Fred to Jim, 6 October 1962

Personal correspondenc

Fred to Jim, 28 February 1958

Personal correspondenc

Remote sensing of near-infrared chlorophyll fluorescence from space in scattering atmospheres: implications for its retrieval and interferences with atmospheric CO_2 retrievals

With the advent of dedicated greenhouse gas space-borne spectrometers sporting high resolution spectra in the O_2 A-band spectral region (755–774 nm), the retrieval of chlorophyll fluorescence has become feasible on a global scale. If unaccounted for, however, fluorescence can indirectly perturb the greenhouse gas retrievals as it perturbs the oxygen absorption features. As atmospheric CO_2 measurements are used to invert net fluxes at the land–atmosphere interface, a bias caused by fluorescence can be crucial as it will spatially correlate with the fluxes to be inverted. Avoiding a bias and retrieving fluorescence accurately will provide additional constraints on both the net and gross fluxes in the global carbon cycle. We show that chlorophyll fluorescence, if neglected, systematically interferes with full-physics multi-band X_(CO_2) retrievals using the O_2 A-band. Systematic biases in X_(CO_2) can amount to +1 ppm if fluorescence constitutes 1% to the continuum level radiance. We show that this bias can be largely eliminated by simultaneously fitting fluorescence in a full-physics based retrieval. If fluorescence is the primary target, a dedicated but very simple retrieval based purely on Fraunhofer lines is shown to be more accurate and very robust even in the presence of large scattering optical depths. We find that about 80% of the surface fluorescence is retained at the top-of-atmosphere, even for cloud optical thicknesses around 2–5. We further show that small instrument modifications to future O_2 A-band spectrometer spectral ranges can result in largely reduced random errors in chlorophyll fluorescence, paving the way towards a more dedicated instrument exploiting solar absorption features only

Higher measured than modeled ozone production at increased NOx levels in the Colorado Front Range

Abstract. Chemical models must correctly calculate the ozone formation rate, P(O3), to accurately predict ozone levels and to test mitigation strategies. However, air quality models can have large uncertainties in P(O3) calculations, which can create uncertainties in ozone forecasts, especially during the summertime when P(O3) is high. One way to test mechanisms is to compare modeled P(O3) to direct measurements. During summer 2014, the Measurement of Ozone Production Sensor (MOPS) directly measured net P(O3) in Golden, CO, approximately 25 km west of Denver along the Colorado Front Range. Net P(O3) was compared to rates calculated by a photochemical box model that was constrained by measurements of other chemical species and that used a lumped chemical mechanism and a more explicit one. Median observed P(O3) was up to a factor of 2 higher than that modeled during early morning hours when nitric oxide (NO) levels were high and was similar to modeled P(O3) for the rest of the day. While all interferences and offsets in this new method are not fully understood, simulations of these possible uncertainties cannot explain the observed P(O3) behavior. Modeled and measured P(O3) and peroxy radical (HO2 and RO2) discrepancies observed here are similar to those presented in prior studies. While a missing atmospheric organic peroxy radical source from volatile organic compounds co-emitted with NO could be one plausible solution to the P(O3) discrepancy, such a source has not been identified and does not fully explain the peroxy radical model–data mismatch. If the MOPS accurately depicts atmospheric P(O3), then these results would imply that P(O3) in Golden, CO, would be NOx-sensitive for more of the day than what is calculated by models, extending the NOx-sensitive P(O3) regime from the afternoon further into the morning. These results could affect ozone reduction strategies for the region surrounding Golden and possibly other areas that do not comply with national ozone regulations. Thus, it is important to continue the development of this direct ozone measurement technique to understand P(O3), especially under high-NOx regimes

Processing TES Level-1B Data

TES L1B Subsystem is a computer program that performs several functions for the Tropospheric Emission Spectrometer (TES). The term "L1B" (an abbreviation of "level 1B"), refers to data, specific to the TES, on radiometric calibrated spectral radiances and their corresponding noise equivalent spectral radiances (NESRs), plus ancillary geolocation, quality, and engineering data. The functions performed by TES L1B Subsystem include shear analysis, monitoring of signal levels, detection of ice build-up, and phase correction and radiometric and spectral calibration of TES target data. Also, the program computes NESRs for target spectra, writes scientific TES level-1B data to hierarchical- data-format (HDF) files for public distribution, computes brightness temperatures, and quantifies interpixel signal variability for the purpose of first-order cloud and heterogeneous land screening by the level-2 software summarized in the immediately following article. This program uses an in-house-developed algorithm, called "NUSRT," to correct instrument line-shape factors

Heterogeneous N2O5 Uptake During Winter: Aircraft Measurements During the 2015 WINTER Campaign and Critical Evaluation of Current Parameterizations

Nocturnal dinitrogen pentoxide (N2O5) heterogeneous chemistry impacts regional air quality and the distribution and lifetime of tropospheric oxidants. Formed from the oxidation of nitrogen oxides, N2O5 is heterogeneously lost to aerosol with a highly variable reaction probability, γ(N2O5), dependent on aerosol composition and ambient conditions. Reaction products include soluble nitrate (HNO3 or NO3−) and nitryl chloride (ClNO2). We report the first‐ever derivations of γ(N2O5) from ambient wintertime aircraft measurements in the critically important nocturnal residual boundary layer. Box modeling of the 2015 Wintertime INvestigation of Transport, Emissions, and Reactivity (WINTER) campaign over the eastern United States derived 2,876 individual γ(N2O5) values with a median value of 0.0143 and range of 2 × 10−5 to 0.1751. WINTER γ(N2O5) values exhibited the strongest correlation with aerosol water content, but weak correlations with other variables, such as aerosol nitrate and organics, suggesting a complex, nonlinear dependence on multiple factors, or an additional dependence on a nonobserved factor. This factor may be related to aerosol phase, morphology (i.e., core shell), or mixing state, none of which are commonly measured during aircraft field studies. Despite general agreement with previous laboratory observations, comparison of WINTER data with 14 literature parameterizations (used to predict γ(N2O5) in chemical transport models) confirms that none of the current methods reproduce the full range of γ(N2O5) values. Nine reproduce the WINTER median within a factor of 2. Presented here is the first field‐based, empirical parameterization of γ(N2O5), fit to WINTER data, based on the functional form of previous parameterizations

Sources and Secondary Production of Organic Aerosols in the Northeastern United States during WINTER

Most intensive field studies investigating aerosols have been conducted in summer, and thus, wintertime aerosol sources and chemistry are comparatively poorly understood. An aerosol mass spectrometer was flown on the National Science Foundation/National Center for Atmospheric Research C‐130 during the Wintertime INvestigation of Transport, Emissions, and Reactivity (WINTER) 2015 campaign in the northeast United States. The fraction of boundary layer submicron aerosol that was organic aerosol (OA) was about a factor of 2 smaller than during a 2011 summertime study in a similar region. However, the OA measured in WINTER was almost as oxidized as OA measured in several other studies in warmer months of the year. Fifty‐eight percent of the OA was oxygenated (secondary), and 42% was primary (POA). Biomass burning OA (likely from residential heating) was ubiquitous and accounted for 33% of the OA mass. Using nonvolatile POA, one of two default secondary OA (SOA) formulations in GEOS‐Chem (v10‐01) shows very large underpredictions of SOA and O/C (5×) and overprediction of POA (2×). We strongly recommend against using that formulation in future studies. Semivolatile POA, an alternative default in GEOS‐Chem, or a simplified parameterization (SIMPLE) were closer to the observations, although still with substantial differences. A case study of urban outflow from metropolitan New York City showed a consistent amount and normalized rate of added OA mass (due to SOA formation) compared to summer studies, although proceeding more slowly due to lower OH concentrations. A box model and SIMPLE perform similarly for WINTER as for Los Angeles, with an underprediction at ages \u3c6 hr, suggesting that fast chemistry might be missing from the models

Anthropogenic Control over Wintertime Oxidation of Atmospheric Pollutants

Anthropogenic air pollutants such as nitrogen oxides (NO(x) = NO + NO(2)), sulfur dioxide (SO(2)), and volatile organic compounds (VOC), among others, are emitted to the atmosphere throughout the year from energy production and use, transportation, and agriculture. These primary pollutants lead to the formation of secondary pollutants such as fine particulate matter (PM(2.5)) and ozone (O(3)) and perturbations to the abundance and lifetimes of short-lived greenhouse gases. Free radical oxidation reactions driven by solar radiation govern the atmospheric lifetimes and transformations of most primary pollutants and thus their spatial distributions. During winter in the mid and high latitudes, where a large fraction of atmospheric pollutants are emitted globally, such photochemical oxidation is significantly slower. Using observations from a highly instrumented aircraft, we show that multi-phase reactions between gas-phase NO(x) reservoirs and aerosol particles, as well as VOC emissions from anthropogenic activities, lead to a suite of atypical radical precursors dominating the oxidizing capacity in polluted winter air, and thus, the distribution and fate of primary pollutants on a regional to global scale

The ACOS CO_2 retrieval algorithm – Part 1: Description and validation against synthetic observations

This work describes the NASA Atmospheric CO_2 Observations from Space (ACOS) X_(CO_2) retrieval algorithm, and its performance on highly realistic, simulated observations. These tests, restricted to observations over land, are used to evaluate retrieval errors in the face of realistic clouds and aerosols, polarized non-Lambertian surfaces, imperfect meteorology, and uncorrelated instrument noise. We find that post-retrieval filters are essential to eliminate the poorest retrievals, which arise primarily due to imperfect cloud screening. The remaining retrievals have RMS errors of approximately 1 ppm. Modeled instrument noise, based on the Greenhouse Gases Observing SATellite (GOSAT) in-flight performance, accounts for less than half the total error in these retrievals. A small fraction of unfiltered clouds, particularly thin cirrus, lead to a small positive bias of ~0.3 ppm. Overall, systematic errors due to imperfect characterization of clouds and aerosols dominate the error budget, while errors due to other simplifying assumptions, in particular those related to the prior meteorological fields, appear small