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NASA NTRSDate not supplied

Spaceborne Passive-Microwave Hail Detection: Global Climatologies, Validation, and Challenges Going Forward

In addition to the myriad threats that severe hailstorms pose to society, infrastructure and agriculture, severe hail is difficult to measure in situ, and surface-based hail reporting and detection methods are inconsistent and vulnerable to nonmeteorological biases. This motivates the use of spaceborne remote-sensing platforms to retrieve hail and construct climatologies in a globally uniform way. We have developed a hail detection algorithm that leverages the sensitivity of spaceborne passive-microwave radiometers to scattering by hail, particularly in the channels from 10 to 89 GHz. We use this retrieval to construct global passive-microwave climatologies of severe hail using the Tropical Rainfall Measuring Mission (TRMM) Microwave Imager (TMI), Global Precipitation Measurement Mission (GPM) Microwave Imager, Advanced Microwave Scanning Radiometer for EOS (AMSR-E), and Advanced Microwave Scanning Radiometer 2 (AMSR2) sensors and are working to extend into the pre-TRMM era to the Special Sensor Microwave Imager/Sounder (SSMI/(S)) data. Using coincident Global Precipitation Measurement (GPM) Ku-band precipitation radar, we assessed this retrieval and several others in the literature for their effectiveness and regional variability. We find that this retrieval, which leverages a signature in the Minimum 19-GHz polarization corrected temperature (PCT) combined with the 37-GHz PCT depression normalized by tropopause height constrains the radar reflectivity most tightly, and gives the least appearance of regional biases compared to other passive-microwave approaches in the literature. Satellite platforms offer consistent observations, even in remote, data-sparse, and oceanic regions that ground-based networks exclude. There are, however, potential disconnects between the processes identified aloft by the satellite and the resultant weather at the ground, leading to uncertainties in the retrievals that may propagate into satellite-based climatologies, particularly in the Tropics, where there are abundant strong - but not necessarily hailing - storms that are strongly represented in the current satellite climatologies. We will discuss ongoing efforts to assess and mitigate the contributing factors to these uncertainties, chiefly among them the effects of non-uniform beam filling in the passive-microwave footprint, and the relationships between the size distributions of hailstones aloft and the dynamic processes and environments with which they interact throughout their trajectories.

Sarah D. Bang↗
NASA NTRSDate not supplied

Identification and Study of Validation Level Test Cases for Computational Modeling of Non-Charring Ablators

Computational modeling of Thermal Protection System (TPS) materials, used for aerospace applications, provides numerous advantages in preliminary selection and design of a heatshield material and shape for atmospheric entry vehicles. However, to serve as a reliable tool for prediction of material thermal and ablative behavior, the modeling approach needs to be validated against real experimental and flight data, preferably at a range of applied conditions. The validation study is typically very complex as it requires reliable measured data not only for the material thermal response and surface recession, but also well characterized environmental conditions. The validation problem becomes even more complex when the material thermal response is dictated by multi-physics effects such as solid conduction, in-depth thermal decomposition, pyrolysis gas flow and chemical reactions. The multi-physics effects complicate not only the modeling effort, but also the experimental measurement for validation of various aspects of the highly coupled problem. In this study, an attempt is made to identify suitable experimental data that could serve as a source for validation of material thermal response modeling tools. To reduce the computational complexity, this study focuses only on non-charring ablators, where the material thermal response could be modeled with a single governing equation for solid conduction and the ablation is limited only to the surface of the material. With a well characterized and publicly available experimental data being sparse, the study is limited in presenting test cases for only three materials: camphor, graphite and FiberForm® in the sequence of increased modeling complexity. Graphite is a commonly used TPS material for aerospace applications, both for leading edges of high-speed vehicles and internal insulation of solid rocket motors. FiberForm® is a porous carbon pre-form used in preparation of the well known PICA material Tran et al. [1996]. Inclusion of camphor into the list is conditioned with the relative simplicity in modeling the material thermal and chemical response and the low-enthalpy flow environment. In addition, camphor has been used as a simple test material for study of flow transition behavior by Stock and Ginoux [1973] and assessment of a heatshield shape change at flight relevant conditions by Rotondi et al. [2022]. In this work, the identified experimental data was extracted from the public literature and test cases that yet have been published. As it was found from the review, not a single test case contains an exhaustive set of data that would validate every aspect of the material physics. However, in the data collected, various aspects of the material behavior can be still validated, such as surface and in-depth temperature, amount of recession and a shape change. The identified experimental data for each case is accompanied with a characterized flow environment and simulated boundary conditions predicted by a Data-Parallel Line Relaxation (DPLR) code Wright et al. [1998]. In addition, material thermal response numerical simulations in each test case are performed with Kentucky Aerothermodynamics and Thermal Response System (KATS-MR) Zibitsker et al. [2022] providing a comparative study and a sanity check for the proposed validation data. Sample results from the performed numerical study are shown below. Figure 1 shows distribution of surface heat flux and pressure values on a hemi-cylinder model made of FiberForm® and tested in HyMETS arc-jet facility. The results are shown for the high pressure condition among the two tests. Flow simulation was performed with DPLR code on a quarter of original geometry. In the figure, the quarter shape was mirrored across zx and xy planes to show the complete distribution. Figure 2 shows the material response results for the high pressure case (7500 Pa), simulated with KATS-MR and a comparison to the experimental data for the surface temperature and shape shape. The simulation was performed on a 2-D slice, extracted in the xy plane at the middle of the sample. Figure 3 shows the material response simulation for the low pressure case (3500 Pa) and a comparison to the experimental data for surface temperature and shape change.

ablation↗
NASA NTRS2022

Assimilation of SMAP Products for Improving Streamflow Simulations over Tropical Climate Region—Is Spatial Information More Important Than Temporal Information?

Streamflow is one of the key variables in the hydrological cycle. Simulation and forecasting of streamflow are challenging tasks for hydrologists, especially in sparsely gauged areas. Coarse spatial resolution remote sensing soil moisture products (equal to or larger than 9 km) are often assimilated into hydrological models to improve streamflow simulation in large catchments. This study uses the Ensemble Kalman Filter (EnKF) technique to assimilate SMAP soil moisture products at the coarse spatial resolution of 9 km (SMAP 9 km), and downscaled SMAP soil moisture product at the higher spatial resolution of 1 km (SMAP 1 km), into the Soil and Water Assessment Tool (SWAT) to investigate the usefulness of different spatial and temporal resolutions of remotely sensed soil moisture products in streamflow simulation and forecasting. The experiment was set up for eight catchments across the tropical climate of Vietnam, with varying catchment areas from 267 to 6430 km^2 during the period 2017–2019. We comprehensively evaluated the EnKF-based SWAT model in simulating streamflow at low, average, and high flow. Our results indicated that high-spatial resolution of downscaled SMAP 1 km is more beneficial in the data assimilation framework in aiding the accuracy of streamflow simulation, as compared to that of SMAP 9 km, especially for the small catchments. Our analysis on the impact of observation resolution also indicates that the improvement in the streamflow simulation with data assimilation is more significant at catchments where downscaled SMAP 1 km has fewer missing observations. This study is helpful for adding more understanding of performances of soil moisture data assimilation based hydrological modelling over the tropical climate region, and exhibits the potential use of remote sensing data assimilation in hydrology.

soil moisture↗
NASA NTRSDate not supplied

Forecasting with the GEOS-CF System and Other NASA Resources to Support Air Quality Management

Air quality (AQ) is a major and growing concern for public health around the world. Economic development, population growth, and climate change are all expected to exacerbate already poor AQ in many regions. Furthermore, AQ is often only sparsely monitored with reference-grade in-situ instruments. NASA resources and products have the potential to help in addressing this AQ data gap. The GEOS-CF (Goddard Earth Observing System – Composition Forecasting) global atmospheric composition modeling system is run each day at a global scale to provide recent estimates and five-day forecasts at hourly temporal resolution of atmospheric constituents relevant to AQ. NASA satellite missions (along with those of other space agencies) provide remotely-sensed estimates of atmospheric composition relevant to AQ. This paper gives a brief overview of these capabilities, and outlines the efforts underway to combine model forecasts, satellite retrievals, and surface-based measurements to provide more comprehensive and accurate estimates and forecasts of local AQ which will be broadly applicable and accessible globally.

GEOS-CF↗
NASA NTRS2022

Drill-Site Selection for Cosmogenic-Nuclide Exposure Dating of the Bed of the Greenland Ice Sheet

Direct observations of the size of the Greenland Ice Sheet during Quaternary interglaciations are sparse yet valuable for testing numerical models of ice-sheet history and sea level contribution. Recent measurements of cosmogenic nuclides in bedrock from beneath the Greenland Ice Sheet collected during past deep-drilling campaigns reveal that the ice sheet was significantly smaller, and perhaps largely absent, sometime during the past 1.1 million years. These discoveries from decades-old basal samples motivate new, targeted sampling for cosmogenic-nuclide analysis beneath the ice sheet. Current drills available for retrieving bed material from the US Ice Drilling Program require < 700 m ice thickness and a frozen bed, while quartz-bearing bedrock lithologies are required for measuring a large suite of cosmogenic nuclides. We find that these and other requirements yield only ∼ 3.4 % of the Greenland Ice Sheet bed as a suitable drilling target using presently available technology. Additional factors related to scientific questions of interest are the following: which areas of the present ice sheet are the most sensitive to warming, where would a retreating ice sheet expose bare ground rather than leave a remnant ice cap, and which areas are most likely to remain frozen bedded throughout glacial cycles and thus best preserve cosmogenic nuclides? Here we identify locations beneath the Greenland Ice Sheet that are best suited for potential future drilling and analysis. These include sites bordering Inglefield Land in northwestern Greenland, near Victoria Fjord and Mylius-Erichsen Land in northern Greenland, and inland from the alpine topography along the ice margin in eastern and northeastern Greenland. Results from cosmogenic-nuclide analysis in new sub-ice bedrock cores from these areas would help to constrain dimensions of the Greenland Ice Sheet in the past.

Greenland↗
NASA NTRS2022

Introducing and Evaluating the Climate Hazards Center IMERG with Stations (CHIMES) Timely Station-Enhanced Integrated Multisatellite Retrievals for Global Precipitation Measurement

As human exposure to hydroclimatic extremes increase and the number of in situ precipitation observations declines, precipitation estimates, such as those provided by the Integrated Multisatellite Retrievals for Global Precipitation Measurement (GPM) (IMERG) mission, provide a critical source of information. Here, we present a new gauge-enhanced dataset [the Climate Hazards Center IMERG with Stations (CHIMES)] designed to support global crop and hydrologic modeling and monitoring. CHIMES enhances the IMERG Late Run product using an updated Climate Hazards Center (CHC) high-resolution climatology (CHPclim) and low-latency rain gauge observations. CHPclim differs from other products because it incorporates long-term averages of satellite precipitation, which increases CHPclim ’s fidelity in data-sparse areas with complex terrain. This fidelity translates into performance increases in unbiased IMERGlate data, which we refer to as CHIME. This is augmented with gauge observations to produce CHIMES. The CHC’s curated rain gauge archive contains valuable contributions from many countries. There are two versions of CHIMES: preliminary and final. The final product has more copious and better-curated station data. Every pentad and month, bias-adjusted IMERGlate fields are combined with gauge observations to create pentadal and monthly CHIMESprelim and CHIMESfinal. Comparisons with pentadal, high-quality gridded station data show that IMERG late performs well (r = 0.75), but has some systematic biases which can be reduced. Monthly cross-validation results indicate that unbiasing increases the variance explained from 50% to 63% and decreases the mean absolute error from 48 to 39 mm month −1. Gauge enhancement then increases the variance explained to 75%, reducing the mean absolute error to 27 mm month −1.

Chris C funk↗
NASA NTRS2021

Trend Detection of Atmospheric Time Series: Incorporating Appropriate Uncertainty Estimates and Handling Extreme Events

This paper is aimed at atmospheric scientists without formal training in statistical theory. Its goal is to, 1) provide a critical review of the rationale for trend analysis of the time series typically encountered in the field of atmospheric chemistry; 2) describe a range of trend-detection methods; and 3) demonstrate effective means of conveying the results to a general audience. Trend detections in atmospheric chemical composition data are often challenged by a variety of sources of uncertainty, which often behave differently to other environmental phenomena such as temperature, precipitation rate, or stream flow, and may require specific methods depending on the science questions to be addressed. Some sources of uncertainty can be explicitly included in the model specification, such as autocorrelation and seasonality, but some inherent uncertainties are difficult to quantify, such as data heterogeneity and measurement uncertainty due to the combined effect of short- and long-term natural variability, instrumental stability, and aggregation of data from sparse sampling frequency. Failure to account for these uncertainties might result in an inappropriate inference of the trends and their estimation errors. On the other hand, the variation in extreme events might be interesting for different scientific questions, for example, the frequency of extremely high surface ozone events and their relevance to human health. In this study we aim to, 1) review trend detection methods for addressing different levels of data complexity in different chemical species; 2) demonstrate that the incorporation of scientifically interpretable covariates can outperform pure numerical curve fitting techniques in terms of uncertainty reduction and improved predictability; 3) illustrate the study of trends based on extreme quantiles that can provide insight beyond standard mean or median based trend estimates; and 4) present an advanced method of quantifying regional trends based on the inter-site correlations of multi-site data. All demonstrations are based on time series of observed trace gases relevant to atmospheric chemistry, but the methods can be applied to other environmental data sets.

Trace gas↗
NASA NTRSDate not supplied

Why Developing A Full-Sun UV Spectrograph Sounding Rocket Is Difficult but Necessary

For a conference focused on a 20-year perspective of where we have been and where we are going, this talk will highlight specifically why we need a sounding rocket to lead the way in obtaining high-resolution UV spectroscopy of our sun-as-a-star. The currently available data is either sparse or at a much lower resolution when compared with Hubble (HST) spectra of other stars. Because of this, we cannot say with certainty if our Sun’s variability is typical. This limitation is hindering our quest to place our Sun in it’s rightful place on our star-charts. Ultraviolet light is a key component in determining this. Elements such as Hydrogen and Iron have strong emission lines here, and from them we can determine many things about the star from which they originate. The width of these spectral features can tell us about the relative plasma activity on the surface of the star, the abundance of those elements, and of course the temperatures. This has of course been done with many instruments that have very narrow field of views and/or narrow bandwidths. The only way to directly compare our Sun’s UV ”fingerprint” with other stars is to take an image of it in the same manner by which HST does: as a point source object. Our team’s aim has been to develop a sounding rocket capable of doing just that. Along the way, the many challenges we face are producing many solutions. A unique take on the traditional Rowland circle spectrograph will allow us to cover a large range of UV spectra with minimal moving parts. A novel in-situ gain calibration technique will be used in order to maintain the high level of radiometric accuracy desired. Naturally, complications arise when one takes UV measurements as you are flying out of earth’s atmosphere and back into it. Though it may be minor, the absorbed UV spectra from the atmosphere will have to be accounted for. In preparing for this, we have stumbled across a way in which those ”telluric” absorption lines may prove useful for spectral calibration purposes. In addition, raw data from previous sounding rocket missions may have hidden within them useful information for the atmospheric-physics community. In this talk, we will highlight the unique calibration problems and solutions we have faced, and how those are of greater importance to the greater heliophysics and atmospheric communities. With these amazing developments at hand, the future of heliophysics instrumentation is looking bright. This material is based upon work supported by the NSF EPSCoR RII-Track-1.2a (Non-invasive plasma diagnostics for LTP) Cooperative Agreement OIA-1655280. Any opinions, findings, and conclusions or recommendations expressed in this material are those of the authors and do not necessarily reflect the views of the National Science Foundation.

NASA, UAH, MSU, Sounding Rocket, Aeronomy, Instrum↗
NASA NTRSDate not supplied

Development of the Ames Global Hyperspectral Synthetic Dataset

This study develops the surface BRDF (bidirectional reflectance distribution function) product of the Ames Global Hyperspectral Synthetic Dataset (AGHSD), based on the corresponding MODIS products, to support the NASA Surface Biology and Geology mission development. A main challenge in deriving a hyperspectral dataset from the multi-band satellite products is how to identify a succinct yet robust algorithm that allow us to infer BRDF at unobserved wavelengths based on the few observed bands. Using the theories of radiative transfer in vegetation canopies, we arrive at a simple equation that accurately approximates hyperspectral surface BRDF as the weighted sum of components from the soil and the vegetation. Each of the components is modeled by the product of the spectrally-dependent optical properties of a surface element (the spectra of the soil surface reflectance, the leaf single albedo, or the canopy scattering coefficient) and a spectrally-independent bidirectional scattering function. The optical properties of the soil and the vegetation can be obtained from existing spectral libraries or model simulations. The bidirectional scattering functions are represented by the Ross-Thick-Li-Sparse BRDF model, where the linear coefficients are estimated with regression analysis from the multi-band MODIS data. We validate the algorithm with simulations by Monte Carlo Ray Tracing model experiments, and the results are highly consistent with the theoretic derivation. We apply the algorithm to generate the AGHSD BRDF product at 1km and 8-day resolutions for the year of 2019. The results are biogeochemically and physically coherent and consistent, and thus serve the goal to support the science and application development of the SBG community.

Hyperspectral↗
NASA NTRS2022

The Earth's Exosphere and Its Response to Space Weather

Neutral-Plasma charge exchange is a fundamental physical process that occurs ubiquitously across the universe. In geospace, charge exchange occurs in the Earth’s topside ionosphere, polar wind, plasmasphere, inner magnetosphere, and magnetosheath. Past and current space missions have profiled plasma and electromagnetic characteristics in various parts of the Earth’s magnetospheric system. However, observations of the exosphere, i.e., neutrals above 500 km altitude, are still sparse and, in some regions, non-existent, which limits our understanding of the neutral contribution to the overall dynamics of the geospace environment. Cold exospheric neutrals (< 10 eV) play an important role in the Sun-Earth interaction. Variability of exospheric density provides key information of the Earth’s atmospheric loss under dynamic space environment conditions. Various neutral species and their density variations in the polar wind can alter ion outflow patterns, modifying global magnetospheric dynamics. Exospheric neutrals also provide an energy sink for the inner magnetosphere by creating Energetic Neutral Atoms (ENAs) through charge exchange with high-energy ring current ions, which subsequently leave our geospace system unimpeded by magnetic fields. Exospheric neutrals also provide a means to observe the global interaction of the solar wind – magnetosphere, through global imaging of the system via ENAs (e.g., the TWINS and IMAGE missions) and soft X-rays (e.g., the upcoming LEXI and SMILE missions), the byproducts of neutral-plasma charge exchange. In the coming decade, we advocate that our community needs to increase our exploration of the neutral populations in the outermost reaches of the Earth’s atmosphere. It is imperative that we improve both in-situ and remote-sensing technologies for measuring key neutral species in our exosphere. We also encourage dedicated exosphere missions and to stimulate model developments of our exosphere and its interaction with the co-located magnetospheric system and neighboring Ionosphere - Thermosphere - Mesosphere system.

Hyunju Connor↗
NASA NTRSDate not supplied

Estimating Sonic Boom Metrics Across a Community Using a Kalman Filter

As part of the Quesst mission, NASA will fly the X‑59 aircraft over selected communities to evaluate community responses to low-intensity sonic booms. The purpose of these community tests is to determine the dose-response relationship between the noise exposure metrics and the community response. The independent variables for the dose-response relationship are the noise exposure metrics experienced by survey respondents within the community. Two sources of noise exposure metrics are available in each community: measurements at sparse locations throughout the community, and calculations from propagation models across the community. Both the measurements and calculations are subject to uncertainty. A Kalman filter is proposed to combine the measured and calculated noise exposure metrics to obtain the best estimate of the true noise exposure metrics across the community. The noise exposure metrics estimated by the Kalman filter have lower uncertainty than either the measured or calculated noise exposure metrics alone. Simulations demonstrate that the Kalman filter produces a more accurate estimate of the true noise exposure metrics than other noise estimation methods.

Sonic boom↗
NASA NTRSDate not supplied

Effects of Dose Error and Sample Size on Sonic Boom Dose-response Curves

NASA will soon be collecting noise-annoyance community survey data as the X-59 aircraft flies supersonically over several communities in the USA. Sparse measurements of the X-59 sonic thumps will be used together with physics-based simulations to estimate noise doses at survey participant locations. These dose estimates have associated error that affects the accuracy of modeled dose-response curves, which can result in misestimation of annoyance. The precision in dose-response curves is also a consideration in selecting the number of survey participants. To enable pretest studies of dose error and precision, simulated dose-response data were generated based on NASA’s Quiet Supersonic Flights 2018 test. The data included various degrees of dose error and sample size. Frequentist multilevel logistic regression models were fit to the true and perturbed dose-response data. Simple proportional relationships were identified between the model parameters and the perturbation standard deviation. The summary dose-response curves illustrate the impact on accuracy if dose error is not accounted for in the model. The precision in the dose-response curves is also shown as the number of participants and degree of participation is varied. Finally, sampling variability is illustrated by showing the dose-response curves for several replicates with random draws of participants and errors.

X-59↗
NASA NTRS2022

Herbarium records provide reliable phenology estimates in the understudied tropics

1. Plant phenology has been shifting dramatically in response to climate change, a shift that may have significant and widespread ecological consequences. Of particular concern are tropical biomes, which represent the most biodiverse and imperilled regions of the world. However, compared to temperate floras, we know little about phenological responses of tropical plants because long-term observational datasets from the tropics are sparse. 2. Herbarium specimens have greatly increased our phenological knowledge in temperate regions, but similar data have been underutilized in the tropics and their suitability for this purpose has not been broadly validated. Here, we compare phenological estimates derived from field observational data (i.e. plot surveys) and herbarium specimens at various spatial and taxonomic scales to determine whether specimens can provide accurate estimations of reproductive timing and its spatial variation. 3. Here, we demonstrate that phenological estimates from field observations and herbarium specimens coincide well. Fewer than 5% of the species exhibited significant differences between flowering periods inferred from field observations versus specimens regardless of spatial aggregation. In contrast to studies based on field records, herbarium specimens sampled much larger geographic and climatic ranges, as has been documented previously for temperate plants, and effectively captured phenological responses across varied environments. 4. Synthesis. Herbarium specimens are verified to be a vital resource for closing the gap in our phenological knowledge of tropical systems. Tropical plant reproductive phenology inferred from herbarium records is widely congruent with field observations, suggesting that they can and should be used to investigate phenological variation and their associated environmental cues more broadly across tropical biomes.

Brazil↗
NASA NTRSDate not supplied

Efficient Parametric Uncertainty Analysis of an Earth Entry Vehicle Concept Using Least Angle Regression

The objective of this work was to outline and apply an efficient and accurate parametric un-certainty propagation approach to the analysis of convective heating on an Earth entry vehicle concept. The described approach was based on Least Angle Regression used to solve a sparse and underdetermined linear system in the point-collocation non-intrusive polynomial chaos surrogate method. This approach involved an iterative process to computing the non-zero terms of the underlying polynomial chaos model using only enough samples to converge uncertainty interval predictions and Sobol index values based global nonlinear sensitivity estimates. The Earth entry vehicle was analyzed at three points along a representative trajectory for a Mars return mission. 329 sources of uncertainty were identified in the computational fluid dynamics model used to predict the forebody convective heating. These included uncertainty in flow field chemical rates, collision integrals, heats of formation, surface finite rate char model reaction rates, wall roughness height, and the turbulent Schmidt number. Results from this study showed that convective heating uncertainty as high as 50% of the nominal was predicted with only about 50 evaluations of the computational model. This was far fewer than would be required for a sampling-based approach or a full basis polynomial chaos model, which would have required over 50,000 samples. Additionally, results showed that over 90% of the total convective heating uncertainty was due to uncertainty in the N2catalytic rate on the surface, while the remainder of the uncertainty was attributed to the turbulent Schmidt number and the wall roughness uncertainties.

Thomas K West IV↗
NASA NTRS2019

Industrial-Era Decline in Subarctic Atlantic Productivity

Marine phytoplankton play a critical role in modulating marine-based food webs, fishery yields, and the global drawdown of atmospheric CO2. Due to sparse measurements prior to 21st century satellite monitoring, however, little is known of the long-term response of planktonic stocks to climate forcing. Here we produce the first continuous, multi-century record of subarctic Atlantic marine productivity, showing a marked 10 ± 7% decline has occurred across this highly-productive ocean basin over the last two centuries. We support this conclusion through the application of a novel marine-productivity proxy, established using a unique signal of planktonic-derived aerosol commonly identified across an array of Greenlandic ice cores. Utilizing contemporaneous satellite-era observations, we demonstrate this signal’s use as a robust and high-resolution proxy for spatially-integrated marine productivity variations. We show that the initiation of declining subarctic Atlantic productivity broadly coincides with the onset of Arctic surface warming, and that productivity strongly covaries with regional sea-surface temperatures and basin-wide gyre circulation strength over recent decades. Taken together, our results suggest the industrial era productivity decline may be evidence of the predicted5 collapse of northern Atlantic planktonic stocks in response to a weakened Atlantic Meridional Overturning Circulation (AMOC). Continued AMOC weakening, as projected for the 21st century, may therefore result in further productivity declines across this globally-relevant region.

Climate change↗
NASA NTRS2019

A Large Source of Cloud Condensation Nuclei from New Particle Formation in the Tropics

Cloud condensation nuclei (CCN) can affect cloud properties and therefore the Earth’s radiative balance. New particle formation (NPF) from condensable vapours in the free troposphere has been suggested to contribute to CCN, especially in remote, pristine atmospheric regions, but direct evidence is sparse, and the magnitude of this contribution is uncertain. Here we use in-situ aircraft measurements of vertical profiles of aerosol size distributions to present a global-scale survey of NPF occurrence. We observed intense NPF occurring at high altitude in tropical convective regions over both the Pacific and Atlantic Oceans. Together with the results of chemical-transport models, our findings indicate that NPF persists at all longitudes as a global-scale band in the tropical upper troposphere, covering about 40% of the Earth’s surface. Furthermore, we find that this NPF in the tropical upper troposphere is a globally important source of CCN in the lower troposphere, where they can affect cloud properties. Our findings suggest that the production of CCN, as these new particles descend towards the surface, is currently not adequately captured in global models, because they tend to underestimate both the magnitude of tropical upper tropospheric NPF and the subsequent growth to CCN sizes. This has potential implications for cloud albedo and the global radiative balance.

Atmospheric chemistry↗
NASA NTRSDate not supplied

Navigation Performance of the BioSentinel Deep Space CubeSat Mission

The BioSentinel mission was recently launched aboard the SLS launch vehicle (LV) as part of the Artemis- 1 campaign. The BioSentinel navigation team successfully tracked and guided the spacecraft through a lunar gravity assist to its destination Earth-trailing heliocentric orbit. This 6U CubeSat carries live yeast cells to analyze the effects of radiation at large distances from Earth, becoming the first biological payload in Deep Space. Prelaunch activities included mission design updates, orbit determination rehearsals and the development of a tracking schedule in coordination with the Artemis-1 payload office and the Deep Space Network (DSN). An important influence on the trajectories of Artemis I secondaries was the uncertainty associated with deployment from the Interim Cryogenic Propulsion System (ICPS), the upper stage of the SLS LV. The ICPS was rotating at a rate of 1 rpm; there was also an uncertainty in the spin axis attitude, which translated into an unknown clock angle of deployment. The variability in this angle and magnitude of deployment implied the existence of a non-negligible risk of a lunar impact, which was evaluated for various potential launch dates. We present the results of Monte Carlo analyses and compute the pertinent maneuvers to avoid it. In addition, we present a comparison with the actual deployment once the mission launched by reconstructing our trajectory with tracking data. On November 16th 2022 BioSentinel successfully deployed from ICPS and the navigation team started to receive 2-way Doppler and Sequential Ranging data from the DSN. We processed early data to try to obtain a first ephemeris using Initial Orbit Determination (IOD) methods such as the least squares. Soon after deployment, the spacecraft was tumbling and entered safe mode, creating a period where the tracking data were sparse. The mission team recovered the spacecraft and after four tracking passes, we solved for a first ephemeris that was sent to the DSN for better tracking of the spacecraft. After propagating this first ephemeris solution, we determined that we avoided impact with a margin of a few hundred km from the lunar surface. More tracking data over the next few days (from DSN as well as ESA antennas) allowed for a more refined orbit solution predicting a periselene altitude of 406 km and a lunar eclipse lasting 36.5 minutes. Therefore, BioSentinel operators aborted any correction maneuvers. This periselene altitude also gave us the necessary energy to achieve a heliocentric orbit. The next challenge was due to the necessary adjustments in our orbit determination method due to the large energy boost resulting from the lunar flyby. After a series of tracking passes we were able to get a nominal solution that resulted into a stable trajectory. This paper discusses in detail the navigation performance using the X-band IRIS transponder, as well as the challenges and lessons learned prior to and during this deep space, CubeSat mission.

Andres Dono Perez↗
NASA NTRS2022

Clumped-Isotope Constraint on Upper-Tropospheric Cooling During the Last Glacial Maximum

Ice cores and other paleotemperature proxies, together with general circulation models, have provided information on past surface temperatures and the atmosphere's composition in different climates. Little is known, however, about past temperatures at high altitudes, which play a crucial role in Earth's radiative energy budget. Paleoclimate records at high-altitude sites are sparse, and the few that are available show poor agreement with climate model predictions. These disagreements could be due to insufficient spatial coverage, spatiotemporal biases, or model physics; new records that can mitigate or avoid these uncertainties are needed. Here, we constrain the change in upper-tropospheric temperature at the global scale during the Last Glacial Maximum (LGM) using the clumped-isotope composition of molecular oxygen trapped in polar ice cores. Aided by global three-dimensional chemical transport modeling, we exploit the intrinsic temperature sensitivity of the clumped-isotope composition of atmospheric oxygen to infer that the upper troposphere (effective mean altitude 10–11 km) was 6–9°C cooler during the LGM than during the late preindustrial Holocene. A complementary energy balance approach supports a minor or negligible steepening of atmospheric lapse rates during the LGM, which is consistent with a range of climate model simulations. Proxy-model disagreements with other high-altitude records may stem from inaccuracies in regional hydroclimate simulation, possibly related to land-atmosphere feedbacks.

clumped isotope↗