{"title":"综述文章:尺度、动力机制和分层。天气持续多久?云有多大?","authors":"S. Lovejoy","doi":"10.5194/npg-30-311-2023","DOIUrl":null,"url":null,"abstract":"Abstract. Until the 1980s, scaling notions were restricted to\nself-similar homogeneous special cases. I review developments over the last\ndecades, especially in multifractals and generalized scale invariance (GSI). The former is necessary for characterizing and modelling strongly\nintermittent scaling processes, while the GSI formalism extends scaling to strongly anisotropic (especially stratified) systems. Both of these\ngeneralizations are necessary for atmospheric applications. The theory and\nsome of the now burgeoning empirical evidence in its favour are reviewed. Scaling can now be understood as a very general symmetry principle. It is\nneeded to clarify and quantify the notion of dynamical regimes. In addition\nto the weather and climate, there is an intermediate “macroweather regime”, and at timescales beyond the climate regime (up to Milankovitch scales), there is a macroclimate and megaclimate regime. By objectively\ndistinguishing weather from macroweather, it answers the question “how long does weather last?”. Dealing with anisotropic scaling systems – notably\natmospheric stratification – requires new (non-Euclidean) definitions of\nthe notion of scale itself. These are needed to answer the question “how\nbig is a cloud?”. In anisotropic scaling systems, morphologies of structures change systematically with scale even though there is no characteristic\nsize. GSI shows that it is unwarranted to infer dynamical processes or\nmechanisms from morphology. Two “sticking points” preventing more widespread acceptance of the scaling paradigm are also discussed. The first is an often implicit\nphenomenological “scalebounded” thinking that postulates a priori the existence of\nnew mechanisms, processes every factor of 2 or so in scale. The second obstacle is the reluctance to abandon isotropic theories of turbulence and\naccept that the atmosphere's scaling is anisotropic. Indeed, there currently appears to be no empirical evidence that the turbulence in any atmospheric\nfield is isotropic. Most atmospheric scientists rely on general circulation models, and these are scaling – they inherited the symmetry from the (scaling) primitive\nequations upon which they are built. Therefore, the real consequence of\nignoring wide-range scaling is that it blinds us to alternative scaling approaches to macroweather and climate – especially to new models for long-range forecasts and to new scaling approaches to climate projections. Such\nstochastic alternatives are increasingly needed, notably to reduce uncertainties in climate projections to the year 2100.\n","PeriodicalId":54714,"journal":{"name":"Nonlinear Processes in Geophysics","volume":" ","pages":""},"PeriodicalIF":1.7000,"publicationDate":"2023-08-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"2","resultStr":"{\"title\":\"Review article: Scaling, dynamical regimes, and stratification. How long does weather last? How big is a cloud?\",\"authors\":\"S. Lovejoy\",\"doi\":\"10.5194/npg-30-311-2023\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Abstract. Until the 1980s, scaling notions were restricted to\\nself-similar homogeneous special cases. I review developments over the last\\ndecades, especially in multifractals and generalized scale invariance (GSI). The former is necessary for characterizing and modelling strongly\\nintermittent scaling processes, while the GSI formalism extends scaling to strongly anisotropic (especially stratified) systems. Both of these\\ngeneralizations are necessary for atmospheric applications. The theory and\\nsome of the now burgeoning empirical evidence in its favour are reviewed. Scaling can now be understood as a very general symmetry principle. It is\\nneeded to clarify and quantify the notion of dynamical regimes. In addition\\nto the weather and climate, there is an intermediate “macroweather regime”, and at timescales beyond the climate regime (up to Milankovitch scales), there is a macroclimate and megaclimate regime. By objectively\\ndistinguishing weather from macroweather, it answers the question “how long does weather last?”. Dealing with anisotropic scaling systems – notably\\natmospheric stratification – requires new (non-Euclidean) definitions of\\nthe notion of scale itself. These are needed to answer the question “how\\nbig is a cloud?”. In anisotropic scaling systems, morphologies of structures change systematically with scale even though there is no characteristic\\nsize. GSI shows that it is unwarranted to infer dynamical processes or\\nmechanisms from morphology. Two “sticking points” preventing more widespread acceptance of the scaling paradigm are also discussed. The first is an often implicit\\nphenomenological “scalebounded” thinking that postulates a priori the existence of\\nnew mechanisms, processes every factor of 2 or so in scale. The second obstacle is the reluctance to abandon isotropic theories of turbulence and\\naccept that the atmosphere's scaling is anisotropic. Indeed, there currently appears to be no empirical evidence that the turbulence in any atmospheric\\nfield is isotropic. Most atmospheric scientists rely on general circulation models, and these are scaling – they inherited the symmetry from the (scaling) primitive\\nequations upon which they are built. Therefore, the real consequence of\\nignoring wide-range scaling is that it blinds us to alternative scaling approaches to macroweather and climate – especially to new models for long-range forecasts and to new scaling approaches to climate projections. 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Review article: Scaling, dynamical regimes, and stratification. How long does weather last? How big is a cloud?
Abstract. Until the 1980s, scaling notions were restricted to
self-similar homogeneous special cases. I review developments over the last
decades, especially in multifractals and generalized scale invariance (GSI). The former is necessary for characterizing and modelling strongly
intermittent scaling processes, while the GSI formalism extends scaling to strongly anisotropic (especially stratified) systems. Both of these
generalizations are necessary for atmospheric applications. The theory and
some of the now burgeoning empirical evidence in its favour are reviewed. Scaling can now be understood as a very general symmetry principle. It is
needed to clarify and quantify the notion of dynamical regimes. In addition
to the weather and climate, there is an intermediate “macroweather regime”, and at timescales beyond the climate regime (up to Milankovitch scales), there is a macroclimate and megaclimate regime. By objectively
distinguishing weather from macroweather, it answers the question “how long does weather last?”. Dealing with anisotropic scaling systems – notably
atmospheric stratification – requires new (non-Euclidean) definitions of
the notion of scale itself. These are needed to answer the question “how
big is a cloud?”. In anisotropic scaling systems, morphologies of structures change systematically with scale even though there is no characteristic
size. GSI shows that it is unwarranted to infer dynamical processes or
mechanisms from morphology. Two “sticking points” preventing more widespread acceptance of the scaling paradigm are also discussed. The first is an often implicit
phenomenological “scalebounded” thinking that postulates a priori the existence of
new mechanisms, processes every factor of 2 or so in scale. The second obstacle is the reluctance to abandon isotropic theories of turbulence and
accept that the atmosphere's scaling is anisotropic. Indeed, there currently appears to be no empirical evidence that the turbulence in any atmospheric
field is isotropic. Most atmospheric scientists rely on general circulation models, and these are scaling – they inherited the symmetry from the (scaling) primitive
equations upon which they are built. Therefore, the real consequence of
ignoring wide-range scaling is that it blinds us to alternative scaling approaches to macroweather and climate – especially to new models for long-range forecasts and to new scaling approaches to climate projections. Such
stochastic alternatives are increasingly needed, notably to reduce uncertainties in climate projections to the year 2100.
期刊介绍:
Nonlinear Processes in Geophysics (NPG) is an international, inter-/trans-disciplinary, non-profit journal devoted to breaking the deadlocks often faced by standard approaches in Earth and space sciences. It therefore solicits disruptive and innovative concepts and methodologies, as well as original applications of these to address the ubiquitous complexity in geoscience systems, and in interacting social and biological systems. Such systems are nonlinear, with responses strongly non-proportional to perturbations, and show an associated extreme variability across scales.