Távérzékelt és repülőgépes megfigyelések alkalmazása a korlátos tartományú ALADIN/HU numerikus időjárás-előrejelző modellben = Utilization of remotely sensed and aircraft observations in the limited area numerical weather prediction model ALADIN/HU

A projekt célja, az időjárás előrejelzések javítása érdekében, minél több megfigyelési adat használata az ALADIN/HU korlátos tartományú modell operatív rendszerében. A kutatás keretein belül műholdas (származtatott–AMV, radiancia-AMSU-B és SEVIRI), repülőgépes (AMDAR), és windprofiler adatok asszimilációját terveztük és végeztük el. A megfigyeléseket az asszimilációs rendszer és modell sajátosságainak figyelembe vételével bevezettük az operatív használatba. Az új adatokat finomabb felbontásban illesztettük be az asszimilációs rendszerbe, mint ahogy a globális modellek használják azokat. A repülőgépes (AMDAR) adatok sikeres alkalmazása a mérési idő szűkítésének és egy finom előzetes szűrés bevezetésének köszönhető. A SEVIRI adatok hatása az analízisre és előrejelzésre csak a feszíni mérésekkel együtt lett elfogadható. A windprofiler adatok használata nem különbözik a globális modellekben való alkalmazásuktól, az AMV adatok pedig a szárazföld fölött is használjuk. Az AMDAR adatok főként a repülési magasságban fejtik ki pozitív hatásukat. Az AMSU-B adatok hatása főleg a nedvességre és a hőmérsékletre volt kimutatható. A SEVIRI radianciák és a felszíni mérések közös használata a felszíni paraméterekre, az AMV adatok pedig a „szélsőséges” időjárási helyzetekben hatottak jobban. A windprofiler hatása az analízisre és az előrejelzésre gyengén pozitív volt. A hagyományos megfigyelések hatása inkább a rövid távú, a radiancia adatoké a hosszabb távú előrejelzésre érvényesülnek jobban. | The project aims to improve the ALADIN/HU operational model analysis and forecasts by adding more observation types in the system. We planed to add in the analysis system satellite (retrieved wind–AMV, and radiances – ATOVS/AMSU-B and MSG/SEVIRI), aircraft (AMDAR), and windprofiler data. All the observations were conducted to the daily operation. The new observations, in contrary to their use in the global models, were assimilated with finer thinning distances. The optimal use of the aircraft data were found by restricting the data extraction time and applying an addition data thinning during the analysis process. The optimal use of the SEVIRI radiance was reached only by using them together with the surface parameters. The windprofiler data were implemented using the global settings, while the AMV data are used over land also. The impact of the AMDAR data were mainly observed around the cruise level. The AMSU-B data effected more the analysis and forecasts of humidity and temperature. The SEVIRI data assimilated together with some surface parameters improved mainly the analysis and forecast of surface fields, while the impact of the AMV data was more pronounced in case of “severe” weather conditions. The impact of the windprofiler data was rather slightly positive than neutral. According to our study, the conventional observations are more important for shorter forecast ranges, while the radiance data are most important for longer forecast ranges

The link between catchment precipitation forecast skill and spread to that of downstream ensemble hydrological forecasts

Operational rainfall and flood forecasting systems across the world are increasingly using ensemble approaches. Such systems are operated by the Flood Forecasting Centre (FFC) and Scottish Flood Forecasting Service (SFFS) across Great Britain producing ensemble gridded hydrological forecasts for the next 5-6 days. In order to maximise the practical day-to-day use of these systems for decision-making and warning, duty hydro-meteorologists require a sound understanding of both the meteorological and hydrological ensemble forecast skill. In this work, a common verification framework is defined and used in order to understand the relative levels of skill in both rainfall and river flow forecasting systems. A blended 24-member ensemble precipitation forecast, produced by the Met Office, is used to drive the operational distributed hydrological model in ensemble mode. The hydrological forecasts provide output every 15 minutes out to 6 days on a 1km grid. The blended rainfall forecast is a mixture of the 2.2 km MOGREPS-UK ensemble up to 36h and the 32 km global MOGREPS-G ensemble at longer lead-times. The forecasts are interpolated on to a common 2 km grid and the hydrological model used is the Grid-to-Grid model (G2G) developed by the Centre for Ecology & Hydrology. To establish an upper bound on skill, assessments over a daily lead-time interval are studied first, and will be the focus here. Spatial and regional variations in forecast skill are compared between the precipitation (e.g. daily accumulations) and the river flow forecasts. Also of interest is the impact of catchment size and how to pool and present the skill metrics in a meaningful way for end-users. For precipitation, the impact of observation type: gridded gauge-only analyses and a radar-derived (gauge calibrated) precipitation product, is compared to quantify the uncertainty that comes from the observations. Of particular interest is understanding how the spread in the precipitation forecast is modulated by the downstream hydrological model. Is it inflated, does it remain comparable, or is it reduced? The work aims to establish the basis for a real-time monitoring tool that can assist hydro-meteorologists in their interpretation of operational ensemble forecasts, and facilitate associated decision making processes

A várandósság és a perinatális időszak egyes jellemzőinek összefüggése a DIFER-készségekkel

Kutatásunkban 418 nagycsoportos gyermek kognitív és szociális alapkészségének a vizsgálatát végeztük el a DIFER Programcsomag négy tesztjével. A gyermekek készségfejlettségének eredményeihez hozzákapcsoltuk azokat a védőnői státuszadatokat, amelyek a perinatális időszakra vonatkoznak. Kutatási kérdésünk a korai befolyásolótényezők és a nagycsoportos készségfejlettség közötti összefüggések kimutatására vonatkozott. Külön-külön elemeztük a gesztációs hét, az egyperces életkorban mért Apgar-érték, valamint a várandósság lefolyása szerint kimutatható különbségeket a nagycsoportosok készségfejlettségében. A statisztikai próbák alapján a 38–42. hétre születettek és a koraszülöttek nagycsoportban mért alapkészség-indexe között nincs szignifikáns különbség. Hasonlóképpen nem találtunk szignifikáns különbséget a fokozott gondozást igénylő és egészséges várandósságból született gyermekek alapkészség-fejlettségében és az 1 perces Apgarérték vonatkozásában sem. Eredményeink egybevágnak azokkal a korábbi kutatási eredményekkel, amelyek arra hívják fel a figyelmet, hogy a koraszülött gyermekek 56 éves életkorukban az egyes fejlődési területeken nem mutatnak jelentős mértékű lemaradást időre született társaikhoz képest (Gráf, 2015; Nagy et al., 2018). A gyermekek egyéni eredményeit megvizsgálva megfogalmaztunk néhány további együttjárást, amelyek óvatos következtetések levonását teszik csak lehetővé. A kiragadott egyéni jellemzők alapján a legalacsonyabb nagycsoportos DIFER-indexszel jellemezhető kisgyermek a 27. gesztációs héten született, nála feltehetően a koraszüléssel is kapcsolatba hozható a kognitív és szociális készségek alacsony szintje. Kutatási eredményeink általánosításában korlátot jelent a minta összetétele. A vizsgálatba olyan gyermekek kerültek be, akik többségi óvodába jártak. Nem voltak tehát olyan gyermekek a mintában, akik speciális óvodai nevelésben vesznek részt. Jóllehet, az ő vizsgálatuk is releváns lenne a kutatási kérdés szempontjából. A speciális intézményekben nagyobb lehet azoknak a gyermekeknek az aránya, akiknél a perinatális jellemzők a normál értékhez képest eltérést mutatnak. A mintánkban kevés olyan gyermek volt, akiket nagyobb mértékű, esetleg szélsőségesen nagy perinatális eltérések jellemeznek. Emiatt ilyen statisztikai összehasonlításokat nem tudtunk végezni, ezeknél a gyermekeknél csak egyedi esetek elemzésére volt lehetőségünk. Következő kutatásunk célja egy speciális mintaválasztást követően a nagyobb mértékű perinatális eltérések prediktív hatásának az elemzése. Jelen vizsgálatunk eredményei arra hívják fel a figyelmet, hogy bár a perinatális időszak történései sok szempontból befolyásolják az értelmi fejlődést, az általunk vizsgált jellemzők prediktív ereje nem determinisztikus. A perinatális jellemzők kismértékű eltérése nem eredményezi a DIFER-készségek elmaradását. Elképzelhető, hogy a biológiai befolyásolótényezőket jól ellensúlyozhatja a családi, pedagógiai, környezeti hatásrendszer, ezeknek a hatásoknak az igazolása azonban további kutatási feladat

Towards operational joint river flow and precipitation ensemble verification: considerations and strategies

Operational rainfall and flood forecasting systems across the world are increasingly using ensemble approaches. In Britain such systems are operated by the Flood Forecasting Centre (FFC) over England & Wales and by the Scottish Flood Forecasting Service (SFFS) over Scotland producing ensemble gridded hydrological forecasts out to 5 or 6 days. In order to maximise the practical day-to-day use of these systems for flood guidance and warning, duty hydrometeorologists require a sound understanding of both the meteorological and hydrological ensemble forecast skill. To help meet this requirement, a common framework for the verification of river flow and precipitation ensembles is developed and demonstrated over Britain for eventual use in an operational flood forecasting setting. The river flow ensembles are obtained from the distributed hydrological model Grid-to-Grid (G2G), configured with national coverage on a 1 km grid and using an ensemble of 15 minute precipitation accumulations as input. The precipitation ensemble consists of operational Numerical Weather Prediction (NWP) forecasts from the Met Office Unified Model. Given the different physical characteristics of river flow and catchment precipitation, and differences in forecast verification methodologies routinely employed by the hydrological and meteorological communities, key considerations for the common verification framework are identified and investigated. These include the appropriateness of different precipitation accumulation periods given timing errors and hydrological response times, the operationally relevant use of river flow and rainfall thresholds for contingency tables and skill scores based on them, and the effects of precipitation observation error on verification. The practical challenges of verification using a limited record of precipitation ensembles, from a system only relatively recently made operational, are highlighted. Methods of obtaining more robust verification statistics, given the available ensembles, are presented and demonstrated for example periods in December 2015. At the regional scale, both river flow and precipitation verification results are shown to be dependent on the locations considered and related to variations in precipitation totals. For river flows, catchment size is found to be a key influence on ensemble performance. It is demonstrated how this behaviour can be used to obtain more-robust river flow verification statistics at sub-regional scales

Catchment-based precipitation and river flow ensemble forecast skill in the presence of observation uncertainty

The use of ensemble forecasts in operational rainfall and flood forecasting systems is rapidly increasing. In the UK, such systems are operated by the Flood Forecasting Centre (FFC) and Scottish Flood Forecasting Service (SFFS) producing ensemble gridded hydrological forecasts out to 6 days. In order to maximise the practical day-to-day use of these systems, for decision-making and warning, duty hydrometeorologists require a sound understanding of both the meteorological and hydrological ensemble forecast skill. A blended Met Office 24-member ensemble precipitation forecast – a mixture of the STEPS nowcast ensemble and STEPS-blended 2.2 km MOGREPS-UK ensemble and 32 km global MOGREPS-G ensemble – drives the Grid-to-Grid (G2G) distributed hydrological model developed by the Centre for Ecology & Hydrology (CEH). G2G uses 15-minute precipitation accumulations as input, and produces river flows at 15-minute intervals on a 1km grid. Phase 1 of the investigation, completed in 2017, formulated and demonstrated a common rainfall and river flow ensemble verification framework. The results gave an initial appreciation of the relative levels of skill in both ensemble rainfall and river flow forecasting systems. In 2018, the verifications of daily and hourly precipitation accumulations will be extended to use 15-minute accumulations. Verifications for three forecast time-horizons – Day 1, Days 2-3 and Days 4-6 – will also be demonstrated. In Phase 1, the sensitivity of verification measures to observation type was illustrated by comparing scores based on radar-only and raingauge-only analyses. Here, in Phase 2, theoretical principles discussed by Ferro (2017) are explored to determine whether a practical application of the theory is possible to gain a more robust measure of forecast performance in the presence of observation uncertainty. Reference Ferro, C.A.T. 2017. Measuring forecast performance in the presence of observation error. Q. J. R. Meteorol. Soc., 143, 2665-2676

Rainfall and river flow ensemble verification: Phase 2. Final report

This document is the Final Report for the “Rainfall and River Flow Ensemble Verification: Phase 2” (EnsVerP2) project forming part of the project “Improving confidence in Flood Guidance through verification of rainfall and river flow ensembles”. Forecasting the weather and floods is a challenging task and inherently uncertain. Acknowledging and accounting for the uncertainty in precipitation and flood forecasts has become increasingly important. This has partly been driven by the move of warning and guidance services to risk-based approaches that combine the likelihood of flooding with its potential impact on society and the environment. In the UK, such risk-based approaches underpin the National Severe Weather Warning Service delivered by the Met Office, and the Flood Guidance Statements produced by the Flood Forecasting Centre (FFC) and Scottish Flood Forecasting Service (SFFS). A standard approach to accounting for forecast uncertainty is to use ensemble methods. For a number of years, FFC and SFFS have used precipitation ensembles coupled with the national Grid-to-Grid (G2G) model of river flow to underpin the Flood Guidance Statement. However, the performance of the overall end-to-end ensemble precipitation and river flow forecasting system is currently not verified routinely. This ensemble verification information and evidence is essential: its absence can limit end-user confidence and inhibit full exploitation for flood-risk guidance. In addition, the local flood forecasting systems - used by the Environment Agency (EA), Scottish Environment Protection Agency (SEPA) and Natural Resources Wales (NRW) - are planned to transition to ensemble forecasting and will have similar requirements for verification information. A first step in addressing this operational gap has been to bring together existing expertise in meteorological and hydrological model performance assessment to design and develop a new, holistic Ensemble Verification Framework. Then to consider how this Framework could be used to develop an operational end-end interactive Ensemble Forecast Visualisation and Verification System. The Framework has been designed so that the operational system developed from it would help forecasters answer the following two key questions. • How well has the ensemble precipitation and flood forecasting system performed in the (recent) past? Particularly for flood events of interest. • What does this mean for interpreting today’s forecast? Forecasters could then make more informed decisions and increase their confidence in the use of ensembles for forecasting the severity and likelihood of precipitation and flooding. To develop and test the potential verification approaches and operational displays, 16-months of precipitation and river flow ensemble forecasts have been processed and verified. Specific case-studies, identified with the help of stakeholders, have been used to prototype, demonstrate, assess and refine the verification tools. The Best Medium Range (BMR) precipitation ensemble is used as input to the national-scale G2G model of river flow across Great Britain and to a small selection of catchment-scale PDM local models of river flow. This approach has allowed rigorous scientific exploration of how to provide robust verification statistics of the ensemble precipitation inputs to the river flow modelling and of its ensemble river flow outputs. The scientific analysis allowed identification of several points relevant to the underpinning verification methodology part of the Framework. • Three different precipitation accumulation time-intervals were evaluated: 15 min (the temporal resolution of the river flow model and its precipitation inputs), hourly and daily. Daily precipitation accumulations appear to provide the best guidance in terms of rain volume for hydrological impacts. One reason for this may well be because it removes the impact of timing errors at the sub-daily scale. Sub-daily precipitation can be more closely related to river flow on an ensemble member-by-member basis. • The source of observed precipitation (raingauge, radar or merged raingauge-radar) has an impact on the verification analyses and G2G river flow performance. • The change in precipitation-intensity characteristics with lead-time between the STEPS, MOGREPS-UK and MOGREPS-G components of the BMR precipitation ensemble, are evident in both rainfall and river flow analysis. • The length of period used for ensemble verification is an important factor: generally longer than two years is recommended if possible. The 16-month test period was sufficient for generating enough precipitation threshold-exceedances for the 95th percentile thresholds: but insufficient for higher thresholds and for considering river flow thresholds above one half the median annual maximum flood at sub-regional scales. • New methods of presenting the precipitation forecast probabilities have been developed for precipitation thresholds that are hydrologically relevant. The verification of these Time-Window Probabilities (TWPs) has shown that the probabilities are larger, and also more reliable: so users can have greater confidence in using them. For new real-time displays to be of value in operational settings, it is important that users (e.g. FFC hydrometeorologists or flood forecasting officers) find the displays understandable and easy to deploy in support of flood guidance and warning. Operational users have been engaged in co-design of the real-time forecast displays through the Project Board and a Workshop. These interactions have identified that the real-time displays need to be flexible and informative, with varying layers of detail. Viewing the precipitation and river flow together, however, is the most important ingredient along with using common methods for conveying information on both. Prototype joint rainfall and river flow displays have been created. Further co-design of interactive displays is recommended during future implementation and interactions should include operational users, researchers and system developers. Case-studies have been used to highlight the potential benefits of these new real-time displays. They have demonstrated how the ensemble verification information can help users make more informed decisions when ensemble verification information is included. For example, knowing whether a forecast is over- or under-confident for different lead-times and severity-thresholds can be very helpful, particularly in marginal cases. That is if a forecast has a tendency to predict too high or low a probability of precipitation, or of river flow, exceeding a given level of severity. Summary and key recommendation: Realising the benefit and value of probabilistic flood-risk information for decision-making was a key motivator for the “Rainfall and River Flow Ensemble Verification: Phase 2” project. The project succeeded in bringing together the meteorology and hydrology to define, test and demonstrate a joint Ensemble Verification Framework for ensemble precipitation and river flow forecasts. The outcomes of the project demonstrate how the subsequent verification information can be used to enhance the user’s perception and ability to deploy ensemble forecasts and derived probabilities in day-to-day flood risk decision-making. Overall, the key finding is that joint precipitation and river flow ensemble verification is possible and useful. The primary recommendation is that an end-to-end interactive Ensemble Forecast Visualisation and Verification System for FFC (and SFFS) be implemented as soon as is practicable. The Ensemble Verification Framework provides the blueprint for the system and the Joint Coding Framework developed and applied here provides the basis for the algorithm and code. A detailed set of recommendations have been provided, including what is required for operational implementation. This also includes a priority list of recommendations for developing a minimum system. The proposed system would address the current urgent operational gap in ensemble forecast verification capability for FFC and SFFS. It would mark a significant addition to the forecasters’ toolkit by providing real-time displays that incorporate ensemble verification information for the first time, and in a usable form. In turn, this will facilitate enhanced and more informed decision-making at times of potential flood-risk. Local model systems have ensemble and probabilistic flood forecasting as an aspiration in their future plans. These systems would eventually benefit from the operationally urgent developments recommended here for the national-scale G2G model used by FFC and SFFS. Local model users could play an early and active part in system co-design as part of a staged implementation process for local model systems

CECILIA Regional Climate Simulations for Future Climate : Analysis of Climate Change Signal

Regional climate models (RCMs) are important tools used for downscaling climate simulations from global scale models. In project CECILIA, two RCMs were used to provide climate change information for regions of Central and Eastern Europe. Models RegCM and ALADIN-Climate were employed in downscaling global simulations from ECHAM5 and ARPEGE-CLIMAT under IPCC A1B emission scenario in periods 2021-2050 and 2071-2100. Climate change signal present in these simulations is consistent with respective driving data, showing similar large-scale features: warming between 0 and 3 degrees C in the first period and 2 and 5 degrees C in the second period with the least warming in northwestern part of the domain increasing in the southeastern direction and small precipitation changes within range of +1 to -1 mm/day. Regional features are amplified by the RCMs, more so in case of the ALADIN family of models