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. 2011 Jan 17:10:12.
doi: 10.1186/1475-2875-10-12.

Raised temperatures over the Kericho tea estates: revisiting the climate in the East African highlands malaria debate

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Raised temperatures over the Kericho tea estates: revisiting the climate in the East African highlands malaria debate

Judith A Omumbo et al. Malar J. .

Abstract

Background: Whether or not observed increases in malaria incidence in the Kenyan Highlands during the last thirty years are associated with co-varying changes in local temperature, possibly connected to global changes in climate, has been debated for over a decade. Studies, using differing data sets and methodologies, produced conflicting results regarding the occurrence of temperature trends and their likelihood of being responsible, at least in part, for the increases in malaria incidence in the highlands of western Kenya. A time series of quality controlled daily temperature and rainfall data from Kericho, in the Kenyan Highlands, may help resolve the controversy. If significant temperature trends over the last three decades have occurred then climate should be included (along with other factors such as land use change and drug resistance) as a potential driver of the observed increases in malaria in the region.

Methods: Over 30 years (1 January 1979 to 31 December 2009) of quality controlled daily observations ( > 97% complete) of maximum, minimum and mean temperature were used in the analysis of trends at Kericho meteorological station, sited in a tea growing area of Kenya's western highlands. Inhomogeneities in all the time series were identified and corrected. Linear trends were identified via a least-squares regression analysis with statistical significance assessed using a two-tailed t-test. These 'gold standard' meteorological observations were compared with spatially interpolated temperature datasets that have been developed for regional or global applications. The relationship of local climate processes with larger climate variations, including tropical sea surface temperatures (SST), and El Niño-Southern Oscillation (ENSO) was also assessed.

Results: An upward trend of ≈0.2°C/decade was observed in all three temperature variables (P < 0.01). Mean temperature variations in Kericho were associated with large-scale climate variations including tropical SST (r = 0.50; p < 0.01). Local rainfall was found to have inverse effects on minimum and maximum temperature. Three versions of a spatially interpolated temperature data set showed markedly different trends when compared with each other and with the Kericho station observations.

Conclusion: This study presents evidence of a warming trend in observed maximum, minimum and mean temperatures at Kericho during the period 1979 to 2009 using gold standard meteorological observations. Although local factors may be contributing to these trends, the findings are consistent with variability and trends that have occurred in correlated global climate processes. Climate should therefore not be dismissed as a potential driver of observed increases in malaria seen in the region during recent decades, however its relative importance compared to other factors needs further elaboration. Climate services, pertinent to the achievement of development targets such as the Millennium Development Goals and the analysis of infectious disease in the context of climate variability and change are being developed and should increase the availability of relevant quality controlled climate data for improving development decisions. The malaria community should seize this opportunity to make their needs heard.

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Figures

Figure 1
Figure 1
Average monthly climate conditions at Kericho for the period 1980-2009 a) lines indicate monthly average temperature (deg. C) Tx (left axis) and Tn (right axis) b) bars indicate average monthly rainfall (mm/day, left axis).
Figure 2
Figure 2
Time series of monthly values of Tx after removing seasonality (i.e., the 30-year mean values shown in Figure 1) (deg. C) for a) original data, also showing model fit, and b) adjusted data after removing an identified break-point and including seasonality. The linear trend for the full data period is shown by the solid line (see Table 1 for slope and significance).
Figure 3
Figure 3
Time series of monthly values of Tn after removing seasonality (i.e., the 30-year mean values shown in Figure 1) (deg. C) for a) original data, also showing model fit, and b) adjusted data after removing two identified break-points and including seasonality. The linear trend for the full data period is shown by the solid line (see Table 1 for slope and significance).
Figure 4
Figure 4
Time series of monthly departures from 1980-2009 mean values (deg. C) with an 11-month moving average applied for Kericho Tmean (green line), global tropical SST (25S-25N) (red line) and tropical land area mean temperature (blue line). Color bars at the bottom of the figure show the occurrence of El Niño and La Niña events (based on the definition in use at the US Climate Prediction Center). See Table 2 for temporal correlations between these variables
Figure 5
Figure 5
Time series of monthly departures from 1980-2009 mean values (deg. C) with an 11-month moving average applied for Kericho a) Tn and b) Tx (green line), global tropical SST (25S-25N) (red line) and tropical land area mean temperature (blue line). Color bars at the bottom of the figure show the occurrence of El Niño and La Niña events (based on the definition in use at the US Climate Prediction Center). See Table 2 for temporal correlations between these variables
Figure 6
Figure 6
Schematic of the relationship between Tx and Tn with unusually dry conditions (left), rainy conditions (center) and in relationship to tropics-wide warming or cooling associated with El Niño or La Niña (right).
Figure 7
Figure 7
Number of stations reporting temperature observations (a) and rainfall observations (b) in UEA CRU v2.1 that are within the "radius of influence" of the grid point closest to the Kericho station. Monthly values, 1920-2002.
Figure 8
Figure 8
Time series (1920-2002) of Tn (a) and Tx (b) of the departures from the 1971-2000 average monthly values (an 11-month moving average applied) for versions 2.1 and interim 3.0 of the UEA CRU data and the gridpoint closest to the Kericho station location. The temporal correlation between the two series is shown in the upper-left of both panels.
Figure 9
Figure 9
Time series of Tn based on versions CRU05 and v2.1 of the UEA CRU data for the period 1970 to 1995 (CRU05) and 2002 (v.2.1). Best-fit linear regressions are shown as dashed lines for the two versions, which show marked differences.

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