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

<p>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.</p><p>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<sup>-1</sup>), second strongest is autumn (mean: -1.01 %K<sup>-1</sup>), the weakest is in summer (mean: -0.18 %K<sup>-1</sup>). Except summer, the SAF strength is approximately 0.15% K<sup>-1</sup> larger than CMIP5 models in the other three seasons. The spread of spring SAF strength (range: -1.09 to -1.37% K<sup>-1</sup>) is larger than CMIP5 models. Oppositely, the spread of summer SAF strength (range: 0.20 to -0.56% K<sup>-1</sup>) is smaller than CMIP5 models. When compared with CMIP5 models, the spread of autumn and winter SAF strength have not changed much.</p>

scholarly journals Assessing Snow Albedo Feedback in Simulated Climate Change

2006 ◽  
Vol 19 (11) ◽  
pp. 2617-2630 ◽  
Author(s):  
Xin Qu ◽  
Alex Hall
Keyword(s):  
Climate Change ◽  
Standard Deviation ◽  
Northern Hemisphere ◽  
Surface Albedo ◽  
Climate Models ◽  
Attenuation Effect ◽  
Albedo Feedback ◽  
Snow Albedo ◽  
The Mean ◽  
Planetary Albedo

Abstract In this paper, the two factors controlling Northern Hemisphere springtime snow albedo feedback in transient climate change are isolated and quantified based on scenario runs of 17 climate models used in the Intergovernmental Panel on Climate Change Fourth Assessment Report. The first factor is the dependence of planetary albedo on surface albedo, representing the atmosphere's attenuation effect on surface albedo anomalies. It is potentially a major source of divergence in simulations of snow albedo feedback because of large differences in simulated cloud fields in Northern Hemisphere land areas. To calculate the dependence, an analytical model governing planetary albedo was developed. Detailed validations of the analytical model for two of the simulations are shown, version 3 of the Community Climate System Model (CCSM3) and the Geophysical Fluid Dynamics Laboratory global coupled Climate Model 2.0 (CM2.0), demonstrating that it facilitates a highly accurate calculation of the dependence of planetary albedo on surface albedo given readily available simulation output. In all simulations it is found that surface albedo anomalies are attenuated by approximately half in Northern Hemisphere land areas as they are transformed into planetary albedo anomalies. The intermodel standard deviation in the dependence of planetary albedo on surface albedo is surprisingly small, less than 10% of the mean. Moreover, when an observational estimate of this factor is calculated by applying the same method to the satellite-based International Satellite Cloud Climatology Project (ISCCP) data, it is found that most simulations agree with ISCCP values to within about 10%, despite further disagreements between observed and simulated cloud fields. This suggests that even large relative errors in simulated cloud fields do not result in significant error in this factor, enhancing confidence in climate models. The second factor, related exclusively to surface processes, is the change in surface albedo associated with an anthropogenically induced temperature change in Northern Hemisphere land areas. It exhibits much more intermodel variability. The standard deviation is about ⅓ of the mean, with the largest value being approximately 3 times larger than the smallest. Therefore this factor is unquestionably the main source of the large divergence in simulations of snow albedo feedback. To reduce the divergence, attention should be focused on differing parameterizations of snow processes, rather than intermodel variations in the attenuation effect of the atmosphere on surface albedo anomalies.

scholarly journals The response of the Northern Hemisphere storm tracks and jetstreams to climate change in the CMIP3, CMIP5, and CMIP6 climate models

2020 ◽  
Author(s):  
Ben Harvey ◽  
Peter Cook ◽  
Len Shaffrey ◽  
Reinhard Schiemann
Keyword(s):  
Climate Change ◽  
Spatial Pattern ◽  
North Atlantic ◽  
Climate Models ◽  
Climate Model ◽  
Storm Track ◽  
Coupled Model ◽  
Storm Tracks ◽  
Cmip5 Models ◽  
Jet Streams

<p>Understanding and predicting how extratropical cyclones might respond to climate change is essential for assessing future weather risks and informing climate change adaptation strategies. Climate model simulations provide a vital component of this assessment, with the caveat that their representation of the present-day climate is adequate. In this study the representation of the NH storm tracks and jet streams and their responses to climate change are evaluated across the three major phases of the Coupled Model Intercomparison Project: CMIP3 (2007), CMIP5 (2012), and CMIP6 (2019). The aim is to quantity how present-day biases in the NH storm tracks and jet streams have evolved with model developments, and to further our understanding of their responses to climate change.</p><p>The spatial pattern of the present-day biases in CMIP3, CMIP5, and CMIP6 are similar. However, the magnitude of the biases in the CMIP6 models is substantially lower in the DJF North Atlantic storm track and jet stream than in the CMIP3 and CMIP5 models. In summer, the biases in the JJA North Atlantic and North Pacific storm tracks are also much reduced in the CMIP6 models. Despite this, the spatial pattern of the climate change response in the NH storm tracks and jet streams are similar across the CMIP3, CMIP5, and CMIP6 ensembles. The SSP2-4.5 scenario responses in the CMIP6 models are substantially larger than in the corresponding RCP4.5 CMIP5 models, consistent with the larger climate sensitivities of the CMIP6 models compared to CMIP5.</p>

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 Northern Hemisphere Snow-Cover Trends (1967–2018): A Comparison between Climate Models and Observations

Geosciences ◽  
2019 ◽  
Vol 9 (3) ◽  
pp. 135 ◽  
Author(s):  
◽  
◽  
◽  
◽  
◽  
...  
Keyword(s):  
Snow Cover ◽  
Northern Hemisphere ◽  
Climate Models ◽  
Climate Model ◽  
Coupled Model ◽  
Poor Performance ◽  
Four Seasons ◽  
Intercomparison Project ◽  
Autumn And Winter

Observed changes in Northern Hemisphere snow cover from satellite records were compared to those predicted by all available Coupled Model Intercomparison Project Phase 5 (“CMIP5”) climate models over the duration of the satellite’s records, i.e., 1967–2018. A total of 196 climate model runs were analyzed (taken from 24 climate models). Separate analyses were conducted for the annual averages and for each of the seasons (winter, spring, summer, and autumn/fall). A longer record (1922–2018) for the spring season which combines ground-based measurements with satellite measurements was also compared to the model outputs. The climate models were found to poorly explain the observed trends. While the models suggest snow cover should have steadily decreased for all four seasons, only spring and summer exhibited a long-term decrease, and the pattern of the observed decreases for these seasons was quite different from the modelled predictions. Moreover, the observed trends for autumn and winter suggest a long-term increase, although these trends were not statistically significant. Possible explanations for the poor performance of the climate models are discussed.

scholarly journals Estimating the Permafrost-Carbon Climate Response in the CMIP5 Climate Models Using a Simplified Approach

2013 ◽  
Vol 26 (14) ◽  
pp. 4897-4909 ◽  
Author(s):  
Eleanor J. Burke ◽  
Chris D. Jones ◽  
Charles D. Koven
Keyword(s):  
Climate Change ◽  
Radiative Forcing ◽  
Climate Models ◽  
Coupled Model ◽  
Climate Feedback ◽  
Cmip5 Models ◽  
Future Climate Change ◽  
Permafrost Region ◽  
Climate Response ◽  
Simplified Approach

Abstract Under climate change, thawing permafrost may cause a release of carbon, which has a positive feedback on the climate. The permafrost-carbon climate response (γPF) is the additional permafrost-carbon made vulnerable to decomposition per degree of global temperature increase. A simple framework was adopted to estimate γPF using the database for phase 5 of the Coupled Model Intercomparison Project (CMIP5). The projected changes in the annual maximum active layer thicknesses (ALTmax) over the twenty-first century were quantified using CMIP5 soil temperatures. These changes were combined with the observed distribution of soil organic carbon and its potential decomposability to give γPF. This estimate of γPF is dependent on the biases in the simulated present-day permafrost. This dependency was reduced by combining a reference estimate of the present-day ALTmax with an estimate of the sensitivity of ALTmax to temperature from the CMIP5 models. In this case, γPF was from −6 to −66 PgC K−1(5th–95th percentile) with a radiative forcing of 0.03–0.29 W m−2 K−1. This range is mainly caused by uncertainties in the amount of soil carbon deeper in the soil profile and whether it thaws over the time scales under consideration. These results suggest that including permafrost-carbon within climate models will lead to an increase in the positive global carbon climate feedback. Under future climate change the northern high-latitude permafrost region is expected to be a small sink of carbon. Adding the permafrost-carbon response is likely to change this region to a source of carbon.

scholarly journals The BRIDGE HadCM3 family of climate models: HadCM3@Bristol v1.0

2017 ◽  
Author(s):  
Paul J. Valdes ◽  
Edward Armstrong ◽  
Marcus P. S. Badger ◽  
Catherine D. Bradshaw ◽  
Fran Bragg ◽  
...  
Keyword(s):  
Climate Change ◽  
Ocean Circulation ◽  
Land Surface ◽  
General Circulation ◽  
Computational Models ◽  
Climate Models ◽  
Climate Model ◽  
Coupled Model ◽  
Circulation Model ◽  
Good Representation

Abstract. Understanding natural and anthropogenic climate change processes involves using computational models that represent the main components of the Earth system: the atmosphere, ocean, sea-ice and land surface. These models have become increasingly computationally expensive as resolution is increased and more complex process representations are included. However, to gain robust insight into how climate may respond to a given forcing, and to meaningfully quantify the associated uncertainty, it is often required to use either or both of ensemble approaches and very long integrations. For this reason, more computationally efficient models can be very valuable tools. Here we provide a comprehensive overview of the suite of climate models based around the coupled general circulation model HadCM3. This model was originally developed at the UK Met Office and has been heavily used during the last 15 years for a range of future (and past) climate change studies but is now largely being replaced by more recent models. However, it continues to be extensively used by the BRIDGE (Bristol Research Initiative for the Dynamic Global Environment) research group at the University of Bristol and elsewhere. Over time, adaptations have been made to the base HadCM3 model. These adaptations mean that the original documentation is not entirely representative, and several other configurations are in use which now differ from the originally described model versions. We therefore describe the key features of a number of configurations of the HadCM3 climate model family, including the atmosphere-only model (HadAM3), the coupled model with a low resolution ocean (HadCM3L), the high resolution atmosphere only model (HadAM3H), the regional model (HadRM3) and a fast coupled model (FAMOUS), which together make up HadCM3@Bristol version 1.0. These also include three versions of the land surface scheme. By comparing with observational datasets, we show that these models produce a good representation of many aspects of the climate system, including the land and sea surface temperatures, precipitation, ocean circulation and vegetation. This evaluation, combined with the relatively fast computational speed (up to 2000× faster than some CMIP6 models), motivates continued development and scientific use of the HadCM3 family of coupled climate models, particularly for quantifying uncertainty and for long multi-millennial scale simulations.

scholarly journals Robust increase of Indian monsoon rainfall and its variability under future warming in CMIP6 models

2021 ◽  
Vol 12 (2) ◽  
pp. 367-386
Author(s):  
Anja Katzenberger ◽  
Jacob Schewe ◽  
Julia Pongratz ◽  
Anders Levermann
Keyword(s):  
Climate Change ◽  
Global Warming ◽  
Climate Models ◽  
Monsoon Rainfall ◽  
Global Climate ◽  
Coupled Model ◽  
Global Climate Models ◽  
Cmip5 Models ◽  
Future Climate Change ◽  
Global Mean Temperature

Abstract. The Indian summer monsoon is an integral part of the global climate system. As its seasonal rainfall plays a crucial role in India's agriculture and shapes many other aspects of life, it affects the livelihood of a fifth of the world's population. It is therefore highly relevant to assess its change under potential future climate change. Global climate models within the Coupled Model Intercomparison Project Phase 5 (CMIP5) indicated a consistent increase in monsoon rainfall and its variability under global warming. Since the range of the results of CMIP5 was still large and the confidence in the models was limited due to partly poor representation of observed rainfall, the updates within the latest generation of climate models in CMIP6 are of interest. Here, we analyze 32 models of the latest CMIP6 exercise with regard to their annual mean monsoon rainfall and its variability. All of these models show a substantial increase in June-to-September (JJAS) mean rainfall under unabated climate change (SSP5-8.5) and most do also for the other three Shared Socioeconomic Pathways analyzed (SSP1-2.6, SSP2-4.5, SSP3-7.0). Moreover, the simulation ensemble indicates a linear dependence of rainfall on global mean temperature with a high agreement between the models independent of the SSP if global warming is the dominant forcing of the monsoon dynamics as it is in the 21st century; the multi-model mean for JJAS projects an increase of 0.33 mm d−1 and 5.3 % per kelvin of global warming. This is significantly higher than in the CMIP5 projections. Most models project that the increase will contribute to the precipitation especially in the Himalaya region and to the northeast of the Bay of Bengal, as well as the west coast of India. Interannual variability is found to be increasing in the higher-warming scenarios by almost all models. The CMIP6 simulations largely confirm the findings from CMIP5 models, but show an increased robustness across models with reduced uncertainties and updated magnitudes towards a stronger increase in monsoon rainfall.

Increased Temperatures Overwhelm Precipitation Changes Leading to Streamflow Declines in the Colorado River Basin

2021 ◽  
Author(s):  
Kristen Whitney ◽  
Enrique Vivoni ◽  
Theodore Bohn ◽  
Zhaocheng Wang ◽  
Mu Xiao ◽  
...  
Keyword(s):  
Climate Change ◽  
River Basin ◽  
Land Surface ◽  
Climate Models ◽  
Colorado River ◽  
Emission Scenario ◽  
Grand Canyon ◽  
Colorado River Basin ◽  
Cmip5 Models ◽  
Infiltration Capacity

<p>The Colorado River Basin (CRB) has experienced widespread and prolonged drought in the 21<sup>st</sup> century with recent precipitation (<em>P</em>) up to 25% below historical means and air temperature (<em>T</em>) up to 0.8 <sup>o</sup>C warmer. The extent that continued warming will lead to streamflow (<em>Q</em>) decline is unclear given the high interannual variability of P. Here we explore physically plausible ways that climate change could impact <em>Q</em> using the Variable Infiltration Capacity (VIC) model. We integrated advances in VIC using Landsat- and MODIS-based products to produce more realistic land surface conditions and used this setup to simulate long-range <em>Q</em> projections. Meteorological datasets were sourced from gridded daily observations (1950-2013) and downscaled historical (1950-2005) and future projections (2006-2099) derived from multiple CMIP5 models under a low and a high emission scenario to explore forcing uncertainties and cases where <em>P</em> increase could offset warming. We compared the impacts of anticipated climate change on hydrologic responses in subbasins key for water management to gauge their importance for basin-wide water budgets and how these relationships could evolve in time, as this has been a largely unexplored aspect in the CRB. Results showed that spatial gradients in seasonal <em>P</em> changes led to contrasting seasonal responses in runoff (<em>R</em>) across the CRB. Whereas most of the Upper Basin had a shift to greater <em>R</em> during the winter, summer <em>R</em> declined over most of the CRB due to heightened evapotranspiration in the northwest (Green, Upper Colorado, Glen Canyon, and Grand Canyon subbasins) and large <em>P </em>decline in the southeast (San Juan, Little Colorado, and Gila subbasins). The strength of seasonal runoff signals across different climate models and their impacts to annual <em>Q</em> were dependent on subbasin area and emission scenario. Annual <em>Q</em> at the CRB outlet declined in most cases, however, reflecting the pervasive drying effect of warming.</p>

scholarly journals Projections of future meteorological drought and wet periods in the Amazon

2015 ◽  
Vol 112 (43) ◽  
pp. 13172-13177 ◽  
Author(s):  
Philip B. Duffy ◽  
Paulo Brando ◽  
Gregory P. Asner ◽  
Christopher B. Field
Keyword(s):  
Climate Change ◽  
Tree Mortality ◽  
Climate Models ◽  
Coupled Model ◽  
Meteorological Drought ◽  
Cmip5 Models ◽  
The North ◽  
Sea Surface Temperature Anomalies ◽  
Amazonian Forests ◽  
Meteorological Droughts

Future intensification of Amazon drought resulting from climate change may cause increased fire activity, tree mortality, and emissions of carbon to the atmosphere across large areas of Amazonia. To provide a basis for addressing these issues, we examine properties of recent and future meteorological droughts in the Amazon in 35 climate models participating in the Coupled Model Intercomparison Project Phase 5 (CMIP5). We find that the CMIP5 climate models, as a group, simulate important properties of historical meteorological droughts in the Amazon. In addition, this group of models reproduces observed relationships between Amazon precipitation and regional sea surface temperature anomalies in the tropical Pacific and the North Atlantic oceans. Assuming the Representative Concentration Pathway 8.5 scenario for future drivers of climate change, the models project increases in the frequency and geographic extent of meteorological drought in the eastern Amazon, and the opposite in the West. For the region as a whole, the CMIP5 models suggest that the area affected by mild and severe meteorological drought will nearly double and triple, respectively, by 2100. Extremes of wetness are also projected to increase after 2040. Specifically, the frequency of periods of unusual wetness and the area affected by unusual wetness are projected to increase after 2040 in the Amazon as a whole, including in locations where annual mean precipitation is projected to decrease. Our analyses suggest that continued emissions of greenhouse gases will increase the likelihood of extreme events that have been shown to alter and degrade Amazonian forests.

scholarly journals Water Budgets of Managed Forests in Northeast Germany under Climate Change—Results from a Model Study on Forest Monitoring Sites

2021 ◽  
Vol 11 (5) ◽  
pp. 2403
Author(s):  
Daniel Ziche ◽  
Winfried Riek ◽  
Alexander Russ ◽  
Rainer Hentschel ◽  
Jan Martin
Keyword(s):  
Climate Change ◽  
Climate Models ◽  
Regional Climate ◽  
Coupled Model ◽  
Regional Climate Models ◽  
Realistic Model ◽  
Forest Monitoring ◽  
Climate Change Scenarios ◽  
Historical Time ◽  
Time Period

To develop measures to reduce the vulnerability of forests to drought, it is necessary to estimate specific water balances in sites and to estimate their development with climate change scenarios. We quantified the water balance of seven forest monitoring sites in northeast Germany for the historical time period 1961–2019, and for climate change projections for the time period 2010–2100. We used the LWF-BROOK90 hydrological model forced with historical data, and bias-adjusted data from two models of the fifth phase of the Coupled Model Intercomparison Project (CMIP5) downscaled with regional climate models under the representative concentration pathways (RCPs) 2.6 and 8.5. Site-specific monitoring data were used to give a realistic model input and to calibrate and validate the model. The results revealed significant trends (evapotranspiration, dry days (actual/potential transpiration < 0.7)) toward drier conditions within the historical time period and demonstrate the extreme conditions of 2018 and 2019. Under RCP8.5, both models simulate an increase in evapotranspiration and dry days. The response of precipitation to climate change is ambiguous, with increasing precipitation with one model. Under RCP2.6, both models do not reveal an increase in drought in 2071–2100 compared to 1990–2019. The current temperature increase fits RCP8.5 simulations, suggesting that this scenario is more realistic than RCP2.6.

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