The ICNet REU Freeze-Thaw Research Project The Climate Change Analysis Technical Guide: Model Output, Pre-Processing, Analysis, and Displaying Results

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1 The ICNet REU Freeze-Thaw Research Project The Climate Change Analysis Technical Guide: Model Output, Pre-Processing, Analysis, and Displaying Results This guide provides the necessary steps for analyzing multiple pavement locations using a modified automation of Model 158, developed by the U.S Army Corps of Engineers. The results include.csv file outputs of daily and annual metrics as well as plots of those metrics. This set of R analysis instructions is only written for one location; Madison, ME. Therefore, steps must be repeated with naming convention adjustments to generate results for other locations. MODEL OUTPUT First, obtain necessary observed data ( ) and CMIP5 downscaled global climate model output ( ) for the geographical region being analyzed. Be sure to properly name files depending on data source chosen prior to performing R analysis. This project uses two different sources of model output: Bureau of Reclamation and Station Data. Bureau of Reclamation Follow instructions below which are adapted from the U.S Department of Transportation: Federal Highway Administration s pdf user guide, linked here: es/user_guide/ 1. Enter the Bureau of Reclamation s website by following this link: Confirm the website entry. 2. Click on the "Projections: Subset Request" tab. 1

2 3. Time Step and Period (Step 1.1) 1. Select Daily. 2. Select the full time period, January 1950 through December Domain (Step 1.2) 1. Select NLDAS (referring to North American Land-Data Assimilation System.) 5. Spatial extent selection method (Step 1.3) 1. Site coordinates must be in decimal degree format. If not, convert them using an online converter. a. For Madison, ME the coordinates: N and W were converted using to Note that Northern and Eastern coordinates are represented by positive numbers, conversely Southern and Western coordinates are shown as negative numbers. b. Choose Location as the method and copy and paste the site coordinates. Then click Map Location and zoom in using the slider tool to check that only one grid cell is selected. Do not click on the map itself because it will change the set coordinates. To focus the zooming, instead click and drag the map until the chosen location is visible. 6. Click on the second tab at the top of the form, Page 2: Products, Variables, Projections 1. Select BCCAv2-CMIP5-Climate-daily. 7. Products & Variables -- daily projections (Step 2.5) 1. Under Products, select 1/8 degree BCCA projections and 1/8 degree Observed data ( ) 2

3 2. Under Variables, select all three: Precipitation Rate (mm/day), Min Surface Air Temperature (deg C), and Max Surface Air Temperature (deg C.) 8. Emissions Scenarios, Climate Models and Runs (Step 2.6) 1. Select any number of models and model runs, but do not include multiple emissions scenarios in an output request. After one request is finished, return to this step to request additional scenarios. For Madison, ME, all available models and model runs were chosen for both requests of RCP4.5 and RCP Click on the third tab at the top of the form, Page 3: Analysis, Format, & Notification 10. Analysis (Step 3.7) 1. Select No Analysis (Extracting Time Series only) 3

4 11. Output Format (Step 3.8) 1. Select ASCII text, comma-delimited (csv.) 12. Notification when Processing is Complete (Step 3.9) 1. Enter the address where it would be helpful to receive a notification when the processing is complete. 13. Usage Information (Step 3.10) 1. Select the appropriate Entity, Application, and Sector(s). 14. Submit 1. When complete, scroll up the page to make sure all boxes for steps are colored green. If a box is white, click on that box, return to the appropriate step in these instructions, and fill in the required information. 2. Once all information is entered, click on Submit Request at the top left corner of the form. A Summary of Requested Files will appear. Select Submit to send the request. It may take up to several hours to receive the requested data. 15. When the data are available, a link to the request will be sent in an (one per emissions scenario.) Open the message and click on the link provided. 16. The link brings up a webpage with links for downloading the requested data. Click on 1_8obs.zip to download the observed data and bcca5.zip to download model output. Note that this is the last step that needs to be followed in the FHWA pdf guide. This analysis does not require the FHWA CMIP tool. Proceed with the next steps below. 17. Once the files are received, create two folders somewhere on your computer and include in the folder name the Location (first three letters, all caps) and emissions 4

5 scenario chosen. After unzipping correct files, save them to corresponding folders. Each folder should have two folders inside called 1_8obs and bcca5. These contain observed data and model output, respectively. 18. Renaming files - this is where adhering to naming conventions is vital. The contents of both folders will look the same, but different files are needed from each. Inside each 1_8obs folder find: tasmax.csv and tasmin.csv and in each bcca5 folder find: COLS_tasmax.txt, tasmax.csv, and tasmin.csv (A total of 5 files for each emissions scenario.) 5

6 Rename the files starting with the Location (first three letters, all caps) and emissions scenario. See the following examples for observed (OBS) and models (MOD) in Madison, ME with RCP 8.5. a. COLS_tasmax.txt à MAD_RCP8.5_List.txt b. tasmax.csv à MAD_RCP8.5_MODTmax.csv MAD_RCP8.5_OBSTmax.csv c. tasmin.csv à MAD_RCP8.5_MODTmin.csv MAD_RCP8.5_OBSTmin.csv 19. Save each renamed file in a newly created folder on the computer called Model 158. This folder will be used for storing inputs and output during freeze-thaw R analysis. The files in this folder are now named in a consistent and distinct manner, which allows them to be saved together in one folder. Station Data and Climate Model Output 1. Station data used for this project are statistically downscaled global climate model output for the station nearest the location being analyzed. This will need to be produced by someone with expertise in statistical downscaling. For this project, Dr. Anne Stoner, TTU provided the required files. 2. Each climate variable should include both observations and model output together in a station file, as well as headers with model names. Rename files as it was done for Madison, ME with RCP 8.5. a. MAD_RCP8.5_STNTmin b. MAD_RCP8.5_STNTmax 3. If files are from a location other than Madison, ME, check which models are contained in the station files. Open up STN_Preprocess.R, saved to the Model 158 folder in the set of MODEL 158 FOLDER PREPARATION instructions below, and make sure that these lines: colnames(modmin) <- c("year","month","day","m4","m6","m7","m0","m11","m12","m16","m17"," M19") colnames(modmax) <- c("year","month","day","m4","m6","m7","m0","m11","m12","m16","m17"," M19") Do in fact show the correct names for the station file headers. This was done for Madison, ME by looking at the MAD_RCP4.5.txt file output after running all of these 6

7 instructions for the Bureau of Reclamation files. The same M# which corresponds to model name must be consistent. (Ex. "ccsm4.1.rcp85" "MAD_RCP8.5_M4.csv" is an association made for RCP8.5 in Bureau of Reclamation files. The"ccsm4.1.rcp85" model was found to be a common model between both sources of output, so when it appeared in station files it was assigned M4 as a name.) Ensure that all other model names match up with one Bureau of Reclamation.txt file of either emission scenario, and that the number of M# names equals the number of models in the station files. If they do not, add correct names to this function and File à Save. Also note which emissions scenario is used as the reference. 7

8 PRE-PROCESSING These steps will ensure that all the files needed to perform the freeze-thaw R analysis are contained in the Model 158 folder. 1. Save the following R functions and scripts in the Model 158 folder: BR_Preprocess_MOD.R BR_Preprocess_OBS.R STN_Preprocess.R M158_Ref_Temp.R M158_Setup.R M158_Calc.R M158_DailyPlot.R M158_Summary.R M158_SubAnnualPlot.R M158_AnnualPlot.R M158_Source.R M158_Names.R M158_FreezeThaw.R 2. Create a.csv file with site-specific parameters and save to the Model 158 folder. The file must have the naming convention: Location_Site.csv. Madison, ME for example is MAD_Site.csv File fields for Location_Site.csv must be: Layer= Either 1,2, or 3 depending on where frost or thaw is occurring d= thickness of the surface asphalt layer (ft) nf= n-factor for freezing nt= n-factor for thawing k= thermal conductivity (BTU/(ft*day* F)) c= volumetric heat capacity (BTU/(ft 3 * F)) L= volumetric latent heat of fusion (BTU/ft 3 ) t= annual length of time below freezing (days) Vo= difference between the mean annual temperature below the ground surface and the freezing temperature ( F) Mf= Multiplier for Frost Depth Computation Mt= Multiplier for Thaw Depth Computation a= Constant (in.) 8

9 b= Constant (in.) CF= Frost depth coefficient CT= Thaw depth coefficient Startday= Start of Winter Year, Julian Day (Ex. Oct.1) Endday= End of Winter Year, Julian Day (Ex. Jun.1) 3. Double-check that every item is in the Model 158 folder. For one location and two emissions scenarios (Ex. MAD_RCP4.5 & 8.5) there should be: 2.txt and 12.csv files obtained through data collection, 13 R files, and 1 site.csv file. Sample Model 158 Folder Contents: 9

10 10

11 FREEZE-THAW R ANALYSIS 1. Make sure that both R and RStudio are installed on the computer and that the versions are correct for the computer s operating system. Both downloads are needed but the analysis will happen inside RStudio. To install R: To install RStudio: 2. Open RStudio. Go to File à Open File and open M158_FreezeThaw.R, previously saved in the Model 158 folder. 3. At the top of the file, beneath the green text, otherwise known as comments, there is a line that looks like: setwd("c:/users/jill/downloads/files for R/Model158") It is the first non-commented line and it sets the working directory. A working directory is the computer s path that designates where inputs can be found and where outputs are stored. This is an example directory from an ICNet computer so it will need to be set again for each different user. If you know the path where you have stored the files, replace ( C /Users/jill/Downloads/Files for R/Model158 ) with your computer s path. If you are not certain what to set for the path, you can use R to help you determine the path. To do this, go to the pull-down menus Session à Set Working Directory à Choose Working Directory and select wherever the Model 158 folder is saved. The path that was taken to get to this folder will appear in the R Console: the window at the bottom of the RStudio interface. The Console is different from an R script or function like M158_FreezeThaw.R because it is not editable like a document. Its purpose is for quick calculations, tracking progress during runs, and displaying errors. When the new working directory appears in the Console, copy and paste it to replace the old working directory. Every time a new R session is started, the working directory must be set either by following this procedure or by running the setwd line. 11

12 4. Highlight and run the next line by clicking Run in the top right corner of the script window: source("m158_source.r") If this results in an error displayed in the Console claiming there is a package not found, type: install.packages( ) in the Console with whichever package name it displays inside the quotes. Press Enter on the keyboard. If R asks whether to use a desired personal library, click yes. 5. Highlight and run the following line: Detail <- if(interactive()) Choose() In the R Console at the bottom of the screen, it will display a question prompt asking which location is being analyzed. Type the answer: MAD in the console and press Enter on the keyboard. R may try to autocorrect MAD to mad, one of its built-in functions. If this occurs, click in the Console to ignore the suggestion and then press Enter. 12

13 The next prompt asks which emissions scenario is being looked at. Choose either RCP4.5 or RCP8.5, type it in the Console, and press Enter. 6. Run every line below this line: Detail <- if(interactive()) Choose() This will run all model run and observed files for the chosen emissions scenario, Namelist, through the entire freeze-thaw Model 158 analysis. Be patient. This step may take around 7 minutes per model. The stop sign icon in the Console means that the code being run is in progress. Do not interrupt the model when it is running. 7. Open the Model 158 folder on the computer during the process and sort the viewing order by Date Modified. This is a good way to check that the functions are working and that outputs are being stored with correct naming conventions. If problems occur and this process is run multiple times, it is important to know that R cannot output a particular file 13

14 if a file of the same name is open. Make sure all.csv and.txt files are closed if the intention is to write over them. 8. After running this process with Namelist, all daily and annual output files for 1 location and 1 emissions scenario, based on input Bureau of Reclamation and Station files, should be stored. Step 6 will result in all daily and annual.csv files being present in the folder. Output for each model run could look like this in Step 8: 9. If daily plots are desired, open M158_Source.R and uncomment the line: #M158_DailyPlot(DailyCalc,Site,PlotName) By deleting the # sign before running the section, daily plots will be produced for all models in the List being run. This results in many plots, so unless necessary, leave this line commented out. Repeat Steps 4-7 to save this change and output plots. 10. If problems are occurring when all the files are run at once or daily plots are only desired for a particular list of models, uncomment lines defining List0 through List9. Then repeat Step 6, replacing List <- List0 with every defined list and then running (Ex. List <-List1) This course of action will produce the same results as Step 6, but it will instead be performing calculations for a few model files at a time, allowing you to determine which model files are causing a problem during the process. 14

15 Note: common problems with model files include: incorrect file names or file extensions and missing data. It is good practice to also monitor the file sizes of inputs and outputs, so that if a file looks out of the ordinary, you can open it to check that all expected data is present. 15

16 11. To run this process for other locations and emissions scenarios, all variables must be deleted to avoid incorrect or unwanted results. To do this, find the Environment tab in the top right window in the RStudio interface. Click the yellow broom icon to clear objects from the workspace. Refer back to Step 5 in R ANALYSIS to run this process for other combinations of locations and emissions scenarios. Do also clear objects from the workspace before attempting creation of annual plots. 16

17 DISPLAYING RESULTS: R ANNUAL PLOTS 1. To produce annual plots for a single emissions scenario, open M158_AnnualPlot.R 2. Set working directory for this script as was done for M158_FreezeThaw.R in Step 3 of FREEZE-THAW R ANALYSIS 3. Run the two source lines: 4. Run the next line and answer the same questions as in Step 5 of FREEZE-THAW R ANALYSIS 5. Run the two lines below this line: 6. Set the ModelNames and MN variables to those that should be displayed on the plots (ModelNames) and corresponding names (MN) to read in the annual.csv files. For RCP 4.5 Madison, ME s names should appear as follows: If, for another, site, actual model names should be displayed on plots, change the names in ModelNames to correspond to the file names. (Ex. ModelName<- ccsm4.1.rcp85 when MN<- M4 ) 7. If working with a site other than Madison, ME, the following customization is available to make plots more visually meaningful a. Set plot titles: Wherever T is defined, it can be changed for each annual metric by highlighting and running to replace T s previously held string value b. Set flag values: If data is missing or unrealistic, V can be changed for each annual metric to flag all these values with the same, recognizable value. 17

18 c. Set the maximum value of y-axis density scales in histograms and PDF s: If plots are not easily compared due to varying y-axis scales, MD can be changed to a maximum value found across all plots, ensuring a uniform scale d. Set the correct labels for units on y-axis scale: L1 and L2 are set to be Date and Miller Day, though they are the same values for annual metrics not measured by date 8. Highlight and run every line below the lines defining Location and Emission to produce all annual plots for 1 emissions scenario. That means these lines: 18

19 All the way until the very last lines: 9. Refer back to Step 4 of FREEZE-THAW R ANNUAL PLOTS to produce plots for other locations and emissions scenarios 19