Hello, everyone!
I tried to get cloud fraction over regions with different elevations (e.g. the Tibetan Plateau, the Sichuan Basin). The low, middle and high clouds can be obtained by the funtion of "wrf_user_getvar(cfrac)" in NCL. The default criterion of low, middle and high clouds is height. However, when compared with the ERA5 reanalysis, the spatial distribution of the three kinds of clouds was unreasonable. Here I just present the low clouds in Figure 1. I thought the terrain height should be added to the "height", but it seems hard to add it in the code (Figure 2). Then, I used the "pressure" to acquire the cloud fraction and the distribution was also unreasonable (Figure 3). I wonder how to get the three kinds of cloud fraction over regions with varing elevations from wrfout data?
Thanks for any help!
I tried to get cloud fraction over regions with different elevations (e.g. the Tibetan Plateau, the Sichuan Basin). The low, middle and high clouds can be obtained by the funtion of "wrf_user_getvar(cfrac)" in NCL. The default criterion of low, middle and high clouds is height. However, when compared with the ERA5 reanalysis, the spatial distribution of the three kinds of clouds was unreasonable. Here I just present the low clouds in Figure 1. I thought the terrain height should be added to the "height", but it seems hard to add it in the code (Figure 2). Then, I used the "pressure" to acquire the cloud fraction and the distribution was also unreasonable (Figure 3). I wonder how to get the three kinds of cloud fraction over regions with varing elevations from wrfout data?
Thanks for any help!