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NASA’s PACE Ocean Color Instrument Thermal Design Evolution: from Goddard’s Instrument Design Lab through Flight Development

NASA’s Plankton, Aerosol, Cloud, ocean Ecosystem (PACE) mission, set to launch in 2024, seeks to provide data continuity for the ocean color, aerosol and cloud measurements acquired by NASA’s on-orbit Earth Science observatories since the 1990s. It will accomplish this through its Ocean Color Instrument (OCI), an optical spectrometer being developed for hyper-spectral measurements in the ultraviolet-to-near-infrared band between 340 nm and 2260 nm. Although OCI’s instrument architecture will provide greater insight and resolution than its predecessors in this wavelength range, the engineering required to achieve this also poses a greater challenge. In thermal engineering, this translates to a more complex thermal control approach to address high heat dissipations, stringent stabilities, the volume of heat that requires transport, and changing thermal environments due to tilting of the entire instrument ±20° twice per orbit. This current work explores how the PACE OCI instrument design has evolved from its initial conception in NASA Goddard’s Instrument Design Laboratory (IDL) to the current iteration of its flight design. The IDL studies explored three separate instrument configurations and two spatial resolutions per configuration, which were then down selected to a single instrument type and spatial resolution for flight instrument development. OCI subsequently went through major project milestones, including Preliminary Design Review (PDR), Critical Design Review (CDR), Pre-Environmental Review (PER) and Pre-Ship Review (PSR), with significant design updates along the way. This paper aims to provide a comprehensive account of OCI’s thermal control architecture evolution and the engineering drivers that have shaped it, with the goal of identifying trends spanning the full instrument development timeline to inform and advance future instrument thermal designs.

PACE↗

NASA’s PACE Ocean Color Instrument Thermal Design Evolution: from Goddard’s Instrument Design Lab through Flight Development

NASA’s Plankton, Aerosol, Cloud, ocean Ecosystem (PACE) mission, set to launch in 2024, seeks to provide data continuity for the ocean color, aerosol and cloud measurements acquired by NASA’s on-orbit Earth Science observatories since the 1990s. It will accomplish this through its Ocean Color Instrument (OCI), an optical spectrometer being developed for hyper-spectral measurements in the ultraviolet-to-near-infrared band between 340 nm and 2260 nm. Although OCI’s instrument architecture will provide greater insight and resolution than its predecessors in this wavelength range, the engineering required to achieve this also poses a greater challenge. In thermal engineering, this translates to a more complex thermal control approach to address high heat dissipations, stringent stabilities, the volume of heat that requires transport, and changing thermal environments due to tilting of the entire instrument ±20° twice per orbit. This current work explores how the PACE OCI instrument design has evolved from its initial conception in NASA Goddard’s Instrument Design Laboratory (IDL) to the current iteration of its flight design. The IDL studies explored three separate instrument configurations and two spatial resolutions per configuration, which were then down selected to a single instrument type and spatial resolution for flight instrument development. OCI subsequently went through major project milestones, including Preliminary Design Review (PDR), Critical Design Review (CDR), Pre-Environmental Review (PER) and Pre-Ship Review (PSR), with significant design updates along the way. This paper aims to provide a comprehensive account of OCI’s thermal control architecture evolution and the engineering drivers that have shaped it, with the goal of identifying trends spanning the full instrument development timeline to inform and advance future instrument thermal designs.

PACE↗

Pinatubo and pre-Pinatubo optical-depth spectra: Mauna Loa measurements, comparisons, inferred particle size distributions, radiative effects, and relationship to lidar data

The Ames airborne tracking sunphotometer was operated at the National Oceanic and Atmospheric Administration (NOAA) Mauna Loa Observatory (MLO) in 1991 and 1992 along with the NOAA Climate Monitoring and Diagnostics Laboratory (CMDL) automated tracking sunphotometer and lidar. June 1991 measurements provided calibrations, optical-depth spectra, and intercomparisons under relatively clean conditions; later measurements provided spectra and comparisons for the Pinatubo cloud plus calibration checks. June 1991 results are similar to previous MLO springtime measurements, with midvisible particle optical depth at the near-background level of 0.012 +/- 0.006 and no significant wavelength dependence in the measured range (lambda = 0.38 to 1.06 micrometers). The arrival of the Pinatubo cloud in July 1991 increased midvisible particle optical depth by more than an order of magnitude and changed the spectral shape of to an approximate power law with an exponent of about -1.4. By clearly September 1991, the spectrum was broadly peaked near 0.5 micrometers, and by July 1992, it was peaked near 0.8 micrometers. Our optical-depth spectra include corrections for diffuse light. NOAA- and Ames Research Center (ARC)-measured spectra are in good agreement. Columnar size distributions inverted from the spectra show that the initial (July 1991) post-Pinatubo cloud was relatively rich in small particles (r less than 0.25 micrometers), which were progressively depleted in the August-September 1991 and July 1992 periods. Conversely, both of the later periods had more of the optically efficient medium-sized particles (0.25 less than r less than 1 micrometers) than did the fresh July 1991 cloud. These changes are consistent with particle growth by condensation and coagulation. Photometer-inferred column backscatter values agree with those measured by the CMDL lidar on nearby nights. Combining lidar-measured backscatter profiles with photometer-derived backscatter-to-area ratios gives peak particle areas that could cause rapid heterogeneous loss of ozone, given sufficiently low particle acidity and suitable solar zenith angles (achieved at mid- to high latitudes). Top-of-troposphere radiative forcings for the September 1991 and July 1992 optical depths and size distributions over MLO are about -5 and -3 W/sq m, respectively (hence comparable in magnitude but opposite in sign to the radiative forcing caused by the increase in manmade greenhouse gases since the industrial revolution). Heating rates in the Pinatubo layer over MLO are 0.55 +/- 0.13 and 0.41 +/- 0.14 K/d for September 1991 and July 1992, respectively.

Russell, P. B.↗

Pinatubo and Pre-Pinatubo Optical-Depth Spectra: Mauna Loa Measurements, Comparisons, Inferred Particle Size Distributions, Radiative Effects, and Relationship to Lidar Data

The Ames airborne tracking sunphotometer was operated at the National Oceanic and Atmospheric Administration (NOAA) Mauna Loa Observatory (MLO) in 1991 and 1992 along with the NOAA Climate Monitoring and Diagnostics Laboratory (CMDL) automated tracking sunphotometer and lidar. June 1991 measurements provided calibrations, optical-depth spectra, and intercomparisons under relatively clean conditions; later measurements provided spectra and comparisons for the Pinatubo cloud plus calibration checks. June 1991 results are similar to previous MLO springtime measurements, with midvisible particle optical depth tau(sub p)(lambda = 0.526 microns) at the near-background level of 0.012 +/- 0.006 and no significant wavelength dependence in the measured range (lambda = 0.38 to 1.06 microns). The arrival of the Pinatubo cloud in July 1991 increased midvisible particle optical depth by more than an order of magnitude and changed the spectral shape of tau(sub p)(lambda) to an approximate power law with an exponent of about -1.4. By early September 1991, the spectrum was broadly peaked near 0.5 microns, and by July 1992, it was peaked near 0.8 microns. Our optical-depth spectra include corrections for diffuse light which increase postvolcanic midvisible tau(sub p) values by 1 to 3% (i.e., 0.0015 to 0.0023). NOAA- and Ames Research Center (ARC)-measured spectra are in good agreement. Columnar size distributions inverted from the spectra show that the initial (July 1991) post-Pinatubo cloud was relatively rich in small particles (r less than 0.25 microns), which were progressively depleted in the August-September 1991 and July 1992 periods. Conversely, both of the later periods had more of the optically efficient medium-sized particles (0.25 less than r less than 1 micron) than did the fresh July 1991 cloud. These changes are consistent with particle growth by condensation and coagulation. The effective, or area-weighted, radius increased from 0.22 +/- 0.06 micron in July 1991 to 0.56 +/- 0.12 micron in August-September 1991 and to 0.86 +/- 0.29 micron in July 1992. Corresponding column mass values were 4.8 +/- 0.7, 9.1 +/- 2.7, and 5.5 +/- 2 micro g/sq cm, and corresponding column surface areas were 4.4 +/- 0.5, 2.9 +/- 0.2, and 1.1 +/- 0.1 sq micron/sq cm,. Photometer-inferred column backscatter values agree with those measured by the CMDL lidar on nearby nights. Combining lidar-measured backscatter profiles with photometer-derived backscatter-to-area ratios gives peak particle areas that could cause rapid heterogeneous loss of ozone, given sufficiently low particle acidity and suitable solar zenith angles (achieved at mid- to high latitudes). Top-of-troposphere radiative forcings for the September 1991 and July 1992 optical depths and size distributions over MLO are about -5 and -3 W 1/sq m, respectively (hence comparable in magnitude but opposite in sign to the radiative forcing caused by the increase in manmade greenhouse gases since the industrial revolution). Heating rates in Pinatubo layer over MLO are 0.55 +/- 0.13 and 0.41 +/- 0.14 K/d for September 1991 and July 1992, respectively.

Russell, P. B.↗

Cloud condensation nuclei activity of internally mixed particle populations at a remote marine free troposphere site in the North Atlantic Ocean

Here, this study reports results from research conducted at the Observatory of Mount Pico (OMP), 2225 m above mean sea level on Pico Island in the Azores archipelago in June and July 2017. We investigated the chemical composition, mixing state, and cloud condensation nuclei (CCN) activities of long-range transported free tropospheric (FT) particles. FLEXible PARTicle Lagrangian particle dispersion model (FLEXPART) simulations reveal that most air masses that arrived at the OMP during the sampling period originated in North America and were highly aged (average plume age > 10 days). We probed size-resolved chemical composition, mixing state, and hygroscopicity parameter ($\mathcal{κ}$) of individual particles using computer-controlled scanning electron microscopy with an energy-dispersive X-ray spectrometer (CCSEM-EDX). Based on the estimated individual particle mass from elemental composition, we calculated the mixing state index, $χ$. During our study, FT particle populations were internally mixed ($χ$ of samples are between 53% and 87%), owing to the long atmospheric aging time. We used data from a miniature Cloud Condensation Nucleus Counter (miniCCNC) to derive the hygroscopicity parameter, $\mathcal{κ}$ CCNC . Combining $\mathcal{κ}$ CCNC and FLEXPART, we found that air masses recirculated above the North Atlantic Ocean with lower mean altitude had higher $\mathcal{κ}$ CCNC due to the higher contribution of sea salt particles. We used CCSEM-EDX and phase state measurements to predict single-particle $\mathcal{κ}$ ($\mathcal{κ}$ CCSEM-EDX ) values, which overlap with the lower range of $\mathcal{κ}$ CCNC measured below 0.15 % SS. Therefore, CCSEM-EDX measurements can be useful in predicting the lower bound of $\mathcal{κ}$, which can be used in climate models to predict CCN activities, especially in remote locations where online CCN measurements are unavailable.

54 ENVIRONMENTAL SCIENCES↗

Examining the Ice-Nucleating Particles from the Eastern North Atlantic (ExINP-ENA) (Field Campaign Report)

The Examining the Ice-Nucleating Particles from the Eastern North Atlantic (ExINP-ENA) field campaign was conducted at the U.S. Department of Energy (DOE) Atmospheric Radiation Measurement (ARM) user facility’s Eastern North Atlantic (ENA) observatory on Graciosa Island, Azores (39.0916° N, 28.0257° W). The ExINP-ENA campaign began on October 1, 2020, and collected data until March 28, 2021, for a total of 179 days of data generated, with a 45-day intensive operational period (IOP) from October 10 to November 24. This campaign was funded by the DOE Office of Science Early Career Research Program through grant DE-SC001879. This grant contains funding for three field campaigns. The previous field campaign at the Southern Great Plains (SGP) site in Oklahoma, ExINP-SGP, was completed in 2020 (36.6073° N, 97.4876° W), and the upcoming field campaign at the North Slope of Alaska (NSA), ExINP-NSA, will take place from October 2021 at the National Oceanic and Atmospheric Administration (NOAA) Barrow Atmospheric Baseline Observatory (71.3230° N, 156.6114° W).

54 ENVIRONMENTAL SCIENCES↗

Multi-seasonal measurements of the ground-level atmospheric ice-nucleating particle abundance on the North Slope of Alaska

Atmospheric ice-nucleating particles (INPs) are an important subset of aerosol particles that are responsible for the heterogeneous formation of ice crystals. INPs modulate the arctic cloud phase (liquid vs. ice), resulting in implications for radiative feedbacks. The number of arctic INP studies investigating specific INP episodes or sources increased recently. However, existing studies are based on short-duration field data, and long-term datasets are lacking. Continuous, long-term measurements are key to determining the abundance and variability of ambient arctic INPs and constraining aerosol–cloud interactions, e.g., to verify and/or improve simulations of mixed-phase clouds. Here, we present a new long-duration INP dataset from the Arctic: 2 years of predominantly immersion-mode INP concentrations (n INP ) measured continuously at the National Oceanic and Atmospheric Administration's Barrow Atmospheric Baseline Observatory (BRW) on the North Slope of Alaska. A portable ice nucleation experiment chamber (PINE-03), which simulates adiabatic expansion cooling, was used to directly measure the ground-level INP abundance with an approximately 12 min time resolution from October 2021 to December 2023. We document PINE-03 n INP measurements as well as estimated ice nucleation active surface site density (n s ) over a wide range of heterogeneous freezing temperatures from −16 to −31 °C from which we introduce new season-specific parameterizations suitable for modeling mixed-phase clouds. Collocated aerosol and meteorological data were analyzed to assess the correlation between ambient n INP , air mass origin region, and meteorological variability. Our findings suggest (1) very high freezing efficiency of INPs across the measured temperatures (n s ≈ 2×10 8 –10 10 m −2 for −16 to −31 °C), which is a factor of 10–1000 times greater efficiency as compared to that found in the previous mid-latitude INP measurements in fall using the same instrument; (2) surprisingly high n INP (≥ 1 L −1 at −25 °C) for the examined temperatures throughout the year that were not measured by PINE-03 at other sites; and (3) high n INP in spring, possibly related to arctic haze episodes. Relatively low concentrations of aerosol surface area and contrasting high-INP concentrations at BRW relative to mid-latitude sites are the possible reasons for the observed high freezing efficiency.

54 ENVIRONMENTAL SCIENCES↗

Relationships between summertime surface albedo and melt pond fraction in the central Arctic Ocean: The aggregate scale of albedo obtained on the MOSAiC floe

As part of the Multidisciplinary drifting Observatory for the Study of Arctic Climate (MOSAiC), the HELiX uncrewed aircraft system (UAS) was deployed over the sea ice in the central Arctic Ocean during summer 2020. Albedo measurements were obtained with stabilized pyranometers, and melt pond fraction was calculated from orthomosaic imagery from a surface-imaging multispectral camera. This study analyzed HELiX flight data to provide insights on the temporal and spatial evolution of albedo and melt pond fraction of the MOSAiC floe during the melt season as it drifted south through Fram Strait. The surface albedo distributions showed peak values changing from high albedo (0.55–0.6) to lower values (0.3) as the season advanced. Inspired by methods developed for satellite data, an algorithm was established to retrieve melt pond fraction from the orthomosaic images. We demonstrate that the near-surface observations of melt pond fraction were highly dependent on sample area, offering insight into the influence of subgrid scale features and spatial heterogeneity in satellite observations. Vertical observations conducted with the HELiX were used to quantify the influence of melt pond scales on observed surface albedo as a function of sensor footprint. These scaling results were used to link surface-based measurements collected during MOSAiC to broader-scale satellite data to investigate the influence of surface features on observed albedo. Albedo values blend underlying features within the sensor footprint, as determined by the melt pond size and concentration. This study framed the downscaling (upscaling) problem related to the airborne (surface) observations of surface albedo across a variety of spatial scales.

54 ENVIRONMENTAL SCIENCES↗

Aerosol Composition, Mixing State, and Phase State of Free Tropospheric Particles and Their Role in Ice Cloud Formation

The prediction of ice cloud formation in the atmosphere remains challenging. Free tropospheric aerosols can act as ice nucleating particles (INPs), affecting cloud properties and precipitation. The physicochemical properties of free tropospheric particles are modified upon long-range transport by different atmospheric processes. These modifications affect the ice formation potential of individual particles. We investigated free tropospheric particles collected at the remote Pico Mountain Observatory at 2225m a.s.l. in the North Atlantic Ocean using multimodal microspectroscopy and chemical imaging techniques. We probed their ice nucleation activity using an ice nucleation stage interfaced with an environmental scanning electron microscope. Retroplume analysis, chemical imaging, and micro-spectroscopy analysis indicated that the size-resolved chemical composition, mixing state, and phase state of the articles with similar aging times but different transport patterns were substantially different. Relative humidity-dependent glass transition temperatures estimated from meteorological conditions were consistent with the observed organic component of the particles' phase. More viscous (solid and semi-solid-like) particles are more ice active in deposition mode at temperature ranging from 205-220 K than those less viscous particles. Finally, this study provides a better understanding of the phase and mixing state of long range transported free tropospheric aerosols and their role in ice cloud formation.

54 ENVIRONMENTAL SCIENCES↗

Adjustments to the law of the wall above an Amazon forest explained by a spectral link

Modification to the law of the wall represented by a dimensionless correction function ϕ RSL (z/h) is derived using atmospheric turbulence measurements collected at two sites in the Amazon in near-neutral stratification, where z is the distance from the forest floor and h is the mean canopy height. The sites are the Amazon Tall Tower Observatory for z/h∈ [1,2.3] and the Green Ocean Amazon (GoAmazon) site for z/h∈ [1,1.4]. Here, a link between the vertical velocity spectrum E ww (k) (k is the longitudinal wavenumber) and ϕ RSL is then established using a co-spectral budget (CSB) model interpreted by the moving-equilibrium hypothesis. The key finding is that ϕ RSL is determined by the ratio of two turbulent viscosities and is given as ν t,BL /ν t,RSL, where ν t,RSL = (1/A)∫$^{∞}_{0}$ τ(k)E ww (k)dk, ν t,BL = k v (z−d)u * , τ(k) is a scale-dependent decorrelation time scale between velocity components, A = C R /(1−C I ) = 4.5 is predicted from the Rotta constant C R = 1.8, and the isotropization of production constant C I = 3/5 given by rapid distortion theory, k v is the von Kármán constant, u * is the friction velocity at the canopy top, and d is the zero-plane displacement. Because the transfer of energy across scales is conserved in E ww (k) and is determined by the turbulent kinetic energy dissipation rate (ε), the CSB model also predicts that ϕ RSL scales with L BL /L d , where L BL is the length scale of attached eddies to z = d, and L d = u$_{*}^{3}$/ε is a macro-scale dissipation length.

54 ENVIRONMENTAL SCIENCES↗

ARM FY2024 Aerosol Operations Plan

The Atmospheric Radiation Measurement user facility (ARM) deploys a suite of aerosol and trace gas (further mentions of aerosols will assume inclusion of trace gases) instrumentation at each of ARM's observatories. ARM currently deploys five Aerosol Observing Systems, one each at: Southern Great Plains (SGP); Eastern North Atlantic (ENA); ARM Mobile Fabilities (AMFI 1, 2, and 3). Aerosol measurements at ARM’s North Slope of Alaska (NSA) observatory have historically been made by the National Oceanic and Atmospheric Administration (NOAA) and provided to ARM through a collaboration. As ARM’s support for aerosol instrumentation increases, it is important for ARM to communicate plans and priorities for aerosol measurements to the community to maximize the benefit and planning around scientific activities and to advance confidence in ARM’s aerosol measurements. ARM will develop a yearly aerosol operations plan for the upcoming fiscal year (October 1-September 30) starting with FY24. This plan will be open and available through the ARM aerosol instrument webpages and will include: Review of the previous activities since the last plan (in this case, 2018); Planned activities and their priorities for the upcoming FY; Calibration timing and efforts; Planned activities for data products and value-added products (VAP).

54 ENVIRONMENTAL SCIENCES↗

The MOSAiC Distributed Network: Observing the coupled Arctic system with multidisciplinary, coordinated platforms

Central Arctic properties and processes are important to the regional and global coupled climate system. The Multidisciplinary drifting Observatory for the Study of Arctic Climate (MOSAiC) Distributed Network (DN) of autonomous ice-tethered systems aimed to bridge gaps in our understanding of temporal and spatial scales, in particular with respect to the resolution of Earth system models. By characterizing variability around local measurements made at a Central Observatory, the DN covers both the coupled system interactions involving the ocean-ice-atmosphere interfaces as well as three-dimensional processes in the ocean, sea ice, and atmosphere. The more than 200 autonomous instruments (“buoys”) were of varying complexity and set up at different sites mostly within 50 km of the Central Observatory. During an exemplary midwinter month, the DN observations captured the spatial variability of atmospheric processes on sub-monthly time scales, but less so for monthly means. They show significant variability in snow depth and ice thickness, and provide a temporally and spatially resolved characterization of ice motion and deformation, showing coherency at the DN scale but less at smaller spatial scales. Ocean data show the background gradient across the DN as well as spatially dependent time variability due to local mixed layer sub-mesoscale and mesoscale processes, influenced by a variable ice cover. The second case (May–June 2020) illustrates the utility of the DN during the absence of manually obtained data by providing continuity of physical and biological observations during this key transitional period. We show examples of synergies between the extensive MOSAiC remote sensing observations and numerical modeling, such as estimating the skill of ice drift forecasts and evaluating coupled system modeling. The MOSAiC DN has been proven to enable analysis of local to mesoscale processes in the coupled atmosphere-ice-ocean system and has the potential to improve model parameterizations of important, unresolved processes in the future.

54 ENVIRONMENTAL SCIENCES↗

A Century of Tidal Variability in the North Pacific Extracted from Hourly Geomagnetic Observatory Measurements at Honolulu

Previous analyses of hourly tide-gauge data taken at Honolulu since 1905 have shown that both sea level and the amplitude of the tides have increased synchronously over time, and a process has been proposed whereby the common cause is an increase in ocean temperature. Validation with independent data of this change in tides, as well as the proposed cause, has been lacking Ocean tides also generate magnetic fields that reach far outside the ocean, and tidal signals are clearly seen in the hourly data since 1905 from the Honolulu geomagnetic observatory. Here, it is found that the tidal amplitudes have increased synchronously in the tide-gauge and magnetic records, providing independent support for the previous results. Further information about the changing ocean is likely contained in the historical data from geomagnetic observatories as well as the global coverage of modern satellite magnetic surveys.

Robert H Tyler↗

Comparison of planetary boundary layer height from ceilometer with ARM radiosonde data

Abstract. Ceilometer measurements of aerosol backscatter profiles have been widely used to provide continuous planetary boundary layer height (PBLHT) estimations. To investigate the robustness of ceilometer-estimated PBLHT under different atmospheric conditions, we compared ceilometer- and radiosonde-estimated PBLHTs using multiple years of U.S. Department of Energy (DOE) Atmospheric Radiation Measurement (ARM) ceilometer and balloon-borne sounding data at ARM fixed-location atmospheric observatories and from ARM mobile facilities deployed around the world for various field campaigns. These observatories cover from the tropics to the polar regions and over both ocean and land surfaces. Statistical comparisons of ceilometer-estimated PBLHTs from the Vaisala CL31 ceilometer data with radiosonde-estimated PBLHTs from the ARM PBLHT-SONDE Value-added Product (VAP) are performed under different atmospheric conditions including stable and unstable atmospheric boundary layer, low-level cloud-free conditions, and cloudy conditions at these ARM observatories. Under unstable conditions, good comparisons are found between ceilometer- and radiosonde-estimated PBLHTs at ARM low- and mid-latitude land observatories. However, it is still challenging to obtain reliable PBLHT estimations over ocean surfaces even using radiosonde data. Under stable conditions, ceilometer- and radiosonde-estimated PBLHTs have weak correlations. We compare different PBLHT estimations utilizing the Heffter, the Liu–Liang, and the bulk Richardson number methods applied to radiosonde data with ceilometer-estimated PBLHT. We find that ceilometer-estimated PBLHT compares better with the Liu–Liang method under unstable conditions and compares better with the bulk Richardson number method under stable conditions.

54 ENVIRONMENTAL SCIENCES↗

Implications of Whole-Disc DSCOVR EPIC Spectral Observations for Estimating Earth's Spectral Reflectivity Based on Low-Earth-Orbiting and Geostationary Observations

Earth's reflectivity is among the key parameters of climate research. National Aeronautics and Space Administration (NASA)'s Earth Polychromatic Imaging Camera (EPIC) onboard National Oceanic and Atmospheric Administration (NOAA)'s Deep Space Climate Observatory (DSCOVR) spacecraft provides spectral reflectance of the entire sunlit Earth in the near backscattering direction every 65 to 110 min. Unlike EPIC, sensors onboard the Earth Orbiting Satellites (EOS) sample reflectance over swaths at a specific local solar time (LST) or over a fixed area. Such intrinsic sampling limits result in an apparent Earth's reflectivity. We generated spectral reflectance over sampling areas using EPIC data. The difference between the EPIC and EOS estimates is an uncertainty in Earth's reflectivity. We developed an Earth Reflector Type Index (ERTI) to discriminate between major Earth atmosphere components: clouds, cloud-free ocean, bare and vegetated land. Temporal variations in Earth's reflectivity are mostly determined by clouds. The sampling area of EOS sensors may not be sufficient to represent cloud variability, resulting in biased estimates. Taking EPIC reflectivity as a reference, low-earth-orbiting-measurements at the sensor-specific LST tend to overestimate EPIC values by 0.8% to 8%. Biases in geostationary orbiting approximations due to a limited sampling area are between −0.7% and 12%. Analyses of ERTI-based Earth component reflectivity indicate that the disagreement between EPIC and EOS estimates depends on the sampling area, observation time and vary between −10% and 23%.

DSCOVR↗

Analyzers Measure Greenhouse Gases, Airborne Pollutants

In complete darkness, a NASA observatory waits. When an eruption of boiling water billows from a nearby crack in the ground, the observatory s sensors seek particles in the fluid, measure shifts in carbon isotopes, and analyze samples for biological signatures. NASA has landed the observatory in this remote location, far removed from air and sunlight, to find life unlike any that scientists have ever seen. It might sound like a scene from a distant planet, but this NASA mission is actually exploring an ocean floor right here on Earth. NASA established a formal exobiology program in 1960, which expanded into the present-day Astrobiology Program. The program, which celebrated its 50th anniversary in 2010, not only explores the possibility of life elsewhere in the universe, but also examines how life begins and evolves, and what the future may hold for life on Earth and other planets. Answers to these questions may be found not only by launching rockets skyward, but by sending probes in the opposite direction. Research here on Earth can revise prevailing concepts of life and biochemistry and point to the possibilities for life on other planets, as was demonstrated in December 2010, when NASA researchers discovered microbes in Mono Lake in California that subsist and reproduce using arsenic, a toxic chemical. The Mono Lake discovery may be the first of many that could reveal possible models for extraterrestrial life. One primary area of interest for NASA astrobiologists lies with the hydrothermal vents on the ocean floor. These vents expel jets of water heated and enriched with chemicals from off-gassing magma below the Earth s crust. Also potentially within the vents: microbes that, like the Mono Lake microorganisms, defy the common characteristics of life on Earth. Basically all organisms on our planet generate energy through the Krebs Cycle, explains Mike Flynn, research scientist at NASA s Ames Research Center. This metabolic process breaks down sugars for energy to fuel cellular functions. "We think this chemical process did not exist when life first formed on Earth," he says, "because it is based on oxygen being available, and there was little oxygen available on the early Earth." It is possible that there are anaerobic regions beneath the sea floor in which life forms like those early non-Krebs Cycle microbes may yet exist. To detect and potentially collect samples of life emerging from hydrothermal vents, Flynn and his colleagues created Medusa, a multi-sensor instrument designed for long-term observation of diked vents on the ocean floor. When the vents erupt, Medusa assesses indicators of life within the expelled water. If the results are positive, the observatory collects samples and detaches from the ocean floor, making the long journey to the surface for retrieval by scientists. One of the indicators Medusa measures is the ratio of carbon isotopes in the water, namely carbon-12 and carbon-13. Living organisms preferentially take up carbon-12, Flynn says, so examining the ratio of these isotopes can help to determine the source of carbon in an environment as either biological or non-biological. "On Mars, there is evidence of localized methane in the atmosphere, and that methane could come from biological sources or from geochemical ones," Flynn says. "Determining the background planetary carbon isotope ratios and then evaluating the specific carbon ratios in this methane would help to determine how it was formed." A long-duration observatory similar to Medusa could one day provide essential evidence for or against the presence of life on the Red Planet or beneath the ice-crusted oceans of Europa.

Source record↗

ARM data-oriented metrics and diagnostics package for climate model evaluation (ARM-DIAGS-V3) version 3

A Python-based metrics and diagnostics package is currently being developed by the ARM Infrastructure Team at Lawrence Livermore National Laboratory to facilitate the use of long-term high frequency measurements from the ARM program in evaluating the regional climate simulation of clouds, radiation, precipitation, and aerosols. This metrics and diagnostics package computes climatological means of targeted climate model simulation and generates tables and plots for comparing the model simulation with ARM observational data. The CMIP model data sets are also included in the package to enable model inter-comparison as demonstrated in Zhang et al. (2018) and Zhang et al. (2020). The mean of the CMIP model can be served as a reference for individual models. Basic performance metrics are computed to measure the accuracy of mean state and variability of climate models. The evaluated physical quantities include cloud fraction, temperature, relative humidity, cloud liquid water path, total column water vapor, precipitation, sensible and latent heat fluxes, aerosol optical depth, and radiative fluxes, with plan to extend to more fields, such as the evaluation of model simulated aerosol physicochemical properties and cloud microphysics properties. Process-oriented diagnostics focusing on aerosol, cloud, and precipitation-related phenomena are also being developed for the evaluation and development of specific model physical parameterizations. In addition to the Southern Great Plains (SGP), North Slope of Alaska (NSA) and Tropical Western Pacific (TWP) atmospheric observatories in the ARMDIAGS version 2.0, the version 3.0 package have extended to the data collected at the ARM Eastern North Atlantic (ENA) atmospheric observatory and the Observation and Modeling of the Green Ocean Amazon (GOAMAZON) field campaign. The metrics and diagnostics package are currently built upon standard Python libraries and additional Python packages developed by DOE (CDAT). The ARM metrics and diagnostic package is available publicly with the hope that it can serve as an easy entry point for climate modelers to compare their models with ARM data. In this report, we first provide an overview of major metrics in section 2. The input data, which constitutes the core content of the metrics and diagnostics package, is summarized in section 3. A user's guide documenting the workflow/structure of the version 3.0 codes and including step-by-step instruction for running the package is described in section 4.

54 ENVIRONMENTAL SCIENCES↗

Examining the Ice-Nucleating Particles from the North Slope of Alaska (ExINP-NSA) (Final Campaign Report)

The Examining the Ice-Nucleating Particles from the North Slope of Alaska (ExINP-NSA) campaign was conducted at the National Oceanic and Atmospheric Administration’s (NOAA) Barrow Atmospheric Baseline Observatory (71.3230° N, 156.6114° W, “BRW” hereafter), next to the Atmospheric Radiation Measurement (ARM) user facility NSA site and ~ 6 km northeast of the town of Utqiaġvik. The location of the NSA site is shown in Figure 1. Our observing period began in October 2021 and continued until May 2024. This campaign was funded by the U.S. Department of Energy (DOE) Office of Science Early Career Research Program through grant number DE-SC001879. This grant contains funding for three ARM field campaigns. The previous field campaigns were performed at ARM’s Southern Great Plains atmospheric observatory in Oklahoma (SGP; 36.6073° N, 97.4876° W) and the ARM’s Eastern North Atlantic atmospheric observatory on Graciosa Island, Azores (ENA; 39.0916° N, 28.0257° W). The ExINP-NSA campaign aims included: • Determining the number concentration of ice-nucleating particles (n INPs ) active at temperatures spanning the range of heterogeneous freezing processes (from ≈−30 °C to 0 °C) using a combination of online and offline measurements, • Determining whether local meteorological conditions and/or synoptic scale air mass transport impact INP abundance and/or ice nucleation efficiency, • Examining if the physicochemical properties of INPs relate to aerosol chemistry, and • Assessing if there is a similarity in INP properties across three ARM sites Multi-seasonal datasets of INP abundance in the NSA region were delivered from this campaign. This campaign also allowed researchers to perform a comprehensive analysis of atmospheric INPs based on long- term ground-based measurements in the Alaskan Arctic. Our data and results from the ExINP-NSA campaign will help refine current earth system models. One of the stated goals of ARM is to advance aerosol-cloud ice interaction, which will be a direct result of this campaign. Current earth system models poorly represent INPs, and the 15-minute time resolution data over several seasons generated during this campaign will provide an invaluable resource, especially combined with the datasets generated during two previous ARM ExINP campaigns. These datasets will allow for a greater understanding of ice nucleation processes as they may (or may not) relate to local meteorological processes and aerosol chemistry and will eventually help further the understanding of the Earth’s atmospheric processes and energy balance.

54 ENVIRONMENTAL SCIENCES↗