Recent Rainfall Trend and Abrupt Changes Over Cavally Basin (West Africa)

Aims: Analyze the recent variations in annual and monthly precipitation at 18 pluviometry stations in the Cavally river basin. Place and Duration of Study: Data of month and annual rainfall data of 37 years (1980-2016) collected from the National direction of Meteorology for Ivory Coast and Guinea and from https://app.climateengine.org/climateEngine for Liberia. Methodology: Statistical methods are used to highlight the evolution of cumulative annual rainfall and the distribution of the different seasons over the period 1980-2016. Hanning’s low pass, Mann-Kendall classic test, modified Mann-Kendall test, Mann-Kendall seasonal test and Standard Normal Homogeneity Test were applied to identify the existing trend direction and significance of change over time. Results: The periods 1980-1996 and 1997-2016 could be considered as wet and dry periods respectively (with a rainfall deficit of 18% after the break in 1996). In addition, we observe a decrease in rainy days of strong accumulation that lead to a significant drop in total annual rainfall. Finally, an abnormal increase in rainfall during the dry season months and a decrease in rainfall during the rainy season months. This indicates an intra-seasonal irregularity (shortening of the rainy season and prolongation of the dry season) of precipitation. Conclusion: The Hanning filter, M-K test and SNHT are non-parametric tests widely used in the study of climate trends. However, the additional consideration of serial autocorrelation (MM-K test) and seasonal trends (M-K-S test) allows to extend and refine the information on climate variability.

Inhomogeneity detection in the rainfall series for the Mae Klong River Basin, Thailand

An accurate and complete rainfall record is prerequisite for climate studies. The purpose of this research study was to evaluate the homogeneity of the rainfall series for the Mae Klong River Basin in Thailand. Monthly rainfall data of eight stations in the Mae Klong River Basin for the period 1971–2015 were used. The double mass curve analysis was used to check the consistency of rainfall data, whereas the absolute homogeneity was assessed using the Pettitt test, standard normal homogeneity test, Buishand test, and von Neumann test at a 5% significance level. The results of these tests were qualitatively classified as ‘useful’, ‘doubtful’, and ‘suspect’ according to the null hypothesis. Results of the monthly time series indicated the rainfall data as ‘useful’ for 75% of the stations, while two stations’ data were classified as ‘doubtful’ (Stn130221) and ‘suspect’ (Stn376401). On an annual scale, seven out of eight stations data were classified as ‘useful,’ while one station (Stn376401) data were classified as ‘suspect’. Double mass curve analysis technique was used for the adjustment of inhomogeneous data. The results of this study can help provide reliable rainfall data for climate studies in the basin.

APPLICATION OF PRINCIPAL COMPONENT ANALYSIS TO DROUGHT INDICATORS OF THREE REPRESENTATIVE CROATIAN REGIONS

Drought has become a very frequent hydrological event globally, including in Croatia. It can generally be explained by air temperature and precipitation changes on an annual and seasonal basis, owing to climate change. To contribute to the knowledge on drought phenomena in Croatia, the changes in air temperature and precipitation over a relatively long period between 1951 and 2018 were analyzed. The meteorological stations included in the research were Osijek, Zagreb, and Split, which represented the climate of the entire country. Drought was estimated using the standardized precipitation evapotranspiration index, which is one of the most comprehensive drought indices. Furthermore, the drought severity and duration were calculated using run theory. These parameters were tested for homogeneity using the standard normal homogeneity test. Only the air temperature exhibited inhomogeneity, with a break year in 1991 (Zagreb and Split) and 1998 (Osijek). The existence of significant temporal trends was tested using the non-parametric Mann–Kendall trend test. The probability of drought occurrence with a certain duration and severity was calculated using the copula function. Finally, principal component analysis was applied to the computed standardized Mann–Kendall test statistic (ZMK ) to define the relevance of each parameter change and their combination in drought occurrence on a seasonal basis. Drought occurrence was less recognizable from 1951 to 1991 (1998). In the second sub-period, the impact of an increasing air temperature was the most significant variable, particularly in Zagreb.

Redefining Homogeneous Climate Regions in Bangladesh Using Multivariate Clustering Approaches

The knowledge of the climate pattern for a particular region is important to alleviate the impact of climate change and protect the environment by taking appropriate actions based on geographical knowledge. It is also equally important for water resources planning and management. In this study, the regional disparities and similarities have been revealed among different climate stations or regions in Bangladesh based on different climatological factors such as rainfall, temperatures, relative humidity, sea level pressure, cloud cover, wind speed, the sunshine hour. We have selected one of the best-fitted algorithms for particular climate data from three multivariate clustering approaches named hierarchical clustering, partitioning around medoids (PAM), and K-means clustering by using different validation tests. Four homogeneity tests (Mann-Kendall Test, Pettitt's test, Buishand Range Test, Standard Normal Homogeneity Test) also have been performed for each of the clusters created based on several factors. The results suggest that the climate regions or meteorological stations of Bangladesh can be clustered into two groups based on a combination of climatological variables. According to the findings, there is a huge variation between the two groups in terms of climatological factors. The first group (cluster 1) is located in the northern part of the country that includes drought-prone and vulnerable regions, whereas, the second group (cluster 2) contains rain-prone and hilly regions, which are mostly situated in the southern part. All newly defined clusters show homogeneous behavior with few exceptions such as clusters based on sea level pressure are not homogeneous.

Time Series Analysis of Monthly and Annual Precipitation in The State of Texas Using High-Resolution Radar Products

Precipitation is the main source for replenishing groundwater stored in aquifers for a myriad of beneficial purposes, especially in arid and semi-arid regions. A significant portion of the municipal and agricultural water demand is satisfied through groundwater withdrawals in Texas. These withdrawals have to be monitored and regulated to be in balance with the recharge amount from precipitation in order to ensure water security. The main goal of this study is to understand the spatio-temporal variability of precipitation in the 21st century using high spatial resolution stage-IV radar data over the state of Texas and examine some climatic controls behind this variability. The results will shed light on the trends of precipitation and hence will contribute to improving water resources management strategies and policies. Pettit’s test and Standard Normal Homogeneity Test (SNHT), tools for detecting change-point in the monthly precipitation, suggested change-points have occurred across the state around the years 2013 and 2014. The test for the homogeneity of the data before and after 2013 revealed that, in over 64% of the state, the precipitation means were significantly different. The Panhandle region (northern part) is the only part of the state that did not show a significant difference in the mean precipitation before and after 2013. Theil-Sen’s slope test, Correlated Seasonal Mann-Kendall Test, and Cox and Stuart Trend Test all indicated that there were no significant trends in the monthly precipitation after 2013 in over 98% of the area of the state. Texas precipitation was found to be influenced significantly by the El Niño-Southern Oscillation (ENSO) and the Pacific Decadal Oscillation (PDO). A significant correlation in more than 82% and 60% of the state was found with ENSO at two-month and with PDO at four-month lag, respectively.

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

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.

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

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.

Temporal Trend Analysis of Meteorological Variables and Reference Evapotranspiration in the Inter-mountain Region of Wyoming

Long-term trends in reference evapotranspiration (ETref) and its controlling factors are critical pieces of information in understanding how agricultural water requirements and water resources respond to a variable and changing climate. In this study, ETref, along with climate variables that directly and indirectly impact it, such as air temperature (T), incoming solar radiation (Rs), wind speed (u), relative humidity (RH), and precipitation (P), are discussed. All variables are analyzed for four weather stations located in irrigated agricultural regions of inter-mountain Wyoming: Pinedale, Torrington, Powell, and Worland. Non-parametric Mann−Kendall (MK) trend test and Theil–Sen’s slope estimator were used to determine the statistical significance of positive or negative trends in climate variables and ETref. Three non-parametric methods—(i) Pettitt Test (PT), (ii) Alexandersson’s Standard Normal Homogeneity Test (SNHT), and (iii) Buishand’s Range Test (BRT)—were used to check the data homogeneity and to detect any significant Trend Change Point (TCP) in the measured data time-series. For the data influenced by serial correlation, a modified version of the MK test (pre-whitening) were applied. Over the study duration, a statistically significant positive trend in maximum, minimum, and average annual temperature (Tmax, Tmin, and Tavg, respectively) was observed at all stations, except for Torrington in the southeast part of Wyoming, where these temperature measures had negative trends. The study indicated that the recent warming trends are much more pronounced than during the 1930s Dust Bowl Era. For all the stations, no TCPs were observed for P; however, significant changes in trends were observed for Tmax and Tmin on both annual and seasonal timescales. Both grass and alfalfa reference evapotranspiration (ETo and ETr) had statistically significant positive trends in at least one season (in particular, the spring months of March, April, and May (MAM) or summer months of June, July, and August (JJA) at all stations, except the station located in southeast Wyoming (Torrington) where no statistically significant positive trends were observed. Torrington instead experienced statistically significant negative trends in ETo and ETr, particularly in the fall months of SON and winter months of DJF. Over the period-of-record, an overall change of +26, +31, −48, and +34 mm in ETo and +28, +40, −80, and +39 mm in ETr was observed at Pinedale, Powell, Torrington, and Worland, respectively. Our analysis indicated that both ETo (−3.4 mm year−1) and ETr (−5.3 mm year−1) are decreasing at a much faster rate in recent years at Torrington compared to other stations. Relationships between climate variables and ETo and ETr on an annual time-step reveal that ETo and ETr were significantly and positively correlated to Tavg, Tmax, Rs, Rn, and VPD, as well as significantly and negatively correlated to RH.

Assessing Inhomogeneities in Extreme Annual Rainfall Data Series by Multifractal Approach

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.