Long-Term Variability Pattern of Monthly and Annual Atmospheric Precipitation in the Polish Carpathian Mountains and Their Foreland (1881–2018)

Walanus, Adam; Cebulska, Marta; Twardosz, Robert

doi:10.1007/s00024-021-02663-9

Cited by 13 publications

(10 citation statements)

References 39 publications

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“…The associated uncertainty should be considered, and better correlations of SP can be obtained with regional circulation indices [64]. The occurrence of periodicity in SP over the region should also be a subject of attention [65]. Still, being a developing area with minimal water resources, the proposed changes in SP over the Gaza region will mostly have principal consequences on the hydrological budget.…”

Section: Summary and Discussionmentioning

confidence: 99%

Variation in Seasonal Precipitation over Gaza (Palestine) and Its Sensitivity to Teleconnection Patterns

Ajjur

Al-Ghamdi

2021

Water

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The seasonal precipitation (SP) trend and its sensitivity to teleconnection patterns over the East Mediterranean (EM) region remain inconsistent. Based on rainfall records during 1974–2016 at seven meteorological stations in the Gaza region, this study aims to (1) analyze the observed SP trend over the Gaza region, and (2) examine the SP sensitivity to climate indices. Pearson and Spearman correlations between climate indices and SP in the current and following years were calculated, and the seasonal period (particular month) with the highest correlation was identified. Results show that the climate indices, with greater impact on SP over the Gaza region in the autumn and spring, were in the order; El Niño-Southern Oscillation (ENSO) > East Atlantic/Western Russia (EAWR) > North Atlantic Oscillation (NAO) > Arctic Oscillation (AO). The indices’ impact was minimal in the winter precipitation. ENSO types’ correlations (Southern Oscillation Index-SOI and Niño 3.4) were moderate and significant at α = 0.05. Rainfall at most stations positively correlates with AO and EAWR in spring and autumn. During the study period, warm phases of ENSO (i.e., El Niño) intensified autumn precipitation. Simultaneously with warm phases of EAWR or AO, more influence on autumn precipitation is exerted. Cold phases of ENSO (i.e., La Niña) have an adverse impact compared to El Niño. EAWR co-variation was evident only with the ENSO. Regarding AO, a non-meaningful action was noticed during the neutral phases of ENSO and EAWR. The findings of this study help understand and predict the seasonal trend of precipitation over the Gaza region. This is essential to set up climate change mitigation and adaptation strategies in the EM region.

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Section: Summary and Discussionmentioning

confidence: 99%

Variation in Seasonal Precipitation over Gaza (Palestine) and Its Sensitivity to Teleconnection Patterns

Ajjur

Al-Ghamdi

2021

Water

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“…e macro average accuracy within 12 months is shown in Figure 6. In the previous work on monthly scale variability, the variability of the atmosphere can be reflected by the precipitation [57]. It has been proved that the typical asymmetry precipitation is closely related to the half-year oscillation, and its periodogram shows higher spectral density at the period of 6 months and 12 months.…”

Section: E Lead Time Of Naoi Variation Prediction Using Rf-mentioning

confidence: 97%

The NAO Variability Prediction and Forecasting with Multiple Time Scales Driven by ENSO Using Machine Learning Approaches

Yuan

et al. 2022

Computational Intelligence and Neuroscience

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Machine learning methods have now become an optional technique in Earth science research, and such data-driven solutions have also made tremendous progress in weather forecasting and climate prediction in recent years. Since climate data are typically time series, the neural network layers, which can identify the intrinsic connections between the points of the sequence and features in two-dimensional data, perform particularly well for climate prediction. The North Atlantic Oscillation (NAO) is a prominent atmospherical mode in the northern hemisphere, with the frequency change characteristic of sea level pressure (SLP) in the North Atlantic sector. One of the reasons why NAO prediction is still challenging is that NAO is also proven to be influenced by other climate circulations, the most significant of which is the interaction between El Niño-Southern Oscillation (ENSO) and NAO. Therefore, sea surface temperature (SST) in the Pacific Ocean used to characterize ENSO is also one of the factors that contribute to the evolution of NAO and can be used as an input factor to predict the NAO. In this paper, the seasonal lag correlation between ENSO and NAO is explored and analyzed. The interaction has been considered in both short-term forecasting and midterm prediction of the NAO variability. The monthly NAO index (NAOI) fluctuation is predicted using the Niño indices based on the RF-Var model, and the accuracy achieves 68% when the lead time is about three months. In addition, integrating multiple physical variables directly related to the NAO and Pacific SST, the short-term NAO forecasting is conducted using a multi-channel neural network named AccNet with trajectory gated recursive unit (TrajGRU) layer. AccNet has the ability to identify the mechanism of the high-frequency variation in several days, and the NAO variability is indicated by SLP. The loss function of AccNet is set to anomaly correlation coefficient (ACC), which is the indicator that verifies spatial correlation in geoscience. Forecasting extreme events of NAO between 2010 and 2021, AccNet presents higher flexibility compared against other structures that can capture spatial-temporal features.

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“…IPCC cũng đánh giá rằng, mưa tại nhiều khu vực trên thế giới đang có xu hướng tăng, thời đoạn và chu kỳ lặp lại của các sự kiện mưa cực đại cũng được nhận định đang gia tăng dưới tác động của BĐKH và điều này sẽ ảnh hưởng đáng kể đến đời sống kinh tế-xã hội toàn cầu [2][3]. So với các yếu tố khí hậu khác, mưa được đánh giá là yếu tố quan trọng có ảnh hưởng trực tiếp đến nhiều mặt của đời sống nhân loại [2,[4][5]. Dưới ảnh hưởng của BĐKH, chu kỳ lặp lại và cường độ của các sự kiện mưa lớn, mưa cực đoan hay mưa trong bão xảy ra ở Việt Nam được nhận định có xu hướng gia tăng và tiềm ẩn các rủi ro cho đời sống nhân dân, gây nhiều tổn thất về cơ sở hạ tầng và tính mạng con người, tác động xấu đến môi trường [2,[6][7].…”

Section: Mở đầUunclassified

Xây dựng đường cong cường độ–thời đoạn–tần suất mưa hướng đến thiết lập bản đồ ngập lụt cho khu vực bán đảo Cà Mau

Toàn¹,

An²

2021

VNJHM

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In recent years, heavy rainfall events have appeared frequently in the Ca Mau peninsula area, causing local flooding and affecting many aspects of life in the area. According to a report of the Ministry of Natural Resources and Environment, rainfall is an increase tend in intensity and frequency in the Ca Mau Peninsula as a part of climate variability. Heavy rainfall tends increase, which will cause the local flooding events in which has low terrain and less severe drainage systems. It is, thus, necessary to proactively prevent adverse effects from flooding events on people's lives. Therefore, the goal of the study is a) to simulate rainfall intensity-duration-frequency (IDF) curve of the extreme rainfall events using the CumFreq software for the Ca Mau Peninsula and b) toward to establish inundation maps based on the simulated data from rainfall IDF curve, contributing to proactively minimize the potential risks of flooding as well as proactively adapt the impacts of climate variability.

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Long-Term Variability Pattern of Monthly and Annual Atmospheric Precipitation in the Polish Carpathian Mountains and Their Foreland (1881–2018)

Cited by 13 publications

References 39 publications

Variation in Seasonal Precipitation over Gaza (Palestine) and Its Sensitivity to Teleconnection Patterns

Variation in Seasonal Precipitation over Gaza (Palestine) and Its Sensitivity to Teleconnection Patterns

The NAO Variability Prediction and Forecasting with Multiple Time Scales Driven by ENSO Using Machine Learning Approaches

Xây dựng đường cong cường độ–thời đoạn–tần suất mưa hướng đến thiết lập bản đồ ngập lụt cho khu vực bán đảo Cà Mau

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