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- Creator:
- Mateling, Marian E. and Pettersen, Claire
- Description:
- This merged Global Precipitation Measurement (GPM) Core Observatory and atmospheric river dataset contains gridded Goddard Profiling (GPROF) algorithm v7 precipitation rates (Kummerow et al. 2015; Randel et al. 2020), Remote Sensing Systems (RSS) atmospheric water vapor (Meissner et al. 2012), and Mattingly et al. (2018) atmospheric rivers in the North Atlantic and North Pacific oceans. The GPROF precipitation rates and RSS atmospheric water vapor are both derived using the GPM Microwave Imager (GMI) brightness temperature observations. The atmospheric river data is derived from MERRA-2 (Modern-Era Retrospective analysis for Research and Applications Reanalysis, Version 2) integrated water vapor transport (Mattingly et al. 2018). , The data coverage starts at the beginning of the GPM data record (GPM launched in Feb 2014 and the processed data coverage starts in May 2014). Subsequent years will be added throughout the lifetime of the project. , The monthly files are compressed into year and basin: either the North Atlantic (NA) or the North Pacific (NP) (e.g., NA_2014) and zipped. The files have the basin name indicated and are by year and month (e.g., gridded_atlantic_201405.nc). The files produced are in NetCDF format ( https://www.unidata.ucar.edu/software/netcdf/) and conform to all standard NetCDF metadata conventions ( http://cfconventions.org/cf-conventions/cf-conventions.html), and Kummerow, C. D., Randel, D. L., Kulie, M., Wang, N. Y., Ferraro, R., Joseph Munchak, S., & Petkovic, V. (2015). The evolution of the Goddard profiling algorithm to a fully parametric scheme. Journal of atmospheric and oceanic technology, 32(12), 2265-2280. https://doi.org/10.1175/JTECH-D-15-0039.1 Mattingly, K. S., Mote, T. L., & Fettweis, X. (2018). Atmospheric river impacts on Greenland Ice Sheet surface mass balance. Journal of Geophysical Research: Atmospheres, 123(16), 8538-8560. https://doi.org/10.1029/2018JD028714 Meissner, T., F. J. Wentz, and D. Draper, 2012: GMI Calibration Algorithm and Analysis Theoretical Basis Document, Remote Sensing Systems, Santa Rosa, CA, report number 041912, 124 pp. Randel, D. L., Kummerow, C. D., & Ringerud, S. (2020). The Goddard Profiling (GPROF) precipitation retrieval algorithm. Satellite Precipitation Measurement: Volume 1, 141-152. https://doi.org/10.1007/978-3-030-24568-9_8
- Keyword:
- Precipitation, satellite, microwave radiometer, atmospheric water vapor, and remote sensing
- Citation to related publication:
- Mateling et al., submitted to Earth and Space Science (updated when finalized)
- Discipline:
- Science
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- Creator:
- Horsley, Timothy J. and Sampson, Christina P.
- Description:
- The data (raw data, composite files [processed], and some images) can be read by the program TerraSurveyor. Version 3.0.34.10 of the software was used to create the composite files in this deposit. and The magnetometer data was the second step in a geophysical survey program that began with magnetic susceptibility survey of a portion of the Weedon Island Preserve in St. Petersburg, Florida. Geophysical survey was used to map human occupation of the study area and to guide subsequent archaeological excavations.
- Keyword:
- magnetometry, geophysical survey, remote sensing, Florida archaeology, and coastal archaeology
- Citation to related publication:
- Sampson, C. P. (2019) Safety Harbor at the Weeden Island Site: Late Pre-Columbian Craft, Community, and Complexity on Florida's Gulf Coast. PhD Dissertation, University of Michigan. and Sampson, Christina Perry and Timothy J. Horsley. Using Multi-Staged Magnetic Survey and Excavation to Assess Community Settlement Organization: A Case Study from the Central Peninsular Gulf Coast of Florida. Advances in Archaeological Practice. Cambridge University Press: 18 December 2019. https://doi.org/10.1017/aap.2019.45
- Discipline:
- Science and Social Sciences
-
- Creator:
- Yang, Emily G, Kort, Eric A, Wu, Dien, Lin, John C, Oda, Tomohiro, Ye, Xinxin, and Lauvaux, Thomas
- Description:
- This data set supports a study that seeks to evaluate global fossil fuel CO2 emissions inventory representations of CO2 emissions of five cities in the Middle East, and assess the ability of satellite observations to inform this evaluation. Improved observational understanding of urban CO2 emissions, a large and dynamic global source of fossil CO2, can provide essential insights for both carbon cycle science and mitigation decision making. In this study we compare three distinct global CO2 emissions inventory representations of urban CO2 emissions for five Middle Eastern cities (Riyadh, Mecca, Tabuk, Jeddah, and Baghdad) and use independent satellite observations from the Orbiting Carbon Observatory-2 (OCO-2) satellite to evaluate the inventory representations of afternoon emissions. We use the column version of the Stochastic Time-Inverted Lagrangian Transport (X-STILT) model to account for atmospheric transport and link emissions to observations. We compare XCO2 simulations with observations to determine optimum inventory scaling factors. Applying these factors, we find that the average summed emissions for all five cities are 100 MtC/y (50-151, 90% CI), which is 2.0 (1.0, 3.0) times the average prior inventory magnitudes. The total adjustment of the emissions of these cities comes out to ~7% (0%, 14%) of total Middle Eastern emissions (~700 MtC/y). We find our results to be insensitive to the prior spatial distributions in inventories of the cities’ emissions, facilitating robust quantitative assessments of urban emission magnitudes without accurate high-resolution gridded inventories. and There are three files included in this data set, and all data are in tab-delimited form. The first file, xco2_lat.zip, contains 26 separate text files, each named by the city and date of the corresponding OCO-2 overpass. Each of these 26 files includes overpass-specific data, with modeled and observed XCO2 values binned by 0.1 degree of latitude. The file overpass_scaling_factors.txt provides the scaling factors for each overpass used in this study. The file city_estimates.txt provides the scaled emissions estimates for each city (or sum of cities) as well as the lower and upper bounds of the 90% confidence intervals, for each inventory.
- Keyword:
- greenhouse gases, carbon dioxide, urban, cities, satellite, remote sensing, Lagrangian modeling, emissions inventories, carbon cycle, and climate
- Citation to related publication:
- Yang, E. G., Kort, E. A., Wu, D., Lin, J. C., Oda, T., Ye, X., & Lauvaux, T. (2020). Using space‐based observations and Lagrangian modeling to evaluate urban carbon dioxide emissions in the Middle East. Journal of Geophysical Research: Atmospheres, 125, e2019JD031922. https://doi.org/10.1029/2019JD031922
- Discipline:
- Science