Robust Future Changes in Meteorological Drought in <scp>CMIP6</scp> Projections Despite Uncertainty in Precipitation

Ukkola, Anna M.; Kauwe, Martin G. De; Roderick, Michael L.; Abramowitz, Gab; Pitman, Andrew J.

doi:10.1029/2020gl087820

Cited by 315 publications

(213 citation statements)

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“…There is better agreement in projected future rainfall trends in CMIP6 models in many regions such as Amazonia (e.g., Cook et al, 2020; Ukkola et al, 2020), but these results should be interpreted with caution for several reasons. Most CMIP6 models show future drying in Amazonia, but the local details of this drying pattern can vary from model to model (Figure S6).…”

Section: Discussionmentioning

confidence: 94%

“…Surface air temperature, rainfall, and soil moisture variability and trends over tropical Central and South America in October–March (ONDJFM) are examined (e.g., Satyamurty et al, 2010; Wang et al, 2018), with a specific focus on northeastern Amazonia (10°S to 8°N, 60–50°W, outlined in Figure 1). Although many CMIP6 models project drying across much of tropical South America (Cook et al, 2020; Ukkola et al, 2020), this study focuses on northeastern Amazonia due to the impact of recent drought in this region in observations (JM16), as well as the robust drying response in CMIP6 models in this region under climate change (Cook et al, 2020, also discussed here). Furthermore, although abnormally low rainfall can occur during various months throughout the year, here the focus is on ONDJFM due to the impacts of El Niño events during the ONDJFM time period (e.g., JM16).…”

Section: Methodsmentioning

confidence: 99%

“…The previous generation of climate models (Coupled Model Intercomparison Project Phase 5, or CMIP5; Taylor et al, 2012) indicated that northeastern Amazonia may dry while western Amazonia may receive increasing rainfall as the globe warms (Duffy et al, 2015). Recent work has shown that the new CMIP Phase 6 (CMIP6; Eyring et al, 2016) simulations agree on the sign of future rainfall trends in Amazonia, with droughts projected to increase in duration and intensity with global warming (Ukkola et al, 2020). Specifically, CMIP6 models show drying across western Amazonia, and most CMIP6 models agree on future decreases in soil moisture and runoff across most of Amazonia in low, medium, and high greenhouse gas emissions scenarios (Cook et al, 2020).…”

Section: Introductionmentioning

confidence: 99%

“…Studies of observed rainfall and temperature indicate that climate change may already be driving “enhanced” (particularly hot and arid) drought in the region; 2016 was the warmest year in Amazonia since 1950 (Marengo et al, 2018), and the recent 2015–2016 drought in eastern Amazonia was at least 1.5°C warmer than the drought associated with the 1997–1998 El Niño event (Jimenez‐Munoz et al, 2016, hereafter JM16). Yet, the risk of this type of recent hot drought has not been investigated in state‐of‐the‐art climate models, and recent preliminary studies of future drought changes in CMIP6 (e.g., Cook et al, 2020; Ukkola et al, 2020) have relied on limited numbers of these new model simulations (e.g., 10–13 models). Given the severity of recent seasonal droughts in the region and the apparent increase in model agreement in terms of future drying in the region, here instrumental records and an expanded suite of CMIP6 simulations are used to examine recent and future trends in rainfall and temperatures, with a focus on the likelihood of the risk of a 2015–2016 type drought under shifting precipitation and temperature baselines.…”

Section: Introductionmentioning

confidence: 99%

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Implications of CMIP6 Projected Drying Trends for 21st Century Amazonian Drought Risk

Parsons

2020

Earth's Future

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Recent exceptionally hot droughts in Amazonia have highlighted the potential role of global warming in driving changes in rainfall and temperatures in the region. The previous generation of global climate models projected that eastern Amazonia would receive less future precipitation while western Amazonia would receive more precipitation, but many of these models disagreed on future precipitation trends in the region. Here Coupled Modeling Intercomparison Project, Phase 6 (CMIP6) models are used to examine the shifting risk of eastern Amazonian droughts under high and low future greenhouse gas emissions scenarios. This new generation of models shows better agreement that most of the Amazonian basin will receive less future rainfall, with particularly strong agreement that eastern and southern Amazonia will dry in the 21st century. These models suggest that global warming may be increasing the likelihood of exceptionally hot drought in the region. With unabated global warming, recent particularly warm and severe droughts will become more common by midcentury, but reducing the rate of greenhouse gas emissions can make extremely hot and dry years less common in the future. Simulated future rainfall changes in Amazonia under high greenhouse gas emissions are associated with changes in the tropical Pacific, but many climate models struggle to reproduce observed trends in the tropical Pacific. These shortcomings highlight the need to improve confidence in global climate models' ability to simulate observed trends in the tropics, even if more CMIP6 models agree on the sign of future rainfall trends. Plain Language Summary Recent exceptionally hot droughts in Amazonia have highlighted the potential role of global warming in driving changes in rainfall and temperatures in the region. The previous generation of global climate models projected that eastern Amazonia would receive less future rainfall while western Amazonia would receive more rainfall. Here the latest climate model simulations are used to examine future rainfall and temperature changes over tropical South America. The new generation of climate models shows that most of the Amazonian basin will receive less future rainfall, with particularly strong agreement that eastern and southern Amazonia will dry in the future if the planet continues to rapidly warm. These models suggest that global warming has already increased the likelihood of exceptionally hot drought in the region, and by midcentury under unabated global warming, recent particularly warm and severe droughts will become more common. Reducing future greenhouse gas emissions decreases these warming and drying trends but does not eliminate them. However, many climate models have traditionally struggled to reproduce several key climate features in the tropics.

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Section: Discussionmentioning

confidence: 94%

Section: Methodsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Implications of CMIP6 Projected Drying Trends for 21st Century Amazonian Drought Risk

Parsons

2020

Earth's Future

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“…Even it can happen in northeast India, the highest rainfall region of the world 15 . A recent study suggests that the wetter parts of the earth would experience more devastating droughts in future 16 . It urges more attention to be given for monitoring and forecasting droughts in tropical regions.…”

Section: Introductionmentioning

confidence: 99%

Forecasting standardized precipitation index using data intelligence models: regional investigation of Bangladesh

Yaseen‬‬‬‬‬‬‬‬‬‬‬‬‬‬‬‬

Ali

Sharafati

et al. 2021

Sci Rep

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A noticeable increase in drought frequency and severity has been observed across the globe due to climate change, which attracted scientists in development of drought prediction models for mitigation of impacts. Droughts are usually monitored using drought indices (DIs), most of which are probabilistic and therefore, highly stochastic and non-linear. The current research investigated the capability of different versions of relatively well-explored machine learning (ML) models including random forest (RF), minimum probability machine regression (MPMR), M5 Tree (M5tree), extreme learning machine (ELM) and online sequential-ELM (OSELM) in predicting the most widely used DI known as standardized precipitation index (SPI) at multiple month horizons (i.e., 1, 3, 6 and 12). Models were developed using monthly rainfall data for the period of 1949–2013 at four meteorological stations namely, Barisal, Bogra, Faridpur and Mymensingh, each representing a geographical region of Bangladesh which frequently experiences droughts. The model inputs were decided based on correlation statistics and the prediction capability was evaluated using several statistical metrics including mean square error (MSE), root mean square error (RMSE), mean absolute error (MAE), correlation coefficient (R), Willmott’s Index of agreement (WI), Nash Sutcliffe efficiency (NSE), and Legates and McCabe Index (LM). The results revealed that the proposed models are reliable and robust in predicting droughts in the region. Comparison of the models revealed ELM as the best model in forecasting droughts with minimal RMSE in the range of 0.07–0.85, 0.08–0.76, 0.062–0.80 and 0.042–0.605 for Barisal, Bogra, Faridpur and Mymensingh, respectively for all the SPI scales except one-month SPI for which the RF showed the best performance with minimal RMSE of 0.57, 0.45, 0.59 and 0.42, respectively.

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Forty‐two years of no‐tillage and cover cropping improved soil oxygen availability and resilience

Lussich,

Dhaliwal,

Wright

et al. 2024

Agricultural & Env Letters

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Healthy soil air–water balance is critical for crop growth. Conservation agricultural practices improve soil physical properties to influence soil oxygen availability. We evaluated the impact of 42 years of hairy vetch (HV) cover cropping (CC), and no‐tillage (NT) on soil oxygen dynamics during a cotton growing season experiencing multiple intensive rain events in silt loam soil. The HV and NT treatments exhibited higher growing season soil oxygen availability (p < 0.05) and experienced three to four times fewer hours of oxygen limitation (i.e., oxygen concentration <10%) as compared to no cover crop (NC) and conventional tillage (CT) treatments. After a heavy rainfall, NT–HV treatment exhibited the highest soil oxygen availability, followed by NT–NC, CT–HV, and CT–NC treatments (p < 0.05). While CC and/or NT treatments quickly regained soil oxygen status within 24 h after saturating rain events, CT–NC suffered from sub‐optimal soil aeration until the third day after rainfall cessation. The combination of CC with NT practices enhanced soil oxygen availability and resilience to extreme precipitation events.Core Ideas Long‐term cover cropping and no‐tillage practices enhanced soil oxygen availability following extreme precipitation events. Cover cropping and no‐tillage practices reduced the duration of anoxia experienced by cotton crops during the growing season by three‐ to four‐fold. Combined cover cropping and no‐tillage implementation exhibited the most significant impact in mitigating immediate soil oxygen stress after heavy rainfall events.

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Robust Future Changes in Meteorological Drought in CMIP6 Projections Despite Uncertainty in Precipitation

Cited by 315 publications

References 44 publications

Implications of CMIP6 Projected Drying Trends for 21st Century Amazonian Drought Risk

Implications of CMIP6 Projected Drying Trends for 21st Century Amazonian Drought Risk

Forecasting standardized precipitation index using data intelligence models: regional investigation of Bangladesh

Forty‐two years of no‐tillage and cover cropping improved soil oxygen availability and resilience

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