Instructions to download Downscaled CMIP3 and CMIP5 Climate and Hydrology Projections for use in the Merced River basin Go to the Downscaled CMIP3 and CMIP5 Climate and Hydrology Projections website. 1. See the Welcome tab for instructions on how to acknowledge/cite the data sets used. Also, the email with the link to the requested data presents recommendations on how to cite the data sets and related publications. 2. The About/Climate tab provides information about the data sets available. According to my SWAT needs, I need BCCA data because it provides precipitation (mm), minimum surface air temperature (deg C), maximum surface air temperature (deg C) and a missing value flag (1E+20). According to Darren Ficklin, missing values mostly occur in the very low spots near the ocean. The CMIP3 coverage goes from: 1961 2000, 2046 2065, 2081 2100 The CMIP5 coverage goes from 1950 2099 Daily resolution. 3. Tutorials tab: Focusing on the BCCA Climate tutorial, this tab provides an example of data analysis for CMIP3 projections. 4. Defining the area of interest using the Projections: Subset Request tab Page 1: Temporal & Spatial Extent: i. Time step and period: SWAT requires daily inputs. The period of interest varies depending on the objective. There is only data from Jan/1950 through Dec/1999 for observed data; projections go all the way through 2099. Since we will be working on calibration and validation of the Merced River model, we select the Jan/1950 through Jan/2000. ii. Domain: either works for the Merced River however, the NLDAS expands to other areas outside the US and then may be preferred on certain occasions. iii. Spatial extent selection method: we use rectangular area. For this, click on one of the defined corners of the area of interest and then drag with the mouse until enclosing the entire area.
Page 2: Products, variables, projections. We request the BCCAv2 CMIP5 Climate daily; 1/8 degree. We won t select anything in step 2.6 (Emissions Scenarios, Climate Models and Runs) since we are going to deal for now with observed data for the calibration and validation of the model.
Page 3: Analysis, Format, & Notification. Select No analysis because we only want the time series of observed data. The format will be provided in NetCDF (will need to deal with this later). Finally, hit Submit Request Go to your email and click on the provided link to download the files. The 1_8obs folder contains the extractions of precipitation, surface temp max and surface temp min, as well as other metadata files for the selected area of interest.
Once the data has been received, notice that the files are.nc. Darren Ficklin shared with us an R script to extract downscaled GCM data into SWAT format. To use this R script, you need to install the ncdf4 package that can be downloaded from here (make sure to add the citation to the paper referenced in Darren s website). Install the ncdf4 package. Open and R console, go to the Packages menu and select Install package(s) from local zip files. The following message should appear: Within R make sure that the working directory is the same where the extraction files are located: > setwd("d:/arcswat/climate_1_8obs.tar/1_8obs") > getwd() [1] "D:/ArcSwat/Climate_1_8obs.tar/1_8obs" Modify the R script by changing the headername with the starting date of your data set, the latitudevarname < 'latitude' to 'lat' and the longitudevarname < 'longitude' to 'lon' in lines 17, 18 and 54 and 55 (this change may not be necessary for all cases but it was for our case). The code should run successfully and will create files of precipitation and temperature for the coordinates given in the file name.
The next step consists of reading the coordinates of each of the files to define the location of the weather stations and then continue to create the stations file that SWAT is looking for. The Reading_pcp_files.r and Reading_tmp_files.r within the Climate_1_8obs.tar/R_code folder are used to read the titles of all the TMP and PCP files and construct the required stations tables that will be called at this point Merced_PCP.txt and Merced_TMP.txt. Assigning an elevation attribute to the station tables. Start by importing x,y data to ArcGIS (i.e., a file containing the location of the stations which is in Geographic Coordinate System/World/WGS84). This events table needs to be transformed to a feature element called Stations_Grid.shp and later converted to the coordinate system of the project (GGS_North_American_1983) using [Data Management Tools / Projections and Transformations / Feature / Project. File name: Stations_NAD1983 ]. Coordinate system is: Projected / UTM / NAD 1983 / NAD 1983 UTM Zone 10N Next, in a new ArcGIS project (project name: Stations ), add the DEM, the masking file, and the Stations_NAD1983 to start thinking about the strategy to assign the elevation property to the stations. The first thing to notice is that some of the points of the Stations_NAD1983 file are outside of the DEM boundary. The user needs to identify those files and erase them from the stations lists (precipitation and temperature files). For the Merced River case, we need to get rid of the northern most row (lat 38.0625) and the two eastern most and the one western most points of each consecutive latitude. After doing this, go back and re run the r scripts ( Reading_pcp_files.r and Reading_tmp_files.r ) so the station files have the adequate ID and we only consider the points that are within the area of the DEM. The figure below shows the downscaled climate station points overlaid on the DEM after I removed the points that did not fall inside the DEM area. Next, we proceed to define a strategy to obtain elevation (see the ObtainingElevations folder) for those points. ArcGIS has the Extract Values to Points tool within the [Spatial Analyst Tools / Extraction]. The input point features is the Stations_NAD1983.shp points file, the Input Raster is the DEM. The output point features is called Stations_final.shp. First, check the Interpolate values at the
point locations option (the value of the cell will be calculated from the adjacent cells with valid values using bilinear interpolation). The Stations_final_actual.shp will have the direct DEM elevation value assigned. There were no significant differences between the two data sets. Either could be used. We decided to use the Stations_final.shp (the interpolated value). Next, proceed to export the data. Output table name: Stations_PCP.txt. From this file, remove the first column (FID_), and rename RASTERVALU to ELEVATION To obtain the Stations_TMP.txt file, make a copy of Stations_PCP.txt, rename it as Stations_TMP.txt and change the file names inside to _TMP (using the replace tool). All the files need to be copied to the ArcSWAT project folder