Attributing drivers of the 2016 Kenyan drought

• Published in: International journal of climatology 2018-04, Vol.38 (S1), p.e554-e568
• Main Authors: Uhe, Peter, Philip, Sjoukje, Kew, Sarah, Shah, Kasturi, Kimutai, Joyce, Mwangi, Emmah, van Oldenborgh, Geert Jan, Singh, Roop, Arrighi, Julie, Jjemba, Eddie, Cullen, Heidi, Otto, Friederike
• Format: Article
• Language: English
• Subjects: Atmospheric precipitations; attribution; Climate change; Climate change influences; Climate models; Computer simulation; Data processing; Drought; Drought conditions; El Nino; El Nino phenomena; El Nino-Southern Oscillation event; El Niño; Environmental impact; Evaporation; Food aid; High temperature; Hydrologic data; Kenya; La Nina; Livestock; Man-induced effects; Natural variability; Precipitation; Precipitation data; Rain; Rainfall; Sea surface; Sea surface temperature; Soil; Soil moisture; Southern Oscillation; Surface temperature; Temperature (air-sea); Temperature effects; Water resources
• ISSN: 0899-8418; 1097-0088
• DOI: 10.1002/joc.5389

ABSTRACT In 2016 and continuing into 2017, Kenya experienced drought conditions, with over 3 million people in need of food aid due to low rainfall during 2016. Whenever extreme events like this happen, questions are raised about the role of climate change and how natural variability such as the El Niño ‐ Southern Oscillation influenced the likelihood and intensity of the event. Here we aim to quantify the relative contributions of different climate drivers to this drought by applying three independent methodologies of extreme event attribution. Analysing precipitation data for the South East and North West of Kenya we found no consistent signal from human‐induced climate change and thus conclude that it has not greatly affected the likelihood of low rainfall such as in 2016. However, 2016 was a La Niña year and we show that this event was indeed more likely because of the specific sea surface temperatures. There is a trend in temperatures in the region due to climate change that may have exacerbated the effects of this drought. By analysing precipitation minus evaporation and soil moisture, simulated by one climate model only, we did not see a reduction in moisture in simulations in the current climate compared with simulations without climate change. However, there are expected effects of higher temperatures that our simulations do not cover, such as increased demand on water resources and stress on livestock. Although we find no significant influence of climate change on precipitation, we cannot rule out that temperature‐related impacts of drought are linked to human‐induced climate change. A multi‐method attribution of the rainfall in the 2016 Kenyan drought found no conclusive influence on climate change, however, a strong signal from La Niña and Indian Ocean sea surface temperatures. The warming trend in temperature may have also worsened the effects of the drought; however, our model simulations did not show evidence of this through a reduction in soil moisture or precipitation minus evaporation.