本文中的气象数据来源于Worldclim 2.0 2.5M数据集，自行搜索下载
1）1970-2020月平均降雨量
读取2.5M 降雨数据，Worldclim 2.0提供的是栅格化气候数据（.tif文件）
> library(raster)
> dir("E:/GIS/WorldClim/precipitation",full.names = T) %>%
+ stack() -> worldclimtemp
> worldclimtemp
class : RasterStack
dimensions : 4320, 8640, 37324800, 12 (nrow, ncol, ncell, nlayers)
resolution : 0.04166667, 0.04166667 (x, y)
extent : -180, 180, -90, 90 (xmin, xmax, ymin, ymax)
crs : +proj=longlat +datum=WGS84 +no_defs
names : wc2.1_2.5m_prec_1, wc2.1_2.5m_prec_10, wc2.1_2.5m_prec_11, wc2.1_2.5m_prec_12, wc2.1_2.5m_prec_2, wc2.1_2.5m_prec_3, wc2.1_2.5m_prec_4, wc2.1_2.5m_prec_5, wc2.1_2.5m_prec_6, wc2.1_2.5m_prec_7, wc2.1_2.5m_prec_8, wc2.1_2.5m_prec_9
min values : 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0
max values : 943, 2342, 755, 834, 1007, 878, 1010, 2077, 2226, 2768, 2027, 1968
> plot(worldclimtemp)
Rplot38.jpeg
2）提取省会城市月平均降雨量
# 首先，获取城市经纬度
> library(sf)
> cities <- readOGR("E:/GIS/四百万数据/省会城市.shp")
> china <- readOGR("E:/GIS/四百万数据/中国界.shp")
> citiesLL <- data.frame(longitude = coordinates(cities)[,1],
latitude = coordinates(cities)[,2])
> head(citiesLL)
longitude latitude
1 116.3809 39.92361
2 117.2035 39.13112
3 114.4898 38.04513
4 112.5694 37.87111
5 111.6633 40.82094
6 123.4117 41.79662
# refs:
# https://qa.1r1g.com/sf/ask/2081560421/
# 其次，根据经纬度提取降雨量数据
> site = cities$PINYIN
> Chinacity <- raster::extract(worldclimtemp, citiesLL)
> Chinacity2 <- Chinacity %>%
+ as_tibble() %>%
+ add_column(Site = site, .before = "Jan")
> head(Chinacity2)
# A tibble: 6 x 13
Site Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec
<chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
1 Beijing 5 4 10 16 31 74 201 154 45 17 7 5
2 Tianjin 8 4 9 18 29 67 207 153 41 16 11 9
3 Shijiazhuang 5 8 11 21 33 51 145 144 51 26 18 6
4 Taiyuan 4 6 13 21 32 53 109 107 52 25 14 5
5 Huhehaote 5 3 6 9 21 32 79 84 33 16 6 4
6 Shenyang 6 7 16 38 55 91 173 154 79 43 19 9
3）全国月平均降雨量
> Chinatemp <- china %>% crop(worldclimtemp, .)
> exactChina <- mask(Chinatemp, china)
> plot(exactChina)
Rplot39.jpeg
