scholarly journals Identifying and interpreting extreme rainfall events using image classification

2021 ◽  
Author(s):  
Andrew Paul Barnes ◽  
Nick McCullen ◽  
Thomas Rodding Kjeldsen
Keyword(s):  
Sensitivity Analysis ◽  
Sea Level ◽  
North Atlantic ◽  
Extreme Rainfall ◽  
Sea Level Pressure ◽  
Extreme Rainfall Events ◽  
Rainfall Events ◽  
North West ◽  
Level Pressure ◽  
The North

Abstract This study presents the first attempt to identify extreme rainfall events based on surrounding sea-level pressure anomalies, using neural network-based classification. Sensitivity analysis was also performed to identify the spatial importance of sea-level pressure anomalies. Three classification models were generated: the first classifies the patterns between extreme and regular rainfall events in the North West of England, the second classifies the patterns between extreme and regular rainfall events in the South East of England, and the third classifies between the patterns of extreme events in the North West and South East of England. All classifiers obtain accuracies between 60 and 65%, with precision and recall metrics showing that extreme events are easier to identify than regular events. Finally, a sensitivity analysis is performed to identify the spatial importance of the patterns across the North Atlantic, highlighting that for all three classifiers the local anomaly sea-level pressure patterns around the British Isles are key to determining the difference between extreme and regular rainfall events. In contrast, the pattern across the mid and western North Atlantic shows no contribution to the overall classifications.

scholarly journals Decadal Shift of NAO-Linked Interannual Sea Level Variability along the U.S. Northeast Coast

2018 ◽  
Vol 31 (13) ◽  
pp. 4981-4989 ◽  
Author(s):  
Jessica S. Kenigson ◽  
Weiqing Han ◽  
Balaji Rajagopalan ◽  
Yanto ◽  
Mike Jasinski
Keyword(s):  
Sea Level ◽  
North Atlantic ◽  
Sea Level Pressure ◽  
Level Pressure ◽  
The North ◽  
Decadal Shift ◽  
Nao Index ◽  
The North Atlantic ◽  
The U.S ◽  
Northeast Coast

Recent studies have linked interannual sea level variability and extreme events along the U.S. northeast coast (NEC) to the North Atlantic Oscillation (NAO), a natural internal climate mode that prevails in the North Atlantic Ocean. The correlation between the NAO index and coastal sea level north of Cape Hatteras was weak from the 1960s to the mid-1980s, but it has markedly increased since around 1987. The causes for the decadal shift remain unknown. Yet understanding the abrupt change is vital for decadal sea level prediction and is essential for risk management. Here we use a robust method, the Bayesian dynamic linear model (DLM), to explore the nonstationary NAO impact on NEC sea level. The results show that a spatial pattern change of NAO-related winds near the NEC is a major cause of the NAO–sea level relationship shift. A new index using regional sea level pressure is developed that is a significantly better predictor of NEC sea level than is the NAO and is strongly linked to the intensity of westerly winds near the NEC. These results point to the vital importance of monitoring regional changes of wind and sea level pressure patterns, rather than the NAO index alone, to achieve more accurate predictions of sea level change along the NEC.

scholarly journals Bayesian Regularized Neural Network Model Development for Predicting Daily Rainfall from Sea Level Pressure Data: Investigation on Solving Complex Hydrology Problem

Complexity ◽  
2021 ◽  
Vol 2021 ◽  
pp. 1-14
Author(s):  
Lu Ye ◽  
Saadya Fahad Jabbar ◽  
Musaddak M. Abdul Zahra ◽  
Mou Leong Tan
Keyword(s):  
Sea Level ◽  
Daily Rainfall ◽  
Peninsular Malaysia ◽  
Gradient Boosting ◽  
Sea Level Pressure ◽  
Extreme Rainfall Events ◽  
Inference System ◽  
Rainfall Events ◽  
Level Pressure ◽  
Extreme Gradient Boosting

Prediction of daily rainfall is important for flood forecasting, reservoir operation, and many other hydrological applications. The artificial intelligence (AI) algorithm is generally used for stochastic forecasting rainfall which is not capable to simulate unseen extreme rainfall events which become common due to climate change. A new model is developed in this study for prediction of daily rainfall for different lead times based on sea level pressure (SLP) which is physically related to rainfall on land and thus able to predict unseen rainfall events. Daily rainfall of east coast of Peninsular Malaysia (PM) was predicted using SLP data over the climate domain. Five advanced AI algorithms such as extreme learning machine (ELM), Bayesian regularized neural networks (BRNNs), Bayesian additive regression trees (BART), extreme gradient boosting (xgBoost), and hybrid neural fuzzy inference system (HNFIS) were used considering the complex relationship of rainfall with sea level pressure. Principle components of SLP domain correlated with daily rainfall were used as predictors. The results revealed that the efficacy of AI models is predicting daily rainfall one day before. The relative performance of the models revealed the higher performance of BRNN with normalized root mean square error (NRMSE) of 0.678 compared with HNFIS (NRMSE = 0.708), BART (NRMSE = 0.784), xgBoost (NRMSE = 0.803), and ELM (NRMSE = 0.915). Visual inspection of predicted rainfall during model validation using density-scatter plot and other novel ways of visual comparison revealed the ability of BRNN to predict daily rainfall one day before reliably.

scholarly journals Impact of the Stratosphere on the Winter Tropospheric Teleconnections between ENSO and the North Atlantic and European Region

2009 ◽  
Vol 22 (5) ◽  
pp. 1223-1238 ◽  
Author(s):  
Chiara Cagnazzo ◽  
Elisa Manzini
Keyword(s):  
Sea Level ◽  
Central Europe ◽  
North Atlantic ◽  
The Arctic ◽  
Stratospheric Warming ◽  
Sudden Stratospheric Warming ◽  
Sea Level Pressure ◽  
Level Pressure ◽  
The North ◽  
The North Atlantic

Abstract The possible role of stratospheric variability on the tropospheric teleconnection between El Niño–Southern Oscillation (ENSO) and the North Atlantic and European (NAE) region is addressed by comparing results from two ensembles of simulations performed with an atmosphere general circulation model fully resolving the stratosphere (with the top at 0.01 hPa) and its low-top version (with the top at 10 hPa). Both ensembles of simulations consist of nine members, covering the 1980–99 period and are forced with prescribed observed sea surface temperatures. It is found that both models capture the sensitivity of the averaged polar winter lower stratosphere to ENSO in the Northern Hemisphere, although with a reduced amplitude for the low-top model. In late winter and spring, the ENSO response at the surface is instead different in the two models. A large-scale coherent pattern in sea level pressure, with high pressures over the Arctic and low pressures over western and central Europe and the North Pacific, is found in the February–March mean of the high-top model. In the low-top model, the Arctic high pressure and the western and central Europe low pressure are very much reduced. The high-top minus low-top model difference in the ENSO temperature and precipitation anomalies is that North Europe is colder and the Northern Atlantic storm track is shifted southward in the high-top model. In addition, it has been found that major sudden stratospheric warming events are virtually lacking in the low-top model, while their frequency of occurrence is broadly realistic in the high-top model. Given that this is a major difference in the dynamical behavior of the stratosphere of the two models and that these events are favored by ENSO, it is concluded that the occurrence of sudden stratospheric warming events affects the reported differences in the tropospheric ENSO–NAE teleconnection. Given that the essence of the high-top minus low-top model difference is a more annular (or zonal) pattern of the anomaly in sea level pressure, relatively larger over the Arctic and the NAE regions, this interpretation is consistent with the observational evidence that sudden stratospheric warmings play a role in giving rise to persistent Arctic Oscillation anomalies at the surface.

scholarly journals Changes in atmospheric variability in a glacial climate and the impacts on proxy data: a model intercomparison

2009 ◽  
Vol 5 (3) ◽  
pp. 489-502 ◽  
Author(s):  
F. S. R. Pausata ◽  
C. Li ◽  
J. J. Wettstein ◽  
K. H. Nisancioglu ◽  
D. S. Battisti
Keyword(s):  
Sea Level ◽  
North Atlantic ◽  
Climate Models ◽  
Atmospheric Variability ◽  
Sea Level Pressure ◽  
Level Pressure ◽  
The North ◽  
Surface Climate ◽  
Leading Mode ◽  
The North Atlantic Oscillation

Abstract. Using four different climate models, we investigate sea level pressure variability in the extratropical North Atlantic in the preindustrial climate (1750 AD) and at the Last Glacial Maximum (LGM, 21 kyrs before present) in order to understand how changes in atmospheric circulation can affect signals recorded in climate proxies. In general, the models exhibit a significant reduction in interannual variance of sea level pressure at the LGM compared to pre-industrial simulations and this reduction is concentrated in winter. For the preindustrial climate, all models feature a similar leading mode of sea level pressure variability that resembles the leading mode of variability in the instrumental record: the North Atlantic Oscillation (NAO). In contrast, the leading mode of sea level pressure variability at the LGM is model dependent, but in each model different from that in the preindustrial climate. In each model, the leading (NAO-like) mode of variability explains a smaller fraction of the variance and also less absolute variance at the LGM than in the preindustrial climate. The models show that the relationship between atmospheric variability and surface climate (temperature and precipitation) variability change in different climates. Results are model-specific, but indicate that proxy signals at the LGM may be misinterpreted if changes in the spatial pattern and seasonality of surface climate variability are not taken into account.

scholarly journals The role of atmospheric rivers in compound events consisting of heavy precipitation and high storm surges along the Dutch coast

2018 ◽  
Vol 18 (12) ◽  
pp. 3311-3326 ◽  
Author(s):  
Nina Ridder ◽  
Hylke de Vries ◽  
Sybren Drijfhout
Keyword(s):  
The Netherlands ◽  
Sea Level ◽  
North Atlantic ◽  
Heavy Precipitation ◽  
Water Levels ◽  
Sea Level Pressure ◽  
Level Pressure ◽  
The North ◽  
Compound Events ◽  
The North Atlantic

Abstract. Atmospheric river (AR) systems play a significant role in the simultaneous occurrence of high coastal water levels and heavy precipitation in the Netherlands. Based on observed precipitation values (E-OBS) and the output of a numerical storm surge model (WAQUA/DSCMv5) forced with ERA-Interim sea level pressure and wind fields, we find that the majority of compound events (CEs) between 1979 and 2015 have been accompanied by the presence of an AR over the Netherlands. In detail, we show that CEs have a 3 to 4 times higher chance of occurrence on days with an AR over the Netherlands compared to any random day (i.e. days without knowledge on presence of an AR). In contrast, the occurrence of a CE on a day without AR is 3 times less likely than on any random day. Additionally, by isolating and assessing the prevailing sea level pressure (SLP) and sea surface temperature (SST) conditions with and without AR involvement up to 7 days before the events, we show that the presence of ARs constitutes a specific type of forcing conditions that (i) resemble the SLP anomaly patterns during the positive phase of the North Atlantic Oscillation (NAO+) with a north–south pressure dipole over the North Atlantic and (ii) cause a cooling of the North Atlantic subpolar gyre and eastern boundary upwelling zone while warming the western boundary of the North Atlantic. These conditions are clearly distinguishable from those during compound events without the influence of an AR which occur under SLP conditions resembling the East Atlantic (EA) pattern with a west–east pressure dipole over northern Europe and are accompanied by a cooling of the West Atlantic. Thus, this study shows that ARs are a useful tool for the early identification of possible harmful meteorological conditions over the Netherlands and supports an effort for the establishment of an early warning system.

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