ESP

Earth System Physics

Contacts:

Environmental Meteorology: From the Fundamentals of Climate to Operational Applications

ICTP & University of Trento Seminar Series

Overview

This series of lectures is a new joint initiative between the Earth System Physics group at ICTP and the Atmospherics Physics group at the University of Trento. They present the current state of research and operational implementation of all areas of weather and climate, past, present and future, and span basic theory, idealized and realistic modelling, through to applications of climate and weather in sectors that include the health, agriculture, energy and the economy.

These seminars are open to all those with an interest in climate and weather and also contribute to the training offered to ICTP pre-PhD diploma programme that provides scholarships to developing country students to and The Master of Science programme in Environmental Meteorology offered by the University of Trento and the University of Innsbruck, Austria.

Organizers

Adrian Tompkins (ICTP) and Simona Bordoni (Trento)

Registration

Participants are required to register in advance at:
https://zoom.us/meeting/register/tJ0lcuyurDMrEtbfP9f16GRLzqF1AiT7PHN7.
After registering, you will receive a confirmation email containing information about joining the meeting.

Jump to Seminar

  • 25/02/2021 Angela Benedetti @ ICTP "The role of aerosols in the predictability at the S2S scale"
  • 04/03/2021 Massimo Bollasina @ University of Trento "Improving our mechanistic understanding of the regional climate response to anthropogenic aerosols"
  • 11/03/2021 Allison Wing @ ICTP "Convective Self-Aggregation and Climate Sensitivity in a Multi-Model Ensemble of Radiative-Convective Equilibrium Simulations"
  • 18/03/2021 Ioana Colfescu @ University of Trento "The role of atmospheric weather noise in forcing the Atlantic Multidecadal Variability"
  • 25/03/2021 Tamma Carleton @ ICTP "Using economics and big data to measure the costs of climate change"
  • 08/04/2021 Ivana Stiperski @ University of Trento "Extending similarity theory into complex terrain"
  • 22/04/2021 Bertrand Carissimo @ University of Trento "Numerical modeling studies of atmospheric dispersion of pollutant around obstacles"
  • 29/04/2021 Benjamin Devenish @ University of Trento "Modelling the dispersion of volcanic ash in the atmosphere: 10 years on from Eyjafjallajökull"
  • 06/05/2021 Anna Creti @ ICTP "Wind farm revenues in Western Europe in present and future climate"
  • 13/05/2021 Anne Jones @ ICTP "Artificial Intelligence for Climate Impacts"
  • 20/05/2021 Veronika Huber @ ICTP "Climate impacts on cold- and heat-related mortality"
  • 27/05/2021 Gianni Tinarelli @ University of Trento "Modelling the dispersion of pollutants in the atmospheric boundary layer. The experience of ARIANET, products and applications"
  • 03/06/2021 Massimo Cassiani @ University of Trento "Stochastic models, an effective tool for simulating atmospheric dispersion and mixing"
  • 10/06/2021 Sandrine Bony @ ICTP "Mesoscale organization of trade-wind clouds: First insights from EUREC4A"

25/02/2021 15:00 @ ICTP
The role of aerosols in the predictability at the S2S scale
[Scientific Calendar]

Angela Benedetti

Angela Benedetti
Senior Scientist at the Research Department, Earth System Assimilation Section, UV and Visible.
European Centre for Medium-Range Weather Forecasts (ECMWF)
Reading, UK

[https://womanscientific.blogspot.com/]

Abstract

Recent years have seen the rise of global operational atmospheric composition models for several applications including climate monitoring, provision of boundary conditions for regional air quality forecasting, and energy sector applications, to mention a few. Typically global forecasts are provided in the medium-range up to five days ahead.

Thanks to a series of EU-funded projects (GEMS, MACC, MACC-II, MACC-III), and now Copernicus, ECMWF has developed the capability to run its Integrated Forecast System (IFS) with atmospheric composition variables. The composition configuration is at the core of the Copernicus Atmospheric Service (CAMS) which provides operational 4D-Var analyses and forecasts of aerosols and reactive gases, as well as many other user-oriented products both at the European scale and at the global scale.

This capability is now being exploited for applications other than atmospheric composition forecasting per se. This is part of an effort to understand how increased complexity in the Earth System model can have beneficial effects on the prediction.

Recent work has shown that the atmospheric constituents such as aerosols, ozone and other trace gases can be important modulators of the radiative processes at the S2S scale. For example, the direct effect of aerosols may influence predictability via the MJO modulation of the aerosol fields. In clear-sky, the cumulative aerosol forcing can modify the radiative balance of the atmospheric column and introduce temperature perturbations which depend on the dominant aerosol types and their optical properties. Wind-emitted aerosols such as dust appear to be the main contributors. However, biomass burning aerosols may also play an important part, in particular for areas where extensive seasonal biomass burning takes place such as central Africa and Indonesia.

Several examples related to this effort will be presented. In particular, the experiments using the ECMWF's coupled Ensemble Prediction System to investigate the role of aerosols in the predictability at the seasonal-to-subseasonal (S2S) will be discussed. Aerosol forecast fields at the weekly/monthly scales will also be presented and compared with corresponding analyses to assess their quality.

 

04/03/2021 15:00 @ University of Trento
Improving our mechanistic understanding of the regional climate response to anthropogenic aerosols
[Scientific Calendar]

Massimo Bollasina

Massimo Bollasina
School of GeoSciences, University of Edinburgh.
Edinburgh, UK

Abstract

By inducing anomalous heating gradients in the atmosphere and at the surface via radiation changes and diabatic heating anomalies, especially in the tropics, aerosols can affect the large-scale atmospheric circulation and, as a result, induce teleconnections which extend the climate impact of aerosols far from their source regions to produce anomalies at hemispheric, if not near-global, scales. One of the key uncertainties hindering our ability to project future climate change more robustly, especially at regional scale, is our limited confidence in understanding and quantifying the atmospheric dynamical response to climate forcing. The latter, in the case of aerosols, is also poorly characterised due to compounding uncertainties in the aerosol processes themselves. This talk will discuss various aspects of the atmospheric circulation response to regional and global aerosol forcing and associated climate impact by using multiple sets of experiments with state-of-the-art climate models with perturbed aerosol emissions. Particular focus is given to tropical-extratropical interactions and the monsoon system, and the underlying physical pathways generating regional and remote climate anomalies are discussed.

 

11/03/2021 15:00 @ ICTP
Convective Self-Aggregation and Climate Sensitivity in a Multi-Model Ensemble of Radiative-Convective Equilibrium Simulations
[Scientific Calendar]

Allison Wing

Allison Wing
Assistant Professor in the Department of Earth, Ocean and Atmospheric Science (EOAS)
Florida State University (FSU)
Florida, USA

[https://myweb.fsu.edu/awing/]

Abstract

The Radiative-Convective Equilibrium Model Intercomparison Project (RCEMIP) is an intercomparison of multiple types of numerical models, including atmospheric general circulation models (GCMs), cloud-resolving models (CRMs), global cloud-resolving models (GCRMs), large eddy simulation models (LES), and single column models (SCMs), configured in radiative-convective equilibrium (RCE). RCE is an idealization of the tropical atmosphere that has long been used to study basic questions in climate science, and is employed here to investigated the response of clouds and convective activity to warming, cloud feedbacks and climate sensitivity, and the aggregation of convection and its role in climate.

Results are presented from the RCEMIP ensemble of more than 30 different models. The robustness of the RCE state across the RCEMIP ensemble is assessed, in terms of mean profiles of temperature, humidity, and cloudiness, and the occurrence of self-aggregation is identified. While there are significant differences across the RCEMIP ensemble in the representation of humidity and cloudiness, nearly all models exhibit self-aggregation and there is agreement that self-aggregation acts to dry the atmosphere and reduce high cloudiness. The dependence of cloudiness and the degree of self-aggregation on SST and the resulting influence on the climate sensitivity of the RCE state is also compared across the RCEMIP ensemble. High clouds tend to rise and warm slightly with warming, and in a majority of models, decrease in extent. There is no clear tendency for either an increase or decrease in self-aggregation with warming, but changes in self-aggregation with warming partially explain the extreme spread in simulated climate sensitivities across the RCEMIP ensemble."

 

18/03/2021 15:00 @ University of Trento
The role of atmospheric weather noise in forcing the Atlantic Multidecadal Variability
[Scientific Calendar]

Ioana Colfescu

Ioana Colfescu
Research Scientist
National Centre for Atmospheric Science (NCAS), University of Leeds
Leeds, UK

Abstract

The Atlantic Multidecadal Variability (AMV) modulates various climate features worldwide with enormous societal and economic implications, including variations in hurricane activity in the Atlantic, sea-level changes, West African and Indian monsoon rainfall, European climate, and hemispheric- scale surface temperature. Leading hypotheses regarding the nature and origin of AMV focus primarily on its links with oceanic and coupled ocean-atmosphere internal variability, and on its response to external forcing. The role of another possible process, that of atmospheric noise forcing of the ocean, has received less attention. This work addressed here by means of historical coupled simulations and diagnostic experiments, which isolate the influences of external and atmospheric noise forcings. Our findings show that external forcing is an important driver of the simulated AMV. They also demonstrate that weather noise is key in driving the simulated internal AMV in the southern part of the (0°-60°N) AMV region, and that weather noise forcing is responsible for up to 10%-20% of the multidecadal internal SST variability in some isolated areas of the sub-polar gyre region. Ocean dynamics independent from the weather noise forcing is found to be the dominant cause of multidecadal SST in the northern part of the AMV region.

 

25/03/2021 15:00 @ ICTP
Using economics and big data to measure the costs of climate change
[Scientific Calendar]

Tamma Carleton

Tamma Carleton
Assistant Professor of Economics at the Bren School of Environmental Science and Management
University of California
Santa Barbara, USA

[https://bren.ucsb.edu/people/tamma-carleton]

Abstract

Estimating the global marginal damages caused by emitting a single ton of carbon dioxide is central to climate policy. However, current measurements of this “social cost of carbon” are based on low-resolution structural models that are not empirically calibrated. In this talk, I will present a new approach from the Climate Impact Lab that combines best-available data, econometrics, and climate science to both update the social cost of carbon and provide climate damage estimates for individual sectors of the economy at local level. Our results contrast starkly with the current estimates of climate damages informing climate policy in the US and beyond.

 

08/04/2021 15:00 @ University of Trento
Extending similarity theory into complex terrain
[Scientific Calendar]

Ivana Stiperski

Ivana Stiperski
Full Professor Department of Atmospheric and Cryospheric Sciences (ACINN)
Universität Innsbruck
Innsbruck, Austria

[https://www.uibk.ac.at/acinn/people/ivana-stiperski.html.en]

Abstract

Turbulence in the atmospheric boundary layer is characterized not only by the magnitude of its fluxes, but also by the state of anisotropy of its Reynolds stress tensor. Anisotropy is strongly influenced by turbulence generation mechanisms such as shear, thermal stratification, and surface characteristics. My recent results show that anisotropy plays a key role not only in the transport of momentum but it is also a key missing variable in similarity scaling relations. In this talk I will show why the information on anisotropy should always be included in any study of turbulence and how it can be used to formulate a novel surface layer scaling framework that extends Monin-Obukhov similarity theory to complex terrain.

 

22/04/2021 15:00 @ University of Trento
Numerical modeling studies of atmospheric dispersion of pollutant around obstacles
[Scientific Calendar]

Bertrand Carissimo

Bertrand Carissimo
Associate Professor at Ecole des Ponts, France and
Senior Scientist at EDF R&D

[https://www.cerea-lab.fr/membres/carissimo_bertrand]

Abstract

In urban neighborhood and around industrial plants, the atmospheric dispersion of pollutants is strongly affected by the presence of buildings. They affect the mean flow field and the turbulence and these in turn will affect the concentrations levels. We describe the use of Computational Fluid Dynamics models (adapted for the atmosphere), following either an Eulerian/Eulerian approach or an hybrid Eulerian/Lagrangian formulation. The results are illustrated using measurements of the Mock Urban Setting Test (MUST) campaign performed in the USA. Using the same field campaign, we will also show how we can use data assimilation of the measurements between the buildings to improve the numerical simulation in urban environments.

 

29/04/2021 15:00 @ University of Trento
Modelling the dispersion of volcanic ash in the atmosphere: 10 years on from Eyjafjallajökull
[Scientific Calendar]

Benjamin Devenish
Atmospheric Dispersion Group
Meteorological Office, UK

Abstract

It has been 10 years since the ash cloud from the eruption of Eyjafjallajökull caused unprecedented disruption to air traffic across Europe. During this event, the London Volcanic Ash Advisory Centre (VAAC), hosted by the UK Met Office, provided advice and guidance on the expected location of volcanic ash in the atmosphere using observations and the atmospheric dispersion model NAME (Numerical Atmospheric-Dispersion Modelling Environment). Rapid changes in regulatory response and procedures during the eruption introduced the requirement to also provide forecasts of ash concentrations, representing a step-change in the level of interrogation of the dispersion model output. Although disruptive, the longevity of the event afforded the scientific community the opportunity to observe and extensively study the transport and dispersion of a volcanic ash cloud. I will discuss what we learnt from that event and the developments we have made to NAME in the decade since the eruption of Eyjafjallajökull. Much of the focus has been on improving the representation of the eruption source parameters which are subject to considerable uncertainty. This has included the application of Bayesian methods to reconstructing the source from satellite data and the use of integral plume models to determine the mass emission rate and other properties of the eruption column. Since the downwind spread of ash is sensitive to the distribution of ash particle size and density, considerable effort has also been made to improve their representation in NAME including secondary effects such as aggregation and particle shape. I will illustrate the effect of these and other changes to NAME.

 

06/05/2021 15:00 @ ICTP
Wind farm revenues in Western Europe in present and future climate
[Scientific Calendar]

Anna Creti

Anna Creti
Professor Laboratoire d'Économie de Dauphine-Centre de Géopolitique de l'Energie et des Matières Premières (LeDA-CGEMP).
Paris Dauphine University
Paris, France

Abstract

Wind energy is one of the key drivers of energy transition, however the flow of investments into this industry is hampered by the uncertainty of the future revenues, arising from the natural variability of the resource, the impact of climate change on wind potential and future electricity prices, and the policy risks. In this article we quantify the uncertainty of the net present value of standardized wind farms in European countries and evaluate the level and cost of support mechanisms needed to guarantee the profitability of the wind fleet under present and future climate. To this end, we build a localized model for wind power output and a country-level model for electricity demand and prices taking into account hourly variation of wind, load and prices, using reanalysis data, climate projections and Integrated Assessment Model (IAM) scenarios. Our methodology is general, but for specific evaluations we focus on the examples of France, Germany and Denmark. Our study reveals that support mechanisms in these countries are needed for wind energy to be profitable under current market prices and current climate. Under future climate, using several scenarios for climate change and energy transition, we also show that the evolution of both price and wind production does not allow the wind energy industry in these countries to develop in a free market environment and that support mechanisms will still be needed in future. The cost of these support mechanisms for a 15-year period is evaluated to 57–172 billion euros in France, 232–397 billion euros in Germany, and 18–50 billion euros in Denmark, depending on the scenario considered and the level of penetration of wind energy.

 

13/05/2021 15:00 @ ICTP
Artificial Intelligence for Climate Impacts
[Scientific Calendar]

Anne Jones

Anne Jones
Research Staff Member.
IBM Research Centre, UK

[https://researcher.watson.ibm.com/researcher/view.php?person=ibm-Anne.Jones]

Abstract

Climate change adaptation in both public and private sectors urgently requires better risk quantification tools to inform decision-making and planning across multiple timescales. In this presentation, I will give an overview of the research activities in IBM's "AI for Climate Impacts" research theme, an initiative to build resilience to climate change by developing AI-enhanced and cloud-enabled models to quantify climate risk. I will describe applications of AI techniques to the specific challenge of improving flood risk quantification, including the use of simulation model surrogates, automated ground truth mapping and model calibration, and machine learning approaches to quantifying and propagating multiple sources of uncertainty.

 

20/05/2021 15:00 @ ICTP
Climate impacts on cold- and heat-related mortality
[Scientific Calendar]

Veronika Huber

Veronika Huber
Senior Researcher.
Universidad Pablo de Olavide (UPO)
Sevilla, Spain

Abstract

Exposure to cold and heat poses a risk to human health. This talk will present recent work about the impacts of climate change on temperature-related excess mortality, encompassing attribution of observed changes and future projections. The geographic scale of the presented studies ranges from hundreds of cities worldwide, based on the Multi-City Multi-Country (MCC) Collaborative Research Project, to individual countries in Europe. Besides introducing basic concepts and summarizing recent published results, the talk will discuss novel approaches for taking acclimatization/adaptation into account when projecting possible future trajectories of temperature-related excess mortality.

 

27/05/2021 15:00 @ University of Trento
Modelling the dispersion of pollutants in the atmospheric boundary layer. The experience of ARIANET, products and applications.
[Scientific Calendar]

Gianni Tinarelli

Gianni Tinarelli
Arianet S.r.l.
Milan, Italy

Abstract

The atmospheric dispersion of pollutants is one of the main phenomena that must be described to obtain an assessment of the air pollution. Among the tools that may allow this, numerical dispersion models constitute one of the main ones. They allow to reconstruct the behavior of pollutants released into the atmosphere by both human activities (transport, heating, industry) and natural phenomena (volcanoes, fires, sand storms). Pollutants are transported by wind and dispersed by turbulence, chemically transformed, deposited by surface contact or removed by rainfall: the aim of the models is to reproduce this complex phenomenology to assess air quality levels that may be harmful to human health and ecosystems. ARIANET has a more than ventennial history in both developing and using this kind of models for many applications at different scales, ranging from impact studies of local industrial pollutant sources to the development, use and maintenance of air quality forecast systems at the national scale. Aim of the seminar is to describe the various products developed and available at ARIANET, including both the Lagrangian Particle Dispersion Model SPRAY and the Eulerian Chemical Transport Model FARM widely used by many institutions in Italy and to give an overview of the many applications of these modeling tools such as in the fields of impact assessment, emergency response, odours, fires, and forecasting systems.

 

03/06/2021 15:00 @ University of Trento
Stochastic models, an effective tool for simulating atmospheric dispersion and mixing
[Scientific Calendar]

Massimo Cassiani

Massimo Cassiani
Senior Scientist at Atmosphere and Climate Department.
Norwegian Institute for Air Research
Kjeller, Norway

Abstract

Turbulence in the atmosphere is typically described as random and unpredictable and requires statistical approaches. In this spirit many processes driven by turbulence can be successfully and efficiently modelled using stochastic approaches. Similarly, but in a wider sense, sub-grid scale dispersion and mixing processes that are not explicitly resolved by atmospheric flow simulations can be often modelled by using stochastic approaches for the considered spatial and temporal scales. I will discuss the formulation and application of simple stochastic models for the simulation of processes related to atmospheric dispersion of gases and particles, with spatial scales ranging from few meters (from an emitting local scalar source) to global.

 

10/06/2021 15:00 @ ICTP
Mesoscale organization of trade-wind clouds: First insights from EUREC4A
[Scientific Calendar]

Sandrine Bony

Sandrine Bony
Directrice de Recherche (CNRS)
Laboratoire de Meteorologie Dynamique (LMD/IPSL)
Sorbonne Université
Paris, France

[https://emc3.lmd.jussieu.fr/en/group-members/sbony]

Abstract

Shallow convection exhibits a large diversity of spatial organizations at the mesoscale. Patterns such as cloud streets, open cells or closed cells have long been identified and characterized, but they are not representative of the patterns that can be found over the warm subtropical oceans. Recently, a few prominent patterns of trade-wind clouds have been identified over the tropical western Atlantic. Based on observations, I will show that these patterns depend on environmental conditions, and that they exert different radiative impacts. This raises two questions: What are the physical processes underlying changes in the mesoscale organization of shallow clouds? and do they matter for climate feedbacks? Answering these questions was one of the motivations for organizing the EUREC4A campaign (http://eurec4a.eu/). During this field study which took place in Jan-Feb 2020 near Barbados, multiple observing platforms characterized the trade-wind clouds together with their dynamical and thermodynamical environment on a wide range of scales. I will present early insights from the campaign, and will discuss some of the processes that appear to be important for the mesoscale organization of tradewind clouds.

 

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