scholarly journals Spatial and temporal variability of precipitation and drought in Portugal

2012 ◽  
Vol 12 (5) ◽  
pp. 1493-1501 ◽  
Author(s):  
D. S. Martins ◽  
T. Raziei ◽  
A. A. Paulo ◽  
L. S. Pereira
Keyword(s):  
Principal Component Analysis ◽  
Standardized Precipitation Index ◽  
Principal Component ◽  
Component Analysis ◽  
Maximum Temperature ◽  
Drought Indices ◽  
Drought Severity ◽  
Spatial And Temporal Variability ◽  
Monthly Precipitation ◽  
Precipitation Regimes

Abstract. The spatial variability of precipitation and drought are investigated for Portugal using monthly precipitation from 74 stations and minimum and maximum temperature from 27 stations, covering the common period of 1941–2006. Seasonal precipitation and the corresponding percentages in the year, as well as the precipitation concentration index (PCI), was computed for all 74 stations and then used as an input matrix for an R-mode principal component analysis to identify the precipitation patterns. The standardized precipitation index at 3 and 12 month time scales were computed for all stations, whereas the Palmer Drought Severity Index (PDSI) and the modified PDSI for Mediterranean conditions (MedPDSI) were computed for the stations with temperature data. The spatial patterns of drought over Portugal were identified by applying the S-mode principal component analysis coupled with varimax rotation to the drought indices matrices. The result revealed two distinct sub-regions in the country relative to both precipitation regimes and drought variability. The analysis of time variability of the PC scores of all drought indices allowed verifying that there is no linear trend indicating drought aggravation or decrease. In addition, the analysis shows that results for SPI-3, SPI-12, PDSI and MedPDSI are coherent among them.

scholarly journals Spatial and Temporal Analysis of Drought in Nepal using Standardized Precipitation Index and its Relationship with Climate Indices

1970 ◽  
Vol 7 (1) ◽  
pp. 59-74 ◽  
Author(s):  
M Sigdel ◽  
M Ikeda
Keyword(s):  
Principal Component Analysis ◽  
Southern Oscillation ◽  
Climatic Variability ◽  
Standardized Precipitation Index ◽  
Principal Component ◽  
Component Analysis ◽  
Precipitation Index ◽  
Climate Indices ◽  
Indian Ocean Dipole Mode ◽  
Time Space

Drought over Nepal is studied on the basis of precipitation as a key parameter. Using monthly mean precipitation data for a period of 33 years, Standardized Precipitation Index (SPI) is produced for the drought analysis with the time scale of 3 months (SPI-3) and 12 months (SPI-12) as they are applicable for agriculture and hydrological aspects, respectively. Time-space variability is explored based on Principal Component Analysis (PCA) along with Rotated PCA (RPCA). Four rotated components were explored for both SPI-3 and SPI-12 representing climatic variability with cores over eastern, central and western Nepal separately. Droughts associated with SPI-3 occurred almost evenly over these regions. Droughts associated with SPI-12 were consistent with SPI-3 for summer, since summer precipitation dominates annual precipitation. Connection between SPI and the climate indices such as Southern Oscillation Index (SOI) and Indian Ocean Dipole Mode Index (DMI) was studied, suggesting that one of the causes for summer droughts is El Nino, while the winter droughts could be related with positive DMI. Keywords: Standardized Precipitation Index; Nepal; Principal component analysis; Drought DOI: http://dx.doi.org/10.3126/jhm.v7i1.5617 JHM 2010; 7(1): 59-74

Multi-response Optimization in Machining of GFRP (Epoxy) Composites: An Integrated Approach

2015 ◽  
Vol 15 (3) ◽  
pp. 267-292 ◽  
Author(s):  
Rajesh Kumar Verma ◽  
Kumar Abhishek ◽  
Saurav Datta ◽  
Pradip Kumar Pal ◽  
S.S. Mahapatra
Keyword(s):  
Principal Component Analysis ◽  
Taguchi Method ◽  
Feed Rate ◽  
Principal Component ◽  
Component Analysis ◽  
Maximum Temperature ◽  
Multi Objective Optimization ◽  
Gfrp Composites ◽  
Multi Objective ◽  
Multiple Process

AbstractThis paper investigates on optimization of process control parameters during machining (drilling and turning) of Glass Fiber Reinforced Polymer (GFRP) composites by considering multiple process performance yields. The main characteristic indices for evaluating drilling performance are thrust force, torque and delamination factor (at entry as well as exit); the corresponding machining parameters are drill speed, feed rate and diameter of the drill bit. The following process parameters viz. spindle speed, feed rate, and depth of cut have been considered to investigate multiple process responses viz. Material Removal Rate (MRR), surface roughness (Ra), tool-tip temperature (maximum temperature generated during machining at tool-tip) and resultant cutting force whilst turning of GFRP (epoxy) composite specimens. As traditional Taguchi method is unable to solve multi-objective optimization problem; to overcome this limitation; the study proposes Principal Component Analysis (PCA) along with fuzzy logic and finally Taguchi philosophy towards multiple-objective optimization in machining of GFRP composites. Analysis of the solutions for the multi-objective optimization by aforesaid approach has been depicted through two case experimental researches. It has also been observed from drilling experiments that PCA-fuzzy (integrated with Taguchi method) has provided better result as compared to WPCA (Weighted Principal Component Analysis) based Taguchi method. The proposed PCA-Fuzzy based Taguchi method can fruitfully be applied for continuous quality improvement and off-line quality control of the process/product.

scholarly journals Southwest monsoon rainfall in Assam: An application of principal component analysis for understanding of variability

MAUSAM ◽  
2021 ◽  
Vol 68 (2) ◽  
pp. 357-366
Author(s):  
PIJUSH BASAK
Keyword(s):  
Principal Component Analysis ◽  
Principal Components ◽  
Temporal Variability ◽  
Monsoon Rainfall ◽  
Principal Component ◽  
Component Analysis ◽  
Southwest Monsoon ◽  
The State ◽  
Spatial And Temporal Variability ◽  
Southwest Monsoon Rainfall

The principal component analysis (PCA) is applied to understand the spatial and temporal variability of monsoonal rainfall in the state Assam in India. The Southwest Monsoon (SWM) rainfall data over 12 widely spread stations located over the state has been analyzed for a period of 60 years for understanding variability. A statistically significant trend and a above/below transition signal has been observed for a few stations and the corresponding principal components (PCs). Coherent regions of Northern and Southern Assam have been identified through PCA to bring out the possible significant signals. It is observed that some of PCs for state-wise and coherent regions have positive or negative trend and significant above/below transition.    

DYNAMICS AND SPATIO-TEMPORAL VARIABILITY OF ENVIRONMENTAL FACTORS IN EASTERN AUSTRALIA USING FUNCTIONAL PRINCIPAL COMPONENT ANALYSIS

2010 ◽  
Vol 18 (04) ◽  
pp. 763-785 ◽  
Author(s):  
JUDIT K. SZABO ◽  
EUGENIO M. FEDRIANI ◽  
M. MANUELA SEGOVIA-GONZÁLEZ ◽  
LEE B. ASTHEIMER ◽  
MIKE J. HOOPER
Keyword(s):  
Principal Component Analysis ◽  
Temporal Variability ◽  
Principal Component ◽  
Component Analysis ◽  
Functional Principal Component Analysis ◽  
Geographical Information ◽  
Spatial And Temporal Variability ◽  
Functional Principal Component ◽  
Eastern Australia ◽  
Spatio Temporal

This paper introduces a new technique in ecology to analyze spatial and temporal variability in environmental variables. By using simple statistics, we explore the relations between abiotic and biotic variables that influence animal distributions. However, spatial and temporal variability in rainfall, a key variable in ecological studies, can cause difficulties to any basic model including time evolution. The study was of a landscape scale (three million square kilometers in eastern Australia), mainly over the period of 1998–2004. We simultaneously considered qualitative spatial (soil and habitat types) and quantitative temporal (rainfall) variables in a Geographical Information System environment. In addition to some techniques commonly used in ecology, we applied a new method, Functional Principal Component Analysis, which proved to be very suitable for this case, as it explained more than 97% of the total variance of the rainfall data, providing us with substitute variables that are easier to manage and are even able to explain rainfall patterns. The main variable came from a habitat classification that showed strong correlations with rainfall values and soil types.

scholarly journals Variability of south west monsoon rainfall in West Bengal : An application of principal component analysis

MAUSAM ◽  
2021 ◽  
Vol 65 (4) ◽  
Author(s):  
PIJUSH BASAK
Keyword(s):  
Principal Component Analysis ◽  
West Bengal ◽  
Monsoon Rainfall ◽  
Principal Component ◽  
Component Analysis ◽  
Southwest Monsoon ◽  
Spatial And Temporal Variability ◽  
Annual Variations ◽  
South West Monsoon ◽  
Southwest Monsoon Rainfall

The principal component analysis is utilized to understand the spatial and temporal variability of monsoonal rainfall. The southwest monsoon rainfall data of West Bengal, situated over 21 stations widely spread over the state, has been analyzed for a period of 60 years for inter-annual variations. A coherent subset of 8 north and 13 south stations has been studied separately to produce statistically significant inter-annual signals. It is observed that the above/below transition is quite significant both for station rainfalls and principal components for state-wise and coherent zone analysis.

scholarly journals Variabilidad espacio-temporal de las sequías en la cuenca Pacífico Norte de México (1961-2010)

2016 ◽  
Vol 42 (1) ◽  
pp. 185 ◽  
Author(s):  
L. Serrano-Barrios ◽  
S. M. Vicente-Serrano ◽  
H. Flores-Magdaleno ◽  
L. Tijerina-Chávez ◽  
D. Vázquez-Soto
Keyword(s):  
Standardized Precipitation Index ◽  
Maximum Temperature ◽  
Drought Indices ◽  
Drought Severity ◽  
Evaporative Demand ◽  
The North ◽  
Weather Stations ◽  
Potential Impact ◽  
Spatio Temporal ◽  
The Standardized Precipitation Index

This article analyses the spatio-temporal variability of droughts in the North Pacific Basin of México between 1961 and 2010, using two drought indices: the Standardized Precipitation Index (SPI) and the Standardized Precipitation Evapotranspiration Index (SPEI). We used data from 48 weather stations with available data of precipitation and monthly minimum and maximum temperature. In 22 of the weather stations, time series of Piché evaporation were also available. The reference evapotranspiration, necessary to obtain the SPEI, was calculated by means of the Hargreaves equation. Results show that major droughts occurred in the 1980s and 2000s, although there is a noticeable spatial variability across the region. Finally, the potential impact of the atmospheric evaporative demand on drought severity observed by the different drought indices is discussed, and the possible implications for an appropriate risk assessment.

scholarly journals Negative regional Standardized Precipitation Index trends prevail in the Mexico’s state of Zacatecas.

2019 ◽  
Vol 37 (4) ◽  
pp. 487
Author(s):  
Rafael Magallanes-Quintanar ◽  
Fidel Blanco-Macías ◽  
Erick Carlos Galván-Tejada ◽  
Jorge Isaac Galván-Tejada ◽  
Miguel Márquez-Madrid ◽  
...  
Keyword(s):  
Time Series ◽  
Standardized Precipitation Index ◽  
Precipitation Index ◽  
Trend Test ◽  
Spatial And Temporal Variability ◽  
Monthly Precipitation ◽  
Precipitation Time Series ◽  
Groundwater Levels ◽  
Sen’S Slope ◽  
Precipitation Regimes

As the earth atmosphere warms, it is unclear how the precipitation will change or how these changes will impact regional rainfall. For the study of spatial and temporal variability of rainfall, several indexes have been developed. The Standardized Precipitation Index (SPI) that only involves recorded rainfall data has been used as a tool for climatic zone classif ication and a drought indicator. Then, the aims of the present study were: 1) to cluster monthly precipitation time series into groups that represent regions under the basis of similar precipitation regimes, 2) to compute regional SPI’s using all the members (time series) of each cluster, and 3) to estimate trends of the regional SPI’s. The cluster analysis approach was used to identify four groups of monthly precipitation time series that represent regions of similar precipitation regimes. Afterwards, regional SPI’s were estimated using all the members of each cluster. Finally, four regional SPI trends were estimated by means of the Mann-Kendall trend test and Sen’s slope estimator. Estimated decreasing SPI trends imply prevail of negative values at the end of the study period (1964-2014), which indicate less than median precipitation in the entire Zacatecas state territory. For instance, SPI at 12-month time scale Sen’s slope values were -0.17 and -0.18 for the wet and dry seasons, respectively in the Semi-desert region. Thus, the evidenced trends may be having influence on the availability of surface water, groundwater levels and aquifers recharge in the near future. So, it is imperative to adjust inhabitants’ activities according to design planned climate change adaptation strategies.

scholarly journals Spatial and temporal patterns of precipitation in Montenegro

Időjárás ◽  
2020 ◽  
Vol 124 (4) ◽  
pp. 499-519
Author(s):  
Golub Ćulafić ◽  
Tatjana Popov ◽  
Slobodan Gnjato ◽  
Davorin Bajić ◽  
Goran Trbić ◽  
...  
Keyword(s):  
Principal Component Analysis ◽  
Hierarchical Clustering ◽  
Principal Component ◽  
Temporal Patterns ◽  
Summer Season ◽  
Monthly Precipitation ◽  
Agglomerative Hierarchical Clustering ◽  
Clustering Method ◽  
Spatial And Temporal Patterns ◽  
Precipitation Regimes

The paper analyses, spatial and temporal patterns of precipitation over Montenegro. Data on mean monthly precipitation during the period 1961–2015 from 17 meteorological stations were used for the analysis. Four regions with different spatial precipitation regimes were identified by using the principal component analysis and the agglomerative hierarchical clustering method. A downward tendency in annual precipitation prevails over Montenegro. The most prominent reduction was present in the summer season. In contrast, precipitation increased during autumn. However, the majority of estimated trend values was low and statistically insignificant.

scholarly journals Comparison of Some Drought Indices in Iraq

2020 ◽  
Vol 30 (4) ◽  
pp. 1
Author(s):  
Usama Sameer Nedham ◽  
Ahmed Sami Hassan
Keyword(s):  
Standardized Precipitation Index ◽  
Precipitation Anomaly ◽  
Drought Indices ◽  
Drought Severity ◽  
Monthly Precipitation ◽  
Wet Season ◽  
Future Period ◽  
Intergovernmental Panel ◽  
The North ◽  
The Standardized Precipitation Index

Drought in Iraq was assessed using three drought indices for two different time periods, past period from 1970 to 2015, and future period from 2016 to 2050 for 4 stations in Iraq. These indices named: the Standardized Precipitation Index (SPI), Percentage of Precipitation Anomaly (PPA), and Z-Score Index (ZSI). The main sources of data were the monthly rainfall archive from Iraqi Meteorological Organization and Seismology (IMOS) for past period, and projection monthly precipitation data from Representative Concentration Pathway scenario (RCP4.5) for Fifth Assessment Report (AR5) affiliate to the Intergovernmental Panel on Climate Change (IPCC) for future period. The results shown good correlation of among 3 indices, with different rank of them, were lowest rank was 0.85. The three indices refer to were good evaluate the drought severity of Iraq. Found too the best index was PPA during past period, and the significant index was ZSI for the future period. The North of Iraq (Mosul Station) was the least vulnerable to drought from the analysis of the results of the three indices for the last period, where the number of dry seasons were 12 on the basis of the PPA classification. South of Iraq (Basra station) has the highest number of wet season on the PPA rating were (15) season.

scholarly journals Principal component analysis of precipitation in Thessaly region (Central Greece)

2013 ◽  
Vol 11 (4) ◽  
pp. 467-476 ◽  
Keyword(s):  
Principal Component Analysis ◽  
Principal Component ◽  
Component Analysis ◽  
Precipitation Pattern ◽  
Monthly Precipitation ◽  
Homogeneous Precipitation ◽  
Precipitation Data ◽  
Cold Pools ◽  
Monthly Precipitation Data ◽  
Gradient Surface

Characteristics of the precipitation pattern are determined for Thessaly region in central Greece by using the Principal Component Analysis (PCA). Mean monthly precipitation data from 75 meteorological stations are used covering a 35 year period (1960-1994). The first two principal components (PCs), which describe 87.7% of the total variance, are taken into consideration. It is demonstrated statistically that PC1 is related to the frequency of the cyclones crossing the area, while PC2 is related to the anticyclonic and non-gradient surface weather types and cold pools aloft. This means that PC1 explains the annual amounts of precipitation and PC2 the summer thundery rainfalls. The spatial distribution of precipitation is studied afterwards. Using the PCs scores, homogeneous precipitation sectors are determined over the territory of which the annual pattern of precipitation is discussed. KEYWORDS:

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