National Meteorological Service Research Articles

Chemical Characteristics and Identification of PM10 Sources in Two Lima Districts, Peru

This study evaluates the concentration of PM10 and PM2.5 and identification of source in the districts of San Juan de Lurigancho and Puente Piedra (PPD) in Lima-Peru. The samples were collected from April to May 2017 by the National Meteorology and Hydrology Service of Peru (Senamhi). The concentration of PM10 and PM2.5, measured by gravimetric techniques, exceeded the international (WHO) and national standards; with maximum values for PM10 and PM2.5 of 160 and 121.56 µg/ m3 in PPD and 295.06 and 154.58 µg/ m3 in SJL. Identification of sources by the Positive Matrix Factorization Model (PMF 5.0) and Principal Component Analysis (ACP), showed similar sources for both districts. In SJL, the combination of vehicular traffic and resuspension of soil dust, marine aerosol and iron and steel industry was determined, while in PPD the resuspension of soil dust, vehicular source, industrial activity and marine aerosol.

Exploring the Need for Developing Impact-Based Forecasting in West Africa

While conventional weather forecasts focus on meteorological thresholds for extreme events, Impact-Based Forecasts (IBF) integrate information about the potential severity of weather impacts with their likelihood of occurrence. As IBF provides an indication of local risk, there is an increasing uptake of this approach globally. Despite the vulnerability of West Africa to severe weather, and the potential benefits of such a risk-based approach for informing disaster risk reduction, IBF remains rarely used in this region. To meet this need, three national workshops were held in Ghana, Nigeria and Senegal with forecasters, project researchers and users of Climate Information Services (CIS) from key sectors (e.g. agriculture, water resources, disaster risk reduction). In addition, a more localised district level workshop was held in Northern Ghana to explore needs at a subnational scale in Tamale District. The objectives of these workshops were to evaluate the current use of forecast products provided by National Meteorological and Hydrological Services (NMHSs) and to explore the potential for applying IBF. Findings indicate a recognition that the quality of forecast products provided by NMHSs in West Africa has substantially improved in recent years. However, challenges remain related to user understanding, clarity about forecast uncertainty, insufficient spatial and temporal resolution of forecasts leading to limited trust in forecasts. The workshops identified high demand for weather information related to storms, droughts and heatwaves in all the three countries. Dust storms were identified as having strong potential for IBF application in both Nigeria and Senegal. To increase the uptake of CIS by users in West Africa, NMHSs will need to develop and implement user-tailored IBF in their normal weather forecast approaches and improve communication channels with user communities. There is an urgent need for governments in West Africa to enhance the capacity of NMHSs to incorporate IBF as a routine forecast activity by first establishing a National Framework for Climate Services with user engagement as a key first pillar.

Using SPEI in predicting water table dynamics in Argentinian plains

Response time of the water table (WT) to rainfall is a relevant parameter for optimal management of water resources in plains. This study explores the response time of WT to climatological variability. WT dynamics were analyzed for a period of 10 years in 7 stations located in the Argentinean Pampean Region: Laboulaye (LAB), Arias, General Pico (GP), Azul, Dolores (DOL), Junin and Barrow. Statistical standard methods were applied on WT data series provided by the National Meteorological Service (in Spanish, SMN) and La Pampa province government. Standardized Precipitation and Evapotranspiration Index (SPEI) was applied in multiple temporal scales. Modeled SPEI data were correlated to WT and water table depth (WTD; in situ data) using the Pearson method. Results indicated that WTD response time is spatially variable in the study region when considering the rainfall and evapotranspiration balance (represented by the temporal behavior of the SPEI). These results allowed for the definition of a second-degree–function theoretical method of WTD that explains its variations for different extreme conditions. Multivariate statistical analysis was used to analyze the similarities of WTD evolution among the 5 stations for the 1986–1990 period. Highest statistical connections were found between GP and LAB, GP and DOL and between DOL and LAB stations, which indicated similarities in their dynamic and the maximum (WTD ~ 3.3 m) and mean (WTD ~ 2 m) WTD values measured during the studied period. Surface water coverage data, obtained through digital processing of satellite images of high spatial resolution, validates the relations between climatological variables and WTD showing increases (km2) during the periods in which the WTD was lowest and vice versa. The method presented in this investigation allows the use of SPEI to the prediction of WTD in zones, where it is difficult to measure it.

German Bight storm activity, 1897–2018

AbstractThis study investigates the evolution of German Bight (southeastern North Sea) storminess from 1897 to 2018 through analysing upper quantiles of geostrophic wind speeds, which act as a proxy for past storm activity. Here, geostrophic wind speeds are calculated from triplets of mean sea level pressure observations that form triangles over the German Bight. The data used in the manuscript are provided by the International Surface Pressure Databank and the national meteorological services of Denmark, Germany, and the Netherlands. The derivation of storm activity is achieved by enhancing the established triangle proxy method via combining and merging storminess time series from numerous partially overlapping triangles in an ensemble‐like manner. The utilized approach allows for the construction of robust, long‐term and subdaily German Bight storminess time series. Further, the method provides insights into the underlying uncertainty of the time series. The results show that storm activity over the German Bight is subject to multidecadal variability. The latest decades are characterized by an increase in activity from the 1960s to the 1990s, followed by a decline lasting into the 2000s and below‐average activity up until present. The results are backed through a comparison with reanalysis products from four datasets, which provide high‐resolution wind and pressure data starting in 1979 and offshore wind speed measurements taken from the FINO‐WIND project. This study also finds that German Bight storminess positively correlates with storminess in the NE Atlantic in general. In certain years, however, notably different levels of storm activity in the two regions can be found, which likely result from shifted large‐scale circulation patterns.

FAIR: a project to realize a user-friendly exchange of open weather data

Abstract. Access to high quality weather and climate data is crucial for a wide range of societal and economic issues. It allows optimising industrial processes, supports the identification of potential risks related to climate change or allows the development of corresponding adaptation and mitigation strategies. Although such data is freely available through Germany’s national meteorological service DWD (Deutscher Wetterdienst) since 2017, the application potential in industry and society has certainly not yet been fully unlocked. Major obstacles are the complexity of the raw data, as well as missing tools for their simple integration into existing industrial applications. The goal of the research project FAIR is to simplify the information exchange between the DWD and economical players. In order to reach this goal a requirement analysis with end-users of weather data from three different sectors was conducted. A central requirement regarding the site assessment of wind plants is quick and easy access to historical wind-series at specific sites. Preferably downloadable in formats like CSV or via an API. Event planning partners are interested in a quick access to health relevant weather information at their event location, and the E-mobility sector in temperature data along planned routes. In this paper, we summarize the results of the requirement analysis and present the deduced technical architecture and FAIR services aiming at a user-friendly exchange of weather data.

Tornadoes in Romania—from Forecasting and Warning to Understanding Public’s Response and Expectations

Significant progress in tornado research and management can be claimed over the last few decades worldwide. However, tornado forecasting and warning continue to be permanent challenges for most European national meteorological services because they require particular skills and experience. Moreover, tornado warnings may generate panic. Therefore, one can remark that the main difficulties are related to (1) forecasting the tornado genesis, and (2) finding the most efficient way to communicate to the general public the possibility of tornado occurrence. This article presents the main characteristics of two convective events that occurred in Romania in order to emphasize the similarities and disparities between the tornado event (30 April 2019) and the non-tornado event (6 May 2019), from the warning perspective. Further, we investigate, for the first time in Romania, the general public’s comprehension, risk perception and reactions regarding the tornado events. The survey performed in 2020 emphasized that the Romanian public is able to recognize tornadoes (60%), understand the risks (over 80%), can manage the panic (over 70%), and is rather desirous to receive clear (over 90%) and real-time (95%) tornado warnings. The lessons learned may support the further development of tornado forecasting and warning procedures, and foster the public’s awareness related to tornado events.

Exploring the ability of the WRF-ARW atmospheric model to simulate different meteorological conditions in Greece

Studies on climate change reveal as its main consequence the mean global temperature rise, as well as the increase of extreme weather events frequency and intensity. The latter are more frequently occurring worldwide over the last years and are becoming of great concern due to their strong societal and economic impacts. The best possible simulation of such events resembling reality and hence, the improvement of their predictability are very important milestones to the scientific community so as to limit down the impact of the related hazards. The WRF-ARW atmospheric model was employed to simulate different meteorological conditions in the framework of compiling a computational approach to forecast and study extremes for risk assessment at country level and particularly in Greece. Firstly, the extra-tropical cyclone (Cleopatra), in November 2013, was investigated with a number of sensitivity tests: a “chemistry including setup” of the WRF model, then the same configuration with the “chemistry” option deactivated and finally, a 3-nest setup with 1-way and 2-way nesting. The follow up of these studies provided the optimum model setup that was the 1-way nesting, which was used afterwards to simulate an extreme hot weather event that occurred in June 2007. Moreover, we examined the performance of this resolved WRF setup for a usual low-pressure system that affected Greece in September 2015. In these studies, NCEP FNL analyses data were used for model input. The main meteorological variables were analyzed and the evaluation of the results was performed with comparisons against in-situ measurements by the network of the Hellenic National Meteorological Service (HNMS) stations. The comparisons showed, in general, very good agreement between the model temperature fields and observations in all test cases. The 3-nest setup with 1-way nesting approach provided high quality prediction of the temperature fields locally at high resolution in the cases of the simulated extreme events. The model behaviour differed between the simulations of the two extreme events and the usual-low pressure system in the calculation of the precipitation variable, particularly over the areas of complex topography. Overall, the model configuration of 1-way nesting proved to be a useful modelling approach for studying and forecasting such events in an attempt to limit down their consequences.

Sensitivity analysis of the WRF model: Assessment of performance in high resolution simulations in complex terrain in the Canary Islands

Canary Islands and other regions have been greatly damaged by weather events during the last decades. For this reason, the main duty of National Meteorological Services is to minimize socio-economic losses by forecasting adverse weather episodes with enough time in advance. To achieve this goal, the use of numerical weather prediction models is highly relevant. And, even more crucial, is to comprehend the model accuracy.In this paper, an exhaustive sensitivity analysis of the Weather Research and Forecasting (WRF) model over the Canary Islands has been carried out. The complex terrain of the archipelago makes the islands a test bench of high interest. Four scores were used to assess the accuracy of the model configurations: Bias, mean absolute error (MAE), root of the Mean Squared Error (RMSE), and the correlation coefficient (r). Initially, twenty-five WRF model configurations were considered. However, a preliminary test discarded inadequate configurations, and reduced the number to six. The variables of interest were air temperature at 2 m (T2m), maximum 1-h wind gust at 10 m and 3-h rainfall accumulation. The results indicated a systematic wind speed underestimation. This underestimation is related to the influence of the location and the complex orography. The most accurate wind forecasts were obtained using the Mellor-Yamada-Janjic Planetary Boudary Layer (PBL) scheme with the WSM6 microphysics (MP) scheme. Another major conclusion is that, for precipitation, the PBL scheme has a greater impact than the MP scheme. Finally, the results show that the Boulac – Thompson combination is the most accurate regarding T2m forecast.

Using weather forecasts to forecast whether bikes are used

Although several papers have shown that bike ridership is affected by actual weather conditions, this is the first study to comprehensively investigate the impact of forecasted weather conditions on bike ridership. The results show that both actual and forecasted weather conditions can be used as useful explanatory variables for predicting bicycle usage. Even incorrect weather forecasts can impact on bike ridership, which underlines the importance of weather forecast effects for traffic planners; for example, forecasted rain can reduce bike traffic by 3.6% in periods that turn out to be rain-free. Additionally, a digital image-processing method is used to calculate the darkness of the cloud coverage displayed on weather forecast maps. The results imply that bike ridership is significantly smaller in regions with darker forecasted clouds. It is also shown that weather forecasts have a stronger impact on recreational bike traffic than on utilitarian traffic. Furthermore, various lagging and leading effects of rain forecasts are outlined. Morning rain forecasts can, for example, reduce bike ridership in midday and afternoon hours that were predicted to be rain-free. To derive these results, hourly bicycle counts from 188 automated counting stations in Germany are collected for the years 2017 and 2018. They are linked to actual weather data from Germany’s National Meteorological Service and with historical weather forecasts that are deduced from weather maps of Germany’s most-watched television news program. Log-linear and negative binomial regression models are then used to estimate the weather forecast effects.

Climatic influence on the risk of abdominal aortic aneurysm rupture.

Our aim is to examine the effects of climatic conditions on the incidence of ruptured abdominal aortic aneurysms (rAAA) in Catalonia, Spain. We combined clinical data from the Public Health official registries in Catalonia, Spain (HD-MBDS) of all rAAA with local climatic data obtained from the closest meteorological station (69 stations, National Meteorological Service: MeteoCat) from 2008 to 2017. We analyzed the median, maximum, minimum, and variability of atmospheric pressure (hPa) and air temperature (°C), solar irradiation (MJ/m2), humidity (%), accumulated precipitation (mm), median wind, and maximum flaw direction and velocity (°, m/s), recorded on the days of events, the previous day, and mean results for 3, 7, and 30 days before, as well as seasonality. Seventy-five control days were randomly selected in a 1-year period around every rAAA day at the same meteorological station, and compared. A total of 717 days and locations with rAAA were identified, and 53,775 controls were randomly selected. For the rAAA days, there were significantly lower temperatures, lower solar global irradiation, and higher mean humidity levels in all time periods (p < 0.001, p < 0.001, p < 0.05); higher atmospheric pressure variability during 1 week and 1 month before (p = 0.011, p = 0.007); and they often occurred during autumn/winter (57.6%, p < 0.001). Logistic regression identified low mean temperatures on the days of ruptures and high mean humidity the week before as independent rupture predictors. In conclusion, low median temperatures the same day and high humidity during 1 week before were identified as independent predictors of rAAA occurrence. The role of climate on pathophysiologic mechanisms may require further investigation.

Regional atmospheric reanalysis activities at Deutscher Wetterdienst: review of evaluation results and application examples with a focus on renewable energy

Abstract. Based on the numerical weather prediction model COSMO of Germany's national meteorological service (Deutscher Wetterdienst, DWD), regional reanalysis datasets have been developed with grid spacing of up to 2 km. This development started as a fundamental research activity within the Hans-Ertel-Centre for Weather Research (HErZ) at the University of Bonn and the University of Cologne. Today, COSMO reanalyses are an established product of the DWD and have been widely used in applications on European and national German level. Successful applications of COSMO reanalyses include renewable energy assessments as well as meteorological risk estimates. The COSMO reanalysis datasets are now publicly available and provide spatio-temporal consistent data of atmospheric parameters covering both near-surface conditions and vertical profiles. This article reviews the status of the COSMO reanalyses, including evaluation results and applications. In many studies, evaluation of the COSMO reanalyses point to an overall good quality and often an added value compared to different contemporary global reanalysis datasets. We further outline current plans for the further development and application of regional reanalyses in the HErZ research group Cologne/Bonn in collaboration with the DWD.

Competencies based innovative learning solutions for co-development of climate services in West Africa

Abstract. In developing countries, and particularly in West Africa, the role of Climate Services (CS) for sustainable development is growing thanks to wide spreading collaboration among European institutions, including National Meteorological and Hydrological Services (NMHS) research centers, universities, and homologue local institutions. Operationally, the implementation of CSs in developing countries is mainly pivoted on NMHS, which, according to the World Meteorological Organization (WMO), are dramatically affected by unmet learning demand. The global scale of learning needs for co-development of CSs calls for innovative solutions and a range of flexible modalities to reach learners in a variety of ways, and for sharing resources and successful strategies within the global education and training community. In order to harmonize expected learning outcomes, WMO defined a competency framework (CF) for CSs to be used in the implementation of training initiatives and knowledge sharing tools. This paper presents the strategic and methodological approach adopted in the implementation of the TOPaCS, a new knowledge-based distance learning initiative, aiming to provide a flexible learning environment within the CSs CF of WMO ensuring coherence with other WMO education initiatives (Global Campus, other RTCs, etc.). The methodological approach adopted is based on the competency-based approach to training, where competencies are composed by elements of knowledge and skill. TOPaCS integrates the WMO CF for CSs into a taxonomy co-designed with stakeholders at different levels, and allows the definition of learning paths, which are a further interactive opportunity for co-development of CSs within the TOPaCS learning ecosystem. Indeed, the approach aims also to guide further instructional strategies and assessments and becomes a starting point to build a common language enabling a better cooperation and exchange between the different CSs training initiatives.

Generation of typical meteorological years for 33 locations in Greece: adaptation to the needs of various applications

A typical meteorological year (TMY) is a set of meteorological and solar radiation parameters usually consisting of hourly values in a year for a given geographical location. Such TMYs have been derived in many countries for various applications. In Greece, TMYs have been generated mainly for Athens. The present work derives TMYs for 33 locations in Greece distributed all over the country and covering its 4 climatic zones defined for energy purposes. The TMYs are based on meteorological data collected from the Hellenic National Meteorological Service network in Greece in the period 1985–2014. The solar radiation needed in the generation of the TMYs is derived by using the meteorological radiation model. The TMY at every one of the 33 locations is provided in 5 versions to adapt to the applications of meteorology-climatology, bio-meteorology, agro-meteorology-hydrology, photovoltaics, and energy design of buildings. The 5 versions of the TMYs are generated following the modified Sandia National Laboratories method. After their generation, each version of the TMYs at any of the 33 locations is compared with the annual- and monthly-averaged values of the selected parameters of the initial 30-year database. The comparison shows that the errors (differences) do not usually exceed 5%, thus supporting the fact that the so-derived TMYs are representative of the sites selected. Also, the distribution of the errors follows the normal distribution curve.

Temporal and spatial analysis of traffic – Related pollutant under the influence of the seasonality and meteorological variables over an urban city in Peru

A four yearlong air monitoring data (since 2015 to 2018) was collected to assess the impact of meteorological parameters such as temperature, relative humidity, wind speed and wind direction on the spatial and temporal variability of CO (carbon monoxide), NO2 (nitrogen oxide), O3 (ozone), SO2 (sulfur dioxide), PM10 and PM2.5 (particulate matter with diameter aerodynamic less than 2.5 μm and 10 μm respectively) in Lima Metropolitan Area (LMA). Data from eight air quality monitoring stations, currently under the supervision of the National Meteorological and Hydrological Service (SENAMHI), was used to capture traffic – related pollutants concentrations under various local traffic conditions. Effects on meteorological events on seasonal traffic-related pollutants concentration variability were identified. Using average data from the eight stations, it was found that the monthly mean traffic-related pollutants since 2015 to 2018 were higher in spring and winter and lower in autumn and summer. Low-wind speed was associated with events that contribute to elevated seasonal PM2.5 levels. Correlation coefficients between PM2.5 concentrations and meteorological variables fluctuated significaly across different seasons. High PM2.5 concentrations were associated with low relative humidity and high wind conditions in spring. Results suggest that there exist a seasonal variation of PM2.5 concentration, and set the need of future work on the understanding of the air pollution effects on human health.

Quality-Based Combination of Multi-Source Precipitation Data

A quantitative precipitation estimate (QPE) provides basic information for the modelling of many kinds of hydro-meteorological processes, e.g., as input to rainfall-runoff models for flash flood forecasting. Weather radar observations are crucial in order to meet the requirements, because of their very high temporal and spatial resolution. Other sources of precipitation data, such as telemetric rain gauges and satellite observations, are also included in the QPE. All of the used data are characterized by different temporal and spatial error structures. Therefore, a combination of the data should be based on quality information quantitatively determined for each input to take advantage of a particular source of precipitation measurement. The presented work on multi-source QPE, being implemented as the RainGRS system, has been carried out in the Polish national meteorological and hydrological service for new nowcasting and hydrological platforms in Poland. For each of the three data sources, different quality algorithms have been designed: (i) rain gauge data is quality controlled and, on this basis, spatial interpolation and estimation of quality field is performed, (ii) radar data are quality controlled by RADVOL-QC software that corrects errors identified in the data and characterizes its final quality, (iii) NWC SAF (Satellite Application Facility on support to Nowcasting and Very Short Range Forecasting) products for both visible and infrared channels are combined and the relevant quality field is determined from empirical relationships that are based on analyses of the product performance. Subsequently, the quality-based QPE is generated with a 1-km spatial resolution every 10 minutes (corresponding to radar data). The basis for the combination is a conditional merging technique that is enhanced by involving detailed quality information that is assigned to individual input data. The validation of the RainGRS estimates was performed taking account of season and kind of precipitation.

Heavy Rainfall and Landslide Event in January 1831 at the Pedregoso Mountains (Cabeza Del Buey, SW Spain)

In this work, a landslide event that took place on January 1831 at the Pedregoso Mountains, Cabeza del Buey, SW Spain, is described. This landslide had not been documented to date and was only described in the local press. This event involved an estimated amount of dislodged material in the order of 104 m3. The amount of meteorological data is very scarce as the event occurred before the setting up of the national meteorological service in Spain. However, data from the relatively near location of SW Iberia suggest that the landslide was preceded by a prolonged period of unusually high precipitation totals and that this intense wet period is compatible with the large-scale atmospheric configuration in the winter of 1829–1830. In fact, the North Atlantic Oscillation (NAO) index for that winter achieved one of the most negative values observed in the bicentennial period spanning 1821 to 2019. This multidisciplinary work represents the first attempt to report and describe the main triggering mechanism for an historical landslide in the Extremadura region that is similar to other great historical landslides which have already been documented for other locations in Spain.

Pronosticos AClimateColombia: A system for the provision of information for climate risk reduction in Colombia

Climate variability poses major risks to agricultural production around the world, including in Colombia. Despite progress, major gaps still exist for the continuous provision of climate services for the Colombian agricultural sector. These gaps include lack of capacities in farming communities and technical assistants to understand and use seasonal forecast information, as well as the systematic provision of agro-climatic information. Here, we describe a user-centered digital agro-climatic forecast system that addresses several of these gaps. The system, named, “Pronosticos AClimateColombia,” and available at https://pronosticos.aclimatecolombia.org, formalizes the processing of climate and crop information from quality control, forecasting, and tailoring to crop-specific decision-making processes. The design, development and evaluation process captured user needs through regular engagement with key stakeholders ranging from the Ministry of Agriculture, the National Meteorological Service (IDEAM), as well as farmer organizations and farmers in a range of agricultural areas. We describe the process of design, testing and deployment of the system, in which forecast generation is performed as a series of automated steps, with agro-climatic forecasts issued on the 7th day of every month with a rolling lead-time of six months. We show that the constant gathering of user requirements and feedback resulted in users expressing substantial interest in using the system, though with some limitations on the level of understanding of the provided information. The limitations indicate a need for improved capacity at the local level. This underscores the importance of cyclical, continuous, feedback and discussion processes for climate services.

Simulación y análisis del comportamiento térmico de una sala informática en una zona cálido-húmeda

El objetivo de este trabajo es conocer el comportamiento térmico de una Sala Informática en diferentes situaciones de uso académico. La misma se encuentra en una Sede Universitaria de la ciudad de Orán (Provincia de Salta, Argentina), lugar caracterizado por tener un clima cálido-húmedo. La simulación se realiza para un periodo de 11 días dentro el periodo lectivo, recurriendo a los datos del Servicio Meteorológico Nacional y a mediciones in situ. El software usado para la simulación es SIMEDIF. La metodología de trabajo incluye actividades de relevamiento, mediciones, preparación de datos y de escenarios académicos, simulación y análisis de resultados. A partir de los resultados de la simulación se detectan situaciones de disconfort y se calcula la carga térmica requerida para superarlas. Se plantea la necesidad de incorporar estrategias bioclimáticas y de enfriamiento pasivo a fin de lograr el confort higro-térmico con el mínimo consumo energético y el mínimo impacto al medio ambiente. La importancia del trabajo radica en poder lograr una primera aproximación al comportamiento real térmico de un ambiente mediante la modelización y simulación con herramientas computacionales.

Climatological and Hydrological Observations for the South American Andes: In situ Stations, Satellite, and Reanalysis Data Sets

Modern hydrology relies on multiple sources of information combined with climatological, hydrological and glaciological data. These data can be collected through various sources such as private initiatives by companies, research programs, and both national and international organisms. They also vary by types, e.g. in-situ measurements, satellite, reanalysis and simulated data. Recently the ANDEX research project, as a GEWEX regional program, was created to understand the processes related to the hydrological cycle and energy fluxes in the Andean region from Colombia to Patagonia. It is quite challenging to carry out this program given the complex orography and diversity of climates from tropical to sub-polar climates. This review article is a compilation of the various databases that are useful for hydrometeorological research in the South American Andes. The National Meteorological and Hydrological Services in Bolivia, Chile, Colombia, Ecuador, Peru, Venezuela and Argentina provide a large amount of data however the high-elevation areas are poorly instrumented and the number of stations varies greatly between the countries. National databases are only partially shared with the international bodies responsible for summarizing the existing data; this causes problems in term of data product assimilation. Across the entire continent, too few radiosondes are being used despite the fact that these data are crucial for validating and identifying problems in the atmospheric models. An increasing number of satellite data are available but it is difficult to assimilate them into the hydroclimatogical models suited to the adjusted spatial and temporal resolutions. Specifically, for precipitation, we recommend merged products that account for the high spatial and temporal variability across the Andes. Finally, the international ANDEX program could be an excellent opportunity to increase the knowledge of the hydrological processes in the Andes.

Hindcasting the First Tornado Forecast in Europe: 25 June 1967

Abstract The tornado outbreak of 24–25 June 1967 was the most damaging in the history of western Europe, producing 7 F2–F5 tornadoes, 232 injuries, and 15 fatalities across France, Belgium, and the Netherlands. Following tornadoes in France on 24 June, the Royal Netherlands Meteorological Institute (KNMI) issued a tornado forecast for 25 June, which became the first ever—and first verified—tornado forecast in Europe. Fifty-two years later, tornadoes are still not usually forecast by most European national meteorological services, and a pan-European counterpart to the NOAA/NWS/Storm Prediction Center (SPC) does not exist to provide convective outlook guidance; yet, tornadoes remain an extant threat. This article asks, “What would a modern-day forecast of the 24–25 June 1967 outbreak look like?” To answer this question, a model simulation of the event is used in three ways: 20-km grid-spacing output to produce a SPC-style convective outlook provided by the European Storm Forecast Experiment (ESTOFEX), 800-m grid-spacing output to analyze simulated reflectivity and surface winds in a nowcasting analog, and 800-m grid-spacing output to produce storm-total footprints of updraft helicity maxima to compare to observed tornado tracks. The model simulates a large supercell on 24 June and weaker embedded mesocyclones on 25 June forming along a stationary front, allowing the ESTOFEX outlooks to correctly identify the threat. Updraft helicity footprints indicate multiple mesocyclones on both days within 40–50 km and 3–4 h of observed tornado tracks, demonstrating the ability to hindcast a large European tornado outbreak.