Jet Propulsion Laboratory Research Articles

The Neptunian gravity estimated from the motion of Triton based on astrometric observations

Context. Accurate gravity and ephemerides estimations for Neptune and its satellites are necessary for the forthcoming deep space exploration missions targeting its system. In addition, these estimations are also meaningful for the modeling of Neptune's interior and for solar system dynamics studies. The body of astrometric data concerning Triton has been accumulating for about two hundred years, but more accurate updates to the ephemerides of this moon and revisions to the relevant gravity parameters would be possible with more precise astrometric data. The new Gaia catalog of star positions plus observations from Voyager 2 and the Hubble Space Telescope provide such a basis for high-precision astrometry and to complement and extend the existing body of data. Aims. We aim to report integrated orbital fits for Triton based on all the available astrometric data from 1847 to 2020, including observations from Earth-based telescopes, Voyager 2, and the Hubble Space Telescope. We also estimate the Neptunian gravity using the motion of Triton. Methods. Triton’s orbital solution was determined by a weighted least-squares method to fit the model to the most complete astrometric data set to date. The DOP853 algorithm was adopted in the numerical integration calculations. For the dynamical model parameters, our orbital model for Triton is similar to the NEP081 but with an update. The perturbations from the inner satellites (Naiad, Thalassa, Despina, Galatea, Larissa, Proteus, and Hippocamp) were considered by adding corrections to J2 and J4 for Neptune. As the gravitational oblateness coefficient of Neptune is correlated with its orientation, the pole parameters were thus kept fixed in the integration when estimating Neptunian gravity. A Monte Carlo analysis was performed, however, to obtain reliable accuracy estimations and to assess the uncertainty of pole parameters on the results’ formal error. Results. We provide a new orbit and dynamical model values for Triton. The estimated accuracy of the model we built and updated fit all the astrometric data. The RMS of the residuals was 0.074 arcsec in the right ascension and 0.071 arcsec in declination. The RMS was 0.102 arcsec for X and 0.139 arcsec for Y in differential coordinates. The RMS for the position angle was 0.834 degrees, and the angular separation distance was 0.257 arcsec for the data collected before 1960. The orbit of Triton was well determined with the orbit differences from NEP081 and NEP097 (so far the latest Triton ephemerides from Jet Propulsion Laboratory) as being less than 300 km (about 15 mas) during the observation coverage period of this study. The large body of astrometric data for Triton over a time interval from 1847 to 2020 was used to constrain its position at the initial epoch, allowing us to reduce formal uncertainty to about 3 km. Based on the most complete weighting astrometric observations of Triton, the estimated mass of the Neptune system is GMs = 6 836 525.210 ±19.526 km3 s−2. Our revised gravity model yields J2 = 3401.655 ±1.850 × 10−6 and J4 = −33.294 ±10.000 × 10−6. The astrometric observations showed little sensitivity to GMs and J4, but acted well on J2. A Monte Carlo method was used to analyze the error caused by a variation in the pole parameters and showed that J2 = 3401.655 ± 3.994 × 10−6 was a more realistic error.

Breaking New Ground: Space Agencies and Epidemiologists Partner Up on Particulates

Breaking New Ground: Space Agencies and Epidemiologists Partner Up on Particulates

Sensitivity Analysis of Modelled Flood Inundation Extents over Hawkesbury–Nepean Catchment

Rainfall runoff and topography are among the major factors controlling the accuracy of modelled riverine inundation extents. We have evaluated the sensitivity of both these variables on a novel 1-D conceptual flood inundation model employing Height Above Nearest Drainage (HAND) thresholds within sub-catchment units called Reach Contributing Area (RCA). We examined the March 2021 flood extent over the Hawkesbury–Nepean Valley (HNV) with 0.05′ gridded runoff derived from the Australian Water Resources Assessment (AWRA) modelling framework. HAND thresholds were enforced within each RCA using rating curve relationships generated by a modelled river geometry dataset obtained from Jet Propulsion Laboratory (JPL) and by modelling Manning’s roughness coefficient as a function of channel slope. We found that the step-like topographic nature of HNV significantly influences the back-water effect within the floodplain. At the same time, the improved accuracy of the GeoFabric Digital Elevation Model (DEM) outperforms SRTM DEM-derived flood output. The precision of HAND thresholds does not add significant value to the analysis. With enhanced access to river bathymetry and an ensemble point-based runoff modelling approach, we can generate an ensemble runoff-based probabilistic extent of inundation.

Estimation of Arctic Sea Ice Thickness from Chinese HY-2B Radar Altimetry Data

Sea ice thickness (SIT) is an important parameter in the study of climate change. During the past 20 years, satellite altimetry has been widely used to observe sea ice thickness. The Chinese Haiyang-2B (HY-2B) radar altimeter, launched in October 2018, can provide data up to 80.6° latitude and can be used as a supplementary means to observe polar sea ice. Reliable HY-2B SIT products will contribute to the sea ice community. In this study, we aimed to assess the Arctic sea ice thickness retrieval ability of the HY-2B radar altimetry data. We processed the HY-2B radar altimetry data from January 2019 to April 2022 and used the processed data to retrieve the Arctic SIT. The Alfred Wegener Institute (AWI) CryoSat-2 (CS-2) SIT products were used to calibrate the HY-2B SIT estimates with a linear regression method. The Goddard Space Flight Center (GSFC) CS-2, Jet Propulsion Laboratory (JPL), and GSFC ICESat-2 (IS-2) SIT products were used to validate the HY-2B calibrated SIT estimates. The HY-2B calibrated SIT estimates have good, consistent spatial distributions with the CS-2 and IS-2 SIT products. The comparison with the IS-2 and IS-2 SIT products shows the root-mean-square error (RMSE) and bias for the HY-2B SIT estimates are significantly reduced after calibration. The HY-2B SIT estimates were also validated using the ice thickness data from Operation IceBridge (OIB) and the ice draft data from the Beaufort Gyre Exploration Project (BGEP). Finally, the monthly variations of the HY-2B SIT estimates were analyzed. Results show that the HY-2B calibrated SIT estimates are reliable, especially when the SIT values are lower than 3 m. The HY-2B altimetry data is a possible source for sea ice thickness data at lower latitudes and will help us better understand the sea ice response to climate change.

Comparison of GRACE Gravity Anomaly Solutions for Terrestrial Water Storage Variability in Arid and Semi-arid Botswana

Explorations of the differences between Gravity Recovery and Climate Experiment (GRACE) solutions in local regions and basins are fundamental in determining their suitability and applicability in these environments. Because of the different mathematical inversions used by the respective processing centers, individual solutions exhibit discrepancies in terms of mass increase or loss, which makes it difficult for users to select the best model for studying terrestrial water storage anomalies (TWSAs). This study compares TWSA trends, as derived from different GRACE solutions over the arid and semi-arid Botswana (2002-2019), where both storage and flux from CSR, JPL, GFZ, TUGRAZ, AIUB, and COST-G[1] were compared. The results show that the six solutions are fairly correlated with the least correlation of R=0.829 between JPL and AIUB, and a maximum of R=0.921 between CSR and TUGRAZ at a 95% confidence level. The TWSA analyses for 2002-2019 indicate that TWS is increasing in Botswana, with the least linear trend of +0.11cm/yr detected from the TUGRAZ inversion model, and the highest linear trend at +0.43cm/year from the COST-G model. On comparing TWS with rainfall, all the solutions presented the same spatio-temporal trends as the rainfall patterns, indicating that the GRACE solutions exhibit the same responses with respect to the received rainfall. Over the 18 years investigated, the long-term rainfall trend was found to decrease, which was only detected by the TUGRAZ model in terms of the recorded equivalent water height (EWH) of -0.008cm/yr from the monthly trend observations. Overall, the AIUB inversion solution gave a better result as its signal was found to be the same as the rainfall signal.
 
 [1] CSR = Center for Space Research; JPL = Jet Propulsion Laboratory; GFZ = the German Research Center for Geosciences; TUGRAZ = Graz University of Techology; AIUB = the Astronomical Institute of the University of Bern; COST-G = the International Combination Service for Time-Variable Gravity Fields

Performance and Consistency of Final Global Ionospheric Maps from Different IGS Analysis Centers

Ionospheric delay is one of the most problematic errors in satellite-based positioning data processing. The Global Ionospheric Map (GIM), which is publicly available daily in various analysis centers, is thus vitally important for positioning users. There are variations in the accuracy and consistency of GIMs issued by Ionosphere Associate Analysis Centers (IAACs) due to the differences in ionospheric modeling methods and selected tracking stations. In this study on the International GNSS Service’s (IGS) final GIM, the ionospheric total electron content (TEC) (from 243 global navigation satellite system (GNSS) monitoring stations around the world) and the ionospheric TEC (from the Jason-3 altimeter satellite) are selected as reference. By using these three references, we evaluate the performance and consistency of final GIM products from seven IGS IAACs, including the Chinese Academy of Sciences (CAS), the Center for Orbit Determination in Europe (CODE), Natural Resources Canada (EMR), the European Space Agency (ESA), the Jet Propulsion Laboratory (JPL), Universitat Politècnica de Catalunya (UPC), and Wuhan University (WHU) in the mid-solar activity year (2022) and the low-solar activity year (2020). Firstly, the comparison with the IGS final GIM shows that the consistency of each GIMs is basically the same, with the mean value ranging from −0.3 TECu (total electron content unit) to 1.4 TECu. Secondly, the validation with Jason-3 altimeter satellite shows that the accuracy of several GIMs is almost the same, except for the JPL with the worst accuracy and an overall mean deviation (BIAS) between 2 and 6 TECu. Thirdly, the comparison with VTEC extracted from GNSS monitor stations shows that the CAS has the best accuracy in different latitude bands with a root mean square (RMS) of about 2.2–4.7 TECu. In addition, it is found that the accuracy in areas with more stations for ionospheric modelling is better than those with less stations in different latitude bands; meanwhile, the accuracy is closely related to the modeling methods of different GIMs.

Near-Earth object 2022 EB5: From atmospheric entry to physical properties and orbit

Context. The near-Earth object (NEO) 2022 EB5 is the fifth NEO found prior to entering the Earth's atmosphere. It fragmented over the Norway Sea on 2022 March 11 about two hours after being discovered by the astronomer Krisztián Sárneczky at Konkoly Observatory in Hungary. The Center for Near-Earth Object Studies (CNEOS) at NASA detected the visible radiation emitted at the time of its atmospheric entry. The Jet Propulsion Laboratory (JPL) and European Space Agency (ESA) derived its orbital elements based on observations of its pre-atmospheric orbit. Aims. This paper aims to calculate the physical properties of this NEO, in particular, the bulk strength, type of the material, albedo, size, and mass, based on observations of its peak brightness at the time of its atmospheric entry. In addition, the heliocentric elements are computed from its interaction with Earth's atmosphere and compared with those derived from observations by JPL and ESA, respectively, to evaluate the accuracy of our method. Methods. The flight equations of 2022 EB5 were inversely integrated from the peak brightness to the atmospheric boundary via the fourth-order Runge-Kutta method. A pancake model was utilized to simulate the fragmentation of the impactor. Parameters needed to complete the integration process that were unknown were set to be optimization variables and determined via a genetic algorithm. Results. The results obtained show that 2022 EB5 was most likely a C-type asteroid with a maximal bulk strength of 2 MPa, diameter of 5–6 m, cometary density, and very low albedo that is no greater than 0.025. In addition, considering the effects of the atmosphere is helpful in getting a more accurate measurement for the semi-major axis, eccentricity, and inclination, although the accuracy of orbital elements strongly depends on the accuracy of USG sensors.

The Mars Microphone Onboard SuperCam

The Mars Microphone is one of the five measurement techniques of SuperCam, an improved version of the ChemCam instrument that has been functioning aboard the Curiosity rover for several years. SuperCam is located on the Rover's Mast Unit, to take advantage of the unique pointing capabilities of the rover's head. In addition to being the first instrument to record sounds on Mars, the SuperCam Microphone can address several original scientific objectives: the study of sound associated with laser impacts on Martian rocks to better understand their mechanical properties, the improvement of our knowledge of atmospheric phenomena at the surface of Mars: atmospheric turbulence, convective vortices, dust lifting processes and wind interactions with the rover itself. The microphone will also help our understanding of the sound signature of the different movements of the rover: operations of the robotic arm and the mast, driving on the rough floor of Mars, monitoring of the pumps, etc ... The SuperCam Microphone was delivered to the SuperCam team in early 2019 and integrated at the Jet Propulsion Laboratory (JPL, Pasadena, CA) with the complete SuperCam instrument. The Mars 2020 Mission launched in July 2020 and landed on Mars on February 18th 2021. The mission operations are expected to last until at least August 2023. The microphone is operating perfectly.

Part 2:Validation for line lists generated for nitric acid (H14N16O3) for the ν1 band and its first two associated hot bands (ν1+ν9-ν9, ν1+ν7-ν7) in the 2.8 μm region, the ν1-ν9, ν1+ν9 and ν1+ν7 bands at 3.2 μm, 2.5 μm and 2.4 μm, respectively

This is the second of two back-to-back works, whose goal is to generate line lists for the ν1 band (3551.766 cm−1) and for the ν1+ν9-ν9 and ν1+ν7-ν7 hot bands for HNO3 in the 2.8 μm region. Also, we computed line lists for the weaker ν1-ν9, ν1+ν9, and ν1+ν7 bands, centered at 3093.53 cm−1, 4006.97 cm−1 and 4127.78 cm−1, respectively. While the first paper (Ref.[1], the preceding article in this issue), here labeled as “Part-1”, was devoted to the description of the determination of the needed spectroscopic parameters in term of line positions and intensities, this paper describes the resulting line lists and the validation process. For this task, we use laboratory spectra recorded at high resolution and described in Part-1, together with the cross-sections established by the Pacific Northwest Laboratory at low resolution. Also, we use high resolution stratospheric solar occultation spectra recorded by the MkIV balloon-borne instrument of the NASA Jet Propulsion Laboratory (JPL). Similar inter-comparisons with laboratory or atmospheric spectra are also performed using the pseudo-line-list generated at JPL in 2005 and with the ab initio ExoMol list calculated by the University College of London. It proves that the line list generated during this work provides significant better agreements between observed and computed spectra.

Groundwater recharge estimation using in-situ and GRACE observations in the eastern region of the United Arab Emirates

The intensive agricultural expansion and rapid urban development in Abu Dhabi Emirate, United Arab Emirates (UAE) have resulted in a major decline in local and regional groundwater levels. By using the latest release (RL06) of Gravity Recovery and Climate Experiment (GRACE) satellite measurements and Global Land Data Assimilation System (GLDAS) products, the groundwater storage change was computed and compared with the time series of in-situ monitoring wells over the period of 2010–2016. The RL06 GRACE products from Jet Propulsion Laboratory (JPL), University of Texas Center for Space Research (CSR), German Research Center for Geosciences (GFZ), and JPL mass concentrations (MASCON) were assessed and have shown satisfactory agreements with the monitoring wells. The JPL MASCON reflected the in-situ groundwater storage change better than the other GRACE products (R = 0.5, lag =1 month, RMSE = 13 mm). The groundwater recharge is estimated for the study area and compared with the in-situ recharge method that considers multi recharge components from the rainfall, irrigation return flow and internal fluxes. The results show that the agreements between in-situ and GRACE-derived recharge estimates are highly agreeable (e.g., R2 = 0.91, RMSE = 1.5 Mm3 to 7.8 Mm3, and Nash-Sutcliff Efficiency = 0.7). Using the Mann-Kendall trend test and Sen's slope, the analyses of policies, number of wells, and farm areal expansion with groundwater time series derived from GRACE helped to validate GRACE and emphasize the importance of regulations for sustainable development of groundwater resources. The impacts of subsidy cuts after 2010 can be captured from the GRACE data in the eastern region of Abu Dhabi Emirate. The linear trend of groundwater storage anomaly obtained from GRACE over the period from 2003 to 2010 is −6.36 ± 0.6 mm/year while it showed a decline trend of −1.2 ± 0.6 mm/year after the subsidy cut. The proposed approach has a potential application for estimating groundwater recharge in other arid regions where in-situ monitoring wells are limited or absent.

Comparison of GRACE/GRACE-FO Spherical Harmonic and Mascon Products in Interpreting GNSS Vertical Loading Deformations over the Amazon Basin

We compute the vertical displacements in the Amazon Basin using the Gravity Recovery and Climate Experiment (GRACE) and GRACE Follow-On (GRACE-FO) observations, including both the gravity spherical harmonic (SH) solutions from the Center for Space Research (CSR), GeoForschungsZentrum (GFZ) and Jet Propulsion Laboratory (JPL) and mascons from CSR, JPL and Goddard Space Flight Center (GSFC). The correlation coefficients, annual amplitude and root mean squares (RMS) reductions are calculated to assess the agreements between the GRACE/GRACE-FO and Global Navigation Satellite System (GNSS) vertical displacements at 22 selected GNSS stations. For the six GRACE/GRACE-FO products (i.e., CSR SH, GFZ SH, JPL SH, CSR mascon, GSFC mascon and JPL mascon), the mean annual amplitude reductions are 77.6%, 76.4%, 76.3%, 78.6%, 78.5% and 76.6%, respectively, the corresponding mean RMS reductions are 63.2%, 61.7%, 62.3%, 64.9%, 65.3% and 63.8%, respectively, and the mean correlation coefficients are all over 0.93. On the whole, mascon solutions agree slightly better with GNSS solutions than SH solutions do. The CSR SH and the GSFC mascon solutions show the best agreements with the GNSS solution among the 3 SH and 3 mascon products, respectively. We estimate GRACE/GRACE-FO noises using the three-cornered hat (TCH) method and find that the CSR SH and GSFC mascons also have the smallest noise variances among the SH and mascon products, respectively. By analyzing the GNSS stations from the central and southern Amazon Basin, we find that: (1) the RMS reductions when the mascon solutions are removed from GNSS height series are slightly larger than those using the SH solutions in the center, while in south all the RMS reductions are fairly close; (2) for both SH solutions and mascon solutions, the correlation coefficients in the center are slightly larger than those in the south, but conversely, the mean annual amplitude reductions in the center are much smaller than those in the south.

Refinement of GRACE‐FO Kinematic Orbit by Combining Least Squares Method and Orbital Dynamic Model

Gravity Recovery and Climate Experiment Follow‐On (GRACE‐FO) satellites are used to map the gravity field of the Earth. The orbit accuracy of GRACE‐FO depends on the quality of on‐board GPS data, which is key factor affecting GRACE‐FO mission execution. To improve the orbit accuracy of GRACE‐FO, a dynamical method was developed to reprocess kinematic orbits. First, with known kinematic orbits, the least squares method was used to estimate the initial state and dynamical parameters of GRACE‐FO orbits. Second, during data processing, orbit coordinates containing outliers were deleted. Finally, GRACE‐FO dynamical orbits with high accuracy were determined by combining initial state and dynamical parameters. To assess the orbit accuracy, dynamical and kinematic orbits were compared with Jet Propulsion Laboratory (JPL) orbits. Three‐dimensional root‐mean‐square (3D‐RMS) results show dynamical and kinematic orbit accuracy of 6.3 and 9.5 cm for GRACE‐FO‐C and 6.6 and 9.7 cm for GRACE‐FO‐D, achieving improvements of 33.68% and 31.96%, respectively. The RMS of satellite laser range (SLR) residuals was about 4.1 and 5.1 cm for GRACE‐FO‐C dynamical and kinematic orbit accuracy, and about 4.2 and 5.4 cm for GRACE‐FO‐D.

Probabilistic Charging Power Forecast of EVCS: Reinforcement Learning Assisted Deep Learning Approach

The electric vehicle (EV) and electric vehicle charging station (EVCS) have been widely deployed with the development of large-scale transportation electrifications. However, since charging behaviors of EVs show large uncertainties, the forecasting of EVCS charging power is non-trivial. This paper tackles this issue by proposing a reinforcement learning assisted deep learning framework for the probabilistic EVCS charging power forecasting to capture its uncertainties. Since the EVCS charging power data are not standard time-series data like electricity load, they are first converted to the time-series format. On this basis, one of the most popular deep learning models, the long short-term memory (LSTM) is used and trained to obtain the point forecast of EVCS charging power. To further capture the forecast uncertainty, a Markov decision process (MDP) is employed to model the change of LSTM cell states, which is solved by our proposed adaptive exploration proximal policy optimization (AePPO) algorithm based on reinforcement learning. Finally, experiments are carried out on the real EVCSs charging data from Caltech, and Jet Propulsion Laboratory, USA, respectively. The results and comparative analysis verify the effectiveness and outperformance of our proposed framework.

Aeronomic and Dynamic Correction of the Global Model GTEC for Disturbed Conditions

An aeronomic and dynamic correction of the GTEC median global model of the total electroncontent for disturbed conditions (Ap ≥ 15 nT) is proposed. The GTEC global median model is developedfor quiet conditions (Ap 15 nT) as a function of the geographic coordinates, universal time UT, day of theyear, and solar activity level (the solar radio emission flux F10.7). The model is based on a spherical harmonicanalysis of the GIM-TEC Global Ionospheric Maps (1996–2019) provided by the Jet PropulsionLaboratory (NASA). The proposed GDMTEC global dynamic model (Global Dynamic Model of TEC)consists of the GTEC median model updated with several dynamic and aeronomic corrections related toformation of the main ionospheric trough, position of the auroral ionization maximum and changes of thethermospheric temperature and composition. The advantage of the proposed corrections of the medianmodel is the independence of forecast of the data in real time from assimilation of the current observationaldata. Testing of the model for disturbed conditions shows an improvement of the forecast compared to theIRI-Plas ionospheric reference model

Low latitude monthly total electron content composite correlations

Spatial correlations of total electron content (TEC) variability are compared among two SAMI3 model runs and Jet Propulsion Laboratory Global Ionospheric Maps (JPL/GIM). Individual monthly correlation maps are constructed with Equatorial reference points at 12 evenly spaced longitudes and 12 universal times. TEC composite correlations (TCCs) are then calculated by averaging the individual maps, shifted zonally to synchronize local time. The TCC structures are quantified using Gaussian fits in the zonal and meridional directions. A non-zero large-scale “base correlation” is found in all three datasets for 2014, a year with high solar activity. Higher base correlations generally occur in the SAMI3 runs than in JPL/GIM. The SAMI3 run driven with climatological neutral fields shows higher correlations than the run driven with neutrals from a Whole Atmosphere Community Climate Model with thermosphere–ionosphere eXtension (WACCM-X) simulation. Base correlation values strongly correlate with monthly F10.7 standard deviations. Empirical orthogonal function (EOF) analyses confirm that large-scale correlations are usually, although not always, related to solar forcing. Strong correlations between the Ap index and EOF modes are also observed, consistent with the geomagnetic forcing of the TEC field. The widths of the correlation structures are also examined, and these vary considerably with local time, month, and dataset. Off-Equator conjugate point correlations are also calculated from each dataset and variations with the month and local time are analyzed. Analysis of TCCs for 2010, a year with low solar activity, shows that base correlations as well as correlations of the first EOF mode with F10.7 are generally weaker than in 2014.

Fast Three‐Dimensional Search Algorithm to Improve the Carrier Tracking Performance During the Entry, Descent, and Landing (EDL) Phase of Mars Probes

AbstractCarrier tracking for highly dynamic and extremely weak signals is challenging, including during the entry, descent, and landing phase of Mars rovers and the soft landing of lunar probes. In this study, a novel frequency detector is designed based on the frequency maximum likelihood estimator, and a frequency‐locked loop algorithm is constructed. The frequency‐locked loop is suitable for tracking Doppler shifts with large first and second derivatives. Compared with the Jet Propulsion Laboratory frequency maximum likelihood estimator, the computation time is significantly reduced. The simulation results illustrate the effectiveness of the proposed algorithm. This method provides a good method for Doppler frequency measurement in deep space exploration, especially when tracking highly dynamic and extremely weak signals.

Application of shaken lattice interferometry based sensors to space navigation

High–sensitivity shaken lattice interferometry (SLI) based sensors have the potential to provide deep space missions with the ability to precisely measure non–gravitational perturbing forces. This work considers the simulation of the OSIRIS-REx mission navigation in the vicinity of Bennu with the addition of measurements from onboard SLI–based accelerometers. The simulation is performed in the Jet Propulsion Laboratory’s (JPL) Mission Analysis, Operations and Navigation Toolkit (MONTE) and incorporates OSIRIS-REx reconstructed trajectory and attitude data from the Navigation and Ancillary Information Facility (NAIF) database. The use of the reconstructed data from NAIF provides realistic true dynamical errors and JPL’s MONTE software allows for a high–fidelity simulation of an integrated trajectory for the filter. The navigation performance and reduction of tracking and complex modelling enabled by the onboard SLI–based sensor are presented for two orbital phases of the OSIRIS–REx mission. Overall, the results show that the addition of SLI–based accelerometer measurements improves navigation performance, when compared to a radiometric tracking only configuration. In addition, results demonstrate that highly–precise accelerometer measurements can effectively replace at least one day of DSN passes over a three–day period, thereby reducing tracking requirements. Furthermore, it is shown that lower–fidelity surface force modeling and parameter estimation is required when using onboard SLI–based accelerometers.

Description and Genome Characterization of Three Novel Fungal Strains Isolated from Mars 2020 Mission-Associated Spacecraft Assembly Facility Surfaces-Recommendations for Two New Genera and One Species.

National Aeronautics and Space Administration's (NASA) spacecraft assembly facilities are monitored for the presence of any bacteria or fungi that might conceivably survive a transfer to an extraterrestrial environment. Fungi present a broad and diverse range of phenotypic and functional traits to adapt to extreme conditions, hence the detection of fungi and subsequent eradication of them are needed to prevent forward contamination for future NASA missions. During the construction and assembly for the Mars 2020 mission, three fungal strains with unique morphological and phylogenetic properties were isolated from spacecraft assembly facilities. The reconstruction of phylogenetic trees based on several gene loci (ITS, LSU, SSU, RPB, TUB, TEF1) using multi-locus sequence typing (MLST) and whole genome sequencing (WGS) analyses supported the hypothesis that these were novel species. Here we report the genus or species-level classification of these three novel strains via a polyphasic approach using phylogenetic analysis, colony and cell morphology, and comparative analysis of WGS. The strain FJI-L9-BK-P1 isolated from the Jet Propulsion Laboratory Spacecraft Assembly Facility (JPL-SAF) exhibited a putative phylogenetic relationship with the strain Aaosphaeria arxii CBS175.79 but showed distinct morphology and microscopic features. Another JPL-SAF strain, FJII-L3-CM-DR1, was phylogenetically distinct from members of the family Trichomeriaceae and exhibited morphologically different features from the genera Lithohypha and Strelitziana. The strain FKI-L1-BK-DR1 isolated from the Kennedy Space Center facility was identified as a member of Dothideomycetes incertae sedis and is closely related to the family Kirschsteiniotheliaceae according to a phylogenetic analysis. The polyphasic taxonomic approach supported the recommendation for establishing two novel genera and one novel species. The names Aaosphaeria pasadenensis (FJI-L9-BK-P1 = NRRL 64424 = DSM 114621), Pasadenomyces melaninifex (FJII-L3-CM-DR1 = NRRL 64433 = DSM 114623), and Floridaphiala radiotolerans (FKI-L1-BK-DR1 = NRRL 64434 = DSM 114624) are proposed as type species. Furthermore, resistance to ultraviolet-C and presence of specific biosynthetic gene cluster(s) coding for metabolically active compounds are unique to these strains.

Spatio-temporal variability of terrestrial water storage in the Yangtze River Basin: Response to climate changes

The Yangtze River Basin (YRB) is an important region for China's economic development. However, it has a complex terrain layout, most of which is affected by monsoon weather, and the geographical and temporal distribution of water resources is severely unbalanced. Therefore, the detailed analysis of spatio-temporal water mass changes is helpful to the development and rational utilization of water resources in the YRB. In this study, the variation of terrestrial water storage (TWS) is monitored by Gravity Recovery and Climate Experiment (GRACE) satellite gravity. We find that the University of Texas Center for Space Research (CSR) solution shows a notable difference with the Jet Propulsion Laboratory (JPL) in space, but the general trend is consistent in time series. Then the GRACE inferred water mass variation reveals that the YRB has experienced several drought and flood events over the past two decades. Global Land Data Assimilation System (GLDAS) results are similar to GRACE. Furthermore, the overall precipitation trend tends to be stable in space, but it is greatly influenced by the strong El Niño-Southern Oscillation (ENSO), which is the response to global climate change. The upper YRB is less affected by ENSO and shows a more stable water storage signal with respect to the lower YRB.

Simulating carbon and water fluxes using a coupled process-based terrestrial biosphere model and joint assimilation of leaf area index and surface soil moisture

Abstract. Reliable modeling of carbon and water fluxes is essential for understanding the terrestrial carbon and water cycles and informing policy strategies aimed at constraining carbon emissions and improving water use efficiency. We designed an assimilation framework (LPJ-Vegetation and soil moisture Joint Assimilation, or LPJ-VSJA) to improve gross primary production (GPP) and evapotranspiration (ET) estimates globally. The integrated model, LPJ-PM (LPJ-PT-JPLSM Model) as the underlying model, was coupled from the Lund–Potsdam–Jena Dynamic Global Vegetation Model (LPJ-DGVM version 3.01) and a hydrology module (i.e., the updated Priestley–Taylor Jet Propulsion Laboratory model, PT-JPLSM). Satellite-based soil moisture products derived from the Soil Moisture and Ocean Salinity (SMOS) and Soil Moisture Active and Passive (SMAP) and leaf area index (LAI) from the Global LAnd and Surface Satellite (GLASS) product were assimilated into LPJ-PM to improve GPP and ET simulations using a proper orthogonal decomposition (POD)-based ensemble four-dimensional variational assimilation method (PODEn4DVar). The joint assimilation framework LPJ-VSJA achieved the best model performance (with an R2 ( coefficient of determination) of 0.91 and 0.81 and an ubRMSD (unbiased root mean square deviation) reduced by 40.3 % and 29.9 % for GPP and ET, respectively, compared with those of LPJ-DGVM at the monthly scale). The GPP and ET resulting from the assimilation demonstrated a better performance in the arid and semi-arid regions (GPP: R2 = 0.73, ubRMSD = 1.05 g C m−2 d−1; ET: R2 = 0.73, ubRMSD = 0.61 mm d−1) than in the humid and sub-dry humid regions (GPP: R2 = 0.61, ubRMSD = 1.23 g C m−2 d−1; ET: R2 = 0.66; ubRMSD = 0.67 mm d−1). The ET simulated by LPJ-PM that assimilated SMAP or SMOS data had a slight difference, and the SMAP soil moisture data performed better than SMOS data. Our global simulation modeled by LPJ-VSJA was compared with several global GPP and ET products (e.g., GLASS GPP, GOSIF GPP, GLDAS ET, and GLEAM ET) using the triple collocation (TC) method. Our products, especially ET, exhibited advantages in the overall error distribution (estimated error (μ): 3.4 mm per month; estimated standard deviation of μ: 1.91 mm per month). Our research showed that the assimilation of multiple datasets could reduce model uncertainties, while the model performance differed across regions and plant functional types. Our assimilation framework (LPJ-VSJA) can improve the model simulation performance of daily GPP and ET globally, especially in water-limited regions.