Multi-model superensemble projection of seasonal soil drought in the midst of various uncertainties

2021 ◽  
Author(s):  
Sisi Chen ◽  
Xing Yuan
Keyword(s):  
Global Warming ◽  
Soil Moisture ◽  
Land Surface ◽  
Climate Models ◽  
Hydrological Cycle ◽  
Coupled Model ◽  
Internal Variability ◽  
Cmip5 Models ◽  
Soil Drought ◽  
Human Society

<p>Seasonal drought has a serious impact on nature and human society, especially during vegetation growing periods. As climate change alters terrestrial hydrological cycle significantly, it is imperative to assess drought changes and develop corresponding risk management measures for adaptation. According to a series of warming targets proposed by IPCC, researchers have focused on the response of regional droughts to global warming, but with inconsistent conclusions due to the large uncertainties in soil moisture simulation by the climate models, and the difficulty in representing the internal variability of climate system by using multi-model ensemble, etc. As compared with Coupled Model Intercomparison Project Phase 5 (CMIP5) models, the future projection of soil moisture based on the latest CMIP6 shows opposite trends over parts of China. Therefore, we project seasonal soil drought over China by using the superensemble that includes a set of CMIP5 and CMIP6 soil moisture data, high resolution land surface simulations driven by bias-corrected CMIP5 climate forcings, as wells large ensemble (LE) simulation data. We also investigate the influences from internal variability, and model uncertainties in responding to global warming at different levels.</p>

scholarly journals The increasing role of vegetation transpiration in soil moisture loss across China under global warming

2021 ◽  
Keyword(s):  
Global Warming ◽  
Soil Moisture ◽  
Land Surface ◽  
Hydrological Cycle ◽  
Coupled Model ◽  
Soil Evaporation ◽  
Moisture Loss ◽  
Climate Projections ◽  
Growing Seasons ◽  
The Future

Abstract Changing pathways of soil moisture loss, either directly from soil (evaporation) or indirectly through vegetation (transpiration), are an indicator of ecosystem and land hydrological cycle responses to the changing climate. Based on the ratio of transpiration to evaporation, this paper investigates soil moisture loss pathway changes across China using five reanalysis-type datasets for the past and Coupled Model Intercomparison Project Phase 6 (CMIP6) climate projections for the future. The results show that across China, the ratio of vegetation transpiration to soil evaporation has generally increased across vegetated land areas, except in grasslands and croplands in North China. During 1981–2014, there was an increase by 51.4 percentage points (pps, p < 0.01) on average according to the reanalyses and by 42.7 pps according to 13 CMIP6 models. The CMIP6 projections suggest that the holistic increasing trend will continue into the 21st century at a rate of 40.8 pps for SSP585, 30.6 pps for SSP245, and –1.0 pps for SSP126 shared socioeconomic pathway scenarios for the period 2015–2100 relative to 1981–2014. Major contributions come from the increases in vegetation transpiration over the semiarid and subhumid grasslands, croplands, and forestlands under the influence of increasing temperatures and prolonged growing seasons (with twin peaks in May and October). The future increasing vegetation transpiration ratio in soil moisture loss implies the potential of regional greening across China under global warming and the risks of intensifying land surface dryness and altering the coupling between soil moisture and climate in regions with water-limited ecosystems.

scholarly journals Accelerated hydrological cycle over the Sanjiangyuan region induces more streamflow extremes at different global warming levels

2020 ◽  
Author(s):  
Peng Ji ◽  
Xing Yuan ◽  
Feng Ma ◽  
Ming Pan
Keyword(s):  
Global Warming ◽  
Land Surface ◽  
Yangtze River ◽  
Climate Models ◽  
Hydrological Cycle ◽  
Yellow River ◽  
Coupled Model ◽  
Ecological Processes ◽  
Intercomparison Project ◽  
Streamflow Extremes

Abstract. Serving source water for the Yellow, Yangtze and Lancang-Mekong rivers, the Sanjiangyuan region concerns ~ 700 million people over its downstream areas. Recent research suggests that the Sanjiangyuan region will become wetter in a warming future, but future changes in streamflow extremes remain unclear due to the complex hydrological processes over high-land areas and limited knowledge of the influences of land cover change and CO2 physiological forcing. Based on high resolution land surface modeling during 1979~2100 driven by the climate and ecological projections from 11 newly released Coupled Model Intercomparison Project Phase 6 (CMIP6) climate models, we show that different accelerating rates of precipitation and evapotranspiration at 1.5 °C global warming level induce 55 % more dry extremes over Yellow river and 138 % more wet extremes over Yangtze river headwaters compared with the reference period (1985~2014). An additional 0.5 °C warming leads to a further nonlinear and more significant increase for both dry extremes over Yellow river (22 %) and wet extremes over Yangtze river (64 %). The combined role of CO2 physiological forcing and vegetation greening, which used to be neglected in hydrological projections, is found to alleviate dry extremes at 1.5 and 2.0 °C warming levels but to intensify dry extremes at 3.0 °C warming level. Moreover, vegetation greening contributes half of the differences between 1.5 and 3.0 °C warming levels. This study emphasizes the importance of ecological processes in determining future changes in streamflow extremes, and suggests a dry gets drier, wet gets wetter condition over headwaters.

scholarly journals Accelerated hydrological cycle over the Sanjiangyuan region induces more streamflow extremes at different global warming levels

2020 ◽  
Vol 24 (11) ◽  
pp. 5439-5451
Author(s):  
Peng Ji ◽  
Xing Yuan ◽  
Feng Ma ◽  
Ming Pan
Keyword(s):  
Global Warming ◽  
Land Surface ◽  
Yangtze River ◽  
Climate Models ◽  
Hydrological Cycle ◽  
Yellow River ◽  
Coupled Model ◽  
Ecological Processes ◽  
Intercomparison Project ◽  
Streamflow Extremes

Abstract. Serving source water for the Yellow, Yangtze and Lancang-Mekong rivers, the Sanjiangyuan region affects 700 million people over its downstream areas. Recent research suggests that the Sanjiangyuan region will become wetter in a warming future, but future changes of streamflow extremes remain unclear due to the complex hydrological processes over high-land areas and limited knowledge of the influences of land cover change and CO2 physiological forcing. Based on high-resolution land surface modeling during 1979–2100 driven by the climate and ecological projections from 11 newly released Coupled Model Intercomparison Project Phase 6 (CMIP6) climate models, we show that different accelerating rates of precipitation and evapotranspiration at 1.5 ∘C global warming level induce 55 % more dry extremes over Yellow River and 138 % more wet extremes over Yangtze River headwaters compared with the reference period (1985–2014). An additional 0.5 ∘C warming leads to a further nonlinear and more significant increase for both dry extremes over Yellow River (22 %) and wet extremes over Yangtze River (64 %). The combined role of CO2 physiological forcing and vegetation greening, which used to be neglected in hydrological projections, is found to alleviate dry extremes at 1.5 and 2.0 ∘C warming levels but to intensify dry extremes at 3.0 ∘C warming level. Moreover, vegetation greening contributes half of the differences between 1.5 and 3.0 ∘C warming levels. This study emphasizes the importance of ecological processes in determining future changes in streamflow extremes and suggests a “dry gets drier, wet gets wetter” condition over the warming headwaters.

scholarly journals Climate Drift in the CMIP5 Models*

2013 ◽  
Vol 26 (21) ◽  
pp. 8597-8615 ◽  
Author(s):  
Alexander Sen Gupta ◽  
Nicolas C. Jourdain ◽  
Jaclyn N. Brown ◽  
Didier Monselesan
Keyword(s):  
Climate Models ◽  
Coupled Model ◽  
Deep Ocean ◽  
Internal Variability ◽  
Correction Method ◽  
Physical Models ◽  
Cmip5 Models ◽  
Steric Sea Level ◽  
Biogeochemical Models ◽  
The Difference

Abstract Climate models often exhibit spurious long-term changes independent of either internal variability or changes to external forcing. Such changes, referred to as model “drift,” may distort the estimate of forced change in transient climate simulations. The importance of drift is examined in comparison to historical trends over recent decades in the Coupled Model Intercomparison Project (CMIP). Comparison based on a selection of metrics suggests a significant overall reduction in the magnitude of drift from phase 3 of CMIP (CMIP3) to phase 5 of CMIP (CMIP5). The direction of both ocean and atmospheric drift is systematically biased in some models introducing statistically significant drift in globally averaged metrics. Nevertheless, for most models globally averaged drift remains weak compared to the associated forced trends and is often smaller than the difference between trends derived from different ensemble members or the error introduced by the aliasing of natural variability. An exception to this is metrics that include the deep ocean (e.g., steric sea level) where drift can dominate in forced simulations. In such circumstances drift must be corrected for using information from concurrent control experiments. Many CMIP5 models now include ocean biogeochemistry. Like physical models, biogeochemical models generally undergo long spinup integrations to minimize drift. Nevertheless, based on a limited subset of models, it is found that drift is an important consideration and must be accounted for. For properties or regions where drift is important, the drift correction method must be carefully considered. The use of a drift estimate based on the full control time series is recommended to minimize the contamination of the drift estimate by internal variability.

scholarly journals Effective radiative forcing and adjustments in CMIP6 models

2020 ◽  
Vol 20 (16) ◽  
pp. 9591-9618 ◽  
Author(s):  
Christopher J. Smith ◽  
Ryan J. Kramer ◽  
Gunnar Myhre ◽  
Kari Alterskjær ◽  
William Collins ◽  
...  
Keyword(s):  
Climate Sensitivity ◽  
Radiative Forcing ◽  
Climate Models ◽  
Coupled Model ◽  
Internal Variability ◽  
Cmip5 Models ◽  
Model Intercomparison ◽  
Aerosol Forcing ◽  
Intercomparison Project ◽  
Effective Radiative Forcing

Abstract. The effective radiative forcing, which includes the instantaneous forcing plus adjustments from the atmosphere and surface, has emerged as the key metric of evaluating human and natural influence on the climate. We evaluate effective radiative forcing and adjustments in 17 contemporary climate models that are participating in the Coupled Model Intercomparison Project (CMIP6) and have contributed to the Radiative Forcing Model Intercomparison Project (RFMIP). Present-day (2014) global-mean anthropogenic forcing relative to pre-industrial (1850) levels from climate models stands at 2.00 (±0.23) W m−2, comprised of 1.81 (±0.09) W m−2 from CO2, 1.08 (± 0.21) W m−2 from other well-mixed greenhouse gases, −1.01 (± 0.23) W m−2 from aerosols and −0.09 (±0.13) W m−2 from land use change. Quoted uncertainties are 1 standard deviation across model best estimates, and 90 % confidence in the reported forcings, due to internal variability, is typically within 0.1 W m−2. The majority of the remaining 0.21 W m−2 is likely to be from ozone. In most cases, the largest contributors to the spread in effective radiative forcing (ERF) is from the instantaneous radiative forcing (IRF) and from cloud responses, particularly aerosol–cloud interactions to aerosol forcing. As determined in previous studies, cancellation of tropospheric and surface adjustments means that the stratospherically adjusted radiative forcing is approximately equal to ERF for greenhouse gas forcing but not for aerosols, and consequentially, not for the anthropogenic total. The spread of aerosol forcing ranges from −0.63 to −1.37 W m−2, exhibiting a less negative mean and narrower range compared to 10 CMIP5 models. The spread in 4×CO2 forcing has also narrowed in CMIP6 compared to 13 CMIP5 models. Aerosol forcing is uncorrelated with climate sensitivity. Therefore, there is no evidence to suggest that the increasing spread in climate sensitivity in CMIP6 models, particularly related to high-sensitivity models, is a consequence of a stronger negative present-day aerosol forcing and little evidence that modelling groups are systematically tuning climate sensitivity or aerosol forcing to recreate observed historical warming.

scholarly journals Intercomparison of the Surface Energy Partitioning in CMIP5 Simulations

Atmosphere ◽  
2019 ◽  
Vol 10 (10) ◽  
pp. 602 ◽  
Author(s):  
Yang ◽  
Wang ◽  
Huang
Keyword(s):  
Soil Moisture ◽  
Surface Energy ◽  
Land Surface ◽  
Radiative Forcing ◽  
Climate Models ◽  
Water Cycle ◽  
Potential Evapotranspiration ◽  
Sensible Heat Flux ◽  
Coupled Model ◽  
Energy Partitioning

The warming climate significantly modifies the global water cycle. Global evapotranspiration has increased over the past decades, yet climate models agree on the drying trend of land surface. In this study, we conducted an intercomparison analysis of the surface energy partitioning across Coupled Model Intercomparison Phase 5 (CMIP5) simulations and evaluated its behaviour with surface temperature and soil moisture anomalies, against the theoretically derived thermodynamic formula. Different responses over land and sea surfaces to elevated greenhouse gas emissions were found. Under the Representative Concentration Pathway of +8.5 W m−2 (RCP8.5) warming scenario, the multi-model mean relative efficiency anomaly from CMIP5 simulations is 3.83 and −0.12 over global sea and land, respectively. The significant anomaly over sea was captured by the thermodynamic solution based on the principle of maximum entropy production, with a mean relative error of 14.6%. The declining trend over land was also reproduced, but an accurate prediction of its small anomaly will require the inclusions of complex physical processes in future work. Despite increased potential evapotranspiration under rising temperatures, both CMIP5 simulations and thermodynamic principles suggest that the soil moisture-temperature feedback cannot support long-term enhanced evapotranspiration at the global scale. The dissipation of radiative forcing eventually shifts towards sensible heat flux and accelerates the warming over land, especially over South America and Europe.

Flash Drought in CMIP5 Models

2021 ◽  
Author(s):  
David Hoffmann ◽  
Ailie J. E. Gallant ◽  
Mike Hobbins
Keyword(s):  
Soil Moisture ◽  
Land Surface ◽  
Climate Models ◽  
Standardized Precipitation Index ◽  
Rapid Onset ◽  
Stress Index ◽  
Cmip5 Models ◽  
Drought Indices ◽  
Similar Proportion ◽  
Evaporative Demand

Abstract‘Flash drought’ (FD) describes the rapid onset of drought on sub-seasonal times scales. It is of particular interest for agriculture as it can deplete soil moisture for crop growth in just a few weeks. To better understand the processes causing FD, we evaluate the importance of evaporative demand and precipitation by comparing three different drought indices that estimate this hazard using meteorological and hydrological parameters from the CMIP5 suite of models. We apply the Standardized Precipitation Index (SPI); the Evaporative Demand Drought Index (EDDI), derived from evaporative demand (E0); and the Evaporative Stress Index (ESI), which connects atmospheric and soil moisture conditions by measuring the ratio of actual and potential evaporation. The results show moderate-to-strong relationships (r2 > 0.5) between drought indices and upper level soil moisture on daily time scales, especially in drought-prone regions. We find that all indices are able to identify FD in the top 10-cm layer of soil moisture in a similar proportion to that in the models’ climatologies. However, there is significant inter-model spread in the characteristics of the FDs identified. This spread is mainly caused by an overestimation of E0, indicating stark differences in the land surface models and coupling in individual CMIP5 models. Of all indices, the SPI provides the highest skill in predicting FD prior to or at the time of onset in soil moisture, while both EDDI and ESI show significantly lower skill. The results highlight that the lack of precipitation is the main contributor to FDs in climate models, with E0 playing a secondary role.

Evaluation of snow albedo feedback simulated by CMIP6 coupled climate models

2020 ◽  
Author(s):  
jiangling hu ◽  
duoying ji
Keyword(s):  
Climate Change ◽  
Northern Hemisphere ◽  
Land Surface ◽  
Climate Models ◽  
Coupled Model ◽  
Cmip5 Models ◽  
Simulation Research ◽  
Albedo Feedback ◽  
Snow Albedo ◽  
Autumn And Winter

&lt;p&gt;As the land surface warms, a subsequent reduction in snow and ice cover reveals a less reflective surface that absorbs more solar radiation, which further enhances the initial warming. This positive feedback climate mechanism is the snow albedo feedback (SAF), which will exacerbate climate warming and is the second largest contributor to Arctic amplification. Snow albedo feedback will increase the sensitivity of climate change in the northern hemisphere, which affects the accuracy of climate models in simulation research of climate change, and further affects the credibility of future climate prediction results.&lt;/p&gt;&lt;p&gt;Using the latest generation of climate models from CMIP6 (Coupled Model Intercomparison Project Version 6), we analyze seasonal cycle snow albedo feedback in Northern Hemisphere extratropics. We find that the strongest SAF strength is in spring (mean: -1.34 %K&lt;sup&gt;-1&lt;/sup&gt;), second strongest is autumn (mean: -1.01 %K&lt;sup&gt;-1&lt;/sup&gt;), the weakest is in summer (mean: -0.18 %K&lt;sup&gt;-1&lt;/sup&gt;). Except summer, the SAF strength is approximately 0.15% K&lt;sup&gt;-1&lt;/sup&gt; larger than CMIP5 models in the other three seasons. The spread of spring SAF strength (range: -1.09 to -1.37% K&lt;sup&gt;-1&lt;/sup&gt;) is larger than CMIP5 models. Oppositely, the spread of summer SAF strength (range: 0.20 to -0.56% K&lt;sup&gt;-1&lt;/sup&gt;) is smaller than CMIP5 models. When compared with CMIP5 models, the spread of autumn and winter SAF strength have not changed much.&lt;/p&gt;

scholarly journals Assessment of soil moisture fields from imperfect climate models with uncertain satellite observations

2009 ◽  
Vol 6 (2) ◽  
pp. 2733-2750 ◽  
Author(s):  
G. Schumann ◽  
D. J. Lunt ◽  
P. J. Valdes ◽  
R. A. M. de Jeu ◽  
K. Scipal ◽  
...  
Keyword(s):  
Soil Moisture ◽  
Land Surface ◽  
General Circulation ◽  
Climate Models ◽  
Climate Model ◽  
Hydrological Cycle ◽  
Circulation Model ◽  
Data Uncertainty ◽  
Limited Area

Abstract. We demonstrate that global satellite products can be used to evaluate climate model soil moisture predictions but conclusions should be drawn with care. The quality of a limited area climate model (LAM) was compared to a general circulation model (GCM) using soil moisture data from two different Earth observing satellites within a model validation scheme that copes with the presence of uncertain data. Results showed that in the face of imperfect models and data, it is difficult to investigate the quality of current land surface schemes in simulating hydrology accurately. Nevertheless, a LAM provides, in general, a better representation of spatial patterns and dynamics of soil moisture. However, in months when data uncertainty is higher, particularly in colder months and in periods when vegetation cover and soil moisture are out of phase (e.g. August in the case of Western Europe), it is not possible to draw firm conclusions about model acceptability. Our work indicates that a higher resolution LAM has more benefits to soil moisture prediction than are due to the resolution alone and can be attributed to an overall intensification of the hydrological cycle relative to the GCM.

ENSO amplitude uncertainty under global warming in CMIP5 models

2020 ◽  
Author(s):  
Goratz Beobide ◽  
Tobias Bayr ◽  
Annika Reintges ◽  
Mojib Latif
Keyword(s):  
Global Warming ◽  
Zonal Wind ◽  
Coupled Model ◽  
Correlation Coefficients ◽  
Internal Variability ◽  
Mean Amplitude ◽  
Cmip5 Models ◽  
Amplitude Change ◽  
Uncertainty Model ◽  
Scenario Uncertainty

&lt;p&gt;The possible change of ENSO amplitude during the 21&lt;sup&gt;st&lt;/sup&gt; century in response to global warming has been analyzed in models participating in the Coupled Model Intercomparison Phase 5 (CMIP5). Three types of uncertainties are investigated: scenario uncertainty, model uncertainty, and uncertainty due to internal variability.&lt;/p&gt;&lt;p&gt;The ENSO response obtained from the CMIP5 models is highly uncertain, leading to an ensemble-mean amplitude change of close to zero until the end of the 21&lt;sup&gt;st&lt;/sup&gt; century, with an uncertainty exceeding 0.3 &amp;#176;C. The internal variability is the main contributor to the uncertainty during the first two decades of the projections. The inter-model differences dominate thereafter, while scenario uncertainty is relatively small throughout the whole 21&lt;sup&gt;st&lt;/sup&gt; century. The zonal wind-SST feedback has been identified as an important factor of ENSO amplitude change: the global warming signal in the ENSO amplitude and zonal wind-SST feedback are highly correlated across the CMIP5 models, with correlation coefficients of 0.87, 0.84 and 0.78 for the RCP4.5, RCP6.0 and RCP8.5 scenarios, respectively.&lt;/p&gt;&lt;p&gt;The CMIP5 models with realistic ENSO dynamics have been analyzed separately. In this sub-ensemble, the global warming signal is strengthened with a mean ENSO amplitude decrease of approximately 0.1&amp;#176;C by the end of the 21&lt;sup&gt;st&lt;/sup&gt; century. When only considering models with large decadal ENSO amplitude variability, the decrease in ENSO amplitude amounts to 0.1&amp;#176;C and 0.2&amp;#176;C for the RCP4.5 and RCP8.5 scenarios, respectively.&lt;/p&gt;

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