22nd November 2022

Science for Society

 

Morning Keynote Plenary

Weather Warnings – What’s the Point?

Dr Will Lang, Head of Situational Awareness, Met Office

In recent years, our understanding of the purpose and value of the UK’s National Severe Weather Warning Service (NSWWS) has evolved significantly. After 10 years of ‘impact-based’ warnings, NSWWS is now embracing an ‘action-based’ approach, with a focus on informing and empowering decision-makers – individuals, communities, organisations and governments – and positive and coordinated behaviour change in the face of impactful weather.

 

This presentation will explore the intersection of atmospheric science with behavioural science and other disciplines , using recent examples including the February storms and July heatwave of 2022.  

Improving the value chain of Earth Observations for Societal Applications

Magdalena Alonso Balmaseda, Head of Earth System Predictability Section, ECMWF, UK

Earth observations are at the core of the seamless forecasting activities. They are needed for forecast initialization, model development, process understanding and verification. But they also play an important role as boundary forcing. Here we focus on recent developments within the Horizon Europe project CONFESS,  where harmonized records of Earth observations are being used to improve the time-varying aspects of the tropospheric aerosols and land properties to improve the quality of the reforecasts used for extended range and seasonal predictions. We also illustrate the value of long observational oceanic records for the evaluation of seasonal forecasts of sea level, ocean heat content and marine heat waves, an activity carried out under the EuroSea project.

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Tropical Cyclones

Numerical simulation of Tropical Cyclones in the Philippines using the Weather Research and Forecasting (WRF) and Cloud-Resolving Storm Simulator (CReSS) model.

Kate Ann Esguerra, Computer Programmer I, University of the Philippines

The associated hazards of the tropical cyclones (TC) that occur near the Philippine archipelago have impacted numerous socio-economic aspects of the country. One way to mitigate these hazards is to properly forecast the TC’s characteristics, particularly its intense wind and rainfall. In this study, two numerical prediction models namely the Cloud Resolving Storm Simulator (CReSS) and Weather Research and Forecasting (WRF) were assessed by simulating two different TC intensities that occurred in 2018. The results on the track, rainfall and wind field of each case shows the proficiency of the models as well as its weakness in the simulation of TCs.

The Relationship between Sea Surface Temperature and North Atlantic Tropical Cyclone Rainfall over Ocean and Land

Dr Samantha Hallam, Post-Doctoral Researcher, ICARUS, Maynooth University, Ireland

There have been increasing losses from freshwater flooding associated with United States (US) landfalling hurricanes in recent years.  This study analyses the relationship between sea surface temperature and North Atlantic tropical cyclone precipitation (TCP)  for the period 1998-2017.

For a 1°C SST increase in the main development region (MDR), there is a 6% increase in the TCP rate (mmhr-1) over the Atlantic, which rises to over 40% over land (US states) and appears linked not only to the Clausius-Clapeyron relationship but also to the increase in tropical cyclone (TC) intensity associated with increasing SSTA. Total annual TCP is significantly correlated with the SST in the MDR. Over the Atlantic there is an increase of 116% and over land there is an increase of 140% in total TCP for a 1°C rise in SST in the MDR. Again, this is linked to the increase in windspeed and the number of TC tracks which also rises with positive SSTAs in the MDR. 

Overall, we find a different TCP response to rising SST over the ocean and land, with the response over land over four times more than the Clausius-Clapeyron rate. The links between SSTA in the MDR and both TCP rate and annual total TCP provide useful insights for seasonal to decadal US flood prediction from TCs and suggest that SSTA in the MDR may be a useful predictive index.

Trends of Tropical Cyclone-Induced Extreme Precipitation in East Asia

Jack Law, Masters Student, University of Edinburgh

This presentation investigates the trends in tropical cyclone-induced extreme precipitation intensity (TCEP) and the number of TCEP events in East Asia using a high-resolution observational rainfall dataset and best track data. Results show there is a significant increase in TCEP intensity by 33.4% basin-wide since 1951. This exceeds the rate of Clausius-Clapeyron scaling from expected warming. Meanwhile there is a large variability in TCEP frequency as it shows a weakly significant increase. These results are consistent between two periods: 1951-2015 (pre-satellite era) and 1979-2015 (satellite era). In particular, the subtropical region in East Asia receives the strongest and most significant increase in both TCEP intensity and frequency. The changes in TCEP intensity and frequency are robust across two different rainfall datasets and the use of a lower threshold for extreme precipitation. These changes cannot be explained by modes of climate variability and are most consistent with the effect of global warming and a decrease in typhoon translation speed.

Dynamical Equatorial Waves: Precursors to tropical cyclone occurrence and intensification

Gui-Ying Yang, Senior Research Scientist, NCAS Climate, University of Reading

Understanding and prediction of tropical cyclone (TC) occurrence and intensification on the medium range remains challenging. Here, we find that the pre-existing dynamical westward-moving equatorial waves can inform the risk of TC occurrence and intensification, based on a observational dataset synchronising TCs and equatorial waves identified from ERA5. Globally, the westward-moving equatorial waves are responsible for 60–70% of TC genesis events and for >80% of genesis events with strong intensity, related to the favourable dynamical conditions modulated by equatorial waves. The waves have the strongest effect on TC genesis in the North Pacific and North Atlantic. We further find that the westward-moving equatorial waves can enhance the intensification rate of TCs when storms locate in a certain phase of the waves. Coherent wave packets associated with TCs are identifiable up to two weeks ahead. Our findings suggest that westward-moving equatorial waves are useful precursors to TC activity, thus providing an unprecedented potential source for improving medium-range TC forecasts.

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Modelling

UKESM2: Current development of the physical core model HadGEM3 GC5 N96ORCA1

Till Kuhlbrodt, NCAS Science Theme Leader for Long-term Global Change, NCAS, Department of Meteorology, University of Reading

Currently the next version of the UK Earth System model, called UKESM2, is under development. It is planned to have UKESM2 ready in 2025, in time for CMIP7. Here we present the ongoing development of the physical climate model that is the core of UKESM2, which is HadGEM3 GC5 N96ORCA1. This development is a joined effort between the Met Office Hadley Centre and NCAS.  N96ORCA1 is a coarse-resolution version of HadGEM3, the Met Office Hadley Centre atmosphere-ocean GCM, with a resolution of about 150 km in the atmosphere and 100 km in the ocean. The presentation builds on the recent assessment of HadGEM3 GC5 across various spatial resolutions. Our work on N96ORCA1 is focussing on closing the heat and freshwater budgets, and on reducing a long-standing subsurface warm bias in the ocean. We present work in progress that hopefully will lead to improvements in the CMIP7 versions of HadGEM3 GC5 N96ORCA1 and of UKESM2. 

Representing Storylines with Causal Networks: Framework and example

Taro Kunimitsu, Senior Researcher, CICERO Center for International Climate Research

We show how embedding physical climate storylines into a causal network framework allows user-held values to be incorporated into the storyline, in the form of probabilistic Bayesian priors and decision making. These user-held values include expectations of the future climate and socioeconomic conditions, as well as risk-averseness of the user.
We exemplify this through a specific storyline, namely a storyline on the impacts of tropical cyclones on the European Union Solidarity Fund (Ciullo et al. 2021). We outline how the constructed causal network can incorporate value judgements, namely prospects on the cyclone intensity increase and on economic growth, and how the causal network responds to policy options chosen by the user. The resulting output from the network leads to individualized policy proposals, allowing the causal network to be used as a possible interface for policy exploration in stakeholder engagements.

Simulating Extreme Weather with Multi-Thousand Member High-Resolution Global Atmospheric Ensembles

Peter Watson, NERC Independent Research Fellow and Proleptic Senior Lecturer, University of Bristol

Multi-thousand member climate model simulations are highly valuable for showing characteristics of extreme weather events in different climates. However, until now, studies using such a physically-based approach have been limited to using models with a resolution much coarser than the most modern systems. We have developed a global atmospheric model with ~60km resolution that can be run in the climateprediction.net distributed computing system to produce such large datasets. This resolution is finer than that of many current global climate models and sufficient for good simulation of extratropical synoptic features such as storms. It also allows many extratropical extreme weather events to be simulated without requiring regional downscaling. We will show that this model's simulation of extratropical winter weather is competitive with that in other state-of-the-art models. We will also present the first results generated by this system. One application has been the production of ~2000 member simulations based on sea surface temperatures in severe future winters produced in the UK Climate Projections 2018 dataset, generating large numbers of examples of plausible extreme wet and warm UK seasons. Another is showing the increasing spatial extent of precipitation extremes in the Northern Hemisphere extratropics.

 

Comparison of Real Variable and Complex Variable Approaches to Models of Potential Flow

Saleem Ali, Student, United States Military Academy, Sebastian Neumann, Student, United States Military Academy,
Morgan Brown, Student, United States Military Academy, Nathon Segovia, Student, United States Military Academy

In this talk, we will present complex variable and real variable models of potential flow in two spatial dimensions. The complex variable approach is developed from the complex variable boundary element method with simple pole basis functions. The real variable approach utilizes the fundamental solution of Laplace’s equation in 2D. Both approaches develop a harmonic approximation function. Furthermore, both approaches are enhanced by the use of a node positioning algorithm, which is used to introduce additional degrees of freedom to the modeling process that can be used to better satisfy target boundary conditions. Collocation is used to fit each approximation function to boundary conditions modeling benchmark problems in potential flow. The two approaches will be compared with regard to maximum error when satisfying the target boundary conditions.

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Air Quality

Oxidative Potential of Fine Particulate Matter over National Capital Region, India

Dr Shivani, Assistant Professor, Indira Gandhi Delhi Technical University for Women, India

Delhi, the capital of India is among the top ten worst polluted cities in world. World Health Organization (WHO) has repeatedly reported that the annual average of fine particulate matter (PM2.5) for Delhi region exceeded the prescribed limits of air quality guidelines (10 µg m-3) by fourteen times. Rapid urbanization for the development of the region and population growth has led to high levels of particulate matter (PM) over Delhi and National Capital region (NCR), India. Consequently, deterioration of the air quality, serious health effects and climate change are the notable impacts of the alarming particulate matter levels. There have been numerous studies for the levels, composition and sources of particulate matter over Delhi. However, there is scarce of studies related to the mechanism of induced health effects caused by toxicity of PM over Delhi and NCR. Health effects associated with exposure to PM may derive from the oxidative stress initiated by the formation of reactive oxygen species (ROS) in the respiratory system by the chemical species in PM. The study describing the PM ROS generating potential with chemical components using source apportionment models is not attempted so far over NCR. This study presents the oxidative potential of fine particulate matter (PM2.5) samples collected over three sampling sites in NCR. 

Study of the evolution of CO2 concentration values obtained with an Eddy covariance infrastructure during 2011-2021: A case study at the Eastern Pyrenees  

Dr Beatriz Fernández-Duque, Post-doctoral researcher, Forest Science and Technology Centre of Catalonia (CTFC), Spain 

 

Alpine grassland is one of the main grassland types in Eurasia providing crucial goods and services for human population, including climate regulation and carbon cycling. However, their role as sources or sinks of CO2 is still not well understood due to the important lack of data in these ecosystems. Motivated for this lack of data, an Eddy covariance tower was installed at Pla de Riart (42º 03’ 48" N, 1º 30’ 48" E, 1003 m a.s.l.), a mountain grassland in the eastern Pyrenees. The Eddy covariance infrastructure was provided with an open-path IRGA (InfraRed Gas Analyzer) analyser (LI-7500, LI-COR Inc., Lincoln, NE, USA) to measure CO2 concentrations over a long-term period which covers 10 years. This unprecedent database was analysed by using harmonic functions to study the temporal CO2 evolution over time at an annual an intra-annual scale. The positive mean trend values for the studied period (399.65 ± 3.14 ppm for daytime values and 402.39 ± 2.97 ppm for night-time values) found at the station agree well with the general trend pattern described at other background sites. To conclude, it will be desirable to analyse more grassland sites according to the methodology described here in order to get insights on CO2 intra and inter-annual evolution over time in highly vulnerable alpine ecosystems.

Air Quality Impacts of Wildfires in the UK: The role of model resolution

Dr Benjamin Drummond, Senior Scientist, Met Office, UK

The Saddleworth Moor fire in 2018 was a high impact wildfire event that led to a considerable deterioration of air quality in nearby urban areas. Numerical modelling of wildfire smoke plumes is critical for emergency response during the event and for estimating impacts in the aftermath of the event. I will present a case study that explores the importance of model spatial resolution for predictions of pollutant concentrations from wildfires, focussing on air quality health impacts, using the Saddleworth Moor fire. A finer horizontal model resolution (2.2 km) gives a narrower smoke plume, with higher peak concentrations of pollutants within the plume, compared with a coarser model (12 km). The narrower plume given by the finer resolution model reduced fraction of the population affected by wildfire smoke, resulting in a lower estimate of excess mortality due to the fire. However, since concentrations within the plume were higher, a small proportion of the considered population (~10%) were exposed to considerably higher PM2.5 concentrations during the peak of the wildfire event. Model resolution was found to be an important factor when modelling air quality impacts of wildfire smoke.

Changes in Ambient Air Quality and Atmospheric Composition and Reactivity in the South East of the UK as a result of the COVID-19 Lockdown

Mark Nichols, Principal Air Quality Consultant, Hydrock / University of Brighton

The COVID-19 pandemic forced governments around the world to impose restrictions on daily life to prevent the spread of the virus. This resulted in unprecedented reductions in anthropogenic activity, and reduced emissions of certain air pollutants, namely oxides of nitrogen. The UK ‘lockdown’ was enforced on 23/03/2020, which led to restrictions on movement, social interaction, and ‘non-essential’ businesses and services. This study employed an ensemble of measurement and modelling techniques to investigate changes in air quality, atmospheric composition and boundary layer reactivity in the South East of the UK post-lockdown. The techniques employed included in-situ gas- and particle-phase monitoring within central and local authority air quality monitoring networks, remote sensing by long path Differential Optical Absorption Spectroscopy and Sentinel-5P's TROPOMI, and detailed 0-D chemical box modelling. Findings showed that de-trended NO2 concentrations decreased by an average of 14–38% when compared to the mean of the same period over the preceding 5-years. We found that de-trended particulate matter concentrations had been influenced by interregional pollution episodes, and de-trended ozone concentrations had increased across most sites, by up to 15%, such that total Ox levels were roughly preserved. 0-D chemical box model simulations showed the observed increases in ozone concentrations during lockdown under the hydrocarbon-limited ozone production regime, where total NOx decreased proportionally greater than total non-methane hydrocarbons, which led to an increase in total hydroxyl, peroxy and organic peroxy radicals. These findings suggest a more complex scenario in terms of changes in air quality owing to the COVID-19 lockdown than originally reported and provide a window into the future to illustrate potential outcomes of policy interventions seeking large-scale NOx emissions reductions without due consideration of other reactive trace species.

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Afternoon Keynote Plenary ​

Sources of Atmospheric Organic Aerosols and Investigating their Impacts on Health

Prof Jacqui Hamilton, NCAS Science Director, NCAS and University of York

Poor air quality is the biggest environmental factor contributing to premature mortality globally and long-term exposures to fine particulate matter (PM2.5) was estimated to contribute to 4.9 million premature deaths annually. Recently the WHO lowered their air quality guidelines from 10 ug/m3 to 5 ug/m3, however in some locations this will be very difficult to achieve. Therefore, understanding the toxicity of different types of particles can provide policy makers with priority emission sources to target specific regulations. A large fraction of PM2.5 in cities is secondary organic aerosol (SOA), but we lack the ability to characterise whether the biogenic or anthropogenic sources are dominant. Using high resolution mass spectrometry, we can start to unpick the complex chemical composition of SOA and use this to improve our understanding of the sources of SOA and to investigate their potentially toxicity to humans.    

Creatively Communicating Climate Change

Dr Adam Levy, Freelance Science Journalist & Creator of ClimateAdam

How can we talk about climate science more and better? There is a vast gulf between research and public and political understanding. Closing this gap and turning research into meaningful action is vitally important. To do this, scientists need to become (better) communicators - sharing the essential climate science that we all need to know, in ways that are true to themselves. Adam Levy will share the lessons learned in moving from climate science to journalism and communication, and touch on the many ways that climate change can - and should - be communicated. Whether it's a serious conversation for a podcast, or a playful 30 second Tiktok video, there are key approaches we can all use to share the information that matters the most, with everyone that needs to hear it.

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Climate

State of the UK Climate 2021

Michael Kendon, Climate Information Scientist, National Climate Information Centre (NCIC), Met Office

I will present some key findings from the State of the UK Climate 2021 report. This annual report by the Met Office National Climate Information Centre (NCIC) shows observations from the UK’s weather station network against the most recent decade, long-term averages and full climate series. The report is based mainly on the HadUK-Grid dataset at 1km resolution, maintained by the NCIC team.

 

Of particular interest is the incorporation of several million monthly rainfall observations from Ed Hawkin’s wonderful rainfall rescue data into HadUK-Grid, allowing our monthly rainfall series to be extended back to 1836 and illustrating the importance of such ongoing data rescue work. Also, we describe some significant weather events of the year, including storm Arwen in November including a comparison between this and the January 1953 East Coast storm surge event. The report includes contributions from the National Oceanography Centre on sea level rise, and phenology data from the Woodland Trust. We use the 1991-2020 reference period for the first time.

 

A week before the report’s publication in July 2021, the UK experienced a moment of climate history when temperatures exceeded 40°C for the first time. This unprecedented heatwave set a new UK all-time temperature record by a margin of 1.6°C. I will also present some observations from this extraordinary event.

The Next Generation of UK Regional Climate Projections

Dr Marina Baldissera Pacchetti, Research Fellow, University of Leeds and Barcelona Supercomputing Centre

This study uses the framework developed by Baldissera Pacchetti et al. (2021a, 2021b) to provide guidance on how to improve the quality of the next generation regional climate projections. The framework defines quality of projections in terms of “epistemic reliability”, which requires that information about future climate and related probabilities (if applicable) suitably represent the likelihood of different realizations of future climate and that there is an explanation of why this is the case. The framework specifies six quality dimensions to assess information about future regional climate, and the methods used to derive it: transparency, theory, historical empirical adequacy, diversity, completeness and number. Our assessment of the latest generation of UK national projections (UKCP18) showed that these projections do not score highly along all the quality dimensions of the framework (Baldissera Pacchetti et al. (2021b)). To broaden the scope of this work and identify gaps and opportunities for improvement in UK regional information about future climate, we have: (1) conducted a systematic literature review of published work on regional scale future precipitation for the UK and evaluated it with the quality framework and (2) conducted a series of semi-structured interviews with key UK-based experts on regional precipitation change about their assessment of current state-of-the art decision-relevant information about future regional precipitation change. Both the interview protocol and the analysis of the interview are based on the quality assessment framework that evaluates information and the methods used to derived it along the dimensions of the quality framework. Our results show that there are indeed quality gaps and ways in which the research community can achieve high quality regional climate information. However, we note that there isn’t always agreement amongst experts about how efforts should be distributed. We end with a series of recommendations derived from the analysis of the interview. 

Utilising Weather and Climate Research to Co-Develop Climate Services for Society

Joshua Macholl, Deployable Scientist, Met Office

Our climate is changing, and we are already seeing its impact on society through infrastructure resilience, international development and the race to net zero. The key question is, how do we successfully exploit weather and climate research to ensure that society can adapt to and mitigate climate change? Climate services are designed to address this challenge, to assist individuals and organisations in making informed decisions based around state-of-the-art climate simulations.

The difficulty for producers of climate services is to develop products that fully address user needs. For example, how do scientists understand the decision-making contexts of UK councils, energy and water industries, and communities in developing countries?

This talk provides an insight into climate services and discusses research undertaken to enhance the co-production of urban climate services with local authorities. Specifically, I discuss the development of a targeted questionnaire, designed to give a deeper understanding of user needs and a user-led aspect to service development. We found that this led to more focused conversations and an overall more time-efficient pass through the early stages of co-production. The additional learnings from this study will be of high interest to those looking to utilise atmospheric science for society.

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Oceans and Teleconnections

The Effects of Atmospheric Forcing on the Circulation and Water’s Physical Properties of the Northern Adriatic Sea 

Javad Babagolimatikolaei, PhD candidate in Atmospheric Science, University of Manchester

This presentation investigates the effects of atmospheric forcing on the circulation and physical properties of water in the northern Adriatic Sea. The northern basin of the Adriatic Sea has been selected due to its importance in the outflow formation and the effects of the Po River plume to the circulation of the Adriatic Sea. In both phenomena, atmospheric forcing effects lead to seasonal variability each year. This effect is mainly because the wind field changes the Po River direction in the different seasons. Also, the net flux which enters the northern Adriatic Sea from the atmosphere directly affects the rate of the outflow formation. Generally, the circulation in the Adriatic is a surface current from the Strait of Otranto that enters from the south in the eastern coast when attaching to the coast and forms a cyclonic circulation and leaves from the strait from the west part of the strait. The dense flow occurs in the cold season when the water loses heat. 
To investigate how the wind drives the circulation of the northern Adriatic Sea, we use ROMS (Regional Ocean Modelling System), a hydrodynamic ocean model developed at the University of Rutgers. ROMS is a free-surface, primitive-equation ocean model using a nonlinear terrain-following coordinate system. The model configuration consisted of 25 vertical layers and a horizontal grid spacing of roughly 2 km. The model ran for seven years (2012–2018) to spin up the ocean circulation, but only the last year’s model output will be discussed for this presentation. Our simulation employs GEBCO data for bathymetry, ERA-5 reanalyses for atmospheric conditions(13 parameters), ICOADS data for the sea’s climatology, and the World Ocean Atlas for the initial conditions. Although other studies have used models running for the whole Adriatic Sea, we discuss only the result of the northern basin to limit the scope of this presentation.


The comparison of model outputs and observation data shows that the model accuracy is acceptable, although some differences can be detectable in model outputs and observation data. The estimation shows that the error of temperature and salinity is less than 1.5 ⁰ C and 0.5 PSU, respectively, whereas the error for the current speed is 15–20%. 
Based on the model outputs, this simulation can appropriately model the physical properties of the Adriatic Sea, such as temperature, salinity, density, and general circulation of the northern basin. The model clearly shows the Po freshwater path when injected into the domain and also the wind-driven current. The model shows an anticyclonic circulation in July and August in the northern part due to the wind field. However, the model seems to underestimate the formation of the cold-season dense flow. To understand why the model has these problems in this matter, various reasons can be stated, such as model configuration. But, since the model calculates other parameters with appropriate accuracy, the problem is not related to the model configuration. Thus, we should address this issue when considering how outflow or dense flow is formed in the northern part. The outflow is formed in the cold season due to evaporation and sinking. We believe the wind data can be the main reason for this, particularly the bora wind. Bora winds are more common from November to March, from the northeast, ranging from one day to six days per month.


The underestimation of the wind and its effect on the northern basin circulation shows itself in the phenomena sensitive to this atmosphere forcing, like outflow formation. This is mainly because most dense water is formed when strong winds and cold air prevails in the region. This is a severe challenge that atmospheric models pose to oceanographers when modeling. For this reason, we suggest that atmospheric modelers pay attention to ERA-5 products when working on developing atmospheric models. It should be considered that we can see the improvement of the ERA-5 compared to ERA-Interim as some papers proved that the outflow had not been formed using ERA-Interim data as an atmosphere forcing of the ocean model. Although the coupling of the ocean and atmosphere is one solution, the massive computation time is its problem. This type of problem can be solvable with the cooperation of atmospheric and ocean modelers. Due to our long-term goals of studying the dense waters of the Mediterranean Sea and the behavior of the outflow over the Strait of Gibraltar, we started our analysis from the Adriatic Sea to understand how sensitive the model is to these atmospheric forcings.

What Potential for Improving Sub-Seasonal Predictions of the Winter NAO?

Chris Kent, Senior Scientist, Climate Dynamics, Met Office Hadley Centre

The North Atlantic Oscillation (NAO) is the leading mode of variability across the Atlantic sector in winter and is a key metric of extratropical forecast performance. Using a leading dynamical prediction system we assess sub-seasonal predictions (one month NAO with a lead time of 20-30 days) and investigate the potential for improving predictions using a large ensemble of dynamical hindcasts. We approach this topic through two questions, firstly, is monthly NAO skill related to medium-range performance? And secondly, can a strengthened MJO-NAO teleconnection improve monthly NAO skill? In the first part we find that forecast errors at the medium-range timescale are only weakly related to monthly NAO predictions. This implies that improving medium-range forecast performance is unlikely to drive significant improvements at longer lead times. In the second part we manually adjust the model forecast NAO to impose the observed MJO-NAO teleconnection. We find that perfect MJO forecasts and teleconnections lead to only small improvements in NAO prediction skill. This work indicates that monthly timescales may represent a predictability gap for the NAO and hence Euro-Atlantic winter climate in which genuine skill improvements are difficult to achieve.

Atmospherically Induced Water Waves in UK Coastal Zones

Clare Lewis, PhD Student, University of Reading 

Meteotsunamis are globally occurring shallow water waves which tend to be initiated by sudden pressure changes (±1 mb) and wind stress from moving atmospheric systems. Sources range from convective clouds, cyclones, squalls, atmospheric gravity waves and strong mid-tropospheric winds. When the water wave reaches the coastline, it is further amplified through coastal resonances where it can elevate the coastal water level and substantially increase flow velocities. Due to the rapid onset and unexpected nature of these waves they have the potential to cause destruction, injuries and even fatalities to coastal communities. Preliminary research has shown that since 2010 there have been over 47 meteotsunami events in UK waters. By highlighting two recent UK events we can look at the atmospheric conditions of meteotsunami and why society is often unaware of the risk.  

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Remote Sensing

A New Refractivity Retrieval Method

Ollie Lewis, PhD Student, Met Office and University of Exeter

Humidity can vary significantly over short spatial and temporal scales, however, it is currently difficult and expensive to measure directly.  A proposed new method uses routinely broadcast aircraft radio signals that have undergone measurable bending in the lower atmosphere to retrieve information about the refractivity structure (which is itself dependent on the atmospheric conditions).  The bending angle   With thousands of flights across UK airspace every day, with each aircraft broadcasting twice per second, there is the potential to tap into a vast source of atmospheric data at relatively low cost.  The technique uses interferometers mounted to radar towers to measure the refracted angle of radio signals, which can then be inverted to retrieve the refractivity field.  

Analysis of C-band Radar Observation from RELAMPAGO Field Campaign using Signal Processing Techniques

Vaibhav Tyagi, Research Scholar (DAASE), Indian Institute of Technology Indore, MP, India

In recent years, environmental remote sensing has grown rapidly and weather radars have gained popularity primarily due to their unique ability to detect storms as microwave signals can penetrate clouds and rain. This enables forecasters to provide timely information warnings and researchers to understand some of the complexities of meteorological

variable events. In this study involving radar remote sensing the objective is to understand the various aspects of C-band radar observations of convective storms that occurred during the RELAMPAGO field campaign using signal processing techniques. The polarimetric measurements from weather radars provide information about the shape and size of the targets and spectral decomposition of these polarimetric variables have been used to get additional information about the storm structure and dynamics. Both Doppler and polarimetric observations are used in spectral analysis for weather radar to represent polarimetric variables as a function of radial velocity. Spectral polarimetric variables: spectral power density, spectral differential reflectivity, and spectral coherency spectrum are estimated at various altitudes and at different distances from the radar. The properties of Doppler power spectrum as well as spectral polarimetric variables are analysed to derive insights about the microphysical and dynamical characteristics of precipitation systems. The results shows interesting microphysical processes like multimodal Doppler power spectrum, slope in the spectral differential reflectivity, lowering of co-polar coherency spectrum and broadening of power spectral density.

Impactful Dry Spells over Southern Africa: Characteristics and drivers

Gibbon Innocent Masukwedza, PhD Student, University of Sussex; Zimbabwe Meteorological Services Department

Dry and heat spells have the potential of altering the maize crop’s physiology and ultimately result in low yield. This study proposes a methodology of moving away from the generic dry spell definitions by using the water requirement satisfaction index (WRSI) output from the Tropical Applications of Meteorology using SATellite data – AgriculturaL Early waRning sysTem (TAMSAT-ALERT) as a metric of the impact such events have on the maize crop. We define these objectively identified events as impactful dry spells (IDS). The total exceedance of the maize crop’s upper-temperature optimal threshold is used to capture extreme temperatures during the growing season and is defined as impactful heat spells (IHS). Results of our analysis show that some seasons with relatively low yields were associated with the co-occurrence of severe IDS and IHS events specifically in the establishment and vegetative development phases. This implies that operational drought monitoring models with methodologies similar to that of TAMSAT-ALERT have the potential of inadvertently underestimating yield since they are incapable of incorporating the impact of heat on the crop’s physiology. We also investigate the rainfall characteristics based on the concept of Shannon entropy and show that seasons with relatively high (low) simulated yields are associated with (un)evenly distributed rainfall. Seasons of low simulated yields are shown to be associated with the southward displacement of Tropical Temperate Troughs; an anomalously weak Angola Low and Mozambique Channel Trough; an anomalously strong Botswana High, Mascarene High-Pressure, and St. Helena High-Pressure systems; coupled with inhibitive atmospheric conditions for convective cloud development. This is the direct opposite to atmospheric patterns in seasons with a high simulated yield.

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