Variability of diurnal temperature range over Pacific Island countries, a case study of Fiji

Ongoma, Victor; Rahman, Mohammad Atiqur; Ayugi, Brian; Nisha, Fhereen; Galvin, Stephen; Shilenje, Zablon W.; Ogwang, Bob Alex

doi:10.1007/s00703-020-00743-4

Cited by 29 publications

(19 citation statements)

References 40 publications

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“…The method was considered to be effective since it is not influenced by any extreme distribution and does not entail any normal distribution of the residuals. Numerous studies have utilized this approach to examine the linear tendencies of hydroclimatic variables across various domains (Wang et al 2018;Mumo et al 2019;Ongoma et al 2020). Mathematical expression explaining this approach is presented as follows:…”

Section: Trend Analysismentioning

confidence: 99%

Assessing current and future spatiotemporal precipitation variability and trends over Uganda, East Africa, based on CHIRPS and regional climate model datasets

Ngoma

Wang

Ojara

et al. 2021

Meteorol Atmos Phys

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The lack of reliable rainfall projection records remains a major challenge to Uganda. In the advent of extreme wetness or drought events, reliable rainfall estimates for local planning and adaptation are essential. The present study used two main datasets to conduct a historical analysis from 1981 to 2019, coupled with future projections under representative concentration pathway (RCP 8.5) for the period 2020-2050. Historical analysis revealed bimodal annual rainfall pattern for March-May (MAM) and September-November (SON) gradients representing heavier to lighter rainfall events respectively over the study area. Investigation of recent trends in rainfall patterns revealed an upward trend from 2010 onwards in annual and seasonal rainfall. Moreover, results for future projections show wet conditions are projected to occur over the study area between the months of April/May and October. Contrarily, March is likely to experience a reduction in wet conditions. Mann-Kendall test employed to make future projections of rainfall depicted decreasing patterns during MAM season whilst increasing tendencies with strong shift was highlighted for SON season over the study region. Meanwhile, annual projections indicate huge variations with linear trends showing a marginal increase as compared to historical trends. Findings would serve as baseline print to propel further studies

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Section: Trend Analysismentioning

confidence: 99%

Assessing current and future spatiotemporal precipitation variability and trends over Uganda, East Africa, based on CHIRPS and regional climate model datasets

Ngoma

Wang

Ojara

et al. 2021

Meteorol Atmos Phys

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“…Besides, the spatio-temporal trends and the significance were calculated using previously mentioned statistical techniques. A number of studies have employed a similar approach to verify the robustness of the moddels in characterizing climatic trends over diverse regions (Ongoma et al, 2020;Tadeyo et al, 2020;Karim et al, 2020). This study also focused on uncertainties in the projections of mean temperature and quantify them in the form of probability density function (PDF).…”

Section: Future Projection Datasets and Data Analysismentioning

confidence: 99%

Evaluation and projection of mean surface temperature using CMIP6 models over East Africa

Ayugi

Ngoma

Babaousmail

et al. 2021

Journal of African Earth Sciences

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This study evaluates the historical mean surface temperature (hereafter T2m) and examines how T2m changes over East Africa (EA) in the 21 st century using CMIP6 models. An evaluation was conducted based on mean state, trends, and statistical metrics (Bias, Correlation Coefficient, Root Mean Square Difference, and Taylor skill score). For future projections over EA, five best performing CMIP6 models (based on their performance ranking in historical mean temperature

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“…where A is the anomaly, X is the season and X is the seasonal mean: This method has been widely used in recent studies (e.g., Asamoah and Ansah-Mensah, 2020;Ongoma et al, 2021;Ngoma et al, 2021a;. The monotonic trend magnitude and detection of abrupt change are tested using Sen Slope Estimator (Sen, 1968) and sequential Mann-Kendall (SQMK;Mann, 1945;Kendall, 1975;Hamed and Rao, 1998) test, respectively.…”

Section: Observed Changes and Trendsmentioning

confidence: 99%

Observed and Coupled Model Intercomparison Project 6 multimodel simulated changes in near‐surface temperature properties over Ghana during the 20th century

Oduro

Ayugi

et al. 2021

Intl Journal of Climatology

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This article investigates seasonal and annual trends of near-surface temperature (NST) during the last century over Ghana. The ability of 24 global climate models (GCMs) from the sixth phase of the Coupled Model Intercomparison Project (CMIP6) to simulate abrupt mean temperature changes in Ghana from 1980 to 2014 was assessed. The trends' magnitude and abrupt changes were detected using Sen Slope Estimator (SSE) and sequential Mann-Kendall (SQMK) tests, respectively. Root mean square difference, correlation coefficient, and mean bias (B) were used to determine the skilfulness of GCMs in simulating NST relative to Climatic Research Unit (CRU TS4.04) datasets. Ghana's Southern belt is characterized by low temperatures, averaging 25 C to 27 C, whilst the northern belt is characterized by high temperatures (29-31 C). The inter-annual variability of temperature over Ghana exhibits an increasing trend. Findings depict a significant increase in both the annual and seasonal temperatures of Tmin and Tmean, with a steady increase in Tmax. Results revealed the rate of increase had been higher in the country's northern regions (0.5 C) than in the south (0.3-0.4 C) in recent decades. The model performances for the interannual variability of annual and FMAM temperatures are better than their JJAS seasonal performances. The study's overall model ranking shows that Ghana's best performing models for annual, FMAM and JJAS seasons are INM-CM5-0, NorCPM1, and KACE-1-0-G, respectively. Observations and comparisons provide useful reference values for a comprehensive assessment of various applications.

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Variability of diurnal temperature range over Pacific Island countries, a case study of Fiji

Cited by 29 publications

References 40 publications

Assessing current and future spatiotemporal precipitation variability and trends over Uganda, East Africa, based on CHIRPS and regional climate model datasets

Assessing current and future spatiotemporal precipitation variability and trends over Uganda, East Africa, based on CHIRPS and regional climate model datasets

Evaluation and projection of mean surface temperature using CMIP6 models over East Africa

Observed and Coupled Model Intercomparison Project 6 multimodel simulated changes in near‐surface temperature properties over Ghana during the 20th century

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