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Human–wildlife conflict studies of high‐altitude areas are rare due to budget constraints and the challenging nature of research in these remote environments. This study investigates the prevalence and increasing trend of human–wildlife conflict (HWC) in the mountainous Gaurishankar Conservation Area (GCA) of Nepal, with a specific focus on leopard (Panthera pardus) and Himalayan black bear (Ursus thibetanus laniger). The study analyzes a decade of HWC reports and identifies goats as the livestock most targeted by leopards. The Dolakha district of GCA received the highest number of reports, highlighting the need for mitigation measures in the area. In GCA, livestock attacks accounted for 85% of compensation, with the remaining 15% for human injuries. We estimate that the number of reported wildlife attacks grew on average by 33% per year, with an additional increase of 57 reports per year following the implementation of a new compensation policy during BS 2076 (2019 AD). While bear attacks showed no significant change post‐rule alteration, leopard attack reports surged from 1 to 60 annually, indicating improved compensation may have resulted in increased leopard‐attack reporting rates. The findings emphasize the economic impact of HWC on local communities and suggest strategies such as increasing prey populations, promoting community education and awareness, enhancing alternative livelihood options, developing community‐based insurance programs, and implementing secure enclosures (corrals) to minimize conflicts and foster harmonious coexistence. This research addresses a knowledge gap in HWC in high‐altitude conservation areas like the GCA, providing valuable insights for conservation stakeholders and contributing to biodiversity conservation and the well‐being of humans and wildlife. Recent policy changes have reduced hurdles to receiving compensation for wildlife attacks on people and livestock within the mountainous Gaurishankar Conservation Area of the Himalayas. We show that over the last decade, the number of reported attacks have increased by approximately 33% per year, after accounting for the boost in reporting due to improved compensation. The reported number of injuries by Himalayan black bears was overshadowed by a rise in reports of leopard predation on livestock, particularly goats, an important source of income for local farmers.

Volcanic ash can interact with the earth system on many temporal and spatial scales and is a significant hazard to aircraft. In the event of a volcanic eruption, fast and robust decisions need to be made by aviation authorities about which routes are safe to operate. Such decisions take into account forecasts of ash location issued by Volcanic Ash Advisory Centers (VAACs) which are informed by simulations from Volcanic Ash Transport and Dispersion (VATD) models. The estimation of the time-evolving vertical distribution of ash emissions for use in VATD simulations in real time is difficult which can lead to large uncertainty in these forecasts. This study presents a method for constraining the ash emission estimates by combining an inversion modeling technique with an ensemble of meteorological forecasts, resulting in an ensemble of ash emission estimates. These estimates of ash emissions can be used to produce a robust ash forecast consistent with observations. This new ensemble approach is applied to the 2011 eruption of the Icelandic volcano Grímsvötn. The resulting emission profiles each have a similar temporal evolution but there are differences in the magnitude of ash emitted at different heights. For this eruption, the impact of precipitation uncertainty (and the associated wet deposition of ash) on the estimate of the total amount of ash emitted is larger than the impact of the uncertainty in the wind fields. Despite the differences that are dominated by wet deposition uncertainty, the ensemble inversion provides confidence that the reduction of the unconstrained emissions (a priori), particularly above 4 km, is robust across all members. In this case, the use of posterior emission profiles greatly reduces the magnitude and extent of the forecast ash cloud. The ensemble of posterior emission profiles gives a range of ash column loadings much closer in agreement with a set of independent satellite retrievals in comparison to the a priori emissions. Furthermore, airspace containing volcanic ash concentrations deemed to be associated with the highest risk (likelihood of exceeding a high concentration threshold) to aviation are reduced by over 85%. Such improvements could have large implications in emergency response situations. Future research will focus on quantifying the impact of uncertainty in precipitation forecasts on wet deposition in other eruptions and developing an inversion system that makes use of the state-of-the-art meteorological ensembles which has the potential to be used in an operational setting.

This study estimates the radiative forcing by biomass burning and dust aerosols over the Indian subcontinent, with emphasis on the Indo-Gangetic Plains (IGP) during the period from January 2021 to April 2021, based on multiple satellite and reanalysis datasets. In this respect, we used retrievals from the Moderate Resolution Spectroradiometer (MODIS) and the Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observation (CALIPSO) system, as well as reanalysis data from the Goddard Earth Observing System, version 5 (GEOS-5), the Modern-Era Retrospective analysis for Research and Applications, version 2 (MERRA-2), the Copernicus Atmosphere Monitoring Service (CAMS), and ERA-Interim. According to the MERRA-2 and the CAMS, the highest black carbon (BC) concentrations in January 2021 were 7–8 µg m−3, which were significantly lower than measurements performed in main cities along the IGP, such as Patiala, Delhi, and Kanpur. The meteorological data analysis accompanied by the CALIPSO lidar measurements showed that the vertical distribution of total attenuated backscatter (TAB) could reach altitudes of up to ~4–5 km and could be transported over the central Himalayan region. The spatial-averaged daily aerosol radiative forcing (ARF) values over the Indian subcontinent from January 2021 to April 2021 were found to range from −51.40 to −6.08 W m−2 (mean of −22.02 ± 9.19 W m−2), while on a monthly basis, the ARF values varied widely, from −146.24 to −1.63 W m−2 (mean of −45.56 ± 22.85 W m−2) over different parts of the study region. Furthermore, the spatial-averaged daily BC radiative forcing ranged from −2.23 to −0.35 (−1.01 ± 0.40 W m−2), while it varied from −15.29 to −0.31 W m−2 (−2.46 ± 2.32 W m−2) over different regions of southern Asia, indicating a rather small contribution to the total aerosol radiative effect and a large presence of highly scattering aerosols. Our findings highlight the importance of growing biomass burning, in light of recent climate change and the rapid decline in air quality over North India and the Indian Ocean.

Remote sensing and in situ measurements made during the Colorado Airborne Multiphase Cloud Study, 2010–2011 (CAMPS) with instruments aboard the University of Wyoming King Air aircraft are used to evaluate lidar–radar-retrieved cloud ice water content (IWC). The collocated remote sensing and in situ measurements provide a unique dataset for evaluation studies. Near-flight-level IWC retrieval is compared with an in situ probe: the Colorado closed-path tunable diode laser hygrometer (CLH). Statistical analysis showed that the mean radar–lidar IWC is within 26% of the mean in situ measurements for pure ice clouds and within 9% for liquid-topped mixed-phase clouds. Considering their different measurement techniques and different sample volumes, the comparison shows a statistically good agreement and is close to the measurement uncertainty of the CLH, which is around 20%. It is shown that ice cloud microphysics including ice crystal shape and orientation has a significant impact on IWC retrievals. These results indicate that the vertical profile of the retrieved lidar–radar IWC can be reliably combined with the flight-level measurements made by the in situ probes to provide a more complete picture of the cloud microphysics.

The amount of time that volcanic aerosols spend in the stratosphere is one of the primary factors influencing the climate impact of volcanic eruptions. Stratospheric aerosol persistence has been described in different ways, with many works quoting an approximately 12-month “residence time” for aerosol from large tropical eruptions. Here, we aim to develop a framework for describing the evolution of global stratospheric aerosol after major volcanic eruptions and quantifying its persistence, based on global satellite-based aerosol observations, tracer transport simulations, and simple conceptual modelling. We show that the stratospheric residence time of air, which is estimated through passive tracer pulse experiments and is one factor influencing the lifetime of stratospheric aerosols, is strongly dependent on the injection latitude and height, with an especially strong sensitivity to injection height in the first 4 km above the tropical tropopause. Simulated stratospheric tracer evolution is best described by a simple model which includes a lag between the injection and initiation of removal from the stratosphere. Based on analysis of global stratospheric aerosol observations, we show that the stratospheric lifetime of stratospheric aerosol from the 1991 Pinatubo eruption is approximately 22 months. We estimate the potential impact of observational uncertainties on this lifetime, finding it unlikely the lifetime of Pinatubo aerosol is less than 18 months.

The Measurement of Aerosol Extinction in the Stratosphere and Troposphere Retrieved by Occultation (MAESTRO) instrument on the SCISAT satellite provides aerosol extinction measurements in multiple solar wavelength bands. In this study, we evaluate the quality and utility of MAESTRO version 3.13 stratospheric aerosol extinction retrievals, from February 2004–February 2021, through comparison with measurements from other satellite instruments. Despite significant scatter in the MAESTRO data, we find that gridded median MAESTRO aerosol extinctions and stratospheric aerosol optical depth (SAOD) values are generally in good agreement with those from other instruments during volcanically quiescent periods. After volcanic eruptions and wildfire injections, gridded median MAESTRO extinction and SAOD are well correlated with other measurement sets but generally biased low by 40 %–80 %. The Ångström exponent (AE), which can provide information on aerosol particle size, is derived from the MAESTRO spectral extinction measurements in the lowermost stratosphere, showing perturbations after volcanic eruptions qualitatively similar to those from the Stratospheric Aerosol and Gas Experiment on the International Space Station (SAGE III/ISS) for the eruptions of Ambae (2018) and Ulawun (2019). Differences in AE anomalies after the 2019 extratropical Raikoke eruption may be due to the different spatiotemporal sampling of the two instruments. Furthermore, we introduce a method to adjust MAESTRO extinction data based on comparison with extinction measurements from SAGE III/ISS during the period from June 2017–February 2021, resulting in improved comparison during volcanically active periods. Our work suggests that empirical bias correction may enhance the utility of MAESTRO aerosol extinction data, which can make it a useful complement to existing satellite records, especially when multi-wavelength solar occultation data from other instruments are unavailable.

In spring 2021, Nepal underwent a record wildfire season in which active fires were detected at a rate 10 times greater than the 2002–2020 average. Prior to these major wildfire events, the country experienced a prolonged precipitation deficit and extreme drought during the post-monsoon period (starting in October 2020). An analysis using observational, reanalysis, and climate model ensemble data indicates that both climate variability and climate change-induced severe drought conditions were at play. Further analysis of climate model outputs suggests the likely reoccurrence of drought conditions, thus favoring active wildfire seasons in Nepal throughout the twenty-first century. While the inter-model uncertainty is large and direct modeling of wildfire spread and suppression has not been completed, the demonstrated relationship between a drought index (the standardized precipitation and evapotranspiration index) and subsequent fire activity may offer actionable opportunities for forest managers to employ the monitoring and projection of climate anomalies at sub-seasonal to decadal timescales to inform their management strategies for Nepal’s wildlands.

The high mountains stretch over 20.4% of Nepal’s land surface with diverse climatic conditions and associated vegetation types. An understanding of tree species and forest structural pattern variations across different climatic regions is crucial for mountain ecology. This study strived to carry out a comparative evaluation of species diversity, main stand variables, and canopy cover of forests with contrasting precipitation conditions in the Annapurna range. Firstly, climate data provided by CHELSA version 1.2, were used to identify distinct precipitation regimes. Lamjung and Mustang were selected as two contrasting precipitation regions, and have average annual precipitation of 2965 mm and 723 mm, respectively. Stratified random sampling was used to study 16 plots, each measuring 500 m2 and near the tree line at an elevation range of 3000 to 4000 m across different precipitation conditions. In total, 870 trees were identified and measured. Five hemispherical photos using a fisheye lens were taken in each plot for recording and analyzing canopy cover. Margalef’s index was used to measure species richness, while two diversity indices: the Shannon–Wiener Index and Simpson Index were used for species diversity. Dominant tree species in both study regions were identified through the Important Value Index (IVI). The Wilcoxon rank-sum test was employed to determine the differences in forest structure and composition variables between the two precipitation regimes. In total, 13 species were recorded with broadleaved species predominating in the high precipitation region and coniferous species in the low precipitation region. Higher species richness and species diversity were recorded in the low precipitation region, whereas the main stand variables: basal area and stem density were found to be higher in the high precipitation region. Overall, an inverse J-shaped diameter distribution was found in both precipitation regions signifying uneven-aged forest. A higher proportion of leaning and buttressed trees were recorded in the high precipitation region. However, similar forest canopy cover conditions (>90%) were observed in both study regions. The findings of this research provide a comprehensive narrative of tree species and forest structure across distinct precipitation regimes, which can be crucial to administrators and local people for the sustainable management of resources in this complex region.

Cloud liquid water path (LWP) strongly influences both radiative and hydrological properties of clouds and satellite-based LWP retrievals provide essential information for characterizing the state of the climate system and for evaluating climate models. However, current satellite LWP retrievals can contain significant biases that are too large to properly constrain inter-model variation. In this study, three years of combined A-train remote sensing measurements from MODIS, AMSR-E, CloudSat and CALIPSO, combined with ground-based measurements and three dimensional radiative-transfer modelling are used to examine uncertainties in MODIS LWP retrievals. MODIS retrievals, based on a bi spectral reflectance technique, are unique in that they can provide global daytime observations of both liquid and ice cloud properties at a spatial resolution of 1 km every one to two days. The focus of this study is to improve the retrieval of LWP from MODIS measurements for both mixed phase clouds and clouds with high solar zenith angle, both of which disproportionately affect the MODIS retrievals at high latitudes.Current MODIS retrievals are based on either liquid or ice phase assumption throughout the cloud vertical layer. This study improves the operational approach in liquid-topped mixed phase clouds by adding complementary information from active sensors onboard the A-train. They allow proper identification of cloud phase and also provide independent measurements of ice clouds properties. Multi-sensor LWP retrievals in liquid topped mixed phase clouds show that inadequate phase classification contribute to the LWP bias that is related to the IWP on average and reaches close to 15% at IWP of 150 g/m2 and can reach 40% or higher when IWP is greater than 400 g/m2.Moreover, A-train and ground-based measurements and radiative transfer modeling are used to quantify the as-of-yet unresolved high bias in MODIS LWP that depends on solar zenith angle. This study confirms that cloud top height inhomogeneity is one of the main factors that contribute to this bias due to 3-dimensional radiative effects. A new approach is introduced to reduce this bias. It utilizes two parameters: the solar zenith angle and cloud heterogeneity index, both of which are provided in the cloud property dataset for each MODIS pixel. Comparisons with collocated satellite and ground-based microwave measurements in carefully screened clouds shows that this method can effectively remove this large first-order MODIS LWP bias. Applying this to MODIS pixel level data collocated along the CloudSat footprint suggests annually averaged MODIS LWP overestimation gradually increases with latitude and can reach over 50 g/m2 at high latitudes. This overestimation becomes even more severe for seasonal or monthly averages and can exceed 100 g/m2 during winter. An improved MODIS LWP dataset will provide an observational constraint on the temperature-dependent cloud phase partitioning in models and can help improve cloud feedback uncertainty in mixed phase clouds, which are prevalent in polar regions where observational data are limited and contain large uncertainties.

Cloud water content and how that water is distributed across hydrometeors are fundamental cloud microphysical properties that influence cloud dynamical and radiative properties. This study utilizes in-situ and remote sensing data collected by the University of Wyoming King Air research aircraft during the Colorado Airborne Multi-phase Cloud Study, 2010-2011 (CAMPS) field campaign to study the reliability of different cloud water content measuring instruments. It has been shown in several previous studies and again demonstrated here from the CAMPS dataset that Forward Scattering Spectrometer Probe (FSSP) measurements are subject to contamination by shattering artifacts in ice and mixed phase clouds. Contaminated measurements from CAMPS show a significant overestimation of large (D > 28 µm) particles and derived liquid water content (LWC). A new approach is developed to characterize, quantify and correct the shattering contribution in FSSP measurements using ice particle information measured by an OAP cloud probe (2D-C). Comparisons with cloud droplet probe (CDP) measurements show that this new approach adequately corrects for ice shattering effects. This new approach can also be applied to standard FSSP historical datasets. These studies may have erroneous conclusions that can be re-evaluated based on this new correction. University of Colorado closed-path tunable diode laser hygrometer (CLH) total water measurements are used to develop a mass-length relationship for CAMPS dataset to calculate ice water content (IWC) from 2D-C size distribution. Then, these well characterized in-situ instruments are used to evaluate IWC retrievals from combined radar and lidar measurements. Comparison of near flight level remote sensing IWC retrievals with in-situ measurements indicates statistically reasonable agreements (difference in mean values about 33%) providing confidence on the retrieved vertical IWC profile. The collocated airborne radar-lidar measurements combined with in-situ measurements provide detailed information about cloud microphysical and radiative properties. These properties can be used to develop and improve cloud parameterizations in numerical models.