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  • 1
    Publication Date: 2018-12-14
    Description: This paper describes ESM-SnowMIP, an international coordinated modelling effort to evaluate current snow schemes, including snow schemes that are included in Earth system models, in a wide variety of settings against local and global observations. The project aims to identify crucial processes and characteristics that need to be improved in snow models in the context of local- and global-scale modelling. A further objective of ESM-SnowMIP is to better quantify snow-related feedbacks in the Earth system. Although it is not part of the sixth phase of the Coupled Model Intercomparison Project (CMIP6), ESM-SnowMIP is tightly linked to the CMIP6-endorsed Land Surface, Snow and Soil Moisture Model Intercomparison (LS3MIP).
    Repository Name: EPIC Alfred Wegener Institut
    Type: Article , NonPeerReviewed
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  • 2
    Publication Date: 2019-03-06
    Description: Abstract
    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 approx.) of climate impacts on agriculture, fisheries, permafrost, biomes, regional and global water and forests. This may 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 evaluation and 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 the input data for the impact models is provided through a central ISIMIP archive (see https://www.isimip.org/gettingstarted/#input-data-bias-correction).This entry refers to the ISIMIP2a simulation data from global hydrology models: CLM4, DBH, H08, JULES_W1, JULES_B1, LPJmL, MATSIRO, MPI-HM, ORCHIDEE, PCR-GLOBWB, SWBM, VIC, WaterGAP2.
    Description: Methods
    Description: The ISIMIP2a water (global) outputs are based on simulations from 13 global hydrology models (see listing) according to the ISIMIP2a protocol (https://www.isimip.org/protocol/#isimip2a). The models simulate hydrological processes and dynamics (part of the models also considering human water abstractions and reservoir regulation) based on climate and physio-geographical information. A more detailed description of the models and model-specific amendments of the protocol are available here: https://www.isimip.org/impactmodels/.
    Keywords: EARTH SCIENCE SERVICES 〉 MODELS 〉 HYDROLOGIC AND TERRESTRIAL WATER CYCLE MODELS ; EARTH SCIENCE 〉 CLIMATE INDICATORS 〉 TERRESTRIAL HYDROSPHERE INDICATORS 〉 FRESHWATER RUNOFF ; EARTH SCIENCE 〉 TERRESTRIAL HYDROSPHERE 〉 GROUND WATER 〉 GROUND WATER DISCHARGE/FLOW ; EARTH SCIENCE 〉 TERRESTRIAL HYDROSPHERE 〉 SNOW/ICE 〉 SNOW WATER EQUIVALENT ; EARTH SCIENCE 〉 TERRESTRIAL HYDROSPHERE 〉 SURFACE WATER 〉 TOTAL SURFACE WATER ; EARTH SCIENCE 〉 TERRESTRIAL HYDROSPHERE 〉 SURFACE WATER 〉 RUNOFF ; EARTH SCIENCE 〉 TERRESTRIAL HYDROSPHERE 〉 SURFACE WATER 〉 DISCHARGE/FLOW ; EARTH SCIENCE 〉 TERRESTRIAL HYDROSPHERE 〉 SURFACE WATER 〉 RIVERS/STREAMS ; EARTH SCIENCE 〉 TERRESTRIAL HYDROSPHERE 〉 SURFACE WATER 〉 FLOODS ; EARTH SCIENCE 〉 TERRESTRIAL HYDROSPHERE 〉 SURFACE WATER 〉 DRAINAGE ; EARTH SCIENCE 〉 TERRESTRIAL HYDROSPHERE 〉 SURFACE WATER 〉 AQUIFER RECHARGE ; EARTH SCIENCE 〉 CRYOSPHERE 〉 SNOW/ICE 〉 SNOW WATER EQUIVALENT ; EARTH SCIENCE 〉 LAND SURFACE 〉 GEOMORPHOLOGY 〉 FLUVIAL LANDFORMS/PROCESSES ; EARTH SCIENCE 〉 LAND SURFACE 〉 SOILS 〉 SOIL MOISTURE/WATER CONTENT ; EARTH SCIENCE 〉 AGRICULTURE 〉 AGRICULTURAL PLANT SCIENCE 〉 IRRIGATION ; EARTH SCIENCE 〉 HUMAN DIMENSIONS 〉 SUSTAINABILITY 〉 SUSTAINABLE DEVELOPMENT ; EARTH SCIENCE 〉 HUMAN DIMENSIONS 〉 SUSTAINABILITY 〉 ENVIRONMENTAL SUSTAINABILITY ; EARTH SCIENCE 〉 HUMAN DIMENSIONS 〉 ENVIRONMENTAL GOVERNANCE/MANAGEMENT 〉 ENVIRONMENTAL ASSESSMENTS ; EARTH SCIENCE 〉 HUMAN DIMENSIONS 〉 ENVIRONMENTAL GOVERNANCE/MANAGEMENT 〉 WATER MANAGEMENT ; EARTH SCIENCE 〉 HUMAN DIMENSIONS 〉 NATURAL HAZARDS 〉 DROUGHTS ; EARTH SCIENCE 〉 HUMAN DIMENSIONS 〉 NATURAL HAZARDS 〉 FLOODS ; EARTH SCIENCE 〉 HUMAN DIMENSIONS 〉 ECONOMIC RESOURCES 〉 ENERGY PRODUCTION/USE 〉 HYDROELECTRIC ENERGY PRODUCTION/USE ; EARTH SCIENCE 〉 HUMAN DIMENSIONS 〉 HABITAT CONVERSION/FRAGMENTATION 〉 IRRIGATION
    Language: English
    Type: Dataset , Dataset
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  • 3
    Publication Date: 2019-03-06
    Description: Abstract
    Description: VERSION HISTORY:-On October 18, 2018 we republished all simulation data for all water (global) sector impact models to get the data sets into the new ESGF search facet structure. There were no changes to the simulation data.- On November 27, 2018 we republished simulation data for monthly variables swe, soilmoist and rootmoist for impact model PCR-GLOBWB due to an error in the units. Instead of reporting mass per area (kg/m2), values corresponded to mass flux rate (kg/m2/s). Values were thus multiplied by 86400 in order to obtain the correct values in kg/m2. This data caveat was documented in the ISIMIP website (ISIMIP2a: PCR-GLOBWB reported three variables in wrong unit).----------------------------------------------------------------------------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 http://doi.org/10.5880/PIK.2017.010 before November 27, 2018 please write to the ISIMIP Data Management Team: isimip-data[at]pik-potsdam.de.----------------------------------------------------------------------------DATA 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 approx.) of climate impacts on agriculture, fisheries, permafrost, biomes, regional and global water and forests. This may 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 evaluation and 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 the input data for the impact models is provided through a central ISIMIP archive (see https://www.isimip.org/gettingstarted/#input-data-bias-correction).This entry refers to the ISIMIP2a simulation data from global hydrology models: CLM4, DBH, H08, JULES_W1, JULES_B1, LPJmL, MATSIRO, MPI-HM, ORCHIDEE, PCR-GLOBWB, SWBM, VIC, WaterGAP2
    Description: Methods
    Description: The ISIMIP2a water (global) outputs are based on simulations from 13 global hydrology models (see listing) according to the ISIMIP2a protocol (https://www.isimip.org/protocol/#isimip2a). The models simulate hydrological processes and dynamics (part of the models also considering human water abstractions and reservoir regulation) based on climate and physio-geographical information. A more detailed description of the models and model-specific amendments of the protocol are available here: https://www.isimip.org/impactmodels/.
    Keywords: EARTH SCIENCE SERVICES 〉 MODELS 〉 HYDROLOGIC AND TERRESTRIAL WATER CYCLE MODELS ; EARTH SCIENCE 〉 CLIMATE INDICATORS 〉 TERRESTRIAL HYDROSPHERE INDICATORS 〉 FRESHWATER RUNOFF ; EARTH SCIENCE 〉 TERRESTRIAL HYDROSPHERE 〉 GROUND WATER 〉 GROUND WATER DISCHARGE/FLOW ; EARTH SCIENCE 〉 TERRESTRIAL HYDROSPHERE 〉 SNOW/ICE 〉 SNOW WATER EQUIVALENT ; EARTH SCIENCE 〉 TERRESTRIAL HYDROSPHERE 〉 SURFACE WATER 〉 TOTAL SURFACE WATER ; EARTH SCIENCE 〉 TERRESTRIAL HYDROSPHERE 〉 SURFACE WATER 〉 RUNOFF ; EARTH SCIENCE 〉 TERRESTRIAL HYDROSPHERE 〉 SURFACE WATER 〉 DISCHARGE/FLOW ; EARTH SCIENCE 〉 TERRESTRIAL HYDROSPHERE 〉 SURFACE WATER 〉 RIVERS/STREAMS ; EARTH SCIENCE 〉 TERRESTRIAL HYDROSPHERE 〉 SURFACE WATER 〉 FLOODS ; EARTH SCIENCE 〉 TERRESTRIAL HYDROSPHERE 〉 SURFACE WATER 〉 DRAINAGE ; EARTH SCIENCE 〉 TERRESTRIAL HYDROSPHERE 〉 SURFACE WATER 〉 AQUIFER RECHARGE ; EARTH SCIENCE 〉 CRYOSPHERE 〉 SNOW/ICE 〉 SNOW WATER EQUIVALENT ; EARTH SCIENCE 〉 LAND SURFACE 〉 GEOMORPHOLOGY 〉 FLUVIAL LANDFORMS/PROCESSES ; EARTH SCIENCE 〉 LAND SURFACE 〉 SOILS 〉 SOIL MOISTURE/WATER CONTENT ; EARTH SCIENCE 〉 AGRICULTURE 〉 AGRICULTURAL PLANT SCIENCE 〉 IRRIGATION ; EARTH SCIENCE 〉 HUMAN DIMENSIONS 〉 SUSTAINABILITY 〉 SUSTAINABLE DEVELOPMENT ; EARTH SCIENCE 〉 HUMAN DIMENSIONS 〉 SUSTAINABILITY 〉 ENVIRONMENTAL SUSTAINABILITY ; EARTH SCIENCE 〉 HUMAN DIMENSIONS 〉 ENVIRONMENTAL GOVERNANCE/MANAGEMENT 〉 ENVIRONMENTAL ASSESSMENTS ; EARTH SCIENCE 〉 HUMAN DIMENSIONS 〉 ENVIRONMENTAL GOVERNANCE/MANAGEMENT 〉 WATER MANAGEMENT ; EARTH SCIENCE 〉 HUMAN DIMENSIONS 〉 NATURAL HAZARDS 〉 DROUGHTS ; EARTH SCIENCE 〉 HUMAN DIMENSIONS 〉 NATURAL HAZARDS 〉 FLOODS ; EARTH SCIENCE 〉 HUMAN DIMENSIONS 〉 ECONOMIC RESOURCES 〉 ENERGY PRODUCTION/USE 〉 HYDROELECTRIC ENERGY PRODUCTION/USE ; EARTH SCIENCE 〉 HUMAN DIMENSIONS 〉 HABITAT CONVERSION/FRAGMENTATION 〉 IRRIGATION
    Language: English
    Type: Dataset , Dataset
    Format: 1 Files
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  • 4
    Publication Date: 2019-11-29
    Description: Abstract
    Description: Current process-based vegetation models are complex scientific tools that require proper evaluation of the different processes included in the models to prove that the models can be used to integrate our understanding of forest ecosystems and project climate change impacts on forests. The PROFOUND database (PROFOUND DB) described here aims to bring together data from a wide range of data sources to evaluate vegetation models and simulate climate impacts at the forest stand scale.It has been designed to fulfill two objectives:- Allow for a thorough evaluation of complex, process-based vegetation models using multiple data streams covering a range of processes at different temporal scales- Allow for climate impact assessments by providing the latest climate scenario data.Therefore, the PROFOUND DB provides general a site description as well as soil, climate, CO2, Nitrogen deposition, tree-level, forest stand-level and remote sensing data for 9 forest stands spread throughout Europe. Moreover, for a subset of 5 sites, also time series of carbon fluxes, energy balances and soil water are available. The climate and nitrogen deposition data contains several datasets for the historic period and a wide range of future climate change scenarios following the Representative Emission Pathways (RCP2.6, RCP4.5, RCP6.0, RCP8.5).In addition, we also provide pre-industrial climate simulations that allow for model runs aimed at disentangling the contribution of climate change to observed forest productivity changes. The PROFOUND Database is available freely but we incite users to respect the data policies of the individual datasets as provided in the metadata of each data file. The database can also be accessed via the PROFOUND R-package, which provides basic functions to explore, plot and extract the data.The data (PROFOUND DB) are provided in two different versions (ProfoundData.sqlite, ProfoundData_ASCII.zip) and documented by the following three documents:(1) PROFOUNDdatabase.pdf: describes the structure, organisation and content of the PROFOUND DB.(2) PROFOUNDsites.pdf: displays the main data of the PROFOUND DB for each of the 9 forest sites in tables and plots.(3) ProfoundData.pdf: explains how to use the PROFOUND R-Package "ProfoundData" to access the PROFOUND DB and provides example scripts on how to apply it.
    Keywords: vegetation model ; soil ; climate ; CO2 ; Nitrogen deposition ; tree-level ; forest stand-level ; remote sensing ; EARTH SCIENCE 〉 BIOSPHERE 〉 VEGETATION 〉 NITROGEN ; EARTH SCIENCE 〉 CLIMATE INDICATORS ; EARTH SCIENCE 〉 LAND SURFACE 〉 SOILS ; EARTH SCIENCE SERVICES 〉 MODELS 〉 DYNAMIC VEGETATION/ECOSYSTEM MODELS
    Type: Dataset
    Format: 8813287391 Bytes
    Format: 5 Files
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  • 5
    Publication Date: 2019-07-12
    Description: The impacts of global climate change on different aspects of humanity's diverse life-support systems are complex and often difficult to predict. To facilitate policy decisions on mitigation and adaptation strategies, it is necessary to understand, quantify, and synthesize these climate-change impacts, taking into account their uncertainties. Crucial to these decisions is an understanding of how impacts in different sectors overlap, as overlapping impacts increase exposure, lead to interactions of impacts, and are likely to raise adaptation pressure. As a first step we develop herein a framework to study coinciding impacts and identify regional exposure hotspots. This framework can then be used as a starting point for regional case studies on vulnerability and multifaceted adaptation strategies. We consider impacts related to water, agriculture, ecosystems, and malaria at different levels of global warming. Multisectoral overlap starts to be seen robustly at a mean global warming of 3 degC above the 1980-2010 mean, with 11% of the world population subject to severe impacts in at least two of the four impact sectors at 4 degC. Despite these general conclusions, we find that uncertainty arising from the impact models is considerable, and larger than that from the climate models. In a low probability-high impact worst-case assessment, almost the whole inhabited world is at risk for multisectoral pressures. Hence, there is a pressing need for an increased research effort to develop a more comprehensive understanding of impacts, as well as for the development of policy measures under existing uncertainty.
    Keywords: Meteorology and Climatology
    Type: GSFC-E-DAA-TN15449
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  • 6
    Publication Date: 2019-07-13
    Description: As earth system models (ESMs) become increasingly complex, there is a growing need for comprehensive and multi-faceted evaluation of model projections. To advance understanding of terrestrial biogeochemical processes and their interactions with hydrology and climate under conditions of increasing atmospheric carbon dioxide, new analysis methods are required that use observations to constrain model predictions, inform model development, and identify needed measurements and field experiments. Better representations of biogeochemistryclimate feedbacks and ecosystem processes in these models are essential for reducing the acknowledged substantial uncertainties in 21st century climate change projections.
    Keywords: Meteorology and Climatology
    Type: DOE/SC-0186 , GSFC-E-DAA-TN43734 , 2016 International Land Model Benchmarking (ILAMB) Workshop; May 16, 2016 - May 18, 2016; Washington, DC; United States
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  • 7
    Publication Date: 2019-07-13
    Description: Global hydrological models (GHMs) have been applied to assess global flood hazards, but their capacity to capture the timing and amplitude of peak river discharge which is crucial in flood simulations has traditionally not been the focus of examination. Here we evaluate to what degree the choice of river routing scheme affects simulations of peak discharge and may help to provide better agreement with observations. To this end we use runoff and discharge simulations of nine GHMs forced by observational climate data (1971-2010) within the ISIMIP2a (Inter-Sectoral Impact Model Intercomparison Project phase 2a) project. The runoff simulations were used as input for the global river routing model CaMa-Flood (Catchment-based Macro-scale Floodplain). The simulated daily discharge was compared to the discharge generated by each GHM using its native river routing scheme. For each GHM both versions of simulated discharge were compared to monthly and daily discharge observations from 1701 GRDC (Global Runoff Data Centre) stations as a benchmark. CaMa-Flood routing shows a general reduction of peak river discharge and a delay of about two to three weeks in its occurrence, likely induced by the buffering capacity of floodplain reservoirs. For a majority of river basins, discharge produced by CaMa-Flood resulted in a better agreement with observations. In particular, maximum daily discharge was adjusted, with a multi-model averaged reduction in bias over about two-thirds of the analysed basin area. The increase in agreement was obtained in both managed and near-natural basins. Overall, this study demonstrates the importance of routing scheme choice in peak discharge simulation, where CaMa-Flood routing accounts for floodplain storage and backwater effects that are not represented in most GHMs. Our study provides important hints that an explicit parameterisation of these processes may be essential in future impact studies.
    Keywords: Meteorology and Climatology
    Type: GSFC-E-DAA-TN44438 , Environmental Research Letters (e-ISSN 1748-9326); 12; 7; 075003
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  • 8
    Publication Date: 2019-07-13
    Description: The Land Surface, Snow and Soil Moisture Model Intercomparison Project (LS3MIP) is designed to provide a comprehensive assessment of land surface, snow, and soil moisture feedbacks on climate variability and climate change, and to diagnose systematic biases in the land modules of current Earth System Models (ESMs). The solid and liquid water stored at the land surface has a large influence on the regional climate, its variability and predictability, including effects on the energy, water and carbon cycles. Notably, snow and soil moisture affect surface radiation and flux partitioning properties, moisture storage and land surface memory. They both strongly affect atmospheric conditions, in particular surface air temperature and precipitation, but also large-scale circulation patterns. However, models show divergent responses and representations of these feedbacks as well as systematic biases in the underlying processes. LS3MIP will provide the means to quantify the associated uncertainties and better constrain climate change projections, which is of particular interest for highly vulnerable regions (densely populated areas, agricultural regions, the Arctic, semi-arid and other sensitive terrestrial ecosystems).The experiments are subdivided in two components, the first addressing systematic land biases in offline mode (LMIP, building upon the 3rd phase of Global Soil Wetness Project; GSWP3) and the second addressing land feedbacks attributed to soil moisture and snow in an integrated framework (LFMIP, building upon the GLACE-CMIP blueprint).
    Keywords: Meteorology and Climatology
    Type: GSFC-E-DAA-TN35358 , Geoscientific Model Development (e-ISSN 1991-9603); 9; 2809–2832
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  • 9
    Publication Date: 2019-07-13
    Description: The global water cycle has been profoundly affected by human land-water management. As the changes in the water cycle on land can affect the functioning of a wide range of biophysical and biogeochemical processes of the Earth system, it is essential to represent human land-water management in Earth system models (ESMs). During the recent past, noteworthy progress has been made in large-scale modeling of human impacts on the water cycle but sufficient advancements have not yet been made in integrating the newly developed schemes into ESMs. This study reviews the progresses made in incorporating human factors in large-scale hydrological models and their integration into ESMs. The study focuses primarily on the recent advancements and existing challenges in incorporating human impacts in global land surface models (LSMs) as a way forward to the development of ESMs with humans as integral components, but a brief review of global hydrological models (GHMs) is also provided. The study begins with the general overview of human impacts on the water cycle. Then, the algorithms currently employed to represent irrigation, reservoir operation, and groundwater pumping are discussed. Next, methodological deficiencies in current modeling approaches and existing challenges are identified. Furthermore, light is shed on the sources of uncertainties associated with model parameterizations, grid resolution, and datasets used for forcing and validation. Finally, representing human land-water management in LSMs is highlighted as an important research direction toward developing integrated models using ESM frameworks for the holistic study of human-water interactions within the Earths system.
    Keywords: Earth Resources and Remote Sensing
    Type: GSFC-E-DAA-TN32164 , Wiley Interdisciplinary Reviews: Water (e-ISSN 2049-1948)
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  • 10
    Publication Date: 2015-04-25
    Description: Article There is significant interest in the evolution of supramolecular chirality via self-assembly of achiral building blocks. Here, the authors report a system where the supramolecular chirality can be selectively and reversibly controlled and arrested by visible and ultraviolet circularly polarized light. Nature Communications doi: 10.1038/ncomms7959 Authors: Jisung Kim, Jinhee Lee, Woo Young Kim, Hyungjun Kim, Sanghwa Lee, Hee Chul Lee, Yoon Sup Lee, Myungeun Seo, Sang Youl Kim
    Electronic ISSN: 2041-1723
    Topics: Biology , Chemistry and Pharmacology , Natural Sciences in General , Physics
    Published by Springer Nature
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