Austin, Timothy · do Valle Chagas Azaneu, Marina · Roughan, Moninya
26 files · 29 MB · netcdf, pdf, pngdeclared
Data collected from a temperature mooring at Lord Howe Island maintained by UNSW Sydney and funded by Parks Australia. The mooring position is longitude = 158.97°E and latitude = -31.51°, and local depth of approximately 52 m. The data were sampled using a series of thermistors (aqualogger 520PTs) deployed on a mooring line at 4m intervals through the water column, with shallowest instrument at 13 m and deepest at 53 m. The time period spans between 14-05-2025 and 22-04-2026. IMOS standard data quality assurance and quality control processes have been followed and the data formatted following IMOS conventions. Data quality control includes automated routines and visual inspection (expert QC) and flagging of obvious errors. File are c.f. compliant NetCDF files, and file name format follows IMOS conventions and includes sampling period in the format: UNSW_Lord_Howe_Marine_Park_TZ_ yyyymmddThhmmss Z_LH050_FV01_ LH050-2511-Aqualogger-AQUAlogger-520PT16-max160m-13_END- yyyymmddThhmmssZ.
Machine-learning-inferred monthly anthropogenic NOx emission over the 2026 Strait-of-Hormuz disruption (global, 0.1 degree, January 2025 - May 2026). This dataset is the top-down NOx emission product underlying the companion manuscript on the 2026 Strait-of-Hormuz shipping-emission collapse. A LightGBM estimator trained on the CAMS-GLOB-ANT v6.2 inventory (2018-2024), with the observed TROPOMI NO2 column and GEOS-CF chemistry/meteorology as predictors, is applied month by month to 2025-01 through 2026-05 to infer the anthropogenic NOx emission flux. Provided as a single self-describing CF-1.8 NetCDF containing: the total anthropogenic NOx flux (kg m-2 s-1, reported as NO) and a per-pixel cross-validation uncertainty (log-space). The estimator resolves the total emission only; no sector decomposition is distributed, because over open ocean the total is essentially ship emission while on land a sector split would only re-apply the CAMS-GLOB-ANT prior shares and is not constrained by the observations. Coverage is land and ocean within +/-60 degrees latitude on a regular 0.1-degree global grid. All units and coordinates are embedded in the file.
Historical Hydrological Simulations over the South African Domain (1990-2024) The mHM's simulations of the Planet4Health project This dataset contains historical hydrological simulations for the South African domain (domain 1020011530) conducted with the Mesoscale Hydrological Model (mHM) at a spatial resolution of 0.015625°. The simulation period spans 1990-2024 and was part of the Planet4Health (P4H) project, utilising the ERA5 meteorological forcing. This archive is prepared for DOI assignment and ensures long-term reproducibility. It includes relevant clipped NetCDF components for soil moisture layers 4, 5 and 6, consistent with the infrastructure provided within the Helmholtz Centre for Environmental Research (UFZ). The simulations were executed using a specific version of the mHM model with the SCC method for gauges, paired with the mRMv1.0 routing configuration. 🛰️ Simulation Details Model: Mesoscale Hydrological Model (mHM) Codebase: scc_for_gauges branch (https://git.ufz.de/shresthp/mhm/-/tree/scc_for_gauges?ref_type=heads) Spatial resolution: 0.015625° Temporal resolution: Daily Simulation period: 1990-2024 Simulation type: Historical simulation Spin-up: 30-year spin-up using 1990-2019 ERA5 climatology Model version: v1.0 Setup Scope: Model run for domain 1020011530, post-processed and clipped. Configuration & Modules The configuration utilises standard structural components with the SCC methodology. Modules included: Snow processes: Degree-day method Soil moisture: Feddes equation for evapotranspiration reduction Infiltration: Multi-layer Brooks-Corey-like approach Direct runoff: Linear reservoir exceedance method Potential evapotranspiration: Hargreaves-Samani method Interflow: Storage reservoir with nonlinear outflow Groundwater: Linear reservoir Routing: Adaptive time-step routing with mRMv1.0 mechanisms 📥 Input Datasets Meteorological Forcing: ERA5 (Hersbach et al., 2020) at a native input meteorological resolution of 0.25°, dynamically downscaled/mapped to model requirements. Processing Infrastructure: Tracked, processed, and validated under the Planet4Health deployment pipeline (https://git.ufz.de/planet4health/mhm_production/-/tree/main/postproc?ref_type=heads). Data Interfaces: Climate Data Interface version 2.2.4 (CDI) | Climate Data Operators version 2.2.2 (CDO) | NetCDF Operators version 5.1.7 (NCO). 📤 Output Variables sm_l04: Volumetric soil moisture layer 4 (300-500 mm depth) [mm mm-1, fraction between 0 and 1] sm_l05: Volumetric soil moisture layer 5 (500-1000 mm depth) [mm mm-1, fraction between 0 and 1] sm_l06: Volumetric soil moisture layer 6 (1000-2000 mm depth) [mm mm-1, fraction between 0 and 1] 📫 Contact Ehsan Modiri - ehsan.modiri@ufz.de Pallav Kumar Shrestha - pallav-kumar.shrestha@ufz.de Institution Helmholtz Centre for Environmental Research - UFZ, Department of Computational Hydrosystems
Historical Hydrological Simulations over the South African Domain (1990-2024) The mHM's simulations of the Planet4Health project This dataset contains historical hydrological simulations for the South African domain (domain 1020011530) conducted with the Mesoscale Hydrological Model (mHM) at a spatial resolution of 0.015625°. The simulation period spans 1990-2024 and was part of the Planet4Health (P4H) project, utilising the ERA5 meteorological forcing. This archive is prepared for DOI assignment and ensures long-term reproducibility. It includes relevant clipped NetCDF components for soil water content layers 3 and 4, consistent with the infrastructure provided within the Helmholtz Centre for Environmental Research (UFZ). The simulations were executed using a specific version of the mHM model with the SCC method for gauges, paired with the mRMv1.0 routing configuration. 🛰️ Simulation Details Model: Mesoscale Hydrological Model (mHM) Codebase: scc_for_gauges branch (https://git.ufz.de/shresthp/mhm/-/tree/scc_for_gauges?ref_type=heads) Spatial resolution: 0.015625° Temporal resolution: Daily Simulation period: 1990-2024 Simulation type: Historical simulation Spin-up: 30-year spin-up using 1990-2019 ERA5 climatology Model version: v1.0 Setup Scope: Model run for domain 1020011530, post-processed and clipped. Configuration & Modules The configuration utilises standard structural components with the SCC methodology. Modules included: Snow processes: Degree-day method Soil moisture: Feddes equation for evapotranspiration reduction Infiltration: Multi-layer Brooks-Corey-like approach Direct runoff: Linear reservoir exceedance method Potential evapotranspiration: Hargreaves-Samani method Interflow: Storage reservoir with nonlinear outflow Groundwater: Linear reservoir Routing: Adaptive time-step routing with mRMv1.0 mechanisms 📥 Input Datasets Meteorological Forcing: ERA5 (Hersbach et al., 2020) at a native input meteorological resolution of 0.25°, dynamically downscaled/mapped to model requirements. Processing Infrastructure: Tracked, processed, and validated under the Planet4Health deployment pipeline (https://git.ufz.de/planet4health/mhm_production/-/tree/main/postproc?ref_type=heads). Data Interfaces: Climate Data Interface version 2.2.4 (CDI) | Climate Data Operators version 2.2.2 (CDO) | NetCDF Operators version 5.1.7 (NCO). 📤 Output Variables swc_l03: Soil water content layer 3 (150-300 mm depth) [mm] swc_l04: Soil water content layer 4 (300-500 mm depth) [mm] 📫 Contact Ehsan Modiri - ehsan.modiri@ufz.de Pallav Kumar Shrestha - pallav-kumar.shrestha@ufz.de Institution Helmholtz Centre for Environmental Research - UFZ, Department of Computational Hydrosystems
Historical Hydrological Simulations over the South African Domain (1990-2024) The mHM's simulations of the Planet4Health project This dataset contains historical hydrological simulations for the South African domain (domain 1020011530) conducted with the Mesoscale Hydrological Model (mHM) at a spatial resolution of 0.015625°. The simulation period spans 1990-2024 and was part of the Planet4Health (P4H) project, utilising the ERA5 meteorological forcing. This archive is prepared for DOI assignment and ensures long-term reproducibility. It includes relevant clipped NetCDF components for soil moisture layers 2 and 3, consistent with the infrastructure provided within the Helmholtz Centre for Environmental Research (UFZ). The simulations were executed using a specific version of the mHM model with the SCC method for gauges, paired with the mRMv1.0 routing configuration. 🛰️ Simulation Details Model: Mesoscale Hydrological Model (mHM) Codebase: scc_for_gauges branch (https://git.ufz.de/shresthp/mhm/-/tree/scc_for_gauges?ref_type=heads) Spatial resolution: 0.015625° Temporal resolution: Daily Simulation period: 1990-2024 Simulation type: Historical simulation Spin-up: 30-year spin-up using 1990-2019 ERA5 climatology Model version: v1.0 Setup Scope: Model run for domain 1020011530, post-processed and clipped. Configuration & Modules The configuration utilises standard structural components with the SCC methodology. Modules included: Snow processes: Degree-day method Soil moisture: Feddes equation for evapotranspiration reduction Infiltration: Multi-layer Brooks-Corey-like approach Direct runoff: Linear reservoir exceedance method Potential evapotranspiration: Hargreaves-Samani method Interflow: Storage reservoir with nonlinear outflow Groundwater: Linear reservoir Routing: Adaptive time-step routing with mRMv1.0 mechanisms 📥 Input Datasets Meteorological Forcing: ERA5 (Hersbach et al., 2020) at a native input meteorological resolution of 0.25°, dynamically downscaled/mapped to model requirements. Processing Infrastructure: Tracked, processed, and validated under the Planet4Health deployment pipeline (https://git.ufz.de/planet4health/mhm_production/-/tree/main/postproc?ref_type=heads). Data Interfaces: Climate Data Interface version 2.2.4 (CDI) | Climate Data Operators version 2.2.2 (CDO) | NetCDF Operators version 5.1.7 (NCO). 📤 Output Variables sm_l02: Volumetric soil moisture layer 2 (50-150 mm depth) [mm mm-1, fraction between 0 and 1] sm_l03: Volumetric soil moisture layer 3 (150-300 mm depth) [mm mm-1, fraction between 0 and 1] 📫 Contact Ehsan Modiri - ehsan.modiri@ufz.de Pallav Kumar Shrestha - pallav-kumar.shrestha@ufz.de Institution Helmholtz Centre for Environmental Research - UFZ, Department of Computational Hydrosystems
Monthly 1-km SPI, SPEI and SRI drought-indicator rasters for Poland (1995-2024) This dataset provides monthly gridded drought indicators for the entire territory of Poland at 1-km resolution for the period 1995-2024. Three complementary standardized indices are included: the Standardized Precipitation Index (SPI, precipitation-based), the Standardized Precipitation-Evapotranspiration Index (SPEI, based on the climatic water balance P - PET) and the Standardized Runoff Index (SRI, runoff-based). Each index is provided at five accumulation scales: 1, 3, 6, 12 and 24 months. Methods. Station indices were computed from IMGW-PIB precipitation and river-runoff observations and from AgERA5 potential evapotranspiration (used for SPEI). SPI and SRI were fitted with a gamma distribution and SPEI with a log-logistic distribution. Station values were then interpolated to a 1-km grid (EPSG:2180, PUWG 1992) by ordinary kriging. Elevation-assisted kriging (kriging with external drift) was evaluated by leave-one-out cross-validation but produced no net national improvement and was not adopted for the final product. File structure. Data are provided as CF-compliant NetCDF (CF-1.8), one file per indicator and accumulation scale (e.g. SPI_s06m_PL_1km_1995-2024_EPSG2180.nc ) . Each file has dimensions (time, y, x) with a regular monthly time axis (360 steps, 1995-01 to 2024-12) and the coordinate reference system stored as a grid_mapping variable. Months in which an index cannot be formed at the edges of the accumulation window are present as fill-valued (missing) layers, so the time axis is continuous; their completeness is documented in raster_index.csv . Contents. netcdf/ - the 15 index rasters; metadata/raster_index.csv - per-layer inventory with min/max/mean, missing-data fraction and a "present" flag; metadata/variables_dictionary.csv - variable definitions; metadata/mckee_classes.csv - the seven-class drought/wetness classification (McKee et al., 1993) with colours; CITATION.cff and checksums.md5 . Usage note. In GIS software the temporal dimension is read via the temporal/time controls (e.g. in QGIS: Layer Properties → Temporal → Dynamic Temporal Control, then the Temporal Controller); in Python the files open directly with xarray, with time parsed as dates. Coordinate reference system. EPSG:2180 (PUWG 1992 / Poland CS92). Map extents delineate the study area and do not necessarily depict accepted national boundaries.
A monthly dataset of volume, heat and salt transport through the Faroe-Shetland Channel. The time step is monthly, from 1993-01 to 2025-08. This data accompanies the paper 'Strengthening of the Atlantic Water Inflow through the Faroe-Shetland Channel'.
Historical Hydrological Simulations over the South African Domain (1990-2024) The mHM's simulations of the Planet4Health project This dataset contains historical hydrological simulations for the South African domain (domain 1020011530) conducted with the Mesoscale Hydrological Model (mHM) at a spatial resolution of 0.015625°. The simulation period spans 1990-2024 and was part of the Planet4Health (P4H) project, utilising the ERA5 meteorological forcing. This archive is prepared for DOI assignment and ensures long-term reproducibility. It includes relevant clipped NetCDF components for soil water content layers 5 and 6, consistent with the infrastructure provided within the Helmholtz Centre for Environmental Research (UFZ). The simulations were executed using a specific version of the mHM model with the SCC method for gauges, paired with the mRMv1.0 routing configuration. 🛰️ Simulation Details Model: Mesoscale Hydrological Model (mHM) Codebase: scc_for_gauges branch (https://git.ufz.de/shresthp/mhm/-/tree/scc_for_gauges?ref_type=heads) Spatial resolution: 0.015625° Temporal resolution: Daily Simulation period: 1990-2024 Simulation type: Historical simulation Spin-up: 30-year spin-up using 1990-2019 ERA5 climatology Model version: v1.0 Setup Scope: Model run for domain 1020011530, post-processed and clipped. Configuration & Modules The configuration utilises standard structural components with the SCC methodology. Modules included: Snow processes: Degree-day method Soil moisture: Feddes equation for evapotranspiration reduction Infiltration: Multi-layer Brooks-Corey-like approach Direct runoff: Linear reservoir exceedance method Potential evapotranspiration: Hargreaves-Samani method Interflow: Storage reservoir with nonlinear outflow Groundwater: Linear reservoir Routing: Adaptive time-step routing with mRMv1.0 mechanisms 📥 Input Datasets Meteorological Forcing: ERA5 (Hersbach et al., 2020) at a native input meteorological resolution of 0.25°, dynamically downscaled/mapped to model requirements. Processing Infrastructure: Tracked, processed, and validated under the Planet4Health deployment pipeline (https://git.ufz.de/planet4health/mhm_production/-/tree/main/postproc?ref_type=heads). Data Interfaces: Climate Data Interface version 2.2.4 (CDI) | Climate Data Operators version 2.2.2 (CDO) | NetCDF Operators version 5.1.7 (NCO). 📤 Output Variables swc_l05: Soil water content layer 5 (500-1000 mm depth) [mm] swc_l06: Soil water content layer 6 (1000-2000 mm depth) [mm] 📫 Contact Ehsan Modiri - ehsan.modiri@ufz.de Pallav Kumar Shrestha - pallav-kumar.shrestha@ufz.de Institution Helmholtz Centre for Environmental Research - UFZ, Department of Computational Hydrosystems
Historical Hydrological Simulations over the South African Domain (1990-2024) The mHM's simulations of the Planet4Health project This dataset contains historical hydrological simulations for the South African domain (domain 1020011530) conducted with the Mesoscale Hydrological Model (mHM) at a spatial resolution of 0.015625°. The simulation period spans 1990-2024 and was part of the Planet4Health (P4H) project, utilising the ERA5 meteorological forcing. This archive is prepared for DOI assignment and ensures long-term reproducibility. It includes relevant clipped NetCDF components for soil water content layers 1 and 2, consistent with the infrastructure provided within the Helmholtz Centre for Environmental Research (UFZ). The simulations were executed using a specific version of the mHM model with the SCC method for gauges, paired with the mRMv1.0 routing configuration. 🛰️ Simulation Details Model: Mesoscale Hydrological Model (mHM) Codebase: scc_for_gauges branch (https://git.ufz.de/shresthp/mhm/-/tree/scc_for_gauges?ref_type=heads) Spatial resolution: 0.015625° Temporal resolution: Daily Simulation period: 1990-2024 Simulation type: Historical simulation Spin-up: 30-year spin-up using 1990-2019 ERA5 climatology Model version: v1.0 Setup Scope: Model run for domain 1020011530, post-processed and clipped. Configuration & Modules The configuration utilises standard structural components with the SCC methodology. Modules included: Snow processes: Degree-day method Soil moisture: Feddes equation for evapotranspiration reduction Infiltration: Multi-layer Brooks-Corey-like approach Direct runoff: Linear reservoir exceedance method Potential evapotranspiration: Hargreaves-Samani method Interflow: Storage reservoir with nonlinear outflow Groundwater: Linear reservoir Routing: Adaptive time-step routing with mRMv1.0 mechanisms 📥 Input Datasets Meteorological Forcing: ERA5 (Hersbach et al., 2020) at a native input meteorological resolution of 0.25°, dynamically downscaled/mapped to model requirements. Processing Infrastructure: Tracked, processed, and validated under the Planet4Health deployment pipeline (https://git.ufz.de/planet4health/mhm_production/-/tree/main/postproc?ref_type=heads). Data Interfaces: Climate Data Interface version 2.2.4 (CDI) | Climate Data Operators version 2.2.2 (CDO) | NetCDF Operators version 5.1.7 (NCO). 📤 Output Variables swc_l01: Soil water content layer 1 (0-50 mm depth) [mm] swc_l02: Soil water content layer 2 (50-150 mm depth) [mm] 📫 Contact Ehsan Modiri - ehsan.modiri@ufz.de Pallav Kumar Shrestha - pallav-kumar.shrestha@ufz.de Institution Helmholtz Centre for Environmental Research - UFZ, Department of Computational Hydrosystems
This archive contains a global monthly marine net primary productivity (NPP) product derived from the Data-based Productivity Model (DbPM), an observationally constrained machine-learning framework developed using an expanded global compilation of in situ 14 C/ 13 C-based NPP measurements and satellite-derived environmental predictors. Original DbPM NPP product - generated directly from satellite observations and therefore containing gaps associated with missing satellite data coverage. Gap-filled DbPM NPP product - reconstructed using Empirical Orthogonal Function (EOF)-based interpolation to fill missing values caused by satellite data gaps, providing a spatially complete global monthly NPP field. Chen, X., Huang, Y., Liu, H., Cassar, N., Liu, X., Wang, W., Chai, F., Kang, J., & Huang, B. (2026). Reduced estimate of global marine primary productivity and hemispheric redistribution over the satellite era revealed by an expanded global observational database. Submitted to Communications Earth & Environment .
Historical Hydrological Simulations over the South African Domain (1990-2024) The mHM's simulations of the Planet4Health project This dataset contains historical hydrological simulations for the South African domain (domain 1020011530) conducted with the Mesoscale Hydrological Model (mHM) at a spatial resolution of 0.015625° . The simulation period spans 1990-2024 and was part of the Planet4Health (P4H) project, utilising the ERA5 meteorological forcing. This archive is prepared for DOI assignment and ensures long-term reproducibility. It includes relevant clipped NetCDF components (streamflow 'q', soil moisture 'sm_l01', domain mask, and uparea assets) , consistent with the infrastructure provided within the Helmholtz Centre for Environmental Research (UFZ) . The simulations were executed using a specific version of the mHM model with the SCC method for gauges, paired with the mRMv1.0 routing configuration. 🛰️ Simulation Details Model: Mesoscale Hydrological Model (mHM) Codebase: scc_for_gauges branch ( https://git.ufz.de/shresthp/mhm/-/tree/scc_for_gauges?ref_type=heads ) Spatial resolution: 0.015625° Temporal resolution: Daily Simulation period: 1990-2024 Simulation type: Historical simulation Model version: mHMv5.11.3 (Release mRMv1.0) Setup Scope: Model run for domain 1020011530, post-processed and clipped. Simulation Version: v1.0 Configuration & Modules The configuration utilises standard structural components with the SCC methodology. Modules included: Snow processes: Degree-day method Soil moisture: Feddes equation for evapotranspiration reduction Infiltration: Multi-layer Brooks-Corey-like approach Direct runoff: Linear reservoir exceedance method Potential evapotranspiration: Hargreaves-Samani method Interflow: Storage reservoir with nonlinear outflow Groundwater: Linear reservoir Routing: Adaptive time-step routing with mRMv1.0 mechanisms 📥 Input Datasets Meteorological Forcing: ERA5 (Hersbach et al., 2020) at a native input meteorological resolution of 0.25°, dynamically downscaled/mapped to model requirements. Processing Infrastructure: Tracked, processed, and validated under the Planet4Health deployment pipeline ( https://git.ufz.de/planet4health/mhm_production/-/tree/main/postproc?ref_type=heads ). Data Interfaces: Climate Data Interface version 2.2.4 (CDI) | Climate Data Operators version 2.2.2 (CDO) | NetCDF Operators version 5.1.7 (NCO). 📤 Output Variables q: Routed streamflow (discharge) [m3 s-1] sm_l01: Volumetric soil moisture of soil layer 1 (top 50 mm) [mm mm-1, fraction between 0 and 1] mask: Domain clipping structure [binary flag / dimensionless] uparea: Upstream catchment area matrix [m2] 📫 Contact For questions or collaboration inquiries, please contact: Ehsan Modiri - ehsan.modiri@ufz.de Pallav Kumar Shrestha - pallav-kumar.shrestha@ufz.de 📚 References Boeing, F. et al., 2022. Hydrol. Earth Syst. Sci. , 26, 5137-5161. Hargreaves, G.H. & Samani, Z.A., 1985. Applied Engineering in Agriculture , 1(2), pp.96-99. Hartmann, J. & Moosdorf, N., 2012. Geochem. Geophys. Geosyst. , 13(12). Hengl, T. et al., 2017. PLoS One , 12(2), e0169748. Hersbach, H. et al., 2020. QJRMS , 146(730), pp.1999-2049. Kumar, R. et al., 2013. Water Resources Research , 49(1), pp.360-379. Lehner, B. et al., 2011. Front. Ecol. Environ. , 9(9), pp.494-502. Rakovec, O. et al., 2016. J. Hydrometeorology , 17(1), pp.287-307. Rakovec, O. et al., 2022. Earth's Future , 10(3), e2021EF002394. Samaniego, L. et al., 2010. Water Resources Research , 46(5). Samaniego, L. et al., 2023. mhm-ufz/mHM: v5.13.1, Zenodo. DOI: 10.5281/zenodo.8279545 Thober, S. et al., 2019. Geosci. Model Dev. , 12(6), pp.2501-2521.
Standardised Precipitation Evapotranspiration Index (SPEI) at 3, 6, 12, and 24-month timescales for the Australian continent at 0.01-degree (~1 km) resolution, computed for the period January 1980 to December 2024. Derived from ANUClimate v2.0 monthly rainfall, maximum temperature, minimum temperature, and solar radiation using the Hargreaves potential evapotranspiration method and log-logistic distribution fitting. Reference period: January 1980 to December 2009 (30 years). Output period for monthly GeoTIFFs: January 2010 to December 2024. Full-timeseries NetCDF files (540 months, 1980-2024) provided for all four timescales. CRS: GDA94 (EPSG:4283). Missing value (NetCDF): -9999. Source data: ANUClimate v2.0 (Hutchinson et al. 2021, doi:10.25914/60a10acd183a2). This is the highest resolution (~1 km, 0.01°) continental SPEI dataset available for Australia and the only one derived from ANUClimate v2.0. The closest existing global product is at 5 km resolution (Gebrechorkos et al. 2023, Earth System Science Data). This work was supported by Western Sydney University and with funding from the Australian Government under the National Environmental Science Program's Resilient Landscapes Hub. Known limitations: - SPEI values of -Inf occur in hyper-arid regions and during extreme drought periods where log-logistic distribution fitting fails. These are retained as -Inf in GeoTIFF outputs and stored as missing value (-9999) in NetCDF outputs. See README.md for full details. - SPEI values within the reference period (January 1980 - December 2009) are self-referential and should be interpreted with caution. The 2010-2024 monthly GeoTIFF outputs are the primary scientific deliverable. Code developed with AI assistance from Claude (Anthropic). https://claude.ai See README.md for full methods, known limitations, and reproduction instructions.
A small example dataset used by the xgcm Grid Metrics documentation. It is a single monthly-mean snapshot from the standard MITgcm verification/tutorial experiment tutorial_global_oce_latlon (a.k.a. global_ocean.90x40x15 ): a 4°×4° global latitude-longitude ocean configuration on an Arakawa C-grid, 90×40 horizontal points and 15 vertical levels. The MITgcm MDS binary output was wrapped into netCDF via xmitgcm.open_mdsdataset(..., geometry='sphericalpolar') . The file is byte-for-byte identical to datasets/mitgcm_example_dataset_v2.nc as historically shipped in the xgcm repository (md5 3176deb0b4d556d2981dff03ba2ed624 ); see the exact source blob on GitHub . It is provided so the documentation example can fetch the data via pooch rather than vendoring a binary in the repository.
Lagos-Zúñiga, Miguel A. · Rondanelli, Roberto · Lyra, Andre
8 files · 1.5 GB · netcdf, zipdeclared
This dataset includes daily precipitation fields from the RegCM4.5 simulation performed by Bozkurt et al. (2019) and the CR2 (2018) dataset, both subsetted to the subtropical Andes. In addition, it includes surface temperature, air temperature at 500 and 850 hPa, and specific humidity at 850 hPa from the Eta model (Mesinger et al., 2012). These fields were used in the manuscript entitled "Potential Instability and Seasonal Extreme Precipitation Projections in the Andes Cordillera through Regional Climate Models (15-35°S)," submitted to Geophysical Research Letters .
Version history Version 2: This version updates Figure1.py and MainFigure.ipynb to match the revised manuscript submitted to Geophysical Research Letters. Specifically, a scale bar was added to Figure 1. No changes were made to the input datasets, analysis workflow, or scientific results. Code All results were analyzed and visualized by Python version 3.9.18. Filename Description MainFigures.ipynb Jupyter Notebook for reproduce all figures in the article. Figure*.py Python file for reproduce each figure in the article. Data Ground Station Observation Filename Description 467530_hr_19800101_20230101.csv Alishan station data managed by Central Weather Administration (CWA) of Taiwan, which is generated from Atmospheric Science Research and Application Databank . Solar Radiation Reduction Ratio (RR SR ) Results Filename Description ReductionRatio_20151001_20220930_31_daily.nc RR SR of Taiwan (119.9°E-122.1°E, 21.8°N-25.4°N, 0.01° x 0.01°) from 2015-10-01 to 2022-09-30, which is generated from TCCIP Grid-point Surface Insolation Derived from Geostationary Satellite Dataset . *_hr_20151001_20220930_seasonal.csv Seasonal mean RR SR for 6 CWA stations (Alishan, Anbu, Yushan, Sun Moon Lake, Chiayi, and Keelung). *_hr_20151001_20220930_DJF_NE_means.csv Winter (December-February) event-mean RR SR for 6 CWA stations (Alishan, Anbu, Yushan, Sun Moon Lake, Chiayi, and Keelung). Land and Non-rainy Mask Filename Description LandNonRainyMask_2015_2022.nc Mask for land area and non-rainy data, which is generated from TCCIP Gridded Historical Daily Dataset for Taiwan . Land-type Classification Generated from Schulz et al. (2017) . Filename Description MCF2017.zip Shapefile of montane cloud forests (MCFs) region in Taiwan. nonMCF2017.zip Shapefile of forest region other than montane cloud forest in Taiwan. MCFfraction_TCCIP.npy Forest classification in Taiwan regrid to TCCIP dataset. North-easterlies events classification Adopted from Taiwan Atmospheric Event Database . Filename Description TAD_NE.csv North-easterlies events classification based on the criteria of Taiwan Atmospheric Event Database (TAD). Others Generated from Open Data in Taiwan . Filename Description Taiwan_WGS84.zip Shapefile of coastlines of Taiwan. dem20_TCCIPInsolation.nc Digital Elevation Model of Taiwan regrid to TCCIP dataset. Note Please unzip .zip first to get shapfile before reproduce the figures in the article.
Albright, Anna Lea · Stevens, Bjorn · Wirth, Martin
89 files · 4.4 GB · netcdf, pdf, pngdeclared
Code to reproduce "Estimating near-surface specific humidity over convective oceanic regions from cloud base height observations" in Atmospheric Measurement Techniques (AMT)
These data belong with the manuscript "Diagnosing the influence of Southern Ocean storms on air-sea carbon dioxide flux from synthetic floats: A modeling study" by Katy M. Christensen , Nicole S. Lovenduski, Mathew Maltrud, LeAnn Conlon, and Cara Nissen (in preparation for Geophysical Research Letters ). Contact for data set: katy.christensen@colorado.edu The data provided here are post-processed from the raw Energy Exascale Earth System Model (E3SMv2) code with Argo float simulator with a Southern Ocean Regionally Refined Mesh (SORRM). Provided are the average (stormfloatsdata_2014_2023.nc) and composite (stormfloatsdata_composite_2014_2023) storm-driven anomalies for various oceanographic and atmospheric variables in Southern Ocean storms for 2014-2023, as sampled by our synthetic float array. Additionally, we provide the same storm anomaly composite variables subsampled at various (ARGO and SOCCOM) distributions of real-world float arrays. The following variables are provided: storm number (snum), storm time (time) storm longitude (lon) storm latitude (lat) Carbon flux anomaly (Cflux) dissolved inorganic carbon anomaly (DIC) ocean surface pCO2 anomaly (pCO2) dpCO2 anomaly (dpCO2) alkalinity anomaly (ALK) mixed layer depth anomaly (MLD) temperature anomaly (T) salinity anomaly (S) zonal/meridional wind anomaly (uwind,vwind) Analysis and plotting scripts are available on GitHub .
These processed data support the CAM4-based analyses in the manuscript "Low-Frequency Stratospheric Variability and its Link to Surface Climate: Insights from Reanalysis and Multi-Century Coupled Climate Model Simulations". The archive includes 1000 years of monthly indices for the NAO, Aleutian Low, PDO, and NAM (10 hPa), as well as monthly fields of sea level pressure, sea surface temperature, and geopotential height.
43 average_NT.py and 43 average_DT_2.py are models for nondiazotrophic Tricho and diazotrophic Tricho 43 figure2.py was used to make Figure 2 43 C_allocation_figure3.py was used to make Figure 3 43 Fe_comparison_HN_Figure_4.py and 43 Fe_comparison_LN_ma.py were used to make Figure 4 43 Tricho2_Fe_N_gradient_2.py was used to make Figure 5 43 map3.py was used to make Figure 6 43 map_env.py is for supplementary figures Figures in the manuscript were also edited using PowerPoint.
Kohopää, Katja · Nissilä, Jaani · Mykkänen, Emma · et al.
8 files · 32 MB · netcdf, zipdeclared
The data supporting publication titled "Fast optical data transfer into a Josephson junction array". The measurement data is in the NetCDF (.nc) files. The .zip file contains folders of simulation data, organized by the figure numbers in the manuscript. The README file contains detailed information about the files.