Parameterization of norfolk sandy loam properties for stochastic modeling of light in-wheel motor UGV

USDA-ARS?s Scientific Manuscript database

To accurately develop a mathematical model for an In-Wheel Motor Unmanned Ground Vehicle (IWM UGV) on soft terrain, parameterization of terrain properties is essential to stochastically model tire-terrain interaction for each wheel independently. Operating in off-road conditions requires paying clos...

Generalized ocean color inversion model for retrieving marine inherent optical properties.

PubMed

Werdell, P Jeremy; Franz, Bryan A; Bailey, Sean W; Feldman, Gene C; Boss, Emmanuel; Brando, Vittorio E; Dowell, Mark; Hirata, Takafumi; Lavender, Samantha J; Lee, ZhongPing; Loisel, Hubert; Maritorena, Stéphane; Mélin, Fréderic; Moore, Timothy S; Smyth, Timothy J; Antoine, David; Devred, Emmanuel; d'Andon, Odile Hembise Fanton; Mangin, Antoine

2013-04-01

Ocean color measured from satellites provides daily, global estimates of marine inherent optical properties (IOPs). Semi-analytical algorithms (SAAs) provide one mechanism for inverting the color of the water observed by the satellite into IOPs. While numerous SAAs exist, most are similarly constructed and few are appropriately parameterized for all water masses for all seasons. To initiate community-wide discussion of these limitations, NASA organized two workshops that deconstructed SAAs to identify similarities and uniqueness and to progress toward consensus on a unified SAA. This effort resulted in the development of the generalized IOP (GIOP) model software that allows for the construction of different SAAs at runtime by selection from an assortment of model parameterizations. As such, GIOP permits isolation and evaluation of specific modeling assumptions, construction of SAAs, development of regionally tuned SAAs, and execution of ensemble inversion modeling. Working groups associated with the workshops proposed a preliminary default configuration for GIOP (GIOP-DC), with alternative model parameterizations and features defined for subsequent evaluation. In this paper, we: (1) describe the theoretical basis of GIOP; (2) present GIOP-DC and verify its comparable performance to other popular SAAs using both in situ and synthetic data sets; and, (3) quantify the sensitivities of their output to their parameterization. We use the latter to develop a hierarchical sensitivity of SAAs to various model parameterizations, to identify components of SAAs that merit focus in future research, and to provide material for discussion on algorithm uncertainties and future emsemble applications.

Generalized Ocean Color Inversion Model for Retrieving Marine Inherent Optical Properties

NASA Technical Reports Server (NTRS)

Werdell, P. Jeremy; Franz, Bryan A.; Bailey, Sean W.; Feldman, Gene C.; Boss, Emmanuel; Brando, Vittorio E.; Dowell, Mark; Hirata, Takafumi; Lavender, Samantha J.; Lee, ZhongPing;

Spectral cumulus parameterization based on cloud-resolving model

NASA Astrophysics Data System (ADS)

Baba, Yuya

2018-02-01

We have developed a spectral cumulus parameterization using a cloud-resolving model. This includes a new parameterization of the entrainment rate which was derived from analysis of the cloud properties obtained from the cloud-resolving model simulation and was valid for both shallow and deep convection. The new scheme was examined in a single-column model experiment and compared with the existing parameterization of Gregory (2001, Q J R Meteorol Soc 127:53-72) (GR scheme). The results showed that the GR scheme simulated more shallow and diluted convection than the new scheme. To further validate the physical performance of the parameterizations, Atmospheric Model Intercomparison Project (AMIP) experiments were performed, and the results were compared with reanalysis data. The new scheme performed better than the GR scheme in terms of mean state and variability of atmospheric circulation, i.e., the new scheme improved positive bias of precipitation in western Pacific region, and improved positive bias of outgoing shortwave radiation over the ocean. The new scheme also simulated better features of convectively coupled equatorial waves and Madden-Julian oscillation. These improvements were found to be derived from the modification of parameterization for the entrainment rate, i.e., the proposed parameterization suppressed excessive increase of entrainment, thus suppressing excessive increase of low-level clouds.

Ice-nucleating particle emissions from photochemically aged diesel and biodiesel exhaust

NASA Astrophysics Data System (ADS)

Schill, G. P.; Jathar, S. H.; Kodros, J. K.; Levin, E. J. T.; Galang, A. M.; Friedman, B.; Link, M. F.; Farmer, D. K.; Pierce, J. R.; Kreidenweis, S. M.; DeMott, P. J.

2016-05-01

Immersion-mode ice-nucleating particle (INP) concentrations from an off-road diesel engine were measured using a continuous-flow diffusion chamber at -30°C. Both petrodiesel and biodiesel were utilized, and the exhaust was aged up to 1.5 photochemically equivalent days using an oxidative flow reactor. We found that aged and unaged diesel exhaust of both fuels is not likely to contribute to atmospheric INP concentrations at mixed-phase cloud conditions. To explore this further, a new limit-of-detection parameterization for ice nucleation on diesel exhaust was developed. Using a global-chemical transport model, potential black carbon INP (INPBC) concentrations were determined using a current literature INPBC parameterization and the limit-of-detection parameterization. Model outputs indicate that the current literature parameterization likely overemphasizes INPBC concentrations, especially in the Northern Hemisphere. These results highlight the need to integrate new INPBC parameterizations into global climate models as generalized INPBC parameterizations are not valid for diesel exhaust.

Develop and Test Coupled Physical Parameterizations and Tripolar Wave Model Grid: NAVGEM / WaveWatch III / HYCOM

DTIC Science & Technology

2013-09-30

Tripolar Wave Model Grid: NAVGEM / WaveWatch III / HYCOM W. Erick Rogers Naval Research Laboratory, Code 7322 Stennis Space Center, MS 39529...Parameterizations and Tripolar Wave Model Grid: NAVGEM / WaveWatch III / HYCOM 5a. CONTRACT NUMBER 5b. GRANT NUMBER 5c. PROGRAM ELEMENT NUMBER 6

Development and Testing of Coupled Land-surface, PBL and Shallow/Deep Convective Parameterizations within the MM5

NASA Technical Reports Server (NTRS)

Stauffer, David R.; Seaman, Nelson L.; Munoz, Ricardo C.

2000-01-01

The objective of this investigation was to study the role of shallow convection on the regional water cycle of the Mississippi and Little Washita Basins using a 3-D mesoscale model, the PSUINCAR MM5. The underlying premise of the project was that current modeling of regional-scale climate and moisture cycles over the continents is deficient without adequate treatment of shallow convection. It was hypothesized that an improved treatment of the regional water cycle can be achieved by using a 3-D mesoscale numerical model having a detailed land-surface parameterization, an advanced boundary-layer parameterization, and a more complete shallow convection parameterization than are available in most current models. The methodology was based on the application in the MM5 of new or recently improved parameterizations covering these three physical processes. Therefore, the work plan focused on integrating, improving, and testing these parameterizations in the MM5 and applying them to study water-cycle processes over the Southern Great Plains (SGP): (1) the Parameterization for Land-Atmosphere-Cloud Exchange (PLACE) described by Wetzel and Boone; (2) the 1.5-order turbulent kinetic energy (TKE)-predicting scheme of Shafran et al.; and (3) the hybrid-closure sub-grid shallow convection parameterization of Deng. Each of these schemes has been tested extensively through this study and the latter two have been improved significantly to extend their capabilities.

On testing two major cumulus parameterization schemes using the CSU Regional Atmospheric Modeling System

DOE Office of Scientific and Technical Information (OSTI.GOV)

Kao, C.Y.J.; Bossert, J.E.; Winterkamp, J.

1993-10-01

One of the objectives of the DOE ARM Program is to improve the parameterization of clouds in general circulation models (GCMs). The approach taken in this research is two fold. We first examine the behavior of cumulus parameterization schemes by comparing their performance against the results from explicit cloud simulations with state-of-the-art microphysics. This is conducted in a two-dimensional (2-D) configuration of an idealized convective system. We then apply the cumulus parameterization schemes to realistic three-dimensional (3-D) simulations over the western US for a case with an enormous amount of convection in an extended period of five days. In themore » 2-D idealized tests, cloud effects are parameterized in the ``parameterization cases`` with a coarse resolution, whereas each cloud is explicitly resolved by the ``microphysics cases`` with a much finer resolution. Thus, the capability of the parameterization schemes in reproducing the growth and life cycle of a convective system can then be evaluated. These 2-D tests will form the basis for further 3-D realistic simulations which have the model resolution equivalent to that of the next generation of GCMs. Two cumulus parameterizations are used in this research: the Arakawa-Schubert (A-S) scheme (Arakawa and Schubert, 1974) used in Kao and Ogura (1987) and the Kuo scheme (Kuo, 1974) used in Tremback (1990). The numerical model used in this research is the Regional Atmospheric Modeling System (RAMS) developed at Colorado State University (CSU).« less

Engelmann Spruce Site Index Models: A Comparison of Model Functions and Parameterizations

PubMed Central

Nigh, Gordon

2015-01-01

Engelmann spruce (Picea engelmannii Parry ex Engelm.) is a high-elevation species found in western Canada and western USA. As this species becomes increasingly targeted for harvesting, better height growth information is required for good management of this species. This project was initiated to fill this need. The objective of the project was threefold: develop a site index model for Engelmann spruce; compare the fits and modelling and application issues between three model formulations and four parameterizations; and more closely examine the grounded-Generalized Algebraic Difference Approach (g-GADA) model parameterization. The model fitting data consisted of 84 stem analyzed Engelmann spruce site trees sampled across the Engelmann Spruce – Subalpine Fir biogeoclimatic zone. The fitted models were based on the Chapman-Richards function, a modified Hossfeld IV function, and the Schumacher function. The model parameterizations that were tested are indicator variables, mixed-effects, GADA, and g-GADA. Model evaluation was based on the finite-sample corrected version of Akaike’s Information Criteria and the estimated variance. Model parameterization had more of an influence on the fit than did model formulation, with the indicator variable method providing the best fit, followed by the mixed-effects modelling (9% increase in the variance for the Chapman-Richards and Schumacher formulations over the indicator variable parameterization), g-GADA (optimal approach) (335% increase in the variance), and the GADA/g-GADA (with the GADA parameterization) (346% increase in the variance). Factors related to the application of the model must be considered when selecting the model for use as the best fitting methods have the most barriers in their application in terms of data and software requirements. PMID:25853472

Electron Impact Ionization: A New Parameterization for 100 eV to 1 MeV Electrons

NASA Technical Reports Server (NTRS)

Fang, Xiaohua; Randall, Cora E.; Lummerzheim, Dirk; Solomon, Stanley C.; Mills, Michael J.; Marsh, Daniel; Jackman, Charles H.; Wang, Wenbin; Lu, Gang

2008-01-01

Low, medium and high energy electrons can penetrate to the thermosphere (90-400 km; 55-240 miles) and mesosphere (50-90 km; 30-55 miles). These precipitating electrons ionize that region of the atmosphere, creating positively charged atoms and molecules and knocking off other negatively charged electrons. The precipitating electrons also create nitrogen-containing compounds along with other constituents. Since the electron precipitation amounts change within minutes, it is necessary to have a rapid method of computing the ionization and production of nitrogen-containing compounds for inclusion in computationally-demanding global models. A new methodology has been developed, which has parameterized a more detailed model computation of the ionizing impact of precipitating electrons over the very large range of 100 eV up to 1,000,000 eV. This new parameterization method is more accurate than a previous parameterization scheme, when compared with the more detailed model computation. Global models at the National Center for Atmospheric Research will use this new parameterization method in the near future.

Studies in the parameterization of cloudiness in climate models and the analysis of radiation fields in general circulation models

NASA Technical Reports Server (NTRS)

HARSHVARDHAN

1990-01-01

Broad-band parameterizations for atmospheric radiative transfer were developed for clear and cloudy skies. These were in the shortwave and longwave regions of the spectrum. These models were compared with other models in an international effort called ICRCCM (Intercomparison of Radiation Codes for Climate Models). The radiation package developed was used for simulations of a General Circulation Model (GCM). A synopsis is provided of the research accomplishments in the two areas separately. Details are available in the published literature.

Analysis of sensitivity to different parameterization schemes for a subtropical cyclone

NASA Astrophysics Data System (ADS)

Quitián-Hernández, L.; Fernández-González, S.; González-Alemán, J. J.; Valero, F.; Martín, M. L.

2018-05-01

A sensitivity analysis to diverse WRF model physical parameterization schemes is carried out during the lifecycle of a Subtropical cyclone (STC). STCs are low-pressure systems that share tropical and extratropical characteristics, with hybrid thermal structures. In October 2014, a STC made landfall in the Canary Islands, causing widespread damage from strong winds and precipitation there. The system began to develop on October 18 and its effects lasted until October 21. Accurate simulation of this type of cyclone continues to be a major challenge because of its rapid intensification and unique characteristics. In the present study, several numerical simulations were performed using the WRF model to do a sensitivity analysis of its various parameterization schemes for the development and intensification of the STC. The combination of parameterization schemes that best simulated this type of phenomenon was thereby determined. In particular, the parameterization combinations that included the Tiedtke cumulus schemes had the most positive effects on model results. Moreover, concerning STC track validation, optimal results were attained when the STC was fully formed and all convective processes stabilized. Furthermore, to obtain the parameterization schemes that optimally categorize STC structure, a verification using Cyclone Phase Space is assessed. Consequently, the combination of parameterizations including the Tiedtke cumulus schemes were again the best in categorizing the cyclone's subtropical structure. For strength validation, related atmospheric variables such as wind speed and precipitable water were analyzed. Finally, the effects of using a deterministic or probabilistic approach in simulating intense convective phenomena were evaluated.

Parameterized reduced-order models using hyper-dual numbers.

DOE Office of Scientific and Technical Information (OSTI.GOV)

Fike, Jeffrey A.; Brake, Matthew Robert

2013-10-01

The goal of most computational simulations is to accurately predict the behavior of a real, physical system. Accurate predictions often require very computationally expensive analyses and so reduced order models (ROMs) are commonly used. ROMs aim to reduce the computational cost of the simulations while still providing accurate results by including all of the salient physics of the real system in the ROM. However, real, physical systems often deviate from the idealized models used in simulations due to variations in manufacturing or other factors. One approach to this issue is to create a parameterized model in order to characterize themore » effect of perturbations from the nominal model on the behavior of the system. This report presents a methodology for developing parameterized ROMs, which is based on Craig-Bampton component mode synthesis and the use of hyper-dual numbers to calculate the derivatives necessary for the parameterization.« less

Numerical Study of the Role of Shallow Convection in Moisture Transport and Climate

NASA Technical Reports Server (NTRS)

Seaman, Nelson L.; Stauffer, David R.; Munoz, Ricardo C.

2001-01-01

The objective of this investigation was to study the role of shallow convection on the regional water cycle of the Mississippi and Little Washita Basins of the Southern Great Plains (SGP) using a 3-D mesoscale model, the PSU/NCAR MM5. The underlying premise of the project was that current modeling of regional-scale climate and moisture cycles over the continents is deficient without adequate treatment of shallow convection. At the beginning of the study, it was hypothesized that an improved treatment of the regional water cycle can be achieved by using a 3-D mesoscale numerical model having high-quality parameterizations for the key physical processes controlling the water cycle. These included a detailed land-surface parameterization (the Parameterization for Land-Atmosphere-Cloud Exchange (PLACE) sub-model of Wetzel and Boone), an advanced boundary-layer parameterization (the 1.5-order turbulent kinetic energy (TKE) predictive scheme of Shafran et al.), and a more complete shallow convection parameterization (the hybrid-closure scheme of Deng et al.) than are available in most current models. PLACE is a product of researchers working at NASA's Goddard Space Flight Center in Greenbelt, MD. The TKE and shallow-convection schemes are the result of model development at Penn State. The long-range goal is to develop an integrated suite of physical sub-models that can be used for regional and perhaps global climate studies of the water budget. Therefore, the work plan focused on integrating, improving, and testing these parameterizations in the MM5 and applying them to study water-cycle processes over the SGP. These schemes have been tested extensively through the course of this study and the latter two have been improved significantly as a consequence.

Domain-averaged snow depth over complex terrain from flat field measurements

NASA Astrophysics Data System (ADS)

Helbig, Nora; van Herwijnen, Alec

2017-04-01

Snow depth is an important parameter for a variety of coarse-scale models and applications, such as hydrological forecasting. Since high-resolution snow cover models are computational expensive, simplified snow models are often used. Ground measured snow depth at single stations provide a chance for snow depth data assimilation to improve coarse-scale model forecasts. Snow depth is however commonly recorded at so-called flat fields, often in large measurement networks. While these ground measurement networks provide a wealth of information, various studies questioned the representativity of such flat field snow depth measurements for the surrounding topography. We developed two parameterizations to compute domain-averaged snow depth for coarse model grid cells over complex topography using easy to derive topographic parameters. To derive the two parameterizations we performed a scale dependent analysis for domain sizes ranging from 50m to 3km using highly-resolved snow depth maps at the peak of winter from two distinct climatic regions in Switzerland and in the Spanish Pyrenees. The first, simpler parameterization uses a commonly applied linear lapse rate. For the second parameterization, we first removed the obvious elevation gradient in mean snow depth, which revealed an additional correlation with the subgrid sky view factor. We evaluated domain-averaged snow depth derived with both parameterizations using flat field measurements nearby with the domain-averaged highly-resolved snow depth. This revealed an overall improved performance for the parameterization combining a power law elevation trend scaled with the subgrid parameterized sky view factor. We therefore suggest the parameterization could be used to assimilate flat field snow depth into coarse-scale snow model frameworks in order to improve coarse-scale snow depth estimates over complex topography.

Dynamically Consistent Parameterization of Mesoscale Eddies This work aims at parameterization of eddy effects for use in non-eddy-resolving ocean models and focuses on the effect of the stochastic part of the eddy forcing that backscatters and induces eastward jet extension of the western boundary currents and its adjacent recirculation zones.

NASA Astrophysics Data System (ADS)

Berloff, P. S.

2016-12-01

This work aims at developing a framework for dynamically consistent parameterization of mesoscale eddy effects for use in non-eddy-resolving ocean circulation models. The proposed eddy parameterization framework is successfully tested on the classical, wind-driven double-gyre model, which is solved both with explicitly resolved vigorous eddy field and in the non-eddy-resolving configuration with the eddy parameterization replacing the eddy effects. The parameterization focuses on the effect of the stochastic part of the eddy forcing that backscatters and induces eastward jet extension of the western boundary currents and its adjacent recirculation zones. The parameterization locally approximates transient eddy flux divergence by spatially localized and temporally periodic forcing, referred to as the plunger, and focuses on the linear-dynamics flow solution induced by it. The nonlinear self-interaction of this solution, referred to as the footprint, characterizes and quantifies the induced eddy forcing exerted on the large-scale flow. We find that spatial pattern and amplitude of each footprint strongly depend on the underlying large-scale flow, and the corresponding relationships provide the basis for the eddy parameterization and its closure on the large-scale flow properties. Dependencies of the footprints on other important parameters of the problem are also systematically analyzed. The parameterization utilizes the local large-scale flow information, constructs and scales the corresponding footprints, and then sums them up over the gyres to produce the resulting eddy forcing field, which is interactively added to the model as an extra forcing. Thus, the assumed ensemble of plunger solutions can be viewed as a simple model for the cumulative effect of the stochastic eddy forcing. The parameterization framework is implemented in the simplest way, but it provides a systematic strategy for improving the implementation algorithm.

The Impact of Parameterized Convection on Climatological Precipitation in Atmospheric Global Climate Models

NASA Astrophysics Data System (ADS)

Maher, Penelope; Vallis, Geoffrey K.; Sherwood, Steven C.; Webb, Mark J.; Sansom, Philip G.

2018-04-01

Convective parameterizations are widely believed to be essential for realistic simulations of the atmosphere. However, their deficiencies also result in model biases. The role of convection schemes in modern atmospheric models is examined using Selected Process On/Off Klima Intercomparison Experiment simulations without parameterized convection and forced with observed sea surface temperatures. Convection schemes are not required for reasonable climatological precipitation. However, they are essential for reasonable daily precipitation and constraining extreme daily precipitation that otherwise develops. Systematic effects on lapse rate and humidity are likewise modest compared with the intermodel spread. Without parameterized convection Kelvin waves are more realistic. An unexpectedly large moist Southern Hemisphere storm track bias is identified. This storm track bias persists without convection schemes, as does the double Intertropical Convergence Zone and excessive ocean precipitation biases. This suggests that model biases originate from processes other than convection or that convection schemes are missing key processes.

Multi-Scale Modeling and the Eddy-Diffusivity/Mass-Flux (EDMF) Parameterization

NASA Astrophysics Data System (ADS)

Teixeira, J.

2015-12-01

Turbulence and convection play a fundamental role in many key weather and climate science topics. Unfortunately, current atmospheric models cannot explicitly resolve most turbulent and convective flow. Because of this fact, turbulence and convection in the atmosphere has to be parameterized - i.e. equations describing the dynamical evolution of the statistical properties of turbulence and convection motions have to be devised. Recently a variety of different models have been developed that attempt at simulating the atmosphere using variable resolution. A key problem however is that parameterizations are in general not explicitly aware of the resolution - the scale awareness problem. In this context, we will present and discuss a specific approach, the Eddy-Diffusivity/Mass-Flux (EDMF) parameterization, that not only is in itself a multi-scale parameterization but it is also particularly well suited to deal with the scale-awareness problems that plague current variable-resolution models. It does so by representing small-scale turbulence using a classic Eddy-Diffusivity (ED) method, and the larger-scale (boundary layer and tropospheric-scale) eddies as a variety of plumes using the Mass-Flux (MF) concept.

Mixing parametrizations for ocean climate modelling

NASA Astrophysics Data System (ADS)

Gusev, Anatoly; Moshonkin, Sergey; Diansky, Nikolay; Zalesny, Vladimir

2016-04-01

The algorithm is presented of splitting the total evolutionary equations for the turbulence kinetic energy (TKE) and turbulence dissipation frequency (TDF), which is used to parameterize the viscosity and diffusion coefficients in ocean circulation models. The turbulence model equations are split into the stages of transport-diffusion and generation-dissipation. For the generation-dissipation stage, the following schemes are implemented: the explicit-implicit numerical scheme, analytical solution and the asymptotic behavior of the analytical solutions. The experiments were performed with different mixing parameterizations for the modelling of Arctic and the Atlantic climate decadal variability with the eddy-permitting circulation model INMOM (Institute of Numerical Mathematics Ocean Model) using vertical grid refinement in the zone of fully developed turbulence. The proposed model with the split equations for turbulence characteristics is similar to the contemporary differential turbulence models, concerning the physical formulations. At the same time, its algorithm has high enough computational efficiency. Parameterizations with using the split turbulence model make it possible to obtain more adequate structure of temperature and salinity at decadal timescales, compared to the simpler Pacanowski-Philander (PP) turbulence parameterization. Parameterizations with using analytical solution or numerical scheme at the generation-dissipation step of the turbulence model leads to better representation of ocean climate than the faster parameterization using the asymptotic behavior of the analytical solution. At the same time, the computational efficiency left almost unchanged relative to the simple PP parameterization. Usage of PP parametrization in the circulation model leads to realistic simulation of density and circulation with violation of T,S-relationships. This error is majorly avoided with using the proposed parameterizations containing the split turbulence model. The high sensitivity of the eddy-permitting circulation model to the definition of mixing is revealed, which is associated with significant changes of density fields in the upper baroclinic ocean layer over the total considered area. For instance, usage of the turbulence parameterization instead of PP algorithm leads to increasing circulation velocity in the Gulf Stream and North Atlantic Current, as well as the subpolar cyclonic gyre in the North Atlantic and Beaufort Gyre in the Arctic basin are reproduced more realistically. Consideration of the Prandtl number as a function of the Richardson number significantly increases the modelling quality. The research was supported by the Russian Foundation for Basic Research (grant № 16-05-00534) and the Council on the Russian Federation President Grants (grant № MK-3241.2015.5)

An Overview of Numerical Weather Prediction on Various Scales

NASA Astrophysics Data System (ADS)

Bao, J.-W.

2009-04-01

The increasing public need for detailed weather forecasts, along with the advances in computer technology, has motivated many research institutes and national weather forecasting centers to develop and run global as well as regional numerical weather prediction (NWP) models at high resolutions (i.e., with horizontal resolutions of ~10 km or higher for global models and 1 km or higher for regional models, and with ~60 vertical levels or higher). The need for running NWP models at high horizontal and vertical resolutions requires the implementation of non-hydrostatic dynamic core with a choice of horizontal grid configurations and vertical coordinates that are appropriate for high resolutions. Development of advanced numerics will also be needed for high resolution global and regional models, in particular, when the models are applied to transport problems and air quality applications. In addition to the challenges in numerics, the NWP community is also facing the challenges of developing physics parameterizations that are well suited for high-resolution NWP models. For example, when NWP models are run at resolutions of ~5 km or higher, the use of much more detailed microphysics parameterizations than those currently used in NWP model will become important. Another example is that regional NWP models at ~1 km or higher only partially resolve convective energy containing eddies in the lower troposphere. Parameterizations to account for the subgrid diffusion associated with unresolved turbulence still need to be developed. Further, physically sound parameterizations for air-sea interaction will be a critical component for tropical NWP models, particularly for hurricane predictions models. In this review presentation, the above issues will be elaborated on and the approaches to address them will be discussed.

Sensitivity of Pacific Cold Tongue and Double-ITCZ Bias to Convective Parameterization

NASA Astrophysics Data System (ADS)

Woelfle, M.; Bretherton, C. S.; Pritchard, M. S.; Yu, S.

2016-12-01

Many global climate models struggle to accurately simulate annual mean precipitation and sea surface temperature (SST) fields in the tropical Pacific basin. Precipitation biases are dominated by the double intertropical convergence zone (ITCZ) bias where models exhibit precipitation maxima straddling the equator while only a single Northern Hemispheric maximum exists in observations. The major SST bias is the enhancement of the equatorial cold tongue. A series of coupled model simulations are used to investigate the sensitivity of the bias development to convective parameterization. Model components are initialized independently prior to coupling to allow analysis of the transient response of the system directly following coupling. These experiments show precipitation and SST patterns to be highly sensitive to convective parameterization. Simulations in which the deep convective parameterization is disabled forcing all convection to be resolved by the shallow convection parameterization showed a degradation in both the cold tongue and double-ITCZ biases as precipitation becomes focused into off-equatorial regions of local SST maxima. Simulations using superparameterization in place of traditional cloud parameterizations showed a reduced cold tongue bias at the expense of additional precipitation biases. The equatorial SST responses to changes in convective parameterization are driven by changes in near equatorial zonal wind stress. The sensitivity of convection to SST is important in determining the precipitation and wind stress fields. However, differences in convective momentum transport also play a role. While no significant improvement is seen in these simulations of the double-ITCZ, the system's sensitivity to these changes reaffirm that improved convective parameterizations may provide an avenue for improving simulations of tropical Pacific precipitation and SST.

Developing Parametric Models for the Assembly of Machine Fixtures for Virtual Multiaxial CNC Machining Centers

NASA Astrophysics Data System (ADS)

Balaykin, A. V.; Bezsonov, K. A.; Nekhoroshev, M. V.; Shulepov, A. P.

2018-01-01

This paper dwells upon a variance parameterization method. Variance or dimensional parameterization is based on sketching, with various parametric links superimposed on the sketch objects and user-imposed constraints in the form of an equation system that determines the parametric dependencies. This method is fully integrated in a top-down design methodology to enable the creation of multi-variant and flexible fixture assembly models, as all the modeling operations are hierarchically linked in the built tree. In this research the authors consider a parameterization method of machine tooling used for manufacturing parts using multiaxial CNC machining centers in the real manufacturing process. The developed method allows to significantly reduce tooling design time when making changes of a part’s geometric parameters. The method can also reduce time for designing and engineering preproduction, in particular, for development of control programs for CNC equipment and control and measuring machines, automate the release of design and engineering documentation. Variance parameterization helps to optimize construction of parts as well as machine tooling using integrated CAE systems. In the framework of this study, the authors demonstrate a comprehensive approach to parametric modeling of machine tooling in the CAD package used in the real manufacturing process of aircraft engines.

Global Modeling and Data Assimilation. Volume 11; Documentation of the Tangent Linear and Adjoint Models of the Relaxed Arakawa-Schubert Moisture Parameterization of the NASA GEOS-1 GCM; 5.2

NASA Technical Reports Server (NTRS)

Suarez, Max J. (Editor); Yang, Wei-Yu; Todling, Ricardo; Navon, I. Michael

1997-01-01

A detailed description of the development of the tangent linear model (TLM) and its adjoint model of the Relaxed Arakawa-Schubert moisture parameterization package used in the NASA GEOS-1 C-Grid GCM (Version 5.2) is presented. The notational conventions used in the TLM and its adjoint codes are described in detail.

Recent developments and assessment of a three-dimensional PBL parameterization for improved wind forecasting over complex terrain

NASA Astrophysics Data System (ADS)

Kosovic, B.; Jimenez, P. A.; Haupt, S. E.; Martilli, A.; Olson, J.; Bao, J. W.

2017-12-01

At present, the planetary boundary layer (PBL) parameterizations available in most numerical weather prediction (NWP) models are one-dimensional. One-dimensional parameterizations are based on the assumption of horizontal homogeneity. This homogeneity assumption is appropriate for grid cell sizes greater than 10 km. However, for mesoscale simulations of flows in complex terrain with grid cell sizes below 1 km, the assumption of horizontal homogeneity is violated. Applying a one-dimensional PBL parameterization to high-resolution mesoscale simulations in complex terrain could result in significant error. For high-resolution mesoscale simulations of flows in complex terrain, we have therefore developed and implemented a three-dimensional (3D) PBL parameterization in the Weather Research and Forecasting (WRF) model. The implementation of the 3D PBL scheme is based on the developments outlined by Mellor and Yamada (1974, 1982). Our implementation in the Weather Research and Forecasting (WRF) model uses a pure algebraic model (level 2) to diagnose the turbulent fluxes. To evaluate the performance of the 3D PBL model, we use observations from the Wind Forecast Improvement Project 2 (WFIP2). The WFIP2 field study took place in the Columbia River Gorge area from 2015-2017. We focus on selected cases when physical phenomena of significance for wind energy applications such as mountain waves, topographic wakes, and gap flows were observed. Our assessment of the 3D PBL parameterization also considers a large-eddy simulation (LES). We carried out a nested LES with grid cell sizes of 30 m and 10 m covering a large fraction of the WFIP2 study area. Both LES domains were discretized using 6000 x 3000 x 200 grid cells in zonal, meridional, and vertical direction, respectively. The LES results are used to assess the relative magnitude of horizontal gradients of turbulent stresses and fluxes in comparison to vertical gradients. The presentation will highlight the advantages of the 3D PBL scheme in regions of complex terrain.

Development of the PCAD Model to Assess Biological Significance of Acoustic Disturbance

DTIC Science & Technology

2015-09-30

We identified northern elephant seals and Atlantic bottlenose dolphins as the best species to parameterize the PCAD model. These species represent...transfer functions described above for southern elephant seals, our goals are to parameterize these models to make them applicable to other species and...northern elephant seal demographic data to estimate adult female survival, reproduction, and pup survival as a function of maternal condition. As a major

Pedotransfer functions in Earth system science: challenges and perspectives

NASA Astrophysics Data System (ADS)

Van Looy, K.; Minasny, B.; Nemes, A.; Verhoef, A.; Weihermueller, L.; Vereecken, H.

2017-12-01

We make a stronghold for a new generation of Pedotransfer functions (PTFs) that is currently developed in the different disciplines of Earth system science, offering strong perspectives for improvement of integrated process-based models, from local to global scale applications. PTFs are simple to complex knowledge rules that relate available soil information to soil properties and variables that are needed to parameterize soil processes. To meet the methodological challenges for a successful application in Earth system modeling, we highlight how PTF development needs to go hand in hand with suitable extrapolation and upscaling techniques such that the PTFs correctly capture the spatial heterogeneity of soils. Most actively pursued recent developments are related to parameterizations of solute transport, heat exchange, soil respiration and organic carbon content, root density and vegetation water uptake. We present an outlook and stepwise approach to the development of a comprehensive set of PTFs that can be applied throughout a wide range of disciplines of Earth system science, with emphasis on land surface models. Novel sensing techniques and soil information availability provide a true breakthrough for this, yet further improvements are necessary in three domains: 1) the determining of unknown relationships and dealing with uncertainty in Earth system modeling; 2) the step of spatially deploying this knowledge with PTF validation at regional to global scales; and 3) the integration and linking of the complex model parameterizations (coupled parameterization). Integration is an achievable goal we will show.

Stochastic Parameterization: Toward a New View of Weather and Climate Models

DOE PAGES

Berner, Judith; Achatz, Ulrich; Batté, Lauriane; ...

2017-03-31

The last decade has seen the success of stochastic parameterizations in short-term, medium-range, and seasonal forecasts: operational weather centers now routinely use stochastic parameterization schemes to represent model inadequacy better and to improve the quantification of forecast uncertainty. Developed initially for numerical weather prediction, the inclusion of stochastic parameterizations not only provides better estimates of uncertainty, but it is also extremely promising for reducing long-standing climate biases and is relevant for determining the climate response to external forcing. This article highlights recent developments from different research groups that show that the stochastic representation of unresolved processes in the atmosphere, oceans,more » land surface, and cryosphere of comprehensive weather and climate models 1) gives rise to more reliable probabilistic forecasts of weather and climate and 2) reduces systematic model bias. We make a case that the use of mathematically stringent methods for the derivation of stochastic dynamic equations will lead to substantial improvements in our ability to accurately simulate weather and climate at all scales. Recent work in mathematics, statistical mechanics, and turbulence is reviewed; its relevance for the climate problem is demonstrated; and future research directions are outlined« less

Stochastic Parameterization: Toward a New View of Weather and Climate Models

DOE Office of Scientific and Technical Information (OSTI.GOV)

Berner, Judith; Achatz, Ulrich; Batté, Lauriane

The last decade has seen the success of stochastic parameterizations in short-term, medium-range, and seasonal forecasts: operational weather centers now routinely use stochastic parameterization schemes to represent model inadequacy better and to improve the quantification of forecast uncertainty. Developed initially for numerical weather prediction, the inclusion of stochastic parameterizations not only provides better estimates of uncertainty, but it is also extremely promising for reducing long-standing climate biases and is relevant for determining the climate response to external forcing. This article highlights recent developments from different research groups that show that the stochastic representation of unresolved processes in the atmosphere, oceans,more » land surface, and cryosphere of comprehensive weather and climate models 1) gives rise to more reliable probabilistic forecasts of weather and climate and 2) reduces systematic model bias. We make a case that the use of mathematically stringent methods for the derivation of stochastic dynamic equations will lead to substantial improvements in our ability to accurately simulate weather and climate at all scales. Recent work in mathematics, statistical mechanics, and turbulence is reviewed; its relevance for the climate problem is demonstrated; and future research directions are outlined« less

Assessing the performance of wave breaking parameterizations in shallow waters in spectral wave models

NASA Astrophysics Data System (ADS)

Lin, Shangfei; Sheng, Jinyu

2017-12-01

Depth-induced wave breaking is the primary dissipation mechanism for ocean surface waves in shallow waters. Different parametrizations were developed for parameterizing depth-induced wave breaking process in ocean surface wave models. The performance of six commonly-used parameterizations in simulating significant wave heights (SWHs) is assessed in this study. The main differences between these six parameterizations are representations of the breaker index and the fraction of breaking waves. Laboratory and field observations consisting of 882 cases from 14 sources of published observational data are used in the assessment. We demonstrate that the six parameterizations have reasonable performance in parameterizing depth-induced wave breaking in shallow waters, but with their own limitations and drawbacks. The widely-used parameterization suggested by Battjes and Janssen (1978, BJ78) has a drawback of underpredicting the SWHs in the locally-generated wave conditions and overpredicting in the remotely-generated wave conditions over flat bottoms. The drawback of BJ78 was addressed by a parameterization suggested by Salmon et al. (2015, SA15). But SA15 had relatively larger errors in SWHs over sloping bottoms than BJ78. We follow SA15 and propose a new parameterization with a dependence of the breaker index on the normalized water depth in deep waters similar to SA15. In shallow waters, the breaker index of the new parameterization has a nonlinear dependence on the local bottom slope rather than the linear dependence used in SA15. Overall, this new parameterization has the best performance with an average scatter index of ∼8.2% in comparison with the three best performing existing parameterizations with the average scatter index between 9.2% and 13.6%.

Improving Convection and Cloud Parameterization Using ARM Observations and NCAR Community Atmosphere Model CAM5

DOE Office of Scientific and Technical Information (OSTI.GOV)

Zhang, Guang J.

2016-11-07

The fundamental scientific objectives of our research are to use ARM observations and the NCAR CAM5 to understand the large-scale control on convection, and to develop improved convection and cloud parameterizations for use in GCMs.

Improving and Understanding Climate Models: Scale-Aware Parameterization of Cloud Water Inhomogeneity and Sensitivity of MJO Simulation to Physical Parameters in a Convection Scheme

NASA Astrophysics Data System (ADS)

Xie, Xin

Microphysics and convection parameterizations are two key components in a climate model to simulate realistic climatology and variability of cloud distribution and the cycles of energy and water. When a model has varying grid size or simulations have to be run with different resolutions, scale-aware parameterization is desirable so that we do not have to tune model parameters tailored to a particular grid size. The subgrid variability of cloud hydrometers is known to impact microphysics processes in climate models and is found to highly depend on spatial scale. A scale- aware liquid cloud subgrid variability parameterization is derived and implemented in the Community Earth System Model (CESM) in this study using long-term radar-based ground measurements from the Atmospheric Radiation Measurement (ARM) program. When used in the default CESM1 with the finite-volume dynamic core where a constant liquid inhomogeneity parameter was assumed, the newly developed parameterization reduces the cloud inhomogeneity in high latitudes and increases it in low latitudes. This is due to both the smaller grid size in high latitudes, and larger grid size in low latitudes in the longitude-latitude grid setting of CESM as well as the variation of the stability of the atmosphere. The single column model and general circulation model (GCM) sensitivity experiments show that the new parameterization increases the cloud liquid water path in polar regions and decreases it in low latitudes. Current CESM1 simulation suffers from the bias of both the pacific double ITCZ precipitation and weak Madden-Julian oscillation (MJO). Previous studies show that convective parameterization with multiple plumes may have the capability to alleviate such biases in a more uniform and physical way. A multiple-plume mass flux convective parameterization is used in Community Atmospheric Model (CAM) to investigate the sensitivity of MJO simulations. We show that MJO simulation is sensitive to entrainment rate specification. We found that shallow plumes can generate and sustain the MJO propagation in the model.

Towards a more efficient and robust representation of subsurface hydrological processes in Earth System Models

NASA Astrophysics Data System (ADS)

Rosolem, R.; Rahman, M.; Kollet, S. J.; Wagener, T.

2017-12-01

Understanding the impacts of land cover and climate changes on terrestrial hydrometeorology is important across a range of spatial and temporal scales. Earth System Models (ESMs) provide a robust platform for evaluating these impacts. However, current ESMs lack the representation of key hydrological processes (e.g., preferential water flow, and direct interactions with aquifers) in general. The typical "free drainage" conceptualization of land models can misrepresent the magnitude of those interactions, consequently affecting the exchange of energy and water at the surface as well as estimates of groundwater recharge. Recent studies show the benefits of explicitly simulating the interactions between subsurface and surface processes in similar models. However, such parameterizations are often computationally demanding resulting in limited application for large/global-scale studies. Here, we take a different approach in developing a novel parameterization for groundwater dynamics. Instead of directly adding another complex process to an established land model, we examine a set of comprehensive experimental scenarios using a very robust and establish three-dimensional hydrological model to develop a simpler parameterization that represents the aquifer to land surface interactions. The main goal of our developed parameterization is to simultaneously maximize the computational gain (i.e., "efficiency") while minimizing simulation errors in comparison to the full 3D model (i.e., "robustness") to allow for easy implementation in ESMs globally. Our study focuses primarily on understanding both the dynamics for groundwater recharge and discharge, respectively. Preliminary results show that our proposed approach significantly reduced the computational demand while model deviations from the full 3D model are considered to be small for these processes.

COLLABORATIVE RESEARCH:USING ARM OBSERVATIONS & ADVANCED STATISTICAL TECHNIQUES TO EVALUATE CAM3 CLOUDS FOR DEVELOPMENT OF STOCHASTIC CLOUD-RADIATION

DOE Office of Scientific and Technical Information (OSTI.GOV)

Somerville, Richard

2013-08-22

The long-range goal of several past and current projects in our DOE-supported research has been the development of new and improved parameterizations of cloud-radiation effects and related processes, using ARM data, and the implementation and testing of these parameterizations in global models. The main objective of the present project being reported on here has been to develop and apply advanced statistical techniques, including Bayesian posterior estimates, to diagnose and evaluate features of both observed and simulated clouds. The research carried out under this project has been novel in two important ways. The first is that it is a key stepmore » in the development of practical stochastic cloud-radiation parameterizations, a new category of parameterizations that offers great promise for overcoming many shortcomings of conventional schemes. The second is that this work has brought powerful new tools to bear on the problem, because it has been a collaboration between a meteorologist with long experience in ARM research (Somerville) and a mathematician who is an expert on a class of advanced statistical techniques that are well-suited for diagnosing model cloud simulations using ARM observations (Shen).« less

Collaborative Research: Using ARM Observations to Evaluate GCM Cloud Statistics for Development of Stochastic Cloud-Radiation Parameterizations

DOE Office of Scientific and Technical Information (OSTI.GOV)

Shen, Samuel S. P.

2013-09-01

The long-range goal of several past and current projects in our DOE-supported research has been the development of new and improved parameterizations of cloud-radiation effects and related processes, using ARM data, and the implementation and testing of these parameterizations in global models. The main objective of the present project being reported on here has been to develop and apply advanced statistical techniques, including Bayesian posterior estimates, to diagnose and evaluate features of both observed and simulated clouds. The research carried out under this project has been novel in two important ways. The first is that it is a key stepmore » in the development of practical stochastic cloud-radiation parameterizations, a new category of parameterizations that offers great promise for overcoming many shortcomings of conventional schemes. The second is that this work has brought powerful new tools to bear on the problem, because it has been an interdisciplinary collaboration between a meteorologist with long experience in ARM research (Somerville) and a mathematician who is an expert on a class of advanced statistical techniques that are well-suited for diagnosing model cloud simulations using ARM observations (Shen). The motivation and long-term goal underlying this work is the utilization of stochastic radiative transfer theory (Lane-Veron and Somerville, 2004; Lane et al., 2002) to develop a new class of parametric representations of cloud-radiation interactions and closely related processes for atmospheric models. The theoretical advantage of the stochastic approach is that it can accurately calculate the radiative heating rates through a broken cloud layer without requiring an exact description of the cloud geometry.« less

Incorporation of New Convective Ice Microphysics into the NASA GISS GCM and Impacts on Cloud Ice Water Path (IWP) Simulation

NASA Technical Reports Server (NTRS)

Elsaesser, Greg; Del Genio, Anthony

2015-01-01

The CMIP5 configurations of the GISS Model-E2 GCM simulated a mid- and high latitude ice IWP that decreased by 50 relative to that simulated for CMIP3 (Jiang et al. 2012; JGR). Tropical IWP increased by 15 in CMIP5. While the tropical IWP was still within the published upper-bounds of IWP uncertainty derived using NASA A-Train satellite observations, it was found that the upper troposphere (200 mb) ice water content (IWC) exceeded the published upper-bound by a factor of 2. This was largely driven by IWC in deep-convecting regions of the tropics.Recent advances in the model-E2 convective parameterization have been found to have a substantial impact on tropical IWC. These advances include the development of both a cold pool parameterization (Del Genio et al. 2015) and new convective ice parameterization. In this presentation, we focus on the new parameterization of convective cloud ice that was developed using data from the NASA TC4 Mission. Ice particle terminal velocity formulations now include information from a number of NASA field campaigns. The new parameterization predicts both an ice water mass weighted-average particle diameter and a particle cross sectional area weighted-average size diameter as a function of temperature and ice water content. By assuming a gamma-distribution functional form for the particle size distribution, these two diameter estimates are all that are needed to explicitly predict the distribution of ice particles as a function of particle diameter.GCM simulations with the improved convective parameterization yield a 50 decrease in upper tropospheric IWC, bringing the tropical and global mean IWP climatologies into even closer agreement with the A-Train satellite observation best estimates.

Incorporation of New Convective Ice Microphysics into the NASA GISS GCM and Impacts on Cloud Ice Water Path (IWP) Simulation

NASA Astrophysics Data System (ADS)

Elsaesser, G.; Del Genio, A. D.

2015-12-01

The CMIP5 configurations of the GISS Model-E2 GCM simulated a mid- and high-latitude ice IWP that decreased by ~50% relative to that simulated for CMIP3 (Jiang et al. 2012; JGR). Tropical IWP increased by ~15% in CMIP5. While the tropical IWP was still within the published upper-bounds of IWP uncertainty derived using NASA A-Train satellite observations, it was found that the upper troposphere (~200 mb) ice water content (IWC) exceeded the published upper-bound by a factor of ~2. This was largely driven by IWC in deep-convecting regions of the tropics. Recent advances in the model-E2 convective parameterization have been found to have a substantial impact on tropical IWC. These advances include the development of both a cold pool parameterization (Del Genio et al. 2015) and new convective ice parameterization. In this presentation, we focus on the new parameterization of convective cloud ice that was developed using data from the NASA TC4 Mission. Ice particle terminal velocity formulations now include information from a number of NASA field campaigns. The new parameterization predicts both an ice water mass weighted-average particle diameter and a particle cross sectional area weighted-average size diameter as a function of temperature and ice water content. By assuming a gamma-distribution functional form for the particle size distribution, these two diameter estimates are all that are needed to explicitly predict the distribution of ice particles as a function of particle diameter. GCM simulations with the improved convective parameterization yield a ~50% decrease in upper tropospheric IWC, bringing the tropical and global mean IWP climatologies into even closer agreement with the A-Train satellite observation best estimates.

Inclusion of Solar Elevation Angle in Land Surface Albedo Parameterization Over Bare Soil Surface.

PubMed

Zheng, Zhiyuan; Wei, Zhigang; Wen, Zhiping; Dong, Wenjie; Li, Zhenchao; Wen, Xiaohang; Zhu, Xian; Ji, Dong; Chen, Chen; Yan, Dongdong

2017-12-01

Land surface albedo is a significant parameter for maintaining a balance in surface energy. It is also an important parameter of bare soil surface albedo for developing land surface process models that accurately reflect diurnal variation characteristics and the mechanism behind the solar spectral radiation albedo on bare soil surfaces and for understanding the relationships between climate factors and spectral radiation albedo. Using a data set of field observations, we conducted experiments to analyze the variation characteristics of land surface solar spectral radiation and the corresponding albedo over a typical Gobi bare soil underlying surface and to investigate the relationships between the land surface solar spectral radiation albedo, solar elevation angle, and soil moisture. Based on both solar elevation angle and soil moisture measurements simultaneously, we propose a new two-factor parameterization scheme for spectral radiation albedo over bare soil underlying surfaces. The results of numerical simulation experiments show that the new parameterization scheme can more accurately depict the diurnal variation characteristics of bare soil surface albedo than the previous schemes. Solar elevation angle is one of the most important factors for parameterizing bare soil surface albedo and must be considered in the parameterization scheme, especially in arid and semiarid areas with low soil moisture content. This study reveals the characteristics and mechanism of the diurnal variation of bare soil surface solar spectral radiation albedo and is helpful in developing land surface process models, weather models, and climate models.

Estimating the Contrail Impact on Climate Using the UK Met Office Model

NASA Astrophysics Data System (ADS)

Rap, A.; Forster, P. M.

2008-12-01

With air travel predicted to increase over the coming century, the emissions associated with air traffic are expected to have a significant warming effect on climate. According to current best estimates, an important contribution comes from contrails. However, as reported by the IPCC fourth assessment report, these current best estimates still have a high uncertainty. The development and validation of contrail parameterizations in global climate models is therefore very important. This current study develops a contrail parameterization within the UK Met Office Climate Model. Using this new parameterization, we estimate that for the 2002 traffic, the global mean annual contrail coverage is approximately 0.11%, a value which in good agreement with several other estimates. The corresponding contrail radiative forcing (RF) is calculated to be approximately 4 and 6 mWm-2 in all-sky and clear-sky conditions, respectively. These values lie within the lower end of the RF range reported by the latest IPCC assessment. The relatively high cloud masking effect on contrails observed by our parameterization compared with other studies is investigated, and a possible cause for this difference is suggested. The effect of the diurnal variations of air traffic on both contrail coverage and contrail RF is also investigated. The new parameterization is also employed in thirty-year slab-ocean model runs in order to give one of the first insights into contrail effects on daily temperature range and the climate impact of contrails.

Gravity Waves Generated by Convection: A New Idealized Model Tool and Direct Validation with Satellite Observations

NASA Astrophysics Data System (ADS)

Alexander, M. Joan; Stephan, Claudia

2015-04-01

In climate models, gravity waves remain too poorly resolved to be directly modelled. Instead, simplified parameterizations are used to include gravity wave effects on model winds. A few climate models link some of the parameterized waves to convective sources, providing a mechanism for feedback between changes in convection and gravity wave-driven changes in circulation in the tropics and above high-latitude storms. These convective wave parameterizations are based on limited case studies with cloud-resolving models, but they are poorly constrained by observational validation, and tuning parameters have large uncertainties. Our new work distills results from complex, full-physics cloud-resolving model studies to essential variables for gravity wave generation. We use the Weather Research Forecast (WRF) model to study relationships between precipitation, latent heating/cooling and other cloud properties to the spectrum of gravity wave momentum flux above midlatitude storm systems. Results show the gravity wave spectrum is surprisingly insensitive to the representation of microphysics in WRF. This is good news for use of these models for gravity wave parameterization development since microphysical properties are a key uncertainty. We further use the full-physics cloud-resolving model as a tool to directly link observed precipitation variability to gravity wave generation. We show that waves in an idealized model forced with radar-observed precipitation can quantitatively reproduce instantaneous satellite-observed features of the gravity wave field above storms, which is a powerful validation of our understanding of waves generated by convection. The idealized model directly links observations of surface precipitation to observed waves in the stratosphere, and the simplicity of the model permits deep/large-area domains for studies of wave-mean flow interactions. This unique validated model tool permits quantitative studies of gravity wave driving of regional circulation and provides a new method for future development of realistic convective gravity wave parameterizations.

New Parameterizations for Neutral and Ion-Induced Sulfuric Acid-Water Particle Formation in Nucleation and Kinetic Regimes

NASA Astrophysics Data System (ADS)

Määttänen, Anni; Merikanto, Joonas; Henschel, Henning; Duplissy, Jonathan; Makkonen, Risto; Ortega, Ismael K.; Vehkamäki, Hanna

2018-01-01

We have developed new parameterizations of electrically neutral homogeneous and ion-induced sulfuric acid-water particle formation for large ranges of environmental conditions, based on an improved model that has been validated against a particle formation rate data set produced by Cosmics Leaving OUtdoor Droplets (CLOUD) experiments at European Organization for Nuclear Research (CERN). The model uses a thermodynamically consistent version of the Classical Nucleation Theory normalized using quantum chemical data. Unlike the earlier parameterizations for H2SO4-H2O nucleation, the model is applicable to extreme dry conditions where the one-component sulfuric acid limit is approached. Parameterizations are presented for the critical cluster sulfuric acid mole fraction, the critical cluster radius, the total number of molecules in the critical cluster, and the particle formation rate. If the critical cluster contains only one sulfuric acid molecule, a simple formula for kinetic particle formation can be used: this threshold has also been parameterized. The parameterization for electrically neutral particle formation is valid for the following ranges: temperatures 165-400 K, sulfuric acid concentrations 104-1013 cm-3, and relative humidities 0.001-100%. The ion-induced particle formation parameterization is valid for temperatures 195-400 K, sulfuric acid concentrations 104-1016 cm-3, and relative humidities 10-5-100%. The new parameterizations are thus applicable for the full range of conditions in the Earth's atmosphere relevant for binary sulfuric acid-water particle formation, including both tropospheric and stratospheric conditions. They are also suitable for describing particle formation in the atmosphere of Venus.

Developing a Physiologically-Based Pharmacokinetic Model Knowledgebase in Support of Provisional Model Construction

EPA Science Inventory

Developing physiologically-based pharmacokinetic (PBPK) models for chemicals can be resource-intensive, as neither chemical-specific parameters nor in vivo pharmacokinetic data are easily available for model construction. Previously developed, well-parameterized, and thoroughly-v...

Developing Remote Sensing Products for Monitoring and Modeling Great Lakes Coastal Wetland Vulnerability to Climate Change and Land Use

NASA Astrophysics Data System (ADS)

Bourgeau-Chavez, L. L.; Miller, M. E.; Battaglia, M.; Banda, E.; Endres, S.; Currie, W. S.; Elgersma, K. J.; French, N. H. F.; Goldberg, D. E.; Hyndman, D. W.

2014-12-01

Spread of invasive plant species in the coastal wetlands of the Great Lakes is degrading wetland habitat, decreasing biodiversity, and decreasing ecosystem services. An understanding of the mechanisms of invasion is crucial to gaining control of this growing threat. To better understand the effects of land use and climatic drivers on the vulnerability of coastal zones to invasion, as well as to develop an understanding of the mechanisms of invasion, research is being conducted that integrates field studies, process-based ecosystem and hydrological models, and remote sensing. Spatial data from remote sensing is needed to parameterize the hydrological model and to test the outputs of the linked models. We will present several new remote sensing products that are providing important physiological, biochemical, and landscape information to parameterize and verify models. This includes a novel hybrid radar-optical technique to delineate stands of invasives, as well as natural wetland cover types; using radar to map seasonally inundated areas not hydrologically connected; and developing new algorithms to estimate leaf area index (LAI) using Landsat. A coastal map delineating wetland types including monocultures of the invaders (Typha spp. and Phragmites austrailis) was created using satellite radar (ALOS PALSAR, 20 m resolution) and optical data (Landsat 5, 30 m resolution) fusion from multiple dates in a Random Forests classifier. These maps provide verification of the integrated model showing areas at high risk of invasion. For parameterizing the hydrological model, maps of seasonal wetness are being developed using spring (wet) imagery and differencing that with summer (dry) imagery to detect the seasonally wet areas. Finally, development of LAI remote sensing high resolution algorithms for uplands and wetlands is underway. LAI algorithms for wetlands have not been previously developed due to the difficulty of a water background. These products are being used to improve the hydrological model through higher resolution products and parameterization of variables that have previously been largely unknown.

Simple liquid models with corrected dielectric constants

PubMed Central

Fennell, Christopher J.; Li, Libo; Dill, Ken A.

2012-01-01

Molecular simulations often use explicit-solvent models. Sometimes explicit-solvent models can give inaccurate values for basic liquid properties, such as the density, heat capacity, and permittivity, as well as inaccurate values for molecular transfer free energies. Such errors have motivated the development of more complex solvents, such as polarizable models. We describe an alternative here. We give new fixed-charge models of solvents for molecular simulations – water, carbon tetrachloride, chloroform and dichloromethane. Normally, such solvent models are parameterized to agree with experimental values of the neat liquid density and enthalpy of vaporization. Here, in addition to those properties, our parameters are chosen to give the correct dielectric constant. We find that these new parameterizations also happen to give better values for other properties, such as the self-diffusion coefficient. We believe that parameterizing fixed-charge solvent models to fit experimental dielectric constants may provide better and more efficient ways to treat solvents in computer simulations. PMID:22397577

Trade-Wind Cloudiness and Climate

NASA Technical Reports Server (NTRS)

Randall, David A.

1997-01-01

Closed Mesoscale Cellular Convection (MCC) consists of mesoscale cloud patches separated by narrow clear regions. Strong radiative cooling occurs at the cloud top. A dry two-dimensional Bousinesq model is used to study the effects of cloud-top cooling on convection. Wide updrafts and narrow downdrafts are used to indicate the asymmetric circulations associated with the mesoscale cloud patches. Based on the numerical results, a conceptual model was constructed to suggest a mechanism for the formation of closed MCC over cool ocean surfaces. A new method to estimate the radioative and evaporative cooling in the entrainment layer of a stratocumulus-topped boundary layer has been developed. The method was applied to a set of Large-Eddy Simulation (LES) results and to a set of tethered-balloon data obtained during FIRE. We developed a statocumulus-capped marine mixed layer model which includes a parameterization of drizzle based on the use of a predicted Cloud Condensation Nuclei (CCN) number concentration. We have developed, implemented, and tested a very elaborate new stratiform cloudiness parameterization for use in GCMs. Finally, we have developed a new, mechanistic parameterization of the effects of cloud-top cooling on the entrainment rate.

A one-dimensional interactive soil-atmosphere model for testing formulations of surface hydrology

NASA Technical Reports Server (NTRS)

Koster, Randal D.; Eagleson, Peter S.

1990-01-01

A model representing a soil-atmosphere column in a GCM is developed for off-line testing of GCM soil hydrology parameterizations. Repeating three representative GCM sensitivity experiments with this one-dimensional model demonstrates that, to first order, the model reproduces a GCM's sensitivity to imposed changes in parameterization and therefore captures the essential physics of the GCM. The experiments also show that by allowing feedback between the soil and atmosphere, the model improves on off-line tests that rely on prescribed precipitation, radiation, and other surface forcing.

Are atmospheric updrafts a key to unlocking climate forcing and sensitivity?

DOE PAGES

Donner, Leo J.; O'Brien, Travis A.; Rieger, Daniel; ...

2016-10-20

Both climate forcing and climate sensitivity persist as stubborn uncertainties limiting the extent to which climate models can provide actionable scientific scenarios for climate change. A key, explicit control on cloud–aerosol interactions, the largest uncertainty in climate forcing, is the vertical velocity of cloud-scale updrafts. Model-based studies of climate sensitivity indicate that convective entrainment, which is closely related to updraft speeds, is an important control on climate sensitivity. Updraft vertical velocities also drive many physical processes essential to numerical weather prediction. Vertical velocities and their role in atmospheric physical processes have been given very limited attention in models for climatemore » and numerical weather prediction. The relevant physical scales range down to tens of meters and are thus frequently sub-grid and require parameterization. Many state-of-science convection parameterizations provide mass fluxes without specifying Vertical velocities and their role in atmospheric physical processes have been given very limited attention in models for climate and numerical weather prediction. The relevant physical scales range down to tens of meters and are thus frequently sub-grid and require parameterization. Many state-of-science convection parameterizations provide mass fluxes without specifying vs in climate models may capture this behavior, but it has not been accounted for when parameterizing cloud and precipitation processes in current models. New observations of convective vertical velocities offer a potentially promising path toward developing process-level cloud models and parameterizations for climate and numerical weather prediction. Taking account of the scale dependence of resolved vertical velocities offers a path to matching cloud-scale physical processes and their driving dynamics more realistically, with a prospect of reduced uncertainty in both climate forcing and sensitivity.« less

Are atmospheric updrafts a key to unlocking climate forcing and sensitivity?

DOE Office of Scientific and Technical Information (OSTI.GOV)

Donner, Leo J.; O'Brien, Travis A.; Rieger, Daniel

Both climate forcing and climate sensitivity persist as stubborn uncertainties limiting the extent to which climate models can provide actionable scientific scenarios for climate change. A key, explicit control on cloud–aerosol interactions, the largest uncertainty in climate forcing, is the vertical velocity of cloud-scale updrafts. Model-based studies of climate sensitivity indicate that convective entrainment, which is closely related to updraft speeds, is an important control on climate sensitivity. Updraft vertical velocities also drive many physical processes essential to numerical weather prediction. Vertical velocities and their role in atmospheric physical processes have been given very limited attention in models for climatemore » and numerical weather prediction. The relevant physical scales range down to tens of meters and are thus frequently sub-grid and require parameterization. Many state-of-science convection parameterizations provide mass fluxes without specifying Vertical velocities and their role in atmospheric physical processes have been given very limited attention in models for climate and numerical weather prediction. The relevant physical scales range down to tens of meters and are thus frequently sub-grid and require parameterization. Many state-of-science convection parameterizations provide mass fluxes without specifying vs in climate models may capture this behavior, but it has not been accounted for when parameterizing cloud and precipitation processes in current models. New observations of convective vertical velocities offer a potentially promising path toward developing process-level cloud models and parameterizations for climate and numerical weather prediction. Taking account of the scale dependence of resolved vertical velocities offers a path to matching cloud-scale physical processes and their driving dynamics more realistically, with a prospect of reduced uncertainty in both climate forcing and sensitivity.« less

Land surface hydrology parameterization for atmospheric general circulation models including subgrid scale spatial variability

NASA Technical Reports Server (NTRS)

Entekhabi, D.; Eagleson, P. S.

1989-01-01

Parameterizations are developed for the representation of subgrid hydrologic processes in atmospheric general circulation models. Reasonable a priori probability density functions of the spatial variability of soil moisture and of precipitation are introduced. These are used in conjunction with the deterministic equations describing basic soil moisture physics to derive expressions for the hydrologic processes that include subgrid scale variation in parameters. The major model sensitivities to soil type and to climatic forcing are explored.

Stochastic parameterization of shallow cumulus convection estimated from high-resolution model data

NASA Astrophysics Data System (ADS)

Dorrestijn, Jesse; Crommelin, Daan T.; Siebesma, A. Pier.; Jonker, Harm J. J.

2013-02-01

In this paper, we report on the development of a methodology for stochastic parameterization of convective transport by shallow cumulus convection in weather and climate models. We construct a parameterization based on Large-Eddy Simulation (LES) data. These simulations resolve the turbulent fluxes of heat and moisture and are based on a typical case of non-precipitating shallow cumulus convection above sea in the trade-wind region. Using clustering, we determine a finite number of turbulent flux pairs for heat and moisture that are representative for the pairs of flux profiles observed in these simulations. In the stochastic parameterization scheme proposed here, the convection scheme jumps randomly between these pre-computed pairs of turbulent flux profiles. The transition probabilities are estimated from the LES data, and they are conditioned on the resolved-scale state in the model column. Hence, the stochastic parameterization is formulated as a data-inferred conditional Markov chain (CMC), where each state of the Markov chain corresponds to a pair of turbulent heat and moisture fluxes. The CMC parameterization is designed to emulate, in a statistical sense, the convective behaviour observed in the LES data. The CMC is tested in single-column model (SCM) experiments. The SCM is able to reproduce the ensemble spread of the temperature and humidity that was observed in the LES data. Furthermore, there is a good similarity between time series of the fractions of the discretized fluxes produced by SCM and observed in LES.

DOE Office of Scientific and Technical Information (OSTI.GOV)

Barnes, Hannah C.; Houze, Robert A.

To equitably compare the spatial pattern of ice microphysical processes produced by three microphysical parameterizations with each other, observations, and theory, simulations of tropical oceanic mesoscale convective systems (MCSs) in the Weather Research and Forecasting (WRF) model were forced to develop the same mesoscale circulations as observations by assimilating radial velocity data from a Doppler radar. The same general layering of microphysical processes was found in observations and simulations with deposition anywhere above the 0°C level, aggregation at and above the 0°C level, melting at and below the 0°C level, and riming near the 0°C level. Thus, this study ismore » consistent with the layered ice microphysical pattern portrayed in previous conceptual models and indicated by dual-polarization radar data. Spatial variability of riming in the simulations suggests that riming in the midlevel inflow is related to convective-scale vertical velocity perturbations. Finally, this study sheds light on limitations of current generally available bulk microphysical parameterizations. In each parameterization, the layers in which aggregation and riming took place were generally too thick and the frequency of riming was generally too high compared to the observations and theory. Additionally, none of the parameterizations produced similar details in every microphysical spatial pattern. Discrepancies in the patterns of microphysical processes between parameterizations likely factor into creating substantial differences in model reflectivity patterns. It is concluded that improved parameterizations of ice-phase microphysics will be essential to obtain reliable, consistent model simulations of tropical oceanic MCSs.« less

Parameterization of N2O5 Reaction Probabilities on the Surface of Particles Containing Ammonium, Sulfate, and Nitrate

EPA Science Inventory

A comprehensive parameterization was developed for the heterogeneous reaction probability (γ) of N₂O₅ as a function of temperature, relative humidity, particle composition, and phase state, for use in advanced air quality models. The reaction probabilities o...

Uncertainty and feasibility of dynamical downscaling for modeling tropical cyclones for storm surge simulation

DOE Office of Scientific and Technical Information (OSTI.GOV)

Yang, Zhaoqing; Taraphdar, Sourav; Wang, Taiping

This paper presents a modeling study conducted to evaluate the uncertainty of a regional model in simulating hurricane wind and pressure fields, and the feasibility of driving coastal storm surge simulation using an ensemble of region model outputs produced by 18 combinations of three convection schemes and six microphysics parameterizations, using Hurricane Katrina as a test case. Simulated wind and pressure fields were compared to observed H*Wind data for Hurricane Katrina and simulated storm surge was compared to observed high-water marks on the northern coast of the Gulf of Mexico. The ensemble modeling analysis demonstrated that the regional model wasmore » able to reproduce the characteristics of Hurricane Katrina with reasonable accuracy and can be used to drive the coastal ocean model for simulating coastal storm surge. Results indicated that the regional model is sensitive to both convection and microphysics parameterizations that simulate moist processes closely linked to the tropical cyclone dynamics that influence hurricane development and intensification. The Zhang and McFarlane (ZM) convection scheme and the Lim and Hong (WDM6) microphysics parameterization are the most skillful in simulating Hurricane Katrina maximum wind speed and central pressure, among the three convection and the six microphysics parameterizations. Error statistics of simulated maximum water levels were calculated for a baseline simulation with H*Wind forcing and the 18 ensemble simulations driven by the regional model outputs. The storm surge model produced the overall best results in simulating the maximum water levels using wind and pressure fields generated with the ZM convection scheme and the WDM6 microphysics parameterization.« less

Parameterized hardware description as object oriented hardware model implementation

NASA Astrophysics Data System (ADS)

Drabik, Pawel K.

2010-09-01

The paper introduces novel model for design, visualization and management of complex, highly adaptive hardware systems. The model settles component oriented environment for both hardware modules and software application. It is developed on parameterized hardware description research. Establishment of stable link between hardware and software, as a purpose of designed and realized work, is presented. Novel programming framework model for the environment, named Graphic-Functional-Components is presented. The purpose of the paper is to present object oriented hardware modeling with mentioned features. Possible model implementation in FPGA chips and its management by object oriented software in Java is described.

Updating sea spray aerosol emissions in the Community Multiscale Air Quality (CMAQ) model version 5.0.2

EPA Pesticide Factsheets

The uploaded data consists of the BRACE Na aerosol observations paired with CMAQ model output, the updated model's parameterization of sea salt aerosol emission size distribution, and the model's parameterization of the sea salt emission factor as a function of sea surface temperature. This dataset is associated with the following publication:Gantt , B., J. Kelly , and J. Bash. Updating sea spray aerosol emissions in the Community Multiscale Air Quality (CMAQ) model version 5.0.2. Geoscientific Model Development. Copernicus Publications, Katlenburg-Lindau, GERMANY, 8: 3733-3746, (2015).

A second-order Budkyo-type parameterization of landsurface hydrology

NASA Technical Reports Server (NTRS)

Andreou, S. A.; Eagleson, P. S.

1982-01-01

A simple, second order parameterization of the water fluxes at a land surface for use as the appropriate boundary condition in general circulation models of the global atmosphere was developed. The derived parameterization incorporates the high nonlinearities in the relationship between the near surface soil moisture and the evaporation, runoff and percolation fluxes. Based on the one dimensional statistical dynamic derivation of the annual water balance, it makes the transition to short term prediction of the moisture fluxes, through a Taylor expansion around the average annual soil moisture. A comparison of the suggested parameterization is made with other existing techniques and available measurements. A thermodynamic coupling is applied in order to obtain estimations of the surface ground temperature.

FIRE Science Results 1989

NASA Technical Reports Server (NTRS)

Mcdougal, David S. (Editor)

1990-01-01

FIRE (First ISCCP Regional Experiment) is a U.S. cloud-radiation research program formed in 1984 to increase the basic understanding of cirrus and marine stratocumulus cloud systems, to develop realistic parameterizations for these systems, and to validate and improve ISCCP cloud product retrievals. Presentations of results culminating the first 5 years of FIRE research activities were highlighted. The 1986 Cirrus Intensive Field Observations (IFO), the 1987 Marine Stratocumulus IFO, the Extended Time Observations (ETO), and modeling activities are described. Collaborative efforts involving the comparison of multiple data sets, incorporation of data measurements into modeling activities, validation of ISCCP cloud parameters, and development of parameterization schemes for General Circulation Models (GCMs) are described.

Simulating Aerosol Indirect Effects with Improved Aerosol-Cloud- Precipitation Representations in a Coupled Regional Climate Model

DOE Office of Scientific and Technical Information (OSTI.GOV)

Zhang, Yang; Leung, L. Ruby; Fan, Jiwen

This is a collaborative project among North Carolina State University, Pacific Northwest National Laboratory, and Scripps Institution of Oceanography, University of California at San Diego to address the critical need for an accurate representation of aerosol indirect effect in climate and Earth system models. In this project, we propose to develop and improve parameterizations of aerosol-cloud-precipitation feedbacks in climate models and apply them to study the effect of aerosols and clouds on radiation and hydrologic cycle. Our overall objective is to develop, improve, and evaluate parameterizations to enable more accurate simulations of these feedbacks in high resolution regional and globalmore » climate models.« less

Vertical structure of mean cross-shore currents across a barred surf zone

USGS Publications Warehouse

Haines, John W.; Sallenger, Asbury H.

1994-01-01

Mean cross-shore currents observed across a barred surf zone are compared to model predictions. The model is based on a simplified momentum balance with a turbulent boundary layer at the bed. Turbulent exchange is parameterized by an eddy viscosity formulation, with the eddy viscosity Aυ independent of time and the vertical coordinate. Mean currents result from gradients due to wave breaking and shoaling, and the presence of a mean setup of the free surface. Descriptions of the wave field are provided by the wave transformation model of Thornton and Guza [1983]. The wave transformation model adequately reproduces the observed wave heights across the surf zone. The mean current model successfully reproduces the observed cross-shore flows. Both observations and predictions show predominantly offshore flow with onshore flow restricted to a relatively thin surface layer. Successful application of the mean flow model requires an eddy viscosity which varies horizontally across the surf zone. Attempts are made to parameterize this variation with some success. The data does not discriminate between alternative parameterizations proposed. The overall variability in eddy viscosity suggested by the model fitting should be resolvable by field measurements of the turbulent stresses. Consistent shortcomings of the parameterizations, and the overall modeling effort, suggest avenues for further development and data collection.

Modeling the interplay between sea ice formation and the oceanic mixed layer: Limitations of simple brine rejection parameterizations

NASA Astrophysics Data System (ADS)

Barthélemy, Antoine; Fichefet, Thierry; Goosse, Hugues; Madec, Gurvan

2015-02-01

The subtle interplay between sea ice formation and ocean vertical mixing is hardly represented in current large-scale models designed for climate studies. Convective mixing caused by the brine release when ice forms is likely to prevail in leads and thin ice areas, while it occurs in models at the much larger horizontal grid cell scale. Subgrid-scale parameterizations have hence been developed to mimic the effects of small-scale convection using a vertical distribution of the salt rejected by sea ice within the mixed layer, instead of releasing it in the top ocean layer. Such a brine rejection parameterization is included in the global ocean-sea ice model NEMO-LIM3. Impacts on the simulated mixed layers and ocean temperature and salinity profiles, along with feedbacks on the sea ice cover, are then investigated in both hemispheres. The changes are overall relatively weak, except for mixed layer depths, which are in general excessively reduced compared to observation-based estimates. While potential model biases prevent a definitive attribution of this vertical mixing underestimation to the brine rejection parameterization, it is unlikely that the latter can be applied in all conditions. In that case, salt rejections do not play any role in mixed layer deepening, which is unrealistic. Applying the parameterization only for low ice-ocean relative velocities improves model results, but introduces additional parameters that are not well constrained by observations.

Modelling the interplay between sea ice formation and the oceanic mixed layer: limitations of simple brine rejection parameterizations

NASA Astrophysics Data System (ADS)

Barthélemy, Antoine; Fichefet, Thierry; Goosse, Hugues; Madec, Gurvan

2015-04-01

The subtle interplay between sea ice formation and ocean vertical mixing is hardly represented in current large-scale models designed for climate studies. Convective mixing caused by the brine release when ice forms is likely to prevail in leads and thin ice areas, while it occurs in models at the much larger horizontal grid cell scale. Subgrid-scale parameterizations have hence been developed to mimic the effects of small-scale convection using a vertical distribution of the salt rejected by sea ice within the mixed layer, instead of releasing it in the top ocean layer. Such a brine rejection parameterization is included in the global ocean--sea ice model NEMO-LIM3. Impacts on the simulated mixed layers and ocean temperature and salinity profiles, along with feedbacks on the sea ice cover, are then investigated in both hemispheres. The changes are overall relatively weak, except for mixed layer depths, which are in general excessively reduced compared to observation-based estimates. While potential model biases prevent a definitive attribution of this vertical mixing underestimation to the brine rejection parameterization, it is unlikely that the latter can be applied in all conditions. In that case, salt rejections do not play any role in mixed layer deepening, which is unrealistic. Applying the parameterization only for low ice--ocean relative velocities improves model results, but introduces additional parameters that are not well constrained by observations.

A revised linear ozone photochemistry parameterization for use in transport and general circulation models: multi-annual simulations

NASA Astrophysics Data System (ADS)

Cariolle, D.; Teyssèdre, H.

2007-01-01

This article describes the validation of a linear parameterization of the ozone photochemistry for use in upper tropospheric and stratospheric studies. The present work extends a previously developed scheme by improving the 2D model used to derive the coefficients of the parameterization. The chemical reaction rates are updated from a compilation that includes recent laboratory works. Furthermore, the polar ozone destruction due to heterogeneous reactions at the surface of the polar stratospheric clouds is taken into account as a function of the stratospheric temperature and the total chlorine content. Two versions of the parameterization are tested. The first one only requires the resolution of a continuity equation for the time evolution of the ozone mixing ratio, the second one uses one additional equation for a cold tracer. The parameterization has been introduced into the chemical transport model MOCAGE. The model is integrated with wind and temperature fields from the ECMWF operational analyses over the period 2000-2004. Overall, the results show a very good agreement between the modelled ozone distribution and the Total Ozone Mapping Spectrometer (TOMS) satellite data and the "in-situ" vertical soundings. During the course of the integration the model does not show any drift and the biases are generally small. The model also reproduces fairly well the polar ozone variability, with notably the formation of "ozone holes" in the southern hemisphere with amplitudes and seasonal evolutions that follow the dynamics and time evolution of the polar vortex. The introduction of the cold tracer further improves the model simulation by allowing additional ozone destruction inside air masses exported from the high to the mid-latitudes, and by maintaining low ozone contents inside the polar vortex of the southern hemisphere over longer periods in spring time. It is concluded that for the study of climatic scenarios or the assimilation of ozone data, the present parameterization gives an interesting alternative to the introduction of detailed and computationally costly chemical schemes into general circulation models.

Parameterization, sensitivity analysis, and inversion: an investigation using groundwater modeling of the surface-mined Tivoli-Guidonia basin (Metropolitan City of Rome, Italy)

NASA Astrophysics Data System (ADS)

La Vigna, Francesco; Hill, Mary C.; Rossetto, Rudy; Mazza, Roberto

2016-09-01

With respect to model parameterization and sensitivity analysis, this work uses a practical example to suggest that methods that start with simple models and use computationally frugal model analysis methods remain valuable in any toolbox of model development methods. In this work, groundwater model calibration starts with a simple parameterization that evolves into a moderately complex model. The model is developed for a water management study of the Tivoli-Guidonia basin (Rome, Italy) where surface mining has been conducted in conjunction with substantial dewatering. The approach to model development used in this work employs repeated analysis using sensitivity and inverse methods, including use of a new observation-stacked parameter importance graph. The methods are highly parallelizable and require few model runs, which make the repeated analyses and attendant insights possible. The success of a model development design can be measured by insights attained and demonstrated model accuracy relevant to predictions. Example insights were obtained: (1) A long-held belief that, except for a few distinct fractures, the travertine is homogeneous was found to be inadequate, and (2) The dewatering pumping rate is more critical to model accuracy than expected. The latter insight motivated additional data collection and improved pumpage estimates. Validation tests using three other recharge and pumpage conditions suggest good accuracy for the predictions considered. The model was used to evaluate management scenarios and showed that similar dewatering results could be achieved using 20 % less pumped water, but would require installing newly positioned wells and cooperation between mine owners.

A new scheme for the parameterization of the turbulent planetary boundary layer in the GLAS fourth order GCM

NASA Technical Reports Server (NTRS)

Helfand, H. M.

1985-01-01

Methods being used to increase the horizontal and vertical resolution and to implement more sophisticated parameterization schemes for general circulation models (GCM) run on newer, more powerful computers are described. Attention is focused on the NASA-Goddard Laboratory for Atmospherics fourth order GCM. A new planetary boundary layer (PBL) model has been developed which features explicit resolution of two or more layers. Numerical models are presented for parameterizing the turbulent vertical heat, momentum and moisture fluxes at the earth's surface and between the layers in the PBL model. An extended Monin-Obhukov similarity scheme is applied to express the relationships between the lowest levels of the GCM and the surface fluxes. On-line weather prediction experiments are to be run to test the effects of the higher resolution thereby obtained for dynamic atmospheric processes.

A cloudy planetary boundary layer oscillation arising from the coupling of turbulence with precipitation in climate simulations

DOE Office of Scientific and Technical Information (OSTI.GOV)

Zheng, X.; Klein, S. A.; Ma, H. -Y.

The Community Atmosphere Model (CAM) adopts Cloud Layers Unified By Binormals (CLUBB) scheme and an updated microphysics (MG2) scheme for a more unified treatment of cloud processes. This makes interactions between parameterizations tighter and more explicit. In this study, a cloudy planetary boundary layer (PBL) oscillation related to interaction between CLUBB and MG2 is identified in CAM. This highlights the need for consistency between the coupled subgrid processes in climate model development. This oscillation occurs most often in the marine cumulus cloud regime. The oscillation occurs only if the modeled PBL is strongly decoupled and precipitation evaporates below the cloud.more » Two aspects of the parameterized coupling assumptions between CLUBB and MG2 schemes cause the oscillation: (1) a parameterized relationship between rain evaporation and CLUBB's subgrid spatial variance of moisture and heat that induces an extra cooling in the lower PBL and (2) rain evaporation which happens at a too low an altitude because of the precipitation fraction parameterization in MG2. Either one of these two conditions can overly stabilize the PBL and reduce the upward moisture transport to the cloud layer so that the PBL collapses. Global simulations prove that turning off the evaporation-variance coupling and improving the precipitation fraction parameterization effectively reduces the cloudy PBL oscillation in marine cumulus clouds. By evaluating the causes of the oscillation in CAM, we have identified the PBL processes that should be examined in models having similar oscillations. This study may draw the attention of the modeling and observational communities to the issue of coupling between parameterized physical processes.« less

A cloudy planetary boundary layer oscillation arising from the coupling of turbulence with precipitation in climate simulations

DOE PAGES

Zheng, X.; Klein, S. A.; Ma, H. -Y.; ...

2017-08-24

The Community Atmosphere Model (CAM) adopts Cloud Layers Unified By Binormals (CLUBB) scheme and an updated microphysics (MG2) scheme for a more unified treatment of cloud processes. This makes interactions between parameterizations tighter and more explicit. In this study, a cloudy planetary boundary layer (PBL) oscillation related to interaction between CLUBB and MG2 is identified in CAM. This highlights the need for consistency between the coupled subgrid processes in climate model development. This oscillation occurs most often in the marine cumulus cloud regime. The oscillation occurs only if the modeled PBL is strongly decoupled and precipitation evaporates below the cloud.more » Two aspects of the parameterized coupling assumptions between CLUBB and MG2 schemes cause the oscillation: (1) a parameterized relationship between rain evaporation and CLUBB's subgrid spatial variance of moisture and heat that induces an extra cooling in the lower PBL and (2) rain evaporation which happens at a too low an altitude because of the precipitation fraction parameterization in MG2. Either one of these two conditions can overly stabilize the PBL and reduce the upward moisture transport to the cloud layer so that the PBL collapses. Global simulations prove that turning off the evaporation-variance coupling and improving the precipitation fraction parameterization effectively reduces the cloudy PBL oscillation in marine cumulus clouds. By evaluating the causes of the oscillation in CAM, we have identified the PBL processes that should be examined in models having similar oscillations. This study may draw the attention of the modeling and observational communities to the issue of coupling between parameterized physical processes.« less

77 FR 61604 - Exposure Modeling Public Meeting; Notice of Public Meeting

Federal Register 2010, 2011, 2012, 2013, 2014

2012-10-10

..., birds, reptiles, and amphibians: Model Parameterization and Knowledge base Development. 4. Standard Operating Procedure for calculating degradation kinetics. 5. Aquatic exposure modeling using field studies...

Prototype Mcs Parameterization for Global Climate Models

NASA Astrophysics Data System (ADS)

Moncrieff, M. W.

2017-12-01

Excellent progress has been made with observational, numerical and theoretical studies of MCS processes but the parameterization of those processes remain in a dire state and are missing from GCMs. The perceived complexity of the distribution, type, and intensity of organized precipitation systems has arguably daunted attention and stifled the development of adequate parameterizations. TRMM observations imply links between convective organization and large-scale meteorological features in the tropics and subtropics that are inadequately treated by GCMs. This calls for improved physical-dynamical treatment of organized convection to enable the next-generation of GCMs to reliably address a slew of challenges. The multiscale coherent structure parameterization (MCSP) paradigm is based on the fluid-dynamical concept of coherent structures in turbulent environments. The effects of vertical shear on MCS dynamics implemented as 2nd baroclinic convective heating and convective momentum transport is based on Lagrangian conservation principles, nonlinear dynamical models, and self-similarity. The prototype MCS parameterization, a minimalist proof-of-concept, is applied in the NCAR Community Climate Model, Version 5.5 (CAM 5.5). The MCSP generates convectively coupled tropical waves and large-scale precipitation features notably in the Indo-Pacific warm-pool and Maritime Continent region, a center-of-action for weather and climate variability around the globe.

Demonstration of Effects on Tropical Cyclone Forecasts with a High Resolution Global Model from Variation in Cumulus Convection Parameterization

NASA Technical Reports Server (NTRS)

Miller, Timothy L.; Robertson, Franklin R.; Cohen, Charles; Mackaro, Jessica

2009-01-01

The Goddard Earth Observing System Model, Version 5 (GEOS-5) is a system of models that have been developed at Goddard Space Flight Center to support NASA's earth science research in data analysis, observing system modeling and design, climate and weather prediction, and basic research. The work presented used GEOS-5 with 0.25o horizontal resolution and 72 vertical levels (up to 0.01 hP) resolving both the troposphere and stratosphere, with closer packing of the levels close to the surface. The model includes explicit (grid-scale) moist physics, as well as convective parameterization schemes. Results will be presented that will demonstrate strong dependence in the results of modeling of a strong hurricane on the type of convective parameterization scheme used. The previous standard (default) option in the model was the Relaxed Arakawa-Schubert (RAS) scheme, which uses a quasi-equilibrium closure. In the cases shown, this scheme does not permit the efficient development of a strong storm in comparison with observations. When this scheme is replaced by a modified version of the Kain-Fritsch scheme, which was originally developed for use on grids with intervals of order 25 km such as the present one, the storm is able to develop to a much greater extent, closer to that of reality. Details of the two cases will be shown in order to elucidate the differences in the two modeled storms.

The predictive consequences of parameterization

NASA Astrophysics Data System (ADS)

White, J.; Hughes, J. D.; Doherty, J. E.

2013-12-01

In numerical groundwater modeling, parameterization is the process of selecting the aspects of a computer model that will be allowed to vary during history matching. This selection process is dependent on professional judgment and is, therefore, inherently subjective. Ideally, a robust parameterization should be commensurate with the spatial and temporal resolution of the model and should include all uncertain aspects of the model. Limited computing resources typically require reducing the number of adjustable parameters so that only a subset of the uncertain model aspects are treated as estimable parameters; the remaining aspects are treated as fixed parameters during history matching. We use linear subspace theory to develop expressions for the predictive error incurred by fixing parameters. The predictive error is comprised of two terms. The first term arises directly from the sensitivity of a prediction to fixed parameters. The second term arises from prediction-sensitive adjustable parameters that are forced to compensate for fixed parameters during history matching. The compensation is accompanied by inappropriate adjustment of otherwise uninformed, null-space parameter components. Unwarranted adjustment of null-space components away from prior maximum likelihood values may produce bias if a prediction is sensitive to those components. The potential for subjective parameterization choices to corrupt predictions is examined using a synthetic model. Several strategies are evaluated, including use of piecewise constant zones, use of pilot points with Tikhonov regularization and use of the Karhunen-Loeve transformation. The best choice of parameterization (as defined by minimum error variance) is strongly dependent on the types of predictions to be made by the model.

Developing a Physiologically-Based Pharmacokinetic Model Knowledgebase in Support of Provisional Model Construction - poster

EPA Science Inventory

Building new physiologically based pharmacokinetic (PBPK) models requires a lot data, such as the chemical-specific parameters and in vivo pharmacokinetic data. Previously-developed, well-parameterized, and thoroughly-vetted models can be great resource for supporting the constr...

Modeling of the Wegener Bergeron Findeisen process—implications for aerosol indirect effects

NASA Astrophysics Data System (ADS)

Storelvmo, T.; Kristjánsson, J. E.; Lohmann, U.; Iversen, T.; Kirkevåg, A.; Seland, Ø.

2008-10-01

A new parameterization of the Wegener-Bergeron-Findeisen (WBF) process has been developed, and implemented in the general circulation model CAM-Oslo. The new parameterization scheme has important implications for the process of phase transition in mixed-phase clouds. The new treatment of the WBF process replaces a previous formulation, in which the onset of the WBF effect depended on a threshold value of the mixing ratio of cloud ice. As no observational guidance for such a threshold value exists, the previous treatment added uncertainty to estimates of aerosol effects on mixed-phase clouds. The new scheme takes subgrid variability into account when simulating the WBF process, allowing for smoother phase transitions in mixed-phase clouds compared to the previous approach. The new parameterization yields a model state which gives reasonable agreement with observed quantities, allowing for calculations of aerosol effects on mixed-phase clouds involving a reduced number of tunable parameters. Furthermore, we find a significant sensitivity to perturbations in ice nuclei concentrations with the new parameterization, which leads to a reversal of the traditional cloud lifetime effect.

A satellite observation test bed for cloud parameterization development

NASA Astrophysics Data System (ADS)

Lebsock, M. D.; Suselj, K.

2015-12-01

We present an observational test-bed of cloud and precipitation properties derived from CloudSat, CALIPSO, and the the A-Train. The focus of the test-bed is on marine boundary layer clouds including stratocumulus and cumulus and the transition between these cloud regimes. Test-bed properties include the cloud cover and three dimensional cloud fraction along with the cloud water path and precipitation water content, and associated radiative fluxes. We also include the subgrid scale distribution of cloud and precipitation, and radiaitive quantities, which must be diagnosed by a model parameterization. The test-bed further includes meterological variables from the Modern Era Retrospective-analysis for Research and Applications (MERRA). MERRA variables provide the initialization and forcing datasets to run a parameterization in Single Column Model (SCM) mode. We show comparisons of an Eddy-Diffusivity/Mass-FLux (EDMF) parameterization coupled to micorphsycis and macrophysics packages run in SCM mode with observed clouds. Comparsions are performed regionally in areas of climatological subsidence as well stratified by dynamical and thermodynamical variables. Comparisons demonstrate the ability of the EDMF model to capture the observed transitions between subtropical stratocumulus and cumulus cloud regimes.

Fundamental statistical relationships between monthly and daily meteorological variables: Temporal downscaling of weather based on a global observational dataset

NASA Astrophysics Data System (ADS)

Sommer, Philipp; Kaplan, Jed

2016-04-01

Accurate modelling of large-scale vegetation dynamics, hydrology, and other environmental processes requires meteorological forcing on daily timescales. While meteorological data with high temporal resolution is becoming increasingly available, simulations for the future or distant past are limited by lack of data and poor performance of climate models, e.g., in simulating daily precipitation. To overcome these limitations, we may temporally downscale monthly summary data to a daily time step using a weather generator. Parameterization of such statistical models has traditionally been based on a limited number of observations. Recent developments in the archiving, distribution, and analysis of "big data" datasets provide new opportunities for the parameterization of a temporal downscaling model that is applicable over a wide range of climates. Here we parameterize a WGEN-type weather generator using more than 50 million individual daily meteorological observations, from over 10'000 stations covering all continents, based on the Global Historical Climatology Network (GHCN) and Synoptic Cloud Reports (EECRA) databases. Using the resulting "universal" parameterization and driven by monthly summaries, we downscale mean temperature (minimum and maximum), cloud cover, and total precipitation, to daily estimates. We apply a hybrid gamma-generalized Pareto distribution to calculate daily precipitation amounts, which overcomes much of the inability of earlier weather generators to simulate high amounts of daily precipitation. Our globally parameterized weather generator has numerous applications, including vegetation and crop modelling for paleoenvironmental studies.

Numerical Modeling of the Global Atmosphere

NASA Technical Reports Server (NTRS)

Arakawa, Akio; Mechoso, Carlos R.

1996-01-01

Under this grant, we continued development and evaluation of the updraft downdraft model for cumulus parameterization. The model includes the mass, rainwater and vertical momentum budget equations for both updrafts and downdrafts. The rainwater generated in an updraft falls partly inside and partly outside the updraft. Two types of stationary solutions are identified for the coupled rainwater budget and vertical momentum equations: (1) solutions for small tilting angles, which are unstable; (2) solutions for large tilting angles, which are stable. In practical applications, we select the smallest stable tilting angle as an optimum value. The model has been incorporated into the Arakawa-Schubert (A-S) cumulus parameterization. The results of semi-prognostic and single-column prognostic tests of the revised A-S parameterization show drastic improvement in predicting the humidity field. Cheng and Arakawa presents the rationale and basic design of the updraft-downdraft model, together with these test results. Cheng and Arakawa, on the other hand gives technical details of the model as implemented in current version of the UCLA GCM.

How certain are the process parameterizations in our models?

NASA Astrophysics Data System (ADS)

Gharari, Shervan; Hrachowitz, Markus; Fenicia, Fabrizio; Matgen, Patrick; Razavi, Saman; Savenije, Hubert; Gupta, Hoshin; Wheater, Howard

2016-04-01

Environmental models are abstract simplifications of real systems. As a result, the elements of these models, including system architecture (structure), process parameterization and parameters inherit a high level of approximation and simplification. In a conventional model building exercise the parameter values are the only elements of a model which can vary while the rest of the modeling elements are often fixed a priori and therefore not subjected to change. Once chosen the process parametrization and model structure usually remains the same throughout the modeling process. The only flexibility comes from the changing parameter values, thereby enabling these models to reproduce the desired observation. This part of modeling practice, parameter identification and uncertainty, has attracted a significant attention in the literature during the last years. However what remains unexplored in our point of view is to what extent the process parameterization and system architecture (model structure) can support each other. In other words "Does a specific form of process parameterization emerge for a specific model given its system architecture and data while no or little assumption has been made about the process parameterization itself? In this study we relax the assumption regarding a specific pre-determined form for the process parameterizations of a rainfall/runoff model and examine how varying the complexity of the system architecture can lead to different or possibly contradictory parameterization forms than what would have been decided otherwise. This comparison implicitly and explicitly provides us with an assessment of how uncertain is our perception of model process parameterization in respect to the extent the data can support.

Multimodel Uncertainty Changes in Simulated River Flows Induced by Human Impact Parameterizations

NASA Technical Reports Server (NTRS)

Liu, Xingcai; Tang, Qiuhong; Cui, Huijuan; Mu, Mengfei; Gerten Dieter; Gosling, Simon; Masaki, Yoshimitsu; Satoh, Yusuke; Wada, Yoshihide

2017-01-01

Human impacts increasingly affect the global hydrological cycle and indeed dominate hydrological changes in some regions. Hydrologists have sought to identify the human-impact-induced hydrological variations via parameterizing anthropogenic water uses in global hydrological models (GHMs). The consequently increased model complexity is likely to introduce additional uncertainty among GHMs. Here, using four GHMs, between-model uncertainties are quantified in terms of the ratio of signal to noise (SNR) for average river flow during 1971-2000 simulated in two experiments, with representation of human impacts (VARSOC) and without (NOSOC). It is the first quantitative investigation of between-model uncertainty resulted from the inclusion of human impact parameterizations. Results show that the between-model uncertainties in terms of SNRs in the VARSOC annual flow are larger (about 2 for global and varied magnitude for different basins) than those in the NOSOC, which are particularly significant in most areas of Asia and northern areas to the Mediterranean Sea. The SNR differences are mostly negative (-20 to 5, indicating higher uncertainty) for basin-averaged annual flow. The VARSOC high flow shows slightly lower uncertainties than NOSOC simulations, with SNR differences mostly ranging from -20 to 20. The uncertainty differences between the two experiments are significantly related to the fraction of irrigation areas of basins. The large additional uncertainties in VARSOC simulations introduced by the inclusion of parameterizations of human impacts raise the urgent need of GHMs development regarding a better understanding of human impacts. Differences in the parameterizations of irrigation, reservoir regulation and water withdrawals are discussed towards potential directions of improvements for future GHM development. We also discuss the advantages of statistical approaches to reduce the between-model uncertainties, and the importance of calibration of GHMs for not only better performances of historical simulations but also more robust and confidential future projections of hydrological changes under a changing environment.

Application of New Chorus Wave Model from Van Allen Probe Observations in Earth's Radiation Belt Modeling

NASA Astrophysics Data System (ADS)

Wang, D.; Shprits, Y.; Spasojevic, M.; Zhu, H.; Aseev, N.; Drozdov, A.; Kellerman, A. C.

2017-12-01

In situ satellite observations, theoretical studies and model simulations suggested that chorus waves play a significant role in the dynamic evolution of relativistic electrons in the Earth's radiation belts. In this study, we developed new wave frequency and amplitude models that depend on Magnetic Local Time (MLT)-, L-shell, latitude- and geomagnetic conditions indexed by Kp for upper-band and lower-band chorus waves using measurements from the Electric and Magnetic Field Instrument Suite and Integrated Science (EMFISIS) instrument onboard the Van Allen Probes. Utilizing the quasi-linear full diffusion code, we calculated corresponding diffusion coefficients in each MLT sector (1 hour resolution) for upper-band and lower-band chorus waves according to the new developed wave models. Compared with former parameterizations of chorus waves, the new parameterizations result in differences in diffusion coefficients that depend on energy and pitch angle. Utilizing obtained diffusion coefficients, lifetime of energetic electrons is parameterized accordingly. In addition, to investigate effects of obtained diffusion coefficients in different MLT sectors and under different geomagnetic conditions, we performed simulations using four-dimensional Versatile Electron Radiation Belt simulations and validated results against observations.

Parameterization and Modeling of Coupled Heat and Mass Transport in the Vadose Zone

NASA Astrophysics Data System (ADS)

Mohanty, B.; Yang, Z.

2016-12-01

The coupled heat and mass transport in the vadose zone is essentially a multiphysics issue. Addressing this issue appropriately has remarkable impacts on soil physical, chemical and biological processes. To data, most coupled heat and water transport modeling has focused on the interactions between liquid water, water vapor and heat transport in homogeneous and layered soils. Comparatively little work has been done on structured soils where preferential infiltration and evaporation flow occurs. Moreover, the traditional coupled heat and water model usually neglects the nonwetting phase air flow, which was found to be significant in the state-of-the-art modeling framework for coupled heat and water transport investigation. However, the parameterizations for the nonwetting phase air permeability largely remain elusive so far. In order to address the above mentioned limitations, this study aims to develop and validate a predictive multiphysics modeling framework for coupled soil heat and water transport in the heterogeneous shallow subsurface. To this end, the following research work is specifically conducted: (a) propose an improved parameterization to better predict the nonwetting phase relative permeability; (b) determine the dynamics, characteristics and processes of simultaneous soil moisture and heat movement in homogeneous and layered soils; and (c) develop a nonisothermal dual permeability model for heterogeneous structured soils. The results of our studies showed that: (a) the proposed modified nonwetting phase relative permeability models are much more accurate, which can be adopted for better parameterization in the subsequent nonisothermal two phase flow models; (b) the isothermal liquid film flow, nonwetting phase gas flow and liquid-vapor phase change non-equilibrium effects are significant in the arid and semiarid environments (Riverside, California and Audubon, Arizona); and (c) the developed nonisothermal dual permeability model is capable of characterizing the preferential evaporation path in the heterogeneous structured soils due to the fact that the capillary forces divert the pore water from coarse-textured soils (high temperature region) toward the fine-textured soils (low temperature region).

Modeling and parameterization of horizontally inhomogeneous cloud radiative properties

NASA Technical Reports Server (NTRS)

Welch, R. M.

1995-01-01

One of the fundamental difficulties in modeling cloud fields is the large variability of cloud optical properties (liquid water content, reflectance, emissivity). The stratocumulus and cirrus clouds, under special consideration for FIRE, exhibit spatial variability on scales of 1 km or less. While it is impractical to model individual cloud elements, the research direction is to model a statistical ensembles of cloud elements with mean-cloud properties specified. The major areas of this investigation are: (1) analysis of cloud field properties; (2) intercomparison of cloud radiative model results with satellite observations; (3) radiative parameterization of cloud fields; and (4) development of improved cloud classification algorithms.

Limitations of one-dimensional mesoscale PBL parameterizations in reproducing mountain-wave flows

DOE PAGES

Munoz-Esparza, Domingo; Sauer, Jeremy A.; Linn, Rodman R.; ...

2015-12-08

In this study, mesoscale models are considered to be the state of the art in modeling mountain-wave flows. Herein, we investigate the role and accuracy of planetary boundary layer (PBL) parameterizations in handling the interaction between large-scale mountain waves and the atmospheric boundary layer. To that end, we use recent large-eddy simulation (LES) results of mountain waves over a symmetric two-dimensional bell-shaped hill [Sauer et al., J. Atmos. Sci. (2015)], and compare them to four commonly used PBL schemes. We find that one-dimensional PBL parameterizations produce reasonable agreement with the LES results in terms of vertical wavelength, amplitude of velocitymore » and turbulent kinetic energy distribution in the downhill shooting flow region. However, the assumption of horizontal homogeneity in PBL parameterizations does not hold in the context of these complex flow configurations. This inappropriate modeling assumption results in a vertical wavelength shift producing errors of ≈ 10 m s–1 at downstream locations due to the presence of a coherent trapped lee wave that does not mix with the atmospheric boundary layer. In contrast, horizontally-integrated momentum flux derived from these PBL schemes displays a realistic pattern. Therefore results from mesoscale models using ensembles of one-dimensional PBL schemes can still potentially be used to parameterize drag effects in general circulation models. Nonetheless, three-dimensional PBL schemes must be developed in order for mesoscale models to accurately represent complex-terrain and other types of flows where one-dimensional PBL assumptions are violated.« less

DOE Office of Scientific and Technical Information (OSTI.GOV)

Donner, Leo J.; O'Brien, Travis A.; Rieger, Daniel

Both climate forcing and climate sensitivity persist as stubborn uncertainties limiting the extent to which climate models can provide actionable scientific scenarios for climate change. A key, explicit control on cloud-aerosol interactions, the largest uncertainty in climate forcing, is the vertical velocity of cloud-scale updrafts. Model-based studies of climate sensitivity indicate that convective entrainment, which is closely related to updraft speeds, is an important control on climate sensitivity. Updraft vertical velocities also drive many physical processes essential to numerical weather prediction. Vertical velocities and their role in atmospheric physical processes have been given very limited attention in models for climatemore » and numerical weather prediction. The relevant physical scales range down to tens of meters and are thus frequently sub-grid and require parameterization. Many state-of-science convection parameterizations provide mass fluxes without specifying vertical velocities, and parameterizations which do provide vertical velocities have been subject to limited evaluation against what have until recently been scant observations. Atmospheric observations imply that the distribution of vertical velocities depends on the areas over which the vertical velocities are averaged. Distributions of vertical velocities in climate models may capture this behavior, but it has not been accounted for when parameterizing cloud and precipitation processes in current models. New observations of convective vertical velocities offer a potentially promising path toward developing process-level cloud models and parameterizations for climate and numerical weather prediction. Taking account of scale-dependence of resolved vertical velocities offers a path to matching cloud-scale physical processes and their driving dynamics more realistically, with a prospect of reduced uncertainty in both climate forcing and sensitivity.« less

Performance Analysis of Transposition Models Simulating Solar Radiation on Inclined Surfaces: Preprint

DOE Office of Scientific and Technical Information (OSTI.GOV)

Xie, Yu; Sengupta, Manajit

2016-06-01

Transposition models are widely used in the solar energy industry to simulate solar radiation on inclined photovoltaic (PV) panels. These transposition models have been developed using various assumptions about the distribution of the diffuse radiation, and most of the parameterizations in these models have been developed using hourly ground data sets. Numerous studies have compared the performance of transposition models, but this paper aims to understand the quantitative uncertainty in the state-of-the-art transposition models and the sources leading to the uncertainty using high-resolution ground measurements in the plane of array. Our results suggest that the amount of aerosol optical depthmore » can affect the accuracy of isotropic models. The choice of empirical coefficients and the use of decomposition models can both result in uncertainty in the output from the transposition models. It is expected that the results of this study will ultimately lead to improvements of the parameterizations as well as the development of improved physical models.« less

Parameterization of planetary wave breaking in the middle atmosphere

NASA Technical Reports Server (NTRS)

Garcia, Rolando R.

1991-01-01

A parameterization of planetary wave breaking in the middle atmosphere has been developed and tested in a numerical model which includes governing equations for a single wave and the zonal-mean state. The parameterization is based on the assumption that wave breaking represents a steady-state equilibrium between the flux of wave activity and its dissipation by nonlinear processes, and that the latter can be represented as linear damping of the primary wave. With this and the additional assumption that the effect of breaking is to prevent further amplitude growth, the required dissipation rate is readily obtained from the steady-state equation for wave activity; diffusivity coefficients then follow from the dissipation rate. The assumptions made in the derivation are equivalent to those commonly used in parameterizations for gravity wave breaking, but the formulation in terms of wave activity helps highlight the central role of the wave group velocity in determining the dissipation rate. Comparison of model results with nonlinear calculations of wave breaking and with diagnostic determinations of stratospheric diffusion coefficients reveals remarkably good agreement, and suggests that the parameterization could be useful for simulating inexpensively, but realistically, the effects of planetary wave transport.

Climate Process Team "Representing calving and iceberg dynamics in global climate models"

NASA Astrophysics Data System (ADS)

Sergienko, O. V.; Adcroft, A.; Amundson, J. M.; Bassis, J. N.; Hallberg, R.; Pollard, D.; Stearns, L. A.; Stern, A. A.

2016-12-01

Iceberg calving accounts for approximately 50% of the ice mass loss from the Greenland and Antarctic ice sheets. By changing a glacier's geometry, calving can also significantly perturb the glacier's stress-regime far upstream of the grounding line. This process can enhance discharge of ice across the grounding line. Once calved, icebergs drift into the open ocean where they melt, injecting freshwater to the ocean and affecting the large-scale ocean circulation. The spatial redistribution of the freshwater flux have strong impact on sea-ice formation and its spatial variability. A Climate Process Team "Representing calving and iceberg dynamics in global climate models" was established in the fall 2014. The major objectives of the CPT are: (1) develop parameterizations of calving processes that are suitable for continental-scale ice-sheet models that simulate the evolution of the Antarctic and Greenland ice sheets; (2) compile the data sets of the glaciological and oceanographic observations that are necessary to test, validate and constrain the developed parameterizations and models; (3) develop a physically based iceberg component for inclusion in the large-scale ocean circulation model. Several calving parameterizations based suitable for various glaciological settings have been developed and implemented in a continental-scale ice sheet model. Simulations of the present-day Antarctic and Greenland ice sheets show that the ice-sheet geometric configurations (thickness and extent) are sensitive to the calving process. In order to guide the development as well as to test calving parameterizations, available observations (of various kinds) have been compiled and organized into a database. Monthly estimates of iceberg distribution around the coast of Greenland have been produced with a goal of constructing iceberg size distribution and probability functions for iceberg occurrence in particular regions. A physically based iceberg model component was used in a GFDL global climate model. The simulation results show that the Antarctic iceberg calving-size distribution affects iceberg trajectories, determines where iceberg meltwater enters the ocean and the increased ice-berg freshwater transport leads to increased sea-ice growth around much of the East Antarctic coastline.

The response of the SSM/I to the marine environment. Part 2: A parameterization of the effect of the sea surface slope distribution on emission and reflection

NASA Technical Reports Server (NTRS)

Petty, Grant W.; Katsaros, Kristina B.

1994-01-01

Based on a geometric optics model and the assumption of an isotropic Gaussian surface slope distribution, the component of ocean surface microwave emissivity variation due to large-scale surface roughness is parameterized for the frequencies and approximate viewing angle of the Special Sensor Microwave/Imager. Independent geophysical variables in the parameterization are the effective (microwave frequency dependent) slope variance and the sea surface temperature. Using the same physical model, the change in the effective zenith angle of reflected sky radiation arising from large-scale roughness is also parameterized. Independent geophysical variables in this parameterization are the effective slope variance and the atmospheric optical depth at the frequency in question. Both of the above model-based parameterizations are intended for use in conjunction with empirical parameterizations relating effective slope variance and foam coverage to near-surface wind speed. These empirical parameterizations are the subject of a separate paper.

Collaborative Research: Reducing tropical precipitation biases in CESM — Tests of unified parameterizations with ARM observations

DOE Office of Scientific and Technical Information (OSTI.GOV)

Larson, Vincent; Gettelman, Andrew; Morrison, Hugh

In state-of-the-art climate models, each cloud type is treated using its own separate cloud parameterization and its own separate microphysics parameterization. This use of separate schemes for separate cloud regimes is undesirable because it is theoretically unfounded, it hampers interpretation of results, and it leads to the temptation to overtune parameters. In this grant, we are creating a climate model that contains a unified cloud parameterization and a unified microphysics parameterization. This model will be used to address the problems of excessive frequency of drizzle in climate models and excessively early onset of deep convection in the Tropics over land.more » The resulting model will be compared with ARM observations.« less

Trends and uncertainties in budburst projections of Norway spruce in Northern Europe.

PubMed

Olsson, Cecilia; Olin, Stefan; Lindström, Johan; Jönsson, Anna Maria

2017-12-01

Budburst is regulated by temperature conditions, and a warming climate is associated with earlier budburst. A range of phenology models has been developed to assess climate change effects, and they tend to produce different results. This is mainly caused by different model representations of tree physiology processes, selection of observational data for model parameterization, and selection of climate model data to generate future projections. In this study, we applied (i) Bayesian inference to estimate model parameter values to address uncertainties associated with selection of observational data, (ii) selection of climate model data representative of a larger dataset, and (iii) ensembles modeling over multiple initial conditions, model classes, model parameterizations, and boundary conditions to generate future projections and uncertainty estimates. The ensemble projection indicated that the budburst of Norway spruce in northern Europe will on average take place 10.2 ± 3.7 days earlier in 2051-2080 than in 1971-2000, given climate conditions corresponding to RCP 8.5. Three provenances were assessed separately (one early and two late), and the projections indicated that the relationship among provenance will remain also in a warmer climate. Structurally complex models were more likely to fail predicting budburst for some combinations of site and year than simple models. However, they contributed to the overall picture of current understanding of climate impacts on tree phenology by capturing additional aspects of temperature response, for example, chilling. Model parameterizations based on single sites were more likely to result in model failure than parameterizations based on multiple sites, highlighting that the model parameterization is sensitive to initial conditions and may not perform well under other climate conditions, whether the change is due to a shift in space or over time. By addressing a range of uncertainties, this study showed that ensemble modeling provides a more robust impact assessment than would a single phenology model run.

Evaluation of Surface Flux Parameterizations with Long-Term ARM Observations

DOE PAGES

Liu, Gang; Liu, Yangang; Endo, Satoshi

2013-02-01

Surface momentum, sensible heat, and latent heat fluxes are critical for atmospheric processes such as clouds and precipitation, and are parameterized in a variety of models ranging from cloud-resolving models to large-scale weather and climate models. However, direct evaluation of the parameterization schemes for these surface fluxes is rare due to limited observations. This study takes advantage of the long-term observations of surface fluxes collected at the Southern Great Plains site by the Department of Energy Atmospheric Radiation Measurement program to evaluate the six surface flux parameterization schemes commonly used in the Weather Research and Forecasting (WRF) model and threemore » U.S. general circulation models (GCMs). The unprecedented 7-yr-long measurements by the eddy correlation (EC) and energy balance Bowen ratio (EBBR) methods permit statistical evaluation of all six parameterizations under a variety of stability conditions, diurnal cycles, and seasonal variations. The statistical analyses show that the momentum flux parameterization agrees best with the EC observations, followed by latent heat flux, sensible heat flux, and evaporation ratio/Bowen ratio. The overall performance of the parameterizations depends on atmospheric stability, being best under neutral stratification and deteriorating toward both more stable and more unstable conditions. Further diagnostic analysis reveals that in addition to the parameterization schemes themselves, the discrepancies between observed and parameterized sensible and latent heat fluxes may stem from inadequate use of input variables such as surface temperature, moisture availability, and roughness length. The results demonstrate the need for improving the land surface models and measurements of surface properties, which would permit the evaluation of full land surface models.« less

A General Framework for Thermodynamically Consistent Parameterization and Efficient Sampling of Enzymatic Reactions

PubMed Central

Saa, Pedro; Nielsen, Lars K.

2015-01-01

Kinetic models provide the means to understand and predict the dynamic behaviour of enzymes upon different perturbations. Despite their obvious advantages, classical parameterizations require large amounts of data to fit their parameters. Particularly, enzymes displaying complex reaction and regulatory (allosteric) mechanisms require a great number of parameters and are therefore often represented by approximate formulae, thereby facilitating the fitting but ignoring many real kinetic behaviours. Here, we show that full exploration of the plausible kinetic space for any enzyme can be achieved using sampling strategies provided a thermodynamically feasible parameterization is used. To this end, we developed a General Reaction Assembly and Sampling Platform (GRASP) capable of consistently parameterizing and sampling accurate kinetic models using minimal reference data. The former integrates the generalized MWC model and the elementary reaction formalism. By formulating the appropriate thermodynamic constraints, our framework enables parameterization of any oligomeric enzyme kinetics without sacrificing complexity or using simplifying assumptions. This thermodynamically safe parameterization relies on the definition of a reference state upon which feasible parameter sets can be efficiently sampled. Uniform sampling of the kinetics space enabled dissecting enzyme catalysis and revealing the impact of thermodynamics on reaction kinetics. Our analysis distinguished three reaction elasticity regions for common biochemical reactions: a steep linear region (0> ΔGr >-2 kJ/mol), a transition region (-2> ΔGr >-20 kJ/mol) and a constant elasticity region (ΔGr <-20 kJ/mol). We also applied this framework to model more complex kinetic behaviours such as the monomeric cooperativity of the mammalian glucokinase and the ultrasensitive response of the phosphoenolpyruvate carboxylase of Escherichia coli. In both cases, our approach described appropriately not only the kinetic behaviour of these enzymes, but it also provided insights about the particular features underpinning the observed kinetics. Overall, this framework will enable systematic parameterization and sampling of enzymatic reactions. PMID:25874556

Evaluating the impacts of agricultural land management practices: A probabilistic hydrologic modeling approach

USDA-ARS?s Scientific Manuscript database

The complexity of the hydrologic system challenges the development of models. One issue faced during the model development stage is the uncertainty involved in model parameterization. Using a single optimized set of parameters (one snapshot) to represent baseline conditions of the system limits the ...

A new fractional snow-covered area parameterization for the Community Land Model and its effect on the surface energy balance

NASA Astrophysics Data System (ADS)

Swenson, S. C.; Lawrence, D. M.

2011-11-01

One function of the Community Land Model (CLM4) is the determination of surface albedo in the Community Earth System Model (CESM1). Because the typical spatial scales of CESM1 simulations are large compared to the scales of variability of surface properties such as snow cover and vegetation, unresolved surface heterogeneity is parameterized. Fractional snow-covered area, or snow-covered fraction (SCF), within a CLM4 grid cell is parameterized as a function of grid cell mean snow depth and snow density. This parameterization is based on an analysis of monthly averaged SCF and snow depth that showed a seasonal shift in the snow depth-SCF relationship. In this paper, we show that this shift is an artifact of the monthly sampling and that the current parameterization does not reflect the relationship observed between snow depth and SCF at the daily time scale. We demonstrate that the snow depth analysis used in the original study exhibits a bias toward early melt when compared to satellite-observed SCF. This bias results in a tendency to overestimate SCF as a function of snow depth. Using a more consistent, higher spatial and temporal resolution snow depth analysis reveals a clear hysteresis between snow accumulation and melt seasons. Here, a new SCF parameterization based on snow water equivalent is developed to capture the observed seasonal snow depth-SCF evolution. The effects of the new SCF parameterization on the surface energy budget are described. In CLM4, surface energy fluxes are calculated assuming a uniform snow cover. To more realistically simulate environments having patchy snow cover, we modify the model by computing the surface fluxes separately for snow-free and snow-covered fractions of a grid cell. In this configuration, the form of the parameterized snow depth-SCF relationship is shown to greatly affect the surface energy budget. The direct exposure of the snow-free surfaces to the atmosphere leads to greater heat loss from the ground during autumn and greater heat gain during spring. The net effect is to reduce annual mean soil temperatures by up to 3°C in snow-affected regions.

A new fractional snow-covered area parameterization for the Community Land Model and its effect on the surface energy balance

NASA Astrophysics Data System (ADS)

Swenson, S. C.; Lawrence, D. M.

2012-11-01

One function of the Community Land Model (CLM4) is the determination of surface albedo in the Community Earth System Model (CESM1). Because the typical spatial scales of CESM1 simulations are large compared to the scales of variability of surface properties such as snow cover and vegetation, unresolved surface heterogeneity is parameterized. Fractional snow-covered area, or snow-covered fraction (SCF), within a CLM4 grid cell is parameterized as a function of grid cell mean snow depth and snow density. This parameterization is based on an analysis of monthly averaged SCF and snow depth that showed a seasonal shift in the snow depth-SCF relationship. In this paper, we show that this shift is an artifact of the monthly sampling and that the current parameterization does not reflect the relationship observed between snow depth and SCF at the daily time scale. We demonstrate that the snow depth analysis used in the original study exhibits a bias toward early melt when compared to satellite-observed SCF. This bias results in a tendency to overestimate SCF as a function of snow depth. Using a more consistent, higher spatial and temporal resolution snow depth analysis reveals a clear hysteresis between snow accumulation and melt seasons. Here, a new SCF parameterization based on snow water equivalent is developed to capture the observed seasonal snow depth-SCF evolution. The effects of the new SCF parameterization on the surface energy budget are described. In CLM4, surface energy fluxes are calculated assuming a uniform snow cover. To more realistically simulate environments having patchy snow cover, we modify the model by computing the surface fluxes separately for snow-free and snow-covered fractions of a grid cell. In this configuration, the form of the parameterized snow depth-SCF relationship is shown to greatly affect the surface energy budget. The direct exposure of the snow-free surfaces to the atmosphere leads to greater heat loss from the ground during autumn and greater heat gain during spring. The net effect is to reduce annual mean soil temperatures by up to 3°C in snow-affected regions.

Inference of cirrus cloud properties using satellite-observed visible and infrared radiances. I - Parameterization of radiance fields

NASA Technical Reports Server (NTRS)

Minnis, Patrick; Liou, Kuo-Nan; Takano, Yoshihide

1993-01-01

The impact of using phase functions for spherical droplets and hexagonal ice crystals to analyze radiances from cirrus is examined. Adding-doubling radiative transfer calculations are employed to compute radiances for different cloud thicknesses and heights over various backgrounds. These radiances are used to develop parameterizations of top-of-the-atmosphere visible reflectance and IR emittance using tables of reflectances as a function of cloud optical depth, viewing and illumination angles, and microphysics. This parameterization, which includes Rayleigh scattering, ozone absorption, variable cloud height, and an anisotropic surface reflectance, reproduces the computed top-of-the-atmosphere reflectances with an accruacy of +/- 6 percent for four microphysical models: 10-micron water droplet, small symmetric crystal, cirrostratus, and cirrus uncinus. The accuracy is twice that of previous models.

Cloud Simulations in Response to Turbulence Parameterizations in the GISS Model E GCM

NASA Technical Reports Server (NTRS)

Yao, Mao-Sung; Cheng, Ye

2013-01-01

The response of cloud simulations to turbulence parameterizations is studied systematically using the GISS general circulation model (GCM) E2 employed in the Intergovernmental Panel on Climate Change's (IPCC) Fifth Assessment Report (AR5).Without the turbulence parameterization, the relative humidity (RH) and the low cloud cover peak unrealistically close to the surface; with the dry convection or with only the local turbulence parameterization, these two quantities improve their vertical structures, but the vertical transport of water vapor is still weak in the planetary boundary layers (PBLs); with both local and nonlocal turbulence parameterizations, the RH and low cloud cover have better vertical structures in all latitudes due to more significant vertical transport of water vapor in the PBL. The study also compares the cloud and radiation climatologies obtained from an experiment using a newer version of turbulence parameterization being developed at GISS with those obtained from the AR5 version. This newer scheme differs from the AR5 version in computing nonlocal transports, turbulent length scale, and PBL height and shows significant improvements in cloud and radiation simulations, especially over the subtropical eastern oceans and the southern oceans. The diagnosed PBL heights appear to correlate well with the low cloud distribution over oceans. This suggests that a cloud-producing scheme needs to be constructed in a framework that also takes the turbulence into consideration.

The importance of parameterization when simulating the hydrologic response of vegetative land-cover change

NASA Astrophysics Data System (ADS)

White, Jeremy; Stengel, Victoria; Rendon, Samuel; Banta, John

2017-08-01

Computer models of hydrologic systems are frequently used to investigate the hydrologic response of land-cover change. If the modeling results are used to inform resource-management decisions, then providing robust estimates of uncertainty in the simulated response is an important consideration. Here we examine the importance of parameterization, a necessarily subjective process, on uncertainty estimates of the simulated hydrologic response of land-cover change. Specifically, we applied the soil water assessment tool (SWAT) model to a 1.4 km2 watershed in southern Texas to investigate the simulated hydrologic response of brush management (the mechanical removal of woody plants), a discrete land-cover change. The watershed was instrumented before and after brush-management activities were undertaken, and estimates of precipitation, streamflow, and evapotranspiration (ET) are available; these data were used to condition and verify the model. The role of parameterization in brush-management simulation was evaluated by constructing two models, one with 12 adjustable parameters (reduced parameterization) and one with 1305 adjustable parameters (full parameterization). Both models were subjected to global sensitivity analysis as well as Monte Carlo and generalized likelihood uncertainty estimation (GLUE) conditioning to identify important model inputs and to estimate uncertainty in several quantities of interest related to brush management. Many realizations from both parameterizations were identified as behavioral in that they reproduce daily mean streamflow acceptably well according to Nash-Sutcliffe model efficiency coefficient, percent bias, and coefficient of determination. However, the total volumetric ET difference resulting from simulated brush management remains highly uncertain after conditioning to daily mean streamflow, indicating that streamflow data alone are not sufficient to inform the model inputs that influence the simulated outcomes of brush management the most. Additionally, the reduced-parameterization model grossly underestimates uncertainty in the total volumetric ET difference compared to the full-parameterization model; total volumetric ET difference is a primary metric for evaluating the outcomes of brush management. The failure of the reduced-parameterization model to provide robust uncertainty estimates demonstrates the importance of parameterization when attempting to quantify uncertainty in land-cover change simulations.

The importance of parameterization when simulating the hydrologic response of vegetative land-cover change

USGS Publications Warehouse

White, Jeremy; Stengel, Victoria G.; Rendon, Samuel H.; Banta, John

2017-01-01

Computer models of hydrologic systems are frequently used to investigate the hydrologic response of land-cover change. If the modeling results are used to inform resource-management decisions, then providing robust estimates of uncertainty in the simulated response is an important consideration. Here we examine the importance of parameterization, a necessarily subjective process, on uncertainty estimates of the simulated hydrologic response of land-cover change. Specifically, we applied the soil water assessment tool (SWAT) model to a 1.4 km2 watershed in southern Texas to investigate the simulated hydrologic response of brush management (the mechanical removal of woody plants), a discrete land-cover change. The watershed was instrumented before and after brush-management activities were undertaken, and estimates of precipitation, streamflow, and evapotranspiration (ET) are available; these data were used to condition and verify the model. The role of parameterization in brush-management simulation was evaluated by constructing two models, one with 12 adjustable parameters (reduced parameterization) and one with 1305 adjustable parameters (full parameterization). Both models were subjected to global sensitivity analysis as well as Monte Carlo and generalized likelihood uncertainty estimation (GLUE) conditioning to identify important model inputs and to estimate uncertainty in several quantities of interest related to brush management. Many realizations from both parameterizations were identified as behavioral in that they reproduce daily mean streamflow acceptably well according to Nash–Sutcliffe model efficiency coefficient, percent bias, and coefficient of determination. However, the total volumetric ET difference resulting from simulated brush management remains highly uncertain after conditioning to daily mean streamflow, indicating that streamflow data alone are not sufficient to inform the model inputs that influence the simulated outcomes of brush management the most. Additionally, the reduced-parameterization model grossly underestimates uncertainty in the total volumetric ET difference compared to the full-parameterization model; total volumetric ET difference is a primary metric for evaluating the outcomes of brush management. The failure of the reduced-parameterization model to provide robust uncertainty estimates demonstrates the importance of parameterization when attempting to quantify uncertainty in land-cover change simulations.

Generalized skew-symmetric interfacial probability distribution in reflectivity and small-angle scattering analysis

DOE Office of Scientific and Technical Information (OSTI.GOV)

Jiang, Zhang; Chen, Wei

Generalized skew-symmetric probability density functions are proposed to model asymmetric interfacial density distributions for the parameterization of any arbitrary density profiles in the `effective-density model'. The penetration of the densities into adjacent layers can be selectively controlled and parameterized. A continuous density profile is generated and discretized into many independent slices of very thin thickness with constant density values and sharp interfaces. The discretized profile can be used to calculate reflectivities via Parratt's recursive formula, or small-angle scattering via the concentric onion model that is also developed in this work.

Generalized skew-symmetric interfacial probability distribution in reflectivity and small-angle scattering analysis

DOE PAGES

Jiang, Zhang; Chen, Wei

2017-11-03

Generalized skew-symmetric probability density functions are proposed to model asymmetric interfacial density distributions for the parameterization of any arbitrary density profiles in the `effective-density model'. The penetration of the densities into adjacent layers can be selectively controlled and parameterized. A continuous density profile is generated and discretized into many independent slices of very thin thickness with constant density values and sharp interfaces. The discretized profile can be used to calculate reflectivities via Parratt's recursive formula, or small-angle scattering via the concentric onion model that is also developed in this work.

Evaluating cloud processes in large-scale models: Of idealized case studies, parameterization testbeds and single-column modelling on climate time-scales

NASA Astrophysics Data System (ADS)

Neggers, Roel

2016-04-01

Boundary-layer schemes have always formed an integral part of General Circulation Models (GCMs) used for numerical weather and climate prediction. The spatial and temporal scales associated with boundary-layer processes and clouds are typically much smaller than those at which GCMs are discretized, which makes their representation through parameterization a necessity. The need for generally applicable boundary-layer parameterizations has motivated many scientific studies, which in effect has created its own active research field in the atmospheric sciences. Of particular interest has been the evaluation of boundary-layer schemes at "process-level". This means that parameterized physics are studied in isolated mode from the larger-scale circulation, using prescribed forcings and excluding any upscale interaction. Although feedbacks are thus prevented, the benefit is an enhanced model transparency, which might aid an investigator in identifying model errors and understanding model behavior. The popularity and success of the process-level approach is demonstrated by the many past and ongoing model inter-comparison studies that have been organized by initiatives such as GCSS/GASS. A red line in the results of these studies is that although most schemes somehow manage to capture first-order aspects of boundary layer cloud fields, there certainly remains room for improvement in many areas. Only too often are boundary layer parameterizations still found to be at the heart of problems in large-scale models, negatively affecting forecast skills of NWP models or causing uncertainty in numerical predictions of future climate. How to break this parameterization "deadlock" remains an open problem. This presentation attempts to give an overview of the various existing methods for the process-level evaluation of boundary-layer physics in large-scale models. This includes i) idealized case studies, ii) longer-term evaluation at permanent meteorological sites (the testbed approach), and iii) process-level evaluation at climate time-scales. The advantages and disadvantages of each approach will be identified and discussed, and some thoughts about possible future developments will be given.

Stochastic and Perturbed Parameter Representations of Model Uncertainty in Convection Parameterization

NASA Astrophysics Data System (ADS)

Christensen, H. M.; Moroz, I.; Palmer, T.

2015-12-01

It is now acknowledged that representing model uncertainty in atmospheric simulators is essential for the production of reliable probabilistic ensemble forecasts, and a number of different techniques have been proposed for this purpose. Stochastic convection parameterization schemes use random numbers to represent the difference between a deterministic parameterization scheme and the true atmosphere, accounting for the unresolved sub grid-scale variability associated with convective clouds. An alternative approach varies the values of poorly constrained physical parameters in the model to represent the uncertainty in these parameters. This study presents new perturbed parameter schemes for use in the European Centre for Medium Range Weather Forecasts (ECMWF) convection scheme. Two types of scheme are developed and implemented. Both schemes represent the joint uncertainty in four of the parameters in the convection parametrisation scheme, which was estimated using the Ensemble Prediction and Parameter Estimation System (EPPES). The first scheme developed is a fixed perturbed parameter scheme, where the values of uncertain parameters are changed between ensemble members, but held constant over the duration of the forecast. The second is a stochastically varying perturbed parameter scheme. The performance of these schemes was compared to the ECMWF operational stochastic scheme, Stochastically Perturbed Parametrisation Tendencies (SPPT), and to a model which does not represent uncertainty in convection. The skill of probabilistic forecasts made using the different models was evaluated. While the perturbed parameter schemes improve on the stochastic parametrisation in some regards, the SPPT scheme outperforms the perturbed parameter approaches when considering forecast variables that are particularly sensitive to convection. Overall, SPPT schemes are the most skilful representations of model uncertainty due to convection parametrisation. Reference: H. M. Christensen, I. M. Moroz, and T. N. Palmer, 2015: Stochastic and Perturbed Parameter Representations of Model Uncertainty in Convection Parameterization. J. Atmos. Sci., 72, 2525-2544.

Automation of a Linear Accelerator Dosimetric Quality Assurance Program

NASA Astrophysics Data System (ADS)

Lebron Gonzalez, Sharon H.

According to the American Society of Radiation Oncology, two-thirds of all cancer patients will receive radiation therapy during their illness with the majority of the treatments been delivered by a linear accelerator (linac). Therefore, quality assurance (QA) procedures must be enforced in order to deliver treatments with a machine in proper conditions. The overall goal of this project is to automate the linac's dosimetric QA procedures by analyzing and accomplishing various tasks. First, the photon beam dosimetry (i.e. total scatter correction factor, infinite percentage depth dose (PDD) and profiles) were parameterized. Parameterization consists of defining the parameters necessary for the specification of a dosimetric quantity model creating a data set that is portable and easy to implement for different applications including: beam modeling data input into a treatment planning system (TPS), comparing measured and TPS modelled data, the QA of a linac's beam characteristics, and the establishment of a standard data set for comparison with other data, etcetera. Second, this parameterization model was used to develop a universal method to determine the radiation field size of flattened (FF), flattening-filter-free (FFF) and wedge beams which we termed the parameterized gradient method (PGM). Third, the parameterized model was also used to develop a profile-based method for assessing the beam quality of photon FF and FFF beams using an ionization chamber array. The PDD and PDD change was also predicted from the measured profile. Lastly, methods were created to automate the multileaf collimator (MLC) calibration and QA procedures as well as the acquisition of the parameters included in monthly and annual photon dosimetric QA. A two field technique was used for the calculation of the MLC leaf relative offsets using an electronic portal imaging device (EPID). A step-and-shoot technique was used to accurately acquire the radiation field size, flatness, symmetry, output and beam quality specifiers in a single delivery to an ionization chamber array for FF and FFF beams.

Infrared radiation parameterizations for the minor CO2 bands and for several CFC bands in the window region

NASA Technical Reports Server (NTRS)

Kratz, David P.; Chou, Ming-Dah; Yan, Michael M.-H.

1993-01-01

Fast and accurate parameterizations have been developed for the transmission functions of the CO2 9.4- and 10.4-micron bands, as well as the CFC-11, CFC-12, and CFC-22 bands located in the 8-12-micron region. The parameterizations are based on line-by-line calculations of transmission functions for the CO2 bands and on high spectral resolution laboratory measurements of the absorption coefficients for the CFC bands. Also developed are the parameterizations for the H2O transmission functions for the corresponding spectral bands. Compared to the high-resolution calculations, fluxes at the tropopause computed with the parameterizations are accurate to within 10 percent when overlapping of gas absorptions within a band is taken into account. For individual gas absorption, the accuracy is of order 0-2 percent. The climatic effects of these trace gases have been studied using a zonally averaged multilayer energy balance model, which includes seasonal cycles and a simplified deep ocean. With the trace gas abundances taken to follow the Intergovernmental Panel on Climate Change Low Emissions 'B' scenario, the transient response of the surface temperature is simulated for the period 1900-2060.

Neutrons in proton pencil beam scanning: parameterization of energy, quality factors and RBE

NASA Astrophysics Data System (ADS)

Schneider, Uwe; Hälg, Roger A.; Baiocco, Giorgio; Lomax, Tony

2016-08-01

The biological effectiveness of neutrons produced during proton therapy in inducing cancer is unknown, but potentially large. In particular, since neutron biological effectiveness is energy dependent, it is necessary to estimate, besides the dose, also the energy spectra, in order to obtain quantities which could be a measure of the biological effectiveness and test current models and new approaches against epidemiological studies on cancer induction after proton therapy. For patients treated with proton pencil beam scanning, this work aims to predict the spatially localized neutron energies, the effective quality factor, the weighting factor according to ICRP, and two RBE values, the first obtained from the saturation corrected dose mean lineal energy and the second from DSB cluster induction. A proton pencil beam was Monte Carlo simulated using GEANT. Based on the simulated neutron spectra for three different proton beam energies a parameterization of energy, quality factors and RBE was calculated. The pencil beam algorithm used for treatment planning at PSI has been extended using the developed parameterizations in order to calculate the spatially localized neutron energy, quality factors and RBE for each treated patient. The parameterization represents the simple quantification of neutron energy in two energy bins and the quality factors and RBE with a satisfying precision up to 85 cm away from the proton pencil beam when compared to the results based on 3D Monte Carlo simulations. The root mean square error of the energy estimate between Monte Carlo simulation based results and the parameterization is 3.9%. For the quality factors and RBE estimates it is smaller than 0.9%. The model was successfully integrated into the PSI treatment planning system. It was found that the parameterizations for neutron energy, quality factors and RBE were independent of proton energy in the investigated energy range of interest for proton therapy. The pencil beam algorithm has been extended using the developed parameterizations in order to calculate the neutron energy, quality factor and RBE.

Neutrons in proton pencil beam scanning: parameterization of energy, quality factors and RBE.

PubMed

Schneider, Uwe; Hälg, Roger A; Baiocco, Giorgio; Lomax, Tony

2016-08-21

The biological effectiveness of neutrons produced during proton therapy in inducing cancer is unknown, but potentially large. In particular, since neutron biological effectiveness is energy dependent, it is necessary to estimate, besides the dose, also the energy spectra, in order to obtain quantities which could be a measure of the biological effectiveness and test current models and new approaches against epidemiological studies on cancer induction after proton therapy. For patients treated with proton pencil beam scanning, this work aims to predict the spatially localized neutron energies, the effective quality factor, the weighting factor according to ICRP, and two RBE values, the first obtained from the saturation corrected dose mean lineal energy and the second from DSB cluster induction. A proton pencil beam was Monte Carlo simulated using GEANT. Based on the simulated neutron spectra for three different proton beam energies a parameterization of energy, quality factors and RBE was calculated. The pencil beam algorithm used for treatment planning at PSI has been extended using the developed parameterizations in order to calculate the spatially localized neutron energy, quality factors and RBE for each treated patient. The parameterization represents the simple quantification of neutron energy in two energy bins and the quality factors and RBE with a satisfying precision up to 85 cm away from the proton pencil beam when compared to the results based on 3D Monte Carlo simulations. The root mean square error of the energy estimate between Monte Carlo simulation based results and the parameterization is 3.9%. For the quality factors and RBE estimates it is smaller than 0.9%. The model was successfully integrated into the PSI treatment planning system. It was found that the parameterizations for neutron energy, quality factors and RBE were independent of proton energy in the investigated energy range of interest for proton therapy. The pencil beam algorithm has been extended using the developed parameterizations in order to calculate the neutron energy, quality factor and RBE.

The impact of structural uncertainty on cost-effectiveness models for adjuvant endocrine breast cancer treatments: the need for disease-specific model standardization and improved guidance.

PubMed

Frederix, Gerardus W J; van Hasselt, Johan G C; Schellens, Jan H M; Hövels, Anke M; Raaijmakers, Jan A M; Huitema, Alwin D R; Severens, Johan L

2014-01-01

Structural uncertainty relates to differences in model structure and parameterization. For many published health economic analyses in oncology, substantial differences in model structure exist, leading to differences in analysis outcomes and potentially impacting decision-making processes. The objectives of this analysis were (1) to identify differences in model structure and parameterization for cost-effectiveness analyses (CEAs) comparing tamoxifen and anastrazole for adjuvant breast cancer (ABC) treatment; and (2) to quantify the impact of these differences on analysis outcome metrics. The analysis consisted of four steps: (1) review of the literature for identification of eligible CEAs; (2) definition and implementation of a base model structure, which included the core structural components for all identified CEAs; (3) definition and implementation of changes or additions in the base model structure or parameterization; and (4) quantification of the impact of changes in model structure or parameterizations on the analysis outcome metrics life-years gained (LYG), incremental costs (IC) and the incremental cost-effectiveness ratio (ICER). Eleven CEA analyses comparing anastrazole and tamoxifen as ABC treatment were identified. The base model consisted of the following health states: (1) on treatment; (2) off treatment; (3) local recurrence; (4) metastatic disease; (5) death due to breast cancer; and (6) death due to other causes. The base model estimates of anastrazole versus tamoxifen for the LYG, IC and ICER were 0.263 years, €3,647 and €13,868/LYG, respectively. In the published models that were evaluated, differences in model structure included the addition of different recurrence health states, and associated transition rates were identified. Differences in parameterization were related to the incidences of recurrence, local recurrence to metastatic disease, and metastatic disease to death. The separate impact of these model components on the LYG ranged from 0.207 to 0.356 years, while incremental costs ranged from €3,490 to €3,714 and ICERs ranged from €9,804/LYG to €17,966/LYG. When we re-analyzed the published CEAs in our framework by including their respective model properties, the LYG ranged from 0.207 to 0.383 years, IC ranged from €3,556 to €3,731 and ICERs ranged from €9,683/LYG to €17,570/LYG. Differences in model structure and parameterization lead to substantial differences in analysis outcome metrics. This analysis supports the need for more guidance regarding structural uncertainty and the use of standardized disease-specific models for health economic analyses of adjuvant endocrine breast cancer therapies. The developed approach in the current analysis could potentially serve as a template for further evaluations of structural uncertainty and development of disease-specific models.

A unified parameterization of clouds and turbulence using CLUBB and subcolumns in the Community Atmosphere Model

DOE PAGES

Thayer-Calder, K.; Gettelman, A.; Craig, C.; ...

2015-06-30

Most global climate models parameterize separate cloud types using separate parameterizations. This approach has several disadvantages, including obscure interactions between parameterizations and inaccurate triggering of cumulus parameterizations. Alternatively, a unified cloud parameterization uses one equation set to represent all cloud types. Such cloud types include stratiform liquid and ice cloud, shallow convective cloud, and deep convective cloud. Vital to the success of a unified parameterization is a general interface between clouds and microphysics. One such interface involves drawing Monte Carlo samples of subgrid variability of temperature, water vapor, cloud liquid, and cloud ice, and feeding the sample points into amore » microphysics scheme.This study evaluates a unified cloud parameterization and a Monte Carlo microphysics interface that has been implemented in the Community Atmosphere Model (CAM) version 5.3. Results describing the mean climate and tropical variability from global simulations are presented. The new model shows a degradation in precipitation skill but improvements in short-wave cloud forcing, liquid water path, long-wave cloud forcing, precipitable water, and tropical wave simulation. Also presented are estimations of computational expense and investigation of sensitivity to number of subcolumns.« less

A unified parameterization of clouds and turbulence using CLUBB and subcolumns in the Community Atmosphere Model

DOE PAGES

Thayer-Calder, Katherine; Gettelman, A.; Craig, Cheryl; ...

2015-12-01

Most global climate models parameterize separate cloud types using separate parameterizations.This approach has several disadvantages, including obscure interactions between parameterizations and inaccurate triggering of cumulus parameterizations. Alternatively, a unified cloud parameterization uses one equation set to represent all cloud types. Such cloud types include stratiform liquid and ice cloud, shallow convective cloud, and deep convective cloud. Vital to the success of a unified parameterization is a general interface between clouds and microphysics. One such interface involves drawing Monte Carlo samples of subgrid variability of temperature, water vapor, cloud liquid, and cloud ice, and feeding the sample points into a microphysicsmore » scheme. This study evaluates a unified cloud parameterization and a Monte Carlo microphysics interface that has been implemented in the Community Atmosphere Model (CAM) version 5.3. Results describing the mean climate and tropical variability from global simulations are presented. In conclusion, the new model shows a degradation in precipitation skill but improvements in short-wave cloud forcing, liquid water path, long-wave cloud forcing, perceptible water, and tropical wave simulation. Also presented are estimations of computational expense and investigation of sensitivity to number of subcolumns.« less

Hydraulic Conductivity Estimation using Bayesian Model Averaging and Generalized Parameterization

NASA Astrophysics Data System (ADS)

Tsai, F. T.; Li, X.

2006-12-01

Non-uniqueness in parameterization scheme is an inherent problem in groundwater inverse modeling due to limited data. To cope with the non-uniqueness problem of parameterization, we introduce a Bayesian Model Averaging (BMA) method to integrate a set of selected parameterization methods. The estimation uncertainty in BMA includes the uncertainty in individual parameterization methods as the within-parameterization variance and the uncertainty from using different parameterization methods as the between-parameterization variance. Moreover, the generalized parameterization (GP) method is considered in the geostatistical framework in this study. The GP method aims at increasing the flexibility of parameterization through the combination of a zonation structure and an interpolation method. The use of BMP with GP avoids over-confidence in a single parameterization method. A normalized least-squares estimation (NLSE) is adopted to calculate the posterior probability for each GP. We employee the adjoint state method for the sensitivity analysis on the weighting coefficients in the GP method. The adjoint state method is also applied to the NLSE problem. The proposed methodology is implemented to the Alamitos Barrier Project (ABP) in California, where the spatially distributed hydraulic conductivity is estimated. The optimal weighting coefficients embedded in GP are identified through the maximum likelihood estimation (MLE) where the misfits between the observed and calculated groundwater heads are minimized. The conditional mean and conditional variance of the estimated hydraulic conductivity distribution using BMA are obtained to assess the estimation uncertainty.

Subgrid-scale physical parameterization in atmospheric modeling: How can we make it consistent?

NASA Astrophysics Data System (ADS)

Yano, Jun-Ichi

2016-07-01

Approaches to subgrid-scale physical parameterization in atmospheric modeling are reviewed by taking turbulent combustion flow research as a point of reference. Three major general approaches are considered for its consistent development: moment, distribution density function (DDF), and mode decomposition. The moment expansion is a standard method for describing the subgrid-scale turbulent flows both in geophysics and engineering. The DDF (commonly called PDF) approach is intuitively appealing as it deals with a distribution of variables in subgrid scale in a more direct manner. Mode decomposition was originally applied by Aubry et al (1988 J. Fluid Mech. 192 115-73) in the context of wall boundary-layer turbulence. It is specifically designed to represent coherencies in compact manner by a low-dimensional dynamical system. Their original proposal adopts the proper orthogonal decomposition (empirical orthogonal functions) as their mode-decomposition basis. However, the methodology can easily be generalized into any decomposition basis. Among those, wavelet is a particularly attractive alternative. The mass-flux formulation that is currently adopted in the majority of atmospheric models for parameterizing convection can also be considered a special case of mode decomposition, adopting segmentally constant modes for the expansion basis. This perspective further identifies a very basic but also general geometrical constraint imposed on the massflux formulation: the segmentally-constant approximation. Mode decomposition can, furthermore, be understood by analogy with a Galerkin method in numerically modeling. This analogy suggests that the subgrid parameterization may be re-interpreted as a type of mesh-refinement in numerical modeling. A link between the subgrid parameterization and downscaling problems is also pointed out.

A revised linear ozone photochemistry parameterization for use in transport and general circulation models: multi-annual simulations

NASA Astrophysics Data System (ADS)

Cariolle, D.; Teyssèdre, H.

2007-05-01

This article describes the validation of a linear parameterization of the ozone photochemistry for use in upper tropospheric and stratospheric studies. The present work extends a previously developed scheme by improving the 2-D model used to derive the coefficients of the parameterization. The chemical reaction rates are updated from a compilation that includes recent laboratory work. Furthermore, the polar ozone destruction due to heterogeneous reactions at the surface of the polar stratospheric clouds is taken into account as a function of the stratospheric temperature and the total chlorine content. Two versions of the parameterization are tested. The first one only requires the solution of a continuity equation for the time evolution of the ozone mixing ratio, the second one uses one additional equation for a cold tracer. The parameterization has been introduced into the chemical transport model MOCAGE. The model is integrated with wind and temperature fields from the ECMWF operational analyses over the period 2000-2004. Overall, the results from the two versions show a very good agreement between the modelled ozone distribution and the Total Ozone Mapping Spectrometer (TOMS) satellite data and the "in-situ" vertical soundings. During the course of the integration the model does not show any drift and the biases are generally small, of the order of 10%. The model also reproduces fairly well the polar ozone variability, notably the formation of "ozone holes" in the Southern Hemisphere with amplitudes and a seasonal evolution that follow the dynamics and time evolution of the polar vortex. The introduction of the cold tracer further improves the model simulation by allowing additional ozone destruction inside air masses exported from the high to the mid-latitudes, and by maintaining low ozone content inside the polar vortex of the Southern Hemisphere over longer periods in spring time. It is concluded that for the study of climate scenarios or the assimilation of ozone data, the present parameterization gives a valuable alternative to the introduction of detailed and computationally costly chemical schemes into general circulation models.

Creating and parameterizing patient-specific deep brain stimulation pathway-activation models using the hyperdirect pathway as an example.

PubMed

Gunalan, Kabilar; Chaturvedi, Ashutosh; Howell, Bryan; Duchin, Yuval; Lempka, Scott F; Patriat, Remi; Sapiro, Guillermo; Harel, Noam; McIntyre, Cameron C

2017-01-01

Deep brain stimulation (DBS) is an established clinical therapy and computational models have played an important role in advancing the technology. Patient-specific DBS models are now common tools in both academic and industrial research, as well as clinical software systems. However, the exact methodology for creating patient-specific DBS models can vary substantially and important technical details are often missing from published reports. Provide a detailed description of the assembly workflow and parameterization of a patient-specific DBS pathway-activation model (PAM) and predict the response of the hyperdirect pathway to clinical stimulation. Integration of multiple software tools (e.g. COMSOL, MATLAB, FSL, NEURON, Python) enables the creation and visualization of a DBS PAM. An example DBS PAM was developed using 7T magnetic resonance imaging data from a single unilaterally implanted patient with Parkinson's disease (PD). This detailed description implements our best computational practices and most elaborate parameterization steps, as defined from over a decade of technical evolution. Pathway recruitment curves and strength-duration relationships highlight the non-linear response of axons to changes in the DBS parameter settings. Parameterization of patient-specific DBS models can be highly detailed and constrained, thereby providing confidence in the simulation predictions, but at the expense of time demanding technical implementation steps. DBS PAMs represent new tools for investigating possible correlations between brain pathway activation patterns and clinical symptom modulation.

The Soil Model Development and Intercomparison Panel (SoilMIP) of the International Soil Modeling Consortium (ISMC)

NASA Astrophysics Data System (ADS)

Vanderborght, Jan; Priesack, Eckart

2017-04-01

The Soil Model Development and Intercomparison Panel (SoilMIP) is an initiative of the International Soil Modeling Consortium. Its mission is to foster the further development of soil models that can predict soil functions and their changes (i) due to soil use and land management and (ii) due to external impacts of climate change and pollution. Since soil functions and soil threats are diverse but linked with each other, the overall aim is to develop holistic models that represent the key functions of the soil system and the links between them. These models should be scaled up and integrated in terrestrial system models that describe the feedbacks between processes in the soil and the other terrestrial compartments. We propose and illustrate a few steps that could be taken to achieve these goals. A first step is the development of scenarios that compare simulations by models that predict the same or different soil services. Scenarios can be considered at three different levels of comparisons: scenarios that compare the numerics (accuracy but also speed) of models, scenarios that compare the effect of differences in process descriptions, and scenarios that compare simulations with experimental data. A second step involves the derivation of metrics or summary statistics that effectively compare model simulations and disentangle parameterization from model concept differences. These metrics can be used to evaluate how more complex model simulations can be represented by simpler models using an appropriate parameterization. A third step relates to the parameterization of models. Application of simulation models implies that appropriate model parameters have to be defined for a range of environmental conditions and locations. Spatial modelling approaches are used to derive parameter distributions. Considering that soils and their properties emerge from the interaction between physical, chemical and biological processes, the combination of spatial models with process models would lead to consistent parameter distributions correlations and could potentially represent self-organizing processes in soils and landscapes.

On constraining pilot point calibration with regularization in PEST

USGS Publications Warehouse

Fienen, M.N.; Muffels, C.T.; Hunt, R.J.

2009-01-01

Ground water model calibration has made great advances in recent years with practical tools such as PEST being instrumental for making the latest techniques available to practitioners. As models and calibration tools get more sophisticated, however, the power of these tools can be misapplied, resulting in poor parameter estimates and/or nonoptimally calibrated models that do not suit their intended purpose. Here, we focus on an increasingly common technique for calibrating highly parameterized numerical models - pilot point parameterization with Tikhonov regularization. Pilot points are a popular method for spatially parameterizing complex hydrogeologic systems; however, additional flexibility offered by pilot points can become problematic if not constrained by Tikhonov regularization. The objective of this work is to explain and illustrate the specific roles played by control variables in the PEST software for Tikhonov regularization applied to pilot points. A recent study encountered difficulties implementing this approach, but through examination of that analysis, insight into underlying sources of potential misapplication can be gained and some guidelines for overcoming them developed. ?? 2009 National Ground Water Association.

Methods of testing parameterizations: Vertical ocean mixing

NASA Technical Reports Server (NTRS)

Tziperman, Eli

1992-01-01

The ocean's velocity field is characterized by an exceptional variety of scales. While the small-scale oceanic turbulence responsible for the vertical mixing in the ocean is of scales a few centimeters and smaller, the oceanic general circulation is characterized by horizontal scales of thousands of kilometers. In oceanic general circulation models that are typically run today, the vertical structure of the ocean is represented by a few tens of discrete grid points. Such models cannot explicitly model the small-scale mixing processes, and must, therefore, find ways to parameterize them in terms of the larger-scale fields. Finding a parameterization that is both reliable and plausible to use in ocean models is not a simple task. Vertical mixing in the ocean is the combined result of many complex processes, and, in fact, mixing is one of the less known and less understood aspects of the oceanic circulation. In present models of the oceanic circulation, the many complex processes responsible for vertical mixing are often parameterized in an oversimplified manner. Yet, finding an adequate parameterization of vertical ocean mixing is crucial to the successful application of ocean models to climate studies. The results of general circulation models for quantities that are of particular interest to climate studies, such as the meridional heat flux carried by the ocean, are quite sensitive to the strength of the vertical mixing. We try to examine the difficulties in choosing an appropriate vertical mixing parameterization, and the methods that are available for validating different parameterizations by comparing model results to oceanographic data. First, some of the physical processes responsible for vertically mixing the ocean are briefly mentioned, and some possible approaches to the parameterization of these processes in oceanographic general circulation models are described in the following section. We then discuss the role of the vertical mixing in the physics of the large-scale ocean circulation, and examine methods of validating mixing parameterizations using large-scale ocean models.

Development and evaluation of a physics-based windblown dust emission scheme implemented in the CMAQ modeling system

EPA Science Inventory

A new windblown dust emission treatment was incorporated in the Community Multiscale Air Quality (CMAQ) modeling system. This new model treatment has been built upon previously developed physics-based parameterization schemes from the literature. A distinct and novel feature of t...

Are Atmospheric Updrafts a Key to Unlocking Climate Forcing and Sensitivity?

DOE PAGES

Donner, Leo J.; O'Brien, Travis A.; Rieger, Daniel; ...

2016-06-08

Both climate forcing and climate sensitivity persist as stubborn uncertainties limiting the extent to which climate models can provide actionable scientific scenarios for climate change. A key, explicit control on cloud-aerosol interactions, the largest uncertainty in climate forcing, is the vertical velocity of cloud-scale updrafts. Model-based studies of climate sensitivity indicate that convective entrainment, which is closely related to updraft speeds, is an important control on climate sensitivity. Updraft vertical velocities also drive many physical processes essential to numerical weather prediction. Vertical velocities and their role in atmospheric physical processes have been given very limited attention in models for climatemore » and numerical weather prediction. The relevant physical scales range down to tens of meters and are thus frequently sub-grid and require parameterization. Many state-of-science convection parameterizations provide mass fluxes without specifying vertical velocities, and parameterizations which do provide vertical velocities have been subject to limited evaluation against what have until recently been scant observations. Atmospheric observations imply that the distribution of vertical velocities depends on the areas over which the vertical velocities are averaged. Distributions of vertical velocities in climate models may capture this behavior, but it has not been accounted for when parameterizing cloud and precipitation processes in current models. New observations of convective vertical velocities offer a potentially promising path toward developing process-level cloud models and parameterizations for climate and numerical weather prediction. Taking account of scale-dependence of resolved vertical velocities offers a path to matching cloud-scale physical processes and their driving dynamics more realistically, with a prospect of reduced uncertainty in both climate forcing and sensitivity.« less

Parameterization of ALMANAC crop simulation model for non-irrigated dry bean in semi-arid temperate areas in Mexico

USDA-ARS?s Scientific Manuscript database

Simulation models can be used to make management decisions when properly parameterized. This study aimed to parameterize the ALMANAC (Agricultural Land Management Alternatives with Numerical Assessment Criteria) crop simulation model for dry bean in the semi-arid temperate areas of Mexico. The par...

SWAT Model Configuration, Calibration and Validation for Lake Champlain Basin

EPA Pesticide Factsheets

The Soil and Water Assessment Tool (SWAT) model was used to develop phosphorus loading estimates for sources in the Lake Champlain Basin. This document describes the model setup and parameterization, and presents calibration results.

Parameterization of eddy sensible heat transports in a zonally averaged dynamic model of the atmosphere

NASA Technical Reports Server (NTRS)

Genthon, Christophe; Le Treut, Herve; Sadourny, Robert; Jouzel, Jean

1990-01-01

A Charney-Branscome based parameterization has been tested as a way of representing the eddy sensible heat transports missing in a zonally averaged dynamic model (ZADM) of the atmosphere. The ZADM used is a zonally averaged version of a general circulation model (GCM). The parameterized transports in the ZADM are gaged against the corresponding fluxes explicitly simulated in the GCM, using the same zonally averaged boundary conditions in both models. The Charney-Branscome approach neglects stationary eddies and transient barotropic disturbances and relies on a set of simplifying assumptions, including the linear appoximation, to describe growing transient baroclinic eddies. Nevertheless, fairly satisfactory results are obtained when the parameterization is performed interactively with the model. Compared with noninteractive tests, a very efficient restoring feedback effect between the modeled zonal-mean climate and the parameterized meridional eddy transport is identified.

Alternate methodologies to experimentally investigate shock initiation properties of explosives

NASA Astrophysics Data System (ADS)

Svingala, Forrest R.; Lee, Richard J.; Sutherland, Gerrit T.; Benjamin, Richard; Boyle, Vincent; Sickels, William; Thompson, Ronnie; Samuels, Phillip J.; Wrobel, Erik; Cornell, Rodger

2017-01-01

Reactive flow models are desired for new explosive formulations early in the development stage. Traditionally, these models are parameterized by carefully-controlled 1-D shock experiments, including gas-gun testing with embedded gauges and wedge testing with explosive plane wave lenses (PWL). These experiments are easy to interpret due to their 1-D nature, but are expensive to perform and cannot be performed at all explosive test facilities. This work investigates alternative methods to probe shock-initiation behavior of new explosives using widely-available pentolite gap test donors and simple time-of-arrival type diagnostics. These experiments can be performed at a low cost at most explosives testing facilities. This allows experimental data to parameterize reactive flow models to be collected much earlier in the development of an explosive formulation. However, the fundamentally 2-D nature of these tests may increase the modeling burden in parameterizing these models and reduce general applicability. Several variations of the so-called modified gap test were investigated and evaluated for suitability as an alternative to established 1-D gas gun and PWL techniques. At least partial agreement with 1-D test methods was observed for the explosives tested, and future work is planned to scope the applicability and limitations of these experimental techniques.

DEVELOPMENT OF A LAND-SURFACE MODEL PART I: APPLICATION IN A MESOSCALE METEOROLOGY MODEL

EPA Science Inventory

Parameterization of land-surface processes and consideration of surface inhomogeneities are very important to mesoscale meteorological modeling applications, especially those that provide information for air quality modeling. To provide crucial, reliable information on the diurn...

Towards improved parameterization of a macroscale hydrologic model in a discontinuous permafrost boreal forest ecosystem

DOE PAGES

Endalamaw, Abraham; Bolton, W. Robert; Young-Robertson, Jessica M.; ...

2017-09-14

Modeling hydrological processes in the Alaskan sub-arctic is challenging because of the extreme spatial heterogeneity in soil properties and vegetation communities. Nevertheless, modeling and predicting hydrological processes is critical in this region due to its vulnerability to the effects of climate change. Coarse-spatial-resolution datasets used in land surface modeling pose a new challenge in simulating the spatially distributed and basin-integrated processes since these datasets do not adequately represent the small-scale hydrological, thermal, and ecological heterogeneity. The goal of this study is to improve the prediction capacity of mesoscale to large-scale hydrological models by introducing a small-scale parameterization scheme, which bettermore » represents the spatial heterogeneity of soil properties and vegetation cover in the Alaskan sub-arctic. The small-scale parameterization schemes are derived from observations and a sub-grid parameterization method in the two contrasting sub-basins of the Caribou Poker Creek Research Watershed (CPCRW) in Interior Alaska: one nearly permafrost-free (LowP) sub-basin and one permafrost-dominated (HighP) sub-basin. The sub-grid parameterization method used in the small-scale parameterization scheme is derived from the watershed topography. We found that observed soil thermal and hydraulic properties – including the distribution of permafrost and vegetation cover heterogeneity – are better represented in the sub-grid parameterization method than the coarse-resolution datasets. Parameters derived from the coarse-resolution datasets and from the sub-grid parameterization method are implemented into the variable infiltration capacity (VIC) mesoscale hydrological model to simulate runoff, evapotranspiration (ET), and soil moisture in the two sub-basins of the CPCRW. Simulated hydrographs based on the small-scale parameterization capture most of the peak and low flows, with similar accuracy in both sub-basins, compared to simulated hydrographs based on the coarse-resolution datasets. On average, the small-scale parameterization scheme improves the total runoff simulation by up to 50 % in the LowP sub-basin and by up to 10 % in the HighP sub-basin from the large-scale parameterization. This study shows that the proposed sub-grid parameterization method can be used to improve the performance of mesoscale hydrological models in the Alaskan sub-arctic watersheds.« less

Towards improved parameterization of a macroscale hydrologic model in a discontinuous permafrost boreal forest ecosystem

DOE Office of Scientific and Technical Information (OSTI.GOV)

Endalamaw, Abraham; Bolton, W. Robert; Young-Robertson, Jessica M.

Modeling hydrological processes in the Alaskan sub-arctic is challenging because of the extreme spatial heterogeneity in soil properties and vegetation communities. Nevertheless, modeling and predicting hydrological processes is critical in this region due to its vulnerability to the effects of climate change. Coarse-spatial-resolution datasets used in land surface modeling pose a new challenge in simulating the spatially distributed and basin-integrated processes since these datasets do not adequately represent the small-scale hydrological, thermal, and ecological heterogeneity. The goal of this study is to improve the prediction capacity of mesoscale to large-scale hydrological models by introducing a small-scale parameterization scheme, which bettermore » represents the spatial heterogeneity of soil properties and vegetation cover in the Alaskan sub-arctic. The small-scale parameterization schemes are derived from observations and a sub-grid parameterization method in the two contrasting sub-basins of the Caribou Poker Creek Research Watershed (CPCRW) in Interior Alaska: one nearly permafrost-free (LowP) sub-basin and one permafrost-dominated (HighP) sub-basin. The sub-grid parameterization method used in the small-scale parameterization scheme is derived from the watershed topography. We found that observed soil thermal and hydraulic properties – including the distribution of permafrost and vegetation cover heterogeneity – are better represented in the sub-grid parameterization method than the coarse-resolution datasets. Parameters derived from the coarse-resolution datasets and from the sub-grid parameterization method are implemented into the variable infiltration capacity (VIC) mesoscale hydrological model to simulate runoff, evapotranspiration (ET), and soil moisture in the two sub-basins of the CPCRW. Simulated hydrographs based on the small-scale parameterization capture most of the peak and low flows, with similar accuracy in both sub-basins, compared to simulated hydrographs based on the coarse-resolution datasets. On average, the small-scale parameterization scheme improves the total runoff simulation by up to 50 % in the LowP sub-basin and by up to 10 % in the HighP sub-basin from the large-scale parameterization. This study shows that the proposed sub-grid parameterization method can be used to improve the performance of mesoscale hydrological models in the Alaskan sub-arctic watersheds.« less

Anisotropic Shear Dispersion Parameterization for Mesoscale Eddy Transport

NASA Astrophysics Data System (ADS)

Reckinger, S. J.; Fox-Kemper, B.

2016-02-01

The effects of mesoscale eddies are universally treated isotropically in general circulation models. However, the processes that the parameterization approximates, such as shear dispersion, typically have strongly anisotropic characteristics. The Gent-McWilliams/Redi mesoscale eddy parameterization is extended for anisotropy and tested using 1-degree Community Earth System Model (CESM) simulations. The sensitivity of the model to anisotropy includes a reduction of temperature and salinity biases, a deepening of the southern ocean mixed-layer depth, and improved ventilation of biogeochemical tracers, particularly in oxygen minimum zones. The parameterization is further extended to include the effects of unresolved shear dispersion, which sets the strength and direction of anisotropy. The shear dispersion parameterization is similar to drifter observations in spatial distribution of diffusivity and high-resolution model diagnosis in the distribution of eddy flux orientation.

Evaluation of a Mesoscale Convective System in Variable-Resolution CESM

NASA Astrophysics Data System (ADS)

Payne, A. E.; Jablonowski, C.

2017-12-01

Warm season precipitation over the Southern Great Plains (SGP) follows a well observed diurnal pattern of variability, peaking at night-time, due to the eastward propagation of mesoscale convection systems that develop over the eastern slopes of the Rockies in the late afternoon. While most climate models are unable to adequately capture the organization of convection and characteristic pattern of precipitation over this region, models with high enough resolution to explicitly resolve convection show improvement. However, high resolution simulations are computationally expensive and, in the case of regional climate models, are subject to boundary conditions. Newly developed variable resolution global climate models strike a balance between the benefits of high-resolution regional climate models and the large-scale dynamics of global climate models and low computational cost. Recently developed parameterizations that are insensitive to the model grid scale provide a way to improve model performance. Here, we present an evaluation of the newly available Cloud Layers Unified by Binormals (CLUBB) parameterization scheme in a suite of variable-resolution CESM simulations with resolutions ranging from 110 km to 7 km within a regionally refined region centered over the SGP Atmospheric Radiation Measurement (ARM) site. Simulations utilize the hindcast approach developed by the Department of Energy's Cloud-Associated Parameterizations Testbed (CAPT) for the assessment of climate models. We limit our evaluation to a single mesoscale convective system that passed over the region on May 24, 2008. The effects of grid-resolution on the timing and intensity of precipitation, as well as, on the transition from shallow to deep convection are assessed against ground-based observations from the SGP ARM site, satellite observations and ERA-Interim reanalysis.

Intercomparison Project on Parameterizations of Large-Scale Dynamics for Simulations of Tropical Convection

NASA Astrophysics Data System (ADS)

Sobel, A. H.; Wang, S.; Bellon, G.; Sessions, S. L.; Woolnough, S.

2013-12-01

Parameterizations of large-scale dynamics have been developed in the past decade for studying the interaction between tropical convection and large-scale dynamics, based on our physical understanding of the tropical atmosphere. A principal advantage of these methods is that they offer a pathway to attack the key question of what controls large-scale variations of tropical deep convection. These methods have been used with both single column models (SCMs) and cloud-resolving models (CRMs) to study the interaction of deep convection with several kinds of environmental forcings. While much has been learned from these efforts, different groups' efforts are somewhat hard to compare. Different models, different versions of the large-scale parameterization methods, and experimental designs that differ in other ways are used. It is not obvious which choices are consequential to the scientific conclusions drawn and which are not. The methods have matured to the point that there is value in an intercomparison project. In this context, the Global Atmospheric Systems Study - Weak Temperature Gradient (GASS-WTG) project was proposed at the Pan-GASS meeting in September 2012. The weak temperature gradient approximation is one method to parameterize large-scale dynamics, and is used in the project name for historical reasons and simplicity, but another method, the damped gravity wave (DGW) method, will also be used in the project. The goal of the GASS-WTG project is to develop community understanding of the parameterization methods currently in use. Their strengths, weaknesses, and functionality in models with different physics and numerics will be explored in detail, and their utility to improve our understanding of tropical weather and climate phenomena will be further evaluated. This presentation will introduce the intercomparison project, including background, goals, and overview of the proposed experimental design. Interested groups will be invited to join (it will not be too late), and preliminary results will be presented.

Longwave Radiative Flux Calculations in the TOVS Pathfinder Path A Data Set

NASA Technical Reports Server (NTRS)

Mehta, Amita; Susskind, Joel

1999-01-01

A radiative transfer model developed to calculate outgoing longwave radiation (OLR) and downwelling longwave, surface flux (DSF) from the Television and Infrared Operational Satellite (TIROS) Operational Vertical Sounder (TOVS) Pathfinder Path A retrieval products is described. The model covers the spectral range of 2 to 2800 cm in 14 medium medium spectral bands. For each band, transmittances are parameterized as a function of temperature, water vapor, and ozone profiles. The form of the band transmittance parameterization is a modified version of the approach we use to model channel transmittances for the High Resolution Infrared Sounder 2 (HIRS2) instrument. We separately derive effective zenith angle for each spectral band such that band-averaged radiance calculated at that angle best approximates directionally integrated radiance for that band. We develop the transmittance parameterization at these band-dependent effective zenith angles to incorporate directional integration of radiances required in the calculations of OLR and DSF. The model calculations of OLR and DSF are accurate and differ by less than 1% from our line-by-line calculations. Also, the model results are within 1% range of other line-by-line calculations provided by the Intercomparison of Radiation Codes in Climate Models (ICRCCM) project for clear-sky and cloudy conditions. The model is currently used to calculate global, multiyear (1985-1998) OLR and DSF from the TOVS Pathfinder Path A Retrievals.

Sensitivity of Coupled Tropical Pacific Model Biases to Convective Parameterization in CESM1

NASA Astrophysics Data System (ADS)

Woelfle, M. D.; Yu, S.; Bretherton, C. S.; Pritchard, M. S.

2018-01-01

Six month coupled hindcasts show the central equatorial Pacific cold tongue bias development in a GCM to be sensitive to the atmospheric convective parameterization employed. Simulations using the standard configuration of the Community Earth System Model version 1 (CESM1) develop a cold bias in equatorial Pacific sea surface temperatures (SSTs) within the first two months of integration due to anomalous ocean advection driven by overly strong easterly surface wind stress along the equator. Disabling the deep convection parameterization enhances the zonal pressure gradient leading to stronger zonal wind stress and a stronger equatorial SST bias, highlighting the role of pressure gradients in determining the strength of the cold bias. Superparameterized hindcasts show reduced SST bias in the cold tongue region due to a reduction in surface easterlies despite simulating an excessively strong low-level jet at 1-1.5 km elevation. This reflects inadequate vertical mixing of zonal momentum from the absence of convective momentum transport in the superparameterized model. Standard CESM1simulations modified to omit shallow convective momentum transport reproduce the superparameterized low-level wind bias and associated equatorial SST pattern. Further superparameterized simulations using a three-dimensional cloud resolving model capable of producing realistic momentum transport simulate a cold tongue similar to the default CESM1. These findings imply convective momentum fluxes may be an underappreciated mechanism for controlling the strength of the equatorial cold tongue. Despite the sensitivity of equatorial SST to these changes in convective parameterization, the east Pacific double-Intertropical Convergence Zone rainfall bias persists in all simulations presented in this study.

Numerical optimization of Ignition and Growth reactive flow modeling for PAX2A

NASA Astrophysics Data System (ADS)

Baker, E. L.; Schimel, B.; Grantham, W. J.

1996-05-01

Variable metric nonlinear optimization has been successfully applied to the parameterization of unreacted and reacted products thermodynamic equations of state and reactive flow modeling of the HMX based high explosive PAX2A. The NLQPEB nonlinear optimization program has been recently coupled to the LLNL developed two-dimensional high rate continuum modeling programs DYNA2D and CALE. The resulting program has the ability to optimize initial modeling parameters. This new optimization capability was used to optimally parameterize the Ignition and Growth reactive flow model to experimental manganin gauge records. The optimization varied the Ignition and Growth reaction rate model parameters in order to minimize the difference between the calculated pressure histories and the experimental pressure histories.

A diapycnal diffusivity model for stratified environmental flows

NASA Astrophysics Data System (ADS)

Bouffard, Damien; Boegman, Leon

2013-06-01

The vertical diffusivity of density, Kρ, regulates ocean circulation, climate and coastal water quality. Kρ is difficult to measure and model in these stratified turbulent flows, resulting in the need for the development of Kρ parameterizations from more readily measurable flow quantities. Typically, Kρ is parameterized from turbulent temperature fluctuations using the Osborn-Cox model or from the buoyancy frequency, N, kinematic viscosity, ν, and the rate of dissipation of turbulent kinetic energy, ɛ, using the Osborn model. More recently, Shih et al. (2005, J. Fluid Mech. 525: 193-214) proposed a laboratory scale parameterization for Kρ, at Prandtl number (ratio of the viscosity over the molecular diffusivity) Pr = 0.7, in terms of the turbulence intensity parameter, Re=ɛ/(νN), which is the ratio between the destabilizing effect of turbulence to the stabilizing effects of stratification and viscosity. In the present study, we extend the SKIF parameterization, against extensive sets of published data, over 0.7 < Pr < 700 and validate it at field scale. Our results show that the SKIF model must be modified to include a new Buoyancy-controlled mixing regime, between the Molecular and Transitional regimes, where Kρ is captured using the molecular diffusivity and Osborn model, respectively. The Buoyancy-controlled regime occurs over 10Pr

Empirical parameterization of setup, swash, and runup

USGS Publications Warehouse

Stockdon, H.F.; Holman, R.A.; Howd, P.A.; Sallenger, A.H.

2006-01-01

Using shoreline water-level time series collected during 10 dynamically diverse field experiments, an empirical parameterization for extreme runup, defined by the 2% exceedence value, has been developed for use on natural beaches over a wide range of conditions. Runup, the height of discrete water-level maxima, depends on two dynamically different processes; time-averaged wave setup and total swash excursion, each of which is parameterized separately. Setup at the shoreline was best parameterized using a dimensional form of the more common Iribarren-based setup expression that includes foreshore beach slope, offshore wave height, and deep-water wavelength. Significant swash can be decomposed into the incident and infragravity frequency bands. Incident swash is also best parameterized using a dimensional form of the Iribarren-based expression. Infragravity swash is best modeled dimensionally using offshore wave height and wavelength and shows no statistically significant linear dependence on either foreshore or surf-zone slope. On infragravity-dominated dissipative beaches, the magnitudes of both setup and swash, modeling both incident and infragravity frequency components together, are dependent only on offshore wave height and wavelength. Statistics of predicted runup averaged over all sites indicate a - 17 cm bias and an rms error of 38 cm: the mean observed runup elevation for all experiments was 144 cm. On intermediate and reflective beaches with complex foreshore topography, the use of an alongshore-averaged beach slope in practical applications of the runup parameterization may result in a relative runup error equal to 51% of the fractional variability between the measured and the averaged slope.

Gsflow-py: An integrated hydrologic model development tool

NASA Astrophysics Data System (ADS)

Gardner, M.; Niswonger, R. G.; Morton, C.; Henson, W.; Huntington, J. L.

2017-12-01

Integrated hydrologic modeling encompasses a vast number of processes and specifications, variable in time and space, and development of model datasets can be arduous. Model input construction techniques have not been formalized or made easily reproducible. Creating the input files for integrated hydrologic models (IHM) requires complex GIS processing of raster and vector datasets from various sources. Developing stream network topology that is consistent with the model resolution digital elevation model is important for robust simulation of surface water and groundwater exchanges. Distribution of meteorologic parameters over the model domain is difficult in complex terrain at the model resolution scale, but is necessary to drive realistic simulations. Historically, development of input data for IHM models has required extensive GIS and computer programming expertise which has restricted the use of IHMs to research groups with available financial, human, and technical resources. Here we present a series of Python scripts that provide a formalized technique for the parameterization and development of integrated hydrologic model inputs for GSFLOW. With some modifications, this process could be applied to any regular grid hydrologic model. This Python toolkit automates many of the necessary and laborious processes of parameterization, including stream network development and cascade routing, land coverages, and meteorological distribution over the model domain.

SWAT: Model use, calibration, and validation

USDA-ARS?s Scientific Manuscript database

SWAT (Soil and Water Assessment Tool) is a comprehensive, semi-distributed river basin model that requires a large number of input parameters which complicates model parameterization and calibration. Several calibration techniques have been developed for SWAT including manual calibration procedures...

A MULTILAYER BIOCHEMICAL DRY DEPOSITION MODEL 1. MODEL FORMULATION

EPA Science Inventory

A multilayer biochemical dry deposition model has been developed based on the NOAA Multilayer Model (MLM) to study gaseous exchanges between the soil, plants, and the atmosphere. Most of the parameterizations and submodels have been updated or replaced. The numerical integration ...

Final Report for “Simulating the Arctic Winter Longwave Indirect Effects. A New Parameterization for Frost Flower Aerosol Salt Emissions” (DESC0006679) for 9/15/2011 through 9/14/2015

DOE Office of Scientific and Technical Information (OSTI.GOV)

Russell, Lynn M.; Somerville, Richard C.J.; Burrows, Susannah

Description of the Project: This project has improved the aerosol formulation in a global climate model by using innovative new field and laboratory observations to develop and implement a novel wind-driven sea ice aerosol flux parameterization. This work fills a critical gap in the understanding of clouds, aerosol, and radiation in polar regions by addressing one of the largest missing particle sources in aerosol-climate modeling. Recent measurements of Arctic organic and inorganic aerosol indicate that the largest source of natural aerosol during the Arctic winter is emitted from crystal structures, known as frost flowers, formed on a newly frozen seamore » ice surface [Shaw et al., 2010]. We have implemented the new parameterization in an updated climate model making it the first capable of investigating how polar natural aerosol-cloud indirect effects relate to this important and previously unrecognized sea ice source. The parameterization is constrained by Arctic ARM in situ cloud and radiation data. The modified climate model has been used to quantify the potential pan-Arctic radiative forcing and aerosol indirect effects due to this missing source. This research supported the work of one postdoc (Li Xu) for two years and contributed to the training and research of an undergraduate student. This research allowed us to establish a collaboration between SIO and PNNL in order to contribute the frost flower parameterization to the new ACME model. One peer-reviewed publications has already resulted from this work, and a manuscript for a second publication has been completed. Additional publications from the PNNL collaboration are expected to follow.« less

Representing the effects of stratosphere–troposphere ...

EPA Pesticide Factsheets

Downward transport of ozone (O3) from the stratosphere can be a significant contributor to tropospheric O3 background levels. However, this process often is not well represented in current regional models. In this study, we develop a seasonally and spatially varying potential vorticity (PV)-based function to parameterize upper tropospheric and/or lower stratospheric (UTLS) O3 in a chemistry transport model. This dynamic O3–PV function is developed based on 21-year ozonesonde records from World Ozone and Ultraviolet Radiation Data Centre (WOUDC) with corresponding PV values from a 21-year Weather Research and Forecasting (WRF) simulation across the Northern Hemisphere from 1990 to 2010. The result suggests strong spatial and seasonal variations of O3 ∕ PV ratios which exhibits large values in the upper layers and in high-latitude regions, with highest values in spring and the lowest values in autumn over an annual cycle. The newly developed O3 ∕ PV function was then applied in the Community Multiscale Air Quality (CMAQ) model for an annual simulation of the year 2006. The simulated UTLS O3 agrees much better with observations in both magnitude and seasonality after the implementation of the new parameterization. Considerable impacts on surface O3 model performance were found in the comparison with observations from three observational networks, i.e., EMEP, CASTNET and WDCGG. With the new parameterization, the negative bias in spring is reduced from

Dynamically consistent parameterization of mesoscale eddies. Part III: Deterministic approach

NASA Astrophysics Data System (ADS)

Berloff, Pavel

2018-07-01

This work continues development of dynamically consistent parameterizations for representing mesoscale eddy effects in non-eddy-resolving and eddy-permitting ocean circulation models and focuses on the classical double-gyre problem, in which the main dynamic eddy effects maintain eastward jet extension of the western boundary currents and its adjacent recirculation zones via eddy backscatter mechanism. Despite its fundamental importance, this mechanism remains poorly understood, and in this paper we, first, study it and, then, propose and test its novel parameterization. We start by decomposing the reference eddy-resolving flow solution into the large-scale and eddy components defined by spatial filtering, rather than by the Reynolds decomposition. Next, we find that the eastward jet and its recirculations are robustly present not only in the large-scale flow itself, but also in the rectified time-mean eddies, and in the transient rectified eddy component, which consists of highly anisotropic ribbons of the opposite-sign potential vorticity anomalies straddling the instantaneous eastward jet core and being responsible for its continuous amplification. The transient rectified component is separated from the flow by a novel remapping method. We hypothesize that the above three components of the eastward jet are ultimately driven by the small-scale transient eddy forcing via the eddy backscatter mechanism, rather than by the mean eddy forcing and large-scale nonlinearities. We verify this hypothesis by progressively turning down the backscatter and observing the induced flow anomalies. The backscatter analysis leads us to formulating the key eddy parameterization hypothesis: in an eddy-permitting model at least partially resolved eddy backscatter can be significantly amplified to improve the flow solution. Such amplification is a simple and novel eddy parameterization framework implemented here in terms of local, deterministic flow roughening controlled by single parameter. We test the parameterization skills in an hierarchy of non-eddy-resolving and eddy-permitting modifications of the original model and demonstrate, that indeed it can be highly efficient for restoring the eastward jet extension and its adjacent recirculation zones. The new deterministic parameterization framework not only combines remarkable simplicity with good performance but also is dynamically transparent, therefore, it provides a powerful alternative to the common eddy diffusion and emerging stochastic parameterizations.

A general science-based framework for dynamical spatio-temporal models

USGS Publications Warehouse

Wikle, C.K.; Hooten, M.B.

2010-01-01

Spatio-temporal statistical models are increasingly being used across a wide variety of scientific disciplines to describe and predict spatially-explicit processes that evolve over time. Correspondingly, in recent years there has been a significant amount of research on new statistical methodology for such models. Although descriptive models that approach the problem from the second-order (covariance) perspective are important, and innovative work is being done in this regard, many real-world processes are dynamic, and it can be more efficient in some cases to characterize the associated spatio-temporal dependence by the use of dynamical models. The chief challenge with the specification of such dynamical models has been related to the curse of dimensionality. Even in fairly simple linear, first-order Markovian, Gaussian error settings, statistical models are often over parameterized. Hierarchical models have proven invaluable in their ability to deal to some extent with this issue by allowing dependency among groups of parameters. In addition, this framework has allowed for the specification of science based parameterizations (and associated prior distributions) in which classes of deterministic dynamical models (e. g., partial differential equations (PDEs), integro-difference equations (IDEs), matrix models, and agent-based models) are used to guide specific parameterizations. Most of the focus for the application of such models in statistics has been in the linear case. The problems mentioned above with linear dynamic models are compounded in the case of nonlinear models. In this sense, the need for coherent and sensible model parameterizations is not only helpful, it is essential. Here, we present an overview of a framework for incorporating scientific information to motivate dynamical spatio-temporal models. First, we illustrate the methodology with the linear case. We then develop a general nonlinear spatio-temporal framework that we call general quadratic nonlinearity and demonstrate that it accommodates many different classes of scientific-based parameterizations as special cases. The model is presented in a hierarchical Bayesian framework and is illustrated with examples from ecology and oceanography. ?? 2010 Sociedad de Estad??stica e Investigaci??n Operativa.

Development and evaluation of an ammonia bidirectional flux parameterization for air quality models

EPA Science Inventory

Ammonia is an important contributor to particulate matter in the atmosphere and can significantly impact terrestrial and aquatic ecosystems. Surface exchange between the atmosphere and biosphere is a key part of the ammonia cycle. New modeling techniques are being developed for u...

Creating and parameterizing patient-specific deep brain stimulation pathway-activation models using the hyperdirect pathway as an example

PubMed Central

Gunalan, Kabilar; Chaturvedi, Ashutosh; Howell, Bryan; Duchin, Yuval; Lempka, Scott F.; Patriat, Remi; Sapiro, Guillermo; Harel, Noam; McIntyre, Cameron C.

2017-01-01

Background Deep brain stimulation (DBS) is an established clinical therapy and computational models have played an important role in advancing the technology. Patient-specific DBS models are now common tools in both academic and industrial research, as well as clinical software systems. However, the exact methodology for creating patient-specific DBS models can vary substantially and important technical details are often missing from published reports. Objective Provide a detailed description of the assembly workflow and parameterization of a patient-specific DBS pathway-activation model (PAM) and predict the response of the hyperdirect pathway to clinical stimulation. Methods Integration of multiple software tools (e.g. COMSOL, MATLAB, FSL, NEURON, Python) enables the creation and visualization of a DBS PAM. An example DBS PAM was developed using 7T magnetic resonance imaging data from a single unilaterally implanted patient with Parkinson’s disease (PD). This detailed description implements our best computational practices and most elaborate parameterization steps, as defined from over a decade of technical evolution. Results Pathway recruitment curves and strength-duration relationships highlight the non-linear response of axons to changes in the DBS parameter settings. Conclusion Parameterization of patient-specific DBS models can be highly detailed and constrained, thereby providing confidence in the simulation predictions, but at the expense of time demanding technical implementation steps. DBS PAMs represent new tools for investigating possible correlations between brain pathway activation patterns and clinical symptom modulation. PMID:28441410

Parameterizing the Spatial Markov Model From Breakthrough Curve Data Alone

NASA Astrophysics Data System (ADS)

Sherman, Thomas; Fakhari, Abbas; Miller, Savannah; Singha, Kamini; Bolster, Diogo

2017-12-01

The spatial Markov model (SMM) is an upscaled Lagrangian model that effectively captures anomalous transport across a diverse range of hydrologic systems. The distinct feature of the SMM relative to other random walk models is that successive steps are correlated. To date, with some notable exceptions, the model has primarily been applied to data from high-resolution numerical simulations and correlation effects have been measured from simulated particle trajectories. In real systems such knowledge is practically unattainable and the best one might hope for is breakthrough curves (BTCs) at successive downstream locations. We introduce a novel methodology to quantify velocity correlation from BTC data alone. By discretizing two measured BTCs into a set of arrival times and developing an inverse model, we estimate velocity correlation, thereby enabling parameterization of the SMM in studies where detailed Lagrangian velocity statistics are unavailable. The proposed methodology is applied to two synthetic numerical problems, where we measure all details and thus test the veracity of the approach by comparison of estimated parameters with known simulated values. Our results suggest that our estimated transition probabilities agree with simulated values and using the SMM with this estimated parameterization accurately predicts BTCs downstream. Our methodology naturally allows for estimates of uncertainty by calculating lower and upper bounds of velocity correlation, enabling prediction of a range of BTCs. The measured BTCs fall within the range of predicted BTCs. This novel method to parameterize the SMM from BTC data alone is quite parsimonious, thereby widening the SMM's practical applicability.

Parameterizing unresolved obstacles with source terms in wave modeling: A real-world application

NASA Astrophysics Data System (ADS)

Mentaschi, Lorenzo; Kakoulaki, Georgia; Vousdoukas, Michalis; Voukouvalas, Evangelos; Feyen, Luc; Besio, Giovanni

2018-06-01

Parameterizing the dissipative effects of small, unresolved coastal features, is fundamental to improve the skills of wave models. The established technique to deal with this problem consists in reducing the amount of energy advected within the propagation scheme, and is currently available only for regular grids. To find a more general approach, Mentaschi et al., 2015b formulated a technique based on source terms, and validated it on synthetic case studies. This technique separates the parameterization of the unresolved features from the energy advection, and can therefore be applied to any numerical scheme and to any type of mesh. Here we developed an open-source library for the estimation of the transparency coefficients needed by this approach, from bathymetric data and for any type of mesh. The spectral wave model WAVEWATCH III was used to show that in a real-world domain, such as the Caribbean Sea, the proposed approach has skills comparable and sometimes better than the established propagation-based technique.

Evaluation of scale-aware subgrid mesoscale eddy models in a global eddy-rich model

NASA Astrophysics Data System (ADS)

Pearson, Brodie; Fox-Kemper, Baylor; Bachman, Scott; Bryan, Frank

2017-07-01

Two parameterizations for horizontal mixing of momentum and tracers by subgrid mesoscale eddies are implemented in a high-resolution global ocean model. These parameterizations follow on the techniques of large eddy simulation (LES). The theory underlying one parameterization (2D Leith due to Leith, 1996) is that of enstrophy cascades in two-dimensional turbulence, while the other (QG Leith) is designed for potential enstrophy cascades in quasi-geostrophic turbulence. Simulations using each of these parameterizations are compared with a control simulation using standard biharmonic horizontal mixing.Simulations using the 2D Leith and QG Leith parameterizations are more realistic than those using biharmonic mixing. In particular, the 2D Leith and QG Leith simulations have more energy in resolved mesoscale eddies, have a spectral slope more consistent with turbulence theory (an inertial enstrophy or potential enstrophy cascade), have bottom drag and vertical viscosity as the primary sinks of energy instead of lateral friction, and have isoneutral parameterized mesoscale tracer transport. The parameterization choice also affects mass transports, but the impact varies regionally in magnitude and sign.

Developing a new parameterization framework for the heterogeneous ice nucleation of atmospheric aerosol particles

NASA Astrophysics Data System (ADS)

Ullrich, Romy; Hiranuma, Naruki; Hoose, Corinna; Möhler, Ottmar; Niemand, Monika; Steinke, Isabelle; Wagner, Robert

2014-05-01

Developing a new parameterization framework for the heterogeneous ice nucleation of atmospheric aerosol particles Ullrich, R., Hiranuma, N., Hoose, C., Möhler, O., Niemand, M., Steinke, I., Wagner, R. Aerosols of different nature induce microphysical processes of importance for the Earth's atmosphere. They affect not only directly the radiative budget, more importantly they essentially influence the formation and life cycles of clouds. Hence, aerosols and their ice nucleating ability are a fundamental input parameter for weather and climate models. During the previous years, the AIDA (Aerosol Interactions and Dynamics in the Atmosphere) cloud chamber was used to extensively measure, under nearly realistic conditions, the ice nucleating properties of different aerosols. Numerous experiments were performed with a broad variety of aerosol types and under different freezing conditions. A reanalysis of these experiments offers the opportunity to develop a uniform parameterization framework of ice formation for many atmospherically relevant aerosols in a broad temperature and humidity range. The analysis includes both deposition nucleation and immersion freezing. The aim of this study is to develop this comprehensive parameterization for heterogeneous ice formation mainly by using the ice nucleation active site (INAS) approach. Niemand et al. (2012) already developed a temperature dependent parameterization for the INAS- density for immersion freezing on desert dust particles. In addition to a reanalysis of the ice nucleation behaviour of desert dust (Niemand et al. (2012)), volcanic ash (Steinke et al. (2010)) and organic particles (Wagner et al. (2010,2011)) this contribution will also show new results for the immersion freezing and deposition nucleation of soot aerosols. The next step will be the implementation of the parameterizations into the COSMO- ART model in order to test and demonstrate the usability of the framework. Hoose, C. and Möhler, O. (2012) Atmos. Chem. Phys. 12, 9817-9854 Niemand, M., Möhler, O., Vogel, B., Hoose, C., Connolly, P., Klein, H., Bingemer, H., DeMott, P.J., Skrotzki, J. and Leisner, T. (2012) J. Atmos. Sci. 69, 3077-3092 Steinke, I., Möhler, O., Kiselev, A., Niemand, M., Saathoff, H., Schnaiter, M., Skrotzki, J., Hoose, C. and Leisner, T. (2011) Atmos. Chem. Phys. 11, 12945-12958 Wagner, R., Möhler, O., Saathoff, H., Schnaiter, M. and Leisner, T. (2010) Atmos. Chem. Phys. 10, 7617-7641 Wagner, R., Möhler, O., Saathoff, H., Schnaiter, M. and Leisner, T. (2011) Atmos. Chem. Phys. 11, 2083-2110

Prediction of heavy rainfall over Chennai Metropolitan City, Tamil Nadu, India: Impact of microphysical parameterization schemes

NASA Astrophysics Data System (ADS)

Singh, K. S.; Bonthu, Subbareddy; Purvaja, R.; Robin, R. S.; Kannan, B. A. M.; Ramesh, R.

2018-04-01

This study attempts to investigate the real-time prediction of a heavy rainfall event over the Chennai Metropolitan City, Tamil Nadu, India that occurred on 01 December 2015 using Advanced Research Weather Research and Forecasting (WRF-ARW) model. The study evaluates the impact of six microphysical (Lin, WSM6, Goddard, Thompson, Morrison and WDM6) parameterization schemes of the model on prediction of heavy rainfall event. In addition, model sensitivity has also been evaluated with six Planetary Boundary Layer (PBL) and two Land Surface Model (LSM) schemes. Model forecast was carried out using nested domain and the impact of model horizontal grid resolutions were assessed at 9 km, 6 km and 3 km. Analysis of the synoptic features using National Center for Environmental Prediction Global Forecast System (NCEP-GFS) analysis data revealed strong upper-level divergence and high moisture content at lower level were favorable for the occurrence of heavy rainfall event over the northeast coast of Tamil Nadu. The study signified that forecasted rainfall was more sensitive to the microphysics and PBL schemes compared to the LSM schemes. The model provided better forecast of the heavy rainfall event using the logical combination of Goddard microphysics, YSU PBL and Noah LSM schemes, and it was mostly attributed to timely initiation and development of the convective system. The forecast with different horizontal resolutions using cumulus parameterization indicated that the rainfall prediction was not well represented at 9 km and 6 km. The forecast with 3 km horizontal resolution provided better prediction in terms of timely initiation and development of the event. The study highlights that forecast of heavy rainfall events using a high-resolution mesoscale model with suitable representations of physical parameterization schemes are useful for disaster management and planning to minimize the potential loss of life and property.

Regularized wave equation migration for imaging and data reconstruction

NASA Astrophysics Data System (ADS)

Kaplan, Sam T.

The reflection seismic experiment results in a measurement (reflection seismic data) of the seismic wavefield. The linear Born approximation to the seismic wavefield leads to a forward modelling operator that we use to approximate reflection seismic data in terms of a scattering potential. We consider approximations to the scattering potential using two methods: the adjoint of the forward modelling operator (migration), and regularized numerical inversion using the forward and adjoint operators. We implement two parameterizations of the forward modelling and migration operators: source-receiver and shot-profile. For both parameterizations, we find requisite Green's function using the split-step approximation. We first develop the forward modelling operator, and then find the adjoint (migration) operator by recognizing a Fredholm integral equation of the first kind. The resulting numerical system is generally under-determined, requiring prior information to find a solution. In source-receiver migration, the parameterization of the scattering potential is understood using the migration imaging condition, and this encourages us to apply sparse prior models to the scattering potential. To that end, we use both a Cauchy prior and a mixed Cauchy-Gaussian prior, finding better resolved estimates of the scattering potential than are given by the adjoint. In shot-profile migration, the parameterization of the scattering potential has its redundancy in multiple active energy sources (i.e. shots). We find that a smallest model regularized inverse representation of the scattering potential gives a more resolved picture of the earth, as compared to the simpler adjoint representation. The shot-profile parameterization allows us to introduce a joint inversion to further improve the estimate of the scattering potential. Moreover, it allows us to introduce a novel data reconstruction algorithm so that limited data can be interpolated/extrapolated. The linearized operators are expensive, encouraging their parallel implementation. For the source-receiver parameterization of the scattering potential this parallelization is non-trivial. Seismic data is typically corrupted by various types of noise. Sparse coding can be used to suppress noise prior to migration. It is a method that stems from information theory and that we apply to noise suppression in seismic data.

Investigating the Sensitivity of Nucleation Parameterization on Ice Growth

NASA Astrophysics Data System (ADS)

Gaudet, L.; Sulia, K. J.

2017-12-01

The accurate prediction of precipitation from lake-effect snow events associated with the Great Lakes region depends on the parameterization of thermodynamic and microphysical processes, including the formation and subsequent growth of frozen hydrometeors. More specifically, the formation of ice hydrometeors has been represented through varying forms of ice nucleation parameterizations considering the different nucleation modes (e.g., deposition, condensation-freezing, homogeneous). These parameterizations have been developed from in-situ measurements and laboratory observations. A suite of nucleation parameterizations consisting of those published in Meyers et al. (1992) and DeMott et al. (2010) as well as varying ice nuclei data sources are coupled with the Adaptive Habit Model (AHM, Harrington et al. 2013), a microphysics module where ice crystal aspect ratio and density are predicted and evolve in time. Simulations are run with the AHM which is implemented in the Weather Research and Forecasting (WRF) model to investigate the effect of ice nucleation parameterization on the non-spherical growth and evolution of ice crystals and the subsequent effects on liquid-ice cloud-phase partitioning. Specific lake-effect storms that were observed during the Ontario Winter Lake-Effect Systems (OWLeS) field campaign (Kristovich et al. 2017) are examined to elucidate this potential microphysical effect. Analysis of these modeled events is aided by dual-polarization radar data from the WSR-88D in Montague, New York (KTYX). This enables a comparison of the modeled and observed polarmetric and microphysical profiles of the lake-effect clouds, which involves investigating signatures of reflectivity, specific differential phase, correlation coefficient, and differential reflectivity. Microphysical features of lake-effect bands, such as ice, snow, and liquid mixing ratios, ice crystal aspect ratio, and ice density are analyzed to understand signatures in the aforementioned modeled dual-polarization radar variables. Hence, this research helps to determine an ice nucleation scheme that will best model observations of lake-effect clouds producing snow off of Lake Ontario and Lake Erie, and analyses will highlight the sensitivity of the evolution of the cases to a given nucleation scheme.

Evaluation of Aerosol-cloud Interaction in the GISS Model E Using ARM Observations

NASA Technical Reports Server (NTRS)

DeBoer, G.; Bauer, S. E.; Toto, T.; Menon, Surabi; Vogelmann, A. M.

2013-01-01

Observations from the US Department of Energy's Atmospheric Radiation Measurement (ARM) program are used to evaluate the ability of the NASA GISS ModelE global climate model in reproducing observed interactions between aerosols and clouds. Included in the evaluation are comparisons of basic meteorology and aerosol properties, droplet activation, effective radius parameterizations, and surface-based evaluations of aerosol-cloud interactions (ACI). Differences between the simulated and observed ACI are generally large, but these differences may result partially from vertical distribution of aerosol in the model, rather than the representation of physical processes governing the interactions between aerosols and clouds. Compared to the current observations, the ModelE often features elevated droplet concentrations for a given aerosol concentration, indicating that the activation parameterizations used may be too aggressive. Additionally, parameterizations for effective radius commonly used in models were tested using ARM observations, and there was no clear superior parameterization for the cases reviewed here. This lack of consensus is demonstrated to result in potentially large, statistically significant differences to surface radiative budgets, should one parameterization be chosen over another.

Sensitivity of liquid clouds to homogenous freezing parameterizations.

PubMed

Herbert, Ross J; Murray, Benjamin J; Dobbie, Steven J; Koop, Thomas

2015-03-16

Water droplets in some clouds can supercool to temperatures where homogeneous ice nucleation becomes the dominant freezing mechanism. In many cloud resolving and mesoscale models, it is assumed that homogeneous ice nucleation in water droplets only occurs below some threshold temperature typically set at -40°C. However, laboratory measurements show that there is a finite rate of nucleation at warmer temperatures. In this study we use a parcel model with detailed microphysics to show that cloud properties can be sensitive to homogeneous ice nucleation as warm as -30°C. Thus, homogeneous ice nucleation may be more important for cloud development, precipitation rates, and key cloud radiative parameters than is often assumed. Furthermore, we show that cloud development is particularly sensitive to the temperature dependence of the nucleation rate. In order to better constrain the parameterization of homogeneous ice nucleation laboratory measurements are needed at both high (>-35°C) and low (<-38°C) temperatures. Homogeneous freezing may be significant as warm as -30°CHomogeneous freezing should not be represented by a threshold approximationThere is a need for an improved parameterization of homogeneous ice nucleation.

Influence of the vertical mixing parameterization on the modeling results of the Arctic Ocean hydrology

NASA Astrophysics Data System (ADS)

Iakshina, D. F.; Golubeva, E. N.

2017-11-01

The vertical distribution of the hydrological characteristics in the upper ocean layer is mostly formed under the influence of turbulent and convective mixing, which are not resolved in the system of equations for large-scale ocean. Therefore it is necessary to include additional parameterizations of these processes into the numerical models. In this paper we carry out a comparative analysis of the different vertical mixing parameterizations in simulations of climatic variability of the Arctic water and sea ice circulation. The 3D regional numerical model for the Arctic and North Atlantic developed in the ICMMG SB RAS (Institute of Computational Mathematics and Mathematical Geophysics of the Siberian Branch of the Russian Academy of Science) and package GOTM (General Ocean Turbulence Model1,2, http://www.gotm.net/) were used as the numerical instruments . NCEP/NCAR reanalysis data were used for determination of the surface fluxes related to ice and ocean. The next turbulence closure schemes were used for the vertical mixing parameterizations: 1) Integration scheme based on the Richardson criteria (RI); 2) Second-order scheme TKE with coefficients Canuto-A3 (CANUTO); 3) First-order scheme TKE with coefficients Schumann and Gerz4 (TKE-1); 4) Scheme KPP5 (KPP). In addition we investigated some important characteristics of the Arctic Ocean state including the intensity of Atlantic water inflow, ice cover state and fresh water content in Beaufort Sea.

Impacts of subgrid-scale orography parameterization on simulated atmospheric fields over Korea using a high-resolution atmospheric forecast model

NASA Astrophysics Data System (ADS)

Lim, Kyo-Sun Sunny; Lim, Jong-Myoung; Shin, Hyeyum Hailey; Hong, Jinkyu; Ji, Young-Yong; Lee, Wanno

2018-06-01

A substantial over-prediction bias at low-to-moderate wind speeds in the Weather Research and Forecasting (WRF) model has been reported in the previous studies. Low-level wind fields play an important role in dispersion of air pollutants, including radionuclides, in a high-resolution WRF framework. By implementing two subgrid-scale orography parameterizations (Jimenez and Dudhia in J Appl Meteorol Climatol 51:300-316, 2012; Mass and Ovens in WRF model physics: problems, solutions and a new paradigm for progress. Preprints, 2010 WRF Users' Workshop, NCAR, Boulder, Colo. http://www.mmm.ucar.edu/wrf/users/workshops/WS2010/presentations/session%204/4-1_WRFworkshop2010Final.pdf, 2010), we tried to compare the performance of parameterizations and to enhance the forecast skill of low-level wind fields over the central western part of South Korea. Even though both subgrid-scale orography parameterizations significantly alleviated the positive bias at 10-m wind speed, the parameterization by Jimenez and Dudhia revealed a better forecast skill in wind speed under our modeling configuration. Implementation of the subgrid-scale orography parameterizations in the model did not affect the forecast skills in other meteorological fields including 10-m wind direction. Our study also brought up the problem of discrepancy in the definition of "10-m" wind between model physics parameterizations and observations, which can cause overestimated winds in model simulations. The overestimation was larger in stable conditions than in unstable conditions, indicating that the weak diurnal cycle in the model could be attributed to the representation error.

An automatic and effective parameter optimization method for model tuning

NASA Astrophysics Data System (ADS)

Zhang, T.; Li, L.; Lin, Y.; Xue, W.; Xie, F.; Xu, H.; Huang, X.

2015-05-01

Physical parameterizations in General Circulation Models (GCMs), having various uncertain parameters, greatly impact model performance and model climate sensitivity. Traditional manual and empirical tuning of these parameters is time consuming and ineffective. In this study, a "three-step" methodology is proposed to automatically and effectively obtain the optimum combination of some key parameters in cloud and convective parameterizations according to a comprehensive objective evaluation metrics. Different from the traditional optimization methods, two extra steps, one determines parameter sensitivity and the other chooses the optimum initial value of sensitive parameters, are introduced before the downhill simplex method to reduce the computational cost and improve the tuning performance. Atmospheric GCM simulation results show that the optimum combination of these parameters determined using this method is able to improve the model's overall performance by 9%. The proposed methodology and software framework can be easily applied to other GCMs to speed up the model development process, especially regarding unavoidable comprehensive parameters tuning during the model development stage.

Data error and highly parameterized groundwater models

USGS Publications Warehouse

Hill, M.C.

2008-01-01

Strengths and weaknesses of highly parameterized models, in which the number of parameters exceeds the number of observations, are demonstrated using a synthetic test case. Results suggest that the approach can yield close matches to observations but also serious errors in system representation. It is proposed that avoiding the difficulties of highly parameterized models requires close evaluation of: (1) model fit, (2) performance of the regression, and (3) estimated parameter distributions. Comparisons to hydrogeologic information are expected to be critical to obtaining credible models. Copyright ?? 2008 IAHS Press.

Evaluating and Improving Wind Forecasts over South China: The Role of Orographic Parameterization in the GRAPES Model

NASA Astrophysics Data System (ADS)

Zhong, Shuixin; Chen, Zitong; Xu, Daosheng; Zhang, Yanxia

2018-06-01

Unresolved small-scale orographic (SSO) drags are parameterized in a regional model based on the Global/Regional Assimilation and Prediction System for the Tropical Mesoscale Model (GRAPES TMM). The SSO drags are represented by adding a sink term in the momentum equations. The maximum height of the mountain within the grid box is adopted in the SSO parameterization (SSOP) scheme as compensation for the drag. The effects of the unresolved topography are parameterized as the feedbacks to the momentum tendencies on the first model level in planetary boundary layer (PBL) parameterization. The SSOP scheme has been implemented and coupled with the PBL parameterization scheme within the model physics package. A monthly simulation is designed to examine the performance of the SSOP scheme over the complex terrain areas located in the southwest of Guangdong. The verification results show that the surface wind speed bias has been much alleviated by adopting the SSOP scheme, in addition to reduction of the wind bias in the lower troposphere. The target verification over Xinyi shows that the simulations with the SSOP scheme provide improved wind estimation over the complex regions in the southwest of Guangdong.

Limitations in estimating phosphorus sorption capacity from soil properties

USDA-ARS?s Scientific Manuscript database

An important component of all P loss models is how P cycling in soils is described. The P cycling routines in most models are based on the routines developed for the EPIC model over 30 years ago. EPIC was developed so that it could be parameterized with easily obtainable soil data and thus, by neces...

Parameterizing the Morse Potential for Coarse-Grained Modeling of Blood Plasma

PubMed Central

Zhang, Na; Zhang, Peng; Kang, Wei; Bluestein, Danny; Deng, Yuefan

2014-01-01

Multiscale simulations of fluids such as blood represent a major computational challenge of coupling the disparate spatiotemporal scales between molecular and macroscopic transport phenomena characterizing such complex fluids. In this paper, a coarse-grained (CG) particle model is developed for simulating blood flow by modifying the Morse potential, traditionally used in Molecular Dynamics for modeling vibrating structures. The modified Morse potential is parameterized with effective mass scales for reproducing blood viscous flow properties, including density, pressure, viscosity, compressibility and characteristic flow dynamics of human blood plasma fluid. The parameterization follows a standard inverse-problem approach in which the optimal micro parameters are systematically searched, by gradually decoupling loosely correlated parameter spaces, to match the macro physical quantities of viscous blood flow. The predictions of this particle based multiscale model compare favorably to classic viscous flow solutions such as Counter-Poiseuille and Couette flows. It demonstrates that such coarse grained particle model can be applied to replicate the dynamics of viscous blood flow, with the advantage of bridging the gap between macroscopic flow scales and the cellular scales characterizing blood flow that continuum based models fail to handle adequately. PMID:24910470

Balancing accuracy, efficiency, and flexibility in a radiative transfer parameterization for dynamical models

NASA Astrophysics Data System (ADS)

Pincus, R.; Mlawer, E. J.

2017-12-01

Radiation is key process in numerical models of the atmosphere. The problem is well-understood and the parameterization of radiation has seen relatively few conceptual advances in the past 15 years. It is nonthelss often the single most expensive component of all physical parameterizations despite being computed less frequently than other terms. This combination of cost and maturity suggests value in a single radiation parameterization that could be shared across models; devoting effort to a single parameterization might allow for fine tuning for efficiency. The challenge lies in the coupling of this parameterization to many disparate representations of clouds and aerosols. This talk will describe RRTMGP, a new radiation parameterization that seeks to balance efficiency and flexibility. This balance is struck by isolating computational tasks in "kernels" that expose as much fine-grained parallelism as possible. These have simple interfaces and are interoperable across programming languages so that they might be repalced by alternative implementations in domain-specific langauges. Coupling to the host model makes use of object-oriented features of Fortran 2003, minimizing branching within the kernels and the amount of data that must be transferred. We will show accuracy and efficiency results for a globally-representative set of atmospheric profiles using a relatively high-resolution spectral discretization.

Collaborative Project. 3D Radiative Transfer Parameterization Over Mountains/Snow for High-Resolution Climate Models. Fast physics and Applications

DOE Office of Scientific and Technical Information (OSTI.GOV)

Liou, Kuo-Nan

2016-02-09

Under the support of the aforementioned DOE Grant, we have made two fundamental contributions to atmospheric and climate sciences: (1) Develop an efficient 3-D radiative transfer parameterization for application to intense and intricate inhomogeneous mountain/snow regions. (2) Innovate a stochastic parameterization for light absorption by internally mixed black carbon and dust particles in snow grains for understanding and physical insight into snow albedo reduction in climate models. With reference to item (1), we divided solar fluxes reaching mountain surfaces into five components: direct and diffuse fluxes, direct- and diffuse-reflected fluxes, and coupled mountain-mountain flux. “Exact” 3D Monte Carlo photon tracingmore » computations can then be performed for these solar flux components to compare with those calculated from the conventional plane-parallel (PP) radiative transfer program readily available in climate models. Subsequently, Parameterizations of the deviations of 3D from PP results for five flux components are carried out by means of the multiple linear regression analysis associated with topographic information, including elevation, solar incident angle, sky view factor, and terrain configuration factor. We derived five regression equations with high statistical correlations for flux deviations and successfully incorporated this efficient parameterization into WRF model, which was used as the testbed in connection with the Fu-Liou-Gu PP radiation scheme that has been included in the WRF physics package. Incorporating this 3D parameterization program, we conducted simulations of WRF and CCSM4 to understand and evaluate the mountain/snow effect on snow albedo reduction during seasonal transition and the interannual variability for snowmelt, cloud cover, and precipitation over the Western United States presented in the final report. With reference to item (2), we developed in our previous research a geometric-optics surface-wave approach (GOS) for the computation of light absorption and scattering by complex and inhomogeneous particles for application to aggregates and snow grains with external and internal mixing structures. We demonstrated that a small black (BC) particle on the order of 1 μm internally mixed with snow grains could effectively reduce visible snow albedo by as much as 5–10%. Following this work and within the context of DOE support, we have made two key accomplishments presented in the attached final report.« less

Radiative flux and forcing parameterization error in aerosol-free clear skies

DOE PAGES

Pincus, Robert; Mlawer, Eli J.; Oreopoulos, Lazaros; ...

2015-07-03

This article reports on the accuracy in aerosol- and cloud-free conditions of the radiation parameterizations used in climate models. Accuracy is assessed relative to observationally validated reference models for fluxes under present-day conditions and forcing (flux changes) from quadrupled concentrations of carbon dioxide. Agreement among reference models is typically within 1 W/m 2, while parameterized calculations are roughly half as accurate in the longwave and even less accurate, and more variable, in the shortwave. Absorption of shortwave radiation is underestimated by most parameterizations in the present day and has relatively large errors in forcing. Error in present-day conditions is essentiallymore » unrelated to error in forcing calculations. Recent revisions to parameterizations have reduced error in most cases. As a result, a dependence on atmospheric conditions, including integrated water vapor, means that global estimates of parameterization error relevant for the radiative forcing of climate change will require much more ambitious calculations.« less

Multisite Evaluation of APEX for Water Quality: II. Regional Parameterization.

PubMed

Nelson, Nathan O; Baffaut, Claire; Lory, John A; Anomaa Senaviratne, G M M M; Bhandari, Ammar B; Udawatta, Ranjith P; Sweeney, Daniel W; Helmers, Matt J; Van Liew, Mike W; Mallarino, Antonio P; Wortmann, Charles S

2017-11-01

Phosphorus (P) Index assessment requires independent estimates of long-term average annual P loss from fields, representing multiple climatic scenarios, management practices, and landscape positions. Because currently available measured data are insufficient to evaluate P Index performance, calibrated and validated process-based models have been proposed as tools to generate the required data. The objectives of this research were to develop a regional parameterization for the Agricultural Policy Environmental eXtender (APEX) model to estimate edge-of-field runoff, sediment, and P losses in restricted-layer soils of Missouri and Kansas and to assess the performance of this parameterization using monitoring data from multiple sites in this region. Five site-specific calibrated models (SSCM) from within the region were used to develop a regionally calibrated model (RCM), which was further calibrated and validated with measured data. Performance of the RCM was similar to that of the SSCMs for runoff simulation and had Nash-Sutcliffe efficiency (NSE) > 0.72 and absolute percent bias (|PBIAS|) < 18% for both calibration and validation. The RCM could not simulate sediment loss (NSE < 0, |PBIAS| > 90%) and was particularly ineffective at simulating sediment loss from locations with small sediment loads. The RCM had acceptable performance for simulation of total P loss (NSE > 0.74, |PBIAS| < 30%) but underperformed the SSCMs. Total P-loss estimates should be used with caution due to poor simulation of sediment loss. Although we did not attain our goal of a robust regional parameterization of APEX for estimating sediment and total P losses, runoff estimates with the RCM were acceptable for P Index evaluation. Copyright © by the American Society of Agronomy, Crop Science Society of America, and Soil Science Society of America, Inc.

A unified view of convective transports by stratocumulus clouds, shallow cumulus clouds, and deep convection

NASA Technical Reports Server (NTRS)

Randall, David A.

1990-01-01

A bulk planetary boundary layer (PBL) model was developed with a simple internal vertical structure and a simple second-order closure, designed for use as a PBL parameterization in a large-scale model. The model allows the mean fields to vary with height within the PBL, and so must address the vertical profiles of the turbulent fluxes, going beyond the usual mixed-layer assumption that the fluxes of conservative variables are linear with height. This is accomplished using the same convective mass flux approach that has also been used in cumulus parameterizations. The purpose is to show that such a mass flux model can include, in a single framework, the compensating subsidence concept, downgradient mixing, and well-mixed layers.

Global model comparison of heterogeneous ice nucleation parameterizations in mixed phase clouds

NASA Astrophysics Data System (ADS)

Yun, Yuxing; Penner, Joyce E.

2012-04-01

A new aerosol-dependent mixed phase cloud parameterization for deposition/condensation/immersion (DCI) ice nucleation and one for contact freezing are compared to the original formulations in a coupled general circulation model and aerosol transport model. The present-day cloud liquid and ice water fields and cloud radiative forcing are analyzed and compared to observations. The new DCI freezing parameterization changes the spatial distribution of the cloud water field. Significant changes are found in the cloud ice water fraction and in the middle cloud fractions. The new DCI freezing parameterization predicts less ice water path (IWP) than the original formulation, especially in the Southern Hemisphere. The smaller IWP leads to a less efficient Bergeron-Findeisen process resulting in a larger liquid water path, shortwave cloud forcing, and longwave cloud forcing. It is found that contact freezing parameterizations have a greater impact on the cloud water field and radiative forcing than the two DCI freezing parameterizations that we compared. The net solar flux at top of atmosphere and net longwave flux at the top of the atmosphere change by up to 8.73 and 3.52 W m-2, respectively, due to the use of different DCI and contact freezing parameterizations in mixed phase clouds. The total climate forcing from anthropogenic black carbon/organic matter in mixed phase clouds is estimated to be 0.16-0.93 W m-2using the aerosol-dependent parameterizations. A sensitivity test with contact ice nuclei concentration in the original parameterization fit to that recommended by Young (1974) gives results that are closer to the new contact freezing parameterization.

Sensitivity of Glacier Mass Balance Estimates to the Selection of WRF Cloud Microphysics Parameterization in the Indus River Watershed

NASA Astrophysics Data System (ADS)

Johnson, E. S.; Rupper, S.; Steenburgh, W. J.; Strong, C.; Kochanski, A.

2017-12-01

Climate model outputs are often used as inputs to glacier energy and mass balance models, which are essential glaciological tools for testing glacier sensitivity, providing mass balance estimates in regions with little glaciological data, and providing a means to model future changes. Climate model outputs, however, are sensitive to the choice of physical parameterizations, such as those for cloud microphysics, land-surface schemes, surface layer options, etc. Furthermore, glacier mass balance (MB) estimates that use these climate model outputs as inputs are likely sensitive to the specific parameterization schemes, but this sensitivity has not been carefully assessed. Here we evaluate the sensitivity of glacier MB estimates across the Indus Basin to the selection of cloud microphysics parameterizations in the Weather Research and Forecasting Model (WRF). Cloud microphysics parameterizations differ in how they specify the size distributions of hydrometeors, the rate of graupel and snow production, their fall speed assumptions, the rates at which they convert from one hydrometeor type to the other, etc. While glacier MB estimates are likely sensitive to other parameterizations in WRF, our preliminary results suggest that glacier MB is highly sensitive to the timing, frequency, and amount of snowfall, which is influenced by the cloud microphysics parameterization. To this end, the Indus Basin is an ideal study site, as it has both westerly (winter) and monsoonal (summer) precipitation influences, is a data-sparse region (so models are critical), and still has lingering questions as to glacier importance for local and regional resources. WRF is run at a 4 km grid scale using two commonly used parameterizations: the Thompson scheme and the Goddard scheme. On average, these parameterizations result in minimal differences in annual precipitation. However, localized regions exhibit differences in precipitation of up to 3 m w.e. a-1. The different schemes also impact the radiative budgets over the glacierized areas. Our results show that glacier MB estimates can differ by up to 45% depending on the chosen cloud microphysics scheme. These findings highlight the need to better account for uncertainties in meteorological inputs into glacier energy and mass balance models.

Final Technical Report for "High-resolution global modeling of the effects of subgrid-scale clouds and turbulence on precipitating cloud systems"

DOE Office of Scientific and Technical Information (OSTI.GOV)

Larson, Vincent

2016-11-25

The Multiscale Modeling Framework (MMF) embeds a cloud-resolving model in each grid column of a General Circulation Model (GCM). A MMF model does not need to use a deep convective parameterization, and thereby dispenses with the uncertainties in such parameterizations. However, MMF models grossly under-resolve shallow boundary-layer clouds, and hence those clouds may still benefit from parameterization. In this grant, we successfully created a climate model that embeds a cloud parameterization (“CLUBB”) within a MMF model. This involved interfacing CLUBB’s clouds with microphysics and reducing computational cost. We have evaluated the resulting simulated clouds and precipitation with satellite observations. Themore » chief benefit of the project is to provide a MMF model that has an improved representation of clouds and that provides improved simulations of precipitation.« less

ALAMEDA, a Structural–Functional Model for Faba Bean Crops: Morphological Parameterization and Verification

PubMed Central

RUIZ-RAMOS, MARGARITA; MÍNGUEZ, M. INÉS

2006-01-01

• Background Plant structural (i.e. architectural) models explicitly describe plant morphology by providing detailed descriptions of the display of leaf and stem surfaces within heterogeneous canopies and thus provide the opportunity for modelling the functioning of plant organs in their microenvironments. The outcome is a class of structural–functional crop models that combines advantages of current structural and process approaches to crop modelling. ALAMEDA is such a model. • Methods The formalism of Lindenmayer systems (L-systems) was chosen for the development of a structural model of the faba bean canopy, providing both numerical and dynamic graphical outputs. It was parameterized according to the results obtained through detailed morphological and phenological descriptions that capture the detailed geometry and topology of the crop. The analysis distinguishes between relationships of general application for all sowing dates and stem ranks and others valid only for all stems of a single crop cycle. • Results and Conclusions The results reveal that in faba bean, structural parameterization valid for the entire plant may be drawn from a single stem. ALAMEDA was formed by linking the structural model to the growth model ‘Simulation d'Allongement des Feuilles’ (SAF) with the ability to simulate approx. 3500 crop organs and components of a group of nine plants. Model performance was verified for organ length, plant height and leaf area. The L-system formalism was able to capture the complex architecture of canopy leaf area of this indeterminate crop and, with the growth relationships, generate a 3D dynamic crop simulation. Future development and improvement of the model are discussed. PMID:16390842

A stepwise, multi-objective, multi-variable parameter optimization method for the APEX model

USDA-ARS?s Scientific Manuscript database

Proper parameterization enables hydrological models to make reliable estimates of non-point source pollution for effective control measures. The automatic calibration of hydrologic models requires significant computational power limiting its application. The study objective was to develop and eval...

Parameterizing deep convection using the assumed probability density function method

DOE PAGES

Storer, R. L.; Griffin, B. M.; Höft, J.; ...

2014-06-11

Due to their coarse horizontal resolution, present-day climate models must parameterize deep convection. This paper presents single-column simulations of deep convection using a probability density function (PDF) parameterization. The PDF parameterization predicts the PDF of subgrid variability of turbulence, clouds, and hydrometeors. That variability is interfaced to a prognostic microphysics scheme using a Monte Carlo sampling method. The PDF parameterization is used to simulate tropical deep convection, the transition from shallow to deep convection over land, and mid-latitude deep convection. These parameterized single-column simulations are compared with 3-D reference simulations. The agreement is satisfactory except when the convective forcing ismore » weak. The same PDF parameterization is also used to simulate shallow cumulus and stratocumulus layers. The PDF method is sufficiently general to adequately simulate these five deep, shallow, and stratiform cloud cases with a single equation set. This raises hopes that it may be possible in the future, with further refinements at coarse time step and grid spacing, to parameterize all cloud types in a large-scale model in a unified way.« less

Parameterizing deep convection using the assumed probability density function method

DOE Office of Scientific and Technical Information (OSTI.GOV)

Storer, R. L.; Griffin, B. M.; Höft, J.

2015-01-06

Due to their coarse horizontal resolution, present-day climate models must parameterize deep convection. This paper presents single-column simulations of deep convection using a probability density function (PDF) parameterization. The PDF parameterization predicts the PDF of subgrid variability of turbulence, clouds, and hydrometeors. That variability is interfaced to a prognostic microphysics scheme using a Monte Carlo sampling method.The PDF parameterization is used to simulate tropical deep convection, the transition from shallow to deep convection over land, and midlatitude deep convection. These parameterized single-column simulations are compared with 3-D reference simulations. The agreement is satisfactory except when the convective forcing is weak.more » The same PDF parameterization is also used to simulate shallow cumulus and stratocumulus layers. The PDF method is sufficiently general to adequately simulate these five deep, shallow, and stratiform cloud cases with a single equation set. This raises hopes that it may be possible in the future, with further refinements at coarse time step and grid spacing, to parameterize all cloud types in a large-scale model in a unified way.« less

Parameterizing deep convection using the assumed probability density function method

DOE Office of Scientific and Technical Information (OSTI.GOV)

Storer, R. L.; Griffin, B. M.; Hoft, Jan

2015-01-06

Due to their coarse horizontal resolution, present-day climate models must parameterize deep convection. This paper presents single-column simulations of deep convection using a probability density function (PDF) parameterization. The PDF parameterization predicts the PDF of subgrid variability of turbulence, clouds, and hydrometeors. That variability is interfaced to a prognostic microphysics scheme using a Monte Carlo sampling method.The PDF parameterization is used to simulate tropical deep convection, the transition from shallow to deep convection over land, and mid-latitude deep convection.These parameterized single-column simulations are compared with 3-D reference simulations. The agreement is satisfactory except when the convective forcing is weak. Themore » same PDF parameterization is also used to simulate shallow cumulus and stratocumulus layers. The PDF method is sufficiently general to adequately simulate these five deep, shallow, and stratiform cloud cases with a single equation set. This raises hopes that it may be possible in the future, with further refinements at coarse time step and grid spacing, to parameterize all cloud types in a large-scale model in a unified way.« less

A unified spectral,parameterization for wave breaking: from the deep ocean to the surf zone

NASA Astrophysics Data System (ADS)

Filipot, J.

2010-12-01

A new wave-breaking dissipation parameterization designed for spectral wave models is presented. It combines wave breaking basic physical quantities, namely, the breaking probability and the dissipation rate per unit area. The energy lost by waves is fi[|#12#|]rst calculated in the physical space before being distributed over the relevant spectral components. This parameterization allows a seamless numerical model from the deep ocean into the surf zone. This transition from deep to shallow water is made possible by a dissipation rate per unit area of breaking waves that varies with the wave height, wavelength and water depth.The parameterization is further tested in the WAVEWATCH III TM code, from the global ocean to the beach scale. Model errors are smaller than with most specialized deep or shallow water parameterizations.

A Goddard Multi-Scale Modeling System with Unified Physics

NASA Technical Reports Server (NTRS)

Tao, W.K.; Anderson, D.; Atlas, R.; Chern, J.; Houser, P.; Hou, A.; Lang, S.; Lau, W.; Peters-Lidard, C.; Kakar, R.;

DOE Office of Scientific and Technical Information (OSTI.GOV)

Kuechler, Erich R.; Department of Chemistry, University of Minnesota, Minneapolis, Minnesota 55455-0431; Giese, Timothy J.

To better represent the solvation effects observed along reaction pathways, and of ionic species in general, a charge-dependent variable-radii smooth conductor-like screening model (VR-SCOSMO) is developed. This model is implemented and parameterized with a third order density-functional tight binding quantum model, DFTB3/3OB-OPhyd, a quantum method which was developed for organic and biological compounds, utilizing a specific parameterization for phosphate hydrolysis reactions. Unlike most other applications with the DFTB3/3OB model, an auxiliary set of atomic multipoles is constructed from the underlying DFTB3 density matrix which is used to interact the solute with the solvent response surface. The resulting method is variational,more » produces smooth energies, and has analytic gradients. As a baseline, a conventional SCOSMO model with fixed radii is also parameterized. The SCOSMO and VR-SCOSMO models shown have comparable accuracy in reproducing neutral-molecule absolute solvation free energies; however, the VR-SCOSMO model is shown to reduce the mean unsigned errors (MUEs) of ionic compounds by half (about 2-3 kcal/mol). The VR-SCOSMO model presents similar accuracy as a charge-dependent Poisson-Boltzmann model introduced by Hou et al. [J. Chem. Theory Comput. 6, 2303 (2010)]. VR-SCOSMO is then used to examine the hydrolysis of trimethylphosphate and seven other phosphoryl transesterification reactions with different leaving groups. Two-dimensional energy landscapes are constructed for these reactions and calculated barriers are compared to those obtained from ab initio polarizable continuum calculations and experiment. Results of the VR-SCOSMO model are in good agreement in both cases, capturing the rate-limiting reaction barrier and the nature of the transition state.« less

A model to inform management actions as a response to chytridiomycosis-associated decline

USGS Publications Warehouse

Converse, Sarah J.; Bailey, Larissa L.; Mosher, Brittany A.; Funk, W. Chris; Gerber, Brian D.; Muths, Erin L.

2017-01-01

Decision-analytic models provide forecasts of how systems of interest will respond to management. These models can be parameterized using empirical data, but sometimes require information elicited from experts. When evaluating the effects of disease in species translocation programs, expert judgment is likely to play a role because complete empirical information will rarely be available. We illustrate development of a decision-analytic model built to inform decision-making regarding translocations and other management actions for the boreal toad (Anaxyrus boreas boreas), a species with declines linked to chytridiomycosis caused by Batrachochytrium dendrobatidis (Bd). Using the model, we explored the management implications of major uncertainties in this system, including whether there is a genetic basis for resistance to pathogenic infection by Bd, how translocation can best be implemented, and the effectiveness of efforts to reduce the spread of Bd. Our modeling exercise suggested that while selection for resistance to pathogenic infectionDecision-analytic models provide forecasts of how systems of interest will respond to management. These models can be parameterized using empirical data, but sometimes require information elicited from experts. When evaluating the effects of disease in species translocation programs, expert judgment is likely to play a role because complete empirical information will rarely be available. We illustrate development of a decision-analytic model built to inform decision-making regarding translocations and other management actions for the boreal toad (Anaxyrus boreas boreas), a species with declines linked to chytridiomycosis caused by Batrachochytrium dendrobatidis (Bd). Using the model, we explored the management implications of major uncertainties in this system, including whether there is a genetic basis for resistance to pathogenic infection by Bd, how translocation can best be implemented, and the effectiveness of efforts to reduce the spread of Bd. Our modeling exercise suggested that while selection for resistance to pathogenic infection by Bd could increase numbers of sites occupied by toads, and translocations could increase the rate of toad recovery, efforts to reduce the spread of Bd may have little effect. We emphasize the need to continue developing and parameterizing models necessary to assess management actions for combating chytridiomycosis-associated declines. by Bd could increase numbers of sites occupied by toads, and translocations could increase the rate of toad recovery, efforts to reduce the spread of Bd may have little effect. We emphasize the need to continue developing and parameterizing models necessary to assess management actions for combating chytridiomycosis-associated declines.

Parametric soil water retention models: a critical evaluation of expressions for the full moisture range

NASA Astrophysics Data System (ADS)

Madi, Raneem; Huibert de Rooij, Gerrit; Mielenz, Henrike; Mai, Juliane

2018-02-01

Few parametric expressions for the soil water retention curve are suitable for dry conditions. Furthermore, expressions for the soil hydraulic conductivity curves associated with parametric retention functions can behave unrealistically near saturation. We developed a general criterion for water retention parameterizations that ensures physically plausible conductivity curves. Only 3 of the 18 tested parameterizations met this criterion without restrictions on the parameters of a popular conductivity curve parameterization. A fourth required one parameter to be fixed. We estimated parameters by shuffled complex evolution (SCE) with the objective function tailored to various observation methods used to obtain retention curve data. We fitted the four parameterizations with physically plausible conductivities as well as the most widely used parameterization. The performance of the resulting 12 combinations of retention and conductivity curves was assessed in a numerical study with 751 days of semiarid atmospheric forcing applied to unvegetated, uniform, 1 m freely draining columns for four textures. Choosing different parameterizations had a minor effect on evaporation, but cumulative bottom fluxes varied by up to an order of magnitude between them. This highlights the need for a careful selection of the soil hydraulic parameterization that ideally does not only rely on goodness of fit to static soil water retention data but also on hydraulic conductivity measurements. Parameter fits for 21 soils showed that extrapolations into the dry range of the retention curve often became physically more realistic when the parameterization had a logarithmic dry branch, particularly in fine-textured soils where high residual water contents would otherwise be fitted.

Evaluation of CSM-CROPGRO-Cotton for simulating effects of management and climate change on cotton growth and evapotranspiration in an arid environment

USDA-ARS?s Scientific Manuscript database

Originally developed for simulating soybean growth and development, the CROPGRO model was recently re-parameterized for cotton. However, further efforts are necessary to evaluate the model's performance against field measurements for new environments and management options. The objective of this stu...

Uranium transport in a crushed granodiorite: Experiments and reactive transport modeling

DOE PAGES

Dittrich, T. M.; Reimus, P. W.

2015-02-12

The primary objective of this study was to develop and demonstrate an experimental method to refine and better parameterize process models for reactive contaminant transport in aqueous subsurface environments and to reduce conservatism in such models without attempting to fully describe the geochemical system.

The impact of overstory density on reproduction establishment in the Missouri Ozarks: models for simulating regeneration stochastically

Treesearch

Lance A. Vickers; David R. Larsen; Daniel C. Dey; Benjamin O. Knapp; John M. Kabrick

2017-01-01

Predicting the effects of silvicultural choices on regeneration has been difficult with the tools available to foresters. In an effort to improve this, we developed a collection of reproduction establishment models based on stand development hypotheses and parameterized with empirical data for several species in the Missouri Ozarks. These models estimate third-year...

Land-Atmosphere Coupling in the Multi-Scale Modelling Framework

NASA Astrophysics Data System (ADS)

Kraus, P. M.; Denning, S.

2015-12-01

The Multi-Scale Modeling Framework (MMF), in which cloud-resolving models (CRMs) are embedded within general circulation model (GCM) gridcells to serve as the model's cloud parameterization, has offered a number of benefits to GCM simulations. The coupling of these cloud-resolving models directly to land surface model instances, rather than passing averaged atmospheric variables to a single instance of a land surface model, the logical next step in model development, has recently been accomplished. This new configuration offers conspicuous improvements to estimates of precipitation and canopy through-fall, but overall the model exhibits warm surface temperature biases and low productivity.This work presents modifications to a land-surface model that take advantage of the new multi-scale modeling framework, and accommodate the change in spatial scale from a typical GCM range of ~200 km to the CRM grid-scale of 4 km.A parameterization is introduced to apportion modeled surface radiation into direct-beam and diffuse components. The diffuse component is then distributed among the land-surface model instances within each GCM cell domain. This substantially reduces the number excessively low light values provided to the land-surface model when cloudy conditions are modeled in the CRM, associated with its 1-D radiation scheme. The small spatial scale of the CRM, ~4 km, as compared with the typical ~200 km GCM scale, provides much more realistic estimates of precipitation intensity, this permits the elimination of a model parameterization of canopy through-fall. However, runoff at such scales can no longer be considered as an immediate flow to the ocean. Allowing sub-surface water flow between land-surface instances within the GCM domain affords better realism and also reduces temperature and productivity biases.The MMF affords a number of opportunities to land-surface modelers, providing both the advantages of direct simulation at the 4 km scale and a much reduced conceptual gap between model resolution and parameterized processes.

Prediction of convective activity using a system of parasitic-nested numerical models

NASA Technical Reports Server (NTRS)

Perkey, D. J.

1976-01-01

A limited area, three dimensional, moist, primitive equation (PE) model is developed to test the sensitivity of quantitative precipitation forecasts to the initial relative humidity distribution. Special emphasis is placed on the squall-line region. To accomplish the desired goal, time dependent lateral boundaries and a general convective parameterization scheme suitable for mid-latitude systems were developed. The sequential plume convective parameterization scheme presented is designed to have the versatility necessary in mid-latitudes and to be applicable for short-range forecasts. The results indicate that the scheme is able to function in the frontally forced squallline region, in the gently rising altostratus region ahead of the approaching low center, and in the over-riding region ahead of the warm front. Three experiments are discussed.

GEWEX Cloud Systems Study (GCSS)

NASA Technical Reports Server (NTRS)

Moncrieff, Mitch

1993-01-01

The Global Energy and Water Cycle Experiment (GEWEX) Cloud Systems Study (GCSS) program seeks to improve the physical understanding of sub-grid scale cloud processes and their representation in parameterization schemes. By improving the description and understanding of key cloud system processes, GCSS aims to develop the necessary parameterizations in climate and numerical weather prediction (NWP) models. GCSS will address these issues mainly through the development and use of cloud-resolving or cumulus ensemble models to generate realizations of a set of archetypal cloud systems. The focus of GCSS is on mesoscale cloud systems, including precipitating convectively-driven cloud systems like MCS's and boundary layer clouds, rather than individual clouds, and on their large-scale effects. Some of the key scientific issues confronting GCSS that particularly relate to research activities in the central U.S. are presented.

Performance assessment and parameterization of the SWAP-WOFOST model for peat soil under agricultural use in northern Europe.

NASA Astrophysics Data System (ADS)

Bertram, Sascha; Bechtold, Michel; Hendriks, Rob; Piayda, Arndt; Regina, Kristiina; Myllys, Merja; Tiemeyer, Bärbel

2017-04-01

Peat soils form a major share of soil suitable for agriculture in northern Europe. Successful agricultural production depends on hydrological and pedological conditions, local climate and agricultural management. Climate change impact assessment on food production and development of mitigation and adaptation strategies require reliable yield forecasts under given emission scenarios. Coupled soil hydrology - crop growth models, driven by regionalized future climate scenarios are a valuable tool and widely used for this purpose. Parameterization on local peat soil conditions and crop breed or grassland specie performance, however, remains a major challenge. The subject of this study is to evaluate the performance and sensitivity of the SWAP-WOFOST coupled soil hydrology and plant growth model with respect to the application on peat soils under different regional conditions across northern Europe. Further, the parameterization of region-specific crop and grass species is discussed. First results of the model application and parameterization at deep peat sites in southern Finland are presented. The model performed very well in reproducing two years of observed, daily ground water level data on four hydrologically contrasting sites. Naturally dry and wet sites could be modelled with the same performance as sites with active water table management by regulated drains in order to improve peat conservation. A simultaneous multi-site calibration scheme was used to estimate plant growth parameters of the local oat breed. Cross-site validation of the modelled yields against two years of observations proved the robustness of the chosen parameter set and gave no indication of possible overparameterization. This study proves the suitability of the coupled SWAP-WOFOST model for the prediction of crop yields and water table dynamics of peat soils in agricultural use under given climate conditions.

Explicit simulation of a midlatitude Mesoscale Convective System

DOE Office of Scientific and Technical Information (OSTI.GOV)

Alexander, G.D.; Cotton, W.R.

1996-04-01

We have explicitly simulated the mesoscale convective system (MCS) observed on 23-24 June 1985 during PRE-STORM, the Preliminary Regional Experiment for the Stormscale Operational and Research and Meterology Program. Stensrud and Maddox (1988), Johnson and Bartels (1992), and Bernstein and Johnson (1994) are among the researchers who have investigated various aspects of this MCS event. We have performed this MCS simulation (and a similar one of a tropical MCS; Alexander and Cotton 1994) in the spirit of the Global Energy and Water Cycle Experiment Cloud Systems Study (GCSS), in which cloud-resolving models are used to assist in the formulation andmore » testing of cloud parameterization schemes for larger-scale models. In this paper, we describe (1) the nature of our 23-24 June MCS dimulation and (2) our efforts to date in using our explicit MCS simulations to assist in the development of a GCM parameterization for mesoscale flow branches. The paper is organized as follows. First, we discuss the synoptic situation surrounding the 23-24 June PRE-STORM MCS followed by a discussion of the model setup and results of our simulation. We then discuss the use of our MCS simulation. We then discuss the use of our MCS simulations in developing a GCM parameterization for mesoscale flow branches and summarize our results.« less

How to assess the impact of a physical parameterization in simulations of moist convection?

NASA Astrophysics Data System (ADS)

Grabowski, Wojciech

2017-04-01

A numerical model capable in simulating moist convection (e.g., cloud-resolving model or large-eddy simulation model) consists of a fluid flow solver combined with required representations (i.e., parameterizations) of physical processes. The later typically include cloud microphysics, radiative transfer, and unresolved turbulent transport. Traditional approaches to investigate impacts of such parameterizations on convective dynamics involve parallel simulations with different parameterization schemes or with different scheme parameters. Such methodologies are not reliable because of the natural variability of a cloud field that is affected by the feedback between the physics and dynamics. For instance, changing the cloud microphysics typically leads to a different realization of the cloud-scale flow, and separating dynamical and microphysical impacts is difficult. This presentation will present a novel modeling methodology, the piggybacking, that allows studying the impact of a physical parameterization on cloud dynamics with confidence. The focus will be on the impact of cloud microphysics parameterization. Specific examples of the piggybacking approach will include simulations concerning the hypothesized deep convection invigoration in polluted environments, the validity of the saturation adjustment in modeling condensation in moist convection, and separation of physical impacts from statistical uncertainty in simulations applying particle-based Lagrangian microphysics, the super-droplet method.

Creating wavelet-based models for real-time synthesis of perceptually convincing environmental sounds

NASA Astrophysics Data System (ADS)

Miner, Nadine Elizabeth

1998-09-01

This dissertation presents a new wavelet-based method for synthesizing perceptually convincing, dynamic sounds using parameterized sound models. The sound synthesis method is applicable to a variety of applications including Virtual Reality (VR), multi-media, entertainment, and the World Wide Web (WWW). A unique contribution of this research is the modeling of the stochastic, or non-pitched, sound components. This stochastic-based modeling approach leads to perceptually compelling sound synthesis. Two preliminary studies conducted provide data on multi-sensory interaction and audio-visual synchronization timing. These results contributed to the design of the new sound synthesis method. The method uses a four-phase development process, including analysis, parameterization, synthesis and validation, to create the wavelet-based sound models. A patent is pending for this dynamic sound synthesis method, which provides perceptually-realistic, real-time sound generation. This dissertation also presents a battery of perceptual experiments developed to verify the sound synthesis results. These experiments are applicable for validation of any sound synthesis technique.

Efficient statistical mapping of avian count data

USGS Publications Warehouse

Royle, J. Andrew; Wikle, C.K.

2005-01-01

We develop a spatial modeling framework for count data that is efficient to implement in high-dimensional prediction problems. We consider spectral parameterizations for the spatially varying mean of a Poisson model. The spectral parameterization of the spatial process is very computationally efficient, enabling effective estimation and prediction in large problems using Markov chain Monte Carlo techniques. We apply this model to creating avian relative abundance maps from North American Breeding Bird Survey (BBS) data. Variation in the ability of observers to count birds is modeled as spatially independent noise, resulting in over-dispersion relative to the Poisson assumption. This approach represents an improvement over existing approaches used for spatial modeling of BBS data which are either inefficient for continental scale modeling and prediction or fail to accommodate important distributional features of count data thus leading to inaccurate accounting of prediction uncertainty.

Impact of Physics Parameterization Ordering in a Global Atmosphere Model

DOE PAGES

Donahue, Aaron S.; Caldwell, Peter M.

2018-02-02

Because weather and climate models must capture a wide variety of spatial and temporal scales, they rely heavily on parameterizations of subgrid-scale processes. The goal of this study is to demonstrate that the assumptions used to couple these parameterizations have an important effect on the climate of version 0 of the Energy Exascale Earth System Model (E3SM) General Circulation Model (GCM), a close relative of version 1 of the Community Earth System Model (CESM1). Like most GCMs, parameterizations in E3SM are sequentially split in the sense that parameterizations are called one after another with each subsequent process feeling the effectmore » of the preceding processes. This coupling strategy is noncommutative in the sense that the order in which processes are called impacts the solution. By examining a suite of 24 simulations with deep convection, shallow convection, macrophysics/microphysics, and radiation parameterizations reordered, process order is shown to have a big impact on predicted climate. In particular, reordering of processes induces differences in net climate feedback that are as big as the intermodel spread in phase 5 of the Coupled Model Intercomparison Project. One reason why process ordering has such a large impact is that the effect of each process is influenced by the processes preceding it. Where output is written is therefore an important control on apparent model behavior. Application of k-means clustering demonstrates that the positioning of macro/microphysics and shallow convection plays a critical role on the model solution.« less

Impact of Physics Parameterization Ordering in a Global Atmosphere Model

NASA Astrophysics Data System (ADS)

Donahue, Aaron S.; Caldwell, Peter M.

2018-02-01

Because weather and climate models must capture a wide variety of spatial and temporal scales, they rely heavily on parameterizations of subgrid-scale processes. The goal of this study is to demonstrate that the assumptions used to couple these parameterizations have an important effect on the climate of version 0 of the Energy Exascale Earth System Model (E3SM) General Circulation Model (GCM), a close relative of version 1 of the Community Earth System Model (CESM1). Like most GCMs, parameterizations in E3SM are sequentially split in the sense that parameterizations are called one after another with each subsequent process feeling the effect of the preceding processes. This coupling strategy is noncommutative in the sense that the order in which processes are called impacts the solution. By examining a suite of 24 simulations with deep convection, shallow convection, macrophysics/microphysics, and radiation parameterizations reordered, process order is shown to have a big impact on predicted climate. In particular, reordering of processes induces differences in net climate feedback that are as big as the intermodel spread in phase 5 of the Coupled Model Intercomparison Project. One reason why process ordering has such a large impact is that the effect of each process is influenced by the processes preceding it. Where output is written is therefore an important control on apparent model behavior. Application of k-means clustering demonstrates that the positioning of macro/microphysics and shallow convection plays a critical role on the model solution.

Impact of Physics Parameterization Ordering in a Global Atmosphere Model

DOE Office of Scientific and Technical Information (OSTI.GOV)

Donahue, Aaron S.; Caldwell, Peter M.

Because weather and climate models must capture a wide variety of spatial and temporal scales, they rely heavily on parameterizations of subgrid-scale processes. The goal of this study is to demonstrate that the assumptions used to couple these parameterizations have an important effect on the climate of version 0 of the Energy Exascale Earth System Model (E3SM) General Circulation Model (GCM), a close relative of version 1 of the Community Earth System Model (CESM1). Like most GCMs, parameterizations in E3SM are sequentially split in the sense that parameterizations are called one after another with each subsequent process feeling the effectmore » of the preceding processes. This coupling strategy is noncommutative in the sense that the order in which processes are called impacts the solution. By examining a suite of 24 simulations with deep convection, shallow convection, macrophysics/microphysics, and radiation parameterizations reordered, process order is shown to have a big impact on predicted climate. In particular, reordering of processes induces differences in net climate feedback that are as big as the intermodel spread in phase 5 of the Coupled Model Intercomparison Project. One reason why process ordering has such a large impact is that the effect of each process is influenced by the processes preceding it. Where output is written is therefore an important control on apparent model behavior. Application of k-means clustering demonstrates that the positioning of macro/microphysics and shallow convection plays a critical role on the model solution.« less

Enhanced representation of soil NO emissions in the ...

EPA Pesticide Factsheets

Modeling of soil nitric oxide (NO) emissions is highly uncertain and may misrepresent its spatial and temporal distribution. This study builds upon a recently introduced parameterization to improve the timing and spatial distribution of soil NO emission estimates in the Community Multiscale Air Quality (CMAQ) model. The parameterization considers soil parameters, meteorology, land use, and mineral nitrogen (N) availability to estimate NO emissions. We incorporate daily year-specific fertilizer data from the Environmental Policy Integrated Climate (EPIC) agricultural model to replace the annual generic data of the initial parameterization, and use a 12 km resolution soil biome map over the continental USA. CMAQ modeling for July 2011 shows slight differences in model performance in simulating fine particulate matter and ozone from Interagency Monitoring of Protected Visual Environments (IMPROVE) and Clean Air Status and Trends Network (CASTNET) sites and NO2 columns from Ozone Monitoring Instrument (OMI) satellite retrievals. We also simulate how the change in soil NO emissions scheme affects the expected O3 response to projected emissions reductions. The National Exposure Research Laboratory (NERL) Computational Exposure Division (CED) develops and evaluates data, decision-support tools, and models to be applied to media-specific or receptor-specific problem areas. CED uses modeling-based approaches to characterize exposures, evaluate fate and transport, and

Statistical properties of the normalized ice particle size distribution

NASA Astrophysics Data System (ADS)

Delanoë, Julien; Protat, Alain; Testud, Jacques; Bouniol, Dominique; Heymsfield, A. J.; Bansemer, A.; Brown, P. R. A.; Forbes, R. M.

2005-05-01

Testud et al. (2001) have recently developed a formalism, known as the "normalized particle size distribution (PSD)", which consists in scaling the diameter and concentration axes in such a way that the normalized PSDs are independent of water content and mean volume-weighted diameter. In this paper we investigate the statistical properties of the normalized PSD for the particular case of ice clouds, which are known to play a crucial role in the Earth's radiation balance. To do so, an extensive database of airborne in situ microphysical measurements has been constructed. A remarkable stability in shape of the normalized PSD is obtained. The impact of using a single analytical shape to represent all PSDs in the database is estimated through an error analysis on the instrumental (radar reflectivity and attenuation) and cloud (ice water content, effective radius, terminal fall velocity of ice crystals, visible extinction) properties. This resulted in a roughly unbiased estimate of the instrumental and cloud parameters, with small standard deviations ranging from 5 to 12%. This error is found to be roughly independent of the temperature range. This stability in shape and its single analytical approximation implies that two parameters are now sufficient to describe any normalized PSD in ice clouds: the intercept parameter N*0 and the mean volume-weighted diameter Dm. Statistical relationships (parameterizations) between N*0 and Dm have then been evaluated in order to reduce again the number of unknowns. It has been shown that a parameterization of N*0 and Dm by temperature could not be envisaged to retrieve the cloud parameters. Nevertheless, Dm-T and mean maximum dimension diameter -T parameterizations have been derived and compared to the parameterization of Kristjánsson et al. (2000) currently used to characterize particle size in climate models. The new parameterization generally produces larger particle sizes at any temperature than the Kristjánsson et al. (2000) parameterization. These new parameterizations are believed to better represent particle size at global scale, owing to a better representativity of the in situ microphysical database used to derive it. We then evaluated the potential of a direct N*0-Dm relationship. While the model parameterized by temperature produces strong errors on the cloud parameters, the N*0-Dm model parameterized by radar reflectivity produces accurate cloud parameters (less than 3% bias and 16% standard deviation). This result implies that the cloud parameters can be estimated from the estimate of only one parameter of the normalized PSD (N*0 or Dm) and a radar reflectivity measurement.

Parameterized Linear Longitudinal Airship Model

NASA Technical Reports Server (NTRS)

Kulczycki, Eric; Elfes, Alberto; Bayard, David; Quadrelli, Marco; Johnson, Joseph

2010-01-01

A parameterized linear mathematical model of the longitudinal dynamics of an airship is undergoing development. This model is intended to be used in designing control systems for future airships that would operate in the atmospheres of Earth and remote planets. Heretofore, the development of linearized models of the longitudinal dynamics of airships has been costly in that it has been necessary to perform extensive flight testing and to use system-identification techniques to construct models that fit the flight-test data. The present model is a generic one that can be relatively easily specialized to approximate the dynamics of specific airships at specific operating points, without need for further system identification, and with significantly less flight testing. The approach taken in the present development is to merge the linearized dynamical equations of an airship with techniques for estimation of aircraft stability derivatives, and to thereby make it possible to construct a linearized dynamical model of the longitudinal dynamics of a specific airship from geometric and aerodynamic data pertaining to that airship. (It is also planned to develop a model of the lateral dynamics by use of the same methods.) All of the aerodynamic data needed to construct the model of a specific airship can be obtained from wind-tunnel testing and computational fluid dynamics

The Grell-Freitas Convective Parameterization: Recent Developments and Applications Within the NASA GEOS Global Model

NASA Astrophysics Data System (ADS)

Freitas, S.; Grell, G. A.; Molod, A.

2017-12-01

We implemented and began to evaluate an alternative convection parameterization for the NASA Goddard Earth Observing System (GEOS) global model. The parameterization (Grell and Freitas, 2014) is based on the mass flux approach with several closures, for equilibrium and non-equilibrium convection, and includes scale and aerosol awareness functionalities. Scale dependence for deep convection is implemented either through using the method described by Arakawa et al (2011), or through lateral spreading of the subsidence terms. Aerosol effects are included though the dependence of autoconversion and evaporation on the CCN number concentration.Recently, the scheme has been extended to a tri-modal spectral size approach to simulate the transition from shallow, congestus, and deep convection regimes. In addition, the inclusion of a new closure for non-equilibrium convection resulted in a substantial gain of realism in model simulation of the diurnal cycle of convection over the land. Also, a beta-pdf is employed now to represent the normalized mass flux profile. This opens up an additional venue to apply stochasticism in the scheme.

Improved Satellite-based Crop Yield Mapping by Spatially Explicit Parameterization of Crop Phenology

NASA Astrophysics Data System (ADS)

Jin, Z.; Azzari, G.; Lobell, D. B.

2016-12-01

Field-scale mapping of crop yields with satellite data often relies on the use of crop simulation models. However, these approaches can be hampered by inaccuracies in the simulation of crop phenology. Here we present and test an approach to use dense time series of Landsat 7 and 8 acquisitions data to calibrate various parameters related to crop phenology simulation, such as leaf number and leaf appearance rates. These parameters are then mapped across the Midwestern United States for maize and soybean, and for two different simulation models. We then implement our recently developed Scalable satellite-based Crop Yield Mapper (SCYM) with simulations reflecting the improved phenology parameterizations, and compare to prior estimates based on default phenology routines. Our preliminary results show that the proposed method can effectively alleviate the underestimation of early-season LAI by the default Agricultural Production Systems sIMulator (APSIM), and that spatially explicit parameterization for the phenology model substantially improves the SCYM performance in capturing the spatiotemporal variation in maize and soybean yield. The scheme presented in our study thus preserves the scalability of SCYM, while significantly reducing its uncertainty.

2D Affine and Projective Shape Analysis.

PubMed

Bryner, Darshan; Klassen, Eric; Huiling Le; Srivastava, Anuj

2014-05-01

Current techniques for shape analysis tend to seek invariance to similarity transformations (rotation, translation, and scale), but certain imaging situations require invariance to larger groups, such as affine or projective groups. Here we present a general Riemannian framework for shape analysis of planar objects where metrics and related quantities are invariant to affine and projective groups. Highlighting two possibilities for representing object boundaries-ordered points (or landmarks) and parameterized curves-we study different combinations of these representations (points and curves) and transformations (affine and projective). Specifically, we provide solutions to three out of four situations and develop algorithms for computing geodesics and intrinsic sample statistics, leading up to Gaussian-type statistical models, and classifying test shapes using such models learned from training data. In the case of parameterized curves, we also achieve the desired goal of invariance to re-parameterizations. The geodesics are constructed by particularizing the path-straightening algorithm to geometries of current manifolds and are used, in turn, to compute shape statistics and Gaussian-type shape models. We demonstrate these ideas using a number of examples from shape and activity recognition.

FastSim: A Fast Simulation for the SuperB Detector

NASA Astrophysics Data System (ADS)

Andreassen, R.; Arnaud, N.; Brown, D. N.; Burmistrov, L.; Carlson, J.; Cheng, C.-h.; Di Simone, A.; Gaponenko, I.; Manoni, E.; Perez, A.; Rama, M.; Roberts, D.; Rotondo, M.; Simi, G.; Sokoloff, M.; Suzuki, A.; Walsh, J.

2011-12-01

We have developed a parameterized (fast) simulation for detector optimization and physics reach studies of the proposed SuperB Flavor Factory in Italy. Detector components are modeled as thin sections of planes, cylinders, disks or cones. Particle-material interactions are modeled using simplified cross-sections and formulas. Active detectors are modeled using parameterized response functions. Geometry and response parameters are configured using xml files with a custom-designed schema. Reconstruction algorithms adapted from BaBar are used to build tracks and clusters. Multiple sources of background signals can be merged with primary signals. Pattern recognition errors are modeled statistically by randomly misassigning nearby tracking hits. Standard BaBar analysis tuples are used as an event output. Hadronic B meson pair events can be simulated at roughly 10Hz.

Performance Assessment of New Land-Surface and Planetary Boundary Layer Physics in the WRF-ARW

EPA Science Inventory

The Pleim-Xiu land surface model, Pleim surface layer scheme, and Asymmetric Convective Model (version 2) are now options in version 3.0 of the Weather Research and Forecasting model (WRF) Advanced Research WRF (ARW) core. These physics parameterizations were developed for the f...

Final Technical Report for "Reducing tropical precipitation biases in CESM"

DOE Office of Scientific and Technical Information (OSTI.GOV)

Larson, Vincent

In state-of-the-art climate models, each cloud type is treated using its own separate cloud parameterization and its own separate microphysics parameterization. This use of separate schemes for separate cloud regimes is undesirable because it is theoretically unfounded, it hampers interpretation of results, and it leads to the temptation to overtune parameters. In this grant, we have created a climate model that contains a unified cloud parameterization (“CLUBB”) and a unified microphysics parameterization (“MG2”). In this model, all cloud types --- including marine stratocumulus, shallow cumulus, and deep cumulus --- are represented with a single equation set. This model improves themore » representation of convection in the Tropics. The model has been compared with ARM observations. The chief benefit of the project is to provide a climate model that is based on a more theoretically rigorous formulation.« less

VR-SCOSMO: A smooth conductor-like screening model with charge-dependent radii for modeling chemical reactions.

PubMed

Kuechler, Erich R; Giese, Timothy J; York, Darrin M

2016-04-28

To better represent the solvation effects observed along reaction pathways, and of ionic species in general, a charge-dependent variable-radii smooth conductor-like screening model (VR-SCOSMO) is developed. This model is implemented and parameterized with a third order density-functional tight binding quantum model, DFTB3/3OB-OPhyd, a quantum method which was developed for organic and biological compounds, utilizing a specific parameterization for phosphate hydrolysis reactions. Unlike most other applications with the DFTB3/3OB model, an auxiliary set of atomic multipoles is constructed from the underlying DFTB3 density matrix which is used to interact the solute with the solvent response surface. The resulting method is variational, produces smooth energies, and has analytic gradients. As a baseline, a conventional SCOSMO model with fixed radii is also parameterized. The SCOSMO and VR-SCOSMO models shown have comparable accuracy in reproducing neutral-molecule absolute solvation free energies; however, the VR-SCOSMO model is shown to reduce the mean unsigned errors (MUEs) of ionic compounds by half (about 2-3 kcal/mol). The VR-SCOSMO model presents similar accuracy as a charge-dependent Poisson-Boltzmann model introduced by Hou et al. [J. Chem. Theory Comput. 6, 2303 (2010)]. VR-SCOSMO is then used to examine the hydrolysis of trimethylphosphate and seven other phosphoryl transesterification reactions with different leaving groups. Two-dimensional energy landscapes are constructed for these reactions and calculated barriers are compared to those obtained from ab initio polarizable continuum calculations and experiment. Results of the VR-SCOSMO model are in good agreement in both cases, capturing the rate-limiting reaction barrier and the nature of the transition state.

A framework for propagation of uncertainty contributed by parameterization, input data, model structure, and calibration/validation data in watershed modeling

USDA-ARS?s Scientific Manuscript database

The progressive improvement of computer science and development of auto-calibration techniques means that calibration of simulation models is no longer a major challenge for watershed planning and management. Modelers now increasingly focus on challenges such as improved representation of watershed...

An automatic and effective parameter optimization method for model tuning

NASA Astrophysics Data System (ADS)

Zhang, T.; Li, L.; Lin, Y.; Xue, W.; Xie, F.; Xu, H.; Huang, X.

2015-11-01

Physical parameterizations in general circulation models (GCMs), having various uncertain parameters, greatly impact model performance and model climate sensitivity. Traditional manual and empirical tuning of these parameters is time-consuming and ineffective. In this study, a "three-step" methodology is proposed to automatically and effectively obtain the optimum combination of some key parameters in cloud and convective parameterizations according to a comprehensive objective evaluation metrics. Different from the traditional optimization methods, two extra steps, one determining the model's sensitivity to the parameters and the other choosing the optimum initial value for those sensitive parameters, are introduced before the downhill simplex method. This new method reduces the number of parameters to be tuned and accelerates the convergence of the downhill simplex method. Atmospheric GCM simulation results show that the optimum combination of these parameters determined using this method is able to improve the model's overall performance by 9 %. The proposed methodology and software framework can be easily applied to other GCMs to speed up the model development process, especially regarding unavoidable comprehensive parameter tuning during the model development stage.

New Concepts for Refinement of Cumulus Parameterization in GCM's the Arakawa-Schubert Framework

NASA Technical Reports Server (NTRS)

Sud, Y. C.; Walker, G. K.; Lau, William (Technical Monitor)

2002-01-01

Several state-of-the-art models including the one employed in this study use the Arakawa-Schubert framework for moist convection, and Sundqvist formulation of stratiform. clouds, for moist physics, in-cloud condensation, and precipitation. Despite a variety of cloud parameterization methodologies developed by several modelers including the authors, most of the parameterized cloud-models have similar deficiencies. These consist of: (a) not enough shallow clouds, (b) too many deep clouds; (c) several layers of clouds in a vertically demoralized model as opposed to only a few levels of observed clouds, and (d) higher than normal incidence of double ITCZ (Inter-tropical Convergence Zone). Even after several upgrades consisting of a sophisticated cloud-microphysics and sub-grid scale orographic precipitation into the Data Assimilation Office (DAO)'s atmospheric model (called GEOS-2 GCM) at two different resolutions, we found that the above deficiencies remained persistent. The two empirical solutions often used to counter the aforestated deficiencies consist of a) diffusion of moisture and heat within the lower troposphere to artificially force the shallow clouds; and b) arbitrarily invoke evaporation of in-cloud water for low-level clouds. Even though helpful, these implementations lack a strong physical rationale. Our research shows that two missing physical conditions can ameliorate the aforestated cloud-parameterization deficiencies. First, requiring an ascending cloud airmass to be saturated at its starting point will not only make the cloud instantly buoyant all through its ascent, but also provide the essential work function (buoyancy energy) that would promote more shallow clouds. Second, we argue that training clouds that are unstable to a finite vertical displacement, even if neutrally buoyant in their ambient environment, must continue to rise and entrain causing evaporation of in-cloud water. These concepts have not been invoked in any of the cloud parameterization schemes so far. We introduced them into the DAO-GEOS-2 GCM with McRAS (Microphysics of Clouds with Relaxed Arakawa-Schubert Scheme).

A comprehensive parameterization of heterogeneous ice nucleation of dust surrogate: laboratory study with hematite particles and its application to atmospheric models

NASA Astrophysics Data System (ADS)

Hiranuma, N.; Paukert, M.; Steinke, I.; Zhang, K.; Kulkarni, G.; Hoose, C.; Schnaiter, M.; Saathoff, H.; Möhler, O.

2014-12-01

A new heterogeneous ice nucleation parameterization that covers a wide temperature range (-36 to -78 °C) is presented. Developing and testing such an ice nucleation parameterization, which is constrained through identical experimental conditions, is important to accurately simulate the ice nucleation processes in cirrus clouds. The ice nucleation active surface-site density (ns) of hematite particles, used as a proxy for atmospheric dust particles, were derived from AIDA (Aerosol Interaction and Dynamics in the Atmosphere) cloud chamber measurements under water subsaturated conditions. These conditions were achieved by continuously changing the temperature (T) and relative humidity with respect to ice (RHice) in the chamber. Our measurements showed several different pathways to nucleate ice depending on T and RHice conditions. For instance, almost T-independent freezing was observed at -60 °C < T < -50 °C, where RHice explicitly controlled ice nucleation efficiency, while both T and RHice played roles in other two T regimes: -78 °C < T < -60 °C and -50 °C < T < -36 °C. More specifically, observations at T lower than -60 °C revealed that higher RHice was necessary to maintain a constant ns, whereas T may have played a significant role in ice nucleation at T higher than -50 °C. We implemented the new hematite-derived ns parameterization, which agrees well with previous AIDA measurements of desert dust, into two conceptual cloud models to investigate their sensitivity to the new parameterization in comparison to existing ice nucleation schemes for simulating cirrus cloud properties. Our results show that the new AIDA-based parameterization leads to an order of magnitude higher ice crystal concentrations and to an inhibition of homogeneous nucleation in lower-temperature regions. Our cloud simulation results suggest that atmospheric dust particles that form ice nuclei at lower temperatures, below -36 °C, can potentially have a stronger influence on cloud properties, such as cloud longevity and initiation, compared to previous parameterizations.

Wave modeling for the Beaufort and Chukchi Seas

NASA Astrophysics Data System (ADS)

Rogers, W.; Thomson, J.; Shen, H. H.; Posey, P. G.; Hebert, D. A.

2016-02-01

Authors: W. Erick Rogers(1), Jim Thomson(2), Hayley Shen (3), PamelaPosey (1), David Hebert (1) 1 Naval Research Laboratory, Stennis Space Center, Mississippi, USA2 Applied Physics Laboratory, University of Washington, Seattle,Washington, USA3 Clarkson University, Potsdam, New York, USA Abstract : In this presentation, we will discuss the development and application of numerical models for prediction of wind-generated surface gravity waves to the Arctic Ocean, and specifically the Beaufort and Chukchi Seas, for which the Office of Naval Research (ONR) has supported two major field campaigns in 2014 and 2015. The modeling platform is the spectral wave model WAVEWATCH III (R) (WW3). We will begin by reviewing progress with the model numerics in 2007 and 2008 which permits efficient application at high latitudes. Then, we will discuss more recent progress (2012 to 2015) adding new physics to WW3 for ice effects. The latter include two parameterizations for dissipation by turbulence at the ice/water interface, and a more complex parameterization which treat the ice as a viscoelastic fluid. With these new physics, the primary challenge is to find observational data suitable for calibration of the parameterization, and there are concerns about validity of application of any calibration to the wide variety of ice types that exist in the Arctic (or Southern Ocean). Quality of input is another major challenge, for which some recent progress has been made (at least in the context of ice concentration and ice edge) with data assimilative ice modeling at NRL. We will discuss our recent work to invert for dissipation rate using data from a 2012 mooring in the Beaufort Sea, how the results vary by season (ice retreat vs. advance), and what this tells us in context of those complex physical parameterizations used by the model. We will summarize plans for further development of the model, such as adding scattering by floes, through collaboration with IFREMER (France), and improving on the simple "proportional scaling" treatment of the open water source functions in presence of partial ice cover. Finally, we will discuss lessons learned for wave modeling from the autumn 2015 R/V Sikuliaq cruise supported by ONR.

Modeling parameterized geometry in GPU-based Monte Carlo particle transport simulation for radiotherapy.

PubMed

Chi, Yujie; Tian, Zhen; Jia, Xun

2016-08-07

Monte Carlo (MC) particle transport simulation on a graphics-processing unit (GPU) platform has been extensively studied recently due to the efficiency advantage achieved via massive parallelization. Almost all of the existing GPU-based MC packages were developed for voxelized geometry. This limited application scope of these packages. The purpose of this paper is to develop a module to model parametric geometry and integrate it in GPU-based MC simulations. In our module, each continuous region was defined by its bounding surfaces that were parameterized by quadratic functions. Particle navigation functions in this geometry were developed. The module was incorporated to two previously developed GPU-based MC packages and was tested in two example problems: (1) low energy photon transport simulation in a brachytherapy case with a shielded cylinder applicator and (2) MeV coupled photon/electron transport simulation in a phantom containing several inserts of different shapes. In both cases, the calculated dose distributions agreed well with those calculated in the corresponding voxelized geometry. The averaged dose differences were 1.03% and 0.29%, respectively. We also used the developed package to perform simulations of a Varian VS 2000 brachytherapy source and generated a phase-space file. The computation time under the parameterized geometry depended on the memory location storing the geometry data. When the data was stored in GPU's shared memory, the highest computational speed was achieved. Incorporation of parameterized geometry yielded a computation time that was ~3 times of that in the corresponding voxelized geometry. We also developed a strategy to use an auxiliary index array to reduce frequency of geometry calculations and hence improve efficiency. With this strategy, the computational time ranged in 1.75-2.03 times of the voxelized geometry for coupled photon/electron transport depending on the voxel dimension of the auxiliary index array, and in 0.69-1.23 times for photon only transport.

A coupled two-dimensional main chain torsional potential for protein dynamics: generation and implementation.

PubMed

Li, Yongxiu; Gao, Ya; Zhang, Xuqiang; Wang, Xingyu; Mou, Lirong; Duan, Lili; He, Xiao; Mei, Ye; Zhang, John Z H

2013-09-01

Main chain torsions of alanine dipeptide are parameterized into coupled 2-dimensional Fourier expansions based on quantum mechanical (QM) calculations at M06 2X/aug-cc-pvtz//HF/6-31G** level. Solvation effect is considered by employing polarizable continuum model. Utilization of the M06 2X functional leads to precise potential energy surface that is comparable to or even better than MP2 level, but with much less computational demand. Parameterization of the 2D expansions is against the full main chain torsion space instead of just a few low energy conformations. This procedure is similar to that for the development of AMBER03 force field, except unique weighting factor was assigned to all the grid points. To avoid inconsistency between quantum mechanical calculations and molecular modeling, the model peptide is further optimized at molecular mechanics level with main chain dihedral angles fixed before the calculation of the conformational energy on molecular mechanical level at each grid point, during which generalized Born model is employed. Difference in solvation models at quantum mechanics and molecular mechanics levels makes this parameterization procedure less straightforward. All force field parameters other than main chain torsions are taken from existing AMBER force field. With this new main chain torsion terms, we have studied the main chain dihedral distributions of ALA dipeptide and pentapeptide in aqueous solution. The results demonstrate that 2D main chain torsion is effective in delineating the energy variation associated with rotations along main chain dihedrals. This work is an implication for the necessity of more accurate description of main chain torsions in the future development of ab initio force field and it also raises a challenge to the development of quantum mechanical methods, especially the quantum mechanical solvation models.

Assessing impacts of PBL and surface layer schemes in simulating the surface–atmosphere interactions and precipitation over the tropical ocean using observations from AMIE/DYNAMO

DOE PAGES

Qian, Yun; Yan, Huiping; Berg, Larry K.; ...

2016-10-28

Accuracy of turbulence parameterization in representing Planetary Boundary Layer (PBL) processes in climate models is critical for predicting the initiation and development of clouds, air quality issues, and underlying surface-atmosphere-cloud interactions. In this study, we 1) evaluate WRF model-simulated spatial patterns of precipitation and surface fluxes, as well as vertical profiles of potential temperature, humidity, moist static energy and moisture tendency terms as simulated by WRF at various spatial resolutions and with PBL, surface layer and shallow convection schemes against measurements, 2) identify model biases by examining the moisture tendency terms contributed by PBL and convection processes through nudging experiments,more » and 3) evaluate the dependence of modeled surface latent heat (LH) fluxes onPBL and surface layer schemes over the tropical ocean. The results show that PBL and surface parameterizations have surprisingly large impacts on precipitation, convection initiation and surface moisture fluxes over tropical oceans. All of the parameterizations tested tend to overpredict moisture in PBL and free atmosphere, and consequently result in larger moist static energy and precipitation. Moisture nudging tends to suppress the initiation of convection and reduces the excess precipitation. The reduction in precipitation bias in turn reduces the surface wind and LH flux biases, which suggests that the model drifts at least partly because of a positive feedback between precipitation and surface fluxes. The updated shallow convection scheme KF-CuP tends to suppress the initiation and development of deep convection, consequently decreasing precipitation. The Eta surface layer scheme predicts more reasonable LH fluxes and the LH-Wind Speed relationship than the MM5 scheme, especially when coupled with the MYJ scheme. By examining various parameterization schemes in WRF, we identify sources of biases and weaknesses of current PBL, surface layer and shallow convection schemes in reproducing PBL processes, the initiation of convection and intra-seasonal variability of precipitation.« less

Evaluation of snow and frozen soil parameterization in a cryosphere land surface modeling framework in the Tibetan Plateau

NASA Astrophysics Data System (ADS)

Zhou, J.

2017-12-01

Snow and frozen soil are important components in the Tibetan Plateau, and influence the water cycle and energy balances through snowpack accumulation and melt and soil freeze-thaw. In this study, a new cryosphere land surface model (LSM) with coupled snow and frozen soil parameterization was developed based on a hydrologically improved LSM (HydroSiB2). First, an energy-balance-based three-layer snow model was incorporated into HydroSiB2 (hereafter HydroSiB2-S) to provide an improved description of the internal processes of the snow pack. Second, a universal and simplified soil model was coupled with HydroSiB2-S to depict soil water freezing and thawing (hereafter HydroSiB2-SF). In order to avoid the instability caused by the uncertainty in estimating water phase changes, enthalpy was adopted as a prognostic variable instead of snow/soil temperature in the energy balance equation of the snow/frozen soil module. The newly developed models were then carefully evaluated at two typical sites of the Tibetan Plateau (TP) (one snow covered and the other snow free, both with underlying frozen soil). At the snow-covered site in northeastern TP (DY), HydroSiB2-SF demonstrated significant improvements over HydroSiB2-F (same as HydroSiB2-SF but using the original single-layer snow module of HydroSiB2), showing the importance of snow internal processes in three-layer snow parameterization. At the snow-free site in southwestern TP (Ngari), HydroSiB2-SF reasonably simulated soil water phase changes while HydroSiB2-S did not, indicating the crucial role of frozen soil parameterization in depicting the soil thermal and water dynamics. Finally, HydroSiB2-SF proved to be capable of simulating upward moisture fluxes toward the freezing front from the underlying soil layers in winter.

Using Petri nets for experimental design in a multi-organ elimination pathway.

PubMed

Reshetova, Polina; Smilde, Age K; Westerhuis, Johan A; van Kampen, Antoine H C

2015-08-01

Genistein is a soy metabolite with estrogenic activity that may result in (un)favorable effects on human health. Elucidation of the mechanisms through which food additives such as genistein exert their beneficiary effects is a major challenge for the food industry. A better understanding of the genistein elimination pathway could shed light on such mechanisms. We developed a Petri net model that represents this multi-organ elimination pathway and which assists in the design of future experiments. Using this model we show that metabolic profiles solely measured in venous blood are not sufficient to uniquely parameterize the model. Based on simulations we suggest two solutions that provide better results: parameterize the model using gut epithelium profiles or add additional biological constrains in the model. Copyright © 2015 Elsevier Ltd. All rights reserved.

A computationally efficient description of heterogeneous freezing: A simplified version of the Soccer ball model

NASA Astrophysics Data System (ADS)

Niedermeier, Dennis; Ervens, Barbara; Clauss, Tina; Voigtländer, Jens; Wex, Heike; Hartmann, Susan; Stratmann, Frank

2014-01-01

In a recent study, the Soccer ball model (SBM) was introduced for modeling and/or parameterizing heterogeneous ice nucleation processes. The model applies classical nucleation theory. It allows for a consistent description of both apparently singular and stochastic ice nucleation behavior, by distributing contact angles over the nucleation sites of a particle population assuming a Gaussian probability density function. The original SBM utilizes the Monte Carlo technique, which hampers its usage in atmospheric models, as fairly time-consuming calculations must be performed to obtain statistically significant results. Thus, we have developed a simplified and computationally more efficient version of the SBM. We successfully used the new SBM to parameterize experimental nucleation data of, e.g., bacterial ice nucleation. Both SBMs give identical results; however, the new model is computationally less expensive as confirmed by cloud parcel simulations. Therefore, it is a suitable tool for describing heterogeneous ice nucleation processes in atmospheric models.

Analysis of Surface Heterogeneity Effects with Mesoscale Terrestrial Modeling Platforms

NASA Astrophysics Data System (ADS)

Simmer, C.

2015-12-01

An improved understanding of the full variability in the weather and climate system is crucial for reducing the uncertainty in weather forecasting and climate prediction, and to aid policy makers to develop adaptation and mitigation strategies. A yet unknown part of uncertainty in the predictions from the numerical models is caused by the negligence of non-resolved land surface heterogeneity and the sub-surface dynamics and their potential impact on the state of the atmosphere. At the same time, mesoscale numerical models using finer horizontal grid resolution [O(1)km] can suffer from inconsistencies and neglected scale-dependencies in ABL parameterizations and non-resolved effects of integrated surface-subsurface lateral flow at this scale. Our present knowledge suggests large-eddy-simulation (LES) as an eventual solution to overcome the inadequacy of the physical parameterizations in the atmosphere in this transition scale, yet we are constrained by the computational resources, memory management, big-data, when using LES for regional domains. For the present, there is a need for scale-aware parameterizations not only in the atmosphere but also in the land surface and subsurface model components. In this study, we use the recently developed Terrestrial Systems Modeling Platform (TerrSysMP) as a numerical tool to analyze the uncertainty in the simulation of surface exchange fluxes and boundary layer circulations at grid resolutions of the order of 1km, and explore the sensitivity of the atmospheric boundary layer evolution and convective rainfall processes on land surface heterogeneity.

An Evaluation of Lightning Flash Rate Parameterizations Based on Observations of Colorado Storms during DC3

NASA Astrophysics Data System (ADS)

Basarab, B.; Fuchs, B.; Rutledge, S. A.

2013-12-01

Predicting lightning activity in thunderstorms is important in order to accurately quantify the production of nitrogen oxides (NOx = NO + NO2) by lightning (LNOx). Lightning is an important global source of NOx, and since NOx is a chemical precursor to ozone, the climatological impacts of LNOx could be significant. Many cloud-resolving models rely on parameterizations to predict lightning and LNOx since the processes leading to charge separation and lightning discharge are not yet fully understood. This study evaluates predicted flash rates based on existing lightning parameterizations against flash rates observed for Colorado storms during the Deep Convective Clouds and Chemistry Experiment (DC3). Evaluating lightning parameterizations against storm observations is a useful way to possibly improve the prediction of flash rates and LNOx in models. Additionally, since convective storms that form in the eastern plains of Colorado can be different thermodynamically and electrically from storms in other regions, it is useful to test existing parameterizations against observations from these storms. We present an analysis of the dynamics, microphysics, and lightning characteristics of two case studies, severe storms that developed on 6 and 7 June 2012. This analysis includes dual-Doppler derived horizontal and vertical velocities, a hydrometeor identification based on polarimetric radar variables using the CSU-CHILL radar, and insight into the charge structure using observations from the northern Colorado Lightning Mapping Array (LMA). Flash rates were inferred from the LMA data using a flash counting algorithm. We have calculated various microphysical and dynamical parameters for these storms that have been used in empirical flash rate parameterizations. In particular, maximum vertical velocity has been used to predict flash rates in some cloud-resolving chemistry simulations. We diagnose flash rates for the 6 and 7 June storms using this parameterization and compare to observed flash rates. For the 6 June storm, a preliminary analysis of aircraft observations of storm inflow and outflow is presented in order to place flash rates (and other lightning statistics) in the context of storm chemistry. An approach to a possibly improved LNOx parameterization scheme using different lightning metrics such as flash area will be discussed.

Parameterization guidelines and considerations for hydrologic models

Treesearch

 R. W. Malone; G. Yagow; C. Baffaut; M.W  Gitau; Z. Qi; Devendra Amatya; P.B.   Parajuli; J.V. Bonta; T.R.  Green

2015-01-01

 Imparting knowledge of the physical processes of a system to a model and determining a set of parameter values for a hydrologic or water quality model application (i.e., parameterization) are important and difficult tasks. An exponential...

Optimal lattice-structured materials

DOE PAGES

Messner, Mark C.

2016-07-09

This paper describes a method for optimizing the mesostructure of lattice-structured materials. These materials are periodic arrays of slender members resembling efficient, lightweight macroscale structures like bridges and frame buildings. Current additive manufacturing technologies can assemble lattice structures with length scales ranging from nanometers to millimeters. Previous work demonstrates that lattice materials have excellent stiffness- and strength-to-weight scaling, outperforming natural materials. However, there are currently no methods for producing optimal mesostructures that consider the full space of possible 3D lattice topologies. The inverse homogenization approach for optimizing the periodic structure of lattice materials requires a parameterized, homogenized material model describingmore » the response of an arbitrary structure. This work develops such a model, starting with a method for describing the long-wavelength, macroscale deformation of an arbitrary lattice. The work combines the homogenized model with a parameterized description of the total design space to generate a parameterized model. Finally, the work describes an optimization method capable of producing optimal mesostructures. Several examples demonstrate the optimization method. One of these examples produces an elastically isotropic, maximally stiff structure, here called the isotruss, that arguably outperforms the anisotropic octet truss topology.« less

Sensitivity of single column model simulations of Arctic springtime clouds to different cloud cover and mixed phase cloud parameterizations

NASA Astrophysics Data System (ADS)

Zhang, Junhua; Lohmann, Ulrike

2003-08-01

The single column model of the Canadian Centre for Climate Modeling and Analysis (CCCma) climate model is used to simulate Arctic spring cloud properties observed during the Surface Heat Budget of the Arctic Ocean (SHEBA) experiment. The model is driven by the rawinsonde observations constrained European Center for Medium-Range Weather Forecasts (ECMWF) reanalysis data. Five cloud parameterizations, including three statistical and two explicit schemes, are compared and the sensitivity to mixed phase cloud parameterizations is studied. Using the original mixed phase cloud parameterization of the model, the statistical cloud schemes produce more cloud cover, cloud water, and precipitation than the explicit schemes and in general agree better with observations. The mixed phase cloud parameterization from ECMWF decreases the initial saturation specific humidity threshold of cloud formation. This improves the simulated cloud cover in the explicit schemes and reduces the difference between the different cloud schemes. On the other hand, because the ECMWF mixed phase cloud scheme does not consider the Bergeron-Findeisen process, less ice crystals are formed. This leads to a higher liquid water path and less precipitation than what was observed.

Technical report series on global modeling and data assimilation. Volume 3: An efficient thermal infrared radiation parameterization for use in general circulation models

NASA Technical Reports Server (NTRS)

Suarex, Max J. (Editor); Chou, Ming-Dah

1994-01-01

A detailed description of a parameterization for thermal infrared radiative transfer designed specifically for use in global climate models is presented. The parameterization includes the effects of the main absorbers of terrestrial radiation: water vapor, carbon dioxide, and ozone. While being computationally efficient, the schemes compute very accurately the clear-sky fluxes and cooling rates from the Earth's surface to 0.01 mb. This combination of accuracy and speed makes the parameterization suitable for both tropospheric and middle atmospheric modeling applications. Since no transmittances are precomputed the atmospheric layers and the vertical distribution of the absorbers may be freely specified. The scheme can also account for any vertical distribution of fractional cloudiness with arbitrary optical thickness. These features make the parameterization very flexible and extremely well suited for use in climate modeling studies. In addition, the numerics and the FORTRAN implementation have been carefully designed to conserve both memory and computer time. This code should be particularly attractive to those contemplating long-term climate simulations, wishing to model the middle atmosphere, or planning to use a large number of levels in the vertical.

Rainfall From Resolved Rather Than Parameterized Processes Better Represents the Present-Day and Climate Change Response of Moderate Rates in the Community Atmosphere Model

DOE PAGES

Kooperman, Gabriel J.; Pritchard, Michael S.; O'Brien, Travis A.; ...

2018-04-01

Deficiencies in the parameterizations of convection used in global climate models often lead to a distorted representation of the simulated rainfall intensity distribution (i.e., too much rainfall from weak rain rates). While encouraging improvements in high percentile rainfall intensity have been found as the horizontal resolution of the Community Atmosphere Model is increased to ~25 km, we demonstrate no corresponding improvement in the moderate rain rates that generate the majority of accumulated rainfall. Using a statistical framework designed to emphasize links between precipitation intensity and accumulated rainfall beyond just the frequency distribution, we show that CAM cannot realistically simulate moderatemore » rain rates, and cannot capture their intensification with climate change, even as resolution is increased. However, by separating the parameterized convective and large-scale resolved contributions to total rainfall, we find that the intensity, geographic pattern, and climate change response of CAM's large-scale rain rates are more consistent with observations (TRMM 3B42), superparameterization, and theoretical expectations, despite issues with parameterized convection. Increasing CAM's horizontal resolution does improve the representation of total rainfall intensity, but not due to changes in the intensity of large-scale rain rates, which are surprisingly insensitive to horizontal resolution. Rather, improvements occur through an increase in the relative contribution of the large-scale component to the total amount of accumulated rainfall. Analysis of sensitivities to convective timescale and entrainment rate confirm the importance of these parameters in the possible development of scale-aware parameterizations, but also reveal unrecognized trade-offs from the entanglement of precipitation frequency and total amount.« less

Rainfall From Resolved Rather Than Parameterized Processes Better Represents the Present-Day and Climate Change Response of Moderate Rates in the Community Atmosphere Model

NASA Astrophysics Data System (ADS)

Kooperman, Gabriel J.; Pritchard, Michael S.; O'Brien, Travis A.; Timmermans, Ben W.

2018-04-01

Deficiencies in the parameterizations of convection used in global climate models often lead to a distorted representation of the simulated rainfall intensity distribution (i.e., too much rainfall from weak rain rates). While encouraging improvements in high percentile rainfall intensity have been found as the horizontal resolution of the Community Atmosphere Model is increased to ˜25 km, we demonstrate no corresponding improvement in the moderate rain rates that generate the majority of accumulated rainfall. Using a statistical framework designed to emphasize links between precipitation intensity and accumulated rainfall beyond just the frequency distribution, we show that CAM cannot realistically simulate moderate rain rates, and cannot capture their intensification with climate change, even as resolution is increased. However, by separating the parameterized convective and large-scale resolved contributions to total rainfall, we find that the intensity, geographic pattern, and climate change response of CAM's large-scale rain rates are more consistent with observations (TRMM 3B42), superparameterization, and theoretical expectations, despite issues with parameterized convection. Increasing CAM's horizontal resolution does improve the representation of total rainfall intensity, but not due to changes in the intensity of large-scale rain rates, which are surprisingly insensitive to horizontal resolution. Rather, improvements occur through an increase in the relative contribution of the large-scale component to the total amount of accumulated rainfall. Analysis of sensitivities to convective timescale and entrainment rate confirm the importance of these parameters in the possible development of scale-aware parameterizations, but also reveal unrecognized trade-offs from the entanglement of precipitation frequency and total amount.

Rainfall From Resolved Rather Than Parameterized Processes Better Represents the Present‐Day and Climate Change Response of Moderate Rates in the Community Atmosphere Model

PubMed Central

Pritchard, Michael S.; O'Brien, Travis A.; Timmermans, Ben W.

2018-01-01

Abstract Deficiencies in the parameterizations of convection used in global climate models often lead to a distorted representation of the simulated rainfall intensity distribution (i.e., too much rainfall from weak rain rates). While encouraging improvements in high percentile rainfall intensity have been found as the horizontal resolution of the Community Atmosphere Model is increased to ∼25 km, we demonstrate no corresponding improvement in the moderate rain rates that generate the majority of accumulated rainfall. Using a statistical framework designed to emphasize links between precipitation intensity and accumulated rainfall beyond just the frequency distribution, we show that CAM cannot realistically simulate moderate rain rates, and cannot capture their intensification with climate change, even as resolution is increased. However, by separating the parameterized convective and large‐scale resolved contributions to total rainfall, we find that the intensity, geographic pattern, and climate change response of CAM's large‐scale rain rates are more consistent with observations (TRMM 3B42), superparameterization, and theoretical expectations, despite issues with parameterized convection. Increasing CAM's horizontal resolution does improve the representation of total rainfall intensity, but not due to changes in the intensity of large‐scale rain rates, which are surprisingly insensitive to horizontal resolution. Rather, improvements occur through an increase in the relative contribution of the large‐scale component to the total amount of accumulated rainfall. Analysis of sensitivities to convective timescale and entrainment rate confirm the importance of these parameters in the possible development of scale‐aware parameterizations, but also reveal unrecognized trade‐offs from the entanglement of precipitation frequency and total amount. PMID:29861837

Rainfall From Resolved Rather Than Parameterized Processes Better Represents the Present-Day and Climate Change Response of Moderate Rates in the Community Atmosphere Model

DOE Office of Scientific and Technical Information (OSTI.GOV)

Kooperman, Gabriel J.; Pritchard, Michael S.; O'Brien, Travis A.

Deficiencies in the parameterizations of convection used in global climate models often lead to a distorted representation of the simulated rainfall intensity distribution (i.e., too much rainfall from weak rain rates). While encouraging improvements in high percentile rainfall intensity have been found as the horizontal resolution of the Community Atmosphere Model is increased to ~25 km, we demonstrate no corresponding improvement in the moderate rain rates that generate the majority of accumulated rainfall. Using a statistical framework designed to emphasize links between precipitation intensity and accumulated rainfall beyond just the frequency distribution, we show that CAM cannot realistically simulate moderatemore » rain rates, and cannot capture their intensification with climate change, even as resolution is increased. However, by separating the parameterized convective and large-scale resolved contributions to total rainfall, we find that the intensity, geographic pattern, and climate change response of CAM's large-scale rain rates are more consistent with observations (TRMM 3B42), superparameterization, and theoretical expectations, despite issues with parameterized convection. Increasing CAM's horizontal resolution does improve the representation of total rainfall intensity, but not due to changes in the intensity of large-scale rain rates, which are surprisingly insensitive to horizontal resolution. Rather, improvements occur through an increase in the relative contribution of the large-scale component to the total amount of accumulated rainfall. Analysis of sensitivities to convective timescale and entrainment rate confirm the importance of these parameters in the possible development of scale-aware parameterizations, but also reveal unrecognized trade-offs from the entanglement of precipitation frequency and total amount.« less

Improving Mixed-phase Cloud Parameterization in Climate Model with the ACRF Measurements

DOE Office of Scientific and Technical Information (OSTI.GOV)

Wang, Zhien

Mixed-phase cloud microphysical and dynamical processes are still poorly understood, and their representation in GCMs is a major source of uncertainties in overall cloud feedback in GCMs. Thus improving mixed-phase cloud parameterizations in climate models is critical to reducing the climate forecast uncertainties. This study aims at providing improved knowledge of mixed-phase cloud properties from the long-term ACRF observations and improving mixed-phase clouds simulations in the NCAR Community Atmosphere Model version 5 (CAM5). The key accomplishments are: 1) An improved retrieval algorithm was developed to provide liquid droplet concentration for drizzling or mixed-phase stratiform clouds. 2) A new ice concentrationmore » retrieval algorithm for stratiform mixed-phase clouds was developed. 3) A strong seasonal aerosol impact on ice generation in Arctic mixed-phase clouds was identified, which is mainly attributed to the high dust occurrence during the spring season. 4) A suite of multi-senor algorithms was applied to long-term ARM observations at the Barrow site to provide a complete dataset (LWC and effective radius profile for liquid phase, and IWC, Dge profiles and ice concentration for ice phase) to characterize Arctic stratiform mixed-phase clouds. This multi-year stratiform mixed-phase cloud dataset provides necessary information to study related processes, evaluate model stratiform mixed-phase cloud simulations, and improve model stratiform mixed-phase cloud parameterization. 5). A new in situ data analysis method was developed to quantify liquid mass partition in convective mixed-phase clouds. For the first time, we reliably compared liquid mass partitions in stratiform and convective mixed-phase clouds. Due to the different dynamics in stratiform and convective mixed-phase clouds, the temperature dependencies of liquid mass partitions are significantly different due to much higher ice concentrations in convective mixed phase clouds. 6) Systematic evaluations of mixed-phase cloud simulations by CAM5 were performed. Measurement results indicate that ice concentrations control stratiform mixed-phase cloud properties. The improvement of ice concentration parameterization in the CAM5 was done in close collaboration with Dr. Xiaohong Liu, PNNL (now at University of Wyoming).« less

Scientific Overview of Temporal Experiment for Storms and Tropical Systems (TEMPEST) Program

NASA Astrophysics Data System (ADS)

Chandra, C. V.; Reising, S. C.; Kummerow, C. D.; van den Heever, S. C.; Todd, G.; Padmanabhan, S.; Brown, S. T.; Lim, B.; Haddad, Z. S.; Koch, T.; Berg, G.; L'Ecuyer, T.; Munchak, S. J.; Luo, Z. J.; Boukabara, S. A.; Ruf, C. S.

2014-12-01

Over the past decade and a half, we have gained a better understanding of the role of clouds and precipitation on Earth's water cycle, energy budget and climate, from focused Earth science observational satellite missions. However, these missions provide only a snapshot at one point in time of the cloud's development. Processes that govern cloud system development occur primarily on time scales of the order of 5-30 minutes that are generally not observable from low Earth orbiting satellites. Geostationary satellites, in contrast, have higher temporal resolution but at present are limited to visible and infrared wavelengths that observe only the tops of clouds. This observing gap was noted by the National Research Council's Earth Science Decadal Survey in 2007. Uncertainties in global climate models are significantly affected by processes that govern the formation and dissipation of clouds that largely control the global water and energy budgets. Current uncertainties in cloud parameterization within climate models lead to drastically different climate outcomes. With all evidence suggesting that the precipitation onset may be governed by factors such atmospheric stability, it becomes critical to have at least first-order observations globally in diverse climate regimes. Similar arguments are valid for ice processes where more efficient ice formation and precipitation have a tendency to leave fewer ice clouds behind that have different but equally important impacts on the Earth's energy budget and resulting temperature trends. TEMPEST is a unique program that will provide a small constellation of inexpensive CubeSats with millimeter-wave radiometers to address key science needs related to cloud and precipitation processes. Because these processes are most critical in the development of climate models that will soon run at scales that explicitly resolve clouds, the TEMPEST program will directly focus on examining, validating and improving the parameterizations currently used in cloud scale models. The time evolution of cloud and precipitation microphysics is dependent upon parameterized process rates. The outcome of TEMPEST will provide a first-order understanding of how individual assumptions in current cloud model parameterizations behave in diverse climate regimes.

Atmospheric Electrical Modeling in Support of the NASA F-106 Storm Hazards Project

NASA Technical Reports Server (NTRS)

Helsdon, John H., Jr.

1988-01-01

A recently developed storm electrification model (SEM) is used to investigate the operating environment of the F-106 airplane during the NASA Storm Hazards Project. The model is 2-D, time dependent and uses a bulkwater microphysical parameterization scheme. Electric charges and fields are included, and the model is fully coupled dynamically, microphysically and electrically. One flight showed that a high electric field was developed at the aircraft's operating altitude (28 kft) and that a strong electric field would also be found below 20 kft; however, this low-altitude, high-field region was associated with the presence of small hail, posing a hazard to the aircraft. An operational procedure to increase the frequency of low-altitude lightning strikes was suggested. To further the understanding of lightning within the cloud environment, a parameterization of the lightning process was included in the SEM. It accounted for the initiation, propagation, termination, and charge redistribution associated with an intracloud discharge. Finally, a randomized lightning propagation scheme was developed, and the effects of cloud particles on the initiation of lightning investigated.

Nitrous Oxide Emissions from Biofuel Crops and Parameterization in the EPIC Biogeochemical Model

EPA Science Inventory

This presentation describes year 1 field measurements of N2O fluxes and crop yields which are used to parameterize the EPIC biogeochemical model for the corresponding field site. Initial model simulations are also presented.

Importance of Physico-Chemical Properties of Aerosols in the Formation of Arctic Ice Clouds

NASA Astrophysics Data System (ADS)

Keita, S. A.; Girard, E.

2014-12-01

Ice clouds play an important role in the Arctic weather and climate system but interactions between aerosols, clouds and radiation are poorly understood. Consequently, it is essential to fully understand their properties and especially their formation process. Extensive measurements from ground-based sites and satellite remote sensing reveal the existence of two Types of Ice Clouds (TICs) in the Arctic during the polar night and early spring. TIC-1 are composed by non-precipitating very small (radar-unseen) ice crystals whereas TIC-2 are detected by both sensors and are characterized by a low concentration of large precipitating ice crystals. It is hypothesized that TIC-2 formation is linked to the acidification of aerosols, which inhibit the ice nucleating properties of ice nuclei (IN). As a result, the IN concentration is reduced in these regions, resulting to a smaller concentration of larger ice crystals. Over the past 10 years, several parameterizations of homogeneous and heterogeneous ice nucleation have been developed to reflect the various physical and chemical properties of aerosols. These parameterizations are derived from laboratory studies on aerosols of different chemical compositions. The parameterizations are also developed according to two main approaches: stochastic (that nucleation is a probabilistic process, which is time dependent) and singular (that nucleation occurs at fixed conditions of temperature and humidity and time-independent). This research aims to better understand the formation process of TICs using a newly-developed ice nucleation parameterizations. For this purpose, we implement some parameterizations (2 approaches) into the Limited Area version of the Global Multiscale Environmental Model (GEM-LAM) and use them to simulate ice clouds observed during the Indirect and Semi-Direct Arctic Cloud (ISDAC) in Alaska. We use both approaches but special attention is focused on the new parameterizations of the singular approach. Simulation results of the TICs-2 observed on April 15th and 25th (polluted or acidic cases) and TICs-1 observed on April 5th (non-polluted cases) will be presented.

Modeling Cloud Phase Fraction Based on In-situ Observations in Stratiform Clouds

NASA Astrophysics Data System (ADS)

Boudala, F. S.; Isaac, G. A.

2005-12-01

Mixed-phase clouds influence weather and climate in several ways. Due to the fact that they exhibit very different optical properties as compared to ice or liquid only clouds, they play an important role in the earth's radiation balance by modifying the optical properties of clouds. Precipitation development in clouds is also enhanced under mixed-phase conditions and these clouds may contain large supercooled drops that freeze quickly in contact with aircraft surfaces that may be a hazard to aviation. The existence of ice and liquid phase clouds together in the same environment is thermodynamically unstable, and thus they are expected to disappear quickly. However, several observations show that mixed-phase clouds are relatively stable in the natural environment and last for several hours. Although there have been some efforts being made in the past to study the microphysical properties of mixed-phase clouds, there are still a number of uncertainties in modeling these clouds particularly in large scale numerical models. In most models, very simple temperature dependent parameterizations of cloud phase fraction are being used to estimate the fraction of ice or liquid phase in a given mixed-phase cloud. In this talk, two different parameterizations of ice fraction using in-situ aircraft measurements of cloud microphysical properties collected in extratropical stratiform clouds during several field programs will be presented. One of the parameterizations has been tested using a single prognostic equation developed by Tremblay et al. (1996) for application in the Canadian regional weather prediction model. The addition of small ice particles significantly increased the vapor deposition rate when the natural atmosphere is assumed to be water saturated, and thus this enhanced the glaciation of simulated mixed-phase cloud via the Bergeron-Findeisen process without significantly affecting the other cloud microphysical processes such as riming and particle sedimentation rates. After the water vapor pressure in mixed-phase cloud was modified based on the Lord et al. (1984) scheme by weighting the saturation water vapor pressure with ice fraction, it was possible to simulate more stable mixed-phase cloud. It was also noted that the ice particle concentration (L>100 μm) in mixed-phase cloud is lower on average by a factor 3 and as a result the parameterization should be corrected for this effect. After accounting for this effect, the parameterized ice fraction agreed well with observed mean ice fraction.

Modeling canopy-induced turbulence in the Earth system: a unified parameterization of turbulent exchange within plant canopies and the roughness sublayer (CLM-ml v0)

NASA Astrophysics Data System (ADS)

Bonan, Gordon B.; Patton, Edward G.; Harman, Ian N.; Oleson, Keith W.; Finnigan, John J.; Lu, Yaqiong; Burakowski, Elizabeth A.

2018-04-01

Land surface models used in climate models neglect the roughness sublayer and parameterize within-canopy turbulence in an ad hoc manner. We implemented a roughness sublayer turbulence parameterization in a multilayer canopy model (CLM-ml v0) to test if this theory provides a tractable parameterization extending from the ground through the canopy and the roughness sublayer. We compared the canopy model with the Community Land Model (CLM4.5) at seven forest, two grassland, and three cropland AmeriFlux sites over a range of canopy heights, leaf area indexes, and climates. CLM4.5 has pronounced biases during summer months at forest sites in midday latent heat flux, sensible heat flux, gross primary production, nighttime friction velocity, and the radiative temperature diurnal range. The new canopy model reduces these biases by introducing new physics. Advances in modeling stomatal conductance and canopy physiology beyond what is in CLM4.5 substantially improve model performance at the forest sites. The signature of the roughness sublayer is most evident in nighttime friction velocity and the diurnal cycle of radiative temperature, but is also seen in sensible heat flux. Within-canopy temperature profiles are markedly different compared with profiles obtained using Monin-Obukhov similarity theory, and the roughness sublayer produces cooler daytime and warmer nighttime temperatures. The herbaceous sites also show model improvements, but the improvements are related less systematically to the roughness sublayer parameterization in these canopies. The multilayer canopy with the roughness sublayer turbulence improves simulations compared with CLM4.5 while also advancing the theoretical basis for surface flux parameterizations.

A frequentist approach to computer model calibration

DOE PAGES

Wong, Raymond K. W.; Storlie, Curtis Byron; Lee, Thomas C. M.

2016-05-05

The paper considers the computer model calibration problem and provides a general frequentist solution. Under the framework proposed, the data model is semiparametric with a non-parametric discrepancy function which accounts for any discrepancy between physical reality and the computer model. In an attempt to solve a fundamentally important (but often ignored) identifiability issue between the computer model parameters and the discrepancy function, the paper proposes a new and identifiable parameterization of the calibration problem. It also develops a two-step procedure for estimating all the relevant quantities under the new parameterization. This estimation procedure is shown to enjoy excellent rates ofmore » convergence and can be straightforwardly implemented with existing software. For uncertainty quantification, bootstrapping is adopted to construct confidence regions for the quantities of interest. As a result, the practical performance of the methodology is illustrated through simulation examples and an application to a computational fluid dynamics model.« less

Impact and Crashworthiness Characteristics of Venera Type Landers for Future Venus Missions

NASA Technical Reports Server (NTRS)

Schroeder, Kevin; Bayandor, Javid; Samareh, Jamshid

2016-01-01

In this paper an in-depth investigation of the structural design of the Venera 9-14 landers is explored. A complete reverse engineering of the Venera lander was required. The lander was broken down into its fundamental components and analyzed. This provided in-sights into the hidden features of the design. A trade study was performed to find the sensitivity of the lander's overall mass to the variation of several key parameters. For the lander's legs, the location, length, configuration, and number are all parameterized. The size of the impact ring, the radius of the drag plate, and other design features are also parameterized, and all of these features were correlated to the change of mass of the lander. A multi-fidelity design tool used for further investigation of the parameterized lander was developed. As a design was passed down from one level to the next, the fidelity, complexity, accuracy, and run time of the model increased. The low-fidelity model was a highly nonlinear analytical model developed to rapidly predict the mass of each design. The medium and high fidelity models utilized an explicit finite element framework to investigate the performance of various landers upon impact with the surface under a range of landing conditions. This methodology allowed for a large variety of designs to be investigated by the analytical model, which identified designs with the optimum structural mass to payload ratio. As promising designs emerged, investigations in the following higher fidelity models were focused on establishing their reliability and crashworthiness. The developed design tool efficiently modelled and tested the best concepts for any scenario based on critical Venusian mission requirements and constraints. Through this program, the strengths and weaknesses inherent in the Venera-Type landers were thoroughly investigated. Key features identified for the design of robust landers will be used as foundations for the development of the next generation of landers for future exploration missions to Venus.

a Physical Parameterization of Snow Albedo for Use in Climate Models.

NASA Astrophysics Data System (ADS)

Marshall, Susan Elaine

The albedo of a natural snowcover is highly variable ranging from 90 percent for clean, new snow to 30 percent for old, dirty snow. This range in albedo represents a difference in surface energy absorption of 10 to 70 percent of incident solar radiation. Most general circulation models (GCMs) fail to calculate the surface snow albedo accurately, yet the results of these models are sensitive to the assumed value of the snow albedo. This study replaces the current simple empirical parameterizations of snow albedo with a physically-based parameterization which is accurate (within +/- 3% of theoretical estimates) yet efficient to compute. The parameterization is designed as a FORTRAN subroutine (called SNOALB) which can be easily implemented into model code. The subroutine requires less then 0.02 seconds of computer time (CRAY X-MP) per call and adds only one new parameter to the model calculations, the snow grain size. The snow grain size can be calculated according to one of the two methods offered in this thesis. All other input variables to the subroutine are available from a climate model. The subroutine calculates a visible, near-infrared and solar (0.2-5 μm) snow albedo and offers a choice of two wavelengths (0.7 and 0.9 mu m) at which the solar spectrum is separated into the visible and near-infrared components. The parameterization is incorporated into the National Center for Atmospheric Research (NCAR) Community Climate Model, version 1 (CCM1), and the results of a five -year, seasonal cycle, fixed hydrology experiment are compared to the current model snow albedo parameterization. The results show the SNOALB albedos to be comparable to the old CCM1 snow albedos for current climate conditions, with generally higher visible and lower near-infrared snow albedos using the new subroutine. However, this parameterization offers a greater predictability for climate change experiments outside the range of current snow conditions because it is physically-based and not tuned to current empirical results.

Physics-based distributed snow models in the operational arena: Current and future challenges

NASA Astrophysics Data System (ADS)

Winstral, A. H.; Jonas, T.; Schirmer, M.; Helbig, N.

2017-12-01

The demand for modeling tools robust to climate change and weather extremes along with coincident increases in computational capabilities have led to an increase in the use of physics-based snow models in operational applications. Current operational applications include the WSL-SLF's across Switzerland, ASO's in California, and USDA-ARS's in Idaho. While the physics-based approaches offer many advantages there remain limitations and modeling challenges. The most evident limitation remains computation times that often limit forecasters to a single, deterministic model run. Other limitations however remain less conspicuous amidst the assumptions that these models require little to no calibration based on their foundation on physical principles. Yet all energy balance snow models seemingly contain parameterizations or simplifications of processes where validation data are scarce or present understanding is limited. At the research-basin scale where many of these models were developed these modeling elements may prove adequate. However when applied over large areas, spatially invariable parameterizations of snow albedo, roughness lengths and atmospheric exchange coefficients - all vital to determining the snowcover energy balance - become problematic. Moreover as we apply models over larger grid cells, the representation of sub-grid variability such as the snow-covered fraction adds to the challenges. Here, we will demonstrate some of the major sensitivities of distributed energy balance snow models to particular model constructs, the need for advanced and spatially flexible methods and parameterizations, and prompt the community for open dialogue and future collaborations to further modeling capabilities.

Enabling PBPK model development through the application of freely available techniques for the creation of a chemically-annotatedcollection of literature

EPA Science Inventory

The creation of Physiologically Based Pharmacokinetic (PBPK) models for a new chemical requires the selection of an appropriate model structure and the collection of a large amount of data for parameterization. Commonly, a large proportion of the needed information is collected ...

Trans-dimensional and hierarchical Bayesian approaches toward rigorous estimation of seismic sources and structures in the Northeast Asia

NASA Astrophysics Data System (ADS)

Kim, Seongryong; Tkalčić, Hrvoje; Mustać, Marija; Rhie, Junkee; Ford, Sean

2016-04-01

A framework is presented within which we provide rigorous estimations for seismic sources and structures in the Northeast Asia. We use Bayesian inversion methods, which enable statistical estimations of models and their uncertainties based on data information. Ambiguities in error statistics and model parameterizations are addressed by hierarchical and trans-dimensional (trans-D) techniques, which can be inherently implemented in the Bayesian inversions. Hence reliable estimation of model parameters and their uncertainties is possible, thus avoiding arbitrary regularizations and parameterizations. Hierarchical and trans-D inversions are performed to develop a three-dimensional velocity model using ambient noise data. To further improve the model, we perform joint inversions with receiver function data using a newly developed Bayesian method. For the source estimation, a novel moment tensor inversion method is presented and applied to regional waveform data of the North Korean nuclear explosion tests. By the combination of new Bayesian techniques and the structural model, coupled with meaningful uncertainties related to each of the processes, more quantitative monitoring and discrimination of seismic events is possible.

Elastic full-waveform inversion and parameterization analysis applied to walk-away vertical seismic profile data for unconventional (heavy oil) reservoir characterization

NASA Astrophysics Data System (ADS)

Pan, Wenyong; Innanen, Kristopher A.; Geng, Yu

2018-03-01

Seismic full-waveform inversion (FWI) methods hold strong potential to recover multiple subsurface elastic properties for hydrocarbon reservoir characterization. Simultaneously updating multiple physical parameters introduces the problem of interparameter tradeoff, arising from the covariance between different physical parameters, which increases nonlinearity and uncertainty of multiparameter FWI. The coupling effects of different physical parameters are significantly influenced by model parameterization and acquisition arrangement. An appropriate choice of model parameterization is critical to successful field data applications of multiparameter FWI. The objective of this paper is to examine the performance of various model parameterizations in isotropic-elastic FWI with walk-away vertical seismic profile (W-VSP) dataset for unconventional heavy oil reservoir characterization. Six model parameterizations are considered: velocity-density (α, β and ρ΄), modulus-density (κ, μ and ρ), Lamé-density (λ, μ΄ and ρ‴), impedance-density (IP, IS and ρ″), velocity-impedance-I (α΄, β΄ and I_P^'), and velocity-impedance-II (α″, β″ and I_S^'). We begin analyzing the interparameter tradeoff by making use of scattering radiation patterns, which is a common strategy for qualitative parameter resolution analysis. In this paper, we discuss the advantages and limitations of the scattering radiation patterns and recommend that interparameter tradeoffs be evaluated using interparameter contamination kernels, which provide quantitative, second-order measurements of the interparameter contaminations and can be constructed efficiently with an adjoint-state approach. Synthetic W-VSP isotropic-elastic FWI experiments in the time domain verify our conclusions about interparameter tradeoffs for various model parameterizations. Density profiles are most strongly influenced by the interparameter contaminations; depending on model parameterization, the inverted density profile can be over-estimated, under-estimated or spatially distorted. Among the six cases, only the velocity-density parameterization provides stable and informative density features not included in the starting model. Field data applications of multicomponent W-VSP isotropic-elastic FWI in the time domain were also carried out. The heavy oil reservoir target zone, characterized by low α-to-β ratios and low Poisson's ratios, can be identified clearly with the inverted isotropic-elastic parameters.

Elastic full-waveform inversion and parameterization analysis applied to walk-away vertical seismic profile data for unconventional (heavy oil) reservoir characterization

DOE PAGES

Pan, Wenyong; Innanen, Kristopher A.; Geng, Yu

2018-03-06

We report seismic full-waveform inversion (FWI) methods hold strong potential to recover multiple subsurface elastic properties for hydrocarbon reservoir characterization. Simultaneously updating multiple physical parameters introduces the problem of interparameter tradeoff, arising from the covariance between different physical parameters, which increases nonlinearity and uncertainty of multiparameter FWI. The coupling effects of different physical parameters are significantly influenced by model parameterization and acquisition arrangement. An appropriate choice of model parameterization is critical to successful field data applications of multiparameter FWI. The objective of this paper is to examine the performance of various model parameterizations in isotropic-elastic FWI with walk-away vertical seismicmore » profile (W-VSP) dataset for unconventional heavy oil reservoir characterization. Six model parameterizations are considered: velocity-density (α, β and ρ'), modulus-density (κ, μ and ρ), Lamé-density (λ, μ' and ρ'''), impedance-density (IP, IS and ρ''), velocity-impedance-I (α', β' and I' P), and velocity-impedance-II (α'', β'' and I'S). We begin analyzing the interparameter tradeoff by making use of scattering radiation patterns, which is a common strategy for qualitative parameter resolution analysis. In this paper, we discuss the advantages and limitations of the scattering radiation patterns and recommend that interparameter tradeoffs be evaluated using interparameter contamination kernels, which provide quantitative, second-order measurements of the interparameter contaminations and can be constructed efficiently with an adjoint-state approach. Synthetic W-VSP isotropic-elastic FWI experiments in the time domain verify our conclusions about interparameter tradeoffs for various model parameterizations. Density profiles are most strongly influenced by the interparameter contaminations; depending on model parameterization, the inverted density profile can be over-estimated, under-estimated or spatially distorted. Among the six cases, only the velocity-density parameterization provides stable and informative density features not included in the starting model. Field data applications of multicomponent W-VSP isotropic-elastic FWI in the time domain were also carried out. Finally, the heavy oil reservoir target zone, characterized by low α-to-β ratios and low Poisson’s ratios, can be identified clearly with the inverted isotropic-elastic parameters.« less

Elastic full-waveform inversion and parameterization analysis applied to walk-away vertical seismic profile data for unconventional (heavy oil) reservoir characterization

DOE Office of Scientific and Technical Information (OSTI.GOV)

Pan, Wenyong; Innanen, Kristopher A.; Geng, Yu

We report seismic full-waveform inversion (FWI) methods hold strong potential to recover multiple subsurface elastic properties for hydrocarbon reservoir characterization. Simultaneously updating multiple physical parameters introduces the problem of interparameter tradeoff, arising from the covariance between different physical parameters, which increases nonlinearity and uncertainty of multiparameter FWI. The coupling effects of different physical parameters are significantly influenced by model parameterization and acquisition arrangement. An appropriate choice of model parameterization is critical to successful field data applications of multiparameter FWI. The objective of this paper is to examine the performance of various model parameterizations in isotropic-elastic FWI with walk-away vertical seismicmore » profile (W-VSP) dataset for unconventional heavy oil reservoir characterization. Six model parameterizations are considered: velocity-density (α, β and ρ'), modulus-density (κ, μ and ρ), Lamé-density (λ, μ' and ρ'''), impedance-density (IP, IS and ρ''), velocity-impedance-I (α', β' and I' P), and velocity-impedance-II (α'', β'' and I'S). We begin analyzing the interparameter tradeoff by making use of scattering radiation patterns, which is a common strategy for qualitative parameter resolution analysis. In this paper, we discuss the advantages and limitations of the scattering radiation patterns and recommend that interparameter tradeoffs be evaluated using interparameter contamination kernels, which provide quantitative, second-order measurements of the interparameter contaminations and can be constructed efficiently with an adjoint-state approach. Synthetic W-VSP isotropic-elastic FWI experiments in the time domain verify our conclusions about interparameter tradeoffs for various model parameterizations. Density profiles are most strongly influenced by the interparameter contaminations; depending on model parameterization, the inverted density profile can be over-estimated, under-estimated or spatially distorted. Among the six cases, only the velocity-density parameterization provides stable and informative density features not included in the starting model. Field data applications of multicomponent W-VSP isotropic-elastic FWI in the time domain were also carried out. Finally, the heavy oil reservoir target zone, characterized by low α-to-β ratios and low Poisson’s ratios, can be identified clearly with the inverted isotropic-elastic parameters.« less

Parameterization of plume chemistry into large-scale atmospheric models: Application to aircraft NOx emissions

NASA Astrophysics Data System (ADS)

Cariolle, D.; Caro, D.; Paoli, R.; Hauglustaine, D. A.; CuéNot, B.; Cozic, A.; Paugam, R.

2009-10-01

A method is presented to parameterize the impact of the nonlinear chemical reactions occurring in the plume generated by concentrated NOx sources into large-scale models. The resulting plume parameterization is implemented into global models and used to evaluate the impact of aircraft emissions on the atmospheric chemistry. Compared to previous approaches that rely on corrected emissions or corrective factors to account for the nonlinear chemical effects, the present parameterization is based on the representation of the plume effects via a fuel tracer and a characteristic lifetime during which the nonlinear interactions between species are important and operate via rates of conversion for the NOx species and an effective reaction rates for O3. The implementation of this parameterization insures mass conservation and allows the transport of emissions at high concentrations in plume form by the model dynamics. Results from the model simulations of the impact on atmospheric ozone of aircraft NOx emissions are in rather good agreement with previous work. It is found that ozone production is decreased by 10 to 25% in the Northern Hemisphere with the largest effects in the north Atlantic flight corridor when the plume effects on the global-scale chemistry are taken into account. These figures are consistent with evaluations made with corrected emissions, but regional differences are noticeable owing to the possibility offered by this parameterization to transport emitted species in plume form prior to their dilution at large scale. This method could be further improved to make the parameters used by the parameterization function of the local temperature, humidity and turbulence properties diagnosed by the large-scale model. Further extensions of the method can also be considered to account for multistep dilution regimes during the plume dissipation. Furthermore, the present parameterization can be adapted to other types of point-source NOx emissions that have to be introduced in large-scale models, such as ship exhausts, provided that the plume life cycle, the type of emissions, and the major reactions involved in the nonlinear chemical systems can be determined with sufficient accuracy.

Improvement of the GEOS-5 AGCM upon Updating the Air-Sea Roughness Parameterization

NASA Technical Reports Server (NTRS)

Garfinkel, C. I.; Molod, A.; Oman, L. D.; Song, I.-S.

2011-01-01

The impact of an air-sea roughness parameterization over the ocean that more closely matches recent observations of air-sea exchange is examined in the NASA Goddard Earth Observing System, version 5 (GEOS-5) atmospheric general circulation model. Surface wind biases in the GEOS-5 AGCM are decreased by up to 1.2m/s. The new parameterization also has implications aloft as improvements extend into the stratosphere. Many other GCMs (both for operational weather forecasting and climate) use a similar class of parameterization for their air-sea roughness scheme. We therefore expect that results from GEOS-5 are relevant to other models as well.

Anisotropic shear dispersion parameterization for ocean eddy transport

NASA Astrophysics Data System (ADS)

Reckinger, Scott; Fox-Kemper, Baylor

2015-11-01

The effects of mesoscale eddies are universally treated isotropically in global ocean general circulation models. However, observations and simulations demonstrate that the mesoscale processes that the parameterization is intended to represent, such as shear dispersion, are typified by strong anisotropy. We extend the Gent-McWilliams/Redi mesoscale eddy parameterization to include anisotropy and test the effects of varying levels of anisotropy in 1-degree Community Earth System Model (CESM) simulations. Anisotropy has many effects on the simulated climate, including a reduction of temperature and salinity biases, a deepening of the southern ocean mixed-layer depth, impacts on the meridional overturning circulation and ocean energy and tracer uptake, and improved ventilation of biogeochemical tracers, particularly in oxygen minimum zones. A process-based parameterization to approximate the effects of unresolved shear dispersion is also used to set the strength and direction of anisotropy. The shear dispersion parameterization is similar to drifter observations in spatial distribution of diffusivity and high-resolution model diagnosis in the distribution of eddy flux orientation.

A unified spectral parameterization for wave breaking: From the deep ocean to the surf zone

NASA Astrophysics Data System (ADS)

Filipot, J.-F.; Ardhuin, F.

2012-11-01

A new wave-breaking dissipation parameterization designed for phase-averaged spectral wave models is presented. It combines wave breaking basic physical quantities, namely, the breaking probability and the dissipation rate per unit area. The energy lost by waves is first explicitly calculated in physical space before being distributed over the relevant spectral components. The transition from deep to shallow water is made possible by using a dissipation rate per unit area of breaking waves that varies with the wave height, wavelength and water depth. This parameterization is implemented in the WAVEWATCH III modeling framework, which is applied to a wide range of conditions and scales, from the global ocean to the beach scale. Wave height, peak and mean periods, and spectral data are validated using in situ and remote sensing data. Model errors are comparable to those of other specialized deep or shallow water parameterizations. This work shows that it is possible to have a seamless parameterization from the deep ocean to the surf zone.

The QBO in Two GISS Global Climate Models: 1. Generation of the QBO

NASA Technical Reports Server (NTRS)

Rind, David; Jonas, Jeffrey A.; Balachandra, Nambath; Schmidt, Gavin A.; Lean, Judith

2014-01-01

The adjustment of parameterized gravity waves associated with model convection and finer vertical resolution has made possible the generation of the quasi-biennial oscillation (QBO) in two Goddard Institute for Space Studies (GISS) models, GISS Middle Atmosphere Global Climate Model III and a climate/middle atmosphere version of Model E2. Both extend from the surface to 0.002 hPa, with 2deg × 2.5deg resolution and 102 layers. Many realistic features of the QBO are simulated, including magnitude and variability of its period and amplitude. The period itself is affected by the magnitude of parameterized convective gravity wave momentum fluxes and interactive ozone (which also affects the QBO amplitude and variability), among other forcings. Although varying sea surface temperatures affect the parameterized momentum fluxes, neither aspect is responsible for the modeled variation in QBO period. Both the parameterized and resolved waves act to produce the respective easterly and westerly wind descent, although their effect is offset in altitude at each level. The modeled and observed QBO influences on tracers in the stratosphere, such as ozone, methane, and water vapor are also discussed. Due to the link between the gravity wave parameterization and the models' convection, and the dependence on the ozone field, the models may also be used to investigate how the QBO may vary with climate change.

The Influence of Microphysical Cloud Parameterization on Microwave Brightness Temperatures

NASA Technical Reports Server (NTRS)

Skofronick-Jackson, Gail M.; Gasiewski, Albin J.; Wang, James R.; Zukor, Dorothy J. (Technical Monitor)

2000-01-01

The microphysical parameterization of clouds and rain-cells plays a central role in atmospheric forward radiative transfer models used in calculating passive microwave brightness temperatures. The absorption and scattering properties of a hydrometeor-laden atmosphere are governed by particle phase, size distribution, aggregate density., shape, and dielectric constant. This study identifies the sensitivity of brightness temperatures with respect to the microphysical cloud parameterization. Cloud parameterizations for wideband (6-410 GHz observations of baseline brightness temperatures were studied for four evolutionary stages of an oceanic convective storm using a five-phase hydrometeor model in a planar-stratified scattering-based radiative transfer model. Five other microphysical cloud parameterizations were compared to the baseline calculations to evaluate brightness temperature sensitivity to gross changes in the hydrometeor size distributions and the ice-air-water ratios in the frozen or partly frozen phase. The comparison shows that, enlarging the rain drop size or adding water to the partly Frozen hydrometeor mix warms brightness temperatures by up to .55 K at 6 GHz. The cooling signature caused by ice scattering intensifies with increasing ice concentrations and at higher frequencies. An additional comparison to measured Convection and Moisture LA Experiment (CAMEX 3) brightness temperatures shows that in general all but, two parameterizations produce calculated T(sub B)'s that fall within the observed clear-air minima and maxima. The exceptions are for parameterizations that, enhance the scattering characteristics of frozen hydrometeors.

Land cover characterization and land surface parameterization research

USGS Publications Warehouse

Steyaert, Louis T.; Loveland, Thomas R.; Parton, William J.

1997-01-01

The understanding of land surface processes and their parameterization in atmospheric, hydrologic, and ecosystem models has been a dominant research theme over the past decade. For example, many studies have demonstrated the key role of land cover characteristics as controlling factors in determining land surface processes, such as the exchange of water, energy, carbon, and trace gases between the land surface and the lower atmosphere. The requirements for multiresolution land cover characteristics data to support coupled-systems modeling have also been well documented, including the need for data on land cover type, land use, and many seasonally variable land cover characteristics, such as albedo, leaf area index, canopy conductance, surface roughness, and net primary productivity. Recently, the developers of land data have worked more closely with the land surface process modelers in these efforts.

Constraints to Dark Energy Using PADE Parameterizations

NASA Astrophysics Data System (ADS)

Rezaei, M.; Malekjani, M.; Basilakos, S.; Mehrabi, A.; Mota, D. F.

2017-07-01

We put constraints on dark energy (DE) properties using PADE parameterization, and compare it to the same constraints using Chevalier-Polarski-Linder (CPL) and ΛCDM, at both the background and the perturbation levels. The DE equation of the state parameter of the models is derived following the mathematical treatment of PADE expansion. Unlike CPL parameterization, PADE approximation provides different forms of the equation of state parameter that avoid the divergence in the far future. Initially we perform a likelihood analysis in order to put constraints on the model parameters using solely background expansion data, and we find that all parameterizations are consistent with each other. Then, combining the expansion and the growth rate data, we test the viability of PADE parameterizations and compare them with CPL and ΛCDM models, respectively. Specifically, we find that the growth rate of the current PADE parameterizations is lower than ΛCDM model at low redshifts, while the differences among the models are negligible at high redshifts. In this context, we provide for the first time a growth index of linear matter perturbations in PADE cosmologies. Considering that DE is homogeneous, we recover the well-known asymptotic value of the growth index (namely {γ }∞ =\\tfrac{3({w}∞ -1)}{6{w}∞ -5}), while in the case of clustered DE, we obtain {γ }∞ ≃ \\tfrac{3{w}∞ (3{w}∞ -5)}{(6{w}∞ -5)(3{w}∞ -1)}. Finally, we generalize the growth index analysis in the case where γ is allowed to vary with redshift, and we find that the form of γ (z) in PADE parameterization extends that of the CPL and ΛCDM cosmologies, respectively.

Mineral solubilities in the Na-K-Mg-Ca-Cl-SO 4-H 2O system: a re-evaluation of the sulfate chemistry in the Spencer-Møller-Weare model

NASA Astrophysics Data System (ADS)

Marion, Giles M.; Farren, Ronald E.

1999-05-01

The Spencer-Møller-Weare (SMW) (1990) model is parameterized for the Na-K-Mg-Ca-Cl-SO 4-H 2O system over the temperature range from -60° to 25°C. This model is one of the few complex chemical equilibrium models for aqueous solutions parameterized for subzero temperatures. The primary focus of the SMW model parameterization and validation deals with chloride systems. There are problems with the sulfate parameterization of the SMW model, most notably with sodium sulfate and magnesium sulfate. The primary objective of this article is to re-estimate the Pitzer-equation parameters governing interactions among sodium, potassium, magnesium, and calcium with sulfate in the SMW model. A mathematical algorithm is developed to estimate 22 temperature-dependent Pitzer-equation parameters. The sodium sulfate reparameterization reduces the overall standard error (SE) from 0.393 with the SMW Pitzer-equation parameters to 0.155. Similarly, the magnesium sulfate reparameterization reduces the SE from 0.335 to 0.124. In addition to the sulfate reparameterization, five additional sulfate minerals are included in the model, which allows a more complete treatment of sulfate chemistry in the Na-K-Mg-Ca-Cl-SO 4-H 2O system. Application of the model to seawater evaporation predicts gypsum precipitation at a seawater concentration factor (SCF) of 3.37 and halite precipitation at an SCF of 10.56, which are in good agreement with previous experimental and theoretical estimates. Application of the model to seawater freezing helps explain the two pathways for seawater freezing. Along the thermodynamically stable "Gitterman pathway," calcium precipitates as gypsum and the seawater eutectic is -36.2°C. Along the metastable "Ringer-Nelson-Thompson pathway," calcium precipitates as antarcticite and the seawater eutectic is -53.8°C.

Modeling of ultrasonic processes utilizing a generic software framework

NASA Astrophysics Data System (ADS)

Bruns, P.; Twiefel, J.; Wallaschek, J.

2017-06-01

Modeling of ultrasonic processes is typically characterized by a high degree of complexity. Different domains and size scales must be regarded, so that it is rather difficult to build up a single detailed overall model. Developing partial models is a common approach to overcome this difficulty. In this paper a generic but simple software framework is presented which allows to coupe arbitrary partial models by slave modules with well-defined interfaces and a master module for coordination. Two examples are given to present the developed framework. The first one is the parameterization of a load model for ultrasonically-induced cavitation. The piezoelectric oscillator, its mounting, and the process load are described individually by partial models. These partial models then are coupled using the framework. The load model is composed of spring-damper-elements which are parameterized by experimental results. In the second example, the ideal mounting position for an oscillator utilized in ultrasonic assisted machining of stone is determined. Partial models for the ultrasonic oscillator, its mounting, the simplified contact process, and the workpiece’s material characteristics are presented. For both applications input and output variables are defined to meet the requirements of the framework’s interface.

Confronting Models with Data: The GEWEX Cloud Systems Study

NASA Technical Reports Server (NTRS)

Randall, David; Curry, Judith; Duynkerke, Peter; Krueger, Steven; Moncrieff, Mitchell; Ryan, Brian; Starr, David OC.; Miller, Martin; Rossow, William; Tselioudis, George

2002-01-01

The GEWEX Cloud System Study (GCSS; GEWEX is the Global Energy and Water Cycle Experiment) was organized to promote development of improved parameterizations of cloud systems for use in climate and numerical weather prediction models, with an emphasis on the climate applications. The strategy of GCSS is to use two distinct kinds of models to analyze and understand observations of the behavior of several different types of clouds systems. Cloud-system-resolving models (CSRMs) have high enough spatial and temporal resolutions to represent individual cloud elements, but cover a wide enough range of space and time scales to permit statistical analysis of simulated cloud systems. Results from CSRMs are compared with detailed observations, representing specific cases based on field experiments, and also with statistical composites obtained from satellite and meteorological analyses. Single-column models (SCMs) are the surgically extracted column physics of atmospheric general circulation models. SCMs are used to test cloud parameterizations in an un-coupled mode, by comparison with field data and statistical composites. In the original GCSS strategy, data is collected in various field programs and provided to the CSRM Community, which uses the data to "certify" the CSRMs as reliable tools for the simulation of particular cloud regimes, and then uses the CSRMs to develop parameterizations, which are provided to the GCM Community. We report here the results of a re-thinking of the scientific strategy of GCSS, which takes into account the practical issues that arise in confronting models with data. The main elements of the proposed new strategy are a more active role for the large-scale modeling community, and an explicit recognition of the importance of data integration.

On parameterization of the inverse problem for estimating aquifer properties using tracer data

NASA Astrophysics Data System (ADS)

Kowalsky, M. B.; Finsterle, S.; Williams, K. H.; Murray, C.; Commer, M.; Newcomer, D.; Englert, A.; Steefel, C. I.; Hubbard, S. S.

2012-06-01

In developing a reliable approach for inferring hydrological properties through inverse modeling of tracer data, decisions made on how to parameterize heterogeneity (i.e., how to represent a heterogeneous distribution using a limited number of parameters that are amenable to estimation) are of paramount importance, as errors in the model structure are partly compensated for by estimating biased property values during the inversion. These biased estimates, while potentially providing an improved fit to the calibration data, may lead to wrong interpretations and conclusions and reduce the ability of the model to make reliable predictions. We consider the estimation of spatial variations in permeability and several other parameters through inverse modeling of tracer data, specifically synthetic and actual field data associated with the 2007 Winchester experiment from the Department of Energy Rifle site. Characterization is challenging due to the real-world complexities associated with field experiments in such a dynamic groundwater system. Our aim is to highlight and quantify the impact on inversion results of various decisions related to parameterization, such as the positioning of pilot points in a geostatistical parameterization; the handling of up-gradient regions; the inclusion of zonal information derived from geophysical data or core logs; extension from 2-D to 3-D; assumptions regarding the gradient direction, porosity, and the semivariogram function; and deteriorating experimental conditions. This work adds to the relatively limited number of studies that offer guidance on the use of pilot points in complex real-world experiments involving tracer data (as opposed to hydraulic head data).

Bioaccumulation and Aquatic System Simulator (BASS) User's Manual Beta Test Version 2.1. EPA/600/R-01/035

EPA Pesticide Factsheets

this report describes the theoretical development, parameterization, and application software of a generalized, community-based, bioaccumulation model called BASS (Bioaccumulation and Aquatic System Simulator).

DOE Office of Scientific and Technical Information (OSTI.GOV)

Wong, Raymond K. W.; Storlie, Curtis Byron; Lee, Thomas C. M.

The paper considers the computer model calibration problem and provides a general frequentist solution. Under the framework proposed, the data model is semiparametric with a non-parametric discrepancy function which accounts for any discrepancy between physical reality and the computer model. In an attempt to solve a fundamentally important (but often ignored) identifiability issue between the computer model parameters and the discrepancy function, the paper proposes a new and identifiable parameterization of the calibration problem. It also develops a two-step procedure for estimating all the relevant quantities under the new parameterization. This estimation procedure is shown to enjoy excellent rates ofmore » convergence and can be straightforwardly implemented with existing software. For uncertainty quantification, bootstrapping is adopted to construct confidence regions for the quantities of interest. As a result, the practical performance of the methodology is illustrated through simulation examples and an application to a computational fluid dynamics model.« less

Continuous piecewise-linear, reduced-order electrochemical model for lithium-ion batteries in real-time applications

NASA Astrophysics Data System (ADS)

Farag, Mohammed; Fleckenstein, Matthias; Habibi, Saeid

2017-02-01

Model-order reduction and minimization of the CPU run-time while maintaining the model accuracy are critical requirements for real-time implementation of lithium-ion electrochemical battery models. In this paper, an isothermal, continuous, piecewise-linear, electrode-average model is developed by using an optimal knot placement technique. The proposed model reduces the univariate nonlinear function of the electrode's open circuit potential dependence on the state of charge to continuous piecewise regions. The parameterization experiments were chosen to provide a trade-off between extensive experimental characterization techniques and purely identifying all parameters using optimization techniques. The model is then parameterized in each continuous, piecewise-linear, region. Applying the proposed technique cuts down the CPU run-time by around 20%, compared to the reduced-order, electrode-average model. Finally, the model validation against real-time driving profiles (FTP-72, WLTP) demonstrates the ability of the model to predict the cell voltage accurately with less than 2% error.

Parameterization and sensitivity analyses of a radiative transfer model for remote sensing plant canopies

NASA Astrophysics Data System (ADS)

Hall, Carlton Raden

A major objective of remote sensing is determination of biochemical and biophysical characteristics of plant canopies utilizing high spectral resolution sensors. Canopy reflectance signatures are dependent on absorption and scattering processes of the leaf, canopy properties, and the ground beneath the canopy. This research investigates, through field and laboratory data collection, and computer model parameterization and simulations, the relationships between leaf optical properties, canopy biophysical features, and the nadir viewed above-canopy reflectance signature. Emphasis is placed on parameterization and application of an existing irradiance radiative transfer model developed for aquatic systems. Data and model analyses provide knowledge on the relative importance of leaves and canopy biophysical features in estimating the diffuse absorption a(lambda,m-1), diffuse backscatter b(lambda,m-1), beam attenuation alpha(lambda,m-1), and beam to diffuse conversion c(lambda,m-1 ) coefficients of the two-flow irradiance model. Data sets include field and laboratory measurements from three plant species, live oak (Quercus virginiana), Brazilian pepper (Schinus terebinthifolius) and grapefruit (Citrus paradisi) sampled on Cape Canaveral Air Force Station and Kennedy Space Center Florida in March and April of 1997. Features measured were depth h (m), projected foliage coverage PFC, leaf area index LAI, and zenith leaf angle. Optical measurements, collected with a Spectron SE 590 high sensitivity narrow bandwidth spectrograph, included above canopy reflectance, internal canopy transmittance and reflectance and bottom reflectance. Leaf samples were returned to laboratory where optical and physical and chemical measurements of leaf thickness, leaf area, leaf moisture and pigment content were made. A new term, the leaf volume correction index LVCI was developed and demonstrated in support of model coefficient parameterization. The LVCI is based on angle adjusted leaf thickness Ltadj, LAI, and h (m). Its function is to translate leaf level estimates of diffuse absorption and backscatter to the canopy scale allowing the leaf optical properties to directly influence above canopy estimates of reflectance. The model was successfully modified and parameterized to operate in a canopy scale and a leaf scale mode. Canopy scale model simulations produced the best results. Simulations based on leaf derived coefficients produced calculated above canopy reflectance errors of 15% to 18%. A comprehensive sensitivity analyses indicated the most important parameters were beam to diffuse conversion c(lambda, m-1), diffuse absorption a(lambda, m-1), diffuse backscatter b(lambda, m-1), h (m), Q, and direct and diffuse irradiance. Sources of error include the estimation procedure for the direct beam to diffuse conversion and attenuation coefficients and other field and laboratory measurement and analysis errors. Applications of the model include creation of synthetic reflectance data sets for remote sensing algorithm development, simulations of stress and drought on vegetation reflectance signatures, and the potential to estimate leaf moisture and chemical status.

Data-driven RBE parameterization for helium ion beams

NASA Astrophysics Data System (ADS)

Mairani, A.; Magro, G.; Dokic, I.; Valle, S. M.; Tessonnier, T.; Galm, R.; Ciocca, M.; Parodi, K.; Ferrari, A.; Jäkel, O.; Haberer, T.; Pedroni, P.; Böhlen, T. T.

2016-01-01

Helium ion beams are expected to be available again in the near future for clinical use. A suitable formalism to obtain relative biological effectiveness (RBE) values for treatment planning (TP) studies is needed. In this work we developed a data-driven RBE parameterization based on published in vitro experimental values. The RBE parameterization has been developed within the framework of the linear-quadratic (LQ) model as a function of the helium linear energy transfer (LET), dose and the tissue specific parameter {{(α /β )}\\text{ph}} of the LQ model for the reference radiation. Analytic expressions are provided, derived from the collected database, describing the \\text{RB}{{\\text{E}}α}={α\\text{He}}/{α\\text{ph}} and {{\\text{R}}β}={β\\text{He}}/{β\\text{ph}} ratios as a function of LET. Calculated RBE values at 2 Gy photon dose and at 10% survival (\\text{RB}{{\\text{E}}10} ) are compared with the experimental ones. Pearson’s correlation coefficients were, respectively, 0.85 and 0.84 confirming the soundness of the introduced approach. Moreover, due to the lack of experimental data at low LET, clonogenic experiments have been performed irradiating A549 cell line with {{(α /β )}\\text{ph}}=5.4 Gy at the entrance of a 56.4 MeV u-1He beam at the Heidelberg Ion Beam Therapy Center. The proposed parameterization reproduces the measured cell survival within the experimental uncertainties. A RBE formula, which depends only on dose, LET and {{(α /β )}\\text{ph}} as input parameters is proposed, allowing a straightforward implementation in a TP system.

Assessing the CAM5 Physics Suite in the WRF-Chem Model: Implementation, Resolution Sensitivity, and a First Evaluation for a Regional Case Study

DOE Office of Scientific and Technical Information (OSTI.GOV)

Ma, Po-Lun; Rasch, Philip J.; Fast, Jerome D.

A suite of physical parameterizations (deep and shallow convection, turbulent boundary layer, aerosols, cloud microphysics, and cloud fraction) from the global climate model Community Atmosphere Model version 5.1 (CAM5) has been implemented in the regional model Weather Research and Forecasting with chemistry (WRF-Chem). A downscaling modeling framework with consistent physics has also been established in which both global and regional simulations use the same emissions and surface fluxes. The WRF-Chem model with the CAM5 physics suite is run at multiple horizontal resolutions over a domain encompassing the northern Pacific Ocean, northeast Asia, and northwest North America for April 2008 whenmore » the ARCTAS, ARCPAC, and ISDAC field campaigns took place. These simulations are evaluated against field campaign measurements, satellite retrievals, and ground-based observations, and are compared with simulations that use a set of common WRF-Chem Parameterizations. This manuscript describes the implementation of the CAM5 physics suite in WRF-Chem provides an overview of the modeling framework and an initial evaluation of the simulated meteorology, clouds, and aerosols, and quantifies the resolution dependence of the cloud and aerosol parameterizations. We demonstrate that some of the CAM5 biases, such as high estimates of cloud susceptibility to aerosols and the underestimation of aerosol concentrations in the Arctic, can be reduced simply by increasing horizontal resolution. We also show that the CAM5 physics suite performs similarly to a set of parameterizations commonly used in WRF-Chem, but produces higher ice and liquid water condensate amounts and near-surface black carbon concentration. Further evaluations that use other mesoscale model parameterizations and perform other case studies are needed to infer whether one parameterization consistently produces results more consistent with observations.« less

Evaluation of NASA GISS post-CMIP5 single column model simulated clouds and precipitation using ARM Southern Great Plains observations

NASA Astrophysics Data System (ADS)

Zhang, Lei; Dong, Xiquan; Kennedy, Aaron; Xi, Baike; Li, Zhanqing

2017-03-01

The planetary boundary layer turbulence and moist convection parameterizations have been modified recently in the NASA Goddard Institute for Space Studies (GISS) Model E2 atmospheric general circulation model (GCM; post-CMIP5, hereafter P5). In this study, single column model (SCM P5) simulated cloud fractions (CFs), cloud liquid water paths (LWPs) and precipitation were compared with Atmospheric Radiation Measurement (ARM) Southern Great Plains (SGP) groundbased observations made during the period 2002-08. CMIP5 SCM simulations and GCM outputs over the ARM SGP region were also used in the comparison to identify whether the causes of cloud and precipitation biases resulted from either the physical parameterization or the dynamic scheme. The comparison showed that the CMIP5 SCM has difficulties in simulating the vertical structure and seasonal variation of low-level clouds. The new scheme implemented in the turbulence parameterization led to significantly improved cloud simulations in P5. It was found that the SCM is sensitive to the relaxation time scale. When the relaxation time increased from 3 to 24 h, SCM P5-simulated CFs and LWPs showed a moderate increase (10%-20%) but precipitation increased significantly (56%), which agreed better with observations despite the less accurate atmospheric state. Annual averages among the GCM and SCM simulations were almost the same, but their respective seasonal variations were out of phase. This suggests that the same physical cloud parameterization can generate similar statistical results over a long time period, but different dynamics drive the differences in seasonal variations. This study can potentially provide guidance for the further development of the GISS model.

Simulating Ice Dynamics in the Amundsen Sea Sector

NASA Astrophysics Data System (ADS)

Schwans, E.; Parizek, B. R.; Morlighem, M.; Alley, R. B.; Pollard, D.; Walker, R. T.; Lin, P.; St-Laurent, P.; LaBirt, T.; Seroussi, H. L.

2017-12-01

Thwaites and Pine Island Glaciers (TG; PIG) exhibit patterns of dynamic retreat forced from their floating margins, and could act as gateways for destabilization of deep marine basins in the West Antarctic Ice Sheet (WAIS). Poorly constrained basal conditions can cause model predictions to diverge. Thus, there is a need for efficient simulations that account for shearing within the ice column, and include adequate basal sliding and ice-shelf melting parameterizations. To this end, UCI/NASA JPL's Ice Sheet System Model (ISSM) with coupled SSA/higher-order physics is used in the Amundsen Sea Embayment (ASE) to examine threshold behavior of TG and PIG, highlighting areas particularly vulnerable to retreat from oceanic warming and ice-shelf removal. These moving-front experiments will aid in targeting critical areas for additional data collection in ASE as well as for weighting accuracy in further melt parameterization development. Furthermore, a sub-shelf melt parameterization, resulting from Regional Ocean Modeling System (ROMS; St-Laurent et al., 2015) and coupled ISSM-Massachusetts Institute of Technology general circulation model (MITgcm; Seroussi et al., 2017) output, is incorporated and initially tested in ISSM. Data-guided experiments include variable basal conditions and ice hardness, and are also forced with constant modern climate in ISSM, providing valuable insight into i) effects of different basal friction parameterizations on ice dynamics, illustrating the importance of constraining the variable bed character beneath TG and PIG; ii) the impact of including vertical shear in ice flow models of outlet glaciers, confirming its role in capturing complex feedbacks proximal to the grounding zone; and iii) ASE's sensitivity to sub-shelf melt and ice-front retreat, possible thresholds, and how these affect ice-flow evolution.

Phenology and density-dependent dispersal predict patterns of mountain pine beetle (Dendroctonus ponderosae) impact

Treesearch

James A. Powell; Barbara J. Bentz

2014-01-01

For species with irruptive population behavior, dispersal is an important component of outbreak dynamics. We developed and parameterized a mechanistic model describing mountain pine beetle (Dendroctonus ponderosae Hopkins) population demographics and dispersal across a landscape. Model components include temperature-dependent phenology, host tree colonization...

QUANTIFYING AN UNCERTAIN FUTURE: HYDROLOGIC MODEL PERFORMANCE FOR A SERIES OF REALIZED "FUTURE" CONDITIONS

EPA Science Inventory

GIS-based hydrologic modeling offers a convenient means of assessing the impacts associated with land-cover/use change for environmental planning efforts. Future scenarios can be developed through a combination of modifications to the land-cover/use maps used to parameterize hydr...

Applying the Principles of Specific Objectivity and of Generalizability to the Measurement of Change.

ERIC Educational Resources Information Center

Fischer, Gerhard H.

1987-01-01

A natural parameterization and formalization of the problem of measuring change in dichotomous data is developed. Mathematically-exact definitions of specific objectivity are presented, and the basic structures of the linear logistic test model and the linear logistic model with relaxed assumptions are clarified. (SLD)

Ecophysiological parameters for Pacific Northwest trees.

Treesearch

Amy E. Hessl; Cristina Milesi; Michael A. White; David L. Peterson; Robert E. Keane

2004-01-01

We developed a species- and location-specific database of published ecophysiological variables typically used as input parameters for biogeochemical models of coniferous and deciduous forested ecosystems in the Western United States. Parameters are based on the requirements of Biome-BGC, a widely used biogeochemical model that was originally parameterized for the...

SENSITIVITY OF THE NATIONAL OCEANIC AND ATMOSPHERIC ADMINISTRATION MULTILAYER MODEL TO INSTRUMENT ERROR AND PARAMETERIZATION UNCERTAINTY

EPA Science Inventory

The response of the National Oceanic and Atmospheric Administration multilayer inferential dry deposition velocity model (NOAA-MLM) to error in meteorological inputs and model parameterization is reported. Monte Carlo simulations were performed to assess the uncertainty in NOA...

Improved parameterization for the vertical flux of dust aerosols emitted by an eroding soil

USDA-ARS?s Scientific Manuscript database

The representation of the dust cycle in atmospheric circulation models hinges on an accurate parameterization of the vertical dust flux at emission. However, existing parameterizations of the vertical dust flux vary substantially in their scaling with wind friction velocity, require input parameters...

The effects of surface evaporation parameterizations on climate sensitivity to solar constant variations

NASA Technical Reports Server (NTRS)

Chou, S.-H.; Curran, R. J.; Ohring, G.

1981-01-01

The effects of two different evaporation parameterizations on the sensitivity of simulated climate to solar constant variations are investigated by using a zonally averaged climate model. One parameterization is a nonlinear formulation in which the evaporation is nonlinearly proportional to the sensible heat flux, with the Bowen ratio determined by the predicted vertical temperature and humidity gradients near the earth's surface (model A). The other is the formulation of Saltzman (1968) with the evaporation linearly proportional to the sensible heat flux (model B). The computed climates of models A and B are in good agreement except for the energy partition between sensible and latent heat at the earth's surface. The difference in evaporation parameterizations causes a difference in the response of temperature lapse rate to solar constant variations and a difference in the sensitivity of longwave radiation to surface temperature which leads to a smaller sensitivity of surface temperature to solar constant variations in model A than in model B. The results of model A are qualitatively in agreement with those of the general circulation model calculations of Wetherald and Manabe (1975).

Current state of aerosol nucleation parameterizations for air-quality and climate modeling

NASA Astrophysics Data System (ADS)

Semeniuk, Kirill; Dastoor, Ashu

2018-04-01

Aerosol nucleation parameterization models commonly used in 3-D air quality and climate models have serious limitations. This includes classical nucleation theory based variants, empirical models and other formulations. Recent work based on detailed and extensive laboratory measurements and improved quantum chemistry computation has substantially advanced the state of nucleation parameterizations. In terms of inorganic nucleation involving BHN and THN including ion effects these new models should be considered as worthwhile replacements for the old models. However, the contribution of organic species to nucleation remains poorly quantified. New particle formation consists of a distinct post-nucleation growth regime which is characterized by a strong Kelvin curvature effect and is thus dependent on availability of very low volatility organic species or sulfuric acid. There have been advances in the understanding of the multiphase chemistry of biogenic and anthropogenic organic compounds which facilitate to overcome the initial aerosol growth barrier. Implementation of processes influencing new particle formation is challenging in 3-D models and there is a lack of comprehensive parameterizations. This review considers the existing models and recent innovations.

The relationship between a deformation-based eddy parameterization and the LANS-α turbulence model

NASA Astrophysics Data System (ADS)

Bachman, Scott D.; Anstey, James A.; Zanna, Laure

2018-06-01

A recent class of ocean eddy parameterizations proposed by Porta Mana and Zanna (2014) and Anstey and Zanna (2017) modeled the large-scale flow as a non-Newtonian fluid whose subgridscale eddy stress is a nonlinear function of the deformation. This idea, while largely new to ocean modeling, has a history in turbulence modeling dating at least back to Rivlin (1957). The new class of parameterizations results in equations that resemble the Lagrangian-averaged Navier-Stokes-α model (LANS-α, e.g., Holm et al., 1998a). In this note we employ basic tensor mathematics to highlight the similarities between these turbulence models using component-free notation. We extend the Anstey and Zanna (2017) parameterization, which was originally presented in 2D, to 3D, and derive variants of this closure that arise when the full non-Newtonian stress tensor is used. Despite the mathematical similarities between the non-Newtonian and LANS-α models which might provide insight into numerical implementation, the input and dissipation of kinetic energy between these two turbulent models differ.

A physiologically based toxicokinetic model for lake trout (Salvelinus namaycush).

PubMed

Lien, G J; McKim, J M; Hoffman, A D; Jenson, C T

2001-01-01

A physiologically based toxicokinetic (PB-TK) model for fish, incorporating chemical exchange at the gill and accumulation in five tissue compartments, was parameterized and evaluated for lake trout (Salvelinus namaycush). Individual-based model parameterization was used to examine the effect of natural variability in physiological, morphological, and physico-chemical parameters on model predictions. The PB-TK model was used to predict uptake of organic chemicals across the gill and accumulation in blood and tissues in lake trout. To evaluate the accuracy of the model, a total of 13 adult lake trout were exposed to waterborne 1,1,2,2-tetrachloroethane (TCE), pentachloroethane (PCE), and hexachloroethane (HCE), concurrently, for periods of 6, 12, 24 or 48 h. The measured and predicted concentrations of TCE, PCE and HCE in expired water, dorsal aortic blood and tissues were generally within a factor of two, and in most instances much closer. Variability noted in model predictions, based on the individual-based model parameterization used in this study, reproduced variability observed in measured concentrations. The inference is made that parameters influencing variability in measured blood and tissue concentrations of xenobiotics are included and accurately represented in the model. This model contributes to a better understanding of the fundamental processes that regulate the uptake and disposition of xenobiotic chemicals in the lake trout. This information is crucial to developing a better understanding of the dynamic relationships between contaminant exposure and hazard to the lake trout.

The GEOS-5 Atmospheric General Circulation Model: Mean Climate and Development from MERRA to Fortuna

NASA Technical Reports Server (NTRS)

Molod, Andrea; Takacs, Lawrence; Suarez, Max; Bacmeister, Julio; Song, In-Sun; Eichmann, Andrew

2012-01-01

This report is a documentation of the Fortuna version of the GEOS-5 Atmospheric General Circulation Model (AGCM). The GEOS-5 AGCM is currently in use in the NASA Goddard Modeling and Assimilation Office (GMAO) for simulations at a wide range of resolutions, in atmosphere only, coupled ocean-atmosphere, and data assimilation modes. The focus here is on the development subsequent to the version that was used as part of NASA s Modern-Era Retrospective Analysis for Research and Applications (MERRA). We present here the results of a series of 30-year atmosphere-only simulations at different resolutions, with focus on the behavior of the 1-degree resolution simulation. The details of the changes in parameterizations subsequent to the MERRA model version are outlined, and results of a series of 30-year, atmosphere-only climate simulations at 2-degree resolution are shown to demonstrate changes in simulated climate associated with specific changes in parameterizations. The GEOS-5 AGCM presented here is the model used for the GMAO s atmosphere-only and coupled CMIP-5 simulations.

The "Grey Zone" cold air outbreak global model intercomparison: A cross evaluation using large-eddy simulations

NASA Astrophysics Data System (ADS)

Tomassini, Lorenzo; Field, Paul R.; Honnert, Rachel; Malardel, Sylvie; McTaggart-Cowan, Ron; Saitou, Kei; Noda, Akira T.; Seifert, Axel

2017-03-01

A stratocumulus-to-cumulus transition as observed in a cold air outbreak over the North Atlantic Ocean is compared in global climate and numerical weather prediction models and a large-eddy simulation model as part of the Working Group on Numerical Experimentation "Grey Zone" project. The focus of the project is to investigate to what degree current convection and boundary layer parameterizations behave in a scale-adaptive manner in situations where the model resolution approaches the scale of convection. Global model simulations were performed at a wide range of resolutions, with convective parameterizations turned on and off. The models successfully simulate the transition between the observed boundary layer structures, from a well-mixed stratocumulus to a deeper, partly decoupled cumulus boundary layer. There are indications that surface fluxes are generally underestimated. The amount of both cloud liquid water and cloud ice, and likely precipitation, are under-predicted, suggesting deficiencies in the strength of vertical mixing in shear-dominated boundary layers. But also regulation by precipitation and mixed-phase cloud microphysical processes play an important role in the case. With convection parameterizations switched on, the profiles of atmospheric liquid water and cloud ice are essentially resolution-insensitive. This, however, does not imply that convection parameterizations are scale-aware. Even at the highest resolutions considered here, simulations with convective parameterizations do not converge toward the results of convection-off experiments. Convection and boundary layer parameterizations strongly interact, suggesting the need for a unified treatment of convective and turbulent mixing when addressing scale-adaptivity.

Remote Sensing of Soil Moisture: A Comparison of Optical and Thermal Methods

NASA Astrophysics Data System (ADS)

Foroughi, H.; Naseri, A. A.; Boroomandnasab, S.; Sadeghi, M.; Jones, S. B.; Tuller, M.; Babaeian, E.

2017-12-01

Recent technological advances in satellite and airborne remote sensing have provided new means for large-scale soil moisture monitoring. Traditional methods for soil moisture retrieval require thermal and optical RS observations. In this study we compared the traditional trapezoid model parameterized based on the land surface temperature - normalized difference vegetation index (LST-NDVI) space with the recently developed optical trapezoid model OPTRAM parameterized based on the shortwave infrared transformed reflectance (STR)-NDVI space for an extensive sugarcane field located in Southwestern Iran. Twelve Landsat-8 satellite images were acquired during the sugarcane growth season (April to October 2016). Reference in situ soil moisture data were obtained at 22 locations at different depths via core sampling and oven-drying. The obtained results indicate that the thermal/optical and optical prediction methods are comparable, both with volumetric moisture content estimation errors of about 0.04 cm3 cm-3. However, the OPTRAM model is more efficient because it does not require thermal data and can be universally parameterized for a specific location, because unlike the LST-soil moisture relationship, the reflectance-soil moisture relationship does not significantly vary with environmental variables (e.g., air temperature, wind speed, etc.).

A stochastic parameterization for deep convection using cellular automata

NASA Astrophysics Data System (ADS)

Bengtsson, L.; Steinheimer, M.; Bechtold, P.; Geleyn, J.

2012-12-01

Cumulus parameterizations used in most operational weather and climate models today are based on the mass-flux concept which took form in the early 1970's. In such schemes it is assumed that a unique relationship exists between the ensemble-average of the sub-grid convection, and the instantaneous state of the atmosphere in a vertical grid box column. However, such a relationship is unlikely to be described by a simple deterministic function (Palmer, 2011). Thus, because of the statistical nature of the parameterization challenge, it has been recognized by the community that it is important to introduce stochastic elements to the parameterizations (for instance: Plant and Craig, 2008, Khouider et al. 2010, Frenkel et al. 2011, Bentsson et al. 2011, but the list is far from exhaustive). There are undoubtedly many ways in which stochastisity can enter new developments. In this study we use a two-way interacting cellular automata (CA), as its intrinsic nature possesses many qualities interesting for deep convection parameterization. In the one-dimensional entraining plume approach, there is no parameterization of horizontal transport of heat, moisture or momentum due to cumulus convection. In reality, mass transport due to gravity waves that propagate in the horizontal can trigger new convection, important for the organization of deep convection (Huang, 1988). The self-organizational characteristics of the CA allows for lateral communication between adjacent NWP model grid-boxes, and temporal memory. Thus the CA scheme used in this study contain three interesting components for representation of cumulus convection, which are not present in the traditional one-dimensional bulk entraining plume method: horizontal communication, memory and stochastisity. The scheme is implemented in the high resolution regional NWP model ALARO, and simulations show enhanced organization of convective activity along squall-lines. Probabilistic evaluation demonstrate an enhanced spread in large-scale variables in regions where convective activity is large. A two month extended evaluation of the deterministic behaviour of the scheme indicate a neutral impact on forecast skill. References: Bengtsson, L., H. Körnich, E. Källén, and G. Svensson, 2011: Large-scale dynamical response to sub-grid scale organization provided by cellular automata. Journal of the Atmospheric Sciences, 68, 3132-3144. Frenkel, Y., A. Majda, and B. Khouider, 2011: Using the stochastic multicloud model to improve tropical convective parameterization: A paradigm example. Journal of the Atmospheric Sciences, doi: 10.1175/JAS-D-11-0148.1. Huang, X.-Y., 1988: The organization of moist convection by internal 365 gravity waves. Tellus A, 42, 270-285. Khouider, B., J. Biello, and A. Majda, 2010: A Stochastic Multicloud Model for Tropical Convection. Comm. Math. Sci., 8, 187-216. Palmer, T., 2011: Towards the Probabilistic Earth-System Simulator: A Vision for the Future of Climate and Weather Prediction. Quarterly Journal of the Royal Meteorological Society 138 (2012) 841-861 Plant, R. and G. Craig, 2008: A stochastic parameterization for deep convection based on equilibrium statistics. J. Atmos. Sci., 65, 87-105.

Foliage Density Distribution and Prediction of Intensively Managed Loblolly Pine

Treesearch

Yujia Zhang; Bruce E. Borders; Rodney E. Will; Hector De Los Santos Posadas

2004-01-01

The pipe model theory says that foliage biomass is proportional to the sapwood area at the base of the live crown. This knowledge was incorporated in an effort to develop a foliage biomass prediction model from integrating a stipulated foliage biomass distribution function within the crown. This model was parameterized using data collected from intensively managed...

Impact of APEX parameterization and soil data on runoff, sediment, and nutrients transport assessment

USDA-ARS?s Scientific Manuscript database

Hydrological models have become essential tools for environmental assessments. This study’s objective was to evaluate a best professional judgment (BPJ) parameterization of the Agricultural Policy and Environmental eXtender (APEX) model with soil-survey data against the calibrated model with either ...

Parameterization guidelines and considerations for hydrologic models

USDA-ARS?s Scientific Manuscript database

Imparting knowledge of the physical processes of a system to a model and determining a set of parameter values for a hydrologic or water quality model application (i.e., parameterization) is an important and difficult task. An exponential increase in literature has been devoted to the use and develo...

Summary of Cumulus Parameterization Workshop

NASA Technical Reports Server (NTRS)

Tao, Wei-Kuo; Starr, David OC.; Hou, Arthur; Newman, Paul; Sud, Yogesh

2002-01-01

A workshop on cumulus parameterization took place at the NASA Goddard Space Flight Center from December 3-5, 2001. The major objectives of this workshop were (1) to review the problem of representation of moist processes in large-scale models (mesoscale models, Numerical Weather Prediction models and Atmospheric General Circulation Models), (2) to review the state-of-the-art in cumulus parameterization schemes, and (3) to discuss the need for future research and applications. There were a total of 31 presentations and about 100 participants from the United States, Japan, the United Kingdom, France and South Korea. The specific presentations and discussions during the workshop are summarized in this paper.

Solid, liquid, and interfacial properties of TiAl alloys: parameterization of a new modified embedded atom method model

NASA Astrophysics Data System (ADS)

Sun, Shoutian; Ramu Ramachandran, Bala; Wick, Collin D.

2018-02-01

New interatomic potentials for pure Ti and Al, and binary TiAl were developed utilizing the second nearest neighbour modified embedded-atom method (MEAM) formalism. The potentials were parameterized to reproduce multiple properties spanning bulk solids, solid surfaces, solid/liquid phase changes, and liquid interfacial properties. This was carried out using a newly developed optimization procedure that combined the simple minimization of a fitness function with a genetic algorithm to efficiently span the parameter space. The resulting MEAM potentials gave good agreement with experimental and DFT solid and liquid properties, and reproduced the melting points for Ti, Al, and TiAl. However, the surface tensions from the model consistently underestimated experimental values. Liquid TiAl’s surface was found to be mostly covered with Al atoms, showing that Al has a significant propensity for the liquid/air interface.

Solid, liquid, and interfacial properties of TiAl alloys: parameterization of a new modified embedded atom method model.

PubMed

Sun, Shoutian; Ramachandran, Bala Ramu; Wick, Collin D

2018-02-21

New interatomic potentials for pure Ti and Al, and binary TiAl were developed utilizing the second nearest neighbour modified embedded-atom method (MEAM) formalism. The potentials were parameterized to reproduce multiple properties spanning bulk solids, solid surfaces, solid/liquid phase changes, and liquid interfacial properties. This was carried out using a newly developed optimization procedure that combined the simple minimization of a fitness function with a genetic algorithm to efficiently span the parameter space. The resulting MEAM potentials gave good agreement with experimental and DFT solid and liquid properties, and reproduced the melting points for Ti, Al, and TiAl. However, the surface tensions from the model consistently underestimated experimental values. Liquid TiAl's surface was found to be mostly covered with Al atoms, showing that Al has a significant propensity for the liquid/air interface.

Modeling the Complex Photochemistry of Biomass Burning Plumes in Plume-Scale, Regional, and Global Air Quality Models

NASA Astrophysics Data System (ADS)

Alvarado, M. J.; Lonsdale, C. R.; Yokelson, R. J.; Travis, K.; Fischer, E. V.; Lin, J. C.

2014-12-01

Forecasting the impacts of biomass burning (BB) plumes on air quality is difficult due to the complex photochemistry that takes place in the concentrated young BB plumes. The spatial grid of global and regional scale Eulerian models is generally too large to resolve BB photochemistry, which can lead to errors in predicting the formation of secondary organic aerosol (SOA) and O3, as well as the partitioning of NOyspecies. AER's Aerosol Simulation Program (ASP v2.1) can be used within plume-scale Lagrangian models to simulate this complex photochemistry. We will present results of validation studies of the ASP model against aircraft observations of young BB smoke plumes. We will also present initial results from the coupling of ASP v2.1 into the Lagrangian particle dispersion model STILT-Chem in order to better examine the interactions between BB plume chemistry and dispersion. In addition, we have used ASP to develop a sub-grid scale parameterization of the near-source chemistry of BB plumes for use in regional and global air quality models. The parameterization takes inputs from the host model, such as solar zenith angle, temperature, and fire fuel type, and calculates enhancement ratios of O3, NOx, PAN, aerosol nitrate, and other NOy species, as well as organic aerosol (OA). We will present results from the ASP-based BB parameterization as well as its implementation into the global atmospheric composition model GEOS-Chem for the SEAC4RS campaign.

The parameterization of microchannel-plate-based detection systems

NASA Astrophysics Data System (ADS)

Gershman, Daniel J.; Gliese, Ulrik; Dorelli, John C.; Avanov, Levon A.; Barrie, Alexander C.; Chornay, Dennis J.; MacDonald, Elizabeth A.; Holland, Matthew P.; Giles, Barbara L.; Pollock, Craig J.

2016-10-01

The most common instrument for low-energy plasmas consists of a top-hat electrostatic analyzer (ESA) geometry coupled with a microchannel-plate-based (MCP-based) detection system. While the electrostatic optics for such sensors are readily simulated and parameterized during the laboratory calibration process, the detection system is often less well characterized. Here we develop a comprehensive mathematical description of particle detection systems. As a function of instrument azimuthal angle, we parameterize (1) particle scattering within the ESA and at the surface of the MCP, (2) the probability distribution of MCP gain for an incident particle, (3) electron charge cloud spreading between the MCP and anode board, and (4) capacitive coupling between adjacent discrete anodes. Using the Dual Electron Spectrometers on the Fast Plasma Investigation on NASA's Magnetospheric Multiscale mission as an example, we demonstrate a method for extracting these fundamental detection system parameters from laboratory calibration. We further show that parameters that will evolve in flight, namely, MCP gain, can be determined through application of this model to specifically tailored in-flight calibration activities. This methodology provides a robust characterization of sensor suite performance throughout mission lifetime. The model developed in this work is not only applicable to existing sensors but also can be used as an analytical design tool for future particle instrumentation.

Amplification of intrinsic emittance due to rough metal cathodes: Formulation of a parameterization model

NASA Astrophysics Data System (ADS)

Charles, T. K.; Paganin, D. M.; Dowd, R. T.

2016-08-01

Intrinsic emittance is often the limiting factor for brightness in fourth generation light sources and as such, a good understanding of the factors affecting intrinsic emittance is essential in order to be able to decrease it. Here we present a parameterization model describing the proportional increase in emittance induced by cathode surface roughness. One major benefit behind the parameterization approach presented here is that it takes the complexity of a Monte Carlo model and reduces the results to a straight-forward empirical model. The resulting models describe the proportional increase in transverse momentum introduced by surface roughness, and are applicable to various metal types, photon wavelengths, applied electric fields, and cathode surface terrains. The analysis includes the increase in emittance due to changes in the electric field induced by roughness as well as the increase in transverse momentum resultant from the spatially varying surface normal. We also compare the results of the Parameterization Model to an Analytical Model which employs various approximations to produce a more compact expression with the cost of a reduction in accuracy.

Research into the influence of spatial variability and scale on the parameterization of hydrological processes

NASA Technical Reports Server (NTRS)

Wood, Eric F.

1993-01-01

The objectives of the research were as follows: (1) Extend the Representative Elementary Area (RE) concept, first proposed and developed in Wood et al, (1988), to the water balance fluxes of the interstorm period (redistribution, evapotranspiration and baseflow) necessary for the analysis of long-term water balance processes. (2) Derive spatially averaged water balance model equations for spatially variable soil, topography and vegetation, over A RANGE OF CLIMATES. This is a necessary step in our goal to derive consistent hydrologic results up to GCM grid scales necessary for global climate modeling. (3) Apply the above macroscale water balance equations with remotely sensed data and begin to explore the feasibility of parameterizing the water balance constitutive equations at GCM grid scale.

Regional tectonic analysis of Venus equatorial highlands and comparison with Earth-based Magellan radar images

NASA Technical Reports Server (NTRS)

Williams, David R.; Wetherill, George

1993-01-01

Research on regional tectonic analysis of Venus equatorial highlands and comparison with earth-based and Magellan radar images is presented. Over the past two years, the tectonic analysis of Venus performed centered on global properties of the planet, in order to understand fundamental aspects of the dynamics of the mantle and lithosphere of Venus. These include studies pertaining to the original constitutive and thermal character of the planet, as well as the evolution of Venus through time, and the present day tectonics. Parameterized convection models of the Earth and Venus were developed. The parameterized convection code was reformulated to model Venus with an initially hydrous mantle to determine how the cold-trap could affect the evolution of the planet.

Modeling Wind Wave Evolution from Deep to Shallow Water

DTIC Science & Technology

2012-09-30

WORK COMPLETED Development of a Lumped Quadruplet Approximation ( LQA ) A scalable parameterization of non-linear four-wave interactions is being...what we refer to as the Lumped Quadruplet Approximation ( LQA ), in which discrete contributions on the locus are treated as individual wave number...includes inhomogeneous wave fields, but is compatible with the action balance generally used in operational wave models. RESULTS Development LQA

Relativistic three-dimensional Lippmann-Schwinger cross sections for space radiation applications

NASA Astrophysics Data System (ADS)

Werneth, C. M.; Xu, X.; Norman, R. B.; Maung, K. M.

2017-12-01

Radiation transport codes require accurate nuclear cross sections to compute particle fluences inside shielding materials. The Tripathi semi-empirical reaction cross section, which includes over 60 parameters tuned to nucleon-nucleus (NA) and nucleus-nucleus (AA) data, has been used in many of the world's best-known transport codes. Although this parameterization fits well to reaction cross section data, the predictive capability of any parameterization is questionable when it is used beyond the range of the data to which it was tuned. Using uncertainty analysis, it is shown that a relativistic three-dimensional Lippmann-Schwinger (LS3D) equation model based on Multiple Scattering Theory (MST) that uses 5 parameterizations-3 fundamental parameterizations to nucleon-nucleon (NN) data and 2 nuclear charge density parameterizations-predicts NA and AA reaction cross sections as well as the Tripathi cross section parameterization for reactions in which the kinetic energy of the projectile in the laboratory frame (TLab) is greater than 220 MeV/n. The relativistic LS3D model has the additional advantage of being able to predict highly accurate total and elastic cross sections. Consequently, it is recommended that the relativistic LS3D model be used for space radiation applications in which TLab > 220MeV /n .

Shortwave radiation parameterization scheme for subgrid topography

NASA Astrophysics Data System (ADS)

Helbig, N.; LöWe, H.

2012-02-01

Topography is well known to alter the shortwave radiation balance at the surface. A detailed radiation balance is therefore required in mountainous terrain. In order to maintain the computational performance of large-scale models while at the same time increasing grid resolutions, subgrid parameterizations are gaining more importance. A complete radiation parameterization scheme for subgrid topography accounting for shading, limited sky view, and terrain reflections is presented. Each radiative flux is parameterized individually as a function of sky view factor, slope and sun elevation angle, and albedo. We validated the parameterization with domain-averaged values computed from a distributed radiation model which includes a detailed shortwave radiation balance. Furthermore, we quantify the individual topographic impacts on the shortwave radiation balance. Rather than using a limited set of real topographies we used a large ensemble of simulated topographies with a wide range of typical terrain characteristics to study all topographic influences on the radiation balance. To this end slopes and partial derivatives of seven real topographies from Switzerland and the United States were analyzed and Gaussian statistics were found to best approximate real topographies. Parameterized direct beam radiation presented previously compared well with modeled values over the entire range of slope angles. The approximation of multiple, anisotropic terrain reflections with single, isotropic terrain reflections was confirmed as long as domain-averaged values are considered. The validation of all parameterized radiative fluxes showed that it is indeed not necessary to compute subgrid fluxes in order to account for all topographic influences in large grid sizes.

Comprehensive assessment of parameterization methods for estimating clear-sky surface downward longwave radiation

NASA Astrophysics Data System (ADS)

Guo, Yamin; Cheng, Jie; Liang, Shunlin

2018-02-01

Surface downward longwave radiation (SDLR) is a key variable for calculating the earth's surface radiation budget. In this study, we evaluated seven widely used clear-sky parameterization methods using ground measurements collected from 71 globally distributed fluxnet sites. The Bayesian model averaging (BMA) method was also introduced to obtain a multi-model ensemble estimate. As a whole, the parameterization method of Carmona et al. (2014) performs the best, with an average BIAS, RMSE, and R 2 of - 0.11 W/m2, 20.35 W/m2, and 0.92, respectively, followed by the parameterization methods of Idso (1981), Prata (Q J R Meteorol Soc 122:1127-1151, 1996), Brunt and Sc (Q J R Meteorol Soc 58:389-420, 1932), and Brutsaert (Water Resour Res 11:742-744, 1975). The accuracy of the BMA is close to that of the parameterization method of Carmona et al. (2014) and comparable to that of the parameterization method of Idso (1981). The advantage of the BMA is that it achieves balanced results compared to the integrated single parameterization methods. To fully assess the performance of the parameterization methods, the effects of climate type, land cover, and surface elevation were also investigated. The five parameterization methods and BMA all failed over land with the tropical climate type, with high water vapor, and had poor results over forest, wetland, and ice. These methods achieved better results over desert, bare land, cropland, and grass and had acceptable accuracies for sites at different elevations, except for the parameterization method of Carmona et al. (2014) over high elevation sites. Thus, a method that can be successfully applied everywhere does not exist.

Accuracy of parameterized proton range models; A comparison

NASA Astrophysics Data System (ADS)

Pettersen, H. E. S.; Chaar, M.; Meric, I.; Odland, O. H.; Sølie, J. R.; Röhrich, D.

2018-03-01

An accurate calculation of proton ranges in phantoms or detector geometries is crucial for decision making in proton therapy and proton imaging. To this end, several parameterizations of the range-energy relationship exist, with different levels of complexity and accuracy. In this study we compare the accuracy of four different parameterizations models for proton range in water: Two analytical models derived from the Bethe equation, and two different interpolation schemes applied to range-energy tables. In conclusion, a spline interpolation scheme yields the highest reproduction accuracy, while the shape of the energy loss-curve is best reproduced with the differentiated Bragg-Kleeman equation.

Integration of nitrogen dynamics into the Noah-MP land surface model v1.1 for climate and environmental predictions

NASA Astrophysics Data System (ADS)

Cai, X.; Yang, Z.-L.; Fisher, J. B.; Zhang, X.; Barlage, M.; Chen, F.

2016-01-01

Climate and terrestrial biosphere models consider nitrogen an important factor in limiting plant carbon uptake, while operational environmental models view nitrogen as the leading pollutant causing eutrophication in water bodies. The community Noah land surface model with multi-parameterization options (Noah-MP) is unique in that it is the next-generation land surface model for the Weather Research and Forecasting meteorological model and for the operational weather/climate models in the National Centers for Environmental Prediction. In this study, we add a capability to Noah-MP to simulate nitrogen dynamics by coupling the Fixation and Uptake of Nitrogen (FUN) plant model and the Soil and Water Assessment Tool (SWAT) soil nitrogen dynamics. This model development incorporates FUN's state-of-the-art concept of carbon cost theory and SWAT's strength in representing the impacts of agricultural management on the nitrogen cycle. Parameterizations for direct root and mycorrhizal-associated nitrogen uptake, leaf retranslocation, and symbiotic biological nitrogen fixation are employed from FUN, while parameterizations for nitrogen mineralization, nitrification, immobilization, volatilization, atmospheric deposition, and leaching are based on SWAT. The coupled model is then evaluated at the Kellogg Biological Station - a Long Term Ecological Research site within the US Corn Belt. Results show that the model performs well in capturing the major nitrogen state/flux variables (e.g., soil nitrate and nitrate leaching). Furthermore, the addition of nitrogen dynamics improves the modeling of net primary productivity and evapotranspiration. The model improvement is expected to advance the capability of Noah-MP to simultaneously predict weather and water quality in fully coupled Earth system models.

The Impact of Varied Discrimination Parameters on Mixed-Format Item Response Theory Model Selection

ERIC Educational Resources Information Center

Whittaker, Tiffany A.; Chang, Wanchen; Dodd, Barbara G.

2013-01-01

Whittaker, Chang, and Dodd compared the performance of model selection criteria when selecting among mixed-format IRT models and found that the criteria did not perform adequately when selecting the more parameterized models. It was suggested by M. S. Johnson that the problems when selecting the more parameterized models may be because of the low…

Parameterized data-driven fuzzy model based optimal control of a semi-batch reactor.

PubMed

Kamesh, Reddi; Rani, K Yamuna

2016-09-01

A parameterized data-driven fuzzy (PDDF) model structure is proposed for semi-batch processes, and its application for optimal control is illustrated. The orthonormally parameterized input trajectories, initial states and process parameters are the inputs to the model, which predicts the output trajectories in terms of Fourier coefficients. Fuzzy rules are formulated based on the signs of a linear data-driven model, while the defuzzification step incorporates a linear regression model to shift the domain from input to output domain. The fuzzy model is employed to formulate an optimal control problem for single rate as well as multi-rate systems. Simulation study on a multivariable semi-batch reactor system reveals that the proposed PDDF modeling approach is capable of capturing the nonlinear and time-varying behavior inherent in the semi-batch system fairly accurately, and the results of operating trajectory optimization using the proposed model are found to be comparable to the results obtained using the exact first principles model, and are also found to be comparable to or better than parameterized data-driven artificial neural network model based optimization results. Copyright © 2016 ISA. Published by Elsevier Ltd. All rights reserved.

Development of a rotorcraft. Propulsion dynamics interface analysis, volume 2

NASA Technical Reports Server (NTRS)

Hull, R.

1982-01-01

A study was conducted to establish a coupled rotor/propulsion analysis that would be applicable to a wide range of rotorcraft systems. The effort included the following tasks: (1) development of a model structure suitable for simulating a wide range of rotorcraft configurations; (2) defined a methodology for parameterizing the model structure to represent a particular rotorcraft; (3) constructing a nonlinear coupled rotor/propulsion model as a test case to use in analyzing coupled system dynamics; and (4) an attempt to develop a mostly linear coupled model derived from the complete nonlinear simulations. Documentation of the computer models developed is presented.

Environmental limitation mapping of potential biomass resources across the conterminous United States

DOE Office of Scientific and Technical Information (OSTI.GOV)

Daly, Christopher; Halbleib, Michael D.; Hannaway, David B.

Several crops have recently been identified as potential dedicated bioenergy feedstocks for the production of power, fuels, and bioproducts. Despite being identified as early as the 1980s, no systematic work has been undertaken to characterize the spatial distribution of their long-term production potentials in the United states. Such information is a starting point for planners and economic modelers, and there is a need for this spatial information to be developed in a consistent manner for a variety of crops, so that their production potentials can be intercompared to support crop selection decisions. As part of the Sun Grant Regional Feedstockmore » Partnership (RFP), an approach to mapping these potential biomass resources was developed to take advantage of the informational synergy realized when bringing together coordinated field trials, close interaction with expert agronomists, and spatial modeling into a single, collaborative effort. A modeling and mapping system called PRISM-ELM was designed to answer a basic question: How do climate and soil characteristics affect the spatial distribution and long-term production patterns of a given crop? This empirical/mechanistic/biogeographical hybrid model employs a limiting factor approach, where productivity is determined by the most limiting of the factors addressed in submodels that simulate water balance, winter low-temperature response, summer high-temperature response, and soil pH, salinity, and drainage. Yield maps are developed through linear regressions relating soil and climate attributes to reported yield data. The model was parameterized and validated using grain yield data for winter wheat and maize, which served as benchmarks for parameterizing the model for upland and lowland switchgrass, CRP grasses, Miscanthus, biomass sorghum, energycane, willow, and poplar. The resulting maps served as potential production inputs to analyses comparing the viability of biomass crops under various economic scenarios. The modeling and parameterization framework can be expanded to include other biomass crops.« less

Environmental limitation mapping of potential biomass resources across the conterminous United States

DOE PAGES

Daly, Christopher; Halbleib, Michael D.; Hannaway, David B.; ...

2017-12-22

Several crops have recently been identified as potential dedicated bioenergy feedstocks for the production of power, fuels, and bioproducts. Despite being identified as early as the 1980s, no systematic work has been undertaken to characterize the spatial distribution of their long-term production potentials in the United states. Such information is a starting point for planners and economic modelers, and there is a need for this spatial information to be developed in a consistent manner for a variety of crops, so that their production potentials can be intercompared to support crop selection decisions. As part of the Sun Grant Regional Feedstockmore » Partnership (RFP), an approach to mapping these potential biomass resources was developed to take advantage of the informational synergy realized when bringing together coordinated field trials, close interaction with expert agronomists, and spatial modeling into a single, collaborative effort. A modeling and mapping system called PRISM-ELM was designed to answer a basic question: How do climate and soil characteristics affect the spatial distribution and long-term production patterns of a given crop? This empirical/mechanistic/biogeographical hybrid model employs a limiting factor approach, where productivity is determined by the most limiting of the factors addressed in submodels that simulate water balance, winter low-temperature response, summer high-temperature response, and soil pH, salinity, and drainage. Yield maps are developed through linear regressions relating soil and climate attributes to reported yield data. The model was parameterized and validated using grain yield data for winter wheat and maize, which served as benchmarks for parameterizing the model for upland and lowland switchgrass, CRP grasses, Miscanthus, biomass sorghum, energycane, willow, and poplar. The resulting maps served as potential production inputs to analyses comparing the viability of biomass crops under various economic scenarios. The modeling and parameterization framework can be expanded to include other biomass crops.« less

Collaborative Research: Quantifying the Uncertainties of Aerosol Indirect Effects and Impacts on Decadal-Scale Climate Variability in NCAR CAM5 and CESM1

DOE Office of Scientific and Technical Information (OSTI.GOV)

Nenes, Athanasios

The goal of this proposed project is to assess the climatic importance and sensitivity of aerosol indirect effect (AIE) to cloud and aerosol processes and feedbacks, which include organic aerosol hygroscopicity, cloud condensation nuclei (CCN) activation kinetics, Giant CCN, cloud-scale entrainment, ice nucleation in mixed-phase and cirrus clouds, and treatment of subgrid variability of vertical velocity. A key objective was to link aerosol, cloud microphysics and dynamics feedbacks in CAM5 with a suite of internally consistent and integrated parameterizations that provide the appropriate degrees of freedom to capture the various aspects of the aerosol indirect effect. The proposal integrated newmore » parameterization elements into the cloud microphysics, moist turbulence and aerosol modules used by the NCAR Community Atmospheric Model version 5 (CAM5). The CAM5 model was then used to systematically quantify the uncertainties of aerosol indirect effects through a series of sensitivity tests with present-day and preindustrial aerosol emissions. New parameterization elements were developed as a result of these efforts, and new diagnostic tools & methodologies were also developed to quantify the impacts of aerosols on clouds and climate within fully coupled models. Observations were used to constrain key uncertainties in the aerosol-cloud links. Advanced sensitivity tools were developed and implements to probe the drivers of cloud microphysical variability with unprecedented temporal and spatial scale. All these results have been published in top and high impact journals (or are in the final stages of publication). This proposal has also supported a number of outstanding graduate students.« less

Modeling the clouds on Venus: model development and improvement of a nucleation parameterization

NASA Astrophysics Data System (ADS)

Määttänen, Anni; Bekki, Slimane; Vehkamäki, Hanna; Julin, Jan; Montmessin, Franck; Ortega, Ismael K.; Lebonnois, Sébastien

2014-05-01

As both the clouds of Venus and aerosols in the Earth's stratosphere are composed of sulfuric acid droplets, we use the 1-D version of a model [1,4] developed for stratospheric aerosols and clouds to study the clouds on Venus. We have removed processes and compounds related to the stratospheric clouds so that the only species remaining are water and sulfuric acid, corresponding to the stratospheric sulfate aerosols, and we have added some key processes. The model describes microphysical processes including condensation/evaporation, and sedimentation. Coagulation, turbulent diffusion, and a parameterization for two-component nucleation [8] of water and sulfuric acid have been added in the model. Since the model describes explicitly the size distribution with a large number of size bins (50-500), it can handle multiple particle modes. The validity ranges of the existing nucleation parameterization [7] have been improved to cover a larger temperature range, and the very low relative humidity (RH) and high sulfuric acid concentrations found in the atmosphere of Venus. We have made several modifications to improve the 2002 nucleation parameterization [7], most notably ensuring that the two-component nucleation model behaves as predicted by the analytical studies at the one-component limit reached at extremely low RH. We have also chosen to use a self-consistent cluster distribution [9], constrained by scaling it to recent quantum chemistry calculations [3]. First tests of the cloud model have been carried out with temperature profiles from VIRA [2] and from the LMD Venus GCM [5], and with a compilation of water vapor and sulfuric acid profiles, as in [6]. The temperature and pressure profiles do not evolve with time, but the vapour profiles naturally change with the cloud. However, no chemistry is included for the moment, so the vapor concentrations are only dependent on the microphysical processes. The model has been run for several hundreds of Earth days to reach a steady state. Preliminary results are evaluated against observations. [1] Jumelet et al., JGR, 2009. [2] Kliore et al., 1986. [3] Kurtén et al., BER, 2007 [4] Larsen et al., JGR, 2000. [5] Lebonnois et al. JGR, 2010. [6] McGouldrick and Toon, Icarus 191, 2007. [7] Vehkamäki et al. JGR, 2002 [9] Wilemski and Wyslouzil, J.Chem.Phys. 1995.

Efficient hierarchical trans-dimensional Bayesian inversion of magnetotelluric data

NASA Astrophysics Data System (ADS)

Xiang, Enming; Guo, Rongwen; Dosso, Stan E.; Liu, Jianxin; Dong, Hao; Ren, Zhengyong

2018-06-01

This paper develops an efficient hierarchical trans-dimensional (trans-D) Bayesian algorithm to invert magnetotelluric (MT) data for subsurface geoelectrical structure, with unknown geophysical model parameterization (the number of conductivity-layer interfaces) and data-error models parameterized by an auto-regressive (AR) process to account for potential error correlations. The reversible-jump Markov-chain Monte Carlo algorithm, which adds/removes interfaces and AR parameters in birth/death steps, is applied to sample the trans-D posterior probability density for model parameterization, model parameters, error variance and AR parameters, accounting for the uncertainties of model dimension and data-error statistics in the uncertainty estimates of the conductivity profile. To provide efficient sampling over the multiple subspaces of different dimensions, advanced proposal schemes are applied. Parameter perturbations are carried out in principal-component space, defined by eigen-decomposition of the unit-lag model covariance matrix, to minimize the effect of inter-parameter correlations and provide effective perturbation directions and length scales. Parameters of new layers in birth steps are proposed from the prior, instead of focused distributions centred at existing values, to improve birth acceptance rates. Parallel tempering, based on a series of parallel interacting Markov chains with successively relaxed likelihoods, is applied to improve chain mixing over model dimensions. The trans-D inversion is applied in a simulation study to examine the resolution of model structure according to the data information content. The inversion is also applied to a measured MT data set from south-central Australia.

An Eddy-Diffusivity Mass-flux (EDMF) closure for the unified representation of cloud and convective processes

NASA Astrophysics Data System (ADS)

Tan, Z.; Schneider, T.; Teixeira, J.; Lam, R.; Pressel, K. G.

2014-12-01

Sub-grid scale (SGS) closures in current climate models are usually decomposed into several largely independent parameterization schemes for different cloud and convective processes, such as boundary layer turbulence, shallow convection, and deep convection. These separate parameterizations usually do not converge as the resolution is increased or as physical limits are taken. This makes it difficult to represent the interactions and smooth transition among different cloud and convective regimes. Here we present an eddy-diffusivity mass-flux (EDMF) closure that represents all sub-grid scale turbulent, convective, and cloud processes in a unified parameterization scheme. The buoyant updrafts and precipitative downdrafts are parameterized with a prognostic multiple-plume mass-flux (MF) scheme. The prognostic term for the mass flux is kept so that the life cycles of convective plumes are better represented. The interaction between updrafts and downdrafts are parameterized with the buoyancy-sorting model. The turbulent mixing outside plumes is represented by eddy diffusion, in which eddy diffusivity (ED) is determined from a turbulent kinetic energy (TKE) calculated from a TKE balance that couples the environment with updrafts and downdrafts. Similarly, tracer variances are decomposed consistently between updrafts, downdrafts and the environment. The closure is internally coupled with a probabilistic cloud scheme and a simple precipitation scheme. We have also developed a relatively simple two-stream radiative scheme that includes the longwave (LW) and shortwave (SW) effects of clouds, and the LW effect of water vapor. We have tested this closure in a single-column model for various regimes spanning stratocumulus, shallow cumulus, and deep convection. The model is also run towards statistical equilibrium with climatologically relevant large-scale forcings. These model tests are validated against large-eddy simulation (LES) with the same forcings. The comparison of results verifies the capacity of this closure to realistically represent different cloud and convective processes. Implementation of the closure in an idealized GCM allows us to study cloud feedbacks to climate change and to study the interactions between clouds, convections, and the large-scale circulation.

Using field observations to inform thermal hydrology models of permafrost dynamics with ATS (v0.83)

DOE PAGES

Atchley, A. L.; Painter, S. L.; Harp, D. R.; ...

2015-04-14

Climate change is profoundly transforming the carbon-rich Arctic tundra landscape, potentially moving it from a carbon sink to a carbon source by increasing the thickness of soil that thaws on a seasonal basis. However, the modeling capability and precise parameterizations of the physical characteristics needed to estimate projected active layer thickness (ALT) are limited in Earth System Models (ESMs). In particular, discrepancies in spatial scale between field measurements and Earth System Models challenge validation and parameterization of hydrothermal models. A recently developed surface/subsurface model for permafrost thermal hydrology, the Advanced Terrestrial Simulator (ATS), is used in combination with field measurementsmore » to calibrate and identify fine scale controls of ALT in ice wedge polygon tundra in Barrow, Alaska. An iterative model refinement procedure that cycles between borehole temperature and snow cover measurements and simulations functions to evaluate and parameterize different model processes necessary to simulate freeze/thaw processes and ALT formation. After model refinement and calibration, reasonable matches between simulated and measured soil temperatures are obtained, with the largest errors occurring during early summer above ice wedges (e.g. troughs). The results suggest that properly constructed and calibrated one-dimensional thermal hydrology models have the potential to provide reasonable representation of the subsurface thermal response and can be used to infer model input parameters and process representations. The models for soil thermal conductivity and snow distribution were found to be the most sensitive process representations. However, information on lateral flow and snowpack evolution might be needed to constrain model representations of surface hydrology and snow depth.« less

Investigate wave-mean flow interaction and transport in the extratropical winter stratosphere

NASA Technical Reports Server (NTRS)

Smith, Anne K.

1993-01-01

The grant supported studies using several models along with observations in order to investigate some questions of wave-mean flow interaction and transport in the extratropical winter stratosphere. A quasi-geostrophic wave model was used to investigate the possibility that resonant growth of planetary wave 2 may have played a role in the sudden stratospheric warming of February 1979. The results of the time-dependent integration support the interpretation of resonance during February, 1979. Because of the possibility that the model treatment of critical line interactions exerted a controlling influence on the atmospheric dynamics, a more accurate model was needed for wave-mean flow interaction studies. A new model was adapted from the 3-dimensional primitive equation model developed by K. Rose and G. Brasseur. In its present form the model is global, rather than hemispheric; it contains an infrared cooling algorithm and a parameterized solar heating; it has parameterized gravity wave drag; and the chemistry has been entirely revised.

Subgrid-scale parameterization and low-frequency variability: a response theory approach

NASA Astrophysics Data System (ADS)

Demaeyer, Jonathan; Vannitsem, Stéphane

2016-04-01

Weather and climate models are limited in the possible range of resolved spatial and temporal scales. However, due to the huge space- and time-scale ranges involved in the Earth System dynamics, the effects of many sub-grid processes should be parameterized. These parameterizations have an impact on the forecasts or projections. It could also affect the low-frequency variability present in the system (such as the one associated to ENSO or NAO). An important question is therefore to know what is the impact of stochastic parameterizations on the Low-Frequency Variability generated by the system and its model representation. In this context, we consider a stochastic subgrid-scale parameterization based on the Ruelle's response theory and proposed in Wouters and Lucarini (2012). We test this approach in the context of a low-order coupled ocean-atmosphere model, detailed in Vannitsem et al. (2015), for which a part of the atmospheric modes is considered as unresolved. A natural separation of the phase-space into a slow invariant set and its fast complement allows for an analytical derivation of the different terms involved in the parameterization, namely the average, the fluctuation and the long memory terms. Its application to the low-order system reveals that a considerable correction of the low-frequency variability along the invariant subset can be obtained. This new approach of scale separation opens new avenues of subgrid-scale parameterizations in multiscale systems used for climate forecasts. References: Vannitsem S, Demaeyer J, De Cruz L, Ghil M. 2015. Low-frequency variability and heat transport in a low-order nonlinear coupled ocean-atmosphere model. Physica D: Nonlinear Phenomena 309: 71-85. Wouters J, Lucarini V. 2012. Disentangling multi-level systems: averaging, correlations and memory. Journal of Statistical Mechanics: Theory and Experiment 2012(03): P03 003.

A~comprehensive parameterization of heterogeneous ice nucleation of dust surrogate: laboratory study with hematite particles and its application to atmospheric models

NASA Astrophysics Data System (ADS)

Hiranuma, N.; Paukert, M.; Steinke, I.; Zhang, K.; Kulkarni, G.; Hoose, C.; Schnaiter, M.; Saathoff, H.; Möhler, O.

2014-06-01

A new heterogeneous ice nucleation parameterization that covers a~wide temperature range (-36 to -78 °C) is presented. Developing and testing such an ice nucleation parameterization, which is constrained through identical experimental conditions, is critical in order to accurately simulate the ice nucleation processes in cirrus clouds. The surface-scaled ice nucleation efficiencies of hematite particles, inferred by ns, were derived from AIDA (Aerosol Interaction and Dynamics in the Atmosphere) cloud chamber measurements under water subsaturated conditions that were realized by continuously changing temperature (T) and relative humidity with respect to ice (RHice) in the chamber. Our measurements showed several different pathways to nucleate ice depending on T and RHice conditions. For instance, almost T-independent freezing was observed at -60 °C < T < -50 °C, where RHice explicitly controlled ice nucleation efficiency, while both T and RHice played roles in other two T regimes: -78 °C < T < -60 °C and -50 °C < T < -36 °C. More specifically, observations at T colder than -60 °C revealed that higher RHice was necessary to maintain constant ns, whereas T may have played a significant role in ice nucleation at T warmer than -50 °C. We implemented new ns parameterizations into two cloud models to investigate its sensitivity and compare with the existing ice nucleation schemes towards simulating cirrus cloud properties. Our results show that the new AIDA-based parameterizations lead to an order of magnitude higher ice crystal concentrations and inhibition of homogeneous nucleation in colder temperature regions. Our cloud simulation results suggest that atmospheric dust particles that form ice nuclei at lower temperatures, below -36 °C, can potentially have stronger influence on cloud properties such as cloud longevity and initiation when compared to previous parameterizations.

A Comprehensive Parameterization of Heterogeneous Ice Nucleation of Dust Surrogate: Laboratory Study with Hematite Particles and Its Application to Atmospheric Models

DOE Office of Scientific and Technical Information (OSTI.GOV)

Hiranuma, Naruki; Paukert, Marco; Steinke, Isabelle

2014-12-10

A new heterogeneous ice nucleation parameterization that covers a wide temperature range (-36 °C to -78 °C) is presented. Developing and testing such an ice nucleation parameterization, which is constrained through identical experimental conditions, is critical in order to accurately simulate the ice nucleation processes in cirrus clouds. The surface-scaled ice nucleation efficiencies of hematite particles, inferred by n s, were derived from AIDA (Aerosol Interaction and Dynamics in the Atmosphere) cloud chamber measurements under water subsaturated conditions that were realized by continuously changing temperature (T) and relative humidity with respect to ice (RH ice) in the chamber. Our measurementsmore » showed several different pathways to nucleate ice depending on T and RH ice conditions. For instance, almost independent freezing was observed at -60 °C < T < -50 °C, where RH ice explicitly controlled ice nucleation efficiency, while both T and RH ice played roles in other two T regimes: -78 °C < T < -60 °C and -50 °C < T < -36 °C. More specifically, observations at T colder than -60 °C revealed that higher RHice was necessary to maintain constant n s, whereas T may have played a significant role in ice nucleation at T warmer than -50 °C. We implemented new n s parameterizations into two cloud models to investigate its sensitivity and compare with the existing ice nucleation schemes towards simulating cirrus cloud properties. Our results show that the new AIDA-based parameterizations lead to an order of magnitude higher ice crystal concentrations and inhibition of homogeneous nucleation in colder temperature regions. Our cloud simulation results suggest that atmospheric dust particles that form ice nuclei at lower temperatures, below -36 °C, can potentially have stronger influence on cloud properties such as cloud longevity and initiation when compared to previous parameterizations.« less

Impacts of spectral nudging on the simulated surface air temperature in summer compared with the selection of shortwave radiation and land surface model physics parameterization in a high-resolution regional atmospheric model

NASA Astrophysics Data System (ADS)

Park, Jun; Hwang, Seung-On

2017-11-01

The impact of a spectral nudging technique for the dynamical downscaling of the summer surface air temperature in a high-resolution regional atmospheric model is assessed. The performance of this technique is measured by comparing 16 analysis-driven simulation sets of physical parameterization combinations of two shortwave radiation and four land surface model schemes of the model, which are known to be crucial for the simulation of the surface air temperature. It is found that the application of spectral nudging to the outermost domain has a greater impact on the regional climate than any combination of shortwave radiation and land surface model physics schemes. The optimal choice of two model physics parameterizations is helpful for obtaining more realistic spatiotemporal distributions of land surface variables such as the surface air temperature, precipitation, and surface fluxes. However, employing spectral nudging adds more value to the results; the improvement is greater than using sophisticated shortwave radiation and land surface model physical parameterizations. This result indicates that spectral nudging applied to the outermost domain provides a more accurate lateral boundary condition to the innermost domain when forced by analysis data by securing the consistency with large-scale forcing over a regional domain. This consequently indirectly helps two physical parameterizations to produce small-scale features closer to the observed values, leading to a better representation of the surface air temperature in a high-resolution downscaled climate.

Resolution-dependent behavior of subgrid-scale vertical transport in the Zhang-McFarlane convection parameterization

DOE Office of Scientific and Technical Information (OSTI.GOV)

Xiao, Heng; Gustafson, Jr., William I.; Hagos, Samson M.

2015-04-18

With this study, to better understand the behavior of quasi-equilibrium-based convection parameterizations at higher resolution, we use a diagnostic framework to examine the resolution-dependence of subgrid-scale vertical transport of moist static energy as parameterized by the Zhang-McFarlane convection parameterization (ZM). Grid-scale input to ZM is supplied by coarsening output from cloud-resolving model (CRM) simulations onto subdomains ranging in size from 8 × 8 to 256 × 256 km 2s.

Evaluating and Understanding Parameterized Convective Processes and their Role in the Development of Mesoscale Precipitation Systems

NASA Technical Reports Server (NTRS)

Fritsch, J. Michael; Kain, John S.

1997-01-01

Research efforts during the second year have centered on improving the manner in which convective stabilization is achieved in the Penn State/NCAR mesoscale model MM5. Ways of improving this stabilization have been investigated by (1) refining the partitioning between the Kain-Fritsch convective parameterization scheme and the grid scale by introducing a form of moist convective adjustment; (2) using radar data to define locations of subgrid-scale convection during a dynamic initialization period; and (3) parameterizing deep-convective feedbacks as subgrid-scale sources and sinks of mass. These investigations were conducted by simulating a long-lived convectively-generated mesoscale vortex that occurred during 14-18 Jul. 1982 and the 10-11 Jun. 1985 squall line that occurred over the Kansas-Oklahoma region during the PRE-STORM experiment. The long-lived vortex tracked across the central Plains states and was responsible for multiple convective outbreaks during its lifetime.

New dynamic variables for rotating spacecraft

NASA Technical Reports Server (NTRS)

Markley, F. Landis

1993-01-01

This paper introduces two new seven-parameter representations for spacecraft attitude dynamics modeling. The seven parameters are the three components of the total system angular momentum in the spacecraft body frame; the three components of the angular momentum in the inertial reference frame; and an angle variable. These obey a single constraint as do parameterizations that include a quaternion; in this case the constraint is the equality of the sum of the squares of the angular momentum components in the two frames. The two representations are nonsingular if the system angular momentum is non-zero and obeys certain orientation constraints. The new parameterizations of the attitude matrix, the equations of motion, and the relation of the solution of these equations to Euler angles for torque-free motion are developed and analyzed. The superiority of the new parameterizations for numerical integration is shown in a specific example.

A linear-RBF multikernel SVM to classify big text corpora.

PubMed

Romero, R; Iglesias, E L; Borrajo, L

2015-01-01

Support vector machine (SVM) is a powerful technique for classification. However, SVM is not suitable for classification of large datasets or text corpora, because the training complexity of SVMs is highly dependent on the input size. Recent developments in the literature on the SVM and other kernel methods emphasize the need to consider multiple kernels or parameterizations of kernels because they provide greater flexibility. This paper shows a multikernel SVM to manage highly dimensional data, providing an automatic parameterization with low computational cost and improving results against SVMs parameterized under a brute-force search. The model consists in spreading the dataset into cohesive term slices (clusters) to construct a defined structure (multikernel). The new approach is tested on different text corpora. Experimental results show that the new classifier has good accuracy compared with the classic SVM, while the training is significantly faster than several other SVM classifiers.

High Resolution Electro-Optical Aerosol Phase Function Database PFNDAT2006

DTIC Science & Technology

2006-08-01

snow models use the gamma distribution (equation 12) with m = 0. 3.4.1 Rain Model The most widely used analytical parameterization for raindrop size ...Uijlenhoet and Stricker (22), as the result of an analytical derivation based on a theoretical parameterization for the raindrop size distribution ...6 2.2 Particle Size Distribution Models

Molecular Modeling in Drug Design for the Development of Organophosphorus Antidotes/Prophylactics.

DTIC Science & Technology

1985-08-01

10 1. INTERFACING OF PROGRAMS ......................... 10 2. PARAMETERIZATION OF ALLINGERS MM2 PROGRAM ....... 11 3. MUSCARINIC AGONISTS...CALCULATION OF PARTIAL CHARGES ..................... 45 10. DERIVATIONOF ELECTROSTATIC POTENTIAL CONTOURS... 53 CONCLUSIONS...60 APPENDIX A - MNDO CHARGE CALCULATIONS ..................... 62 6mwwm &&A-Q- 5.- FIGURES PAGE FIGURE 1 - CHOLINERGIC RECEPTOR MODEL OF KIER

U1108 performance model

NASA Technical Reports Server (NTRS)

Trachta, G.

1976-01-01

A model of Univac 1108 work flow has been developed to assist in performance evaluation studies and configuration planning. Workload profiles and system configurations are parameterized for ease of experimental modification. Outputs include capacity estimates and performance evaluation functions. The U1108 system is conceptualized as a service network; classical queueing theory is used to evaluate network dynamics.

Consequences of parameterization and structure of applied demographic models: a comment on Pardini et al. (2009)

USDA-ARS?s Scientific Manuscript database

In a recently published study, Pardini et al. (2009, hereafter "PDCK" after the authors' initials) developed a demographic model of the invasive weed Alliaria petiolata (garlic mustard, Brassicaceae [M. Bieb] Cavara and Grande). This was then used to identify optimal stages in the plant's life histo...

Hillslope threshold response to rainfall: (2) development and use of a macroscale model

Treesearch

Chris B. Graham; Jeffrey J. McDonnell

2010-01-01

Hillslope hydrological response to precipitation is extremely complex and poorly modeled. One possible approach for reducing the complexity of hillslope response and its mathematical parameterization is to look for macroscale hydrological behavior. Hillslope threshold response to storm precipitation is one such macroscale behavior observed at field sites across the...

Computation at a coordinate singularity

NASA Astrophysics Data System (ADS)

Prusa, Joseph M.

2018-05-01

Coordinate singularities are sometimes encountered in computational problems. An important example involves global atmospheric models used for climate and weather prediction. Classical spherical coordinates can be used to parameterize the manifold - that is, generate a grid for the computational spherical shell domain. This particular parameterization offers significant benefits such as orthogonality and exact representation of curvature and connection (Christoffel) coefficients. But it also exhibits two polar singularities and at or near these points typical continuity/integral constraints on dependent fields and their derivatives are generally inadequate and lead to poor model performance and erroneous results. Other parameterizations have been developed that eliminate polar singularities, but problems of weaker singularities and enhanced grid noise compared to spherical coordinates (away from the poles) persist. In this study reparameterization invariance of geometric objects (scalars, vectors and the forms generated by their covariant derivatives) is utilized to generate asymptotic forms for dependent fields of interest valid in the neighborhood of a pole. The central concept is that such objects cannot be altered by the metric structure of a parameterization. The new boundary conditions enforce symmetries that are required for transformations of geometric objects. They are implemented in an implicit polar filter of a structured grid, nonhydrostatic global atmospheric model that is simulating idealized Held-Suarez flows. A series of test simulations using different configurations of the asymptotic boundary conditions are made, along with control simulations that use the default model numerics with no absorber, at three different grid sizes. Typically the test simulations are ∼ 20% faster in wall clock time than the control-resulting from a decrease in noise at the poles in all cases. In the control simulations adverse numerical effects from the polar singularity are observed to increase with grid resolution. In contrast, test simulations demonstrate robust polar behavior independent of grid resolution.

Exploring Alternate Parameterizations for Snowfall with Validation from Satellite and Terrestrial Radars

NASA Technical Reports Server (NTRS)

Molthan, Andrew L.; Petersen, Walter A.; Case, Jonathan L.; Dembek, Scott R.; Jedlovec, Gary J.

2009-01-01

Increases in computational resources have allowed operational forecast centers to pursue experimental, high resolution simulations that resolve the microphysical characteristics of clouds and precipitation. These experiments are motivated by a desire to improve the representation of weather and climate, but will also benefit current and future satellite campaigns, which often use forecast model output to guide the retrieval process. Aircraft, surface and radar data from the Canadian CloudSat/CALIPSO Validation Project are used to check the validity of size distribution and density characteristics for snowfall simulated by the NASA Goddard six-class, single-moment bulk water microphysics scheme, currently available within the Weather Research and Forecast (WRF) Model. Widespread snowfall developed across the region on January 22, 2007, forced by the passing of a midlatitude cyclone, and was observed by the dual-polarimetric, C-band radar King City, Ontario, as well as the NASA 94 GHz CloudSat Cloud Profiling Radar. Combined, these data sets provide key metrics for validating model output: estimates of size distribution parameters fit to the inverse-exponential equations prescribed within the model, bulk density and crystal habit characteristics sampled by the aircraft, and representation of size characteristics as inferred by the radar reflectivity at C- and W-band. Specified constants for distribution intercept and density differ significantly from observations throughout much of the cloud depth. Alternate parameterizations are explored, using column-integrated values of vapor excess to avoid problems encountered with temperature-based parameterizations in an environment where inversions and isothermal layers are present. Simulation of CloudSat reflectivity is performed by adopting the discrete-dipole parameterizations and databases provided in literature, and demonstrate an improved capability in simulating radar reflectivity at W-band versus Mie scattering assumptions.

Automated finite element modeling of the lumbar spine: Using a statistical shape model to generate a virtual population of models.

PubMed

Campbell, J Q; Petrella, A J

2016-09-06

Population-based modeling of the lumbar spine has the potential to be a powerful clinical tool. However, developing a fully parameterized model of the lumbar spine with accurate geometry has remained a challenge. The current study used automated methods for landmark identification to create a statistical shape model of the lumbar spine. The shape model was evaluated using compactness, generalization ability, and specificity. The primary shape modes were analyzed visually, quantitatively, and biomechanically. The biomechanical analysis was performed by using the statistical shape model with an automated method for finite element model generation to create a fully parameterized finite element model of the lumbar spine. Functional finite element models of the mean shape and the extreme shapes (±3 standard deviations) of all 17 shape modes were created demonstrating the robust nature of the methods. This study represents an advancement in finite element modeling of the lumbar spine and will allow population-based modeling in the future. Copyright © 2016 Elsevier Ltd. All rights reserved.

Automatic Parameterization Strategy for Cardiac Electrophysiology Simulations.

PubMed

Costa, Caroline Mendonca; Hoetzl, Elena; Rocha, Bernardo Martins; Prassl, Anton J; Plank, Gernot

2013-10-01

Driven by recent advances in medical imaging, image segmentation and numerical techniques, computer models of ventricular electrophysiology account for increasingly finer levels of anatomical and biophysical detail. However, considering the large number of model parameters involved parameterization poses a major challenge. A minimum requirement in combined experimental and modeling studies is to achieve good agreement in activation and repolarization sequences between model and experiment or patient data. In this study, we propose basic techniques which aid in determining bidomain parameters to match activation sequences. An iterative parameterization algorithm is implemented which determines appropriate bulk conductivities which yield prescribed velocities. In addition, a method is proposed for splitting the computed bulk conductivities into individual bidomain conductivities by prescribing anisotropy ratios.

The application of depletion curves for parameterization of subgrid variability of snow

Treesearch

C. H. Luce; D. G. Tarboton

2004-01-01

Parameterization of subgrid-scale variability in snow accumulation and melt is important for improvements in distributed snowmelt modelling. We have taken the approach of using depletion curves that relate fractional snowcovered area to element-average snow water equivalent to parameterize the effect of snowpack heterogeneity within a physically based mass and energy...

A review of recent research on improvement of physical parameterizations in the GLA GCM

NASA Technical Reports Server (NTRS)

Sud, Y. C.; Walker, G. K.

1990-01-01

A systematic assessment of the effect of a series of improvements in physical parameterizations of the Goddard Laboratory for Atmospheres (GLA) general circulation model (GCM) are summarized. The implementation of the Simple Biosphere Model (SiB) in the GCM is followed by a comparison of SiB GCM simulations with that of the earlier slab soil hydrology GCM (SSH-GCM) simulations. In the Sahelian context, the biogeophysical component of desertification was analyzed for SiB-GCM simulations. Cumulus parameterization is found to be the primary determinant of the organization of the simulated tropical rainfall of the GLA GCM using Arakawa-Schubert cumulus parameterization. A comparison of model simulations with station data revealed excessive shortwave radiation accompanied by excessive drying and heating to the land. The perpetual July simulations with and without interactive soil moisture shows that 30 to 40 day oscillations may be a natural mode of the simulated earth atmosphere system.

Modeling large woody debris recruitment for small streams of the Central Rocky Mountains

Treesearch

Don C. Bragg; Jeffrey L. Kershner; David W. Roberts

2000-01-01

As our understanding of the importance of large woody debris (LWD) evolves, planning for its production in riparian forest management is becoming more widely recognized. This report details the development of a model (CWD, version 1.4) that predicts LWD inputs, including descriptions of the field sampling used to parameterize parts of the model, the theoretical and...

Exploring the potential of machine learning to break deadlock in convection parameterization

NASA Astrophysics Data System (ADS)

Pritchard, M. S.; Gentine, P.

2017-12-01

We explore the potential of modern machine learning tools (via TensorFlow) to replace parameterization of deep convection in climate models. Our strategy begins by generating a large ( 1 Tb) training dataset from time-step level (30-min) output harvested from a one-year integration of a zonally symmetric, uniform-SST aquaplanet integration of the SuperParameterized Community Atmosphere Model (SPCAM). We harvest the inputs and outputs connecting each of SPCAM's 8,192 embedded cloud-resolving model (CRM) arrays to its host climate model's arterial thermodynamic state variables to afford 143M independent training instances. We demonstrate that this dataset is sufficiently large to induce preliminary convergence for neural network prediction of desired outputs of SP, i.e. CRM-mean convective heating and moistening profiles. Sensitivity of the machine learning convergence to the nuances of the TensorFlow implementation are discussed, as well as results from pilot tests from the neural network operating inline within the SPCAM as a replacement to the (super)parameterization of convection.

A subdivision-based parametric deformable model for surface extraction and statistical shape modeling of the knee cartilages

NASA Astrophysics Data System (ADS)

Fripp, Jurgen; Crozier, Stuart; Warfield, Simon K.; Ourselin, Sébastien

2006-03-01

Subdivision surfaces and parameterization are desirable for many algorithms that are commonly used in Medical Image Analysis. However, extracting an accurate surface and parameterization can be difficult for many anatomical objects of interest, due to noisy segmentations and the inherent variability of the object. The thin cartilages of the knee are an example of this, especially after damage is incurred from injuries or conditions like osteoarthritis. As a result, the cartilages can have different topologies or exist in multiple pieces. In this paper we present a topology preserving (genus 0) subdivision-based parametric deformable model that is used to extract the surfaces of the patella and tibial cartilages in the knee. These surfaces have minimal thickness in areas without cartilage. The algorithm inherently incorporates several desirable properties, including: shape based interpolation, sub-division remeshing and parameterization. To illustrate the usefulness of this approach, the surfaces and parameterizations of the patella cartilage are used to generate a 3D statistical shape model.

Effects of microphysics parameterization on simulations of summer heavy precipitation in the Yangtze-Huaihe Region, China

NASA Astrophysics Data System (ADS)

Kan, Yu; Chen, Bo; Shen, Tao; Liu, Chaoshun; Qiao, Fengxue

2017-09-01

It has been a longstanding problem for current weather/climate models to accurately predict summer heavy precipitation over the Yangtze-Huaihe Region (YHR) which is the key flood-prone area in China with intensive population and developed economy. Large uncertainty has been identified with model deficiencies in representing precipitation processes such as microphysics and cumulus parameterizations. This study focuses on examining the effects of microphysics parameterization on the simulation of different type of heavy precipitation over the YHR taking into account two different cumulus schemes. All regional persistent heavy precipitation events over the YHR during 2008-2012 are classified into three types according to their weather patterns: the type I associated with stationary front, the type II directly associated with typhoon or with its spiral rain band, and the type III associated with strong convection along the edge of the Subtropical High. Sixteen groups of experiments are conducted for three selected cases with different types and a local short-time rainstorm in Shanghai, using the WRF model with eight microphysics and two cumulus schemes. Results show that microphysics parameterization has large but different impacts on the location and intensity of regional heavy precipitation centers. The Ferrier (microphysics) -BMJ (cumulus) scheme and Thompson (microphysics) - KF (cumulus) scheme most realistically simulates the rain-bands with the center location and intensity for type I and II respectively. For type III, the Lin microphysics scheme shows advantages in regional persistent cases over YHR, while the WSM5 microphysics scheme is better in local short-term case, both with the BMJ cumulus scheme.

Sensitivity of Tropical Cyclones to Parameterized Convection in the NASA GEOS5 Model

NASA Technical Reports Server (NTRS)

Lim, Young-Kwon; Schubert, Siegfried D.; Reale, Oreste; Lee, Myong-In; Molod, Andrea M.; Suarez, Max J.

2014-01-01

The sensitivity of tropical cyclones (TCs) to changes in parameterized convection is investigated to improve the simulation of TCs in the North Atlantic. Specifically, the impact of reducing the influence of the Relaxed Arakawa-Schubert (RAS) scheme-based parameterized convection is explored using the Goddard Earth Observing System version5 (GEOS5) model at 0.25 horizontal resolution. The years 2005 and 2006 characterized by very active and inactive hurricane seasons, respectively, are selected for simulation. A reduction in parameterized deep convection results in an increase in TC activity (e.g., TC number and longer life cycle) to more realistic levels compared to the baseline control configuration. The vertical and horizontal structure of the strongest simulated hurricane shows the maximum lower-level (850-950hPa) wind speed greater than 60 ms and the minimum sea level pressure reaching 940mb, corresponding to a category 4 hurricane - a category never achieved by the control configuration. The radius of the maximum wind of 50km, the location of the warm core exceeding 10 C, and the horizontal compactness of the hurricane center are all quite realistic without any negatively affecting the atmospheric mean state. This study reveals that an increase in the threshold of minimum entrainment suppresses parameterized deep convection by entraining more dry air into the typical plume. This leads to cooling and drying at the mid- to upper-troposphere, along with the positive latent heat flux and moistening in the lower-troposphere. The resulting increase in conditional instability provides an environment that is more conducive to TC vortex development and upward moisture flux convergence by dynamically resolved moist convection, thereby increasing TC activity.

Impact of Snow Grain Shape and Internal Mixing with Black Carbon Aerosol on Snow Optical Properties for use in Climate Models

NASA Astrophysics Data System (ADS)

He, C.; Liou, K. N.; Takano, Y.; Yang, P.; Li, Q.; Chen, F.

2017-12-01

A set of parameterizations is developed for spectral single-scattering properties of clean and black carbon (BC)-contaminated snow based on geometric-optic surface-wave (GOS) computations, which explicitly resolves BC-snow internal mixing and various snow grain shapes. GOS calculations show that, compared with nonspherical grains, volume-equivalent snow spheres show up to 20% larger asymmetry factors and hence stronger forward scattering, particularly at wavelengths <1 mm. In contrast, snow grain sizes have a rather small impact on the asymmetry factor at wavelengths <1 mm, whereas size effects are important at longer wavelengths. The snow asymmetry factor is parameterized as a function of effective size, aspect ratio, and shape factor, and shows excellent agreement with GOS calculations. According to GOS calculations, the single-scattering coalbedo of pure snow is predominantly affected by grain sizes, rather than grain shapes, with higher values for larger grains. The snow single-scattering coalbedo is parameterized in terms of the effective size that combines shape and size effects, with an accuracy of >99%. Based on GOS calculations, BC-snow internal mixing enhances the snow single-scattering coalbedo at wavelengths <1 mm, but it does not alter the snow asymmetry factor. The BC-induced enhancement ratio of snow single-scattering coalbedo, independent of snow grain size and shape, is parameterized as a function of BC concentration with an accuracy of >99%. Overall, in addition to snow grain size, both BC-snow internal mixing and snow grain shape play critical roles in quantifying BC effects on snow optical properties. The present parameterizations can be conveniently applied to snow, land surface, and climate models including snowpack radiative transfer processes.

Parameterization Interactions in Global Aquaplanet Simulations

NASA Astrophysics Data System (ADS)

Bhattacharya, Ritthik; Bordoni, Simona; Suselj, Kay; Teixeira, João.

2018-02-01

Global climate simulations rely on parameterizations of physical processes that have scales smaller than the resolved ones. In the atmosphere, these parameterizations represent moist convection, boundary layer turbulence and convection, cloud microphysics, longwave and shortwave radiation, and the interaction with the land and ocean surface. These parameterizations can generate different climates involving a wide range of interactions among parameterizations and between the parameterizations and the resolved dynamics. To gain a simplified understanding of a subset of these interactions, we perform aquaplanet simulations with the global version of the Weather Research and Forecasting (WRF) model employing a range (in terms of properties) of moist convection and boundary layer (BL) parameterizations. Significant differences are noted in the simulated precipitation amounts, its partitioning between convective and large-scale precipitation, as well as in the radiative impacts. These differences arise from the way the subcloud physics interacts with convection, both directly and through various pathways involving the large-scale dynamics and the boundary layer, convection, and clouds. A detailed analysis of the profiles of the different tendencies (from the different physical processes) for both potential temperature and water vapor is performed. While different combinations of convection and boundary layer parameterizations can lead to different climates, a key conclusion of this study is that similar climates can be simulated with model versions that are different in terms of the partitioning of the tendencies: the vertically distributed energy and water balances in the tropics can be obtained with significantly different profiles of large-scale, convection, and cloud microphysics tendencies.

Brain Surface Conformal Parameterization Using Riemann Surface Structure

PubMed Central

Wang, Yalin; Lui, Lok Ming; Gu, Xianfeng; Hayashi, Kiralee M.; Chan, Tony F.; Toga, Arthur W.; Thompson, Paul M.; Yau, Shing-Tung

2011-01-01

In medical imaging, parameterized 3-D surface models are useful for anatomical modeling and visualization, statistical comparisons of anatomy, and surface-based registration and signal processing. Here we introduce a parameterization method based on Riemann surface structure, which uses a special curvilinear net structure (conformal net) to partition the surface into a set of patches that can each be conformally mapped to a parallelogram. The resulting surface subdivision and the parameterizations of the components are intrinsic and stable (their solutions tend to be smooth functions and the boundary conditions of the Dirichlet problem can be enforced). Conformal parameterization also helps transform partial differential equations (PDEs) that may be defined on 3-D brain surface manifolds to modified PDEs on a two-dimensional parameter domain. Since the Jacobian matrix of a conformal parameterization is diagonal, the modified PDE on the parameter domain is readily solved. To illustrate our techniques, we computed parameterizations for several types of anatomical surfaces in 3-D magnetic resonance imaging scans of the brain, including the cerebral cortex, hippocampi, and lateral ventricles. For surfaces that are topologically homeomorphic to each other and have similar geometrical structures, we show that the parameterization results are consistent and the subdivided surfaces can be matched to each other. Finally, we present an automatic sulcal landmark location algorithm by solving PDEs on cortical surfaces. The landmark detection results are used as constraints for building conformal maps between surfaces that also match explicitly defined landmarks. PMID:17679336

A Seismic Source Model for Central Europe and Italy

NASA Astrophysics Data System (ADS)

Nyst, M.; Williams, C.; Onur, T.

2006-12-01

We present a seismic source model for Central Europe (Belgium, Germany, Switzerland, and Austria) and Italy, as part of an overall seismic risk and loss modeling project for this region. A separate presentation at this conference discusses the probabilistic seismic hazard and risk assessment (Williams et al., 2006). Where available we adopt regional consensus models and adjusts these to fit our format, otherwise we develop our own model. Our seismic source model covers the whole region under consideration and consists of the following components: 1. A subduction zone environment in Calabria, SE Italy, with interface events between the Eurasian and African plates and intraslab events within the subducting slab. The subduction zone interface is parameterized as a set of dipping area sources that follow the geometry of the surface of the subducting plate, whereas intraslab events are modeled as plane sources at depth; 2. The main normal faults in the upper crust along the Apennines mountain range, in Calabria and Central Italy. Dipping faults and (sub-) vertical faults are parameterized as dipping plane and line sources, respectively; 3. The Upper and Lower Rhine Graben regime that runs from northern Italy into eastern Belgium, parameterized as a combination of dipping plane and line sources, and finally 4. Background seismicity, parameterized as area sources. The fault model is based on slip rates using characteristic recurrence. The modeling of background and subduction zone seismicity is based on a compilation of several national and regional historic seismic catalogs using a Gutenberg-Richter recurrence model. Merging the catalogs encompasses the deletion of double, fake and very old events and the application of a declustering algorithm (Reasenberg, 2000). The resulting catalog contains a little over 6000 events, has an average b-value of -0.9, is complete for moment magnitudes 4.5 and larger, and is used to compute a gridded a-value model (smoothed historical seismicity) for the region. The logic tree weighs various completeness intervals and minimum magnitudes. Using a weighted scheme of European and global ground motion models together with a detailed site classification map for Europe based on Eurocode 8, we generate hazard maps for recurrence periods of 200, 475, 1000 and 2500 yrs.

Test Driven Development of a Parameterized Ice Sheet Component

NASA Astrophysics Data System (ADS)

Clune, T.

2011-12-01

Test driven development (TDD) is a software development methodology that offers many advantages over traditional approaches including reduced development and maintenance costs, improved reliability, and superior design quality. Although TDD is widely accepted in many software communities, the suitability to scientific software is largely undemonstrated and warrants a degree of skepticism. Indeed, numerical algorithms pose several challenges to unit testing in general, and TDD in particular. Among these challenges are the need to have simple, non-redundant closed-form expressions to compare against the results obtained from the implementation as well as realistic error estimates. The necessity for serial and parallel performance raises additional concerns for many scientific applicaitons. In previous work I demonstrated that TDD performed well for the development of a relatively simple numerical model that simulates the growth of snowflakes, but the results were anecdotal and of limited relevance to far more complex software components typical of climate models. This investigation has now been extended by successfully applying TDD to the implementation of a substantial portion of a new parameterized ice sheet component within a full climate model. After a brief introduction to TDD, I will present techniques that address some of the obstacles encountered with numerical algorithms. I will conclude with some quantitative and qualitative comparisons against climate components developed in a more traditional manner.

Approaches in highly parameterized inversion - PEST++, a Parameter ESTimation code optimized for large environmental models

USGS Publications Warehouse

Welter, David E.; Doherty, John E.; Hunt, Randall J.; Muffels, Christopher T.; Tonkin, Matthew J.; Schreuder, Willem A.

2012-01-01

An object-oriented parameter estimation code was developed to incorporate benefits of object-oriented programming techniques for solving large parameter estimation modeling problems. The code is written in C++ and is a formulation and expansion of the algorithms included in PEST, a widely used parameter estimation code written in Fortran. The new code is called PEST++ and is designed to lower the barriers of entry for users and developers while providing efficient algorithms that can accommodate large, highly parameterized problems. This effort has focused on (1) implementing the most popular features of PEST in a fashion that is easy for novice or experienced modelers to use and (2) creating a software design that is easy to extend; that is, this effort provides a documented object-oriented framework designed from the ground up to be modular and extensible. In addition, all PEST++ source code and its associated libraries, as well as the general run manager source code, have been integrated in the Microsoft Visual Studio® 2010 integrated development environment. The PEST++ code is designed to provide a foundation for an open-source development environment capable of producing robust and efficient parameter estimation tools for the environmental modeling community into the future.

Framework to parameterize and validate APEX to support deployment of the nutrient tracking tool

USDA-ARS?s Scientific Manuscript database

The Agricultural Policy Environmental eXtender (APEX) model is the scientific basis for the Nutrient Tracking Tool (NTT). NTT is an enhanced version of the Nitrogen Trading Tool, a user-friendly web-based computer program originally developed by the USDA. NTT was developed to estimate reductions in...

A canopy architectural model to study the competitive ability of chickpea with sowthistle.

PubMed

Cici, S-Zahra-Hosseini; Adkins, Steve; Hanan, Jim

2008-06-01

Improving the competitive ability of crops is a sustainable method of weed management. This paper shows how a virtual plant model of competition between chickpea (Cicer arietinum) and sowthistle (Sonchus oleraceus) can be used as a framework for discovering and/or developing more competitive chickpea cultivars. The virtual plant models were developed using the L-systems formalism, parameterized according to measurements taken on plants at intervals during their development. A quasi-Monte Carlo light-environment model was used to model the effect of chickpea canopy on the development of sowthistle. The chickpea-light environment-sowthistle model (CLES model) captured the hypothesis that the architecture of chickpea plants modifies the light environment inside the canopy and determines sowthistle growth and development pattern. The resulting CLES model was parameterized for different chickpea cultivars (viz. 'Macarena', 'Bumper', 'Jimbour' and '99071-1001') to compare their competitive ability with sowthistle. To validate the CLES model, an experiment was conducted using the same four chickpea cultivars as different treatments with a sowthistle growing under their canopy. The growth of sowthistle, both in silico and in glasshouse experiments, was reduced most by '99071-1001', a cultivar with a short phyllochron. The second rank of competitive ability belonged to 'Macarena' and 'Bumper', while 'Jimbour' was the least competitive cultivar. The architecture of virtual chickpea plants modified the light inside the canopy, which influenced the growth and development of the sowthistle plants in response to different cultivars. This is the first time that a virtual plant model of a crop-weed interaction has been developed. This virtual plant model can serve as a platform for a broad range of applications in the study of chickpea-weed interactions and their environment.

Radar and microphysical characteristics of convective storms simulated from a numerical model using a new microphysical parameterization

NASA Technical Reports Server (NTRS)

Ferrier, Brad S.; Tao, Wei-Kuo; Simpson, Joanne

1991-01-01

The basic features of a new and improved bulk-microphysical parameterization capable of simulating the hydrometeor structure of convective systems in all types of large-scale environments (with minimal adjustment of coefficients) are studied. Reflectivities simulated from the model are compared with radar observations of an intense midlatitude convective system. Simulated reflectivities using the novel four-class ice scheme with a microphysical parameterization rain distribution at 105 min are illustrated. Preliminary results indicate that this new ice scheme works efficiently in simulating midlatitude continental storms.

Comparison of different objective functions for parameterization of simple respiration models

Treesearch

M.T. van Wijk; B. van Putten; D.Y. Hollinger; A.D. Richardson

2008-01-01

The eddy covariance measurements of carbon dioxide fluxes collected around the world offer a rich source for detailed data analysis. Simple, aggregated models are attractive tools for gap filling, budget calculation, and upscaling in space and time. Key in the application of these models is their parameterization and a robust estimate of the uncertainty and reliability...

A Parameterization for Land-Atmosphere-Cloud Exchange (PLACE): Documentation and Testing of a Detailed Process Model of the Partly Cloudy Boundary Layer over Heterogeneous Land.

NASA Astrophysics Data System (ADS)

Wetzel, Peter J.; Boone, Aaron

1995-07-01

This paper presents a general description of, and demonstrates the capabilities of, the Parameterization for Land-Atmosphere-Cloud Exchange (PLACE). The PLACE model is a detailed process model of the partly cloudy atmospheric boundary layer and underlying heterogeneous land surfaces. In its development, particular attention has been given to three of the model's subprocesses: the prediction of boundary layer cloud amount, the treatment of surface and soil subgrid heterogeneity, and the liquid water budget. The model includes a three-parameter nonprecipitating cumulus model that feeds back to the surface and boundary layer through radiative effects. Surface heterogeneity in the PLACE model is treated both statistically and by resolving explicit subgrid patches. The model maintains a vertical column of liquid water that is divided into seven reservoirs, from the surface interception store down to bedrock.Five single-day demonstration cases are presented, in which the PLACE model was initialized, run, and compared to field observations from four diverse sites. The model is shown to predict cloud amount well in these while predicting the surface fluxes with similar accuracy. A slight tendency to underpredict boundary layer depth is noted in all cases.Sensitivity tests were also run using anemometer-level forcing provided by the Project for Inter-comparison of Land-surface Parameterization Schemes (PILPS). The purpose is to demonstrate the relative impact of heterogeneity of surface parameters on the predicted annual mean surface fluxes. Significant sensitivity to subgrid variability of certain parameters is demonstrated, particularly to parameters related to soil moisture. A major result is that the PLACE-computed impact of total (homogeneous) deforestation of a rain forest is comparable in magnitude to the effect of imposing heterogeneity of certain surface variables, and is similarly comparable to the overall variance among the other PILPS participant models. Were this result to be bourne out by further analysis, it would suggest that today's average land surface parameterization has little credibility when applied to discriminating the local impacts of any plausible future climate change.

Pedotransfer Functions in Earth System Science: Challenges and Perspectives

NASA Astrophysics Data System (ADS)

Van Looy, Kris; Bouma, Johan; Herbst, Michael; Koestel, John; Minasny, Budiman; Mishra, Umakant; Montzka, Carsten; Nemes, Attila; Pachepsky, Yakov A.; Padarian, José; Schaap, Marcel G.; Tóth, Brigitta; Verhoef, Anne; Vanderborght, Jan; van der Ploeg, Martine J.; Weihermüller, Lutz; Zacharias, Steffen; Zhang, Yonggen; Vereecken, Harry

2017-12-01

Soil, through its various functions, plays a vital role in the Earth's ecosystems and provides multiple ecosystem services to humanity. Pedotransfer functions (PTFs) are simple to complex knowledge rules that relate available soil information to soil properties and variables that are needed to parameterize soil processes. In this paper, we review the existing PTFs and document the new generation of PTFs developed in the different disciplines of Earth system science. To meet the methodological challenges for a successful application in Earth system modeling, we emphasize that PTF development has to go hand in hand with suitable extrapolation and upscaling techniques such that the PTFs correctly represent the spatial heterogeneity of soils. PTFs should encompass the variability of the estimated soil property or process, in such a way that the estimation of parameters allows for validation and can also confidently provide for extrapolation and upscaling purposes capturing the spatial variation in soils. Most actively pursued recent developments are related to parameterizations of solute transport, heat exchange, soil respiration, and organic carbon content, root density, and vegetation water uptake. Further challenges are to be addressed in parameterization of soil erosivity and land use change impacts at multiple scales. We argue that a comprehensive set of PTFs can be applied throughout a wide range of disciplines of Earth system science, with emphasis on land surface models. Novel sensing techniques provide a true breakthrough for this, yet further improvements are necessary for methods to deal with uncertainty and to validate applications at global scale.

Bayesian parameter estimation for nonlinear modelling of biological pathways.

PubMed

Ghasemi, Omid; Lindsey, Merry L; Yang, Tianyi; Nguyen, Nguyen; Huang, Yufei; Jin, Yu-Fang

2011-01-01

The availability of temporal measurements on biological experiments has significantly promoted research areas in systems biology. To gain insight into the interaction and regulation of biological systems, mathematical frameworks such as ordinary differential equations have been widely applied to model biological pathways and interpret the temporal data. Hill equations are the preferred formats to represent the reaction rate in differential equation frameworks, due to their simple structures and their capabilities for easy fitting to saturated experimental measurements. However, Hill equations are highly nonlinearly parameterized functions, and parameters in these functions cannot be measured easily. Additionally, because of its high nonlinearity, adaptive parameter estimation algorithms developed for linear parameterized differential equations cannot be applied. Therefore, parameter estimation in nonlinearly parameterized differential equation models for biological pathways is both challenging and rewarding. In this study, we propose a Bayesian parameter estimation algorithm to estimate parameters in nonlinear mathematical models for biological pathways using time series data. We used the Runge-Kutta method to transform differential equations to difference equations assuming a known structure of the differential equations. This transformation allowed us to generate predictions dependent on previous states and to apply a Bayesian approach, namely, the Markov chain Monte Carlo (MCMC) method. We applied this approach to the biological pathways involved in the left ventricle (LV) response to myocardial infarction (MI) and verified our algorithm by estimating two parameters in a Hill equation embedded in the nonlinear model. We further evaluated our estimation performance with different parameter settings and signal to noise ratios. Our results demonstrated the effectiveness of the algorithm for both linearly and nonlinearly parameterized dynamic systems. Our proposed Bayesian algorithm successfully estimated parameters in nonlinear mathematical models for biological pathways. This method can be further extended to high order systems and thus provides a useful tool to analyze biological dynamics and extract information using temporal data.

Towards Linking 3D SAR and Lidar Models with a Spatially Explicit Individual Based Forest Model

NASA Astrophysics Data System (ADS)

Osmanoglu, B.; Ranson, J.; Sun, G.; Armstrong, A. H.; Fischer, R.; Huth, A.

2017-12-01

In this study, we present a parameterization of the FORMIND individual-based gap model (IBGM)for old growth Atlantic lowland rainforest in La Selva, Costa Rica for the purpose of informing multisensor remote sensing techniques for above ground biomass techniques. The model was successfully parameterized and calibrated for the study site; results show that the simulated forest reproduces the structural complexity of Costa Rican rainforest based on comparisons with CARBONO inventory plot data. Though the simulated stem numbers (378) slightly underestimated the plot data (418), particularly for canopy dominant intermediate shade tolerant trees and shade tolerant understory trees, overall there was a 9.7% difference. Aboveground biomass (kg/ha) showed a 0.1% difference between the simulated forest and inventory plot dataset. The Costa Rica FORMIND simulation was then used to parameterize a spatially explicit (3D) SAR and lidar backscatter models. The simulated forest stands were used to generate a Look Up Table as a tractable means to estimate aboveground forest biomass for these complex forests. Various combinations of lidar and radar variables were evaluated in the LUT inversion. To test the capability of future data for estimation of forest height and biomass, we considered data of 1) L- (or P-) band polarimetric data (backscattering coefficients of HH, HV and VV); 2) L-band dual-pol repeat-pass InSAR data (HH/HV backscattering coefficients and coherences, height of scattering phase center at HH and HV using DEM or surface height from lidar data as reference); 3) P-band polarimetric InSAR data (canopy height from inversion of PolInSAR data or use the coherences and height of scattering phase center at HH, HV and VV); 4) various height indices from waveform lidar data); and 5) surface and canopy top height from photon-counting lidar data. The methods for parameterizing the remote sensing models with the IBGM and developing Look Up Tables will be discussed. Results from various remote sensing scenarios will also be presented.

Simulating imaging spectrometer data of a mixed old-growth forest: A parameterization of a 3D radiative transfer model based on airborne and terrestrial laser scanning

NASA Astrophysics Data System (ADS)

Schneider, F. D.; Leiterer, R.; Morsdorf, F.; Gastellu-Etchegorry, J.; Lauret, N.; Pfeifer, N.; Schaepman, M. E.

2013-12-01

Remote sensing offers unique potential to study forest ecosystems by providing spatially and temporally distributed information that can be linked with key biophysical and biochemical variables. The estimation of biochemical constituents of leaves from remotely sensed data is of high interest revealing insight on photosynthetic processes, plant health, plant functional types, and speciation. However, the scaling of observations at the canopy level to the leaf level or vice versa is not trivial due to the structural complexity of forests. Thus, a common solution for scaling spectral information is the use of physically-based radiative transfer models. The discrete anisotropic radiative transfer model (DART), being one of the most complete coupled canopy-atmosphere 3D radiative transfer models, was parameterized based on airborne and in-situ measurements. At-sensor radiances were simulated and compared with measurements from an airborne imaging spectrometer. The study was performed on the Laegern site, a temperate mixed forest characterized by steep slopes, a heterogeneous spectral background, and deciduous and coniferous trees at different development stages (dominated by beech trees; 47°28'42.0' N, 8°21'51.8' E, 682 m asl, Switzerland). It is one of the few studies conducted on an old-growth forest. Particularly the 3D modeling of the complex canopy architecture is crucial to model the interaction of photons with the vegetation canopy and its background. Thus, we developed two forest reconstruction approaches: 1) based on a voxel grid, and 2) based on individual tree detection. Both methods are transferable to various forest ecosystems and applicable at scales between plot and landscape. Our results show that the newly developed voxel grid approach is favorable over a parameterization based on individual trees. In comparison to the actual imaging spectrometer data, the simulated images exhibit very similar spatial patterns, whereas absolute radiance values are partially differing depending on the respective wavelength. We conclude that our proposed method provides a representation of the 3D radiative regime within old-growth forests that is suitable for simulating most spectral and spatial features of imaging spectrometer data. It indicates the potential of simulating future Earth observation missions, such as ESA's Sentinel-2. However, the high spectral variability of leaf optical properties among species has to be addressed in future radiative transfer modeling. The results further reveal that research emphasis has to be put on the accurate parameterization of small-scale structures, such as the clumping of needles into shoots or the distribution of leaf angles.

The GIS weasel - An interface for the development of spatial information in modeling

USGS Publications Warehouse

Viger, R.J.; Markstrom, S.M.; Leavesley, G.H.; ,

2005-01-01

The GIS Weasel is a map and Graphical User Interface (GUI) driven tool that has been developed as an aid to modelers in the delineation, characterization of geographic features, and their parameterization for use in distributed or lumped parameter physical process models. The interface does not require user expertise in geographic information systems (GIS). The user does need knowledge of how the model will use the output from the GIS Weasel. The GIS Weasel uses Workstation ArcInfo and its the Grid extension. The GIS Weasel will run on all platforms that Workstation ArcInfo runs (i.e. numerous flavors of Unix and Microsoft Windows).The GIS Weasel requires an input ArcInfo grid of some topographical description of the Area of Interest (AOI). This is normally a digital elevation model, but can be the surface of a ground water table or any other data that flow direction can be resolved from. The user may define the AOI as a custom drainage area based on an interactively specified watershed outlet point, or use a previously created map. The user is then able to use any combination of the GIS Weasel's tool set to create one or more maps for depicting different kinds of geographic features. Once the spatial feature maps have been prepared, then the GIS Weasel s many parameterization routines can be used to create descriptions of each element in each of the user s created maps. Over 200 parameterization routines currently exist, generating information about shape, area, and topological association with other features of the same or different maps, as well many types of information based on ancillary data layers such as soil and vegetation properties. These tools easily integrate other similarly formatted data sets.

Development of a new physics-based internal coordinate mechanics force field and its application to protein loop modeling.

PubMed

Arnautova, Yelena A; Abagyan, Ruben A; Totrov, Maxim

2011-02-01

We report the development of internal coordinate mechanics force field (ICMFF), new force field parameterized using a combination of experimental data for crystals of small molecules and quantum mechanics calculations. The main features of ICMFF include: (a) parameterization for the dielectric constant relevant to the condensed state (ε = 2) instead of vacuum, (b) an improved description of hydrogen-bond interactions using duplicate sets of van der Waals parameters for heavy atom-hydrogen interactions, and (c) improved backbone covalent geometry and energetics achieved using novel backbone torsional potentials and inclusion of the bond angles at the C(α) atoms into the internal variable set. The performance of ICMFF was evaluated through loop modeling simulations for 4-13 residue loops. ICMFF was combined with a solvent-accessible surface area solvation model optimized using a large set of loop decoys. Conformational sampling was carried out using the biased probability Monte Carlo method. Average/median backbone root-mean-square deviations of the lowest energy conformations from the native structures were 0.25/0.21 Å for four residues loops, 0.84/0.46 Å for eight residue loops, and 1.16/0.73 Å for 12 residue loops. To our knowledge, these results are significantly better than or comparable with those reported to date for any loop modeling method that does not take crystal packing into account. Moreover, the accuracy of our method is on par with the best previously reported results obtained considering the crystal environment. We attribute this success to the high accuracy of the new ICM force field achieved by meticulous parameterization, to the optimized solvent model, and the efficiency of the search method. © 2010 Wiley-Liss, Inc.

Development of a coupled wave-flow-vegetation interaction model

USGS Publications Warehouse

Beudin, Alexis; Kalra, Tarandeep S.; Ganju, Neil K.; Warner, John C.

2017-01-01

Emergent and submerged vegetation can significantly affect coastal hydrodynamics. However, most deterministic numerical models do not take into account their influence on currents, waves, and turbulence. In this paper, we describe the implementation of a wave-flow-vegetation module into a Coupled-Ocean-Atmosphere-Wave-Sediment Transport (COAWST) modeling system that includes a flow model (ROMS) and a wave model (SWAN), and illustrate various interacting processes using an idealized shallow basin application. The flow model has been modified to include plant posture-dependent three-dimensional drag, in-canopy wave-induced streaming, and production of turbulent kinetic energy and enstrophy to parameterize vertical mixing. The coupling framework has been updated to exchange vegetation-related variables between the flow model and the wave model to account for wave energy dissipation due to vegetation. This study i) demonstrates the validity of the plant posture-dependent drag parameterization against field measurements, ii) shows that the model is capable of reproducing the mean and turbulent flow field in the presence of vegetation as compared to various laboratory experiments, iii) provides insight into the flow-vegetation interaction through an analysis of the terms in the momentum balance, iv) describes the influence of a submerged vegetation patch on tidal currents and waves separately and combined, and v) proposes future directions for research and development.

Highly parameterized model calibration with cloud computing: an example of regional flow model calibration in northeast Alberta, Canada

NASA Astrophysics Data System (ADS)

Hayley, Kevin; Schumacher, J.; MacMillan, G. J.; Boutin, L. C.

2014-05-01

Expanding groundwater datasets collected by automated sensors, and improved groundwater databases, have caused a rapid increase in calibration data available for groundwater modeling projects. Improved methods of subsurface characterization have increased the need for model complexity to represent geological and hydrogeological interpretations. The larger calibration datasets and the need for meaningful predictive uncertainty analysis have both increased the degree of parameterization necessary during model calibration. Due to these competing demands, modern groundwater modeling efforts require a massive degree of parallelization in order to remain computationally tractable. A methodology for the calibration of highly parameterized, computationally expensive models using the Amazon EC2 cloud computing service is presented. The calibration of a regional-scale model of groundwater flow in Alberta, Canada, is provided as an example. The model covers a 30,865-km2 domain and includes 28 hydrostratigraphic units. Aquifer properties were calibrated to more than 1,500 static hydraulic head measurements and 10 years of measurements during industrial groundwater use. Three regionally extensive aquifers were parameterized (with spatially variable hydraulic conductivity fields), as was the aerial recharge boundary condition, leading to 450 adjustable parameters in total. The PEST-based model calibration was parallelized on up to 250 computing nodes located on Amazon's EC2 servers.

Performance Analysis of GFDL's GCM Line-By-Line Radiative Transfer Model on GPU and MIC Architectures

NASA Astrophysics Data System (ADS)

Menzel, R.; Paynter, D.; Jones, A. L.

2017-12-01

Due to their relatively low computational cost, radiative transfer models in global climate models (GCMs) run on traditional CPU architectures generally consist of shortwave and longwave parameterizations over a small number of wavelength bands. With the rise of newer GPU and MIC architectures, however, the performance of high resolution line-by-line radiative transfer models may soon approach those of the physical parameterizations currently employed in GCMs. Here we present an analysis of the current performance of a new line-by-line radiative transfer model currently under development at GFDL. Although originally designed to specifically exploit GPU architectures through the use of CUDA, the radiative transfer model has recently been extended to include OpenMP in an effort to also effectively target MIC architectures such as Intel's Xeon Phi. Using input data provided by the upcoming Radiative Forcing Model Intercomparison Project (RFMIP, as part of CMIP 6), we compare model results and performance data for various model configurations and spectral resolutions run on both GPU and Intel Knights Landing architectures to analogous runs of the standard Oxford Reference Forward Model on traditional CPUs.

Structural and parameteric uncertainty quantification in cloud microphysics parameterization schemes

NASA Astrophysics Data System (ADS)

van Lier-Walqui, M.; Morrison, H.; Kumjian, M. R.; Prat, O. P.; Martinkus, C.

2017-12-01

Atmospheric model parameterization schemes employ approximations to represent the effects of unresolved processes. These approximations are a source of error in forecasts, caused in part by considerable uncertainty about the optimal value of parameters within each scheme -- parameteric uncertainty. Furthermore, there is uncertainty regarding the best choice of the overarching structure of the parameterization scheme -- structrual uncertainty. Parameter estimation can constrain the first, but may struggle with the second because structural choices are typically discrete. We address this problem in the context of cloud microphysics parameterization schemes by creating a flexible framework wherein structural and parametric uncertainties can be simultaneously constrained. Our scheme makes no assuptions about drop size distribution shape or the functional form of parametrized process rate terms. Instead, these uncertainties are constrained by observations using a Markov Chain Monte Carlo sampler within a Bayesian inference framework. Our scheme, the Bayesian Observationally-constrained Statistical-physical Scheme (BOSS), has flexibility to predict various sets of prognostic drop size distribution moments as well as varying complexity of process rate formulations. We compare idealized probabilistic forecasts from versions of BOSS with varying levels of structural complexity. This work has applications in ensemble forecasts with model physics uncertainty, data assimilation, and cloud microphysics process studies.

Climate and the equilibrium state of land surface hydrology parameterizations

NASA Technical Reports Server (NTRS)

Entekhabi, Dara; Eagleson, Peter S.

1991-01-01

For given climatic rates of precipitation and potential evaporation, the land surface hydrology parameterizations of atmospheric general circulation models will maintain soil-water storage conditions that balance the moisture input and output. The surface relative soil saturation for such climatic conditions serves as a measure of the land surface parameterization state under a given forcing. The equilibrium value of this variable for alternate parameterizations of land surface hydrology are determined as a function of climate and the sensitivity of the surface to shifts and changes in climatic forcing are estimated.

SUMMA and Model Mimicry: Understanding Differences Among Land Models

NASA Astrophysics Data System (ADS)

Nijssen, B.; Nearing, G. S.; Ou, G.; Clark, M. P.

2016-12-01

Model inter-comparison and model ensemble experiments suffer from an inability to explain the mechanisms behind differences in model outcomes. We can clearly demonstrate that the models are different, but we cannot necessarily identify the reasons why, because most models exhibit myriad differences in process representations, model parameterizations, model parameters and numerical solution methods. This inability to identify the reasons for differences in model performance hampers our understanding and limits model improvement, because we cannot easily identify the most promising paths forward. We have developed the Structure for Unifying Multiple Modeling Alternatives (SUMMA) to allow for controlled experimentation with model construction, numerical techniques, and parameter values and therefore isolate differences in model outcomes to specific choices during the model development process. In developing SUMMA, we recognized that hydrologic models can be thought of as individual instantiations of a master modeling template that is based on a common set of conservation equations for energy and water. Given this perspective, SUMMA provides a unified approach to hydrologic modeling that integrates different modeling methods into a consistent structure with the ability to instantiate alternative hydrologic models at runtime. Here we employ SUMMA to revisit a previous multi-model experiment and demonstrate its use for understanding differences in model performance. Specifically, we implement SUMMA to mimic the spread of behaviors exhibited by the land models that participated in the Protocol for the Analysis of Land Surface Models (PALS) Land Surface Model Benchmarking Evaluation Project (PLUMBER) and draw conclusions about the relative performance of specific model parameterizations for water and energy fluxes through the soil-vegetation continuum. SUMMA's ability to mimic the spread of model ensembles and the behavior of individual models can be an important tool in focusing model development and improvement efforts.

Determination of the 4D-Tropospheric Water Vapor Distribution by GPS for the Assimilation into Numerical Weather Prediction Models

NASA Astrophysics Data System (ADS)

Perler, D.; Geiger, A.; Rothacher, M.

2011-12-01

Water vapor is involved in many atmospheric processes and is therefore a crucial quantity in numerical weather prediction (NWP). Recent flood events in Switzerland have pointed out several deficiencies in planning and prediction methods used for flood risk mitigation. Investigations have shown that one of the limiting factors to forecast such events with NWP models is the insufficient knowledge of the water vapor distribution in the atmosphere. Global Navigation Satellite System (GNSS) ground-based tomography is a technique to monitor the 4D distribution of water vapor in the troposphere and has the potential to considerably improve the initial water vapor field used in NWP. We developed a GNSS tomography software called AWATOS-2 which is based on the Kalman filter technique and provides different parameterizations of the tropospheric wet refractivity field (Perler et al., 2010; Perler et al., 2011). The software can be used for the assimilation of different observations such as GNSS zero-differences, GNSS double-differences and any kind of point observations (e.g. balloons, aircrafts). In this talk, we present the results of a long-term study where GPS double-difference delays have been processed. The tomographic solutions have been investigated in view of their assimilation into local NWP models. The data set comprises observations from 46 GPS stations collected during 1 year. The core area of the investigation is located in Central Europe. We analyzed the performance of different voxel parameterizations used in the tomographic reconstruction of the troposphere and developed a new bias correction model which minimizes systematic differences. The correction model reduces the root-mean-square error (RMSE) with respected to the NWP model from 4.6 ppm to 3.0 ppm. After bias correction, high-elevation stations still show high RMSEs. In the presentation, we will discuss the treatment of such stations in terms of assimilation into NWP models and will show how sophisticated voxel parameterizations improve the accuracy. Perler, D.; Hurter, F.; Brockmann, E.; Leuenberger, D.; Ruffieux, D.; Geiger, A. and Rothacher, M. (2010). In Proceedings of the 7th Management Committee (MC7) and Working Group (WG) Meeting, Colone (Germany), 8 pp. Perler, D.; Geiger, A. and Hurter, F. (2011). 4D GPS water vapor tomography: new parameterized approaches. J. Geodesy 85(8), pp. 539-550, DOI 10.1007/s00190-011-0454-2.

Adaptively Parameterized Tomography of the Western Hellenic Subduction Zone

NASA Astrophysics Data System (ADS)

Hansen, S. E.; Papadopoulos, G. A.

2017-12-01

The Hellenic subduction zone (HSZ) is the most seismically active region in Europe and plays a major role in the active tectonics of the eastern Mediterranean. This complicated environment has the potential to generate both large magnitude (M > 8) earthquakes and tsunamis. Situated above the western end of the HSZ, Greece faces a high risk from these geologic hazards, and characterizing this risk requires detailed understanding of the geodynamic processes occurring in this area. However, despite previous investigations, the kinematics of the HSZ are still controversial. Regional tomographic studies have yielded important information about the shallow seismic structure of the HSZ, but these models only image down to 150 km depth within small geographic areas. Deeper structure is constrained by global tomographic models but with coarser resolution ( 200-300 km). Additionally, current tomographic models focused on the HSZ were generated with regularly-spaced gridding, and this type of parameterization often over-emphasizes poorly sampled regions of the model or under-represents small-scale structure. Therefore, we are developing a new, high-resolution image of the mantle structure beneath the western HSZ using an adaptively parameterized seismic tomography approach. By combining multiple, regional travel-time datasets in the context of a global model, with adaptable gridding based on the sampling density of high-frequency data, this method generates a composite model of mantle structure that is being used to better characterize geodynamic processes within the HSZ, thereby allowing for improved hazard assessment. Preliminary results will be shown.

Alternative ways of using field-based estimates to calibrate ecosystem models and their implications for carbon cycle studies

USGS Publications Warehouse

He, Yujie; Zhuang, Qianlai; McGuire, David; Liu, Yaling; Chen, Min

2013-01-01

Model-data fusion is a process in which field observations are used to constrain model parameters. How observations are used to constrain parameters has a direct impact on the carbon cycle dynamics simulated by ecosystem models. In this study, we present an evaluation of several options for the use of observations in modeling regional carbon dynamics and explore the implications of those options. We calibrated the Terrestrial Ecosystem Model on a hierarchy of three vegetation classification levels for the Alaskan boreal forest: species level, plant-functional-type level (PFT level), and biome level, and we examined the differences in simulated carbon dynamics. Species-specific field-based estimates were directly used to parameterize the model for species-level simulations, while weighted averages based on species percent cover were used to generate estimates for PFT- and biome-level model parameterization. We found that calibrated key ecosystem process parameters differed substantially among species and overlapped for species that are categorized into different PFTs. Our analysis of parameter sets suggests that the PFT-level parameterizations primarily reflected the dominant species and that functional information of some species were lost from the PFT-level parameterizations. The biome-level parameterization was primarily representative of the needleleaf PFT and lost information on broadleaf species or PFT function. Our results indicate that PFT-level simulations may be potentially representative of the performance of species-level simulations while biome-level simulations may result in biased estimates. Improved theoretical and empirical justifications for grouping species into PFTs or biomes are needed to adequately represent the dynamics of ecosystem functioning and structure.

Evaluation of Extratropical Cyclone Precipitation in the North Atlantic Basin: An analysis of ERA-Interim, WRF, and two CMIP5 models.

PubMed

Booth, James F; Naud, Catherine M; Willison, Jeff

2018-03-01

The representation of extratropical cyclones (ETCs) precipitation in general circulation models (GCMs) and a weather research and forecasting (WRF) model is analyzed. This work considers the link between ETC precipitation and dynamical strength and tests if parameterized convection affects this link for ETCs in the North Atlantic Basin. Lagrangian cyclone tracks of ETCs in ERA-Interim reanalysis (ERAI), the GISS and GFDL CMIP5 models, and WRF with two horizontal resolutions are utilized in a compositing analysis. The 20-km resolution WRF model generates stronger ETCs based on surface wind speed and cyclone precipitation. The GCMs and ERAI generate similar composite means and distributions for cyclone precipitation rates, but GCMs generate weaker cyclone surface winds than ERAI. The amount of cyclone precipitation generated by the convection scheme differs significantly across the datasets, with GISS generating the most, followed by ERAI and then GFDL. The models and reanalysis generate relatively more parameterized convective precipitation when the total cyclone-averaged precipitation is smaller. This is partially due to the contribution of parameterized convective precipitation occurring more often late in the ETC life cycle. For reanalysis and models, precipitation increases with both cyclone moisture and surface wind speed, and this is true if the contribution from the parameterized convection scheme is larger or not. This work shows that these different models generate similar total ETC precipitation despite large differences in the parameterized convection, and these differences do not cause unexpected behavior in ETC precipitation sensitivity to cyclone moisture or surface wind speed.

Modeling particle nucleation and growth over northern California during the 2010 CARES campaign

NASA Astrophysics Data System (ADS)

Lupascu, A.; Easter, R.; Zaveri, R.; Shrivastava, M.; Pekour, M.; Tomlinson, J.; Yang, Q.; Matsui, H.; Hodzic, A.; Zhang, Q.; Fast, J. D.

2015-11-01

Accurate representation of the aerosol lifecycle requires adequate modeling of the particle number concentration and size distribution in addition to their mass, which is often the focus of aerosol modeling studies. This paper compares particle number concentrations and size distributions as predicted by three empirical nucleation parameterizations in the Weather Research and Forecast coupled with chemistry (WRF-Chem) regional model using 20 discrete size bins ranging from 1 nm to 10 μm. Two of the parameterizations are based on H2SO4, while one is based on both H2SO4 and organic vapors. Budget diagnostic terms for transport, dry deposition, emissions, condensational growth, nucleation, and coagulation of aerosol particles have been added to the model and are used to analyze the differences in how the new particle formation parameterizations influence the evolving aerosol size distribution. The simulations are evaluated using measurements collected at surface sites and from a research aircraft during the Carbonaceous Aerosol and Radiative Effects Study (CARES) conducted in the vicinity of Sacramento, California. While all three parameterizations captured the temporal variation of the size distribution during observed nucleation events as well as the spatial variability in aerosol number, all overestimated by up to a factor of 2.5 the total particle number concentration for particle diameters greater than 10 nm. Using the budget diagnostic terms, we demonstrate that the combined H2SO4 and low-volatility organic vapor parameterization leads to a different diurnal variability of new particle formation and growth to larger sizes compared to the parameterizations based on only H2SO4. At the CARES urban ground site, peak nucleation rates are predicted to occur around 12:00 Pacific (local) standard time (PST) for the H2SO4 parameterizations, whereas the highest rates were predicted at 08:00 and 16:00 PST when low-volatility organic gases are included in the parameterization. This can be explained by higher anthropogenic emissions of organic vapors at these times as well as lower boundary-layer heights that reduce vertical mixing. The higher nucleation rates in the H2SO4-organic parameterization at these times were largely offset by losses due to coagulation. Despite the different budget terms for ultrafine particles, the 10-40 nm diameter particle number concentrations from all three parameterizations increased from 10:00 to 14:00 PST and then decreased later in the afternoon, consistent with changes in the observed size and number distribution. We found that newly formed particles could explain up to 20-30 % of predicted cloud condensation nuclei at 0.5 % supersaturation, depending on location and the specific nucleation parameterization. A sensitivity simulation using 12 discrete size bins ranging from 1 nm to 10 μm diameter gave a reasonable estimate of particle number and size distribution compared to the 20 size bin simulation, while reducing the associated computational cost by ~ 36 %.

Integration of nitrogen dynamics into the Noah-MP land surface model v1.1 for climate and environmental predictions

DOE PAGES

Cai, X.; Yang, Z. -L.; Fisher, J. B.; ...

2016-01-15

Climate and terrestrial biosphere models consider nitrogen an important factor in limiting plant carbon uptake, while operational environmental models view nitrogen as the leading pollutant causing eutrophication in water bodies. The community Noah land surface model with multi-parameterization options (Noah-MP) is unique in that it is the next-generation land surface model for the Weather Research and Forecasting meteorological model and for the operational weather/climate models in the National Centers for Environmental Prediction. Here in this study, we add a capability to Noah-MP to simulate nitrogen dynamics by coupling the Fixation and Uptake of Nitrogen (FUN) plant model and the Soilmore » and Water Assessment Tool (SWAT) soil nitrogen dynamics. This model development incorporates FUN's state-of-the-art concept of carbon cost theory and SWAT's strength in representing the impacts of agricultural management on the nitrogen cycle. Parameterizations for direct root and mycorrhizal-associated nitrogen uptake, leaf retranslocation, and symbiotic biological nitrogen fixation are employed from FUN, while parameterizations for nitrogen mineralization, nitrification, immobilization, volatilization, atmospheric deposition, and leaching are based on SWAT. The coupled model is then evaluated at the Kellogg Biological Station – a Long Term Ecological Research site within the US Corn Belt. Results show that the model performs well in capturing the major nitrogen state/flux variables (e.g., soil nitrate and nitrate leaching). Furthermore, the addition of nitrogen dynamics improves the modeling of net primary productivity and evapotranspiration. The model improvement is expected to advance the capability of Noah-MP to simultaneously predict weather and water quality in fully coupled Earth system models.« less

Integration of nitrogen dynamics into the Noah-MP land surface model v1.1 for climate and environmental predictions

DOE Office of Scientific and Technical Information (OSTI.GOV)

Cai, X.; Yang, Z. -L.; Fisher, J. B.

Climate and terrestrial biosphere models consider nitrogen an important factor in limiting plant carbon uptake, while operational environmental models view nitrogen as the leading pollutant causing eutrophication in water bodies. The community Noah land surface model with multi-parameterization options (Noah-MP) is unique in that it is the next-generation land surface model for the Weather Research and Forecasting meteorological model and for the operational weather/climate models in the National Centers for Environmental Prediction. Here in this study, we add a capability to Noah-MP to simulate nitrogen dynamics by coupling the Fixation and Uptake of Nitrogen (FUN) plant model and the Soilmore » and Water Assessment Tool (SWAT) soil nitrogen dynamics. This model development incorporates FUN's state-of-the-art concept of carbon cost theory and SWAT's strength in representing the impacts of agricultural management on the nitrogen cycle. Parameterizations for direct root and mycorrhizal-associated nitrogen uptake, leaf retranslocation, and symbiotic biological nitrogen fixation are employed from FUN, while parameterizations for nitrogen mineralization, nitrification, immobilization, volatilization, atmospheric deposition, and leaching are based on SWAT. The coupled model is then evaluated at the Kellogg Biological Station – a Long Term Ecological Research site within the US Corn Belt. Results show that the model performs well in capturing the major nitrogen state/flux variables (e.g., soil nitrate and nitrate leaching). Furthermore, the addition of nitrogen dynamics improves the modeling of net primary productivity and evapotranspiration. The model improvement is expected to advance the capability of Noah-MP to simultaneously predict weather and water quality in fully coupled Earth system models.« less

Using field observations to inform thermal hydrology models of permafrost dynamics with ATS (v0.83)

DOE PAGES

Atchley, Adam L.; Painter, Scott L.; Harp, Dylan R.; ...

2015-09-01

Climate change is profoundly transforming the carbon-rich Arctic tundra landscape, potentially moving it from a carbon sink to a carbon source by increasing the thickness of soil that thaws on a seasonal basis. Thus, the modeling capability and precise parameterizations of the physical characteristics needed to estimate projected active layer thickness (ALT) are limited in Earth system models (ESMs). In particular, discrepancies in spatial scale between field measurements and Earth system models challenge validation and parameterization of hydrothermal models. A recently developed surface–subsurface model for permafrost thermal hydrology, the Advanced Terrestrial Simulator (ATS), is used in combination with field measurementsmore » to achieve the goals of constructing a process-rich model based on plausible parameters and to identify fine-scale controls of ALT in ice-wedge polygon tundra in Barrow, Alaska. An iterative model refinement procedure that cycles between borehole temperature and snow cover measurements and simulations functions to evaluate and parameterize different model processes necessary to simulate freeze–thaw processes and ALT formation. After model refinement and calibration, reasonable matches between simulated and measured soil temperatures are obtained, with the largest errors occurring during early summer above ice wedges (e.g., troughs). The results suggest that properly constructed and calibrated one-dimensional thermal hydrology models have the potential to provide reasonable representation of the subsurface thermal response and can be used to infer model input parameters and process representations. The models for soil thermal conductivity and snow distribution were found to be the most sensitive process representations. However, information on lateral flow and snowpack evolution might be needed to constrain model representations of surface hydrology and snow depth.« less

Impact of parameterization of physical processes on simulation of track and intensity of tropical cyclone Nargis (2008) with WRF-NMM model.

PubMed

Pattanayak, Sujata; Mohanty, U C; Osuri, Krishna K

2012-01-01

The present study is carried out to investigate the performance of different cumulus convection, planetary boundary layer, land surface processes, and microphysics parameterization schemes in the simulation of a very severe cyclonic storm (VSCS) Nargis (2008), developed in the central Bay of Bengal on 27 April 2008. For this purpose, the nonhydrostatic mesoscale model (NMM) dynamic core of weather research and forecasting (WRF) system is used. Model-simulated track positions and intensity in terms of minimum central mean sea level pressure (MSLP), maximum surface wind (10 m), and precipitation are verified with observations as provided by the India Meteorological Department (IMD) and Tropical Rainfall Measurement Mission (TRMM). The estimated optimum combination is reinvestigated with six different initial conditions of the same case to have better conclusion on the performance of WRF-NMM. A few more diagnostic fields like vertical velocity, vorticity, and heat fluxes are also evaluated. The results indicate that cumulus convection play an important role in the movement of the cyclone, and PBL has a crucial role in the intensification of the storm. The combination of Simplified Arakawa Schubert (SAS) convection, Yonsei University (YSU) PBL, NMM land surface, and Ferrier microphysics parameterization schemes in WRF-NMM give better track and intensity forecast with minimum vector displacement error.

A Comparison between High-Energy Radiation Background Models and SPENVIS Trapped-Particle Radiation Models

NASA Technical Reports Server (NTRS)

Krizmanic, John F.

2013-01-01

We have been assessing the effects of background radiation in low-Earth orbit for the next generation of X-ray and Cosmic-ray experiments, in particular for International Space Station orbit. Outside the areas of high fluxes of trapped radiation, we have been using parameterizations developed by the Fermi team to quantify the high-energy induced background. For the low-energy background, we have been using the AE8 and AP8 SPENVIS models to determine the orbit fractions where the fluxes of trapped particles are too high to allow for useful operation of the experiment. One area we are investigating is how the fluxes of SPENVIS predictions at higher energies match the fluxes at the low-energy end of our parameterizations. I will summarize our methodology for background determination from the various sources of cosmogenic and terrestrial radiation and how these compare to SPENVIS predictions in overlapping energy ranges.

Precipitation Processes developed during ARM (1997), TOGA COARE (1992), GATE (1974), SCSMEX (1998), and KWAJEX (1999), Consistent 2D, semi-3D and 3D Cloud Resolving Model Simulations

NASA Technical Reports Server (NTRS)

Tao, Wei-Kuo; Hou, A.; Atlas, R.; Starr, D.; Sud, Y.

2003-01-01

Real clouds and cloud systems are inherently three-dimensional (3D). Because of the limitations in computer resources, however, most cloud-resolving models (CRMs) today are still two-dimensional (2D). A few 3D CRMs have been used to study the response of clouds to large-scale forcing. In these 3D simulations, the model domain was small, and the integration time was 6 hours. The major objectives of this paper are: (1) to assess the performance of the super-parameterization technique (i.e. is 2D or semi-3D CRM appropriate for the super-parameterization?); (2) calculate and examine the surface energy (especially radiation) and water budgets; (3) identify the differences and similarities in the organization and entrainment rates of convection between simulated 2D and 3D cloud systems.

The terminal area simulation system. Volume 1: Theoretical formulation

NASA Technical Reports Server (NTRS)

Proctor, F. H.

1987-01-01

A three-dimensional numerical cloud model was developed for the general purpose of studying convective phenomena. The model utilizes a time splitting integration procedure in the numerical solution of the compressible nonhydrostatic primitive equations. Turbulence closure is achieved by a conventional first-order diagnostic approximation. Open lateral boundaries are incorporated which minimize wave reflection and which do not induce domain-wide mass trends. Microphysical processes are governed by prognostic equations for potential temperature water vapor, cloud droplets, ice crystals, rain, snow, and hail. Microphysical interactions are computed by numerous Orville-type parameterizations. A diagnostic surface boundary layer is parameterized assuming Monin-Obukhov similarity theory. The governing equation set is approximated on a staggered three-dimensional grid with quadratic-conservative central space differencing. Time differencing is approximated by the second-order Adams-Bashforth method. The vertical grid spacing may be either linear or stretched. The model domain may translate along with a convective cell, even at variable speeds.

Parameterized Radiative Convective Equilibrium Across a Range of Domains: A Unifying Tool for General Circulation Models and High Resolution Models

NASA Astrophysics Data System (ADS)

Silvers, L. G.; Stevens, B. B.; Mauritsen, T.; Marco, G. A.

2015-12-01

The characteristics of clouds in General Circulation Models (GCMs) need to be constrained in a consistent manner with theory, observations, and high resolution models (HRMs). One way forward is to base improvements of parameterizations on high resolution studies which resolve more of the important dynamical motions and allow for less parameterizations. This is difficult because of the numerous differences between GCMs and HRMs, both technical and theoretical. Century long simulations at resolutions of 20-250 km on a global domain are typical of GCMs while HRMs often simulate hours at resolutions of 0.1km-5km on domains the size of a single GCM grid cell. The recently developed mode ICON provides a flexible framework which allows many of these difficulties to be overcome. This study uses the ICON model to compute SST perturbation simulations on multiple domains in a state of Radiative Convective Equilibrium (RCE) with parameterized convection. The domains used range from roughly the size of Texas to nearly half of Earth's surface area. All simulations use a doubly periodic domain with an effective distance between cell centers of 13 km and are integrated to a state of statistical stationarity. The primary analysis examines the mean characteristics of the cloud related fields and the feedback parameter of the simulations. It is shown that the simulated atmosphere of a GCM in RCE is sufficiently similar across a range of domain sizes to justify the use of RCE to study both a GCM and a HRM on the same domain with the goal of improved constraints on the parameterized clouds. The simulated atmospheres are comparable to what could be expected at midday in a typical region of Earth's tropics under calm conditions. In particular, the differences between the domains are smaller than differences which result from choosing different physics schemes. Significant convective organization is present on all domain sizes with a relatively high subsidence fraction. Notwithstanding the overall qualitative similarities of the simulations, quantitative differences lead to a surprisingly large sensitivity of the feedback parameter. This range of the feedback parameter is more than a factor of two and is similar to the range of feedbacks which were obtained by the CMIP5 models.

Aerosol indirect effect on the grid-scale clouds in the two-way coupled WRF-CMAQ: model description, development, evaluation and regional analysis

EPA Science Inventory

This study implemented first, second and glaciations aerosol indirect effects (AIE) on resolved clouds in the two-way coupled WRF-CMAQ modeling system by including parameterizations for both cloud drop and ice number concentrations on the basis of CMAQ predicted aerosol distribu...

Projecting land-use and land cover change in a subtropical urban watershed

Treesearch

John J. Lagrosa IV; Wayne C. Zipperer; Michael G. Andreu

2018-01-01

Urban landscapes are heterogeneous mosaics that develop via significant land-use and land cover (LULC) change. Current LULC models project future landscape patterns, but generally avoid urban landscapes due to heterogeneity. To project LULC change for an urban landscape, we parameterize an established LULC model (Dyna-CLUE) under baseline conditions (continued current...

Representing the effects of stratosphere–troposphere exchange on 3-D O3 distributions in chemistry transport models using a potential vorticity-based parameterization

EPA Science Inventory

Downward transport of ozone (O3) from the stratosphere can be a significant contributor to tropospheric O3 background levels. However, this process often is not well represented in current regional models. In this study, we develop a seasonally and spatially varying potential vor...

Evaluating and Understanding Parameterized Convective Processes and Their Role in the Development of Mesoscale Precipitation Systems

NASA Technical Reports Server (NTRS)

Fritsch, J. Michael; Kain, John S.

1996-01-01

Research efforts focused on numerical simulations of two convective systems with the Penn State/NCAR mesoscale model. The first of these systems was tropical cyclone Irma, which occurred in 1987 in Australia's Gulf of Carpentaria during the AMEX field program. Comparison simulations of this system were done with two different convective parameterization schemes (CPS's), the Kain-Fritsch (KF) and the Betts-Miller (BM) schemes. The second system was the June 10-11, 1985 squall line simulation, which occurred over the Kansas-Oklahoma region during the PRE-STORM experiment. Simulations of this system using the KF scheme were examined in detail.

ARM - Midlatitude Continental Convective Clouds

DOE Data Explorer

Jensen, Mike; Bartholomew, Mary Jane; Genio, Anthony Del; Giangrande, Scott; Kollias, Pavlos

2012-01-19

Convective processes play a critical role in the Earth's energy balance through the redistribution of heat and moisture in the atmosphere and their link to the hydrological cycle. Accurate representation of convective processes in numerical models is vital towards improving current and future simulations of Earths climate system. Despite improvements in computing power, current operational weather and global climate models are unable to resolve the natural temporal and spatial scales important to convective processes and therefore must turn to parameterization schemes to represent these processes. In turn, parameterization schemes in cloud-resolving models need to be evaluated for their generality and application to a variety of atmospheric conditions. Data from field campaigns with appropriate forcing descriptors have been traditionally used by modelers for evaluating and improving parameterization schemes.

ARM - Midlatitude Continental Convective Clouds (comstock-hvps)

DOE Data Explorer

Jensen, Mike; Comstock, Jennifer; Genio, Anthony Del; Giangrande, Scott; Kollias, Pavlos

2012-01-06

Convective processes play a critical role in the Earth's energy balance through the redistribution of heat and moisture in the atmosphere and their link to the hydrological cycle. Accurate representation of convective processes in numerical models is vital towards improving current and future simulations of Earths climate system. Despite improvements in computing power, current operational weather and global climate models are unable to resolve the natural temporal and spatial scales important to convective processes and therefore must turn to parameterization schemes to represent these processes. In turn, parameterization schemes in cloud-resolving models need to be evaluated for their generality and application to a variety of atmospheric conditions. Data from field campaigns with appropriate forcing descriptors have been traditionally used by modelers for evaluating and improving parameterization schemes.

Automatic Parameterization Strategy for Cardiac Electrophysiology Simulations

PubMed Central

Costa, Caroline Mendonca; Hoetzl, Elena; Rocha, Bernardo Martins; Prassl, Anton J; Plank, Gernot

2014-01-01

Driven by recent advances in medical imaging, image segmentation and numerical techniques, computer models of ventricular electrophysiology account for increasingly finer levels of anatomical and biophysical detail. However, considering the large number of model parameters involved parameterization poses a major challenge. A minimum requirement in combined experimental and modeling studies is to achieve good agreement in activation and repolarization sequences between model and experiment or patient data. In this study, we propose basic techniques which aid in determining bidomain parameters to match activation sequences. An iterative parameterization algorithm is implemented which determines appropriate bulk conductivities which yield prescribed velocities. In addition, a method is proposed for splitting the computed bulk conductivities into individual bidomain conductivities by prescribing anisotropy ratios. PMID:24729986

A method for coupling a parameterization of the planetary boundary layer with a hydrologic model

NASA Technical Reports Server (NTRS)

Lin, J. D.; Sun, Shu Fen

1986-01-01

Deardorff's parameterization of the planetary boundary layer is adapted to drive a hydrologic model. The method converts the atmospheric conditions measured at the anemometer height at one site to the mean values in the planetary boundary layer; it then uses the planetary boundary layer parameterization and the hydrologic variables to calculate the fluxes of momentum, heat and moisture at the atmosphere-land interface for a different site. A simplified hydrologic model is used for a simulation study of soil moisture and ground temperature on three different land surface covers. The results indicate that this method can be used to drive a spatially distributed hydrologic model by using observed data available at a meteorological station located on or nearby the site.

Mechanisms controlling primary and new production in a global ecosystem model - Part I: Validation of the biological simulation

NASA Astrophysics Data System (ADS)

Popova, E. E.; Coward, A. C.; Nurser, G. A.; de Cuevas, B.; Fasham, M. J. R.; Anderson, T. R.

2006-12-01

A global general circulation model coupled to a simple six-compartment ecosystem model is used to study the extent to which global variability in primary and export production can be realistically predicted on the basis of advanced parameterizations of upper mixed layer physics, without recourse to introducing extra complexity in model biology. The "K profile parameterization" (KPP) scheme employed, combined with 6-hourly external forcing, is able to capture short-term periodic and episodic events such as diurnal cycling and storm-induced deepening. The model realistically reproduces various features of global ecosystem dynamics that have been problematic in previous global modelling studies, using a single generic parameter set. The realistic simulation of deep convection in the North Atlantic, and lack of it in the North Pacific and Southern Oceans, leads to good predictions of chlorophyll and primary production in these contrasting areas. Realistic levels of primary production are predicted in the oligotrophic gyres due to high frequency external forcing of the upper mixed layer (accompanying paper Popova et al., 2006) and novel parameterizations of zooplankton excretion. Good agreement is shown between model and observations at various JGOFS time series sites: BATS, KERFIX, Papa and HOT. One exception is the northern North Atlantic where lower grazing rates are needed, perhaps related to the dominance of mesozooplankton there. The model is therefore not globally robust in the sense that additional parameterizations are needed to realistically simulate ecosystem dynamics in the North Atlantic. Nevertheless, the work emphasises the need to pay particular attention to the parameterization of mixed layer physics in global ocean ecosystem modelling as a prerequisite to increasing the complexity of ecosystem models.

Development of a lifetime prediction model for lithium-ion batteries based on extended accelerated aging test data

NASA Astrophysics Data System (ADS)

Ecker, Madeleine; Gerschler, Jochen B.; Vogel, Jan; Käbitz, Stefan; Hust, Friedrich; Dechent, Philipp; Sauer, Dirk Uwe

2012-10-01

Battery lifetime prognosis is a key requirement for successful market introduction of electric and hybrid vehicles. This work aims at the development of a lifetime prediction approach based on an aging model for lithium-ion batteries. A multivariable analysis of a detailed series of accelerated lifetime experiments representing typical operating conditions in hybrid electric vehicle is presented. The impact of temperature and state of charge on impedance rise and capacity loss is quantified. The investigations are based on a high-power NMC/graphite lithium-ion battery with good cycle lifetime. The resulting mathematical functions are physically motivated by the occurring aging effects and are used for the parameterization of a semi-empirical aging model. An impedance-based electric-thermal model is coupled to the aging model to simulate the dynamic interaction between aging of the battery and the thermal as well as electric behavior. Based on these models different drive cycles and management strategies can be analyzed with regard to their impact on lifetime. It is an important tool for vehicle designers and for the implementation of business models. A key contribution of the paper is the parameterization of the aging model by experimental data, while aging simulation in the literature usually lacks a robust empirical foundation.

Impact of physical parameterizations on idealized tropical cyclones in the Community Atmosphere Model

NASA Astrophysics Data System (ADS)

Reed, K. A.; Jablonowski, C.

2011-02-01

This paper explores the impact of the physical parameterization suite on the evolution of an idealized tropical cyclone within the National Center for Atmospheric Research's (NCAR) Community Atmosphere Model (CAM). The CAM versions 3.1 and 4 are used to study the development of an initially weak vortex in an idealized environment over a 10-day simulation period within an aqua-planet setup. The main distinction between CAM 3.1 and CAM 4 lies within the physical parameterization of deep convection. CAM 4 now includes a dilute plume Convective Available Potential Energy (CAPE) calculation and Convective Momentum Transport (CMT). The finite-volume dynamical core with 26 vertical levels in aqua-planet mode is used at horizontal grid spacings of 1.0°, 0.5° and 0.25°. It is revealed that CAM 4 produces stronger and larger tropical cyclones by day 10 at all resolutions, with a much earlier onset of intensification when compared to CAM 3.1. At the highest resolution CAM 4 also accounts for changes in the storm's vertical structure, such as an increased outward slope of the wind contours with height, when compared to CAM 3.1. An investigation concludes that the new dilute CAPE calculation in CAM 4 is largely responsible for the changes observed in the development, strength and structure of the tropical cyclone.

The evaluation of GCMs and a new cloud parameterisation using satellite and in-situ data as part of a Climate Process Team

NASA Astrophysics Data System (ADS)

Grosvenor, D. P.; Wood, R.

2012-12-01

As part of one of the Climate Process Teams (CPTs) we have been testing the implementation of a new cloud parameterization into the CAM5 and AM3 GCMs. The CLUBB parameterization replaces all but the deep convection cloud scheme and uses an innovative PDF based approach to diagnose cloud water content and turbulence. We have evaluated the base models and the CLUBB parameterization in the SE Pacific stratocumulus region using a suite of satellite observation metrics including: Liquid Water Path (LWP) measurements from AMSRE; cloud fractions from CloudSat/CALIPSO; droplet concentrations (Nd) and Cloud Top Temperatures from MODIS; CloudSat precipitation; and relationships between Estimated Inversion Strength (calculated from AMSRE SSTs, Cloud Top Temperatures from MODIS and ECMWF re-analysis fields) and cloud fraction. This region has the advantage of an abundance of in-situ aircraft observations taken during the VOCALS campaign, which is facilitating the diagnosis of the model problems highlighted by the model evaluation. This data has also been recently used to demonstrate the reliability of MODIS Nd estimates. The satellite data needs to be filtered to ensure accurate retrievals and we have been careful to apply the same screenings to the model fields. For example, scenes with high cloud fractions and with output times near to the satellite overpass times can be extracted from the model for a fair comparison with MODIS Nd estimates. To facilitate this we have been supplied with instantaneous model output since screening would not be possible based on time averaged data. We also have COSP satellite simulator output, which allows a fairer comparison between satellite and model. For example, COSP cloud fraction is based upon the detection threshold of the satellite instrument in question. These COSP fields are also used for the model output filtering just described. The results have revealed problems with both the base models and the versions with the CLUBB parameterization. The CAM5 model produces realistic near-coast cloud cover, but too little further west in the stratocumulus to cumulus regions. The implementation of CLUBB has vastly improved this situation with cloud cover that is very similar to that observed. CLUBB also improves the Nd field in CAM5 by producing realistic near-coast increases and by removing high Nd values associated with the detrainment of droplets by cumulus clouds. AM3 has a lack of stratocumulus cloud near the South American coast and has much lower droplet concentrations than observed. VOCALS measurements showed that sulfate mass loadings were generally too high in both base models, whereas CCN concentrations were too low. This suggests a problem with the mass distribution partitioning of sulfate that is being investigated. Diurnal and seasonal comparisons have been very illuminating. CLUBB produces very little diurnal variation in LWP, but large variations in precipitation rates. This is likely to point to problems that are now being addressed by the modeling part of the CPT team, creating an iterative workflow process between the model developers and the model testers, which should facilitate efficient parameterization improvement. We will report on the latest developments of this process.

Water balance model for Kings Creek

NASA Technical Reports Server (NTRS)

Wood, Eric F.

1990-01-01

Particular attention is given to the spatial variability that affects the representation of water balance at the catchment scale in the context of macroscale water-balance modeling. Remotely sensed data are employed for parameterization, and the resulting model is developed so that subgrid spatial variability is preserved and therefore influences the grid-scale fluxes of the model. The model permits the quantitative evaluation of the surface-atmospheric interactions related to the large-scale hydrologic water balance.

Idea and implementation studies of populating TOPO250 component with the data from TOPO10 - generalization of geographic information in the BDG database. (Polish Title: Koncepcja i studium implementacji procesu zasilania komponentu TOPO250 danymi TOPO10 - generalizacja informacji geograficznej w bazie danych BDG )

NASA Astrophysics Data System (ADS)

Olszewski, R.; Pillich-Kolipińska, A.; Fiedukowicz, A.

2013-12-01

Implementation of INSPIRE Directive in Poland requires not only legal transposition but also development of a number of technological solutions. The one of such tasks, associated with creation of Spatial Information Infrastructure in Poland, is developing a complex model of georeference database. Significant funding for GBDOT project enables development of the national basic topographical database as a multiresolution database (MRDB). Effective implementation of this type of database requires developing procedures for generalization of geographic information (generalization of digital landscape model - DLM), which, treating TOPO10 component as the only source for creation of TOPO250 component, will allow keeping conceptual and classification consistency between those database elements. To carry out this task, the implementation of the system's concept (prepared previously for Head Office of Geodesy and Cartography) is required. Such system is going to execute the generalization process using constrained-based modeling and allows to keep topological relationships between the objects as well as between the object classes. Full implementation of the designed generalization system requires running comprehensive tests which would help with its calibration and parameterization of the generalization procedures (related to the character of generalized area). Parameterization of this process will allow determining the criteria of specific objects selection, simplification algorithms as well as the operation order. Tests with the usage of differentiated, related to the character of the area, generalization process parameters become nowadays the priority issue. Parameters are delivered to the system in the form of XML files, which, with the help of dedicated tool, are generated from the spreadsheet files (XLS) filled in by user. Using XLS file makes entering and modifying the parameters easier. Among the other elements defined by the external parametric files there are: criteria of object selection, metric parameters of generalization algorithms (e.g. simplification or aggregation) and the operations' sequence. Testing on the trial areas of diverse character will allow developing the rules of generalization process' realization, its parameterization with the proposed tool within the multiresolution reference database. The authors have attempted to develop a generalization process' parameterization for a number of different trial areas. The generalization of the results will contribute to the development of a holistic system of generalized reference data stored in the national geodetic and cartographic resources.

A Heuristic Parameterization for the Integrated Vertical Overlap of Cumulus and Stratus

NASA Astrophysics Data System (ADS)

Park, Sungsu

2017-10-01

The author developed a heuristic parameterization to handle the contrasting vertical overlap structures of cumulus and stratus in an integrated way. The parameterization assumes that cumulus is maximum-randomly overlapped with adjacent cumulus; stratus is maximum-randomly overlapped with adjacent stratus; and radiation and precipitation areas at each model interface are grouped into four categories, that is, convective, stratiform, mixed, and clear areas. For simplicity, thermodynamic scalars within individual portions of cloud, radiation, and precipitation areas are assumed to be internally homogeneous. The parameterization was implemented into the Seoul National University Atmosphere Model version 0 (SAM0) in an offline mode and tested over the globe. The offline control simulation reasonably reproduces the online surface precipitation flux and longwave cloud radiative forcing (LWCF). Although the cumulus fraction is much smaller than the stratus fraction, cumulus dominantly contributes to precipitation production in the tropics. For radiation, however, stratus is dominant. Compared with the maximum overlap, the random overlap of stratus produces stronger LWCF and, surprisingly, more precipitation flux due to less evaporation of convective precipitation. Compared with the maximum overlap, the random overlap of cumulus simulates stronger LWCF and weaker precipitation flux. Compared with the control simulation with separate cumulus and stratus, the simulation with a single-merged cloud substantially enhances the LWCF in the tropical deep convection and midlatitude storm track regions. The process-splitting treatment of convective and stratiform precipitation with an independent precipitation approximation (IPA) simulates weaker surface precipitation flux than the control simulation in the tropical region.

Physically-based modeling of drag force caused by natural woody vegetation

NASA Astrophysics Data System (ADS)

Järvelä, J.; Aberle, J.

2014-12-01

Riparian areas and floodplains are characterized by woody vegetation, which is an essential feature to be accounted for in many hydro-environmental models. For applications including flood protection, river restoration and modelling of sediment processes, there is a need to improve the reliability of flow resistance estimates. Conventional methods such as the use of lumped resistance coefficients or simplistic cylinder-based drag force equations can result in significant errors, as these methods do not adequately address the effect of foliage and reconfiguration of flexible plant parts under flow action. To tackle the problem, physically-based methods relying on objective and measurable vegetation properties are advantageous for describing complex vegetation. We have conducted flume and towing tank investigations with living and artificial plants, both in arrays and with isolated plants, providing new insight into advanced parameterization of natural vegetation. The stem, leaf and total areas of the trees confirmed to be suitable characteristic dimensions for estimating flow resistance. Consequently, we propose the use of leaf area index and leaf-to-stem-area ratio to achieve better drag force estimates. Novel remote sensing techniques including laser scanning have become available for effective collection of the required data. The benefits of the proposed parameterization have been clearly demonstrated in our newest experimental studies, but it remains to be investigated to what extent the parameter values are species-specific and how they depend on local habitat conditions. The purpose of this contribution is to summarize developments in the estimation of vegetative drag force based on physically-based approaches as the latest research results are somewhat dispersed. In particular, concerning woody vegetation we seek to discuss three issues: 1) parameterization of reconfiguration with the Vogel exponent; 2) advantage of parameterizing plants with the leaf area index and leaf-to-stem-area ratio, and 3) effect of plant scale (size from twigs to mature trees). To analyze these issues we use experimental data from the authors' research teams as well as from other researchers. The results are expected to be useful for the design of future experimental campaigns and developing drag force models.

DOE Office of Scientific and Technical Information (OSTI.GOV)

Kuang, Zhiming; Gentine, Pierre

Over the duration of this project, we have made the following advances. 1) We have developed a novel approach to obtain a Lagrangian view of convection from high-resolution numerical model through Lagrangian tracking. This approach nicely complements the more traditionally used Eulerian statistics. We have applied this approach to a range of problem. 2) We have looked into improving and extending our parameterizations based on stochastically entraining parcels, developed previously for shallow convection. 3) This grant also supported our effort on a paper where we compared cumulus parameterizations and cloud resolving models in terms of their linear response functions. Thismore » work will help the community to better evaluate and develop cumulus parameterization. 4) We have applied Lagrangian tracking to shallow convection, deep convection with and without convective organization to better characterize their dynamics and the transition between them. 5) We have devised a novel way of using Lagrangian to identify cold pools, an area identified as of great interest by the ASR community. Our algorithm has a number of advantages and in particular can handle merging cold pools more gracefully than existing techniques. 6) We demonstrated that we can, for the first time, correctly reproduce both the diurnal and seasonal cycle of the hydrologic cycle in the Amazon using a strategy that explicitly represents convection but parameterizes large-scale circulation. In addition we showed that the main cause of the wet season is the presence of an early morning fog, which insulate the surface from top of the atmosphere shortwave radiation. In essence this fog makes the day shorter because radiation cannot penetrate to the surface in the early morning. This is why all fluxes are reduced in the wet season compared to the dry season. 7) We have investigated the life cycle of cold pools and the role of surface diabatic heating. We show that surface heating can kill cold pols and reduce the number of large cold pools and the organization of convection. The effect is quite dramatic over land where the entire distribution of cold pools is modified, and the cold pools are much warmer and more humid with surface diabatic heating below the cold pools. The PI and the co-PI continue to work together on parameterization of cold pools.« less

Parameterization of Model Validating Sets for Uncertainty Bound Optimizations. Revised

NASA Technical Reports Server (NTRS)

Lim, K. B.; Giesy, D. P.

2000-01-01

Given measurement data, a nominal model and a linear fractional transformation uncertainty structure with an allowance on unknown but bounded exogenous disturbances, easily computable tests for the existence of a model validating uncertainty set are given. Under mild conditions, these tests are necessary and sufficient for the case of complex, nonrepeated, block-diagonal structure. For the more general case which includes repeated and/or real scalar uncertainties, the tests are only necessary but become sufficient if a collinearity condition is also satisfied. With the satisfaction of these tests, it is shown that a parameterization of all model validating sets of plant models is possible. The new parameterization is used as a basis for a systematic way to construct or perform uncertainty tradeoff with model validating uncertainty sets which have specific linear fractional transformation structure for use in robust control design and analysis. An illustrative example which includes a comparison of candidate model validating sets is given.

Parameterizing Coefficients of a POD-Based Dynamical System

NASA Technical Reports Server (NTRS)

Kalb, Virginia L.

2010-01-01

A method of parameterizing the coefficients of a dynamical system based of a proper orthogonal decomposition (POD) representing the flow dynamics of a viscous fluid has been introduced. (A brief description of POD is presented in the immediately preceding article.) The present parameterization method is intended to enable construction of the dynamical system to accurately represent the temporal evolution of the flow dynamics over a range of Reynolds numbers. The need for this or a similar method arises as follows: A procedure that includes direct numerical simulation followed by POD, followed by Galerkin projection to a dynamical system has been proven to enable representation of flow dynamics by a low-dimensional model at the Reynolds number of the simulation. However, a more difficult task is to obtain models that are valid over a range of Reynolds numbers. Extrapolation of low-dimensional models by use of straightforward Reynolds-number-based parameter continuation has proven to be inadequate for successful prediction of flows. A key part of the problem of constructing a dynamical system to accurately represent the temporal evolution of the flow dynamics over a range of Reynolds numbers is the problem of understanding and providing for the variation of the coefficients of the dynamical system with the Reynolds number. Prior methods do not enable capture of temporal dynamics over ranges of Reynolds numbers in low-dimensional models, and are not even satisfactory when large numbers of modes are used. The basic idea of the present method is to solve the problem through a suitable parameterization of the coefficients of the dynamical system. The parameterization computations involve utilization of the transfer of kinetic energy between modes as a function of Reynolds number. The thus-parameterized dynamical system accurately predicts the flow dynamics and is applicable to a range of flow problems in the dynamical regime around the Hopf bifurcation. Parameter-continuation software can be used on the parameterized dynamical system to derive a bifurcation diagram that accurately predicts the temporal flow behavior.

Integration of environmental simulation models with satellite remote sensing and geographic information systems technologies: case studies

USGS Publications Warehouse

Steyaert, Louis T.; Loveland, Thomas R.; Brown, Jesslyn F.; Reed, Bradley C.

1993-01-01

Environmental modelers are testing and evaluating a prototype land cover characteristics database for the conterminous United States developed by the EROS Data Center of the U.S. Geological Survey and the University of Nebraska Center for Advanced Land Management Information Technologies. This database was developed from multi temporal, 1-kilometer advanced very high resolution radiometer (AVHRR) data for 1990 and various ancillary data sets such as elevation, ecological regions, and selected climatic normals. Several case studies using this database were analyzed to illustrate the integration of satellite remote sensing and geographic information systems technologies with land-atmosphere interactions models at a variety of spatial and temporal scales. The case studies are representative of contemporary environmental simulation modeling at local to regional levels in global change research, land and water resource management, and environmental simulation modeling at local to regional levels in global change research, land and water resource management and environmental risk assessment. The case studies feature land surface parameterizations for atmospheric mesoscale and global climate models; biogenic-hydrocarbons emissions models; distributed parameter watershed and other hydrological models; and various ecological models such as ecosystem, dynamics, biogeochemical cycles, ecotone variability, and equilibrium vegetation models. The case studies demonstrate the important of multi temporal AVHRR data to develop to develop and maintain a flexible, near-realtime land cover characteristics database. Moreover, such a flexible database is needed to derive various vegetation classification schemes, to aggregate data for nested models, to develop remote sensing algorithms, and to provide data on dynamic landscape characteristics. The case studies illustrate how such a database supports research on spatial heterogeneity, land use, sensitivity analysis, and scaling issues involving regional extrapolations and parameterizations of dynamic land processes within simulation models.

Evaluation of WRF physical parameterizations against ARM/ASR Observations in the post-cold-frontal region to improve low-level clouds representation in CAM5

NASA Astrophysics Data System (ADS)

Lamraoui, F.; Booth, J. F.; Naud, C. M.

2017-12-01

The representation of subgrid-scale processes of low-level marine clouds located in the post-cold-frontal region poses a serious challenge for climate models. More precisely, the boundary layer parameterizations are predominantly designed for individual regimes that can evolve gradually over time and does not accommodate the cold front passage that can overly modify the boundary layer rapidly. Also, the microphysics schemes respond differently to the quick development of the boundary layer schemes, especially under unstable conditions. To improve the understanding of cloud physics in the post-cold frontal region, the present study focuses on exploring the relationship between cloud properties, the local processes and large-scale conditions. In order to address these questions, we explore the WRF sensitivity to the interaction between various combinations of the boundary layer and microphysics parameterizations, including the Community Atmospheric Model version 5 (CAM5) physical package in a perturbed physics ensemble. Then, we evaluate these simulations against ground-based ARM observations over the Azores. The WRF-based simulations demonstrate particular sensitivities of the marine cold front passage and the associated post-cold frontal clouds to the domain size, the resolution and the physical parameterizations. First, it is found that in multiple different case studies the model cannot generate the cold front passage when the domain size is larger than 3000 km2. Instead, the modeled cold front stalls, which shows the importance of properly capturing the synoptic scale conditions. The simulation reveals persistent delay in capturing the cold front passage and also an underestimated duration of the post-cold-frontal conditions. Analysis of the perturbed physics ensemble shows that changing the microphysics scheme leads to larger differences in the modeled clouds than changing the boundary layer scheme. The in-cloud heating tendencies are analyzed to explain this sensitivity.

Exploring Alternative Parameterizations for Snowfall with Validation from Satellite and Terrestrial Radars

NASA Technical Reports Server (NTRS)

Molthan, Andrew L.; Petersen, Walter A.; Case, Jonathan L.; Dembek, Scott R.

2009-01-01

Increases in computational resources have allowed operational forecast centers to pursue experimental, high resolution simulations that resolve the microphysical characteristics of clouds and precipitation. These experiments are motivated by a desire to improve the representation of weather and climate, but will also benefit current and future satellite campaigns, which often use forecast model output to guide the retrieval process. The combination of reliable cloud microphysics and radar reflectivity may constrain radiative transfer models used in satellite simulators during future missions, including EarthCARE and the NASA Global Precipitation Measurement. Aircraft, surface and radar data from the Canadian CloudSat/CALIPSO Validation Project are used to check the validity of size distribution and density characteristics for snowfall simulated by the NASA Goddard six-class, single moment bulk water microphysics scheme, currently available within the Weather Research and Forecast (WRF) Model. Widespread snowfall developed across the region on January 22, 2007, forced by the passing of a mid latitude cyclone, and was observed by the dual-polarimetric, C-band radar King City, Ontario, as well as the NASA 94 GHz CloudSat Cloud Profiling Radar. Combined, these data sets provide key metrics for validating model output: estimates of size distribution parameters fit to the inverse-exponential equations prescribed within the model, bulk density and crystal habit characteristics sampled by the aircraft, and representation of size characteristics as inferred by the radar reflectivity at C- and W-band. Specified constants for distribution intercept and density differ significantly from observations throughout much of the cloud depth. Alternate parameterizations are explored, using column-integrated values of vapor excess to avoid problems encountered with temperature-based parameterizations in an environment where inversions and isothermal layers are present. Simulation of CloudSat reflectivity is performed by adopting the discrete-dipole parameterizations and databases provided in literature, and demonstrate an improved capability in simulating radar reflectivity at W-band versus Mie scattering assumptions.

A test harness for accelerating physics parameterization advancements into operations

NASA Astrophysics Data System (ADS)

Firl, G. J.; Bernardet, L.; Harrold, M.; Henderson, J.; Wolff, J.; Zhang, M.

2017-12-01

The process of transitioning advances in parameterization of sub-grid scale processes from initial idea to implementation is often much quicker than the transition from implementation to use in an operational setting. After all, considerable work must be undertaken by operational centers to fully test, evaluate, and implement new physics. The process is complicated by the scarcity of like-to-like comparisons, availability of HPC resources, and the ``tuning problem" whereby advances in physics schemes are difficult to properly evaluate without first undertaking the expensive and time-consuming process of tuning to other schemes within a suite. To address this process shortcoming, the Global Model TestBed (GMTB), supported by the NWS NGGPS project and undertaken by the Developmental Testbed Center, has developed a physics test harness. It implements the concept of hierarchical testing, where the same code can be tested in model configurations of varying complexity from single column models (SCM) to fully coupled, cycled global simulations. Developers and users may choose at which level of complexity to engage. Several components of the physics test harness have been implemented, including a SCM and an end-to-end workflow that expands upon the one used at NOAA/EMC to run the GFS operationally, although the testbed components will necessarily morph to coincide with changes to the operational configuration (FV3-GFS). A standard, relatively user-friendly interface known as the Interoperable Physics Driver (IPD) is available for physics developers to connect their codes. This prerequisite exercise allows access to the testbed tools and removes a technical hurdle for potential inclusion into the Common Community Physics Package (CCPP). The testbed offers users the opportunity to conduct like-to-like comparisons between the operational physics suite and new development as well as among multiple developments. GMTB staff have demonstrated use of the testbed through a comparison between the 2017 operational GFS suite and one containing the Grell-Freitas convective parameterization. An overview of the physics test harness and its early use will be presented.

Changes in physiological attributes of ponderosa pine from seedling to mature tree

Treesearch

Nancy E. Grulke; William A. Retzlaff

2001-01-01

Plant physiological models are generally parameterized from many different sources of data, including chamber experiments and plantations, from seedlings to mature trees. We obtained a comprehensive data set for a natural stand of ponderosa pine (Pinus ponderosa Laws.) and used these data to parameterize the physiologically based model, TREGRO....

Collaborative Project. A Flexible Atmospheric Modeling Framework for the Community Earth System Model (CESM)

DOE Office of Scientific and Technical Information (OSTI.GOV)

Gettelman, Andrew

2015-10-01

In this project we have been upgrading the Multiscale Modeling Framework (MMF) in the Community Atmosphere Model (CAM), also known as Super-Parameterized CAM (SP-CAM). This has included a major effort to update the coding standards and interface with CAM so that it can be placed on the main development trunk. It has also included development of a new software structure for CAM to be able to handle sub-grid column information. These efforts have formed the major thrust of the work.

A Review on Regional Convection-Permitting Climate Modeling: Demonstrations, Prospects, and Challenges

NASA Astrophysics Data System (ADS)

Prein, A. F.; Langhans, W.; Fosser, G.; Ferrone, A.; Ban, N.; Goergen, K.; Keller, M.; Tölle, M.; Gutjahr, O.; Feser, F.; Brisson, E.; Kollet, S. J.; Schmidli, J.; Van Lipzig, N. P. M.; Leung, L. R.

2015-12-01

Regional climate modeling using convection-permitting models (CPMs; horizontal grid spacing <4 km) emerges as a promising framework to provide more reliable climate information on regional to local scales compared to traditionally used large-scale models (LSMs; horizontal grid spacing >10 km). CPMs no longer rely on convection parameterization schemes, which had been identified as a major source of errors and uncertainties in LSMs. Moreover, CPMs allow for a more accurate representation of surface and orography fields. The drawback of CPMs is the high demand on computational resources. For this reason, first CPM climate simulations only appeared a decade ago. We aim to provide a common basis for CPM climate simulations by giving a holistic review of the topic. The most important components in CPMs such as physical parameterizations and dynamical formulations are discussed critically. An overview of weaknesses and an outlook on required future developments is provided. Most importantly, this review presents the consolidated outcome of studies that addressed the added value of CPM climate simulations compared to LSMs. Improvements are evident mostly for climate statistics related to deep convection, mountainous regions, or extreme events. The climate change signals of CPM simulations suggest an increase in flash floods, changes in hail storm characteristics, and reductions in the snowpack over mountains. In conclusion, CPMs are a very promising tool for future climate research. However, coordinated modeling programs are crucially needed to advance parameterizations of unresolved physics and to assess the full potential of CPMs.

A review on regional convection-permitting climate modeling: Demonstrations, prospects, and challenges.

PubMed

Prein, Andreas F; Langhans, Wolfgang; Fosser, Giorgia; Ferrone, Andrew; Ban, Nikolina; Goergen, Klaus; Keller, Michael; Tölle, Merja; Gutjahr, Oliver; Feser, Frauke; Brisson, Erwan; Kollet, Stefan; Schmidli, Juerg; van Lipzig, Nicole P M; Leung, Ruby

2015-06-01

Regional climate modeling using convection-permitting models (CPMs; horizontal grid spacing <4 km) emerges as a promising framework to provide more reliable climate information on regional to local scales compared to traditionally used large-scale models (LSMs; horizontal grid spacing >10 km). CPMs no longer rely on convection parameterization schemes, which had been identified as a major source of errors and uncertainties in LSMs. Moreover, CPMs allow for a more accurate representation of surface and orography fields. The drawback of CPMs is the high demand on computational resources. For this reason, first CPM climate simulations only appeared a decade ago. In this study, we aim to provide a common basis for CPM climate simulations by giving a holistic review of the topic. The most important components in CPMs such as physical parameterizations and dynamical formulations are discussed critically. An overview of weaknesses and an outlook on required future developments is provided. Most importantly, this review presents the consolidated outcome of studies that addressed the added value of CPM climate simulations compared to LSMs. Improvements are evident mostly for climate statistics related to deep convection, mountainous regions, or extreme events. The climate change signals of CPM simulations suggest an increase in flash floods, changes in hail storm characteristics, and reductions in the snowpack over mountains. In conclusion, CPMs are a very promising tool for future climate research. However, coordinated modeling programs are crucially needed to advance parameterizations of unresolved physics and to assess the full potential of CPMs.

Enhanced basal lubrication and the contribution of the Greenland ice sheet to future sea-level rise

PubMed Central

Shannon, Sarah R.; Payne, Antony J.; Bartholomew, Ian D.; van den Broeke, Michiel R.; Edwards, Tamsin L.; Fettweis, Xavier; Gagliardini, Olivier; Gillet-Chaulet, Fabien; Goelzer, Heiko; Hoffman, Matthew J.; Huybrechts, Philippe; Mair, Douglas W. F.; Nienow, Peter W.; Perego, Mauro; Price, Stephen F.; Smeets, C. J. P. Paul; Sole, Andrew J.; van de Wal, Roderik S. W.; Zwinger, Thomas

2013-01-01

We assess the effect of enhanced basal sliding on the flow and mass budget of the Greenland ice sheet, using a newly developed parameterization of the relation between meltwater runoff and ice flow. A wide range of observations suggest that water generated by melt at the surface of the ice sheet reaches its bed by both fracture and drainage through moulins. Once at the bed, this water is likely to affect lubrication, although current observations are insufficient to determine whether changes in subglacial hydraulics will limit the potential for the speedup of flow. An uncertainty analysis based on our best-fit parameterization admits both possibilities: continuously increasing or bounded lubrication. We apply the parameterization to four higher-order ice-sheet models in a series of experiments forced by changes in both lubrication and surface mass budget and determine the additional mass loss brought about by lubrication in comparison with experiments forced only by changes in surface mass balance. We use forcing from a regional climate model, itself forced by output from the European Centre Hamburg Model (ECHAM5) global climate model run under scenario A1B. Although changes in lubrication generate widespread effects on the flow and form of the ice sheet, they do not affect substantial net mass loss; increase in the ice sheet’s contribution to sea-level rise from basal lubrication is projected by all models to be no more than 5% of the contribution from surface mass budget forcing alone. PMID:23940337

A review on regional convection-permitting climate modeling: Demonstrations, prospects, and challenges

NASA Astrophysics Data System (ADS)

Prein, Andreas F.; Langhans, Wolfgang; Fosser, Giorgia; Ferrone, Andrew; Ban, Nikolina; Goergen, Klaus; Keller, Michael; Tölle, Merja; Gutjahr, Oliver; Feser, Frauke; Brisson, Erwan; Kollet, Stefan; Schmidli, Juerg; van Lipzig, Nicole P. M.; Leung, Ruby

2015-06-01

Regional climate modeling using convection-permitting models (CPMs; horizontal grid spacing <4 km) emerges as a promising framework to provide more reliable climate information on regional to local scales compared to traditionally used large-scale models (LSMs; horizontal grid spacing >10 km). CPMs no longer rely on convection parameterization schemes, which had been identified as a major source of errors and uncertainties in LSMs. Moreover, CPMs allow for a more accurate representation of surface and orography fields. The drawback of CPMs is the high demand on computational resources. For this reason, first CPM climate simulations only appeared a decade ago. In this study, we aim to provide a common basis for CPM climate simulations by giving a holistic review of the topic. The most important components in CPMs such as physical parameterizations and dynamical formulations are discussed critically. An overview of weaknesses and an outlook on required future developments is provided. Most importantly, this review presents the consolidated outcome of studies that addressed the added value of CPM climate simulations compared to LSMs. Improvements are evident mostly for climate statistics related to deep convection, mountainous regions, or extreme events. The climate change signals of CPM simulations suggest an increase in flash floods, changes in hail storm characteristics, and reductions in the snowpack over mountains. In conclusion, CPMs are a very promising tool for future climate research. However, coordinated modeling programs are crucially needed to advance parameterizations of unresolved physics and to assess the full potential of CPMs.

Low Cloud Feedback to Surface Warming in the World's First Global Climate Model with Explicit Embedded Boundary Layer Turbulence

NASA Astrophysics Data System (ADS)

Parishani, H.; Pritchard, M. S.; Bretherton, C. S.; Wyant, M. C.; Khairoutdinov, M.; Singh, B.

2017-12-01

Biases and parameterization formulation uncertainties in the representation of boundary layer clouds remain a leading source of possible systematic error in climate projections. Here we show the first results of cloud feedback to +4K SST warming in a new experimental climate model, the ``Ultra-Parameterized (UP)'' Community Atmosphere Model, UPCAM. We have developed UPCAM as an unusually high-resolution implementation of cloud superparameterization (SP) in which a global set of cloud resolving arrays is embedded in a host global climate model. In UP, the cloud-resolving scale includes sufficient internal resolution to explicitly generate the turbulent eddies that form marine stratocumulus and trade cumulus clouds. This is computationally costly but complements other available approaches for studying low clouds and their climate interaction, by avoiding parameterization of the relevant scales. In a recent publication we have shown that UP, while not without its own complexity trade-offs, can produce encouraging improvements in low cloud climatology in multi-month simulations of the present climate and is a promising target for exascale computing (Parishani et al. 2017). Here we show results of its low cloud feedback to warming in multi-year simulations for the first time. References: Parishani, H., M. S. Pritchard, C. S. Bretherton, M. C. Wyant, and M. Khairoutdinov (2017), Toward low-cloud-permitting cloud superparameterization with explicit boundary layer turbulence, J. Adv. Model. Earth Syst., 9, doi:10.1002/2017MS000968.

Enhanced basal lubrication and the contribution of the Greenland ice sheet to future sea-level rise.

PubMed

Shannon, Sarah R; Payne, Antony J; Bartholomew, Ian D; van den Broeke, Michiel R; Edwards, Tamsin L; Fettweis, Xavier; Gagliardini, Olivier; Gillet-Chaulet, Fabien; Goelzer, Heiko; Hoffman, Matthew J; Huybrechts, Philippe; Mair, Douglas W F; Nienow, Peter W; Perego, Mauro; Price, Stephen F; Smeets, C J P Paul; Sole, Andrew J; van de Wal, Roderik S W; Zwinger, Thomas

2013-08-27

We assess the effect of enhanced basal sliding on the flow and mass budget of the Greenland ice sheet, using a newly developed parameterization of the relation between meltwater runoff and ice flow. A wide range of observations suggest that water generated by melt at the surface of the ice sheet reaches its bed by both fracture and drainage through moulins. Once at the bed, this water is likely to affect lubrication, although current observations are insufficient to determine whether changes in subglacial hydraulics will limit the potential for the speedup of flow. An uncertainty analysis based on our best-fit parameterization admits both possibilities: continuously increasing or bounded lubrication. We apply the parameterization to four higher-order ice-sheet models in a series of experiments forced by changes in both lubrication and surface mass budget and determine the additional mass loss brought about by lubrication in comparison with experiments forced only by changes in surface mass balance. We use forcing from a regional climate model, itself forced by output from the European Centre Hamburg Model (ECHAM5) global climate model run under scenario A1B. Although changes in lubrication generate widespread effects on the flow and form of the ice sheet, they do not affect substantial net mass loss; increase in the ice sheet's contribution to sea-level rise from basal lubrication is projected by all models to be no more than 5% of the contribution from surface mass budget forcing alone.

The parameterization of the planetary boundary layer in the UCLA general circulation model - Formulation and results

NASA Technical Reports Server (NTRS)

Suarez, M. J.; Arakawa, A.; Randall, D. A.

1983-01-01

A planetary boundary layer (PBL) parameterization for general circulation models (GCMs) is presented. It uses a mixed-layer approach in which the PBL is assumed to be capped by discontinuities in the mean vertical profiles. Both clear and cloud-topped boundary layers are parameterized. Particular emphasis is placed on the formulation of the coupling between the PBL and both the free atmosphere and cumulus convection. For this purpose a modified sigma-coordinate is introduced in which the PBL top and the lower boundary are both coordinate surfaces. The use of a bulk PBL formulation with this coordinate is extensively discussed. Results are presented from a July simulation produced by the UCLA GCM. PBL-related variables are shown, to illustrate the various regimes the parameterization is capable of simulating.

A new parameterization of the post-fire snow albedo effect

NASA Astrophysics Data System (ADS)

Gleason, K. E.; Nolin, A. W.

2013-12-01

Mountain snowpack serves as an important natural reservoir of water: recharging aquifers, sustaining streams, and providing important ecosystem services. Reduced snowpacks and earlier snowmelt have been shown to affect fire size, frequency, and severity in the western United States. In turn, wildfire disturbance affects patterns of snow accumulation and ablation by reducing canopy interception, increasing turbulent fluxes, and modifying the surface radiation balance. Recent work shows that after a high severity forest fire, approximately 60% more solar radiation reaches the snow surface due to the reduction in canopy density. Also, significant amounts of pyrogenic carbon particles and larger burned woody debris (BWD) are shed from standing charred trees, which concentrate on the snowpack, darken its surface, and reduce snow albedo by 50% during ablation. Although the post-fire forest environment drives a substantial increase in net shortwave radiation at the snowpack surface, driving earlier and more rapid melt, hydrologic models do not explicitly incorporate forest fire disturbance effects to snowpack dynamics. The objective of this study was to parameterize the post-fire snow albedo effect due to BWD deposition on snow to better represent forest fire disturbance in modeling of snow-dominated hydrologic regimes. Based on empirical results from winter experiments, in-situ snow monitoring, and remote sensing data from a recent forest fire in the Oregon High Cascades, we characterized the post-fire snow albedo effect, and developed a simple parameterization of snowpack albedo decay in the post-fire forest environment. We modified the recession coefficient in the algorithm: α = α0 + K exp (-nr) where α = snowpack albedo, α0 = minimum snowpack albedo (≈0.4), K = constant (≈ 0.44), -n = number of days since last major snowfall, r = recession coefficient [Rohrer and Braun, 1994]. Our parameterization quantified BWD deposition and snow albedo decay rates and related these forest disturbance effects to radiative heating and snow melt rates. We validated our parameterization of the post-fire snow albedo effect at the plot scale using a physically-based, spatially-distributed snow accumulation and melt model, and in-situ eddy covariance and snow monitoring data. This research quantified wildfire impacts to snow dynamics in the Oregon High Cascades, and provided a new parameterization of post-fire drivers to changes in high elevation winter water storage.

PyrE, an interactive fire module within the NASA-GISS Earth System Model

NASA Astrophysics Data System (ADS)

Mezuman, K.; Bauer, S. E.; Tsigaridis, K.

2017-12-01

Fires directly affect the composition of the atmosphere and Earth's radiation balance by emitting a suite of reactive gases and particles. Having an interactive fire module in an Earth System Model allows us to study the natural and anthropogenic drivers, feedbacks, and interactions of biomass burning in different time periods. To do so we have developed PyrE, the NASA-GISS interactive fire emissions model. PyrE uses the flammability, ignition, and suppression parameterization proposed by Pechony and Shindell (2009), and is coupled to a burned area and surface recovery parameterization. The burned area calculation follows CLM's approach (Li et al., 2012), paired with an offline recovery scheme based on Ent's Terrestrial Biosphere Model (Ent TBM) carbon pool turnover time. PyrE is driven by environmental variables calculated by climate simulations, population density data, MODIS fire counts and LAI retrievals, as well as GFED4s emissions. Since the model development required extensive use of reference datasets, in addition to comparing it to GFED4s BA, we evaluate it by studying the effect of fires on atmospheric composition and climate. Our results show good agreement globally, with some regional differences. Finally, we quantify the present day fire radiative forcing. The development of PyrE allowed us for the first time to interactively simulate climate and fire activity with GISS-ModelE3

Electromagnetic forward modelling for realistic Earth models using unstructured tetrahedral meshes and a meshfree approach

NASA Astrophysics Data System (ADS)

Farquharson, C.; Long, J.; Lu, X.; Lelievre, P. G.

2017-12-01

Real-life geology is complex, and so, even when allowing for the diffusive, low resolution nature of geophysical electromagnetic methods, we need Earth models that can accurately represent this complexity when modelling and inverting electromagnetic data. This is particularly the case for the scales, detail and conductivity contrasts involved in mineral and hydrocarbon exploration and development, but also for the larger scale of lithospheric studies. Unstructured tetrahedral meshes provide a flexible means of discretizing a general, arbitrary Earth model. This is important when wanting to integrate a geophysical Earth model with a geological Earth model parameterized in terms of surfaces. Finite-element and finite-volume methods can be derived for computing the electric and magnetic fields in a model parameterized using an unstructured tetrahedral mesh. A number of such variants have been proposed and have proven successful. However, the efficiency and accuracy of these methods can be affected by the "quality" of the tetrahedral discretization, that is, how many of the tetrahedral cells in the mesh are long, narrow and pointy. This is particularly the case if one wants to use an iterative technique to solve the resulting linear system of equations. One approach to deal with this issue is to develop sophisticated model and mesh building and manipulation capabilities in order to ensure that any mesh built from geological information is of sufficient quality for the electromagnetic modelling. Another approach is to investigate other methods of synthesizing the electromagnetic fields. One such example is a "meshfree" approach in which the electromagnetic fields are synthesized using a mesh that is distinct from the mesh used to parameterized the Earth model. There are then two meshes, one describing the Earth model and one used for the numerical mathematics of computing the fields. This means that there are no longer any quality requirements on the model mesh, which makes the process of building a geophysical Earth model from a geological model much simpler. In this presentation we will explore the issues that arise when working with realistic Earth models and when synthesizing geophysical electromagnetic data for them. We briefly consider meshfree methods as a possible means of alleviating some of these issues.

Modelling surface-water depression storage in a Prairie Pothole Region

USGS Publications Warehouse

Hay, Lauren E.; Norton, Parker A.; Viger, Roland; Markstrom, Steven; Regan, R. Steven; Vanderhoof, Melanie

2018-01-01

In this study, the Precipitation-Runoff Modelling System (PRMS) was used to simulate changes in surface-water depression storage in the 1,126-km2 Upper Pipestem Creek basin located within the Prairie Pothole Region of North Dakota, USA. The Prairie Pothole Region is characterized by millions of small water bodies (or surface-water depressions) that provide numerous ecosystem services and are considered an important contribution to the hydrologic cycle. The Upper Pipestem PRMS model was extracted from the U.S. Geological Survey's (USGS) National Hydrologic Model (NHM), developed to support consistent hydrologic modelling across the conterminous United States. The Geospatial Fabric database, created for the USGS NHM, contains hydrologic model parameter values derived from datasets that characterize the physical features of the entire conterminous United States for 109,951 hydrologic response units. Each hydrologic response unit in the Geospatial Fabric was parameterized using aggregated surface-water depression area derived from the National Hydrography Dataset Plus, an integrated suite of application-ready geospatial datasets. This paper presents a calibration strategy for the Upper Pipestem PRMS model that uses normalized lake elevation measurements to calibrate the parameters influencing simulated fractional surface-water depression storage. Results indicate that inclusion of measurements that give an indication of the change in surface-water depression storage in the calibration procedure resulted in accurate changes in surface-water depression storage in the water balance. Regionalized parameterization of the USGS NHM will require a proxy for change in surface-storage to accurately parameterize surface-water depression storage within the USGS NHM.

Evaluating GCM land surface hydrology parameterizations by computing river discharges using a runoff routing model: Application to the Mississippi basin

NASA Technical Reports Server (NTRS)

Liston, G. E.; Sud, Y. C.; Wood, E. F.

1994-01-01

To relate general circulation model (GCM) hydrologic output to readily available river hydrographic data, a runoff routing scheme that routes gridded runoffs through regional- or continental-scale river drainage basins is developed. By following the basin overland flow paths, the routing model generates river discharge hydrographs that can be compared to observed river discharges, thus allowing an analysis of the GCM representation of monthly, seasonal, and annual water balances over large regions. The runoff routing model consists of two linear reservoirs, a surface reservoir and a groundwater reservoir, which store and transport water. The water transport mechanisms operating within these two reservoirs are differentiated by their time scales; the groundwater reservoir transports water much more slowly than the surface reservior. The groundwater reservior feeds the corresponding surface store, and the surface stores are connected via the river network. The routing model is implemented over the Global Energy and Water Cycle Experiment (GEWEX) Continental-Scale International Project Mississippi River basin on a rectangular grid of 2 deg X 2.5 deg. Two land surface hydrology parameterizations provide the gridded runoff data required to run the runoff routing scheme: the variable infiltration capacity model, and the soil moisture component of the simple biosphere model. These parameterizations are driven with 4 deg X 5 deg gridded climatological potential evapotranspiration and 1979 First Global Atmospheric Research Program (GARP) Global Experiment precipitation. These investigations have quantified the importance of physically realistic soil moisture holding capacities, evaporation parameters, and runoff mechanisms in land surface hydrology formulations.

The Super Tuesday Outbreak: Forecast Sensitivities to Single-Moment Microphysics Schemes

NASA Technical Reports Server (NTRS)

Molthan, Andrew L.; Case, Jonathan L.; Dembek, Scott R.; Jedlovec, Gary J.; Lapenta, William M.

2008-01-01

Forecast precipitation and radar characteristics are used by operational centers to guide the issuance of advisory products. As operational numerical weather prediction is performed at increasingly finer spatial resolution, convective precipitation traditionally represented by sub-grid scale parameterization schemes is now being determined explicitly through single- or multi-moment bulk water microphysics routines. Gains in forecasting skill are expected through improved simulation of clouds and their microphysical processes. High resolution model grids and advanced parameterizations are now available through steady increases in computer resources. As with any parameterization, their reliability must be measured through performance metrics, with errors noted and targeted for improvement. Furthermore, the use of these schemes within an operational framework requires an understanding of limitations and an estimate of biases so that forecasters and model development teams can be aware of potential errors. The National Severe Storms Laboratory (NSSL) Spring Experiments have produced daily, high resolution forecasts used to evaluate forecast skill among an ensemble with varied physical parameterizations and data assimilation techniques. In this research, high resolution forecasts of the 5-6 February 2008 Super Tuesday Outbreak are replicated using the NSSL configuration in order to evaluate two components of simulated convection on a large domain: sensitivities of quantitative precipitation forecasts to assumptions within a single-moment bulk water microphysics scheme, and to determine if these schemes accurately depict the reflectivity characteristics of well-simulated, organized, cold frontal convection. As radar returns are sensitive to the amount of hydrometeor mass and the distribution of mass among variably sized targets, radar comparisons may guide potential improvements to a single-moment scheme. In addition, object-based verification metrics are evaluated for their utility in gauging model performance and QPF variability.

Internal wave emission from baroclinic jets: experimental results

NASA Astrophysics Data System (ADS)

Borcia, Ion D.; Rodda, Costanza; Harlander, Uwe

2016-04-01

Large-scale balanced flows can spontaneously radiate meso-scale inertia-gravity waves (IGWs) and are thus in fact unbalanced. While flow-dependent parameterizations for the radiation of IGWs from orographic and convective sources do exist, the situation is less developed for spontaneously emitted IGWs. Observations identify increased IGW activity in the vicinity of jet exit regions. A direct interpretation of those based on geostrophic adjustment might be tempting. However, directly applying this concept to the parameterization of spontaneous imbalance is difficult since the dynamics itself is continuously re-establishing an unbalanced flow which then sheds imbalances by GW radiation. Examining spontaneous IGW emission in the atmosphere and validating parameterization schemes confronts the scientist with particular challenges. Due to its extreme complexity, GW emission will always be embedded in the interaction of a multitude of interdependent processes, many of which are hardly detectable from analysis or campaign data. The benefits of repeated and more detailed measurements, while representing the only source of information about the real atmosphere, are limited by the non-repeatability of an atmospheric situation. The same event never occurs twice. This argues for complementary laboratory experiments, which can provide a more focused dialogue between experiment and theory. Indeed, life cycles are also examined in rotating-annulus laboratory experiments. Thus, these experiments might form a useful empirical benchmark for theoretical and modeling work that is also independent of any sort of subgrid model. In addition, the more direct correspondence between experimental and model data and the data reproducibility makes lab experiments a powerful testbed for parameterizations. Here we show first results from a small rotating annulus experiments and we will further present our new experimental facility to study wave emission from jets and fronts.

A basal stress parameterization for modeling landfast ice

NASA Astrophysics Data System (ADS)

Lemieux, Jean-François; Tremblay, L. Bruno; Dupont, Frédéric; Plante, Mathieu; Smith, Gregory C.; Dumont, Dany

2015-04-01

Current large-scale sea ice models represent very crudely or are unable to simulate the formation, maintenance and decay of coastal landfast ice. We present a simple landfast ice parameterization representing the effect of grounded ice keels. This parameterization is based on bathymetry data and the mean ice thickness in a grid cell. It is easy to implement and can be used for two-thickness and multithickness category models. Two free parameters are used to determine the critical thickness required for large ice keels to reach the bottom and to calculate the basal stress associated with the weight of the ridge above hydrostatic balance. A sensitivity study was conducted and demonstrates that the parameter associated with the critical thickness has the largest influence on the simulated landfast ice area. A 6 year (2001-2007) simulation with a 20 km resolution sea ice model was performed. The simulated landfast ice areas for regions off the coast of Siberia and for the Beaufort Sea were calculated and compared with data from the National Ice Center. With optimal parameters, the basal stress parameterization leads to a slightly shorter landfast ice season but overall provides a realistic seasonal cycle of the landfast ice area in the East Siberian, Laptev and Beaufort Seas. However, in the Kara Sea, where ice arches between islands are key to the stability of the landfast ice, the parameterization consistently leads to an underestimation of the landfast area.

Measures of Microbial Biomass for Soil Carbon Decomposition Models

NASA Astrophysics Data System (ADS)

Mayes, M. A.; Dabbs, J.; Steinweg, J. M.; Schadt, C. W.; Kluber, L. A.; Wang, G.; Jagadamma, S.

2014-12-01

Explicit parameterization of the decomposition of plant inputs and soil organic matter by microbes is becoming more widely accepted in models of various complexity, ranging from detailed process models to global-scale earth system models. While there are multiple ways to measure microbial biomass, chloroform fumigation-extraction (CFE) is commonly used to parameterize models.. However CFE is labor- and time-intensive, requires toxic chemicals, and it provides no specific information about the composition or function of the microbial community. We investigated correlations between measures of: CFE; DNA extraction yield; QPCR base-gene copy numbers for Bacteria, Fungi and Archaea; phospholipid fatty acid analysis; and direct cell counts to determine the potential for use as proxies for microbial biomass. As our ultimate goal is to develop a reliable, more informative, and faster methods to predict microbial biomass for use in models, we also examined basic soil physiochemical characteristics including texture, organic matter content, pH, etc. to identify multi-factor predictive correlations with one or more measures of the microbial community. Our work will have application to both microbial ecology studies and the next generation of process and earth system models.

Effects of a polar stratosphere cloud parameterization on ozone depletion due to stratospheric aircraft in a two-dimensional model

NASA Technical Reports Server (NTRS)

Considine, David B.; Douglass, Anne R.; Jackman, Charles H.

1994-01-01

A parameterization of Type 1 and 2 polar stratospheric cloud (PSC) formation is presented which is appropriate for use in two-dimensional (2-D) photochemical models of the stratosphere. The calculations of PSC frequency of occurrence and surface area density uses climatological temperature probability distributions obtained from National Meteorological Center data to avoid using zonal mean temperatures, which are not good predictors of PSC behavior. The parameterization does not attempt to model the microphysics of PSCs. The parameterization predicts changes in PSC formation and heterogeneous processing due to perturbations of stratospheric trace constituents. It is therefore useful in assessing the potential effects of a fleet of stratospheric aircraft (high speed civil transports, or HSCTs) on stratospheric composition. the model calculated frequency of PSC occurrence agrees well with a climatology based on stratospheric aerosol measurement (SAM) 2 observations. PSCs are predicted to occur in the tropics. Their vertical range is narrow, however, and their impact on model O3 fields is small. When PSC and sulfate aerosol heterogeneous processes are included in the model calculations, the O3 change for 1980 - 1990 is in substantially better agreement with the total ozone mapping spectrometer (TOMS)-derived O3 trend than otherwise. The overall changes in model O3 response to standard HSCT perturbation scenarios produced by the parameterization are small and tend to decrease the model sensitivity to the HSCT perturbation. However, in the southern hemisphere spring a significant increase in O3 sensitivity to HSCT perturbations is found. At this location and time, increased PSC formation leads to increased levels of active chlorine, which produce the O3 decreases.

Assessment of the GECKO-A Modeling Tool and Simplified 3D Model Parameterizations for SOA Formation

NASA Astrophysics Data System (ADS)

Aumont, B.; Hodzic, A.; La, S.; Camredon, M.; Lannuque, V.; Lee-Taylor, J. M.; Madronich, S.

2014-12-01

Explicit chemical mechanisms aim to embody the current knowledge of the transformations occurring in the atmosphere during the oxidation of organic matter. These explicit mechanisms are therefore useful tools to explore the fate of organic matter during its tropospheric oxidation and examine how these chemical processes shape the composition and properties of the gaseous and the condensed phases. Furthermore, explicit mechanisms provide powerful benchmarks to design and assess simplified parameterizations to be included 3D model. Nevertheless, the explicit mechanism describing the oxidation of hydrocarbons with backbones larger than few carbon atoms involves millions of secondary organic compounds, far exceeding the size of chemical mechanisms that can be written manually. Data processing tools can however be designed to overcome these difficulties and automatically generate consistent and comprehensive chemical mechanisms on a systematic basis. The Generator for Explicit Chemistry and Kinetics of Organics in the Atmosphere (GECKO-A) has been developed for the automatic writing of explicit chemical schemes of organic species and their partitioning between the gas and condensed phases. GECKO-A can be viewed as an expert system that mimics the steps by which chemists might develop chemical schemes. GECKO-A generates chemical schemes according to a prescribed protocol assigning reaction pathways and kinetics data on the basis of experimental data and structure-activity relationships. In its current version, GECKO-A can generate the full atmospheric oxidation scheme for most linear, branched and cyclic precursors, including alkanes and alkenes up to C25. Assessments of the GECKO-A modeling tool based on chamber SOA observations will be presented. GECKO-A was recently used to design a parameterization for SOA formation based on a Volatility Basis Set (VBS) approach. First results will be presented.

Using Laboratory Experiments to Improve Ice-Ocean Parameterizations

NASA Astrophysics Data System (ADS)

McConnochie, C. D.; Kerr, R. C.

2017-12-01

Numerical models of ice-ocean interactions are typically unable to resolve the transport of heat and salt to the ice face. Instead, models rely upon parameterizations that have not been sufficiently validated by observations. Recent laboratory experiments of ice-saltwater interactions allow us to test the standard parameterization of heat and salt transport to ice faces - the three-equation model. The three-equation model predicts that the melt rate is proportional to the fluid velocity while the experimental results typically show that the melt rate is independent of the fluid velocity. By considering an analysis of the boundary layer that forms next to a melting ice face, we suggest a resolution to this disagreement. We show that the three-equation model makes the implicit assumption that the thickness of the diffusive sublayer next to the ice is set by a shear instability. However, at low flow velocities, the sublayer is instead set by a convective instability. This distinction leads to a threshold velocity of approximately 4 cm/s at geophysically relevant conditions, above which the form of the parameterization should be valid. In contrast, at flow speeds below 4 cm/s, the three-equation model will underestimate the melt rate. By incorporating such a minimum velocity into the three-equation model, predictions made by numerical simulations could be easily improved.

On the Relationship between Observed NLDN Lightning ...

EPA Pesticide Factsheets

Lightning-produced nitrogen oxides (NOX=NO+NO2) in the middle and upper troposphere play an essential role in the production of ozone (O3) and influence the oxidizing capacity of the troposphere. Despite much effort in both observing and modeling lightning NOX during the past decade, considerable uncertainties still exist with the quantification of lightning NOX production and distribution in the troposphere. It is even more challenging for regional chemistry and transport models to accurately parameterize lightning NOX production and distribution in time and space. The Community Multiscale Air Quality Model (CMAQ) parameterizes the lightning NO emissions using local scaling factors adjusted by the convective precipitation rate that is predicted by the upstream meteorological model; the adjustment is based on the observed lightning strikes from the National Lightning Detection Network (NLDN). For this parameterization to be valid, the existence of an a priori reasonable relationship between the observed lightning strikes and the modeled convective precipitation rates is needed. In this study, we will present an analysis leveraged on the observed NLDN lightning strikes and CMAQ model simulations over the continental United States for a time period spanning over a decade. Based on the analysis, new parameterization scheme for lightning NOX will be proposed and the results will be evaluated. The proposed scheme will be beneficial to modeling exercises where the obs

Uncertainties of parameterized surface downward clear-sky shortwave and all-sky longwave radiation.

NASA Astrophysics Data System (ADS)

Gubler, S.; Gruber, S.; Purves, R. S.

2012-06-01

As many environmental models rely on simulating the energy balance at the Earth's surface based on parameterized radiative fluxes, knowledge of the inherent model uncertainties is important. In this study we evaluate one parameterization of clear-sky direct, diffuse and global shortwave downward radiation (SDR) and diverse parameterizations of clear-sky and all-sky longwave downward radiation (LDR). In a first step, SDR is estimated based on measured input variables and estimated atmospheric parameters for hourly time steps during the years 1996 to 2008. Model behaviour is validated using the high quality measurements of six Alpine Surface Radiation Budget (ASRB) stations in Switzerland covering different elevations, and measurements of the Swiss Alpine Climate Radiation Monitoring network (SACRaM) in Payerne. In a next step, twelve clear-sky LDR parameterizations are calibrated using the ASRB measurements. One of the best performing parameterizations is elected to estimate all-sky LDR, where cloud transmissivity is estimated using measured and modeled global SDR during daytime. In a last step, the performance of several interpolation methods is evaluated to determine the cloud transmissivity in the night. We show that clear-sky direct, diffuse and global SDR is adequately represented by the model when using measurements of the atmospheric parameters precipitable water and aerosol content at Payerne. If the atmospheric parameters are estimated and used as a fix value, the relative mean bias deviance (MBD) and the relative root mean squared deviance (RMSD) of the clear-sky global SDR scatter between between -2 and 5%, and 7 and 13% within the six locations. The small errors in clear-sky global SDR can be attributed to compensating effects of modeled direct and diffuse SDR since an overestimation of aerosol content in the atmosphere results in underestimating the direct, but overestimating the diffuse SDR. Calibration of LDR parameterizations to local conditions reduces MBD and RMSD strongly compared to using the published values of the parameters, resulting in relative MBD and RMSD of less than 5% respectively 10% for the best parameterizations. The best results to estimate cloud transmissivity during nighttime were obtained by linearly interpolating the average of the cloud transmissivity of the four hours of the preceeding afternoon and the following morning. Model uncertainty can be caused by different errors such as code implementation, errors in input data and in estimated parameters, etc. The influence of the latter (errors in input data and model parameter uncertainty) on model outputs is determined using Monte Carlo. Model uncertainty is provided as the relative standard deviation σrel of the simulated frequency distributions of the model outputs. An optimistic estimate of the relative uncertainty σrel resulted in 10% for the clear-sky direct, 30% for diffuse, 3% for global SDR, and 3% for the fitted all-sky LDR.

Comparative study of transient hydraulic tomography with varying parameterizations and zonations: Laboratory sandbox investigation

NASA Astrophysics Data System (ADS)

Luo, Ning; Zhao, Zhanfeng; Illman, Walter A.; Berg, Steven J.

2017-11-01

Transient hydraulic tomography (THT) is a robust method of aquifer characterization to estimate the spatial distributions (or tomograms) of both hydraulic conductivity (K) and specific storage (Ss). However, the highly-parameterized nature of the geostatistical inversion approach renders it computationally intensive for large-scale investigations. In addition, geostatistics-based THT may produce overly smooth tomograms when head data used to constrain the inversion is limited. Therefore, alternative model conceptualizations for THT need to be examined. To investigate this, we simultaneously calibrated different groundwater models with varying parameterizations and zonations using two cases of different pumping and monitoring data densities from a laboratory sandbox. Specifically, one effective parameter model, four geology-based zonation models with varying accuracy and resolution, and five geostatistical models with different prior information are calibrated. Model performance is quantitatively assessed by examining the calibration and validation results. Our study reveals that highly parameterized geostatistical models perform the best among the models compared, while the zonation model with excellent knowledge of stratigraphy also yields comparable results. When few pumping tests with sparse monitoring intervals are available, the incorporation of accurate or simplified geological information into geostatistical models reveals more details in heterogeneity and yields more robust validation results. However, results deteriorate when inaccurate geological information are incorporated. Finally, our study reveals that transient inversions are necessary to obtain reliable K and Ss estimates for making accurate predictions of transient drawdown events.

Optimization and analysis of large chemical kinetic mechanisms using the solution mapping method - Combustion of methane

NASA Technical Reports Server (NTRS)

Frenklach, Michael; Wang, Hai; Rabinowitz, Martin J.

1992-01-01

A method of systematic optimization, solution mapping, as applied to a large-scale dynamic model is presented. The basis of the technique is parameterization of model responses in terms of model parameters by simple algebraic expressions. These expressions are obtained by computer experiments arranged in a factorial design. The developed parameterized responses are then used in a joint multiparameter multidata-set optimization. A brief review of the mathematical background of the technique is given. The concept of active parameters is discussed. The technique is applied to determine an optimum set of parameters for a methane combustion mechanism. Five independent responses - comprising ignition delay times, pre-ignition methyl radical concentration profiles, and laminar premixed flame velocities - were optimized with respect to thirteen reaction rate parameters. The numerical predictions of the optimized model are compared to those computed with several recent literature mechanisms. The utility of the solution mapping technique in situations where the optimum is not unique is also demonstrated.

Parameterization of single-scattering properties of snow

NASA Astrophysics Data System (ADS)

Räisänen, P.; Kokhanovsky, A.; Guyot, G.; Jourdan, O.; Nousiainen, T.

2015-02-01

Snow consists of non-spherical grains of various shapes and sizes. Still, in many radiative transfer applications, single-scattering properties of snow have been based on the assumption of spherical grains. More recently, second-generation Koch fractals have been employed. While they produce a relatively flat phase function typical of deformed non-spherical particles, this is still a rather ad-hoc choice. Here, angular scattering measurements for blowing snow conducted during the CLimate IMpacts of Short-Lived pollutants In the Polar region (CLIMSLIP) campaign at Ny Ålesund, Svalbard, are used to construct a reference phase function for snow. Based on this phase function, an optimized habit combination (OHC) consisting of severely rough (SR) droxtals, aggregates of SR plates and strongly distorted Koch fractals is selected. The single-scattering properties of snow are then computed for the OHC as a function of wavelength λ and snow grain volume-to-projected area equivalent radius rvp. Parameterization equations are developed for λ = 0.199-2.7 μm and rvp = 10-2000 μm, which express the single-scattering co-albedo β, the asymmetry parameter g and the phase function P11 as functions of the size parameter and the real and imaginary parts of the refractive index. The parameterizations are analytic and simple to use in radiative transfer models. Compared to the reference values computed for the OHC, the accuracy of the parameterization is very high for β and g. This is also true for the phase function parameterization, except for strongly absorbing cases (β > 0.3). Finally, we consider snow albedo and reflected radiances for the suggested snow optics parameterization, making comparisons to spheres and distorted Koch fractals.

Parameterization of single-scattering properties of snow

NASA Astrophysics Data System (ADS)

Räisänen, P.; Kokhanovsky, A.; Guyot, G.; Jourdan, O.; Nousiainen, T.

2015-06-01

Snow consists of non-spherical grains of various shapes and sizes. Still, in many radiative transfer applications, single-scattering properties of snow have been based on the assumption of spherical grains. More recently, second-generation Koch fractals have been employed. While they produce a relatively flat phase function typical of deformed non-spherical particles, this is still a rather ad hoc choice. Here, angular scattering measurements for blowing snow conducted during the CLimate IMpacts of Short-Lived pollutants In the Polar region (CLIMSLIP) campaign at Ny Ålesund, Svalbard, are used to construct a reference phase function for snow. Based on this phase function, an optimized habit combination (OHC) consisting of severely rough (SR) droxtals, aggregates of SR plates and strongly distorted Koch fractals is selected. The single-scattering properties of snow are then computed for the OHC as a function of wavelength λ and snow grain volume-to-projected area equivalent radius rvp. Parameterization equations are developed for λ = 0.199-2.7 μm and rvp = 10-2000 μm, which express the single-scattering co-albedo β, the asymmetry parameter g and the phase function P11 as functions of the size parameter and the real and imaginary parts of the refractive index. The parameterizations are analytic and simple to use in radiative transfer models. Compared to the reference values computed for the OHC, the accuracy of the parameterization is very high for β and g. This is also true for the phase function parameterization, except for strongly absorbing cases (β > 0.3). Finally, we consider snow albedo and reflected radiances for the suggested snow optics parameterization, making comparisons to spheres and distorted Koch fractals.

MAMI: Modeling of the Magnetosphere-Ionosphere-Atmosphere System

NASA Technical Reports Server (NTRS)

1998-01-01

Major emphasis of the investigation was the development of theoretical and numerical models of the aurora and of high latitude ionospheric processes. In particular: (1) the NCAR TIGCM (Thermosphere-Ionosphere Global Circulation Model) was updated to include mid and low latitude electrodynamics (this version is called TIE-GCM); (2) the NCAR TIE-GCM was modified to include a more realistic representation of the aurora; (3) the UAF auroral electron transport model was modified to include local acceleration processes; (4) a local ionospheric and auroral model (AURORA) was developed to allow detailed studies of the aurora; (5) a proton-hydrogen transport code has been developed to model proton aurora; and (6) a theory for the production of suprathermal atoms and ions in the upper atmosphere was developed and applied to studies of atomic nitrogen transport and helium escape on open field lines. These models enable us to devise schemes for tile interpretation and quantitative analysis of data obtained by the POLAR spacecraft. Parameterizations were formulated and are available to the GGS investigators. The UVI and VIS teams have adopted these parameterizations and include them in their data analysis. We have developed software for the quantitative interpretation of UVI and VIS images. After the launch of the POLAR satellite we used the image data from UVI and VIS in combination with ground based data from SuperDARN and incoherent scatter radars, magnetometers, and in situ observations from DMSP and NOAA satellites to characterize the state of the ionosphere. A number of event studies have been carried out in cooperation with other CGS theory teams.

Evaluation of Warm-Rain Microphysical Parameterizations in Cloudy Boundary Layer Transitions

NASA Astrophysics Data System (ADS)

Nelson, K.; Mechem, D. B.

2014-12-01

Common warm-rain microphysical parameterizations used for marine boundary layer (MBL) clouds are either tuned for specific cloud types (e.g., the Khairoutdinov and Kogan 2000 parameterization, "KK2000") or are altogether ill-posed (Kessler 1969). An ideal microphysical parameterization should be "unified" in the sense of being suitable across MBL cloud regimes that include stratocumulus, cumulus rising into stratocumulus, and shallow trade cumulus. The recent parameterization of Kogan (2013, "K2013") was formulated for shallow cumulus but has been shown in a large-eddy simulation environment to work quite well for stratocumulus as well. We report on our efforts to implement and test this parameterization into a regional forecast model (NRL COAMPS). Results from K2013 and KK2000 are compared with the operational Kessler parameterization for a 5-day period of the VOCALS-REx field campaign, which took place over the southeast Pacific. We focus on both the relative performance of the three parameterizations and also on how they compare to the VOCALS-REx observations from the NOAA R/V Ronald H. Brown, in particular estimates of boundary-layer depth, liquid water path (LWP), cloud base, and area-mean precipitation rate obtained from C-band radar.

Impact of a Stochastic Parameterization Scheme on El Nino-Southern Oscillation in the Community Climate System Model

NASA Astrophysics Data System (ADS)

Christensen, H. M.; Berner, J.; Sardeshmukh, P. D.

2017-12-01

Stochastic parameterizations have been used for more than a decade in atmospheric models. They provide a way to represent model uncertainty through representing the variability of unresolved sub-grid processes, and have been shown to have a beneficial effect on the spread and mean state for medium- and extended-range forecasts. There is increasing evidence that stochastic parameterization of unresolved processes can improve the bias in mean and variability, e.g. by introducing a noise-induced drift (nonlinear rectification), and by changing the residence time and structure of flow regimes. We present results showing the impact of including the Stochastically Perturbed Parameterization Tendencies scheme (SPPT) in coupled runs of the National Center for Atmospheric Research (NCAR) Community Atmosphere Model, version 4 (CAM4) with historical forcing. SPPT results in a significant improvement in the representation of the El Nino-Southern Oscillation in CAM4, improving the power spectrum, as well as both the inter- and intra-annual variability of tropical pacific sea surface temperatures. We use a Linear Inverse Modelling framework to gain insight into the mechanisms by which SPPT has improved ENSO-variability.

An Investigation of the Influence of Waves on Sediment Processes in Skagit Bay

DTIC Science & Technology

2012-09-30

parameterizations common to most surface wave models, including wave generation by wind , energy dissipation from whitecapping, and quadruplet wave-wave...supply and wind on tidal flat sediment transport. It will be used to evaluate the capabilities of state-of-the-art open source sediment models and to...N00014-08-1-1115 which supported the hydrodynamic model development. Wind forcing for the wave and hydrodynamic models for realistic experiments will

Approaches for Subgrid Parameterization: Does Scaling Help?

NASA Astrophysics Data System (ADS)

Yano, Jun-Ichi

2016-04-01

Arguably the scaling behavior is a well-established fact in many geophysical systems. There are already many theoretical studies elucidating this issue. However, the scaling law is slow to be introduced in "operational" geophysical modelling, notably for weather forecast as well as climate projection models. The main purpose of this presentation is to ask why, and try to answer this question. As a reference point, the presentation reviews the three major approaches for traditional subgrid parameterization: moment, PDF (probability density function), and mode decomposition. The moment expansion is a standard method for describing the subgrid-scale turbulent flows both in the atmosphere and the oceans. The PDF approach is intuitively appealing as it directly deals with a distribution of variables in subgrid scale in a more direct manner. The third category, originally proposed by Aubry et al (1988) in context of the wall boundary-layer turbulence, is specifically designed to represent coherencies in compact manner by a low--dimensional dynamical system. Their original proposal adopts the proper orthogonal decomposition (POD, or empirical orthogonal functions, EOF) as their mode-decomposition basis. However, the methodology can easily be generalized into any decomposition basis. The mass-flux formulation that is currently adopted in majority of atmospheric models for parameterizing convection can also be considered a special case of the mode decomposition, adopting the segmentally-constant modes for the expansion basis. The mode decomposition can, furthermore, be re-interpreted as a type of Galarkin approach for numerically modelling the subgrid-scale processes. Simple extrapolation of this re-interpretation further suggests us that the subgrid parameterization problem may be re-interpreted as a type of mesh-refinement problem in numerical modelling. We furthermore see a link between the subgrid parameterization and downscaling problems along this line. The mode decomposition approach would also be the best framework for linking between the traditional parameterizations and the scaling perspectives. However, by seeing the link more clearly, we also see strength and weakness of introducing the scaling perspectives into parameterizations. Any diagnosis under a mode decomposition would immediately reveal a power-law nature of the spectrum. However, exploiting this knowledge in operational parameterization would be a different story. It is symbolic to realize that POD studies have been focusing on representing the largest-scale coherency within a grid box under a high truncation. This problem is already hard enough. Looking at differently, the scaling law is a very concise manner for characterizing many subgrid-scale variabilities in systems. We may even argue that the scaling law can provide almost complete subgrid-scale information in order to construct a parameterization, but with a major missing link: its amplitude must be specified by an additional condition. The condition called "closure" in the parameterization problem, and known to be a tough problem. We should also realize that the studies of the scaling behavior tend to be statistical in the sense that it hardly provides complete information for constructing a parameterization: can we specify the coefficients of all the decomposition modes by a scaling law perfectly when the first few leading modes are specified? Arguably, the renormalization group (RNG) is a very powerful tool for reducing a system with a scaling behavior into a low dimension, say, under an appropriate mode decomposition procedure. However, RNG is analytical tool: it is extremely hard to apply it to real complex geophysical systems. It appears that it is still a long way to go for us before we can begin to exploit the scaling law in order to construct operational subgrid parameterizations in effective manner.

Prototype of an Integrated Hurricane Information System for Research: Description and Illustration of its Use in Evaluating WRF Model Simulations

NASA Astrophysics Data System (ADS)

Hristova-Veleva, S.; Chao, Y.; Vane, D.; Lambrigtsen, B.; Li, P. P.; Knosp, B.; Vu, Q. A.; Su, H.; Dang, V.; Fovell, R.; Tanelli, S.; Garay, M.; Willis, J.; Poulsen, W.; Fishbein, E.; Ao, C. O.; Vazquez, J.; Park, K. J.; Callahan, P.; Marcus, S.; Haddad, Z.; Fetzer, E.; Kahn, R.

2007-12-01

In spite of recent improvements in hurricane track forecast accuracy, currently there are still many unanswered questions about the physical processes that determine hurricane genesis, intensity, track and impact on large- scale environment. Furthermore, a significant amount of work remains to be done in validating hurricane forecast models, understanding their sensitivities and improving their parameterizations. None of this can be accomplished without a comprehensive set of multiparameter observations that are relevant to both the large- scale and the storm-scale processes in the atmosphere and in the ocean. To address this need, we have developed a prototype of a comprehensive hurricane information system of high- resolution satellite, airborne and in-situ observations and model outputs pertaining to: i) the thermodynamic and microphysical structure of the storms; ii) the air-sea interaction processes; iii) the larger-scale environment as depicted by the SST, ocean heat content and the aerosol loading of the environment. Our goal was to create a one-stop place to provide the researchers with an extensive set of observed hurricane data, and their graphical representation, together with large-scale and convection-resolving model output, all organized in an easy way to determine when coincident observations from multiple instruments are available. Analysis tools will be developed in the next step. The analysis tools will be used to determine spatial, temporal and multiparameter covariances that are needed to evaluate model performance, provide information for data assimilation and characterize and compare observations from different platforms. We envision that the developed hurricane information system will help in the validation of the hurricane models, in the systematic understanding of their sensitivities and in the improvement of the physical parameterizations employed by the models. Furthermore, it will help in studying the physical processes that affect hurricane development and impact on large-scale environment. This talk will describe the developed prototype of the hurricane information systems. Furthermore, we will use a set of WRF hurricane simulations and compare simulated to observed structures to illustrate how the information system can be used to discriminate between simulations that employ different physical parameterizations. The work described here was performed at the Jet Propulsion Laboratory, California Institute of Technology, under contract with the National Aeronautics ans Space Administration.

Coarse-grained models using local-density potentials optimized with the relative entropy: Application to implicit solvation

NASA Astrophysics Data System (ADS)

Sanyal, Tanmoy; Shell, M. Scott

2016-07-01

Bottom-up multiscale techniques are frequently used to develop coarse-grained (CG) models for simulations at extended length and time scales but are often limited by a compromise between computational efficiency and accuracy. The conventional approach to CG nonbonded interactions uses pair potentials which, while computationally efficient, can neglect the inherently multibody contributions of the local environment of a site to its energy, due to degrees of freedom that were coarse-grained out. This effect often causes the CG potential to depend strongly on the overall system density, composition, or other properties, which limits its transferability to states other than the one at which it was parameterized. Here, we propose to incorporate multibody effects into CG potentials through additional nonbonded terms, beyond pair interactions, that depend in a mean-field manner on local densities of different atomic species. This approach is analogous to embedded atom and bond-order models that seek to capture multibody electronic effects in metallic systems. We show that the relative entropy coarse-graining framework offers a systematic route to parameterizing such local density potentials. We then characterize this approach in the development of implicit solvation strategies for interactions between model hydrophobes in an aqueous environment.

Electronegativity equalization method: parameterization and validation for organic molecules using the Merz-Kollman-Singh charge distribution scheme.

PubMed

Jirousková, Zuzana; Vareková, Radka Svobodová; Vanek, Jakub; Koca, Jaroslav

2009-05-01

The electronegativity equalization method (EEM) was developed by Mortier et al. as a semiempirical method based on the density-functional theory. After parameterization, in which EEM parameters A(i), B(i), and adjusting factor kappa are obtained, this approach can be used for calculation of average electronegativity and charge distribution in a molecule. The aim of this work is to perform the EEM parameterization using the Merz-Kollman-Singh (MK) charge distribution scheme obtained from B3LYP/6-31G* and HF/6-31G* calculations. To achieve this goal, we selected a set of 380 organic molecules from the Cambridge Structural Database (CSD) and used the methodology, which was recently successfully applied to EEM parameterization to calculate the HF/STO-3G Mulliken charges on large sets of molecules. In the case of B3LYP/6-31G* MK charges, we have improved the EEM parameters for already parameterized elements, specifically C, H, N, O, and F. Moreover, EEM parameters for S, Br, Cl, and Zn, which have not as yet been parameterized for this level of theory and basis set, we also developed. In the case of HF/6-31G* MK charges, we have developed the EEM parameters for C, H, N, O, S, Br, Cl, F, and Zn that have not been parameterized for this level of theory and basis set so far. The obtained EEM parameters were verified by a previously developed validation procedure and used for the charge calculation on a different set of 116 organic molecules from the CSD. The calculated EEM charges are in a very good agreement with the quantum mechanically obtained ab initio charges. 2008 Wiley Periodicals, Inc.

Evaluation of surface layer flux parameterizations using in-situ observations

NASA Astrophysics Data System (ADS)

Katz, Jeremy; Zhu, Ping

2017-09-01

Appropriate calculation of surface turbulent fluxes between the atmosphere and the underlying ocean/land surface is one of the major challenges in geosciences. In practice, the surface turbulent fluxes are estimated from the mean surface meteorological variables based on the bulk transfer model combined with the Monnin-Obukhov Similarity (MOS) theory. Few studies have been done to examine the extent to which such a flux parameterization can be applied to different weather and surface conditions. A novel validation method is developed in this study to evaluate the surface flux parameterization using in-situ observations collected at a station off the coast of Gulf of Mexico. The main findings are: (a) the theoretical prediction that uses MOS theory does not match well with those directly computed from the observations. (b) The largest spread in exchange coefficients is shown in strong stable conditions with calm winds. (c) Large turbulent eddies, which depend strongly on the mean flow pattern and surface conditions, tend to break the constant flux assumption in the surface layer.

Parameterized examination in econometrics

NASA Astrophysics Data System (ADS)

Malinova, Anna; Kyurkchiev, Vesselin; Spasov, Georgi

2018-01-01

The paper presents a parameterization of basic types of exam questions in Econometrics. This algorithm is used to automate and facilitate the process of examination, assessment and self-preparation of a large number of students. The proposed parameterization of testing questions reduces the time required to author tests and course assignments. It enables tutors to generate a large number of different but equivalent dynamic questions (with dynamic answers) on a certain topic, which are automatically assessed. The presented methods are implemented in DisPeL (Distributed Platform for e-Learning) and provide questions in the areas of filtering and smoothing of time-series data, forecasting, building and analysis of single-equation econometric models. Questions also cover elasticity, average and marginal characteristics, product and cost functions, measurement of monopoly power, supply, demand and equilibrium price, consumer and product surplus, etc. Several approaches are used to enable the required numerical computations in DisPeL - integration of third-party mathematical libraries, developing our own procedures from scratch, and wrapping our legacy math codes in order to modernize and reuse them.

Modeling particle nucleation and growth over northern California during the 2010 CARES campaign

NASA Astrophysics Data System (ADS)

Lupascu, A.; Easter, R.; Zaveri, R.; Shrivastava, M.; Pekour, M.; Tomlinson, J.; Yang, Q.; Matsui, H.; Hodzic, A.; Zhang, Q.; Fast, J. D.

2015-07-01

Accurate representation of the aerosol lifecycle requires adequate modeling of the particle number concentration and size distribution in addition to their mass, which is often the focus of aerosol modeling studies. This paper compares particle number concentrations and size distributions as predicted by three empirical nucleation parameterizations in the Weather Research and Forecast coupled with chemistry (WRF-Chem) regional model using 20 discrete size bins ranging from 1 nm to 10 μm. Two of the parameterizations are based on H2SO4 while one is based on both H2SO4 and organic vapors. Budget diagnostic terms for transport, dry deposition, emissions, condensational growth, nucleation, and coagulation of aerosol particles have been added to the model and are used to analyze the differences in how the new particle formation parameterizations influence the evolving aerosol size distribution. The simulations are evaluated using measurements collected at surface sites and from a research aircraft during the Carbonaceous Aerosol and Radiative Effects Study (CARES) conducted in the vicinity of Sacramento, California. While all three parameterizations captured the temporal variation of the size distribution during observed nucleation events as well as the spatial variability in aerosol number, all overestimated by up to a factor of 2.5 the total particle number concentration for particle diameters greater than 10 nm. Using the budget diagnostic terms, we demonstrate that the combined H2SO4 and low-volatility organic vapors parameterization leads to a different diurnal variability of new particle formation and growth to larger sizes compared to the parameterizations based on only H2SO4. At the CARES urban ground site, peak nucleation rates were predicted to occur around 12:00 Pacific (local) standard time (PST) for the H2SO4 parameterizations, whereas the highest rates were predicted at 08:00 and 16:00 PST when low-volatility organic gases are included in the parameterization. This can be explained by higher anthropogenic emissions of organic vapors at these times as well as lower boundary layer heights that reduce vertical mixing. The higher nucleation rates in the H2SO4-organic parameterization at these times were largely offset by losses due to coagulation. Despite the different budget terms for ultrafine particles, the 10-40 nm diameter particle number concentrations from all three parameterizations increased from 10:00 to 14:00 PST and then decreased later in the afternoon, consistent with changes in the observed size and number distribution. Differences among the three simulations for the 40-100 nm particle diameter range are mostly associated with the timing of the peak total tendencies that shift the morning increase and afternoon decrease in particle number concentration by up to two hours. We found that newly formed particles could explain up to 20-30 % of predicted cloud condensation nuclei at 0.5 % supersaturation, depending on location and the specific nucleation parameterization. A sensitivity simulation using 12 discrete size bins ranging from 1 nm to 10 μm diameter gave a reasonable estimate of particle number and size distribution compared to the 20 size bin simulation, while reducing the associated computational cost by ∼ 36 %.

Modeling Surfzone/Inner-shelf Exchange

DTIC Science & Technology

2013-09-30

goal here is the use a wave-resolving Boussinesq model to figure out how to parameterize the vorticity generation due to short-crested breaking of...individual waves. The Boussinesq model funwaveC used here, developed by the PI and distributed as open-source software, has been val- idated in ONR funded...shading of bottom bathymetry, mooring locations (green squares) and the local co-ordinate system (black arrows). Positive x is directed towards the

An ensemble constrained variational analysis of atmospheric forcing data and its application to evaluate clouds in CAM5: Ensemble 3DCVA and Its Application

DOE PAGES

Tang, Shuaiqi; Zhang, Minghua; Xie, Shaocheng

2016-01-05

Large-scale atmospheric forcing data can greatly impact the simulations of atmospheric process models including Large Eddy Simulations (LES), Cloud Resolving Models (CRMs) and Single-Column Models (SCMs), and impact the development of physical parameterizations in global climate models. This study describes the development of an ensemble variationally constrained objective analysis of atmospheric large-scale forcing data and its application to evaluate the cloud biases in the Community Atmospheric Model (CAM5). Sensitivities of the variational objective analysis to background data, error covariance matrix and constraint variables are described and used to quantify the uncertainties in the large-scale forcing data. Application of the ensemblemore » forcing in the CAM5 SCM during March 2000 intensive operational period (IOP) at the Southern Great Plains (SGP) of the Atmospheric Radiation Measurement (ARM) program shows systematic biases in the model simulations that cannot be explained by the uncertainty of large-scale forcing data, which points to the deficiencies of physical parameterizations. The SCM is shown to overestimate high clouds and underestimate low clouds. These biases are found to also exist in the global simulation of CAM5 when it is compared with satellite data.« less

An ensemble constrained variational analysis of atmospheric forcing data and its application to evaluate clouds in CAM5: Ensemble 3DCVA and Its Application

DOE Office of Scientific and Technical Information (OSTI.GOV)

Tang, Shuaiqi; Zhang, Minghua; Xie, Shaocheng

Large-scale atmospheric forcing data can greatly impact the simulations of atmospheric process models including Large Eddy Simulations (LES), Cloud Resolving Models (CRMs) and Single-Column Models (SCMs), and impact the development of physical parameterizations in global climate models. This study describes the development of an ensemble variationally constrained objective analysis of atmospheric large-scale forcing data and its application to evaluate the cloud biases in the Community Atmospheric Model (CAM5). Sensitivities of the variational objective analysis to background data, error covariance matrix and constraint variables are described and used to quantify the uncertainties in the large-scale forcing data. Application of the ensemblemore » forcing in the CAM5 SCM during March 2000 intensive operational period (IOP) at the Southern Great Plains (SGP) of the Atmospheric Radiation Measurement (ARM) program shows systematic biases in the model simulations that cannot be explained by the uncertainty of large-scale forcing data, which points to the deficiencies of physical parameterizations. The SCM is shown to overestimate high clouds and underestimate low clouds. These biases are found to also exist in the global simulation of CAM5 when it is compared with satellite data.« less

Regulation-Structured Dynamic Metabolic Model Provides a Potential Mechanism for Delayed Enzyme Response in Denitrification Process

DOE Office of Scientific and Technical Information (OSTI.GOV)

Song, Hyun-Seob; Thomas, Dennis G.; Stegen, James C.

In a recent study of denitrification dynamics in hyporheic zone sediments, we observed a significant time lag (up to several days) in enzymatic response to the changes in substrate concentration. To explore an underlying mechanism and understand the interactive dynamics between enzymes and nutrients, we developed a trait-based model that associates a community’s traits with functional enzymes, instead of typically used species guilds (or functional guilds). This enzyme-based formulation allows to collectively describe biogeochemical functions of microbial communities without directly parameterizing the dynamics of species guilds, therefore being scalable to complex communities. As a key component of modeling, we accountedmore » for microbial regulation occurring through transcriptional and translational processes, the dynamics of which was parameterized based on the temporal profiles of enzyme concentrations measured using a new signature peptide-based method. The simulation results using the resulting model showed several days of a time lag in enzymatic responses as observed in experiments. Further, the model showed that the delayed enzymatic reactions could be primarily controlled by transcriptional responses and that the dynamics of transcripts and enzymes are closely correlated. The developed model can serve as a useful tool for predicting biogeochemical processes in natural environments, either independently or through integration with hydrologic flow simulators.« less

Development and evaluation of an ammonia bidirectional flux parameterization for air quality models

NASA Astrophysics Data System (ADS)

Pleim, Jonathan E.; Bash, Jesse O.; Walker, John T.; Cooter, Ellen J.

2013-05-01

is an important contributor to particulate matter in the atmosphere and can significantly impact terrestrial and aquatic ecosystems. Surface exchange between the atmosphere and biosphere is a key part of the ammonia cycle. New modeling techniques are being developed for use in air quality models that replace current ammonia emissions from fertilized crops and ammonia dry deposition with a bidirectional surface flux model including linkage to a detailed biogeochemical and farm management model. Recent field studies involving surface flux measurements over crops that predominate in North America have been crucial for extending earlier bidirectional flux models toward more realistic treatment of NH3 fluxes for croplands. Comparisons of the ammonia bidirection flux algorithm to both lightly fertilized soybeans and heavily fertilized corn demonstrate that the model can capture the magnitude and dynamics of observed ammonia fluxes, both net deposition and evasion, over a range of conditions with overall biases on the order of the uncertainty of the measurements. However, successful application to the field experiment in heavily fertilized corn required substantial modification of the model to include new parameterizations for in-soil diffusion resistance, ground quasi-laminar boundary layer resistance, and revised cuticular resistance that is dependent on in-canopy NH3 concentration and RH at the leaf surface. This new bidirectional flux algorithm has been incorporated in an air quality modeling system, which also includes an implementation of a soil nitrification model.

Implementation of a generalized actuator line model for wind turbine parameterization in the Weather Research and Forecasting model

DOE Office of Scientific and Technical Information (OSTI.GOV)

Marjanovic, Nikola; Mirocha, Jeffrey D.; Kosović, Branko

A generalized actuator line (GAL) wind turbine parameterization is implemented within the Weather Research and Forecasting model to enable high-fidelity large-eddy simulations of wind turbine interactions with boundary layer flows under realistic atmospheric forcing conditions. Numerical simulations using the GAL parameterization are evaluated against both an already implemented generalized actuator disk (GAD) wind turbine parameterization and two field campaigns that measured the inflow and near-wake regions of a single turbine. The representation of wake wind speed, variance, and vorticity distributions is examined by comparing fine-resolution GAL and GAD simulations and GAD simulations at both fine and coarse-resolutions. The higher-resolution simulationsmore » show slightly larger and more persistent velocity deficits in the wake and substantially increased variance and vorticity when compared to the coarse-resolution GAD. The GAL generates distinct tip and root vortices that maintain coherence as helical tubes for approximately one rotor diameter downstream. Coarse-resolution simulations using the GAD produce similar aggregated wake characteristics to both fine-scale GAD and GAL simulations at a fraction of the computational cost. The GAL parameterization provides the capability to resolve near wake physics, including vorticity shedding and wake expansion.« less

Non-perturbational surface-wave inversion: A Dix-type relation for surface waves

USGS Publications Warehouse

Haney, Matt; Tsai, Victor C.

2015-01-01

We extend the approach underlying the well-known Dix equation in reflection seismology to surface waves. Within the context of surface wave inversion, the Dix-type relation we derive for surface waves allows accurate depth profiles of shear-wave velocity to be constructed directly from phase velocity data, in contrast to perturbational methods. The depth profiles can subsequently be used as an initial model for nonlinear inversion. We provide examples of the Dix-type relation for under-parameterized and over-parameterized cases. In the under-parameterized case, we use the theory to estimate crustal thickness, crustal shear-wave velocity, and mantle shear-wave velocity across the Western U.S. from phase velocity maps measured at 8-, 20-, and 40-s periods. By adopting a thin-layer formalism and an over-parameterized model, we show how a regularized inversion based on the Dix-type relation yields smooth depth profiles of shear-wave velocity. In the process, we quantitatively demonstrate the depth sensitivity of surface-wave phase velocity as a function of frequency and the accuracy of the Dix-type relation. We apply the over-parameterized approach to a near-surface data set within the frequency band from 5 to 40 Hz and find overall agreement between the inverted model and the result of full nonlinear inversion.

MIZMAS: Modeling the Evolution of Ice Thickness and Floe Size Distributions in the Marginal Ice Zone of the Chukchi and Beaufort Seas

DTIC Science & Technology

2014-09-30

existing data sources, gathering and maintaining the data needed, and completing and reviewing the collection of information. Send comments regarding this...through downscaling future projection simulations. APPROACH To address the scientific objectives, we plan to develop, implement, and validate a...ITD and FSD at the same time. The development of MIZMAS will be based on systematic model parameterization, calibration, and validation, and data

Node-Splitting Generalized Linear Mixed Models for Evaluation of Inconsistency in Network Meta-Analysis.

PubMed

Yu-Kang, Tu

2016-12-01

Network meta-analysis for multiple treatment comparisons has been a major development in evidence synthesis methodology. The validity of a network meta-analysis, however, can be threatened by inconsistency in evidence within the network. One particular issue of inconsistency is how to directly evaluate the inconsistency between direct and indirect evidence with regard to the effects difference between two treatments. A Bayesian node-splitting model was first proposed and a similar frequentist side-splitting model has been put forward recently. Yet, assigning the inconsistency parameter to one or the other of the two treatments or splitting the parameter symmetrically between the two treatments can yield different results when multi-arm trials are involved in the evaluation. We aimed to show that a side-splitting model can be viewed as a special case of design-by-treatment interaction model, and different parameterizations correspond to different design-by-treatment interactions. We demonstrated how to evaluate the side-splitting model using the arm-based generalized linear mixed model, and an example data set was used to compare results from the arm-based models with those from the contrast-based models. The three parameterizations of side-splitting make slightly different assumptions: the symmetrical method assumes that both treatments in a treatment contrast contribute to inconsistency between direct and indirect evidence, whereas the other two parameterizations assume that only one of the two treatments contributes to this inconsistency. With this understanding in mind, meta-analysts can then make a choice about how to implement the side-splitting method for their analysis. Copyright © 2016 International Society for Pharmacoeconomics and Outcomes Research (ISPOR). Published by Elsevier Inc. All rights reserved.

Pedotransfer Functions in Earth System Science: Challenges and Perspectives: PTFs in Earth system science perspective

DOE Office of Scientific and Technical Information (OSTI.GOV)

Van Looy, Kris; Bouma, Johan; Herbst, Michael

Soil, through its various functions, plays a vital role in the Earth's ecosystems and provides multiple ecosystem services to humanity. Pedotransfer functions (PTFs) are simple to complex knowledge rules that relate available soil information to soil properties and variables that are needed to parameterize soil processes. Here in this article, we review the existing PTFs and document the new generation of PTFs developed in the different disciplines of Earth system science. To meet the methodological challenges for a successful application in Earth system modeling, we emphasize that PTF development has to go hand in hand with suitable extrapolation and upscalingmore » techniques such that the PTFs correctly represent the spatial heterogeneity of soils. PTFs should encompass the variability of the estimated soil property or process, in such a way that the estimation of parameters allows for validation and can also confidently provide for extrapolation and upscaling purposes capturing the spatial variation in soils. Most actively pursued recent developments are related to parameterizations of solute transport, heat exchange, soil respiration, and organic carbon content, root density, and vegetation water uptake. Further challenges are to be addressed in parameterization of soil erosivity and land use change impacts at multiple scales. We argue that a comprehensive set of PTFs can be applied throughout a wide range of disciplines of Earth system science, with emphasis on land surface models. Novel sensing techniques provide a true breakthrough for this, yet further improvements are necessary for methods to deal with uncertainty and to validate applications at global scale.« less

Pedotransfer Functions in Earth System Science: Challenges and Perspectives: PTFs in Earth system science perspective

DOE PAGES

Van Looy, Kris; Bouma, Johan; Herbst, Michael; ...

2017-12-28

Soil, through its various functions, plays a vital role in the Earth's ecosystems and provides multiple ecosystem services to humanity. Pedotransfer functions (PTFs) are simple to complex knowledge rules that relate available soil information to soil properties and variables that are needed to parameterize soil processes. Here in this article, we review the existing PTFs and document the new generation of PTFs developed in the different disciplines of Earth system science. To meet the methodological challenges for a successful application in Earth system modeling, we emphasize that PTF development has to go hand in hand with suitable extrapolation and upscalingmore » techniques such that the PTFs correctly represent the spatial heterogeneity of soils. PTFs should encompass the variability of the estimated soil property or process, in such a way that the estimation of parameters allows for validation and can also confidently provide for extrapolation and upscaling purposes capturing the spatial variation in soils. Most actively pursued recent developments are related to parameterizations of solute transport, heat exchange, soil respiration, and organic carbon content, root density, and vegetation water uptake. Further challenges are to be addressed in parameterization of soil erosivity and land use change impacts at multiple scales. We argue that a comprehensive set of PTFs can be applied throughout a wide range of disciplines of Earth system science, with emphasis on land surface models. Novel sensing techniques provide a true breakthrough for this, yet further improvements are necessary for methods to deal with uncertainty and to validate applications at global scale.« less

Parameterization and Observability Analysis of Scalable Battery Clusters for Onboard Thermal Management

DTIC Science & Technology

2011-12-01

the designed parameterization scheme and adaptive observer. A cylindri- cal battery thermal model in Eq. (1) with parameters of an A123 32157 LiFePO4 ...Morcrette, M. and Delacourt, C. (2010) Thermal modeling of a cylindrical LiFePO4 /graphite lithium-ion battery. Journal of Power Sources. 195, 2961

Modeling the formation and aging of secondary organic aerosols in the Los Angeles metropolitan region during the CalNex 2010 field campaign

NASA Astrophysics Data System (ADS)

Hayes, P. L.; Ma, P. K.; Jimenez, J. L.; Zhao, Y.; Robinson, A. L.; Carlton, A. M. G.; Baker, K. R.; Ahmadov, R.; Washenfelder, R. A.; Alvarez, S. L.; Rappenglück, B.; Gilman, J.; Kuster, W.; De Gouw, J. A.; Prevot, A. S.; Zotter, P.; Szidat, S.; Kleindienst, T. E.; Offenberg, J. H.

2015-12-01

Several different literature parameterizations for the formation and evolution of urban secondary organic aerosol (SOA) are evaluated using a box model representing the Los Angeles Region during CalNex. The model SOA formed only from the oxidation of VOCs (V-SOA) is insufficient to explain the observed SOA concentrations, even when using SOA parameterizations with multi-generation oxidation that produce much higher yields than have been observed in chamber experiments, or when increasing yields to their upper limit estimates accounting for recently reported losses of vapors to chamber walls. Including SOA from primary semi-volatile and intermediate volatility organic compounds (P-S/IVOCs) following the parameterizations of Robinson et al. (2007), Grieshop et al. (2009), or Pye and Seinfeld (2010) improves model/measurement agreement for mass concentration at shorter photochemical ages (0.5 days). Our results strongly suggest that other precursors besides VOCs are needed to explain the observed SOA concentrations. In contrast, all of the literature P-S/IVOC parameterizations over-predict urban SOA formation at long photochemical ages (3 days) compared to observations from multiple sites, which can lead to problems in regional and global modeling. Sensitivity studies that reduce the IVOC emissions by one-half in the model improve SOA predictions at these long ages. In addition, when IVOC emissions in the Robinson et al. parameterization are constrained using recently reported measurements of these species model/measurement agreement is achieved. The amounts of SOA mass from diesel vehicles, gasoline vehicles, and cooking emissions are estimated to be 16 - 27%, 35 - 61%, and 19 - 35%, respectively, depending on the parameterization used, which is consistent with the observed fossil fraction of urban SOA, 71(±3)%. The percentage of SOA from diesel vehicle emissions is the same, within the estimated uncertainty, as reported in previous work that analyzed the weekly cycles in SOA concentrations (Bahreini et al., 2012; Hayes et al., 2013). However, the modeling work presented here suggests a strong anthropogenic source of modern carbon in urban SOA, possibly cooking emissions, that was not accounted for in those previous studies, and which is higher on weekends.

Dynamical properties of a minimally parameterized mathematical model for metronomic chemotherapy.

PubMed

Schättler, Heinz; Ledzewicz, Urszula; Amini, Behrooz

2016-04-01

A minimally parameterized mathematical model for low-dose metronomic chemotherapy is formulated that takes into account angiogenic signaling between the tumor and its vasculature and tumor inhibiting effects of tumor-immune system interactions. The dynamical equations combine a model for tumor development under angiogenic signaling formulated by Hahnfeldt et al. with a model for tumor-immune system interactions by Stepanova. The dynamical properties of the model are analyzed. Depending on the parameter values, the system encompasses a variety of medically realistic scenarios that range from cases when (i) low-dose metronomic chemotherapy is able to eradicate the tumor (all trajectories converge to a tumor-free equilibrium point) to situations when (ii) tumor dormancy is induced (a unique, globally asymptotically stable benign equilibrium point exists) to (iii) multi-stable situations that have both persistent benign and malignant behaviors separated by the stable manifold of an unstable equilibrium point and finally to (iv) situations when tumor growth cannot be overcome by low-dose metronomic chemotherapy. The model forms a basis for a more general study of chemotherapy when the main components of a tumor's microenvironment are taken into account.

Method of sound synthesis

DOEpatents

Miner, Nadine E.; Caudell, Thomas P.

2004-06-08

A sound synthesis method for modeling and synthesizing dynamic, parameterized sounds. The sound synthesis method yields perceptually convincing sounds and provides flexibility through model parameterization. By manipulating model parameters, a variety of related, but perceptually different sounds can be generated. The result is subtle changes in sounds, in addition to synthesis of a variety of sounds, all from a small set of models. The sound models can change dynamically according to changes in the simulation environment. The method is applicable to both stochastic (impulse-based) and non-stochastic (pitched) sounds.

Building integral projection models: a user's guide

PubMed Central

Rees, Mark; Childs, Dylan Z; Ellner, Stephen P; Coulson, Tim

2014-01-01

In order to understand how changes in individual performance (growth, survival or reproduction) influence population dynamics and evolution, ecologists are increasingly using parameterized mathematical models. For continuously structured populations, where some continuous measure of individual state influences growth, survival or reproduction, integral projection models (IPMs) are commonly used. We provide a detailed description of the steps involved in constructing an IPM, explaining how to: (i) translate your study system into an IPM; (ii) implement your IPM; and (iii) diagnose potential problems with your IPM. We emphasize how the study organism's life cycle, and the timing of censuses, together determine the structure of the IPM kernel and important aspects of the statistical analysis used to parameterize an IPM using data on marked individuals. An IPM based on population studies of Soay sheep is used to illustrate the complete process of constructing, implementing and evaluating an IPM fitted to sample data. We then look at very general approaches to parameterizing an IPM, using a wide range of statistical techniques (e.g. maximum likelihood methods, generalized additive models, nonparametric kernel density estimators). Methods for selecting models for parameterizing IPMs are briefly discussed. We conclude with key recommendations and a brief overview of applications that extend the basic model. The online Supporting Information provides commented R code for all our analyses. PMID:24219157

Evaluating and Understanding Parameterized Convective Processes and Their Role in the Development of Mesoscale Precipitation Systems

NASA Technical Reports Server (NTRS)

Fritsch, J. Michael (Principal Investigator); Kain, John S.

1995-01-01

Research efforts during the first year focused on numerical simulations of two convective systems with the Penn State/NCAR mesoscale model. The first of these systems was tropical cyclone Irma, which occurred in 1987 in Australia's Gulf of Carpentaria during the AMEX field program. Comparison simulations of this system were done with two different convective parameterization schemes (CPS's), the Kain-Fritsch (1993 - KF) and the Betts-Miller (Betts 1986- BM) schemes. The second system was the June 10-11 1985 squall line simulation, which occurred over the Kansas-Oklahoma region during the PRE-STORM experiment. Simulations of this system using the KF scheme were examined in detail.

Anisotropic dissipation of the global internal tide from a higher-order multiscale barotropic tidal simulation

NASA Astrophysics Data System (ADS)

Salehipour, Hesam; Peltier, W. Richard

2013-04-01

Increasing recognition of the importance of the diapycnal mixing induced by the dissipation of internal tides excited by the interaction of the barotropic tide with bottom topography has begun to attract increasing attention. The partition of the dissipation of the barotropic tide between that related to the internal tide and that related to bottom friction is also of considerable interest as this partition has been shown to shift significantly between the modern and Last Glacial Maximum tidal regimes [Griffiths and Peltier, 2008, 2009] . Ocean general circulation models, though clearly unable to explicitly resolve small scale mixing processes, currently rely on the introduction of an appropriate parameterization of the contribution to such mixing due to dissipation of the internal tidal. One widely-used parameterization of this kind (which is currently employed in POP2) is that proposed by Jayne and St. Laurent [GRL 2001] and is based on topographic roughness. This contrasts with the parameterization of Carrere and Lyard [GRL 2003] and Lyard [Ocean Dynamics, 2006] which also considers the flow direction with respect to the topographic features. Both of these parameterizations require the tuning of parameters to arrive at sensible tidal amplitudes. We have developed an original higher order barotropic tidal model based on the discontinuous Galerkin finite element method applied on global triangular grids [Salehipour et al., submitted to Ocean Modelling] in which we parameterize the energy conversion to baroclinic tides by introducing an anisotropic internal tide drag [Griffiths and Peltier GRL 2008, Griffiths and Peltier J Climate 2009] which also considers the time dependent angle of attack of the barotropic tidal flow on abyssal topographic features but requires no tuning parameters. The model is massively parallelized which enables very high resolution modeling of global barotropic tides as well as the implementation of local grid refinement. In this paper we will present maps of energy dissipation for different tidal constituents using grids with resolutions up to 1/18° in coastal regions as well as in areas with high gradients in the bottom topography. The discontinuous Galerkin formulation provides important energy conservation properties as well as enabling the accurate representation of sharp topographic gradients without smoothing, a feature well matched to the multi-scale problem of the dissipation of the internal tide. We will describe the detailed energy budgets delivered by this model under both modern and Last Glacial Maximum oceanographic conditions, including relative sea level and internal density stratification effects. The results of the simulations will be illustrated with global maps with enhanced resolution for the internal tidal dissipation which may be exploited in the parameterization of vertical mixing. We will use the reconstructed paleotopography of the ICE-5G model of Peltier [Annu. Rev. Earth Planet Sci. 2004] as well as the more recent refinement (ICE-6G) to compute the characteristics of the LGM tidal regime and will compare these characteristics to those of the modern ocean.

Objective calibration of regional climate models

NASA Astrophysics Data System (ADS)

Bellprat, O.; Kotlarski, S.; Lüthi, D.; SchäR, C.

2012-12-01

Climate models are subject to high parametric uncertainty induced by poorly confined model parameters of parameterized physical processes. Uncertain model parameters are typically calibrated in order to increase the agreement of the model with available observations. The common practice is to adjust uncertain model parameters manually, often referred to as expert tuning, which lacks objectivity and transparency in the use of observations. These shortcomings often haze model inter-comparisons and hinder the implementation of new model parameterizations. Methods which would allow to systematically calibrate model parameters are unfortunately often not applicable to state-of-the-art climate models, due to computational constraints facing the high dimensionality and non-linearity of the problem. Here we present an approach to objectively calibrate a regional climate model, using reanalysis driven simulations and building upon a quadratic metamodel presented by Neelin et al. (2010) that serves as a computationally cheap surrogate of the model. Five model parameters originating from different parameterizations are selected for the optimization according to their influence on the model performance. The metamodel accurately estimates spatial averages of 2 m temperature, precipitation and total cloud cover, with an uncertainty of similar magnitude as the internal variability of the regional climate model. The non-linearities of the parameter perturbations are well captured, such that only a limited number of 20-50 simulations are needed to estimate optimal parameter settings. Parameter interactions are small, which allows to further reduce the number of simulations. In comparison to an ensemble of the same model which has undergone expert tuning, the calibration yields similar optimal model configurations, but leading to an additional reduction of the model error. The performance range captured is much wider than sampled with the expert-tuned ensemble and the presented methodology is effective and objective. It is argued that objective calibration is an attractive tool and could become standard procedure after introducing new model implementations, or after a spatial transfer of a regional climate model. Objective calibration of parameterizations with regional models could also serve as a strategy toward improving parameterization packages of global climate models.

Parameterization of turbulence and the planetary boundary layer in the GLA Fourth Order GCM

NASA Technical Reports Server (NTRS)

Helfand, H. M.

1985-01-01

A new scheme has been developed to model the planetary boundary layer in the GLAS Fourth Order GCM through explicit resolution of its vertical structure into two or more vertical layers. This involves packing the lowest layers of the GCM close to the ground and developing new parameterization schemes that can express the turbulent vertical fluxes of heat, momentum and moisture at the earth's surface and between the layers that are contained with the PBL region. Offline experiments indicate that the combination of the modified level 2.5 second-order turbulent closure scheme and the 'extended surface layer' similarity scheme should work well to simulate the behavior of the turbulent PBL even at the coarsest vertical resolution with which such schemes will conceivably be used in the GLA Fourth Order GCM.

GHI calculation sensitivity on microphysics, land- and cumulus parameterization in WRF over the Reunion Island

NASA Astrophysics Data System (ADS)

De Meij, A.; Vinuesa, J.-F.; Maupas, V.

2018-05-01

The sensitivity of different microphysics and dynamics schemes on calculated global horizontal irradiation (GHI) values in the Weather Research Forecasting (WRF) model is studied. 13 sensitivity simulations were performed for which the microphysics, cumulus parameterization schemes and land surface models were changed. Firstly we evaluated the model's performance by comparing calculated GHI values for the Base Case with observations for the Reunion Island for 2014. In general, the model calculates the largest bias during the austral summer. This indicates that the model is less accurate in timing the formation and dissipation of clouds during the summer, when higher water vapor quantities are present in the atmosphere than during the austral winter. Secondly, the model sensitivity on changing the microphysics, cumulus parameterization and land surface models on calculated GHI values is evaluated. The sensitivity simulations showed that changing the microphysics from the Thompson scheme (or Single-Moment 6-class scheme) to the Morrison double-moment scheme, the relative bias improves from 45% to 10%. The underlying reason for this improvement is that the Morrison double-moment scheme predicts the mass and number concentrations of five hydrometeors, which help to improve the calculation of the densities, size and lifetime of the cloud droplets. While the single moment schemes only predicts the mass for less hydrometeors. Changing the cumulus parameterization schemes and land surface models does not have a large impact on GHI calculations.

Improved parametrization of the growth index for dark energy and DGP models

NASA Astrophysics Data System (ADS)

Jing, Jiliang; Chen, Songbai

2010-03-01

We propose two improved parameterized form for the growth index of the linear matter perturbations: (I) γ(z)=γ0+(γ∞-γ0)z/z+1 and (II) γ(z)=γ0+γ1 z/z+1 +(γ∞-γ1-γ0)(. With these forms of γ(z), we analyze the accuracy of the approximation the growth factor f by Ωmγ(z) for both the wCDM model and the DGP model. For the first improved parameterized form, we find that the approximation accuracy is enhanced at the high redshifts for both kinds of models, but it is not at the low redshifts. For the second improved parameterized form, it is found that Ωmγ(z) approximates the growth factor f very well for all redshifts. For chosen α, the relative error is below 0.003% for the ΛCDM model and 0.028% for the DGP model when Ωm=0.27. Thus, the second improved parameterized form of γ(z) should be useful for the high precision constraint on the growth index of different models with the observational data. Moreover, we also show that α depends on the equation of state w and the fractional energy density of matter Ωm0, which may help us learn more information about dark energy and DGP models.

Local identifiability and sensitivity analysis of neuromuscular blockade and depth of hypnosis models.

PubMed

Silva, M M; Lemos, J M; Coito, A; Costa, B A; Wigren, T; Mendonça, T

2014-01-01

This paper addresses the local identifiability and sensitivity properties of two classes of Wiener models for the neuromuscular blockade and depth of hypnosis, when drug dose profiles like the ones commonly administered in the clinical practice are used as model inputs. The local parameter identifiability was assessed based on the singular value decomposition of the normalized sensitivity matrix. For the given input signal excitation, the results show an over-parameterization of the standard pharmacokinetic/pharmacodynamic models. The same identifiability assessment was performed on recently proposed minimally parameterized parsimonious models for both the neuromuscular blockade and the depth of hypnosis. The results show that the majority of the model parameters are identifiable from the available input-output data. This indicates that any identification strategy based on the minimally parameterized parsimonious Wiener models for the neuromuscular blockade and for the depth of hypnosis is likely to be more successful than if standard models are used. Copyright © 2013 Elsevier Ireland Ltd. All rights reserved.

A dual-loop model of the human controller in single-axis tracking tasks

NASA Technical Reports Server (NTRS)

Hess, R. A.

1977-01-01

A dual loop model of the human controller in single axis compensatory tracking tasks is introduced. This model possesses an inner-loop closure which involves feeding back that portion of the controlled element output rate which is due to control activity. The sensory inputs to the human controller are assumed to be system error and control force. The former is assumed to be sensed via visual, aural, or tactile displays while the latter is assumed to be sensed in kinesthetic fashion. A nonlinear form of the model is briefly discussed. This model is then linearized and parameterized. A set of general adaptive characteristics for the parameterized model is hypothesized. These characteristics describe the manner in which the parameters in the linearized model will vary with such things as display quality. It is demonstrated that the parameterized model can produce controller describing functions which closely approximate those measured in laboratory tracking tasks for a wide variety of controlled elements.

Importance of Chemical Composition of Ice Nuclei on the Formation of Arctic Ice Clouds

NASA Astrophysics Data System (ADS)

Keita, Setigui Aboubacar; Girard, Eric

2016-09-01

Ice clouds play an important role in the Arctic weather and climate system but interactions between aerosols, clouds and radiation remain poorly understood. Consequently, it is essential to fully understand their properties and especially their formation process. Extensive measurements from ground-based sites and satellite remote sensing reveal the existence of two Types of Ice Clouds (TICs) in the Arctic during the polar night and early spring. TICs-1 are composed by non-precipitating small (radar-unseen) ice crystals of less than 30 μm in diameter. The second type, TICs-2, are detected by radar and are characterized by a low concentration of large precipitating ice crystals ice crystals (>30 μm). To explain these differences, we hypothesized that TIC-2 formation is linked to the acidification of aerosols, which inhibits the ice nucleating properties of ice nuclei (IN). As a result, the IN concentration is reduced in these regions, resulting to a lower concentration of larger ice crystals. Water vapor available for deposition being the same, these crystals reach a larger size. Current weather and climate models cannot simulate these different types of ice clouds. This problem is partly due to the parameterizations implemented for ice nucleation. Over the past 10 years, several parameterizations of homogeneous and heterogeneous ice nucleation on IN of different chemical compositions have been developed. These parameterizations are based on two approaches: stochastic (that is nucleation is a probabilistic process, which is time dependent) and singular (that is nucleation occurs at fixed conditions of temperature and humidity and time-independent). The best approach remains unclear. This research aims to better understand the formation process of Arctic TICs using recently developed ice nucleation parameterizations. For this purpose, we have implemented these ice nucleation parameterizations into the Limited Area version of the Global Multiscale Environmental Model (GEM-LAM) and use them to simulate ice clouds observed during the Indirect and Semi-Direct Aerosol Campaign (ISDAC) in Alaska. Simulation results of the TICs-2 observed on April 15th and 25th (acidic cases) and TICs-1 observed on April 5th (non-acidic cases) are presented. Our results show that the stochastic approach based on the classical nucleation theory with the appropriate contact angle is better. Parameterizations of ice nucleation based on the singular approach tend to overestimate the ice crystal concentration in TICs-1 and TICs-2. The classical nucleation theory using the appropriate contact angle is the best approach to use to simulate the ice clouds investigated in this research.

Impact of Parameterization of Physical Processes on Simulation of Track and Intensity of Tropical Cyclone Nargis (2008) with WRF-NMM Model

PubMed Central

Pattanayak, Sujata; Mohanty, U. C.; Osuri, Krishna K.

2012-01-01

The present study is carried out to investigate the performance of different cumulus convection, planetary boundary layer, land surface processes, and microphysics parameterization schemes in the simulation of a very severe cyclonic storm (VSCS) Nargis (2008), developed in the central Bay of Bengal on 27 April 2008. For this purpose, the nonhydrostatic mesoscale model (NMM) dynamic core of weather research and forecasting (WRF) system is used. Model-simulated track positions and intensity in terms of minimum central mean sea level pressure (MSLP), maximum surface wind (10 m), and precipitation are verified with observations as provided by the India Meteorological Department (IMD) and Tropical Rainfall Measurement Mission (TRMM). The estimated optimum combination is reinvestigated with six different initial conditions of the same case to have better conclusion on the performance of WRF-NMM. A few more diagnostic fields like vertical velocity, vorticity, and heat fluxes are also evaluated. The results indicate that cumulus convection play an important role in the movement of the cyclone, and PBL has a crucial role in the intensification of the storm. The combination of Simplified Arakawa Schubert (SAS) convection, Yonsei University (YSU) PBL, NMM land surface, and Ferrier microphysics parameterization schemes in WRF-NMM give better track and intensity forecast with minimum vector displacement error. PMID:22701366

Quality Assessment of the Cobel-Isba Numerical Forecast System of Fog and Low Clouds

NASA Astrophysics Data System (ADS)

Bergot, Thierry

2007-06-01

Short-term forecasting of fog is a difficult issue which can have a large societal impact. Fog appears in the surface boundary layer and is driven by the interactions between land surface and the lower layers of the atmosphere. These interactions are still not well parameterized in current operational NWP models, and a new methodology based on local observations, an adaptive assimilation scheme and a local numerical model is tested. The proposed numerical forecast method of foggy conditions has been run during three years at Paris-CdG international airport. This test over a long-time period allows an in-depth evaluation of the forecast quality. This study demonstrates that detailed 1-D models, including detailed physical parameterizations and high vertical resolution, can reasonably represent the major features of the life cycle of fog (onset, development and dissipation) up to +6 h. The error on the forecast onset and burn-off time is typically 1 h. The major weakness of the methodology is related to the evolution of low clouds (stratus lowering). Even if the occurrence of fog is well forecasted, the value of the horizontal visibility is only crudely forecasted. Improvements in the microphysical parameterization and in the translation algorithm converting NWP prognostic variables into a corresponding horizontal visibility seems necessary to accurately forecast the value of the visibility.

Ruffed grouse population dynamics in the central and southern Appalachians

Treesearch

John M. Giuliano Tirpak; C. Allan Miller; Thomas J. Allen; Steve Bittner; David A. Buehler; John W. Edwards; Craig A. Harper; William K. Igo; Gary W. Norman; M. Seamster; Dean F. Stauffer

2006-01-01

Ruffed grouse (Bonasa urnbellus; hereafter grouse) populations in the central and southern Appalachians are in decline. However, limited information on the dynamics of these populations prevents the development of effective management strategies to reverse these trends. We used radiotelemetry data collected on grouse to parameterize 6 models of...

AUTOMATED GEOSPATIAL WATERSHED ASSESSMENT (AGWA): A GIS-BASED HYDROLOGIC MODELING TOOL FOR WATERSHED ASSESSMENT AND ANALYSIS

EPA Science Inventory

The Automated Geospatial Watershed Assessment tool (AGWA) is a GIS interface jointly developed by the USDA Agricultural Research Service, the U.S. Environmental Protection Agency, the University of Arizona, and the University of Wyoming to automate the parameterization and execu...

AUTOMATED GEOSPATICAL WATERSHED ASSESSMENT (AGWA): A GIS-BASED HYDROLOICAL MODELING TOOL FOR WATERSHED ASSESSMENT AND ANALYSIS

EPA Science Inventory

The Automated Geospatial Watershed Assessment tool (AGWA) is a GIS interface jointly developed by the USDA Agricultural Research Service, the U.S. Environmental Protection Agency, the University of Arizona, and the University of Wyoming to automate the parameterization and execut...

A Model for Predicting Thermoelectric Properties of Bi2Te3

NASA Technical Reports Server (NTRS)

Lee, Seungwon; VonAllmen, Paul

2009-01-01

A parameterized orthogonal tight-binding mathematical model of the quantum electronic structure of the bismuth telluride molecule has been devised for use in conjunction with a semiclassical transport model in predicting the thermoelectric properties of doped bismuth telluride. This model is expected to be useful in designing and analyzing Bi2Te3 thermoelectric devices, including ones that contain such nano - structures as quantum wells and wires. In addition, the understanding gained in the use of this model can be expected to lead to the development of better models that could be useful for developing other thermoelectric materials and devices having enhanced thermoelectric properties. Bi2Te3 is one of the best bulk thermoelectric materials and is widely used in commercial thermoelectric devices. Most prior theoretical studies of the thermoelectric properties of Bi2Te3 have involved either continuum models or ab-initio models. Continuum models are computationally very efficient, but do not account for atomic-level effects. Ab-initio models are atomistic by definition, but do not scale well in that computation times increase excessively with increasing numbers of atoms. The present tight-binding model bridges the gap between the well-scalable but non-atomistic continuum models and the atomistic but poorly scalable ab-initio models: The present tight-binding model is atomistic, yet also computationally efficient because of the reduced (relative to an ab-initio model) number of basis orbitals and flexible parameterization of the Hamiltonian.

Modelling storm development and the impact when introducing waves, sea spray and heat fluxes

NASA Astrophysics Data System (ADS)

Wu, Lichuan; Rutgersson, Anna; Sahlée, Erik

2015-04-01

In high wind speed conditions, sea spray generated due to intensity breaking waves have big influence on the wind stress and heat fluxes. Measurements show that drag coefficient will decrease in high wind speed. Sea spray generation function (SSGF), an important term of wind stress parameterization in high wind speed, usually treated as a function of wind speed/friction velocity. In this study, we introduce a wave state depended SSGG and wave age depended Charnock number into a high wind speed wind stress parameterization (Kudryavtsev et al., 2011; 2012). The proposed wind stress parameterization and sea spray heat fluxes parameterization from Andreas et al., (2014) were applied to an atmosphere-wave coupled model to test on four storm cases. Compared with measurements from the FINO1 platform in the North Sea, the new wind stress parameterization can reduce the forecast errors of wind in high wind speed range, but not in low wind speed. Only sea spray impacted on wind stress, it will intensify the storms (minimum sea level pressure and maximum wind speed) and lower the air temperature (increase the errors). Only the sea spray impacted on the heat fluxes, it can improve the model performance on storm tracks and the air temperature, but not change much in the storm intensity. If both of sea spray impacted on the wind stress and heat fluxes are taken into account, it has the best performance in all the experiment for minimum sea level pressure and maximum wind speed and air temperature. Andreas, E. L., Mahrt, L., and Vickers, D. (2014). An improved bulk air-sea surface flux algorithm, including spray-mediated transfer. Quarterly Journal of the Royal Meteorological Society. Kudryavtsev, V. and Makin, V. (2011). Impact of ocean spray on the dynamics of the marine atmospheric boundary layer. Boundary-layer meteorology, 140(3):383-410. Kudryavtsev, V., Makin, V., and S, Z. (2012). On the sea-surface drag and heat/mass transfer at strong winds. Technical report, Royal Netherlands Meteorological Institute.

Toward Improved Parameterization of a Meso-Scale Hydrologic Model in a Discontinuous Permafrost, Boreal Forest Ecosystem

NASA Astrophysics Data System (ADS)

Endalamaw, A. M.; Bolton, W. R.; Young, J. M.; Morton, D.; Hinzman, L. D.

2013-12-01

The sub-arctic environment can be characterized as being located in the zone of discontinuous permafrost. Although the distribution of permafrost is site specific, it dominates many of the hydrologic and ecologic responses and functions including vegetation distribution, stream flow, soil moisture, and storage processes. In this region, the boundaries that separate the major ecosystem types (deciduous dominated and coniferous dominated ecosystems) as well as permafrost (permafrost verses non-permafrost) occur over very short spatial scales. One of the goals of this research project is to improve parameterizations of meso-scale hydrologic models in this environment. Using the Caribou-Poker Creeks Research Watershed (CPCRW) as the test area, simulations of the headwater catchments of varying permafrost and vegetation distributions were performed. CPCRW, located approximately 50 km northeast of Fairbanks, Alaska, is located within the zone of discontinuous permafrost and the boreal forest ecosystem. The Variable Infiltration Capacity (VIC) model was selected as the hydrologic model. In CPCRW, permafrost and coniferous vegetation is generally found on north facing slopes and valley bottoms. Permafrost free soils and deciduous vegetation is generally found on south facing slopes. In this study, hydrologic simulations using fine scale vegetation and soil parameterizations - based upon slope and aspect analysis at a 50 meter resolution - were conducted. Simulations were also conducted using downscaled vegetation from the Scenarios Network for Alaska and Arctic Planning (SNAP) (1 km resolution) and soil data sets from the Food and Agriculture Organization (FAO) (approximately 9 km resolution). Preliminary simulation results show that soil and vegetation parameterizations based upon fine scale slope/aspect analysis increases the R2 values (0.5 to 0.65 in the high permafrost (53%) basin; 0.43 to 0.56 in the low permafrost (2%) basin) relative to parameterization based on coarse scale data. These results suggest that using fine resolution parameterizations can be used to improve meso-scale hydrological modeling in this region.

Evaluation of Planetary Boundary Layer Scheme Sensitivities for the Purpose of Parameter Estimation

EPA Science Inventory

Meteorological model errors caused by imperfect parameterizations generally cannot be overcome simply by optimizing initial and boundary conditions. However, advanced data assimilation methods are capable of extracting significant information about parameterization behavior from ...

SURA-IOOS Coastal Inundation Testbed Inter-Model Evaluation of Tides, Waves, and Hurricane Surge in the Gulf of Mexico

NASA Astrophysics Data System (ADS)

Kerr, P. C.; Donahue, A.; Westerink, J. J.; Luettich, R.; Zheng, L.; Weisberg, R. H.; Wang, H. V.; Slinn, D. N.; Davis, J. R.; Huang, Y.; Teng, Y.; Forrest, D.; Haase, A.; Kramer, A.; Rhome, J.; Feyen, J. C.; Signell, R. P.; Hanson, J. L.; Taylor, A.; Hope, M.; Kennedy, A. B.; Smith, J. M.; Powell, M. D.; Cardone, V. J.; Cox, A. T.

2012-12-01

The Southeastern Universities Research Association (SURA), in collaboration with the NOAA Integrated Ocean Observing System program and other federal partners, developed a testbed to help accelerate progress in both research and the transition to operational use of models for both coastal and estuarine prediction. This testbed facilitates cyber-based sharing of data and tools, archival of observation data, and the development of cross-platform tools to efficiently access, visualize, skill assess, and evaluate model results. In addition, this testbed enables the modeling community to quantitatively assess the behavior (e.g., skill, robustness, execution speed) and implementation requirements (e.g. resolution, parameterization, computer capacity) that characterize the suitability and performance of selected models from both operational and fundamental science perspectives. This presentation focuses on the tropical coastal inundation component of the testbed and compares a variety of model platforms as well as grids in simulating tides, and the wave and surge environments for two extremely well documented historical hurricanes, Hurricanes Rita (2005) and Ike (2008). Model platforms included are ADCIRC, FVCOM, SELFE, SLOSH, SWAN, and WWMII. Model validation assessments were performed on simulation results using numerous station observation data in the form of decomposed harmonic constituents, water level high water marks and hydrographs of water level and wave data. In addition, execution speed, inundation extents defined by differences in wetting/drying schemes, resolution and parameterization sensitivities are also explored.

Parameterizing Urban Canopy Layer transport in an Lagrangian Particle Dispersion Model

NASA Astrophysics Data System (ADS)

Stöckl, Stefan; Rotach, Mathias W.

2016-04-01

The percentage of people living in urban areas is rising worldwide, crossed 50% in 2007 and is even higher in developed countries. High population density and numerous sources of air pollution in close proximity can lead to health issues. Therefore it is important to understand the nature of urban pollutant dispersion. In the last decades this field has experienced considerable progress, however the influence of large roughness elements is complex and has as of yet not been completely described. Hence, this work studied urban particle dispersion close to source and ground. It used an existing, steady state, three-dimensional Lagrangian particle dispersion model, which includes Roughness Sublayer parameterizations of turbulence and flow. The model is valid for convective and neutral to stable conditions and uses the kernel method for concentration calculation. As most Lagrangian models, its lower boundary is the zero-plane displacement, which means that roughly the lower two-thirds of the mean building height are not included in the model. This missing layer roughly coincides with the Urban Canopy Layer. An earlier work "traps" particles hitting the lower model boundary for a recirculation period, which is calculated under the assumption of a vortex in skimming flow, before "releasing" them again. The authors hypothesize that improving the lower boundary condition by including Urban Canopy Layer transport could improve model predictions. This was tested herein by not only trapping the particles, but also advecting them with a mean, parameterized flow in the Urban Canopy Layer. Now the model calculates the trapping period based on either recirculation due to vortex motion in skimming flow regimes or vertical velocity if no vortex forms, depending on incidence angle of the wind on a randomly chosen street canyon. The influence of this modification, as well as the model's sensitivity to parameterization constants, was investigated. To reach this goal, the model was initialized and compared with meteorological and SF6 tracer measurements from the Basel UrBan Boundary Layer Experiment (BUBBLE). The proposed modification does not improve the model's agreement with concentration observations, even though the trapping time shows promising agreement with measurements. Additionally, the modification's influence is smaller than those of different turbulence profiles, zero-plane displacement height and Roughness Sublayer height.

Dependence of marine stratocumulus reflectivities on liquid water paths

NASA Technical Reports Server (NTRS)

Coakley, James A., Jr.; Snider, Jack B.

1990-01-01

Simple parameterizations that relate cloud liquid water content to cloud reflectivity are often used in general circulation climate models to calculate the effect of clouds in the earth's energy budget. Such parameterizations have been developed by Stephens (1978) and by Slingo and Schrecker (1982) and others. Here researchers seek to verify the parametric relationship through the use of simultaneous observations of cloud liquid water content and cloud reflectivity. The column amount of cloud liquid was measured using a microwave radiometer on San Nicolas Island following techniques described by Hogg et al., (1983). Cloud reflectivity was obtained through spatial coherence analysis of Advanced Very High Resolution Radiometer (AVHRR) imagery data (Coakley and Beckner, 1988). They present the dependence of the observed reflectivity on the observed liquid water path. They also compare this empirical relationship with that proposed by Stephens (1978). Researchers found that by taking clouds to be isotropic reflectors, the observed reflectivities and observed column amounts of cloud liquid water are related in a manner that is consistent with simple parameterizations often used in general circulation climate models to determine the effect of clouds on the earth's radiation budget. Attempts to use the results of radiative transfer calculations to correct for the anisotropy of the AVHRR derived reflectivities resulted in a greater scatter of the points about the relationship expected between liquid water path and reflectivity. The anisotropy of the observed reflectivities proved to be small, much smaller than indicated by theory. To critically assess parameterizations, more simultaneous observations of cloud liquid water and cloud reflectivities and better calibration of the AVHRR sensors are needed.

The Effect of Subsurface Parameterizations on Modeled Flows in the Catchment Land Surface Model, Fortuna 2.5

NASA Astrophysics Data System (ADS)

Roningen, J. M.; Eylander, J. B.

2014-12-01

Groundwater use and management is subject to economic, legal, technical, and informational constraints and incentives at a variety of spatial and temporal scales. Planned and de facto management practices influenced by tax structures, legal frameworks, and agricultural and trade policies that vary at the country scale may have medium- and long-term effects on the ability of a region to support current and projected agricultural and industrial development. USACE is working to explore and develop global-scale, physically-based frameworks to serve as a baseline for hydrologic policy comparisons and consequence assessment, and such frameworks must include a reasonable representation of groundwater systems. To this end, we demonstrate the effects of different subsurface parameterizations, scaling, and meteorological forcings on surface and subsurface components of the Catchment Land Surface Model Fortuna v2.5 (Koster et al. 2000). We use the Land Information System 7 (Kumar et al. 2006) to process model runs using meteorological components of the Air Force Weather Agency's AGRMET forcing data from 2006 through 2011. Seasonal patterns and trends are examined in areas of the Upper Nile basin, northern China, and the Mississippi Valley. We also discuss the relevance of the model's representation of the catchment deficit with respect to local hydrogeologic structures.

Parameterized isoprene and monoterpene emissions from the boreal forest floor: Implementation into a 1D chemistry-transport model and investigation of the influence on atmospheric chemistry

NASA Astrophysics Data System (ADS)

Mogensen, Ditte; Aaltonen, Hermanni; Aalto, Juho; Bäck, Jaana; Kieloaho, Antti-Jussi; Gierens, Rosa; Smolander, Sampo; Kulmala, Markku; Boy, Michael

2015-04-01

Volatile organic compounds (VOCs) are emitted from the biosphere and can work as precursor gases for aerosol particles that can affect the climate (e.g. Makkonen et al., ACP, 2012). VOC emissions from needles and leaves have gained the most attention, however other parts of the ecosystem also have the ability to emit a vast amount of VOCs. This, often neglected, source can be important e.g. at periods where leaves are absent. Both sources and drivers related to forest floor emission of VOCs are currently limited. It is thought that the sources are mainly due to degradation of organic matter (Isidorov and Jdanova, Chemosphere, 2002), living roots (Asensio et al., Soil Biol. Biochem., 2008) and ground vegetation. The drivers are biotic (e.g. microbes) and abiotic (e.g. temperature and moisture). However, the relative importance of the sources and the drivers individually are currently poorly understood. Further, the relative importance of these factors is highly dependent on the tree species occupying the area of interest. The emission of isoprene and monoterpenes where measured from the boreal forest floor at the SMEAR II station in Southern Finland (Hari and Kulmala, Boreal Env. Res., 2005) during the snow-free period in 2010-2012. We used a dynamic method with 3 automated chambers analyzed by Proton Transfer Reaction - Mass Spectrometer (Aaltonen et al., Plant Soil, 2013). Using this data, we have developed empirical parameterizations for the emission of isoprene and monoterpenes from the forest floor. These parameterizations depends on abiotic factors, however, since the parameterizations are based on field measurements, biotic features are captured. Further, we have used the 1D chemistry-transport model SOSAA (Boy et al., ACP, 2011) to test the seasonal relative importance of inclusion of these parameterizations of the forest floor compared to the canopy crown emissions, on the atmospheric reactivity throughout the canopy.

Understanding and Improving Ocean Mixing Parameterizations for modeling Climate Change

NASA Astrophysics Data System (ADS)

Howard, A. M.; Fells, J.; Clarke, J.; Cheng, Y.; Canuto, V.; Dubovikov, M. S.

2017-12-01

Climate is vital. Earth is only habitable due to the atmosphere&oceans' distribution of energy. Our Greenhouse Gas emissions shift overall the balance between absorbed and emitted radiation causing Global Warming. How much of these emissions are stored in the ocean vs. entering the atmosphere to cause warming and how the extra heat is distributed depends on atmosphere&ocean dynamics, which we must understand to know risks of both progressive Climate Change and Climate Variability which affect us all in many ways including extreme weather, floods, droughts, sea-level rise and ecosystem disruption. Citizens must be informed to make decisions such as "business as usual" vs. mitigating emissions to avert catastrophe. Simulations of Climate Change provide needed knowledge but in turn need reliable parameterizations of key physical processes, including ocean mixing, which greatly impacts transport&storage of heat and dissolved CO2. The turbulence group at NASA-GISS seeks to use physical theory to improve parameterizations of ocean mixing, including smallscale convective, shear driven, double diffusive, internal wave and tidal driven vertical mixing, as well as mixing by submesoscale eddies, and lateral mixing along isopycnals by mesoscale eddies. Medgar Evers undergraduates aid NASA research while learning climate science and developing computer&math skills. We write our own programs in MATLAB and FORTRAN to visualize and process output of ocean simulations including producing statistics to help judge impacts of different parameterizations on fidelity in reproducing realistic temperatures&salinities, diffusivities and turbulent power. The results can help upgrade the parameterizations. Students are introduced to complex system modeling and gain deeper appreciation of climate science and programming skills, while furthering climate science. We are incorporating climate projects into the Medgar Evers college curriculum. The PI is both a member of the turbulence group at NASA-GISS and an associate professor at Medgar Evers College of CUNY, an urban minority serving institution in central Brooklyn. Supported by NSF Award AGS-1359293 And NASA Award NNX17AC81G.

Correction of Excessive Precipitation over Steep and High Mountains in a GCM: A Simple Method of Parameterizing the Thermal Effects of Subgrid Topographic Variation

NASA Technical Reports Server (NTRS)

Chao, Winston C.

2015-01-01

The excessive precipitation over steep and high mountains (EPSM) in GCMs and meso-scale models is due to a lack of parameterization of the thermal effects of the subgrid-scale topographic variation. These thermal effects drive subgrid-scale heated slope induced vertical circulations (SHVC). SHVC provide a ventilation effect of removing heat from the boundary layer of resolvable-scale mountain slopes and depositing it higher up. The lack of SHVC parameterization is the cause of EPSM. The author has previously proposed a method of parameterizing SHVC, here termed SHVC.1. Although this has been successful in avoiding EPSM, the drawback of SHVC.1 is that it suppresses convective type precipitation in the regions where it is applied. In this article we propose a new method of parameterizing SHVC, here termed SHVC.2. In SHVC.2 the potential temperature and mixing ratio of the boundary layer are changed when used as input to the cumulus parameterization scheme over mountainous regions. This allows the cumulus parameterization to assume the additional function of SHVC parameterization. SHVC.2 has been tested in NASA Goddard's GEOS-5 GCM. It achieves the primary goal of avoiding EPSM while also avoiding the suppression of convective-type precipitation in regions where it is applied.

Development, Parameterization, and Validation of a Visco-Plastic Material Model for Sand with DifferentLevels of Water Saturation

DTIC Science & Technology

2009-01-01

Generali- zed cap model for geological materials. J. Geotech . Eng. Div. ASME, 1976, 102(GT7), 638–699. 25 Sandler, I. S. and Rubin, D. An algorithm and a...under high strain rate loading. J. Geotech . Geoenviron. Eng., 2007, 133(2), 206–214. 27 Wong, J. R. and Reece, A. R. Prediction of rigid wheel

Sensitivity of Rainfall-runoff Model Parametrization and Performance to Potential Evaporation Inputs

NASA Astrophysics Data System (ADS)

Jayathilake, D. I.; Smith, T. J.

2017-12-01

Many watersheds of interest are confronted with insufficient data and poor process understanding. Therefore, understanding the relative importance of input data types and the impact of different qualities on model performance, parameterization, and fidelity is critically important to improving hydrologic models. In this paper, the change in model parameterization and performance are explored with respect to four different potential evapotranspiration (PET) products of varying quality. For each PET product, two widely used, conceptual rainfall-runoff models are calibrated with multiple objective functions to a sample of 20 basins included in the MOPEX data set and analyzed to understand how model behavior varied. Model results are further analyzed by classifying catchments as energy- or water-limited using the Budyko framework. The results demonstrated that model fit was largely unaffected by the quality of the PET inputs. However, model parameterizations were clearly sensitive to PET inputs, as their production parameters adjusted to counterbalance input errors. Despite this, changes in model robustness were not observed for either model across the four PET products, although robustness was affected by model structure.

A theory-based parameterization for heterogeneous ice nucleation and implications for the simulation of ice processes in atmospheric models

NASA Astrophysics Data System (ADS)

Savre, J.; Ekman, A. M. L.

2015-05-01

A new parameterization for heterogeneous ice nucleation constrained by laboratory data and based on classical nucleation theory is introduced. Key features of the parameterization include the following: a consistent and modular modeling framework for treating condensation/immersion and deposition freezing, the possibility to consider various potential ice nucleating particle types (e.g., dust, black carbon, and bacteria), and the possibility to account for an aerosol size distribution. The ice nucleating ability of each aerosol type is described using a contact angle (θ) probability density function (PDF). A new modeling strategy is described to allow the θ PDF to evolve in time so that the most efficient ice nuclei (associated with the lowest θ values) are progressively removed as they nucleate ice. A computationally efficient quasi Monte Carlo method is used to integrate the computed ice nucleation rates over both size and contact angle distributions. The parameterization is employed in a parcel model, forced by an ensemble of Lagrangian trajectories extracted from a three-dimensional simulation of a springtime low-level Arctic mixed-phase cloud, in order to evaluate the accuracy and convergence of the method using different settings. The same model setup is then employed to examine the importance of various parameters for the simulated ice production. Modeling the time evolution of the θ PDF is found to be particularly crucial; assuming a time-independent θ PDF significantly overestimates the ice nucleation rates. It is stressed that the capacity of black carbon (BC) to form ice in the condensation/immersion freezing mode is highly uncertain, in particular at temperatures warmer than -20°C. In its current version, the parameterization most likely overestimates ice initiation by BC.

Improved Climate Simulations through a Stochastic Parameterization of Ocean Eddies

NASA Astrophysics Data System (ADS)

Williams, Paul; Howe, Nicola; Gregory, Jonathan; Smith, Robin; Joshi, Manoj

2016-04-01

In climate simulations, the impacts of the sub-grid scales on the resolved scales are conventionally represented using deterministic closure schemes, which assume that the impacts are uniquely determined by the resolved scales. Stochastic parameterization relaxes this assumption, by sampling the sub-grid variability in a computationally inexpensive manner. This presentation shows that the simulated climatological state of the ocean is improved in many respects by implementing a simple stochastic parameterization of ocean eddies into a coupled atmosphere-ocean general circulation model. Simulations from a high-resolution, eddy-permitting ocean model are used to calculate the eddy statistics needed to inject realistic stochastic noise into a low-resolution, non-eddy-permitting version of the same model. A suite of four stochastic experiments is then run to test the sensitivity of the simulated climate to the noise definition, by varying the noise amplitude and decorrelation time within reasonable limits. The addition of zero-mean noise to the ocean temperature tendency is found to have a non-zero effect on the mean climate. Specifically, in terms of the ocean temperature and salinity fields both at the surface and at depth, the noise reduces many of the biases in the low-resolution model and causes it to more closely resemble the high-resolution model. The variability of the strength of the global ocean thermohaline circulation is also improved. It is concluded that stochastic ocean perturbations can yield reductions in climate model error that are comparable to those obtained by refining the resolution, but without the increased computational cost. Therefore, stochastic parameterizations of ocean eddies have the potential to significantly improve climate simulations. Reference PD Williams, NJ Howe, JM Gregory, RS Smith, and MM Joshi (2016) Improved Climate Simulations through a Stochastic Parameterization of Ocean Eddies. Journal of Climate, under revision.

10 Ways to Improve the Representation of MCSs in Climate Models

NASA Astrophysics Data System (ADS)

Schumacher, C.

2017-12-01

1. The first way to improve the representation of mesoscale convective systems (MCSs) in global climate models (GCMs) is to recognize that MCSs are important to climate. That may be obvious to most of the people attending this session, but it cannot be taken for granted in the wider community. The fact that MCSs produce large amounts of the global rainfall and that they dramatically impact the atmosphere via transports of heat, moisture, and momentum must be continuously stressed. 2-4. There has traditionally been three approaches to representing MCSs and/or their impacts in GCMs. The first is to focus on improving cumulus parameterizations by implementing things like cold pools that are assumed to better organize convection. The second is to focus on including mesoscale processes in the cumulus parameterization such as mesoscale vertical motions. The third is to just buy your way out with higher resolution using techniques like super-parameterization or global cloud-resolving model runs. All of these approaches have their pros and cons, but none of them satisfactorily solve the MCS climate modeling problem. 5-10. Looking forward, there is active discussion and new ideas in the modeling community on how to better represent convective organization in models. A number of ideas are a dramatic shift from the traditional plume-based cumulus parameterizations of most GCMs, such as implementing mesoscale parmaterizations based on their physical impacts (e.g., via heating), on empirical relationships based on big data/machine learning, or on stochastic approaches. Regardless of the technique employed, smart evaluation processes using observations are paramount to refining and constraining the inevitable tunable parameters in any parameterization.

Approaches to highly parameterized inversion-A guide to using PEST for groundwater-model calibration

USGS Publications Warehouse

Doherty, John E.; Hunt, Randall J.

2010-01-01

Highly parameterized groundwater models can create calibration difficulties. Regularized inversion-the combined use of large numbers of parameters with mathematical approaches for stable parameter estimation-is becoming a common approach to address these difficulties and enhance the transfer of information contained in field measurements to parameters used to model that system. Though commonly used in other industries, regularized inversion is somewhat imperfectly understood in the groundwater field. There is concern that this unfamiliarity can lead to underuse, and misuse, of the methodology. This document is constructed to facilitate the appropriate use of regularized inversion for calibrating highly parameterized groundwater models. The presentation is directed at an intermediate- to advanced-level modeler, and it focuses on the PEST software suite-a frequently used tool for highly parameterized model calibration and one that is widely supported by commercial graphical user interfaces. A brief overview of the regularized inversion approach is provided, and techniques for mathematical regularization offered by PEST are outlined, including Tikhonov, subspace, and hybrid schemes. Guidelines for applying regularized inversion techniques are presented after a logical progression of steps for building suitable PEST input. The discussion starts with use of pilot points as a parameterization device and processing/grouping observations to form multicomponent objective functions. A description of potential parameter solution methodologies and resources available through the PEST software and its supporting utility programs follows. Directing the parameter-estimation process through PEST control variables is then discussed, including guidance for monitoring and optimizing the performance of PEST. Comprehensive listings of PEST control variables, and of the roles performed by PEST utility support programs, are presented in the appendixes.

Simulated cold bias being improved by using MODIS time-varying albedo in the Tibetan Plateau in WRF model

NASA Astrophysics Data System (ADS)

Meng, X.; Lyu, S.; Zhang, T.; Zhao, L.; Li, Z.; Han, B.; Li, S.; Ma, D.; Chen, H.; Ao, Y.; Luo, S.; Shen, Y.; Guo, J.; Wen, L.

2018-04-01

Systematic cold biases exist in the simulation for 2 m air temperature in the Tibetan Plateau (TP) when using regional climate models and global atmospheric general circulation models. We updated the albedo in the Weather Research and Forecasting (WRF) Model lower boundary condition using the Global LAnd Surface Satellite Moderate-Resolution Imaging Spectroradiometer albedo products and demonstrated evident improvement for cold temperature biases in the TP. It is the large overestimation of albedo in winter and spring in the WRF model that resulted in the large cold temperature biases. The overestimated albedo was caused by the simulated precipitation biases and over-parameterization of snow albedo. Furthermore, light-absorbing aerosols can result in a large reduction of albedo in snow and ice cover. The results suggest the necessity of developing snow albedo parameterization using observations in the TP, where snow cover and melting are very different from other low-elevation regions, and the influence of aerosols should be considered as well. In addition to defining snow albedo, our results show an urgent call for improving precipitation simulation in the TP.

DOE Office of Scientific and Technical Information (OSTI.GOV)

Zhang, Na; Zhang, Peng; Kang, Wei

Multiscale simulations of fluids such as blood represent a major computational challenge of coupling the disparate spatiotemporal scales between molecular and macroscopic transport phenomena characterizing such complex fluids. In this paper, a coarse-grained (CG) particle model is developed for simulating blood flow by modifying the Morse potential, traditionally used in Molecular Dynamics for modeling vibrating structures. The modified Morse potential is parameterized with effective mass scales for reproducing blood viscous flow properties, including density, pressure, viscosity, compressibility and characteristic flow dynamics of human blood plasma fluid. The parameterization follows a standard inverse-problem approach in which the optimal micro parameters aremore » systematically searched, by gradually decoupling loosely correlated parameter spaces, to match the macro physical quantities of viscous blood flow. The predictions of this particle based multiscale model compare favorably to classic viscous flow solutions such as Counter-Poiseuille and Couette flows. It demonstrates that such coarse grained particle model can be applied to replicate the dynamics of viscous blood flow, with the advantage of bridging the gap between macroscopic flow scales and the cellular scales characterizing blood flow that continuum based models fail to handle adequately.« less

Statistical models of global Langmuir mixing

NASA Astrophysics Data System (ADS)

Li, Qing; Fox-Kemper, Baylor; Breivik, Øyvind; Webb, Adrean

2017-05-01

The effects of Langmuir mixing on the surface ocean mixing may be parameterized by applying an enhancement factor which depends on wave, wind, and ocean state to the turbulent velocity scale in the K-Profile Parameterization. Diagnosing the appropriate enhancement factor online in global climate simulations is readily achieved by coupling with a prognostic wave model, but with significant computational and code development expenses. In this paper, two alternatives that do not require a prognostic wave model, (i) a monthly mean enhancement factor climatology, and (ii) an approximation to the enhancement factor based on the empirical wave spectra, are explored and tested in a global climate model. Both appear to reproduce the Langmuir mixing effects as estimated using a prognostic wave model, with nearly identical and substantial improvements in the simulated mixed layer depth and intermediate water ventilation over control simulations, but significantly less computational cost. Simpler approaches, such as ignoring Langmuir mixing altogether or setting a globally constant Langmuir number, are found to be deficient. Thus, the consequences of Stokes depth and misaligned wind and waves are important.

Characterization of Cloud Water-Content Distribution

NASA Technical Reports Server (NTRS)

Lee, Seungwon

2010-01-01

The development of realistic cloud parameterizations for climate models requires accurate characterizations of subgrid distributions of thermodynamic variables. To this end, a software tool was developed to characterize cloud water-content distributions in climate-model sub-grid scales. This software characterizes distributions of cloud water content with respect to cloud phase, cloud type, precipitation occurrence, and geo-location using CloudSat radar measurements. It uses a statistical method called maximum likelihood estimation to estimate the probability density function of the cloud water content.

The evolution of biomass-burning aerosol size distributions due to coagulation: dependence on fire and meteorological details and parameterization

NASA Astrophysics Data System (ADS)

Sakamoto, Kimiko M.; Laing, James R.; Stevens, Robin G.; Jaffe, Daniel A.; Pierce, Jeffrey R.

2016-06-01

Biomass-burning aerosols have a significant effect on global and regional aerosol climate forcings. To model the magnitude of these effects accurately requires knowledge of the size distribution of the emitted and evolving aerosol particles. Current biomass-burning inventories do not include size distributions, and global and regional models generally assume a fixed size distribution from all biomass-burning emissions. However, biomass-burning size distributions evolve in the plume due to coagulation and net organic aerosol (OA) evaporation or formation, and the plume processes occur on spacial scales smaller than global/regional-model grid boxes. The extent of this size-distribution evolution is dependent on a variety of factors relating to the emission source and atmospheric conditions. Therefore, accurately accounting for biomass-burning aerosol size in global models requires an effective aerosol size distribution that accounts for this sub-grid evolution and can be derived from available emission-inventory and meteorological parameters. In this paper, we perform a detailed investigation of the effects of coagulation on the aerosol size distribution in biomass-burning plumes. We compare the effect of coagulation to that of OA evaporation and formation. We develop coagulation-only parameterizations for effective biomass-burning size distributions using the SAM-TOMAS large-eddy simulation plume model. For the most-sophisticated parameterization, we use the Gaussian Emulation Machine for Sensitivity Analysis (GEM-SA) to build a parameterization of the aged size distribution based on the SAM-TOMAS output and seven inputs: emission median dry diameter, emission distribution modal width, mass emissions flux, fire area, mean boundary-layer wind speed, plume mixing depth, and time/distance since emission. This parameterization was tested against an independent set of SAM-TOMAS simulations and yields R2 values of 0.83 and 0.89 for Dpm and modal width, respectively. The size distribution is particularly sensitive to the mass emissions flux, fire area, wind speed, and time, and we provide simplified fits of the aged size distribution to just these input variables. The simplified fits were tested against 11 aged biomass-burning size distributions observed at the Mt. Bachelor Observatory in August 2015. The simple fits captured over half of the variability in observed Dpm and modal width even though the freshly emitted Dpm and modal widths were unknown. These fits may be used in global and regional aerosol models. Finally, we show that coagulation generally leads to greater changes in the particle size distribution than OA evaporation/formation does, using estimates of OA production/loss from the literature.

Impact of Parameterized Lee Wave Drag on the Energy Budget of an Eddying Global Ocean Model

DTIC Science & Technology

2013-08-26

Teixeira, J., Peng, M., Hogan, T.F., Pauley, R., 2002. Navy Operational Global Atmospheric Prediction System (NOGAPS): Forcing for ocean models...Impact of parameterized lee wave drag on the energy budget of an eddying global ocean model David S. Trossman a,⇑, Brian K. Arbic a, Stephen T...input and output terms in the total mechanical energy budget of a hybrid coordinate high-resolution global ocean general circulation model forced by winds

A Canopy Architectural Model to Study the Competitive Ability of Chickpea with Sowthistle

PubMed Central

Cici, S-Zahra-Hosseini; Adkins, Steve; Hanan, Jim

2008-01-01

Background and Aims Improving the competitive ability of crops is a sustainable method of weed management. This paper shows how a virtual plant model of competition between chickpea (Cicer arietinum) and sowthistle (Sonchus oleraceus) can be used as a framework for discovering and/or developing more competitive chickpea cultivars. Methods The virtual plant models were developed using the L-systems formalism, parameterized according to measurements taken on plants at intervals during their development. A quasi-Monte Carlo light-environment model was used to model the effect of chickpea canopy on the development of sowthistle. The chickpea–light environment–sowthistle model (CLES model) captured the hypothesis that the architecture of chickpea plants modifies the light environment inside the canopy and determines sowthistle growth and development pattern. The resulting CLES model was parameterized for different chickpea cultivars (viz. ‘Macarena’, ‘Bumper’, ‘Jimbour’ and ‘99071-1001’) to compare their competitive ability with sowthistle. To validate the CLES model, an experiment was conducted using the same four chickpea cultivars as different treatments with a sowthistle growing under their canopy. Results and Conclusions The growth of sowthistle, both in silico and in glasshouse experiments, was reduced most by ‘99071-1001’, a cultivar with a short phyllochron. The second rank of competitive ability belonged to ‘Macarena’ and ‘Bumper’, while ‘Jimbour’ was the least competitive cultivar. The architecture of virtual chickpea plants modified the light inside the canopy, which influenced the growth and development of the sowthistle plants in response to different cultivars. This is the first time that a virtual plant model of a crop–weed interaction has been developed. This virtual plant model can serve as a platform for a broad range of applications in the study of chickpea–weed interactions and their environment. PMID:18375962

Ensemble projections of wildfire activity and carbonaceous aerosol concentrations over the western United States in the mid-21st century

PubMed Central

Yue, Xu; Mickley, Loretta J.; Logan, Jennifer A.; Kaplan, Jed O.

2013-01-01

We estimate future wildfire activity over the western United States during the mid-21st century (2046–2065), based on results from 15 climate models following the A1B scenario. We develop fire prediction models by regressing meteorological variables from the current and previous years together with fire indexes onto observed regional area burned. The regressions explain 0.25–0.60 of the variance in observed annual area burned during 1980–2004, depending on the ecoregion. We also parameterize daily area burned with temperature, precipitation, and relative humidity. This approach explains ~0.5 of the variance in observed area burned over forest ecoregions but shows no predictive capability in the semi-arid regions of Nevada and California. By applying the meteorological fields from 15 climate models to our fire prediction models, we quantify the robustness of our wildfire projections at mid-century. We calculate increases of 24–124% in area burned using regressions and 63–169% with the parameterization. Our projections are most robust in the southwestern desert, where all GCMs predict significant (p<0.05) meteorological changes. For forested ecoregions, more GCMs predict significant increases in future area burned with the parameterization than with the regressions, because the latter approach is sensitive to hydrological variables that show large inter-model variability in the climate projections. The parameterization predicts that the fire season lengthens by 23 days in the warmer and drier climate at mid-century. Using a chemical transport model, we find that wildfire emissions will increase summertime surface organic carbon aerosol over the western United States by 46–70% and black carbon by 20–27% at midcentury, relative to the present day. The pollution is most enhanced during extreme episodes: above the 84th percentile of concentrations, OC increases by ~90% and BC by ~50%, while visibility decreases from 130 km to 100 km in 32 Federal Class 1 areas in Rocky Mountains Forest. PMID:24015109

Bias Reduction as Guidance for Developing Convection and Cloud Parameterization in GFDL AM4/CM4

NASA Astrophysics Data System (ADS)

Zhao, M.; Held, I.; Golaz, C.

2016-12-01

The representations of moist convection and clouds are challenging in global climate models and they are known to be important to climate simulations at all spatial and temporal scales. Many climate simulation biases can be traced to deficiencies in convection and cloud parameterizations. I will present some key biases that we are concerned about and the efforts that we have made to reduce the biases during the development of NOAA's Geophysical Fluid Dynamics Laboratory (GFDL) new generation global climate model AM4/CM4. In particular, I will present a modified version of the moist convection scheme that is based on the University of Washington Shallow Cumulus scheme (UWShCu, Bretherton et. al 2004). The new scheme produces marked improvement in simulation of the Madden-Julian Oscillation (MJO) and the El Niño-Southern Oscillation (ENSO) compared to that used in AM3 and HIRAM. AM4/CM4 also produces high quality simulation of global distribution of cloud radiative effects and the precipitation with realistic mean climate state. This differs from models of improved MJO but with a much deteriorated mean state. The modifications to the UWShCu include an additional bulk plume for representing deep convection. The entrainment rate in the deep plume is parameterized to be a function of column-integrated relative humidity. The deep convective closure is based on relaxation of the convective available potential energy (CAPE) or cloud work function. The plumes' precipitation efficiency is optimized for better simulations of the cloud radiative effects. Precipitation re-evaporation is included in both shallow and deep plumes. In addition, a parameterization of convective gustiness is included with an energy source driven by cold pool derived from precipitation re-evaporation within the boundary layer and energy sink due to dissipation. I will present the motivations of these changes which are driven by reducing some aspects of the AM4/CM4 biases. Finally, I will also present the biases in current AM4/CM4 and challenges to further reduce them.

Implementation of rooftop reciculation parameterization into the QUIC fast response urban wind model

DOE Office of Scientific and Technical Information (OSTI.GOV)

Bagal, N.; Singh, B.; Pardyjak, E. R.

2004-01-01

The QUIC (Quick Urban & Industrial Complex) dispersion modeling system has been developed to provide high-resolution wind and concentration fields in cities. The fast response 3D urban wind model QUIC-URB explicitly solves for the flow field around buildings using a suite of empirical parameterizations and mass conservation. This procedure is based on the work of Rockle (1990). The current Rockle (1990) model does not capture the rooftop recirculation region associated with flow separation from the leading edge of an isolated building. According to Banks et al. (2001), there are two forms of separation depending on the incident wind angle. Formore » an incident wind angle within 20{sup o} of perpendicular to the front face of the building, 'bubble separation' occurs in which cylindrical vortices whose axis are orthogonal to the flow are generated along the rooftop surface (see Fig. 1). For a 'corner wind' flow or incident wind angle of 30{sup o} to 70{sup o} of perpendicular to the front face of the building, 'conical' or 'delta wing' vortices form along the roof surface (Fig. 3). In this work, a model for rooftop recirculation is implemented into the QUIC- URB model for the two incident wind angle regimes described above. The parameterizations for the length and height of the recirculation region are from Wilson (1979) for the case of flow perpendicular or near perpendicular to the building and from Banks et al. (2000) for the case of off-angle flow. In this paper, we describe the rooftop algorithms and show how the model results are improved through comparisons to experimental data (Snyder and Lawson 1994).« less

Evaluating Cloud Initialization in a Convection-permit NWP Model

NASA Astrophysics Data System (ADS)

Li, Jia; Chen, Baode

2015-04-01

In general, to avoid "double counting precipitation" problem, in convection permit NWP models, it was a common practice to turn off convective parameterization. However, if there were not any cloud information in the initial conditions, the occurrence of precipitation could be delayed due to spin-up of cloud field or microphysical variables. In this study, we utilized the complex cloud analysis package from the Advanced Regional Prediction System (ARPS) to adjust the initial states of the model on water substance, such as cloud water, cloud ice, rain water, et al., that is, to initialize the microphysical variables (i.e., hydrometers), mainly based on radar reflectivity observations. Using the Advanced Research WRF (ARW) model, numerical experiments with/without cloud initialization and convective parameterization were carried out at grey-zone resolutions (i.e. 1, 3, and 9 km). The results from the experiments without convective parameterization indicate that model ignition with radar reflectivity can significantly reduce spin-up time and accurately simulate precipitation at the initial time. In addition, it helps to improve location and intensity of predicted precipitation. With grey-zone resolutions (i.e. 1, 3, and 9 km), using the cumulus convective parameterization scheme (without radar data) cannot produce realistic precipitation at the early time. The issues related to microphysical parametrization associated with cloud initialization were also discussed.

Usage of Parameterized Fatigue Spectra and Physics-Based Systems Engineering Models for Wind Turbine Component Sizing: Preprint

DOE Office of Scientific and Technical Information (OSTI.GOV)

Parsons, Taylor; Guo, Yi; Veers, Paul

Software models that use design-level input variables and physics-based engineering analysis for estimating the mass and geometrical properties of components in large-scale machinery can be very useful for analyzing design trade-offs in complex systems. This study uses DriveSE, an OpenMDAO-based drivetrain model that uses stress and deflection criteria to size drivetrain components within a geared, upwind wind turbine. Because a full lifetime fatigue load spectrum can only be defined using computationally-expensive simulations in programs such as FAST, a parameterized fatigue loads spectrum that depends on wind conditions, rotor diameter, and turbine design life has been implemented. The parameterized fatigue spectrummore » is only used in this paper to demonstrate the proposed fatigue analysis approach. This paper details a three-part investigation of the parameterized approach and a comparison of the DriveSE model with and without fatigue analysis on the main shaft system. It compares loads from three turbines of varying size and determines if and when fatigue governs drivetrain sizing compared to extreme load-driven design. It also investigates the model's sensitivity to shaft material parameters. The intent of this paper is to demonstrate how fatigue considerations in addition to extreme loads can be brought into a system engineering optimization.« less

Numerical experiments on the role of radiative processes in the development and maintenance of upper level clouds

NASA Technical Reports Server (NTRS)

Starr, D. O'C.; Cox, S. K.

1981-01-01

A time-dependent, two-dimensional Eulerian model is presented whose purpose is to obtain more realistic parameterizations of extended high level cloudiness, and the results of a numerical experiment using the model are reported. The model is anelastic and the Bousinesque assumption is invoked. Unresolved subgrid scale processes are parameterized as eddy diffusion processes. Two phases of water are incorporated and equilibrium between them is assumed. The effects of infrared radiative processes are parametrically represented. Two simulations were conducted with identical initial conditions; in one of them, the radiation term was never turned on. The mean values of perturbation potential temperature at each level in the domain are plotted versus height after 15, 30, and 60 minutes of simulated time. The influence of the radiative term is seen to impose a cooling trend, leading to an increased generation of ice water and an increased generation of turbulent kinetic energy in the cloud layer.

A python framework for environmental model uncertainty analysis

USGS Publications Warehouse

White, Jeremy; Fienen, Michael N.; Doherty, John E.

2016-01-01

We have developed pyEMU, a python framework for Environmental Modeling Uncertainty analyses, open-source tool that is non-intrusive, easy-to-use, computationally efficient, and scalable to highly-parameterized inverse problems. The framework implements several types of linear (first-order, second-moment (FOSM)) and non-linear uncertainty analyses. The FOSM-based analyses can also be completed prior to parameter estimation to help inform important modeling decisions, such as parameterization and objective function formulation. Complete workflows for several types of FOSM-based and non-linear analyses are documented in example notebooks implemented using Jupyter that are available in the online pyEMU repository. Example workflows include basic parameter and forecast analyses, data worth analyses, and error-variance analyses, as well as usage of parameter ensemble generation and management capabilities. These workflows document the necessary steps and provides insights into the results, with the goal of educating users not only in how to apply pyEMU, but also in the underlying theory of applied uncertainty quantification.

Modeling late rectal toxicities based on a parameterized representation of the 3D dose distribution

NASA Astrophysics Data System (ADS)

Buettner, Florian; Gulliford, Sarah L.; Webb, Steve; Partridge, Mike

2011-04-01

Many models exist for predicting toxicities based on dose-volume histograms (DVHs) or dose-surface histograms (DSHs). This approach has several drawbacks as firstly the reduction of the dose distribution to a histogram results in the loss of spatial information and secondly the bins of the histograms are highly correlated with each other. Furthermore, some of the complex nonlinear models proposed in the past lack a direct physical interpretation and the ability to predict probabilities rather than binary outcomes. We propose a parameterized representation of the 3D distribution of the dose to the rectal wall which explicitly includes geometrical information in the form of the eccentricity of the dose distribution as well as its lateral and longitudinal extent. We use a nonlinear kernel-based probabilistic model to predict late rectal toxicity based on the parameterized dose distribution and assessed its predictive power using data from the MRC RT01 trial (ISCTRN 47772397). The endpoints under consideration were rectal bleeding, loose stools, and a global toxicity score. We extract simple rules identifying 3D dose patterns related to a specifically low risk of complication. Normal tissue complication probability (NTCP) models based on parameterized representations of geometrical and volumetric measures resulted in areas under the curve (AUCs) of 0.66, 0.63 and 0.67 for predicting rectal bleeding, loose stools and global toxicity, respectively. In comparison, NTCP models based on standard DVHs performed worse and resulted in AUCs of 0.59 for all three endpoints. In conclusion, we have presented low-dimensional, interpretable and nonlinear NTCP models based on the parameterized representation of the dose to the rectal wall. These models had a higher predictive power than models based on standard DVHs and their low dimensionality allowed for the identification of 3D dose patterns related to a low risk of complication.