Review of trace organic chemicals in urban stormwater: Concentrations, distributions, risks, and drivers - Kefeng Zhang; Zhaozhi Zheng; Lena Mutzner; Baiqian Shi; David McCarthy; Pierre Le-Clech; Stuart Khan; Tim D. Fletcher; Marty Hancock; Ana Deletic (Water Research, 2024)

Evaluating the readiness for electric vehicle adoption among the urban population using geospatial techniques - Anna Charly; Gourav Misra; Shubham Sonarghare; Rowan Fealy; Tim McCarthy; Brian Caulfield (Journal of Transport Geography, 2024)

State of the UK Climate 2023 - Mike Kendon; Amy Doherty; Dan Hollis; Emily Carlisle; Stephen Packman; Mark McCarthy; Svetlana Jevrejeva; Andrew Matthews; Joanne Williams; Judith Garforth; Tim Sparks (International Journal of Climatology, 2024)

A conceptual framework to help choose appropriate blue nature-based solutions - Géraldine Pérez; Bethan C. O'Leary; Elena Allegri; Gema Casal; Cindy C. Cornet; Silvia de Juan; Pierre Failler; Stein Fredriksen; Catarina Fonseca; Elisa Furlan; Artur Gil; Julie P. Hawkins; et al. (Journal of Environmental Management, 2024)

Marine coastal biodiversity and services in Ireland in a three-dimensional context: Scientific, news media, and legislative - Gema Casal; Tim McCarthy (Ocean & Coastal Management, 2023)

State of the UK Climate 2022 - Mike Kendon; Mark McCarthy; Svetlana Jevrejeva; Andrew Matthews; Joanne Williams; Tim Sparks; Fritha West (International Journal of Climatology, 2023)

State of the UK Climate 2021 - Mike Kendon; Mark McCarthy; Svetlana Jevrejeva; Andrew Matthews; Tim Sparks; Judith Garforth; John Kennedy (International Journal of Climatology, 2022)
INTRODUCTION This report provides a summary of the UK weather and climate through the calendar year 2021, alongside the historical context for a number of essential climate variables. This is the eighth in a series of annual “State of the UK Climate” publications and an update to the 2020 report (Kendon et al ., 2021). It provides an accessible, authoritative and up‐to‐date assessment of UK climate trends, variations and extremes based on the most up‐to‐date observational datasets of climate quality. The majority of this report is based on observations of temperature, precipitation, sunshine and wind speed from the UK land weather station network as managed by the Met Office and a number of key partners and co‐operating volunteers. The observations are carefully managed such that they conform to current best‐practice observational standards as defined by the World Meteorological Organization (WMO). The observations also pass through a range of quality assurance procedures at the Met Office before application for climate monitoring. Time series of near‐coast sea‐surface temperature and sea level are also presented and in addition there is a short section on phenology which provides dates of “first leaf” and “bare tree” indicators for four common shrub or tree species. The reliance of this report on these observations highlights the ongoing need to adequately maintain the observation networks, in particular the UK land weather station network, into the future, to ensure that this UK climate monitoring capability is continued. National and regional statistics in this report are from the HadUK‐Grid dataset which is the principal source of data (Hollis et al ., 2019). Temperature and rainfall series from this dataset extend back to 1884 and 1836, respectively. Details of the datasets used throughout this report and how the various series which are presented are derived are provided in the appendices. A recent development to the underpinning dataset has been the inclusion of several million recently digitized historical monthly rainfall data (Hawkins et al ., 2022). These data significantly improve the geographical representation of rainfall before 1960 and allow for the extension of the national series back to 1836. The report presents summary statistics for the most recent year 2021 against the most recent decade 2012–2021, and following World Meteorological Organization (WMO) climatological best‐practice against the most recent 30‐year standard climate normal period 1991–2020 and the baseline period 1961–1990 (WMO, 2017). These two 30‐year reference periods do not overlap. The full series provide longer‐term context, while a comparison is also made to centennial averages for the Central England Temperature series. The decade 2012–2021 is a nonstandard reference period, but it provides a 10‐year “snapshot” of the most recent experience of the UK's climate and how that compares to historical records. This means that differences between 2012–2021 and the 30‐year reference periods may reflect shorter‐term decadal variations as well as long‐term trends. For this annual publication, the most recent decade (currently 2012–2021) changes every year, while the most recent 30‐year reference period changes every decade. For this year's report, we use the 30‐year reference period 1991–2020 for the first time, updated from 1981 to 2010 for last year's report (Kendon et al ., 2021). The baseline reference period 1961–1990 is retained, as this is a consistent reference period used not only throughout the series of State of UK Climate reports but also more widely for historical comparison, climate change monitoring and climate modelling following the WMO best‐practice. Throughout the report's text the terms “above normal,” “above average,” etc. refer to the 1991–2020 reference period unless otherwise stated. The majority of maps in this report show the year 2021 relative to the 1991–2020 reference period, that is, they are anomaly maps which show the spatial variation in this difference from average. Maps of actual values are in most cases not displayed because these are dominated by the underlying climatology, which for this report is of a lesser interest than the year‐to‐year variability. These data are presented to show what has happened in recent years, not necessarily what is expected to happen in a changing climate. Values quoted in tables throughout this report are rounded, but where the difference between two such values is quoted in the text (e.g., comparing the most recent decade with 1991–2020), this difference is calculated from the original unrounded values. Updates compared to state of UK climate 2020 The most recent 30‐year reference period is changed from 1981–2010 to 1991–2020. The dataset used to generate the summer North Atlantic Oscillation index is changed. Figures showing the UK average daily mean temperature and daily rainfall for each day of the year are added. A figure showing UK annual mean wind speed from 1969 has been added. The sea‐level section has been revised. Feedback We would welcome suggestions or recommendations for future annual publications of this report. Please send any feedback to the Met Office at ncic@metoffice.gov.uk . This State of the UK Climate report was supported by the Met Office Hadley Centre Climate Programme funded by BEIS and Defra.

Prediction of disability-free survival in healthy older people - Johannes Tobias Neumann; Le T. P. Thao; Anne M. Murray; Emily Callander; Prudence R. Carr; Mark R. Nelson; Rory Wolfe; Robyn L. Woods; Christopher M. Reid; Raj C. Shah; Anne B. Newman; Jeff D. Williamson; et al. (GeroScience, 2022)
Prolonging survival in good health is a fundamental societal goal. However, the leading determinants of disability-free survival in healthy older people have not been well established. Data from ASPREE, a bi-national placebo-controlled trial of aspirin with 4.7 years median follow-up, was analysed. At enrolment, participants were healthy and without prior cardiovascular events, dementia or persistent physical disability. Disability-free survival outcome was defined as absence of dementia, persistent disability or death. Selection of potential predictors from amongst 25 biomedical, psychosocial and lifestyle variables including recognized geriatric risk factors, utilizing a machine-learning approach. Separate models were developed for men and women. The selected predictors were evaluated in a multivariable Cox proportional hazards model and validated internally by bootstrapping. We included 19,114 Australian and US participants aged ≥65 years (median 74 years, IQR 71.6–77.7). Common predictors of a worse prognosis in both sexes included higher age, lower Modified Mini-Mental State Examination score, lower gait speed, lower grip strength and abnormal (low or elevated) body mass index. Additional risk factors for men included current smoking, and abnormal eGFR. In women, diabetes and depression were additional predictors. The biased-corrected areas under the receiver operating characteristic curves for the final prognostic models at 5 years were 0.72 for men and 0.75 for women. Final models showed good calibration between the observed and predicted risks. We developed a prediction model in which age, cognitive function and gait speed were the strongest predictors of disability-free survival in healthy older people. Trial registration Clinicaltrials.gov (NCT01038583)

Common, low-frequency, rare, and ultra-rare coding variants contribute to COVID-19 severity - Chiara Fallerini; Nicola Picchiotti; Margherita Baldassarri; Kristina Zguro; Sergio Daga; Francesca Fava; Elisa Benetti; Sara Amitrano; Mirella Bruttini; Maria Palmieri; Susanna Croci; Mirjam Lista; et al. (Human Genetics, 2022)
The combined impact of common and rare exonic variants in COVID-19 host genetics is currently insufficiently understood. Here, common and rare variants from whole-exome sequencing data of about 4000 SARS-CoV-2-positive individuals were used to define an interpretable machine-learning model for predicting COVID-19 severity. First, variants were converted into separate sets of Boolean features, depending on the absence or the presence of variants in each gene. An ensemble of LASSO logistic regression models was used to identify the most informative Boolean features with respect to the genetic bases of severity. The Boolean features selected by these logistic models were combined into an Integrated PolyGenic Score that offers a synthetic and interpretable index for describing the contribution of host genetics in COVID-19 severity, as demonstrated through testing in several independent cohorts. Selected features belong to ultra-rare, rare, low-frequency, and common variants, including those in linkage disequilibrium with known GWAS loci. Noteworthily, around one quarter of the selected genes are sex-specific. Pathway analysis of the selected genes associated with COVID-19 severity reflected the multi-organ nature of the disease. The proposed model might provide useful information for developing diagnostics and therapeutics, while also being able to guide bedside disease management.

State of the UK Climate 2020 - Mike Kendon; Mark McCarthy; Svetlana Jevrejeva; Andrew Matthews; Tim Sparks; Judith Garforth (International Journal of Climatology, 2021)
INTRODUCTION This report provides a summary of the UK weather and climate through the calendar year 2020, alongside the historical context for a number of essential climate variables. This is the seventh in a series of annual ‘State of the UK climate’ publications and an update to the 2019 report (Kendon et al ., 2020). It provides an accessible, authoritative and up‐to‐date assessment of UK climate trends, variations and extremes based on the most up to date observational datasets of climate quality. The majority of this report is based on observations of temperature, precipitation, sunshine and wind speed from the UK land weather station network as managed by the Met Office and a number of key partners and co‐operating volunteers. The observations are carefully managed such that they conform to current best practice observational standards as defined by the World Meteorological Organization (WMO). The observations also pass through a range of quality assurance procedures at the Met Office before application for climate monitoring. Time series of near‐coast sea‐surface temperature and sea‐level are also presented and in addition a short section on phenology which provides dates of first leaf and bare tree indicators for four common shrub or tree species. National and regional statistics in this report are from the HadUK‐Grid dataset which is the principal source of data (Hollis et al ., 2019). Temperature and rainfall series from this dataset extend back to 1884 and 1862, respectively. Details of the datasets used throughout this report and how the various series which are presented are derived are provided in the appendices. The report presents summary statistics for the most recent year 2020 against the most recent decade 2011–2020, the most recent 30‐year reference period (1981–2010) and the climate reference period 1961–1990. The full series provide longer‐term context, while a comparison is also made to centennial averages for the Central England Temperature series. The decade 2011–2020 is a non‐standard reference period, but it provides a 10‐year ‘snapshot’ of the most recent experience of the UK's climate and how that compares to historical records. This means differences between 2011 and 2020 and 30‐year reference periods may reflect shorter‐term decadal variations as well as long‐term trends. For this annual publication, the most recent decade (currently 2011–2020) changes every year, while the most recent 30‐year reference period (currently 1981–2010) changes every decade. For next year's report, the most recent 30‐year reference period will change from 1981–2010 to 1991–2020, while the climate reference period 1961–1990 will be retained. However, this report also includes a brief summary of key differences between preliminary 1991–2020 and 1981–2010 averages for temperature and rainfall. Throughout the report's text the terms “above normal” and “above average” and so on refer to the 1981–2010 baseline reference period unless otherwise stated. The majority of maps in this report show the year 2020 relative to the 1981–2010 reference period—that is, they are anomaly maps which show the spatial variation in this difference from average. Maps of actual values are in most cases not displayed because these are dominated by the underlying climatology, which for this report is of a lesser interest than the year‐to‐year variability. These data are presented to show what has happened in recent years, not necessarily what is expected to happen in a changing climate. Values quoted in tables throughout this report are rounded, but where the difference between two such values is quoted in the text (e.g., comparing the most recent decade with 1981–2010), this difference is calculated from the original unrounded values. Updates Compared to State of UK Climate 2019 A chart showing global surface temperature has been added. The section on sea level rise has been revised. A section summarizing key differences between preliminary 1991–2010 and 1981–2010 averages has been added. Feedback We would welcome suggestions or recommendations for future annual publications of this report. Please send any feedback to the Met Office at ncic@metoffice.gov.uk This State of the UK Climate report was supported by the Met Office Hadley Centre Climate Programme funded by BEIS and Defra.

State of the UK Climate 2019 - Mike Kendon; Mark McCarthy; Svetlana Jevrejeva; Andrew Matthews; Tim Sparks; Judith Garforth (International Journal of Climatology, 2020)
INTRODUCTION This report provides a summary of the UK weather and climate through the calendar year 2019, alongside the historical context for a number of essential climate variables. This is the sixth in a series of annual ‘State of the UK Climate’ publications and an update to the 2018 report (Kendon et al ., 2019). It provides an accessible, authoritative and up‐to‐date assessment of UK climate trends, variations and extremes based on the most up to date observational datasets of climate quality. The majority of this report is based on observations of temperature, precipitation, sunshine and wind speed from the UK land weather station network as managed by the Met Office and a number of key partners and co‐operating volunteers. The observations are carefully managed such that they conform to current best practice observational standards as defined by the World Meteorological Organization (WMO). The observations also pass through a range of quality assurance procedures at the Met Office before application for climate monitoring. Time series of near‐coast sea‐surface temperature (SST) and sea‐level are also presented and in addition a short section on phenology which provides dates of first leaf and bare tree indicators for four common shrub or tree species. National and regional statistics in this report are from the HadUK‐Grid dataset (Hollis et al ., 2019). Temperature and rainfall series from this dataset extend back to 1884 and 1862, respectively. Details are provided in the relevant sections and appendices. The report presents summary statistics for the year 2019 and the most recent decade (2010–2019) relative to 1961–1990 and 1981–2010 averages. The period 2010–2019 is a non‐standard reference period, but it provides a 10‐year ‘snapshot’ of the most recent experience of the UK's climate and how that compares to historical records. This means differences between 2010 and 2019 and the baseline reference averages may reflect shorter‐term decadal variations as well as long‐term trends. These data are presented to show what has happened in recent years, not necessarily what is expected to happen in a changing climate. The majority of maps in this report show the year 2019 relative to the 1981–2010 baseline reference averaging period—that is, they are anomaly maps which show the spatial variation in this difference from average. Maps of actual values are in most cases not displayed because these are dominated by the underlying climatology, which for this report is of a lesser interest than the year‐to‐year variability. Throughout the report's text the terms ‘above normal’ and ‘above average’, and so on refer to the 1981–2010 baseline reference averaging period unless otherwise stated. Values quoted in tables throughout this report are rounded, but where the difference between two such values is quoted in the text (e.g., comparing the most recent decade with 1981–2010), this difference is calculated from the original unrounded values. Updates compared to State of UK Climate 2018 A section on phenology has been added The method used to calculate rainfall percentiles (fig. 31) has been revised Updated climate data to HadUK‐Grid version 1.0.2.0, including data rescue projects that have improved or extended early monthly sunshine and rainfall series. Feedback We would welcome suggestions or recommendations for future publications of this report. Please send any feedback to the Met Office at ncic@metoffice.gov.uk This State of the UK Climate report was supported by the Met Office Hadley Centre Climate Programme funded by BEIS and Defra.

State of the UK climate 2018 - Mike Kendon; Mark McCarthy; Svetlana Jevrejeva; Andrew Matthews; Tim Legg (International Journal of Climatology, 2019)
INTRODUCTION This report provides a summary of the UK weather and climate through the calendar year 2018, alongside the historical context for a number of essential climate variables. This is the fifth in a series of annual “State of the UK climate” publications and an update to the 2017 report (Kendon et al ., 2018). It provides an accessible, authoritative and up‐to‐date assessment of UK climate trends, variations and extremes based on the most up to date observational datasets of climate quality. The majority of this report is based on observations of temperature, precipitation, sunshine and wind speed from the UK land weather station network as managed by the Met Office and a number of key partners and co‐operating volunteers. The observations are carefully managed such that they conform to current best practice observational standards as defined by the World Meteorological Organization (WMO). The observations also pass through a range of quality assurance procedures at the Met Office before application for climate monitoring. In addition, time series of near‐coast sea‐surface temperature (SST) and sea‐level rise are also presented. The process for generating national and regional statistics from these observations has been updated since Kendon et al ., 2018. This report makes use of a new dataset, HadUK‐Grid, which provides improved quality and traceability for these national statistics along with temperature and rainfall series that extend back into the 19th Century. Differences with previous data are described in the relevant sections and appendices. The report presents summary statistics for year 2018 and the most recent decade (2009–2018) against 1961–1990 and 1981–2010 averages. Year 2009–2018 is a non‐standard reference period, but it provides a 10‐year “snapshot” of the most recent experience of the UK's climate and how that compares to historical records. This means differences between 2009 and 2018 and the baseline reference averages may reflect shorter‐term decadal variations as well as long‐term trends. These data are presented to show what has happened in recent years, not necessarily what is expected to happen in a changing climate. The majority of maps in this report show year 2018 against the 1981–2010 baseline reference averaging period—that is, they are anomaly maps which show the spatial variation in this difference from average. Maps of actual values are in most cases not displayed because these are dominated by the underlying climatology, which for this report is of a lesser interest than the year‐to‐year variability. Throughout the report's text the terms “above normal” and “above average,” etc. refer to the 1981–2010 baseline reference averaging period unless otherwise stated. Values quoted in tables throughout this report are rounded, but where the difference between two such values is quoted in the text (for example, comparing the most recent decade with 1981–2010), this difference is calculated from the original unrounded values. FEEDBACK We would welcome suggestions or recommendations for future publications of this report. Please send any feedback to the Met Office at ncic@metoffice.gov.uk This State of the UK Climate report was supported by the Met Office Hadley Centre Climate Programme funded by BEIS and Defra.

Assessment of empirical algorithms for bathymetry extraction using Sentinel-2 data - Gema Casal; Xavier Monteys; John Hedley; Paul Harris; Conor Cahalane; Tim McCarthy (International Journal of Remote Sensing, 2019)

Recent multivariate changes in the North Atlantic climate system, with a focus on 2005–2016 - Jon Robson; Rowan T. Sutton; Alex Archibald; Fenwick Cooper; Matthew Christensen; Lesley J. Gray; N. Penny Holliday; Claire Macintosh; Malcolm McMillan; Ben Moat; Maria Russo; Rachel Tilling; et al. (International Journal of Climatology, 2018)
Major changes are occurring across the North Atlantic climate system, including in the atmosphere, ocean and cryosphere, and many observed changes are unprecedented in instrumental records. As the changes in the North Atlantic directly affect the climate and air quality of the surrounding continents, it is important to fully understand how and why the changes are taking place, not least to predict how the region will change in the future. To this end, this article characterizes the recent observed changes in the North Atlantic region, especially in the period 2005–2016, across many different aspects of the system including: atmospheric circulation; atmospheric composition; clouds and aerosols; ocean circulation and properties; and the cryosphere. Recent changes include: an increase in the speed of the North Atlantic jet stream in winter; a southward shift in the North Atlantic jet stream in summer, associated with a weakening summer North Atlantic Oscillation; increases in ozone and methane; increases in net absorbed radiation in the mid‐latitude western Atlantic, linked to an increase in the abundance of high level clouds and a reduction in low level clouds; cooling of sea surface temperatures in the North Atlantic subpolar gyre, concomitant with increases in the western subtropical gyre, and a decline in the Atlantic Ocean's overturning circulation; a decline in Atlantic sector Arctic sea ice and rapid melting of the Greenland Ice Sheet. There are many interactions between these changes, but these interactions are poorly understood. This article concludes by highlighting some of the key outstanding questions.

State of the UK climate 2017 - Mike Kendon; Mark McCarthy; Svetlana Jevrejeva; Andrew Matthews; Tim Legg (International Journal of Climatology, 2018)
INTRODUCTION This report provides a summary of the UK weather and climate through the calendar year 2017, alongside the historical context for a number of essential climate variables. This is the fourth in a series of annual “State of the UK climate” publications and an update to the 2016 report (Kendon et al., ). It provides an accessible, authoritative and up‐to‐date assessment of UK climate trends, variations and extremes based on the most up to date observational datasets of climate quality. The majority of this report is based on observations of temperature, precipitation, sunshine and wind speed from the UK land weather station network as managed by the Met Office and a number of key partners and co‐operating volunteers. The observations are carefully managed such that they conform to current best practice observational standards as defined by the World Meteorological Organization (WMO). The observations also pass through a range of quality assurance procedures at the Met Office before application for climate monitoring. In addition, time series of near‐coast sea‐surface temperature and sea‐level rise are also presented. The report presents summary statistics for year 2017 and the most recent decade (2008–2017) against 1961–1990 and 1981–2010 averages. 2008–2017 is a non‐standard reference period, but it provides a 10‐year “snapshot” of the most recent experience of the UK’s climate and how that compares to historical records. This means differences between 2008–2017 and the baseline reference averages may reflect shorter‐term decadal variations as well as long‐term trends. These data are presented to show what has happened in recent years, not necessarily what is expected to happen in a changing climate. The majority of maps in this report show year 2017 against the 1981–2010 baseline reference averaging period—i.e., they are anomaly maps which show the spatial variation in this difference from average. Maps of actual values are not displayed because these are dominated by the underlying climatology, which for this report is of a lesser interest than the year‐to‐year variability. Throughout the report’s text the terms “above normal” and “above average” etc. refer to the 1981–2010 baseline reference averaging period unless otherwise stated. Values quoted in tables throughout this report are rounded, but where the difference between two such values is quoted in the text (for example comparing the most recent decade with 1981–2010), this difference is calculated from the original unrounded values.

Acute liver effects, disposition and metabolic fate of [14C]-fenclozic acid following oral administration to normal and bile-cannulated male C57BL/6J mice - Kathryn Pickup; Scott Martin; Elizabeth A. Partridge; Huw B. Jones; Jonathan Wills; Tim Schulz-Utermoehl; Alan McCarthy; Alison Rodrigues; Chris Page; Kerry Ratcliffe; Sunil Sarda; Ian D. Wilson (Archives of Toxicology, 2017)

Cell size trade‐offs govern light exploitation strategies in marine phytoplankton - Tim Key; Avery McCarthy; Douglas A. Campbell; Christophe Six; Suzanne Roy; Zoe V. Finkel (Environmental Microbiology, 2010)
Summary Marine phytoplankton show complex community structures and biogeographic distributions, the net results of physiological and ecological trade‐offs of species responses to fluctuating, heterogeneous environments. We analysed photosynthesis, responses to variable light and macromolecular allocations across a size panel of marine centric diatoms. The diatoms have strong capacities to withstand and exploit fluctuating light, when compared with picophytoplankton. Within marine diatoms, small species show larger effective cross‐sections for photochemistry, and fast metabolic repair of photosystem II after photoinactivation. In contrast, large diatoms show lower susceptibility to photoinactivation, and therefore incur lower costs to endure short‐term exposures to high light, especially under conditions that limit metabolic rates. This size scaling of key photophysiological parameters thus helps explain the relative competitive advantages of larger versus smaller species under different environmental regimes, with implications for the function of the biogenic carbon pump. These results provide a mechanistic framework to explain and predict shifts in marine phytoplankton community size structure with changes in surface irradiance and mixed layer depth.

HD‐GYP domain proteins regulate biofilm formation and virulence in Pseudomonas aeruginosa - Robert P. Ryan; Jean Lucey; Karen O'Donovan; Yvonne McCarthy; Liang Yang; Tim Tolker‐Nielsen; J. Maxwell Dow (Environmental Microbiology, 2009)
Summary HD‐GYP is a protein domain involved in the hydrolysis of the bacterial second messenger cyclic‐di‐GMP. The genome of the human pathogen Pseudomonas aeruginosa PAO1 encodes two proteins (PA4108, PA4781) with an HD‐GYP domain and a third protein, PA2572, which contains a domain with variant key residues (YN‐GYP). Here we have investigated the role of these proteins in biofilm formation, virulence factor synthesis and virulence of P. aeruginosa . Mutation of PA4108 and PA4781 led to an increase in the level of cyclic‐di‐GMP in P. aeruginosa , consistent with the predicted activity of the encoded proteins as cyclic‐di‐GMP phosphodiesterases. Mutation of both genes led to reduced swarming motility but had differing effects on production of the virulence factors pyocyanin, pyoverdin and ExoS. Mutation of PA2572 had no effect on cyclic‐di‐GMP levels and did not influence swarming motility. However, PA2572 had a negative influence on swarming that was cryptic and was revealed only after removal of an uncharacterized C‐terminal domain. Mutation of PA4108 , PA4781 and PA2572 had distinct effects on biofilm formation and architecture of P. aeruginosa. All three proteins contributed to virulence of P. aeruginosa to larvae of the Greater Wax moth Galleria mellonella.