Summarises a get_weather output by environment and, optionally, by
user-defined time intervals such as phenological stages.
Usage
summaryWTH(
env.data,
id.names = NULL,
env.id = NULL,
days.id = NULL,
var.id = NULL,
statistic = NULL,
probs = NULL,
by.interval = FALSE,
time.window = NULL,
names.window = NULL,
verbose = TRUE
)Arguments
- env.data
data.frame. A
get_weatheroutput.- id.names
vector (character). Columns treated as identifiers.
- env.id
character. Environment-id column. Default
"env".- days.id
character. Column holding days from start. Default
"daysFromStart".- var.id
vector (character). Variables to summarise. Defaults to every non-identifier column.
- statistic
character. One of
"all","sum","mean","quantile".- probs
vector (numeric). Quantile probabilities. Default
c(0.25, 0.50, 0.75).- by.interval
boolean. Summarise within time intervals.
- time.window
vector (numeric). Interval breakpoints in days.
- names.window
vector (character). Interval names.
- verbose
boolean. If
TRUE(default) prints a progress banner.
Details
Quantiles are computed with stats::aggregate rather than the previous
nested foreach loops, which registered no parallel backend and therefore
ran sequentially while emitting a warning on every call.
Examples
# \donttest{
env.data <- get_weather(lat = -13.05, lon = -56.05)
#> ---------------------------------------------------------------
#> get_weather -- downloads daily weather from NASA POWER
#> Last updated at 09/27/2026
#> ---------------------------------------------------------------
#> start.day is NULL; matched as 2024-01-26
#> end.day is NULL; matched as 2024-02-25
#> ---------------------------------------------------------------
#> get_weather() - daily weather from NASA POWER
#> https://docs.ropensci.org/nasapower
#> ---------------------------------------------------------------
#> Start .............................. Thu Oct 22 18:35:09 2026
#> Environmental units ................ 1
#> Parallel ........................... [ ]
#> [1/1] env1 downloaded
#> Computing VPD ...................... [ x ]
#> Computing N, RTA ................... [ x ]
#> Computing n ........................ [ x ]
#> Computing TH1 ...................... [ x ]
#> Computing TH2 ...................... [ x ]
#> Computing PAR_TEMP ................. [ x ]
#> Environmental units downloaded ..... 1/1
#> Daily weather features ............. 25
#> Done ............................... Thu Oct 22 18:35:11 2026
#> Total time ......................... 1.08s
summaryWTH(env.data, env.id = "env", statistic = "mean")
#> ---------------------------------------------------------------
#> summaryWTH -- summarises weather by environment and interval
#> Last updated at 09/27/2026
#> ---------------------------------------------------------------
#> env variable mean
#> 1 env1 T2M 25.92709677
#> 2 env1 T2M_MAX 30.52935484
#> 3 env1 T2M_MIN 22.16516129
#> 4 env1 T2MDEW 22.89483871
#> 5 env1 ALLSKY_SFC_LW_DWN 36.08806452
#> 6 env1 ALLSKY_SFC_SW_DWN 20.05838710
#> 7 env1 ALLSKY_SFC_SW_DNI 11.89387097
#> 8 env1 ALLSKY_SFC_PAR_TOT 9.72709677
#> 9 env1 ALLSKY_SFC_UVA 1.34967742
#> 10 env1 ALLSKY_SFC_UVB 0.04290323
#> 11 env1 PRECTOT 9.26806452
#> 12 env1 EVPTRNS 9.04677419
#> 13 env1 QV2M 18.13903226
#> 14 env1 RH2M 84.88129032
#> 15 env1 GWETROOT 0.74548387
#> 16 env1 GWETTOP 0.79032258
#> 17 env1 FROST_DAYS 0.00000000
#> 18 env1 WS2M 0.48419355
#> 19 env1 VPD 0.74065646
#> 20 env1 N 12.57587097
#> 21 env1 RTA 39.78167742
#> 22 env1 n 3.76003226
#> 23 env1 TH1 76.91020373
#> 24 env1 TH2 75.36923871
#> 25 env1 PAR_TEMP 0.37401389
summaryWTH(env.data, env.id = "env", by.interval = TRUE,
time.window = c(0, 14, 35, 60, 90, 120),
names.window = c("P-E", "E-V1", "V1-V4", "V4-VT", "VT-GF", "GF-PM"))
#> ---------------------------------------------------------------
#> summaryWTH -- summarises weather by environment and interval
#> Last updated at 09/27/2026
#> ---------------------------------------------------------------
#> env interval variable mean sum prob_0.25
#> 1 env1 E-V1 ALLSKY_SFC_LW_DWN 36.30000000 653.400000 36.0125000
#> 2 env1 E-V1 ALLSKY_SFC_PAR_TOT 9.26500000 166.770000 7.6075000
#> 3 env1 E-V1 ALLSKY_SFC_SW_DNI 10.48444444 188.720000 4.5450000
#> 4 env1 E-V1 ALLSKY_SFC_SW_DWN 18.98333333 341.700000 15.2525000
#> 5 env1 E-V1 ALLSKY_SFC_UVA 1.28444444 23.120000 1.0775000
#> 6 env1 E-V1 ALLSKY_SFC_UVB 0.04055556 0.730000 0.0300000
#> 7 env1 E-V1 EVPTRNS 9.76777778 175.820000 7.7625000
#> 8 env1 E-V1 FROST_DAYS 0.00000000 0.000000 0.0000000
#> 9 env1 E-V1 GWETROOT 0.76500000 13.770000 0.7525000
#> 10 env1 E-V1 GWETTOP 0.80833333 14.550000 0.7800000
#> 11 env1 E-V1 N 12.50661111 225.119000 12.4587500
#> 12 env1 E-V1 PAR_TEMP 0.35741969 6.433554 0.2919944
#> 13 env1 E-V1 PRECTOT 9.17388889 165.130000 1.8600000
#> 14 env1 E-V1 QV2M 18.53722222 333.670000 18.3000000
#> 15 env1 E-V1 RH2M 86.65055556 1559.710000 83.3300000
#> 16 env1 E-V1 RTA 39.54622222 711.832000 39.3470000
#> 17 env1 E-V1 T2M 25.85833333 465.450000 25.1125000
#> 18 env1 E-V1 T2MDEW 23.25500000 418.590000 23.0800000
#> 19 env1 E-V1 T2M_MAX 30.22888889 544.120000 29.3300000
#> 20 env1 E-V1 T2M_MIN 22.22722222 400.090000 21.7625000
#> 21 env1 E-V1 TH1 77.01414081 1386.254535 76.3980104
#> 22 env1 E-V1 TH2 75.43013333 1357.742400 74.8568000
#> 23 env1 E-V1 VPD 0.64251066 11.565192 0.5248762
#> 24 env1 E-V1 WS2M 0.52722222 9.490000 0.4600000
#> 25 env1 E-V1 n 3.31538889 59.677000 1.4360000
#> 26 env1 P-E ALLSKY_SFC_LW_DWN 35.79461538 465.330000 35.3300000
#> 27 env1 P-E ALLSKY_SFC_PAR_TOT 10.36692308 134.770000 9.7600000
#> 28 env1 P-E ALLSKY_SFC_SW_DNI 13.84538462 179.990000 6.6100000
#> 29 env1 P-E ALLSKY_SFC_SW_DWN 21.54692308 280.110000 19.9600000
#> 30 env1 P-E ALLSKY_SFC_UVA 1.44000000 18.720000 1.3600000
#> 31 env1 P-E ALLSKY_SFC_UVB 0.04615385 0.600000 0.0400000
#> 32 env1 P-E EVPTRNS 8.04846154 104.630000 5.9600000
#> 33 env1 P-E FROST_DAYS 0.00000000 0.000000 0.0000000
#> 34 env1 P-E GWETROOT 0.71846154 9.340000 0.6900000
#> 35 env1 P-E GWETTOP 0.76538462 9.950000 0.7200000
#> 36 env1 P-E N 12.67176923 164.733000 12.6430000
#> 37 env1 P-E PAR_TEMP 0.39699048 5.160876 0.3806796
#> 38 env1 P-E PRECTOT 9.39846154 122.180000 3.8900000
#> 39 env1 P-E QV2M 17.58769231 228.640000 17.1300000
#> 40 env1 P-E RH2M 82.43153846 1071.610000 78.2500000
#> 41 env1 P-E RTA 40.10769231 521.400000 40.0420000
#> 42 env1 P-E T2M 26.02230769 338.290000 24.9200000
#> 43 env1 P-E T2MDEW 22.39615385 291.150000 21.9900000
#> 44 env1 P-E T2M_MAX 30.94538462 402.290000 29.1900000
#> 45 env1 P-E T2M_MIN 22.07923077 287.030000 21.6900000
#> 46 env1 P-E TH1 76.76629085 997.961781 75.3024542
#> 47 env1 P-E TH2 75.28492308 978.704000 74.0364000
#> 48 env1 P-E VPD 0.87655065 11.395159 0.6340613
#> 49 env1 P-E WS2M 0.42461538 5.520000 0.3800000
#> 50 env1 P-E n 4.37569231 56.884000 2.0870000
#> prob_0.5 prob_0.75
#> 1 36.2450000 36.6275000
#> 2 8.9400000 11.4650000
#> 3 8.3150000 17.4975000
#> 4 18.0900000 23.8250000
#> 5 1.2650000 1.5475000
#> 6 0.0400000 0.0500000
#> 7 9.9250000 12.3850000
#> 8 0.0000000 0.0000000
#> 9 0.7650000 0.7775000
#> 10 0.8000000 0.8350000
#> 11 12.5075000 12.5552500
#> 12 0.3540806 0.4347733
#> 13 5.1050000 15.8875000
#> 14 18.5250000 18.8675000
#> 15 86.8000000 88.8650000
#> 16 39.5715000 39.7617500
#> 17 25.7900000 26.5275000
#> 18 23.2550000 23.5325000
#> 19 30.2250000 31.0300000
#> 20 22.3900000 22.7000000
#> 21 76.9598732 77.8659916
#> 22 75.4212000 76.1458000
#> 23 0.6453706 0.7696406
#> 24 0.5350000 0.5775000
#> 25 2.6315000 5.5290000
#> 26 35.9800000 36.2200000
#> 27 10.8000000 11.5900000
#> 28 15.3500000 17.7300000
#> 29 22.3600000 24.1700000
#> 30 1.5100000 1.6100000
#> 31 0.0500000 0.0500000
#> 32 8.0600000 10.5300000
#> 33 0.0000000 0.0000000
#> 34 0.7100000 0.7500000
#> 35 0.7500000 0.8000000
#> 36 12.6730000 12.7010000
#> 37 0.4049855 0.4432030
#> 38 8.1700000 12.1000000
#> 39 17.5100000 18.0400000
#> 40 80.1000000 85.5400000
#> 41 40.1170000 40.1800000
#> 42 26.3800000 26.9800000
#> 43 22.3500000 22.8200000
#> 44 31.2900000 32.8300000
#> 45 22.1800000 22.3200000
#> 46 77.1698742 77.9281685
#> 47 75.6052000 76.2984000
#> 48 0.9479085 1.1868980
#> 49 0.4300000 0.4600000
#> 50 4.8500000 5.5970000
# }