scholarly journals Rainfall variability in Malay Peninsula region of Southeast Asia using gridded data

2019 ◽  
Vol 81 ◽  
pp. 01002
Author(s):  
Vishal Singh ◽  
Xiaosheng Qin
Keyword(s):  
Time Series ◽  
Southeast Asia ◽  
Rainfall Variability ◽  
Rainfall Time Series ◽  
Malay Peninsula ◽  
Gap Filling ◽  
Mathematical Functions ◽  
Rainfall Analysis ◽  
The Past ◽  
Filling Analysis

Southeast Asia is recognized as a climate-change vulnerable region as it has been significantly affected by many extreme events in the past. This study carried out a rainfall analysis over the Malay Peninsula region of Southeast Asia utilizing historical (1981-2007) gridded rainfall datasets (0.5°×0.5°). The rainfall variability was analyzed in an intra-decadal time series duration. The uncertainty involved in all datasets was also checked based on the comparison of multiple global rainfall datasets. Rainfall gap filling analysis was conducted for producing more accurate rainfall time series after testing multiple mathematical functions. Frequency-based rainfall extreme indices such as Dry Days and Wet days are generated to assess the rainfall variability over the study area. Our results revealed a notable variation existed in the rainfalls over Malay Peninsula as per the long historical duration (1981-2007).

scholarly journals Evaluation of Seven Gap-Filling Techniques for Daily Station-Based Rainfall Datasets in South Ethiopia

2021 ◽  
Vol 2021 ◽  
pp. 1-15
Author(s):  
Alefu Chinasho ◽  
Bobe Bedadi ◽  
Tesfaye Lemma ◽  
Tamado Tana ◽  
Tilahun Hordofa ◽  
...  
Keyword(s):  
Time Series ◽  
Missing Values ◽  
Daily Rainfall ◽  
Substantial Contribution ◽  
Ratio Method ◽  
Rainfall Time Series ◽  
Gap Filling ◽  
Quantile Mapping ◽  
South Ethiopia ◽  
Skill Scores

Meteorological stations, mainly located in developing countries, have gigantic missing values in the climate dataset (rainfall and temperature). Ignoring the missing values from analyses has been used as a technique to manage it. However, it leads to partial and biased results in data analyses. Instead, filling the data gaps using the reference datasets is a better and widely used approach. Thus, this study was initiated to evaluate the seven gap-filling techniques in daily rainfall datasets in five meteorological stations of Wolaita Zone and the surroundings in South Ethiopia. The considered gap-filling techniques in this study were simple arithmetic means (SAM), normal ratio method (NRM), correlation coefficient weighing (CCW), inverse distance weighting (IDW), multiple linear regression (MLR), empirical quantile mapping (EQM), and empirical quantile mapping plus (EQM+). The techniques were preferred because of their computational simplicity and appreciable accuracies. Their performance was evaluated against mean absolute error (MAE), root mean square error (RMSE), skill scores (SS), and Pearson’s correlation coefficients (R). The results indicated that MLR outperformed other techniques in all of the five meteorological stations. It showed the lowest RMSE and the highest SS and R in all stations. Four techniques (SAM, NRM, CCW, and IDW) showed similar performance and were second-ranked in all of the stations with little exceptions in time series. EQM+ improved (not substantial) the performance levels of gap-filling techniques in some stations. In general, MLR is suggested to fill in the missing values of the daily rainfall time series. However, the second-ranked techniques could also be used depending on the required time series (period) of each station. The techniques have better performance in stations located in higher altitudes. The authors expect a substantial contribution of this paper to the achievement of sustainable development goal thirteen (climate action) through the provision of gap-filling techniques with better accuracy.

scholarly journals Building hazard maps of extreme daily rainy events from PDF ensemble, via REA method, on Senegal River Basin

2011 ◽  
Vol 15 (11) ◽  
pp. 3605-3615 ◽  
Author(s):  
J. D. Giraldo Osorio ◽  
S. G. García Galiano
Keyword(s):  
Time Series ◽  
River Basin ◽  
Rainfall Variability ◽  
Quantitative Measure ◽  
Extreme Rainfall ◽  
Rainfall Time Series ◽  
Hazard Maps ◽  
Senegal River ◽  
Mitigation And Adaptation ◽  
Senegal River Basin

Abstract. The Sudano-Sahelian zone of West Africa, one of the poorest of the Earth, is characterized by high rainfall variability and rapid population growth. In this region, heavy storm events frequently cause extensive damage. Nonetheless, the projections for change in extreme rainfall values have shown a great divergence between Regional Climate Models (RCM), increasing the forecast uncertainty. Novel methodologies should be applied, taking into account both the variability provided by different RCMs, as well as the non-stationary nature of time series for the building of hazard maps of extreme rainfall events. The present work focuses on the probability density functions (PDFs)-based evaluation and a simple quantitative measure of how well each RCM considered can capture the observed annual maximum daily rainfall (AMDR) series on the Senegal River basin. Since meaningful trends have been detected in historical rainfall time series for the region, non-stationary probabilistic models were used to fit the PDF parameters to the AMDR time series. In the development of PDF ensemble by bootstrapping techniques, Reliability Ensemble Averaging (REA) maps were applied to score the RCMs. The REA factors were computed using a metric to evaluate the agreement between observed -or best estimated- PDFs, and that simulated with each RCM. The assessment of plausible regional trends associated to the return period, from the hazard maps of AMDR, showed a general rise, owing to an increase in the mean and the variability of extreme precipitation. These spatial-temporal distributions could be considered by Organization for the Development of the Senegal River (Organisation pour la mise en valeur du fleuve Sénégal, OMVS), in such a way as to reach a better balance between mitigation and adaptation.

scholarly journals A map of the extent and year of detection of oil palm plantations in Indonesia, Malaysia and Thailand

2021 ◽  
Vol 8 (1) ◽  
Author(s):  
Olga Danylo ◽  
Johannes Pirker ◽  
Guido Lemoine ◽  
Guido Ceccherini ◽  
Linda See ◽  
...  
Keyword(s):  
Remote Sensing ◽  
Time Series ◽  
Southeast Asia ◽  
Oil Palm ◽  
Abrupt Increase ◽  
The Past ◽  
Oil Palm Plantation ◽  
Time Series Approach ◽  
Landscape Level

AbstractIn recent decades, global oil palm production has shown an abrupt increase, with almost 90% produced in Southeast Asia alone. To understand trends in oil palm plantation expansion and for landscape-level planning, accurate maps are needed. Although different oil palm maps have been produced using remote sensing in the past, here we use Sentinel 1 imagery to generate an oil palm plantation map for Indonesia, Malaysia and Thailand for the year 2017. In addition to location, the age of the oil palm plantation is critical for calculating yields. Here we have used a Landsat time series approach to determine the year in which the oil palm plantations are first detected, at which point they are 2 to 3 years of age. From this, the approximate age of the oil palm plantation in 2017 can be derived.

scholarly journals Building hazard maps of extreme daily rainy events from PDF ensemble, via REA method, on Senegal River Basin

2011 ◽  
Vol 8 (2) ◽  
pp. 3817-3839
Author(s):  
J. D. Giraldo ◽  
S. G. García Galiano
Keyword(s):  
Time Series ◽  
River Basin ◽  
Rainfall Variability ◽  
Quantitative Measure ◽  
Extreme Rainfall ◽  
Rainfall Time Series ◽  
Hazard Maps ◽  
Senegal River ◽  
Mitigation And Adaptation ◽  
Senegal River Basin

Abstract. The Sudano-Sahelian zone of West Africa, one of the poorest of the Earth, is characterized by high rainfall variability and rapid population growth. In this region, heavy storm events frequently cause extensive damage. Nonetheless, the projections for change in extreme rainfall values have shown a great divergence between Regional Climate Models (RCM), increasing the forecast uncertainty. Novel methodologies should be applied, taking into account both the variability provided by different RCMs, as well as the non-stationary nature of time series for the building of hazard maps of extreme rainfall events. The present work focuses in the probability density functions (PDFs)-based evaluation and a simple quantitative measure of how well each RCM considered can capture the observed annual maximum daily rainfall (AMDR) series on the Senegal River basin. Since meaningful trends have been detected in historical rainfall time series for the region, non-stationary probabilistic models were used to fit the PDF parameters to the AMDR time series. In the development of PDF ensemble by bootstrapping techniques, Reliability Ensemble Averaging (REA) maps were applied to score the RCMs. The REA factors were computed using a metric to evaluate the agreement between observed -or best estimated- PDFs, and that simulated with each RCM. The assessment of plausible regional trends associated to the return period, from the hazard maps of AMDR, showed a general rise, owing to an increase in the mean and the variability of extreme precipitation. These spatial-temporal distributions could be considered by local stakeholders in such a way as to reach a better balance between mitigation and adaptation.

scholarly journals RAINFALL ANALYSIS IN KLANG RIVER BASIN USING CONTINUOUS WAVELET TRANSFORM

2016 ◽  
Vol 10 (1) ◽  
pp. 3-10 ◽  
Author(s):  
Celso A. G. Santos ◽  
Richarde Marques Silva ◽  
Seyed Ahmad Akrami
Keyword(s):  
Time Series ◽  
Wavelet Transform ◽  
River Basin ◽  
Continuous Wavelet Transform ◽  
Rainfall Data ◽  
Accurate Information ◽  
Rainfall Time Series ◽  
Continuous Wavelet ◽  
Rainfall Analysis ◽  
Frequency Components

The rainfall characteristics within Klang River basin is analyzed by the continuous wavelet transform using monthly rainfall data (1997–2009) from a raingauge and also using daily rainfall data (1998–2013) from the Tropical Rainfall Measuring Mission (TRMM). The wavelet power spectrum showed that some frequency components were presented within the rainfall time series, but the observed time series is short to provide accurate information, thus the daily TRMM rainfall data were used. In such analysis, two main frequency components, i.e., 6 and 12 months, showed to be present during the entire period of 16 years. Such semiannual and annual frequencies were confirmed by the global wavelet power spectra. Finally, the modulation in the 8–16-month and 256–512-day bands were examined by an average of all scales between 8 and 16 months, and 256 and 512 days, respectively, giving a measure of the average monthly/daily variance versus time, where the periods with low or high variance could be identified.

Precipitation trends in Victoria, Australia

2014 ◽  
Vol 6 (2) ◽  
pp. 278-287 ◽  
Author(s):  
Siti Nazahiyah Rahmat ◽  
Niranjali Jayasuriya ◽  
Muhammed A. Bhuiyan
Keyword(s):  
Time Series ◽  
Time Series Data ◽  
Annual Rainfall ◽  
Series Data ◽  
Rainfall Time Series ◽  
Full Data ◽  
Data Set ◽  
Rainfall Analysis ◽  
Mk Test ◽  
Abrupt Changes

Annual rainfall series trends were investigated for more than 100 years of data using two non-parametric trend tests Mann–Kendall (MK) and Sen's slope (Q) for five selected meteorological stations in Victoria, Australia. The annual rainfall time series showed no significant trends for any of the five stations. To assess the sensitivity of trends to the length of the time periods considered, the annual rainfall analysis was repeated using recent data from approximately half the data set between 1949 and 2011. Contrasting results from the original full data set analysis were revealed. All five stations showed decreasing trends with two stations showing significant trends suggesting that this recent time period has added more low precipitation data to the time series. The year of abrupt changes for all the five stations identified using the sequential MK test varied. Conclusions drawn from this paper, point to the importance of selecting the time series data length in identifying trends and abrupt changes. Due to the climate variability, trend testing results might be biased and strongly dependent on the data period selected. Therefore, use of the full data set available would be required in order to improve understanding of change or to undertake any further studies.

scholarly journals RAINFALL ANALYSIS IN KLANG RIVER BASIN USING CONTINUOUS WAVELET TRANSFORM

2016 ◽  
Vol 10 (1) ◽  
pp. 3-10
Author(s):  
Celso A. G. Santos ◽  
Richarde Marques Silva ◽  
Seyed Ahmad Akrami
Keyword(s):  
Time Series ◽  
Wavelet Transform ◽  
River Basin ◽  
Continuous Wavelet Transform ◽  
Rainfall Data ◽  
Accurate Information ◽  
Rainfall Time Series ◽  
Continuous Wavelet ◽  
Rainfall Analysis ◽  
Frequency Components

The rainfall characteristics within Klang River basin is analyzed by the continuous wavelet transform using monthly rainfall data (1997–2009) from a raingauge and also using daily rainfall data (1998–2013) from the Tropical Rainfall Measuring Mission (TRMM). The wavelet power spectrum showed that some frequency components were presented within the rainfall time series, but the observed time series is short to provide accurate information, thus the daily TRMM rainfall data were used. In such analysis, two main frequency components, i.e., 6 and 12 months, showed to be present during the entire period of 16 years. Such semiannual and annual frequencies were confirmed by the global wavelet power spectra. Finally, the modulation in the 8–16-month and 256–512-day bands were examined by an average of all scales between 8 and 16 months, and 256 and 512 days, respectively, giving a measure of the average monthly/daily variance versus time, where the periods with low or high variance could be identified.

scholarly journals Temporal change of extreme precipitation intensity–duration–frequency relationships in Thailand

2021 ◽  
Author(s):  
N. Yamoat ◽  
R. Hanchoowong ◽  
S. Sriboonlue ◽  
A. Kangrang
Keyword(s):  
Time Series ◽  
Extreme Precipitation ◽  
Extreme Rainfall ◽  
Precipitation Intensity ◽  
Rainfall Time Series ◽  
The Past ◽  
The North ◽  
Hourly Rainfall ◽  
Idf Curves ◽  
Intensity Duration Frequency

Abstract Due to climate change, many research studies have derived the updated extreme precipitation intensity–duration–frequency relationship (IDF curve) from forecasted sub-hourly rainfall intensity time series, which is one of the most important tools for the planning and designing of hydraulic infrastructures. In this study, the IDF curves (1990–2016) of the six regions and procedures are used in accordance with those of the Royal Irrigation Department (RID)’s study (1950–1988). Each set of IDF relationships consists of 81 intensity values which are the combination of nine durations and nine return periods. The intensity ratios of this study and RID are compared. A greater-than-1 ratio indicates extreme intensity increment from the past to the present. Considering 81 ratios for each region, the number of greater-than-1 ratios for the North, Northeast, Central, East, West, and South regions are 8, 2, 31, 34, 6, and 7, respectively. These ratio numbers are far below 81 which means that the majority of extreme rainfall intensities do not increase from the past to the present. The study found that using accurate historical sub-hourly rainfall time series to create a set of IDF curves would be more reliable than using forecasted rainfall modeling.

On The Possibility of an Autonomous History of Modern Southeast Asia

1961 ◽  
Vol 2 (2) ◽  
pp. 73-105 ◽  
Author(s):  
John R. W. Small
Keyword(s):  
Southeast Asia ◽  
Contemporary History ◽  
The Past ◽  
History Of

It is generally accepted that history is an element of culture and the historian a member of society, thus, in Croce's aphorism, that the only true history is contemporary history. It follows from this that when there occur great changes in the contemporary scene, there must also be great changes in historiography, that the vision not merely of the present but also of the past must change.

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