Last active
March 5, 2025 08:05
-
-
Save apatlpo/017aba7edbe0f12704728adfb1d226f3 to your computer and use it in GitHub Desktop.
ekman analytical
This file contains hidden or bidirectional Unicode text that may be interpreted or compiled differently than what appears below. To review, open the file in an editor that reveals hidden Unicode characters.
Learn more about bidirectional Unicode characters
| { | |
| "cells": [ | |
| { | |
| "cell_type": "markdown", | |
| "id": "f02d0197-f112-4914-b36b-537b51253540", | |
| "metadata": {}, | |
| "source": [ | |
| "# analytical wind-driven currents Lilly & Elipot 2021" | |
| ] | |
| }, | |
| { | |
| "cell_type": "code", | |
| "execution_count": 1, | |
| "id": "b16811e2-aad5-4f84-a1b8-da1d71db814c", | |
| "metadata": {}, | |
| "outputs": [], | |
| "source": [ | |
| "import numpy as np\n", | |
| "import pandas as pd\n", | |
| "import xarray as xr\n", | |
| "\n", | |
| "from scipy.special import iv, kv, erf\n", | |
| "from scipy.fft import fftfreq, fft, ifft\n", | |
| "#import scipy as sc\n", | |
| "\n", | |
| "import matplotlib.pyplot as plt\n", | |
| "%matplotlib inline" | |
| ] | |
| }, | |
| { | |
| "cell_type": "markdown", | |
| "id": "8f6462b8-113b-4d01-b6d1-3b4e0feec2b2", | |
| "metadata": { | |
| "jp-MarkdownHeadingCollapsed": true | |
| }, | |
| "source": [ | |
| "---\n", | |
| "\n", | |
| "## dev tests" | |
| ] | |
| }, | |
| { | |
| "cell_type": "code", | |
| "execution_count": 57, | |
| "id": "1a46c0d0-4a91-4e98-9878-b0c2cf9fd990", | |
| "metadata": {}, | |
| "outputs": [ | |
| { | |
| "name": "stdout", | |
| "output_type": "stream", | |
| "text": [ | |
| "K0=7.94e-04 m2/s, K1=1.98e-04 m/s\n" | |
| ] | |
| } | |
| ], | |
| "source": [ | |
| "rho = 1025 # kg/m^3\n", | |
| "f = 2*2*np.pi*np.sin(np.deg2rad(43))/86400\n", | |
| "h = 50 # m\n", | |
| "\n", | |
| "delta = 4 # m\n", | |
| "z0 = 4 # m\n", | |
| "\n", | |
| "#K0 = 1e-3 # m^2/s\n", | |
| "K0 = delta**2*f/2\n", | |
| "#K1 = 1e-3/100 # m/s\n", | |
| "K1 = K0/z0\n", | |
| "\n", | |
| "# derived\n", | |
| "#delta = np.sqrt(2*K0/f)\n", | |
| "mu = 2*K1/f\n", | |
| "#z0 = K0/K1\n", | |
| "\n", | |
| "print(f\"K0={K0:.2e} m2/s, K1={K1:.2e} m/s\")" | |
| ] | |
| }, | |
| { | |
| "cell_type": "code", | |
| "execution_count": 58, | |
| "id": "a33f1b4c-081d-4d7f-ad62-38b9d9911a61", | |
| "metadata": {}, | |
| "outputs": [], | |
| "source": [ | |
| "nt = 24*60\n", | |
| "dt = 1/24\n", | |
| "nx = 2\n", | |
| "ny = 2\n", | |
| "\n", | |
| "ds = xr.Dataset(\n", | |
| " coords=dict(\n", | |
| " x=(\"x\", np.arange(nx)),\n", | |
| " y=(\"y\", np.arange(ny)), \n", | |
| " t=(\"t\", np.arange(nt)*dt)),\n", | |
| ")\n", | |
| "#np.random()\n", | |
| "\n", | |
| "tau_0 = .01\n", | |
| "noise = 1/10\n", | |
| "noise = 0\n", | |
| "ds[\"tau_x\"] = ((\"t\", \"x\", \"y\"), np.random.randn(nt, nx, ny)*noise)\n", | |
| "ds[\"tau_y\"] = ((\"t\", \"x\", \"y\"), np.random.randn(nt, nx, ny)*noise)\n", | |
| "#ds[\"tau_x\"] = ds[\"tau_x\"] + np.heaviside(ds[\"t\"]-ds[\"t\"].mean(\"t\"), .5)\n", | |
| "ds[\"tau_x\"] = ds[\"tau_x\"] + (1+erf( (ds[\"t\"]-ds[\"t\"].mean(\"t\"))/.1 ))/2\n", | |
| "\n", | |
| "ds[\"tau_x\"].isel(x=0,y=0).plot()" | |
| ] | |
| }, | |
| { | |
| "cell_type": "code", | |
| "execution_count": 61, | |
| "id": "94003358-6b9d-4d34-a681-0d78d1cc4bb8", | |
| "metadata": {}, | |
| "outputs": [ | |
| { | |
| "data": { | |
| "text/plain": [ | |
| "[<matplotlib.lines.Line2D at 0x1363dea70>]" | |
| ] | |
| }, | |
| "execution_count": 61, | |
| "metadata": {}, | |
| "output_type": "execute_result" | |
| }, | |
| { | |
| "data": { | |
| "image/png": "iVBORw0KGgoAAAANSUhEUgAAAjcAAAGwCAYAAABVdURTAAAAOXRFWHRTb2Z0d2FyZQBNYXRwbG90bGliIHZlcnNpb24zLjkuMiwgaHR0cHM6Ly9tYXRwbG90bGliLm9yZy8hTgPZAAAACXBIWXMAAA9hAAAPYQGoP6dpAAA7k0lEQVR4nO3de3xU9Z3/8fdckpkEkklCIBeJEBEFRNEGq4AoWk0Xb+32Iq3b4gVcWW0pUrsVaau1bmHbQrFVoFatumsrv7ZqdcVLdisBi7aCoVJAQUHDJSEmQCYJkMvM+f0xORNiAoQwM2fOmdfz8UglJzPwyWHKvPP53lyGYRgCAABwCLfVBQAAAMQS4QYAADgK4QYAADgK4QYAADgK4QYAADgK4QYAADgK4QYAADiK1+oCEi0cDmvPnj3KysqSy+WyuhwAANAHhmGoqalJxcXFcruP3ZtJuXCzZ88elZSUWF0GAADoh507d2ro0KHHfEzKhZusrCxJkZuTnZ1tcTUAAKAvgsGgSkpKou/jx5Jy4cYcisrOzibcAABgM32ZUsKEYgAA4CiEGwAA4CiEGwAA4CiEGwAA4CiEGwAA4CiEGwAA4CiEGwAA4CiEGwAA4CiEGwAA4CiEGwAA4CiWhpvVq1frmmuuUXFxsVwul5577rnjPqeyslJlZWXy+/067bTTtHz58vgXCgAAbMPScNPS0qJx48bpwQcf7NPjd+zYoSuvvFKTJ09WVVWV7r77bs2ePVt//OMf41wpAACwC0sPzpw6daqmTp3a58cvX75cp556qpYsWSJJGj16tNatW6ef/exn+uIXvxinKhErhmGoI2woFO76rwzJkNH5dXX+KvJYo/Oa1PmY6K/Nx/b+PAD24nK55Ir+uvO/nVdcLkW/pmN8zTxM8cjfx9X1hBN6/CfPZeztay5JHrerT4c4IvFsdSr4G2+8ofLy8m7XPvvZz+rRRx9Ve3u70tLSejyntbVVra2t0c+DwWDc63Saw+0h7dx3UDv3H1R9c5v2tbSpoblVDS1taj7coUPtIbW0duhgW0iH2kM61BZSeyjcI8iEwgQPAM6S5nEp3eNWuveID49b6V6PfF63svxeBTLSlJ2RFvmvP01DsnwqzsnQKTkZKgz4le5l+mus2Src1NbWqqCgoNu1goICdXR0qL6+XkVFRT2es2DBAv3whz9MVIm213ioXW9/tF9VOw/o7zsP6P26Zu1pPCSrGyJH/rR05E9c3X7K6/5DGgAbMKL/070ba142u7Fd3dlEVnd87SFD7aGQWtpC/Xq+yyWVDhqg0cXZGlOUrfHDcnXeqbkEnpNkq3AjqUcL0HzhH601OG/ePM2dOzf6eTAYVElJSfwKtKF9LW16fsNuvbp5r/62Y586eumwDPR5VZKXqcFZPuUPSNeggenKG+BTlt+rzHRP50fk1/60yE8sXo9bXrdLHrfriP+65fVEfu12uXq0ibu1iGn3AjiGaPA5IgyZ1z8ZhgwZPYJRb1/75BD3kcPjnwxhHWFDbR3hyEco8t/Wzs/bQ2Edbg+p6XCHGg+1q/FQu4KH29V4sF11Ta3afeCQdh84pLaOsLbXt2h7fYtefKdGkpSZ7tHEEYN07bmnqHxMgfxpnpO+V6nGVuGmsLBQtbW13a7V1dXJ6/Vq0KBBvT7H5/PJ5/Mlojzb2bq3ScsrP9D/vFOjto5w9Hpp/gCdd2qOzivJ0eiibA3PH6BBA9IJGwCSSrSL2+OfJnv8W2UYhj5uatW7tU3aXBPUP3Y36o0PGtTQ0qb/3VKn/91SpyyfV9dfcKpmXFSqIdl+q0u2DVuFmwkTJuiFF17odu3VV1/V+PHje51vg941NLfqP19+V39Yv0tmk2bsKdn6/Lmn6PLRBRqeP8DaAgEgBbhcLg3J9mtItl8XnzFYkhQOG9pSG9TL/6jVs1W7tWv/If1q9XY9vvZD3X7p6br1ktPk89LJOR6XYeHykubmZr3//vuSpPPOO0+LFy/WpZdeqry8PJ166qmaN2+edu/erSeffFJSZCn42LFjdeutt+qWW27RG2+8oVmzZul3v/tdn1dLBYNBBQIBNTY2Kjs7O27fW7Kq2LxX8555R/XNbZKkz55VoH+bcrrGDQ3QmQGAJBIOG1q1tU4P/vl9vV19QJJ0Wv4A/fL683RWccDa4ixwIu/floabVatW6dJLL+1x/YYbbtDjjz+uG2+8UR9++KFWrVoV/VplZaXuuOMObdq0ScXFxfrud7+rWbNm9fnPTNVwEw4bWlTxnh567QNJ0pkFWfrxF85W2bBciysDAByLYRh64Z0a/eh/Nuvjplale91a+IWz9YVPDbW6tISyTbixQiqGm1DY0Hd+/3c9U7VbkjTzolJ955/OpLUJADZy4GCb5v6/v+vP79ZJkr5/9RjNuKjU4qoS50Tev1lr5nCGYWj+sxv1TNVued0u/eRL5+h7V48h2ACAzeRkpuuR6eN1y+RIoPnR/2zWk298aG1RSYpw43C//PP7evqtnXK7pAe+cp6uG88yeACwK7fbpbuvHK3ZnxkpSbr3+U363817La4q+RBuHGz11o/18//dKkm6//Nn66pzem5yCACwF5fLpTsuH6mvnF+isCHNWbFBO/cdtLqspEK4caiG5lbNWbFBhiF99dMluv6CU60uCQAQIy6XSz/6/FidPzxXza0dmrNigzpC4eM/MUUQbhzqP17con0tbRpVmKV7rjnL6nIAADGW5nFr8XXnKsvn1fqP9uvXa3ZYXVLSINw40F/er9czVbvlckkLv3gOW3cDgEOV5GXq+9eMkST98s/bVNt42OKKkgPhxmHCYUP3v7hFkjT9wmE6tyTH2oIAAHH1pU8NVdmwXB1sC2nhS1usLicpEG4c5qV/1GpLTVBZPq/uuOIMq8sBAMSZ2+3SvZ3TD/709z3atrfJ4oqsR7hxkFDY0OKK9yRJMyefppzMdIsrAgAkwtlDA/rsWQUyDOmB/9tmdTmWI9w4SMXmvfrg4xblZKbp5ouGW10OACCB5lwe6da/uLFG1Q2pvTSccOMg5k6V13/6VGX5OSUdAFLJ6KJsXXLGYBmG9ESK71xMuHGIrXubtPaDBrld0tcuHGZ1OQAAC9w4abgk6f+9tVPNrR3WFmMhwo1DmF2b8jGFKs7JsLYYAIAlLhk5WKX5A9TU2qGV79RYXY5lCDcO0NYR1gt/j7yI6doAQOpyu136UtlQSdIf395lcTXWIdw4wOqtH6vxULuGZPk0YcQgq8sBAFjon887RS6X9Ncd+1L2zCnCjQM8//c9kqSrzimSx+2yuBoAgJWKczI0sfMH3T9t2G1xNdYg3NjcwbYOVXQed3/tuGKLqwEAJINrzom8H7y8qdbiSqxBuLG51979WIfaQyrJy+CoBQCAJOnyMQVyu6R/7A5q1/7UG5oi3Njca+/VSZI+O6ZQLhdDUgAAKX+gT+OH5UlStLufSgg3NhYOG6rc+rEkacqZQyyuBgCQTMrPKpBEuIHNbK4J6uOmVmWme3R+aa7V5QAAkshloyI/9K77cL8OtqXWhn6EGxtb1TkkNXFEvnxej8XVAACSSWn+AJ2Sk6G2UFh/3bHP6nISinBjY6veiwxJXTpqsMWVAACSjcvl0uSR+ZKk17fVW1xNYhFubOpgW4c27DwgSbp4JOEGANDT5M73hzXbPra4ksQi3NjUhuoD6ggbKgr4NTSXs6QAAD1NOj2ymd/Wvc2qb261uJrEIdzY1N8+jIyfnj88jyXgAIBe5WSm68yCLEmRicWpgnBjU2+Z4aY0z+JKAADJrGx4ZDXt+o9SZ1Ix4caG2kNhVVUfkCR9ejjhBgBwdOd3hpu36NwgmW3eE9TBtpACGWkaOWSg1eUAAJKYuVPxP3Y36lBbyOJqEoNwY0PrPoqk7/HDcuXmFHAAwDEMzc1QQbZPHWFDf991wOpyEoJwY0MbO1+cHJQJADgel8sVfb/YuKvR2mIShHBjQxt3R16cY4cGLK4EAGAHZ58Seb8w3z+cjnBjMy2tHdpe3yJJGltMuAEAHN/ZQ3MkEW6QpDbXBGUYUmG2X4OzfFaXAwCwAbNzs6O+RcHD7RZXE3+EG5v5hzkkdUq2xZUAAOwib0C6TsmJ7Gb/jxTo3hBubCY63+YUhqQAAH13Tuc8TcINks6m3UFJzLcBAJyYs4ojHf93a5osriT+CDc2crg9pG11kRclnRsAwIk4o/OMqXdrCTdIIh983KywIeVkpqkgm8nEAIC+G1UY6dy8/3GzOkJhi6uJL8KNjbxf1yxJGjlkICeBAwBOyNDcDGWme9TWEdaHDQetLieuCDc2sm1vJNycPiTL4koAAHbjdrs0snNo6j2HD00Rbmxk697Ii5HDMgEA/THKDDd7CTdIEuawlDkpDACAE3FGodm5CVpcSXwRbmzicHtIHzZEjl0YWUDnBgBw4s7ofP8wf1h2KsKNTeyob1HYkLL8Xg3h2AUAQD+cNjgSbqr3HXT0iinCjU1sO2JIipVSAID+KMr2y5/mVnvI0M79h6wuJ24INzaxjcnEAICT5Ha7VJofeR/Z/rFzh6YINzaxvT4y32bEYMINAKD/Ths8QJK0/eMWiyuJH8KNTXzUOZl42KBMiysBANjZiPzOcFNPuIGFDMPQR/WR3SSHd74oAQDoj9Jo54ZhKVho/8F2NbV2SJJOzaNzAwDov9PMOTd0bmAlc3+bwmy//Gkei6sBANiZ2bn5uKlVzZ0/ODsN4cYGqjsPOGO+DQDgZGX705STmSZJ2rnPmQdoEm5swOzcDB/EfBsAwMkzpzgQbmAZs3NzKp0bAEAMlOR2hhuHbuRHuLEBOjcAgFgampchic5N3CxdulSlpaXy+/0qKyvTmjVrjvn4p556SuPGjVNmZqaKiop00003qaGhIUHVWuMj5twAAGIo2rkh3MTeihUrNGfOHM2fP19VVVWaPHmypk6dqurq6l4f//rrr2v69OmaMWOGNm3apN///vd66623NHPmzARXnjhNh9vV0NImiXADAIiN6Jyb/YSbmFu8eLFmzJihmTNnavTo0VqyZIlKSkq0bNmyXh//5ptvavjw4Zo9e7ZKS0t10UUX6dZbb9W6desSXHni7NwXGQ/NG5CuLH+axdUAAJygJDqh+JAMw7C4mtizLNy0tbVp/fr1Ki8v73a9vLxca9eu7fU5EydO1K5du7Ry5UoZhqG9e/fqD3/4g6666qqj/jmtra0KBoPdPuxk94FIuDklJ8PiSgAATlGc45fLJR1qD0VHB5zEsnBTX1+vUCikgoKCbtcLCgpUW1vb63MmTpyop556StOmTVN6eroKCwuVk5OjX/7yl0f9cxYsWKBAIBD9KCkpien3EW97CDcAgBjzeT0qzPZLkqodOO/G8gnFLper2+eGYfS4Ztq8ebNmz56tH/zgB1q/fr1efvll7dixQ7NmzTrq7z9v3jw1NjZGP3bu3BnT+uPNDDfFhBsAQAyVOHivG69Vf3B+fr48Hk+PLk1dXV2Pbo5pwYIFmjRpkr7zne9Iks455xwNGDBAkydP1v3336+ioqIez/H5fPL5fLH/BhJkdzTc+C2uBADgJCW5mfrbjn3a5cC9bizr3KSnp6usrEwVFRXdrldUVGjixIm9PufgwYNyu7uX7PFEzlpy4oQoiWEpAEB8lHTudbPLgSumLB2Wmjt3rh555BE99thj2rJli+644w5VV1dHh5nmzZun6dOnRx9/zTXX6JlnntGyZcu0fft2/eUvf9Hs2bP16U9/WsXFxVZ9G3G158BhSQxLAQBiqzgQeV8x32ecxLJhKUmaNm2aGhoadN9996mmpkZjx47VypUrNWzYMElSTU1Ntz1vbrzxRjU1NenBBx/Ut7/9beXk5Oiyyy7Tf/7nf1r1LcRVeyisvU2EGwBA7BUGItMdahudF25chlPHc44iGAwqEAiosbFR2dnZVpdzTDv3HdTkn7ymdK9b7/3on4460RoAgBP1fl2TLl+8Wtl+r96597NWl3NcJ/L+bflqKRzdkXvcEGwAALFU2DksFTzcoZbWDouriS3CTRLbw0opAECcDPR5leWPzE6pcdjQFOEmiUXDTYD5NgCA2CvqnHdT0+is5eCEmyS2m5VSAIA4Moem6NwgYdjjBgAQT8UOXTFFuElie4ORF1tBgDk3AIDYK2RYColW19QqSSrItu/xEQCA5FXMsBQSqbUjpH2dx9AXZNG5AQDEXrRz47Bdigk3Serjzq5NusetnMw0i6sBADgRq6WQUHuDkXAzJNvHBn4AgLgoynHmRn6EmyRVZ04mzmZICgAQHwN9XmX5nLeRH+EmSUVXSjGZGAAQR4M732fM6RBOQLhJUns7X2RDmEwMAIijIVmd4aaZcIM428uwFAAgAQZ3/hBtTodwAsJNkqoLsscNACD+Bg+kc4MEoXMDAEiEIeacmyDhBnHGhGIAQCLQuUFCHGoLKXg4st/AYCYUAwDiaAirpZAIdU2Rro0/za1sv9fiagAATja4c7VUHeEG8dR1YKaf3YkBAHFlDkvta2lTeyhscTWxQbhJQuZKKXPvAQAA4iU3M11ed+QH6XqHzLsh3CShhpbIiyt/IOEGABBfbrcr+n7jlHk3hJskVN/54ho0MN3iSgAAqcBpk4oJN0movqVNEp0bAEBimPNunDKpmHCThLo6N4QbAED8mSum6Nwgbho6OzeDGZYCACTAkOhycGecL0W4SULmbHU6NwCARIjudeOQIxgIN0mooTnSuRk0gM4NACD+zDme5siB3RFukszh9pCaWyNHL+Szzw0AIAHyOn+Y3ke4QTyYQ1LpHreyfBy9AACIP3MaRAOb+CEezCGp/IHpHL0AAEgIcxpE8HCH2jrsfwQD4SbJMJkYAJBogYw0eTqPYNh/0P5DU4SbJHNk5wYAgERwu13KzYy875jvQ3ZGuEkyH9O5AQBYwByaMs83tDPCTZLp6twQbgAAieOkFVOEmyRjzrlhWAoAkEjmYc0MSyHmzHYgnRsAQCIxLIW4qW/q3J2Yzg0AIIHyBkR+qGZYCjG3r3MJXh5HLwAAEohhKcSFYRja30K4AQAkXtewFOEGMdTc2qGOsCFJ0f0GAABIBFZLIS72t7RLkjLSPPKneSyuBgCQSsz91eodcL4U4SaJMN8GAGAVc1iqyQHnSxFukoh5nkdOZprFlQAAUo2Tzpci3CQRJhMDAKxy5PlSdh+aItwkkf0HI3NucphMDACwwCCHTCom3CSRaOeGYSkAgAVyB0Tef8wftu2KcJNEzAnFuQxLAQAskJMRef85wJwbxIr5YmKPGwCAFaKdmxY6N4gRc4yTzg0AwArmnM8Dh+jcIEYOdI5x5jLnBgBggZyMyPvPAebcIFainRuGpQAAFjDff9jnBjFhGEZX54ZhKQCABcxNZOncICZa2kJqC0W2u86jcwMAsEB0zg2dG8SCuceNz+tWRjqHZgIAEs+c88k+N4iJ/RyaCQCwmNm5CR5uVyhsWFxN/xFukgSTiQEAVgt0rpYyDCl4yL7dG8vDzdKlS1VaWiq/36+ysjKtWbPmmI9vbW3V/PnzNWzYMPl8Po0YMUKPPfZYgqqNn67JxCwDBwBYI93r1kCfV5K9V0x5rfzDV6xYoTlz5mjp0qWaNGmSfvWrX2nq1KnavHmzTj311F6fc91112nv3r169NFHdfrpp6uurk4dHR0Jrjz26NwAAJJBTmaamls7dMDGnRtLw83ixYs1Y8YMzZw5U5K0ZMkSvfLKK1q2bJkWLFjQ4/Evv/yyKisrtX37duXl5UmShg8ffsw/o7W1Va2tXUe3B4PB2H0DMcTRCwCAZJCTmaZd+w/ZesWUZcNSbW1tWr9+vcrLy7tdLy8v19q1a3t9zvPPP6/x48frJz/5iU455RSdccYZuvPOO3Xo0KGj/jkLFixQIBCIfpSUlMT0+4gVDs0EACSD6EZ+Nj5fyrLOTX19vUKhkAoKCrpdLygoUG1tba/P2b59u15//XX5/X49++yzqq+v12233aZ9+/Yddd7NvHnzNHfu3OjnwWAwKQOO+SLi6AUAgJW6zpci3PSby+Xq9rlhGD2umcLhsFwul5566ikFAgFJkaGtL33pS3rooYeUkZHR4zk+n08+ny/2hcfYfoalAABJIDe6SzHDUicsPz9fHo+nR5emrq6uRzfHVFRUpFNOOSUabCRp9OjRMgxDu3btimu98WaulgrQuQEAWMg8PNPOq6UsCzfp6ekqKytTRUVFt+sVFRWaOHFir8+ZNGmS9uzZo+bm5ui1rVu3yu12a+jQoXGtN94aO9t/5osKAAArdB3BYN9hKUv3uZk7d64eeeQRPfbYY9qyZYvuuOMOVVdXa9asWZIi82WmT58effz111+vQYMG6aabbtLmzZu1evVqfec739HNN9/c65CUnZibJQUINwAAC5n7rdk53Fg652batGlqaGjQfffdp5qaGo0dO1YrV67UsGHDJEk1NTWqrq6OPn7gwIGqqKjQN7/5TY0fP16DBg3Sddddp/vvv9+qbyEmOkJhNbVG9uoh3AAArJST0blaysbDUpZPKL7tttt022239fq1xx9/vMe1UaNG9RjKsrvg4a5NCLMJNwAAC+Vk2r9zY/nxC+iabzPQ51Wah78SAIB1cqNzbuzbueGdNAk0Mt8GAJAkzM5NS1tIbR1hi6vpn36Fm4MHD8a6jpRmhhuGpAAAVsv2p8ndud3cgUP27N70K9zk5ORo4sSJuvvuu/XKK6+opaUl1nWlFLP1F8iwfAoUACDFud2u6EiCXefd9CvcVFZW6tprr9Xbb7+tL3/5y8rNzdWFF16ou+66Sy+99FKsa3S8YHSPG3YnBgBYzww3jTY9gqFf4WbChAm666679PLLL2v//v1avXq1Ro0apUWLFunqq6+OdY2Ox5wbAEAyMadJBG0abvo9DvLuu+9q1apVqqys1KpVq9Te3q5rrrlGl1xySSzrSwnRcMPRCwCAJGD3zk2/wk1hYaHa29t12WWXacqUKbr77rt19tlnx7q2lEHnBgCQTLJtHm76NSxVWFio5uZmVVdXq7q6Wrt27ep23hNOjDlhi9VSAIBkkO03h6U6jvPI5NSvcLNhwwbt3btX8+fPV0dHh77//e9r8ODBuuCCC3TXXXfFukbH49BMAEAySclhKSmyHPzaa6/VRRddpEmTJulPf/qTfvvb32rdunVauHBhLGt0PIalAADJJCXDzbPPPqtVq1Zp1apV2rRpkwYNGqTJkyfr5z//uS699NJY1+h4nAgOAEgm2Z37rqVUuLn11lt18cUX65ZbbtGUKVM0duzYWNeVUg4QbgAAScR8PwoeTqFwU1dXF+s6UlZ7KKyDbSFJXed5AABgpUCq7nMTCoX03HPPacuWLXK5XBo9erQ+97nPyePxxLI+xzuy5ZflJ9wAAKxnrpZKqWGp999/X1deeaV2796tM888U4ZhaOvWrSopKdGLL76oESNGxLpOxzJfOFl+rzzmSWUAAFjI7p2bfi0Fnz17tkaMGKGdO3fq7bffVlVVlaqrq1VaWqrZs2fHukZHM/e4Yb4NACBZmO9JLW0htYfCFldz4vrVuamsrNSbb76pvLy86LVBgwZp4cKFmjRpUsyKSwXRQzOZbwMASBJZ/q54EDzUrkEDfRZWc+L61bnx+Xxqamrqcb25uVnp6ZxsfSLY4wYAkGy8HrcG+iIBJ3jYfrsU9yvcXH311frXf/1X/fWvf5VhGDIMQ2+++aZmzZqla6+9NtY1OhrhBgCQjLL99t3rpl/h5he/+IVGjBihCRMmyO/3y+/3a9KkSTr99NP1wAMPxLpGRyPcAACSkZ0Pz+zXnJucnBz96U9/0rZt2/Tuu+/KMAyNGTNGp59+eqzrc7yuCcUM5wEAkoedV0z1e58bSRo5cqRGjhwZq1pSkrn7o7nVNQAAySAlOjdz587t82+6ePHifhWTijhXCgCQjOx8eGafw01VVVW3z9evX69QKKQzzzxTkrR161Z5PB6VlZXFtkKHMzs37E4MAEgmdj5fqs/h5rXXXov+evHixcrKytITTzyh3NxcSdL+/ft10003afLkybGv0sGaOpfYHbmnAAAAVjOPYLDjnJt+rZZatGiRFixYEA02kpSbm6v7779fixYtillxqSA654bODQAgiQQyUmwpeDAY1N69e3tcr6ur63VzPxyd2bnJpnMDAEgigUyzc5Mim/j98z//s2666Sb94Q9/0K5du7Rr1y794Q9/0IwZM/SFL3wh1jU6lmEYXeGGCcUAgCRi55PB+9UuWL58ue6880597WtfU3t75Jv2er2aMWOGfvrTn8a0QCc72BZSKGxIYs4NACC5pMRqqSNlZmZq6dKl+ulPf6oPPvhAhmHo9NNP14ABA2Jdn6OZXRuv26WMNI/F1QAA0CUlVkv1ZsCAATrnnHNiVUvK6VoG7pXL5bK4GgAAumQfsUNxOGzI7bbP+1S/wk1LS4sWLlyo//u//1NdXZ3C4XC3r2/fvj0mxTldU3R3YubbAACSi9m5CRtSc1uHrVb19ivczJw5U5WVlfr617+uoqIiug79ZM5AZ74NACDZ+LxupXlcag9FFr84Pty89NJLevHFFzVp0qRY15NS2OMGAJCsXC6Xsvxp2tfS1jnSkGF1SX3Wr6Xgubm5ysvLi3UtKSfI7sQAgCRm7sFmLoCxi36Fmx/96Ef6wQ9+oIMHD8a6npTSxLlSAIAklmXTIxj61TJYtGiRPvjgAxUUFGj48OFKS+v+5vz222/HpDin69qdmHADAEg+WTbt3PQr3Hz+85+PcRmpyUzCDEsBAJJRV7hJgc7NPffcE+s6UhJHLwAAkln0ZHCbdW76NecGsXHkJn4AACSb6Jwbp3Zu8vLytHXrVuXn5ys3N/eYe9vs27cvJsU5HXNuAADJzPFzbn7+858rKytLkrRkyZJ41ZNSzDk32XRuAABJyPHh5oYbboj++tVXX9Ull1yiKVOm6IwzzohLYamAOTcAgGRmvj/ZbUJxv+bcZGVlafHixRo1apSKi4v11a9+VcuXL9e7774b6/ocjTk3AIBkZo4s2G2fm36FGzPI7NmzR4sXL1YgENADDzygs846S0VFRbGu0ZE6QmEdbAtJYhM/AEByMt+f7DYsdVKrpbKyspSbm6vc3Fzl5OTI6/WqsLAwVrU5WnNr1wuFzg0AIBnZdc5Nv8LNd7/7XV144YXKz8/X9773PbW1tWnevHnau3evqqqqYl2jI5kngmekeZTmYUU+ACD5ZPvtOeemXy2Dn/70pxo8eLDuuecefe5zn9Po0aNjXZfjRU8Ez6BrAwBITmbnpqUtpI5QWF6b/DDer3fWqqoqVVZWatWqVVq0aJE8Hk909dSUKVMIO30Q5NBMAECSO/I9qrm1QzmZ6RZW03f9Cjfjxo3TuHHjNHv2bEnS3//+dy1ZskSzZ89WOBxWKBSKaZFO1LWBH50bAEBySve65fO61doRVtNhh4cbKdK9WbVqlVatWqU1a9YoGAzq3HPP1aWXXhrL+hyr69BMOjcAgOSVnZGmj5tabXUEQ7/CTW5urpqbmzVu3DhNmTJFt9xyiy6++GJlZ2fHuj7HYgM/AIAdZPm9kXBzyD4rpvoVbv7rv/6LMHOS2MAPAGAHWTZcMdWvd9arr7461nWkHA7NBADYQbYN97qxx5ouB2qicwMAsAE77nVjebhZunSpSktL5ff7VVZWpjVr1vTpeX/5y1/k9Xp17rnnxrfAODHHLlktBQBIZuYP4UE6N32zYsUKzZkzR/Pnz1dVVZUmT56sqVOnqrq6+pjPa2xs1PTp0/WZz3wmQZXGXlOruYkfw1IAgOTVdQQDnZs+Wbx4sWbMmKGZM2dq9OjRWrJkiUpKSrRs2bJjPu/WW2/V9ddfrwkTJiSo0tgzOzcMSwEAkpkdD8+0LNy0tbVp/fr1Ki8v73a9vLxca9euPerzfvOb3+iDDz7QPffc06c/p7W1VcFgsNtHMjATMBOKAQDJjAnFJ6C+vl6hUEgFBQXdrhcUFKi2trbX52zbtk133XWXnnrqKXm9fet4LFiwQIFAIPpRUlJy0rXHgjl2ySZ+AIBkZr5P2WkTP8snFLtcrm6fG4bR45okhUIhXX/99frhD3+oM844o8+//7x589TY2Bj92Llz50nXfLIMw+jq3HBwJgAgidlxQrFl76z5+fnyeDw9ujR1dXU9ujmS1NTUpHXr1qmqqkrf+MY3JEnhcFiGYcjr9erVV1/VZZdd1uN5Pp9PPp8vPt9EPx1uD6s9ZEiicwMASG523MTPss5Nenq6ysrKVFFR0e16RUWFJk6c2OPx2dnZ2rhxozZs2BD9mDVrls4880xt2LBBF1xwQaJKP2nmC8TtkgakeyyuBgCAozNHGOw058bSMZG5c+fq61//usaPH68JEybo4YcfVnV1tWbNmiUpMqS0e/duPfnkk3K73Ro7dmy35w8ZMkR+v7/H9WR35Hyb3obgAABIFubCF/PAZzuwNNxMmzZNDQ0Nuu+++1RTU6OxY8dq5cqVGjZsmCSppqbmuHve2BHnSgEA7MJ8r2rtCKutI6x0r+XTdY/LZRiGYXURiRQMBhUIBNTY2GjZwZ+VWz/WDY/9TWOKsrXyW5MtqQEAgL7oCIV1+vyXJEnrv3e5Bg20Zh7ribx/J3/8ciCztUfnBgCQ7Lwed3R+qF3m3RBuLBA9EZyjFwAANmC3XYoJNxZgzg0AwE669rqxx6Riwo0FOHoBAGAndjs8k3BjAfPQzGw6NwAAGzCnUdhll2LCjQW6jl6gcwMASH7MucFxdW3iR+cGAJD8onNubLKRH+HGAk3RCcV0bgAAya9rzg2dGxxFE50bAICNZNvs8EzCjQWi+9zQuQEA2EA2nRscD/vcAADsxJxGwT436FU4bKi5tetUcAAAkh1zbnBMzW0dMo8qpXMDALADc+sS5tygV2bqTfe45U/zWFwNAADHR+cGx9TEfBsAgM0cOefGMIcfkhjhJsFYBg4AsBtztVR7yFBrR9jiao6PcJNgbOAHALCbAeleuVyRX9thxRThJsGie9xk0LkBANiD2+3SQJ95BEPyz7sh3CRY9FwpH50bAIB92GmXYsJNgpmHjjHnBgBgJ3ZaMUW4SbCuCcV0bgAA9pFto12KCTcJxlJwAIAdmXNF6dygB5aCAwDsKIs5Nzga80XBieAAADsxfyhntRR6oHMDALAjVkvhqLr2uaFzAwCwD1ZL4aiYUAwAsKMsVkvhaFgKDgCwI3O1VJDODY4UChtqamXODQDAfrpWSxFucITm1q4XBOEGAGAnXaulGJbCEcz5Nulet3xej8XVAADQd6yWQq+iK6Xo2gAAbMZ872pu7ZBhGBZXc2yEmwRiMjEAwK7M966wIbW0hSyu5tgINwnEMnAAgF3509xK87gkJf+8G8JNAnUNS9G5AQDYi8vlss2KKcJNAtG5AQDYWdcuxXRu0CnIuVIAABvLtskuxYSbBApGOzcMSwEA7Mcu50sRbhKIE8EBAHYW3ciPcAMTS8EBAHYWHZZitRRMTCgGANgZq6XQAzsUAwDsjNVS6MF8MbDPDQDAjrIzzNVSdG7QiTk3AAA7o3ODHswJWMy5AQDYUTZLwXGkUNiIHjRGuAEA2BGrpdBN8xEpl2EpAIAdsVoK3Zi7E/u8bqV7ue0AAPthzg26YTIxAMDuzNVSLW0hdYTCFldzdISbBOlaBs58GwCAPR05Z7S5NXmHpgg3CcK5UgAAu0vzuOVPi0SHZJ53Q7hJkKbWzs5NBsNSAAD7MldMNSbxiinCTYIED9G5AQDYX5YN9roh3CRI9NBMH50bAIB9dS0Hp3OT8phzAwBwAjucL0W4SZAgS8EBAA5gh71uLA83S5cuVWlpqfx+v8rKyrRmzZqjPvaZZ57RFVdcocGDBys7O1sTJkzQK6+8ksBq+8/cqjqQQecGAGBfdjhfytJws2LFCs2ZM0fz589XVVWVJk+erKlTp6q6urrXx69evVpXXHGFVq5cqfXr1+vSSy/VNddco6qqqgRXfuLMWeWBTDo3AAD7ymbOzbEtXrxYM2bM0MyZMzV69GgtWbJEJSUlWrZsWa+PX7Jkif793/9d559/vkaOHKkf//jHGjlypF544YUEV37igtFN/Ag3AAD7MoelzFXAyciycNPW1qb169ervLy82/Xy8nKtXbu2T79HOBxWU1OT8vLyjvqY1tZWBYPBbh9WiHZu2OcGAGBj0dVSrXRueqivr1coFFJBQUG36wUFBaqtre3T77Fo0SK1tLTouuuuO+pjFixYoEAgEP0oKSk5qbr7K0i4AQA4QHYGc26Oy+VydfvcMIwe13rzu9/9Tvfee69WrFihIUOGHPVx8+bNU2NjY/Rj586dJ13ziTIMI7paih2KAQB2Zu7XFkziHYotW7qTn58vj8fTo0tTV1fXo5vzSStWrNCMGTP0+9//XpdffvkxH+vz+eTz+U663pPR3NqhUNiQROcGAGBv7FB8DOnp6SorK1NFRUW36xUVFZo4ceJRn/e73/1ON954o37729/qqquuineZMWF2bdI9bvm8ljfLAADoNzts4mfppitz587V17/+dY0fP14TJkzQww8/rOrqas2aNUtSZEhp9+7devLJJyVFgs306dP1wAMP6MILL4x2fTIyMhQIBCz7Po6n8WDXoZl9GXIDACBZRVdLJfFScEvDzbRp09TQ0KD77rtPNTU1Gjt2rFauXKlhw4ZJkmpqarrtefOrX/1KHR0duv3223X77bdHr99www16/PHHE11+n5kvADbwAwDYndm5aesI63B7SP40j8UV9WT5u+1tt92m2267rdevfTKwrFq1Kv4FxYG5DJzJxAAAuxuY7pXbJYWNyKTiZAw3TABJAPa4AQA4hdvtir6fHUjSFVOEmwQwl8uxOzEAwAnMcNNIuEldbOAHAHCSQGa6JOnAQcJNyjKXyxFuAABOQOcGR0wotnz+NgAAJy3HnHNzsM3iSnpHuEkAJhQDAJzEfD9L1iMYCDcJwIRiAICT5GSyWirl0bkBADgJc27AJn4AAEeJ7nPDaqnU1XX8AuEGAGB/dG5SXGtHSIfbw5Lo3AAAnCGnc58bwk2KCh6K7HHjcklZPpaCAwDsL8BS8NTWeCjyF5/l88rtdllcDQAAJ89cLdV4qF3hsGFxNT0RbuJsf+dkq9wB6RZXAgBAbJidm7AhNbd1WFxNT4SbONvfEuncmOOTAADYnT/NI583EiEak3DFFOEmzsxlcrmZTCYGADhHMq+YItzE2f7OyVa5dG4AAA5y5LybZEO4iTNzzk0OnRsAgIMk80Z+hJs4O0DnBgDgQIGM5N3rhnATZ9FhKVZLAQAcJNq5OZR8e90QbuJsfwsTigEAzhOdc8OwVOphQjEAwInMH9r3J+EuxYSbOGNCMQDAiczpFvta6NykFMMwmFAMAHCkQdFw02pxJT0RbuKoubVDHZ1nbhBuAABOkjfAJ0na18KwVEox1/77vG5lpHssrgYAgNjJ6+zcNBBuUguTiQEATmUOSzUd7lBbR9jiaroj3MQRk4kBAE4VyEiTx+2SlHwrpgg3ccRkYgCAU7ndruhy8IZmwk3KMP+y89idGADgQOYP73RuUkh9c2R5XP5Awg0AwHmSdVIx4SaOzM5N/kCfxZUAABB7gzp/eN/XnFx73RBu4sjs3Awi3AAAHCgvupEfnZuUUd9idm4YlgIAOI+5kR/DUimkvqlzzk0WnRsAgPMMonOTWgzD6JpQPIBwAwBwHoalUkxLW0itnTs25mcxLAUAcB6zc1PPhOLUYA5JZaZ7lJnutbgaAABib0h2ZGSirolwkxIaWsyVUnRtAADONCTbLylyvtShtpDF1XQh3MTJx02R8cdBzLcBADhUls+rjDSPJKmu6bDF1XQh3MTJ3mDkL7mwM9UCAOA0LpdLBZ1DU3uDyTM0RbiJk5rGznATINwAAJzLHJoyf6hPBoSbOKltPCRJKiLcAAAcbEiW2bkh3DgenRsAQCoo6OzcJNOKKcJNnNR2JtiiQIbFlQAAED/mnJs6OjfOZhhGtHPDsBQAwMnMzk0t4cbZ9h9sV1vn7sTmBkcAADjRKTmREYpd+w9ZXEkXwk0c1HZ2bfIHpsvn9VhcDQAA8VOSlylJ2nPgkNpDYYuriSDcxMHuA5H0ymRiAIDTDR7ok8/rVtiQag4kx9AU4SYOPmpokSQNyxtgcSUAAMSX2+2Kdm+q9x20uJoIwk0cfNQQ+csdNijT4koAAIi/Uwk3zvfRPsINACB1lORGJhUTbhzsw/rOYalBDEsBAJzPHJbaSbhxpoNtHdq5P/KXO2LwQIurAQAg/kYMibzfvbe3yeJKIgg3MfZebZMMQxqc5dPgLPa4AQA435iibEnS9o+bdbg9ZHE1hJuY21ITSa2jO/+iAQBwuiFZPuUNSFfYkLYmQffG8nCzdOlSlZaWyu/3q6ysTGvWrDnm4ysrK1VWVia/36/TTjtNy5cvT1ClffN29X5J0lnFhBsAQGpwuVzR9723P9pvcTUWh5sVK1Zozpw5mj9/vqqqqjR58mRNnTpV1dXVvT5+x44duvLKKzV58mRVVVXp7rvv1uzZs/XHP/4xwZX3zjAMvb6tXpI0ccQgi6sBACBxJnS+773+fr3FlVgcbhYvXqwZM2Zo5syZGj16tJYsWaKSkhItW7as18cvX75cp556qpYsWaLRo0dr5syZuvnmm/Wzn/0swZX37u3qA6oNHpbP69b5w/OsLgcAgIS5eORgSdLaDxq0v6XN0losCzdtbW1av369ysvLu10vLy/X2rVre33OG2+80ePxn/3sZ7Vu3Tq1t7f3+pzW1lYFg8FuH/Gw/qP9+pdH3pQkXXl2kfxpnCkFAEgdZxVna+SQgTrYFtIVP1+tfRYGHMvCTX19vUKhkAoKCrpdLygoUG1tba/Pqa2t7fXxHR0dqq/vvQ22YMECBQKB6EdJSUlsvoFPOKs4WwN9aTr7lIDumjoqLn8GAADJyuVy6WdfHqeigF9nFAxU3oB0y2rxWvYnd3K5XN0+Nwyjx7XjPb6366Z58+Zp7ty50c+DwWBcAo4/zaPnbp+oU3Iyjlk/AABONa4kR5XfudTSro1kYbjJz8+Xx+Pp0aWpq6vr0Z0xFRYW9vp4r9erQYN6n8Dr8/nk8yVmv5mhuRy3AABIbeletwoDfktrsGxYKj09XWVlZaqoqOh2vaKiQhMnTuz1ORMmTOjx+FdffVXjx49XWlpa3GoFAAD2Yelqqblz5+qRRx7RY489pi1btuiOO+5QdXW1Zs2aJSkypDR9+vTo42fNmqWPPvpIc+fO1ZYtW/TYY4/p0Ucf1Z133mnVtwAAAJKMpXNupk2bpoaGBt13332qqanR2LFjtXLlSg0bNkySVFNT023Pm9LSUq1cuVJ33HGHHnroIRUXF+sXv/iFvvjFL1r1LQAAgCTjMswZuSkiGAwqEAiosbFR2dnsIgwAgB2cyPu35ccvAAAAxBLhBgAAOArhBgAAOArhBgAAOArhBgAAOArhBgAAOArhBgAAOArhBgAAOArhBgAAOIqlxy9YwdyQORgMWlwJAADoK/N9uy8HK6RcuGlqapIklZSUWFwJAAA4UU1NTQoEAsd8TMqdLRUOh7Vnzx5lZWXJ5XLF9PcOBoMqKSnRzp07ObfqOLhXfce9OjHcr77jXvUd96rv4nWvDMNQU1OTiouL5XYfe1ZNynVu3G63hg4dGtc/Izs7mxd/H3Gv+o57dWK4X33Hveo77lXfxeNeHa9jY2JCMQAAcBTCDQAAcBTCTQz5fD7dc8898vl8VpeS9LhXfce9OjHcr77jXvUd96rvkuFepdyEYgAA4Gx0bgAAgKMQbgAAgKMQbgAAgKMQbgAAgKMQbmJk6dKlKi0tld/vV1lZmdasWWN1SUlh9erVuuaaa1RcXCyXy6Xnnnuu29cNw9C9996r4uJiZWRkaMqUKdq0aZM1xVpowYIFOv/885WVlaUhQ4bo85//vN57771uj+FedVm2bJnOOeec6CZhEyZM0EsvvRT9Ovfq6BYsWCCXy6U5c+ZEr3G/Iu699165XK5uH4WFhdGvc5+62717t772ta9p0KBByszM1Lnnnqv169dHv27l/SLcxMCKFSs0Z84czZ8/X1VVVZo8ebKmTp2q6upqq0uzXEtLi8aNG6cHH3yw16//5Cc/0eLFi/Xggw/qrbfeUmFhoa644oroGWCporKyUrfffrvefPNNVVRUqKOjQ+Xl5WppaYk+hnvVZejQoVq4cKHWrVundevW6bLLLtPnPve56D+c3KvevfXWW3r44Yd1zjnndLvO/epy1llnqaamJvqxcePG6Ne4T13279+vSZMmKS0tTS+99JI2b96sRYsWKScnJ/oYS++XgZP26U9/2pg1a1a3a6NGjTLuuusuiypKTpKMZ599Nvp5OBw2CgsLjYULF0avHT582AgEAsby5cstqDB51NXVGZKMyspKwzC4V32Rm5trPPLII9yro2hqajJGjhxpVFRUGJdcconxrW99yzAMXltHuueee4xx48b1+jXuU3ff/e53jYsuuuioX7f6ftG5OUltbW1av369ysvLu10vLy/X2rVrLarKHnbs2KHa2tpu987n8+mSSy5J+XvX2NgoScrLy5PEvTqWUCikp59+Wi0tLZowYQL36ihuv/12XXXVVbr88su7Xed+dbdt2zYVFxertLRUX/nKV7R9+3ZJ3KdPev755zV+/Hh9+ctf1pAhQ3Teeefp17/+dfTrVt8vws1Jqq+vVygUUkFBQbfrBQUFqq2ttagqezDvD/euO8MwNHfuXF100UUaO3asJO5VbzZu3KiBAwfK5/Np1qxZevbZZzVmzBjuVS+efvppvf3221qwYEGPr3G/ulxwwQV68skn9corr+jXv/61amtrNXHiRDU0NHCfPmH79u1atmyZRo4cqVdeeUWzZs3S7Nmz9eSTT0qy/nWVcqeCx4vL5er2uWEYPa6hd9y77r7xjW/onXfe0euvv97ja9yrLmeeeaY2bNigAwcO6I9//KNuuOEGVVZWRr/OvYrYuXOnvvWtb+nVV1+V3+8/6uO4X9LUqVOjvz777LM1YcIEjRgxQk888YQuvPBCSdwnUzgc1vjx4/XjH/9YknTeeedp06ZNWrZsmaZPnx59nFX3i87NScrPz5fH4+mRROvq6nokVnRnrkLg3nX55je/qeeff16vvfaahg4dGr3OveopPT1dp59+usaPH68FCxZo3LhxeuCBB7hXn7B+/XrV1dWprKxMXq9XXq9XlZWV+sUvfiGv1xu9J9yvngYMGKCzzz5b27Zt43X1CUVFRRozZky3a6NHj44upLH6fhFuTlJ6errKyspUUVHR7XpFRYUmTpxoUVX2UFpaqsLCwm73rq2tTZWVlSl37wzD0De+8Q0988wz+vOf/6zS0tJuX+deHZ9hGGptbeVefcJnPvMZbdy4URs2bIh+jB8/Xv/yL/+iDRs26LTTTuN+HUVra6u2bNmioqIiXlefMGnSpB7bVWzdulXDhg2TlAT/ZsV9ynIKePrpp420tDTj0UcfNTZv3mzMmTPHGDBggPHhhx9aXZrlmpqajKqqKqOqqsqQZCxevNioqqoyPvroI8MwDGPhwoVGIBAwnnnmGWPjxo3GV7/6VaOoqMgIBoMWV55Y//Zv/2YEAgFj1apVRk1NTfTj4MGD0cdwr7rMmzfPWL16tbFjxw7jnXfeMe6++27D7XYbr776qmEY3KvjOXK1lGFwv0zf/va3jVWrVhnbt2833nzzTePqq682srKyov+Wc5+6/O1vfzO8Xq/xH//xH8a2bduMp556ysjMzDT++7//O/oYK+8X4SZGHnroIWPYsGFGenq68alPfSq6hDfVvfbaa4akHh833HCDYRiR5YL33HOPUVhYaPh8PuPiiy82Nm7caG3RFujtHkkyfvOb30Qfw73qcvPNN0f//zZ48GDjM5/5TDTYGAb36ng+GW64XxHTpk0zioqKjLS0NKO4uNj4whe+YGzatCn6de5Tdy+88IIxduxYw+fzGaNGjTIefvjhbl+38n65DMMw4t8fAgAASAzm3AAAAEch3AAAAEch3AAAAEch3AAAAEch3AAAAEch3AAAAEch3AAAAEch3AAAAEch3AAAAEch3ABwjClTpmjOnDlWlwHAYoQbAADgKJwtBcARbrzxRj3xxBPdru3YsUPDhw+3piAAliHcAHCExsZGTZ06VWPHjtV9990nSRo8eLA8Ho/FlQFINK/VBQBALAQCAaWnpyszM1OFhYVWlwPAQsy5AQAAjkK4AQAAjkK4AeAY6enpCoVCVpcBwGKEGwCOMXz4cP31r3/Vhx9+qPr6eoXDYatLAmABwg0Ax7jzzjvl8Xg0ZswYDR48WNXV1VaXBMACLAUHAACOQucGAAA4CuEGAAA4CuEGAAA4CuEGAAA4CuEGAAA4CuEGAAA4CuEGAAA4CuEGAAA4CuEGAAA4CuEGAAA4CuEGAAA4yv8Hhux6sN73UmUAAAAASUVORK5CYII=", | |
| "text/plain": [ | |
| "<Figure size 640x480 with 1 Axes>" | |
| ] | |
| }, | |
| "metadata": {}, | |
| "output_type": "display_data" | |
| } | |
| ], | |
| "source": [ | |
| "ds[\"omega\"] = (\"omega\", fftfreq(nt, d=dt) *2*np.pi/86400) # rad/s\n", | |
| "ds[\"z\"] = (\"z\", np.arange(0,20))\n", | |
| "\n", | |
| "# tappering window\n", | |
| "T_tapper = 2 # in days\n", | |
| "ds[\"window\"] = np.tanh((ds.t-ds.t.min(\"t\"))/T_tapper)**2 * np.tanh((ds.t-ds.t.max(\"t\"))/T_tapper)**2\n", | |
| "ds[\"window\"].plot()" | |
| ] | |
| }, | |
| { | |
| "cell_type": "code", | |
| "execution_count": 62, | |
| "id": "e3c173b7-ee73-48db-bf51-71f7d193451e", | |
| "metadata": {}, | |
| "outputs": [], | |
| "source": [ | |
| "s = lambda omega: np.sign(f) * np.sign(1+omega/f)\n", | |
| "zeta = lambda z, omega: 2*np.sqrt(2)*np.exp(s(omega)*1j*np.pi/4) * z0/delta * np.sqrt((1+z/z0)*np.abs(1+omega/f))\n", | |
| "#zeta_z = zeta(ds.z, ds.omega)\n", | |
| "#np.abs(zeta_z).sortby(\"omega\").plot(y=\"z\")" | |
| ] | |
| }, | |
| { | |
| "cell_type": "code", | |
| "execution_count": 63, | |
| "id": "22f7b3bd-a466-4880-b28b-5457a7afb145", | |
| "metadata": {}, | |
| "outputs": [], | |
| "source": [ | |
| "def get_ekman_currents(omega):\n", | |
| "\n", | |
| " zeta_0 = zeta(0, omega)\n", | |
| " zeta_h = zeta(h, omega)\n", | |
| " zeta_z = zeta(ds.z, omega)\n", | |
| "\n", | |
| " G = (\n", | |
| " np.sqrt(2) \n", | |
| " * np.exp(-s(omega)*1j*np.pi/4) \n", | |
| " /rho/np.abs(f)/delta/np.sqrt(np.abs(1+omega/f))\n", | |
| " *( iv(0,zeta_h) * kv(0,zeta_z) - iv(0, zeta_z)*kv(0, zeta_h) )\n", | |
| " /( iv(0,zeta_h) * kv(1,zeta_0) - iv(1, zeta_0)*kv(0, zeta_h) )\n", | |
| " )\n", | |
| "\n", | |
| "\n", | |
| " # !! be careful to axis of fft operation !!\n", | |
| " ds[\"tau_hat\"] = ( (\"omega\", \"x\", \"y\"), (fft( (ds.tau_x + 1j*ds.tau_y )*ds.window, axis=0) ) )\n", | |
| "\n", | |
| " U_hat = G*ds[\"tau_hat\"]\n", | |
| " div_stress_hat = 1j*(omega+f)*U_hat\n", | |
| " \n", | |
| " ds[\"U\"] = ((\"t\", \"z\", \"x\", \"y\"), ifft(U_hat, axis=0))\n", | |
| " ds[\"div_stress\"] = ((\"t\", \"z\", \"x\", \"y\"), ifft(div_stress_hat, axis=0))\n", | |
| "\n", | |
| " return ds[\"U\"], ds[\"div_stress\"]" | |
| ] | |
| }, | |
| { | |
| "cell_type": "code", | |
| "execution_count": 64, | |
| "id": "6fdf1ebc-f9f0-4c09-824d-0bed0f49e923", | |
| "metadata": {}, | |
| "outputs": [], | |
| "source": [ | |
| "U0, div_stress0 = get_ekman_currents(ds.omega*0.)\n", | |
| "U, div_stress = get_ekman_currents(ds.omega)" | |
| ] | |
| }, | |
| { | |
| "cell_type": "code", | |
| "execution_count": 65, | |
| "id": "6ded0675-8bfc-4c6e-a178-1bc55b2cb7a9", | |
| "metadata": {}, | |
| "outputs": [ | |
| { | |
| "data": { | |
| "text/plain": [ | |
| "Text(0.5, 1.0, '')" | |
| ] | |
| }, | |
| "execution_count": 65, | |
| "metadata": {}, | |
| "output_type": "execute_result" | |
| }, | |
| { | |
| "data": { | |
| "image/png": "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", | |
| "text/plain": [ | |
| "<Figure size 1000x1000 with 3 Axes>" | |
| ] | |
| }, | |
| "metadata": {}, | |
| "output_type": "display_data" | |
| } | |
| ], | |
| "source": [ | |
| "_ds = ds.isel(x=0,y=0)\n", | |
| "_U0 = U0.isel(x=0,y=0)\n", | |
| "_U = U.isel(x=0,y=0)\n", | |
| "\n", | |
| "fig, axes = plt.subplots(3,1, sharex=True, figsize=(10,10))\n", | |
| "\n", | |
| "ax = axes[0]\n", | |
| "_ds[\"tau_x\"].plot(ax=ax, label=\"tau_x\")\n", | |
| "_ds[\"tau_y\"].plot(ax=ax, label=\"tau_y\")\n", | |
| "ax.set_ylabel(\"\")\n", | |
| "ax.set_title(\"wind stress\")\n", | |
| "ax.legend()\n", | |
| "\n", | |
| "ax = axes[1]\n", | |
| "_U.sel(z=0).real.plot(ax=ax, label=\"u(z=0)\")\n", | |
| "_U.sel(z=0).imag.plot(ax=ax, label=\"v(z=0)\")\n", | |
| "ax.set_ylabel(\"\")\n", | |
| "ax.legend()\n", | |
| "ax.set_title(\"\")\n", | |
| "\n", | |
| "ax = axes[2]\n", | |
| "_U0.sel(z=0).real.plot(ax=ax, label=\"u(z=0)\")\n", | |
| "_U0.sel(z=0).imag.plot(ax=ax, label=\"v(z=0)\")\n", | |
| "(_U.sel(z=0).real-_U0.sel(z=0).real).plot(ax=ax, label=\"u(z=0)-u_sta(z=0)\")\n", | |
| "ax.set_ylabel(\"\")\n", | |
| "ax.legend()\n", | |
| "ax.set_title(\"\")" | |
| ] | |
| }, | |
| { | |
| "cell_type": "code", | |
| "execution_count": 56, | |
| "id": "48d90a0f-fc57-41f2-a6b6-477376c161ae", | |
| "metadata": {}, | |
| "outputs": [ | |
| { | |
| "data": { | |
| "text/plain": [ | |
| "<matplotlib.collections.QuadMesh at 0x136a672e0>" | |
| ] | |
| }, | |
| "execution_count": 56, | |
| "metadata": {}, | |
| "output_type": "execute_result" | |
| }, | |
| { | |
| "data": { | |
| "image/png": "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", | |
| "text/plain": [ | |
| "<Figure size 640x480 with 2 Axes>" | |
| ] | |
| }, | |
| "metadata": {}, | |
| "output_type": "display_data" | |
| } | |
| ], | |
| "source": [ | |
| "_ds[\"U\"].real.plot(x=\"t\")" | |
| ] | |
| }, | |
| { | |
| "cell_type": "code", | |
| "execution_count": null, | |
| "id": "e5bcc910-31b4-4472-b03e-613263d334ff", | |
| "metadata": {}, | |
| "outputs": [], | |
| "source": [] | |
| }, | |
| { | |
| "cell_type": "markdown", | |
| "id": "74e8b573-6910-4496-b4c8-af07047e6ddb", | |
| "metadata": {}, | |
| "source": [ | |
| "---\n", | |
| "\n", | |
| "## wrap eveything in a single callable methods" | |
| ] | |
| }, | |
| { | |
| "cell_type": "code", | |
| "execution_count": 2, | |
| "id": "77b80068-e4a4-4f83-bc94-23e29e837b3b", | |
| "metadata": {}, | |
| "outputs": [], | |
| "source": [ | |
| "\n", | |
| "# helper functions\n", | |
| "s_func = lambda omega, f: np.sign(f) * np.sign(1+omega/f)\n", | |
| "zeta_func = lambda omega, z, delta, z0, f: \\\n", | |
| " 2*np.sqrt(2)*np.exp(s_func(omega, f)*1j*np.pi/4) * z0/delta * np.sqrt((1+z/z0)*np.abs(1+omega/f))\n", | |
| "\n", | |
| "def EkmanUnified_transfer_function(\n", | |
| " omega,\n", | |
| " z,\n", | |
| " h,\n", | |
| " delta,\n", | |
| " z0,\n", | |
| " latitude,\n", | |
| " rho,\n", | |
| " verbose=False,\n", | |
| "):\n", | |
| " \"\"\" compute the unified Ekman transfer function\n", | |
| " Lilly and Elipot 2021\n", | |
| " \"\"\"\n", | |
| " \n", | |
| " # derived parameters\n", | |
| " f = 2*2*np.pi*np.sin(np.deg2rad(latitude))/86400\n", | |
| " K0 = delta**2 * f/2\n", | |
| " K1 = K0/z0\n", | |
| " mu = 2*K1/f\n", | |
| " if verbose:\n", | |
| " print(f\"K0={K0:.2e} m2/s, K1={K1:.2e} m/s, mu={mu:.2e} m\")\n", | |
| "\n", | |
| " if isinstance(omega, tuple):\n", | |
| " nt, dt = omega\n", | |
| " omega = fftfreq(nt, d=dt) *2*np.pi/86400 # rad/s\n", | |
| " elif not isinstance(omega, np.ndarray):\n", | |
| " omega = np.array(omega)\n", | |
| "\n", | |
| " if not isinstance(z, np.ndarray):\n", | |
| " z=np.array(z)\n", | |
| " \n", | |
| " ds = xr.Dataset(\n", | |
| " coords=dict(\n", | |
| " omega=(\"omega\", omega, dict(units=\"rad/s\")),\n", | |
| " omega_cpd=(\"omega\", omega*86400/2/np.pi, dict(units=\"cpd\")),\n", | |
| " z=(\"z\", z, dict(units=\"m\"))),\n", | |
| " )\n", | |
| "\n", | |
| " zeta_0 = zeta_func(ds.omega, 0, delta, z0, f)\n", | |
| " zeta_h = zeta_func(ds.omega, h, delta, z0, f)\n", | |
| " zeta_z = zeta_func(ds.omega, ds.z, delta, z0, f)\n", | |
| "\n", | |
| " ds[\"G\"] = (\n", | |
| " np.sqrt(2) \n", | |
| " * np.exp(-s_func(ds.omega, f)*1j*np.pi/4) \n", | |
| " /rho/np.abs(f)/delta/np.sqrt(np.abs(1+ds.omega/f))\n", | |
| " *( iv(0,zeta_h)*kv(0,zeta_z) - iv(0, zeta_z)*kv(0, zeta_h) )\n", | |
| " /( iv(0,zeta_h)*kv(1,zeta_0) + iv(1, zeta_0)*kv(0, zeta_h) )\n", | |
| " )\n", | |
| "\n", | |
| " ds.attrs.update(\n", | |
| " h=h,\n", | |
| " delta=delta,\n", | |
| " z0=z0,\n", | |
| " latitude=latitude,\n", | |
| " rho=rho,\n", | |
| " f=f,\n", | |
| " )\n", | |
| " \n", | |
| " return ds\n", | |
| "\n", | |
| "def EkmanUnified_tseries(\n", | |
| " tau_x, tau_y, t,\n", | |
| " z,\n", | |
| " h,\n", | |
| " delta,\n", | |
| " z0,\n", | |
| " latitude,\n", | |
| " rho,\n", | |
| " T_tapper=2, # in days\n", | |
| "):\n", | |
| " \"\"\" compute the current time series according the unified Ekman solution\n", | |
| " Lilly and Elipot 2021\n", | |
| "\n", | |
| " Parameters\n", | |
| " ----------\n", | |
| "\n", | |
| " \n", | |
| " \"\"\"\n", | |
| " \n", | |
| " assert tau_x.ndim==1, \"code need adjustment for multidimensional dataset, ask aurelien\"\n", | |
| " #assert taux.time.attrs[\"units\"]==\"days\", ...\n", | |
| " ds = xr.merge([tau_x, tau_y]) # assumes xarray objects\n", | |
| " \n", | |
| " if not isinstance(z, np.ndarray):\n", | |
| " z=np.array(z)\n", | |
| " ds[\"z\"] = (\"z\", z)\n", | |
| "\n", | |
| " # tappering window\n", | |
| " t_dim = str(t.dims[0])\n", | |
| " dt = float(t.diff(t_dim).mean())\n", | |
| " ds[\"window\"] = np.tanh((t-t.min())/T_tapper)**2 * np.tanh((t-t.max())/T_tapper)**2\n", | |
| "\n", | |
| " _tau = (ds.tau_x + 1j*ds.tau_y )*ds.window\n", | |
| " ds[\"tau_hat\"] = ( (\"omega\",), (fft( _tau.data, axis=_tau.get_axis_num(t_dim)) ) )\n", | |
| "\n", | |
| " dsG = EkmanUnified_transfer_function(\n", | |
| " (t.size, dt),\n", | |
| " z,\n", | |
| " h,\n", | |
| " delta,\n", | |
| " z0,\n", | |
| " latitude,\n", | |
| " rho,\n", | |
| " )\n", | |
| " f = dsG.attrs[\"f\"]\n", | |
| "\n", | |
| " # compute fourier transform variables\n", | |
| " U_hat = dsG.G*ds[\"tau_hat\"]\n", | |
| " div_stress_hat = 1j*(dsG.omega+f)*U_hat\n", | |
| "\n", | |
| " # inverse fft\n", | |
| " ds[\"U\"] = (\n", | |
| " (\"t\", \"z\",), \n", | |
| " ifft(U_hat.data, axis=U_hat.get_axis_num(\"omega\"))\n", | |
| " )\n", | |
| " ds[\"div_stress\"] = (\n", | |
| " (\"t\", \"z\",),\n", | |
| " ifft(div_stress_hat.data, axis=div_stress_hat.get_axis_num(\"omega\")),\n", | |
| " )\n", | |
| "\n", | |
| " ds.attrs.update(**dsG.attrs)\n", | |
| "\n", | |
| " return ds\n" | |
| ] | |
| }, | |
| { | |
| "cell_type": "code", | |
| "execution_count": 8, | |
| "id": "e1cfb208-d929-466c-8832-c0601b2373a3", | |
| "metadata": {}, | |
| "outputs": [ | |
| { | |
| "name": "stdout", | |
| "output_type": "stream", | |
| "text": [ | |
| "K0=1.24e-03 m2/s, K1=2.48e-04 m/s, mu=5.00e+00 m\n" | |
| ] | |
| }, | |
| { | |
| "data": { | |
| "text/plain": [ | |
| "<matplotlib.collections.QuadMesh at 0x1363c8f70>" | |
| ] | |
| }, | |
| "execution_count": 8, | |
| "metadata": {}, | |
| "output_type": "execute_result" | |
| }, | |
| { | |
| "data": { | |
| "image/png": "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", | |
| "text/plain": [ | |
| "<Figure size 640x480 with 2 Axes>" | |
| ] | |
| }, | |
| "metadata": {}, | |
| "output_type": "display_data" | |
| } | |
| ], | |
| "source": [ | |
| "# input parameters\n", | |
| "h = 50 # m\n", | |
| "z = np.arange(0,h)\n", | |
| "delta = 5 # m\n", | |
| "z0 = 5 # m\n", | |
| "latitude = 43 # deg\n", | |
| "rho = 1025 # kg/m^3\n", | |
| "\n", | |
| "dsG = EkmanUnified_transfer_function(\n", | |
| " (24*100,1/24),\n", | |
| " z,\n", | |
| " h,\n", | |
| " delta,\n", | |
| " z0,\n", | |
| " latitude,\n", | |
| " rho,\n", | |
| " verbose=True,\n", | |
| ")\n", | |
| "\n", | |
| "np.abs(dsG.G).sortby(\"omega\").plot(x=\"omega_cpd\")" | |
| ] | |
| }, | |
| { | |
| "cell_type": "code", | |
| "execution_count": 9, | |
| "id": "bd49b944-9e77-4f45-9e8d-a9f44c162edb", | |
| "metadata": {}, | |
| "outputs": [ | |
| { | |
| "data": { | |
| "text/plain": [ | |
| "[<matplotlib.lines.Line2D at 0x136490a60>]" | |
| ] | |
| }, | |
| "execution_count": 9, | |
| "metadata": {}, | |
| "output_type": "execute_result" | |
| }, | |
| { | |
| "data": { | |
| "image/png": "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", | |
| "text/plain": [ | |
| "<Figure size 640x480 with 1 Axes>" | |
| ] | |
| }, | |
| "metadata": {}, | |
| "output_type": "display_data" | |
| } | |
| ], | |
| "source": [ | |
| "_G = (\n", | |
| " np.abs(dsG.G)\n", | |
| " .sortby(\"omega\")\n", | |
| " .sel(z=5, method=\"nearest\")\n", | |
| ")\n", | |
| " \n", | |
| "_G.plot(x=\"omega_cpd\")" | |
| ] | |
| }, | |
| { | |
| "cell_type": "code", | |
| "execution_count": 10, | |
| "id": "dd8dc86e-32c8-496c-a805-333820b579bd", | |
| "metadata": {}, | |
| "outputs": [], | |
| "source": [ | |
| "\n", | |
| "# assemble test dataset\n", | |
| "nt, dt = 24*60, 1/24\n", | |
| "ds = xr.Dataset(\n", | |
| " coords=dict(\n", | |
| " time=(\"time\", np.arange(nt)*dt)),\n", | |
| ")\n", | |
| "\n", | |
| "tau_0 = .01\n", | |
| "#noise = tau_0/10\n", | |
| "noise = 0\n", | |
| "ds[\"tau_x\"] = ((\"time\", ), np.random.randn(nt)*noise)\n", | |
| "ds[\"tau_y\"] = ((\"time\", ), np.random.randn(nt)*noise)\n", | |
| "#ds[\"tau_x\"] = ds[\"tau_x\"] + np.heaviside(ds[\"t\"]-ds[\"t\"].mean(\"t\"), .5)\n", | |
| "ds[\"tau_x\"] = ds[\"tau_x\"] + tau_0*(1+erf( (ds[\"time\"]-ds[\"time\"].mean(\"time\"))/.1 ))/2" | |
| ] | |
| }, | |
| { | |
| "cell_type": "code", | |
| "execution_count": 11, | |
| "id": "97336638-9551-44d3-9af7-3466f13189b9", | |
| "metadata": {}, | |
| "outputs": [ | |
| { | |
| "data": { | |
| "text/plain": [ | |
| "<matplotlib.collections.QuadMesh at 0x136518130>" | |
| ] | |
| }, | |
| "execution_count": 11, | |
| "metadata": {}, | |
| "output_type": "execute_result" | |
| }, | |
| { | |
| "data": { | |
| "image/png": "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", | |
| "text/plain": [ | |
| "<Figure size 640x480 with 2 Axes>" | |
| ] | |
| }, | |
| "metadata": {}, | |
| "output_type": "display_data" | |
| } | |
| ], | |
| "source": [ | |
| "ds = EkmanUnified_tseries(\n", | |
| " ds.tau_x, ds.tau_y, ds.time,\n", | |
| " z,\n", | |
| " h,\n", | |
| " delta,\n", | |
| " z0,\n", | |
| " latitude,\n", | |
| " rho,\n", | |
| " T_tapper=2, # in days\n", | |
| ")\n", | |
| "\n", | |
| "ds[\"U\"].real.plot(x=\"t\")" | |
| ] | |
| }, | |
| { | |
| "cell_type": "code", | |
| "execution_count": 12, | |
| "id": "81f5f48f-30b7-45f2-9d17-ddd4590ad7ed", | |
| "metadata": {}, | |
| "outputs": [ | |
| { | |
| "data": { | |
| "text/plain": [ | |
| "[<matplotlib.lines.Line2D at 0x1364d1a50>]" | |
| ] | |
| }, | |
| "execution_count": 12, | |
| "metadata": {}, | |
| "output_type": "execute_result" | |
| }, | |
| { | |
| "data": { | |
| "image/png": "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", | |
| "text/plain": [ | |
| "<Figure size 640x480 with 1 Axes>" | |
| ] | |
| }, | |
| "metadata": {}, | |
| "output_type": "display_data" | |
| } | |
| ], | |
| "source": [ | |
| "ds[\"U\"].sel(z=5, method=\"nearest\").real.plot(x=\"t\")" | |
| ] | |
| }, | |
| { | |
| "cell_type": "code", | |
| "execution_count": null, | |
| "id": "80ca4e5d-4fce-4407-b6c9-3fbdf0fbb52f", | |
| "metadata": {}, | |
| "outputs": [], | |
| "source": [] | |
| }, | |
| { | |
| "cell_type": "code", | |
| "execution_count": null, | |
| "id": "f8536b92-c673-4f30-8c89-ebb633931c2b", | |
| "metadata": {}, | |
| "outputs": [], | |
| "source": [] | |
| } | |
| ], | |
| "metadata": { | |
| "kernelspec": { | |
| "display_name": "Python 3 (ipykernel)", | |
| "language": "python", | |
| "name": "python3" | |
| }, | |
| "language_info": { | |
| "codemirror_mode": { | |
| "name": "ipython", | |
| "version": 3 | |
| }, | |
| "file_extension": ".py", | |
| "mimetype": "text/x-python", | |
| "name": "python", | |
| "nbconvert_exporter": "python", | |
| "pygments_lexer": "ipython3", | |
| "version": "3.10.14" | |
| } | |
| }, | |
| "nbformat": 4, | |
| "nbformat_minor": 5 | |
| } |
Sign up for free
to join this conversation on GitHub.
Already have an account?
Sign in to comment