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All sourcesNASA NTRSDOE OSTI
NASA NTRS2013

A Global Ozone Climatology from Ozone Soundings via Trajectory Mapping: A Stratospheric Perspective

This study explores a domain-filling trajectory approach to generate a global ozone climatology from sparse ozonesonde data. Global ozone soundings of 51,898 profiles at 116 stations over 44 years (1965-2008) are used, from which forward and backward trajectories are performed for 4 days, driven by a set of meteorological reanalysis data. Ozone mixing ratios of each sounding from the surface to 26 km altitude are assigned to the entire path along the trajectory. The resulting global ozone climatology is archived monthly for five decades from the 1960s to the 2000s with grids of 5 degree 5 degree 1 km (latitude, longitude, and altitude). It is also archived yearly from 1965 to 2008. This climatology is validated at 20 ozonesonde stations by comparing the actual ozone sounding profile with that found through the trajectories, using the ozone soundings at all the stations except one being tested. The two sets of profiles are in good agreement, both individually with correlation coefficients between 0.975 and 0.998 and root mean square (RMS) differences of 87 to 482 ppbv, and overall with a correlation coefficient of 0.991 and an RMS of 224 ppbv. The ozone climatology is also compared with two sets of satellite data, from the Satellite Aerosol and Gas Experiment (SAGE) and the Optical Spectrography and InfraRed Imager System (OSIRIS). Overall, the ozone climatology compares well with SAGE and OSIRIS data by both seasonal and zonal means. The mean difference is generally under 20 above 15 km. The comparison is better in the northern hemisphere, where there are more ozonesonde stations, than in the southern hemisphere; it is also better in the middle and high latitudes than in the tropics, where assimilated winds are imperfect in some regions. This ozone climatology can capture known features in the stratosphere, as well as seasonal and decadal variations of these features. Furthermore, it provides a wealth of detail about longitudinal variations in the stratosphere such as the spring ozone maximum over the Canadian Arctic. It also covers higher latitudes than current satellite data. The climatology shows clearly the depletion of ozone from the 1970s to the mid 1990s and ozone recovery in the 2000s. When this climatology is used as the upper boundary condition in an Environment Canada operational chemical forecast model, the forecast is improved in the vicinity of the upper tropospherelower stratosphere region. As this ozone climatology is neither dependent on a priori data or photochemical modeling, it provides independent information and insight that can supplement satellite data and model simulations and enhance our understanding of stratospheric ozone.

SAGE↗
NASA NTRS2022

Impact of Meteorological Factors on the Mesoscale Morphology of Cloud Streets during a Cold-Air Outbreak over the Western North Atlantic

Postfrontal clouds (PFC) are ubiquitous in the marine boundary layer, and their morphology is essential to estimating the radiation budget in weather and climate models. Here we examine the roles of sea surface temperature (SST) and meteorological factors in controlling the mesoscale morphology and evolution of shallow clouds associated with a cold-air outbreak that occurred on 1 March 2020 during phase I of the Aerosol Cloud Meteorology Interactions over the Western Atlantic Experiment (ACTIVATE). Our results show that the simulated PFC structure and ambient conditions by the Weather Research and Forecasting (WRF) Model are generally consistent with observations from GOES-16 and dropsonde measurements. We also examine the thermodynamical and dynamical influences in the cloud mesoscale morphology using WRF sensitivity experiments driven by two meteorological forcing datasets with different domain-mean SST and spatial gradients, which lead to dissimilar values of hydrometeor water path and cloud core fraction. The SST from ERA5 leads to weaker stability and higher inversion height than the SST from FNL does. In addition, the use of large-scale meteorological forcings from ERA5 yields a distinctive time evolution of wind direction shear in the inner domain, which favors the formation and persistence of longer cloud rolls. Both factors contribute to a change in the time evolution of domain-mean water path and cloud core fraction of cloud streets. Our study takes advantage of the simulation driven by the differences between two large-scale forcing datasets to illustrate the importance of SST and wind direction shear in the cloud street morphology in a realistic scenario

Jingyi Chen↗
DOE OSTI2021

Representations of Precipitation Diurnal Cycle in the Amazon as Simulated by Observationally Constrained Cloud‐System Resolving and Global Climate Models

Abstract The ability of an observationally‐constrained cloud‐system resolving model (Weather Research and Forecasting; WRF, 4‐km grid spacing) and a global climate model (Energy Exascale Earth System Model; E3SM, 1‐degree grid spacing) to represent the precipitation diurnal cycle over the Amazon basin during the 2014 wet season is assessed. The WRF model coupled with a 3‐D variational data assimilation scheme reproduces the spatial variability of the precipitation diurnal cycle over the basin and the lifecycle of westward propagating MCSs initiated by the coastal sea‐breeze front. In contrast, a single morning peak in rainfall is produced by E3SM for simulations despite the nudging of large‐scale winds toward global reanalysis, indicating precipitation in E3SM is largely controlled by local convection associated with diurnal heating. The role of propagating MCS on the environment are discussed by using a multivariate perturbation analysis. We also find that the advection of moisture perturbations from ocean to inland regions have a higher correlation with the occurrence of MCSs in the Amazon than the intensity of colder air intrusion associated with sea breezes along the coast. Moreover, the presence of large cold pools over the central Amazon basin are responsible for the maintenance of propagating deep convection.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2024

Effects of Pollen on Hydrometeors and Precipitation in a Convective System

Anemophilous (wind-driven) pollen is one type of primary biological aerosol particle, which can rupture under high humidity conditions and form smaller sub-pollen particles (SPPs). Both pollen and SPPs can reach the upper troposphere under convective conditions, acting as cloud condensation nuclei (CCN) and ice nucleating particles (INPs), thus influencing cloud formation and precipitation. However, the impacts of these biological aerosols on cold cloud formation and local climate remain unclear as there are large uncertainties on their emission flux and ice nucleating abilities. Here, we incorporate pollen emission and rupture processes in the Weather Research and Forecasting Model with Chemistry (WRF-Chem) simulations and update the Morrison microphysics scheme within WRF-Chem using aerosol-aware INP parameterizations to account for pollen in addition to other anthropogenic and biogenic aerosol. INP parameterizations for pollen and SPP are derived from laboratory experiments. When including pollen rupture rates as observed in a series of chamber studies, SPP concentrations increase, leading to an increase of cloud ice and water by up to 50% and potentially extending the duration of the convective system. Among all simulated hydrometeors, graupel and raindrops exhibit the largest enhancements from the inclusion of SPPs, with intensifying precipitation at the backside of the convective system and a greater spatial extent. Sensitivity simulations indicate that SPPs have a greater effect on cloud microphysical processes than whole pollen grains, and further observational evidence is needed to constrain these processes.

54 ENVIRONMENTAL SCIENCES↗
NASA NTRS1997

Interannual Fluctuations in Atmospheric Angular Momentum Simulated by the National Centers for Environmental Prediction Medium Range Forecast Model

An earlier study established the existence of globally coherent interannual fluctuations in atmospheric angular momentum (AAM), associated with the El Nino-Southern Oscillation (ENSO) cycle. In this paper, we pursue the origin and the structure of these fluctuations using an ensemble of experiments generated by the National Centers for Environmental Prediction, medium range forecast model version 9. In the control experiments, where the observed sea surface temperatures (SSTs) were used as the lower boundary conditions, the model captures the characteristic V-like structure in time-latitude plots of zonally averaged AAM, while experiments with climatological SSTs and those with either perpetual warm or cold ENSO conditions superimposed on the climatological SSTs failed to reproduce this structure. The numerical results indicate that these AAM structures are related to SST variations associated with transitions between different phases of the ENSO cycle and have both propagating and standing components. The largest zonal wind contribution from the levels studied (850, 500, and 200 hPa) is at 200 hPa, where the tropical convective outflow is the strongest. Composites of zonal wind and geopotential height show a clear relationship between the stages of the global AAM oscillation and the ENSO cycle. The strong similarity between the simulated and observed AAM series attests to the model's ability to realistically simulate the interannual response of the atmosphere to ENSO SST anomalies.

Mo, Kingtse C.↗
NASA NTRS2008

Displaying Composite and Archived Soundings in the Advanced Weather Interactive Processing System

In a previous task, the Applied Meteorology Unit (AMU) developed spatial and temporal climatologies of lightning occurrence based on eight atmospheric flow regimes. The AMU created climatological, or composite, soundings of wind speed and direction, temperature, and dew point temperature at four rawinsonde observation stations at Jacksonville, Tampa, Miami, and Cape Canaveral Air Force Station, for each of the eight flow regimes. The composite soundings were delivered to the National Weather Service (NWS) Melbourne (MLB) office for display using the National version of the Skew-T Hodograph analysis and Research Program (NSHARP) software program. The NWS MLB requested the AMU make the composite soundings available for display in the Advanced Weather Interactive Processing System (AWIPS), so they could be overlaid on current observed soundings. This will allow the forecasters to compare the current state of the atmosphere with climatology. This presentation describes how the AMU converted the composite soundings from NSHARP Archive format to Network Common Data Form (NetCDF) format, so that the soundings could be displayed in AWl PS. The NetCDF is a set of data formats, programming interfaces, and software libraries used to read and write scientific data files. In AWIPS, each meteorological data type, such as soundings or surface observations, has a unique NetCDF format. Each format is described by a NetCDF template file. Although NetCDF files are in binary format, they can be converted to a text format called network Common data form Description Language (CDL). A software utility called ncgen is used to create a NetCDF file from a CDL file, while the ncdump utility is used to create a CDL file from a NetCDF file. An AWIPS receives soundings in Binary Universal Form for the Representation of Meteorological data (BUFR) format (http://dss.ucar.edu/docs/formats/bufr/), and then decodes them into NetCDF format. Only two sounding files are generated in AWIPS per day. One file contains all of the soundings received worldwide between 0000 UTC and 1200 UTC, and the other includes all soundings between 1200 UTC and 0000 UTC. In order to add the composite soundings into AWIPS, a procedure was created to configure, or localize, AWIPS. This involved modifying and creating several configuration text files. A unique fourcharacter site identifier was created for each of the 32 soundings so each could be viewed separately. The first three characters were based on the site identifier of the observed sounding, while the last character was based on the flow regime. While researching the localization process for soundings, the AMU discovered a method of archiving soundings so old soundings would not get purged automatically by AWl PS. This method could provide an alternative way of localizing AWl PS for composite soundings. In addition, this would allow forecasters to use archived soundings in AWIPS for case studies. A test sounding file in NetCDF format was written in order to verify the correct format for soundings in AWIPS. After the file was viewed successfully in AWIPS, the AMU wrote a software program in the Tool Command Language/Tool Kit (Tcl/Tk) language to convert the 32 composite soundings from NSHARP Archive to CDL format. The ncgen utility was then used to convert the CDL file to a NetCDF file. The NetCDF file could then be read and displayed in AWIPS.

Barrett, Joe H., III↗
DOE OSTI2018

Verifying and assessing the performance of the perturbation strategy in polynomial chaos ensemble forecasts of the circulation in the Gulf of Mexico

Here we present an analysis of two recent efforts aimed at quantifying the uncertainties in a 30-day HYbrid Coordinate Ocean Model forecast of the circulation in the Gulf of Mexico, with particular emphasis on the separation of Loop Current Eddy Franklin, using Polynomial Chaos methods. The analysis herein explores whether the model perturbations lead to realistic representation of the uncertainty in the Gulf Circulation. Comparisons of model output with Sea Surface Height and current mooring data show that the observational data generally falls within the envelope of the ensemble and that the modal decomposition delivers “realistic” perturbations in the Loop Current region. We use information theory metrics to quantify the information gain and the computational trade-offs between different wind and initial conditions perturbation modes. The relative entropy measures indicate that two modes for initial condition perturbations are enough, in our model configuration, to represent the uncertainty in the Loop Current region; while two modes for wind forcing perturbations are necessary in order to estimate the uncertainty in the coastal zone. The ensemble statistics are then explored using the Polynomial Chaos surrogate and the newly developed contour boxplot methods.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2019

The High-resolution Transmission Spectrum of HD 189733b Interpreted with Atmospheric Doppler Shifts from Three-dimensional General Circulation Models

The signature of wind patterns caused by the interplay of rotation and energy redistribution in hot Jupiters is detectable at high spectral resolution, yet no direct comparison has been attempted between predictions from general circulation models (GCMs) and observed high-resolution spectra. We present the first such comparison on near-infrared transmission spectra of the hot Jupiter HD 189733b. Exploring 12 rotation rates and two chemical regimes, we have created model spectra from 3D GCMs and cross-correlated them with the observed spectra. Comparing our models against those of HD 189733b, we obtain three key results: (1) we confirm CO and H{sub 2}O in the planet’s atmosphere at a detection significance of 8.2σ; (2) we recover the signature of day-to-night winds with speeds of several km s{sup −1} at pressures of several millibars; and (3) we constrain the rotation period of the planet to between 1.2 and 4.69 days (synchronous rotation (2.2 days) remains consistent with existing observations). Our results do not suffer from the shortcomings of 1D models as cross-correlation templates—these models mainly tend to overconstrain the slower rotation rates and show evidence for anomalous blueshifts. Our 3D models instead match the observed line-of-sight velocity of this planet by self-consistently including the effects of high-altitude day-to-night winds. Overall, we find a high degree of consistency between observations of HD 189733b and our GCM-based spectra, implying that the physics and chemistry are adequately described in current 3D forward models for the purpose of interpreting observations at high spectral resolution.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2026

Process-oriented evaluation of quasi-stationary Rossby waves and their impact on surface air temperature extremes in dynamical downscaling over North America

Quasi-stationary Rossby waves are a crucial component of the general circulation and play a significant role in regional water and energy cycles, as well as in extreme events. However, process-oriented evaluation for Rossby waves is rarely performed for dynamical downscaling simulations. To close this gap, we evaluate three classes of dynamical downscaling approaches, with a focus on quasi-stationary Rossby waves and their impact on surface air temperature over North America during Northern Hemisphere summer. The three classes of models differ in the way large-scale forcing is provided: a limited-area model (LAM) constrained only by lateral boundary conditions, represented by RegCM4 from the North American branch of the Coordinated Regional Downscaling Experiment (NA-CORDEX), a LAM with spectral nudging to maintain consistency in large-scale dynamics with the forcing data, represented by the Weather Research and Forecasting (WRF) model simulation in NA-CORDEX, and a global variable-resolution model with smoothly varying grid spacings, represented by the Community Atmosphere Model version 5.4, with the Model for Prediction Across Scales (MPAS) as its dynamical core (CAM-MPAS). With no constraints on the atmospheric dynamics, CAM-MPAS exhibits several mean biases in the upper-level circulations over the Pacific Coast region: a weaker subtropical jet, a northward-shifted mid-latitude jet, and an overestimated southerly flow. With the lateral boundary constraint alone, RegCM4 also exhibits weaker jets and overestimated southerly winds off the West Coast. Rossby ray theory reveals that those wind biases direct incoming Rossby waves northward. The erroneously routed Rossby waves distort the relationship between the accumulation of wave activity over the US West Coast and surface temperature anomalies over the Southern Great Plains, which emerges approximately 4 d after the convergence of wave-activity flux in the ERA-Interim reanalysis. Furthermore, the response of heatwaves to the extreme wave activity flux is not reproduced by the two models, a serious drawback as a dynamical downscaling framework is expected to connect large-scale forcing to local-scale phenomena. The WRF model employing spectral nudging is largely free from the aforementioned problems. A pair of sensitivity simulations suggests that spectral nudging is the key to improving the dynamics of quasi-stationary Rossby waves and their impact on surface air temperature. Our results also demonstrate the effectiveness of Rossby wave diagnostics that allow for realistic background flows for assessing the credibility of dynamical downscaling over North America, where incoming Rossby waves propagate through complex circulation patterns before traveling across the continent.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2020

A Time Series Sustainability Assessment of a Partial Energy Portfolio Transition

Energy portfolios are overwhelmingly dependent on fossil fuel resources that perpetuate the consequences associated with climate change. Therefore, it is imperative to transition to more renewable alternatives to limit further harm to the environment. This study presents a univariate time series prediction model that evaluates sustainability outcomes of partial energy transitions. Future electricity generation at the state-level is predicted using exponential smoothing and autoregressive integrated moving average (ARIMA). The best prediction results are then used as an input for a sustainability assessment of a proposed transition by calculating carbon, water, land, and cost footprints. Missouri, USA was selected as a model testbed due to its dependence on coal. Of the time series methods, ARIMA exhibited the best performance and was used to predict annual electricity generation over a 10-year period. The proposed transition consisted of a one-percent annual decrease of coal’s portfolio share to be replaced with an equal share of solar and wind supply. The sustainability outcomes of the transition demonstrate decreases in carbon and water footprints but increases in land and cost footprints. Decision makers can use the results presented here to better inform strategic provisioning of critical resources in the context of proposed energy transitions.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
NASA NTRS2013

Genesis of Hurricane Sandy (2012) Simulated with a Global Mesoscale Model

In this study, we investigate the formation predictability of Hurricane Sandy (2012) with a global mesoscale model. We first present five track and intensity forecasts of Sandy initialized at 00Z 22-26 October 2012, realistically producing its movement with a northwestward turn prior to its landfall. We then show that three experiments initialized at 00Z 16-18 October captured the genesis of Sandy with a lead time of up to 6 days and simulated reasonable evolution of Sandy's track and intensity in the next 2 day period of 18Z 21-23 October. Results suggest that the extended lead time of formation prediction is achieved by realistic simulations of multiscale processes, including (1) the interaction between an easterly wave and a low-level westerly wind belt (WWB) and (2) the appearance of the upper-level trough at 200 hPa to Sandy's northwest. The low-level WWB and upper-level trough are likely associated with a Madden-Julian Oscillation.

multiscale processes↗
DOE OSTI2016

Efficient Uncertainty Quantification in Stochastic Economic Dispatch

Stochastic economic dispatch models usually address uncertainties in forecasts of renewable generation output by considering a finite number of realizations drawn from a stochastic process model, typically via Monte Carlo sampling. Accurate evaluations of expectations or higher order moments for quantities of interest, e.g., generating cost, can require a prohibitively large number of samples. We propose an alternative to Monte Carlo sampling based on polynomial chaos expansions. These representations enable efficient and accurate propagation of uncertainties in model parameters, using sparse quadrature methods. Furthermore, we use Karhunen-Loève expansions for efficient representation of uncertain renewable energy generation that follows geographical and temporal correlations derived from historical data at each wind farm. Considering expected production cost, we show that the proposed approach can yield several orders of magnitude reduction in computational cost for solving stochastic economic dispatch relative to Monte Carlo sampling, for a given target error threshold.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2019

Seesaw haze pollution in North China modulated by the sub-seasonal variability of atmospheric circulation

Utilizing a recent observational dataset of particulate matter with diameters less than 2.5 µ m (PM 2.5 ) in North China, this study reveals adistinct seesaw feature of abnormally high and low PM 2.5 concentrationsin the adjacent two months of December 2015 and January 2016, accompanied bydistinct meteorological modulations. The seesaw pattern is postulated to belinked to a super El Niño and the Arctic Oscillation (AO). During themature phase of El Niño in December 2015, the weakened East Asian wintermonsoon (EAWM) and the associated low-level southerly wind anomaly reducedplanetary boundary layer (PBL) height, favoring strong haze formation. Thiscirculation pattern was completely reversed in the following month, in partdue to a sudden phase change of the AO from positive to negative and thebeginning of a decay of the El Niño, which enhanced the southward shiftof the upper tropospheric jet from December to January relative toclimatology, leading to an enhanced EAWM and substantially lower hazeformation. This sub-seasonal change in circulation is also robustly found in1982–1983 and 1997–1998, implicative of a general physical mechanismdynamically linked to El Niño and the AO. Numerical experiments using theWeather Research and Forecasting (WRF) Community Multiscale Air Quality(CMAQ) model were used to test the modulation of the meteorologicalconditions on haze formation. With the same emission, simulations for threesuper El Niño periods (1983, 1997 and 2015) robustly show higherPM 2.5 concentrations under the mature phase of the super El Niño,but substantially lower PM 2.5 concentrations during the decay phase ofEl Niño (and the sudden AO phase change), further verifying themodulation effect of the sub-seasonal circulation anomaly on PM 2.5 concentrations in North China

54 ENVIRONMENTAL SCIENCES↗
NASA NTRS1994

The formation of Hurricane Frederic of 1979

A high-resolution global model forecast of the formation of Hurricane Frederic of 1979 is analyzed by means of several diagnostic computations on the model's output history. The formation is addressed from an analysis of limited-area energetics where the growth of eddy kinetic energy is examined. The question on internal versus external forcing during the formative stage of the hurricane is explored by means of the Kuo-Eliassen framework for the radial-vertical circulation of the hurricane. The intensity of the predicted hurricane is diagnosed from a detailed angular momentum budget following the three-dimensional motion of parcels arriving at the maximum wind belt. Overall, the successful simulation of the hurricane has enabled us to make such a detailed diagnosis of the predicted hurricane at a high resolution. The principal findings of this study are that a north-south-oriented heating function maintained a zonal easterly flow that supplied energy barotropically during the growth of an African wave. The growth of eddy kinetic energy is somewhat monotonic and slow throughout the history of the computations. The initial development of the easterly wave appears to be related to the widespread weak convective heating that contributes to a covariance of heating and temperature and of temperature and vertical velocity. The hurricane development period is seen as one where both the barotropic and convective processes contribute to the growth of eddy kinetic energy.

Krishnamurti, T. N.↗
DOE OSTI2022

Combined Cycle Integrated Thermal Energy Storage “CiTES” (Final Scientific/Technical Report)

The Phase I of this project confirmed the technical feasibility of a Combined Cycle integrated Thermal Energy Storage “CiTES” system, calculated the key performance parameters like power efficiency and costs, and proved its commercial value with full-year simulations for several US electricity markets with high degree of variable renewable generation and volatile hourly electricity prices. The core element of this project is the Electro Thermal Energy Storage (ETES) technology from Siemens Gamesa Renewable Energy GmbH, using thermally stable and inexpensive volcanic rocks as storage material and air as heat transfer medium. This technology is backed by more than 10 years of experience and a 440MMBTU (130MWh-th) pilot plant in Hamburg, Germany, which is in operation since 2019. The integration of this thermal storage in an existing combined cycle power plant (CCPP) is typical power plant technology without any major technology risks. It allows the storage of inexpensive renewable energy during times of surplus renewable generation and the discharge of this energy in times of high energy demand when the fossil plant is in operation. This supplements the fossil power generation with CO2-emission-free energy. The secondary effect of the CiTES system is that a small part of the stored thermal energy is used to keep the heat recovery steam generator (HRSG) and steam turbine (ST) of the combined cycle power plant in hot and ready-to-start condition. This enables the plant to start rapidly when fossil generation is required to satisfy demand as soon variable generation drops off in the evenings or during cloud cover and calm wind periods. Without pre-warming of the HRSG and ST, the CCPP would need several hours for a cold or warm start, burn a lot of gas and release high NOx emissions during start and wouldn’t be able to use the short times of high energy prices in an efficient or economical manner. The economic parameters of CiTES were determined by a full year “8760” simulation using a data set calculation for each of the hours of the year, and historical electricity and gas prices. For consistency, the simulations were focused on the pre-COVID year 2019. The financially most attractive markets were in the Energy Reliability Council of Texas (ERCOT) region, which allowed substantial value generation with arbitrage (charge with cheap energy during renewable surplus times and discharge when energy is needed and expensive). The improvement of flexibility with the CiTES system by pre-heating and warm-keeping of the CCPP allowed for additional power generation during short time periods when demand is high but renewable generation is down; when the hourly energy prices are highest in these markets. The simulations are based on 2019 data, when ERCOT had 27GW of installed photovoltaic (PV) and wind generation. They showed that the created revenue with the prototypically sized CiTES system of 1,000MMBTU (300MWh-th) falls a little bit short of what is expected from a commercially viable investment. The system has optimization opportunities for cost reduction and increased effectiveness which will be realized during a potential Phase II Pre-FEED study following this project. Furthermore, it is safe to assume that a lot of renewable generation capacity will be added all over the US in the coming years. As an example, ERCOT is predicting to more than double its renewable generation from 27GW in 2019 to a forecasted 63GW in 2023. This will increase the amount of renewable overproduction exponentially. This rapid increase of local overproduction and the need to curtail renewable generation is well documented by the California ISO (www.CAISO.com / managing oversupply). However, the simulations also revealed a weakness in the structure of the electricity markets in the US. More specifically, when electricity prices are very low and approaching negative levels, the owners of Variable Renewable Energy (VRE) will curtail a part of their facility to stabilize the price by reducing supply. This results in a situation in which storage facilities, which are integrated in existing fossil assets and don’t have the behind-the-meter benefit of a VRE, won’t be able to purchase low cost – otherwise curtailed – renewable energy off the grid. A special tariff, which motivates VRE owners to sell otherwise curtailed renewable energy to storage facilities (Hydrogen, thermal, pumped hydro, etc.) can solve this issue. The implementation of such a regulating tariff by Independent System Operators, thus avoiding renewable curtailment, is a pre condition for successful commercialization for renewable energy storage technologies. With this advancement of design and technology and improvements in the market environment, it can be expected that the Combined Cycle integrated Thermal Energy Storage proves itself as an important innovation to keep highly efficient, natural gas-based power generation economically successful and relevant for the power industry in the United States of America.

Wolf, Thorsten↗
DOE OSTI2014

Final report on "Carbon Data Assimilation with a Coupled Ensemble Kalman Filter"

We proposed (and accomplished) the development of an Ensemble Kalman Filter (EnKF) approach for the estimation of surface carbon fluxes as if they were parameters, augmenting the model with them. Our system is quite different from previous approaches, such as carbon flux inversions, 4D-Var, and EnKF with approximate background error covariance (Peters et al., 2008). We showed (using observing system simulation experiments, OSSEs) that these differences lead to a more accurate estimation of the evolving surface carbon fluxes at model grid-scale resolution. The main properties of the LETKF-C are: a) The carbon cycle LETKF is coupled with the simultaneous assimilation of the standard atmospheric variables, so that the ensemble wind transport of the CO2 provides an estimation of the carbon transport uncertainty. b) The use of an assimilation window (6hr) much shorter than the months-long windows used in other methods. This avoids the inevitable “blurring” of the signal that takes place in long windows due to turbulent mixing since the CO2 does not have time to mix before the next window. In this development we introduced new, advanced techniques that have since been adopted by the EnKF community (Kang, 2009, Kang et al., 2011, Kang et al. 2012). These advances include “variable localization” that reduces sampling errors in the estimation of the forecast error covariance, more advanced adaptive multiplicative and additive inflations, and vertical localization based on the time scale of the processes. The main result has been obtained using the LETKF-C with all these advances, and assimilating simulated atmospheric CO2 observations from different observing systems (surface flask observations of CO2 but no surface carbon fluxes observations, total column CO2 from GoSAT/OCO-2, and upper troposphere AIRS retrievals). After a spin-up of about one month, the LETKF-C succeeded in reconstructing the true evolving surface fluxes of carbon at a model grid resolution. When applied to the CAM3.5 model, the LETKF gave very promising results as well, although only one month is available.

58 GEOSCIENCES↗
DOE OSTI2017

Methane emissions from dairies in the Los Angeles Basin

We estimate the amount of methane (CH 4 ) emitted by the largest dairies in the southern California region by combining measurements from four mobile solar-viewing ground-based spectrometers (EM27/SUN), in situ isotopic 13/12 CH 4 measurements from a CRDS analyzer (Picarro), and a high-resolution atmospheric transport simulation with a Weather Research and Forecasting model in large-eddy simulation mode (WRF-LES). The remote sensing spectrometers measure the total column-averaged dry-air mole fractions of CH 4 and CO 2 (X CH 4 and X CO 2 ) in the near infrared region, providing information on total emissions of the dairies at Chino. Differences measured between the four EM27/SUN ranged from 0.2 to 22ppb (part per billion) and from 0.7 to 3ppm (part per million) for X CH 4 and X CO 2 , respectively. To assess the fluxes of the dairies, these differential measurements are used in conjunction with the local atmospheric dynamics from wind measurements at two local airports and from the WRF-LES simulations at 111m resolution. Our top-down CH 4 emissions derived using the Fourier transform spectrometers (FTS) observations of 1.4 to 4.8ppts -1 are in the low end of previous top-down estimates, consistent with reductions of the dairy farms and urbanization in the domain. However, the wide range of inferred fluxes points to the challenges posed by the heterogeneity of the sources and meteorology. Inverse modeling from WRF-LES is utilized to resolve the spatial distribution of CH 4 emissions in the domain. Both the model and the measurements indicate heterogeneous emissions, with contributions from anthropogenic and biogenic sources at Chino. A Bayesian inversion and a Monte Carlo approach are used to provide the CH 4 emissions of 2.2 to 3.5ppts -1 at Chino.

54 ENVIRONMENTAL SCIENCES↗
NASA NTRS2012

An Analysis of Operational Total Lightning Data During Long-Track Tornadoes

The 27 April 2011 tornado outbreak brought three distinct waves of tornadic thunderstorms to portions of Mississippi, Alabama, Tennessee, and Georgia, striking the Tennessee Valley of north Alabama and southern Tennessee particularly hard. A total of 42 tornado paths were surveyed across the fourteen county area covered by the National Weather Service (NWS) forecast office in Huntsville, Alabama. Ten of these tornadoes were on the ground for at least 20 miles, two had total path lengths over 130 miles, and six tornadoes were classified as violent (EF-4 or EF-5 on the Enhanced Fujita Scale). Many of these tornadoes occurred within the domain of the North Alabama Lightning Mapping Array (NALMA), a ground-based total lightning detection network owned and operated by the NASA Marshall Space Flight Center. Since 2003, the NASA Short-term Prediction Research and Transition Center has supplied data from NALMA in real time to NWS forecast offices in Huntsville, Knoxville/Tri-Cities, Birmingham, and Nashville. Previous research has documented the utility of total lightning information in predicting tornadogenesis, particularly when combined with other remote sensing tools. Basic warning decision-making during events such as 27 April is not the most difficult part of the process; instead, the focus of warning meteorologists shifts to looking for changes in intensity or possible particularly dangerous situations, since doppler radar velocity data often cannot distinguish between weak and strong tornadoes. To that end, this research attempts to determine if any correlation exists between flash densities of the longest-tracked tornadoes over time, and the surveyed wind speeds of the tornadoes. The long-track EF-5 tornado which struck the Hackleburg, Phil Campbell, and Tanner communities in north Alabama was the primary focus of this research due to its intensity and extended life cycle. However, not all tornadoes were available for total lightning analysis due to widespread power outages which negatively affected the detection efficiency and operation of the NALMA. Therefore, additional storms from 2008-2010 with tracks of at least 20 miles were analyzed for comparison purposes.

Carcione, Brian C.↗