cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.48577/jpl.lsecrl
title: Which combinations of environmental conditions and microphysical parameter values produce a given orographic precipitation distribution?

description: This study applies an idealized modeling framework, alongside a Bayesian Markov chain Monte Carlo (MCMC) algorithm, to explore which combinations of upstream environmental conditions and cloud microphysical parameter values can produce a particular precipitation distribution over an idealized two-dimensional, bell-shaped mountain. Simulations focus on orographic precipitation produced when an atmospheric river interacts with topography. MCMC-based analysis reveals that different combinations of parameter values produce a similar precipitation distribution, with the most influential parameters being relative humidity (RH), horizontal wind speed (U), surface potential temperature (θsfc), and the snow fallspeed coefficient (As). RH, U, and As exhibit inter-dependence: changes in one or more of these factors can be mitigated by compensating changes in the other(s) to produce similar orographic precipitation rates. The results also indicate that the parameter sensitivities and relationships can vary for spatial sub-regions and given different environmental conditions. In particular, high θsfc values are more likely to produce the target precipitation rate and spatial distribution, and thus the ensemble of simulations shows a preference for liquid precipitation at the surface. The results presented here highlight the complexity of orographic precipitation controls, and have implications for flood and water management, observational efforts, and climate change.
DOI: 10.48577/jpl.ni4zbd
title: Regional Tropical Aboveground Biomass Mapping with L-Band Repeat-Pass Interferometric Radar, Sparse Lidar, and Multiscale Superpixels

description: To extend the NISAR mission’s applicable range of aboveground biomass (AGB) in tropical forests, we introduce a multi-scale superpixel approach that leverages repeat-pass interferometric coherence and sparse AGB estimates from spaceborne lidar. Airborne and spaceborne L-band radar and full-waveform airborne Lidar data are used to simulate the NISAR and GEDI mission, respectively. In addition to UAVSAR data, we use spaceborne ALOS-2/PALSAR-2 imagery with 14-day temporal baseline, which is comparable to NISAR’s 12-day baseline. Our reference AGB maps are derived from the airborne LVIS data during the AfriSAR campaign for three sites (Mondah, Ogooue, and Lope). Each tropical site has mean AGB of at least 125 Mg/ha in addition to areas with AGB exceeding 700 Mg/ha. Spatially sampling from these LVIS-derived AGB reference maps, we approximate GEDI AGB estimates. To evaluate our methodology, we perform several different analyses. First, we partition each study site into low (≤ 100 Mg/ha) and high (&gt; 100 Mg/ha) AGB areas, in conformity with the NISAR mission requirement to provide AGB estimates for forests between 0 and 100Mg/ha with a RMSE below 20 Mg/ha. In the low AGB areas, this RMSE requirement is satisfied in Lope and Mondah and exceeded in Ogooue by less 3 Mg/ha with UAVSAR and 6 Mg/ha with PALSAR-2. We note that our maps have higher resolution (50 meters) than NISAR requires (1 hectare). In the high AGB areas, the normalized RMSE increases to 51% (i.e. &lt; 90 Mg/ha), but with negligible bias for all three sites. Second, using a single model to estimate AGB across both high and low AGB regimes simultaneously, the normalized RMSE is &lt; 60% (or &lt; 100 Mg/ha). Lastly, we show the use of both (a) multiscale superpixels and (b) interferometric coherence significantly improves accuracy of the AGB estimates. Using interferometric coherence, in particular, reduces the normalized RMSE over Mondah by approximately 8% (12 Mg/ha) and 9% (9 Mg/ha) with UAVSAR and PALSAR-2 data respectively. This work illustrates one of the numerous synergistic relationship between the spaceborne lidars such as GEDI with L-band SAR such as PALSAR-2 and NISAR to produce robust regional AGB in high biomass tropical regions.
DOI: 10.48577/jpl.qkycxu
title: Decay of the snow cover over Arctic sea ice from ICESat-2 acquisitions during summer melt in 2019

description: From the onset of melt in early June, corresponding declines in ICESat-2 freeboard and surface albedo can be seen over the entire Arctic sea ice cover. In the 2019 summer, area-averaged freeboard decreased from 34cm prior to melt to a minimum of 12cm in August while the area-averaged albedo decreased from ~0.7 to 0.38 for the same period. Calculations using ICESat-2 freeboards and modeled ice-thickness from PIOMAS give area-averaged snow depths ranging from 17cm prior to melt to 3cm in August over seasonal ice, and from 34cm to 4cm over multiyear ice. Mean rates of snow ablation (including evaporation) in mid-June were as high as 2 cm/day, comparable to field records from other years. Increases in freeboard after mid-August in the high latitude (&gt;80oN) multiyear ice cover, north of the Greenland coast, is likely due to earlier freeze-up and snow accumulation in these regions with shorter melt seasons.
DOI: 10.48577/jpl.tx6wb5
title: H¬2-pressure broadening and frequency shifts of methane in the v2+v3 band measured in the temperature range between 80 and 370 K

description: We have made the first measurements of H2-broadened line shape parameters of CH4 transitions in the v2+v3 band located at 2.2 μm to support accurate atmospheric opacity calculations of cold giant planets, hot Jupiters, and low mass brown dwarfs, for which H2 is the dominant atmospheric constituent. For this reason, a series of spectra of pure CH4 and CH4-H2 mixtures were obtained in the Octad (4100-4600 cm-1) region for a wide temperature range between 80 and 370 K using a Bruker 125HR high-resolution Fourier transform spectrometer (FTS) at JPL. Three custom-designed gas absorption cells vacuum coupled to the FTS were used to obtain the spectra. All spectra were fit simultaneously using a multispectrum non-linear least-squares fitting software (Labfit), which adopts a speed-dependent Voigt line shape using full line mixing taken into account through a relaxation matrix operation. H2 pressure broadened half-width, and H2 pressure-induced shift coefficients were determined in 12 J-manifolds covering P(4) – R(6), including the Q-branch. The temperature dependences of the width and shift coefficients were determined based upon the power law and the linear models. Collisional line mixing coefficients for CH4- H2 were retrieved for ten transition pairs across the v2+v3 band along with their temperature dependence on the power-law model analogous to that of pressure broadening. The measured H2-widths at 296 K vary from 0.05 – 0.08 cm-1/atm, which are slightly greater than the Air-widths by ~8%. They also exhibited the well-known A/E/F rotational symmetry species dependence, as discussed in earlier literature. The H2 pressure-induced frequency shifts at 295 K were all measured negative and ranged between -0.005 and -0.015 cm-1/atm. Temperature dependences were observed to be 0.58 (i.e., very close to the theoretical value, 0.5) for the H2-broadening, which is substantially lower than that for Air-broadening, i.e., 0.82. We also measured the temperature dependence for the H2-shifts slightly smaller than that of Air-shifts for the corresponding transitions of CH4 in the same band, v2+v3. For the same transitions, speed dependence parameters for the CH4-H2 transitions were found to be smaller than for CH4-Air-broadening. For the collisional line mixing parameters, we present the off-diagonal relaxation matrix elements (ORMEs) for the line coupling pairs as well as Rosenkranz line mixing coefficients calculated from the retrieved ORMEs. Finally, we have compiled all the retrieved line parameters in an electronic format and reported as electronic supplemental documents to facilitate the analyses of planetary and exoplanetary atmospheres using ground-, air- and space-based observations (e.g., Keck I and II, SOFIA, JWST, etc.).
DOI: 10.48577/jpl.602asy
title: The Antarctic sea ice cover from ICESat-2 and CryoSat-2: freeboard, snow depth and ice thickness

description: We offer a view of the Antarctic sea ice cover from lidar (ICESat-2) and radar (CryoSat-2) 5 altimetry, with retrievals of freeboards, snow depth, and ice volume that span an 8-month winter between April, 2019 and November 16, 2019. Snow depths are from freeboard differences. The remarkable response of the ice cover to mechanical convergence in the coastal Amundsen Sea was captured in the correlated increase in local freeboards and thickness. The multiyear ice in the West Weddell sector also stands out with mean sector thickness of &gt; 2 m. Thinnest ice is found near polynyas (Ross Sea and Ronne) where new ice areas are exported seaward and entrained in the surrounding ice cover. For all months, the results suggest that ~60-70% of the total freeboard is comprised of snow. While the spatial patterns in the freeboard, snow depth, and thickness composite are as expected, the observed seasonality in these variables is surprisingly weak, likely attributable to the competing processes (snowfall, snow redistribution, snow-ice formation, ice deformation, basal growth/melt) that contribute to uncorrelated changes in the total and radar freeboards. Evidence points to biases in CryoSat-2 freeboards from high salinity (&gt;10 psu) in the basal snow-layer resulting in lower/higher snow depth/ice thickness retrievals. Adjusting CS-freeboards by 6 cm gives a circumpolar ice volume of 12,500 km3 in October, for an average thickness of ~0.93 m. Validation of Antarctic sea ice parameters remain a challenge, there are no seasonally and regionally diverse data set that could be used to assess the large-scale satellite retrievals.
DOI: 10.48577/jpl.atodph
title: Extending the global mass change data record: GRACE Follow-On instrument and science data performance

description: Since June, 2018, the Gravity Recovery and Climate Experiment Follow-On (GRACE-FO) is extending the 15-year monthly mass change record of the GRACE mission, which ended in June 2017. The GRACE-FO instrument and flight system performance has improved over GRACE. Better attitude solutions and enhanced pointing performance result in reduced fuel consumption and gravity range rate post-fit residuals. One accelerometer requires additional calibrations due to unexpected measurement noise. The GRACE-FO gravity and mass change fields from June 2018 through December 2019 continue the GRACE record at an equivalent precision and spatio-temporal sampling. During this period, GRACE-FO observed large interannual terrestrial water variations associated with excess rainfall (Central US, Middle East), drought (Europe, Australia), and ice melt (Greenland). These observations are consistent with independent mass change estimates, providing high confidence that no inter-mission biases exist from GRACE to GRACE-FO, despite the 11-month gap. GRACE-FO has also successfully demonstrated satellite-to-satellite laser ranging interferometry.
DOI: 10.48577/jpl.nyue36
title: Modeling suggests fossil fuel emissions have been driving increased land carbon uptake since the turn of the 20th Century

description: Terrestrial vegetation removes CO2 from the atmosphere; an important climate regulation service that slows global warming1. This 119 Pg C per annum transfer of CO2 into plants2—gross primary productivity (GPP)—is the largest land carbon flux globally. While understanding past and anticipated future GPP changes is necessary to support carbon management, the factors driving long-term changes in GPP are largely unknown. Here we show that 1901 to 2010 changes in GPP have been dominated by anthropogenic activity. Our dual constraint attribution approach provides three insights into the spatiotemporal patterns of GPP change. First, anthropogenic controls on GPP change have increased from 57% (1901 decade) to 94% (2001 decade) of the vegetated land surface. Second, CO2 fertilization and nitrogen deposition are the most important drivers of change, 19.8 and 11.1 Pg C per annum (2001 decade) respectively, especially in the tropics and industrialized areas since the 1970’s. Third, changes in climate have functioned as fertilization to enhance GPP (1.4 Pg C per annum in the 2001 decade). These findings suggest that, from a land carbon balance perspective, the Anthropocene began over 100 years ago and that global change drivers have allowed GPP uptake to keep pace with anthropogenic emissions.
DOI: 10.48577/jpl.fnxnqn
title: The dynamics of large silicic systems from satellite remote sensing observations: the intriguing case of Domuyo volcano, Argentina

description: Silicic magmatic systems are the most dangerous volcanoes on Earth, capable of large and catastrophic eruptions, yet their low eruptive frequency makes it challenging to interpret their short-term unrest. Here we present a decade-plus analysis that integrates, for the first time, time series of satellite interferometric synthetic aperture radar (InSAR) surface deformation and satellite thermal infrared edifice-scale surface warming at a large silicic system: Domuyo volcano, in Argentina. We find that deformation and warming are highly correlated, and depending on the sign and lag between the time series, either shallow sealing or magma influx could drive Domuyo’s ongoing inflation (~0.15 m/year; from an InSAR-derived tabular source, ~11x8x1 km; ~6.5 km depth; ~0.037 km3/yr volume-change rate) and warming (0.3-0.4 °C/year). This study shows the potential that combined satellite surface deformation and edifice-scale surface warming time series have on assessing the physical mechanisms of silicic volcanic systems and for constraining deterministic models.
DOI: 10.48577/jpl.s5aktq
title: Investigating the sensitivity of soil heterotrophic respiration to recent snow cover changes in Alaska using a satellite-based permafrost carbon model

description: The contribution of soil heterotrophic respiration to the boreal-Arctic carbon (CO2) cycle and its potential feedback to climate change remain poorly quantified. We developed a remote sensing driven permafrost carbon model at intermediate scale (~1 km) to investigate how environmental factors affect the magnitude and seasonality of soil heterotrophic respiration in Alaska. The permafrost carbon model simulates snow and soil thermal dynamics, and accounts for vertical soil carbon transport and decomposition at depths up to 3 m below surface. Model outputs include soil temperature profiles and carbon fluxes at 1-km resolution spanning the recent satellite era (2001-2017) across Alaska. Comparisons with eddy covariance tower measurements show that the model captures the seasonality of carbon fluxes, with favorable accuracy in simulating net ecosystem CO2 exchange (NEE) for both tundra (R &gt; 0.8, RMSE = 0.34 g C m-2 d-1) and boreal forest (R &gt; 0.73, RMSE = 0.51 g C m-2 d-1). Benchmark assessments using two regional in-situ datasets indicate that the model captures the complex influence of snow insulation on soil temperature, and the temperature sensitivity of cold-season soil heterotrophic respiration. Across Alaska, we find that seasonal 3snow cover imposes strong controls on the contribution from different soil depths to total soil heterotrophic respiration. Earlier snow melt in spring promotes deeper soil warming and enhances the contribution of deeper soils to total soil heterotrophic respiration during the later growing season, thereby reducing net ecosystem carbon uptake. Early cold-season soil heterotrophic respiration is closely linked to the number of snow-free days after the land surface freezes (R = -0.48, p &lt; 0.1), i.e. the delay in snow onset relative to surface freeze onset. Recent trends toward earlier autumn snow onset in northern Alaska promote a longer zero-curtain period and enhanced cold-season respiration. In contrast, southwestern Alaska shows a strong reduction in the number of snow-free days after land surface freeze onset, leading to earlier soil freezing and a large reduction in cold-season soil heterotrophic respiration. Our results also show non-negligible influences of sub-grid variability of surface conditions on the model simulated CO2 seasonal cycle, especially during the early cold season at 10-km scale. Our results demonstrate the critical role of snow cover affecting the seasonality of soil temperature and respiration, and highlight the challenges of incorporating these complex processes into future projections of the boreal-Arctic carbon cycle.
DOI: 10.48577/jpl.vjwums
title: Optimal Estimation Retrievals and Their Uncertainties: What Every Atmospheric Scientist Should Know

description: Remote sensing instruments are heavily used to provide observations for both the operational and research communities. These sensors do not provide direct observations of the desired atmospheric variables, but instead, retrieval algorithms are necessary to convert the indirect observations into the variable of interest. It is critical to be aware of the underlying assumptions made by many retrieval algorithms, including that the retrieval problem is often ill-posed and that there are various sources of uncertainty that need to be treated properly. In short, the retrieval challenge is to invert a set of noisy observations to obtain estimates of atmospheric quantities. The problem is often complicated by imperfect forward models, imperfect prior knowledge, and by the existence of nonunique solutions. Optimal Estimation (OE) is a widely used physical retrieval method that combines measurements, prior information, and the corresponding uncertainties based on Bayes’ theorem to find an optimal solution for the atmospheric state. Furthermore, OE also allows the relative contributions of the different sources of error to the uncertainty in the final retrieved atmospheric state to be understood. Here, we provide a novel Python library to illustrate the use of OE for inverse problems in Atmospheric Sciences. We introduce two example problems: How to retrieve drop size distribution parameters from radar observations and how to retrieve the temperature profile from ground-based microwave sensors. Using these examples, we discuss common pitfalls, how the various error sources impact the retrieval and how the quality of the retrieval results can be quantified.
DOI: 10.48577/jpl.faahzh
title: Superresolution Reconstruction of Severely Undersampled Point-spread Functions Using Point-source Stacking and Deconvolution

description: Point-spread function (PSF) estimation in spatially undersampled images is challenging because large pixels average fine-scale spatial information. This is problematic when fine-resolution details are necessary, as in optimal photometry where knowledge of the illumination pattern beyond the native spatial resolution of the image may be required. Here, we introduce a method of PSF reconstruction where point sources are artificially sampled beyond the native resolution of an image and combined together via stacking to return a finely sampled estimate of the PSF. This estimate is then deconvolved from the pixel-gridding function to return a superresolution kernel that can be used for optimally weighted photometry. We benchmark against the &lt;1% photometric error requirement of the upcoming SPHEREx mission to assess performance in a concrete example. We find that standard methods like Richardson–Lucy deconvolution are not sufficient to achieve this stringent requirement. We investigate a more advanced method with significant heritage in image analysis called iterative back-projection (IBP) and demonstrate it using idealized Gaussian cases and simulated SPHEREx images. In testing this method on real images recorded by the LORRI instrument on New Horizons, we are able to identify systematic pointing drift. Our IBP-derived PSF kernels allow photometric accuracy significantly better than the requirement in individual SPHEREx exposures. This PSF reconstruction method is broadly applicable to a variety of problems and combines computationally simple techniques in a way that is robust to complicating factors such as severe undersampling, spatially complex PSFs, noise, crowded fields, or limited source numbers.
DOI: 10.48577/jpl.mtojhc
title: HD 219134 Revisited: Planet d Transit Upper Limit and Planet f Transit Non-Detection with ASTERIA and TESS

description: HD 219134 is a K3V dwarf star with six reported planets discovered by the radial velocity method. The two innermost planets HD 219134 b and c show transits, raising the possibility of the HD 219134 system to be the nearest (6.53 pc), brightest (V=5.57) example of a star with a compact multiple transiting planet system. Ground-based searches for transits of planets beyond b and c is not feasible because of the infrequent transits, long transit duration (~5 hours), shallow transit depths (&lt; 1%), and large transit time uncertainty (~ half a day). We use the space-based telescopes ASTERIA and TESS to search for transits of planets HD 219134 f (P =22.717 days and M_sin(i) = 7.3 +/- 0.04 M_Earth) and d (P = 46.859 days and M_sin(i) = 16.7 +/- 0.64 M_Earth). ASTERIA was a technology demonstration CubeSat with an opportunity for science in an extended program. ASTERIA observations of HD 219134 were designed to cover the 3-sigma transit windows for planets f and d via repeated visits over many months. While TESS has much higher sensitivity and more continuous time coverage than ASTERIA, only the HD 219134 f transit window fell within the TESS survey's observations. Our TESS photometric results definitively rule out planetary transits for HD 219134 f. We do not detect the Neptune-mass HD 219134 d transits and our ASTERIA data are sensitive to planets as small as 4.1 R_Earth. We provide TESS updated transit times for HD 219134 b and c, which are designated TOI 1469.01 and 1469.02 respectively.
DOI: 10.48577/jpl.pqbiaz
title: The Spiderweb Structure of Stratocumulus Clouds

description: Stratocumulus clouds have a distinctive structure composed of a combination of lumpy cellular structures and thin elongated regions, resembling canyons or slits. We refer to the elongated slits as “spiderweb” structure. Using very high resolution large-eddy simulations (LES) it is shown that the spiderweb structure is caused by cloud-top evaporative cooling and the resulting buoyancy reversal instability (BRI). Analysis of liquid water path and the cloud liquid water content shows that cloud-top evaporative cooling generates relatively shallow slits near the cloud top. Because most of the liquid water mass is concentrated near the cloud top, these regions of clear air have a large impact on the entire column LWP. When the evaporative cooling is suppressed in the LES, LWP exhibits cellular lumpy structure without the elongated low LWP regions. Even though the spiderweb signature on the LWP distribution is negligible, the cloud-top evaporative cooling process significantly affects integral boundary layer quantities, such as the vertically integrated turbulent kinetic energy, mean liquid water path, and the entrainment rate. In a pair of simulations driven only by cloud-top radiative cooling, evaporative cooling nearly doubles the entrainment rate.