Tropical highland environments present substantial challenges for climate projections due to sparse observations, significant local heterogeneity and inconsistent performance of global climate models (GCMs). Moreover, these areas are often densely populated, with agriculture‐based livelihoods sensitive to transient climate extremes not always included in available climate projections. In this context, we present an analysis of observed and projected trends in temperature and precipitation extremes across agroecosystems (AESs) in the northwest Ethiopian Highlands, to provide more relevant information for adaptation. Limited observational networks are supplemented with a satellite‐station hybrid product, and trends are calculated locally and summarized at the adaptation‐relevant unit of the AES. Projections are then presented from GCM realizations with divergent climate projections, and results are interpreted in the context of agricultural climate sensitivities. Trends in temperature extremes (1981–2016) are typically consistent across sites and AES, but with different implications for agricultural activities in the other AES. Trends in temperature extremes from GCM projected data also generally have the same sign as the observed trends. For precipitation extremes, there is greater site‐to‐site variability. Summarized by AES, however, there is a clear tendency towards reduced precipitation, associated with decreases in wet extremes and a tendency towards temporally clustered wet and dry days. Over the retrospective analysis period, neither of the two analysed GCMs captures these trends. Future projections from both GCMs include significant wetting and an increase in precipitation extremes across AES. However, given the lack of agreement between GCMs and observations with respect to trends in recent decades, the reliability of these projections is questionable. The present study is consistent with the “East Africa Paradox” that observations show drying in summer season rainfall while GCMs project wetting. This has an expression in summertime Ethiopian rain that has not received significant attention in previous studies.
Societies in much of the Horn of Africa are affected by variability in two distinct rainy seasons: the March–May (MAM) “long” rains and the October–December (OND) “short” rains. A recent five-season, La Niña–forced drought has renewed concerns about possible anthropogenic drying trends in the long rains, which had partially recovered after a multidecadal drying trend in the 1980s through the 2000s. Despite observed drying, previous generations of global climate models (GCMs) have consistently projected long-term wetting due to increased greenhouse gas concentrations, an East African “paradox” which complicates the interpretation of East African rainfall projections. We investigate the paradox in new phase 6 of the Coupled Model Intercomparison Project (CMIP6) and seasonal forecast models, leveraging an improved observational record and large ensembles to better differentiate internal and forced trends. We find observed drying trends are at the limits of the GCM spread during the peak paradox period, though the recent recovery is comfortably within the model spread. We find that the apparent paradox is largely removed by prescribing sea surface temperatures (SSTs) and is likely caused by the GCM difficulties in simulating observed tropical Pacific SST trends in recent decades. In line with arguments that these SST trends are at least partially forced anthropogenically, we recommend users of future rainfall projections in East Africa consider the possibility of long-term MAM drying despite GCM wetting and call for future model simulations that better sample the expected spread of SSTs.
Societies in the Horn of Africa depend on the March–May “long” rains and the September–December “short” rains to support agricultural and pastoral practices on rain-fed lands. Recent major droughts have raised worries about possible anthropogenically forced drying trends in the long rains through global climate models (GCMs) project wetting. This East African “paradox” complicates long-term climate adaptation planning. We find the paradox continues in the newest generation of GCMs and seasonal forecast models; though a recent recovery in rainfall is well-captured, the strongest observed drying trends are rare in simulations. The paradox likely arises from known GCM biases in the Pacific Ocean interacting with natural variability. We recommend that researchers and policymakers consider possible long-term drying despite GCM projections of wetting.
- PAR ID:
- 10556190
- Publisher / Repository:
- American Meteorological Society
- Date Published:
- Journal Name:
- Journal of Climate
- Volume:
- 37
- Issue:
- 24
- ISSN:
- 0894-8755
- Format(s):
- Medium: X Size: p. 6641-6658
- Size(s):
- p. 6641-6658
- Sponsoring Org:
- National Science Foundation
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Abstract -
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