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Wennberg, Paul

Publications and source records attributed to Wennberg, Paul.

At least 19 records

Reflecting Sunlight: Recommendations for Solar Geoengineering Research and Research Governance

The National Academies of Sciences, Engineering, and Medicine (NASEM) report "Reflecting Sunlight: Recommendations for Solar Geoengineering Research and Research Governance" focused on three atmospheric-based Solar Geoengineering strategies: Stratospheric Aerosol Injection, Marine Cloud Brightening, Cirrus Cloud Thinning. The study recommends that a national (and internationally-coordinated) Solar Geoengineering research program be established and coordinated by the U.S. Global Change Research Program—with a focus on developing information needed by decision makers, not advancing a path to deployment. The study recommends a detailed framework for governance of this research, at both national and international levels. The study also recommends a detailed research agenda for this program, encompassing over a dozen transdisciplinary research topics that can be loosely grouped into the categories of (i) technical dimensions and impacts, (ii) social dimensions, and (iii) context and goals for solar geoengineering research itself.

54 ENVIRONMENTAL SCIENCES↗

Validation of OCO-2 and ACOS-GOSAT using HIPPO and TCCON

Consistent validation of satellite CO2 estimates is a prerequisite for using multiple satellite CO2measurements for joint flux inversion and establishing a long-term atmospheric CO2 data record. Wevalidate recent satellite observation of OCO-2 v7 and ACOS-GOSAT v7.3 using similar analysis as previouswork (Kulawik et al. (2016) and Frankenberg et al. (2106)) through comparisons to the HIAPER Pole-to-Pole Observations (HIPPO) and the Total Carbon Column Observing Network (TCCON) to estimate biasesand errors affecting the understanding of carbon cycle science. CarbonTracker RT is also compared tothe validation data, and additionally used to evaluate the mismatch between the HIPPO observationtimeframe and the OCO-2 record, which are offset by 3-7 years. Some key metrics that are validatedinclude the seasonal cycle phase and amplitude, latitudinal gradient by season, regional biases, anderrors with respect to averaging.

Kulawik, Susan S.↗

Validation of GOSAT Data Products; Interim Report on the GOSAT/TANSO Project

The Orbiting Carbon Observatory-2 (OCO-2) Team has continued working closely with the Greenhouse Gases Observing Satellite (GOSAT) team to (i) conduct vicarious calibration experiments in Railroad Valley, NV, U.S.A., (ii) retrieve estimates of X CO2 from OCO-2 and GOSAT TANSO-FTS data, and (iii) validate these products using internationally recognized standards. The OCO-/GOSAT relationship was reinforced in March 2015 with the signing a new Memorandum of Understanding between NASA and the GOSAT and GOSAT-2 partners. Over the past year, while the GOSAT team has been finalizing the V201 product, the OCO-2 team has focused primarily on the delivery of the OCO-2 product, providing new opportunities for cross calibration of the OCO-2 and GOSAT instruments and cross validation of their products. These efforts are just now producing results. Members of the OCO-2 team have also continued the analysis of the GOSAT V161.161 data and the ACOS B3.5 products. Those efforts have produced 2 new refereed publications and several others in review. The OCO-2 now preparing to reprocess the entire GOSAT TANSO-FTS data record using the GOSAT V201 product and OCO-2 B7 algorithm to produce a 7-year, multi-satellite climate data record for X(sub CO2).

Wennberg, Paul↗

Convective Distribution of Tropospheric Ozone and Tracers in the Central American ITCZ Region: Evidence from Observations During TC4

During the Tropical Composition, Clouds and Climate Coupling (TC4) experiment that occurred in July and August of 2007, extensive sampling of active convection in the ITCZ region near Central America was performed from multiple aircraft and satellite sensors. As part of a sampling strategy designed to study cloud processes, the NASA ER-2, WB-57 and DC-8 flew in stacked "racetrack patterns" in convective cells. On July 24, 2007, the ER-2 and DC-8 probed an actively developing storm and the DC-8 was hit by lightning. Case studies of this flight, and of convective outflow on August 5, 2007 reveal a significant anti-correlation between ozone and condensed cloud water content. With little variability in the boundary layer and a vertical gradient, low ozone in the upper troposphere indicates convective transport. Because of the large spatial and temporal variability in surface CO and other pollutants in this region, low ozone is a better convective indicator. Lower tropospheric tracers methyl hydrogen peroxide, total organic bromine and calcium substantiate the ozone results. OMI measurements of mean upper tropospheric ozone near convection show lower ozone in convective outflow. A mass balance estimation of the amount of convective turnover below the tropical tropopause transition layer (TTL) is 50%, with an altitude of maximum convective outflow located between 10 and 11 km, 4 km below the cirrus anvil tops. It appears that convective lofting in this region of the ITCZ is either a two-stage or a rapid mixing process, because undiluted boundary layer air is never sampled in the convective outflow.

Avery, Melody↗

Monitoring Exchange of CO2 - A KISS Workshop Report 2009

The problem and context: Can top-down estimates of carbon dioxide (CO2) fluxes resolve the anthropogenic emissions of China, India, the United States, and the European Union with an accuracy of +/-10% or better?The workshop "Monitoring Exchange of Carbon Dioxide" was convened at the Keck Institute for Space Studies in Pasadena, California in February 2010 to address this question. The Workshop brought together an international, interdisciplinary group of 24 experts in carbon cycle science, remote sensing, emissions inventory estimation, and inverse modeling. The participants reviewed the potential of space-based and sub-orbital observational and modeling approaches to monitor anthropogenic CO2 emissions in the presence of much larger natural fluxes from the exchange of CO2 between the land, atmosphere, and ocean. This particular challenge was motivated in part by the NRC Report "Verifying Greenhouse Gas Emissions" [Pacala et al., 2010]. This workshop report includes several recommendations for improvements to observing strategies and modeling frameworks for optimal and cost-effective monitoring of carbon exchange

Greenhouse Gas Emissions↗

Automation for System Safety Analysis

This presentation describes work to integrate a set of tools to support early model-based analysis of failures and hazards due to system-software interactions. The tools perform and assist analysts in the following tasks: 1) extract model parts from text for architecture and safety/hazard models; 2) combine the parts with library information to develop the models for visualization and analysis; 3) perform graph analysis and simulation to identify and evaluate possible paths from hazard sources to vulnerable entities and functions, in nominal and anomalous system-software configurations and scenarios; and 4) identify resulting candidate scenarios for software integration testing. There has been significant technical progress in model extraction from Orion program text sources, architecture model derivation (components and connections) and documentation of extraction sources. Models have been derived from Internal Interface Requirements Documents (IIRDs) and FMEA documents. Linguistic text processing is used to extract model parts and relationships, and the Aerospace Ontology also aids automated model development from the extracted information. Visualizations of these models assist analysts in requirements overview and in checking consistency and completeness.

Malin, Jane T.↗

A Sample of What We Have Learned from A-Train Cloud Measurements

The A-train active sensors CloudSat and CALIPSO provide detailed information about cloud vertical structure. Coarse vertical information can also be obtained from a combination of passive sensors (e.g. cloud liquid water content from AMSR-E, cloud ice properties from MLS and HIRDLS, cloud-top pressure from MODIS and AIRS, and UVNISINear IR absorption and scattering from OMI, MODIS, and POLDER). In addition, the wide swaths of instruments such as MODIS, AIRS, OMI, POLDER, and AMSR-E can be exploited to create estimates of the three-dimensional cloud extent. We will show how data fusion from A-train sensors can be used, e.g., to detect and map the presence of multiple layer/phase clouds. Ultimately, combined cloud information from Atrain instruments will allow for estimates of heating and radiative flux at the surface as well as UV/VIS/Near IR trace-gas absorption at the overpass time on a near-global daily basis. CloudSat has also dramatically improved our interpretation of visible and UV passive measurements in complex cloudy situations such as deep convection and multiple cloud layers. This has led to new approaches for unique and accurate constituent retrievals from A-train instruments. For example, ozone mixing ratios inside tropical deep convective clouds have recently been estimated using the Aura Ozone Monitoring Instrument (OMI). Field campaign data from TC4 provide additional information about the spatial variability and origin of trace-gases inside convective clouds. We will highlight some of the new applications of remote sensing in cloudy conditions that have been enabled by the synergy between the A-train active and passive sensors.

Joiner, Joanna↗