High-resolution regional climate model evaluation using variable-resolution CESM over California

NASA Astrophysics Data System (ADS)

Huang, X.; Rhoades, A.; Ullrich, P. A.; Zarzycki, C. M.

2015-12-01

Understanding the effect of climate change at regional scales remains a topic of intensive research. Though computational constraints remain a problem, high horizontal resolution is needed to represent topographic forcing, which is a significant driver of local climate variability. Although regional climate models (RCMs) have traditionally been used at these scales, variable-resolution global climate models (VRGCMs) have recently arisen as an alternative for studying regional weather and climate allowing two-way interaction between these domains without the need for nudging. In this study, the recently developed variable-resolution option within the Community Earth System Model (CESM) is assessed for long-term regional climate modeling over California. Our variable-resolution simulations will focus on relatively high resolutions for climate assessment, namely 28km and 14km regional resolution, which are much more typical for dynamically downscaled studies. For comparison with the more widely used RCM method, the Weather Research and Forecasting (WRF) model will be used for simulations at 27km and 9km. All simulations use the AMIP (Atmospheric Model Intercomparison Project) protocols. The time period is from 1979-01-01 to 2005-12-31 (UTC), and year 1979 was discarded as spin up time. The mean climatology across California's diverse climate zones, including temperature and precipitation, is analyzed and contrasted with the Weather Research and Forcasting (WRF) model (as a traditional RCM), regional reanalysis, gridded observational datasets and uniform high-resolution CESM at 0.25 degree with the finite volume (FV) dynamical core. The results show that variable-resolution CESM is competitive in representing regional climatology on both annual and seasonal time scales. This assessment adds value to the use of VRGCMs for projecting climate change over the coming century and improve our understanding of both past and future regional climate related to fine-scale processes. This assessment is also relevant for addressing the scale limitation of current RCMs or VRGCMs when next-generation model resolution increases to ~10km and beyond.

North Atlantic Tropical Cyclones: historical simulations and future changes with the new high-resolution Arpege AGCM.

NASA Astrophysics Data System (ADS)

Pilon, R.; Chauvin, F.; Palany, P.; Belmadani, A.

2017-12-01

A new version of the variable high-resolution Meteo-France Arpege atmospheric general circulation model (AGCM) has been developed for tropical cyclones (TC) studies, with a focus on the North Atlantic basin, where the model horizontal resolution is 15 km. Ensemble historical AMIP (Atmospheric Model Intercomparison Project)-type simulations (1965-2014) and future projections (2020-2080) under the IPCC (Intergovernmental Panel on Climate Change) representative concentration pathway (RCP) 8.5 scenario have been produced. TC-like vortices tracking algorithm is used to investigate TC activity and variability. TC frequency, genesis, geographical distribution and intensity are examined. Historical simulations are compared to best-track and reanalysis datasets. Model TC frequency is generally realistic but tends to be too high during the rst decade of the historical simulations. Biases appear to originate from both the tracking algorithm and model climatology. Nevertheless, the model is able to simulate extremely well intense TCs corresponding to category 5 hurricanes in the North Atlantic, where grid resolution is highest. Interaction between developing TCs and vertical wind shear is shown to be contributing factor for TC variability. Future changes in TC activity and properties are also discussed.

Using Empirical Orthogonal Teleconnections to Analyze Interannual Precipitation Variability in China

NASA Astrophysics Data System (ADS)

Stephan, C.; Klingaman, N. P.; Vidale, P. L.; Turner, A. G.; Demory, M. E.; Guo, L.

2017-12-01

Interannual rainfall variability in China affects agriculture, infrastructure and water resource management. A consistent and objective method, Empirical Orthogonal Teleconnection (EOT) analysis, is applied to precipitation observations over China in all seasons. Instead of maximizing the explained space-time variance, the method identifies regions in China that best explain the temporal variability in domain-averaged rainfall. It produces known teleconnections, that include high positive correlations with ENSO in eastern China in winter, along the Yangtze River in summer, and in southeast China during spring. New findings include that variability along the southeast coast in winter, in the Yangtze valley in spring, and in eastern China in autumn, are associated with extratropical Rossby wave trains. The same analysis is applied to six climate simulations of the Met Office Unified Model with and without air-sea coupling and at various horizontal resolutions of 40, 90 and 200 km. All simulations reproduce the observed patterns of interannual rainfall variability in winter, spring and autumn; the leading pattern in summer is present in all but one simulation. However, only in two simulations are all patterns associated with the observed physical mechanism. Coupled simulations capture more observed patterns of variability and associate more of them with the correct physical mechanism, compared to atmosphere-only simulations at the same resolution. Finer resolution does not improve the fidelity of these patterns or their associated mechanisms. Evaluating climate models by only geographical distribution of mean precipitation and its interannual variance is insufficient; attention must be paid to associated mechanisms.

A Study on the Effects of Spatial Scale on Snow Process in Hyper-Resolution Hydrological Modelling over Mountainous Areas

NASA Astrophysics Data System (ADS)

Garousi Nejad, I.; He, S.; Tang, Q.; Ogden, F. L.; Steinke, R. C.; Frazier, N.; Tarboton, D. G.; Ohara, N.; Lin, H.

2017-12-01

Spatial scale is one of the main considerations in hydrological modeling of snowmelt in mountainous areas. The size of model elements controls the degree to which variability can be explicitly represented versus what needs to be parameterized using effective properties such as averages or other subgrid variability parameterizations that may degrade the quality of model simulations. For snowmelt modeling terrain parameters such as slope, aspect, vegetation and elevation play an important role in the timing and quantity of snowmelt that serves as an input to hydrologic runoff generation processes. In general, higher resolution enhances the accuracy of the simulation since fine meshes represent and preserve the spatial variability of atmospheric and surface characteristics better than coarse resolution. However, this increases computational cost and there may be a scale beyond which the model response does not improve due to diminishing sensitivity to variability and irreducible uncertainty associated with the spatial interpolation of inputs. This paper examines the influence of spatial resolution on the snowmelt process using simulations of and data from the Animas River watershed, an alpine mountainous area in Colorado, USA, using an unstructured distributed physically based hydrological model developed for a parallel computing environment, ADHydro. Five spatial resolutions (30 m, 100 m, 250 m, 500 m, and 1 km) were used to investigate the variations in hydrologic response. This study demonstrated the importance of choosing the appropriate spatial scale in the implementation of ADHydro to obtain a balance between representing spatial variability and the computational cost. According to the results, variation in the input variables and parameters due to using different spatial resolution resulted in changes in the obtained hydrological variables, especially snowmelt, both at the basin-scale and distributed across the model mesh.

Regional model simulations of New Zealand climate

NASA Astrophysics Data System (ADS)

Renwick, James A.; Katzfey, Jack J.; Nguyen, Kim C.; McGregor, John L.

1998-03-01

Simulation of New Zealand climate is examined through the use of a regional climate model nested within the output of the Commonwealth Scientific and Industrial Research Organisation nine-level general circulation model (GCM). R21 resolution GCM output is used to drive a regional model run at 125 km grid spacing over the Australasian region. The 125 km run is used in turn to drive a simulation at 50 km resolution over New Zealand. Simulations with a full seasonal cycle are performed for 10 model years. The focus is on the quality of the simulation of present-day climate, but results of a doubled-CO2 run are discussed briefly. Spatial patterns of mean simulated precipitation and surface temperatures improve markedly as horizontal resolution is increased, through the better resolution of the country's orography. However, increased horizontal resolution leads to a positive bias in precipitation. At 50 km resolution, simulated frequency distributions of daily maximum/minimum temperatures are statistically similar to those of observations at many stations, while frequency distributions of daily precipitation appear to be statistically different to those of observations at most stations. Modeled daily precipitation variability at 125 km resolution is considerably less than observed, but is comparable to, or exceeds, observed variability at 50 km resolution. The sensitivity of the simulated climate to changes in the specification of the land surface is discussed briefly. Spatial patterns of the frequency of extreme temperatures and precipitation are generally well modeled. Under a doubling of CO2, the frequency of precipitation extremes changes only slightly at most locations, while air frosts become virtually unknown except at high-elevation sites.

Analyzing the Effects of Horizontal Resolution on Long-Term Coupled WRF-CMAQ Simulations

EPA Science Inventory

The objective of this study is to determine the adequacy of using a relatively coarse horizontal resolution (i.e. 36 km) to simulate long-term trends of pollutant concentrations and radiation variables with the coupled WRF-CMAQ model. To this end, WRF-CMAQ simulations over the co...

Assessment of the effects of horizontal grid resolution on long ...

EPA Pesticide Factsheets

The objective of this study is to determine the adequacy of using a relatively coarse horizontal resolution (i.e. 36 km) to simulate long-term trends of pollutant concentrations and radiation variables with the coupled WRF-CMAQ model. WRF-CMAQ simulations over the continental United State are performed over the 2001 to 2010 time period at two different horizontal resolutions of 12 and 36 km. Both simulations used the same emission inventory and model configurations. Model results are compared both in space and time to assess the potential weaknesses and strengths of using coarse resolution in long-term air quality applications. The results show that the 36 km and 12 km simulations are comparable in terms of trends analysis for both pollutant concentrations and radiation variables. The advantage of using the coarser 36 km resolution is a significant reduction of computational cost, time and storage requirement which are key considerations when performing multiple years of simulations for trend analysis. However, if such simulations are to be used for local air quality analysis, finer horizontal resolution may be beneficial since it can provide information on local gradients. In particular, divergences between the two simulations are noticeable in urban, complex terrain and coastal regions. The National Exposure Research Laboratory’s Atmospheric Modeling Division (AMAD) conducts research in support of EPA’s mission to protect human health and the environment.

Impact of Variable-Resolution Meshes on Regional Climate Simulations

NASA Astrophysics Data System (ADS)

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.

Impact of Variable-Resolution Meshes on Regional Climate Simulations

NASA Astrophysics Data System (ADS)

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

2013-12-01

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 NCEP/NCAR 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.

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

NASA Astrophysics Data System (ADS)

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.

Effect of climate data on simulated carbon and nitrogen balances for Europe

NASA Astrophysics Data System (ADS)

Blanke, Jan Hendrik; Lindeskog, Mats; Lindström, Johan; Lehsten, Veiko

2016-05-01

In this study, we systematically assess the spatial variability in carbon and nitrogen balance simulations related to the choice of global circulation models (GCMs), representative concentration pathways (RCPs), spatial resolutions, and the downscaling methods used as calculated with LPJ-GUESS. We employed a complete factorial design and performed 24 simulations for Europe with different climate input data sets and different combinations of these four factors. Our results reveal that the variability in simulated output in Europe is moderate with 35.6%-93.5% of the total variability being common among all combinations of factors. The spatial resolution is the most important factor among the examined factors, explaining 1.5%-10.7% of the total variability followed by GCMs (0.3%-7.6%), RCPs (0%-6.3%), and downscaling methods (0.1%-4.6%). The higher-order interactions effect that captures nonlinear relations between the factors and random effects is pronounced and accounts for 1.6%-45.8% to the total variability. The most distinct hot spots of variability include the mountain ranges in North Scandinavia and the Alps, and the Iberian Peninsula. Based on our findings, we advise to conduct the application of models such as LPJ-GUESS at a reasonably high spatial resolution which is supported by the model structure. There is no notable gain in simulations of ecosystem carbon and nitrogen stocks and fluxes from using regionally downscaled climate in preference to bias-corrected, bilinearly interpolated CMIP5 projections.

Assessment of the effects of horizontal grid resolution on long-term air quality trends using coupled WRF-CMAQ simulations

EPA Science Inventory

The objective of this study is to determine the adequacy of using a relatively coarse horizontal resolution (i.e. 36 km) to simulate long-term trends of pollutant concentrations and radiation variables with the coupled WRF-CMAQ model. WRF-CMAQ simulations over the continental Uni...

Simulation of Anomalous Regional Climate Events with a Variable Resolution Stretched Grid GCM

NASA Technical Reports Server (NTRS)

Fox-Rabinovitz, Michael S.

1999-01-01

The stretched-grid approach provides an efficient down-scaling and consistent interactions between global and regional scales due to using one variable-resolution model for integrations. It is a workable alternative to the widely used nested-grid approach introduced over a decade ago as a pioneering step in regional climate modeling. A variable-resolution General Circulation Model (GCM) employing a stretched grid, with enhanced resolution over the US as the area of interest, is used for simulating two anomalous regional climate events, the US summer drought of 1988 and flood of 1993. The special mode of integration using a stretched-grid GCM and data assimilation system is developed that allows for imitating the nested-grid framework. The mode is useful for inter-comparison purposes and for underlining the differences between these two approaches. The 1988 and 1993 integrations are performed for the two month period starting from mid May. Regional resolutions used in most of the experiments is 60 km. The major goal and the result of the study is obtaining the efficient down-scaling over the area of interest. The monthly mean prognostic regional fields for the stretched-grid integrations are remarkably close to those of the verifying analyses. Simulated precipitation patterns are successfully verified against gauge precipitation observations. The impact of finer 40 km regional resolution is investigated for the 1993 integration and an example of recovering subregional precipitation is presented. The obtained results show that the global variable-resolution stretched-grid approach is a viable candidate for regional and subregional climate studies and applications.

Evaluation of a Mesoscale Convective System in Variable-Resolution CESM

NASA Astrophysics Data System (ADS)

Payne, A. E.; Jablonowski, C.

2017-12-01

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

Unraveling the martian water cycle with high-resolution global climate simulations

NASA Astrophysics Data System (ADS)

Pottier, Alizée; Forget, François; Montmessin, Franck; Navarro, Thomas; Spiga, Aymeric; Millour, Ehouarn; Szantai, André; Madeleine, Jean-Baptiste

2017-07-01

Global climate modeling of the Mars water cycle is usually performed at relatively coarse resolution (200 - 300km), which may not be sufficient to properly represent the impact of waves, fronts, topography effects on the detailed structure of clouds and surface ice deposits. Here, we present new numerical simulations of the annual water cycle performed at a resolution of 1° × 1° (∼ 60 km in latitude). The model includes the radiative effects of clouds, whose influence on the thermal structure and atmospheric dynamics is significant, thus we also examine simulations with inactive clouds to distinguish the direct impact of resolution on circulation and winds from the indirect impact of resolution via water ice clouds. To first order, we find that the high resolution does not dramatically change the behavior of the system, and that simulations performed at ∼ 200 km resolution capture well the behavior of the simulated water cycle and Mars climate. Nevertheless, a detailed comparison between high and low resolution simulations, with reference to observations, reveal several significant changes that impact our understanding of the water cycle active today on Mars. The key northern cap edge dynamics are affected by an increase in baroclinic wave strength, with a complication of northern summer dynamics. South polar frost deposition is modified, with a westward longitudinal shift, since southern dynamics are also influenced. Baroclinic wave mode transitions are observed. New transient phenomena appear, like spiral and streak clouds, already documented in the observations. Atmospheric circulation cells in the polar region exhibit a large variability and are fine structured, with slope winds. Most modeled phenomena affected by high resolution give a picture of a more turbulent planet, inducing further variability. This is challenging for long-period climate studies.

High resolution modelling of soil moisture patterns with TerrSysMP: A comparison with sensor network data

NASA Astrophysics Data System (ADS)

Gebler, S.; Hendricks Franssen, H.-J.; Kollet, S. J.; Qu, W.; Vereecken, H.

2017-04-01

The prediction of the spatial and temporal variability of land surface states and fluxes with land surface models at high spatial resolution is still a challenge. This study compares simulation results using TerrSysMP including a 3D variably saturated groundwater flow model (ParFlow) coupled to the Community Land Model (CLM) of a 38 ha managed grassland head-water catchment in the Eifel (Germany), with soil water content (SWC) measurements from a wireless sensor network, actual evapotranspiration recorded by lysimeters and eddy covariance stations and discharge observations. TerrSysMP was discretized with a 10 × 10 m lateral resolution, variable vertical resolution (0.025-0.575 m), and the following parameterization strategies of the subsurface soil hydraulic parameters: (i) completely homogeneous, (ii) homogeneous parameters for different soil horizons, (iii) different parameters for each soil unit and soil horizon and (iv) heterogeneous stochastic realizations. Hydraulic conductivity and Mualem-Van Genuchten parameters in these simulations were sampled from probability density functions, constructed from either (i) soil texture measurements and Rosetta pedotransfer functions (ROS), or (ii) estimated soil hydraulic parameters by 1D inverse modelling using shuffle complex evolution (SCE). The results indicate that the spatial variability of SWC at the scale of a small headwater catchment is dominated by topography and spatially heterogeneous soil hydraulic parameters. The spatial variability of the soil water content thereby increases as a function of heterogeneity of soil hydraulic parameters. For lower levels of complexity, spatial variability of the SWC was underrepresented in particular for the ROS-simulations. Whereas all model simulations were able to reproduce the seasonal evapotranspiration variability, the poor discharge simulations with high model bias are likely related to short-term ET dynamics and the lack of information about bedrock characteristics and an on-site drainage system in the uncalibrated model. In general, simulation performance was better for the SCE setups. The SCE-simulations had a higher inverse air entry parameter resulting in SWC dynamics in better correspondence with data than the ROS simulations during dry periods. This illustrates that small scale measurements of soil hydraulic parameters cannot be transferred to the larger scale and that interpolated 1D inverse parameter estimates result in an acceptable performance for the catchment.

Data for Figures and Tables in Journal Article Assessment of the Effects of Horizontal Grid Resolution on Long-Term Air Quality Trends using Coupled WRF-CMAQ Simulations, doi:10.1016/j.atmosenv.2016.02.036

EPA Pesticide Factsheets

The dataset represents the data depicted in the Figures and Tables of a Journal Manuscript with the following abstract: The objective of this study is to determine the adequacy of using a relatively coarse horizontal resolution (i.e. 36 km) to simulate long-term trends of pollutant concentrations and radiation variables with the coupled WRF-CMAQ model. WRF-CMAQ simulations over the continental United State are performed over the 2001 to 2010 time period at two different horizontal resolutions of 12 and 36 km. Both simulations used the same emission inventory and model configurations. Model results are compared both in space and time to assess the potential weaknesses and strengths of using coarse resolution in long-term air quality applications. The results show that the 36 km and 12 km simulations are comparable in terms of trends analysis for both pollutant concentrations and radiation variables. The advantage of using the coarser 36 km resolution is a significant reduction of computational cost, time and storage requirement which are key considerations when performing multiple years of simulations for trend analysis. However, if such simulations are to be used for local air quality analysis, finer horizontal resolution may be beneficial since it can provide information on local gradients. In particular, divergences between the two simulations are noticeable in urban, complex terrain and coastal regions.This dataset is associated with the following publication

Understanding climate variability and global climate change using high-resolution GCM simulations

NASA Astrophysics Data System (ADS)

Feng, Xuelei

In this study, three climate processes are examined using long-term simulations from multiple climate models with increasing horizontal resolutions. These simulations include the European Center for Medium-range Weather Forecasts (ECMWF) atmospheric general circulation model (AGCM) runs forced with observed sea surface temperatures (SST) (the Athena runs) and a set of coupled ocean-atmosphere seasonal hindcasts (the Minerva runs). Both sets of runs use different AGCM resolutions, the highest at 16 km. A pair of the Community Climate System Model (CCSM) simulations with ocean general circulation model (OGCM) resolutions at 100 and 10 km are also examined. The higher resolution CCSM run fully resolves oceanic mesoscale eddies. The resolution influence on the precipitation climatology over the Gulf Stream (GS) region is first investigated. In the Athena simulations, the resolution increase generates enhanced mean GS precipitation moderately in both large-scale and sub-scale rainfalls in the North Atlantic, with the latter more tightly confined near the oceanic front. However, the non-eddy resolving OGCM in the Minerva runs simulates a weaker oceanic front and weakens the mean GS precipitation response. On the other hand, an increase in CCSM oceanic resolutions from non-eddy-resolving to eddy resolving regimes greatly improves the model's GS precipitation climatology, resulting in both stronger intensity and more realistic structure. Further analyses show that the improvement of the GS precipitation climatology due to resolution increases is caused by the enhanced atmospheric response to an increased SST gradient near the oceanic front, which leads to stronger surface convergence and upper level divergence. Another focus of this study is on the global warming impacts on precipitation characteristic changes using the high-resolution Athena simulations under the SST forcing from the observations and a global warming scenario. As a comparison, results from the coarse resolution simulation are also analyzed to examine the dependence on resolution. The increasing rates of globally averaged precipitation amount for the high and low resolution simulations are 1.7%/K-1 and 1.8%/K-1, respectively. The sensitivities for heavy, moderate, light and drizzle rain are 6.8, -1.2, 0.0, 0.2%/K-1 for low and 6.3, -1.5, 0.4, -0.2%/K -1 for high resolution simulations. The number of rainy days decreases in a warming scenario, by 3.4 and 4.2 day/year-1, respectively. The most sensitive response of 6.3-6.8%/K-1 for the heavy rain approaches that of the 7%/K-1 for the Clausius-Clapeyron scaling limit. During the twenty-first century simulation, the increases in precipitation are larger over high latitude and wet regions in low and mid-latitudes. Over the dry regions, such as the subtropics, the precipitation amount and frequency decrease. There is a higher occurrence of low and heavy rain from the tropics to mid-latitudes at the expense of the decreases in the frequency of moderate rain. In the third part, the inter-annual variability of the northern hemisphere storm tracks is examined. In the Athena simulations, the leading modes of the observed storm track variability are reproduced realistically by all runs. In general, the fluctuations of the model storm tracks in the North Pacific and Atlantic basins are largely independent of each other. Within each basin, the variations are characterized by the intensity change near the climatological center and the meridional shift of the storm track location. These two modes are associated with major teleconnection patterns of the low frequency atmospheric variations. These model results are not sensitive to resolution. Using the Minerva hindcast initialized in November, it is shown that a portion of the winter (December-January) storm track variability is predictable, mainly due to the influences of the atmospheric wave trains induced by the El Nino and Southern Oscillation.

Local-scale changes in mean and heavy precipitation in Western Europe, climate change or internal variability?

NASA Astrophysics Data System (ADS)

Aalbers, Emma E.; Lenderink, Geert; van Meijgaard, Erik; van den Hurk, Bart J. J. M.

2018-06-01

High-resolution climate information provided by e.g. regional climate models (RCMs) is valuable for exploring the changing weather under global warming, and assessing the local impact of climate change. While there is generally more confidence in the representativeness of simulated processes at higher resolutions, internal variability of the climate system—`noise', intrinsic to the chaotic nature of atmospheric and oceanic processes—is larger at smaller spatial scales as well, limiting the predictability of the climate signal. To quantify the internal variability and robustly estimate the climate signal, large initial-condition ensembles of climate simulations conducted with a single model provide essential information. We analyze a regional downscaling of a 16-member initial-condition ensemble over western Europe and the Alps at 0.11° resolution, similar to the highest resolution EURO-CORDEX simulations. We examine the strength of the forced climate response (signal) in mean and extreme daily precipitation with respect to noise due to internal variability, and find robust small-scale geographical features in the forced response, indicating regional differences in changes in the probability of events. However, individual ensemble members provide only limited information on the forced climate response, even for high levels of global warming. Although the results are based on a single RCM-GCM chain, we believe that they have general value in providing insight in the fraction of the uncertainty in high-resolution climate information that is irreducible, and can assist in the correct interpretation of fine-scale information in multi-model ensembles in terms of a forced response and noise due to internal variability.

Local-scale changes in mean and heavy precipitation in Western Europe, climate change or internal variability?

NASA Astrophysics Data System (ADS)

Aalbers, Emma E.; Lenderink, Geert; van Meijgaard, Erik; van den Hurk, Bart J. J. M.

2017-09-01

High-resolution climate information provided by e.g. regional climate models (RCMs) is valuable for exploring the changing weather under global warming, and assessing the local impact of climate change. While there is generally more confidence in the representativeness of simulated processes at higher resolutions, internal variability of the climate system—`noise', intrinsic to the chaotic nature of atmospheric and oceanic processes—is larger at smaller spatial scales as well, limiting the predictability of the climate signal. To quantify the internal variability and robustly estimate the climate signal, large initial-condition ensembles of climate simulations conducted with a single model provide essential information. We analyze a regional downscaling of a 16-member initial-condition ensemble over western Europe and the Alps at 0.11° resolution, similar to the highest resolution EURO-CORDEX simulations. We examine the strength of the forced climate response (signal) in mean and extreme daily precipitation with respect to noise due to internal variability, and find robust small-scale geographical features in the forced response, indicating regional differences in changes in the probability of events. However, individual ensemble members provide only limited information on the forced climate response, even for high levels of global warming. Although the results are based on a single RCM-GCM chain, we believe that they have general value in providing insight in the fraction of the uncertainty in high-resolution climate information that is irreducible, and can assist in the correct interpretation of fine-scale information in multi-model ensembles in terms of a forced response and noise due to internal variability.

High-resolution surface analysis for extended-range downscaling with limited-area atmospheric models

NASA Astrophysics Data System (ADS)

Separovic, Leo; Husain, Syed Zahid; Yu, Wei; Fernig, David

2014-12-01

High-resolution limited-area model (LAM) simulations are frequently employed to downscale coarse-resolution objective analyses over a specified area of the globe using high-resolution computational grids. When LAMs are integrated over extended time frames, from months to years, they are prone to deviations in land surface variables that can be harmful to the quality of the simulated near-surface fields. Nudging of the prognostic surface fields toward a reference-gridded data set is therefore devised in order to prevent the atmospheric model from diverging from the expected values. This paper presents a method to generate high-resolution analyses of land-surface variables, such as surface canopy temperature, soil moisture, and snow conditions, to be used for the relaxation of lower boundary conditions in extended-range LAM simulations. The proposed method is based on performing offline simulations with an external surface model, forced with the near-surface meteorological fields derived from short-range forecast, operational analyses, and observed temperatures and humidity. Results show that the outputs of the surface model obtained in the present study have potential to improve the near-surface atmospheric fields in extended-range LAM integrations.

A new method to assess the added value of high-resolution regional climate simulations: application to the EURO-CORDEX dataset

NASA Astrophysics Data System (ADS)

Soares, P. M. M.; Cardoso, R. M.

2017-12-01

Regional climate models (RCM) are used with increasing resolutions pursuing to represent in an improved way regional to local scale atmospheric phenomena. The EURO-CORDEX simulations at 0.11° and simulations exploiting finer grid spacing approaching the convective-permitting regimes are representative examples. The climate runs are computationally very demanding and do not always show improvements. These depend on the region, variable and object of study. The gains or losses associated with the use of higher resolution in relation to the forcing model (global climate model or reanalysis), or to different resolution RCM simulations, is known as added value. Its characterization is a long-standing issue, and many different added-value measures have been proposed. In the current paper, a new method is proposed to assess the added value of finer resolution simulations, in comparison to its forcing data or coarser resolution counterparts. This approach builds on a probability density function (PDF) matching score, giving a normalised measure of the difference between diverse resolution PDFs, mediated by the observational ones. The distribution added value (DAV) is an objective added value measure that can be applied to any variable, region or temporal scale, from hindcast or historical (non-synchronous) simulations. The DAVs metric and an application to the EURO-CORDEX simulations, for daily temperatures and precipitation, are here presented. The EURO-CORDEX simulations at both resolutions (0.44o,0.11o) display a clear added value in relation to ERA-Interim, with values around 30% in summer and 20% in the intermediate seasons, for precipitation. When both RCM resolutions are directly compared the added value is limited. The regions with the larger precipitation DAVs are areas where convection is relevant, e.g. Alps and Iberia. When looking at the extreme precipitation PDF tail, the higher resolution improvement is generally greater than the low resolution for seasons and regions. For temperature, the added value is smaller. AcknowledgmentsThe authors wish to acknowledge SOLAR (PTDC/GEOMET/7078/2014) and FCT UID/GEO/50019/ 2013 (Instituto Dom Luiz) projects.

What model resolution is required in climatological downscaling over complex terrain?

NASA Astrophysics Data System (ADS)

El-Samra, Renalda; Bou-Zeid, Elie; El-Fadel, Mutasem

2018-05-01

This study presents results from the Weather Research and Forecasting (WRF) model applied for climatological downscaling simulations over highly complex terrain along the Eastern Mediterranean. We sequentially downscale general circulation model results, for a mild and wet year (2003) and a hot and dry year (2010), to three local horizontal resolutions of 9, 3 and 1 km. Simulated near-surface hydrometeorological variables are compared at different time scales against data from an observational network over the study area comprising rain gauges, anemometers, and thermometers. The overall performance of WRF at 1 and 3 km horizontal resolution was satisfactory, with significant improvement over the 9 km downscaling simulation. The total yearly precipitation from WRF's 1 km and 3 km domains exhibited < 10% bias with respect to observational data. The errors in minimum and maximum temperatures were reduced by the downscaling, along with a high-quality delineation of temperature variability and extremes for both the 1 and 3 km resolution runs. Wind speeds, on the other hand, are generally overestimated for all model resolutions, in comparison with observational data, particularly on the coast (up to 50%) compared to inland stations (up to 40%). The findings therefore indicate that a 3 km resolution is sufficient for the downscaling, especially that it would allow more years and scenarios to be investigated compared to the higher 1 km resolution at the same computational effort. In addition, the results provide a quantitative measure of the potential errors for various hydrometeorological variables.

Results of the spatial resolution simulation for multispectral data (resolution brochures)

NASA Technical Reports Server (NTRS)

1982-01-01

The variable information content of Earth Resource products at different levels of spatial resolution and in different spectral bands is addressed. A low-cost brochure that scientists and laymen could use to visualize the effects of increasing the spatial resolution of multispectral scanner images was produced.

Atmospheric Moisture Budget and Spatial Resolution Dependence of Precipitation Extremes in Aquaplanet Simulations

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

Yang, Qing; Leung, Lai-Yung R.; Rauscher, Sara

This study investigates the resolution dependency of precipitation extremes in an aqua-planet framework. Strong resolution dependency of precipitation extremes is seen over both tropics and extra-tropics, and the magnitude of this dependency also varies with dynamical cores. Moisture budget analyses based on aqua-planet simulations with the Community Atmosphere Model (CAM) using the Model for Prediction Across Scales (MPAS) and High Order Method Modeling Environment (HOMME) dynamical cores but the same physics parameterizations suggest that during precipitation extremes moisture supply for surface precipitation is mainly derived from advective moisture convergence. The resolution dependency of precipitation extremes mainly originates from advective moisturemore » transport in the vertical direction. At most vertical levels over the tropics and in the lower atmosphere over the subtropics, the vertical eddy transport of mean moisture field dominates the contribution to precipitation extremes and its resolution dependency. Over the subtropics, the source of moisture, its associated energy, and the resolution dependency during extremes are dominated by eddy transport of eddies moisture at the mid- and upper-troposphere. With both MPAS and HOMME dynamical cores, the resolution dependency of the vertical advective moisture convergence is mainly explained by dynamical changes (related to vertical velocity or omega), although the vertical gradients of moisture act like averaging kernels to determine the sensitivity of the overall resolution dependency to the changes in omega at different vertical levels. The natural reduction of variability with coarser resolution, represented by areal data averaging (aggregation) effect, largely explains the resolution dependency in omega. The thermodynamic changes, which likely result from non-linear feedback in response to the large dynamical changes, are small compared to the overall changes in dynamics (omega). However, after excluding the data aggregation effect in omega, thermodynamic changes become relatively significant in offsetting the effect of dynamics leading to reduce differences between the simulated and aggregated results. Compared to MPAS, the simulated stronger vertical motion with HOMME also results in larger resolution dependency. Compared to the simulation at fine resolution, the vertical motion during extremes is insufficiently resolved/parameterized at the coarser resolution even after accounting for the natural reduction in variability with coarser resolution, and this is more distinct in the simulation with HOMME. To reduce uncertainties in simulated precipitation extremes, future development in cloud parameterizations must address their sensitivity to spatial resolution as well as dynamical cores.« less

The dependence on atmospheric resolution of ENSO and related East Asian-western North Pacific summer climate variability in a coupled model

NASA Astrophysics Data System (ADS)

Liu, Bo; Zhao, Guijie; Huang, Gang; Wang, Pengfei; Yan, Bangliang

2017-08-01

The authors present results for El Niño-Southern Oscillation (ENSO) and East Asian-western North Pacific climate variability simulated in a new version high-resolution coupled model (ICM.V2) developed at the Center for Monsoon System Research of the Institute of Atmospheric Physics (CMSR, IAP), Chinese Academy of Sciences. The analyses are based on the last 100-year output of a 1000-year simulation. Results are compared to an earlier version of the same coupled model (ICM.V1), reanalysis, and observations. The two versions of ICM have similar physics but different atmospheric resolution. The simulated climatological mean states show marked improvement over many regions, especially the tropics in ICM.V2 compared to those in ICM.V1. The common bias in the cold tongue has reduced, and the warm biases along the ocean boundaries have improved as well. With improved simulation of ENSO, including its period and strength, the ENSO-related western North Pacific summer climate variability becomes more realistic compared to the observations. The simulated East Asian summer monsoon anomalies in the El Niño decaying summer are substantially more realistic in ICM.V2, which might be related to a better simulation of the Indo-Pacific Ocean capacitor (IPOC) effect and Pacific decadal oscillation (PDO).

A 12-year (1987-1998) Ensemble Simulation of the US Climate with a Variable Resolution Stretched Grid GCM

NASA Technical Reports Server (NTRS)

Fox-Rabinovitz, Michael S.; Takacs, Lawrence L.; Govindaraju, Ravi C.

2002-01-01

The variable-resolution stretched-grid (SG) GEOS (Goddard Earth Observing System) GCM has been used for limited ensemble integrations with a relatively coarse, 60 to 100 km, regional resolution over the U.S. The experiments have been run for the 12-year period, 1987-1998, that includes the recent ENSO cycles. Initial conditions 1-2 days apart are used for ensemble members. The goal of the experiments is analyzing the long-term SG-GCM ensemble integrations in terms of their potential in reducing the uncertainties of regional climate simulation while producing realistic mesoscales. The ensemble integration results are analyzed for both prognostic and diagnostic fields. A special attention is devoted to analyzing the variability of precipitation over the U.S. The internal variability of the SG-GCM has been assessed. The ensemble means appear to be closer to the verifying analyses than the individual ensemble members. The ensemble means capture realistic mesoscale patterns, especially those of induced by orography. Two ENSO cycles have been analyzed in terms their impact on the U.S. climate, especially on precipitation. The ability of the SG-GCM simulations to produce regional climate anomalies has been confirmed. However, the optimal size of the ensembles depending on fine regional resolution used, is still to be determined. The SG-GCM ensemble simulations are performed as a preparation or a preliminary stage for the international SGMIP (Stretched-Grid Model Intercomparison Project) that is under way with participation of the major centers and groups employing the SG-approach for regional climate modeling.

Exploring a Variable-Resolution Approach for Simulating Regional Climate in the Rocky Mountain Region Using the VR-CESM

NASA Astrophysics Data System (ADS)

Wu, Chenglai; Liu, Xiaohong; Lin, Zhaohui; Rhoades, Alan M.; Ullrich, Paul A.; Zarzycki, Colin M.; Lu, Zheng; Rahimi-Esfarjani, Stefan R.

2017-10-01

The reliability of climate simulations and projections, particularly in the regions with complex terrains, is greatly limited by the model resolution. In this study we evaluate the variable-resolution Community Earth System Model (VR-CESM) with a high-resolution (0.125°) refinement over the Rocky Mountain region. The VR-CESM results are compared with observations, as well as CESM simulation at a quasi-uniform 1° resolution (UNIF) and Canadian Regional Climate Model version 5 (CRCM5) simulation at a 0.11° resolution. We find that VR-CESM is effective at capturing the observed spatial patterns of temperature, precipitation, and snowpack in the Rocky Mountains with the performance comparable to CRCM5, while UNIF is unable to do so. VR-CESM and CRCM5 simulate better the seasonal variations of precipitation than UNIF, although VR-CESM still overestimates winter precipitation whereas CRCM5 and UNIF underestimate it. All simulations distribute more winter precipitation along the windward (west) flanks of mountain ridges with the greatest overestimation in VR-CESM. VR-CESM simulates much greater snow water equivalent peaks than CRCM5 and UNIF, although the peaks are still 10-40% less than observations. Moreover, the frequency of heavy precipitation events (daily precipitation ≥ 25 mm) in VR-CESM and CRCM5 is comparable to observations, whereas the same events in UNIF are an order of magnitude less frequent. In addition, VR-CESM captures the observed occurrence frequency and seasonal variation of rain-on-snow days and performs better than UNIF and CRCM5. These results demonstrate the VR-CESM's capability in regional climate modeling over the mountainous regions and its promising applications for climate change studies.

The effect of bathymetric filtering on nearshore process model results

USGS Publications Warehouse

Plant, N.G.; Edwards, K.L.; Kaihatu, J.M.; Veeramony, J.; Hsu, L.; Holland, K.T.

2009-01-01

Nearshore wave and flow model results are shown to exhibit a strong sensitivity to the resolution of the input bathymetry. In this analysis, bathymetric resolution was varied by applying smoothing filters to high-resolution survey data to produce a number of bathymetric grid surfaces. We demonstrate that the sensitivity of model-predicted wave height and flow to variations in bathymetric resolution had different characteristics. Wave height predictions were most sensitive to resolution of cross-shore variability associated with the structure of nearshore sandbars. Flow predictions were most sensitive to the resolution of intermediate scale alongshore variability associated with the prominent sandbar rhythmicity. Flow sensitivity increased in cases where a sandbar was closer to shore and shallower. Perhaps the most surprising implication of these results is that the interpolation and smoothing of bathymetric data could be optimized differently for the wave and flow models. We show that errors between observed and modeled flow and wave heights are well predicted by comparing model simulation results using progressively filtered bathymetry to results from the highest resolution simulation. The damage done by over smoothing or inadequate sampling can therefore be estimated using model simulations. We conclude that the ability to quantify prediction errors will be useful for supporting future data assimilation efforts that require this information.

Estimating Ecosystem Carbon Stock Change in the Conterminous United States from 1971 to 2010

NASA Astrophysics Data System (ADS)

Liu, J.; Sleeter, B. M.; Zhu, Z.; Loveland, T. R.; Sohl, T.; Howard, S. M.; Hawbaker, T. J.; Liu, S.; Heath, L. S.; Cochrane, M. A.; Key, C. H.; Jiang, H.; Price, D. T.; Chen, J. M.

2015-12-01

There is significant geographic variability in U.S. ecosystem carbon sequestration due to natural and human environmental conditions. Climate change, natural disturbance and human land use are the major driving forces that can alter local and regional carbon sequestration rates. In this study, a comprehensive environmental input dataset (1-km resolution) was developed and used in the process-based Integrated Biosphere Simulator (IBIS) to quantify the U.S. carbon stock changes from 1971-2010, which potentially forms a baseline for future U.S. carbon scenarios. The key environmental data sources include land cover change information from more than 2,600 sample blocks across U.S. (10-km by 10-km in size, 60-m resolution, 1973-2000), wildland fire scar and burn severity information (30-m resolution, 1984-2010), vegetation canopy percentage and live biomass level (30-m resolution, ~2000), spatially heterogeneous atmospheric carbon dioxide and nitrogen deposition (~50-km resolution, 2003-2009), and newly available climate (4-km resolution, 1895-2010) and soil variables (1-km resolution, ~2000). The IBIS simulated the effects of atmospheric CO2 fertilization, nitrogen deposition, climate change, fire, logging, and deforestation/devegetation on ecosystem carbon changes. Multiple comparable simulations were implemented to quantify the contributions of key environmental drivers.

Scales of variability of black carbon plumes and their dependence on resolution of ECHAM6-HAM

NASA Astrophysics Data System (ADS)

Weigum, Natalie; Stier, Philip; Schutgens, Nick; Kipling, Zak

2015-04-01

Prediction of the aerosol effect on climate depends on the ability of three-dimensional numerical models to accurately estimate aerosol properties. However, a limitation of traditional grid-based models is their inability to resolve variability on scales smaller than a grid box. Past research has shown that significant aerosol variability exists on scales smaller than these grid-boxes, which can lead to discrepancies between observations and aerosol models. The aim of this study is to understand how a global climate model's (GCM) inability to resolve sub-grid scale variability affects simulations of important aerosol features. This problem is addressed by comparing observed black carbon (BC) plume scales from the HIPPO aircraft campaign to those simulated by ECHAM-HAM GCM, and testing how model resolution affects these scales. This study additionally investigates how model resolution affects BC variability in remote and near-source regions. These issues are examined using three different approaches: comparison of observed and simulated along-flight-track plume scales, two-dimensional autocorrelation analysis, and 3-dimensional plume analysis. We find that the degree to which GCMs resolve variability can have a significant impact on the scales of BC plumes, and it is important for models to capture the scales of aerosol plume structures, which account for a large degree of aerosol variability. In this presentation, we will provide further results from the three analysis techniques along with a summary of the implication of these results on future aerosol model development.

Update of global TC simulations using a variable resolution non-hydrostatic model

NASA Astrophysics Data System (ADS)

Park, S. H.

2017-12-01

Using in a variable resolution meshes in MPAS during 2017 summer., Tropical cyclone (TC) forecasts are simulated. Two physics suite are tested to explore performance and bias of each physics suite for TC forecasting. A WRF physics suite is selected from experience on weather forecasting and CAM (Community Atmosphere Model) physics is taken from a AMIP type climate simulation. Based on the last year results from CAM5 physical parameterization package and comparing with WRF physics, we investigated a issue with intensity bias using updated version of CAM physics (CAM6). We also compared these results with coupled version of TC simulations. During this talk, TC structure will be compared specially around of boundary layer and investigate their relationship between TC intensity and different physics package.

Performance of the WRF model to simulate the seasonal and interannual variability of hydrometeorological variables in East Africa: a case study for the Tana River basin in Kenya

NASA Astrophysics Data System (ADS)

Kerandi, Noah Misati; Laux, Patrick; Arnault, Joel; Kunstmann, Harald

2017-10-01

This study investigates the ability of the regional climate model Weather Research and Forecasting (WRF) in simulating the seasonal and interannual variability of hydrometeorological variables in the Tana River basin (TRB) in Kenya, East Africa. The impact of two different land use classifications, i.e., the Moderate Resolution Imaging Spectroradiometer (MODIS) and the US Geological Survey (USGS) at two horizontal resolutions (50 and 25 km) is investigated. Simulated precipitation and temperature for the period 2011-2014 are compared with Tropical Rainfall Measuring Mission (TRMM), Climate Research Unit (CRU), and station data. The ability of Tropical Rainfall Measuring Mission (TRMM) and Climate Research Unit (CRU) data in reproducing in situ observation in the TRB is analyzed. All considered WRF simulations capture well the annual as well as the interannual and spatial distribution of precipitation in the TRB according to station data and the TRMM estimates. Our results demonstrate that the increase of horizontal resolution from 50 to 25 km, together with the use of the MODIS land use classification, significantly improves the precipitation results. In the case of temperature, spatial patterns and seasonal cycle are well reproduced, although there is a systematic cold bias with respect to both station and CRU data. Our results contribute to the identification of suitable and regionally adapted regional climate models (RCMs) for East Africa.

Fine-scale application of WRF-CAM5 during a dust storm episode over East Asia: Sensitivity to grid resolutions and aerosol activation parameterizations

NASA Astrophysics Data System (ADS)

Wang, Kai; Zhang, Yang; Zhang, Xin; Fan, Jiwen; Leung, L. Ruby; Zheng, Bo; Zhang, Qiang; He, Kebin

2018-03-01

An advanced online-coupled meteorology and chemistry model WRF-CAM5 has been applied to East Asia using triple-nested domains at different grid resolutions (i.e., 36-, 12-, and 4-km) to simulate a severe dust storm period in spring 2010. Analyses are performed to evaluate the model performance and investigate model sensitivity to different horizontal grid sizes and aerosol activation parameterizations and to examine aerosol-cloud interactions and their impacts on the air quality. A comprehensive model evaluation of the baseline simulations using the default Abdul-Razzak and Ghan (AG) aerosol activation scheme shows that the model can well predict major meteorological variables such as 2-m temperature (T2), water vapor mixing ratio (Q2), 10-m wind speed (WS10) and wind direction (WD10), and shortwave and longwave radiation across different resolutions with domain-average normalized mean biases typically within ±15%. The baseline simulations also show moderate biases for precipitation and moderate-to-large underpredictions for other major variables associated with aerosol-cloud interactions such as cloud droplet number concentration (CDNC), cloud optical thickness (COT), and cloud liquid water path (LWP) due to uncertainties or limitations in the aerosol-cloud treatments. The model performance is sensitive to grid resolutions, especially for surface meteorological variables such as T2, Q2, WS10, and WD10, with the performance generally improving at finer grid resolutions for those variables. Comparison of the sensitivity simulations with an alternative (i.e., the Fountoukis and Nenes (FN) series scheme) and the default (i.e., AG scheme) aerosol activation scheme shows that the former predicts larger values for cloud variables such as CDNC and COT across all grid resolutions and improves the overall domain-average model performance for many cloud/radiation variables and precipitation. Sensitivity simulations using the FN series scheme also have large impacts on radiations, T2, precipitation, and air quality (e.g., decreasing O3) through complex aerosol-radiation-cloud-chemistry feedbacks. The inclusion of adsorptive activation of dust particles in the FN series scheme has similar impacts on the meteorology and air quality but to lesser extent as compared to differences between the FN series and AG schemes. Compared to the overall differences between the FN series and AG schemes, impacts of adsorptive activation of dust particles can contribute significantly to the increase of total CDNC (∼45%) during dust storm events and indicate their importance in modulating regional climate over East Asia.

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

NASA Astrophysics Data System (ADS)

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.

Effect of elevation resolution on evapotranspiration simulations using MODFLOW.

PubMed

Kambhammettu, B V N P; Schmid, Wolfgang; King, James P; Creel, Bobby J

2012-01-01

Surface elevations represented in MODFLOW head-dependent packages are usually derived from digital elevation models (DEMs) that are available at much high resolution. Conventional grid refinement techniques to simulate the model at DEM resolution increases computational time, input file size, and in many cases are not feasible for regional applications. This research aims at utilizing the increasingly available high resolution DEMs for effective simulation of evapotranspiration (ET) in MODFLOW as an alternative to grid refinement techniques. The source code of the evapotranspiration package is modified by considering for a fixed MODFLOW grid resolution and for different DEM resolutions, the effect of variability in elevation data on ET estimates. Piezometric head at each DEM cell location is corrected by considering the gradient along row and column directions. Applicability of the research is tested for the lower Rio Grande (LRG) Basin in southern New Mexico. The DEM at 10 m resolution is aggregated to resampled DEM grid resolutions which are integer multiples of MODFLOW grid resolution. Cumulative outflows and ET rates are compared at different coarse resolution grids. Results of the analysis conclude that variability in depth-to-groundwater within the MODFLOW cell is a major contributing parameter to ET outflows in shallow groundwater regions. DEM aggregation methods for the LRG Basin have resulted in decreased volumetric outflow due to the formation of a smoothing error, which lowered the position of water table to a level below the extinction depth. © 2011, The Author(s). Ground Water © 2011, National Ground Water Association.

High resolution simulations of aerosol microphysics in a global and regionally nested chemical transport model

NASA Astrophysics Data System (ADS)

Adams, P. J.; Marks, M.

2015-12-01

The aerosol indirect effect is the largest source of forcing uncertainty in current climate models. This effect arises from the influence of aerosols on the reflective properties and lifetimes of clouds, and its magnitude depends on how many particles can serve as cloud droplet formation sites. Assessing levels of this subset of particles (cloud condensation nuclei, or CCN) requires knowledge of aerosol levels and their global distribution, size distributions, and composition. A key tool necessary to advance our understanding of CCN is the use of global aerosol microphysical models, which simulate the processes that control aerosol size distributions: nucleation, condensation/evaporation, and coagulation. Previous studies have found important differences in CO (Chen, D. et al., 2009) and ozone (Jang, J., 1995) modeled at different spatial resolutions, and it is reasonable to believe that short-lived, spatially-variable aerosol species will be similarly - or more - susceptible to model resolution effects. The goal of this study is to determine how CCN levels and spatial distributions change as simulations are run at higher spatial resolution - specifically, to evaluate how sensitive the model is to grid size, and how this affects comparisons against observations. Higher resolution simulations are necessary supports for model/measurement synergy. Simulations were performed using the global chemical transport model GEOS-Chem (v9-02). The years 2008 and 2009 were simulated at 4ox5o and 2ox2.5o globally and at 0.5ox0.667o over Europe and North America. Results were evaluated against surface-based particle size distribution measurements from the European Supersites for Atmospheric Aerosol Research project. The fine-resolution model simulates more spatial and temporal variability in ultrafine levels, and better resolves topography. Results suggest that the coarse model predicts systematically lower ultrafine levels than does the fine-resolution model. Significant differences are also evident with respect to model-measurement comparisons, and will be discussed.

Climate SPHINX: evaluating the impact of resolution and stochastic physics parameterisations in the EC-Earth global climate model

NASA Astrophysics Data System (ADS)

Davini, Paolo; von Hardenberg, Jost; Corti, Susanna; Christensen, Hannah M.; Juricke, Stephan; Subramanian, Aneesh; Watson, Peter A. G.; Weisheimer, Antje; Palmer, Tim N.

2017-03-01

The Climate SPHINX (Stochastic Physics HIgh resolutioN eXperiments) project is a comprehensive set of ensemble simulations aimed at evaluating the sensitivity of present and future climate to model resolution and stochastic parameterisation. The EC-Earth Earth system model is used to explore the impact of stochastic physics in a large ensemble of 30-year climate integrations at five different atmospheric horizontal resolutions (from 125 up to 16 km). The project includes more than 120 simulations in both a historical scenario (1979-2008) and a climate change projection (2039-2068), together with coupled transient runs (1850-2100). A total of 20.4 million core hours have been used, made available from a single year grant from PRACE (the Partnership for Advanced Computing in Europe), and close to 1.5 PB of output data have been produced on SuperMUC IBM Petascale System at the Leibniz Supercomputing Centre (LRZ) in Garching, Germany. About 140 TB of post-processed data are stored on the CINECA supercomputing centre archives and are freely accessible to the community thanks to an EUDAT data pilot project. This paper presents the technical and scientific set-up of the experiments, including the details on the forcing used for the simulations performed, defining the SPHINX v1.0 protocol. In addition, an overview of preliminary results is given. An improvement in the simulation of Euro-Atlantic atmospheric blocking following resolution increase is observed. It is also shown that including stochastic parameterisation in the low-resolution runs helps to improve some aspects of the tropical climate - specifically the Madden-Julian Oscillation and the tropical rainfall variability. 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).

Spatial and temporal variability of clouds and precipitation over Germany: multiscale simulations across the "gray zone"

NASA Astrophysics Data System (ADS)

Barthlott, C.; Hoose, C.

2015-11-01

This paper assesses the resolution dependance of clouds and precipitation over Germany by numerical simulations with the COnsortium for Small-scale MOdeling (COSMO) model. Six intensive observation periods of the HOPE (HD(CP)2 Observational Prototype Experiment) measurement campaign conducted in spring 2013 and 1 summer day of the same year are simulated. By means of a series of grid-refinement resolution tests (horizontal grid spacing 2.8, 1 km, 500, and 250 m), the applicability of the COSMO model to represent real weather events in the gray zone, i.e., the scale ranging between the mesoscale limit (no turbulence resolved) and the large-eddy simulation limit (energy-containing turbulence resolved), is tested. To the authors' knowledge, this paper presents the first non-idealized COSMO simulations in the peer-reviewed literature at the 250-500 m scale. It is found that the kinetic energy spectra derived from model output show the expected -5/3 slope, as well as a dependency on model resolution, and that the effective resolution lies between 6 and 7 times the nominal resolution. Although the representation of a number of processes is enhanced with resolution (e.g., boundary-layer thermals, low-level convergence zones, gravity waves), their influence on the temporal evolution of precipitation is rather weak. However, rain intensities vary with resolution, leading to differences in the total rain amount of up to +48 %. Furthermore, the location of rain is similar for the springtime cases with moderate and strong synoptic forcing, whereas significant differences are obtained for the summertime case with air mass convection. Domain-averaged liquid water paths and cloud condensate profiles are used to analyze the temporal and spatial variability of the simulated clouds. Finally, probability density functions of convection-related parameters are analyzed to investigate their dependance on model resolution and their impact on cloud formation and subsequent precipitation.

Simulating the Agulhas system in global ocean models - nesting vs. multi-resolution unstructured meshes

NASA Astrophysics Data System (ADS)

Biastoch, Arne; Sein, Dmitry; Durgadoo, Jonathan V.; Wang, Qiang; Danilov, Sergey

2018-01-01

Many questions in ocean and climate modelling require the combined use of high resolution, global coverage and multi-decadal integration length. For this combination, even modern resources limit the use of traditional structured-mesh grids. Here we compare two approaches: A high-resolution grid nested into a global model at coarser resolution (NEMO with AGRIF) and an unstructured-mesh grid (FESOM) which allows to variably enhance resolution where desired. The Agulhas system around South Africa is used as a testcase, providing an energetic interplay of a strong western boundary current and mesoscale dynamics. Its open setting into the horizontal and global overturning circulations also requires global coverage. Both model configurations simulate a reasonable large-scale circulation. Distribution and temporal variability of the wind-driven circulation are quite comparable due to the same atmospheric forcing. However, the overturning circulation differs, owing each model's ability to represent formation and spreading of deep water masses. In terms of regional, high-resolution dynamics, all elements of the Agulhas system are well represented. Owing to the strong nonlinearity in the system, Agulhas Current transports of both configurations and in comparison with observations differ in strength and temporal variability. Similar decadal trends in Agulhas Current transport and Agulhas leakage are linked to the trends in wind forcing.

Spectral characteristics of mid-latitude continental convection from a global variable-resolution Voronoi-mesh atmospheric model

NASA Astrophysics Data System (ADS)

Wong, M.; Skamarock, W. C.

2015-12-01

Global numerical weather forecast tests were performed using the global nonhydrostatic atmospheric model, Model for Prediction Across Scales (MPAS), for the NOAA Storm Prediction Center 2015 Spring Forecast Experiment (May 2015) and the Plains Elevated Convection at Night (PECAN) field campaign (June to mid-July 2015). These two sets of forecasts were performed on 50-to-3 km and 15-to-3 km smoothly-varying horizontal meshes, respectively. Both variable-resolution meshes have nominal convection-permitting 3-km grid spacing over the entire continental US. Here we evaluate the limited-area (vs. global) spectra from these NWP simulations. We will show the simulated spectral characteristics of total kinetic energy, vertical velocity variance, and precipitation during these spring and summer periods when diurnal continental convection is most active over central US. Spectral characteristics of a high-resolution global 3-km simulation (essentially no nesting) from the 20 May 2013 Moore, OK tornado case are also shown. These characteristics include spectral scaling, shape, and anisotropy, as well as the effective resolution of continental convection representation in MPAS.

A variable resolution nonhydrostatic global atmospheric semi-implicit semi-Lagrangian model

NASA Astrophysics Data System (ADS)

Pouliot, George Antoine

2000-10-01

The objective of this project is to develop a variable-resolution finite difference adiabatic global nonhydrostatic semi-implicit semi-Lagrangian (SISL) model based on the fully compressible nonhydrostatic atmospheric equations. To achieve this goal, a three-dimensional variable resolution dynamical core was developed and tested. The main characteristics of the dynamical core can be summarized as follows: Spherical coordinates were used in a global domain. A hydrostatic/nonhydrostatic switch was incorporated into the dynamical equations to use the fully compressible atmospheric equations. A generalized horizontal variable resolution grid was developed and incorporated into the model. For a variable resolution grid, in contrast to a uniform resolution grid, the order of accuracy of finite difference approximations is formally lost but remains close to the order of accuracy associated with the uniform resolution grid provided the grid stretching is not too significant. The SISL numerical scheme was implemented for the fully compressible set of equations. In addition, the generalized minimum residual (GMRES) method with restart and preconditioner was used to solve the three-dimensional elliptic equation derived from the discretized system of equations. The three-dimensional momentum equation was integrated in vector-form to incorporate the metric terms in the calculations of the trajectories. Using global re-analysis data for a specific test case, the model was compared to similar SISL models previously developed. Reasonable agreement between the model and the other independently developed models was obtained. The Held-Suarez test for dynamical cores was used for a long integration and the model was successfully integrated for up to 1200 days. Idealized topography was used to test the variable resolution component of the model. Nonhydrostatic effects were simulated at grid spacings of 400 meters with idealized topography and uniform flow. Using a high-resolution topographic data set and the variable resolution grid, sets of experiments with increasing resolution were performed over specific regions of interest. Using realistic initial conditions derived from re-analysis fields, nonhydrostatic effects were significant for grid spacings on the order of 0.1 degrees with orographic forcing. If the model code was adapted for use in a message passing interface (MPI) on a parallel supercomputer today, it was estimated that a global grid spacing of 0.1 degrees would be achievable for a global model. In this case, nonhydrostatic effects would be significant for most areas. A variable resolution grid in a global model provides a unified and flexible approach to many climate and numerical weather prediction problems. The ability to configure the model from very fine to very coarse resolutions allows for the simulation of atmospheric phenomena at different scales using the same code. We have developed a dynamical core illustrating the feasibility of using a variable resolution in a global model.

Interannual Tropical Rainfall Variability in General Circulation Model Simulations Associated with the Atmospheric Model Intercomparison Project.

NASA Astrophysics Data System (ADS)

Sperber, K. R.; Palmer, T. N.

1996-11-01

The interannual variability of rainfall over the Indian subcontinent, the African Sahel, and the Nordeste region of Brazil have been evaluated in 32 models for the period 1979-88 as part of the Atmospheric Model Intercomparison Project (AMIP). The interannual variations of Nordeste rainfall are the most readily captured, owing to the intimate link with Pacific and Atlantic sea surface temperatures. The precipitation variations over India and the Sahel are less well simulated. Additionally, an Indian monsoon wind shear index was calculated for each model. Evaluation of the interannual variability of a wind shear index over the summer monsoon region indicates that the models exhibit greater fidelity in capturing the large-scale dynamic fluctuations than the regional-scale rainfall variations. A rainfall/SST teleconnection quality control was used to objectively stratify model performance. Skill scores improved for those models that qualitatively simulated the observed rainfall/El Niño- Southern Oscillation SST correlation pattern. This subset of models also had a rainfall climatology that was in better agreement with observations, indicating a link between systematic model error and the ability to simulate interannual variations.A suite of six European Centre for Medium-Range Weather Forecasts (ECMWF) AMIP runs (differing only in their initial conditions) have also been examined. As observed, all-India rainfall was enhanced in 1988 relative to 1987 in each of these realizations. All-India rainfall variability during other years showed little or no predictability, possibly due to internal chaotic dynamics associated with intraseasonal monsoon fluctuations and/or unpredictable land surface process interactions. The interannual variations of Nordeste rainfall were best represented. The State University of New York at Albany/National Center for Atmospheric Research Genesis model was run in five initial condition realizations. In this model, the Nordeste rainfall variability was also best reproduced. However, for all regions the skill was less than that of the ECMWF model.The relationships of the all-India and Sahel rainfall/SST teleconnections with horizontal resolution, convection scheme closure, and numerics have been evaluated. Models with resolution T42 performed more poorly than lower-resolution models. The higher resolution models were predominantly spectral. At low resolution, spectral versus gridpoint numerics performed with nearly equal verisimilitude. At low resolution, moisture convergence closure was slightly more preferable than other convective closure techniques. At high resolution, the models that used moisture convergence closure performed very poorly, suggesting that moisture convergence may be problematic for models with horizontal resolution T42.

Final Report: Closeout of the Award NO. DE-FG02-98ER62618 (M.S. Fox-Rabinovitz, P.I.)

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

Fox-Rabinovitz, M. S.

The final report describes the study aimed at exploring the variable-resolution stretched-grid (SG) approach to decadal regional climate modeling using advanced numerical techniques. The obtained results have shown that variable-resolution SG-GCMs using stretched grids with fine resolution over the area(s) of interest, is a viable established approach to regional climate modeling. The developed SG-GCMs have been extensively used for regional climate experimentation. The SG-GCM simulations are aimed at studying the U.S. regional climate variability with an emphasis on studying anomalous summer climate events, the U.S. droughts and floods.

Downscaled and debiased climate simulations for North America from 21,000 years ago to 2100AD

PubMed Central

Lorenz, David J.; Nieto-Lugilde, Diego; Blois, Jessica L.; Fitzpatrick, Matthew C.; Williams, John W.

2016-01-01

Increasingly, ecological modellers are integrating paleodata with future projections to understand climate-driven biodiversity dynamics from the past through the current century. Climate simulations from earth system models are necessary to this effort, but must be debiased and downscaled before they can be used by ecological models. Downscaling methods and observational baselines vary among researchers, which produces confounding biases among downscaled climate simulations. We present unified datasets of debiased and downscaled climate simulations for North America from 21 ka BP to 2100AD, at 0.5° spatial resolution. Temporal resolution is decadal averages of monthly data until 1950AD, average climates for 1950–2005 AD, and monthly data from 2010 to 2100AD, with decadal averages also provided. This downscaling includes two transient paleoclimatic simulations and 12 climate models for the IPCC AR5 (CMIP5) historical (1850–2005), RCP4.5, and RCP8.5 21st-century scenarios. Climate variables include primary variables and derived bioclimatic variables. These datasets provide a common set of climate simulations suitable for seamlessly modelling the effects of past and future climate change on species distributions and diversity. PMID:27377537

Downscaled and debiased climate simulations for North America from 21,000 years ago to 2100AD.

PubMed

Lorenz, David J; Nieto-Lugilde, Diego; Blois, Jessica L; Fitzpatrick, Matthew C; Williams, John W

2016-07-05

Increasingly, ecological modellers are integrating paleodata with future projections to understand climate-driven biodiversity dynamics from the past through the current century. Climate simulations from earth system models are necessary to this effort, but must be debiased and downscaled before they can be used by ecological models. Downscaling methods and observational baselines vary among researchers, which produces confounding biases among downscaled climate simulations. We present unified datasets of debiased and downscaled climate simulations for North America from 21 ka BP to 2100AD, at 0.5° spatial resolution. Temporal resolution is decadal averages of monthly data until 1950AD, average climates for 1950-2005 AD, and monthly data from 2010 to 2100AD, with decadal averages also provided. This downscaling includes two transient paleoclimatic simulations and 12 climate models for the IPCC AR5 (CMIP5) historical (1850-2005), RCP4.5, and RCP8.5 21st-century scenarios. Climate variables include primary variables and derived bioclimatic variables. These datasets provide a common set of climate simulations suitable for seamlessly modelling the effects of past and future climate change on species distributions and diversity.

Spatial Heterogeneity of Leaf Area Index (LAI) and Its Temporal Course on Arable Land: Combining Field Measurements, Remote Sensing and Simulation in a Comprehensive Data Analysis Approach (CDAA).

PubMed

Reichenau, Tim G; Korres, Wolfgang; Montzka, Carsten; Fiener, Peter; Wilken, Florian; Stadler, Anja; Waldhoff, Guido; Schneider, Karl

2016-01-01

The ratio of leaf area to ground area (leaf area index, LAI) is an important state variable in ecosystem studies since it influences fluxes of matter and energy between the land surface and the atmosphere. As a basis for generating temporally continuous and spatially distributed datasets of LAI, the current study contributes an analysis of its spatial variability and spatial structure. Soil-vegetation-atmosphere fluxes of water, carbon and energy are nonlinearly related to LAI. Therefore, its spatial heterogeneity, i.e., the combination of spatial variability and structure, has an effect on simulations of these fluxes. To assess LAI spatial heterogeneity, we apply a Comprehensive Data Analysis Approach that combines data from remote sensing (5 m resolution) and simulation (150 m resolution) with field measurements and a detailed land use map. Test area is the arable land in the fertile loess plain of the Rur catchment on the Germany-Belgium-Netherlands border. LAI from remote sensing and simulation compares well with field measurements. Based on the simulation results, we describe characteristic crop-specific temporal patterns of LAI spatial variability. By means of these patterns, we explain the complex multimodal frequency distributions of LAI in the remote sensing data. In the test area, variability between agricultural fields is higher than within fields. Therefore, spatial resolutions less than the 5 m of the remote sensing scenes are sufficient to infer LAI spatial variability. Frequency distributions from the simulation agree better with the multimodal distributions from remote sensing than normal distributions do. The spatial structure of LAI in the test area is dominated by a short distance referring to field sizes. Longer distances that refer to soil and weather can only be derived from remote sensing data. Therefore, simulations alone are not sufficient to characterize LAI spatial structure. It can be concluded that a comprehensive picture of LAI spatial heterogeneity and its temporal course can contribute to the development of an approach to create spatially distributed and temporally continuous datasets of LAI.

Spatial Heterogeneity of Leaf Area Index (LAI) and Its Temporal Course on Arable Land: Combining Field Measurements, Remote Sensing and Simulation in a Comprehensive Data Analysis Approach (CDAA)

PubMed Central

Korres, Wolfgang; Montzka, Carsten; Fiener, Peter; Wilken, Florian; Stadler, Anja; Waldhoff, Guido; Schneider, Karl

2016-01-01

The ratio of leaf area to ground area (leaf area index, LAI) is an important state variable in ecosystem studies since it influences fluxes of matter and energy between the land surface and the atmosphere. As a basis for generating temporally continuous and spatially distributed datasets of LAI, the current study contributes an analysis of its spatial variability and spatial structure. Soil-vegetation-atmosphere fluxes of water, carbon and energy are nonlinearly related to LAI. Therefore, its spatial heterogeneity, i.e., the combination of spatial variability and structure, has an effect on simulations of these fluxes. To assess LAI spatial heterogeneity, we apply a Comprehensive Data Analysis Approach that combines data from remote sensing (5 m resolution) and simulation (150 m resolution) with field measurements and a detailed land use map. Test area is the arable land in the fertile loess plain of the Rur catchment on the Germany-Belgium-Netherlands border. LAI from remote sensing and simulation compares well with field measurements. Based on the simulation results, we describe characteristic crop-specific temporal patterns of LAI spatial variability. By means of these patterns, we explain the complex multimodal frequency distributions of LAI in the remote sensing data. In the test area, variability between agricultural fields is higher than within fields. Therefore, spatial resolutions less than the 5 m of the remote sensing scenes are sufficient to infer LAI spatial variability. Frequency distributions from the simulation agree better with the multimodal distributions from remote sensing than normal distributions do. The spatial structure of LAI in the test area is dominated by a short distance referring to field sizes. Longer distances that refer to soil and weather can only be derived from remote sensing data. Therefore, simulations alone are not sufficient to characterize LAI spatial structure. It can be concluded that a comprehensive picture of LAI spatial heterogeneity and its temporal course can contribute to the development of an approach to create spatially distributed and temporally continuous datasets of LAI. PMID:27391858

Improved Climate Simulations through a Stochastic Parameterization of Ocean Eddies

NASA Astrophysics Data System (ADS)

Williams, Paul; Howe, Nicola; Gregory, Jonathan; Smith, Robin; Joshi, Manoj

2016-04-01

In climate simulations, the impacts of the sub-grid scales on the resolved scales are conventionally represented using deterministic closure schemes, which assume that the impacts are uniquely determined by the resolved scales. Stochastic parameterization relaxes this assumption, by sampling the sub-grid variability in a computationally inexpensive manner. This presentation shows that the simulated climatological state of the ocean is improved in many respects by implementing a simple stochastic parameterization of ocean eddies into a coupled atmosphere-ocean general circulation model. Simulations from a high-resolution, eddy-permitting ocean model are used to calculate the eddy statistics needed to inject realistic stochastic noise into a low-resolution, non-eddy-permitting version of the same model. A suite of four stochastic experiments is then run to test the sensitivity of the simulated climate to the noise definition, by varying the noise amplitude and decorrelation time within reasonable limits. The addition of zero-mean noise to the ocean temperature tendency is found to have a non-zero effect on the mean climate. Specifically, in terms of the ocean temperature and salinity fields both at the surface and at depth, the noise reduces many of the biases in the low-resolution model and causes it to more closely resemble the high-resolution model. The variability of the strength of the global ocean thermohaline circulation is also improved. It is concluded that stochastic ocean perturbations can yield reductions in climate model error that are comparable to those obtained by refining the resolution, but without the increased computational cost. Therefore, stochastic parameterizations of ocean eddies have the potential to significantly improve climate simulations. Reference PD Williams, NJ Howe, JM Gregory, RS Smith, and MM Joshi (2016) Improved Climate Simulations through a Stochastic Parameterization of Ocean Eddies. Journal of Climate, under revision.

Improved assessment of gross and net primary productivity of Canada's landmass

NASA Astrophysics Data System (ADS)

Gonsamo, Alemu; Chen, Jing M.; Price, David T.; Kurz, Werner A.; Liu, Jane; Boisvenue, Céline; Hember, Robbie A.; Wu, Chaoyang; Chang, Kuo-Hsien

2013-12-01

assess Canada's gross primary productivity (GPP) and net primary productivity (NPP) using boreal ecosystem productivity simulator (BEPS) at 250 m spatial resolution with improved input parameter and driver fields and phenology and nutrient release parameterization schemes. BEPS is a process-based two-leaf enzyme kinetic terrestrial ecosystem model designed to simulate energy, water, and carbon (C) fluxes using spatial data sets of meteorology, remotely sensed land surface variables, soil properties, and photosynthesis and respiration rate parameters. Two improved key land surface variables, leaf area index (LAI) and land cover type, are derived at 250 m from Moderate Resolution Imaging Spectroradiometer sensor. For diagnostic error assessment, we use nine forest flux tower sites where all measured C flux, meteorology, and ancillary data sets are available. The errors due to input drivers and parameters are then independently corrected for Canada-wide GPP and NPP simulations. The optimized LAI use, for example, reduced the absolute bias in GPP from 20.7% to 1.1% for hourly BEPS simulations. Following the error diagnostics and corrections, daily GPP and NPP are simulated over Canada at 250 m spatial resolution, the highest resolution simulation yet for the country or any other comparable region. Total NPP (GPP) for Canada's land area was 1.27 (2.68) Pg C for 2008, with forests contributing 1.02 (2.2) Pg C. The annual comparisons between measured and simulated GPP show that the mean differences are not statistically significant (p > 0.05, paired t test). The main BEPS simulation error sources are from the driver fields.

Kilometric Scale Modeling of the North West European Shelf Seas: Exploring the Spatial and Temporal Variability of Internal Tides

NASA Astrophysics Data System (ADS)

Guihou, K.; Polton, J.; Harle, J.; Wakelin, S.; O'Dea, E.; Holt, J.

2018-01-01

The North West European Shelf break acts as a barrier to the transport and exchange between the open ocean and the shelf seas. The strong spatial variability of these exchange processes is hard to fully explore using observations, and simulations generally are too coarse to simulate the fine-scale processes over the whole region. In this context, under the FASTNEt program, a new NEMO configuration of the North West European Shelf and Atlantic Margin at 1/60° (˜1.8 km) has been developed, with the objective to better understand and quantify the seasonal and interannual variability of shelf break processes. The capability of this configuration to reproduce the seasonal cycle in SST, the barotropic tide, and fine-resolution temperature profiles is assessed against a basin-scale (1/12°, ˜9 km) configuration and a standard regional configuration (7 km resolution). The seasonal cycle is well reproduced in all configurations though the fine-resolution allows the simulation of smaller scale processes. Time series of temperature at various locations on the shelf show the presence of internal waves with a strong spatiotemporal variability. Spectral analysis of the internal waves reveals peaks at the diurnal, semidiurnal, inertial, and quarter-diurnal bands, which are only realistically reproduced in the new configuration. Tidally induced pycnocline variability is diagnosed in the model and shown to vary with the spring neap cycle with mean displacement amplitudes in excess of 2 m for 30% of the stratified domain. With sufficiently fine resolution, internal tides are shown to be generated at numerous bathymetric features resulting in a complex pycnocline displacement superposition pattern.

GFDL's unified regional-global weather-climate modeling system with variable resolution capability for severe weather predictions and regional climate simulations

NASA Astrophysics Data System (ADS)

Lin, S. J.

2015-12-01

The NOAA/Geophysical Fluid Dynamics Laboratory has been developing a unified regional-global modeling system with variable resolution capabilities that can be used for severe weather predictions (e.g., tornado outbreak events and cat-5 hurricanes) and ultra-high-resolution (1-km) regional climate simulations within a consistent global modeling framework. The fundation of this flexible regional-global modeling system is the non-hydrostatic extension of the vertically Lagrangian dynamical core (Lin 2004, Monthly Weather Review) known in the community as FV3 (finite-volume on the cubed-sphere). Because of its flexability and computational efficiency, the FV3 is one of the final candidates of NOAA's Next Generation Global Prediction System (NGGPS). We have built into the modeling system a stretched (single) grid capability, a two-way (regional-global) multiple nested grid capability, and the combination of the stretched and two-way nests, so as to make convection-resolving regional climate simulation within a consistent global modeling system feasible using today's High Performance Computing System. One of our main scientific goals is to enable simulations of high impact weather phenomena (such as tornadoes, thunderstorms, category-5 hurricanes) within an IPCC-class climate modeling system previously regarded as impossible. In this presentation I will demonstrate that it is computationally feasible to simulate not only super-cell thunderstorms, but also the subsequent genesis of tornadoes using a global model that was originally designed for century long climate simulations. As a unified weather-climate modeling system, we evaluated the performance of the model with horizontal resolution ranging from 1 km to as low as 200 km. In particular, for downscaling studies, we have developed various tests to ensure that the large-scale circulation within the global varaible resolution system is well simulated while at the same time the small-scale can be accurately captured within the targeted high resolution region.

Sensitivity to grid resolution in the ability of a chemical transport model to simulate observed oxidant chemistry under high-isoprene conditions

NASA Astrophysics Data System (ADS)

Yu, Karen; Jacob, Daniel J.; Fisher, Jenny A.; Kim, Patrick S.; Marais, Eloise A.; Miller, Christopher C.; Travis, Katherine R.; Zhu, Lei; Yantosca, Robert M.; Sulprizio, Melissa P.; Cohen, Ron C.; Dibb, Jack E.; Fried, Alan; Mikoviny, Tomas; Ryerson, Thomas B.; Wennberg, Paul O.; Wisthaler, Armin

2016-04-01

Formation of ozone and organic aerosol in continental atmospheres depends on whether isoprene emitted by vegetation is oxidized by the high-NOx pathway (where peroxy radicals react with NO) or by low-NOx pathways (where peroxy radicals react by alternate channels, mostly with HO2). We used mixed layer observations from the SEAC4RS aircraft campaign over the Southeast US to test the ability of the GEOS-Chem chemical transport model at different grid resolutions (0.25° × 0.3125°, 2° × 2.5°, 4° × 5°) to simulate this chemistry under high-isoprene, variable-NOx conditions. Observations of isoprene and NOx over the Southeast US show a negative correlation, reflecting the spatial segregation of emissions; this negative correlation is captured in the model at 0.25° × 0.3125° resolution but not at coarser resolutions. As a result, less isoprene oxidation takes place by the high-NOx pathway in the model at 0.25° × 0.3125° resolution (54 %) than at coarser resolution (59 %). The cumulative probability distribution functions (CDFs) of NOx, isoprene, and ozone concentrations show little difference across model resolutions and good agreement with observations, while formaldehyde is overestimated at coarse resolution because excessive isoprene oxidation takes place by the high-NOx pathway with high formaldehyde yield. The good agreement of simulated and observed concentration variances implies that smaller-scale non-linearities (urban and power plant plumes) are not important on the regional scale. Correlations of simulated vs. observed concentrations do not improve with grid resolution because finer modes of variability are intrinsically more difficult to capture. Higher model resolution leads to decreased conversion of NOx to organic nitrates and increased conversion to nitric acid, with total reactive nitrogen oxides (NOy) changing little across model resolutions. Model concentrations in the lower free troposphere are also insensitive to grid resolution. The overall low sensitivity of modeled concentrations to grid resolution implies that coarse resolution is adequate when modeling continental boundary layer chemistry for global applications.

High Resolution Model Intercomparison Project (HighResMIP v1.0) for CMIP6

NASA Astrophysics Data System (ADS)

Haarsma, Reindert J.; Roberts, Malcolm J.; Vidale, Pier Luigi; Senior, Catherine A.; Bellucci, Alessio; Bao, Qing; Chang, Ping; Corti, Susanna; Fučkar, Neven S.; Guemas, Virginie; von Hardenberg, Jost; Hazeleger, Wilco; Kodama, Chihiro; Koenigk, Torben; Leung, L. Ruby; Lu, Jian; Luo, Jing-Jia; Mao, Jiafu; Mizielinski, Matthew S.; Mizuta, Ryo; Nobre, Paulo; Satoh, Masaki; Scoccimarro, Enrico; Semmler, Tido; Small, Justin; von Storch, Jin-Song

2016-11-01

Robust projections and predictions of climate variability and change, particularly at regional scales, rely on the driving processes being represented with fidelity in model simulations. The role of enhanced horizontal resolution in improved process representation in all components of the climate system is of growing interest, particularly as some recent simulations suggest both the possibility of significant changes in large-scale aspects of circulation as well as improvements in small-scale processes and extremes. However, such high-resolution global simulations at climate timescales, with resolutions of at least 50 km in the atmosphere and 0.25° in the ocean, have been performed at relatively few research centres and generally without overall coordination, primarily due to their computational cost. Assessing the robustness of the response of simulated climate to model resolution requires a large multi-model ensemble using a coordinated set of experiments. The Coupled Model Intercomparison Project 6 (CMIP6) is the ideal framework within which to conduct such a study, due to the strong link to models being developed for the CMIP DECK experiments and other model intercomparison projects (MIPs). Increases in high-performance computing (HPC) resources, as well as the revised experimental design for CMIP6, now enable a detailed investigation of the impact of increased resolution up to synoptic weather scales on the simulated mean climate and its variability. The High Resolution Model Intercomparison Project (HighResMIP) presented in this paper applies, for the first time, a multi-model approach to the systematic investigation of the impact of horizontal resolution. A coordinated set of experiments has been designed to assess both a standard and an enhanced horizontal-resolution simulation in the atmosphere and ocean. The set of HighResMIP experiments is divided into three tiers consisting of atmosphere-only and coupled runs and spanning the period 1950-2050, with the possibility of extending to 2100, together with some additional targeted experiments. This paper describes the experimental set-up of HighResMIP, the analysis plan, the connection with the other CMIP6 endorsed MIPs, as well as the DECK and CMIP6 historical simulations. HighResMIP thereby focuses on one of the CMIP6 broad questions, "what are the origins and consequences of systematic model biases?", but we also discuss how it addresses the World Climate Research Program (WCRP) grand challenges.

Spatial variability of the Black Sea surface temperature from high resolution modeling and satellite measurements

NASA Astrophysics Data System (ADS)

Mizyuk, Artem; Senderov, Maxim; Korotaev, Gennady

2016-04-01

Large number of numerical ocean models were implemented for the Black Sea basin during last two decades. They reproduce rather similar structure of synoptical variability of the circulation. Since 00-s numerical studies of the mesoscale structure are carried out using high performance computing (HPC). With the growing capacity of computing resources it is now possible to reconstruct the Black Sea currents with spatial resolution of several hundreds meters. However, how realistic these results can be? In the proposed study an attempt is made to understand which spatial scales are reproduced by ocean model in the Black Sea. Simulations are made using parallel version of NEMO (Nucleus for European Modelling of the Ocean). A two regional configurations with spatial resolutions 5 km and 2.5 km are described. Comparison of the SST from simulations with two spatial resolutions shows rather qualitative difference of the spatial structures. Results of high resolution simulation are compared also with satellite observations and observation-based products from Copernicus using spatial correlation and spectral analysis. Spatial scales of correlations functions for simulated and observed SST are rather close and differs much from satellite SST reanalysis. Evolution of spectral density for modelled SST and reanalysis showed agreed time periods of small scales intensification. Using of the spectral analysis for satellite measurements is complicated due to gaps. The research leading to this results has received funding from Russian Science Foundation (project № 15-17-20020)

A new synoptic scale resolving global climate simulation using the Community Earth System Model

NASA Astrophysics Data System (ADS)

Small, R. Justin; Bacmeister, Julio; Bailey, David; Baker, Allison; Bishop, Stuart; Bryan, Frank; Caron, Julie; Dennis, John; Gent, Peter; Hsu, Hsiao-ming; Jochum, Markus; Lawrence, David; Muñoz, Ernesto; diNezio, Pedro; Scheitlin, Tim; Tomas, Robert; Tribbia, Joseph; Tseng, Yu-heng; Vertenstein, Mariana

2014-12-01

High-resolution global climate modeling holds the promise of capturing planetary-scale climate modes and small-scale (regional and sometimes extreme) features simultaneously, including their mutual interaction. This paper discusses a new state-of-the-art high-resolution Community Earth System Model (CESM) simulation that was performed with these goals in mind. The atmospheric component was at 0.25° grid spacing, and ocean component at 0.1°. One hundred years of "present-day" simulation were completed. Major results were that annual mean sea surface temperature (SST) in the equatorial Pacific and El-Niño Southern Oscillation variability were well simulated compared to standard resolution models. Tropical and southern Atlantic SST also had much reduced bias compared to previous versions of the model. In addition, the high resolution of the model enabled small-scale features of the climate system to be represented, such as air-sea interaction over ocean frontal zones, mesoscale systems generated by the Rockies, and Tropical Cyclones. Associated single component runs and standard resolution coupled runs are used to help attribute the strengths and weaknesses of the fully coupled run. The high-resolution run employed 23,404 cores, costing 250 thousand processor-hours per simulated year and made about two simulated years per day on the NCAR-Wyoming supercomputer "Yellowstone."

File Specification for the 7-km GEOS-5 Nature Run, Ganymed Release Non-Hydrostatic 7-km Global Mesoscale Simulation

NASA Technical Reports Server (NTRS)

da Silva, Arlindo M.; Putman, William; Nattala, J.

2014-01-01

This document describes the gridded output files produced by a two-year global, non-hydrostatic mesoscale simulation for the period 2005-2006 produced with the non-hydrostatic version of GEOS-5 Atmospheric Global Climate Model (AGCM). In addition to standard meteorological parameters (wind, temperature, moisture, surface pressure), this simulation includes 15 aerosol tracers (dust, sea-salt, sulfate, black and organic carbon), O3, CO and CO2. This model simulation is driven by prescribed sea-surface temperature and sea-ice, daily volcanic and biomass burning emissions, as well as high-resolution inventories of anthropogenic sources. A description of the GEOS-5 model configuration used for this simulation can be found in Putman et al. (2014). The simulation is performed at a horizontal resolution of 7 km using a cubed-sphere horizontal grid with 72 vertical levels, extending up to to 0.01 hPa (approximately 80 km). For user convenience, all data products are generated on two logically rectangular longitude-latitude grids: a full-resolution 0.0625 deg grid that approximately matches the native cubed-sphere resolution, and another 0.5 deg reduced-resolution grid. The majority of the full-resolution data products are instantaneous with some fields being time-averaged. The reduced-resolution datasets are mostly time-averaged, with some fields being instantaneous. Hourly data intervals are used for the reduced-resolution datasets, while 30-minute intervals are used for the full-resolution products. All full-resolution output is on the model's native 72-layer hybrid sigma-pressure vertical grid, while the reduced-resolution output is given on native vertical levels and on 48 pressure surfaces extending up to 0.02 hPa. Section 4 presents additional details on horizontal and vertical grids. Information of the model surface representation can be found in Appendix B. The GEOS-5 product is organized into file collections that are described in detail in Appendix C. Additional details about variables listed in this file specification can be found in a separate document, the GEOS-5 File Specification Variable Definition Glossary. Documentation about the current access methods for products described in this document can be found on the GEOS-5 Nature Run portal: http://gmao.gsfc.nasa.gov/projects/G5NR. Information on the scientific quality of this simulation will appear in a forthcoming NASA Technical Report Series on Global Modeling and Data Assimilation to be available from http://gmao.gsfc.nasa.gov/pubs/tm/.

Uncertainty Propagation of Non-Parametric-Derived Precipitation Estimates into Multi-Hydrologic Model Simulations

NASA Astrophysics Data System (ADS)

Bhuiyan, M. A. E.; Nikolopoulos, E. I.; Anagnostou, E. N.

2017-12-01

Quantifying the uncertainty of global precipitation datasets is beneficial when using these precipitation products in hydrological applications, because precipitation uncertainty propagation through hydrologic modeling can significantly affect the accuracy of the simulated hydrologic variables. In this research the Iberian Peninsula has been used as the study area with a study period spanning eleven years (2000-2010). This study evaluates the performance of multiple hydrologic models forced with combined global rainfall estimates derived based on a Quantile Regression Forests (QRF) technique. In QRF technique three satellite precipitation products (CMORPH, PERSIANN, and 3B42 (V7)); an atmospheric reanalysis precipitation and air temperature dataset; satellite-derived near-surface daily soil moisture data; and a terrain elevation dataset are being utilized in this study. A high-resolution, ground-based observations driven precipitation dataset (named SAFRAN) available at 5 km/1 h resolution is used as reference. Through the QRF blending framework the stochastic error model produces error-adjusted ensemble precipitation realizations, which are used to force four global hydrological models (JULES (Joint UK Land Environment Simulator), WaterGAP3 (Water-Global Assessment and Prognosis), ORCHIDEE (Organizing Carbon and Hydrology in Dynamic Ecosystems) and SURFEX (Stands for Surface Externalisée) ) to simulate three hydrologic variables (surface runoff, subsurface runoff and evapotranspiration). The models are forced with the reference precipitation to generate reference-based hydrologic simulations. This study presents a comparative analysis of multiple hydrologic model simulations for different hydrologic variables and the impact of the blending algorithm on the simulated hydrologic variables. Results show how precipitation uncertainty propagates through the different hydrologic model structures to manifest in reduction of error in hydrologic variables.

Spatial Variability in Column CO2 Inferred from High Resolution GEOS-5 Global Model Simulations: Implications for Remote Sensing and Inversions

NASA Technical Reports Server (NTRS)

Ott, L.; Putman, B.; Collatz, J.; Gregg, W.

2012-01-01

Column CO2 observations from current and future remote sensing missions represent a major advancement in our understanding of the carbon cycle and are expected to help constrain source and sink distributions. However, data assimilation and inversion methods are challenged by the difference in scale of models and observations. OCO-2 footprints represent an area of several square kilometers while NASA s future ASCENDS lidar mission is likely to have an even smaller footprint. In contrast, the resolution of models used in global inversions are typically hundreds of kilometers wide and often cover areas that include combinations of land, ocean and coastal areas and areas of significant topographic, land cover, and population density variations. To improve understanding of scales of atmospheric CO2 variability and representativeness of satellite observations, we will present results from a global, 10-km simulation of meteorology and atmospheric CO2 distributions performed using NASA s GEOS-5 general circulation model. This resolution, typical of mesoscale atmospheric models, represents an order of magnitude increase in resolution over typical global simulations of atmospheric composition allowing new insight into small scale CO2 variations across a wide range of surface flux and meteorological conditions. The simulation includes high resolution flux datasets provided by NASA s Carbon Monitoring System Flux Pilot Project at half degree resolution that have been down-scaled to 10-km using remote sensing datasets. Probability distribution functions are calculated over larger areas more typical of global models (100-400 km) to characterize subgrid-scale variability in these models. Particular emphasis is placed on coastal regions and regions containing megacities and fires to evaluate the ability of coarse resolution models to represent these small scale features. Additionally, model output are sampled using averaging kernels characteristic of OCO-2 and ASCENDS measurement concepts to create realistic pseudo-datasets. Pseudo-data are averaged over coarse model grid cell areas to better understand the ability of measurements to characterize CO2 distributions and spatial gradients on both short (daily to weekly) and long (monthly to seasonal) time scales

The Challenge of Simulating the Regional Climate over Florida

NASA Astrophysics Data System (ADS)

Misra, V.; Mishra, A. K.

2015-12-01

In this study we show that the unique geography of the peninsular Florida with close proximity to strong mesoscale surface ocean currents among other factors warrants the use of relatively high resolution climate models to project Florida's hydroclimate. In the absence of such high resolution climate models we highlight the deficiencies of two relatively coarse spatial resolution CMIP5 models with respect to the warm western boundary current of the Gulf Stream. As a consequence it affects the coastal SST and the land-ocean contrast, affecting the rainy summer seasonal precipitation accumulation over peninsular Florida. We also show this through two sensitivity studies conducted with a regional coupled ocean atmosphere model with different bathymetries that dislocate and modulate the strength of the Gulf Stream that locally affects the SST in the two simulations. These studies show that a stronger and more easterly displaced Gulf Stream produces warmer coastal SST's along the Atlantic coast of Florida that enhances the precipitation over peninsular Florida relative to the other regional climate model simulation. However the regional model simulations indicate that variability of wet season rainfall variability in peninsular Florida becomes less dependent on the land-ocean contrast with a stronger Gulf Stream current.

Spatial heterogeneity of leaf area index across scales from simulation and remote sensing

NASA Astrophysics Data System (ADS)

Reichenau, Tim G.; Korres, Wolfgang; Montzka, Carsten; Schneider, Karl

2016-04-01

Leaf area index (LAI, single sided leaf area per ground area) influences mass and energy exchange of vegetated surfaces. Therefore LAI is an input variable for many land surface schemes of coupled large scale models, which do not simulate LAI. Since these models typically run on rather coarse resolution grids, LAI is often inferred from coarse resolution remote sensing. However, especially in agriculturally used areas, a grid cell of these products often covers more than a single land-use. In that case, the given LAI does not apply to any single land-use. Therefore, the overall spatial heterogeneity in these datasets differs from that on resolutions high enough to distinguish areas with differing land-use. Detailed process-based plant growth models simulate LAI for separate plant functional types or specific species. However, limited availability of observations causes reduced spatial heterogeneity of model input data (soil, weather, land-use). Since LAI is strongly heterogeneous in space and time and since processes depend on LAI in a nonlinear way, a correct representation of LAI spatial heterogeneity is also desirable on coarse resolutions. The current study assesses this issue by comparing the spatial heterogeneity of LAI from remote sensing (RapidEye) and process-based simulations (DANUBIA simulation system) across scales. Spatial heterogeneity is assessed by analyzing LAI frequency distributions (spatial variability) and semivariograms (spatial structure). Test case is the arable land in the fertile loess plain of the Rur catchment near the Germany-Netherlands border.

Impact of resolution on aerosol radiative feedbacks with in online-coupled chemistry/climate simulations (WRF-Chem) for EURO-CORDEX compliant domains

NASA Astrophysics Data System (ADS)

López-Romero, Jose Maria; Baró, Rocío; Palacios-Peña, Laura; Jerez, Sonia; Jiménez-Guerrero, Pedro; Montávez, Juan Pedro

2016-04-01

Several studies have shown that a high spatial resolution in atmospheric model runs improves the simulation of some meteorological variables, such as precipitation, particularly extreme events and in regions with complex orography [1]. However, increasing model spatial resolution makes the computational time rise exponentially. Hence, very high resolution experiments on large domains can hamper the execution of climatic runs. This problem shoots up when using online-coupled chemistry climate models, making a careful evaluation of improvements versus costs mandatory. Under this umbrella, the objective of this work is to investigate the sensitivity of aerosol radiative feedbacks from online-coupled chemistry regional model simulations to the spatial resolution. For that, the WRF-Chem [2] model is used for a case study to simulate the episode occurring between July 25th and August 15th of 2010. It is characterized by a high loading of atmospheric aerosol particles coming mainly from wildfires over large European regions (Russia, Iberian Peninsula). Three spatial resolutions are used defined for Euro-Cordex compliant domains [3]: 0.44°, 0.22° and 0.11°. Anthropogenic emissions come from TNO databases [4]. The analysis focuses on air quality variables (mainly PM10, PM2.5), meteorological variables (temperature, radiation) and other aerosol optical properties (aerosol optical depth). The CPU time ratio for the different domains is 1 (0.44°), 4(0.22°) and 28(0.11°) (normalized times). Comparison among simulations and observations are analyzed. Preliminary results show the difficulty to justify the much larger computational cost of high-resolution experiments when comparing with observations from a meteorological point of view, despite the finer spatio-temporal detail of the obtained pollutant fields. [1] Prein, A. F. (2014, December). Precipitation in the EURO-CORDEX 0.11° and 0.44° simulations: high resolution, high benefits?. In AGU Fall Meeting Abstracts (Vol. 1, p. 3893). [2] Grell, G. A., Peckham, S. E., Schmitz, R., McKeen, S. A., Frost, G., Skamarock, W. C., & Eder, B. (2005). Fully coupled "online" chemistry within the WRF model. Atmospheric Environment, 39(37), 6957-6975. [3] Jacob, D., Petersen, J., Eggert, B., Alias, A., Christensen, O. B., Bouwer, L. M., ... & Georgopoulou, E. (2014). EURO-CORDEX: new high-resolution climate change projections for European impact research. Regional Environmental Change, 14(2), 563-578. [4] Pouliot, G., Denier van der Gon, H., Kuenen, J., Makar, P., Zhang, J., Moran, M., 2015. Analysis of the emission inventories and model-ready emission datasets of Europe and North America for phase 2 of the AQMEII project. Atmos. Environ. 115, 345-360.

Monte Carlo study of x-ray cross talk in a variable resolution x-ray detector

NASA Astrophysics Data System (ADS)

Melnyk, Roman; DiBianca, Frank A.

2003-06-01

A variable resolution x-ray (VRX) detector provides a great increase in the spatial resolution of a CT scanner. An important factor that limits the spatial resolution of the detector is x-ray cross-talk. A theoretical study of the x-ray cross-talk is presented in this paper. In the study, two types of the x-ray cross-talk were considered: inter-cell and inter-arm cross-talk. Both types of the x-ray cross-talk were simulated, using the Monte Carlo method, as functions of the detector field of view (FOV). The simulation was repeated for lead and tungsten separators between detector cells. The inter-cell x-ray cross-talk was maximum at the 34-36 cm FOV, but it was low at small and the maximum FOVs. The inter-arm x-ray cross-talk was high at small and medium FOVs, but it was greatly reduced when variable width collimators were placed on the front surfaces of the detector. The inter-cell, but not inter-arm, x-ray cross-talk was lower for tungsten than for lead separators. From the results, x-ray cross-talk in a VRX detector can be minimized by imaging all objects between 24 cm and 40 cm in diameter with the 40 cm FOV, using tungsten separators, and placing variable width collimators in front of the detector.

Meteorology, Emissions, and Grid Resolution: Effects on Discrete and Probabilistic Model Performance

EPA Science Inventory

In this study, we analyze the impacts of perturbations in meteorology and emissions and variations in grid resolution on air quality forecast simulations. The meteorological perturbations con-sidered in this study introduce a typical variability of ~1°C, 250 - 500 m, 1 m/s, and 1...

Improved Climate Simulations through a Stochastic Parameterization of Ocean Eddies

NASA Astrophysics Data System (ADS)

Williams, Paul; Howe, Nicola; Gregory, Jonathan; Smith, Robin; Joshi, Manoj

2017-04-01

In climate simulations, the impacts of the subgrid scales on the resolved scales are conventionally represented using deterministic closure schemes, which assume that the impacts are uniquely determined by the resolved scales. Stochastic parameterization relaxes this assumption, by sampling the subgrid variability in a computationally inexpensive manner. This study shows that the simulated climatological state of the ocean is improved in many respects by implementing a simple stochastic parameterization of ocean eddies into a coupled atmosphere-ocean general circulation model. Simulations from a high-resolution, eddy-permitting ocean model are used to calculate the eddy statistics needed to inject realistic stochastic noise into a low-resolution, non-eddy-permitting version of the same model. A suite of four stochastic experiments is then run to test the sensitivity of the simulated climate to the noise definition by varying the noise amplitude and decorrelation time within reasonable limits. The addition of zero-mean noise to the ocean temperature tendency is found to have a nonzero effect on the mean climate. Specifically, in terms of the ocean temperature and salinity fields both at the surface and at depth, the noise reduces many of the biases in the low-resolution model and causes it to more closely resemble the high-resolution model. The variability of the strength of the global ocean thermohaline circulation is also improved. It is concluded that stochastic ocean perturbations can yield reductions in climate model error that are comparable to those obtained by refining the resolution, but without the increased computational cost. Therefore, stochastic parameterizations of ocean eddies have the potential to significantly improve climate simulations. Reference Williams PD, Howe NJ, Gregory JM, Smith RS, and Joshi MM (2016) Improved Climate Simulations through a Stochastic Parameterization of Ocean Eddies. Journal of Climate, 29, 8763-8781. http://dx.doi.org/10.1175/JCLI-D-15-0746.1

Predictive displays for a process-control schematic interface.

PubMed

Yin, Shanqing; Wickens, Christopher D; Helander, Martin; Laberge, Jason C

2015-02-01

Our objective was to examine the extent to which increasing precision of predictive (rate of change) information in process control will improve performance on a simulated process-control task. Predictive displays have been found to be useful in process control (as well as aviation and maritime industries). However, authors of prior research have not examined the extent to which predictive value is increased by increasing predictor resolution, nor has such research tied potential improvements to changes in process control strategy. Fifty nonprofessional participants each controlled a simulated chemical mixture process (honey mixer simulation) that simulated the operations found in process control. Participants in each of five groups controlled with either no predictor or a predictor ranging in the resolution of prediction of the process. Increasing detail resolution generally increased the benefit of prediction over the control condition although not monotonically so. The best overall performance, combining quality and predictive ability, was obtained by the display of intermediate resolution. The two displays with the lowest resolution were clearly inferior. Predictors with higher resolution are of value but may trade off enhanced sensitivity to variable change (lower-resolution discrete state predictor) with smoother control action (higher-resolution continuous predictors). The research provides guidelines to the process-control industry regarding displays that can most improve operator performance.

Prompt optical emission from gamma-ray bursts with multiple timescale variability of central engine activities

NASA Astrophysics Data System (ADS)

Xu, Si-Yao; Li, Zhuo

2014-04-01

Complete high-resolution light curves of GRB 080319B observed by Swift present an opportunity for detailed temporal analysis of prompt optical emission. With a two-component distribution of initial Lorentz factors, we simulate the dynamical process of shells being ejected from the central engine in the framework of the internal shock model. The emitted radiations are decomposed into different frequency ranges for a temporal correlation analysis between the light curves in different energy bands. The resulting prompt optical and gamma-ray emissions show similar temporal profiles, with both showing a superposition of a component with slow variability and a component with fast variability, except that the gamma-ray light curve is much more variable than its optical counterpart. The variability in the simulated light curves and the strong correlation with a time lag between the optical and gamma-ray emissions are in good agreement with observations of GRB 080319B. Our simulations suggest that the variations seen in the light curves stem from the temporal structure of the shells injected from the central engine of gamma-ray bursts. Future observations with high temporal resolution of prompt optical emission from GRBs, e.g., by UFFO-Pathfinder and SVOM-GWAC, will provide a useful tool for investigating the central engine activity.

Evaluation of tropical channel refinement using MPAS-A aquaplanet simulations

DOE PAGES

Martini, Matus N.; Gustafson, Jr., William I.; O'Brien, Travis A.; ...

2015-09-13

Climate models with variable-resolution grids offer a computationally less expensive way to provide more detailed information at regional scales and increased accuracy for processes that cannot be resolved by a coarser grid. This study uses the Model for Prediction Across Scales–Atmosphere (MPAS22A), consisting of a nonhydrostatic dynamical core and a subset of Advanced Research Weather Research and Forecasting (ARW-WRF) model atmospheric physics that have been modified to include the Community Atmosphere Model version 5 (CAM5) cloud fraction parameterization, to investigate the potential benefits of using increased resolution in an tropical channel. The simulations are performed with an idealized aquaplanet configurationmore » using two quasi-uniform grids, with 30 km and 240 km grid spacing, and two variable-resolution grids spanning the same grid spacing range; one with a narrow (20°S–20°N) and one with a wide (30°S–30°N) tropical channel refinement. Results show that increasing resolution in the tropics impacts both the tropical and extratropical circulation. Compared to the quasi-uniform coarse grid, the narrow-channel simulation exhibits stronger updrafts in the Ferrel cell as well as in the middle of the upward branch of the Hadley cell. The wider tropical channel has a closer correspondence to the 30 km quasi-uniform simulation. However, the total atmospheric poleward energy transports are similar in all simulations. The largest differences are in the low-level cloudiness. The refined channel simulations show improved tropical and extratropical precipitation relative to the global 240 km simulation when compared to the global 30 km simulation. All simulations have a single ITCZ. Furthermore, the relatively small differences in mean global and tropical precipitation rates among the simulations are a promising result, and the evidence points to the tropical channel being an effective method for avoiding the extraneous numerical artifacts seen in earlier studies that only refined portion of the tropics.« less

Diagnosis of boreal summer intraseasonal oscillation in high resolution NCEP climate forecast system

NASA Astrophysics Data System (ADS)

Abhik, S.; Mukhopadhyay, P.; Krishna, R. P. M.; Salunke, Kiran D.; Dhakate, Ashish R.; Rao, Suryachandra A.

2016-05-01

The present study examines the ability of high resolution (T382) National Centers for Environmental Prediction coupled atmosphere-ocean climate forecast system version 2 (CFS T382) in simulating the salient spatio-temporal characteristics of the boreal summertime mean climate and the intraseasonal variability. The shortcomings of the model are identified based on the observation and compared with earlier reported biases of the coarser resolution of CFS (CFS T126). It is found that the CFS T382 reasonably mimics the observed features of basic state climate during boreal summer. But some prominent biases are noted in simulating the precipitation, tropospheric temperature (TT) and sea surface temperature (SST) over the global tropics. Although CFS T382 primarily reproduces the observed distribution of the intraseasonal variability over the Indian summer monsoon region, some difficulty remains in simulating the boreal summer intraseasonal oscillation (BSISO) characteristics. The simulated eastward propagation of BSISO decays rapidly across the Maritime Continent, while the northward propagation appears to be slightly slower than observation. However, the northward propagating BSISO convection propagates smoothly from the equatorial region to the northern latitudes with observed magnitude. Moreover, the observed northwest-southeast tilted rain band is not well reproduced in CFS T382. The warm mean SST bias and inadequate simulation of high frequency modes appear to be responsible for the weak simulation of eastward propagating BSISO. Unlike CFS T126, the simulated mean SST and TT exhibit warm biases, although the mean precipitation and simulated BSISO characteristics are largely similar in both the resolutions of CFS. Further analysis of the convectively coupled equatorial waves (CCEWs) indicates that model overestimates the gravest equatorial Rossby waves and underestimates the Kelvin and mixed Rossby-gravity waves. Based on analysis of CCEWs, the study further explains the possible reasons behind the realistic simulation of northward propagating BSISO in CFS T382, even though the model shows substantial biases in simulating mean state and other BSISO modes.

A Dasymetric-Based Monte Carlo Simulation Approach to the Probabilistic Analysis of Spatial Variables

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

Morton, April M; Piburn, Jesse O; McManamay, Ryan A

2017-01-01

Monte Carlo simulation is a popular numerical experimentation technique used in a range of scientific fields to obtain the statistics of unknown random output variables. Despite its widespread applicability, it can be difficult to infer required input probability distributions when they are related to population counts unknown at desired spatial resolutions. To overcome this challenge, we propose a framework that uses a dasymetric model to infer the probability distributions needed for a specific class of Monte Carlo simulations which depend on population counts.

Inter-annual variability of the Mediterranean thermohaline circulation in Med-CORDEX simulations

NASA Astrophysics Data System (ADS)

Vittoria Struglia, Maria; Adani, Mario; Carillo, Adriana; Pisacane, Giovanna; Sannino, Gianmaria; Beuvier, Jonathan; Lovato, Tomas; Sevault, Florence; Vervatis, Vassilios

2016-04-01

Recent atmospheric reanalysis products, such as ERA40 and ERA-interim, and their regional dynamical downscaling prompted the HyMeX/Med-CORDEX community to perform hind-cast simulations of the Mediterranean Sea, giving the opportunity to evaluate the response of different ocean models to a realistic inter-annual atmospheric forcing. Ocean numerical modeling studies have been steadily improving over the last decade through hind-cast processing, and are complementary to observations in studying the relative importance of the mechanisms playing a role in ocean variability, either external forcing or internal ocean variability. This work presents a review and an inter-comparison of the most recent hind-cast simulations of the Mediterranean Sea Circulation, produced in the framework of the Med-CORDEX initiative, at resolutions spanning from 1/8° to 1/16°. The richness of the simulations available for this study is exploited to address the effects of increasing resolution, both of models and forcing, the initialization procedure, and the prescription of the atmospheric boundary conditions, which are particularly relevant in order to model a realistic THC, in the perspective of fully coupled regional ocean-atmosphere models. The mean circulation is well reproduced by all the simulations. However, it can be observed that the horizontal resolution of both atmospheric forcing and ocean model plays a fundamental role in the reproduction of some specific features of both sub-basins and important differences can be observed among low and high resolution atmosphere forcing. We analyze the mean circulation on both the long-term and decadal time scale, and the represented inter-annual variability of intermediate and deep water mass formation processes in both the Eastern and Western sub-basins, finding that models agree with observations in correspondence of specific events, such as the 1992-1993 Eastern Mediterranean Transient, and the 2005-2006 event in the Gulf of Lion. Long-term trends of the hydrological properties have been investigated at sub-basin scale and have been interpreted in terms of response to forcing and boundary conditions, detectable differences resulting mainly due either to the different initialization and spin up procedure or to the different prescription of Atlantic boundary conditions.

DEM Based Modeling: Grid or TIN? The Answer Depends

NASA Astrophysics Data System (ADS)

Ogden, F. L.; Moreno, H. A.

2015-12-01

The availability of petascale supercomputing power has enabled process-based hydrological simulations on large watersheds and two-way coupling with mesoscale atmospheric models. Of course with increasing watershed scale come corresponding increases in watershed complexity, including wide ranging water management infrastructure and objectives, and ever increasing demands for forcing data. Simulations of large watersheds using grid-based models apply a fixed resolution over the entire watershed. In large watersheds, this means an enormous number of grids, or coarsening of the grid resolution to reduce memory requirements. One alternative to grid-based methods is the triangular irregular network (TIN) approach. TINs provide the flexibility of variable resolution, which allows optimization of computational resources by providing high resolution where necessary and low resolution elsewhere. TINs also increase required effort in model setup, parameter estimation, and coupling with forcing data which are often gridded. This presentation discusses the costs and benefits of the use of TINs compared to grid-based methods, in the context of large watershed simulations within the traditional gridded WRF-HYDRO framework and the new TIN-based ADHydro high performance computing watershed simulator.

Quantitative Evaluation of PET Respiratory Motion Correction Using MR Derived Simulated Data

NASA Astrophysics Data System (ADS)

Polycarpou, Irene; Tsoumpas, Charalampos; King, Andrew P.; Marsden, Paul K.

2015-12-01

The impact of respiratory motion correction on quantitative accuracy in PET imaging is evaluated using simulations for variable patient specific characteristics such as tumor uptake and respiratory pattern. Respiratory patterns from real patients were acquired, with long quiescent motion periods (type-1) as commonly observed in most patients and with long-term amplitude variability as is expected under conditions of difficult breathing (type-2). The respiratory patterns were combined with an MR-derived motion model to simulate real-time 4-D PET-MR datasets. Lung and liver tumors were simulated with diameters of 10 and 12 mm and tumor-to-background ratio ranging from 3:1 to 6:1. Projection data for 6- and 3-mm PET resolution were generated for the Philips Gemini scanner and reconstructed without and with motion correction using OSEM (2 iterations, 23 subsets). Motion correction was incorporated into the reconstruction process based on MR-derived motion fields. Tumor peak standardized uptake values (SUVpeak) were calculated from 30 noise realizations. Respiratory motion correction improves the quantitative performance with the greatest benefit observed for patients of breathing type-2. For breathing type-1 after applying motion correction, SUVpeak of 12-mm liver tumor with 6:1 contrast was increased by 46% for a current PET resolution (i.e., 6 mm) and by 47% for a higher PET resolution (i.e., 3 mm). Furthermore, the results of this study indicate that the benefit of higher scanner resolution is small unless motion correction is applied. In particular, for large liver tumor (12 mm) with low contrast (3:1) after motion correction, the SUVpeak was increased by 34% for 6-mm resolution and by 50% for a higher PET resolution (i.e., 3-mm resolution. This investigation indicates that there is a high impact of respiratory motion correction on tumor quantitative accuracy and that motion correction is important in order to benefit from the increased resolution of future PET scanners.

A downscaling scheme for atmospheric variables to drive soil-vegetation-atmosphere transfer models

NASA Astrophysics Data System (ADS)

Schomburg, A.; Venema, V.; Lindau, R.; Ament, F.; Simmer, C.

2010-09-01

For driving soil-vegetation-transfer models or hydrological models, high-resolution atmospheric forcing data is needed. For most applications the resolution of atmospheric model output is too coarse. To avoid biases due to the non-linear processes, a downscaling system should predict the unresolved variability of the atmospheric forcing. For this purpose we derived a disaggregation system consisting of three steps: (1) a bi-quadratic spline-interpolation of the low-resolution data, (2) a so-called `deterministic' part, based on statistical rules between high-resolution surface variables and the desired atmospheric near-surface variables and (3) an autoregressive noise-generation step. The disaggregation system has been developed and tested based on high-resolution model output (400m horizontal grid spacing). A novel automatic search-algorithm has been developed for deriving the deterministic downscaling rules of step 2. When applied to the atmospheric variables of the lowest layer of the atmospheric COSMO-model, the disaggregation is able to adequately reconstruct the reference fields. Applying downscaling step 1 and 2, root mean square errors are decreased. Step 3 finally leads to a close match of the subgrid variability and temporal autocorrelation with the reference fields. The scheme can be applied to the output of atmospheric models, both for stand-alone offline simulations, and a fully coupled model system.

Analysis and High-Resolution Modeling of Tropical Cyclogenesis During the TCS-08 and TPARC Field Campaign

DTIC Science & Technology

2014-10-13

synoptic and dynamic aspects of cyclogenesis, a multi-nested WRF model (with 2 km resolution in the innermost mesh) will be used to simulate both...intraseasonal and interannual variability of TC activity in the WNP. For the data assimilation task, WRF 3DVar assimilation system will be employed...simulated using WRF . This genesis is associated with Rossby wave energy dispersion of a pre- existing TC Bills (2000). Using the reanalysis data as an

Analyzing and leveraging self-similarity for variable resolution atmospheric models

NASA Astrophysics Data System (ADS)

O'Brien, Travis; Collins, William

2015-04-01

Variable resolution modeling techniques are rapidly becoming a popular strategy for achieving high resolution in a global atmospheric models without the computational cost of global high resolution. However, recent studies have demonstrated a variety of resolution-dependent, and seemingly artificial, features. We argue that the scaling properties of the atmosphere are key to understanding how the statistics of an atmospheric model should change with resolution. We provide two such examples. In the first example we show that the scaling properties of the cloud number distribution define how the ratio of resolved to unresolved clouds should increase with resolution. We show that the loss of resolved clouds, in the high resolution region of variable resolution simulations, with the Community Atmosphere Model version 4 (CAM4) is an artifact of the model's treatment of condensed water (this artifact is significantly reduced in CAM5). In the second example we show that the scaling properties of the horizontal velocity field, combined with the incompressibility assumption, necessarily result in an intensification of vertical mass flux as resolution increases. We show that such an increase is present in a wide variety of models, including CAM and the regional climate models of the ENSEMBLES intercomparision. We present theoretical arguments linking this increase to the intensification of precipitation with increasing resolution.

TopoSCALE v.1.0: downscaling gridded climate data in complex terrain

NASA Astrophysics Data System (ADS)

Fiddes, J.; Gruber, S.

2014-02-01

Simulation of land surface processes is problematic in heterogeneous terrain due to the the high resolution required of model grids to capture strong lateral variability caused by, for example, topography, and the lack of accurate meteorological forcing data at the site or scale it is required. Gridded data products produced by atmospheric models can fill this gap, however, often not at an appropriate spatial resolution to drive land-surface simulations. In this study we describe a method that uses the well-resolved description of the atmospheric column provided by climate models, together with high-resolution digital elevation models (DEMs), to downscale coarse-grid climate variables to a fine-scale subgrid. The main aim of this approach is to provide high-resolution driving data for a land-surface model (LSM). The method makes use of an interpolation of pressure-level data according to topographic height of the subgrid. An elevation and topography correction is used to downscale short-wave radiation. Long-wave radiation is downscaled by deriving a cloud-component of all-sky emissivity at grid level and using downscaled temperature and relative humidity fields to describe variability with elevation. Precipitation is downscaled with a simple non-linear lapse and optionally disaggregated using a climatology approach. We test the method in comparison with unscaled grid-level data and a set of reference methods, against a large evaluation dataset (up to 210 stations per variable) in the Swiss Alps. We demonstrate that the method can be used to derive meteorological inputs in complex terrain, with most significant improvements (with respect to reference methods) seen in variables derived from pressure levels: air temperature, relative humidity, wind speed and incoming long-wave radiation. This method may be of use in improving inputs to numerical simulations in heterogeneous and/or remote terrain, especially when statistical methods are not possible, due to lack of observations (i.e. remote areas or future periods).

Design and testing of a novel multi-stroke micropositioning system with variable resolutions.

PubMed

Xu, Qingsong

2014-02-01

Multi-stroke stages are demanded in micro-/nanopositioning applications which require smaller and larger motion strokes with fine and coarse resolutions, respectively. This paper presents the conceptual design of a novel multi-stroke, multi-resolution micropositioning stage driven by a single actuator for each working axis. It eliminates the issue of the interference among different drives, which resides in conventional multi-actuation stages. The stage is devised based on a fully compliant variable stiffness mechanism, which exhibits unequal stiffnesses in different strokes. Resistive strain sensors are employed to offer variable position resolutions in the different strokes. To quantify the design of the motion strokes and coarse/fine resolution ratio, analytical models are established. These models are verified through finite-element analysis simulations. A proof-of-concept prototype XY stage is designed, fabricated, and tested to demonstrate the feasibility of the presented ideas. Experimental results of static and dynamic testing validate the effectiveness of the proposed design.

Sensitivity of Hydrologic Extremes to Spatial Resolution of Meteorological Forcings: A Case Study of the Conterminous United States

NASA Astrophysics Data System (ADS)

Kao, S. C.; Naz, B. S.; Gangrade, S.; Ashfaq, M.; Rastogi, D.

2016-12-01

The magnitude and frequency of hydroclimate extremes are projected to increase in the conterminous United States (CONUS) with significant implications for future water resource planning and flood risk management. Nevertheless, apart from the change of natural environment, the choice of model spatial resolution could also artificially influence the features of simulated extremes. To better understand how the spatial resolution of meteorological forcings may affect hydroclimate projections, we test the runoff sensitivity using the Variable Infiltration Capacity (VIC) model that was calibrated for each CONUS 8-digit hydrologic unit (HUC8) at 1/24° ( 4km) grid resolution. The 1980-2012 gridded Daymet and PRISM meteorological observations are used to conduct the 1/24° resolution control simulation. Comparative simulations are achieved by smoothing the 1/24° forcing into 1/12° and 1/8° resolutions which are then used to drive the VIC model for the CONUS. In addition, we also test how the simulated high and low runoff conditions would react to change in precipitation (±10%) and temperature (+1°C). The results are further analyzed for various types of hydroclimate extremes across different watersheds in the CONUS. This work helps us understand the sensitivity of simulated runoff to different spatial resolutions of climate forcings and also its sensitivity to different watershed sizes and characteristics of extreme events in the future climate conditions.

High Resolution Model Intercomparison Project (HighResMIP v1.0) for CMIP6

DOE PAGES

Haarsma, Reindert J.; Roberts, Malcolm J.; Vidale, Pier Luigi; ...

2016-11-22

Robust projections and predictions of climate variability and change, particularly at regional scales, rely on the driving processes being represented with fidelity in model simulations. The role of enhanced horizontal resolution in improved process representation in all components of the climate system is of growing interest, particularly as some recent simulations suggest both the possibility of significant changes in large-scale aspects of circulation as well as improvements in small-scale processes and extremes. However, such high-resolution global simulations at climate timescales, with resolutions of at least 50 km in the atmosphere and 0.25° in the ocean, have been performed at relativelymore » few research centres and generally without overall coordination, primarily due to their computational cost. Assessing the robustness of the response of simulated climate to model resolution requires a large multi-model ensemble using a coordinated set of experiments. The Coupled Model Intercomparison Project 6 (CMIP6) is the ideal framework within which to conduct such a study, due to the strong link to models being developed for the CMIP DECK experiments and other model intercomparison projects (MIPs). Increases in high-performance computing (HPC) resources, as well as the revised experimental design for CMIP6, now enable a detailed investigation of the impact of increased resolution up to synoptic weather scales on the simulated mean climate and its variability. The High Resolution Model Intercomparison Project (HighResMIP) presented in this paper applies, for the first time, a multi-model approach to the systematic investigation of the impact of horizontal resolution. A coordinated set of experiments has been designed to assess both a standard and an enhanced horizontal-resolution simulation in the atmosphere and ocean. The set of HighResMIP experiments is divided into three tiers consisting of atmosphere-only and coupled runs and spanning the period 1950–2050, with the possibility of extending to 2100, together with some additional targeted experiments. This paper describes the experimental set-up of HighResMIP, the analysis plan, the connection with the other CMIP6 endorsed MIPs, as well as the DECK and CMIP6 historical simulations. Lastly, HighResMIP thereby focuses on one of the CMIP6 broad questions, “what are the origins and consequences of systematic model biases?”, but we also discuss how it addresses the World Climate Research Program (WCRP) grand challenges.« less

Sharpening method of satellite thermal image based on the geographical statistical model

NASA Astrophysics Data System (ADS)

Qi, Pengcheng; Hu, Shixiong; Zhang, Haijun; Guo, Guangmeng

2016-04-01

To improve the effectiveness of thermal sharpening in mountainous regions, paying more attention to the laws of land surface energy balance, a thermal sharpening method based on the geographical statistical model (GSM) is proposed. Explanatory variables were selected from the processes of land surface energy budget and thermal infrared electromagnetic radiation transmission, then high spatial resolution (57 m) raster layers were generated for these variables through spatially simulating or using other raster data as proxies. Based on this, the local adaptation statistical relationship between brightness temperature (BT) and the explanatory variables, i.e., the GSM, was built at 1026-m resolution using the method of multivariate adaptive regression splines. Finally, the GSM was applied to the high-resolution (57-m) explanatory variables; thus, the high-resolution (57-m) BT image was obtained. This method produced a sharpening result with low error and good visual effect. The method can avoid the blind choice of explanatory variables and remove the dependence on synchronous imagery at visible and near-infrared bands. The influences of the explanatory variable combination, sampling method, and the residual error correction on sharpening results were analyzed deliberately, and their influence mechanisms are reported herein.

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

Sakaguchi, Koichi; Leung, Lai-Yung R.; Zhao, Chun

This study presents a diagnosis of a multi-resolution approach using the Model for Prediction Across Scales - Atmosphere (MPAS-A) for simulating regional climate. Four AMIP experiments are conducted for 1999-2009. In the first two experiments, MPAS-A is configured using global quasi-uniform grids at 120 km and 30 km grid spacing. In the other two experiments, MPAS-A is configured using variable-resolution (VR) mesh with local refinement at 30 km over North America and South America embedded inside a quasi-uniform domain at 120 km elsewhere. Precipitation and related fields in the four simulations are examined to determine how well the VR simulationsmore » reproduce the features simulated by the globally high-resolution model in the refined domain. In previous analyses of idealized aqua-planet simulations, the characteristics of the global high-resolution simulation in moist processes only developed near the boundary of the refined region. In contrast, the AMIP simulations with VR grids are able to reproduce the high-resolution characteristics across the refined domain, particularly in South America. This indicates the importance of finely resolved lower-boundary forcing such as topography and surface heterogeneity for the regional climate, and demonstrates the ability of the MPAS-A VR to replicate the large-scale moisture transport as simulated in the quasi-uniform high-resolution model. Outside of the refined domain, some upscale effects are detected through large-scale circulation but the overall climatic signals are not significant at regional scales. Our results provide support for the multi-resolution approach as a computationally efficient and physically consistent method for modeling regional climate.« less

Rim Fire and its Radiative impact Simulated in CESM/CARMA

NASA Astrophysics Data System (ADS)

Yu, P.; Toon, O. B.; Bardeen, C.; Bucholtz, A.; Rosenlof, K. H.; Saide, P. E.; da Silva, A. M., Jr.; Ziemba, L. D.; Jimenez, J. L.; Schwarz, J. P.; Wagner, N. L.; Lack, D. A.; Mills, M. J.; Reid, J. S.

2015-12-01

The Rim Fire of 2013, the third largest area burned by fire recorded in California history, is simulated by CESM1/CARMA. Modeled aerosol mass, number, effective radius, and extinction coefficient are within variability of data obtained from multiple airborne measurements and satellite measurements. Simulations suggest Rim Fire smoke may block 4-6% of sunlight reaching the surface, with a cooling efficiency around 120-150 W m-2 per unit aerosol optical depth. This study shows that exceptional events like the 2013 Rim Fire can be simulated by a climate model with one-degree resolution, though that resolution is still not sufficient to resolve the smoke peak near the source region.

Quantifying the Contribution of Wind-Driven Linear Response to the Seasonal and Interannual Variability of Amoc Volume Transports Across 26.5ºN

NASA Astrophysics Data System (ADS)

Shimizu, K.; von Storch, J. S.; Haak, H.; Nakayama, K.; Marotzke, J.

2014-12-01

Surface wind stress is considered to be an important forcing of the seasonal and interannual variability of Atlantic Meridional Overturning Circulation (AMOC) volume transports. A recent study showed that even linear response to wind forcing captures observed features of the mean seasonal cycle. However, the study did not assess the contribution of wind-driven linear response in realistic conditions against the RAPID/MOCHA array observation or Ocean General Circulation Model (OGCM) simulations, because it applied a linear two-layer model to the Atlantic assuming constant upper layer thickness and density difference across the interface. Here, we quantify the contribution of wind-driven linear response to the seasonal and interannual variability of AMOC transports by comparing wind-driven linear simulations under realistic continuous stratification against the RAPID observation and OCGM (MPI-OM) simulations with 0.4º resolution (TP04) and 0.1º resolution (STORM). All the linear and MPI-OM simulations capture more than 60% of the variance in the observed mean seasonal cycle of the Upper Mid-Ocean (UMO) and Florida Strait (FS) transports, two components of the upper branch of the AMOC. The linear and TP04 simulations also capture 25-40% of the variance in the observed transport time series between Apr 2004 and Oct 2012; the STORM simulation does not capture the observed variance because of the stochastic signal in both datasets. Comparison of half-overlapping 12-month-long segments reveals some periods when the linear and TP04 simulations capture 40-60% of the observed variance, as well as other periods when the simulations capture only 0-20% of the variance. These results show that wind-driven linear response is a major contributor to the seasonal and interannual variability of the UMO and FS transports, and that its contribution varies in an interannual timescale, probably due to the variability of stochastic processes.

An advanced stochastic weather generator for simulating 2-D high-resolution climate variables

NASA Astrophysics Data System (ADS)

Peleg, Nadav; Fatichi, Simone; Paschalis, Athanasios; Molnar, Peter; Burlando, Paolo

2017-07-01

A new stochastic weather generator, Advanced WEather GENerator for a two-dimensional grid (AWE-GEN-2d) is presented. The model combines physical and stochastic approaches to simulate key meteorological variables at high spatial and temporal resolution: 2 km × 2 km and 5 min for precipitation and cloud cover and 100 m × 100 m and 1 h for near-surface air temperature, solar radiation, vapor pressure, atmospheric pressure, and near-surface wind. The model requires spatially distributed data for the calibration process, which can nowadays be obtained by remote sensing devices (weather radar and satellites), reanalysis data sets and ground stations. AWE-GEN-2d is parsimonious in terms of computational demand and therefore is particularly suitable for studies where exploring internal climatic variability at multiple spatial and temporal scales is fundamental. Applications of the model include models of environmental systems, such as hydrological and geomorphological models, where high-resolution spatial and temporal meteorological forcing is crucial. The weather generator was calibrated and validated for the Engelberg region, an area with complex topography in the Swiss Alps. Model test shows that the climate variables are generated by AWE-GEN-2d with a level of accuracy that is sufficient for many practical applications.

Los Angeles megacity: a high-resolution land–atmosphere modelling system for urban CO 2 emissions

DOE PAGES

Feng, Sha; Lauvaux, Thomas; Newman, Sally; ...

2016-07-22

Megacities are major sources of anthropogenic fossil fuel CO 2 (FFCO 2) emissions. The spatial extents of these large urban systems cover areas of 10 000 km 2 or more with complex topography and changing landscapes. We present a high-resolution land–atmosphere modelling system for urban CO 2 emissions over the Los Angeles (LA) megacity area. The Weather Research and Forecasting (WRF)-Chem model was coupled to a very high-resolution FFCO 2 emission product, Hestia-LA, to simulate atmospheric CO 2 concentrations across the LA megacity at spatial resolutions as fine as ~1 km. We evaluated multiple WRF configurations, selecting one that minimizedmore » errors in wind speed, wind direction, and boundary layer height as evaluated by its performance against meteorological data collected during the CalNex-LA campaign (May–June 2010). Our results show no significant difference between moderate-resolution (4 km) and high-resolution (1.3 km) simulations when evaluated against surface meteorological data, but the high-resolution configurations better resolved planetary boundary layer heights and vertical gradients in the horizontal mean winds. We coupled our WRF configuration with the Vulcan 2.2 (10 km resolution) and Hestia-LA (1.3 km resolution) fossil fuel CO 2 emission products to evaluate the impact of the spatial resolution of the CO 2 emission products and the meteorological transport model on the representation of spatiotemporal variability in simulated atmospheric CO 2 concentrations. We find that high spatial resolution in the fossil fuel CO 2 emissions is more important than in the atmospheric model to capture CO 2 concentration variability across the LA megacity. Finally, we present a novel approach that employs simultaneous correlations of the simulated atmospheric CO 2 fields to qualitatively evaluate the greenhouse gas measurement network over the LA megacity. Spatial correlations in the atmospheric CO 2 fields reflect the coverage of individual measurement sites when a statistically significant number of sites observe emissions from a specific source or location. We conclude that elevated atmospheric CO 2 concentrations over the LA megacity are composed of multiple fine-scale plumes rather than a single homogenous urban dome. Furthermore, we conclude that FFCO 2 emissions monitoring in the LA megacity requires FFCO 2 emissions modelling with ~1 km resolution because coarser-resolution emissions modelling tends to overestimate the observational constraints on the emissions estimates.« less

Los Angeles megacity: a high-resolution land–atmosphere modelling system for urban CO 2 emissions

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

Feng, Sha; Lauvaux, Thomas; Newman, Sally

Megacities are major sources of anthropogenic fossil fuel CO 2 (FFCO 2) emissions. The spatial extents of these large urban systems cover areas of 10 000 km 2 or more with complex topography and changing landscapes. We present a high-resolution land–atmosphere modelling system for urban CO 2 emissions over the Los Angeles (LA) megacity area. The Weather Research and Forecasting (WRF)-Chem model was coupled to a very high-resolution FFCO 2 emission product, Hestia-LA, to simulate atmospheric CO 2 concentrations across the LA megacity at spatial resolutions as fine as ~1 km. We evaluated multiple WRF configurations, selecting one that minimizedmore » errors in wind speed, wind direction, and boundary layer height as evaluated by its performance against meteorological data collected during the CalNex-LA campaign (May–June 2010). Our results show no significant difference between moderate-resolution (4 km) and high-resolution (1.3 km) simulations when evaluated against surface meteorological data, but the high-resolution configurations better resolved planetary boundary layer heights and vertical gradients in the horizontal mean winds. We coupled our WRF configuration with the Vulcan 2.2 (10 km resolution) and Hestia-LA (1.3 km resolution) fossil fuel CO 2 emission products to evaluate the impact of the spatial resolution of the CO 2 emission products and the meteorological transport model on the representation of spatiotemporal variability in simulated atmospheric CO 2 concentrations. We find that high spatial resolution in the fossil fuel CO 2 emissions is more important than in the atmospheric model to capture CO 2 concentration variability across the LA megacity. Finally, we present a novel approach that employs simultaneous correlations of the simulated atmospheric CO 2 fields to qualitatively evaluate the greenhouse gas measurement network over the LA megacity. Spatial correlations in the atmospheric CO 2 fields reflect the coverage of individual measurement sites when a statistically significant number of sites observe emissions from a specific source or location. We conclude that elevated atmospheric CO 2 concentrations over the LA megacity are composed of multiple fine-scale plumes rather than a single homogenous urban dome. Furthermore, we conclude that FFCO 2 emissions monitoring in the LA megacity requires FFCO 2 emissions modelling with ~1 km resolution because coarser-resolution emissions modelling tends to overestimate the observational constraints on the emissions estimates.« less

Variable-Resolution Ensemble Climatology Modeling of Sierra Nevada Snowpack within the Community Earth System Model (CESM)

NASA Astrophysics Data System (ADS)

Rhoades, A.; Ullrich, P. A.; Zarzycki, C. M.; Levy, M.; Taylor, M.

2014-12-01

Snowpack is crucial for the western USA, providing around 75% of the total fresh water supply (Cayan et al., 1996) and buffering against seasonal aridity impacts on agricultural, ecosystem, and urban water demands. The resilience of the California water system is largely dependent on natural stores provided by snowpack. This resilience has shown vulnerabilities due to anthropogenic global climate change. Historically, the northern Sierras showed a net decline of 50-75% in snow water equivalent (SWE) while the southern Sierras showed a net accumulation of 30% (Mote et al., 2005). Future trends of SWE highlight that western USA SWE may decline by 40-70% (Pierce and Cayan, 2013), snowfall may decrease by 25-40% (Pierce and Cayan, 2013), and more winter storms may tend towards rain rather than snow (Bales et al., 2006). The volatility of Sierran snowpack presents a need for scientific tools to help water managers and policy makers assess current and future trends. A burgeoning tool to analyze these trends comes in the form of variable-resolution global climate modeling (VRGCM). VRGCMs serve as a bridge between regional and global models and provide added resolution in areas of need, eliminate lateral boundary forcings, provide model runtime speed up, and utilize a common dynamical core, physics scheme and sub-grid scale parameterization package. A cubed-sphere variable-resolution grid with 25 km horizontal resolution over the western USA was developed for use in the Community Atmosphere Model (CAM) within the Community Earth System Model (CESM). A 25-year three-member ensemble climatology (1980-2005) is presented and major snowpack metrics such as SWE, snow depth, snow cover, and two-meter surface temperature are assessed. The ensemble simulation is also compared to observational, reanalysis, and WRF model datasets. The variable-resolution model provides a mechanism for reaching towards non-hydrostatic scales and simulations are currently being developed with refined nests of 12.5km resolution over California.

Can we improve streamflow simulation by using higher resolution rainfall information?

NASA Astrophysics Data System (ADS)

Lobligeois, Florent; Andréassian, Vazken; Perrin, Charles

2013-04-01

The catchment response to rainfall is the interplay between space-time variability of precipitation, catchment characteristics and antecedent hydrological conditions. Precipitation dominates the high frequency hydrological response, and its simulation is thus dependent on the way rainfall is represented. One of the characteristics which distinguishes distributed from lumped models is their ability to represent explicitly the spatial variability of precipitation and catchment characteristics. The sensitivity of runoff hydrographs to the spatial variability of forcing data has been a major concern of researchers over the last three decades. However, although the literature on the relationship between spatial rainfall and runoff response is abundant, results are contrasted and sometimes contradictory. Several studies concluded that including information on rainfall spatial distribution improves discharge simulation (e.g. Ajami et al., 2004, among others) whereas other studies showed the lack of significant improvement in simulations with better information on rainfall spatial pattern (e.g. Andréassian et al., 2004, among others). The difficulties to reach a clear consensus is mainly due to the fact that each modeling study is implemented only on a few catchments whereas the impact of the spatial distribution of rainfall on runoff is known to be catchment and event characteristics-dependent. Many studies are virtual experiments and only compare flow simulations, which makes it difficult to reach conclusions transposable to real-life case studies. Moreover, the hydrological rainfall-runoff models differ between the studies and the parameterization strategies sometimes tend to advantage the distributed approach (or the lumped one). Recently, Météo-France developed a rainfall reanalysis over the whole French territory at the 1-kilometer resolution and the hourly time step over a 10-year period combining radar data and raingauge measurements: weather radar data were corrected and adjusted with both hourly and daily raingauge data. Based on this new high resolution product, we propose a framework to evaluate the improvements in streamflow simulation by using higher resolution rainfall information. Semi-distributed modelling is performed for different spatial resolution of precipitation forcing: from lumped to semi-distributed simulations. Here we do not work on synthetic (simulated) streamflow, but with actual measurements, on a large set of 181 French catchments representing a variety of size and climate. The rainfall-runoff model is re-calibrated for each resolution of rainfall spatial distribution over a 5-year sub-period and evaluated on the complementary sub-period in validation mode. The results are analysed by catchment classes based on catchment area and for various types of rainfall events based on the spatial variability of precipitation. References Ajami, N. K., Gupta, H. V, Wagener, T. & Sorooshian, S. (2004) Calibration of a semi-distributed hydrologic model for streamflow estimation along a river system. Journal of Hydrology 298(1-4), 112-135. Andréassian, V., Oddos, A., Michel, C., Anctil, F., Perrin, C. & Loumagne, C. (2004) Impact of spatial aggregation of inputs and parameters on the efficiency of rainfall-runoff models: A theoretical study using chimera watersheds. Water Resources Research 40(5), 1-9.

Surface Variability of Short-wavelength Radiation and Temperature on Exoplanets around M Dwarfs

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

Zhang, Xin; Tian, Feng; Wang, Yuwei

2017-03-10

It is a common practice to use 3D General Circulation Models (GCM) with spatial resolution of a few hundred kilometers to simulate the climate of Earth-like exoplanets. The enhanced albedo effect of clouds is especially important for exoplanets in the habitable zones around M dwarfs that likely have fixed substellar regions and substantial cloud coverage. Here, we carry out mesoscale model simulations with 3 km spatial resolution driven by the initial and boundary conditions in a 3D GCM and find that it could significantly underestimate the spatial variability of both the incident short-wavelength radiation and the temperature at planet surface.more » Our findings suggest that mesoscale models with cloud-resolving capability be considered for future studies of exoplanet climate.« less

A Variable-Resolution Stretched-Grid General Circulation Model and Data Assimilation System with Multiple Areas of Interest: Studying the Anomalous Regional Climate Events of 1998

NASA Technical Reports Server (NTRS)

Fox-Rabinovitz, Michael S.; Takacs, Lawrence; Govindaraju, Ravi C.; Atlas, Robert (Technical Monitor)

2002-01-01

The new stretched-grid design with multiple (four) areas of interest, one at each global quadrant, is implemented into both a stretched-grid GCM (general circulation model) and a stretched-grid data assimilation system (DAS). The four areas of interest include: the U.S./Northern Mexico, the El Nino area/Central South America, India/China, and the Eastern Indian Ocean/Australia. Both the stretched-grid GCM and DAS annual (November 1997 through December 1998) integrations are performed with 50 km regional resolution. The efficient regional down-scaling to mesoscales is obtained for each of the four areas of interest while the consistent interactions between regional and global scales and the high quality of global circulation, are preserved. This is the advantage of the stretched-grid approach. The global variable resolution DAS incorporating the stretched-grid GCM has been developed and tested as an efficient tool for producing regional analyses and diagnostics with enhanced mesoscale resolution. The anomalous regional climate events of 1998 that occurred over the U.S., Mexico, South America, China, India, African Sahel, and Australia are investigated in both simulation and data assimilation modes. Tree assimilated products are also used, along with gauge precipitation data, for validating the simulation results. The obtained results show that the stretched-grid GCM and DAS are capable of producing realistic high quality simulated and assimilated products at mesoscale resolution for regional climate studies and applications.

Outcomes and challenges of global high-resolution non-hydrostatic atmospheric simulations using the K computer

NASA Astrophysics Data System (ADS)

Satoh, Masaki; Tomita, Hirofumi; Yashiro, Hisashi; Kajikawa, Yoshiyuki; Miyamoto, Yoshiaki; Yamaura, Tsuyoshi; Miyakawa, Tomoki; Nakano, Masuo; Kodama, Chihiro; Noda, Akira T.; Nasuno, Tomoe; Yamada, Yohei; Fukutomi, Yoshiki

2017-12-01

This article reviews the major outcomes of a 5-year (2011-2016) project using the K computer to perform global numerical atmospheric simulations based on the non-hydrostatic icosahedral atmospheric model (NICAM). The K computer was made available to the public in September 2012 and was used as a primary resource for Japan's Strategic Programs for Innovative Research (SPIRE), an initiative to investigate five strategic research areas; the NICAM project fell under the research area of climate and weather simulation sciences. Combining NICAM with high-performance computing has created new opportunities in three areas of research: (1) higher resolution global simulations that produce more realistic representations of convective systems, (2) multi-member ensemble simulations that are able to perform extended-range forecasts 10-30 days in advance, and (3) multi-decadal simulations for climatology and variability. Before the K computer era, NICAM was used to demonstrate realistic simulations of intra-seasonal oscillations including the Madden-Julian oscillation (MJO), merely as a case study approach. Thanks to the big leap in computational performance of the K computer, we could greatly increase the number of cases of MJO events for numerical simulations, in addition to integrating time and horizontal resolution. We conclude that the high-resolution global non-hydrostatic model, as used in this five-year project, improves the ability to forecast intra-seasonal oscillations and associated tropical cyclogenesis compared with that of the relatively coarser operational models currently in use. The impacts of the sub-kilometer resolution simulation and the multi-decadal simulations using NICAM are also reviewed.

Time-resolved High Spectral Resolution Observation of 2MASSW J0746425+200032AB

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

Wang, Ji; Mawet, Dimitri; Prato, Lisa, E-mail: ji.wang@caltech.edu

Many brown dwarfs (BDs) exhibit photometric variability at levels from tenths to tens of percents. The photometric variability is related to magnetic activity or patchy cloud coverage, characteristic of BDs near the L–T transition. Time-resolved spectral monitoring of BDs provides diagnostics of cloud distribution and condensate properties. However, current time-resolved spectral studies of BDs are limited to low spectral resolution ( R ∼ 100) with the exception of the study of Luhman 16 AB at a resolution of 100,000 using the VLT+CRIRES. This work yielded the first map of BD surface inhomogeneity, highlighting the importance and unique contribution of highmore » spectral resolution observations. Here, we report on the time-resolved high spectral resolution observations of a nearby BD binary, 2MASSW J0746425+200032AB. We find no coherent spectral variability that is modulated with rotation. Based on simulations, we conclude that the coverage of a single spot on 2MASSW J0746425+200032AB is smaller than 1% or 6.25% if spot contrast is 50% or 80% of its surrounding flux, respectively. Future high spectral resolution observations aided by adaptive optics systems can put tighter constraints on the spectral variability of 2MASSW J0746425+200032AB and other nearby BDs.« less

Orbiting passive microwave sensor simulation applied to soil moisture estimation

NASA Technical Reports Server (NTRS)

Newton, R. W. (Principal Investigator); Clark, B. V.; Pitchford, W. M.; Paris, J. F.

1979-01-01

A sensor/scene simulation program was developed and used to determine the effects of scene heterogeneity, resolution, frequency, look angle, and surface and temperature relations on the performance of a spaceborne passive microwave system designed to estimate soil water information. The ground scene is based on classified LANDSAT images which provide realistic ground classes, as well as geometries. It was determined that the average sensitivity of antenna temperature to soil moisture improves as the antenna footprint size increased. Also, the precision (or variability) of the sensitivity changes as a function of resolution.

Impact of Spatial Soil and Climate Input Data Aggregation on Regional Yield Simulations

PubMed Central

Hoffmann, Holger; Zhao, Gang; Asseng, Senthold; Bindi, Marco; Biernath, Christian; Constantin, Julie; Coucheney, Elsa; Dechow, Rene; Doro, Luca; Eckersten, Henrik; Gaiser, Thomas; Grosz, Balázs; Heinlein, Florian; Kassie, Belay T.; Kersebaum, Kurt-Christian; Klein, Christian; Kuhnert, Matthias; Lewan, Elisabet; Moriondo, Marco; Nendel, Claas; Priesack, Eckart; Raynal, Helene; Roggero, Pier P.; Rötter, Reimund P.; Siebert, Stefan; Specka, Xenia; Tao, Fulu; Teixeira, Edmar; Trombi, Giacomo; Wallach, Daniel; Weihermüller, Lutz; Yeluripati, Jagadeesh; Ewert, Frank

2016-01-01

We show the error in water-limited yields simulated by crop models which is associated with spatially aggregated soil and climate input data. Crop simulations at large scales (regional, national, continental) frequently use input data of low resolution. Therefore, climate and soil data are often generated via averaging and sampling by area majority. This may bias simulated yields at large scales, varying largely across models. Thus, we evaluated the error associated with spatially aggregated soil and climate data for 14 crop models. Yields of winter wheat and silage maize were simulated under water-limited production conditions. We calculated this error from crop yields simulated at spatial resolutions from 1 to 100 km for the state of North Rhine-Westphalia, Germany. Most models showed yields biased by <15% when aggregating only soil data. The relative mean absolute error (rMAE) of most models using aggregated soil data was in the range or larger than the inter-annual or inter-model variability in yields. This error increased further when both climate and soil data were aggregated. Distinct error patterns indicate that the rMAE may be estimated from few soil variables. Illustrating the range of these aggregation effects across models, this study is a first step towards an ex-ante assessment of aggregation errors in large-scale simulations. PMID:27055028

Impact of Spatial Soil and Climate Input Data Aggregation on Regional Yield Simulations.

PubMed

Hoffmann, Holger; Zhao, Gang; Asseng, Senthold; Bindi, Marco; Biernath, Christian; Constantin, Julie; Coucheney, Elsa; Dechow, Rene; Doro, Luca; Eckersten, Henrik; Gaiser, Thomas; Grosz, Balázs; Heinlein, Florian; Kassie, Belay T; Kersebaum, Kurt-Christian; Klein, Christian; Kuhnert, Matthias; Lewan, Elisabet; Moriondo, Marco; Nendel, Claas; Priesack, Eckart; Raynal, Helene; Roggero, Pier P; Rötter, Reimund P; Siebert, Stefan; Specka, Xenia; Tao, Fulu; Teixeira, Edmar; Trombi, Giacomo; Wallach, Daniel; Weihermüller, Lutz; Yeluripati, Jagadeesh; Ewert, Frank

2016-01-01

We show the error in water-limited yields simulated by crop models which is associated with spatially aggregated soil and climate input data. Crop simulations at large scales (regional, national, continental) frequently use input data of low resolution. Therefore, climate and soil data are often generated via averaging and sampling by area majority. This may bias simulated yields at large scales, varying largely across models. Thus, we evaluated the error associated with spatially aggregated soil and climate data for 14 crop models. Yields of winter wheat and silage maize were simulated under water-limited production conditions. We calculated this error from crop yields simulated at spatial resolutions from 1 to 100 km for the state of North Rhine-Westphalia, Germany. Most models showed yields biased by <15% when aggregating only soil data. The relative mean absolute error (rMAE) of most models using aggregated soil data was in the range or larger than the inter-annual or inter-model variability in yields. This error increased further when both climate and soil data were aggregated. Distinct error patterns indicate that the rMAE may be estimated from few soil variables. Illustrating the range of these aggregation effects across models, this study is a first step towards an ex-ante assessment of aggregation errors in large-scale simulations.

Atmospheric icing of structures: Observations and simulations

NASA Astrophysics Data System (ADS)

Ágústsson, H.; Elíasson, Á. J.; Thorsteins, E.; Rögnvaldsson, Ó.; Ólafsson, H.

2012-04-01

This study compares observed icing in a test span in complex orography at Hallormsstaðaháls (575 m) in East-Iceland with parameterized icing based on an icing model and dynamically downscaled weather at high horizontal resolution. Four icing events have been selected from an extensive dataset of observed atmospheric icing in Iceland. A total of 86 test-spans have been erected since 1972 at 56 locations in complex terrain with more than 1000 icing events documented. The events used here have peak observed ice load between 4 and 36 kg/m. Most of the ice accretion is in-cloud icing but it may partly be mixed with freezing drizzle and wet snow icing. The calculation of atmospheric icing is made in two steps. First the atmospheric data is created by dynamically downscaling the ECMWF-analysis to high resolution using the non-hydrostatic mesoscale Advanced Research WRF-model. The horizontal resolution of 9, 3, 1 and 0.33 km is necessary to allow the atmospheric model to reproduce correctly local weather in the complex terrain of Iceland. Secondly, the Makkonen-model is used to calculate the ice accretion rate on the conductors based on the simulated temperature, wind, cloud and precipitation variables from the atmospheric data. In general, the atmospheric model correctly simulates the atmospheric variables and icing calculations based on the atmospheric variables correctly identify the observed icing events, but underestimate the load due to too slow ice accretion. This is most obvious when the temperature is slightly below 0°C and the observed icing is most intense. The model results improve significantly when additional observations of weather from an upstream weather station are used to nudge the atmospheric model. However, the large variability in the simulated atmospheric variables results in high temporal and spatial variability in the calculated ice accretion. Furthermore, there is high sensitivity of the icing model to the droplet size and the possibility that some of the icing may be due to freezing drizzle or wet snow instead of in-cloud icing of super-cooled droplets. In addition, the icing model (Makkonen) may not be accurate for the highest icing loads observed.

Multi-platform validation of a high-resolution model in the Western Mediterranean Sea: insight into spatial-temporal variability

NASA Astrophysics Data System (ADS)

Aguiar, Eva; Mourre, Baptiste; Heslop, Emma; Juza, Mélanie; Escudier, Romain; Tintoré, Joaquín

2017-04-01

This study focuses on the validation of the high resolution Western Mediterranean Operational model (WMOP) developed at SOCIB, the Balearic Islands Coastal Observing and Forecasting System. The Mediterranean Sea is often seen as a small scale ocean laboratory where energetic eddies, fronts and circulation features have important ecological consequences. The Medclic project is a program between "La Caixa" Foundation and SOCIB which aims at characterizing and forecasting the "oceanic weather" in the Western Mediterranean Sea, specifically investigating the interactions between the general circulation and mesoscale processes. We use a WMOP 2009-2015 free run hindcast simulation and available observational datasets (altimetry, moorings and gliders) to both assess the numerical simulation and investigate the ocean variability. WMOP has a 2-km spatial resolution and uses CMEMS Mediterranean products as initial and boundary conditions, with surface forcing from the high-resolution Spanish Meteorological Agency model HIRLAM. Different aspects of the spatial and temporal variability in the model are validated from local to regional and basin scales: (1) the principal axis of variability of the surface circulation using altimetry and moorings along the Iberian coast, (2) the inter-annual changes of the surface flows incorporating also glider data, (3) the propagation of mesoscale eddies formed in the Algerian sub-basin using altimetry, and (4) the statistical properties of eddies (number, rotation, size) applying an eddy tracker detection method in the Western Mediterranean Sea. With these key points evaluated in the model, EOF analysis of sea surface height maps are used to investigate spatial patterns of variability associated with eddies, gyres and the basis-scale circulation and so gain insight into the interconnections between sub-basins, as well as the interactions between physical processes at different scales.

Virtual mission stage I: Implications of a spaceborne surface water mission

NASA Astrophysics Data System (ADS)

Clark, E. A.; Alsdorf, D. E.; Bates, P.; Wilson, M. D.; Lettenmaier, D. P.

2004-12-01

The interannual and interseasonal variability of the land surface water cycle depend on the distribution of surface water in lakes, wetlands, reservoirs, and river systems; however, measurements of hydrologic variables are sparsely distributed, even in industrialized nations. Moreover, the spatial extent and storage variations of lakes, reservoirs, and wetlands are poorly known. We are developing a virtual mission to demonstrate the feasibility of observing surface water extent and variations from a spaceborne platform. In the first stage of the virtual mission, on which we report here, surface water area and fluxes are emulated using simulation modeling over three continental scale river basins, including the Ohio River, the Amazon River and an Arctic river. The Variable Infiltration Capacity (VIC) macroscale hydrologic model is used to simulate evapotranspiration, soil moisture, snow accumulation and ablation, and runoff and streamflow over each basin at one-eighth degree resolution. The runoff from this model is routed using a linear transfer model to provide input to a much more detailed flow hydraulics model. The flow hydraulics model then routes runoff through various channel and floodplain morphologies at a 250 m spatial and 20 second temporal resolution over a 100 km by 500 km domain. This information is used to evaluate trade-offs between spatial and temporal resolutions of a hypothetical high resolution spaceborne altimeter by synthetically sampling the resultant model-predicted water surface elevations.

Design, development, and application of LANDIS-II, a spatial landscape simulation model with flexible temporal and spatial resolution

Treesearch

Robert M. Scheller; James B. Domingo; Brian R. Sturtevant; Jeremy S. Williams; Arnold Rudy; Eric J. Gustafson; David J. Mladenoff

2007-01-01

We introduce LANDIS-II, a landscape model designed to simulate forest succession and disturbances. LANDIS-II builds upon and preserves the functionality of previous LANDIS forest landscape simulation models. LANDIS-II is distinguished by the inclusion of variable time steps for different ecological processes; our use of a rigorous development and testing process used...

Bayesian Techniques for Comparing Time-dependent GRMHD Simulations to Variable Event Horizon Telescope Observations

NASA Astrophysics Data System (ADS)

Kim, Junhan; Marrone, Daniel P.; Chan, Chi-Kwan; Medeiros, Lia; Özel, Feryal; Psaltis, Dimitrios

2016-12-01

The Event Horizon Telescope (EHT) is a millimeter-wavelength, very-long-baseline interferometry (VLBI) experiment that is capable of observing black holes with horizon-scale resolution. Early observations have revealed variable horizon-scale emission in the Galactic Center black hole, Sagittarius A* (Sgr A*). Comparing such observations to time-dependent general relativistic magnetohydrodynamic (GRMHD) simulations requires statistical tools that explicitly consider the variability in both the data and the models. We develop here a Bayesian method to compare time-resolved simulation images to variable VLBI data, in order to infer model parameters and perform model comparisons. We use mock EHT data based on GRMHD simulations to explore the robustness of this Bayesian method and contrast it to approaches that do not consider the effects of variability. We find that time-independent models lead to offset values of the inferred parameters with artificially reduced uncertainties. Moreover, neglecting the variability in the data and the models often leads to erroneous model selections. We finally apply our method to the early EHT data on Sgr A*.

BAYESIAN TECHNIQUES FOR COMPARING TIME-DEPENDENT GRMHD SIMULATIONS TO VARIABLE EVENT HORIZON TELESCOPE OBSERVATIONS

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

Kim, Junhan; Marrone, Daniel P.; Chan, Chi-Kwan

2016-12-01

The Event Horizon Telescope (EHT) is a millimeter-wavelength, very-long-baseline interferometry (VLBI) experiment that is capable of observing black holes with horizon-scale resolution. Early observations have revealed variable horizon-scale emission in the Galactic Center black hole, Sagittarius A* (Sgr A*). Comparing such observations to time-dependent general relativistic magnetohydrodynamic (GRMHD) simulations requires statistical tools that explicitly consider the variability in both the data and the models. We develop here a Bayesian method to compare time-resolved simulation images to variable VLBI data, in order to infer model parameters and perform model comparisons. We use mock EHT data based on GRMHD simulations to explore themore » robustness of this Bayesian method and contrast it to approaches that do not consider the effects of variability. We find that time-independent models lead to offset values of the inferred parameters with artificially reduced uncertainties. Moreover, neglecting the variability in the data and the models often leads to erroneous model selections. We finally apply our method to the early EHT data on Sgr A*.« less

Regional Climate Simulation with a Variable Resolution Stretched Grid GCM: The Regional Down-Scaling Effects

NASA Technical Reports Server (NTRS)

Fox-Rabinovitz, Michael S.; Takacs, Lawrence L.; Suarez, Max; Sawyer, William; Govindaraju, Ravi C.

1999-01-01

The results obtained with the variable resolution stretched grid (SG) GEOS GCM (Goddard Earth Observing System General Circulation Models) are discussed, with the emphasis on the regional down-scaling effects and their dependence on the stretched grid design and parameters. A variable resolution SG-GCM and SG-DAS using a global stretched grid with fine resolution over an area of interest, is a viable new approach to REGIONAL and subregional CLIMATE studies and applications. The stretched grid approach is an ideal tool for representing regional to global scale interactions. It is an alternative to the widely used nested grid approach introduced a decade ago as a pioneering step in regional climate modeling. The GEOS SG-GCM is used for simulations of the anomalous U.S. climate events of 1988 drought and 1993 flood, with enhanced regional resolution. The height low level jet, precipitation and other diagnostic patterns are successfully simulated and show the efficient down-scaling over the area of interest the U.S. An imitation of the nested grid approach is performed using the developed SG-DAS (Data Assimilation System) that incorporates the SG-GCM. The SG-DAS is run with withholding data over the area of interest. The design immitates the nested grid framework with boundary conditions provided from analyses. No boundary condition buffer is needed for the case due to the global domain of integration used for the SG-GCM and SG-DAS. The experiments based on the newly developed versions of the GEOS SG-GCM and SG-DAS, with finer 0.5 degree (and higher) regional resolution, are briefly discussed. The major aspects of parallelization of the SG-GCM code are outlined. The KEY OBJECTIVES of the study are: 1) obtaining an efficient DOWN-SCALING over the area of interest with fine and very fine resolution; 2) providing CONSISTENT interactions between regional and global scales including the consistent representation of regional ENERGY and WATER BALANCES; 3) providing a high computational efficiency for future SG-GCM and SG-DAS versions using PARALLEL codes.

Analysis of the long-term surface wind variability over complex terrain using a high spatial resolution WRF simulation

NASA Astrophysics Data System (ADS)

Jiménez, Pedro A.; González-Rouco, J. Fidel; Montávez, Juan P.; García-Bustamante, E.; Navarro, J.; Dudhia, J.

2013-04-01

This work uses a WRF numerical simulation from 1960 to 2005 performed at a high horizontal resolution (2 km) to analyze the surface wind variability over a complex terrain region located in northern Iberia. A shorter slice of this simulation has been used in a previous study to demonstrate the ability of the WRF model in reproducing the observed wind variability during the period 1992-2005. Learning from that validation exercise, the extended simulation is herein used to inspect the wind behavior where and when observations are not available and to determine the main synoptic mechanisms responsible for the surface wind variability. A principal component analysis was applied to the daily mean wind. Two principal modes of variation accumulate a large percentage of the wind variability (83.7%). The first mode reflects the channeling of the flow between the large mountain systems in northern Iberia modulated by the smaller topographic features of the region. The second mode further contributes to stress the differentiated wind behavior over the mountains and valleys. Both modes show significant contributions at the higher frequencies during the whole analyzed period, with different contributions at lower frequencies during the different decades. A strong relationship was found between these two modes and the zonal and meridional large scale pressure gradients over the area. This relationship is described in the context of the influence of standard circulation modes relevant in the European region like the North Atlantic Oscillation, the East Atlantic pattern, East Atlantic/Western Russia pattern, and the Scandinavian pattern.

Retrieval of Precipitation Profiles from Multiresolution, Multifrequency, Active and Passive Microwave Observations

NASA Technical Reports Server (NTRS)

Grecu, Mircea; Anagnostou, Emmanouil N.; Olson, William S.; Starr, David OC. (Technical Monitor)

2002-01-01

In this study, a technique for estimating vertical profiles of precipitation from multifrequency, multiresolution active and passive microwave observations is investigated using both simulated and airborne data. The technique is applicable to the Tropical Rainfall Measuring Mission (TRMM) satellite multi-frequency active and passive observations. These observations are characterized by various spatial and sampling resolutions. This makes the retrieval problem mathematically more difficult and ill-determined because the quality of information decreases with decreasing resolution. A model that, given reflectivity profiles and a small set of parameters (including the cloud water content, the intercept drop size distribution, and a variable describing the frozen hydrometeor properties), simulates high-resolution brightness temperatures is used. The high-resolution simulated brightness temperatures are convolved at the real sensor resolution. An optimal estimation procedure is used to minimize the differences between simulated and observed brightness temperatures. The retrieval technique is investigated using cloud model synthetic and airborne data from the Fourth Convection And Moisture Experiment. Simulated high-resolution brightness temperatures and reflectivities and airborne observation strong are convolved at the resolution of the TRMM instruments and retrievals are performed and analyzed relative to the reference data used in observations synthesis. An illustration of the possible use of the technique in satellite rainfall estimation is presented through an application to TRMM data. The study suggests improvements in combined active and passive retrievals even when the instruments resolutions are significantly different. Future work needs to better quantify the retrievals performance, especially in connection with satellite applications, and the uncertainty of the models used in retrieval.

Simulation of population-based commuter exposure to NO₂ using different air pollution models.

PubMed

Ragettli, Martina S; Tsai, Ming-Yi; Braun-Fahrländer, Charlotte; de Nazelle, Audrey; Schindler, Christian; Ineichen, Alex; Ducret-Stich, Regina E; Perez, Laura; Probst-Hensch, Nicole; Künzli, Nino; Phuleria, Harish C

2014-05-12

We simulated commuter routes and long-term exposure to traffic-related air pollution during commute in a representative population sample in Basel (Switzerland), and evaluated three air pollution models with different spatial resolution for estimating commute exposures to nitrogen dioxide (NO2) as a marker of long-term exposure to traffic-related air pollution. Our approach includes spatially and temporally resolved data on actual commuter routes, travel modes and three air pollution models. Annual mean NO2 commuter exposures were similar between models. However, we found more within-city and within-subject variability in annual mean (±SD) NO2 commuter exposure with a high resolution dispersion model (40 ± 7 µg m(-3), range: 21-61) than with a dispersion model with a lower resolution (39 ± 5 µg m(-3); range: 24-51), and a land use regression model (41 ± 5 µg m(-3); range: 24-54). Highest median cumulative exposures were calculated along motorized transport and bicycle routes, and the lowest for walking. For estimating commuter exposure within a city and being interested also in small-scale variability between roads, a model with a high resolution is recommended. For larger scale epidemiological health assessment studies, models with a coarser spatial resolution are likely sufficient, especially when study areas include suburban and rural areas.

Towards multi-resolution global climate modeling with ECHAM6-FESOM. Part II: climate variability

NASA Astrophysics Data System (ADS)

Rackow, T.; Goessling, H. F.; Jung, T.; Sidorenko, D.; Semmler, T.; Barbi, D.; Handorf, D.

2018-04-01

This study forms part II of two papers describing ECHAM6-FESOM, a newly established global climate model with a unique multi-resolution sea ice-ocean component. While part I deals with the model description and the mean climate state, here we examine the internal climate variability of the model under constant present-day (1990) conditions. We (1) assess the internal variations in the model in terms of objective variability performance indices, (2) analyze variations in global mean surface temperature and put them in context to variations in the observed record, with particular emphasis on the recent warming slowdown, (3) analyze and validate the most common atmospheric and oceanic variability patterns, (4) diagnose the potential predictability of various climate indices, and (5) put the multi-resolution approach to the test by comparing two setups that differ only in oceanic resolution in the equatorial belt, where one ocean mesh keeps the coarse 1° resolution applied in the adjacent open-ocean regions and the other mesh is gradually refined to 0.25°. Objective variability performance indices show that, in the considered setups, ECHAM6-FESOM performs overall favourably compared to five well-established climate models. Internal variations of the global mean surface temperature in the model are consistent with observed fluctuations and suggest that the recent warming slowdown can be explained as a once-in-one-hundred-years event caused by internal climate variability; periods of strong cooling in the model (`hiatus' analogs) are mainly associated with ENSO-related variability and to a lesser degree also to PDO shifts, with the AMO playing a minor role. Common atmospheric and oceanic variability patterns are simulated largely consistent with their real counterparts. Typical deficits also found in other models at similar resolutions remain, in particular too weak non-seasonal variability of SSTs over large parts of the ocean and episodic periods of almost absent deep-water formation in the Labrador Sea, resulting in overestimated North Atlantic SST variability. Concerning the influence of locally (isotropically) increased resolution, the ENSO pattern and index statistics improve significantly with higher resolution around the equator, illustrating the potential of the novel unstructured-mesh method for global climate modeling.

Mesoscale Circulation Variability from Five years of Quasi-continuous Glider Observations and Numerical Simulation at a Key Sub-basin 'Choke' Point.

NASA Astrophysics Data System (ADS)

Heslop, E. E.; Mourre, B.; Juza, M.; Troupin, C.; Escudier, R.; Torner, M.; Tintore, J.

2016-02-01

Quasi-continuous glider observations over 5 years have uniquely characterised a high frequency variability in the circulation through the Ibiza Channel, an important `choke' point in the Western Mediterranean Sea. This `choke' point governs the basin/sub-basin scale circulation and the north/south exchanges of different water masses. The resulting multi-scale variability impacts the regional shelf and open ocean ecosystems, including the spawning grounds of Atlantic bluefin tuna. Through the unique glider record we show the relevance of the weekly/mesoscale variability, which is of same order as the previously established seasonal and inter-annual variability. To understand the drivers of this variability we combine the glider data with numerical simulations (WMOP) and altimetry. Two key drivers are identified; extreme winter events, which cause the formation of a cold winter mode water (Winter Intermediate Water) in the shelf areas to the north of the Ibiza Channel, and mesoscale activity, which to the north produce channel `blocking' eddies and to the south intermittent and vigorous flows of fresher `Atlantic' waters through the Ibiza Channel. Results from the 2 km resolution WMOP are compared with the high-resolution (2 - 3 km.) glider data, giving insight into model validation across different scales, for both circulation and water masses. There is an emerging consensus that gliders can uniquely access critical time and length scales and in this study gliders complement existing satellite measurements and models, while opening up new capabilities for multidisciplinary, autonomous and high-resolution ocean observation.

PBSM3D: A finite volume, scalar-transport blowing snow model for use with variable resolution meshes

NASA Astrophysics Data System (ADS)

Marsh, C.; Wayand, N. E.; Pomeroy, J. W.; Wheater, H. S.; Spiteri, R. J.

2017-12-01

Blowing snow redistribution results in heterogeneous snowcovers that are ubiquitous in cold, windswept environments. Capturing this spatial and temporal variability is important for melt and runoff simulations. Point scale blowing snow transport models are difficult to apply in fully distributed hydrological models due to landscape heterogeneity and complex wind fields. Many existing distributed snow transport models have empirical wind flow and/or simplified wind direction algorithms that perform poorly in calculating snow redistribution where there are divergent wind flows, sharp topography, and over large spatial extents. Herein, a steady-state scalar transport model is discretized using the finite volume method (FVM), using parameterizations from the Prairie Blowing Snow Model (PBSM). PBSM has been applied in hydrological response units and grids to prairie, arctic, glacier, and alpine terrain and shows a good capability to represent snow redistribution over complex terrain. The FVM discretization takes advantage of the variable resolution mesh in the Canadian Hydrological Model (CHM) to ensure efficient calculations over small and large spatial extents. Variable resolution unstructured meshes preserve surface heterogeneity but result in fewer computational elements versus high-resolution structured (raster) grids. Snowpack, soil moisture, and streamflow observations were used to evaluate CHM-modelled outputs in a sub-arctic and an alpine basin. Newly developed remotely sensed snowcover indices allowed for validation over large basins. CHM simulations of snow hydrology were improved by inclusion of the blowing snow model. The results demonstrate the key role of snow transport processes in creating pre-melt snowcover heterogeneity and therefore governing post-melt soil moisture and runoff generation dynamics.

Real-world hydrologic assessment of a fully-distributed hydrological model in a parallel computing environment

NASA Astrophysics Data System (ADS)

Vivoni, Enrique R.; Mascaro, Giuseppe; Mniszewski, Susan; Fasel, Patricia; Springer, Everett P.; Ivanov, Valeriy Y.; Bras, Rafael L.

2011-10-01

SummaryA major challenge in the use of fully-distributed hydrologic models has been the lack of computational capabilities for high-resolution, long-term simulations in large river basins. In this study, we present the parallel model implementation and real-world hydrologic assessment of the Triangulated Irregular Network (TIN)-based Real-time Integrated Basin Simulator (tRIBS). Our parallelization approach is based on the decomposition of a complex watershed using the channel network as a directed graph. The resulting sub-basin partitioning divides effort among processors and handles hydrologic exchanges across boundaries. Through numerical experiments in a set of nested basins, we quantify parallel performance relative to serial runs for a range of processors, simulation complexities and lengths, and sub-basin partitioning methods, while accounting for inter-run variability on a parallel computing system. In contrast to serial simulations, the parallel model speed-up depends on the variability of hydrologic processes. Load balancing significantly improves parallel speed-up with proportionally faster runs as simulation complexity (domain resolution and channel network extent) increases. The best strategy for large river basins is to combine a balanced partitioning with an extended channel network, with potential savings through a lower TIN resolution. Based on these advances, a wider range of applications for fully-distributed hydrologic models are now possible. This is illustrated through a set of ensemble forecasts that account for precipitation uncertainty derived from a statistical downscaling model.

The Impact of Varying the Physics Grid Resolution Relative to the Dynamical Core Resolution in CAM-SE-CSLAM

NASA Astrophysics Data System (ADS)

Herrington, A. R.; Lauritzen, P. H.; Reed, K. A.

2017-12-01

The spectral element dynamical core of the Community Atmosphere Model (CAM) has recently been coupled to an approximately isotropic, finite-volume grid per implementation of the conservative semi-Lagrangian multi-tracer transport scheme (CAM-SE-CSLAM; Lauritzen et al. 2017). In this framework, the semi-Lagrangian transport of tracers are computed on the finite-volume grid, while the adiabatic dynamics are solved using the spectral element grid. The physical parameterizations are evaluated on the finite-volume grid, as opposed to the unevenly spaced Gauss-Lobatto-Legendre nodes of the spectral element grid. Computing the physics on the finite-volume grid reduces numerical artifacts such as grid imprinting, possibly because the forcing terms are no longer computed at element boundaries where the resolved dynamics are least smooth. The separation of the physics grid and the dynamics grid allows for a unique opportunity to understand the resolution sensitivity in CAM-SE-CSLAM. The observed large sensitivity of CAM to horizontal resolution is a poorly understood impediment to improved simulations of regional climate using global, variable resolution grids. Here, a series of idealized moist simulations are presented in which the finite-volume grid resolution is varied relative to the spectral element grid resolution in CAM-SE-CSLAM. The simulations are carried out at multiple spectral element grid resolutions, in part to provide a companion set of simulations, in which the spectral element grid resolution is varied relative to the finite-volume grid resolution, but more generally to understand if the sensitivity to the finite-volume grid resolution is consistent across a wider spectrum of resolved scales. Results are interpreted in the context of prior ideas regarding resolution sensitivity of global atmospheric models.

Improving sea level simulation in Mediterranean regional climate models

NASA Astrophysics Data System (ADS)

Adloff, Fanny; Jordà, Gabriel; Somot, Samuel; Sevault, Florence; Arsouze, Thomas; Meyssignac, Benoit; Li, Laurent; Planton, Serge

2017-08-01

For now, the question about future sea level change in the Mediterranean remains a challenge. Previous climate modelling attempts to estimate future sea level change in the Mediterranean did not meet a consensus. The low resolution of CMIP-type models prevents an accurate representation of important small scales processes acting over the Mediterranean region. For this reason among others, the use of high resolution regional ocean modelling has been recommended in literature to address the question of ongoing and future Mediterranean sea level change in response to climate change or greenhouse gases emissions. Also, it has been shown that east Atlantic sea level variability is the dominant driver of the Mediterranean variability at interannual and interdecadal scales. However, up to now, long-term regional simulations of the Mediterranean Sea do not integrate the full sea level information from the Atlantic, which is a substantial shortcoming when analysing Mediterranean sea level response. In the present study we analyse different approaches followed by state-of-the-art regional climate models to simulate Mediterranean sea level variability. Additionally we present a new simulation which incorporates improved information of Atlantic sea level forcing at the lateral boundary. We evaluate the skills of the different simulations in the frame of long-term hindcast simulations spanning from 1980 to 2012 analysing sea level variability from seasonal to multidecadal scales. Results from the new simulation show a substantial improvement in the modelled Mediterranean sea level signal. This confirms that Mediterranean mean sea level is strongly influenced by the Atlantic conditions, and thus suggests that the quality of the information in the lateral boundary conditions (LBCs) is crucial for the good modelling of Mediterranean sea level. We also found that the regional differences inside the basin, that are induced by circulation changes, are model-dependent and thus not affected by the LBCs. Finally, we argue that a correct configuration of LBCs in the Atlantic should be used for future Mediterranean simulations, which cover hindcast period, but also for scenarios.

Characteristics of the ocean simulations in the Max Planck Institute Ocean Model (MPIOM) the ocean component of the MPI-Earth system model

NASA Astrophysics Data System (ADS)

Jungclaus, J. H.; Fischer, N.; Haak, H.; Lohmann, K.; Marotzke, J.; Matei, D.; Mikolajewicz, U.; Notz, D.; von Storch, J. S.

2013-06-01

MPI-ESM is a new version of the global Earth system model developed at the Max Planck Institute for Meteorology. This paper describes the ocean state and circulation as well as basic aspects of variability in simulations contributing to the fifth phase of the Coupled Model Intercomparison Project (CMIP5). The performance of the ocean/sea-ice model MPIOM, coupled to a new version of the atmosphere model ECHAM6 and modules for land surface and ocean biogeochemistry, is assessed for two model versions with different grid resolution in the ocean. The low-resolution configuration has a nominal resolution of 1.5°, whereas the higher resolution version features a quasiuniform, eddy-permitting global resolution of 0.4°. The paper focuses on important oceanic features, such as surface temperature and salinity, water mass distribution, large-scale circulation, and heat and freshwater transports. In general, these integral quantities are simulated well in comparison with observational estimates, and improvements in comparison with the predecessor system are documented; for example, for tropical variability and sea ice representation. Introducing an eddy-permitting grid configuration in the ocean leads to improvements, in particular, in the representation of interior water mass properties in the Atlantic and in the representation of important ocean currents, such as the Agulhas and Equatorial current systems. In general, however, there are more similarities than differences between the two grid configurations, and several shortcomings, known from earlier versions of the coupled model, prevail.

Impact of Variable SST on Simulated Warm Season Precipitation

NASA Astrophysics Data System (ADS)

Saleeby, S. M.; Cotton, W. R.

2007-05-01

The Colorado State University - Regional Atmospheric Modeling System (CSU-RAMS) is being used to examine the variability in monsoon-related warm season precipitation over Mexico and the United States due to variability in SST. Given recent improvements and increased resolution in satellite derived SSTs it is pertinent to examine the sensitivity of the RAMS model to the variety of SST data sources that are available. In particular, we are examining this dependence across continental scales over the full warm season, as well as across the regional scale centered around the Gulf of California on time scales of individual surge events. In this study we performed an ensemble of simulations that include the 2002, 2003, and 2004 warm seasons with use of the Climatology, Reynold's, AVHRR, and MODIS SSTs. From the seasonal 90-day simulations with 30km grid spacing, it was found that variations in surface latent heat flux are directly linked to differences in SST. Regions with cooler (warmer) SST have decreased (increased) moisture flux from the ocean which is in proportion to the magnitude of the SST difference. Over the eastern Pacific, differences in low-level horizontal moisture flux show a general trend toward reduced fluxes over cooler waters and very little inland impact. Over the Gulf of Mexico, however, there is substantial variability for each dataset comparison, despite having only limited variability among the SST data. Causes of this unexpected variability are not straight-forward. Precipitation impacts are greatest near the southern coast of Mexico and along the Sierra Madres. Precipitation variability over the CONUS is rather chaotic and is limited to areas impacted by the Gulf of Mexico or monsoon convection. Another unexpected outcome is the lack of variability in areas near the northern Gulf of California where SST and latent heat flux variability is a maximum. From the 7-day surge period simulations at 7km grid spacing, we found that SST differences on the higher resolution nested grid reveal fine scale variability that is otherwise smoothed out or unapparent on the coarser grid. Unlike the coarse grid, the latent heat flux, temperature, and moisture transport differences on the fine grid reveal an inland impact. This is likely due to fine scale variability in onshore moisture transport and sea- breeze circulations which may alter monsoonal convection and precipitation. However, only the largest SST differences (spatially and in magnitude) tend to invoke large, coherent responses in moisture flux. The SST variability at high resolution produces relatively large differences in precipitation that are focused along the slopes of the SMO, with a tendency toward greater variability along the western slope adjacent to the coast. The precipitation differences are of fine resolution, with variability of +/- 30 mm (over 5 days) along the length of the SMO. Variability on the fine grid also invokes precipitation changes over AZ/NM that are not resolved on the coarse grid. Vertical cross-sections examined along the GoC during the surge episode revealed variations in the moisture and temperature structure of the surge. The cooler SSTs in the climatological dataset produced the greatest variability compared to the other datasets. The surge produced from climatology SSTs was nearly 5g/kg drier and up to 4°C cooler compared to surges influenced by the SST datasets. The overall northward propagation of the surge appeared unaffected by the SSTs.

Efficient Approaches for Propagating Hydrologic Forcing Uncertainty: High-Resolution Applications Over the Western United States

NASA Astrophysics Data System (ADS)

Hobbs, J.; Turmon, M.; David, C. H.; Reager, J. T., II; Famiglietti, J. S.

2017-12-01

NASA's Western States Water Mission (WSWM) combines remote sensing of the terrestrial water cycle with hydrological models to provide high-resolution state estimates for multiple variables. The effort includes both land surface and river routing models that are subject to several sources of uncertainty, including errors in the model forcing and model structural uncertainty. Computational and storage constraints prohibit extensive ensemble simulations, so this work outlines efficient but flexible approaches for estimating and reporting uncertainty. Calibrated by remote sensing and in situ data where available, we illustrate the application of these techniques in producing state estimates with associated uncertainties at kilometer-scale resolution for key variables such as soil moisture, groundwater, and streamflow.

Design of a variable-line-spacing grating pattern for spectrometers based on a grating Fresnel device.

PubMed

Li, Xinghui; Zhang, Jinchao; Zhou, Qian; Ni, Kai; Pang, Jinchao; Tian, Rui

2016-04-01

In this Letter, we propose a variable-line-spacing (VLS) grating pattern for a hybrid diffractive device termed a grating Fresnel (G-Fresnel) lens, which is used in spectrometers to improve spectral resolution over a wide spectral range. The VLS grating pattern disperses light of specific wavelengths with a different angle and position such that the aberration caused by the Fresnel surface can be compensated for. In this manner, high resolution can be achieved over a relatively wide spectral range. The VLS grating pattern is designed based on the least wave-change principle and simulated by ZEMAX. Results reveal that the VLS G-Fresnel device allows a subnanometer resolution over a spectral range of 200 nm.

Estimating urban ground-level PM10 using MODIS 3km AOD product and meteorological parameters from WRF model

NASA Astrophysics Data System (ADS)

Ghotbi, Saba; Sotoudeheian, Saeed; Arhami, Mohammad

2016-09-01

Satellite remote sensing products of AOD from MODIS along with appropriate meteorological parameters were used to develop statistical models and estimate ground-level PM10. Most of previous studies obtained meteorological data from synoptic weather stations, with rather sparse spatial distribution, and used it along with 10 km AOD product to develop statistical models, applicable for PM variations in regional scale (resolution of ≥10 km). In the current study, meteorological parameters were simulated with 3 km resolution using WRF model and used along with the rather new 3 km AOD product (launched in 2014). The resulting PM statistical models were assessed for a polluted and largely variable urban area, Tehran, Iran. Despite the critical particulate pollution problem, very few PM studies were conducted in this area. The issue of rather poor direct PM-AOD associations existed, due to different factors such as variations in particles optical properties, in addition to bright background issue for satellite data, as the studied area located in the semi-arid areas of Middle East. Statistical approach of linear mixed effect (LME) was used, and three types of statistical models including single variable LME model (using AOD as independent variable) and multiple variables LME model by using meteorological data from two sources, WRF model and synoptic stations, were examined. Meteorological simulations were performed using a multiscale approach and creating an appropriate physic for the studied region, and the results showed rather good agreements with recordings of the synoptic stations. The single variable LME model was able to explain about 61%-73% of daily PM10 variations, reflecting a rather acceptable performance. Statistical models performance improved through using multivariable LME and incorporating meteorological data as auxiliary variables, particularly by using fine resolution outputs from WRF (R2 = 0.73-0.81). In addition, rather fine resolution for PM estimates was mapped for the studied city, and resulting concentration maps were consistent with PM recordings at the existing stations.

Hydrologic Implications of Dynamical and Statistical Approaches to Downscaling Climate Model Outputs

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

Wood, Andrew W; Leung, Lai R; Sridhar, V

Six approaches for downscaling climate model outputs for use in hydrologic simulation were evaluated, with particular emphasis on each method's ability to produce precipitation and other variables used to drive a macroscale hydrology model applied at much higher spatial resolution than the climate model. Comparisons were made on the basis of a twenty-year retrospective (1975–1995) climate simulation produced by the NCAR-DOE Parallel Climate Model (PCM), and the implications of the comparison for a future (2040–2060) PCM climate scenario were also explored. The six approaches were made up of three relatively simple statistical downscaling methods – linear interpolation (LI), spatial disaggregationmore » (SD), and bias-correction and spatial disaggregation (BCSD) – each applied to both PCM output directly (at T42 spatial resolution), and after dynamical downscaling via a Regional Climate Model (RCM – at ½-degree spatial resolution), for downscaling the climate model outputs to the 1/8-degree spatial resolution of the hydrological model. For the retrospective climate simulation, results were compared to an observed gridded climatology of temperature and precipitation, and gridded hydrologic variables resulting from forcing the hydrologic model with observations. The most significant findings are that the BCSD method was successful in reproducing the main features of the observed hydrometeorology from the retrospective climate simulation, when applied to both PCM and RCM outputs. Linear interpolation produced better results using RCM output than PCM output, but both methods (PCM-LI and RCM-LI) lead to unacceptably biased hydrologic simulations. Spatial disaggregation of the PCM output produced results similar to those achieved with the RCM interpolated output; nonetheless, neither PCM nor RCM output was useful for hydrologic simulation purposes without a bias-correction step. For the future climate scenario, only the BCSD-method (using PCM or RCM) was able to produce hydrologically plausible results. With the BCSD method, the RCM-derived hydrology was more sensitive to climate change than the PCM-derived hydrology.« less

Evaluation of fine soil moisture data from the IFloodS (NASA GPM) Ground Validation campaign using a fully-distributed ecohydrological model

NASA Astrophysics Data System (ADS)

Bastola, S.; Dialynas, Y. G.; Arnone, E.; Bras, R. L.

2014-12-01

The spatial variability of soil, vegetation, topography, and precipitation controls hydrological processes, consequently resulting in high spatio-temporal variability of most of the hydrological variables, such as soil moisture. Limitation in existing measuring system to characterize this spatial variability, and its importance in various application have resulted in a need of reconciling spatially distributed soil moisture evolution model and corresponding measurements. Fully distributed ecohydrological model simulates soil moisture at high resolution soil moisture. This is relevant for range of environmental studies e.g., flood forecasting. They can also be used to evaluate the value of space born soil moisture data, by assimilating them into hydrological models. In this study, fine resolution soil moisture data simulated by a physically-based distributed hydrological model, tRIBS-VEGGIE, is compared with soil moisture data collected during the field campaign in Turkey river basin, Iowa. The soil moisture series at the 2 and 4 inch depth exhibited a more rapid response to rainfall as compared to bottom 8 and 20 inch ones. The spatial variability in two distinct land surfaces of Turkey River, IA, reflects the control of vegetation, topography and soil texture in the characterization of spatial variability. The comparison of observed and simulated soil moisture at various depth showed that model was able to capture the dynamics of soil moisture at a number of gauging stations. Discrepancies are large in some of the gauging stations, which are characterized by rugged terrain and represented, in the model, through large computational units.

How does mesoscale impact deep convection? Answers from ensemble Northwestern Mediterranean Sea simulations.

NASA Astrophysics Data System (ADS)

Waldman, Robin; Herrmann, Marine; Somot, Samuel; Arsouze, Thomas; Benshila, Rachid; Bosse, Anthony; Chanut, Jérôme; Giordani, Hervé; Pennel, Romain; Sevault, Florence; Testor, Pierre

2017-04-01

Ocean deep convection is a major process of interaction between surface and deep ocean. The Gulf of Lions is a well-documented deep convection area in the Mediterranean Sea, and mesoscale dynamics is a known factor impacting this phenomenon. However, previous modelling studies don't allow to address the robustness of its impact with respect to the physical configuration and ocean intrinsic variability. In this study, the impact of mesoscale on ocean deep convection in the Gulf of Lions is investigated using a multi-resolution ensemble simulation of the northwestern Mediterranean sea. The eddy-permitting Mediterranean model NEMOMED12 (6km resolution) is compared to its eddy-resolving counterpart with the 2-way grid refinement AGRIF in the northwestern Mediterranean (2km resolution). We focus on the well-documented 2012-2013 period and on the multidecadal timescale (1979-2013). The impact of mesoscale on deep convection is addressed in terms of its mean and variability, its impact on deep water transformations and on associated dynamical structures. Results are interpreted by diagnosing regional mean and eddy circulation and using buoyancy budgets. We find a mean inhibition of deep convection by mesoscale with large interannual variability. It is associated with a large impact on mean and transient circulation and a large air-sea flux feedback.

Long-term hydrometeorological trends in the Midwest region based on a century long gridded hydrometeorological dataset and simulations from a macro-scale hydrology model

NASA Astrophysics Data System (ADS)

Chiu, C. M.; Hamlet, A. F.

2014-12-01

Climate change is likely to impact the Great Lakes region and Midwest region via changes in Great Lakes water levels, agricultural impacts, river flooding, urban stormwater impacts, drought, water temperature, and impacts to terrestrial and aquatic ecosystems. Self-consistent and temporally homogeneous long-term data sets of precipitation and temperature over the entire Great Lakes region and Midwest regions are needed to provide inputs to hydrologic models, assess historical trends in hydroclimatic variables, and downscale global and regional-scale climate models. To support these needs a new hybrid gridded meteorological forcing dataset at 1/16 degree resolution based on data from co-op station records, the U. S Historical Climatology Network (HCN) , the Historical Canadian Climate Database (HCCD), and Precipitation Regression on Independent Slopes Method (PRISM) has been assembled over the Great Lakes and Midwest region from 1915-2012 at daily time step. These data were then used as inputs to the macro-scale Variable Infiltration Capacity (VIC) hydrology model, implemented over the Midwest and Great Lakes region at 1/16 degree resolution, to produce simulated hydrologic variables that are amenable to long-term trend analysis. Trends in precipitation and temperature from the new meteorological driving data sets, as well as simulated hydrometeorological variables such as snowpack, soil moisture, runoff, and evaporation over the 20th century are presented and discussed.

Estimation of Atlantic-Mediterranean netflow variability

NASA Astrophysics Data System (ADS)

Guerreiro, Catarina; Peliz, Alvaro; Miranda, Pedro

2016-04-01

The exchanges at the Strait of Gibraltar are extremely difficult to measure due to the strong temporal and across-strait variabilities; yet the Atlantic inflow into the Mediterranean is extremely important both for climate and to ecosystems. Most of the published numerical modeling studies do not resolve the Strait of Gibraltar realistically. Models that represent the strait at high resolution focus primarily in high frequency dynamics, whereas long-term dynamics are studied in low resolution model studies, and for that reason the Strait dynamics are poorly resolved. Estimating the variability of the exchanges requires long term and high-resolutions studies, thus an improved simulation with explicit and realistic representation of the Strait is necessary. On seasonal to inter-annual timescales the flow is essentially driven by the net evaporation contribution and consequently realistic fields of precipitation and evaporation are necessary for model setup. A comparison between observations, reanalysis and combined products shows ERA-Interim Reanalysis has the most suitable product for Mediterranean Sea. Its time and space variability are in close agreement with NOC 1.1 for the common period (1980 - 1993) and also with evaporation from OAFLUX (1989 - 2014). Subinertial fluctuations, periods from days to a few months, are the second most energetic, after tides, and are the response to atmospheric pressure fluctuations and local winds. Atmospheric pressure fluctuations in the Mediterranean cause sea level oscillations that induce a barotropic flow through the Strait. Candela's analytical model has been used to quantify this response in later studies, though comparison with observations points to an underestimation of the flow at strait. An improved representation of this term contribution to the Atlantic - Mediterranean exchange must be achieved on longer time-scales. We propose a new simulation for the last 36 years (1979 - 2014) for the Mediterranean - Atlantic domain with explicit representation of the Strait. The simulations are performed using the Regional Ocean Modeling System (ROMS) and forced with the different contributions of the freshwater budget, sea level pressure fluctuations and winds from ERA-Interim Reanalysis. The model of sea level pressure induced barotropic fluctuations simulates the barotropic variability at the Strait of Gibraltar for the last decades.

Numerical Simulation of The Mediterranean Sea Using Diecast: Interaction Between Basin, Sub-basin and Local Scale Features and Natural Variability.

NASA Astrophysics Data System (ADS)

Fernández, V.; Dietrich, D. E.; Haney, R. L.; Tintoré, J.

In situ and satellite data obtained during the last ten years have shown that the circula- tion in the Mediterranean Sea is extremely complex in space, with significant features ranging from mesoscale to sub-basin and basin scale, and highly variable in time, with mesoscale to seasonal and interannual signals. Also, the steep bottom topography and the variable atmospheric conditions from one sub-basin to another, make the circula- tion to be composed of numerous energetic and narrow coastal currents, density fronts and mesoscale structures that interact at sub-basin scale with the large scale circula- tion. To simulate numerically and better understand these features, besides high grid resolution, a low numerical dispersion and low physical dissipation ocean model is required. We present the results from a 1/8z horizontal resolution numerical simula- tion of the Mediterranean Sea using DieCAST ocean model, which meets the above requirements since it is stable with low general dissipation and uses accurate fourth- order-accurate approximations with low numerical dispersion. The simulations are carried out with climatological surface forcing using monthly mean winds and relax- ation towards climatological values of temperature and salinity. The model reproduces the main features of the large basin scale circulation, as well as the seasonal variabil- ity of sub-basin scale currents that are well documented by observations in straits and channels. In addition, DieCAST brings out natural fronts and eddies that usually do not appear in numerical simulations of the Mediterranean and that lead to a natural interannual variability. The role of this intrinsic variability in the general circulation will be discussed.

Speeding up N-body simulations of modified gravity: chameleon screening models

NASA Astrophysics Data System (ADS)

Bose, Sownak; Li, Baojiu; Barreira, Alexandre; He, Jian-hua; Hellwing, Wojciech A.; Koyama, Kazuya; Llinares, Claudio; Zhao, Gong-Bo

2017-02-01

We describe and demonstrate the potential of a new and very efficient method for simulating certain classes of modified gravity theories, such as the widely studied f(R) gravity models. High resolution simulations for such models are currently very slow due to the highly nonlinear partial differential equation that needs to be solved exactly to predict the modified gravitational force. This nonlinearity is partly inherent, but is also exacerbated by the specific numerical algorithm used, which employs a variable redefinition to prevent numerical instabilities. The standard Newton-Gauss-Seidel iterative method used to tackle this problem has a poor convergence rate. Our new method not only avoids this, but also allows the discretised equation to be written in a form that is analytically solvable. We show that this new method greatly improves the performance and efficiency of f(R) simulations. For example, a test simulation with 5123 particles in a box of size 512 Mpc/h is now 5 times faster than before, while a Millennium-resolution simulation for f(R) gravity is estimated to be more than 20 times faster than with the old method. Our new implementation will be particularly useful for running very high resolution, large-sized simulations which, to date, are only possible for the standard model, and also makes it feasible to run large numbers of lower resolution simulations for covariance analyses. We hope that the method will bring us to a new era for precision cosmological tests of gravity.

Detection and Attribution of Regional Climate Change

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

Bala, G; Mirin, A

2007-01-19

We developed a high resolution global coupled modeling capability to perform breakthrough studies of the regional climate change. The atmospheric component in our simulation uses a 1{sup o} latitude x 1.25{sup o} longitude grid which is the finest resolution ever used for the NCAR coupled climate model CCSM3. Substantial testing and slight retuning was required to get an acceptable control simulation. The major accomplishment is the validation of this new high resolution configuration of CCSM3. There are major improvements in our simulation of the surface wind stress and sea ice thickness distribution in the Arctic. Surface wind stress and oceanmore » circulation in the Antarctic Circumpolar Current are also improved. Our results demonstrate that the FV version of the CCSM coupled model is a state of the art climate model whose simulation capabilities are in the class of those used for IPCC assessments. We have also provided 1000 years of model data to Scripps Institution of Oceanography to estimate the natural variability of stream flow in California. In the future, our global model simulations will provide boundary data to high-resolution mesoscale model that will be used at LLNL. The mesoscale model would dynamically downscale the GCM climate to regional scale on climate time scales.« less

Sobol' sensitivity analysis for stressor impacts on honeybee ...

EPA Pesticide Factsheets

We employ Monte Carlo simulation and nonlinear sensitivity analysis techniques to describe the dynamics of a bee exposure model, VarroaPop. Daily simulations are performed of hive population trajectories, taking into account queen strength, foraging success, mite impacts, weather, colony resources, population structure, and other important variables. This allows us to test the effects of defined pesticide exposure scenarios versus controlled simulations that lack pesticide exposure. The daily resolution of the model also allows us to conditionally identify sensitivity metrics. We use the variancebased global decomposition sensitivity analysis method, Sobol’, to assess firstand secondorder parameter sensitivities within VarroaPop, allowing us to determine how variance in the output is attributed to each of the input variables across different exposure scenarios. Simulations with VarroaPop indicate queen strength, forager life span and pesticide toxicity parameters are consistent, critical inputs for colony dynamics. Further analysis also reveals that the relative importance of these parameters fluctuates throughout the simulation period according to the status of other inputs. Our preliminary results show that model variability is conditional and can be attributed to different parameters depending on different timescales. By using sensitivity analysis to assess model output and variability, calibrations of simulation models can be better informed to yield more

Impact of Urbanization on Spatial Variability of Rainfall-A case study of Mumbai city with WRF Model

NASA Astrophysics Data System (ADS)

Mathew, M.; Paul, S.; Devanand, A.; Ghosh, S.

2015-12-01

Urban precipitation enhancement has been identified over many cities in India by previous studies conducted. Anthropogenic effects such as change in land cover from hilly forest areas to flat topography with solid concrete infrastructures has certain effect on the local weather, the same way the greenhouse gas has on climate change. Urbanization could alter the large scale forcings to such an extent that it may bring about temporal and spatial changes in the urban weather. The present study investigate the physical processes involved in urban forcings, such as the effect of sudden increase in wind velocity travelling through the channel space in between the dense array of buildings, which give rise to turbulence and air mass instability in urban boundary layer and in return alters the rainfall distribution as well as rainfall initiation. A numerical model study is conducted over Mumbai metropolitan city which lies on the west coast of India, to assess the effect of urban morphology on the increase in number of extreme rainfall events in specific locations. An attempt has been made to simulate twenty extreme rainfall events that occurred over the summer monsoon period of the year 2014 using high resolution WRF-ARW (Weather Research and Forecasting-Advanced Research WRF) model to assess the urban land cover mechanisms that influences precipitation variability over this spatially varying urbanized region. The result is tested against simulations with altered land use. The correlation of precipitation with spatial variability of land use is found using a detailed urban land use classification. The initial and boundary conditions for running the model were obtained from the global model ECMWF(European Centre for Medium Range Weather Forecast) reanalysis data having a horizontal resolution of 0.75 °x 0.75°. The high resolution simulations show significant spatial variability in the accumulated rainfall, within a few kilometers itself. Understanding the spatial variability of precipitation will help in the planning and management of the built environment more efficiently.

Orographic precipitation at global and regional scales: Observational uncertainty and evaluation of 25-km global model simulations

NASA Astrophysics Data System (ADS)

Schiemann, Reinhard; Roberts, Charles J.; Bush, Stephanie; Demory, Marie-Estelle; Strachan, Jane; Vidale, Pier Luigi; Mizielinski, Matthew S.; Roberts, Malcolm J.

2015-04-01

Precipitation over land exhibits a high degree of variability due to the complex interaction of the precipitation generating atmospheric processes with coastlines, the heterogeneous land surface, and orography. Global general circulation models (GCMs) have traditionally had very limited ability to capture this variability on the mesoscale (here ~50-500 km) due to their low resolution. This has changed with recent investments in resolution and ensembles of multidecadal climate simulations of atmospheric GCMs (AGCMs) with ~25 km grid spacing are becoming increasingly available. Here, we evaluate the mesoscale precipitation distribution in one such set of simulations obtained in the UPSCALE (UK on PrACE - weather-resolving Simulations of Climate for globAL Environmental risk) modelling campaign with the HadGEM-GA3 AGCM. Increased model resolution also poses new challenges to the observational datasets used to evaluate models. Global gridded data products such as those provided by the Global Precipitation Climatology Project (GPCP) are invaluable for assessing large-scale features of the precipitation distribution but may not sufficiently resolve mesoscale structures. In the absence of independent estimates, the intercomparison of different observational datasets may be the only way to get some insight into the uncertainties associated with these observations. Here, we focus on mid-latitude continental regions where observations based on higher-density gauge networks are available in addition to the global data sets: Europe/the Alps, South and East Asia, and the continental US. The ability of GCMs to represent mesoscale variability is of interest in its own right, as climate information on this scale is required by impact studies. An additional motivation for the research proposed here arises from continuing efforts to quantify the components of the global radiation budget and water cycle. Recent estimates based on radiation measurements suggest that the global mean precipitation/evaporation may be up to 10 Wm-2 (about 0.35 mm day-1) larger than the estimate obtained from GPCP. While the main part of this discrepancy is thought to be due to the underestimation of remotely-sensed ocean precipitation, there is also considerable uncertainty about 'unobserved' precipitation over land, in particular in the form of snow in regions of high latitude/altitude. We aim to contribute to this discussion, at least at a qualitative level, by considering case studies of how area-averaged mountain precipitation is represented in different observational datasets and by HadGEM3-GA3 at different resolutions. Our results show that the AGCM simulates considerably more orographic precipitation at higher resolution. We find this at the global scale both for the winter and summer hemispheres, as well as in several case studies in mid-latitude regions. Gridded observations based on gauge measurements generally capture the mesoscale spatial variability of precipitation, but differ strongly from one another in the magnitude of area-averaged precipitation, so that they are of very limited use for evaluating this aspect of the modelled climate. We are currently conducting a sensitivity experiment (coarse-grained orography in high-resolution HadGEM3) to further investigate the resolution sensitivity seen in the model.

Simulation of Population-Based Commuter Exposure to NO2 Using Different Air Pollution Models

PubMed Central

Ragettli, Martina S.; Tsai, Ming-Yi; Braun-Fahrländer, Charlotte; de Nazelle, Audrey; Schindler, Christian; Ineichen, Alex; Ducret-Stich, Regina E.; Perez, Laura; Probst-Hensch, Nicole; Künzli, Nino; Phuleria, Harish C.

2014-01-01

We simulated commuter routes and long-term exposure to traffic-related air pollution during commute in a representative population sample in Basel (Switzerland), and evaluated three air pollution models with different spatial resolution for estimating commute exposures to nitrogen dioxide (NO2) as a marker of long-term exposure to traffic-related air pollution. Our approach includes spatially and temporally resolved data on actual commuter routes, travel modes and three air pollution models. Annual mean NO2 commuter exposures were similar between models. However, we found more within-city and within-subject variability in annual mean (±SD) NO2 commuter exposure with a high resolution dispersion model (40 ± 7 µg m−3, range: 21–61) than with a dispersion model with a lower resolution (39 ± 5 µg m−3; range: 24–51), and a land use regression model (41 ± 5 µg m−3; range: 24–54). Highest median cumulative exposures were calculated along motorized transport and bicycle routes, and the lowest for walking. For estimating commuter exposure within a city and being interested also in small-scale variability between roads, a model with a high resolution is recommended. For larger scale epidemiological health assessment studies, models with a coarser spatial resolution are likely sufficient, especially when study areas include suburban and rural areas. PMID:24823664

Mesosacle eddies in a high resolution OGCM and coupled ocean-atmosphere GCM

NASA Astrophysics Data System (ADS)

Yu, Y.; Liu, H.; Lin, P.

2017-12-01

The present study described high-resolution climate modeling efforts including oceanic, atmospheric and coupled general circulation model (GCM) at the state key laboratory of numerical modeling for atmospheric sciences and geophysical fluid dynamics (LASG), Institute of Atmospheric Physics (IAP). The high-resolution OGCM is established based on the latest version of the LASG/IAP Climate system Ocean Model (LICOM2.1), but its horizontal resolution and vertical resolution are increased to 1/10° and 55 layers, respectively. Forced by the surface fluxes from the reanalysis and observed data, the model has been integrated for approximately more than 80 model years. Compared with the simulation of the coarse-resolution OGCM, the eddy-resolving OGCM not only better simulates the spatial-temporal features of mesoscale eddies and the paths and positions of western boundary currents but also reproduces the large meander of the Kuroshio Current and its interannual variability. Another aspect, namely, the complex structures of equatorial Pacific currents and currents in the coastal ocean of China, are better captured due to the increased horizontal and vertical resolution. Then we coupled the high resolution OGCM to NCAR CAM4 with 25km resolution, in which the mesoscale air-sea interaction processes are better captured.

Sahra integrated modeling approach to address water resources management in semi-arid river basins

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

Springer, E. P.; Gupta, Hoshin V.; Brookshire, David S.

Water resources decisions in the 21Sf Century that will affect allocation of water for economic and environmental will rely on simulations from integrated models of river basins. These models will not only couple natural systems such as surface and ground waters, but will include economic components that can assist in model assessments of river basins and bring the social dimension to the decision process. The National Science Foundation Science and Technology Center for Sustainability of semi-Arid Hydrology and Riparian Areas (SAHRA) has been developing integrated models to assess impacts of climate variability and land use change on water resources inmore » semi-arid river basins. The objectives of this paper are to describe the SAHRA integrated modeling approach and to describe the linkage between social and natural sciences in these models. Water resources issues that arise from climate variability or land use change may require different resolution models to answer different questions. For example, a question related to streamflow may not need a high-resolution model whereas a question concerning the source and nature of a pollutant will. SAHRA has taken a multiresolution approach to integrated model development because one cannot anticipate the questions in advance, and the computational and data resources may not always be available or needed for the issue to be addressed. The coarsest resolution model is based on dynamic simulation of subwatersheds or river reaches. This model resolution has the advantage of simplicity and social factors are readily incorporated. Users can readily take this model (and they have) and examine the effects of various management strategies such as increased cost of water. The medium resolution model is grid based and uses variable grid cells of 1-12 km. The surface hydrology is more physically based using basic equations for energy and water balance terms, and modules are being incorporated that will simulate engineering components such as reservoirs or irrigation diversions and economic features such as variable demand. The fine resolution model is viewed as a tool to examine basin response using best available process models. The fine resolution model operates on a grid cell size of 100 m or less, which is consistent with the scale that our process knowledge has developed. The fine resolution model couples atmosphere, surface water and groundwater modules using high performance computing. The medium and fine resolution models are not expected at this time to be operated by users as opposed to the coarse resolution model. One of the objectives of the SAHRA integrated modeling task is to present results in a manner that can be used by those making decisions. The application of these models within SAHRA is driven by a scenario analysis and a place location. The place is the Rio Grande from its headwaters in Colorado to the New Mexico-Texas border. This provides a focus for model development and an attempt to see how the results from the various models relate. The scenario selected by SAHRA is the impact of a 1950's style drought using 1990's population and land use on Rio Grande water resources including surface and groundwater. The same climate variables will be used to drive all three models so that comparison will be based on how the three resolutions partition and route water through the river basin. Aspects of this scenario will be discussed and initial model simulation will be presented. The issue of linking economic modules into the modeling effort will be discussed and the importance of feedback from the social and economic modules to the natural science modules will be reviewed.« less

Constraining regional scale carbon budgets at the US West Coast using a high-resolution atmospheric inverse modeling approach

NASA Astrophysics Data System (ADS)

Goeckede, M.; Michalak, A. M.; Vickers, D.; Turner, D.; Law, B.

2009-04-01

The study presented is embedded within the NACP (North American Carbon Program) West Coast project ORCA2, which aims at determining the regional carbon balance of the US states Oregon, California and Washington. Our work specifically focuses on the effect of disturbance history and climate variability, aiming at improving our understanding of e.g. drought stress and stand age on carbon sources and sinks in complex terrain with fine-scale variability in land cover types. The ORCA2 atmospheric inverse modeling approach has been set up to capture flux variability on the regional scale at high temporal and spatial resolution. Atmospheric transport is simulated coupling the mesoscale model WRF (Weather Research and Forecast) with the STILT (Stochastic Time Inverted Lagrangian Transport) footprint model. This setup allows identifying sources and sinks that influence atmospheric observations with highly resolved mass transport fields and realistic turbulent mixing. Terrestrial biosphere carbon fluxes are simulated at spatial resolutions of up to 1km and subdaily timesteps, considering effects of ecoregion, land cover type and disturbance regime on the carbon budgets. Our approach assimilates high-precision atmospheric CO2 concentration measurements and eddy-covariance data from several sites throughout the model domain, as well as high-resolution remote sensing products (e.g. LandSat, MODIS) and interpolated surface meteorology (DayMet, SOGS, PRISM). We present top-down modeling results that have been optimized using Bayesian inversion, reflecting the information on regional scale carbon processes provided by the network of high-precision CO2 observations. We address the level of detail (e.g. spatial and temporal resolution) that can be resolved by top-down modeling on the regional scale, given the uncertainties introduced by various sources for model-data mismatch. Our results demonstrate the importance of accurate modeling of carbon-water coupling, with the representation of water availability and drought stress playing a dominant role to capture spatially variable CO2 exchange rates in a region characterized by strong climatic gradients.

Use of the quasi-geostrophic dynamical framework to reconstruct the 3-D ocean state in a high-resolution realistic simulation of North Atlantic.

NASA Astrophysics Data System (ADS)

Fresnay, Simon; Ponte, Aurélien

2017-04-01

The quasi-geostrophic (QG) framework has been, is and will be still for years to come a cornerstone method linking observations with estimates of the ocean circulation and state. We have used here the QG framework to reconstruct dynamical variables of the 3-D ocean in a state-of-the-art high-resolution (1/60 deg, 300 vertical levels) numerical simulation of the North Atlantic (NATL60). The work was carried out in 3 boxes of the simulation: Gulf Stream, Azores and Reykjaness Ridge. In a first part, general diagnostics describing the eddying dynamics have been performed and show that the QG scaling verifies in general, at depths distant from mixed layer and bathymetric gradients. Correlations with surface observables variables (e.g. temperature, sea level) were computed and estimates of quasi-geostrophic potential vorticity (QGPV) were reconstructed by the means of regression laws. It is shown that that reconstruction of QGPV exhibits valuable skill for a restricted scale range, mainly using sea level as the variable of regression. Additional discussion is given, based on the flow balanced with QGPV. This work is part of the DIMUP project, aiming to improve our ability to operationnaly estimate the ocean state.

Characterisation and comparison of event generators for pair conversion: A crucial step for future low energy gamma telescope

NASA Astrophysics Data System (ADS)

Gros, P.; Bernard, D.

2017-05-01

Gamma ray astronomy suffers from a sensitivity gap between 0.1 and 100Mev. With high angular resolution for the electrons, it will also be possible to probe the linear polarisation of the photons. An accurate simulation is necessary to correctly design and compare these detectors. We establish baseline distributions of key kinematic variables as simulated by a 5D, exact down to threshold, and polarised event generator. We compare them to simulations with the low energy electromagnetic models available in Geant4 and in EGS5. We show that different generators give a different picture of the optimal angular resolution of pair telescopes. We also show that, of all the simulations we used, only the full 5D generator describes accurately the angular asymmetry in the case of polarised photons.

Wavefront sensor-driven variable-geometry pupil for ground-based aperture synthesis imaging

NASA Astrophysics Data System (ADS)

Tyler, David W.

2000-07-01

I describe a variable-geometry pupil (VGP) to increase image resolution for ground-based near-IR and optical imaging. In this scheme, a curvature-type wavefront sensor provides an estimate of the wavefront curvature to the controller of a high-resolution spatial light modulator (SLM) or micro- electromechanical (MEM) mirror, positioned at an image of the telescope pupil. This optical element, the VGP, passes or reflects the incident beam only where the wavefront phase is sufficiently smooth, viz., where the curvature is sufficiently low. Using a computer simulation, I show the VGP can sharpen and smooth the long-exposure PSF and increase the OTF SNR for tilt-only and low-order AO systems, allowing higher resolution and more stable deconvolution with dimmer AO guidestars.

Searching for the right scale in catchment hydrology: the effect of soil spatial variability in simulated states and fluxes

NASA Astrophysics Data System (ADS)

Baroni, Gabriele; Zink, Matthias; Kumar, Rohini; Samaniego, Luis; Attinger, Sabine

2017-04-01

The advances in computer science and the availability of new detailed data-sets have led to a growing number of distributed hydrological models applied to finer and finer grid resolutions for larger and larger catchment areas. It was argued, however, that this trend does not necessarily guarantee better understanding of the hydrological processes or it is even not necessary for specific modelling applications. In the present study, this topic is further discussed in relation to the soil spatial heterogeneity and its effect on simulated hydrological state and fluxes. To this end, three methods are developed and used for the characterization of the soil heterogeneity at different spatial scales. The methods are applied at the soil map of the upper Neckar catchment (Germany), as example. The different soil realizations are assessed regarding their impact on simulated state and fluxes using the distributed hydrological model mHM. The results are analysed by aggregating the model outputs at different spatial scales based on the Representative Elementary Scale concept (RES) proposed by Refsgaard et al. (2016). The analysis is further extended in the present study by aggregating the model output also at different temporal scales. The results show that small scale soil variabilities are not relevant when the integrated hydrological responses are considered e.g., simulated streamflow or average soil moisture over sub-catchments. On the contrary, these small scale soil variabilities strongly affect locally simulated states and fluxes i.e., soil moisture and evapotranspiration simulated at the grid resolution. A clear trade-off is also detected by aggregating the model output by spatial and temporal scales. Despite the scale at which the soil variabilities are (or are not) relevant is not universal, the RES concept provides a simple and effective framework to quantify the predictive capability of distributed models and to identify the need for further model improvements e.g., finer resolution input. For this reason, the integration in this analysis of all the relevant input factors (e.g., precipitation, vegetation, geology) could provide a strong support for the definition of the right scale for each specific model application. In this context, however, the main challenge for a proper model assessment will be the correct characterization of the spatio- temporal variability of each input factor. Refsgaard, J.C., Højberg, A.L., He, X., Hansen, A.L., Rasmussen, S.H., Stisen, S., 2016. Where are the limits of model predictive capabilities?: Representative Elementary Scale - RES. Hydrol. Process. doi:10.1002/hyp.11029

Using Bayesian variable selection to analyze regular resolution IV two-level fractional factorial designs

DOE PAGES

Chipman, Hugh A.; Hamada, Michael S.

2016-06-02

Regular two-level fractional factorial designs have complete aliasing in which the associated columns of multiple effects are identical. Here, we show how Bayesian variable selection can be used to analyze experiments that use such designs. In addition to sparsity and hierarchy, Bayesian variable selection naturally incorporates heredity . This prior information is used to identify the most likely combinations of active terms. We also demonstrate the method on simulated and real experiments.

Using Bayesian variable selection to analyze regular resolution IV two-level fractional factorial designs

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

Chipman, Hugh A.; Hamada, Michael S.

Regular two-level fractional factorial designs have complete aliasing in which the associated columns of multiple effects are identical. Here, we show how Bayesian variable selection can be used to analyze experiments that use such designs. In addition to sparsity and hierarchy, Bayesian variable selection naturally incorporates heredity . This prior information is used to identify the most likely combinations of active terms. We also demonstrate the method on simulated and real experiments.

An intercomparison of GCM and RCM dynamical downscaling for characterizing the hydroclimatology of California and Nevada

NASA Astrophysics Data System (ADS)

Xu, Z.; Rhoades, A.; Johansen, H.; Ullrich, P. A.; Collins, W. D.

2017-12-01

Dynamical downscaling is widely used to properly characterize regional surface heterogeneities that shape the local hydroclimatology. However, the factors in dynamical downscaling, including the refinement of model horizontal resolution, large-scale forcing datasets and dynamical cores, have not been fully evaluated. Two cutting-edge global-to-regional downscaling methods are used to assess these, specifically the variable-resolution Community Earth System Model (VR-CESM) and the Weather Research & Forecasting (WRF) regional climate model, under different horizontal resolutions (28, 14, and 7 km). Two groups of WRF simulations are driven by either the NCEP reanalysis dataset (WRF_NCEP) or VR-CESM outputs (WRF_VRCESM) to evaluate the effects of the large-scale forcing datasets. The impacts of dynamical core are assessed by comparing the VR-CESM simulations to the coupled WRF_VRCESM simulations with the same physical parameterizations and similar grid domains. The simulated hydroclimatology (i.e., total precipitation, snow cover, snow water equivalent and surface temperature) are compared with the reference datasets. The large-scale forcing datasets are critical to the WRF simulations in more accurately simulating total precipitation, SWE and snow cover, but not surface temperature. Both the WRF and VR-CESM results highlight that no significant benefit is found in the simulated hydroclimatology by just increasing horizontal resolution refinement from 28 to 7 km. Simulated surface temperature is sensitive to the choice of dynamical core. WRF generally simulates higher temperatures than VR-CESM, alleviates the systematic cold bias of DJF temperatures over the California mountain region, but overestimates the JJA temperature in California's Central Valley.

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

Bose, Sownak; Li, Baojiu; He, Jian-hua

We describe and demonstrate the potential of a new and very efficient method for simulating certain classes of modified gravity theories, such as the widely studied f ( R ) gravity models. High resolution simulations for such models are currently very slow due to the highly nonlinear partial differential equation that needs to be solved exactly to predict the modified gravitational force. This nonlinearity is partly inherent, but is also exacerbated by the specific numerical algorithm used, which employs a variable redefinition to prevent numerical instabilities. The standard Newton-Gauss-Seidel iterative method used to tackle this problem has a poor convergencemore » rate. Our new method not only avoids this, but also allows the discretised equation to be written in a form that is analytically solvable. We show that this new method greatly improves the performance and efficiency of f ( R ) simulations. For example, a test simulation with 512{sup 3} particles in a box of size 512 Mpc/ h is now 5 times faster than before, while a Millennium-resolution simulation for f ( R ) gravity is estimated to be more than 20 times faster than with the old method. Our new implementation will be particularly useful for running very high resolution, large-sized simulations which, to date, are only possible for the standard model, and also makes it feasible to run large numbers of lower resolution simulations for covariance analyses. We hope that the method will bring us to a new era for precision cosmological tests of gravity.« less

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

Meehl, G A; Covey, C; McAvaney, B

The Coupled Model Intercomparison Project (CMIP) is designed to allow study and intercomparison of multi-model simulations of present-day and future climate. The latter are represented by idealized forcing of compounded 1% per year CO2 increase to the time of CO2 doubling near year 70 in simulations with global coupled models that contain, typically, components representing atmosphere, ocean, sea ice and land surface. Results from CMIP diagnostic subprojects were presented at the Second CMIP Workshop held at the Max Planck Institute for Meteorology in Hamburg, Germany, in September, 2003. Significant progress in diagnosing and understanding results from global coupled models hasmore » been made since the First CMIP Workshop in Melbourne, Australia in 1998. For example, the issue of flux adjustment is slowly fading as more and more models obtain stable multi-century surface climates without them. El Nino variability, usually about half the observed amplitude in the previous generation of coupled models, is now more accurately simulated in the present generation of global coupled models, though there are still biases in simulating the patterns of maximum variability. Typical resolutions of atmospheric component models contained in coupled models is now usually around 2.5 degrees latitude-longitude, with the ocean components often having about twice the atmospheric model resolution, with even higher resolution in the equatorial tropics. Some new-generation coupled models have atmospheric model resolutions of around 1.5 degrees latitude-longitude. Modeling groups now routinely run the CMIP control and 1% CO2 simulations in addition to 20th and 21st century climate simulations with a variety of forcings (e.g. volcanoes, solar variability, anthropogenic sulfate aerosols, ozone, and greenhouse gases (GHGs), with the anthropogenic forcings for future climate as well). However, persistent systematic errors noted in previous generations of global coupled models still are present in the present generation (e.g. over-extensive equatorial Pacific cold tongue, double ITCZ). This points to the next challenge for the global coupled climate modeling community. Planning and imminent commencement of the IPCC Fourth Assessment Report (AR4) has prompted rapid coupled model development, which will lead to an expanded CMIP-like activity to collect and analyze results for the control, 1% CO2, 20th, 21st and 22nd century simulations performed for the AR4. The international climate community is encouraged to become involved in this analysis effort, and details are provided below in how to do so.« less

A new variable-resolution associative memory for high energy physics

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

Annovi, A.; Amerio, S.; Beretta, M.

2011-07-01

We describe an important advancement for the Associative Memory device (AM). The AM is a VLSI processor for pattern recognition based on Content Addressable Memory (CAM) architecture. The AM is optimized for on-line track finding in high-energy physics experiments. Pattern matching is carried out by finding track candidates in coarse resolution 'roads'. A large AM bank stores all trajectories of interest, called 'patterns', for a given detector resolution. The AM extracts roads compatible with a given event during detector read-out. Two important variables characterize the quality of the AM bank: its 'coverage' and the level of fake roads. The coverage,more » which describes the geometric efficiency of a bank, is defined as the fraction of tracks that match at least one pattern in the bank. Given a certain road size, the coverage of the bank can be increased just adding patterns to the bank, while the number of fakes unfortunately is roughly proportional to the number of patterns in the bank. Moreover, as the luminosity increases, the fake rate increases rapidly because of the increased silicon occupancy. To counter that, we must reduce the width of our roads. If we decrease the road width using the current technology, the system will become very large and extremely expensive. We propose an elegant solution to this problem: the 'variable resolution patterns'. Each pattern and each detector layer within a pattern will be able to use the optimal width, but we will use a 'don't care' feature (inspired from ternary CAMs) to increase the width when that is more appropriate. In other words we can use patterns of variable shape. As a result we reduce the number of fake roads, while keeping the efficiency high and avoiding excessive bank size due to the reduced width. We describe the idea, the implementation in the new AM design and the implementation of the algorithm in the simulation. Finally we show the effectiveness of the 'variable resolution patterns' idea using simulated high occupancy events in the ATLAS detector. (authors)« less

On the use of GPS tomography to investigate water vapor variability during a Mistral/sea breeze event in southeastern France

NASA Astrophysics Data System (ADS)

Bastin, Sophie; Champollion, Cédric; Bock, Olivier; Drobinski, Philippe; Masson, Frédéric

2005-03-01

Global Positioning System (GPS) tomography analyses of water vapor, complemented by high-resolution numerical simulations are used to investigate a Mistral/sea breeze event in the region of Marseille, France, during the ESCOMPTE experiment. This is the first time GPS tomography has been used to validate the three-dimensional water vapor concentration from numerical simulation, and to analyze a small-scale meteorological event. The high spatial and temporal resolution of GPS analyses provides a unique insight into the evolution of the vertical and horizontal distribution of water vapor during the Mistral/sea-breeze transition.

Rainfall variability and extremes over southern Africa: assessment of a climate model to reproduce daily extremes

NASA Astrophysics Data System (ADS)

Williams, C.; Kniveton, D.; Layberry, R.

2009-04-01

It is increasingly accepted that that any possible climate change will not only have an influence on mean climate but may also significantly alter climatic variability. A change in the distribution and magnitude of extreme rainfall events (associated with changing variability), such as droughts or flooding, may have a far greater impact on human and natural systems than a changing mean. This issue is of particular importance for environmentally vulnerable regions such as southern Africa. The subcontinent is considered especially vulnerable to and ill-equipped (in terms of adaptation) for extreme events, due to a number of factors including extensive poverty, famine, disease and political instability. Rainfall variability and the identification of rainfall extremes is a function of scale, so high spatial and temporal resolution data are preferred to identify extreme events and accurately predict future variability. The majority of previous climate model verification studies have compared model output with observational data at monthly timescales. In this research, the assessment of ability of a state of the art climate model to simulate climate at daily timescales is carried out using satellite derived rainfall data from the Microwave Infra-Red Algorithm (MIRA). This dataset covers the period from 1993-2002 and the whole of southern Africa at a spatial resolution of 0.1 degree longitude/latitude. The ability of a climate model to simulate current climate provides some indication of how much confidence can be applied to its future predictions. In this paper, simulations of current climate from the UK Meteorological Office Hadley Centre's climate model, in both regional and global mode, are firstly compared to the MIRA dataset at daily timescales. This concentrates primarily on the ability of the model to simulate the spatial and temporal patterns of rainfall variability over southern Africa. Secondly, the ability of the model to reproduce daily rainfall extremes will be assessed, again by a comparison with extremes from the MIRA dataset.

Dynamically downscaled climate simulations over North America: Methods, evaluation, and supporting documentation for users

USGS Publications Warehouse

Hostetler, S.W.; Alder, J.R.; Allan, A.M.

2011-01-01

We have completed an array of high-resolution simulations of present and future climate over Western North America (WNA) and Eastern North America (ENA) by dynamically downscaling global climate simulations using a regional climate model, RegCM3. The simulations are intended to provide long time series of internally consistent surface and atmospheric variables for use in climate-related research. In addition to providing high-resolution weather and climate data for the past, present, and future, we have developed an integrated data flow and methodology for processing, summarizing, viewing, and delivering the climate datasets to a wide range of potential users. Our simulations were run over 50- and 15-kilometer model grids in an attempt to capture more of the climatic detail associated with processes such as topographic forcing than can be captured by general circulation models (GCMs). The simulations were run using output from four GCMs. All simulations span the present (for example, 1968-1999), common periods of the future (2040-2069), and two simulations continuously cover 2010-2099. The trace gas concentrations in our simulations were the same as those of the GCMs: the IPCC 20th century time series for 1968-1999 and the A2 time series for simulations of the future. We demonstrate that RegCM3 is capable of producing present day annual and seasonal climatologies of air temperature and precipitation that are in good agreement with observations. Important features of the high-resolution climatology of temperature, precipitation, snow water equivalent (SWE), and soil moisture are consistently reproduced in all model runs over WNA and ENA. The simulations provide a potential range of future climate change for selected decades and display common patterns of the direction and magnitude of changes. As expected, there are some model to model differences that limit interpretability and give rise to uncertainties. Here, we provide background information about the GCMs and the RegCM3, a basic evaluation of the model output and examples of simulated future climate. We also provide information needed to access the web applications for visualizing and downloading the data, and give complete metadata that describe the variables in the datasets.

Rediscovering the doldrums in high resolution simulations of the tropical Atlantic

NASA Astrophysics Data System (ADS)

Klocke, Daniel; Brueck, Matthias; Stevens, Bjorn

2017-04-01

When sailors started crossing the tropics, they quickly discovered and learned to fear the belt of calm and variable winds around the ITCZ. They named this region the doldrums. The doldrums are such a persistent and dominant part of the general circulation that they were marked and described in the earliest maps and studies concerned with the winds over the oceans. After the invention of steam ships the interest in the doldrums faded and the doldrums mainly lived on in colloquial language as an expression for stagnation, listlessness and depression describing the experience of the sailors rather than the region. The research focus shifted to the ITCZ, which describes more the position of a variable front of strong convergence and maximum precipitation residing in the doldrums. GCMs continue to correctly simulate the position of the ITCZ, which is partly determined by small scale processes which are parameterized. In support of the NARVAL measurement campaign, convection permitting simulations were conducted for a winter and a summer months covering the tropical Atlantic (9000x3300 km) with the Icosahedral Nonhydrostatic Model (ICON). These simulations reveal the doldrums with their embedded convective structures including cold pools, convective storms and squall lines. The calms and the high variability of the wind direction between the trades connected to convective activity in the ITCZ is presented using the high resolution simulations and are compared to historical and current observations. Comparisons with current NWP models using parameterized convection show that parameterized models struggle to reproduce some of the essential features connected to the doldrums.

Enhancing SMAP Soil Moisture Retrievals via Superresolution Techniques

NASA Astrophysics Data System (ADS)

Beale, K. D.; Ebtehaj, A. M.; Romberg, J. K.; Bras, R. L.

2017-12-01

Soil moisture is a key state variable that modulates land-atmosphere interactions and its high-resolution global scale estimates are essential for improved weather forecasting, drought prediction, crop management, and the safety of troop mobility. Currently, NASA's Soil Moisture Active/Passive (SMAP) satellite provides a global picture of soil moisture variability at a resolution of 36 km, which is prohibitive for some hydrologic applications. The goal of this research is to enhance the resolution of SMAP passive microwave retrievals by a factor of 2 to 4 using modern superresolution techniques that rely on the knowledge of high-resolution land surface models. In this work, we explore several super-resolution techniques including an empirical dictionary method, a learned dictionary method, and a three-layer convolutional neural network. Using a year of global high-resolution land surface model simulations as training set, we found that we are able to produce high-resolution soil moisture maps that outperform the original low-resolution observations both qualitatively and quantitatively. In particular, on a patch-by-patch basis we are able to produce estimates of high-resolution soil moisture maps that improve on the original low-resolution patches by on average 6% in terms of mean-squared error, and 14% in terms of the structural similarity index.

Tropical Cyclone Activity in the High-Resolution Community Earth System Model and the Impact of Ocean Coupling

NASA Astrophysics Data System (ADS)

Li, Hui; Sriver, Ryan L.

2018-01-01

High-resolution Atmosphere General Circulation Models (AGCMs) are capable of directly simulating realistic tropical cyclone (TC) statistics, providing a promising approach for TC-climate studies. Active air-sea coupling in a coupled model framework is essential to capturing TC-ocean interactions, which can influence TC-climate connections on interannual to decadal time scales. Here we investigate how the choices of ocean coupling can affect the directly simulated TCs using high-resolution configurations of the Community Earth System Model (CESM). We performed a suite of high-resolution, multidecadal, global-scale CESM simulations in which the atmosphere (˜0.25° grid spacing) is configured with three different levels of ocean coupling: prescribed climatological sea surface temperature (SST) (ATM), mixed layer ocean (SLAB), and dynamic ocean (CPL). We find that different levels of ocean coupling can influence simulated TC frequency, geographical distributions, and storm intensity. ATM simulates more storms and higher overall storm intensity than the coupled simulations. It also simulates higher TC track density over the eastern Pacific and the North Atlantic, while TC tracks are relatively sparse within CPL and SLAB for these regions. Storm intensification and the maximum wind speed are sensitive to the representations of local surface flux feedbacks in different coupling configurations. Key differences in storm number and distribution can be attributed to variations in the modeled large-scale climate mean state and variability that arise from the combined effect of intrinsic model biases and air-sea interactions. Results help to improve our understanding about the representation of TCs in high-resolution coupled Earth system models, with important implications for TC-climate applications.

Spatial Heterodyne Observations of Water (SHOW) vapour in the upper troposphere and lower stratosphere from a high altitude aircraft: Modelling and sensitivity analysis

NASA Astrophysics Data System (ADS)

Langille, J. A.; Letros, D.; Zawada, D.; Bourassa, A.; Degenstein, D.; Solheim, B.

2018-04-01

A spatial heterodyne spectrometer (SHS) has been developed to measure the vertical distribution of water vapour in the upper troposphere and the lower stratosphere with a high vertical resolution (∼500 m). The Spatial Heterodyne Observations of Water (SHOW) instrument combines an imaging system with a monolithic field-widened SHS to observe limb scattered sunlight in a vibrational band of water (1363 nm-1366 nm). The instrument has been optimized for observations from NASA's ER-2 aircraft as a proof-of-concept for a future low earth orbit satellite deployment. A robust model has been developed to simulate SHOW ER-2 limb measurements and retrievals. This paper presents the simulation of the SHOW ER-2 limb measurements along a hypothetical flight track and examines the sensitivity of the measurement and retrieval approach. Water vapour fields from an Environment and Climate Change Canada forecast model are used to represent realistic spatial variability along the flight path. High spectral resolution limb scattered radiances are simulated using the SASKTRAN radiative transfer model. It is shown that the SHOW instrument onboard the ER-2 is capable of resolving the water vapour variability in the UTLS from approximately 12 km - 18 km with ±1 ppm accuracy. Vertical resolutions between 500 m and 1 km are feasible. The along track sampling capability of the instrument is also discussed.

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

NASA Astrophysics Data System (ADS)

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.

An evaluation of simulated Thematic Mapper data and Landsat MSS data for discriminating suburban and regional land use and land cover

NASA Technical Reports Server (NTRS)

Toll, D. L.

1984-01-01

An airborne multispectral scanner, operating in the same spectral channels as the Landsat Thematic Mapper (TM), was used in a region east of Denver, CO, for a simulation test performed in the framework of using TM to discriminate the level I and level II classes. It is noted that at the 30-m spatial resolution of the Thematic Mapper Simulator (TMS) the overall discrimination for such classes as commercial/industrial land, rangeland, irrigated sod, irrigated alfalfa, and irrigated pasture was superior to that of the Landsat Multispectral Scanner, primarily due to four added spectral bands. For residential and other spectrally heterogeneous classes, however, the higher resolution of TMS resulted in increased variability within the class and a larger spectral overlap.

Dynamic Downscaling of Seasonal Simulations over South America.

NASA Astrophysics Data System (ADS)

Misra, Vasubandhu; Dirmeyer, Paul A.; Kirtman, Ben P.

2003-01-01

In this paper multiple atmospheric global circulation model (AGCM) integrations at T42 spectral truncation and prescribed sea surface temperature were used to drive regional spectral model (RSM) simulations at 80-km resolution for the austral summer season (January-February-March). Relative to the AGCM, the RSM improves the ensemble mean simulation of precipitation and the lower- and upper-level tropospheric circulation over both tropical and subtropical South America and the neighboring ocean basins. It is also seen that the RSM exacerbates the dry bias over the northern tip of South America and the Nordeste region, and perpetuates the erroneous split intertropical convergence zone (ITCZ) over both the Pacific and Atlantic Ocean basins from the AGCM. The RSM at 80-km horizontal resolution is able to reasonably resolve the Altiplano plateau. This led to an improvement in the mean precipitation over the plateau. The improved resolution orography in the RSM did not substantially change the predictability of the precipitation, surface fluxes, or upper- and lower-level winds in the vicinity of the Andes Mountains from the AGCM. In spite of identical convective and land surface parameterization schemes, the diagnostic quantities, such as precipitation and surface fluxes, show significant differences in the intramodel variability over oceans and certain parts of the Amazon River basin (ARB). However, the prognostic variables of the models exhibit relatively similar model noise structures and magnitude. This suggests that the model physics are in large part responsible for the divergence of the solutions in the two models. However, the surface temperature and fluxes from the land surface scheme of the model [Simplified Simple Biosphere scheme (SSiB)] display comparable intramodel variability, except over certain parts of ARB in the two models. This suggests a certain resilience of predictability in SSiB (over the chosen domain of study) to variations in horizontal resolution. It is seen in this study that the summer precipitation over tropical and subtropical South America is highly unpredictable in both models.

Examining the Impacts of High-Resolution Land Surface Initialization on Model Predictions of Convection in the Southeastern U.S.

NASA Technical Reports Server (NTRS)

Case, Jonathan L.; Kumar, Sujay V.; Santos, Pablo; Medlin, Jeffrey M.; Jedlovec, Gary J.

2009-01-01

One of the most challenging weather forecast problems in the southeastern U.S. is daily summertime pulse convection. During the summer, atmospheric flow and forcing are generally weak in this region; thus, convection typically initiates in response to local forcing along sea/lake breezes, and other discontinuities often related to horizontal gradients in surface heating rates. Numerical simulations of pulse convection usually have low skill, even in local predictions at high resolution, due to the inherent chaotic nature of these precipitation systems. Forecast errors can arise from assumptions within physics parameterizations, model resolution limitations, as well as uncertainties in both the initial state of the atmosphere and land surface variables such as soil moisture and temperature. For this study, it is hypothesized that high-resolution, consistent representations of surface properties such as soil moisture and temperature, ground fluxes, and vegetation are necessary to better simulate the interactions between the land surface and atmosphere, and ultimately improve predictions of local circulations and summertime pulse convection. The NASA Short-term Prediction Research and Transition (SPORT) Center has been conducting studies to examine the impacts of high-resolution land surface initialization data generated by offline simulations of the NASA Land Informatiot System (LIS) on subsequent numerical forecasts using the Weather Research and Forecasting (WRF) model (Case et al. 2008, to appear in the Journal of Hydrometeorology). Case et al. presents improvements to simulated sea breezes and surface verification statistics over Florida by initializing WRF with land surface variables from an offline LIS spin-up run, conducted on the exact WRF domain and resolution. The current project extends the previous work over Florida, focusing on selected case studies of typical pulse convection over the southeastern U.S., with an emphasis on improving local short-term WRF simulations over the Mobile, AL and Miami, FL NWS county warning areas. Future efforts may involve examining the impacts of assimilating remotely-sensed soil moisture data, and/or introducing weekly greenness vegetation fraction composites (as opposed to monthly climatologies) into ol'fline NASA LIS runs. Based on positive impacts, the offline LIS runs could be transitioned into an operational mode, providing land surface initialization data to NWS forecast offices in real time.

Contribution of high resolution remote sensing data to the modeling of the snow cover the in Atlas Mountains

NASA Astrophysics Data System (ADS)

Baba, Wassim; Gascoin, Simon; Hanich, Lahoucine; Kinnard, Christophe

2017-04-01

Snow melt from the Atlas Mountains watersheds represent an important water resource for the semi-arid, cultivated, lowlands. Due to the high incoming solar radiation and low precipitation, the spatial-temporal variability of the snowpack is expected to be strongly influenced by the topography. We explore this hypothesis using a distributed energy balance snow model (SnowModel) in the experimental watershed of the Rheraya River in Morocco (225 km2). The digital elevation model (DEM) in SnowModel is used for the computation of the gridded meteorological forcing from the automatic weather stations data. We acquired three Pléiades stereo pairs in to produce an accurate, high resolution DEM of the Rheraya watershed at 4 m posting. Then, the DEM was resampled to different spatial resolutions (8 m, 30 m, 90 m, 250 m and 500 m) to simulate the snowpack evolution over 2008-2009 snow season. As validation data we used a time series of 15 maps of the snow cover area (SCA) from Formosat-2 imagery over the same snow season in the upper Rheraya watershed. These maps have a resolution of 8 m, which enables to capture small-scale variability in the snow cover. We found that the simulations at 90 m, 30 m and 8 m yield similar results at the catchment scale, with significant differences in areas of very steep topography only. From February to April, an overall good agreement was observed between the simulated SCA and the Formosat-2 SCA at 8 m and 90 m. Before the melting season, true positive (TP) column of confusion matrix is close to 1, but it drops to 0.6 during the melting season. Heidke Skill Score is higher than 0.7 for the most of the validation dates and averages 0.8. On the contrary, 500 m simulation underestimates the SCA throughout the snow season and the TP score is always inferior to the one obtained at 8 m and 90 m. We further analyzed the effect of topography by comparing the distribution of meteorological and snowpack variables along north-south and east-west transects. This analysis indicates that the impact of the topography on the simulated SWE and snow melt is mainly driven by changes in the solar radiations and the precipitations.

Chemistry Simulations Using MERRA-2 Reanalysis with the GMI CTM and Replay in Support of the Atmospheric Composition Community

NASA Technical Reports Server (NTRS)

Oman, Luke D.; Strahan, Susan E.

2016-01-01

Simulations using reanalyzed meteorological conditions have been long used to understand causes of atmospheric composition change over the recent past. Using the new Modern-Era Retrospective analysis for Research and Applications, version 2 (MERRA-2) meteorology, chemistry simulations are being conducted to create products covering 1980-2016 for the atmospheric composition community. These simulations use the Global Modeling Initiative (GMI) chemical mechanism in two different models: the GMI Chemical Transport Model (CTM) and the GEOS-5 model developed Replay mode. Replay mode means an integration of the GEOS-5 general circulation model that is incrementally adjusted each time step toward the MERRA-2 analysis. The GMI CTM is a 1 x 1.25 simulation and the MERRA-2 GMI Replay simulation uses the native MERRA-2 approximately horizontal resolution on the cubed sphere. The Replay simulations is driven by the online use of key MERRA-2 meteorological variables (i.e. U, V, T, and surface pressure) with all other variables calculated in response to those variables. A specialized set of transport diagnostics is included in both runs to better understand trace gas transport and changes over the recent past.

Recent variability of the tropical tropopause inversion layer

NASA Astrophysics Data System (ADS)

Wang, Wuke; Matthes, Katja; Schmidt, Torsten; Neef, Lisa

2013-12-01

The recent variability of the tropopause temperature and the tropopause inversion layer (TIL) are investigated with Global Positioning System Radio Occultation data and simulations with the National Center for Atmospheric Research's Whole Atmosphere Community Climate Model (WACCM). Over the past decade (2001-2011) the data show an increase of 0.8 K in the tropopause temperature and a decrease of 0.4 K in the strength of the tropopause inversion layer in the tropics, meaning that the vertical temperature gradient has declined, and therefore that the stability above the tropopause has weakened. WACCM simulations with finer vertical resolution show a more realistic TIL structure and variability. Model simulations show that the increased tropopause temperature and the weaker tropopause inversion layer are related to weakened upwelling in the tropics. Such changes in the thermal structure of the upper troposphere and lower stratosphere may have important implications for climate, such as a possible rise in water vapor in the lower stratosphere.

Evaluating WRF Simulations of Urban Boundary Layer Processes during DISCOVER-AQ

NASA Astrophysics Data System (ADS)

Hegarty, J. D.; Henderson, J.; Lewis, J. R.; McGrath-Spangler, E. L.; Scarino, A. J.; Ferrare, R. A.; DeCola, P.; Welton, E. J.

2015-12-01

The accurate representation of processes in the planetary boundary layer (PBL) in meteorological models is of prime importance to air quality and greenhouse gas simulations as it governs the depth to which surface emissions are vertically mixed and influences the efficiency by which they are transported downwind. In this work we evaluate high resolution (~1 km) WRF simulations of PBL processes in the Washington DC - Baltimore and Houston urban areas during the respective DISCOVER-AQ 2011 and 2013 field campaigns using MPLNET micro-pulse lidar (MPL), mini-MPL, airborne high spectral resolution lidar (HSRL), Doppler wind profiler and CALIPSO satellite measurements along with complimentary surface and aircraft measurements. We will discuss how well WRF simulates the spatiotemporal variability of the PBL height in the urban areas and the development of fine-scale meteorological features such as bay and sea breezes that influence the air quality of the urban areas studied.

Impact of land cover data on the simulation of urban heat island for Berlin using WRF coupled with bulk approach of Noah-LSM

NASA Astrophysics Data System (ADS)

Li, Huidong; Wolter, Michael; Wang, Xun; Sodoudi, Sahar

2017-09-01

Urban-rural difference of land cover is the key determinant of urban heat island (UHI). In order to evaluate the impact of land cover data on the simulation of UHI, a comparative study between up-to-date CORINE land cover (CLC) and Urban Atlas (UA) with fine resolution (100 and 10 m) and old US Geological Survey (USGS) data with coarse resolution (30 s) was conducted using the Weather Research and Forecasting model (WRF) coupled with bulk approach of Noah-LSM for Berlin. The comparison between old data and new data partly reveals the effect of urbanization on UHI and the historical evolution of UHI, while the comparison between different resolution data reveals the impact of resolution of land cover on the simulation of UHI. Given the high heterogeneity of urban surface and the fine-resolution land cover data, the mosaic approach was implemented in this study to calculate the sub-grid variability in land cover compositions. Results showed that the simulations using UA and CLC data perform better than that using USGS data for both air and land surface temperatures. USGS-based simulation underestimates the temperature, especially in rural areas. The longitudinal variations of both temperature and land surface temperature show good agreement with urban fraction for all the three simulations. To better study the comprehensive characteristic of UHI over Berlin, the UHI curves (UHIC) are developed for all the three simulations based on the relationship between temperature and urban fraction. CLC- and UA-based simulations show smoother UHICs than USGS-based simulation. The simulation with old USGS data obviously underestimates the extent of UHI, while the up-to-date CLC and UA data better reflect the real urbanization and simulate the spatial distribution of UHI more accurately. However, the intensity of UHI simulated by CLC and UA data is not higher than that simulated by USGS data. The simulated air temperature is not dominated by the land cover as much as the land surface temperature, as air temperature is also affected by air advection.

Further influence of the eastern boundary on the seasonal variability of the Atlantic Meridional Overturning Circulation at 26N

NASA Astrophysics Data System (ADS)

Baehr, Johanna; Schmidt, Christian

2016-04-01

The seasonal cycle of the Atlantic Meridional Overturning Circulation (AMOC) at 26.5 N has been shown to arise predominantly from sub-surface density variations at the Eastern boundary. Here, we suggest that these sub-surface density variations have their origin in the seasonal variability of the Canary Current system, in particular the Poleward Undercurrent (PUC). We use a high-resolution ocean model (STORM) for which we show that the seasonal variability resembles observations for both sub-surface density variability and meridional transports. In particular, the STORM model simulation density variations at the eastern boundary show seasonal variations reaching down to well over 1000m, a pattern that most model simulations systematically underestimate. We find that positive wind stress curl anomalies in late summer and already within one degree off the eastern boundary result -through water column stretching- in strong transport anomlies in PUC in fall, coherent down to 1000m depth. Simultaneously with a westward propagation of these transport anomalies, we find in winter a weak PUC between 200 m and 500m, and southward transports between 600m and 1300m. This variability is in agreement with the observationally-based suggestion of a seasonal reversal of the meridional transports at intermediate depths. Our findings extend earlier studies which suggested that the seasonal variability at of the meridional transports across 26N is created by changes in the basin-wide thermocline through wind-driven upwelling at the eastern boundary analyzing wind stress curl anomalies 2 degrees off the eastern boundary. Our results suggest that the investigation of AMOC variability and particular its seasonal cycle modulations require the analysis of boundary wind stress curl and the upper ocean transports within 1 degree off the eastern boundary. These findings also implicate that without high-resolution coverage of the eastern boundary, coarser model simulation might not fully represent the AMOC's seasonal variability.

Global River Water Temperature Modelling at Hyper-Resolution

NASA Astrophysics Data System (ADS)

Wanders, N.; van Vliet, M. T. H.; Wada, Y.; Van Beek, L. P.

2017-12-01

The temperature of river water plays a crucial role in many physical, chemical and biological aquatic processes. The influence of changing water temperatures is not only felt locally, but also has regional and downstream impacts. Sectors that might be affected by sudden or gradual changes in the water temperature are: energy production, industry and recreation. Although it is very important to have detailed information on this environmental variable, high-resolution simulations of water temperature on a large scale are currently lacking. Here we present a novel hyper-resolution water temperature dataset at the global scale. We developed the 1-D energy routing model WARM, to simulate river temperature for the period 1980-2014 at 10 km and 50 km resolution. The WARM model accounts for surface water abstraction, reservoirs, riverine flooding and formation of ice, therefore enabling a realistic representation of the water temperature. The water temperature simulations have been validated against 358 river monitoring stations globally for the period 1980 to 2014. The results indicate the increase in resolution significantly improves the simulation performance with a decrease in the water temperature RMSE from 3.5°C to 3.0°C and an increase in the mean correlation of the daily discharge simulations, from R=0.4 to 0.6. We find an average global increase in water temperature of 0.22°C per decade between 1960-2014, with increasing trends towards the end of the simulations period. Strong increasing trends in maxima in the Northern Hemisphere (0.62°C per decade) and minima in the Southern Hemisphere (0.45°C per decade). Finally, we show the impact of major heatwaves and drought events on the water temperature and water availability. The high resolution not only improves the model performance; it also positively impacts the relevancy of the simulation for local and regional scale studies and impact assessments. This new global water temperature dataset could help to develop decision-support system related to water quality with increasing precision and accuracy.

Prediction of Indian Summer-Monsoon Onset Variability: A Season in Advance.

PubMed

Pradhan, Maheswar; Rao, A Suryachandra; Srivastava, Ankur; Dakate, Ashish; Salunke, Kiran; Shameera, K S

2017-10-27

Monsoon onset is an inherent transient phenomenon of Indian Summer Monsoon and it was never envisaged that this transience can be predicted at long lead times. Though onset is precipitous, its variability exhibits strong teleconnections with large scale forcing such as ENSO and IOD and hence may be predictable. Despite of the tremendous skill achieved by the state-of-the-art models in predicting such large scale processes, the prediction of monsoon onset variability by the models is still limited to just 2-3 weeks in advance. Using an objective definition of onset in a global coupled ocean-atmosphere model, it is shown that the skillful prediction of onset variability is feasible under seasonal prediction framework. The better representations/simulations of not only the large scale processes but also the synoptic and intraseasonal features during the evolution of monsoon onset are the comprehensions behind skillful simulation of monsoon onset variability. The changes observed in convection, tropospheric circulation and moisture availability prior to and after the onset are evidenced in model simulations, which resulted in high hit rate of early/delay in monsoon onset in the high resolution model.

Effects of spatial and temporal resolution on simulated feedbacks from polygonal tundra.

NASA Astrophysics Data System (ADS)

Coon, E.; Atchley, A. L.; Painter, S. L.; Karra, S.; Moulton, J. D.; Wilson, C. J.; Liljedahl, A.

2014-12-01

Earth system land models typically resolve permafrost regions at spatial resolutions grossly larger than the scales of topographic variation. This observation leads to two critical questions: How much error is introduced by this lack of resolution, and what is the effect of this approximation on other coupled components of the Earth system, notably the energy balance and carbon cycle? Here we use the Arctic Terrestrial Simulator (ATS) to run micro-topography resolving simulations of polygonal ground, driven by meteorological data from Barrow, AK, to address these questions. ATS couples surface and subsurface processes, including thermal hydrology, surface energy balance, and a snow model. Comparisons are made between one-dimensional "column model" simulations (similar to, for instance, CLM or other land models typically used in Earth System models) and higher-dimensional simulations which resolve micro-topography, allowing for distributed surface runoff, horizontal flow in the subsurface, and uneven snow distribution. Additionally, we drive models with meteorological data averaged over different time scales from daily to weekly moving windows. In each case, we compare fluxes important to the surface energy balance including albedo, latent and sensible heat fluxes, and land-to-atmosphere long-wave radiation. Results indicate that spatial topography variation and temporal variability are important in several ways. Snow distribution greatly affects the surface energy balance, fundamentally changing the partitioning of incoming solar radiation between the subsurface and the atmosphere. This has significant effects on soil moisture and temperature, with implications for vegetation and decomposition. Resolving temporal variability is especially important in spring, when early warm days can alter the onset of snowmelt by days to weeks. We show that high-resolution simulations are valuable in evaluating current land models, especially in areas of polygonal ground. This work was supported by LANL Laboratory Directed Research and Development Project LDRD201200068DR and by the The Next-Generation Ecosystem Experiments (NGEE Arctic) project. NGEE-Arctic is supported by the Office of Biological and Environmental Research in the DOE Office of Science. LA-UR-14-26227.

Probabilistic Downscaling of Remote Sensing Data with Applications for Multi-Scale Biogeochemical Flux Modeling.

PubMed

Stoy, Paul C; Quaife, Tristan

2015-01-01

Upscaling ecological information to larger scales in space and downscaling remote sensing observations or model simulations to finer scales remain grand challenges in Earth system science. Downscaling often involves inferring subgrid information from coarse-scale data, and such ill-posed problems are classically addressed using regularization. Here, we apply two-dimensional Tikhonov Regularization (2DTR) to simulate subgrid surface patterns for ecological applications. Specifically, we test the ability of 2DTR to simulate the spatial statistics of high-resolution (4 m) remote sensing observations of the normalized difference vegetation index (NDVI) in a tundra landscape. We find that the 2DTR approach as applied here can capture the major mode of spatial variability of the high-resolution information, but not multiple modes of spatial variability, and that the Lagrange multiplier (γ) used to impose the condition of smoothness across space is related to the range of the experimental semivariogram. We used observed and 2DTR-simulated maps of NDVI to estimate landscape-level leaf area index (LAI) and gross primary productivity (GPP). NDVI maps simulated using a γ value that approximates the range of observed NDVI result in a landscape-level GPP estimate that differs by ca 2% from those created using observed NDVI. Following findings that GPP per unit LAI is lower near vegetation patch edges, we simulated vegetation patch edges using multiple approaches and found that simulated GPP declined by up to 12% as a result. 2DTR can generate random landscapes rapidly and can be applied to disaggregate ecological information and compare of spatial observations against simulated landscapes.

Probabilistic Downscaling of Remote Sensing Data with Applications for Multi-Scale Biogeochemical Flux Modeling

PubMed Central

Stoy, Paul C.; Quaife, Tristan

2015-01-01

Upscaling ecological information to larger scales in space and downscaling remote sensing observations or model simulations to finer scales remain grand challenges in Earth system science. Downscaling often involves inferring subgrid information from coarse-scale data, and such ill-posed problems are classically addressed using regularization. Here, we apply two-dimensional Tikhonov Regularization (2DTR) to simulate subgrid surface patterns for ecological applications. Specifically, we test the ability of 2DTR to simulate the spatial statistics of high-resolution (4 m) remote sensing observations of the normalized difference vegetation index (NDVI) in a tundra landscape. We find that the 2DTR approach as applied here can capture the major mode of spatial variability of the high-resolution information, but not multiple modes of spatial variability, and that the Lagrange multiplier (γ) used to impose the condition of smoothness across space is related to the range of the experimental semivariogram. We used observed and 2DTR-simulated maps of NDVI to estimate landscape-level leaf area index (LAI) and gross primary productivity (GPP). NDVI maps simulated using a γ value that approximates the range of observed NDVI result in a landscape-level GPP estimate that differs by ca 2% from those created using observed NDVI. Following findings that GPP per unit LAI is lower near vegetation patch edges, we simulated vegetation patch edges using multiple approaches and found that simulated GPP declined by up to 12% as a result. 2DTR can generate random landscapes rapidly and can be applied to disaggregate ecological information and compare of spatial observations against simulated landscapes. PMID:26067835

Use of dynamical downscaling to improve the simulation of Central U.S. warm season precipitation in CMIP5 models

NASA Astrophysics Data System (ADS)

Harding, Keith J.; Snyder, Peter K.; Liess, Stefan

2013-11-01

supporting exceptionally productive agricultural lands, the Central U.S. is susceptible to severe droughts and floods. Such precipitation extremes are expected to worsen with climate change. However, future projections are highly uncertain as global climate models (GCMs) generally fail to resolve precipitation extremes. In this study, we assess how well models from the Coupled Model Intercomparison Project Phase 5 (CMIP5) simulate summer means, variability, extremes, and the diurnal cycle of Central U.S. summer rainfall. Output from a subset of historical CMIP5 simulations are used to drive the Weather Research and Forecasting model to determine whether dynamical downscaling improves the representation of Central U.S. rainfall. We investigate which boundary conditions influence dynamically downscaled precipitation estimates and identify GCMs that can reasonably simulate precipitation when downscaled. The CMIP5 models simulate the seasonal mean and variability of summer rainfall reasonably well but fail to resolve extremes, the diurnal cycle, and the dynamic forcing of precipitation. Downscaling to 30 km improves these characteristics of precipitation, with the greatest improvement in the representation of extremes. Additionally, sizeable diurnal cycle improvements occur with higher (10 km) resolution and convective parameterization disabled, as the daily rainfall peak shifts 4 h closer to observations than 30 km resolution simulations. This lends greater confidence that the mechanisms responsible for producing rainfall are better simulated. Because dynamical downscaling can more accurately simulate these aspects of Central U.S. summer rainfall, policymakers can have added confidence in dynamically downscaled rainfall projections, allowing for more targeted adaptation and mitigation.

Analysis of the variability of extra-tropical cyclones at the regional scale for the coasts of Northern Germany and investigation of their coastal impacts

NASA Astrophysics Data System (ADS)

Schaaf, Benjamin; Feser, Frauke

2015-04-01

The evaluation of long-term changes in wind speeds is very important for the coastal areas and the protection measures. Therefor the wind variability at the regional scale for the coast of Northern Germany shall be analysed. In order to derive changes in storminess it is essential to analyse long, homogeneous meteorological time series. Wind measurements often suffer from inconsistencies which arise from changes in instrumentation, observation method, or station location. Reanalysis data take into account such inhomogeneities of observation data and convert these measurements into a consistent, gridded data set with the same grid spacing and time intervals. This leads to a smooth, homogeneous data set, but with relatively low resolution (about 210 km for the longest reanalysis data set, the NCEP reanalysis starting in 1948). Therefore a high-resolution regional atmospheric model will be used to bring these reanalyses to a higher resolution, using in addition to a dynamical downscaling approach the spectral nudging technique. This method 'nudges' the large spatial scales of the regional climate model towards the reanalysis, while the smaller spatial scales are left unchanged. It was applied successfully in a number of applications, leading to realistic atmospheric weather descriptions of the past. With the regional climate model COSMO-CLM a very high-resolution data set was calculated for the last 67 years, the period from 1948 until now. The model area is North Germany with the coastal area of the North sea and parts of the Baltic sea. This is one of the first model simulations on climate scale with a very high resolution of 2.8 km, so even small scale effects can be detected. With this hindcast-simulation there are numerous options of evaluation. One can create wind climatologies for regional areas such as for the metropolitan region of Hamburg. Otherwise one can investigate individual storms in a case study. With a filtering and tracking program the course of individual storms can be tracked and compared with observations. Also statistical studies can be done and one can calculate percentiles, return periods and other different extreme value statistic variables. Later, with a further nesting simulation, the resolution can be reduced to 1 km for individual areas of interest to analyse small islands (as Foehr or Amrum) and their effects on the atmospheric flow more closely.

Application of optimal control theory to the design of broadband excitation pulses for high-resolution NMR.

PubMed

Skinner, Thomas E; Reiss, Timo O; Luy, Burkhard; Khaneja, Navin; Glaser, Steffen J

2003-07-01

Optimal control theory is considered as a methodology for pulse sequence design in NMR. It provides the flexibility for systematically imposing desirable constraints on spin system evolution and therefore has a wealth of applications. We have chosen an elementary example to illustrate the capabilities of the optimal control formalism: broadband, constant phase excitation which tolerates miscalibration of RF power and variations in RF homogeneity relevant for standard high-resolution probes. The chosen design criteria were transformation of I(z)-->I(x) over resonance offsets of +/- 20 kHz and RF variability of +/-5%, with a pulse length of 2 ms. Simulations of the resulting pulse transform I(z)-->0.995I(x) over the target ranges in resonance offset and RF variability. Acceptably uniform excitation is obtained over a much larger range of RF variability (approximately 45%) than the strict design limits. The pulse performs well in simulations that include homonuclear and heteronuclear J-couplings. Experimental spectra obtained from 100% 13C-labeled lysine show only minimal coupling effects, in excellent agreement with the simulations. By increasing pulse power and reducing pulse length, we demonstrate experimental excitation of 1H over +/-32 kHz, with phase variations in the spectra <8 degrees and peak amplitudes >93% of maximum. Further improvements in broadband excitation by optimized pulses (BEBOP) may be possible by applying more sophisticated implementations of the optimal control formalism.

Surface Dimming by the 2013 Rim Fire Simulated by a Sectional Aerosol Model

NASA Technical Reports Server (NTRS)

Yu, Pengfei; Toon, Owen B.; Bardeen, Charles G; Bucholtz, Anthony; Rosenlof, Karen; Saide, Pablo E.; Da Silva, Arlindo M.; Ziemba, Luke D.; Thornhill, Kenneth L.; Jimenez, Jose-Luis;

Surface dimming by the 2013 Rim Fire simulated by a sectional aerosol model.

PubMed

Yu, Pengfei; Toon, Owen B; Bardeen, Charles G; Bucholtz, Anthony; Rosenlof, Karen H; Saide, Pablo E; Da Silva, Arlindo; Ziemba, Luke D; Thornhill, Kenneth L; Jimenez, Jose-Luis; Campuzano-Jost, Pedro; Schwarz, Joshua P; Perring, Anne E; Froyd, Karl D; Wagner, N L; Mills, Michael J; Reid, Jeffrey S

2016-06-27

The Rim Fire of 2013, the third largest area burned by fire recorded in California history, is simulated by a climate model coupled with a size-resolved aerosol model. Modeled aerosol mass, number, and particle size distribution are within variability of data obtained from multiple-airborne in situ measurements. Simulations suggest that Rim Fire smoke may block 4-6% of sunlight energy reaching the surface, with a dimming efficiency around 120-150 W m -2 per unit aerosol optical depth in the midvisible at 13:00-15:00 local time. Underestimation of simulated smoke single scattering albedo at midvisible by 0.04 suggests that the model overestimates either the particle size or the absorption due to black carbon. This study shows that exceptional events like the 2013 Rim Fire can be simulated by a climate model with 1° resolution with overall good skill, although that resolution is still not sufficient to resolve the smoke peak near the source region.

Air-Sea Interaction Processes in Low and High-Resolution Coupled Climate Model Simulations for the Southeast Pacific

NASA Astrophysics Data System (ADS)

Porto da Silveira, I.; Zuidema, P.; Kirtman, B. P.

2017-12-01

The rugged topography of the Andes Cordillera along with strong coastal upwelling, strong sea surface temperatures (SST) gradients and extensive but geometrically-thin stratocumulus decks turns the Southeast Pacific (SEP) into a challenge for numerical modeling. In this study, hindcast simulations using the Community Climate System Model (CCSM4) at two resolutions were analyzed to examine the importance of resolution alone, with the parameterizations otherwise left unchanged. The hindcasts were initialized on January 1 with the real-time oceanic and atmospheric reanalysis (CFSR) from 1982 to 2003, forming a 10-member ensemble. The two resolutions are (0.1o oceanic and 0.5o atmospheric) and (1.125o oceanic and 0.9o atmospheric). The SST error growth in the first six days of integration (fast errors) and those resulted from model drift (saturated errors) are assessed and compared towards evaluating the model processes responsible for the SST error growth. For the high-resolution simulation, SST fast errors are positive (+0.3oC) near the continental borders and negative offshore (-0.1oC). Both are associated with a decrease in cloud cover, a weakening of the prevailing southwesterly winds and a reduction of latent heat flux. The saturated errors possess a similar spatial pattern, but are larger and are more spatially concentrated. This suggests that the processes driving the errors already become established within the first week, in contrast to the low-resolution simulations. These, instead, manifest too-warm SSTs related to too-weak upwelling, driven by too-strong winds and Ekman pumping. Nevertheless, the ocean surface tends to be cooler in the low-resolution simulation than the high-resolution due to a higher cloud cover. Throughout the integration, saturated SST errors become positive and could reach values up to +4oC. These are accompanied by upwelling dumping and a decrease in cloud cover. High and low resolution models presented notable differences in how SST errors variability drove atmospheric changes, especially because the high resolution is sensitive to resurgence regions. This allows the model to resolve cloud heights and establish different radiative feedbacks.

Forecasting Lightning Threat Using WRF Proxy Fields

NASA Technical Reports Server (NTRS)

McCaul, E. W., Jr.

2010-01-01

Objectives: Given that high-resolution WRF forecasts can capture the character of convective outbreaks, we seek to: 1. Create WRF forecasts of LTG threat (1-24 h), based on 2 proxy fields from explicitly simulated convection: - graupel flux near -15 C (captures LTG time variability) - vertically integrated ice (captures LTG threat area). 2. Calibrate each threat to yield accurate quantitative peak flash rate densities. 3. Also evaluate threats for areal coverage, time variability. 4. Blend threats to optimize results. 5. Examine sensitivity to model mesh, microphysics. Methods: 1. Use high-resolution 2-km WRF simulations to prognose convection for a diverse series of selected case studies. 2. Evaluate graupel fluxes; vertically integrated ice (VII). 3. Calibrate WRF LTG proxies using peak total LTG flash rate densities from NALMA; relationships look linear, with regression line passing through origin. 4. Truncate low threat values to make threat areal coverage match NALMA flash extent density obs. 5. Blend proxies to achieve optimal performance 6. Study CAPS 4-km ensembles to evaluate sensitivities.

Spatial Variability of Wet Troposphere Delays Over Inland Water Bodies

NASA Astrophysics Data System (ADS)

Mehran, Ali; Clark, Elizabeth A.; Lettenmaier, Dennis P.

2017-11-01

Satellite radar altimetry has enabled the study of water levels in large lakes and reservoirs at a global scale. The upcoming Surface Water and Ocean Topography (SWOT) satellite mission (scheduled launch 2020) will simultaneously measure water surface extent and elevation at an unprecedented accuracy and resolution. However, SWOT retrieval accuracy will be affected by a number of factors, including wet tropospheric delay—the delay in the signal's passage through the atmosphere due to atmospheric water content. In past applications, the wet tropospheric delay over large inland water bodies has been corrected using atmospheric moisture profiles based on atmospheric reanalysis data at relatively coarse (tens to hundreds of kilometers) spatial resolution. These products cannot resolve subgrid variations in wet tropospheric delays at the spatial resolutions (of 1 km and finer) that SWOT is intended to resolve. We calculate zenith wet tropospheric delays (ZWDs) and their spatial variability from Weather Research and Forecasting (WRF) numerical weather prediction model simulations at 2.33 km spatial resolution over the southwestern U.S., with attention in particular to Sam Rayburn, Ray Hubbard, and Elephant Butte Reservoirs which have width and length dimensions that are of order or larger than the WRF spatial resolution. We find that spatiotemporal variability of ZWD over the inland reservoirs depends on climatic conditions at the reservoir location, as well as distance from ocean, elevation, and surface area of the reservoir, but that the magnitude of subgrid variability (relative to analysis and reanalysis products) is generally less than 10 mm.

Overview of Proposal on High Resolution Climate Model Simulations of Recent Hurricane and Typhoon Activity: The Impact of SSTs and the Madden Julian Oscillation

NASA Technical Reports Server (NTRS)

Schubert, Siegfried; Kang, In-Sik; Reale, Oreste

2009-01-01

This talk gives an update on the progress and further plans for a coordinated project to carry out and analyze high-resolution simulations of tropical storm activity with a number of state-of-the-art global climate models. Issues addressed include, the mechanisms by which SSTs control tropical storm. activity on inter-annual and longer time scales, the modulation of that activity by the Madden Julian Oscillation on sub-seasonal time scales, as well as the sensitivity of the results to model formulation. The project also encourages companion coarser resolution runs to help assess resolution dependence, and. the ability of the models to capture the large-scale and long-terra changes in the parameters important for hurricane development. Addressing the above science questions is critical to understanding the nature of the variability of the Asian-Australian monsoon and its regional impacts, and thus CLIVAR RAMP fully endorses the proposed tropical storm simulation activity. The project is open to all interested organizations and investigators, and the results from the runs will be shared among the participants, as well as made available to the broader scientific community for analysis.

Natural climate variability and teleconnections to precipitation over the Pacific-North American region in CMIP3 and CMIP5 models

NASA Astrophysics Data System (ADS)

Polade, Suraj D.; Gershunov, Alexander; Cayan, Daniel R.; Dettinger, Michael D.; Pierce, David W.

2013-05-01

climate variability will continue to be an important aspect of future regional climate even in the midst of long-term secular changes. Consequently, the ability of climate models to simulate major natural modes of variability and their teleconnections provides important context for the interpretation and use of climate change projections. Comparisons reported here indicate that the CMIP5 generation of global climate models shows significant improvements in simulations of key Pacific climate mode and their teleconnections to North America compared to earlier CMIP3 simulations. The performance of 14 models with simulations in both the CMIP3 and CMIP5 archives are assessed using singular value decomposition analysis of simulated and observed winter Pacific sea surface temperatures (SSTs) and concurrent precipitation over the contiguous United States and northwestern Mexico. Most of the models reproduce basic features of the key natural mode and their teleconnections, albeit with notable regional deviations from observations in both SST and precipitation. Increasing horizontal resolution in the CMIP5 simulations is an important, but not a necessary, factor in the improvement from CMIP3 to CMIP5.

Natural climate variability and teleconnections to precipitation over the Pacific-North American region in CMIP3 and CMIP5 models

USGS Publications Warehouse

Polade, Suraj D.; Gershunov, Alexander; Cayan, Daniel R.; Dettinger, Michael D.; Pierce, David W.

2013-01-01

Natural climate variability will continue to be an important aspect of future regional climate even in the midst of long-term secular changes. Consequently, the ability of climate models to simulate major natural modes of variability and their teleconnections provides important context for the interpretation and use of climate change projections. Comparisons reported here indicate that the CMIP5 generation of global climate models shows significant improvements in simulations of key Pacific climate mode and their teleconnections to North America compared to earlier CMIP3 simulations. The performance of 14 models with simulations in both the CMIP3 and CMIP5 archives are assessed using singular value decomposition analysis of simulated and observed winter Pacific sea surface temperatures (SSTs) and concurrent precipitation over the contiguous United States and northwestern Mexico. Most of the models reproduce basic features of the key natural mode and their teleconnections, albeit with notable regional deviations from observations in both SST and precipitation. Increasing horizontal resolution in the CMIP5 simulations is an important, but not a necessary, factor in the improvement from CMIP3 to CMIP5.

Global land-atmosphere coupling associated with cold climate processes

NASA Astrophysics Data System (ADS)

Dutra, Emanuel

This dissertation constitutes an assessment of the role of cold processes, associated with snow cover, in controlling the land-atmosphere coupling. The work was based on model simulations, including offline simulations with the land surface model HTESSEL, and coupled atmosphere simulations with the EC-EARTH climate model. A revised snow scheme was developed and tested in HTESSEL and EC-EARTH. The snow scheme is currently operational at the European Centre for Medium-Range Weather Forecasts integrated forecast system, and in the default configuration of EC-EARTH. The improved representation of the snowpack dynamics in HTESSEL resulted in improvements in the near surface temperature simulations of EC-EARTH. The new snow scheme development was complemented with the option of multi-layer version that showed its potential in modeling thick snowpacks. A key process was the snow thermal insulation that led to significant improvements of the surface water and energy balance components. Similar findings were observed when coupling the snow scheme to lake ice, where lake ice duration was significantly improved. An assessment on the snow cover sensitivity to horizontal resolution, parameterizations and atmospheric forcing within HTESSEL highlighted the role of the atmospheric forcing accuracy and snowpack parameterizations in detriment of horizontal resolution over flat regions. A set of experiments with and without free snow evolution was carried out with EC-EARTH to assess the impact of the interannual variability of snow cover on near surface and soil temperatures. It was found that snow cover interannual variability explained up to 60% of the total interannual variability of near surface temperature over snow covered regions. Although these findings are model dependent, the results showed consistency with previously published work. Furthermore, the detailed validation of the snow dynamics simulations in HTESSEL and EC-EARTH guarantees consistency of the results.

The relationship between Arabian Sea upwelling and Indian Monsoon revisited in a high resolution ocean simulation

NASA Astrophysics Data System (ADS)

Yi, Xing; Hünicke, Birgit; Tim, Nele; Zorita, Eduardo

2018-01-01

Studies based on sediment records, sea-surface temperature and wind suggest that upwelling along the western coast of Arabian Sea is strongly affected by the Indian summer Monsoon. We examine this relationship directly in an eddy-resolving global ocean simulation STORM driven by atmospheric reanalysis over the last 61 years. With its very high spatial resolution (10 km), STORM allows us to identify characteristics of the upwelling system. We analyse the co-variability between upwelling and meteorological and oceanic variables from 1950 to 2010. The analysis reveals high interannual correlations between coastal upwelling and along-shore wind-stress (r = 0.73) as well as with sea-surface temperature (r = -0.83). However, the correlation between the upwelling and the Monsoon is small. We find an atmospheric circulation pattern different from the one that drives the Monsoon as the main modulator of the upwelling variability. In spite of this, the patterns of temperature anomalies that are either linked to Arabian Sea upwelling or to the Monsoon are spatially quite similar, although the physical mechanisms of these links are different. In addition, no long-term trend is detected in our modelled upwelling in the Arabian Sea.

High-resolution, regional-scale crop yield simulations for the Southwestern United States

NASA Astrophysics Data System (ADS)

Stack, D. H.; Kafatos, M.; Medvigy, D.; El-Askary, H. M.; Hatzopoulos, N.; Kim, J.; Kim, S.; Prasad, A. K.; Tremback, C.; Walko, R. L.; Asrar, G. R.

2012-12-01

Over the past few decades, there have been many process-based crop models developed with the goal of better understanding the impacts of climate, soils, and management decisions on crop yields. These models simulate the growth and development of crops in response to environmental drivers. Traditionally, process-based crop models have been run at the individual farm level for yield optimization and management scenario testing. Few previous studies have used these models over broader geographic regions, largely due to the lack of gridded high-resolution meteorological and soil datasets required as inputs for these data intensive process-based models. In particular, assessment of regional-scale yield variability due to climate change requires high-resolution, regional-scale, climate projections, and such projections have been unavailable until recently. The goal of this study was to create a framework for extending the Agricultural Production Systems sIMulator (APSIM) crop model for use at regional scales and analyze spatial and temporal yield changes in the Southwestern United States (CA, AZ, and NV). Using the scripting language Python, an automated pipeline was developed to link Regional Climate Model (RCM) output with the APSIM crop model, thus creating a one-way nested modeling framework. This framework was used to combine climate, soil, land use, and agricultural management datasets in order to better understand the relationship between climate variability and crop yield at the regional-scale. Three different RCMs were used to drive APSIM: OLAM, RAMS, and WRF. Preliminary results suggest that, depending on the model inputs, there is some variability between simulated RCM driven maize yields and historical yields obtained from the United States Department of Agriculture (USDA). Furthermore, these simulations showed strong non-linear correlations between yield and meteorological drivers, with critical threshold values for some of the inputs (e.g. minimum and maximum temperature), beyond which the yields were negatively affected. These results are now being used for further regional-scale yield analysis as the aforementioned framework is adaptable to multiple geographic regions and crop types.

Effects of Cloud Horizontal Inhomogeneity and Drizzle on Remote Sensing of Cloud Droplet Effective Radius: Case Studies Based on Large-eddy Simulations

NASA Technical Reports Server (NTRS)

Zhang, Zhibo; Ackerman, Andrew S.; Feingold, Graham; Platnick, Steven; Pincus, Robert; Xue, Huiwen

2012-01-01

This study investigates effects of drizzle and cloud horizontal inhomogeneity on cloud effective radius (re) retrievals from the Moderate Resolution Imaging Spectroradiometer (MODIS). In order to identify the relative importance of various factors, we developed a MODIS cloud property retrieval simulator based on the combination of large-eddy simulations (LES) and radiative transfer computations. The case studies based on synthetic LES cloud fields indicate that at high spatial resolution (100 m) 3-D radiative transfer effects, such as illumination and shadowing, can induce significant differences between retrievals ofre based on reflectance at 2.1 m (re,2.1) and 3.7 m (re,3.7). It is also found that 3-D effects tend to have stronger impact onre,2.1 than re,3.7, leading to positive difference between the two (re,3.72.1) from illumination and negative re,3.72.1from shadowing. The cancellation of opposing 3-D effects leads to overall reasonable agreement betweenre,2.1 and re,3.7 at high spatial resolution as far as domain averages are concerned. At resolutions similar to MODIS, however, re,2.1 is systematically larger than re,3.7when averaged over the LES domain, with the difference exhibiting a threshold-like dependence on bothre,2.1and an index of the sub-pixel variability in reflectance (H), consistent with MODIS observations. In the LES cases studied, drizzle does not strongly impact reretrievals at either wavelength. It is also found that opposing 3-D radiative transfer effects partly cancel each other when cloud reflectance is aggregated from high spatial resolution to MODIS resolution, resulting in a weaker net impact of 3-D radiative effects onre retrievals. The large difference at MODIS resolution between re,3.7 and re,2.1 for highly inhomogeneous pixels with H 0.4 can be largely attributed to what we refer to as the plane-parallelrebias, which is attributable to the impact of sub-pixel level horizontal variability of cloud optical thickness onre retrievals and is greater for re,2.1 than re,3.7. These results suggest that there are substantial uncertainties attributable to 3-D radiative effects and plane-parallelre bias in the MODIS re,2.1retrievals for pixels with strong sub-pixel scale variability, and theH index can be used to identify these uncertainties.

Modeling and measurement of the detector presampling MTF of a variable resolution x-ray CT scanner.

PubMed

Melnyk, Roman; DiBianca, Frank A

2007-03-01

The detector presampling modulation transfer function (MTF) of a 576-channel variable resolution x-ray (VRX) computed tomography (CT) scanner was evaluated in this study. The scanner employs a VRX detector, which provides increased spatial resolution by matching the scanner's field of view (FOV) to the size of an object being imaged. Because spatial resolution is the parameter the scanner promises to improve, the evaluation of this resolution is important. The scanner's pre-reconstruction spatial resolution, represented by the detector presampling MTF, was evaluated using both modeling (Monte Carlo simulation) and measurement (the moving slit method). The theoretical results show the increase in the cutoff frequency of the detector presampling MTF from 1.39 to 43.38 cycles/mm as the FOV of the VRX CT scanner decreases from 32 to 1 cm. The experimental results are in reasonable agreement with the theoretical data. Some discrepancies between the measured and the modeled detector presampling MTFs can be explained by the limitations of the model. At small FOVs (1-8 cm), the MTF measurements were limited by the size of the focal spot. The obtained results are important for further development of the VRX CT scanner.

Modeling and measurement of the detector presampling MTF of a variable resolution x-ray CT scanner

PubMed Central

Melnyk, Roman; DiBianca, Frank A.

2007-01-01

The detector presampling MTF of a 576-channel variable resolution x-ray (VRX) CT scanner was evaluated in this study. The scanner employs a VRX detector, which provides increased spatial resolution by matching the scanner’s field of view (FOV) to the size of an object being imaged. Because spatial resolution is the parameter the scanner promises to improve, the evaluation of this resolution is important. The scanner’s pre-reconstruction spatial resolution, represented by the detector presampling MTF, was evaluated using both modeling (Monte Carlo simulation) and measurement (the moving slit method). The theoretical results show the increase in the cutoff frequency of the detector presampling MTF from 1.39 cy/mm to 43.38 cy/mm as the FOV of the VRX CT scanner decreases from 32 cm to 1 cm. The experimental results are in reasonable agreement with the theoretical data. Some discrepancies between the measured and the modeled detector presampling MTFs can be explained by the limitations of the model. At small FOVs (1–8 cm), the MTF measurements were limited by the size of the focal spot. The obtained results are important for further development of the VRX CT scanner. PMID:17369872

Near-surface wind variability over the broader Adriatic region: insights from an ensemble of regional climate models

NASA Astrophysics Data System (ADS)

Belušić, Andreina; Prtenjak, Maja Telišman; Güttler, Ivan; Ban, Nikolina; Leutwyler, David; Schär, Christoph

2018-06-01

Over the past few decades the horizontal resolution of regional climate models (RCMs) has steadily increased, leading to a better representation of small-scale topographic features and more details in simulating dynamical aspects, especially in coastal regions and over complex terrain. Due to its complex terrain, the broader Adriatic region represents a major challenge to state-of-the-art RCMs in simulating local wind systems realistically. The objective of this study is to identify the added value in near-surface wind due to the refined grid spacing of RCMs. For this purpose, we use a multi-model ensemble composed of CORDEX regional climate simulations at 0.11° and 0.44° grid spacing, forced by the ERA-Interim reanalysis, a COSMO convection-parameterizing simulation at 0.11° and a COSMO convection-resolving simulation at 0.02° grid spacing. Surface station observations from this region and satellite QuikSCAT data over the Adriatic Sea have been compared against daily output obtained from the available simulations. Both day-to-day wind and its frequency distribution are examined. The results indicate that the 0.44° RCMs rarely outperform ERA-Interim reanalysis, while the performance of the high-resolution simulations surpasses that of ERA-Interim. We also disclose that refining the grid spacing to a few km is needed to properly capture the small-scale wind systems. Finally, we show that the simulations frequently yield the accurate angle of local wind regimes, such as for the Bora flow, but overestimate the associated wind magnitude. Finally, spectral analysis shows good agreement between measurements and simulations, indicating the correct temporal variability of the wind speed.

Progress in Modeling Global Atmospheric CO2 Fluxes and Transport: Results from Simulations with Diurnal Fluxes

NASA Technical Reports Server (NTRS)

Collatz, G. James; Kawa, R.

2007-01-01

Progress in better determining CO2 sources and sinks will almost certainly rely on utilization of more extensive and intensive CO2 and related observations including those from satellite remote sensing. Use of advanced data requires improved modeling and analysis capability. Under NASA Carbon Cycle Science support we seek to develop and integrate improved formulations for 1) atmospheric transport, 2) terrestrial uptake and release, 3) biomass and 4) fossil fuel burning, and 5) observational data analysis including inverse calculations. The transport modeling is based on meteorological data assimilation analysis from the Goddard Modeling and Assimilation Office. Use of assimilated met data enables model comparison to CO2 and other observations across a wide range of scales of variability. In this presentation we focus on the short end of the temporal variability spectrum: hourly to synoptic to seasonal. Using CO2 fluxes at varying temporal resolution from the SIB 2 and CASA biosphere models, we examine the model's ability to simulate CO2 variability in comparison to observations at different times, locations, and altitudes. We find that the model can resolve much of the variability in the observations, although there are limits imposed by vertical resolution of boundary layer processes. The influence of key process representations is inferred. The high degree of fidelity in these simulations leads us to anticipate incorporation of realtime, highly resolved observations into a multiscale carbon cycle analysis system that will begin to bridge the gap between top-down and bottom-up flux estimation, which is a primary focus of NACP.

Nonlinear responses of southern African rainfall to forcing from Atlantic SST in a high-resolution regional climate model

NASA Astrophysics Data System (ADS)

Williams, C.; Kniveton, D.; Layberry, R.

2009-04-01

It is increasingly accepted that any possible climate change will not only have an influence on mean climate but may also significantly alter climatic variability. A change in the distribution and magnitude of extreme rainfall events (associated with changing variability), such as droughts or flooding, may have a far greater impact on human and natural systems than a changing mean. This issue is of particular importance for environmentally vulnerable regions such as southern Africa. The subcontinent is considered especially vulnerable to and ill-equipped (in terms of adaptation) for extreme events, due to a number of factors including extensive poverty, famine, disease and political instability. Rainfall variability is a function of scale, so high spatial and temporal resolution data are preferred to identify extreme events and accurately predict future variability. In this research, high resolution satellite derived rainfall data from the Microwave Infra-Red Algorithm (MIRA) are used as a basis for undertaking model experiments using a state-of-the-art regional climate model. The MIRA dataset covers the period from 1993-2002 and the whole of southern Africa at a spatial resolution of 0.1 degree longitude/latitude. Once the model's ability to reproduce extremes has been assessed, idealised regions of sea surface temperature (SST) anomalies are used to force the model, with the overall aim of investigating the ways in which SST anomalies influence rainfall extremes over southern Africa. In this paper, results from sensitivity testing of the regional climate model's domain size are briefly presented, before a comparison of simulated daily rainfall from the model with the satellite-derived dataset. Secondly, simulations of current climate and rainfall extremes from the model are compared to the MIRA dataset at daily timescales. Finally, the results from the idealised SST experiments are presented, suggesting highly nonlinear associations between rainfall extremes remote SST anomalies.

Seasonal and spatial variation in broadleaf forest model parameters

NASA Astrophysics Data System (ADS)

Groenendijk, M.; van der Molen, M. K.; Dolman, A. J.

2009-04-01

Process based, coupled ecosystem carbon, energy and water cycle models are used with the ultimate goal to project the effect of future climate change on the terrestrial carbon cycle. A typical dilemma in such exercises is how much detail the model must be given to describe the observations reasonably realistic while also be general. We use a simple vegetation model (5PM) with five model parameters to study the variability of the parameters. These parameters are derived from the observed carbon and water fluxes from the FLUXNET database. For 15 broadleaf forests the model parameters were derived for different time resolutions. It appears that in general for all forests, the correlation coefficient between observed and simulated carbon and water fluxes improves with a higher parameter time resolution. The quality of the simulations is thus always better when a higher time resolution is used. These results show that annual parameters are not capable of properly describing weather effects on ecosystem fluxes, and that two day time resolution yields the best results. A first indication of the climate constraints can be found by the seasonal variation of the covariance between Jm, which describes the maximum electron transport for photosynthesis, and climate variables. A general seasonality we found is that during winter the covariance with all climate variables is zero. Jm increases rapidly after initial spring warming, resulting in a large covariance with air temperature and global radiation. During summer Jm is less variable, but co-varies negatively with air temperature and vapour pressure deficit and positively with soil water content. A temperature response appears during spring and autumn for broadleaf forests. This shows that an annual model parameter cannot be representative for the entire year. And relations with mean annual temperature are not possible. During summer the photosynthesis parameters are constrained by water availability, soil water content and vapour pressure deficit.

Dynamical downscaling of historical climate over CORDEX East Asia domain: A comparison of regional ocean-atmosphere coupled model to stand-alone RCM simulations

NASA Astrophysics Data System (ADS)

Zou, Liwei; Zhou, Tianjun; Peng, Dongdong

2016-02-01

The FROALS (flexible regional ocean-atmosphere-land system) model, a regional ocean-atmosphere coupled model, has been applied to the Coordinated Regional Downscaling Experiment (CORDEX) East Asia domain. Driven by historical simulations from a global climate system model, dynamical downscaling for the period from 1980 to 2005 has been conducted at a uniform horizontal resolution of 50 km. The impacts of regional air-sea couplings on the simulations of East Asian summer monsoon rainfall have been investigated, and comparisons have been made to corresponding simulations performed using a stand-alone regional climate model (RCM). The added value of the FROALS model with respect to the driving global climate model was evident in terms of both climatology and the interannual variability of summer rainfall over East China by the contributions of both the high horizontal resolution and the reasonably simulated convergence of the moisture fluxes. Compared with the stand-alone RCM simulations, the spatial pattern of the simulated low-level monsoon flow over East Asia and the western North Pacific was improved in the FROALS model due to its inclusion of regional air-sea coupling. The results indicated that the simulated sea surface temperature (SSTs) resulting from the regional air-sea coupling were lower than those derived directly from the driving global model over the western North Pacific north of 15°N. These colder SSTs had both positive and negative effects. On the one hand, they strengthened the western Pacific subtropical high, which improved the simulation of the summer monsoon circulation over East Asia. On the other hand, the colder SSTs suppressed surface evaporation and favored weaker local interannual variability in the SST, which led to less summer rainfall and weaker interannual rainfall variability over the Korean Peninsula and Japan. Overall, the reference simulation performed using the FROALS model is reasonable in terms of rainfall over the land area of East Asia and will become the basis for the generation of climate change scenarios for the CORDEX East Asia domain that will be described in future reports.

The Super Tuesday Outbreak: Forecast Sensitivities to Single-Moment Microphysics Schemes

NASA Technical Reports Server (NTRS)

Molthan, Andrew L.; Case, Jonathan L.; Dembek, Scott R.; Jedlovec, Gary J.; Lapenta, William M.

2008-01-01

Forecast precipitation and radar characteristics are used by operational centers to guide the issuance of advisory products. As operational numerical weather prediction is performed at increasingly finer spatial resolution, convective precipitation traditionally represented by sub-grid scale parameterization schemes is now being determined explicitly through single- or multi-moment bulk water microphysics routines. Gains in forecasting skill are expected through improved simulation of clouds and their microphysical processes. High resolution model grids and advanced parameterizations are now available through steady increases in computer resources. As with any parameterization, their reliability must be measured through performance metrics, with errors noted and targeted for improvement. Furthermore, the use of these schemes within an operational framework requires an understanding of limitations and an estimate of biases so that forecasters and model development teams can be aware of potential errors. The National Severe Storms Laboratory (NSSL) Spring Experiments have produced daily, high resolution forecasts used to evaluate forecast skill among an ensemble with varied physical parameterizations and data assimilation techniques. In this research, high resolution forecasts of the 5-6 February 2008 Super Tuesday Outbreak are replicated using the NSSL configuration in order to evaluate two components of simulated convection on a large domain: sensitivities of quantitative precipitation forecasts to assumptions within a single-moment bulk water microphysics scheme, and to determine if these schemes accurately depict the reflectivity characteristics of well-simulated, organized, cold frontal convection. As radar returns are sensitive to the amount of hydrometeor mass and the distribution of mass among variably sized targets, radar comparisons may guide potential improvements to a single-moment scheme. In addition, object-based verification metrics are evaluated for their utility in gauging model performance and QPF variability.

Natural and anthropogenic land cover change and its impact on the regional climate and hydrological extremes over Sanjiangyuan region

NASA Astrophysics Data System (ADS)

Ji, P.; Yuan, X.

2017-12-01

Located in the northern Tibetan Plateau, Sanjiangyuan is the headwater region of the Yellow River, Yangtze River and Mekong River. Besides climate change, natural and human-induced land cover change (e.g., Graze for Grass Project) is also influencing the regional hydro-climate and hydrological extremes significantly. To quantify their impacts, a land surface model (LSM) with consideration of soil moisture-lateral surface flow interaction and quasi-three-dimensional subsurface flow, is used to conduct long-term high resolution simulations driven by China Meteorological Administration Land Data Assimilation System forcing data and different land cover scenarios. In particular, the role of surface and subsurface lateral flows is also analyzed by comparing with typical one-dimensional models. Lateral flows help to simulate soil moisture variability caused by topography at hyper-resolution (e.g., 100m), which is also essential for simulating hydrological extremes including soil moisture dryness/wetness and high/low flows. The LSM will also be coupled with a regional climate model to simulate the effect of natural and anthropogenic land cover change on regional climate, with particular focus on the land-atmosphere coupling at different resolutions with different configurations in modeling land surface hydrology.

Low-frequency variability of the Atlantic MOC in the eddying regime : the intrinsic component.

NASA Astrophysics Data System (ADS)

Gregorio, S.; Penduff, T.; Barnier, B.; Molines, J.-M.; Le Sommer, J.

2012-04-01

A 327-year 1/4° global ocean/sea-ice simulation has been produced by the DRAKKAR ocean modeling consortium. This simulation is forced by a repeated seasonal atmospheric forcing but nevertheless exhibits a substantial low-frequency variability (at interannual and longer timescales), which is therefore of intrinsic origin. This nonlinearly-generated intrinsic variability is almost absent from the coarse-resolution (2°) version of this simulation. Comparing the 1/4° simulation with its fully-forced counterpart, Penduff et al. (2011) have shown that the low-frequency variability of local sea-level is largely generated by the ocean itself in eddying areas, rather than directly forced by the atmosphere. Using the same simulations, the present study quantifies the imprint of the intrinsic low-frequency variability on the Meridional Overturning Circulation (MOC) at interannual-to-decadal timescales in the Atlantic. We first compare the intrinsic and atmospherically-forced interannual variances of the Atlantic MOC calculated in geopotential coordinates. This analysis reveals substantial sources of intrinsic MOC variability in the South Atlantic (driven by the Agulhas mesoscale activity according to Biastoch et al. (2008)), but also in the North Atlantic. We extend our investigation to the MOC calculated in isopycnal coordinates, and identify regions in the basin where the water mass transformation exhibits low-frequency intrinsic variability. In this eddy-permitting regime, intrinsic processes are shown to generate about half the total (geopotential and isopycnal) MOC interannual variance in certain key regions of the Atlantic. This intrinsic variability is absent from 2° simulations. Penduff, T., Juza, M., Barnier, B., Zika, J., Dewar, W.K., Treguier, A.-M., Molines, J.-M., Audiffren, N., 2011: Sea-level expression of intrinsic and forced ocean variabilities at interannual time scales. J. Climate, 24, 5652-5670. doi: 10.1175/JCLI-D-11-00077.1. Biastoch, A., Böning, C. W., Lutjeharms, J. R. E., 2008: Agulhas leakage dynamics affects decadal variability in Atlantic overturning circulation. Nature, 456, 489-492, doi: 10.1038/nature07426.

Variable Entry Biased Paracentric Hemispherical Deflector: Experimental results on energy resolution for different entry positions

NASA Astrophysics Data System (ADS)

Dogan, Mevlut; Ulu, Melike; Gennerakis, Giannis; Zouros, Theo J. M.

2014-04-01

A new hemispherical deflector analyzer (HDA) which is designed for electron energy analysis in atomic collisions has been constructed and tested. Using the crossed beam technique at the electron spectrometer, test measurements were performed for electron beam (200 eV) - Helium atoms interactions. These first experimental results show that the paracentric entries give almost twice as good resolution as that for the conventional entry. Supporting simulations of the entire lens+HDA spectrometer are found in relatively good agreement with experiment.

Application of multi-scale wavelet entropy and multi-resolution Volterra models for climatic downscaling

NASA Astrophysics Data System (ADS)

Sehgal, V.; Lakhanpal, A.; Maheswaran, R.; Khosa, R.; Sridhar, Venkataramana

2018-01-01

This study proposes a wavelet-based multi-resolution modeling approach for statistical downscaling of GCM variables to mean monthly precipitation for five locations at Krishna Basin, India. Climatic dataset from NCEP is used for training the proposed models (Jan.'69 to Dec.'94) and are applied to corresponding CanCM4 GCM variables to simulate precipitation for the validation (Jan.'95-Dec.'05) and forecast (Jan.'06-Dec.'35) periods. The observed precipitation data is obtained from the India Meteorological Department (IMD) gridded precipitation product at 0.25 degree spatial resolution. This paper proposes a novel Multi-Scale Wavelet Entropy (MWE) based approach for clustering climatic variables into suitable clusters using k-means methodology. Principal Component Analysis (PCA) is used to obtain the representative Principal Components (PC) explaining 90-95% variance for each cluster. A multi-resolution non-linear approach combining Discrete Wavelet Transform (DWT) and Second Order Volterra (SoV) is used to model the representative PCs to obtain the downscaled precipitation for each downscaling location (W-P-SoV model). The results establish that wavelet-based multi-resolution SoV models perform significantly better compared to the traditional Multiple Linear Regression (MLR) and Artificial Neural Networks (ANN) based frameworks. It is observed that the proposed MWE-based clustering and subsequent PCA, helps reduce the dimensionality of the input climatic variables, while capturing more variability compared to stand-alone k-means (no MWE). The proposed models perform better in estimating the number of precipitation events during the non-monsoon periods whereas the models with clustering without MWE over-estimate the rainfall during the dry season.

Spectral decomposition of internal gravity wave sea surface height in global models

NASA Astrophysics Data System (ADS)

Savage, Anna C.; Arbic, Brian K.; Alford, Matthew H.; Ansong, Joseph K.; Farrar, J. Thomas; Menemenlis, Dimitris; O'Rourke, Amanda K.; Richman, James G.; Shriver, Jay F.; Voet, Gunnar; Wallcraft, Alan J.; Zamudio, Luis

2017-10-01

Two global ocean models ranging in horizontal resolution from 1/12° to 1/48° are used to study the space and time scales of sea surface height (SSH) signals associated with internal gravity waves (IGWs). Frequency-horizontal wavenumber SSH spectral densities are computed over seven regions of the world ocean from two simulations of the HYbrid Coordinate Ocean Model (HYCOM) and three simulations of the Massachusetts Institute of Technology general circulation model (MITgcm). High wavenumber, high-frequency SSH variance follows the predicted IGW linear dispersion curves. The realism of high-frequency motions (>0.87 cpd) in the models is tested through comparison of the frequency spectral density of dynamic height variance computed from the highest-resolution runs of each model (1/25° HYCOM and 1/48° MITgcm) with dynamic height variance frequency spectral density computed from nine in situ profiling instruments. These high-frequency motions are of particular interest because of their contributions to the small-scale SSH variability that will be observed on a global scale in the upcoming Surface Water and Ocean Topography (SWOT) satellite altimetry mission. The variance at supertidal frequencies can be comparable to the tidal and low-frequency variance for high wavenumbers (length scales smaller than ˜50 km), especially in the higher-resolution simulations. In the highest-resolution simulations, the high-frequency variance can be greater than the low-frequency variance at these scales.

3D visualization of ultra-fine ICON climate simulation data

NASA Astrophysics Data System (ADS)

Röber, Niklas; Spickermann, Dela; Böttinger, Michael

2016-04-01

Advances in high performance computing and model development allow the simulation of finer and more detailed climate experiments. The new ICON model is based on an unstructured triangular grid and can be used for a wide range of applications, ranging from global coupled climate simulations down to very detailed and high resolution regional experiments. It consists of an atmospheric and an oceanic component and scales very well for high numbers of cores. This allows us to conduct very detailed climate experiments with ultra-fine resolutions. ICON is jointly developed in partnership with DKRZ by the Max Planck Institute for Meteorology and the German Weather Service. This presentation discusses our current workflow for analyzing and visualizing this high resolution data. The ICON model has been used for eddy resolving (<10km) ocean simulations, as well as for ultra-fine cloud resolving (120m) atmospheric simulations. This results in very large 3D time dependent multi-variate data that need to be displayed and analyzed. We have developed specific plugins for the free available visualization software ParaView and Vapor, which allows us to read and handle that much data. Within ParaView, we can additionally compare prognostic variables with performance data side by side to investigate the performance and scalability of the model. With the simulation running in parallel on several hundred nodes, an equal load balance is imperative. In our presentation we show visualizations of high-resolution ICON oceanographic and HDCP2 atmospheric simulations that were created using ParaView and Vapor. Furthermore we discuss our current efforts to improve our visualization capabilities, thereby exploring the potential of regular in-situ visualization, as well as of in-situ compression / post visualization.

Rainfall variability and extremes over southern Africa: Assessment of a climate model to reproduce daily extremes

NASA Astrophysics Data System (ADS)

Williams, C. J. R.; Kniveton, D. R.; Layberry, R.

2009-04-01

It is increasingly accepted that that any possible climate change will not only have an influence on mean climate but may also significantly alter climatic variability. A change in the distribution and magnitude of extreme rainfall events (associated with changing variability), such as droughts or flooding, may have a far greater impact on human and natural systems than a changing mean. This issue is of particular importance for environmentally vulnerable regions such as southern Africa. The subcontinent is considered especially vulnerable to and ill-equipped (in terms of adaptation) for extreme events, due to a number of factors including extensive poverty, famine, disease and political instability. Rainfall variability and the identification of rainfall extremes is a function of scale, so high spatial and temporal resolution data are preferred to identify extreme events and accurately predict future variability. The majority of previous climate model verification studies have compared model output with observational data at monthly timescales. In this research, the assessment of ability of a state of the art climate model to simulate climate at daily timescales is carried out using satellite derived rainfall data from the Microwave Infra-Red Algorithm (MIRA). This dataset covers the period from 1993-2002 and the whole of southern Africa at a spatial resolution of 0.1 degree longitude/latitude. The ability of a climate model to simulate current climate provides some indication of how much confidence can be applied to its future predictions. In this paper, simulations of current climate from the UK Meteorological Office Hadley Centre's climate model, in both regional and global mode, are firstly compared to the MIRA dataset at daily timescales. This concentrates primarily on the ability of the model to simulate the spatial and temporal patterns of rainfall variability over southern Africa. Secondly, the ability of the model to reproduce daily rainfall extremes will be assessed, again by a comparison with extremes from the MIRA dataset. The paper will conclude by discussing the user needs of satellite rainfall retrievals from a climate change modelling prospective.

NASCAP simulation of PIX 2 experiments

NASA Technical Reports Server (NTRS)

Roche, J. C.; Mandell, M. J.

1985-01-01

The latest version of the NASCAP/LEO digital computer code used to simulate the PIX 2 experiment is discussed. NASCAP is a finite-element code and previous versions were restricted to a single fixed mesh size. As a consequence the resolution was dictated by the largest physical dimension to be modeled. The latest version of NASCAP/LEO can subdivide selected regions. This permitted the modeling of the overall Delta launch vehicle in the primary computational grid at a coarse resolution, with subdivided regions at finer resolution being used to pick up the details of the experiment module configuration. Langmuir probe data from the flight were used to estimate the space plasma density and temperature and the Delta ground potential relative to the space plasma. This information is needed for input to NASCAP. Because of the uncertainty or variability in the values of these parameters, it was necessary to explore a range around the nominal value in order to determine the variation in current collection. The flight data from PIX 2 were also compared with the results of the NASCAP simulation.

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

NASA Astrophysics Data System (ADS)

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.1.05/1.1.00/02.0073). The partial support was also provided under the projects P209-11-0956 of the Czech Science Foundation and CZ.1.07/2.4.00/31.0056 (Operational Programme of Education for Competitiveness of Ministry of Education, Youth and Sports of the Czech Republic).

Simulation of the Impact of Climate Variability on Malaria Transmission in the Sahel

NASA Astrophysics Data System (ADS)

Bomblies, A.; Eltahir, E.; Duchemin, J.

2007-12-01

A coupled hydrology and entomology model for simulation of malaria transmission and malaria transmitting mosquito population dynamics is presented. Model development and validation is done using field data and observations collected at Banizoumbou and Zindarou, Niger spanning three wet seasons, from 2005 through 2007. The primary model objective is the accurate determination of climate variability effects on village scale malaria transmission. Malaria transmission dependence on climate variables is highly nonlinear and complex. Temperature and humidity affect mosquito longevity, temperature controls parasite development rates in the mosquito as well as subadult mosquito development rates, and precipitation determines the formation and persistence of adequate breeding pools. Moreover, unsaturated zone hydrology influences overland flow, and climate controlled evapotranspiration rates and root zone uptake therefore also influence breeding pool formation. High resolution distributed hydrologic simulation allows representation of the small-scale ephemeral pools that constitute the primary habitat of Anopheles gambiae mosquitoes, the dominant malaria vectors in the Niger Sahel. Remotely sensed soil type, vegetation type, and microtopography rasters are used to assign the distributed parameter fields for simulation of the land surface hydrologic response to precipitation and runoff generation. Predicted runoff from each cell flows overland and into topographic depressions, with explicit representation of infiltration and evapotranspiration. The model's entomology component interacts with simulated pools. Subadult (aquatic stage) mosquito breeding is simulated in the pools, and water temperature dependent stage advancement rates regulate adult mosquito emergence into the model domain. Once emerged, adult mosquitoes are tracked as independent individual agents that interact with their immediate environment. Attributes relevant to malaria transmission such as gonotrophic state, infected and infectious states, age, and location relative to human population are tracked for each individual. The model operates at a resolution consistent with the characteristic scale of relevant ecological processes. Microhabitat exploitation and spatial structure of the mosquito population surrounding villages is reproduced in this manner. The resulting coupled model predicts not only malaria transmission's response to interannual climate variability, but can also evaluate land use change effects on malaria transmission. The late Professor Andrew Spielman of the Harvard School of Public Health provided medical entomology expertise and was a part of this effort.

Variability of North Atlantic Hurricane Frequency in a Large Ensemble of High-Resolution Climate Simulations

NASA Astrophysics Data System (ADS)

Mei, W.; Kamae, Y.; Xie, S. P.

2017-12-01

Forced and internal variability of North Atlantic hurricane frequency during 1951-2010 is studied using a large ensemble of climate simulations by a 60-km atmospheric general circulation model that is forced by observed sea surface temperatures (SSTs). The simulations well capture the interannual-to-decadal variability of hurricane frequency in best track data, and further suggest a possible underestimate of hurricane counts in the current best track data prior to 1966 when satellite measurements were unavailable. A genesis potential index (GPI) averaged over the Main Development Region (MDR) accounts for more than 80% of the forced variations in hurricane frequency, with potential intensity and vertical wind shear being the dominant factors. In line with previous studies, the difference between MDR SST and tropical mean SST is a simple but useful predictor; a one-degree increase in this SST difference produces 7.1±1.4 more hurricanes. The hurricane frequency also exhibits internal variability that is comparable in magnitude to the interannual variability. The 100-member ensemble allows us to address the following important questions: (1) Are the observations equivalent to one realization of such a large ensemble? (2) How many ensemble members are needed to reproduce the variability in observations and in the forced component of the simulations? The sources of the internal variability in hurricane frequency will be identified and discussed. The results provide an explanation for the relatively week correlation ( 0.6) between MDR GPI and hurricane frequency on interannual timescales in observations.

Wind, Circulation, and Topographic Effects on Alongshore Phytoplankton Variability in the California Current

NASA Astrophysics Data System (ADS)

Fiechter, Jerome; Edwards, Christopher A.; Moore, Andrew M.

2018-04-01

A physical-biogeochemical model is used to produce a retrospective analysis at 3-km resolution of alongshore phytoplankton variability in the California Current during 1988-2010. The simulation benefits from downscaling a regional circulation reanalysis, which provides improved physical ocean state estimates in the high-resolution domain. The emerging pattern is one of local upwelling intensification in response to increased alongshore wind stress in the lee of capes, modulated by alongshore meanders in the geostrophic circulation. While stronger upwelling occurs near most major topographic features, substantial increases in phytoplankton biomass only ensue where local circulation patterns are conducive to on-shelf retention of upwelled nutrients. Locations of peak nutrient delivery and chlorophyll accumulation also exhibit interannual variability and trends noticeably larger than the surrounding shelf regions, thereby suggesting that long-term planktonic ecosystem response in the California Current exhibits a significant local scale (O(100 km)) alongshore component.

Towards a high resolution, integrated hydrology model of North America.

NASA Astrophysics Data System (ADS)

Maxwell, R. M.; Condon, L. E.

2015-12-01

Recent studies demonstrate feedbacks between groundwater dynamics, overland flow, land surface and vegetation processes, and atmospheric boundary layer development that significantly affect local and regional climate across a range of climatic conditions. Furthermore, the type and distribution of vegetation cover alters land-atmosphere water and energy fluxes, as well as runoff generation and overland flow processes. These interactions can result in significant feedbacks on local and regional climate. In mountainous regions, recent research has shown that spatial and temporal variability in annual evapotranspiration, and thus water budgets, is strongly dependent on lateral groundwater flow; however, the full effects of these feedbacks across varied terrain (e.g. from plains to mountains) are not well understood. Here, we present a high-resolution, integrated hydrology model that covers much of continental North America and encompasses the Mississippi and Colorado watersheds. The model is run in a fully-transient manner at hourly temporal resolution incorporating fully-coupled land energy states and fluxes with integrated surface and subsurface hydrology. Connections are seen between hydrologic variables (such as water table depth) and land energy fluxes (such as latent heat) and spatial and temporal scaling is shown to span many orders of magnitude. Using these transient simulations as a proof of concept, we present a vision for future integrated simulation capabilities.

Long-term Observations of Intense Precipitation Small-scale Spatial Variability in a Semi-arid Catchment

NASA Astrophysics Data System (ADS)

Cropp, E. L.; Hazenberg, P.; Castro, C. L.; Demaria, E. M.

2017-12-01

In the southwestern US, the summertime North American Monsoon (NAM) provides about 60% of the region's annual precipitation. Recent research using high-resolution atmospheric model simulations and retrospective predictions has shown that since the 1950's, and more specifically in the last few decades, the mean daily precipitation in the southwestern U.S. during the NAM has followed a decreasing trend. Furthermore, days with more extreme precipitation have intensified. The current work focuses the impact of these long-term changes on the observed small-scale spatial variability of intense precipitation. Since limited long-term high-resolution observational data exist to support such climatological-induced spatial changes in precipitation frequency and intensity, the current work utilizes observations from the USDA-ARS Walnut Gulch Experimental Watershed (WGEW) in southeastern Arizona. Within this 150 km^2 catchment over 90 rain gauges have been installed since the 1950s, measuring at sub-hourly resolution. We have applied geospatial analyses and the kriging interpolation technique to identify long-term changes in the spatial and temporal correlation and anisotropy of intense precipitation. The observed results will be compared with the previously model simulated results, as well as related to large-scale variations in climate patterns, such as the El Niño Southern Oscillation (ENSO) and the Pacific Decadal Oscillation (PDO).

Climate Modeling: Ocean Cavities below Ice Shelves

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

Petersen, Mark Roger

The Accelerated Climate Model for Energy (ACME), a new initiative by the U.S. Department of Energy, includes unstructured-mesh ocean, land-ice, and sea-ice components using the Model for Prediction Across Scales (MPAS) framework. The ability to run coupled high-resolution global simulations efficiently on large, high-performance computers is a priority for ACME. Sub-ice shelf ocean cavities are a significant new capability in ACME, and will be used to better understand how changing ocean temperature and currents influence glacial melting and retreat. These simulations take advantage of the horizontal variable-resolution mesh and adaptive vertical coordinate in MPAS-Ocean, in order to place high resolutionmore » below ice shelves and near grounding lines.« less

Regional simulation of Indian summer monsoon intraseasonal oscillations at gray-zone resolution

NASA Astrophysics Data System (ADS)

Chen, Xingchao; Pauluis, Olivier M.; Zhang, Fuqing

2018-01-01

Simulations of the Indian summer monsoon by the cloud-permitting Weather Research and Forecasting (WRF) model at gray-zone resolution are described in this study, with a particular emphasis on the model ability to capture the monsoon intraseasonal oscillations (MISOs). Five boreal summers are simulated from 2007 to 2011 using the ERA-Interim reanalysis as the lateral boundary forcing data. Our experimental setup relies on a horizontal grid spacing of 9 km to explicitly simulate deep convection without the use of cumulus parameterizations. When compared to simulations with coarser grid spacing (27 km) and using a cumulus scheme, the 9 km simulations reduce the biases in mean precipitation and produce more realistic low-frequency variability associated with MISOs. Results show that the model at the 9 km gray-zone resolution captures the salient features of the summer monsoon. The spatial distributions and temporal evolutions of monsoon rainfall in the WRF simulations verify qualitatively well against observations from the Tropical Rainfall Measurement Mission (TRMM), with regional maxima located over Western Ghats, central India, Himalaya foothills, and the west coast of Myanmar. The onset, breaks, and withdrawal of the summer monsoon in each year are also realistically captured by the model. The MISO-phase composites of monsoon rainfall, low-level wind, and precipitable water anomalies in the simulations also agree qualitatively with the observations. Both the simulations and observations show a northeastward propagation of the MISOs, with the intensification and weakening of the Somali Jet over the Arabian Sea during the active and break phases of the Indian summer monsoon.

A new variable parallel holes collimator for scintigraphic device with validation method based on Monte Carlo simulations

NASA Astrophysics Data System (ADS)

Trinci, G.; Massari, R.; Scandellari, M.; Boccalini, S.; Costantini, S.; Di Sero, R.; Basso, A.; Sala, R.; Scopinaro, F.; Soluri, A.

2010-09-01

The aim of this work is to show a new scintigraphic device able to change automatically the length of its collimator in order to adapt the spatial resolution value to gamma source distance. This patented technique replaces the need for collimator change that standard gamma cameras still feature. Monte Carlo simulations represent the best tool in searching new technological solutions for such an innovative collimation structure. They also provide a valid analysis on response of gamma cameras performances as well as on advantages and limits of this new solution. Specifically, Monte Carlo simulations are realized with GEANT4 (GEometry ANd Tracking) framework and the specific simulation object is a collimation method based on separate blocks that can be brought closer and farther, in order to reach and maintain specific spatial resolution values for all source-detector distances. To verify the accuracy and the faithfulness of these simulations, we have realized experimental measurements with identical setup and conditions. This confirms the power of the simulation as an extremely useful tool, especially where new technological solutions need to be studied, tested and analyzed before their practical realization. The final aim of this new collimation system is the improvement of the SPECT techniques, with the real control of the spatial resolution value during tomographic acquisitions. This principle did allow us to simulate a tomographic acquisition of two capillaries of radioactive solution, in order to verify the possibility to clearly distinguish them.

Analysis of the sensitivity to rainfall spatio-temporal variability of an operational urban rainfall-runoff model in a multifractal framework

NASA Astrophysics Data System (ADS)

Gires, A.; Tchiguirinskaia, I.; Schertzer, D. J.; Lovejoy, S.

2011-12-01

In large urban areas, storm water management is a challenge with enlarging impervious areas. Many cities have implemented real time control (RTC) of their urban drainage system to either reduce overflow or limit urban contamination. A basic component of RTC is hydraulic/hydrologic model. In this paper we use the multifractal framework to suggest an innovative way to test the sensitivity of such a model to the spatio-temporal variability of its rainfall input. Indeed the rainfall variability is often neglected in urban context, being considered as a non-relevant issue at the scales involve. Our results show that on the contrary the rainfall variability should be taken into account. Universal multifractals (UM) rely on the concept of multiplicative cascade and are a standard tool to analyze and simulate with a reduced number of parameters geophysical processes that are extremely variable over a wide range of scales. This study is conducted on a 3 400 ha urban area located in Seine-Saint-Denis, in the North of Paris (France). We use the operational semi-distributed model that was calibrated by the local authority (Direction Eau et Assainnissement du 93) that is in charge of urban drainage. The rainfall data comes from the C-Band radar of Trappes operated by Météo-France. The rainfall event of February 9th, 2009 was used. A stochastic ensemble approach was implemented to quantify the uncertainty on discharge associated to the rainfall variability occurring at scales smaller than 1 km x 1 km x 5 min that is usually available with C-band radar networks. An analysis of the quantiles of the simulated peak flow showed that the uncertainty exceeds 20 % for upstream links. To evaluate a potential gain from a direct use of the rainfall data available at the resolution of X-band radar, we performed similar analysis of the rainfall fields of the degraded resolution of 9 km x 9 km x 20 min. The results show a clear decrease in uncertainty when the original resolution of C-band radar data is used. This analysis highlights the interest of implementing X-band radars in urban areas. Indeed such radars provide the rainfall data at a hectometric resolution that would enable a better nowcasting and management of storm water. The multifractal properties of the simulated hydrographs were analysed with the help of simulated rainfall fields of resolution 111 m x 111 m x 1 min, lasting 4 hours, and corresponding to a 5 year return period event. On the whole, the discharge exhibits a good scaling behaviour over the range 4 h - 5 min. Both UM parameters tend to be greater for the discharge than for the rainfall. The notion of maximum probable singularity was used to clarify the consequences on the assessment of extremes. It appears that the urban drainage network basically reproduces the extremes, or only slightly damps them, at least in terms of multifractal statistics. The results were obtained with the financial support from the EU FP7 SMARTesT Project and the Chair "Hydrology for Resilient Cities" (sponsored by Veolia) of Ecole des Ponts ParisTech.

Dynamical downscaling of wind fields for wind power applications

NASA Astrophysics Data System (ADS)

Mengelkamp, H.-T.; Huneke, S.; Geyer, J.

2010-09-01

Dynamical downscaling of wind fields for wind power applications H.-T. Mengelkamp*,**, S. Huneke**, J, Geyer** *GKSS Research Center Geesthacht GmbH **anemos Gesellschaft für Umweltmeteorologie mbH Investments in wind power require information on the long-term mean wind potential and its temporal variations on daily to annual and decadal time scales. This information is rarely available at specific wind farm sites. Short-term on-site measurements usually are only performed over a 12 months period. These data have to be set into the long-term perspective through correlation to long-term consistent wind data sets. Preliminary wind information is often asked for to select favourable wind sites over regional and country wide scales. Lack of high-quality wind measurements at weather stations was the motivation to start high resolution wind field simulations The simulations are basically a refinement of global scale reanalysis data by means of high resolution simulations with an atmospheric mesoscale model using high-resolution terrain and land-use data. The 3-dimensional representation of the atmospheric state available every six hours at 2.5 degree resolution over the globe, known as NCAR/NCEP reanalysis data, forms the boundary conditions for continuous simulations with the non-hydrostatic atmospheric mesoscale model MM5. MM5 is nested in itself down to a horizontal resolution of 5 x 5 km². The simulation is performed for different European countries and covers the period 2000 to present and is continuously updated. Model variables are stored every 10 minutes for various heights. We have analysed the wind field primarily. The wind data set is consistent in space and time and provides information on the regional distribution of the long-term mean wind potential, the temporal variability of the wind potential, the vertical variation of the wind potential, and the temperature, and pressure distribution (air density). In the context of wind power these data are used • as an initial estimate of wind and energy potential • for the long-term correlation of wind measurements and turbine production data • to provide wind potential maps on a regional to country wide scale • to provide input data sets for simulation models • to determine the spatial correlation of the wind field in portfolio calculations • to calculate the wind turbine energy loss during prescribed downtimes • to provide information on the temporal variations of the wind and wind turbine energy production The time series of wind speed and wind direction are compared to measurements at offshore and onshore locations.

Parameter uncertainty in simulations of extreme precipitation and attribution studies.

NASA Astrophysics Data System (ADS)

Timmermans, B.; Collins, W. D.; O'Brien, T. A.; Risser, M. D.

2017-12-01

The attribution of extreme weather events, such as heavy rainfall, to anthropogenic influence involves the analysis of their probability in simulations of climate. The climate models used however, such as the Community Atmosphere Model (CAM), employ approximate physics that gives rise to "parameter uncertainty"—uncertainty about the most accurate or optimal values of numerical parameters within the model. In particular, approximate parameterisations for convective processes are well known to be influential in the simulation of precipitation extremes. Towards examining the impact of this source of uncertainty on attribution studies, we investigate the importance of components—through their associated tuning parameters—of parameterisations relating to deep and shallow convection, and cloud and aerosol microphysics in CAM. We hypothesise that as numerical resolution is increased the change in proportion of variance induced by perturbed parameters associated with the respective components is consistent with the decreasing applicability of the underlying hydrostatic assumptions. For example, that the relative influence of deep convection should diminish as resolution approaches that where convection can be resolved numerically ( 10 km). We quantify the relationship between the relative proportion of variance induced and numerical resolution by conducting computer experiments that examine precipitation extremes over the contiguous U.S. In order to mitigate the enormous computational burden of running ensembles of long climate simulations, we use variable-resolution CAM and employ both extreme value theory and surrogate modelling techniques ("emulators"). We discuss the implications of the relationship between parameterised convective processes and resolution both in the context of attribution studies and progression towards models that fully resolve convection.

Assessing the competing roles of model resolution and meteorological forcing fidelity in hyperresolution simulations of snowpack and streamflow in the southern Rocky Mountains

NASA Astrophysics Data System (ADS)

Gochis, D. J.; Dugger, A. L.; Karsten, L. R.; Barlage, M. J.; Sampson, K. M.; Yu, W.; Pan, L.; McCreight, J. L.; Howard, K.; Busto, J.; Deems, J. S.

2017-12-01

Hydrometeorological processes vary over comparatively short length scales in regions of complex terrain such as the southern Rocky Mountains. Changes in temperature, precipitation, wind and solar radiation can vary significantly across elevation gradients, terrain landform and land cover conditions throughout the region. Capturing such variability in hydrologic models can necessitate the utilization of so-called `hyper-resolution' spatial meshes with effective element spacings of less than 100m. However, it is often difficult to obtain meteorological forcings of high quality in such regions at those resolutions which can result in significant uncertainty in fundamental in hydrologic model inputs. In this study we examine the comparative influences of meteorological forcing data fidelity and spatial resolution on seasonal simulations of snowpack evolution, runoff and streamflow in a set of high mountain watersheds in southern Colorado. We utilize the operational, NOAA National Water Model configuration of the community WRF-Hydro system as a baseline and compare against it, additional model scenarios with differing specifications of meteorological forcing data, with and without topographic downscaling adjustments applied, with and without experimental high resolution radar derived precipitation estimates and with WRF-Hydro configurations of progressively finer spatial resolution. The results suggest significant influence from and importance of meteorological downscaling techniques in controlling spatial distributions of meltout and runoff timing. The use of radar derived precipitation exhibits clear sensitivity on hydrologic simulation skill compared with the use of coarser resolution, background precipitation analyses. Advantages and disadvantages of the utilization of progressively higher resolution model configurations both in terms of computational requirements and model fidelity are also discussed.

The Effect of Rainfall Measurement Technique and Its Spatiotemporal Resolution on Discharge Predictions in the Netherlands

NASA Astrophysics Data System (ADS)

Uijlenhoet, R.; Brauer, C.; Overeem, A.; Sassi, M.; Rios Gaona, M. F.

2014-12-01

Several rainfall measurement techniques are available for hydrological applications, each with its own spatial and temporal resolution. We investigated the effect of these spatiotemporal resolutions on discharge simulations in lowland catchments by forcing a novel rainfall-runoff model (WALRUS) with rainfall data from gauges, radars and microwave links. The hydrological model used for this analysis is the recently developed Wageningen Lowland Runoff Simulator (WALRUS). WALRUS is a rainfall-runoff model accounting for hydrological processes relevant to areas with shallow groundwater (e.g. groundwater-surface water feedback). Here, we used WALRUS for case studies in a freely draining lowland catchment and a polder with controlled water levels. We used rain gauge networks with automatic (hourly resolution but low spatial density) and manual gauges (high spatial density but daily resolution). Operational (real-time) and climatological (gauge-adjusted) C-band radar products and country-wide rainfall maps derived from microwave link data from a cellular telecommunication network were also used. Discharges simulated with these different inputs were compared to observations. We also investigated the effect of spatiotemporal resolution with a high-resolution X-band radar data set for catchments with different sizes. Uncertainty in rainfall forcing is a major source of uncertainty in discharge predictions, both with lumped and with distributed models. For lumped rainfall-runoff models, the main source of input uncertainty is associated with the way in which (effective) catchment-average rainfall is estimated. When catchments are divided into sub-catchments, rainfall spatial variability can become more important, especially during convective rainfall events, leading to spatially varying catchment wetness and spatially varying contribution of quick flow routes. Improving rainfall measurements and their spatiotemporal resolution can improve the performance of rainfall-runoff models, indicating their potential for reducing flood damage through real-time control.

LOOPREF: A Fluid Code for the Simulation of Coronal Loops

NASA Technical Reports Server (NTRS)

deFainchtein, Rosalinda; Antiochos, Spiro; Spicer, Daniel

1998-01-01

This report documents the code LOOPREF. LOOPREF is a semi-one dimensional finite element code that is especially well suited to simulate coronal-loop phenomena. It has a full implementation of adaptive mesh refinement (AMR), which is crucial for this type of simulation. The AMR routines are an improved version of AMR1D. LOOPREF's versatility makes is suitable to simulate a wide variety of problems. In addition to efficiently providing very high resolution in rapidly changing regions of the domain, it is equipped to treat loops of variable cross section, any non-linear form of heat conduction, shocks, gravitational effects, and radiative loss.

Hydrologic impacts of land cover variability and change at seasonal to decadal time scales over North America, 1992-2016

NASA Astrophysics Data System (ADS)

Bohn, T. J.; Vivoni, E. R.

2017-12-01

Land cover variability and change have been shown to influence the terrestrial hydrologic cycle by altering the partitioning of moisture and energy fluxes. However, the magnitude and directionality of the relationship between land cover and surface hydrology has been shown to vary substantially across regions. Here, we provide an assessment of the impacts of land cover change on hydrologic processes at seasonal (vegetation phenology) to decadal scales (land cover conversion) in the United States and Mexico. To this end, we combine time series of remotely-sensed land surface characteristics with land cover maps for different decades as input to the Variable Infiltration Capacity hydrologic model. Land surface characteristics (leaf area index, surface albedo, and canopy fraction derived from normalized difference vegetation index) were obtained from the Moderate Resolution Imaging Spectrometer (MODIS) at 8-day intervals over the period 2000-2016. Land cover maps representing conditions in 1992, 2001, and 2011 were derived by homogenizing the National Land Cover Database over the US and the INEGI Series I through V maps over Mexico. An additional map covering all of North America was derived from the most frequent land cover class observed in each pixel of the MODIS MOD12Q1 product during 2001-2013. Land surface characteristics were summarized over land cover fractions at 1/16 degree (6 km) resolution. For each land cover map, hydrologic simulations were conducted that covered the period 1980-2013, using the best-available, hourly meteorological forcings at a similar spatial resolution. Based on these simulations, we present a comparison of the contributions of land cover change and climate variability at seasonal to decadal scales on the hydrologic and energy budgets, identifying the dominant components through time and space. This work also offers a valuable dataset on land cover variability and its hydrologic response for continental-scale assessments and modeling.

Influence of high-resolution surface databases on the modeling of local atmospheric circulation systems

NASA Astrophysics Data System (ADS)

Paiva, L. M. S.; Bodstein, G. C. R.; Pimentel, L. C. G.

2013-12-01

Large-eddy simulations are performed using the Advanced Regional Prediction System (ARPS) code at horizontal grid resolutions as fine as 300 m to assess the influence of detailed and updated surface databases on the modeling of local atmospheric circulation systems of urban areas with complex terrain. Applications to air pollution and wind energy are sought. These databases are comprised of 3 arc-sec topographic data from the Shuttle Radar Topography Mission, 10 arc-sec vegetation type data from the European Space Agency (ESA) GlobCover Project, and 30 arc-sec Leaf Area Index and Fraction of Absorbed Photosynthetically Active Radiation data from the ESA GlobCarbon Project. Simulations are carried out for the Metropolitan Area of Rio de Janeiro using six one-way nested-grid domains that allow the choice of distinct parametric models and vertical resolutions associated to each grid. ARPS is initialized using the Global Forecasting System with 0.5°-resolution data from the National Center of Environmental Prediction, which is also used every 3 h as lateral boundary condition. Topographic shading is turned on and two soil layers with depths of 0.01 and 1.0 m are used to compute the soil temperature and moisture budgets in all runs. Results for two simulated runs covering the period from 6 to 7 September 2007 are compared to surface and upper-air observational data to explore the dependence of the simulations on initial and boundary conditions, topographic and land-use databases and grid resolution. Our comparisons show overall good agreement between simulated and observed data and also indicate that the low resolution of the 30 arc-sec soil database from United States Geological Survey, the soil moisture and skin temperature initial conditions assimilated from the GFS analyses and the synoptic forcing on the lateral boundaries of the finer grids may affect an adequate spatial description of the meteorological variables.

Simulation and optimization of a dc SQUID with finite capacitance

NASA Astrophysics Data System (ADS)

de Waal, V. J.; Schrijner, P.; Llurba, R.

1984-02-01

This paper deals with the calculations of the noise and the optimization of the energy resolution of a dc SQUID with finite junction capacitance. Up to now noise calculations of dc SQUIDs were performed using a model without parasitic capacitances across the Josephson junctions. As the capacitances limit the performance of the SQUID, for a good optimization one must take them into account. The model consists of two coupled nonlinear second-order differential equations. The equations are very suitable for simulation with an analog circuit. We implemented the model on a hybrid computer. The noise spectrum from the model is calculated with a fast Fourier transform. A calculation of the energy resolution for one set of parameters takes about 6 min of computer time. Detailed results of the optimization are given for products of inductance and temperature of LT=1.2 and 5 nH K. Within a range of β and β c between 1 and 2, which is optimum, the energy resolution is nearly independent of these variables. In this region the energy resolution is near the value calculated without parasitic capacitances. Results of the optimized energy resolution are given as a function of LT between 1.2 and 10 mH K.

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

NASA Astrophysics Data System (ADS)

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.

MetMSLine: an automated and fully integrated pipeline for rapid processing of high-resolution LC-MS metabolomic datasets.

PubMed

Edmands, William M B; Barupal, Dinesh K; Scalbert, Augustin

2015-03-01

MetMSLine represents a complete collection of functions in the R programming language as an accessible GUI for biomarker discovery in large-scale liquid-chromatography high-resolution mass spectral datasets from acquisition through to final metabolite identification forming a backend to output from any peak-picking software such as XCMS. MetMSLine automatically creates subdirectories, data tables and relevant figures at the following steps: (i) signal smoothing, normalization, filtration and noise transformation (PreProc.QC.LSC.R); (ii) PCA and automatic outlier removal (Auto.PCA.R); (iii) automatic regression, biomarker selection, hierarchical clustering and cluster ion/artefact identification (Auto.MV.Regress.R); (iv) Biomarker-MS/MS fragmentation spectra matching and fragment/neutral loss annotation (Auto.MS.MS.match.R) and (v) semi-targeted metabolite identification based on a list of theoretical masses obtained from public databases (DBAnnotate.R). All source code and suggested parameters are available in an un-encapsulated layout on http://wmbedmands.github.io/MetMSLine/. Readme files and a synthetic dataset of both X-variables (simulated LC-MS data), Y-variables (simulated continuous variables) and metabolite theoretical masses are also available on our GitHub repository. © The Author 2014. Published by Oxford University Press.

MetMSLine: an automated and fully integrated pipeline for rapid processing of high-resolution LC–MS metabolomic datasets

PubMed Central

Edmands, William M. B.; Barupal, Dinesh K.; Scalbert, Augustin

2015-01-01

Summary: MetMSLine represents a complete collection of functions in the R programming language as an accessible GUI for biomarker discovery in large-scale liquid-chromatography high-resolution mass spectral datasets from acquisition through to final metabolite identification forming a backend to output from any peak-picking software such as XCMS. MetMSLine automatically creates subdirectories, data tables and relevant figures at the following steps: (i) signal smoothing, normalization, filtration and noise transformation (PreProc.QC.LSC.R); (ii) PCA and automatic outlier removal (Auto.PCA.R); (iii) automatic regression, biomarker selection, hierarchical clustering and cluster ion/artefact identification (Auto.MV.Regress.R); (iv) Biomarker—MS/MS fragmentation spectra matching and fragment/neutral loss annotation (Auto.MS.MS.match.R) and (v) semi-targeted metabolite identification based on a list of theoretical masses obtained from public databases (DBAnnotate.R). Availability and implementation: All source code and suggested parameters are available in an un-encapsulated layout on http://wmbedmands.github.io/MetMSLine/. Readme files and a synthetic dataset of both X-variables (simulated LC–MS data), Y-variables (simulated continuous variables) and metabolite theoretical masses are also available on our GitHub repository. Contact: ScalbertA@iarc.fr PMID:25348215

Comparing large-scale hydrological model predictions with observed streamflow in the Pacific Northwest: effects of climate and groundwater

Treesearch

Mohammad Safeeq; Guillaume S. Mauger; Gordon E. Grant; Ivan Arismendi; Alan F. Hamlet; Se-Yeun Lee

2014-01-01

Assessing uncertainties in hydrologic models can improve accuracy in predicting future streamflow. Here, simulated streamflows using the Variable Infiltration Capacity (VIC) model at coarse (1/16°) and fine (1/120°) spatial resolutions were evaluated against observed streamflows from 217 watersheds. In...

Pathways of Atlantic Waters in the Nordic seas: locally eddy-permitting ocean simulation in a global setup

NASA Astrophysics Data System (ADS)

Wekerle, C.; Wang, Q.; Danilov, S.; Jung, T.; Schourup-Kristensen, V.

2016-02-01

Atlantic Water (AW) passes through the Nordic Seas and enters the Arctic Ocean through the shallow Barents Sea and the deep Fram Strait. Since the 1990's, observations indicate a series of anomalously warm pulses of Atlantic Water that entered the Arctic Ocean. In fact, poleward oceanic heat transport may even increase in the future, which might have implications for the heat uptake in the Arctic Ocean as well as for the sea ice cover. The ability of models to faithfully simulate the pathway of the AW and accompanying dynamics is thus of high climate relevance. In this study, we explore the potential of a global multi-resolution sea ice-ocean model with a locally eddy-permitting resolution (around 4.5 km) in the Nordic seas region and Arctic Ocean in improving the representation of Atlantic Water inflow, and more broadly, the dynamics of the circulation in the Northern North Atlantic and Arctic. The simulation covers the time period 1969-2009. We find that locally increased resolution improves the localization and thickness of the Atlantic Water layer in the Nordic seas, compared with a 20 km resolution reference simulation. In particular, the inflow of Atlantic Waters through the Greenland Scotland Ridge and the narrow branches of the Norwegian Atlantic Current can be realistically represented. Lateral spreading due to simulated eddies essentially reduces the bias in the surface temperature. In addition, a qualitatively good agreement of the simulated eddy kinetic energy field with observations can be achieved. This study indicates that a substantial improvement in representing local ocean dynamics can be reached through the local refinement, which requires a rather moderate computational effort. The successful model assessment allows us to further investigate the variability and mechanisms behind Atlantic Water transport into the Arctic Ocean.

Simulation of semi-arid hydrological processes at different spatial resolutions using the AgroEcoSystem-Watershed (AgES-W) model

NASA Astrophysics Data System (ADS)

Green, T. R.; Erksine, R. H.; David, O.; Ascough, J. C., II; Kipka, H.; Lloyd, W. J.; McMaster, G. S.

2015-12-01

Water movement and storage within a watershed may be simulated at different spatial resolutions of land areas or hydrological response units (HRUs). Here, effects of HRU size on simulated soil water and surface runoff are tested using the AgroEcoSystem-Watershed (AgES-W) model with three different resolutions of HRUs. We studied a 56-ha agricultural watershed in northern Colorado, USA farmed primarily under a wheat-fallow rotation. The delineation algorithm was based upon topography (surface flow paths), land use (crop management strips and native grass), and mapped soil units (three types), which produced HRUs that follow the land use and soil boundaries. AgES-W model parameters that control surface and subsurface hydrology were calibrated using simulated daily soil moisture at different landscape positions and depths where soil moisture was measured hourly and averaged up to daily values. Parameter sets were both uniform and spatially variable with depth and across the watershed (5 different calibration approaches). Although forward simulations were computationally efficient (less than 1 minute each), each calibration required thousands of model runs. Execution of such large jobs was facilitated by using the Object Modeling System with the Cloud Services Innovation Platform to manage four virtual machines on a commercial web service configured with a total of 64 computational cores and 120 GB of memory. Results show how spatially distributed and averaged soil moisture and runoff at the outlet vary with different HRU delineations. The results will help guide HRU delineation, spatial resolution and parameter estimation methods for improved hydrological simulations in this and other semi-arid agricultural watersheds.

Moderate effect of damming the Romaine River (Quebec, Canada) on coastal plankton dynamics

NASA Astrophysics Data System (ADS)

Senneville, Simon; Schloss, Irene R.; St-Onge Drouin, Simon; Bélanger, Simon; Winkler, Gesche; Dumont, Dany; Johnston, Patricia; St-Onge, Isabelle

2018-04-01

Rivers' damming disrupts the seasonal cycle of freshwater and nutrient inputs into the marine system, which can lead to changes in coastal plankton dynamics. Here we use a 3-D 5-km resolution coupled biophysical model and downscale it to a 400-m resolution to simulate the effect of damming the Romaine River in Québec, Canada, which discharges on average 327 m3 s-1 of freshwater into the northern Gulf of St. Lawrence. Model results are compared with environmental data obtained from 2 buoys and in situ sampling near the Romaine River mouth during the 2013 spring-summer period. Noteworthy improvements are made to the light attenuation parametrization and the trophic links of the biogeochemical model. The modelled variables reproduced most of the observed levels of variability. Comparisons between natural and regulated discharge simulation show differences in primary production and in the dominance of plankton groups in the Romaine River plume. The maximum increase in primary production when averaged over the inner part of Mingan Archipelago is 41%, but 7.1% when the primary production anomaly is averaged from March to September.

Novel detector design for reducing intercell x-ray cross-talk in the variable resolution x-ray CT scanner: a Monte Carlo study.

PubMed

Arabi, Hosein; Asl, Ali Reza Kamali; Ay, Mohammad Reza; Zaidi, Habib

2011-03-01

The variable resolution x-ray (VRX) CT scanner provides substantial improvement in the spatial resolution by matching the scanner's field of view (FOV) to the size of the object being imaged. Intercell x-ray cross-talk is one of the most important factors limiting the spatial resolution of the VRX detector. In this work, a new cell arrangement in the VRX detector is suggested to decrease the intercell x-ray cross-talk. The idea is to orient the detector cells toward the opening end of the detector. Monte Carlo simulations were used for performance assessment of the oriented cell detector design. Previously published design parameters and simulation results of x-ray cross-talk for the VRX detector were used for model validation using the GATE Monte Carlo package. In the first step, the intercell x-ray cross-talk of the actual VRX detector model was calculated as a function of the FOV. The obtained results indicated an optimum cell orientation angle of 28 degrees to minimize the x-ray cross-talk in the VRX detector. Thereafter, the intercell x-ray cross-talk in the oriented cell detector was modeled and quantified. The intercell x-ray cross-talk in the actual detector model was considerably high, reaching up to 12% at FOVs from 24 to 38 cm. The x-ray cross-talk in the oriented cell detector was less than 5% for all possible FOVs, except 40 cm (maximum FOV). The oriented cell detector could provide considerable decrease in the intercell x-ray cross-talk for the VRX detector, thus leading to significant improvement in the spatial resolution and reduction in the spatial resolution nonuniformity across the detector length. The proposed oriented cell detector is the first dedicated detector design for the VRX CT scanners. Application of this concept to multislice and flat-panel VRX detectors would also result in higher spatial resolution.

Surface Wind and Upper-Ocean Variability Associated with the Madden-Julian Oscillation Simulated by the Coupled Ocean-Atmosphere Mesoscale Prediction System

DTIC Science & Technology

2013-07-01

observed data at one location include variability caused by small -scale atmospheric convec- tion and wind variations that cannot be resolved by the... data sources, gathering and maintaining the data needed, and completing and reviewing the collection of information. Send comments regarding this...high-resolution nested grid (9 km) for the atmospheric component is used for the central Indian Ocean. While observational data are assimilated into the

Coupling a three-dimensional subsurface flow model with a land surface model to simulate stream-aquifer-land interactions

NASA Astrophysics Data System (ADS)

Huang, M.; Bisht, G.; Zhou, T.; Chen, X.; Dai, H.; Hammond, G. E.; Riley, W. J.; Downs, J.; Liu, Y.; Zachara, J. M.

2016-12-01

A fully coupled three-dimensional surface and subsurface land model is developed and applied to a site along the Columbia River to simulate three-way interactions among river water, groundwater, and land surface processes. The model features the coupling of the Community Land Model version 4.5 (CLM4.5) and a massively-parallel multi-physics reactive tranport model (PFLOTRAN). The coupled model (CLM-PFLOTRAN) is applied to a 400m×400m study domain instrumented with groundwater monitoring wells in the Hanford 300 Area along the Columbia River. CLM-PFLOTRAN simulations are performed at three different spatial resolutions over the period 2011-2015 to evaluate the impact of spatial resolution on simulated variables. To demonstrate the difference in model simulations with and without lateral subsurface flow, a vertical-only CLM-PFLOTRAN simulation is also conducted for comparison. Results show that the coupled model is skillful in simulating stream-aquifer interactions, and the land-surface energy partitioning can be strongly modulated by groundwater-river water interactions in high water years due to increased soil moisture availability caused by elevated groundwater table. In addition, spatial resolution does not seem to impact the land surface energy flux simulations, although it is a key factor for accurately estimating the mass exchange rates at the boundaries and associated biogeochemical reactions in the aquifer. The coupled model developed in this study establishes a solid foundation for understanding co-evolution of hydrology and biogeochemistry along the river corridors under historical and future hydro-climate changes.

Variability and Dynamics of the Yucatan Upwelling: High-Resolution Simulations

NASA Astrophysics Data System (ADS)

Jouanno, J.; Pallàs-Sanz, E.; Sheinbaum, J.

2018-02-01

The Yucatan shelf in the southern Gulf of Mexico is under the influence of an upwelling that uplifts cool and nutrient rich waters over the continental shelf. The analysis of a set of high-resolution (Δx = Δy ≈ 2.8 km) simulations of the Gulf of Mexico shows two dominant modes of variability of the Yucatan upwelling system: (1) a low-frequency mode related to variations in position and intensity of the Loop Current along the shelf, with upwelling intensified when the Loop Current is strong and approaches to the Yucatan shelf break and (2) a high-frequency mode with peak frequency in the 6-10 days band related to wind-forced coastal waves that force vertical velocities along the eastern Yucatan shelf break. To first order, the strength and position of the Loop Current are found to control the intensity of the upwelling, but we show that high-frequency winds also contribute (˜17%) to a net input of cool waters (<22.5°C) on the Yucatan shelf. Finally, although more observational studies are needed to corroborate the topographic character of the Yucatan upwelling system, this study reveals the key role played by a notch along the Yucatan shelf break: a sensitivity simulation without the notch shows a 55% reduction of the upwelling.

Alternative techniques for high-resolution spectral estimation of spectrally encoded endoscopy

NASA Astrophysics Data System (ADS)

Mousavi, Mahta; Duan, Lian; Javidi, Tara; Ellerbee, Audrey K.

2015-09-01

Spectrally encoded endoscopy (SEE) is a minimally invasive optical imaging modality capable of fast confocal imaging of internal tissue structures. Modern SEE systems use coherent sources to image deep within the tissue and data are processed similar to optical coherence tomography (OCT); however, standard processing of SEE data via the Fast Fourier Transform (FFT) leads to degradation of the axial resolution as the bandwidth of the source shrinks, resulting in a well-known trade-off between speed and axial resolution. Recognizing the limitation of FFT as a general spectral estimation algorithm to only take into account samples collected by the detector, in this work we investigate alternative high-resolution spectral estimation algorithms that exploit information such as sparsity and the general region position of the bulk sample to improve the axial resolution of processed SEE data. We validate the performance of these algorithms using bothMATLAB simulations and analysis of experimental results generated from a home-built OCT system to simulate an SEE system with variable scan rates. Our results open a new door towards using non-FFT algorithms to generate higher quality (i.e., higher resolution) SEE images at correspondingly fast scan rates, resulting in systems that are more accurate and more comfortable for patients due to the reduced image time.

Parameterizing deep convection using the assumed probability density function method

DOE PAGES

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

2014-06-11

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

Parameterizing deep convection using the assumed probability density function method

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

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

2015-01-06

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

Parameterizing deep convection using the assumed probability density function method

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

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

2015-01-06

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

Techniques and resources for storm-scale numerical weather prediction

NASA Technical Reports Server (NTRS)

Droegemeier, Kelvin; Grell, Georg; Doyle, James; Soong, Su-Tzai; Skamarock, William; Bacon, David; Staniforth, Andrew; Crook, Andrew; Wilhelmson, Robert

1993-01-01

The topics discussed include the following: multiscale application of the 5th-generation PSU/NCAR mesoscale model, the coupling of nonhydrostatic atmospheric and hydrostatic ocean models for air-sea interaction studies; a numerical simulation of cloud formation over complex topography; adaptive grid simulations of convection; an unstructured grid, nonhydrostatic meso/cloud scale model; efficient mesoscale modeling for multiple scales using variable resolution; initialization of cloud-scale models with Doppler radar data; and making effective use of future computing architectures, networks, and visualization software.

Comparison of VRX CT scanners geometries

NASA Astrophysics Data System (ADS)

DiBianca, Frank A.; Melnyk, Roman; Duckworth, Christopher N.; Russ, Stephan; Jordan, Lawrence M.; Laughter, Joseph S.

2001-06-01

A technique called Variable-Resolution X-ray (VRX) detection greatly increases the spatial resolution in computed tomography (CT) and digital radiography (DR) as the field size decreases. The technique is based on a principle called `projective compression' that allows both the resolution element and the sampling distance of a CT detector to scale with the subject or field size. For very large (40 - 50 cm) field sizes, resolution exceeding 2 cy/mm is possible and for very small fields, microscopy is attainable with resolution exceeding 100 cy/mm. This paper compares the benefits obtainable with two different VRX detector geometries: the single-arm geometry and the dual-arm geometry. The analysis is based on Monte Carlo simulations and direct calculations. The results of this study indicate that the dual-arm system appears to have more advantages than the single-arm technique.

Resolution of ab initio shapes determined from small-angle scattering.

PubMed

Tuukkanen, Anne T; Kleywegt, Gerard J; Svergun, Dmitri I

2016-11-01

Spatial resolution is an important characteristic of structural models, and the authors of structures determined by X-ray crystallography or electron cryo-microscopy always provide the resolution upon publication and deposition. Small-angle scattering of X-rays or neutrons (SAS) has recently become a mainstream structural method providing the overall three-dimensional structures of proteins, nucleic acids and complexes in solution. However, no quantitative resolution measure is available for SAS-derived models, which significantly hampers their validation and further use. Here, a method is derived for resolution assessment for ab initio shape reconstruction from scattering data. The inherent variability of the ab initio shapes is utilized and it is demonstrated how their average Fourier shell correlation function is related to the model resolution. The method is validated against simulated data for proteins with known high-resolution structures and its efficiency is demonstrated in applications to experimental data. It is proposed that henceforth the resolution be reported in publications and depositions of ab initio SAS models.

Resolution of ab initio shapes determined from small-angle scattering

PubMed Central

Tuukkanen, Anne T.; Kleywegt, Gerard J.; Svergun, Dmitri I.

2016-01-01

Spatial resolution is an important characteristic of structural models, and the authors of structures determined by X-ray crystallography or electron cryo-microscopy always provide the resolution upon publication and deposition. Small-angle scattering of X-rays or neutrons (SAS) has recently become a mainstream structural method providing the overall three-dimensional structures of proteins, nucleic acids and complexes in solution. However, no quantitative resolution measure is available for SAS-derived models, which significantly hampers their validation and further use. Here, a method is derived for resolution assessment for ab initio shape reconstruction from scattering data. The inherent variability of the ab initio shapes is utilized and it is demonstrated how their average Fourier shell correlation function is related to the model resolution. The method is validated against simulated data for proteins with known high-resolution structures and its efficiency is demonstrated in applications to experimental data. It is proposed that henceforth the resolution be reported in publications and depositions of ab initio SAS models. PMID:27840683

Impact of respiratory motion correction and spatial resolution on lesion detection in PET: a simulation study based on real MR dynamic data

NASA Astrophysics Data System (ADS)

Polycarpou, Irene; Tsoumpas, Charalampos; King, Andrew P.; Marsden, Paul K.

2014-02-01

The aim of this study is to investigate the impact of respiratory motion correction and spatial resolution on lesion detectability in PET as a function of lesion size and tracer uptake. Real respiratory signals describing different breathing types are combined with a motion model formed from real dynamic MR data to simulate multiple dynamic PET datasets acquired from a continuously moving subject. Lung and liver lesions were simulated with diameters ranging from 6 to 12 mm and lesion to background ratio ranging from 3:1 to 6:1. Projection data for 6 and 3 mm PET scanner resolution were generated using analytic simulations and reconstructed without and with motion correction. Motion correction was achieved using motion compensated image reconstruction. The detectability performance was quantified by a receiver operating characteristic (ROC) analysis obtained using a channelized Hotelling observer and the area under the ROC curve (AUC) was calculated as the figure of merit. The results indicate that respiratory motion limits the detectability of lung and liver lesions, depending on the variation of the breathing cycle length and amplitude. Patients with large quiescent periods had a greater AUC than patients with regular breathing cycles and patients with long-term variability in respiratory cycle or higher motion amplitude. In addition, small (less than 10 mm diameter) or low contrast (3:1) lesions showed the greatest improvement in AUC as a result of applying motion correction. In particular, after applying motion correction the AUC is improved by up to 42% with current PET resolution (i.e. 6 mm) and up to 51% for higher PET resolution (i.e. 3 mm). Finally, the benefit of increasing the scanner resolution is small unless motion correction is applied. This investigation indicates high impact of respiratory motion correction on lesion detectability in PET and highlights the importance of motion correction in order to benefit from the increased resolution of future PET scanners.

Assessment of summer rainfall forecast skill in the Intra-Americas in GFDL high and low-resolution models

NASA Astrophysics Data System (ADS)

Krishnamurthy, Lakshmi; Muñoz, Ángel G.; Vecchi, Gabriel A.; Msadek, Rym; Wittenberg, Andrew T.; Stern, Bill; Gudgel, Rich; Zeng, Fanrong

2018-05-01

The Caribbean low-level jet (CLLJ) is an important component of the atmospheric circulation over the Intra-Americas Sea (IAS) which impacts the weather and climate both locally and remotely. It influences the rainfall variability in the Caribbean, Central America, northern South America, the tropical Pacific and the continental Unites States through the transport of moisture. We make use of high-resolution coupled and uncoupled models from the Geophysical Fluid Dynamics Laboratory (GFDL) to investigate the simulation of the CLLJ and its teleconnections and further compare with low-resolution models. The high-resolution coupled model FLOR shows improvements in the simulation of the CLLJ and its teleconnections with rainfall and SST over the IAS compared to the low-resolution coupled model CM2.1. The CLLJ is better represented in uncoupled models (AM2.1 and AM2.5) forced with observed sea-surface temperatures (SSTs), emphasizing the role of SSTs in the simulation of the CLLJ. Further, we determine the forecast skill for observed rainfall using both high- and low-resolution predictions of rainfall and SSTs for the July-August-September season. We determine the role of statistical correction of model biases, coupling and horizontal resolution on the forecast skill. Statistical correction dramatically improves area-averaged forecast skill. But the analysis of spatial distribution in skill indicates that the improvement in skill after statistical correction is region dependent. Forecast skill is sensitive to coupling in parts of the Caribbean, Central and northern South America, and it is mostly insensitive over North America. Comparison of forecast skill between high and low-resolution coupled models does not show any dramatic difference. However, uncoupled models show improvement in the area-averaged skill in the high-resolution atmospheric model compared to lower resolution model. Understanding and improving the forecast skill over the IAS has important implications for highly vulnerable nations in the region.

Role of resolution in regional climate change projections over China

NASA Astrophysics Data System (ADS)

Shi, Ying; Wang, Guiling; Gao, Xuejie

2017-11-01

This paper investigates the sensitivity of projected future climate changes over China to the horizontal resolution of a regional climate model RegCM4.4 (RegCM), using RCP8.5 as an example. Model validation shows that RegCM performs better in reproducing the spatial distribution and magnitude of present-day temperature, precipitation and climate extremes than the driving global climate model HadGEM2-ES (HadGEM, at 1.875° × 1.25° degree resolution), but little difference is found between the simulations at 50 and 25 km resolutions. Comparison with observational data at different resolutions confirmed the added value of the RCM and finer model resolutions in better capturing the probability distribution of precipitation. However, HadGEM and RegCM at both resolutions project a similar pattern of significant future warming during both winter and summer, and a similar pattern of winter precipitation changes including dominant increase in most areas of northern China and little change or decrease in the southern part. Projected precipitation changes in summer diverge among the three models, especially over eastern China, with a general increase in HadGEM, little change in RegCM at 50 km, and a mix of increase and decrease in RegCM at 25 km resolution. Changes of temperature-related extremes (annual total number of daily maximum temperature > 25 °C, the maximum value of daily maximum temperature, the minimum value of daily minimum temperature in the three simulations especially in the two RegCM simulations are very similar to each other; so are the precipitation-related extremes (maximum consecutive dry days, maximum consecutive 5-day precipitation and extremely wet days' total amount). Overall, results from this study indicate a very low sensitivity of projected changes in this region to model resolution. While fine resolution is critical for capturing the spatial variability of the control climate, it may not be as important for capturing the climate response to homogeneous forcing (in this case greenhouse gas concentration changes).

Verification of High Resolution Soil Moisture and Latent Heat in Germany

NASA Astrophysics Data System (ADS)

Samaniego, L. E.; Warrach-Sagi, K.; Zink, M.; Wulfmeyer, V.

2012-12-01

Improving our understanding of soil-land-surface-atmosphere feedbacks is fundamental to make reliable predictions of water and energy fluxes on land systems influenced by anthropogenic activities. Estimating, for instance, which would be the likely consequences of changing climatic regimes on water availability and crop yield, requires of high resolution soil moisture. Modeling it at large-scales, however, is difficult and uncertain because of the interplay between state variables and fluxes and the significant parameter uncertainty of the predicting models. At larger scales, the sub-grid variability of the variables involved and the nonlinearity of the processes complicate the modeling exercise even further because parametrization schemes might be scale dependent. Two contrasting modeling paradigms (WRF/Noah-MP and mHM) were employed to quantify the effects of model and data complexity on soil moisture and latent heat over Germany. WRF/Noah-MP was forced ERA-interim on the boundaries of the rotated CORDEX-Grid (www.meteo.unican.es/wiki/cordexwrf) with a spatial resolution of 0.11o covering Europe during the period from 1989 to 2009. Land cover and soil texture were represented in WRF/Noah-MP with 1×1~km MODIS images and a single horizon, coarse resolution European-wide soil map with 16 soil texture classes, respectively. To ease comparison, the process-based hydrological model mHM was forced with daily precipitation and temperature fields generated by WRF during the same period. The spatial resolution of mHM was fixed at 4×4~km. The multiscale parameter regionalization technique (MPR, Samaniego et al. 2010) was embedded in mHM to be able to estimate effective model parameters using hyper-resolution input data (100×100~km) obtained from Corine land cover and detailed soil texture fields for various horizons comprising 72 soil texture classes for Germany, among other physiographical variables. mHM global parameters, in contrast with those of Noah-MP, were obtained by closing the water balance over major river basins in Germany. Simulated soil moisture and latent heat flux were also evaluated at several eddy covariance sites in Germany. Comparison of monthly soil moisture and latent heat fields obtained with both models over Germany exhibited significant differences, which are mainly attributed to the subgrid variability of key model parameters such as porosity and aerodynamic resistance. Comparison of soil moisture fields obtained with WRF/Noah-MP and mHM forced with grided metereological observations (German Meteorological Service) showed that the differences between both models are mainly due to a combination of precipitation bias and different soil texture resolution. However, EOF analyses indicate that CORDEX results start recovering structures due to soil and vegetation properties. This experiment clearly highlighted the importance of hyper resolution input data to address these challenge. High resolution mHM simulations also indicate that the parametric uncertainty of land surface models is significant, and should not be neglected if a model is to be employed for application at regional scales, e.g. for drought monitoring.

Importance of ocean mesoscale variability for air-sea interactions in the Gulf of Mexico

NASA Astrophysics Data System (ADS)

Putrasahan, D. A.; Kamenkovich, I.; Le Hénaff, M.; Kirtman, B. P.

2017-06-01

Mesoscale variability of currents in the Gulf of Mexico (GoM) can affect oceanic heat advection and air-sea heat exchanges, which can influence climate extremes over North America. This study is aimed at understanding the influence of the oceanic mesoscale variability on the lower atmosphere and air-sea heat exchanges. The study contrasts global climate model (GCM) with 0.1° ocean resolution (high resolution; HR) with its low-resolution counterpart (1° ocean resolution with the same 0.5° atmosphere resolution; LR). The LR simulation is relevant to current generation of GCMs that are still unable to resolve the oceanic mesoscale. Similar to observations, HR exhibits positive correlation between sea surface temperature (SST) and surface turbulent heat flux anomalies, while LR has negative correlation. For HR, we decompose lateral advective heat fluxes in the upper ocean into mean (slowly varying) and mesoscale-eddy (fast fluctuations) components. We find that the eddy flux divergence/convergence dominates the lateral advection and correlates well with the SST anomalies and air-sea latent heat exchanges. This result suggests that oceanic mesoscale advection supports warm SST anomalies that in turn feed surface heat flux. We identify anticyclonic warm-core circulation patterns (associated Loop Current and rings) which have an average diameter of 350 km. These warm anomalies are sustained by eddy heat flux convergence at submonthly time scales and have an identifiable imprint on surface turbulent heat flux, atmospheric circulation, and convective precipitation in the northwest portion of an averaged anticyclone.

Lightning Forcing in Global Fire Models: The Importance of Temporal Resolution

NASA Astrophysics Data System (ADS)

Felsberg, A.; Kloster, S.; Wilkenskjeld, S.; Krause, A.; Lasslop, G.

2018-01-01

In global fire models, lightning is typically prescribed from observational data with monthly mean temporal resolution while meteorological forcings, such as precipitation or temperature, are prescribed in a daily resolution. In this study, we investigate the importance of the temporal resolution of the lightning forcing for the simulation of burned area by varying from daily to monthly and annual mean forcing. For this, we utilize the vegetation fire model JSBACH-SPITFIRE to simulate burned area, forced with meteorological and lightning data derived from the general circulation model ECHAM6. On a global scale, differences in burned area caused by lightning forcing applied in coarser temporal resolution stay below 0.55% compared to the use of daily mean forcing. Regionally, however, differences reach up to 100%, depending on the region and season. Monthly averaged lightning forcing as well as the monthly lightning climatology cause differences through an interaction between lightning ignitions and fire prone weather conditions, accounted for by the fire danger index. This interaction leads to decreased burned area in the boreal zone and increased burned area in the Tropics and Subtropics under the coarser temporal resolution. The exclusion of interannual variability, when forced with the lightning climatology, has only a minor impact on the simulated burned area. Annually averaged lightning forcing causes differences as a direct result of the eliminated seasonal characteristics of lightning. Burned area is decreased in summer and increased in winter where fuel is available. Regions with little seasonality, such as the Tropics and Subtropics, experience an increase in burned area.

Assessment of a climate model to reproduce rainfall variability and extremes over Southern Africa

NASA Astrophysics Data System (ADS)

Williams, C. J. R.; Kniveton, D. R.; Layberry, R.

2010-01-01

It is increasingly accepted that any possible climate change will not only have an influence on mean climate but may also significantly alter climatic variability. A change in the distribution and magnitude of extreme rainfall events (associated with changing variability), such as droughts or flooding, may have a far greater impact on human and natural systems than a changing mean. This issue is of particular importance for environmentally vulnerable regions such as southern Africa. The sub-continent is considered especially vulnerable to and ill-equipped (in terms of adaptation) for extreme events, due to a number of factors including extensive poverty, famine, disease and political instability. Rainfall variability and the identification of rainfall extremes is a function of scale, so high spatial and temporal resolution data are preferred to identify extreme events and accurately predict future variability. The majority of previous climate model verification studies have compared model output with observational data at monthly timescales. In this research, the assessment of ability of a state of the art climate model to simulate climate at daily timescales is carried out using satellite-derived rainfall data from the Microwave Infrared Rainfall Algorithm (MIRA). This dataset covers the period from 1993 to 2002 and the whole of southern Africa at a spatial resolution of 0.1° longitude/latitude. This paper concentrates primarily on the ability of the model to simulate the spatial and temporal patterns of present-day rainfall variability over southern Africa and is not intended to discuss possible future changes in climate as these have been documented elsewhere. Simulations of current climate from the UK Meteorological Office Hadley Centre's climate model, in both regional and global mode, are firstly compared to the MIRA dataset at daily timescales. Secondly, the ability of the model to reproduce daily rainfall extremes is assessed, again by a comparison with extremes from the MIRA dataset. The results suggest that the model reproduces the number and spatial distribution of rainfall extremes with some accuracy, but that mean rainfall and rainfall variability is under-estimated (over-estimated) over wet (dry) regions of southern Africa.

Attribution of soil information associated with modeling background clutter

NASA Astrophysics Data System (ADS)

Mason, George; Melloh, Rae

2006-05-01

This paper examines the attribution of data fields required to generate high resolution soil profiles for support of Computational Test Bed (CTB) used for countermine research. The countermine computational test bed is designed to realistically simulate the geo-environment to support the evaluation of sensors used to locate unexploded ordnance. The goal of the CTB is to derive expected moisture, chemical compounds, and measure heat migration over time, from which we expect to optimize sensor performance. Several tests areas were considered for the collection of soils data to populate the CTB. Collection of bulk soil properties has inherent spatial resolution limits. Novel techniques are therefore required to populate a high resolution model. This paper presents correlations between spatial variability in texture as related to hydraulic permeability and heat transfer properties of the soil. The extracted physical properties are used to exercise models providing a signature of subsurface media and support the simulation of detection by various sensors of buried and surface ordnance.

Assessment of the Suitability of High Resolution Numerical Weather Model Outputs for Hydrological Modelling in Mountainous Cold Regions

NASA Astrophysics Data System (ADS)

Rasouli, K.; Pomeroy, J. W.; Hayashi, M.; Fang, X.; Gutmann, E. D.; Li, Y.

2017-12-01

The hydrology of mountainous cold regions has a large spatial variability that is driven both by climate variability and near-surface process variability associated with complex terrain and patterns of vegetation, soils, and hydrogeology. There is a need to downscale large-scale atmospheric circulations towards the fine scales that cold regions hydrological processes operate at to assess their spatial variability in complex terrain and quantify uncertainties by comparison to field observations. In this research, three high resolution numerical weather prediction models, namely, the Intermediate Complexity Atmosphere Research (ICAR), Weather Research and Forecasting (WRF), and Global Environmental Multiscale (GEM) models are used to represent spatial and temporal patterns of atmospheric conditions appropriate for hydrological modelling. An area covering high mountains and foothills of the Canadian Rockies was selected to assess and compare high resolution ICAR (1 km × 1 km), WRF (4 km × 4 km), and GEM (2.5 km × 2.5 km) model outputs with station-based meteorological measurements. ICAR with very low computational cost was run with different initial and boundary conditions and with finer spatial resolution, which allowed an assessment of modelling uncertainty and scaling that was difficult with WRF. Results show that ICAR, when compared with WRF and GEM, performs very well in precipitation and air temperature modelling in the Canadian Rockies, while all three models show a fair performance in simulating wind and humidity fields. Representation of local-scale atmospheric dynamics leading to realistic fields of temperature and precipitation by ICAR, WRF, and GEM makes these models suitable for high resolution cold regions hydrological predictions in complex terrain, which is a key factor in estimating water security in western Canada.

Improving synoptic and intraseasonal variability in CFSv2 via stochastic representation of organized convection

NASA Astrophysics Data System (ADS)

Goswami, B. B.; Khouider, B.; Phani, R.; Mukhopadhyay, P.; Majda, A.

2017-01-01

To better represent organized convection in the Climate Forecast System version 2 (CFSv2), a stochastic multicloud model (SMCM) parameterization is adopted and a 15 year climate run is made. The last 10 years of simulations are analyzed here. While retaining an equally good mean state (if not better) as the parent model, the CFS-SMCM simulation shows significant improvement in the synoptic and intraseasonal variability. The CFS-SMCM provides a better account of convectively coupled equatorial waves and the Madden-Julian oscillation. The CFS-SMCM exhibits improvements in northward and eastward propagation of intraseasonal oscillation of convection including the MJO propagation beyond the maritime continent barrier, which is the Achilles Heel for coarse-resolution global climate models (GCMs). The distribution of precipitation events is better simulated in CFSsmcm and spreads naturally toward high-precipitation events. Deterministic GCMs tend to simulate a narrow distribution with too much drizzling precipitation and too little high-precipitation events.

Observed and predicted sensitivities of extreme surface ozone to meteorological drivers in three US cities

NASA Astrophysics Data System (ADS)

Fix, Miranda J.; Cooley, Daniel; Hodzic, Alma; Gilleland, Eric; Russell, Brook T.; Porter, William C.; Pfister, Gabriele G.

2018-03-01

We conduct a case study of observed and simulated maximum daily 8-h average (MDA8) ozone (O3) in three US cities for summers during 1996-2005. The purpose of this study is to evaluate the ability of a high resolution atmospheric chemistry model to reproduce observed relationships between meteorology and high or extreme O3. We employ regional coupled chemistry-transport model simulations to make three types of comparisons between simulated and observational data, comparing (1) tails of the O3 response variable, (2) distributions of meteorological predictor variables, and (3) sensitivities of high and extreme O3 to meteorological predictors. This last comparison is made using two methods: quantile regression, for the 0.95 quantile of O3, and tail dependence optimization, which is used to investigate even higher O3 extremes. Across all three locations, we find substantial differences between simulations and observational data in both meteorology and meteorological sensitivities of high and extreme O3.

SST Variation Due to Interactive Convective-Radiative Processes

NASA Technical Reports Server (NTRS)

Tao, W.-K.; Shie, C.-L.; Johnson, D.; Simpson, J.; Li, X.; Sui, C.-H.

2000-01-01

The recent linking of Cloud-Resolving Models (CRMs) to Ocean-Mixed Layer (OML) models has provided a powerful new means of quantifying the role of cloud systems in ocean-atmosphere coupling. This is due to the fact that the CRM can better resolve clouds and cloud systems and allow for explicit cloud-radiation interaction. For example, Anderson (1997) applied an atmospheric forcing associated with a CRM simulated squall line to a 3-D OML model (one way or passive interaction). His results suggested that the spatial variability resulting from the squall forcing can last at least 24 hours when forced with otherwise spatially uniform fluxes. In addition, the sea surface salinity (SSS) variability continuously decreased following the forcing, while some of the SST variability remained when a diurnal mixed layer capped off the surface structure. The forcing used in the OML model, however, focused on shorter time (8 h) and smaller spatial scales (100-120 km). In this study, the 3-D Goddard Cumulus Ensemble Model (GCE; 512 x 512 x 23 cu km, 2-km horizontal resolution) is used to simulate convective active episodes occurring in the Western Pacific warm pool and Eastern Atlantic regions. The model is integrated for seven days, and the simulated results are coupled to an OML model to better understand the impact of precipitation and changes in the planetary boundary layer upon SST variation. We will specifically examine and compare the results of linking the OML model with various spatially-averaged outputs from GCE simulations (i.e., 2 km vs. 10-50 km horizontal resolutions), in order to help understand the SST sensitivity to multi-scale influences. This will allow us to assess the importance of explicitly simulated deep and shallow clouds, as well as the subgrid-scale effects (in coarse-model runs) upon SST variation. Results using both 1-D and 2-D OML models will be evaluated to assess the effects of horizontal advection.

Hydrological Dynamics of Central America: Time-of-Emergence of the Global Warming Signal

NASA Astrophysics Data System (ADS)

Imbach, P. A.; Georgiou, S.; Calderer, L.; Coto, A.; Nakaegawa, T.; Chou, S. C.; Lyra, A. A.; Hidalgo, H. G.; Ciais, P.

2016-12-01

Central America is among the world's most vulnerable regions to climate variability and change. Country economies are highly dependent on the agricultural sector and over 40 million people's rural livelihoods directly depend on the use of natural resources. Future climate scenarios show a drier outlook (higher temperatures and lower precipitation) over a region where rural livelihoods are already compromised by water availability and climate variability. Previous efforts to validate modelling of the regional hydrology have been based on high resolution (1 km2) equilibrium models (Imbach et al., 2010) or using dynamic models (Variable Infiltration Capacity) with coarse climate forcing (0.5°) (Hidalgo et al., 2013; Maurer et al., 2009). We present here: (i) validation of the hydrological outputs from high-resolution simulations (10 km2) of a dynamic vegetation model (Orchidee), using 7 different sets of model input forcing data, with monthly runoff observations from 182 catchments across Central America; (ii) the first assessments of the region's hydrological variability using the historical simulations (iii) an estimation of the time of emergence of the climate change signal (under the SRES emission scenarios) on the water balance. We found model performance to be comparable with that from studies in other world regions (Yang et al. 2016) when forced with high resolution precipitation data (monthly values at 5 km2, Funk et al. (2015)) and the Climate Research Unit (CRU 3.2, Harris et al. (2014)) dataset of meteorological parameters. Validation results showed a Pearson correlation coefficient ≈ 0.6, general underestimation of runoff of ≈ 60% and variability close to observed values (ratio of standard deviations of ≈ 0.7). Maps of historical runoff are presented to show areas where high runoff variability follows high mean annual runoff, with opposite trends over the Caribbean. Future scenarios show large areas where future maximum water availability will always fall below minus-one standard deviation of the historical values by mid-century. Additionally, our results highlight the time horizon left to develop adaptation strategies to cope with future reductions in water availability.

On the Representation of Subgrid Microtopography Effects in Process-based Hydrologic Models

NASA Astrophysics Data System (ADS)

Jan, A.; Painter, S. L.; Coon, E. T.

2017-12-01

Increased availability of high-resolution digital elevation are enabling process-based hydrologic modeling on finer and finer scales. However, spatial variability in surface elevation (microtopography) exists below the scale of a typical hyper-resolution grid cell and has the potential to play a significant role in water retention, runoff, and surface/subsurface interactions. Though the concept of microtopographic features (depressions, obstructions) and the associated implications on flow and discharge are well established, representing those effects in watershed-scale integrated surface/subsurface hydrology models remains a challenge. Using the complex and coupled hydrologic environment of the Arctic polygonal tundra as an example, we study the effects of submeter topography and present a subgrid model parameterized by small-scale spatial heterogeneities for use in hyper-resolution models with polygons at a scale of 15-20 meters forming the surface cells. The subgrid model alters the flow and storage terms in the diffusion wave equation for surface flow. We compare our results against sub-meter scale simulations (acts as a benchmark for our simulations) and hyper-resolution models without the subgrid representation. The initiation of runoff in the fine-scale simulations is delayed and the recession curve is slowed relative to simulated runoff using the hyper-resolution model with no subgrid representation. Our subgrid modeling approach improves the representation of runoff and water retention relative to models that ignore subgrid topography. We evaluate different strategies for parameterizing subgrid model and present a classification-based method to efficiently move forward to larger landscapes. This work was supported by the Interoperable Design of Extreme-scale Application Software (IDEAS) project and the Next-Generation Ecosystem Experiments-Arctic (NGEE Arctic) project. NGEE-Arctic is supported by the Office of Biological and Environmental Research in the DOE Office of Science.

Elevation-dependent warming in global climate model simulations at high spatial resolution

NASA Astrophysics Data System (ADS)

Palazzi, Elisa; Mortarini, Luca; Terzago, Silvia; von Hardenberg, Jost

2018-06-01

The enhancement of warming rates with elevation, so-called elevation-dependent warming (EDW), is one of the regional, still not completely understood, expressions of global warming. Sentinels of climate and environmental changes, mountains have experienced more rapid and intense warming trends in the recent decades, leading to serious impacts on mountain ecosystems and downstream. In this paper we use a state-of-the-art Global Climate Model (EC-Earth) to investigate the impact of model spatial resolution on the representation of this phenomenon and to highlight possible differences in EDW and its causes in different mountain regions of the Northern Hemisphere. To this end we use EC-Earth climate simulations at five different spatial resolutions, from ˜ 125 to ˜ 16 km, to explore the existence and the driving mechanisms of EDW in the Colorado Rocky Mountains, the Greater Alpine Region and the Tibetan Plateau-Himalayas. Our results show that the more frequent EDW drivers in all regions and seasons are the changes in albedo and in downward thermal radiation and this is reflected in both daytime and nighttime warming. In the Tibetan Plateau-Himalayas and in the Greater Alpine Region, an additional driver is the change in specific humidity. We also find that, while generally the model shows no clear resolution dependence in its ability to simulate the existence of EDW in the different regions, specific EDW characteristics such as its intensity and the relative role of different driving mechanisms may be different in simulations performed at different spatial resolutions. Moreover, we find that the role of internal climate variability can be significant in modulating the EDW signal, as suggested by the spread found in the multi-member ensemble of the EC-Earth experiments which we use.

Development of a High-Resolution Climate Model for Future Climate Change Projection on the Earth Simulator

NASA Astrophysics Data System (ADS)

Kanzawa, H.; Emori, S.; Nishimura, T.; Suzuki, T.; Inoue, T.; Hasumi, H.; Saito, F.; Abe-Ouchi, A.; Kimoto, M.; Sumi, A.

2002-12-01

The fastest supercomputer of the world, the Earth Simulator (total peak performance 40TFLOPS) has recently been available for climate researches in Yokohama, Japan. We are planning to conduct a series of future climate change projection experiments on the Earth Simulator with a high-resolution coupled ocean-atmosphere climate model. The main scientific aims for the experiments are to investigate 1) the change in global ocean circulation with an eddy-permitting ocean model, 2) the regional details of the climate change including Asian monsoon rainfall pattern, tropical cyclones and so on, and 3) the change in natural climate variability with a high-resolution model of the coupled ocean-atmosphere system. To meet these aims, an atmospheric GCM, CCSR/NIES AGCM, with T106(~1.1o) horizontal resolution and 56 vertical layers is to be coupled with an oceanic GCM, COCO, with ~ 0.28ox 0.19o horizontal resolution and 48 vertical layers. This coupled ocean-atmosphere climate model, named MIROC, also includes a land-surface model, a dynamic-thermodynamic seaice model, and a river routing model. The poles of the oceanic model grid system are rotated from the geographic poles so that they are placed in Greenland and Antarctic land masses to avoild the singularity of the grid system. Each of the atmospheric and the oceanic parts of the model is parallelized with the Message Passing Interface (MPI) technique. The coupling of the two is to be done with a Multi Program Multi Data (MPMD) fashion. A 100-model-year integration will be possible in one actual month with 720 vector processors (which is only 14% of the full resources of the Earth Simulator).

Errors and uncertainties in regional climate simulations of rainfall variability over Tunisia: a multi-model and multi-member approach

NASA Astrophysics Data System (ADS)

Fathalli, Bilel; Pohl, Benjamin; Castel, Thierry; Safi, Mohamed Jomâa

2018-02-01

Temporal and spatial variability of rainfall over Tunisia (at 12 km spatial resolution) is analyzed in a multi-year (1992-2011) ten-member ensemble simulation performed using the WRF model, and a sample of regional climate hindcast simulations from Euro-CORDEX. RCM errors and skills are evaluated against a dense network of local rain gauges. Uncertainties arising, on the one hand, from the different model configurations and, on the other hand, from internal variability are furthermore quantified and ranked at different timescales using simple spread metrics. Overall, the WRF simulation shows good skill for simulating spatial patterns of rainfall amounts over Tunisia, marked by strong altitudinal and latitudinal gradients, as well as the rainfall interannual variability, in spite of systematic errors. Mean rainfall biases are wet in both DJF and JJA seasons for the WRF ensemble, while they are dry in winter and wet in summer for most of the used Euro-CORDEX models. The sign of mean annual rainfall biases over Tunisia can also change from one member of the WRF ensemble to another. Skills in regionalizing precipitation over Tunisia are season dependent, with better correlations and weaker biases in winter. Larger inter-member spreads are observed in summer, likely because of (1) an attenuated large-scale control on Mediterranean and Tunisian climate, and (2) a larger contribution of local convective rainfall to the seasonal amounts. Inter-model uncertainties are globally stronger than those attributed to model's internal variability. However, inter-member spreads can be of the same magnitude in summer, emphasizing the important stochastic nature of the summertime rainfall variability over Tunisia.

Using simulated 3D surface fuelbeds and terrestrial laser scan data to develop inputs to fire behavior models

Treesearch

Eric Rowell; E. Louise Loudermilk; Carl Seielstad; Joseph O' Brien

2016-01-01

Understanding fine-scale variability in understory fuels is increasingly important as physics-based fire behavior modelsdrive needs for higher-resolution data. Describing fuelbeds 3Dly is critical in determining vertical and horizontal distributions offuel elements and the mass, especially in frequently burned pine ecosystems where fine-scale...

Evaluations of high-resolution dynamically downscaled ensembles over the contiguous United States

NASA Astrophysics Data System (ADS)

Zobel, Zachary; Wang, Jiali; Wuebbles, Donald J.; Kotamarthi, V. Rao

2018-02-01

This study uses Weather Research and Forecast (WRF) model to evaluate the performance of six dynamical downscaled decadal historical simulations with 12-km resolution for a large domain (7200 × 6180 km) that covers most of North America. The initial and boundary conditions are from three global climate models (GCMs) and one reanalysis data. The GCMs employed in this study are the Geophysical Fluid Dynamics Laboratory Earth System Model with Generalized Ocean Layer Dynamics component, Community Climate System Model, version 4, and the Hadley Centre Global Environment Model, version 2-Earth System. The reanalysis data is from the National Centers for Environmental Prediction-US. Department of Energy Reanalysis II. We analyze the effects of bias correcting, the lateral boundary conditions and the effects of spectral nudging. We evaluate the model performance for seven surface variables and four upper atmospheric variables based on their climatology and extremes for seven subregions across the United States. The results indicate that the simulation's performance depends on both location and the features/variable being tested. We find that the use of bias correction and/or nudging is beneficial in many situations, but employing these when running the RCM is not always an improvement when compared to the reference data. The use of an ensemble mean and median leads to a better performance in measuring the climatology, while it is significantly biased for the extremes, showing much larger differences than individual GCM driven model simulations from the reference data. This study provides a comprehensive evaluation of these historical model runs in order to make informed decisions when making future projections.

Undersampling strategies for compressed sensing accelerated MR spectroscopic imaging

NASA Astrophysics Data System (ADS)

Vidya Shankar, Rohini; Hu, Houchun Harry; Bikkamane Jayadev, Nutandev; Chang, John C.; Kodibagkar, Vikram D.

2017-03-01

Compressed sensing (CS) can accelerate magnetic resonance spectroscopic imaging (MRSI), facilitating its widespread clinical integration. The objective of this study was to assess the effect of different undersampling strategy on CS-MRSI reconstruction quality. Phantom data were acquired on a Philips 3 T Ingenia scanner. Four types of undersampling masks, corresponding to each strategy, namely, low resolution, variable density, iterative design, and a priori were simulated in Matlab and retrospectively applied to the test 1X MRSI data to generate undersampled datasets corresponding to the 2X - 5X, and 7X accelerations for each type of mask. Reconstruction parameters were kept the same in each case(all masks and accelerations) to ensure that any resulting differences can be attributed to the type of mask being employed. The reconstructed datasets from each mask were statistically compared with the reference 1X, and assessed using metrics like the root mean square error and metabolite ratios. Simulation results indicate that both the a priori and variable density undersampling masks maintain high fidelity with the 1X up to five-fold acceleration. The low resolution mask based reconstructions showed statistically significant differences from the 1X with the reconstruction failing at 3X, while the iterative design reconstructions maintained fidelity with the 1X till 4X acceleration. In summary, a pilot study was conducted to identify an optimal sampling mask in CS-MRSI. Simulation results demonstrate that the a priori and variable density masks can provide statistically similar results to the fully sampled reference. Future work would involve implementing these two masks prospectively on a clinical scanner.

Intraseasonal Variability of the Indian Monsoon as Simulated by a Global Model

NASA Astrophysics Data System (ADS)

Joshi, Sneh; Kar, S. C.

2018-01-01

This study uses the global forecast system (GFS) model at T126 horizontal resolution to carry out seasonal simulations with prescribed sea-surface temperatures. Main objectives of the study are to evaluate the simulated Indian monsoon variability in intraseasonal timescales. The GFS model has been integrated for 29 monsoon seasons with 15 member ensembles forced with observed sea-surface temperatures (SSTs) and additional 16-member ensemble runs have been carried out using climatological SSTs. Northward propagation of intraseasonal rainfall anomalies over the Indian region from the model simulations has been examined. It is found that the model is unable to simulate the observed moisture pattern when the active zone of convection is over central India. However, the model simulates the observed pattern of specific humidity during the life cycle of northward propagation on day - 10 and day + 10 of maximum convection over central India. The space-time spectral analysis of the simulated equatorial waves shows that the ensemble members have varying amount of power in each band of wavenumbers and frequencies. However, variations among ensemble members are more in the antisymmetric component of westward moving waves and maximum difference in power is seen in the 8-20 day mode among ensemble members.

The Future of Wind Energy in California: Future Projections in Variable-Resolution CESM

NASA Astrophysics Data System (ADS)

Wang, M.; Ullrich, P. A.; Millstein, D.; Collier, C.

2017-12-01

This study focuses on the wind energy characterization and future projection at five primary wind turbine sites in California. Historical (1980-2000) and mid-century (2030-2050) simulations were produced using the Variable-Resolution Community Earth System Model (VR-CESM) to analyze the trends and variations in wind energy under climate change. Datasets from Det Norske Veritas Germanischer Llyod (DNV GL), MERRA-2, CFSR, NARR, as well as surface observational data were used for model validation and comparison. Significant seasonal wind speed changes under RCP8.5 were detected from several wind farm sites. Large-scale patterns were then investigated to analyze the synoptic-scale impact on localized wind change. The agglomerative clustering method was applied to analyze and group different wind patterns. The associated meteorological background of each cluster was investigated to analyze the drivers of different wind patterns. This study improves the characterization of uncertainty around the magnitude and variability in space and time of California's wind resources in the near future, and also enhances understanding of the physical mechanisms related to the trends in wind resource variability.

Quantification of marine aerosol subgrid variability and its correlation with clouds based on high-resolution regional modeling: Quantifying Aerosol Subgrid Variability

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

Lin, Guangxing; Qian, Yun; Yan, Huiping

One limitation of most global climate models (GCMs) is that with the horizontal resolutions they typically employ, they cannot resolve the subgrid variability (SGV) of clouds and aerosols, adding extra uncertainties to the aerosol radiative forcing estimation. To inform the development of an aerosol subgrid variability parameterization, here we analyze the aerosol SGV over the southern Pacific Ocean simulated by the high-resolution Weather Research and Forecasting model coupled to Chemistry. We find that within a typical GCM grid, the aerosol mass subgrid standard deviation is 15% of the grid-box mean mass near the surface on a 1 month mean basis.more » The fraction can increase to 50% in the free troposphere. The relationships between the sea-salt mass concentration, meteorological variables, and sea-salt emission rate are investigated in both the clear and cloudy portion. Under clear-sky conditions, marine aerosol subgrid standard deviation is highly correlated with the standard deviations of vertical velocity, cloud water mixing ratio, and sea-salt emission rates near the surface. It is also strongly connected to the grid box mean aerosol in the free troposphere (between 2 km and 4 km). In the cloudy area, interstitial sea-salt aerosol mass concentrations are smaller, but higher correlation is found between the subgrid standard deviations of aerosol mass and vertical velocity. Additionally, we find that decreasing the model grid resolution can reduce the marine aerosol SGV but strengthen the correlations between the aerosol SGV and the total water mixing ratio (sum of water vapor, cloud liquid, and cloud ice mixing ratios).« less

On the Lack of Stratospheric Dynamical Variability in Low-top Versions of the CMIP5 Models

NASA Technical Reports Server (NTRS)

Charlton-Perez, Andrew J.; Baldwin, Mark P.; Birner, Thomas; Black, Robert X.; Butler, Amy H.; Calvo, Natalia; Davis, Nicholas A.; Gerber, Edwin P.; Gillett, Nathan; Hardiman, Steven;

Requirements for Large Eddy Simulation Computations of Variable-Speed Power Turbine Flows

NASA Technical Reports Server (NTRS)

Ameri, Ali A.

2016-01-01

Variable-speed power turbines (VSPTs) operate at low Reynolds numbers and with a wide range of incidence angles. Transition, separation, and the relevant physics leading to them are important to VSPT flow. Higher fidelity tools such as large eddy simulation (LES) may be needed to resolve the flow features necessary for accurate predictive capability and design of such turbines. A survey conducted for this report explores the requirements for such computations. The survey is limited to the simulation of two-dimensional flow cases and endwalls are not included. It suggests that a grid resolution necessary for this type of simulation to accurately represent the physics may be of the order of Delta(x)+=45, Delta(x)+ =2 and Delta(z)+=17. Various subgrid-scale (SGS) models have been used and except for the Smagorinsky model, all seem to perform well and in some instances the simulations worked well without SGS modeling. A method of specifying the inlet conditions such as synthetic eddy modeling (SEM) is necessary to correctly represent the inlet conditions.

The QBO Impact on Stratospheric Composition as Revealed by the MERRA-2 GMI Simulation and NASA Satellite Observations

NASA Astrophysics Data System (ADS)

Oman, L.; Strahan, S. E.

2017-12-01

The Quasi-Biennial Oscillation (QBO) is the dominant mode of variability in the tropical stratosphere on interannual time scales. It has been shown to impact both stratospheric dynamics and important trace gas constituent distributions. The QBO timing with respect to the seasonal cycle in each hemisphere is significant in determining its impact on up to decadal scale variability. The composition response to the QBO is examined using the new MERRA-2 GMI "Replay" simulation, an atmospheric composition community resource, run at the native MERRA-2 approximately ½° horizontal resolution on the cubed sphere. MERRA-2 GMI is driven by the online use of key MERRA-2 meteorological quantities (i.e. U, V, T, and P) with all other variables calculated in response to those and boundary condition forcings from 1980-2016. The simulation combined with NASA's UARS and Aura satellite measurements have allowed us to quantify the impact of the QBO on stratospheric composition in more detail than was ever possible before. Revealing preferential pathways and transport timings necessary in understanding the QBO impact on composition throughout the stratosphere.

Convergence behavior of idealized convection-resolving simulations of summertime deep moist convection over land

NASA Astrophysics Data System (ADS)

Panosetti, Davide; Schlemmer, Linda; Schär, Christoph

2018-05-01

Convection-resolving models (CRMs) can explicitly simulate deep convection and resolve interactions between convective updrafts. They are thus increasingly used in numerous weather and climate applications. However, the truncation of the continuous energy cascade at scales of O (1 km) poses a serious challenge, as in kilometer-scale simulations the size and properties of the simulated convective cells are often determined by the horizontal grid spacing (Δ x ).In this study, idealized simulations of deep moist convection over land are performed to assess the convergence behavior of a CRM at Δ x = 8, 4, 2, 1 km and 500 m. Two types of convergence estimates are investigated: bulk convergence addressing domain-averaged and integrated variables related to the water and energy budgets, and structural convergence addressing the statistics and scales of individual clouds and updrafts. Results show that bulk convergence generally begins at Δ x =4 km, while structural convergence is not yet fully achieved at the kilometer scale, despite some evidence that the resolution sensitivity of updraft velocities and convective mass fluxes decreases at finer resolution. In particular, at finer grid spacings the maximum updraft velocity generally increases, and the size of the smallest clouds is mostly determined by Δ x . A number of different experiments are conducted, and it is found that the presence of orography and environmental vertical wind shear yields more energetic structures at scales much larger than Δ x , sometimes reducing the resolution sensitivity. Overall the results lend support to the use of kilometer-scale resolutions in CRMs, despite the inability of these models to fully resolve the associated cloud field.

Systematic errors in the simulation of the Asian summer monsoon: the role of rainfall variability on a range of time and space scales

NASA Astrophysics Data System (ADS)

Martin, Gill; Levine, Richard; Klingaman, Nicholas; Bush, Stephanie; Turner, Andrew; Woolnough, Steven

2015-04-01

Despite considerable efforts worldwide to improve model simulations of the Asian summer monsoon, significant biases still remain in climatological seasonal mean rainfall distribution, timing of the onset, and northward and eastward extent of the monsoon domain (Sperber et al., 2013). Many modelling studies have shown sensitivity to convection and boundary layer parameterization, cloud microphysics and land surface properties, as well as model resolution. Here we examine the problems in representing short-timescale rainfall variability (related to convection parameterization), problems in representing synoptic-scale systems such as monsoon depressions (related to model resolution), and the relationship of each of these with longer-term systematic biases. Analysis of the spatial distribution of rainfall intensity on a range of timescales ranging from ~30 minutes to daily, in the MetUM and in observations (where available), highlights how rainfall biases in the South Asian monsoon region on different timescales in different regions can be achieved in models through a combination of the incorrect frequency and/or intensity of rainfall. Over the Indian land area, the typical dry bias is related to sub-daily rainfall events being too infrequent, despite being too intense when they occur. In contrast, the wet bias regions over the equatorial Indian Ocean are mainly related to too frequent occurrence of lower-than-observed 3-hourly rainfall accumulations which result in too frequent occurrence of higher-than-observed daily rainfall accumulations. This analysis sheds light on the model deficiencies behind the climatological seasonal mean rainfall biases that many models exhibit in this region. Changing physical parameterizations alters this behaviour, with associated adjustments in the climatological rainfall distribution, although the latter is not always improved (Bush et al., 2014). This suggests a more complex interaction between the diabatic heating and the large-scale circulation than is indicated by the intensity and frequency of rainfall alone. Monsoon depressions and low pressure systems are important contributors to monsoon rainfall over central and northern India, areas where MetUM climate simulations typically show deficient monsoon rainfall. Analysis of MetUM climate simulations at resolutions ranging from N96 (~135km) to N512 (~25km) suggests that at lower resolution the numbers and intensities of monsoon depressions and low pressure systems and their associated rainfall are very low compared with re-analyses/observations. We show that there are substantial increases with horizontal resolution, but resolution is not the only factor. Idealised simulations, either using nudged atmospheric winds or initialised coupled hindcasts, which improve (strengthen) the mean state monsoon and cyclonic circulation over the Indian peninsula, also result in a substantial increase in monsoon depressions and associated rainfall. This suggests that a more realistic representation of monsoon depressions is possible even at lower resolution if the larger-scale systematic error pattern in the monsoon is improved.

Multi-scale coupled modelling of waves and currents on the Catalan shelf.

NASA Astrophysics Data System (ADS)

Grifoll, M.; Warner, J. C.; Espino, M.; Sánchez-Arcilla, A.

2012-04-01

Catalan shelf circulation is characterized by a background along-shelf flow to the southwest (including some meso-scale features) plus episodic storm driven patterns. To investigate these dynamics, a coupled multi-scale modeling system is applied to the Catalan shelf (North-western Mediterranean Sea). The implementation consists of a set of increasing-resolution nested models, based on the circulation model ROMS and the wave model SWAN as part of the COAWST modeling system, covering from the slope and shelf region (~1 km horizontal resolution) down to a local area around Barcelona city (~40 m). The system is initialized with MyOcean products in the coarsest outer domain, and uses atmospheric forcing from other sources for the increasing resolution inner domains. Results of the finer resolution domains exhibit improved agreement with observations relative to the coarser model results. Several hydrodynamic configurations were simulated to determine dominant forcing mechanisms and hydrodynamic processes that control coastal scale processes. The numerical results reveal that the short term (hours to days) inner-shelf variability is strongly influenced by local wind variability, while sea-level slope, baroclinic effects, radiation stresses and regional circulation constitute second-order processes. Additional analysis identifies the significance of shelf/slope exchange fluxes, river discharge and the effect of the spatial resolution of the atmospheric fluxes.

High resolution dynamical downscaling of air temperature and relative humidity: performance assessment of WRF for Portugal

NASA Astrophysics Data System (ADS)

Menezes, Isilda; Pereira, Mário; Moreira, Demerval; Carvalheiro, Luís; Bugalho, Lourdes; Corte-Real, João

2017-04-01

Air temperature and relative humidity are two of the atmospheric variables with higher impact on human and natural systems, contributing to define the stress/comfortable conditions, affecting the productivity and health of the individuals as well as diminishing the resilience to other environmental hazards. Atmospheric regional models, driven by large scale forecasts from global circulation models, are the best way to reproduce such environmental conditions in high space-time resolution. This study is focused on the performance assessment of the WRF mesoscale model to perform high resolution dynamical downscaling for Portugal with three two-way nested grids, at 60 km, 20 km and 5 km horizontal resolution. The simulations of WRF models were produced with different initial and boundary forcing conditions. The NCEP-FNL Operational Global Analysis data available on 1-degree by 1-degree grid every six hours and ERA-Interim reanalyses dataset were used to drive the models. Two alternative configurations of the WRF model, including planetary boundary, layer schemes, microphysics, land-surface models, radiation schemes, were used and tested within the 5 km spatial resolution domain. Simulations of air temperature and relative humidity were produced for January and July of 2016 and compared with the observed datasets provided by the Instituto Português do Mar e da Atmosfera (IPMA) for 83 weather stations. Different performance measures of bias, precision, and accuracy were used, namely normalized bias, standard deviation, mean absolute error, root mean square error, bias of root mean square error as well as correlation based measures (e.g., coefficient of determination) and goodness of fit measures (index of agreement). Main conclusions from the obtained results reveal: (i) great similarity between the spatial patterns of the simulated and observed fields; (ii) only small differences between simulations produced with ERA-Interim and NCEP-FNL, in spite of some differences between the input variables; (iii) the tested parametrizations do not force significantly different simulation patterns; (iv) observed and simulated hourly air temperature are very well correlated (91%), presenting similar variance and a low bias over the country. Obtained results are also in good agreement with other dynamical downscaling studies for Portugal supporting the use of WRF as a regional forecast model. Acknowledgements: This work was supported by: (i) the project Interact - Integrative Research in Environment,Agro-Chain and Technology, NORTE-01-0145-FEDER-000017, research line BEST, cofinanced by FEDER/NORTE 2020; (ii) the FIREXTR project, PTDC/ATP¬GEO/0462/2014; and, (iii) European Investment Funds by FEDER/COMPETE/POCI-Operacional Competitiveness and Internacionalization Programme, under Project POCI-01-0145-FEDER-006958 and National Funds by FCT - Portuguese Foundation for Science and Technology, under the project UID/AGR/04033.

The Modulation of Tropical Storm Activity in the Western North Pacific by the Madden-Julian Oscillation in GEOS-5 AGCM Experiments

NASA Technical Reports Server (NTRS)

Kim, Dongmin; Lee, Myong-In; Kim, Hye-Mi; Schubert, Siegfried D.; Yoo, Jin Ho

2014-01-01

This study examines the influence of the Madden-Julian Oscillation (MJO) on tropical storm (TS) activity in the western North Pacific, using observations and GEOS-5 simulations at 50-km horizontal resolution. While GEOS-5 produces an MJO of faster propagation and weaker amplitude, it nevertheless reproduces the observed modulation of TS activity by the MJO with the highest TS genesis and increased track density in the active phases of MJO. The study suggests that the simulation of the sub-seasonal variability of TS activity could be improved by improving the simulations of the MJO in climate models.

The UPSCALE project: a large simulation campaign

NASA Astrophysics Data System (ADS)

Mizielinski, Matthew; Roberts, Malcolm; Vidale, Pier Luigi; Schiemann, Reinhard; Demory, Marie-Estelle; Strachan, Jane

2014-05-01

The development of a traceable hierarchy of HadGEM3 global climate models, based upon the Met Office Unified Model, at resolutions from 135 km to 25 km, now allows the impact of resolution on the mean state, variability and extremes of climate to be studied in a robust fashion. In 2011 we successfully obtained a single-year grant of 144 million core hours of supercomputing time from the PRACE organization to run ensembles of 27 year atmosphere-only (HadGEM3-A GA3.0) climate simulations at 25km resolution, as used in present global weather forecasting, on HERMIT at HLRS. Through 2012 the UPSCALE project (UK on PRACE: weather-resolving Simulations of Climate for globAL Environmental risk) ran over 650 years of simulation at resolutions of 25 km (N512), 60 km (N216) and 135 km (N96) to look at the value of high resolution climate models in the study of both present climate and a potential future climate scenario based on RCP8.5. Over 400 TB of data was produced using HERMIT, with additional simulations run on HECToR (UK supercomputer) and MONSooN (Met Office NERC Supercomputing Node). The data generated was transferred to the JASMIN super-data cluster, hosted by STFC CEDA in the UK, where analysis facilities are allowing rapid scientific exploitation of the data set. Many groups across the UK and Europe are already taking advantage of these facilities and we welcome approaches from other interested scientists. This presentation will briefly cover the following points; Purpose and requirements of the UPSCALE project and facilities used. Technical implementation and hurdles (model porting and optimisation, automation, numerical failures, data transfer). Ensemble specification. Current analysis projects and access to the data set. A full description of UPSCALE and the data set generated has been submitted to Geoscientific Model development, with overview information available from http://proj.badc.rl.ac.uk/upscale .

Signature of present and projected climate change at an urban scale: The case of Addis Ababa

NASA Astrophysics Data System (ADS)

Arsiso, Bisrat Kifle; Mengistu Tsidu, Gizaw; Stoffberg, Gerrit Hendrik

2018-06-01

Understanding climate change and variability at an urban scale is essential for water resource management, land use planning, development of adaption plans, mitigation of air and water pollution. However, there are serious challenges to meet these goals due to unavailability of observed and/or simulated high resolution spatial and temporal climate data. The statistical downscaling of general circulation climate model, for instance, is usually driven by sparse observational data hindering the use of downscaled data to investigate urban scale climate variability and change in the past. Recently, these challenges are partly resolved by concerted international effort to produce global and high spatial resolution climate data. In this study, the 1 km2 high resolution NIMR-HadGEM2-AO simulations for future projections under Representative Concentration Pathways (RCP4.5 and RCP8.5) scenarios and gridded observations provided by Worldclim data center are used to assess changes in rainfall, minimum and maximum temperature expected under the two scenarios over Addis Ababa city. The gridded 1 km2 observational data set for the base period (1950-2000) is compared to observation from a meteorological station in the city in order to assess its quality for use as a reference (baseline) data. The comparison revealed that the data set has a very good quality. The rainfall anomalies under RCPs scenarios are wet in the 2030s (2020-2039), 2050s (2040-2069) and 2080s (2070-2099). Both minimum and maximum temperature anomalies under RCPs are successively getting warmer during these periods. Thus, the projected changes under RCPs scenarios show a general increase in rainfall and temperatures with strong variabilities in rainfall during rainy season implying level of difficulty in water resource use and management as well as land use planning and management.

A proxy for high-resolution regional reanalysis for the Southeast United States: assessment of precipitation variability in dynamically downscaled reanalyses

USGS Publications Warehouse

Stefanova, Lydia; Misra, Vasubandhu; Chan, Steven; Griffin, Melissa; O'Brien, James J.; Smith, Thomas J.

2012-01-01

We present an analysis of the seasonal, subseasonal, and diurnal variability of rainfall from COAPS Land- Atmosphere Regional Reanalysis for the Southeast at 10-km resolution (CLARReS10). Most of our assessment focuses on the representation of summertime subseasonal and diurnal variability.Summer precipitation in the Southeast United States is a particularly challenging modeling problem because of the variety of regional-scale phenomena, such as sea breeze, thunderstorms and squall lines, which are not adequately resolved in coarse atmospheric reanalyses but contribute significantly to the hydrological budget over the region. We find that the dynamically downscaled reanalyses are in good agreement with station and gridded observations in terms of both the relative seasonal distribution and the diurnal structure of precipitation, although total precipitation amounts tend to be systematically overestimated. The diurnal cycle of summer precipitation in the downscaled reanalyses is in very good agreement with station observations and a clear improvement both over their "parent" reanalyses and over newer-generation reanalyses. The seasonal cycle of precipitation is particularly well simulated in the Florida; this we attribute to the ability of the regional model to provide a more accurate representation of the spatial and temporal structure of finer-scale phenomena such as fronts and sea breezes. Over the northern portion of the domain summer precipitation in the downscaled reanalyses remains, as in the "parent" reanalyses, overestimated. Given the degree of success that dynamical downscaling of reanalyses demonstrates in the simulation of the characteristics of regional precipitation, its favorable comparison to conventional newer-generation reanalyses and its cost-effectiveness, we conclude that for the Southeast United states such downscaling is a viable proxy for high-resolution conventional reanalysis.

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

NASA Astrophysics Data System (ADS)

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.

Observation and simulation of net primary productivity in Qilian Mountain, western China.

PubMed

Zhou, Y; Zhu, Q; Chen, J M; Wang, Y Q; Liu, J; Sun, R; Tang, S

2007-11-01

We modeled net primary productivity (NPP) at high spatial resolution using an advanced spaceborne thermal emission and reflection radiometer (ASTER) image of a Qilian Mountain study area using the boreal ecosystem productivity simulator (BEPS). Two key driving variables of the model, leaf area index (LAI) and land cover type, were derived from ASTER and moderate resolution imaging spectroradiometer (MODIS) data. Other spatially explicit inputs included daily meteorological data (radiation, precipitation, temperature, humidity), available soil water holding capacity (AWC), and forest biomass. NPP was estimated for coniferous forests and other land cover types in the study area. The result showed that NPP of coniferous forests in the study area was about 4.4 tCha(-1)y(-1). The correlation coefficient between the modeled NPP and ground measurements was 0.84, with a mean relative error of about 13.9%.

On the added value and sensitivity of WRF to driving conditions over CORDEX-Africa domain

NASA Astrophysics Data System (ADS)

Lorente-Plazas, Raquel; García-Díez, Markel; Jimenez-Guerrero, Pedro; Fernández, Jesús; Montavez, Juan Pedro

2014-05-01

The assessment of the climate variability over Africa has recently attracted the interest of the regional climate downscaling research community. The main reasons are not only because Africa is a climate change hot-spot, but also due to the low capacity of this region for the adaptation and mitigation under negative impacts and its direct dependency on its socio-economic sustainability of the climate variability. Therefore, improvements in the understanding of the African climate could help the governments in decision-making. Under this umbrella, regional climate models (RCMs) are promising tools to assess the African regional climate. The main advantage of the RCMs, with respect to global reanalysis datasets, is the higher detail provided by the increased resolution which implies a better representation of land-surface interactions and atmospheric processes. However, the confidence on the RCMs strongly depends on the reduction/bounding of uncertainties. One of these sources of uncertainties is associated with the selection of the boundary conditions for driving the regional models. In this work, two identical CORDEX-compliant simulations have been performed over Africa with the unique difference of being driven by two different reanalyses. The reanalyses used were the European Centre for Medium Range Weather Forecasts Interim reanalysis (ERA-I) and the Japanese 25-year reanalysis (JRA-25) by the Japanese Meteorological Service. Both reanalyses have identical temporal resolution (6-hr) but different spatial grid resolution, 0.75 and 1.25 degrees, respectively. The regional model used was the Weather Research and Forecasting Model (WRF). The numerical experiments encompass the period 1989-2010 covering the Africa-CORDEX domain with a 50 km horizontal spatial resolution and 28 vertical levels up to 50 hPa. The WRF simulations are compared between them and against observations. For the mean and maximum temperature the CRU monthly time series (0.25deg) from Climatic Research Unit of the University of East Anglia are used. The precipitation is compared against the Tropical Rainfall Measuring Mission Project (TRMM) monthly data (0.25deg). The results depict that none of the reanalyses used outperforms the other in representing the African climate, since their performance depends on the variable, season and region assessed. The simulations show a noticeable disagreement for 2-m temperature in north-western Africa, where WRF-JRA tends to underestimate this variable mostly in winter and spring. For the monthly mean daily maximum temperature, WRF-JRA tends to overestimate the temperature in the Sahel in summer and in the border between Angola and Namibia in Winter. When comparing with CRU observations, there is a remarkably better spatial representation for the WRF-EI simulation in the North of Africa. However, the behaviour of WRF-EI and WRF-JRA is similar in the South of Africa. Intra-annual variability is well represented except in Atlas mountains where WRF-JRA underestimates temperature. Regarding precipitation, the main differences appear over the Sahel region in JAS and in the Congo area during JFM. The comparison with the TRMM data shows a better agreement with the WRF-JRA simulation except during summer in the Sahel region. The monthly annual cycle is well captured, except in Ethiopian highlands and Northern West Africa where WRF-JRA (WRF-EI) underestimate (overestimate) the annual cycle.

Process-level improvements in CMIP5 models and their impact on tropical variability, the Southern Ocean, and monsoons

NASA Astrophysics Data System (ADS)

Lauer, Axel; Jones, Colin; Eyring, Veronika; Evaldsson, Martin; Hagemann, Stefan; Mäkelä, Jarmo; Martin, Gill; Roehrig, Romain; Wang, Shiyu

2018-01-01

The performance of updated versions of the four earth system models (ESMs) CNRM, EC-Earth, HadGEM, and MPI-ESM is assessed in comparison to their predecessor versions used in Phase 5 of the Coupled Model Intercomparison Project. The Earth System Model Evaluation Tool (ESMValTool) is applied to evaluate selected climate phenomena in the models against observations. This is the first systematic application of the ESMValTool to assess and document the progress made during an extensive model development and improvement project. This study focuses on the South Asian monsoon (SAM) and the West African monsoon (WAM), the coupled equatorial climate, and Southern Ocean clouds and radiation, which are known to exhibit systematic biases in present-day ESMs. The analysis shows that the tropical precipitation in three out of four models is clearly improved. Two of three updated coupled models show an improved representation of tropical sea surface temperatures with one coupled model not exhibiting a double Intertropical Convergence Zone (ITCZ). Simulated cloud amounts and cloud-radiation interactions are improved over the Southern Ocean. Improvements are also seen in the simulation of the SAM and WAM, although systematic biases remain in regional details and the timing of monsoon rainfall. Analysis of simulations with EC-Earth at different horizontal resolutions from T159 up to T1279 shows that the synoptic-scale variability in precipitation over the SAM and WAM regions improves with higher model resolution. The results suggest that the reasonably good agreement of modeled and observed mean WAM and SAM rainfall in lower-resolution models may be a result of unrealistic intensity distributions.

Crop Yield Simulations Using Multiple Regional Climate Models in the Southwestern United States

NASA Astrophysics Data System (ADS)

Stack, D.; Kafatos, M.; Kim, S.; Kim, J.; Walko, R. L.

2013-12-01

Agricultural productivity (described by crop yield) is strongly dependent on climate conditions determined by meteorological parameters (e.g., temperature, rainfall, and solar radiation). California is the largest producer of agricultural products in the United States, but crops in associated arid and semi-arid regions live near their physiological limits (e.g., in hot summer conditions with little precipitation). Thus, accurate climate data are essential in assessing the impact of climate variability on agricultural productivity in the Southwestern United States and other arid regions. To address this issue, we produced simulated climate datasets and used them as input for the crop production model. For climate data, we employed two different regional climate models (WRF and OLAM) using a fine-resolution (8km) grid. Performances of the two different models are evaluated in a fine-resolution regional climate hindcast experiment for 10 years from 2001 to 2010 by comparing them to the North American Regional Reanalysis (NARR) dataset. Based on this comparison, multi-model ensembles with variable weighting are used to alleviate model bias and improve the accuracy of crop model productivity over large geographic regions (county and state). Finally, by using a specific crop-yield simulation model (APSIM) in conjunction with meteorological forcings from the multi-regional climate model ensemble, we demonstrate the degree to which maize yields are sensitive to the regional climate in the Southwestern United States.

Test of High-resolution Global and Regional Climate Model Projections

NASA Astrophysics Data System (ADS)

Stenchikov, Georgiy; Nikulin, Grigory; Hansson, Ulf; Kjellström, Erik; Raj, Jerry; Bangalath, Hamza; Osipov, Sergey

2014-05-01

In scope of CORDEX project we have simulated the past (1975-2005) and future (2006-2050) climates using the GFDL global high-resolution atmospheric model (HIRAM) and the Rossby Center nested regional model RCA4 for the Middle East and North Africa (MENA) region. Both global and nested runs were performed with roughly the same spatial resolution of 25 km in latitude and longitude, and were driven by the 2°x2.5°-resolution fields from GFDL ESM2M IPCC AR5 runs. The global HIRAM simulations could naturally account for interaction of regional processes with the larger-scale circulation features like Indian Summer Monsoon, which is lacking from regional model setup. Therefore in this study we specifically address the consistency of "global" and "regional" downscalings. The performance of RCA4, HIRAM, and ESM2M is tested based on mean, extreme, trends, seasonal and inter-annual variability of surface temperature, precipitation, and winds. The impact of climate change on dust storm activity, extreme precipitation and water resources is specifically addressed. We found that the global and regional climate projections appear to be quite consistent for the modeled period and differ more significantly from ESM2M than between each other.

Uncertainty estimates of altimetric Global Mean Sea Level timeseries

NASA Astrophysics Data System (ADS)

Scharffenberg, Martin; Hemming, Michael; Stammer, Detlef

2016-04-01

An attempt is being presented concerned with providing uncertainty measures for global mean sea level time series. For this purpose sea surface height (SSH) fields, simulated by the high resolution STORM/NCEP model for the period 1993 - 2010, were subsampled along altimeter tracks and processed similar to techniques used by five working groups to estimate GMSL. Results suggest that the spatial and temporal resolution have a substantial impact on GMSL estimates. Major impacts can especially result from the interpolation technique or the treatment of SSH outliers and easily lead to artificial temporal variability in the resulting time series.

Evaluating MODIS snow products for modelling snowmelt runoff: Case study of the Rio Grande headwaters

NASA Astrophysics Data System (ADS)

Steele, Caitriana; Dialesandro, John; James, Darren; Elias, Emile; Rango, Albert; Bleiweiss, Max

2017-12-01

Snow-covered area (SCA) is a key variable in the Snowmelt-Runoff Model (SRM) and in other models for simulating discharge from snowmelt. Landsat Thematic Mapper (TM), Enhanced Thematic Mapper (ETM +) or Operational Land Imager (OLI) provide remotely sensed data at an appropriate spatial resolution for mapping SCA in small headwater basins, but the temporal resolution of the data is low and may not always provide sufficient cloud-free dates. The coarser spatial resolution Moderate Resolution Imaging Spectroradiometer (MODIS) offers better temporal resolution and in cloudy years, MODIS data offer the best alternative for mapping snow cover when finer spatial resolution data are unavailable. However, MODIS' coarse spatial resolution (500 m) can obscure fine spatial patterning in snow cover and some MODIS products are not sensitive to end-of-season snow cover. In this study, we aimed to test MODIS snow products for use in simulating snowmelt runoff from smaller headwater basins by a) comparing maps of TM and MODIS-based SCA and b) determining how SRM streamflow simulations are changed by the different estimates of seasonal snow depletion. We compared gridded MODIS snow products (Collection 5 MOD10A1 fractional and binary SCA; SCA derived from Collection 6 MOD10A1 Normalised Difference Snow Index (NDSI) Snow Cover), and the MODIS Snow Covered-Area and Grain size retrieval (MODSCAG) canopy-corrected fractional SCA (SCAMG), with reference SCA maps (SCAREF) generated from binary classification of TM imagery. SCAMG showed strong agreement with SCAREF; excluding true negatives (where both methods agreed no snow was present) the median percent difference between SCAREF and SCAMG ranged between -2.4% and 4.7%. We simulated runoff for each of the four study years using SRM populated with and calibrated for snow depletion curves derived from SCAREF. We then substituted in each of the MODIS-derived depletion curves. With efficiency coefficients ranging between 0.73 and 0.93, SRM simulation results from the SCAMG runs yielded the best results of all the MODIS products and only slightly underestimated discharge volume (between 7 and 11% of measured annual discharge). SRM simulations that used SCA derived from Collection 6 NDSI Snow Cover also yielded promising results, with efficiency coefficients ranging between 0.73 and 0.91. In conclusion, we recommend that when simulating snowmelt runoff from small basins (<4000 km2) with SRM, we recommend that users select either canopy-corrected MODSCAG or create their own site-specific products from the Collection 6 MOD10A1 NDSI.

Nonhydrostatic nested climate modeling: A case study of the 2010 summer season over the western United States

NASA Astrophysics Data System (ADS)

Lebassi-Habtezion, Bereket; Diffenbaugh, Noah S.

2013-10-01

potential importance of local-scale climate phenomena motivates development of approaches to enable computationally feasible nonhydrostatic climate simulations. To that end, we evaluate the potential viability of nested nonhydrostatic model approaches, using the summer climate of the western United States (WUSA) as a case study. We use the Weather Research and Forecast (WRF) model to carry out five simulations of summer 2010. This suite allows us to test differences between nonhydrostatic and hydrostatic resolutions, single and multiple nesting approaches, and high- and low-resolution reanalysis boundary conditions. WRF simulations were evaluated against station observations, gridded observations, and reanalysis data over domains that cover the 11 WUSA states at nonhydrostatic grid spacing of 4 km and hydrostatic grid spacing of 25 km and 50 km. Results show that the nonhydrostatic simulations more accurately resolve the heterogeneity of surface temperature, precipitation, and wind speed features associated with the topography and orography of the WUSA region. In addition, we find that the simulation in which the nonhydrostatic grid is nested directly within the regional reanalysis exhibits the greatest overall agreement with observational data. Results therefore indicate that further development of nonhydrostatic nesting approaches is likely to yield important insights into the response of local-scale climate phenomena to increases in global greenhouse gas concentrations. However, the biases in regional precipitation, atmospheric circulation, and moisture flux identified in a subset of the nonhydrostatic simulations suggest that alternative nonhydrostatic modeling approaches such as superparameterization and variable-resolution global nonhydrostatic modeling will provide important complements to the nested approaches tested here.

Four-arm variable-resolution x-ray detector for CT target imaging

NASA Astrophysics Data System (ADS)

DiBianca, Frank A.; Gulabani, Daya; Jordan, Lawrence M.; Vangala, Sravanthi; Rendon, David; Laughter, Joseph S.; Melnyk, Roman; Gaber, M. W.; Keyes, Gary S.

2005-04-01

The basic VRX technique boosts spatial resolution of a CT scanner in the scan plane by two or more orders of magnitude by reducing the angle of incidence of the x-ray beam with respect to the detector surface. A four-arm Variable-Resolution X-ray (VRX) detector has been developed for CT scanning. The detector allows for "target imaging" in which an area of interest is scanned at higher resolution than the remainder of the subject, yielding even higher resolution for the focal area than that obtained from the basic VRX technique. The new VRX-CT detector comprises four quasi-identical arms each containing six 24-cell modules (576 cells total). The modules are made of individual custom CdWO4 scintillators optically-coupled to custom photodiode arrays. The maximum scan field is 40 cm for a magnification of 1.4. A significant advantage of the four-arm geometry is that it can transform quickly to the two-arm, or even the single-arm geometry, for comparison studies. These simpler geometries have already been shown experimentally to yield in-plane CT detector resolution exceeding 60 cy/mm (<8μ) for small fields of view. Geometrical size and resolution limits of the target VRX field are calculated. Two-arm VRX-CT data are used to simulate and establish the feasibility of VRX CT target imaging. A prototype target VRX-CT scanner has been built and is undergoing initial testing.

Variability along the Atlantic water pathway in the forced Norwegian Earth System Model

NASA Astrophysics Data System (ADS)

Langehaug, H. R.; Sandø, A. B.; Årthun, M.; Ilıcak, M.

2018-03-01

The growing attention on mechanisms that can provide predictability on interannual-to-decadal time scales, makes it necessary to identify how well climate models represent such mechanisms. In this study we use a high (0.25° horizontal grid) and a medium (1°) resolution version of a forced global ocean-sea ice model, utilising the Norwegian Earth System Model, to assess the impact of increased ocean resolution. Our target is the simulation of temperature and salinity anomalies along the pathway of warm Atlantic water in the subpolar North Atlantic and the Nordic Seas. Although the high resolution version has larger biases in general at the ocean surface, the poleward propagation of thermohaline anomalies is better resolved in this version, i.e., the time for an anomaly to travel northward is more similar to observation based estimates. The extent of these anomalies can be rather large in both model versions, as also seen in observations, e.g., stretching from Scotland to northern Norway. The easternmost branch into the Nordic and Barents Seas, carrying warm Atlantic water, is also improved by higher resolution, both in terms of mean heat transport and variability in thermohaline properties. A more detailed assessment of the link between the North Atlantic Ocean circulation and the thermohaline anomalies at the entrance of the Nordic Seas reveals that the high resolution is more consistent with mechanisms that are previously published. This suggests better dynamics and variability in the subpolar region and the Nordic Seas in the high resolution compared to the medium resolution. This is most likely due a better representation of the mean circulation in the studied region when using higher resolution. As the poleward propagation of ocean heat anomalies is considered to be a key source of climate predictability, we recommend that similar methodology presented herein should be performed on coupled climate models that are used for climate prediction.

Weather extremes in very large, high-resolution ensembles: the weatherathome experiment

NASA Astrophysics Data System (ADS)

Allen, M. R.; Rosier, S.; Massey, N.; Rye, C.; Bowery, A.; Miller, J.; Otto, F.; Jones, R.; Wilson, S.; Mote, P.; Stone, D. A.; Yamazaki, Y. H.; Carrington, D.

2011-12-01

Resolution and ensemble size are often seen as alternatives in climate modelling. Models with sufficient resolution to simulate many classes of extreme weather cannot normally be run often enough to assess the statistics of rare events, still less how these statistics may be changing. As a result, assessments of the impact of external forcing on regional climate extremes must be based either on statistical downscaling from relatively coarse-resolution models, or statistical extrapolation from 10-year to 100-year events. Under the weatherathome experiment, part of the climateprediction.net initiative, we have compiled the Met Office Regional Climate Model HadRM3P to run on personal computer volunteered by the general public at 25 and 50km resolution, embedded within the HadAM3P global atmosphere model. With a global network of about 50,000 volunteers, this allows us to run time-slice ensembles of essentially unlimited size, exploring the statistics of extreme weather under a range of scenarios for surface forcing and atmospheric composition, allowing for uncertainty in both boundary conditions and model parameters. Current experiments, developed with the support of Microsoft Research, focus on three regions, the Western USA, Europe and Southern Africa. We initially simulate the period 1959-2010 to establish which variables are realistically simulated by the model and on what scales. Our next experiments are focussing on the Event Attribution problem, exploring how the probability of various types of extreme weather would have been different over the recent past in a world unaffected by human influence, following the design of Pall et al (2011), but extended to a longer period and higher spatial resolution. We will present the first results of the unique, global, participatory experiment and discuss the implications for the attribution of recent weather events to anthropogenic influence on climate.

Quantifying the impact of sub-grid surface wind variability on sea salt and dust emissions in CAM5

NASA Astrophysics Data System (ADS)

Zhang, Kai; Zhao, Chun; Wan, Hui; Qian, Yun; Easter, Richard C.; Ghan, Steven J.; Sakaguchi, Koichi; Liu, Xiaohong

2016-02-01

This paper evaluates the impact of sub-grid variability of surface wind on sea salt and dust emissions in the Community Atmosphere Model version 5 (CAM5). The basic strategy is to calculate emission fluxes multiple times, using different wind speed samples of a Weibull probability distribution derived from model-predicted grid-box mean quantities. In order to derive the Weibull distribution, the sub-grid standard deviation of surface wind speed is estimated by taking into account four mechanisms: turbulence under neutral and stable conditions, dry convective eddies, moist convective eddies over the ocean, and air motions induced by mesoscale systems and fine-scale topography over land. The contributions of turbulence and dry convective eddy are parameterized using schemes from the literature. Wind variabilities caused by moist convective eddies and fine-scale topography are estimated using empirical relationships derived from an operational weather analysis data set at 15 km resolution. The estimated sub-grid standard deviations of surface wind speed agree well with reference results derived from 1 year of global weather analysis at 15 km resolution and from two regional model simulations with 3 km grid spacing.The wind-distribution-based emission calculations are implemented in CAM5. In terms of computational cost, the increase in total simulation time turns out to be less than 3 %. Simulations at 2° resolution indicate that sub-grid wind variability has relatively small impacts (about 7 % increase) on the global annual mean emission of sea salt aerosols, but considerable influence on the emission of dust. Among the considered mechanisms, dry convective eddies and mesoscale flows associated with topography are major causes of dust emission enhancement. With all the four mechanisms included and without additional adjustment of uncertain parameters in the model, the simulated global and annual mean dust emission increase by about 50 % compared to the default model. By tuning the globally constant dust emission scale factor, the global annual mean dust emission, aerosol optical depth, and top-of-atmosphere radiative fluxes can be adjusted to the level of the default model, but the frequency distribution of dust emission changes, with more contribution from weaker wind events and less contribution from stronger wind events. In Africa and Asia, the overall frequencies of occurrence of dust emissions increase, and the seasonal variations are enhanced, while the geographical patterns of the emission frequency show little change.

Quantifying the impact of sub-grid surface wind variability on sea salt and dust emissions in CAM5

DOE PAGES

Zhang, Kai; Zhao, Chun; Wan, Hui; ...

2016-02-12

This paper evaluates the impact of sub-grid variability of surface wind on sea salt and dust emissions in the Community Atmosphere Model version 5 (CAM5). The basic strategy is to calculate emission fluxes multiple times, using different wind speed samples of a Weibull probability distribution derived from model-predicted grid-box mean quantities. In order to derive the Weibull distribution, the sub-grid standard deviation of surface wind speed is estimated by taking into account four mechanisms: turbulence under neutral and stable conditions, dry convective eddies, moist convective eddies over the ocean, and air motions induced by mesoscale systems and fine-scale topography overmore » land. The contributions of turbulence and dry convective eddy are parameterized using schemes from the literature. Wind variabilities caused by moist convective eddies and fine-scale topography are estimated using empirical relationships derived from an operational weather analysis data set at 15 km resolution. The estimated sub-grid standard deviations of surface wind speed agree well with reference results derived from 1 year of global weather analysis at 15 km resolution and from two regional model simulations with 3 km grid spacing.The wind-distribution-based emission calculations are implemented in CAM5. In terms of computational cost, the increase in total simulation time turns out to be less than 3 %. Simulations at 2° resolution indicate that sub-grid wind variability has relatively small impacts (about 7 % increase) on the global annual mean emission of sea salt aerosols, but considerable influence on the emission of dust. Among the considered mechanisms, dry convective eddies and mesoscale flows associated with topography are major causes of dust emission enhancement. With all the four mechanisms included and without additional adjustment of uncertain parameters in the model, the simulated global and annual mean dust emission increase by about 50 % compared to the default model. By tuning the globally constant dust emission scale factor, the global annual mean dust emission, aerosol optical depth, and top-of-atmosphere radiative fluxes can be adjusted to the level of the default model, but the frequency distribution of dust emission changes, with more contribution from weaker wind events and less contribution from stronger wind events. Lastly, in Africa and Asia, the overall frequencies of occurrence of dust emissions increase, and the seasonal variations are enhanced, while the geographical patterns of the emission frequency show little change.« less

Quantifying the impact of sub-grid surface wind variability on sea salt and dust emissions in CAM5

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

Zhang, Kai; Zhao, Chun; Wan, Hui

This paper evaluates the impact of sub-grid variability of surface wind on sea salt and dust emissions in the Community Atmosphere Model version 5 (CAM5). The basic strategy is to calculate emission fluxes multiple times, using different wind speed samples of a Weibull probability distribution derived from model-predicted grid-box mean quantities. In order to derive the Weibull distribution, the sub-grid standard deviation of surface wind speed is estimated by taking into account four mechanisms: turbulence under neutral and stable conditions, dry convective eddies, moist convective eddies over the ocean, and air motions induced by mesoscale systems and fine-scale topography overmore » land. The contributions of turbulence and dry convective eddy are parameterized using schemes from the literature. Wind variabilities caused by moist convective eddies and fine-scale topography are estimated using empirical relationships derived from an operational weather analysis data set at 15 km resolution. The estimated sub-grid standard deviations of surface wind speed agree well with reference results derived from 1 year of global weather analysis at 15 km resolution and from two regional model simulations with 3 km grid spacing.The wind-distribution-based emission calculations are implemented in CAM5. In terms of computational cost, the increase in total simulation time turns out to be less than 3 %. Simulations at 2° resolution indicate that sub-grid wind variability has relatively small impacts (about 7 % increase) on the global annual mean emission of sea salt aerosols, but considerable influence on the emission of dust. Among the considered mechanisms, dry convective eddies and mesoscale flows associated with topography are major causes of dust emission enhancement. With all the four mechanisms included and without additional adjustment of uncertain parameters in the model, the simulated global and annual mean dust emission increase by about 50 % compared to the default model. By tuning the globally constant dust emission scale factor, the global annual mean dust emission, aerosol optical depth, and top-of-atmosphere radiative fluxes can be adjusted to the level of the default model, but the frequency distribution of dust emission changes, with more contribution from weaker wind events and less contribution from stronger wind events. Lastly, in Africa and Asia, the overall frequencies of occurrence of dust emissions increase, and the seasonal variations are enhanced, while the geographical patterns of the emission frequency show little change.« less

The effects of temporal variability of mixed layer depth on primary productivity around Bermuda

NASA Technical Reports Server (NTRS)

Bissett, W. Paul; Meyers, Mark B.; Walsh, John J.; Mueller-Karger, Frank E.

1994-01-01

Temporal variations in primary production and surface chlorophyll concentrations, as measured by ship and satellite around Bermuda, were simulated with a numerical model. In the upper 450 m of the water column, population dynamics of a size-fractionated phytoplankton community were forced by daily changes of wind, light, grazing stress, and nutrient availability. The temporal variations of production and chlorophyll were driven by changes in nutrient introduction to the euphotic zone due to both high- and low-frequency changes of the mixed layer depth within 32 deg-34 deg N, 62 deg-64 deg W between 1979 and 1984. Results from the model derived from high-frequency (case 1) changes in the mixed layer depth showed variations in primary production and peak chlorophyll concentrations when compared with results from the model derived from low-frequency (case 2) mixed layer depth changes. Incorporation of size-fractionated plankton state variables in the model led to greater seasonal resolution of measured primary production and vertical chlorophyll profiles. The findings of this study highlight the possible inadequacy of estimating primary production in the sea from data of low-frequency temporal resolution and oversimplified biological simulations.

Nonlinear vs. linear biasing in Trp-cage folding simulations

NASA Astrophysics Data System (ADS)

Spiwok, Vojtěch; Oborský, Pavel; Pazúriková, Jana; Křenek, Aleš; Králová, Blanka

2015-03-01

Biased simulations have great potential for the study of slow processes, including protein folding. Atomic motions in molecules are nonlinear, which suggests that simulations with enhanced sampling of collective motions traced by nonlinear dimensionality reduction methods may perform better than linear ones. In this study, we compare an unbiased folding simulation of the Trp-cage miniprotein with metadynamics simulations using both linear (principle component analysis) and nonlinear (Isomap) low dimensional embeddings as collective variables. Folding of the mini-protein was successfully simulated in 200 ns simulation with linear biasing and non-linear motion biasing. The folded state was correctly predicted as the free energy minimum in both simulations. We found that the advantage of linear motion biasing is that it can sample a larger conformational space, whereas the advantage of nonlinear motion biasing lies in slightly better resolution of the resulting free energy surface. In terms of sampling efficiency, both methods are comparable.

Nonlinear vs. linear biasing in Trp-cage folding simulations.

PubMed

Spiwok, Vojtěch; Oborský, Pavel; Pazúriková, Jana; Křenek, Aleš; Králová, Blanka

2015-03-21

Biased simulations have great potential for the study of slow processes, including protein folding. Atomic motions in molecules are nonlinear, which suggests that simulations with enhanced sampling of collective motions traced by nonlinear dimensionality reduction methods may perform better than linear ones. In this study, we compare an unbiased folding simulation of the Trp-cage miniprotein with metadynamics simulations using both linear (principle component analysis) and nonlinear (Isomap) low dimensional embeddings as collective variables. Folding of the mini-protein was successfully simulated in 200 ns simulation with linear biasing and non-linear motion biasing. The folded state was correctly predicted as the free energy minimum in both simulations. We found that the advantage of linear motion biasing is that it can sample a larger conformational space, whereas the advantage of nonlinear motion biasing lies in slightly better resolution of the resulting free energy surface. In terms of sampling efficiency, both methods are comparable.

Benchmarking the mesoscale variability in global ocean eddy-permitting numerical systems

NASA Astrophysics Data System (ADS)

Cipollone, Andrea; Masina, Simona; Storto, Andrea; Iovino, Doroteaciro

2017-10-01

The role of data assimilation procedures on representing ocean mesoscale variability is assessed by applying eddy statistics to a state-of-the-art global ocean reanalysis (C-GLORS), a free global ocean simulation (performed with the NEMO system) and an observation-based dataset (ARMOR3D) used as an independent benchmark. Numerical results are computed on a 1/4 ∘ horizontal grid (ORCA025) and share the same resolution with ARMOR3D dataset. This "eddy-permitting" resolution is sufficient to allow ocean eddies to form. Further to assessing the eddy statistics from three different datasets, a global three-dimensional eddy detection system is implemented in order to bypass the need of regional-dependent definition of thresholds, typical of commonly adopted eddy detection algorithms. It thus provides full three-dimensional eddy statistics segmenting vertical profiles from local rotational velocities. This criterion is crucial for discerning real eddies from transient surface noise that inevitably affects any two-dimensional algorithm. Data assimilation enhances and corrects mesoscale variability on a wide range of features that cannot be well reproduced otherwise. The free simulation fairly reproduces eddies emerging from western boundary currents and deep baroclinic instabilities, while underestimates shallower vortexes that populate the full basin. The ocean reanalysis recovers most of the missing turbulence, shown by satellite products , that is not generated by the model itself and consistently projects surface variability deep into the water column. The comparison with the statistically reconstructed vertical profiles from ARMOR3D show that ocean data assimilation is able to embed variability into the model dynamics, constraining eddies with in situ and altimetry observation and generating them consistently with local environment.

Evaluating climate models: Should we use weather or climate observations?

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

Oglesby, Robert J; Erickson III, David J

2009-12-01

Calling the numerical models that we use for simulations of climate change 'climate models' is a bit of a misnomer. These 'general circulation models' (GCMs, AKA global climate models) and their cousins the 'regional climate models' (RCMs) are actually physically-based weather simulators. That is, these models simulate, either globally or locally, daily weather patterns in response to some change in forcing or boundary condition. These simulated weather patterns are then aggregated into climate statistics, very much as we aggregate observations into 'real climate statistics'. Traditionally, the output of GCMs has been evaluated using climate statistics, as opposed to their abilitymore » to simulate realistic daily weather observations. At the coarse global scale this may be a reasonable approach, however, as RCM's downscale to increasingly higher resolutions, the conjunction between weather and climate becomes more problematic. We present results from a series of present-day climate simulations using the WRF ARW for domains that cover North America, much of Latin America, and South Asia. The basic domains are at a 12 km resolution, but several inner domains at 4 km have also been simulated. These include regions of complex topography in Mexico, Colombia, Peru, and Sri Lanka, as well as a region of low topography and fairly homogeneous land surface type (the U.S. Great Plains). Model evaluations are performed using standard climate analyses (e.g., reanalyses; NCDC data) but also using time series of daily station observations. Preliminary results suggest little difference in the assessment of long-term mean quantities, but the variability on seasonal and interannual timescales is better described. Furthermore, the value-added by using daily weather observations as an evaluation tool increases with the model resolution.« less

High-resolution dynamical downscaling of the future Alpine climate

NASA Astrophysics Data System (ADS)

Bozhinova, Denica; José Gómez-Navarro, Juan; Raible, Christoph

2017-04-01

The Alpine region and Switzerland is a challenging area for simulating and analysing Global Climate Model (GCM) results. This is mostly due to the combination of a very complex topography and the still rather coarse horizontal resolution of current GCMs, in which not all of the many-scale processes that drive the local weather and climate can be resolved. In our study, the Weather Research and Forecasting (WRF) model is used to dynamically downscale a GCM simulation to a resolution as high as 2 km x 2 km. WRF is driven by initial and boundary conditions produced with the Community Earth System Model (CESM) for the recent past (control run) and until 2100 using the RCP8.5 climate scenario (future run). The control run downscaled with WRF covers the period 1976-2005, while the future run investigates a 20-year-slice simulated for the 2080-2099. We compare the control WRF-CESM simulations to an observational product provided by MeteoSwiss and an additional WRF simulation driven by the ERA-Interim reanalysis, to estimate the bias that is introduced by the extra modelling step of our framework. Several bias-correction methods are evaluated, including a quantile mapping technique, to ameliorate the bias in the control WRF-CESM simulation. In the next step of our study these corrections are applied to our future WRF-CESM run. The resulting downscaled and bias-corrected data is analysed for the properties of precipitation and wind speed in the future climate. Our special interest focuses on the absolute quantities simulated for these meteorological variables as these are used to identify extreme events, such as wind storms and situations that can lead to floods.

On the Feasibility of Monitoring Carbon Monoxide in the Lower Troposphere from a Constellation of Northern Hemisphere Geostationary Satellites (PART 1)

NASA Technical Reports Server (NTRS)

Barre, Jerome; Edwards, David; Worden, Helen; Da Silva, Arlindo; Lahoz, William

2015-01-01

By the end of the current decade, there are plans to deploy several geostationary Earth orbit (GEO) satellite missions for atmospheric composition over North America, East Asia and Europe with additional missions proposed. Together, these present the possibility of a constellation of geostationary platforms to achieve continuous time-resolved high-density observations over continental domains for mapping pollutant sources and variability at diurnal and local scales. In this paper, we use a novel approach to sample a very high global resolution model (GEOS-5 at 7 km horizontal resolution) to produce a dataset of synthetic carbon monoxide pollution observations representative of those potentially obtainable from a GEO satellite constellation with predicted measurement sensitivities based on current remote sensing capabilities. Part 1 of this study focuses on the production of simulated synthetic measurements for air quality OSSEs (Observing System Simulation Experiments). We simulate carbon monoxide nadir retrievals using a technique that provides realistic measurements with very low computational cost. We discuss the sampling methodology: the projection of footprints and areas of regard for geostationary geometries over each of the North America, East Asia and Europe regions; the regression method to simulate measurement sensitivity; and the measurement error simulation. A detailed analysis of the simulated observation sensitivity is performed, and limitations of the method are discussed. We also describe impacts from clouds, showing that the efficiency of an instrument making atmospheric composition measurements on a geostationary platform is dependent on the dominant weather regime over a given region and the pixel size resolution. These results demonstrate the viability of the "instrument simulator" step for an OSSE to assess the performance of a constellation of geostationary satellites for air quality measurements.

Seasonal and interannual variability of the Arctic sea ice: A comparison between AO-FVCOM and observations

NASA Astrophysics Data System (ADS)

Zhang, Yu; Chen, Changsheng; Beardsley, Robert C.; Gao, Guoping; Qi, Jianhua; Lin, Huichan

2016-11-01

A high-resolution (up to 2 km), unstructured-grid, fully ice-sea coupled Arctic Ocean Finite-Volume Community Ocean Model (AO-FVCOM) was used to simulate the sea ice in the Arctic over the period 1978-2014. The spatial-varying horizontal model resolution was designed to better resolve both topographic and baroclinic dynamics scales over the Arctic slope and narrow straits. The model-simulated sea ice was in good agreement with available observed sea ice extent, concentration, drift velocity and thickness, not only in seasonal and interannual variability but also in spatial distribution. Compared with six other Arctic Ocean models (ECCO2, GSFC, INMOM, ORCA, NAME, and UW), the AO-FVCOM-simulated ice thickness showed a higher mean correlation coefficient of ˜0.63 and a smaller residual with observations. Model-produced ice drift speed and direction errors varied with wind speed: the speed and direction errors increased and decreased as the wind speed increased, respectively. Efforts were made to examine the influences of parameterizations of air-ice external and ice-water interfacial stresses on the model-produced bias. The ice drift direction was more sensitive to air-ice drag coefficients and turning angles than the ice drift speed. Increasing or decreasing either 10% in water-ice drag coefficient or 10° in water-ice turning angle did not show a significant influence on the ice drift velocity simulation results although the sea ice drift speed was more sensitive to these two parameters than the sea ice drift direction. Using the COARE 4.0-derived parameterization of air-water drag coefficient for wind stress did not significantly influence the ice drift velocity simulation.

High resolution numerical simulation (WRF V3) of an extreme rainy event over the Guadeloupe archipelago: Case of 3-5 january 2011.

NASA Astrophysics Data System (ADS)

Bernard, Didier C.; Cécé, Raphaël; Dorville, Jean-François

2013-04-01

During the dry season, the Guadeloupe archipelago may be affected by extreme rainy disturbances which may induce floods in a very short time. C. Brévignon (2003) considered a heavy rain event for rainfall upper 100 mm per day (out of mountainous areas) for this tropical region. During a cold front passage (3-5 January 2011), torrential rainfalls caused floods, major damages, landslides and five deaths. This phenomenon has put into question the current warning system based on large scale numerical models. This low-resolution forecasting (around 50-km scale) has been unsuitable for small tropical island like Guadeloupe (1600 km2). The most affected area was the middle of Grande-Terre island which is the main flat island of the archipelago (area of 587 km2, peak at 136 m). It is the most populated sector of Guadeloupe. In this area, observed rainfall have reached to 100-160 mm in 24 hours (this amount is equivalent to two months of rain for January (C. Brévignon, 2003)), in less 2 hours drainage systems have been saturated, and five people died in a ravine. Since two years, the atmospheric model WRF ARW V3 (Skamarock et al., 2008) has been used to modeling meteorological variables fields observed over the Guadeloupe archipelago at high resolution 1-km scale (Cécé et al., 2011). The model error estimators show that meteorological variables seem to be properly simulated for standard types of weather: undisturbed, strong or weak trade winds. These simulations indicate that for synoptic winds weak to moderate, a small island like Grande-Terre is able to generate inland convergence zones during daytime. In this presentation, we apply this high resolution model to simulate this extreme rainy disturbance of 3-5 January 2011. The evolution of modeling meteorological variable fields is analyzed in the most affected area of Grande-Terre (city of Les Abymes). The main goal is to examine local quasi-stationary updraft systems and highlight their convective mechanisms. The spatio-temporal distribution of simulated rainfall could help to design the prevention and evacuation plan, particularly for the flooding areas. The meteorological variable fields simulated are evaluated by comparison with observed data of meteorological weather stations (French Met. Office) available in the area. Brévignon, C., 2003: Atlas climatique: l'environnement atmosphérique de la Guadeloupe, de Saint-Barthélémy et Saint-martin. Météo-France, Service Régional de Guadeloupe, 92 pp. Cécé, R., T. Plocoste, C. D'Alexis, D. Bernard and J.-F. Dorville, 2012: Modélisation numérique à l'échelle locale des situations météorologiques observées au cours de la transition saison sèche - saison humide à l'aide de WRF ARW V3 : cas de l'archipel de la Guadeloupe. AMA 2012, Toulouse. Skamarock, W. C., J. B. Klemp, J. Dudhia, D. O. Gill, D. M. Barker, M. G. Duda, X.-Y. Huang, W. Wang, and J. G. Powers, 2008: A Description of the Advanced Research WRF Version 3.Tech. Rep., National Center for Atmospheric Research.

Assessment of upper-ocean variability and the Madden-Julian Oscillation in extended-range air-ocean coupled mesoscale simulations

NASA Astrophysics Data System (ADS)

Hong, Xiaodong; Reynolds, Carolyn A.; Doyle, James D.; May, Paul; O'Neill, Larry

2017-06-01

Atmosphere-ocean interaction, particular the ocean response to strong atmospheric forcing, is a fundamental component of the Madden-Julian Oscillation (MJO). In this paper, we examine how model errors in previous Madden-Julian Oscillation (MJO) events can affect the simulation of subsequent MJO events due to increased errors that develop in the upper-ocean before the MJO initiation stage. Two fully coupled numerical simulations with 45-km and 27-km horizontal resolutions were integrated for a two-month period from November to December 2011 using the Navy's limited area Coupled Ocean/Atmosphere Mesoscale Prediction System (COAMPS®). There are three MJO events that occurred subsequently in early November, mid-November, and mid-December during the simulations. The 45-km simulation shows an excessive warming of the SSTs during the suppressed phase that occurs before the initiation of the second MJO event due to erroneously strong surface net heat fluxes. The simulated second MJO event stalls over the Maritime Continent which prevents the recovery of the deep mixed layer and associated barrier layer. Cross-wavelet analysis of solar radiation and SSTs reveals that the diurnal warming is absent during the second suppressed phase after the second MJO event. The mixed layer heat budget indicates that the cooling is primarily caused by horizontal advection associated with the stalling of the second MJO event and the cool SSTs fail to initiate the third MJO event. When the horizontal resolution is increased to 27-km, three MJOs are simulated and compare well with observations on multi-month timescales. The higher-resolution simulation of the second MJO event and more-realistic upper-ocean response promote the onset of the third MJO event. Simulations performed with analyzed SSTs indicate that the stalling of the second MJO in the 45-km run is a robust feature, regardless of ocean forcing, while the diurnal cycle analysis indicates that both 45-km and 27-km ocean resolutions respond realistically when provided with realistic atmospheric forcing. Thus, the problem in the 45-km simulation appears to originate in the atmosphere. Additional simulations show that while the details of the simulations are sensitive to small changes in the initial integration time, the large differences between the 45-km and 27-km runs during the suppressed phase in early December are robust.

Role of Micro-Topographic Variability on the Distribution of Inorganic Soil-Nitrogen Age in Intensively Managed Landscape

NASA Astrophysics Data System (ADS)

Woo, Dong K.; Kumar, Praveen

2017-10-01

How does the variability of topography structure the spatial heterogeneity of nutrient dynamics? In particular, what role does micro-topographic depression play in the spatial and temporal dynamics of nitrate, ammonia, and ammonium? We explore these questions using the 3-D simulation of their joint dynamics of concentration and age. To explicitly resolve micro-topographic variability and its control on moisture, vegetation, and carbon-nitrogen dynamics, we use a high-resolution LiDAR data over an agricultural site under a corn-soybean rotation in the Intensively Managed landscapes Critical Zone Observatory in the U.S. Midwest. We utilize a hybrid CPU-GPU parallel computing architecture to reduce the computational cost associated with such high-resolution simulations. Our results show that in areas that present closed topographic depressions, relatively lower nitrate concentration and age are observed compared to elsewhere. The periodic ponding in depressions increases the downward flux of water that carries more dissolved nitrate to the deeper soil layer. However, the variability in the depressions is relatively higher as a result of the episodic ponding pattern. When aggregate efflux from the soil domain at the bottom of the soil is considered, we find a gradual decrease in the age on the rising limb of nitrate efflux and a gradual increase on the falling limb. In addition, the age of the nitrate efflux ranges from 4 to 7 years. These are significantly higher as compared to the ages associated with a nonreactive tracer indicating that they provide an inaccurate estimate of residence time of a reactive constituent through the soil column.

High resolution modeling of a small urban catchment

NASA Astrophysics Data System (ADS)

Skouri-Plakali, Ilektra; Ichiba, Abdellah; Gires, Auguste; Tchiguirinskaia, Ioulia; Schertzer, Daniel

2016-04-01

Flooding is one of the most complex issues that urban environments have to deal with. In France, flooding remains the first natural risk with 72% of decrees state of natural disaster issued between October 1982 and mid-November 2014. Flooding is a result of meteorological extremes that are usually aggravated by the hydrological behavior of urban catchments and human factors. The continuing urbanization process is indeed changing the whole urban water cycle by limiting the infiltration and promoting runoff. Urban environments are very complex systems due to their extreme variability, the interference between human activities and natural processes but also the effect of the ongoing urbanization process that changes the landscape and hardly influences their hydrologic behavior. Moreover, many recent works highlight the need to simulate all urban water processes at their specific temporal and spatial scales. However, considering urban catchments heterogeneity still challenging for urban hydrology, even after advances noticed in term of high-resolution data collection and computational resources. This issue is more to be related to the architecture of urban models being used and how far these models are ready to take into account the extreme variability of urban catchments. In this work, high spatio-temporal resolution modeling is performed for a small and well-equipped urban catchment. The aim of this work is to identify urban modeling needs in terms of spatial and temporal resolution especially for a very small urban area (3.7 ha urban catchment located in the Perreux-sur-Marne city at the southeast of Paris) MultiHydro model was selected to carry out this work, it is a physical based and fully distributed model that interacts four existing modules each of them representing a portion of the water cycle in urban environments. MultiHydro was implemented at 10m, 5m and 2m resolution. Simulations were performed at different spatio-temporal resolutions and analyzed with respect to real flow measurements. First Results coming out show improvements obtained in terms of the model performance at high spatio-temporal resolution.

Simulating Virtual Terminal Area Weather Data Bases for Use in the Wake Vortex Avoidance System (Wake VAS) Prediction Algorithm

NASA Technical Reports Server (NTRS)

Kaplan, Michael L.; Lin, Yuh-Lang

2004-01-01

During the research project, sounding datasets were generated for the region surrounding 9 major airports, including Dallas, TX, Boston, MA, New York, NY, Chicago, IL, St. Louis, MO, Atlanta, GA, Miami, FL, San Francico, CA, and Los Angeles, CA. The numerical simulation of winter and summer environments during which no instrument flight rule impact was occurring at these 9 terminals was performed using the most contemporary version of the Terminal Area PBL Prediction System (TAPPS) model nested from 36 km to 6 km to 1 km horizontal resolution and very detailed vertical resolution in the planetary boundary layer. The soundings from the 1 km model were archived at 30 minute time intervals for a 24 hour period and the vertical dependent variables as well as derived quantities, i.e., 3-dimensional wind components, temperatures, pressures, mixing ratios, turbulence kinetic energy and eddy dissipation rates were then interpolated to 5 m vertical resolution up to 1000 m elevation above ground level. After partial validation against field experiment datasets for Dallas as well as larger scale and much coarser resolution observations at the other 8 airports, these sounding datasets were sent to NASA for use in the Virtual Air Space and Modeling program. The application of these datasets being to determine representative airport weather environments to diagnose the response of simulated wake vortices to realistic atmospheric environments. These virtual datasets are based on large scale observed atmospheric initial conditions that are dynamically interpolated in space and time. The 1 km nested-grid simulated datasets providing a very coarse and highly smoothed representation of airport environment meteorological conditions. Details concerning the airport surface forcing are virtually absent from these simulated datasets although the observed background atmospheric processes have been compared to the simulated fields and the fields were found to accurately replicate the flows surrounding the airport where coarse verification data were available as well as where airport scale datasets were available.

Downscaled climate change projections with uncertainty assessment over India using a high resolution multi-model approach.

PubMed

Kumar, Pankaj; Wiltshire, Andrew; Mathison, Camilla; Asharaf, Shakeel; Ahrens, Bodo; Lucas-Picher, Philippe; Christensen, Jens H; Gobiet, Andreas; Saeed, Fahad; Hagemann, Stefan; Jacob, Daniela

2013-12-01

This study presents the possible regional climate change over South Asia with a focus over India as simulated by three very high resolution regional climate models (RCMs). One of the most striking results is a robust increase in monsoon precipitation by the end of the 21st century but regional differences in strength. First the ability of RCMs to simulate the monsoon climate is analyzed. For this purpose all three RCMs are forced with ECMWF reanalysis data for the period 1989-2008 at a horizontal resolution of ~25 km. The results are compared against independent observations. In order to simulate future climate the models are driven by lateral boundary conditions from two global climate models (GCMs: ECHAM5-MPIOM and HadCM3) using the SRES A1B scenario, except for one RCM, which only used data from one GCM. The results are presented for the full transient simulation period 1970-2099 and also for several time slices. The analysis concentrates on precipitation and temperature over land. All models show a clear signal of gradually wide-spread warming throughout the 21st century. The ensemble-mean warming over India is 1.5°C at the end of 2050, whereas it is 3.9°C at the end of century with respect to 1970-1999. The pattern of projected precipitation changes shows considerable spatial variability, with an increase in precipitation over the peninsular of India and coastal areas and, either no change or decrease further inland. From the analysis of a larger ensemble of global climate models using the A1B scenario a wide spread warming (~3.2°C) and an overall increase (~8.5%) in mean monsoon precipitation by the end of the 21st century is very likely. The influence of the driving GCM on the projected precipitation change simulated with each RCM is as strong as the variability among the RCMs driven with one. Copyright © 2013 Elsevier B.V. All rights reserved.

Holocene climate variability in Texas, USA: An integration of existing paleoclimate data and modeling with a new, high-resolution speleothem record

NASA Astrophysics Data System (ADS)

Wong, Corinne I.; Banner, Jay L.; Musgrove, MaryLynn

2015-11-01

Delineating the climate processes governing precipitation variability in drought-prone Texas is critical for predicting and mitigating climate change effects, and requires the reconstruction of past climate beyond the instrumental record. We synthesize existing paleoclimate proxy data and climate simulations to provide an overview of climate variability in Texas during the Holocene. Conditions became progressively warmer and drier transitioning from the early to mid Holocene, culminating between 7 and 3 ka (thousand years ago), and were more variable during the late Holocene. The timing and relative magnitude of Holocene climate variability, however, is poorly constrained owing to considerable variability among the different records. To help address this, we present a new speleothem (NBJ) reconstruction from a central Texas cave that comprises the highest resolution proxy record to date, spanning the mid to late Holocene. NBJ trace-element concentrations indicate variable moisture conditions with no clear temporal trend. There is a decoupling between NBJ growth rate, trace-element concentrations, and δ18O values, which indicate that (i) the often direct relation between speleothem growth rate and moisture availability is likely complicated by changes in the overlying ecosystem that affect subsurface CO2 production, and (ii) speleothem δ18O variations likely reflect changes in moisture source (i.e., proportion of Pacific-vs. Gulf of Mexico-derived moisture) that appear not to be linked to moisture amount.

Investigating wind turbine impacts on near-wake flow using profiling Lidar data and large-eddy simulations with an actuator disk model

DOE PAGES

Mirocha, Jeffrey D.; Rajewski, Daniel A.; Marjanovic, Nikola; ...

2015-08-27

In this study, wind turbine impacts on the atmospheric flow are investigated using data from the Crop Wind Energy Experiment (CWEX-11) and large-eddy simulations (LESs) utilizing a generalized actuator disk (GAD) wind turbine model. CWEX-11 employed velocity-azimuth display (VAD) data from two Doppler lidar systems to sample vertical profiles of flow parameters across the rotor depth both upstream and in the wake of an operating 1.5 MW wind turbine. Lidar and surface observations obtained during four days of July 2011 are analyzed to characterize the turbine impacts on wind speed and flow variability, and to examine the sensitivity of thesemore » changes to atmospheric stability. Significant velocity deficits (VD) are observed at the downstream location during both convective and stable portions of four diurnal cycles, with large, sustained deficits occurring during stable conditions. Variances of the streamwise velocity component, σ u, likewise show large increases downstream during both stable and unstable conditions, with stable conditions supporting sustained small increases of σ u , while convective conditions featured both larger magnitudes and increased variability, due to the large coherent structures in the background flow. Two representative case studies, one stable and one convective, are simulated using LES with a GAD model at 6 m resolution to evaluate the compatibility of the simulation framework with validation using vertically profiling lidar data in the near wake region. Virtual lidars were employed to sample the simulated flow field in a manner consistent with the VAD technique. Simulations reasonably reproduced aggregated wake VD characteristics, albeit with smaller magnitudes than observed, while σu values in the wake are more significantly underestimated. The results illuminate the limitations of using a GAD in combination with coarse model resolution in the simulation of near wake physics, and validation thereof using VAD data.« less

Simulating and explaining passive air sampling rates for semi-volatile compounds on polyurethane foam passive samplers

PubMed Central

Petrich, Nicholas T.; Spak, Scott N.; Carmichael, Gregory R.; Hu, Dingfei; Martinez, Andres; Hornbuckle, Keri C.

2013-01-01

Passive air samplers (PAS) including polyurethane foam (PUF) are widely deployed as an inexpensive and practical way to sample semi-volatile pollutants. However, concentration estimates from PAS rely on constant empirical mass transfer rates, which add unquantified uncertainties to concentrations. Here we present a method for modeling hourly sampling rates for semi-volatile compounds from hourly meteorology using first-principle chemistry, physics, and fluid dynamics, calibrated from depuration experiments. This approach quantifies and explains observed effects of meteorology on variability in compound-specific sampling rates and analyte concentrations; simulates nonlinear PUF uptake; and recovers synthetic hourly concentrations at a reference temperature. Sampling rates are evaluated for polychlorinated biphenyl congeners at a network of Harner model samplers in Chicago, Illinois during 2008, finding simulated average sampling rates within analytical uncertainty of those determined from loss of depuration compounds, and confirming quasi-linear uptake. Results indicate hourly, daily and interannual variability in sampling rates, sensitivity to temporal resolution in meteorology, and predictable volatility-based relationships between congeners. We quantify importance of each simulated process to sampling rates and mass transfer and assess uncertainty contributed by advection, molecular diffusion, volatilization, and flow regime within the PAS, finding PAS chamber temperature contributes the greatest variability to total process uncertainty (7.3%). PMID:23837599

Visualization of the Eastern Renewable Generation Integration Study: Preprint

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

Gruchalla, Kenny; Novacheck, Joshua; Bloom, Aaron

The Eastern Renewable Generation Integration Study (ERGIS), explores the operational impacts of the wide spread adoption of wind and solar photovoltaics (PV) resources in the U.S. Eastern Interconnection and Quebec Interconnection (collectively, EI). In order to understand some of the economic and reliability challenges of managing hundreds of gigawatts of wind and PV generation, we developed state of the art tools, data, and models for simulating power system operations using hourly unit commitment and 5-minute economic dispatch over an entire year. Using NREL's high-performance computing capabilities and new methodologies to model operations, we found that the EI, as simulated withmore » evolutionary change in 2026, could balance the variability and uncertainty of wind and PV at a 5-minute level under a variety of conditions. A large-scale display and a combination of multiple coordinated views and small multiples were used to visually analyze the four large highly multivariate scenarios with high spatial and temporal resolutions. state of the art tools, data, and models for simulating power system operations using hourly unit commitment and 5-minute economic dispatch over an entire year. Using NRELs high-performance computing capabilities and new methodologies to model operations, we found that the EI, as simulated with evolutionary change in 2026, could balance the variability and uncertainty of wind and PV at a 5-minute level under a variety of conditions. A large-scale display and a combination of multiple coordinated views and small multiples were used to visually analyze the four large highly multivariate scenarios with high spatial and temporal resolutions.« less

A high-resolution, regional analysis of stormwater runoff for managed aquifer recharge site assessment

NASA Astrophysics Data System (ADS)

Young, K. S.; Fisher, A. T.; Beganskas, S.; Harmon, R. E.; Teo, E. K.; Weir, W. B.; Lozano, S.

2016-12-01

Distributed Stormwater Collection-Managed Aquifer Recharge (DSC-MAR) presents a cost-effective method of aquifer replenishment by collecting runoff and infiltrating it into underlying aquifers, but its successful implementation demands thorough knowledge of the distribution and availability of hillslope runoff. We applied a surface hydrology model to analyze the dynamics of hillslope runoff at high resolution (0.1 to 1.0 km2) across the 350 km2 San Lorenzo River Basin (SLRB) watershed, northern Santa Cruz County, CA. We used a 3 m digital elevation model to create a detailed model grid, which we parameterized with high-resolution geologic, hydrologic, and land use data. To analyze hillslope runoff under a range of precipitation regimes, we developed dry, normal, and wet climate scenarios from historic daily precipitation records (1981-2014). Simulation results show high spatial variability of hillslope runoff generation as a function of differences in precipitation and soil and land use conditions, and reveal a consistent increase in the spatial and temporal variability of runoff under wetter climate scenarios. Our results suggest that there may be opportunities to develop successful DSC-MAR projects that provide benefits during all climate scenarios. In the SLRB, our results indicate that annual hillslope runoff generation achieves a target minimum of 100 acre-ft, per 100 acres of drainage area, in approximately 15% of the region during dry climate scenarios and 60% of the region during wet climate scenarios. The high spatial and temporal resolution of our simulation output enables quantification of hillslope runoff at sub-watershed scales, commensurate with the spacing and operation of DSC-MAR. This study demonstrates a viable tool for screening of potential DSC-MAR project sites and assessing project performance under a range of climate and land use scenarios.

Algebraic dynamic multilevel method for compositional flow in heterogeneous porous media

NASA Astrophysics Data System (ADS)

Cusini, Matteo; Fryer, Barnaby; van Kruijsdijk, Cor; Hajibeygi, Hadi

2018-02-01

This paper presents the algebraic dynamic multilevel method (ADM) for compositional flow in three dimensional heterogeneous porous media in presence of capillary and gravitational effects. As a significant advancement compared to the ADM for immiscible flows (Cusini et al., 2016) [33], here, mass conservation equations are solved along with k-value based thermodynamic equilibrium equations using a fully-implicit (FIM) coupling strategy. Two different fine-scale compositional formulations are considered: (1) the natural variables and (2) the overall-compositions formulation. At each Newton's iteration the fine-scale FIM Jacobian system is mapped to a dynamically defined (in space and time) multilevel nested grid. The appropriate grid resolution is chosen based on the contrast of user-defined fluid properties and on the presence of specific features (e.g., well source terms). Consistent mapping between different resolutions is performed by the means of sequences of restriction and prolongation operators. While finite-volume restriction operators are employed to ensure mass conservation at all resolutions, various prolongation operators are considered. In particular, different interpolation strategies can be used for the different primary variables, and multiscale basis functions are chosen as pressure interpolators so that fine scale heterogeneities are accurately accounted for across different resolutions. Several numerical experiments are conducted to analyse the accuracy, efficiency and robustness of the method for both 2D and 3D domains. Results show that ADM provides accurate solutions by employing only a fraction of the number of grid-cells employed in fine-scale simulations. As such, it presents a promising approach for large-scale simulations of multiphase flow in heterogeneous reservoirs with complex non-linear fluid physics.

Towards a high resolution, integrated hydrology model of North America: Diagnosis of feedbacks between groundwater and land energy fluxes at continental scales.

NASA Astrophysics Data System (ADS)

Maxwell, Reed; Condon, Laura

2016-04-01

Recent studies demonstrate feedbacks between groundwater dynamics, overland flow, land surface and vegetation processes, and atmospheric boundary layer development that significantly affect local and regional climate across a range of climatic conditions. Furthermore, the type and distribution of vegetation cover alters land-atmosphere water and energy fluxes, as well as runoff generation and overland flow processes. These interactions can result in significant feedbacks on local and regional climate. In mountainous regions, recent research has shown that spatial and temporal variability in annual evapotranspiration, and thus water budgets, is strongly dependent on lateral groundwater flow; however, the full effects of these feedbacks across varied terrain (e.g. from plains to mountains) are not well understood. Here, we present a high-resolution, integrated hydrology model that covers much of continental North America and encompasses the Mississippi and Colorado watersheds. The model is run in a fully-transient manner at hourly temporal resolution incorporating fully-coupled land energy states and fluxes with integrated surface and subsurface hydrology. Connections are seen between hydrologic variables (such as water table depth) and land energy fluxes (such as latent heat) and spatial and temporal scaling is shown to span many orders of magnitude. Model results suggest that partitioning of plant transpiration to bare soil evaporation is a function of water table depth and later groundwater flow. Using these transient simulations as a proof of concept, we present a vision for future integrated simulation capabilities.

Monthly and spatially resolved black carbon emission inventory of India: uncertainty analysis

NASA Astrophysics Data System (ADS)

Paliwal, Umed; Sharma, Mukesh; Burkhart, John F.

2016-10-01

Black carbon (BC) emissions from India for the year 2011 are estimated to be 901.11 ± 151.56 Gg yr-1 based on a new ground-up, GIS-based inventory. The grid-based, spatially resolved emission inventory includes, in addition to conventional sources, emissions from kerosene lamps, forest fires, diesel-powered irrigation pumps and electricity generators at mobile towers. The emissions have been estimated at district level and were spatially distributed onto grids at a resolution of 40 × 40 km2. The uncertainty in emissions has been estimated using a Monte Carlo simulation by considering the variability in activity data and emission factors. Monthly variation of BC emissions has also been estimated to account for the seasonal variability. To the total BC emissions, domestic fuels contributed most significantly (47 %), followed by industry (22 %), transport (17 %), open burning (12 %) and others (2 %). The spatial and seasonal resolution of the inventory will be useful for modeling BC transport in the atmosphere for air quality, global warming and other process-level studies that require greater temporal resolution than traditional inventories.

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

NASA Astrophysics Data System (ADS)

Teixeira, J.

2015-12-01

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

Chemical transport model ozone simulations for spring 2001 over the western Pacific: Comparisons with TRACE-P lidar, ozonesondes, and Total Ozone Mapping Spectrometer columns

NASA Astrophysics Data System (ADS)

Wild, Oliver; Sundet, Jostein K.; Prather, Michael J.; Isaksen, Ivar S. A.; Akimoto, Hajime; Browell, Edward V.; Oltmans, Samuel J.

2003-11-01

Two closely related chemical transport models (CTMs) employing the same high-resolution meteorological data (˜180 km × ˜180 km × ˜600 m) from the European Centre for Medium-Range Weather Forecasts are used to simulate the ozone total column and tropospheric distribution over the western Pacific region that was explored by the NASA Transport and Chemical Evolution over the Pacific (TRACE-P) measurement campaign in February-April 2001. We make extensive comparisons with ozone measurements from the lidar instrument on the NASA DC-8, with ozonesondes taken during the period around the Pacific Rim, and with TOMS total column ozone. These demonstrate that within the uncertainties of the meteorological data and the constraints of model resolution, the two CTMs (FRSGC/UCI and Oslo CTM2) can simulate the observed tropospheric ozone and do particularly well when realistic stratospheric ozone photochemistry is included. The greatest differences between the models and observations occur in the polluted boundary layer, where problems related to the simplified chemical mechanism and inadequate horizontal resolution are likely to have caused the net overestimation of about 10 ppb mole fraction. In the upper troposphere, the large variability driven by stratospheric intrusions makes agreement very sensitive to the timing of meteorological features.

A Coupled Surface Nudging Scheme for use in Retrospective ...

EPA Pesticide Factsheets

A surface analysis nudging scheme coupling atmospheric and land surface thermodynamic parameters has been implemented into WRF v3.8 (latest version) for use with retrospective weather and climate simulations, as well as for applications in air quality, hydrology, and ecosystem modeling. This scheme is known as the flux-adjusting surface data assimilation system (FASDAS) developed by Alapaty et al. (2008). This scheme provides continuous adjustments for soil moisture and temperature (via indirect nudging) and for surface air temperature and water vapor mixing ratio (via direct nudging). The simultaneous application of indirect and direct nudging maintains greater consistency between the soil temperature–moisture and the atmospheric surface layer mass-field variables. The new method, FASDAS, consistently improved the accuracy of the model simulations at weather prediction scales for different horizontal grid resolutions, as well as for high resolution regional climate predictions. This new capability has been released in WRF Version 3.8 as option grid_sfdda = 2. This new capability increased the accuracy of atmospheric inputs for use air quality, hydrology, and ecosystem modeling research to improve the accuracy of respective end-point research outcome. IMPACT: A new method, FASDAS, was implemented into the WRF model to consistently improve the accuracy of the model simulations at weather prediction scales for different horizontal grid resolutions, as wel

Impact of the model resolution on the simulation of elevation-dependent warming in the Tibetan Plateau-Himalayas, Greater Alpine Region, and Rocky mountains

NASA Astrophysics Data System (ADS)

Palazzi, Elisa; Mortarini, Luca; Terzago, Silvia; von Hardenberg, Jost

2017-04-01

The enhancement of warming rates with elevation, the so-called elevation-dependent warming (EDW), is one of the clearest regional expressions of global warming. Real sentinels of climate and environmental changes, mountains have experienced more rapid and intense warming rates in the recent decades, leading to serious impacts on mountain ecosystems and downstream societies, some of which are already occurring. In this study we use the historical and scenario simulations of one state-of-the-art global climate model, the EC-Earth GCM, run at five different spatial resolutions, from ˜125 km to ˜16 km, to explore the existence, characteristics and driving mechanisms of EDW in three different mountain regions of the world - the Colorado Rocky Mountains, the Greater Alpine Region and the Tibetan Plateau-Himalayas. The aim of this study is twofold: to investigate the impact (if any) of increasing model resolution on the representation of EDW and to highlight possible differences in this phenomenon and its driving mechanisms in different mountain regions of the northern hemisphere. Preliminary results indicate that autumn (September to November) is the only season in which EDW is simulated by the model in both the maximum and the minimum temperature, in all three regions and across all model resolutions. Regional differences emerge in the other seasons: for example, the Tibetan Plateau-Himalayas is the only area in which EDW is detected in winter. As for the analysis of EDW drivers, we identify albedo and downward longwave radiation as being the most important variables for EDW, in all three areas considered and in all seasons. Further these results are robust to changes in model resolution, even though a clearer signal is associated with finer resolutions. We finally use the highest resolution EC-Earth simulations available (˜16 km) to identify what areas, within the three considered mountain ranges, are expected to undergo a significant reduction of snow or ice cover in the period 2039-2068 with respect to the period 1979-2008, using the EC-Earth projections under the RCP 8.5 concentration scenario.

An operational wave forecasting system for the east coast of India

NASA Astrophysics Data System (ADS)

Sandhya, K. G.; Murty, P. L. N.; Deshmukh, Aditya N.; Balakrishnan Nair, T. M.; Shenoi, S. S. C.

2018-03-01

Demand for operational ocean state forecasting is increasing, owing to the ever-increasing marine activities in the context of blue economy. In the present study, an operational wave forecasting system for the east coast of India is proposed using unstructured Simulating WAves Nearshore model (UNSWAN). This modelling system uses very high resolution mesh near the Indian east coast and coarse resolution offshore, and thus avoids the necessity of nesting with a global wave model. The model is forced with European Centre for Medium-Range Weather Forecasts (ECMWF) winds and simulates wave parameters and wave spectra for the next 3 days. The spatial pictures of satellite data overlaid on simulated wave height show that the model is capable of simulating the significant wave heights and their gradients realistically. Spectral validation has been done using the available data to prove the reliability of the model. To further evaluate the model performance, the wave forecast for the entire year 2014 is evaluated against buoy measurements over the region at 4 waverider buoy locations. Seasonal analysis of significant wave height (Hs) at the four locations showed that the correlation between the modelled and observed was the highest (in the range 0.78-0.96) during the post-monsoon season. The variability of Hs was also the highest during this season at all locations. The error statistics showed clear seasonal and geographical location dependence. The root mean square error at Visakhapatnam was the same (0.25) for all seasons, but it was the smallest for pre-monsoon season (0.12 m and 0.17 m) for Puducherry and Gopalpur. The wind sea component showed higher variability compared to the corresponding swell component in all locations and for all seasons. The variability was picked by the model to a reasonable level in most of the cases. The results of statistical analysis show that the modelling system is suitable for use in the operational scenario.

Wavefront propagation simulations for a UV/soft x-ray beamline: Electron Spectro-Microscopy beamline at NSLS-II

NASA Astrophysics Data System (ADS)

Canestrari, N.; Bisogni, V.; Walter, A.; Zhu, Y.; Dvorak, J.; Vescovo, E.; Chubar, O.

2014-09-01

A "source-to-sample" wavefront propagation analysis of the Electron Spectro-Microscopy (ESM) UV / soft X-ray beamline, which is under construction at the National Synchrotron Light Source II (NSLS-II) in the Brookhaven National Laboratory, has been conducted. All elements of the beamline - insertion device, mirrors, variable-line-spacing gratings and slits - are included in the simulations. Radiation intensity distributions at the sample position are displayed for representative photon energies in the UV range (20 - 100 eV) where diffraction effects are strong. The finite acceptance of the refocusing mirrors is the dominating factor limiting the spatial resolution at the sample (by ~3 μm at 20 eV). Absolute estimates of the radiation flux and energy resolution at the sample are also obtained from the electromagnetic calculations. The analysis of the propagated UV range undulator radiation at different deflection parameter values demonstrates that within the beamline angular acceptance a slightly "red-shifted" radiation provides higher flux at the sample and better energy resolution compared to the on-axis resonant radiation of the fundamental harmonic.

Discovering variable fractional orders of advection-dispersion equations from field data using multi-fidelity Bayesian optimization

NASA Astrophysics Data System (ADS)

Pang, Guofei; Perdikaris, Paris; Cai, Wei; Karniadakis, George Em

2017-11-01

The fractional advection-dispersion equation (FADE) can describe accurately the solute transport in groundwater but its fractional order has to be determined a priori. Here, we employ multi-fidelity Bayesian optimization to obtain the fractional order under various conditions, and we obtain more accurate results compared to previously published data. Moreover, the present method is very efficient as we use different levels of resolution to construct a stochastic surrogate model and quantify its uncertainty. We consider two different problem set ups. In the first set up, we obtain variable fractional orders of one-dimensional FADE, considering both synthetic and field data. In the second set up, we identify constant fractional orders of two-dimensional FADE using synthetic data. We employ multi-resolution simulations using two-level and three-level Gaussian process regression models to construct the surrogates.

Eddy-driven low-frequency variability: physics and observability through altimetry

NASA Astrophysics Data System (ADS)

Penduff, Thierry; Sérazin, Guillaume; Arbic, Brian; Mueller, Malte; Richman, James G.; Shriver, Jay F.; Morten, Andrew J.; Scott, Robert B.

2015-04-01

Model studies have revealed the propensity of the eddying ocean circulation to generate strong low-frequency variability (LFV) intrinsically, i.e. without low-frequency atmospheric variability. In the present study, gridded satellite altimeter products, idealized quasi-geostrophic (QG) turbulent simulations, and realistic high-resolution global ocean simulations are used to study the spontaneous tendency of mesoscale (relatively high frequency and high wavenumber) kinetic energy to non-linearly cascade towards larger time and space scales. The QG model reveals that large-scale variability, arising from the well-known spatial inverse cascade, is associated with low frequencies. Low-frequency, low-wavenumber energy is maintained primarily by nonlinearities in the QG model, with forcing (by large-scale shear) and friction playing secondary roles. In realistic simulations, nonlinearities also generally drive kinetic energy to low frequencies and low wavenumbers. In some, but not all, regions of the gridded altimeter product, surface kinetic energy is also found to cascade toward low frequencies. Exercises conducted with the realistic model suggest that the spatial and temporal filtering inherent in the construction of gridded satellite altimeter maps may contribute to the discrepancies seen in some regions between the direction of frequency cascade in models versus gridded altimeter maps. Finally, the range of frequencies that are highly energized and engaged these cascades appears much greater than the range of highly energized and engaged wavenumbers. Global eddying simulations, performed in the context of the CHAOCEAN project in collaboration with the CAREER project, provide estimates of the range of timescales that these oceanic nonlinearities are likely to feed without external variability.

Statistical Downscaling of WRF-Chem Model: An Air Quality Analysis over Bogota, Colombia

NASA Astrophysics Data System (ADS)

Kumar, Anikender; Rojas, Nestor

2015-04-01

Statistical downscaling is a technique that is used to extract high-resolution information from regional scale variables produced by coarse resolution models such as Chemical Transport Models (CTMs). The fully coupled WRF-Chem (Weather Research and Forecasting with Chemistry) model is used to simulate air quality over Bogota. Bogota is a tropical Andean megacity located over a high-altitude plateau in the middle of very complex terrain. The WRF-Chem model was adopted for simulating the hourly ozone concentrations. The computational domains were chosen of 120x120x32, 121x121x32 and 121x121x32 grid points with horizontal resolutions of 27, 9 and 3 km respectively. The model was initialized with real boundary conditions using NCAR-NCEP's Final Analysis (FNL) and a 1ox1o (~111 km x 111 km) resolution. Boundary conditions were updated every 6 hours using reanalysis data. The emission rates were obtained from global inventories, namely the REanalysis of the TROpospheric (RETRO) chemical composition and the Emission Database for Global Atmospheric Research (EDGAR). Multiple linear regression and artificial neural network techniques are used to downscale the model output at each monitoring stations. The results confirm that the statistically downscaled outputs reduce simulated errors by up to 25%. This study provides a general overview of statistical downscaling of chemical transport models and can constitute a reference for future air quality modeling exercises over Bogota and other Colombian cities.

A Large-Scale, High-Resolution Hydrological Model Parameter Data Set for Climate Change Impact Assessment for the Conterminous US

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

Oubeidillah, Abdoul A; Kao, Shih-Chieh; Ashfaq, Moetasim

2014-01-01

To extend geographical coverage, refine spatial resolution, and improve modeling efficiency, a computation- and data-intensive effort was conducted to organize a comprehensive hydrologic dataset with post-calibrated model parameters for hydro-climate impact assessment. Several key inputs for hydrologic simulation including meteorologic forcings, soil, land class, vegetation, and elevation were collected from multiple best-available data sources and organized for 2107 hydrologic subbasins (8-digit hydrologic units, HUC8s) in the conterminous United States at refined 1/24 (~4 km) spatial resolution. Using high-performance computing for intensive model calibration, a high-resolution parameter dataset was prepared for the macro-scale Variable Infiltration Capacity (VIC) hydrologic model. The VICmore » simulation was driven by DAYMET daily meteorological forcing and was calibrated against USGS WaterWatch monthly runoff observations for each HUC8. The results showed that this new parameter dataset may help reasonably simulate runoff at most US HUC8 subbasins. Based on this exhaustive calibration effort, it is now possible to accurately estimate the resources required for further model improvement across the entire conterminous United States. We anticipate that through this hydrologic parameter dataset, the repeated effort of fundamental data processing can be lessened, so that research efforts can emphasize the more challenging task of assessing climate change impacts. The pre-organized model parameter dataset will be provided to interested parties to support further hydro-climate impact assessment.« less

High-resolution stochastic generation of extreme rainfall intensity for urban drainage modelling applications

NASA Astrophysics Data System (ADS)

Peleg, Nadav; Blumensaat, Frank; Molnar, Peter; Fatichi, Simone; Burlando, Paolo

2016-04-01

Urban drainage response is highly dependent on the spatial and temporal structure of rainfall. Therefore, measuring and simulating rainfall at a high spatial and temporal resolution is a fundamental step to fully assess urban drainage system reliability and related uncertainties. This is even more relevant when considering extreme rainfall events. However, the current space-time rainfall models have limitations in capturing extreme rainfall intensity statistics for short durations. Here, we use the STREAP (Space-Time Realizations of Areal Precipitation) model, which is a novel stochastic rainfall generator for simulating high-resolution rainfall fields that preserve the spatio-temporal structure of rainfall and its statistical characteristics. The model enables a generation of rain fields at 102 m and minute scales in a fast and computer-efficient way matching the requirements for hydrological analysis of urban drainage systems. The STREAP model was applied successfully in the past to generate high-resolution extreme rainfall intensities over a small domain. A sub-catchment in the city of Luzern (Switzerland) was chosen as a case study to: (i) evaluate the ability of STREAP to disaggregate extreme rainfall intensities for urban drainage applications; (ii) assessing the role of stochastic climate variability of rainfall in flow response and (iii) evaluate the degree of non-linearity between extreme rainfall intensity and system response (i.e. flow) for a small urban catchment. The channel flow at the catchment outlet is simulated by means of a calibrated hydrodynamic sewer model.

Southern Hemisphere climate variability forced by Northern Hemisphere ice-sheet topography

NASA Astrophysics Data System (ADS)

Jones, T. R.; Roberts, W. H. G.; Steig, E. J.; Cuffey, K. M.; Markle, B. R.; White, J. W. C.

2018-02-01

The presence of large Northern Hemisphere ice sheets and reduced greenhouse gas concentrations during the Last Glacial Maximum fundamentally altered global ocean-atmosphere climate dynamics. Model simulations and palaeoclimate records suggest that glacial boundary conditions affected the El Niño-Southern Oscillation, a dominant source of short-term global climate variability. Yet little is known about changes in short-term climate variability at mid- to high latitudes. Here we use a high-resolution water isotope record from West Antarctica to demonstrate that interannual to decadal climate variability at high southern latitudes was almost twice as large at the Last Glacial Maximum as during the ensuing Holocene epoch (the past 11,700 years). Climate model simulations indicate that this increased variability reflects an increase in the teleconnection strength between the tropical Pacific and West Antarctica, owing to a shift in the mean location of tropical convection. This shift, in turn, can be attributed to the influence of topography and albedo of the North American ice sheets on atmospheric circulation. As the planet deglaciated, the largest and most abrupt decline in teleconnection strength occurred between approximately 16,000 years and 15,000 years ago, followed by a slower decline into the early Holocene.

From AWE-GEN to AWE-GEN-2d: a high spatial and temporal resolution weather generator

NASA Astrophysics Data System (ADS)

Peleg, Nadav; Fatichi, Simone; Paschalis, Athanasios; Molnar, Peter; Burlando, Paolo

2016-04-01

A new weather generator, AWE-GEN-2d (Advanced WEather GENerator for 2-Dimension grid) is developed following the philosophy of combining physical and stochastic approaches to simulate meteorological variables at high spatial and temporal resolution (e.g. 2 km x 2 km and 5 min for precipitation and cloud cover and 100 m x 100 m and 1 h for other variables variable (temperature, solar radiation, vapor pressure, atmospheric pressure and near-surface wind). The model is suitable to investigate the impacts of climate variability, temporal and spatial resolutions of forcing on hydrological, ecological, agricultural and geomorphological impacts studies. Using appropriate parameterization the model can be used in the context of climate change. Here we present the model technical structure of AWE-GEN-2d, which is a substantial evolution of four preceding models (i) the hourly-point scale Advanced WEather GENerator (AWE-GEN) presented by Fatichi et al. (2011, Adv. Water Resour.) (ii) the Space-Time Realizations of Areal Precipitation (STREAP) model introduced by Paschalis et al. (2013, Water Resour. Res.), (iii) the High-Resolution Synoptically conditioned Weather Generator developed by Peleg and Morin (2014, Water Resour. Res.), and (iv) the Wind-field Interpolation by Non Divergent Schemes presented by Burlando et al. (2007, Boundary-Layer Meteorol.). The AWE-GEN-2d is relatively parsimonious in terms of computational demand and allows generating many stochastic realizations of current and projected climates in an efficient way. An example of model application and testing is presented with reference to a case study in the Wallis region, a complex orography terrain in the Swiss Alps.

Application of a fast Newton-Krylov solver for equilibrium simulations of phosphorus and oxygen

NASA Astrophysics Data System (ADS)

Fu, Weiwei; Primeau, François

2017-11-01

Model drift due to inadequate spinup is a serious problem that complicates the interpretation of climate change simulations. Even after a 300 year spinup we show that solutions are not only still drifting but often drifting away from their eventual equilibrium over large parts of the ocean. Here we present a Newton-Krylov solver for computing cyclostationary equilibrium solutions of a biogeochemical model for the cycling of phosphorus and oxygen. In addition to using previously developed preconditioning strategies - time-averaging and coarse-graining the Jacobian matrix - we also introduce a new strategy: the adiabatic elimination of a fast variable (particulate organic phosphorus) by slaving it to a slow variable (dissolved inorganic phosphorus). We use transport matrices derived from the Community Earth System Model (CESM) with a nominal horizontal resolution of 1° × 1° and 60 vertical levels to implement and test the solver. We find that the new solver obtains seasonally-varying equilibrium solutions with no visible drift using no more than 80 simulation years.

High Resolution Mapping of Wetland Ecosystems SPOT-5 Take 5 for Evaluation of Sentinel-2

NASA Astrophysics Data System (ADS)

Ade, Christiana; Hestir, Erin L.; Khanna, Shruti; Ustin, Susan L.

2016-08-01

Around the world wetlands are critical to human societies and ecosystems, providing services such as habitat, water, food and fiber, flood and nutrient control, and cultural, recreational and religious value. However, the dynamic nature of tidal wetlands makes measuring ecosystem responses to climate change, seasonal inundation regimes, and anthropogenic disturbance from current and previous Earth observing sensors challenging due to limited spatial and temporal resolutions. Sentinel- 2 will directly address this challenge by providing high spatial resolution data with frequent revisit time. This pilot study aims to develop methodology for future Sentinel-2 products and highlight the variability of tidal wetland ecosystems, thereby demonstrating the necessity of improved spatial particularly temporal resolution. Here the simulated Sentinel-2 dataset from the SPOT-5 Take 5 experiment reveals the capacity of the new sensor to simultaneously assess tidal wetland ecosystem phenology and water quality in inland waters.

Seasonal variability of atmospheric tides in the mesosphere and lower thermosphere: meteor radar data and simulations

NASA Astrophysics Data System (ADS)

Pokhotelov, Dimitry; Becker, Erich; Stober, Gunter; Chau, Jorge L.

2018-06-01

Thermal tides play an important role in the global atmospheric dynamics and provide a key mechanism for the forcing of thermosphere-ionosphere dynamics from below. A method for extracting tidal contributions, based on the adaptive filtering, is applied to analyse multi-year observations of mesospheric winds from ground-based meteor radars located in northern Germany and Norway. The observed seasonal variability of tides is compared to simulations with the Kühlungsborn Mechanistic Circulation Model (KMCM). It is demonstrated that the model provides reasonable representation of the tidal amplitudes, though substantial differences from observations are also noticed. The limitations of applying a conventionally coarse-resolution model in combination with parametrisation of gravity waves are discussed. The work is aimed towards the development of an ionospheric model driven by the dynamics of the KMCM.

Comparing SMAP to Macro-scale and Hyper-resolution Land Surface Models over Continental U. S.

NASA Astrophysics Data System (ADS)

Pan, Ming; Cai, Xitian; Chaney, Nathaniel; Wood, Eric

2016-04-01

SMAP sensors collect moisture information in top soil at the spatial resolution of ~40 km (radiometer) and ~1 to 3 km (radar, before its failure in July 2015). Such information is extremely valuable for understanding various terrestrial hydrologic processes and their implications on human life. At the same time, soil moisture is a joint consequence of numerous physical processes (precipitation, temperature, radiation, topography, crop/vegetation dynamics, soil properties, etc.) that happen at a wide range of scales from tens of kilometers down to tens of meters. Therefore, a full and thorough analysis/exploration of SMAP data products calls for investigations at multiple spatial scales - from regional, to catchment, and to field scales. Here we first compare the SMAP retrievals to the Variable Infiltration Capacity (VIC) macro-scale land surface model simulations over the continental U. S. region at 3 km resolution. The forcing inputs to the model are merged/downscaled from a suite of best available data products including the NLDAS-2 forcing, Stage IV and Stage II precipitation, GOES Surface and Insolation Products, and fine elevation data. The near real time VIC simulation is intended to provide a source of large scale comparisons at the active sensor resolution. Beyond the VIC model scale, we perform comparisons at 30 m resolution against the recently developed HydroBloks hyper-resolution land surface model over several densely gauged USDA experimental watersheds. Comparisons are also made against in-situ point-scale observations from various SMAP Cal/Val and field campaign sites.

Background concentrations for high resolution satellite observing systems of methane

NASA Astrophysics Data System (ADS)

Benmergui, J. S.; Propp, A. M.; Turner, A. J.; Wofsy, S. C.

2017-12-01

Emerging satellite technologies promise to measure total column dry-air mole fractions of methane (XCH4) at resolutions on the order of a kilometer. XCH4 is linearly related to regional methane emissions through enhancements in the mixed layer, giving these satellites the ability to constrain emissions at unprecedented resolution. However, XCH4 is also sensitive to variability in transport of upwind concentrations (the "background concentration"). Variations in the background concentration are caused by synoptic scale transport in both the free troposphere and the stratosphere, as well as the rate of methane oxidation. Misspecification of the background concentration is aliased onto retrieved emissions as bias. This work explores several methods of specifying the background concentration for high resolution satellite observations of XCH4. We conduct observing system simulation experiments (OSSEs) that simulate the retrieval of emissions in the Barnett Shale using observations from a 1.33 km resolution XCH4 imaging satellite. We test background concentrations defined (1) from an external continental-scale model, (2) using pixels along the edge of the image as a boundary value, (3) using differences between adjacent pixels, and (4) using differences between the same pixel separated by one hour in time. We measure success using the accuracy of the retrieval, the potential for bias induced by misspecification of the background, and the computational expedience of the method. Pathological scenarios are given to each method.

High-resolution numerical approximation of traffic flow problems with variable lanes and free-flow velocities.

PubMed

Zhang, Peng; Liu, Ru-Xun; Wong, S C

2005-05-01

This paper develops macroscopic traffic flow models for a highway section with variable lanes and free-flow velocities, that involve spatially varying flux functions. To address this complex physical property, we develop a Riemann solver that derives the exact flux values at the interface of the Riemann problem. Based on this solver, we formulate Godunov-type numerical schemes to solve the traffic flow models. Numerical examples that simulate the traffic flow around a bottleneck that arises from a drop in traffic capacity on the highway section are given to illustrate the efficiency of these schemes.

Modeling the direct sun component in buildings using matrix algebraic approaches: Methods and validation

DOE PAGES

Lee, Eleanor S.; Geisler-Moroder, David; Ward, Gregory

2017-12-23

Simulation tools that enable annual energy performance analysis of optically-complex fenestration systems have been widely adopted by the building industry for use in building design, code development, and the development of rating and certification programs for commercially-available shading and daylighting products. The tools rely on a three-phase matrix operation to compute solar heat gains, using as input low-resolution bidirectional scattering distribution function (BSDF) data (10–15° angular resolution; BSDF data define the angle-dependent behavior of light-scattering materials and systems). Measurement standards and product libraries for BSDF data are undergoing development to support solar heat gain calculations. Simulation of other metrics suchmore » as discomfort glare, annual solar exposure, and potentially thermal discomfort, however, require algorithms and BSDF input data that more accurately model the spatial distribution of transmitted and reflected irradiance or illuminance from the sun (0.5° resolution). This study describes such algorithms and input data, then validates the tools (i.e., an interpolation tool for measured BSDF data and the five-phase method) through comparisons with ray-tracing simulations and field monitored data from a full-scale testbed. Simulations of daylight-redirecting films, a micro-louvered screen, and venetian blinds using variable resolution, tensor tree BSDF input data derived from interpolated scanning goniophotometer measurements were shown to agree with field monitored data to within 20% for greater than 75% of the measurement period for illuminance-based performance parameters. The three-phase method delivered significantly less accurate results. We discuss the ramifications of these findings on industry and provide recommendations to increase end user awareness of the current limitations of existing software tools and BSDF product libraries.« less

Modeling the direct sun component in buildings using matrix algebraic approaches: Methods and validation

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

Lee, Eleanor S.; Geisler-Moroder, David; Ward, Gregory

Simulation tools that enable annual energy performance analysis of optically-complex fenestration systems have been widely adopted by the building industry for use in building design, code development, and the development of rating and certification programs for commercially-available shading and daylighting products. The tools rely on a three-phase matrix operation to compute solar heat gains, using as input low-resolution bidirectional scattering distribution function (BSDF) data (10–15° angular resolution; BSDF data define the angle-dependent behavior of light-scattering materials and systems). Measurement standards and product libraries for BSDF data are undergoing development to support solar heat gain calculations. Simulation of other metrics suchmore » as discomfort glare, annual solar exposure, and potentially thermal discomfort, however, require algorithms and BSDF input data that more accurately model the spatial distribution of transmitted and reflected irradiance or illuminance from the sun (0.5° resolution). This study describes such algorithms and input data, then validates the tools (i.e., an interpolation tool for measured BSDF data and the five-phase method) through comparisons with ray-tracing simulations and field monitored data from a full-scale testbed. Simulations of daylight-redirecting films, a micro-louvered screen, and venetian blinds using variable resolution, tensor tree BSDF input data derived from interpolated scanning goniophotometer measurements were shown to agree with field monitored data to within 20% for greater than 75% of the measurement period for illuminance-based performance parameters. The three-phase method delivered significantly less accurate results. We discuss the ramifications of these findings on industry and provide recommendations to increase end user awareness of the current limitations of existing software tools and BSDF product libraries.« less

Wavelet-based resolution recovery using an anatomical prior provides quantitative recovery for human population phantom PET [11C]raclopride data

NASA Astrophysics Data System (ADS)

Shidahara, M.; Tsoumpas, C.; McGinnity, C. J.; Kato, T.; Tamura, H.; Hammers, A.; Watabe, H.; Turkheimer, F. E.

2012-05-01

The objective of this study was to evaluate a resolution recovery (RR) method using a variety of simulated human brain [11C]raclopride positron emission tomography (PET) images. Simulated datasets of 15 numerical human phantoms were processed by a wavelet-based RR method using an anatomical prior. The anatomical prior was in the form of a hybrid segmented atlas, which combined an atlas for anatomical labelling and a PET image for functional labelling of each anatomical structure. We applied RR to both 60 min static and dynamic PET images. Recovery was quantified in 84 regions, comparing the typical ‘true’ value for the simulation, as obtained in normal subjects, simulated and RR PET images. The radioactivity concentration in the white matter, striatum and other cortical regions was successfully recovered for the 60 min static image of all 15 human phantoms; the dependence of the solution on accurate anatomical information was demonstrated by the difficulty of the technique to retrieve the subthalamic nuclei due to mismatch between the two atlases used for data simulation and recovery. Structural and functional synergy for resolution recovery (SFS-RR) improved quantification in the caudate and putamen, the main regions of interest, from -30.1% and -26.2% to -17.6% and -15.1%, respectively, for the 60 min static image and from -51.4% and -38.3% to -27.6% and -20.3% for the binding potential (BPND) image, respectively. The proposed methodology proved effective in the RR of small structures from brain [11C]raclopride PET images. The improvement is consistent across the anatomical variability of a simulated population as long as accurate anatomical segmentations are provided.

Simulating the dispersion of NOx and CO2 in the city of Zurich at building resolving scale

NASA Astrophysics Data System (ADS)

Brunner, Dominik; Berchet, Antoine; Emmenegger, Lukas; Henne, Stephan; Müller, Michael

2017-04-01

Cities are emission hotspots for both greenhouse gases and air pollutants. They contribute about 70% of global greenhouse gas emissions and are home to a growing number of people potentially suffering from poor air quality in the urban environment. High-resolution atmospheric transport modelling of greenhouse gases and air pollutants at the city scale has, therefore, several important applications such as air pollutant exposure assessment, air quality forecasting, or urban planning and management. When combined with observations, it also has the potential to quantify emissions and monitor their long-term trends, which is the main motivation for the deployment of urban greenhouse gas monitoring networks. We have developed a comprehensive atmospheric modeling model system for the city of Zurich, Switzerland ( 600,000 inhabitants including suburbs), which is composed of the mesoscale model GRAMM simulating the flow in a larger domain around Zurich at 100 m resolution, and the nested high-resolution model GRAL simulating the flow and air pollutant dispersion in the city at building resolving (5-10 m) scale. Based on an extremely detailed emission inventory provided by the municipality of Zurich, we have simulated two years of hourly NOx and CO2 concentration fields across the entire city. Here, we present a detailed evaluation of the simulations against a comprehensive network of continuous monitoring sites and passive samplers for NOx and analyze the sensitivity of the results to the temporal variability of the emissions. Furthermore, we present first simulations of CO2 and investigate the challenges associated with CO2 sources not covered by the inventory such as human respiration and exchange fluxes with urban vegetation.

The Helioseismic and Magnetic Imager (HMI) Vector Magnetic Field Pipeline: Magnetohydrodynamics Simulation Module for the Global Solar Corona.

PubMed

Hayashi, K; Hoeksema, J T; Liu, Y; Bobra, M G; Sun, X D; Norton, A A

Time-dependent three-dimensional magnetohydrodynamics (MHD) simulation modules are implemented at the Joint Science Operation Center (JSOC) of the Solar Dynamics Observatory (SDO). The modules regularly produce three-dimensional data of the time-relaxed minimum-energy state of the solar corona using global solar-surface magnetic-field maps created from Helioseismic and Magnetic Imager (HMI) full-disk magnetogram data. With the assumption of a polytropic gas with specific-heat ratio of 1.05, three types of simulation products are currently generated: i) simulation data with medium spatial resolution using the definitive calibrated synoptic map of the magnetic field with a cadence of one Carrington rotation, ii) data with low spatial resolution using the definitive version of the synchronic frame format of the magnetic field, with a cadence of one day, and iii) low-resolution data using near-real-time (NRT) synchronic format of the magnetic field on a daily basis. The MHD data available in the JSOC database are three-dimensional, covering heliocentric distances from 1.025 to 4.975 solar radii, and contain all eight MHD variables: the plasma density, temperature, and three components of motion velocity, and three components of the magnetic field. This article describes details of the MHD simulations as well as the production of the input magnetic-field maps, and details of the products available at the JSOC database interface. To assess the merits and limits of the model, we show the simulated data in early 2011 and compare with the actual coronal features observed by the Atmospheric Imaging Assembly (AIA) and the near-Earth in-situ data.

Variability of 4D flow parameters when subjected to changes in MRI acquisition parameters using a realistic thoracic aortic phantom.

PubMed

Montalba, Cristian; Urbina, Jesus; Sotelo, Julio; Andia, Marcelo E; Tejos, Cristian; Irarrazaval, Pablo; Hurtado, Daniel E; Valverde, Israel; Uribe, Sergio

2018-04-01

To assess the variability of peak flow, mean velocity, stroke volume, and wall shear stress measurements derived from 3D cine phase contrast (4D flow) sequences under different conditions of spatial and temporal resolutions. We performed controlled experiments using a thoracic aortic phantom. The phantom was connected to a pulsatile flow pump, which simulated nine physiological conditions. For each condition, 4D flow data were acquired with different spatial and temporal resolutions. The 2D cine phase contrast and 4D flow data with the highest available spatio-temporal resolution were considered as a reference for comparison purposes. When comparing 4D flow acquisitions (spatial and temporal resolution of 2.0 × 2.0 × 2.0 mm 3 and 40 ms, respectively) with 2D phase-contrast flow acquisitions, the underestimation of peak flow, mean velocity, and stroke volume were 10.5, 10 and 5%, respectively. However, the calculated wall shear stress showed an underestimation larger than 70% for the former acquisition, with respect to 4D flow, with spatial and temporal resolution of 1.0 × 1.0 × 1.0 mm 3 and 20 ms, respectively. Peak flow, mean velocity, and stroke volume from 4D flow data are more sensitive to changes of temporal than spatial resolution, as opposed to wall shear stress, which is more sensitive to changes in spatial resolution. Magn Reson Med 79:1882-1892, 2018. © 2017 International Society for Magnetic Resonance in Medicine. © 2017 International Society for Magnetic Resonance in Medicine.

RELATIVISTIC MHD SIMULATIONS OF COLLISION-INDUCED MAGNETIC DISSIPATION IN POYNTING-FLUX-DOMINATED JETS/OUTFLOWS

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

Deng, Wei; Zhang, Bing; Li, Hui

We perform 3D relativistic ideal magnetohydrodynamics (MHD) simulations to study the collisions between high-σ (Poynting-flux-dominated (PFD)) blobs which contain both poloidal and toroidal magnetic field components. This is meant to mimic the interactions inside a highly variable PFD jet. We discover a significant electromagnetic field (EMF) energy dissipation with an Alfvénic rate with the efficiency around 35%. Detailed analyses show that this dissipation is mostly facilitated by the collision-induced magnetic reconnection. Additional resolution and parameter studies show a robust result that the relative EMF energy dissipation efficiency is nearly independent of the numerical resolution or most physical parameters in themore » relevant parameter range. The reconnection outflows in our simulation can potentially form the multi-orientation relativistic mini jets as needed for several analytical models. We also find a linear relationship between the σ values before and after the major EMF energy dissipation process. Our results give support to the proposed astrophysical models that invoke significant magnetic energy dissipation in PFD jets, such as the internal collision-induced magnetic reconnection and turbulence model for gamma-ray bursts, and reconnection triggered mini jets model for active galactic nuclei. The simulation movies are shown in http://www.physics.unlv.edu/∼deng/simulation1.html.« less

Adaptive mesh refinement and adjoint methods in geophysics simulations

NASA Astrophysics Data System (ADS)

Burstedde, Carsten

2013-04-01

It is an ongoing challenge to increase the resolution that can be achieved by numerical geophysics simulations. This applies to considering sub-kilometer mesh spacings in global-scale mantle convection simulations as well as to using frequencies up to 1 Hz in seismic wave propagation simulations. One central issue is the numerical cost, since for three-dimensional space discretizations, possibly combined with time stepping schemes, a doubling of resolution can lead to an increase in storage requirements and run time by factors between 8 and 16. A related challenge lies in the fact that an increase in resolution also increases the dimensionality of the model space that is needed to fully parametrize the physical properties of the simulated object (a.k.a. earth). Systems that exhibit a multiscale structure in space are candidates for employing adaptive mesh refinement, which varies the resolution locally. An example that we found well suited is the mantle, where plate boundaries and fault zones require a resolution on the km scale, while deeper area can be treated with 50 or 100 km mesh spacings. This approach effectively reduces the number of computational variables by several orders of magnitude. While in this case it is possible to derive the local adaptation pattern from known physical parameters, it is often unclear what are the most suitable criteria for adaptation. We will present the goal-oriented error estimation procedure, where such criteria are derived from an objective functional that represents the observables to be computed most accurately. Even though this approach is well studied, it is rarely used in the geophysics community. A related strategy to make finer resolution manageable is to design methods that automate the inference of model parameters. Tweaking more than a handful of numbers and judging the quality of the simulation by adhoc comparisons to known facts and observations is a tedious task and fundamentally limited by the turnaround times required by human intervention and analysis. Specifying an objective functional that quantifies the misfit between the simulation outcome and known constraints and then minimizing it through numerical optimization can serve as an automated technique for parameter identification. As suggested by the similarity in formulation, the numerical algorithm is closely related to the one used for goal-oriented error estimation. One common point is that the so-called adjoint equation needs to be solved numerically. We will outline the derivation and implementation of these methods and discuss some of their pros and cons, supported by numerical results.

A semi-urban case study of small scale variability of rainfall and run-off, with C- and X-band radars and the fully distributed hydrological model Multi-Hydro

NASA Astrophysics Data System (ADS)

Alves de Souza, Bianca; da Silva Rocha Paz, Igor; Gires, Auguste; Tchiguirinskaia, Ioulia; Schertzer, Daniel

2016-04-01

The complexity of urban hydrology results both from that of urban systems and the extreme rainfall variability. The latter can display strongly localised rain cells that can be extremely damaging when hitting vulnerable parts of urban systems. This paper investigates this complexity on a semi-urban sub-catchment - located in Massy (South of Paris, France) - of the Bievre river, which is known for its frequent flashfloods. Advanced geo-processing techniques were used to find the ideal pixel size for this 6.326km2 basin. C-band and X-band radar data are multifractally downscaled at various resolutions and input to the fully distributed hydrological model Multi-Hydro. The latter has been developed at Ecole des Ponts ParisTech. It integrates validated modules dealing with surface flow, saturated and unsaturated surface flow, and sewer flow. The C-band radar is located in Trappes, approx. 21km East of the catchment, is operated by Méteo-France and has a resolution of 1km x 1km x 5min. The X-band radar operated by Ecole des Ponts Paris Tech on its campus has a resolution of 125m x 125m x 3.4min. The performed multifractal downscaling enables both the generation of large ensemble realizations and easy change of resolution (e.g. down to 10 m in the present study). This in turn allows a detailed analysis of the impacts of small scale variability and the required resolution to obtain accurate simulations, therefore predictions. This will be shown on two rainy episodes over the chosen sub-catchment of the Bievre river.

Accounting for Rainfall Spatial Variability in Prediction of Flash Floods

NASA Astrophysics Data System (ADS)

Saharia, M.; Kirstetter, P. E.; Gourley, J. J.; Hong, Y.; Vergara, H. J.

2016-12-01

Flash floods are a particularly damaging natural hazard worldwide in terms of both fatalities and property damage. In the United States, the lack of a comprehensive database that catalogues information related to flash flood timing, location, causative rainfall, and basin geomorphology has hindered broad characterization studies. First a representative and long archive of more than 20,000 flooding events during 2002-2011 is used to analyze the spatial and temporal variability of flash floods. We also derive large number of spatially distributed geomorphological and climatological parameters such as basin area, mean annual precipitation, basin slope etc. to identify static basin characteristics that influence flood response. For the same period, the National Severe Storms Laboratory (NSSL) has produced a decadal archive of Multi-Radar/Multi-Sensor (MRMS) radar-only precipitation rates at 1-km spatial resolution with 5-min temporal resolution. This provides an unprecedented opportunity to analyze the impact of event-level precipitation variability on flooding using a big data approach. To analyze the impact of sub-basin scale rainfall spatial variability on flooding, certain indices such as the first and second scaled moment of rainfall, horizontal gap, vertical gap etc. are computed from the MRMS dataset. Finally, flooding characteristics such as rise time, lag time, and peak discharge are linked to derived geomorphologic, climatologic, and rainfall indices to identify basin characteristics that drive flash floods. Next the model is used to predict flash flooding characteristics all over the continental U.S., specifically over regions poorly covered by hydrological observations. So far studies involving rainfall variability indices have only been performed on a case study basis, and a large scale approach is expected to provide a deeper insight into how sub-basin scale precipitation variability affects flooding. Finally, these findings are validated using the National Weather Service storm reports and a historical flood fatalities database. This analysis framework will serve as a baseline for evaluating distributed hydrologic model simulations such as the Flooded Locations And Simulated Hydrographs Project (FLASH) (http://flash.ou.edu).

Accounting for rainfall spatial variability in the prediction of flash floods

NASA Astrophysics Data System (ADS)

Saharia, Manabendra; Kirstetter, Pierre-Emmanuel; Gourley, Jonathan J.; Hong, Yang; Vergara, Humberto; Flamig, Zachary L.

2017-04-01

Flash floods are a particularly damaging natural hazard worldwide in terms of both fatalities and property damage. In the United States, the lack of a comprehensive database that catalogues information related to flash flood timing, location, causative rainfall, and basin geomorphology has hindered broad characterization studies. First a representative and long archive of more than 15,000 flooding events during 2002-2011 is used to analyze the spatial and temporal variability of flash floods. We also derive large number of spatially distributed geomorphological and climatological parameters such as basin area, mean annual precipitation, basin slope etc. to identify static basin characteristics that influence flood response. For the same period, the National Severe Storms Laboratory (NSSL) has produced a decadal archive of Multi-Radar/Multi-Sensor (MRMS) radar-only precipitation rates at 1-km spatial resolution with 5-min temporal resolution. This provides an unprecedented opportunity to analyze the impact of event-level precipitation variability on flooding using a big data approach. To analyze the impact of sub-basin scale rainfall spatial variability on flooding, certain indices such as the first and second scaled moment of rainfall, horizontal gap, vertical gap etc. are computed from the MRMS dataset. Finally, flooding characteristics such as rise time, lag time, and peak discharge are linked to derived geomorphologic, climatologic, and rainfall indices to identify basin characteristics that drive flash floods. The database has been subjected to rigorous quality control by accounting for radar beam height and percentage snow in basins. So far studies involving rainfall variability indices have only been performed on a case study basis, and a large scale approach is expected to provide a deeper insight into how sub-basin scale precipitation variability affects flooding. Finally, these findings are validated using the National Weather Service storm reports and a historical flood fatalities database. This analysis framework will serve as a baseline for evaluating distributed hydrologic model simulations such as the Flooded Locations And Simulated Hydrographs Project (FLASH) (http://flash.ou.edu).

Future intensification of hydro-meteorological extremes: downscaling using the weather research and forecasting model

NASA Astrophysics Data System (ADS)

El-Samra, R.; Bou-Zeid, E.; Bangalath, H. K.; Stenchikov, G.; El-Fadel, M.

2017-12-01

A set of ten downscaling simulations at high spatial resolution (3 km horizontally) were performed using the Weather Research and Forecasting (WRF) model to generate future climate projections of annual and seasonal temperature and precipitation changes over the Eastern Mediterranean (with a focus on Lebanon). The model was driven with the High Resolution Atmospheric Model (HiRAM), running over the whole globe at a resolution of 25 km, under the conditions of two Representative Concentration Pathways (RCP) (4.5 and 8.5). Each downscaling simulation spanned one year. Two past years (2003 and 2008), also forced by HiRAM without data assimilation, were simulated to evaluate the model's ability to capture the cold and wet (2003) and hot and dry (2008) extremes. The downscaled data were in the range of recent observed climatic variability, and therefore corrected for the cold bias of HiRAM. Eight future years were then selected based on an anomaly score that relies on the mean annual temperature and accumulated precipitation to identify the worst year per decade from a water resources perspective. One hot and dry year per decade, from 2011 to 2050, and per scenario was simulated and compared to the historic 2008 reference. The results indicate that hot and dry future extreme years will be exacerbated and the study area might be exposed to a significant decrease in annual precipitation (rain and snow), reaching up to 30% relative to the current extreme conditions.

A cost-effective method for simulating city-wide air flow and pollutant dispersion at building resolving scale

NASA Astrophysics Data System (ADS)

Berchet, Antoine; Zink, Katrin; Muller, Clive; Oettl, Dietmar; Brunner, Juerg; Emmenegger, Lukas; Brunner, Dominik

2017-06-01

A cost-effective method is presented allowing to simulate the air flow and pollutant dispersion in a whole city over multiple years at the building-resolving scale with hourly time resolution. This combination of high resolution and long time span is critically needed for epidemiological studies and for air pollution control, but still poses a great challenge for current state-of-the-art modelling techniques. The presented method relies on the pre-computation of a discrete set of possible weather situations and corresponding steady-state flow and dispersion patterns. The most suitable situation for any given hour is then selected by matching the simulated wind patterns to meteorological observations in and around the city. The catalogue of pre-computed situations corresponds to different large-scale forcings in terms of wind speed, wind direction and stability. A meteorological model converts these forcings into realistic mesoscale flow patterns accounting for the effects of topography and land-use contrasts in a domain covering the city and its surroundings. These mesoscale patterns serve as boundary conditions for a microscale urban flow model which finally drives a Lagrangian air pollutant dispersion model. The method is demonstrated with the modelling system GRAMM/GRAL v14.8 for two Swiss cities in complex terrain, Zurich and Lausanne. The mesoscale flow patterns in the two regions of interest, dominated by land-lake breezes and driven by the partly steep topography, are well reproduced in the simulations matched to in situ observations. In particular, the combination of wind measurements at different locations around the city appeared to be a robust approach to deduce the stability class for the boundary layer within the city. This information is critical for predicting the temporal variability of pollution concentration within the city, regarding their relationship with the intensity of horizontal and vertical dispersion and of turbulence. In the vicinity of sources, the 5 m resolution chosen in our set-up is not always sufficient to reproduce the very steep concentration gradients, pointing at additional cost optimisations in the method required to make higher resolutions affordable. Nevertheless, the catalogue-based methodology allows reproducing concentration variability very consistently further away from emission sources, hence for most parts of the city.

Scaling between reanalyses and high-resolution land-surface modelling in mountainous areas - enabling better application and testing of reanalyses in heterogeneous environments

NASA Astrophysics Data System (ADS)

Gruber, S.; Fiddes, J.

2013-12-01

In mountainous topography, the difference in scale between atmospheric reanalyses (typically tens of kilometres) and relevant processes and phenomena near the Earth surface, such as permafrost or snow cover (meters to tens of meters) is most obvious. This contrast of scales is one of the major obstacles to using reanalysis data for the simulation of surface phenomena and to confronting reanalyses with independent observation. At the example of modelling permafrost in mountain areas (but simple to generalise to other phenomena and heterogeneous environments), we present and test methods against measurements for (A) scaling atmospheric data from the reanalysis to the ground level and (B) smart sampling of the heterogeneous landscape in order to set up a lumped model simulation that represents the high-resolution land surface. TopoSCALE (Part A, see http://dx.doi.org/10.5194/gmdd-6-3381-2013) is a scheme, which scales coarse-grid climate fields to fine-grid topography using pressure level data. In addition, it applies necessary topographic corrections e.g. those variables required for computation of radiation fields. This provides the necessary driving fields to the LSM. Tested against independent ground data, this scheme has been shown to improve the scaling and distribution of meteorological parameters in complex terrain, as compared to conventional methods, e.g. lapse rate based approaches. TopoSUB (Part B, see http://dx.doi.org/10.5194/gmd-5-1245-2012) is a surface pre-processor designed to sample a fine-grid domain (defined by a digital elevation model) along important topographical (or other) dimensions through a clustering scheme. This allows constructing a lumped model representing the main sources of fine-grid variability and applying a 1D LSM efficiently over large areas. Results can processed to derive (i) summary statistics at coarse-scale re-analysis grid resolution, (ii) high-resolution data fields spatialized to e.g., the fine-scale digital elevation model grid, or (iii) validation products for locations at which measurements exist, only. The ability of TopoSUB to approximate results simulated by a 2D distributed numerical LSM at a factor of ~10,000 less computations is demonstrated by comparison of 2D and lumped simulations. Successful application of the combined scheme in the European Alps is reported and based on its results, open issues for future research are outlined.

Novel Atmospheric and Sea State Modeling in Ocean Energy Applications

NASA Astrophysics Data System (ADS)

Kallos, George; Galanis, George; Kalogeri, Christina; Larsen, Xiaoli Guo

2013-04-01

The rapidly increasing use of renewable energy sources poses new challenges for the research and technological community today. The integration of the, usually, highly variable wind and wave energy amounts into the general grid, the optimization of energy transition and the forecast of extreme values that could lead to instabilities and failures of the system can be listed among them. In the present work, novel methodologies based on state of the art numerical wind/wave simulation systems and advanced statistical techniques addressing such type of problems are discussed. In particular, extremely high resolution modeling systems simulating the atmospheric and sea state conditions with spatial resolution of 100 meters or less and temporal discretization of a few seconds are utilized in order to simulate in the most detailed way the combined wind-wave energy potential at offshore sites. In addition, a statistical analysis based on a variety of mean and variation measures as well as univariate and bivariate probability distributions is used for the estimation of the variability of the power potential revealing the advantages of the use of combined forms of energy by offshore platforms able to produce wind and wave power simultaneously. The estimation and prediction of extreme wind/wave conditions - a critical issue both for site assessment and infrastructure maintenance - is also studied by means of the 50-year return period over areas with increased power potential. This work has been carried out within the framework of the FP7 project MARINA Platform (http://www.marina-platform.info/index.aspx).

An atmospheric turbulence and telescope simulator for the development of AOLI

NASA Astrophysics Data System (ADS)

Puga, Marta; López, Roberto; King, David; Oscoz, Alejandro

2014-08-01

AOLI, Adaptive Optics Lucky Imager, is the next generation of extremely high resolution instruments in the optical range, combining the two more promising techniques: Adaptive optics and lucky imaging. The possibility of reaching fainter objects at maximum resolution implies a better use of weak energy on each lucky image. AOLI aims to achieve this by using an adaptive optics system to reduce the dispersion that seeing causes on the spot and therefore increasing the number of optimal images to accumulate, maximizing the efficiency of the lucky imaging technique. The complexity of developments in hardware, control and software for in-site telescope tests claim for a system to simulate the telescope performance. This paper outlines the requirements and a concept/preliminary design for the William Herschel Telescope (WHT) and atmospheric turbulence simulator. The design consists of pupil resemble, a variable intensity point source, phase plates and a focal plane mask to assist in the alignment, diagnostics and calibration of AOLI wavefront sensor, AO loop and science detectors, as well as enabling stand-alone test operation of AOLI.

Monte Carlo-based assessment of the trade-off between spatial resolution, field-of-view and scattered radiation in the variable resolution X-ray CT scanner.

PubMed

Arabi, Hossein; Kamali Asl, Ali Reza; Ay, Mohammad Reza; Zaidi, Habib

2015-07-01

The purpose of this work is to evaluate the impact of optimization of magnification on performance parameters of the variable resolution X-ray (VRX) CT scanner. A realistic model based on an actual VRX CT scanner was implemented in the GATE Monte Carlo simulation platform. To evaluate the influence of system magnification, spatial resolution, field-of-view (FOV) and scatter-to-primary ratio of the scanner were estimated for both fixed and optimum object magnification at each detector rotation angle. Comparison and inference between these performance parameters were performed angle by angle to determine appropriate object position at each opening half angle. Optimization of magnification resulted in a trade-off between spatial resolution and FOV of the scanner at opening half angles of 90°-12°, where the spatial resolution increased up to 50% and the scatter-to-primary ratio decreased from 4.8% to 3.8% at a detector angle of about 90° for the same FOV and X-ray energy spectrum. The disadvantage of magnification optimization at these angles is the significant reduction of the FOV (up to 50%). Moreover, magnification optimization was definitely beneficial for opening half angles below 12° improving the spatial resolution from 7.5 cy/mm to 20 cy/mm. Meanwhile, the FOV increased by more than 50% at these angles. It can be concluded that optimization of magnification is essential for opening half angles below 12°. For opening half angles between 90° and 12°, the VRX CT scanner magnification should be set according to the desired spatial resolution and FOV. Copyright © 2015 Associazione Italiana di Fisica Medica. Published by Elsevier Ltd. All rights reserved.

Influence of reanalysis datasets on dynamically downscaling the recent past

NASA Astrophysics Data System (ADS)

Moalafhi, Ditiro B.; Evans, Jason P.; Sharma, Ashish

2017-08-01

Multiple reanalysis datasets currently exist that can provide boundary conditions for dynamic downscaling and simulating local hydro-climatic processes at finer spatial and temporal resolutions. Previous work has suggested that there are two reanalyses alternatives that provide the best lateral boundary conditions for downscaling over southern Africa. This study dynamically downscales these reanalyses (ERA-I and MERRA) over southern Africa to a high resolution (10 km) grid using the WRF model. Simulations cover the period 1981-2010. Multiple observation datasets were used for both surface temperature and precipitation to account for observational uncertainty when assessing results. Generally, temperature is simulated quite well, except over the Namibian coastal plain where the simulations show anomalous warm temperature related to the failure to propagate the influence of the cold Benguela current inland. Precipitation tends to be overestimated in high altitude areas, and most of southern Mozambique. This could be attributed to challenges in handling complex topography and capturing large-scale circulation patterns. While MERRA driven WRF exhibits slightly less bias in temperature especially for La Nina years, ERA-I driven simulations are on average superior in terms of RMSE. When considering multiple variables and metrics, ERA-I is found to produce the best simulation of the climate over the domain. The influence of the regional model appears to be large enough to overcome the small difference in relative errors present in the lateral boundary conditions derived from these two reanalyses.

Trans-Pacific transport and evolution of aerosols: evaluation of quasi-global WRF-Chem simulation with multiple observations

NASA Astrophysics Data System (ADS)

Hu, Zhiyuan; Zhao, Chun; Huang, Jianping; Leung, L. Ruby; Qian, Yun; Yu, Hongbin; Huang, Lei; Kalashnikova, Olga V.

2016-05-01

A fully coupled meteorology-chemistry model (WRF-Chem, the Weather Research and Forecasting model coupled with chemistry) has been configured to conduct quasi-global simulation for 5 years (2010-2014) and evaluated with multiple observation data sets for the first time. The evaluation focuses on the simulation over the trans-Pacific transport region using various reanalysis and observational data sets for meteorological fields and aerosol properties. The simulation generally captures the overall spatial and seasonal variability of satellite retrieved aerosol optical depth (AOD) and absorbing AOD (AAOD) over the Pacific that is determined by the outflow of pollutants and dust and the emissions of marine aerosols. The assessment of simulated extinction Ångström exponent (EAE) indicates that the model generally reproduces the variability of aerosol size distributions as seen by satellites. In addition, the vertical profile of aerosol extinction and its seasonality over the Pacific are also well simulated. The difference between the simulation and satellite retrievals can be mainly attributed to model biases in estimating marine aerosol emissions as well as the satellite sampling and retrieval uncertainties. Compared with the surface measurements over the western USA, the model reasonably simulates the observed magnitude and seasonality of dust, sulfate, and nitrate surface concentrations, but significantly underestimates the peak surface concentrations of carbonaceous aerosol likely due to model biases in the spatial and temporal variability of biomass burning emissions and secondary organic aerosol (SOA) production. A sensitivity simulation shows that the trans-Pacific transported dust, sulfate, and nitrate can make significant contribution to surface concentrations over the rural areas of the western USA, while the peaks of carbonaceous aerosol surface concentrations are dominated by the North American emissions. Both the retrievals and simulation show small interannual variability of aerosol characteristics for 2010-2014 averaged over three Pacific sub-regions. The evaluation in this study demonstrates that the WRF-Chem quasi-global simulation can be used for investigating trans-Pacific transport of aerosols and providing reasonable inflow chemical boundaries for the western USA, allowing one to further understand the impact of transported pollutants on the regional air quality and climate with high-resolution nested regional modeling.

Tropical Cyclones, Hurricanes, and Climate: NASA's Global Cloud-Scale Simulations and New Observations that Characterize the Lifecycle of Hurricanes

NASA Technical Reports Server (NTRS)

Putman, William M.

2010-01-01

One of the primary interests of Global Change research is the impact of climate changes and climate variability on extreme weather events, such as intense tropical storms and hurricanes. Atmospheric climate models run at resolutions of global weather models have been used to study the impact of climate variability, as seen in sea surface temperatures, on the frequency and intensity of tropical cyclones. NASA's Goddard Earth Observing System Model, version 5 (GEOS-5) in ensembles run at 50 km resolution has been able to reproduce the interannual variations of tropical cyclone frequency seen in nature. This, and other global models, have found it much more difficult to reproduce the interannual changes in intensity, a result that reflects the inability of the models to simulate the intensities of the most extreme storms. Better representation of the structures of cyclones requires much higher resolution models. Such improved representation is also fundamental to making best use of satellite observations. In collaboration with NOAA's Geophysical Fluid Dynamics Laboratory, GEOS-5 now has the capability of running at much higher resolution to better represent cloud-scale resolutions. Global simulations at cloud-permitting resolutions (10- to 3.5-km) allows for the development of realistic tropical cyclones from tropical storm 119 km/hr winds) to category 5 (>249km1hr winds) intensities. GEOS-5 has produced realistic rain-band and eye-wall structures in tropical cyclones that can be directly analyzed against satellite observations. For the first time a global climate model is capable of representing realistic intensity and track variability on a seasonal scale across basins. GEOS-5 is also used in assimilation mode to test the impact of NASA's observations on tropical cyclone forecasts. One such test, for tropical cyclone Nargis in the Indian Ocean in May 2008, showed that observations from Atmospheric Infrared Sounder (AIRS) and the Advanced Microwave Sounding Unit (AMSU-A) on Aqua substantially reduced forecast track errors. Tropical cyclones in the northern Indian Ocean pose serious challenges to operational weather forecasting systems, partly due to their shorter lifespan and more erratic track, compared to those in the Atlantic and the Pacific. SA is also bringing several state of the art instruments in recent field campaigns to peer under the clouds and study the inner workings of the tropical storms. With the Genesis and Rapid Intensification Processes (GRIP) experiment, a NASA Earth science field experiment in 2010 that includes the Global Hawk Unmanned Airborne System (UAS) configured with a suite of in situ and remote sensing instruments that are observing and characterizing the lifecycle of hurricanes, we expect significant improvement in our understanding of the track and intensification processes with the assimilation of the satellite and field campaign observations of meteorological parameters in the numerical prediction models.

Peptide crystal simulations reveal hidden dynamics

PubMed Central

Janowski, Pawel A.; Cerutti, David S.; Holton, James; Case, David A.

2013-01-01

Molecular dynamics simulations of biomolecular crystals at atomic resolution have the potential to recover information on dynamics and heterogeneity hidden in the X-ray diffraction data. We present here 9.6 microseconds of dynamics in a small helical peptide crystal with 36 independent copies of the unit cell. The average simulation structure agrees with experiment to within 0.28 Å backbone and 0.42 Å all-atom rmsd; a model refined against the average simulation density agrees with the experimental structure to within 0.20 Å backbone and 0.33 Å all-atom rmsd. The R-factor between the experimental structure factors and those derived from this unrestrained simulation is 23% to 1.0 Å resolution. The B-factors for most heavy atoms agree well with experiment (Pearson correlation of 0.90), but B-factors obtained by refinement against the average simulation density underestimate the coordinate fluctuations in the underlying simulation where the simulation samples alternate conformations. A dynamic flow of water molecules through channels within the crystal lattice is observed, yet the average water density is in remarkable agreement with experiment. A minor population of unit cells is characterized by reduced water content, 310 helical propensity and a gauche(−) side-chain rotamer for one of the valine residues. Careful examination of the experimental data suggests that transitions of the helices are a simulation artifact, although there is indeed evidence for alternate valine conformers and variable water content. This study highlights the potential for crystal simulations to detect dynamics and heterogeneity in experimental diffraction data, as well as to validate computational chemistry methods. PMID:23631449

Seasonal variations of soil erosion in UK under climate change: simulations with the use of high-resolution regional climatic models

NASA Astrophysics Data System (ADS)

Ciampalini, Rossano; Kendon, Elizabeth; Constantine, José Antonio; Schindewolf, Marcus; Hall, Ian

2017-04-01

Climate change is expected to have a significant impact on the hydrological cycle, twenty-first century climate change simulations for Great Britain forecast an increase of surface runoff and flooding frequency. Once quality and resolution of the simulated rainfall deeply influence the results, we adopted rainfall simulations issued of a high-resolution climate model recently carried out for extended periods (13 years for present-day and future periods 2100) at 1.5 km grid scale over the south of the United Kingdom (simulations, which for the future period use the Intergovernmental Panel on Climate Change RCP 8.5 scenario, Kendon et al., 2014). We simulated soil erosion with 3D soil erosion model Schmidt (1990) on two catchments of Great Britain: the Rother catchment (350 km2) in West Sussex, England, because it has reported some of the most erosive events observed during the last 50 years in the UK, and the Conwy catchment (628 Km2) in North Wales, which is extremely resilient to soil erosion because of the abundant natural vegetation. Estimation of changes in soil moisture, saturation deficit as well as vegetation cover at daily time step have been done with the Joint UK Land Environment Simulator (JULES) (Best et al, 2011). Our results confirm the Rother catchment is the most erosive, while the Conwy catchment is the more resilient to soil erosion. Sediment production is perceived increase in both cases for the end of the century (27% and 50%, respectively). Seasonal disaggregation of the results revels that, while the most part of soil erosion is produced in winter months (DJF), the higher soil erosion variability for future periods is observed in summer (JJA). This behaviour is supported by the rainfall simulation analyse which highlighted this dual behaviour in precipitations.

The Mars Climate Database (MCD version 5.3)

NASA Astrophysics Data System (ADS)

Millour, Ehouarn; Forget, Francois; Spiga, Aymeric; Vals, Margaux; Zakharov, Vladimir; Navarro, Thomas; Montabone, Luca; Lefevre, Franck; Montmessin, Franck; Chaufray, Jean-Yves; Lopez-Valverde, Miguel; Gonzalez-Galindo, Francisco; Lewis, Stephen; Read, Peter; Desjean, Marie-Christine; MCD/GCM Development Team

2017-04-01

Our Global Circulation Model (GCM) simulates the atmospheric environment of Mars. It is developped at LMD (Laboratoire de Meteorologie Dynamique, Paris, France) in close collaboration with several teams in Europe (LATMOS, France, University of Oxford, The Open University, the Instituto de Astrofisica de Andalucia), and with the support of ESA (European Space Agency) and CNES (French Space Agency). GCM outputs are compiled to build a Mars Climate Database, a freely available tool useful for the scientific and engineering communities. The Mars Climate Database (MCD) has over the years been distributed to more than 300 teams around the world. The latest series of reference simulations have been compiled in a new version (v5.3) of the MCD, released in the first half of 2017. To summarize, MCD v5.3 provides: - Climatologies over a series of synthetic dust scenarios: standard (climatology) year, cold (ie: low dust), warm (ie: dusty atmosphere) and dust storm, all topped by various cases of Extreme UV solar inputs (low, mean or maximum). These scenarios have been derived from home-made, instrument-derived (TES, THEMIS, MCS, MERs), dust climatology of the last 8 Martian years. The MCD also provides simulation outputs (MY24-31) representative of these actual years. - Mean values and statistics of main meteorological variables (atmospheric temperature, density, pressure and winds), as well as surface pressure and temperature, CO2 ice cover, thermal and solar radiative fluxes, dust column opacity and mixing ratio, [H20] vapor and ice columns, concentrations of many species: [CO], [O2], [O], [N2], [H2], [O3], ... - A high resolution mode which combines high resolution (32 pixel/degree) MOLA topography records and Viking Lander 1 pressure records with raw lower resolution GCM results to yield, within the restriction of the procedure, high resolution values of atmospheric variables. - The possibility to reconstruct realistic conditions by combining the provided climatology with additional large scale and small scale perturbations schemes. At EGU, we will report on the latest improvements in the Mars Climate Database, with comparisons with available measurements from orbit (e.g.: TES, MCS) and landers (Viking, Phoenix, MSL).

High Resolution Forecasting System for Mountain area based on KLAPS-WRF

NASA Astrophysics Data System (ADS)

Chun, Ji Min; Rang Kim, Kyu; Lee, Seon-Yong; Kang, Wee Soo; Park, Jong Sun; Yi, Chae Yeon; Choi, Young-jean; Park, Eun Woo; Hong, Soon Sung; Jung, Hyun-Sook

2013-04-01

This paper reviews the results of recent observations and simulations on the thermal belt and cold air drainage, which are outstanding in local climatic phenomena in mountain areas. In a mountain valley, cold air pool and thermal belt were simulated with the Weather and Research Forecast (WRF) model and the Korea Local Analysis and Prediction System (KLAPS) to determine the impacts of planetary boundary layer (PBL) schemes and topography resolution on model performance. Using the KLAPS-WRF models, an information system was developed for 12 hour forecasting of cold air damage in orchard. This system was conducted on a three level nested grid from 1 km to 111 m horizontal resolution. Results of model runs were verified by the data from automated weather stations, which were installed at twelve sites in a valley at Yeonsuri, Yangpyeonggun, Gyeonggido to measure temperature and wind speed and direction during March to May 2012. The potential of the numerical model to simulate these local features was found to be dependent on the planetary boundary layer schemes. Statistical verification results indicate that Mellor-Yamada-Janjic (MYJ) PBL scheme was in good agreement with night time temperature, while the no-PBL scheme produced predictions similar to the day time temperature observation. Although the KLAPS-WRF system underestimates temperature in mountain areas and overestimates wind speed, it produced an accurate description of temperature, with an RMSE of 1.67 ˚C in clear daytime. Wind speed and direction were not forecasted well in precision (RMSE: 5.26 m/s and 10.12 degree). It might have been caused by the measurement uncertainty and spatial variability. Additionally, the performance of KLAPS-WRF was performed to evaluate for different terrain resolution: Topography data were improved from USGS (United States Geological Survey) 30" to NGII (National Geographic Information Institute) 10 m. The simulated results were quantitatively compared to observations and there was a significant improvement (RMSE: 2.06 ˚C -> 1.73 ˚C) in the temperature prediction in the study area. The results will provide useful guidance of grid size selection on high resolution simulation over the mountain regions in Korea.

The Mars Climate Database (MCD version 5.2)

NASA Astrophysics Data System (ADS)

Millour, E.; Forget, F.; Spiga, A.; Navarro, T.; Madeleine, J.-B.; Montabone, L.; Pottier, A.; Lefevre, F.; Montmessin, F.; Chaufray, J.-Y.; Lopez-Valverde, M. A.; Gonzalez-Galindo, F.; Lewis, S. R.; Read, P. L.; Huot, J.-P.; Desjean, M.-C.; MCD/GCM development Team

2015-10-01

The Mars Climate Database (MCD) is a database of meteorological fields derived from General Circulation Model (GCM) numerical simulations of the Martian atmosphere and validated using available observational data. The MCD includes complementary post-processing schemes such as high spatial resolution interpolation of environmental data and means of reconstructing the variability thereof. We have just completed (March 2015) the generation of a new version of the MCD, MCD version 5.2

Interannual variability of temperature over 50 years in the Bay of Biscay described by global simulations

NASA Astrophysics Data System (ADS)

Assassi, Charefeddine; Vandermeirsch, Frederic; Morel, Yves; Charria, Guillaume; Theetten, Sébastien; Dussin, Raphaël; Molines, Jean-Marc

2014-05-01

The aim of this study is to better understand the different overriding mechanisms that control the evolution of the temperature in the Bay of Biscay, through realistic simulations over a period of 50 years. Before performing and analyzing our own numerical experiments with a spatial resolution of 4 km, we compared two global simulations, ORCA-G70 and ORCA-GRD100 (¼° resolution) carried out from the ocean circulation model NEMO by the DRAKKAR group with inter-annual climatologies (WOA04, Levitus et al. 2005 and Bobyclim, Michel et al. 2009). Both simulations differ in their vertical resolution (46 levels in G70 and 75 levels in GRD100) and atmospheric forcings. The comparison of the two simulations shows an underestimation of the absolute temperature in GRD100 approximately 0.4°C in the first 300 meters for the entire period of the simulation (1958-2004) compared to G70, although the net air-sea heat flux is significantly higher in GRD100 (2.92 TW for GRD100 and 0.20 TW for G70). Several parameters can explain this apparent contradiction. On one hand, the wind is more intense in GRD100 and can contribute to the heat penetration on depth. On the other hand, the thermal balances at different depths show a great disparity between both simulations, especially in terms of advective transport. However, the temperature anomaly in the two global simulations is very close to observations (climatology) in the first 400 meters. The standard deviation is higher in the mixed layer (0.29°C for both simulations ORCA) and lower in the intermediate layers (0.15°C for G70 and to 0.13°C for GRD100). Moreover, the calculation of the surface linear trend of temperature in GRD100 (0.14°C.decade-1) is closer to the observations W0A04 (0.19°C.decade-1) while it is only (0.10°C.decade-1) in G70. The GRD100 simulation provides a better evolution than G70. These analysis confirm the suitability of the simulation GRD100 to drive a regional numerical experiment at higher resolution in the Bay of Biscay. The first experiments during a short period of our regional model (4 km spatial resolution, based on MARS3D code) showed consistency in the forcings used and give realistic results in temperature. This regional approach will be used to explore and understand the main mechanisms involved in the evolution of the temperature at multi-decadal scales.

Trends in soil moisture and real evapotranspiration in Douro River for the period 1980-2010

NASA Astrophysics Data System (ADS)

García-Valdecasas-Ojeda, Matilde; de Franciscis, Sebastiano; Raquel Gámiz-Fortis, Sonia; Castro-Díez, Yolanda; Jesús Esteban-Parra, María

2017-04-01

This study analyzes the evolution of different hydrological variables, such as soil moisture and real evapotranspiration, for the last 30 years, in the Douro Basin, the most extensive basin in the Iberian Peninsula. The different components of the real evaporation, connected to the soil moisture content, can be important when analyzing the intensity of droughts and heat waves, and particularly relevant for the study of the climate change impacts. The real evapotranspiration and soil moisture data are provided by simulations obtained using the Variable Infiltration Capacity (VIC) hydrological model. This model is a large-scale hydrologic model and allows estimates of different variables in the hydrological system of a basin. Land surface is modeled as a grid of large and uniform cells with sub-grid heterogeneity (e.g. land cover), while water influx is local, only depending from the interaction between grid cells and local atmosphere environment. Observational data of temperature and precipitation from Spain02 dataset are used as input variables for VIC model. The simulations have a spatial resolution of about 9 km, and the analysis is carried out on a seasonal time-scale. Additionally, we compare these results with those obtained from a dynamical downscaling driven by ERA-Interim data using the Weather Research and Forecasting (WRF) model, with the same spatial resolution. The results obtained from Spain02 data show a decrease in soil moisture at different parts of the basin during spring and summer, meanwhile soil moisture seems to be increased for autumn. No significant changes are found for real evapotranspiration. Keywords: real evapotranspiration, soil moisture, Douro Basin, trends, VIC, WRF. Acknowledgements: This work has been financed by the projects P11-RNM-7941 (Junta de Andalucía-Spain) and CGL2013-48539-R (MINECO-Spain, FEDER).

Impact of the Mesoscale Dynamics on Ocean Deep Convection: The 2012-2013 Case Study in the Northwestern Mediterranean Sea

NASA Astrophysics Data System (ADS)

Waldman, Robin; Herrmann, Marine; Somot, Samuel; Arsouze, Thomas; Benshila, Rachid; Bosse, Anthony; Chanut, Jerome; Giordani, Herve; Sevault, Florence; Testor, Pierre

2017-11-01

Winter 2012-2013 was a particularly intense and well-observed Dense Water Formation (DWF) event in the Northwestern Mediterranean Sea. In this study, we investigate the impact of the mesoscale dynamics on DWF. We perform two perturbed initial state simulation ensembles from summer 2012 to 2013, respectively, mesoscale-permitting and mesoscale-resolving, with the AGRIF refinement tool in the Mediterranean configuration NEMOMED12. The mean impact of the mesoscale on DWF occurs mainly through the high-resolution physics and not the high-resolution bathymetry. This impact is shown to be modest: the mesoscale does not modify the chronology of the deep convective winter nor the volume of dense waters formed. It however impacts the location of the mixed patch by reducing its extent to the west of the North Balearic Front and by increasing it along the Northern Current, in better agreement with observations. The maximum mixed patch volume is significantly reduced from 5.7 ± 0.2 to 4.2 ± 0.6 × 1013 m3. Finally, the spring restratification volume is more realistic and enhanced from 1.4 ± 0.2 to 1.8 ± 0.2 × 1013 m3 by the mesoscale. We also address the mesoscale impact on the ocean intrinsic variability by performing perturbed initial state ensemble simulations. The mesoscale enhances the intrinsic variability of the deep convection geography, with most of the mixed patch area impacted by intrinsic variability. The DWF volume has a low intrinsic variability but it is increased by 2-3 times with the mesoscale. We relate it to a dramatic increase of the Gulf of Lions eddy kinetic energy from 5.0 ± 0.6 to 17.3 ± 1.5 cm2/s2, in remarkable agreement with observations.

Hydrologic scales, cloud variability, remote sensing, and models: Implications for forecasting snowmelt and streamflow

USGS Publications Warehouse

Simpson, James J.; Dettinger, M.D.; Gehrke, F.; McIntire, T.J.; Hufford, Gary L.

2004-01-01

Accurate prediction of available water supply from snowmelt is needed if the myriad of human, environmental, agricultural, and industrial demands for water are to be satisfied, especially given legislatively imposed conditions on its allocation. Robust retrievals of hydrologic basin model variables (e.g., insolation or areal extent of snow cover) provide several advantages over the current operational use of either point measurements or parameterizations to help to meet this requirement. Insolation can be provided at hourly time scales (or better if needed during rapid melt events associated with flooding) and at 1-km spatial resolution. These satellite-based retrievals incorporate the effects of highly variable (both in space and time) and unpredictable cloud cover on estimates of insolation. The insolation estimates are further adjusted for the effects of basin topography using a high-resolution digital elevation model prior to model input. Simulations of two Sierra Nevada rivers in the snowmelt seasons of 1998 and 1999 indicate that even the simplest improvements in modeled insolation can improve snowmelt simulations, with 10%-20% reductions in root-mean-square errors. Direct retrieval of the areal extent of snow cover may mitigate the need to rely entirely on internal calculations of this variable, a reliance that can yield large errors that are difficult to correct until long after the season is complete and that often leads to persistent underestimates or overestimates of the volumes of the water to operational reservoirs. Agencies responsible for accurately predicting available water resources from the melt of snowpack [e.g., both federal (the National Weather Service River Forecast Centers) and state (the California Department of Water Resources)] can benefit by incorporating concepts developed herein into their operational forecasting procedures. ?? 2004 American Meteorological Society.

Holocene climate variability in Texas, USA: An integration of existing paleoclimate data and modeling with a new, high-resolution speleothem record

USGS Publications Warehouse

Wong, Corinne I.; Banner, Jay L.; Musgrove, MaryLynn

2015-01-01

Delineating the climate processes governing precipitation variability in drought-prone Texas is critical for predicting and mitigating climate change effects, and requires the reconstruction of past climate beyond the instrumental record. We synthesize existing paleoclimate proxy data and climate simulations to provide an overview of climate variability in Texas during the Holocene. Conditions became progressively warmer and drier transitioning from the early to mid Holocene, culminating between 7 and 3 ka (thousand years ago), and were more variable during the late Holocene. The timing and relative magnitude of Holocene climate variability, however, is poorly constrained owing to considerable variability among the different records. To help address this, we present a new speleothem (NBJ) reconstruction from a central Texas cave that comprises the highest resolution proxy record to date, spanning the mid to late Holocene. NBJ trace-element concentrations indicate variable moisture conditions with no clear temporal trend. There is a decoupling between NBJ growth rate, trace-element concentrations, and δ18O values, which indicate that (i) the often direct relation between speleothem growth rate and moisture availability is likely complicated by changes in the overlying ecosystem that affect subsurface CO2 production, and (ii) speleothem δ18O variations likely reflect changes in moisture source (i.e., proportion of Pacific-vs. Gulf of Mexico-derived moisture) that appear not to be linked to moisture amount.

Nonlinear vs. linear biasing in Trp-cage folding simulations

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

Spiwok, Vojtěch, E-mail: spiwokv@vscht.cz; Oborský, Pavel; Králová, Blanka

2015-03-21

Biased simulations have great potential for the study of slow processes, including protein folding. Atomic motions in molecules are nonlinear, which suggests that simulations with enhanced sampling of collective motions traced by nonlinear dimensionality reduction methods may perform better than linear ones. In this study, we compare an unbiased folding simulation of the Trp-cage miniprotein with metadynamics simulations using both linear (principle component analysis) and nonlinear (Isomap) low dimensional embeddings as collective variables. Folding of the mini-protein was successfully simulated in 200 ns simulation with linear biasing and non-linear motion biasing. The folded state was correctly predicted as the free energymore » minimum in both simulations. We found that the advantage of linear motion biasing is that it can sample a larger conformational space, whereas the advantage of nonlinear motion biasing lies in slightly better resolution of the resulting free energy surface. In terms of sampling efficiency, both methods are comparable.« less

A Modeling and Verification Study of Summer Precipitation Systems Using NASA Surface Initialization Datasets

NASA Technical Reports Server (NTRS)

Jonathan L. Case; Kumar, Sujay V.; Srikishen, Jayanthi; Jedlovec, Gary J.

2010-01-01

One of the most challenging weather forecast problems in the southeastern U.S. is daily summertime pulse-type convection. During the summer, atmospheric flow and forcing are generally weak in this region; thus, convection typically initiates in response to local forcing along sea/lake breezes, and other discontinuities often related to horizontal gradients in surface heating rates. Numerical simulations of pulse convection usually have low skill, even in local predictions at high resolution, due to the inherent chaotic nature of these precipitation systems. Forecast errors can arise from assumptions within parameterization schemes, model resolution limitations, and uncertainties in both the initial state of the atmosphere and land surface variables such as soil moisture and temperature. For this study, it is hypothesized that high-resolution, consistent representations of surface properties such as soil moisture, soil temperature, and sea surface temperature (SST) are necessary to better simulate the interactions between the surface and atmosphere, and ultimately improve predictions of summertime pulse convection. This paper describes a sensitivity experiment using the Weather Research and Forecasting (WRF) model. Interpolated land and ocean surface fields from a large-scale model are replaced with high-resolution datasets provided by unique NASA assets in an experimental simulation: the Land Information System (LIS) and Moderate Resolution Imaging Spectroradiometer (MODIS) SSTs. The LIS is run in an offline mode for several years at the same grid resolution as the WRF model to provide compatible land surface initial conditions in an equilibrium state. The MODIS SSTs provide detailed analyses of SSTs over the oceans and large lakes compared to current operational products. The WRF model runs initialized with the LIS+MODIS datasets result in a reduction in the overprediction of rainfall areas; however, the skill is almost equally as low in both experiments using traditional verification methodologies. Output from object-based verification within NCAR s Meteorological Evaluation Tools reveals that the WRF runs initialized with LIS+MODIS data consistently generated precipitation objects that better matched observed precipitation objects, especially at higher precipitation intensities. The LIS+MODIS runs produced on average a 4% increase in matched precipitation areas and a simultaneous 4% decrease in unmatched areas during three months of daily simulations.

Improving surface-subsurface water budgeting using high resolution satellite imagery applied on a brownfield.

PubMed

Dujardin, J; Batelaan, O; Canters, F; Boel, S; Anibas, C; Bronders, J

2011-01-15

The estimation of surface-subsurface water interactions is complex and highly variable in space and time. It is even more complex when it has to be estimated in urban areas, because of the complex patterns of the land-cover in these areas. In this research a modeling approach with integrated remote sensing analysis has been developed for estimating water fluxes in urban environments. The methodology was developed with the aim to simulate fluxes of contaminants from polluted sites. Groundwater pollution in urban environments is linked to patterns of land use and hence it is essential to characterize the land cover in a detail. An object-oriented classification approach applied on high-resolution satellite data has been adopted. To assign the image objects to one of the land-cover classes a multiple layer perceptron approach was adopted (Kappa of 0.86). Groundwater recharge has been simulated using the spatially distributed WetSpass model and the subsurface water flow using MODFLOW in order to identify and budget water fluxes. The developed methodology is applied to a brownfield case site in Vilvoorde, Brussels (Belgium). The obtained land use map has a strong impact on the groundwater recharge, resulting in a high spatial variability. Simulated groundwater fluxes from brownfield to the receiving River Zenne were independently verified by measurements and simulation of groundwater-surface water interaction based on thermal gradients in the river bed. It is concluded that in order to better quantify total fluxes of contaminants from brownfields in the groundwater, remote sensing imagery can be operationally integrated in a modeling procedure. Copyright © 2010 Elsevier B.V. All rights reserved.

Present and Future Projections of Habitat Suitability of the Asian Tiger Mosquito, a Vector of Viral Pathogens, from Global Climate Simulations.

NASA Astrophysics Data System (ADS)

Proestos, Y.; Christophides, G.; Erguler, K.; Tanarhte, M.; Waldock, J.; Lelieveld, J.

2014-12-01

Climate change can influence the transmission of vector borne diseases (VBDs) through altering the habitat suitability of insect vectors. Here we present global climate model simulations and evaluate the associated uncertainties in view of the main meteorological factors that may affect the distribution of the Asian Tiger mosquito (Aedes albopictus), which can transmit pathogens that cause Chikungunya, Dengue fever, yellow fever and various encephalitides. Using a general circulation model (GCM) at 50 km horizontal resolution to simulate mosquito survival variables including temperature, precipitation and relative humidity, we present both global and regional projections of the habitat suitability up to the middle of the 21st century. The model resolution of 50 km allows evaluation against previous projections for Europe and provides a basis for comparative analyses with other regions. Model uncertainties and performance are addressed in light of the recent CMIP5 ensemble climate model simulations for the RCP8.5 concentration pathway and using meteorological re-analysis data (ERA-Interim/ECMWF) for the recent past. Uncertainty ranges associated with the thresholds of meteorological variables that may affect the distribution of Ae. albopictus are diagnosed using fuzzy-logic methodology, notably to assess the influence of selected meteorological criteria and combinations of criteria that influence mosquito habitat suitability. From the climate projections for 2050, and adopting a habitat suitability index larger than 70%, we estimate that about 2.4 billion individuals in a land area of nearly 20 million square kilometres will potentially be exposed to Ae. albopictus. The synthesis of fuzzy-logic based on mosquito biology and climate change analysis provides new insights into the regional and global spreading of VBDs to support disease control and policy making.

COSP: Satellite simulation software for model assessment

DOE PAGES

Bodas-Salcedo, A.; Webb, M. J.; Bony, S.; ...

2011-08-01

Errors in the simulation of clouds in general circulation models (GCMs) remain a long-standing issue in climate projections, as discussed in the Intergovernmental Panel on Climate Change (IPCC) Fourth Assessment Report. This highlights the need for developing new analysis techniques to improve our knowledge of the physical processes at the root of these errors. The Cloud Feedback Model Intercomparison Project (CFMIP) pursues this objective, and under that framework the CFMIP Observation Simulator Package (COSP) has been developed. COSP is a flexible software tool that enables the simulation of several satellite-borne active and passive sensor observations from model variables. The flexibilitymore » of COSP and a common interface for all sensors facilitates its use in any type of numerical model, from high-resolution cloud-resolving models to the coarser-resolution GCMs assessed by the IPCC, and the scales in between used in weather forecast and regional models. The diversity of model parameterization techniques makes the comparison between model and observations difficult, as some parameterized variables (e.g., cloud fraction) do not have the same meaning in all models. The approach followed in COSP permits models to be evaluated against observations and compared against each other in a more consistent manner. This thus permits a more detailed diagnosis of the physical processes that govern the behavior of clouds and precipitation in numerical models. The World Climate Research Programme (WCRP) Working Group on Coupled Modelling has recommended the use of COSP in a subset of climate experiments that will be assessed by the next IPCC report. Here we describe COSP, present some results from its application to numerical models, and discuss future work that will expand its capabilities.« less

Modeling Global Atmospheric CO2 Fluxes and Transport Using NASA MERRA Reanalysis Data

NASA Astrophysics Data System (ADS)

Liu, Y.; Kawa, S. R.; Collatz, G. J.

2010-12-01

We present our first results of CO2 surface biosphere fluxes and global atmospheric CO2 transport using NASA’s new MERRA reanalysis data. MERRA is the Modern Era Retrospective-Analysis For Research And Applications based on the Goddard Global Modeling and Assimilation Office GEOS-5 data assimilation system. After some application testing and analysis, we have generated biospheric CO2 fluxes at 3-hourly temporal resolution from an updated version of the CASA carbon cycle model using the 1x1.25-degree reanalysis data. The experiment covers a period of 9 years from 2000 -2008. The affects of US midwest crop (largely corn and soy) carbon uptake and removal by harvest are explicitly included in this version of CASA. Across the agricultural regions of the Midwest US, USDA crop yield data are used to scale vegetation fluxes producing a strong sink in the growing season and a comparatively weaker source from respiration after harvest. Comparisons of the new fluxes to previous ones generated using GEOS-4 data are provided. The Parameterized Chemistry/Transport Model (PCTM) is then used with the analyzed meteorology in offline CO2 transport. In the simulation of CO2 transport, we have a higher vertical resolution from MERRA (the lowest 56 of 72 levels are used in our simulation). A preliminary analysis of the CO2 simulation results is carried out, including diurnal, seasonal and latitudinal variability. We make comparisons of our simulation to continuous CO2 analyzer sites, especially those in agricultural regions. The results show that the model captures reasonably well the observed synoptic variability due to transport changes and biospheric fluxes.

Resolution convergence in cosmological hydrodynamical simulations using adaptive mesh refinement

NASA Astrophysics Data System (ADS)

Snaith, Owain N.; Park, Changbom; Kim, Juhan; Rosdahl, Joakim

2018-06-01

We have explored the evolution of gas distributions from cosmological simulations carried out using the RAMSES adaptive mesh refinement (AMR) code, to explore the effects of resolution on cosmological hydrodynamical simulations. It is vital to understand the effect of both the resolution of initial conditions (ICs) and the final resolution of the simulation. Lower initial resolution simulations tend to produce smaller numbers of low-mass structures. This will strongly affect the assembly history of objects, and has the same effect of simulating different cosmologies. The resolution of ICs is an important factor in simulations, even with a fixed maximum spatial resolution. The power spectrum of gas in simulations using AMR diverges strongly from the fixed grid approach - with more power on small scales in the AMR simulations - even at fixed physical resolution and also produces offsets in the star formation at specific epochs. This is because before certain times the upper grid levels are held back to maintain approximately fixed physical resolution, and to mimic the natural evolution of dark matter only simulations. Although the impact of hold-back falls with increasing spatial and IC resolutions, the offsets in the star formation remain down to a spatial resolution of 1 kpc. These offsets are of the order of 10-20 per cent, which is below the uncertainty in the implemented physics but are expected to affect the detailed properties of galaxies. We have implemented a new grid-hold-back approach to minimize the impact of hold-back on the star formation rate.

The ARM Cloud Radar Simulator for Global Climate Models: Bridging Field Data and Climate Models

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

Zhang, Yuying; Xie, Shaocheng; Klein, Stephen A.

Clouds play an important role in Earth’s radiation budget and hydrological cycle. However, current global climate models (GCMs) have had difficulties in accurately simulating clouds and precipitation. To improve the representation of clouds in climate models, it is crucial to identify where simulated clouds differ from real world observations of them. This can be difficult, since significant differences exist between how a climate model represents clouds and what instruments observe, both in terms of spatial scale and the properties of the hydrometeors which are either modeled or observed. To address these issues and minimize impacts of instrument limitations, the conceptmore » of instrument “simulators”, which convert model variables into pseudo-instrument observations, has evolved with the goal to improve and to facilitate the comparison of modeled clouds with observations. Many simulators have (and continue to be developed) for a variety of instruments and purposes. A community satellite simulator package, the Cloud Feedback Model Intercomparison Project (CFMIP) Observation Simulator Package (COSP; Bodas-Salcedo et al. 2011), contains several independent satellite simulators and is being widely used in the global climate modeling community to exploit satellite observations for model cloud evaluation (e.g., Klein et al. 2013; Zhang et al. 2010). This article introduces a ground-based cloud radar simulator developed by the U.S. Department of Energy (DOE) Atmospheric Radiation Measurement (ARM) program for comparing climate model clouds with ARM observations from its vertically pointing 35-GHz radars. As compared to CloudSat radar observations, ARM radar measurements occur with higher temporal resolution and finer vertical resolution. This enables users to investigate more fully the detailed vertical structures within clouds, resolve thin clouds, and quantify the diurnal variability of clouds. Particularly, ARM radars are sensitive to low-level clouds, which are difficult for the CloudSat radar to detect due to surface contamination (Mace et al. 2007; Marchand et al. 2008). Therefore, the ARM ground-based cloud observations can provide important observations of clouds that complement measurements from space.« less

Changing precipitation in western Europe, climate change or natural variability?

NASA Astrophysics Data System (ADS)

Aalbers, Emma; Lenderink, Geert; van Meijgaard, Erik; van den Hurk, Bart

2017-04-01

Multi-model RCM-GCM ensembles provide high resolution climate projections, valuable for among others climate impact assessment studies. While the application of multiple models (both GCMs and RCMs) provides a certain robustness with respect to model uncertainty, the interpretation of differences between ensemble members - the combined result of model uncertainty and natural variability of the climate system - is not straightforward. Natural variability is intrinsic to the climate system, and a potentially large source of uncertainty in climate change projections, especially for projections on the local to regional scale. To quantify the natural variability and get a robust estimate of the forced climate change response (given a certain model and forcing scenario), large ensembles of climate model simulations of the same model provide essential information. While for global climate models (GCMs) a number of such large single model ensembles exists and have been analyzed, for regional climate models (RCMs) the number and size of single model ensembles is limited, and the predictability of the forced climate response at the local to regional scale is still rather uncertain. We present a regional downscaling of a 16-member single model ensemble over western Europe and the Alps at a resolution of 0.11 degrees (˜12km), similar to the highest resolution EURO-CORDEX simulations. This 16-member ensemble was generated by the GCM EC-EARTH, which was downscaled with the RCM RACMO for the period 1951-2100. This single model ensemble has been investigated in terms of the ensemble mean response (our estimate of the forced climate response), as well as the difference between the ensemble members, which measures natural variability. We focus on the response in seasonal mean and extreme precipitation (seasonal maxima and extremes with a return period up to 20 years) for the near to far future. For most precipitation indices we can reliably determine the climate change signal, given the applied model chain and forcing scenario. However, the analysis also shows how limited the information in single ensemble members is on the local scale forced climate response, even for high levels of global warming when the forced response has emerged from natural variability. Analysis and application of multi-model ensembles like EURO-CORDEX should go hand-in-hand with single model ensembles, like the one presented here, to be able to correctly interpret the fine-scale information in terms of a forced signal and random noise due to natural variability.

Stratospheric temperatures and tracer transport in a nudged 4-year middle atmosphere GCM simulation

NASA Astrophysics Data System (ADS)

van Aalst, M. K.; Lelieveld, J.; Steil, B.; Brühl, C.; Jöckel, P.; Giorgetta, M. A.; Roelofs, G.-J.

2005-02-01

We have performed a 4-year simulation with the Middle Atmosphere General Circulation Model MAECHAM5/MESSy, while slightly nudging the model's meteorology in the free troposphere (below 113 hPa) towards ECMWF analyses. We show that the nudging 5 technique, which leaves the middle atmosphere almost entirely free, enables comparisons with synoptic observations. The model successfully reproduces many specific features of the interannual variability, including details of the Antarctic vortex structure. In the Arctic, the model captures general features of the interannual variability, but falls short in reproducing the timing of sudden stratospheric warmings. A 10 detailed comparison of the nudged model simulations with ECMWF data shows that the model simulates realistic stratospheric temperature distributions and variabilities, including the temperature minima in the Antarctic vortex. Some small (a few K) model biases were also identified, including a summer cold bias at both poles, and a general cold bias in the lower stratosphere, most pronounced in midlatitudes. A comparison 15 of tracer distributions with HALOE observations shows that the model successfully reproduces specific aspects of the instantaneous circulation. The main tracer transport deficiencies occur in the polar lowermost stratosphere. These are related to the tropopause altitude as well as the tracer advection scheme and model resolution. The additional nudging of equatorial zonal winds, forcing the quasi-biennial oscillation, sig20 nificantly improves stratospheric temperatures and tracer distributions.

Downscaling Solar Power Output to 4-Seconds for Use in Integration Studies (Presentation)

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

Hummon, M.; Weekley, A.; Searight, K.

2013-10-01

High penetration renewable integration studies require solar power data with high spatial and temporal accuracy to quantify the impact of high frequency solar power ramps on the operation of the system. Our previous work concentrated on downscaling solar power from one hour to one minute by simulation. This method used clearness classifications to categorize temporal and spatial variability, and iterative methods to simulate intra-hour clearness variability. We determined that solar power ramp correlations between sites decrease with distance and the duration of the ramp, starting at around 0.6 for 30-minute ramps between sites that are less than 20 km apart.more » The sub-hour irradiance algorithm we developed has a noise floor that causes the correlations to approach ~0.005. Below one minute, the majority of the correlations of solar power ramps between sites less than 20 km apart are zero, and thus a new method to simulate intra-minute variability is needed. These intra-minute solar power ramps can be simulated using several methods, three of which we evaluate: a cubic spline fit to the one-minute solar power data; projection of the power spectral density toward the higher frequency domain; and average high frequency power spectral density from measured data. Each of these methods either under- or over-estimates the variability of intra-minute solar power ramps. We show that an optimized weighted linear sum of methods, dependent on the classification of temporal variability of the segment of one-minute solar power data, yields time series and ramp distributions similar to measured high-resolution solar irradiance data.« less

Downscaling Solar Power Output to 4-Seconds for Use in Integration Studies: Preprint

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

Hummon, M.; Weekley, A.; Searight, K.

2013-10-01

High penetration renewable integration studies require solar power data with high spatial and temporal accuracy to quantify the impact of high frequency solar power ramps on the operation of the system. Our previous work concentrated on downscaling solar power from one hour to one minute by simulation. This method used clearness classifications to categorize temporal and spatial variability, and iterative methods to simulate intra-hour clearness variability. We determined that solar power ramp correlations between sites decrease with distance and the duration of the ramp, starting at around 0.6 for 30-minute ramps between sites that are less than 20 km apart.more » The sub-hour irradiance algorithm we developed has a noise floor that causes the correlations to approach ~0.005. Below one minute, the majority of the correlations of solar power ramps between sites less than 20 km apart are zero, and thus a new method to simulate intra-minute variability is needed. These intra-minute solar power ramps can be simulated using several methods, three of which we evaluate: a cubic spline fit to the one-minute solar power data; projection of the power spectral density toward the higher frequency domain; and average high frequency power spectral density from measured data. Each of these methods either under- or over-estimates the variability of intra-minute solar power ramps. We show that an optimized weighted linear sum of methods, dependent on the classification of temporal variability of the segment of one-minute solar power data, yields time series and ramp distributions similar to measured high-resolution solar irradiance data.« less

Towards Improving Satellite Tropospheric NO2 Retrieval Products: Impacts of the spatial resolution and lighting NOx production from the a priori chemical transport model

NASA Astrophysics Data System (ADS)

Smeltzer, C. D.; Wang, Y.; Zhao, C.; Boersma, F.

2009-12-01

Polar orbiting satellite retrievals of tropospheric nitrogen dioxide (NO2) columns are important to a variety of scientific applications. These NO2 retrievals rely on a priori profiles from chemical transport models and radiative transfer models to derive the vertical columns (VCs) from slant columns measurements. In this work, we compare the retrieval results using a priori profiles from a global model (TM4) and a higher resolution regional model (REAM) at the OMI overpass hour of 1330 local time, implementing the Dutch OMI NO2 (DOMINO) retrieval. We also compare the retrieval results using a priori profiles from REAM model simulations with and without lightning NOx (NO + NO2) production. A priori model resolution and lightning NOx production are both found to have large impact on satellite retrievals by altering the satellite sensitivity to a particular observation by shifting the NO2 vertical distribution interpreted by the radiation model. The retrieved tropospheric NO2 VCs may increase by 25-100% in urban regions and be reduced by 50% in rural regions if the a priori profiles from REAM simulations are used during the retrievals instead of the profiles from TM4 simulations. The a priori profiles with lightning NOx may result in a 25-50% reduction of the retrieved tropospheric NO2 VCs compared to the a priori profiles without lightning. As first priority, a priori vertical NO2 profiles from a chemical transport model with a high resolution, which can better simulate urban-rural NO2 gradients in the boundary layer and make use of observation-based parameterizations of lightning NOx production, should be first implemented to obtain more accurate NO2 retrievals over the United States, where NOx source regions are spatially separated and lightning NOx production is significant. Then as consequence of a priori NO2 profile variabilities resulting from lightning and model resolution dynamics, geostationary satellite, daylight observations would further promote the next step towards producing a more complete NO2 data product provided sufficient resolution of the observations. Both the corrected retrieval algorithm and the proposed next generation geostationary satellite observations would thus improve emission inventories, better validate model simulations, and advantageously optimize regional specific ozone control strategies.

Simulating Ice Shelf Response to Potential Triggers of Collapse Using the Material Point Method

NASA Astrophysics Data System (ADS)

Huth, A.; Smith, B. E.

2017-12-01

Weakening or collapse of an ice shelf can reduce the buttressing effect of the shelf on its upstream tributaries, resulting in sea level rise as the flux of grounded ice into the ocean increases. Here we aim to improve sea level rise projections by developing a prognostic 2D plan-view model that simulates the response of an ice sheet/ice shelf system to potential triggers of ice shelf weakening or collapse, such as calving events, thinning, and meltwater ponding. We present initial results for Larsen C. Changes in local ice shelf stresses can affect flow throughout the entire domain, so we place emphasis on calibrating our model to high-resolution data and precisely evolving fracture-weakening and ice geometry throughout the simulations. We primarily derive our initial ice geometry from CryoSat-2 data, and initialize the model by conducting a dual inversion for the ice viscosity parameter and basal friction coefficient that minimizes mismatch between modeled velocities and velocities derived from Landsat data. During simulations, we implement damage mechanics to represent fracture-weakening, and track ice thickness evolution, grounding line position, and ice front position. Since these processes are poorly represented by the Finite Element Method (FEM) due to mesh resolution issues and numerical diffusion, we instead implement the Material Point Method (MPM) for our simulations. In MPM, the ice domain is discretized into a finite set of Lagrangian material points that carry all variables and are tracked throughout the simulation. Each time step, information from the material points is projected to a Eulerian grid where the momentum balance equation (shallow shelf approximation) is solved similarly to FEM, but essentially treating the material points as integration points. The grid solution is then used to determine the new positions of the material points and update variables such as thickness and damage in a diffusion-free Lagrangian frame. The grid does not store any variables permanently, and can be replaced at any time step. MPM naturally tracks the ice front and grounding line at a subgrid scale. MPM also facilitates the implementation of rift propagation in arbitrary directions, and therefore shows promise for predicting calving events. To our knowledge, this is the first application of MPM to ice flow modeling.

Generation of Multivariate Surface Weather Series with Use of the Stochastic Weather Generator Linked to Regional Climate Model

NASA Astrophysics Data System (ADS)

Dubrovsky, M.; Farda, A.; Huth, R.

2012-12-01

The regional-scale simulations of weather-sensitive processes (e.g. hydrology, agriculture and forestry) for the present and/or future climate often require high resolution meteorological inputs in terms of the time series of selected surface weather characteristics (typically temperature, precipitation, solar radiation, humidity, wind) for a set of stations or on a regular grid. As even the latest Global and Regional Climate Models (GCMs and RCMs) do not provide realistic representation of statistical structure of the surface weather, the model outputs must be postprocessed (downscaled) to achieve the desired statistical structure of the weather data before being used as an input to the follow-up simulation models. One of the downscaling approaches, which is employed also here, is based on a weather generator (WG), which is calibrated using the observed weather series and then modified (in case of simulations for the future climate) according to the GCM- or RCM-based climate change scenarios. The present contribution uses the parametric daily weather generator M&Rfi to follow two aims: (1) Validation of the new simulations of the present climate (1961-1990) made by the ALADIN-Climate/CZ (v.2) Regional Climate Model at 25 km resolution. The WG parameters will be derived from the RCM-simulated surface weather series and compared to those derived from observational data in the Czech meteorological stations. The set of WG parameters will include selected statistics of the surface temperature and precipitation (characteristics of the mean, variability, interdiurnal variability and extremes). (2) Testing a potential of RCM output for calibration of the WG for the ungauged locations. The methodology being examined will consist in using the WG, whose parameters are interpolated from the surrounding stations and then corrected based on a RCM-simulated spatial variability. The quality of the weather series produced by the WG calibrated in this way will be assessed in terms of selected climatic characteristics focusing on extreme precipitation and temperature characteristics (including characteristics of dry/wet/hot/cold spells). Acknowledgements: The present experiment is made within the frame of projects ALARO (project P209/11/2405 sponsored by the Czech Science Foundation), WG4VALUE (project LD12029 sponsored by the Ministry of Education, Youth and Sports) and VALUE (COST ES 1102 action).

Leaf Area Index Estimation Using Chinese GF-1 Wide Field View Data in an Agriculture Region.

PubMed

Wei, Xiangqin; Gu, Xingfa; Meng, Qingyan; Yu, Tao; Zhou, Xiang; Wei, Zheng; Jia, Kun; Wang, Chunmei

2017-07-08

Leaf area index (LAI) is an important vegetation parameter that characterizes leaf density and canopy structure, and plays an important role in global change study, land surface process simulation and agriculture monitoring. The wide field view (WFV) sensor on board the Chinese GF-1 satellite can acquire multi-spectral data with decametric spatial resolution, high temporal resolution and wide coverage, which are valuable data sources for dynamic monitoring of LAI. Therefore, an automatic LAI estimation algorithm for GF-1 WFV data was developed based on the radiative transfer model and LAI estimation accuracy of the developed algorithm was assessed in an agriculture region with maize as the dominated crop type. The radiative transfer model was firstly used to simulate the physical relationship between canopy reflectance and LAI under different soil and vegetation conditions, and then the training sample dataset was formed. Then, neural networks (NNs) were used to develop the LAI estimation algorithm using the training sample dataset. Green, red and near-infrared band reflectances of GF-1 WFV data were used as the input variables of the NNs, as well as the corresponding LAI was the output variable. The validation results using field LAI measurements in the agriculture region indicated that the LAI estimation algorithm could achieve satisfactory results (such as R² = 0.818, RMSE = 0.50). In addition, the developed LAI estimation algorithm had potential to operationally generate LAI datasets using GF-1 WFV land surface reflectance data, which could provide high spatial and temporal resolution LAI data for agriculture, ecosystem and environmental management researches.

Using wind fields from a high resolution atmospheric model for simulating snow dynamics in mountainous terrain

NASA Astrophysics Data System (ADS)

Bernhardt, M.; Strasser, U.; Zängl, G.; Mauser, W.; Liston, G.; Pohl, S.

2008-12-01

Wind-induced snow transport processes lead to a significant variability of the snow cover. Knowledge about this variability is important for e.g. determining the temporal dynamics of the snowmelt runoff. For predicting the correct amount of transported snow knowledge of the local wind-field is an essential. In high-alpine rugged relief wind fields can hardly be provided by a simple interpolation of station recordings. In this work we use a modified version of the PSU/NCAR Mesoscale Model MM5 to derive wind fields for a 450 km² area at a target resolution of 200 m, accounting for topography and related dynamic effects. We have modelled 220 wind fields representing the most characteristic wind situations within the test-area. The criteria for the extraction of the wind field for the current snowmodel (SNOWTRAND-3D) time step are mean wind speeds and directions in the 700 hPa level derived from DWD (German Weather Service) Local Model reanalysis data with a temporal resolution of one hour. These data are then compared with the corresponding mean wind speeds and directions from the appropriate MM5 nesting area indicating which one of the library files represents the best fit. Verification is conducted by comparison of historical station measurements with corresponding downscaled simulation results. For this downscaling a semi-empirical approach is utilized which accounts for topographic effects. Results for the winter seasons 2003/04 and 2004/05 showing that the presented scheme is able to improve the quality of SNOWTRAN-3D runs with respect to the snow height.

Impact of temporal upscaling and chemical transport model horizontal resolution on reducing ozone exposure misclassification

NASA Astrophysics Data System (ADS)

Xu, Yadong; Serre, Marc L.; Reyes, Jeanette M.; Vizuete, William

2017-10-01

We have developed a Bayesian Maximum Entropy (BME) framework that integrates observations from a surface monitoring network and predictions from a Chemical Transport Model (CTM) to create improved exposure estimates that can be resolved into any spatial and temporal resolution. The flexibility of the framework allows for input of data in any choice of time scales and CTM predictions of any spatial resolution with varying associated degrees of estimation error and cost in terms of implementation and computation. This study quantifies the impact on exposure estimation error due to these choices by first comparing estimations errors when BME relied on ozone concentration data either as an hourly average, the daily maximum 8-h average (DM8A), or the daily 24-h average (D24A). Our analysis found that the use of DM8A and D24A data, although less computationally intensive, reduced estimation error more when compared to the use of hourly data. This was primarily due to the poorer CTM model performance in the hourly average predicted ozone. Our second analysis compared spatial variability and estimation errors when BME relied on CTM predictions with a grid cell resolution of 12 × 12 km2 versus a coarser resolution of 36 × 36 km2. Our analysis found that integrating the finer grid resolution CTM predictions not only reduced estimation error, but also increased the spatial variability in daily ozone estimates by 5 times. This improvement was due to the improved spatial gradients and model performance found in the finer resolved CTM simulation. The integration of observational and model predictions that is permitted in a BME framework continues to be a powerful approach for improving exposure estimates of ambient air pollution. The results of this analysis demonstrate the importance of also understanding model performance variability and its implications on exposure error.

Daily and 3-hourly Variability in Global Fire Emissions and Consequences for Atmospheric Model Predictions of Carbon Monoxide

NASA Technical Reports Server (NTRS)

Mu, M.; Randerson, J. T.; vanderWerf, G. R.; Giglio, L.; Kasibhatla, P.; Morton, D.; Collatz, G. J.; DeFries, R. S.; Hyer, E. J.; Prins, E. M.;

Daily and Hourly Variability in Global Fire Emissions and Consequences for Atmospheric Model Predictions of Carbon Monoxide

NASA Technical Reports Server (NTRS)

Mu, M.; Randerson, J. T.; van der Werf, G. R.; Giglio, L.; Kasibhatla, P.; Morton, D.; Collatz, G. J.; DeFries, R. S.; Hyer, E. J.; Prins, E. M.;

Electron-excited energy dispersive x-ray spectrometry in the variable pressure scanning electron microscope (EDS/VPSEM): it's not microanalysis anymore!

NASA Astrophysics Data System (ADS)

Newbury, Dale E.; Ritchie, Nicholas W. M.

2015-10-01

X-ray spectra suffer significantly degraded spatial resolution when measured in the variable-pressure scanning electron microscope (VPSEM, chamber pressure 1 Pa to 2500 Pa) as compared to highvacuum SEM (operating pressure < 10 mPa). Depending on the gas path length, electrons that are scattered hundreds of micrometers outside the focused beam can contribute 90% or more of the measured spectrum. Monte Carlo electron trajectory simulation, available in NIST DTSA-II, models the gas scattering and simulates mixed composition targets, e.g., particle on substrate. The impact of gas scattering at the major (C > 0.1 mass fraction), minor (0.01 <= C <= 0.1), and trace (C < 0.01) constituent levels can be estimated. NIST DTSA-II for Java-platforms is available free at: http://www.cstl.nist.gov/div837/837.02/epq/dtsa2/index.html).

Composition measurement in substitutionally disordered materials by atomic resolution energy dispersive X-ray spectroscopy in scanning transmission electron microscopy.

PubMed

Chen, Z; Taplin, D J; Weyland, M; Allen, L J; Findlay, S D

2017-05-01

The increasing use of energy dispersive X-ray spectroscopy in atomic resolution scanning transmission electron microscopy invites the question of whether its success in precision composition determination at lower magnifications can be replicated in the atomic resolution regime. In this paper, we explore, through simulation, the prospects for composition measurement via the model system of Al x Ga 1-x As, discussing the approximations used in the modelling, the variability in the signal due to changes in configuration at constant composition, and the ability to distinguish between different compositions. Results are presented in such a way that the number of X-ray counts, and thus the expected variation due to counting statistics, can be gauged for a range of operating conditions. Copyright © 2016 Elsevier B.V. All rights reserved.

Investigating the impact of diurnal cycle of SST on the intraseasonal and climate variability

NASA Astrophysics Data System (ADS)

Tseng, W. L.; Hsu, H. H.; Chang, C. W. J.; Keenlyside, N. S.; Lan, Y. Y.; Tsuang, B. J.; Tu, C. Y.

2016-12-01

The diurnal cycle is a prominent feature of our climate system and the most familiar example of externally forced variability. Despite this it remains poorly simulated in state-of-the-art climate models. A particular problem is the diurnal cycle in sea surface temperature (SST), which is a key variable in air-sea heat flux exchange. In most models the diurnal cycle in SST is not well resolved, due to insufficient vertical resolution in the upper ocean mixed-layer and insufficiently frequent ocean-atmosphere coupling. Here, we coupled a 1-dimensional ocean model (SIT) to two atmospheric general circulation model (ECHAM5 and CAM5). In particular, we focus on improving the representations of the diurnal cycle in SST in a climate model, and investigate the role of the diurnal cycle in climate and intraseasonal variability.

How model and input uncertainty impact maize yield simulations in West Africa

NASA Astrophysics Data System (ADS)

Waha, Katharina; Huth, Neil; Carberry, Peter; Wang, Enli

2015-02-01

Crop models are common tools for simulating crop yields and crop production in studies on food security and global change. Various uncertainties however exist, not only in the model design and model parameters, but also and maybe even more important in soil, climate and management input data. We analyze the performance of the point-scale crop model APSIM and the global scale crop model LPJmL with different climate and soil conditions under different agricultural management in the low-input maize-growing areas of Burkina Faso, West Africa. We test the models’ response to different levels of input information from little to detailed information on soil, climate (1961-2000) and agricultural management and compare the models’ ability to represent the observed spatial (between locations) and temporal variability (between years) in crop yields. We found that the resolution of different soil, climate and management information influences the simulated crop yields in both models. However, the difference between models is larger than between input data and larger between simulations with different climate and management information than between simulations with different soil information. The observed spatial variability can be represented well from both models even with little information on soils and management but APSIM simulates a higher variation between single locations than LPJmL. The agreement of simulated and observed temporal variability is lower due to non-climatic factors e.g. investment in agricultural research and development between 1987 and 1991 in Burkina Faso which resulted in a doubling of maize yields. The findings of our study highlight the importance of scale and model choice and show that the most detailed input data does not necessarily improve model performance.

Influence of Leaf Area Index Prescriptions on Simulations of Heat, Moisture, and Carbon Fluxes

NASA Technical Reports Server (NTRS)

Kala, Jatin; Decker, Mark; Exbrayat, Jean-Francois; Pitman, Andy J.; Carouge, Claire; Evans, Jason P.; Abramowitz, Gab; Mocko, David

2013-01-01

Leaf-area index (LAI), the total one-sided surface area of leaf per ground surface area, is a key component of land surface models. We investigate the influence of differing, plausible LAI prescriptions on heat, moisture, and carbon fluxes simulated by the Community Atmosphere Biosphere Land Exchange (CABLEv1.4b) model over the Australian continent. A 15-member ensemble monthly LAI data-set is generated using the MODIS LAI product and gridded observations of temperature and precipitation. Offline simulations lasting 29 years (1980-2008) are carried out at 25 km resolution with the composite monthly means from the MODIS LAI product (control simulation) and compared with simulations using each of the 15-member ensemble monthly-varying LAI data-sets generated. The imposed changes in LAI did not strongly influence the sensible and latent fluxes but the carbon fluxes were more strongly affected. Croplands showed the largest sensitivity in gross primary production with differences ranging from -90 to 60 %. PFTs with high absolute LAI and low inter-annual variability, such as evergreen broadleaf trees, showed the least response to the different LAI prescriptions, whilst those with lower absolute LAI and higher inter-annual variability, such as croplands, were more sensitive. We show that reliance on a single LAI prescription may not accurately reflect the uncertainty in the simulation of the terrestrial carbon fluxes, especially for PFTs with high inter-annual variability. Our study highlights that the accurate representation of LAI in land surface models is key to the simulation of the terrestrial carbon cycle. Hence this will become critical in quantifying the uncertainty in future changes in primary production.

WRF added value to capture the spatio-temporal drought variability

NASA Astrophysics Data System (ADS)

García-Valdecasas Ojeda, Matilde; Quishpe-Vásquez, César; Raquel Gámiz-Fortis, Sonia; Castro-Díez, Yolanda; Jesús Esteban-Parra, María

2017-04-01

Regional Climate Models (RCM) has been widely used as a tool to perform high resolution climate fields in areas with high climate variability such as Spain. However, the outputs provided by downscaling techniques have many sources of uncertainty associated at different aspects. In this study, the ability of the Weather Research and Forecasting (WRF) model to capture drought conditions has been analyzed. The WRF simulation was carried out for a period that spanned from 1980 to 2010 over a domain centered in the Iberian Peninsula with a spatial resolution of 0.088°, and nested in the coarser EURO-CORDEX domain (0.44° spatial resolution). To investigate the spatiotemporal drought variability, the Standardized Precipitation Index (SPI) and the Standardized Precipitation Evapotranspiration Index (SPEI) has been computed at two different timescales: 3- and 12-months due to its suitability to study agricultural and hydrological droughts. The drought indices computed from WRF outputs were compared with those obtained from the observational (MOTEDAS and MOPREDAS) datasets. In order to assess the added value provided by downscaled fields, these indices were also computed from the ERA-Interim Re-Analysis database, which provides the lateral and boundary conditions of the WRF simulations. Results from this study indicate that WRF provides a noticeable benefit with respect to ERA-Interim for many regions in Spain in terms of drought indices, greater for SPI than for SPEI. The improvement offered by WRF depends on the region, index and timescale analyzed, being greater at longer timescales. These findings prove the reliability of the downscaled fields to detect drought events and, therefore, it is a remarkable source of knowledge for a suitable decision making related to water-resource management. Keywords: Drought, added value, Regional Climate Models, WRF, SPEI, SPI. Acknowledgements: This work has been financed by the projects P11-RNM-7941 (Junta de Andalucía-Spain) and CGL2013-48539-R (MINECO-Spain, FEDER).

Monsoon Variability in the Arabian Sea from Enhanced and Standard Horizontal Resolution Coupled Climate Models.

NASA Astrophysics Data System (ADS)

McClean, J.; Veneziani, C.; Maltrud, M. E.; Taylor, M.; Bader, D. C.; Branstetter, M. L.; Evans, K. J.; Mahajan, S.

2016-02-01

The circulation of the upper ocean in the Arabian Sea switches direction seasonally due to the change in direction of the prevailing winds associated with the Indian Monsoon. Predictability of the monsoon circulation, however, is uncertain due to incomplete understanding of the physical processes operating on the monsoon and other time scales, particularly interannual and intraseasonal. We use the Community Earth System Model (CESM) with enhanced horizontal resolution in each of its components relative to standard coupled climate model resolution, to better understand these time scale interactions. A standard resolution CESM counterpart is used to assess how horizontal resolution impacts the depiction of these processes. In the enhanced resolution case, 0.25° Community Atmosphere Model 5 (CAM5) is coupled to, among other components, the tripolar nominal 0.1° Parallel Ocean Program 2 (POP2). The fine resolution CESM simulation was run for 85 years; constant 1850 preindustrial forcing was used throughout the run, allowing us to isolate internal variability of the coupled system. Model parameters were adjusted ("tuned") to produce an acceptably small top of the atmosphere radiation imbalance. The reversal of the Somali Current (SC), the western boundary current off northeast Africa, has typically been associated with that of the monsoon. The SC reverses from southwestward in boreal winter to northeastward in summer; coastal upwelling is induced by the summer monsoonal winds. Recently it has been shown from new observations that the SC starts to reverse prior to the monsoon switch. Westward propagating Rossby waves have been implicated as responsible for the early SC reversal. We will discuss the sequencing of remote and local forcing on the timing of the spring inter-monsoonal switch in the direction of the SC and the appearance of the Great Whirl off the Oman Coast. Particularly, we consider how the Indian Ocean Dipole (IOD) acts to modify the seasonal strength and variability of the western boundary current system including upwelling. We look for a connection between interannual upwelling variability and that of rainfall off the west coast of India. As well, we examine changes due to the IOD in the upper ocean temperature and salinity structure along the Rossby wave propagation route in the Arabian Sea.

Evaluation and comparison of different RCMs simulations of the Mediterranean climate: a view on the impact of model resolution and Mediterranean sea coupling.

NASA Astrophysics Data System (ADS)

Panthou, Gérémy; Vrac, Mathieu; Drobinski, Philippe; Bastin, Sophie; Somot, Samuel; Li, Laurent

2015-04-01

As regularly stated by numerous authors, the Mediterranean climate is considered as one major climate 'hot spot'. At least, three reasons may explain this statement. First, this region is known for being regularly affected by extreme hydro-meteorological events (heavy precipitation and flash-floods during the autumn season; droughts and heat waves during spring and summer). Second, the vulnerability of populations in regard of these extreme events is expected to increase during the XXIst century (at least due to the projected population growth in this region). At last, Global Circulation Models project that this regional climate will be highly sensitive to climate change. Moreover, global warming is expected to intensify the hydrological cycle and thus to increase the frequency of extreme hydro-meteorological events. In order to propose adaptation strategies, the robust estimation of the future evolution of the Mediterranean climate and the associated extreme hydro-meteorological events (in terms of intensity/frequency) is of great relevance. However, these projections are characterized by large uncertainties. Many components of the simulation chain can explain these large uncertainties : (i) uncertainties concerning the emission scenario; (ii) climate model simulations suffer of parametrization errors and uncertainties concerning the initial state of the climate; and (iii) the additional uncertainties given by the (dynamical or statistical) downscaling techniques and the impact model. Narrowing (as fine as possible) these uncertainties is a major challenge of the actual climate research. One way for that is to reduce the uncertainties associated with each component. In this study, we are interested in evaluating the potential improvement of : (i) coupled RCM simulations (with the Mediterranean Sea) in comparison with atmosphere only (stand-alone) RCM simulations and (ii) RCM simulations at a finer resolution in comparison with larger resolution. For that, three different RCMs (WRF, ALADIN, LMDZ4) were run, forced by ERA-Interim reanalyses, within the MED-CORDEX experiment. For each RCM, different versions (coupled/stand-alone, high/low resolution) were realized. A large set of scores was developed and applied in order to evaluate the performances of these different RCMs simulations. These scores were applied for three variables (daily precipitation amount, mean daily air temperature and the dry spell lengths). A particular attention was given to the RCM capability to reproduce the seasonal and spatial pattern of extreme statistics. Results show that the differences between coupled and stand-alone RCMs are localized very near the Mediterranean sea and that the model resolution has a slight impact on the scores obtained. Globally, the main differences between the RCM simulations come from the RCM used. Keywords: Mediterranean climate, extreme hydro-meteorological events, RCM simulations, evaluation of climate simulations

Climate Downscaling over Nordeste, Brazil, Using the NCEP RSM97.

NASA Astrophysics Data System (ADS)

Sun, Liqiang; Ferran Moncunill, David; Li, Huilan; Divino Moura, Antonio; de Assis de Souza Filho, Francisco

2005-02-01

The NCEP Regional Spectral Model (RSM), with horizontal resolution of 60 km, was used to downscale the ECHAM4.5 AGCM (T42) simulations forced with observed SSTs over northeast Brazil. An ensemble of 10 runs for the period January-June 1971-2000 was used in this study. The RSM can resolve the spatial patterns of observed seasonal precipitation and capture the interannual variability of observed seasonal precipitation as well. The AGCM bias in displacement of the Atlantic ITCZ is partially corrected in the RSM. The RSM probability distribution function of seasonal precipitation anomalies is in better agreement with observations than that of the driving AGCM. Good potential prediction skills are demonstrated by the RSM in predicting the interannual variability of regional seasonal precipitation. The RSM can also capture the interannual variability of observed precipitation at intraseasonal time scales, such as precipitation intensity distribution and dry spells. A drought index and a flooding index were adopted to indicate the severity of drought and flooding conditions, and their interannual variability was reproduced by the RSM. The overall RSM performance in the downscaled climate of the ECHAM4.5 AGCM is satisfactory over Nordeste. The primary deficiency is a systematic dry bias for precipitation simulation.

Characterization of applied fields for ion mobility separations in traveling wave based structures for lossless ion manipulations (SLIM)

DOE PAGES

Hamid, Ahmed M.; Prabhakaran, Aneesh; Garimella, Sandilya V. B.; ...

2018-03-26

Ion mobility (IM) is rapidly gaining attention for the separation and analysis of biomolecules due to the ability to distinguish the shapes of ions. However, conventional constant electric field drift tube IM separations have limited resolving power, constrained by practical limitations on the path length and maximum applied voltage. The implementation of traveling waves (TW) in IM removes the latter limitation, allowing higher resolution to be achieved using extended path lengths. Both of these can be readily obtained in Structures for Lossless Ion Manipulations (SLIM), which are fabricated from arrays of electrodes patterned on two parallel surfaces where potentials aremore » applied to generate appropriate electric fields between the surfaces. Here we have investigated the relationship between the primary SLIM variables, such as electrode dimensions, inter-surface gap, and the applied TW voltages, that directly impact the fields experienced by ions. Ion trajectory simulations and theoretical calculations have been utilized to understand the dependence of SLIM geometry and effective electric fields on IM resolution. The variables explored impact both ion confinement and the observed IM resolution using SLIM modules.« less

Characterization of applied fields for ion mobility separations in traveling wave based structures for lossless ion manipulations (SLIM)

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

Hamid, Ahmed M.; Prabhakaran, Aneesh; Garimella, Sandilya V. B.

Ion mobility (IM) is rapidly gaining attention for the separation and analysis of biomolecules due to the ability to distinguish the shapes of ions. However, conventional constant electric field drift tube IM separations have limited resolving power, constrained by practical limitations on the path length and maximum applied voltage. The implementation of traveling waves (TW) in IM removes the latter limitation, allowing higher resolution to be achieved using extended path lengths. Both of these can be readily obtained in Structures for Lossless Ion Manipulations (SLIM), which are fabricated from arrays of electrodes patterned on two parallel surfaces where potentials aremore » applied to generate appropriate electric fields between the surfaces. Here we have investigated the relationship between the primary SLIM variables, such as electrode dimensions, inter-surface gap, and the applied TW voltages, that directly impact the fields experienced by ions. Ion trajectory simulations and theoretical calculations have been utilized to understand the dependence of SLIM geometry and effective electric fields on IM resolution. The variables explored impact both ion confinement and the observed IM resolution using SLIM modules.« less

Evaluation of the Surface Representation of the Greenland Ice Sheet in a General Circulation Model

NASA Technical Reports Server (NTRS)

Cullather, Richard I.; Nowicki, Sophie M. J.; Zhao, Bin; Suarez, Max J.

2014-01-01

Simulated surface conditions of the Goddard Earth Observing System model, version 5 (GEOS 5) atmospheric general circulation model (AGCM) are examined for the contemporary Greenland Ice Sheet (GrIS). A surface parameterization that explicitly models surface processes including snow compaction, meltwater percolation and refreezing, and surface albedo is found to remedy an erroneous deficit in the annual net surface energy flux and provide an adequate representation of surface mass balance (SMB) in an evaluation using simulations at two spatial resolutions. The simulated 1980-2008 GrIS SMB average is 24.7+/-4.5 cm yr(- 1) water-equivalent (w.e.) at.5 degree model grid spacing, and 18.2+/-3.3 cm yr(- 1) w.e. for 2 degree grid spacing. The spatial variability and seasonal cycle of the simulation compare favorably to recent studies using regional climate models, while results from 2 degree integrations reproduce the primary features of the SMB field. In comparison to historical glaciological observations, the coarser resolution model overestimates accumulation in the southern areas of the GrIS, while the overall SMB is underestimated. These changes relate to the sensitivity of accumulation and melt to the resolution of topography. The GEOS-5 SMB fields contrast with available corresponding atmospheric models simulations from the Coupled Model Intercomparison Project (CMIP5). It is found that only a few of the CMIP5 AGCMs examined provide significant summertime runoff, a dominant feature of the GrIS seasonal cycle. This is a condition that will need to be remedied if potential contributions to future eustatic change from polar ice sheets are to be examined with GCMs.

Impact of large-scale circulation changes in the North Atlantic sector on the current and future Mediterranean winter hydroclimate

NASA Astrophysics Data System (ADS)

Barcikowska, Monika J.; Kapnick, Sarah B.; Feser, Frauke

2018-03-01

The Mediterranean region, located in the transition zone between the dry subtropical and wet European mid-latitude climate, is very sensitive to changes in the global mean climate state. Projecting future changes of the Mediterranean hydroclimate under global warming therefore requires dynamic climate models to reproduce the main mechanisms controlling regional hydroclimate with sufficiently high resolution to realistically simulate climate extremes. To assess future winter precipitation changes in the Mediterranean region we use the Geophysical Fluid Dynamics Laboratory high-resolution general circulation model for control simulations with pre-industrial greenhouse gas and aerosol concentrations which are compared to future scenario simulations. Here we show that the coupled model is able to reliably simulate the large-scale winter circulation, including the North Atlantic Oscillation and Eastern Atlantic patterns of variability, and its associated impacts on the mean Mediterranean hydroclimate. The model also realistically reproduces the regional features of daily heavy rainfall, which are absent in lower-resolution simulations. A five-member future projection ensemble, which assumes comparatively high greenhouse gas emissions (RCP8.5) until 2100, indicates a strong winter decline in Mediterranean precipitation for the coming decades. Consistent with dynamical and thermodynamical consequences of a warming atmosphere, derived changes feature a distinct bipolar behavior, i.e. wetting in the north—and drying in the south. Changes are most pronounced over the northwest African coast, where the projected winter precipitation decline reaches 40% of present values. Despite a decrease in mean precipitation, heavy rainfall indices show drastic increases across most of the Mediterranean, except the North African coast, which is under the strong influence of the cold Canary Current.

Observations of the sub-inertial, near-surface East India Coastal Current

NASA Astrophysics Data System (ADS)

Mukhopadhyay, S.; Shankar, D.; Aparna, S. G.; Mukherjee, A.

2017-09-01

We present surface current measurements made using two pairs of HF (high-frequency) radars deployed on the east coast of India. The radar data, used in conjunction with data from acoustic Doppler current profiler (ADCP) measurements on the shelf and slope off the Indian east coast, confirm that the East India Coastal Current (EICC) flows poleward as a deep current during February-March. During the summer monsoon, when the EICC flows poleward, and October-December, when the EICC flows equatorward, the current is shallow (< 40 m deep), except towards the northern end of the coast. Data from Argo floats confirm a shallow mixed layer that leads to a strong vertical shear off southeast India during October-December. A consequence of the strong stratification is that the upward propagation of phase evident in the ADCP data does not always extend to the surface. Even within the seasons, however, the poleward and equatorward flows show variability at periods of the order of 20-45 days, implying that the EICC direction is the same over the top ∼100 m for short durations. The high spatial resolution of the HF radar data brings out features at scales shorter than those resolved by the altimeter and the high temporal resolution captures short bursts that are not captured in satellite-derived estimates of surface currents. The radar data show that the EICC, which is a boundary current, leaves a strong imprint on the current at the coast. Since the EICC is known to be affected significantly by remote forcing, this correlation between the boundary and nearshore current implies the need to use large-domain models even for simulating the nearshore current. Comparison with a simulation by a state-of-the-art Ocean General Circulation Model, run at a resolution of 0.1 ° × 0.1 ° , shows that the model is able to simulate only the low-frequency variability.

Influence of spatial resolution on precipitation simulations for the central Andes Mountains

NASA Astrophysics Data System (ADS)

Trachte, Katja; Bendix, Jörg

2013-04-01

The climate of South America is highly influenced by the north-south oriented Andes Mountains. Their complex structure causes modifications of large-scale atmospheric circulations resulting in various mesoscale phenomena as well as a high variability in the local conditions. Due to their height and length the terrain generates distinctly climate conditions between the western and the eastern slopes. While in the tropical regions along the western flanks the conditions are cold and arid, the eastern slopes are dominated by warm-moist and rainy air coming from the Amazon basin. Below 35° S the situation reverses with rather semiarid conditions in the eastern part and temperate rainy climate along southern Chile. Generally, global circulation models (GCMs) describe the state of the global climate and its changes, but are disabled to capture regional or even local features due to their coarse resolution. This is particularly true in heterogeneous regions such as the Andes Mountains, where local driving features, e. g. local circulation systems, highly varies on small scales and thus, lead to a high variability of rainfall distributions. An appropriate technique to overcome this problem and to gain regional and local scale rainfall information is the dynamical downscaling of the global data using a regional climate model (RCM). The poster presents results of the evaluation of the performance of the Weather Research and Forecasting (WRF) model over South America with special focus on the central Andes Mountains of Ecuador. A sensitivity study regarding the cumulus parametrization, microphysics, boundary layer processes and the radiation budget is conducted. With 17 simulations consisting of 16 parametrization scheme combinations and 1 default run a suitable model set-up for climate research in this region is supposed to be evaluated. The simulations were conducted in a two-way nested mode i) to examine the best physics scheme combination for the target and ii) to analyze the impact of spatial resolution and thus, the representation of the terrain on the result.

Seasonal and Interannual Variability of the Arctic Sea Ice: A Comparison between AO-FVCOM and Observations

NASA Astrophysics Data System (ADS)

Zhang, Y.; Chen, C.; Beardsley, R. C.; Gao, G.; Qi, J.; Lin, H.

2016-02-01

A high-resolution (up to 2 km), unstructured-grid, fully ice-sea coupled Arctic Ocean Finite-Volume Community Ocean Model (AO-FVCOM) was used to simulate the Arctic sea ice over the period 1978-2014. Good agreements were found between simulated and observed sea ice extent, concentration, drift velocity and thickness, indicating that the AO-FVCOM captured not only the seasonal and interannual variability but also the spatial distribution of the sea ice in the Arctic in the past 37 years. Compared with other six Arctic Ocean models (ECCO2, GSFC, INMOM, ORCA, NAME and UW), the AO-FVCOM-simulated ice thickness showed a higher correlation coefficient and a smaller difference with observations. An effort was also made to examine the physical processes attributing to the model-produced bias in the sea ice simulation. The error in the direction of the ice drift velocity was sensitive to the wind turning angle; smaller when the wind was stronger, but larger when the wind was weaker. This error could lead to the bias in the near-surface current in the fully or partially ice-covered zone where the ice-sea interfacial stress was a major driving force.

Determining wave direction using curvature parameters.

PubMed

de Queiroz, Eduardo Vitarelli; de Carvalho, João Luiz Baptista

2016-01-01

The curvature of the sea wave was tested as a parameter for estimating wave direction in the search for better results in estimates of wave direction in shallow waters, where waves of different sizes, frequencies and directions intersect and it is difficult to characterize. We used numerical simulations of the sea surface to determine wave direction calculated from the curvature of the waves. Using 1000 numerical simulations, the statistical variability of the wave direction was determined. The results showed good performance by the curvature parameter for estimating wave direction. Accuracy in the estimates was improved by including wave slope parameters in addition to curvature. The results indicate that the curvature is a promising technique to estimate wave directions.•In this study, the accuracy and precision of curvature parameters to measure wave direction are analyzed using a model simulation that generates 1000 wave records with directional resolution.•The model allows the simultaneous simulation of time-series wave properties such as sea surface elevation, slope and curvature and they were used to analyze the variability of estimated directions.•The simultaneous acquisition of slope and curvature parameters can contribute to estimates wave direction, thus increasing accuracy and precision of results.

Role of Updraft Velocity in Temporal Variability of Global Cloud Hydrometeor Number

NASA Technical Reports Server (NTRS)

Sullivan, Sylvia C.; Lee, Dong Min; Oreopoulos, Lazaros; Nenes, Athanasios

2016-01-01

Understanding how dynamical and aerosol inputs affect the temporal variability of hydrometeor formation in climate models will help to explain sources of model diversity in cloud forcing, to provide robust comparisons with data, and, ultimately, to reduce the uncertainty in estimates of the aerosol indirect effect. This variability attribution can be done at various spatial and temporal resolutions with metrics derived from online adjoint sensitivities of droplet and crystal number to relevant inputs. Such metrics are defined and calculated from simulations using the NASA Goddard Earth Observing System Model, Version 5 (GEOS-5) and the National Center for Atmospheric Research Community Atmosphere Model Version 5.1 (CAM5.1). Input updraft velocity fluctuations can explain as much as 48% of temporal variability in output ice crystal number and 61% in droplet number in GEOS-5 and up to 89% of temporal variability in output ice crystal number in CAM5.1. In both models, this vertical velocity attribution depends strongly on altitude. Despite its importance for hydrometeor formation, simulated vertical velocity distributions are rarely evaluated against observations due to the sparsity of relevant data. Coordinated effort by the atmospheric community to develop more consistent, observationally based updraft treatments will help to close this knowledge gap.

Role of updraft velocity in temporal variability of global cloud hydrometeor number

DOE PAGES

Sullivan, Sylvia C.; Lee, Dongmin; Oreopoulos, Lazaros; ...

2016-05-16

Understanding how dynamical and aerosol inputs affect the temporal variability of hydrometeor formation in climate models will help to explain sources of model diversity in cloud forcing, to provide robust comparisons with data, and, ultimately, to reduce the uncertainty in estimates of the aerosol indirect effect. This variability attribution can be done at various spatial and temporal resolutions with metrics derived from online adjoint sensitivities of droplet and crystal number to relevant inputs. Such metrics are defined and calculated from simulations using the NASA Goddard Earth Observing System Model, Version 5 (GEOS-5) and the National Center for Atmospheric Research Communitymore » Atmosphere Model Version 5.1 (CAM5.1). Input updraft velocity fluctuations can explain as much as 48% of temporal variability in output ice crystal number and 61% in droplet number in GEOS-5 and up to 89% of temporal variability in output ice crystal number in CAM5.1. In both models, this vertical velocity attribution depends strongly on altitude. Despite its importance for hydrometeor formation, simulated vertical velocity distributions are rarely evaluated against observations due to the sparsity of relevant data. Finally, coordinated effort by the atmospheric community to develop more consistent, observationally based updraft treatments will help to close this knowledge gap.« less

Role of updraft velocity in temporal variability of global cloud hydrometeor number

NASA Astrophysics Data System (ADS)

Sullivan, Sylvia C.; Lee, Dongmin; Oreopoulos, Lazaros; Nenes, Athanasios

2016-05-01

Understanding how dynamical and aerosol inputs affect the temporal variability of hydrometeor formation in climate models will help to explain sources of model diversity in cloud forcing, to provide robust comparisons with data, and, ultimately, to reduce the uncertainty in estimates of the aerosol indirect effect. This variability attribution can be done at various spatial and temporal resolutions with metrics derived from online adjoint sensitivities of droplet and crystal number to relevant inputs. Such metrics are defined and calculated from simulations using the NASA Goddard Earth Observing System Model, Version 5 (GEOS-5) and the National Center for Atmospheric Research Community Atmosphere Model Version 5.1 (CAM5.1). Input updraft velocity fluctuations can explain as much as 48% of temporal variability in output ice crystal number and 61% in droplet number in GEOS-5 and up to 89% of temporal variability in output ice crystal number in CAM5.1. In both models, this vertical velocity attribution depends strongly on altitude. Despite its importance for hydrometeor formation, simulated vertical velocity distributions are rarely evaluated against observations due to the sparsity of relevant data. Coordinated effort by the atmospheric community to develop more consistent, observationally based updraft treatments will help to close this knowledge gap.

Measurement and modeling of moist processes

NASA Technical Reports Server (NTRS)

Cotton, William; Starr, David; Mitchell, Kenneth; Fleming, Rex; Koch, Steve; Smith, Steve; Mailhot, Jocelyn; Perkey, Don; Tripoli, Greg

1993-01-01

The keynote talk summarized five years of work simulating observed mesoscale convective systems with the RAMS (Regional Atmospheric Modeling System) model. Excellent results are obtained when simulating squall line or other convective systems that are strongly forced by fronts or other lifting mechanisms. Less highly forced systems are difficult to model. The next topic in this colloquium was measurement of water vapor and other constituents of the hydrologic cycle. Impressive accuracy was shown measuring water vapor with both the airborne DIAL (Differential Absorption Lidar) system and the the ground-based Raman Lidar. NMC's plans for initializing land water hydrology in mesoscale models was presented before water vapor measurement concepts for GCIP were discussed. The subject of using satellite data to provide mesoscale moisture and wind analyses was next. Recent activities in modeling of moist processes in mesoscale systems was reported on. These modeling activities at the Canadian Atmospheric Environment Service (AES) used a hydrostatic, variable-resolution grid model. Next the spatial resolution effects of moisture budgets was discussed; in particular, the effects of temporal resolution on heat and moisture budgets for cumulus parameterization. The conclusion of this colloquium was on modeling scale interaction processes.

On the feasibility of monitoring carbon monoxide in the lower troposphere from a constellation of Northern Hemisphere geostationary satellites. (Part 1)

NASA Astrophysics Data System (ADS)

Barré, Jérôme; Edwards, David; Worden, Helen; Da Silva, Arlindo; Lahoz, William

2015-07-01

By the end of the current decade, there are plans to deploy several geostationary Earth orbit (GEO) satellite missions for atmospheric composition over North America, East Asia and Europe with additional missions proposed. Together, these present the possibility of a constellation of geostationary platforms to achieve continuous time-resolved high-density observations over continental domains for mapping pollutant sources and variability at diurnal and local scales. In this paper, we use a novel approach to sample a very high global resolution model (GEOS-5 at 7 km horizontal resolution) to produce a dataset of synthetic carbon monoxide pollution observations representative of those potentially obtainable from a GEO satellite constellation with predicted measurement sensitivities based on current remote sensing capabilities. Part 1 of this study focuses on the production of simulated synthetic measurements for air quality OSSEs (Observing System Simulation Experiments). We simulate carbon monoxide nadir retrievals using a technique that provides realistic measurements with very low computational cost. We discuss the sampling methodology: the projection of footprints and areas of regard for geostationary geometries over each of the North America, East Asia and Europe regions; the regression method to simulate measurement sensitivity; and the measurement error simulation. A detailed analysis of the simulated observation sensitivity is performed, and limitations of the method are discussed. We also describe impacts from clouds, showing that the efficiency of an instrument making atmospheric composition measurements on a geostationary platform is dependent on the dominant weather regime over a given region and the pixel size resolution. These results demonstrate the viability of the ;instrument simulator; step for an OSSE to assess the performance of a constellation of geostationary satellites for air quality measurements. We describe the OSSE results in a follow up paper (Part 2 of this study).

High-frequency and meso-scale winter sea-ice variability in the Southern Ocean in a high-resolution global ocean model

NASA Astrophysics Data System (ADS)

Stössel, Achim; von Storch, Jin-Song; Notz, Dirk; Haak, Helmuth; Gerdes, Rüdiger

2018-03-01

This study is on high-frequency temporal variability (HFV) and meso-scale spatial variability (MSV) of winter sea-ice drift in the Southern Ocean simulated with a global high-resolution (0.1°) sea ice-ocean model. Hourly model output is used to distinguish MSV characteristics via patterns of mean kinetic energy (MKE) and turbulent kinetic energy (TKE) of ice drift, surface currents, and wind stress, and HFV characteristics via time series of raw variables and correlations. We find that (1) along the ice edge, the MSV of ice drift coincides with that of surface currents, in particular such due to ocean eddies; (2) along the coast, the MKE of ice drift is substantially larger than its TKE and coincides with the MKE of wind stress; (3) in the interior of the ice pack, the TKE of ice drift is larger than its MKE, mostly following the TKE pattern of wind stress; (4) the HFV of ice drift is dominated by weather events, and, in the absence of tidal currents, locally and to a much smaller degree by inertial oscillations; (5) along the ice edge, the curl of the ice drift is highly correlated with that of surface currents, mostly reflecting the impact of ocean eddies. Where ocean eddies occur and the ice is relatively thin, ice velocity is characterized by enhanced relative vorticity, largely matching that of surface currents. Along the ice edge, ocean eddies produce distinct ice filaments, the realism of which is largely confirmed by high-resolution satellite passive-microwave data.

High resolution modeling in urban hydrology: comparison between two modeling approaches and their sensitivity to high rainfall variability

NASA Astrophysics Data System (ADS)

Ichiba, Abdellah; Gires, Auguste; Tchiguirinskaia, Ioulia; Bompard, Philippe; Schertzer, Daniel

2015-04-01

Urban water management is becoming increasingly complex, due to the rapid increase of impervious areas, and the potential effects of climate change. The large amount of water generated in a very short period of time and the limited capacity of sewer systems increase the vulnerability of urban environments to flooding risk and make it necessary to implement specific devices in order to handle the volume of water generated. This complex situation in urban environments makes the use of hydrological models as well as the implementation of more accurate and reliable tools for flow and rainfall measurements essential for a good pluvial network management, the use of decision support tools such as real-time radar forecasting system, the developpement of general public communication and warning systems, and the implementation of management strategy participate on limiting the flood damages. The very high spatial variability characteristic of urban environments makes it necessary to integrate the variability of physical properties and precipitation at fine scales in modeling processes, suggesting a high resolution modeling approach. In this paper we suggest a comparison between two modeling approaches and their sensitivity to small-scale rainfall variability on a 2.15 km2 urban area located in the County of Val-de-Marne (South-East of Paris, France). The first model used in this study is CANOE, which is a semi-distributed model widely used in France by practitioners for urban hydrology and urban water management. Two configurations of this model are be used in this study, the first one integrate 9 sub-catchments with sizes range from (1ha to 76ha), in the second configuration, the spatial resolution of this model has been improved with 45 sub-catchments with sizes range from (1ha to 14ha), the aim is to see how the semi-distributed model resolution affects it sensitivity to rainfall variability. The second model is Multi-Hydro fully distributed model developed at the Ecole des Ponts ParisTech. It is an interacting core between open source software packages, each of them representing a portion of the water cycle in urban environment. Multi-Hydro has been set up at two resolutions, 10m and 5m. The validation of these two models is performed using 5 rainfall events that occurred between 2010 and 2013. Radar data comes from the Météo-France radar mosaic and the resolution is 1 km in space and 5 min in time. Raingauge and flow measurements data comes from the General Council of Val-de-Marne County. In this validation part, the hydrological responses given by two models and the different configurations are compared to flow measurements. It appears that CANOE gives better results than Multi-Hydro model, especially when using raingauge data. For some events, we noticed that model responses given when using raingauge and radar data are different, suggesting a sign of sensitivity to the spatial variability of rainfall. 10 high-resolution rainfall events are used in the second part to study the sensitivity of each modeling approach to high rainfall variability. Radar data was available at four spatial resolutions (100, 200, 500 and 1000m) and two temporal resolutions (1min and 5min), for each event, two rainfall directions (parallel and perpendicular) are used, meaning that 16 hydrological responses are simulated for each event and the variability within it analyzed. First results suggest that the fully distributed model is more sensitive to high rainfall variability than the semi-distributed one, the increase of both hydrological model spatial resolution improves their sensitivity to rainfall variability. This study highlights some technical challenges facing the high-resolution modeling, especially the difficulty to obtain reliable input data at an acceptable resolution and also the high computation time noticed particularly for the semi-distributed model making it difficult to use it in real time. The authors greatly acknowledge partial financial support from the project RainGain (http://www.raingain.eu) of the EU Interreg program.

Intercomparison of Downscaling Methods on Hydrological Impact for Earth System Model of NE United States

NASA Astrophysics Data System (ADS)

Yang, P.; Fekete, B. M.; Rosenzweig, B.; Lengyel, F.; Vorosmarty, C. J.

2012-12-01

Atmospheric dynamics are essential inputs to Regional-scale Earth System Models (RESMs). Variables including surface air temperature, total precipitation, solar radiation, wind speed and humidity must be downscaled from coarse-resolution, global General Circulation Models (GCMs) to the high temporal and spatial resolution required for regional modeling. However, this downscaling procedure can be challenging due to the need to correct for bias from the GCM and to capture the spatiotemporal heterogeneity of the regional dynamics. In this study, the results obtained using several downscaling techniques and observational datasets were compared for a RESM of the Northeast Corridor of the United States. Previous efforts have enhanced GCM model outputs through bias correction using novel techniques. For example, the Climate Impact Research at Potsdam Institute developed a series of bias-corrected GCMs towards the next generation climate change scenarios (Schiermeier, 2012; Moss et al., 2010). Techniques to better represent the heterogeneity of climate variables have also been improved using statistical approaches (Maurer, 2008; Abatzoglou, 2011). For this study, four downscaling approaches to transform bias-corrected HADGEM2-ES Model output (daily at .5 x .5 degree) to the 3'*3'(longitude*latitude) daily and monthly resolution required for the Northeast RESM were compared: 1) Bilinear Interpolation, 2) Daily bias-corrected spatial downscaling (D-BCSD) with Gridded Meteorological Datasets (developed by Abazoglou 2011), 3) Monthly bias-corrected spatial disaggregation (M-BCSD) with CRU(Climate Research Unit) and 4) Dynamic Downscaling based on Weather Research and Forecast (WRF) model. Spatio-temporal analysis of the variability in precipitation was conducted over the study domain. Validation of the variables of different downscaling methods against observational datasets was carried out for assessment of the downscaled climate model outputs. The effects of using the different approaches to downscale atmospheric variables (specifically air temperature and precipitation) for use as inputs to the Water Balance Model (WBMPlus, Vorosmarty et al., 1998;Wisser et al., 2008) for simulation of daily discharge and monthly stream flow in the Northeast US for a 100-year period in the 21st century were also assessed. Statistical techniques especially monthly bias-corrected spatial disaggregation (M-BCSD) showed potential advantage among other methods for the daily discharge and monthly stream flow simulation. However, Dynamic Downscaling will provide important complements to the statistical approaches tested.

Diagnostic accuracy of cone-beam computed tomography scans with high- and low-resolution modes for the detection of root perforations.

PubMed

Shokri, Abbas; Eskandarloo, Amir; Norouzi, Marouf; Poorolajal, Jalal; Majidi, Gelareh; Aliyaly, Alireza

2018-03-01

This study compared the diagnostic accuracy of cone-beam computed tomography (CBCT) scans obtained with 2 CBCT systems with high- and low-resolution modes for the detection of root perforations in endodontically treated mandibular molars. The root canals of 72 mandibular molars were cleaned and shaped. Perforations measuring 0.2, 0.3, and 0.4 mm in diameter were created at the furcation area of 48 roots, simulating strip perforations, or on the external surfaces of 48 roots, simulating root perforations. Forty-eight roots remained intact (control group). The roots were filled using gutta-percha (Gapadent, Tianjin, China) and AH26 sealer (Dentsply Maillefer, Ballaigues, Switzerland). The CBCT scans were obtained using the NewTom 3G (QR srl, Verona, Italy) and Cranex 3D (Soredex, Helsinki, Finland) CBCT systems in high- and low-resolution modes, and were evaluated by 2 observers. The chi-square test was used to assess the nominal variables. In strip perforations, the accuracies of low- and high-resolution modes were 75% and 83% for NewTom 3G and 67% and 69% for Cranex 3D. In root perforations, the accuracies of low- and high-resolution modes were 79% and 83% for NewTom 3G and was 56% and 73% for Cranex 3D. The accuracy of the 2 CBCT systems was different for the detection of strip and root perforations. The Cranex 3D had non-significantly higher accuracy than the NewTom 3G. In both scanners, the high-resolution mode yielded significantly higher accuracy than the low-resolution mode. The diagnostic accuracy of CBCT scans was not affected by the perforation diameter.

Water-vapour variability within a convective boundary-layer assessed by large-eddy simulations and IHOP_2002 observations

NASA Astrophysics Data System (ADS)

Couvreux, F.; Guichard, F.; Redelsperger, J. L.; Kiemle, C.; Masson, V.; Lafore, J. P.; Flamant, C.

2005-10-01

This study presents a comprehensive analysis of the variability of water vapour in a growing convective boundary-layer (CBL) over land, highlighting the complex links between advection, convective activity and moisture heterogeneity in the boundary layer. A Large-eddy Simulation (LES) is designed, based on observations, and validated, using an independent data-set collected during the International H2O Project (IHOP 2002) fieldexperiment. Ample information about the moisture distribution in space and time, as well as other important CBL parameters are acquired by mesonet stations, balloon soundings, instruments on-board two aircraft and the DLR airborne water-vapour differential-absorption lidar. Because it can deliver two-dimensional cross-sections at high spatial resolution (140 m horizontal, 200 m vertical), the airborne lidar offers valuable insights of small-scale moisture-variability throughout the CBL. The LES is able to reproduce the development of the CBL in the morning and early afternoon, as assessed by comparisons of simulated mean profiles of key meteorological variables with sounding data. Simulated profiles of the variance of water-vapour mixing-ratio were found to be in good agreement with the lidar-derived counterparts. Finally, probability-density functions of potential temperature, vertical velocity and water-vapour mixing-ratio calculated from the LES show great consistency with those derived from aircraft in situ measurements in the middle of the CBL. Downdraughts entrained from above the CBL are governing the scale of moisture variability. Characteristic length-scales are found to be larger for water-vapour mixing-ratio than for temperature.The observed water-vapour variability exhibits contributions from different scales. The influence of the mesoscale (larger than LES domain size, i.e. 10 km) on the smaller-scale variability is assessed using LES and observations. The small-scale variability of water vapour is found to be important and to be driven by the dynamics of the CBL. Both lidar observations and LES evidence that dry downdraughts entrained from above the CBL are governing the scale of moisture variability. Characteristic length-scales are found to be larger for water-vapour mixing-ratio than for temperature and vertical velocity. In particular, intrusions of drier free-troposphere air from above the growing CBL impose a marked negative skewness on the water-vapour distribution within it, both as observed and in the simulation.

Hydrological characterization of Guadalquivir River Basin for the period 1980-2010 using VIC model

NASA Astrophysics Data System (ADS)

García-Valdecasas-Ojeda, Matilde; de Franciscis, Sebastiano; Raquel Gámiz-Fortis, Sonia; Castro-Díez, Yolanda; Jesús Esteban-Parra, María

2017-04-01

This study analyzes the changes of soil moisture and real evapotranspiration (ETR), during the last 30 years, in the Guadalquivir River Basin, located in the south of the Iberian Peninsula. Soil moisture content is related with the different components of the real evaporation, it is a relevant factor when analyzing the intensity of droughts and heat waves, and particularly, for the impact study of the climate change. The soil moisture and real evapotranspiration data consist of simulations obtained by using the Variable Infiltration Capacity (VIC) hydrological model. This is a large-scale hydrologic model and allows the estimations of different variables in the hydrological system of a basin. Land surface is modeled as a grid of large and uniform cells with sub-grid heterogeneity (e.g. land cover), while water influx is local, only depending from the interaction between grid cell and local atmosphere environment. Observational data of temperature and precipitation from Spain02 dataset have been used as input variables for VIC model. Additionally, estimates of actual evapotranspiration and soil moisture are also analyzed using temperature, precipitation, wind, humidity and radiation as input variables for VIC. These variables are obtained from a dynamical downscaling from ERA-Interim data by the Weather Research and Forecasting (WRF) model. The simulations have a spatial resolution about 9 km and the analysis is done on a seasonal time-scale. Preliminary results show that ETR presents very low values for autumn from WRF simulations compared with VIC simulations. Only significant positive trends are found during autumn for the western part of the basin for the ETR obtained with VIC model, meanwhile no significant trends are found for the ETR WRF simulations. Keywords: Soil moisture, Real evapotranspiration, Guadalquivir Basin, trends, VIC, WRF. Acknowledgements: This work has been financed by the projects P11-RNM-7941 (Junta de Andalucía-Spain) and CGL2013-48539-R (MINECO-Spain, FEDER).

Application of WRF/Chem-MADRID and WRF/Polyphemus in Europe - Part 1: Model description and evaluation of meteorological predictions

NASA Astrophysics Data System (ADS)

Zhang, Y.; Sartelet, K.; Wu, S.-Y.; Seigneur, C.

2013-02-01

Comprehensive model evaluation and comparison of two 3-D air quality modeling systems (i.e. the Weather Research and Forecast model (WRF)/Polyphemus and WRF with chemistry and the Model of Aerosol Dynamics, Reaction, Ionization, and Dissolution (MADRID) (WRF/Chem-MADRID) are conducted over western Europe. Part 1 describes the background information for the model comparison and simulation design, as well as the application of WRF for January and July 2001 over triple-nested domains in western Europe at three horizontal grid resolutions: 0.5°, 0.125°, and 0.025°. Six simulated meteorological variables (i.e. temperature at 2 m (T2), specific humidity at 2 m (Q2), relative humidity at 2 m (RH2), wind speed at 10 m (WS10), wind direction at 10 m (WD10), and precipitation (Precip)) are evaluated using available observations in terms of spatial distribution, domainwide daily and site-specific hourly variations, and domainwide performance statistics. WRF demonstrates its capability in capturing diurnal/seasonal variations and spatial gradients of major meteorological variables. While the domainwide performance of T2, Q2, RH2, and WD10 at all three grid resolutions is satisfactory overall, large positive or negative biases occur in WS10 and Precip even at 0.025°. In addition, discrepancies between simulations and observations exist in T2, Q2, WS10, and Precip at mountain/high altitude sites and large urban center sites in both months, in particular, during snow events or thunderstorms. These results indicate the model's difficulty in capturing meteorological variables in complex terrain and subgrid-scale meteorological phenomena, due to inaccuracies in model initialization parameterization (e.g. lack of soil temperature and moisture nudging), limitations in the physical parameterizations of the planetary boundary layer (e.g. cloud microphysics, cumulus parameterizations, and ice nucleation treatments) as well as limitations in surface heat and moisture budget parameterizations (e.g. snow-related processes, subgrid-scale surface roughness elements, and urban canopy/heat island treatments and CO2 domes). While the use of finer grid resolutions of 0.125° and 0.025° shows some improvement for WS10, Precip, and some mesoscale events (e.g. strong forced convection and heavy precipitation), it does not significantly improve the overall statistical performance for all meteorological variables except for Precip. These results indicate a need to further improve the model representations of the above parameterizations at all scales.

Inferential consequences of modeling rather than measuring snow accumulation in studies of animal ecology

USGS Publications Warehouse

Cross, Paul C.; Klaver, Robert W.; Brennan, Angela; Creel, Scott; Beckmann, Jon P.; Higgs, Megan D.; Scurlock, Brandon M.

2013-01-01

Abstract. It is increasingly common for studies of animal ecology to use model-based predictions of environmental variables as explanatory or predictor variables, even though model prediction uncertainty is typically unknown. To demonstrate the potential for misleading inferences when model predictions with error are used in place of direct measurements, we compared snow water equivalent (SWE) and snow depth as predicted by the Snow Data Assimilation System (SNODAS) to field measurements of SWE and snow depth. We examined locations on elk (Cervus canadensis) winter ranges in western Wyoming, because modeled data such as SNODAS output are often used for inferences on elk ecology. Overall, SNODAS predictions tended to overestimate field measurements, prediction uncertainty was high, and the difference between SNODAS predictions and field measurements was greater in snow shadows for both snow variables compared to non-snow shadow areas. We used a simple simulation of snow effects on the probability of an elk being killed by a predator to show that, if SNODAS prediction uncertainty was ignored, we might have mistakenly concluded that SWE was not an important factor in where elk were killed in predatory attacks during the winter. In this simulation, we were interested in the effects of snow at finer scales (2) than the resolution of SNODAS. If bias were to decrease when SNODAS predictions are averaged over coarser scales, SNODAS would be applicable to population-level ecology studies. In our study, however, averaging predictions over moderate to broad spatial scales (9–2200 km2) did not reduce the differences between SNODAS predictions and field measurements. This study highlights the need to carefully evaluate two issues when using model output as an explanatory variable in subsequent analysis: (1) the model’s resolution relative to the scale of the ecological question of interest and (2) the implications of prediction uncertainty on inferences when using model predictions as explanatory or predictor variables.

High resolution modeling of reservoir storage and extent dynamics at the continental scale

NASA Astrophysics Data System (ADS)

Shin, S.; Pokhrel, Y. N.

2017-12-01

Over the past decade, significant progress has been made in developing reservoir schemes in large scale hydrological models to better simulate hydrological fluxes and storages in highly managed river basins. These schemes have been successfully used to study the impact of reservoir operation on global river basins. However, improvements in the existing schemes are needed for hydrological fluxes and storages, especially at the spatial resolution to be used in hyper-resolution hydrological modeling. In this study, we developed a reservoir routing scheme with explicit representation of reservoir storage and extent at the grid scale of 5km or less. Instead of setting reservoir area to a fixed value or diagnosing it using the area-storage equation, which is a commonly used approach in the existing reservoir schemes, we explicitly simulate the inundated storage and area for all grid cells that are within the reservoir extent. This approach enables a better simulation of river-floodplain-reservoir storage by considering both the natural flood and man-made reservoir storage. Results of the seasonal dynamics of reservoir storage, river discharge at the downstream of dams, and the reservoir inundation extent are evaluated with various datasets from ground-observations and satellite measurements. The new model captures the dynamics of these variables with a good accuracy for most of the large reservoirs in the western United States. It is expected that the incorporation of the newly developed reservoir scheme in large-scale land surface models (LSMs) will lead to improved simulation of river flow and terrestrial water storage in highly managed river basins.

Seasonal variability of the Canary Current: A numerical study

NASA Astrophysics Data System (ADS)

Mason, Evan; Colas, Francois; Molemaker, Jeroen; Shchepetkin, Alexander F.; Troupin, Charles; McWilliams, James C.; Sangrã, Pablo

2011-06-01

A high-resolution numerical model study of the Canary Basin in the northeast subtropical Atlantic Ocean is presented. A long-term climatological solution from the Regional Oceanic Modeling System (ROMS) reveals mesoscale variability associated with the Azores and Canary Current systems, the northwest African coastal upwelling, and the Canary Island archipelago. The primary result concerns the Canary Current (CanC) which, in the solution, transports ˜3 Sv southward in line with observations. The simulated CanC has a well-defined path with pronounced seasonal variability. This variability is shown to be mediated by the westward passage of two large annually excited counterrotating anomalous structures that originate at the African coast. The anomalies have a sea surface expression, permitting their validation using altimetry and travel at the phase speed of baroclinic planetary (Rossby) waves. The role of nearshore wind stress curl variability as a generating mechanism for the anomalies is confirmed through a sensitivity experiment forced by low-resolution winds. The resulting circulation is weak in comparison to the base run, but the propagating anomalies are still discernible, so we cannot discount a further role in their generation being played by annual reversals of the large-scale boundary flow that are known to occur along the African margin. An additional sensitivity experiment, where the Azores Current is removed by closing the Strait of Gibraltar presents the same anomalies and CanC behavior as the base run, suggesting that the CanC is rather insensitive to upstream variability from the Azores Current.

Whole Atmosphere Modeling and Data Analysis: Success Stories, Challenges and Perspectives

NASA Astrophysics Data System (ADS)

Yudin, V. A.; Akmaev, R. A.; Goncharenko, L. P.; Fuller-Rowell, T. J.; Matsuo, T.; Ortland, D. A.; Maute, A. I.; Solomon, S. C.; Smith, A. K.; Liu, H.; Wu, Q.

2015-12-01

At the end of the 20-th century Raymond Roble suggested an ambitious target of developing an atmospheric general circulation model (GCM) that spans from the surface to the thermosphere for modeling the coupled atmosphere-ionosphere with drivers from terrestrial meteorology and solar-geomagnetic inputs. He pointed out several areas of research and applications that would benefit highly from the development and improvement of whole atmosphere modeling. At present several research groups using middle and whole atmosphere models have attempted to perform coupled ionosphere-thermosphere predictions to interpret the "unexpected" anomalies in the electron content, ions and plasma drifts observed during recent stratospheric warming events. The recent whole atmosphere inter-comparison case studies also displayed striking differences in simulations of prevailing flows, planetary waves and dominant tidal modes even when the lower atmosphere domain of those models were constrained by similar meteorological analyses. We will present the possible reasons of such differences between data-constrained whole atmosphere simulations when analyses with 6-hour time resolution are used and discuss the potential model-data and model-model differences above the stratopause. The possible shortcomings of the whole atmosphere simulations associated with model physics, dynamical cores and resolutions will be discussed. With the increased confidence in the space-borne temperature, winds and ozone observations and extensive collections of ground-based upper atmosphere observational facilities, the whole atmosphere modelers will be able to quantify annual and year-to-variability of the zonal mean flows, planetary wave and tides. We will demonstrate the value of tidal and planetary wave variability deduced from the space-borne data and ground-based systems for evaluation and tune-up of whole atmosphere simulations including corrections of systematic model errors. Several success stories on the middle and whole atmosphere simulations coupled with the ionosphere models will be highlighted, and future perspectives for links of the space and terrestrial weather predictions constrained by current and scheduled ionosphere-thermosphere-mesosphere satellite missions will be presented

Dynamics of Magnetopause Reconnection in Response to Variable Solar Wind Conditions

NASA Astrophysics Data System (ADS)

Berchem, J.; Richard, R. L.; Escoubet, C. P.; Pitout, F.

2017-12-01

Quantifying the dynamics of magnetopause reconnection in response to variable solar wind driving is essential to advancing our predictive understanding of the interaction of the solar wind/IMF with the magnetosphere. To this end we have carried out numerical studies that combine global magnetohydrodynamic (MHD) and Large-Scale Kinetic (LSK) simulations to identify and understand the effects of solar wind/IMF variations. The use of the low dissipation, high resolution UCLA MHD code incorporating a non-linear local resistivity allows the representation of the global configuration of the dayside magnetosphere while the use of LSK ion test particle codes with distributed particle detectors allows us to compare the simulation results with spacecraft observations such as ion dispersion signatures observed by the Cluster spacecraft. We present the results of simulations that focus on the impacts of relatively simple solar wind discontinuities on the magnetopause and examine how the recent history of the interaction of the magnetospheric boundary with solar wind discontinuities can modify the dynamics of magnetopause reconnection in response to the solar wind input.

GERLUMPH Data Release 2: 2.5 Billion Simulated Microlensing Light Curves

NASA Astrophysics Data System (ADS)

Vernardos, G.; Fluke, C. J.; Bate, N. F.; Croton, D.; Vohl, D.

2015-04-01

In the upcoming synoptic all-sky survey era of astronomy, thousands of new multiply imaged quasars are expected to be discovered and monitored regularly. Light curves from the images of gravitationally lensed quasars are further affected by superimposed variability due to microlensing. In order to disentangle the microlensing from the intrinsic variability of the light curves, the time delays between the multiple images have to be accurately measured. The resulting microlensing light curves can then be analyzed to reveal information about the background source, such as the size of the quasar accretion disk. In this paper we present the most extensive and coherent collection of simulated microlensing light curves; we have generated \\gt 2.5 billion light curves using the GERLUMPH high resolution microlensing magnification maps. Our simulations can be used to train algorithms to measure lensed quasar time delays, plan future monitoring campaigns, and study light curve properties throughout parameter space. Our data are openly available to the community and are complemented by online eResearch tools, located at http://gerlumph.swin.edu.au.

High-resolution dynamical downscaling of re-analysis data over the Kerguelen Islands using the WRF model

NASA Astrophysics Data System (ADS)

Fonseca, Ricardo; Martín-Torres, Javier

2018-03-01

We have used the Weather Research and Forecasting (WRF) model to simulate the climate of the Kerguelen Islands (49° S, 69° E) and investigate its inter-annual variability. Here, we have dynamically downscaled 30 years of the Climate Forecast System Reanalysis (CFSR) over these islands at 3-km horizontal resolution. The model output is found to agree well with the station and radiosonde data at the Port-aux-Français station, the only location in the islands for which observational data is available. An analysis of the seasonal mean WRF data showed a general increase in precipitation and decrease in temperature with elevation. The largest seasonal rainfall amounts occur at the highest elevations of the Cook Ice Cap in winter where the summer mean temperature is around 0 °C. Five modes of variability are considered: conventional and Modoki El Niño-Southern Oscillation (ENSO), Indian Ocean Dipole (IOD), Subtropical IOD (SIOD) and Southern Annular Mode (SAM). It is concluded that a key mechanism by which these modes impact the local climate is through interaction with the diurnal cycle in particular in the summer season when it has a larger magnitude. One of the most affected regions is the area just to the east of the Cook Ice Cap extending into the lower elevations between the Gallieni and Courbet Peninsulas. The WRF simulation shows that despite the small annual variability, the atmospheric flow in the Kerguelen Islands is rather complex which may also be the case for the other islands located in the Southern Hemisphere at similar latitudes.

Ocean sea-ice modelling in the Southern Ocean around Indian Antarctic stations

NASA Astrophysics Data System (ADS)

Kumar, Anurag; Dwivedi, Suneet; Rajak, D. Ram

2017-07-01

An eddy-resolving coupled ocean sea-ice modelling is carried out in the Southern Ocean region (9°-78°E; 51°-71°S) using the MITgcm. The model domain incorporates the Indian Antarctic stations, Maitri (11.7{°}E; 70.7{°}S) and Bharati (76.1{°}E; 69.4{°}S). The realistic simulation of the surface variables, namely, sea surface temperature (SST), sea surface salinity (SSS), surface currents, sea ice concentration (SIC) and sea ice thickness (SIT) is presented for the period of 1997-2012. The horizontal resolution of the model varies between 6 and 10 km. The highest vertical resolution of 5 m is taken near the surface, which gradually increases with increasing depths. The seasonal variability of the SST, SSS, SIC and currents is compared with the available observations in the region of study. It is found that the SIC of the model domain is increasing at a rate of 0.09% per month (nearly 1% per year), whereas, the SIC near Maitri and Bharati regions is increasing at a rate of 0.14 and 0.03% per month, respectively. The variability of the drift of the sea-ice is also estimated over the period of simulation. It is also found that the sea ice volume of the region increases at the rate of 0.0004 km3 per month (nearly 0.005 km3 per year). Further, it is revealed that the accumulation of sea ice around Bharati station is more as compared to Maitri station.

Dual-TRACER: High resolution fMRI with constrained evolution reconstruction.

PubMed

Li, Xuesong; Ma, Xiaodong; Li, Lyu; Zhang, Zhe; Zhang, Xue; Tong, Yan; Wang, Lihong; Sen Song; Guo, Hua

2018-01-01

fMRI with high spatial resolution is beneficial for studies in psychology and neuroscience, but is limited by various factors such as prolonged imaging time, low signal to noise ratio and scarcity of advanced facilities. Compressed Sensing (CS) based methods for accelerating fMRI data acquisition are promising. Other advanced algorithms like k-t FOCUSS or PICCS have been developed to improve performance. This study aims to investigate a new method, Dual-TRACER, based on Temporal Resolution Acceleration with Constrained Evolution Reconstruction (TRACER), for accelerating fMRI acquisitions using golden angle variable density spiral. Both numerical simulations and in vivo experiments at 3T were conducted to evaluate and characterize this method. Results show that Dual-TRACER can provide functional images with a high spatial resolution (1×1mm 2 ) under an acceleration factor of 20 while maintaining hemodynamic signals well. Compared with other investigated methods, dual-TRACER provides a better signal recovery, higher fMRI sensitivity and more reliable activation detection. Copyright © 2017 Elsevier Inc. All rights reserved.

A novel method for enhancing the lateral resolution and image SNR in confocal microscopy

NASA Astrophysics Data System (ADS)

Chen, Youhua; Zhu, Dazhao; Fang, Yue; Kuang, Cuifang; Liu, Xu

2017-12-01

There is always a tradeoff between the resolution and the signal-to-noise ratio (SNR) in confocal microscopy. In particular, the pinhole size is very important for maintaining a balance between them. In this paper, we propose a method for improving the lateral resolution and image SNR in confocal microscopy without making any changes to the hardware. By using the fluorescence emission difference (FED) approach, we divide the images acquired by different pinhole sizes into one image acquired by the central pinhole and several images acquired by ring-shaped pinholes. Then, they are added together with the deconvolution method. Simulation and experimental results for fluorescent particles and cells show that our method can achieve a far better resolution than a large pinhole and a higher SNR than a small pinhole. Moreover, our method can improve the performance of classic confocal laser scanning microscopy (CLSM) to a certain extent, especially CLSM with a continuously variable pinhole.

Superensemble of a Regional Climate Model for the Western US using Climateprediction.net

NASA Astrophysics Data System (ADS)

Mote, P.; Salahuddin, A.; Allen, M.; Jones, R.

2010-12-01

For over a decade, a citizen science experiment called climateprediction.net organized by Oxford University has used computer time contributed by over 80,000 volunteers around the world to create superensembles of global climate simulations. A new climateprediction.net experiment built by the UK Meteorological Office and Oxford, and released in late summer 2010, brings these computing resources to bear on regional climate modeling for the Western US, western Europe, and southern Africa. For the western US, the spatial resolution of 25km permits important topological features -- mountain ranges and valleys -- to be resolved and to influence simulated climate, which consequently includes many important observed features of climate like the fact that California’s Central Valley is hottest at the north and south ends in summer, and cooler in the middle owing to the maritime influence that leaks through the gap in the coast range in the San Francisco area. We designed the output variables to satisfy both research needs and societal and environmental impacts needs. These include atmospheric circulation on regional and global scales, surface fluxes of energy, and hydrologic variables; extremes of temperature, precipitation, and wind; and derived quantities like frost days and number of consecutive dry days. Early results from pre-release beta testing suggest that the simulated fields compare favorably with available observations, and that the model performs as well in the distributed computing environment as on a dedicated high-performance machine. The advantages of a superensemble in interpreting regional climate change will permit an unprecedented combination of statistical completeness and spatial resolution.

Spatial variability of summer Florida precipitation and its impact on microwave radiometer rainfall-measurement systems

NASA Technical Reports Server (NTRS)

Turner, B. J.; Austin, G. L.

1993-01-01

Three-dimensional radar data for three summer Florida storms are used as input to a microwave radiative transfer model. The model simulates microwave brightness observations by a 19-GHz, nadir-pointing, satellite-borne microwave radiometer. The statistical distribution of rainfall rates for the storms studied, and therefore the optimal conversion between microwave brightness temperatures and rainfall rates, was found to be highly sensitive to the spatial resolution at which observations were made. The optimum relation between the two quantities was less sensitive to the details of the vertical profile of precipitation. Rainfall retrievals were made for a range of microwave sensor footprint sizes. From these simulations, spatial sampling-error estimates were made for microwave radiometers over a range of field-of-view sizes. The necessity of matching the spatial resolution of ground truth to radiometer footprint size is emphasized. A strategy for the combined use of raingages, ground-based radar, microwave, and visible-infrared (VIS-IR) satellite sensors is discussed.

Data Analysis and Non-local Parametrization Strategies for Organized Atmospheric Convection

NASA Astrophysics Data System (ADS)

Brenowitz, Noah D.

The intrinsically multiscale nature of moist convective processes in the atmosphere complicates scientific understanding, and, as a result, current coarse-resolution climate models poorly represent convective variability in the tropics. This dissertation addresses this problem by 1) studying new cumulus convective closures in a pair of idealized models for tropical moist convection, and 2) developing innovative strategies for analyzing high-resolution numerical simulations of organized convection. The first two chapters of this dissertation revisit a historical controversy about the use of convective closures based on the large-scale wind field or moisture convergence. In the first chapter, a simple coarse resolution stochastic model for convective inhibition is designed which includes the non-local effects of wind-convergence on convective activity. This model is designed to replicate the convective dynamics of a typical coarse-resolution climate prediction model. The non-local convergence coupling is motivated by the phenomena of gregarious convection, whereby mesoscale convective systems emit gravity waves which can promote convection at a distant locations. Linearized analysis and nonlinear simulations show that this convergence coupling allows for increased interaction between cumulus convection and the large-scale circulation, but does not suffer from the deleterious behavior of traditional moisture-convergence closures. In the second chapter, the non-local convergence coupling idea is extended to an idealized stochastic multicloud model. This model allows for stochastic transitions between three distinct cloud types, and non-local convergence coupling is most beneficial when applied to the transition from shallow to deep convection. This is consistent with recent observational and numerical modeling evidence, and there is a growing body of work highlighting the importance of this transition in tropical meteorology. In a series of idealized Walker cell simulations, convergence coupling enhances the persistence of Kelvin wave analogs in dry regions of the domain while leaving the dynamics in moist regions largely unaltered. The final chapter of this dissertation presents a technique for analyzing the variability of a direct numerical simulation of Rayleigh-Benard convection at large aspect ratio, which is a basic prototype of convective organization. High resolution numerical models are an invaluable tool for studying atmospheric dynamics, but modern data analysis techniques struggle with the extreme size of the model outputs and the trivial symmetries of the underlying dynamical systems (e.g. shift-invariance). A new data analysis approach which is invariant to spatial symmetries is derived by combining a quasi-Lagrangian description of the data, time-lagged embedding, and manifold learning techniques. The quasi-Lagrangian description is obtained by a straightforward isothermal binning procedure, which compresses the data in a dynamically-aware fashion. A small number of orthogonal modes returned by this algorithm are able to explain the highly intermittent dynamics of the bulk heat transfer, as quantified by the Nusselt Number.

Interannual variability (1979-2013) of the North-Western Mediterranean deep water mass formation: past observation reanalysis and coupled ocean-atmosphere high-resolution modelling

NASA Astrophysics Data System (ADS)

Somot, Samuel; Houpert, Loic; Sevault, Florence; Testor, Pierre; Bosse, Anthony; Durrieu de Madron, Xavier; Dubois, Clotilde; Herrmann, Marine; Waldman, Robin; Bouin, Marie-Noëlle; Cassou, Christophe

2015-04-01

The North-Western Mediterranean Sea is known as one of the only place in the world where open-sea deep convection occurs (often up to more than 2000m) with the formation of the Western Mediterranean Deep Water (WMDW). This phenomena is mostly driven by local preconditioning of the water column and strong buoyancy losses during Winter. At the event scale, the WMDW formation is characterized by different phases (preconditioning, strong mixing, restratification and spreading), intense air-sea interaction and strong meso-scale activity but, on a longer time scale, it also shows a large interannual variability and may be strongly affected by climate change with impact on the regional biogeochemistry. Therefore observing, simulating and understanding the long-term temporal variability of the North-Western Mediterranean deep water formation is still today a very challenging task. We try here to tackle those issues thanks to (1) a thorough reanalysis of past in-situ observations (CTD, Argo, surface and deep moorings, gliders) and (2) an ERA-Interim driven simulation using a recently-developed fully coupled Regional Climate System Model (CNRM-RCSM4, Sevault et al. 2014). The multi-decadal simulation (1979-2013) is designed to be temporally and spatially homogeneous with a realistic chronology, a high resolution representation of both the regional ocean and atmosphere, specific initial conditions, a long-term spin-up and a full ocean-atmosphere coupling without constraint at the air-sea interface. The observation reanalysis allows to reconstruct interannual time series of deep water formation indicators (ocean surface variables, mixed layer depth, surface of the convective area, dense water volumes and characteristics of the deep water). Using the observation-based indicators and the model outputs, the 34 Winters of the period 1979-2013 are analysed in terms of weather regimes, related Winter air-sea fluxes, ocean preconditioning, mixed layer depth, surface of the convective area, deep water formation rate and long-term evolution of the deep water hydrology.

Simulation of Space-borne Radar Observation from High Resolution Cloud Model - for GPM Dual frequency Precipitation Radar -

NASA Astrophysics Data System (ADS)

Kim, H.; Meneghini, R.; Jones, J.; Liao, L.

2011-12-01

A comprehensive space-borne radar simulator has been developed to support active microwave sensor satellite missions. The two major objectives of this study are: 1) to develop a radar simulator optimized for the Dual-frequency Precipitation Radar (KuPR and KaPR) on the Global Precipitation Measurement Mission satellite (GPM-DPR) and 2) to generate the synthetic test datasets for DPR algorithm development. This simulator consists of two modules: a DPR scanning configuration module and a forward module that generates atmospheric and surface radar observations. To generate realistic DPR test data, the scanning configuration module specifies the technical characteristics of DPR sensor and emulates the scanning geometry of the DPR with a inner swath of about 120 km, which contains matched-beam data from both frequencies, and an outer swath from 120 to 245 km over which only Ku-band data will be acquired. The second module is a forward model used to compute radar observables (reflectivity, attenuation and polarimetric variables) from input model variables including temperature, pressure and water content (rain water, cloud water, cloud ice, snow, graupel and water vapor) over the radar resolution volume. Presently, the input data to the simulator come from the Goddard Cumulus Ensemble (GCE) and Weather Research and Forecast (WRF) models where a constant mass density is assumed for each species with a particle size distribution given by an exponential distribution with fixed intercept parameter (N0) and a slope parameter (Λ) determined from the equivalent water content. Although the model data do not presently contain mixed phase hydrometeors, the Yokoyama-Tanaka melting model is used along with the Bruggeman effective dielectric constant to replace rain and snow particles, where both are present, with mixed phase particles while preserving the snow/water fraction. For testing one of the DPR retrieval algorithms, the Surface Reference Technique (SRT), the simulator uses the normalized radar cross sections of the surface,σ0, at each frequency and incidence angle to generate the radar return power from the surface. The simulated σ0 data are modeled as realizations from jointly Gaussian random variables with means, variances and correlations obtained from measurements of σ0 from the JPL APR2 (2nd generation Airborne Precipitation Radar) data, which operates at approximately the same frequencies as the DPR. We will discuss the general capabilities of the radar simulator, present some sample results and show how they can be used to assess the performance of the radar retrieval algorithms proposed for the Dual-Frequency GPM radar. In addition, we will report on updates to the simulator using inputs from cloud models with spectral bin microphysics.

Analyzing Spatial and Temporal Variation in Precipitation Estimates in a Coupled Model

NASA Astrophysics Data System (ADS)

Tomkins, C. D.; Springer, E. P.; Costigan, K. R.

2001-12-01

Integrated modeling efforts at the Los Alamos National Laboratory aim to simulate the hydrologic cycle and study the impacts of climate variability and land use changes on water resources and ecosystem function at the regional scale. The integrated model couples three existing models independently responsible for addressing the atmospheric, land surface, and ground water components: the Regional Atmospheric Model System (RAMS), the Los Alamos Distributed Hydrologic System (LADHS), and the Finite Element and Heat Mass (FEHM). The upper Rio Grande Basin, extending 92,000 km2 over northern New Mexico and southern Colorado, serves as the test site for this model. RAMS uses nested grids to simulate meteorological variables, with the smallest grid over the Rio Grande having 5-km horizontal grid spacing. As LADHS grid spacing is 100 m, a downscaling approach is needed to estimate meteorological variables from the 5km RAMS grid for input into LADHS. This study presents daily and cumulative precipitation predictions, in the month of October for water year 1993, and an approach to compare LADHS downscaled precipitation to RAMS-simulated precipitation. The downscaling algorithm is based on kriging, using topography as a covariate to distribute the precipitation and thereby incorporating the topographical resolution achieved at the 100m-grid resolution in LADHS. The results of the downscaling are analyzed in terms of the level of variance introduced into the model, mean simulated precipitation, and the correlation between the LADHS and RAMS estimates. Previous work presented a comparison of RAMS-simulated and observed precipitation recorded at COOP and SNOTEL sites. The effects of downscaling the RAMS precipitation were evaluated using Spearman and linear correlations and by examining the variance of both populations. The study focuses on determining how the downscaling changes the distribution of precipitation compared to the RAMS estimates. Spearman correlations computed for the LADHS and RAMS cumulative precipitation reveal a disassociation over time, with R equal to 0.74 at day eight and R equal to 0.52 at day 31. Linear correlation coefficients (Pearson) returned a stronger initial correlation of 0.97, decreasing to 0.68. The standard deviations for the 2500 LADHS cells underlying each 5km RAMS cell range from 8 mm to 695 mm in the Sangre de Cristo Mountains and 2 mm to 112 mm in the San Luis Valley. Comparatively, the standard deviations of the RAMS estimates in these regions are 247 mm and 30 mm respectively. The LADHS standard deviations provide a measure of the variability introduced through the downscaling routine, which exceeds RAMS regional variability by a factor of 2 to 4. The coefficient of variation for the average LADHS grid cell values and the RAMS cell values in the Sangre de Cristo Mountains are 0.66 and 0.27, respectively, and 0.79 and 0.75 in the San Luis Valley. The coefficients of variation evidence the uniformity of the higher precipitation estimates in the mountains, especially for RAMS, and also the lower means and variability found in the valley. Additionally, Kolmogorov-Smirnov tests indicate clear spatial and temporal differences in mean simulated precipitation across the grid.

Synoptic variability in the nudged version of LMDZ over the West African monsoon region during the AMMA campaign.

NASA Astrophysics Data System (ADS)

Ly, M.; Roca, R.; Hourdin, F.

2009-04-01

The Laboratoire de Météorologie Dynamique General circulation Model (LMDz) is ran in a nudged mode using various sets of atmospheric analysis during the wet season of 2006. The zoom capability of the model is used and reaches a mesh size of around 80km over the whole West African region. Sensitivity experiments have been performed in order to highlight the behaviour of the nudged model under a wide range of conditions: spatial and vertical resolution, zoom intensity, surface scheme formulation as well as for the forcing and driving parameters: relaxation time, type of analysis (ECMWF, NCEP/GFS, Sea Surface Temperature (climatology vs. 2006) and the nudging variables (wind, temperature, and combination). A combination of satellite data (E.g., GPCP rain estimates, METEOSAT Free tropospheric humidity,…) and in-situ observations acquired during the AMMA campaign (temperature and humidity profiles from radiosondes, GPS precipitable water,…) are all used to evaluate the simulations. The analysis is focused on the representation of the synoptic variability by the model in terms of rainfall and water vapour variability. It is shown that the model captures the free troposphere water vapour variability reasonably well with highly significant correlations between the radiosondes and the simulated fields. In the lowest levels of the atmosphere and in the upper troposphere, the agreement is less good. When the fields are filtered using a pass-band filter between 3-10 days, the correlation overall increases. Detailed of the sensitivity of these results to the simulation configuration mentioned above will be further discussed at the conference.

Instrumental resolution of the chopper spectrometer 4SEASONS evaluated by Monte Carlo simulation

NASA Astrophysics Data System (ADS)

Kajimoto, Ryoichi; Sato, Kentaro; Inamura, Yasuhiro; Fujita, Masaki

2018-05-01

We performed simulations of the resolution function of the 4SEASONS spectrometer at J-PARC by using the Monte Carlo simulation package McStas. The simulations showed reasonably good agreement with analytical calculations of energy and momentum resolutions by using a simplified description. We implemented new functionalities in Utsusemi, the standard data analysis tool used in 4SEASONS, to enable visualization of the simulated resolution function and predict its shape for specific experimental configurations.

Covariability of seasonal temperature and precipitation over the Iberian Peninsula in high-resolution regional climate simulations (1001-2099)

NASA Astrophysics Data System (ADS)

Fernández-Montes, S.; Gómez-Navarro, J. J.; Rodrigo, F. S.; García-Valero, J. A.; Montávez, J. P.

2017-04-01

Precipitation and surface temperature are interdependent variables, both as a response to atmospheric dynamics and due to intrinsic thermodynamic relationships and feedbacks between them. This study analyzes the covariability of seasonal temperature (T) and precipitation (P) across the Iberian Peninsula (IP) using regional climate paleosimulations for the period 1001-1990, driven by reconstructions of external forcings. Future climate (1990-2099) was simulated according to SRES scenarios A2 and B2. These simulations enable exploring, at high spatial resolution, robust and physically consistent relationships. In winter, positive P-T correlations dominate west-central IP (Pearson correlation coefficient ρ = + 0.43, for 1001-1990), due to prevalent cold-dry and warm-wet conditions, while this relationship weakens and become negative towards mountainous, northern and eastern regions. In autumn, negative correlations appear in similar regions as in winter, whereas for summer they extend also to the N/NW of the IP. In spring, the whole IP depicts significant negative correlations, strongest for eastern regions (ρ = - 0.51). This is due to prevalent frequency of warm-dry and cold-wet modes in these regions and seasons. At the temporal scale, regional correlation series between seasonal anomalies of temperature and precipitation (assessed in 31 years running windows in 1001-1990) show very large multidecadal variability. For winter and spring, periodicities of about 50-60 years arise. The frequency of warm-dry and cold-wet modes appears correlated with the North Atlantic Oscillation (NAO), explaining mainly co-variability changes in spring. For winter and some regions in autumn, maximum and minimum P-T correlations appear in periods with enhanced meridional or easterly circulation (low or high pressure anomalies in the Mediterranean and Europe). In spring and summer, the Atlantic Multidecadal Oscillation shows some fingerprint on the frequency of warm/cold modes. For future scenarios, an intensification of the negative P-T relationship is generally found, as a result of an increased frequency of the warm-dry mode.

Chemistry Simulations using the MERRA-2 Reanalysis with the GMI CTM and Replay in Support of the Atmospheric Composition Community

NASA Technical Reports Server (NTRS)

Oman, Luke D.; Strahan, Susan E.

2017-01-01

Simulations using reanalysis meteorological fields have long been used to understand the causes of atmospheric composition change in the recent past. Using the new MERRA-2 reanalysis, we are conducting chemistry simulations to create products covering 1980-2016 for the atmospheric composition community. These simulations use the Global Modeling Initiative (GMI) chemical mechanism in two different models: the GMI Chemical Transport Model (CTM) and the GEOS-5 model in Replay mode. Replay mode means an integration of the GEOS-5 general circulation model that is incrementally adjusted each time step toward the MERRA-2 reanalysis. The GMI CTM is a 1 deg x 1.25 deg simulation and the MERRA-2 GMI Replay simulation uses the native MERRA-2 grid of approximately 1/2 deg horizontal resolution on the cubed sphere. A specialized set of transport diagnostics is included in both runs to better understand trace gas transport and its variability in the recent past.

Initial conditions and modeling for simulations of shock driven turbulent material mixing

DOE PAGES

Grinstein, Fernando F.

2016-11-17

Here, we focus on the simulation of shock-driven material mixing driven by flow instabilities and initial conditions (IC). Beyond complex multi-scale resolution issues of shocks and variable density turbulence, me must address the equally difficult problem of predicting flow transition promoted by energy deposited at the material interfacial layer during the shock interface interactions. Transition involves unsteady large-scale coherent-structure dynamics capturable by a large eddy simulation (LES) strategy, but not by an unsteady Reynolds-Averaged Navier–Stokes (URANS) approach based on developed equilibrium turbulence assumptions and single-point-closure modeling. On the engineering end of computations, such URANS with reduced 1D/2D dimensionality and coarsermore » grids, tend to be preferred for faster turnaround in full-scale configurations.« less

Investigating the effect and uncertainties of light absorbing impurities in snow and ice on snow melt and discharge generation using a hydrologic catchment model and satellite data

NASA Astrophysics Data System (ADS)

Matt, Felix; Burkhart, John F.

2017-04-01

Light absorbing impurities in snow and ice (LAISI) originating from atmospheric deposition enhance snow melt by increasing the absorption of short wave radiation. The consequences are a shortening of the snow cover duration due to increased snow melt and, with respect to hydrologic processes, a temporal shift in the discharge generation. However, the magnitude of these effects as simulated in numerical models have large uncertainties, originating mainly from uncertainties in the wet and dry deposition of light absorbing aerosols, limitations in the model representation of the snowpack, and the lack of observable variables required to estimate model parameters and evaluate the simulated variables connected with the representation of LAISI. This leads to high uncertainties in the additional energy absorbed by the snow due to the presence of LAISI, a key variable in understanding snowpack energy-balance dynamics. In this study, we assess the effect of LAISI on snow melt and discharge generation and the involved uncertainties in a high mountain catchment located in the western Himalayas by using a distributed hydrological catchment model with focus on the representation of the seasonal snow pack. The snow albedo is hereby calculated from a radiative transfer model for snow, taking the increased absorption of short wave radiation by LAISI into account. Meteorological forcing data is generated from an assimilation of observations and high resolution WRF simulations, and LAISI mixing ratios from deposition rates of Black Carbon simulated with the FLEXPART model. To asses the quality of our simulations and the related uncertainties, we compare the simulated additional energy absorbed by the snow due to the presence of LAISI to the MODIS Dust Radiative Forcing in Snow (MODDRFS) algorithm satellite product.

Relativistic MHD simulations of collision-induced magnetic dissipation in poynting-flux-dominated jets/outflows

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

Deng, Wei; Li, Hui; Zhang, Bing

We perform 3D relativistic ideal MHD simulations to study the collisions between high-σ (Poynting- ux-dominated) blobs which contain both poloidal and toroidal magnetic field components. This is meant to mimic the interactions inside a highly variable Poynting- ux-dominated jet. We discover a significant electromagnetic field (EMF) energy dissipation with an Alfvenic rate with the efficiency around 35%. Detailed analyses show that this dissipation is mostly facilitated by the collision-induced magnetic reconnection. Additional resolution and parameter studies show a robust result that the relative EMF energy dissipation efficiency is nearly independent of the numerical resolution or most physical parameters in themore » relevant parameter range. The reconnection outflows in our simulation can potentially form the multi-orientation relativistic mini-jets as needed for several analytical models. We also find a linear relationship between the σ values before and after the major EMF energy dissipation process. In conclusion, our results give support to the proposed astrophysical models that invoke signi cant magnetic energy dissipation in Poynting- ux-dominated jets, such as the internal collision-induced magnetic reconnection and turbulence (ICMART) model for GRBs, and reconnection triggered mini-jets model for AGNs.« less

Relativistic MHD simulations of collision-induced magnetic dissipation in poynting-flux-dominated jets/outflows

DOE PAGES

Deng, Wei; Li, Hui; Zhang, Bing; ...

2015-05-29

We perform 3D relativistic ideal MHD simulations to study the collisions between high-σ (Poynting- ux-dominated) blobs which contain both poloidal and toroidal magnetic field components. This is meant to mimic the interactions inside a highly variable Poynting- ux-dominated jet. We discover a significant electromagnetic field (EMF) energy dissipation with an Alfvenic rate with the efficiency around 35%. Detailed analyses show that this dissipation is mostly facilitated by the collision-induced magnetic reconnection. Additional resolution and parameter studies show a robust result that the relative EMF energy dissipation efficiency is nearly independent of the numerical resolution or most physical parameters in themore » relevant parameter range. The reconnection outflows in our simulation can potentially form the multi-orientation relativistic mini-jets as needed for several analytical models. We also find a linear relationship between the σ values before and after the major EMF energy dissipation process. In conclusion, our results give support to the proposed astrophysical models that invoke signi cant magnetic energy dissipation in Poynting- ux-dominated jets, such as the internal collision-induced magnetic reconnection and turbulence (ICMART) model for GRBs, and reconnection triggered mini-jets model for AGNs.« less

Coupling a three-dimensional subsurface flow and transport model with a land surface model to simulate stream-aquifer-land interactions (CP v1.0)

NASA Astrophysics Data System (ADS)

Bisht, Gautam; Huang, Maoyi; Zhou, Tian; Chen, Xingyuan; Dai, Heng; Hammond, Glenn E.; Riley, William J.; Downs, Janelle L.; Liu, Ying; Zachara, John M.

2017-12-01

A fully coupled three-dimensional surface and subsurface land model is developed and applied to a site along the Columbia River to simulate three-way interactions among river water, groundwater, and land surface processes. The model features the coupling of the Community Land Model version 4.5 (CLM4.5) and a massively parallel multiphysics reactive transport model (PFLOTRAN). The coupled model, named CP v1.0, is applied to a 400 m × 400 m study domain instrumented with groundwater monitoring wells along the Columbia River shoreline. CP v1.0 simulations are performed at three spatial resolutions (i.e., 2, 10, and 20 m) over a 5-year period to evaluate the impact of hydroclimatic conditions and spatial resolution on simulated variables. Results show that the coupled model is capable of simulating groundwater-river-water interactions driven by river stage variability along managed river reaches, which are of global significance as a result of over 30 000 dams constructed worldwide during the past half-century. Our numerical experiments suggest that the land-surface energy partitioning is strongly modulated by groundwater-river-water interactions through expanding the periodically inundated fraction of the riparian zone, and enhancing moisture availability in the vadose zone via capillary rise in response to the river stage change. Meanwhile, CLM4.5 fails to capture the key hydrologic process (i.e., groundwater-river-water exchange) at the site, and consequently simulates drastically different water and energy budgets. Furthermore, spatial resolution is found to significantly impact the accuracy of estimated the mass exchange rates at the boundaries of the aquifer, and it becomes critical when surface and subsurface become more tightly coupled with groundwater table within 6 to 7 meters below the surface. Inclusion of lateral subsurface flow influenced both the surface energy budget and subsurface transport processes as a result of river-water intrusion into the subsurface in response to an elevated river stage that increased soil moisture for evapotranspiration and suppressed available energy for sensible heat in the warm season. The coupled model developed in this study can be used for improving mechanistic understanding of ecosystem functioning and biogeochemical cycling along river corridors under historical and future hydroclimatic changes. The dataset presented in this study can also serve as a good benchmarking case for testing other integrated models.

Coupling a three-dimensional subsurface flow and transport model with a land surface model to simulate stream–aquifer–land interactions (CP v1.0)

DOE PAGES

Bisht, Gautam; Huang, Maoyi; Zhou, Tian; ...

2017-12-12

A fully coupled three-dimensional surface and subsurface land model is developed and applied to a site along the Columbia River to simulate three-way interactions among river water, groundwater, and land surface processes. The model features the coupling of the Community Land Model version 4.5 (CLM4.5) and a massively parallel multiphysics reactive transport model (PFLOTRAN). The coupled model, named CP v1.0, is applied to a 400 m × 400 m study domain instrumented with groundwater monitoring wells along the Columbia River shoreline. CP v1.0 simulations are performed at three spatial resolutions (i.e., 2, 10, and 20 m) over a 5-year periodmore » to evaluate the impact of hydroclimatic conditions and spatial resolution on simulated variables. Results show that the coupled model is capable of simulating groundwater–river-water interactions driven by river stage variability along managed river reaches, which are of global significance as a result of over 30 000 dams constructed worldwide during the past half-century. Our numerical experiments suggest that the land-surface energy partitioning is strongly modulated by groundwater–river-water interactions through expanding the periodically inundated fraction of the riparian zone, and enhancing moisture availability in the vadose zone via capillary rise in response to the river stage change. Meanwhile, CLM4.5 fails to capture the key hydrologic process (i.e., groundwater–river-water exchange) at the site, and consequently simulates drastically different water and energy budgets. Furthermore, spatial resolution is found to significantly impact the accuracy of estimated the mass exchange rates at the boundaries of the aquifer, and it becomes critical when surface and subsurface become more tightly coupled with groundwater table within 6 to 7 meters below the surface. Inclusion of lateral subsurface flow influenced both the surface energy budget and subsurface transport processes as a result of river-water intrusion into the subsurface in response to an elevated river stage that increased soil moisture for evapotranspiration and suppressed available energy for sensible heat in the warm season. The coupled model developed in this study can be used for improving mechanistic understanding of ecosystem functioning and biogeochemical cycling along river corridors under historical and future hydroclimatic changes. The dataset presented in this study can also serve as a good benchmarking case for testing other integrated models.« less

Coupling a three-dimensional subsurface flow and transport model with a land surface model to simulate stream–aquifer–land interactions (CP v1.0)

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

Bisht, Gautam; Huang, Maoyi; Zhou, Tian

A fully coupled three-dimensional surface and subsurface land model is developed and applied to a site along the Columbia River to simulate three-way interactions among river water, groundwater, and land surface processes. The model features the coupling of the Community Land Model version 4.5 (CLM4.5) and a massively parallel multiphysics reactive transport model (PFLOTRAN). The coupled model, named CP v1.0, is applied to a 400 m × 400 m study domain instrumented with groundwater monitoring wells along the Columbia River shoreline. CP v1.0 simulations are performed at three spatial resolutions (i.e., 2, 10, and 20 m) over a 5-year period to evaluate themore » impact of hydroclimatic conditions and spatial resolution on simulated variables. Results show that the coupled model is capable of simulating groundwater–river-water interactions driven by river stage variability along managed river reaches, which are of global significance as a result of over 30 000 dams constructed worldwide during the past half-century. Our numerical experiments suggest that the land-surface energy partitioning is strongly modulated by groundwater–river-water interactions through expanding the periodically inundated fraction of the riparian zone, and enhancing moisture availability in the vadose zone via capillary rise in response to the river stage change. Meanwhile, CLM4.5 fails to capture the key hydrologic process (i.e., groundwater–river-water exchange) at the site, and consequently simulates drastically different water and energy budgets. Furthermore, spatial resolution is found to significantly impact the accuracy of estimated the mass exchange rates at the boundaries of the aquifer, and it becomes critical when surface and subsurface become more tightly coupled with groundwater table within 6 to 7 meters below the surface. Inclusion of lateral subsurface flow influenced both the surface energy budget and subsurface transport processes as a result of river-water intrusion into the subsurface in response to an elevated river stage that increased soil moisture for evapotranspiration and suppressed available energy for sensible heat in the warm season. The coupled model developed in this study can be used for improving mechanistic understanding of ecosystem functioning and biogeochemical cycling along river corridors under historical and future hydroclimatic changes. The dataset presented in this study can also serve as a good benchmarking case for testing other integrated models.« less

Coupling a three-dimensional subsurface flow and transport model with a land surface model to simulate stream–aquifer–land interactions (CP v1.0)

DOE PAGES

Bisht, Gautam; Huang, Maoyi; Zhou, Tian; ...

2017-01-01

A fully coupled three-dimensional surface and subsurface land model is developed and applied to a site along the Columbia River to simulate three-way interactions among river water, groundwater, and land surface processes. The model features the coupling of the Community Land Model version 4.5 (CLM4.5) and a massively parallel multiphysics reactive transport model (PFLOTRAN). The coupled model, named CP v1.0, is applied to a 400 m × 400 m study domain instrumented with groundwater monitoring wells along the Columbia River shoreline. CP v1.0 simulations are performed at three spatial resolutions (i.e., 2, 10, and 20 m) over a 5-year period to evaluate themore » impact of hydroclimatic conditions and spatial resolution on simulated variables. Results show that the coupled model is capable of simulating groundwater–river-water interactions driven by river stage variability along managed river reaches, which are of global significance as a result of over 30 000 dams constructed worldwide during the past half-century. Our numerical experiments suggest that the land-surface energy partitioning is strongly modulated by groundwater–river-water interactions through expanding the periodically inundated fraction of the riparian zone, and enhancing moisture availability in the vadose zone via capillary rise in response to the river stage change. Meanwhile, CLM4.5 fails to capture the key hydrologic process (i.e., groundwater–river-water exchange) at the site, and consequently simulates drastically different water and energy budgets. Furthermore, spatial resolution is found to significantly impact the accuracy of estimated the mass exchange rates at the boundaries of the aquifer, and it becomes critical when surface and subsurface become more tightly coupled with groundwater table within 6 to 7 meters below the surface. Inclusion of lateral subsurface flow influenced both the surface energy budget and subsurface transport processes as a result of river-water intrusion into the subsurface in response to an elevated river stage that increased soil moisture for evapotranspiration and suppressed available energy for sensible heat in the warm season. The coupled model developed in this study can be used for improving mechanistic understanding of ecosystem functioning and biogeochemical cycling along river corridors under historical and future hydroclimatic changes. The dataset presented in this study can also serve as a good benchmarking case for testing other integrated models.« less

Coupling a three-dimensional subsurface flow and transport model with a land surface model to simulate stream–aquifer–land interactions (CP v1.0)

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

Bisht, Gautam; Huang, Maoyi; Zhou, Tian

A fully coupled three-dimensional surface and subsurface land model is developed and applied to a site along the Columbia River to simulate three-way interactions among river water, groundwater, and land surface processes. The model features the coupling of the Community Land Model version 4.5 (CLM4.5) and a massively parallel multiphysics reactive transport model (PFLOTRAN). The coupled model, named CP v1.0, is applied to a 400 m × 400 m study domain instrumented with groundwater monitoring wells along the Columbia River shoreline. CP v1.0 simulations are performed at three spatial resolutions (i.e., 2, 10, and 20 m) over a 5-year periodmore » to evaluate the impact of hydroclimatic conditions and spatial resolution on simulated variables. Results show that the coupled model is capable of simulating groundwater–river-water interactions driven by river stage variability along managed river reaches, which are of global significance as a result of over 30 000 dams constructed worldwide during the past half-century. Our numerical experiments suggest that the land-surface energy partitioning is strongly modulated by groundwater–river-water interactions through expanding the periodically inundated fraction of the riparian zone, and enhancing moisture availability in the vadose zone via capillary rise in response to the river stage change. Meanwhile, CLM4.5 fails to capture the key hydrologic process (i.e., groundwater–river-water exchange) at the site, and consequently simulates drastically different water and energy budgets. Furthermore, spatial resolution is found to significantly impact the accuracy of estimated the mass exchange rates at the boundaries of the aquifer, and it becomes critical when surface and subsurface become more tightly coupled with groundwater table within 6 to 7 meters below the surface. Inclusion of lateral subsurface flow influenced both the surface energy budget and subsurface transport processes as a result of river-water intrusion into the subsurface in response to an elevated river stage that increased soil moisture for evapotranspiration and suppressed available energy for sensible heat in the warm season. The coupled model developed in this study can be used for improving mechanistic understanding of ecosystem functioning and biogeochemical cycling along river corridors under historical and future hydroclimatic changes. The dataset presented in this study can also serve as a good benchmarking case for testing other integrated models.« less

A Bayesian Measurment Error Model for Misaligned Radiographic Data

DOE PAGES

Lennox, Kristin P.; Glascoe, Lee G.

2013-09-06

An understanding of the inherent variability in micro-computed tomography (micro-CT) data is essential to tasks such as statistical process control and the validation of radiographic simulation tools. The data present unique challenges to variability analysis due to the relatively low resolution of radiographs, and also due to minor variations from run to run which can result in misalignment or magnification changes between repeated measurements of a sample. Positioning changes artificially inflate the variability of the data in ways that mask true physical phenomena. We present a novel Bayesian nonparametric regression model that incorporates both additive and multiplicative measurement error inmore » addition to heteroscedasticity to address this problem. We also use this model to assess the effects of sample thickness and sample position on measurement variability for an aluminum specimen. Supplementary materials for this article are available online.« less

Evaluation of decadal hindcasts using satellite simulators

NASA Astrophysics Data System (ADS)

Spangehl, Thomas; Mazurkiewicz, Alex; Schröder, Marc

2013-04-01

The evaluation of dynamical ensemble forecast systems requires a solid validation of basic processes such as the global atmospheric water and energy cycle. The value of any validation approach strongly depends on the quality of the observational data records used. Current approaches utilize in situ measurements, remote sensing data and reanalyses. Related data records are subject to a number of uncertainties and limitations such as representativeness, spatial and temporal resolution and homogeneity. However, recently several climate data records with known and sufficient quality became available. In particular, the satellite data records offer the opportunity to obtain reference information on global scales including the oceans. Here we consider the simulation of satellite radiances from the climate model output enabling an evaluation in the instrument's parameter space to avoid uncertainties stemming from the application of retrieval schemes in order to minimise uncertainties on the reference side. Utilizing the CFMIP Observation Simulator Package (COSP) we develop satellite simulators for the Tropical Rainfall Measuring Mission precipitation radar (TRMM PR) and the Infrared Atmospheric Sounding Interferometer (IASI). The simulators are applied within the MiKlip project funded by BMBF (German Federal Ministry of Education and Research) to evaluate decadal climate predictions performed with the MPI-ESM developed at the Max Planck Institute for Meteorology. While TRMM PR enables the evaluation of the vertical structure of precipitation over tropical and sub-tropical areas, IASI is used to support the global evaluation of clouds and radiation. In a first step the reliability of the developed simulators needs to be explored. The simulation of radiances in the instrument space requires the generation of sub-grid scale variability from the climate model output. Furthermore, assumptions are made to simulate radiances such as, for example, the distribution of different hydrometeor types. Therefore, testing is performed to determine the extent to which the quality of the simulator results depends on the applied methods used to generate sub-grid variability (e.g. sub-grid resolution). Moreover, the sensitivity of results to the choice of different distributions of hydrometeors is explored. The model evaluation is carried out in a statistical manner using histograms of radar reflectivities (TRMM PR) and brightness temperatures (IASI). Finally, methods to deduce data suitable for probabilistic evaluation of decadal hindcasts such as simple indices are discussed.

Resolution requirements for numerical simulations of transition

NASA Technical Reports Server (NTRS)

Zang, Thomas A.; Krist, Steven E.; Hussaini, M. Yousuff

1989-01-01

The resolution requirements for direct numerical simulations of transition to turbulence are investigated. A reliable resolution criterion is determined from the results of several detailed simulations of channel and boundary-layer transition.

Comparing proxy and model estimates of hydroclimate variability and change over the Common Era

NASA Astrophysics Data System (ADS)

Hydro2k Consortium, Pages

2017-12-01

Water availability is fundamental to societies and ecosystems, but our understanding of variations in hydroclimate (including extreme events, flooding, and decadal periods of drought) is limited because of a paucity of modern instrumental observations that are distributed unevenly across the globe and only span parts of the 20th and 21st centuries. Such data coverage is insufficient for characterizing hydroclimate and its associated dynamics because of its multidecadal to centennial variability and highly regionalized spatial signature. High-resolution (seasonal to decadal) hydroclimatic proxies that span all or parts of the Common Era (CE) and paleoclimate simulations from climate models are therefore important tools for augmenting our understanding of hydroclimate variability. In particular, the comparison of the two sources of information is critical for addressing the uncertainties and limitations of both while enriching each of their interpretations. We review the principal proxy data available for hydroclimatic reconstructions over the CE and highlight the contemporary understanding of how these proxies are interpreted as hydroclimate indicators. We also review the available last-millennium simulations from fully coupled climate models and discuss several outstanding challenges associated with simulating hydroclimate variability and change over the CE. A specific review of simulated hydroclimatic changes forced by volcanic events is provided, as is a discussion of expected improvements in estimated radiative forcings, models, and their implementation in the future. Our review of hydroclimatic proxies and last-millennium model simulations is used as the basis for articulating a variety of considerations and best practices for how to perform proxy-model comparisons of CE hydroclimate. This discussion provides a framework for how best to evaluate hydroclimate variability and its associated dynamics using these comparisons and how they can better inform interpretations of both proxy data and model simulations. We subsequently explore means of using proxy-model comparisons to better constrain and characterize future hydroclimate risks. This is explored specifically in the context of several examples that demonstrate how proxy-model comparisons can be used to quantitatively constrain future hydroclimatic risks as estimated from climate model projections.

Comparing Proxy and Model Estimates of Hydroclimate Variability and Change over the Common Era

NASA Technical Reports Server (NTRS)

Smerdon, Jason E.; Luterbacher, Jurg; Phipps, Steven J.; Anchukaitis, Kevin J.; Ault, Toby; Coats, Sloan; Cobb, Kim M.; Cook, Benjamin I.; Colose, Chris; Felis, Thomas;

The evolution of extreme precipitations in high resolution scenarios over France

NASA Astrophysics Data System (ADS)

Colin, J.; Déqué, M.; Somot, S.

2009-09-01

Over the past years, improving the modelling of extreme events and their variability at climatic time scales has become one of the challenging issue raised in the regional climate research field. This study shows the results of a high resolution (12 km) scenario run over France with the limited area model (LAM) ALADIN-Climat, regarding the representation of extreme precipitations. The runs were conducted in the framework of the ANR-SCAMPEI national project on high resolution scenarios over French mountains. As a first step, we attempt to quantify one of the uncertainties implied by the use of LAM : the size of the area on which the model is run. In particular, we address the issue of whether a relatively small domain allows the model to create its small scale process. Indeed, high resolution scenarios cannot be run on large domains because of the computation time. Therefore one needs to answer this preliminary question before producing and analyzing such scenarios. To do so, we worked in the framework of a « big brother » experiment. We performed a 23-year long global simulation in present-day climate (1979-2001) with the ARPEGE-Climat GCM, at a resolution of approximately 50 km over Europe (stretched grid). This first simulation, named ARP50, constitutes the « big brother » reference of our experiment. It has been validated in comparison with the CRU climatology. Then we filtered the short waves (up to 200 km) from ARP50 in order to obtain the equivalent of coarse resolution lateral boundary conditions (LBC). We have carried out three ALADIN-Climat simulations at a 50 km resolution with these LBC, using different configurations of the model : * FRA50, run over a small domain (2000 x 2000 km, centered over France), * EUR50, run over a larger domain (5000 x 5000 km, centered over France as well), * EUR50-SN, run over the large domain (using spectral nudging). Considering the facts that ARPEGE-Climat and ALADIN-Climat models share the same physics and dynamics and that both regional and global simulations were run at the same resolution, ARP50 can be regarded as a reference with which FRA50, EUR50 and EUR50-SN should each be compared. After an analysis of the differences between the regional simulations and ARP50 in annual and seasonal mean, we focus on the representation of rainfall extremes comparing two dimensional fields of various index inspired from STARDEX and quantile-quantile plots. The results show a good agreement with the ARP50 reference for all three regional simulations and little differences are found between them. This result indicates that the use of small domains is not significantly detrimental to the modelling of extreme precipitation events. It also shows that the spectral nudging technique has no detrimental effect on the extreme precipitation. Therefore, high resolution scenarios performed on a relatively small domain such as the ones run for SCAMPEI, can be regarded as good tools to explore their possible evolution in the future climate. Preliminary results on the response of precipitation extremes over South-East France are given.

Performance of a reconfigured atmospheric general circulation model at low resolution

NASA Astrophysics Data System (ADS)

Wen, Xinyu; Zhou, Tianjun; Wang, Shaowu; Wang, Bin; Wan, Hui; Li, Jian

2007-07-01

Paleoclimate simulations usually require model runs over a very long time. The fast integration version of a state-of-the-art general circulation model (GCM), which shares the same physical and dynamical processes but with reduced horizontal resolution and increased time step, is usually developed. In this study, we configure a fast version of an atmospheric GCM (AGCM), the Grid Atmospheric Model of IAP/LASG (Institute of Atmospheric Physics/State Key Laboratory of Numerical Modeling for Atmospheric Sciences and Geophysical Fluid Dynamics), at low resolution (GAMIL-L, hereafter), and compare the simulation results with the NCEP/NCAR reanalysis and other data to examine its performance. GAMIL-L, which is derived from the original GAMIL, is a finite difference AGCM with 72×40 grids in longitude and latitude and 26 vertical levels. To validate the simulated climatology and variability, two runs were achieved. One was a 60-year control run with fixed climatological monthly sea surface temperature (SST) forcing, and the other was a 50-yr (1950 2000) integration with observational time-varying monthly SST forcing. Comparisons between these two cases and the reanalysis, including intra-seasonal and inter-annual variability are also presented. In addition, the differences between GAMIL-L and the original version of GAMIL are also investigated. The results show that GAMIL-L can capture most of the large-scale dynamical features of the atmosphere, especially in the tropics and mid latitudes, although a few deficiencies exist, such as the underestimated Hadley cell and thereby the weak strength of the Asia summer monsoon. However, the simulated mean states over high latitudes, especially over the polar regions, are not acceptable. Apart from dynamics, the thermodynamic features mainly depend upon the physical parameterization schemes. Since the physical package of GAMIL-L is exactly the same as the original high-resolution version of GAMIL, in which the NCAR Community Atmosphere Model (CAM2) physical package was used, there are only small differences between them in the precipitation and temperature fields. Because our goal is to develop a fast-running AGCM and employ it in the coupled climate system model of IAP/LASG for paleoclimate studies such as ENSO and Australia-Asia monsoon, particular attention has been paid to the model performances in the tropics. More model validations, such as those ran for the Southern Oscillation and South Asia monsoon, indicate that GAMIL-L is reasonably competent and valuable in this regard.

The CSIRO Mk3L climate system model v1.0 coupled to the CABLE land surface scheme v1.4b: evaluation of the control climatology

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

Mao, Jiafu; Phipps, S.J.; Pitman, A.J.

The CSIRO Mk3L climate system model, a reduced-resolution coupled general circulation model, has previously been described in this journal. The model is configured for millennium scale or multiple century scale simulations. This paper reports the impact of replacing the relatively simple land surface scheme that is the default parameterisation in Mk3L with a sophisticated land surface model that simulates the terrestrial energy, water and carbon balance in a physically and biologically consistent way. An evaluation of the new model s near-surface climatology highlights strengths and weaknesses, but overall the atmospheric variables, including the near-surface air temperature and precipitation, are simulatedmore » well. The impact of the more sophisticated land surface model on existing variables is relatively small, but generally positive. More significantly, the new land surface scheme allows an examination of surface carbon-related quantities including net primary productivity which adds significantly to the capacity of Mk3L. Overall, results demonstrate that this reduced-resolution climate model is a good foundation for exploring long time scale phenomena. The addition of the more sophisticated land surface model enables an exploration of important Earth System questions including land cover change and abrupt changes in terrestrial carbon storage.« less

Trans-Pacific transport and evolution of aerosols: Evaluation of quasi-global WRF-Chem simulation with multiple observations

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

Hu, Zhiyuan; Zhao, Chun; Huang, Jianping

A fully coupled meteorology-chemistry model (WRF-Chem, the Weather Research and Forecasting model coupled with chemistry) has been configured to conduct quasi-global simulation for 5 years (2010–2014) and evaluated with multiple observation data sets for the first time. The evaluation focuses on the simulation over the trans-Pacific transport region using various reanalysis and observational data sets for meteorological fields and aerosol properties. The simulation generally captures the overall spatial and seasonal variability of satellite retrieved aerosol optical depth (AOD) and absorbing AOD (AAOD) over the Pacific that is determined by the outflow of pollutants and dust and the emissions of marine aerosols.more » The assessment of simulated extinction Ångström exponent (EAE) indicates that the model generally reproduces the variability of aerosol size distributions as seen by satellites. In addition, the vertical profile of aerosol extinction and its seasonality over the Pacific are also well simulated. The difference between the simulation and satellite retrievals can be mainly attributed to model biases in estimating marine aerosol emissions as well as the satellite sampling and retrieval uncertainties. Compared with the surface measurements over the western USA, the model reasonably simulates the observed magnitude and seasonality of dust, sulfate, and nitrate surface concentrations, but significantly underestimates the peak surface concentrations of carbonaceous aerosol likely due to model biases in the spatial and temporal variability of biomass burning emissions and secondary organic aerosol (SOA) production. A sensitivity simulation shows that the trans-Pacific transported dust, sulfate, and nitrate can make significant contribution to surface concentrations over the rural areas of the western USA, while the peaks of carbonaceous aerosol surface concentrations are dominated by the North American emissions. Both the retrievals and simulation show small interannual variability of aerosol characteristics for 2010–2014 averaged over three Pacific sub-regions. Furthermore, the evaluation in this study demonstrates that the WRF-Chem quasi-global simulation can be used for investigating trans-Pacific transport of aerosols and providing reasonable inflow chemical boundaries for the western USA, allowing one to further understand the impact of transported pollutants on the regional air quality and climate with high-resolution nested regional modeling.« less

Trans-Pacific transport and evolution of aerosols: Evaluation of quasi-global WRF-Chem simulation with multiple observations

DOE PAGES

Hu, Zhiyuan; Zhao, Chun; Huang, Jianping; ...

2016-05-10

A fully coupled meteorology-chemistry model (WRF-Chem, the Weather Research and Forecasting model coupled with chemistry) has been configured to conduct quasi-global simulation for 5 years (2010–2014) and evaluated with multiple observation data sets for the first time. The evaluation focuses on the simulation over the trans-Pacific transport region using various reanalysis and observational data sets for meteorological fields and aerosol properties. The simulation generally captures the overall spatial and seasonal variability of satellite retrieved aerosol optical depth (AOD) and absorbing AOD (AAOD) over the Pacific that is determined by the outflow of pollutants and dust and the emissions of marine aerosols.more » The assessment of simulated extinction Ångström exponent (EAE) indicates that the model generally reproduces the variability of aerosol size distributions as seen by satellites. In addition, the vertical profile of aerosol extinction and its seasonality over the Pacific are also well simulated. The difference between the simulation and satellite retrievals can be mainly attributed to model biases in estimating marine aerosol emissions as well as the satellite sampling and retrieval uncertainties. Compared with the surface measurements over the western USA, the model reasonably simulates the observed magnitude and seasonality of dust, sulfate, and nitrate surface concentrations, but significantly underestimates the peak surface concentrations of carbonaceous aerosol likely due to model biases in the spatial and temporal variability of biomass burning emissions and secondary organic aerosol (SOA) production. A sensitivity simulation shows that the trans-Pacific transported dust, sulfate, and nitrate can make significant contribution to surface concentrations over the rural areas of the western USA, while the peaks of carbonaceous aerosol surface concentrations are dominated by the North American emissions. Both the retrievals and simulation show small interannual variability of aerosol characteristics for 2010–2014 averaged over three Pacific sub-regions. Furthermore, the evaluation in this study demonstrates that the WRF-Chem quasi-global simulation can be used for investigating trans-Pacific transport of aerosols and providing reasonable inflow chemical boundaries for the western USA, allowing one to further understand the impact of transported pollutants on the regional air quality and climate with high-resolution nested regional modeling.« less

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

NASA Astrophysics Data System (ADS)

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.

Simulating the characteristics of tropical cyclones over the South West Indian Ocean using a Stretched-Grid Global Climate Model

NASA Astrophysics Data System (ADS)

Maoyi, Molulaqhooa L.; Abiodun, Babatunde J.; Prusa, Joseph M.; Veitch, Jennifer J.

2018-03-01

Tropical cyclones (TCs) are one of the most devastating natural phenomena. This study examines the capability of a global climate model with grid stretching (CAM-EULAG, hereafter CEU) in simulating the characteristics of TCs over the South West Indian Ocean (SWIO). In the study, CEU is applied with a variable increment global grid that has a fine horizontal grid resolution (0.5° × 0.5°) over the SWIO and coarser resolution (1° × 1°—2° × 2.25°) over the rest of the globe. The simulation is performed for the 11 years (1999-2010) and validated against the Joint Typhoon Warning Center (JTWC) best track data, global precipitation climatology project (GPCP) satellite data, and ERA-Interim (ERAINT) reanalysis. CEU gives a realistic simulation of the SWIO climate and shows some skill in simulating the spatial distribution of TC genesis locations and tracks over the basin. However, there are some discrepancies between the observed and simulated climatic features over the Mozambique channel (MC). Over MC, CEU simulates a substantial cyclonic feature that produces a higher number of TC than observed. The dynamical structure and intensities of the CEU TCs compare well with observation, though the model struggles to produce TCs with a deep pressure centre as low as the observed. The reanalysis has the same problem. The model captures the monthly variation of TC occurrence well but struggles to reproduce the interannual variation. The results of this study have application in improving and adopting CEU for seasonal forecasting over the SWIO.

Evaluate Hydrologic Response on Spatiotemporal Characteristics of Rainfall Using High Resolution Radar Rainfall Data and WRF-Hydro Model

NASA Astrophysics Data System (ADS)

Gao, S.; Fang, N. Z.

2017-12-01

A previously developed Dynamic Moving Storm (DMS) generator is a multivariate rainfall model simulating the complex nature of precipitation field: spatial variability, temporal variability, and storm movement. Previous effort by the authors has investigated the sensitivity of DMS parameters on corresponding hydrologic responses by using synthetic storms. In this study, the DMS generator has been upgraded to generate more realistic precipitation field. The dependence of hydrologic responses on rainfall features was investigated by dissecting the precipitation field into rain cells and modifying their spatio-temporal specification individually. To retrieve DMS parameters from radar rainfall data, rain cell segmentation and tracking algorithms were respectively developed and applied on high resolution radar rainfall data (1) to spatially determine the rain cells within individual radar image and (2) to temporally analyze their dynamic behavior. Statistics of DMS parameters were established by processing a long record of rainfall data (10 years) to keep the modification on real storms within the limit of regional climatology. Empirical distributions of the DMS parameters were calculated to reveal any preferential pattern and seasonality. Subsequently, the WRF-Hydro model forced by the remodeled and modified precipitation was used for hydrologic simulation. The study area was the Upper Trinity River Basin (UTRB) watershed, Texas; and two kinds of high resolution radar data i.e. the Next-Generation Radar (NEXRAD) level III Digital Hybrid Reflectivity (DHR) product and Multi-Radar Multi-Sensor (MRMS) precipitation rate product, were utilized to establish parameter statistics and to recreate/remodel historical events respectively. The results demonstrated that rainfall duration is a significant linkage between DMS parameters and their hydrologic impacts—any combination of spatiotemporal characteristics that keep rain cells longer over the catchment will produce higher peak discharge.

Comparison of Measured and Numerically Simulated Turbulence Statistics in a Convective Boundary Layer Over Complex Terrain

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

Rai, Raj K.; Berg, Larry K.; Kosović, Branko

High resolution numerical simulation can provide insight into important physical processes that occur within the planetary boundary layer (PBL). The present work employs large eddy simulation (LES) using the Weather Forecasting and Research (WRF) model, with the LES domain nested within mesoscale simulation, to simulate real conditions in the convective PBL over an area of complex terrain. A multiple nesting approach has been used to downsize the grid spacing from 12.15 km (mesoscale) to 0.03 km (LES). A careful selection of grid spacing in the WRF Meso domain has been conducted to minimize artifacts in the WRF-LES solutions. The WRF-LESmore » results have been evaluated with in situ and remote sensing observations collected during the US Department of Energy-supported Columbia BasinWind Energy Study (CBWES). Comparison of the first- and second-order moments, turbulence spectrum, and probability density function (PDF) of wind speed shows good agreement between the simulations and data. Furthermore, the WRF-LES variables show a great deal of variability in space and time caused by the complex topography in the LES domain. The WRF-LES results show that the flow structures, such as roll vortices and convective cells, vary depending on both the location and time of day. In addition to basic studies related to boundary-layer meteorology, results from these simulations can be used in other applications, such as studying wind energy resources, atmospheric dispersion, fire weather etc.« less

Three-dimensional plant architecture and sunlit-shaded patterns: a stochastic model of light dynamics in canopies.

PubMed

Retkute, Renata; Townsend, Alexandra J; Murchie, Erik H; Jensen, Oliver E; Preston, Simon P

2018-05-25

Diurnal changes in solar position and intensity combined with the structural complexity of plant architecture result in highly variable and dynamic light patterns within the plant canopy. This affects productivity through the complex ways that photosynthesis responds to changes in light intensity. Current methods to characterize light dynamics, such as ray-tracing, are able to produce data with excellent spatio-temporal resolution but are computationally intensive and the resulting data are complex and high-dimensional. This necessitates development of more economical models for summarizing the data and for simulating realistic light patterns over the course of a day. High-resolution reconstructions of field-grown plants are assembled in various configurations to form canopies, and a forward ray-tracing algorithm is applied to the canopies to compute light dynamics at high (1 min) temporal resolution. From the ray-tracer output, the sunlit or shaded state for each patch on the plants is determined, and these data are used to develop a novel stochastic model for the sunlit-shaded patterns. The model is designed to be straightforward to fit to data using maximum likelihood estimation, and fast to simulate from. For a wide range of contrasting 3-D canopies, the stochastic model is able to summarize, and replicate in simulations, key features of the light dynamics. When light patterns simulated from the stochastic model are used as input to a model of photoinhibition, the predicted reduction in carbon gain is similar to that from calculations based on the (extremely costly) ray-tracer data. The model provides a way to summarize highly complex data in a small number of parameters, and a cost-effective way to simulate realistic light patterns. Simulations from the model will be particularly useful for feeding into larger-scale photosynthesis models for calculating how light dynamics affects the photosynthetic productivity of canopies.

Linking a one-dimensional pesticide fate model to a three-dimensional groundwater model to simulate pollution risks of shallow and deep groundwater underlying fractured till.

PubMed

Stenemo, Fredrik; Jørgensen, Peter R; Jarvis, Nicholas

2005-09-01

The one-dimensional pesticide fate model MACRO was loose-linked to the three-dimensional discrete fracture/matrix diffusion model FRAC3DVS to describe transport of the pesticide mecoprop in a fractured moraine till and local sand aquifer (5-5.5 m depth) overlying a regional limestone aquifer (16 m depth) at Havdrup, Denmark. Alternative approaches to describe the upper boundary in the groundwater model were examined. Field-scale simulations were run to compare a uniform upper boundary condition with a spatially variable upper boundary derived from Monte-Carlo simulations with MACRO. Plot-scale simulations were run to investigate the influence of the temporal resolution of the upper boundary conditions for fluxes in the groundwater model and the effects of different assumptions concerning the macropore/fracture connectivity between the two models. The influence of within-field variability of leaching on simulated mecoprop concentrations in the local aquifer was relatively small. A fully transient simulation with FRAC3DVS gave 20 times larger leaching to the regional aquifer compared to the case with steady-state water flow, assuming full connectivity with respect to macropores/fractures across the boundary between the two models. For fully transient simulations 'disconnecting' the macropores/fractures at the interface between the two models reduced leaching by a factor 24. A fully connected, transient simulation with FRAC3DVS, with spatially uniform upper boundary fluxes derived from a MACRO simulation with 'effective' parameters is therefore recommended for assessing leaching risks to the regional aquifer, at this, and similar sites.

Potential for added value in precipitation simulated by high-resolution nested Regional Climate Models and observations

NASA Astrophysics Data System (ADS)

di Luca, Alejandro; de Elía, Ramón; Laprise, René

2012-03-01

Regional Climate Models (RCMs) constitute the most often used method to perform affordable high-resolution regional climate simulations. The key issue in the evaluation of nested regional models is to determine whether RCM simulations improve the representation of climatic statistics compared to the driving data, that is, whether RCMs add value. In this study we examine a necessary condition that some climate statistics derived from the precipitation field must satisfy in order that the RCM technique can generate some added value: we focus on whether the climate statistics of interest contain some fine spatial-scale variability that would be absent on a coarser grid. The presence and magnitude of fine-scale precipitation variance required to adequately describe a given climate statistics will then be used to quantify the potential added value (PAV) of RCMs. Our results show that the PAV of RCMs is much higher for short temporal scales (e.g., 3-hourly data) than for long temporal scales (16-day average data) due to the filtering resulting from the time-averaging process. PAV is higher in warm season compared to cold season due to the higher proportion of precipitation falling from small-scale weather systems in the warm season. In regions of complex topography, the orographic forcing induces an extra component of PAV, no matter the season or the temporal scale considered. The PAV is also estimated using high-resolution datasets based on observations allowing the evaluation of the sensitivity of changing resolution in the real climate system. The results show that RCMs tend to reproduce relatively well the PAV compared to observations although showing an overestimation of the PAV in warm season and mountainous regions.

Revised mineral dust emissions in the atmospheric chemistry-climate model EMAC (MESSy 2.52 DU_Astitha1 KKDU2017 patch)

NASA Astrophysics Data System (ADS)

Klingmüller, Klaus; Metzger, Swen; Abdelkader, Mohamed; Karydis, Vlassis A.; Stenchikov, Georgiy L.; Pozzer, Andrea; Lelieveld, Jos

2018-03-01

To improve the aeolian dust budget calculations with the global ECHAM/MESSy atmospheric chemistry-climate model (EMAC), which combines the Modular Earth Submodel System (MESSy) with the ECMWF/Hamburg (ECHAM) climate model developed at the Max Planck Institute for Meteorology in Hamburg based on a weather prediction model of the European Centre for Medium-Range Weather Forecasts (ECMWF), we have implemented new input data and updates of the emission scheme.The data set comprises land cover classification, vegetation, clay fraction and topography. It is based on up-to-date observations, which are crucial to account for the rapid changes of deserts and semi-arid regions in recent decades. The new Moderate Resolution Imaging Spectroradiometer (MODIS)-based land cover and vegetation data are time dependent, and the effect of long-term trends and variability of the relevant parameters is therefore considered by the emission scheme. All input data have a spatial resolution of at least 0.1° compared to 1° in the previous version, equipping the model for high-resolution simulations.We validate the updates by comparing the aerosol optical depth (AOD) at 550 nm wavelength from a 1-year simulation at T106 (about 1.1°) resolution with Aerosol Robotic Network (AERONET) and MODIS observations, the 10 µm dust AOD (DAOD) with Infrared Atmospheric Sounding Interferometer (IASI) retrievals, and dust concentration and deposition results with observations from the Aerosol Comparisons between Observations and Models (AeroCom) dust benchmark data set. The update significantly improves agreement with the observations and is therefore recommended to be used in future simulations.

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

Herrnstein, Aaron R.

An ocean model with adaptive mesh refinement (AMR) capability is presented for simulating ocean circulation on decade time scales. The model closely resembles the LLNL ocean general circulation model with some components incorporated from other well known ocean models when appropriate. Spatial components are discretized using finite differences on a staggered grid where tracer and pressure variables are defined at cell centers and velocities at cell vertices (B-grid). Horizontal motion is modeled explicitly with leapfrog and Euler forward-backward time integration, and vertical motion is modeled semi-implicitly. New AMR strategies are presented for horizontal refinement on a B-grid, leapfrog time integration,more » and time integration of coupled systems with unequal time steps. These AMR capabilities are added to the LLNL software package SAMRAI (Structured Adaptive Mesh Refinement Application Infrastructure) and validated with standard benchmark tests. The ocean model is built on top of the amended SAMRAI library. The resulting model has the capability to dynamically increase resolution in localized areas of the domain. Limited basin tests are conducted using various refinement criteria and produce convergence trends in the model solution as refinement is increased. Carbon sequestration simulations are performed on decade time scales in domains the size of the North Atlantic and the global ocean. A suggestion is given for refinement criteria in such simulations. AMR predicts maximum pH changes and increases in CO 2 concentration near the injection sites that are virtually unattainable with a uniform high resolution due to extremely long run times. Fine scale details near the injection sites are achieved by AMR with shorter run times than the finest uniform resolution tested despite the need for enhanced parallel performance. The North Atlantic simulations show a reduction in passive tracer errors when AMR is applied instead of a uniform coarse resolution. No dramatic or persistent signs of error growth in the passive tracer outgassing or the ocean circulation are observed to result from AMR.« less

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

NASA Astrophysics Data System (ADS)

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

2013-04-01

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 features of the RCM ALARO-Climate and results of the first model simulations on longer time-scales (1961-1990). The model was driven by the ERA-40/Interim re-analyses and run on the large pan-European integration domain ("ENSEMBLES / Euro-Cordex domain") with spatial resolution of 25 km. The simulated model climate was compared with the gridded observation of air temperature (mean, maximum, minimum) and precipitation from the E-OBS version 7 dataset. The validation of the first ERA-40 simulation has revealed significant cold biases in all seasons (between -4 and -2 °C) and overestimation of precipitation on 20% to 60% in the selected Central Europe target area (0° - 30° eastern longitude ; 40° - 60° northern latitude). The consequent adaptations in the model and their effect on the simulated properties of climate variables are illustrated. 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.1.05/1.1.00/02.0073). The partial support was also provided under the projects P209-11-0956 of the Czech Science Foundation and CZ.1.07/2.4.00/31.0056 (Operational Programme of Education for Competitiveness of Ministry of Education, Youth and Sports of the Czech Republic).

Toward Improved Parameterization of a Meso-Scale Hydrologic Model in a Discontinuous Permafrost, Boreal Forest Ecosystem

NASA Astrophysics Data System (ADS)

Endalamaw, A. M.; Bolton, W. R.; Young, J. M.; Morton, D.; Hinzman, L. D.

2013-12-01

The sub-arctic environment can be characterized as being located in the zone of discontinuous permafrost. Although the distribution of permafrost is site specific, it dominates many of the hydrologic and ecologic responses and functions including vegetation distribution, stream flow, soil moisture, and storage processes. In this region, the boundaries that separate the major ecosystem types (deciduous dominated and coniferous dominated ecosystems) as well as permafrost (permafrost verses non-permafrost) occur over very short spatial scales. One of the goals of this research project is to improve parameterizations of meso-scale hydrologic models in this environment. Using the Caribou-Poker Creeks Research Watershed (CPCRW) as the test area, simulations of the headwater catchments of varying permafrost and vegetation distributions were performed. CPCRW, located approximately 50 km northeast of Fairbanks, Alaska, is located within the zone of discontinuous permafrost and the boreal forest ecosystem. The Variable Infiltration Capacity (VIC) model was selected as the hydrologic model. In CPCRW, permafrost and coniferous vegetation is generally found on north facing slopes and valley bottoms. Permafrost free soils and deciduous vegetation is generally found on south facing slopes. In this study, hydrologic simulations using fine scale vegetation and soil parameterizations - based upon slope and aspect analysis at a 50 meter resolution - were conducted. Simulations were also conducted using downscaled vegetation from the Scenarios Network for Alaska and Arctic Planning (SNAP) (1 km resolution) and soil data sets from the Food and Agriculture Organization (FAO) (approximately 9 km resolution). Preliminary simulation results show that soil and vegetation parameterizations based upon fine scale slope/aspect analysis increases the R2 values (0.5 to 0.65 in the high permafrost (53%) basin; 0.43 to 0.56 in the low permafrost (2%) basin) relative to parameterization based on coarse scale data. These results suggest that using fine resolution parameterizations can be used to improve meso-scale hydrological modeling in this region.

Impacts of spatial resolution and representation of flow connectivity on large-scale simulation of floods

NASA Astrophysics Data System (ADS)

Mateo, Cherry May R.; Yamazaki, Dai; Kim, Hyungjun; Champathong, Adisorn; Vaze, Jai; Oki, Taikan

2017-10-01

Global-scale river models (GRMs) are core tools for providing consistent estimates of global flood hazard, especially in data-scarce regions. Due to former limitations in computational power and input datasets, most GRMs have been developed to use simplified representations of flow physics and run at coarse spatial resolutions. With increasing computational power and improved datasets, the application of GRMs to finer resolutions is becoming a reality. To support development in this direction, the suitability of GRMs for application to finer resolutions needs to be assessed. This study investigates the impacts of spatial resolution and flow connectivity representation on the predictive capability of a GRM, CaMa-Flood, in simulating the 2011 extreme flood in Thailand. Analyses show that when single downstream connectivity (SDC) is assumed, simulation results deteriorate with finer spatial resolution; Nash-Sutcliffe efficiency coefficients decreased by more than 50 % between simulation results at 10 km resolution and 1 km resolution. When multiple downstream connectivity (MDC) is represented, simulation results slightly improve with finer spatial resolution. The SDC simulations result in excessive backflows on very flat floodplains due to the restrictive flow directions at finer resolutions. MDC channels attenuated these effects by maintaining flow connectivity and flow capacity between floodplains in varying spatial resolutions. While a regional-scale flood was chosen as a test case, these findings should be universal and may have significant impacts on large- to global-scale simulations, especially in regions where mega deltas exist.These results demonstrate that a GRM can be used for higher resolution simulations of large-scale floods, provided that MDC in rivers and floodplains is adequately represented in the model structure.

Downscaling essential climate variable soil moisture using multisource data from 2003 to 2010 in China

NASA Astrophysics Data System (ADS)

Wang, Hui-Lin; An, Ru; You, Jia-jun; Wang, Ying; Chen, Yuehong; Shen, Xiao-ji; Gao, Wei; Wang, Yi-nan; Zhang, Yu; Wang, Zhe; Quaye-Ballard, Jonathan Arthur

2017-10-01

Soil moisture plays an important role in the water cycle within the surface ecosystem, and it is the basic condition for the growth of plants. Currently, the spatial resolutions of most soil moisture data from remote sensing range from ten to several tens of km, while those observed in-situ and simulated for watershed hydrology, ecology, agriculture, weather, and drought research are generally <1 km. Therefore, the existing coarse-resolution remotely sensed soil moisture data need to be downscaled. This paper proposes a universal and multitemporal soil moisture downscaling method suitable for large areas. The datasets comprise land surface, brightness temperature, precipitation, and soil and topographic parameters from high-resolution data and active/passive microwave remotely sensed essential climate variable soil moisture (ECV_SM) data with a spatial resolution of 25 km. Using this method, a total of 288 soil moisture maps of 1-km resolution from the first 10-day period of January 2003 to the last 10-day period of December 2010 were derived. The in-situ observations were used to validate the downscaled ECV_SM. In general, the downscaled soil moisture values for different land cover and land use types are consistent with the in-situ observations. Mean square root error is reduced from 0.070 to 0.061 using 1970 in-situ time series observation data from 28 sites distributed over different land uses and land cover types. The performance was also assessed using the GDOWN metric, a measure of the overall performance of the downscaling methods based on the same dataset. It was positive in 71.429% of cases, indicating that the suggested method in the paper generally improves the representation of soil moisture at 1-km resolution.

A general CFD framework for fault-resilient simulations based on multi-resolution information fusion

NASA Astrophysics Data System (ADS)

Lee, Seungjoon; Kevrekidis, Ioannis G.; Karniadakis, George Em

2017-10-01

We develop a general CFD framework for multi-resolution simulations to target multiscale problems but also resilience in exascale simulations, where faulty processors may lead to gappy, in space-time, simulated fields. We combine approximation theory and domain decomposition together with statistical learning techniques, e.g. coKriging, to estimate boundary conditions and minimize communications by performing independent parallel runs. To demonstrate this new simulation approach, we consider two benchmark problems. First, we solve the heat equation (a) on a small number of spatial "patches" distributed across the domain, simulated by finite differences at fine resolution and (b) on the entire domain simulated at very low resolution, thus fusing multi-resolution models to obtain the final answer. Second, we simulate the flow in a lid-driven cavity in an analogous fashion, by fusing finite difference solutions obtained with fine and low resolution assuming gappy data sets. We investigate the influence of various parameters for this framework, including the correlation kernel, the size of a buffer employed in estimating boundary conditions, the coarseness of the resolution of auxiliary data, and the communication frequency across different patches in fusing the information at different resolution levels. In addition to its robustness and resilience, the new framework can be employed to generalize previous multiscale approaches involving heterogeneous discretizations or even fundamentally different flow descriptions, e.g. in continuum-atomistic simulations.

a Spiral-Based Downscaling Method for Generating 30 M Time Series Image Data

NASA Astrophysics Data System (ADS)

Liu, B.; Chen, J.; Xing, H.; Wu, H.; Zhang, J.

2017-09-01

The spatial detail and updating frequency of land cover data are important factors influencing land surface dynamic monitoring applications in high spatial resolution scale. However, the fragmentized patches and seasonal variable of some land cover types (e. g. small crop field, wetland) make it labor-intensive and difficult in the generation of land cover data. Utilizing the high spatial resolution multi-temporal image data is a possible solution. Unfortunately, the spatial and temporal resolution of available remote sensing data like Landsat or MODIS datasets can hardly satisfy the minimum mapping unit and frequency of current land cover mapping / updating at the same time. The generation of high resolution time series may be a compromise to cover the shortage in land cover updating process. One of popular way is to downscale multi-temporal MODIS data with other high spatial resolution auxiliary data like Landsat. But the usual manner of downscaling pixel based on a window may lead to the underdetermined problem in heterogeneous area, result in the uncertainty of some high spatial resolution pixels. Therefore, the downscaled multi-temporal data can hardly reach high spatial resolution as Landsat data. A spiral based method was introduced to downscale low spatial and high temporal resolution image data to high spatial and high temporal resolution image data. By the way of searching the similar pixels around the adjacent region based on the spiral, the pixel set was made up in the adjacent region pixel by pixel. The underdetermined problem is prevented to a large extent from solving the linear system when adopting the pixel set constructed. With the help of ordinary least squares, the method inverted the endmember values of linear system. The high spatial resolution image was reconstructed on the basis of high spatial resolution class map and the endmember values band by band. Then, the high spatial resolution time series was formed with these high spatial resolution images image by image. Simulated experiment and remote sensing image downscaling experiment were conducted. In simulated experiment, the 30 meters class map dataset Globeland30 was adopted to investigate the effect on avoid the underdetermined problem in downscaling procedure and a comparison between spiral and window was conducted. Further, the MODIS NDVI and Landsat image data was adopted to generate the 30m time series NDVI in remote sensing image downscaling experiment. Simulated experiment results showed that the proposed method had a robust performance in downscaling pixel in heterogeneous region and indicated that it was superior to the traditional window-based methods. The high resolution time series generated may be a benefit to the mapping and updating of land cover data.

Spectral quality requirements for effluent identification

NASA Astrophysics Data System (ADS)

Czerwinski, R. N.; Seeley, J. A.; Wack, E. C.

2005-11-01

We consider the problem of remotely identifying gaseous materials using passive sensing of long-wave infrared (LWIR) spectral features at hyperspectral resolution. Gaseous materials are distinguishable in the LWIR because of their unique spectral fingerprints. A sensor degraded in capability by noise or limited spectral resolution, however, may be unable to positively identify contaminants, especially if they are present in low concentrations or if the spectral library used for comparisons includes materials with similar spectral signatures. This paper will quantify the relative importance of these parameters and express the relationships between them in a functional form which can be used as a rule of thumb in sensor design or in assessing sensor capability for a specific task. This paper describes the simulation of remote sensing datacontaining a gas cloud.In each simulation, the spectra are degraded in spectral resolution and through the addition of noise to simulate spectra collected by sensors of varying design and capability. We form a trade space by systematically varying the number of sensor spectral channels and signal-to-noise ratio over a range of values. For each scenario, we evaluate the capability of the sensor for gas identification by computing the ratio of the F-statistic for the truth gas tothe same statistic computed over the rest of the library.The effect of the scope of the library is investigated as well, by computing statistics on the variability of the identification capability as the library composition is varied randomly.

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

NASA Astrophysics Data System (ADS)

Park, Jun; Hwang, Seung-On

2017-11-01

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

High-resolution climate and land surface interactions modeling over Belgium: current state and decennial scale projections

NASA Astrophysics Data System (ADS)

Jacquemin, Ingrid; Henrot, Alexandra-Jane; Beckers, Veronique; Berckmans, Julie; Debusscher, Bos; Dury, Marie; Minet, Julien; Hamdi, Rafiq; Dendoncker, Nicolas; Tychon, Bernard; Hambuckers, Alain; François, Louis

2016-04-01

The interactions between land surface and climate are complex. Climate changes can affect ecosystem structure and functions, by altering photosynthesis and productivity or inducing thermal and hydric stresses on plant species. These changes then impact socio-economic systems, through e.g., lower farming or forestry incomes. Ultimately, it can lead to permanent changes in land use structure, especially when associated with other non-climatic factors, such as urbanization pressure. These interactions and changes have feedbacks on the climate systems, in terms of changing: (1) surface properties (albedo, roughness, evapotranspiration, etc.) and (2) greenhouse gas emissions (mainly CO2, CH4, N2O). In the framework of the MASC project (« Modelling and Assessing Surface Change impacts on Belgian and Western European climate »), we aim at improving regional climate model projections at the decennial scale over Belgium and Western Europe by combining high-resolution models of climate, land surface dynamics and socio-economic processes. The land surface dynamics (LSD) module is composed of a dynamic vegetation model (CARAIB) calculating the productivity and growth of natural and managed vegetation, and an agent-based model (CRAFTY), determining the shifts in land use and land cover. This up-scaled LSD module is made consistent with the surface scheme of the regional climate model (RCM: ALARO) to allow simulations of the RCM with a fully dynamic land surface for the recent past and the period 2000-2030. In this contribution, we analyze the results of the first simulations performed with the CARAIB dynamic vegetation model over Belgium at a resolution of 1km. This analysis is performed at the species level, using a set of 17 species for natural vegetation (trees and grasses) and 10 crops, especially designed to represent the Belgian vegetation. The CARAIB model is forced with surface atmospheric variables derived from the monthly global CRU climatology or ALARO outputs (from a 4 km resolution simulation) for the recent past and the decennial projections. Evidently, these simulations lead to a first analysis of the impact of climate change on carbon stocks (e.g., biomass, soil carbon) and fluxes (e.g., gross and net primary productivities (GPP and NPP) and net ecosystem production (NEP)). The surface scheme is based on two land use/land cover databases, ECOPLAN for the Flemish region and, for the Walloon region, the COS-Wallonia database and the Belgian agricultural statistics for agricultural land. Land use and land cover are fixed through time (reference year: 2007) in these simulations, but a first attempt of coupling between CARAIB and CRAFTY will be made to establish dynamic land use change scenarios for the next decades. A simulation with variable land use would allow an analysis of land use change impacts not only on crop yields and the land carbon budget, but also on climate relevant parameters, such as surface albedo, roughness length and evapotranspiration towards a coupling with the RCM.

Retrieved Products from Simulated Hyperspectral Observations of a Hurricane

NASA Technical Reports Server (NTRS)

Susskind, Joel; Kouvaris, Louis; Iredell, Lena; Blaisdell, John

2015-01-01

Demonstrate via Observing System Simulation Experiments (OSSEs) the potential utility of flying high spatial resolution AIRS class IR sounders on future LEO and GEO missions.The study simulates and analyzes radiances for 3 sounders with AIRS spectral and radiometric properties on different orbits with different spatial resolutions: 1) Control run 13 kilometers AIRS spatial resolution at nadir on LEO in Aqua orbit; 2) 2 kilometer spatial resolution LEO sounder at nadir ARIES; 3) 5 kilometers spatial resolution sounder on a GEO orbit, radiances simulated every 72 minutes.

Mesoscale Effects on Carbon Export: A Global Perspective

NASA Astrophysics Data System (ADS)

Harrison, Cheryl S.; Long, Matthew C.; Lovenduski, Nicole S.; Moore, Jefferson K.

2018-04-01

Carbon export from the surface to the deep ocean is a primary control on global carbon budgets and is mediated by plankton that are sensitive to physical forcing. Earth system models generally do not resolve ocean mesoscale circulation (O(10-100) km), scales that strongly affect transport of nutrients and plankton. The role of mesoscale circulation in modulating export is evaluated by comparing global ocean simulations conducted at 1° and 0.1° horizontal resolution. Mesoscale resolution produces a small reduction in globally integrated export production (<2%) however, the impact on local export production can be large (±50%), with compensating effects in different ocean basins. With mesoscale resolution, improved representation of coastal jets block off-shelf transport, leading to lower export in regions where shelf-derived nutrients fuel production. Export is further reduced in these regions by resolution of mesoscale turbulence, which restricts the spatial area of production. Maximum mixed layer depths are narrower and deeper across the Subantarctic at higher resolution, driving locally stronger nutrient entrainment and enhanced summer export production. In energetic regions with seasonal blooms, such as the Subantarctic and North Pacific, internally generated mesoscale variability drives substantial interannual variation in local export production. These results suggest that biogeochemical tracer dynamics show different sensitivities to transport biases than temperature and salinity, which should be considered in the formulation and validation of physical parameterizations. Efforts to compare estimates of export production from observations and models should account for large variability in space and time expected for regions strongly affected by mesoscale circulation.

Characterization of extreme sea level at the European coast

NASA Astrophysics Data System (ADS)

Elizalde, Alberto; Jorda, Gabriel; Mathis, Moritz; Mikolajewicz, Uwe

2015-04-01

Extreme high sea levels arise as a combination of storm surges and particular high tides events. Future climate simulations not only project changes in the atmospheric circulation, which induces changes in the wind conditions, but also an increase in the global mean sea level by thermal expansion and ice melting. Such changes increase the risk of coastal flooding, which represents a possible hazard for human activities. Therefore, it is important to investigate the pattern of sea level variability and long-term trends at coastal areas. In order to analyze further extreme sea level events at the European coast in the future climate projections, a new setup for the global ocean model MPIOM coupled with the regional atmosphere model REMO is prepared. The MPIOM irregular grid has enhanced resolution in the European region to resolve the North and the Mediterranean Seas (up to 11 x 11 km at the North Sea). The ocean model includes as well the full luni-solar ephemeridic tidal potential for tides simulation. To simulate the air-sea interaction, the regional atmospheric model REMO is interactively coupled to the ocean model over Europe. Such region corresponds to the EuroCORDEX domain with a 50 x 50 km resolution. Besides the standard fluxes of heat, mass (freshwater), momentum and turbulent energy input, the ocean model is also forced with sea level pressure, in order to be able to capture the full variation of sea level. The hydrological budget within the study domain is closed using a hydrological discharge model. With this model, simulations for present climate and future climate scenarios are carried out to study transient changes on the sea level and extreme events. As a first step, two simulations (coupled and uncoupled ocean) driven by reanalysis data (ERA40) have been conducted. They are used as reference runs to evaluate the climate projection simulations. For selected locations at the coast side, time series of sea level are separated on its different components: tides, short time atmospheric process influence (1-30 days), seasonal cycle and interannual variability. Every sea level component is statistically compared with data from local tide gauges.

Non-Gaussian Multi-resolution Modeling of Magnetosphere-Ionosphere Coupling Processes

NASA Astrophysics Data System (ADS)

Fan, M.; Paul, D.; Lee, T. C. M.; Matsuo, T.

2016-12-01

The most dynamic coupling between the magnetosphere and ionosphere occurs in the Earth's polar atmosphere. Our objective is to model scale-dependent stochastic characteristics of high-latitude ionospheric electric fields that originate from solar wind magnetosphere-ionosphere interactions. The Earth's high-latitude ionospheric electric field exhibits considerable variability, with increasing non-Gaussian characteristics at decreasing spatio-temporal scales. Accurately representing the underlying stochastic physical process through random field modeling is crucial not only for scientific understanding of the energy, momentum and mass exchanges between the Earth's magnetosphere and ionosphere, but also for modern technological systems including telecommunication, navigation, positioning and satellite tracking. While a lot of efforts have been made to characterize the large-scale variability of the electric field in the context of Gaussian processes, no attempt has been made so far to model the small-scale non-Gaussian stochastic process observed in the high-latitude ionosphere. We construct a novel random field model using spherical needlets as building blocks. The double localization of spherical needlets in both spatial and frequency domains enables the model to capture the non-Gaussian and multi-resolutional characteristics of the small-scale variability. The estimation procedure is computationally feasible due to the utilization of an adaptive Gibbs sampler. We apply the proposed methodology to the computational simulation output from the Lyon-Fedder-Mobarry (LFM) global magnetohydrodynamics (MHD) magnetosphere model. Our non-Gaussian multi-resolution model results in characterizing significantly more energy associated with the small-scale ionospheric electric field variability in comparison to Gaussian models. By accurately representing unaccounted-for additional energy and momentum sources to the Earth's upper atmosphere, our novel random field modeling approach will provide a viable remedy to the current numerical models' systematic biases resulting from the underestimation of high-latitude energy and momentum sources.

Validation of a new SAFRAN-based gridded precipitation product for Spain and comparisons to Spain02 and ERA-Interim

NASA Astrophysics Data System (ADS)

Quintana-Seguí, Pere; Turco, Marco; Herrera, Sixto; Miguez-Macho, Gonzalo

2017-04-01

Offline land surface model (LSM) simulations are useful for studying the continental hydrological cycle. Because of the nonlinearities in the models, the results are very sensitive to the quality of the meteorological forcing; thus, high-quality gridded datasets of screen-level meteorological variables are needed. Precipitation datasets are particularly difficult to produce due to the inherent spatial and temporal heterogeneity of that variable. They do, however, have a large impact on the simulations, and it is thus necessary to carefully evaluate their quality in great detail. This paper reports the quality of two high-resolution precipitation datasets for Spain at the daily time scale: the new SAFRAN-based dataset and Spain02. SAFRAN is a meteorological analysis system that was designed to force LSMs and has recently been extended to the entirety of Spain for a long period of time (1979/1980-2013/2014). Spain02 is a daily precipitation dataset for Spain and was created mainly to validate regional climate models. In addition, ERA-Interim is included in the comparison to show the differences between local high-resolution and global low-resolution products. The study compares the different precipitation analyses with rain gauge data and assesses their temporal and spatial similarities to the observations. The validation of SAFRAN with independent data shows that this is a robust product. SAFRAN and Spain02 have very similar scores, although the latter slightly surpasses the former. The scores are robust with altitude and throughout the year, save perhaps in summer when a diminished skill is observed. As expected, SAFRAN and Spain02 perform better than ERA-Interim, which has difficulty capturing the effects of the relief on precipitation due to its low resolution. However, ERA-Interim reproduces spells remarkably well in contrast to the low skill shown by the high-resolution products. The high-resolution gridded products overestimate the number of precipitation days, which is a problem that affects SAFRAN more than Spain02 and is likely caused by the interpolation method. Both SAFRAN and Spain02 underestimate high precipitation events, but SAFRAN does so more than Spain02. The overestimation of low precipitation events and the underestimation of intense episodes will probably have hydrological consequences once the data are used to force a land surface or hydrological model.

Using speech sounds to test functional spectral resolution in listeners with cochlear implants

PubMed Central

Winn, Matthew B.; Litovsky, Ruth Y.

2015-01-01

In this study, spectral properties of speech sounds were used to test functional spectral resolution in people who use cochlear implants (CIs). Specifically, perception of the /ba/-/da/ contrast was tested using two spectral cues: Formant transitions (a fine-resolution cue) and spectral tilt (a coarse-resolution cue). Higher weighting of the formant cues was used as an index of better spectral cue perception. Participants included 19 CI listeners and 10 listeners with normal hearing (NH), for whom spectral resolution was explicitly controlled using a noise vocoder with variable carrier filter widths to simulate electrical current spread. Perceptual weighting of the two cues was modeled with mixed-effects logistic regression, and was found to systematically vary with spectral resolution. The use of formant cues was greatest for NH listeners for unprocessed speech, and declined in the two vocoded conditions. Compared to NH listeners, CI listeners relied less on formant transitions, and more on spectral tilt. Cue-weighting results showed moderately good correspondence with word recognition scores. The current approach to testing functional spectral resolution uses auditory cues that are known to be important for speech categorization, and can thus potentially serve as the basis upon which CI processing strategies and innovations are tested. PMID:25786954

Variability of wet troposphere delays over inland reservoirs as simulated by a high-resolution regional climate model

NASA Astrophysics Data System (ADS)

Clark, E.; Lettenmaier, D. P.

2014-12-01

Satellite radar altimetry is widely used for measuring global sea level variations and, increasingly, water height variations of inland water bodies. Existing satellite radar altimeters measure water surfaces directly below the spacecraft (approximately at nadir). Over the ocean, most of these satellites use radiometry to measure the delay of radar signals caused by water vapor in the atmosphere (also known as the wet troposphere delay (WTD)). However, radiometry can only be used to estimate this delay over the largest inland water bodies, such as the Great Lakes, due to spatial resolution issues. As a result, atmospheric models are typically used to simulate and correct for the WTD at the time of observations. The resolutions of these models are quite coarse, at best about 5000 km2 at 30˚N. The upcoming NASA- and CNES-led Surface Water and Ocean Topography (SWOT) mission, on the other hand, will use interferometric synthetic aperture radar (InSAR) techniques to measure a 120-km-wide swath of the Earth's surface. SWOT is expected to make useful measurements of water surface elevation and extent (and storage change) for inland water bodies at spatial scales as small as 250 m, which is much smaller than current altimetry targets and several orders of magnitude smaller than the models used for wet troposphere corrections. Here, we calculate WTD from very high-resolution (4/3-km to 4-km) simulations of the Weather Research and Forecasting (WRF) regional climate model, and use the results to evaluate spatial variations in WTD. We focus on six U.S. reservoirs: Lake Elwell (MT), Lake Pend Oreille (ID), Upper Klamath Lake (OR), Elephant Butte (NM), Ray Hubbard (TX), and Sam Rayburn (TX). The reservoirs vary in climate, shape, use, and size. Because evaporation from open water impacts local water vapor content, we compare time series of WTD over land and water in the vicinity of each reservoir. To account for resolution effects, we examine the difference in WRF-simulated WTD averaged over ECMWF and NCEP-NCAR resolution grid cells and compare the magnitudes of each over reservoirs. Finally, we also test the degree to which, if uncorrected, the WTD would dampen or strengthen measured changes in water levels (and storage) at each reservoir.

Integration of airborne LiDAR data and voxel-based ray tracing to determine high-resolution solar radiation dynamics at the forest floor: implications for improving stand-scale distributed snowmelt models

NASA Astrophysics Data System (ADS)

Musselman, K. N.; Molotch, N. P.; Margulis, S. A.

2012-12-01

Forest architecture dictates sub-canopy solar irradiance and the resulting patterns can vary seasonally and over short spatial distances. These radiation dynamics are thought to have significant implications on snowmelt processes, regional hydrology, and remote sensing signatures. The variability calls into question many assumptions inherent in traditional canopy models (e.g. Beer's Law) when applied at high resolution (i.e. 1 m). We present a method of estimating solar canopy transmissivity using airborne LiDAR data. The canopy structure is represented in 3-D voxel space (i.e. a cubic discretization of a 3-D domain analogous to a pixel representation of a 2-D space). The solar direct beam canopy transmissivity (DBT) is estimated with a ray-tracing algorithm and the diffuse component is estimated from LiDAR-derived effective LAI. Results from one year at five-minute temporal and 1 m spatial resolutions are presented from Sequoia National Park. Compared to estimates from 28 hemispherical photos, the ray-tracing model estimated daily mean DBT with a 10% average error, while the errors from a Beer's-type DBT estimate exceeded 20%. Compared to the ray-tracing estimates, the Beer's-type transmissivity method was unable to resolve complex spatial patterns resulting from canopy gaps, individual tree canopies and boles, and steep variable terrain. The snowmelt model SNOWPACK was applied at locations of ultrasonic snow depth sensors. Two scenarios were tested; 1) a nominal case where canopy model parameters were obtained from hemispherical photographs, and 2) an explicit scenario where the model was modified to accept LiDAR-derived time-variant DBT. The bulk canopy treatment was generally unable to simulate the sub-canopy snowmelt dynamics observed at the depth sensor locations. The explicit treatment reduced error in the snow disappearance date by one week and both positive and negative melt-season SWE biases were reduced. The results highlight the utility of LiDAR canopy measurements and physically based snowmelt models to simulate spatially distributed stand- and slope-scale snowmelt dynamics at resolutions necessary to capture the inherent underlying variability.iDAR-derived solar direct beam canopy transmissivity computed as the daily average for March 1st and May 1st.

Representing soil moisture - precipitation feedbacks in the Sahel: spatial scale and parameterisation

NASA Astrophysics Data System (ADS)

Taylor, C.; Birch, C.; Parker, D.; Guichard, F.; Nikulin, G.; Dixon, N.

2013-12-01

Land surface properties influence the life cycle of convective systems across West Africa via space-time variability in sensible and latent heat fluxes. Previous observational and modelling studies have shown that areas with strong mesoscale variability in vegetation cover or soil moisture induce coherent structures in the daytime planetary boundary layer. In particular, horizontal gradients in sensible heat flux can induce convergence zones which favour the initiation of deep convection. A recent study based on satellite data (Taylor et al. 2011), illustrated the climatological importance of soil moisture gradients in the initiation of long-lived Mesoscale Convective Systems (MCS) in the Sahel. Here we provide a unique assessment of how models of different spatial resolutions represent soil moisture - precipitation feedbacks in the region, and compare their behaviour to observations. Specifically we examine whether the inability of large-scale models to capture the observed preference for afternoon rain over drier soil in semi-arid regions [Taylor et al., 2012] is due to inadequate spatial resolution and/or systematic bias in convective parameterisations. Firstly, we use a convection-permitting simulation at 4km resolution to explore the underlying mechanisms responsible for soil moisture controls on daytime convective initiation in the Sahel. The model reproduces very similar spatial structure as the observations in terms of antecedent soil moisture in the vicinity of a large sample of convective initiations. We then examine how this same model, run at coarser resolution, simulates the feedback of soil moisture on daily rainfall. In particular we examine the impact of switching on the convective parameterisation on rainfall persistence, and compare the findings with 10 regional climate models (RCMs). Finally, we quantify the impact of the feedback on dry-spell return times using a simple statistical model. The results highlight important weaknesses in convective parameterisations which are likely to impact land surface sensitivity studies and hydroclimatic variability on certain time and space scales. Taylor, C.M., Gounou, A., Guichard, F., Harris, P.P., Ellis, R.J.,Couvreux, F., and M. De Kauwe. 2011, Frequency of Sahelian storm initiation enhanced over mesoscale soil-moisture patterns, Nature Geoscience, 4, 430-433, doi:10.1038/ngeo1173 Taylor, C.M., de Jeu, R.A.M., Guichard, F., Harris, P.P, and W.A. Dorigo. 2012, Afternoon rain more likely over drier soils, Nature, 489, 423-426, doi:10.1038/nature11377

Evaluating scale and roughness effects in urban flood modelling using terrestrial LIDAR data

NASA Astrophysics Data System (ADS)

Ozdemir, H.; Sampson, C. C.; de Almeida, G. A. M.; Bates, P. D.

2013-10-01

This paper evaluates the results of benchmark testing a new inertial formulation of the St. Venant equations, implemented within the LISFLOOD-FP hydraulic model, using different high resolution terrestrial LiDAR data (10 cm, 50 cm and 1 m) and roughness conditions (distributed and composite) in an urban area. To examine these effects, the model is applied to a hypothetical flooding scenario in Alcester, UK, which experienced surface water flooding during summer 2007. The sensitivities of simulated water depth, extent, arrival time and velocity to grid resolutions and different roughness conditions are analysed. The results indicate that increasing the terrain resolution from 1 m to 10 cm significantly affects modelled water depth, extent, arrival time and velocity. This is because hydraulically relevant small scale topography that is accurately captured by the terrestrial LIDAR system, such as road cambers and street kerbs, is better represented on the higher resolution DEM. It is shown that altering surface friction values within a wide range has only a limited effect and is not sufficient to recover the results of the 10 cm simulation at 1 m resolution. Alternating between a uniform composite surface friction value (n = 0.013) or a variable distributed value based on land use has a greater effect on flow velocities and arrival times than on water depths and inundation extent. We conclude that the use of extra detail inherent in terrestrial laser scanning data compared to airborne sensors will be advantageous for urban flood modelling related to surface water, risk analysis and planning for Sustainable Urban Drainage Systems (SUDS) to attenuate flow.

Evaluating scale and roughness effects in urban flood modelling using terrestrial LIDAR data

NASA Astrophysics Data System (ADS)

Ozdemir, H.; Sampson, C. C.; de Almeida, G. A. M.; Bates, P. D.

2013-05-01

This paper evaluates the results of benchmark testing a new inertial formulation of the de St. Venant equations, implemented within the LISFLOOD-FP hydraulic model, using different high resolution terrestrial LiDAR data (10 cm, 50 cm and 1 m) and roughness conditions (distributed and composite) in an urban area. To examine these effects, the model is applied to a hypothetical flooding scenario in Alcester, UK, which experienced surface water flooding during summer 2007. The sensitivities of simulated water depth, extent, arrival time and velocity to grid resolutions and different roughness conditions are analysed. The results indicate that increasing the terrain resolution from 1 m to 10 cm significantly affects modelled water depth, extent, arrival time and velocity. This is because hydraulically relevant small scale topography that is accurately captured by the terrestrial LIDAR system, such as road cambers and street kerbs, is better represented on the higher resolution DEM. It is shown that altering surface friction values within a wide range has only a limited effect and is not sufficient to recover the results of the 10 cm simulation at 1 m resolution. Alternating between a uniform composite surface friction value (n = 0.013) or a variable distributed value based on land use has a greater effect on flow velocities and arrival times than on water depths and inundation extent. We conclude that the use of extra detail inherent in terrestrial laser scanning data compared to airborne sensors will be advantageous for urban flood modelling related to surface water, risk analysis and planning for Sustainable Urban Drainage Systems (SUDS) to attenuate flow.

A High Space-Time Resolution Dataset Linking Meteorological Forcing and Hydro-Sedimentary Response in a Mesoscale Mediterranean Catchment (Auzon) of the Ardèche Region, France

NASA Astrophysics Data System (ADS)

Nord, G.; Braud, I.; Boudevillain, B.; Gérard, S.; Molinié, G.; Vandervaere, J. P.; Huza, J.; Le Coz, J.; Dramais, G.; Legout, C.; Berne, A.; Grazioli, J.; Raupach, T.; Van Baelen, J.; Wijbrans, A.; Delrieu, G.; Andrieu, J.; Caliano, M.; Aubert, C.; Teuling, R.; Le Boursicaud, R.; Branger, F.; Vincendon, B.; Horner, I.

2014-12-01

A comprehensive hydrometeorological dataset is presented spanning the period 1 Jan 2011-31 Dec 2014 to improve the understanding and simulation of the hydrological processes leading to flash floods in a mesoscale catchment (Auzon, 116 km2) of the Mediterranean region. The specificity of the dataset is its high space-time resolution, especially concerning rainfall and the hydrological response which is particularly adapted to the highly spatially variable rainfall events that may occur in this region. This type of dataset is rare in scientific literature because of the quantity and type of sensors for meteorology and surface hydrology. Rainfall data include continuous precipitation measured by rain-gages (5 min time step for the research network of 21 rain-gages and 1h time step for the operational network of 9 rain-gages), S-band Doppler dual-polarization radar (1 km2, 5 min resolution), and disdrometers (11 sensors working at 1 min time step). During the special observation period (SOP-1) and enhanced observation period (Sep-Dec 2012, Sep-Dec 2013) of the HyMeX (Hydrological Cycle in the Mediterranean Experiment) project, two X-band radars provided precipitation measurements at very fine spatial and temporal scales (1 ha, 5 min). Meteorological data are taken from the operational surface weather observation stations of Meteo France at the hourly time resolution (6 stations in the region of interest). The monitoring of surface hydrology and suspended sediment is multi-scale and based on nested catchments. Three hydrometric stations measure water discharge and additional physico-chemical variables at a 2-10 min time resolution. Two experimental plots monitor overland flow and erosion at 1 min time resolution on a hillslope with vineyard. A network of 11 gauges continuously measures water level and temperature in headwater subcatchments at a time resolution of 2-5 min. A network of soil moisture sensors enable the continuous measurement of soil volumetric water content at 20 min time resolution at 9 sites. Additionally, opportunistic observations (soil moisture measurements and stream gauging) were performed during floods between 2012 and 2014. The data are appropriate for understanding rainfall variability, improving areal rainfall estimations and progress in distributed hydrological modelling.

A High Space-Time Resolution Dataset Linking Meteorological Forcing and Hydro-Sedimentary Response in a Mesoscale Mediterranean Catchment (Auzon) of the Ardèche Region, France

NASA Astrophysics Data System (ADS)

Nord, G.; Braud, I.; Boudevillain, B.; Gérard, S.; Molinié, G.; Vandervaere, J. P.; Huza, J.; Le Coz, J.; Dramais, G.; Legout, C.; Berne, A.; Grazioli, J.; Raupach, T.; Van Baelen, J.; Wijbrans, A.; Delrieu, G.; Andrieu, J.; Caliano, M.; Aubert, C.; Teuling, R.; Le Boursicaud, R.; Branger, F.; Vincendon, B.; Horner, I.

2015-12-01

A comprehensive hydrometeorological dataset is presented spanning the period 1 Jan 2011-31 Dec 2014 to improve the understanding and simulation of the hydrological processes leading to flash floods in a mesoscale catchment (Auzon, 116 km2) of the Mediterranean region. The specificity of the dataset is its high space-time resolution, especially concerning rainfall and the hydrological response which is particularly adapted to the highly spatially variable rainfall events that may occur in this region. This type of dataset is rare in scientific literature because of the quantity and type of sensors for meteorology and surface hydrology. Rainfall data include continuous precipitation measured by rain-gages (5 min time step for the research network of 21 rain-gages and 1h time step for the operational network of 9 rain-gages), S-band Doppler dual-polarization radar (1 km2, 5 min resolution), and disdrometers (11 sensors working at 1 min time step). During the special observation period (SOP-1) and enhanced observation period (Sep-Dec 2012, Sep-Dec 2013) of the HyMeX (Hydrological Cycle in the Mediterranean Experiment) project, two X-band radars provided precipitation measurements at very fine spatial and temporal scales (1 ha, 5 min). Meteorological data are taken from the operational surface weather observation stations of Meteo France at the hourly time resolution (6 stations in the region of interest). The monitoring of surface hydrology and suspended sediment is multi-scale and based on nested catchments. Three hydrometric stations measure water discharge and additional physico-chemical variables at a 2-10 min time resolution. Two experimental plots monitor overland flow and erosion at 1 min time resolution on a hillslope with vineyard. A network of 11 gauges continuously measures water level and temperature in headwater subcatchments at a time resolution of 2-5 min. A network of soil moisture sensors enable the continuous measurement of soil volumetric water content at 20 min time resolution at 9 sites. Additionally, opportunistic observations (soil moisture measurements and stream gauging) were performed during floods between 2012 and 2014. The data are appropriate for understanding rainfall variability, improving areal rainfall estimations and progress in distributed hydrological modelling.

Simulating Halos with the Caterpillar Project

NASA Astrophysics Data System (ADS)

Kohler, Susanna

2016-04-01

The Caterpillar Project is a beautiful series of high-resolution cosmological simulations. The goal of this project is to examine the evolution of dark-matter halos like the Milky Ways, to learn about how galaxies like ours formed. This immense computational project is still in progress, but the Caterpillar team is already providing a look at some of its first results.Lessons from Dark-Matter HalosWhy simulate the dark-matter halos of galaxies? Observationally, the formation history of our galaxy is encoded in galactic fossil record clues, like the tidal debris from disrupted satellite galaxies in the outer reaches of our galaxy, or chemical abundance patterns throughout our galactic disk and stellar halo.But to interpret this information in a way that lets us learn about our galaxys history, we need to first test galaxy formation and evolution scenarios via cosmological simulations. Then we can compare the end result of these simulations to what we observe today.This figure illustrates the difference that mass resolution makes. In the left panel, the mass resolution is 1.5*10^7 solar masses per particle. In the right panel, the mass resolution is 3*10^4 solar masses per particle [Griffen et al. 2016]A Computational ChallengeDue to how computationally expensive such simulations are, previous N-body simulations of the growth of Milky-Way-like halos have consisted of only one or a few halos each. But in order to establish a statistical understanding of how galaxy halos form and find out whether the Milky Ways halo is typical or unusual! it is necessary to simulate a larger number of halos.In addition, in order to accurately follow the formation and evolution of substructure within the dark-matter halos, these simulations must be able to resolve the smallest dwarf galaxies, which are around a million solar masses. This requires an extremely high mass resolution, which adds to the computational expense of the simulation.First OutcomesThese are the challenges faced by the Caterpillar Project, detailed in a recently published paper led by Brendan Griffen (Massachusetts Institute of Technology). The Caterpillar Project was designed to simulate 70 Milky-Way-size halos (quadrupling the total number of halos that have been simulated in the past!) at a high mass resolution (10,000 solar masses per particle) and time resolution (5 Myr per snapshot). The project is extremely computationally intense, requiring 14 million CPU hours and 700 TB of data storage!Mass evolution of the first 24 Caterpillar halos (selected to be Milky-Way-size at z=0). The inset panel shows the mass evolution normalized by the halo mass at z=0, demonstrating the highly varied evolution these different halos undergo. [Griffen et al. 2016]In this first study, the Griffen and collaboratorsshow the end states for the first 24 halos of the project, evolved from a large redshift to today (z=0). They use these initialresults to demonstrate the integrity of their data and the utility of their methods, which include new halo-finding techniques that recover more substructure within each halo.The first results from the Caterpillar Project are already enough to show clear general trends, such as the highly variable paths the different halos take as they merge, accrete, and evolve, as well as how different their ends states can be. Statistically examining the evolution of these halos is an importantnext step in providinginsight intothe origin and evolution of the Milky Way, and helping us to understand how our galaxy differs from other galaxies of similar mass. Keep an eye out for future results from this project!BonusCheck out this video (make sure to watch in HD!) of how the first 24 Milky-Way-like halos from the Caterpillar simulations form. Seeingthese halos evolve simultaneously is an awesome way to identifythe similarities and differences between them.CitationBrendan F. Griffen et al 2016 ApJ 818 10. doi:10.3847/0004-637X/818/1/10

The influence of model spatial resolution on simulated ozone and fine particulate matter for Europe: implications for health impact assessments

NASA Astrophysics Data System (ADS)

Fenech, Sara; Doherty, Ruth M.; Heaviside, Clare; Vardoulakis, Sotiris; Macintyre, Helen L.; O'Connor, Fiona M.

2018-04-01

We examine the impact of model horizontal resolution on simulated concentrations of surface ozone (O3) and particulate matter less than 2.5 µm in diameter (PM2.5), and the associated health impacts over Europe, using the HadGEM3-UKCA chemistry-climate model to simulate pollutant concentrations at a coarse (˜ 140 km) and a finer (˜ 50 km) resolution. The attributable fraction (AF) of total mortality due to long-term exposure to warm season daily maximum 8 h running mean (MDA8) O3 and annual-average PM2.5 concentrations is then calculated for each European country using pollutant concentrations simulated at each resolution. Our results highlight a seasonal variation in simulated O3 and PM2.5 differences between the two model resolutions in Europe. Compared to the finer resolution results, simulated European O3 concentrations at the coarse resolution are higher on average in winter and spring (˜ 10 and ˜ 6 %, respectively). In contrast, simulated O3 concentrations at the coarse resolution are lower in summer and autumn (˜ -1 and ˜ -4 %, respectively). These differences may be partly explained by differences in nitrogen dioxide (NO2) concentrations simulated at the two resolutions. Compared to O3, we find the opposite seasonality in simulated PM2.5 differences between the two resolutions. In winter and spring, simulated PM2.5 concentrations are lower at the coarse compared to the finer resolution (˜ -8 and ˜ -6 %, respectively) but higher in summer and autumn (˜ 29 and ˜ 8 %, respectively). Simulated PM2.5 values are also mostly related to differences in convective rainfall between the two resolutions for all seasons. These differences between the two resolutions exhibit clear spatial patterns for both pollutants that vary by season, and exert a strong influence on country to country variations in estimated AF for the two resolutions. Warm season MDA8 O3 levels are higher in most of southern Europe, but lower in areas of northern and eastern Europe when simulated at the coarse resolution compared to the finer resolution. Annual-average PM2.5 concentrations are higher across most of northern and eastern Europe but lower over parts of southwest Europe at the coarse compared to the finer resolution. Across Europe, differences in the AF associated with long-term exposure to population-weighted MDA8 O3 range between -0.9 and +2.6 % (largest positive differences in southern Europe), while differences in the AF associated with long-term exposure to population-weighted annual mean PM2.5 range from -4.7 to +2.8 % (largest positive differences in eastern Europe) of the total mortality. Therefore this study, with its unique focus on Europe, demonstrates that health impact assessments calculated using modelled pollutant concentrations, are sensitive to a change in model resolution by up to ˜ ±5 % of the total mortality across Europe.

Quantifying Diurnal and Spatial Variations in CO2 Concentrations and Partial Columns using High-Resolution Global Model Simulations

NASA Astrophysics Data System (ADS)

Pawson, S.; Nielsen, J.; Ott, L. E.; Darmenov, A.; Putman, W.

2015-12-01

Model-data fusion approaches, such as global inverse modeling for surface flux estimation, have traditionally been performed at spatial resolutions of several tens to a few hundreds of kilometers. Use of such coarse scales presents a fundamental limitation in reconciling the modeled field with both the atmospheric observations and the distribution of surface emissions and uptake. Emissions typically occur on small scales, including point sources (e.g. power plants, forest fires) or with inhomegeneous structure. Biological uptake can have spatial variations related to complex, diverse vegetation, etc. Atmospheric observations of CO2 are either surface based, providing information at a single point, or space based with a finite-sized footprint. For instance, GOSAT and OCO-2 have footprint sizes of around 10km and proposed active sensors (such as ASCENDS) will likely have even finer footprints. One important aspect of reconciling models to measurements is the representativeness of the observation for the model field, and this depends on the generally unknown spatio-temporal variations of the CO2 field around the measurement location and time. This work presents an assessment of the global spatio-temporal variations of the CO2 field using the "7km GEOS-5 Nature Run" (7km-G5NR), which includes CO2 emissions and uptake mapped to the finest possible resolution. Results are shown for surface CO2 concentrations, total-column CO2, and separate upper and lower tropospheric columns. Spatial variability is shown to be largest in regions with strong point sources and at night in regions with complex terrain, especially where biological processes dominate the local CO2 fluxes, where the day-night differences are also most marked. The spatio-temporal variations are strongest for surface concentrations and for lower tropospheric CO2. While these results are largely anticipated, these high resolution simulations provide quantitative estimates of the global nature of spatio-temporal CO2 variability. Implications for characterizing representativeness of passive CO2 observations will be discussed. Differences between daytime and nighttime structures will be considered in light of active CO2 sensors. Finally, some possible limitations of the model will be highlighted, using some global 3-km simulations.

Allocating emissions to 4 km and 1 km horizontal spatial resolutions and its impact on simulated NOx and O3 in Houston, TX

NASA Astrophysics Data System (ADS)

Pan, Shuai; Choi, Yunsoo; Roy, Anirban; Jeon, Wonbae

2017-09-01

A WRF-SMOKE-CMAQ air quality modeling system was used to investigate the impact of horizontal spatial resolution on simulated nitrogen oxides (NOx) and ozone (O3) in the Greater Houston area (a non-attainment area for O3). We employed an approach recommended by the United States Environmental Protection Agency to allocate county-based emissions to model grid cells in 1 km and 4 km horizontal grid resolutions. The CMAQ Integrated Process Rate analyses showed a substantial difference in emissions contributions between 1 and 4 km grids but similar NOx and O3 concentrations over urban and industrial locations. For example, the peak NOx emissions at an industrial and urban site differed by a factor of 20 for the 1 km and 8 for the 4 km grid, but simulated NOx concentrations changed only by a factor of 1.2 in both cases. Hence, due to the interplay of the atmospheric processes, we cannot expect a similar level of reduction of the gas-phase air pollutants as the reduction of emissions. Both simulations reproduced the variability of NASA P-3B aircraft measurements of NOy and O3 in the lower atmosphere (from 90 m to 4.5 km). Both simulations provided similar reasonable predictions at surface, while 1 km case depicted more detailed features of emissions and concentrations in heavily polluted areas, such as highways, airports, and industrial regions, which are useful in understanding the major causes of O3 pollution in such regions, and to quantify transport of O3 to populated communities in urban areas. The Integrated Reaction Rate analyses indicated a distinctive difference of chemistry processes between the model surface layer and upper layers, implying that correcting the meteorological conditions at the surface may not help to enhance the O3 predictions. The model-observation O3 bias in our studies (e.g., large over-prediction during the nighttime or along Gulf of Mexico coastline), were due to uncertainties in meteorology, chemistry or other processes. Horizontal grid resolution is unlikely the major contributor to these biases.

Aerosol indirect effects on summer precipitation in a regional climate model for the Euro-Mediterranean region

NASA Astrophysics Data System (ADS)

Da Silva, Nicolas; Mailler, Sylvain; Drobinski, Philippe

2018-03-01

Aerosols affect atmospheric dynamics through their direct and semi-direct effects as well as through their effects on cloud microphysics (indirect effects). The present study investigates the indirect effects of aerosols on summer precipitation in the Euro-Mediterranean region, which is located at the crossroads of air masses carrying both natural and anthropogenic aerosols. While it is difficult to disentangle the indirect effects of aerosols from the direct and semi-direct effects in reality, a numerical sensitivity experiment is carried out using the Weather Research and Forecasting (WRF) model, which allows us to isolate indirect effects, all other effects being equal. The Mediterranean hydrological cycle has often been studied using regional climate model (RCM) simulations with parameterized convection, which is the approach we adopt in the present study. For this purpose, the Thompson aerosol-aware microphysics scheme is used in a pair of simulations run at 50 km resolution with extremely high and low aerosol concentrations. An additional pair of simulations has been performed at a convection-permitting resolution (3.3 km) to examine these effects without the use of parameterized convection. While the reduced radiative flux due to the direct effects of the aerosols is already known to reduce precipitation amounts, there is still no general agreement on the sign and magnitude of the aerosol indirect forcing effect on precipitation, with various processes competing with each other. Although some processes tend to enhance precipitation amounts, some others tend to reduce them. In these simulations, increased aerosol loads lead to weaker precipitation in the parameterized (low-resolution) configuration. The fact that a similar result is obtained for a selected area in the convection-permitting (high-resolution) configuration allows for physical interpretations. By examining the key variables in the model outputs, we propose a causal chain that links the aerosol effects on microphysics to their simulated effect on precipitation, essentially through reduction of the radiative heating of the surface and corresponding reductions of surface temperature, resulting in increased atmospheric stability in the presence of high aerosol loads.

Modeling circulation patterns induced by spatial cross-shore wind variability in a small-size coastal embayment

NASA Astrophysics Data System (ADS)

Cerralbo, Pablo; Espino, Manuel; Grifoll, Manel

2016-08-01

This contribution shows the importance of the cross-shore spatial wind variability in the water circulation in a small-sized micro-tidal bay. The hydrodynamic wind response at Alfacs Bay (Ebro River delta, NW Mediterranean Sea) is investigated with a numerical model (ROMS) supported by in situ observations. The wind variability observed in meteorological measurements is characterized with meteorological model (WRF) outputs. From the hydrodynamic simulations of the bay, the water circulation response is affected by the cross-shore wind variability, leading to water current structures not observed in the homogeneous-wind case. If the wind heterogeneity response is considered, the water exchange in the longitudinal direction increases significantly, reducing the water exchange time by around 20%. Wind resolutions half the size of the bay (in our case around 9 km) inhibit cross-shore wind variability, which significantly affects the resultant circulation pattern. The characteristic response is also investigated using idealized test cases. These results show how the wind curl contributes to the hydrodynamic response in shallow areas and promotes the exchange between the bay and the open sea. Negative wind curl is related to the formation of an anti-cyclonic gyre at the bay's mouth. Our results highlight the importance of considering appropriate wind resolution even in small-scale domains (such as bays or harbors) to characterize the hydrodynamics, with relevant implications in the water exchange time and the consequent water quality and ecological parameters.

Hazardous Convective Weather in the Central United States: Present and Future

NASA Astrophysics Data System (ADS)

Liu, C.; Ikeda, K.; Rasmussen, R.

2017-12-01

Two sets of 13-year continental-scale convection-permitting simulations were performed using the 4-km-resolution WRF model. They consist of a retrospective simulation, which downscales the ERA-Interim reanalysis during the period October 2000 - September 2013, and a future climate sensitivity simulation for the same period based on the perturbed reanalysis-derived boundary conditions with the CMIP5 ensemble-mean high-end emission scenario climate change. The evaluation of the retrospective simulation indicates that the model is able to realistically reproduce the main characteristics of deep precipitating convection observed in the current climate such as the spectra of convective population and propagating mesoscale convective systems (MCSs). It is also shown that severe convection and associated MCS will increase in frequency and intensity, implying a potential increase in high impact convective weather in a future warmer climate. In this study, the warm-season hazardous convective weather (i.e., tonadoes, hails and damaging gusty wind) in the central United states is examined using these 4-km downscaling simulations. First, a model-based proxy for hazardous convective weather is derived on the basis of a set of characteristic meteorological variables such as the model composite radar reflectivity, updraft helicity, vertical wind shear, and low-level wind. Second, the developed proxy is applied to the retrospective simulation for estimate of the model hazardous weather events during the historical period. Third, the simulated hazardous weather statistics are evaluated against the NOAA severe weather reports. Lastly, the proxy is applied to the future climate simulation for the projected change of hazardous convective weather in response to global warming. Preliminary results will be reported at the 2017 AGU session "High Resolution Climate Modeling".

On the generation of climate model ensembles

NASA Astrophysics Data System (ADS)

Haughton, Ned; Abramowitz, Gab; Pitman, Andy; Phipps, Steven J.

2014-10-01

Climate model ensembles are used to estimate uncertainty in future projections, typically by interpreting the ensemble distribution for a particular variable probabilistically. There are, however, different ways to produce climate model ensembles that yield different results, and therefore different probabilities for a future change in a variable. Perhaps equally importantly, there are different approaches to interpreting the ensemble distribution that lead to different conclusions. Here we use a reduced-resolution climate system model to compare three common ways to generate ensembles: initial conditions perturbation, physical parameter perturbation, and structural changes. Despite these three approaches conceptually representing very different categories of uncertainty within a modelling system, when comparing simulations to observations of surface air temperature they can be very difficult to separate. Using the twentieth century CMIP5 ensemble for comparison, we show that initial conditions ensembles, in theory representing internal variability, significantly underestimate observed variance. Structural ensembles, perhaps less surprisingly, exhibit over-dispersion in simulated variance. We argue that future climate model ensembles may need to include parameter or structural perturbation members in addition to perturbed initial conditions members to ensure that they sample uncertainty due to internal variability more completely. We note that where ensembles are over- or under-dispersive, such as for the CMIP5 ensemble, estimates of uncertainty need to be treated with care.

Identification of Hard X-ray Sources in Galactic Globular Clusters: Simbol-X Simulations

NASA Astrophysics Data System (ADS)

Servillat, M.

2009-05-01

Globular clusters harbour an excess of X-ray sources compared to the number of X-ray sources in the Galactic plane. It has been proposed that many of these X-ray sources are cataclysmic variables that have an intermediate magnetic field, i.e. intermediate polars, which remains to be confirmed and understood. We present here several methods to identify intermediate polars in globular clusters from multiwavelength analysis. First, we report on XMM-Newton, Chandra and HST observations of the very dense Galactic globular cluster NGC 2808. By comparing UV and X-ray properties of the cataclysmic variable candidates, the fraction of intermediate polars in this cluster can be estimated. We also present the optical spectra of two cataclysmic variables in the globular cluster M 22. The HeII (4868 Å) emission line in these spectra could be related to the presence of a magnetic field in these objects. Simulations of Simbol-X observations indicate that the angular resolution is sufficient to study X-ray sources in the core of close, less dense globular clusters, such as M 22. The sensitivity of Simbol-X in an extended energy band up to 80 keV will allow us to discriminate between hard X-ray sources (such as magnetic cataclysmic variables) and soft X-ray sources (such as chromospherically active binaries).