237 lines
7.3 KiB
Plaintext
237 lines
7.3 KiB
Plaintext
{
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"cells": [
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{
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"# 气象大数据云平台的模式数据读取\n",
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"\n",
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"#### —— nmc_met_io程序库使用说明\n",
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"\n",
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"国家气象中心天气预报技术研发室 \n",
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"June, 2020 \n",
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"Kan Dai "
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]
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},
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{
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"## Prepare"
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]
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},
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{
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"cell_type": "code",
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"execution_count": 1,
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"metadata": {},
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"outputs": [],
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"source": [
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"# set up things\n",
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"%matplotlib inline\n",
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"%load_ext autoreload\n",
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"%autoreload 2\n",
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"\n",
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"import warnings\n",
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"warnings.filterwarnings('ignore')"
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]
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},
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{
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"cell_type": "code",
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"execution_count": 2,
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"metadata": {},
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"outputs": [
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{
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"data": {
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"text/plain": [
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"<xarray.core.options.set_options at 0x7fc33c112590>"
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]
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},
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"execution_count": 2,
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"metadata": {},
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"output_type": "execute_result"
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}
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],
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"source": [
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"import numpy as np\n",
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"import xarray as xr\n",
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"\n",
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"from nmc_met_io.retrieve_cmadaas import cmadaas_model_grid\n",
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"\n",
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"xr.set_options(display_style=\"text\")"
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]
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},
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{
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"## 读取单个数值模式预报数据"
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]
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},
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{
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"cell_type": "code",
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"execution_count": 3,
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"metadata": {},
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"outputs": [
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{
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"data": {
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"text/html": [
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"<pre><xarray.Dataset>\n",
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"Dimensions: (lat: 1441, lon: 2880, time: 1)\n",
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"Coordinates:\n",
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" * time (time) datetime64[ns] 2020-07-29\n",
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" * lat (lat) float64 90.0 89.88 89.75 ... -89.88 -90.0\n",
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" * lon (lon) float64 0.0 0.125 0.25 ... 359.6 359.8 359.9\n",
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" forecast_reference_time datetime64[ns] 2020-07-29\n",
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" forecast_period (time) float64 0.0\n",
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"Data variables:\n",
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" temperature (time, lat, lon) float32 1.706543 ... -50.730957\n",
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"Attributes:\n",
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" Conventions: CF-1.6\n",
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" Origin: CIMISS Server by MUSIC API</pre>"
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],
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"text/plain": [
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"<xarray.Dataset>\n",
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"Dimensions: (lat: 1441, lon: 2880, time: 1)\n",
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"Coordinates:\n",
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" * time (time) datetime64[ns] 2020-07-29\n",
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" * lat (lat) float64 90.0 89.88 89.75 ... -89.88 -90.0\n",
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" * lon (lon) float64 0.0 0.125 0.25 ... 359.6 359.8 359.9\n",
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" forecast_reference_time datetime64[ns] 2020-07-29\n",
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" forecast_period (time) float64 0.0\n",
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"Data variables:\n",
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" temperature (time, lat, lon) float32 1.706543 ... -50.730957\n",
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"Attributes:\n",
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" Conventions: CF-1.6\n",
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" Origin: CIMISS Server by MUSIC API"
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]
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},
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"execution_count": 3,
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"metadata": {},
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"output_type": "execute_result"
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}
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],
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"source": [
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"# set retrieve parameters\n",
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"dataCode = \"NAFP_ECMF_C1D_GLB_FOR\" # 资料代码: 大气模式确定性预报产品\n",
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"init_time = \"2020072900\" # 起报时间: \n",
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"fcst_Ele = \"TEM\"\n",
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"levelType = 1\n",
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"fcastLevel = 0\n",
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"validTime = 0\n",
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"\n",
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"# retrieve data from CMADaaS\n",
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"data = cmadaas_model_grid(dataCode, init_time, validTime, fcst_Ele, fcastLevel, levelType, \n",
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" varname='temperature', units='Degree', scale_off=[1.0, -273.15],\n",
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" levattrs={'long_name':'height_above_ground', 'units':'m', '_CoordinateAxisType':'Height'})\n",
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"data"
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]
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},
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{
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"## 读取CRA40再分析数据\n",
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"\n",
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"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°。"
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]
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},
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{
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"cell_type": "code",
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"execution_count": 4,
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"metadata": {},
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"outputs": [
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{
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"data": {
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"text/html": [
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"<pre><xarray.Dataset>\n",
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"Dimensions: (lat: 361, level: 1, lon: 720, time: 1)\n",
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"Coordinates:\n",
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" * time (time) datetime64[ns] 2020-04-19\n",
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" * level (level) int64 500\n",
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" * lat (lat) float64 90.0 89.5 89.0 ... -89.0 -89.5 -90.0\n",
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" * lon (lon) float64 0.0 0.5 1.0 1.5 ... 358.5 359.0 359.5\n",
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" forecast_reference_time datetime64[ns] 2020-04-19\n",
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" forecast_period (time) float64 0.0\n",
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"Data variables:\n",
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" geopotential_height (time, level, lat, lon) float32 5.14e+03 ... 4.8...\n",
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"Attributes:\n",
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" Conventions: CF-1.6\n",
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" Origin: CIMISS Server by MUSIC API</pre>"
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],
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"text/plain": [
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"<xarray.Dataset>\n",
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"Dimensions: (lat: 361, level: 1, lon: 720, time: 1)\n",
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"Coordinates:\n",
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" * time (time) datetime64[ns] 2020-04-19\n",
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" * level (level) int64 500\n",
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" * lat (lat) float64 90.0 89.5 89.0 ... -89.0 -89.5 -90.0\n",
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" * lon (lon) float64 0.0 0.5 1.0 1.5 ... 358.5 359.0 359.5\n",
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" forecast_reference_time datetime64[ns] 2020-04-19\n",
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" forecast_period (time) float64 0.0\n",
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"Data variables:\n",
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" geopotential_height (time, level, lat, lon) float32 5.14e+03 ... 4.8...\n",
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"Attributes:\n",
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" Conventions: CF-1.6\n",
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" Origin: CIMISS Server by MUSIC API"
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]
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},
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"execution_count": 4,
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"metadata": {},
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"output_type": "execute_result"
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}
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],
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"source": [
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"# set retrieve parameters\n",
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"data_code = \"NAFP_CRA40_FTM_6HOR_ANA\"\n",
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"init_time = \"2020041900\"\n",
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"valid_time = 0\n",
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"fcst_ele = \"GPH\" # 位势高度场\n",
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"fcst_level = 500 # 500hPa层次\n",
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"level_type = \"-\"\n",
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"\n",
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"# retrieve data from CMADaSS\n",
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"data = cmadaas_model_grid(data_code, init_time, valid_time, fcst_ele, fcst_level, level_type,\n",
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" varname='geopotential_height', units='gpm', \n",
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" levattrs={'long_name':'isobaric', 'units':'hPa', '_CoordinateAxisType':'isobaric'},\n",
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" cache=False)\n",
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"data"
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]
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},
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{
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"cell_type": "code",
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"execution_count": null,
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"metadata": {},
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"outputs": [],
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}
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],
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"metadata": {
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"kernelspec": {
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"display_name": "Python 3",
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"language": "python",
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"name": "python3"
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},
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"language_info": {
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"codemirror_mode": {
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"name": "ipython",
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"version": 3
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},
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"file_extension": ".py",
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"mimetype": "text/x-python",
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"name": "python",
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"nbconvert_exporter": "python",
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"pygments_lexer": "ipython3",
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"version": "3.7.10"
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},
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"widgets": {
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"nbformat": 4,
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