Labs WMT Permafrost KudryavtsevModel1D

Introduction to Permafrost Processes - Lesson 2 Kudryavtsev Model

This lab has been designed and developed by Irina Overeem, CSDMS, University of Colorado, CO
with assistance of Kang Wang, Scott Stewart at CSDMS, University of Colorado, CO, and Elchin Jafarov, at Los Alamos National Labs, NM

Classroom organization
This lab is the second in a series of introduction to permafrost process modeling, designed for inexperienced users. In this second lesson, we explore the Kudryavstev model and learn to use this models in the CSDMS Web Model tool (WMT). We implemented the Kudryavstev model (as formulated by Anisimov et al.1997). This series of labs is designed for inexperienced modelers to gain some experience with running a numerical model, changing model inputs, and analyzing model output. Specifically, this lab looks at what controls soil temperature and active layer thickness and compares model output with observed longterm data collected at permafrost active layer thickness monitoring sites in Fairbanks and Barrow, Alaska.
Basic theory on the Kudryavstev model is presented in these slides

to complete in the classroom. This time assumes you now have gained some familiarity with the WMT and have learned how to set parameters, save runs, download data and look at output. If this is not the case, either start with Lab 1 in this series, or do the WMT Tutorial

Learning objectives

Skills

• familiarize with a basic configuration of the Kudryavstev Model
• hands-on experience with visualizing NetCDF time series with Panoply.
• data to model comparisons and how to think about uncertainty in data and model output.

Topical learning objectives:

• what are controls on permafrost soil temperature
• what is a steady-state model
• what are important parameters for calculating active layer thickness
• active layer thickness evolution with climate warming in two locations in Alaska

Lab Notes
>> We will run the Kudryatsev model for conditions in Barrow, Alaska in a very cold year, 1964. The mean annaul temperature for 1964 was -15.21C, the amplitude over that year was 18.51C. It was close to an average snow year, meaning the average snow thickness over this winter was 0.22m.

>> Adapt the settings in the Ku model for Barrow 1964. Make sure you request an output file. Save the simulation settings and submit your simulation. Download the model results and open them in Panoply.

 What was the active layer thickness the model predicted? 
 Sketch a soil profile for winter conditions versus August conditions, indicate where the frozen-unfrozen boundary is in each two cases.

 How do you think snow affects the active layer thickness predictions?

>> Run the Kudryatsev model with a range of snow conditions. What happens if there is no snow at all (0.0m)? In extremely snowy years, the mean snow thickness over the winter is 0.4m, what is the active layer thickness prediction for such a year?

>> Posted here are time-series for climate conditions for both Barrow and Fairbanks, Alaska. Time-series are annual values and run from 1961-2015, the data include mean annual temperature (MAAT), temperature amplitude (TAMP) and winter-average snow depth (SD).