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Update example notebooks.

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NMC-DAVE 2020-07-30 07:55:35 +08:00
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commit f414f47c2c
7 changed files with 173 additions and 195 deletions
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documents/MICAPS4产品列表_2020.pdf Normal file
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examples/retreive_micaps_files.ipynb
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examples/retrieve_caiyun_api.ipynb
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@ -4,23 +4,16 @@
"cell_type": "markdown",
"metadata": {},
"source": [
"<a name=\"top\"></a>\n",
"<div style=\"width:1000 px\">\n",
"# 访问彩云天气的预报数据\n",
"\n",
"<div style=\"float:right; width:68 px; height:68px;\">\n",
"<img src=\"./images/nmc_logo.png\" alt=\"NMC Logo\" style=\"height: 68px;\">\n",
"</div>\n",
" \n",
"<h1 align=\"left\">访问彩云天气的预报数据</h1>\n",
"#### —— nmc_met_io程序库使用说明\n",
"\n",
"<div style=\"clear:both\"></div>\n",
"</div>\n",
"\n",
"<hr style=\"height:2px;\">\n",
"\n",
"[彩云天气](http://caiyunapp.com/)提供了API接口, 用于实时访问其预报数据。 \n",
"国家气象中心天气预报技术研发室 \n",
"June, 2020 \n",
"Kan Dai \n",
"\n",
"### 彩云天气预报数据\n",
"* [彩云天气](http://caiyunapp.com/)提供了API接口, 用于实时访问其预报数据。 \n",
"* 需要在网站上注册用户名,并进入[彩云科技开放平台](https://dashboard.caiyunapp.com/v1/token/)申请免费试用的令牌(免费试用的日申请次数不能超过1000次);\n",
"* 获得试用令牌之后, 在\"用户名/nmcdev/config.ini\"中配置好令牌参数:\n",
"```\n",
@ -786,7 +779,14 @@
"name": "python",
"nbconvert_exporter": "python",
"pygments_lexer": "ipython3",
"version": "3.7.6"
"version": "3.7.7"
},
"widgets": {
"application/vnd.jupyter.widget-state+json": {
"state": {},
"version_major": 2,
"version_minor": 0
}
}
},
"nbformat": 4,

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examples/retrieve_cmadaas_model.ipynb
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@ -4,24 +4,25 @@
"cell_type": "markdown",
"metadata": {},
"source": [
"<a name=\"top\"></a>\n",
"<div style=\"width:1000 px\">\n",
"# 气象大数据云平台的模式数据读取\n",
"\n",
"<div style=\"float:right; width:68 px; height:68px;\">\n",
"<img src=\"./images/nmc_logo.png\" alt=\"NMC Logo\" style=\"height: 68px;\">\n",
"</div>\n",
" \n",
"<h1 align=\"left\">气象大数据云平台的模式数据读取</h1>\n",
"#### —— nmc_met_io程序库使用说明\n",
"\n",
"<div style=\"clear:both\"></div>\n",
"</div>\n",
"\n",
"<hr style=\"height:2px;\">\n"
"国家气象中心天气预报技术研发室 \n",
"June, 2020 \n",
"Kan Dai "
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"## Prepare"
]
},
{
"cell_type": "code",
"execution_count": 3,
"execution_count": 1,
"metadata": {},
"outputs": [],
"source": [
@ -36,16 +37,16 @@
},
{
"cell_type": "code",
"execution_count": 17,
"execution_count": 2,
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"<xarray.core.options.set_options at 0x7faf7c300290>"
"<xarray.core.options.set_options at 0x7fe7790ad4d0>"
]
},
"execution_count": 17,
"execution_count": 2,
"metadata": {},
"output_type": "execute_result"
}
@ -68,43 +69,43 @@
},
{
"cell_type": "code",
"execution_count": 19,
"execution_count": 3,
"metadata": {},
"outputs": [
{
"data": {
"text/html": [
"<pre>&lt;xarray.Dataset&gt;\n",
"Dimensions: (lat: 1441, lon: 2880, time: 1)\n",
"Dimensions: (lat: 1441, lon: 2877, time: 1)\n",
"Coordinates:\n",
" * time (time) datetime64[ns] 2020-03-30\n",
" * lat (lat) float64 90.0 89.88 89.75 ... -89.88 -90.0\n",
" * lon (lon) float64 0.0 0.125 0.25 ... 359.6 359.8 359.9\n",
" forecast_reference_time datetime64[ns] 2020-03-30\n",
" * time (time) datetime64[ns] 2020-07-29\n",
" * lat (lat) float64 -90.0 -89.88 -89.75 ... 89.88 90.0\n",
" * lon (lon) float64 0.0 0.125 0.25 ... 359.2 359.4 359.5\n",
" forecast_reference_time datetime64[ns] 2020-07-29\n",
" forecast_period (time) float64 0.0\n",
"Data variables:\n",
" temperature (time, lat, lon) float32 -25.38974 ... -50.20224\n",
" temperature (time, lat, lon) float32 -50.730957 ... 1.706543\n",
"Attributes:\n",
" Conventions: CF-1.6\n",
" Origin: CIMISS Server by MUSIC API</pre>"
],
"text/plain": [
"<xarray.Dataset>\n",
"Dimensions: (lat: 1441, lon: 2880, time: 1)\n",
"Dimensions: (lat: 1441, lon: 2877, time: 1)\n",
"Coordinates:\n",
" * time (time) datetime64[ns] 2020-03-30\n",
" * lat (lat) float64 90.0 89.88 89.75 ... -89.88 -90.0\n",
" * lon (lon) float64 0.0 0.125 0.25 ... 359.6 359.8 359.9\n",
" forecast_reference_time datetime64[ns] 2020-03-30\n",
" * time (time) datetime64[ns] 2020-07-29\n",
" * lat (lat) float64 -90.0 -89.88 -89.75 ... 89.88 90.0\n",
" * lon (lon) float64 0.0 0.125 0.25 ... 359.2 359.4 359.5\n",
" forecast_reference_time datetime64[ns] 2020-07-29\n",
" forecast_period (time) float64 0.0\n",
"Data variables:\n",
" temperature (time, lat, lon) float32 -25.38974 ... -50.20224\n",
" temperature (time, lat, lon) float32 -50.730957 ... 1.706543\n",
"Attributes:\n",
" Conventions: CF-1.6\n",
" Origin: CIMISS Server by MUSIC API"
]
},
"execution_count": 19,
"execution_count": 3,
"metadata": {},
"output_type": "execute_result"
}
@ -112,7 +113,7 @@
"source": [
"# set retrieve parameters\n",
"dataCode = \"NAFP_ECMF_C1D_GLB_FOR\" # 资料代码: 大气模式确定性预报产品\n",
"init_time = \"2020033000\" # 起报时间: \n",
"init_time = \"2020072900\" # 起报时间: \n",
"fcst_Ele = \"TEM\"\n",
"levelType = 1\n",
"fcastLevel = 0\n",
@ -149,7 +150,14 @@
"name": "python",
"nbconvert_exporter": "python",
"pygments_lexer": "ipython3",
"version": "3.7.6"
"version": "3.7.7"
},
"widgets": {
"application/vnd.jupyter.widget-state+json": {
"state": {},
"version_major": 2,
"version_minor": 0
}
}
},
"nbformat": 4,

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examples/retrieve_global_daily_obs.ipynb
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@ -4,19 +4,13 @@
"cell_type": "markdown",
"metadata": {},
"source": [
"<a name=\"top\"></a>\n",
"<div style=\"width:1000 px\">\n",
"# 读取全球站点观测日值观测数据\n",
"\n",
"<div style=\"float:right; width:68 px; height:68px;\">\n",
"<img src=\"./images/nmc_logo.png\" alt=\"NMC Logo\" style=\"height: 68px;\">\n",
"</div>\n",
" \n",
"<h1 align=\"left\">读取全球站点观测日值观测数据</h1>\n",
"#### —— nmc_met_io程序库使用说明\n",
"\n",
"<div style=\"clear:both\"></div>\n",
"</div>\n",
"\n",
"<hr style=\"height:2px;\">\n",
"国家气象中心天气预报技术研发室 \n",
"June, 2020 \n",
"Kan Dai \n",
"\n",
"[GHCH (Global Historical Climate Network)-Daily](https://www.ncdc.noaa.gov/ghcn-daily-description)是由美国NOAA的环境信息中心提供的 \n",
"一套完整的全球地面气象站观测日值资料. GHCN-Daily由不同数据来源的站点观测整合形成，并经过一系列的质量控制。 \n",
@ -46,6 +40,13 @@
"---"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"## Prepare"
]
},
{
"cell_type": "code",
"execution_count": 2,
@ -651,7 +652,7 @@
"name": "python",
"nbconvert_exporter": "python",
"pygments_lexer": "ipython3",
"version": "3.7.6"
"version": "3.7.7"
},
"widgets": {
"application/vnd.jupyter.widget-state+json": {

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examples/retrieve_mdfs_model.ipynb
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examples/retrieve_radar.ipynb
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@ -4,19 +4,13 @@
"cell_type": "markdown",
"metadata": {},
"source": [
"<a name=\"top\"></a>\n",
"<div style=\"width:1000 px\">\n",
"# 读取天气雷达数据\n",
"\n",
"<div style=\"float:right; width:68 px; height:68px;\">\n",
"<img src=\"./images/nmc_logo.png\" alt=\"NMC Logo\" style=\"height: 68px;\">\n",
"</div>\n",
" \n",
"<h1 align=\"left\">读取天气雷达数据</h1>\n",
"#### —— nmc_met_io程序库使用说明\n",
"\n",
"<div style=\"clear:both\"></div>\n",
"</div>\n",
"\n",
"<hr style=\"height:2px;\">\n",
"国家气象中心天气预报技术研发室 \n",
"June, 2020 \n",
"Kan Dai \n",
"\n",
"### 主要功能:\n",
"* **read_radar**模块提供`StandardData`类, 用于读取[\"天气雷达基数据标准格式(V1.0)\"](https://wenku.baidu.com/view/07e7d51a842458fb770bf78a6529647d272834d6.html)\n",
@ -25,7 +19,16 @@
" * `get_radar_mosaic`读取雷达拼图数据\n",
" * `get_radar_mosaics`读取多个雷达拼图数据\n",
" * `get_swan_radar`读取SWAN的131雷达格式数据\n",
" * `get_radar_standard`读取单站雷达标准格式基数据"
" * `get_radar_standard`读取单站雷达标准格式基数据\n",
"\n",
"----"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"## Prepare"
]
},
{
@ -472,7 +475,7 @@
"name": "python",
"nbconvert_exporter": "python",
"pygments_lexer": "ipython3",
"version": "3.7.6"
"version": "3.7.7"
},
"widgets": {
"application/vnd.jupyter.widget-state+json": {