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from dagshub.streaming import DagsHubFilesystem
fs = DagsHubFilesystem(".", repo_url="https://dagshub.com/DagsHub-Datasets/noaa-uwpd-cmip5-dataset")
fs.listdir("s3://noaa-nws-uwpd-cmip5-pds")
The University of Wisconsin Probabilistic Downscaling (UWPD) is a statistically downscaled dataset based on the Coupled Model Intercomparison Project Phase 5 (CMIP5) climate models. UWPD consists of three variables, daily precipitation and maximum and minimum temperature. The spatial resolution is 0.1°x0.1° degree resolution for the United States and southern Canada east of the Rocky Mountains.
The downscaling methodology is not deterministic. Instead, to properly capture unexplained variability and extreme events, the methodology predicts a spatially and temporally varying Probability Density Function (PDF) for each variable. Statistics such as the mean, mean PDF and annual maximum statistics can be calculated directly from the daily PDF and these statistics are included in the dataset. In addition, “standard”, “raw” data is created by randomly sampling from the PDFs to create a “realization” of the local scale given the large-scale from the climate model. There are 3 realizations for temperature and 14 realizations for precipitation.
The directory structure of the data is as follows
[cmip_version]/[scenario]/[climate_model]/[ensemble_member]/
The realizations are as follows
prcp_[realization_number][year].nc
temp
[realization_number][year].nc
The time mean files averaged over certain year bounds are as follows
prcp_mean
[year_bound_1][year_bound_2].nc
temp_mean
[year_bound_1][year_bound_2].nc
The time-mean Cumulative Distribution Function (CDF) files are as follows
prcp_cdf
[year_bound_1][year_bound_2].nc
temp_cdf
[year_bound_1][year_bound_2].nc
The CDF of the annual maximum precipitation is given for each year in the record
prcp_annual_max_cdf
[start_year_of_scenario]_[end_year_of_scenario].nc
The University of Wisconsin Probabilistic Downscaling (UWPD) is a statistically downscaled dataset based on the Coupled Model Intercomparison Project Phase 5 (CMIP5) climate models. UWPD consists of three variables, daily precipitation and maximum and minimum temperature. The spatial resolution is 0.1°x0.1° degree resolution for the United States and southern Canada east of the Rocky Mountains.
The downscaling methodology is not deterministic. Instead, to properly capture unexplained variability and extreme events, the methodology predicts a spatially and temporally varying Probability Density Function (PDF) for each variable. Statistics such as the mean, mean PDF and annual maximum statistics can be calculated directly from the daily PDF and these statistics are included in the dataset. In addition, “standard”, “raw” data is created by randomly sampling from the PDFs to create a “realization” of the local scale given the large-scale from the climate model. There are 3 realizations for temperature and 14 realizations for precipitation.
The directory structure of the data is as follows
[cmip_version]/[scenario]/[climate_model]/[ensemble_member]/
The realizations are as follows
prcp_[realization_number][year].nc
temp
[realization_number][year].nc
The time mean files averaged over certain year bounds are as follows
prcp_mean
[year_bound_1][year_bound_2].nc
temp_mean
[year_bound_1][year_bound_2].nc
The time-mean Cumulative Distribution Function (CDF) files are as follows
prcp_cdf
[year_bound_1][year_bound_2].nc
temp_cdf
[year_bound_1][year_bound_2].nc
The CDF of the annual maximum precipitation is given for each year in the record
prcp_annual_max_cdf
[start_year_of_scenario]_[end_year_of_scenario].nc
Periodically, as new data becomes available or when corrections are implemented.
aws-pds, climate, coastal, disaster response, environmental, meteorological, sustainability, oceans, water, weather
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