Climate Indices and Measurements Application for Agrometeorological Services in Kenya

Determination of climate variability and change for agriculture define necessity to map tropical relevant indices and carry out meteorological measurements capable for agrometeorological services. In this study ERA5 reanalysis data were used to characterise precipitation and climate based indices spatial patterns from 1991 to 2020 (30 years) climate normal. In our study, five precipitation-based and two temperature-based climate indices were analysed and visualised based on their agricultural importance and tropical position of Kenya. They include annual total wet day (PRCP), consecutive dry days (CDD), consecutive wet days (CWD), very wet days (R95P), extremely wet days (R99P), summer days (SU35) and diurnal temperature range (DTR). ERA5 data was pre-processed in climate data operator (CDO).The resultant network common data Form (NetCDF) generated from CDO were visualized in own python programme to obtain spatial pattern distribution maps. In addition, high-quality temperature, humidity and soil moisture data measurements were carried out in from 2023. Trends, variation  and correlations for the measurements were analysed and compared using different regression methods, ordinary least squares (OLS) and Theil-Sen regression. Results indicate average S35 of between 260.7 to 365 days in arid Northwestern Kenya in the 2011-2020 decade. Most parts of the country show average DTR between 10 °C to 12 °C while mean annual average CDD ranged between 0 (minima) to 300 days per decade with Kenyan highlands and coastal strip recording 0 to 60 days. Higher number of CWD were observed with an average between 219 to 292 per decade in highlands. However, spatial distribution patterns and the changes in the extreme events are inconsistent from one decade to the other. Increasing CDD and decreasing CWD is a constraint to crop yield and maturity and determinants to crop developmental stages. The risk of reduced yields can be monitored. Meteorological and soil moisture preliminary results indicate variability between seasons. Comparison of temperature (2m) and temperature from the soil moisture sensor from two different elevations and depths reveal a partly linear and  heteroscedastic pattern. Regression models produced similarities in behavioural patterns of measurements from the two elevations. Soil moisture deficiency informs irrigation requirements (IRR), a strategy for crop's evapotranspiration and optimal yields. Further, the measurements act as a reference for comparison with nearby weather station measurements as well as gridded datasets for better understanding of quality control. Overall, the results demonstrates importance of quality measurements and indices analysis for agrometeorological services for farmers during cropping and irrigation seasons and monitoring of agricultural yields in Kenya.

Keywords: Agriculture, Climate indices, Measurements, Services, Soil moisture, Kenya