diff --git a/R/WindPowerDensity.R b/R/WindPowerDensity.R
index 5691bb55c052750f6bc2d9e7f2c887ad2962d963..357820999cb83f3c53bfdb08795d8265094026a9 100644
--- a/R/WindPowerDensity.R
+++ b/R/WindPowerDensity.R
@@ -34,8 +34,8 @@
#'wind$data <- array(rweibull(n = 100, shape = 2, scale = 6),
#' c(member = 10, lat = 2, lon = 5))
#'wind$coords <- list(lat = c(40, 41), lon = 1:5)
-#'variable <- list(Variable = list(varName = 'sfcWind',
-#' metadata = list(sfcWind = list(level = 'Surface'))))
+#'variable <- list(varName = 'sfcWind',
+#' metadata = list(sfcWind = list(level = 'Surface')))
#'wind$attrs <- list(Variable = variable, Datasets = 'synthetic',
#' when = Sys.time(), Dates = '1990-01-01 00:00:00')
#'class(wind) <- 's2dv_cube'
diff --git a/man/CST_WindCapacityFactor.Rd b/man/CST_WindCapacityFactor.Rd
index 9d9cfa4769401369d2aa3cfac3d9df2bcef5dd85..638f5b858ff97d9dcc7302bfda05c49a5b921959 100644
--- a/man/CST_WindCapacityFactor.Rd
+++ b/man/CST_WindCapacityFactor.Rd
@@ -62,8 +62,8 @@ wind <- NULL
wind$data <- array(rweibull(n = 100, shape = 2, scale = 6),
c(member = 10, lat = 2, lon = 5))
wind$coords <- list(lat = c(40, 41), lon = 1:5)
-variable <- list(Variable = list(varName = 'sfcWind',
- metadata = list(sfcWind = list(level = 'Surface'))))
+variable <- list(varName = 'sfcWind',
+ metadata = list(sfcWind = list(level = 'Surface')))
wind$attrs <- list(Variable = variable, Datasets = 'synthetic',
when = Sys.time(), Dates = '1990-01-01 00:00:00')
class(wind) <- 's2dv_cube'
diff --git a/man/CST_WindPowerDensity.Rd b/man/CST_WindPowerDensity.Rd
index 54390a00830ccadccac247807a4605f09eceef7f..c33bd8d99a3cb0f0bb37e1872e962f1878ab7674 100644
--- a/man/CST_WindPowerDensity.Rd
+++ b/man/CST_WindPowerDensity.Rd
@@ -55,8 +55,8 @@ wind <- NULL
wind$data <- array(rweibull(n = 100, shape = 2, scale = 6),
c(member = 10, lat = 2, lon = 5))
wind$coords <- list(lat = c(40, 41), lon = 1:5)
-variable <- list(Variable = list(varName = 'sfcWind',
- metadata = list(sfcWind = list(level = 'Surface'))))
+variable <- list(varName = 'sfcWind',
+ metadata = list(sfcWind = list(level = 'Surface')))
wind$attrs <- list(Variable = variable, Datasets = 'synthetic',
when = Sys.time(), Dates = '1990-01-01 00:00:00')
class(wind) <- 's2dv_cube'
diff --git a/vignettes/AgriculturalIndicators.Rmd b/vignettes/AgriculturalIndicators.Rmd
index ec14f58a0ef816c058344cc515cb61a7324744a9..3c9cf7d23a9b4fd68b8f819638c85f328bd7c761 100644
--- a/vignettes/AgriculturalIndicators.Rmd
+++ b/vignettes/AgriculturalIndicators.Rmd
@@ -167,7 +167,7 @@ PlotEquiMap(Bias[1, , ], lon = prlr_obs$coords$lon, lat = prlr_obs$coords$lat,
```
You will see the following maps of HarvestR bias in 2013.
-
+
In 2013, the ensemble-mean SEAS5 seasonal forecast of HarvestR is underestimated by up to 60 mm over Douro Valley region (the central four grid points).
@@ -267,7 +267,7 @@ PlotEquiMap(GST_Clim, lon = tas_obs$coords$lon, lat = tas_obs$coords$lat,
The ERA5 GST climatology is shown as below.
-
+
ERA5 GST ranges from 17-18.5°C over the Douro Valley region for the period from 2013-2016 as shown in the figure.
@@ -395,9 +395,9 @@ PlotEquiMap(SU35_exp_BC_Y2016,
You can see the figure as below.
-
-
-
+
+
+
As seen above, the bias-adjusted SU35 forecasts are much closer to the ERA5 results, although differences remain.
@@ -436,7 +436,7 @@ SU35_exp_Percentile <- TotalTimeExceedingThreshold(S5txP, threshold = obs_percen
Compute the same ensemble-mean SU35 **with percentile adjustment** in 2016 by running
```
-SU35_exp_per_Y2016 <- MeanDims(SU35_exp_Percentile[, 4, , ], 'member')
+SU35_exp_per_Y2016 <- MeanDims(SU35_exp_Percentile[4, , , ], 'member')
```
Plot the same map for comparison
@@ -454,8 +454,7 @@ PlotEquiMap(SU35_exp_per_Y2016,
bar_extra_margin = c(0, 0, 0, 0), units_scale = 2)
```
-
-
+
As seen in the figure above, applying the percentile adjustment seems to implicitly adjust certain extent of bias which was observed in the non-bias-adjusted SEAS5 forecast.
@@ -513,7 +512,7 @@ PlotEquiMap(GDD_Corr, lon = tas_obs$coords$lon, lat = tas_obs$coords$lat,
The map of correlation coefficient for the 2013-2016 period is shown as below.
-
+
The 2013-2016 correlation coefficients of the SEAS5 forecasts of GDD in reference with ERA5 reanalysis over Douro Valley range between 0.6 and 0.8.
@@ -584,7 +583,8 @@ PlotEquiMap(WSDI_FRPSS, lon = tasmax_obs$coords$lon, lat = tasmax_obs$coords$lat
The FRPSS map for 2013-2016 SEAS WSDI is shown as below.
-
+
+
As seen in the map, the FRPSS in the eastern part of Douro Valley falls in 0.6-0.9, which are good enough to be useful when compared to observational climatology.
diff --git a/vignettes/figures/GDD_SEAS5_Corr_Y13-16-1.png b/vignettes/Figures/GDD_SEAS5_Corr_Y13-16-1.png
similarity index 100%
rename from vignettes/figures/GDD_SEAS5_Corr_Y13-16-1.png
rename to vignettes/Figures/GDD_SEAS5_Corr_Y13-16-1.png
diff --git a/vignettes/figures/GST_ERA5_Climatology-1.png b/vignettes/Figures/GST_ERA5_Climatology-1.png
similarity index 100%
rename from vignettes/figures/GST_ERA5_Climatology-1.png
rename to vignettes/Figures/GST_ERA5_Climatology-1.png
diff --git a/vignettes/figures/HarvestR_Bias_2013-1.png b/vignettes/Figures/HarvestR_Bias_2013-1.png
similarity index 100%
rename from vignettes/figures/HarvestR_Bias_2013-1.png
rename to vignettes/Figures/HarvestR_Bias_2013-1.png
diff --git a/vignettes/figures/SU35_ERA5_Y2016-1.png b/vignettes/Figures/SU35_ERA5_Y2016-1.png
similarity index 100%
rename from vignettes/figures/SU35_ERA5_Y2016-1.png
rename to vignettes/Figures/SU35_ERA5_Y2016-1.png
diff --git a/vignettes/figures/SU35_Percentile_SEAS5_Y2016-1.png b/vignettes/Figures/SU35_Percentile_SEAS5_Y2016-1.png
similarity index 100%
rename from vignettes/figures/SU35_Percentile_SEAS5_Y2016-1.png
rename to vignettes/Figures/SU35_Percentile_SEAS5_Y2016-1.png
diff --git a/vignettes/figures/SU35_SEAS5_BC_Y2016-1.png b/vignettes/Figures/SU35_SEAS5_BC_Y2016-1.png
similarity index 100%
rename from vignettes/figures/SU35_SEAS5_BC_Y2016-1.png
rename to vignettes/Figures/SU35_SEAS5_BC_Y2016-1.png
diff --git a/vignettes/figures/SU35_SEAS5_Y2016-1.png b/vignettes/Figures/SU35_SEAS5_Y2016-1.png
similarity index 100%
rename from vignettes/figures/SU35_SEAS5_Y2016-1.png
rename to vignettes/Figures/SU35_SEAS5_Y2016-1.png
diff --git a/vignettes/figures/WCF_histogram.png b/vignettes/Figures/WCF_histogram.png
similarity index 100%
rename from vignettes/figures/WCF_histogram.png
rename to vignettes/Figures/WCF_histogram.png
diff --git a/vignettes/figures/WPD_histogram.png b/vignettes/Figures/WPD_histogram.png
similarity index 100%
rename from vignettes/figures/WPD_histogram.png
rename to vignettes/Figures/WPD_histogram.png
diff --git a/vignettes/figures/WSDI_SEAS5_FRPSS_Y13-16-1.png b/vignettes/Figures/WSDI_SEAS5_FRPSS_Y13-16-1.png
similarity index 100%
rename from vignettes/figures/WSDI_SEAS5_FRPSS_Y13-16-1.png
rename to vignettes/Figures/WSDI_SEAS5_FRPSS_Y13-16-1.png