UMBC GESTAR II

Permanent URI for this collectionhttp://hdl.handle.net/11603/24116

n December 2021, GESTAR II partnered with NASA Goddard Space Flight Center’s Earth Science Division to advance Earth science and Goddard’s leadership by providing a competitive environment to hire and retain high-quality scientists who are on track to be leaders at NASA, in academia and in industry. GESTAR II exemplifies the power of mentorship, embracing a career development strategy that only a university research center can provide. In GESTAR II, early-career researchers and students can build outstanding resumes, launching them to become the Earth science leaders of tomorrow.

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Multispectral Land Surface Reflectance Reconstruction Based on Non-Negative Matrix Factorization: Bridging Spectral Resolution Gaps for GRASP TROPOMI BRDF Product in Visible
(MDPI, 2025-03-17) Hou, Weizhen; Liu, Xiong; Wang, Jun; Chen, Cheng; Xu, Xiaoguang
In satellite remote sensing, mixed pixels commonly arise in medium- and low-resolution imagery, where surface reflectance is a combination of various land cover types. The widely adopted linear mixing model enables the decomposition of mixed pixels into constituent endmembers, effectively bridging spectral resolution gaps by retrieving the spectral properties of individual land cover types. This study introduces a method to enhance multispectral surface reflectance data by reconstructing additional spectral information, particularly in the visible spectral range, using the TROPOMI BRDF product generated by the Generalized Retrieval of Atmosphere and Surface Properties (GRASP) algorithm. Employing non-negative matrix factorization (NMF), the approach extracts spectral basis vectors from reference spectral libraries and reconstructs key spectral features using a limited number of wavelength bands. The comprehensive test results show that this method is particularly effective in supplementing surface reflectance information for specific wavelengths where gas absorption is strong or atmospheric correction errors are significant, demonstrating its applicability not only within the 400–800 nm range but also across the broader spectral range of 400–2400 nm. While not a substitute for hyperspectral observations, this approach provides a cost-effective means to address spectral resolution gaps in multispectral datasets, facilitating improved surface characterization and environmental monitoring. Future research will focus on refining spectral libraries, improving reconstruction accuracy, and expanding the spectral range to enhance the applicability and robustness of the method for diverse remote sensing applications.
Multi-GNSS Airborne Radio Occultation Observations as a Complement to Dropsondes in Atmospheric River Reconnaissance
(AGU, 2021-11-22) Haase, J. S.; Murphy, Michael; Cao, B.; Ralph, F. M.; Zheng, M.; Delle Monache, L.
Variations in the water vapor that atmospheric rivers (ARs) carry toward North America within Pacific storms strongly modulates the spatiotemporal distribution of west-coast precipitation. The “AR Recon” program was established to improve forecasts of landfalling Pacific-coast ARs and their associated precipitation. Dropsondes are deployed from weather reconnaissance aircraft and pressure sensors have been added to drifting ocean buoys to fill a major gap in standard weather observations, while research is being conducted on the potential for airborne Global Navigation Satellite System (GNSS) radio occultation (ARO) to also contribute to forecast improvement. ARO further expands the spatial coverage of the data collected during AR Recon flights. This study provides the first description of these data, which provide water vapor and temperature information typically as far as 300 km to the side of the aircraft. The first refractivity profiles from European Galileo satellites are provided and their accuracy is evaluated using the dropsondes. It is shown that spatial variations in the refractivity anomaly (difference from the climatological background) are modulated by AR features, including the low-level jet and tropopause fold, illustrating the potential for RO measurements to represent key AR characteristics. It is demonstrated that assimilation of ARO refractivity profiles can influence the moisture used as initial conditions in a high-resolution model. While the dropsonde measurements provide precise, in situ wind, temperature and water vapor vertical profiles beneath the aircraft, and the buoys provide surface pressure, ARO provides complementary thermodynamic information aloft in broad areas not otherwise sampled at no additional expendable cost.
Integrating Frequency-Domain Representations with Low-Rank Adaptation in Vision-Language Models
(2025-03-08) Khan, Md Azim; Gangopadhyay, Aryya; Wang, Jianwu; Erbacher, Robert F.
Situational awareness applications rely heavily on real-time processing of visual and textual data to provide actionable insights. Vision language models (VLMs) have become essential tools for interpreting complex environments by connecting visual inputs with natural language descriptions. However, these models often face computational challenges, especially when required to perform efficiently in real environments. This research presents a novel vision language model (VLM) framework that leverages frequency domain transformations and low-rank adaptation (LoRA) to enhance feature extraction, scalability, and efficiency. Unlike traditional VLMs, which rely solely on spatial-domain representations, our approach incorporates Discrete Fourier Transform (DFT) based low-rank features while retaining pretrained spatial weights, enabling robust performance in noisy or low visibility scenarios. We evaluated the proposed model on caption generation and Visual Question Answering (VQA) tasks using benchmark datasets with varying levels of Gaussian noise. Quantitative results demonstrate that our model achieves evaluation metrics comparable to state-of-the-art VLMs, such as CLIP ViT-L/14 and SigLIP. Qualitative analysis further reveals that our model provides more detailed and contextually relevant responses, particularly for real-world images captured by a RealSense camera mounted on an Unmanned Ground Vehicle (UGV).
Impact of increased anthropogenic Amazon wildfires on Antarctic Sea ice melt via albedo reduction
(Cambridge University Press, 2025-03-10) Chakraborty, Sudip; Devnath, Maloy Kumar; Jabeli, Atefeh; Kulkarni, Chhaya; Boteju, Gehan; Wang, Jianwu; Janeja, Vandana
This study shows the impact of black carbon (BC) aerosol atmospheric rivers (AAR) on the Antarctic Sea ice retreat. We detect that a higher number of BC AARs arrived in the Antarctic region due to increased anthropogenic wildfire activities in 2019 in the Amazon compared to 2018. Our analyses suggest that the BC AARs led to a reduction in the sea ice albedo, increased the amount of sunlight absorbed at the surface, and a significant reduction of sea ice over the Weddell, Ross Sea (Ross), and Indian Ocean (IO) regions in 2019. The Weddell region experienced the largest amount of sea ice retreat ( km2) during the presence of BC AARs as compared to km2 during non-BC days. We used a suite of data science techniques, including random forest, elastic net regression, matrix profile, canonical correlations, and causal discovery analyses, to discover the effects and validate them. Random forest, elastic net regression, and causal discovery analyses show that the shortwave upward radiative flux or the reflected sunlight, temperature, and longwave upward energy from the earth are the most important features that affect sea ice extent. Canonical correlation analysis confirms that aerosol optical depth is negatively correlated with albedo, positively correlated with shortwave energy absorbed at the surface, and negatively correlated with Sea Ice Extent. The relationship is stronger in 2019 than in 2018. This study also employs the matrix profile and convolution operation of the Convolution Neural Network (CNN) to detect anomalous events in sea ice loss. These methods show that a higher amount of anomalous melting events were detected over the Weddell and Ross regions.
Impact of electric and clean-fuel vehicles on future PM2.5 and ozone pollution over Delhi
(IOP, 2024-07-09) Mogno, Caterina; Wallington, Timothy J.; Palmer, Paul I.; Hakkim, Haseeb; Sinha, Baerbel; Sinha, Vinayak; Steiner, Allison L.; Sharma, Sumit
We investigate the impact of adoption of electric vehicles and cleaner fuels on future surface levels of PM2.5 and ozone over Delhi for two contrasting seasons, pre-monsoon and post-monsoon. We run the WRF-Chem atmospheric transport model at high resolution (4 km) with two transport emission scenarios for year 2030: (1) a scenario with electrification of two- and three-wheelers and light commercial vehicles, and (2) a scenario which also includes conversion of diesel vehicles to compressed natural gas (CNG). Compared to the baseline values in 2019, the scenario with both electrification and conversion of diesel vehicles to CNG has a greater reduction in PM2.5 concentrations (up to 5%) than the electrification of two- and three-wheelers and light commercial vehicles alone (within 1%), mainly due to the the greater reduction in primary emissions of PM2.5 and black carbon from diesel conversion to CNG. Vehicles electrification could result in an increase in the daily maximum 8-hours ozone concentrations, which are partially offset by additionally converting to CNG—by ?1.9% and +2.4% during pre-monsoon and post-monsoon seasons. This reflects higher NOx emissions from the CNG vehicle scenario compared to electrification-alone scenario, which limits the increase of surface ozone in the VOC-limited chemical environment over Delhi. Our findings highlight the importance of a coordinated strategy for PM2.5 and ozone when considering traffic emission controls, and highlight that the transition to electric vehicles should be accompanied by the conversion of diesel vehicles to CNG to limit surface ozone increase and achieve greater reduction in PM2.5 concentrations over Delhi. However, the small changes in PM2.5 and in ozone compared to the baseline scenario highlight the importance of joint emissions reduction from other sectors to achieve substantial progress in PM2.5 and ozone air quality in Delhi.
From Column to Surface: Connecting the Performance in Simulating Aerosol Optical Properties and PM2.5 Concentrations in the NASA GEOS-CCM Model
(NTRS, 2024-12) Mogno, Caterina; Colarco, Peter R.; Collow, Allison; Strode, Sarah A.; Valenti, Vanessa; Liang, Qing; Oman, Luke; Knowland, K. Emma
Evaluating spectral cloud effective radius retrievals from the Enhanced MODIS Airborne Simulator (eMAS) during ORACLES
(EGU, 2025-02-27) Meyer, Kerry; Platnick, Steven; Arnold, G. Thomas; Amarasinghe, Nandana; Miller, Daniel J.; Small-Griswold, Jennifer; Witte, Mikael; Cairns, Brian; Gupta, Siddhant; McFarquhar, Greg; O'Brien, Joseph
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.
A Diagnosis of Oceanic Precipitation in IMERG-GMI
(AMS, 2025-03-06) Watters, Daniel C.; Huffman, George J.; Gatlin, Patrick N.; Kirstetter, Pierre-Emmanuel; Bolvin, David T.; Joyce, Robert; Nelkin, Eric J.; Tan, Jackson; Wolff, David B.
Diagnosing errors in spaceborne oceanic precipitation estimates is difficult due tocomplicated multi-satellite algorithms and limited surface-based measurements. The Global Precipitation Measurement (GPM) mission helps to alleviate these challenges with NASA’s Integrated Multi-satellitE Retrievals for GPM (IMERG) product, which is transparently designed to encourage community validation activities, and the GPM Validation Network, which collects observations across global precipitation regimes from over 100 ground-based weather radars to serve as reference datasets for the GPM precipitation products. This study uses the GPM Validation Network’s oceanic precipitation observations from 32 island and coastal radars to diagnose the performance of IMERG V06B & V07B Final Run products during GPM Microwave Imager (GMI) overpasses (i.e., IMERG-GMI) in the period June 2014 – September 2021. Errors are traced from the input Level-2 (satellite footprint) Goddard Profiling Algorithm climate (GPROF-CLIM) GMI product through the successive gridding, calibration and precipitation distribution restoration steps of IMERG’s Level-3 (gridded) algorithm. Results highlight that IMERG-GMI V07B outperforms V06B in detecting and quantifying oceanic precipitation, with a significant improvement over high-latitude ocean (V06B: +143%; V07B: +50%). Furthermore, there is a clear oceanic latitudinal trend in the mean relative bias of IMERG-GMI V07B (high-latitude: +50%; mid-latitude: +10%; tropical: -41%), which largely traces back to GPROF-CLIM V07 (high-latitude: +22%; mid-latitude: -8%; tropical: -44%), with bias differences driven by IMERG’s passive microwave calibration scheme. This error tracing approach supports future IMERG algorithm developments by disentangling how algorithm steps enhance or mitigate errors.
Dynamic Impact of the Southern Annular Mode on the Antarctic Ozone Hole Area
(MDPI, 2025-02-27) Lee, Jae N.; Wu, Dong L.
This study investigates the impact of dynamic variability of the Southern Hemisphere (SH) polar middle atmosphere on the ozone hole area. We analyze the influence of the southern annular mode (SAM) and planetary waves (PWs) on ozone depletion from 19 years (2005–2023) of aura microwave limb sounder (MLS) geopotential height (GPH) measurements. We employ empirical orthogonal function (EOF) analysis to decompose the GPH variability into distinct spatial patterns. EOF analysis reveals a strong relationship between the first EOF (representing the SAM) and the Antarctic ozone hole area (γ = 0.91). A significant negative lag correlation between the August principal component of the second EOF (PC2) and the September SAM index (γ = -0.76) suggests that lower stratospheric wave activity in August can precondition the polar vortex strength in September. The minor sudden stratospheric warming (SSW) event in 2019 is an example of how strong wave activity can disrupt the polar vortex, leading to significant temperature anomalies and reduced ozone depletion. The coupling of PWs is evident in the lag correlation analysis between different altitudes. A “bottom-up” propagation of PWs from the lower stratosphere to the mesosphere and a potential “top-down” influence from the mesosphere to the lower stratosphere are observed with time lags of 21–30 days. These findings highlight the complex dynamics of PW propagation and their potential impact on the SAM and ozone layer. Further analysis of these correlations could improve one-month lead predictions of the SAM and the ozone hole area.
A comparison of the meridional meandering of extratropical precipitation during boreal winter: eddy momentum flux versus Eulerian storm tracks
(Springer Nature, 2025-03-13) Yoo, Changhyun; Jin, Daeho; Lee, Sukyoung; Kim, Daehyun
The latitudinal distribution of winter extratropical precipitation is often regarded as being determined by the location and intensity of the storm track. Here, we compare the precipitation variability associated with the meridional eddy momentum flux (EMF) with that associated with an Eulerian storm track measure. Observations show that when the midlatitude EMF is anomalously poleward, the occurrence of moderate-to-heavy precipitation (1–33 mm day⁻¹) increases between 45°N and 70°N, while decreasing between 25°N and 45°N. This shift occurs mostly downstream of the climatological storm track maximum, with generally greater precipitation anomalies compared to those associated with storm track changes. The shift is tied to changes in horizontal moisture transport primarily by planetary scale waves. These results suggest that, in addition to the storm track intensity, dynamics of the horizontal wave tilts which affect the EMF intensity need to be considered when projecting future changes in precipitation variability.
Developing Advanced Cloud Retrievals for PACE: Building a Joint Spectro-Polarimetric Cloud Microphysics Retrieval
(NASA, 2024-12) Miller, Daniel J.; Meyer, Kerry; Platnick, Steven E.; Zhang, Zhibo; Ademakinwa, Adeleke; Sinclair, Kenneth; Alexandrov, Mikhail; Geogdzhayev, Igor; van Diedenhoven, Bastiaan
Developing a Lagrangian Frame Transformation on Satellite Data to Study Cloud Microphysical Transitions in Arctic Marine Cold Air Outbreaks
(2025-03-13) Seppala, Hannah; Zhang, Zhibo; Zheng, Xue
Arctic marine cold air outbreaks (CAOs) generate distinct and dynamic cloud regimes due to intense air-sea interactions. To understand the temporal evolution of CAO cloud properties and compare different CAO events, a Lagrangian perspective is particularly useful. We developed a novel technique that enables the conversion of inherently Eulerian satellite data into a Lagrangian framework, combining the broad spatiotemporal coverage of satellite observations with the advantages of Lagrangian tracking. This technique was applied to eight CAO cases associated with a recent field campaign. Our results reveal a striking contrast among the cases in terms of cloud-top phase transitions, providing new insights into the evolution of CAO cloud properties.
Correlation to Causation: A Causal Deep Learning Framework for Arctic Sea Ice Prediction
(2025-03-03) Hossain, Emam; Ferdous, Muhammad Hasan; Wang, Jianwu; Subramanian, Aneesh; Gani, Md Osman
Traditional machine learning and deep learning techniques rely on correlation-based learning, often failing to distinguish spurious associations from true causal relationships, which limits robustness, interpretability, and generalizability. To address these challenges, we propose a causality-driven deep learning framework that integrates Multivariate Granger Causality (MVGC) and PCMCI+ causal discovery algorithms with a hybrid deep learning architecture. Using 43 years (1979-2021) of daily and monthly Arctic Sea Ice Extent (SIE) and ocean-atmospheric datasets, our approach identifies causally significant factors, prioritizes features with direct influence, reduces feature overhead, and improves computational efficiency. Experiments demonstrate that integrating causal features enhances the deep learning model's predictive accuracy and interpretability across multiple lead times. Beyond SIE prediction, the proposed framework offers a scalable solution for dynamic, high-dimensional systems, advancing both theoretical understanding and practical applications in predictive modeling.
Conducting an online STEAM-themed treasure hunt event during the COVID-19 pandemic
(Xjenza, 2024) Lynch, C.; Gargiulo, M. V.; Mogno, Caterina; Oyewale, O. A.; Roblas, M. I. C.; Duca, E.
The in-person Malta-based STEAM Summer School intensive science communication course was transformed into the STEAM Digital School due to COVID-19 pandemic restrictions. Still retaining real world features, the course managed to incorporate individuals from three different continents to learn and work together simultaneously. Upon completion of the course, the students organised an online event during worldwide stay-at-home restrictions to stimulate excitement among youth about scientific topics; in this case, communication within nature. The organisers developed an online treasure hunt for teenagers, a novel format for online learning. The game involved solving puzzles with a science theme through an online platform. Through this medium, the participants were exposed to scientific ideas such as quantum waves, and how a microwave works, in order to increase their possible interest in the area. The organisers aimed to encourage the participants to develop an interest in science and research within society, against the backdrop of the COVID-19 pandemic. The event was evaluated to assess the impact on the participants and organisers, and the results indicated the event was generally enjoyed by the participants, though some puzzle difficulties were perhaps too high for those in the targeted age bracket of 16 19-year-olds. Further suggestions for the improvement of the online intensive course and this event format are discussed within the report. We found the event format to be an overall success, with all participants indicating an increased interest in science as a result.
Towards the Harmonization of Nitrate Aerosol Simulations within the NASA Goddard Earth Observing System (GEOS) Model
(NTRS, 2024-10) Mogno, Caterina; Colarco, Peter R.; Bian, Huisheng; Strode, Sarah A.; Collow, Allison; Valenti, Vanessa; Liang, Qing
The Impact of Assimilating Large Volumes of GNSS Radio Occultation Observations from Spire’s Commercial Constellation into NASA’s GEOS
(NTRS, 2024-01-30) Murphy, Michael; Chattopadhyay, Mohar; Akkraoui, Amal El; Damon, Megan R.
The upcoming retrospective analysis for the 21st century (R21C) reanalysis product from NASA will include the full dataset of GNSS Radio Occultation (RO) observations collected by Spire with their constellation of smallsats. The Spire RO dataset, which was purchased by NASA for its Commercial Smallsat Data Acquisition (CSDA) archive, has global coverage and includes approximately 6 thousand RO profiles per day during 2019 increasing to nearly 20 thousand in 2022-2023. This more than doubles the volume of RO profiles from all other routinely assimilated RO missions combined during 2023. The increase in the number of RO profiles available is particularly important in the extratropics as the next largest RO constellation, the state-of-the-science Formosa Satellite Mission 7 (FORMOSAT-7)/Constellation Observing System for Meteorology, Ionosphere and Climate (COSMIC-2) mission (hereafter COSMIC-2), is focused on the Tropics and only provides approximately 4 thousand RO profiles per day. The large number of observations in the Spire RO dataset have great potential to improve analyses and forecasts of the Earth’s atmosphere produced by numerical weather prediction systems. Their impact is assessed through numerical experiments using NASA’s Global Earth Observing System (GEOS) Atmospheric Data Assimilation System (ADAS) with and without the observations from the COSMIC-2 mission. The ability of the Spire RO observations to make up for the omission of the RO observations from COSMIC-2 is directly assessed over the tropics and the impact of Spire over the extratropics is compared to that of the available RO missions that sample over this region. Finally, the quality of the Spire RO observations is compared to that of the routinely assimilated RO missions using Forecast Sensitivity-based Observation Impact (FSOI).
Satellite remote sensing for environmental sustainable development goals: A review of applications for terrestrial and marine protected areas
(Elsevier, 2025-01-01) McCarthy, Matthew J.; Herrero, Hannah V.; Insalaco, Stephanie A.; Hinten, Melissa T.; Anyamba, Assaf
With few years left to achieve the vital United Nations Sustainable Development Goals (SDGs), member nations must urgently leverage technological advancements in environmental monitoring to succeed. Remote sensing now provides decades of global observations at a variety of spatio-temporal scales and a litany of data products to guide comprehensive measures for climate action, and aquatic and terrestrial biota preservation. Protected areas, such as national parks and wildlife preserves, represent largely untapped resources for both applying robust conservation measures and testing ambitious new approaches to sustainable development that could jumpstart the much-needed adoption of strategies to efficiently pursue global sustainability. This review summarizes recent demonstrated utilities of remotely sensed data applied to protected areas for research related to SDG goals 13, 14, and 15: “Climate Action”, “Life below Water”, and “Life on Land”. We identify successful uses of such data for each SDG, identify areas for improvement, and provide recommendations from the literature on how to expand what others have done to achieve lofty goals with global impact. We demonstrate that remote sensing provides a valuable tool for achieving SDGs as it facilitates monitoring vegetation health, water quality and condition, and climate variables at large spatial and fine temporal scales, while also evaluating the effectiveness of management and conservation practices. Issues remain, however, in that there is currently no reference from which to relate goal progress to human livelihoods. The current relationship between remotely sensed indices and ecological services that determine sustainable development omit steps that would establish this connection.
PLANT DISEASE DETECTION TECHNOLOGY ASSESSMENT
(ORNL, 2024-04) Graham, David E.; Anyamba, Assaf; Davison, Brian H.; Martin, Stanton; Petoskey, Bill J.; Rush, Tomás A.; Weston, David J.; Yang, Xiaohan
Widespread Expansion of Salt Marsh Pools Observed on Maine Marshes Since 2009
(WIley, 2025-02-25) DeWater, K.; Kochtitzky, W.; Ellis, R.; Merrill, P.; Pittsley, M.; Morgan, P.; Burns, C.; Campbell, Anthony D.; Adamowicz, S.
Salt marshes provide critical habitats, protect coastal infrastructure, and are increasingly exposed to sea level rise, with many having a history of agricultural use and ditching over the centuries. Pool area coverage can be considered an indicator of marsh health but is rarely quantified. In this study, we digitized marsh pools using aerial imagery to quantify changes in pool area and density on 12 salt marshes in Maine from 2009 to 2021 as a case study of marsh response to environmental changes. We categorized pools into three types: mega-pools, individual pools, and perimeter pools, based on morphology and examined whether pools remained singular, split, or combined. We found a 15.7% increase in pool area from 2009 to 2021 on all marshes, primarily driven by mega-pool expansion, whereas individual and perimeter pools remained relatively constant. The rate of pool expansion across all marshes was 49,000 m2 a−1 with mean mega-pool size 6,400 ± 400 m2. There was an increase in pool count per km2 on all marshes except for the York River marsh, which still experienced area expansion. Pools primarily increase in cover through merging or being engulfed by mega-pools. Area cover change was not substantial when pools remained singular, split into many pools, or were only present in 2009 or 2021. Mega-pools were larger on lower marsh elevations and expanded at a greater rate when overlapping ditches, suggesting influence by sea level rise and historic agriculture. Marsh restoration projects that promote the drainage and re-vegetation of mega-pools may reverse this trend.
Evaluating and Comparing Dust Emission Schemes within the NASA GEOS Model
(NTRS, 2025-01-15) Joshi, Janak R.; Silva, Arlindo da; Colarco, Peter; Darmenov, Anton; Ginoux, Paul; Kok, Jasper; Collow, Allison; Nowottnick, Edward

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