ZIP追逐台风卡努项目源码及数据集 44.95MB

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资源文件列表:

台风卡努追踪实验.zip 大约有306个文件
  1. 台风卡努追踪实验/Data/
  2. 台风卡努追踪实验/Data/mean_sea_level_pressure.nc 15.23MB
  3. 台风卡努追踪实验/Image/
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  301. 台风卡努追踪实验/Resource/
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  303. 台风卡努追踪实验/Video/
  304. 台风卡努追踪实验/Video/台风卡努.mp4 1.26MB
  305. 台风卡努追踪实验/合成视频代码.docx 10.84KB
  306. 台风卡努追踪实验/卡努台风追踪图片生成代码.docx 12.36KB

资源介绍:

大家都追逐过春风吧？但有人追逐过台风吗！！！? 今天我就带大家来追逐台风卡努！ 什么学校气象学能和清华并列第一？通过气象小项目带大家爱上Python（加强版） 完整内容： -----国际气象网站：ERA5 中关于台风卡努的全球海平面平均气压值的精确的完整数据集 -----项目需要的额外图片（panel图标） -----项目第一部分将生成的全部图片（由于项目较大，生成图片需要大量时间） -----项目两部分对应的完整代码 项目最终结果：生成的完整视频
<link href="/image.php?url=https://csdnimg.cn/release/download_crawler_static/css/base.min.css" rel="stylesheet"/><link href="/image.php?url=https://csdnimg.cn/release/download_crawler_static/css/fancy.min.css" rel="stylesheet"/><link href="/image.php?url=https://csdnimg.cn/release/download_crawler_static/89495083/raw.css" rel="stylesheet"/><div id="sidebar" style="display: none"><div id="outline"></div></div><div class="pf w0 h0" data-page-no="1" id="pf1"><div class="pc pc1 w0 h0"><img alt="" class="bi x0 y0 w1 h1" src="/image.php?url=https://csdnimg.cn/release/download_crawler_static/89495083/bg1.jpg"/><div class="t m0 x1 h2 y1 ff1 fs0 fc0 sc0 ls0 ws0">import netCDF4 as nc</div><div class="t m0 x1 h2 y2 ff1 fs0 fc0 sc0 ls0 ws0">import numpy as np</div><div class="t m0 x1 h2 y3 ff1 fs0 fc0 sc0 ls0 ws0">import matplotlib.pyplot as plt</div><div class="t m0 x1 h2 y4 ff1 fs0 fc0 sc0 ls0 ws0">import cartopy.crs as ccrs</div><div class="t m0 x1 h2 y5 ff1 fs0 fc0 sc0 ls0 ws0">import cartopy.feature as cfeature</div><div class="t m0 x1 h2 y6 ff1 fs0 fc0 sc0 ls0 ws0">from matplotlib.patches import Rectangle, Circle</div><div class="t m0 x1 h2 y7 ff1 fs0 fc0 sc0 ls0 ws0">from matplotlib.offsetbox import OffsetImage, AnnotationBbox</div><div class="t m0 x1 h2 y8 ff1 fs0 fc0 sc0 ls0 ws0">import os</div><div class="t m0 x1 h2 y9 ff1 fs0 fc0 sc0 ls0 ws0">import matplotlib</div><div class="t m0 x1 h2 ya ff1 fs0 fc0 sc0 ls0 ws0">matplotlib.use('TkAgg')</div><div class="t m0 x1 h3 yb ff1 fs0 fc0 sc0 ls0 ws0"># <span class="_ _0"> </span><span class="ff2">打开</span> <span class="_ _0"> </span>NetCDF <span class="_ _0"> </span><span class="ff2">文件</span> <span class="_ _0"> </span><span class="ff2">替换为自己的保存路径</span></div><div class="t m0 x1 h3 yc ff1 fs0 fc0 sc0 ls0 ws0">dataset <span class="_ _1"> </span>= <span class="_ _1"> </span>nc.Dataset('C:/Users/Mayn/Desktop/<span class="_ _1"> </span><span class="ff2">台<span class="_ _1"> </span>风<span class="_ _1"> </span>实<span class="_ _1"> </span>验<span class="_ _1"> </span></span>/<span class="_ _1"> </span><span class="ff2">台<span class="_ _1"> </span>风<span class="_ _1"> </span>实<span class="_ _1"> </span>验</span></div><div class="t m0 x1 h2 yd ff1 fs0 fc0 sc0 ls0 ws0">/mean_sea_level_pressure.nc', 'r')</div><div class="t m0 x1 h3 ye ff1 fs0 fc0 sc0 ls0 ws0"># <span class="_ _0"> </span><span class="ff2">读取海平面气压数据</span></div><div class="t m0 x1 h2 yf ff1 fs0 fc0 sc0 ls0 ws0">seapress = dataset.variables['msl'][:]</div><div class="t m0 x1 h3 y10 ff1 fs0 fc0 sc0 ls0 ws0">seapress = seapress / 100 <span class="_ _2"> </span># <span class="_ _0"> </span><span class="ff2">转换为百帕</span></div><div class="t m0 x1 h3 y11 ff1 fs0 fc0 sc0 ls0 ws0"># <span class="_ _0"> </span><span class="ff2">提取经度和纬度信息</span></div><div class="t m0 x1 h2 y12 ff1 fs0 fc0 sc0 ls0 ws0">lons = dataset.variables['longitude'][:]</div><div class="t m0 x1 h2 y13 ff1 fs0 fc0 sc0 ls0 ws0">lats = dataset.variables['latitude'][:]</div><div class="t m0 x1 h3 y14 ff1 fs0 fc0 sc0 ls0 ws0"># <span class="_ _0"> </span><span class="ff2">提取时间变量</span></div><div class="t m0 x1 h2 y15 ff1 fs0 fc0 sc0 ls0 ws0">times = dataset.variables['time'][:]</div><div class="t m0 x1 h2 y16 ff1 fs0 fc0 sc0 ls0 ws0">time_units = dataset.variables['time'].units</div><div class="t m0 x1 h2 y17 ff1 fs0 fc0 sc0 ls0 ws0">calendar <span class="_ _3"> </span>= <span class="_ _3"> </span>dataset.variables['time'].calendar <span class="_ _3"> </span>if <span class="_ _3"> </span>hasattr(dataset.variables['time'], <span class="_ _3"> </span>'calendar') <span class="_ _3"> </span>else </div><div class="t m0 x1 h2 y18 ff1 fs0 fc0 sc0 ls0 ws0">'standard'</div><div class="t m0 x1 h2 y19 ff1 fs0 fc0 sc0 ls0 ws0">time_vals = nc.num2date(times, units=time_units, calendar=calendar)</div><div class="t m0 x1 h3 y1a ff1 fs0 fc0 sc0 ls0 ws0"># <span class="_ _0"> </span><span class="ff2">读取天气图标</span> <span class="_ _0"> </span><span class="ff2">替换为自己的保存路径</span></div><div class="t m0 x1 h3 y1b ff1 fs0 fc0 sc0 ls0 ws0">weather_icon_path = 'C:/Users/Mayn/Desktop/<span class="ff2">台风实验</span>/<span class="ff2">台风实验</span>/panel.png'</div><div class="t m0 x1 h2 y1c ff1 fs0 fc0 sc0 ls0 ws0">icon_img = plt.imread(weather_icon_path)</div><div class="t m0 x1 h2 y1d ff1 fs0 fc0 sc0 ls0 ws0">icon_zoom = 0.030</div><div class="t m0 x1 h2 y1e ff1 fs0 fc0 sc0 ls0 ws0">rect_width = 14</div><div class="t m0 x1 h2 y1f ff1 fs0 fc0 sc0 ls0 ws0">rect_height = 2.5</div><div class="t m0 x1 h2 y20 ff1 fs0 fc0 sc0 ls0 ws0">line_color = (68 / 255, 65 / 255, 65 / 255, 0.84)</div><div class="t m0 x1 h3 y21 ff1 fs0 fc0 sc0 ls0 ws0"># <span class="_ _0"> </span><span class="ff2">确保目录存在</span> <span class="_ _2"> </span><span class="ff2">替换为自己的保存路径</span></div><div class="t m0 x1 h3 y22 ff1 fs0 fc0 sc0 ls0 ws0">save_dir = 'C:/Users/Mayn/Desktop/<span class="ff2">台风实验</span>/<span class="ff2">台风实验</span>/image'</div><div class="t m0 x1 h2 y23 ff1 fs0 fc0 sc0 ls0 ws0">if not os.path.exists(save_dir):</div><div class="t m0 x1 h2 y24 ff1 fs0 fc0 sc0 ls0 ws0"> <span class="_ _1"> </span>os.makedirs(save_dir)</div></div><div class="pi" data-data='{"ctm":[1.611830,0.000000,0.000000,1.611830,0.000000,0.000000]}'></div></div><div id="pf2" class="pf w0 h0" data-page-no="2"><div class="pc pc2 w0 h0"><img class="bi x0 y0 w1 h1" alt="" src="/image.php?url=https://csdnimg.cn/release/download_crawler_static/89495083/bg2.jpg"><div class="t m0 x1 h3 y25 ff1 fs0 fc0 sc0 ls0 ws0"># <span class="_ _0"> </span><span class="ff2">&#23547;&#25214;&#26368;&#20302;&#28857;&#30340;&#20989;&#25968;</span></div><div class="t m0 x1 h2 y2 ff1 fs0 fc0 sc0 ls0 ws0">def detect_low_pressure_center(msl_data):</div><div class="t m0 x1 h2 y3 ff1 fs0 fc0 sc0 ls0 ws0"> <span class="_ _1"> </span>min_val = np.min(msl_data)</div><div class="t m0 x1 h2 y4 ff1 fs0 fc0 sc0 ls0 ws0"> <span class="_ _1"> </span>min_idx = np.unravel_index(np.argmin(msl_data), msl_data.shape)</div><div class="t m0 x1 h2 y5 ff1 fs0 fc0 sc0 ls0 ws0"> <span class="_ _1"> </span>return min_val, min_idx</div><div class="t m0 x1 h3 y26 ff1 fs0 fc0 sc0 ls0 ws0"># <span class="_ _0"> </span><span class="ff2">&#23450;&#20041;&#20989;&#25968;&#20197;&#26597;&#25214;<span class="_ _4"> </span></span>3x3<span class="_ _4"> </span><span class="ff2">&#32593;&#26684;&#20869;&#30340;&#19979;&#19968;&#20010;&#26368;&#20302;&#28857;</span></div><div class="t m0 x1 h2 y8 ff1 fs0 fc0 sc0 ls0 ws0">def find_min_in_3x3_region(msl_data, center_idx):</div><div class="t m0 x1 h2 y9 ff1 fs0 fc0 sc0 ls0 ws0"> <span class="_ _1"> </span>x, y = center_idx</div><div class="t m0 x1 h3 y27 ff1 fs0 fc0 sc0 ls0 ws0"> <span class="_ _1"> </span># <span class="_ _0"> </span><span class="ff2">&#30830;&#20445;&#25628;&#32034;&#33539;&#22260;&#22312;&#25968;&#25454;&#33539;&#22260;&#20869;</span></div><div class="t m0 x1 h2 ya ff1 fs0 fc0 sc0 ls0 ws0"> <span class="_ _1"> </span>x_min = max(0, x - 1)</div><div class="t m0 x1 h2 y28 ff1 fs0 fc0 sc0 ls0 ws0"> <span class="_ _1"> </span>x_max = min(msl_data.shape[0] - 1, x + 1)</div><div class="t m0 x1 h2 y29 ff1 fs0 fc0 sc0 ls0 ws0"> <span class="_ _1"> </span>y_min = max(0, y - 1)</div><div class="t m0 x1 h2 y2a ff1 fs0 fc0 sc0 ls0 ws0"> <span class="_ _1"> </span>y_max = min(msl_data.shape[1] - 1, y + 1)</div><div class="t m0 x1 h3 y2b ff1 fs0 fc0 sc0 ls0 ws0"> <span class="_ _1"> </span># <span class="_ _0"> </span><span class="ff2">&#25552;&#21462;<span class="_ _4"> </span></span>3x3<span class="_ _4"> </span><span class="ff2">&#21306;&#22495;&#24182;&#25214;&#21040;&#26368;&#23567;&#28857;</span></div><div class="t m0 x1 h2 y2c ff1 fs0 fc0 sc0 ls0 ws0"> <span class="_ _1"> </span>sub_region = msl_data[x_min:x_max + 1, y_min:y_max + 1]</div><div class="t m0 x1 h2 yf ff1 fs0 fc0 sc0 ls0 ws0"> <span class="_ _1"> </span>min_val = np.min(sub_region)</div><div class="t m0 x1 h2 y2d ff1 fs0 fc0 sc0 ls0 ws0"> <span class="_ _1"> </span>min_idx = np.unravel_index(np.argmin(sub_region), sub_region.shape)</div><div class="t m0 x1 h3 y11 ff1 fs0 fc0 sc0 ls0 ws0"> <span class="_ _1"> </span># <span class="_ _0"> </span><span class="ff2">&#36820;&#22238;&#22312;&#21407;&#22987;&#25968;&#25454;&#20013;&#30340;&#23454;&#38469;&#32034;&#24341;</span></div><div class="t m0 x1 h2 y12 ff1 fs0 fc0 sc0 ls0 ws0"> <span class="_ _1"> </span>return min_val, (x_min + min_idx[0], y_min + min_idx[1])</div><div class="t m0 x1 h3 y2e ff1 fs0 fc0 sc0 ls0 ws0"># <span class="_ _0"> </span><span class="ff2">&#33719;&#21462;&#21021;&#22987;&#26368;&#20302;&#28857;</span></div><div class="t m0 x1 h2 y2f ff1 fs0 fc0 sc0 ls0 ws0">seapress_2d_0 = seapress[0, :, :]</div><div class="t m0 x1 h2 y15 ff1 fs0 fc0 sc0 ls0 ws0">initial_min_val, initial_min_idx = detect_low_pressure_center(seapress_2d_0)</div><div class="t m0 x1 h3 y30 ff1 fs0 fc0 sc0 ls0 ws0"># <span class="_ _0"> </span><span class="ff2">&#35760;&#24405;&#24403;&#21069;&#26368;&#20302;&#28857;&#20301;&#32622;</span></div><div class="t m0 x1 h2 y17 ff1 fs0 fc0 sc0 ls0 ws0">current_min_idx = initial_min_idx</div><div class="t m0 x1 h3 y31 ff1 fs0 fc0 sc0 ls0 ws0"># <span class="_ _0"> </span><span class="ff2">&#36941;&#21382;&#27599;&#20010;&#26102;&#38388;&#29255;</span></div><div class="t m0 x1 h2 y32 ff1 fs0 fc0 sc0 ls0 ws0">for t in range(len(times)):</div><div class="t m0 x1 h3 y1b ff1 fs0 fc0 sc0 ls0 ws0"> <span class="_ _1"> </span># <span class="_ _0"> </span><span class="ff2">&#25552;&#21462;&#24403;&#21069;&#26102;&#38388;&#27493;&#30340;<span class="_ _4"> </span></span>2D<span class="_ _4"> </span><span class="ff2">&#25968;&#25454;</span></div><div class="t m0 x1 h2 y1c ff1 fs0 fc0 sc0 ls0 ws0"> <span class="_ _1"> </span>seapress_2d = seapress[t, :, :]</div><div class="t m0 x1 h3 y33 ff1 fs0 fc0 sc0 ls0 ws0"> <span class="_ _1"> </span># <span class="_ _0"> </span><span class="ff2">&#20351;&#29992;<span class="_ _4"> </span></span>3x3<span class="_ _4"> </span><span class="ff2">&#32593;&#26684;&#25214;&#21040;&#26368;&#20302;&#28857;</span></div><div class="t m0 x1 h2 y1f ff1 fs0 fc0 sc0 ls0 ws0"> <span class="_ _1"> </span>min_val, min_idx = find_min_in_3x3_region(seapress_2d, current_min_idx)</div><div class="t m0 x1 h3 y34 ff1 fs0 fc0 sc0 ls0 ws0"> <span class="_ _1"> </span># <span class="_ _0"> </span><span class="ff2">&#26356;&#26032;&#24403;&#21069;&#26368;&#20302;&#28857;&#30340;&#20301;&#32622;</span></div><div class="t m0 x1 h2 y35 ff1 fs0 fc0 sc0 ls0 ws0"> <span class="_ _1"> </span>current_min_idx = min_idx</div><div class="t m0 x1 h3 y36 ff1 fs0 fc0 sc0 ls0 ws0"> <span class="_ _1"> </span># <span class="_ _0"> </span><span class="ff2">&#32472;&#21046;&#22270;&#24418;</span></div><div class="t m0 x1 h2 y24 ff1 fs0 fc0 sc0 ls0 ws0"> <span class="_ _1"> </span>fig = plt.figure(figsize=(10, 6))</div></div><div class="pi" data-data='{"ctm":[1.611830,0.000000,0.000000,1.611830,0.000000,0.000000]}'></div></div>
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