scholarly journals Evaluating the Quality of Spatial Data for the Analysis of Climate Variability in the Coastal Region of Nigeria

2021 ◽  
Vol 5 (1) ◽  
pp. 76-90
Author(s):  
A.I. Agbonaye ◽  
O.C. Izinyon
Keyword(s):  
Climate Change ◽  
Climate Variability ◽  
Spatial Data ◽  
Coastal Region ◽  
Climatic Research Unit ◽  
Data Series ◽  
Homogeneity Test ◽  
Climatic Data ◽  
Omnibus Test ◽  
Standard Normal Homogeneity Test

The lack of truly reliable data for climate change analyses and prediction presents challenges in climate modeling. Needed data are required to be hydrologically/statistically reliable to be useful for hydrological, meteorological, climate change, and estimation studies. Thus, data quality and homogeneity screening are preliminary analyses. In this study, the homogeneity of the climatic data used for analyses of climate variability was conducted in the coastal region of Nigeria. Climatic Research Unit (CRU 0.5× 0.5) gridded monthly climatic data for sixty years (1956- 2016) for nine states of the coastal region of Nigeria obtained from internet sources were validated with the Nigerian Meteorological Agency (NiMet) data to assure adequacy for use. The data were tested for normality using the Shapiro-Wilk (S-W) test, D’Agostino-Pearson omnibus test, and skewness test. Four homogeneity test methods were applied to 257 locations in the nine states of the coastal region of Nigeria and they include Pettit’s, Standard Normal Homogeneity Test (SNHT), Buishand’s and Von Neumann Ratio (VNR) tests. The results of the validity analysis indicated that the CRU data are very reliable and thus justified their use for the further analysis carried out in the study. Also, the results obtained indicated that CRU climatic data series were normally distributed and parametric methods could be used in further analysis of the data. Rainfall data homogeneity was detected for Bayelsa, Delta, Edo, Lagos, Ogun, and Ondo states and inhomogeneity for Akwa Ibom, Cross Rivers, and Rivers States. Also, temperature data inhomogeneity was detected for all the states in the study area.

scholarly journals Homogenization of Portuguese long-term temperature data series: Lisbon, Coimbra and Porto

2012 ◽  
Vol 5 (2) ◽  
pp. 521-584 ◽  
Author(s):  
A. L. Morozova ◽  
M. A. Valente
Keyword(s):  
Climate Variability ◽  
Volcanic Eruptions ◽  
Temperature Data ◽  
Temperature Series ◽  
Data Series ◽  
Homogeneity Test ◽  
Homogeneity Tests ◽  
Future Studies ◽  
Standard Normal Homogeneity Test

Abstract. Three long-term temperature data series measured in Portugal were studied to detect and correct non-climatic homogeneity breaks and are now available for future studies of climate variability. Series of monthly minimum (Tmin) and maximum (Tmax) temperatures measured in the three Portuguese meteorological stations of Lisbon (from 1856 to 2008), Coimbra (from 1865 to 2005) and Porto (from 1888 to 2001) were studied to detect and correct non-climatic homogeneity breaks. These series together with monthly series of average temperature (Taver) and temperature range (DTR) derived from them were tested in order to detect homogeneity breaks, using, firstly, metadata, secondly, a visual analysis and, thirdly, four widely used homogeneity tests: von Neumann ratio test, Buishand test, standard normal homogeneity test and Pettitt test. The homogeneity tests were used in absolute (using temperature series themselves) and relative (using sea-surface temperature anomalies series obtained from HadISST2 close to the Portuguese coast or already corrected temperature series as reference series) modes. We considered the Tmin, Tmax and DTR series as most informative for the detection of homogeneity breaks due to the fact that Tmin and Tmax could respond differently to changes in position of a thermometer or other changes in the instrument's environment; Taver series have been used, mainly, as control. The homogeneity tests show strong inhomogeneity of the original data series, which could have both internal climatic and non-climatic origins. Homogeneity breaks which have been identified by the last three mentioned homogeneity tests were compared with available metadata containing data, such as instrument changes, changes in station location and environment, observing procedures, etc. Significant homogeneity breaks (significance 95% or more) that coincide with known dates of instrumental changes have been corrected using standard procedures. It was also noted that some significant homogeneity breaks, which could not be connected to the known dates of any changes in the park of instruments or stations location and environment, could be caused by large volcanic eruptions. The corrected series were again tested for homogeneity: the corrected series were considered free of non-climatic breaks when the tests of most of monthly series showed no significant (significance 95% or more) homogeneity breaks that coincide with dates of known instrument changes. Corrected series are now available in the frame of ERA-CLIM FP7 project for future studies of climate variability (http://doi.pangaea.de/10.1594/PANGAEA.785377).

scholarly journals Homogenization of Portuguese long-term temperature data series: Lisbon, Coimbra and Porto

2012 ◽  
Vol 4 (1) ◽  
pp. 187-213 ◽  
Author(s):  
A. L. Morozova ◽  
M. A. Valente
Keyword(s):  
Climate Variability ◽  
Volcanic Eruptions ◽  
Temperature Data ◽  
Temperature Series ◽  
Data Series ◽  
Homogeneity Test ◽  
Homogeneity Tests ◽  
Future Studies ◽  
Standard Normal Homogeneity Test

Abstract. Three long-term temperature data series measured in Portugal were studied to detect and correct non-climatic homogeneity breaks and are now available for future studies of climate variability. Series of monthly minimum (Tmin) and maximum (Tmax) temperatures measured in the three Portuguese meteorological stations of Lisbon (from 1856 to 2008), Coimbra (from 1865 to 2005) and Porto (from 1888 to 2001) were studied to detect and correct non-climatic breaks. These series, together with monthly series of average temperature (Taver) and temperature range (DTR) derived from them, were tested in order to detect breaks, using firstly metadata, secondly a visual analysis, and thirdly four widely used homogeneity tests: von Neumann ratio test, Buishand test, standard normal homogeneity test, and Pettitt test. The homogeneity tests were used in absolute (using temperature series themselves) and relative (using sea-surface temperature anomalies series obtained from HadISST2.0.0.0 close to the Portuguese coast or already corrected temperature series as reference series) modes. We considered the Tmin, Tmax and DTR series as most informative for the detection of breaks due to the fact that Tmin and Tmax could respond differently to changes in position of a thermometer or other changes in the instrument's environment; Taver series have been used mainly as control. The homogeneity tests showed strong inhomogeneity of the original data series, which could have both internal climatic and non-climatic origins. Breaks that were identified by the last three mentioned homogeneity tests were compared with available metadata containing data such as instrument changes, changes in station location and environment, observation procedures, etc. Significant breaks (significance 95% or more) that coincided with known dates of instrumental changes were corrected using standard procedures. It was also noted that some significant breaks, which could not be connected to known dates of any changes in the park of instruments or stations location and environment, were probably caused by large volcanic eruptions. The corrected series were again tested for homogeneity; the corrected series were considered free of non-climatic breaks when the tests of most of monthly series showed no significant (significance 95% or more) breaks that coincide with dates of known instrument changes. Corrected series are now available within the framework of ERA-CLIM FP7 project for future studies of climate variability (doi:10.1594/PANGAEA.785377).

scholarly journals Combat climate change challenges in considering climatic vulnerabilities and risk factors for wheat production

2017 ◽  
Vol 14 (2) ◽  
pp. 137-149
Author(s):  
MM Rahman ◽  
MG Miah ◽  
SR Saha
Keyword(s):  
Climate Change ◽  
Climate Variability ◽  
Water Levels ◽  
Agricultural Drought ◽  
Maximum Temperature ◽  
Climatic Data ◽  
Wheat Production ◽  
Combat Climate Change ◽  
Northwest Region

The present study was undertaken for assessing the impacts of climate variability on wheat production as well as the field based suggestions opined by the wheat growers to combat the future challenges particularly climate variability during November 2014 to March 2015. The study was conducted at northwest region at Dinajpur sadar and Kaharul upazilas in Dinajpur of Bangladesh. One hundred sixty wheat farmers were selected by using previously pre-tested interview schedules adopting multistage proportionate systematic random sampling technique. Climatic variability was assessed by analysis of long term data of local meteorological station. Assessment of long term climatic data particularly for wheat growing season revealed that minimum temperature has been increased, while maximum temperature and rainfall were decreased. Farmer’s opinions on these aspects were almost similar. Farmers opined that both surface and ground water levels have been decreased, resulting agricultural drought. Farmer’s also opined regarding suitable technology to combat climate change impact on wheat production revealed the use of newly recommended varieties. Finally, the outcome of the results could help researchers as well as government and NGOs to take appropriate climate change adaptation policy thus facilitating farmers in sustaining their livelihoods against changing climate in the near future of Northwest region in Bangladesh.SAARC J. Agri., 14(2): 137-149 (2016)

scholarly journals Assessing Inhomogeneities in Extreme Annual Rainfall Data Series by Multifractal Approach

Water ◽  
2020 ◽  
Vol 12 (4) ◽  
pp. 1030 ◽  
Author(s):  
Amanda García-Marín ◽  
Javier Estévez ◽  
Renato Morbidelli ◽  
Carla Saltalippi ◽  
José Ayuso-Muñoz ◽  
...  
Keyword(s):  
Central Italy ◽  
Extreme Rainfall ◽  
Break Point ◽  
Rainfall Data ◽  
Annual Rainfall ◽  
Data Series ◽  
Homogeneity Test ◽  
Umbria Region ◽  
Standard Normal Homogeneity Test ◽  
Break Points

Testing the homogeneity in extreme rainfall data series is an important step to be performed before applying the frequency analysis method to obtain quantile values. In this work, six homogeneity tests were applied in order to check the existence of break points in extreme annual 24-h rainfall data at eight stations located in the Umbria region (Central Italy). Two are parametric tests (the standard normal homogeneity test and Buishand test) whereas the other four are non-parametric (the Pettitt, Sequential Mann–Kendal, Mann–Whitney U, and Cumulative Sum tests). No break points were detected at four of the stations analyzed. Where inhomogeneities were found, the multifractal approach was applied in order to check if they were real or not by comparing the split and whole data series. The generalized fractal dimension functions Dq and the multifractal spectra f(α) were obtained, and their main parameters were used to decide whether or not a break point existed.

scholarly journals Historical trends in precipitation and stream discharge at the Skjern River catchment, Denmark

2014 ◽  
Vol 18 (2) ◽  
pp. 595-610 ◽  
Author(s):  
I. B. Karlsson ◽  
T. O. Sonnenborg ◽  
K. H. Jensen ◽  
J. C. Refsgaard
Keyword(s):  
Climate Change ◽  
Hydrological Model ◽  
Drought Indices ◽  
Homogeneity Test ◽  
Threshold Method ◽  
Data Set ◽  
River Catchment ◽  
Stream Discharge ◽  
Predict Climate Change ◽  
Standard Normal Homogeneity Test

Abstract. A 133 yr data set from the 1055 km2 Skjern River catchment in western Denmark has been analysed with respect to precipitation, temperature, evapotranspiration and discharge. The precipitation series have been tested and corrected using the standard normal homogeneity test and subsequently corrected for undercatch. The degree of change in the climatic variables is examined using the non-parametric Mann–Kendall test. During the last 133 yr the area has experienced a significant change in precipitation of 26% and a temperature change of 1.4°C, leading to increases in river discharge of 52% and groundwater recharge of 86%. A lumped conceptual hydrological model, NAM, was calibrated on the period 1951–1980 and showed generally an excellent match between simulated and observed discharge. The capability of the hydrological model to predict climate change impact was investigated by looking at performances outside the calibration period. The results showed a reduced model fit, especially for recent time periods (after the 1980s), and not all hydrological changes could be explained. This might indicate that hydrological models cannot be expected to predict climate change impacts on discharge as accurately in the future, compared to the performance under present conditions, where they can be calibrated. The (simulated) stream discharge was subsequently analysed using high flow and drought indices based on the threshold method. The extreme signal was found to depend highly on the period chosen as reference to normal. The analysis indicated that no significant amplitude increase of the hydrograph for both wet and dry extremes could be found superimposed on the overall discharge increase.

scholarly journals Penalized Maximal t Test for Detecting Undocumented Mean Change in Climate Data Series

2007 ◽  
Vol 46 (6) ◽  
pp. 916-931 ◽  
Author(s):  
Xiaolan L. Wang ◽  
Qiuzi H. Wen ◽  
Yuehua Wu
Keyword(s):  
Time Series ◽  
Practical Importance ◽  
T Test ◽  
Data Series ◽  
Homogeneity Test ◽  
Climate Data ◽  
Series Length ◽  
Standard Normal Homogeneity Test ◽  
Higher Power ◽  
Standard Normal

Abstract In this paper, a penalized maximal t test (PMT) is proposed for detecting undocumented mean shifts in climate data series. PMT takes the relative position of each candidate changepoint into account, to diminish the effect of unequal sample sizes on the power of detection. Monte Carlo simulation studies are conducted to evaluate the performance of PMT, in comparison with the most popularly used method, the standard normal homogeneity test (SNHT). An application of the two methods to atmospheric pressure series recorded at a Canadian site is also presented. It is shown that the false-alarm rate of PMT is very close to the specified level of significance and is evenly distributed across all candidate changepoints, whereas that of SNHT can be up to 10 times the specified level for points near the ends of series and much lower for the middle points. In comparison with SNHT, therefore, PMT has higher power for detecting all changepoints that are not too close to the ends of series and lower power for detecting changepoints that are near the ends of series. On average, however, PMT has significantly higher power of detection. The smaller the shift magnitude Δ is relative to the noise standard deviation σ, the greater is the improvement of PMT over SNHT. The improvement in hit rate can be as much as 14%–25% for detecting small shifts (Δ < σ) regardless of time series length and up to 5% for detecting medium shifts (Δ = σ–1.5σ) in time series of length N < 100. For all detectable shift sizes, the largest improvement is always obtained when N < 100, which is of great practical importance, because most annual climate data series are of length N < 100.

scholarly journals Simulating rainfall IDF curve for flood warnings in the Ca Mau coastal area under the impacts of climate change

2020 ◽  
Vol 12 (5) ◽  
pp. 705-715
Author(s):  
Seung Kyu Lee ◽  
Truong An Dang
Keyword(s):  
Return Period ◽  
Extreme Rainfall ◽  
Rainfall Data ◽  
Data Series ◽  
Homogeneity Test ◽  
Content Type ◽  
Pettitt Test ◽  
Standard Normal Homogeneity Test ◽  
Intensity Duration Frequency ◽  
The Right

Purpose The purpose of this study is to evaluate the rainfall intensities and their limits for durations from 0.25 to 8 h with return periods from 2 to 100 years for Ca Mau City in Vietnam. Design/methodology/approach First, the quality of the historical rainfall data series in 44 years (1975–2018) at Ca Mau station was assessed using the standard normal homogeneity test and the Pettitt test. Second, the appraised rainfall data series are used to establish the rainfall intensity-duration-frequency curve for the study area. Findings Based on the findings, a two-year return period, the extreme rainfall intensities (ERIs) ranged from 9.1 mm/h for 8 h rainstorms to 91.2 mm/h for 0.25 h. At a 100-year return period, the ERIs ranged from 18.4 mm/h for 8 h rainstorms to 185.8 mm/h for 0.25 h. The results also show that the narrowest uncertainty level between the lower and upper limits recorded 1.6 mm at 8 h for the two-year return period while the widest range is at 42.5 mm at 0.25 h for the 100-year return period. In general, the possibility of high-intensity rainfall values compared to the extreme rainfall intensities is approximately 2.0% at the 100-year return period. Originality/value The results of the rainfall IDF curves can provide useful information for policymakers to make the right decisions in controlling and minimizing flooding in the study area.

VARIABILIDAD CLIMÁTICA, CAMBIO CLIMÁTICO Y PESQUERÍAS EN EL ECUADOR.

2012 ◽  
Vol 1 (1) ◽  
Author(s):  
Johnny Chavarría Viteri ◽  
Dennis Tomalá Solano
Keyword(s):  
Climate Change ◽  
Climate Variability ◽  
Pacific Decadal Oscillation ◽  
El Niño ◽  
El Nino ◽  
Southern Oscillation ◽  
El Niño Southern Oscillation ◽  
El Nino Southern Oscillation ◽  
Current Action ◽  
Palabras Clave

La variabilidad climática es la norma que ha modulado la vida en el planeta. Este trabajo demuestra que las pesquerías y acuicultura costera ecuatorianas no son la excepción, puesto que tales actividades están fuertemente influenciadas por la variabilidad ENSO (El Niño-Oscilación del Sur) y PDO (Oscilación Decadal del Pacífico), planteándose que la señal del cambio climático debe contribuir a esta influencia. Se destaca también que, en el análisis de los efectos de la variabilidad climática sobre los recursos pesqueros, el esfuerzo extractivo también debe ser considerado. Por su parte, la acción actual de la PDO está afectando la señal del cambio climático, encontrándose actualmente en fases opuestas. Se espera que estas señales entren en fase a finales de esta década, y principalmente durante la década de los 20 y consecuentemente se evidencien con mayor fuerza los efectos del Cambio Climático. Palabras Clave: Variabilidad Climática, Cambio Climático, ENSO, PDO, Pesquerías, Ecuador. ABSTRACT Climate variability is the standard that has modulated life in the planet. This work shows that the Ecuadorian  fisheries and aquaculture are not the exception, since such activities are strongly influenced by ENSO variability (El Niño - Southern Oscillation) and PDO (Pacific Decadal Oscillation), considering that the signal of climate change should contribute to this influence. It also emphasizes that in the analysis of the effects of climate variability on the fishing resources, the extractive effort must also be considered. For its part, the current action of the PDO is affecting the signal of climate change, now found on opposite phases. It is hoped that these signals come into phase at the end of this decade, and especially during the decade of the 20’s and more strongly evidencing the effects of climate change. Keywords: Climate variability, climate change, ENSO (El Niño - Southern Oscillation) and PDO  (Pacific Decadal Oscillation); fisheries, Ecuador. Recibido: mayo, 2012Aprobado: agosto, 2012

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