EUREC4A-UK: Elucidating the role of cloud-circulation coupling in climate
Lead Research Organisation:
University of Leeds
Department Name: School of Earth and Environment
Abstract
EUREC4A-UK is a programme of observational and modelling research which aims
to study the detailed aerosol and cloud processes in the life cycle of shallow trade
cumulus clouds and the two-way interactions between the cloud processes and the
large-scale dynamics. The different responses of these clouds to warming in global
climate models (GCM) explain most of the inter-model differences, yet the physics
of these responses remains poorly constrained. The programme is focussed on
the participation of UK scientists and the BAS Twin Otter aircraft in EUREC4A
(Elucidating the Role of Clouds-Circulation Coupling in Climate). EUREC4A is
a coordinated international campaign that aims to address the current lack of understanding of
the processes controlling the response of trade-wind cumulus clouds to changing environmental
conditions in a warmer climate. The goal of EUREC4A is to examine the interplay between the
clouds, atmospheric circulations and climate sensitivity. EUREC4A-UK will make a unique and self-
contained contribution to the international programme by: (i) providing observational facilities which
are needed as part of the coordinated field campaign; (ii) conducting and leading the analysis of
the aerosols, cloud microphysics and boundary-layer processes in the life cycle of shallow trade
cumulus clouds; (iii) placing the analysis in the context of the EUREC4A problems by modelling the
two-way interactions between the cloud processes and the large-scale dynamics; and (iv) applying
the results by testing the new convection scheme in the UM and using the improved model to determine
the dominant processes controlling the cloud fields. International partners will complement the re-
search with a focus on observing and modelling the macrophysical properties and the environment
of trade-cumulus clouds in order to determine: (i) what controls the convective mass flux, mesoscale
organization and depth of shallow-cumulus clouds; (ii) how the trade-cumulus cloud fraction varies
with turbulence, convective mixing and large-scale circulations; and (iii) the impact this variation has
on atmospheric radiation.
The radiative properties of the trade-wind cumulus clouds that are ubiquitous over the tropical oceans have a major influence on the Earth's radiation budget. The response to global warming of these clouds is therefore critical for global mean cloud feedbacks. It is the differing response to warming that explains most of the spread of climate sensitivity in climate models. Hence, a better understanding is required of the mechanisms that control the low-level cloud fraction. The urgency of the research is made clear by the fact that the World Climate Research Programme endorses the EUREC4A field project which supports the Grand Challenge on Clouds, Circulation and Climate Sensitivity.
There is a clear need for EUREC4A-UK because the aerosol,
cloud and precipitation processes influence the macrophysical properties of the clouds in different
environments. For example, the vertical distribution of rain
can affect the concentration and size of cloud drops in the upper detrainment layers, which influ-
ences cloud radiative properties. The intensity of rain and evaporation of raindrops influences the
strength of gust fronts and hence secondary cloud-production. However, model calculations of the
rate of production of rain and hence the quantity of rain are uncertain due to the complex interactions
of aerosols, entrainment, turbulence and giant cloud condensation nuclei (GCCN). These processes
depend on the environment conditions, controlled by the large-scale dynamics. Equally, the aerosol-
cloud-precipitation processes can influence the larger-scale dynamics, for example through radiative
transfer. Indeed there are many interactions between processes on a range of scales that need to be
understood and represented in models.
to study the detailed aerosol and cloud processes in the life cycle of shallow trade
cumulus clouds and the two-way interactions between the cloud processes and the
large-scale dynamics. The different responses of these clouds to warming in global
climate models (GCM) explain most of the inter-model differences, yet the physics
of these responses remains poorly constrained. The programme is focussed on
the participation of UK scientists and the BAS Twin Otter aircraft in EUREC4A
(Elucidating the Role of Clouds-Circulation Coupling in Climate). EUREC4A is
a coordinated international campaign that aims to address the current lack of understanding of
the processes controlling the response of trade-wind cumulus clouds to changing environmental
conditions in a warmer climate. The goal of EUREC4A is to examine the interplay between the
clouds, atmospheric circulations and climate sensitivity. EUREC4A-UK will make a unique and self-
contained contribution to the international programme by: (i) providing observational facilities which
are needed as part of the coordinated field campaign; (ii) conducting and leading the analysis of
the aerosols, cloud microphysics and boundary-layer processes in the life cycle of shallow trade
cumulus clouds; (iii) placing the analysis in the context of the EUREC4A problems by modelling the
two-way interactions between the cloud processes and the large-scale dynamics; and (iv) applying
the results by testing the new convection scheme in the UM and using the improved model to determine
the dominant processes controlling the cloud fields. International partners will complement the re-
search with a focus on observing and modelling the macrophysical properties and the environment
of trade-cumulus clouds in order to determine: (i) what controls the convective mass flux, mesoscale
organization and depth of shallow-cumulus clouds; (ii) how the trade-cumulus cloud fraction varies
with turbulence, convective mixing and large-scale circulations; and (iii) the impact this variation has
on atmospheric radiation.
The radiative properties of the trade-wind cumulus clouds that are ubiquitous over the tropical oceans have a major influence on the Earth's radiation budget. The response to global warming of these clouds is therefore critical for global mean cloud feedbacks. It is the differing response to warming that explains most of the spread of climate sensitivity in climate models. Hence, a better understanding is required of the mechanisms that control the low-level cloud fraction. The urgency of the research is made clear by the fact that the World Climate Research Programme endorses the EUREC4A field project which supports the Grand Challenge on Clouds, Circulation and Climate Sensitivity.
There is a clear need for EUREC4A-UK because the aerosol,
cloud and precipitation processes influence the macrophysical properties of the clouds in different
environments. For example, the vertical distribution of rain
can affect the concentration and size of cloud drops in the upper detrainment layers, which influ-
ences cloud radiative properties. The intensity of rain and evaporation of raindrops influences the
strength of gust fronts and hence secondary cloud-production. However, model calculations of the
rate of production of rain and hence the quantity of rain are uncertain due to the complex interactions
of aerosols, entrainment, turbulence and giant cloud condensation nuclei (GCCN). These processes
depend on the environment conditions, controlled by the large-scale dynamics. Equally, the aerosol-
cloud-precipitation processes can influence the larger-scale dynamics, for example through radiative
transfer. Indeed there are many interactions between processes on a range of scales that need to be
understood and represented in models.
Planned Impact
Governments and businesses world wide, and the general public will benefit greatly from this research because of the greater accuracy (reduced uncertainty) in climate model predictions that will result from this research. Specifically, EUREC4A will help to reduce the uncertainty in climate sensitivity, or estimates of aerosol-radiative forcing by advancing our understanding of cloud processes and their feedbacks. Improved planning for climate change will deliver major economic benefits. Advancing understanding and modelling of clouds and circulation in the trade-wind regions is also very important for improving Numerical Weather Prediction models.
The UK addition would also contribute to the goals of the NCAS-led project the North Atlantic Climate System Integrated Study (ACSIS). Furthermore, the Global Energy and Water Cycle Exchanges Project (GEWEX) Aerosols, Clouds, Precipitation and Climate (ACPC) programme want to include EUREC4A since the cloud systems and circulation will be measured so well. This proposal provides a unique opportunity to add urgently needed measurements of aerosol and cloud processes.
The UK addition would also contribute to the goals of the NCAS-led project the North Atlantic Climate System Integrated Study (ACSIS). Furthermore, the Global Energy and Water Cycle Exchanges Project (GEWEX) Aerosols, Clouds, Precipitation and Climate (ACPC) programme want to include EUREC4A since the cloud systems and circulation will be measured so well. This proposal provides a unique opportunity to add urgently needed measurements of aerosol and cloud processes.
Organisations
- University of Leeds (Lead Research Organisation)
- National Center for Scientific Research (Centre National de la Recherche Scientifique CNRS) (Collaboration)
- Max Planck Society (Collaboration)
- Meteorological Office UK (Collaboration)
- Laboratoire de Météorologie Dynamique (Project Partner)
- Max Planck Institutes (Project Partner)
- Caribbean Int. Meteorology & Hydrology (Project Partner)
- University of Oxford (Project Partner)
- Met Office (Project Partner)
Publications
Denby L
(2020)
Discovering the Importance of Mesoscale Cloud Organization Through Unsupervised Classification
in Geophysical Research Letters
Lachlan-Cope T
(2020)
Clouds and Aerosols observed during EUREC4A by the UK Twin Otter aircraft.
Saffin L
(2021)
Driving a Convection Parametrization with EUREC4A Observations
Stevens B
(2021)
EUREC<sup>4</sup>A
in Earth System Science Data
Stevens B
(2020)
EUREC4A: First Impressions
| Description | New methods using machine learning have been developed to classify the cloud types and boundary-layer structures. A new Lagrangian trajectory method has been developed to provide the input conditions required to run the LES model that we are using (MONC). |
| Exploitation Route | The new methods will be used by the scientists in the large international EUREC4A project to help answer the question about the role of low level cloud fraction on climate change. This will in turn have immense implications for climate models. |
| Sectors | Environment,Government, Democracy and Justice |
| Description | The Met Office has benefited as a result of EUREC4A-UK research contributing to testing and refining the new convection parametrisation scheme (CoMorph) of the Unified Model (UM). EUREC4A-UK research also contributed to developing the convection-permitting global configuration of the Unified Model and the regional model configuration RA3. The public will ultimately benefit as a result of improved local and global forecasts. National Meteorological Services in the Caribbean have gained enhanced capability of forecasters in understanding local weather, such as localized storms, through the training workshop and forecast test-bed led by EUREC4A-UK scientists. The local populations are vulnerable to high-impact rainfall events right across the Caribbean. The project supported capability development within the Caribbean through forecasting activities linked to the field campaign and through lectures and exercises on the underpinning science needed for model development. |
| First Year Of Impact | 2019 |
| Sector | Agriculture, Food and Drink,Education,Environment |
| Impact Types | Economic,Policy & public services |
| Description | Caribbean Weather Forecasting Initiative, Workshop |
| Geographic Reach | Multiple continents/international |
| Policy Influence Type | Influenced training of practitioners or researchers |
| Impact | National Meteorological Services in the Caribbean have gained enhanced capability of forecasters in understanding local weather, such as localized storms, through the training workshop and forecast test-bed. The project supported capability development within the Caribbean through forecasting activities linked to the field campaign and through lectures and exercises on the underpinning science needed for model development. Through the workshop, forecasters enhanced their capacity to monitor and forecast local weather with the use of state-of-the-art, high-resolution weather forecasting models; especially related to dry-season conditions. From the forecasters, the researchers gained knowledge of weather variability that will influence their research missions. The forecast testbed plans were drafted at the end of the workshop and dry-runs of the virtual forecast testbed briefings were conducted with researchers in the United Kingdom during December 2019 and early January 2020. During the workshop forecasters also had the opportunity to describe their own numerical weather prediction modelling systems and to develop recommendations and ideas for the use of numerical weather prediction in their routine operations. |
| Title | Identifying mesoscale cloud structures using unsupervised machine learning |
| Description | A neural network can, without labelled training data, automatically discover different forms of cloud organization and through this learn to group input images containing similar cloud structures together. This was demonstrated by first training a neural network with 10,000 triplets of input image tiles sampled from 3 months of GOES-16 data and then studying the clustering of predictions produced by the network on 1,000 image tiles not seen during training. Using hierarchical clustering, it was shown that not only does the model identify different cloud structures and group images with similar structures but also generates a representation where the similarity between different structures can be studied. Through the use of two channels of the GOES-16 radiance measurements in the long- and short-wave frequency range, as well as common metrics of cloud structure, it was shown that different cloud structures have distinct radiative and morphological properties. This indicates that the neural network discovers cloud structures which have unique physical characteristics. |
| Type Of Material | Improvements to research infrastructure |
| Year Produced | 2019 |
| Provided To Others? | Yes |
| Impact | The application to new spatial domains without needing hand-labelled training data and the automatic discovery of the cloud structure types present enables systematic study of very disparate cloud types (e.g., mesoscale convective systems, cold-air outbreaks, cirrus, and ship-tracks) and regimes of cloud organization across the Earth. For example, having quantified the type of cloud structures present at a given location and time, the environmental conditions may be extracted from reanalysis data sets and analysed to provide insight into what conditions are required for different forms of convective organization to occur. The temporal evolution of one type of cloud structure into another (e.g., closed- to open-cell stratocumulus) can also be studied by combining the model's ability to represent similarity between cloud structures together with observations from high-temporal resolution geostationary satellite images (GOES-16 ?t = 10 min). This can be done by studying the trajectory of a given spatial domain through the embed- ding space of the neural network (see section 2 for details), enabling quantitative analysis of the transition between different regimes. In addition, the technique is applicable beyond the study of clouds and their interaction with the environment and can be applied to autonomously discover coherent structures of a given length-scale in any 2D geophysical field. This opens up the possibility of identifying structures which drive physical behaviour which are currently unknown, and only appear when different fields are composited together, and eliminates the need for hand-labelling of training data to study patterns in geophysical data. |
| Description | Bjorn Stevens and his group in Germany |
| Organisation | Max Planck Society |
| Department | Max Planck Institute for Meterology |
| Country | Germany |
| Sector | Charity/Non Profit |
| PI Contribution | Data gathered by the BAS Twin Otter aircraft during the field campaign and the analysis of that data. The cloud physics data is of particular interest. Also contributions to the successful preparations of the field campaign. |
| Collaborator Contribution | Bjorn Stevens and Sandrine Bony are responsible for EUREC4A. The partners provided platforms for the field campaign and the operation of the instruments on those platforms, as well as analysis of the data gathered. |
| Impact | Successful preparation and execution of the EUREC4A field campaign. |
| Start Year | 2019 |
| Description | Met Office involvement in EUREC4A |
| Organisation | Meteorological Office UK |
| Country | United Kingdom |
| Sector | Academic/University |
| PI Contribution | Provision of BAS Twin Otter data gathered in the EUREC4A field campaign and analysis of data. Organisation of forecast meetings and logistics for the field campaign |
| Collaborator Contribution | Staff time setting up model runs and providing output leading up to the field campaign and during it. Participation in WP work doing and helping with model runs and interpretation of model results. Comparisons with observations. Staff time during the workshop and testbed. Staff time as a mission scientist during the field campaign. |
| Impact | Successful workshop and testbed. Successful preparations for the field campaign. Successful field campaign. |
| Start Year | 2019 |
| Description | Sandrine Bony and her group in France |
| Organisation | National Center for Scientific Research (Centre National de la Recherche Scientifique CNRS) |
| Country | France |
| Sector | Academic/University |
| PI Contribution | Provision of data from the BAS Twin Otter aircraft gathered during the field campaign and analysis of the data. The cloud physics data in particular is of great interest. |
| Collaborator Contribution | Dr Bony is the PI of EUREC4A and as such is responsible along with Prof Bjorn Steven for making the project possible. Contributions of whole EUREC4A project, in particular data from the French aircraft gathered during the field campaign. |
| Impact | Successful preparation and completion of the EUREC4A field campaign. |
| Start Year | 2019 |
| Title | Lagtraj: a tool for deriving forcings along Lagrangian trajectories |
| Description | Lagtraj is a novel framework for the calculation of atmospheric trajectories and the input files for Lagrangian simulations along these trajectories based on reanalysis data. The simulations can be either Single Column Model simulations or Large-Eddy simulations. Lagtraj aims to streamline the workflow that is required to perform these simulations and perform sensitivity studies, and to ensure simulations are set up in a traceable fashion. Lagtraj has been developed to serve as a community tool that can be further extended with different input and output formats. |
| Type Of Technology | Software |
| Year Produced | 2022 |
| Open Source License? | Yes |
| Impact | This tool has allowed us to set up Large-Eddy Simulations for EUREC4A, and the derived trajectories have also been used to analyse satellite observations and weather models. |
| URL | https://github.com/EUREC4A-UK/lagtraj/ |
| Description | Caribbean Weather Forecasting Initiative Forecast Testbed |
| Form Of Engagement Activity | Participation in an activity, workshop or similar |
| Part Of Official Scheme? | No |
| Geographic Reach | International |
| Primary Audience | Study participants or study members |
| Results and Impact | During the testbed, the same forecasters that participated in the workshop held in 2019 worked in dispersed teams, collaborating via the CMO-licensed web-conferencing system, to deliver weather forecasts to the scientists involved in the field campaign of the EUREC4A project. The scientists needed forecasts in order to plan their flights. The local expertise from these forecasters was an important part of the planning. The testbed participants evaluated the forecasts using information gathered during the project. |
| Year(s) Of Engagement Activity | 2020 |
| URL | https://eurec4a.uk/forecast_testbed/ |
| Description | Caribbean Weather Forecasting Initiative Workshop 2 |
| Form Of Engagement Activity | Participation in an activity, workshop or similar |
| Part Of Official Scheme? | No |
| Geographic Reach | International |
| Primary Audience | Study participants or study members |
| Results and Impact | Through a partnership between the Caribbean Meteorological Organization (CMO) and the EUREC4A-UK project, led by the University of Leeds, the Caribbean Weather Forecasting Initiative has been leveraged to support the Severe Weather Forecast Programme (SWFP) in the Eastern Caribbean. The workshops 1 and 2 and forecast testbed support the SWFP by developing collaboration practice among regional forecasters and helping forecasters to understand the capabilities and limitations of high-resolution NWP models and global ensemble systems. National Meteorological Services in the Caribbean have gained enhanced capability of forecasters in understanding local weather, such as localized storms, through the training workshop 2. The project supported capability development within the Caribbean through forecasting activities linked to the synoptic conditions experienced during the EUREC4A field campaign and through lectures and exercises on the underpinning science needed for model development. |
| Year(s) Of Engagement Activity | 2023 |
| URL | http://www.cmo.org.tt/eurec4a.html |
| Description | Caribbean Weather Forecasting Initiative Workshop I |
| Form Of Engagement Activity | Participation in an activity, workshop or similar |
| Part Of Official Scheme? | No |
| Geographic Reach | International |
| Primary Audience | Study participants or study members |
| Results and Impact | Through a partnership between the Caribbean Meteorological Organization (CMO) and the EUREC4A-UK project, led by the University of Leeds, the Caribbean Weather Forecasting Initiative has been leveraged to support the Severe Weather Forecast Programme (SWFP) in the Eastern Caribbean. The workshops and forecast testbed support the SWFP by developing collaboration practice among regional forecasters and helping forecasters to understand the capabilities and limitations of high-resolution NWP models and global ensemble systems. National Meteorological Services in the Caribbean have gained enhanced capability of forecasters in understanding local weather, such as localized storms, through the training workshop and forecast test-bed. The project supported capability development within the Caribbean through forecasting activities linked to the field campaign and through lectures and exercises on the underpinning science needed for model development. |
| Year(s) Of Engagement Activity | 2019 |
| URL | http://www.cmo.org.tt/eurec4a.html |
| Description | EUREC4A UM SCM simulations - ParaCon |
| Form Of Engagement Activity | A formal working group, expert panel or dialogue |
| Part Of Official Scheme? | No |
| Geographic Reach | National |
| Primary Audience | Professional Practitioners |
| Results and Impact | Talk at the UK Met Office for a plenary meeting of the ParaCon programme |
| Year(s) Of Engagement Activity | 2022 |
| Description | EUREC4A: large-eddy simulations and parametrisation development |
| Form Of Engagement Activity | A formal working group, expert panel or dialogue |
| Part Of Official Scheme? | No |
| Geographic Reach | National |
| Primary Audience | Professional Practitioners |
| Results and Impact | Presentation in the context of the Met Office Academic Partnership. |
| Year(s) Of Engagement Activity | 2022 |