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Abstract 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.
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A comparison of multiple statistically downscaled climate change datasets for the conterminous USA
Abstract Climate change projections provided by global climate models (GCM) are generally too coarse for local and regional applications. Local and regional climate change impact studies therefore use downscaled datasets. While there are studies that evaluate downscaling methodologies, there is no study comparing the downscaled datasets that are actually distributed and used in climate change impact studies, and there is no guidance for selecting a published downscaled dataset. We compare five widely used statistically downscaled climate change projection datasets that cover the conterminous USA (CONUS): ClimateNA, LOCA, MACAv2-LIVNEH, MACAv2-METDATA, and NEX-DCP30. All of the datasets are derived from CMIP5 GCMs and are publicly distributed. The five datasets generally have good agreement across CONUS for Representative Concentration Pathways (RCP) 4.5 and 8.5, although the agreement among the datasets vary greatly depending on the GCM, and there are many localized areas of sharp disagreements. Areas of higher dataset disagreement emerge over time, and their importance relative to differences among GCMs is comparable between RCP4.5 and RCP8.5. Dataset disagreement displays distinct regional patterns, with greater disagreement in △Tmax and △Tmin in the interior West and in the North, and disagreement in △P in California and the Southeast. LOCA and ClimateNA are often the outlier dataset, while the seasonal timing of ClimateNA is somewhat shifted from the others. To easily identify regional study areas with high disagreement, we generated maps of dataset disagreement aggregated to states, ecoregions, watersheds, and forests. Climate change assessment studies can use the maps to evaluate and select one or more downscaled datasets for their study area.
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- Award ID(s):
- 1802885
- PAR ID:
- 10381853
- Publisher / Repository:
- IOP Publishing
- Date Published:
- Journal Name:
- Environmental Research Communications
- Volume:
- 4
- Issue:
- 12
- ISSN:
- 2515-7620
- Page Range / eLocation ID:
- Article No. 125005
- Format(s):
- Medium: X
- Sponsoring Org:
- National Science Foundation
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