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Ott, L.

Publications and source records attributed to Ott, L..

17 records
All sourcesNASA NTRSDOE OSTI
NASA NTRS2019

Characteristics of Total Column CO2 Retrievals from the OCO Missions: Biases, Information Content and Implications for Flux Inversions

The Orbiting Carbon Observatory-2 and Orbiting Carbon Observatory-3, launched in 2015 and 2019, respectively, are intended to collect and deliver high-resolution observations of CO2 with unprecedented space and time coverage. Observations of CO2 from these remote-sensing missions (also known as XCO2, or column-based average, dry air mole fraction of CO2) are then used by the global carbon cycle community to answer a wide range of science questions, from the distribution and quantification of global and regional CO2 source-sink patterns to quantification of anthropogenic sources at urban scales. Even though we have had the OCO-2 mission flying for a few years now, the retrieval algorithms are continuously evolving and improving to deliver XCO2 retrievals with very high precision and high accuracy (or low biases). In this presentation, we will discuss a simple yet effective quantitative framework that has been developed by the OCO-2 flux team to evaluate the information content of these XCO2 retrievals as soon as they are released, i.e., with lower latency than full-scale flux inversions. This framework serves as a precursor to advanced inverse modeling frameworks and is intended to provide an early but accurate assessment of the signal present in the satellite retrievals, the robustness of that signal, and the ability of these retrievals to resolve patterns in CO2 surface fluxes that cannot be resolved by our current network of surface sites. Specific results will tackle a tiered set of questions that are being addressed using this framework: (a) what are the distribution of retrievals in the different modes of operation and how do they vary in space and time? (b) what is the information that is being given to the inverse modeling frameworks from the space-based data, information above and beyond what is provided by the in-situ data? and (c) how do these factors influence our choices for doing flux inversions with the satellite retrievals? While the primary focus of the results will be on application of this technique to mature OCO-2 retrievals, we will show early results for a couple of months of OCO-3 retrievals. For the time-period that the retrievals from the two missions overlap, we will highlight how this framework allows us to effortlessly put the information from OCO-3 and OCO-2 on an equal footing, thus enabling easy comparison between the two pioneering missions.

Chatterjee, Abhishek↗
NASA NTRS2019

GEOS-Carb III: Delivering Mature Carbon Flux and Concentration Datasets in Support of NASA's Carbon Monitoring System

The GEOS-Carb project seeks to make high quality, data-driven products that support NASA's Carbon Monitoring System Program. These include bottom-up land and ocean flux estimates along with fossil fuel emissions, all informed by satellite data and the MERRA-2 reanalysis. These flux data support atmospheric carbon products that include both simulations and data assimilation products. We show examples of this work and discuss applications to future mission planning.

Ott, L.↗
NASA NTRS2019

Progress in Atmospheric Carbon Monitoring Using NASA's GEOS Model and Data from the OCO and GOSAT Missions

NASA's Global Modeling and Assimilation Office (GMAO) produces a variety of carbon products based the synthesis of satellite remote sensing data and outputs of the Goddard Earth Observing System (GEOS). This includes bottom-up surface fluxes due to fossil fuel emissions, biomass burning, terrestrial biospheric exchange, and ocean exchangeconstrained by measurements of nighttime lights, fire radiative power, normalized difference vegetation index, and ocean color. These fluxes are the basis of top-down estimates of carbon concentrations and fluxes. In particular, the GMAO system processes retrievals of column carbon dioxide (XCO2) from GOSAT and OCO-2 to produce a high-resolution, long-term global analysis of CO2 in three dimensions every 6 hours. Here, we discuss the potential applications of such products for satellite intercomparison and evaluation against independent, non-coincident data. We also highlight the ability to provide monthly global atmospheric growth rates inferred from the assimilated CO2 concentration product. Finally, we discuss the challenges facing such products including bias correction and the estimation and analysis of model transport errors.

Weir, B.↗
NASA NTRS2019

The Ability of GeoCarb to Constrain the Interannual Variability of Carbon Gases over the Amazon

We perform a number of idealized assimilation experiments with the GEOS constituent data assimilation system to test the ability of GeoCarb retrievals of CO, CO2, and CH4 to constrain the interannual variability of these gases over the Amazon. Retrievals for instruments on other satellites which observe in similar channels (e.g. MOPITT, GOSAT, and OCO-2) are limited due to persistent cloud coverage. Given its ability to sample the same location multiple times in one day, the expectation is that GeoCarb retrievals will return more soundings than those from previous missions. The goal of the assimilation experiments is to understand which scanning strategies lead to the best sounding densities and thus have the best chance of constraining interannual variability in the carbon species. The experiments each begin by picking a given year at random from a nature run (i.e., a model simulation meant to represent the truth). The model fields are sampled according to a given strategy and then screened to account for cloud coverage. Next, we pick another year at random and assimilate the synthetic GeoCarb samples into the GEOS model for that year. The output of the assimilation, 6-hourly, 3D fields of each constituent, is then directly comparable to the nature run. This comparison allows us to evaluate the ability of GeoCarb measurements to constrain the interannual variability of each gas.

Weir, B.↗
NASA NTRS2018

Toward Integrated Seasonal Predictions of Land and Ocean Carbon Flux: Lessons from the 2015-16 El Nino

Seasonal forecasts made by coupled atmosphere-ocean general circulation models (GCMs) are increasingly able to provide skillful forecasts of climate anomalies. At some centers, the capabilities of these models are being expanded to represent carbon-climate feedbacks including ocean biogeochemistry (OB), terrestrial biosphere (TB) interactions, and fires. These advances raise the question of whether such models can support skillful forecasts of carbon fluxes.Here, we examine whether land and ocean carbon flux anomalies associated with the 2015-16 El Nino could have been predicted months in advance. This El Nino was noteworthy for the magnitude of the ocean temperature perturbation, the skill with which this perturbation was predicted, and the extensive satellite observations that can be used to track its impact. We explore this topic using NASA's Goddard Earth Observing System (GEOS) model, which routinely produces an ensemble of seasonal climate forecasts, and a suite of offline dynamical and statistical models that estimate carbon flux processes. Using GEOS forecast fields from 2015-16 to force flux model hindcasts shows that these models are able to reproduce significant features observed by satellites. Specifically, OB hindcasts are able to predict anomalies in chlorophyll distributions with lead times of 3-4 months. The ability of TB hindcasts to reproduce NDVI anomalies is driven by the skill of the climate forecast, which is greatest at short lead times over tropical landmasses. Statistical fire forecasts driven by ocean climate indices are able to predict burned area in the tropics with lead times of 3-12 months. We also integrate the ocean and land hindcast fluxes into the GEOS GCM to examine the magnitude of the atmospheric carbon dioxide anomaly and compare with satellite and ground-based observations.While seasonal forecasting remains an active area of research, these results demonstrate that forecasts of carbon flux processes can support a variety of applications, potentially allowing scientists to understand carbon-climate feedbacks as they happen and to capitalize on more flexible satellite technologies that allow areas of interest to be targeted with lead times of weeks to months. We also provide a first glimpse at the spring 2019 carbon forecast using the GEOS-based forecasting system.

Ott, L.↗
NASA NTRS2018

The Use of Gridded Fossil Fuel CO2 Emissions (FFCO2) Inventory for Climate Mitigation Applications: Errors, Uncertainties, and Current and Future Challenges

Emission Inventory (EI) is a fundamental tool to monitor global compliance of greenhouse gases (GHGs) emissions reduction actions. Inventory guidelines provide a best practice to help EI compilers to make comparable national emission estimates, in spite of the differences in data availability across countries and regions. There are a variety of sources of errors and uncertainties, however, that originate beyond what the inventory guidelines define. For example, spatially-explicit EIs, which are a key product for atmospheric modeling applications, are often developed for research purposes, and there are no specific guidelines to disaggregate emission estimates from country scale. On top of that, EIs are fundamentally prone to systematic biases due to the simple calculation methodology and thus an objective evaluation (e.g. atmospheric top-down estimates) is needed to assure the accuracy of the estimates. ODIAC is a global high-resolution (1x1 km) fossil fuel carbon dioxide (CO2) gridded EI that is now often used in atmospheric CO2 modeling. ODIAC is based on disaggregation of national emission estimates made by CDIAC, which is the well accepted standard in the community. The ODIAC emission data product is updated on an annual basis using best available statistical data. Subnational spatial emission patterns are estimated using power plant profiles and satellite-observations of nighttime lights. In addition to the conventional CDIAC gridded data product, ODIAC carries international bunker emissions (shipping and aviation), which allows flux inversion modelers to accurately impose the global total fossil fuel emissions and their horizontal and vertical distribution. We have extensively evaluated ODIAC emissions using fine-grained EIs as well as a high-resolution atmospheric model simulation across different scales (national, subnational/regional, and urban policy relevant) with a focus on the uncertainties associated with the emission disaggregation. We have examined the use of NASA's Black Marble Suomi-NPP/VIIRS nightlight data.

Oda, Tomohiro↗
NASA NTRS2017

Assessing Uncertainties in Gridded Emissions: A Case Study for Fossil Fuel Carbon Dioxide (FFCO2) Emission Data

Fossil fuel carbon dioxide (CO2) emissions (FFCO2) are the largest input to the global carbon cycle on a decadal time scale. Because total emissions are assumed to be reasonably well constrained by fuel statistics, FFCO2 often serves as a reference in order to deduce carbon uptake by poorly understood terrestrial and ocean sinks. Conventional atmospheric CO2 flux inversions solve for spatially explicit regional sources and sinks and estimate land and ocean fluxes by subtracting FFCO2. Thus, errors in FFCO2 can propagate into the final inferred flux estimates. Gridded emissions are often based on disaggregation of emissions estimated at national or regional level. Although national and regional total FFCO2 are well known, gridded emission fields are subject to additional uncertainties due to the emission disaggregation. Assessing such uncertainties is often challenging because of the lack of physical measurements for evaluation. We first review difficulties in assessing uncertainties associated with gridded FFCO2 emission data and present several approaches for evaluation of such uncertainties at multiple scales. Given known limitations, inter-emission data differences are often used as a proxy for the uncertainty. The popular approach allows us to characterize differences in emissions, but does not allow us to fully quantify emission disaggregation biases. Our work aims to vicariously evaluate FFCO2 emission data using atmospheric models and measurements. We show a global simulation experiment where uncertainty estimates are propagated as an atmospheric tracer (uncertainty tracer) alongside CO2 in NASA's GEOS model and discuss implications of FFCO2 uncertainties in the context of flux inversions. We also demonstrate the use of high resolution urban CO2 simulations as a tool for objectively evaluating FFCO2 data over intense emission regions. Though this study focuses on FFCO2 emission data, the outcome of this study could also help improve the knowledge of similar gridded emissions data for non-CO2 compounds with similar emission characteristics.

FFCO↗
NASA NTRS2014

Sensitivity of CO2 Simulation in a GCM to the Convective Transport Algorithms

Convection plays an important role in the transport of heat, moisture and trace gases. In this study, we simulated CO2 concentrations with an atmospheric general circulation model (GCM). Three different convective transport algorithms were used. One is a modified Arakawa-Shubert scheme that was native to the GCM; two others used in two off-line chemical transport models (CTMs) were added to the GCM here for comparison purposes. Advanced CO2 surfaced fluxes were used for the simulations. The results were compared to a large quantity of CO2 observation data. We find that the simulation results are sensitive to the convective transport algorithms. Overall, the three simulations are quite realistic and similar to each other in the remote marine regions, but are significantly different in some land regions with strong fluxes such as Amazon and Siberia during the convection seasons. Large biases against CO2 measurements are found in these regions in the control run, which uses the original GCM. The simulation with the simple diffusive algorithm is better. The difference of the two simulations is related to the very different convective transport speed.

Convection↗
NASA NTRS2014

Observation of Mountain Lee Waves with MODIS NIR Column Water Vapor

Mountain lee waves have been previously observed in data from the Moderate Resolution Imaging Spectroradiometer (MODIS) "water vapor" 6.7 micrometers channel which has a typical peak sensitivity at 550 hPa in the free troposphere. This paper reports the first observation of mountain waves generated by the Appalachian Mountains in the MODIS total column water vapor (CWV) product derived from near-infrared (NIR) (0.94 micrometers) measurements, which indicate perturbations very close to the surface. The CWV waves are usually observed during spring and late fall or some summer days with low to moderate CWV (below is approx. 2 cm). The observed lee waves display wavelengths from3-4 to 15kmwith an amplitude of variation often comparable to is approx. 50-70% of the total CWV. Since the bulk of atmospheric water vapor is confined to the boundary layer, this indicates that the impact of thesewaves extends deep into the boundary layer, and these may be the lowest level signatures of mountain lee waves presently detected by remote sensing over the land.

satellite remote sensing↗
NASA NTRS2012

Global Estimates of PBL Depth from Space-Borne LIDAR

The planetary boundary layer (PBL) is responsible for communicating the exchange of energy, moisture, momentum, pollutants, and aerosols between the surface and the free atmosphere and is therefore crucial to many studies of the atmosphere. Unfortunately, there have historically been few observations of this important layer due to the complexity involved in its measurement. However, with the advent of more advanced satellites, global measurements of the PBL are now becoming possible. The PBL is often characterized by a high concentration of aerosols within the layer and low level clouds capping it and these are observable from space. The Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observations (CALIPSO) satellite was launched in 2006 with the intention of observing aerosols and clouds and was the first space-based LIDAR optimized for this purpose. CALIPSO observations are therefore well suited to observing the depth of the PBL. Since it was launched, CALIPSO has been making nearly continuous measurements enabling a global picture of PBL depth. We plan to present a global PBL depth product and how it evolves throughout the year. The product is able to identify deeper PBL depths in the summer hemisphere over land and deeper depths along the northern hemisphere oceanic storm tracks in winter associated with cold air traveling over warm water. Large seasonal cycles are also evident in the subtropical desert locations among other features. In addition, comparisons will be made between several estimates of PBL depth based on turbulent intensity, meteorology profiles, and aerosol profiles from the GEOS5 model.

McGrath-Spangler, Erica lynn↗
NASA NTRS2012

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

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

Ott, L.↗
NASA NTRS2012

New Approaches to Quantifying Transport Model Error in Atmospheric CO2 Simulations

In recent years, much progress has been made in observing CO2 distributions from space. However, the use of these observations to infer source/sink distributions in inversion studies continues to be complicated by difficulty in quantifying atmospheric transport model errors. We will present results from several different experiments designed to quantify different aspects of transport error using the Goddard Earth Observing System, Version 5 (GEOS-5) Atmospheric General Circulation Model (AGCM). In the first set of experiments, an ensemble of simulations is constructed using perturbations to parameters in the model s moist physics and turbulence parameterizations that control sub-grid scale transport of trace gases. Analysis of the ensemble spread and scales of temporal and spatial variability among the simulations allows insight into how parameterized, small-scale transport processes influence simulated CO2 distributions. In the second set of experiments, atmospheric tracers representing model error are constructed using observation minus analysis statistics from NASA's Modern-Era Retrospective Analysis for Research and Applications (MERRA). The goal of these simulations is to understand how errors in large scale dynamics are distributed, and how they propagate in space and time, affecting trace gas distributions. These simulations will also be compared to results from NASA's Carbon Monitoring System Flux Pilot Project that quantified the impact of uncertainty in satellite constrained CO2 flux estimates on atmospheric mixing ratios to assess the major factors governing uncertainty in global and regional trace gas distributions.

Ott, L.↗
NASA NTRS2011

Towards a Model Climatology of Relative Humidity in the Upper Troposphere for Estimation of Contrail and Contrail-Induced Cirrus

The formation of contrails and contrail cirrus is very sensitive to the relative humidity of the upper troposphere. To reduce uncertainty in an estimate of the radiative impact of aviation-induced cirrus, a model must therefore be able to reproduce the observed background moisture fields with reasonable and quantifiable fidelity. Here we present an upper tropospheric moisture climatology from a 26-year ensemble of simulations using the GEOS CCM. We compare this free-running model's moisture fields to those obtained from the MLS and AIRS satellite instruments, our most comprehensive observational databases for upper tropospheric water vapor. Published comparisons have shown a substantial wet bias in GEOS-5 assimilated fields with respect to MLS water vapor and ice water content. This tendency is clear as well in the GEOS CCM simulations. The GEOS-5 moist physics in the GEOS CCM uses a saturation adjustment that prevents supersaturation, which is unrealistic when compared to in situ moisture observations from MOZAIC aircraft and balloon sondes as we will show. Further, the large-scale satellite datasets also consistently underestimate super-saturation when compared to the in-situ observations. We place these results in the context of estimates of contrail and contrail cirrus frequency.

Selkirk, Henry B.↗
NASA NTRS2004

Florida Thunderstorms: A Faucet of Reactive Nitrogen to the Upper Troposphere

During the NASA Cirrus Regional Study of Tropical Anvils and Cirrus Layers-Florida Area Cirrus Experiment (CRYSTAL-FACE) enhanced mixing ratios of nitric oxide were measured in the anvils of thunderstorms and in clear air downwind of storm systems on flights of a Wl3-57F high-altitude aircraft. Mixing ratios greater than l0 - 20 times background were readily observed over distances of 25-120 km due to lightning activity. In many of the Florida storms deposition of NO occurred up to near the tropopause but major deposition usually occurred 1 - 2 km below the tropopause, or mostly within the visible anvil volume formed prior to storm decay. Observations from two storms of very different anvil size and electrical activity allowed estimates of the total mass of NO, vented to the middle and upper troposphere. Using the cloud-to ground (CG) flash accumulations from the National Lightning Detection Network, climatological intra-cloud (IC) to CG ratios, and assuming that CG and IC flashes were of equivalent efficiency for NO production, the ranges of production per flash for a moderate-sized and a large storm were (0.51 - 1.0) x l0(exp 26) and (2.3 - 3.1) x 10(exp 26) molecules NO/flash, respectively. Using the recently determined average global flash rate of 44 8, a gross extrapolation of these two storms to represent possible global annual production rates yield 1.6 - 3.2 and 7.3 - 9.9 Tg(N)/yr, respectively. If the more usual assumption is made that IC efficiency is l/l0th that of CG activity, the ranges of production for the moderate-sized and large storm were (1.3 - 2.7) x l0(exp 26) and (6.0 - 8.1) x l0(exp 26) molecules NO/CG flash, respectively. The estimates from the large storm may be high because there is indirect evidence that the IC/CG ratio was larger than would be derived from climatology. These two storms and others studied did not have flash rates that scaled as approx. H(sup 5) where H is the cloud top altitude. The observed CG flash accumulations and NO(x) mass production estimate for the month of July over the Florida area were compared with a representative 3D global Chemistry-Transport Model (CTMJ that uses the Price et al. lightning parameterization. For two land grid points representing the Florida peninsula the model compared well with the observations: CG flash rates were low by only a factor of approx. 2. When the model grid points included the coastal regions of Florida the flash accumulations were lower than observed by a factor of 3.4 - 4.6. It is recommended that models using the Price et al. parameterization allow any global coastal grid point to maintain the land rather than the marine flash rate parameterization. The convection in this CTM underestimated the actual cloud top heights over Florida by 1 - 2 km and thus the total lightning flash rates and the altitude range of reactive nitrogen deposition. Broad scale (20 - 120 km) median mixing ratios of NO within anvils over Florida were significantly larger than in storms previously investigated over Colorado and New Mexico.

Ridley, B.↗
NASA NTRS1995

Results from GROCSE I: A real-time search for gamma ray burst optical counterparts

The GROCSE I experiment (Gamma-Ray Optical Counterpart Search Experiment) is a rapid slewing wide field of view optical telescope at Lawrence Livermore National Laboratory which responds to triggers from the BATSE GRB data telemetry stream that have been processed and distributed by the BACODINE network. GROCSE 1 has been in continuous automated operation since January 1994. As of October 1995, sky images for 22 GRB triggers have been recorded, in some cases while the burst was still emitting gamma rays. The preliminary analysis of eight of these events are presented here. No optical counterparts have yet been detected. Limits for optical emission are given.

Lee, B.↗
NASA NTRS1995

Gamma Ray Burst Optical Counterpart Search Experiment (GROCSE)

GROCSE (Gamma-Ray Optical Counterpart Search Experiments) is a system of automated telescopes that search for simultaneous optical activity associated with gamma ray bursts in response to real-time burst notifications provided by the BATSE/BACODINE network. The first generation system, GROCSE 1, is sensitive down to Mv (approximately) 8.5 and requires an average of 12 seconds to obtain the first images of the gamma ray burst error box defined by the BACODINE trigger. The collaboration is now constructing a second generation system which has a 4 second slewing time and can reach Mv (approximately) 14 with a 5 second exposure. GROCSE 2 consists of 4 cameras on a single mount. Each camera views the night sky through a commercial Canon lens (f/1.8, focal length 200 mm) and utilizes a 2K x 2K Loral CCD. Light weight and low noise custom readout electronics were designed and fabricated for these CCDs. The total field of view of the 4 cameras is 17.6 x 17.6 (degree). GROCSE 2 will be operated by the end of 1995. In this paper, the authors present an overview of the GROCSE system and the results of measurements with a GROCSE 2 prototype unit.

Park, H. S.↗