The goal of GrapeWeatheR is to provide analysis of Environment Canada Climate Data for grape growers and agriculture purposes.
We need to have weather data downloaded to analyze. We’ll download data from Point Pelee for the last few years:
pelee_data<-weathercan::weather_dl(27533, interval = 'day', start = '2010-01-01')
With the data at hand, we can calculate a few climatological indecies. Winkler, Huglin and Biologically Effective Degree Day (BEDD) indecies are various ways of determining the suitability of an area or expecting the type of grapes that may be more suitable for a location. In addition, more annual indices are calculated, see Ramos et. al (2008).
annual_pelee <- calculate_annual_indicies(pelee_data)
annual_pelee[,c("year", "GST_region", "WI_region", "HI_region", "BEDD_region")]
#> # A tibble: 10 x 5
#> year GST_region WI_region HI_region BEDD_region
#> <int> <chr> <chr> <chr> <chr>
#> 1 2010 Intermediate Region II Temperate Temperate
#> 2 2011 Warm Region II Temperate Temperate
#> 3 2012 Warm Region I Very Cool Warm Temperate
#> 4 2013 Warm Too Cool Too Cool Warm Temperate
#> 5 2014 Intermediate Region I Cool Temperate
#> 6 2015 Intermediate Region II Temperate Temperate
#> 7 2016 Warm Region II Temperate Temperate
#> 8 2017 Intermediate Region II Cool Temperate
#> 9 2018 Intermediate Region II Temperate Temperate
#> 10 2019 Intermediate Region I Very Cool Too Cool
We can see that the past few years of BEDD indicies have shown the Pelee region to be Temperate, Temperate, Warm Temperate, Warm Temperate, Temperate, Temperate, Temperate, Temperate, Temperate, Too Cool.
We can plot some annualized results as well.
plot_index_history(pelee_data, index = 'GST')
Or, we can show the daily progression in degree growing days:
plot_index_progress(pelee_data, "Huglin")
Precipitation also matters for viticulture. GrapeWeatheR
can evaluate
and plot precipitation metrics as well. We’ll use Ottawa data, as Point
Pelee has limited precipitation data available. We can plot
precipitatoin on a daily, weekly, monthly, or annual
basis.
ottawa_data<-weathercan::weather_dl(49568, start = '2010-01-01', interval = 'day')
plot_precip_history(ottawa_data, interval = 'month', trim_years = 10)
As with the indecies, you can also plot ‘progression’ of precipitation accumilation for a region.
plot_precip_progress(ottawa_data)
Add the following code to your website.
For more information on customizing the embed code, read Embedding Snippets.