The Impact of Human‐Induced Climate Change on Regional Drought in the Horn of Africa

Abstract

A severe drought hit the Greater Horn of Africa (GHA) in 2014, but it remains unclear whether this extreme event was attributable to anthropogenic climate change or part of longer‐term natural cycles. Precipitation patterns are known to be changing across the GHA, but trajectories in land surface variables are much less well known. We simulated the GHA land surface environment to assess the balance between natural cycles and human‐induced climate change. Using a new form of event attribution study where we focused on both climate variables and also directly simulated land surface variables, we combined publicly volunteered distributed computing with land surface simulations to quantify land surface responses. Uncertainty was quantified both for climate model and land surface model outputs. We identified two distinct “drought trajectories” in the GHA bimodal seasonality area during the March–May (Long Rains season) of 2014. Human‐induced climate change may have resulted in regions from Lake Nalubaale (Lake Victoria) to Northern Kenya receiving less precipitation in this season and having up to 20% higher probability of drought‐level evapotranspiration rates (increasing drought). In contrast, the simulated anthropogenic climate change signal for this season induced somewhat wetter conditions and up to 20% lower probability of drought‐level evapotranspiration in Eastern Ethiopia, Southern Somalia, and coastal Kenya (decreasing drought). Uncertainties in our modeling system varied by region and variable of focus, but broadly we found that land surface simulation uncertainty neither added significantly to climate model uncertainty nor significantly reduced it.

A global-scale evaluation of extreme event uncertainty in the <i>eartH2Observe</i> project

“…Under what circumstances can uncertainty in the prediction of water cycle quantities be attributed clearly to the model in use (model uncertainty) and/or to the pre- Table 1. Types of precipitation and their main controlling factors (McGregor and Nieuwolt, 1998).…”

“…Data products are known to be more accurate away from areas with consistent cloud cover and a high occurrence of convective rainfall (Table 1) (Derin et al, 2016;Levizzani et al, 2018), which might explain this for data uncertainty, but having model uncertainty follow the same geographic distribution indicates that we must also consider uncertainties in the calculations of runoff and evapotranspiration. It seems also to be the case that the simple water balance approach taken by land surface and hydrology models becomes approximate in latitudinal zones where low flows are generally combined with higher temperatures and more episodic rainfall events (McGregor and Nieuwolt, 1998). This could indicate that using generalised approaches for all environments (e.g.…”

Inundation prediction in tropical wetlands from JULES-CaMa-Flood global land surface simulations

“…There has recently been significant progress in our understanding of wetlands and the roles they play in climate processes, land surface processes and their impacts on human society (IPCC, 2014;Mitsch and Gosselink, 2015;Moomaw et al, 2018;Saunois et al, 2020). However, even though the physics of flood inundation is relatively well-known (Bates et al, 2010;Fassoni-Andrade et al, 2018;Yamazaki et al, 2013), many hydrological processes relevant to the representation of flooding in Earth system models remain poorly characterised at the high resolutions required to address issues of local and regional impact (Bierkens, 2015;Clark et al, 2015;Marthews et al, 2019;Zhou et al, in prep. 2020), including infiltration (Clark et al, 2015;d'Orgeval et al, 2008), and evaporation (d'Orgeval et al, 2008;Robinson et al, 2017) of flood waters, as well as groundwater effects (Clark et al, 2015).…”

“…Seasonally-varying levels of inundation are primarily dependent on upstream precipitation and how this translates into these two forms of inflow, and secondarily on the ambient rates of evaporation and infiltration (Clark et al, 2015;d'Orgeval et al, 2008;Marthews et al, 2019). Further classification of wetlands in terms of vegetation or substrate is not required for our study (but see Wheeler and Shaw (1995), USEPA (2002), Gerbeaux et al (2018) and Ramsar (2016)).…”

“…as found by Parker et al (2018) for the process of overbank inundation). The storage and conveyance of water in lakes, floodplains, groundwater and river channels, especially, is generally simulated only with relatively high uncertainty in the current generation of land surface models (LSMs) (Marthews et al, 2020;Marthews et al, 2019).…”