Dear R users;
I have downloaded a grib file format (Met.grib) and I want to export its
data to excel file. Also I want to do some mathematic on some columns. But
I got error. I would be more than happy if anyone can help me to do this. I
have provided the codes and the Met.grib file in this email.
Sincerely yours
# Load the necessary libraries
> library(raster) # For reading GRIB files
> library(dplyr) # For data manipulation
> library(lubridate) # For date manipulation
> library(openxlsx) # For writing Excel files
# Specify the file paths
> grib_file_path <- "C:/Users/Omrab_Lab/Downloads/Met.grib"
> excel_file_path <- "C:/Users/Omrab_Lab/Downloads/Met_updated.xlsx"
# Open the GRIB file
> raster_data <- stack(grib_file_path)
# Check the names of the layers to identify which ones to extract
> layer_names <- names(raster_data)
> print(layer_names) # Prints
> # Extract layers based on layer names - adjust as necessary
> t2m <- raster_data[[grep("t2m", layer_names)]]
> d2m <- raster_data[[grep("d2m", layer_names)]]
> tcc <- raster_data[[grep("tcc", layer_names)]]
> valid_time <- raster_data[[grep("valid_time", layer_names)]]
> t2m
class : RasterStack
nlayers : 0
> # Check if the raster layers are loaded correctly
> if (is.null(t2m) || is.null(d2m) || is.null(tcc) || is.null(valid_time))
{
+ stop("One or more raster layers could not be loaded. Please check the
layer names.")
+ }
> # Convert raster values to vectors
> t2m_values <- values(t2m)
Error in dimnames(x) <- dn :
length of 'dimnames' [2] not equal to array extent
> d2m_values <- values(d2m)
Error in dimnames(x) <- dn :
length of 'dimnames' [2] not equal to array extent
> tcc_values <- values(tcc)
Error in dimnames(x) <- dn :
length of 'dimnames' [2] not equal to array extent
> valid_time_values <- values(valid_time)
Error in dimnames(x) <- dn :
length of 'dimnames' [2] not equal to array extent
# Check for NA values and dimensions
if (any(is.na(t2m_values)) || any(is.na(d2m_values)) || any(is.na(tcc_values))
|| any(is.na(valid_time_values))) {
warning("One or more layers contain NA values. These will be removed.")
}
# Create the data frame, ensuring no NA values are included
df <- data.frame(
t2m = t2m_values,
d2m = d2m_values,
tcc = tcc_values,
valid_time = valid_time_values,
stringsAsFactors = FALSE
)
# Remove rows with NA values
df <- na.omit(df)
# Convert temperatures from Kelvin to Celsius
df$t2m <- df$t2m - 273.15
df$d2m <- df$d2m - 273.15
# Calculate relative humidity
calculate_relative_humidity <- function(t2m, d2m) {
es <- 6.112 * exp((17.67 * t2m) / (t2m + 243.5))
e <- 6.112 * exp((17.67 * d2m) / (d2m + 243.5))
rh <- (e / es) * 100
return(rh)
}
df$RH <- calculate_relative_humidity(df$t2m, df$d2m)
# Convert valid_time from numeric to POSIXct assuming it's in seconds since
the epoch
df$valid_time <- as.POSIXct(df$valid_time, origin = "1970-01-01")
# Extract year, month, day, and hour from valid_time
df$Year <- year(df$valid_time)
df$Month <- month(df$valid_time)
df$Day <- day(df$valid_time)
df$Hour <- hour(df$valid_time)
# Select only the desired columns
df_selected <- df %>% select(Year, Month, Day, Hour, tcc, t2m, RH)
# Save the updated DataFrame to an Excel file
write.xlsx(df_selected, excel_file_path, row.names = FALSE)
--
Best Regards
Javad Bayat
M.Sc. Environment Engineering
Alternative Mail: bayat...@yahoo.com
[[alternative HTML version deleted]]
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