This study investigates CNT-doped Cu2O thin film deposited by spray pyrolysis technique at a substrate temperature of 100°C. The samples were annealed at temperatures of 200°C and 230°C for 30 minutes. The effect of CNT doping on certain optical properties, such as extinction and absorption coefficients, a refractive index of doped Cu2O thin films were examined. The absorbance of the doped samples increases within the visible range and decreases in the ultraviolet range of the electromagnetic spectrum (EM). Both absorbance and extinction coefficients increased with temperature making the samples a good candidate for use as absorbance layer in device fabrication. In addition, there was an increase in direct bandgap with the increase in CNT concentration of the thin films. The result of the study revealed that CNT doping has a significant effect on the properties of Cu2O.

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Global spatial and annual distribution of surface water vapour density were estimated using 2005-2016 monthly air temperature and relative humidity at 1° ×1° resolution obtained from Era interim and NCEP/NCAR database products. Obtained results from reanalysis were statistically tested using in situ data from Tropospheric Data Acquisition Network (TRODAN) of The Center for Atmospheric Research (CAR). Four seasonal variations of surface water vapour density (winter (DJF), spring (MAM), summer (JJA) and autumn (SON)) was examined. Observed result from the two reanalysis follow similar trends with value from Era interim leading. High values ranges between 50 g/m 2 and 68 g/m 2 were observed in tropical regions and humid subtropical regions. Low values ranges between 8 g/m 2 and 38 g/m 2 were observed in Ice cap, Tundra and arid regions. High warming may be experienced in tropical and subtropical regions, similarly, climate change with alarming rate may be experienced in locations with low values. The annual cycle of surface water vapor density is clearly established from two reanalysis across world classified into twelve regions. The statistical test for the reanalysis present good result with a mean bias error, MBE, root mean square error,

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