Automated Author ProfileBoynton, Ryan
Boynton, Ryan
Current S-Index
Sum of Dataset Indices for all datasets
Average Dataset Index per Dataset
Average Dataset Index per dataset
Total Datasets
Total datasets for this author
Average FAIR Score
Average FAIR Score per dataset
Total Citations
Total citations to the author's datasets
Total Mentions
Total mentions of the author's datasets
S-Index Interpretation
The S-Index (Sharing Index) is a comprehensive metric that represents the cumulative impact of all your datasets. It is calculated as the sum of Dataset Index scores across all your claimed datasets.
What it means:
- A higher S-index indicates greater overall impact of your datasets relative to typical datasets in their fields of research
- The S-Index grows as you add more datasets or as existing datasets gain more citations and mentions
- It provides a single number to track your research data impact over time
Current S-Index: 1.6 (sum of 1 dataset Dataset Index scores)
More information here.
S-Index Over Time
Cumulative Citations Over Time
Cumulative Mentions Over Time
Datasets
The California Basin Characterization Model (CA-BCM 2014) dataset provides historical and projected climate and hydrologic surfaces for the region that encompasses the state of California and all the streams that flow into it (California hydrologic region ). The CA-BCM 2014 applies a monthly regional water-balance model to simulate hydrologic responses to climate at the spatial resolution of a 270-m grid. The model has been calibrated using a total of 159 relatively unimpaired watersheds for the California region. The historical data is based on 800m PRISM data spatially downscaled to 270 m using the gradient-inverse distance squared approach (GIDS), and the projected climate surfaces include five CMIP-3 (GFDL, PCM, MIROC3_2, CSIRO, GISS_AOM) and nine CMIP-5 (MIROC5, MIROC , GISS, MRI, MPI, CCSM4, IPSL, CNRM, FGOALS) General Circulation Models under a range of emission scenarios or representative concentration pathways (RCPs) for a total of 18 futures that have been statistically downscaled using BCSD to 800 m and further downscaled using GIDS to 270 m for model application. The BCM approach uses a regional water balance model based on this high resolution precipitation and temperature as well as elevation, geology, and soils to produce surfaces for the following variables: precipitation, air temperature, recharge, runoff, potential evapotranspiration (PET), actual evapotranspiration, and climatic water deficit, a parameter that is calculated as PET minus actual evapotranspiration. The following data are available in this archive: Raw, monthly model output for historical and future periods. Projected data is available for the following GCM and emission scenario or RCP combinations: GFDL-B1, GFDL-A2 PCM-B1, PCM-A2 MIROC3_2-A2 CSIRO-A1B GISS_AOM-A1B, MIROC5-RCP2.6, MIROC-RCP4.5, MIROC-RCP6.0, MIROC-RCP8.5 GISS-RCP2.6, MRI-RCP2.6, MPI- RCP4.5, CCSM4-RCP8.5, IPSL-RCP8.5, CNRM-RCP8.5, FGOALS-RCP8.5. Data variables: Actual evapotranspiration - water available between wilting point and field capacity, mm (aet); Climatic water deficit - Potential minus actual evapotranspiration, mm (cwd); Maximum monthly temperature, degrees C - (tmx); Minimum monthly temperature, degrees C - (tmn); Potential evapotranspiration - Water that could evaporate or transpire from plants if available, mm (pet); Recharge - Amount of water that penetrates below the root zone, mm (rch); Runoff - Amount of water that becomes stream flow, mm (run); Precipitation, mm - (ppt). Note that another archive, hosted by the California Climate Commons contains various climatological summaries of these data. That archive can be found at: http://climate.calcommons.org/
Authors
- Flint, Lorraine ;
- Flint, Alan ;
- Thorne, James ;
- Boynton, Ryan