMIP5 projections differ having increased descent mostly in the western sector but also decreased descent in parts of the eastern sector. Local changes in circulation, particularly the meridional wind, promote cold air advection that anchors the descent but the barotropic Rossby wave nature of the wind anomalies consisting of alternating northerlies/southerlies favors alternating descent/ascent locations. In fact, the local mid-tropospheric meridional wind changes have the strongest correlation with the regions where the difference in subsidence is largest. There decreased rainfall is mostly balanced by changes in moisture, omega and in the horizontal advection of moisture.

Seasonal rainfall in the Caribbean Basin is known to be modulated by sea surface temperature anomalies (SSTAs) in the Atlantic and Pacific Oceans, and particularly those in the Equatorial Pacific and Atlantic and the Tropical North Atlantic. However, little is known about how these major oceans influence the seasonal precipitation of individual small island states within the region as climate variability at the island-scale may differ from the Caribbean as a whole. Correlation and composite analyses were determined using monthly rainfall data for the southernmost island of the Caribbean, Trinidad, and an extended area of global SSTAs. In addition to the subregions that are known to modulate Caribbean rainfall, our analyses show that sea surface temperatures (SSTs) located in the subtropical South Pacific, the South Atlantic, and the Gulf of Mexico also have weak (r2 &lt, 0.5) yet significant influences on the islands&rsquo, early rainy season (ERS) and late rainy season (LRS) precipitation. Composite maps confirm that the South Pacific, South Atlantic, and the Gulf of Mexico show significant SSTAs in December&ndash, January&ndash, February (DJF) and March&ndash, April&ndash, May (MAM) prior to the ERS and the LRS. Statistical models for seasonal forecasting of rainfall at the island scale could be improved by using the SSTAs of the Pacific and Atlantic subregions identified in this study.

Predicting North Atlantic hurricane activity months in advance is of great potential societal significance. The ocean temperature, both in terms of North Atlantic/tropical averages and upper ocean heat content, is demonstrated to be a significant predictor. To investigate the relationship between the thermal state of the Atlantic Ocean and the tropical cyclone (TC) activity in terms of accumulated cyclone energy (ACE), we use observed 1980-2015 TC records and a 1/4 degrees resolution global ocean reanalysis. This paper highlights the nonlocal effect associated with eastern Atlantic Ocean temperature, via a reduction of wind shear, and provides additional predictive skill of TC activity, when considering subsurface temperature instead of sea surface temperature (SST) only. The most active TC seasons occur for lower than normal wind shear conditions over the main development region, which is also driven by reduced trade wind strength. A significant step toward operationally reliable TC activity predictions is gained after including upper ocean mean temperatures over the eastern Atlantic domain. Remote effects are found to provide potential skill of ACE up to 3 months in advance. These results indicate that consideration of the upper 40-m ocean average temperature improves upon a prediction of September Atlantic hurricane activity using only SST.

We characterise the representation of the Southern Ocean water mass structure and sea ice within a suite of 15 global ocean-ice models run with the Coordinated Ocean-ice Reference Experiment Phase II (CORE-II) protocol. The main focus is the representation of the present (1988-2007) mode and intermediate waters, thus framing an analysis of winter and summer mixed layer depths; temperature, salinity, and potential vorticity structure; and temporal variability of sea ice distributions. We also consider the interannual variability over the same 20 year period. Comparisons are made between models as well as to observation-based analyses where available. The CORE-II models exhibit several biases relative to Southern Ocean observations, including an underestimation of the model mean mixed layer depths of mode and intermediate water masses in March (associated with greater ocean surface heat gain), and an overestimation in September (associated with greater high latitude ocean heat loss and a more northward winter sea-ice extent). In addition, the models have cold and fresh/warm and salty water column biases centred near 50 degrees S. Over the 1933-2007 period, the CORE-II models consistently simulate spatially variable trends in sea-ice concentration, surface freshwater fluxes, mixed layer depths, and 200-700 in ocean heat content. In particular, sea-ice coverage around most of the Antarctic continental shelf is reduced, leading to a cooling and freshening of the near surface waters. The shoaling of the mixed layer is associated with increased surface buoyancy gain, except in the Pacific where sea ice is also influential. The models are in disagreement, despite the common CORE-II atmospheric state, in their spatial pattern of the 20-year trends in the mixed layer depth and sea-ice. (C) 2015 Elsevier Ltd. All rights reserved

In the framework of the second phase of the Coordinated Ocean-ice Reference Experiments (CORE-II), we present an analysis of the representation of the Antarctic Circumpolar Current (ACC) and Southern Ocean meridional overturning circulation (MOC) in a suite of seventeen global ocean-sea ice models. We focus on the mean, variability and trends of both the ACC and MOC over the 1958-2007 period, and discuss their relationship with the surface forcing. We aim to quantify the degree of eddy saturation and eddy compensation in the models participating in CORE-II, and compare our results with available observations, previous fineresolution numerical studies and theoretical constraints. Most models show weak ACC transport sensitivity to changes in forcing during the past five decades, and they can be considered to be in an eddy saturated regime. Larger contrasts arise when considering MOC trends, with a majority of models exhibiting significant strengthening of the MOC during the late 20th and early 21st century. Only a few models show a relatively small sensitivity to forcing changes, responding with an intensified eddy-induced circulation that provides some degree of eddy compensation, while still showing considerable decadal trends. Both ACC and MOC interannual variabilities are largely controlled by the Southern Annular Mode (SAM). Based on these results, models are clustered into two groups. Models with constant or two-dimensional (horizontal) specification of the eddy-induced advection coefficient K show larger ocean interior decadal trends, larger ACC transport decadal trends and no eddy compensation in the MOC. Eddy-permitting models or models with a threedimensional time varying K show smaller changes in isopycnal slopes and associated ACC trends, and partial eddy compensation. As previously argued, a constant in time or space lc is responsible for a poor representation of mesoscale eddy effects and cannot properly simulate the sensitivity of the ACC and MOC to changing surface forcing. Evidence is given for a larger sensitivity of the MOC as compared to the ACC transport, even when approaching eddy saturation. Future process studies designed for disentangling the role of momentum and buoyancy forcing in driving the ACC and MOC are proposed. (C) 2015 Elsevier Ltd. All rights reserved.

Ensembles of retrospective 2-month dynamical forecasts initiated on 1 May are used to predict the onset of the Indian summer monsoon (ISM) for the period 1989–2005. The subseasonal predictions (SSPs) are based on a coupled general circulation model and recently they have been upgraded by the realistic initialization of the atmosphere with initial conditions taken from reanalysis. Two objective large-scale methods based on dynamical-circulation and hydrological indices are applied to detect the ISM onset. The SSPs show some skill in forecasting earlier-than-normal ISM onsets, while they have difficulty in predicting late onsets. It is shown that significant contribution to the skill in forecasting early ISM onsets comes from the newly developed initialization of the atmosphere from reanalysis. On one hand, atmospheric initialization produces a better representation of the atmospheric mean state in the initial conditions, leading to a systematically improved monsoon onset sequence. On the other hand, the initialization of the atmosphere allows some skill in forecasting the northward-propagating intraseasonal wind and precipitation anomalies over the tropical Indian Ocean. The northward-propagating intraseasonal modes trigger the monsoon in some early-onset years. The realistic phase initialization of these modes improves the forecasts of the associated earlier-than-normal monsoon onsets. The prediction of late onsets is not noticeably improved by the initialization of the atmosphere. It is suggested that late onsets of the monsoon are too far away from the start date of the forecasts to conserve enough memory of the intraseasonal oscillation (ISO) anomalies and of the improved representation of the mean state in the initial conditions.

Possible changes in the intensity of heavy precipitation events at the end of the twenty-first century over the Euro-Mediterranean region are investigated, using a subset of numerical climate simulations taking part to the fifth phase of the Coupled Model Intercomparison Project (CMIP5). As a measure of the intensity associated with heavy precipitation events, we use the difference between the 99th and the 90th percentiles. Despite a slight tendency to underestimate the observed heavy precipitation intensity during summer and to overestimate it during winter, the considered CMIP5 models well represent the observed patterns of the defined 99th–90th percentile metric during both seasons for the 1997–2005 period over the Euro-Mediterranean region. Over the investigated domain, an increase of the width of the right tail of the precipitation distribution is projected in a warmer climate, even over regions where nearly the entire precipitation distribution becomes dryer. This is the case of the European domain within the 45N–55N belt.

Heavy precipitation and flooding associated with tropical cyclones (TCs) are responsible for a large number of fatalities and economic damage worldwide. Due to the societal and economic relevance of this hazard, studies have focused on the potential changes in heavy rainfall associated with TCs in a warmer climate. Despite the overall agreement about the tendency of TC rainfall to increase with greenhouse warming, the uncertainty of the projected changes is large, ranging from 3 to 37 %. Models project an increase in rainfall over land, both in terms of average and extremes, and a large spatial variability is associated with changes in projected rainfall amount.

The numerical seasonal prediction system using the Scale Interaction Experiment–Frontier version 1 (SINTEX-F) ocean–atmosphere coupled model has so far demonstrated a good performance for prediction of the Indian Ocean dipole mode (IOD) despite the fact that the system adopts a relatively simple initialization scheme based on nudging only the sea surface temperature (SST). However, it is to be expected that the system is not sufficient to capture in detail the subsurface oceanic precondition. Therefore, the authors have introduced a new three-dimensional variational ocean data assimilation (3DVAR) method that takes three-dimensional observed ocean temperature and salinity into account. Since the new system has successfully improved IOD predictions, the present study is showing that the ocean observational efforts in the tropical Indian Ocean are decisive for improvement of the IOD predictions and may have a large impact on important socioeconomic activities, particularly in the Indian Ocean rim countries.

The general theory of stochastic differential equations is presented in this chapter, including the theoretical background on how measured statistics from time series can be used to develop a stochastic parameterization. The general rules of stochastic calculus, including the important and often overlooked differences between Ito and Stratonovich calculus, are mentioned, and references are provided in which more detail may be found. We discuss how Stratonovich calculus is usually appropriate for fluid systems, whereas Ito calculus is often appropriate for data assimilation. We also discuss some common numerical pitfalls awaiting the unwary modeler, and warn against unsophisticated random number generators. Finally, we offer a selection of examples showing the importance of the variability of unresolved scales in an ocean model and, by citation, a variety of methods that have been employed.

This paper reviews the historical development of concepts and practices in the science of ocean predictions. It begins with meteorology, which conducted the first forecasting experiment in 1950, followed by wind waves, and continuing with tidal and storm surge predictions to arrive at the first successful ocean mesoscale forecast in 1983. The work of Professor A. R. Robinson of Harvard University, who produced the first mesoscale ocean predictions for the deep ocean regions is documented for the first time. The scientific and technological developments that made accurate ocean predictions possible are linked with the gradual understanding of the importance of the oceanic mesoscales and their inclusion in the numerical models. Ocean forecasting developed first at the regional level, due to the relatively low computational requirements, but by the end of the 1990s, it was possible to produce global ocean uncoupled forecasts and coupled ocean-atmosphere seasonal forecasts.

Dry summers over the eastern Mediterranean are characterized by strong descent anchored by long Rossby waves, which are forced by diabatic heating associated with summer monsoon rainfall over South Asia. The large-scale teleconnection between rising and subsiding air masses is referred to as the “monsoon–desert mechanism.” This study evaluates the ability of the phase 5 of the Coupled Model Intercomparison Project (CMIP5) models in representing the physical processes involved in this mechanism. An evaluation of statistics between summer climatologies of monsoon diabatic heating and that of vertical velocity over the eastern Mediterranean suggests a linear relationship. Despite large spatial diversity in monsoon heating, descent over the Mediterranean is coherently located and realistic in intensity. To measure the sensitivity of descent to the diversity in the horizontal and vertical distribution of monsoon heating, a series of linear atmosphere model experiments are performed. It is shown that column-integrated heating over both the Bay of Bengal and the Arabian Sea provides the largest descent with a more realistic spatial pattern. In the vertical, CMIP5 models underestimate the diabatic heating at upper levels, while they overestimate it at lower levels, resulting in a weaker forced response and weaker associated descent over the Mediterranean. A moist static energy budget analysis applied to CMIP5 suggests that most models capture the dominant role of horizontal temperature advection and radiative fluxes in balancing descent over the Mediterranean. Based on the objective analysis herein, a subset of models is identified that captures the teleconnection for reasons consistent with observations. The recognized processes vary at interannual time scales as well, with imprints of severe weak/strong monsoons noticeable over the Mediterranean.

In this work the authors investigate possible changes in the intensity of rainfall events associated with tropical cyclones (TCs) under idealized forcing scenarios, including a uniformly warmer climate, with a special focus on landfalling storms. A new set of experiments designed within the U.S. Climate Variability and Predictability (CLIVAR) Hurricane Working Group allows disentangling the relative role of changes in atmospheric carbon dioxide from that played by sea surface temperature (SST) in changing the amount of precipitation associated with TCs in a warmer world. Compared to the present-day simulation, an increase in TC precipitation was found under the scenarios involving SST increases. On the other hand, in a CO2-doubling-only scenario, the changes in TC rainfall are small and it was found that, on average, TC rainfall tends to decrease compared to the present-day climate. The results of this study highlight the contribution of landfalling TCs to the projected increase in the precipitation changes affecting the tropical coastal regions.

The present manuscript compares Marine Isotope Stage 5 (MIS 5, 125–115 kyr BP) and MIS 7 (236–229 kyr BP) with the aim to investigate the origin of the difference in ice-sheet growth over the Northern Hemisphere high latitudes between these last two inceptions. Our approach combines a low resolution coupled atmosphere–ocean–sea-ice general circulation model and a 3-D thermo-mechanical ice-sheet model to simulate the state of the ice sheets associated with the inception climate states of MIS 5 and MIS 7. Our results show that external forcing (orbitals and GHG) and sea-ice albedo feedbacks are the main factors responsible for the difference in the land-ice initial state between MIS 5 and MIS 7 and that our cold climate model bias impacts more during a cold inception, such as MIS 7, than during a warm inception, such as MIS 5. In addition, if proper ice-elevation and albedo feedbacks are not taken into consideration, the evolution towards glacial inception is hardly simulated, especially for MIS 7. Finally, results highlight that while simulated ice volumes for MIS 5 glacial inception almost fit with paleo-reconstructions, the lack of precipitation over high latitudes, identified as a bias of our climate model, does not allow for a proper simulation of MIS 7 glacial inception.

The impact of land surface and atmosphere initialization on the forecast skill of a seasonal prediction system is investigated, and an effort to disentangle the role played by the individual components to the global predictability is done, via a hierarchy of seasonal forecast experiments performed under different initialization strategies. A realistic atmospheric initial state allows an improved equilibrium between the ocean and overlying atmosphere, increasing the model predictive skill in the ocean. In fact, in regions characterized by strong air–sea coupling, the atmosphere initial condition affects forecast skill for several months. In particular, the ENSO region, eastern tropical Atlantic, and North Pacific benefit significantly from the atmosphere initialization. On the mainland, the effect of atmospheric initial conditions is detected in the early phase of the forecast, while the quality of land surface initialization affects forecast skill in the following seasons. Winter forecasts in the high-latitude plains benefit from the snow initialization, while the impact of soil moisture initial state is particularly effective in the Mediterranean region and central Asia. However, the initialization strategy based on the full value technique may not be the best choice for land surface, since soil moisture is a strongly model-dependent variable: in fact, initialization through land surface reanalysis does not systematically guarantee a skill improvement. Nonetheless, using a different initialization strategy for land, as opposed to atmosphere and ocean, may generate inconsistencies. Overall, the introduction of a realistic initialization for land and atmosphere substantially increases skill and accuracy. However, further developments in the procedure for land surface initialization are required for more accurate seasonal forecasts.

A formalism to obtain a mean sea level equation (MSLE) is constructed for any limited ocean region and/or the global ocean by considering the mass conservation equation with compressible effects and a linear equation of state. The MSLE contains buoyancy fluxes terms representing the steric effects and the mass flux is represented by surface water fluxes and volume transport terms. The MSLE is studied for the Mediterranean Sea case using a simulation experiment for the decade 1999–2008. It is found that the Mediterranean MSL tendency is made of a steric contribution that is almost periodic in time superimposed on a stochastic-like signal due to the mass balance, dominating the MSL tendency. The MSL tendency stochastic-like term is a result of the imbalance between the volume flux at Gibraltar and the area average surface water flux.

The relationship between atmospheric blocking over Europe and the Atlantic eddy-driven jet stream is investigated in the NCEP/NCAR Reanalysis and in a climate model. This is carried out using a bidimensional blocking index based on geopotential height and a diagnostic providing daily latitudinal position and strength of the jet stream. It is shown that European Blocking (EB) is not decoupled from the jet stream but it is mainly associated with its poleward displacements. Moreover, the whole blocking area placed on the equatorward side of the jet stream, broadly ranging from Azores up to Scandinavia, emerges as associated with poleward jet displacements. The diagnostics are hence applied to two different climate model simulations in order to evaluate the biases in the jet stream and in the blocking representation. This analysis highlights large underestimation of EB, typical feature of general circulation models. Interestingly, observed blocking and jet biases over the Euro-Atlantic area are consistent with the blocking-jet relationship observed in the NCEP/NCAR Reanalysis. Finally, the importance of sea surface temperatures (SSTs) is investigated showing that realistic SSTs can reduce the bias in the jet stream variability but not in the frequency of EB. We conclude highlighting that blocking-related diagnostics can provide more information about the Euro-Atlantic variability than diagnostics simply based on the Atlantic jet stream.

Ocean reanalyses are data assimilative simulations, aimed at estimating the four-dimensional state of the ocean over long periods, in a way as consistent over time as possible. They are designed for a wide range of climate applications, such as climate monitoring and low-frequency variability studies, along with several downstream applications (e.g. biogeochemical and fishery modelling, initial conditions for long-range coupled predictions, regional model nesting). An upgraded version of the Euro-Mediterranean Center for Climate Change (CMCC) eddy-permitting global ocean reanalysis, named CMCC Global Ocean Reanalysis System (C-GLORS) version 4, was recently released. The reanalysis covers the meteorological satellite era (1982-2012). This article details the configuration of the reanalysis system and provides an extensive validation, focusing on the evaluation of main indexes related to climate monitoring. Cumulative denial experiments are also conducted, in order to understand the relative impact of assimilation components included in C-GLORS (i.e. altimetric data, variational assimilation, bias correction and surface nudging). Results indicate that C-GLORS proves reliable in simulating long-term means, heat and freshwater trends, sea-level variability, mean surface circulation and transports, eddy variability and meridional overturning circulation and its associated heat transport, except for a few specific issues (overestimation of volume transports in the Southern Ocean and slight underestimation of the Atlantic ocean meridional overturning circulation and associated heat transport, the latter mostly linked to underestimation of western boundary northward transports). The results also demonstrate the complementarity of the assimilation components, all improving verification skill scores, for example the importance of the variational assimilation for the simulation of the reanalysis small-scale variability, the importance of the bias-correction scheme for correcting subsurface salinity errors or the role of surface nudging in driving the North Atlantic ocean circulation. The analyses presented here offer ideas for improving C-GLORS further and for the requirements of next-generation ocean reanalysis systems.

This paper describes the motivation for the creation of the Vulnerability, Impacts, Adaptation and Climate Services (VIACS) Advisory Board for the Sixth Phase of the Coupled Model Intercomparison Project (CMIP6), its initial activities, and its plans to serve as a bridge between climate change applications experts and climate modelers. The climate change application community comprises researchers and other specialists who use climate information (alongside socioeconomic and other environmental information) to analyze vulnerability, impacts, and adaptation of natural systems and society in relation to past, ongoing, and projected future climate change. Much of this activity is directed toward the co-development of information needed by decision-makers for managing projected risks. CMIP6 provides a unique opportunity to facilitate a two-way dialog between climate modelers and VIACS experts who are looking to apply CMIP6 results for a wide array of research and climate services objectives. The VIACS Advisory Board convenes leaders of major impact sectors, international programs, and climate services to solicit community feedback that increases the applications relevance of the CMIP6-Endorsed Model Intercomparison Projects (MIPs). As an illustration of its potential, the VIACS community provided CMIP6 leadership with a list of prioritized climate model variables and MIP experiments of the greatest interest to the climate model applications community, indicating the applicability and societal relevance of climate model simulation outputs. The VIACS Advisory Board also recommended an impacts version of Obs4MIPs and indicated user needs for the gridding and processing of model output.

Simulated inter-annual to decadal variability and trends in the North Atlantic for the 1958-2007 period from twenty global ocean - sea-ice coupled models are presented. These simulations are performed as contributions to the second phase of the Coordinated Ocean-ice Reference Experiments (CORE-II). The study is Part II of our companion paper (Danabasoglu et al., 2014) which documented the mean states in the North Atlantic from the same models. A major focus of the present study is the representation of Atlantic meridional overturning circulation (AMOC) variability in the participating models. Relationships between AMOC variability and those of some other related variables, such as subpolar mixed layer depths, the North Atlantic Oscillation (NAO), and the Labrador Sea upper-ocean hydrographic properties, are also investigated. In general, AMOC variability shows three distinct stages. During the first stage that lasts until the mid-to late-1970s, AMOC is relatively steady, remaining lower than its long-term (1958-2007) mean. Thereafter, AMOC intensifies with maximum transports achieved in the mid-to late-1990s. This enhancement is then followed by a weakening trend until the end of our integration period. This sequence of low frequency AMOC variability is consistent with previous studies. Regarding strengthening of AMOC between about the mid-1970s and the mid-1990s, our results support a previously identified variability mechanism where AMOC intensification is connected to increased deep water formation in the subpolar North Atlantic, driven by NAO-related surface fluxes. The simulations tend to show general agreement in their temporal representations of, for example, AMOC, sea surface temperature (SST), and subpolar mixed layer depth variabilities. In particular, the observed variability of the North Atlantic SSTs is captured well by all models. These findings indicate that simulated variability and trends are primarily dictated by the atmospheric datasets which include the influence of ocean dynamics from nature superimposed onto anthropogenic effects. Despite these general agreements, there are many differences among the model solutions, particularly in the spatial structures of variability patterns. For example, the location of the maximum AMOC variability differs among the models between Northern and Southern Hemispheres. (C) 2015 Elsevier Ltd. All rights reserved.

The surface ocean explains a considerable part of the inter-annual Tropical Atlantic variability. The present work makes use of observational datasets to investigate the effect of freshwater flow on sea surface salinity (SSS) and temperature (SST) in the Gulf of Guinea. In particular, the Congo River discharges a huge amount of freshwater into the ocean, affecting SSS in the Eastern Equatorial Atlantic (EEA) and stratifying the surface layers. The hypothesis is that an excess of river runoff emphasize stratification, influencing the ocean temperature. In fact, our findings show that SSTs in the Gulf of Guinea are warmer in summers following an anomalously high Congo spring discharge. Vice versa, when the river discharges low freshwater, a cold anomaly appears in the Gulf. The response of SST is not linear: temperature anomalies are considerable and long-lasting in the event of large freshwater flow, while in dry years they are less remarkable, although still significant. An excess of freshwater seems able to form a barrier layer, which inhibits vertical mixing and the entrainment of the cold thermocline water into the surface. Other processes may contribute to SST variability, among which the net input of atmospheric freshwater falling over EEA. Likewise the case of continental runoff from Congo River, warm anomalies occur after anomalously rainy seasons and low temperatures follow dry seasons, confirming the effect of freshwater on SST. However, the two sources of freshwater anomaly are not in phase, so that it is possible to split between atypical SST following continental freshwater anomalies and rainfall anomalies. Also, variations in air-sea fluxes can produce heating and cooling of the Gulf of Guinea. Nevertheless, atypical SSTs cannot be ascribed to fluxes, since the temperature variation induced by them is not sufficient to explain the SST anomalies appearing in the Gulf after anomalous peak discharges. The interaction processes between river runoff, sea surface salinity and temperature play an effective role in the interannual variability in the EEA region. Our results add a new source of variability in the area, which was often neglected by previous studies.