scholarly journals ARIMAX model for rainfall forecasting in Pangkalpinang, Indonesia

2021 ◽  
Vol 926 (1) ◽  
pp. 012034
Author(s):  
R Amelia ◽  
D Y Dalimunthe ◽  
E Kustiawan ◽  
I Sulistiana
Keyword(s):  
Wind Speed ◽  
Arima Model ◽  
Daily Rainfall ◽  
Monthly Rainfall ◽  
Rainfall Data ◽  
Maximum Wind Speed ◽  
Series Data ◽  
Rainfall Forecasting ◽  
Maximum Wind ◽  
Maximum Daily Rainfall

Abstract In recent years, the weather and climate are unpredictable and the most visible is the rotation of the rainy season and the dry season. The extreme changes in rainfall can cause disasters and losses for the community. For that we need to predict the rainfall to anticipate the worst events. Rainfall is included in the periodic series data, so the forecasting method that can be used is the ARIMAX model which is ARIMA model expanded by adding the exogen variable. The aim of this research is to predict the rainfall data in Pangkalpinang City, Indonesia. The best model for each rainfall is ARIMAX (0,1,3) for monthly rainfall data and ARIMAX (0,1,2) for maximum daily rainfall. This research shows that there is an influence maximum wind speed variable to monthly rainfall and maximum daily rainfall in the Pangkalpinang City. Nevertheless, when viewed from the ARIMA and ARIMAX models based on the obtained AIC value, the ARIMAX value is still better than ARIMA. However, the prediction value using ARIMAX needs to increase again to take into account seasonal data rainfall. Then, possible to add other exogeneous factors besides maximum wind speed.

A COMPREHENSIVE STUDY ON RADIUS TO TYPHOON-GENERATED MAXIMUM WIND SPEED BASED ON DATA ANALYSES

2020 ◽  
Vol 76 (2) ◽  
pp. I_223-I_228
Author(s):  
Masataka YAMAGUCHI ◽  
Kunimitsu INOUCHI ◽  
Yoshihiro UTSUNOMIYA ◽  
Hirokazu NONAKA ◽  
Yoshio HATADA ◽  
...  
Keyword(s):  
Wind Speed ◽  
Maximum Wind Speed ◽  
Maximum Wind ◽  
Data Analyses ◽  
Comprehensive Study

EFFECTS OF MAXIMUM WIND SPEED RADIUS AND TRANSLATION SPEED OF SCENARIO TYPHOON ON STORM SURGE AND WAVE

2018 ◽  
Vol 74 (2) ◽  
pp. I_583-I_588
Author(s):  
Masafumi KIMIZUKA ◽  
Tomotsuka TAKAYAMA ◽  
Hiroyasu KAWAI ◽  
Masafumi MIYATA ◽  
Katsuya HIRAYAMA ◽  
...  
Keyword(s):  
Wind Speed ◽  
Storm Surge ◽  
Maximum Wind Speed ◽  
Translation Speed ◽  
Maximum Wind

scholarly journals Uncertainty Propagation in Coupled Atmosphere–Wave–Ocean Prediction System: A Study of Hurricane Earl (2010)

2019 ◽  
Vol 147 (1) ◽  
pp. 221-245 ◽  
Author(s):  
Guotu Li ◽  
Milan Curcic ◽  
Mohamed Iskandarani ◽  
Shuyi S. Chen ◽  
Omar M. Knio
Keyword(s):  
Wind Speed ◽  
Initial Conditions ◽  
Uncertainty Propagation ◽  
Storm Track ◽  
Coupled Model ◽  
Surrogate Models ◽  
Maximum Wind Speed ◽  
Track Forecast ◽  
Initial Strength ◽  
Maximum Wind

This study focuses on understanding the evolution of Hurricane Earl (2010) with respect to random perturbations in the storm’s initial strength, size, and asymmetry in wind distribution. We rely on the Unified Wave Interface-Coupled Model (UWIN-CM), a fully coupled atmosphere–wave–ocean system to generate a storm realization ensemble, and use polynomial chaos (PC) expansions to build surrogate models for time evolution of both the maximum wind speed and minimum sea level pressure in Earl. The resulting PC surrogate models provide statistical insights on probability distributions of model responses throughout the simulation time span. Statistical analysis of rapid intensification (RI) suggests that initial perturbations having intensified and counterclockwise-rotated winds are more likely to undergo RI. In addition, for the range of initial conditions considered RI seems mostly sensitive to azimuthally averaged maximum wind speed and asymmetry orientation, rather than storm size and asymmetry magnitude; this is consistent with global sensitivity analysis of PC surrogate models. Finally, we combine initial condition perturbations with a stochastic kinetic energy backscatter scheme (SKEBS) forcing in the UWIN-CM simulations and conclude that the storm tracks are substantially influenced by the SKEBS forcing perturbations, whereas the perturbations in initial conditions alone had only limited impact on the storm-track forecast.

scholarly journals Joint Modeling of Severe Dust Storm Events in Arid and Hyper Arid Regions Based on Copula Theory: A Case Study in the Yazd Province, Iran

Climate ◽  
2020 ◽  
Vol 8 (5) ◽  
pp. 64 ◽  
Author(s):  
Tayyebeh Mesbahzadeh ◽  
Maryam Mirakbari ◽  
Mohsen Mohseni Saravi ◽  
Farshad Soleimani Sardoo ◽  
Nir Y. Krakauer
Keyword(s):  
Wind Speed ◽  
Natural Disasters ◽  
Return Period ◽  
Vertical Velocity ◽  
Geopotential Height ◽  
Dust Storms ◽  
Maximum Wind Speed ◽  
Near Surface ◽  
Copula Theory ◽  
Maximum Wind

Natural disasters such as dust storms are random phenomena created by complicated mechanisms involving many parameters. In this study, we used copula theory for bivariate modeling of dust storms. Copula theory is a suitable method for multivariate modeling of natural disasters. We identified 40 severe dust storms, as defined by the World Meteorological Organization, during 1982–2017 in Yazd province, central Iran. We used parameters at two spatial vertical levels (near-surface and upper atmosphere) that included surface maximum wind speed, and geopotential height and vertical velocity at 500, 850, and 1000 hPa. We compared two bivariate models based on the pairs of maximum wind speed–geopotential height and maximum wind speed–vertical velocity. We determined the bivariate return period using Student t and Gaussian copulas, which were considered as the most suitable functions for these variables. The results obtained for maximum wind speed–geopotential height indicated that the maximum return period was consistent with the observed frequency of severe dust storms. The bivariate modeling of dust storms based on maximum wind speed and geopotential height better described the conditions of severe dust storms than modeling based on maximum wind speed and vertical velocity. The finding of this study can be useful to improve risk management and mitigate the impacts of severe dust storms.

scholarly journals Studying monthly rainfall over Dibrugarh, Assam: Use of SARIMA approach

MAUSAM ◽  
2021 ◽  
Vol 68 (2) ◽  
pp. 349-356
Author(s):  
J. HAZARIKA ◽  
B. PATHAK ◽  
A. N. PATOWARY
Keyword(s):  
Time Series ◽  
Time Series Data ◽  
Moving Average ◽  
Demand Management ◽  
Arima Model ◽  
Monthly Rainfall ◽  
Series Data ◽  
Data Set ◽  
Modeling And Forecasting ◽  
Moving Average Model

Perceptive the rainfall pattern is tough for the solution of several regional environmental issues of water resources management, with implications for agriculture, climate change, and natural calamity such as floods and droughts. Statistical computing, modeling and forecasting data are key instruments for studying these patterns. The study of time series analysis and forecasting has become a major tool in different applications in hydrology and environmental fields. Among the most effective approaches for analyzing time series data is the ARIMA (Autoregressive Integrated Moving Average) model introduced by Box and Jenkins. In this study, an attempt has been made to use Box-Jenkins methodology to build ARIMA model for monthly rainfall data taken from Dibrugarh for the period of 1980- 2014 with a total of 420 points.  We investigated and found that ARIMA (0, 0, 0) (0, 1, 1)12 model is suitable for the given data set. As such this model can be used to forecast the pattern of monthly rainfall for the upcoming years, which can help the decision makers to establish priorities in terms of agricultural, flood, water demand management etc.  

scholarly journals Variability of Daily Maximum Wind Speed across China, 1975–2016: An Examination of Likely Causes

2020 ◽  
Vol 33 (7) ◽  
pp. 2793-2816 ◽  
Author(s):  
Gangfeng Zhang ◽  
Cesar Azorin-Molina ◽  
Deliang Chen ◽  
Jose A. Guijarro ◽  
Feng Kong ◽  
...  
Keyword(s):  
Wind Speed ◽  
Large Scale ◽  
Southern Oscillation ◽  
Vertical Wind Shear ◽  
Maximum Wind Speed ◽  
The Arctic ◽  
Risk Governance ◽  
Daily Maximum ◽  
Near Surface ◽  
Maximum Wind

AbstractAssessing change in daily maximum wind speed and its likely causes is crucial for many applications such as wind power generation and wind disaster risk governance. Multidecadal variability of observed near-surface daily maximum wind speed (DMWS) from 778 stations over China is analyzed for 1975–2016. A robust homogenization protocol using the R package Climatol was applied to the DMWS observations. The homogenized dataset displayed a significant (p < 0.05) declining trend of −0.038 m s−1 decade−1 for all China annually, with decreases in winter (−0.355 m s−1 decade−1, p < 0.05) and autumn (−0.108 m s−1 decade−1; p < 0.05) and increases in summer (+0.272 m s−1 decade−1, p < 0.05) along with a weak recovery in spring (+0.032 m s−1 decade−1; p > 0.10); that is, DMWS declined during the cold semester (October–March) and increased during the warm semester (April–September). Correlation analysis of the Arctic Oscillation, the Southern Oscillation, and the west Pacific modes exhibited significant correlation with DMWS variability, unveiling their complementarity in modulating DMWS. Further, we explored potential physical processes relating to the atmospheric circulation changes and their impacts on DMWS and found that 1) overall weakened horizontal airflow [large-scale mean horizontal pressure gradient (from −0.24 to +0.02 hPa decade−1) and geostrophic wind speed (from −0.6 to +0.6 m s−1 decade−1)], 2) widely decreased atmospheric vertical momentum transport [atmospheric stratification thermal instability (from −3 to +1.5 decade−1) and vertical wind shear (from −0.4 to +0.2 m s−1 decade−1)], and 3) decreased extratropical cyclones frequency (from −0.3 to 0 month decade−1) are likely causes of DMWS change.

scholarly journals Temporal variations in the wind and wave climate at a location in the eastern Arabian Sea based on ERA-Interim reanalysis data

2014 ◽  
Vol 14 (5) ◽  
pp. 1371-1381 ◽  
Author(s):  
P. R. Shanas ◽  
V. Sanil Kumar
Keyword(s):  
Wind Speed ◽  
Arabian Sea ◽  
Temporal Variations ◽  
Reanalysis Data ◽  
Maximum Wind Speed ◽  
Annual Maximum ◽  
Upward Trend ◽  
Monsoon Period ◽  
Maximum Wind ◽  
Eastern Arabian Sea

Abstract. Temporal variations in wind speed and significant wave height (SWH) at a location in the eastern Arabian Sea are studied using ERA-Interim reanalysis data from 1979 to 2012. A shallow water location is selected for the study since measured buoy data are available close to the location for comparison with the reanalysis data. The annual mean wind speed shows a statistically significant decreasing trend of 1.5 cm s−1 year−1, whereas a statistically insignificant increasing trend of 3.6 cm s−1 year−1 is observed for annual maximum wind speed due to the local events that altered the trend in annual maximum wind speed. Weakening of SWH during one of the peak monsoon months (August) is identified from the monthly analysis of SWH, which shows a higher upward trend in SWH during the southwest monsoon period, with an exception during August. The annual mean SWH shows a slight upward trend (0.012 cm year−1), whereas a larger upward trend (1.4 cm year−1) is observed for annual maximum SWH. Both identified trends are statistically insignificant. The influence of tropical cyclone activity is also studied and it is found that the maximum SWH and wind speed during 1996 are directly related to the cyclonic event.

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