Quantifying the Anthropogenic Greenhouse Gas Contribution to the Observed Spring Snow-Cover Decline Using the CMIP6 Multimodel Ensemble

2020 ◽  
Vol 33 (21) ◽  
pp. 9261-9269
Author(s):  
Seungmok Paik ◽  
Seung-Ki Min
Keyword(s):  
Snow Cover ◽  
Greenhouse Gas ◽  
Coupled Model ◽  
Extended Period ◽  
Early Spring ◽  
Ecological Impacts ◽  
Anthropogenic Aerosol ◽  
Surface Warming ◽  
Detection And Attribution ◽  
Snow Cover Extent

AbstractThis study conducts a detection and attribution analysis of the observed changes in boreal spring snow-cover extent (SCE) for an extended period of 1925–2019 for early spring (March and April) and 1970–2019 for late spring (May and June) using updated observations and multimodel simulations from phase 6 of the Coupled Model Intercomparison Project (CMIP6). The observed and simulated SCE changes over the Northern Hemisphere (NH), Eurasia, and North America are compared using an optimal fingerprinting technique. Detection results indicate that anthropogenic influences are robustly detected in the observed SCE decrease over NH and the continental regions, in separation from natural forcing influences. In contrast to previous studies, anthropogenic response in the early spring SCE shows a consistent magnitude with observations, due to an extension of the time period to 2019. It is demonstrated for the first time that the greenhouse gas (GHG) influence is robustly detected in separation from anthropogenic aerosol and natural forcing influences, and that most of the observed spring SCE decrease is attributable to GHG influences. The observed SCE decline is also found to be closely associated with the surface warming over the corresponding extratropical lands. Our first quantification of GHG contribution to the observed SCE changes has important implications for reliable future projections of the SCE changes and its hydrological and ecological impacts.

scholarly journals Detection and Attribution of Observed Changes in Northern Hemisphere Spring Snow Cover

2013 ◽  
Vol 26 (18) ◽  
pp. 6904-6914 ◽  
Author(s):  
David E. Rupp ◽  
Philip W. Mote ◽  
Nathaniel L. Bindoff ◽  
Peter A. Stott ◽  
David A. Robinson
Keyword(s):  
Snow Cover ◽  
Northern Hemisphere ◽  
Climate Models ◽  
Global Climate ◽  
Coupled Model ◽  
Internal Variability ◽  
Global Climate Models ◽  
Anthropogenic Forcing ◽  
Detection And Attribution ◽  
Snow Cover Extent

Abstract Significant declines in spring Northern Hemisphere (NH) snow cover extent (SCE) have been observed over the last five decades. As one step toward understanding the causes of this decline, an optimal fingerprinting technique is used to look for consistency in the temporal pattern of spring NH SCE between observations and simulations from 15 global climate models (GCMs) that form part of phase 5 of the Coupled Model Intercomparison Project. The authors examined simulations from 15 GCMs that included both natural and anthropogenic forcing and simulations from 7 GCMs that included only natural forcing. The decline in observed NH SCE could be largely explained by the combined natural and anthropogenic forcing but not by natural forcing alone. However, the 15 GCMs, taken as a whole, underpredicted the combined forcing response by a factor of 2. How much of this underprediction was due to underrepresentation of the sensitivity to external forcing of the GCMs or to their underrepresentation of internal variability has yet to be determined.

scholarly journals Causes of Robust Seasonal Land Precipitation Changes*

2013 ◽  
Vol 26 (17) ◽  
pp. 6679-6697 ◽  
Author(s):  
Debbie Polson ◽  
Gabriele C. Hegerl ◽  
Xuebin Zhang ◽  
Timothy J. Osborn
Keyword(s):  
Greenhouse Gas ◽  
Coupled Model ◽  
Anthropogenic Aerosol ◽  
Detection And Attribution ◽  
Aerosol Forcing ◽  
External Forcings ◽  
Spatial Coverage ◽  
Intercomparison Project ◽  
Precipitation Changes

Abstract Historical simulations from phase 5 of the Coupled Model Intercomparison Project (CMIP5) archive are used to calculate the zonal-mean change in seasonal land precipitation for the second half of the twentieth century in response to a range of external forcings, including anthropogenic and natural forcings combined (ALL), greenhouse gas forcing, anthropogenic aerosol forcing, anthropogenic forcings combined, and natural forcing. These simulated patterns of change are used as fingerprints in a detection and attribution study applied to four different gridded observational datasets of global land precipitation from 1951 to 2005. There are large differences in the spatial and temporal coverage in the observational datasets. Yet despite these differences, the zonal-mean patterns of change are mostly consistent except at latitudes where spatial coverage is limited. The results show some differences between datasets, but the influence of external forcings is robustly detected in March–May, December–February, and for annual changes for the three datasets more suitable for studying changes. For June–August and September–November, external forcing is only detected for the dataset that includes only long-term stations. Fingerprints for combinations of forcings that include the effect of greenhouse gases are similarly detectable to those for ALL forcings, suggesting that greenhouse gas influence drives the detectable features of the ALL forcing fingerprint. Fingerprints of only natural or only anthropogenic aerosol forcing are not detected. This, together with two-fingerprint results, suggests that at least some of the detected change in zonal land precipitation can be attributed to human influences.

scholarly journals Historical Northern Hemisphere snow cover trends and projected changes in the CMIP-6 multi-model ensemble

2020 ◽  
Author(s):  
Lawrence Mudryk ◽  
Maria Santolaria-Otín ◽  
Gerhard Krinner ◽  
Martin Ménégoz ◽  
Chris Derksen ◽  
...  
Keyword(s):  
Snow Cover ◽  
Northern Hemisphere ◽  
Coupled Model ◽  
Surface Air Temperature ◽  
Research Programme ◽  
Fast Response ◽  
Model Ensemble ◽  
Near Surface ◽  
Snow Cover Extent ◽  
Snow Mass

Abstract. This paper presents an analysis of observed and simulated historical snow cover extent and snow mass, along with future snow cover projections from models participating in the 6th phase of the World Climate Research Programme Coupled Model Inter-comparison Project (CMIP-6). Where appropriate, the CMIP-6 output is compared to CMIP-5 results in order to assess progress (or absence thereof) between successive model generations. An ensemble of six products are used to produce a new time series of northern hemisphere snow extent anomalies and trends; a subset of four of these products are used for snow mass. Trends in snow extent over 1981–2018 are negative in all months, and exceed −50 × 103 km2 during November, December, March, and May. Snow mass trends are approximately −5 Gt/year or more for all months from December to May. Overall, the CMIP-6 multi-model ensemble better represents the snow extent climatology over the 1981–2014 period for all months, correcting a low bias in CMIP-5. Simulated snow extent and snow mass trends over the 1981–2014 period are slightly stronger in CMIP-6 than in CMIP-5, although large inter-model spread remains in the simulated trends for both variables. There is a single linear relationship between projected spring snow extent and global surface air temperature (GSAT) changes, which is valid across all scenarios. This finding suggests that Northern Hemisphere spring snow extent will decrease by about 8 % relative to the 1995–2014 level per °C of GSAT increase. The sensitivity of snow to temperature forcing largely explains the absence of any climate change pathway dependency, similar to other fast response components of the cryosphere such as sea ice and near surface permafrost.

The role of GCM resolution in simulating glacial inception

The Holocene ◽  
2011 ◽  
Vol 21 (5) ◽  
pp. 819-830 ◽  
Author(s):  
Steve Vavrus ◽  
Gwenaëlle Philippon-Berthier ◽  
John E. Kutzbach ◽  
William F. Ruddiman
Keyword(s):  
Snow Cover ◽  
Greenhouse Gas ◽  
Moisture Flux ◽  
Laurentide Ice Sheet ◽  
Baffin Island ◽  
Enhanced Sensitivity ◽  
Snow Cover Extent ◽  
Orbital Configuration ◽  
Northern Rockies ◽  
Pressure Changes

We test the influence of model resolution on glacial inception using a coupled atmosphere–slab ocean version of NCAR’s CCSM3 GCM. Simulations employ a modern orbital configuration and greenhouse gas concentrations representing both recent (year 1990) and hypothetically lower values based on Ruddiman’s Early Anthropogenic Hypothesis (240 ppm CO2, 450 ppb CH4). We ran the model at two different horizontal resolutions: relatively coarse (spectral T42, approximately 2.8°) and comparatively fine (T85, approximately 1.4°). Under contemporary greenhouse forcing, permanent boreal snow cover extent in the two model configurations is similar, but lowering greenhouse gas concentrations generates much more extensive glacial inception in the T85 experiment (150% increase) than at T42 resolution (80% increase). Furthermore, the spatial patterns of glacial inception differ considerably. Only the T85 version produces permanent snow cover over the Rocky Mountains and Baffin Island, consistent with geologic evidence for early glaciation in the northern Rockies and Laurentide ice sheet nucleation in northeastern Canada. Although enhanced sensitivity at higher resolution is largely attributable to the expected colder and wetter conditions over elevated topography, much of the response is also driven dynamically. Atmospheric pressure changes at the surface and aloft differ considerably between model resolutions. The T85 circulation anomalies favor a stronger onshore moisture flux and therefore more snowfall over the northern Rockies and Baffin Island. Although these experiments are driven by greenhouse forcing rather than orbital anomalies, our findings may apply to general mechanisms of glacial inception.

scholarly journals Quantifying the Uncertainty in Historical and Future Simulations of Northern Hemisphere Spring Snow Cover

2016 ◽  
Vol 29 (23) ◽  
pp. 8647-8663 ◽  
Author(s):  
Chad W. Thackeray ◽  
Christopher G. Fletcher ◽  
Lawrence R. Mudryk ◽  
Chris Derksen
Keyword(s):  
Snow Cover ◽  
Northern Hemisphere ◽  
Climate Model ◽  
Coupled Model ◽  
Internal Variability ◽  
Winter Precipitation ◽  
First Century ◽  
Internal Climate Variability ◽  
Snow Cover Extent ◽  
Twenty First Century

Abstract Projections of twenty-first-century Northern Hemisphere (NH) spring snow cover extent (SCE) from two climate model ensembles are analyzed to characterize their uncertainty. Phase 5 of the Coupled Model Intercomparison Project (CMIP5) multimodel ensemble exhibits variability resulting from both model differences and internal climate variability, whereas spread generated from a Canadian Earth System Model–Large Ensemble (CanESM-LE) experiment is solely a result of internal variability. The analysis shows that simulated 1981–2010 spring SCE trends are slightly weaker than observed (using an ensemble of snow products). Spring SCE is projected to decrease by −3.7% ± 1.1% decade−1 within the CMIP5 ensemble over the twenty-first century. SCE loss is projected to accelerate for all spring months over the twenty-first century, with the exception of June (because most snow in this month has melted by the latter half of the twenty-first century). For 30-yr spring SCE trends over the twenty-first century, internal variability estimated from CanESM-LE is substantial, but smaller than intermodel spread from CMIP5. Additionally, internal variability in NH extratropical land warming trends can affect SCE trends in the near future (R2 = 0.45), while variability in winter precipitation can also have a significant (but lesser) impact on SCE trends. On the other hand, a majority of the intermodel spread is driven by differences in simulated warming (dominant in March–May) and snow cover available for melt (dominant in June). The strong temperature–SCE linkage suggests that model uncertainty in projections of SCE could be potentially reduced through improved simulation of spring season warming over land.

scholarly journals Evaluation of snow cover and snow water equivalent in the continental Arctic in CMIP5 models

2020 ◽  
Vol 55 (11-12) ◽  
pp. 2993-3016
Author(s):  
María Santolaria-Otín ◽  
Olga Zolina
Keyword(s):  
Snow Cover ◽  
Climate Models ◽  
Snow Water Equivalent ◽  
Coupled Model ◽  
Cmip5 Models ◽  
Spatial And Temporal Patterns ◽  
Multiple Data ◽  
Snow Cover Extent ◽  
Snow Water ◽  
Intercomparison Project

Abstract Spatial and temporal patterns of snow cover extent (SCE) and snow water equivalent (SWE) over the terrestrial Arctic are analyzed based on multiple observational datasets and an ensemble of CMIP5 models during 1979–2005. For evaluation of historical simulations of the Coupled Model Intercomparison Project (CMIP5) ensemble, we used two reanalysis products, one satellite-observed product and an ensemble of different datasets. The CMIP5 models tend to significantly underestimate the observed SCE in spring but are in better agreement with observations in autumn; overall, the observed annual SCE cycle is well captured by the CMIP5 ensemble. In contrast, for SWE, the annual cycle is significantly biased, especially over North America, where some models retain snow even in summer, in disagreement with observations. The snow margin position (SMP) in the CMIP5 historical simulations is in better agreement with observations in spring than in autumn, when close agreement across the CMIP5 models is only found in central Siberia. Historical experiments from most CMIP5 models show negative pan-Arctic trends in SCE and SWE. These trends are, however, considerably weaker (and less statistically significant) than those reported from observations. Most CMIP5 models can more accurately capture the trend pattern of SCE than that of SWE, which shows quantitative and qualitative differences with the observed trends over Eurasia. Our results demonstrate the importance of using multiple data sources for the evaluation of snow characteristics in climate models. Further developments should focus on the improvement of both dataset quality and snow representation in climate models, especially ESM-SnowMIP.

scholarly journals Observed high-altitude warming and snow cover retreat over Tibet and the Himalayas enhanced by black carbon aerosols

2016 ◽  
Vol 16 (3) ◽  
pp. 1303-1315 ◽  
Author(s):  
Y. Xu ◽  
V. Ramanathan ◽  
W. M. Washington
Keyword(s):  
Tibetan Plateau ◽  
High Altitude ◽  
Snow Cover ◽  
Black Carbon ◽  
Global Climate Model ◽  
Anthropogenic Factors ◽  
Climate Projections ◽  
The Tibetan Plateau ◽  
Surface Warming ◽  
Snow Cover Extent

Abstract. Himalayan mountain glaciers and the snowpack over the Tibetan Plateau provide the headwater of several major rivers in Asia. In situ observations of snow cover extent since the 1960s suggest that the snowpack in the region have retreated significantly, accompanied by a surface warming of 2–2.5 °C observed over the peak altitudes (5000 m). Using a high-resolution ocean–atmosphere global climate model and an observationally constrained black carbon (BC) aerosol forcing, we attribute the observed altitude dependence of the warming trends as well as the spatial pattern of reductions in snow depths and snow cover extent to various anthropogenic factors. At the Tibetan Plateau altitudes, the increase in atmospheric CO2 concentration exerted a warming of 1.7 °C, BC 1.3 °C where as cooling aerosols cause about 0.7 °C cooling, bringing the net simulated warming consistent with the anomalously large observed warming. We therefore conclude that BC together with CO2 has contributed to the snow retreat trends. In particular, BC increase is the major factor in the strong elevation dependence of the observed surface warming. The atmospheric warming by BC as well as its surface darkening of snow is coupled with the positive snow albedo feedbacks to account for the disproportionately large role of BC in high-elevation regions. These findings reveal that BC impact needs to be properly accounted for in future regional climate projections, in particular on high-altitude cryosphere.

scholarly journals Historical Northern Hemisphere snow cover trends and projected changes in the CMIP6 multi-model ensemble

2020 ◽  
Vol 14 (7) ◽  
pp. 2495-2514 ◽  
Author(s):  
Lawrence Mudryk ◽  
María Santolaria-Otín ◽  
Gerhard Krinner ◽  
Martin Ménégoz ◽  
Chris Derksen ◽  
...  
Keyword(s):  
Snow Cover ◽  
Northern Hemisphere ◽  
Coupled Model ◽  
Surface Air Temperature ◽  
Research Programme ◽  
Fast Response ◽  
Model Ensemble ◽  
Near Surface ◽  
Snow Cover Extent ◽  
Snow Mass

Abstract. This paper presents an analysis of observed and simulated historical snow cover extent and snow mass, along with future snow cover projections from models participating in the World Climate Research Programme Coupled Model Intercomparison Project Phase 6 (CMIP6). Where appropriate, the CMIP6 output is compared to CMIP5 results in order to assess progress (or absence thereof) between successive model generations. An ensemble of six observation-based products is used to produce a new time series of historical Northern Hemisphere snow extent anomalies and trends; a subset of four of these products is used for snow mass. Trends in snow extent over 1981–2018 are negative in all months and exceed -50×103 km2 yr−1 during November, December, March, and May. Snow mass trends are approximately −5 Gt yr−1 or more for all months from December to May. Overall, the CMIP6 multi-model ensemble better represents the snow extent climatology over the 1981–2014 period for all months, correcting a low bias in CMIP5. Simulated snow extent and snow mass trends over the 1981–2014 period are stronger in CMIP6 than in CMIP5, although large inter-model spread remains in the simulated trends for both variables. There is a single linear relationship between projected spring snow extent and global surface air temperature (GSAT) changes, which is valid across all CMIP6 Shared Socioeconomic Pathways. This finding suggests that Northern Hemisphere spring snow extent will decrease by about 8 % relative to the 1995–2014 level per degree Celsius of GSAT increase. The sensitivity of snow to temperature forcing largely explains the absence of any climate change pathway dependency, similar to other fast-response components of the cryosphere such as sea ice and near-surface permafrost extent.

scholarly journals Incorrect Asian aerosols affecting the attribution and projection of regional climate change in CMIP6 models

2021 ◽  
Vol 4 (1) ◽  
Author(s):  
Zhili Wang ◽  
Lei Lin ◽  
Yangyang Xu ◽  
Huizheng Che ◽  
Xiaoye Zhang ◽  
...  
Keyword(s):  
Climate Change ◽  
Radiative Forcing ◽  
Impact Analysis ◽  
Climate Model ◽  
Regional Climate ◽  
Eastern China ◽  
Coupled Model ◽  
Regional Climate Change ◽  
Anthropogenic Aerosol ◽  
Wide Range

AbstractAnthropogenic aerosol (AA) forcing has been shown as a critical driver of climate change over Asia since the mid-20th century. Here we show that almost all Coupled Model Intercomparison Project Phase 6 (CMIP6) models fail to capture the observed dipole pattern of aerosol optical depth (AOD) trends over Asia during 2006–2014, last decade of CMIP6 historical simulation, due to an opposite trend over eastern China compared with observations. The incorrect AOD trend over China is attributed to problematic AA emissions adopted by CMIP6. There are obvious differences in simulated regional aerosol radiative forcing and temperature responses over Asia when using two different emissions inventories (one adopted by CMIP6; the other from Peking university, a more trustworthy inventory) to driving a global aerosol-climate model separately. We further show that some widely adopted CMIP6 pathways (after 2015) also significantly underestimate the more recent decline in AA emissions over China. These flaws may bring about errors to the CMIP6-based regional climate attribution over Asia for the last two decades and projection for the next few decades, previously anticipated to inform a wide range of impact analysis.

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