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The CDSimX package provides an advanced framework for climate simulation, forecasting, visualization, validation, and climate data export in R.
The package supports:
synthetic weather station generation
stochastic climate simulation
machine learning forecasting
climate validation
NetCDF and CSV export
visualization of climate variables
climate dependence modelling
CDSimX is useful for:
climate research
hydrological modelling
machine learning experiments
educational demonstrations
sensitivity analysis
simulation studies
The stations can be created either by: loading from a CSV file, accepting an existing data frame, or auto-generating synthetic stations in a bounding box. We begin by generating synthetic climate stations.
stations <- create_stations(
n = 3,
seed = 123
)
#> Generating synthetic station network...
#> Generated 3 synthetic stations within bounding box.
#> Deriving climate-aware station attributes...
stations
#> Station LON LAT ELEV CLIMATE_ZONE COASTAL_INDEX TEMP_BASE
#> 1 Station_1 -2.0621124 10.681122 422.5 Savannah 0.932 27.17
#> 2 Station_2 0.4415257 11.083271 713.9 Savannah 1.000 26.27
#> 3 Station_3 -1.4551154 4.818895 441.1 Coastal 0.000 27.04
#> RAIN_REGIME
#> 1 Monomodal
#> 2 Monomodal
#> 3 BimodalEach station contains:
station identifier
longitude
latitude
elevation (if available)
CDSimX supports daily, monthly, and yearly temporal resolutions.
time_index <- generate_time_index(
start_date = "2019-01-01",
end_date = "2024-12-31",
frequency = "day"
)
#> Generated 2192 time steps at daily resolution.
head(time_index)
#> START_DATE END_DATE DATE Year Month Day DOY Week Quarter Season
#> 1 2019-01-01 2019-01-01 2019-01-01 2019 1 1 1 1 1 Dry
#> 2 2019-01-02 2019-01-02 2019-01-02 2019 1 2 2 1 1 Dry
#> 3 2019-01-03 2019-01-03 2019-01-03 2019 1 3 3 1 1 Dry
#> 4 2019-01-04 2019-01-04 2019-01-04 2019 1 4 4 1 1 Dry
#> 5 2019-01-05 2019-01-05 2019-01-05 2019 1 5 5 1 1 Dry
#> 6 2019-01-06 2019-01-06 2019-01-06 2019 1 6 6 1 1 Dry
#> Frequency
#> 1 daily
#> 2 daily
#> 3 daily
#> 4 daily
#> 5 daily
#> 6 dailyClimate variables can now be simulated using the generated stations and time index.
climate <- simulate_climate(
stations = stations,
time_index = time_index,
seed = 123
)
#> Temperature simulation complete for 3 stations.
#> Rainfall simulation complete for 3 stations.
#> Relative humidity simulation complete for 3 stations.
#> Dew point simulation complete for 3 stations.
#> Wind speed simulation complete for 3 stations.
#> Wind direction simulation complete for 3 stations.
#> Solar radiation simulation complete for 3 stations.
#> Evapotranspiration simulation complete for 3 stations.
#> Integrated climate simulation complete for 3 stations.
head(climate)
#> Station DATE LON LAT ELEV Year Month Season Tmin Tmax
#> 1 Station_1 2019-01-01 -2.062112 10.68112 422.5 2019 1 Dry 20.31 28.03
#> 2 Station_1 2019-01-02 -2.062112 10.68112 422.5 2019 1 Dry 20.21 28.64
#> 3 Station_1 2019-01-03 -2.062112 10.68112 422.5 2019 1 Dry 21.91 29.66
#> 4 Station_1 2019-01-04 -2.062112 10.68112 422.5 2019 1 Dry 21.96 30.36
#> 5 Station_1 2019-01-05 -2.062112 10.68112 422.5 2019 1 Dry 22.07 30.95
#> 6 Station_1 2019-01-06 -2.062112 10.68112 422.5 2019 1 Dry 23.76 32.02
#> Avg.Temp DTR CLIMATE_ZONE COASTAL_INDEX Rain_Days Rainfall Wet_Day
#> 1 24.17 7.72 Savannah 0.932 0 0.00 0
#> 2 24.42 8.43 Savannah 0.932 0 0.00 0
#> 3 25.78 7.75 Savannah 0.932 0 0.00 0
#> 4 26.16 8.41 Savannah 0.932 1 0.84 1
#> 5 26.51 8.88 Savannah 0.932 0 0.00 0
#> 6 27.89 8.26 Savannah 0.932 0 0.00 0
#> Extreme_Event Rain_Anomaly RH Humidity_Anomaly DewPoint
#> 1 0 -1.08 53.05 -5.07 13.35
#> 2 0 -1.08 52.75 -5.37 14.20
#> 3 0 -1.08 57.88 -0.23 16.23
#> 4 0 -0.24 58.04 -0.07 17.29
#> 5 0 -1.08 57.92 -0.19 18.05
#> 6 0 -1.08 62.81 4.70 20.03
#> Dewpoint_Depression WindSpeed Extreme_Wind Wind_Anomaly WindDirection
#> 1 10.82 3.45 0 -3.87 148.59
#> 2 10.22 5.44 0 -1.87 140.34
#> 3 9.55 5.98 0 -1.34 240.74
#> 4 8.87 7.78 0 0.46 234.74
#> 5 8.46 9.15 0 1.84 231.49
#> 6 7.86 9.67 0 2.35 276.37
#> WindSector Prevailing_Direction Direction_Variability Extreme_Shift Wind_u
#> 1 SE 180 60 0 -1.80
#> 2 SE 180 60 0 -3.47
#> 3 SW 180 60 0 5.22
#> 4 SW 180 30 0 6.35
#> 5 SW 180 30 0 7.16
#> 6 W 180 30 0 9.61
#> Wind_v Solar_Radiation Clear_Sky_Radiation Cloud_Factor Sunshine_Fraction
#> 1 2.94 16.31 21.04 0.85 0.8739915
#> 2 4.19 21.47 21.07 0.93 0.9212083
#> 3 2.92 18.10 21.09 0.87 0.8337447
#> 4 4.49 17.12 21.12 0.93 0.8956804
#> 5 5.70 22.41 21.15 0.94 0.9298279
#> 6 -1.07 16.35 21.18 0.81 0.8450011
#> Radiation_Anomaly Atmospheric_Pressure VPD ET0 Dryness_Index Dryness_Class
#> 1 -3.08 96.4 1.42 5.88 0.82 Very Dry
#> 2 2.08 96.4 1.45 6.78 0.64 Very Dry
#> 3 -1.29 96.4 1.40 7.05 0.73 Very Dry
#> 4 -2.27 96.4 1.42 6.77 0.79 Very Dry
#> 5 3.02 96.4 1.46 7.58 0.62 Very Dry
#> 6 -3.04 96.4 1.40 7.48 0.81 Very Dry
#> ET_Anomaly
#> 1 -1.20
#> 2 -0.30
#> 3 -0.03
#> 4 -0.31
#> 5 0.50
#> 6 0.40The simulated dataset may include:
Tmin
Tmax
Rainfall
RH
WindSpeed
Solar_Radiation
ET0
DewPoint
CDSimX includes customizable visualization functions.
plot_station_timeseries(
climate,
station = "Station_1",
var = "Tmax"
)
#> `geom_smooth()` using formula = 'y ~ x'
Users may customize:
colors
themes
smoothing
labels
seasonal highlighting
CDSimX supports several machine learning forecasting approaches.
Available methods include:
Random Forest
Linear Regression
GBM
ARIMA
XGBoost
Neural Networks
forecast_result <- forecasting_ml(
climate_data = climate,
target = "Rainfall",
forecast_horizon = 12,
method = "rf"
)
#> Machine learning forecasting complete using rf method.
forecast_result$model_performance
#> Method Target RMSE MAE Correlation
#> 1 rf Rainfall 44.88 35 0.39Forecasted values:
head(forecast_result$forecast_data)
#> DATE Forecast
#> 1 2025-01-31 30.03
#> 2 2025-03-03 27.36
#> 3 2025-03-31 39.77
#> 4 2025-05-01 16.97
#> 5 2025-05-31 38.12
#> 6 2025-07-01 55.73CDSimX includes climate validation tools for checking realism and statistical consistency.
validation <- validate_climate(climate)
#> Climate dataset validation complete.
validation
#> $summary_statistics
#> Variable Mean SD Min Max Skewness
#> 1 LON -1.03 1.07 -2.06 0.44 0.54
#> 2 LAT 8.86 2.86 4.82 11.08 -0.70
#> 3 ELEV 525.83 133.21 422.50 713.90 0.70
#> 4 Year 2021.50 1.71 2019.00 2024.00 0.00
#> 5 Month 6.52 3.45 1.00 12.00 -0.01
#> 6 Tmin 20.36 3.55 10.03 30.19 -0.23
#> 7 Tmax 26.90 3.75 15.74 38.67 0.35
#> 8 Avg.Temp 23.63 3.46 13.60 34.36 0.10
#> 9 DTR 6.54 2.33 1.79 10.29 -0.64
#> 10 COASTAL_INDEX 0.64 0.46 0.00 1.00 -0.70
#> 11 Rain_Days 0.42 0.49 0.00 1.00 0.31
#> 12 Rainfall 21.69 37.45 0.00 429.86 2.36
#> 13 Wet_Day 0.42 0.49 0.00 1.00 0.31
#> 14 Extreme_Event 0.01 0.08 0.00 1.00 11.83
#> 15 Rain_Anomaly 0.00 32.88 -69.56 381.95 1.84
#> 16 RH 64.34 17.59 29.97 100.00 0.47
#> 17 Humidity_Anomaly 0.00 5.42 -19.15 19.99 -0.07
#> 18 DewPoint 16.03 6.36 -3.36 30.10 -0.33
#> 19 Dewpoint_Depression 7.60 4.14 0.00 17.23 -0.29
#> 20 WindSpeed 7.85 3.70 0.00 34.17 0.25
#> 21 Extreme_Wind 0.01 0.10 0.00 1.00 10.24
#> 22 Wind_Anomaly 0.00 2.89 -9.40 25.04 0.38
#> 23 WindDirection 187.24 78.26 0.21 359.89 -0.28
#> 24 Prevailing_Direction 195.00 21.21 180.00 225.00 0.71
#> 25 Direction_Variability 37.49 16.01 15.00 60.00 0.46
#> 26 Extreme_Shift 0.01 0.09 0.00 1.00 10.41
#> 27 Wind_u 2.46 6.14 -12.78 33.11 0.37
#> 28 Wind_v 3.10 4.68 -17.96 19.85 -0.62
#> 29 Solar_Radiation 20.99 2.48 12.61 29.50 0.04
#> 30 Clear_Sky_Radiation 24.55 1.59 20.90 26.83 -0.68
#> 31 Cloud_Factor 0.86 0.05 0.71 0.97 -0.08
#> 32 Sunshine_Fraction 0.85 0.06 0.64 1.00 -0.08
#> 33 Radiation_Anomaly 0.00 1.95 -6.91 6.27 0.01
#> 34 Atmospheric_Pressure 95.24 1.49 93.14 96.40 -0.70
#> 35 VPD 1.02 0.49 0.00 1.65 -0.75
#> 36 ET0 6.82 0.89 3.94 9.89 0.02
#> 37 Dryness_Index 0.47 0.22 0.00 0.98 -0.56
#> 38 ET_Anomaly 0.00 0.69 -2.66 2.64 0.01
#>
#> $missing_values
#> Variable Missing_Count Missing_Percent
#> Station Station 0 0
#> DATE DATE 0 0
#> LON LON 0 0
#> LAT LAT 0 0
#> ELEV ELEV 0 0
#> Year Year 0 0
#> Month Month 0 0
#> Season Season 0 0
#> Tmin Tmin 0 0
#> Tmax Tmax 0 0
#> Avg.Temp Avg.Temp 0 0
#> DTR DTR 0 0
#> CLIMATE_ZONE CLIMATE_ZONE 0 0
#> COASTAL_INDEX COASTAL_INDEX 0 0
#> Rain_Days Rain_Days 0 0
#> Rainfall Rainfall 0 0
#> Wet_Day Wet_Day 0 0
#> Extreme_Event Extreme_Event 0 0
#> Rain_Anomaly Rain_Anomaly 0 0
#> RH RH 0 0
#> Humidity_Anomaly Humidity_Anomaly 0 0
#> DewPoint DewPoint 0 0
#> Dewpoint_Depression Dewpoint_Depression 0 0
#> WindSpeed WindSpeed 0 0
#> Extreme_Wind Extreme_Wind 0 0
#> Wind_Anomaly Wind_Anomaly 0 0
#> WindDirection WindDirection 0 0
#> WindSector WindSector 0 0
#> Prevailing_Direction Prevailing_Direction 0 0
#> Direction_Variability Direction_Variability 0 0
#> Extreme_Shift Extreme_Shift 0 0
#> Wind_u Wind_u 0 0
#> Wind_v Wind_v 0 0
#> Solar_Radiation Solar_Radiation 0 0
#> Clear_Sky_Radiation Clear_Sky_Radiation 0 0
#> Cloud_Factor Cloud_Factor 0 0
#> Sunshine_Fraction Sunshine_Fraction 0 0
#> Radiation_Anomaly Radiation_Anomaly 0 0
#> Atmospheric_Pressure Atmospheric_Pressure 0 0
#> VPD VPD 0 0
#> ET0 ET0 0 0
#> Dryness_Index Dryness_Index 0 0
#> Dryness_Class Dryness_Class 0 0
#> ET_Anomaly ET_Anomaly 0 0
#>
#> $physical_checks
#> $physical_checks$Temperature_Inconsistency
#> [1] 0
#>
#> $physical_checks$RH_Out_Of_Bounds
#> [1] 0
#>
#> $physical_checks$Negative_Rainfall
#> [1] 0
#>
#> $physical_checks$Negative_WindSpeed
#> [1] 0
#>
#> $physical_checks$Invalid_WindDirection
#> [1] 0
#>
#> $physical_checks$Invalid_DewPoint
#> [1] 0
#>
#> $physical_checks$Invalid_SunshineFraction
#> [1] 0
#>
#> $physical_checks$Negative_ET0
#> [1] 0
#>
#>
#> $correlation_matrix
#> Tmin Tmax Avg.Temp Rainfall RH DewPoint WindSpeed
#> Tmin 1.00 0.80 0.95 -0.04 0.65 0.94 0.73
#> Tmax 0.80 1.00 0.95 -0.25 0.08 0.59 0.45
#> Avg.Temp 0.95 0.95 1.00 -0.15 0.38 0.80 0.61
#> Rainfall -0.04 -0.25 -0.15 1.00 0.28 0.10 0.11
#> RH 0.65 0.08 0.38 0.28 1.00 0.85 0.74
#> DewPoint 0.94 0.59 0.80 0.10 0.85 1.00 0.85
#> WindSpeed 0.73 0.45 0.61 0.11 0.74 0.85 1.00
#> Solar_Radiation 0.04 0.15 0.10 -0.19 -0.13 -0.03 -0.05
#> ET0 0.84 0.82 0.87 -0.13 0.40 0.75 0.73
#> Solar_Radiation ET0
#> Tmin 0.04 0.84
#> Tmax 0.15 0.82
#> Avg.Temp 0.10 0.87
#> Rainfall -0.19 -0.13
#> RH -0.13 0.40
#> DewPoint -0.03 0.75
#> WindSpeed -0.05 0.73
#> Solar_Radiation 1.00 0.37
#> ET0 0.37 1.00
#>
#> $seasonal_summary
#> Season Tmin Tmax Avg.Temp Rainfall RH DewPoint WindSpeed
#> 1 Dry 21.12 27.65 24.39 9.05 65.96 17.17 8.28
#> 2 Post-Wet 18.30 24.86 21.58 22.13 58.99 12.79 6.74
#> 3 Pre-Wet 22.83 29.37 26.10 15.98 70.55 19.91 9.36
#> 4 Wet 18.97 25.50 22.24 35.14 61.14 13.89 6.94
#> Solar_Radiation ET0
#> 1 19.83 6.82
#> 2 19.45 6.27
#> 3 22.48 7.46
#> 4 21.51 6.61
#>
#> $station_summary
#> Station Tmin Tmax Avg.Temp Rainfall RH DewPoint WindSpeed
#> 1 Station_1 21.00 29.37 25.19 11.60 55.31 15.49 6.42
#> 2 Station_2 18.36 26.28 22.32 13.59 51.17 11.64 6.72
#> 3 Station_3 21.72 25.05 23.38 39.89 86.55 20.96 10.40
#> Solar_Radiation ET0
#> 1 21.00 6.97
#> 2 21.67 6.66
#> 3 20.31 6.83
#>
#> $extreme_summary
#> Metric Value
#> 1 Extreme_Rainfall_Events 46
#> 2 Extreme_Wind_Events 61
#>
#> $validation_summary
#> Metric Value
#> 1 Mean_Tmin 20.36
#> 2 Mean_Tmax 26.90
#> 3 Mean_Temperature 23.63
#> 4 Mean_Rainfall 21.69
#> 5 Mean_RH 64.34
#> 6 Mean_WindSpeed 7.85
#> 7 Mean_SolarRadiation 20.99
#> 8 Mean_ET0 6.82Validation diagnostics may include:
physical constraint checks
variability assessment
correlations
temporal consistency
distributional diagnostics
These formats support interoperability with:
ncdf4
terra
stars
xarray
climate modelling workflows
CDSimX provides a modern climate simulation ecosystem for generating, forecasting, validating, visualizing, and exporting synthetic climate data.
The package is designed to support reproducible climate science, machine learning applications, and environmental modelling workflows.
These binaries (installable software) and packages are in development.
They may not be fully stable and should be used with caution. We make no claims about them.
Health stats visible at Monitor.