Seasonal prediction of the Leeuwin Current using the POAMA dynamical seasonal forecast model

2009 ◽  
Vol 34 (7-8) ◽  
pp. 1129-1137 ◽  
Author(s):  
Harry H. Hendon ◽  
Guomin Wang
Keyword(s):  
Forecast Model ◽  
Seasonal Prediction ◽  
Seasonal Forecast ◽  
Leeuwin Current

scholarly journals Brief communication: Seasonal prediction of salinity intrusion in the Mekong Delta

2019 ◽  
Author(s):  
Heiko Apel ◽  
Mai Khiem ◽  
Nguyen Hong Quan ◽  
To Quang Toan
Keyword(s):  
Agricultural Production ◽  
Mekong Delta ◽  
Forecast Model ◽  
Seasonal Prediction ◽  
Seasonal Forecast ◽  
Salinity Intrusion ◽  
Negative Effects ◽  
Local Livelihoods ◽  
Production Area ◽  
High Skill

Abstract. The Mekong Delta is the most important food production area in Vietnam. Salinity intrusion during the dry season poses a serious threat to agricultural production and local livelihoods. A seasonal forecast of salinity intrusion is required in order to mitigate the negative effects. This communication present a simple statistical seasonal forecast model able to predict the salinity intrusion up to 9 months ahead with high skill. The model can thus be used as a basis for timely adaptation and mitigation planning, which is urgently needed for the imminent severe salinity intrusion expected in spring 2020.

scholarly journals Brief communication: Seasonal prediction of salinity intrusion in the Mekong Delta

2020 ◽  
Vol 20 (6) ◽  
pp. 1609-1616
Author(s):  
Heiko Apel ◽  
Mai Khiem ◽  
Nguyen Hong Quan ◽  
To Quang Toan
Keyword(s):  
Agricultural Production ◽  
Food Production ◽  
Operating Characteristic ◽  
Mekong Delta ◽  
Forecast Model ◽  
Seasonal Prediction ◽  
Seasonal Forecast ◽  
Salinity Intrusion ◽  
Negative Effects ◽  
Production Area

Abstract. The Mekong Delta is the most important food production area in Vietnam, but salinity intrusion during the dry season poses a serious threat to agricultural production and livelihoods. A seasonal forecast of salinity intrusion is required in order to mitigate the negative effects. This communication presents a statistical seasonal forecast model based on logistic regression using either the ENSO34 index or streamflow as a predictor. The model is able to reliably predict the salinity intrusion up to 9 months ahead (receiver operating characteristic (ROC) scores: >0.8). The model can thus be used operationally as a basis for timely adaptation and mitigation planning.

Development of a seasonal forecast model for Kuwait winter precipitation

2001 ◽  
Vol 48 (2) ◽  
pp. 233-242 ◽  
Author(s):  
H.A. Nasrallah ◽  
R.C. Balling ◽  
N.J. Selover ◽  
R.S. Vose
Keyword(s):  
Forecast Model ◽  
Winter Precipitation ◽  
Seasonal Forecast

scholarly journals Dynamical mechanisms linking Indian monsoon precipitation and the circumglobal teleconnection

2021 ◽  
Author(s):  
Jonathan D. Beverley ◽  
Steven J. Woolnough ◽  
Laura H. Baker ◽  
Stephanie J. Johnson ◽  
Antje Weisheimer ◽  
...  
Keyword(s):  
North America ◽  
Northern Hemisphere ◽  
Rossby Waves ◽  
Wave Train ◽  
Forecast Model ◽  
Seasonal Forecast ◽  
The North ◽  
Circumglobal Teleconnection ◽  
Rossby Wave Train ◽  
Ecmwf Model

AbstractThe circumglobal teleconnection (CGT) is an important mode of circulation variability, with an influence across many parts of the northern hemisphere. Here, we examine the excitation mechanisms of the CGT in the ECMWF seasonal forecast model, and the relationship between the Indian summer monsoon (ISM), the CGT and the extratropical northern hemisphere circulation. Results from relaxation experiments, in which the model is corrected to reanalysis in specific regions, suggest that errors over northwest Europe are more important in inhibiting the model skill at representing the CGT, in addition to northern hemisphere skill more widely, than west-central Asia and the ISM region, although the link between ISM precipitation and the extratropical circulation is weak in all experiments. Thermal forcing experiments in the ECMWF model, in which a heating is applied over India, suggest that the ISM does force an extratropical Rossby wave train, with upper tropospheric anticyclonic anomalies over east Asia, the North Pacific and North America associated with increased ISM heating. However, this eastward-propagating branch of the wave train does not project into Europe, and the response there occurs largely through westward-propagating Rossby waves. Results from barotropic model experiments show a response that is highly consistent with the seasonal forecast model, with similar eastward- and westward-propagating Rossby waves. This westward-propagating response is shown to be important in the downstream reinforcement of the wave train between Asia and North America.

Seasonal-to-Decadal Predictability and Prediction of North American Climate—The Atlantic Influence

2006 ◽  
Vol 19 (23) ◽  
pp. 6005-6024 ◽  
Author(s):  
H. M. Van den Dool ◽  
Peitao Peng ◽  
Åke Johansson ◽  
Muthuvel Chelliah ◽  
Amir Shabbar ◽  
...  
Keyword(s):  
North American ◽  
Seasonal Prediction ◽  
Atmospheric Model ◽  
The United States ◽  
Seasonal Forecast ◽  
Ocean Model ◽  
Prediction Skill ◽  
Basic Material ◽  
Atlantic Sector ◽  
The Impact

Abstract The question of the impact of the Atlantic on North American (NA) seasonal prediction skill and predictability is examined. Basic material is collected from the literature, a review of seasonal forecast procedures in Canada and the United States, and some fresh calculations using the NCEP–NCAR reanalysis data. The general impression is one of low predictability (due to the Atlantic) for seasonal mean surface temperature and precipitation over NA. Predictability may be slightly better in the Caribbean and the (sub)tropical Americas, even for precipitation. The NAO is widely seen as an agent making the Atlantic influence felt in NA. While the NAO is well established in most months, its prediction skill is limited. Year-round evidence for an equatorially displaced version of the NAO (named ED_NAO) carrying a good fraction of the variance is also found. In general the predictability from the Pacific is thought to dominate over that from the Atlantic sector, which explains the minimal number of reported Atmospheric Model Intercomparison Project (AMIP) runs that explore Atlantic-only impacts. Caveats are noted as to the question of the influence of a single predictor in a nonlinear environment with many predictors. Skill of a new one-tier global coupled atmosphere–ocean model system at NCEP is reviewed; limited skill is found in midlatitudes and there is modest predictability to look forward to. There are several signs of enthusiasm in the community about using “trends” (low-frequency variations): (a) seasonal forecast tools include persistence of last 10 years’ averaged anomaly (relative to the official 30-yr climatology), (b) hurricane forecasts are based largely on recognizing a global multidecadal mode (which is similar to an Atlantic trend mode in SST), and (c) two recent papers, one empirical and one modeling, giving equal roles to the (North) Pacific and Atlantic in “explaining” variations in drought frequency over NA on a 20 yr or longer time scale during the twentieth century.

scholarly journals The Predictability of Soil Moisture and Near-Surface Temperature in Hindcasts of the NCEP Seasonal Forecast Model

2003 ◽  
Vol 16 (3) ◽  
pp. 510-521 ◽  
Author(s):  
Masao Kanamitsu ◽  
Cheng-Hsuan Lu ◽  
Jae Schemm ◽  
Wesley Ebisuzaki
Keyword(s):  
Soil Moisture ◽  
Surface Temperature ◽  
Forecast Model ◽  
Seasonal Forecast ◽  
Near Surface

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>

Assessing reasons for skilful predictions of winter windstorms over the Atlantic/European region

2020 ◽  
Author(s):  
Lisa Degenhardt ◽  
Gregor Leckebusch ◽  
Adam Scaife
Keyword(s):  
Large Scale ◽  
Surface Wind ◽  
Forecast Model ◽  
Surface Wind Speed ◽  
Seasonal Forecast ◽  
Forecast Skill ◽  
Seasonal Forecasts ◽  
Financial Industry ◽  
Near Surface ◽  
Skill Scores

<p>Severe Atlantic winter storms are affecting densely populated regions of Europe (e.g. UK, France, Germany, etc.). Consequently, different parts of the society, financial industry (e.g., insurance) and last but not least the general public are interested in skilful forecasts for the upcoming storm season (usually December to March). To allow for a best possible use of steadily improved seasonal forecasts, the understanding which factors contribute to realise forecast skill is essential and will allow for an assessment whether to expect a forecast to be skilful or not.</p><p>This study analyses the predictability of the seasonal forecast model of the UK MetOffice, the GloSea5. Windstorm events are identified and tracked following Leckebusch et al. (2008) via the exceedance of the 98<sup>th</sup> percentile of the near surface wind speed.</p><p>Seasonal predictability of windstorm frequency in comparison to observations (based e.g., on ERA5 reanalysis) are calculated and different statistical methods (skill scores) are compared.</p><p>Large scale patterns (e.g., NAO, AO, EAWR, etc.) and dynamical factors (e.g., Eady Growth Rate) are analysed and their predictability is assessed in comparison to storm frequency forecast skill. This will lead to an idea how the forecast skill of windstorms is depending on the forecast skill of forcing factors conditional to the phase of large-scale variability modes. Thus, we deduce information, which factors are most important to generate seasonal forecast skill for severe extra-tropical windstorms.</p><p>The results can be used to get a better understanding of the resulting skill for the upcoming windstorm season.</p>

scholarly journals Duration and decay of Arctic stratospheric vortex events in the ECMWF seasonal forecast model

2018 ◽  
Vol 144 (717) ◽  
pp. 2876-2888 ◽  
Author(s):  
Yvan J. Orsolini ◽  
Kazuaki Nishii ◽  
Hisashi Nakamura
Keyword(s):  
Forecast Model ◽  
Seasonal Forecast

Skill assessment of a seasonal forecast model to predict drought events for water resource systems

2018 ◽  
Vol 564 ◽  
pp. 574-587 ◽  
Author(s):  
Jaime Madrigal ◽  
Abel Solera ◽  
Sara Suárez-Almiñana ◽  
Javier Paredes-Arquiola ◽  
Joaquín Andreu ◽  
...  
Keyword(s):  
Water Resource ◽  
Forecast Model ◽  
Seasonal Forecast ◽  
Skill Assessment ◽  
Resource Systems
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