Journal cover Journal topic
Geoscientific Model Development An interactive open-access journal of the European Geosciences Union
https://doi.org/10.5194/gmd-2018-15
© Author(s) 2018. This work is distributed under
the Creative Commons Attribution 4.0 License.
Development and technical paper
06 Mar 2018
Review status
This discussion paper is a preprint. A revision of this manuscript was accepted for the journal Geoscientific Model Development (GMD) and is expected to appear here in due course.
PIC: Comprehensive R package for permafrost indices computing with daily weather observations and atmospheric forcing over the Qinghai–Tibet Plateau
Lihui Luo1, Zhongqiong Zhang1, Wei Ma1, Shuhua Yi2, and Yanli Zhuang3 1State Key Laboratory of Frozen Soils Engineering, Cold and Arid Regions Environmental and Engineering Research Institute, Chinese Academy of Sciences, Lanzhou, Gansu Province 730000, China
2State Key Laboratory of Cryospheric Sciences, Cold and Arid Regions Environmental and Engineering Research Institute, Chinese Academy of Sciences, Lanzhou, Gansu Province 730000, China
3Linze Inland River Basin Research Station, Key Laboratory of Inland River Basin Ecohydrology, Cold and Arid Regions Environmental and Engineering Research Institute, Chinese Academy of Sciences, Lanzhou, Gansu Province 730000, China
Abstract. An R package permafrost indices computing (PIC) was developed, which integrates meteorological observations, remote sensing data, 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 to estimate the possible change trends of frozen soil in the Qinghai–Tibet Plateau (QTP). These indices include the mean annual air temperature, mean annual ground surface temperature, mean annual ground temperature, 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, active layer thickness, and maximum seasonal freeze depth. The PIC package supports two computational modes, namely, the stations and region calculation that enables statistical analysis and intuitive visualization on the time series and spatial simulations. Over 10 statistical methods were adopted to evaluate these indices in stations, and a sequential Mann-Kendall trend test and spatial trend method were adopted. Multiple visual manners display the temporal and spatial variabilities on the stations and region. 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. Simulation results show extensive permafrost degradation in QTP, and the temporal–spatial trends of the permafrost conditions in QTP were consistent with those of previous studies. The PIC package will serve engineering applications and can be used to assess the impact of climate change on permafrost.
Citation: Luo, L., Zhang, Z., Ma, W., Yi, S., and Zhuang, Y.: PIC: Comprehensive R package for permafrost indices computing with daily weather observations and atmospheric forcing over the Qinghai–Tibet Plateau, Geosci. Model Dev. Discuss., https://doi.org/10.5194/gmd-2018-15, in review, 2018.
Lihui Luo et al.

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Short summary
Based on the current situation of permafrost modeling in the Qinghai-Tibet Plateau (QTP), a software PIC was developed to evaluate the temporal–spatial change trends of permafrost, which allows to automatically compute permafrost indices with daily weather and atmospheric forcing datasets. The main features include computing, visualization and statistics. The software will serve engineering applications and can be used to assess the impact of climate change on permafrost over the QTP.
Based on the current situation of permafrost modeling in the Qinghai-Tibet Plateau (QTP), a...
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