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Spatio-temporal evolution of surface temperature trends in Ghana (1983-2021): a multi-station approach

John Bagiliko, David Stern, Denis Ndanguza

Abstract

Surface temperature is a fundamental Essential Climate Variable, serving as a primary indicator of climate change and exerting a profound influence on ecosystems, agriculture, and human livelihoods. Although existing research provides a foundation for understanding the climate of Ghana, there remains an opportunity to enhance this landscape with granular station-level analysis. Such high-resolution analysis complements existing studies by capturing localised climatic nuances. This study conducts a detailed spatio-temporal analysis of temperature trends across 22 meteorological stations from 1983 to 2021. Using daily maximum (Tmax) and minimum (Tmin) observations, data were subjected to quality control, homogeneity testing, and homogenisation according to World Meteorological Organisation (WMO) standards, using AgERA5 reanalysis as a reference.The significance and magnitude of trends were determined using the Modified Mann-Kendall test, which is robust in handling potential effects of autocorrelation, and Sen's slope estimator. Results revealed that temperature trends in Ghana are highly localised and seasonal, highlighting the necessity for more studies of this nature. A critical finding is the asymmetric warming across the country, with minimum temperatures rising at an accelerated rate compared to maximum temperatures. This narrowing of the diurnal temperature range poses significant threats to agricultural stability and public health because nocturnal cooling is diminished. These findings underscore the urgent need for site-specific, seasonal climate monitoring to inform customised adaptation strategies. To mitigate these impacts, the study recommends a robust policy framework focusing on afforestation and the transition to green energy.

Spatio-temporal evolution of surface temperature trends in Ghana (1983-2021): a multi-station approach

Abstract

Surface temperature is a fundamental Essential Climate Variable, serving as a primary indicator of climate change and exerting a profound influence on ecosystems, agriculture, and human livelihoods. Although existing research provides a foundation for understanding the climate of Ghana, there remains an opportunity to enhance this landscape with granular station-level analysis. Such high-resolution analysis complements existing studies by capturing localised climatic nuances. This study conducts a detailed spatio-temporal analysis of temperature trends across 22 meteorological stations from 1983 to 2021. Using daily maximum (Tmax) and minimum (Tmin) observations, data were subjected to quality control, homogeneity testing, and homogenisation according to World Meteorological Organisation (WMO) standards, using AgERA5 reanalysis as a reference.The significance and magnitude of trends were determined using the Modified Mann-Kendall test, which is robust in handling potential effects of autocorrelation, and Sen's slope estimator. Results revealed that temperature trends in Ghana are highly localised and seasonal, highlighting the necessity for more studies of this nature. A critical finding is the asymmetric warming across the country, with minimum temperatures rising at an accelerated rate compared to maximum temperatures. This narrowing of the diurnal temperature range poses significant threats to agricultural stability and public health because nocturnal cooling is diminished. These findings underscore the urgent need for site-specific, seasonal climate monitoring to inform customised adaptation strategies. To mitigate these impacts, the study recommends a robust policy framework focusing on afforestation and the transition to green energy.
Paper Structure (17 sections, 13 equations, 17 figures)

This paper contains 17 sections, 13 equations, 17 figures.

Table of Contents

  1. Introduction
  2. Materials and methods
  3. Study Area
  4. Data and quality control
  5. Homogeneity test and homogenisation
  6. Autocorrelation adjustment and trend estimation
  7. Results
  8. Homogeneity Test Results
  9. Spatio-temporal analysis of temperature trends
  10. Discussion
  11. Conclusion
  12. Homogeneity tests definitions
  13. The Standard Normal Homogeneity Test (SNHT)
  14. Pettitt Test (PT)
  15. Buishand's tests
  16. ...and 2 more sections

Figures (17)

  • Figure 1: Physical and climatic characteristics of the study area in Ghana. Climatic zoning is defined according to Bessah2022, with topographical elevations derived from the Shuttle Radar Topography Mission (SRTM) Digital Elevation Model Farr2007
  • Figure 2: Ombrothermic diagrams of the stations considered in the study. The bars show the mean monthly total rainfall values while the line plots show the mean Tmax (red) and mean Tmin (orange). The rainfall scale $=$ temperature scale $\times$ 10
  • Figure 3: Homogeneity test results for the annual DTR series across all stations. Values represent test statistics and associated p-values
  • Figure 4: A map showing the homogeneity test results for the annual DTR series across all stations. Green points represent "Useful" stations, oranges "Suspect" stations, while red points with an X on them represent "Suspect" stations. The size of the points depicts, in the reverse order, the number of tests that rejected $H_{o}$
  • Figure 5: A map showing the homogeneity test results for the monthly DTR series across all stations. Green points represent "Useful" stations, oranges "Suspect" stations, while red points with an X on them represent "Suspect" stations. The size of the points depicts, in the reverse order, the number of tests that rejected $H_{o}$
  • ...and 12 more figures