High-resolution monthly precipitation and temperature time series from 2006 to 2100

Karger, Dirk Nikolaus; Schmatz, Dirk R.; Dettling, Gabriel; Zimmermann, Niklaus E.

doi:10.1038/s41597-020-00587-y

Cited by 116 publications

(96 citation statements)

References 70 publications

(82 reference statements)

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“…From these downscaled CHELSA 1.2 time series, we derived four climate variables to retrace past conditions during the establishment of today's adult trees: yearly mean temperature and precipitation sum, and mean temperature and summed precipitation over the growing season (May–October). For future data, we used the CHELSA cmip5 ts (available for RCP4.5 and RCP8.5; Karger et al, 2020) based on the five most informative models (Sanderson et al, 2015) in the Alps for the reference period 2061–2080. Projected future climate variables were taken from five global circulation models (GCMs), which were downscaled to 1 km × 1 km resolution using an additive (for temperature), or multiplicative (for precipitation) change factor method using CHELSA 1.2 as a baseline.…”

Section: Methodsmentioning

confidence: 99%

Genomic vulnerability to rapid climate warming in a tree species with a long generation time

Dauphin

Rellstab

Schmid

et al. 2020

Global Change Biology

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The ongoing increase in global temperature affects biodiversity, especially in mountain regions where climate change is exacerbated. As sessile, long‐lived organisms, trees are especially challenged in terms of adapting to rapid climate change. Here, we show that low rates of allele frequency shifts in Swiss stone pine (Pinus cembra) occurring near the treeline result in high genomic vulnerability to future climate warming, presumably due to the species’ long generation time. Using exome sequencing data from adult and juvenile cohorts in the Swiss Alps, we found an average rate of allele frequency shift of 1.23 × 10−2/generation (i.e. 40 years) at presumably neutral loci, with similar rates for putatively adaptive loci associated with temperature (0.96 × 10−2/generation) and precipitation (0.91 × 10−2/generation). These recent shifts were corroborated by forward‐in‐time simulations at neutral and adaptive loci. Additionally, in juvenile trees at the colonisation front we detected alleles putatively beneficial under a future warmer and drier climate. Notably, the observed past rate of allele frequency shift in temperature‐associated loci was decidedly lower than the estimated average rate of 6.29 × 10−2/generation needed to match a moderate future climate scenario (RCP4.5). Our findings suggest that species with long generation times may have difficulty keeping up with the rapid climate change occurring in high mountain areas and thus are prone to local extinction in their current main elevation range.

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Section: Methodsmentioning

confidence: 99%

Genomic vulnerability to rapid climate warming in a tree species with a long generation time

Dauphin

Rellstab

Schmid

et al. 2020

Global Change Biology

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“…resolution in a World Mercator projection. Orographic precipitation effects are less pronounced just above the surface, as well as in the free atmosphere above the planetary boundary layer (Daly et al, 1997;Karger et al, 2020;Oke, 2002;Stull, 2012). The highest impact of orography is considered just at the boundary layer height where the airflow interacts with the terrain.…”

Section: Precipitation Estimationmentioning

confidence: 99%

“…For the recent past the gap between the coarse GCM resolution and the high resolution needed has be bridged using satellite data (Biasutti et al, 2011;Funk et al, 2015;Huffman et al, 2007), statistical downscaling (Karger et al, 2017a(Karger et al, , 2020Maraun et al, 2010;Schmidli et al, 2006;Wilby et al, 1998;Wood et al, 2004), dynamical downscaling (Skamarock et al, 2019), or interpolation of meteorological station data (Daly et al, 1997;Harris et al, 2020;Hijmans et al, 2005;Meyer-Christoffer et al, 2015). While all of these methods work comparably well for current climatic conditions, satellite or station data are not available before the 19 th Century (end of the 20 th century for satellite data), hampering an application of said methods to paleoclimatic models.…”

Section: Introductionmentioning

confidence: 99%

CHELSA-TraCE21k v1.0. Downscaled transient temperature and precipitation data since the last glacial maximum

Karger

Nobis

Normand

et al. 2021

Preprint

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Abstract. High resolution, downscaled climate model data are used in a wide variety of applications in environmental sciences. Here we present the CHELSA-TraCE21k downscaling algorithm to create global monthly climatologies for temperature and precipitation at 30 arcsec spatial resolution in 100 year time steps for the last 21,000 years. Paleo orography at high spatial resolution and at each timestep is created by combining high resolution information on glacial cover from current and Last Glacial Maximum (LGM) glacier databases with the interpolation of a dynamic ice sheet model (ICE6G) and a coupling to mean annual temperatures from CCSM3-TraCE21k. Based on the reconstructed paleo orography, mean annual temperature and precipitation was downscaled using the CHELSA V1.2 algorithm. The data were validated by comparisons with the glacial extent of the Laurentide ice shield based on expert delineations, proxy data from Greenland ice cores, historical climate data from meteorological stations, and a dynamic simulation of species a distribution throughout the Holocene. Validations show that CHELSA TraCE21k output creates a reasonable representation of the distribution of temperature and precipitation through time at a high spatial resolution, and simulations based on the data are capable of detecting effective LGM refugia of species.

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“…S4a). The growing CO 2 concentrations can either increase AGB through enhanced photosynthetic rates (Fay et al, 2012;Lee et al, 2010) or have limited influences because of other environmental constraints on plant growth (Brookshire and Weaver, 2015). In this study, we deduced future AGB dynamics both including and not including the effect of CO 2 enrichment on grassland AGB.…”

Section: Regional Mapping and Uncertainty Analysismentioning

confidence: 99%

“…Furthermore, it has been reported that carbon dioxide (CO 2 ) enrichment may increase plant productivity through enhancing photosynthetic rates and reducing stomatal conductance, thereby increasing water use efficiency (Fay et al, 2012;Pastore et al, 2019). This might provide an opportunity to mitigate or even reverse the harmful effects of other environmental changes on grassland AGB (Lee et al, 2010), e.g. the enhanced water limitations resulting from climate warming.…”

Section: Introductionmentioning

confidence: 99%

Simulating the spatiotemporal variations in aboveground biomass in Inner Mongolian grasslands under environmental changes

et al. 2021

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Abstract. Grassland aboveground biomass (AGB) is a critical component of the global carbon cycle and reflects ecosystem productivity. Although it is widely acknowledged that dynamics of grassland biomass is significantly regulated by climate change, in situ evidence at meaningfully large spatiotemporal scales is limited. Here, we combine biomass measurements from six long-term (> 30 years) experiments and data in existing literatures to explore the spatiotemporal changes in AGB in Inner Mongolian temperate grasslands. We show that, on average, annual AGB over the past 4 decades is 2561, 1496 and 835 kg ha−1, respectively, in meadow steppe, typical steppe and desert steppe in Inner Mongolia. The spatiotemporal changes of AGB are regulated by interactions of climatic attributes, edaphic properties, grassland type and livestock. Using a machine-learning-based approach, we map annual AGB (from 1981 to 2100) across the Inner Mongolian grasslands at the spatial resolution of 1 km. We find that on the regional scale, meadow steppe has the highest annual AGB, followed by typical and desert steppe. Future climate change characterized mainly by warming could lead to a general decrease in grassland AGB. Under climate change, on average, compared with the historical AGB (i.e. average of 1981–2019), the AGB at the end of this century (i.e. average of 2080–2100) would decrease by 14 % under Representative Concentration Pathway (RCP) 4.5 and 28 % under RCP8.5. If the carbon dioxide (CO2) enrichment effect on AGB is considered, however, the estimated decreases in future AGB can be reversed due to the growing atmospheric CO2 concentrations under both RCP4.5 and RCP8.5. The projected changes in AGB show large spatial and temporal disparities across different grassland types and RCP scenarios. Our study demonstrates the accuracy of predictions in AGB using a modelling approach driven by several readily obtainable environmental variables and provides new data at a large scale and fine resolution extrapolated from field measurements.

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High-resolution monthly precipitation and temperature time series from 2006 to 2100

Cited by 116 publications

References 70 publications

Genomic vulnerability to rapid climate warming in a tree species with a long generation time

Genomic vulnerability to rapid climate warming in a tree species with a long generation time

CHELSA-TraCE21k v1.0. Downscaled transient temperature and precipitation data since the last glacial maximum

Simulating the spatiotemporal variations in aboveground biomass in Inner Mongolian grasslands under environmental changes

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