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.

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 The Strong Precipitation of the Dry Warm Front Cyclone in Syria and Its Prediction by Data Mining Modeling

Atmosphere ◽  
2021 ◽  
Vol 12 (12) ◽  
pp. 1667
Author(s):  
Jianhong Wang ◽  
Nour Alakol ◽  
Xing Wang ◽  
Dongpo He ◽  
Kanike Raghavendra Kumar ◽  
...  
Keyword(s):  
Mediterranean Climate ◽  
Forecast Accuracy ◽  
Middle Layer ◽  
Forecast Model ◽  
Winter Precipitation ◽  
Reanalysis Data ◽  
The North ◽  
Warm Front ◽  
The Mediterranean ◽  
Upper Level

The Eastern inland of Syria has a Mediterranean climate in the north and a tropical desert climate in the south, which results in a dry south and wet north climate feature, especially in winter. The circulation dynamics analysis of 16 winter strong precipitation events shows that the key system is the dry and warm front cyclone. In most cases (81–100% of the 16 cases), the moisture content in the northern part of the cyclone is higher than that in the southern part (influenced by the Mediterranean climate zone). The humidity in the middle layer is higher than that near the surface (uplifting of the dry warm front), and the thickness of the wet layer and the vertical ascending layer obviously expands upward (as shown by the satellite cloud top reflection). These characteristics lead to the moisture thermodynamic instability in the eastern part of the cyclone (dry and warm air at low level and wet and cold air at upper level). The cyclone flow transports momentum to the local humid layer of the Mediterranean climate belt and then causes unstable conditions and strong rainfall. Considering the limitations of the Syrian ground station network, the NCEP/CFSR global reanalysis data and MODIS aqua-3 cloud parameter data are used to build a multi-source factor index of winter precipitation from 2002 to 2016. A decision tree prediction model is then established and the factors index is constructed into tree shapes by the nodes and branches through calculating rules of information entropy. The suitable tree shape models are adjusted and selected by an automated training and testing process. The forecast model can classify rainfall with a forecast accuracy of more than 90% for strong rainfall over 30 mm.

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

scholarly journals Effect of Realistic Soil Moisture Initialization on the Canadian CanCM3 Seasonal Forecast Model

2012 ◽  
Vol 50 (4) ◽  
pp. 466-474 ◽  
Author(s):  
Gordon Drewitt ◽  
Aaron A. Berg ◽  
William J. Merryfield ◽  
Woo-Sung Lee
Keyword(s):  
Soil Moisture ◽  
Forecast Model ◽  
Seasonal Forecast ◽  
Soil Moisture Initialization

scholarly journals Cluster Analysis of the Seasonal Forecast Skill of the NCEP SFM over the Pacific–North America Sector

2006 ◽  
Vol 19 (1) ◽  
pp. 123-138 ◽  
Author(s):  
Tosiyuki Nakaegawa ◽  
Masao Kanamitsu
Keyword(s):  
Cluster Analysis ◽  
North America ◽  
Winter Season ◽  
Correlation Coefficients ◽  
Forecast Model ◽  
Seasonal Forecast ◽  
The Pacific ◽  
Skill Scores ◽  
Multiple Regimes ◽  
Ensemble Mean

Abstract Cluster analysis was used to study seasonal forecast skills of the winter season NCEP seasonal forecast model (SFM) hindcasts over the Pacific–North America (PNA) sector. Two skill scores based on cluster mean and ensemble mean are compared. It was shown that the anomaly correlation coefficients (ACCs) of cluster mean are generally higher than those of the simple ensemble mean. The results indicated that the skill was affected by the existence of multiple atmospheric regimes. Multiple regimes tend to appear more often in near-normal tropical Pacific sea surface temperature (SST) episodes, while a single regime tends to appear during warm/cold episodes. The dissimilarity among the cluster members is small and the number of the dominant cluster members is also small when the tropical SST anomaly is large, suggesting that the external forcing reduces the frequency of occurrence of the multiple regimes. The ACC improvements from the ensemble mean ACCs to the cluster mean ACCs are statistically significant. Thus, the cluster mean can be used as a supplementary tool for seasonal forecasting.

scholarly journals The use of regression for assessing a seasonal forecast model experiment

2016 ◽  
Author(s):  
Rasmus E. Benestad ◽  
Retish Senan ◽  
Yvan Orsolini
Keyword(s):  
Sea Ice ◽  
Forecast Model ◽  
Seasonal Forecast ◽  
Ocean Model ◽  
Seasonal Forecasts ◽  
Model Set ◽  
Set Up ◽  
Numerical Model Experiments ◽  
The Tropics

Abstract. We demonstrate how factorial regression can be used to analyse numerical model experiments, testing the effect of different model settings. We analysed results from a coupled atmosphere-ocean model to explore how the different choices in the experimental set-up influence the seasonal predictions. These choices included a representation of the sea-ice and the choice of top of the atmosphere, and the results suggested that the simulated monthly mean temperatures poleward of the mid-latitudes are highly sensitivity to the specification of the top of the atmosphere, interpreted as the presence or absence of a stratosphere. The seasonal forecasts for the mid-to-high latitudes were also sensitive to whether the model set-up included a dynamic or non-dynamics sea-ice representation, although this effect was less important than the role of the stratosphere. The temperature in the tropics was insensitive to these choices.

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