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3 | <meta content="text/html; charset=windows-1252" http-equiv="CONTENT-TYPE"><title>PALM chapter 2.0</title> <meta content="StarOffice 7 (Win32)" name="GENERATOR"> <meta content="Marcus Oliver Letzel" name="AUTHOR"> <meta content="20040719;14534028" name="CREATED"> <meta content="20041117;10385730" name="CHANGED"> <meta content="parallel LES model" name="KEYWORDS"> <style> |
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9 | <body style="direction: ltr;" lang="en-US"><h2 style="line-height: 100%;"><font size="4">2.0 |
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10 | Basic techniques of |
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11 | the LES model and its parallelization </font> |
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12 | </h2><p style="line-height: 100%;">LES models |
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13 | generally permit the |
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14 | simulation of turbulent flows, whereby those eddies, that carry the |
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15 | main energy are resolved by the numerical grid. Only the |
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16 | effect of such turbulence elements with diameter equal to or smaller |
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17 | than the grid spacing are parameterized in the model and |
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18 | by so-called subgrid-scale (SGS) transport. Larger structures are |
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19 | simulated directly (they are explicitly resolved) and their effects are |
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20 | represented by the advection terms. </p> |
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21 | <p style="font-style: normal; line-height: 100%;">PALM is |
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22 | based on the |
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23 | non-hydrostatic incompressible Boussinesq equations. It contains a |
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24 | water cycle with cloud formation and takes into account infrared |
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25 | radiative cooling in cloudy conditions. The model has six prognostic |
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26 | quantities in total – u,v,w, liquid water potential |
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27 | temperature |
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28 | <font face="Thorndale, serif">Θ</font><sub>l |
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29 | </sub>(BETTS, |
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30 | 1973), total water content q and subgrid-scale turbulent kinetic energy |
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31 | e. The |
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32 | subgrid-scale turbulence is modeled according to DEARDOFF (1980) and |
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33 | requires the solution of an additional prognostic equation for the |
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34 | turbulent kinetic energy e. The long wave radiation scheme is based |
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35 | on the parametrization of cloud effective emissivity (e.g. Cox, 1976) |
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36 | and condensation is considered by a simple '0%-or-100%'-scheme, which |
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37 | assumes that within each grid box the air is either entirely |
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38 | unsaturated or entirely saturated ( see e.g., CUIJPERS and DUYNKERKE, |
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39 | 1993). The water cycle is closed by using a simplified version of |
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40 | KESSLERs scheme (KESSLER, 1965; 1969) to parameterize precipitation |
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41 | processes (MÜLLER and CHLOND, 1996). Incompressibility is |
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42 | applied by means of a Poisson equation for pressure, which is solved |
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43 | with a direct method (SCHUMANN and SWEET, 1988). The Poisson equation |
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44 | is Fourier transformed in both horizontal directions and the |
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45 | resulting tridiagonal matrix is solved for the transformed pressure |
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46 | which is then transformed back. Alternatively, a multigrid method can |
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47 | also be used. Lateral boundary conditions of the model are cyclic and |
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48 | MONIN-OBUKHOV similarity is assumed between the surface and the first |
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49 | computational grid level above. Alternatively, noncyclic boundary |
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50 | conditions |
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51 | (Dirichlet/Neumann) can be used along one of the |
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52 | horizontal directions. At the lower surface, either temperature/ |
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53 | humidity or their respective fluxes can be prescribed. </p> |
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54 | <p style="font-style: normal; line-height: 100%;">The |
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55 | advection terms |
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56 | are treated by the scheme proposed by PIACSEK and WILLIAMS (1970), |
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57 | which conserves the integral of linear and quadratic quantities up to |
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58 | very small errors. The advection of scalar quantities can optionally |
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59 | be performed by the monotone, locally modified version of Botts |
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60 | advection scheme (CHLOND, 1994). The time integration is performed |
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61 | with the third-order Runge-Kutta scheme. A second-order Runge-Kutta |
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62 | scheme, a leapfrog scheme and an Euler scheme are also implemented.</p> |
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63 | <p style="line-height: 100%;">By default, the time step is |
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64 | computed |
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65 | with respect to the different criteria (CFL, diffusion) and adapted |
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66 | automatically. In case of a non-zero geostrophic |
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67 | wind the coordinate system can be moved along with the mean wind in |
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68 | order to maximize the time step (Galilei-Transformation). </p> |
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69 | <p style="font-style: normal; line-height: 100%;">In |
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70 | principle a model |
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71 | run is carried out in the following way: After reading the control |
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72 | parameters given by the user, all prognostic variables are |
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73 | initialized. Initial values can be e.g. vertical profiles of the |
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74 | horizontal wind, calculated using a 1D subset of the 3D prognostic |
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75 | equation and are set in the 3D-Model as horizontally homogeneous |
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76 | initial values. Temperature profiles can only be prescribed linear |
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77 | (with constant gradients, which may change for different vertical |
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78 | height intervals) and they are assumed in the 1D-Model as stationary. |
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79 | After the initialization phase during which also different kinds of |
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80 | disturbances may be imposed to the prognostic fields, the time |
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81 | integration begins. Here for each individual time step the prognostic |
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82 | equations are successively solved for the velocity components u, v and |
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83 | w |
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84 | as well as for the potential temperature and possibly for the TKE. |
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85 | After the calculation of the boundary values in accordance with the |
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86 | given boundary conditions the provisional velocity fields are |
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87 | corrected with the help of the pressure solver. Following this, all |
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88 | diagnostic turbulence quantities including possible |
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89 | Prandtl-layer–quantities are computed. At the end of a time |
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90 | step the data output requested by the user is made |
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91 | (e.g. statistic of analyses for control purposes or profiles and/or |
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92 | graphics data). If the given end-time was reached, binary data maybe |
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93 | be saved for restart. </p> |
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94 | <p style="font-style: normal; line-height: 100%;">The |
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95 | model is based |
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96 | on the originally non-parallel LES model which has been operated at the |
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97 | institute since 1989 |
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98 | and which was parallelized for massively parallel computers with |
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99 | distributed memory using the Message-Passing-Standard MPI. It is |
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100 | still applicable on a single processor and also well optimized for |
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101 | vector machines. The parallelization takes place via a so-called domain |
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102 | decomposition, which divides the entire model |
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103 | domain into individual, vertically standing cubes, which extend from |
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104 | the bottom to the top of the model domain. One processor (processing |
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105 | element, PE) is assigned to each cube, which |
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106 | accomplishes the computations on all grid points of the subdomain. |
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107 | Users can choose between a two- and a one-dimensional domain |
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108 | decomposition. A 1D-decomposition is preferred on machines with a |
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109 | slow network interconnection. In case of a 1D-decomposition, |
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110 | the |
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111 | grid points along x direction are |
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112 | distributed among the individual processors, but in y- and z-direction |
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113 | all respective grid points belong to the same PE. </p> |
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114 | <p style="line-height: 100%;">The calculation of central |
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115 | differences or |
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116 | non-local arithmetic operations (e.g. global |
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117 | sums, FFT) demands communication and an appropriate data exchange |
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118 | between the PEs. As a substantial innovation in relation to |
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119 | the non-parallel model version the individual subdomains are |
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120 | surrounded by so-called ghost points, which contain the grid point |
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121 | information of the neighbor processors. The appropriate grid point |
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122 | values must be exchanged after each change (i.e. in particular after |
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123 | each time step). For this purpose MPI routines (<tt>MPI_SENDRCV</tt>) |
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124 | are used. For the solution of the FFT conventional (non-parallelized) |
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125 | procedures are used. Given that the FFTs are used in x and/or |
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126 | y-direction, the data which lie distributed on the individual central |
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127 | processing elements, have to be collected and/or relocated before. |
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128 | This happens by means of the routine <tt>MPI_ALLTOALLV</tt>. |
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129 | Certain |
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130 | global operations like e.g. the search for absolute maxima or minima |
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131 | within the 3D-arrays likewise require the employment of special MPI |
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132 | routines (<tt>MPI_ALLREDUCE</tt>). </p> |
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133 | <p style="line-height: 100%;">Further details of the |
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134 | internal model |
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135 | structure are described in the <a href="../tec/index.html">technical/numerical |
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136 | documentation</a>. <br> |
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137 | </p> |
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138 | <hr><font color="#000080"><font color="#000080"><br><a href="chapter_1.0.html"><font color="#000080"><img name="Grafik1" src="left.gif" align="bottom" border="2" height="32" width="32"></font></a><a href="index.html"><font color="#000080"><img name="Grafik2" src="up.gif" align="bottom" border="2" height="32" width="32"></font></a><a href="chapter_3.0.html"><font color="#000080"><img name="Grafik3" src="right.gif" align="bottom" border="2" height="32" width="32"></font></a><br> |
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139 | </font></font><br><p style="line-height: 100%;"><span style="font-style: italic;">Last |
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140 | change: </span>$Id: chapter_2.0.html 62 2007-03-13 02:52:40Z Giersch $<font color="#000080"><font color="#000080"><br> |
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141 | </font></font></p></body></html> |
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