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2013 Simulated EnMAP Mosaics for the Lake Tahoe region, USA

This dataset is composed of three-season simulated EnMAP mosaics for the Lake Tahoe region, USA. HyspIRI Airborne Campaign AVIRIS imagery from spring, summer and fall formed the basis for simulating EnMAP data with 30 m spatial resolution and 195 spectral bands ranging from 420 to 2450 nm. The mosaics are provided as Analysis-Ready-Datasets (tiled surface reflectance products) to be used for regional-scale and multi-season hyperspectral image analysis of California’s diverse ecoregions. The dataset primarily intends to support the development of processing algorithms and to demonstrate spaceborne hyperspectral data capabilities during the pre-launch activities of the forthcoming EnMAP mission. This dataset was processed in line with companion simulated EnMAP mosaics for the San Francisco Bay Area and for the Santa Barbara region.

2013 Simulated EnMAP Mosaics for the Santa Barbara region, USA

This dataset is composed of three-season simulated EnMAP mosaics for the Santa Barbara region, USA. HyspIRI Airborne Campaign AVIRIS imagery from spring, summer and fall formed the basis for simulating EnMAP data with 30 m spatial resolution and 195 spectral bands ranging from 420 to 2450 nm. The mosaics are provided as Analysis-Ready-Datasets (tiled surface reflectance products) to be used for regional-scale and multi-season hyperspectral image analysis of California’s diverse ecoregions. The dataset primarily intends to support the development of processing algorithms and to demonstrate spaceborne hyperspectral data capabilities during the pre-launch activities of the forthcoming EnMAP mission. This dataset was processed in line with companion simulated EnMAP mosaics for the San Francisco Bay Area and for the Lake Tahoe region.

2013 Simulated EnMAP Mosaics for the San Francisco Bay Area, USA

This dataset is composed of simulated EnMAP mosaics for the San Francisco Bay Area, USA. Hyperspectral imagery used for the EnMAP simulation was collected across three time periods (Spring, Summer, and Fall) in 2013 with the AVIRIS-Classic sensor flown as part of the HyspIRI Preparatory Campaign. Flight lines were simulated to EnMAP-like data using the EnMAP end-to end Simulation tool to produce 30 x 30 m imagery with 195 bands (after band removal) ranging from 423 to 2439 nm. Secondary geometric correction was applied using automatically generated tie points, and a class-wise empirical across track brightness correction was implemented to mitigate brightness gradients.

Dataset for evaluation element fluxes released by weathering and taken up by plants along the EarthShape climate and vegetation gradient

With this data, we expand the data set characterizing the Critical Zone geochemistry along the Chilean Coastal Cordillera provided by Oeser et al. (2018). This data set completes the results of bulk geochemical analysis of bedrock and regolith with those of bulk analysis of major plants and those of the bio-available fraction in saprolite and soil (determined using a modified sequential extraction method on bulk regolith samples after Arunachalam et al., 1996; He et al., 1995; Tessier et al., 1979). For all those compartments of the Earth’s Critical Zone, we further present 87Sr/86Sr isotope ratios. A detailed graphical presentation and discussion of this data as well as method description is given in Oeser and von Blanckenburg (2020), Decoupling primary productivity from silicate weathering – how ecosystems regulate nutrient uptake along a climate and vegetation gradient.Using this data, we were thus, able to determine weathering rates and nutrient uptake along the “EarthShape” climate and vegetation gradient in the Chilean Coastal Cordillera and to identify the sources of mineral nutrients to plants. Ultimately, we were able to budget inventories, gains and losses of nutritive elements in and out of these ecosystems and to quantify nutrient recycling. We found that the weathering rate does not increase from north to south along the climate gradient. Instead, the increase in biomass growth rate is accommodated by faster nutrient recycling. The absence of an increase in weathering rate in spite of a five-fold increase in precipitation led us to hypothesize that the presence of plants even negatively impacts weathering through reducing the water flow, inducing secondary-mineral formation, and fostering a microbial community specializing on nutrient-recycling rather than nutrient-acquisition through weathering.All samples are assigned with International Geo Sample Numbers (IGSN), a globally unique and persistent Identifier for physical samples. The IGSNs are provided in the data tables and link to a comprehensive sample description in the internet.Tables included in this data publication:Table S1: Chemical composition of representative bedrock samples from Pan de Azúcar, Santa Gracia, La Campana, and Nahuelbuta.Table S2: Weathering indices CDF and τ along with radiogenic 87Sr/86Sr ratios of the 2 × 4 regolith profiles.Table S3: Concentration of the bio-available fraction, comprised of the water-soluble and the exchangeable fraction.Table S4: Concentration of the water-soluble and the exchangeable fraction, and the relative amount of the bio-available fraction (pooled water-soluble and exchangeable fraction) on bulk regolith.Table S5: Chemical composition of the study sites’ single plant organs along with their respective 87Sr/86Sr ratio.

ISIMIP2b Simulation Data from Biomes Sector

The Inter-Sectoral Impact Model Intercomparison Project (ISIMIP) provides a framework for the collation of a set of consistent, multi-sector, multi-scale climate-impact simulations, based on scientifically and politically relevant historical and future scenarios. This framework serves as a basis for robust projections of climate impacts, as well as facilitating model evaluation and improvement, allowing for advanced estimates of the biophysical and socio-economic impacts of climate change at different levels of global warming. It also provides a unique opportunity to consider interactions between climate impacts across sectors.ISIMIP2b is the second simulation round of the second phase of ISIMIP. ISIMIP2b considers impacts on different sectors at the global and regional scales: water, fisheries and marine ecosystems, energy supply and demand, forests, biomes, agriculture, agro-economic modeling, terrestrial biodiversity, permafrost, coastal infrastructure, health and lakes.ISIMIP2b simulations focus on separating the impacts and quantifying the pure climate change effects of historical warming (1861-2005) compared to pre-industrial reference levels (1661-1860); and on quantifying the future (2006-2099) and extended future (2006-2299) impact projections accounting for low (RCP2.6), mid-high (RCP6.0) and high (RCP8.5) greenhouse gas emissions, assuming either constant (year 2005) or dynamic population, land and water use and -management, economic development, bioenergy demand, and other societal factors. The scientific rationale for the scenario design is documented in Frieler et al. (2017).The ISIMIP2b bias-corrected observational climate input data (Lange, 2018; Frieler et al., 2017) consists of an updated version of the observational dataset EWEMBI at daily temporal and 0.5° spatial resolution, which better represents the CMIP5 GCM ensemble in terms of both spatial model resolution and equilibrium climate sensitivity. The bias correction methods (Lange, 2018; Frieler et al., 2017; Lange, 2016) were applied to CMIP5 output of GDFL-ESM2M, HadGEM2-ES, IPSL-CM5A-LP and MIROC5. Access to the input data for the impact models, and further information on bias correction methods, is provided through a central ISIMIP archive (see https://www.isimip.org/gettingstarted/isimip2b-bias-correction).This entry refers to the ISIMIP2b simulation data from eight global vegetation (biomes) models:CARAIBCLM4.5,DLEM,LPJmL,ORCHIDEE,VEGAS,VISIT,LPJ-GUESS----------------------------------------------------------------------------The Inter-Sectoral Impact Model Intercomparison Project (ISIMIP) simulation data is under continuous review and improvement, and updates are thus likely to happen. All changes and caveats are documented under https://www.isimip.org/outputdata/output-data-changelog/ (ISIMIP Changelog) and https://www.isimip.org/outputdata/dois-isimip-data-sets/ (ISIMIP DOI publications).----------------------------------------------------------------------------

ISIMIP2a Simulation Data from Biomes Sector (V. 1.1)

VERSION HISTORY:- On April 10, 2018 we renamed some simulation files of impact models LPJ-GUESS, ORCHIDEE, JULES-UoE and VISIT, due to the correction of social scenario label “nosoc” for “varsoc”. For impact model VISIT, “nosoc” was relabeled to “pressoc”. These data caveats were documented in the ISIMIP website (ISIMIP2a Biomes: correction of scenario names in file names).- On October 17, 2018, we republished all simulation data for all biomes sector impact models to get the data sets into the new ESGF search facet structure. There were no changes to the simulation data.The Inter-Sectoral Impact Model Intercomparison Project (ISIMIP) simulation data is under continuous review and improvement, and updates are thus likely to happen. All changes and caveats are documented under https://www.isimip.org/outputdata/output-data-changelog/.For accessing the data set as in the previous version (http://doi.org/10.5880/PIK.2017.002) before October 17, 2018 please write to the ISIMIP Data Management Team: isimip-data[at]pik-potsdam.deDATA DESCRIPTION:The Inter-Sectoral Impact Model Intercomparison Project (ISIMIP) provides a framework for the collation of a set of consistent, multi-sector, multi-scale climate-impact simulations, based on scientifically and politically-relevant historical and future scenarios. This framework serves as a basis for robust projections of climate impacts, as well as facilitating model evaluation and improvement, allowing for improved estimates of the biophysical and socio-economic impacts of climate change at different levels of global warming. It also provides a unique opportunity to consider interactions between climate change impacts across sectors.ISIMIP2a is the second ISIMIP simulation round, focusing on historical simulations (1971-2010) of climate impacts on agriculture, fisheries, permafrost, biomes, regional and global water and forests. This will serve as a basis for model evaluation and improvement, allowing for improved estimates of the biophysical and socio-economic impacts of climate change at different levels of global warming.The focus topic for ISIMIP2a is model validation, in particular with respect to the representation of impacts of extreme weather events and climate variability. During this phase, four common global observational climate data sets were provided across all impact models and sectors. In addition, appropriate observational data sets of impacts for each sector were collected, against which the models can be benchmarked. Access to all these data is provided through a central ISIMIP archive (see https://www.isimip.org/gettingstarted/#input-data-bias-correction).The ISIMIP2a biome outputs are based on simulations from 8 global vegetation (biomes) models (CARAIB, DLEM, JULES-B1, LPJ-GUESS, LPJmL, ORCHIDEE, VEGAS, VISIT) according to the ISIMIP2a protocol (https://www.isimip.org/protocol/#isimip2a).

ISIMIP2a Simulation Data from Biomes Sector

The Inter-Sectoral Impact Model Intercomparison Project (ISIMIP) provides a framework for the collation of a set of consistent, multi-sector, multi-scale climate-impact simulations, based on scientifically and politically-relevant historical and future scenarios. This framework serves as a basis for robust projections of climate impacts, as well as facilitating model evaluation and improvement, allowing for improved estimates of the biophysical and socio-economic impacts of climate change at different levels of global warming. It also provides a unique opportunity to consider interactions between climate change impacts across sectors.ISIMIP2a is the second ISIMIP simulation round, focusing on historical simulations (1971-2010) of climate impacts on agriculture, fisheries, permafrost, biomes, regional and global water and forests. This will serve as a basis for model evaluation and improvement, allowing for improved estimates of the biophysical and socio-economic impacts of climate change at different levels of global warming.The focus topic for ISIMIP2a is model validation, in particular with respect to the representation of impacts of extreme weather events and climate variability. During this phase, four common global observational climate data sets were provided across all impact models and sectors. In addition, appropriate observational data sets of impacts for each sector were collected, against which the models can be benchmarked. Access to all these data is provided through a central ISIMIP archive (see https://www.isimip.org/gettingstarted/#input-data-bias-correction).The ISIMIP2a biome outputs are based on simulations from 8 global vegetation (biomes) models (CARAIB, DLEM, JULES-B1, LPJ-GUESS, LPJmL, ORCHIDEE, VEGAS, VISIT) according to the ISIMIP2a protocol (https://www.isimip.org/protocol/#isimip2a).

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