9 documents found in 380ms
# 1
Geiger, Tobias • Frieler, Katja • Bresch, David N.
Abstract: Tropical cyclones (TCs) pose a major risk to societies worldwide. While data on observed cyclones tracks (location of the center) and wind speeds is publicly available these data sets do not contain information about the spatial extent of the storm and people or assets exposed. Here, we apply a simplified wind field model to estimate all areas (grid cells) exposed to wind speeds above 34 knots. Based on available spatially-explicit data on population densities and Gross Domestic Product (GDP) we estimate 1) the number of people and 2) the sum of assets exposed to above tropical storm force wind speeds for temporal changes in historical distribution of population and assets (TCE-hist) and assuming fixed 2015 patterns (TCE-2015). The associated spatially-explicit exposure data (TCE-DAT) covers the period 1950 to 2015. It is considered key information to 1) assess the contribution of climatological versus socio-economic drivers of changes in exposure to tropical cyclones, 2) estimate changes in vulnerability from the difference in exposure and reported damages and calibrate associated damage functions, and 3) build improved exposure-based predictors to estimate higher-level societal impacts such as long-term effects on GDP, employment, or migration. We validate the adequateness of our methodology by comparing our exposure estimate to estimated exposure obtained from reported wind fields available since 1988 for the United States. We expect that the free availability of the underlying model and TCE-DAT will make research on tropical cyclone risks more accessible to non-experts and stakeholders. Files included in the zip folder: (1) TCE-DAT_single_events_historical.zip: Zipped archive containing 2707 files with exposed population and assets by grid cell using historical socio-economic exposure estimates.(2) TCE-DAT_single_events_2015.zip: Zipped archive containing 2713 files with exposed population and assets by grid cell using fixed socio-economic exposure at 2015 values.(3) Data-description_TCE-DAT_2017.008.pdf: full description of the data set including information on data sources and the description of variables/ data columns Additional information on each TC event in the zipped archive (e.g. TC name, NatCatSERVICE_ID, genesis_basin, aggregated exposure estimates by country) are available in the exposure data sets aggregated on country-event level (see Geiger et al., 2017; http://doi.org/10.5880/pik.2017.005 for details).
# 2
Geiger, Tobias • Frieler, Katja • Bresch, David N.
Abstract: Tropical cyclones (TCs) pose a major risk to societies worldwide. While data on observed cyclones tracks (location of the center) and wind speeds is publicly available these data sets do not contain information on the spatial extent of the storm and people or assets exposed. Here, we provide a collection of tropical cyclone exposure data (TCE-DAT) derived with the help of spatially-explicit data on population densities and Gross Domestic Product (GDP), also available at http://doi.org/10.5880/pik.2017.007. Up to now, this collection contains: 1) A global data set of tropical cyclone exposure accumulated to the country/event level http://doi.org/10.5880/pik.2017.0052) A global data set of spatially-explicit tropical cyclone exposure available for all TC events since 1950 http://doi.org/10.5880/pik.2017.008 TCE-DAT is considered key information to 1) assess the contribution of climatological versus socioeconomic drivers of changes in exposure to tropical cyclones, 2) estimate changes in vulnerability from the difference in exposure and reported damages and calibrate associated damage functions, and 3) build improved exposure-based predictors to estimate higher-level societal impacts such as long-term effects on GDP, employment, or migration. We expect that the free availability of the underlying model and TCE-DAT will make research on tropical cyclone risks more accessible to non-experts and stakeholders.
# 3
Gosling, Simon • Müller Schmied, Hannes • Betts, Richard • Chang, Jinfeng • Ciais, Philippe • (et. al.)
Abstract: 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.
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/.
# 4
Krysanova, Valentina • Hattermann, Fred • Aich, Valentin • Alemayehu, Tadesse • Arheimer, Berit • (et. al.)
Abstract: 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. In the regional water sector, future simulations of climate-change impacts were also carried out, using climate data from five global climate models (GCMs: HadGEM2-ES, IPSL-CM5A-LR, MIROC-ESM-CHEM, GFDL-ESM2M and NorESM1-M) for the four Representative Concentration Pathways (RCPs: RCP2.6, RCP4.5, RCP6.0 and RCP8.5). 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 regional hydrology models (river basins in brackets):HBV-CMA (Yangtze)HBV-IWW (Tagus)HBV-JLU (Rhine, Ganges, Mississippi)HBV-PIK (Rhine, Niger, Yellow, Blue Nile, Amazon)HYMOD-JLU (Rhine, Ganges, Mississippi)HYMOD-UFZ (Rhine, Niger, Blue Nile, Ganges, Yellow, Darling, Mississippi, Amazon)HYPE (Rhine, Tagus, Niger, Ganges, Lena, Mackenzie)mHM (Rhine, Niger, Blue Nile, Ganges, Yellow, Darling, Mississippi, Amazon)SWAP (Rhine, Tagus, Niger, Ganges, Yellow, Yangtze; Lena, Darling, MacKenzie, Mississippi, Amazon)SWAT (Yangtze; Darling; Blue Nile; Amazon; Mississippi; Niger)SWIM (Rhine, Yellow, Mississippi; Niger; Lena; Tagus; Blue Nile; Yangtze; Ganges, Amazon)VIC (Tagus, Blue Nile, Yellow, Lena, Darling, Amazon, MacKenzie; Rhine, Niger, Mississippi; Ganges; Yangtze)VIP (Yellow)WaterGAP3 (Rhine, Tagus, Niger, Blue Nile, Ganges, Yellow, Lena, Mississippi)ECOMAG (Lena, MacKenzie)
The ISIMIP2a water (regional) outputs are based on simulations from 15 regional 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/.
# 5
Arneth, Almut • Balkovic, Juraj • Ciais, Philippe • de Wit, Allard • Deryng, Delphine • (et. al.)
Abstract: 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 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 Agricultural Sector models: CGMS-WOFOST, CLM-Crop, EPIC-Boku, EPIC-IIASA, EPIC-TAMU, GEPIC, LPJ-GUESS, LPJmL, ORCHIDEE-CROP, pAPSIM, pDSSAT, PEGASUS, PEPIC, PRYSBI2.
The ISIMIP2a agriculture outputs are based on simulations from 14 agricultural sector models (see listing) according to the ISIMIP2a protocol (https://www.isimip.org/protocol/#isimip2a). The models simulate cop yields and irrigation water withdrawal (assuming unlimited water supply), based on planting dates, crop variety parameters, approximate maturity dates (to allow for spatially-explicit variety parameterization), as well as fertilizer use (N, P, K). A more detailed description of the models and model-specific amendments of the protocol are available here: https://www.isimip.org/impactmodels/.
# 6
Geiger, Tobias • Frieler, Katja • Bresch, David N.
Abstract: Tropical cyclones (TCs) pose a major risk to societies worldwide. While data on observed cyclones tracks (location of the center) and wind speeds is publicly available these data sets do not contain information about the spatial extent of the storm and people or assets exposed. Here, we apply a simplified wind field model to estimate the areas exposed to wind speeds above 34, 64, and 96 knots. Based on available spatially-explicit data on population densities and Gross Domestic Product (GDP) we estimate 1) the number of people and 2) the sum of assets exposed to wind speeds above these thresholds accounting for temporal changes in historical distribution of population and assets (TCE-hist) and assuming fixed 2015 patterns (TCE-2015). The associated country-event level exposure data (TCE-DAT) covers the period 1950 to 2015. It is considered key information to 1) assess the contribution of climatological versus socioeconomic drivers of changes in exposure to tropical cyclones, 2) estimate changes in vulnerability from the difference in exposure and reported damages and calibrate associated damage functions, and 3) build improved exposure-based predictors to estimate higher-level societal impacts such as long-term effects on GDP, employment, or migration. We validate the adequateness of our methodology by comparing our exposure estimate to estimated exposure obtained from reported wind fields available since 1988 for the United States. We expect that the free availability of the underlying model and TCE-DAT will make research on tropical cyclone risks more accessible to non-experts and stakeholders. Files included in the data set: (1) TCE-DAT_historic-exposure_1950-2015.csv: Exposed population and assets by event and country using historical socio-economic exposure estimates.(2) TCE-DAT_2015-exposure_1950-2015.csv: Exposed population and assets by event and country using fixed socio-economic exposure at 2015 values.(3) Data-description_TCE-DAT_2017.005.pdf: full description of the data set including information on data sources and the description of variables/ data columns
# 7
Moreno, Marcos • Bedford, Jonathan • Baez, Juan Carlos • Klotz, Jürgen • Hoffmann, Felix • (et. al.)
Abstract: The survey-mode GPS (sGPS) network in the IPOC region consists of 91 geodetic markers. Over the last decade, the positions of these points in the network have been periodically measured, thus enabling us to quantify the decadal patterns of deformation processes. This temporal catalogue of coordinates complement the continuous GPS (cGPS) array. Meta-data and raw data in Rinex format for the surveys carried out in 2008, 2011, 2013, 2014, 2015, and 2016 are available for 91 sites in the north of Chile and the northwest of Argentina. Included in this temporal catalogue are observations made shortly after the 2014 Pisagua-Iquique earthquake. Detailed information about data availability, metadata and site descriptions can be found at: https://kg189/gnss/IPOCSGPS. More description about the Integrated Plate Boundary Observatory Chile (IPOC) can be found at the IPOC Website (www.ipoc-network.org) and on the sGPS Survey on www.ipoc-network.org/associated-projects/gps-campaigns/.
# 8
Heimann, Sebastian • Kriegerowski, Marius • Isken, Marius • Cesca, Simone • Daout, Simon • (et. al.)
Abstract: Pyrocko is an open source seismology toolbox and library, written in the Python programming language. It can be utilized flexibly for a variety of geophysical tasks, like seismological data processing and analysis, calculation of Green's functions and earthquake models' synthetic waveforms and static displacements (InSAR or GPS). Those can be used to characterize extended earthquake ruptures, point sources (moment tensors) and other seismic sources. This publication includes the Pyrocko core, a library providing building blocks for researchers and students wishing to develop their own applications. The Pyrocko framework also ships with application: (1) Snuffler (interactive seismogram browser and workbench), (2) Cake (1D travel-time and ray-path computations), (3) Fomosto (calculate and manage Green’s function databases) and (4) Jackseis (waveform archive data manipulation). Additional applications, as of Grond, Lassie and Kite are individual software publications. See the project page (www.pyrocko.org) for full documentation, tutorials and installation instructions.
# 9
Motagh, Mahdi • Shamshiri, Roghayeh • Haghshenas-Haghighi, Mahmud • Wetzel, Hans-Ulrich • Akbari, Bahman • (et. al.)
Abstract: This data publication provides supplementary material to Motagh et. al (2017), which presents the results of an InSAR time series analysis obtained by the exploitation of Envisat, ALOS and Sentinel-1 (S1) SAR data archives between June 2004, and May 2016. The study investigates land subsidence due to groundwater overexploitation for agriculture and industrial development in the Rafsanjan plain of southeastern Iran. Datasets included are a list of SAR data used for the study and the Line of Sight (LOS) displacement rates from Envisat, ALOS and Sentinel 1 (S1) satellites in ASCII format. More in formation is avalable in Motagh-et-al-2017-Supplementary_Material_readme.pdf.
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