Search

This paper presents a method for reconstructing the historical hourly concentrations of Particulate Matter 2.5 (PM2.5) over the Kathmandu Valley from 1980 to the present. The method uses a machine learning model that is trained using PM2.5 readings from the US Embassy (Phora Durbar) as a ground truth, and the meteorological data from the Modern-Era Retrospective Analysis for Research and Applications v2 (MERRA2) as input. The Extreme Gradient Boosting (XGBoost) model acquires a credible 10-fold cross-validation (CV) score of ~83.4%, an r2-score of ~84%, a Root Mean Square Error (RMSE) of ~15.82 µg/m3, and a Mean Absolute Error (MAE) of ~10.27 µg/m3. Further demonstrating the model's applicability to years other than those for which truth values are unavailable, the multiple cross-tests with an unseen data set offered r2-scores for 2018, 2019, and 2020 ranging from 56% to 67%. The model-predicted data agree with true values and indicate that MERRA2 underestimates PM2.5 over the region. It strongly agrees with ground-based evidence showing substantially higher mass concentrations in the dry pre- and post-monsoon seasons than in the monsoon months. It also shows a strong anti-correlation between PM2.5 concentration and humidity. The results also demonstrate that none of the years fulfilled the annual mean air quality index (AQI) standards set by the World Health Organization (WHO). [ABSTRACT FROM AUTHOR]

Clouds and blowing snow (BLSN) occur frequently over Antarctica, where it is critical to understand their feedbacks to surface and atmospheric boundary layer processes. Dome C, an elevated East Antarctic station, dominated by lengthy periods of surface longwave (LW) radiative cooling, is selected to reveal cloud and BLSN impacts within a largely stable environment. The sky condition is classified as clear, cloudy, or BLSN, using 3 years of Cloud‐Aerosol Lidar and Infrared Pathfinder Satellite Observations satellite data. Co‐located and contemporaneous in situ observations are used to investigate the relationship of sky condition with surface and atmospheric boundary layer thermal structure, focusing on seasonal variability. Results show that increased downwelling LW radiation from clouds abate surface radiative cooling losses, contributing to warming during all seasons. An increase of 3°C in the mean surface air temperature is observed during spring, whereas, a more dramatic rise (around 10°C), due to accompanying large‐scale subsidence, is observed during fall and winter in association with clouds. For all seasons, the wind speed and wind speed shear are strongest during BLSN events, and the surface‐based inversion is weakened by cooling which peaks in a shallow above‐surface turbulent layer. The stronger background stability during fall and winter seasons, restricts turbulence and BLSN depths generally to the lowest tens of meters. The Earth's cryosphere is among the most rapidly evolving yet least well‐observed regions, and knowledge of clouds and BLSN interactions with the typical stable atmospheric boundary layer can help further understand energy and moisture exchanges. Plain Language Summary: The sky‐condition over Antarctica can be cloudy, clear, or characterized by blowing snow (BLSN) which is a phenomenon where snow is lifted, sometimes up to few hundreds of meters, and transported across the continent by winds. Knowing the impact of clouds and BLSN on the surface and the atmospheric boundary layer, which is the lower portion of the atmosphere that is directly linked to the surface, is crucial for understanding Antarctic climate. Dome C, an elevated dome‐shaped peak in East Antarctica, is chosen to study these impacts. In this location, an investigation covering a 3 year period using satellite observations and in situ measurements reveals that clouds can warm the surface and atmospheric boundary layer by increasing the downwelling longwave radiation. BLSN is accompanied by relatively stronger winds, and the wind‐driven atmospheric turbulence tends to weaken the strong positive temperature gradient in the atmospheric boundary layer, which is known as the temperature inversion. Temperature inversions are common at Dome C, and are most intense in the fall and winter seasons during which time they seemingly restrict the atmospheric turbulence and BLSN layer depth to a few tens to several tens of meters. Key Points: Cloud‐Aerosol Lidar and Infrared Pathfinder Satellite Observations and co‐located in situ observations allow study of cloud and blowing snow (BLSN) impacts on Antarctic atmosphereAt Dome C, clouds abate surface longwave radiative cooling losses, causing warming in all seasonsBLSN, accompanied by intense winds, weakens the temperature inversion, and is vertically restricted by strong background stability [ABSTRACT FROM AUTHOR]

Laser beams emitted from the Geoscience Laser Altimeter System (GLAS), as well as other spaceborne laser instruments, can only penetrate clouds to a limit of a few optical depths. As a result, only optical depths of thinner clouds (< about 3 for GLAS) are retrieved from the reflected lidar signal. This paper presents a comprehensive study of possible retrievals of optical depth of thick clouds using solar background light and treating GLAS as a solar radiometer. To do so one must first calibrate the reflected solar radiation received by the photon-counting detectors of the GLAS 532-nm channel, the primary channel for atmospheric products. Solar background radiation is regarded as a noise to be subtracted in the retrieval process of the lidar products. However, once calibrated, it becomes a signal that can be used in studying the properties of optically thick clouds. In this paper, three calibration methods are presented: (i) calibration with coincident airborne and GLAS observations, (ii) calibration with coincident Geostationary Operational Environmental Satellite (GOES) and GLAS observations of deep convective clouds, and (iii) calibration from first principles using optical depth of thin water clouds over ocean retrieved by GLAS active remote sensing. Results from the three methods agree well with each other. Cloud optical depth (COD) is retrieved from the calibrated solar background signal using a one-channel retrieval. Comparison with COD retrieved from GOES during GLAS overpasses shows that the average difference between the two retrievals is 24%. As an example, the COD values retrieved from GLAS solar background are illustrated for a marine stratocumulus cloud field that is too thick to be penetrated by the GLAS laser. Based on this study, optical depths for thick clouds will be provided as a supplementary product to the existing operational GLAS cloud products in future GLAS data releases.

Gene expression profiles of blood can reflect the physiopathologic status of the immune system. The dynamic microRNA (miRNA) expression profiles of peripheral blood from pigs at different developmental stages, and how differential expression of miRNAs might relate to immune system development, are unknown. In this study, peripheral blood samples taken at five developmental stages were used to construct 15 miRNA libraries (three biological replicates/stage): 0 days (newborn), 30 days (weaning), 60 days (weaned), and 180 and 360 days (puberty). We identified 295 known mature miRNAs. Hierarchical clustering of the miRNA expression profile showed significant differences between individuals at the neonatal and postnatal stages. Functional enrichment analysis revealed that miRNAs differentially expressed between pairwise comparisons of the developmental stages were over-represented in immune-related pathways such as toll-like receptor signaling. The time-course of expression of the over-representated miRNAs exhibited a pattern of steady decline over time, for both the complete miRNA compendium and immune-related miRNAs. We identified six marker miRNAs that were highly negatively correlated with chronologic age and enriched for genes involved in immune-related pathways. This study of a peripheral blood miRNA transcriptome offers insight into immune system development in swine and provides a resource for pig genome annotation. [ABSTRACT FROM AUTHOR]

Remote sensing from Earth‐observing satellites is now providing valuable information about ocean phytoplankton distributions. This paper presents the new ocean subsurface optical properties obtained from two space‐based lidars: the Cloud‐Aerosol Lidar with Orthogonal Polarization (CALIOP) aboard the Cloud‐Aerosol Lidar and Infrared Pathfinder Satellite Observations satellite and the Advanced Topographic Laser Altimeter System (ATLAS) aboard the Ice, Cloud, and land Elevation Satellite‐2 satellite. Obtaining reliable estimates of subsurface biomass necessitates removing instrument artifacts peculiar to each sensor, that is, polarization crosstalk artifacts in the CALIOP signals and after pulsing effects arising from the ATLAS photodetectors. We validate the optical properties derived from the corrected lidar backscatter signals using MODerate‐resolution Imaging Spectroradiometer ocean color measurements and autonomous biogeochemical Argo float profiles. Our results support the continued use of present and future spaceborne lidars to study the global plankton system and characterize its vertical structures in the upper ocean. Key Points: Global ocean subsurface properties are retrieved from Cloud‐Aerosol Lidar with Orthogonal Polarization (CALIOP)The CALIOP crosstalk artifact and Advanced Topographic Laser Altimeter System (ATLAS) after pulsing effects are removedHigh vertical resolution of ocean subsurface profiles can be obtained from ATLAS/Ice, Cloud, and land Elevation Satellite‐2 [ABSTRACT FROM AUTHOR]

The Advanced Topographic Laser Altimeter System (ATLAS) was launched aboard the Ice Cloud and land‐Elevation Satellite‐2 (ICESat‐2) satellite in September 2018. ATLAS is a single wavelength (532 nm) lidar system designed to acquire high resolution measurements of the earth's surface while also obtaining atmospheric backscatter from molecules, clouds, and aerosols. Because ATLAS is optimized for altimetry, the atmospheric data acquired is unique in many respects and requires non‐standard analysis techniques. For example, the high repetition rate laser limits the vertical extent of the profiles to just 14 km and causes atmospheric scattering from above 15 km to be added to the scattering in the lower 0–14 km profile. In addition, the limited vertical range of the acquired profiles renders it difficult to compute the magnitude of the solar background and hinders the application of standard calibration techniques. Despite these limitations, methods have been developed to successfully produce data products that have value to the atmospheric community for cloud and aerosol research and are currently available at the National Snow and Ice Data Center (NSIDC). In this paper we describe the ICESat‐2 atmospheric channel and the methods used to process the ATLAS raw photon count data to obtain calibrated backscatter and higher level products such as layer heights and type, blowing snow, column optical depth and apparent surface reflectance. Plain Language Summary: ICESat‐2 is a polar orbiting satellite equipped with a high repetition rate laser that fires green pulses of light to earth 10,000 times per second. The main objective of ICESat‐2 is the high‐resolution measurement of the height of the earth's surface, with emphasis on the change in elevation of ice sheets that cover most of Greenland and Antarctica. In addition to surface elevation, ICESat‐2 also obtains information on the vertical structure of the atmosphere including the height and thickness of clouds and aerosols. The atmospheric measurements are important for climate studies and because they extend the data record begun by other earth‐orbiting satellite lidars like Cloud‐Aerosol Lidar and Infrared Pathfinder Satellite Observations (CALIPSO) which has been acquiring atmospheric data since 2006 and is nearing the end of its life. The creation of a long record of cloud and aerosol observations is very important for detecting changes that may be occurring due to humanity's influence on the climate system. Key Points: ICESat‐2 is a satellite lidar that acquires atmospheric backscatter profiles from 0 to 14 km every 280 m along the satellite trackThe high repetition rate laser creates unusual problems for processing the raw data to higher level data productsProducts such as calibrated backscatter, cloud and aerosol layer heights, column optical depth and blowing snow are described and shown [ABSTRACT FROM AUTHOR]

The Advanced Topographic Laser Altimeter System (ATLAS) aboard the Ice, Cloud, and land Elevation Satellite‐2 (ICESat‐2) has been making very high resolution measurements of the Earth's surface elevation since October 2018. ATLAS uses photomultiplier tubes (PMTs) as detectors in photon counting mode, so that a single photon reflected back to the receiver triggers a detection within the ICESat‐2 data acquisition system. However, one characteristic of ICESat‐2 detected photons is the possible presence of afterpulses, defined as small amplitude pulses occurring after the primary signal pulse due to photon arrival. The disadvantage of these afterpulses is that they often confound the accurate measurements of low level signals following a large amplitude of signal and can degrade energy resolution and cause errors in pulse counting applications. This paper discusses and summarizes the after‐pulsing effects exhibited by the ATLAS PMTs based on on‐orbit measurements over different seasons and geographic regions. The potential impacts of these after‐pulsing effects on altimetry and ocean subsurface retrievals are discussed. Plain Language Summary: After‐pulsing effects occurring in the ICESat‐2 Advanced Topographic Laser Altimeter System (ATLAS) are characterized from the on‐orbit measurements acquired over different surface types. Multiple echoes due to after‐pulsing effects in the ATLAS photomultiplier tubes (PMTs) are clearly seen below the Earth's surface where the signal should be totally attenuated. The afterpulses captured from on‐orbit measurements are caused by three different reasons: (1) the effects of the dead‐time circuit (∼3 ns) due to PMT saturation; (2) the effects of optical reflections within the ATLAS receiver optical components; (3) PMT afterpulses. The echoes separated by ∼0.45 m are attributed to the effect of the dead‐time circuit (∼3 ns) due to PMT saturation. The echoes at ∼2.3 and ∼4.2 m below the primary surface returns are caused by the optical reflections within the ATLAS receiver optical components, while the echoes from ∼10 to ∼45 m away from the primary surface signal are due to the PMT afterpulses with a longer time delay. The ICESat‐2 ATLAS instrument response is derived from both a measurement of the transmitted laser pulse shape and measured photon events arising from land surfaces with different surface albedos. The ICESat‐2 on‐orbit measurements demonstrate that the ATLAS impulse response during different months and over different surface types is essentially identical. Key Points: The effects of after‐pulsing by the Advanced Topographic Laser Altimeter System (ATLAS) aboard the ICESat‐2 satellite are describedThe transient response of the ATLAS receiver is characterized over different measurement regimesThe potential impacts of these detector artifacts on ICESat‐2 science studies are discussed [ABSTRACT FROM AUTHOR]

As a common phenomenon over Antarctica, blowing snow (BLSN), especially the large BLSN storms, play an important role in the Antarctic surface mass balance, radiation budget, and planetary boundary layer processes. This study presents the work on BLSN storm identification and analysis with observations from the Moderate Resolution Imaging Spectroradiometer (MODIS) onboard the Aqua satellite. Spectral analysis shows that BLSN identification is feasible with MODIS daytime data. A random forest machine learning model is developed and observations from the Cloud‐Aerosol Lidar with Orthogonal Polarization are used for training. Model performance results show that machine‐learning based classification can achieve over 90% overall accuracy when classifying MODIS pixels into cloud, clear, and BLSN categories. The machine learning model is applied to MODIS observations during the month of October 2009 for BLSN storm analysis. Results show that the size of BLSN storms has a large spectrum and can reach hundreds of thousands km2. The MODIS based BLSN storm frequency map extends the Cloud‐Aerosol Lidar and Infrared Pathfinder Satellite Observations coverage limit from 82°S to the South Pole. A BLSN storm belt, which extends from the South Pole region to the coastal area between 130°E and 160°E along the Transantarctic Mountains, provides a potential pathway of snow transport. These results are important in improving the understanding of BLSN impact on Antarctic surface mass balance and boundary layer processes. [ABSTRACT FROM AUTHOR]

An analytic transfer inverse model for Earth Polychromatic Imaging Camera (EPIC) observations is proposed to retrieve the cloud-top pressure (CTP) with the consideration of in-cloud photon penetration. In this model, an analytic equation was developed to represent the reflection at the top of the atmosphere from above cloud, in cloud, and below cloud. The coefficients of this analytic equation can be derived from a series of EPIC simulations under different atmospheric conditions using a nonlinear regression algorithm. With estimated cloud pressure thickness, the CTP can be retrieved from EPIC observation data by solving the analytic equation. To simulate the EPIC measurements, a program package using the double- k approach was developed. Compared to line-by-line calculation, this approach can calculate high-accuracy results with a 100-fold computation time reduction. During the retrieval processes, two kinds of retrieval results, i.e., baseline CTP and retrieved CTP, are provided. The baseline CTP is derived without considering in-cloud photon penetration, and the retrieved CTP is derived by solving the analytic equation, taking into consideration in-cloud and below-cloud interactions. The retrieved CTPs for the oxygen A and B bands are smaller than their related baseline CTP. At the same time, both baseline CTP and retrieved CTP at the oxygen B band are larger than those at the oxygen A band. Compared to the difference in baseline CTP between the B band and A band, the difference in retrieved CTP between these two bands is generally reduced. Out of around 10 000 cases, in retrieved CTP between the A and B bands we found an average bias of 93 mb with a standard deviation of 81 mb. The cloud layer top pressure from Cloud–Aerosol Lidar and Infrared Pathfinder Satellite Observations (CALIPSO) measurements is used for validation. Under single-layer cloud situations, the retrieved CTPs for the oxygen A band agree well with the CTPs from CALIPSO, the mean difference of which within 5 mb in the case study. Under multiple-layer cloud situations, the CTPs derived from EPIC measurements may be larger than the CTPs of high-level thin clouds due to the effect of photon penetration. [ABSTRACT FROM AUTHOR]

Satellite cloud detection over snow and ice has been difficult for passive remote sensing instruments due to the lack of contrast between clouds and cold/bright surfaces; cloud mask algorithms often heavily rely on shortwave infrared (IR) channels over such surfaces. The Earth Polychromatic Imaging Camera (EPIC) on board the Deep Space Climate Observatory (DSCOVR) does not have infrared channels, which makes cloud detection over snow and ice surfaces even more challenging. This study investigates the methodology of applying EPIC's two oxygen absorption band pair ratios in the A band (764, 780 nm) and B band (688, 680 nm) for cloud detection over the snow and ice surfaces. We develop a novel elevation and zenith-angle-dependent threshold scheme based on radiative transfer model simulations that achieves significant improvements over the existing algorithm. When compared against a composite cloud mask based on geosynchronous Earth orbit (GEO) and low Earth orbit (LEO) sensors, the positive detection rate over snow and ice surfaces increased from around 36 % to 65 % while the false detection rate dropped from 50 % to 10 % for observations of January 2016 and 2017. The improvement in July is less substantial due to relatively better performance in the current algorithm. The new algorithm is applicable for all snow and ice surfaces including Antarctic, sea ice, high-latitude snow, and high-altitude glacier regions. This method is less reliable when clouds are optically thin or below 3 km because the sensitivity is low in oxygen band ratios for these cases. [ABSTRACT FROM AUTHOR]

Recent high‐resolution dropsonde observations from the 2010 Concordiasi field campaign in austral spring season show that surface‐based inversions (SBIs) over Antarctica are frequently eroded, with well‐mixed boundary layers occurring 33% and 18% of the time in West and East Antarctica, respectively. In this study, using the dropsonde observations, we evaluate the performance of the Modern‐Era Retrospective analysis for Research and Applications, version 2 (MERRA2) in representing the Antarctic boundary layer thermodynamic structure. Results show that MERRA2 has a good overall representation of the Antarctic surface stability and correctly predicts 82% of the SBIs. However, an underprediction of less stable boundary layer occurrence, especially over the elevated East Antarctic plateau, is favored during conditions of increased lower tropospheric stability associated with model dynamics, indicating difficulty in parameterizing turbulence in very stable boundary layers. In addition, a lower tropospheric cool bias (first model level and above) is observed in the MERRA2 reanalysis, especially over West Antarctica, which amplifies in the boundary layer during mixed conditions. The near‐surface cold bias is most pronounced when the model fails to predict mixed layers over West Antarctica and is expected to negatively impact the representation of surface energy budget and melt processes. Key Points: MERRA2 has good skill in representing the frequency of less stable and stable Antarctic boundary layersThe model underpredicts turbulence and the frequency of less stable boundary layers especially over elevated regions of East AntarcticaRepercussions of missing boundary layer turbulent processes are more severe for the representation of West Antarctic surface processes [ABSTRACT FROM AUTHOR]

This paper presents the physical basis of the Earth Polychromatic Imaging Camera (EPIC) cloud product algorithms and an initial evaluation of their performance. Since June 2015, EPIC has been providing observations of the sunlit side of the Earth with its 10 spectral channels ranging from the UV to the near-infrared. A suite of algorithms has been developed to generate the standard EPIC Level 2 cloud products that include cloud mask, cloud effective pressure/height, and cloud optical thickness. The EPIC cloud mask adopts the threshold method and utilizes multichannel observations and ratios as tests. Cloud effective pressure/height is derived with observations from the O2 A-band (780 and 764 nm) and B-band (680 and 688 nm) pairs. The EPIC cloud optical thickness retrieval adopts a single-channel approach in which the 780 and 680 nm channels are used for retrievals over ocean and over land, respectively. Comparison with co-located cloud retrievals from geosynchronous earth orbit (GEO) and low earth orbit (LEO) satellites shows that the EPIC cloud product algorithms are performing well and are consistent with theoretical expectations. These products are publicly available at the Atmospheric Science Data Center at the NASA Langley Research Center for climate studies and for generating other geophysical products that require cloud properties as input. [ABSTRACT FROM AUTHOR]

This paper presents an innovative retrieval method that translates the CALIOP land surface laser pulse returns into the surface bidirectional reflectance. To better analyze the surface returns, the CALIOP receiver impulse response and the downlinked samples' distribution at 30m vertical resolution are discussed. The saturated laser pulse magnitudes from snow and ice surfaces are recovered based on information extracted from the tail end of the surface signal. The retrieved snow surface bidirectional reflectance is compared with reflectance from both CALIOP cloud-covered regions and MODIS BRDF--albedo model parameters. In addition to the surface bidirectional reflectance, the column top-of-atmosphere bidirectional reflectances are calculated from the CALIOP lidar background data and compared with the bidirectional reflectances derived from WFC radiance measurements. The retrieved CALIOP surface bidirectional reflectance and column top-of-atmosphere bidirectional reflectance results provide unique information to complement existing MODIS standard data products and are expected to have valuable applications for modelers. [ABSTRACT FROM AUTHOR]

Growth performance and meat quality are important traits for the pig industry and consumers. Adipose tissue is the main site at which fat storage and fatty acid synthesis occur. Therefore, we combined high-throughput transcriptomic sequencing in adipose and muscle tissues with the quantification of corresponding phenotypic features using seven Chinese indigenous pig breeds and one Western commercial breed (Yorkshire). We obtained data on 101 phenotypic traits, from which principal component analysis distinguished two groups: one associated with the Chinese breeds and one with Yorkshire. The numbers of differentially expressed genes between all Chinese breeds and Yorkshire were shown to be 673 and 1056 in adipose and muscle tissues, respectively. Functional enrichment analysis revealed that these genes are associated with biological functions and canonical pathways related to oxidoreductase activity, immune response, and metabolic process. Weighted gene coexpression network analysis found more coexpression modules significantly correlated with the measured phenotypic traits in adipose than in muscle, indicating that adipose regulates meat and carcass quality. Using the combination of differential expression, QTL information, gene significance, and module hub genes, we identified a large number of candidate genes potentially related to economically important traits in pig, which should help us improve meat production and quality. [ABSTRACT FROM AUTHOR]