The GTNP DMS enable to upload data in a great variety of dimensions in terms of variables, data types, frequencies, profiles. Datasets are processed either onthefly or by running scripts.
Variable  Unit  Comments 
AVG Temp  (°C)  Mean of all measurements over the full period 
MIN Temp  (°C)  Lowest measured value over the full period 
MAX Temp  (°C)  Highest measured value over the full period 
StDev  Standard deviation over all measurements and the full period  
Variance  Variance over all measurements and the full period  
Data  Number of single data in the dataset  
Null  Number of null values (fields lacking values)  
Start  First day of the measurement period  
End  Last day of the measurement period 
Statistics are computed for all ground temperature datasets and at each sensor's depths.
Variable  Unit  Comment 
AVG  (°C)  Mean temperature for each depth and year 
MIN  (°C)  Minimum temperature for each depth and year 
MAX  (°C)  Maximum temperature for each depth and year 
Data count 
Variable  Unit  Comment 
Tolerance  (+/°C)  Temperature variation tolerance in order to set the ZAA depth 
ZAA depth for each year, positive down  (m)  Applicable only if the profile reach the ZAA, if measurements over one depth > 2 month within a year ? 
ZAA temperature (°C)  (°C)  Interpolated temperature found at ZAA 
ZAA_deta  (m)  Delta of the computed ZAA depths over the all time serie 
ZAA depth trends  (m/year)  linear regression. Applicable only if the the ZAA depth as been found over more than a year 
Methodical approach:
The ZAA is computed from the annual MIN, MAX profiles when measurements reach the ZAA depth (0.15°C of tolerance).
Linear regression a spline curve is created to find the ZAA depth at the choosen tolerance (0.15°C).
The statistical dispersion of the data, only enable a full representativeness of the trends after a period of 30 years with 2 months maximum consecutive gaps from at least monthly time series.
None of our data, so far, are eligible to this quality standard. However the International Permafrost Association's Action Group on Data quality assesses the quality parametres of the permafrost community.
In order to produce orthogonal matrix of data: Reducing the data of each eligible boreholes to 5 depths in the following concept:
0 m, Annual Min.,Max., Average temperature
1 m, Annual Min.,Max., Average temperature
2 m, Annual Min.,Max., Average temperature
5 m, Annual Min.,Max., Average temperature
10 m, Annual Min.,Max., Average temperature
Methodical approach:
Every value gets a „flag_depth“ either borehole (1) reaching 10m, (2) reaching 5m, (3) reaching 2m, (4) reaching 1m, (5) reaching less than 1m.
Every value gets a „flag_frequency“ either (1) min. max. and average available or (2) only average available (due to existing raw data).

Statistics are computed for all active layer thickness grids and transects
Variable  Unit  Comment 
AVG  (cm)  over the grid for each date of measurements 
MIN  (cm)  over the grid for each date of measurements 
MAX  (cm)  over the grid for each date of measurements 
Stdev  (cm)  over the grid for each date of measurements 
Variance  (cm2)  over the grid for each date of measurements 
Annual rate of thawing  (cm/day)  Applicable only if more than 3 measurements a year 
Annual endofseason thawing trend  (cm/year)  Applicable only if more than 2 years of mesurements 
Methodical approach: The statistical dispersion of the data, only enable a certain representativeness of the trends after a period of 30 years with 2 years maximum of consecutive gap. None of our data, so far, are eligible to this quality standard. However the International Permafrost Association's Action Group on Data quality assesses the quality parametres of the permafrost community.
Read more:
Functions within the data management system to compute statistics