这可能会有所帮助：

国家边界数据

library("rnaturalearth")
library("rnaturalearthdata")
world <- ne_countries(scale = "medium",returnclass = "sf")

然后可以裁剪和绘制感兴趣的区域，如下所示：

world_cropped <- st_crop(world,xmin = -180.0,xmax = 180.0,ymin = 45.0,ymax = 90.0)
ggplot(data = world_cropped) + 
  geom_sf() + 
  geom_sf(data = ArcticCircle,linetype = "dashed",aes())+
  geom_sf(data = dat_sf,color = 'red') + 
  coord_sf(crs = 
             "+proj=lcc +lat_1=50 +lat_2=70 +lat_0=40 +lon_0=-96 +x_0=0 +y_0=0 +datum=NAD83 +units=m +no_defs +ellps=GRS80 +towgs84=0,0") 

我在您的代码中发现了一些错误，首先您的dat数据帧包含字符串格式的x和y值，并且不是数字（这在绘制时无济于事！）。

第二，与其他GIS软件不同，R不能进行即时投影转换！因此，将LAT LONG和LAT LONG一起使用时，对您的shapefile无效，因为在不同的CRS中使用！这是ArcticCircle的CRS：

proj4string:    +proj=lcc +lat_1=50 +lat_2=70 +lat_0=40 +lon_0=-96 +x_0=0 +y_0=0 +datum=NAD83 +units=m +no_defs

所以，我所做的就是将您的LAT LONG点文件转换为上面显示的CRS，然后进行了ggplot，我将在下面将所有代码加在一起，并加上注释：

library(ggplot2)
library(rgdal)
library(ggmap)
library(sp)
library(dplyr) 
library(ggspatial) #To use geom_sf to add shapefiles

#### Breaking apart all the values
x = c(-21.5,19.0,-161.5,-147.5)
y = c(70.5,74.5,58.5,60.5)
Type =c("A","B","A","B")

### Creating spatial LAT LONG coordinates,which will be converted to Lambert Conformal Conic Projection below
dat <- data.frame(lon = x,lat = y)

#### Creating LAT LONG SpatialPoints
  coordinates(dat) = c("lon","lat")
proj4string(dat) <- CRS("+init=epsg:4326")

#### The coordinate reference system,that is used in your shapefile. Will use this when converting the spatial points
polar = "+proj=lcc +lat_1=50 +lat_2=70 +lat_0=40 +lon_0=-96 +x_0=0 +y_0=0 +datum=NAD83 +units=m +no_defs +ellps=GRS80 +towgs84=0,0"

### Converting the LAT LONG to the polar CRS shown above
polar_dat = spTransform(dat,polar)
polar_dat = as.data.frame(polar_dat)

#### Adding the Type column back to the data frame,with the new polar coordinates
polar_dat = data.frame(polar_dat,Type)

#### Reading in the Circle Shapefile
ArcticCircle = st_read("P:\\SHP\\LCC_AC\\LCC_AC.shp")

### Putting it togather in ggplot
p <- ggplot()+
  geom_point(data = polar_dat,aes(x = lon,y = lat,colour = Type))+
  geom_sf(data = ArcticCircle,aes())+
  xlab("Longitude")+
  ylab("Latitude")

这是情节最后的样子：

希望能有所帮助，让我知道是否有任何不清楚的地方！

编辑：带有底图的新代码（感谢Majid提供数据）

library(ggplot2)
library(rgdal)
library(ggmap)
library(sp)
library(dplyr) 
library(ggspatial)
library(sf)
library(rnaturalearth)
library(rnaturalearthdata)

#### Breaking apart all the values
x = c(-21.5,lat = y)

#### Creating LAT LONG SpatialPoints
coordinates(dat) = c("lon",0"
b <- bbox(dat)

### Converting the LAT LONG to the polar CRS shown above
polar_dat = spTransform(dat,Type)

#### Reading in the Circle Shapefile
ArcticCircle = st_read("P:\\SHP\\LCC_AC\\LCC_AC.shp")

### Getting basemap shapefile
world <- ne_countries(scale = "medium",returnclass = "sf")
world_cropped <- st_crop(world,ymax = 90.0)

### Plotting it all togather
p = ggplot(data = world_cropped) + 
  geom_sf(colour = "#6380ad",fill = "#9cb3db") + 
  geom_sf(data = ArcticCircle,aes())+
  geom_point(data = polar_dat,colour = Type))+
  coord_sf(crs = 
             "+proj=lcc +lat_1=50 +lat_2=70 +lat_0=40 +lon_0=-96 +x_0=0 +y_0=0 +datum=NAD83 +units=m +no_defs +ellps=GRS80 +towgs84=0,0")