iffylaw/PIC: PIC v1.2: Comprehensive R package for permafrost indices computing
An R package permafrost indices computing (PIC v1.2) was developed, which integrates meteorological observations, gridded meteorological dataset, soil database, and field measurements to compute the factors or indices of permafrost and seasonal frozen soil. At present, 16 temperature/depth-related i...
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| Format: | Software |
| Language: | unknown |
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2018
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| Online Access: | https://zenodo.org/record/1237428 https://doi.org/10.5281/zenodo.1237428 |
| Summary: | An R package permafrost indices computing (PIC v1.2) was developed, which integrates meteorological observations, gridded meteorological dataset, soil database, and field measurements to compute the factors or indices of permafrost and seasonal frozen soil. At present, 16 temperature/depth-related indices are integrated into the R package PIC v1.2 to estimate the possible change trends of frozen soil in the Qinghai–Tibet Plateau (QTP). These indices include the mean annual air temperature (MAAT), mean annual ground surface temperature (MAGST), mean annual ground temperature (MAGT), seasonal thawing/freezing n factor (nt/nf), thawing/freezing degree-days of air and ground surface (DDTa/DDTs/DDFa/DDFs), temperature at the top of the permafrost (TTOP), active layer thickness (ALT), and maximum seasonal freeze depth. The PIC v1.1 supports two computational modes, namely, the stations and region calculation that enables statistical analysis and intuitive visualization on the time series and spatial simulations. The data sets of 52 weather stations and a central region of QTP were prepared and simulated to evaluate the temporal–spatial change trends of permafrost with the climate. Over 10 statistical methods and a sequential Mann-Kendall trend test was adopted to evaluate these indices in stations, and spatial trend method were adopted to the spatial change trends . Multiple visual manners display the temporal and spatial variabilities on the stations and region. Simulation results show extensive permafrost degradation in QTP, and the temporal–spatial trends of the permafrost conditions in QTP were closed with those of previous studies. The transparency and repeatability of the PIC v1.2 package and its data will can be used and extended to assess the impact of climate change on permafrost. |
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