diff --git a/03_run_forecast.R b/03_run_forecast.R
index a76f378..38302b3 100644
--- a/03_run_forecast.R
+++ b/03_run_forecast.R
@@ -56,4 +56,6 @@ run_forecast <- function(model,met_forecast,site_data){
     select(datetime, reference_datetime, site_id, variable, parameter, prediction)
   
   return(forecast)
-}
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+}
+
+#blahblahblah
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diff --git a/Main.R b/Main.R
new file mode 100644
index 0000000..9b6087b
--- /dev/null
+++ b/Main.R
@@ -0,0 +1,56 @@
+### Aquatic Forecast Workflow ###
+# devtools::install_github("eco4cast/neon4cast")
+library(tidyverse)
+library(neon4cast)
+library(lubridate)
+#install.packages("rMR")
+library(rMR)
+
+forecast_date <- Sys.Date()
+noaa_date <- Sys.Date() - days(1)  #Need to use yesterday's NOAA forecast because today's is not available yet
+
+#Step 0: Define team name and team members 
+team_info <- list(team_name = "air2waterSat_MCD",
+                  team_list = list(list(individualName = list(givenName = "Mike", 
+                                                              surName = "Dietze"),
+                                        organizationName = "Boston University",
+                                        electronicMailAddress = "dietze@bu.edu"))
+)
+
+## Load required functions
+if(file.exists("01_download_data.R"))      source("01_download_data.R")
+if(file.exists("02_calibrate_forecast.R")) source("02_calibrate_forecast.R")
+if(file.exists("03_run_forecast.R"))       source("03_run_forecast.R")
+if(file.exists("04_submit_forecast.R"))    source("04_submit_forecast.R")
+
+### Step 1: Download Required Data
+target     <- download_targets()       ## Y variables
+site_data  <- download_site_meta()
+target     <- merge_met_past(target)   ## append met data (X) into target file
+met_future <- download_met_forecast(forecast_date) ## Weather forecast (future X)
+
+## visual check of data
+ggplot(target, aes(x = temperature, y = air_temperature)) +
+  geom_point() +
+  labs(x = "NEON water temperature (C)", y = "NOAA air temperature (C)") +
+  facet_wrap(~site_id)
+
+met_future %>% 
+  ggplot(aes(x = datetime, y = air_temperature, group = parameter)) +
+  geom_line() +
+  facet_grid(~site_id, scale ="free")
+
+### Step 2: Calibrate forecast model
+model <- calibrate_forecast(target)
+
+### Step 3: Make a forecast into the future
+forecast <- run_forecast(model,met_future,site_data)
+
+#Visualize forecast.  Is it reasonable?
+forecast %>% 
+  ggplot(aes(x = datetime, y = prediction, group = parameter)) +
+  geom_line() +
+  facet_grid(variable~site_id, scale ="free")
+
+### Step 4: Save and submit forecast and metadata
+submit_forecast(forecast,team_info,submit=FALSE)
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