Natural Ocean Carbon Cycle Sensitivity to Parameterizations of the Recycling in a Climate Model

Science.gov (United States)

Romanou, A.; Romanski, J.; Gregg, W. W.

2014-01-01

Sensitivities of the oceanic biological pump within the GISS (Goddard Institute for Space Studies ) climate modeling system are explored here. Results are presented from twin control simulations of the air-sea CO2 gas exchange using two different ocean models coupled to the same atmosphere. The two ocean models (Russell ocean model and Hybrid Coordinate Ocean Model, HYCOM) use different vertical coordinate systems, and therefore different representations of column physics. Both variants of the GISS climate model are coupled to the same ocean biogeochemistry module (the NASA Ocean Biogeochemistry Model, NOBM), which computes prognostic distributions for biotic and abiotic fields that influence the air-sea flux of CO2 and the deep ocean carbon transport and storage. In particular, the model differences due to remineralization rate changes are compared to differences attributed to physical processes modeled differently in the two ocean models such as ventilation, mixing, eddy stirring and vertical advection. GISSEH(GISSER) is found to underestimate mixed layer depth compared to observations by about 55% (10 %) in the Southern Ocean and overestimate it by about 17% (underestimate by 2%) in the northern high latitudes. Everywhere else in the global ocean, the two models underestimate the surface mixing by about 12-34 %, which prevents deep nutrients from reaching the surface and promoting primary production there. Consequently, carbon export is reduced because of reduced production at the surface. Furthermore, carbon export is particularly sensitive to remineralization rate changes in the frontal regions of the subtropical gyres and at the Equator and this sensitivity in the model is much higher than the sensitivity to physical processes such as vertical mixing, vertical advection and mesoscale eddy transport. At depth, GISSER, which has a significant warm bias, remineralizes nutrients and carbon faster thereby producing more nutrients and carbon at depth, which

The role of aerosols in cloud drop parameterizations and its applications in global climate models

Energy Technology Data Exchange (ETDEWEB)

Chuang, C.C.; Penner, J.E. [Lawrence Livermore National Lab., CA (United States)

1996-04-01

The characteristics of the cloud drop size distribution near cloud base are initially determined by aerosols that serve as cloud condensation nuclei and the updraft velocity. We have developed parameterizations relating cloud drop number concentration to aerosol number and sulfate mass concentrations and used them in a coupled global aerosol/general circulation model (GCM) to estimate the indirect aerosol forcing. The global aerosol model made use of our detailed emissions inventories for the amount of particulate matter from biomass burning sources and from fossil fuel sources as well as emissions inventories of the gas-phase anthropogenic SO{sub 2}. This work is aimed at validating the coupled model with the Atmospheric Radiation Measurement (ARM) Program measurements and assessing the possible magnitude of the aerosol-induced cloud effects on climate.

The cloud-phase feedback in the Super-parameterized Community Earth System Model

Science.gov (United States)

Burt, M. A.; Randall, D. A.

2016-12-01

Recent comparisons of observations and climate model simulations by I. Tan and colleagues have suggested that the Wegener-Bergeron-Findeisen (WBF) process tends to be too active in climate models, making too much cloud ice, and resulting in an exaggerated negative cloud-phase feedback on climate change. We explore the WBF process and its effect on shortwave cloud forcing in present-day and future climate simulations with the Community Earth System Model, and its super-parameterized counterpart. Results show that SP-CESM has much less cloud ice and a weaker cloud-phase feedback than CESM.

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

Science.gov (United States)

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.

Climate Simulations from Super-parameterized and Conventional General Circulation Models with a Third-order Turbulence Closure

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Xu, Kuan-Man; Cheng, Anning

2014-05-01

A high-resolution cloud-resolving model (CRM) embedded in a general circulation model (GCM) is an attractive alternative for climate modeling because it replaces all traditional cloud parameterizations and explicitly simulates cloud physical processes in each grid column of the GCM. Such an approach is called "Multiscale Modeling Framework." MMF still needs to parameterize the subgrid-scale (SGS) processes associated with clouds and large turbulent eddies because circulations associated with planetary boundary layer (PBL) and in-cloud turbulence are unresolved by CRMs with horizontal grid sizes on the order of a few kilometers. A third-order turbulence closure (IPHOC) has been implemented in the CRM component of the super-parameterized Community Atmosphere Model (SPCAM). IPHOC is used to predict (or diagnose) fractional cloudiness and the variability of temperature and water vapor at scales that are not resolved on the CRM's grid. This model has produced promised results, especially for low-level cloud climatology, seasonal variations and diurnal variations (Cheng and Xu 2011, 2013a, b; Xu and Cheng 2013a, b). Because of the enormous computational cost of SPCAM-IPHOC, which is 400 times of a conventional CAM, we decided to bypass the CRM and implement the IPHOC directly to CAM version 5 (CAM5). IPHOC replaces the PBL/stratocumulus, shallow convection, and cloud macrophysics parameterizations in CAM5. Since there are large discrepancies in the spatial and temporal scales between CRM and CAM5, IPHOC used in CAM5 has to be modified from that used in SPCAM. In particular, we diagnose all second- and third-order moments except for the fluxes. These prognostic and diagnostic moments are used to select a double-Gaussian probability density function to describe the SGS variability. We also incorporate a diagnostic PBL height parameterization to represent the strong inversion above PBL. The goal of this study is to compare the simulation of the climatology from these three

The urban land use in the COSMO-CLM model: a comparison of three parameterizations for Berlin

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Kristina Trusilova

2016-05-01

Full Text Available The regional non-hydrostatic climate model COSMO-CLM is increasingly being used on fine spatial scales of 1–5 km. Such applications require a detailed differentiation between the parameterization for natural and urban land uses. Since 2010, three parameterizations for urban land use have been incorporated into COSMO-CLM. These parameterizations vary in their complexity, required city parameters and their computational cost. We perform model simulations with the COSMO-CLM coupled to these three parameterizations for urban land in the same model domain of Berlin on a 1-km grid and compare results with available temperature observations. While all models capture the urban heat island, they differ in spatial detail, magnitude and the diurnal variation.

The influence of Cloud Longwave Scattering together with a state-of-the-art Ice Longwave Optical Parameterization in Climate Model Simulations

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Chen, Y. H.; Kuo, C. P.; Huang, X.; Yang, P.

2017-12-01

Clouds play an important role in the Earth's radiation budget, and thus realistic and comprehensive treatments of cloud optical properties and cloud-sky radiative transfer are crucial for simulating weather and climate. However, most GCMs neglect LW scattering effects by clouds and tend to use inconsistent cloud SW and LW optical parameterizations. Recently, co-authors of this study have developed a new LW optical properties parameterization for ice clouds, which is based on ice cloud particle statistics from MODIS measurements and state-of-the-art scattering calculation. A two-stream multiple-scattering scheme has also been implemented into the RRTMG_LW, a widely used longwave radiation scheme by climate modeling centers. This study is to integrate both the new LW cloud-radiation scheme for ice clouds and the modified RRTMG_LW with scattering capability into the NCAR CESM to improve the cloud longwave radiation treatment. A number of single column model (SCM) simulations using the observation from the ARM SGP site on July 18 to August 4 in 1995 are carried out to assess the impact of new LW optical properties of clouds and scattering-enabled radiation scheme on simulated radiation budget and cloud radiative effect (CRE). The SCM simulation allows interaction between cloud and radiation schemes with other parameterizations, but the large-scale forcing is prescribed or nudged. Comparing to the results from the SCM of the standard CESM, the new ice cloud optical properties alone leads to an increase of LW CRE by 26.85 W m-2 in average, as well as an increase of the downward LW flux at surface by 6.48 W m-2. Enabling LW cloud scattering further increases the LW CRE by another 3.57 W m-2 and the downward LW flux at the surface by 0.2 W m-2. The change of LW CRE is mainly due to an increase of cloud top height, which enhances the LW CRE. A long-term simulation of CESM will be carried out to further understand the impact of such changes on simulated climates.

Parameterization of clouds and radiation in climate models

Energy Technology Data Exchange (ETDEWEB)

Roeckner, E. [Max Planck Institute for Meterology, Hamburg (Germany)

1995-09-01

Clouds are a very important, yet poorly modeled element in the climate system. There are many potential cloud feedbacks, including those related to cloud cover, height, water content, phase change, and droplet concentration and size distribution. As a prerequisite to studying the cloud feedback issue, this research reports on the simulation and validation of cloud radiative forcing under present climate conditions using the ECHAM general circulation model and ERBE top-of-atmosphere radiative fluxes.

Formulation of an ocean model for global climate simulations

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S. M. Griffies

2005-01-01

Full Text Available This paper summarizes the formulation of the ocean component to the Geophysical Fluid Dynamics Laboratory's (GFDL climate model used for the 4th IPCC Assessment (AR4 of global climate change. In particular, it reviews the numerical schemes and physical parameterizations that make up an ocean climate model and how these schemes are pieced together for use in a state-of-the-art climate model. Features of the model described here include the following: (1 tripolar grid to resolve the Arctic Ocean without polar filtering, (2 partial bottom step representation of topography to better represent topographically influenced advective and wave processes, (3 more accurate equation of state, (4 three-dimensional flux limited tracer advection to reduce overshoots and undershoots, (5 incorporation of regional climatological variability in shortwave penetration, (6 neutral physics parameterization for representation of the pathways of tracer transport, (7 staggered time stepping for tracer conservation and numerical efficiency, (8 anisotropic horizontal viscosities for representation of equatorial currents, (9 parameterization of exchange with marginal seas, (10 incorporation of a free surface that accomodates a dynamic ice model and wave propagation, (11 transport of water across the ocean free surface to eliminate unphysical ``virtual tracer flux' methods, (12 parameterization of tidal mixing on continental shelves. We also present preliminary analyses of two particularly important sensitivities isolated during the development process, namely the details of how parameterized subgridscale eddies transport momentum and tracers.

Improvement and implementation of a parameterization for shallow cumulus in the global climate model ECHAM5-HAM

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Isotta, Francesco; Spichtinger, Peter; Lohmann, Ulrike; von Salzen, Knut

2010-05-01

Convection is a crucial component of weather and climate. Its parameterization in General Circulation Models (GCMs) is one of the largest sources of uncertainty. Convection redistributes moisture and heat, affects the radiation budget and transports tracers from the PBL to higher levels. Shallow convection is very common over the globe, in particular over the oceans in the trade wind regions. A recently developed shallow convection scheme by von Salzen and McFarlane (2002) is implemented in the ECHAM5-HAM GCM instead of the standard convection scheme by Tiedtke (1989). The scheme of von Salzen and McFarlane (2002) is a bulk parameterization for an ensemble of transient shallow cumuli. A life cycle is considered, as well as inhomogeneities in the horizontal distribution of in-cloud properties due to mixing. The shallow convection scheme is further developed to take the ice phase and precipitation in form of rain and snow into account. The double moment microphysics scheme for cloud droplets and ice crystals implemented is consistent with the stratiform scheme and with the other types of convective clouds. The ice phase permits to alter the criterion to distinguish between shallow convection and the other two types of convection, namely deep and mid-level, which are still calculated by the Tiedtke (1989) scheme. The lunching layer of the test parcel in the shallow convection scheme is chosen as the one with maximum moist static energy in the three lowest levels. The latter is modified to the ``frozen moist static energy'' to account for the ice phase. Moreover, tracers (e.g. aerosols) are transported in the updraft and scavenged in and below clouds. As a first test of the performance of the new scheme and the interaction with the rest of the model, the Barbados Oceanographic and Meteorological EXperiment (BOMEX) and the Rain In Cumulus over the Ocean experiment (RICO) case are simulated with the single column model (SCM) and the results are compared with large eddy

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

Science.gov (United States)

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.

Mixing parametrizations for ocean climate modelling

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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

On the Dependence of Cloud Feedbacks on Physical Parameterizations in WRF Aquaplanet Simulations

Science.gov (United States)

Cesana, Grégory; Suselj, Kay; Brient, Florent

2017-10-01

We investigate the effects of physical parameterizations on cloud feedback uncertainty in response to climate change. For this purpose, we construct an ensemble of eight aquaplanet simulations using the Weather Research and Forecasting (WRF) model. In each WRF-derived simulation, we replace only one parameterization at a time while all other parameters remain identical. By doing so, we aim to (i) reproduce cloud feedback uncertainty from state-of-the-art climate models and (ii) understand how parametrizations impact cloud feedbacks. Our results demonstrate that this ensemble of WRF simulations, which differ only in physical parameterizations, replicates the range of cloud feedback uncertainty found in state-of-the-art climate models. We show that microphysics and convective parameterizations govern the magnitude and sign of cloud feedbacks, mostly due to tropical low-level clouds in subsidence regimes. Finally, this study highlights the advantages of using WRF to analyze cloud feedback mechanisms owing to its plug-and-play parameterization capability.

Scale dependency of regional climate modeling of current and future climate extremes in Germany

Science.gov (United States)

Tölle, Merja H.; Schefczyk, Lukas; Gutjahr, Oliver

2017-11-01

A warmer climate is projected for mid-Europe, with less precipitation in summer, but with intensified extremes of precipitation and near-surface temperature. However, the extent and magnitude of such changes are associated with creditable uncertainty because of the limitations of model resolution and parameterizations. Here, we present the results of convection-permitting regional climate model simulations for Germany integrated with the COSMO-CLM using a horizontal grid spacing of 1.3 km, and additional 4.5- and 7-km simulations with convection parameterized. Of particular interest is how the temperature and precipitation fields and their extremes depend on the horizontal resolution for current and future climate conditions. The spatial variability of precipitation increases with resolution because of more realistic orography and physical parameterizations, but values are overestimated in summer and over mountain ridges in all simulations compared to observations. The spatial variability of temperature is improved at a resolution of 1.3 km, but the results are cold-biased, especially in summer. The increase in resolution from 7/4.5 km to 1.3 km is accompanied by less future warming in summer by 1 ∘C. Modeled future precipitation extremes will be more severe, and temperature extremes will not exclusively increase with higher resolution. Although the differences between the resolutions considered (7/4.5 km and 1.3 km) are small, we find that the differences in the changes in extremes are large. High-resolution simulations require further studies, with effective parameterizations and tunings for different topographic regions. Impact models and assessment studies may benefit from such high-resolution model results, but should account for the impact of model resolution on model processes and climate change.

Parameterizing sub-surface drainage with geology to improve modeling streamflow responses to climate in data limited environments

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C. L. Tague

2013-01-01

Full Text Available Hydrologic models are one of the core tools used to project how water resources may change under a warming climate. These models are typically applied over a range of scales, from headwater streams to higher order rivers, and for a variety of purposes, such as evaluating changes to aquatic habitat or reservoir operation. Most hydrologic models require streamflow data to calibrate subsurface drainage parameters. In many cases, long-term gage records may not be available for calibration, particularly when assessments are focused on low-order stream reaches. Consequently, hydrologic modeling of climate change impacts is often performed in the absence of sufficient data to fully parameterize these hydrologic models. In this paper, we assess a geologic-based strategy for assigning drainage parameters. We examine the performance of this modeling strategy for the McKenzie River watershed in the US Oregon Cascades, a region where previous work has demonstrated sharp contrasts in hydrology based primarily on geological differences between the High and Western Cascades. Based on calibration and verification using existing streamflow data, we demonstrate that: (1 a set of streams ranging from 1st to 3rd order within the Western Cascade geologic region can share the same drainage parameter set, while (2 streams from the High Cascade geologic region require a different parameter set. Further, we show that a watershed comprised of a mixture of High and Western Cascade geologies can be modeled without additional calibration by transferring parameters from these distinctive High and Western Cascade end-member parameter sets. More generally, we show that by defining a set of end-member parameters that reflect different geologic classes, we can more efficiently apply a hydrologic model over a geologically complex landscape and resolve geo-climatic differences in how different watersheds are likely to respond to simple warming scenarios.

Droplet Nucleation: Physically-Based Parameterizations and Comparative Evaluation

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Steve Ghan

2011-10-01

Full Text Available One of the greatest sources of uncertainty in simulations of climate and climate change is the influence of aerosols on the optical properties of clouds. The root of this influence is the droplet nucleation process, which involves the spontaneous growth of aerosol into cloud droplets at cloud edges, during the early stages of cloud formation, and in some cases within the interior of mature clouds. Numerical models of droplet nucleation represent much of the complexity of the process, but at a computational cost that limits their application to simulations of hours or days. Physically-based parameterizations of droplet nucleation are designed to quickly estimate the number nucleated as a function of the primary controlling parameters: the aerosol number size distribution, hygroscopicity and cooling rate. Here we compare and contrast the key assumptions used in developing each of the most popular parameterizations and compare their performances under a variety of conditions. We find that the more complex parameterizations perform well under a wider variety of nucleation conditions, but all parameterizations perform well under the most common conditions. We then discuss the various applications of the parameterizations to cloud-resolving, regional and global models to study aerosol effects on clouds at a wide range of spatial and temporal scales. We compare estimates of anthropogenic aerosol indirect effects using two different parameterizations applied to the same global climate model, and find that the estimates of indirect effects differ by only 10%. We conclude with a summary of the outstanding challenges remaining for further development and application.

Splitting turbulence algorithm for mixing parameterization embedded in the ocean climate model. Examples of data assimilation and Prandtl number variations.

Science.gov (United States)

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

2017-04-01

Series of experiments were performed with a three-dimensional, free surface, sigma coordinate eddy-permitting ocean circulation model for Atlantic (from 30°S) - Arctic and Bering sea domain (0.25 degrees resolution, Institute of Numerical Mathematics Ocean Model or INMOM) using vertical grid refinement in the zone of fully developed turbulence (40 sigma-levels). The model variables are horizontal velocity components, potential temperature, and salinity as well as free surface height. For parameterization of viscosity and diffusivity, the original splitting turbulence algorithm (STA) is used when total evolutionary equations for the turbulence kinetic energy (TKE) and turbulence dissipation frequency (TDF) split into the stages of transport-diffusion and generation-dissipation. For the generation-dissipation stage the analytical solution was obtained for TKE and TDF as functions of the buoyancy and velocity shift frequencies (BF and VSF). The proposed model with STA is similar to the contemporary differential turbulence models, concerning the physical formulations. At the same time, its algorithm has high enough computational efficiency. For mixing simulation in the zone of turbulence decay, the two kind numerical experiments were carried out, as with assimilation of annual mean climatic buoyancy frequency, as with variation of Prandtl number function dependence upon the BF, VSF, TKE and TDF. The CORE-II data for 1948-2009 were used for experiments. Quality of temperature T and salinity S structure simulation is estimated by the comparison of model monthly profiles T and S averaged for 1980-2009, with T and S monthly data from the World Ocean Atlas 2013. Form of coefficients in equations for TKE and TDF on the generation-dissipation stage makes it possible to assimilate annual mean climatic buoyancy frequency in a varying degree that cardinally improves adequacy of model results to climatic data in all analyzed model domain. The numerical experiments with modified

Carbody structural lightweighting based on implicit parameterized model

Science.gov (United States)

Chen, Xin; Ma, Fangwu; Wang, Dengfeng; Xie, Chen

2014-05-01

Most of recent research on carbody lightweighting has focused on substitute material and new processing technologies rather than structures. However, new materials and processing techniques inevitably lead to higher costs. Also, material substitution and processing lightweighting have to be realized through body structural profiles and locations. In the huge conventional workload of lightweight optimization, model modifications involve heavy manual work, and it always leads to a large number of iteration calculations. As a new technique in carbody lightweighting, the implicit parameterization is used to optimize the carbody structure to improve the materials utilization rate in this paper. The implicit parameterized structural modeling enables the use of automatic modification and rapid multidisciplinary design optimization (MDO) in carbody structure, which is impossible in the traditional structure finite element method (FEM) without parameterization. The structural SFE parameterized model is built in accordance with the car structural FE model in concept development stage, and it is validated by some structural performance data. The validated SFE structural parameterized model can be used to generate rapidly and automatically FE model and evaluate different design variables group in the integrated MDO loop. The lightweighting result of body-in-white (BIW) after the optimization rounds reveals that the implicit parameterized model makes automatic MDO feasible and can significantly improve the computational efficiency of carbody structural lightweighting. This paper proposes the integrated method of implicit parameterized model and MDO, which has the obvious practical advantage and industrial significance in the carbody structural lightweighting design.

A stratiform cloud parameterization for General Circulation Models

International Nuclear Information System (INIS)

Ghan, S.J.; Leung, L.R.; Chuang, C.C.; Penner, J.E.; McCaa, J.

1994-01-01

The crude treatment of clouds in General Circulation Models (GCMs) is widely recognized as a major limitation in the application of these models to predictions of global climate change. The purpose of this project is to develop a paxameterization for stratiform clouds in GCMs that expresses stratiform clouds in terms of bulk microphysical properties and their subgrid variability. In this parameterization, precipitating cloud species are distinguished from non-precipitating species, and the liquid phase is distinguished from the ice phase. The size of the non-precipitating cloud particles (which influences both the cloud radiative properties and the conversion of non-precipitating cloud species to precipitating species) is determined by predicting both the mass and number concentrations of each species

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

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A. Endalamaw

2017-09-01

Full Text Available 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 better 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

Sensitivity of the weather research and forecasting model to parameterization schemes for regional climate of Nile River Basin

Science.gov (United States)

Tariku, Tebikachew Betru; Gan, Thian Yew

2018-06-01

Regional climate models (RCMs) have been used to simulate rainfall at relatively high spatial and temporal resolutions useful for sustainable water resources planning, design and management. In this study, the sensitivity of the RCM, weather research and forecasting (WRF), in modeling the regional climate of the Nile River Basin (NRB) was investigated using 31 combinations of different physical parameterization schemes which include cumulus (Cu), microphysics (MP), planetary boundary layer (PBL), land-surface model (LSM) and radiation (Ra) schemes. Using the European Centre for Medium-Range Weather Forecast (ECMWF) ERA-Interim reanalysis data as initial and lateral boundary conditions, WRF was configured to model the climate of NRB at a resolution of 36 km with 30 vertical levels. The 1999-2001 simulations using WRF were compared with satellite data combined with ground observation and the NCEP reanalysis data for 2 m surface air temperature (T2), rainfall, short- and longwave downward radiation at the surface (SWRAD, LWRAD). Overall, WRF simulated more accurate T2 and LWRAD (with correlation coefficients >0.8 and low root-mean-square error) than SWRAD and rainfall for the NRB. Further, the simulation of rainfall is more sensitive to PBL, Cu and MP schemes than other schemes of WRF. For example, WRF simulated less biased rainfall with Kain-Fritsch combined with MYJ than with YSU as the PBL scheme. The simulation of T2 is more sensitive to LSM and Ra than to Cu, PBL and MP schemes selected, SWRAD is more sensitive to MP and Ra than to Cu, LSM and PBL schemes, and LWRAD is more sensitive to LSM, Ra and PBL than Cu, and MP schemes. In summary, the following combination of schemes simulated the most representative regional climate of NRB: WSM3 microphysics, KF cumulus, MYJ PBL, RRTM longwave radiation and Dudhia shortwave radiation schemes, and Noah LSM. The above configuration of WRF coupled to the Noah LSM has also been shown to simulate representative regional

Sensitivity of the weather research and forecasting model to parameterization schemes for regional climate of Nile River Basin

Science.gov (United States)

Tariku, Tebikachew Betru; Gan, Thian Yew

2017-08-01

Regional climate models (RCMs) have been used to simulate rainfall at relatively high spatial and temporal resolutions useful for sustainable water resources planning, design and management. In this study, the sensitivity of the RCM, weather research and forecasting (WRF), in modeling the regional climate of the Nile River Basin (NRB) was investigated using 31 combinations of different physical parameterization schemes which include cumulus (Cu), microphysics (MP), planetary boundary layer (PBL), land-surface model (LSM) and radiation (Ra) schemes. Using the European Centre for Medium-Range Weather Forecast (ECMWF) ERA-Interim reanalysis data as initial and lateral boundary conditions, WRF was configured to model the climate of NRB at a resolution of 36 km with 30 vertical levels. The 1999-2001 simulations using WRF were compared with satellite data combined with ground observation and the NCEP reanalysis data for 2 m surface air temperature (T2), rainfall, short- and longwave downward radiation at the surface (SWRAD, LWRAD). Overall, WRF simulated more accurate T2 and LWRAD (with correlation coefficients >0.8 and low root-mean-square error) than SWRAD and rainfall for the NRB. Further, the simulation of rainfall is more sensitive to PBL, Cu and MP schemes than other schemes of WRF. For example, WRF simulated less biased rainfall with Kain-Fritsch combined with MYJ than with YSU as the PBL scheme. The simulation of T2 is more sensitive to LSM and Ra than to Cu, PBL and MP schemes selected, SWRAD is more sensitive to MP and Ra than to Cu, LSM and PBL schemes, and LWRAD is more sensitive to LSM, Ra and PBL than Cu, and MP schemes. In summary, the following combination of schemes simulated the most representative regional climate of NRB: WSM3 microphysics, KF cumulus, MYJ PBL, RRTM longwave radiation and Dudhia shortwave radiation schemes, and Noah LSM. The above configuration of WRF coupled to the Noah LSM has also been shown to simulate representative regional

New Gravity Wave Treatments for GISS Climate Models

Science.gov (United States)

Geller, Marvin A.; Zhou, Tiehan; Ruedy, Reto; Aleinov, Igor; Nazarenko, Larissa; Tausnev, Nikolai L.; Sun, Shan; Kelley, Maxwell; Cheng, Ye

2011-01-01

Previous versions of GISS climate models have either used formulations of Rayleigh drag to represent unresolved gravity wave interactions with the model-resolved flow or have included a rather complicated treatment of unresolved gravity waves that, while being climate interactive, involved the specification of a relatively large number of parameters that were not well constrained by observations and also was computationally very expensive. Here, the authors introduce a relatively simple and computationally efficient specification of unresolved orographic and nonorographic gravity waves and their interaction with the resolved flow. Comparisons of the GISS model winds and temperatures with no gravity wave parameterization; with only orographic gravity wave parameterization; and with both orographic and nonorographic gravity wave parameterizations are shown to illustrate how the zonal mean winds and temperatures converge toward observations. The authors also show that the specifications of orographic and nonorographic gravity waves must be different in the Northern and Southern Hemispheres. Then results are presented where the nonorographic gravity wave sources are specified to represent sources from convection in the intertropical convergence zone and spontaneous emission from jet imbalances. Finally, a strategy to include these effects in a climate-dependent manner is suggested.

A stratiform cloud parameterization for general circulation models

International Nuclear Information System (INIS)

Ghan, S.J.; Leung, L.R.; Chuang, C.C.; Penner, J.E.; McCaa, J.

1994-01-01

The crude treatment of clouds in general circulation models (GCMs) is widely recognized as a major limitation in applying these models to predictions of global climate change. The purpose of this project is to develop in GCMs a stratiform cloud parameterization that expresses clouds in terms of bulk microphysical properties and their subgrid variability. Various clouds variables and their interactions are summarized. Precipitating cloud species are distinguished from non-precipitating species, and the liquid phase is distinguished from the ice phase. The size of the non-precipitating cloud particles (which influences both the cloud radiative properties and the conversion of non-precipitating cloud species to precipitating species) is determined by predicting both the mass and number concentrations of each species

Atmospheric water vapor transport: Estimation of continental precipitation recycling and parameterization of a simple climate model. M.S. Thesis

Science.gov (United States)

Brubaker, Kaye L.; Entekhabi, Dara; Eagleson, Peter S.

1991-01-01

The advective transport of atmospheric water vapor and its role in global hydrology and the water balance of continental regions are discussed and explored. The data set consists of ten years of global wind and humidity observations interpolated onto a regular grid by objective analysis. Atmospheric water vapor fluxes across the boundaries of selected continental regions are displayed graphically. The water vapor flux data are used to investigate the sources of continental precipitation. The total amount of water that precipitates on large continental regions is supplied by two mechanisms: (1) advection from surrounding areas external to the region; and (2) evaporation and transpiration from the land surface recycling of precipitation over the continental area. The degree to which regional precipitation is supplied by recycled moisture is a potentially significant climate feedback mechanism and land surface-atmosphere interaction, which may contribute to the persistence and intensification of droughts. A simplified model of the atmospheric moisture over continents and simultaneous estimates of regional precipitation are employed to estimate, for several large continental regions, the fraction of precipitation that is locally derived. In a separate, but related, study estimates of ocean to land water vapor transport are used to parameterize an existing simple climate model, containing both land and ocean surfaces, that is intended to mimic the dynamics of continental climates.

Spectral cumulus parameterization based on cloud-resolving model

Science.gov (United States)

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.

Parameterization of Rocket Dust Storms on Mars in the LMD Martian GCM: Modeling Details and Validation

Science.gov (United States)

Wang, Chao; Forget, François; Bertrand, Tanguy; Spiga, Aymeric; Millour, Ehouarn; Navarro, Thomas

2018-04-01

The origin of the detached dust layers observed by the Mars Climate Sounder aboard the Mars Reconnaissance Orbiter is still debated. Spiga et al. (2013, https://doi.org/10.1002/jgre.20046) revealed that deep mesoscale convective "rocket dust storms" are likely to play an important role in forming these dust layers. To investigate how the detached dust layers are generated by this mesoscale phenomenon and subsequently evolve at larger scales, a parameterization of rocket dust storms to represent the mesoscale dust convection is designed and included into the Laboratoire de Météorologie Dynamique (LMD) Martian Global Climate Model (GCM). The new parameterization allows dust particles in the GCM to be transported to higher altitudes than in traditional GCMs. Combined with the horizontal transport by large-scale winds, the dust particles spread out and form detached dust layers. During the Martian dusty seasons, the LMD GCM with the new parameterization is able to form detached dust layers. The formation, evolution, and decay of the simulated dust layers are largely in agreement with the Mars Climate Sounder observations. This suggests that mesoscale rocket dust storms are among the key factors to explain the observed detached dust layers on Mars. However, the detached dust layers remain absent in the GCM during the clear seasons, even with the new parameterization. This implies that other relevant atmospheric processes, operating when no dust storms are occurring, are needed to explain the Martian detached dust layers. More observations of local dust storms could improve the ad hoc aspects of this parameterization, such as the trigger and timing of dust injection.

Impact of a Stochastic Parameterization Scheme on El Nino-Southern Oscillation in the Community Climate System Model

Science.gov (United States)

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 energetically consistent vertical mixing parameterization in CCSM4

DEFF Research Database (Denmark)

Nielsen, Søren Borg; Jochum, Markus; Eden, Carsten

2018-01-01

An energetically consistent stratification-dependent vertical mixing parameterization is implemented in the Community Climate System Model 4 and forced with energy conversion from the barotropic tides to internal waves. The structures of the resulting dissipation and diffusivity fields are compared......, however, depends greatly on the details of the vertical mixing parameterizations, where the new energetically consistent parameterization results in low thermocline diffusivities and a sharper and shallower thermocline. It is also investigated if the ocean state is more sensitive to a change in forcing...

Sensitivity of U.S. summer precipitation to model resolution and convective parameterizations across gray zone resolutions

Science.gov (United States)

Gao, Yang; Leung, L. Ruby; Zhao, Chun; Hagos, Samson

2017-03-01

Simulating summer precipitation is a significant challenge for climate models that rely on cumulus parameterizations to represent moist convection processes. Motivated by recent advances in computing that support very high-resolution modeling, this study aims to systematically evaluate the effects of model resolution and convective parameterizations across the gray zone resolutions. Simulations using the Weather Research and Forecasting model were conducted at grid spacings of 36 km, 12 km, and 4 km for two summers over the conterminous U.S. The convection-permitting simulations at 4 km grid spacing are most skillful in reproducing the observed precipitation spatial distributions and diurnal variability. Notable differences are found between simulations with the traditional Kain-Fritsch (KF) and the scale-aware Grell-Freitas (GF) convection schemes, with the latter more skillful in capturing the nocturnal timing in the Great Plains and North American monsoon regions. The GF scheme also simulates a smoother transition from convective to large-scale precipitation as resolution increases, resulting in reduced sensitivity to model resolution compared to the KF scheme. Nonhydrostatic dynamics has a positive impact on precipitation over complex terrain even at 12 km and 36 km grid spacings. With nudging of the winds toward observations, we show that the conspicuous warm biases in the Southern Great Plains are related to precipitation biases induced by large-scale circulation biases, which are insensitive to model resolution. Overall, notable improvements in simulating summer rainfall and its diurnal variability through convection-permitting modeling and scale-aware parameterizations suggest promising venues for improving climate simulations of water cycle processes.

A review on regional convection-permitting climate modeling: Demonstrations, prospects, and challenges.

Science.gov (United States)

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 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.

Modeling of clouds and radiation for development of parameterizations for general circulation models

International Nuclear Information System (INIS)

Westphal, D.; Toon, B.; Jensen, E.; Kinne, S.; Ackerman, A.; Bergstrom, R.; Walker, A.

1994-01-01

Atmospheric Radiation Measurement (ARM) Program research at NASA Ames Research Center (ARC) includes radiative transfer modeling, cirrus cloud microphysics, and stratus cloud modeling. These efforts are designed to provide the basis for improving cloud and radiation parameterizations in our main effort: mesoscale cloud modeling. The range of non-convective cloud models used by the ARM modeling community can be crudely categorized based on the number of predicted hydrometers such as cloud water, ice water, rain, snow, graupel, etc. The simplest model has no predicted hydrometers and diagnoses the presence of clouds based on the predicted relative humidity. The vast majority of cloud models have two or more predictive bulk hydrometers and are termed either bulk water (BW) or size-resolving (SR) schemes. This study compares the various cloud models within the same dynamical framework, and compares results with observations rather than climate statistics

Alternative Parameterization of the 3-PG Model for Loblolly Pine: A Regional Validation and Climate Change Assessment on Stand Productivity

Science.gov (United States)

Yang, J.; Gonzalez-Benecke, C. A.; Teskey, R. O.; Martin, T.; Jokela, E. J.

2015-12-01

Loblolly pine (Pinus taeda L.) is one of the fastest growing pine species. It has been planted on more than 10 million ha in the southeastern U.S., and also been introduced into many countries. Using data from the literature and long-term productivity studies, we re-parameterized the 3-PG model for loblolly pine stands. We developed new functions for estimating NPP allocation dynamics, canopy cover and needlefall dynamics, effects of frost on production, density-independent and density-dependent tree mortality, biomass pools at variable starting ages, and the fertility rating. New functions to estimate merchantable volume partitioning were also included, allowing for economic analyses. The fertility rating was determined as a function of site index (mean height of dominant trees at age=25 years). We used the largest and most geographically extensive validation dataset for this species ever used (91 pots in 12 states in U.S. and 10 plots in Uruguay). Comparison of modeled to measured data showed robust agreement across the natural range in the U.S., as well as in Uruguay, where the species is grown as an exotic. Using the new set of functions and parameters with downscaled projections from twenty different climate models, the model was applied to assess the impact of future climate change scenarios on stand productivity in the southeastern U.S.

Automatic Generation of Symbolic Model for Parameterized Synchronous Systems

Institute of Scientific and Technical Information of China (English)

Wei-Wen Xu

2004-01-01

With the purpose of making the verification of parameterized system more general and easier, in this paper, a new and intuitive language PSL (Parameterized-system Specification Language) is proposed to specify a class of parameterized synchronous systems. From a PSL script, an automatic method is proposed to generate a constraint-based symbolic model. The model can concisely symbolically represent the collections of global states by counting the number of processes in a given state. Moreover, a theorem has been proved that there is a simulation relation between the original system and its symbolic model. Since the abstract and symbolic techniques are exploited in the symbolic model, state-explosion problem in traditional verification methods is efficiently avoided. Based on the proposed symbolic model, a reachability analysis procedure is implemented using ANSI C++ on UNIX platform. Thus, a complete tool for verifying the parameterized synchronous systems is obtained and tested for some cases. The experimental results show that the method is satisfactory.

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

Science.gov (United States)

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 Coordinated Effort to Improve Parameterization of High-Latitude Cloud and Radiation Processes

International Nuclear Information System (INIS)

J. O. Pinto; A.H. Lynch

2004-01-01

The goal of this project is the development and evaluation of improved parameterization of arctic cloud and radiation processes and implementation of the parameterizations into a climate model. Our research focuses specifically on the following issues: (1) continued development and evaluation of cloud microphysical parameterizations, focusing on issues of particular relevance for mixed phase clouds; and (2) evaluation of the mesoscale simulation of arctic cloud system life cycles

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

Science.gov (United States)

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.

An analysis of MM5 sensitivity to different parameterizations for high-resolution climate simulations

Science.gov (United States)

Argüeso, D.; Hidalgo-Muñoz, J. M.; Gámiz-Fortis, S. R.; Esteban-Parra, M. J.; Castro-Díez, Y.

2009-04-01

An evaluation of MM5 mesoscale model sensitivity to different parameterizations schemes is presented in terms of temperature and precipitation for high-resolution integrations over Andalusia (South of Spain). As initial and boundary conditions ERA-40 Reanalysis data are used. Two domains were used, a coarse one with dimensions of 55 by 60 grid points with spacing of 30 km and a nested domain of 48 by 72 grid points grid spaced 10 km. Coarse domain fully covers Iberian Peninsula and Andalusia fits loosely in the finer one. In addition to parameterization tests, two dynamical downscaling techniques have been applied in order to examine the influence of initial conditions on RCM long-term studies. Regional climate studies usually employ continuous integration for the period under survey, initializing atmospheric fields only at the starting point and feeding boundary conditions regularly. An alternative approach is based on frequent re-initialization of atmospheric fields; hence the simulation is divided in several independent integrations. Altogether, 20 simulations have been performed using varying physics options, of which 4 were fulfilled applying the re-initialization technique. Surface temperature and accumulated precipitation (daily and monthly scale) were analyzed for a 5-year period covering from 1990 to 1994. Results have been compared with daily observational data series from 110 stations for temperature and 95 for precipitation Both daily and monthly average temperatures are generally well represented by the model. Conversely, daily precipitation results present larger deviations from observational data. However, noticeable accuracy is gained when comparing with monthly precipitation observations. There are some especially conflictive subregions where precipitation is scarcely captured, such as the Southeast of the Iberian Peninsula, mainly due to its extremely convective nature. Regarding parameterization schemes performance, every set provides very

Parameterization of the ACRU model for estimating biophysical and climatological change impacts, Beaver Creek, Alberta

Science.gov (United States)

Forbes, K. A.; Kienzle, S. W.; Coburn, C. A.; Byrne, J. M.

2006-12-01

Multiple threats, including intensification of agricultural production, non-renewable resource extraction and climate change, are threatening Southern Alberta's water supply. The objective of this research is to calibrate/evaluate the Agricultural Catchments Research Unit (ACRU) agrohydrological model; with the end goal of forecasting the impacts of a changing environment on water quantity. The strength of this model is the intensive multi-layered soil water budgeting routine that integrates water movement between the surface and atmosphere. The ACRU model was parameterized using data from Environment Canada's climate database for a twenty year period (1984-2004) and was used to simulate streamflow for Beaver Creek. The simulated streamflow was compared to Environment Canada's historical streamflow database to validate the model output. The Beaver Creek Watershed, located in the Porcupine Hills southwestern Alberta, Canada contains a heterogeneous cover of deciduous, coniferous, native prairie grasslands and forage crops. In a catchment with highly diversified land cover, canopy architecture cannot be overlooked in rainfall interception parameterization. Preliminary testing of ACRU suggests that streamflows were sensitive to varied levels of leaf area index (LAI), a representative fraction of canopy foliage. Further testing using remotely sensed LAI's will provide a more accurate representation of canopy foliage and ultimately best represent this important element of the hydrological cycle and the associated processes which govern the natural hydrology of the Beaver Creek watershed.

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

Directory of Open Access Journals (Sweden)

G. B. Bonan

2018-04-01

Full Text Available 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.

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

Science.gov (United States)

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.

Impact of model structure and parameterization on Penman-Monteith type evaporation models

KAUST Repository

Ershadi, A.

2015-04-12

The impact of model structure and parameterization on the estimation of evaporation is investigated across a range of Penman-Monteith type models. To examine the role of model structure on flux retrievals, three different retrieval schemes are compared. The schemes include a traditional single-source Penman-Monteith model (Monteith, 1965), a two-layer model based on Shuttleworth and Wallace (1985) and a three-source model based on Mu et al. (2011). To assess the impact of parameterization choice on model performance, a number of commonly used formulations for aerodynamic and surface resistances were substituted into the different formulations. Model response to these changes was evaluated against data from twenty globally distributed FLUXNET towers, representing a cross-section of biomes that include grassland, cropland, shrubland, evergreen needleleaf forest and deciduous broadleaf forest. Scenarios based on 14 different combinations of model structure and parameterization were ranked based on their mean value of Nash-Sutcliffe Efficiency. Results illustrated considerable variability in model performance both within and between biome types. Indeed, no single model consistently outperformed any other when considered across all biomes. For instance, in grassland and shrubland sites, the single-source Penman-Monteith model performed the best. In croplands it was the three-source Mu model, while for evergreen needleleaf and deciduous broadleaf forests, the Shuttleworth-Wallace model rated highest. Interestingly, these top ranked scenarios all shared the simple lookup-table based surface resistance parameterization of Mu et al. (2011), while a more complex Jarvis multiplicative method for surface resistance produced lower ranked simulations. The highly ranked scenarios mostly employed a version of the Thom (1975) formulation for aerodynamic resistance that incorporated dynamic values of roughness parameters. This was true for all cases except over deciduous broadleaf

Modelling and parameterizing the influence of tides on ice-shelf melt rates

Science.gov (United States)

Jourdain, N.; Molines, J. M.; Le Sommer, J.; Mathiot, P.; de Lavergne, C.; Gurvan, M.; Durand, G.

2017-12-01

Significant Antarctic ice sheet thinning is observed in several sectors of Antarctica, in particular in the Amundsen Sea sector, where warm circumpolar deep waters affect basal melting. The later has the potential to trigger marine ice sheet instabilities, with an associated potential for rapid sea level rise. It is therefore crucial to simulate and understand the processes associated with ice-shelf melt rates. In particular, the absence of tides representation in ocean models remains a caveat of numerous ocean hindcasts and climate projections. In the Amundsen Sea, tides are relatively weak and the melt-induced circulation is stronger than the tidal circulation. Using a regional 1/12° ocean model of the Amundsen Sea, we nonetheless find that tides can increase melt rates by up to 36% in some ice-shelf cavities. Among the processes that can possibly affect melt rates, the most important is an increased exchange at the ice/ocean interface resulting from the presence of strong tidal currents along the ice drafts. Approximately a third of this effect is compensated by a decrease in thermal forcing along the ice draft, which is related to an enhanced vertical mixing in the ocean interior in presence of tides. Parameterizing the effect of tides is an alternative to the representation of explicit tides in an ocean model, and has the advantage not to require any filtering of ocean model outputs. We therefore explore different ways to parameterize the effects of tides on ice shelf melt. First, we compare several methods to impose tidal velocities along the ice draft. We show that getting a realistic spatial distribution of tidal velocities in important, and can be deduced from the barotropic velocities of a tide model. Then, we explore several aspects of parameterized tidal mixing to reproduce the tide-induced decrease in thermal forcing along the ice drafts.

Impact of climate seasonality on catchment yield: A parameterization for commonly-used water balance formulas

Science.gov (United States)

de Lavenne, Alban; Andréassian, Vazken

2018-03-01

This paper examines the hydrological impact of the seasonality of precipitation and maximum evaporation: seasonality is, after aridity, a second-order determinant of catchment water yield. Based on a data set of 171 French catchments (where aridity ranged between 0.2 and 1.2), we present a parameterization of three commonly-used water balance formulas (namely, Turc-Mezentsev, Tixeront-Fu and Oldekop formulas) to account for seasonality effects. We quantify the improvement of seasonality-based parameterization in terms of the reconstitution of both catchment streamflow and water yield. The significant improvement obtained (reduction of RMSE between 9 and 14% depending on the formula) demonstrates the importance of climate seasonality in the determination of long-term catchment water balance.

Effective single scattering albedo estimation using regional climate model

CSIR Research Space (South Africa)

Tesfaye, M

2011-09-01

Full Text Available In this study, by modifying the optical parameterization of Regional Climate model (RegCM), the authors have computed and compared the Effective Single-Scattering Albedo (ESSA) which is a representative of VIS spectral region. The arid, semi...

Cumulus parameterizations in chemical transport models

Science.gov (United States)

Mahowald, Natalie M.; Rasch, Philip J.; Prinn, Ronald G.

1995-12-01

Global three-dimensional chemical transport models (CTMs) are valuable tools for studying processes controlling the distribution of trace constituents in the atmosphere. A major uncertainty in these models is the subgrid-scale parametrization of transport by cumulus convection. This study seeks to define the range of behavior of moist convective schemes and point toward more reliable formulations for inclusion in chemical transport models. The emphasis is on deriving convective transport from meteorological data sets (such as those from the forecast centers) which do not routinely include convective mass fluxes. Seven moist convective parameterizations are compared in a column model to examine the sensitivity of the vertical profile of trace gases to the parameterization used in a global chemical transport model. The moist convective schemes examined are the Emanuel scheme [Emanuel, 1991], the Feichter-Crutzen scheme [Feichter and Crutzen, 1990], the inverse thermodynamic scheme (described in this paper), two versions of a scheme suggested by Hack [Hack, 1994], and two versions of a scheme suggested by Tiedtke (one following the formulation used in the ECMWF (European Centre for Medium-Range Weather Forecasting) and ECHAM3 (European Centre and Hamburg Max-Planck-Institut) models [Tiedtke, 1989], and one formulated as in the TM2 (Transport Model-2) model (M. Heimann, personal communication, 1992). These convective schemes vary in the closure used to derive the mass fluxes, as well as the cloud model formulation, giving a broad range of results. In addition, two boundary layer schemes are compared: a state-of-the-art nonlocal boundary layer scheme [Holtslag and Boville, 1993] and a simple adiabatic mixing scheme described in this paper. Three tests are used to compare the moist convective schemes against observations. Although the tests conducted here cannot conclusively show that one parameterization is better than the others, the tests are a good measure of the

Parameterization Improvements and Functional and Structural Advances in Version 4 of the Community Land Model

Directory of Open Access Journals (Sweden)

Andrew G. Slater

2011-05-01

Full Text Available The Community Land Model is the land component of the Community Climate System Model. Here, we describe a broad set of model improvements and additions that have been provided through the CLM development community to create CLM4. The model is extended with a carbon-nitrogen (CN biogeochemical model that is prognostic with respect to vegetation, litter, and soil carbon and nitrogen states and vegetation phenology. An urban canyon model is added and a transient land cover and land use change (LCLUC capability, including wood harvest, is introduced, enabling study of historic and future LCLUC on energy, water, momentum, carbon, and nitrogen fluxes. The hydrology scheme is modified with a revised numerical solution of the Richards equation and a revised ground evaporation parameterization that accounts for litter and within-canopy stability. The new snow model incorporates the SNow and Ice Aerosol Radiation model (SNICAR - which includes aerosol deposition, grain-size dependent snow aging, and vertically-resolved snowpack heating –– as well as new snow cover and snow burial fraction parameterizations. The thermal and hydrologic properties of organic soil are accounted for and the ground column is extended to ~50-m depth. Several other minor modifications to the land surface types dataset, grass and crop optical properties, atmospheric forcing height, roughness length and displacement height, and the disposition of snow-capped runoff are also incorporated.Taken together, these augmentations to CLM result in improved soil moisture dynamics, drier soils, and stronger soil moisture variability. The new model also exhibits higher snow cover, cooler soil temperatures in organic-rich soils, greater global river discharge, and lower albedos over forests and grasslands, all of which are improvements compared to CLM3.5. When CLM4 is run with CN, the mean biogeophysical simulation is slightly degraded because the vegetation structure is prognostic rather

Natural and anthropogenic climate change

International Nuclear Information System (INIS)

Ko, M.K.W.; Clough, S.A.; Molnar, G.I.; Iacono, M.; Wang, W.C.; State Univ. of New York, Albany, NY

1992-03-01

This report consists of two parts: (1) progress for the period 9/1/91--3/31/92 and (2) the plan for the remaining period 4/1/92--8/31/92. The project includes two tasks: atmospheric radiation and improvement of climate models to evaluate the climatic effects of radiation changes. The atmospheric radiation task includes four subtasks: (1) Intercomparison of Radiation Codes in Climate Models (ICRCCM), (2) analysis of the water vapor continuum using line-by-line calculations to develop a parameterization for use in climate models, (3) parameterization of longwave radiation and (4) climate/radiation interactions of desert aerosols. Our effort in this period is focused on the first three subtasks. The improvement of climate models to evaluate the subtasks: (1) general circulation model study and (2) 2- D model development and application

Impact of model structure and parameterization on Penman-Monteith type evaporation models

KAUST Repository

Ershadi, A.; McCabe, Matthew; Evans, J.P.; Wood, E.F.

2015-01-01

Overall, the results illustrate the sensitivity of Penman-Monteith type models to model structure, parameterization choice and biome type. A particular challenge in flux estimation relates to developing robust and broadly applicable model formulations. With many choices available for use, providing guidance on the most appropriate scheme to employ is required to advance approaches for routine global scale flux estimates, undertake hydrometeorological assessments or develop hydrological forecasting tools, amongst many other applications. In such cases, a multi-model ensemble or biome-specific tiled evaporation product may be an appropriate solution, given the inherent variability in model and parameterization choice that is observed within single product estimates.

Examining Chaotic Convection with Super-Parameterization Ensembles

Science.gov (United States)

Jones, Todd R.

This study investigates a variety of features present in a new configuration of the Community Atmosphere Model (CAM) variant, SP-CAM 2.0. The new configuration (multiple-parameterization-CAM, MP-CAM) changes the manner in which the super-parameterization (SP) concept represents physical tendency feedbacks to the large-scale by using the mean of 10 independent two-dimensional cloud-permitting model (CPM) curtains in each global model column instead of the conventional single CPM curtain. The climates of the SP and MP configurations are examined to investigate any significant differences caused by the application of convective physical tendencies that are more deterministic in nature, paying particular attention to extreme precipitation events and large-scale weather systems, such as the Madden-Julian Oscillation (MJO). A number of small but significant changes in the mean state climate are uncovered, and it is found that the new formulation degrades MJO performance. Despite these deficiencies, the ensemble of possible realizations of convective states in the MP configuration allows for analysis of uncertainty in the small-scale solution, lending to examination of those weather regimes and physical mechanisms associated with strong, chaotic convection. Methods of quantifying precipitation predictability are explored, and use of the most reliable of these leads to the conclusion that poor precipitation predictability is most directly related to the proximity of the global climate model column state to atmospheric critical points. Secondarily, the predictability is tied to the availability of potential convective energy, the presence of mesoscale convective organization on the CPM grid, and the directive power of the large-scale.

Improvement in the Modeled Representation of North American Monsoon Precipitation Using a Modified Kain–Fritsch Convective Parameterization Scheme

KAUST Repository

Luong, Thang

2018-01-22

A commonly noted problem in the simulation of warm season convection in the North American monsoon region has been the inability of atmospheric models at the meso-β scales (10 s to 100 s of kilometers) to simulate organized convection, principally mesoscale convective systems. With the use of convective parameterization, high precipitation biases in model simulations are typically observed over the peaks of mountain ranges. To address this issue, the Kain–Fritsch (KF) cumulus parameterization scheme has been modified with new diagnostic equations to compute the updraft velocity, the convective available potential energy closure assumption, and the convective trigger function. The scheme has been adapted for use in the Weather Research and Forecasting (WRF). A numerical weather prediction-type simulation is conducted for the North American Monsoon Experiment Intensive Observing Period 2 and a regional climate simulation is performed, by dynamically downscaling. In both of these applications, there are notable improvements in the WRF model-simulated precipitation due to the better representation of organized, propagating convection. The use of the modified KF scheme for atmospheric model simulations may provide a more computationally economical alternative to improve the representation of organized convection, as compared to convective-permitting simulations at the kilometer scale or a super-parameterization approach.

Modelling pesticide leaching under climate change: parameter vs. climate input uncertainty

Directory of Open Access Journals (Sweden)

K. Steffens

2014-02-01

Full Text Available Assessing climate change impacts on pesticide leaching requires careful consideration of different sources of uncertainty. We investigated the uncertainty related to climate scenario input and its importance relative to parameter uncertainty of the pesticide leaching model. The pesticide fate model MACRO was calibrated against a comprehensive one-year field data set for a well-structured clay soil in south-western Sweden. We obtained an ensemble of 56 acceptable parameter sets that represented the parameter uncertainty. Nine different climate model projections of the regional climate model RCA3 were available as driven by different combinations of global climate models (GCM, greenhouse gas emission scenarios and initial states of the GCM. The future time series of weather data used to drive the MACRO model were generated by scaling a reference climate data set (1970–1999 for an important agricultural production area in south-western Sweden based on monthly change factors for 2070–2099. 30 yr simulations were performed for different combinations of pesticide properties and application seasons. Our analysis showed that both the magnitude and the direction of predicted change in pesticide leaching from present to future depended strongly on the particular climate scenario. The effect of parameter uncertainty was of major importance for simulating absolute pesticide losses, whereas the climate uncertainty was relatively more important for predictions of changes of pesticide losses from present to future. The climate uncertainty should be accounted for by applying an ensemble of different climate scenarios. The aggregated ensemble prediction based on both acceptable parameterizations and different climate scenarios has the potential to provide robust probabilistic estimates of future pesticide losses.

The Milankovitch theory and climate sensitivity. I - Equilibrium climate model solutions for the present surface conditions. II - Interaction between the Northern Hemisphere ice sheets and the climate system

Science.gov (United States)

Neeman, Binyamin U.; Ohring, George; Joseph, Joachim H.

1988-01-01

A seasonal climate model was developed to test the climate sensitivity and, in particular, the Milankovitch (1941) theory. Four climate model versions were implemented to investigate the range of uncertainty in the parameterizations of three basic feedback mechanisms: the ice albedo-temperature, the outgoing long-wave radiation-temperature, and the eddy transport-meridional temperature gradient. It was found that the differences between the simulation of the present climate by the four versions were generally small, especially for annually averaged results. The climate model was also used to study the effect of growing/shrinking of a continental ice sheet, bedrock sinking/uplifting, and sea level changes on the climate system, taking also into account the feedback effects on the climate of the building of the ice caps.

Climate effects of anthropogenic sulfate: Simulations from a coupled chemistry/climate model

International Nuclear Information System (INIS)

Chuang, C.C.; Penner, J.E.; Taylor, K.E.; Walton, J.J.

1993-09-01

In this paper, we use a more comprehensive approach by coupling a climate model with a 3-D global chemistry model to investigate the forcing by anthropogenic aerosol sulfate. The chemistry model treats the global-scale transport, transformation, and removal of SO 2 , DMS and H 2 SO 4 species in the atmosphere. The mass concentration of anthropogenic sulfate from fossil fuel combustion and biomass burning is calculated in the chemistry model and provided to the climate model where it affects the shortwave radiation. We also investigate the effect, with cloud nucleation parameterized in terms of local aerosol number, sulfate mass concentration and updraft velocity. Our simulations indicate that anthropogenic sulfate may result in important increases in reflected solar radiation, which would mask locally the radiative forcing from increased greenhouse gases. Uncertainties in these results will be discussed

Modelling and observing urban climate in the Netherlands

International Nuclear Information System (INIS)

Van Hove, B.; Steeneveld, G.J.; Heusinkveld, B.; Holtslag, B.; Jacobs, C.; Ter Maat, H.; Elbers, J.; Moors, E.

2011-06-01

The main aims of the present study are: (1) to evaluate the performance of two well-known mesoscale NWP (numerical weather prediction) models coupled to a UCM (Urban Canopy Models), and (2) to develop a proper measurement strategy for obtaining meteorological data that can be used in model evaluation studies. We choose the mesoscale models WRF (Weather Research and Forecasting Model) and RAMS (Regional Atmospheric Modeling System), respectively, because the partners in the present project have a large expertise with respect to these models. In addition WRF and RAMS have been successfully used in the meteorology and climate research communities for various purposes, including weather prediction and land-atmosphere interaction research. Recently, state-of-the-art UCM's were embedded within the land surface scheme of the respective models, in order to better represent the exchange of heat, momentum, and water vapour in the urban environment. Key questions addressed here are: What is the general model performance with respect to the urban environment?; How can useful and observational data be obtained that allow sensible validation and further parameterization of the models?; and Can the models be easily modified to simulate the urban climate under Dutch climatic conditions, urban configuration and morphology? Chapter 2 reviews the available Urban Canopy Models; we discuss their theoretical basis, the different representations of the urban environment, the required input and the output. Much of the information was obtained from the Urban Surface Energy Balance: Land Surface Scheme Comparison project (PILPS URBAN, PILPS stands for Project for Inter-comparison of Land-Surface Parameterization Schemes). This project started in March 2008 and was coordinated by the Department of Geography, King's College London. In order to test the performance of our models we participated in this project. Chapter 3 discusses the main results of the first phase of PILPS URBAN. A first

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

Science.gov (United States)

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

Air quality modeling: evaluation of chemical and meteorological parameterizations

International Nuclear Information System (INIS)

Kim, Youngseob

2011-01-01

The influence of chemical mechanisms and meteorological parameterizations on pollutant concentrations calculated with an air quality model is studied. The influence of the differences between two gas-phase chemical mechanisms on the formation of ozone and aerosols in Europe is low on average. For ozone, the large local differences are mainly due to the uncertainty associated with the kinetics of nitrogen monoxide (NO) oxidation reactions on the one hand and the representation of different pathways for the oxidation of aromatic compounds on the other hand. The aerosol concentrations are mainly influenced by the selection of all major precursors of secondary aerosols and the explicit treatment of chemical regimes corresponding to the nitrogen oxides (NO x ) levels. The influence of the meteorological parameterizations on the concentrations of aerosols and their vertical distribution is evaluated over the Paris region in France by comparison to lidar data. The influence of the parameterization of the dynamics in the atmospheric boundary layer is important; however, it is the use of an urban canopy model that improves significantly the modeling of the pollutant vertical distribution (author) [fr

Utilization of Short-Simulations for Tuning High-Resolution Climate Model

Science.gov (United States)

Lin, W.; Xie, S.; Ma, P. L.; Rasch, P. J.; Qian, Y.; Wan, H.; Ma, H. Y.; Klein, S. A.

2016-12-01

Many physical parameterizations in atmospheric models are sensitive to resolution. Tuning the models that involve a multitude of parameters at high resolution is computationally expensive, particularly when relying primarily on multi-year simulations. This work describes a complementary set of strategies for tuning high-resolution atmospheric models, using ensembles of short simulations to reduce the computational cost and elapsed time. Specifically, we utilize the hindcast approach developed through the DOE Cloud Associated Parameterization Testbed (CAPT) project for high-resolution model tuning, which is guided by a combination of short (tests have been found to be effective in numerous previous studies in identifying model biases due to parameterized fast physics, and we demonstrate that it is also useful for tuning. After the most egregious errors are addressed through an initial "rough" tuning phase, longer simulations are performed to "hone in" on model features that evolve over longer timescales. We explore these strategies to tune the DOE ACME (Accelerated Climate Modeling for Energy) model. For the ACME model at 0.25° resolution, it is confirmed that, given the same parameters, major biases in global mean statistics and many spatial features are consistent between Atmospheric Model Intercomparison Project (AMIP)-type simulations and CAPT-type hindcasts, with just a small number of short-term simulations for the latter over the corresponding season. The use of CAPT hindcasts to find parameter choice for the reduction of large model biases dramatically improves the turnaround time for the tuning at high resolution. Improvement seen in CAPT hindcasts generally translates to improved AMIP-type simulations. An iterative CAPT-AMIP tuning approach is therefore adopted during each major tuning cycle, with the former to survey the likely responses and narrow the parameter space, and the latter to verify the results in climate context along with assessment in

Factors influencing the parameterization of anvil clouds within general circulation models

International Nuclear Information System (INIS)

Leone, J.M. Jr.; Chin, H.N.

1994-01-01

The overall goal of this project is to improve the representation of clouds and their effects within global climate models (GCMs). We have concentrated on a small portion of the overall goal, the evolution of convectively generated cirrus clouds and their effects on the large-scale environment. Because of the large range of time and length scales involved, we have been using a multi-scale attack. For the early time generation and development of the cirrus anvil, we are using a cloud-scale model with horizontal resolution of 1 to 2 kilometers; for the larger scale transport by the larger scale flow, we are using a mesoscale model with a horizontal resolution of 20 to 60 kilometers. The eventual goal is to use the information obtained from these simulations, together with available observations, to derive improved cloud parameterizations for use in GCMs. This paper presents a new tool, a cirrus generator, that we have developed to aid in our mesoscale studies

Evaluation of five dry particle deposition parameterizations for incorporation into atmospheric transport models

Science.gov (United States)

Khan, Tanvir R.; Perlinger, Judith A.

2017-10-01

Despite considerable effort to develop mechanistic dry particle deposition parameterizations for atmospheric transport models, current knowledge has been inadequate to propose quantitative measures of the relative performance of available parameterizations. In this study, we evaluated the performance of five dry particle deposition parameterizations developed by Zhang et al. (2001) (Z01), Petroff and Zhang (2010) (PZ10), Kouznetsov and Sofiev (2012) (KS12), Zhang and He (2014) (ZH14), and Zhang and Shao (2014) (ZS14), respectively. The evaluation was performed in three dimensions: model ability to reproduce observed deposition velocities, Vd (accuracy); the influence of imprecision in input parameter values on the modeled Vd (uncertainty); and identification of the most influential parameter(s) (sensitivity). The accuracy of the modeled Vd was evaluated using observations obtained from five land use categories (LUCs): grass, coniferous and deciduous forests, natural water, and ice/snow. To ascertain the uncertainty in modeled Vd, and quantify the influence of imprecision in key model input parameters, a Monte Carlo uncertainty analysis was performed. The Sobol' sensitivity analysis was conducted with the objective to determine the parameter ranking from the most to the least influential. Comparing the normalized mean bias factors (indicators of accuracy), we find that the ZH14 parameterization is the most accurate for all LUCs except for coniferous forest, for which it is second most accurate. From Monte Carlo simulations, the estimated mean normalized uncertainties in the modeled Vd obtained for seven particle sizes (ranging from 0.005 to 2.5 µm) for the five LUCs are 17, 12, 13, 16, and 27 % for the Z01, PZ10, KS12, ZH14, and ZS14 parameterizations, respectively. From the Sobol' sensitivity results, we suggest that the parameter rankings vary by particle size and LUC for a given parameterization. Overall, for dp = 0.001 to 1.0 µm, friction velocity was one of

A review on regional convection permitting climate modeling

Science.gov (United States)

van Lipzig, Nicole; Prein, Andreas; Brisson, Erwan; Van Weverberg, Kwinten; Demuzere, Matthias; Saeed, Sajjad; Stengel, Martin

2016-04-01

With the increase of computational resources, it has recently become possible to perform climate model integrations where at least part the of convection is resolved. Since convection-permitting models (CPMs) are performing better than models where convection is parameterized, especially for high-impact weather like extreme precipitation, there is currently strong scientific progress in this research domain (Prein et al., 2015). Another advantage of CPMs, that have a horizontal grid spacing climate model COSMO-CLM is frequently applied for CPM simulations, due to its non-hydrostatic dynamics and open international network of scientists. This presentation consists of an overview of the recent progress in CPM, with a focus on COSMO-CLM. It consists of three parts, namely the discussion of i) critical components of CPM, ii) the added value of CPM in the present-day climate and iii) the difference in climate sensitivity in CPM compared to coarser scale models. In terms of added value, the CPMs especially improve the representation of precipitation's, diurnal cycle, intensity and spatial distribution. However, an in depth-evaluation of cloud properties with CCLM over Belgium indicates a strong underestimation of the cloud fraction, causing an overestimation of high temperature extremes (Brisson et al., 2016). In terms of climate sensitivity, the CPMs indicate a stronger increase in flash floods, changes in hail storm characteristics, and reductions in the snowpack over mountains compared to coarser scale models. In conclusion, CPMs are a very promising tool for future climate research. However, additional efforts are necessary to overcome remaining deficiencies, like improving the cloud characteristics. This will be a challenging task due to compensating deficiencies that currently exist in `state-of-the-art' models, yielding a good representation of average climate conditions. In the light of using CPMs to study climate change it is necessary that these deficiencies

A Comparison Between Gravity Wave Momentum Fluxes in Observations and Climate Models

Science.gov (United States)

Geller, Marvin A.; Alexadner, M. Joan; Love, Peter T.; Bacmeister, Julio; Ern, Manfred; Hertzog, Albert; Manzini, Elisa; Preusse, Peter; Sato, Kaoru; Scaife, Adam A.;

Tool-driven Design and Automated Parameterization for Real-time Generic Drivetrain Models

Directory of Open Access Journals (Sweden)

Schwarz Christina

2015-01-01

Full Text Available Real-time dynamic drivetrain modeling approaches have a great potential for development cost reduction in the automotive industry. Even though real-time drivetrain models are available, these solutions are specific to single transmission topologies. In this paper an environment for parameterization of a solution is proposed based on a generic method applicable to all types of gear transmission topologies. This enables tool-guided modeling by non- experts in the fields of mechanic engineering and control theory leading to reduced development and testing efforts. The approach is demonstrated for an exemplary automatic transmission using the environment for automated parameterization. Finally, the parameterization is validated via vehicle measurement data.

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

Science.gov (United States)

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.

Evaluation of five dry particle deposition parameterizations for incorporation into atmospheric transport models

Directory of Open Access Journals (Sweden)

T. R. Khan

2017-10-01

Full Text Available Despite considerable effort to develop mechanistic dry particle deposition parameterizations for atmospheric transport models, current knowledge has been inadequate to propose quantitative measures of the relative performance of available parameterizations. In this study, we evaluated the performance of five dry particle deposition parameterizations developed by Zhang et al. (2001 (Z01, Petroff and Zhang (2010 (PZ10, Kouznetsov and Sofiev (2012 (KS12, Zhang and He (2014 (ZH14, and Zhang and Shao (2014 (ZS14, respectively. The evaluation was performed in three dimensions: model ability to reproduce observed deposition velocities, Vd (accuracy; the influence of imprecision in input parameter values on the modeled Vd (uncertainty; and identification of the most influential parameter(s (sensitivity. The accuracy of the modeled Vd was evaluated using observations obtained from five land use categories (LUCs: grass, coniferous and deciduous forests, natural water, and ice/snow. To ascertain the uncertainty in modeled Vd, and quantify the influence of imprecision in key model input parameters, a Monte Carlo uncertainty analysis was performed. The Sobol' sensitivity analysis was conducted with the objective to determine the parameter ranking from the most to the least influential. Comparing the normalized mean bias factors (indicators of accuracy, we find that the ZH14 parameterization is the most accurate for all LUCs except for coniferous forest, for which it is second most accurate. From Monte Carlo simulations, the estimated mean normalized uncertainties in the modeled Vd obtained for seven particle sizes (ranging from 0.005 to 2.5 µm for the five LUCs are 17, 12, 13, 16, and 27 % for the Z01, PZ10, KS12, ZH14, and ZS14 parameterizations, respectively. From the Sobol' sensitivity results, we suggest that the parameter rankings vary by particle size and LUC for a given parameterization. Overall, for dp  =  0.001 to 1.0�

A shallow convection parameterization for the non-hydrostatic MM5 mesoscale model

Energy Technology Data Exchange (ETDEWEB)

Seaman, N.L.; Kain, J.S.; Deng, A. [Pennsylvania State Univ., University Park, PA (United States)

1996-04-01

A shallow convection parameterization suitable for the Pennsylvannia State University (PSU)/National Center for Atmospheric Research nonhydrostatic mesoscale model (MM5) is being developed at PSU. The parameterization is based on parcel perturbation theory developed in conjunction with a 1-D Mellor Yamada 1.5-order planetary boundary layer scheme and the Kain-Fritsch deep convection model.

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

Science.gov (United States)

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.

Black carbon ageing in the Canadian Centre for Climate modelling and analysis atmospheric general circulation model

Directory of Open Access Journals (Sweden)

B. Croft

2005-01-01

Full Text Available Black carbon (BC particles in the atmosphere have important impacts on climate. The amount of BC in the atmosphere must be carefully quantified to allow evaluation of the climate effects of this type of aerosol. In this study, we present the treatment of BC aerosol in the developmental version of the 4th generation Canadian Centre for Climate modelling and analysis (CCCma atmospheric general circulation model (AGCM. The focus of this work is on the conversion of insoluble BC to soluble/mixed BC by physical and chemical ageing. Physical processes include the condensation of sulphuric and nitric acid onto the BC aerosol, and coagulation with more soluble aerosols such as sulphates and nitrates. Chemical processes that may age the BC aerosol include the oxidation of organic coatings by ozone. Four separate parameterizations of the ageing process are compared to a control simulation that assumes no ageing occurs. These simulations use 1 an exponential decay with a fixed 24h half-life, 2 a condensation and coagulation scheme, 3 an oxidative scheme, and 4 a linear combination of the latter two ageing treatments. Global BC burdens are 2.15, 0.15, 0.11, 0.21, and 0.11TgC for the control run, and four ageing schemes, respectively. The BC lifetimes are 98.1, 6.6, 5.0, 9.5, and 4.9 days, respectively. The sensitivity of modelled BC burdens, and concentrations to the factor of two uncertainty in the emissions inventory is shown to be greater than the sensitivity to the parameterization used to represent the BC ageing, except for the oxidation based parameterization. A computationally efficient parameterization that represents the processes of condensation, coagulation, and oxidation is shown to simulate BC ageing well in the CCCma AGCM. As opposed to the globally fixed ageing time scale, this treatment of BC ageing is responsive to varying atmospheric composition.

Developing a stochastic parameterization to incorporate plant trait variability into ecohydrologic modeling

Science.gov (United States)

Liu, S.; Ng, G. H. C.

2017-12-01

The global plant database has revealed that plant traits can vary more within a plant functional type (PFT) than among different PFTs, indicating that the current paradigm in ecohydrogical models of specifying fixed parameters based solely on plant functional type (PFT) could potentially bias simulations. Although some recent modeling studies have attempted to incorporate this observed plant trait variability, many failed to consider uncertainties due to sparse global observation, or they omitted spatial and/or temporal variability in the traits. Here we present a stochastic parameterization for prognostic vegetation simulations that are stochastic in time and space in order to represent plant trait plasticity - the process by which trait differences arise. We have developed the new PFT parameterization within the Community Land Model 4.5 (CLM 4.5) and tested the method for a desert shrubland watershed in the Mojave Desert, where fixed parameterizations cannot represent acclimation to desert conditions. Spatiotemporally correlated plant trait parameters were first generated based on TRY statistics and were then used to implement ensemble runs for the study area. The new PFT parameterization was then further conditioned on field measurements of soil moisture and remotely sensed observations of leaf-area-index to constrain uncertainties in the sparse global database. Our preliminary results show that incorporating data-conditioned, variable PFT parameterizations strongly affects simulated soil moisture and water fluxes, compared with default simulations. The results also provide new insights about correlations among plant trait parameters and between traits and environmental conditions in the desert shrubland watershed. Our proposed stochastic PFT parameterization method for ecohydrological models has great potential in advancing our understanding of how terrestrial ecosystems are predicted to adapt to variable environmental conditions.

Flexible climate modeling systems: Lessons from Snowball Earth, Titan and Mars

Science.gov (United States)

Pierrehumbert, R. T.

2007-12-01

Climate models are only useful to the extent that real understanding can be extracted from them. Most leading- edge problems in climate change, paleoclimate and planetary climate require a high degree of flexibility in terms of incorporating model physics -- for example in allowing methane or CO2 to be a condensible substance instead of water vapor. This puts a premium on model design that allows easy modification, and on physical parameterizations that are close to fundamentals with as little empirical ad-hoc formulation as possible. I will provide examples from two approaches to this problem we have been using at the University of Chicago. The first is the FOAM general circulation model, which is a clean single-executable Fortran-77/c code supported by auxiliary applications in Python and Java. The second is a new approach based on using Python as a shell for assembling building blocks in compiled-code into full models. Applications to Snowball Earth, Titan and Mars, as well as pedagogical uses, will be discussed. One painful lesson we have learned is that Fortran-95 is a major impediment to portability and cross-language interoperability; in this light the trend toward Fortran-95 in major modelling groups is seen as a significant step backwards. In this talk, I will focus on modeling projects employing a full representation of atmospheric fluid dynamics, rather than "intermediate complexity" models in which the associated transports are parameterized.

Analyses of the stratospheric dynamics simulated by a GCM with a stochastic nonorographic gravity wave parameterization

Science.gov (United States)

Serva, Federico; Cagnazzo, Chiara; Riccio, Angelo

2016-04-01

The effects of the propagation and breaking of atmospheric gravity waves have long been considered crucial for their impact on the circulation, especially in the stratosphere and mesosphere, between heights of 10 and 110 km. These waves, that in the Earth's atmosphere originate from surface orography (OGWs) or from transient (nonorographic) phenomena such as fronts and convective processes (NOGWs), have horizontal wavelengths between 10 and 1000 km, vertical wavelengths of several km, and frequencies spanning from minutes to hours. Orographic and nonorographic GWs must be accounted for in climate models to obtain a realistic simulation of the stratosphere in both hemispheres, since they can have a substantial impact on circulation and temperature, hence an important role in ozone chemistry for chemistry-climate models. Several types of parameterization are currently employed in models, differing in the formulation and for the values assigned to parameters, but the common aim is to quantify the effect of wave breaking on large-scale wind and temperature patterns. In the last decade, both global observations from satellite-borne instruments and the outputs of very high resolution climate models provided insight on the variability and properties of gravity wave field, and these results can be used to constrain some of the empirical parameters present in most parameterization scheme. A feature of the NOGW forcing that clearly emerges is the intermittency, linked with the nature of the sources: this property is absent in the majority of the models, in which NOGW parameterizations are uncoupled with other atmospheric phenomena, leading to results which display lower variability compared to observations. In this work, we analyze the climate simulated in AMIP runs of the MAECHAM5 model, which uses the Hines NOGW parameterization and with a fine vertical resolution suitable to capture the effects of wave-mean flow interaction. We compare the results obtained with two

Assessment of two physical parameterization schemes for desert dust emissions in an atmospheric chemistry general circulation model

Science.gov (United States)

Astitha, M.; Abdel Kader, M.; Pozzer, A.; Lelieveld, J.

2012-04-01

Atmospheric particulate matter and more specific desert dust has been the topic of numerous research studies in the past due to the wide range of impacts in the environment and climate and the uncertainty of characterizing and quantifying these impacts in a global scale. In this work we present two physical parameterizations of the desert dust production that have been incorporated in the atmospheric chemistry general circulation model EMAC (ECHAM5/MESSy2.41 Atmospheric Chemistry). The scope of this work is to assess the impact of the two physical parameterizations in the global distribution of desert dust and highlight the advantages and disadvantages of using either technique. The dust concentration and deposition has been evaluated using the AEROCOM dust dataset for the year 2000 and data from the MODIS and MISR satellites as well as sun-photometer data from the AERONET network was used to compare the modelled aerosol optical depth with observations. The implementation of the two parameterizations and the simulations using relatively high spatial resolution (T106~1.1deg) has highlighted the large spatial heterogeneity of the dust emission sources as well as the importance of the input parameters (soil size and texture, vegetation, surface wind speed). Also, sensitivity simulations with the nudging option using reanalysis data from ECMWF and without nudging have showed remarkable differences for some areas. Both parameterizations have revealed the difficulty of simulating all arid regions with the same assumptions and mechanisms. Depending on the arid region, each emission scheme performs more or less satisfactorily which leads to the necessity of treating each desert differently. Even though this is a quite different task to accomplish in a global model, some recommendations are given and ideas for future improvements.

A stochastic parameterization for deep convection using cellular automata

Science.gov (United States)

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

A parameterization of cloud droplet nucleation

International Nuclear Information System (INIS)

Ghan, S.J.; Chuang, C.; Penner, J.E.

1993-01-01

Droplet nucleation is a fundamental cloud process. The number of aerosols activated to form cloud droplets influences not only the number of aerosols scavenged by clouds but also the size of the cloud droplets. Cloud droplet size influences the cloud albedo and the conversion of cloud water to precipitation. Global aerosol models are presently being developed with the intention of coupling with global atmospheric circulation models to evaluate the influence of aerosols and aerosol-cloud interactions on climate. If these and other coupled models are to address issues of aerosol-cloud interactions, the droplet nucleation process must be adequately represented. Here we introduce a droplet nucleation parametrization that offers certain advantages over the popular Twomey (1959) parameterization

On the Correspondence between Mean Forecast Errors and Climate Errors in CMIP5 Models

Energy Technology Data Exchange (ETDEWEB)

Ma, H. -Y.; Xie, S.; Klein, S. A.; Williams, K. D.; Boyle, J. S.; Bony, S.; Douville, H.; Fermepin, S.; Medeiros, B.; Tyteca, S.; Watanabe, M.; Williamson, D.

2014-02-01

The present study examines the correspondence between short- and long-term systematic errors in five atmospheric models by comparing the 16 five-day hindcast ensembles from the Transpose Atmospheric Model Intercomparison Project II (Transpose-AMIP II) for July–August 2009 (short term) to the climate simulations from phase 5 of the Coupled Model Intercomparison Project (CMIP5) and AMIP for the June–August mean conditions of the years of 1979–2008 (long term). Because the short-term hindcasts were conducted with identical climate models used in the CMIP5/AMIP simulations, one can diagnose over what time scale systematic errors in these climate simulations develop, thus yielding insights into their origin through a seamless modeling approach. The analysis suggests that most systematic errors of precipitation, clouds, and radiation processes in the long-term climate runs are present by day 5 in ensemble average hindcasts in all models. Errors typically saturate after few days of hindcasts with amplitudes comparable to the climate errors, and the impacts of initial conditions on the simulated ensemble mean errors are relatively small. This robust bias correspondence suggests that these systematic errors across different models likely are initiated by model parameterizations since the atmospheric large-scale states remain close to observations in the first 2–3 days. However, biases associated with model physics can have impacts on the large-scale states by day 5, such as zonal winds, 2-m temperature, and sea level pressure, and the analysis further indicates a good correspondence between short- and long-term biases for these large-scale states. Therefore, improving individual model parameterizations in the hindcast mode could lead to the improvement of most climate models in simulating their climate mean state and potentially their future projections.

Low Cloud Feedback to Surface Warming in the World's First Global Climate Model with Explicit Embedded Boundary Layer Turbulence

Science.gov (United States)

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.

Parameterization of a Hydrological Model for a Large, Ungauged Urban Catchment

Directory of Open Access Journals (Sweden)

Gerald Krebs

2016-10-01

Full Text Available Urbanization leads to the replacement of natural areas by impervious surfaces and affects the catchment hydrological cycle with adverse environmental impacts. Low impact development tools (LID that mimic hydrological processes of natural areas have been developed and applied to mitigate these impacts. Hydrological simulations are one possibility to evaluate the LID performance but the associated small-scale processes require a highly spatially distributed and explicit modeling approach. However, detailed data for model development are often not available for large urban areas, hampering the model parameterization. In this paper we propose a methodology to parameterize a hydrological model to a large, ungauged urban area by maintaining at the same time a detailed surface discretization for direct parameter manipulation for LID simulation and a firm reliance on available data for model conceptualization. Catchment delineation was based on a high-resolution digital elevation model (DEM and model parameterization relied on a novel model regionalization approach. The impact of automated delineation and model regionalization on simulation results was evaluated for three monitored study catchments (5.87–12.59 ha. The simulated runoff peak was most sensitive to accurate catchment discretization and calibration, while both the runoff volume and the fit of the hydrograph were less affected.

Impact of a simple parameterization of convective gravity-wave drag in a stratosphere-troposphere general circulation model and its sensitivity to vertical resolution

Directory of Open Access Journals (Sweden)

C. Bossuet

Full Text Available Systematic westerly biases in the southern hemisphere wintertime flow and easterly equatorial biases are experienced in the Météo-France climate model. These biases are found to be much reduced when a simple parameterization is introduced to take into account the vertical momentum transfer through the gravity waves excited by deep convection. These waves are quasi-stationary in the frame of reference moving with convection and they propagate vertically to higher levels in the atmosphere, where they may exert a significant deceleration of the mean flow at levels where dissipation occurs. Sixty-day experiments have been performed from a multiyear simulation with the standard 31 levels for a summer and a winter month, and with a T42 horizontal resolution. The impact of this parameterization on the integration of the model is found to be generally positive, with a significant deceleration in the westerly stratospheric jet and with a reduction of the easterly equatorial bias. The sensitivity of the Météo-France climate model to vertical resolution is also investigated by increasing the number of vertical levels, without moving the top of the model. The vertical resolution is increased up to 41 levels, using two kinds of level distribution. For the first, the increase in vertical resolution concerns especially the troposphere (with 22 levels in the troposphere, and the second treats the whole atmosphere in a homogeneous way (with 15 levels in the troposphere; the standard version of 31 levels has 10 levels in the troposphere. A comparison is made between the dynamical aspects of the simulations. The zonal wind and precipitation are presented and compared for each resolution. A positive impact is found with the finer tropospheric resolution on the precipitation in the mid-latitudes and on the westerly stratospheric jet, but the general impact on the model climate is weak, the physical parameterizations used appear to be mostly independent to the

Statistical dynamical subgrid-scale parameterizations for geophysical flows

International Nuclear Information System (INIS)

O'Kane, T J; Frederiksen, J S

2008-01-01

Simulations of both atmospheric and oceanic circulations at given finite resolutions are strongly dependent on the form and strengths of the dynamical subgrid-scale parameterizations (SSPs) and in particular are sensitive to subgrid-scale transient eddies interacting with the retained scale topography and the mean flow. In this paper, we present numerical results for SSPs of the eddy-topographic force, stochastic backscatter, eddy viscosity and eddy-mean field interaction using an inhomogeneous statistical turbulence model based on a quasi-diagonal direct interaction approximation (QDIA). Although the theoretical description on which our model is based is for general barotropic flows, we specifically focus on global atmospheric flows where large-scale Rossby waves are present. We compare and contrast the closure-based results with an important earlier heuristic SSP of the eddy-topographic force, based on maximum entropy or statistical canonical equilibrium arguments, developed specifically for general ocean circulation models (Holloway 1992 J. Phys. Oceanogr. 22 1033-46). Our results demonstrate that where strong zonal flows and Rossby waves are present, such as in the atmosphere, maximum entropy arguments are insufficient to accurately parameterize the subgrid contributions due to eddy-eddy, eddy-topographic and eddy-mean field interactions. We contrast our atmospheric results with findings for the oceans. Our study identifies subgrid-scale interactions that are currently not parameterized in numerical atmospheric climate models, which may lead to systematic defects in the simulated circulations.

The Explicit-Cloud Parameterized-Pollutant hybrid approach for aerosol-cloud interactions in multiscale modeling framework models: tracer transport results

International Nuclear Information System (INIS)

Jr, William I Gustafson; Berg, Larry K; Easter, Richard C; Ghan, Steven J

2008-01-01

All estimates of aerosol indirect effects on the global energy balance have either completely neglected the influence of aerosol on convective clouds or treated the influence in a highly parameterized manner. Embedding cloud-resolving models (CRMs) within each grid cell of a global model provides a multiscale modeling framework for treating both the influence of aerosols on convective as well as stratiform clouds and the influence of clouds on the aerosol, but treating the interactions explicitly by simulating all aerosol processes in the CRM is computationally prohibitive. An alternate approach is to use horizontal statistics (e.g., cloud mass flux, cloud fraction, and precipitation) from the CRM simulation to drive a single-column parameterization of cloud effects on the aerosol and then use the aerosol profile to simulate aerosol effects on clouds within the CRM. Here, we present results from the first component of the Explicit-Cloud Parameterized-Pollutant parameterization to be developed, which handles vertical transport of tracers by clouds. A CRM with explicit tracer transport serves as a benchmark. We show that this parameterization, driven by the CRM's cloud mass fluxes, reproduces the CRM tracer transport significantly better than a single-column model that uses a conventional convective cloud parameterization

The Explicit-Cloud Parameterized-Pollutant hybrid approach for aerosol-cloud interactions in multiscale modeling framework models: tracer transport results

Energy Technology Data Exchange (ETDEWEB)

Jr, William I Gustafson; Berg, Larry K; Easter, Richard C; Ghan, Steven J [Atmospheric Science and Global Change Division, Pacific Northwest National Laboratory, PO Box 999, MSIN K9-30, Richland, WA (United States)], E-mail: William.Gustafson@pnl.gov

2008-04-15

All estimates of aerosol indirect effects on the global energy balance have either completely neglected the influence of aerosol on convective clouds or treated the influence in a highly parameterized manner. Embedding cloud-resolving models (CRMs) within each grid cell of a global model provides a multiscale modeling framework for treating both the influence of aerosols on convective as well as stratiform clouds and the influence of clouds on the aerosol, but treating the interactions explicitly by simulating all aerosol processes in the CRM is computationally prohibitive. An alternate approach is to use horizontal statistics (e.g., cloud mass flux, cloud fraction, and precipitation) from the CRM simulation to drive a single-column parameterization of cloud effects on the aerosol and then use the aerosol profile to simulate aerosol effects on clouds within the CRM. Here, we present results from the first component of the Explicit-Cloud Parameterized-Pollutant parameterization to be developed, which handles vertical transport of tracers by clouds. A CRM with explicit tracer transport serves as a benchmark. We show that this parameterization, driven by the CRM's cloud mass fluxes, reproduces the CRM tracer transport significantly better than a single-column model that uses a conventional convective cloud parameterization.

Parameterization of dust emissions in the global atmospheric chemistry-climate model EMAC: impact of nudging and soil properties

Science.gov (United States)

Astitha, M.; Lelieveld, J.; Abdel Kader, M.; Pozzer, A.; de Meij, A.

2012-11-01

Airborne desert dust influences radiative transfer, atmospheric chemistry and dynamics, as well as nutrient transport and deposition. It directly and indirectly affects climate on regional and global scales. Two versions of a parameterization scheme to compute desert dust emissions are incorporated into the atmospheric chemistry general circulation model EMAC (ECHAM5/MESSy2.41 Atmospheric Chemistry). One uses a globally uniform soil particle size distribution, whereas the other explicitly accounts for different soil textures worldwide. We have tested these two versions and investigated the sensitivity to input parameters, using remote sensing data from the Aerosol Robotic Network (AERONET) and dust concentrations and deposition measurements from the AeroCom dust benchmark database (and others). The two versions are shown to produce similar atmospheric dust loads in the N-African region, while they deviate in the Asian, Middle Eastern and S-American regions. The dust outflow from Africa over the Atlantic Ocean is accurately simulated by both schemes, in magnitude, location and seasonality. Approximately 70% of the modelled annual deposition data and 70-75% of the modelled monthly aerosol optical depth (AOD) in the Atlantic Ocean stations lay in the range 0.5 to 2 times the observations for all simulations. The two versions have similar performance, even though the total annual source differs by ~50%, which underscores the importance of transport and deposition processes (being the same for both versions). Even though the explicit soil particle size distribution is considered more realistic, the simpler scheme appears to perform better in several locations. This paper discusses the differences between the two versions of the dust emission scheme, focusing on their limitations and strengths in describing the global dust cycle and suggests possible future improvements.

Parameterization of dust emissions in the global atmospheric chemistry-climate model EMAC: impact of nudging and soil properties

Directory of Open Access Journals (Sweden)

M. Astitha

2012-11-01

Full Text Available Airborne desert dust influences radiative transfer, atmospheric chemistry and dynamics, as well as nutrient transport and deposition. It directly and indirectly affects climate on regional and global scales. Two versions of a parameterization scheme to compute desert dust emissions are incorporated into the atmospheric chemistry general circulation model EMAC (ECHAM5/MESSy2.41 Atmospheric Chemistry. One uses a globally uniform soil particle size distribution, whereas the other explicitly accounts for different soil textures worldwide. We have tested these two versions and investigated the sensitivity to input parameters, using remote sensing data from the Aerosol Robotic Network (AERONET and dust concentrations and deposition measurements from the AeroCom dust benchmark database (and others. The two versions are shown to produce similar atmospheric dust loads in the N-African region, while they deviate in the Asian, Middle Eastern and S-American regions. The dust outflow from Africa over the Atlantic Ocean is accurately simulated by both schemes, in magnitude, location and seasonality. Approximately 70% of the modelled annual deposition data and 70–75% of the modelled monthly aerosol optical depth (AOD in the Atlantic Ocean stations lay in the range 0.5 to 2 times the observations for all simulations. The two versions have similar performance, even though the total annual source differs by ~50%, which underscores the importance of transport and deposition processes (being the same for both versions. Even though the explicit soil particle size distribution is considered more realistic, the simpler scheme appears to perform better in several locations. This paper discusses the differences between the two versions of the dust emission scheme, focusing on their limitations and strengths in describing the global dust cycle and suggests possible future improvements.

Collaborative Research: Towards Advanced Understanding and Predictive Capability of Climate Change in the Arctic Using a High-Resolution Regional Arctic Climate Model

Energy Technology Data Exchange (ETDEWEB)

Cassano, John [Principal Investigator

2013-06-30

The primary research task completed for this project was the development of the Regional Arctic Climate Model (RACM). This involved coupling existing atmosphere, ocean, sea ice, and land models using the National Center for Atmospheric Research (NCAR) Community Climate System Model (CCSM) coupler (CPL7). RACM is based on the Weather Research and Forecasting (WRF) atmospheric model, the Parallel Ocean Program (POP) ocean model, the CICE sea ice model, and the Variable Infiltration Capacity (VIC) land model. A secondary research task for this project was testing and evaluation of WRF for climate-scale simulations on the large pan-Arctic model domain used in RACM. This involved identification of a preferred set of model physical parameterizations for use in our coupled RACM simulations and documenting any atmospheric biases present in RACM.

Impact of changes in the formulation of cloud-related processes on model biases and climate feedbacks

NARCIS (Netherlands)

Lacagnina, C.; Selten, F.; Siebesma, A.P.

2014-01-01

To test the impact of modeling uncertainties and biases on the simulation of cloud feedbacks, several configurations of the EC-Earth climate model are built altering physical parameterizations. An overview of the various radiative feedbacks diagnosed from the reference EC-Earth configuration is

Accounting for Unresolved Spatial Variability in Large Scale Models: Development and Evaluation of a Statistical Cloud Parameterization with Prognostic Higher Order Moments

Energy Technology Data Exchange (ETDEWEB)

Robert Pincus

2011-05-17

This project focused on the variability of clouds that is present across a wide range of scales ranging from the synoptic to the millimeter. In particular, there is substantial variability in cloud properties at scales smaller than the grid spacing of models used to make climate projections (GCMs) and weather forecasts. These models represent clouds and other small-scale processes with parameterizations that describe how those processes respond to and feed back on the largescale state of the atmosphere.

Development of a cloud microphysical model and parameterizations to describe the effect of CCN on warm cloud

Directory of Open Access Journals (Sweden)

N. Kuba

2006-01-01

Full Text Available First, a hybrid cloud microphysical model was developed that incorporates both Lagrangian and Eulerian frameworks to study quantitatively the effect of cloud condensation nuclei (CCN on the precipitation of warm clouds. A parcel model and a grid model comprise the cloud model. The condensation growth of CCN in each parcel is estimated in a Lagrangian framework. Changes in cloud droplet size distribution arising from condensation and coalescence are calculated on grid points using a two-moment bin method in a semi-Lagrangian framework. Sedimentation and advection are estimated in the Eulerian framework between grid points. Results from the cloud model show that an increase in the number of CCN affects both the amount and the area of precipitation. Additionally, results from the hybrid microphysical model and Kessler's parameterization were compared. Second, new parameterizations were developed that estimate the number and size distribution of cloud droplets given the updraft velocity and the number of CCN. The parameterizations were derived from the results of numerous numerical experiments that used the cloud microphysical parcel model. The input information of CCN for these parameterizations is only several values of CCN spectrum (they are given by CCN counter for example. It is more convenient than conventional parameterizations those need values concerned with CCN spectrum, C and k in the equation of N=CSk, or, breadth, total number and median radius, for example. The new parameterizations' predictions of initial cloud droplet size distribution for the bin method were verified by using the aforesaid hybrid microphysical model. The newly developed parameterizations will save computing time, and can effectively approximate components of cloud microphysics in a non-hydrostatic cloud model. The parameterizations are useful not only in the bin method in the regional cloud-resolving model but also both for a two-moment bulk microphysical model and

Implementation of a parallel version of a regional climate model

Energy Technology Data Exchange (ETDEWEB)

Gerstengarbe, F.W. [ed.; Kuecken, M. [Potsdam-Institut fuer Klimafolgenforschung (PIK), Potsdam (Germany); Schaettler, U. [Deutscher Wetterdienst, Offenbach am Main (Germany). Geschaeftsbereich Forschung und Entwicklung

1997-10-01

A regional climate model developed by the Max Planck Institute for Meterology and the German Climate Computing Centre in Hamburg based on the `Europa` and `Deutschland` models of the German Weather Service has been parallelized and implemented on the IBM RS/6000 SP computer system of the Potsdam Institute for Climate Impact Research including parallel input/output processing, the explicit Eulerian time-step, the semi-implicit corrections, the normal-mode initialization and the physical parameterizations of the German Weather Service. The implementation utilizes Fortran 90 and the Message Passing Interface. The parallelization strategy used is a 2D domain decomposition. This report describes the parallelization strategy, the parallel I/O organization, the influence of different domain decomposition approaches for static and dynamic load imbalances and first numerical results. (orig.)

Climate model biases in seasonality of continental water storage revealed by satellite gravimetry

Science.gov (United States)

Swenson, Sean; Milly, P.C.D.

2006-01-01

Satellite gravimetric observations of monthly changes in continental water storage are compared with outputs from five climate models. All models qualitatively reproduce the global pattern of annual storage amplitude, and the seasonal cycle of global average storage is reproduced well, consistent with earlier studies. However, global average agreements mask systematic model biases in low latitudes. Seasonal extrema of low‐latitude, hemispheric storage generally occur too early in the models, and model‐specific errors in amplitude of the low‐latitude annual variations are substantial. These errors are potentially explicable in terms of neglected or suboptimally parameterized water stores in the land models and precipitation biases in the climate models.

Morphing methods to parameterize specimen-specific finite element model geometries.

Science.gov (United States)

Sigal, Ian A; Yang, Hongli; Roberts, Michael D; Downs, J Crawford

2010-01-19

Shape plays an important role in determining the biomechanical response of a structure. Specimen-specific finite element (FE) models have been developed to capture the details of the shape of biological structures and predict their biomechanics. Shape, however, can vary considerably across individuals or change due to aging or disease, and analysis of the sensitivity of specimen-specific models to these variations has proven challenging. An alternative to specimen-specific representation has been to develop generic models with simplified geometries whose shape is relatively easy to parameterize, and can therefore be readily used in sensitivity studies. Despite many successful applications, generic models are limited in that they cannot make predictions for individual specimens. We propose that it is possible to harness the detail available in specimen-specific models while leveraging the power of the parameterization techniques common in generic models. In this work we show that this can be accomplished by using morphing techniques to parameterize the geometry of specimen-specific FE models such that the model shape can be varied in a controlled and systematic way suitable for sensitivity analysis. We demonstrate three morphing techniques by using them on a model of the load-bearing tissues of the posterior pole of the eye. We show that using relatively straightforward procedures these morphing techniques can be combined, which allows the study of factor interactions. Finally, we illustrate that the techniques can be used in other systems by applying them to morph a femur. Morphing techniques provide an exciting new possibility for the analysis of the biomechanical role of shape, independently or in interaction with loading and material properties. Copyright 2009 Elsevier Ltd. All rights reserved.

Errors and uncertainties introduced by a regional climate model in climate impact assessments: example of crop yield simulations in West Africa

International Nuclear Information System (INIS)

Ramarohetra, Johanna; Pohl, Benjamin; Sultan, Benjamin

2015-01-01

The challenge of estimating the potential impacts of climate change has led to an increasing use of dynamical downscaling to produce fine spatial-scale climate projections for impact assessments. In this work, we analyze if and to what extent the bias in the simulated crop yield can be reduced by using the Weather Research and Forecasting (WRF) regional climate model to downscale ERA-Interim (European Centre for Medium-Range Weather Forecasts (ECMWF) Re-Analysis) rainfall and radiation data. Then, we evaluate the uncertainties resulting from both the choice of the physical parameterizations of the WRF model and its internal variability. Impact assessments were performed at two sites in Sub-Saharan Africa and by using two crop models to simulate Niger pearl millet and Benin maize yields. We find that the use of the WRF model to downscale ERA-Interim climate data generally reduces the bias in the simulated crop yield, yet this reduction in bias strongly depends on the choices in the model setup. Among the physical parameterizations considered, we show that the choice of the land surface model (LSM) is of primary importance. When there is no coupling with a LSM, or when the LSM is too simplistic, the simulated precipitation and then the simulated yield are null, or respectively very low; therefore, coupling with a LSM is necessary. The convective scheme is the second most influential scheme for yield simulation, followed by the shortwave radiation scheme. The uncertainties related to the internal variability of the WRF model are also significant and reach up to 30% of the simulated yields. These results suggest that regional models need to be used more carefully in order to improve the reliability of impact assessments. (letter)

Application of the dual Youla parameterization

DEFF Research Database (Denmark)

Niemann, Hans Henrik

1999-01-01

Different applications of the parameterization of all systems stabilized by a given controller, i.e. the dual Youla parameterization, are considered in this paper. It will be shown how the parameterization can be applied in connection with controller design, adaptive controllers, model validation...

Structural and parameteric uncertainty quantification in cloud microphysics parameterization schemes

Science.gov (United States)

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.

Parameterizing the Spatial Markov Model From Breakthrough Curve Data Alone

Science.gov (United States)

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.

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

Science.gov (United States)

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.

Parameterization of ion-induced nucleation rates based on ambient observations

Directory of Open Access Journals (Sweden)

T. Nieminen

2011-04-01

Full Text Available Atmospheric ions participate in the formation of new atmospheric aerosol particles, yet their exact role in this process has remained unclear. Here we derive a new simple parameterization for ion-induced nucleation or, more precisely, for the formation rate of charged 2-nm particles. The parameterization is semi-empirical in the sense that it is based on comprehensive results of one-year-long atmospheric cluster and particle measurements in the size range ~1–42 nm within the EUCAARI (European Integrated project on Aerosol Cloud Climate and Air Quality interactions project. Data from 12 field sites across Europe measured with different types of air ion and cluster mobility spectrometers were used in our analysis, with more in-depth analysis made using data from four stations with concomitant sulphuric acid measurements. The parameterization is given in two slightly different forms: a more accurate one that requires information on sulfuric acid and nucleating organic vapor concentrations, and a simpler one in which this information is replaced with the global radiation intensity. These new parameterizations are applicable to all large-scale atmospheric models containing size-resolved aerosol microphysics, and a scheme to calculate concentrations of sulphuric acid, condensing organic vapours and cluster ions.

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

Science.gov (United States)

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.

Climate Shocks and Migration: An Agent-Based Modeling Approach

Science.gov (United States)

Entwisle, Barbara; Williams, Nathalie E.; Verdery, Ashton M.; Rindfuss, Ronald R.; Walsh, Stephen J.; Malanson, George P.; Mucha, Peter J.; Frizzelle, Brian G.; McDaniel, Philip M.; Yao, Xiaozheng; Heumann, Benjamin W.; Prasartkul, Pramote; Sawangdee, Yothin; Jampaklay, Aree

2016-01-01

This is a study of migration responses to climate shocks. We construct an agent-based model that incorporates dynamic linkages between demographic behaviors, such as migration, marriage, and births, and agriculture and land use, which depend on rainfall patterns. The rules and parameterization of our model are empirically derived from qualitative and quantitative analyses of a well-studied demographic field site, Nang Rong district, Northeast Thailand. With this model, we simulate patterns of migration under four weather regimes in a rice economy: 1) a reference, ‘normal’ scenario; 2) seven years of unusually wet weather; 3) seven years of unusually dry weather; and 4) seven years of extremely variable weather. Results show relatively small impacts on migration. Experiments with the model show that existing high migration rates and strong selection factors, which are unaffected by climate change, are likely responsible for the weak migration response. PMID:27594725

Parameterized Linear Longitudinal Airship Model

Science.gov (United States)

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

A Thermal Infrared Radiation Parameterization for Atmospheric Studies

Science.gov (United States)

Chou, Ming-Dah; Suarez, Max J.; Liang, Xin-Zhong; Yan, Michael M.-H.; Cote, Charles (Technical Monitor)

2001-01-01

This technical memorandum documents the longwave radiation parameterization developed at the Climate and Radiation Branch, NASA Goddard Space Flight Center, for a wide variety of weather and climate applications. Based on the 1996-version of the Air Force Geophysical Laboratory HITRAN data, the parameterization includes the absorption due to major gaseous absorption (water vapor, CO2, O3) and most of the minor trace gases (N2O, CH4, CFCs), as well as clouds and aerosols. The thermal infrared spectrum is divided into nine bands. To achieve a high degree of accuracy and speed, various approaches of computing the transmission function are applied to different spectral bands and gases. The gaseous transmission function is computed either using the k-distribution method or the table look-up method. To include the effect of scattering due to clouds and aerosols, the optical thickness is scaled by the single-scattering albedo and asymmetry factor. The parameterization can accurately compute fluxes to within 1% of the high spectral-resolution line-by-line calculations. The cooling rate can be accurately computed in the region extending from the surface to the 0.01-hPa level.

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

Science.gov (United States)

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%.

Energy-balance climate models: stability experiments with a refined albedo and updated coefficients for infrared emission

NARCIS (Netherlands)

Oerlemans, J.

1978-01-01

A zonally averaged' climate model of the energy-balance type is examined. Recently published satellite measurements were used to improve existing parameterizations of planetary albedo and outgoing radiation in terms of surface and sea level temperature. A realistic constant for the diffusion of

Regional modelling of tracer transport by tropical convection – Part 1: Sensitivity to convection parameterization

Directory of Open Access Journals (Sweden)

J. Arteta

2009-09-01

Full Text Available The general objective of this series of papers is to evaluate long duration limited area simulations with idealised tracers as a tool to assess tracer transport in chemistry-transport models (CTMs. In this first paper, we analyse the results of six simulations using different convection closures and parameterizations. The simulations are using the Grell and Dévényi (2002 mass-flux framework for the convection parameterization with different closures (Grell = GR, Arakawa-Shubert = AS, Kain-Fritch = KF, Low omega = LO, Moisture convergence = MC and an ensemble parameterization (EN based on the other five closures. The simulations are run for one month during the SCOUT-O3 field campaign lead from Darwin (Australia. They have a 60 km horizontal resolution and a fine vertical resolution in the upper troposphere/lower stratosphere. Meteorological results are compared with satellite products, radiosoundings and SCOUT-O3 aircraft campaign data. They show that the model is generally in good agreement with the measurements with less variability in the model. Except for the precipitation field, the differences between the six simulations are small on average with respect to the differences with the meteorological observations. The comparison with TRMM rainrates shows that the six parameterizations or closures have similar behaviour concerning convection triggering times and locations. However, the 6 simulations provide two different behaviours for rainfall values, with the EN, AS and KF parameterizations (Group 1 modelling better rain fields than LO, MC and GR (Group 2. The vertical distribution of tropospheric tracers is very different for the two groups showing significantly more transport into the TTL for Group 1 related to the larger average values of the upward velocities. Nevertheless the low values for the Group 1 fluxes at and above the cold point level indicate that the model does not simulate significant overshooting. For stratospheric tracers

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

Science.gov (United States)

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.

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

Science.gov (United States)

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.

Investigation of tropical diurnal convection biases in a climate model using TWP-ICE observations and convection-permitting simulations

Science.gov (United States)

Lin, W.; Xie, S.; Jackson, R. C.; Endo, S.; Vogelmann, A. M.; Collis, S. M.; Golaz, J. C.

2017-12-01

Climate models are known to have difficulty in simulating tropical diurnal convections that exhibit distinct characteristics over land and open ocean. While the causes are rooted in deficiencies in convective parameterization in general, lack of representations of mesoscale dynamics in terms of land-sea breeze, convective organization, and propagation of convection-induced gravity waves also play critical roles. In this study, the problem is investigated at the process-level with the U.S. Department of Energy Accelerated Climate Modeling for Energy (ACME) model in short-term hindcast mode using the Cloud Associated Parameterization Testbed (CAPT) framework. Convective-scale radar retrievals and observation-driven convection-permitting simulations for the Tropical Warm Pool-International Cloud Experiment (TWP-ICE) cases are used to guide the analysis of the underlying processes. The emphasis will be on linking deficiencies in representation of detailed process elements to the model biases in diurnal convective properties and their contrast among inland, coastal and open ocean conditions.

A polar stratospheric cloud parameterization for the global modeling initiative three-dimensional model and its response to stratospheric aircraft

International Nuclear Information System (INIS)

Considine, D. B.; Douglass, A. R.; Connell, P. S.; Kinnison, D. E.; Rotman, D. A.

2000-01-01

We describe a new parameterization of polar stratospheric clouds (PSCs) which was written for and incorporated into the three-dimensional (3-D) chemistry and transport model (CTM) developed for NASA's Atmospheric Effects of Aviation Project (AEAP) by the Global Modeling Initiative (GMI). The parameterization was designed to respond to changes in NO y and H 2 O produced by high-speed civilian transport (HSCT) emissions. The parameterization predicts surface area densities (SADs) of both Type 1 and Type 2 PSCs for use in heterogeneous chemistry calculations. Type 1 PSCs are assumed to have a supercooled ternary sulfate (STS) composition, and Type 2 PSCs are treated as water ice with a coexisting nitric acid trihydrate (NAT) phase. Sedimentation is treated by assuming that the PSC particles obey lognormal size distributions, resulting in a realistic mass flux of condensed phase H 2 O and HNO 3 . We examine a simulation of the Southern Hemisphere high-latitude lower stratosphere winter and spring seasons driven by temperature and wind fields from a modified version of the National Center for Atmospheric Research (NCAR) Middle Atmosphere Community Climate Model Version 2 (MACCM2). Predicted PSC SADs and median radii for both Type 1 and Type 2 PSCs are consistent with observations. Gas phase HNO 3 and H 2 O concentrations in the high-latitude lower stratosphere qualitatively agree with Cryogenic Limb Array Etalon Spectrometer (CLAES) HNO 3 and Microwave Limb Sounder (MLS) H 2 O observations. The residual denitrification and dehydration of the model polar vortex after polar winter compares well with atmospheric trace molecule spectroscopy (ATMOS) observations taken during November 1994. When the NO x and H 2 O emissions of a standard 500-aircraft HSCT fleet with a NO x emission index of 5 are added, NO x and H 2 O concentrations in the Southern Hemisphere polar vortex before winter increase by up to 3%. This results in earlier onset of PSC formation, denitrification, and

Improving microphysics in a convective parameterization: possibilities and limitations

Science.gov (United States)

Labbouz, Laurent; Heikenfeld, Max; Stier, Philip; Morrison, Hugh; Milbrandt, Jason; Protat, Alain; Kipling, Zak

2017-04-01

The convective cloud field model (CCFM) is a convective parameterization implemented in the climate model ECHAM6.1-HAM2.2. It represents a population of clouds within each ECHAM-HAM model column, simulating up to 10 different convective cloud types with individual radius, vertical velocities and microphysical properties. Comparisons between CCFM and radar data at Darwin, Australia, show that in order to reproduce both the convective cloud top height distribution and the vertical velocity profile, the effect of aerodynamic drag on the rising parcel has to be considered, along with a reduced entrainment parameter. A new double-moment microphysics (the Predicted Particle Properties scheme, P3) has been implemented in the latest version of CCFM and is compared to the standard single-moment microphysics and the radar retrievals at Darwin. The microphysical process rates (autoconversion, accretion, deposition, freezing, …) and their response to changes in CDNC are investigated and compared to high resolution CRM WRF simulations over the Amazon region. The results shed light on the possibilities and limitations of microphysics improvements in the framework of CCFM and in convective parameterizations in general.

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

Energy Technology Data Exchange (ETDEWEB)

Charles, T.K. [School of Physics and Astronomy, Monash University, Clayton, Victoria, 3800 (Australia); Australian Synchrotron, 800 Blackburn Road, Clayton, Victoria, 3168 (Australia); Paganin, D.M. [School of Physics and Astronomy, Monash University, Clayton, Victoria, 3800 (Australia); Dowd, R.T. [Australian Synchrotron, 800 Blackburn Road, Clayton, Victoria, 3168 (Australia)

2016-08-21

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.

Efficient Parameterization for Grey-box Model Identification of Complex Physical Systems

DEFF Research Database (Denmark)

Blanke, Mogens; Knudsen, Morten Haack

2006-01-01

Grey box model identification preserves known physical structures in a model but with limits to the possible excitation, all parameters are rarely identifiable, and different parametrizations give significantly different model quality. Convenient methods to show which parameterizations are the be...... that need be constrained to achieve satisfactory convergence. Identification of nonlinear models for a ship illustrate the concept....

Parameterizing Subgrid-Scale Orographic Drag in the High-Resolution Rapid Refresh (HRRR) Atmospheric Model

Science.gov (United States)

Toy, M. D.; Olson, J.; Kenyon, J.; Smirnova, T. G.; Brown, J. M.

2017-12-01

The accuracy of wind forecasts in numerical weather prediction (NWP) models is improved when the drag forces imparted on atmospheric flow by subgrid-scale orography are included. Without such parameterizations, only the terrain resolved by the model grid, along with the small-scale obstacles parameterized by the roughness lengths can have an effect on the flow. This neglects the impacts of subgrid-scale terrain variations, which typically leads to wind speeds that are too strong. Using statistical information about the subgrid-scale orography, such as the mean and variance of the topographic height within a grid cell, the drag forces due to flow blocking, gravity wave drag, and turbulent form drag are estimated and distributed vertically throughout the grid cell column. We recently implemented the small-scale gravity wave drag paramterization of Steeneveld et al. (2008) and Tsiringakis et al. (2017) for stable planetary boundary layers, and the turbulent form drag parameterization of Beljaars et al. (2004) in the High-Resolution Rapid Refresh (HRRR) NWP model developed at the National Oceanic and Atmospheric Administration (NOAA). As a result, a high surface wind speed bias in the model has been reduced and small improvement to the maintenance of stable layers has also been found. We present the results of experiments with the subgrid-scale orographic drag parameterization for the regional HRRR model, as well as for a global model in development at NOAA, showing the direct and indirect impacts.

Global Climate Models Intercomparison of Anthropogenic Aerosols Effects on Regional Climate over North Pacific

Science.gov (United States)

Hu, J.; Zhang, R.; Wang, Y.; Ming, Y.; Lin, Y.; Pan, B.

2015-12-01

Aerosols can alter atmospheric radiation and cloud physics, which further exert impacts on weather and global climate. With the development and industrialization of the developing Asian countries, anthropogenic aerosols have received considerable attentions and remain to be the largest uncertainty in the climate projection. Here we assess the performance of two stat-of-art global climate models (National Center for Atmospheric Research-Community Atmosphere Model 5 (CAM5) and Geophysical Fluid Dynamics Laboratory Atmosphere Model 3 (AM3)) in simulating the impacts of anthropogenic aerosols on North Pacific storm track region. By contrasting two aerosol scenarios, i.e. present day (PD) and pre-industrial (PI), both models show aerosol optical depth (AOD) enhanced by about 22%, with CAM5 AOD 40% lower in magnitude due to the long range transport of anthropogenic aerosols. Aerosol effects on the ice water path (IWP), stratiform precipitation, convergence and convection strengths in the two models are distinctive in patterns and magnitudes. AM3 shows qualitatively good agreement with long-term satellite observations, while CAM5 overestimates convection and liquid water path resulting in an underestimation of large-scale precipitation and IWP. Due to coarse resolution and parameterization in convection schemes, both models' performance on convection needs to be improved. Aerosols performance on large-scale circulation and radiative budget are also examined in this study.

Mesoscale model parameterizations for radiation and turbulent fluxes at the lower boundary

International Nuclear Information System (INIS)

Somieski, F.

1988-11-01

A radiation parameterization scheme for use in mesoscale models with orography and clouds has been developed. Broadband parameterizations are presented for the solar and the terrestrial spectral ranges. They account for clear, turbid or cloudy atmospheres. The scheme is one-dimensional in the atmosphere, but the effects of mountains (inclination, shading, elevated horizon) are taken into account at the surface. In the terrestrial band, grey and black clouds are considered. Furthermore, the calculation of turbulent fluxes of sensible and latent heat and momentum at an inclined lower model boundary is described. Surface-layer similarity and the surface energy budget are used to evaluate the ground surface temperature. The total scheme is part of the mesoscale model MESOSCOP. (orig.) With 3 figs., 25 refs [de

CLOUD PARAMETERIZATIONS, CLOUD PHYSICS, AND THEIR CONNECTIONS: AN OVERVIEW

International Nuclear Information System (INIS)

LIU, Y.; DAUM, P.H.; CHAI, S.K.; LIU, F.

2002-01-01

This paper consists of three parts. The first part is concerned with the parameterization of cloud microphysics in climate models. We demonstrate the crucial importance of spectral dispersion of the cloud droplet size distribution in determining radiative properties of clouds (e.g., effective radius), and underline the necessity of specifying spectral dispersion in the parameterization of cloud microphysics. It is argued that the inclusion of spectral dispersion makes the issue of cloud parameterization essentially equivalent to that of the droplet size distribution function, bringing cloud parameterization to the forefront of cloud physics. The second part is concerned with theoretical investigations into the spectral shape of droplet size distributions in cloud physics. After briefly reviewing the mainstream theories (including entrainment and mixing theories, and stochastic theories), we discuss their deficiencies and the need for a paradigm shift from reductionist approaches to systems approaches. A systems theory that has recently been formulated by utilizing ideas from statistical physics and information theory is discussed, along with the major results derived from it. It is shown that the systems formalism not only easily explains many puzzles that have been frustrating the mainstream theories, but also reveals such new phenomena as scale-dependence of cloud droplet size distributions. The third part is concerned with the potential applications of the systems theory to the specification of spectral dispersion in terms of predictable variables and scale-dependence under different fluctuating environments

A scheme for parameterizing ice cloud water content in general circulation models

Science.gov (United States)

Heymsfield, Andrew J.; Donner, Leo J.

1989-01-01

A method for specifying ice water content in GCMs is developed, based on theory and in-cloud measurements. A theoretical development of the conceptual precipitation model is given and the aircraft flights used to characterize the ice mass distribution in deep ice clouds is discussed. Ice water content values derived from the theoretical parameterization are compared with the measured values. The results demonstrate that a simple parameterization for atmospheric ice content can account for ice contents observed in several synoptic contexts.

Robustness and sensitivities of central U.S. summer convection in the super-parameterized CAM: Multi-model intercomparison with a new regional EOF index

Science.gov (United States)

Kooperman, Gabriel J.; Pritchard, Michael S.; Somerville, Richard C. J.

2013-06-01

Mesoscale convective systems (MCSs) can bring up to 60% of summer rainfall to the central United States but are not simulated by most global climate models. In this study, a new empirical orthogonal function based index is developed to isolate the MCS activity, similar to that developed by Wheeler and Hendon (2004) for the Madden-Julian Oscillation. The index is applied to compactly compare three conventional- and super-parameterized (SP) versions (3.0, 3.5, and 5.0) of the National Center for Atmospheric Research Community Atmosphere Model (CAM). Results show that nocturnal, eastward propagating convection is a robust effect of super-parameterization but is sensitive to its specific implementation. MCS composites based on the index show that in SP-CAM3.5, convective MCS anomalies are unrealistically large scale and concentrated, while surface precipitation is too weak. These aspects of the MCS signal are improved in the latest version (SP-CAM5.0), which uses high-order microphysics.

A Stochastic Lagrangian Basis for a Probabilistic Parameterization of Moisture Condensation in Eulerian Models

OpenAIRE

Tsang, Yue-Kin; Vallis, Geoffrey K.

2018-01-01

In this paper we describe the construction of an efficient probabilistic parameterization that could be used in a coarse-resolution numerical model in which the variation of moisture is not properly resolved. An Eulerian model using a coarse-grained field on a grid cannot properly resolve regions of saturation---in which condensation occurs---that are smaller than the grid boxes. Thus, in the absence of a parameterization scheme, either the grid box must become saturated or condensation will ...

Cloud ice: A climate model challenge with signs and expectations of progress

Science.gov (United States)

Waliser, Duane E.; Li, Jui-Lin F.; Woods, Christopher P.; Austin, Richard T.; Bacmeister, Julio; Chern, Jiundar; Del Genio, Anthony; Jiang, Jonathan H.; Kuang, Zhiming; Meng, Huan; Minnis, Patrick; Platnick, Steve; Rossow, William B.; Stephens, Graeme L.; Sun-Mack, Szedung; Tao, Wei-Kuo; Tompkins, Adrian M.; Vane, Deborah G.; Walker, Christopher; Wu, Dong

2009-04-01

Present-day shortcomings in the representation of upper tropospheric ice clouds in general circulation models (GCMs) lead to errors in weather and climate forecasts as well as account for a source of uncertainty in climate change projections. An ongoing challenge in rectifying these shortcomings has been the availability of adequate, high-quality, global observations targeting ice clouds and related precipitating hydrometeors. In addition, the inadequacy of the modeled physics and the often disjointed nature between model representation and the characteristics of the retrieved/observed values have hampered GCM development and validation efforts from making effective use of the measurements that have been available. Thus, even though parameterizations in GCMs accounting for cloud ice processes have, in some cases, become more sophisticated in recent years, this development has largely occurred independently of the global-scale measurements. With the relatively recent addition of satellite-derived products from Aura/Microwave Limb Sounder (MLS) and CloudSat, there are now considerably more resources with new and unique capabilities to evaluate GCMs. In this article, we illustrate the shortcomings evident in model representations of cloud ice through a comparison of the simulations assessed in the Intergovernmental Panel on Climate Change Fourth Assessment Report, briefly discuss the range of global observational resources that are available, and describe the essential components of the model parameterizations that characterize their "cloud" ice and related fields. Using this information as background, we (1) discuss some of the main considerations and cautions that must be taken into account in making model-data comparisons related to cloud ice, (2) illustrate present progress and uncertainties in applying satellite cloud ice (namely from MLS and CloudSat) to model diagnosis, (3) show some indications of model improvements, and finally (4) discuss a number of

Prognostic parameterization of cloud ice with a single category in the aerosol-climate model ECHAM(v6.3.0)-HAM(v2.3)

Science.gov (United States)

Dietlicher, Remo; Neubauer, David; Lohmann, Ulrike

2018-04-01

A new scheme for stratiform cloud microphysics has been implemented in the ECHAM6-HAM2 general circulation model. It features a widely used description of cloud water with two categories for cloud droplets and raindrops. The unique aspect of the new scheme is the break with the traditional approach to describe cloud ice analogously. Here we parameterize cloud ice by a single category that predicts bulk particle properties (P3). This method has already been applied in a regional model and most recently also in the Community Atmosphere Model 5 (CAM5). A single cloud ice category does not rely on heuristic conversion rates from one category to another. Therefore, it is conceptually easier and closer to first principles. This work shows that a single category is a viable approach to describe cloud ice in climate models. Prognostic representation of sedimentation is achieved by a nested approach for sub-stepping the cloud microphysics scheme. This yields good results in terms of accuracy and performance as compared to simulations with high temporal resolution. Furthermore, the new scheme allows for a competition between various cloud processes and is thus able to unbiasedly represent the ice formation pathway from nucleation to growth by vapor deposition and collisions to sedimentation. Specific aspects of the P3 method are evaluated. We could not produce a purely stratiform cloud where rime growth dominates growth by vapor deposition and conclude that the lack of appropriate conditions renders the prognostic parameters associated with the rime properties unnecessary. Limitations inherent in a single category are examined.

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

Science.gov (United States)

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.

Effects of model resolution and parameterizations on the simulations of clouds, precipitation, and their interactions with aerosols

Science.gov (United States)

Lee, Seoung Soo; Li, Zhanqing; Zhang, Yuwei; Yoo, Hyelim; Kim, Seungbum; Kim, Byung-Gon; Choi, Yong-Sang; Mok, Jungbin; Um, Junshik; Ock Choi, Kyoung; Dong, Danhong

2018-01-01

This study investigates the roles played by model resolution and microphysics parameterizations in the well-known uncertainties or errors in simulations of clouds, precipitation, and their interactions with aerosols by the numerical weather prediction (NWP) models. For this investigation, we used cloud-system-resolving model (CSRM) simulations as benchmark simulations that adopt high-resolution and full-fledged microphysical processes. These simulations were evaluated against observations, and this evaluation demonstrated that the CSRM simulations can function as benchmark simulations. Comparisons between the CSRM simulations and the simulations at the coarse resolutions that are generally adopted by current NWP models indicate that the use of coarse resolutions as in the NWP models can lower not only updrafts and other cloud variables (e.g., cloud mass, condensation, deposition, and evaporation) but also their sensitivity to increasing aerosol concentration. The parameterization of the saturation process plays an important role in the sensitivity of cloud variables to aerosol concentrations. while the parameterization of the sedimentation process has a substantial impact on how cloud variables are distributed vertically. The variation in cloud variables with resolution is much greater than what happens with varying microphysics parameterizations, which suggests that the uncertainties in the NWP simulations are associated with resolution much more than microphysics parameterizations.

Combining super-ensembles and statistical emulation to improve a regional climate and vegetation model

Science.gov (United States)

Hawkins, L. R.; Rupp, D. E.; Li, S.; Sarah, S.; McNeall, D. J.; Mote, P.; Betts, R. A.; Wallom, D.

2017-12-01

Changing regional patterns of surface temperature, precipitation, and humidity may cause ecosystem-scale changes in vegetation, altering the distribution of trees, shrubs, and grasses. A changing vegetation distribution, in turn, alters the albedo, latent heat flux, and carbon exchanged with the atmosphere with resulting feedbacks onto the regional climate. However, a wide range of earth-system processes that affect the carbon, energy, and hydrologic cycles occur at sub grid scales in climate models and must be parameterized. The appropriate parameter values in such parameterizations are often poorly constrained, leading to uncertainty in predictions of how the ecosystem will respond to changes in forcing. To better understand the sensitivity of regional climate to parameter selection and to improve regional climate and vegetation simulations, we used a large perturbed physics ensemble and a suite of statistical emulators. We dynamically downscaled a super-ensemble (multiple parameter sets and multiple initial conditions) of global climate simulations using a 25-km resolution regional climate model HadRM3p with the land-surface scheme MOSES2 and dynamic vegetation module TRIFFID. We simultaneously perturbed land surface parameters relating to the exchange of carbon, water, and energy between the land surface and atmosphere in a large super-ensemble of regional climate simulations over the western US. Statistical emulation was used as a computationally cost-effective tool to explore uncertainties in interactions. Regions of parameter space that did not satisfy observational constraints were eliminated and an ensemble of parameter sets that reduce regional biases and span a range of plausible interactions among earth system processes were selected. This study demonstrated that by combining super-ensemble simulations with statistical emulation, simulations of regional climate could be improved while simultaneously accounting for a range of plausible land

Model-driven harmonic parameterization of the cortical surface: HIP-HOP.

Science.gov (United States)

Auzias, G; Lefèvre, J; Le Troter, A; Fischer, C; Perrot, M; Régis, J; Coulon, O

2013-05-01

In the context of inter subject brain surface matching, we present a parameterization of the cortical surface constrained by a model of cortical organization. The parameterization is defined via an harmonic mapping of each hemisphere surface to a rectangular planar domain that integrates a representation of the model. As opposed to previous landmark-based registration methods we do not match folds between individuals but instead optimize the fit between cortical sulci and specific iso-coordinate axis in the model. This strategy overcomes some limitation to sulcus-based registration techniques such as topological variability in sulcal landmarks across subjects. Experiments on 62 subjects with manually traced sulci are presented and compared with the result of the Freesurfer software. The evaluation involves a measure of dispersion of sulci with both angular and area distortions. We show that the model-based strategy can lead to a natural, efficient and very fast (less than 5 min per hemisphere) method for defining inter subjects correspondences. We discuss how this approach also reduces the problems inherent to anatomically defined landmarks and open the way to the investigation of cortical organization through the notion of orientation and alignment of structures across the cortex.

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

Energy Technology Data Exchange (ETDEWEB)

Russell, Lynn M. [Univ. of California, San Diego, CA (United States); Somerville, Richard C.J. [Univ. of California, San Diego, CA (United States); Burrows, Susannah [Pacific Northwest National Lab. (PNNL), Richland, WA (United States); Rasch, Phil [Pacific Northwest National Lab. (PNNL), Richland, WA (United States)

2015-12-12

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 sea 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.

Potential decadal predictability and its sensitivity to sea ice albedo parameterization in a global coupled model

Energy Technology Data Exchange (ETDEWEB)

Koenigk, Torben; Caian, Mihaela; Doescher, Ralf; Wyser, Klaus [Swedish Meteorological and Hydrological Institute, Rossby Centre, Norrkoeping (Sweden); Koenig Beatty, Christof [Universite Catholique de Louvain, Louvain-la-Neuve (Belgium)

2012-06-15

Decadal prediction is one focus of the upcoming 5th IPCC Assessment report. To be able to interpret the results and to further improve the decadal predictions it is important to investigate the potential predictability in the participating climate models. This study analyzes the upper limit of climate predictability on decadal time scales and its dependency on sea ice albedo parameterization by performing two perfect ensemble experiments with the global coupled climate model EC-Earth. In the first experiment, the standard albedo formulation of EC-Earth is used, in the second experiment sea ice albedo is reduced. The potential prognostic predictability is analyzed for a set of oceanic and atmospheric parameters. The decadal predictability of the atmospheric circulation is small. The highest potential predictability was found in air temperature at 2 m height over the northern North Atlantic and the southern South Atlantic. Over land, only a few areas are significantly predictable. The predictability for continental size averages of air temperature is relatively good in all northern hemisphere regions. Sea ice thickness is highly predictable along the ice edges in the North Atlantic Arctic Sector. The meridional overturning circulation is highly predictable in both experiments and governs most of the decadal climate predictability in the northern hemisphere. The experiments using reduced sea ice albedo show some important differences like a generally higher predictability of atmospheric variables in the Arctic or higher predictability of air temperature in Europe. Furthermore, decadal variations are substantially smaller in the simulations with reduced ice albedo, which can be explained by reduced sea ice thickness in these simulations. (orig.)

Development of ALARO-Climate regional climate model for a very high resolution

Science.gov (United States)

Skalak, Petr; Farda, Ales; Brozkova, Radmila; Masek, Jan

2014-05-01

ALARO-Climate is a new regional climate model (RCM) derived from the ALADIN LAM model family. It is based on the numerical weather prediction model ALARO and developed at the Czech Hydrometeorological Institute. The model is expected to able to work in the so called "grey zone" physics (horizontal resolution of 4 - 7 km) and at the same time retain its ability to be operated in resolutions in between 20 and 50 km, which are typical for contemporary generation of regional climate models. Here we present the main results of the RCM ALARO-Climate model simulations in 25 and 6.25 km resolutions on the longer time-scale (1961-1990). The model was driven by the ERA-40 re-analyses and run on the integration domain of ~ 2500 x 2500 km size covering the central Europe. The simulated model climate was compared with the gridded observation of air temperature (mean, maximum, minimum) and precipitation from the E-OBS version dataset 8. Other simulated parameters (e.g., cloudiness, radiation or components of water cycle) were compared to the ERA-40 re-analyses. The validation of the first ERA-40 simulation in both, 25 km and 6.25 km resolutions, revealed significant cold biases in all seasons and overestimation of precipitation in the selected Central Europe target area (0° - 30° eastern longitude ; 40° - 60° northern latitude). The differences between these simulations were small and thus revealed a robustness of the model's physical parameterization on the resolution change. The series of 25 km resolution simulations with several model adaptations was carried out to study their effect on the simulated properties of climate variables and thus possibly identify a source of major errors in the simulated climate. The current investigation suggests the main reason for biases is related to the model physic. Acknowledgements: This study was performed within the frame of projects ALARO (project P209/11/2405 sponsored by the Czech Science Foundation) and CzechGlobe Centre (CZ.1

Albedo and heat transport in 3-D model simulations of the early Archean climate

Directory of Open Access Journals (Sweden)

H. Kienert

2013-08-01

Full Text Available At the beginning of the Archean eon (ca. 3.8 billion years ago, the Earth's climate state was significantly different from today due to the lower solar luminosity, smaller continental fraction, higher rotation rate and, presumably, significantly larger greenhouse gas concentrations. All these aspects play a role in solutions to the "faint young Sun paradox" which must explain why the ocean surface was not fully frozen at that time. Here, we present 3-D model simulations of climate states that are consistent with early Archean boundary conditions and have different CO2 concentrations, aiming at an understanding of the fundamental characteristics of the early Archean climate system. In order to do so, we have appropriately modified an intermediate complexity climate model that couples a statistical-dynamical atmosphere model (involving parameterizations of the dynamics to an ocean general circulation model and a thermodynamic-dynamic sea-ice model. We focus on three states: one of them is ice-free, one has the same mean surface air temperature of 288 K as today's Earth and the third one is the coldest stable state in which there is still an area with liquid surface water (i.e. the critical state at the transition to a "snowball Earth". We find a reduction in meridional heat transport compared to today, which leads to a steeper latitudinal temperature profile and has atmospheric as well as oceanic contributions. Ocean surface velocities are largely zonal, and the strength of the atmospheric meridional circulation is significantly reduced in all three states. These aspects contribute to the observed relation between global mean temperature and albedo, which we suggest as a parameterization of the ice-albedo feedback for 1-D model simulations of the early Archean and thus the faint young Sun problem.

An efficient regional energy-moisture balance model for simulation of the Greenland Ice Sheet response to climate change

Directory of Open Access Journals (Sweden)

A. Robinson

2010-04-01

Full Text Available In order to explore the response of the Greenland ice sheet (GIS to climate change on long (centennial to multi-millennial time scales, a regional energy-moisture balance model has been developed. This model simulates seasonal variations of temperature and precipitation over Greenland and explicitly accounts for elevation and albedo feedbacks. From these fields, the annual mean surface temperature and surface mass balance can be determined and used to force an ice sheet model. The melt component of the surface mass balance is computed here using both a positive degree day approach and a more physically-based alternative that includes insolation and albedo explicitly. As a validation of the climate model, we first simulated temperature and precipitation over Greenland for the prescribed, present-day topography. Our simulated climatology compares well to observations and does not differ significantly from that of a simple parameterization used in many previous simulations. Furthermore, the calculated surface mass balance using both melt schemes falls within the range of recent regional climate model results. For a prescribed, ice-free state, the differences in simulated climatology between the regional energy-moisture balance model and the simple parameterization become significant, with our model showing much stronger summer warming. When coupled to a three-dimensional ice sheet model and initialized with present-day conditions, the two melt schemes both allow realistic simulations of the present-day GIS.

Climatic change due to land surface alterations

Energy Technology Data Exchange (ETDEWEB)

Franchito, S.H.; Rao, V.B.

1992-01-01

A primitive equations global zonally averaged climate model is developed. The model includes biofeedback mechanisms. For the Northern Hemisphere the parameterization of biofeedback mechanisms is similar to that used by Gutman et al. For the Southern Hemisphere new parameterizations are derived. The model simulates reasonably well the mean annual zonally averaged climate and geobotanic zones. Deforestation, desertification, and irrigation experiments are performed. In the case of deforestation and desertification there is a reduction in the surface net radiation, evaporation, and precipitation and an increase in the surface temperature. In the case of irrigation experiment opposite changes occurred. In all the cases considered the changes in evapotranspiration overcome the effect of surface albedo modification. In all the experiments changes are smaller in the Southern Hemisphere.

Coupling of climate models and ice sheet models by surface mass balance gradients: application to the Greenland Ice Sheet

Directory of Open Access Journals (Sweden)

M. M. Helsen

2012-03-01

Full Text Available It is notoriously difficult to couple surface mass balance (SMB results from climate models to the changing geometry of an ice sheet model. This problem is traditionally avoided by using only accumulation from a climate model, and parameterizing the meltwater run-off as a function of temperature, which is often related to surface elevation (H_s. In this study, we propose a new strategy to calculate SMB, to allow a direct adjustment of SMB to a change in ice sheet topography and/or a change in climate forcing. This method is based on elevational gradients in the SMB field as computed by a regional climate model. Separate linear relations are derived for ablation and accumulation, using pairs of H_s and SMB within a minimum search radius. The continuously adjusting SMB forcing is consistent with climate model forcing fields, also for initially non-glaciated areas in the peripheral areas of an ice sheet. When applied to an asynchronous coupled ice sheet – climate model setup, this method circumvents traditional temperature lapse rate assumptions. Here we apply it to the Greenland Ice Sheet (GrIS. Experiments using both steady-state forcing and glacial-interglacial forcing result in realistic ice sheet reconstructions.

Climate change, crop yields, and undernutrition: development of a model to quantify the impact of climate scenarios on child undernutrition.

Science.gov (United States)

Lloyd, Simon J; Kovats, R Sari; Chalabi, Zaid

2011-12-01

Global climate change is anticipated to reduce future cereal yields and threaten food security, thus potentially increasing the risk of undernutrition. The causation of undernutrition is complex, and there is a need to develop models that better quantify the potential impacts of climate change on population health. We developed a model for estimating future undernutrition that accounts for food and nonfood (socioeconomic) causes and can be linked to available regional scenario data. We estimated child stunting attributable to climate change in five regions in South Asia and sub-Saharan Africa (SSA) in 2050. We used current national food availability and undernutrition data to parameterize and validate a global model, using a process-driven approach based on estimations of the physiological relationship between a lack of food and stunting. We estimated stunting in 2050 using published modeled national calorie availability under two climate scenarios and a reference scenario (no climate change). We estimated that climate change will lead to a relative increase in moderate stunting of 1-29% in 2050 compared with a future without climate change. Climate change will have a greater impact on rates of severe stunting, which we estimated will increase by 23% (central SSA) to 62% (South Asia). Climate change is likely to impair future efforts to reduce child malnutrition in South Asia and SSA, even when economic growth is taken into account. Our model suggests that to reduce and prevent future undernutrition, it is necessary to both increase food access and improve socioeconomic conditions, as well as reduce greenhouse gas emissions.

An investigation of the astronomical theory of the ice ages using a simple climate-ice sheet model

Science.gov (United States)

Pollard, D.

1978-01-01

The astronomical theory of the Quaternary ice ages is incorporated into a simple climate model for global weather; important features of the model include the albedo feedback, topography and dynamics of the ice sheets. For various parameterizations of the orbital elements, the model yields realistic assessments of the northern ice sheet. Lack of a land-sea heat capacity contrast represents one of the chief difficulties of the model.

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

Science.gov (United States)

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.

Forecasting Brassica rapa: Merging climate models with genotype specific process models for evaluation whole species response to climate change.

Science.gov (United States)

Pleban, J. R.; Mackay, D. S.; Ewers, B. E.; Weinig, C.; Guadagno, C. L.

2016-12-01

Human society has modified agriculture management practices and utilized a variety of breeding approaches to adapt to changing environments. Presently a dual pronged challenge has emerged as environmental change is occurring more rapidly while the demand of population growth on food supply is rising. Knowledge of how current agricultural practices will respond to these challenges can be informed through crafted prognostic modeling approaches. Amongst the uncertainties associated with forecasting agricultural production in a changing environment is evaluation of the responses across the existing genotypic diversity of crop species. Mechanistic models of plant productivity provide a means of genotype level parameterization allowing for a prognostic evaluation of varietal performance under changing climate. Brassica rapa represents an excellent species for this type of investigation because of its wide cultivation as well as large morphological and physiological diversity. We incorporated genotypic parameterization of B. rapa genotypes based on unique CO2 assimilation strategies, vulnerabilities to cavitation, and root to leaf area relationships into the TREES model. Three climate drivers, following the "business-as-usual" greenhouse gas emissions scenario (RCP 8.5) from Coupled Model Intercomparison Project, Phase 5 (CMIP5) were considered: temperature (T) along with associated changes in vapor pressure deficit (VPD), increasing CO2, as well as alternatives in irrigation regime across a temporal scale of present day to 2100. Genotypic responses to these drivers were evaluated using net primary productivity (NPP) and percent loss hydraulic conductance (PLC) as a measure of tolerance for a particular watering regime. Genotypic responses to T were witnessed as water demand driven by increases in VPD at 2050 and 2100 drove some genotypes to greater PLC and in a subset of these saw periodic decreases in NPP during a growing season. Genotypes able to withstand the greater

Transforming the representation of the boundary layer and low clouds for high-resolution regional climate modeling: Final report

Energy Technology Data Exchange (ETDEWEB)

Hall, Alex [University of California, Los Angeles, CA (United States). Joint Institute for Regional Earth System Science and Engineering

2013-07-24

Stratocumulus and shallow cumulus clouds in subtropical oceanic regions (e.g., Southeast Pacific) cover thousands of square kilometers and play a key role in regulating global climate (e.g., Klein and Hartmann, 1993). Numerical modeling is an essential tool to study these clouds in regional and global systems, but the current generation of climate and weather models has difficulties in representing them in a realistic way (e.g., Siebesma et al., 2004; Stevens et al., 2007; Teixeira et al., 2011). While numerical models resolve the large-scale flow, subgrid-scale parameterizations are needed to estimate small-scale properties (e.g. boundary layer turbulence and convection, clouds, radiation), which have significant influence on the resolved scale due to the complex nonlinear nature of the atmosphere. To represent the contribution of these fine-scale processes to the resolved scale, climate models use various parameterizations, which are the main pieces in the model that contribute to the low clouds dynamics and therefore are the major sources of errors or approximations in their representation. In this project, we aim to 1) improve our understanding of the physical processes in thermal circulation and cloud formation, 2) examine the performance and sensitivity of various parameterizations in the regional weather model (Weather Research and Forecasting model; WRF), and 3) develop, implement, and evaluate the advanced boundary layer parameterization in the regional model to better represent stratocumulus, shallow cumulus, and their transition. Thus, this project includes three major corresponding studies. We find that the mean diurnal cycle is sensitive to model domain in ways that reveal the existence of different contributions originating from the Southeast Pacific land-masses. The experiments suggest that diurnal variations in circulations and thermal structures over this region are influenced by convection over the Peruvian sector of the Andes cordillera, while

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

Science.gov (United States)

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|) 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.

Approaches to highly parameterized inversion-A guide to using PEST for groundwater-model calibration

Science.gov (United States)

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.

Uncertainties of parameterized surface downward clear-sky shortwave and all-sky longwave radiation.

Science.gov (United States)

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

Uncertainties of parameterized surface downward clear-sky shortwave and all-sky longwave radiation.

Directory of Open Access Journals (Sweden)

S. Gubler

2012-06-01

Full Text Available 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

Solvation of monovalent anions in formamide and methanol: Parameterization of the IEF-PCM model

International Nuclear Information System (INIS)

Boees, Elvis S.; Bernardi, Edson; Stassen, Hubert; Goncalves, Paulo F.B.

2008-01-01

The thermodynamics of solvation for a series of monovalent anions in formamide and methanol has been studied using the polarizable continuum model (PCM). The parameterization of this continuum model was guided by molecular dynamics simulations. The parameterized PCM model predicts the Gibbs free energies of solvation for 13 anions in formamide and 16 anions in methanol in very good agreement with experimental data. Two sets of atomic radii were tested in the definition of the solute cavities in the PCM and their performances are evaluated and discussed. Mean absolute deviations of the calculated free energies of solvation from the experimental values are in the range of 1.3-2.1 kcal/mol

A Solar Radiation Parameterization for Atmospheric Studies. Volume 15

Science.gov (United States)

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

1999-01-01

The solar radiation parameterization (CLIRAD-SW) developed at the Goddard Climate and Radiation Branch for application to atmospheric models are described. It includes the absorption by water vapor, O3, O2, CO2, clouds, and aerosols and the scattering by clouds, aerosols, and gases. Depending upon the nature of absorption, different approaches are applied to different absorbers. In the ultraviolet and visible regions, the spectrum is divided into 8 bands, and single O3 absorption coefficient and Rayleigh scattering coefficient are used for each band. In the infrared, the spectrum is divided into 3 bands, and the k-distribution method is applied for water vapor absorption. The flux reduction due to O2 is derived from a simple function, while the flux reduction due to CO2 is derived from precomputed tables. Cloud single-scattering properties are parameterized, separately for liquid drops and ice, as functions of water amount and effective particle size. A maximum-random approximation is adopted for the overlapping of clouds at different heights. Fluxes are computed using the Delta-Eddington approximation.

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

International Nuclear Information System (INIS)

Cai, X.; Zhang, X.

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. 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 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.

Failure analysis of parameter-induced simulation crashes in climate models

Science.gov (United States)

Lucas, D. D.; Klein, R.; Tannahill, J.; Ivanova, D.; Brandon, S.; Domyancic, D.; Zhang, Y.

2013-08-01

Simulations using IPCC (Intergovernmental Panel on Climate Change)-class climate models are subject to fail or crash for a variety of reasons. Quantitative analysis of the failures can yield useful insights to better understand and improve the models. During the course of uncertainty quantification (UQ) ensemble simulations to assess the effects of ocean model parameter uncertainties on climate simulations, we experienced a series of simulation crashes within the Parallel Ocean Program (POP2) component of the Community Climate System Model (CCSM4). About 8.5% of our CCSM4 simulations failed for numerical reasons at combinations of POP2 parameter values. We applied support vector machine (SVM) classification from machine learning to quantify and predict the probability of failure as a function of the values of 18 POP2 parameters. A committee of SVM classifiers readily predicted model failures in an independent validation ensemble, as assessed by the area under the receiver operating characteristic (ROC) curve metric (AUC > 0.96). The causes of the simulation failures were determined through a global sensitivity analysis. Combinations of 8 parameters related to ocean mixing and viscosity from three different POP2 parameterizations were the major sources of the failures. This information can be used to improve POP2 and CCSM4 by incorporating correlations across the relevant parameters. Our method can also be used to quantify, predict, and understand simulation crashes in other complex geoscientific models.

Responses of Mixed-Phase Cloud Condensates and Cloud Radiative Effects to Ice Nucleating Particle Concentrations in NCAR CAM5 and DOE ACME Climate Models

Science.gov (United States)

Liu, X.; Shi, Y.; Wu, M.; Zhang, K.

2017-12-01

Mixed-phase clouds frequently observed in the Arctic and mid-latitude storm tracks have the substantial impacts on the surface energy budget, precipitation and climate. In this study, we first implement the two empirical parameterizations (Niemand et al. 2012 and DeMott et al. 2015) of heterogeneous ice nucleation for mixed-phase clouds in the NCAR Community Atmosphere Model Version 5 (CAM5) and DOE Accelerated Climate Model for Energy Version 1 (ACME1). Model simulated ice nucleating particle (INP) concentrations based on Niemand et al. and DeMott et al. are compared with those from the default ice nucleation parameterization based on the classical nucleation theory (CNT) in CAM5 and ACME, and with in situ observations. Significantly higher INP concentrations (by up to a factor of 5) are simulated from Niemand et al. than DeMott et al. and CNT especially over the dust source regions in both CAM5 and ACME. Interestingly the ACME model simulates higher INP concentrations than CAM5, especially in the Polar regions. This is also the case when we nudge the two models' winds and temperature towards the same reanalysis, indicating more efficient transport of aerosols (dust) to the Polar regions in ACME. Next, we examine the responses of model simulated cloud liquid water and ice water contents to different INP concentrations from three ice nucleation parameterizations (Niemand et al., DeMott et al., and CNT) in CAM5 and ACME. Changes in liquid water path (LWP) reach as much as 20% in the Arctic regions in ACME between the three parameterizations while the LWP changes are smaller and limited in the Northern Hemispheric mid-latitudes in CAM5. Finally, the impacts on cloud radiative forcing and dust indirect effects on mixed-phase clouds are quantified with the three ice nucleation parameterizations in CAM5 and ACME.

Parameterization Of Solar Radiation Using Neural Network

International Nuclear Information System (INIS)

Jiya, J. D.; Alfa, B.

2002-01-01

This paper presents a neural network technique for parameterization of global solar radiation. The available data from twenty-one stations is used for training the neural network and the data from other ten stations is used to validate the neural model. The neural network utilizes latitude, longitude, altitude, sunshine duration and period number to parameterize solar radiation values. The testing data was not used in the training to demonstrate the performance of the neural network in unknown stations to parameterize solar radiation. The results indicate a good agreement between the parameterized solar radiation values and actual measured values

Parameterizing Urban Canopy Layer transport in an Lagrangian Particle Dispersion Model

Science.gov (United States)

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

Modeling climatic effects of anthropogenic CO2 emissions: Unknowns and uncertainties

Science.gov (United States)

Soon, W.; Baliunas, S.; Idso, S.; Kondratyev, K. Ya.; Posmentier, E. S.

2001-12-01

A likelihood of disastrous global environmental consequences has been surmised as a result of projected increases in anthropogenic greenhouse gas emissions. These estimates are based on computer climate modeling, a branch of science still in its infancy despite recent, substantial strides in knowledge. Because the expected anthropogenic climate forcings are relatively small compared to other background and forcing factors (internal and external), the credibility of the modeled global and regional responses rests on the validity of the models. We focus on this important question of climate model validation. Specifically, we review common deficiencies in general circulation model calculations of atmospheric temperature, surface temperature, precipitation and their spatial and temporal variability. These deficiencies arise from complex problems associated with parameterization of multiply-interacting climate components, forcings and feedbacks, involving especially clouds and oceans. We also review examples of expected climatic impacts from anthropogenic CO2 forcing. Given the host of uncertainties and unknowns in the difficult but important task of climate modeling, the unique attribution of observed current climate change to increased atmospheric CO2 concentration, including the relatively well-observed latest 20 years, is not possible. We further conclude that the incautious use of GCMs to make future climate projections from incomplete or unknown forcing scenarios is antithetical to the intrinsically heuristic value of models. Such uncritical application of climate models has led to the commonly-held but erroneous impression that modeling has proven or substantiated the hypothesis that CO2 added to the air has caused or will cause significant global warming. An assessment of the positive skills of GCMs and their use in suggesting a discernible human influence on global climate can be found in the joint World Meteorological Organisation and United Nations

Upgrades, Current Capabilities and Near-Term Plans of the NASA ARC Mars Climate

Science.gov (United States)

Hollingsworth, J. L.; Kahre, Melinda April; Haberle, Robert M.; Schaeffer, James R.

2012-01-01

We describe and review recent upgrades to the ARC Mars climate modeling framework, in particular, with regards to physical parameterizations (i.e., testing, implementation, modularization and documentation); the current climate modeling capabilities; selected research topics regarding current/past climates; and then, our near-term plans related to the NASA ARC Mars general circulation modeling (GCM) project.

Climate SPHINX: High-resolution present-day and future climate simulations with an improved representation of small-scale variability

Science.gov (United States)

Davini, Paolo; von Hardenberg, Jost; Corti, Susanna; Subramanian, Aneesh; Weisheimer, Antje; Christensen, Hannah; Juricke, Stephan; Palmer, Tim

2016-04-01

The PRACE Climate SPHINX project investigates the sensitivity of climate simulations to model resolution and stochastic parameterization. The EC-Earth Earth-System Model is used to explore the impact of stochastic physics in 30-years climate integrations as a function of model resolution (from 80km up to 16km for the atmosphere). The experiments include more than 70 simulations in both a historical scenario (1979-2008) and a climate change projection (2039-2068), using RCP8.5 CMIP5 forcing. A total amount of 20 million core hours will be used at end of the project (March 2016) and about 150 TBytes of post-processed data will be available to the climate community. Preliminary results show a clear improvement in the representation of climate variability over the Euro-Atlantic following resolution increase. More specifically, the well-known atmospheric blocking negative bias over Europe is definitely resolved. High resolution runs also show improved fidelity in representation of tropical variability - such as the MJO and its propagation - over the low resolution simulations. It is shown that including stochastic parameterization in the low resolution runs help to improve some of the aspects of the MJO propagation further. These findings show the importance of representing the impact of small scale processes on the large scale climate variability either explicitly (with high resolution simulations) or stochastically (in low resolution simulations).

Introducing Enabling Computational Tools to the Climate Sciences: Multi-Resolution Climate Modeling with Adaptive Cubed-Sphere Grids

Energy Technology Data Exchange (ETDEWEB)

Jablonowski, Christiane [Univ. of Michigan, Ann Arbor, MI (United States)

2015-07-14

The research investigates and advances strategies how to bridge the scale discrepancies between local, regional and global phenomena in climate models without the prohibitive computational costs of global cloud-resolving simulations. In particular, the research explores new frontiers in computational geoscience by introducing high-order Adaptive Mesh Refinement (AMR) techniques into climate research. AMR and statically-adapted variable-resolution approaches represent an emerging trend for atmospheric models and are likely to become the new norm in future-generation weather and climate models. The research advances the understanding of multi-scale interactions in the climate system and showcases a pathway how to model these interactions effectively with advanced computational tools, like the Chombo AMR library developed at the Lawrence Berkeley National Laboratory. The research is interdisciplinary and combines applied mathematics, scientific computing and the atmospheric sciences. In this research project, a hierarchy of high-order atmospheric models on cubed-sphere computational grids have been developed that serve as an algorithmic prototype for the finite-volume solution-adaptive Chombo-AMR approach. The foci of the investigations have lied on the characteristics of both static mesh adaptations and dynamically-adaptive grids that can capture flow fields of interest like tropical cyclones. Six research themes have been chosen. These are (1) the introduction of adaptive mesh refinement techniques into the climate sciences, (2) advanced algorithms for nonhydrostatic atmospheric dynamical cores, (3) an assessment of the interplay between resolved-scale dynamical motions and subgrid-scale physical parameterizations, (4) evaluation techniques for atmospheric model hierarchies, (5) the comparison of AMR refinement strategies and (6) tropical cyclone studies with a focus on multi-scale interactions and variable-resolution modeling. The results of this research project

Toward an ultra-high resolution community climate system model for the BlueGene platform

International Nuclear Information System (INIS)

Dennis, John M; Jacob, Robert; Vertenstein, Mariana; Craig, Tony; Loy, Raymond

2007-01-01

Global climate models need to simulate several small, regional-scale processes which affect the global circulation in order to accurately simulate the climate. This is particularly important in the ocean where small scale features such as oceanic eddies are currently represented with adhoc parameterizations. There is also a need for higher resolution to provide climate predictions at small, regional scales. New high-performance computing platforms such as the IBM BlueGene can provide the necessary computational power to perform ultra-high resolution climate model integrations. We have begun to investigate the scaling of the individual components of the Community Climate System Model to prepare it for integrations on BlueGene and similar platforms. Our investigations show that it is possible to successfully utilize O(32K) processors. We describe the scalability of five models: the Parallel Ocean Program (POP), the Community Ice CodE (CICE), the Community Land Model (CLM), and the new CCSM sequential coupler (CPL7) which are components of the next generation Community Climate System Model (CCSM); as well as the High-Order Method Modeling Environment (HOMME) which is a dynamical core currently being evaluated within the Community Atmospheric Model. For our studies we concentrate on 1/10 0 resolution for CICE, POP, and CLM models and 1/4 0 resolution for HOMME. The ability to simulate high resolutions on the massively parallel petascale systems that will dominate high-performance computing for the foreseeable future is essential to the advancement of climate science

Statistical framework for evaluation of climate model simulations by use of climate proxy data from the last millennium - Part 1: Theory

Science.gov (United States)

Sundberg, R.; Moberg, A.; Hind, A.

2012-08-01

A statistical framework for comparing the output of ensemble simulations from global climate models with networks of climate proxy and instrumental records has been developed, focusing on near-surface temperatures for the last millennium. This framework includes the formulation of a joint statistical model for proxy data, instrumental data and simulation data, which is used to optimize a quadratic distance measure for ranking climate model simulations. An essential underlying assumption is that the simulations and the proxy/instrumental series have a shared component of variability that is due to temporal changes in external forcing, such as volcanic aerosol load, solar irradiance or greenhouse gas concentrations. Two statistical tests have been formulated. Firstly, a preliminary test establishes whether a significant temporal correlation exists between instrumental/proxy and simulation data. Secondly, the distance measure is expressed in the form of a test statistic of whether a forced simulation is closer to the instrumental/proxy series than unforced simulations. The proposed framework allows any number of proxy locations to be used jointly, with different seasons, record lengths and statistical precision. The goal is to objectively rank several competing climate model simulations (e.g. with alternative model parameterizations or alternative forcing histories) by means of their goodness of fit to the unobservable true past climate variations, as estimated from noisy proxy data and instrumental observations.

Parameterization of Nitrogen Limitation for a Dynamic Ecohydrological Model: a Case Study from the Luquillo Critical Zone Observatory

Science.gov (United States)

Bastola, S.; Bras, R. L.

2017-12-01

Feedbacks between vegetation and the soil nutrient cycle are important in ecosystems where nitrogen limits plant growth, and consequently influences the carbon balance in the plant-soil system. However, many biosphere models do not include such feedbacks, because interactions between carbon and the nitrogen cycle can be complex, and remain poorly understood. In this study we coupled a nitrogen cycle model with an eco-hydrological model by using the concept of carbon cost economics. This concept accounts for different "costs" to the plant of acquiring nitrogen via different pathways. This study builds on tRIBS-VEGGIE, a spatially explicit hydrological model coupled with a model of photosynthesis, stomatal resistance, and energy balance, by combining it with a model of nitrogen recycling. Driven by climate and spatially explicit data of soils, vegetation and topography, the model (referred to as tRIBS-VEGGIE-CN) simulates the dynamics of carbon and nitrogen in the soil-plant system; the dynamics of vegetation; and different components of the hydrological cycle. The tRIBS-VEGGIE-CN is applied in a humid tropical watershed at the Luquillo Critical Zone Observatory (LCZO). The region is characterized by high availability and cycling of nitrogen, high soil respiration rates, and large carbon stocks.We drive the model under contemporary CO2 and hydro-climatic forcing and compare results to a simulation under doubling CO2 and a range of future climate scenarios. The results with parameterization of nitrogen limitation based on carbon cost economics show that the carbon cost of the acquisition of nitrogen is 14% of the net primary productivity (NPP) and the N uptake cost for different pathways vary over a large range depending on leaf nitrogen content, turnover rates of carbon in soil and nitrogen cycling processes. Moreover, the N fertilization simulation experiment shows that the application of N fertilizer does not significantly change the simulated NPP. Furthermore, an

Global high resolution versus Limited Area Model climate change projections over Europe

DEFF Research Database (Denmark)

Déqué, Michel; Jones, R. G.; Wild, M.

2005-01-01

the 2071-2100 and the 1961-1990 means is compared with the same diagnostic obtained with nine Regional Climate Models (RCM) all driven by the Hadley Centre atmospheric GCM. The seasonal mean response for 2m temperature and precipitation is investigated. For temperature, GCMs and RCMs behave similarly......, except that GCMs exhibit a larger spread. However, during summer, the spread of the RCMs - in particular in terms of precipitation - is larger than that of the GCMs. This indicates that the European summer climate is strongly controlled by parameterized physics and/or high-resolution processes...... errors are more spread. In addition, GCM precipitation response is slightly but significantly different from that of the RCMs....

Importance of ensembles in projecting regional climate trends

Science.gov (United States)

Arritt, Raymond; Daniel, Ariele; Groisman, Pavel

2016-04-01

We have performed an ensemble of simulations using RegCM4 to examine the ability to reproduce observed trends in precipitation intensity and to project future changes through the 21st century for the central United States. We created a matrix of simulations over the CORDEX North America domain for 1950-2099 by driving the regional model with two different global models (HadGEM2-ES and GFDL-ESM2M, both for RCP8.5), by performing simulations at both 50 km and 25 km grid spacing, and by using three different convective parameterizations. The result is a set of 12 simulations (two GCMs by two resolutions by three convective parameterizations) that can be used to systematically evaluate the influence of simulation design on predicted precipitation. The two global models were selected to bracket the range of climate sensitivity in the CMIP5 models: HadGEM2-ES has the highest ECS of the CMIP5 models, while GFDL-ESM2M has one of the lowestt. Our evaluation metrics differ from many other RCM studies in that we focus on the skill of the models in reproducing past trends rather than the mean climate state. Trends in frequency of extreme precipitation (defined as amounts exceeding 76.2 mm/day) for most simulations are similar to the observed trend but with notable variations depending on RegCM4 configuration and on the driving GCM. There are complex interactions among resolution, choice of convective parameterization, and the driving GCM that carry over into the future climate projections. We also note that biases in the current climate do not correspond to biases in trends. As an example of these points the Emanuel scheme is consistently "wet" (positive bias in precipitation) yet it produced the smallest precipitation increase of the three convective parameterizations when used in simulations driven by HadGEM2-ES. However, it produced the largest increase when driven by GFDL-ESM2M. These findings reiterate that ensembles using multiple RCM configurations and driving GCMs are

RACORO Continental Boundary Layer Cloud Investigations: 3. Separation of Parameterization Biases in Single-Column Model CAM5 Simulations of Shallow Cumulus

Science.gov (United States)

Lin, Wuyin; Liu, Yangang; Vogelmann, Andrew M.; Fridlind, Ann; Endo, Satoshi; Song, Hua; Feng, Sha; Toto, Tami; Li, Zhijin; Zhang, Minghua

2015-01-01

Climatically important low-level clouds are commonly misrepresented in climate models. The FAst-physics System TEstbed and Research (FASTER) Project has constructed case studies from the Atmospheric Radiation Measurement Climate Research Facility's Southern Great Plain site during the RACORO aircraft campaign to facilitate research on model representation of boundary-layer clouds. This paper focuses on using the single-column Community Atmosphere Model version 5 (SCAM5) simulations of a multi-day continental shallow cumulus case to identify specific parameterization causes of low-cloud biases. Consistent model biases among the simulations driven by a set of alternative forcings suggest that uncertainty in the forcing plays only a relatively minor role. In-depth analysis reveals that the model's shallow cumulus convection scheme tends to significantly under-produce clouds during the times when shallow cumuli exist in the observations, while the deep convective and stratiform cloud schemes significantly over-produce low-level clouds throughout the day. The links between model biases and the underlying assumptions of the shallow cumulus scheme are further diagnosed with the aid of large-eddy simulations and aircraft measurements, and by suppressing the triggering of the deep convection scheme. It is found that the weak boundary layer turbulence simulated is directly responsible for the weak cumulus activity and the simulated boundary layer stratiform clouds. Increased vertical and temporal resolutions are shown to lead to stronger boundary layer turbulence and reduction of low-cloud biases.

Test Driven Development of a Parameterized Ice Sheet Component

Science.gov (United States)

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.

WRF model sensitivity to choice of parameterization: a study of the `York Flood 1999'

Science.gov (United States)

Remesan, Renji; Bellerby, Tim; Holman, Ian; Frostick, Lynne

2015-10-01

Numerical weather modelling has gained considerable attention in the field of hydrology especially in un-gauged catchments and in conjunction with distributed models. As a consequence, the accuracy with which these models represent precipitation, sub-grid-scale processes and exceptional events has become of considerable concern to the hydrological community. This paper presents sensitivity analyses for the Weather Research Forecast (WRF) model with respect to the choice of physical parameterization schemes (both cumulus parameterisation (CPSs) and microphysics parameterization schemes (MPSs)) used to represent the `1999 York Flood' event, which occurred over North Yorkshire, UK, 1st-14th March 1999. The study assessed four CPSs (Kain-Fritsch (KF2), Betts-Miller-Janjic (BMJ), Grell-Devenyi ensemble (GD) and the old Kain-Fritsch (KF1)) and four MPSs (Kessler, Lin et al., WRF single-moment 3-class (WSM3) and WRF single-moment 5-class (WSM5)] with respect to their influence on modelled rainfall. The study suggests that the BMJ scheme may be a better cumulus parameterization choice for the study region, giving a consistently better performance than other three CPSs, though there are suggestions of underestimation. The WSM3 was identified as the best MPSs and a combined WSM3/BMJ model setup produced realistic estimates of precipitation quantities for this exceptional flood event. This study analysed spatial variability in WRF performance through categorical indices, including POD, FBI, FAR and CSI during York Flood 1999 under various model settings. Moreover, the WRF model was good at predicting high-intensity rare events over the Yorkshire region, suggesting it has potential for operational use.

Subgrid Parameterization of the Soil Moisture Storage Capacity for a Distributed Rainfall-Runoff Model

Directory of Open Access Journals (Sweden)

Weijian Guo

2015-05-01

Full Text Available Spatial variability plays an important role in nonlinear hydrologic processes. Due to the limitation of computational efficiency and data resolution, subgrid variability is usually assumed to be uniform for most grid-based rainfall-runoff models, which leads to the scale-dependence of model performances. In this paper, the scale effect on the Grid-Xinanjiang model was examined. The bias of the estimation of precipitation, runoff, evapotranspiration and soil moisture at the different grid scales, along with the scale-dependence of the effective parameters, highlights the importance of well representing the subgrid variability. This paper presents a subgrid parameterization method to incorporate the subgrid variability of the soil storage capacity, which is a key variable that controls runoff generation and partitioning in the Grid-Xinanjiang model. In light of the similar spatial pattern and physical basis, the soil storage capacity is correlated with the topographic index, whose spatial distribution can more readily be measured. A beta distribution is introduced to represent the spatial distribution of the soil storage capacity within the grid. The results derived from the Yanduhe Basin show that the proposed subgrid parameterization method can effectively correct the watershed soil storage capacity curve. Compared to the original Grid-Xinanjiang model, the model performances are quite consistent at the different grid scales when the subgrid variability is incorporated. This subgrid parameterization method reduces the recalibration necessity when the Digital Elevation Model (DEM resolution is changed. Moreover, it improves the potential for the application of the distributed model in the ungauged basin.

Parameterizing the Spatial Markov Model from Breakthrough Curve Data Alone

Science.gov (United States)

Sherman, T.; Bolster, D.; Fakhari, A.; Miller, S.; Singha, K.

2017-12-01

The spatial Markov model (SMM) uses a correlated random walk and has been shown to effectively capture anomalous transport in porous media systems; in the SMM, particles' future trajectories are correlated to their current velocity. It is common practice to use a priori Lagrangian velocity statistics obtained from high resolution simulations to determine a distribution of transition probabilities (correlation) between velocity classes that govern predicted transport behavior; however, this approach is computationally cumbersome. Here, we introduce a methodology to quantify velocity correlation from Breakthrough (BTC) curve data alone; discretizing two measured BTCs into a set of arrival times and reverse engineering the rules of the SMM allows for prediction of velocity correlation, thereby enabling parameterization of the SMM in studies where Lagrangian velocity statistics are not available. The introduced methodology is applied to estimate velocity correlation from BTCs measured in high resolution simulations, thus allowing for a comparison of estimated parameters with known simulated values. Results show 1) estimated transition probabilities agree with simulated values and 2) using the SMM with estimated parameterization accurately predicts BTCs downstream. Additionally, we include uncertainty measurements by calculating lower and upper estimates of velocity correlation, which allow for prediction of a range of BTCs. The simulated BTCs fall in the range of predicted BTCs. This research proposes a novel method to parameterize the SMM from BTC data alone, thereby reducing the SMM's computational costs and widening its applicability.

Can phenological models predict tree phenology accurately under climate change conditions?

Science.gov (United States)

Chuine, Isabelle; Bonhomme, Marc; Legave, Jean Michel; García de Cortázar-Atauri, Inaki; Charrier, Guillaume; Lacointe, André; Améglio, Thierry

2014-05-01

or compromise dormancy break at the species equatorward range limits leading to a delay or even impossibility to flower or set new leaves. These models are classically parameterized with flowering or budburst dates only, with no information on the dormancy break date because this information is very scarce. We evaluated the efficiency of a set of process-based phenological models to accurately predict the dormancy break dates of four fruit trees. Our results show that models calibrated solely with flowering or budburst dates do not accurately predict the dormancy break date. Providing dormancy break date for the model parameterization results in much more accurate simulation of this latter, with however a higher error than that on flowering or bud break dates. But most importantly, we show also that models not calibrated with dormancy break dates can generate significant differences in forecasted flowering or bud break dates when using climate scenarios. Our results claim for the urgent need of massive measurements of dormancy break dates in forest and fruit trees to yield more robust projections of phenological changes in a near future.

An energy-balance model with multiply-periodic and quasi-chaotic free oscillations. [for climate forecasting

Science.gov (United States)

Bhattacharya, K.; Ghil, M.

1979-01-01

A slightly modified version of the one-dimensional time-dependent energy-balance climate model of Ghil and Bhattacharya (1978) is presented. The albedo-temperature parameterization has been reformulated and the smoothing of the temperature distribution in the tropics has been eliminated. The model albedo depends on time-lagged temperature in order to account for finite growth and decay time of continental ice sheets. Two distinct regimes of oscillatory behavior which depend on the value of the albedo-temperature time lag are considered.

Parameterization of phase change of water in a mesoscale model

Energy Technology Data Exchange (ETDEWEB)

Levkov, L; Eppel, D; Grassl, H

1987-01-01

A parameterization scheme of phase change of water is suggested to be used in the 3-D numerical nonhydrostatic model GESIMA. The microphysical formulation follows the so-called bulk technique. With this procedure the net production rates in the balance equations for water and potential temperature are given both for liquid and ice-phase. Convectively stable as well as convectively unstable mesoscale systems are considered. With 2 figs..

Impact of Vegetation Cover Fraction Parameterization schemes on Land Surface Temperature Simulation in the Tibetan Plateau

Science.gov (United States)

Lv, M.; Li, C.; Lu, H.; Yang, K.; Chen, Y.

2017-12-01

The parameterization of vegetation cover fraction (VCF) is an important component of land surface models. This paper investigates the impacts of three VCF parameterization schemes on land surface temperature (LST) simulation by the Common Land Model (CoLM) in the Tibetan Plateau (TP). The first scheme is a simple land cover (LC) based method; the second one is based on remote sensing observation (hereafter named as RNVCF) , in which multi-year climatology VCFs is derived from Moderate-resolution Imaging Spectroradiometer (MODIS) NDVI (Normalized Difference Vegetation Index); the third VCF parameterization scheme derives VCF from the LAI simulated by LSM and clump index at every model time step (hereafter named as SMVCF). Simulated land surface temperature(LST) and soil temperature by CoLM with three VCF parameterization schemes were evaluated by using satellite LST observation and in situ soil temperature observation, respectively, during the period of 2010 to 2013. The comparison against MODIS Aqua LST indicates that (1) CTL produces large biases for both four seasons in early afternoon (about 13:30, local solar time), while the mean bias in spring reach to 12.14K; (2) RNVCF and SMVCF reduce the mean bias significantly, especially in spring as such reduce is about 6.5K. Surface soil temperature observed at 5 cm depth from three soil moisture and temperature monitoring networks is also employed to assess the skill of three VCF schemes. The three networks, crossing TP from West to East, have different climate and vegetation conditions. In the Ngari network, located in the Western TP with an arid climate, there are not obvious differences among three schemes. In Naqu network, located in central TP with a semi-arid climate condition, CTL shows a severe overestimates (12.1 K), but such overestimations can be reduced by 79% by RNVCF and 87% by SMVCF. In the third humid network (Maqu in eastern TP), CoLM performs similar to Naqu. However, at both Naqu and Maqu networks

Toward an ultra-high resolution community climate system model for the BlueGene platform

Energy Technology Data Exchange (ETDEWEB)

Dennis, John M [Computer Science Section, National Center for Atmospheric Research, Boulder, CO (United States); Jacob, Robert [Mathematics and Computer Science Division, Argonne National Laboratory, Argonne, IL (United States); Vertenstein, Mariana [Climate and Global Dynamics Division, National Center for Atmospheric Research, Boulder, CO (United States); Craig, Tony [Climate and Global Dynamics Division, National Center for Atmospheric Research, Boulder, CO (United States); Loy, Raymond [Mathematics and Computer Science Division, Argonne National Laboratory, Argonne, IL (United States)

2007-07-15

Global climate models need to simulate several small, regional-scale processes which affect the global circulation in order to accurately simulate the climate. This is particularly important in the ocean where small scale features such as oceanic eddies are currently represented with adhoc parameterizations. There is also a need for higher resolution to provide climate predictions at small, regional scales. New high-performance computing platforms such as the IBM BlueGene can provide the necessary computational power to perform ultra-high resolution climate model integrations. We have begun to investigate the scaling of the individual components of the Community Climate System Model to prepare it for integrations on BlueGene and similar platforms. Our investigations show that it is possible to successfully utilize O(32K) processors. We describe the scalability of five models: the Parallel Ocean Program (POP), the Community Ice CodE (CICE), the Community Land Model (CLM), and the new CCSM sequential coupler (CPL7) which are components of the next generation Community Climate System Model (CCSM); as well as the High-Order Method Modeling Environment (HOMME) which is a dynamical core currently being evaluated within the Community Atmospheric Model. For our studies we concentrate on 1/10{sup 0} resolution for CICE, POP, and CLM models and 1/4{sup 0} resolution for HOMME. The ability to simulate high resolutions on the massively parallel petascale systems that will dominate high-performance computing for the foreseeable future is essential to the advancement of climate science.

Implementation of a generalized actuator line model for wind turbine parameterization in the Weather Research and Forecasting model

Energy Technology Data Exchange (ETDEWEB)

Marjanovic, Nikola [Department of Civil and Environmental Engineering, University of California, Berkeley, MC 1710, Berkeley, California 94720-1710, USA; Atmospheric, Earth and Energy Division, Lawrence Livermore National Laboratory, PO Box 808, L-103, Livermore, California 94551, USA; Mirocha, Jeffrey D. [Atmospheric, Earth and Energy Division, Lawrence Livermore National Laboratory, PO Box 808, L-103, Livermore, California 94551, USA; Kosović, Branko [Research Applications Laboratory, Weather Systems and Assessment Program, University Corporation for Atmospheric Research, PO Box 3000, Boulder, Colorado 80307, USA; Lundquist, Julie K. [Department of Atmospheric and Oceanic Sciences, University of Colorado, Boulder, Campus Box 311, Boulder, Colorado 80309, USA; National Renewable Energy Laboratory, 15013 Denver West Parkway, Golden, Colorado 80401, USA; Chow, Fotini Katopodes [Department of Civil and Environmental Engineering, University of California, Berkeley, MC 1710, Berkeley, California 94720-1710, USA

2017-11-01

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 simulations 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.

Quantifying uncertainty due to internal variability using high-resolution regional climate model simulations

Science.gov (United States)

Gutmann, E. D.; Ikeda, K.; Deser, C.; Rasmussen, R.; Clark, M. P.; Arnold, J. R.

2015-12-01

The uncertainty in future climate predictions is as large or larger than the mean climate change signal. As such, any predictions of future climate need to incorporate and quantify the sources of this uncertainty. One of the largest sources comes from the internal, chaotic, variability within the climate system itself. This variability has been approximated using the 30 ensemble members of the Community Earth System Model (CESM) large ensemble. Here we examine the wet and dry end members of this ensemble for cool-season precipitation in the Colorado Rocky Mountains with a set of high-resolution regional climate model simulations. We have used the Weather Research and Forecasting model (WRF) to simulate the periods 1990-2000, 2025-2035, and 2070-2080 on a 4km grid. These simulations show that the broad patterns of change depicted in CESM are inherited by the high-resolution simulations; however, the differences in the height and location of the mountains in the WRF simulation, relative to the CESM simulation, means that the location and magnitude of the precipitation changes are very different. We further show that high-resolution simulations with the Intermediate Complexity Atmospheric Research model (ICAR) predict a similar spatial pattern in the change signal as WRF for these ensemble members. We then use ICAR to examine the rest of the CESM Large Ensemble as well as the uncertainty in the regional climate model due to the choice of physics parameterizations.

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

Science.gov (United States)

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.

A comparison of simulation results from two terrestrial carbon cycle models using three climate data sets

International Nuclear Information System (INIS)

Ito, Akihiko; Sasai, Takahiro

2006-01-01

This study addressed how different climate data sets influence simulations of the global terrestrial carbon cycle. For the period 1982-2001, we compared the results of simulations based on three climate data sets (NCEP/NCAR, NCEP/DOE AMIP-II and ERA40) employed in meteorological, ecological and biogeochemical studies and two different models (BEAMS and Sim-CYCLE). The models differed in their parameterizations of photosynthetic and phenological processes but used the same surface climate (e.g. shortwave radiation, temperature and precipitation), vegetation, soil and topography data. The three data sets give different climatic conditions, especially for shortwave radiation, in terms of long-term means, linear trends and interannual variability. Consequently, the simulation results for global net primary productivity varied by 16%-43% only from differences in the climate data sets, especially in these regions where the shortwave radiation data differed markedly: differences in the climate data set can strongly influence simulation results. The differences among the climate data set and between the two models resulted in slightly different spatial distribution and interannual variability in the net ecosystem carbon budget. To minimize uncertainty, we should pay attention to the specific climate data used. We recommend developing an accurate standard climate data set for simulation studies

Sensitivity analysis with the regional climate model COSMO-CLM over the CORDEX-MENA domain

Science.gov (United States)

Bucchignani, E.; Cattaneo, L.; Panitz, H.-J.; Mercogliano, P.

2016-02-01

The results of a sensitivity work based on ERA-Interim driven COSMO-CLM simulations over the Middle East-North Africa (CORDEX-MENA) domain are presented. All simulations were performed at 0.44° spatial resolution. The purpose of this study was to ascertain model performances with respect to changes in physical and tuning parameters which are mainly related to surface, convection, radiation and cloud parameterizations. Evaluation was performed for the whole CORDEX-MENA region and six sub-regions, comparing a set of 26 COSMO-CLM runs against a combination of available ground observations, satellite products and reanalysis data to assess temperature, precipitation, cloud cover and mean sea level pressure. The model proved to be very sensitive to changes in physical parameters. The optimized configuration allows COSMO-CLM to improve the simulated main climate features of this area. Its main characteristics consist in the new parameterization of albedo, based on Moderate Resolution Imaging Spectroradiometer data, and the new parameterization of aerosol, based on NASA-GISS AOD distributions. When applying this configuration, Mean Absolute Error values for the considered variables are as follows: about 1.2 °C for temperature, about 15 mm/month for precipitation, about 9 % for total cloud cover, and about 0.6 hPa for mean sea level pressure.

Parameterization of mixing by secondary circulation in estuaries

Science.gov (United States)

Basdurak, N. B.; Huguenard, K. D.; Valle-Levinson, A.; Li, M.; Chant, R. J.

2017-07-01

Eddy viscosity parameterizations that depend on a gradient Richardson number Ri have been most pertinent to the open ocean. Parameterizations applicable to stratified coastal regions typically require implementation of a numerical model. Two novel parameterizations of the vertical eddy viscosity, based on Ri, are proposed here for coastal waters. One turbulence closure considers temporal changes in stratification and bottom stress and is coined the "regular fit." The alternative approach, named the "lateral fit," incorporates variability of lateral flows that are prevalent in estuaries. The two turbulence parameterization schemes are tested using data from a Self-Contained Autonomous Microstructure Profiler (SCAMP) and an Acoustic Doppler Current Profiler (ADCP) collected in the James River Estuary. The "regular fit" compares favorably to SCAMP-derived vertical eddy viscosity values but only at relatively small values of gradient Ri. On the other hand, the "lateral fit" succeeds at describing the lateral variability of eddy viscosity over a wide range of Ri. The modifications proposed to Ri-dependent eddy viscosity parameterizations allow applicability to stratified coastal regions, particularly in wide estuaries, without requiring implementation of a numerical model.

Modeling the energy balance in Marseille: Sensitivity to roughness length parameterizations and thermal admittance

Science.gov (United States)

Demuzere, M.; De Ridder, K.; van Lipzig, N. P. M.

2008-08-01

During the ESCOMPTE campaign (Experience sur Site pour COntraindre les Modeles de Pollution atmospherique et de Transport d'Emissions), a 4-day intensive observation period was selected to evaluate the Advanced Regional Prediction System (ARPS), a nonhydrostatic meteorological mesoscale model that was optimized with a parameterization for thermal roughness length to better represent urban surfaces. The evaluation shows that the ARPS model is able to correctly reproduce temperature, wind speed, and direction for one urban and two rural measurements stations. Furthermore, simulated heat fluxes show good agreement compared to the observations, although simulated sensible heat fluxes were initially too low for the urban stations. In order to improve the latter, different roughness length parameterization schemes were tested, combined with various thermal admittance values. This sensitivity study showed that the Zilitinkevich scheme combined with and intermediate value of thermal admittance performs best.

The Community Earth System Model-Polar Climate Working Group and the status of CESM2.

Science.gov (United States)

Bailey, D. A.; Holland, M. M.; DuVivier, A. K.

2017-12-01

The Polar Climate Working Group (PCWG) is a consortium of scientists who are interested in modeling and understanding the climate in the Arctic and the Antarctic, and how polar climate processes interact with and influence climate at lower latitudes. Our members come from universities and laboratories, and our interests span all elements of polar climate, from the ocean depths to the top of the atmosphere. In addition to conducting scientific modeling experiments, we are charged with contributing to the development and maintenance of the state-of-the-art sea ice model component (CICE) used in the Community Earth System Model (CESM). A recent priority for the PCWG has been to come up with innovative ways to bring the observational and modeling communities together. This will allow for more robust validation of climate model simulations, the development and implementation of more physically-based model parameterizations, improved data assimilation capabilities, and the better use of models to design and implement field experiments. These have been informed by topical workshops and scientific visitors that we have hosted in these areas. These activities will be discussed and information on how the better integration of observations and models has influenced the new version of the CESM, which is due to be released in late 2017, will be provided. Additionally, we will address how enhanced interactions with the observational community will contribute to model developments and validation moving forward.

Climate stability and sensitivity in some simple conceptual models

Energy Technology Data Exchange (ETDEWEB)

Bates, J. Ray [University College Dublin, Meteorology and Climate Centre, School of Mathematical Sciences, Dublin (Ireland)

2012-02-15

A theoretical investigation of climate stability and sensitivity is carried out using three simple linearized models based on the top-of-the-atmosphere energy budget. The simplest is the zero-dimensional model (ZDM) commonly used as a conceptual basis for climate sensitivity and feedback studies. The others are two-zone models with tropics and extratropics of equal area; in the first of these (Model A), the dynamical heat transport (DHT) between the zones is implicit, in the second (Model B) it is explicitly parameterized. It is found that the stability and sensitivity properties of the ZDM and Model A are very similar, both depending only on the global-mean radiative response coefficient and the global-mean forcing. The corresponding properties of Model B are more complex, depending asymmetrically on the separate tropical and extratropical values of these quantities, as well as on the DHT coefficient. Adopting Model B as a benchmark, conditions are found under which the validity of the ZDM and Model A as climate sensitivity models holds. It is shown that parameter ranges of physical interest exist for which such validity may not hold. The 2 x CO{sub 2} sensitivities of the simple models are studied and compared. Possible implications of the results for sensitivities derived from GCMs and palaeoclimate data are suggested. Sensitivities for more general scenarios that include negative forcing in the tropics (due to aerosols, inadvertent or geoengineered) are also studied. Some unexpected outcomes are found in this case. These include the possibility of a negative global-mean temperature response to a positive global-mean forcing, and vice versa. (orig.)

Modeling transport of nutrients & sediment loads into Lake Tahoe under climate change

Science.gov (United States)

Riverson, John; Coats, Robert; Costa-Cabral, Mariza; Dettinger, Mike; Reuter, John; Sahoo, Goloka; Schladow, Geoffrey

2013-01-01

The outputs from two General Circulation Models (GCMs) with two emissions scenarios were downscaled and bias-corrected to develop regional climate change projections for the Tahoe Basin. For one model—the Geophysical Fluid Dynamics Laboratory or GFDL model—the daily model results were used to drive a distributed hydrologic model. The watershed model used an energy balance approach for computing evapotranspiration and snowpack dynamics so that the processes remain a function of the climate change projections. For this study, all other aspects of the model (i.e. land use distribution, routing configuration, and parameterization) were held constant to isolate impacts of climate change projections. The results indicate that (1) precipitation falling as rain rather than snow will increase, starting at the current mean snowline, and moving towards higher elevations over time; (2) annual accumulated snowpack will be reduced; (3) snowpack accumulation will start later; and (4) snowmelt will start earlier in the year. Certain changes were masked (or counter-balanced) when summarized as basin-wide averages; however, spatial evaluation added notable resolution. While rainfall runoff increased at higher elevations, a drop in total precipitation volume decreased runoff and fine sediment load from the lower elevation meadow areas and also decreased baseflow and nitrogen loads basin-wide. This finding also highlights the important role that the meadow areas could play as high-flow buffers under climatic change. Because the watershed model accounts for elevation change and variable meteorological patterns, it provided a robust platform for evaluating the impacts of projected climate change on hydrology and water quality.

An ARM data-oriented diagnostics package to evaluate the climate model simulation

Science.gov (United States)

Zhang, C.; Xie, S.

2016-12-01

A set of diagnostics that utilize long-term high frequency measurements from the DOE Atmospheric Radiation Measurement (ARM) program is developed for evaluating the regional simulation of clouds, radiation and precipitation in climate models. The diagnostics results are computed and visualized automatically in a python-based package that aims to serve as an easy entry point for evaluating climate simulations using the ARM data, as well as the CMIP5 multi-model simulations. Basic performance metrics are computed to measure the accuracy of mean state and variability of simulated regional climate. The evaluated physical quantities include vertical profiles of clouds, temperature, relative humidity, cloud liquid water path, total column water vapor, precipitation, sensible and latent heat fluxes, radiative fluxes, aerosol and cloud microphysical properties. Process-oriented diagnostics focusing on individual cloud and precipitation-related phenomena are developed for the evaluation and development of specific model physical parameterizations. Application of the ARM diagnostics package will be presented in the AGU session. This work is performed under the auspices of the U.S. Department of Energy by Lawrence Livermore National Laboratory under Contract DE-AC52-07NA27344, IM release number is: LLNL-ABS-698645.

Parameterized post-Newtonian cosmology

International Nuclear Information System (INIS)

Sanghai, Viraj A A; Clifton, Timothy

2017-01-01

Einstein’s theory of gravity has been extensively tested on solar system scales, and for isolated astrophysical systems, using the perturbative framework known as the parameterized post-Newtonian (PPN) formalism. This framework is designed for use in the weak-field and slow-motion limit of gravity, and can be used to constrain a large class of metric theories of gravity with data collected from the aforementioned systems. Given the potential of future surveys to probe cosmological scales to high precision, it is a topic of much contemporary interest to construct a similar framework to link Einstein’s theory of gravity and its alternatives to observations on cosmological scales. Our approach to this problem is to adapt and extend the existing PPN formalism for use in cosmology. We derive a set of equations that use the same parameters to consistently model both weak fields and cosmology. This allows us to parameterize a large class of modified theories of gravity and dark energy models on cosmological scales, using just four functions of time. These four functions can be directly linked to the background expansion of the universe, first-order cosmological perturbations, and the weak-field limit of the theory. They also reduce to the standard PPN parameters on solar system scales. We illustrate how dark energy models and scalar-tensor and vector-tensor theories of gravity fit into this framework, which we refer to as ‘parameterized post-Newtonian cosmology’ (PPNC). (paper)

Parameterized post-Newtonian cosmology

Science.gov (United States)

Sanghai, Viraj A. A.; Clifton, Timothy

2017-03-01

Einstein’s theory of gravity has been extensively tested on solar system scales, and for isolated astrophysical systems, using the perturbative framework known as the parameterized post-Newtonian (PPN) formalism. This framework is designed for use in the weak-field and slow-motion limit of gravity, and can be used to constrain a large class of metric theories of gravity with data collected from the aforementioned systems. Given the potential of future surveys to probe cosmological scales to high precision, it is a topic of much contemporary interest to construct a similar framework to link Einstein’s theory of gravity and its alternatives to observations on cosmological scales. Our approach to this problem is to adapt and extend the existing PPN formalism for use in cosmology. We derive a set of equations that use the same parameters to consistently model both weak fields and cosmology. This allows us to parameterize a large class of modified theories of gravity and dark energy models on cosmological scales, using just four functions of time. These four functions can be directly linked to the background expansion of the universe, first-order cosmological perturbations, and the weak-field limit of the theory. They also reduce to the standard PPN parameters on solar system scales. We illustrate how dark energy models and scalar-tensor and vector-tensor theories of gravity fit into this framework, which we refer to as ‘parameterized post-Newtonian cosmology’ (PPNC).

A Simple Approach to Account for Climate Model Interdependence in Multi-Model Ensembles

Science.gov (United States)

Herger, N.; Abramowitz, G.; Angelil, O. M.; Knutti, R.; Sanderson, B.

2016-12-01

Multi-model ensembles are an indispensable tool for future climate projection and its uncertainty quantification. Ensembles containing multiple climate models generally have increased skill, consistency and reliability. Due to the lack of agreed-on alternatives, most scientists use the equally-weighted multi-model mean as they subscribe to model democracy ("one model, one vote").Different research groups are known to share sections of code, parameterizations in their model, literature, or even whole model components. Therefore, individual model runs do not represent truly independent estimates. Ignoring this dependence structure might lead to a false model consensus, wrong estimation of uncertainty and effective number of independent models.Here, we present a way to partially address this problem by selecting a subset of CMIP5 model runs so that its climatological mean minimizes the RMSE compared to a given observation product. Due to the cancelling out of errors, regional biases in the ensemble mean are reduced significantly.Using a model-as-truth experiment we demonstrate that those regional biases persist into the future and we are not fitting noise, thus providing improved observationally-constrained projections of the 21st century. The optimally selected ensemble shows significantly higher global mean surface temperature projections than the original ensemble, where all the model runs are considered. Moreover, the spread is decreased well beyond that expected from the decreased ensemble size.Several previous studies have recommended an ensemble selection approach based on performance ranking of the model runs. Here, we show that this approach can perform even worse than randomly selecting ensemble members and can thus be harmful. We suggest that accounting for interdependence in the ensemble selection process is a necessary step for robust projections for use in impact assessments, adaptation and mitigation of climate change.

Parameterized combinatorial geometry modeling in Moritz

International Nuclear Information System (INIS)

Van Riper, K.A.

2005-01-01

We describe the use of named variables as surface and solid body coefficients in the Moritz geometry editing program. Variables can also be used as material numbers, cell densities, and transformation values. A variable is defined as a constant or an arithmetic combination of constants and other variables. A variable reference, such as in a surface coefficient, can be a single variable or an expression containing variables and constants. Moritz can read and write geometry models in MCNP and ITS ACCEPT format; support for other codes will be added. The geometry can be saved with either the variables in place, for modifying the models in Moritz, or with the variables evaluated for use in the transport codes. A program window shows a list of variables and provides fields for editing them. Surface coefficients and other values that use a variable reference are shown in a distinctive style on object property dialogs; associated buttons show fields for editing the reference. We discuss our use of variables in defining geometry models for shielding studies in PET clinics. When a model is parameterized through the use of variables, changes such as room dimensions, shielding layer widths, and cell compositions can be quickly achieved by changing a few numbers without requiring knowledge of the input syntax for the transport code or the tedious and error prone work of recalculating many surface or solid body coefficients. (author)

New insight of Arctic cloud parameterization from regional climate model simulations, satellite-based, and drifting station data

Science.gov (United States)

Klaus, D.; Dethloff, K.; Dorn, W.; Rinke, A.; Wu, D. L.

2016-05-01

Cloud observations from the CloudSat and CALIPSO satellites helped to explain the reduced total cloud cover (Ctot) in the atmospheric regional climate model HIRHAM5 with modified cloud physics. Arctic climate conditions are found to be better reproduced with (1) a more efficient Bergeron-Findeisen process and (2) a more generalized subgrid-scale variability of total water content. As a result, the annual cycle of Ctot is improved over sea ice, associated with an almost 14% smaller area average than in the control simulation. The modified cloud scheme reduces the Ctot bias with respect to the satellite observations. Except for autumn, the cloud reduction over sea ice improves low-level temperature profiles compared to drifting station data. The HIRHAM5 sensitivity study highlights the need for improving accuracy of low-level (<700 m) cloud observations, as these clouds exert a strong impact on the near-surface climate.

Improving the representation of river-groundwater interactions in land surface modeling at the regional scale: Observational evidence and parameterization applied in the Community Land Model

KAUST Repository

Zampieri, Matteo

2012-02-01

Groundwater is an important component of the hydrological cycle, included in many land surface models to provide a lower boundary condition for soil moisture, which in turn plays a key role in the land-vegetation-atmosphere interactions and the ecosystem dynamics. In regional-scale climate applications land surface models (LSMs) are commonly coupled to atmospheric models to close the surface energy, mass and carbon balance. LSMs in these applications are used to resolve the momentum, heat, water and carbon vertical fluxes, accounting for the effect of vegetation, soil type and other surface parameters, while lack of adequate resolution prevents using them to resolve horizontal sub-grid processes. Specifically, LSMs resolve the large-scale runoff production associated with infiltration excess and sub-grid groundwater convergence, but they neglect the effect from loosing streams to groundwater. Through the analysis of observed data of soil moisture obtained from the Oklahoma Mesoscale Network stations and land surface temperature derived from MODIS we provide evidence that the regional scale soil moisture and surface temperature patterns are affected by the rivers. This is demonstrated on the basis of simulations from a land surface model (i.e., Community Land Model - CLM, version 3.5). We show that the model cannot reproduce the features of the observed soil moisture and temperature spatial patterns that are related to the underlying mechanism of reinfiltration of river water to groundwater. Therefore, we implement a simple parameterization of this process in CLM showing the ability to reproduce the soil moisture and surface temperature spatial variabilities that relate to the river distribution at regional scale. The CLM with this new parameterization is used to evaluate impacts of the improved representation of river-groundwater interactions on the simulated water cycle parameters and the surface energy budget at the regional scale. © 2011 Elsevier B.V.

Evaluation of the regional climate response in Australia to large-scale climate modes in the historical NARCliM simulations

Science.gov (United States)

Fita, L.; Evans, J. P.; Argüeso, D.; King, A.; Liu, Y.

2017-10-01

NARCliM (New South Wales (NSW)/Australian Capital Territory (ACT) Regional Climate Modelling project) is a regional climate modeling project for the Australian area. It is providing a comprehensive dynamically downscaled climate dataset for the CORDEX-AustralAsia region at 50-km resolution, and south-East Australia at a resolution of 10 km. The first phase of NARCliM produced 60-year long reanalysis driven regional simulations to allow evaluation of the regional model performance. This long control period (1950-2009) was used so that the model ability to capture the impact of large scale climate modes on Australian climate could be examined. Simulations are evaluated using a gridded observational dataset. Results show that using model independence as a criteria for choosing atmospheric model configuration from different possible sets of parameterizations may contribute to the regional climate models having different overall biases. The regional models generally capture the regional climate response to large-scale modes better than the driving reanalysis, though no regional model improves on all aspects of the simulated climate.

Parameterization analysis and inversion for orthorhombic media

KAUST Repository

Masmoudi, Nabil

2018-05-01

Accounting for azimuthal anisotropy is necessary for the processing and inversion of wide-azimuth and wide-aperture seismic data because wave speeds naturally depend on the wave propagation direction. Orthorhombic anisotropy is considered the most effective anisotropic model that approximates the azimuthal anisotropy we observe in seismic data. In the framework of full wave form inversion (FWI), the large number of parameters describing orthorhombic media exerts a considerable trade-off and increases the non-linearity of the inversion problem. Choosing a suitable parameterization for the model, and identifying which parameters in that parameterization could be well resolved, are essential to a successful inversion. In this thesis, I derive the radiation patterns for different acoustic orthorhombic parameterization. Analyzing the angular dependence of the scattering of the parameters of different parameterizations starting with the conventionally used notation, I assess the potential trade-off between the parameters and the resolution in describing the data and inverting for the parameters. In order to build practical inversion strategies, I suggest new parameters (called deviation parameters) for a new parameterization style in orthorhombic media. The novel parameters denoted ∈d, ƞd and δd are dimensionless and represent a measure of deviation between the vertical planes in orthorhombic anisotropy. The main feature of the deviation parameters consists of keeping the scattering of the vertical transversely isotropic (VTI) parameters stationary with azimuth. Using these scattering features, we can condition FWI to invert for the parameters which the data are sensitive to, at different stages, scales, and locations in the model. With this parameterization, the data are mainly sensitive to the scattering of 3 parameters (out of six that describe an acoustic orthorhombic medium): the horizontal velocity in the x1 direction, ∈1 which provides scattering mainly near

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.

Science.gov (United States)

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

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

Science.gov (United States)

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.

Parameterizing Size Distribution in Ice Clouds

Energy Technology Data Exchange (ETDEWEB)

DeSlover, Daniel; Mitchell, David L.

2009-09-25

PARAMETERIZING SIZE DISTRIBUTIONS IN ICE CLOUDS David L. Mitchell and Daniel H. DeSlover ABSTRACT An outstanding problem that contributes considerable uncertainty to Global Climate Model (GCM) predictions of future climate is the characterization of ice particle sizes in cirrus clouds. Recent parameterizations of ice cloud effective diameter differ by a factor of three, which, for overcast conditions, often translate to changes in outgoing longwave radiation (OLR) of 55 W m-2 or more. Much of this uncertainty in cirrus particle sizes is related to the problem of ice particle shattering during in situ sampling of the ice particle size distribution (PSD). Ice particles often shatter into many smaller ice fragments upon collision with the rim of the probe inlet tube. These small ice artifacts are counted as real ice crystals, resulting in anomalously high concentrations of small ice crystals (D < 100 µm) and underestimates of the mean and effective size of the PSD. Half of the cirrus cloud optical depth calculated from these in situ measurements can be due to this shattering phenomenon. Another challenge is the determination of ice and liquid water amounts in mixed phase clouds. Mixed phase clouds in the Arctic contain mostly liquid water, and the presence of ice is important for determining their lifecycle. Colder high clouds between -20 and -36 oC may also be mixed phase but in this case their condensate is mostly ice with low levels of liquid water. Rather than affecting their lifecycle, the presence of liquid dramatically affects the cloud optical properties, which affects cloud-climate feedback processes in GCMs. This project has made advancements in solving both of these problems. Regarding the first problem, PSD in ice clouds are uncertain due to the inability to reliably measure the concentrations of the smallest crystals (D < 100 µm), known as the “small mode”. Rather than using in situ probe measurements aboard aircraft, we employed a treatment of ice

On the usage of classical nucleation theory in predicting the impact of bacteria on weather and climate

Science.gov (United States)

Sahyoun, Maher; Woetmann Nielsen, Niels; Havskov Sørensen, Jens; Finster, Kai; Bay Gosewinkel Karlson, Ulrich; Šantl-Temkiv, Tina; Smith Korsholm, Ulrik

2014-05-01

Bacteria, e.g. Pseudomonas syringae, have previously been found efficient in nucleating ice heterogeneously at temperatures close to -2°C in laboratory tests. Therefore, ice nucleation active (INA) bacteria may be involved in the formation of precipitation in mixed phase clouds, and could potentially influence weather and climate. Investigations into the impact of INA bacteria on climate have shown that emissions were too low to significantly impact the climate (Hoose et al., 2010). The goal of this study is to clarify the reason for finding the marginal impact on climate when INA bacteria were considered, by investigating the usability of ice nucleation rate parameterization based on classical nucleation theory (CNT). For this purpose, two parameterizations of heterogeneous ice nucleation were compared. Both parameterizations were implemented and tested in a 1-d version of the operational weather model (HIRLAM) (Lynch et al., 2000; Unden et al., 2002) in two different meteorological cases. The first parameterization is based on CNT and denoted CH08 (Chen et al., 2008). This parameterization is a function of temperature and the size of the IN. The second parameterization, denoted HAR13, was derived from nucleation measurements of SnomaxTM (Hartmann et al., 2013). It is a function of temperature and the number of protein complexes on the outer membranes of the cell. The fraction of cloud droplets containing each type of IN as percentage in the cloud droplets population were used and the sensitivity of cloud ice production in each parameterization was compared. In this study, HAR13 produces more cloud ice and precipitation than CH08 when the bacteria fraction increases. In CH08, the increase of the bacteria fraction leads to decreasing the cloud ice mixing ratio. The ice production using HAR13 was found to be more sensitive to the change of the bacterial fraction than CH08 which did not show a similar sensitivity. As a result, this may explain the marginal impact of

Assessing and Upgrading Ocean Mixing for the Study of Climate Change

Science.gov (United States)

Howard, A. M.; Fells, J.; Lindo, F.; Tulsee, V.; Canuto, V.; Cheng, Y.; Dubovikov, M. S.; Leboissetier, A.

2016-12-01

Climate is critical. Climate variability affects us all; Climate Change is a burning issue. Droughts, floods, other extreme events, and Global Warming's effects on these and problems such as sea-level rise and ecosystem disruption threaten lives. Citizens must be informed to make decisions concerning climate such as "business as usual" vs. mitigating emissions to keep warming within bounds. Medgar Evers undergraduates aid NASA research while learning climate science and developing computer&math skills. To make useful predictions we must realistically model each component of the climate system, including the ocean, whose critical role includes transporting&storing heat and dissolved CO2. We need physically based parameterizations of key ocean processes that can't be put explicitly in a global climate model, e.g. vertical&lateral mixing. The NASA-GISS turbulence group uses theory to model mixing including: 1) a comprehensive scheme for small scale vertical mixing, including convection&shear, internal waves & double-diffusion, and bottom tides 2) a new parameterization for the lateral&vertical mixing by mesoscale eddies. For better understanding we write our own programs. To assess the modelling MATLAB programs visualize and calculate statistics, including means, standard deviations and correlations, on NASA-GISS OGCM output with different mixing schemes and help us study drift from observations. We also try to upgrade the schemes, e.g. the bottom tidal mixing parameterizations' roughness, calculated from high resolution topographic data using Gaussian weighting functions with cut-offs. We study the effects of their parameters to improve them. A FORTRAN program extracts topography data subsets of manageable size for a MATLAB program, tested on idealized cases, to visualize&calculate roughness on. Students are introduced to modeling a complex system, gain a deeper appreciation of climate science, programming skills and familiarity with MATLAB, while furthering climate

A Caveat Note on Tuning in the Development of Coupled Climate Models

Science.gov (United States)

Dommenget, Dietmar; Rezny, Michael

2018-01-01

State-of-the-art coupled general circulation models (CGCMs) have substantial errors in their simulations of climate. In particular, these errors can lead to large uncertainties in the simulated climate response (both globally and regionally) to a doubling of CO2. Currently, tuning of the parameterization schemes in CGCMs is a significant part of the developed. It is not clear whether such tuning actually improves models. The tuning process is (in general) neither documented, nor reproducible. Alternative methods such as flux correcting are not used nor is it clear if such methods would perform better. In this study, ensembles of perturbed physics experiments are performed with the Globally Resolved Energy Balance (GREB) model to test the impact of tuning. The work illustrates that tuning has, in average, limited skill given the complexity of the system, the limited computing resources, and the limited observations to optimize parameters. While tuning may improve model performance (such as reproducing observed past climate), it will not get closer to the "true" physics nor will it significantly improve future climate change projections. Tuning will introduce artificial compensating error interactions between submodels that will hamper further model development. In turn, flux corrections do perform well in most, but not all aspects. A main advantage of flux correction is that it is much cheaper, simpler, more transparent, and it does not introduce artificial error interactions between submodels. These GREB model experiments should be considered as a pilot study to motivate further CGCM studies that address the issues of model tuning.

Large-scale tropospheric transport in the Chemistry-Climate Model Initiative (CCMI) simulations

Science.gov (United States)

Orbe, Clara; Yang, Huang; Waugh, Darryn W.; Zeng, Guang; Morgenstern, Olaf; Kinnison, Douglas E.; Lamarque, Jean-Francois; Tilmes, Simone; Plummer, David A.; Scinocca, John F.; Josse, Beatrice; Marecal, Virginie; Jöckel, Patrick; Oman, Luke D.; Strahan, Susan E.; Deushi, Makoto; Tanaka, Taichu Y.; Yoshida, Kohei; Akiyoshi, Hideharu; Yamashita, Yousuke; Stenke, Andreas; Revell, Laura; Sukhodolov, Timofei; Rozanov, Eugene; Pitari, Giovanni; Visioni, Daniele; Stone, Kane A.; Schofield, Robyn; Banerjee, Antara

2018-05-01

Understanding and modeling the large-scale transport of trace gases and aerosols is important for interpreting past (and projecting future) changes in atmospheric composition. Here we show that there are large differences in the global-scale atmospheric transport properties among the models participating in the IGAC SPARC Chemistry-Climate Model Initiative (CCMI). Specifically, we find up to 40 % differences in the transport timescales connecting the Northern Hemisphere (NH) midlatitude surface to the Arctic and to Southern Hemisphere high latitudes, where the mean age ranges between 1.7 and 2.6 years. We show that these differences are related to large differences in vertical transport among the simulations, in particular to differences in parameterized convection over the oceans. While stronger convection over NH midlatitudes is associated with slower transport to the Arctic, stronger convection in the tropics and subtropics is associated with faster interhemispheric transport. We also show that the differences among simulations constrained with fields derived from the same reanalysis products are as large as (and in some cases larger than) the differences among free-running simulations, most likely due to larger differences in parameterized convection. Our results indicate that care must be taken when using simulations constrained with analyzed winds to interpret the influence of meteorology on tropospheric composition.

Large-scale tropospheric transport in the Chemistry–Climate Model Initiative (CCMI simulations

Directory of Open Access Journals (Sweden)

C. Orbe

2018-05-01

Full Text Available Understanding and modeling the large-scale transport of trace gases and aerosols is important for interpreting past (and projecting future changes in atmospheric composition. Here we show that there are large differences in the global-scale atmospheric transport properties among the models participating in the IGAC SPARC Chemistry–Climate Model Initiative (CCMI. Specifically, we find up to 40 % differences in the transport timescales connecting the Northern Hemisphere (NH midlatitude surface to the Arctic and to Southern Hemisphere high latitudes, where the mean age ranges between 1.7 and 2.6 years. We show that these differences are related to large differences in vertical transport among the simulations, in particular to differences in parameterized convection over the oceans. While stronger convection over NH midlatitudes is associated with slower transport to the Arctic, stronger convection in the tropics and subtropics is associated with faster interhemispheric transport. We also show that the differences among simulations constrained with fields derived from the same reanalysis products are as large as (and in some cases larger than the differences among free-running simulations, most likely due to larger differences in parameterized convection. Our results indicate that care must be taken when using simulations constrained with analyzed winds to interpret the influence of meteorology on tropospheric composition.

Final scientific report for DOE award title: Improving the Representation of Ice Sedimentation Rates in Global Climate Models

Energy Technology Data Exchange (ETDEWEB)

Mitchell, David L. [Desert Research Institute, Reno, NV (United States)

2013-09-05

It is well known that cirrus clouds play a major role in regulating the earth’s climate, but the details of how this works are just beginning to be understood. This project targeted the main property of cirrus clouds that influence climate processes; the ice fall speed. That is, this project improves the representation of the mass-weighted ice particle fall velocity, V_m, in climate models, used to predict future climate on global and regional scales. Prior to 2007, the dominant sizes of ice particles in cirrus clouds were poorly understood, making it virtually impossible to predict how cirrus clouds interact with sunlight and thermal radiation. Due to several studies investigating the performance of optical probes used to measure the ice particle size distribution (PSD), as well as the remote sensing results from our last ARM project, it is now well established that the anomalously high concentrations of small ice crystals often reported prior to 2007 were measurement artifacts. Advances in the design and data processing of optical probes have greatly reduced these ice artifacts that resulted from the shattering of ice particles on the probe tips and/or inlet tube, and PSD measurements from one of these improved probes (the 2-dimensional Stereo or 2D-S probe) are utilized in this project to parameterize V_m for climate models. Our original plan in the proposal was to parameterize the ice PSD (in terms of temperature and ice water content) and ice particle mass and projected area (in terms of mass- and area-dimensional power laws or m-D/A-D expressions) since these are the microphysical properties that determine V_m, and then proceed to calculate V_m from these parameterized properties. But the 2D-S probe directly measures ice particle projected area and indirectly estimates ice particle mass for each size bin. It soon became apparent that the original plan would introduce more uncertainty in the V_m calculations

On the use of nudging techniques for regional climate modeling: application for tropical convection

Science.gov (United States)

Pohl, Benjamin; Crétat, Julien

2014-09-01

Using a large set of WRF ensemble simulations at 70-km horizontal resolution over a domain encompassing the Warm Pool region and its surroundings [45°N-45°S, 10°E-240°E], this study aims at quantifying how nudging techniques can modify the simulation of deep atmospheric convection. Both seasonal mean climate, transient variability at intraseasonal timescales, and the respective weight of internal (stochastic) and forced (reproducible) variability are considered. Sensitivity to a large variety of nudging settings (nudged variables and layers and nudging strength) and to the model physics (using 3 convective parameterizations) is addressed. Integrations are carried out during a 7-month season characterized by neutral background conditions and strong intraseasonal variability. Results show that (1) the model responds differently to the nudging from one parameterization to another. Biases are decreased by ~50 % for Betts-Miller-Janjic convection against 17 % only for Grell-Dévényi, the scheme producing yet the largest biases; (2) relaxing air temperature is the most efficient way to reduce biases, while nudging the wind increases most co-variability with daily observations; (3) the model's internal variability is drastically reduced and mostly depends on the nudging strength and nudged variables; (4) interrupting the relaxation before the end of the simulations leads to an abrupt convergence towards the model's natural solution, with no clear effects on the simulated climate after a few days. The usefulness and limitations of the approach are finally discussed through the example of the Madden-Julian Oscillation, that the model fails at simulating and that can be artificially and still imperfectly reproduced in relaxation experiments.

Framework of cloud parameterization including ice for 3-D mesoscale models

Energy Technology Data Exchange (ETDEWEB)

Levkov, L; Jacob, D; Eppel, D; Grassl, H

1989-01-01

A parameterization scheme for the simulation of ice in clouds incorporated into the hydrostatic version of the GKSS three-dimensional mesoscale model. Numerical simulations of precipitation are performed: over the Northe Sea, the Hawaiian trade wind area and in the region of the intertropical convergence zone. Not only some major features of convective structures in all three areas but also cloud-aerosol interactions have successfully been simulated. (orig.) With 19 figs., 2 tabs.

Automatic Parameterization Strategy for Cardiac Electrophysiology Simulations.

Science.gov (United States)

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.

Large-eddy simulation of stable atmospheric boundary layers to develop better turbulence closures for climate and weather models

Science.gov (United States)

Bou-Zeid, Elie; Huang, Jing; Golaz, Jean-Christophe

2011-11-01

A disconnect remains between our improved physical understanding of boundary layers stabilized by buoyancy and how we parameterize them in coarse atmospheric models. Most operational climate models require excessive turbulence mixing in such conditions to prevent decoupling of the atmospheric component from the land component, but the performance of such a model is unlikely to be satisfactory under weakly and moderately stable conditions. Using Large-eddy simulation, we revisit some of the basic challenges in parameterizing stable atmospheric boundary layers: eddy-viscosity closure is found to be more reliable due to an improved alignment of vertical Reynolds stresses and mean strains under stable conditions, but the dependence of the magnitude of the eddy viscosity on stability is not well represented by several models tested here. Thus, we propose a new closure that reproduces the different stability regimes better. Subsequently, tests of this model in the GFDL's single-column model (SCM) are found to yield good agreement with LES results in idealized steady-stability cases, as well as in cases with gradual and sharp changes of stability with time.

A Semi-empirical Model of the Stratosphere in the Climate System

Science.gov (United States)

Sodergren, A. H.; Bodeker, G. E.; Kremser, S.; Meinshausen, M.; McDonald, A.

2014-12-01

Chemistry climate models (CCMs) currently used to project changes in Antarctic ozone are extremely computationally demanding. CCM projections are uncertain due to lack of knowledge of future emissions of greenhouse gases (GHGs) and ozone depleting substances (ODSs), as well as parameterizations within the CCMs that have weakly constrained tuning parameters. While projections should be based on an ensemble of simulations, this is not currently possible due to the complexity of the CCMs. An inexpensive but realistic approach to simulate changes in stratospheric ozone, and its coupling to the climate system, is needed as a complement to CCMs. A simple climate model (SCM) can be used as a fast emulator of complex atmospheric-ocean climate models. If such an SCM includes a representation of stratospheric ozone, the evolution of the global ozone layer can be simulated for a wide range of GHG and ODS emissions scenarios. MAGICC is an SCM used in previous IPCC reports. In the current version of the MAGICC SCM, stratospheric ozone changes depend only on equivalent effective stratospheric chlorine (EESC). In this work, MAGICC is extended to include an interactive stratospheric ozone layer using a semi-empirical model of ozone responses to CO2and EESC, with changes in ozone affecting the radiative forcing in the SCM. To demonstrate the ability of our new, extended SCM to generate projections of global changes in ozone, tuning parameters from 19 coupled atmosphere-ocean general circulation models (AOGCMs) and 10 carbon cycle models (to create an ensemble of 190 simulations) have been used to generate probability density functions of the dates of return of stratospheric column ozone to 1960 and 1980 levels for different latitudes.

High-Latitude Stratospheric Sensitivity to QBO Width in a Chemistry-Climate Model with Parameterized Ozone Chemistry

Science.gov (United States)

Hurwitz, M. M.; Braesicke, P.; Pyle, J. A.

2010-01-01

In a pair of idealized simulations with a simplified chemistry-climate model, the sensitivity of the wintertime Arctic stratosphere to variability in the width of the quasi-biennial oscillation (QBO) is assessed. The width of the QBO appears to have equal influence on the Arctic stratosphere as does the phase (i.e. the Holton-Tan mechanism). In the model, a wider QBO acts like a preferential shift toward the easterly phase of the QBO, where zonal winds at 60 N tend to be relatively weaker, while 50 hPa geopotential heights and polar ozone values tend to be higher.

Validation of the Regional Climate Model ALARO with different dynamical downscaling approaches and different horizontal resolutions

Science.gov (United States)

Berckmans, Julie; Hamdi, Rafiq; De Troch, Rozemien; Giot, Olivier

2015-04-01

At the Royal Meteorological Institute of Belgium (RMI), climate simulations are performed with the regional climate model (RCM) ALARO, a version of the ALADIN model with improved physical parameterizations. In order to obtain high-resolution information of the regional climate, lateral bounary conditions (LBC) are prescribed from the global climate model (GCM) ARPEGE. Dynamical downscaling is commonly done in a continuous long-term simulation, with the initialisation of the model at the start and driven by the regularly updated LBCs of the GCM. Recently, more interest exists in the dynamical downscaling approach of frequent reinitializations of the climate simulations. For these experiments, the model is initialised daily and driven for 24 hours by the GCM. However, the surface is either initialised daily together with the atmosphere or free to evolve continuously. The surface scheme implemented in ALARO is SURFEX, which can be either run in coupled mode or in stand-alone mode. The regional climate is simulated on different domains, on a 20km horizontal resolution over Western-Europe and a 4km horizontal resolution over Belgium. Besides, SURFEX allows to perform a stand-alone or offline simulation on 1km horizontal resolution over Belgium. This research is in the framework of the project MASC: "Modelling and Assessing Surface Change Impacts on Belgian and Western European Climate", a 4-year project funded by the Belgian Federal Government. The overall aim of the project is to study the feedbacks between climate changes and land surface changes in order to improve regional climate model projections at the decennial scale over Belgium and Western Europe and thus to provide better climate projections and climate change evaluation tools to policy makers, stakeholders and the scientific community.

Parameterizing Coefficients of a POD-Based Dynamical System

Science.gov (United States)

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

Parameterized Analysis of Paging and List Update Algorithms

DEFF Research Database (Denmark)

Dorrigiv, Reza; Ehmsen, Martin R.; López-Ortiz, Alejandro

2015-01-01

that a larger cache leads to a better performance. We also apply the parameterized analysis framework to list update and show that certain randomized algorithms which are superior to MTF in the classical model are not so in the parameterized case, which matches experimental results....... set model and express the performance of well known algorithms in terms of this parameter. This explicitly introduces parameterized-style analysis to online algorithms. The idea is that rather than normalizing the performance of an online algorithm by an (optimal) offline algorithm, we explicitly...... express the behavior of the algorithm in terms of two more natural parameters: the size of the cache and Denning’s working set measure. This technique creates a performance hierarchy of paging algorithms which better reflects their experimentally observed relative strengths. It also reflects the intuition...

Usage of Parameterized Fatigue Spectra and Physics-Based Systems Engineering Models for Wind Turbine Component Sizing: Preprint

Energy Technology Data Exchange (ETDEWEB)

Parsons, Taylor; Guo, Yi; Veers, Paul; Dykes, Katherine; Damiani, Rick

2016-01-26

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 spectrum 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.

Evaluation of regional climate simulations over the Great Lakes region driven by three global data sets

Science.gov (United States)

Shiyuan Zhong; Xiuping Li; Xindi Bian; Warren E. Heilman; L. Ruby Leung; William I. Jr. Gustafson

2012-01-01

The performance of regional climate simulations is evaluated for the Great Lakes region. Three 10-year (1990-1999) current-climate simulations are performed using the MM5 regional climate model (RCM) with 36-km horizontal resolution. The simulations employed identical configuration and physical parameterizations, but different lateral boundary conditions and sea-...

Improved parameterization of managed grassland in a global process-based vegetation model using Bayesian statistics

Science.gov (United States)

Rolinski, S.; Müller, C.; Lotze-Campen, H.; Bondeau, A.

2010-12-01

More than a quarter of the Earth’s land surface is covered by grassland, which is also the major part (~ 70 %) of the agricultural area. Most of this area is used for livestock production in different degrees of intensity. The dynamic global vegetation model LPJmL (Sitch et al., Global Change Biology, 2003; Bondeau et al., Global Change Biology, 2007) is one of few process-based model that simulates biomass production on managed grasslands at the global scale. The implementation of managed grasslands and its evaluation has received little attention so far, as reference data on grassland productivity are scarce and the definition of grassland extent and usage are highly uncertain. However, grassland productivity is related to large areas, and strongly influences global estimates of carbon and water budgets and should thus be improved. Plants are implemented in LPJmL in an aggregated form as plant functional types assuming that processes concerning carbon and water fluxes are quite similar between species of the same type. Therefore, the parameterization of a functional type is possible with parameters in a physiologically meaningful range of values. The actual choice of the parameter values from the possible and reasonable phase space should satisfy the condition of the best fit of model results and measured data. In order to improve the parameterization of managed grass we follow a combined procedure using model output and measured data of carbon and water fluxes. By comparing carbon and water fluxes simultaneously, we expect well-balanced refinements and avoid over-tuning of the model in only one direction. The comparison of annual biomass from grassland to data from the Food and Agriculture Organization of the United Nations (FAO) per country provide an overview about the order of magnitude and the identification of deviations. The comparison of daily net primary productivity, soil respiration and water fluxes at specific sites (FluxNet Data) provides

Quantifying Key Climate Parameter Uncertainties Using an Earth System Model with a Dynamic 3D Ocean

Science.gov (United States)

Olson, R.; Sriver, R. L.; Goes, M. P.; Urban, N.; Matthews, D.; Haran, M.; Keller, K.

2011-12-01

Climate projections hinge critically on uncertain climate model parameters such as climate sensitivity, vertical ocean diffusivity and anthropogenic sulfate aerosol forcings. Climate sensitivity is defined as the equilibrium global mean temperature response to a doubling of atmospheric CO2 concentrations. Vertical ocean diffusivity parameterizes sub-grid scale ocean vertical mixing processes. These parameters are typically estimated using Intermediate Complexity Earth System Models (EMICs) that lack a full 3D representation of the oceans, thereby neglecting the effects of mixing on ocean dynamics and meridional overturning. We improve on these studies by employing an EMIC with a dynamic 3D ocean model to estimate these parameters. We carry out historical climate simulations with the University of Victoria Earth System Climate Model (UVic ESCM) varying parameters that affect climate sensitivity, vertical ocean mixing, and effects of anthropogenic sulfate aerosols. We use a Bayesian approach whereby the likelihood of each parameter combination depends on how well the model simulates surface air temperature and upper ocean heat content. We use a Gaussian process emulator to interpolate the model output to an arbitrary parameter setting. We use Markov Chain Monte Carlo method to estimate the posterior probability distribution function (pdf) of these parameters. We explore the sensitivity of the results to prior assumptions about the parameters. In addition, we estimate the relative skill of different observations to constrain the parameters. We quantify the uncertainty in parameter estimates stemming from climate variability, model and observational errors. We explore the sensitivity of key decision-relevant climate projections to these parameters. We find that climate sensitivity and vertical ocean diffusivity estimates are consistent with previously published results. The climate sensitivity pdf is strongly affected by the prior assumptions, and by the scaling

Observations of surface momentum exchange over the marginal-ice-zone and recommendations for its parameterization

Science.gov (United States)

Elvidge, A. D.; Renfrew, I. A.; Weiss, A. I.; Brooks, I. M.; Lachlan-Cope, T. A.; King, J. C.

2015-10-01

Comprehensive aircraft observations are used to characterise surface roughness over the Arctic marginal ice zone (MIZ) and consequently make recommendations for the parameterization of surface momentum exchange in the MIZ. These observations were gathered in the Barents Sea and Fram Strait from two aircraft as part of the Aerosol-Cloud Coupling And Climate Interactions in the Arctic (ACCACIA) project. They represent a doubling of the total number of such aircraft observations currently available over the Arctic MIZ. The eddy covariance method is used to derive estimates of the 10 m neutral drag coefficient (CDN10) from turbulent wind velocity measurements, and a novel method using albedo and surface temperature is employed to derive ice fraction. Peak surface roughness is found at ice fractions in the range 0.6 to 0.8 (with a mean interquartile range in CDN10 of 1.25 to 2.85 × 10-3). CDN10 as a function of ice fraction is found to be well approximated by the negatively skewed distribution provided by a leading parameterization scheme (Lüpkes et al., 2012) tailored for sea ice drag over the MIZ in which the two constituent components of drag - skin and form drag - are separately quantified. Current parameterization schemes used in the weather and climate models are compared with our results and the majority are found to be physically unjustified and unrepresentative. The Lüpkes et al. (2012) scheme is recommended in a computationally simple form, with adjusted parameter settings. A good agreement is found to hold for subsets of the data from different locations despite differences in sea ice conditions. Ice conditions in the Barents Sea, characterised by small, unconsolidated ice floes, are found to be associated with higher CDN10 values - especially at the higher ice fractions - than those of Fram Strait, where typically larger, smoother floes are observed. Consequently, the important influence of sea ice morphology and floe size on surface roughness is

Constraining Carbonaceous Aerosol Climate Forcing by Bridging Laboratory, Field and Modeling Studies

Science.gov (United States)

Dubey, M. K.; Aiken, A. C.; Liu, S.; Saleh, R.; Cappa, C. D.; Williams, L. R.; Donahue, N. M.; Gorkowski, K.; Ng, N. L.; Mazzoleni, C.; China, S.; Sharma, N.; Yokelson, R. J.; Allan, J. D.; Liu, D.

2014-12-01

Biomass and fossil fuel combustion emits black (BC) and brown carbon (BrC) aerosols that absorb sunlight to warm climate and organic carbon (OC) aerosols that scatter sunlight to cool climate. The net forcing depends strongly on the composition, mixing state and transformations of these carbonaceous aerosols. Complexities from large variability of fuel types, combustion conditions and aging processes have confounded their treatment in models. We analyse recent laboratory and field measurements to uncover fundamental mechanism that control the chemical, optical and microphysical properties of carbonaceous aerosols that are elaborated below: Wavelength dependence of absorption and the single scattering albedo (ω) of fresh biomass burning aerosols produced from many fuels during FLAME-4 was analysed to determine the factors that control the variability in ω. Results show that ω varies strongly with fire-integrated modified combustion efficiency (MCEFI)—higher MCEFI results in lower ω values and greater spectral dependence of ω (Liu et al GRL 2014). A parameterization of ω as a function of MCEFI for fresh BB aerosols is derived from the laboratory data and is evaluated by field data, including BBOP. Our laboratory studies also demonstrate that BrC production correlates with BC indicating that that they are produced by a common mechanism that is driven by MCEFI (Saleh et al NGeo 2014). We show that BrC absorption is concentrated in the extremely low volatility component that favours long-range transport. We observe substantial absorption enhancement for internally mixed BC from diesel and wood combustion near London during ClearFlo. While the absorption enhancement is due to BC particles coated by co-emitted OC in urban regions, it increases with photochemical age in rural areas and is simulated by core-shell models. We measure BrC absorption that is concentrated in the extremely low volatility components and attribute it to wood burning. Our results support

Simulation of the present-day climate with the climate model INMCM5

Science.gov (United States)

Volodin, E. M.; Mortikov, E. V.; Kostrykin, S. V.; Galin, V. Ya.; Lykossov, V. N.; Gritsun, A. S.; Diansky, N. A.; Gusev, A. V.; Iakovlev, N. G.

2017-12-01

In this paper we present the fifth generation of the INMCM climate model that is being developed at the Institute of Numerical Mathematics of the Russian Academy of Sciences (INMCM5). The most important changes with respect to the previous version (INMCM4) were made in the atmospheric component of the model. Its vertical resolution was increased to resolve the upper stratosphere and the lower mesosphere. A more sophisticated parameterization of condensation and cloudiness formation was introduced as well. An aerosol module was incorporated into the model. The upgraded oceanic component has a modified dynamical core optimized for better implementation on parallel computers and has two times higher resolution in both horizontal directions. Analysis of the present-day climatology of the INMCM5 (based on the data of historical run for 1979-2005) shows moderate improvements in reproduction of basic circulation characteristics with respect to the previous version. Biases in the near-surface temperature and precipitation are slightly reduced compared with INMCM4 as well as biases in oceanic temperature, salinity and sea surface height. The most notable improvement over INMCM4 is the capability of the new model to reproduce the equatorial stratospheric quasi-biannual oscillation and statistics of sudden stratospheric warmings.

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

Science.gov (United States)

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

Improving predictions of tropical forest response to climate change through integration of field studies and ecosystem modeling

Science.gov (United States)

Feng, Xiaohui; Uriarte, María; González, Grizelle; Reed, Sasha C.; Thompson, Jill; Zimmerman, Jess K.; Murphy, Lora

2018-01-01

Tropical forests play a critical role in carbon and water cycles at a global scale. Rapid climate change is anticipated in tropical regions over the coming decades and, under a warmer and drier climate, tropical forests are likely to be net sources of carbon rather than sinks. However, our understanding of tropical forest response and feedback to climate change is very limited. Efforts to model climate change impacts on carbon fluxes in tropical forests have not reached a consensus. Here we use the Ecosystem Demography model (ED2) to predict carbon fluxes of a Puerto Rican tropical forest under realistic climate change scenarios. We parameterized ED2 with species-specific tree physiological data using the Predictive Ecosystem Analyzer workflow and projected the fate of this ecosystem under five future climate scenarios. The model successfully captured inter-annual variability in the dynamics of this tropical forest. Model predictions closely followed observed values across a wide range of metrics including above-ground biomass, tree diameter growth, tree size class distributions, and leaf area index. Under a future warming and drying climate scenario, the model predicted reductions in carbon storage and tree growth, together with large shifts in forest community composition and structure. Such rapid changes in climate led the forest to transition from a sink to a source of carbon. Growth respiration and root allocation parameters were responsible for the highest fraction of predictive uncertainty in modeled biomass, highlighting the need to target these processes in future data collection. Our study is the first effort to rely on Bayesian model calibration and synthesis to elucidate the key physiological parameters that drive uncertainty in tropical forests responses to climatic change. We propose a new path forward for model-data synthesis that can substantially reduce uncertainty in our ability to model tropical forest responses to future climate.

Classification of parameter-dependent quantum integrable models, their parameterization, exact solution and other properties

International Nuclear Information System (INIS)

Owusu, Haile K; Yuzbashyan, Emil A

2011-01-01

We study general quantum integrable Hamiltonians linear in a coupling constant and represented by finite N x N real symmetric matrices. The restriction on the coupling dependence leads to a natural notion of nontrivial integrals of motion and classification of integrable families into types according to the number of such integrals. A type M family in our definition is formed by N-M nontrivial mutually commuting operators linear in the coupling. Working from this definition alone, we parameterize type M operators, i.e. resolve the commutation relations, and obtain an exact solution for their eigenvalues and eigenvectors. We show that our parameterization covers all type 1, 2 and 3 integrable models and discuss the extent to which it is complete for other types. We also present robust numerical observation on the number of energy-level crossings in type M integrable systems and analyze the taxonomy of types in the 1D Hubbard model. (paper)

Process-Oriented Diagnostics of Tropical Cyclones in Global Climate Models

Science.gov (United States)

Moon, Y.; Kim, D.; Camargo, S. J.; Wing, A. A.; Sobel, A. H.; Bosilovich, M. G.; Murakami, H.; Reed, K. A.; Vecchi, G. A.; Wehner, M. F.; Zarzycki, C. M.; Zhao, M.

2017-12-01

Simulating tropical cyclone (TC) activity with global climate models (GCMs) remains a challenging problem. While some GCMs are able to simulate TC activity that is in good agreement with the observations, many other models exhibit strong biases. Decreasing horizontal grid spacing of the GCM simulations tends to improve the characteristics of simulated TCs, but this enhancement alone does not necessarily lead to greater skill in simulating TC activity. This study uses process-based diagnostics to identify model characteristics that could explain why some GCM simulations are able to produce more realistic TC activity than others. The diagnostics examine how convection, moisture, clouds and related processes are coupled at individual grid points, which yields useful information into how convective parameterizations interact with resolved model dynamics. These diagnostics share similarities with those originally developed to examine the Madden-Julian Oscillations in climate models. This study will examine TCs in eight different GCM simulations performed at NOAA/GFDL, NCAR and NASA that have different horizontal resolutions and ocean coupling. Preliminary results suggest that stronger TCs are closely associated with greater rainfall - thus greater diabatic heating - in the inner-core regions of the storms, which is consistent with previous theoretical studies. Other storm characteristics that can be used to infer why GCM simulations with comparable horizontal grid spacings produce different TC activity will be examined.

Evaluation and Improvement of Cloud and Convective Parameterizations from Analyses of ARM Observations and Models

Energy Technology Data Exchange (ETDEWEB)

Del Genio, Anthony D. [NASA Goddard Inst. for Space Studies (GISS), New York, NY (United States)

2016-03-11

Over this period the PI and his performed a broad range of data analysis, model evaluation, and model improvement studies using ARM data. These included cloud regimes in the TWP and their evolution over the MJO; M-PACE IOP SCM-CRM intercomparisons; simulations of convective updraft strength and depth during TWP-ICE; evaluation of convective entrainment parameterizations using TWP-ICE simulations; evaluation of GISS GCM cloud behavior vs. long-term SGP cloud statistics; classification of aerosol semi-direct effects on cloud cover; depolarization lidar constraints on cloud phase; preferred states of the winter Arctic atmosphere, surface, and sub-surface; sensitivity of convection to tropospheric humidity; constraints on the parameterization of mesoscale organization from TWP-ICE WRF simulations; updraft and downdraft properties in TWP-ICE simulated convection; insights from long-term ARM records at Manus and Nauru.

Aerosol activation and cloud processing in the global aerosol-climate model ECHAM5-HAM

Directory of Open Access Journals (Sweden)

G. J. Roelofs

2006-01-01

Full Text Available A parameterization for cloud processing is presented that calculates activation of aerosol particles to cloud drops, cloud drop size, and pH-dependent aqueous phase sulfur chemistry. The parameterization is implemented in the global aerosol-climate model ECHAM5-HAM. The cloud processing parameterization uses updraft speed, temperature, and aerosol size and chemical parameters simulated by ECHAM5-HAM to estimate the maximum supersaturation at the cloud base, and subsequently the cloud drop number concentration (CDNC due to activation. In-cloud sulfate production occurs through oxidation of dissolved SO2 by ozone and hydrogen peroxide. The model simulates realistic distributions for annually averaged CDNC although it is underestimated especially in remote marine regions. On average, CDNC is dominated by cloud droplets growing on particles from the accumulation mode, with smaller contributions from the Aitken and coarse modes. The simulations indicate that in-cloud sulfate production is a potentially important source of accumulation mode sized cloud condensation nuclei, due to chemical growth of activated Aitken particles and to enhanced coalescence of processed particles. The strength of this source depends on the distribution of produced sulfate over the activated modes. This distribution is affected by uncertainties in many parameters that play a direct role in particle activation, such as the updraft velocity, the aerosol chemical composition and the organic solubility, and the simulated CDNC is found to be relatively sensitive to these uncertainties.

Downscaling a global climate model to simulate climate change over the US and the implication on regional and urban air quality

Directory of Open Access Journals (Sweden)

M. Trail

2013-09-01

Full Text Available Climate change can exacerbate future regional air pollution events by making conditions more favorable to form high levels of ozone. In this study, we use spectral nudging with the Weather Research and Forecasting (WRF model to downscale NASA earth system GISS modelE2 results during the years 2006 to 2010 and 2048 to 2052 over the contiguous United States in order to compare the resulting meteorological fields from the air quality perspective during the four seasons of five-year historic and future climatological periods. GISS results are used as initial and boundary conditions by the WRF regional climate model (RCM to produce hourly meteorological fields. The downscaling technique and choice of physics parameterizations used are evaluated by comparing them with in situ observations. This study investigates changes of similar regional climate conditions down to a 12 km by 12 km resolution, as well as the effect of evolving climate conditions on the air quality at major US cities. The high-resolution simulations produce somewhat different results than the coarse-resolution simulations in some regions. Also, through the analysis of the meteorological variables that most strongly influence air quality, we find consistent changes in regional climate that would enhance ozone levels in four regions of the US during fall (western US, Texas, northeastern, and southeastern US, one region during summer (Texas, and one region where changes potentially would lead to better air quality during spring (Northeast. Changes in regional climate that would enhance ozone levels are increased temperatures and stagnation along with decreased precipitation and ventilation. We also find that daily peak temperatures tend to increase in most major cities in the US, which would increase the risk of health problems associated with heat stress. Future work will address a more comprehensive assessment of emissions and chemistry involved in the formation and removal of air

Global climate feedbacks

Energy Technology Data Exchange (ETDEWEB)

Manowitz, B.

1990-10-01

The important physical, chemical, and biological events that affect global climate change occur on a mesoscale -- requiring high spatial resolution for their analysis. The Department of Energy has formulated two major initiatives under the US Global Change Program: ARM (Atmospheric Radiation Measurements), and CHAMMP (Computer Hardware Advanced Mathematics and Model Physics). ARM is designed to use ground and air-craft based observations to document profiles of atmospheric composition, clouds, and radiative fluxes. With research and models of important physical processes, ARM will delineate the relationships between trace gases, aerosol and cloud structure, and radiative transfer in the atmosphere, and will improve the parameterization of global circulation models. The present GCMs do not model important feedbacks, including those from clouds, oceans, and land processes. The purpose of this workshop is to identify such potential feedbacks, to evaluate the uncertainties in the feedback processes (and, if possible, to parameterize the feedback processes so that they can be treated in a GCM), and to recommend research programs that will reduce the uncertainties in important feedback processes. Individual reports are processed separately for the data bases.

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

Science.gov (United States)

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

Aerosol-Cloud-Precipitation Interactions in WRF Model:Sensitivity to Autoconversion Parameterization

Institute of Scientific and Technical Information of China (English)

解小宁; 刘晓东

2015-01-01

Cloud-to-rain autoconversion process is an important player in aerosol loading, cloud morphology, and precipitation variations because it can modulate cloud microphysical characteristics depending on the par-ticipation of aerosols, and aff ects the spatio-temporal distribution and total amount of precipitation. By applying the Kessler, the Khairoutdinov-Kogan (KK), and the Dispersion autoconversion parameterization schemes in a set of sensitivity experiments, the indirect eff ects of aerosols on clouds and precipitation are investigated for a deep convective cloud system in Beijing under various aerosol concentration backgrounds from 50 to 10000 cm−3. Numerical experiments show that aerosol-induced precipitation change is strongly dependent on autoconversion parameterization schemes. For the Kessler scheme, the average cumulative precipitation is enhanced slightly with increasing aerosols, whereas surface precipitation is reduced signifi-cantly with increasing aerosols for the KK scheme. Moreover, precipitation varies non-monotonically for the Dispersion scheme, increasing with aerosols at lower concentrations and decreasing at higher concentrations. These diff erent trends of aerosol-induced precipitation change are mainly ascribed to diff erences in rain wa-ter content under these three autoconversion parameterization schemes. Therefore, this study suggests that accurate parameterization of cloud microphysical processes, particularly the cloud-to-rain autoconversion process, is needed for improving the scientifi c understanding of aerosol-cloud-precipitation interactions.

Prediction of the impacts of climate changes on the stream flow of ...

African Journals Online (AJOL)

Abstract. Soil and Water Assessment Tool, (SWAT) model was used to predict the impacts of Climate Change on Ajali River watershed, Aguobu-Umumba, Ezeagu, Enugu State, Nigeria. The model was first used to simulate stream flow using observed data. After model run, parameterization, sensitivity analysis, the monthly ...

On the sensitivity of mesoscale models to surface-layer parameterization constants

Science.gov (United States)

Garratt, J. R.; Pielke, R. A.

1989-09-01

The Colorado State University standard mesoscale model is used to evaluate the sensitivity of one-dimensional (1D) and two-dimensional (2D) fields to differences in surface-layer parameterization “constants”. Such differences reflect the range in the published values of the von Karman constant, Monin-Obukhov stability functions and the temperature roughness length at the surface. The sensitivity of 1D boundary-layer structure, and 2D sea-breeze intensity, is generally less than that found in published comparisons related to turbulence closure schemes generally.

Cross-section parameterization of the pebble bed modular reactor using the dimension-wise expansion model

International Nuclear Information System (INIS)

Zivanovic, Rastko; Bokov, Pavel M.

2010-01-01

This paper discusses the use of the dimension-wise expansion model for cross-section parameterization. The components of the model were approximated with tensor products of orthogonal polynomials. As we demonstrate, the model for a specific cross-section can be built in a systematic way directly from data without any a priori knowledge of its structure. The methodology is able to construct a finite basis of orthogonal polynomials that is required to approximate a cross-section with pre-specified accuracy. The methodology includes a global sensitivity analysis that indicates irrelevant state parameters which can be excluded from the model without compromising the accuracy of the approximation and without repetition of the fitting process. To fit the dimension-wise expansion model, Randomised Quasi-Monte-Carlo Integration and Sparse Grid Integration methods were used. To test the parameterization methods with different integrations embedded we have used the OECD PBMR 400 MW benchmark problem. It has been shown in this paper that the Sparse Grid Integration achieves pre-specified accuracy with a significantly (up to 1-2 orders of magnitude) smaller number of samples compared to Randomised Quasi-Monte-Carlo Integration.

A review of the theoretical basis for bulk mass flux convective parameterization

Directory of Open Access Journals (Sweden)

R. S. Plant

2010-04-01

Full Text Available Most parameterizations for precipitating convection in use today are bulk schemes, in which an ensemble of cumulus elements with different properties is modelled as a single, representative entraining-detraining plume. We review the underpinning mathematical model for such parameterizations, in particular by comparing it with spectral models in which elements are not combined into the representative plume. The chief merit of a bulk model is that the representative plume can be described by an equation set with the same structure as that which describes each element in a spectral model. The equivalence relies on an ansatz for detrained condensate introduced by Yanai et al. (1973 and on a simplified microphysics. There are also conceptual differences in the closure of bulk and spectral parameterizations. In particular, we show that the convective quasi-equilibrium closure of Arakawa and Schubert (1974 for spectral parameterizations cannot be carried over to a bulk parameterization in a straightforward way. Quasi-equilibrium of the cloud work function assumes a timescale separation between a slow forcing process and a rapid convective response. But, for the natural bulk analogue to the cloud-work function, the relevant forcing is characterised by a different timescale, and so its quasi-equilibrium entails a different physical constraint. Closures of bulk parameterizations that use a parcel value of CAPE do not suffer from this timescale issue. However, the Yanai et al. (1973 ansatz must be invoked as a necessary ingredient of those closures.

Factors influencing the parameterization of anvil clouds within GCMs

International Nuclear Information System (INIS)

Leone, J.M. Jr.; Chin, Hung-Neng.

1993-03-01

The overall goal of this project is to improve the representation of clouds and their effects within global climate models (GCMs). The authors have concentrated on a small portion of the overall goal, the evolution of convectively generated cirrus clouds and their effects on the large-scale environment. Because of the large range of time and length scales involved they have been using a multi-scale attack. For the early time generation and development of the cirrus anvil they are using a cloud-scale model with horizontal resolution of 1--2 kilometers; while for the larger scale transport by the larger scale flow they are using a mesoscale model with a horizontal resolution of 20--60 kilometers. The eventual goal is to use the information obtained from these simulations together with available observations to derive improved cloud parameterizations for use in GCMs. This paper presents results from their cloud-scale studies and describes a new tool, a cirrus generator, that they have developed to aid in their mesoscale studies

Projected changes over western Canada using convection-permitting regional climate model and the pseudo-global warming method

Science.gov (United States)

Li, Y.; Kurkute, S.; Chen, L.

2017-12-01

Results from the General Circulation Models (GCMs) suggest more frequent and more severe extreme rain events in a climate warmer than the present. However, current GCMs cannot accurately simulate extreme rainfall events of short duration due to their coarse model resolutions and parameterizations. This limitation makes it difficult to provide the detailed quantitative information for the development of regional adaptation and mitigation strategies. Dynamical downscaling using nested Regional Climate Models (RCMs) are able to capture key regional and local climate processes with an affordable computational cost. Recent studies have demonstrated that the downscaling of GCM results with weather-permitting mesoscale models, such as the pseudo-global warming (PGW) technique, could be a viable and economical approach of obtaining valuable climate change information on regional scales. We have conducted a regional climate 4-km Weather Research and Forecast Model (WRF) simulation with one domain covering the whole western Canada, for a historic run (2000-2015) and a 15-year future run to 2100 and beyond with the PGW forcing. The 4-km resolution allows direct use of microphysics and resolves the convection explicitly, thus providing very convincing spatial detail. With this high-resolution simulation, we are able to study the convective mechanisms, specifically the control of convections over the Prairies, the projected changes of rainfall regimes, and the shift of the convective mechanisms in a warming climate, which has never been examined before numerically at such large scale with such high resolution.

Assessing Impact, DIF, and DFF in Accommodated Item Scores: A Comparison of Multilevel Measurement Model Parameterizations

Science.gov (United States)

Beretvas, S. Natasha; Cawthon, Stephanie W.; Lockhart, L. Leland; Kaye, Alyssa D.

2012-01-01

This pedagogical article is intended to explain the similarities and differences between the parameterizations of two multilevel measurement model (MMM) frameworks. The conventional two-level MMM that includes item indicators and models item scores (Level 1) clustered within examinees (Level 2) and the two-level cross-classified MMM (in which item…

A new parameterization for waveform inversion in acoustic orthorhombic media

KAUST Repository

Masmoudi, Nabil

2016-05-26

Orthorhombic anisotropic model inversion is extra challenging because of the multiple parameter nature of the inversion problem. The high number of parameters required to describe the medium exerts considerable trade-off and additional nonlinearity to a full-waveform inversion (FWI) application. Choosing a suitable set of parameters to describe the model and designing an effective inversion strategy can help in mitigating this problem. Using the Born approximation, which is the central ingredient of the FWI update process, we have derived radiation patterns for the different acoustic orthorhombic parameterizations. Analyzing the angular dependence of scattering (radiation patterns) of the parameters of different parameterizations starting with the often used Thomsen-Tsvankin parameterization, we have assessed the potential trade-off between the parameters and the resolution in describing the data and inverting for the parameters. The analysis led us to introduce new parameters ϵd, δd, and ηd, which have azimuthally dependent radiation patterns, but keep the scattering potential of the transversely isotropic parameters stationary with azimuth (azimuth independent). The novel parameters ϵd, δd, and ηd are dimensionless and represent a measure of deviation between the vertical planes in orthorhombic anisotropy. Therefore, these deviation parameters offer a new parameterization style for an acoustic orthorhombic medium described by six parameters: three vertical transversely isotropic (VTI) parameters, two deviation parameters, and one parameter describing the anisotropy in the horizontal symmetry plane. The main feature of any parameterization based on the deviation parameters, is the azimuthal independency of the modeled data with respect to the VTI parameters, which allowed us to propose practical inversion strategies based on our experience with the VTI parameters. This feature of the new parameterization style holds for even the long-wavelength components of

Development of a parameterization scheme of mesoscale convective systems

International Nuclear Information System (INIS)

Cotton, W.R.

1994-01-01

The goal of this research is to develop a parameterization scheme of mesoscale convective systems (MCS) including diabatic heating, moisture and momentum transports, cloud formation, and precipitation. The approach is to: Perform explicit cloud-resolving simulation of MCSs; Perform statistical analyses of simulated MCSs to assist in fabricating a parameterization, calibrating coefficients, etc.; Test the parameterization scheme against independent field data measurements and in numerical weather prediction (NWP) models emulating general circulation model (GCM) grid resolution. Thus far we have formulated, calibrated, implemented and tested a deep convective engine against explicit Florida sea breeze convection and in coarse-grid regional simulations of mid-latitude and tropical MCSs. Several explicit simulations of MCSs have been completed, and several other are in progress. Analysis code is being written and run on the explicitly simulated data

A clinically parameterized mathematical model of Shigella immunity to inform vaccine design.

Directory of Open Access Journals (Sweden)

Courtney L Davis

Full Text Available We refine and clinically parameterize a mathematical model of the humoral immune response against Shigella, a diarrheal bacteria that infects 80-165 million people and kills an estimated 600,000 people worldwide each year. Using Latin hypercube sampling and Monte Carlo simulations for parameter estimation, we fit our model to human immune data from two Shigella EcSf2a-2 vaccine trials and a rechallenge study in which antibody and B-cell responses against Shigella's lipopolysaccharide (LPS and O-membrane proteins (OMP were recorded. The clinically grounded model is used to mathematically investigate which key immune mechanisms and bacterial targets confer immunity against Shigella and to predict which humoral immune components should be elicited to create a protective vaccine against Shigella. The model offers insight into why the EcSf2a-2 vaccine had low efficacy and demonstrates that at a group level a humoral immune response induced by EcSf2a-2 vaccine or wild-type challenge against Shigella's LPS or OMP does not appear sufficient for protection. That is, the model predicts an uncontrolled infection of gut epithelial cells that is present across all best-fit model parameterizations when fit to EcSf2a-2 vaccine or wild-type challenge data. Using sensitivity analysis, we explore which model parameter values must be altered to prevent the destructive epithelial invasion by Shigella bacteria and identify four key parameter groups as potential vaccine targets or immune correlates: 1 the rate that Shigella migrates into the lamina propria or epithelium, 2 the rate that memory B cells (BM differentiate into antibody-secreting cells (ASC, 3 the rate at which antibodies are produced by activated ASC, and 4 the Shigella-specific BM carrying capacity. This paper underscores the need for a multifaceted approach in ongoing efforts to design an effective Shigella vaccine.

A clinically parameterized mathematical model of Shigella immunity to inform vaccine design.

Science.gov (United States)

Davis, Courtney L; Wahid, Rezwanul; Toapanta, Franklin R; Simon, Jakub K; Sztein, Marcelo B

2018-01-01

We refine and clinically parameterize a mathematical model of the humoral immune response against Shigella, a diarrheal bacteria that infects 80-165 million people and kills an estimated 600,000 people worldwide each year. Using Latin hypercube sampling and Monte Carlo simulations for parameter estimation, we fit our model to human immune data from two Shigella EcSf2a-2 vaccine trials and a rechallenge study in which antibody and B-cell responses against Shigella's lipopolysaccharide (LPS) and O-membrane proteins (OMP) were recorded. The clinically grounded model is used to mathematically investigate which key immune mechanisms and bacterial targets confer immunity against Shigella and to predict which humoral immune components should be elicited to create a protective vaccine against Shigella. The model offers insight into why the EcSf2a-2 vaccine had low efficacy and demonstrates that at a group level a humoral immune response induced by EcSf2a-2 vaccine or wild-type challenge against Shigella's LPS or OMP does not appear sufficient for protection. That is, the model predicts an uncontrolled infection of gut epithelial cells that is present across all best-fit model parameterizations when fit to EcSf2a-2 vaccine or wild-type challenge data. Using sensitivity analysis, we explore which model parameter values must be altered to prevent the destructive epithelial invasion by Shigella bacteria and identify four key parameter groups as potential vaccine targets or immune correlates: 1) the rate that Shigella migrates into the lamina propria or epithelium, 2) the rate that memory B cells (BM) differentiate into antibody-secreting cells (ASC), 3) the rate at which antibodies are produced by activated ASC, and 4) the Shigella-specific BM carrying capacity. This paper underscores the need for a multifaceted approach in ongoing efforts to design an effective Shigella vaccine.

Modelling snow accumulation on Greenland in Eemian, glacial inception, and modern climates in a GCM

Directory of Open Access Journals (Sweden)

H. J. Punge

2012-11-01

Full Text Available Changing climate conditions on Greenland influence the snow accumulation rate and surface mass balance (SMB on the ice sheet and, ultimately, its shape. This can in turn affect local climate via orography and albedo variations and, potentially, remote areas via changes in ocean circulation triggered by melt water or calving from the ice sheet. Examining these interactions in the IPSL global model requires improving the representation of snow at the ice sheet surface. In this paper, we present a new snow scheme implemented in LMDZ, the atmospheric component of the IPSL coupled model. We analyse surface climate and SMB on the Greenland ice sheet under insolation and oceanic boundary conditions for modern, but also for two different past climates, the last glacial inception (115 kyr BP and the Eemian (126 kyr BP. While being limited by the low resolution of the general circulation model (GCM, present-day SMB is on the same order of magnitude as recent regional model findings. It is affected by a moist bias of the GCM in Western Greenland and a dry bias in the north-east. Under Eemian conditions, the SMB decreases largely, and melting affects areas in which the ice sheet surface is today at high altitude, including recent ice core drilling sites as NEEM. In contrast, glacial inception conditions lead to a higher mass balance overall due to the reduced melting in the colder summer climate. Compared to the widely applied positive degree-day (PDD parameterization of SMB, our direct modelling results suggest a weaker sensitivity of SMB to changing climatic forcing. For the Eemian climate, our model simulations using interannually varying monthly mean forcings for the ocean surface temperature and sea ice cover lead to significantly higher SMB in southern Greenland compared to simulations forced with climatological monthly means.

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

Science.gov (United States)

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.

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

Directory of Open Access Journals (Sweden)

Kabilar Gunalan

Full Text Available 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.

A theory-based parameterization for heterogeneous ice nucleation and implications for the simulation of ice processes in atmospheric models

Science.gov (United States)

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.

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

Science.gov (United States)

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.

Study of tropical clouds feedback to a climate warming as simulated by climate models

International Nuclear Information System (INIS)

Brient, Florent

2012-01-01

The last IPCC report affirms the predominant role of low cloud-radiative feedbacks in the inter-model spread of climate sensitivity. Understanding the mechanisms that control the behavior of low-level clouds is thus crucial. However, the complexity of coupled ocean-atmosphere models and the large number of processes potentially involved make the analysis of this response difficult. To simplify the analysis and to identify the most critical controls of cloud feedbacks, we analyze the cloud response to climate change simulated by the IPSL-CM5A model in a hierarchy of configurations. A comparison between three model configurations (coupled, atmospheric and aqua-planet) using the same physical parametrizations shows that the cloud response to global warming is dominated by a decrease of low clouds in regimes of moderate subsidence. Using a Single Column Model, forced by weak subsidence large-scale forcing, allows us to reproduce the vertical cloud profile predicted in the 3D model, as well as its response to climate change (if a stochastic forcing is added on vertical velocity). We analyze the sensitivity of this low-cloud response to external forcing and also to uncertain parameters of physical parameterizations involved on the atmospheric model. Through a moist static energy (MSE) budget, we highlight several mechanisms: (1) Robust: Over weak subsidence regimes, the Clausius-Clapeyron relationship predicts that a warmer atmosphere leads to a increase of the vertical MSE gradient, resulting on a strengthening of the import of low-MSE from the free atmosphere into the cloudy boundary layer. The MSE budget links changes of vertical advection and cloud radiative effects. (2) Physics Model Dependent: The coupling between shallow convection, turbulence and cloud schemes allows the intensification of low-MSE transport so that cloud radiative cooling becomes 'less necessary' to balance the energy budget (Robust positive low cloud-radiative feedback for the model). The

Normalization of the parameterized Courant-Snyder matrix for symplectic factorization of a parameterized Taylor map

International Nuclear Information System (INIS)

Yan, Y.T.

1991-01-01

The transverse motion of charged particles in a circular accelerator can be well represented by a one-turn high-order Taylor map. For particles without energy deviation, the one-turn Taylor map is a 4-dimensional polynomials of four variables. The four variables are the transverse canonical coordinates and their conjugate momenta. To include the energy deviation (off-momentum) effects, the map has to be parameterized with a smallness factor representing the off-momentum and so the Taylor map becomes a 4-dimensional polynomials of five variables. It is for this type of parameterized Taylor map that a mehtod is presented for converting it into a parameterized Dragt-Finn factorization map. Parameterized nonlinear normal form and parameterized kick factorization can thus be obtained with suitable modification of the existing technique

High Resolution Simulations of Future Climate in West Africa Using a Variable-Resolution Atmospheric Model

Science.gov (United States)

Adegoke, J. O.; Engelbrecht, F.; Vezhapparambu, S.

2013-12-01

In previous work demonstrated the application of a var¬iable-resolution global atmospheric model, the conformal-cubic atmospheric model (CCAM), across a wide range of spatial and time scales to investigate the ability of the model to provide realistic simulations of present-day climate and plausible projections of future climate change over sub-Saharan Africa. By applying the model in stretched-grid mode the versatility of the model dynamics, numerical formulation and physical parameterizations to function across a range of length scales over the region of interest, was also explored. We primarily used CCAM to illustrate the capability of the model to function as a flexible downscaling tool at the climate-change time scale. Here we report on additional long term climate projection studies performed by downscaling at much higher resolutions (8 Km) over an area that stretches from just south of Sahara desert to the southern coast of the Niger Delta and into the Gulf of Guinea. To perform these simulations, CCAM was provided with synoptic-scale forcing of atmospheric circulation from 2.5 deg resolution NCEP reanalysis at 6-hourly interval and SSTs from NCEP reanalysis data uses as lower boundary forcing. CCAM 60 Km resolution downscaled to 8 Km (Schmidt factor 24.75) then 8 Km resolution simulation downscaled to 1 Km (Schmidt factor 200) over an area approximately 50 Km x 50 Km in the southern Lake Chad Basin (LCB). Our intent in conducting these high resolution model runs was to obtain a deeper understanding of linkages between the projected future climate and the hydrological processes that control the surface water regime in this part of sub-Saharan Africa.

Agricultural drought in a future climate: results from 15 global climate models participating in the IPCC 4th assessment

Science.gov (United States)

Wang, Guiling

2005-12-01

This study examines the impact of greenhouse gas warming on soil moisture based on predictions of 15 global climate models by comparing the after-stabilization climate in the SRESA1b experiment with the pre-industrial control climate. The models are consistent in predicting summer dryness and winter wetness in only part of the northern middle and high latitudes. Slightly over half of the models predict year-round wetness in central Eurasia and/or year-round dryness in Siberia and mid-latitude Northeast Asia. One explanation is offered that relates such lack of seasonality to the carryover effect of soil moisture storage from season to season. In the tropics and subtropics, a decrease of soil moisture is the dominant response. The models are especially consistent in predicting drier soil over the southwest North America, Central America, the Mediterranean, Australia, and the South Africa in all seasons, and over much of the Amazon and West Africa in the June July August (JJA) season and the Asian monsoon region in the December January February (DJF) season. Since the only major areas of future wetness predicted with a high level of model consistency are part of the northern middle and high latitudes during the non-growing season, it is suggested that greenhouse gas warming will cause a worldwide agricultural drought. Over regions where there is considerable consistency among the analyzed models in predicting the sign of soil moisture changes, there is a wide range of magnitudes of the soil moisture response, indicating a high degree of model dependency in terrestrial hydrological sensitivity. A major part of the inter-model differences in the sensitivity of soil moisture response are attributable to differences in land surface parameterization.

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

Science.gov (United States)

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.

Parameterized and resolved Southern Ocean eddy compensation

Science.gov (United States)

Poulsen, Mads B.; Jochum, Markus; Nuterman, Roman

2018-04-01

The ability to parameterize Southern Ocean eddy effects in a forced coarse resolution ocean general circulation model is assessed. The transient model response to a suite of different Southern Ocean wind stress forcing perturbations is presented and compared to identical experiments performed with the same model in 0.1° eddy-resolving resolution. With forcing of present-day wind stress magnitude and a thickness diffusivity formulated in terms of the local stratification, it is shown that the Southern Ocean residual meridional overturning circulation in the two models is different in structure and magnitude. It is found that the difference in the upper overturning cell is primarily explained by an overly strong subsurface flow in the parameterized eddy-induced circulation while the difference in the lower cell is mainly ascribed to the mean-flow overturning. With a zonally constant decrease of the zonal wind stress by 50% we show that the absolute decrease in the overturning circulation is insensitive to model resolution, and that the meridional isopycnal slope is relaxed in both models. The agreement between the models is not reproduced by a 50% wind stress increase, where the high resolution overturning decreases by 20%, but increases by 100% in the coarse resolution model. It is demonstrated that this difference is explained by changes in surface buoyancy forcing due to a reduced Antarctic sea ice cover, which strongly modulate the overturning response and ocean stratification. We conclude that the parameterized eddies are able to mimic the transient response to altered wind stress in the high resolution model, but partly misrepresent the unperturbed Southern Ocean meridional overturning circulation and associated heat transports.

Sensitivity of aerosol indirect forcing and autoconversion to cloud droplet parameterization: an assessment with the NASA Global Modeling Initiative.

Science.gov (United States)

Sotiropoulou, R. P.; Meshkhidze, N.; Nenes, A.

2006-12-01

The aerosol indirect forcing is one of the largest sources of uncertainty in assessments of anthropogenic climate change [IPCC, 2001]. Much of this uncertainty arises from the approach used for linking cloud droplet number concentration (CDNC) to precursor aerosol. Global Climate Models (GCM) use a wide range of cloud droplet activation mechanisms ranging from empirical [Boucher and Lohmann, 1995] to detailed physically- based formulations [e.g., Abdul-Razzak and Ghan, 2000; Fountoukis and Nenes, 2005]. The objective of this study is to assess the uncertainties in indirect forcing and autoconversion of cloud water to rain caused by the application of different cloud droplet parameterization mechanisms; this is an important step towards constraining the aerosol indirect effects (AIE). Here we estimate the uncertainty in indirect forcing and autoconversion rate using the NASA Global Model Initiative (GMI). The GMI allows easy interchange of meteorological fields, chemical mechanisms and the aerosol microphysical packages. Therefore, it is an ideal tool for assessing the effect of different parameters on aerosol indirect forcing. The aerosol module includes primary emissions, chemical production of sulfate in clear air and in-cloud aqueous phase, gravitational sedimentation, dry deposition, wet scavenging in and below clouds, and hygroscopic growth. Model inputs include SO2 (fossil fuel and natural), black carbon (BC), organic carbon (OC), mineral dust and sea salt. The meteorological data used in this work were taken from the NASA Data Assimilation Office (DAO) and two different GCMs: the NASA GEOS4 finite volume GCM (FVGCM) and the Goddard Institute for Space Studies version II' (GISS II') GCM. Simulations were carried out for "present day" and "preindustrial" emissions using different meteorological fields (i.e. DAO, FVGCM, GISS II'); cloud droplet number concentration is computed from the correlations of Boucher and Lohmann [1995], Abdul-Razzak and Ghan [2000

Parameterization of planetary wave breaking in the middle atmosphere

Science.gov (United States)

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.

Impact of ocean model resolution on CCSM climate simulations

Energy Technology Data Exchange (ETDEWEB)

Kirtman, Ben P.; Rousset, Clement; Siqueira, Leo [University of Miami, Rosenstiel School for Marine and Atmospheric Science, Coral Gables, FL (United States); Bitz, Cecilia [University of Washington, Department of Atmospheric Science, Seattle, WA (United States); Bryan, Frank; Dennis, John; Hearn, Nathan; Loft, Richard; Tomas, Robert; Vertenstein, Mariana [National Center for Atmospheric Research, Boulder, CO (United States); Collins, William [University of California, Berkeley, Berkeley, CA (United States); Kinter, James L.; Stan, Cristiana [Center for Ocean-Land-Atmosphere Studies, Calverton, MD (United States); George Mason University, Fairfax, VA (United States)

2012-09-15

The current literature provides compelling evidence suggesting that an eddy-resolving (as opposed to eddy-permitting or eddy-parameterized) ocean component model will significantly impact the simulation of the large-scale climate, although this has not been fully tested to date in multi-decadal global coupled climate simulations. The purpose of this paper is to examine how resolved ocean fronts and eddies impact the simulation of large-scale climate. The model used for this study is the NCAR Community Climate System Model version 3.5 (CCSM3.5) - the forerunner to CCSM4. Two experiments are reported here. The control experiment is a 155-year present-day climate simulation using a 0.5 atmosphere component (zonal resolution 0.625 meridional resolution 0.5 ; land surface component at the same resolution) coupled to ocean and sea-ice components with zonal resolution of 1.2 and meridional resolution varying from 0.27 at the equator to 0.54 in the mid-latitudes. The second simulation uses the same atmospheric and land-surface models coupled to eddy-resolving 0.1 ocean and sea-ice component models. The simulations are compared in terms of how the representation of smaller scale features in the time mean ocean circulation and ocean eddies impact the mean and variable climate. In terms of the global mean surface temperature, the enhanced ocean resolution leads to a ubiquitous surface warming with a global mean surface temperature increase of about 0.2 C relative to the control. The warming is largest in the Arctic and regions of strong ocean fronts and ocean eddy activity (i.e., Southern Ocean, western boundary currents). The Arctic warming is associated with significant losses of sea-ice in the high-resolution simulation. The sea surface temperature gradients in the North Atlantic, in particular, are better resolved in the high-resolution model leading to significantly sharper temperature gradients and associated large-scale shifts in the rainfall. In the extra-tropics, the

Use of ARM Data to address the Climate Change Further Development and Applications of A Multi-scale Modeling Framework

Energy Technology Data Exchange (ETDEWEB)

David A. Randall; Marat Khairoutdinov

2007-12-14

The Colorado State University (CSU) Multi-scale Modeling Framework (MMF) is a new type of general circulation model (GCM) that replaces the conventional parameterizations of convection, clouds and boundary layer with a cloud-resolving model (CRM) embedded into each grid column. The MMF that we have been working with is a “super-parameterized” version of the Community Atmosphere Model (CAM). As reported in the publications listed below, we have done extensive work with the model. We have explored the MMF’s performance in several studies, including an AMIP run and a CAPT test, and we have applied the MMF to an analysis of climate sensitivity.

Human impact parameterizations in global hydrological models improve estimates of monthly discharges and hydrological extremes: a multi-model validation study

NARCIS (Netherlands)

Veldkamp, T I E; Zhao, F; Ward, P J; Moel, H de; Aerts, J C J H; Schmied, H Müller; Portmann, F T; Masaki, Y; Pokhrel, Y; Liu, X; Satoh, Yusuke; Gerten, Dieter; Gosling, S N; Zaherpour, J; Wada, Yoshihide

2018-01-01

Human activity has a profound influence on river discharges, hydrological extremes and water-related hazards. In this study, we compare the results of five state-of-the-art global hydrological models (GHMs) with observations to examine the role of human impact parameterizations (HIP) in the

New representation of water activity based on a single solute specific constant to parameterize the hygroscopic growth of aerosols in atmospheric models

Directory of Open Access Journals (Sweden)

S. Metzger

2012-06-01

Full Text Available Water activity is a key factor in aerosol thermodynamics and hygroscopic growth. We introduce a new representation of water activity (a_w, which is empirically related to the solute molality (μ_s through a single solute specific constant, ν_i. Our approach is widely applicable, considers the Kelvin effect and covers ideal solutions at high relative humidity (RH, including cloud condensation nuclei (CCN activation. It also encompasses concentrated solutions with high ionic strength at low RH such as the relative humidity of deliquescence (RHD. The constant ν_i can thus be used to parameterize the aerosol hygroscopic growth over a wide range of particle sizes, from nanometer nucleation mode to micrometer coarse mode particles. In contrast to other a_w-representations, our ν_i factor corrects the solute molality both linearly and in exponent form x · a^x. We present four representations of our basic a_w-parameterization at different levels of complexity for different a_w-ranges, e.g. up to 0.95, 0.98 or 1. ν_i is constant over the selected a_w-range, and in its most comprehensive form, the parameterization describes the entire a_w range (0–1. In this work we focus on single solute solutions. ν_i can be pre-determined with a root-finding method from our water activity representation using an a_w−μ_s data pair, e.g. at solute saturation using RHD and solubility measurements. Our a_w and supersaturation (Köhler-theory results compare well with the thermodynamic reference model E-AIM for the key compounds NaCl and (NH₄₂SO₄ relevant for CCN modeling and calibration studies. Envisaged applications include regional and global atmospheric chemistry and

Parameterization of cloud droplet formation for global and regional models: including adsorption activation from insoluble CCN

Directory of Open Access Journals (Sweden)

P. Kumar

2009-04-01

Full Text Available Dust and black carbon aerosol have long been known to exert potentially important and diverse impacts on cloud droplet formation. Most studies to date focus on the soluble fraction of these particles, and overlook interactions of the insoluble fraction with water vapor (even if known to be hydrophilic. To address this gap, we developed a new parameterization that considers cloud droplet formation within an ascending air parcel containing insoluble (but wettable particles externally mixed with aerosol containing an appreciable soluble fraction. Activation of particles with a soluble fraction is described through well-established Köhler theory, while the activation of hydrophilic insoluble particles is treated by "adsorption-activation" theory. In the latter, water vapor is adsorbed onto insoluble particles, the activity of which is described by a multilayer Frenkel-Halsey-Hill (FHH adsorption isotherm modified to account for particle curvature. We further develop FHH activation theory to i find combinations of the adsorption parameters A_FHH, B_FHH which yield atmospherically-relevant behavior, and, ii express activation properties (critical supersaturation that follow a simple power law with respect to dry particle diameter.

The new parameterization is tested by comparing the parameterized cloud droplet number concentration against predictions with a detailed numerical cloud model, considering a wide range of particle populations, cloud updraft conditions, water vapor condensation coefficient and FHH adsorption isotherm characteristics. The agreement between parameterization and parcel model is excellent, with an average error of 10% and R²~0.98. A preliminary sensitivity study suggests that the sublinear response of droplet number to Köhler particle concentration is not as strong for FHH particles.

Parameterization of radiocaesium soil-plant transfer using soil characteristics

International Nuclear Information System (INIS)

Konoplev, A. V.; Drissner, J.; Klemt, E.; Konopleva, I. V.; Zibold, G.

1996-01-01

A model of radionuclide soil-plant transfer is proposed to parameterize the transfer factor by soil and soil solution characteristics. The model is tested with experimental data on the aggregated transfer factor T ag and soil parameters for 8 forest sites in Baden-Wuerttemberg. It is shown that the integral soil-plant transfer factor can be parameterized through radiocaesium exchangeability, capacity of selective sorption sites and ion composition of the soil solution or the water extract. A modified technique of (FES) measurement for soils with interlayer collapse is proposed. (author)

Analysis of sensitivity to different parameterization schemes for a subtropical cyclone

Science.gov (United States)

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.

Assessing Sexual Dicromatism: The Importance of Proper Parameterization in Tetrachromatic Visual Models.

Directory of Open Access Journals (Sweden)

Pierre-Paul Bitton

Full Text Available Perceptual models of animal vision have greatly contributed to our understanding of animal-animal and plant-animal communication. The receptor-noise model of color contrasts has been central to this research as it quantifies the difference between two colors for any visual system of interest. However, if the properties of the visual system are unknown, assumptions regarding parameter values must be made, generally with unknown consequences. In this study, we conduct a sensitivity analysis of the receptor-noise model using avian visual system parameters to systematically investigate the influence of variation in light environment, photoreceptor sensitivities, photoreceptor densities, and light transmission properties of the ocular media and the oil droplets. We calculated the chromatic contrast of 15 plumage patches to quantify a dichromatism score for 70 species of Galliformes, a group of birds that display a wide range of sexual dimorphism. We found that the photoreceptor densities and the wavelength of maximum sensitivity of the short-wavelength-sensitive photoreceptor 1 (SWS1 can change dichromatism scores by 50% to 100%. In contrast, the light environment, transmission properties of the oil droplets, transmission properties of the ocular media, and the peak sensitivities of the cone photoreceptors had a smaller impact on the scores. By investigating the effect of varying two or more parameters simultaneously, we further demonstrate that improper parameterization could lead to differences between calculated and actual contrasts of more than 650%. Our findings demonstrate that improper parameterization of tetrachromatic visual models can have very large effects on measures of dichromatism scores, potentially leading to erroneous inferences. We urge more complete characterization of avian retinal properties and recommend that researchers either determine whether their species of interest possess an ultraviolet or near-ultraviolet sensitive SWS1

Collaborative Proposal: Transforming How Climate System Models are Used: A Global, Multi-Resolution Approach

Energy Technology Data Exchange (ETDEWEB)

Estep, Donald

2013-04-15

Despite the great interest in regional modeling for both weather and climate applications, regional modeling is not yet at the stage that it can be used routinely and effectively for climate modeling of the ocean. The overarching goal of this project is to transform how climate models are used by developing and implementing a robust, efficient, and accurate global approach to regional ocean modeling. To achieve this goal, we will use theoretical and computational means to resolve several basic modeling and algorithmic issues. The first task is to develop techniques for transitioning between parameterized and high-fidelity regional ocean models as the discretization grid transitions from coarse to fine regions. The second task is to develop estimates for the error in scientifically relevant quantities of interest that provide a systematic way to automatically determine where refinement is needed in order to obtain accurate simulations of dynamic and tracer transport in regional ocean models. The third task is to develop efficient, accurate, and robust time-stepping schemes for variable spatial resolution discretizations used in regional ocean models of dynamics and tracer transport. The fourth task is to develop frequency-dependent eddy viscosity finite element and discontinuous Galerkin methods and study their performance and effectiveness for simulation of dynamics and tracer transport in regional ocean models. These four projects share common difficulties and will be approach using a common computational and mathematical toolbox. This is a multidisciplinary project involving faculty and postdocs from Colorado State University, Florida State University, and Penn State University along with scientists from Los Alamos National Laboratory. The completion of the tasks listed within the discussion of the four sub-projects will go a long way towards meeting our goal of developing superior regional ocean models that will transform how climate system models are used.

Identifying a key physical factor sensitive to the performance of Madden-Julian oscillation simulation in climate models

Science.gov (United States)

Kim, Go-Un; Seo, Kyong-Hwan

2018-01-01

A key physical factor in regulating the performance of Madden-Julian oscillation (MJO) simulation is examined by using 26 climate model simulations from the World Meteorological Organization's Working Group for Numerical Experimentation/Global Energy and Water Cycle Experiment Atmospheric System Study (WGNE and MJO-Task Force/GASS) global model comparison project. For this, intraseasonal moisture budget equation is analyzed and a simple, efficient physical quantity is developed. The result shows that MJO skill is most sensitive to vertically integrated intraseasonal zonal wind convergence (ZC). In particular, a specific threshold value of the strength of the ZC can be used as distinguishing between good and poor models. An additional finding is that good models exhibit the correct simultaneous convection and large-scale circulation phase relationship. In poor models, however, the peak circulation response appears 3 days after peak rainfall, suggesting unfavorable coupling between convection and circulation. For an improving simulation of the MJO in climate models, we propose that this delay of circulation in response to convection needs to be corrected in the cumulus parameterization scheme.

Markov-switching model for nonstationary runoff conditioned on El Nino information

DEFF Research Database (Denmark)

Gelati, Emiliano; Madsen, H.; Rosbjerg, Dan

2010-01-01

We define a Markov-modulated autoregressive model with exogenous input (MARX) to generate runoff scenarios using climatic information. Runoff parameterization is assumed to be conditioned on a hidden climate state following a Markov chain, where state transition probabilities are functions...... of the climatic input. MARX allows stochastic modeling of nonstationary runoff, as runoff anomalies are described by a mixture of autoregressive models with exogenous input, each one corresponding to a climate state. We apply MARX to inflow time series of the Daule Peripa reservoir (Ecuador). El Nino Southern...... Oscillation (ENSO) information is used to condition runoff parameterization. Among the investigated ENSO indexes, the NINO 1+2 sea surface temperature anomalies and the trans-Nino index perform best as predictors. In the perspective of reservoir optimization at various time scales, MARX produces realistic...

A general circulation model (GCM) parameterization of Pinatubo aerosols

Energy Technology Data Exchange (ETDEWEB)

Lacis, A.A.; Carlson, B.E.; Mishchenko, M.I. [NASA Goddard Institute for Space Studies, New York, NY (United States)

1996-04-01

The June 1991 volcanic eruption of Mt. Pinatubo is the largest and best documented global climate forcing experiment in recorded history. The time development and geographical dispersion of the aerosol has been closely monitored and sampled. Based on preliminary estimates of the Pinatubo aerosol loading, general circulation model predictions of the impact on global climate have been made.

High Resolution Modeling of Hurricanes in a Climate Context

Science.gov (United States)

Knutson, T. R.

2007-12-01

Modeling of tropical cyclone activity in a climate context initially focused on simulation of relatively weak tropical storm-like disturbances as resolved by coarse grid (200 km) global models. As computing power has increased, multi-year simulations with global models of grid spacing 20-30 km have become feasible. Increased resolution also allowed for simulation storms of increasing intensity, and some global models generate storms of hurricane strength, depending on their resolution and other factors, although detailed hurricane structure is not simulated realistically. Results from some recent high resolution global model studies are reviewed. An alternative for hurricane simulation is regional downscaling. An early approach was to embed an operational (GFDL) hurricane prediction model within a global model solution, either for 5-day case studies of particular model storm cases, or for "idealized experiments" where an initial vortex is inserted into an idealized environments derived from global model statistics. Using this approach, hurricanes up to category five intensity can be simulated, owing to the model's relatively high resolution (9 km grid) and refined physics. Variants on this approach have been used to provide modeling support for theoretical predictions that greenhouse warming will increase the maximum intensities of hurricanes. These modeling studies also simulate increased hurricane rainfall rates in a warmer climate. The studies do not address hurricane frequency issues, and vertical shear is neglected in the idealized studies. A recent development is the use of regional model dynamical downscaling for extended (e.g., season-length) integrations of hurricane activity. In a study for the Atlantic basin, a non-hydrostatic model with grid spacing of 18km is run without convective parameterization, but with internal spectral nudging toward observed large-scale (basin wavenumbers 0-2) atmospheric conditions from reanalyses. Using this approach, our

Invariant box-parameterization of neutrino oscillations

International Nuclear Information System (INIS)

Weiler, Thomas J.; Wagner, DJ

1998-01-01

The model-independent 'box' parameterization of neutrino oscillations is examined. The invariant boxes are the classical amplitudes of the individual oscillating terms. Being observables, the boxes are independent of the choice of parameterization of the mixing matrix. Emphasis is placed on the relations among the box parameters due to mixing-matrix unitarity, and on the reduction of the number of boxes to the minimum basis set. Using the box algebra, we show that CP-violation may be inferred from measurements of neutrino flavor mixing even when the oscillatory factors have averaged. General analyses of neutrino oscillations among n≥3 flavors can readily determine the boxes, which can then be manipulated to yield magnitudes of mixing matrix elements

Use of regional climate models data for groundwater recharge modelling in Baltic artesian basin

Science.gov (United States)

Timuhins, A.; Klints, I.; Sennikovs, J.; Virbulis, J.

2012-04-01

Baltic artesian basin (BAB) covers about 480000 square kilometres. BAB includes territory of Latvia, Lithuania, Estonia, parts of Poland, Russia, Belarus and Baltic Sea. The closed hydrogeological mathematical model for the BAB is developed in University of Latvia and reference calculations made in steady state mode. No-flow boundary condition is applied on the bottom and side boundaries of BAB. Hydraulic head is fixed on the seabed and largest lakes, and along the main river lines. Main water supply wells also are presented in the model as a pointwise water extraction. Precipitation is the main source of the groundwater recharge in the BAB region. Infiltration parameterization is responsible for this water source in BAB model. During the early stage of calibration of BAB hydrogeological model an automatic calibration for the hydraulic conductivities of permeable layers and single infiltration rate was attempted. Performing BAB model calibration it was noted that the differences of calculated and observed hydraulic heads (used for calculating the calibration penalty function) can be reduced by introducing a spatially distributed infiltration model. The aim of the present study is improving of the infiltration model, as well as preserving a short computation time (several minutes) for the piezometric head. Direct solution of improvement of the infiltration would be a usage of the advanced hydrological models. However, an accurate hydrological model requires a lot of computational power. It should couple meteorological and hydrological parameters and requires additional calibration. The regional climate model (KNMI-RACMO2 25 km resolution) results from ENSEMBLES project are used for the spatially distributed infiltration field calculation. The infiltration field is constructed as weighted difference of 30 year averaged precipitation and evaporation fields. The weight value is calibrated and a considerable decrease of the value of penalty function of the groundwater

A new parameterization for integrated population models to document amphibian reintroductions.

Science.gov (United States)

Duarte, Adam; Pearl, Christopher A; Adams, Michael J; Peterson, James T

2017-09-01

Managers are increasingly implementing reintroduction programs as part of a global effort to alleviate amphibian declines. Given uncertainty in factors affecting populations and a need to make recurring decisions to achieve objectives, adaptive management is a useful component of these efforts. A major impediment to the estimation of demographic rates often used to parameterize and refine decision-support models is that life-stage-specific monitoring data are frequently sparse for amphibians. We developed a new parameterization for integrated population models to match the ecology of amphibians and capitalize on relatively inexpensive monitoring data to document amphibian reintroductions. We evaluate the capability of this model by fitting it to Oregon spotted frog (Rana pretiosa) monitoring data collected from 2007 to 2014 following their reintroduction within the Klamath Basin, Oregon, USA. The number of egg masses encountered and the estimated adult and metamorph abundances generally increased following reintroduction. We found that survival probability from egg to metamorph ranged from 0.01 in 2008 to 0.09 in 2009 and was not related to minimum spring temperatures, metamorph survival probability ranged from 0.13 in 2010-2011 to 0.86 in 2012-2013 and was positively related to mean monthly temperatures (logit-scale slope = 2.37), adult survival probability was lower for founders (0.40) than individuals recruited after reintroduction (0.56), and the mean number of egg masses per adult female was 0.74. Our study is the first to test hypotheses concerning Oregon spotted frog egg-to-metamorph and metamorph-to-adult transition probabilities in the wild and document their response at multiple life stages following reintroduction. Furthermore, we provide an example to illustrate how the structure of our integrated population model serves as a useful foundation for amphibian decision-support models within adaptive management programs. The integration of multiple, but

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

Science.gov (United States)

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

An assessment of urban heat island effect adopting urban parameterizations in COSMO-CLM simulations over big cities in Northern Italy

Science.gov (United States)

Montesarchio, Myriam; Rianna, Guido; Mercogliano, Paola; Castellari, Sergio; Schiano, Pasquale

2015-04-01

In Europe, about 80% of people live in urban areas, which most of them can be particularly vulnerable to climate impacts (e.g. high air temperatures along with heat waves, flooding due to intense precipitation events, water scarcity and droughts). In fact, the density of people and assets within relatively small geographic areas, such as an urban settlements, mean more risk exposure than in rural areas. Therefore, reliable numerical climate models are needed for elaborating climate risk assessment at urban scale. These models must take into account the effects of the complex three-dimensional structure of urban settlements, combined with the mixture of surface types with contrasting radiative, thermal and moisture characteristics. In this respect, previous studies (e.g. Trusilova et al., 2013) have already assessed the importance to consider urban properties in very high resolution regional climate modeling to better reproduce the features of urban climate, especially in terms of urban heat island effect. In this work, two different configurations of the regional climate model COSMO-CLM at the horizontal resolution of 0.02° (about 2.2km), one including urban parameterization scheme and another without including them, have been applied in order to perform two different climate simulations covering the entire northern Italy. In particular, the present study is focused on large urban settlements such as Milan and Turin. Due to high computational cost required to run very high resolution simulations, the results of the two simulations have been compared over a period of ten years, from 1980 to 1989. Preliminary results indicate that the modification of climate conditions, due to the presence of urban areas, is present mainly in the areas covered by big cities and surrounding them, or rather the presence of urban areas induces modification mainly in their local climate. Other evidences are that the simulation including urban parameterization scheme shows, in general

Sensitivity analysis of a parameterization of the stomatal component of the DO3SE model for Quercus ilex to estimate ozone fluxes

International Nuclear Information System (INIS)

Alonso, Rocio; Elvira, Susana; Sanz, Maria J.; Gerosa, Giacomo; Emberson, Lisa D.; Bermejo, Victoria; Gimeno, Benjamin S.

2008-01-01

A sensitivity analysis of a proposed parameterization of the stomatal conductance (g s ) module of the European ozone deposition model (DO 3 SE) for Quercus ilex was performed. The performance of the model was tested against measured g s in the field at three sites in Spain. The best fit of the model was found for those sites, or during those periods, facing no or mild stress conditions, but a worse performance was found under severe drought or temperature stress, mostly occurring at continental sites. The best performance was obtained when both f phen and f SWP were included. A local parameterization accounting for the lower temperatures recorded in winter and the higher water shortage at the continental sites resulted in a better performance of the model. The overall results indicate that two different parameterizations of the model are needed, one for marine-influenced sites and another one for continental sites. - No redundancy between phenological and water-related modifying functions was found when estimating stomatal behavior of Holm oak

Herdsmen’s Adaptation to Climate Changes and Subsequent Impacts in the Ecologically Fragile Zone, China

Directory of Open Access Journals (Sweden)

Yingcheng Liu

2013-01-01

Full Text Available The change of land surface can exert significant influence on the future climate change. This study analyzed the effects of herdsmen’s adaptation to climate changes on the livestock breeding, income, and land surface dynamics with a land surface parameterization scheme. The empirical analysis was first carried out on the impacts of the adaptation measures of herdsmen on their income in the context of the climate change with the positive mathematical programming (PMP model on the basis of the household survey data in the Three-River Source Region, an ecologically fragile area in Qinghai Province, China. Then, the land surface parameterization process is analyzed based on the agent-based model (ABM, which involves the herdsmen’s adaptation measures on climate change, and it also provides reference for the land surface change projection. The result shows that the climate change adaptation measures will have a positive effect on the increasing of the amount of herdsman’s livestock and income as well as future land surface dynamics. Some suggestions on the land use management were finally proposed, which can provide significant reference information for the land use planning.

Elastic orthorhombic anisotropic parameter inversion: An analysis of parameterization

KAUST Repository

Oh, Juwon

2016-09-15

The resolution of a multiparameter full-waveform inversion (FWI) is highly influenced by the parameterization used in the inversion algorithm, as well as the data quality and the sensitivity of the data to the elastic parameters because the scattering patterns of the partial derivative wavefields (PDWs) vary with parameterization. For this reason, it is important to identify an optimal parameterization for elastic orthorhombic FWI by analyzing the radiation patterns of the PDWs for many reasonable model parameterizations. We have promoted a parameterization that allows for the separation of the anisotropic properties in the radiation patterns. The central parameter of this parameterization is the horizontal P-wave velocity, with an isotropic scattering potential, influencing the data at all scales and directions. This parameterization decouples the influence of the scattering potential given by the P-wave velocity perturbation fromthe polar changes described by two dimensionless parameter perturbations and from the azimuthal variation given by three additional dimensionless parameters perturbations. In addition, the scattering potentials of the P-wave velocity perturbation are also decoupled from the elastic influences given by one S-wave velocity and two additional dimensionless parameter perturbations. The vertical S-wave velocity is chosen with the best resolution obtained from S-wave reflections and converted waves, little influence on P-waves in conventional surface seismic acquisition. The influence of the density on observed data can be absorbed by one anisotropic parameter that has a similar radiation pattern. The additional seven dimensionless parameters describe the polar and azimuth variations in the P- and S-waves that we may acquire, with some of the parameters having distinct influences on the recorded data on the earth\\'s surface. These characteristics of the new parameterization offer the potential for a multistage inversion from high symmetry

Elastic orthorhombic anisotropic parameter inversion: An analysis of parameterization

KAUST Repository

Oh, Juwon; Alkhalifah, Tariq Ali

2016-01-01

The resolution of a multiparameter full-waveform inversion (FWI) is highly influenced by the parameterization used in the inversion algorithm, as well as the data quality and the sensitivity of the data to the elastic parameters because the scattering patterns of the partial derivative wavefields (PDWs) vary with parameterization. For this reason, it is important to identify an optimal parameterization for elastic orthorhombic FWI by analyzing the radiation patterns of the PDWs for many reasonable model parameterizations. We have promoted a parameterization that allows for the separation of the anisotropic properties in the radiation patterns. The central parameter of this parameterization is the horizontal P-wave velocity, with an isotropic scattering potential, influencing the data at all scales and directions. This parameterization decouples the influence of the scattering potential given by the P-wave velocity perturbation fromthe polar changes described by two dimensionless parameter perturbations and from the azimuthal variation given by three additional dimensionless parameters perturbations. In addition, the scattering potentials of the P-wave velocity perturbation are also decoupled from the elastic influences given by one S-wave velocity and two additional dimensionless parameter perturbations. The vertical S-wave velocity is chosen with the best resolution obtained from S-wave reflections and converted waves, little influence on P-waves in conventional surface seismic acquisition. The influence of the density on observed data can be absorbed by one anisotropic parameter that has a similar radiation pattern. The additional seven dimensionless parameters describe the polar and azimuth variations in the P- and S-waves that we may acquire, with some of the parameters having distinct influences on the recorded data on the earth's surface. These characteristics of the new parameterization offer the potential for a multistage inversion from high symmetry

Reliable control using the primary and dual Youla parameterizations

DEFF Research Database (Denmark)

Niemann, Hans Henrik; Stoustrup, J.

2002-01-01

Different aspects of modeling faults in dynamic systems are considered in connection with reliable control (RC). The fault models include models with additive faults, multiplicative faults and structural changes in the models due to faults in the systems. These descriptions are considered...... in connection with reliable control and feedback control with fault rejection. The main emphasis is on fault modeling. A number of fault diagnosis problems, reliable control problems, and feedback control with fault rejection problems are formulated/considered, again, mainly from a fault modeling point of view....... Reliability is introduced by means of the (primary) Youla parameterization of all stabilizing controllers, where an additional loop is closed around a diagnostic signal. In order to quantify the level of reliability, the dual Youla parameterization is introduced which can be used to analyze how large faults...

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

Science.gov (United States)

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.

Parameterization and evaluation of sulfate adsorption in a dynamic soil chemistry model

International Nuclear Information System (INIS)

Martinson, Liisa; Alveteg, Mattias; Warfvinge, Per

2003-01-01

Including sulfate adsorption improves the dynamic behavior of the SAFE model. - Sulfate adsorption was implemented in the dynamic, multi-layer soil chemistry model SAFE. The process is modeled by an isotherm in which sulfate adsorption is considered to be fully reversible and dependent on sulfate concentration as well as pH in soil solution. The isotherm was parameterized by a site-specific series of simple batch experiments at different pH (3.8-5.0) and sulfate concentration (10-260 μmol l -1 ) levels. Application of the model to the Lake Gaardsjoen roof covered site shows that including sulfate adsorption improves the dynamic behavior of the model and sulfate adsorption and desorption delay acidification and recovery of the soil. The modeled adsorbed pool of sulfate at the site reached a maximum level of 700 mmol/m 2 in the late 1980s, well in line with experimental data

Parameter Estimation and Sensitivity Analysis of an Urban Surface Energy Balance Parameterization at a Tropical Suburban Site

Science.gov (United States)

Harshan, S.; Roth, M.; Velasco, E.

2014-12-01

Forecasting of the urban weather and climate is of great importance as our cities become more populated and considering the combined effects of global warming and local land use changes which make urban inhabitants more vulnerable to e.g. heat waves and flash floods. In meso/global scale models, urban parameterization schemes are used to represent the urban effects. However, these schemes require a large set of input parameters related to urban morphological and thermal properties. Obtaining all these parameters through direct measurements are usually not feasible. A number of studies have reported on parameter estimation and sensitivity analysis to adjust and determine the most influential parameters for land surface schemes in non-urban areas. Similar work for urban areas is scarce, in particular studies on urban parameterization schemes in tropical cities have so far not been reported. In order to address above issues, the town energy balance (TEB) urban parameterization scheme (part of the SURFEX land surface modeling system) was subjected to a sensitivity and optimization/parameter estimation experiment at a suburban site in, tropical Singapore. The sensitivity analysis was carried out as a screening test to identify the most sensitive or influential parameters. Thereafter, an optimization/parameter estimation experiment was performed to calibrate the input parameter. The sensitivity experiment was based on the "improved Sobol's global variance decomposition method" . The analysis showed that parameters related to road, roof and soil moisture have significant influence on the performance of the model. The optimization/parameter estimation experiment was performed using the AMALGM (a multi-algorithm genetically adaptive multi-objective method) evolutionary algorithm. The experiment showed a remarkable improvement compared to the simulations using the default parameter set. The calibrated parameters from this optimization experiment can be used for further model

Sensitivity of Greenland Ice Sheet surface mass balance to surface albedo parameterization: a study with a regional climate model

OpenAIRE

Angelen, J. H.; Lenaerts, J. T. M.; Lhermitte, S.; Fettweis, X.; Kuipers Munneke, P.; Broeke, M. R.; Meijgaard, E.; Smeets, C. J. P. P.

2012-01-01

We present a sensitivity study of the surface mass balance (SMB) of the Greenland Ice Sheet, as modeled using a regional atmospheric climate model, to various parameter settings in the albedo scheme. The snow albedo scheme uses grain size as a prognostic variable and further depends on cloud cover, solar zenith angle and black carbon concentration. For the control experiment the overestimation of absorbed shortwave radiation (+6%) at the K-transect (west Greenland) for the period 2004–2009 is...

A satellite simulator for TRMM PR applied to climate model simulations

Science.gov (United States)

Spangehl, T.; Schroeder, M.; Bodas-Salcedo, A.; Hollmann, R.; Riley Dellaripa, E. M.; Schumacher, C.

2017-12-01

Climate model simulations have to be compared against observation based datasets in order to assess their skill in representing precipitation characteristics. Here we use a satellite simulator for TRMM PR in order to evaluate simulations performed with MPI-ESM (Earth system model of the Max Planck Institute for Meteorology in Hamburg, Germany) performed within the MiKlip project (https://www.fona-miklip.de/, funded by Federal Ministry of Education and Research in Germany). While classical evaluation methods focus on geophysical parameters such as precipitation amounts, the application of the satellite simulator enables an evaluation in the instrument's parameter space thereby reducing uncertainties on the reference side. The CFMIP Observation Simulator Package (COSP) provides a framework for the application of satellite simulators to climate model simulations. The approach requires the introduction of sub-grid cloud and precipitation variability. Radar reflectivities are obtained by applying Mie theory, with the microphysical assumptions being chosen to match the atmosphere component of MPI-ESM (ECHAM6). The results are found to be sensitive to the methods used to distribute the convective precipitation over the sub-grid boxes. Simple parameterization methods are used to introduce sub-grid variability of convective clouds and precipitation. In order to constrain uncertainties a comprehensive comparison with sub-grid scale convective precipitation variability which is deduced from TRMM PR observations is carried out.

Design off-shore wind climate

Energy Technology Data Exchange (ETDEWEB)

Larsen, G C; Joergensen, H E [Risoe National Lab., Wind Energy and Atmospheric Physics Dept., Roskilde (Denmark)

1999-03-01

Specific recommendations of off-shore turbulence intensities, applicable for design purposes, are lacking in the present IEC-code. The present off-shore wind climate analysis presents the distribution of the turbulence standard deviation around the mean turbulence standard deviation, conditioned on the mean wind speed. Measured distributions, based on a huge amount of measuring data from two shallow water off-shore sites, are parameterized by fitting to a three parameter Weibull distribution. Combining a simple heuristic load model with the parameterized probability density functions of the turbulence standard deviations, an empirical off-shore design turbulence intensity is evaluated that in average yields the same fatigue damage as the distributed turbulence intensity. The proposed off-shore design turbulence intensity is, within the IEC code framework, applicable for extreme as well as for fatigue load determination. (au)

Invariant box parameterization of neutrino oscillations

International Nuclear Information System (INIS)

Weiler, T.J.; Wagner, D.

1998-01-01

The model-independent 'box' parameterization of neutrino oscillations is examined. The invariant boxes are the classical amplitudes of the individual oscillating terms. Being observables, the boxes are independent of the choice of parameterization of the mixing matrix. Emphasis is placed on the relations among the box parameters due to mixing matrix unitarity, and on the reduction of the number of boxes to the minimum basis set. Using the box algebra, we show that CP-violation may be inferred from measurements of neutrino flavor mixing even when the oscillatory factors have averaged. General analyses of neutrino oscillations among n≥3 flavors can readily determine the boxes, which can then be manipulated to yield magnitudes of mixing matrix elements. copyright 1998 American Institute of Physics

Polynomial Chaos–Based Bayesian Inference of K-Profile Parameterization in a General Circulation Model of the Tropical Pacific

KAUST Repository

Sraj, Ihab; Zedler, Sarah E.; Knio, Omar; Jackson, Charles S.; Hoteit, Ibrahim

2016-01-01

The authors present a polynomial chaos (PC)-based Bayesian inference method for quantifying the uncertainties of the K-profile parameterization (KPP) within the MIT general circulation model (MITgcm) of the tropical Pacific. The inference

Climate Impacts of Fire-Induced Land-Surface Changes

Science.gov (United States)

Liu, Y.; Hao, X.; Qu, J. J.

2017-12-01

One of the consequences of wildfires is the changes in land-surface properties such as removal of vegetation. This will change local and regional climate through modifying the land-air heat and water fluxes. This study investigates mechanism by developing and a parameterization of fire-induced land-surface property changes and applying it to modeling of the climate impacts of large wildfires in the United States. Satellite remote sensing was used to quantitatively evaluate the land-surface changes from large fires provided from the Monitoring Trends in Burning Severity (MTBS) dataset. It was found that the changes in land-surface properties induced by fires are very complex, depending on vegetation type and coverage, climate type, season and time after fires. The changes in LAI are remarkable only if the actual values meet a threshold. Large albedo changes occur in winter for fires in cool climate regions. The signs are opposite between the first post-fire year and the following years. Summer day-time temperature increases after fires, while nigh-time temperature changes in various patterns. The changes are larger in forested lands than shrub / grassland lands. In the parameterization scheme, the detected post-fire changes are decomposed into trends using natural exponential functions and fluctuations of periodic variations with the amplitudes also determined by natural exponential functions. The final algorithm is a combination of the trends, periods, and amplitude functions. This scheme is used with Earth system models to simulate the local and regional climate effects of wildfires.

Automatic Parameterization Strategy for Cardiac Electrophysiology Simulations

OpenAIRE

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

2013-01-01

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 ...

Towards product design automation based on parameterized standard model with diversiform knowledge

Science.gov (United States)

Liu, Wei; Zhang, Xiaobing

2017-04-01

Product standardization based on CAD software is an effective way to improve design efficiency. In the past, research and development on standardization mainly focused on the level of component, and the standardization of the entire product as a whole is rarely taken into consideration. In this paper, the size and structure of 3D product models are both driven by the Excel datasheets, based on which a parameterized model library is therefore established. Diversiform knowledge including associated parameters and default properties are embedded into the templates in advance to simplify their reuse. Through the simple operation, we can obtain the correct product with the finished 3D models including single parts or complex assemblies. Two examples are illustrated later to invalid the idea, which will greatly improve the design efficiency.

Effects of cloudy/clear air mixing and droplet pH on sulfate aerosol formation in a coupled chemistry/climate global model

Energy Technology Data Exchange (ETDEWEB)

Molenkamp, C.R.; Atherton, C.A. [Lawrence Livermore National Lab., CA (United States); Penner, J.E.; Walton, J.J. [Michigan Univ., Ann Arbor, MI (United States). Dept. of Atmospheric, Oceanic and Space Sciences

1996-10-01

In this paper we will briefly describe our coupled ECHAM/GRANTOUR model, provide a detailed description of our atmospheric chemistry parameterizations, and discuss a couple of numerical experiments in which we explore the influence of assumed pH and rate of mixing between cloudy and clear air on aqueous sulfate formation and concentration. We have used our tropospheric chemistry and transport model, GRANTOUR, to estimate the life cycle and global distributions of many trace species. Recently, we have coupled GRANTOUR with the ECHAM global climate model, which provides several enhanced capabilities in the representation of aerosol interactions.

Combining state-and-transition simulations and species distribution models to anticipate the effects of climate change

Science.gov (United States)

Miller, Brian W.; Frid, Leonardo; Chang, Tony; Piekielek, N. B.; Hansen, Andrew J.; Morisette, Jeffrey T.

2015-01-01

State-and-transition simulation models (STSMs) are known for their ability to explore the combined effects of multiple disturbances, ecological dynamics, and management actions on vegetation. However, integrating the additional impacts of climate change into STSMs remains a challenge. We address this challenge by combining an STSM with species distribution modeling (SDM). SDMs estimate the probability of occurrence of a given species based on observed presence and absence locations as well as environmental and climatic covariates. Thus, in order to account for changes in habitat suitability due to climate change, we used SDM to generate continuous surfaces of species occurrence probabilities. These data were imported into ST-Sim, an STSM platform, where they dictated the probability of each cell transitioning between alternate potential vegetation types at each time step. The STSM was parameterized to capture additional processes of vegetation growth and disturbance that are relevant to a keystone species in the Greater Yellowstone Ecosystem—whitebark pine (Pinus albicaulis). We compared historical model runs against historical observations of whitebark pine and a key disturbance agent (mountain pine beetle, Dendroctonus ponderosae), and then projected the simulation into the future. Using this combination of correlative and stochastic simulation models, we were able to reproduce historical observations and identify key data gaps. Results indicated that SDMs and STSMs are complementary tools, and combining them is an effective way to account for the anticipated impacts of climate change, biotic interactions, and disturbances, while also allowing for the exploration of management options.

Distance parameterization for efficient seismic history matching with the ensemble Kalman Filter

NARCIS (Netherlands)

Leeuwenburgh, O.; Arts, R.

2012-01-01

The Ensemble Kalman Filter (EnKF), in combination with travel-time parameterization, provides a robust and flexible method for quantitative multi-model history matching to time-lapse seismic data. A disadvantage of the parameterization in terms of travel-times is that it requires simulation of

Best convective parameterization scheme within RegCM4 to downscale CMIP5 multi-model data for the CORDEX-MENA/Arab domain

Science.gov (United States)

Almazroui, Mansour; Islam, Md. Nazrul; Al-Khalaf, A. K.; Saeed, Fahad

2016-05-01

A suitable convective parameterization scheme within Regional Climate Model version 4.3.4 (RegCM4) developed by the Abdus Salam International Centre for Theoretical Physics, Trieste, Italy, is investigated through 12 sensitivity runs for the period 2000-2010. RegCM4 is driven with European Centre for Medium-Range Weather Forecasts (ECMWF) ERA-Interim 6-hourly boundary condition fields for the CORDEX-MENA/Arab domain. Besides ERA-Interim lateral boundary conditions data, the Climatic Research Unit (CRU) data is also used to assess the performance of RegCM4. Different statistical measures are taken into consideration in assessing model performance for 11 sub-domains throughout the analysis domain, out of which 7 (4) sub-domains give drier (wetter) conditions for the area of interest. There is no common best option for the simulation of both rainfall and temperature (with lowest bias); however, one option each for temperature and rainfall has been found to be superior among the 12 options investigated in this study. These best options for the two variables vary from region to region as well. Overall, RegCM4 simulates large pressure and water vapor values along with lower wind speeds compared to the driving fields, which are the key sources of bias in simulating rainfall and temperature. Based on the climatic characteristics of most of the Arab countries located within the study domain, the drier sub-domains are given priority in the selection of a suitable convective scheme, albeit with a compromise for both rainfall and temperature simulations. The most suitable option Grell over Land and Emanuel over Ocean in wet (GLEO wet) delivers a rainfall wet bias of 2.96 % and a temperature cold bias of 0.26 °C, compared to CRU data. An ensemble derived from all 12 runs provides unsatisfactory results for rainfall (28.92 %) and temperature (-0.54 °C) bias in the drier region because some options highly overestimate rainfall (reaching up to 200 %) and underestimate

Framework for Probabilistic Projections of Energy-Relevant Streamflow Indicators under Climate Change Scenarios for the U.S.

Energy Technology Data Exchange (ETDEWEB)

Wagener, Thorsten [Univ. of Bristol (United Kingdom); Mann, Michael [Pennsylvania State Univ., State College, PA (United States); Crane, Robert [Pennsylvania State Univ., State College, PA (United States)

2014-04-29

This project focuses on uncertainty in streamflow forecasting under climate change conditions. The objective is to develop easy to use methodologies that can be applied across a range of river basins to estimate changes in water availability for realistic projections of climate change. There are three major components to the project: Empirical downscaling of regional climate change projections from a range of Global Climate Models; Developing a methodology to use present day information on the climate controls on the parameterizations in streamflow models to adjust the parameterizations under future climate conditions (a trading-space-for-time approach); and Demonstrating a bottom-up approach to establishing streamflow vulnerabilities to climate change. The results reinforce the need for downscaling of climate data for regional applications, and further demonstrates the challenges of using raw GCM data to make local projections. In addition, it reinforces the need to make projections across a range of global climate models. The project demonstrates the potential for improving streamflow forecasts by using model parameters that are adjusted for future climate conditions, but suggests that even with improved streamflow models and reduced climate uncertainty through the use of downscaled data, there is still large uncertainty is the streamflow projections. The most useful output from the project is the bottom-up vulnerability driven approach to examining possible climate and land use change impacts on streamflow. Here, we demonstrate an inexpensive and easy to apply methodology that uses Classification and Regression Trees (CART) to define the climate and environmental parameters space that can produce vulnerabilities in the system, and then feeds in the downscaled projections to determine the probability top transitioning to a vulnerable sate. Vulnerabilities, in this case, are defined by the end user.

Parameterized examination in econometrics

Science.gov (United States)

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.

Sensitivity analysis of a parameterization of the stomatal component of the DO{sub 3}SE model for Quercus ilex to estimate ozone fluxes

Energy Technology Data Exchange (ETDEWEB)

Alonso, Rocio [Ecotoxicology of Air Pollution, CIEMAT, Avenida Complutense 22, 28040 Madrid (Spain)], E-mail: rocio.alonso@ciemat.es; Elvira, Susana [Ecotoxicology of Air Pollution, CIEMAT, Avenida Complutense 22, 28040 Madrid (Spain)], E-mail: susana.elvira@ciemat.es; Sanz, Maria J. [Fundacion CEAM, Charles Darwin 14, 46980 Paterna, Valencia (Spain)], E-mail: mjose@ceam.es; Gerosa, Giacomo [Department of Mathematics and Physics, Universita Cattolica del Sacro Cuore, via Musei 41, 25121 Brescia (Italy)], E-mail: giacomo.gerosa@unicatt.it; Emberson, Lisa D. [Stockholm Environment Institute, University of York, York YO 10 5DD (United Kingdom)], E-mail: lde1@york.ac.uk; Bermejo, Victoria [Ecotoxicology of Air Pollution, CIEMAT, Avenida Complutense 22, 28040 Madrid (Spain)], E-mail: victoria.bermejo@ciemat.es; Gimeno, Benjamin S. [Ecotoxicology of Air Pollution, CIEMAT, Avenida Complutense 22, 28040 Madrid (Spain)], E-mail: benjamin.gimeno@ciemat.es

2008-10-15

A sensitivity analysis of a proposed parameterization of the stomatal conductance (g{sub s}) module of the European ozone deposition model (DO{sub 3}SE) for Quercus ilex was performed. The performance of the model was tested against measured g{sub s} in the field at three sites in Spain. The best fit of the model was found for those sites, or during those periods, facing no or mild stress conditions, but a worse performance was found under severe drought or temperature stress, mostly occurring at continental sites. The best performance was obtained when both f{sub phen} and f{sub SWP} were included. A local parameterization accounting for the lower temperatures recorded in winter and the higher water shortage at the continental sites resulted in a better performance of the model. The overall results indicate that two different parameterizations of the model are needed, one for marine-influenced sites and another one for continental sites. - No redundancy between phenological and water-related modifying functions was found when estimating stomatal behavior of Holm oak.

Downscaling a Global Climate Model to Simulate Climate Change Impacts on U.S. Regional and Urban Air Quality

Science.gov (United States)

Trail, M.; Tsimpidi, A. P.; Liu, P.; Tsigaridis, K.; Hu, Y.; Nenes, A.; Russell, A. G.

2013-01-01

Climate change can exacerbate future regional air pollution events by making conditions more favorable to form high levels of ozone. In this study, we use spectral nudging with WRF to downscale NASA earth system GISS modelE2 results during the years 2006 to 2010 and 2048 to 2052 over the continental United States in order to compare the resulting meteorological fields from the air quality perspective during the four seasons of five-year historic and future climatological periods. GISS results are used as initial and boundary conditions by the WRF RCM to produce hourly meteorological fields. The downscaling technique and choice of physics parameterizations used are evaluated by comparing them with in situ observations. This study investigates changes of similar regional climate conditions down to a 12km by 12km resolution, as well as the effect of evolving climate conditions on the air quality at major U.S. cities. The high resolution simulations produce somewhat different results than the coarse resolution simulations in some regions. Also, through the analysis of the meteorological variables that most strongly influence air quality, we find consistent changes in regional climate that would enhance ozone levels in four regions of the U.S. during fall (Western U.S., Texas, Northeastern, and Southeastern U.S), one region during summer (Texas), and one region where changes potentially would lead to better air quality during spring (Northeast). We also find that daily peak temperatures tend to increase in most major cities in the U.S. which would increase the risk of health problems associated with heat stress. Future work will address a more comprehensive assessment of emissions and chemistry involved in the formation and removal of air pollutants.

TRACKING CLIMATE MODELS

Data.gov (United States)

National Aeronautics and Space Administration — CLAIRE MONTELEONI*, GAVIN SCHMIDT, AND SHAILESH SAROHA* Climate models are complex mathematical models designed by meteorologists, geophysicists, and climate...

Modeling dynamics of western juniper under climate change in a semiarid ecosystem

Science.gov (United States)

Shrestha, R.; Glenn, N. F.; Flores, A. N.

2013-12-01

Modeling future vegetation dynamics in response to climate change and disturbances such as fire relies heavily on model parameterization. Fine-scale field-based measurements can provide the necessary parameters for constraining models at a larger scale. But the time- and labor-intensive nature of field-based data collection leads to sparse sampling and significant spatial uncertainties in retrieved parameters. In this study we quantify the fine-scale carbon dynamics and uncertainty of juniper woodland in the Reynolds Creek Experimental Watershed (RCEW) in southern Idaho, which is a proposed critical zone observatory (CZO) site for soil carbon processes. We leverage field-measured vegetation data along with airborne lidar and timeseries Landsat imagery to initialize a state-and-transition model (VDDT) and a process-based fire-model (FlamMap) to examine the vegetation dynamics in response to stochastic fire events and climate change. We utilize recently developed and novel techniques to measure biomass and canopy characteristics of western juniper at the individual tree scale using terrestrial and airborne laser scanning techniques in RCEW. These fine-scale data are upscaled across the watershed for the VDDT and FlamMap models. The results will immediately improve our understanding of fine-scale dynamics and carbon stocks and fluxes of woody vegetation in a semi-arid ecosystem. Moreover, quantification of uncertainty will also provide a basis for generating ensembles of spatially-explicit alternative scenarios to guide future land management decisions in the region.

Elastic FWI for VTI media: A synthetic parameterization study

KAUST Repository

Kamath, Nishant

2016-09-06

A major challenge for multiparameter full-waveform inversion (FWI) is the inherent trade-offs (or cross-talk) between model parameters. Here, we perform FWI of multicomponent data generated for a synthetic VTI (transversely isotropic with a vertical symmetry axis) model based on a geologic section of the Valhall field. A horizontal displacement source, which excites intensive shear waves in the conventional offset range, helps provide more accurate updates to the SV-wave vertical velocity. We test three model parameterizations, which exhibit different radiation patterns and, therefore, create different parameter trade-offs. The results show that the choice of parameterization for FWI depends on the availability of long-offset data, the quality of the initial model for the anisotropy coefficients, and the parameter that needs to be resolved with the highest accuracy.

Quantifying the economic risks of climate change

Science.gov (United States)

Diaz, Delavane; Moore, Frances

2017-11-01

Understanding the value of reducing greenhouse-gas emissions matters for policy decisions and climate risk management, but quantification is challenging because of the complex interactions and uncertainties in the Earth and human systems, as well as normative ethical considerations. Current modelling approaches use damage functions to parameterize a simplified relationship between climate variables, such as temperature change, and economic losses. Here we review and synthesize the limitations of these damage functions and describe how incorporating impacts, adaptation and vulnerability research advances and empirical findings could substantially improve damage modelling and the robustness of social cost of carbon values produced. We discuss the opportunities and challenges associated with integrating these research advances into cost-benefit integrated assessment models, with guidance for future work.

Parameterization of cirrus microphysical and radiative properties in larger-scale models

International Nuclear Information System (INIS)

Heymsfield, A.J.; Coen, J.L.

1994-01-01

This study exploits measurements in clouds sampled during several field programs to develop and validate parameterizations that represent the physical and radiative properties of convectively generated cirrus clouds in intermediate and large-scale models. The focus is on cirrus anvils because they occur frequently, cover large areas, and play a large role in the radiation budget. Preliminary work focuses on understanding the microphysical, radiative, and dynamical processes that occur in these clouds. A detailed microphysical package has been constructed that considers the growth of the following hydrometer types: water drops, needles, plates, dendrites, columns, bullet rosettes, aggregates, graupel, and hail. Particle growth processes include diffusional and accretional growth, aggregation, sedimentation, and melting. This package is being implemented in a simple dynamical model that tracks the evolution and dispersion of hydrometers in a stratiform anvil cloud. Given the momentum, vapor, and ice fluxes into the stratiform region and the temperature and humidity structure in the anvil's environment, this model will suggest anvil properties and structure

An improved hindcast approach for evaluation and diagnosis of physical processes in global climate models

Science.gov (United States)

Ma, H.-Y.; Chuang, C. C.; Klein, S. A.; Lo, M.-H.; Zhang, Y.; Xie, S.; Zheng, X.; Ma, P.-L.; Zhang, Y.; Phillips, T. J.

2015-12-01

We present an improved procedure of generating initial conditions (ICs) for climate model hindcast experiments with specified sea surface temperature and sea ice. The motivation is to minimize errors in the ICs and lead to a better evaluation of atmospheric parameterizations' performance in the hindcast mode. We apply state variables (horizontal velocities, temperature, and specific humidity) from the operational analysis/reanalysis for the atmospheric initial states. Without a data assimilation system, we apply a two-step process to obtain other necessary variables to initialize both the atmospheric (e.g., aerosols and clouds) and land models (e.g., soil moisture). First, we nudge only the model horizontal velocities toward operational analysis/reanalysis values, given a 6 h relaxation time scale, to obtain all necessary variables. Compared to the original strategy in which horizontal velocities, temperature, and specific humidity are nudged, the revised approach produces a better representation of initial aerosols and cloud fields which are more consistent and closer to observations and model's preferred climatology. Second, we obtain land ICs from an off-line land model simulation forced with observed precipitation, winds, and surface fluxes. This approach produces more realistic soil moisture in the land ICs. With this refined procedure, the simulated precipitation, clouds, radiation, and surface air temperature over land are improved in the Day 2 mean hindcasts. Following this procedure, we propose a "Core" integration suite which provides an easily repeatable test allowing model developers to rapidly assess the impacts of various parameterization changes on the fidelity of modeled cloud-associated processes relative to observations.

USING PARAMETERIZATION OF OBJECTS IN AUTODESK INVENTOR IN DESIGNING STRUCTURAL CONNECTORS

Directory of Open Access Journals (Sweden)

Gabriel Borowski

2015-05-01

Full Text Available The article presents the parameterization of objects used for designing the type of elements as structural connectors and making modifications of their characteristics. The design process was carried out using Autodesk Inventor 2015. We show the latest software tools, which were used for parameterization and modeling selected types of structural connectors. We also show examples of the use of parameterization facilities in the process of constructing some details and making changes to geometry with holding of the shape the element. The presented method of Inventor usage has enabled fast and efficient creation of new objects based on sketches created.

The quest for reliable regional scenarios of climate change

International Nuclear Information System (INIS)

Gates, W.L.

1991-01-01

A number of problems still confront climate modelers if the challenge of providing information that can be used for local impact estimation is to be met. First, the models must be improved. Models continue to show large systematic errors, and the structure and behavior of these errors are not well understood. This suggests the need for more analysis, diagnosis, and intercomparison of model results, in order to understand the reasons for the differences among models and their sensitivity to both parameterization and resolution. It is to be hoped that the resources necessary to do this on a sustained and coordinated basis will be made available. It should also be recognized that modeled climate changes will inevitably be in terms of frequency distributions rather than categorical results. Ideally, these distributions should be constructed from the statistics of an ensemble of model runs, rather than by guessing or by uncertain analogs. Such information would permit the determination of the risk or uncertainty of the derived climate impact estimates and would place climate model applications on a firmer scientific basis

Impact of global warming on the geobotanic zones: an experiment with a statistical-dynamical climate model

Energy Technology Data Exchange (ETDEWEB)

Franchito, Sergio H.; Brahmananda Rao, V. [Instituto Nacional de Pesquisas Espaciais, Centro de Ciencia do Sistema Terrestre, CCST, Sau Paulo, SP (Brazil); Moraes, E.C. [Instituto Nacional de Pesquisas Espaciais, Divisao de Sensoriamento Remoto, DSR, Sau Paulo, SP (Brazil)

2011-11-15

In this study, a zonally-averaged statistical climate model (SDM) is used to investigate the impact of global warming on the distribution of the geobotanic zones over the globe. The model includes a parameterization of the biogeophysical feedback mechanism that links the state of surface to the atmosphere (a bidirectional interaction between vegetation and climate). In the control experiment (simulation of the present-day climate) the geobotanic state is well simulated by the model, so that the distribution of the geobotanic zones over the globe shows a very good agreement with the observed ones. The impact of global warming on the distribution of the geobotanic zones is investigated considering the increase of CO{sub 2} concentration for the B1, A2 and A1FI scenarios. The results showed that the geobotanic zones over the entire earth can be modified in future due to global warming. Expansion of subtropical desert and semi-desert zones in the Northern and Southern Hemispheres, retreat of glaciers and sea-ice, with the Arctic region being particularly affected and a reduction of the tropical rainforest and boreal forest can occur due to the increase of the greenhouse gases concentration. The effects were more pronounced in the A1FI and A2 scenarios compared with the B1 scenario. The SDM results confirm IPCC AR4 projections of future climate and are consistent with simulations of more complex GCMs, reinforcing the necessity of the mitigation of climate change associated to global warming. (orig.)

A subgrid parameterization scheme for precipitation

Directory of Open Access Journals (Sweden)

S. Turner

2012-04-01

Full Text Available With increasing computing power, the horizontal resolution of numerical weather prediction (NWP models is improving and today reaches 1 to 5 km. Nevertheless, clouds and precipitation formation are still subgrid scale processes for most cloud types, such as cumulus and stratocumulus. Subgrid scale parameterizations for water vapor condensation have been in use for many years and are based on a prescribed probability density function (PDF of relative humidity spatial variability within the model grid box, thus providing a diagnosis of the cloud fraction. A similar scheme is developed and tested here. It is based on a prescribed PDF of cloud water variability and a threshold value of liquid water content for droplet collection to derive a rain fraction within the model grid. Precipitation of rainwater raises additional concerns relative to the overlap of cloud and rain fractions, however. The scheme is developed following an analysis of data collected during field campaigns in stratocumulus (DYCOMS-II and fair weather cumulus (RICO and tested in a 1-D framework against large eddy simulations of these observed cases. The new parameterization is then implemented in a 3-D NWP model with a horizontal resolution of 2.5 km to simulate real cases of precipitating cloud systems over France.

Hydrological modeling as an evaluation tool of EURO-CORDEX climate projections and bias correction methods

Science.gov (United States)

Hakala, Kirsti; Addor, Nans; Seibert, Jan

2017-04-01

Streamflow stemming from Switzerland's mountainous landscape will be influenced by climate change, which will pose significant challenges to the water management and policy sector. In climate change impact research, the determination of future streamflow is impeded by different sources of uncertainty, which propagate through the model chain. In this research, we explicitly considered the following sources of uncertainty: (1) climate models, (2) downscaling of the climate projections to the catchment scale, (3) bias correction method and (4) parameterization of the hydrological model. We utilize climate projections at the 0.11 degree 12.5 km resolution from the EURO-CORDEX project, which are the most recent climate projections for the European domain. EURO-CORDEX is comprised of regional climate model (RCM) simulations, which have been downscaled from global climate models (GCMs) from the CMIP5 archive, using both dynamical and statistical techniques. Uncertainties are explored by applying a modeling chain involving 14 GCM-RCMs to ten Swiss catchments. We utilize the rainfall-runoff model HBV Light, which has been widely used in operational hydrological forecasting. The Lindström measure, a combination of model efficiency and volume error, was used as an objective function to calibrate HBV Light. Ten best sets of parameters are then achieved by calibrating using the genetic algorithm and Powell optimization (GAP) method. The GAP optimization method is based on the evolution of parameter sets, which works by selecting and recombining high performing parameter sets with each other. Once HBV is calibrated, we then perform a quantitative comparison of the influence of biases inherited from climate model simulations to the biases stemming from the hydrological model. The evaluation is conducted over two time periods: i) 1980-2009 to characterize the simulation realism under the current climate and ii) 2070-2099 to identify the magnitude of the projected change of

The ECHAM3 atmospheric general circulation model

International Nuclear Information System (INIS)

1993-09-01

The ECHAM model has been developed from the ECMWF model (cycle 31, November 1988). It contains several changes, mostly in the parameterization, in order to adjust the model for climate simulations. The technical details of the ECHAM operational model are described. (orig./KW)

Progress Towards Achieving the Challenge of Indian Summer Monsoon Climate Simulation in a Coupled Ocean-Atmosphere Model

Science.gov (United States)

Hazra, Anupam; Chaudhari, Hemantkumar S.; Saha, Subodh Kumar; Pokhrel, Samir; Goswami, B. N.

2017-10-01

Simulation of the spatial and temporal structure of the monsoon intraseasonal oscillations (MISOs), which have effects on the seasonal mean and annual cycle of Indian summer monsoon (ISM) rainfall, remains a grand challenge for the state-of-the-art global coupled models. Biases in simulation of the amplitude and northward propagation of MISOs and related dry rainfall bias over ISM region in climate models are limiting the current skill of monsoon prediction. Recent observations indicate that the convective microphysics of clouds may be critical in simulating the observed MISOs. The hypothesis is strongly supported by high fidelity in simulation of the amplitude and space-time spectra of MISO by a coupled climate model, when our physically based modified cloud microphysics scheme is implemented in conjunction with a modified new Simple Arakawa Schubert (nSAS) convective parameterization scheme. Improved simulation of MISOs appears to have been aided by much improved simulation of the observed high cloud fraction and convective to stratiform rain fractions and resulted into a much improved simulation of the ISM rainfall, monsoon onset, and the annual cycle.

Climate models and scenarios

Energy Technology Data Exchange (ETDEWEB)

Fortelius, C; Holopainen, E; Kaurola, J; Ruosteenoja, K; Raeisaenen, J [Helsinki Univ. (Finland). Dept. of Meteorology

1997-12-31

In recent years the modelling of interannual climate variability has been studied, the atmospheric energy and water cycles, and climate simulations with the ECHAM3 model. In addition, the climate simulations of several models have been compared with special emphasis in the area of northern Europe

Climate models and scenarios

Energy Technology Data Exchange (ETDEWEB)

Fortelius, C.; Holopainen, E.; Kaurola, J.; Ruosteenoja, K.; Raeisaenen, J. [Helsinki Univ. (Finland). Dept. of Meteorology

1996-12-31

In recent years the modelling of interannual climate variability has been studied, the atmospheric energy and water cycles, and climate simulations with the ECHAM3 model. In addition, the climate simulations of several models have been compared with special emphasis in the area of northern Europe

ARM Data-Oriented Metrics and Diagnostics Package for Climate Model Evaluation Value-Added Product

Energy Technology Data Exchange (ETDEWEB)

Zhang, Chengzhu [Lawrence Livermore National Lab. (LLNL), Livermore, CA (United States); Xie, Shaocheng [Lawrence Livermore National Lab. (LLNL), Livermore, CA (United States)

2017-10-15

A Python-based metrics and diagnostics package is currently being developed by the U.S. Department of Energy (DOE) Atmospheric Radiation Measurement (ARM) Infrastructure Team at Lawrence Livermore National Laboratory (LLNL) to facilitate the use of long-term, high-frequency measurements from the ARM Facility in evaluating the regional climate simulation of clouds, radiation, and precipitation. This metrics and diagnostics package computes climatological means of targeted climate model simulation and generates tables and plots for comparing the model simulation with ARM observational data. The Coupled Model Intercomparison Project (CMIP) model data sets are also included in the package to enable model intercomparison as demonstrated in Zhang et al. (2017). The mean of the CMIP model can serve as a reference for individual models. Basic performance metrics are computed to measure the accuracy of mean state and variability of climate models. The evaluated physical quantities include cloud fraction, temperature, relative humidity, cloud liquid water path, total column water vapor, precipitation, sensible and latent heat fluxes, and radiative fluxes, with plan to extend to more fields, such as aerosol and microphysics properties. Process-oriented diagnostics focusing on individual cloud- and precipitation-related phenomena are also being developed for the evaluation and development of specific model physical parameterizations. The version 1.0 package is designed based on data collected at ARM’s Southern Great Plains (SGP) Research Facility, with the plan to extend to other ARM sites. The metrics and diagnostics package is currently built upon standard Python libraries and additional Python packages developed by DOE (such as CDMS and CDAT). The ARM metrics and diagnostic package is available publicly with the hope that it can serve as an easy entry point for climate modelers to compare their models with ARM data. In this report, we first present the input data, which

A Flexible Atmospheric Modeling Framework for the CESM

Energy Technology Data Exchange (ETDEWEB)

Randall, David [Colorado State University; Heikes, Ross [Colorado State University; Konor, Celal [Colorado State University

2014-11-12

We have created two global dynamical cores based on the unified system of equations and Z-grid staggering on an icosahedral grid, which are collectively called UZIM (Unified Z-grid Icosahedral Model). The z-coordinate version (UZIM-height) can be run in hydrostatic and nonhydrostatic modes. The sigma-coordinate version (UZIM-sigma) runs in only hydrostatic mode. The super-parameterization has been included as a physics option in both models. The UZIM versions with the super-parameterization are called SUZI. With SUZI-height, we have completed aquaplanet runs. With SUZI-sigma, we are making aquaplanet runs and realistic climate simulations. SUZI-sigma includes realistic topography and a SiB3 model to parameterize the land-surface processes.

A Multi-Scale Energy Food Systems Modeling Framework For Climate Adaptation

Science.gov (United States)

Siddiqui, S.; Bakker, C.; Zaitchik, B. F.; Hobbs, B. F.; Broaddus, E.; Neff, R.; Haskett, J.; Parker, C.

2016-12-01

Our goal is to understand coupled system dynamics across scales in a manner that allows us to quantify the sensitivity of critical human outcomes (nutritional satisfaction, household economic well-being) to development strategies and to climate or market induced shocks in sub-Saharan Africa. We adopt both bottom-up and top-down multi-scale modeling approaches focusing our efforts on food, energy, water (FEW) dynamics to define, parameterize, and evaluate modeled processes nationally as well as across climate zones and communities. Our framework comprises three complementary modeling techniques spanning local, sub-national and national scales to capture interdependencies between sectors, across time scales, and on multiple levels of geographic aggregation. At the center is a multi-player micro-economic (MME) partial equilibrium model for the production, consumption, storage, and transportation of food, energy, and fuels, which is the focus of this presentation. We show why such models can be very useful for linking and integrating across time and spatial scales, as well as a wide variety of models including an agent-based model applied to rural villages and larger population centers, an optimization-based electricity infrastructure model at a regional scale, and a computable general equilibrium model, which is applied to understand FEW resources and economic patterns at national scale. The MME is based on aggregating individual optimization problems for relevant players in an energy, electricity, or food market and captures important food supply chain components of trade and food distribution accounting for infrastructure and geography. Second, our model considers food access and utilization by modeling food waste and disaggregating consumption by income and age. Third, the model is set up to evaluate the effects of seasonality and system shocks on supply, demand, infrastructure, and transportation in both energy and food.

Combining state-and-transition simulations and species distribution models to anticipate the effects of climate change

Directory of Open Access Journals (Sweden)

Brian W. Miller

2015-05-01

Full Text Available State-and-transition simulation models (STSMs are known for their ability to explore the combined effects of multiple disturbances, ecological dynamics, and management actions on vegetation. However, integrating the additional impacts of climate change into STSMs remains a challenge. We address this challenge by combining an STSM with species distribution modeling (SDM. SDMs estimate the probability of occurrence of a given species based on observed presence and absence locations as well as environmental and climatic covariates. Thus, in order to account for changes in habitat suitability due to climate change, we used SDM to generate continuous surfaces of species occurrence probabilities. These data were imported into ST-Sim, an STSM platform, where they dictated the probability of each cell transitioning between alternate potential vegetation types at each time step. The STSM was parameterized to capture additional processes of vegetation growth and disturbance that are relevant to a keystone species in the Greater Yellowstone Ecosystem—whitebark pine (Pinus albicaulis. We compared historical model runs against historical observations of whitebark pine and a key disturbance agent (mountain pine beetle, Dendroctonus ponderosae, and then projected the simulation into the future. Using this combination of correlative and stochastic simulation models, we were able to reproduce historical observations and identify key data gaps. Results indicated that SDMs and STSMs are complementary tools, and combining them is an effective way to account for the anticipated impacts of climate change, biotic interactions, and disturbances, while also allowing for the exploration of management options.

Mechanistic variables can enhance predictive models of endotherm distributions: The American pika under current, past, and future climates

Science.gov (United States)

Mathewson, Paul; Moyer-Horner, Lucas; Beever, Erik; Briscoe, Natalie; Kearney, Michael T.; Yahn, Jeremiah; Porter, Warren P.

2017-01-01

How climate constrains species’ distributions through time and space is an important question in the context of conservation planning for climate change. Despite increasing awareness of the need to incorporate mechanism into species distribution models (SDMs), mechanistic modeling of endotherm distributions remains limited in this literature. Using the American pika (Ochotona princeps) as an example, we present a framework whereby mechanism can be incorporated into endotherm SDMs. Pika distribution has repeatedly been found to be constrained by warm temperatures, so we used Niche Mapper, a mechanistic heat-balance model, to convert macroclimate data to pika-specific surface activity time in summer across the western United States. We then explored the difference between using a macroclimate predictor (summer temperature) and using a mechanistic predictor (predicted surface activity time) in SDMs. Both approaches accurately predicted pika presences in current and past climate regimes. However, the activity models predicted 8–19% less habitat loss in response to annual temperature increases of ~3–5 °C predicted in the region by 2070, suggesting that pikas may be able to buffer some climate change effects through behavioral thermoregulation that can be captured by mechanistic modeling. Incorporating mechanism added value to the modeling by providing increased confidence in areas where different modeling approaches agreed and providing a range of outcomes in areas of disagreement. It also provided a more proximate variable relating animal distribution to climate, allowing investigations into how unique habitat characteristics and intraspecific phenotypic variation may allow pikas to exist in areas outside those predicted by generic SDMs. Only a small number of easily obtainable data are required to parameterize this mechanistic model for any endotherm, and its use can improve SDM predictions by explicitly modeling a widely applicable direct physiological effect

Mechanistic variables can enhance predictive models of endotherm distributions: the American pika under current, past, and future climates.

Science.gov (United States)

Mathewson, Paul D; Moyer-Horner, Lucas; Beever, Erik A; Briscoe, Natalie J; Kearney, Michael; Yahn, Jeremiah M; Porter, Warren P

2017-03-01

How climate constrains species' distributions through time and space is an important question in the context of conservation planning for climate change. Despite increasing awareness of the need to incorporate mechanism into species distribution models (SDMs), mechanistic modeling of endotherm distributions remains limited in this literature. Using the American pika (Ochotona princeps) as an example, we present a framework whereby mechanism can be incorporated into endotherm SDMs. Pika distribution has repeatedly been found to be constrained by warm temperatures, so we used Niche Mapper, a mechanistic heat-balance model, to convert macroclimate data to pika-specific surface activity time in summer across the western United States. We then explored the difference between using a macroclimate predictor (summer temperature) and using a mechanistic predictor (predicted surface activity time) in SDMs. Both approaches accurately predicted pika presences in current and past climate regimes. However, the activity models predicted 8-19% less habitat loss in response to annual temperature increases of ~3-5 °C predicted in the region by 2070, suggesting that pikas may be able to buffer some climate change effects through behavioral thermoregulation that can be captured by mechanistic modeling. Incorporating mechanism added value to the modeling by providing increased confidence in areas where different modeling approaches agreed and providing a range of outcomes in areas of disagreement. It also provided a more proximate variable relating animal distribution to climate, allowing investigations into how unique habitat characteristics and intraspecific phenotypic variation may allow pikas to exist in areas outside those predicted by generic SDMs. Only a small number of easily obtainable data are required to parameterize this mechanistic model for any endotherm, and its use can improve SDM predictions by explicitly modeling a widely applicable direct physiological effect

A general framework for thermodynamically consistent parameterization and efficient sampling of enzymatic reactions.

Directory of Open Access Journals (Sweden)

Pedro Saa

2015-04-01

Full Text Available 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

Tuning controllers using the dual Youla parameterization

DEFF Research Database (Denmark)

Niemann, Hans Henrik; Stoustrup, Jakob

2000-01-01

This paper describes the application of the Youla parameterization of all stabilizing controllers and the dual Youla parameterization of all systems stabilized by a given controller in connection with tuning of controllers. In the uncertain case, it is shown that the use of the Youla parameteriza......This paper describes the application of the Youla parameterization of all stabilizing controllers and the dual Youla parameterization of all systems stabilized by a given controller in connection with tuning of controllers. In the uncertain case, it is shown that the use of the Youla...

Parameterized neural networks for high-energy physics

Energy Technology Data Exchange (ETDEWEB)

Baldi, Pierre; Sadowski, Peter [University of California, Department of Computer Science, Irvine, CA (United States); Cranmer, Kyle [NYU, Department of Physics, New York, NY (United States); Faucett, Taylor; Whiteson, Daniel [University of California, Department of Physics and Astronomy, Irvine, CA (United States)

2016-05-15

We investigate a new structure for machine learning classifiers built with neural networks and applied to problems in high-energy physics by expanding the inputs to include not only measured features but also physics parameters. The physics parameters represent a smoothly varying learning task, and the resulting parameterized classifier can smoothly interpolate between them and replace sets of classifiers trained at individual values. This simplifies the training process and gives improved performance at intermediate values, even for complex problems requiring deep learning. Applications include tools parameterized in terms of theoretical model parameters, such as the mass of a particle, which allow for a single network to provide improved discrimination across a range of masses. This concept is simple to implement and allows for optimized interpolatable results. (orig.)

Parameterized neural networks for high-energy physics

International Nuclear Information System (INIS)

Baldi, Pierre; Sadowski, Peter; Cranmer, Kyle; Faucett, Taylor; Whiteson, Daniel

2016-01-01

We investigate a new structure for machine learning classifiers built with neural networks and applied to problems in high-energy physics by expanding the inputs to include not only measured features but also physics parameters. The physics parameters represent a smoothly varying learning task, and the resulting parameterized classifier can smoothly interpolate between them and replace sets of classifiers trained at individual values. This simplifies the training process and gives improved performance at intermediate values, even for complex problems requiring deep learning. Applications include tools parameterized in terms of theoretical model parameters, such as the mass of a particle, which allow for a single network to provide improved discrimination across a range of masses. This concept is simple to implement and allows for optimized interpolatable results. (orig.)

THOR: A New Higher-Order Closure Assumed PDF Subgrid-Scale Parameterization; Evaluation and Application to Low Cloud Feedbacks

Science.gov (United States)

Firl, G. J.; Randall, D. A.

2013-12-01

included in THOR to drive existing microphysical and radiation parameterizations with samples drawn from the trivariate PDF. THOR has been tested in a single-column model framework using standardized test cases spanning a range of large-scale conditions conducive to both shallow cumulus and stratocumulus clouds and the transition between the two states. The results were compared to published LES intercomparison results using the same cases, and the gross characteristics of both cloudiness and boundary layer turbulence produced by THOR were within the range of results from the respective LES ensembles. In addition, THOR was used in a single-column model framework to study low cloud feedbacks in the northeastern Pacific Ocean. Using initialization and forcings developed as part of the CGILS project, THOR was run at 8 points along a cross-section from the trade-wind cumulus region east of Hawaii to the coastal stratocumulus region off the coast of California for both the control climate and a climate perturbed by +2K SST. A neutral to weakly positive cloud feedback of 0-4 W m-2 K-1 was simulated along the cross-section. The physical mechanisms responsible appeared to be increased boundary layer entrainment and stratocumulus decoupling leading to reduced maximum cloud cover and liquid water path.

Modelling the inorganic ocean carbon cycle under past and future climate change

International Nuclear Information System (INIS)

Ewan, T.L.

2004-01-01

This study used a coupled ocean-atmosphere-sea ice model with an inorganic carbon component to examine the inorganic ocean carbon cycle with particular reference to how climate feedback influences future uptake. In the last 150 years, the increase in atmosphere carbon dioxide (CO 2 ) concentrations have been higher than any time during the Earth's history. Although the oceans are the largest sink for carbon dioxide, it is not know how the ocean carbon cycle will respond to increasing anthropogenic carbon dioxide concentrations in the future. Climate feedbacks could potentially reduce further uptake of carbon by the ocean. In addition to examining past climate transitions, including both abrupt and glacial-interglacial climate transitions, this study also examined the sensitivity of the inorganic carbon cycle to increased atmospheric carbon dioxide. Atmospheric carbon dioxide levels were also projected under a range of global warming scenarios. Most simulations identified a transient weakening of the North Atlantic and increased sea surface temperatures (SST). These positive feedbacks act on the carbon system to reduce uptake. However, the ocean has the capacity to take up 65 to 75 per cent of the anthropogenic carbon dioxide increases. An analysis of climate feedback on future carbon uptake shows that oceans store 7 per cent more carbon when there are no climate feedbacks acting on the system. Sensitivity experiments using the Gent McWilliams parameterization for mixing associated with mesoscale eddies show a further 6 per cent increase in oceanic uptake. Inclusion of sea ice dynamics resulted in a 2 per cent difference in uptake. This study also examined changes in atmospheric carbon dioxide concentration that occur during abrupt climate change events. Changes in ocean circulation and carbon solubility cause significant increases in atmospheric carbon dioxide concentrations when melt water episodes are simulated in both hemispheres. The response of the carbon

Impact of Variable-Resolution Meshes on Regional Climate Simulations

Science.gov (United States)

Fowler, L. D.; Skamarock, W. C.; Bruyere, C. L.

2014-12-01

The Model for Prediction Across Scales (MPAS) is currently being used for seasonal-scale simulations on globally-uniform and regionally-refined meshes. Our ongoing research aims at analyzing simulations of tropical convective activity and tropical cyclone development during one hurricane season over the North Atlantic Ocean, contrasting statistics obtained with a variable-resolution mesh against those obtained with a quasi-uniform mesh. Analyses focus on the spatial distribution, frequency, and intensity of convective and grid-scale precipitations, and their relative contributions to the total precipitation as a function of the horizontal scale. Multi-month simulations initialized on May 1st 2005 using ERA-Interim re-analyses indicate that MPAS performs satisfactorily as a regional climate model for different combinations of horizontal resolutions and transitions between the coarse and refined meshes. Results highlight seamless transitions for convection, cloud microphysics, radiation, and land-surface processes between the quasi-uniform and locally- refined meshes, despite the fact that the physics parameterizations were not developed for variable resolution meshes. Our goal of analyzing the performance of MPAS is twofold. First, we want to establish that MPAS can be successfully used as a regional climate model, bypassing the need for nesting and nudging techniques at the edges of the computational domain as done in traditional regional climate modeling. Second, we want to assess the performance of our convective and cloud microphysics parameterizations as the horizontal resolution varies between the lower-resolution quasi-uniform and higher-resolution locally-refined areas of the global domain.

Parameterizing correlations between hydrometeor species in mixed-phase Arctic clouds

Science.gov (United States)

Larson, Vincent E.; Nielsen, Brandon J.; Fan, Jiwen; Ovchinnikov, Mikhail

2011-01-01

Mixed-phase Arctic clouds, like other clouds, contain small-scale variability in hydrometeor fields, such as cloud water or snow mixing ratio. This variability may be worth parameterizing in coarse-resolution numerical models. In particular, for modeling multispecies processes such as accretion and aggregation, it would be useful to parameterize subgrid correlations among hydrometeor species. However, one difficulty is that there exist many hydrometeor species and many microphysical processes, leading to complexity and computational expense. Existing lower and upper bounds on linear correlation coefficients are too loose to serve directly as a method to predict subgrid correlations. Therefore, this paper proposes an alternative method that begins with the spherical parameterization framework of Pinheiro and Bates (1996), which expresses the correlation matrix in terms of its Cholesky factorization. The values of the elements of the Cholesky matrix are populated here using a "cSigma" parameterization that we introduce based on the aforementioned bounds on correlations. The method has three advantages: (1) the computational expense is tolerable; (2) the correlations are, by construction, guaranteed to be consistent with each other; and (3) the methodology is fairly general and hence may be applicable to other problems. The method is tested noninteractively using simulations of three Arctic mixed-phase cloud cases from two field experiments: the Indirect and Semi-Direct Aerosol Campaign and the Mixed-Phase Arctic Cloud Experiment. Benchmark simulations are performed using a large-eddy simulation (LES) model that includes a bin microphysical scheme. The correlations estimated by the new method satisfactorily approximate the correlations produced by the LES.

Influence of ecohydrologic feedbacks from simulated crop growth on integrated regional hydrologic simulations under climate scenarios

Science.gov (United States)

van Walsum, P. E. V.; Supit, I.

2012-06-01

Hydrologic climate change modelling is hampered by climate-dependent model parameterizations. To reduce this dependency, we extended the regional hydrologic modelling framework SIMGRO to host a two-way coupling between the soil moisture model MetaSWAP and the crop growth simulation model WOFOST, accounting for ecohydrologic feedbacks in terms of radiation fraction that reaches the soil, crop coefficient, interception fraction of rainfall, interception storage capacity, and root zone depth. Except for the last, these feedbacks are dependent on the leaf area index (LAI). The influence of regional groundwater on crop growth is included via a coupling to MODFLOW. Two versions of the MetaSWAP-WOFOST coupling were set up: one with exogenous vegetation parameters, the "static" model, and one with endogenous crop growth simulation, the "dynamic" model. Parameterization of the static and dynamic models ensured that for the current climate the simulated long-term averages of actual evapotranspiration are the same for both models. Simulations were made for two climate scenarios and two crops: grass and potato. In the dynamic model, higher temperatures in a warm year under the current climate resulted in accelerated crop development, and in the case of potato a shorter growing season, thus partly avoiding the late summer heat. The static model has a higher potential transpiration; depending on the available soil moisture, this translates to a higher actual transpiration. This difference between static and dynamic models is enlarged by climate change in combination with higher CO2 concentrations. Including the dynamic crop simulation gives for potato (and other annual arable land crops) systematically higher effects on the predicted recharge change due to climate change. Crop yields from soils with poor water retention capacities strongly depend on capillary rise if moisture supply from other sources is limited. Thus, including a crop simulation model in an integrated

Remote Sensing Image Enhancement Based on Non-subsampled Shearlet Transform and Parameterized Logarithmic Image Processing Model

Directory of Open Access Journals (Sweden)

TAO Feixiang

2015-08-01

Full Text Available Aiming at parts of remote sensing images with dark brightness and low contrast, a remote sensing image enhancement method based on non-subsampled Shearlet transform and parameterized logarithmic image processing model is proposed in this paper to improve the visual effects and interpretability of remote sensing images. Firstly, a remote sensing image is decomposed into a low-frequency component and high frequency components by non-subsampled Shearlet transform.Then the low frequency component is enhanced according to PLIP (parameterized logarithmic image processing model, which can improve the contrast of image, while the improved fuzzy enhancement method is used to enhance the high frequency components in order to highlight the information of edges and details. A large number of experimental results show that, compared with five kinds of image enhancement methods such as bidirectional histogram equalization method, the method based on stationary wavelet transform and the method based on non-subsampled contourlet transform, the proposed method has advantages in both subjective visual effects and objective quantitative evaluation indexes such as contrast and definition, which can more effectively improve the contrast of remote sensing image and enhance edges and texture details with better visual effects.

Modelling heterogeneous ice nucleation on mineral dust and soot with parameterizations based on laboratory experiments

Science.gov (United States)

Hoose, C.; Hande, L. B.; Mohler, O.; Niemand, M.; Paukert, M.; Reichardt, I.; Ullrich, R.

2016-12-01

Between 0 and -37°C, ice formation in clouds is triggered by aerosol particles acting as heterogeneous ice nuclei. At lower temperatures, heterogeneous ice nucleation on aerosols can occur at lower supersaturations than homogeneous freezing of solutes. In laboratory experiments, the ability of different aerosol species (e.g. desert dusts, soot, biological particles) has been studied in detail and quantified via various theoretical or empirical parameterization approaches. For experiments in the AIDA cloud chamber, we have quantified the ice nucleation efficiency via a temperature- and supersaturation dependent ice nucleation active site density. Here we present a new empirical parameterization scheme for immersion and deposition ice nucleation on desert dust and soot based on these experimental data. The application of this parameterization to the simulation of cirrus clouds, deep convective clouds and orographic clouds will be shown, including the extension of the scheme to the treatment of freezing of rain drops. The results are compared to other heterogeneous ice nucleation schemes. Furthermore, an aerosol-dependent parameterization of contact ice nucleation is presented.

A new first-order turbulence mixing model for the stable atmospheric boundary-layer: development and testing in large-eddy and single column models

Science.gov (United States)

Huang, J.; Bou-Zeid, E.; Golaz, J.

2011-12-01

Parameterization of the stably-stratified atmospheric boundary-layer is of crucial importance to different aspects of numerical weather prediction at regional scales and climate modeling at global scales, such as land-surface temperature forecasts, fog and frost prediction, and polar climate. It is well-known that most operational climate models require excessive turbulence mixing of the stable boundary-layer to prevent decoupling of the atmospheric component from the land component under strong stability, but the performance of such a model is unlikely to be satisfactory under weakly and moderately stable conditions. In this study we develop and test a general turbulence mixing model of the stable boundary-layer which works under different stabilities and for steady as well as unsteady conditions. A-priori large-eddy simulation (LES) tests are presented to motivate and verify the new parameterization. Subsequently, an assessment of this model using the GFDL single-column model (SCM) is performed. Idealized test cases including continuously varying stability, as well as stability discontinuity, are used to test the new SCM against LES results. A good match of mean and flux profiles is found when the new parameterization is used, while other traditional first-order turbulence models using the concept of stability function perform poorly. SCM spatial resolution is also found to have little impact on the performance of the new turbulence closure, but temporal resolution is important and a numerical stability criterion based on the model time step is presented.

The influence of atmospheric grid resolution in a climate model-forced ice sheet simulation

Science.gov (United States)

Lofverstrom, Marcus; Liakka, Johan

2018-04-01

Coupled climate-ice sheet simulations have been growing in popularity in recent years. Experiments of this type are however challenging as ice sheets evolve over multi-millennial timescales, which is beyond the practical integration limit of most Earth system models. A common method to increase model throughput is to trade resolution for computational efficiency (compromise accuracy for speed). Here we analyze how the resolution of an atmospheric general circulation model (AGCM) influences the simulation quality in a stand-alone ice sheet model. Four identical AGCM simulations of the Last Glacial Maximum (LGM) were run at different horizontal resolutions: T85 (1.4°), T42 (2.8°), T31 (3.8°), and T21 (5.6°). These simulations were subsequently used as forcing of an ice sheet model. While the T85 climate forcing reproduces the LGM ice sheets to a high accuracy, the intermediate resolution cases (T42 and T31) fail to build the Eurasian ice sheet. The T21 case fails in both Eurasia and North America. Sensitivity experiments using different surface mass balance parameterizations improve the simulations of the Eurasian ice sheet in the T42 case, but the compromise is a substantial ice buildup in Siberia. The T31 and T21 cases do not improve in the same way in Eurasia, though the latter simulates the continent-wide Laurentide ice sheet in North America. The difficulty to reproduce the LGM ice sheets in the T21 case is in broad agreement with previous studies using low-resolution atmospheric models, and is caused by a substantial deterioration of the model climate between the T31 and T21 resolutions. It is speculated that this deficiency may demonstrate a fundamental problem with using low-resolution atmospheric models in these types of experiments.

Improving the CROPGRO-Tomato model for predicting growth and yield to temperature

NARCIS (Netherlands)

Boote, K.J.; Rybak, M.R.; Scholberg, J.M.S.; Jones, J.W.

2012-01-01

Parameterizing crop models for more accurate response to climate factors such as temperature is important considering potential temperature increases associated with climate change, particularly for tomato (Lycopersicon esculentum Mill.), which is a heat-sensitive crop. The objective of this work

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

Science.gov (United States)

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.

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

International Nuclear Information System (INIS)

Kowalsky, M. B.; Finsterle, Stefan A.; Williams, Kenneth H.; Murray, Christopher J.; Commer, Michael; Newcomer, Darrell R.; Englert, Andreas L.; Steefel, Carl I.; Hubbard, Susan

2012-01-01

We consider a field-scale tracer experiment conducted in 2007 in a shallow uranium-contaminated aquifer at Rifle, Colorado. In developing a reliable approach for inferring hydrological properties at the site through inverse modeling of the 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. We present an approach for hydrological inversion of the tracer data and explore, using a 2D synthetic example at first, how parameterization affects the solution, and how additional characterization data could be incorporated to reduce uncertainty. Specifically, we examine sensitivity of the results to the configuration of pilot points used in a geostatistical parameterization, and to the sampling frequency and measurement error of the concentration data. A reliable solution of the inverse problem is found when the pilot point configuration is carefully implemented. In addition, we examine the use of a zonation parameterization, in which the geometry of the geological facies is known (e.g., from geophysical data or core data), to reduce the non-uniqueness of the solution and the number of unknown parameters to be estimated. When zonation information is only available for a limited region, special treatment in the remainder of the model is necessary, such as using a geostatistical parameterization. Finally, inversion of the actual field data is performed using 2D and 3D models, and results are compared with slug test data.

Regional Arctic System Model (RASM): A Tool to Advance Understanding and Prediction of Arctic Climate Change at Process Scales

Science.gov (United States)

Maslowski, W.; Roberts, A.; Osinski, R.; Brunke, M.; Cassano, J. J.; Clement Kinney, J. L.; Craig, A.; Duvivier, A.; Fisel, B. J.; Gutowski, W. J., Jr.; Hamman, J.; Hughes, M.; Nijssen, B.; Zeng, X.

2014-12-01

The Arctic is undergoing rapid climatic changes, which are some of the most coordinated changes currently occurring anywhere on Earth. They are exemplified by the retreat of the perennial sea ice cover, which integrates forcing by, exchanges with and feedbacks between atmosphere, ocean and land. While historical reconstructions from Global Climate and Global Earth System Models (GC/ESMs) are in broad agreement with these changes, the rate of change in the GC/ESMs remains outpaced by observations. Reasons for that stem from a combination of coarse model resolution, inadequate parameterizations, unrepresented processes and a limited knowledge of physical and other real world interactions. We demonstrate the capability of the Regional Arctic System Model (RASM) in addressing some of the GC/ESM limitations in simulating observed seasonal to decadal variability and trends in the sea ice cover and climate. RASM is a high resolution, fully coupled, pan-Arctic climate model that uses the Community Earth System Model (CESM) framework. It uses the Los Alamos Sea Ice Model (CICE) and Parallel Ocean Program (POP) configured at an eddy-permitting resolution of 1/12° as well as the Weather Research and Forecasting (WRF) and Variable Infiltration Capacity (VIC) models at 50 km resolution. All RASM components are coupled via the CESM flux coupler (CPL7) at 20-minute intervals. RASM is an example of limited-area, process-resolving, fully coupled earth system model, which due to the additional constraints from lateral boundary conditions and nudging within a regional model domain facilitates detailed comparisons with observational statistics that are not possible with GC/ESMs. In this talk, we will emphasize the utility of RASM to understand sensitivity to variable parameter space, importance of critical processes, coupled feedbacks and ultimately to reduce uncertainty in arctic climate change projections.

Improved cloud parameterization for Arctic climate simulations based on satellite data

Science.gov (United States)

Klaus, Daniel; Dethloff, Klaus; Dorn, Wolfgang; Rinke, Annette

2015-04-01

The defective representation of Arctic cloud processes and properties remains a crucial problem in climate modelling and in reanalysis products. Satellite-based cloud observations (MODIS and CPR/CALIOP) and single-column model simulations (HIRHAM5-SCM) were exploited to evaluate and improve the simulated Arctic cloud cover of the atmospheric regional climate model HIRHAM5. The ECMWF reanalysis dataset 'ERA-Interim' (ERAint) was used for the model initialization, the lateral boundary forcing as well as the dynamical relaxation inside the pan-Arctic domain. HIRHAM5 has a horizontal resolution of 0.25° and uses 40 pressure-based and terrain-following vertical levels. In comparison with the satellite observations, the HIRHAM5 control run (HH5ctrl) systematically overestimates total cloud cover, but to a lesser extent than ERAint. The underestimation of high- and mid-level clouds is strongly outweighed by the overestimation of low-level clouds. Numerous sensitivity studies with HIRHAM5-SCM suggest (1) the parameter tuning, enabling a more efficient Bergeron-Findeisen process, combined with (2) an extension of the prognostic-statistical (PS) cloud scheme, enabling the use of negatively skewed beta distributions. This improved model setup was then used in a corresponding HIRHAM5 sensitivity run (HH5sens). While the simulated high- and mid-level cloud cover is improved only to a limited extent, the large overestimation of low-level clouds can be systematically and significantly reduced, especially over sea ice. Consequently, the multi-year annual mean area average of total cloud cover with respect to sea ice is almost 14% lower than in HH5ctrl. Overall, HH5sens slightly underestimates the observed total cloud cover but shows a halved multi-year annual mean bias of 2.2% relative to CPR/CALIOP at all latitudes north of 60° N. Importantly, HH5sens produces a more realistic ratio between the cloud water and ice content. The considerably improved cloud simulation manifests in

On the uncertainty of phenological responses to climate change, and implications for a terrestrial biosphere model

Directory of Open Access Journals (Sweden)

M. Migliavacca

2012-06-01

degree of warming varied between 2.2 days °C⁻¹ and 5.2 days °C⁻¹ depending on model structure.

We quantified the impact of uncertainties in bud-burst forecasts on simulated photosynthetic CO₂ uptake and evapotranspiration (ET using a process-based terrestrial biosphere model. Uncertainty in phenology model structure led to uncertainty in the description of forest seasonality, which accumulated to uncertainty in annual model estimates of gross primary productivity (GPP and ET of 9.6% and 2.9%, respectively. A sensitivity analysis shows that a variation of ±10 days in bud-burst dates led to a variation of ±5.0% for annual GPP and about ±2.0% for ET.

For phenology models, differences among future climate scenarios (i.e. driver represent the largest source of uncertainty, followed by uncertainties related to model structure, and finally, related to model parameterization. The uncertainties we have quantified will affect the description of the seasonality of ecosystem processes and in particular the simulation of carbon uptake by forest ecosystems, with a larger impact of uncertainties related to phenology model structure, followed by uncertainties related to phenological model parameterization.

Climate Impacts of Ice Nucleation

Science.gov (United States)

Gettelman, Andrew; Liu, Xiaohong; Barahona, Donifan; Lohmann, Ulrike; Chen, Celia

2012-01-01

Several different ice nucleation parameterizations in two different General Circulation Models (GCMs) are used to understand the effects of ice nucleation on the mean climate state, and the Aerosol Indirect Effects (AIE) of cirrus clouds on climate. Simulations have a range of ice microphysical states that are consistent with the spread of observations, but many simulations have higher present-day ice crystal number concentrations than in-situ observations. These different states result from different parameterizations of ice cloud nucleation processes, and feature different balances of homogeneous and heterogeneous nucleation. Black carbon aerosols have a small (0.06 Wm(exp-2) and not statistically significant AIE when included as ice nuclei, for nucleation efficiencies within the range of laboratory measurements. Indirect effects of anthropogenic aerosols on cirrus clouds occur as a consequence of increasing anthropogenic sulfur emissions with different mechanisms important in different models. In one model this is due to increases in homogeneous nucleation fraction, and in the other due to increases in heterogeneous nucleation with coated dust. The magnitude of the effect is the same however. The resulting ice AIE does not seem strongly dependent on the balance between homogeneous and heterogeneous ice nucleation. Regional effects can reach several Wm2. Indirect effects are slightly larger for those states with less homogeneous nucleation and lower ice number concentration in the base state. The total ice AIE is estimated at 0.27 +/- 0.10 Wm(exp-2) (1 sigma uncertainty). This represents a 20% offset of the simulated total shortwave AIE for ice and liquid clouds of 1.6 Wm(sup-2).

The Canadian Centre for Climate Modelling and Analysis global coupled model and its climate

Energy Technology Data Exchange (ETDEWEB)

Flato, G.M.; Boer, G.J.; Lee, W.G.; McFarlane, N.A.; Ramsden, D.; Reader, M.C. [Canadian Centre for Climate Modelling and Analysis, Victoria, BC (Canada); Weaver, A.J. [School of Earth and Ocean Sciences, University of Victoria, BC (Canada)

2000-06-01

A global, three-dimensional climate model, developed by coupling the CCCma second-generation atmospheric general circulation model (GCM2) to a version of the GFDL modular ocean model (MOM1), forms the basis for extended simulations of past, current and projected future climate. The spin-up and coupling procedures are described, as is the resulting climate based on a 200 year model simulation with constant atmospheric composition and external forcing. The simulated climate is systematically compared to available observations in terms of mean climate quantities and their spatial patterns, temporal variability, and regional behavior. Such comparison demonstrates a generally successful reproduction of the broad features of mean climate quantities, albeit with local discrepancies. Variability is generally well-simulated over land, but somewhat underestimated in the tropical ocean and the extratropical storm-track regions. The modelled climate state shows only small trends, indicating a reasonable level of balance at the surface, which is achieved in part by the use of heat and freshwater flux adjustments. The control simulation provides a basis against which to compare simulated climate change due to historical and projected greenhouse gas and aerosol forcing as described in companion publications. (orig.)

Climate Model Diagnostic Analyzer

Science.gov (United States)

Lee, Seungwon; Pan, Lei; Zhai, Chengxing; Tang, Benyang; Kubar, Terry; Zhang, Zia; Wang, Wei

2015-01-01

The comprehensive and innovative evaluation of climate models with newly available global observations is critically needed for the improvement of climate model current-state representation and future-state predictability. A climate model diagnostic evaluation process requires physics-based multi-variable analyses that typically involve large-volume and heterogeneous datasets, making them both computation- and data-intensive. With an exploratory nature of climate data analyses and an explosive growth of datasets and service tools, scientists are struggling to keep track of their datasets, tools, and execution/study history, let alone sharing them with others. In response, we have developed a cloud-enabled, provenance-supported, web-service system called Climate Model Diagnostic Analyzer (CMDA). CMDA enables the physics-based, multivariable model performance evaluations and diagnoses through the comprehensive and synergistic use of multiple observational data, reanalysis data, and model outputs. At the same time, CMDA provides a crowd-sourcing space where scientists can organize their work efficiently and share their work with others. CMDA is empowered by many current state-of-the-art software packages in web service, provenance, and semantic search.

Response to the eruption of Mount Pinatubo in relation to climate sensitivity in the CMIP3 models

Energy Technology Data Exchange (ETDEWEB)

Bender, Frida A.M.; Ekman, Annica M.L.; Rodhe, Henning [Stockholm University, Department of Meteorology, Stockholm (Sweden)

2010-10-15

The radiative flux perturbations and subsequent temperature responses in relation to the eruption of Mount Pinatubo in 1991 are studied in the ten general circulation models incorporated in the Coupled Model Intercomparison Project, phase 3 (CMIP3), that include a parameterization of volcanic aerosol. Models and observations show decreases in global mean temperature of up to 0.5 K, in response to radiative perturbations of up to 10 W m{sup -2}, averaged over the tropics. The time scale representing the delay between radiative perturbation and temperature response is determined by the slow ocean response, and is estimated to be centered around 4 months in the models. Although the magnitude of the temperature response to a volcanic eruption has previously been used as an indicator of equilibrium climate sensitivity in models, we find these two quantities to be only weakly correlated. This may partly be due to the fact that the size of the volcano-induced radiative perturbation varies among the models. It is found that the magnitude of the modelled radiative perturbation increases with decreasing climate sensitivity, with the exception of one outlying model. Therefore, we scale the temperature perturbation by the radiative perturbation in each model, and use the ratio between the integrated temperature perturbation and the integrated radiative perturbation as a measure of sensitivity to volcanic forcing. This ratio is found to be well correlated with the model climate sensitivity, more sensitive models having a larger ratio. Further, if this correspondence between ''volcanic sensitivity'' and sensitivity to CO{sub 2} forcing is a feature not only among the models, but also of the real climate system, the alleged linear relation can be used to estimate the real climate sensitivity. The observational value of the ratio signifying volcanic sensitivity is hereby estimated to correspond to an equilibrium climate sensitivity, i.e. equilibrium temperature

Will high-resolution global ocean models benefit coupled predictions on short-range to climate timescales?

Science.gov (United States)

Hewitt, Helene T.; Bell, Michael J.; Chassignet, Eric P.; Czaja, Arnaud; Ferreira, David; Griffies, Stephen M.; Hyder, Pat; McClean, Julie L.; New, Adrian L.; Roberts, Malcolm J.

2017-12-01

As the importance of the ocean in the weather and climate system is increasingly recognised, operational systems are now moving towards coupled prediction not only for seasonal to climate timescales but also for short-range forecasts. A three-way tension exists between the allocation of computing resources to refine model resolution, the expansion of model complexity/capability, and the increase of ensemble size. Here we review evidence for the benefits of increased ocean resolution in global coupled models, where the ocean component explicitly represents transient mesoscale eddies and narrow boundary currents. We consider lessons learned from forced ocean/sea-ice simulations; from studies concerning the SST resolution required to impact atmospheric simulations; and from coupled predictions. Impacts of the mesoscale ocean in western boundary current regions on the large-scale atmospheric state have been identified. Understanding of air-sea feedback in western boundary currents is modifying our view of the dynamics in these key regions. It remains unclear whether variability associated with open ocean mesoscale eddies is equally important to the large-scale atmospheric state. We include a discussion of what processes can presently be parameterised in coupled models with coarse resolution non-eddying ocean models, and where parameterizations may fall short. We discuss the benefits of resolution and identify gaps in the current literature that leave important questions unanswered.

Analyzing Multidecadal Trends in Cloudiness Over the Subtropical Andes Mountains of South America Using a Regional Climate Model.

Science.gov (United States)

Zaitchik, B. F.; Russell, A.; Gnanadesikan, A.

2016-12-01

Satellite-based products indicate that many parts of South America have been experiencing increases in outgoing longwave radiation (OLR) and corresponding decreases in cloudiness over the last few decades, with the strongest trends occurring in the subtropical Andes Mountains - an area that is highly vulnerable to climate change due to its reliance on glacial melt for dry-season runoff. Changes in cloudiness may be contributing to increases in atmospheric temperature, thereby raising the freezing level height (FLH) - a critical geophysical parameter. Yet these trends are only partially captured in reanalysis products, while AMIP climate models generally show no significant trend in OLR over this timeframe, making it difficult to determine the underlying drivers. Therefore, controlled numerical experiments with a regional climate model are performed in order to investigate drivers of the observed OLR and cloudiness trends. The Weather Research and Forecasting model (WRF) is used here because it offers several advantages over global models, including higher resolution - a critical asset in areas of complex topography - as well as flexible physics, parameterization, and data assimilation capabilities. It is likely that changes in the mean states and meridional gradients of SSTs in the Pacific and Atlantic oceans are driving regional trends in clouds. A series of lower boundary manipulations are performed with WRF to determine to what extent changes in SSTs influence regional OLR.

Tsunami damping by mangrove forest: a laboratory study using parameterized trees

Directory of Open Access Journals (Sweden)

A. Strusińska-Correia

2013-02-01

Full Text Available Tsunami attenuation by coastal vegetation was examined under laboratory conditions for mature mangroves Rhizophora sp. The developed novel tree parameterization concept, accounting for both bio-mechanical and structural tree properties, allowed to substitute the complex tree structure by a simplified tree model of identical hydraulic resistance. The most representative parameterized mangrove model was selected among the tested models with different frontal area and root density, based on hydraulic test results. The selected parameterized tree models were arranged in a forest model of different width and further tested systematically under varying incident tsunami conditions (solitary waves and tsunami bores. The damping performance of the forest models under these two flow regimes was compared in terms of wave height and force envelopes, wave transmission coefficient as well as drag and inertia coefficients. Unlike the previous studies, the results indicate a significant contribution of the foreshore topography to solitary wave energy reduction through wave breaking in comparison to that attributed to the forest itself. A similar rate of tsunami transmission (ca. 20% was achieved for both flow conditions (solitary waves and tsunami bores and the widest forest (75 m in prototype investigated. Drag coefficient C_D attributed to the solitary waves tends to be constant (C_D = 1.5 over the investigated range of the Reynolds number.

Modeling the regional impact of ship emissions on NOx and ozone levels over the Eastern Atlantic and Western Europe using ship plume parameterization

Directory of Open Access Journals (Sweden)

P. Pisoft

2010-07-01

Full Text Available In general, regional and global chemistry transport models apply instantaneous mixing of emissions into the model's finest resolved scale. In case of a concentrated source, this could result in erroneous calculation of the evolution of both primary and secondary chemical species. Several studies discussed this issue in connection with emissions from ships and aircraft. In this study, we present an approach to deal with the non-linear effects during dispersion of NOx emissions from ships. It represents an adaptation of the original approach developed for aircraft NOx emissions, which uses an exhaust tracer to trace the amount of the emitted species in the plume and applies an effective reaction rate for the ozone production/destruction during the plume's dilution into the background air. In accordance with previous studies examining the impact of international shipping on the composition of the troposphere, we found that the contribution of ship induced surface NOx to the total reaches 90% over remote ocean and makes 10–30% near coastal regions. Due to ship emissions, surface ozone increases by up to 4–6 ppbv making 10% contribution to the surface ozone budget. When applying the ship plume parameterization, we show that the large scale NOx decreases and the ship NOx contribution is reduced by up to 20–25%. A similar decrease was found in the case of O3. The plume parameterization suppressed the ship induced ozone production by 15–30% over large areas of the studied region. To evaluate the presented parameterization, nitrogen monoxide measurements over the English Channel were compared with modeled values and it was found that after activating the parameterization the model accuracy increases.

Parameterization of pion production and reaction cross sections at LAMPF energies

International Nuclear Information System (INIS)

Burman, R.L.; Smith, E.S.

1989-05-01

A parameterization of pion production and reaction cross sections is developed for eventual use in modeling neutrino production by protons in a beam stop. Emphasis is placed upon smooth parameterizations for proton energies up to 800 MeV, for all pion energies and angles, and for a wide range of materials. The resulting representations of the data are well-behaved and can be used for extrapolation to regions where there are no measurements. 22 refs., 16 figs., 2 tabs

Modeling radiative transfer with the doubling and adding approach in a climate GCM setting

Science.gov (United States)

Lacis, A. A.

2017-12-01

The nonlinear dependence of multiply scattered radiation on particle size, optical depth, and solar zenith angle, makes accurate treatment of multiple scattering in the climate GCM setting problematic, due primarily to computational cost issues. In regard to the accurate methods of calculating multiple scattering that are available, their computational cost is far too prohibitive for climate GCM applications. Utilization of two-stream-type radiative transfer approximations may be computationally fast enough, but at the cost of reduced accuracy. We describe here a parameterization of the doubling/adding method that is being used in the GISS climate GCM, which is an adaptation of the doubling/adding formalism configured to operate with a look-up table utilizing a single gauss quadrature point with an extra-angle formulation. It is designed to closely reproduce the accuracy of full-angle doubling and adding for the multiple scattering effects of clouds and aerosols in a realistic atmosphere as a function of particle size, optical depth, and solar zenith angle. With an additional inverse look-up table, this single-gauss-point doubling/adding approach can be adapted to model fractional cloud cover for any GCM grid-box in the independent pixel approximation as a function of the fractional cloud particle sizes, optical depths, and solar zenith angle dependence.

Evaluating Lightning-generated NOx (LNOx) Parameterization based on Cloud Top Height at Resolutions with Partially-resolved Convection for Upper Tropospheric Chemistry Studies

Science.gov (United States)

Wong, J.; Barth, M. C.; Noone, D. C.

2012-12-01

Lightning-generated nitrogen oxides (LNOx) is an important precursor to tropospheric ozone production. With a meteorological time-scale variability similar to that of the ozone chemical lifetime, it can nonlinearly perturb tropospheric ozone concentration. Coupled with upper-air circulation patterns, LNOx can accumulate in significant amount in the upper troposphere with other precursors, thus enhancing ozone production (see attached figure). While LNOx emission has been included and tuned extensively in global climate models, its inclusions in regional chemistry models are seldom tested. Here we present a study that evaluates the frequently used Price and Rind parameterization based on cloud-top height at resolutions that partially resolve deep convection using the Weather Research and Forecasting model with Chemistry (WRF-Chem) over the contiguous United States. With minor modifications, the parameterization is shown to generate integrated flash counts close to those observed. However, the modeled frequency distribution of cloud-to-ground flashes do not represent well for storms with high flash rates, bringing into question the applicability of the intra-cloud/ground partitioning (IC:CG) formulation of Price and Rind in some studies. Resolution dependency also requires attention when sub-grid cloud-tops are used instead of the originally intended grid-averaged cloud-top. LNOx passive tracers being gathered by monsoonal upper tropospheric anticyclone.

Evaluating hourly rainfall characteristics over the U.S. Great Plains in dynamically downscaled climate model simulations using NASA-Unified WRF

Science.gov (United States)

Lee, Huikyo; Waliser, Duane E.; Ferraro, Robert; Iguchi, Takamichi; Peters-Lidard, Christa D.; Tian, Baijun; Loikith, Paul C.; Wright, Daniel B.

2017-07-01

Accurate simulation of extreme precipitation events remains a challenge in climate models. This study utilizes hourly precipitation data from ground stations and satellite instruments to evaluate rainfall characteristics simulated by the NASA-Unified Weather Research and Forecasting (NU-WRF) regional climate model at horizontal resolutions of 4, 12, and 24 km over the Great Plains of the United States. We also examined the sensitivity of the simulated precipitation to different spectral nudging approaches and the cumulus parameterizations. The rainfall characteristics in the observations and simulations were defined as an hourly diurnal cycle of precipitation and a joint probability distribution function (JPDF) between duration and peak intensity of precipitation events over the Great Plains in summer. We calculated a JPDF for each data set and the overlapping area between observed and simulated JPDFs to measure the similarity between the two JPDFs. Comparison of the diurnal precipitation cycles between observations and simulations does not reveal the added value of high-resolution simulations. However, the performance of NU-WRF simulations measured by the JPDF metric strongly depends on horizontal resolution. The simulation with the highest resolution of 4 km shows the best agreement with the observations in simulating duration and intensity of wet spells. Spectral nudging does not affect the JPDF significantly. The effect of cumulus parameterizations on the JPDFs is considerable but smaller than that of horizontal resolution. The simulations with lower resolutions of 12 and 24 km show reasonable agreement but only with the high-resolution observational data that are aggregated into coarse resolution and spatially averaged.

Impact of cloud microphysics and cumulus parameterization on ...

Indian Academy of Sciences (India)

2007-10-09

Oct 9, 2007 ... Bangladesh. Weather Research and Forecast (WRF–ARW version) modelling system with six dif- .... tem intensified rapidly into a land depression over southern part of ... Impact of cloud microphysics and cumulus parameterization on heavy rainfall. 261 .... tent and temperature and is represented as a sum.

Parameterized Disturbance Observer Based Controller to Reduce Cyclic Loads of Wind Turbine

Directory of Open Access Journals (Sweden)

Raja M. Imran

2018-05-01

Full Text Available This paper is concerned with bump-less transfer of parameterized disturbance observer based controller with individual pitch control strategy to reduce cyclic loads of wind turbine in full load operation. Cyclic loads are generated due to wind shear and tower shadow effects. Multivariable disturbance observer based linear controllers are designed with objective to reduce output power fluctuation, tower oscillation and drive-train torsion using optimal control theory. Linear parameterized controllers are designed by using a smooth scheduling mechanism between the controllers. The proposed parameterized controller with individual pitch was tested on nonlinear Fatigue, Aerodynamics, Structures, and Turbulence (FAST code model of National Renewable Energy Laboratory (NREL’s 5 MW wind turbine. The closed-loop system performance was assessed by comparing the simulation results of proposed controller with a fixed gain and parameterized controller with collective pitch for full load operation of wind turbine. Simulations are performed with step wind to see the behavior of the system with wind shear and tower shadow effects. Then, turbulent wind is applied to see the smooth transition of the controllers. It can be concluded from the results that the proposed parameterized control shows smooth transition from one controller to another controller. Moreover, 3p and 6p harmonics are well mitigated as compared to fixed gain DOBC and parameterized DOBC with collective pitch.

Toward Process-resolving Synthesis and Prediction of Arctic Climate Change Using the Regional Arctic System Model

Science.gov (United States)

Maslowski, W.

2017-12-01

The Regional Arctic System Model (RASM) has been developed to better understand the operation of Arctic System at process scale and to improve prediction of its change at a spectrum of time scales. RASM is a pan-Arctic, fully coupled ice-ocean-atmosphere-land model with marine biogeochemistry extension to the ocean and sea ice models. The main goal of our research is to advance a system-level understanding of critical processes and feedbacks in the Arctic and their links with the Earth System. The secondary, an equally important objective, is to identify model needs for new or additional observations to better understand such processes and to help constrain models. Finally, RASM has been used to produce sea ice forecasts for September 2016 and 2017, in contribution to the Sea Ice Outlook of the Sea Ice Prediction Network. Future RASM forecasts, are likely to include increased resolution for model components and ecosystem predictions. Such research is in direct support of the US environmental assessment and prediction needs, including those of the U.S. Navy, Department of Defense, and the recent IARPC Arctic Research Plan 2017-2021. In addition to an overview of RASM technical details, selected model results are presented from a hierarchy of climate models together with available observations in the region to better understand potential oceanic contributions to polar amplification. RASM simulations are analyzed to evaluate model skill in representing seasonal climatology as well as interannual and multi-decadal climate variability and predictions. Selected physical processes and resulting feedbacks are discussed to emphasize the need for fully coupled climate model simulations, high model resolution and sensitivity of simulated sea ice states to scale dependent model parameterizations controlling ice dynamics, thermodynamics and coupling with the atmosphere and ocean.