Mathematics of Climate and Weather Forecasting最新文献_第2页

A model for warm clouds with implicit droplet activation, avoiding saturation adjustment 一个具有隐式液滴激活、避免饱和度调整的暖云模型

Mathematics of Climate and Weather Forecasting Pub Date : 2018-11-28 DOI: 10.1515/mcwf-2018-0003

Nikolas Porz, M. Hanke, Manuel Baumgartner, P. Spichtinger

引用次数: 10

Spatial and Temporal Averaging Windows and Their Impact on Forecasting: Exactly Solvable Examples 时空平均窗及其对预测的影响:精确可解的例子

Mathematics of Climate and Weather Forecasting Pub Date : 2018-11-01 DOI: 10.1515/mcwf-2018-0002

Ying Li, S. Stechmann

{"title":"Spatial and Temporal Averaging Windows and Their Impact on Forecasting: Exactly Solvable Examples","authors":"Ying Li, S. Stechmann","doi":"10.1515/mcwf-2018-0002","DOIUrl":"https://doi.org/10.1515/mcwf-2018-0002","url":null,"abstract":"Abstract In making weather and climate predictions, the goal is often not to predict the instantaneous, local value of temperature, wind speed, or rainfall; instead, the goal is often to predict these quantities after averaging in time and/or space-for example, over one day or one week. What is the impact of spatial and/or temporal averaging on forecasting skill?Here this question is investigated using simple stochastic models that can be solved exactly analytically. While the models are idealized, their exact solutions allow clear results that are not affected by errors from numerical simulations or from random sampling. As a model of time series of oscillatory weather fluctuations, the complex Ornstein-Uhlenbeck process is used. To furthermore investigate spatial averaging, the stochastic heat equation is used as an idealized spatiotemporal model for moisture and rainfall. Space averaging and time averaging are shown to have distinctly different impacts on prediction skill. Spatial averaging leads to improved forecast skill, in line with some forms of basic intuition. Time averaging, on the other hand, is more subtle: it may either increase or decrease forecast skill. The subtle effects of time averaging are seen to arise from the relative definitions of the time averaging window and the lead time. These results should help in understanding and comparing forecasts with different temporal and spatial averaging windows.","PeriodicalId":106200,"journal":{"name":"Mathematics of Climate and Weather Forecasting","volume":"2 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133354349","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 3

Scale Dependent Analytical Investigation of the Dynamic State Index Concerning the Quasi-Geostrophic Theory 准地转理论动态指标的尺度相关分析研究

Mathematics of Climate and Weather Forecasting Pub Date : 2018-10-01 DOI: 10.1515/mcwf-2018-0001

A. Müller, P. Névir, R. Klein

{"title":"Scale Dependent Analytical Investigation of the Dynamic State Index Concerning the Quasi-Geostrophic Theory","authors":"A. Müller, P. Névir, R. Klein","doi":"10.1515/mcwf-2018-0001","DOIUrl":"https://doi.org/10.1515/mcwf-2018-0001","url":null,"abstract":"Abstract The Dynamic State Index (DSI) is a scalar diagnostic field that quantifies local deviations from a steady and adiabatic wind solution and thus indicates non-stationarity aswell as diabaticity. The DSI-concept has originally been developed through the Energy-Vorticity Theory based on the full compressible flow equations without regard to the characteristic scale-dependence of many atmospheric processes. But such scaledependent information is often of importance, and particularly so in the context of precipitation modeling: Small scale convective events are often organized in storms, clusters up to “Großwetterlagen” on the synoptic scale. Therefore, a DSI index for the quasi-geostrophic model is developed using (i) the Energy-Vorticity Theory and (ii) showing that it is asymptotically consistent with the original index for the primitive equations. In the last part, using meteorological reanalysis data it is demonstrated on a case study that both indices capture systematically different scale-dependent precipitation information. A spin-off of the asymptotic analysis is a novel non-equilibrium time scale combining potential vorticity and the DSI indices.","PeriodicalId":106200,"journal":{"name":"Mathematics of Climate and Weather Forecasting","volume":"420 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115248844","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 7

Spectral stability of nonlinear gravity waves in the atmosphere 大气中非线性重力波的谱稳定性

Mathematics of Climate and Weather Forecasting Pub Date : 2018-02-18 DOI: 10.1515/mcwf-2019-0002

M. Schlutow, E. Wahlén, P. Birken

{"title":"Spectral stability of nonlinear gravity waves in the atmosphere","authors":"M. Schlutow, E. Wahlén, P. Birken","doi":"10.1515/mcwf-2019-0002","DOIUrl":"https://doi.org/10.1515/mcwf-2019-0002","url":null,"abstract":"Abstract We apply spectral stability theory to investigate nonlinear gravity waves in the atmosphere. These waves are determined by modulation equations that result from Wentzel-Kramers-Brillouin theory. First, we establish that plane waves, which represent exact solutions to the inviscid Boussinesq equations, are spectrally stable with respect to their nonlinear modulation equations under the same conditions as what is known as modulational stability from weakly nonlinear theory. In contrast to Boussinesq, the pseudo-incompressible regime does fully account for the altitudinal varying background density. Second,we show for the first time that upward-traveling non-plane wave fronts solving the inviscid nonlinear modulation equations, that compare to pseudo-incompressible theory, are unconditionally unstable. Both inviscid regimes turn out to be ill-posed as the spectra allow for arbitrarily large instability growth rates. Third, a regularization is found by including dissipative effects. The corresponding nonlinear traveling wave solutions have localized amplitude. As a consequence of the nonlinearity, envelope and linear group velocity, as given by the derivative of the frequency with respect to wavenumber, do not coincide anymore. These waves blow up unconditionally by embedded eigenvalue instabilities but the instability growth rate is bounded from above and can be computed analytically. Additionally, all three types of nonlinear modulation equations are solved numerically to further investigate and illustrate the nature of the analytic stability results.","PeriodicalId":106200,"journal":{"name":"Mathematics of Climate and Weather Forecasting","volume":"92 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-02-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125364179","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 5

Covariate-based stochastic parameterization of baroclinic ocean eddies 斜压海洋涡旋基于协变量的随机参数化

Mathematics of Climate and Weather Forecasting Pub Date : 2017-12-07 DOI: 10.1515/mcwf-2017-0005

N. Verheul, J. Viebahn, D. Crommelin

{"title":"Covariate-based stochastic parameterization of baroclinic ocean eddies","authors":"N. Verheul, J. Viebahn, D. Crommelin","doi":"10.1515/mcwf-2017-0005","DOIUrl":"https://doi.org/10.1515/mcwf-2017-0005","url":null,"abstract":"Abstract In this study we investigate a covariate-based stochastic approach to parameterize unresolved turbulent processes within a standard model of the idealised, wind-driven ocean circulation. We focus on vertical instead of horizontal coarse-graining, such that we avoid the subtle difficulties of horizontal coarsegraining. The corresponding eddy forcing is uniquely defined and has a clear physical interpretation related to baroclinic instability.We propose to emulate the baroclinic eddy forcing by sampling from the conditional probability distribution functions of the eddy forcing obtained from the baroclinic reference model data. These conditional probability distribution functions are approximated here by sampling uniformly from discrete reference values. We analyze in detail the different performances of the stochastic parameterization dependent on whether the eddy forcing is conditioned on a suitable flow-dependent covariate or on a timelagged covariate or on both. The results demonstrate that our non-Gaussian, non-linear methodology is able to accurately reproduce the first four statistical moments and spatial/temporal correlations of the stream function, energetics, and enstrophy of the reference baroclinic model.","PeriodicalId":106200,"journal":{"name":"Mathematics of Climate and Weather Forecasting","volume":"17 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-12-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128285297","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 8

Influence sampling of trailing variables of dynamical systems 影响动力系统尾随变量的采样

Mathematics of Climate and Weather Forecasting Pub Date : 2017-11-27 DOI: 10.1515/mcwf-2017-0003

P. Krause

{"title":"Influence sampling of trailing variables of dynamical systems","authors":"P. Krause","doi":"10.1515/mcwf-2017-0003","DOIUrl":"https://doi.org/10.1515/mcwf-2017-0003","url":null,"abstract":"Abstract For dealing with dynamical instability in predictions, numerical models should be provided with accurate initial values on the attractor of the dynamical system they generate. A discrete control scheme is presented to this end for trailing variables of an evolutive system of ordinary differential equations. The Influence Sampling (IS) scheme adapts sample values of the trailing variables to input values of the determining variables in the attractor. The optimal IS scheme has affordable cost for large systems. In discrete data assimilation runs conducted with the Lorenz 1963 equations and a nonautonomous perturbation of the Lorenz equations whose dynamics shows on-off intermittency the optimal IS was compared to the straightforward insertion method and the Ensemble Kalman Filter (EnKF). With these unstable systems the optimal IS increases by one order of magnitude the maximum spacing between insertion times that the insertion method can handle and performs comparably to the EnKF when the EnKF converges. While the EnKF converges for sample sizes greater than or equal to 10, the optimal IS scheme does so fromsample size 1. This occurs because the optimal IS scheme stabilizes the individual paths of the Lorenz 1963 equations within data assimilation processes.","PeriodicalId":106200,"journal":{"name":"Mathematics of Climate and Weather Forecasting","volume":"36 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-11-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115993560","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 1

Moisture Transport due to Baroclinic Waves: Linear Analysis of Precipitating Quasi-Geostrophic Dynamics 斜压波引起的水汽输送:降水准地转动力学的线性分析

Mathematics of Climate and Weather Forecasting Pub Date : 2017-08-28 DOI: 10.1515/mcwf-2017-0002

A. Wetzel, L. Smith, S. Stechmann

{"title":"Moisture Transport due to Baroclinic Waves: Linear Analysis of Precipitating Quasi-Geostrophic Dynamics","authors":"A. Wetzel, L. Smith, S. Stechmann","doi":"10.1515/mcwf-2017-0002","DOIUrl":"https://doi.org/10.1515/mcwf-2017-0002","url":null,"abstract":"Abstract The effects of rainfall speed, VT, and meridional/vertical moisture gradients on the meridional moisture transport are examined in the context of mid-latitude baroclinic waves. These effects are investigated in an idealized model that can be solved analytically. The model is systematically derived in a precipitating quasi-geostrophic limit, starting from a moist atmospheric model with minimal representation of cloud microphysics. Single-phase dynamics are considered, with a comparison of three cases: unsaturated, saturated with VT = 0, and saturated with VT > 0. The Eady problem for linear baroclinic waves is analyzed, with modifications to incorporate moisture. As a preliminary step, the moist waves are shown to have properties consistent with prior studies, including larger growth rates and smaller spatial scales in the saturated cases in comparison to the classic dry Eady problem. Then, in addition, it is shown that the meridional moisture flux, as a function of height, has a mid-tropospheric maximum in the case of VT = 0, and a maximum in the lower troposphere or at the surface for sufficiently large values of VT. These results for different VT values are discussed in the context of meridional moisture transport in observational data.","PeriodicalId":106200,"journal":{"name":"Mathematics of Climate and Weather Forecasting","volume":"9 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-08-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126882073","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 15

An object-based model for convective cold pool dynamics 基于对象的对流冷池动力学模型

Mathematics of Climate and Weather Forecasting Pub Date : 2016-01-14 DOI: 10.1515/mcwf-2016-0003

S. Böing

{"title":"An object-based model for convective cold pool dynamics","authors":"S. Böing","doi":"10.1515/mcwf-2016-0003","DOIUrl":"https://doi.org/10.1515/mcwf-2016-0003","url":null,"abstract":"Abstract A simple model of the organization of atmospheric moist convection by cold outflows is presented. The model consists of two layers: a lower layer where instability gradually builds up, and an upper layer where instability is rapidly released. Its formulation is inspired by Abelian sandpile models: instability and convection are both represented in terms of particles that are coupled to a lattice grid. An excess of particles in the lower layer triggers a particle release into the upper (cloud) layer. Particles in the upper layer also induce particle movement in the lower layer: this reverse coupling represents the effect of precipitation and the associated cold outflows. The model shows two behavioral regimes. Activity is scattered when the reverse coupling is weak, but when it is strong, convection forms cellular patterns. Though this model does not contain a detailed representation of physical processes in convection, it captures some key dynamical features of precipitating convection seen in satellite observations and LES studies. These include the formation of open cells, temporal oscillations in convective intensity, hysteresis, and the effect of precipitation on the scale of convection. We argue that an object-based representation of convection may be able to capture properties of convective organization that are missing in traditional parameterizations.","PeriodicalId":106200,"journal":{"name":"Mathematics of Climate and Weather Forecasting","volume":"80 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-01-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133928529","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 25

Initiation and termination of intraseasonal oscillations in nonlinear Laplacian spectral analysis-based indices 基于非线性拉普拉斯谱分析的指数的季节内振荡的开始和终止

Mathematics of Climate and Weather Forecasting Pub Date : 2016-01-07 DOI: 10.1515/mcwf-2016-0001

E. Székely, D. Giannakis, A. Majda

引用次数: 8

Prediction skill of tropical synoptic scale transients from ECMWF and NCEP Ensemble Prediction Systems ECMWF和NCEP集合预报系统对热带天气尺度瞬变的预报技巧

Mathematics of Climate and Weather Forecasting Pub Date : 2016-01-05 DOI: 10.1515/mcwf-2016-0002

S. Taraphdar, P. Mukhopadhyay, L. Leung, K. Landu

{"title":"Prediction skill of tropical synoptic scale transients from ECMWF and NCEP Ensemble Prediction Systems","authors":"S. Taraphdar, P. Mukhopadhyay, L. Leung, K. Landu","doi":"10.1515/mcwf-2016-0002","DOIUrl":"https://doi.org/10.1515/mcwf-2016-0002","url":null,"abstract":"Abstract The prediction skill of tropical synoptic scale transients (SSTR) such as monsoon low and depression during the boreal summer of 2007–2009 are assessed using high resolution ECMWF and NCEP TIGGE forecasts data. By analyzing 246 forecasts for lead times up to 10 days, it is found that the models have good skills in forecasting the planetary scale means but the skills of SSTR remain poor, with the latter showing no skill beyond 2 days for the global tropics and Indian region. Consistent forecast skills among precipitation, velocity potential, and vorticity provide evidence that convection is the primary process responsible for precipitation. The poor skills of SSTR can be attributed to the larger random error in the models as they fail to predict the locations and timings of SSTR. Strong correlation between the random error and synoptic precipitation suggests that the former starts to develop from regions of convection. As the NCEP model has larger biases of synoptic scale precipitation, it has a tendency to generate more random error that ultimately reduces the prediction skill of synoptic systems in that model. The larger biases in NCEP may be attributed to the model moist physics and/or coarser horizontal resolution compared to ECMWF.","PeriodicalId":106200,"journal":{"name":"Mathematics of Climate and Weather Forecasting","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-01-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131380801","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 8