Engineering Papers⌕ Search

SEARCH · Engineering Papers

Results for “spatial variability”

Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 1,171 records · Page 65
All sourcesNASA NTRSDOE OSTI
DOE OSTI2025

Integrating Contaminant Source Indicators, Water Quality Measures, and Ecotoxicity to Characterize Contaminant Mixtures and Per- and Polyfluoroalkyl Substance (PFAS) Variability in an Urban Watershed

Thousands of chemical contaminants threaten watersheds but are time and cost prohibitive to monitor. Identifying their sources, transport, and ecological risk is limited in heterogeneous urban watersheds. We present an integrative watershed approach using source-specific indicator compounds, common water quality measures, and ecotoxicity assays to examine the distribution of contaminant mixtures in an urbanized watershed. Indicator compound concentrations were temporally and spatially distributed for treated/untreated sewage (sucralose, artificial sweetener), road runoff (diphenyl-guanidine [DPG] and 6PPD-quinone [6PPD-Q], automobile tire additives), and lawncare runoff (aminomethanephosphonic acid (AMPA), major degradant of the herbicide glyphosate). Sucralose was predominately sourced from treated wastewater; measurable concentrations in tributaries indicated raw sewage inputs. DPG and 6PPD-Q concentrations correlated to road density during base flow and were elevated during stormflow. AMPA was measurable spring through fall, especially where lawns were dense. When specific sources dominated flow, water quality measures correlated with wastewater (sulfate, potassium, chloride, and sodium) and road runoff (chromium and lead) indicators. The limited behavioral toxicity observed in exposed zebrafish (Danio rerio) (18%) was not well explained by source-indicators. PFAS concentrations were highly variable spatially but not well explained by our source-specific indicator compounds. Here, more costly compound-specific monitoring may be necessary when multiple sources exist or when unexpected toxicity trends occur.

computer simulations↗
NASA NTRS2017

Comparing Proxy and Model Estimates of Hydroclimate Variability and Change over the Common Era

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.

Common Era↗
NASA NTRS1979

AVE-SESAME 1: 25-MB sounding data

Seven atmospheric variability experiments (AVE), two atmospheric variability and severe storms experiments (AVSSE), and six atmospheric variability experiment-severe environmental storm and mesoscale experiments (AVE-SESAME) conducted by NASA are discussed. The dates, observation times, and data reports for each of the experiments for which data was processed are listed. The AVE experiments were conducted primarily to study atmospheric variability with emphasis on spatial and temporal in atmospheric structure that can be detected from soundings taken at 3 hr intervals but not seen in soundings taken at 12 hr intervals. The AVSSE experiments were conducted to study atmospheric structure and variability associated with severe storms combining both rawinsonde and aircraft data to provide information on near storm environments. The method of processing is discussed, estimates of the rms errors in the data are presented, an example of contact data is given, and soundings are listed which exhibited abnormal characteristics.

Gerhard, M. L.↗
DOE OSTI2022

H α emission in local galaxies: star formation, time variability, and the diffuse ionized gas

ABSTRACT The nebular recombination line H α is widely used as a star formation rate (SFR) indicator in the local and high-redshift Universe. We present a detailed H α radiative transfer study of high-resolution isolated Milky-Way and Large Magellanic Cloud simulations that include radiative transfer, non-equilibrium thermochemistry, and dust evolution. We focus on the spatial morphology and temporal variability of the H α emission, and its connection to the underlying gas and star formation properties. The H α and H β radial and vertical surface brightness profiles are in excellent agreement with observations of nearby galaxies. We find that the fraction of H α emission from collisional excitation amounts to fcol ∼ 5–$10{{\ \rm per\ cent}}$, only weakly dependent on radius and vertical height, and that scattering boosts the H α luminosity by $\sim 40{{\ \rm per\ cent}}$. The dust correction via the Balmer decrement works well (intrinsic H α emission recoverable within 25 per cent), though the dust attenuation law depends on the amount of attenuation itself both on spatially resolved and integrated scales. Important for the understanding of the H α–SFR connection is the dust and helium absorption of ionizing radiation (Lyman continuum [LyC] photons), which are about $f_{\rm abs}\approx 28{{\ \rm per\ cent}}$ and $f_{\rm He}\approx 9{{\ \rm per\ cent}}$, respectively. Together with an escape fraction of $f_{\rm esc}\approx 6{{\ \rm per\ cent}}$, this reduces the available budget for hydrogen line emission by nearly half ($f_{\rm H}\approx 57{{\ \rm per\ cent}}$). We discuss the impact of the diffuse ionized gas, showing – among other things – that the extraplanar H α emission is powered by LyC photons escaping the disc. Future applications of this framework to cosmological (zoom-in) simulations will assist in the interpretation of spectroscopy of high-redshift galaxies with the upcoming James Webb Space Telescope.

79 ASTRONOMY AND ASTROPHYSICS↗
NASA NTRS1998

Characterizing Mediterranean Land Surfaces as Component of the Regional Climate System by Remote Sensing

Extensive areas in the Mediterranean region are subject to land degradation and desertification. The high variability of the coupling between the surface and the atmosphere affects the regional climate. Relevant surface characteristics, such as spectral reflectance, surface emissivity in the thermal-infrared region, and vegetation indices, serve as "primary" level indicators for the state of the surface. Their spatial, seasonal and interannual variability can be monitored from satellites. Using relationships between these primary data and combining them with prior information about the land surfaces (such as topography, dominant soil type, land use, collateral ground measurements and models), a second layer of information is built up which specifies the land surfaces as a component of the regional climate system. To this category of parameters which are directly involved in the exchange of energy, momentum and mass between the surface and the atmosphere, belong broadband albedo, thermodynamic surface temperature, vegetation types, vegetation cover density, soil top moisture, and soil heat flux. Information about these parameters finally leads to the computation of sensible and latent heat fluxes. The methodology was tested with pilot data sets. Full resolution, properly calibrated and normalized NOAA-AVHRR multi-annual primary data sets are presently compiled for the whole Mediterranean area, to study interannual variability and longer term trends.

Bolle, H.-J.↗
NASA NTRS1989

An investigation of a mathematical model of an optically pumped Ti(3+):Al2O3 laser system

During the last several years, solid state lasers were developed that have the potential for meeting rigorous performance requirements for space-based remote sensing of the atmosphere. In order to design a stable and efficient laser and to understand the effect on laser output of changes in the physical and design parameters, an understanding of the development of the dynamical processes of the laser is necessary. Typically, the dynamical processes in a laser system are investigated via rate equations describing the evolution of the occupancy in the electronic levels and of the photon density in the laser cavity. There are two approaches to this type of study. Most often, for the sake of simplicity, the spatial variations of the dynamic variables in the laser system are disregarded and the mathematical model consists of a system of first order nonlinear ordinary differential equations (ODE). The second approach is to take into account both spatial and temporal variations in the dynamic variables in the laser cavity. The resulting model consists of a first order semilinear system of partial differential equations (PDE). The model which was studied was studied was generic in the sense that it was a four-level laser system, but the parameters used in the numerical study were specific to Titanium-doped sapphire. For simplicity, a constant, spatially uniform pumping scheme was considered. In addition, a simplification of the model was made so that it treats a single lasing wavelength with a narrow bandwidth. The purpose was to investigate both versions of the mathematical model and to determine whether the numerical solutions are similar both qualitatively and quantitatively. The systems of ordinary differential equations were solved numerically using a Runge-Kutta-Fehlberg algorithm which was very efficient for typical values of the physical parameters. A numerical scheme, based on the Modified Euler method, for computing solutions to the system of partial differential equations was developed and implemented. The PDE model was solved numerically at the expense of greatly increased computer time.

Roberts, Lila F.↗
NASA NTRS2021

Climate Drivers of Arctic Tundra Variability and Change Using an Indicators Framework

This study applies an indicators framework to investigate climate drivers of tundra vegetation trends and variability over the 1982–2019 period. Previously known indicators relevant for tundra productivity (summer warmth index (SWI), coastal spring sea-ice (SI) area, coastal summer open-water (OW)) and three additional indicators (continentality, summer precipitation, and the Arctic Dipole (AD): second mode of sea level pressure variability) are analyzed with maximum annual Normalized Difference Vegetation Index (MaxNDVI) and the sum of summer bi-weekly (time-integrated) NDVI (TI-NDVI) from the Advanced Very High Resolution Radiometer time-series. Climatological mean, trends, and correlations between variables are presented. Changes in SI continue to drive variations in the other indicators. As spring SI has decreased, summer OW, summer warmth, MaxNDVI, and TI-NDVI have increased. However, the initial very strong upward trends in previous studies for MaxNDVI and TI-NDVI are weakening and becoming spatially and temporally more variable as the ice retreats from the coastal areas. TI-NDVI has declined over the last decade particularly over High Arctic regions and southwest Alaska. The continentality index (CI) (maximum minus minimum monthly temperatures) is decreasing across the tundra, more so over North America than Eurasia. The relationship has weakened between SI and SWI and TI-NDVI, as the maritime influence of OW has increased along with total precipitation. The winter AD is correlated in Eurasia with spring SI, summer OW, MaxNDVI, TI-NDVI, the CI and total summer precipitation. This winter connection to tundra emphasizes the role of SI in driving the summer indicators. The winter (DJF) AD drives SI variations which in turn shape summer OW, the atmospheric SWI and NDVI anomalies. The winter and spring indicators represent potential predictors of tundra vegetation productivity a season or two in advance of the growing season.

Uma S. Bhatt↗
NASA NTRS2020

150 Shades of Green: Using the Full Spectrum of Remote Sensing Reflectance to Elucidate Color Shifts in the Ocean

This article proposes a simple and intuitive classification system by which to define full spectral remote sensing reflectance (Rrs(λ)) data with a quantitative output that enables a more manageable handling of spectral information for aquatic science applications. The weighted harmonic mean of the Rrs(λ) wavelengths outputs an Apparent Visible Wavelength (in units of nanometers), representing a one-dimensional geophysical metric of color that is inherently correlated to spectral shape. This dimensionality reduction of spectral information combined with the output along a continuum of wavelength values offers a robust and user-friendly means to describe and analyze spectral Rrs(λ) in terms of spatial and temporal trends and variability. The uncertainty in the algorithm's estimation of spectral shape is demonstrated on a global scale, in addition to the utility of the algorithm to discern spectral-spatial-temporal trends in the ocean, on a per-pixel basis for the entire 22 year continuous ocean color (SeaWiFS and MODIS-Aqua) time-series. This technique can be applied to datasets of varying multi- and hyper-spectral resolutions, providing continuity between heritage and future satellite sensors, and further enabling an effective means of elucidating similarities or differences in complex spectral signatures within the constraints of two dimensions. This straightforward means of conceptualizing multi-dimensional variability can help maximize the potential of the spectral information embedded in remote sensing data.

ocean color↗
DOE OSTI2022

Evaluation of WRF simulation of deep convection in the US Southern Great Plains

The Southern Great Plains (SGP) exhibits a relatively high frequency of periods with extremely high rainfall rates (RR) and hail. Here, seven months of 2017 are simulated using the Weather Research and Forecasting (WRF) model applied at convection permitting resolution with the Mibrandt-Yau microphysics scheme. Simulation fidelity is evaluated, particularly during intense convective events, using data from ASOS stations, dual-polarization RADAR, gridded data sets and observations at the DoE Atmospheric Radiation Measurement site. The spatial gradients and temporal variability of precipitation and the cumulative density functions for both RR and wind speeds exhibit fidelity. Odds ratios >1 indicate WRF is also skillful in simulating high composite reflectivity (cREF, used as a measure of widespread convection) and RR > 5 mmhr –1 over the domain. Detailed analyses of the ten days with highest spatial coverage of cREF >30 dBZ show spatially similar reflectivity fields and high RR in both RADAR data and WRF simulations. However, during periods of high reflectivity, WRF exhibits a positive bias in terms of very high RR (> 25 mmhr –1 ) and hail occurrence, and during the summer and transition months, maximum hail size is underestimated. For some renewable energy applications fidelity is required with respect to the joint probabilities of wind speed and RR and/or hail. While partial fidelity is achieved for the marginal probabilities, performance during events of critical importance to these energy applications is currently not sufficient. Further research into optimal WRF configurations in support of potential damage quantification for these applications is warranted.

54 ENVIRONMENTAL SCIENCES↗
NASA NTRS2014

Background Error Covariance Estimation Using Information from a Single Model Trajectory with Application to Ocean Data Assimilation

An attractive property of ensemble data assimilation methods is that they provide flow dependent background error covariance estimates which can be used to update fields of observed variables as well as fields of unobserved model variables. Two methods to estimate background error covariances are introduced which share the above property with ensemble data assimilation methods but do not involve the integration of multiple model trajectories. Instead, all the necessary covariance information is obtained from a single model integration. The Space Adaptive Forecast error Estimation (SAFE) algorithm estimates error covariances from the spatial distribution of model variables within a single state vector. The Flow Adaptive error Statistics from a Time series (FAST) method constructs an ensemble sampled from a moving window along a model trajectory.SAFE and FAST are applied to the assimilation of Argo temperature profiles into version 4.1 of the Modular Ocean Model (MOM4.1) coupled to the GEOS-5 atmospheric model and to the CICE sea ice model. The results are validated against unassimilated Argo salinity data. They show that SAFE and FAST are competitive with the ensemble optimal interpolation (EnOI) used by the Global Modeling and Assimilation Office (GMAO) to produce its ocean analysis. Because of their reduced cost, SAFE and FAST hold promise for high-resolution data assimilation applications.

Error Covariance↗
NASA NTRS2014

Background Error Covariance Estimation using Information from a Single Model Trajectory with Application to Ocean Data Assimilation into the GEOS-5 Coupled Model

An attractive property of ensemble data assimilation methods is that they provide flow dependent background error covariance estimates which can be used to update fields of observed variables as well as fields of unobserved model variables. Two methods to estimate background error covariances are introduced which share the above property with ensemble data assimilation methods but do not involve the integration of multiple model trajectories. Instead, all the necessary covariance information is obtained from a single model integration. The Space Adaptive Forecast error Estimation (SAFE) algorithm estimates error covariances from the spatial distribution of model variables within a single state vector. The Flow Adaptive error Statistics from a Time series (FAST) method constructs an ensemble sampled from a moving window along a model trajectory. SAFE and FAST are applied to the assimilation of Argo temperature profiles into version 4.1 of the Modular Ocean Model (MOM4.1) coupled to the GEOS-5 atmospheric model and to the CICE sea ice model. The results are validated against unassimilated Argo salinity data. They show that SAFE and FAST are competitive with the ensemble optimal interpolation (EnOI) used by the Global Modeling and Assimilation Office (GMAO) to produce its ocean analysis. Because of their reduced cost, SAFE and FAST hold promise for high-resolution data assimilation applications.

Data Assimilation↗
NASA NTRS1994

Electron-Beam Diagnostic Methods for Hypersonic Flow Diagnostics

The purpose of this work was the evaluation of the use of electron-bean fluorescence for flow measurements during hypersonic flight. Both analytical and numerical models were developed in this investigation to evaluate quantitatively flow field imaging concepts based upon the electron beam fluorescence technique for use in flight research and wind tunnel applications. Specific models were developed for: (1) fluorescence excitation/emission for nitrogen, (2) rotational fluorescence spectrum for nitrogen, (3) single and multiple scattering of electrons in a variable density medium, (4) spatial and spectral distribution of fluorescence, (5) measurement of rotational temperature and density, (6) optical filter design for fluorescence imaging, and (7) temperature accuracy and signal acquisition time requirements. Application of these models to a typical hypersonic wind tunnel flow is presented. In particular, the capability of simulating the fluorescence resulting from electron impact ionization in a variable density nitrogen or air flow provides the capability to evaluate the design of imaging instruments for flow field mapping. The result of this analysis is a recommendation that quantitative measurements of hypersonic flow fields using electron-bean fluorescence is a tractable method with electron beam energies of 100 keV. With lower electron energies, electron scattering increases with significant beam divergence which makes quantitative imaging difficult. The potential application of the analytical and numerical models developed in this work is in the design of a flow field imaging instrument for use in hypersonic wind tunnels or onboard a flight research vehicle.

Source record↗
NASA NTRS2000

Application of the Space-Time Conservation Element and Solution Element Method to One-Dimensional Convection-Diffusion Problems

In the space-time conservation element and solution element (CE/SE) method, the independent marching variables used comprise not only the mesh value of the physical dependent variables but also, in contrast to it typical numerical method, the Mesh values of the spatial derivatives of the physical variables The use of the extra marching variables results from the need to construct the two-level explicit and nondissipative schemes which are at the core of the CE/SE development. It also results from the need to minimize the stencil while maintaining accuracy. In this paper using the 1D(sub (alpha)-mu) scheme as an example, the effect of this added complication on consistency, accuracy and operation count is assessed. As part of this effort, an equivalent yet more efficient form of the alpha-mu scheme in which the independent marching variables are the local fluxes tied to each mesh point is introduced. Also, the intriguing relations that exist among the alpha-mu. Leapfrog, and DuFort-Frankel schemes are further explored. In addition, the redundance of the Leapfrog, DUFort-Frankel, and Lax scheme and the remedy for this redundance are discussed. This paper is concluded with the construction and evaluation of a CE/SE solver for the inviscid Burger equation.

Chang, Sin-Chung↗
DOE OSTI2021

A Systematic Interpretation of Subsurface Proppant Concentration from Drilling Mud Returns: Case Study from Hydraulic Fracturing Test Site (HFTS-2) in Delaware Basin

The aim of this study is generation and validation of a proppant log using analysis of drilling mud returns for child wells. Proppant log provides qualitative as well as quantitative insights into spatial distribution of proppant sand particles from prior stimulation of parent wells. While the basic methodology was developed and formalized during analysis of material collected from through fracture cores at Hydraulic Fracturing Test Site in Midland Basin (HFTS – 1), the test wells at HFTS – 2 in the neighboring Delaware Basin allowed the opportunity to validate the workflow on actual mud return samples from subsurface. As a child well is being drilled, periodic mud return samples are collected at the rig site and preserved for analysis. The workflow involves systematic cleaning of the samples including various steps such as washing, drying and segregation of samples into relevant size fractions of interest (< Mesh 20) based on specifications of pumped sand during stimulation of the parent well. Clean samples are imaged using high resolution transparency scanning. Scan images are then systematically analyzed for particles of interest using computer vision techniques. Sample counts are further validated using elemental analysis of smaller sub-samples at various depths of interest. This step is necessary to isolate proppant versus other naturally occurring minerals such as sulphates and carbonates which show similar optical properties. We successfully correlated proppant distribution against the existing parent well and validated propped versus relatively un-propped zones for a child well at the test site. The advantage of testing the proppant log concept at the HFTS – 2 site is the plethora of additional diagnostic data that is available to validate our primary observations. We can correlate spatial proppant distribution against variability in stimulation response based on independent observations such as image logs, microseismic attributes as well as DAS response, all of which tend to corroborate one another. One of our significant successes was being able to describe varying degrees of impact of the parent well along the lateral length of a stimulated child well. Our workflow represents a systematic and one-of-a-kind interpretation of spatial proppant distribution while drilling child wells. This provides unique opportunities to better understand the current state of the Downloaded from http://onepetro.org/URTECONF/proceedings-pdf/21URTC/2-21URTC/D021S031R003/2477415/urtec-2021-5189-ms.pdf/1 by Carol Worster on 28 February 2022 URTeC 5189 2 reservoir being targeted including zones which are likely more drained relative to others and how the planned completion of the child well can be improved. Lastly, this log can be useful is validating optimal well spacing in relatively new fields under development.

58 GEOSCIENCES↗
NASA NTRS1989

Dust around Mira variables: An analysis of IRAS LRS spectra

The spatial extent and spectral appearance of the thin dust shell around Mira variables is determined largely by the dust absorptivity, Q(sub abs)(lambda), and the dust condensation temperature T(sub cond). Both Q(sub abs)(lambda) and T(sub cond) are extracted from IRAS low-resolution spectra (LRS) spectra. In order to do this, the assumption that the ratio of total power in the 10 micron feature to that in the 20 micron feature should be equal to that measured in other amorphous silicates (e.g., synthesized amorphous Mg2SiO4). It was found that T(sub cond) decreases with decreasing strength of the 10 micron feature, from T(sub cond) = 1000 K to 500 K (estimated error 20 percent). A value for the near-infrared dust absorptivity could not be determined. Although this parameter strongly affects the condensation radius, it hardly affects the shape of the LRS spectrum (as long as the optically thin approximation is valid), because it scales the spatial distribution of the dust. Information on the magnitude of the near-infrared dust absorptivity may be deduced from the unique carbon star BM Gem. This star has a LRS spectrum with silicate features indication an inner dust shell temperature of at least 1000 K. However, on the basis of observations in the 1920s-30s one may infer an inner dust shell radius of at least 6x10(exp 12)m. To have this high temperature at such a large distance, the near-infrared absorptivity of the dust must be high.

Slijkhuis, S.↗
DOE OSTI2022

Passive and active peer effects in the spatial diffusion of residential solar panels: A case study of the Las Vegas Valley

This research analyzes the role of peer influences on the adoption of residential rooftop solar photovoltaic panels (PV) within the context of the Diffusion of Innovation Theory. PV literature indicates that adopters are influenced by word of mouth (WOM) information exchange with peers, i.e., active peer effects, while other studies suggest that living near households with visible rooftop PV installations influences adoption, i.e., passive peer effects. We bridge the gap in this literature by conducting a mixed methods analysis. We develop and administer a survey to Las Vegas Valley (LVV) residents to identify current and potential PV adopters' perceptions of peer-effects and consumer intention variables. We conduct a spatial analysis of Google's Project Sunroof data to identify LVV neighborhoods in the later stages of the PV diffusion process, i.e., those with the highest PV adoption rates. Key results show that current PV adopters living in early diffusion areas report significantly higher active and passive peer effects compared to adopters in later diffusion areas. Potential adopters in later diffusion areas report higher passive peer effects than those in early diffusion areas. Overall, because LVV has a low PV adoption rate (<3%), short term strategies aimed at increasing PV adoption should emphasize WOM active peer effects. Here, we caution against long-term green marketing strategies focusing solely on peer-effects as the PV market matures.

14 SOLAR ENERGY↗
NASA NTRS2001

Interannual Variability of Tropical Precipitation: How Well Do Climate Models Agree With Current Satellite Estimates?

Since the beginning of the World Climate Research Program's Global Precipitation Climatology Project (GPCP) satellite remote sensing of precipitation has made dramatic improvements, particularly for tropical regions. Data from microwave and infrared sensors now form the most critical input to precipitation data sets and can be calibrated with surface gauges to so that the strengths of each data source can be maximized in some statistically optimal sense. Recent availability of the TRMM (Tropical Rainfall Measuring Mission) has further aided in narrowing uncertainties in rainfall over die tropics and subtropics. Although climate modeling efforts have long relied on space-based precipitation estimates for validation, we now are in a position to make more quantitative assessments of model performance, particularly in tropical regions. An integration of the CCM3 using observed SSTs as a lower boundary condition is used to examine how well this model responds to ENSO forcing in terms of anomalous precipitation. An integration of the NCEP spectral model used for the Reanalysis-H effort is also examined. This integration is run with specified SSTs, but with no data assimilation. Our analysis focuses on two aspects of inter-annual variability. First are the spatial anomalies that are indicative of dislocations in Hadley and Walker circulations. Second, we consider the ability of models to replicate observed increases in oceanic precipitation that are noted in satellite observations for large ENSO events. Finally, we consider a slab ocean version of the CCM3 model with prescribed ocean beat transports that mimic upwelling anomalies, but which still allows the surface energy balance to be predicted. This less restrictive experiment is used to understand why model experiments with specified SSTs seem to have noticeably less interannual variability in precipitation than do the satellite observations.

Robertson, Franklin R.↗
NASA NTRS2012

The Role of Lightning in Controlling Interannual Variability of Tropical Tropospheric Ozone and OH and its Implications for Climate

Nitrogen oxides (NO(x) = NO + NO2) produced by lightning make a major contribution to the production of the dominant tropospheric oxidants (OH and ozone). These oxidants control the lifetime of many trace gases including long-lived greenhouse gases, and control the source-receptor relationship of inter-hemispheric pollutant transport. Lightning is affected by meteorological variability, and therefore represents a potentially important tropospheric chemistry-climate feedback. Understanding how interannual variability (IAV) in lightning affects IAV in ozone and OH in the recent past is important if we are to predict how oxidant levels may change in a future warmer climate. However, lightning parameterizations for chemical transport models (CTMs) show low skill in reproducing even climatological distributions of flash rates from the Lightning Imaging Sensor (LIS) and the Optical Transient Detector (OTD) satellite instruments. We present an optimized regional scaling algorithm for CTMs that enables sufficient sampling of spatiotemporally sparse satellite lightning data from LIS to constrain the spatial, seasonal, and interannual variability of tropical lightning. We construct a monthly time series of lightning flash rates for 1998-2010 and 35degS-35degN, and find a correlation of IAV in total tropical lightning with El Nino. We use the IAV-constraint to drive a 9-year hindcast (1998-2006) of the GEOS-Chem 3D chemical transport model, and find the increased IAV in LNO(x) drives increased IAV in ozone and OH, improving the model fs ability to simulate both. Although lightning contributes more than any other emission source to IAV in ozone, we find ozone more sensitive to meteorology, particularly convective transport. However, we find IAV in OH to be highly sensitive to lightning NO(x), and the constraint improves the ability of the model to capture the temporal behavior of OH anomalies inferred from observations of methyl chloroform and other gases. The sensitivity of OH is explained using photochemical reaction rates which show a "magnification" effect of the initial lightning NO perturbation on OH primary production, HO(x) recycling, and OH loss frequencies. This influence on OH may represent a negative feedback, if lightning increases in a warming world..

Murray, Lee T.↗