From 22fcd16ca1d5d99f4c8d723a68a1fdc51e7f74a7 Mon Sep 17 00:00:00 2001 From: Nick Wogan Date: Mon, 30 Oct 2023 11:49:24 -0700 Subject: [PATCH] updated to 0.4.1 clima --- CMakeLists.txt | 2 +- examples/Tutorial_AdiabatClimate.ipynb | 1176 ------------------------ src/dependencies/CMakeLists.txt | 4 +- 3 files changed, 3 insertions(+), 1179 deletions(-) delete mode 100644 examples/Tutorial_AdiabatClimate.ipynb diff --git a/CMakeLists.txt b/CMakeLists.txt index 17016b9..325014c 100644 --- a/CMakeLists.txt +++ b/CMakeLists.txt @@ -1,6 +1,6 @@ cmake_minimum_required(VERSION "3.14") cmake_policy(SET CMP0148 OLD) -project(Photochem LANGUAGES Fortran C VERSION "0.4.3") +project(Photochem LANGUAGES Fortran C VERSION "0.4.4") include(FortranCInterface) FortranCInterface_VERIFY() diff --git a/examples/Tutorial_AdiabatClimate.ipynb b/examples/Tutorial_AdiabatClimate.ipynb deleted file mode 100644 index 8e828c1..0000000 --- a/examples/Tutorial_AdiabatClimate.ipynb +++ /dev/null @@ -1,1176 +0,0 @@ -{ - "cells": [ - { - "cell_type": "code", - "execution_count": 1, - "id": "8832d85e", - "metadata": {}, - "outputs": [], - "source": [ - "# Download clima so that we can access a template\n", - "from photochem import clima\n", - "import requests, zipfile, io\n", - "r = requests.get(\"https://github.com/Nicholaswogan/clima/archive/refs/tags/v\"+clima.__version__+\".zip\")\n", - "z = zipfile.ZipFile(io.BytesIO(r.content))\n", - "z.extractall(\".\")" - ] - }, - { - "cell_type": "markdown", - "id": "7e54bb54", - "metadata": {}, - "source": [ - "# AdiabatClimate\n", - "\n", - "`AdiabatClimate` is a simple 1-D climate model which assumes the atmosphere is made of a pseudo-moist adiabat troposphere connected to an isothermal stratosphere. The code accounts for gas condensation, which effects the temperature profile from released latent heat, and pretends that any condensed material immediately leaves the atmosphere." - ] - }, - { - "cell_type": "code", - "execution_count": 2, - "id": "bfb3a831", - "metadata": {}, - "outputs": [ - { - "data": { - "text/plain": [ - "" - ] - }, - "execution_count": 2, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "import numpy as np\n", - "import numba as nb\n", - "from matplotlib import pyplot as plt\n", - "from scipy import constants as const\n", - "\n", - "from photochem.clima import AdiabatClimate\n", - "\n", - "from threadpoolctl import threadpool_limits\n", - "threadpool_limits(limits=4) # set number of threads. Must come after import of AdiabatClimate" - ] - }, - { - "cell_type": "markdown", - "id": "7438096b", - "metadata": {}, - "source": [ - "## Initialization\n", - "\n", - "The model can be initialized with the following three files. Check out the `species.yaml` and `settings.yaml` files they are heavily commented to show all possible options. " - ] - }, - { - "cell_type": "code", - "execution_count": 3, - "id": "d44f06e3", - "metadata": {}, - "outputs": [], - "source": [ - "species_file = 'clima-'+clima.__version__+'/templates/runaway_greenhouse/species.yaml' # Species and their thermodynamic properties\n", - "settings_file = 'clima-'+clima.__version__+'/templates/runaway_greenhouse/settings.yaml' # Planet properties, and radiative transfer settings\n", - "star_file = 'clima-'+clima.__version__+'/templates/ModernEarth/Sun_Now.txt' # The stellar flux\n", - "\n", - "c = AdiabatClimate(species_file, \n", - " settings_file, \n", - " star_file)" - ] - }, - { - "cell_type": "code", - "execution_count": 4, - "id": "25c092dd", - "metadata": {}, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "['H2O', 'CO2', 'N2']\n" - ] - } - ], - "source": [ - "print(c.species_names) # species in the model" - ] - }, - { - "cell_type": "markdown", - "id": "f1f62fad", - "metadata": {}, - "source": [ - "## Constructing an atmosphere\n", - "\n", - "### `make_profile`\n", - "\n", - "Given the surface temperature and volatile inventories `AdiabatClimate` is able to draw a temperature profile and distribute gases in the atmosphere. One function that does this is `AdiabatClimate.make_profile`, which I illustrate below." - ] - }, - { - "cell_type": "code", - "execution_count": 5, - "id": "8a948ebd", - "metadata": {}, - "outputs": [], - "source": [ - "# P_i are the partial pressure \"reservoirs\" of each gas in in dynes/cm2. \n", - "# Order is the same as `c.species_names`.\n", - "P_i = np.array([\n", - " 260.0, # H2O\n", - " 10.0, # CO2\n", - " 1.0, # N2\n", - "])*1.0e6\n", - "T_surf = 280 # surface temperature (K)\n", - "\n", - "c.P_top = 1.0e-2 # pressure of top of the atmosphere (dynes/cm^2). \n", - "c.T_trop = 150 # tropopause temperature (K). \n", - "c.RH = np.ones(len(c.species_names)) # Relative humidity of each species. default is 1.0\n", - "\n", - "# Integrates a multispecies pseudoadiabat upward following\n", - "# Equation (1) in Graham et al. 2021 (doi.org/10.3847/PSJ/ac214c)\n", - "c.make_profile(T_surf, P_i)" - ] - }, - { - "cell_type": "markdown", - "id": "5407e0e7", - "metadata": {}, - "source": [ - "The object `c` now has attributes that describe the atmosphere\n", - "- `c.P`, pressures in atmospheric layers (dynes/cm$^2$)\n", - "- `c.P_surf` surface pressure (dynes/cm$^2$)\n", - "- `c.T`, temperature in atmospheric layers (K)\n", - "- `c.f_i`, mixing ratios of all species in atmospheric layers (2-D array)\n", - "- `c.z`, altitude of center of atmospheric layers (cm)\n", - "- `c.dz`, thickness of each atmospheric layers (cm)\n", - "- `c.N_atmos`, reservoir of each gas in the atmosphere (mol/cm$^2$)\n", - "- `c.N_surface`, reservoir of each gas on the surface (mol/cm$^2$)\n", - "- `c.N_ocean`, reservoir of each gas dissolved in oceans (mol/cm$^2$)\n", - "\n", - "Here are some illustrative plots:" - ] - }, - { - "cell_type": "code", - "execution_count": 6, - "id": "45eb1d50", - "metadata": {}, - "outputs": [ - { - "data": { - "image/png": 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", - "text/plain": [ - "
" - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], - "source": [ - "plt.rcParams.update({'font.size': 15})\n", - "fig,ax = plt.subplots(1,1,figsize=[5,4])\n", - "\n", - "for i in range(len(c.species_names)):\n", - " ax.plot(c.f_i[:,i], c.P/1e6, lw=2, label=c.species_names[i])\n", - "ax.set_yscale('log')\n", - "ax.set_xscale('log')\n", - "ax.set_ylim(c.P[0]/1e6,1e-5)\n", - "ax.legend(ncol=1,bbox_to_anchor=(1.1, 1.02), loc='upper left')\n", - "ax.grid()\n", - "ax.set_ylabel('Pressure (bar)')\n", - "ax.set_xlabel('Mixing ratio')\n", - "\n", - "ax1 = ax.twiny()\n", - "\n", - "ax1.plot(c.T, c.P/1e6, 'k--', lw=2, label='Temperature')\n", - "ax1.set_xlabel('Temperature (K)')\n", - "ax1.legend(ncol=1,bbox_to_anchor=(1.1, .3), loc='upper left')\n", - "ax1.set_xlim(130,300)\n", - "\n", - "plt.show()" - ] - }, - { - "cell_type": "markdown", - "id": "a2e9268c", - "metadata": {}, - "source": [ - "In the figure above, the tropopause is at $10^{-2}$ bars. Below that, in the troposphere, the slope of the temperature profile changes at about 3 bars pressure. This is caused by the start of CO$_2$ condensation.\n", - "\n", - "`c.N_atmos`, `c.N_surface` and `c.N_ocean` contains the reservoir of volatiles in mol/cm$^{2}$ in the atmosphere, surface, and dissolved in oceans. Only gases that are saturated at surface have a surface reservoir. In this case, only water has a surface reservoir, which can be thought of as an ocean. We have not included gas dissolution in oceans, so the model reports no dissolved gases. Later in this notebook we implement gas dissolution in oceans. " - ] - }, - { - "cell_type": "code", - "execution_count": 7, - "id": "6f88e513", - "metadata": {}, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "[4.70266896e-02 2.39196291e+02 2.43237880e+01]\n" - ] - } - ], - "source": [ - "print(c.N_atmos)" - ] - }, - { - "cell_type": "code", - "execution_count": 8, - "id": "efa46e52", - "metadata": {}, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "[14696.15911658 0. 0. ]\n" - ] - } - ], - "source": [ - "print(c.N_surface)" - ] - }, - { - "cell_type": "code", - "execution_count": 9, - "id": "17d3dd49", - "metadata": {}, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "[[0. 0. 0.]\n", - " [0. 0. 0.]\n", - " [0. 0. 0.]]\n" - ] - } - ], - "source": [ - "print(c.N_ocean)" - ] - }, - { - "cell_type": "markdown", - "id": "ff7f349f", - "metadata": {}, - "source": [ - "The surface pressure is about 11.01 bars from 10 bars of CO$_2$, 1 bar of N$_2$ and a little water vapor." - ] - }, - { - "cell_type": "code", - "execution_count": 10, - "id": "590609bd", - "metadata": {}, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "11.010013835389936\n" - ] - } - ], - "source": [ - "print(c.P_surf/1e6) # bars" - ] - }, - { - "cell_type": "markdown", - "id": "1962ff08", - "metadata": {}, - "source": [ - "### `make_column`\n", - "\n", - "`AdiabatClimate.make_column` is another function, similar to `AdiabatClimate.make_profile`, for constructing an atmosphere. The difference is that `AdiabatClimate.make_column` instead accepts column abundances of gases (mol/cm$^2$)." - ] - }, - { - "cell_type": "code", - "execution_count": 11, - "id": "85f5cbc8", - "metadata": {}, - "outputs": [], - "source": [ - "c.T_trop = 200 # change tropopause temperature\n", - "\n", - "T_surf = 280 # surface temperature (K)\n", - "N_i = np.array([15.0e3, 23.0, 36.0]) # mol/cm^2\n", - "c.make_column(T_surf, N_i)" - ] - }, - { - "cell_type": "markdown", - "id": "962484f4", - "metadata": {}, - "source": [ - "We can check that the total column abundances matches the inputs. Some water is on the ground." - ] - }, - { - "cell_type": "code", - "execution_count": 12, - "id": "d5c640cd", - "metadata": {}, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "[ 0.0640347 22.99999999 35.99999999]\n", - "[14999.9359653 0. 0. ]\n", - "[15000. 22.99999999 35.99999999]\n" - ] - } - ], - "source": [ - "print(c.N_atmos)\n", - "print(c.N_surface)\n", - "print(c.N_atmos+c.N_surface)" - ] - }, - { - "cell_type": "markdown", - "id": "7db7dbcc", - "metadata": {}, - "source": [ - "### `make_profile_bg_gas`\n", - "\n", - "The final function that constructs atmospheres is `AdiabatClimate.make_profile_bg_gas`. This function specifies a surface pressure and a background gas. The background gas is varied in abundance to allow for the specified surface pressure." - ] - }, - { - "cell_type": "code", - "execution_count": 13, - "id": "3e2edd10", - "metadata": {}, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "1999999.999999999\n" - ] - } - ], - "source": [ - "T_surf = 280 # surface temperature (K)\n", - "P_i = np.array([260.0, 1.0, 1.0])*1.0e6\n", - "P_surf = 2.0e6 # dynes/cm^2\n", - "bg_gas = 'N2'\n", - "c.make_profile_bg_gas(T_surf, P_i, P_surf, bg_gas)\n", - "\n", - "# Surface pressure\n", - "print(c.P_surf)" - ] - }, - { - "cell_type": "markdown", - "id": "cade340e", - "metadata": {}, - "source": [ - "The model will fail if you specify a surface pressure that can not be satisfied. For example, a 0.5 bar atmosphere is not possible with these inputs because there must be at least 1 bar of CO$_2$ in the atmosphere." - ] - }, - { - "cell_type": "code", - "execution_count": 14, - "id": "e32ceb9e", - "metadata": {}, - "outputs": [], - "source": [ - "# Uncoment and run to see the error\n", - "# P_surf = 0.5e6 # dynes/cm^2\n", - "# c.make_profile_bg_gas(T_surf, P_i, P_surf, bg_gas)" - ] - }, - { - "cell_type": "markdown", - "id": "98b4c13c", - "metadata": {}, - "source": [ - "## Radiative transfer\n", - "\n", - "So far this notebook has shown a variety of methods (`make_profile`, `make_column`, and `make_profile_bg_gas`) for constructing atmospheres. `AdiabatClimate` had complementary methods which construct atmosphere, then subsequently compute shortwave and long-wave radiative transfer.\n", - "\n", - "- `AdiabatClimate.TOA_fluxes` calls `AdiabatClimate.make_profile` then does radiative transfer on the constructed atmosphere.\n", - "- `AdiabatClimate.TOA_fluxes_column` calls `AdiabatClimate.make_column` then does radiative transfer on the constructed atmosphere.\n", - "- `AdiabatClimate.TOA_fluxes_bg_gas` calls `AdiabatClimate.make_profile_bg_gas` then does radiative transfer on the constructed atmosphere.\n", - "\n", - "Each function returns the incoming solar energy and outgoing long-wave energy at the top of the atmosphere. In the examples below I use `TOA_fluxes`, but the other two functions work in a very similar way." - ] - }, - { - "cell_type": "code", - "execution_count": 15, - "id": "e772b520", - "metadata": {}, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "254840.78215888917\n", - "246722.76354168897\n" - ] - } - ], - "source": [ - "P_i = np.array([260.0, 400.0e-6, 1.0])*1.0e6\n", - "T_surf = 280\n", - "c.T_trop = 215\n", - "c.RH = np.ones(len(c.species_names))\n", - "\n", - "# Call TOA fluxes\n", - "ISR, OLR = c.TOA_fluxes(T_surf, P_i)\n", - "print(ISR) # mW/m^2\n", - "print(OLR) # mW/m^2" - ] - }, - { - "cell_type": "markdown", - "id": "5c0572f2", - "metadata": {}, - "source": [ - "### The runway greenhouse limit and inner edge of the habitable zone\n", - "\n", - "We can use these functions to compute the famous \"runaway greenhouse limit\". This is the maximum radiation that a steam-dominated atmosphere can emit based on the optical properties of water. [Goldblatt et al. (2013)](https://doi.org/10.1038/ngeo1892) is a good paper that explains this phenomenon in more detail." - ] - }, - { - "cell_type": "code", - "execution_count": 16, - "id": "220d1439", - "metadata": {}, - "outputs": [], - "source": [ - "# Lets check the runway greenhouse limit\n", - "P_i = np.array([200.0, 1.0e-10, 1.0])*1.0e6\n", - "TT = np.linspace(216,2000,100)\n", - "OLR = np.empty(TT.shape[0])\n", - "ISR = np.empty(TT.shape[0])\n", - "for i,T in enumerate(TT):\n", - " ISR_, OLR_ = c.TOA_fluxes(T, P_i)\n", - " OLR[i] = OLR_/1.0e3\n", - " ISR[i] = ISR_/1.0e3" - ] - }, - { - "cell_type": "code", - "execution_count": 17, - "id": "06faf3e6", - "metadata": {}, - "outputs": [ - { - "data": { - "image/png": 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", - "text/plain": [ - "
" - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], - "source": [ - "plt.rcParams.update({'font.size': 15})\n", - "fig,ax = plt.subplots(1,1,figsize=[5,4])\n", - "\n", - "ax.plot(TT,OLR,lw=2, label='Outgoing longwave')\n", - "ax.plot(TT,ISR,lw=2, label='Incoming shortwave')\n", - "\n", - "ax.grid()\n", - "ax.set_ylabel('Flux (W m$^{-1}$)')\n", - "ax.set_xlabel('Surface Temperature (K)')\n", - "ax.legend(ncol=1,bbox_to_anchor=(0, 1.02), loc='lower left')\n", - "ax.set_ylim(100,400)\n", - "ax.set_xlim(min(TT),max(TT))\n", - "\n", - "plt.show()" - ] - }, - { - "cell_type": "markdown", - "id": "2cf35360", - "metadata": {}, - "source": [ - "In the plot above, you can see that the outgoing long-wave radiation plateaus for 500 K < T < 1700 K. This is the runway greenhouse limit." - ] - }, - { - "cell_type": "code", - "execution_count": 18, - "id": "b606d0e5", - "metadata": {}, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Runway greenhouse limit = 291.051421 W/m^2\n" - ] - } - ], - "source": [ - "P_i = np.array([200.0, 1.0e-10, 1.0])*1.0e6\n", - "ISR, OLR = c.TOA_fluxes(1000, P_i)\n", - "print(\"Runway greenhouse limit = %f W/m^2\"%(OLR/1e3))" - ] - }, - { - "cell_type": "markdown", - "id": "ca75e813", - "metadata": {}, - "source": [ - "The runway greenhouse limit marks the inner edge of the [habitable zone](https://en.wikipedia.org/wiki/Circumstellar_habitable_zone), or the distance from a star that liquid water can persist on a planet. \n", - "\n", - "We can compute the quantity $S_\\mathrm{eff}$, which is the fraction of the Modern solar constant required to maintain a give surface temperature. This can be converted to a distance from the sun in AU (astronomical units) with $d = \\sqrt{1/S_\\mathrm{eff}}$.\n", - "\n", - "Below we compute $S_\\mathrm{eff}$ at the runaway greenhouse limit, and with it, find the inner edge of the habitable zone to be at 0.97 AU. This matches results from [Kopparapu et al. (2013)](https://doi.org/10.1088/0004-637X/765/2/131)." - ] - }, - { - "cell_type": "code", - "execution_count": 19, - "id": "5c6270a3", - "metadata": {}, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Inner edge of the habitable zone 0.97 AU\n" - ] - } - ], - "source": [ - "S_eff = OLR/ISR\n", - "d_IHZ = np.sqrt(1/S_eff)\n", - "print('Inner edge of the habitable zone %.2f AU'%(d_IHZ))" - ] - }, - { - "cell_type": "markdown", - "id": "f4d0cd68", - "metadata": {}, - "source": [ - "You can also look at the radiation as a function of wavelength. Here we consider a case that roughly reproduces Fig. 1c, 300 K case in [Goldblatt et al. (2013)](https://doi.org/10.1038/ngeo1892)" - ] - }, - { - "cell_type": "code", - "execution_count": 20, - "id": "d445df9c", - "metadata": {}, - "outputs": [ - { - "data": { - "image/png": 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ggMzMTK4zQGQGbvPdcDv7NlztXJESon92MHNQq9VITk6Gh4dHqaesKy/HQERUVWRkZMDR0dFs52uS7gx069YNCxcuxL1791CnTh0MGDAANjY2+OKLL3Dr1i24ubnh119/xb179zBu3Di5YyYiIiIiIhlISgaGDRuGW7du4dKlS6hTpw5q1qyJZcuWYdSoUZgzZw4EQYAoimjevHmFGy9ARERERFRVSEoGfH198dtvv+mUvfXWW+jUqRO2b9+O9PR0NGnSBAMGDOAgVyIiIiKickryCsT6eHh44IMPPpCzSSIiIiIiMhFJ6wwQEREREVHFZ9Cdgf379wMA2rdvDysrK+1rQ3Xp0qX0kRERERERkUkZlAwEBARAEARcunQJTZo00b42VEFBgeQAiYiIiIjINAxKBkaMGAFBEODg4KDzmoiIiIiIKi6DkoGVK1cW+5qIiIiIiCoeDiAmIiIiIqqimAwQEREREVVRBj0mNH36dMkdCIKA0NBQyfsTEREREZFpGJQMTJs2DYIgQBRFnfIXBxFrtv2zjMkAEREREVH5ZFAysGLFikJlhw4dwk8//QQPDw8EBQXBw8MDAJCcnIyoqCjcvHkT7777Ljp27ChvxEREREREJAuDkoGRI0fqvD5y5Ajef/99hIaGIiwsDBYWFjrbv/vuO0RERGD27NkIDg6WLVgiIiIiIpKPIP7z2R8D/Otf/8K9e/dw5syZYuv5+vqiTp06+PvvvyUHSPLJysqCg4MDMjMzYW9vX9bhEFV6bvPdcDv7NlztXJESklJmcajVaiQnJ8PDwwMKRenmjdAcg0JQwMXWxeD97JR2iAiMQFCzoNKGS0RUpWVkZMDR0dFs52sG3Rn4p2PHjqFv374l1mvRogViYmKkdEFEROWAndIOyAbUohq3s28bvmM2EBobymSAiKick5QMAEBCQoIsdYiIqPyKCIxAaGwosvOyDd5HlaOCWlSXah8iIiobkpIBf39/7NixA3PmzMGXX36pt87cuXNx6tQpvPbaa0YFSEREZSeoWVCpr+5rHi0iIqLyT1IyMHPmTOzduxdfffUVVqxYoZ1NSBAE3Lx5E1FRUUhISED16tUxc+ZMuWMmIiIiIiIZSEoGfHx8sHv3bgQHByMhIQEzZszQri+gGY/cpEkTrFy5Ej4+PvJFS0REREREspE8ZuDVV1/FxYsXsXfvXhw4cAB37tyBKIqoV68e/P39ERgYqLMAGRERERERlS+SkwHg+WrDgYGBCAwMlCseIiIiIiIyk9JNOE1ERERERJWGUXcGAODChQu4cuUKsrOzUdT6ZSNGjDC2GyIiIiIikpnkZGDXrl348MMPkZSUVGQdURQhCAKTASKqdDZc2ICwvWHFzqWvylGZMSIiIqLSk/SY0PHjx9G3b18kJyfj7bffxiuvvAIA+OqrrzB06FA4OjoCAEaNGoWwsDD5ojWjEydOYPbs2Rg8eDBcXV0hCAKsrKyKrC8IQolf3bp1M7j/4ODgYtv6z3/+I8dhEpFEYXvDkJCWgNvZt4v8UotqAP9/FV8iIqJySNKdgVmzZiE/Px9//vknevbsiVGjRuHcuXP49ttvAQAZGRl4//33sW3bNhw/flzWgM0lIiICW7ZsMbj+yJEji9wWExODtLQ0dO7cudRx9OrVC3Xr1i1U3rRp01K3RUTy0dwRUAgKuNi6FFnPTmmHiMAIc4VFRERUKpKSgUOHDqFVq1bo2bOn3u01atTA6tWr0aBBA0yZMgWrVq0yKsiy4OfnB19fX7Rr1w7t2rXTe0L+opUrV+otz8jIwO+//w4AGD58eKnj+OqrrxAQEFDq/YjIPFxsXZASklLWYRAREUkiKRl4+PAhunbtqn1drVo1AMCjR49gY2MDAFAqlejcuTN27twpQ5jmN2nSJFna2bBhA/Ly8tChQwc0btxYljaJiIiIiOQgacyAs7MzsrKydF4DwLVr13TqPXnyBJmZmUaEV/H9+uuvAIB33nmnjCMhIiIiItIl6c5Ao0aNdGYRat++PURRxLJly7BkyRIAwNWrV7Fnzx40bNhQnkgroOTkZMTFxcHS0hJvvPGGpDY2bdqEqKgoFBQUwNPTE/3794e3t7fMkRIRERFRVSQpGXjttdfw1Vdf4fz582jRogV69+6N+vXr48cff0R8fDzc3NywZ88e5ObmYsyYMXLHXGGsWbMGoiiiT58+qFWrlqQ2fvjhB53XkyZNwrhx47Bo0SK89FLxP768vDzk5eVpX2vu5qjVaqjVaknxEFFh5f39pHnPl0Wc5f17Q0RU3pj7c1NSMjBixAg4ODhAEAQAz8cM/PHHH/i///s/xMfHIz4+HgqFAmPHjsWnn34qa8AViTGPCLVq1Qp+fn7o1q0b3NzccPfuXezYsQNTpkzB0qVLUa1aNSxYsKDYNmbNmoXw8PBC5bdu3YKdHac6JDJGQUGB9t/k5OQyjqZ4oigiPT1dOzWxqVWk7w0RUXnz4qP45iCIRS0bLFFCQgLS09PRqFEj7ViCykAQBCiVSuTm5hpU/+TJk2jTpg1q1KiBu3fvQqlUyhLH+fPn0aZNGxQUFOD69etwd3cvsq6+OwPu7u5IT0+Hvb29LPEQVVUeCz1wO/s2XO1ckfxZ+T7hVavVSE5OhoeHBxQKSUPFSqUifW+IiMqbjIwM1KpVC5mZmWY5X5N0Z2Dx4sWoXr06xo4dW2gbn2d/TnNXYOjQobIlAgDQokULDBgwABs3bsSuXbswatSoIusqlUq9fSsUCrOcEBBVFRXh/aR535s71orwvSEiKk/M/jktZafPP/8cW7dulTuWSqOgoMCotQVKopmiVKVSyd42EREREVUdkpKBunXrwsrKSu5YKo3du3dDpVKhfv36klYdLkl6ejoAwNbWVva2iYiIiKjqkJQM9OrVCwcOHMDTp0/ljqdS0DwiNHz4cNkH6+Xl5SEmJgYA0KZNG1nbJiIiIqKqRVIy8O2338LCwgLDhg3joyr/8PjxY0RHRwMo+RGhY8eOwdvbG927d9cpT0xMxJYtW7QzcmikpqbizTffxK1bt+Dr64uOHTvKGzwRERERVSmSBhBPnjwZvr6+2LRpE2JiYtC6dWt4eHjofXRIEAQsX77c6EDNLSYmBhERETplT58+RYcOHbSvQ0ND0bdvX506mzdvRk5ODtq1a1fiYOrHjx8jMTGx0AxFKpUKAwcORK1ateDt7Q1XV1fcv38fJ06cQHZ2Ntzc3LB+/XqzTBFIRERERJWXpGRg5cqV2v/n5ubi0KFDOHTokN66FTUZSE1NxdGjR3XKRFHUKUtNTS2034uPCEnVpEkTfPbZZzhy5AiSkpJw7NgxKJVKNGnSBP3798enn34KR0dHye0TEREREQESk4HY2Fi54yh3goODERwcXOr9tm/fbnDdgIAA6FvmoV69eiUuKEZEREREZCxJyUDXrl3ljoOIiIiIiMyMq8EQEREREVVRTAaIiIiIiKooJgNERERERFWUpDEDREREJVHlqOA2363U+9kp7RARGIGgZkEmiIqIiF7EZICIiGRlp7QDsgG1qMbt7NulbyAbCI0NZTJARGQGTAaIiEhWEYERCI0NRXZedqn3VeWooBbVkvYlIqLSYzJARESyCmoWJPmqvtt8N2l3E4iISBIOICYiIiIiqqIMujOwf/9+ozrp0qWLUfsTEREREZH8DEoGAgICIAiC5E4KCgok70tERERERKZhUDIwYsQIo5IBIiIiIiIqfwxKBlauXGniMIiIiIiIyNw4gJiIiIiIqIpiMkBEREREVEUZtc7A48ePERsbiytXriA7OxuiKBaqIwgCQkNDjemGiIiIiIhMQHIysHLlSkyYMAFZWVnaMlEUdQYaa14zGSAiIiIiKn8kPSa0a9cujBkzBoIg4Ouvv4afnx8AYNmyZfjyyy/RqFEjiKKI8ePHIzIyUtaAiYiIiIhIHpKSgXnz5kEQBMTGxiIiIgKNGzcGALz77ruYPXs2Ll68iM8++wyRkZFo06aNrAETEREREZE8JCUD8fHx6NChA3x9ffVut7CwwNy5c1G7dm1MnTrVqACJiIiIiMg0JCUDOTk58PDw0L62srICAGRnZ/+vYYUCr776KuLi4owMkYiIiIiITEFSMlC3bl2kpaXpvAaAy5cv69R7+PAhnjx5YkR4RERERERkKpKSAW9vb50T/44dO0IURXz33Xfa6UUPHTqEPXv2oGnTpvJESkREREREspKUDPTt2xfJyck4cuQIAKB79+7w8fFBVFQUXF1d0aZNGwQGBkKtVuOzzz6TM14iIiIiIpKJpGRgxIgR2LFjB1xcXJ43olAgJiYGPXv2xP3793Hq1ClUr14dM2bMwPDhw2UNmIiIiIiI5CFp0TEHBwf06tVLp8zV1RV//vknHj9+jMzMTNSuXRsWFhayBElERERERPKTdGegONWrV4eLi4vJEoFnz57h/PnziI2NxebNmxEbG4vz58/j2bNnsvZz4sQJzJ49G4MHD4arqysEQdDOmqTPtGnTIAhCkV9fffVVqWNQq9VYuHAhXnnlFVhbW8PZ2RlDhw7FxYsXjTk0IiIiIiIAEu8MmFtqaipWrlyJmJgYHDt2DHl5eYXqWFlZoX379ujbty9GjhwJZ2dno/qMiIjAli1bSr1fp06d0KhRo0LlpV18TRRFvPHGG9i4cSNq1KiBvn37Ii0tDVFRUYiJiUFsbCxeffXVUsdHRERERKQhORlITU3F0qVLsW/fPqhUKr0n6AAgCAKSkpIk9XHlyhWEhYUhOjoaT58+BQA4OTmhTZs2qFmzJuzt7ZGZmYn09HQkJCRg37592LdvH6ZMmYLBgwdj+vTpek/MDeHn5wdfX1+0a9cO7dq1006fWpKxY8ciODhYUp8vWrFiBTZu3IjGjRsjLi4OderUAQBERUUhKCgIw4YNQ0JCAl56qULkc0RERERUDkk6kzx37hy6deuGhw8faqcSldvHH3+M//73vygoKEBgYCDefvttBAQEwNPTs8h9rl27htjYWKxduxbr169HVFQU3nvvPfzwww+l7n/SpEnGhG+0efPmAQC+//57bSIAAEOGDMGAAQPwxx9/YMuWLRgyZEhZhUhEREREFZykMQOfffYZHjx4gHfeeQdnzpxBTk4O1Gp1kV9SLF++HOPGjUNycjJ27tyJUaNGFZsIAEDDhg0xZswY7N69Gzdv3sQHH3yAyMhISf2XpevXr+PixYuwtrZG3759C20PCgoCAGzdutXcoRERERFRJSLpzsCRI0fg4+ODlStXyhzO/1y7ds3gR3P0cXV1xaJFizB58mQZoyrZnj17cPr0aeTm5sLNzQ19+vQp9XiBM2fOAABatGgBS0vLQttbt26tU4+IiIiISApJyYCtrS0aN24sdyw6jEkETNGOoX755Red16GhoRgyZAhWrlwJW1tbg9pITk4GALi5uendrinX1CtKXl6ezliOrKwsADDqjg0RFVbe30/G3qktKxUtXiIiOZj7s09SMtCtWzccP35c7lgqtEaNGmHu3Lno06cP6tevj/T0dOzfvx8TJ05EVFQUCgoKEB0dbVBbOTk5AJ5P06qPjY2NTr2izJo1C+Hh4YXKb926BTs7O4NiISL9CgoKtP+WlJiXNVEUkZ6erp3quDyrSN9XIiJT0Fy8NRdJycCMGTPg5+eHiRMnYvbs2VAoZF+uoML550rLNjY2ePvttxEYGIhXXnkFmzdvxqFDh9CxY8cS29IMyjb2j/bkyZMREhKifZ2VlQV3d3e4u7vD3t7eqLaJqjrNWioWFhbw8PAo42iKp1arIYoi3N3dy/3ndUX6vhIRmUJGRoZZ+5OUDHh5eeHQoUN4/fXXsXnzZgQEBGgX5vonQRAQGhpqdKAaly5dQt++fXHt2jXZ2jQlFxcXjBo1CnPnzsVff/1lUDKguWr/6NEjvds15SU9dqRUKqFUKguVKxSKcn9CQFSRVIT3k+Z9XxFi1ahIsRIRycXcn32SkoFnz57h22+/RUJCAkRRxNWrV4usK3cy8PTpU9y8eVO29sxBM75CpVIZVF9zNSwlJUXvdk05r5oRERERkTEkJQNTpkzBqlWrUKdOHQwbNgwNGzbUPsdurOnTpxe7/e7du7L0Y07p6ekASr6Sr+Hr6wsAOH/+PJ49e1ZoRqGTJ08CAHx8fGSMkoio/FDlqOA2X/8kCsWxU9ohIjACQc2CTBAVEVHlIykZWLNmDZydnXHmzBnUrl1b1oCmTZsGFxcXVKtWTe92zUrEFYUoitqBw4ZOMerp6YmXX34Zly5dQkxMDAYOHKizfePGjQCAfv36yRorEVFZs1PaAdmAWlTjdvbt0jeQDYTGhjIZICIykKSHktLT0+Hv7y97IgA8f/Rl4cKFuH79ut6vmJgY2fs0VlpaGlavXq0zjSfwfLafcePG4ejRo6hbty4GDRqks/3YsWPw9vZG9+7dC7WpGfg7ceJE3L9/X1u+adMm/PHHH/D09CyUJBARVXQRgRHwdvKGq51rqb8UwvM/adl52WV8FEREFYekOwPNmzfHvXv35I4FANCyZUucPn0aQ4cO1btdEATtbDumFBMTg4iICJ2yp0+fokOHDtrXoaGh6Nu3L3JycjBy5Eh8/PHHePnll+Hh4YGMjAycPHkSDx48QI0aNbBx48ZCU4U+fvwYiYmJyM3NLdT/6NGjsX37dkRHR2sThrS0NOzbtw9WVlb49ddf9S5IRkRUkQU1C5J8Vd9tvpu0uwlERFWYpGTg888/xzvvvGPwVJmlbbu4+fMbNWqE2NhYWfvUJzU1FUePHtUpE0VRpyw1NRUAUKtWLUyaNAlHjhzB1atXcfr0aVhYWMDT0xPBwcGYMGECXF1dS9W/QqHAhg0bsGjRIkRGRmLbtm2wsbHBoEGDMH36dDRv3tz4gyQiIiKiKk0QJVxmT05OxsKFCxEZGYmQkBD06NGjyKlFAc56U15kZWXBwcEBmZmZXGeAyEiaq9Cudq5ICdE/81d5oVarkZycDA8Pj0o9XWdF+pkQERUlIyMDjo6OZjtfk3RnoEGDBtrHdcLDw/WucqshCALy8/MlB0hERERERKYhKRno0qWL2Za0T01NxaRJkxAZGWmW/oiIiIiIqgpJycDevXtlDqNoWVlZWLVqFX7++edKfXubiIiIiMjcJJ1dDx48GOPHj5c7FiIiIiIiMiNJdwa2b9/OOe6JqNLZcGEDwvaGGTRPvSpHZYaIiIiITEtSMuDp6YlHjx7JHQsRUZkK2xuGhLSEUu1jp7QzUTRERESmJykZeOuttzB37lzcvXsXdevWlTsmIqIyobkjoBAUcLF1KbG+ndIOEYERJdYjIiIqryQlA5MnT8bRo0fRtWtXzJ49G/369eNquERUabjYunCeeiIiqhIkJQNNmzaFWq3GrVu3EBQUBEEQULt2bVhZWRWqKwgCkpKSjA6UiIiIiIjkJSkZuHHjhs5rURRx9+5dOeLRS8IiyUREREREVAJJyYBarZY7jiLVrFkTU6dO5RoDREREREQyK/dn2I6Ojpg6dWpZh0FEREREVOmU+2SAiIiIiIhMw6hkYMeOHRg4cCBcXV2hVCoxZswYnW0hISG4c+eO0UESEREREZH8JI0ZAIAPP/wQy5YtgyiKsLOzw7Nnz3QG+taoUQMLFy6Em5sbQkJCZAkWeD54ef/+/VCpVMjLy9NbRxAEhIaGytYnEREREVFlJCkZiIyMxH/+8x+8+uqrWLZsGXx8fAoN8PXz84Orqyu2bt0qSzKQm5uLd999F2vXrgVQ/AxDTAaIiIiIiEomKRlYtmwZatasiW3btqFWrVpF1mvUqBGuXbsmObgXTZo0CWvWrEHt2rUxbNgweHl5wcbGRpa2iYiIiIiqIknJwIULFxAYGFhsIgAAdevWxZEjRyQF9k/r1q2Dk5MTTp8+jbp168rSJhERERFRVSZpALFCoTBorYE7d+7IdvU+JycHnTt3ZiJARERERCQTScmAt7c3jh8/jsePHxdZ58GDBzh9+jR8fHwkB/ei5s2b4969e7K0RUREREREEpOBYcOGITU1FR999BHy8/MLbRdFEZ988glycnLwzjvvGB0kAHzxxRc4duwYDh06JEt7RERERERVnaQxAx9++CGioqKwatUqHDhwAL169QIAnD17Fl988QW2bduGy5cvo1u3bhg5cqQsgQ4dOhQpKSl4/fXX8fHHH6NHjx5wdXWFIAh663t4eMjSLxERERFRZSUpGbC0tMSff/6JL774AsuXL8fSpUsBACdPnsTJkydhYWGBMWPGYPHixYWmHDWGj48PHB0dER4ejvDw8CLrCYKg944FERERERH9j+RFx6pXr46lS5ciPDwc+/btw40bN1BQUAA3NzcEBgaiXr16csaJbdu2YfDgwcjPz4ezszPq16/PqUWJiIiIiIwgORnQcHZ2RlBQkByxFGvq1KkQRRErVqzAiBEjinw8iIiIqjZVjgpu890MqmuntENEYASCmpn+7xgRUXlkdDJgLpcuXUKXLl1kG4NARESVi53SDsgG1KIat7NvG7ZTNhAaG8pkgIiqLKOSgb1792L//v1QqVTIy8vTW0cQBCxfvtyYbgAATk5OsLW1NbodQ504cQI7d+7EsWPHcPToUdy5cwdKpRK5ubmF6qrVahw8eBBbt27Fvn37cP36dWRmZsLNzQ09e/bEpEmT4OnpWar+g4ODsWrVqiK3//jjj/jggw9KfVxERJVVRGAEQmNDkZ2XbVB9VY4KalFtcH0iospIUjKQmZmJ119/HXFxcRBFsdi6ciUDQUFBWLNmDbKysmBvb290eyWJiIjAli1bDKp77do1dOnSBQDg6uqKjh07QqFQ4NixY1i2bBnWrl2L7du3w9/fv9Rx9OrVS+9Ca02bNi11W0RElVlQs6BSXeF3m+9m+B0EIqJKSlIyMGnSJOzfvx+NGjXCuHHj0KRJE5NftZ8xYwYOHz6MwYMH46effir1lfbS8vPzg6+vL9q1a4d27doVu/KxIAjo1asXvv76a21SAAB5eXn44IMPsHLlSgwbNgxXr16FpaVlqeL46quvEBAQIPUwiIiIiIiKJCkZ2LJlC+rUqYMjR46gZs2acsekV79+/WBhYYHY2Fg0bdoUDRo0KHKdAUEQsHv3bqP6mzRpksF1vby88OeffxYqVyqV+PHHHxEdHY3k5GQcOnQIXbt2NSouIiIiIiK5SH5MqE+fPmZLBIDn4xM08vPzcfXqVVy9elVv3fI005CVlRWaNGmC+Ph43Llzp6zDISIiIiLSkpQMNG7cGKmpqXLHUqzr16+btT+5FBQU4ObNmwBQ7KNGRdm0aROioqJQUFAAT09P9O/fH97e3nKHSURERERVkKRk4OOPP8b48eNx7tw5vPLKK3LHpFf9+vXN0o/cfv/9d9y/fx/Ozs7o2LFjqff/4YcfdF5PmjQJ48aNw6JFi/DSS8X/+PLy8nRmecrKygLwfPYjtVpd6liIqpLK9B7RvOcr0zHJjd8bIiovzP15JCkZGDt2LK5cuYI+ffpgxowZ6NmzJ1xdXeWOTcfhw4fh4+NToVYdvnXrFj777DMAwPTp06FUKg3et1WrVvDz80O3bt3g5uaGu3fvYseOHZgyZQqWLl2KatWqYcGCBcW2MWvWLISHh+uNy87OrlTHQlQVFBQUaP9NTk4u42jkI4oi0tPTIQhCuXqMsqxV1p83EVVsmou35iKIJc0NCsDCwkJvuSiKJf5hEQQB+fn50qJ7gUKhgEKhgJeXF1q2bKnz5eLioq333nvvoU2bNnj//feN7vNFgiAUuc6APo8ePULXrl1x4sQJDBw4ENHR0bLEcf78ebRp0wYFBQW4fv063N3di6yr786Au7s70tPTzTI9K1FF47HQA7ezb8PVzhXJn1Wek0O1Wo3k5GR4eHhAoVCUdTjlRmX9eRNRxZaRkYFatWohMzPTLOdrBt0ZcHd3L/OrSW+99RbOnDmDxMREXLlyBRs2bNDG5OTkhJYtW8LLywvR0dHYunWr7MlAaTx79gxDhgzBiRMn4O/vj7Vr18rWdosWLTBgwABs3LgRu3btwqhRo4qsq1Qq9d6N0CRWRFS0yvYe0bzvK9txyYXfFyIqL8z9eWRQMnDjxg0Th1GyNWvWAHh+tfvcuXM4ffq09is+Ph47d+7Erl27IIpisVfLTU2tVmP48OH466+/4Ovri61bt8La2lrWPho3bgwAUKlUsrZLRERERFWLpDEDZUmpVKJt27Zo27attiwzMxMrVqzAN998g1deeQWrV68us/g+/PBDrF+/Hk2aNMHff/+NGjVqyN5Heno6AJh8oTciIiIiqtwk3Yfo1q0bvv/++xLrzZ07F926dZPSRak4ODjgs88+w++//474+HicO3fO5H3q8/XXX2PZsmXw8PDAzp07Ubt2bdn7yMvLQ0xMDACgTZs2srdPRERERFWHpGRg7969SEhIKLFeYmIi9u3bJ6ULSfr374+mTZti5syZZutTY/78+Zg1axbq1q2LXbt2wcPDo8R9jh07Bm9vb3Tv3l2nPDExEVu2bNHOdKGRmpqKN998E7du3YKvr6+kqUqJiIiIiDRM+phQbm5uiXPhy61hw4bYs2eP0e3ExMQgIiJCp+zp06fo0KGD9nVoaCj69u2L06dP44svvgAAeHp64ttvv9Xb5tixY+Hv7699/fjxYyQmJhaaoUilUmHgwIGoVasWvL294erqivv37+PEiRPIzs6Gm5sb1q9fX+aDuomIiIioYjPZmXpWVhYOHTqkM+2nMT799FO0atUKrVq1QvPmzYtMMpKSkiSt9PtPqampOHr0qE6ZKIo6ZZpVmDMyMqCZofXw4cM4fPiw3jYDAgJ0koGiNGnSBJ999hmOHDmCpKQkHDt2DEqlEk2aNEH//v3x6aefwtHRUeqhEREREREBKEUy0LBhQ53XGzduxN69e/XWzc/Px71795Cfn4/x48cbFaDGDz/8oL0SbmlpiebNm2uTgxYtWkCpVOLXX3/F5cuX8eOPPxrdX3BwMIKDgw2qGxAQAAOWazB4v3r16pW4oBgRERERkbEMTgZenF5UEATk5OQgJydHb11LS0vUq1cPAwYMwKxZs4wOEgA2bdqEU6dOFfr656MyjRo1woMHD/Dnn3+idevWJhnES0RERERUGRicDKjVau3/FQoFgoODERkZaZKg9Bk4cCAGDhyofZ2WllYoMbh69SquXLmCKVOmaOu5uLigTZs22LJli9liJSIiIiKqCCSNGVixYgUaNWokdyyl4uTkhJ49e6Jnz57askePHuHMmTM6CcKFCxewbdu2MoyUiIiIiKh8kpQMjBw5Uu44ZGFjY4OOHTvqTLmZn5+PCxculGFURERERETlk6R1BiqSl156Cb6+vmUdBhERERFRuVPpkwEiIiIiItKPyQARERERURXFZICIiIiIqIpiMkBEREREVEUxGSAiIiIiqqIkTS36oocPH+LEiRNIS0tD/fr1dab1JCIiIiKi8kvynYF79+7hjTfeQJ06ddC7d28MHz4cP//8s3b70qVLUbNmTcTFxZW67Q0bNmDo0KEYN24czpw5o7MtLS0NDRs2lBo2ERERERH9f5KSgbS0NHTs2BEbNmyAj48PPvroI4iiqFNn4MCByM7OxsaNG0vV9tq1a/Hmm2/i8ePHOHv2LF599VWsXr1au72goAA3b96UEjYREREREb1AUjIQERGB69evY/r06Thx4gQWL15cqE69evXw8ssvY//+/aVqe/78+fjuu+8QExODgwcPYtmyZXj//ffxyy+/SAmViIiIiIiKIGnMwB9//IGXX34ZU6ZMKbZe/fr1ceTIkVK1ffnyZQwePFj7euTIkahRowbefPNNWFlZoUuXLlJCJiIiIiKif5B0Z0ClUqFFixYl1rOyskJ2dnap2rayskJ6erpO2euvv44VK1Zg5MiR+OOPP0rVHhERERER6SfpzoCDgwNu375dYr0rV66gbt26pWq7RYsWOHDgANq0aaNT/uabbyI7OxsffvhhqdojIiIiIiL9JN0Z6NixI44dO4YLFy4UWefgwYM4e/ZsqR/rGTFiBI4fP65327vvvovvvvsOHh4epWqTiIiIiIgKk5QMfP755ygoKMCAAQOwe/duqNVqne0HDhzAO++8g5deegkTJkwoVdvBwcHFDhYOCQnB9evXpYRNREREREQvkJQM+Pv7Y8GCBbh58yb+9a9/oWbNmhAEAZs2bYKzszO6du2K5ORkLFy4EK1atZI7ZiIiIiIikoHkFYg/+eQTtG/fHrNnz8aePXsgiiKysrKgVCrxr3/9C19//TU6d+4sZ6xERESyU+Wo4DbfTdK+dko7RARGIKhZkMxRERGZh6Rk4OzZs1AoFOjQoQM2b94MURTx4MEDFBQUwMnJCRYWFrIFmJqaikmTJiEyMlK2NomIiOyUdkA2oBbVuJ1d8qQYemUDobGhTAaIqMKSlAy0bNkSXbt2RWxsLABAEAQ4OTnJGphGVlYWVq1ahZ9//hkKhaSnmoiIiAqJCIxAaGwosvNKNwW2hipHBbWolrw/EVF5ICkZqFmzJurVqyd3LERERGYT1CzIqCv6bvPdpN9RICIqJyRdau/QoQPOnTsndyxERERERGRGkpKBqVOnIjExEfPmzZM7HiIiIiIiMhNJjwldunQJw4cPx8SJE/HLL7+gX79+8PDwgJWVld76I0aMMCrIsnDixAns3LkTx44dw9GjR3Hnzh0olUrk5uYWu9/q1auxZMkSXLx4EdWqVUOHDh0wZcoUdOzYsdQxqNVqLF68GMuXL8fVq1dha2uLgIAAhIeHo1mzZlIPjYiIiIgIgMRkIDg4GIIgQBRFnD17FmfPnoUgCIXqiaIIQRAqZDIQERGBLVu2lGqfkJAQLFiwANbW1vjXv/6F3Nxc7Ny5E3///Tc2bNiAQYMGGdyWKIp44403sHHjRtSoUQN9+/ZFWloaoqKiEBMTg9jYWLz66qulPSwiIiIiIi1JyUBYWJjek//KxM/PD76+vmjXrh3atWuHunXrFlt/z549WLBgAWrVqoXDhw+jcePGAIDDhw8jICAAo0aNQkBAABwdHQ3qf8WKFdi4cSMaN26MuLg41KlTBwAQFRWFoKAgDBs2DAkJCXjpJclLRRARERFRFSfpTHLatGkyh1E8URTN2h8ATJo0qVT1NeMnpkyZok0EgOdJxQcffIDFixcjMjISn3/+eana+/7777WJAAAMGTIEAwYMwB9//IEtW7ZgyJAhpYqTiIiIiEij3E/cX7NmTUydOrVcrzGQm5uL3bt3AwCCggpPU6cp27p1q0HtXb9+HRcvXoS1tTX69u1rdHtERERERPoY/YzJ6dOnER8fj7S0NDRv3hwDBgwAAOTl5SEvLw/29vZGte/o6IipU6caG6ZJJSQkIC8vD87OznBzK7ykfevWrQE8X7nZEGfOnAEAtGjRApaWlkW2p6lHRERERCSF5GTg0qVLGDVqFOLj47VlI0eO1CYDkZGRGD9+PGJiYtC7d2/jIy3HkpOTAUBvIgAANjY2qFGjBtLT05GdnQ07Ozuj2tOUa+oVRZOQaWRlZQF4PkuRWq0udl+iqq4yvUc07/nKdEzlDb+3RCQXc3+eSEoGbt68iS5duuDBgwcYOHAgOnXqhC+//FKnzptvvokJEyYgKipK1mTgxo0b2L9/P1Qqlc6J7osEQUBoaKhsfZYkJycHAFC9evUi69jY2CAjIwM5OTklJgMltWdjY6NTryizZs1CeHh4ofJbt26VGANRVVRQUKD9t6RkuyIRRRHp6ekQBKHST/5gTpX194WIypbm4q25SEoGwsPD8fDhQ6xatQrvvPMOABRKBhwdHdGsWTMcPnzY+Cjx/Ln8d999F2vXrgVQ/KBicycDmliK+yNbmkHQhrRniMmTJyMkJET7OisrC+7u7nB3dzf68S2iysjCwkL7r4eHRxlHIx+1Wg1RFOHu7l6ux19VNJX194WIylZGRoZZ+5OUDPz1119o1aqVNhEoSv369bFv3z5Jgf3TpEmTsGbNGtSuXRvDhg2Dl5eX9gp5WdNcZX/06FGRdR4/fgwAsLW1Nbo9TXlJbSmVSiiVykLlCoWCJwREJahs7xHN+76yHVd5we8rEcnF3J8nkpKBBw8ewN/fv8R6giCUuGKvodatWwcnJyecPn26xDn/zU1zRSglJUXv9kePHiEjIwM1atQw6PGcktrTlPNKFBEREREZQ1Lq4eTkhOvXr5dY79KlS3B1dZXSRSE5OTno3LlzuUsEAKBp06ZQKpVITU3VewJ/8uRJAICPj49B7fn6+gIAzp8/j2fPnhndHhERERGRPpKSga5du+LEiRM4ePBgkXW2bduGxMRE9OzZU3JwL2revDnu3bsnS1tys7a2Rrdu3QAAGzduLLRdU9avXz+D2vP09MTLL7+MJ0+eICYmxuj2iIiIiIj0kZQMTJ48GZaWlujfvz+WL1+O1NRU7bacnBz8+uuvGDVqFKpXr27wirsl+eKLL3Ds2DEcOnRIlvbkphmoO2PGDFy5ckVbfvjwYSxbtgz29vYYM2aMzj7Hjh2Dt7c3unfvXmR7EydOxP3797XlmzZtwh9//AFPT08MHDjQBEdCRERERFWFpDEDLVq0wJo1azBy5Ei89957eO+99yAIAlavXo1Vq1YBAKysrPDrr7/Cy8tLlkCHDh2KlJQUvP766/j444/Ro0cPuLq6FjnjjrHP08fExCAiIkKn7OnTp+jQoYP2dWhoqHaF4B49euDTTz/FokWL0LJlS/Ts2RNPnz7Fzp07oVarsWbNGtSsWVOnvcePHyMxMVHvuIrRo0dj+/btiI6O1iYMaWlp2Ldvn/Z7q29BMiIiIiIiQ0ledGzIkCFo06YNFi5ciF27duHGjRsoKCiAm5sbevTogc8//xyNGjWSM1b4+PjA0dER4eHheufP1xAEAfn5+Ub1lZqaiqNHj+qUiaKoU/biHREAWLhwIVq2bIklS5Zg586dsLS0RPfu3TFlyhSDBly/SKFQYMOGDVi0aBEiIyOxbds22NjYYNCgQZg+fTqaN28u/eCIiIiIiAAIYmkmwC9D27Ztw+DBg5Gfnw9nZ2fUr1+/2KlFY2NjzRhdxZCVlQUHBwdkZmZynQGqMjZc2ICwvWHIzssusa4qRwW1qIarnStSQvTP5lURqdVqJCcnw8PDg1NgyshtvhtuZ9+udL8vRFS2MjIy4OjoaLbzNcl3Bsxt6tSpEEURK1aswIgRI7iKJhEZJGxvGBLSEkq1j52SK3QTEVHVYHQykJ+fjwcPHiAvL6/IOnLMh3/p0iV06dIFI0eONLotIqo6NHcEFIICLrYuJda3U9ohIjCixHpERESVgeRkYNeuXZgxYwaOHDmidy58DTme3weer21gyOq9RET6uNi68FEOIiKif5CUDGzbtg2DBg1CQUEBHB0d0bBhQ5OfqAcFBWHNmjXIysri8+5ERERERDKQlAyEh4dDrVZj4cKF+Oijj2BhYSF3XIXMmDEDhw8fxuDBg/HTTz/B09PT5H0SEREREVVmkpKBCxcuwM/PD5988onc8RSpX79+sLCwQGxsLJo2bYoGDRoUuc6AIAjYvXu32WIjIiIiIqqIJCUDtra2qFOnjtyxFGvv3r3a/+fn5+Pq1au4evWq3rqcaYiIiIiIqGSSkoEePXrg8OHDUKvVZpuz+vr162bph4iIiIioqpCUDHz33Xdo164dPv/8c8ydO9csYwbq169v8j6IiIiIiKoSg5KB6dOnFyrr06cPFi9ejG3btiEgIABubm5FPr8fGhpqfKRERERERCQrg5KBadOmQRAEiKJYaFtSUhKSkpKK3JfJABERERFR+WRQMrBixQpTx0FERERERGZmUDIwcuRIU8dBRERERERmZp6pgIiIiIiIqNyRNJvQi44ePYoDBw7gzp07AIB69eqhU6dO6NChg9HBERERERGR6UhOBs6dO4fRo0fj5MmTAKAdXKyZUahly5ZYsWIFfHx8ZAiTiIiofFLlqOA2303y/nZKO0QERiCoWZCMURERGUZSMpCYmIiuXbsiIyMD7u7uGDJkCBo0aABRFJGcnIyoqCicOnUKXbt2xeHDh+Ht7V3qPtq3b48uXbrA398f/v7+cHJykhIqERGRSdgp7YBsQC2qcTv7tvSGsoHQ2FAmA0RUJiQlA19//TUyMjLw1VdfYfr06XjpJd1mvv/+e4SFhWHWrFn45ptvEBUVVeo+jh8/jhMnTmDBggUAgKZNm6Jz587aLy5CRkREZSkiMAKhsaHIzsuW3IYqRwW1qDaqDSIiYwiivsUDSlCzZk24urri3LlzxdZ75ZVXcPv2bTx8+LDUgW3fvh0HDhzAgQMHcPz4ceTm5j4P+P8/huTq6qqTHDRv3rzUfVQ1WVlZcHBwQGZmJuzt7cs6HCKzcJvvhtvZt+Fq54qUkJSyDqdMqNVqJCcnw8PDAwoF540oT/j7SUT/lJGRAUdHR7Odr0m6M/Ds2TODxgL4+Pjgxo0bUrrAa6+9htdee03bX3x8vDY5OHToEFJSUvDbb7/h999/BwDUqFED/v7+6Ny5M/z9/TmAmYiIiIioBJKSAV9f32JXHdZISkqCr6+vlC50WFpaomPHjujYsSMmTpwIALh48SIOHDiAuLg4HDx4EDdu3MC2bduwbds2CIKA/Px8o/slIiIiIqrMJN0v/uabbxAfH4/IyMgi66xYsQLx8fH4+uuvJQdXnGbNmuG9997DL7/8gq1bt2LKlClwcHCAKIqQ8OQTEREREVGVI+nOgI2NDcaNG4d3330XK1euxBtvvKEd0Hvz5k2sW7cOBw8exLhx42Bra4v9+/fr7N+lSxfJAefn5+P48eM6dwXS09MhiiIEQUCzZs3QqVMnye0TEREREVUVkpKBgIAACIIAURRx4MABHDx4UGe75sr8jz/+iB9//LHQ/gUFBQb3lZOTg8OHDyMuLg5xcXE4duwYcnNzIYoirK2t0a5dO3Tq1AmdOnVCx44dUaNGDSmHRERERERU5UhKBkaMGKGd1cdUJkyYgLi4OJw5c0abPNStWxd9+vTRnvy3bt260LSmRERERERkGEln0itXrpQ5jMIWLVoEQRDg6+uL8ePHIyAgAA0bNjR5v1Lt3bsXgYGBJdYLDw9HWFhYifUaNGiAmzdvFrn90qVLkhZzIyIiIiLSKLeX1a2trfHkyROcPn0an3zyCdq3bw9/f3906tQJfn5+5W6e/Lp162LkyJF6txUUFODXX38FAHTu3LlU7RbVpoODQ+kCJCIiIiL6B9mTgb/++gvnzp2Dh4cHBg8eLPkxnqysLJw4cUJnbYG9e/dCEAQIgoAWLVqgU6dO2gTBw8ND5iMpHW9v7yLvmOzYsQO//vor3N3d0bVr11K1a467MERERERUNUk6U1+6dCnmzp2L1atXw9/fX1v+1ltvYf369drXr776KmJjY6FUKkvdh4WFBdq3b4/27dsjJCQEAHD58mWdWYQ0A5QFQYCrq6s2MfD395dlfQO5aO4KDBs2jKt/EhEREVG5ISkZiI6OxqNHj9CxY0dt2c6dO7Fu3Tq4ubnhnXfewZ49e3D06FEsX74cH374oSzBNmnSBE2aNMHo0aMBAKmpqYiLi9PePYiKisK6devK1aJjjx49wpYtWwAAw4cPL+NoiIiIiIj+R1IykJiYiBYtWuhc5V67di0EQcDGjRvRvn175OXlwcPDA6tXr5YtGfgne3t7ODk5wcnJCTVr1oRSqcSzZ89M0pdUmzZtwqNHj9CqVSs0b9681PvPmTMHSUlJUCqVaN68OQYNGgRnZ2cTREpEREREVY2kZCA1NbXQwmH79++Hh4cH2rdvDwBQKpXo2LEjDh06ZHyU/19GRgYOHjyovRtw/Phx7cm/Zm0DLy+vUg/SNSXNI0LvvPOOpP0nTpyo83rChAlYvHgxxowZY3RsRERERFS1SUoGatSogYyMDO1rlUqF69evY8SIETr1bGxskJOTIzm4lJQU7Yl/XFwcLl68CFEUtSf+CoUCPj4+6Ny5s/arbt26kvuT2927d7F7925YWFjgrbfeKtW+AwYMQGBgINq0aQNnZ2dcu3YNkZGRWLRoEcaOHYtatWph4MCBxbaRl5eHvLw87eusrCwAgFqthlqtLvXxEFV0VfX3XvOer6rHX1Hw50NEgPk/CyQlA40bN8aBAweQmZkJBwcHrFmzBoIgoHfv3jr1UlJSJJ+ce3p6Ijk5GcD/rvorlUq0bdtWe+LfqVOncjfF6IvWrl2LgoIC9O7du9Tfh8WLF+u8bt68OebNm4emTZvi/fffx6RJk0pMBmbNmoXw8PBC5bdu3YKdnV2p4iGqqDSLFhYUFGg/U6oaURSRnp6unY2Nyg/+fhLRP2ku3pqLIGrOtEvh999/x9tvv42GDRvCx8cHMTExcHR0xNWrV2FrawsAePLkCZydnREYGIitW7eWOjCFQgF7e3v4+flpT/7bt28vaWaistK6dWucOnUKa9aswdtvvy1Lm2q1Gi4uLrh//z6uXbsGT0/PIuvquzPg7u6O9PT0cp1EEcnJY6EHbmffhqudK5I/q5onW2q1GsnJyfDw8OCMZuUMfz+J6J8yMjJQq1YtZGZmmuV8TdKdgTfffBOnT5/GokWLcO3aNbi5uWHVqlXaRAAA1q9fj8ePH6Nbt26SAjtx4gR8fX0r7B+uS5cu4dSpU7C1tS3xCn5pKBQKeHl54f79+1CpVMUmA0qlUm/ypFAoKuz3lcgYVfn3XvO+r8rfg/KOPxsiAsz/WSB50bHZs2cjPDwcWVlZeme36datG06dOgUvLy9J7bdq1UpqaOXCL7/8AgAYPHgwqlevLmvb6enpAKCTfBERERERlZZRqYdSqSxymkt3d3f4+vpKPmFNSEgwJjTZ2ykNURSxdu1aANJnESrKhQsXkJiYiOrVq8Pb21vWtomIiIioajH6PoRKpUJUVBR++OEHLFmyBFFRUVCpVEYH1qJFCwwbNgznz5+XtP/p06fx5ptv4pVXXjE6ltKKi4vDzZs3Ua9evWIfk1qyZAm8vb0xefJknfK//voLJ06cKFT/7NmzGDp0KERRxNixY1GtWjXZYyciIiKiqkPyY0Kpqan4+OOPERUVVWgKJIVCgSFDhuCHH36QvEBWaGgo5s2bh99//x2+vr4YNmwYunbtCl9fX1haWhaqn5eXh1OnTiE2NhZr167FxYsXYWNjg7CwMEn9G0OztsCwYcOKfe4rLS0NiYmJhZKnw4cPIzw8HPXr14eXlxecnZ1x/fp1nDx5Evn5+ejatStmzZpl0mMgIiIiospPUjKQmZmJLl26IDExEdbW1vjXv/6FBg0aAABu3ryJv//+G+vXr8eZM2dw5MgRODg4lLqPqVOnYty4cfj222+xevVqfPnllxAEAZaWlmjQoAEcHR1hZ2eHrKwsPHz4EDdv3kR+fj5EUYSDgwM+/fRTTJ482eyr9ebl5WHjxo0AgOHDh0tqo1evXrh16xbi4+Nx5swZ7Whyf39/DBs2DKNGjYKFhYWcYRMRERFRFSRpatHJkyfju+++w9ChQ7FkyZJCJ9xpaWkYP3481q9fj6+++gozZ840KsgnT55g/fr12LZtGw4ePIi7d+8WqlO3bl107twZffv2xf/93//BysrKqD4ro6ysLDg4OJhtqiqi8sBtvpt26saUkJSyDqdMcGrR8ou/n0T0TxkZGXB0dDTb+ZqkZMDb2xtPnjzB1atX9T6yAwDPnj1Do0aNYGVlhcTERKMDfVFqairu37+vXfSsdu3aZr8DUBExGaCqiCdbTAbKM/5+EtE/mTsZkPSY0M2bNzFo0KAiEwEAsLS0RKdOnRAdHS05uKI4Ozvz5J+IiIiIyEiSLhFZW1sjLS2txHppaWmwtraW0gUREREREZmYpGSgTZs22Ldvn97pLzVOnDiBvXv3om3btpKDIyIiIiIi05GUDEyYMAHPnj1D9+7dER4ejitXruDp06d4+vQprly5gmnTpqFHjx4oKCjAhAkT5I6ZiIiIiIhkIGnMwGuvvYZvv/0WoaGhmD59OqZPnw5BEAA8X30XAARBwIwZM9CnTx/5oiUiIqqEVDkquM13k7y/ndIOEYERCGoWJGNURFQVSF50bPLkyejZsyd++OEHHDhwAHfu3AEA1KtXD507d8ZHH32Edu3ayRYoERFRZWOntAOyAbWoxu3s29IbygZCY0OZDBBRqUlOBgCgbdu2WLVqlVyxEBERVSkRgREIjQ1Fdl625DZUOSqoRbVRbRBR1WVUMkBERETSBTULMvpqvmatAiIiKYxOBgoKCpCWloa8vLwi63h4eBjbDRERERERyUxyMrBz507MnDkThw8fxrNnz4qsJwgC8vPzpXZDREREREQmIikZiIqKwhtvvAG1Wg0nJyc0aNAANjY2csdGREREREQmJCkZmDZtGgDg559/RnBwMBQKScsVEBERERFRGZKUDFy9ehVdu3bF6NGj5Y6HiIiIiIjMRNIl/bp168LW1lbuWIiIiIiIyIwkJQNBQUE4fPgwsrKy5I6HiIiIiIjMRFIyEB4ejgYNGmDQoEG4fv263DEREREREZEZSBozUL16dezatQsdO3ZE06ZN0aBBA7i6ukIQhEJ1BUHA7t27jQ6UiIiIiIjkJSkZuH37Nnr06IHLly9DFEVcvXoVV69e1VtXX4JARERERERlT1IyEBISgsTERPTo0QOffPIJGjZsyHUGiIiIiIgqGEnJwK5du9C4cWPs2LEDFhYWcsdERERERERmIGkAsVqthq+vLxMBIiIiIqIKTFIy0KFDByQkJMgdCxERERERmZGkx4S+/fZbdOrUCT/88AM+/vhjuWMiIirRhgsbELY3DNl52cXWU+WozBQRERFRxSMpGTh//jxGjRqFzz77DNHR0ejRo0eRU4sCwIgRI4wKkojon8L2hiEhzfA7lHZKOxNGQ0REVDFJSgaCg4MhCAJEUcTevXuxb98+vfVEUYQgCEwGiEh2mjsCCkEBF1uXYuvaKe0QERhhjrCIiIgqFEnJQFhYGNcP0CMgIKDIxAgAduzYgd69exvcXkZGBqZNm4bo6GjcvXsXdevWxcCBAxEeHo4aNWrIEDFRxedi64KUkJSyDoOIiKhCkpQMTJs2TeYwKpchQ4bA1ta2ULmrq6vBbTx48AB+fn64cuUKGjZsiIEDB+LChQtYvHgxtm/fjiNHjqBWrVpyhk1EREREVYykZCA5ORm2traoWbNmsfXS09ORnZ0NDw8PScFVVHPnzkWDBg2MamPChAm4cuUKBg8ejHXr1uGll57/qD755BP88MMPCAkJwapVq2SIloiIiIiqKklTi3p6euLLL78ssd7EiRPRsGFDKV1UaXfv3sWaNWtgaWmJpUuXahMBAJgzZw6cnZ2xZs0a3Lt3rwyjJCIiIqKKTlIyIIoiRFE0uC6Vzo4dO6BWq9GlSxfUqVNHZ5tSqUT//v1RUFCAHTt2lFGERERERFQZSHpMyFBpaWmwtrY2ZRfl0vLly/HgwQMoFAo0adIEAwcOLNWjUmfOnAEAtG7dWu/21q1bIzIyUluPiIiIiEgKg5OB/fv367y+e/duoTKN/Px8JCYm4s8//0SLFi2Mi7ACmjFjhs7rL774AqGhoQgNDTVo/+TkZACAm5ub3u2ack29ouTl5SEvL0/7OisrCwCgVquhVqsNioWoIuDvc/E073l+nyo//oyJKj5zv48NTgYCAgJ0phP966+/8NdffxVZX7PGwOeff25chBVIly5dMHbsWHTs2BEuLi64desWNm7ciBkzZiAsLAz29vb49NNPS2wnJycHAFC9enW9221sbHTqFWXWrFkIDw8vVH7r1i3Y2XEBJqrYCgoKtP+WlBhXdaIoIj09HYIgcFroSojvBaLKRXPx1lwMTgZGjBih/SOyatUqeHl5oVOnTnrrVqtWDfXq1UP//v2LfNSlMpo+fbrO6yZNmuDrr79G27Zt0atXL0ydOhXvvfdeiY9OacZZFPVH29BxGJMnT0ZISIj2dVZWFtzd3eHu7g57e3uD2iAqrywsLLT/VrUZy0pLrVZDFEW4u7tDoZA0VIzKMb4XiCqXjIwMs/ZncDKwcuVK7f9XrVoFf39/REZGmiKmSudf//oX2rZti+PHj+PIkSMIDAwstr7mqv2jR4/0bn/8+DEA6F3L4EVKpRJKpbJQuUKh4AkBVSr8fS6Z5n3P71Xlxp8vUcVn7vexpAHEfCax9Bo3bozjx49DpVKVWFdzZSclRf+qqppyXgEiIiIiImOYdDYh+p/09HQAJV/NBwBfX18AwMmTJ/Vu15T7+PjIFB0REVV0qhwV3Obrn3hCCjulHSICIxDULEi2Nomo/DEqGUhOTsbWrVtx5coVZGdn632WXRAELF++3JhuKrzU1FTExcUBKHq60Bf17t0bCoUCcXFxuH//PmrXrq3dlpeXh61bt0KhUKBPnz4mi5mIiCoGO6UdkA2oRTVuZ9+Wr+FsIDQ2lMkAUSUnORmYPn06IiIidB4Z+ufAV82MQlUhGThy5AiePHlSaNalGzduYPjw4Xj06BEGDBigM13okiVLsGTJEgwaNAizZs3Slru4uOCtt97CmjVr8OGHH+L333/XrkI8ceJEpKamYvjw4ahbt675DpCIiMqliMAIhMaGIjsvW7Y2VTkqqEW1rG0SUfkkKRlYt24dpk2bhgYNGuCbb77Bhg0bsHPnTvz111+4du0a1q1bh7179yIkJAT9+/eXO+ZyKSEhAaNGjYKLiwuaNGmCunXrIiUlBSdOnEBubi6aN2+On376SWeftLQ0JCYm6h1HsHDhQhw5cgRRUVHw9vZG27ZtceHCBZw/fx5eXl5YsGCBuQ6NiIjKsaBmQbJfvXeb7ybvXQYiKrckDVdeunQpqlWrhtjYWIwZMwYuLi4AgJ49e+L999/Hnj17MG/ePCxatEg75Vll9+qrr2LcuHFwcXHBxYsXERUVhfPnz6Nly5aYN28e4uPjdR73KYmTkxPi4+Px8ccf4+nTp4iOjkZmZibGjx+PY8eOwcnJyYRHQ0RERERVgSAaOmn9CxwdHdGqVSvs2bMHADB69GisWrUK+fn5Oo/ItGjRAm5ubvjzzz/li5gky8rKgoODAzIzM7nOAFV4miuXrnauSAnRP/MWPadWq5GcnAwPDw9OPUkG4fuLqOxkZGTA0dHRbOdrkv4q5OXl6TyvbmVlBaDwIgm+vr6Ij4+XHh0REREREZmMpGTAxcUFd+/e1b52dXUFAFy4cEGnXkpKinaZdCIiIiIiKl8kDSB+5ZVXcOzYMe3rgIAAiKKIsLAw/PHHH7C1tcX69esRFxcHPz8/2YIloqphw4UNCNsbVuxMJqqckhfwIyIiouJJSgb69++PP/74A7t27UKPHj3QqVMnBAYGIjY2FjVr1oSdnR0yMjIgCAJCQ0PljpmIKrmwvWFISEswqK6d0s7E0RAREVVekpKB4cOHw9/fH87Oztqy6OhoTJw4EZs3b0Z6ejqaNWuGyZMno3fv3rIFS0SGMeTK+j+Vp9VGNXErBAVcbF2KrKeJmYiIiKSRlAwolUo0bdpUp8ze3h7/+c9/8J///EeWwIhIutJcWdcqh6uNuti6cCYTIiIiE5K8AjERlV+GXlnX4GqjREREVROTAaJKzNAr61xtlIiIqGri6jNERERERFUUkwEiIiIioiqKjwkRkZYqRwW3+W7F1ilPsw4RERGRcZgMENHzufqzAbWoLnnsQDmcdYiIiIikMSgZmD59Olq2bIkBAwaYOh4iKgMRgREIjQ0tcTYhzjpERERUuRiUDEybNg3BwcHaZMDCwgLBwcFYvny5SYMjIvMIahZk0JV+zjpERERUuRiUDFhYWODp06fa16IoQhRFkwVFROVbcWMLOKaAiIio4jAoGXBxcUF8fDxyc3NhZWVl6piIqJwyaGwBxxQQERFVGAYlAwMHDsSSJUvg5OSE2rVrAwA2btyIvXv3lrivIAhISkoyKkgiKh9KGlvAMQVEREQVi0HJwOzZswEAW7Zswc2bNyEIAnJycpCTk2PS4IiofClpbAHHFBAREVUsBi06Vr16dSxevBg3b95EQUEBRFFEcHAw1Gq1QV9ERERERFT+SFpnoGvXrvD29pY7FiIqwYYLGxC2N8ygKUDLEgcYExERVQySkoHY2Fi54yAiA4TtDUNCWoLB9e2UdiaMpoj+DBhgPHTDULjauRbZTlknM0T0nCGrkkvBiwJE5YfRKxAfO3YMcXFxuHPnDgRBgIuLCzp37oz27dvLER8RvUBzR0AhKOBi61JsXc0fW3MqaYDxiwmCIWMLzJ3MENFzpVqVXArOOkZUbkhOBi5fvowRI0YgPj4eALTrDgiCAABo3749Vq9ejcaNG8sQJhG9yMXWBSkhKWUdRiElDTDeeHGjQSsdA2WTzBDRc4auSi4FZx0jKl8kJQMqlQpdu3bFvXv3UK9ePQwdOhQNGjQAANy8eRMbNmzA0aNHERAQgOPHj8PFpfgrmERUNRi60jERlS1Tvlc56xhR+SIpGZgxYwbu3buHCRMmYNasWahWrZrO9u+++w6TJ0/G/PnzMXPmTPzwww+yBEtERERERPIxaGrRf9q+fTuaNm2KefPmFUoEAMDS0hJz5sxB06ZNsW3bNqODJCIiIiIi+UlKBlQqFVq3bl1sHUEQ0Lp1a6hUVWNWkMePH2Pz5s0YM2YMfHx8YG9vDxsbG/j6+mL69OmlXqCtQYMGEAShyK+EBMNnlCEiIiIi0kfSY0L29va4detWifVu3boFe3t7KV1UOGvXrsW7774LAGjevDl69+6NrKwsHDp0CFOnTsVvv/2Gffv2oXbt2qVqd+TIkXrLHRwcjI6ZiIiIiKo2ScmAn58fYmJisGPHDvTp00dvne3bt+PgwYPo37+/UQFWFNWqVcO4ceMwYcIEnRmUVCoV+vbti1OnTuGzzz7D2rVrS9XuypUrZY6UiIiIiOg5SY8JffXVVxAEAQMHDsSoUaOwc+dOXLlyBVevXsXOnTsRHByMQYMGwcLCAl999ZXcMZdLI0aMwNKlSwtNperi4oJ///vfAIBNmzbh6dOnZREeEREREVEhku8MrFixAu+//z5WrVqF1atX62wXRRHW1tb473//iw4dOsgSaEXm6+sLAMjLy8ODBw841SoRERERlQuSFx0bPnw4AgIC8NNPP+HAgQO4c+cOAKBevXro3LkzxowZA3d3d9kCrciuXbsG4PksSzVr1izVvnPmzEFSUhKUSiWaN2+OQYMGwdnZ2RRhEhEREVEVIzkZAAA3NzeEh4fLFUultWjRIgBA7969oVQqS7XvxIkTdV5PmDABixcvxpgxY0rcNy8vD3l5edrXWVlZAAC1Wg21Wl2qOKj84c+QDKV5z/N3hsob/k4SFWbu94VRyQCVbPv27Vi+fDksLS0RERFh8H4DBgxAYGAg2rRpA2dnZ1y7dg2RkZFYtGgRxo4di1q1amHgwIHFtjFr1iy9ydqtW7dgZ2dX2kOhcqCgoED7b3JychlHQxWFKIpIT0/XTk1MVJb4OUZUPM3FW3MRRFEUzdpjFXLp0iV06tQJ6enpWLhwIT799FOj2/zvf/+L999/H02aNEFiYmKxdfXdGXB3d0d6enqVmfK1PNtwcQOm7Z2G7KfZBu+jylFBLarhaueK5M/4R5QMo1arkZycDA8PDygUkuaNIJKNx0IP3M6+zc8xoiJkZGSgVq1ayMzMNMv5Gu8MmEhKSgp69+6N9PR0hISEyJIIAMDYsWMRGhqKy5cv4/r16/D09CyyrlKp1PtYkkKh4AlBOTBt3zQkPJC2eJyd0o4/QyoVzfuevzdUnvD3kagwc78vmAyYQFpaGnr27Ink5GSMGjUKc+fOla1thUIBLy8v3L9/HyqVqthkgMq37LzndwQUggIutobPMGWntENEoOGPnBEREREVhcmAzLKzs9GnTx8kJCRg8ODB+Omnn2R/Rjc9PR0AYGtrK2u7VDZcbF2QEpJS1mEQERFRFcT7czLKy8vD66+/juPHj6NXr1747bffYGFhIWsfFy5cQGJiIqpXrw5vb29Z2yYiIiKiqoXJgEwKCgrw1ltvITY2Fp07d8amTZtQrVq1YvdZsmQJvL29MXnyZJ3yv/76CydOnChU/+zZsxg6dChEUcTYsWNLbJ+IiIiIqDiyPCb04MED7aJjLi4ucHJykqPZCmXJkiWIjo4GADg5OeHDDz/UW2/u3Lna709aWhoSExOhUql06hw+fBjh4eGoX78+vLy84OzsjOvXr+PkyZPIz89H165dMWvWLNMeEBERkQmpclRwm+9mkrY1Y6uCmgWZpH2iykRyMiCKIv7973/j3//+Ny5fvqyzrUmTJvjwww/x0UcfVZmZAjTP8QPQJgX6TJs2rcRkqVevXrh16xbi4+Nx5swZ7dRS/v7+GDZsGEaNGiX740dERETmYKe0A7IBtajG7ezbpukkGwiNDWUyQGQASesM5OXloX///ti9ezdEUYSjoyPq168PURSRnJysXdymW7du2LZtW6lX3SXTyMrKgoODg9nmraXiuc130861zQHEZEpcZ4DKk40XNyI0NlQ7o5rcXlyPhZ+tVBFlZGTA0dGxfK8zMHPmTOzatQstWrTAnDlz0KtXL53tf/31FyZOnIg9e/Zg5syZelfBJSIioqonqFmQSa/Yay60EJFhJF0i+vXXX1GjRg3ExsYWSgSA54+57N69Gw4ODvjll1+MDpKIiIiIiOQnKRm4c+cOunfvjlq1ahVZx8nJCd26dSs0OJaIiIiIiMoHScmAq6srnj59WmK9Z8+eoV69elK6ICIiIiIiE5OUDAwbNgy7d+/GzZs3i6xz8+ZN7N69G2+//bbk4IiIiIiIyHQkJQNTpkxB9+7d0aVLF0RGRuLRo0fabY8ePUJkZCS6du2K7t27IywsTLZgiYiIiIhIPpJmE2ratClEUURKSgreffddvPvuu3B0dASgO9++IAho2rSpzr6CICApKcmIkImIiIiISA6SkoEbN24UKnv48GGhsuIeIyIiIiIiorIlKRlQq9Vyx0FERERERGYmKRkgImDDhQ0I2xsmeRVNVQ6n3SUiIqKyxWSASKKwvWFISEswuh07pZ0M0RARERGVnlHJwPnz57F06VLExcXhzp07EAQBLi4u6NKlC8aNG4cWLVrIFSdRuaO5I6AQFHCxdZHUhp3SDhGBEXKGRURERGQwycnAokWL8OWXX6KgoACiKGrLHz58iAsXLuCnn37CnDlz8Omnn8oSKFF55WLrgpSQlLIOg4iIiKjUJCUDO3fuxIQJE1C9enV88MEHeOedd9CgQQMIgoAbN27gl19+wX/+8x+EhISgRYsW6N69u9xxExERERVJlaOC23w3s/erueMb1CzI7H0TSSEpGZg/fz5eeukl/P333+jYsaPONh8fH8yZMweDBw9Gly5dMG/ePCYDREREZBZ2SjsgG1CLatzOvm3+ALKB0NhQJgNUYUhKBo4dO4auXbsWSgRe5Ofnh4CAABw9elRycERERESlEREYgdDYUMkzvRlDlaOCWlSXSd9EUklKBh4/fgxnZ+cS6zk7O+Px48dSuiAiIiIqtaBmQWV2Vd5tvlvZ3I0gMoJCyk7u7u44fPgwCgoKiqyTn5+Pw4cPw93dXXJwRERERERkOpKSgddffx03b97E2LFjkZWVVWh7VlYW3n33XSQnJ2PgwIHGxkhERERERCZg0GNCDRs2xNChQ/Hdd98BACZPnoxNmzZh9erV2Lx5M1577TXtbELXr19HTEwMsrKy0LBhQ0yePNmkB0BERERERNIYlAzcuHEDqamp2tc1a9ZEXFwc3n//fcTExOC3334rtE/fvn2xbNkyODo6yhctERERERHJRvKiY/Xq1cPWrVtx/fp1HDhwAHfu3NGW+/v7w9PTU7YgiYiIiIhIfpKTAQ1PT0+e+BMRERERVUCSBhATEREREVHFZ/CdgdOnT2P69OmSOgkLC5O0H5EpbbiwAWF7wyQvDqPKUckcEREREZF5GZwMnDlzBmfOnClV46IoQhAEJgNULoXtDUNCWoLR7dgp7WSIhoiIKgtVjgpu893KOgyD2CntEBEYUWYLtVHZMzgZ8PLyQqdOnUwZS6WQm5uLWbNm4bfffkNycjJq1qyJ3r17Y/r06XBzK90HQ0ZGBqZNm4bo6GjcvXsXdevWxcCBAxEeHo4aNWqY5gCqEM0dAYWggIuti6Q2NB+iREREdko7IBtQi+qKsxJxNhAaG8pkoAozOBnw9/dHZGSkKWOp8HJzc9G9e3ccOnQILi4ueP3113Hjxg2sWLEC27Ztw+HDh+Hl5WVQWw8ePICfnx+uXLmChg0bYuDAgbhw4QIWL16M7du348iRI6hVq5aJj6hqcLF1QUpISlmHQUREFVxEYARCY0MlP35qbqocFdSiusLES6Zh9GxC9D8zZ87EoUOH4Ofnh7///hu2trYAgPnz5+Pzzz/H6NGjsW/fPoPamjBhAq5cuYLBgwdj3bp1eOml5z+qTz75BD/88ANCQkKwatUqkx0LERERlU5Qs6AKdYXdbb5bxbmDQSbD2YRk8uzZM/zwww8AgH//+9/aRAAAQkJC4OPjg/379+PEiRMltnX37l2sWbMGlpaWWLp0qTYRAIA5c+bA2dkZa9aswb179+Q/ECIiIiKqMnhnQCYHDhxARkYGvLy80KpVq0Lbg4KCcPbsWWzduhVt2rQptq0dO3ZArVYjMDAQderU0dmmVCrRv39/REZGYseOHQgODpbzMIiIiKiKqUgDno3FAdOFMRmQiWampdatW+vdrik3ZEYmQ9qKjIws9exOlQ2nBiUiIpKuQg54NhYHTBdiUDKgVqtNHUeFl5ycDABFzhikKdfUM0dbeXl5yMvL077OzMwEADSZ2wQKq4r/hJgqW56T+erVqyMjI0OWtojKI7VajczMTGRkZEChqPjvfSKSx6Q2kzAzbiZynuWUdShmcTfnLkRRROLtRNSbWa+swymSOvf5ebcoimbpj3cGZJKT8/yNVL16db3bbWxsdOqZo61Zs2YhPDy8UPm9CI41eNEVXIHjRMeyDoOIiIjMQIQIFcr/0wEPHjyAg4ODyfthMiATTfYmCEKx283Z1uTJkxESEqJ9rVar0aZNG5w8ebLItiu7du3aIT4+vqzDKJXyFnNZxGPqPk3RvpxtGttWVlYW3N3dcevWLdjb28sSE5leeXvvl4WK+D0obzHzM9v8bRrbVmZmJjw8PFCzZk1Z4ikJkwGZ2Nk9X4X20aNHerc/fvwYAHRmGTJ1W0qlEkqlslCZObLM8srCwqLCnQyVt5jLIh5T92mK9uVsU6627O3ty9XvEhWvvL33y0JF/B6Ut5j5mW3+NuVqy1yPdfLhUZl4eHgAAFJS9C9epSnX1DNXW//00UcflXqfyqQiHn95i7ks4jF1n6ZoX842y9vvAJkHf+4V83tQ3mLmZ7b52yxvvwMlEURzjU6o5GJjY9GtWzd4eXnh6tWrhbZHREQgLCwMYWFhep/jf9GKFSswevRodO/eHbt27Sq0fcyYMYiMjERkZCRGjRol2zEQUeWUlZUFBwcHZGZmlqsrlkREVJi5P7N5Z0AmnTp1goODA5KSknDq1KlC2zdu3AgA6NevX4lt9e7dGwqFAnFxcbh//77Otry8PGzduhUKhQJ9+vSRJ3giqtSUSiWmTp1a6LFBIiIqf8z9mc1kQCbVqlXD+PHjAQDjx4/Xed5//vz5OHv2LPz9/dGuXTtt+ZIlS+Dt7Y3JkyfrtOXi4oK33noLT58+xYcffoj8/HzttokTJyI1NRVvv/026tata+KjIqLKQKlUYtq0aUwGiIgqAHN/ZnMAsYymTJmCXbt24dChQ2jcuDE6d+6Mmzdv4ujRo6hVqxZWrFihUz8tLQ2JiYlQqQpPb7Vw4UIcOXIEUVFR8Pb2Rtu2bXHhwgWcP38eXl5eWLBggbkOi4iIiIgqKd4ZkJGVlRViY2MRGhqK6tWrY/Pmzbhx4wZGjhyJU6dOoVGjRga35eTkhPj4eHz88cd4+vQpoqOjkZmZifHjx+PYsWNwcnIy4ZEQERERUVXAAcRERERERFUU7wwQEREREVVRTAaIiAgAsH//frz++uuoX78+BEHAtGnTyjokIiIqwooVKxAYGAhnZ2fY2dmhTZs2WLNmTanbYTJAREQAgJycHDRr1gzff/89ZysjIirndu/ejQEDBmD79u04deoU3nzzTbzzzjtYt25dqdrhmAEiogrgxIkT2LlzJ44dO4ajR4/izp07UCqVyM3NLXa/3NxczJo1C7/99huSk5NRs2ZN9O7dG9OnT4ebm1uR+zVo0ADBwcG8O0BEJIG5P7M1XnvtNVhbWyMqKsrgWDm1KBFRBRAREYEtW7aUap/c3Fx0794dhw4dgouLC15//XXcuHEDK1aswLZt23D48GF4eXmZKGIioqqrrD6zMzIy4O7uXqp++ZgQEVEF4Ofnh7CwMGzduhV37941aJ+ZM2fi0KFD8PPzw+XLl7Fu3TocPXoU8+bNQ2pqKkaPHm3iqImIqqay+MxetWoVjh8/jvfff79UsfIxISKiCkgQhGJvOT979gy1a9dGRkYGTp48iVatWuls9/X1xdmzZ3H8+HG0adOm0P58TIiISD6m/szesmUL3njjDfz4448YNWpUqWLjnQEiokrowIEDyMjIgJeXV6E/KgAQFBQEANi6dau5QyMion8w5jP7999/xxtvvIH//Oc/pU4EACYDRESV0pkzZwAArVu31rtdU66pR0REZUfqZ/ZPP/2E4OBgrFy5EsHBwZL65gBiIqJKKDk5GQCKnH1CU66pBzyfWvTq1asAgKdPn+Lu3bs4ffo0qlWrhmbNmpk4YiKiqkvKZ/b8+fMxceJE/Pvf/0ZAQIB2bIKFhQWcnZ0N7pt3BoiIKqGcnBwAQPXq1fVut7Gx0akHAMePH0erVq3QqlUrqFQqLFu2DK1atcJrr71m+oCJiKowKZ/ZixcvRkFBAT744AO4uLhov9q1a1eqvnlngIioEtLMDSEIQrHbXxQQEKC3nIiITEvKZ/aNGzdk6Zt3BoiIKiE7OzsAwKNHj/Ruf/z4MQDA1tbWbDEREZF+ZfmZzWSAiKgS8vDwAACkpKTo3a4p19QjIqKyU5af2UwGiIgqIV9fXwDAyZMn9W7XlPv4+JgtJiIi0q8sP7OZDBARVUKdOnWCg4MDkpKScOrUqULbN27cCADo16+fuUMjIqJ/KMvPbCYDRESVULVq1TB+/HgAwPjx43WeQ50/fz7Onj0Lf3//Us86QURE8ivLz2xB5NQRRETlXkxMDCIiIrSvjx49CkEQ0L59e21ZaGgo+vbtq32dm5uLgIAAHD16FC4uLujcuTNu3ryJo0ePolatWjhy5AgaNWpk1uMgIqoKKtJnNqcWJSKqAFJTU3H06FGdMlEUdcpSU1N1tltZWSE2NhazZs3C2rVrsXnzZjg6OmLkyJGIiIiAu7u7WWInIqpqKtJnNu8MEBERERFVURwzQERERERURTEZICIiIiKqopgMEBERERFVUUwGiIiIiIiqKCYDRERERERVFJMBIiIiIqIqiskAEREREVEVxWSAiIiIiKiKYjJARERERFRFMRkgIiIiIqqimAwQEREREVVRTAaIiIiIiKooJgNERCZy8uRJCIKA+vXr692en58PGxsbCIKATz/9VG+dmJgYCIKAtm3bmjJUWQiCgAYNGpR1GLK5ceMGBEFAQECA7G2Hh4fDwsICFy9elL1tY6lUKlhbW+Ojjz4q61CIyAyYDBARmYivry/s7e2RnJyM5OTkQttPnDiBx48fAwDi4uL0tnHgwAEAQOfOnU0XaBVlypP94ty7dw9z587F0KFD0axZM7P2bQgXFxe89957+O9//4vExMSyDoeITIzJABGRiVhYWMDPzw+A/pN9zYm+r68vzpw5g6ysrCLrMBmoPGbOnImcnBxMnjy5rEMp0sSJE6FWqxEWFlbWoRCRiTEZICIyIc1JvOak/kUHDhyAtbU1xo8fD7VajcOHD+tsf/r0KY4fPw4A8Pf3N32wZHKPHz/GqlWr4OPjA19f37IOp0iurq4IDAxEdHQ07t27V9bhEJEJMRkgIjIhTTKg787AoUOH0K5dOwQGBuqtEx8fj9zcXDRt2hS1a9fWlsfExGD06NF4+eWXYW9vDxsbG/j6+mLmzJnIy8vTaePEiRMQBAEdOnQoMsbvv/8egiDgm2++0Sm/ceMG3n//fTRo0ABKpRLOzs4ICgrC2bNnS/dNKGVbLz6+8+TJE3z11VeoX78+lEolGjVqhO+++w6iKOrtZ/369WjXrh2sra1Rp04djBo1Cvfu3UNwcDAEQcDevXsBANOmTYOnpycAYN++fRAEQfsVHBxcqN3SxlGUDRs2IDMzE8OGDdO7PTo6GoIg4OOPP9a7fdiwYRAEAQcPHiz0vXr06BFCQkLg7u4Oa2trtG7dGlu3btXpu3379rCxsUGdOnXwySef4MmTJ0XG+vbbb+PZs2dYuXJlqY6RiCoYkYiITObJkyeiUqkUBUEQHzx4oC1PSEgQAYhff/21KIqiWLduXbFLly46+86ePVsEII4dO1anvE6dOqKtra346quvikOHDhV79eolOjo6igDEbt26ifn5+Tr1vb29RQDi1atX9cbo6+srAhDPnz+vLYuLixPt7e1FAGLz5s3FoKAg0c/PTxQEQbS2thb37NlTqB0AYv369QuVl7at69eviwBEPz8/0d/fX3R0dBR79eol9urVS7SyshIBiN98802hfhYsWCACEC0sLMTu3buLb7zxhujq6io2aNBAHDBggAhAjI2NFUVRFKOjo8UhQ4aIAMQ6deqII0eO1H799NNPRsVRnKCgIBGAePToUb3bQ0NDRQDi8uXL9W5v1qyZKAiCmJWVVSjGV199VXRychL79esnBgQEiAqFQrSwsBB37twpzp8/X3zppZdEPz8/ceDAgWKtWrVEAOLbb79dZKxJSUkiALFz586lOkYiqliYDBARmVinTp1EAOIff/yhLfv5559FAGJMTIwoiqI4ePBg0crKSszLy9PW6devnwhAXLVqlU570dHRYk5Ojk5ZVlZWkfWnT58uAhCnT59eKLaLFy+KAMSWLVtqyzIzM8W6deuKlpaW4oYNG3Tq79y5U6xWrZro6uqqE6so6k8GpLSlOcHVnIimpqZqt8XHx4svvfSSWL16dTE7O1tbnpSUJFarVk20srIS9+/fry1/8uSJ2LdvX217mmTgxX66du1a6PsiNY6SaL4Xubm5erdrfoYnT54stO3JkyeihYWF2KhRI70xBgQEiA8fPtRuW7FihQhAbNSokVizZk2d78vt27fF2rVriwDEpKSkIuN1cnISlUplkfESUcXHx4SIiExM36NCBw4cgCAI6NixIwCgU6dOyM3N1Y4REEURhw4d0tlfY+DAgbCxsdEps7Ozw4IFCwAAW7Zs0dmmeSRlzZo1hWLTlL342EpkZCTu3r2LL774AkFBQTr1e/TogQ8//BC3b9/Gtm3bSjx2Y9pSKBT4+eef4eTkpC1r27Yt+vTpg8ePH2u/V5p+nj59ipEjR+p8v6ysrLBo0SIoFNL/3JUmjuLcv38fd+/e1T4qpc+pU6dgaWmJ5s2bF9p27tw5FBQUoGXLloW2WVhY4KeffoKjo6O2bMSIEXB2dsbVq1cxfvx4ne9LvXr1tD/z/fv3Fxlz06ZNkZeXx1mFiCoxJgNERCambxDxgQMH0KJFC9SoUQPA82TgxToXL17Ew4cP4erqqn22/UVXrlzBokWL8PHHH2P06NEIDg5GRESEdtuLGjZsiA4dOiAxMREnT57U2fb7779DoVDgzTff1Jbt3LkTwPOkQx/NYOb4+PgSj92Ytho0aIAmTZoUKteUqVQqbZkmcRo6dGih+l5eXmjVqlWJsRalNHEU5/79+wCgc8L+otTUVNy+fRvNmzdHtWrVCm0/ffo0AOhNBho0aIBGjRrplCkUCu0aFz179iy0j5eXV4nx16xZUxsbEVVOL5V1AERElV2nTp2gUChw/PhxPHnyBNnZ2bh69So++OADbZ3WrVvD2toacXFxmDhxYpFTioqiiC+++AILFiwocvBqdnZ2obJhw4bhyJEjWLNmDVq3bg0AOHLkCJKSkhAYGAg3Nzdt3Rs3bgAAXn311WKPKy0trcRjN6atF2N6ka2tLQDoDJa+c+cOAMDd3V3vPh4eHjhx4kSJ8epTmjiKk5mZCeD5XRx9Tp06BQBFJi7FJQOurq5699HcQdK3XbOtuPjt7e0B/C92Iqp8mAwQEZmYg4MDXnnlFZw5cwZHjx7FgwcPAOhOF2ppaYl27drh4MGDEEWxyGRg3bp1mD9/Ptzc3LBw4UL4+fnB2dkZlpaWePr0KZRKpd4k4Y033sCECRPw+++/Y86cOVAoFFi7di0AFJrZpqCgAMDzq+zVq1cv8rhKOsE3ti1BEEps39B9ikqcjGmztBwcHABA73oSgHHJQEkxSj0GTRKgiZ2IKh8mA0REZtC5c2ecOXMGBw4c0CYDmkeDNDp16oT9+/fjwoULRSYD0dHRAIAff/wR/fr109l27dq1Ivt3dnZGz549sWPHDuzduxddu3bF+vXroVQqMWTIEJ26bm5uSExMxJQpU+Dj4yPtgE3QVnFcXFyQmJiI5ORkNG7cuND2W7dumaxvQ2mmh3348KHe7ZpkoEWLFoW2ZWRkID4+Hk5OTkXeBTCF9PR0AM9/f4iocuKYASIiM3hxEPGBAwfg6uqKBg0a6NTRJAfr1q3DjRs3UKNGjUInhpqTM32Pw6xfv77YGDR3ANauXYvdu3fj3r176Nu3r3bcgkaPHj0AAJs3bzbo2IojZ1vF0QzE3rhxY6Ft165d055ov0jzXH5+fr5JY9OoXbs26tati5s3b+qd318To77BxStXrsSzZ8/03hUwpYSEBFhZWaFp06Zm7ZeIzIfJABGRGWiSgUOHDuH06dN6VxTu2LEjBEHAkiVLADx/jOifj3doBq3+97//1Xn0JS4uDnPmzCk2Bs0sRFFRUVixYgWAwo8IAcD7778PZ2dnzJw5EytWrCj0iM2jR4+wevVqpKSklHTYsrZVnFGjRsHS0hIrV67UDiYGgNzcXHz22WdQq9WF9nFycoKlpSWSkpK0jzOZWufOnZGfn18oOcnJycHVq1cBAL/++qvO92nr1q34+uuvAfxv0K85JCUl4cGDB2jfvn2Rsx8RUcXHZICIyAxcXFzg5eWFnJwc5OfnF3pECHg+y8zLL7+MjIwMAIUfEQKATz75BDY2Nli6dClatGiBt956C126dEHXrl11BiTrY2Njg9dffx0ZGRn4/fff4eDggL59++qNIzo6GjY2Nhg9ejQ8PT3Rr18/DBkyBO3atUOdOnUwcuRIgwYQy9lWcRo1aoSZM2ciNzcXXbp0Qc+ePfHmm2+icePGOHPmDPr37w8AOrP0VKtWDb1798bdu3fh6+uLESNGYOzYsdpEyRQ03+/Y2Fid8jNnzkCtVqNRo0b48ccf8fLLL6Nv3754+eWXMWDAAO0doo0bN2Ls2LEmi+9FmtWaX3vtNbP0R0Rlg8kAEZGZvHhyr+/OAKA7jkBfnSZNmiA+Ph79+/dHWloa/vjjD+Tk5GDZsmUl3hkAdO8EDBkypMgrvp06dcK5c+fw+eefw9raGnv27MHff/+NrKws9OvXD+vWrUOzZs1K7E/utorzxRdf4LfffoOvry/i4uKwZ88eBAYG4siRI9rHcmrVqqWzz88//4x33nkHDx48wNq1a7F8+XLs27fP6FiK8n//939wcHDQDt7W0NwpCA4Oxo8//ojc3Fzs3r0bSqUS69atw+rVq+Hm5gYLCwvtbFCmtnbtWlhaWiI4ONgs/RFR2RBEY6ZYICIiKucePXqEBg0a4MmTJ8jMzISFhUWZxjNhwgQsXLgQJ06c0J7YjxkzBpGRkYiJiSkXV+JTUlJQv359BAUFYd26dWUdDhGZEO8MEBFRpXDt2rVC8+Hn5OTggw8+QFpaGt54440yTwQAYPLkybC1tcXs2bO1ZZo7A+a66l8SzfSz06dPL+tQiMjEeGeAiIgqhdmzZ2PatGlo06YN3NzckJ6ejlOnTiEtLQ0NGjTAkSNHUKdOnbIOEwAwffp0hIeH49y5c2jcuDFsbW1Rq1Yt7eJpZUmlUqFhw4YYNWoUli5dWtbhEJGJMRkgIqJKIT4+HvPmzcORI0dw//59iKIIDw8P9O/fH5MmTSq3c+WfPn0arVq1Qt++fbFt27ayDoeIqhgmA0REREREVRTHDBARERERVVFMBoiIiIiIqigmA0REREREVRSTASIiIiKiKorJABERERFRFcVkgIiIiIioimIyQERERERURTEZICIiIiKqopgMEBERERFVUUwGiIiIiIiqqP8H/T8ow/7YkX4AAAAASUVORK5CYII=", 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" - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], - "source": [ - "P_i = np.array([270.0, 1e-20, 1e-20])*1.0e6\n", - "T_surf = 300\n", - "ISR, OLR = c.TOA_fluxes(T_surf, P_i)\n", - "\n", - "freq = c.rad.ir.freq # Hz\n", - "freq_av = (freq[1:]+freq[:-1])/2 # Hz\n", - "wv_av = 1e6*const.c/freq_av # microns\n", - "# c.rad.wrk_ir.fup_a is mW/m^2/Hz. Here I convert to W/m^2/um\n", - "F = 1e-3*c.rad.wrk_ir.fup_a[-1,:]*(freq_av/(wv_av))\n", - "\n", - "plt.rcParams.update({'font.size': 15})\n", - "fig,ax = plt.subplots(1,1,figsize=[8,5])\n", - "\n", - "ax.plot(wv_av, F, drawstyle='steps-pre',lw=2,c='g')\n", - "\n", - "ax.set_xscale(\"log\")\n", - "ax.set_xlim(2,100)\n", - "ax.set_ylim(0,ax.get_ylim()[1])\n", - "ax.grid(alpha=0.4)\n", - "\n", - "ax.set_ylabel('Top of atmosphere thermal radiance\\n(W m$^{-2}$ $\\mu$m$^{-1}$)')\n", - "ax.set_xlabel('Wavelength ($\\mu$m)')\n", - "\n", - "plt.show()" - ] - }, - { - "cell_type": "markdown", - "id": "7f251fa9", - "metadata": {}, - "source": [ - "### Outer edge of the habitable zone\n", - "\n", - "We can also compute the outer edge of the habitable zone. Following [Kopparapu et al. (2013)](https://doi.org/10.1088/0004-637X/765/2/131) we set the surface temperature to be just above the freezing point of water, then compute radiative transfer as a function of the CO$_2$ in the atmosphere. " - ] - }, - { - "cell_type": "code", - "execution_count": 21, - "id": "5ccc87c5", - "metadata": {}, - "outputs": [], - "source": [ - "c.T_trop = 157.0 # Follows Kopparapu et al.\n", - "c.rad.surface_albedo = 0.2\n", - "\n", - "P_CO2s = np.logspace(0,2,100)\n", - "P_i = np.array([200, 8, 1.0])*1e6\n", - "\n", - "OLR = np.empty(P_CO2s.shape[0])\n", - "ISR = np.empty(P_CO2s.shape[0])\n", - "for i,P_CO2 in enumerate(P_CO2s):\n", - " P_i[c.species_names.index('CO2')] = P_CO2*1e6\n", - " ISR_, OLR_ = c.TOA_fluxes(273.2, P_i)\n", - " OLR[i] = OLR_/1e3\n", - " ISR[i] = ISR_/1e3\n", - " \n", - "Seff = OLR/ISR" - ] - }, - { - "cell_type": "code", - "execution_count": 22, - "id": "0cb66a61", - "metadata": {}, - "outputs": [ - { - "data": { - "image/png": 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", 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" - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], - "source": [ - "plt.rcParams.update({'font.size': 15})\n", - "fig,[ax,ax1] = plt.subplots(1,2,figsize=[10,4],sharex=True)\n", - "\n", - "ax.plot(P_CO2s, OLR, lw=2, label='Outgoing longwave')\n", - "ax.plot(P_CO2s, ISR, lw=2, label='Incoming shortwave')\n", - "ax.set_ylim(50,250)\n", - "ax.set_xlim(1e0,1e2)\n", - "ax.set_xscale('log')\n", - "ax.set_ylabel('Flux (W/m$^2$)')\n", - "ax.set_xlabel('Surface CO$_2$ partial pressure (bar)')\n", - "ax.legend(ncol=1,bbox_to_anchor=(0, 1.02), loc='lower left')\n", - "ax.grid()\n", - "\n", - "ax1.plot(P_CO2s, Seff, lw=2, c='k')\n", - "ax1.set_xscale('log')\n", - "ax1.set_ylabel('$S_\\mathrm{eff}$')\n", - "ax1.set_xlabel('Surface CO$_2$ partial pressure (bar)')\n", - "ax1.grid()\n", - "\n", - "plt.subplots_adjust(wspace=0.3)\n", - "\n", - "plt.show()" - ] - }, - { - "cell_type": "markdown", - "id": "89c986c2", - "metadata": {}, - "source": [ - "The above plot is similar to Figure 5 in [Kopparapu et al. (2013)](https://doi.org/10.1088/0004-637X/765/2/131). The outgoing long-wave decreases with increased CO$_2$ because of CO$_2$'s greenhouse effect. The incoming shortwave radiation also decreases because of CO$_2$ Rayleigh scattering. The minimum of $S_\\mathrm{eff} \\approx 0.39$ at ~9 bars CO$_2$ is the outer edge of the habitable zone which corresponds to a distance of 1.60 AU.\n", - "\n", - "[Kopparapu et al. (2013)](https://doi.org/10.1088/0004-637X/765/2/131) finds the outer edge of the habitable zone to be instead at 1.67 AU. I am not certain, but I think our results disagree slightly because of subtle differences in the CO$_2$-CO$_2$ CIA opacities." - ] - }, - { - "cell_type": "code", - "execution_count": 23, - "id": "22cc037e", - "metadata": {}, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Outer edge of the habitable zone 1.60 AU\n" - ] - } - ], - "source": [ - "Seff_OHZ = np.min(Seff)\n", - "d_OHZ = np.sqrt(1/Seff_OHZ)\n", - "print('Outer edge of the habitable zone %.2f AU'%(d_OHZ))" - ] - }, - { - "cell_type": "code", - "execution_count": 24, - "id": "88c2b46a", - "metadata": {}, - "outputs": [], - "source": [ - "# return values to what they were before\n", - "c.rad.surface_albedo = 0.25\n", - "c.T_trop = 215.0" - ] - }, - { - "cell_type": "markdown", - "id": "80fa9029", - "metadata": {}, - "source": [ - "## Steady-state climate modeling\n", - "\n", - "Up to this point we have merely constructed atmospheres and computed their radiative properties. In this section we calculate steady-state climates. To find steady states, we numerically solve (via a variation of Newton's method) for the surface temperature which constructs an atmosphere that has balanced incoming solar and outgoing long-wave radiation. There are three climate functions, corresponding to our three methods of constructing an atmosphere\n", - "\n", - "- `AdiabatClimate.surface_temperature` uses `AdiabatClimate.make_profile`\n", - "- `AdiabatClimate.surface_temperature_column` uses `AdiabatClimate.make_column`\n", - "- `AdiabatClimate.surface_temperature_bg_gas` uses `AdiabatClimate.make_profile_bg_gas`\n", - "\n", - "Here are some examples:" - ] - }, - { - "cell_type": "code", - "execution_count": 25, - "id": "3c714a6a", - "metadata": {}, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "285.53248092727057\n" - ] - } - ], - "source": [ - "P_i = np.array([270.0, 400.0e-6, 1.0])*1.0e6\n", - "T_surf = c.surface_temperature(P_i, T_guess = 280) # optionally include a guess for T_surf\n", - "print(T_surf)" - ] - }, - { - "cell_type": "code", - "execution_count": 26, - "id": "8af3de30", - "metadata": {}, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "283.8068156878317\n" - ] - } - ], - "source": [ - "N_i = np.array([15.0e3, 400.0e-6*23.0, 36.0])\n", - "T_surf = c.surface_temperature_column(N_i, T_guess = 280)\n", - "print(T_surf)" - ] - }, - { - "cell_type": "code", - "execution_count": 27, - "id": "e6955468", - "metadata": {}, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "285.5405786410711\n" - ] - } - ], - "source": [ - "P_i = np.array([270.0, 400.0e-6, 1.0])*1.0e6\n", - "P_surf = 1.0e6\n", - "bg_gas = \"N2\"\n", - "T_surf = c.surface_temperature_bg_gas(P_i, P_surf, bg_gas, T_guess = 280)\n", - "print(T_surf)" - ] - }, - { - "cell_type": "markdown", - "id": "918af37d", - "metadata": {}, - "source": [ - "Since this steady-state modeling involves solving a non-linear equation, the algorithm can sometimes fail. Failure can be caused by a bad initial starting guess, or it is also possible that there is no steady-state climate for the chosen inputs. Another possibility is that there are multiple steady-state climates. Make sure to proceed with caution." - ] - }, - { - "cell_type": "markdown", - "id": "95cb2458", - "metadata": {}, - "source": [ - "## The ice-albedo feedback\n", - "As Earth gets colder, the ice caps get bigger. More ice means the surface reflects more sunlight, which in turn might make the Earth even colder. This effect is known as the ice-albedo feedback. This part of the tutorial shows how you can implement an ice-albedo feedback in `AdiabatClimate`.\n", - "\n", - "The function below parameterizes the ice-albedo feedback following [Arney et al. 2016](https://www.liebertpub.com/doi/full/10.1089/ast.2015.1422) (with some modifications)." - ] - }, - { - "cell_type": "code", - "execution_count": 28, - "id": "46aef260", - "metadata": {}, - "outputs": [], - "source": [ - "@nb.cfunc(nb.double(nb.double))\n", - "def arney_ice_albedo_feedback(T):\n", - " if T <= 240:\n", - " albedo = 0.65\n", - " elif 240 < T <= 290:\n", - " albedo = 0.65 + (0.2 - 0.65)*((T-240)/(290-240))**0.37\n", - " elif T > 290:\n", - " albedo = 0.2\n", - " return albedo" - ] - }, - { - "cell_type": "code", - "execution_count": 29, - "id": "6d490301", - "metadata": {}, - "outputs": [], - "source": [ - "c.T_trop = 200\n", - "c.albedo_fcn = arney_ice_albedo_feedback # sets the feedback function\n", - "\n", - "N_i = np.array([15.0e3, 400.0e-6*23.0, 36.0])\n", - "TT = np.linspace(201,310,100)\n", - "OLR = np.empty(TT.shape[0])\n", - "ISR = np.empty(TT.shape[0])\n", - "albedo = np.empty(TT.shape[0])\n", - "for i,T in enumerate(TT):\n", - " ISR_, OLR_ = c.TOA_fluxes_column(T, N_i)\n", - " OLR[i] = OLR_/1.0e3\n", - " ISR[i] = ISR_/1.0e3\n", - " albedo[i] = c.rad.surface_albedo" - ] - }, - { - "cell_type": "code", - "execution_count": 30, - "id": "21d11573", - "metadata": {}, - "outputs": [ - { - "data": { - "image/png": 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" - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], - "source": [ - "plt.rcParams.update({'font.size': 15})\n", - "fig,ax = plt.subplots(1,1,figsize=[5,4])\n", - "\n", - "ax.plot(TT,OLR,lw=2, label='Outgoing longwave')\n", - "ax.plot(TT,ISR,lw=2, label='Incoming shortwave')\n", - "\n", - "ax.grid()\n", - "ax.set_ylabel('Flux (W m$^{-1}$)')\n", - "ax.set_xlabel('Surface Temperature (K)')\n", - "ax.legend(ncol=1,bbox_to_anchor=(0, 1.02), loc='lower left')\n", - "ax.set_ylim(100,300)\n", - "ax.set_xlim(min(TT),max(TT))\n", - "\n", - "ax1 = ax.twinx()\n", - "ax1.plot(TT, albedo, c='k', ls='--', label='Surface albedo')\n", - "ax1.set_ylabel('Surface albedo')\n", - "ax1.legend(ncol=1,bbox_to_anchor=(0, 1.25), loc='lower left')\n", - "\n", - "plt.show()" - ] - }, - { - "cell_type": "markdown", - "id": "54ac1ea7", - "metadata": {}, - "source": [ - "In the figure above, you can see two stable climates. One is cold (T = 220 K) with high albedo. This represents Earth in an ice-ball state. Another stable climate is about ~290 K with a low albedo, which represents Earth with little ice, similar to today.\n", - "\n", - "There is an additional unstable equilibrium climate at ~240 K. This is unstable because if the planet gets warmer by a small amount, then the incoming solar radiation would be greater than the outgoing longwave radiation. So, the planet would warm until it reached the stable warm climate." - ] - }, - { - "cell_type": "code", - "execution_count": 31, - "id": "1c7f2220", - "metadata": {}, - "outputs": [], - "source": [ - "c.T_trop = 215 # restore T_trop\n", - "c.albedo_fcn = None # remove albedo feedback\n", - "c.rad.surface_albedo = 0.25 # restore albedo" - ] - }, - { - "cell_type": "markdown", - "id": "ad3d8d02", - "metadata": {}, - "source": [ - "## Gas dissolution in an ocean\n", - "\n", - "Here we add the complexity of a surface ocean which gases can dissolve into. We will consider a ocean of H$_2$O, but the model can account for gas dissolution in other more exotic oceans (e.g. CO$_2$ ocean?). For N$_2$, gas dissolution is very simple because it is governed by [Henry's law](https://en.wikipedia.org/wiki/Henry%27s_law) and, to first order, there is no further chemistry in the ocean that complicates things. CO$_2$ is much more complicated because of further reactions that occur in the aqueous phase:\n", - "\n", - "$$\\mathrm{CO_2}(\\mathrm{g}) \\leftrightarrow \\mathrm{CO_2}(\\mathrm{aq}) \\tag{1} \\label{eq:co2_dis1}$$\n", - "$$\\mathrm{CO_2}(\\mathrm{aq}) + \\mathrm{H_2O} \\leftrightarrow \\mathrm{H^+} + \\mathrm{HCO_3^-} \\tag{2} \\label{eq:co2_dis2}$$\n", - "$$\\mathrm{HCO_3^-} \\leftrightarrow \\mathrm{H^+} + \\mathrm{CO_3^{2-}} \\tag{3} \\label{eq:co2_dis3}$$\n", - "\n", - "The total reservoir of CO$_2$ in the ocean is the sum of the aqueous $\\mathrm{CO_2}$, $\\mathrm{HCO_3^-}$ and $\\mathrm{CO_3^{2-}}$. Below I write down some functions which account for N$_2$ solubility, and CO$_2$ solubility as well as CO$_2$ ocean chemistry. The final function, `water_ocean_solubility_fcn`, is a `numba.cfunc` that can be passed to the model. The function has to have the exact signature that I give in the example." - ] - }, - { - "cell_type": "code", - "execution_count": 32, - "id": "2163ad42", - "metadata": {}, - "outputs": [], - "source": [ - "@nb.njit()\n", - "def N2_henrys_constant(T):\n", - " alpha = 0.00060*np.exp(1300.0*((1/T) - 1/(298.15))) # mol/(kg*bar)\n", - " return alpha\n", - "\n", - "@nb.njit()\n", - "def CO2_henrys_constant(T):\n", - " # from NIST\n", - " alpha = 0.035*np.exp(2400.0*((1/T) - 1/(298.15)))\n", - " return alpha\n", - "\n", - "@nb.njit()\n", - "def K2_eq_constant(T):\n", - " # p. 123 in Pilson: An Introduction to the Chemistry of the Sea \n", - " pK2 = 17.788 - .073104 *T - .0051087*35 + 1.1463*10**-4*T**2\n", - " K2 = 10.0**(-pK2)\n", - " return K2\n", - "\n", - "@nb.njit()\n", - "def K3_eq_constant(T):\n", - " # p. 123 in Pilson: An Introduction to the Chemistry of the Sea \n", - " pK3 = 20.919 - .064209 *T - .011887*35 + 8.7313*10**-5*T**2\n", - " K3 = 10.0**(-pK3)\n", - " return K3\n", - "\n", - "@nb.njit()\n", - "def aqueous_carbon_chemistry(T, P_CO2, pH):\n", - " m_H = 10.0**(-pH)\n", - " m_CO2 = P_CO2*CO2_henrys_constant(T)\n", - " m_HCO3 = m_CO2*K2_eq_constant(T)/m_H\n", - " m_CO3 = m_HCO3*K3_eq_constant(T)/m_H\n", - " return m_CO2, m_HCO3, m_CO3\n", - "\n", - "sig = nb.void(nb.double,nb.int32,nb.types.CPointer(nb.double),nb.types.CPointer(nb.double), nb.types.voidptr)\n", - "@nb.cfunc(sig)\n", - "def water_ocean_solubility_fcn(T_surf, ng, P_i, m_i, p):\n", - " # P_i in bar\n", - " # m_i in mol/kg\n", - " \n", - " pH = 8.1 # we assume pH of ocean\n", - " \n", - " if T_surf < 273.15:\n", - " # Frozen planet. No ocean\n", - " for i in range(ng):\n", - " m_i[i] = 0.0\n", - " else:\n", - " # We have an ocean.\n", - " # H2O\n", - " m_i[0] = 0.0\n", - "\n", - " # CO2\n", - " P_CO2 = P_i[1]\n", - " m_CO2, m_HCO3, m_CO3 = aqueous_carbon_chemistry(T_surf, P_CO2, pH)\n", - " m_i[1] = m_CO2 + m_HCO3 + m_CO3 # total dissolved CO2\n", - "\n", - " # N2\n", - " P_N2 = P_i[2]\n", - " m_i[2] = N2_henrys_constant(T_surf)*P_N2\n" - ] - }, - { - "cell_type": "code", - "execution_count": 33, - "id": "744d13e9", - "metadata": {}, - "outputs": [], - "source": [ - "# set solubility function\n", - "ocean_species = 'H2O' # ocean is made of water\n", - "c.set_ocean_solubility_fcn(ocean_species, water_ocean_solubility_fcn)\n", - "\n", - "# A modern Earth-like case\n", - "c.T_trop = 200\n", - "T_surf = 288\n", - "N_i = np.array([15.0e3, 100*400.0e-6*23.0, 36.0]) # mol/cm^2\n", - "c.make_column(T_surf, N_i)" - ] - }, - { - "cell_type": "code", - "execution_count": 34, - "id": "11be897d", - "metadata": {}, - "outputs": [], - "source": [ - "# a little function for printing reservoirs\n", - "def print_reservoirs(c, num_fmt = '%.3e'):\n", - " fmt = \"{:15}\"\n", - " print('Fraction of species in each reservoir')\n", - " print(fmt.format('species') + fmt.format('atmos') + fmt.format('surface') + fmt.format('dissolved') + fmt.format('tot'))\n", - " print(fmt.format('---')+fmt.format('---')+fmt.format('---')+fmt.format('---')+fmt.format('---'))\n", - " for i in range(len(c.species_names)):\n", - " tot = c.N_atmos[i]+c.N_surface[i]+c.N_ocean[i,0]\n", - " print(fmt.format(c.species_names[i]),end='')\n", - " print(fmt.format(num_fmt%(c.N_atmos[i]/tot)),end='')\n", - " print(fmt.format(num_fmt%(c.N_surface[i]/tot)),end='')\n", - " print(fmt.format(num_fmt%(c.N_ocean[i,0]/tot)),end='')\n", - " print(fmt.format(num_fmt%(tot/tot)),end='')\n", - " print()" - ] - }, - { - "cell_type": "code", - "execution_count": 35, - "id": "e70c5480", - "metadata": {}, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Fraction of species in each reservoir\n", - "species atmos surface dissolved tot \n", - "--- --- --- --- --- \n", - "H2O 0.000012 0.999988 0.000000 1.000000 \n", - "CO2 0.024380 0.000000 0.975620 1.000000 \n", - "N2 0.994900 0.000000 0.005100 1.000000 \n" - ] - } - ], - "source": [ - "print_reservoirs(c, num_fmt='%.6f')" - ] - }, - { - "cell_type": "markdown", - "id": "f8a93aa4", - "metadata": {}, - "source": [ - "The case above is comparable to modern Earth. ~97% of CO$_2$ is dissolved in the ocean. This removes a lot of CO$_2$ from the atmosphere, lowering greenhouse warming. To demonstrate this, below I compute the surface temperature without and with gas dissolution in the ocean. Accounting for gas dissolution lowers the surface temperature by close to ~50 K." - ] - }, - { - "cell_type": "code", - "execution_count": 36, - "id": "4acdb9be", - "metadata": {}, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Surface Temperature = 334.4 K\n" - ] - } - ], - "source": [ - "c.set_ocean_solubility_fcn('H2O', None) # remove solubility\n", - "T_surf = c.surface_temperature_column(N_i, T_guess=330)\n", - "print('Surface Temperature = %.1f K'%T_surf)" - ] - }, - { - "cell_type": "code", - "execution_count": 37, - "id": "552bb124", - "metadata": {}, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Surface Temperature = 289.9 K\n" - ] - } - ], - "source": [ - "c.set_ocean_solubility_fcn('H2O', water_ocean_solubility_fcn) # add back gas dissolution\n", - "T_surf = c.surface_temperature_column(N_i, T_guess=280)\n", - "print('Surface Temperature = %.1f K'%T_surf)" - ] - }, - { - "cell_type": "markdown", - "id": "0856b659", - "metadata": {}, - "source": [ - "## Utility functions\n", - "\n", - "There is also the `AdiabatClimate.to_regular_grid` function. This routine re-grids the atmosphere so that is regular in altitude. Additionally there is `AdiabatClimate.out2atmosphere_txt`, which outputs the atmosphere to a file." - ] - }, - { - "cell_type": "code", - "execution_count": 38, - "id": "13a27215", - "metadata": {}, - "outputs": [], - "source": [ - "P_i = np.array([270.0, 400.0e-6, 1.0])*1.0e6\n", - "T_surf = c.surface_temperature(P_i, T_guess = 280)\n", - "\n", - "# To regular grid\n", - "c.to_regular_grid()\n", - "\n", - "# Output to file\n", - "c.out2atmosphere_txt('atmosphere.txt',eddy=np.zeros(len(c.T)),overwrite=True)" - ] - } - ], - "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": "3.11.4" - } - }, - "nbformat": 4, - "nbformat_minor": 5 -} diff --git a/src/dependencies/CMakeLists.txt b/src/dependencies/CMakeLists.txt index 7c8773d..f177602 100644 --- a/src/dependencies/CMakeLists.txt +++ b/src/dependencies/CMakeLists.txt @@ -49,7 +49,7 @@ CPMAddPackage( CPMAddPackage( NAME clima - VERSION 0.4.0 + VERSION 0.4.1 OPTIONS "BUILD_EXECUTABLE OFF" "BUILD_WITH_OPENMP ${BUILD_WITH_OPENMP}" @@ -57,6 +57,6 @@ CPMAddPackage( "BUILD_PYTHON_CLIMA ${BUILD_PYTHON_PHOTOCHEM}" "PYTHON_CLIMA_DESTINATION photochem" GITHUB_REPOSITORY "Nicholaswogan/clima" - GIT_TAG "v0.4.0" + GIT_TAG "v0.4.1" EXCLUDE_FROM_ALL OFF ) \ No newline at end of file