Extreme climate events have profound impacts on economies and livelihoods of many regions of the world. In Kenya, the extreme climate events often have strong impacts on agriculture production systems in the Arid and Semi-Arid Lands (ASALs). A small change in the mean climate condition can cause large changes in these production systems. There is a paucity of information on trends in climate and climate extremes in the country. However, a joint World Meteorological Commission for Climatology/World Climate Research Programme (WCPRP) project on climate Variability and Predictability (WMO CCl/CLIVAR) Expert Team (ET) on Climate Change Detection, Monitoring and Indices has defined 27 core climate indices mainly focusing on extreme events which can be derived through the use of RClimDex Software. In this study, therefore, the RClimDex software has been used to derive climate extreme indices for five stations in the ASALs of South-Eastern Kenya based on climate data for the period 1961 to 2009. The objective was to examine trends in these extremes to aid agricultural planning and practice. These indices have shown decreasing trends in annual rainfall, rainfall intensity and consecutive wet days but increasing trends in consecutive dry days. Steady warming patterns were evident in both the maximum and minimum temperature indices. This paper concludes that indeed significant changes in climate extremes are apparent in the ASALs of the country and recommends a re-thinking of planning and practice of rain-fed agriculture in the ASALs of South-Eastern Kenya.
The Arid and Semi-arid Lands (ASALs) of Kenya are characterised by high climatic variability. This is especially manifest in the erratic nature of seasonal rainfall with respect to onset, quantity, distribution and cessation. This constitutes a major constraint to decision making by smallholder farmers, with respect to production management.
The relatively high frequencies and intensities of extreme climate events, particularly drought and floods, are projected to be exacerbated in the light of climate change [
The Kenya Vision 2030 [
The problem of inadequate climate data to enable climate change detection and analysis in the African countries including Kenya continue to inhibit progress in climate vulnerability and impact assessments. Climate indices (indicators of trends) based on extremes can be used as means to communicate climate change impact relations [
In Kenya, a number of indices are used to detect drought and then subsequently monitor and analyse its occurrence. The simplest indices that have been developed only use precipitation data in the calculations. However, no index has been able to describe the trends in form of length of dry spells. The objective of this study, therefore, was to examine trends in extreme precipitation and temperature indices derived from observed rainfall and temperature for Katumani, Makindu, Kitui, Mwingi and Mutomo meteorological stations in the south-eastern ASALs of Kenya. The information on these trends is critical in decision making with regard to agricultural planning and practice. Attempts have been made by some researchers to derive these indices [
Long term daily rainfall, maximum (Tmax) and minimum (Tmin) temperature data for five stations namely Makindu, Katumani, Kitui, (these stations had both rainfall and temperature data), Mutomo and Mwingi (these two stations had only rainfall data) have been used in the study. The ASALs of south eastern Kenya investigated in this study are within the circle indicated in
For rain-fed agriculture economies in ASALs, rainfall is the most important climate element. The dry spell duration indicators have been increasing all over south eastern ASALs of Kenya. Trend of annual total precipitation (PRCPTOT) shows negative slope as depicted in the classical examples for Mwingi and Kitui stations at 5% significant
level (
Heavy precipitation days is represented by a count of the number of days of heavy precipitation of 10 mm (R10), 20 mm (R20) and 30 mm (R30) of rain per day respectively. Trends of decreasing heavy precipitation were evident as indicated in the examples provided for Kitui station at 5% significant level (Figures 6-8).
The “Simple Day Intensity Index for rain” (SDII) is the ratio of annual total rainfall to the number of days during the year when rainfall occurred. A decrease in the rain intensity index can result from an increase in rain days while the total amount of annual rainfall remains relatively unchanged. The decrease can also result from a greater increase (smaller decrease) in the number of rainfall days compared to the increase (decrease) in annual rainfall. Similarly, an increase in this indicator could result from a decrease in rainfall days while the total amount of annual rainfall remains relatively unchanged or from a greater increase (smaller decrease) in the annual rainfall compared to the increase (decrease) in the number of rainfall days. Therefore, on average,
ID | Indicator name | UNITS | |
---|---|---|---|
SU25 | Summer days | Annual count when TX (daily maximum) >25˚C | Days |
TNn | Min Tmin | Monthly minimum value of daily minimum temp | ˚C |
TN10p | Cool nights | Percentage of days when TN < 10th percentile | Days |
TX10p | Cool days | Percentage of days when TX < 10th percentile | Days |
TN90p | Warm nights | Percentage of days when TN > 90th percentile | Days |
TX90p | Warm days | Percentage of days when TX > 90th percentile | Days |
WSDI | Warm spell duration indicator | Annual count of days with at least 6 consecutive days when TX > 90th percentile | Days |
DTR | Diurnal temperature range | Monthly mean difference between TX and TN | ˚C |
SDII | Simple daily intensity index | Annual total precipitation divided by the number of wet days (defined as PR ≥ 1.0 mm) in the year | mm/day |
R10 | Number of heavy precipitation days | Annual count of days when PR ≥ 10 mm | Days |
R20 | Number of very heavy precipitation | days Annual count of days when PR ≥ 20 mm | Days |
R30 | Number of very heavy precipitation days | Annual count of days when PR ≥ 30 mm | Days |
CDD | Consecutive dry days | Maximum number of consecutive days with RR < 1 mm | Days |
CWD | Consecutive wet days | Maximum number of consecutive days with RR ≥ 1 mm | Days |
PRCPTOT | Annual total wet-day precipitation | Annual total PRCP in wet days (PR ≥ 1 mm) | mm |
less daily rain is falling if the index decreases, while more daily rain is falling if the index increases. Trends of decreasing SDII were evident as displayed by the example of Kitui station at 5% significant level (
Plants produce maximum growth when exposed to certain threshold values of day and night temperatures. Cumulative temperature values above certain thresholds (which are crop specific) constitute the “Degree Days” which are the determinants of crop growth and development. High temperatures cause increased respiration, sometimes above the rate of photosynthesis. This means that the products of photosynthesis are being used more rapidly than they are being produced. For growth to occur, photosynthesis must be greater than respiration. On the other hand, low temperatures can result in poor growth. The arid and semi-arid lands of Kenya are generally characterised by high day time temperatures.
Analysed temperature trends indicated that the number of warm days have continued to increase over south eastern Kenya. Analysis of extreme temperature trend revealed that the days are warmer as indicated by the index “summer days” (SUTmax > 25˚C). The examples provided for Katumani and Makindu stations (
An increasing trend of frequency of days with Tmin <10th percentile of daily minimum temperature “cold nights” (TNIOP) was also revealed as depicted in the examples provided for Katumani and Kitui stations (
in the examples for Makindu and Kitui stations (
These indices show decreasing trend in annual rainfall, rainfall intensity, decreasing
number of consecutive wet days and increase of consecutive dry days. Steady warming patterns are evident for both the maximum and minimum temperature indices. The diurnal temperature ranges on the other hand depict decreasing trends.
The results of this study are in a general agreement with those obtained by earlier researchers [
The information is important as it reveals that the climate extremes can be a factor which may contribute to the limitations in the ability of society and the area’s fragile environment to cope with climate extremes. Agriculture planning and practice in these areas would therefore require careful and full mainstreaming of this information at all stages of decision making.
The risks associated with extreme weather/climate events have a great impact on the county’s socio-economic activities. It is, therefore, essential that all parts of Kenya be examined for evidence of changes in these extremes at the smallest (localized) area as possible and their trends documented. The trends, as observed for the ASALS of South-Eastern Kenya, call for a re-thinking of planning and practice of rain-fed agriculture in the rest of the ASALs of the country.
The authors would like to thank the Kenya Meteorological Department for availing the data used in this study. Our sincere gratitude goes to the two anonymous reviewers whose comments considerably improved the manuscript.
Marigi, S.N., Njogu, A.K. and Githungo, W.N. (2016) Trends of Extreme Temperature and Rainfall Indices for Arid and Semi-Arid Lands of South Eastern Kenya. Journal of Geoscience and Environment Protection, 4, 158-171. http://dx.doi.org/10.4236/gep.2016.412012