Met Éireann

Abstract We present a dataset of daily resolution climatic time series that has been compiled for the European Climate Assessment (ECA). As of December 2001, this ECA dataset comprises 199 series of minimum, maximum and/or daily mean temperature and 195 series of daily precipitation amount observed at meteorological stations in Europe and the Middle East. Almost all series cover the standard normal period 1961–90, and about 50% extends back to at least 1925. Part of the dataset (90%) is made available for climate research on CDROM and through the Internet (at http://www.knmi.nl/samenw/eca ). A comparison of the ECA dataset with existing gridded datasets, having monthly resolution, shows that correlation coefficients between ECA stations and nearest land grid boxes between 1946 and 1999 are higher than 0.8 for 93% of the temperature series and for 51% of the precipitation series. The overall trends in the ECA dataset are of comparable magnitude to those in the gridded datasets. The potential of the ECA dataset for climate studies is demonstrated in two examples. In the first example, it is shown that the winter (October–March) warming in Europe in the 1976–99 period is accompanied by a positive trend in the number of warm‐spell days at most stations, but not by a negative trend in the number of cold‐spell days. Instead, the number of cold‐spell days increases over Europe. In the second example, it is shown for winter precipitation between 1946 and 1999 that positive trends in the mean amount per wet day prevail in areas that are getting drier and wetter. Because of its daily resolution, the ECA dataset enables a variety of empirical climate studies, including detailed analyses of changes in the occurrence of extremes in relation to changes in mean temperature and total precipitation. Copyright © 2002 Royal Meteorological Society.

T he ChAllenge. Climate and weather forecasting applications share a common ancestry and build on the same physical principles. Nevertheless, climate research and numerical weather prediction (NWP) are commonly seen as different disciplines. The emerging concept of "seamless prediction" forges weather forecasting and climate change studies into a single framework. At the same

Abstract The aim of this article is to describe the reference configuration of the convection-permitting numerical weather prediction (NWP) model HARMONIE-AROME, which is used for operational short-range weather forecasts in Denmark, Estonia, Finland, Iceland, Ireland, Lithuania, the Netherlands, Norway, Spain, and Sweden. It is developed, maintained, and validated as part of the shared ALADIN–HIRLAM system by a collaboration of 26 countries in Europe and northern Africa on short-range mesoscale NWP. HARMONIE–AROME is based on the model AROME developed within the ALADIN consortium. Along with the joint modeling framework, AROME was implemented and utilized in both northern and southern European conditions by the above listed countries, and this activity has led to extensive updates to the model’s physical parameterizations. In this paper the authors present the differences in model dynamics and physical parameterizations compared with AROME, as well as important configuration choices of the reference, such as lateral boundary conditions, model levels, horizontal resolution, model time step, as well as topography, physiography, and aerosol databases used. Separate documentation will be provided for the atmospheric and surface data-assimilation algorithms and observation types used, as well as a separate description of the ensemble prediction system based on HARMONIE–AROME, which is called HarmonEPS.

Microfibers (mf) are the most common type of microplastic in the environment. Few studies have focused on their abundance in atmospheric deposition in background environments. In the current study, we collected wet-only and bulk rainfall from four precipitation chemistry monitoring stations, primarily located in coastal areas around Ireland. Anthropogenic mf were observed in all samples; the average deposition across the four study sites was 80 mf m–2 day–1. Wet-only mf deposition was 70 mf m–2 day–1 compared with bulk deposition of 100 mf m–2 day–1. The wet-only collectors were estimated to capture ∼70% of the bulk collectors, suggesting that dry deposition makes up at least 30% of total deposition. Meteorological variables, i.e., relative humidity, rainfall volume, wind speed, and wind direction, were significantly related to mf abundance, suggesting that rainfall washout and air mass movement are important predictors of mf deposition in background regions. In total, 15% of all anthropogenic mf were identified as plastic. The most abundant polymer type was polyester or polyethylene terephthalate at 71%, followed by polyacrylonitrile at 11%, polyethylene at 11%, and polypropylene at 4%. The average deposition of plastic mf was 12 mf m–2 day–1.

Throughout spring and summer 2020, ozone stations in the northern extratropics recorded unusually low ozone in the free troposphere. From April to August, and from 1 to 8 kilometers altitude, ozone was on average 7% (≈4 nmol/mol) below the 2000-2020 climatological mean. Such low ozone, over several months, and at so many stations, has not been observed in any previous year since at least 2000. Atmospheric composition analyses from the Copernicus Atmosphere Monitoring Service and simulations from the NASA GMI model indicate that the large 2020 springtime ozone depletion in the Arctic stratosphere contributed less than one-quarter of the observed tropospheric anomaly. The observed anomaly is consistent with recent chemistry-climate model simulations, which assume emissions reductions similar to those caused by the COVID-19 crisis. COVID-19 related emissions reductions appear to be the major cause for the observed reduced free tropospheric ozone in 2020.

Analyzed data for numerical prediction can be effectively initialized by means of a digital filter. Computation time is reduced by using an optimal filter. The construction of optimal filters involves the solution of a nonlinear minimization problem using an iterative procedure. In this paper a simple filter based on the Dolph-Chebyshev window, which has properties similar to those of an optimal filter, is described. It is shown to be optimal for an appropriate choice of parameters. It has an explicit analytical expression and is easily implemented. Its effectiveness is demonstrated by application to Richardson's forecast: the initial pressure tendency is reduced from 145 hPa per 6 h to 0.9 hPa per 6 h. Use of the filter is not restricted to initialization; it may also be applied as a weak constraint in four-dimensional data assimilation.

During Arctic winters with a cold, stable stratospheric circulation, reactions on the surface of polar stratospheric clouds (PSCs) lead to elevated abundances of chlorine monoxide (ClO) that, in the presence of sunlight, destroy ozone. Here we show that PSCs were more widespread during the 1999/2000 Arctic winter than for any other Arctic winter in the past two decades. We have used three fundamentally different approaches to derive the degree of chemical ozone loss from ozonesonde, balloon, aircraft, and satellite instruments. We show that the ozone losses derived from these different instruments and approaches agree very well, resulting in a high level of confidence in the results. Chemical processes led to a 70% reduction of ozone for a region ∼1 km thick of the lower stratosphere, the largest degree of local loss ever reported for the Arctic. The Match analysis of ozonesonde data shows that the accumulated chemical loss of ozone inside the Arctic vortex totaled 117 ± 14 Dobson units (DU) by the end of winter. This loss, combined with dynamical redistribution of air parcels, resulted in a 88 ± 13 DU reduction in total column ozone compared to the amount that would have been present in the absence of any chemical loss. The chemical loss of ozone throughout the winter was nearly balanced by dynamical resupply of ozone to the vortex, resulting in a relatively constant value of total ozone of 340 ± 50 DU between early January and late March. This observation of nearly constant total ozone in the Arctic vortex is in contrast to the increase of total column ozone between January and March that is observed during most years.

OBJECTIVE: Grading of hypertension severity by fundoscopic appearance is difficult and inaccurate. We investigated whether essential hypertension (EHT) and malignant phase hypertension (MHT) were associated with quantifiable abnormalities of the topology and architecture of the retinal circulation. METHODS: The topology and architecture of the retinal microvasculature were compared in images from 20 normotensive subjects, 20 patients with EHT and 20 patients with MHT. Digitized retinal photographs were analysed by a novel multiscale image analysis method using a semi-automated program to quantify geometrical and topological properties of arteriolar and venular trees. RESULTS: EHT was associated with an increase in the arteriolar length-to-diameter ratio (P < 0.01). There were also alterations in arteriolar topology indicative of rarefaction, including a marked reduction in the number of terminal branches in EHT (P < 0.01). These changes in the arteriolar network were exaggerated in MHT and there was also increased venular tortuosity and venular rarefaction in MHT compared with normotensive subjects. CONCLUSIONS: Hypertension is associated with marked topological alterations in the retinal vasculature, and quantification of these changes may be a useful novel approach to the assessment of target organ damage in hypertension.

ABSTRACT Long‐term precipitation series are critical for understanding emerging changes to the hydrological cycle. To this end we construct a homogenized Island of Ireland Precipitation ( IIP ) network comprising 25 stations and a composite series covering the period 1850–2010, providing the second‐longest regional precipitation archive in the British‐Irish Isles. We expand the existing catalogue of long‐term precipitation records for the island by recovering archived data for an additional eight stations. Following bridging and updating of stations HOMogenisation softwarE in R ( HOMER ) homogenization software is used to detect breaks using pairwise and joint detection. A total of 25 breakpoints are detected across 14 stations, and the majority (20) are corroborated by metadata. Assessment of variability and change in homogenized and extended precipitation records reveal positive (winter) and negative (summer) trends. Trends in records covering the typical period of digitization (1941 onwards) are not always representative of longer records. Furthermore, trends in post‐homogenization series change magnitude and even direction at some stations. While cautionary flags are raised for some series, confidence in the derived network is high given attention paid to metadata, coherence of behaviour across the network and consistency of findings with other long‐term climatic series such as England and Wales precipitation. As far as we are aware, this work represents the first application of HOMER to a long‐term precipitation network and bodes well for use in other regions. It is expected that the homogenized IIP network will find wider utility in benchmarking and supporting climate services across the Island of Ireland, a sentinel location in the North Atlantic.

The stability and accuracy of the multiply-upstream, semi-Lagrangian method of integrating the advective equation in two dimensions is examined for four different interpolation schemes; namely, bilinear, biquadratic, bicubic and biquartic. All are shown to be consistent and unconditionally stable for constant advecting velocity. Their respective amplitude and phase errors are discussed. They are then used to integrate the test problem of a cone being advected about the plane at constant angular velocity. The merits of the schemes relative to each other and relative to a well tried Eulerian scheme am examined with particular regard to accuracy and computation time.

Abrupt climate change is abundant in geological records, but climate models rarely have been able to simulate such events in response to realistic forcing. Here we report on a spontaneous abrupt cooling event, lasting for more than a century, with a temperature anomaly similar to that of the Little Ice Age. The event was simulated in the preindustrial control run of a high-resolution climate model, without imposing external perturbations. Initial cooling started with a period of enhanced atmospheric blocking over the eastern subpolar gyre. In response, a southward progression of the sea-ice margin occurred, and the sea-level pressure anomaly was locked to the sea-ice margin through thermal forcing. The cold-core high steered more cold air to the area, reinforcing the sea-ice concentration anomaly east of Greenland. The sea-ice surplus was carried southward by ocean currents around the tip of Greenland. South of 70 °N, sea ice already started melting and the associated freshwater anomaly was carried to the Labrador Sea, shutting off deep convection. There, surface waters were exposed longer to atmospheric cooling and sea surface temperature dropped, causing an even larger thermally forced high above the Labrador Sea. In consequence, east of Greenland, anomalous winds changed from north to south, terminating the event with similar abruptness to its onset. Our results imply that only climate models that possess sufficient resolution to correctly represent atmospheric blocking, in combination with a sensitive sea-ice model, are able to simulate this kind of abrupt climate change.

A stable, semi-Lagrangian, semi-implicit, two-time-level, gridpoint integration scheme for the shallow water equations on the sphere is presented. A rotated spherical coordinate system is used to integrate the equations of motion at each gridpoint poleward of a certain latitude, thus overcoming problems associated with the polar singularity. The results of medium term integrations of large scale test patterns using a long time step are presented.

Abstract Many nations responded to the corona virus disease‐2019 (COVID‐19) pandemic by restricting travel and other activities during 2020, resulting in temporarily reduced emissions of CO 2 , other greenhouse gases and ozone and aerosol precursors. We present the initial results from a coordinated Intercomparison, CovidMIP, of Earth system model simulations which assess the impact on climate of these emissions reductions. 12 models performed multiple initial‐condition ensembles to produce over 300 simulations spanning both initial condition and model structural uncertainty. We find model consensus on reduced aerosol amounts (particularly over southern and eastern Asia) and associated increases in surface shortwave radiation levels. However, any impact on near‐surface temperature or rainfall during 2020–2024 is extremely small and is not detectable in this initial analysis. Regional analyses on a finer scale, and closer attention to extremes (especially linked to changes in atmospheric composition and air quality) are required to test the impact of COVID‐19‐related emission reductions on near‐term climate.

Abstract Observations are the foundation for understanding the climate system. Yet, currently available land meteorological data are highly fractured into various global, regional, and national holdings for different variables and time scales, from a variety of sources, and in a mixture of formats. Added to this, many data are still inaccessible for analysis and usage. To meet modern scientific and societal demands as well as emerging needs such as the provision of climate services, it is essential that we improve the management and curation of available land-based meteorological holdings. We need a comprehensive global set of data holdings, of known provenance, that is truly integrated both across essential climate variables (ECVs) and across time scales to meet the broad range of stakeholder needs. These holdings must be easily discoverable, made available in accessible formats, and backed up by multitiered user support. The present paper provides a high-level overview, based upon broad community input, of the steps that are required to bring about this integration. The significant challenge is to find a sustained means to realize this vision. This requires a long-term international program. The database that results will transform our collective ability to provide societally relevant research, analysis, and predictions in many weather- and climate-related application areas across much of the globe.

The use of sensors fixed to in-service trains has the potential to provide real-time track condition monitoring to inform maintenance planning. An Irish Rail intercity train was instrumented for a period of 1 month so that a numerical method developed to find track longitudinal profile from measured vehicle inertial responses could be experimentally tested. A bogie-mounted accelerometer and gyrometer measured vertical acceleration and angular velocity as the train made regular service operations between Dublin and Belfast on the island of Ireland. Cross entropy optimisation is used to find a track longitudinal profile that generates a numerical inertial response that best fits the measured response. Tolerance limits are used to inject variance where required to ensure a good match between measured and modelled signals. A section of track with known track settlement history is selected as a case study. A level survey was undertaken during the measurement campaign to characterise the longitudinal profile through the test section. Bandpass filters are used to compare inferred profiles and the surveyed profile. Good agreement is found between the two profiles although improvements in accuracy and reproducibility are required before conformance with current standards is achieved.

Abstract A World Meteorological Organization (WMO) committee officially evaluated temperature record extremes of 54.0°C at two locations, one in Mitribah, Kuwait on July 21, 2016 and a second in Turbat, Pakistan on May 28, 2017. The committee agreed that quantity and quality of documentation of both observations were excellent. Additional metrological testing of the equipment focused on three aspects: the calibration of both thermometers, an effort to estimate the factors influencing the measurements and a direct comparison of the two thermometers when exposed simultaneously to 54°C. The metrological analysis's conclusion for the Mitribah value is a temperature estimated to be 53.87°C with an expanded uncertainty of ±0.08°C. Correspondingly, for the Turbat value the temperature is estimated to be 53.72°C with an expanded uncertainty of ±0.40°C. Following that analysis, the committee recommended acceptance of the calibrated observations to the first decimal digit such that the Mitribah observation is accepted as 53.9 ± 0.1°C and the Turbat as 53.7 ± 0.4°C. The Mitribah, Kuwait temperature is now accepted by the WMO as the highest temperature ever recorded for Asia (WMO RA II) and the two observations are the third (tied within uncertainty limits) and fourth highest WMO‐recognized temperature extremes and, significantly, they are the highest, officially recognized temperatures to have been recorded in the last 76 years. This evaluation has involved the most extensive temperature extremes analysis ever to be undertaken by an international evaluation committee of the WMO CCl Archive of Weather and Climate Extremes.

Abstract. This paper presents a first statistical validation of tropospheric ozone products derived from measurements of the IASI satellite instrument. Since the end of 2006, IASI (Infrared Atmospheric Sounding Interferometer) aboard the polar orbiter Metop-A measures infrared spectra of the Earth's atmosphere in nadir geometry. This validation covers the northern mid-latitudes and the period from July 2007 to August 2008. Retrieval results from four different sources are presented: three are from scientific products (LATMOS, LISA, LPMAA) and the fourth one is the pre-operational product distributed by EUMETSAT (version 4.2). The different products are derived from different algorithms with different approaches. The difference and their implications for the retrieved products are discussed. In order to evaluate the quality and the performance of each product, comparisons with the vertical ozone concentration profiles measured by balloon sondes are performed and lead to estimates of the systematic and random errors in the IASI ozone products (profiles and partial columns). A first comparison is performed on the given profiles; a second comparison takes into account the altitude dependent sensitivity of the retrievals. Tropospheric columnar amounts are compared to the sonde for a lower tropospheric column (surface to about 6 km) and a "total" tropospheric column (surface to about 11 km). On average both tropospheric columns have small biases for the scientific products, less than 2 Dobson Units (DU) for the lower troposphere and less than 1 DU for the total troposphere. The comparison of the still pre-operational EUMETSAT columns shows higher mean differences of about 5 DU.

Abstract. A continuous 305-year (1711–2016) monthly rainfall series (IoI_1711) is created for the Island of Ireland. The post 1850 series draws on an existing quality assured rainfall network for Ireland, while pre-1850 values come from instrumental and documentary series compiled, but not published by the UK Met Office. The series is evaluated by comparison with independent long-term observations and reconstructions of precipitation, temperature and circulation indices from across the British–Irish Isles. Strong decadal consistency of IoI_1711 with other long-term observations is evident throughout the annual, boreal spring and autumn series. Annually, the most recent decade (2006–2015) is found to be the wettest in over 300 years. The winter series is probably too dry between the 1740s and 1780s, but strong consistency with other long-term observations strengthens confidence from 1790 onwards. The IoI_1711 series has remarkably wet winters during the 1730s, concurrent with a period of strong westerly airflow, glacial advance throughout Scandinavia and near unprecedented warmth in the Central England Temperature record – all consistent with a strongly positive phase of the North Atlantic Oscillation. Unusually wet summers occurred in the 1750s, consistent with proxy (tree-ring) reconstructions of summer precipitation in the region. Our analysis shows that inter-decadal variability of precipitation is much larger than previously thought, while relationships with key modes of climate variability are time-variant. The IoI_1711 series reveals statistically significant multi-centennial trends in winter (increasing) and summer (decreasing) seasonal precipitation. However, given uncertainties in the early winter record, the former finding should be regarded as tentative. The derived record, one of the longest continuous series in Europe, offers valuable insights for understanding multi-decadal and centennial rainfall variability in Ireland, and provides a firm basis for benchmarking other long-term records and reconstructions of past climate. Correlation of Irish rainfall with other parts of Europe increases the utility of the series for understanding historical climate in further regions.

The IPCC states that climate change unequivocally impacts on various aspects of the natural and built environment, including our vital critical infrastructure systems (transport, energy, water/wastewater and communications). It is thus essential for countries to gain an understanding of critical infrastructure vulnerability to current and future climate-related threats, in order to develop effective climate adaptation strategies. The first requisite step towards implementing these strategies, before any detailed analysis can commence, is high-level vulnerability or risk assessments. The work in this paper is concerned with such high-level assessments, however the framework presented is GIS-based, facilitating modelling of geographical variability in both climate and asset vulnerability within a country. This permits the identification of potential climate change risk hotspots across a range of critical infrastructure sectors. The framework involves a number of distinct steps. Sectoral information matrices are developed to highlight the key relationships between the infrastructure and climate threats. This information is complemented with sectoral maps showing, on an asset-level, the potential geospatial impacts of climate change, facilitating initial quantification of the vulnerable portions of the infrastructure systems. Finally, the approach allows for development of multi-sectoral semi-quantitative risk ranking maps that account for the geographical proximities of various assets from different critical infrastructure sectors which are vulnerable to a specific climate threat. The framework is presented in the paper and applied as a case study in the context of Irish critical infrastructure. The case-study identified for instance, potentially substantial increases in fluvial flooding risk for Irish critical infrastructure, while the multi-sectoral risk ranking maps highlighted a number of Ireland’s urban and rural areas as climate change risk hotspots. These high-level insights are likely to be useful in informing more detailed assessment, and initiating important conversations relating to a region’s critical infrastructure cross-sectoral risk.

A two-time-level, three-dimensional semi-Lagrangian, semi-implicit primitive equation gridpoint model that incorporates a sophisticated physics package is presented. It is shown to give accurate 24-h forecasts when integrated over a limited area using a 1.5°×1.5° Arakawa C grid in the horizontal and 16 levels in the vertical for time steps up to 2 h. Also, it is shown to be as accurate as, and approximately twice as efficient as, a three-time-level semi-Lagrangian scheme for time steps up to 2 h but slightly less accurate for a 3-h time step. Finally, it is shown to give accurate forecasts on a 0.5°×0.5° horizontal grid, again using 16 vertical levels, for time steps up to 40 min.