I have two datasets. The first one shows information about multiple weather phenomena in Brazil measured by weather stations in the country. I also have information regarding the latitude and longitude of these stations, and the weather data is provided by year.
id_estacao ano precipitacao_total pressao_atm_max pressao_atm_min
1 A001 2016 0.12988728 888.0399 887.5521
2 A002 2016 0.14282787 932.8559 932.3215
3 A003 2016 0.12486339 930.6114 930.0861
4 A009 2016 0.07696277 979.3086 978.7480
5 A010 2016 0.11548640 980.2251 979.6578
6 A011 2016 0.13886103 958.5196 957.9678
radiacao_global temperatura_max temperatura_min umidade_rel_max
1 1508.024 22.77794 21.34106 65.52186
2 1419.644 24.90139 23.40798 66.28074
3 1460.937 24.00484 22.46128 68.25395
4 1440.643 29.22710 27.79419 61.87001
5 1540.398 27.52555 25.87737 63.64414
6 1471.004 24.95090 23.36305 66.69974
umidade_rel_min vento_velocidade id_municipio estacao latitude
1 59.04111 2.3430377 5300108 Brasilia -15.78944
2 59.56990 1.2416667 5208707 Goiania -16.64284
3 59.71499 1.6017190 5213806 Morrinhos -17.74507
4 55.21366 1.5202973 1721000 Palmas -10.19074
5 57.01889 0.9295148 1716208 Parana -12.61500
6 60.26358 1.7454093 5220405 Sao Simao -18.96914
longitude
1 -47.92583
2 -49.22022
3 -49.10170
4 -48.30181
5 -47.87194
6 -50.63345
Moreover, I have information about the location of the Brazilian municipalities (cities).
id_municipio latitude longitude
1 1100015 -11.92 -61.99
2 1100023 -9.91 -63.04
3 1100031 -13.49 -60.54
4 1100049 -11.43 -61.44
5 1100056 -13.18 -60.81
6 1100064 -13.11 -60.54
I want to use interpolation to predict the weather phenomena in these cities using the information provided in the first dataset. I have been working with the package "fields", which uses this function:
# Kriging of the rainfall data by station
fit = Krig(x,precip[,d])
# Predict the value on the unit
pred<-predict(fit,Y)
It basically makes a loop with d-days (in this case, years). precip[,d] is the precipitation variable (in this case, all the weather variables) on day d, and x is the latitude and longitude of the station. This should provide a fit which is the output of krig and Y (the latitude and longitude of the municipalities).
However, I have been struggling to make this function fit my data. I would like to know if someone could help me.
