Search Results (808)

This study examines diurnal surface temperature dynamics across major Moroccan cities during the growing season and explores the interaction between urban and vegetated surfaces. We also introduce the Urban Thermal Impact Ratio (UTIR), a novel metric designed to quantify urban thermal comfort as a function of the surface urban heat island (SUHI) intensity. The analysis is based on outputs from a land surface model (LSM) for the year 2010, integrating high-resolution Landsat and MODIS data to characterize land cover and biophysical parameters across twelve land cover types. Our findings reveal moderate urban–vegetation temperature differences in coastal cities like Tangier (1.8 °C) and Rabat (1.0 °C), where winter vegetation remains active. In inland areas, urban morphology plays a more dominant role: Fes, with a 20% impervious surface area (ISA), exhibits a smaller SUHI than Meknes (5% ISA), due to higher urban heating in the latter. The Atlantic desert city of Dakhla shows a distinct pattern, with a nighttime SUHI of 2.1 °C and a daytime urban cooling of −0.7 °C, driven by irrigated parks and lawns enhancing evapotranspiration and shading. At the regional scale, summer UTIR values remain below one in Tangier-Tetouan-Al Hoceima, Rabat-Sale-Kenitra, and Casablanca-Settat, suggesting that urban conditions generally stay within thermal comfort thresholds. In contrast, higher UTIR values in Marrakech-Safi, Beni Mellal-Khénifra, and Guelmim-Oued Noun indicate elevated heat discomfort. At the city scale, the UTIR in Tangier, Rabat, and Casablanca demonstrates a clear diurnal pattern: it emerges around 11:00 a.m., peaks at 1:00 p.m., and fades by 3:00 p.m. This study highlights the critical role of vegetation in regulating urban surface temperatures and modulating urban–rural thermal contrasts. The UTIR provides a practical, scalable indicator of urban heat stress, particularly valuable in data-scarce settings. These findings carry significant implications for climate-resilient urban planning, optimized energy use, and the design of public health early warning systems in the context of climate change. Full article

ComPair, a prototype of the All-sky Medium Energy Gamma-ray Observatory (AMEGO), completed a short-duration high-altitude balloon campaign on 27 August 2023 from Fort Sumner, New Mexico, USA. The goal of the balloon flight was to demonstrate ComPair as both a Compton and Pair telescope in flight, reject the charged particle background, and measure the background $\gamma$-ray spectrum. This analysis compares measurements from the balloon flight with Monte Carlo simulations to benchmark the instrument. The comparison finds good agreement between the measurements and simulations and supports the conclusion that ComPair accomplished its goals for the balloon campaign. Additionally, two charged particle background rejection schemes are discussed: a soft ACD veto that records a higher charged particle event rate but with less risk of event loss, and a hard ACD veto that limits the charged particle event rate on board. There was little difference in the measured spectra from the soft and hard ACD veto schemes, indicating that the hard ACD veto could be used for future flights. The successes of ComPair’s engineering flight will inform the development of the next generation of ComPair with upgraded detector technology and larger active area. Full article

Background: Caregiving can be a challenging experience, particularly for caregivers of people with Parkinson’s disease, given the array of motor and neuropsychiatric symptoms. Elevated care tasks and demands related to these symptoms may result in greater care burden, heightened caregiving-related strain, and, in turn, poorer health for Parkinson’s disease (PD) caregivers compared to non-PD caregivers. Guided by the Stress Process Model, the purpose of this study was to explore the pathways connecting PD caregiving and caregiver health, with attention to the role of care burden and caregiving-related strain. Methods: We applied path analysis in a structural equation modeling framework to data from 3116 PD and non-PD caregivers participating in the National Alliance for Caregiving and AARP’s Caregiving in the U.S. 2015 and 2020 surveys. We estimated pathways between PD caregiving, care burden, caregiving-related strain (i.e., emotional, physical, and financial), and caregiver self-reported health simultaneously, then decomposed these pathways into total, indirect, and direct effects. Results: Findings show PD caregiving is indirectly linked to poorer health among caregivers through increased care burden and heightened caregiving-related strain, with additional path analysis models pointing to physical strain as an important component of caregiving-related strain in mediating the associations between PD caregiving and overall health. Conclusions: Our findings suggest a need to be especially attentive to the accumulation of care burden and caregiving-related strain—particularly physical strain—among PD caregivers, given the potential consequences for caregiver health. Solutions are needed, such as caregiver screening and caregiver-specific care plans, to better support reductions in burden and strain among PD caregivers, thereby promoting their overall health. Full article

We revisit 77 relaxed (extra)solar multibody (sub)systems containing 2–9 bodies orbiting about gravitationally dominant central bodies. The listings are complete down to (sub)systems with 5 orbiting bodies and additionally contain 33 smaller systems with 2–4 orbiting bodies. Most of the multiplanet systems (68) have been observed outside of our solar system, and very few of them (5) exhibit classical Laplace resonances (LRs). The remaining 9 subsystems have been found in our solar system; they include 7 well-known satellite groups in addition to the four gaseous giant planets and the four terrestrial planets, and they exhibit only one classical Laplace resonant chain, the famous Galilean LR. The orbiting bodies (planets, dwarfs, or satellites) appear to be locked in/near global mean-motion resonances (MMRs), as these are determined in reference to the orbital period of the most massive (most inert) body in each (sub)system. We present a library of these 77 multibody subsystems for future use and reference. The library listings of dynamical properties also include regular spacings of the orbital semimajor axes. Regularities in the spatial configurations of the bodies were determined from patterns that had existed in the mean tidal field that drove multibody migrations toward MMRs, well before the tidal field was erased by the process of `gravitational Landau damping’ which concluded its work when all major bodies had finally settled in/near the global MMRs presently observed. Finally, detailed comparisons of results help us discern the longest commonly-occurring MMR chains, distinguish the most important groups of triple MMRs, and identify a new criterion for the absence of librations in triple MMRs. Full article

Monitoring chlorophyll-a concentration (Chl-a) is essential for assessing aquatic ecosystem health, yet its retrieval using remote sensing remains challenging in turbid coastal waters because of the intricate optical characteristics of these environments. Elevated levels of colored (chromophoric) dissolved organic matter (CDOM) and suspended sediments (aka total suspended solids, TSS) interfere with satellite-based Chl-a estimates, necessitating alternative approaches. One potential solution is machine learning, indirectly including non-Chl-a signals into the models. In this research, we develop machine learning models to predict Chl-a concentrations in the Chesapeake Bay, one of the largest estuaries on North America’s East Coast. Our approach leverages the Extra-Trees (ET) algorithm, a tree-based ensemble method that offers predictive accuracy comparable to that of other ensemble models, while significantly improving computational efficiency. Using the entire ocean color datasets acquired by the satellite sensors MODIS-Aqua (>20 years) and VIIRS-SNPP (>10 years), we generated long-term Chl-a estimates covering the entire Chesapeake Bay area. The models achieve a multiplicative absolute error of approximately 1.40, demonstrating reliable performance. The predicted spatiotemporal Chl-a patterns align with known ecological processes in the Chesapeake Bay, particularly those influenced by riverine inputs and seasonal variability. This research emphasizes the potential of machine learning to enhance satellite-based water quality monitoring in optically complex coastal waters, providing valuable insights for ecosystem management and conservation. Full article

The Joint Polar Satellite System (JPSS) is a collaborative program between NASA and NOAA to provide scientific measurements from multiple polar-orbiting satellites. The development, testing, launch, and operation of the satellites is jointly overseen by NASA and NOAA, with NASA responsible for developing and building instruments, spacecraft, ground systems, and launching into orbit. While three VIIRS instruments are currently on-orbit, spacecraft integration of the two VIIRS instruments planned for launch on the JPSS-3 and -4 spacecraft is ongoing. The latest build in the series, set to be launched on the JPSS-4 platform, recently completed its main ground calibration program at the vendor facility. This program covered a comprehensive series of performance metrics designed to ensure that the instrument can maintain its calibration successfully on-orbit. In this paper, we present the results from the radiometric calibration process, which includes metrics such as dynamic range, signal-to-noise ratio, noise equivalent differential temperature, polarization sensitivity, scattered light response, relative spectral response, response versus scan angle, and crosstalk. All key metrics have met or exceeded their design requirements, with some minor exceptions. Also included are comparisons with previous VIIRS instruments, as well as a description of their expected performance once on-orbit. Full article

Aerosols considerably reduce the upwelling radiance in the thermal infrared (IR) window; thus, it is worthwhile to understand the effects and challenges of assimilating aerosol-affected (i.e., hazy-sky) IR observations for all-sky data assimilation (DA). This study introduces an aerosol-aware DA framework for the Infrared Atmospheric Sounder Interferometer (IASI) to exploit hazy-sky IR observations and investigate the impact of assimilating hazy-sky IR observations on analyses and subsequent forecasts. The DA framework consists of the detection of hazy-sky pixels and an observation error model as the function of the aerosol effect. Compared to the baseline experiment, the experiment utilized an aerosol-aware framework that reduces biases in the sea surface temperature in the tropical region, particularly over the areas affected by heavy dust plumes. There are no significant differences in the evaluation of the analyses and the 7-day forecasts between the experiments. To further improve the aerosol-aware framework, the enhancements in quality control (e.g., aerosol detection) and bias correction need to be addressed in the future. Full article

Blowing snow is a common phenomenon over the Antarctic ice sheet and sea ice regions, playing a crucial role in the Antarctic climate system. Previous research developed an optimized machine learning (ML) model to diagnose blowing snow occurrence using meteorological fields from the Modern-Era Retrospective Analysis for Research and Applications, Version 2 (MERRA-2). This paper extends that work by optimizing an ML model to estimate blowing snow height and optical depth for operational data production. Observations from the Cloud–Aerosol Lidar and Infrared Pathfinder Satellite Observation (CALIPSO) serve as ground truth for training. The optimization process involves selecting relevant input features and identifying the most effective ML regressor. As a result, 21 MERRA-2 fields were identified as key input features, and Extreme Gradient Boosting emerged as the most effective regressor. Feature importance analysis highlights wind components and surface pressure as the most significant predictors for blowing snow height and optical depth. Individual models were developed for each month. Using 10 years of CALIPSO data (2007–2016) for training, these optimized models can be applied across the full MERRA-2 dataset, spanning from 1980 to the present. This enables the generation of hourly blowing snow height and optical depth data on the MERRA-2 grid for the entire MERRA-2 time span. Full article

The impact of stratospheric aerosols on Earth’s climate, particularly through atmospheric heating and ozone depletion, remains a critical area of atmospheric research. While satellite data provide valuable insights, independent validation methods are necessary for ensuring accuracy. Twilight near-infrared (NIR) radiometry offers a promising approach for investigating aerosol properties, such as optical depth and layer height, at high altitudes. This study aims to evaluate the effectiveness of twilight radiometry in corroborating satellite data and assessing aerosol characteristics. Two methods based on twilight radiometry—the color ratio and the derivative method—are employed to derive the aerosol layer height and optical depth. Radiances at 450, 550, 762, 775, and 1050 nm wavelengths are analyzed at varying solar zenith angles, using zenith viewing geometry for consistency. Comparisons of aerosol optical depths (AODs) between Research Pandora (ResPan) and AErosol RObotic NETwork (AERONET) data (R = 0.99) and between ResPan and Modern-Era Retrospective analysis for Research and Applications (MERRA-2) data (R = 0.86) demonstrate a strong correlation. Twilight ResPan data are also used to estimate the aerosol layer height, with results in good agreement with SAGE and lidar measurements, particularly following the Hunga Tonga eruption in Lauder, New Zealand. The simulation database, created using the libRadtran DISORT and Monte Carlo packages for daylight and twilight calculations, is capable of detecting AODs as low as 10⁻³ using the derivative method. This work highlights the potential of twilight radiometry as a simple, cost-effective tool for atmospheric research and satellite data validation, offering valuable insights into aerosol dynamics at stratospheric altitudes. Full article

Morocco, like many nations undergoing significant economic and social transformation, is experiencing rapid urbanization alongside an ongoing rural exodus. This, coupled with the country’s diverse climate and heterogeneous geography, warrants a detailed exploration of urbanization’s effect on surface climate. Utilizing the Simple Biosphere (SiB2) model’s simulated surface temperature, this study analyses summer’s urban heat structure of seven Moroccan urban areas and their surroundings, assessing the urban impact on surface temperature at the city center, and the intensity and spatial distribution of the urban heat island (UHI) effect at different spatial resolutions. Results show wide-ranging dissimilarities in urban thermal profiles, with the maximum UHI intensity recorded at 8.7 °C in the Dakhla peninsula. Urban heat sink (UHS) effects were observed in six of the seven studied cities, with Marrakech being the exception, only exhibiting UHI effects. A more detailed examination of the thermal profile in Rabat’s metropole at a finer scale, using Landsat-observed land surface temperature (LST), yields additional insights into UHI characteristics, and the findings are contrasted with the existing literature to provide broader insights. The implications of this study strongly resonate within the Moroccan context and its neighboring regions with similar environmental and socio-economic features and should aid in the development of sustainable regional urban planning. Full article

Timberline marks the transitions from continuous forests to sparse forests and tundra landscapes. As the spatial distribution and dynamics of timberline are closely associated with regional energy and carbon balance, mapping timberline is important to a wide range of environmental and ecological studies. However, current timberline delineation approaches remain under-developed. We proposed an automatic timberline delineation method based on a seeded region-growing segmentation technique and satellite-derived products of tree fractional cover. We applied our approach to the West Siberian Plain and Alaska treeline regions as defined by the Circumpolar Arctic Vegetation Map. The results demonstrate the effectiveness of the proposed method for the accurate delineation of the timberlines that spatially align well with very-high-resolution satellite images. Based on the delineated timberlines, we find regional-scale tree encroachment to be not as substantial as previously reported. The proposed approach can be applied to understanding climate-induced forest responses and inform forest management practices. Full article

Satellite observations provide broad spatial coverage of complex coastal environments but may lack temporal resolution to capture rapid changes in these dynamic systems. This study explores the potential of the recently installed NASA Aerosol Robotic Network Ocean Color (AERONET-OC) in the Chesapeake Bay, USA, both for comparison with satellite remote sensing and to complement the satellite observations by filling temporal gaps at a fixed site. Using AERONET-OC’s effectiveness as a validation tool through comparisons with multi- and hyperspectral satellites, we find agreement between AERONET-OC and satellite remote sensing reflectance measurements in the Chesapeake Bay. We use AERONET-OC to estimate total suspended matter transport through the upper bay, revealing a 3-day lag of sediment plume transport from riverine discharge to the AERONET-OC site. During the 2023 Canadian wildfire smoke episode, AERONET-OC aerosol optical depth measurements in the Chesapeake Bay agree with satellite products while capturing diurnal variations that are not observable through daily satellite passes. This study demonstrates the potential of continuous in situ monitoring by AERONET-OC to complement satellite observations with higher frequency, important for capturing extreme events that may be missed by daily satellite overpass or are less frequent when cloudy. Full article

Understanding building energy demand is critical for addressing climate uncertainty challenges and ensuring sustainable urban growth. This study develops a building energy demand (BED) model to explore how climate variation and urban expansion affect residential and commercial space heating and cooling demands in Morocco for three scenarios, namely, 2005, 2018, and 2018 + 1.5 °C. The results show that coastal cities have lower heating and cooling needs due to the oceanic influence, while interior cities require significantly higher heating demand per-unit-floorspace. Between 2005 and 2018, urban growth increased total heating and cooling demand by 218.8 GWh, particularly in northern and coastal regions, despite per-unit-floorspace reductions in milder climates and improved building efficiency in 2018. Residential heating remains the dominant energy use, though commercial demand is significant in urban centers. Under the 2018 + 1.5 °C hypothetical scenario, heating demand across Morocco declines by 335.8 GWh compared to 2018, with urban areas amplifying this trend. Meanwhile, cooling demand increases slightly by 44.4 GWh, with major cities experiencing relative increases of up to 50%. These findings highlight a trade-off where reduced winter heating needs are partly offset by increased summer cooling demands in densely urbanized areas. The study identifies key urban hotspots for targeted interventions, emphasizing the need for energy-efficient building designs, climate-adaptive urban planning, and resilient energy management strategies to sustainably address shifting seasonal energy patterns. Full article

Biomass burning (BB) aerosols are the largest source of absorbing aerosols on Earth. Coupled with marine stratocumulus clouds (MSC), their radiative effects are enhanced and can cause cloud property changes (first indirect effect) or cloud burn-off and warm up the atmospheric column (semi-direct effect). Nevertheless, the derivation of their quantity and optical properties in the presence of MSC clouds is confounded by the uncertainties in the retrieval of the underlying cloud properties. Therefore, a robust methodology is needed for the coupled retrievals of absorbing aerosol above clouds. Here, we present a new retrieval approach implemented for a Spectro radiometric multi-angle polarimetric airborne platform, the research scanning polarimeter (RSP), during the ORACLES campaign over the Southeast Atlantic Ocean. Our approach transforms the 1D measurements over multiple angles and wavelengths into a 3D image-like input, which is then processed using various deep learning (DL) schemes to yield aerosol single scattering albedos (SSAs), aerosol optical depths (AODs), aerosol effective radii, and aerosol complex refractive indices, together with cloud optical depths (CODs), cloud effective radii and variances. We present a comparison between the different DL approaches, as well as their comparison to existing algorithms. We discover that the Vision Transformer (ViT) scheme, traditionally used by natural language models, is superior to the ResNet convolutional Neural-Network (CNN) approach. We show good validation statistics on synthetic and real airborne data and discuss paths forward for making this approach flexible and readily applicable over multiple platforms. Full article

This paper introduces a method of monitoring infrared channel calibration stability through direct comparison of calibrated radiances by two Advanced Baseline Imager (ABI) on two geostationary (GEO) platforms. This GEO-GEO comparison is based on radiances in the overlapping area observed by the two ABIs, pixel by pixel, at approximately the same time, location, spectrum, and viewing zenith angle. It was initially developed for GOES-17 and subsequent GOES missions to validate the ABI’s calibration around its local midnight—a subject of particular interest for instruments on three-axis stabilized geostationary satellites. With the cryocooler anomaly of the GOES-17 ABI, however, the GEO-GEO comparison became an indispensable tool to characterize GOES-17 ABI infrared (IR) channel calibration with high frequency, low uncertainty, and in near real time, providing critical feedback to root cause investigation and mitigation options. Later, the GEO-GEO comparison was applied to the GOES-18 ABI as originally intended and was proved successful. It confirms that, with few exceptions, radiometric calibration for all ABIs is stable to within 0.1 K when the radiance fluctuation is converted to the brightness temperature at 300 K. Full article