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第49行： − + − {{main|Parametrization (climate)}}+ − Weather and climate model gridboxes have sides of between {{convert|5|km|mi}} and {{convert|300|km|mi}}. A typical [[cumulus cloud]] has a scale of less than {{convert|1|km|mi}}, and would require a grid even finer than this to be represented physically by the equations of fluid motion. Therefore, the processes that such [[clouds]] represent are ''[[Parametrization (atmospheric modeling)|parameterized]]'', by processes of various sophistication. In the earliest models, if a column of air in a model gridbox was unstable (i.e., the bottom warmer than the top) then it would be overturned, and the air in that vertical column mixed. More sophisticated schemes add enhancements, recognizing that only some portions of the box might [[convection|convect]] and that entrainment and other processes occur. Weather models that have gridboxes with sides between {{convert|5|km|mi}} and {{convert|25|km|mi}} can explicitly represent convective clouds, although they still need to parameterize [[cloud microphysics]].<ref>{{cite journal|url=http://ams.confex.com/ams/pdfpapers/126017.pdf|title=3.7 Improving Precipitation Forecasts by the Operational Nonhydrostatic Mesoscale Model with the Kain-Fritsch Convective Parameterization and Cloud Microphysics|author1=Narita, Masami |author2=Shiro Ohmori |name-list-style=amp |date=2007-08-06|access-date=2011-02-15|publisher=[[American Meteorological Society]]|journal=12th Conference on Mesoscale Processes}}</ref> The formation of large-scale ([[stratus cloud|stratus]]-type) clouds is more physically based, they form when the [[relative humidity]] reaches some prescribed value. Still, sub grid scale processes need to be taken into account. Rather than assuming that clouds form at 100% relative humidity, the [[cloud fraction]] can be related to a critical relative humidity of 70% for stratus-type clouds, and at or above 80% for cumuliform clouds,<ref>{{cite web|url=http://www.atmos.washington.edu/~dargan/591/diag_cloud.tech.pdf |pages=4–5 |title=The Diagnostic Cloud Parameterization Scheme |author=Frierson, Dargan |publisher=[[University of Washington]] |date=2000-09-14 |access-date=2011-02-15 |archive-url=https://web.archive.org/web/20110401013742/http://www.atmos.washington.edu/~dargan/591/diag_cloud.tech.pdf |archive-date=1 April 2011 |url-status=dead }}</ref> reflecting the sub grid scale variation that would occur in the real world. − Weather and climate model gridboxes have sides of between and . A typical cumulus cloud has a scale of less than , and would require a grid even finer than this to be represented physically by the equations of fluid motion. Therefore, the processes that such clouds represent are parameterized, by processes of various sophistication. In the earliest models, if a column of air in a model gridbox was unstable (i.e., the bottom warmer than the top) then it would be overturned, and the air in that vertical column mixed. More sophisticated schemes add enhancements, recognizing that only some portions of the box might convect and that entrainment and other processes occur. Weather models that have gridboxes with sides between and can explicitly represent convective clouds, although they still need to parameterize cloud microphysics. The formation of large-scale (stratus-type) clouds is more physically based, they form when the relative humidity reaches some prescribed value. Still, sub grid scale processes need to be taken into account. Rather than assuming that clouds form at 100% relative humidity, the cloud fraction can be related to a critical relative humidity of 70% for stratus-type clouds, and at or above 80% for cumuliform clouds, reflecting the sub grid scale variation that would occur in the real world.+ − 【更正】Weather and climate model gridboxes have sides of between 5 kilometres (3.1 mi) and 300 kilometres (190 mi). A typical cumulus cloud has a scale of less than 1 kilometre (0.62 mi), and would require a grid even finer than this to be represented physically by the equations of fluid motion. Therefore, the processes that such clouds represent are ''parameterized'', by processes of various sophistication. In the earliest models, if a column of air in a model gridbox was unstable (i.e., the bottom warmer than the top) then it would be overturned, and the air in that vertical column mixed. More sophisticated schemes add enhancements, recognizing that only some portions of the box might convect and that entrainment and other processes occur. Weather models that have gridboxes with sides between 5 kilometres (3.1 mi) and 25 kilometres (16 mi) can explicitly represent convective clouds, although they still need to parameterize cloud microphysics. The formation of large-scale (stratus-type) clouds is more physically based, they form when the relative humidity reaches some prescribed value. Still, sub grid scale processes need to be taken into account. Rather than assuming that clouds form at 100% relative humidity, the cloud fraction can be related to a critical relative humidity of 70% for stratus-type clouds, and at or above 80% for cumuliform clouds, reflecting the sub grid scale variation that would occur in the real world.+ − − = = = 天气和气候模型网格参量化的边界在到之间。一个典型的积云的尺度小于，并且需要一个比这更精细的网格才能用流体运动方程来表示。因此，这些云所代表的过程是通过各种复杂的过程来参数化的。在最早的模型中，如果模型网格盒中的空气柱是不稳定的(即，底部比顶部暖) ，那么它将被推翻，并且垂直柱中的空气将混合。更复杂的方案增加了增强功能，认识到只有盒子的一部分可能会突起，并且夹带和其他过程会发生。具有边界在到之间的网格框的天气模型可以明确地表示对流云，尽管它们仍然需要将云的微物理参数化。大尺度云(层云类型)的形成更多的是基于物理上的，它们是在相对湿度达到某个规定值时形成的。不过，次级电网规模的过程仍然需要考虑。与其假设云的形成相对湿度是100% ，不如假设层云型云的形成临界相对湿度是70% ，而积云型云的形成率是80% 或以上，这反映了现实世界中亚网格尺度的变化。 − − 【终稿】天气和气象模式网格具有5千米（3.1英里）到300千米（190英里）之间的边界。典型的积云尺度小于1千米（0.62英里），因此需要比这更精细的网格才能被流体运动方程表示。故而，这些云所代表的过程是通过各种复杂的处理来表示的。最早的模式中，如果模式中的空气柱是不稳定的（即底部比顶部热），那么它将被破坏，该垂直柱中的空气将被混合。更加复杂的模式中有增强功能，它们知道整个网格中只有一部分会发生对流、夹带或者一些其它过程。边界在5千米（3.1英里）到25千米（16英里）的气象模式可以明确地表示对流云，尽管它们仍然需要参数化云的微物理过程。大尺度（层云型）云的形成更加基于物理规律，它们在相对湿度达到某个规定值时形成。此时仍然有亚网格尺寸的过程也需要被考虑进来。层云形成的临界湿度被设定为70%而不是100%，相对湿度超过80%时认为形成的是积云，这反应了现实世界中可能发生的亚网格尺寸的变化。 − − The amount of solar radiation reaching ground level in rugged terrain, or due to variable cloudiness, is parameterized as this process occurs on the molecular scale.<ref>{{cite book|url=https://books.google.com/books?id=lMXSpRwKNO8C&pg=PA56|title=Parameterization schemes: keys to understanding numerical weather prediction models|author=Stensrud, David J.|page=6|year=2007|publisher=Cambridge University Press|isbn=978-0-521-86540-1}}</ref> Also, the grid size of the models is large when compared to the actual size and roughness of clouds and topography. Sun angle as well as the impact of multiple cloud layers is taken into account.<ref>{{cite book|url=https://books.google.com/books?id=vdg5BgBmMkQC&pg=PA226|author1=Melʹnikova, Irina N.|author2=Alexander V. Vasilyev |name-list-style=amp |pages=226–228|title=Short-wave solar radiation in the earth's atmosphere: calculation, oberservation, interpretation|year=2005|publisher=Springer|isbn=978-3-540-21452-6}}</ref> Soil type, vegetation type, and soil moisture all determine how much radiation goes into warming and how much moisture is drawn up into the adjacent atmosphere. Thus, they are important to parameterize.<ref>{{cite book|url=https://books.google.com/books?id=lMXSpRwKNO8C&pg=PA56|title=Parameterization schemes: keys to understanding numerical weather prediction models|author=Stensrud, David J.|pages=12–14|year=2007|publisher=Cambridge University Press|isbn=978-0-521-86540-1}}</ref> − − The amount of solar radiation reaching ground level in rugged terrain, or due to variable cloudiness, is parameterized as this process occurs on the molecular scale. Also, the grid size of the models is large when compared to the actual size and roughness of clouds and topography. Sun angle as well as the impact of multiple cloud layers is taken into account. Soil type, vegetation type, and soil moisture all determine how much radiation goes into warming and how much moisture is drawn up into the adjacent atmosphere. Thus, they are important to parameterize. − − 当这个过程在分子尺度上发生时，在崎岖地形中到达地面的太阳辐射量，或者由于变化的云量，被参数化了。此外，网格大小的模型是大相比，实际大小和粗糙的云和地形。太阳的角度以及多个云层的影响被考虑在内。土壤类型、植被类型和土壤湿度都决定有多少辐射进入气候变暖，有多少湿气进入邻近的大气层。因此，将它们参数化很重要。 − − 【终稿】在崎岖的地形中或云量多变地区达到地面的太阳辐射量也被参数化了，因为该过程发生在分子尺寸。并且，模型的网格尺寸相对于实际的云和地形的尺寸及粗糙度都要大得多。太阳角度以及其对多个云层的影响均被考虑在内。土壤类型、植被类型以及土壤湿度均决定了多少辐射参与邻近大气的加热以及湿度的增加。因此，它们也是重要的需要参数化的量。
→Parameterization 参数化
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== Parameterization 参数化 ==
== 参数化 ==
天气和气象模式网格具有5千米（3.1英里）到300千米（190英里）之间的边界。典型的积云尺度小于1千米（0.62英里），因此需要比这更精细的网格才能被流体运动方程表示。故而，这些云所代表的过程是通过各种复杂的处理来表示的。最早的模式中，如果模式中的空气柱是不稳定的（即底部比顶部热），那么它将被破坏，该垂直柱中的空气将被混合。更加复杂的模式中有增强功能，它们知道整个网格中只有一部分会发生对流、夹带或者一些其它过程。边界在5千米（3.1英里）到25千米（16英里）的气象模式可以明确地表示对流云，尽管它们仍然需要参数化云的微物理过程。<ref>{{cite journal|url=http://ams.confex.com/ams/pdfpapers/126017.pdf|title=3.7 Improving Precipitation Forecasts by the Operational Nonhydrostatic Mesoscale Model with the Kain-Fritsch Convective Parameterization and Cloud Microphysics|author1=Narita, Masami|author2=Shiro Ohmori |name-list-style=amp |date=2007-08-06|access-date=2011-02-15|publisher=[[American Meteorological Society]]|journal=12th Conference on Mesoscale Processes}}</ref>大尺度（层云型）云的形成更加基于物理规律，它们在相对湿度达到某个规定值时形成。此时仍然有亚网格尺寸的过程也需要被考虑进来。层云形成的临界湿度被设定为70%而不是100%，相对湿度超过80%时认为形成的是积云，<ref>{{cite web|url=http://www.atmos.washington.edu/~dargan/591/diag_cloud.tech.pdf |pages=4–5 |title=The Diagnostic Cloud Parameterization Scheme |author=Frierson, Dargan |publisher=[[University of Washington]] |date=2000-09-14 |access-date=2011-02-15 |archive-url=https://web.archive.org/web/20110401013742/http://www.atmos.washington.edu/~dargan/591/diag_cloud.tech.pdf |archive-date=1 April 2011 |url-status=dead }}</ref>这反应了现实世界中可能发生的亚网格尺寸的变化。
在崎岖的地形中或云量多变地区达到地面的太阳辐射量也被参数化了，因为该过程发生在分子尺寸。<ref>{{cite book|url=https://books.google.com/books?id=lMXSpRwKNO8C&pg=PA56|title=Parameterization schemes: keys to understanding numerical weather prediction models|author=Stensrud, David J.|page=6|year=2007|publisher=Cambridge University Press|isbn=978-0-521-86540-1}}</ref> 并且，模型的网格尺寸相对于实际的云和地形的尺寸及粗糙度都要大得多。太阳角度以及其对多个云层的影响均被考虑在内。<ref>{{cite book|url=https://books.google.com/books?id=vdg5BgBmMkQC&pg=PA226|author1=Melʹnikova, Irina N.|author2=Alexander V. Vasilyev |name-list-style=amp |pages=226–228|title=Short-wave solar radiation in the earth's atmosphere: calculation, oberservation, interpretation|year=2005|publisher=Springer|isbn=978-3-540-21452-6}}</ref>土壤类型、植被类型以及土壤湿度均决定了多少辐射参与邻近大气的加热以及湿度的增加。因此，它们也是重要的需要参数化的量。<ref>{{cite book|url=https://books.google.com/books?id=lMXSpRwKNO8C&pg=PA56|title=Parameterization schemes: keys to understanding numerical weather prediction models|author=Stensrud, David J.|pages=12–14|year=2007|publisher=Cambridge University Press|isbn=978-0-521-86540-1}}</ref>
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==Domains 范围==
==Domains 范围==