Large contribution from anthropogenic warming to an emerging North American megadrought

Science ◽  
2020 ◽  
Vol 368 (6488) ◽  
pp. 314-318 ◽  
Author(s):  
A. Park Williams ◽  
Edward R. Cook ◽  
Jason E. Smerdon ◽  
Benjamin I. Cook ◽  
John T. Abatzoglou ◽  
...  
Keyword(s):  
Climate Change ◽  
Soil Moisture ◽  
North America ◽  
Relative Humidity ◽  
Climate Models ◽  
Hydrological Modeling ◽  
Drought Severity ◽  
Large Contribution ◽  
Moderate Drought

Severe and persistent 21st-century drought in southwestern North America (SWNA) motivates comparisons to medieval megadroughts and questions about the role of anthropogenic climate change. We use hydrological modeling and new 1200-year tree-ring reconstructions of summer soil moisture to demonstrate that the 2000–2018 SWNA drought was the second driest 19-year period since 800 CE, exceeded only by a late-1500s megadrought. The megadrought-like trajectory of 2000–2018 soil moisture was driven by natural variability superimposed on drying due to anthropogenic warming. Anthropogenic trends in temperature, relative humidity, and precipitation estimated from 31 climate models account for 46% (model interquartiles of 34 to 103%) of the 2000–2018 drought severity, pushing an otherwise moderate drought onto a trajectory comparable to the worst SWNA megadroughts since 800 CE.

scholarly journals The role of irrigation expansion on historical climate change during the last 115 years: insights from CMIP6

2021 ◽  
Author(s):  
Amen Al-Yaari ◽  
Agnes Ducharne ◽  
Wim Thiery ◽  
Frederique Cheruy ◽  
David Lawrence
Keyword(s):  
Climate Change ◽  
Soil Moisture ◽  
Air Temperature ◽  
Land Management ◽  
Climate Models ◽  
Temporal Trends ◽  
World Population ◽  
The World ◽  
Over Time

<p>Irrigated areas have increased, faster than the growth of the world population, from around 0.63 million km<sup>2</sup> at the start of the 20th century to 3.1 million km<sup>2</sup> of land in 2005, that is five times of area in 1900 (0.6 million km<sup>2</sup>). Irrigation is one of the land management practices with the largest biogeochemical and biogeophysical effects on climate. However, incorporating land management factors (including irrigation) into most of the state‐of‐the‐art climate models under the Coupled Model Intercomparison Project, Phase 6 (CMIP6) coordinated by the World Climate Research Programme (WCRP) is still overlooked. To our best knowledge, three models, however, take into account irrigation activities: namely NorESM2‐LM, GISS‐E2‐H, and CESM2. The overall objective of the study is to investigate the role of irrigation on climate change at the global scale by looking at temporal trends of Essential Climate variables (ECVs) that characterize the Earth's climate (Evapotranspiration, leaf area index, precipitation, soil moisture, radiation, and air temperature) over the last 115 years (i.e. 1900-2014). Within this investigation, we compared models with irrigation vs. models without irrigation using 20 models from different CMIP6 experiments: coupled land-atmosphere amip (observed sea surface temperatures and sea ice concentrations), coupled land-atmosphere-ocean historical simulation, and offline land-hist (land only simulations). Temporal trends over the 1900-2014 period were computed then spatially binned by the "FAO Global Map of Irrigation Areas", which represents area equipped for irrigation expressed as percentage of total area around the year 2005. For the three CMIP6 experiments, the three models with irrigation switched on showed similar and distinguished behavior from all other models with irrigation switched off over intensively irrigated areas: mean annual evapotranspiration and soil moisture increased over time (positive trends vs. negative or no trends for all other none-irrigation models). This increase in evapotranspiration over time was reflected in the negative trends (i.e. cooling) of annual maximum air temperature for the irrigation models vs. positive trends for most of the none-irrigation models. The ET temporal positive trends over intensively irrigated areas were detected and confirmed by four different satellite-based ET products. The consistent results among the three experiments and confirmed by different satellite data imply the importance of incorporating anthropogenic factors in the next generation of climate models.</p>

Assess 21st century Flash Drought in the United States using high resolution regional climate models

2021 ◽  
Author(s):  
Brandi Gamelin ◽  
Jiali Wang ◽  
V. Rao Kotamarthi
Keyword(s):  
Climate Change ◽  
United States ◽  
Soil Moisture ◽  
Climate Models ◽  
Wrf Model ◽  
The United States ◽  
Future Climate Change ◽  
Climate Change Scenarios ◽  
Regional Variability ◽  
Groundwater Levels

<p>Flash droughts are the rapid intensification of drought conditions generally associated with increased temperatures and decreased precipitation on short time scales.  Consequently, flash droughts are responsible for reduced soil moisture which contributes to diminished agricultural yields and lower groundwater levels. Drought management, especially flash drought in the United States is vital to address the human and economic impact of crop loss, diminished water resources and increased wildfire risk. In previous research, climate change scenarios show increased growing season (i.e. frost-free days) and drying in soil moisture over most of the United States by 2100. Understanding projected flash drought is important to assess regional variability, frequency and intensity of flash droughts under future climate change scenarios. Data for this work was produced with the Weather Research and Forecasting (WRF) model. Initial and boundary conditions for the model were supplied by CCSM4, GFDL-ESM2G, and HadGEM2-ES and based on the 8.5 Representative Concentration Pathway (RCP8.5). The WRF model was downscaled to a 12 km spatial resolution for three climate time frames: 1995-2004 (Historical), 2045-2054 (Mid), and 2085-2094 (Late).  A key characteristic of flash drought is the rapid onset and intensification of dry conditions. For this, we identify onset with vapor pressure deficit during each time frame. Known flash drought cases during the Historical run are identified and compared to flash droughts in the Mid and Late 21<sup>st</sup> century.</p>

scholarly journals Meteorological, soil moisture, surface water, and groundwater data from the St Denis National Wildlife Area, Saskatchewan, Canada

2018 ◽  
Author(s):  
Edward K. P. Bam ◽  
Rosa Brannen ◽  
Sujata Budhathoki ◽  
Andrew M. Ireson ◽  
Chris Spence ◽  
...  
Keyword(s):  
Climate Change ◽  
Soil Moisture ◽  
Surface Water ◽  
Climate Models ◽  
Multiple Scales ◽  
Full Range ◽  
Research Network ◽  
Groundwater Levels ◽  
Groundwater Availability ◽  
Surface Water And Groundwater

Abstract. Long-term meteorological, soil moisture, surface water, and groundwater data provide information on past climate change, most notably information that can be used to analyze past changes in precipitation and groundwater availability in a region. These data are also valuable to test, calibrate and validate hydrological and climate models. CCRN (Changing Cold Regions Network) is a collaborative research network that brought together a team of over 40 experts from 8 universities and 4 federal government agencies in Canada for 5 years (2013–18) through the Climate Change and Atmospheric Research (CCAR) Initiative of the Natural Sciences and Engineering Research Council of Canada (NSERC). The working group aimed to integrate existing and new data with improved predictive and observational tools to understand, diagnose and predict interactions amongst the cryospheric, ecological, hydrological, and climatic components of the changing Earth system at multiple scales, with a geographic focus on the rapidly changing cold interior of Western Canada. The St Denis National Wildlife Area database contains data for the prairie research site, St Denis National Wildlife Research Area, and includes atmosphere, soil, and groundwater. The meteorological measurements are observed every 5 seconds, and half-hourly averages (or totals) are logged. Soil moisture data comprise volumetric water content, soil temperature, electrical conductivity and matric potential for probes installed at depths of 5 cm, 20 cm, 50 cm, 100 cm, 200 cm and 300 cm in all soil profiles. Additional data on snow surveys, pond and groundwater levels, and water isotope isotopes collected on an intermittent basis between 1968 and 2018 are also presented including information on the dates and ground elevations (datum) used to construct hydraulic heads. The metadata table provides location information, information about the full range of measurements carried out on each parameter and GPS locations that are relevant to the interpretation of the records, as well as citations for both publications and archived data. The compiled data are available at https://doi.org/10.20383/101.0115.

scholarly journals Prediction of the Long-Term Potential Distribution of Cryptorhynchus lapathi (L.) under Climate Change

Forests ◽  
2019 ◽  
Vol 11 (1) ◽  
pp. 5 ◽  
Author(s):  
Ya Zou ◽  
Linjing Zhang ◽  
Xuezhen Ge ◽  
Siwei Guo ◽  
Xue Li ◽  
...  
Keyword(s):  
Climate Change ◽  
North America ◽  
Potential Distribution ◽  
Climate Models ◽  
Global Climate ◽  
Global Climate Models ◽  
Prevention Measures ◽  
Climate Data ◽  
Effective Prevention ◽  
Future Global Warming

The poplar and willow borer, Cryptorhynchus lapathi (L.), is a severe worldwide quarantine pest that causes great economic, social, and ecological damage in Europe, North America, and Asia. CLIMEX4.0.0 was used to study the likely impact of climate change on the potential global distribution of C. lapathi based on existing (1987–2016) and predicted (2021–2040, 2041–2080, and 2081–2100) climate data. Future climate data were simulated based on global climate models from Coupled Model Inter-comparison Project Phase 5 (CMIP5) under the RCP4.5 projection. The potential distribution of C. lapathi under historical climate conditions mainly includes North America, Africa, Europe, and Asia. Future global warming may cause a northward shift in the northern boundary of potential distribution. The total suitable area would increase by 2080–2100. Additionally, climatic suitability would change in large regions of the northern hemisphere and decrease in a small region of the southern hemisphere. The projected potential distribution will help determine the impacts of climate change and identify areas at risk of pest invasion in the future. In turn, this will help design and implement effective prevention measures for expanding pest populations, using natural enemies, microorganisms, and physical barriers in very favorable regions to impede the movement and oviposition of C. lapathi.

Effects of Hydrologic Model Choice and Calibration on the Portrayal of Climate Change Impacts

2015 ◽  
Vol 16 (2) ◽  
pp. 762-780 ◽  
Author(s):  
Pablo A. Mendoza ◽  
Martyn P. Clark ◽  
Naoki Mizukami ◽  
Andrew J. Newman ◽  
Michael Barlage ◽  
...  
Keyword(s):  
Climate Change ◽  
Water Resources ◽  
Climate Models ◽  
Climate Change Impacts ◽  
Hydrologic Model ◽  
Global Climate Models ◽  
Change Scenario ◽  
Hydrologic Models ◽  
Climate System Model

Abstract The assessment of climate change impacts on water resources involves several methodological decisions, including choices of global climate models (GCMs), emission scenarios, downscaling techniques, and hydrologic modeling approaches. Among these, hydrologic model structure selection and parameter calibration are particularly relevant and usually have a strong subjective component. The goal of this research is to improve understanding of the role of these decisions on the assessment of the effects of climate change on hydrologic processes. The study is conducted in three basins located in the Colorado headwaters region, using four different hydrologic model structures [PRMS, VIC, Noah LSM, and Noah LSM with multiparameterization options (Noah-MP)]. To better understand the role of parameter estimation, model performance and projected hydrologic changes (i.e., changes in the hydrology obtained from hydrologic models due to climate change) are compared before and after calibration with the University of Arizona shuffled complex evolution (SCE-UA) algorithm. Hydrologic changes are examined via a climate change scenario where the Community Climate System Model (CCSM) change signal is used to perturb the boundary conditions of the Weather Research and Forecasting (WRF) Model configured at 4-km resolution. Substantial intermodel differences (i.e., discrepancies between hydrologic models) in the portrayal of climate change impacts on water resources are demonstrated. Specifically, intermodel differences are larger than the mean signal from the CCSM–WRF climate scenario examined, even after the calibration process. Importantly, traditional single-objective calibration techniques aimed to reduce errors in runoff simulations do not necessarily improve intermodel agreement (i.e., same outputs from different hydrologic models) in projected changes of some hydrological processes such as evapotranspiration or snowpack.

scholarly journals Varying soil moisture-atmosphere feedbacks explain divergent temperature extremes and precipitation projections in Central Europe

2018 ◽  
Author(s):  
Martha M. Vogel ◽  
Jakob Zscheischler ◽  
Sonia I. Seneviratne
Keyword(s):  
Climate Change ◽  
Soil Moisture ◽  
Central Europe ◽  
Climate Models ◽  
Global Climate ◽  
Summer Precipitation ◽  
Global Climate Models ◽  
Temperature Extremes ◽  
Extreme Temperatures

Abstract. The frequency and intensity of climate extremes is expected to increase in many regions due to anthropogenic climate change. In Central Europe extreme temperatures are projected to change more strongly than global mean temperatures and soil moisture-temperature feedbacks significantly contribute to this regional amplification. Because of their strong societal, ecological and economic impacts, robust projections of temperature extremes are needed. Unfortunately, in current model projections, temperature extremes in Central Europe are prone to large uncertainties. In order to understand and potentially reduce uncertainties of extreme temperatures projections in Europe, we analyze global climate models from the CMIP5 ensemble for the business-as-usual high-emission scenario (RCP8.5). We find a divergent behavior in long-term projections of summer precipitation until the end of the 21st century, resulting in a trimodal distribution of precipitation (wet, dry and very dry). All model groups show distinct characteristics for summer latent heat flux, top soil moisture, and temperatures on the hottest day of the year (TXx), whereas for net radiation and large-scale circulation no clear trimodal behavior is detectable. This suggests that different land-atmosphere coupling strengths may be able to explain the uncertainties in temperature extremes. Constraining the full model ensemble with observed present-day correlations between summer precipitation and TXx excludes most of the very dry and dry models. In particular, the very dry models tend to overestimate the negative coupling between precipitation and TXx, resulting in a too strong warming. This is particularly relevant for global warming levels above 2 °C. The analysis allows for the first time to substantially reduce uncertainties in the projected changes of TXx in global climate models. Our results suggest that long-term temperature changes in TXx in Central Europe are about 20 % lower than projected by the multi-model median of the full ensemble. In addition, mean summer precipitation is found to be more likely to stay close to present-day levels. These results are highly relevant for improving estimates of regional climate-change impacts including heat stress, water supply and crop failure for Central Europe.

Late Quaternary Bison diminution on the Great Plains of North America: evaluating the role of human hunting versus climate change

2008 ◽  
Vol 27 (17-18) ◽  
pp. 1752-1771 ◽  
Author(s):  
Matthew E. Hill ◽  
Matthew G. Hill ◽  
Christopher C. Widga
Keyword(s):  
Climate Change ◽  
North America ◽  
Great Plains ◽  
Late Quaternary

scholarly journals Climate model validation and selection for hydrological applications in representative Mediterranean catchments

2013 ◽  
Vol 10 (7) ◽  
pp. 9105-9145 ◽  
Author(s):  
R. Deidda ◽  
M. Marrocu ◽  
G. Caroletti ◽  
G. Pusceddu ◽  
A. Langousis ◽  
...  
Keyword(s):  
Climate Change ◽  
Climate Models ◽  
Hydrological Modeling ◽  
Climate Model ◽  
Epistemic Uncertainty ◽  
Regional Climate ◽  
Primary Objective ◽  
The Mediterranean ◽  
Ensembles Project ◽  
The Eu

Abstract. This paper discusses the relative performance of several climate models in providing reliable forcing for hydrological modeling in six representative catchments in the Mediterranean region. We consider 14 Regional Climate Models (RCMs), from the EU-FP6 ENSEMBLES project, run for the A1B emission scenario on a common 0.22-degree (about 24 km) rotated grid over Europe and the Mediterranean. In the validation period (1951 to 2010) we consider daily precipitation and surface temperatures from the E-OBS dataset, available from the ENSEMBLES project and the data providers in the ECA&D project. Our primary objective is to rank the 14 RCMs for each catchment and select the four best performing ones to use as common forcing for hydrological models in the six Mediterranean basins considered in the EU-FP7 CLIMB project. Using a common suite of 4 RCMs for all studied catchments reduces the (epistemic) uncertainty when evaluating trends and climate change impacts in the XXI century. We present and discuss the validation setting, as well as the obtained results and, to some detail, the difficulties we experienced when processing the data. In doing so we also provide useful information and hint for an audience of researchers not directly involved in climate modeling, but interested in the use of climate model outputs for hydrological modeling and, more in general, climate change impact studies in the Mediterranean.

scholarly journals Climate projections of a multi-variate heat stress index: the role of downscaling and bias correction

2019 ◽  
Author(s):  
Ana Casanueva ◽  
Sven Kotlarski ◽  
Sixto Herrera ◽  
Andreas M. Fischer ◽  
Tord Kjellstrom ◽  
...  
Keyword(s):  
Climate Change ◽  
Heat Stress ◽  
Bias Correction ◽  
Climate Models ◽  
Dew Point ◽  
Added Value ◽  
Stress Index ◽  
Corrected Data ◽  
Heat Stress Index

Abstract. Along with the higher demand of bias-corrected data for climate impact studies, the number of available data sets has largely increased in the recent years. For instance, the Inter-Sectoral Impact Model Intercomparison Project (ISIMIP) constitutes a framework for consistently projecting the impacts of climate change across affected sectors and spatial scales. These data are very attractive for any impact application since they offer worldwide bias-corrected data based on Global Climate Models (GCMs). Complementary, the CORDEX initiative has incorporated experiments based on regionally-downscaled bias-corrected data by means of debiasing and quantile mapping (QM) methods. In light of this situation, it is challenging to distil the most accurate and useful information for climate services, but at the same time it creates a perfect framework for intercomparison and sensitivity analyses. In the present study, the trend-preserving ISIMIP method and empirical QM are applied to climate model simulations that were carried out at different spatial resolutions (CMIP5 GCM and EURO-CORDEX Regional Climate Models (RCMs), at approximately 150 km, 50 km and 12 km horizontal resolution, respectively) in order to assess the role of downscaling and bias correction in a multi-variate framework. The analysis is carried out for the wet bulb globe temperature (WBGT), a heat stress index that is commonly used in the context of working people and labour productivity. WBGT for shaded conditions depends on air temperature and dew point temperature, which in this work are individually bias-corrected prior to the index calculation. Our results show that the added value of RCMs with respect to the driving GCM is limited after bias correction. The two bias correction methods are able to adjust the central part of the WBGT distribution, but some added value of QM is found in WBGT percentiles and in the intervariable relationships. The evaluation in present climate of such multivariate indices should be performed with caution since biases in the individual variables might compensate, thus leading to better performance for the wrong reason. Climate change projections of WBGT reveal a larger increase of summer mean heat stress for the GCM than for the RCMs, related to the well-known reduced summer warming of the EURO-CORDEX RCMs. These differences are lowered after QM, since this bias correction method modifies the change signals and brings the results for GCM and RCMs closer to each other. We also highlight the need of large ensembles of simulations to assess the feasibility of the derived projections.

scholarly journals Impact of Climate Change on Crop Yield: A Case Study of Rainfed Corn in Central Illinois

2009 ◽  
Vol 48 (9) ◽  
pp. 1868-1881 ◽  
Author(s):  
Ximing Cai ◽  
Dingbao Wang ◽  
Romain Laurent
Keyword(s):  
Climate Change ◽  
Soil Moisture ◽  
Crop Yield ◽  
Climate Models ◽  
Regional Scale ◽  
Risk Estimate ◽  
Yield Reduction ◽  
Equal Weight ◽  
Corn Yield ◽  
Central Illinois

Abstract This paper assesses the effect of climate change on crop yield from a soil water balance perspective. The uncertainties of regional-scale climate models, local-scale climate variability, emissions scenarios, and crop growth models are combined to explore the possible range of climate change effects on rainfed corn yield in central Illinois in 2055. The results show that a drier and warmer summer during the corn growth season and wetter and warmer precrop and postcrop seasons will likely occur. Greater temperature and precipitation variability may lead to more variable soil moisture and crop yield, and larger soil moisture deficit and crop yield reduction are likely to occur more frequently. The increased water stress is likely to be most pronounced during the flowering and yield formation stages. The expected rainfed corn yield in 2055 is likely to decline by 23%–34%, and the probability that the yield may not reach 50% of the potential yield ranges from 32% to 70% if no adaptation measures are instituted. Among the multiple uncertainty sources, the greenhouse gas emissions projection may have the strongest effect on the risk estimate of crop yield reduction. The effects from the various uncertainties can be offset to some degree when the uncertainties are considered jointly. An ensemble of GCMs with an equal weight may overestimate the risk of soil moisture deficits and crop yield reduction in comparison with an ensemble of GCMs with different weight determined by the root-mean-square error minimization method. The risk estimate presented in this paper implies that climate change adaptation is needed to avoid reduced corn yields and the resulting profit losses in central Illinois.

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