National Meteorological Service Research Articles

The association between weather warnings and hip fractures in the Republic of Ireland

SummaryThis study examined the relationship between hip fractures and weather warnings with the hypothesis higher rates of fractures occur during warnings. National hip fracture database and weather warning records were utilised. Higher rates of hip fractures were found with severe warnings. This has implications for planning in future severe warnings.BackgroundHip fractures represent a significant burden on the Irish Health system with 3666 in 2020. The Irish National Meteorological Service operates a colour coded warning system. Yellow being least severe, while orange represents weather with capacity to impact individuals in affected areas and red represents advice to protect themselves and property. Previous studies investigated the seasonality of hip fractures, which remains but none have investigated the relationship between weather warnings and rates of hip fractures. The hypothesis was that increasing weather warnings would be associated with increased hip fractures. The aim was to investigate the relationship between weather warnings and hip fractures in the Republic of Ireland.MethodsComparison of national weather warning archives from 2013 to 2019 to Fracture Database records. Reviews assessed whether fractures occurred on days a weather warning was in place in the individual’s local county. A statistical analysis of warning features and their relationship to hip fractures was then performed. Fractures and weather warnings were stratified by county with both a panel and case crossover analysis performed.ResultsThere was a tendency towards increased incidence of hip fractures with weather warnings in adjusted analysis (IRR 1.02; 95%CI 0.99–1.06; p-value 0.123). Orange warnings were associated with a statistically higher incidence of fractures (IRR 1.06; 1.01–1.12; p-value 0.026). In both panel and case crossover analysis, both orange and yellow warnings were associated with fractures. Red warnings were associated with a lower incidence of fracture on day of warning (adjusted incidence rate ratio 0.92; 0.70–1.22; p-value 0.569) but a higher incidence on the following day (adjusted incidence rate ratio 1.14; 0.88–1.46; p-value 0.313).ConclusionAn increased incidence of hip fractures appears to occur during weather warnings. Consideration should be given when preparing for periods of extreme weather, ensuring sufficiently resources.

Spatiotemporal investigation of wet–cold compound events in Greece

Abstract. Climate change is set to affect extreme climate and meteorological events. The combination of interacting physical processes (climate drivers) across various spatial and temporal scales resulting to an extreme event is referred to as compound event. The complex geography and topography of Greece forms a variety of regions with different local climate conditions affecting the daily minimum temperature and precipitation distributions and subsequently the distribution of compound events of low temperature and high precipitation values. The aim of our study in this work is to identify these wet–cold events based on observational data from the Hellenic National Meteorological Service (HNMS) stations, which are divided into five different geographical categories, in the period 1980–2004 and coldest months of the year (November-April) on monthly basis. Two available reanalysis products, that of ERA-Interim downscaled with the Weather Research and Forecasting (WRF) model at 5km horizontal resolution (WRF_5), and the coarser resolution (∼30 km) ERA5 Reanalysis dataset from European Centre for Medium-Range Weather Forecasts (ECMWF), are adopted to derive a gridded monthly spatial distribution of wet–cold compound events, after performing a comparison with the observations. The results yield that the monthly maximum HNMS probabilities range from 0.07 % in April to 0.85 % in February, ERA5 range from 0.4 % in April to 2.97 % in February and WRF_5 from 10.4 % in November to 25.04 % in February. The results also displayed that February, January and December, are in this order, the months with the highest WCCEs.

Weathering the storm: Developing a user-centric weather forecast and warning system for Ireland

This paper appraises current usage and future weather service needs in Ireland. The data for this study were collected using a household preparedness questionnaire and focus groups with urban communities, rural dwellers, and marine users, farmers, students, and an island community. The questionnaire was used to collect data on weather warnings and preparedness following a category red severe weather warning. Data on participants’ need for weather forecasts and warnings, current and future weather service requirements, and the effectiveness of the National Meteorological and Hydrological Service (NMHS) were collected from the focus groups.Our analysis identifies the importance of accurate weather forecasts to the public and groups such as farmers as they plan their professional and private lives. Participants were aware of the weather warning system's color-coded structure, with the highest-level warnings considered most effective in capturing attention. Most participants spoke negatively about category yellow warnings, as they perceived them to be issued too frequently. Experience of warnings being issued and threats failing to materialize caused a minority of participants to ignore warnings and not take preparedness action. The professionalism of the NMHS was praised by focus group participants, and there was a high level of overall satisfaction with the quality of the national weather warning system (75.1% of survey participants were mostly or extremely satisfied).Opportunities to improve weather services included enhanced communication with service users, improved web and app interfaces, a move to probabilistic forecasting, and weather warnings that encompass calls to action.

Comparison between the Operational and Statistical Daily Maximum and Minimum Temperature Forecasts on the Central Coast of Peru

Abstract Multiple linear regression models were developed for 1–3-day lead forecasts of maximum and minimum temperature for two locations in the city of Lima, on the central coast of Peru (12°S), and contrasted with the operational forecasts issued by the National Meteorological and Hydrological Service—SENAMHI and the output of a regional numerical atmospheric model. We developed empirical models, fitted to data from the 2000–13 period, and verified their skill for the 2014–19 period. Since El Niño produces a strong low-frequency signal, the models focus on the high-frequency weather and subseasonal variability (60-day cutoff). The empirical models outperformed the operational forecasts and the numerical model. For instance, the high-frequency annual correlation coefficient and root-mean-square error (RMSE) for the 1-day lead forecasts were 0.37°–0.53° and 0.74°–1.76°C for the empirical model, respectively, but from around −0.05° to 0.24° and 0.88°–4.21°C in the operational case. Only three predictors were considered for the models, including persistence and large-scale atmospheric indices. Contrary to our belief, the model skill was lowest for the austral winter (June–August), when the extratropical influence is largest, suggesting an enhanced role of local effects. Including local specific humidity as a predictor for minimum temperature at the inland location substantially increased the skill and reduced its seasonality. There were cases in which both the operational and empirical forecast had similar strong errors and we suggest mesoscale circulations, such as the low-level cyclonic vortex over the ocean, as the culprit. Incorporating such information could be valuable for improving the forecasts. Significance Statement We wanted to compare the temperature of the operational forecast of the Meteorological and Hydrological Service, an atmospheric model, and persistence with the observed temperatures on the Peruvian central coast. In addition, we generated an empirical forecast model considering both atmospheric and local predictors. We got better results with this empirical model, considering the highest Pearson correlations and the lowest RMSE values. These results will allow us to use this empirical model as the main tool to automate the forecast on the central coast of Peru. Future work should be aimed at testing the skill of this model for forecasting in other cities of Peru.

EURADCLIM: the European climatological high-resolution gauge-adjusted radar precipitation dataset

Abstract. The European climatological high-resolution gauge-adjusted radar precipitation dataset, EURADCLIM, addresses the need for an accurate (sub)daily precipitation product covering 78 % of Europe at a high spatial resolution. A climatological dataset of 1 and 24 h precipitation accumulations on a 2 km grid is derived for the period 2013 through 2020. The starting point is the European Meteorological Network (EUMETNET) Operational Program on the Exchange of Weather Radar Information (OPERA) gridded radar dataset of 15 min instantaneous surface rain rates, which is based on data from, on average, 138 ground-based weather radars. First, methods are applied to further remove non-meteorological echoes from these composites by applying two statistical methods and a satellite-based cloud-type mask. Second, the radar composites are merged with the European Climate Assessment & Dataset (ECA&D) with potentially ∼ 7700 rain gauges from National Meteorological and Hydrological Services (NMHSs) in order to substantially improve its quality. Characteristics of the radar, rain gauge and satellite datasets are presented, as well as a detailed account of the applied algorithms. The clutter-removal algorithms are effective while removing few precipitation echoes. The usefulness of EURADCLIM for quantitative precipitation estimation (QPE) is confirmed by comparison against rain gauge accumulations employing scatter density plots, statistical metrics and a spatial verification. These show a strong improvement with respect to the original OPERA product. The potential of EURADCLIM to derive pan-European precipitation climatologies and to evaluate extreme precipitation events is shown. Specific attention is given to the remaining artifacts in and limitations of EURADCLIM. Finally, it is recommended to further improve EURADCLIM by applying algorithms to 3D instead of 2D radar data and by obtaining more rain gauge data for the radar–gauge merging. The EURADCLIM 1 and 24 h precipitation datasets are publicly available at https://doi.org/10.21944/7ypj-wn68 (Overeem et al., 2022a) and https://doi.org/10.21944/1a54-gg96 (Overeem et al., 2022b).

Analysis of rainfall and temperature variability for agricultural water management in the upper Genale river basin, Ethiopia

A better understanding of climate-induced changes and support for adaptation strategies requires knowledged of the spatiotemporal dynamics of climatic variables. This study aims to assess long-term changes in annual and seasonal rainfall and temperature for agricultural water management in the upper Genale river basin, Ethiopia. To achieve this objective, long-term climate data from 13 stations between 1975 and 2018, as well as maximum and minimum temperatures for six stations were collected from the Ethiopian National Meteorological Service Agency (NMA). The characteristics of rainfall (onset, cessation, length of growing season, and crop water requirement) were assessed using the Coefficient of Variation (CV), Standard Rainfall Anomaly (SRA), and Precipitation Concentration Index (PCI). Additionally, the Mann–Kendall test and Sen's slope estimator were used to assess the trend and magnitude of changes in rainfall and temperature. The annual, winter, spring, summer and autumn CVs were 20%, 89%, 30%, 45%, and 32%, respectively. The standardized anomalies of annual and seasonal rainfall for the climate stations indicated that the basin had a drier season than a wet season. The mean length of the growing season in Belg and Kiremt ranged from 43 to 79 days and 38 to 170 days, respectively. On an annual, summer, and autumn season basis, most rainfall stations showed a non-significant trend. In contrast, in the spring season, rainfall showed a decreasing but statistically insignificant trend in all stations except Bensadaye, Bore, Telamokentise, and Yirba Muda stations. According to the analysis of the crop water requirements in the studied basin, supplemental irrigation is essential to reducing yield reduction and crop failure during spring and autumn. In these seasons, maize and sorghum varieties required supplementary irrigation up to 202 mm and 252 mm, respectively. Annual and seasonal maximum and minimum temperatures showed an increasing trend at all the stations except Hagre Selam station. Generally, there was a spatially and temporally variable trend in rainfall while the temperature trend was increasing irrespective of the temporal and spatial factors. Thus, this study contributes to a better understanding of climate change in the basin and these findings can be used in planning for adaptation measures against a changing climate.

Effectiveness of agrometeorological services for smallholder farmers: The case study in the regions of Dosso and Tillabéri in Niger

The increasing frequency of extreme events in West Africa, such as droughts and floods, has made populations that base their subsistence mostly on rainfed agriculture even more vulnerable to climate threats. Climate Services (CS) are largely acknowledged as effective tools for tackling climate risks in agriculture, particularly in semi-arid developing countries but evidences of their effectiveness are still jeopardized. In Niger a climate service (CS) has been set up in the regions of Dosso and Tillabéri by the National Meteorological Service (NMS) to provide salient information for smallholder farmers. The CS was built on a robust collaboration among NMS, local extension services and authorities and farmers in 8 municipalities. The case study shows that a large share of farmers receives throughout the cropping season climatic information and advice via roving seminars and various media, including instant messaging services and radio broadcasts. Nevertheless, the results indicate that access to CS alone doesn’t imply relevant positive impacts on crop yields while the training of farmers in the use of the information results to be a significant factor. Indeed, in 2020, yields of trained farmers are significantly higher by around 17% compared to those of non-trained ones. Training and iterative interaction between farmers and NMS could also have indirect effects on information uptake, contributing to building reciprocal trust and therefore stronger action by trained farmers. The study confirms the importance of the social learning process in CS co-development. Since the study is limited by the small sample and the dataset covering only one cropping season, further research is needed to deepen cost-benefit analysis and disentangle the relative contribution of the CS components to yield increase. Indeed, evidences of the positive impact of CS could represent a leverage for local governments and international funders to support CS co-development and related capacity building activities. Practical implicationClimate variability and a strong increase in extreme hydro meteorological events are affecting agriculture production and exacerbating food insecurity in West Africa. In Niger, the vulnerability of agricultural production systems is coupled to ecosystem fragility and soil degradation. In this area, the rural population is the most vulnerable to climate threats because they have a reduced capability to implement effective risk reduction and climate change adaptation strategies and national government has limited resources to invest in climate policies. The CS implemented for the regions of Dosso and Tillabéri in Niger demonstrates that it is possible to set up an effective network for disseminating agrometeorological information for smallholder farmers at the municipal level with the aim of reducing the impact of climate threats on agriculture production. The information produced by the National Meteorological Service (NMS) is spread through extension services and rural radios to reach farmers. At the same time the agrometeorological field data are collected by local farmers and sent to the national service, ensuring the continuous monitoring of the cropping season. Subsequently, the agrometeorological information is coupled with setting up roving seminars in each municipality to spread tailored advice for farmers concerning seasonal climate forecasts and to build capacities in the use of agrometeorological advices during the season. During these seminars, rain gauges are also distributed to farmers and their use explained. In this way, farmers become able to autonomously take some tactical decisions, such as better timing the sowing of crops or performing farming activities, basing these choices on direct observations. The present case study demonstrates that the mere receipt of the climate information is not clearly related to an increase in yields; contrariwise, farmers who received training on how to properly use the information, have significantly higher yields. Repeated capacity building and information distribution over the years represent an element of trust building for end users who are more prone to use these CS in their agricultural choices, integrating their traditional knowledge. The next challenge is to guarantee the sustainability of these networks over time, because, even if technology advances could reduce the costs of the production and distribution of climate services, the training activities and maintaining the rural observation network are challenging. A possible way to make it sustainable is to reinforce institutional collaboration. Moreover, the use of a participatory approach in co-designing the CS could be a key element in pursuing the active involvement of the local population and administrations and could increase their motivation in the data exchange process. Basing on obtained results, the authors recommend to pursue the development of tailored CS for smallholder farmers in similar rural contexts, since these services constitute a real contribution to climate change adaptation at the local level in rural areas and future experiences could ensure the fine tuning of the climate information products, reducing delivery costs and increasing benefits for stakeholders. Finally, it is also recommended to further assess the cost/benefit ratio of CS in order to leverage funds and ensure scaling up and sustainability.

Presentations to eye emergency departments with flashes and floaters differ dependent on incident solar radiation.

The aim of this retrospective review was to analyse the frequency of patients presenting with flashes and/or floaters (F/F) on bright versus dark days to the eye emergency department of a tertiary referral hospital (the Mater Misericordiae University Hospital) over a 3-year period. The diagnostic and clinical outcomes of F/F presentations were also analysed. This retrospective study assessed eye casualty attendances between January 2018 and December 2020. Solar irradiation (j/cm2) at ground level was retrieved from the records of Met Eireann (Irish National Meteorological Service) via their open access records. A review of electronic patient medical records using the in-house database patient centre was carried out of all patients who attended EED of during the study timeline on the 5 'brightest' and 5 'darkest' days of each year. Seven hundred forty patient presentations were analysed in total. Overall, 16% (n = 119) of all patients that attended EED during the timeframe of the study presented with F/F. One hundred six patients (89%) presented with floaters, 40 patients (34%) presented with flashing lights/photopsia, and 35 patients (29%) presented with both F/F. More patients presented to EED with F/F on bright days when compared with dark days (74 vs 45, p < 0.05). Eighty-nine percent of all patients with F/F presented with monocular floaters. There were more floater presentations during bright when compared with dark days (70 vs 36, p < 0.05). More patients were diagnosed with PVD on bright days when compared with those diagnosed with PVD on dark days (43vs 15, p < 0.05). More RDs were diagnosed on dark days compared with bright days (7 vs 3, p < 0.05). This study established that F/F presentations were more likely to present during bright days when compared with dark days. The diagnosis of PVD was more common during bright days, and RDs were diagnosed significantly more frequently on dark days. Although incident solar radiation was correlated with greater floaters/PVD presentation, causation is unlikely, and the duration of PVD may have been longer in patients presenting on bright days (i.e. pseudo-sudden symptoms).

Reassessing long-standing meteorological records: an example using the national hottest day in Ireland

Abstract. This analysis highlights the potential value in reanalysing early national meteorological records from around the world. These were oftentimes measured via techniques that preceded standardisation of instrumentation and methods of observation and thus could be subject to considerable biases and uncertainties. This analysis uses the techniques pioneered by WMO record assessment teams. The highest currently recognised air temperature (33.3 ∘C) ever recorded in the Republic of Ireland was logged at Kilkenny Castle in 1887. The original observational record however no longer exists. Given that Ireland is now the only country in Europe to have a national heat record that was set in the 19th century, a reassessment of the verity of this record is both timely and valuable. The present analysis undertakes a fundamental reassessment of the plausibility of the 1887 temperature record using methods similar to those used to assess various weather extremes under WMO auspices over recent years. Specifically, we undertake an inter-station reassessment using sparse available records and make recourse to the new and improved 20CRv3 sparse-input reanalysis product. Neither surrounding available stations nor the reanalysis offer substantive support for the Kilkenny record of 33.3 ∘C being correct. Moreover, recent data rescue efforts have uncovered several earlier extreme values, one of which exceeds the Kilkenny value (33.5 ∘C on 16 July 1876 recorded at the Phoenix Park). However, the sparsity of early observational networks, a distinct lack of synoptic support from 20CRv3 for many of the extreme heat values, and the fact that these measurements were obtained using non-standard exposures lead us to conclude that there is grossly insufficient evidence to support any of these 19th century extremes as robust national heat record candidates. Data from the early 20th century onwards benefit from a denser network of stations undertaking measurements in a more standardised manner, many under the direct auspices of Met Éireann and its predecessors, adhering to WMO guidance and protocols. This enables more robust cross-checking of records. We argue that the Met Éireann-recognised 20th century heat record from Boora in 1976 is verified as the most plausible robust national temperature record based upon the synoptic situation and comparisons with nearby neighbouring stations. This measurement of 32.5 ∘C thus likely constitutes the highest reliably recorded temperature measurement in the Republic of Ireland. Ultimately, the formal decision on any reassessment and reassignment of the national record rests with the national meteorological service, Met Éireann.

Considerations regarding the evolution of extreme temperatures in the Banat Plain in the last six decades

During cold winter nights we often hear the question "where is the global warming, should it not be warmer?". Low temperatures that can still be recorded in the Banat Plain during winter or media reports of cold waves affecting various regions worldwide seem to the common man to be in total contradiction with the concerns of the scientific community about global warming. With this article we are trying to follow the evolution of some meteorological parameters that can affect the population in one way or another, namely number of tropical days, number of winter days, number of tropical nights, number of frosty nights, absolute maximum and minimum temperatures. Thus, the data obtained from the three national meteorological services (Romanian, Hungarian, and Serbian) operating on the territory of the Banat Plain were grouped in a common database and analyzed both in Excel and with the help of the non-parametric Mann-Kendall test, obtaining a series of conclusions on the evolution of the abovementioned parameters, as well as on the way how the increase in the risk of high temperatures is compensated (or not) by the decrease in the risk of low temperatures.

Temporal progress of coffee leaf rust and environmental conditions affecting severity in Veracruz State, Mexico

Coffee is an important crop in Mexico. Unfortunately, coffee production has been affected by coffee leaf rust (CLR). The severity of this infection occurs with variations along the year described before in different coffee-producing regions worldwide. For Veracruz, there are available reports of weekly CLR severity, but this information is only descriptive. We analyzed variations along the year of CLR severity in Veracruz with data from municipal weekly reports provided by Mexico’s federal government phytosanitary epidemiological monitoring coffee program. We selected reports dated in 2018 from nine municipalities and after calculations of mean monthly severity values, we conducted a one-way ANOVA (months as factors) of severity data. We compared this information with other coffee-producing regions. Additionally, we explored the association of temperature, rainfall, and altitude with CLR severity using Principal Component Analysis and multiple linear regressions. Temperature and rainfall data were obtained from Mexican National Meteorological Service. We found that CLR severity in January, October, November, and December (months of harvest period) was significantly higher than values from March-June. During the harvest period, coffee plants allocate resources mainly for fruiting which competes in resources for other tasks such as defense and leaf growth, so this competition of resources can explain the positive relationship found between fruit load and CLR severity. This monthly variation of severity was similar to those reported in Chiapas, Guatemala, Colombia, Uganda, and Ethiopia. Our model (R2 = 0.401) showed a significant and negative effect of altitude and medium temperature on CLR severity, while the effect of rainfall was positive. With our study, we suggest applications of fungicides in March-June when coffee plantations are in leaf phenophase. Key words: Altitude; Coffea arabica; Hemileia vastatrix; phenophase.

Heritage management and sustainability of heritage sites. The case of ancient Greek theatre of Dodoni, Epirus, Greece

Heritage is composed of tangible and intangible assets, as well as cultural and natural sites threatened by the effects of climate change. The sustainability of heritage is significant for its transmission to the next generations, future progress, cultural development and diversity. Thus, this paper is focused on the protection and management of heritage, presenting as case study the ancient Greek Theatre of Dodoni, located in Epirus. Stakeholders are related to scientists for climate change, heritage managers, society (including educational organizations), local community as well as the visitors. The interaction of these groups offers a management plan focused on the needs of the place. Moreover, the research of the local identity of the landscape should be combined with climatic data showing the course of the climate change and its effects on the site of study. This information of climate indices is retrieved by meteorological stations in North-Western Greece. In particular, we analyze climatological data of temperature, humidity and precipitation, collected by the meteorological station of Ioannina (Hellenic National Meteorological Service) for the period 1956-2022. Therefore, the assessment of measurements and extremities can be combined with the vulnerability approach and the risk assessment for the structure of heritage management and the dissemination.

New temperature indices for the estimation of temperature variability. Application in Athens’s greater area.

This current work attempts to explore the temperature’s variability through the selection of indicators that refer to the increases and decreases of three typical values of daily temperature (mean, maximum, minimum). The primary meteorological data that has been used come from the station of the Hellenic National Meteorological Service in Tatoi, the period 1955 to 2001. In total, nine indicators were developed; the time series of the number of days recorded with decrease, increase or stability of the day-by-day temperature’s characteristic value were examined annually and seasonally. The results of time series analysis led to the conclusion that, as time passes, there are changes in the decrease, increase and stability of the mean, minimum and maximum day-by-day temperature variability.

Use of new indices for the quantification of climate change based on air temperature variability

The current study attempted to investigate the temperature’s variability through the selection of indicators that refer mostly to the increases and decreases of three typical values of daily temperature (mean, maximum, minimum). The primary meteorological data that has been used come from the station of the Hellenic National Meteorological Service in Tatoi, the time period 1955-2001. The time series of the maximum and the mean number of days with a continuous increase or decrease in the daily temperature was investigated seasonally and annually. In addition, the number of switches (increases/decreases) on annual and seasonal scales was analyzed. The results of the time series analysis led to the indication that as time passes temperature’s variability grows with more switches (ups and downs), while its variations become a bit milder.

Investigation of the extreme wet–cold compound events changes between 2025–2049 and 1980–2004 using regional simulations in Greece

Abstract. This paper aims to study wet–cold compound events (WCCEs) in Greece for the wet and cold season November–April since these events may affect directly human activities for short or longer periods, as no similar research has been conducted for the country studying the past and future development of these compound events. WCCEs are divided into two different daily compound events, maximum temperature– (TX) accumulated precipitation (RR) and minimum temperature– (TN) accumulated precipitation (RR), using fixed thresholds (RR over 20 mm d−1 and temperature under 0 ∘C). Observational data from the Hellenic National Meteorology Service (HNMS) and simulation data from reanalysis and EURO-CORDEX models were used in the study for the historical period 1980–2004. The ensemble mean of the simulation datasets from projection models was employed for the near future period (2025–2049) to study the impact of climate change on the occurrence of WCCEs under the Representative Concentration Pathways (RCPs) 4.5 and 8.5 scenarios. Following data processing and validation of the models, the potential changes in the distribution of WCCEs in the future were investigated based on the projected and historical simulations. WCCEs determined by fixed thresholds were mostly found over high altitudes with TN–RR events exhibiting a future tendency to reduce particularly under the RCP 8.5 scenario and TX–RR exhibiting similar reduction of probabilities for both scenarios.

Smallholder farmers' perception of climate change and choice of adaptation strategies in East Hararghe Zone, Eastern Ethiopia

PurposeChange of climate is attributed to human activity that alters the composition of the global atmosphere observed over comparable periods. The purpose of this paper is to explore smallholder farmers' perceptions of climate change and compare it with meteorological data, as well as to identify perceived adaptation barriers and examine the factors that influence the choice of adaptation options in eastern Ethiopia.Design/methodology/approachIn total, 384 sample households were chosen from four districts of the zone. A cross-sectional survey was used to conduct the study. Primary data was acquired through key informant interviews, focus group discussions and semistructured interviews, whereas meteorological data was collected from the National Meteorological Service Agency of Ethiopia. A Mann–Kendall statistical test was used to analyze temperature and rainfall trends over 33 years. A multivariate probit (MVP) model was used to identify the determinants of farmers' choice of climate change adaptation strategies.FindingsThe result indicated that temperature was significantly increased, whereas rainfall was significantly reduced over the time span of 33 years. This change in climate over time was consistently perceived by farmers. Smallholder farmers use improved varieties of crops, crop diversification, adjusting planting dates, soil and water conservation practices, reducing livestock holdings, planting trees and small-scale irrigation adaptation strategies. Moreover, this study indicated that sex of the household head, landholding size, livestock ownership, access to extension, access to credit, social capital, market distance, access to climate change-related training, nonfarm income, agroecological setting and poverty status of the households significantly influence farmers’ choice of adaptation strategies.Research limitations/implicationsFurther research is required to evaluate the economic impact of each adaptation options on the livelihood of smallholder farmers.Practical implicationsInstitutional variables significantly influenced how farmers adapted to climate change, and all of these issues might potentially be addressed by improving institutional service delivery. To improve farm-level adaptation, local authorities are recommended to investigate the institutional service provision system while also taking demographic and agroecological factors in to account.Originality/valueThis study compared farmers' perceptions with temperature and rainfall trend analysis, which has been rarely addressed by other studies. This study adopts an MVP model and indicated the adaptation strategies that complement/substitute strategies each other. Furthermore, this study discovered that the choice of adaptation options differed between poor and nonpoor households, which has been overlooked in previous climate change adaptation research.

Downscaled climate change scenarios for Central America

Abstract. The intersectoral workshop held in December 2016 among the Ibero-American networks on water, climate change and meteorology, identified the need of downscaled climate change scenarios for Central America. Such scenarios would be developed by National Meteorological and Hydrological Services in the region, based on a common methodology, allowing the assessment of climate change impacts on water resources and extreme hydro-meteorological events. This project was supported by the International and Ibero-American Foundation for Administration and Public Policies of Spain in the framework of the EUROCLIMA+ programme. One final outcome of the project has been a freely accessible web viewer, installed on the Centro Clima webpage (https://centroclima.org/escenarios-cambio-climatico/, last access: 26 September 2022), managed by the Regional Committee on Hydraulic Resources of the Central American Integration System, where all information generated during the project is available for consultation and data downloading by the different sectors of users. A key element in this project has been to integrate many downscaled projections based on different methods (dynamical and statistical), totalizing 45 different projections, and aiming at estimating the uncertainty coming from different sources in the best possible way. Another essential element has been the strong involvement of the different user sectors through national workshops, first, at the beginning of the project for the identification and definition of viewer features, and then for the presentation of results and planning of its use by prioritized sectors. In a second phase of the project, a regional working group made up of experts from the participating National Meteorological and Hydrological Services will be in charge of viewer maintenance and upgrade, including new sectoral parameters, developed in collaboration with interested users, and computation and addition of new downscaled projections from CMIP6 in collaboration with the State Meteorological Agency of Spain.

Automatic quality control of telemetric rain gauge data providing quantitative quality information (RainGaugeQC)

Abstract. The RainGaugeQC scheme described in this paper is intended for real-time quality control of telemetric rain gauge data. It consists of several checks: detection of exceedance of the natural limit and climate-based threshold as well as checking of the conformity of rain gauge and radar observations, the consistency of time series from heated and unheated sensors, and the spatial consistency of adjacent gauges. The proposed approach is focused on assessing the reliability of individual rain gauge observations. A quantitative indicator of reliability, called the quality index (QI), describes the quality of each measurement as a number in the range from 0.0 (completely unreliable measurement) to 1.0 (perfect measurement). The QI of a measurement which fails any check is lowered, and only a measurement very likely to be erroneous is replaced with a “no data” value. The performance of this scheme has been evaluated by analysing the spatial distribution of the precipitation field and comparing it with precipitation observations and estimates provided by other techniques. The effectiveness of the RainGaugeQC scheme was also analysed in terms of the statistics of QI reduction. The quality information provided is very useful in further applications of rain gauge data. The scheme is used operationally by the Polish national meteorological and hydrological service (Institute of Meteorology and Water Management – National Research Institute).

Impact-based forecasting for improving the capacity of typhoon-related disaster risk reduction in typhoon committee region

The two most common types of disasters caused by natural hazards in the Asia-Pacific region are floods and storms, many of them associated with typhoon (tropical cyclone) related impacts. To improve the capacity of typhoon-related disaster risk reduction so as to maximum reduce the losses of people’s life and properties, the decision makers and the public are imminently demanding the information of the targeted impact caused by typhoon. As the front line in hydro-meteorological disaster prevention and mitigation against the typhoon-related disasters, National Meteorological and Hydrological Services (NMHSs) in TC Members have recognized that forecasting impact became more important than forecasting pure causing-disaster elements. Impact-based forecasting signals an evolution from “what the weather will be” to “what the weather will do”. Many things change as impact based forecasts evolve from previous weather forecasts. To enhance impact-based typhoon forecasting, the Typhoon Committee added it into the new updated Strategic Plan 2022–2026. This paper briefed generally the concept of impact based forecasting, introduced the implementation and progresses on typhoon impact based forecasting in TC Members in recent years, and initially discussed the measures and direction for enhancement of impact-based typhoon forecasting and early warning services in future.

ADT: The automatic weather station data tool

Climate data are essential in an array of climate research and applications. Climate data also provide the foundation for the provision of climate services. However, in many parts of Africa, weather stations are sparse, and their numbers have been declining over the last half-century. Moreover, the distribution of existing meteorological stations is uneven, with most weather stations located in towns and cities along the main roads. To address these data gaps, efforts over the last decade, largely driven by external donor funding, have focused on expanding meteorological observation networks in many parts of Africa, mainly through the provision of Automatic Weather Stations (AWS) to National Meteorological Services (NMS). While AWS offer a number of advantages over the conventional ones, which include automated reporting at a very fine temporal resolution (15 min, on average), they also have several disadvantages and accompanying challenges to their use. Some of these well-known challenges are the high maintenance requirements and associated costs that arise from the need to procure replacement parts that may not be available locally. However, another major, under-discussed challenge confronting NMS is the disparities between the different station types provided by different donors that has given rise to barriers to pragmatically using the plethora of data collected by AWS in decision-making processes. These disparities include major differences in the way the data from various AWS types are formatted and stored, which result in poorly coordinated, fragmented, and unharmonized datasets coming from different AWS networks. The end result is that while top-of-the-line AWS networks may systematically be collecting highly needed data, the inability of NMS to efficiently, combine, synchronize, and otherwise integrate these data coherently in their databases limits their use. To address these challenges, a free web-based application called Automatic Weather Station Data Tool (ADT) with an easy-to-use graphical user interface was developed to help NMS to access, process, perform quality control, and visualize data from different AWS networks in one place. Now implemented in five African countries (Ethiopia, Ghana, Kenya, Rwanda, and Zambia), ADT also enables real-time monitoring of stations to see which ones are working and which ones are offline. This tool emerged from a wider climate services approach, the Enhancing National Climate Services (ENACTS), recognizing that availability of high-quality climate data does not automatically translate to ease of access or effective use.