Northern Hemisphere permafrost map based on TTOP modelling for 2000–2016 at 1 km2 scale

Obu, Jaroslav; Westermann, Sebastian; Bartsch, Annett; Berdnikov, Nikolai M.; Christiansen, Hanne H.; Dashtseren, Avirmed; Delaloye, Reynald; Elberling, Bo; Etzelmüller, Bernd; Kholodov, Alexander; Khomutov, Artem; Kääb, Andreas; Leibman, Marina; Lewkowicz, Antoni G.; Panda, Santosh K.; Romanovsky, V. E.; Way, Robert G.; Westergaard‐Nielsen, Andreas; Wu, Tonghua; Yamkhin, Jambaljav; Zou, Defu

doi:10.1016/j.earscirev.2019.04.023

Cited by 670 publications

(669 citation statements)

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“…Overall there is some uncertainty in the proportion of the land surface with M AAT < 0 • C that contains permafrost -the observational estimates are 0.55, 0.62 and 0.77. The Brown et al (1998) data have a similar value for the P F af f area but a higher probability of finding permafrost at air temperature less than -4.3 • C. Overall the CCI-PF data (Obu et al, 2019) shows consistently less permafrost M AGST at 20 cm and M AGT . A full description of these data and their post-processing are included in Zhang et al (2018).…”

Section: Permafrost Extentmentioning

confidence: 80%

“…The Climate Change Initiative permafrost (CCI-PF) reanalysis data set (Obu et al, 2019) is a recently developed data set that supplies the mean annual ground temperature (M AGT ) and the probability of permafrost for each grid cell. These were 105 derived from an equilibrium model of permafrost at 1 km resolution and provide a snapshot of the 2000-2016 period.…”

Section: Permafrost Extentmentioning

confidence: 99%

“…The inclusion of organic soils and the addition of a moss layer improves the insulating capacity and ability of the soil to hold water and will reduce this thaw depth (Chadburn et al, 2015). (Brown et al, 2003;Obu et al, 2019;Chadburn et al, 2017) available for evaluation and this paper introduces an observational-based estimate of annual thawed and frozen volume by extrapolating the site specific relationship between annual mean thawed fraction ( D) and M AGT to the 360 larger scale using the CCI-PF data set. Figure 9 shows the relationship between annual mean thawed fraction ( D) and M AGT for the available CALM and GTNP data sets is relatively well constrained.…”

Section: Mean Annual Ground Temperaturementioning

confidence: 99%

“…The thermal offset between the soil surface and the top of the permafrost is 45 mainly due to the seasonal changes of the thermal conductivity between the soil surface and the top of the permafrost -the top of the permafrost tends to be slightly colder than the soil surface temperature (Smith and Riseborough, 2002). Figure 1 shows a schematic of this climate-permafrost relationship which was parameterised by (Smith and Riseborough, 2002;Obu et al, 2019). In fact Obu et al (2019) developed a large-scale and high resolution observations-based estimate of mean annual ground temperature and probability of permafrost using this framework.…”

mentioning

confidence: 99%

“…Figure 1 shows a schematic of this climate-permafrost relationship which was parameterised by (Smith and Riseborough, 2002;Obu et al, 2019). In fact Obu et al (2019) developed a large-scale and high resolution observations-based estimate of mean annual ground temperature and probability of permafrost using this framework. Figure 1.…”

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confidence: 99%

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Evaluating permafrost physics in the CMIP6 models and their sensitivity to climate change

Burke

Krinner

2020

Preprint

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Abstract. Permafrost is an important component of the Arctic system and its future fate is likely to control changes in northern high latitude hydrology and biogeochemistry. Here we evaluate the permafrost dynamics in the global models participating in the Coupled Model Intercomparison Project (present generation – CMIP6; previous generation – CMIP5) along with the the sensitivity of permafrost to climate change. Whilst the northern high latitude air temperatures are relatively well simulated by the climate models, they do introduce a bias into any subsequent model estimate of permafrost. Therefore evaluation metrics are defined in relation to the air temperature. This paper shows the climate, snow and permafrost physics of the CMIP6 multi-model ensemble is very similar to that of the CMIP5 multi-model ensemble. The main difference is that a small number of models have demonstrably better snow insulation in CMIP6 than in CMIP5 which improves their representation of the permafrost extent. The simulation of maximum summer thaw depth does not improve between CMIP5 and CMIP6. We suggest that models should include a better resolved and deeper soil profile as a first step towards addressing this. We use the annual mean thawed volume of the top 2 m of the soil defined from the model soil profiles for the permafrost region to quantify changes in permafrost dynamics. The CMIP6 models suggest this is projected to increase by 20–30 %/°C of global mean temperature increase. Under climate change and in equilibrium this may result in an additional 80–120 Gt C/°C of permafrost carbon becoming vulnerable to decomposition.

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Section: Permafrost Extentmentioning

confidence: 80%

Section: Permafrost Extentmentioning

confidence: 99%

Section: Mean Annual Ground Temperaturementioning

confidence: 99%

mentioning

confidence: 99%

mentioning

confidence: 99%

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Evaluating permafrost physics in the CMIP6 models and their sensitivity to climate change

Burke

Krinner

2020

Preprint

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Current and past climate co‐shape community‐level plant species richness in the Western Siberian Arctic

Zemlianskii,

Brun,

Zimmermann

et al. 2024

Ecology and Evolution

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The Arctic ecosystems and their species are exposed to amplified climate warming and, in some regions, to rapidly developing economic activities. This study assesses, models, and maps the geographic patterns of community‐level plant species richness in the Western Siberian Arctic and estimates the relative impact of environmental and anthropogenic factors driving these patterns. With our study, we aim at contributing toward conservation efforts for Arctic plant diversity in the Western Siberian Arctic. We investigated the relative importance of environmental and anthropogenic predictors of community‐level plant species richness in the Western Siberian Arctic using macroecological models trained with an extensive geobotanical dataset. We included vascular plants, mosses and lichens in our analysis, as non‐vascular plants substantially contribute to species richness and ecosystem functions in the Arctic. We found that the mean community‐level plant species richness in this vast Arctic region does not decrease with increasing latitude. Instead, we identified an increase in species richness from South‐West to North‐East, which can be well explained by environmental factors. We found that paleoclimatic factors exhibit higher explained deviance compared to contemporary climate predictors, potentially indicating a lasting impact of ancient climate on tundra plant species richness. We also show that the existing protected areas cover only a small fraction of the regions with highest species richness. Our results reveal complex spatial patterns of community‐level species richness in the Western Siberian Arctic. We show that climatic factors such as temperature (including paleotemperature) and precipitation are the main drivers of plant species richness in this area, and the role of relief is clearly secondary. We suggest that while community‐level plant species richness is mostly driven by environmental factors, an improved spatial sampling will be needed to robustly and more precisely assess the impact of human activities on community‐level species richness patterns. Our approach and results can be used to design conservation strategies and to investigate drivers of plant species richness in other arctic regions.

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The predictability of near‐term forest biomass change in boreal North America

Burrell,

Cooperdock,

Potter

et al. 2024

Ecosphere

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Climate change is driving substantial changes in North American boreal forests, including changes in productivity, mortality, recruitment, and biomass. Despite the importance for carbon budgets and informing management decisions, there is a lack of near‐term (5–30 year) forecasts of expected changes in aboveground biomass (AGB). In this study, we forecast AGB changes across the North American boreal forest using machine learning, repeat measurements from 25,000 forest inventory sites, and gridded geospatial datasets. We find that AGB change can be predicted up to 30 years into the future, and that training on sites across the entire domain allows accurate predictions even in regions with only a small amount of existing field data. While predicting AGB loss is less skillful than gains, using a multi‐model ensemble can improve the accuracy in detecting change direction to >90% for observed increases, and up to 70% for observed losses. Higher stem density, winter temperatures, and the presence of temperate tree species in forest plots were positively associated with AGB change, whereas greater initial biomass, continentality (difference between mean summer and winter temperatures), prevalence of black spruce (Picea mariana), summer precipitation, and early warning metrics from long‐term remote sensing time series were negatively associated with AGB change. Across the domain, we predict nondisturbance‐induced declines in AGB at 23% of sites by 2030. The approach developed here can be used to estimate near‐future forest biomass in boreal North America and inform relevant management decisions. Our study also highlights the power of machine learning multi‐model ensembles when trained on a large volume of forest inventory plots, which could be applied to other regions with adequate plot density and spatial coverage.

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Northern Hemisphere permafrost map based on TTOP modelling for 2000–2016 at 1 km2 scale

Cited by 670 publications

References 95 publications

Evaluating permafrost physics in the CMIP6 models and their sensitivity to climate change

Evaluating permafrost physics in the CMIP6 models and their sensitivity to climate change

Current and past climate co‐shape community‐level plant species richness in the Western Siberian Arctic

The predictability of near‐term forest biomass change in boreal North America

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Northern Hemisphere permafrost map based on TTOP modelling for 2000–2016 at 1 km2 scale

Cited by 670 publications

References 95 publications

Evaluating permafrost physics in the CMIP6 models and their sensitivity to climate change

Evaluating permafrost physics in the CMIP6 models and their sensitivity to climate change

Current and past climate co‐shape community‐level plant species richness in the Western Siberian Arctic

The predictability of near‐term forest biomass change in boreal North America

Contact Info

Product

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About

Northern Hemisphere permafrost map based on TTOP modelling for 2000–2016 at 1 km2 scale