# set up things
%matplotlib inline
%load_ext autoreload
%autoreload 2
import warnings
warnings.filterwarnings('ignore')
import numpy as np
import xarray as xr
from nmc_met_io.retrieve_cmadaas import cmadaas_model_grid
xr.set_options(display_style="text")
<xarray.core.options.set_options at 0x7fc33c112590>
# set retrieve parameters
dataCode = "NAFP_ECMF_C1D_GLB_FOR" # 资料代码: 大气模式确定性预报产品
init_time = "2020072900" # 起报时间:
fcst_Ele = "TEM"
levelType = 1
fcastLevel = 0
validTime = 0
# retrieve data from CMADaaS
data = cmadaas_model_grid(dataCode, init_time, validTime, fcst_Ele, fcastLevel, levelType,
varname='temperature', units='Degree', scale_off=[1.0, -273.15],
levattrs={'long_name':'height_above_ground', 'units':'m', '_CoordinateAxisType':'Height'})
data
<xarray.Dataset> Dimensions: (lat: 1441, lon: 2880, time: 1) Coordinates: * time (time) datetime64[ns] 2020-07-29 * lat (lat) float64 90.0 89.88 89.75 ... -89.88 -90.0 * lon (lon) float64 0.0 0.125 0.25 ... 359.6 359.8 359.9 forecast_reference_time datetime64[ns] 2020-07-29 forecast_period (time) float64 0.0 Data variables: temperature (time, lat, lon) float32 1.706543 ... -50.730957 Attributes: Conventions: CF-1.6 Origin: CIMISS Server by MUSIC API
CRA40为中国研制的第一套长时间序列全球大气再分析数据集-逐6小时产品,覆盖全球范围,时间跨度40年(197901-201812)并准实时更新,水平分辨率34公里、0.25°、0.5°、1.0°、2.5°。
# set retrieve parameters
data_code = "NAFP_CRA40_FTM_6HOR_ANA"
init_time = "2020041900"
valid_time = 0
fcst_ele = "GPH" # 位势高度场
fcst_level = 500 # 500hPa层次
level_type = "-"
# retrieve data from CMADaSS
data = cmadaas_model_grid(data_code, init_time, valid_time, fcst_ele, fcst_level, level_type,
varname='geopotential_height', units='gpm',
levattrs={'long_name':'isobaric', 'units':'hPa', '_CoordinateAxisType':'isobaric'},
cache=False)
data
<xarray.Dataset> Dimensions: (lat: 361, level: 1, lon: 720, time: 1) Coordinates: * time (time) datetime64[ns] 2020-04-19 * level (level) int64 500 * lat (lat) float64 90.0 89.5 89.0 ... -89.0 -89.5 -90.0 * lon (lon) float64 0.0 0.5 1.0 1.5 ... 358.5 359.0 359.5 forecast_reference_time datetime64[ns] 2020-04-19 forecast_period (time) float64 0.0 Data variables: geopotential_height (time, level, lat, lon) float32 5.14e+03 ... 4.8... Attributes: Conventions: CF-1.6 Origin: CIMISS Server by MUSIC API