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At least 91 records · Page 5

Updating and Evaluating Anthropogenic Emissions for NOAA’s Global Ensemble Forecast Systems for Aerosols (GEFS-Aerosols): Application of an SO 2 Bias-Scaling Method

We updated the anthropogenic emissions inventory in NOAA’s operational Global Ensemble Forecast for Aerosols (GEFS-Aerosols) to improve the model’s prediction of aerosol optical depth (AOD). We used a methodology to quickly update the pivotal global anthropogenic sulfur dioxide (SO 2 ) emissions using a speciated AOD bias-scaling method. The AOD bias-scaling method is based on the latest model predictions compared to NASA’s Modern-Era Retrospective analysis for Research and Applications, version 2 (MERRA2). The model bias was subsequently applied to the CEDS 2019 SO 2 emissions for adjustment. The monthly mean GEFS-Aerosols AOD predictions were evaluated against a suite of satellite observations (e.g., MISR, VIIRS, and MODIS), ground-based AERONET observations, and the International Cooperative for Aerosol Prediction (ICAP) ensemble results. The results show that transitioning from CEDS 2014 to CEDS 2019 emissions data led to a significant improvement in the operational GEFS-Aerosols model performance, and applying the bias-scaled SO 2 emissions could further improve global AOD distributions. The biases of the simulated AODs against the observed AODs varied with observation type and seasons by a factor of 3~13 and 2~10, respectively. The global AOD distributions showed that the differences in the simulations against ICAP, MISR, VIIRS, and MODIS were the largest in March–May (MAM) and the smallest in December–February (DJF). When evaluating against the ground-truth AERONET data, the bias-scaling methods improved the global seasonal correlation (r), Index of Agreement (IOA), and mean biases, except for the MAM season, when the negative regional biases were exacerbated compared to the positive regional biases. The effect of bias-scaling had the most beneficial impact on model performance in the regions dominated by anthropogenic emissions, such as East Asia. However, it showed less improvement in other areas impacted by the greater relative transport of natural emissions sources, such as India. The accuracies of the reference observation or assimilation data for the adjusted inputs and the model physics for outputs, and the selection of regions with less seasonal emissions of natural aerosols determine the success of the bias-scaling methods. A companion study on emission scaling of anthropogenic absorbing aerosols needs further improved aerosol prediction.

54 ENVIRONMENTAL SCIENCES↗

MiniCarb: a passive, occultation-viewing, 6U CubeSat for observations of CO 2 , CH 4 , and H 2 O

In this report we present the final design, environmental testing, and launch history of MiniCarb, a 6U CubeSat developed through a partnership between NASA Goddard Space Flight Center and Lawrence Livermore National Laboratory. MiniCarb’s science payload, developed at Goddard, was an occultation-viewing, passive laser heterodyne radiometer for observing methane, carbon dioxide, and water vapor in Earth’s atmosphere at ~1.6 µm s -1 . MiniCarb’s satellite, developed at Livermore, implemented their CubeSat Next Generation Bus plug-and-play architecture to produce a modular platform that could be tailored to a range of science payloads. Following the launch on 5 December 2019, MiniCarb traveled to the International Space Station and was set into orbit on 1 February 2020 via Northrop Grumman’s Cygnus capsule which deployed MiniCarb with tipoff rotation of about 20° s (significantly higher than the typical rate of 3° s -1 from prior CubeSats), from which the attitude control system was unable to recover resulting in a loss of power. In spite of this early failure, MiniCarb had many successes including rigorous environmental testing, successful deployment of its solar panels, and a successful test of the radio and communication through the Iridium network. This prior work and enticing cost (approximately $\$2$ M for the satellite and $\$$250 K for the payload) makes MiniCarb an ideal candidate for a low-cost and rapid rebuild as a single orbiter or constellation to globally observe key greenhouse gases.

47 OTHER INSTRUMENTATION↗

Monthly Quality-filtered Aggregation of NOAA Climate Data Record (CDR) of AVHRR Leaf Area Index (LAI) and Fraction of Absorbed Photosynthetically Active Radiation (FAPAR), Version 5

This dataset contains gridded monthly Leaf Area Index (LAI) derived from the daily NOAA Climate Data Record (CDR) of AVHRR Leaf Area Index (LAI) and Fraction of Absorbed Photosynthetically Active Radiation (FAPAR), Version 5. This data record spans from 1981 to 2018 using data from eight NOAA polar orbiting satellites: NOAA-7, -9, -11, -14, -16, -17, -18 and -19. The data are projected on a 0.05 degree x 0.05 degree global grid, as in the original CDR. The original CDR is one of the Land Surface CDR Version 5 products produced by the NASA Goddard Space Flight Center (GSFC) and the University of Maryland (UMD), which is accompanied by algorithm documentation, data flow diagram and source code for the NOAA CDR Program. This dataset is in the netCDF-4 file format following ACDD and CF Conventions. This dataset has applied quality assurance information to only include "OK" data from the original CDR in the monthly aggregation.

Vermote, Eric [NASA Goddard Space Flight Center (G↗

Extensive Secondary Cratering From the InSight Sol 1034a Impact Event

Abstract Impact cratering is one of the fundamental processes throughout the history of the Solar System. The formation of new impact craters on planetary bodies has been observed with repeat images from orbiting satellites. However, the time gap between images is often large enough to preclude detailed analysis of smaller‐scale features such as secondary impact craters, which are often removed or buried over a short time period. Here we use a seismic event detected on Mars by the NASA InSight mission to investigate secondary cratering at a new impact crater. We strengthen the case that the seismic event that occurred on Sol 1034 (S1034a) is the result of a new impact cratering event. Using the exact timing of this event from InSight, we investigated the resulting new impact crater in orbital image data. The S1034a impact crater is approximately 9 m in diameter but is responsible for over 900 secondary impact events in the form of low albedo spots that are located at distances of up to almost 7 km from the primary crater. We suggest that the low albedo spots formed from relatively low energy ejecta, with individual ejecta block velocities less than 200 m s −1 . We estimate that the low albedo spots, the main evidence of secondary impact processes at this new impact event, fade within 200–300 days after formation.

Grindrod, P. M. [Natural History Museum London UK]↗

Monthly Quality-filtered Aggregation of NOAA Climate Data Record (CDR) of AVHRR (Version 5) and VIIRS (Version 1) Leaf Area Index (LAI) and Fraction of Absorbed Photosynthetically Active Radiation (FAPAR)

This dataset contains gridded monthly Leaf Area Index (LAI) derived from the daily NOAA Climate Data Record (CDR) of AVHRR (Version 5) and VIIRS (Version 1) Leaf Area Index (LAI) and Fraction of Absorbed Photosynthetically Active Radiation (FAPAR). This data record spans from 1981 to 2024 using data from NOAA polar orbiting satellites: NOAA-7, -9, -11, -14, -16, -17, -18, -19 and S-NPP. The data are projected on a 0.05 degree x 0.05 degree global grid, as in the original CDR. The original CDR is one of the Land Surface CDR products produced by the NASA Goddard Space Flight Center (GSFC) and the University of Maryland (UMD), which is accompanied by algorithm documentation, data flow diagram and source code for the NOAA CDR Program. This dataset is in the netCDF-4 file format following ACDD and CF Conventions. This dataset has applied quality assurance information to only include "OK" data from the original CDR in the monthly aggregation.

Vermote, Eric [NASA Goddard Space Flight Center (G↗

Tropospheric aerosols over the western North Atlantic Ocean during the winter and summer deployments of ACTIVATE 2020: life cycle, transport, and distribution

The Aerosol Cloud meTeorology Interactions oVer the western ATlantic Experiment (ACTIVATE) is a NASA mission to characterize aerosol–cloud interactions over the western North Atlantic Ocean (WNAO). Such characterization requires understanding of life cycle, composition, transport pathways, and distribution of aerosols over the WNAO. This study uses the GEOS-Chem model to simulate aerosol distributions and properties that are evaluated against aircraft, ground-based, and satellite observations during the winter and summer field deployments in 2020 of ACTIVATE. Transport in the boundary layer (BL) behind cold fronts was a major mechanism for the North American continental outflow of pollution to the WNAO in winter. Turbulent mixing was the main driver for the upward transport of sea salt within and ventilation out of BL in winter. The BL aerosol composition was dominated by sea salt, which increased in the summer, followed by organics and sulfate. Aircraft in situ aerosol measurements provided useful constraints on wet scavenging in GEOS-Chem. The model generally captured observed features such as continental outflow, land–ocean gradient, and mixing of anthropogenic aerosols with sea salt. Model sensitivity experiments with elevated smoke injection heights to the mid-troposphere (versus within BL) better reproduced observations of smoke aerosols from the western US wildfires over the WNAO in the summer. Model analysis suggests strong hygroscopic growth of sea salt particles and their seeding of marine BL clouds over the WNAO (< 35° N). Future modeling efforts should focus on improving parameterizations for aerosol wet scavenging, implementing realistic smoke injection heights, and applying high-resolution models that better resolve vertical transport.

54 ENVIRONMENTAL SCIENCES↗

PreMevE Update: Forecasting Ultra-Relativistic Electrons Inside Earth's Outer Radiation Belt

Energetic electrons inside Earth's Van Allen belts pose a major radiation threat to spaceborne electronics that often play vital roles in modern society. Ultra-relativistic electrons with energies greater than or equal to two megaelectron-volt (MeV) are of particular interest, and thus forecasting these ≥2 MeV electrons has a significant meaning to all space sectors. Here, we update the latest development of the predictive model for MeV electrons in the outer radiation belt. The new version, called PREdictive MEV Electron (PreMevE)-2E, forecasts ultra-relativistic electron flux distributions across the outer belt, with no need for in situ measurements of the trapped MeV electron population except at the geosynchronous orbit (GEO). Model inputs include precipitating electrons observed in low-Earthorbits by NOAA satellites, upstream solar wind speeds and densities from solar wind monitors, as well as ultra-relativistic electrons measured by one Los Alamos GEO satellite. We evaluated 32 supervised machine learning models that fall into four different classes of linear and neural network architectures, and successfully tested ensemble forecasting by using groups of top-performing models. All models are individually trained, validated, and tested by in situ electron data from NASA's Van Allen Probes mission. It is shown that the final ensemble model outperforms individual models at most L-shells, and this PreMevE-2E model can provide 25-h (~1-day) and 50-h (~2-day) forecasts with high mean performance efficiency and correlation values. Our results also suggest that this new model is dominated by nonlinear components at L-shells <~4 for ultra-relativistic electrons, different from the dominance of linear components for 1 MeV electrons as previously discovered.

79 ASTRONOMY AND ASTROPHYSICS↗

Correction and calibration of atmospheric impact observations in GOES GLM data

The Earth's atmosphere is impacted daily by both meteoroids and artificial objects. Calibrated observations of the emitted light at sufficiently high sampling rates can enable or improve the estimation of impactor attributes such as size, cohesion, trajectory, and composition, but are difficult to obtain owing to the unpredictability, brevity, and high dynamic (brightness) range of impacts. Ground-based camera systems have successfully monitored small regions of the atmosphere at video frame rates and with limited radiometric capabilities, but most impacts occur over the 70% of the Earth's surface covered by water and are therefore missed by these networks. The Geostationary Lightning Mapper (GLM) instruments aboard Geostationary Operational Environmental Satellites 16 and 17 provide near-hemispherical coverage at 500 frames per second. These data have been shown to contain the signatures of many independently confirmed impacts, often from both viewing angles simultaneously, and constitute an observational resource that is currently unparalleled in the public domain. NASA's Asteroid Threat Assessment Project has implemented an automated impact detection pipeline that processes data from GLM daily. Given a detected impact, the GLM data contain a wealth of information for use in quantitative follow-up analyses. However, impact events differ from lightning in ways that violate key assumptions built into GLM's design. The result is that GLM's onboard processing introduces errors into pixel observations of impact events and the calibrated energies near the periphery of the detector may be substantially overestimated. We present methods for mitigating these and other issues to produce a data product more suitable for impact analyses than the existing GLM lightning product.

58 GEOSCIENCES↗

MODIS Aerosol and Low‐Cloud Retrievals: Orographic Effects in the Wake of Macquarie Island

Abstract Visible/infrared imagery from passive satellites is commonly relied upon to study low cloud microphysics over oceanic regions, including for the Southern Ocean (SO), but relatively little validation has been undertaken for the SO. In this article, we compare low‐cloud effective radius ( r e ), cloud droplet number concentration ( N d ) and cloud liquid water path (LWP) retrievals from the NASA Moderate Imaging Spectroradiometer (MODIS) with surface measurements collected during the Macquarie Island Cloud and Radiation Experiment (MICRE). MODIS 3.7‐μm band retrievals show little bias and moderately good correlation relative to MICRE retrievals for liquid‐phase low clouds when restricted to Solar Zenith Angles <65° on spatial scales of 50–100 km. However, the low overall bias in 3.7‐μm band effective radius ( r e 3.7 ) retrievals partly results from cancellation of errors: r e 3.7 is overestimated for non‐to‐lightly precipitating clouds, and underestimated for heavier drizzling clouds by ∼1–1.5 μm. 1.6‐μm and 2.1‐μm band r e retrievals are biased high. N d may likewise be slightly under‐ or overestimated depending on the concentration, but there is insufficient data to provide confidence in this result. Interestingly, a composite of MODIS retrievals from 2002 to 2020 show a distinct region of enhanced cloud cover and N d (and lower r e ) in the wake of Macquarie Island associated with orographic cloud formation. MODIS retrievals of aerosol optical depth (AOD) and Angstrom Exponent (AE) upwind and downwind of the island do not differ significantly. Comparison with MICRE measurements suggests that MODIS Collection 6 AOD retrievals are reasonable, while AE is problematically large.

54 ENVIRONMENTAL SCIENCES↗

A Lunar Farside Low Radio Frequency Array for Dark Ages 21-cm Cosmology

An array of low-frequency dipole antennas on the lunar farside surface will probe a unique, unexplored epoch in the early Universe called the Dark Ages. It begins at Recombination when neutral hydrogen atoms formed, first revealed by the cosmic microwave background. This epoch is free of stars and astrophysics, so it is ideal to investigate high energy particle processes including dark matter, early Dark Energy, neutrinos, and cosmic strings. A NASA-funded study investigated the design of the instrument and the deployment strategy from a lander of 128 pairs of antenna dipoles across a 10 kmx10 km area on the lunar surface. The antenna nodes are tethered to the lander for central data processing, power, and data transmission to a relay satellite. The array, named FARSIDE, would provide the capability to image the entire sky in 1400 channels spanning frequencies from 100 kHz to 40 MHz, extending down two orders of magnitude below bands accessible to ground-based radio astronomy. The lunar farside can simultaneously provide isolation from terrestrial radio frequency interference, the Earth's auroral kilometric radiation, and plasma noise from the solar wind. It is thus the only location within the inner solar system from which sky noise limited observations can be carried out at sub-MHz frequencies. Through precision calibration via an orbiting beacon and exquisite foreground characterization, the farside array would measure the Dark Ages global 21-cm signal at redshifts z~35-200. It will also be a pathfinder for a larger 21-cm power spectrum instrument by carefully measuring the foreground with high dynamic range.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

“Godzilla,” the Extreme African Dust Event of June 2020: Origins, Transport, and Impact on Air Quality in the Greater Caribbean Basin

In June 2020, the tropical Atlantic and the Caribbean Basin were affected by a series of African dust outbreaks unprecedented in size and intensity. These events, informally named “Godzilla,” coincided with CALIMA, a large field campaign, offering a rare opportunity to assess the impact of African dust on air quality in the Greater Caribbean Basin. Network measurements of respirable particles (i.e., PM 10 and PM 2.5 ) showed that dust significantly degraded regional air quality and increased the risk to public health in the Caribbean, the southern United States, northern South America, and Central America. CALIMA examined the meteorological context of Godzilla dust events over North Africa and how these conditions might relate to the greatly increased dust emissions and enhanced transport to the Americas. Godzilla was linked to strong pressure anomalies over West Africa, resulting in a large-scale geostrophic wind anomaly at 700 hPa over North Africa. We used surface-based and columnar measurements to test the performance of two frequently used aerosol forecast models: the NASA Goddard Earth Observing System (GEOS) and Weather Research and Forecasting Model coupled with Chemistry (WRF-Chem) models. The models showed some skills but differed substantially between their forecasts, suggesting large uncertainties in these forecasts that are critical for issuing early warnings of health-threatening dust events. Our results demonstrate the value of an integrated approach in characterizing the spatial and temporal variability of African dust transport and assessing its impact on regional air quality. Future studies are needed to improve models and to track the long-term changes in dust transport from Africa under a changing climate.

Aerosols/particulates↗

The Amazon River‐Breeze Circulation Limits Detection of Aerosol‐Cloud Interactions in Warm Clouds

Increased aerosol concentrations can brighten low-level clouds and extend their lifetimes, but aerosol–cloud interactions (ACI) remain highly uncertain and difficult to quantify. We show that part of this uncertainty is caused by topographical influences on clouds, that is, those arising from land–water contrasts. This is demonstrated using satellite retrievals in regions with extensive river networks, such as the Amazon Basin. 15 years of MODerate resolution Imaging Spectroradiometer (MODIS) satellite data show cloud formation over the Amazon River basin is suppressed by 26% with warm low clouds above the river exhibiting a 22% smaller droplet effective radius and 18% higher droplet concentration ($N_d$) compared to adjacent land clouds. Thus, clouds above the river may appear polluted but are actually influenced by river-breeze circulations driven by the thermal contrast between the river and the surrounding land. These responses are robust in both wet and dry seasons, and tests using an improved MODIS retrieval product show cloud differences are unlikely due to retrieval artifacts. In situ measurements from the Green Ocean Amazon Experiment (GoAmazon) confirm that $N_d$ is elevated above rivers and are also higher when carbon monoxide concentrations are elevated near the large city of Manaus. Lagrangian airmass tracking over Manaus shows that regional-scale river-breeze circulations impact $N_d$ as much as the urban aerosol plume, complicating ACI attribution and highlighting the need to isolate land-surface effects to assess ACI in continental regions.

Aerosol-Cloud Interactions↗

High-resolution mapping of nitrogen oxide emissions in large US cities from TROPOMI retrievals of tropospheric nitrogen dioxide columns

Satellite-derived spatiotemporal patterns of nitrogen oxide (NOx) emissions can improve accuracy of emission inventories to better support air quality and climate research and policy studies. In this study, we develop a new method by coupling the chemical transport Model-Independent SATellite-derived Emission estimation Algorithm for Mixed-sources (MISATEAM) with a divergence method to map high-resolution NO x emissions across US cities using TROPOspheric Monitoring Instrument (TROPOMI) tropospheric nitrogen dioxide (NO 2 ) retrievals. The accuracy of the coupled method is validated through application to synthetic NO 2 observations from the NASA-Unified Weather Research and Forecasting (NU-WRF) model, with a horizontal spatial resolution of 4 km × 4 km for 33 large and mid-size US cities. Validation reveals excellent agreement between inferred and NU-WRF-provided emission magnitudes (R= 0.99, normalized mean bias, NMB = —0.01) and a consistent spatial pattern when comparing emissions for individual grid cells (R = 0.88 ± 0.06). We then develop a TROPOMI-based database reporting annual emissions for 39 US cities at a horizontal spatial resolution of 0.05° × 0.05° from 2018 to 2021. This database demonstrates a strong correlation (R= 0.90) with the National Emission Inventory (NEI) but reveals some bias (NMB = —0.24). There are noticeable differences in the spatial patterns of emissions in some cities. Our analysis suggests that uncertainties in TROPOMI-based emissions and potential misallocation of emissions and/or missing sources in bottom-up emission inventories both contribute to these differences.

54 ENVIRONMENTAL SCIENCES↗

Biomass burning emission analysis based on MODIS aerosol optical depth and AeroCom multi-model simulations: implications for model constraints and emission inventories

We assessed the biomass burning (BB) smoke aerosol optical depth (AOD) simulations of 11 global models that participated in the AeroCom phase III BB emission experiment. By comparing multi-model simulations and satellite observations in the vicinity of fires over 13 regions globally, we (1) assess model-simulated BB AOD performance as an indication of smoke source–strength, (2) identify regions where the common emission dataset used by the models might underestimate or overestimate smoke sources, and (3) assess model diversity and identify underlying causes as much as possible. Using satellite-derived AOD snapshots to constrain source strength works best where BB smoke from active sources dominates background non-BB aerosol, such as in boreal forest regions and over South America and southern hemispheric Africa. The comparison is inconclusive where the total AOD is low, as in many agricultural burning areas, and where the background is high, such as parts of India and China. Many inter-model BB AOD differences can be traced to differences in values for the mass ratio of organic aerosol to organic carbon, the BB aerosol mass extinction efficiency, and the aerosol loss rate from each model. The results point to a need for increased numbers of available BB cases for study in some regions and especially to a need for more extensive regional-to-global-scale measurements of aerosol loss rates and of detailed particle microphysical and optical properties; this would both better constrain models and help distinguish BB from other aerosol types in satellite retrievals. More generally, there is the need for additional efforts at constraining aerosol source strength and other model attributes with multi-platform observations.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Combined Optical and Radio–Frequency Perspectives on the Time Evolution of Lightning Measured by the FORTE Satellite

We use a cluster feature data set for the Fast On-orbit Recording of Transient Events (FORTE) satellite that combines detections from its pixelated Lightning Locating System (LLS), photodiode detector (PDD) and Radio-Frequency (RF) instrumentation to generate statistics describing the frequency and timing of lightning events detected by each instrument during lightning flashes. Coincident observations from the same vantage point allow us to directly compare flash details that can be resolved by the wide Field of View (FOV) instruments relative to the pixelated LLS—whose design is based on NASA's Lightning Imaging Sensor. We find that both the PDD and RF system typically generate more detections than the lightning imager (mean: 1.5 PDD events per LLS group, 2 RF events per LLS group) from pulses that are either not sufficiently bright in the optical band (in the case of RF) or that lack the optical energy density (in the case of the PDD) required to trigger one of the pixels on the LLS imaging array. This includes additional activity before the first LLS group or after the final LLS group. These FORTE results demonstrate that certain lightning processes would be better resolved by wide-FOV optical and RF instruments than lightning imagers. Current/future space-based missions that use/plan to use similar instruments will improve our understanding of flash evolution by resolving details missed by lightning imagers.

47 OTHER INSTRUMENTATION↗

Evaluating spectral cloud effective radius retrievals from the Enhanced MODIS Airborne Simulator (eMAS) during ORACLES

Satellite remote sensing retrievals of cloud effective radius (CER) are widely used for studies of aerosol–cloud interactions. Such retrievals, however, rely on forward radiative transfer (RT) calculations using simplified assumptions that can lead to retrieval errors when the real atmosphere deviates from the forward model. Here, coincident airborne remote sensing and in situ observations obtained during NASA's ObseRvations of Aerosols above CLouds and their intEractionS (ORACLES) field campaign are used to evaluate retrievals of CER for marine boundary layer stratocumulus clouds and to explore impacts of forward RT model assumptions and other confounding factors. Specifically, spectral CER retrievals from the Enhanced MODIS Airborne Simulator (eMAS) and the Research Scanning Polarimeter (RSP) are compared with polarimetric retrievals from RSP and with CER derived from droplet size distributions (DSDs) observed by the Phase Doppler Interferometer (PDI) and a combination of the Cloud and Aerosol Spectrometer (CAS) and the Two-Dimensional Stereo Probe (2D-S). The sensitivities of the eMAS and RSP spectral retrievals to assumptions about the DSD effective variance (CEV) and liquid water complex index of refraction are explored. CER and CEV inferred from eMAS spectral reflectance observations of the backscatter glory provide additional context for the spectral CER retrievals. The spectral and polarimetric CER retrieval agreement is case dependent, and updating the retrieval RT assumptions, including using RSP polarimetric CEV retrievals as a constraint, yields mixed results that are tied to differing sensitivities to vertical heterogeneity. Moreover, the in situ cloud probes, often used as the benchmark for remote sensing CER retrieval assessments, themselves do not agree, with PDI DSDs yielding CER values 1.3–1.6 µm larger than CAS and with CEV roughly 50 %–60 % smaller than CAS. Implications for the interpretation of spectral and polarimetric CER retrievals and their agreement are discussed.

Meyer, Kerry [NASA Goddard Space Flight Center (GS↗

Assimilation of Satellite-Derived Soil Moisture for Improved Forecasts of the Great Plains Low-Level Jet

In the context of forecasting societally impactful Great Plains low-level jets (GPLLJs), the potential added value of satellite soil moisture (SM) data assimilation (DA) is high. GPLLJs are both sensitive to regional soil moisture gradients and frequent drivers of severe weather, including mesoscale convective systems. An untested hypothesis is that SM DA is more effective in forecasts of weakly synoptically forced, or uncoupled GPLLJs, than in forecasts of cyclone-induced coupled GPLLJs. Using the NASA Unified Weather Research and Forecasting (NU-WRF) Model, 75 GPLLJs are simulated at 9-km resolution both with and without NASA Soil Moisture Active Passive SM DA. Differences in modeled SM, surface sensible (SH) and latent heat (LH) fluxes, 2-m temperature (T2), 2-m humidity (Q2), PBL height (PBLH), and 850-hPa wind speed (W850) are quantified for individual jets and jet-type event subsets over the south-central Great Plains, as well as separately for each GPLLJ sector (entrance, core, and exit). At the GPLLJ core, DA-related changes of up to 5.4 kg m–2 in SM can result in T2, Q2, LH, SH, PBLH, and W850 differences of 0.68°C, 0.71 g kg –2 , 59.9 W m –2 , 52.4 W m –2 , 240 m, and 4 m s –1 , respectively. W850 differences focus along the jet axis and tend to increase from south to north. Further, jet-type differences are most evident at the GPLLJ exit where DA increases and decreases W850 in uncoupled and coupled GPLLJs, respectively. Data assimilation marginally reduces negative wind speed bias for all jets, but the correction is greater for uncoupled GPLLJs, as hypothesized.

54 ENVIRONMENTAL SCIENCES↗

Spurious solar-wind effects on acceleration noise in LISA Pathfinder

Spurious solar-wind effects are a potential noise source in future Laser Interferometer Space Antenna (LISA) measurements. One noise coupling mechanism is constrained by estimating solar-wind effects on acceleration noise in LISA Pathfinder (LPF). While LISA is designed for drag-free differential measurement, predicting the realistic impact both bounds the operational environment and assesses whether LISA could provide serendipitous space-weather observations. Data from NASA's Advanced Composition Explorer (ACE), situated at the L1 Lagrange point, serves as a reliable source of solar-wind data. The data sets are compared over the 114 d time period from 1 March 2016 to 23 June 2016. This period gives the longest readily-available open data set, without interference from other commissioning activities. To evaluate space weather effects, the data from both satellites are formatted, gap-filled/interpolated, and fast-Fourier transformed for amplitude spectral density and coherence comparisons. Solar wind effects are not seen in a coherence plot between LPF and ACE; modest coherence in the planned LISA observational frequency band can be attributed to chance. This result indicates that measurable correlation due to solar-wind acceleration noise over 3 month timescales will be a negligible noise source. LISA is unlikely to inform solar wind measurements routinely. Another source of noise from the Sun, solar radiation pressure, is estimated to impart greater acceleration noise, but has yet to be analyzed.

79 ASTRONOMY AND ASTROPHYSICS↗