scholarly journals Evaluation of Probabilistic Quality and Value of the ENSEMBLES Multimodel Seasonal Forecasts: Comparison with DEMETER

2011 ◽  
Vol 139 (2) ◽  
pp. 581-607 ◽  
Author(s):  
Andrea Alessandri ◽  
Andrea Borrelli ◽  
Antonio Navarra ◽  
Alberto Arribas ◽  
Michel Déqué ◽  
...  
Keyword(s):  
Seasonal Prediction ◽  
The Other ◽  
Seasonal Forecasts ◽  
Potential Predictability ◽  
Anomalous Surface ◽  
Discrimination Information ◽  
Time Variations ◽  
Prediction Systems ◽  
The Tropics ◽  
Start Dates

Abstract The performance of the new multimodel seasonal prediction system developed in the framework of the European Commission FP7 project called ENSEMBLE-based predictions of climate changes and their impacts (ENSEMBLES) is compared with the results from the previous project [i.e., Development of a European Multimodel Ensemble System for Seasonal-to-Interannual Prediction (DEMETER)]. The comparison is carried out over the five seasonal prediction systems (SPSs) that participated in both projects. Since DEMETER, the contributing SPSs have improved in all aspects with the main advancements including the increase in resolution, the better representation of subgrid physical processes, land, sea ice, and greenhouse gas boundary forcing, and the more widespread use of assimilation for ocean initialization. The ENSEMBLES results show an overall enhancement for the prediction of anomalous surface temperature conditions. However, the improvement is quite small and with considerable space–time variations. In the tropics, ENSEMBLES systematically improves the sharpness and the discrimination attributes of the forecasts. Enhancements of the ENSEMBLES resolution attribute are also reported in the tropics for the forecasts started 1 February, 1 May, and 1 November. Our results indicate that, in ENSEMBLES, an increased portion of prediction signal from the single-models effectively contributes to amplify the multimodel forecasts skill. On the other hand, a worsening is shown for the multimodel calibration over the tropics compared to DEMETER. Significant changes are also shown in northern midlatitudes, where the ENSEMBLES multimodel discrimination, resolution, and reliability improve for February, May, and November starting dates. However, the ENSEMBLES multimodel decreases the capability to amplify the performance with respect to the contributing single models for the forecasts started in February, May, and August. This is at least partly due to the reduced overconfidence of the ENSEMBLES single models with respect to the DEMETER counterparts. Provided that they are suitably calibrated beforehand, it is shown that the ENSEMBLES multimodel forecasts represent a step forward for the potential economical value they can supply. A warning for all potential users concerns the need for calibration due to the degraded tropical reliability compared to DEMETER. In addition, the superiority of recalibrating the ENSEMBLES predictions through the discrimination information is shown. Concerning the forecasts started in August, ENSEMBLES exhibits mixed results over both tropics and northern midlatitudes. In this case, the increased potential predictability compared to DEMETER appears to be balanced by the reduction in the independence of the SPSs contributing to ENSEMBLES. Consequently, for the August start dates no clear advantage of using one multimodel system instead of the other can be evidenced.

Potential predictability of Southwest US rainfall : role of tropical and high-latitude variability

2021 ◽  
pp. 1-45
Keyword(s):  
Time Scale ◽  
Climate Model ◽  
Southern Oscillation ◽  
Seasonal Prediction ◽  
Seasonal Rainfall ◽  
The Arctic ◽  
Sea Ice Concentration ◽  
Potential Predictability ◽  
Subseasonal Variability ◽  
The Tropics

Abstract This study explores the potential predictability of Southwest US (SWUS) precipitation for the November-March season in a set of numerical experiments performed with the Whole Atmospheric Community Climate Model. In addition to the prescription of observed sea surface temperature and sea ice concentration, observed variability from the MERRA-2 reanalysis is prescribed in the tropics and/or the Arctic through nudging of wind and temperature. These experiments reveal how a perfect prediction of tropical and/or Arctic variability in the model would impact the prediction of seasonal rainfall over the SWUS, at various time scales. Imposing tropical variability improves the representation of the observed North Pacific atmospheric circulation, and the associated SWUS seasonal precipitation. This is also the case at the subseasonal time scale due to the inclusion of the Madden-Julian Oscillation (MJO) in the model. When additional nudging is applied in the Arctic, the model skill improves even further, suggesting that improving seasonal predictions in high latitudes may also benefit prediction of SWUS precipitation. An interesting finding of our study is that subseasonal variability represents a source of noise (i.e., limited predictability) for the seasonal time scale. This is because when prescribed in the model, subseasonal variability, mostly the MJO, weakens the El Niño Southern Oscillation (ENSO) teleconnection with SWUS precipitation. Such knowledge may benefit S2S and seasonal prediction as it shows that depending on the amount of subseasonal activity in the tropics on a given year, better skill may be achieved in predicting subseasonal rather than seasonal rainfall anomalies, and conversely.

A novel model independence methodology to improve multi-model seasonal forecasts combination

2020 ◽  
Author(s):  
Franco Catalano ◽  
Andrea Alessandri ◽  
Kristian Nielsen ◽  
Irene Cionni ◽  
Matteo De Felice
Keyword(s):  
Seasonal Prediction ◽  
Boreal Summer ◽  
Brier Score ◽  
Boreal Winter ◽  
Seasonal Forecasts ◽  
Surface Solar Radiation ◽  
Model Ensembles ◽  
Prediction Systems ◽  
June July ◽  
Forecasts Combination

<p align="justify">Multi-model ensembles (MMEs) are powerful tools in dynamical climate prediction as they account for the overconfidence and the uncertainties related to single model ensembles. The potential benefit that can be expected by using a MME amplifies with the increase of the independence of the contributing Seasonal Prediction Systems. To this aim, a novel methodology has been developed to assess the relative independence of the prediction systems in the probabilistic information they provide.</p><p align="justify"><span>We considered the Copernicus C3S seasonal forecasts product considering the one-month lead retrospective seasonal predictions for boreal summer and boreal winter seasons (1</span><sup><span>st</span></sup><span> May and 1</span><sup><span>st</span></sup><span> November start dates, i.e. June-July-August, JJA and December-January-February, DJF). We analysed the seasonal hindcasts in terms of deterministic and probabilistic scores with a particular focus on </span><span>continental areas</span><span>, since little evaluation has been performed so far over land domains that is where most of the applications of seasonal forecasts are based. The most relevant target variables of interest for the energy users have been considered and skill differences between the prediction systems have been analysed together with related possible sources of predictability. The analysis evidenced the importance of snow-albedo processes for temperature predictions in DJF and the effect of the atmospheric dynamics through moisture convergence for the prediction of surface solar radiation in JJA. </span><span>A</span><span> new metric, the Brier Score Covariance, designed to quantify the probabilistic independence among the models, has been </span><span>developed and </span><span>applied to optimize model selection and combination strategies with a particular focus on the most relevant variables for energy applications.</span></p>

scholarly journals Medium-Range, Monthly, and Seasonal Prediction for Europe and the Use of Forecast Information

2006 ◽  
Vol 19 (23) ◽  
pp. 6025-6046 ◽  
Author(s):  
Mark J. Rodwell ◽  
Francisco J. Doblas-Reyes
Keyword(s):  
Coupled Model ◽  
Seasonal Prediction ◽  
Model Potential ◽  
Mitigation Strategies ◽  
General Level ◽  
Seasonal Forecasts ◽  
Seasonal Predictability ◽  
Potential Predictability ◽  
Medium Range ◽  
The Impact

Abstract Operational probabilistic (ensemble) forecasts made at ECMWF during the European summer heat wave of 2003 indicate significant skill on medium (3–10 day) and monthly (10–30 day) time scales. A more general “unified” analysis of many medium-range, monthly, and seasonal forecasts confirms a high degree of probabilistic forecast skill for European temperatures over the first month. The unified analysis also identifies seasonal predictability for Europe, which is not yet realized in seasonal forecasts. Interestingly, the initial atmospheric state appears to be important even for month 2 of a coupled forecast. Seasonal coupled model forecasts capture the general level of observed European deterministic predictability associated with the persistence of anomalies. A review is made of the possibilities to improve seasonal forecasts. This includes multimodel and probabilistic techniques and the potential for “windows of opportunity” where better representation of the effects of boundary conditions (e.g., sea surface temperature and soil moisture) may improve forecasts. “Perfect coupled model” potential predictability estimates are sensitive to the coupled model used and so it is not yet possible to estimate ultimate levels of seasonal predictability. The impact of forecast information on different users with different mitigation strategies (i.e., ways of coping with a weather or climate event) is investigated. The importance of using forecast information to reduce volatility as well as reducing the expected expense is highlighted. The possibility that weather forecasts can affect the cost of mitigating actions is considered. The simplified analysis leads to different conclusions about the usefulness of forecasts that could guide decisions about the development of “end-to-end” (forecast-to-user decision) systems.

scholarly journals A Comprehensive Assessment of CFS Seasonal Forecasts over the Tropics*

2012 ◽  
Vol 27 (1) ◽  
pp. 3-27 ◽  
Author(s):  
K. P. Sooraj ◽  
H. Annamalai ◽  
Arun Kumar ◽  
Hui Wang
Keyword(s):  
Real Time ◽  
El Niño ◽  
El Nino ◽  
Seasonal Prediction ◽  
Skill Score ◽  
Seasonal Forecasts ◽  
Skill Scores ◽  
Different Types ◽  
The Tropics ◽  
Sst Anomalies

Abstract The 15-member ensemble hindcasts performed with the National Centers for Environmental Prediction Climate Forecast System (CFS) for the period 1981–2005, as well as real-time forecasts for the period 2006–09, are assessed for seasonal prediction skills over the tropics, from deterministic (anomaly correlation), categorical (Heidke skill score), and probabilistic (rank probability skill score) perspectives. Further, persistence, signal-to-noise ratio, and root-mean-square error analyses are also performed. The CFS demonstrates high skill in forecasting El Niño–Southern Oscillation (ENSO) related sea surface temperature (SST) anomalies during developing and mature phases, including that of different types of El Niño. During ENSO, the space–time evolution of anomalous SST, 850-hPa wind, and rainfall along the equatorial Pacific, as well as the mechanisms involved in the teleconnection to the tropical Indian Ocean, are also well represented. During ENSO phase transition and in the summer, the skill of forecasting Pacific SST anomalies is modest. An examination of CFS ability in forecasting seasonal rainfall anomalies over the U.S. Affiliated Pacific Islands (USAPI) indicates that forecasting the persistence of dryness from El Niño winter into the following spring/summer is skillful at leads > 3 months. During strong El Niño years the persistence is predicted by all members with a 6-month lead time. Also, the model is skillful in predicting regional rainfall responses during different types of El Niño. Since both deterministic and probabilistic skill scores converge, the suggestion is that the forecast is useful. The model’s skill in the real-time forecasts for the period 2006–09 is also discussed. The results suggest the feasibility that a dynamical-system-based seasonal prediction of precipitation over the USAPI can be considered.

scholarly journals Predictions of the boreal winter stratosphere with the C3S multi-model seasonal forecast system

2021 ◽  
Author(s):  
Alice Portal ◽  
Paolo Ruggieri ◽  
Froila M. Palmeiro ◽  
Javier Garcı́a-Serrano ◽  
Daniela I. V. Domeisen ◽  
...  
Keyword(s):  
Southern Oscillation ◽  
Polar Vortex ◽  
Seasonal Prediction ◽  
Seasonal Forecast ◽  
Wave Activity ◽  
Arctic Sea Ice ◽  
Mean Flow ◽  
Seasonal Forecasts ◽  
Stratospheric Polar Vortex ◽  
Prediction Systems

<p>As a result of the recent progress in the performance of seasonal prediction systems, forecasts of the mid-latitude weather at seasonal time scales are becoming increasingly important for societal decision making, as in risk estimate and management of meteorological extreme events. The predictability of the Northern-Hemisphere winter troposphere, especially in the Euro-Atlantic region, stems from the representation of a number of sources of predictability, notably El Nino Southern Oscillation, the stratospheric polar vortex, Arctic sea-ice extent, Eurasian snow cover. Among these, the stratospheric polar vortex is known to play a paramount role in seasonal forecasts of the winter tropospheric flow.</p><p>Here, we investigate the performance in the stratosphere of five seasonal prediction systems taking part in the Copernicus Climate Change Service (C3S), with a focus on the seasonal forecast skill and variability, and on the assessment of stratospheric processes. We show that dynamical forecasts of the stratosphere initialised at the beginning of November are considerably more skilful than empirical forecasts based on observed October or November anomalies. Advances in the representation of stratospheric seasonal variability and extremes, i.e. sudden stratospheric warming frequency, are identified with respect to previous generations of climate models running roughly a decade ago. Such results display, however, a large model dependence. Finally, we stress the importance of the relation between the stratospheric wave activity and the stratospheric polar vortex (i.e. the wave—mean-flow interaction), applied both to the variability and to the predictability of the stratospheric mean flow. Indeed, forecasts of the winter stratospheric polar vortex are closely connected to the prediction of November-to-February stratospheric wave activity, in particular in the Eurasian sector.</p>

scholarly journals Influence of “Realistic” Land Surface Wetness on Predictability of Seasonal Precipitation in Boreal Summer

2006 ◽  
Vol 19 (8) ◽  
pp. 1450-1460 ◽  
Author(s):  
Shinjiro Kanae ◽  
Yukiko Hirabayashi ◽  
Tomohito Yamada ◽  
Taikan Oki
Keyword(s):  
Land Surface ◽  
Seasonal Prediction ◽  
Atmospheric Model ◽  
Surface Fluxes ◽  
The Other ◽  
Boreal Summer ◽  
Seasonal Precipitation ◽  
Potential Predictability ◽  
Surface Wetness ◽  
Semiarid Regions

Abstract Outputs from two ensembles of atmospheric model simulations for 1951–98 define the influence of “realistic” land surface wetness on seasonal precipitation predictability in boreal summer. The ensembles consist of one forced with observed sea surface temperatures (SSTs) and the other forced with realistic land surface wetness as well as SSTs. Predictability was determined from correlations between the time series of simulated and observed precipitation. The ratio of forced variance to total variance determined potential predictability. Predictability occurred over some land areas adjacent to tropical oceans without land wetness forcing. On the other hand, because of the chaotic nature of the atmosphere, considerable parts of the land areas of the globe did not even show potential predictability with both land wetness and SST forcings. The use of land wetness forcing enhanced predictability over semiarid regions. Such semiarid regions are generally characterized by a negative correlation between fluxes of latent heat and sensible heat from the land surface, and are “water-regulating” areas where soil moisture plays a governing role in land–atmosphere interactions. Actual seasonal prediction may be possible in these regions if slowly varying surface conditions can be estimated in advance. In contrast, some land regions (e.g., south of the Sahel, the Amazon, and Indochina) showed little predictability despite high potential predictability. These regions are mostly characterized by a positive correlation between the surface fluxes, and are “radiation-regulating” areas where the atmosphere plays a leading role. Improvements in predictability for these regions may require further improvements in model physics.

Grand Multi-Model Seasonal Forecasts in the SECLI-FIRM project

2020 ◽  
Author(s):  
Andrea Alessandri ◽  
Franco Catalano ◽  
Matteo De Felice ◽  
Kristian Nielsen ◽  
Alberto Troccoli ◽  
...  
Keyword(s):  
Seasonal Prediction ◽  
Added Value ◽  
Japan Meteorological Agency ◽  
Brier Score ◽  
Seasonal Forecasts ◽  
Seasonal Climate ◽  
Climate Forecasts ◽  
Prediction Systems ◽  
Seasonal Climate Forecasts ◽  
Selection Of

<p>A key objective of the Added Value of Seasonal Climate Forecasts for Integrated Risk Management Decisions (SECLI-FIRM, www.secli-firm.eu) project is the optimisation of the performance of seasonal climate forecasts provided by many producing centers, in a Grand Multi-Model approach, for predictands relevant for the specific case studies considered in SECLI-FIRM.</p><p>The Grand Multi-Model Ensemble (MME) consists of the five Seasonal Prediction Systems (SPSs) provided by the European Copernicus C3S and a selection of other five SPSs independently developed by centres outside Europe, four by the North American (NMME) plus the SPS by the Japan Meteorological Agency (JMA).</p><p>All the possible multi-model combinations have been evaluated showing that, in general, only a limited number of SPSs is required to obtain the maximum attainable performance. Although the selection of models that perform better is usually different depending on the region/phenomenon under consideration, it is shown that the performance of the Grand-MME seasonal predictions is enhanced with the increase of the independence of the contributing SPSs, i.e. by mixing European SPSs with those from NMME-JMA.</p><p>Starting from the definition of the Brier score a novel metric has been developed, named the Brier score covariance (BScov), which estimates the relative independence of the prediction systems. BScov is used to quantify independence among the SPSs and, together with probabilistic skill metrics, used to develop a strategy for the identification of the combinations that optimize the probabilistic performance of seasonal predictions for the study cases.</p>

scholarly journals Evaluation of Submonthly Precipitation Forecast Skill from Global Ensemble Prediction Systems

2015 ◽  
Vol 143 (7) ◽  
pp. 2871-2889 ◽  
Author(s):  
Shuhua Li ◽  
Andrew W. Robertson
Keyword(s):  
Skill Score ◽  
Forecast Skill ◽  
Prediction Skill ◽  
Precipitation Forecast ◽  
Ensemble Prediction ◽  
Boreal Summer ◽  
Seasonal Forecasts ◽  
Maritime Continent ◽  
Prediction Systems ◽  
The Tropics

Abstract The prediction skill of precipitation at submonthly time scales during the boreal summer season is investigated based on hindcasts from three global ensemble prediction systems (EPSs). The results, analyzed for lead times up to 4 weeks, indicate encouraging correlation skill over some regions, particularly over the Maritime Continent and the equatorial Pacific and Atlantic Oceans. The hindcasts from all three models correspond to high prediction skill over the first week compared to the following three weeks. The ECMWF forecast system tends to yield higher prediction skill than the other two systems, in terms of both correlation and mean squared skill score. However, all three systems are found to exhibit large conditional biases in the tropics, highlighted using the mean squared skill score. The sources of submonthly predictability are examined in the ECMWF hindcasts over the Maritime Continent in three typical years of contrasting ENSO phase, with a focus on the combined impact of the intraseasonal MJO and interannual ENSO. Rainfall variations over Borneo in the ENSO-neutral year are found to correspond well with the dominant MJO phase. The contribution of ENSO becomes substantial in the two ENSO years, but the MJO impact can become dominant when the MJO occurs in phases 2–3 during El Niño or in phases 5–6 during the La Niña year. These results support the concept that “windows of opportunity” of high forecast skill exist as a function of ENSO and the MJO in certain locations and seasons, which may lead to subseasonal-to-seasonal forecasts of substantial societal value in the future.

scholarly journals Yearly evolution of Euro-Atlantic weather regimes and of their sub-seasonal predictability

2021 ◽  
Author(s):  
Nicola Cortesi ◽  
Verónica Torralba ◽  
Llorenó Lledó ◽  
Andrea Manrique-Suñén ◽  
Nube Gonzalez-Reviriego ◽  
...  
Keyword(s):  
Annual Cycle ◽  
Winter Season ◽  
Skill Score ◽  
Seasonal Forecast ◽  
Forecast Skill ◽  
Seasonal Forecasts ◽  
Sea Level Pressure ◽  
Weather Regimes ◽  
Start Dates ◽  
Weekly Frequency

AbstractIt is often assumed that weather regimes adequately characterize atmospheric circulation variability. However, regime classifications spanning many months and with a low number of regimes may not satisfy this assumption. The first aim of this study is to test such hypothesis for the Euro-Atlantic region. The second one is to extend the assessment of sub-seasonal forecast skill in predicting the frequencies of occurrence of the regimes beyond the winter season. Two regime classifications of four regimes each were obtained from sea level pressure anomalies clustered from October to March and from April to September respectively. Their spatial patterns were compared with those representing the annual cycle. Results highlight that the two regime classifications are able to reproduce most part of the patterns of the annual cycle, except during the transition weeks between the two periods, when patterns of the annual cycle resembling Atlantic Low regime are not also observed in any of the two classifications. Forecast skill of Atlantic Low was found to be similar to that of NAO+, the regime replacing Atlantic Low in the two classifications. Thus, although clustering yearly circulation data in two periods of 6 months each introduces a few deviations from the annual cycle of the regime patterns, it does not negatively affect sub-seasonal forecast skill. Beyond the winter season and the first ten forecast days, sub-seasonal forecasts of ECMWF are still able to achieve weekly frequency correlations of r = 0.5 for some regimes and start dates, including summer ones. ECMWF forecasts beat climatological forecasts in case of long-lasting regime events, and when measured by the fair continuous ranked probability skill score, but not when measured by the Brier skill score. Thus, more efforts have to be done yet in order to achieve minimum skill necessary to develop forecast products based on weather regimes outside winter season.

scholarly journals Chance or Necessity—The Fungi Co−Occurring with Formica polyctena Ants

Insects ◽  
2021 ◽  
Vol 12 (3) ◽  
pp. 204
Author(s):  
Igor Siedlecki ◽  
Michał Gorczak ◽  
Alicja Okrasińska ◽  
Marta Wrzosek
Keyword(s):  
Molecular Identification ◽  
High Frequency ◽  
Its Rdna ◽  
The Other ◽  
Formica Polyctena ◽  
Ant Nests ◽  
Mutualistic Fungi ◽  
The Tropics ◽  
High Diversity ◽  
Better Than

Studies on carton nesting ants and domatia−dwelling ants have shown that ant–fungi interactions may be much more common and widespread than previously thought. Until now, studies focused predominantly on parasitic and mutualistic fungi–ant interactions occurring mostly in the tropics, neglecting less−obvious interactions involving the fungi common in ants’ surroundings in temperate climates. In our study, we characterized the mycobiota of the surroundings of Formica polyctena ants by identifying nearly 600 fungal colonies that were isolated externally from the bodies of F. polyctena workers. The ants were collected from mounds found in northern and central Poland. Isolated fungi were assigned to 20 genera via molecular identification (ITS rDNA barcoding). Among these, Penicillium strains were the most frequent, belonging to eight different taxonomic sections. Other common and widespread members of Eurotiales, such as Aspergillus spp., were isolated very rarely. In our study, we managed to characterize the genera of fungi commonly present on F. polyctena workers. Our results suggest that Penicillium, Trichoderma, Mucor, Schwanniomyces and Entomortierella are commonly present in F. polyctena surroundings. Additionally, the high diversity and high frequency of Penicillium colonies isolated from ants in this study suggest that representatives of this genus may be adapted to survive in ant nests environment better than the other fungal groups, or that they are preferentially sustained by the insects in nests.

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