Both the hourly and daily data are provided in the product. The hourly data are grouped by day in distinct NetCDF files, which are named as “EPIC_SW_PAR_Hourly_yyyymmdd.nc” where “yyyy”, “mm”, and “dd” denote year, month, and day (UTC time). The daily data are grouped by month in distinct NetCDF...

Both the hourly and daily data are provided in the product. The hourly data are grouped by day in distinct NetCDF files, which are named as “EPIC_SW_PAR_Hourly_yyyymmdd.nc” where “yyyy”, “mm”, and “dd” denote year, month, and day (UTC time). The daily data are grouped by month in distinct NetCDF...

Both the hourly and daily data are provided in the product. The hourly data are grouped by day in distinct NetCDF files, which are named as “EPIC_SW_PAR_Hourly_yyyymmdd.nc” where “yyyy”, “mm”, and “dd” denote year, month, and day (UTC time). The daily data are grouped by month in distinct NetCDF...

Both the hourly and daily data are provided in the product. The hourly data are grouped by day in distinct NetCDF files, which are named as “EPIC_SW_PAR_Hourly_yyyymmdd.nc” where “yyyy”, “mm”, and “dd” denote year, month, and day (UTC time). The daily data are grouped by month in distinct NetCDF...

Both the hourly and daily data are provided in the product. The hourly data are grouped by day in distinct NetCDF files, which are named as “EPIC_SW_PAR_Hourly_yyyymmdd.nc” where “yyyy”, “mm”, and “dd” denote year, month, and day (UTC time). The daily data are grouped by month in distinct NetCDF...

Both the hourly and daily data are provided in the product. The hourly data are grouped by day in distinct NetCDF files, which are named as “EPIC_SW_PAR_Hourly_yyyymmdd.nc” where “yyyy”, “mm”, and “dd” denote year, month, and day (UTC time). The daily data are grouped by month in distinct NetCDF...

Both the hourly and daily data are provided in the product. The hourly data are grouped by day in distinct NetCDF files, which are named as “EPIC_SW_PAR_Hourly_yyyymmdd.nc” where “yyyy”, “mm”, and “dd” denote year, month, and day (UTC time). The daily data are grouped by month in distinct NetCDF...

Both the hourly and daily data are provided in the product. The hourly data are grouped by day in distinct NetCDF files, which are named as “EPIC_SW_PAR_Hourly_yyyymmdd.nc” where “yyyy”, “mm”, and “dd” denote year, month, and day (UTC time). The daily data are grouped by month in distinct NetCDF...

Both the hourly and daily data are provided in the product. The hourly data are grouped by day in distinct NetCDF files, which are named as “EPIC_SW_PAR_Hourly_yyyymmdd.nc” where “yyyy”, “mm”, and “dd” denote year, month, and day (UTC time). The daily data are grouped by month in distinct NetCDF...

Both the hourly and daily data are provided in the product. The hourly data are grouped by day in distinct NetCDF files, which are named as “EPIC_SW_PAR_Hourly_yyyymmdd.nc” where “yyyy”, “mm”, and “dd” denote year, month, and day (UTC time). The daily data are grouped by month in distinct NetCDF...

Both the hourly and daily data are provided in the product. The hourly data are grouped by day in distinct NetCDF files, which are named as “EPIC_SW_PAR_Hourly_yyyymmdd.nc” where “yyyy”, “mm”, and “dd” denote year, month, and day (UTC time). The daily data are grouped by month in distinct NetCDF...

LIQUID Software Overview LIQUID provides users with the capability to process high throughput data and contains a customizable target library and scoring model per project needs. The graphical user interface provides visualization of multiple lines of spectral evidence for each lipid identification...

pmartR Software Overview The pmartR package provides a single software tool for QC (filtering and normalization), exploratory data analysis (EDA), and statistical analysis (robust to missing data) and includes numerous visualization capabilities of mass spectrometry (MS) omics data (proteomic...

Last updated on 2023-02-23T19:37:46+00:00 by LN Anderson Snekmer: A scalable pipeline for protein sequence fingerprinting using amino acid recoding (AAR) Snekmer is a software package designed to reduce the representation of protein sequences by combining amino acid reduction (AAR) with the kmer...

The influence of tidal inundation dynamics on below ground carbon pools is poorly understood across coastal terrestrial-aquatic interface (TAI) ecosystems. The dynamic environmental conditions of tidally-influenced landscapes, the chemically complex nature of carbon compounds, the diverse nature of...