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Abstract Objective Neuromyelitis optica spectrum disorder (NMOSD) is an autoimmune‐mediated disorder with aquaporin 4‐immunoglobulin G (AQP4‐IgG) in most settings. Soluble programmed death‐1 (sPD‐1) and soluble programmed death ligand 1 (sPD‐L1) play key roles in immunomodulation. We aim to assess the association of sPD‐1 and sPD‐L1 with cytokines and their clinical significance in AQP4‐IgG (+) NMOSD. Method We measured plasma sPD‐1, sPD‐L1, and 10 cytokines levels of 66 AQP4‐IgG (+) NMOSD patients, including 40 patients in attack (attack‐NMOSD) and 26 patients in remission (remission‐NMOSD) phases, and 28 healthy controls through ultrasensitive Simoa and SP‐X platform, respectively. We also performed >2 years (median) of follow‐up after testing and analyzed the relationship between the detection index and current and future clinical parameters. Result Plasma sPD‐1 level discriminated attack‐NMOSD from remission‐NMOSD (AUC = 0.692, p = 0.009). sPD‐1 and sPD‐L1 levels positively correlated with IL‐6 (rsPD‐1 = 0.313; rsPD‐L1 = 0.508), IFN‐γ (rsPD‐1 = 0.331; rsPD‐L1 = 0.456), and TNF‐α (rsPD‐1 = 0.451; rsPD‐L1 = 0.531) expression, as well as clinical indicators, including the EDSS score (rsPD‐1 = 0.331; rsPD‐L1 = 0.402), number of attacks (rsPD‐1 = 0.431) and segments of spinal cord involvement (rsPD‐1 = 0.462; rsPD‐L1 = 0.508). The risk of relapse within 2 years after sampling was associated with higher sPD‐1/sPD‐L1 ratio in attack‐NMOSD (p = 0.022; Exp(B) = 1.589). Interpretation Plasma sPD‐1 and sPD‐L1 levels reflected current disease severity and activity, and predicted future relapses in AQP4‐IgG (+) NMOSD, suggesting that they hold the potential to guide timely and targeted treatment.

Abstract Type 2 diabetes (T2D)-related fragility fractures represent an increasingly tough medical challenge, and the current treatment options are limited. Mechanical loading is essential for maintaining bone integrity, although bone mechano-responsiveness in T2D remains poorly characterized. Herein, we report that exogenous cyclic loading-induced improvements in bone architecture and strength are compromised in both genetically spontaneous and experimentally-induced T2D mice. T2D-induced reduction in bone mechano-responsiveness is directly associated with the weakened Ca2+ oscillatory dynamics of osteocytes, although not those of osteoblasts, which is dependent on PPARα-mediated specific reduction in osteocytic SERCA2 pump expression. Treatment with the SERCA2 agonist istaroxime was demonstrated to improve T2D bone mechano-responsiveness by rescuing osteocyte Ca2+ dynamics and the associated regulation of osteoblasts and osteoclasts. Moreover, T2D-induced deterioration of bone mechano-responsiveness is blunted in mice with osteocytic SERCA2 overexpression. Collectively, our study provides mechanistic insights into T2D-mediated deterioration of bone mechano-responsiveness and identifies a promising countermeasure against T2D-associated fragility fractures.

The National Oceanic and Atmospheric Administration (NOAA) 21 Visible Infrared Imaging Radiometer Suite (VIIRS) was successfully launched on 10 November 2022. To ensure the required instrument performance, a series of Post-Launch Tests (PLTs) were performed and analyzed. The primary calibration source for NOAA-21 VIIRS Reflective Solar Bands (RSBs) is the Solar Diffuser (SD), which retains the prelaunch radiometric calibration standard from prelaunch to on-orbit. Upon reaching orbit, the SD undergoes degradation as a result of ultraviolet solar illumination. The rate of SD degradation (called the H-factor) is monitored by a Solar Diffuser Stability Monitor (SDSM). The initial H-factor’s instability was significantly improved by deriving a new sun transmittance function from the yaw maneuver and one-year SDSM data. The F-factors (normally represent the inverse of instrument gain) thus calculated for the Visible/Near-Infrared (VISNIR) bands were proven to be stable throughout the first year of the on-orbit operations. On the other hand, the Shortwave Infrared (SWIR) bands unexpectedly showed fast degradation, which is possibly due to unknown substance accumulation along the optical path. To mitigate these SWIR band gain changes, the NOAA VIIRS Sensor Data Record (SDR) team used an automated calibration software package called RSBautoCal. In March 2024, the second middle-mission outgassing event to reverse SWIR band degradation was shown to be successful and its effects are closely monitored. Finally, the deep convective cloud trends and lunar collection results validated the operational F-factors. This paper summarizes the preliminary on-orbit radiometric calibration updates and performance for the NOAA-21 VIIRS SDR products in the RSB.

This study investigates the long-term stability of the Suomi National Polar-orbiting Partnership (S-NPP) Visible Infrared Imaging Radiometer Suite (VIIRS) moderate-resolution Thermal Emissive Bands (M TEBs; M12–M16) covering a period from February 2012 to August 2020. It also assesses inter-sensor consistency of the VIIRS M TEBs among three satellites (S-NPP, NOAA-20, and NOAA-21) over eight months spanning from 18 March to 30 November 2023. The field of interest is limited to the ocean surface between 60°S and 60°N, specifically under clear-sky conditions. Taking radiative transfer modeling (RTM) as the transfer reference, we employed the Community Radiative Transfer Model (CRTM) to simulate VIIRS TEB brightness temperature (BTs), incorporating European Centre for Medium-range Weather Forecasts (ECMWF) reanalysis data as inputs. Our results reveal two key findings. Firstly, the reprocessed S-NPP VIIRS TEBs exhibit a robust long-term stability, as demonstrated through analyses of the observation minus background BT differences (O-B ∆BTs) between VIIRS measurements (O) and CRTM simulations (B). The drifts of the O-B BT differences are consistently less than 0.102 K/Decade across all S-NPP VIIRS M TEB bands. Notably, observations from VIIRS M14 and M16 stand out with drifts well within 0.04 K/Decade, reinforcing their exceptional reliability for climate change studies. Secondly, excellent inter-sensor consistency among these three VIIRS instruments is confirmed through the double-difference analysis method (O-O). This method relies on the O-B BT differences obtained from daily VIIRS operational data. The mean inter-VIIRS O-O BT differences remain within 0.08 K for all M TEBs, except for M13. Even in the case of M13, the O-O BT differences between NOAA-21 and NOAA-20/S-NPP have values of 0.312 K and 0.234 K, respectively, which are comparable to the 0.2 K difference observed in overlapping TEBs between VIIRS and MODIS. These disparities are primarily attributed to the significant differences in the Spectral Response Function (SRF) of NOAA-21 compared to NOAA-20 and S-NPP. It is also found that the remnant scene temperature dependence of NOAA-21 versus NOAA-20/S-NPP M13 O-O BT difference after accounting for SRF difference is ~0.0033 K/K, an order of magnitude smaller than the corresponding rates in the direct BT comparisons between NOAA-21 and NOAA-20/S-NPP. Our study confirms the versatility and effectiveness of the RTM-based TEB quality evaluation method in assessing long-term sensor stability and inter-sensor consistency. The double-difference approach effectively mitigates uncertainties and biases inherent to CRTM simulations, establishing a robust mechanism for assessing inter-sensor consistency. Moreover, for M12 operating as a shortwave infrared channel, it is found that the daytime O-B BT differences of S-NPP M12 exhibit greater seasonal variability compared to the nighttime data, which can be attributed to the idea that M12 radiance is affected by the reflected solar radiation during the daytime. Furthermore, in this study, we’ve also characterized the spatial distributions of inter-VIIRS BT differences, identifying variations among VIIRS M TEBs, as well as spatial discrepancies between the daytime and nighttime data.

Summary: Bone stress injuries are common overuse injuries, especially in soldiers, athletes, and performers. In contrast to various post-injury treatments, early protection against bone stress injuries can provide greater benefit. This study explored the early protection strategies against bone stress injuries by mobilization of endogenous targeted bone remodeling. The effects of various pharmaceutical/biophysical approaches, individual or combinational, were investigated by giving intervention before fatigue loading. We optimized the dosage and administration parameters and found that early intervention with pulsed electromagnetic field and parathyroid hormone (i.e., PEMF+PTH) resulted in the most pronounced protective effects among all the approaches against the bone stress injuries. In addition, the mechanisms by which the strategy mobilizes targeted bone remodeling and enhances the self-repair capacity of bone were systematically investigated. This study proposes strategies to reduce the incidence of bone stress injuries in high-risk populations (e.g., soldiers and athletes), particularly for those before sudden increased physical training.

Recently, the NOAA has included GNSS (Global Navigation Satellite System) Radio Occultation (RO) data as one of the crucial long-term observables for weather and climate applications. To include more GNSS RO data in its numerical weather prediction systems, the NOAA Commercial Weather Data Pilot program (CWDP) started to explore the commercial RO data available on the market. After two rounds of pilot studies, the CWDP decided to award the first Indefinite Delivery Indefinite Quantity (IDIQ) contract to GeoOptics and Spire Incs. in 2020. This study examines the quality of Spire RO data products for weather and climate applications. Spire RO data collected from commercial CubeSats are carefully compared with data from Formosa Satellite Mission 7–Constellation Observing System for Meteorology, Ionosphere, and Climate-2 (COSMIC-2), the fifth-generation European Centre for Medium-Range Weather Forecasts (ECMWF) atmospheric reanalysis (ERA5), and high-quality radiosonde data. The results demonstrate that, despite their generally lower Signal-Noise-Ratio (SNR), Spire RO data show a pattern of lowest penetration height similar to that of COSMIC-2. The Spire and COSMIC-2 penetration heights are between 0.6 and 0.8 km altitude over tropical oceans. Although using different GNSS RO receivers, the precision of Spire STRATOS receivers is of the same quality as those of the COSMIC-2 TriG (Global Positioning System—GPS, GALILEO, and GLObal NAvigation Satellite System—GLONASS) RO Receiver System (TGRS) receivers. Furthermore, the Spire and COSMIC-2 retrieval accuracies are quite comparable. We validate the Spire temperature and water vapor profiles by comparing them with collocated radiosonde observation (RAOB) data. Generally, over the height region between 8 km and 16.5 km, the Spire temperature profiles match those from RS41 RAOB very well, with temperature biases of

Disuse osteoporosis is a metabolic bone disease resulting from skeletal unloading (e.g., during extended bed rest, limb immobilization, and spaceflight), and the slow and insufficient bone recovery during reambulation remains an unresolved medical challenge. Here, we demonstrated that loading-induced increase in bone architecture/strength was suppressed in skeletons previously exposed to unloading. This reduction in bone mechanosensitivity was directly associated with attenuated osteocytic Ca2+ oscillatory dynamics. The unloading-induced compromised osteocytic Ca2+ response to reloading resulted from the HIF-1α/PDK1 axis–mediated increase in glycolysis, and a subsequent reduction in ATP synthesis. HIF-1α also transcriptionally induced substantial glutaminase 2 expression and thereby glutamine addiction in osteocytes. Inhibition of glycolysis by blockade of PDK1 or glutamine supplementation restored the mechanosensitivity in those skeletons with previous unloading by fueling the tricarboxylic acid cycle and rescuing subsequent Ca2+ oscillations in osteocytes. Thus, we provide mechanistic insight into disuse-induced deterioration of bone mechanosensitivity and a promising therapeutic approach to accelerate bone recovery after long-duration disuse.

Global Navigation Satellite System (GNSS) Radio Occultation (RO) data play an essential role in improving numerical weather prediction (NWP) and monitoring climate change. The NOAA Commercial RO Purchase Program (CDP) purchased RO data provided by Spire Global Inc. To ensure the data quality from Spire Global Inc. is consistent with other RO missions, we need to quantify their accuracy and retrieval uncertainty carefully. In this work, Spire Wet Profile (wet temperature profile) data from 7 September 2021 to 31 October 2022, processed by the University Corporation for Atmospheric Research (UCAR), and COSMIC-2 (Constellation Observing System for Meteorology, Ionosphere, and Climate-2/Formosa Satellite Mission 7) data are evaluated through comparison with NOAA-20 Advanced Technology Microwave Sounder (ATMS) microwave sounder measurements and collocated RS41 radiosonde measurements. Through the Community Radiative Transfer Model (CRTM) simulation, we convert the Spire and COSMIC-2 RO retrievals to ATMS brightness temperature (BT) at sounding channels CH07 to CH14 (temperature channels), with weighting function peak heights from 8 km to 35 km, and CH19 to CH22 (water vapor channels), with weighting function peak heights ranging from 3.2 km to 6.7 km, and compare the simulations with the collocated NOAA-20 ATMS measurements over ocean. Using ATMS observations as references, Spire and COSMIC-2 BTs agree well with ATMS within 0.07 K for CH07-14 and 0.20 K for CH19-22. The trends between Spire and COSMIC-2 are consistent within 0.07 K/year over the oceans for ATMS CH07-CH13 and CH19-22, indicating that Spire/COSMIC-2 wet profiles are, in general, compatible with each other over oceans. The RO retrievals and RS41 radiosonde observation (RAOB) comparison shows that above 0.2 km altitude, RS41 RAOB matches Spire/COSMIC-2 temperature profiles well with a temperature difference of

Boron forms compounds with nearly all metals, with notable exception of copper and other group IB and IIB elements. Here, we report an unexpected discovery of ordered copper boride grown epitaxially on Cu(111) under ultrahigh vacuum. Scanning tunneling microscopy experiments combined with ab initio evolutionary structure prediction reveal a remarkably complex structure of 2D-Cu8B14. Strong intra-layer p–d hybridization and a large amount of charge transfer between Cu and B atoms are the key factors for the emergence of copper boride. This makes the discovered material unique and opens up the possibility of synthesizing ordered low-dimensional structures in similar immiscible systems.

The Advanced Baseline Imager (ABI) is the primary instrument onboard the NOAA Geostationary Operational Environmental Satellite-R Series (GOES-R) satellites, providing continuous weather imagery over the vast area in the Western Hemisphere. It is imperative to ensure consistent calibration accuracy within the instrument’s field of regard (FOR). This paper characterized the spatial uniformity in the east–west (EW) direction for the six ABI visible and near-infrared (VNIR) bands of the first two GOES-R satellites, GOES-16 (G16) and GOES-17 (G17), using a special collection of lunar chasing images during their post-launch testing and post-launch product testing (PLT/PLPT) periods. The EW response versus scan-angle (RVS) is examined with the normalized lunar irradiance ratios at varying scan angles combined from multiple lunar-chasing events. The impacts of straylight from the Earth were found in some of the B01–B03 lunar images. The straylight, including those scattered into the spacelook scenes near the polar regions and those leaked into space near the Moon, can cause RVS variation up to 1% for B01 and to a lesser magnitude for the other two bands. Straylight correction algorithms are applied for the accurate ABI lunar image irradiance calculation. After the corrections, the RVS variation is reduced to less than 0.3% for all the VNIR bands of both G16/17 in full-disk (FD) images. Results of this study also confirm that the Global Space-based Inter-Calibration System (GSICS) Implementation of the ROLO (GIRO) model has high relative accuracy for the ABI VNIR bands when the lunar images are collected within a relatively short time. The method described in this paper can be applied to validate the EW spatial uniformity for imagers on other geostationary satellites, including the recently launched GOES-18 and the future GOES-U satellites.

The γ -ray narrow-line Seyfert 1 (NLS1) galaxies can be considered to be the third class of γ -ray active galactic nuclei possessing relativistic jets. In this paper, we present multi-band high-resolution Very Long Baseline Array (VLBA) images of the γ -ray NLS1, SDSS J211852.96-073227.5 (J2118-0732, z = 0.26). We find a core-jet radio morphology and significant flux density variations in the radio core. The high brightness temperature estimated from VLBA images and core variability demonstrate that it exhibits substantial relativistic beaming effects. By considering radio emission in several bands, we find that the source has an inverted spectrum above 1 GHz but a steep spectrum at low frequencies ranging from 74 MHz–1 GHz; these may arise from the present activity and the old diffuse/extended emission, respectively. The core-jet morphology, significant flux density variations, and beaming effect make J2118-0732 resemble a blazar. Considering the low mass of its central black hole and the ongoing merger environment, J2118-0732 may represent a low-mass, low-power counterpart of blazars, and may finally evolve into a blazar.

The global navigation satellite system (GNSS) radio occultation (RO) is becoming an essential component of National Oceanic and Atmospheric Administration (NOAA) observation systems. The constellation observing system for meteorology, ionosphere, and climate (COSMIC) 2 mission and the Formosa satellite mission 7, a COSMIC follow-on mission, is now the NOAA’s backbone RO mission. The NOAA’s dedicated GNSS RO SAtellite processing and science Application Center (RO-SAAC) was established at the Center for Satellite Applications and Research (STAR). To better quantify how the observation uncertainty from clock error and geometry determination may propagate to bending angle and refractivity profiles, STAR has developed the GNSS RO data processing and validation system. This study describes the COSMIC-2 neutral atmospheric temperature and moisture profile inversion algorithms at STAR. We used RS41 and ERA5, and UCAR 1D-Var products (wetPrf2) to validate the accuracy and uncertainty of the STAR 1D-Var thermal profiles. The STAR-RS41 temperature differences are less than a few tenths of 1 K from 8 km to 30 km altitude with a standard deviation (std) of 1.5–2 K. The mean STAR-RS41 water vapor specific humidity difference and the standard deviation are −0.35 g/kg and 1.2 g/kg, respectively. We also used the 1D-Var-derived temperature and water vapor profiles to compute the simulated brightness temperature (BTs) for advanced technology microwave sounder (ATMS) and cross-track infrared sounder (CrIS) channels and compared them to the collocated ATMS and CrIS measurements. The BT differences of STAR COSMIC-2-simulated BTs relative to SNPP ATMS are less than 0.1 K over all ATMS channels.

An automatic visual scene recognition has attracted increasing attention for developing multimedia systems as it provides rich information beyond object recognition and action recognition. Each scene image often contains or is characterized by a certain of same essential objects and relations, for example, scene images of “wedding” usually have bridegroom and bride next to him. Theoretically, this kind of scene knowledge can be properly modeled by some essential objects in the scene image and with their relations for each scene class. Inspired by the observation, we proposed a novel approach to improve the accuracy of scene recognition by mining essential scene sub-graph and learning a bi-enhanced knowledge space. The essential scene sub-graph describes the essential objects and their relations for each scene class. The learned knowledge space is bi-enhanced by global representation on the entire image and local representation on the corresponding essential scene sub-graph. The experiment results in the widely used scene classification dataset Scene30 and Scene15 demonstrate the effectiveness of the proposed approach with improvements in scene recognition accuracy compared with the state-of-the-art techniques.

In this paper, we try to solve the personalized travel recommendation problem by exploiting the multi-modal data available from the real world social media, and a probabilistic graph model so called Sentiment-aware Multi-modal Topic Model (SMTM) is proposed to mine the latent semantics of the multi-modal data on the online travel website. Distinguished from previous approaches, our proposed approach try to mine the topics from tourist and attraction domains separately for disclosing semantics for tourist topics and attraction themes. In addition, we analyze tourist's sentiments on attractions to further obtain the tourist's attitude over attractions and recommend the attraction with proper sentiment on the related attraction themes accordingly. Based on the proposed SMTM model, the documents in tourist domain and in attraction domain can be compared with each other after they were projected into the mutual topic space, and this latent space projection scheme can be further applied to two personalized traveling recommendations, that is, the single platform traveling recommendation and the inter-platform traveling recommendation. Evaluation results based on the real world online travel website have shown the improved performance of our method.

In this study, we used RVUS data from RadCalNet as a benchmark to verify the radiometric accuracy and stability of operational and reprocessed SNPP/VIIRS data and the accuracy of NOAA-20/VIIRS data, as well as to assess the efficiency of the SNPP/VIIRS reprocessing algorithm. In addition, to remove the uncertainty of the RVUS site itself, we used Landsat 8/OLI as another benchmark with which to validate the accuracy and stability of VIIRS data through the RUVS site. The radiometric biases of the operational and reprocessed SNPP VIIRS bands were within ±4% and ±2%, respectively, as compared with the RUVS site and OLI, except for the M10 and M11 bands. In particular, the biases of the M5 and M7 bands were reduced by ~2% in this study. NOAA-20 VIIRS, on the other hand, was consistently lower than SNPP by ~2 to ~4% for all the bands. For the equivalent bands, the drift differences between operational and reprocessed SNPP/VIIRS and OLI were no larger than 0.24%/year and 0.1%/year, respectively. The reprocessing algorithm of SNPP VIIRS efficiently improved the radiometric accuracy and stability of the SNPP/VIIRS dataset to meet its specifications.

In recent years, Global Navigation Satellite System (GNSS) radio occultation (RO) has become a critical observation system for global operational numerical weather prediction. Constellation Observing System for Meteorology, Ionosphere, Climate (COSMIC) 2 (COSMIC-2) has been a backbone RO mission for NOAA. NOAA also began to purchase RO data from commercial sources in 2020. To ensure the consistent quality of RO data from different sources, NOAA Center for Satellite Applications and Research (STAR) has developed capabilities to process all available RO data from different missions. This paper describes the STAR RO processing systems which convert the pseudo-range and carrier phase observations to excess phases and bending angles (BAs). We compared our COSMIC-2 data products with those processed by the University Corporation for Atmospheric Research (UCAR) COSMIC Data Analysis and Archive Center (CDAAC). We processed more than twelve thousand COSMIC-2 occultation profiles. Our results show that the excess phase difference between UCAR and STAR is within a few centimeters at high altitudes, although the difference increases towards the lower atmosphere. The BA profiles derived from the excess phase are consistent with UCAR. The mean relative BA differences at impact height from 10 to 30 km are less than 0.1% for GLObal NAvigation Satellite System (GLONASS) L2C signals and Global Positioning System (GPS) L2C and L2P signals. The standard deviations are 1.15%, 1.15%, and 1.32% for GLONASS L2C signal and for GPS L2C and L2P signals, respectively. The BA profiles agree with those derived from European Center for Medium-range Weather Forecast (ECMWF) reanalysis version 5 (ERA5). The Signal-to-Noise-Ratio (SNR) plays an essential role in the processing. The STAR BA profiles with higher L1 SNRs (L1 at 80 km) tend to yield more consistent results than those from UCAR, with a negligible difference and a smaller deviation than lower SNR profiles. Profiles with lower SNR values tend to show a more significant standard deviation towards the surface during the open-loop stage in the lower troposphere than those of higher SNR. We also found that the different COSMIC-2 clock solutions could contribute to the significant relative BA difference at high altitudes; however, it has little effect on the lower troposphere comparisons given larger BA values.

Since 28 October 2011, the VIIRS Infrared Imaging Radiometer Suite (VIIRS) on the Suomi National Polar-orbiting Partnership (S-NPP) has operated over 10 years and successfully generated scientific global images for the Earth’s environment and climate studies. Besides thermal and day night bands, VIIRS has 14 reflective solar bands (RSBs) that cover a spectral range of 0.41 µm to 2.25 µm. The primary and daily source of calibration for the RSBs is the Solar Diffuser (SD) as an onboard calibrator, and its degradations are tracked by the Solar Diffuser Stability Monitor (SDSM). Alternatively, monthly scheduled lunar calibration has provided long-term on-orbit trends that validate the corresponding SD-based calibration results. In this paper, on-orbit lunar calibration and comparison results are focused on, in conjunction with the SD calibrations that are performed by the National Oceanic and Atmospheric Administration (NOAA) VIIRS team. In addition, a recent study showed that there is increasing striping in the VIIRS images in the RSBs caused by the non-uniform SD degradation. The estimation of the SD non-uniformity and a mitigation method is proposed along with the striping reductions.

The Visible Infrared Imaging Radiometer Suite (VIIRS) is a key instrument onboard the Suomi NPP (S-NPP) and the NOAA-20 satellites that provides state-of-the-art Earth observations for ocean, land, aerosol, and cloud applications. VIIRS Reflective Solar Band (RSB) Sensor Data Records (SDR, or Level 1b products) are calibrated and produced independently by The National Oceanic and Atmospheric Administration (NOAA) and the National Aeronautics and Space Administration (NASA) VIIRS science teams. Multiple versions of S-NPP and NOAA-20 VIIRS SDRs are available to date. This study evaluates the long-term calibration stability, biases, and inter-channel consistency of S-NPP and NOAA-20 VIIRS SDRs generated by NOAA and NASA over Deep Convective Clouds (DCC) to support downstream applications, especially climate data record studies. Five VIIRS RSB SDRs were analyzed in this study: (1) NOAA version 2 S-NPP VIIRS reprocessed SDRs (NOAA-NPP-V2, 2012–2020), (2) NASA Collection 1 S-NPP VIIRS SDRs (NASA-NPP-C1, 2012–2021), (3) NASA Collection 2 S-NPP VIIRS SDRs (NASA-NPP-C2, 2012–2021), (4) NOAA constant F-factor calibrated NOAA-20 VIIRS SDRs (NOAA-N20-ConstF, 2018–2021), and (5) NASA Collection 2 NOAA-20 VIIRS SDRs (NASA-N20-C2, 2018–2021). The DCC time series analysis results indicate that the calibrations of the three S-NPP VIIRS RSB SDRs are generally stable, with trends within ±0.1%/year for all RSBs, except for M3–M4 (all three S-NPP SDRs) and I3 (NASA-NPP-C1 only). The calibration of NASA-NPP-C2 SDRs is more uniform at individual detector levels. NOAA-NPP-V2 and NASA-NPP-C1 SDRs exhibit non-negligible time-dependent detector level degradation in M1–M4 (up to 1.5% in 2020–2021), causing striping in the SDR imagery. The biases between NOAA and NASA S-NPP VIIRS RSB SDRs are from 0.1% to 2.4%. The calibrations of the two NOAA-20 VIIRS RSB SDRs are also generally stable, with trends within ±0.16%/year. Small downward trends were observed in the visible and near-infrared (VIS/NIR) bands, and small upward trends were observed in the shortwave infrared (SWIR) bands for both NOAA and NASA NOAA-20 SDRs. The biases between NOAA and NASA NOAA-20 VIIRS RSB SDRs are nearly constant over time and within ±0.2% for VIS/NIR bands and ±0.7% for SWIR bands. There exists large inter-satellite biases between S-NPP and NOAA-20 VIIRS SDRs, especially in the VIS/NIR bands (up to 4.5% for NOAA SDRs and up to 7% for NASA SDRs). In addition, the DCC reflectance of S-NPP VIIRS RSB spectral bands is more consistent with that of the SCanning Imaging Absorption SpectroMeter for Atmospheric CHartographY (SCIAMACHY) than that of NOAA-20. Bands M4 and M9 seem out of family in all five S-NPP and NOAA-20 RSB SDRs evaluated.

The accuracy of brightness temperature (BT) from the Cross-track Infrared Sounder (CrIS) onboard the Suomi National Polar-orbiting Partnership (S-NPP) satellite and NOAA-20 is estimated using the Constellation Observing System for Meteorology, Ionosphere, and Climate 2 (COSMIC-2) radio occultation (RO) wet retrievals (temperature and water vapor profiles) as input to the Community Radiative Transfer Model (CRTM). The matchup criteria between RO and CrIS observations are time less than 30 min, a distance less than 50 km, and over oceans to reduce the collocation and simulation uncertainty. Based on the information provided in the CrIS and RO observations, only upper temperature sounding channels with weighting function peak height (WFPH) above 200 hPa (~12 km) from the CrIS longwave infrared (LWIR) and shortwave infrared (SWIR) bands and water vapor channels from the CrIS mid-wave infrared (MWIR) band with WFPH above 500 hPa (~6.3 km) are selected for comparison to minimize the impacts from the surface emission, cloud absorption/scattering, and atmospheric gaseous absorption. The absolute differences between CrIS observations and their CRTM simulations using RO data as input are less than 1.0 K for the majority of those selected channels. The double differences between CrIS observations on NOAA-20 and S-NPP using CRTM simulations as transfer references are very stable. They range from −0.05 K to 0.15 K for LWIR channels and −0.20 K to 0.10 K for SWIR channels during the two years from 1 October 2019 to 30 September 2021. For MWIR channels, the double differences range from −0.15 K to 0.25 K but have significant variations in both daily mean and monthly mean time series. The results provide ways to understand the qualities of RO retrieval and CrIS measurements: RO data can be used to assess the consistency and stability of CrIS observations quantitatively, and CrIS measurements have the quality to assess the quality and stability of RO retrievals.

Chronic high-altitude hypoxia (HAH) results in compensatory pathological adaptations, especially in the cardiorespiratory system. The oxygen enrichment technology can provide long-lasting oxygen supply and minimize oxygen toxicity, which has proven to be effective to increase oxygen saturation, decrease heart rate, and improve human exercise performance after ascending to high altitudes. Nevertheless, it remains unknown whether oxygen enrichment can resist chronic HAH-induced cardiorespiratory alterations. Thirty-six male rats were equally assigned to the normal control (NC), HAH, and HAH with oxygen enrichment (HAHO) groups. The HAH and HAHO rats were housed in a hypobaric hypoxia chamber equivalent to 5,000 m for 4 weeks. The HAHO rats were exposed to oxygen-enriched air for 8 h/day. We found that oxygen enrichment mitigated the augmented skin blood flow and improved the locomotor activity of HAH-exposed rats. Oxygen enrichment inhibited HAH-induced increase in the production of red blood cells (RBCs). The hemodynamic results showed that oxygen enrichment decreased right ventricular systolic pressure (RVSP) and mean pulmonary artery pressure (mPAP) in HAH-exposed rats. HAH-associated right ventricular hypertrophy and cardiomyocyte enlargement were ameliorated by oxygen enrichment. Oxygen enrichment inhibited HAH-induced excessive expression of cytokines associated with cardiac hypertrophy and myocardial fibrosis [angiotensin-converting enzyme (ACE)/angiotensin-converting enzyme 2 (ACE2), angiotensin II (Ang II), collagen type I alpha 1 (Col1α1), collagen type III alpha 1 (Col3α1), and hydroxyproline] in the right ventricle (RV). Oxygen enrichment inhibited medial thickening, stenosis and fibrosis of pulmonary arterioles, and cytokine expression related with fibrosis (Col1α1, Col3α1, and hydroxyproline) and pulmonary vasoconstriction [endothelin-1(ET-1)] in HAH-exposed rats. This study represents the first effort testing the efficacy of the oxygen enrichment technique on cardiopulmonary structure and function in chronic HAH animals, and we found oxygen enrichment has the capability of ameliorating chronic HAH-induced cardiopulmonary alterations.

The High-Resolution Infrared Radiation Sounder (HIRS) on NOAA and MetOp A/B satellites has been observing the Earth continuously for over four decades, providing essential data for operational numerical weather prediction, retrieval of atmospheric vertical profile, and total column information on atmospheric temperature, moisture, water vapor, ozone, cloud climatology, and other geophysical parameters globally. Although the HIRS data meets the needs of the short-term weather forecast, there are inconsistencies when the long-term decadal time series is used for time series analysis. The discrepancies are caused by several factors, including spectral response differences between the HIRS models on the satellites and spectral response uncertainties and other calibration issues. Previous studies have demonstrated that significant improvements can be achieved by recalibrating some of the HIRS longwave CO2 channels (Channels 4, 5, 6, and 7), which has helped make the time series more consistent. The current study aims to extend the previous study to the remaining longwave infrared sounding channels, including Channels 1, 2, 3, and 8, using a similar approach. Similar to previous findings, the spectral shift of the HIRS bands has helped improve the consistency in the time series from NOAA-06 to MetOp-A and B for these channels. We also found that HIRS channels on MetOp-B also have bias relative to Infrared Atmospheric Sounding Interferometer (IASI) on the same satellite, especially Channel 4, and a spectral shift significantly reduced the bias. To bridge the observation gap in time series in the mid-1980s between NOAA-07 and NOAA-09, the global mean method has been used since no transfer radiometers between them was available for this period, and the spectral response function corrections, therefore, can be applied to the earliest satellites (NOAA-06) for these channels. The recalibration parameters have been provided to other scientists at the University of Wisconsin for improving the time series in their long-term studies using historical HIRS data and are now made available to the science community.

Radio occultation (RO) sensor measurements have critical roles in numerical weather prediction (NWP) by complementing microwave and infrared sounder measurements with information of the atmospheric profiles at high accuracy, precision, and vertical resolution. This study evaluates Constellation Observing System for Meteorology, Ionosphere, and Climate 2 (COSMIC-2) wet temperature and humidity data products’ consistency and stability through inter-comparison with SNPP advanced technology microwave sounder (ATMS) measurements. Through the community radiative transfer model (CRTM), brightness temperature (BT) at SNPP ATMS channels are simulated with COSMIC-2 retrieved atmospheric profiles from two versions of the University Corporation for Atmospheric Research (UCAR) wet profiles (WETprf and WETpf2) as inputs to the CRTM simulation. The analysis was focused on ATMS sounding channels CH07–14 and CH19–22 with sounding weighting function peak heights from 3.2 to 35 km. The COSMIC-2 vs. ATMS inter-comparison indicates that their BT biases are consistent, and the latitudinal difference is

The Global Navigation Satellite System (GNSS) radio occultation (RO) is a remote sensing technique that uses International System of Units (SI) traceable GNSS signals for atmospheric limb soundings. The RO bending angle/sounding profiles are needed for assimilation in Numerical Weather Prediction (NWP) models, weather, climate, and space weather applications. Evaluating these RO data to ensure the high data quality for these applications is becoming more and more critical. This study presents a method for predicting radio occultation events, from which simultaneous radio occultation (SRO) for a pair of low-Earth-orbit (LEO) satellites on the limb to the same GNSS satellite can be obtained. The SRO method complements the Simultaneous Nadir Overpass (SNO) method (for nadir viewing satellite instruments), which has been widely used to inter-calibrate LEO to LEO and LEO to geosynchronous-equatorial-orbit (GEO) satellites. Unlike the SNO method, the SRO method involves three satellites: a GNSS and two LEO satellites with RO receivers. The SRO method allows for the direct comparison of bending angles when the simultaneous RO measurements for two LEO satellites receiving the same GNSS signal pass through approximately the same atmosphere within minutes in time and within less than 200 km of distance from each other. The prediction method can also be applied to radiosonde overpass prediction, and coordinate radiosonde launches for inter-comparisons between RO and radiosonde profiles. The main advantage of the SRO comparisons of bending angles is the significantly reduced uncertainties due to the much shorter time and smaller atmospheric path differences than traditional RO comparisons. To demonstrate the usefulness of this method, we present a comparison of the Constellation Observing System for Meteorology, Ionosphere, and Climate-2 (COSMIC-2) and GeoOpitcs RO profiles using SRO data for two time periods: Commercial Weather Data (CWD) data delivery order-1 (DO-1): 15 December 2020–15 January 2021 and CWD DO-2: 17 March 2021–31 August 2021. The results show good agreement in the bending angles between the COSMIC-2 RO measurements and those from GeoOptics, although systematic biases are also found in the inter-comparisons. Instrument and processing algorithm performances for the signal-to-noise ratio (SNR), penetration height, and bending angle retrieval uncertainty are also characterized. Given the efficiency of this method and the many RO measurements that are publicly and commercially available as well as the expansion of receiver capabilities to all GNSS systems, it is expected that this method can be used to validate/inter-calibrate GNSS RO measurements from different missions.

In this study, we validated the consistency of the GRUAN RS92 and RS41 datasets, versions EDT.1 and GDP.2, in the upper troposphere and lower stratosphere (200–20 hPa), through dual launch campaigns at the GRUAN site and using the radio occultation (RO) product and the ERA5 reanalysis from ECMWF as standards for double difference comparison. Separate comparisons with the references were also performed in order to trace the origin of the bias between the two instruments. Then, the performance of the GRUAN raw temperature correction algorithm was evaluated, from the aspects of day–night, the solar zenith angle, and the pressure level, for GDP.2 version products. The results show that RS92.EDT.1 has a warm bias of 0.355 K, compared to RS41.EDT.1, at 20 hPa, during daytime. This bias was found to mainly originate from RS92.EDT.1, based on the separate comparison with RO or ECMWF ERA5 data. RS92.GDP.2 is consistent with RS41.GDP.2, but a separate comparison indicated that the two original GDP.2 products have a ~1 K warm bias at 20 hPa during daytime, compared with RO or ECMWF ERA5 data. The GRUAN correction method can reduce the warm bias up to 0.5 K at 20 hPa during daytime. As a result, this GRUAN correction method is efficient, and it is dependent on the solar zenith angle and pressure level.

Due to complex radiometric calibration, the imagery collected by the Day/Night Band (DNB) of the Visible Infrared Imaging Radiometer Suite (VIIRS) onboard the Suomi National Polar Partnership (Suomi-NPP) and the NOAA-20 follow-on satellite is subject to artifacts such as striping, which eventually affect Earth remote sensing applications. Through comprehensive analysis using the NOAA-20 VIIRS DNB prelaunch-test and on-orbit data, it is revealed that the striping results from flaws in the calibration process. In particular, a discrepancy between the low-gain stage (LGS) Earth view (EV) gain and the onboard calibrator solar diffuser view gain makes the operational LGS gain coefficients of a few aggregation modes and detectors biased. Detector nonlinearity at low radiance level also induces errors to the mid-gain stage (MGS) and high-gain stage (HGS) gain through the biased gain ratios. These systematic errors are corrected by scaling the operational LGS gains using the factors derived from the NOAA-20 VIIRS DNB prelaunch test data and by adopting linear regression for evaluating the gain ratios. Striping in the NOAA-20 VIIRS DNB imagery is visibly reduced after the upgraded gain calibration process was implemented in the operational calibration.

An analytical model for hole boring proton acceleration by a circularly-polarized CO2 laser pulse in a gas jet is developed. The plasma density profile near the density peak is taken to be rectangular, with inner region thickness l around a laser wavelength and density 10% above the critical, while the outside density is 10% below the critical. On the rear side, plasma density falls off rapidly to a small value. The laser suffers strong reflection from the central region and, at normalized amplitude a0≥1, creates a double layer. The space charge field of the double layer, moving with velocity vfz^, reflects up-stream protons to 2vf velocity, incurring momentum loss at a rate comparable to radiation pressure. Reflection occurs for vf≤ωpzflm/mp, where m and mp are the electron and proton masses, zf is the distance traveled by the compressed electron layer and ωp is the plasma frequency. For Gaussian temporal profile of the laser and parabolic density profile of the upstream plasma, the proton energy distribution is narrowly peaked.

Suomi NPP has been successfully operating since its launch on 28 October 2011. As one of the major payloads, along with microwave and infrared sounders (Advanced Technology Microwave Sounder (ATMS), Cross-track Infrared Sounder (CrIS)), and ozone mapping/profiling (OMPS) instruments, the Visible Infrared Imaging Radiometer Suite (VIIRS) has performed for well beyond its mission design life. Its data have been used for a variety of applications for nearly 30 environmental data products, including global imagery twice daily with 375 and 750 m resolutions, clouds, aerosol, cryosphere, ocean color and sea-surface temperature, a number of land products (vegetation, land-cover, fire and others), and geophysical and social economic studies with nightlights. During the early days of VIIRS operational calibration and data production, there were inconsistencies in both algorithms and calibration inputs, for several reasons. While these inconsistencies have less impact on nowcasting and near real-time applications, they introduce challenges for time series analysis due to calibration artifacts. To address this issue, we developed a comprehensive algorithm, and recalibrated and reprocessed the Suomi NPP VIIRS radiometric data that have been produced since the launch. In the recalibration, we resolved inconsistencies in the processing algorithms, terrain correction, straylight correction, and anomalies in the thermal bands. To improve the stability of the reflective solar bands, we developed a Kalman filtering model to incorporate onboard solar, lunar, desert site, inter-satellite calibration, and a deep convective cloud calibration methodology. We further developed and implemented the Solar Diffuser Surface Roughness Rayleigh Scattering model to account for the sensor responsivity degradation in the near infrared bands. The recalibrated dataset was validated using vicarious sites and alternative methods, and compared with independent processing from other organizations. The recalibrated radiometric dataset (namely, the level 1b or sensor data records) also incorporates a bias correction for the reflective solar bands, which not only addresses known calibration biases, but also allows alternative calibrations to be applied if so desired. The recalibrated data have been proven to be of high quality, with much improved stability (better than 0.3%) and accuracy (by up to 2%). The recalibrated radiance data are now available from 2012 to 2020 for users and will eventually be archived on the NOAA CLASS database.

A COSMIC-1/FORMOSAT-3 (Constellation Observing System for Meteorology, Ionosphere, and Climate-1 and Formosa Satellite Mission 3) follow-on mission, COSMIC-2/FORMOSAT-7, had been successfully launched into low-inclination orbits on 25 June 2019. COSMIC-2 has a significantly increased Signal-to-Noise ratio (SNR) compared to other Radio Occultation (RO) missions. This study summarized the initial assessment of COSMIC-2 data quality conducted by the NOAA (National Oceanic and Atmospheric Administration) Center for Satellite Applications and Research (STAR). We use validated data from other RO missions to quantify the stability of COSMIC-2. In addition, we use the Vaisala RS41 radiosonde observations to assess the accuracy and uncertainty of the COSMIC-2 neutral atmospheric profiles. RS41 is currently the most accurate radiosonde observation system. The COSMIC-2 SNR ranges from 200 v/v to about 2800 v/v. To see if the high SNR COSMIC-2 signals lead to better retrieval results, we separate the COSMIC-2–RS41 comparisons into different SNR groups (i.e., 0–500 v/v group, 500–1000 v/v group, 1000–1500 v/v group, 1500–2000 v/v group, and >2000 v/v group). In general, the COSMIC-2 data quality in terms of stability, precision, accuracy, and uncertainty of the accuracy is very compatible with those from COSMIC-1. Results show that the mean COSMIC-2–RS41 water vapor difference from surface to 5 km altitude for each SNR groups are equal to −1.34 g/kg (0–500 v/v), −1.17 g/kg (500–1000 v/v), −1.33 g/kg (1000–1500 v/v), −0.93 g/kg (1500–2000 v/v), and −1.52 g/kg (>2000 v/v). Except for the >2000 v/v group, the high SNR measurements from COSMIC-2 seem to improve the mean water vapor difference for the higher SNR group slightly (especially for the 1500–2000 v/v group) comparing with those from lower SNR groups.

The launch of the National Oceanic and Atmospheric Administration (NOAA)/ National Aeronautics and Space Administration (NASA) Suomi National Polar-orbiting Partnership (S-NPP) and its follow-on NOAA Joint Polar Satellite Systems (JPSS) satellites marks the beginning of a new era of operational satellite observations of the Earth and atmosphere for environmental applications with high spatial resolution and sampling rate. The S-NPP and JPSS are equipped with five instruments, each with advanced design in Earth sampling, including the Advanced Technology Microwave Sounder (ATMS), the Cross-track Infrared Sounder (CrIS), the Ozone Mapping and Profiler Suite (OMPS), the Visible Infrared Imaging Radiometer Suite (VIIRS), and the Clouds and the Earth’s Radiant Energy System (CERES). Among them, the ATMS is the new generation of microwave sounder measuring temperature profiles from the surface to the upper stratosphere and moisture profiles from the surface to the upper troposphere, while CrIS is the first of a series of advanced operational hyperspectral sounders providing more accurate atmospheric and moisture sounding observations with higher vertical resolution for weather and climate applications. The OMPS instrument measures solar backscattered ultraviolet to provide information on the concentrations of ozone in the Earth’s atmosphere, and VIIRS provides global observations of a variety of essential environmental variables over the land, atmosphere, cryosphere, and ocean with visible and infrared imagery. The CERES instrument measures the solar energy reflected by the Earth, the longwave radiative emission from the Earth, and the role of cloud processes in the Earth’s energy balance. Presently, observations from several instruments on S-NPP and JPSS-1 (re-named NOAA-20 after launch) provide near real-time monitoring of the environmental changes and improve weather forecasting by assimilation into numerical weather prediction models. Envisioning the need for consistencies in satellite retrievals, improving climate reanalyses, development of climate data records, and improving numerical weather forecasting, the NOAA/Center for Satellite Applications and Research (STAR) has been reprocessing the S-NPP observations for ATMS, CrIS, OMPS, and VIIRS through their life cycle. This article provides a summary of the instrument observing principles, data characteristics, reprocessing approaches, calibration algorithms, and validation results of the reprocessed sensor data records. The reprocessing generated consistent Level-1 sensor data records using unified and consistent calibration algorithms for each instrument that removed artificial jumps in data owing to operational changes, instrument anomalies, contaminations by anomaly views of the environment or spacecraft, and other causes. The reprocessed sensor data records were compared with and validated against other observations for a consistency check whenever such data were available. The reprocessed data will be archived in the NOAA data center with the same format as the operational data and technical support for data requests. Such a reprocessing is expected to improve the efficiency of the use of the S-NPP and JPSS satellite data and the accuracy of the observed essential environmental variables through either consistent satellite retrievals or use of the reprocessed data in numerical data assimilations.

This paper shows that the state of the magnetosphere, resulting from continuous but variable forcing of the solar wind and the interplanetary magnetic field (IMF), can be empirically specified by a magnetospheric state vector Ψ, consisting of a set of hourly-averaged magnetospheric driver and response parameters. It is demonstrated that there exists a correspondence between the magnetospheric driver and multiple geomagnetic response parameters. This parameter correspondence allows different magnetopsheric states to be specified by means of a look-up table, provided that the relative time lags between various driver (e.g. Vsw, IMF) and response parameters (e.g. Kp, Dst, and AE) are taken into account. Using the magnetospheric state specifications, multi-scale geomagnetic responses can then be simultaneously prescribed statistically from their corresponding driver parameters. Magnetospheric state specifications have been determined by using magnetospheric state parameter data taken in 1970–2000. Their validities have been tested by specifying the multi-geomagnetic responses over three representative intervals: (1) a magnetic cloud event, (2) a period of multiple storms, and (3) the years of 2001 and 2002. For all the intervals, we have found good correlation (with r>0.75) between the prescribed and observed geomagnetic indices at hourly resolution, and the magnetospheric state specifications are thus validated.

The Visible Infrared Imaging Radiometer Suite (VIIRS) onboard Suomi National Polar Orbiting Partnership (SNPP) uses a solar diffuser (SD) as its radiometric calibrator for the reflective solar band calibration. The SD is made of Spectralon™ (one type of fluoropolymer) and was chosen because of its controlled reflectance in the Visible/Near-Infrared/Shortwave-Infrared region and its near-Lambertian reflectance property. On-orbit changes in VIIRS SD reflectance as monitored by the Solar Diffuser Stability Monitor showed faster degradation of SD reflectance for 0.4 to 0.6 µm channels than the longer wavelength channels. Analysis of VIIRS SD reflectance data show that the spectral dependent degradation of SD reflectance in short wavelength can be explained with a SD Surface Roughness (length scale << wavelength) based Rayleigh Scattering (SRRS) model due to exposure to solar UV radiation and energetic particles. The characteristic length parameter of the SD surface roughness is derived from the long term reflectance data of the VIIRS SD and it changes at approximately the tens of nanometers level over the operational period of VIIRS. This estimated roughness length scale is consistent with the experimental result from radiation exposure of a fluoropolymer sample and validates the applicability of the Rayleigh scattering-based model. The model is also applicable to explaining the spectral dependent degradation of the SDs on other satellites. This novel approach allows us to better understand the physical processes of the SD degradation, and is complementary to previous mathematics based models.

The radiometric calibration equations for the thermal emissive bands (TEB) and the reflective solar bands (RSB) measurements of the earth scenes by the polar satellite sensors, (Terra and Aqua) MODIS and Suomi NPP (VIIRS), and geostationary sensors, GOES Imager and the GOES-R Advanced Baseline Imager (ABI) are analyzed towards calibration algorithm harmonization on the basis of SI traceability which is one of the goals of the NOAA National Calibration Center (NCC). One of the overarching goals of NCC is to provide knowledge base on the NOAA operational satellite sensors and recommend best practices for achieving SI traceability for the radiance measurements on-orbit. As such, the calibration methodologies of these satellite optical sensors are reviewed in light of the recommended practice for radiometric calibration at the National Institute of Standards and Technology (NIST). The equivalence of some of the spectral bands in these sensors for their end products is presented. The operational and calibration features of the sensors for on-orbit observation of radiance are also compared in tabular form. This review is also to serve as a quick cross reference to researchers and analysts on how the observed signals from these sensors in space are converted to radiances.

Nighttime light imagery offers a unique view of the Earth’s surface. In the past, the nighttime light data collected by the DMSP-OLS sensors have been used as an efficient means to correlate regional and global socio-economic activities. With the launch of the Suomi National Polar-orbiting Partnership (Suomi-NPP) satellite in 2011, the day-night band (DNB) of the Visible Infrared Imaging Radiometer Suite (VIIRS) onboard represents a major advancement in nighttime imaging capabilities, because it surpasses its predecessor DMSP-OLS in radiometric accuracy, spatial resolution and geometric quality. In this paper, four variables (total night light, light area, average night light and log average night light) are extracted from nighttime radiance data observed by the VIIRS-DNB composite in 2013 and nighttime digital number (DN) data from the DMSP-OLS stable dataset in 2012, respectively, and correlated with 12 socio-economic parameters at the provincial level in mainland China during the corresponding period. Background noise of DNB composite data is removed using either a masking method or an optimal threshold method. In general, the correlation of these socio-economic data with the total night light and light area of VIIRS-DNB composite data is better than with the DMSP-OLS stable data. The correlations between total night light of denoised DNB composite data and built-up area, gross regional product (GRP) and power consumption are higher than 0.9 and so are the correlations between the light area of denoised DNB composite data and city and town population, built-up area, GRP, power consumption and waste water discharge. However, the correlations of socio-economic data with the average night light and log average night light of VIIRS-DNB composite data are not as good as with the DMSP-OLS stable data. To quantitatively analyze the reasons for the correlation difference, a cubic regression method is developed to correct the saturation effect of the DMSP stable data, and we artificially convert the pixel value of the DNB composite into six bits to match the DMSP stable data format. The correlation results between the processed data and socio-economic data show that the effects of saturation and quantization are two of the reasons for the correlation difference. Additionally, on this basis, we estimate the total night light ratio between saturation-corrected DMSP stable data and finite quantization DNB composite data, and it is found that the ratio is ~11.28 ± 4.02 for China. Therefore, it appears that a different acquisition time is the other reason for the correlation difference.

The Suomi NPP (S-NPP) Visible Infrared Imaging Radiometer Suite (VIIRS) performs the scheduled lunar roll maneuver on a monthly basis. The lunar calibration coefficients and lunar F-factor are calculated by taking the ratio of the lunar observed radiance to the simulated radiance from the Miller and Turner (MT) lunar model. The lunar F-factor is also validated against that derived from the VIIRS Solar Diffuser (SD). The MT model-based lunar F-factors in general agree with SD F-factors. The Lunar Band Ratio (LBR) is also derived from two channel lunar radiances and is implemented in the National Oceanic and Atmospheric Administration (NOAA) Integrated Calibration and Validation System (ICVS) to monitor the VIIRS long-term radiometric performance. The lunar radiances at pixels are summed for each of the VIIRS Reflective Solar Bands (RSBs) and normalized by the reference band M11 which has the most stable SD-based calibration coefficient. LBRs agree with the SD based F-factor ratios within one percent. Based on analysis with these two independent lunar calibration methods, SD-based and LBR-based calibrations show a lifetime consistency. Thus, it is recommended that LBR be used for both VIIRS radiometric calibration and lifetime stability monitoring.

We present a theoretical and numerical study of a novel acceleration scheme by applying a combination of laser radiation pressure and shielded Coulomb repulsion in laser acceleration of protons in multi-species gaseous targets. By using a circularly polarized CO _2 laser pulse with a wavelength of 10 μ m—much greater than that of a Ti: Sapphire laser—the critical density is significantly reduced, and a high-pressure gaseous target can be used to achieve an overdense plasma. This gives us a larger degree of freedom in selecting the target compounds or mixtures, as well as their density and thickness profiles. By impinging such a laser beam on a carbon–hydrogen target, the gaseous target is first compressed and accelerated by radiation pressure until the electron layer disrupts, after which the protons are further accelerated by the electron-shielded carbon ion layer. An 80 MeV quasi-monoenergetic proton beam can be generated using a half-sine shaped laser beam with a peak power of 70 TW and a pulse duration of 150 wave periods.