New and On-Going Research at the University of Reading; a PhD Mini Conference
LOCATION
Whiteknights, Reading RG6 6AH
Radar and severe convection, the dynamics of summer-time Arctic cyclones and anthropogenic impacts on atmospheric turbulence are three very different, yet cutting-edge, research projects that shall all be discussed in this mini-conference styled event. The wide range of topics, encapsulating different areas of meteorology and climate change research, were chosen to entice our audience to attend in-person. This was the first in-person RMetS SE event since the pandemic. Our speakers were three third-year PhD candidates at the University of Reading, Brian Lo, Hannah Croad and Isabel Smith. More information about our presenters and their presentations can be found below.
Speakers
Brian Lo
Towards operational use of ZDR columns for early detection of severe convection in the United Kingdom
Bio: Brian’s fascination in the subject of meteorology and physics started at the age of eight, when he visited the Hong Kong Observatory’s (HKO) Open Day in 2005. After having studied an integrated master’s degree in Natural Sciences specialising in Physics at the University of Cambridge, he went on to complete an MSc in Atmosphere, Oceans and Climate at the University of Reading. During the summers of 2017 and 2018, Brian worked at the HKO as a research intern exploring satellite nowcasting techniques using machine learning. He also contributed to the Observatory’s Short-range Warning of Intense Rainstorms in Localized Systems (SWIRLS) nowcasting system and was involved in releasing a community version of SWIRLS for use in other national meteorological agencies. Brian is now a third-year PhD candidate at the Department of Meteorology in the University of Reading. His research specialises in using radars to study severe convection
Abstract: Differential reflectivity (ZDR) columns were seen using a Met Office three-dimensional radar composite running on a subdomain of radars in the UK. A threshold-based algorithm that identifies a contiguous volume intersecting and extending 500m beyond the freezing level derived from the Met Office Global Model with ZDR 1.0dB and reflectivity ZH 10dBZ was implemented for the automatic detection of ZDR columns. Across three case days, detected ZDR columns were found to precede severe convection in tracked convective cells with a lead time of up to 20 minutes. Detecting ZDR columns having maximum values exceeding thresholds of approximately 1.6dB and 26dBZ of ZDR and ZH respectively within storms were optimal in nowcasting severe convection, although the sensitivity of this result varied across case days. This is consistent with physical understanding that ZDR columns are collocated with strong updrafts that contain a small concentration of millimetre-sized rain droplets that contribute to severe weather phenomena in convective cells.
Hannah Croad
Arctic Summer-time Cyclones Field Campaign
Bio: "Hannah Croad is a 3rd year PhD student at the University of Reading. She holds a MMet Meteorology and Climate degree from the University of Reading, which included a study year abroad at the University of Oklahoma. Her research interests are large-scale atmospheric dynamics and weather systems. During her undergraduate degree, Hannah worked on research projects about severe (convective) weather environments and tropical jet streams. In her PhD project she is investigating the dynamics of summer-time Arctic cyclones, including their interaction with sea ice. As part of her PhD project, Hannah was involved in the Arctic summer-time cyclones field campaign, based in Svalbard (Norway) in July and August 2022, where she was part of the team forecasting, flight planning, and conducting science flights. She recently spoke about the field campaign on BBC Radio 4’s Inside Science programme."
Abstract: The rapid decline of sea ice is permitting increased human activity in the summer-time Arctic, where it will be exposed to the risks of Arctic weather. Arctic cyclones are the major weather hazard in the summer-time Arctic, producing strong winds and ocean waves over large areas. One of the biggest uncertainties in our understanding of Arctic cyclones is how they interact with sea ice. This was the subject of the recent (July/August 2022) Arctic Summer-time Cyclones field campaign, where we conducted science flights through Arctic cyclones. We obtained the measurements required to investigate how sea ice coupling influences Arctic cyclone dynamics.
In this talk, I provided an introduction on Arctic cyclones, demonstrating that their structure can differ from mid-latitude cyclones. I then motivated and described the field campaign, outlining the aims, desired measurements, and equipment/instrumentation. With the field campaign now finished, I reviewed the science flights conducted and measurements obtained, and discuss future plans for using the data.
Isabel H. Smith
Using high-resolution climate models to predict increases in atmospheric turbulence
Bio: Isabel Smith is a meteorology PhD candidate at the University of Reading, UK. She was fascinated by weather and the atmosphere from a young age, being raised in both wet and windy Glasgow and Hong Kong. Isabel graduated with a first class combined master’s degree in Meteorology and Climate at the University of Reading. During her degree she was a part-time student forecaster at MeteoGroup (DNT) and interned at weathertrending. She is a RMetS student ambassador and helped to organise the RMetS 2021 Student and Early Careers Conference. Her PhD project focuses on upper-level atmospheric turbulence, and global climate model biases. She recently given a talk about her work at the European Geoscience Union Conference, in Vienna.
Abstract: Atmospheric turbulence has a serious, dangerous, and costly impact on aviation. Turbulence makes up most weather-related in-flight accidents and costs the global aviation sector up to US$1 billion every year. Upper-level turbulence can be broken down into four main types: Clear-Air Turbulence (CAT), Convectively Induced Turbulence (CIT), Near-Cloud Turbulence (NCT), and Mountain Wave Turbulence (MWT). Aviation is often impacted by CAT, which is not visible on radar and is therefore extremely hard to detect in advance of an encounter. Previous literature has shown that climate change is strengthening CAT globally, with increased severity particularly over the North Atlantic, a busy flight route, within the winter months. These findings have been based on CMIP3 and CMIP5 climate models, which have now been superseded by CMIP6 (Coupled Model Intercomparison Project Phase 6) models with higher resolution.
In this talk we built and developed these previous findings further by using the CMIP6 HighResMIP PRIMAVERA simulations, which have grid spacings from 135km to 25km. CAT has not previously been investigated with models that come this close to resolving individual patches of turbulence. Comparisons between several resolutions have given us a better understanding of how different climate models, and their grid spacings, represent turbulence. Despite some multidecadal and yearly variability, CAT is found to increase in frequency, in all turbulent severities, in time and with increased near-surface temperatures. Interestingly, atmosphere-only global climate models predict a smaller increase in CAT, in comparison to coupled atmosphere-ocean models. Our findings suggest that an increasing mean near-surface temperature over the North Atlantic will lead to further light to severe turbulence events, which results in extremely bumpy air travel, longer travel times, and increased CO2 emissions into the atmosphere.
Registration
REGISTRATION IS NOW CLOSED
Radar and severe convection, the dynamics of summer-time Arctic cyclones and anthropogenic impacts on atmospheric turbulence are three very different, yet cutting-edge, research projects that shall all be discussed in this mini-conference styled event. The wide range of topics, encapsulating different areas of meteorology and climate change research, were chosen to entice our audience to attend in-person. This was the first in-person RMetS SE event since the pandemic. Our speakers were three third-year PhD candidates at the University of Reading, Brian Lo, Hannah Croad and Isabel Smith. More information about our presenters and their presentations can be found below.
Speakers
Brian Lo
Towards operational use of ZDR columns for early detection of severe convection in the United Kingdom
Bio: Brian’s fascination in the subject of meteorology and physics started at the age of eight, when he visited the Hong Kong Observatory’s (HKO) Open Day in 2005. After having studied an integrated master’s degree in Natural Sciences specialising in Physics at the University of Cambridge, he went on to complete an MSc in Atmosphere, Oceans and Climate at the University of Reading. During the summers of 2017 and 2018, Brian worked at the HKO as a research intern exploring satellite nowcasting techniques using machine learning. He also contributed to the Observatory’s Short-range Warning of Intense Rainstorms in Localized Systems (SWIRLS) nowcasting system and was involved in releasing a community version of SWIRLS for use in other national meteorological agencies. Brian is now a third-year PhD candidate at the Department of Meteorology in the University of Reading. His research specialises in using radars to study severe convection
Abstract: Differential reflectivity (ZDR) columns were seen using a Met Office three-dimensional radar composite running on a subdomain of radars in the UK. A threshold-based algorithm that identifies a contiguous volume intersecting and extending 500m beyond the freezing level derived from the Met Office Global Model with ZDR 1.0dB and reflectivity ZH 10dBZ was implemented for the automatic detection of ZDR columns. Across three case days, detected ZDR columns were found to precede severe convection in tracked convective cells with a lead time of up to 20 minutes. Detecting ZDR columns having maximum values exceeding thresholds of approximately 1.6dB and 26dBZ of ZDR and ZH respectively within storms were optimal in nowcasting severe convection, although the sensitivity of this result varied across case days. This is consistent with physical understanding that ZDR columns are collocated with strong updrafts that contain a small concentration of millimetre-sized rain droplets that contribute to severe weather phenomena in convective cells.
Hannah Croad
Arctic Summer-time Cyclones Field Campaign
Bio: "Hannah Croad is a 3rd year PhD student at the University of Reading. She holds a MMet Meteorology and Climate degree from the University of Reading, which included a study year abroad at the University of Oklahoma. Her research interests are large-scale atmospheric dynamics and weather systems. During her undergraduate degree, Hannah worked on research projects about severe (convective) weather environments and tropical jet streams. In her PhD project she is investigating the dynamics of summer-time Arctic cyclones, including their interaction with sea ice. As part of her PhD project, Hannah was involved in the Arctic summer-time cyclones field campaign, based in Svalbard (Norway) in July and August 2022, where she was part of the team forecasting, flight planning, and conducting science flights. She recently spoke about the field campaign on BBC Radio 4’s Inside Science programme."
Abstract: The rapid decline of sea ice is permitting increased human activity in the summer-time Arctic, where it will be exposed to the risks of Arctic weather. Arctic cyclones are the major weather hazard in the summer-time Arctic, producing strong winds and ocean waves over large areas. One of the biggest uncertainties in our understanding of Arctic cyclones is how they interact with sea ice. This was the subject of the recent (July/August 2022) Arctic Summer-time Cyclones field campaign, where we conducted science flights through Arctic cyclones. We obtained the measurements required to investigate how sea ice coupling influences Arctic cyclone dynamics.
In this talk, I provided an introduction on Arctic cyclones, demonstrating that their structure can differ from mid-latitude cyclones. I then motivated and described the field campaign, outlining the aims, desired measurements, and equipment/instrumentation. With the field campaign now finished, I reviewed the science flights conducted and measurements obtained, and discuss future plans for using the data.
Isabel H. Smith
Using high-resolution climate models to predict increases in atmospheric turbulence
Bio: Isabel Smith is a meteorology PhD candidate at the University of Reading, UK. She was fascinated by weather and the atmosphere from a young age, being raised in both wet and windy Glasgow and Hong Kong. Isabel graduated with a first class combined master’s degree in Meteorology and Climate at the University of Reading. During her degree she was a part-time student forecaster at MeteoGroup (DNT) and interned at weathertrending. She is a RMetS student ambassador and helped to organise the RMetS 2021 Student and Early Careers Conference. Her PhD project focuses on upper-level atmospheric turbulence, and global climate model biases. She recently given a talk about her work at the European Geoscience Union Conference, in Vienna.
Abstract: Atmospheric turbulence has a serious, dangerous, and costly impact on aviation. Turbulence makes up most weather-related in-flight accidents and costs the global aviation sector up to US$1 billion every year. Upper-level turbulence can be broken down into four main types: Clear-Air Turbulence (CAT), Convectively Induced Turbulence (CIT), Near-Cloud Turbulence (NCT), and Mountain Wave Turbulence (MWT). Aviation is often impacted by CAT, which is not visible on radar and is therefore extremely hard to detect in advance of an encounter. Previous literature has shown that climate change is strengthening CAT globally, with increased severity particularly over the North Atlantic, a busy flight route, within the winter months. These findings have been based on CMIP3 and CMIP5 climate models, which have now been superseded by CMIP6 (Coupled Model Intercomparison Project Phase 6) models with higher resolution.
In this talk we built and developed these previous findings further by using the CMIP6 HighResMIP PRIMAVERA simulations, which have grid spacings from 135km to 25km. CAT has not previously been investigated with models that come this close to resolving individual patches of turbulence. Comparisons between several resolutions have given us a better understanding of how different climate models, and their grid spacings, represent turbulence. Despite some multidecadal and yearly variability, CAT is found to increase in frequency, in all turbulent severities, in time and with increased near-surface temperatures. Interestingly, atmosphere-only global climate models predict a smaller increase in CAT, in comparison to coupled atmosphere-ocean models. Our findings suggest that an increasing mean near-surface temperature over the North Atlantic will lead to further light to severe turbulence events, which results in extremely bumpy air travel, longer travel times, and increased CO2 emissions into the atmosphere.
Registration
REGISTRATION IS NOW CLOSED
