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Earth radiation budget (ERB) satellite observations require conversion of the measured radiance, which is a remotely sensed quantity, to a derived irradiance, which is the relevant energy balance quantity routinely used in modeling and analysis of the climate system. The state-of-the-art approach for radiance-to-irradiance conversion taken by the Clouds and the Earth's Radiant Energy System (CERES) benefits from the exhaustive sampling of radiance anisotropy by multiple CERES instruments across many years. Unfortunately, the CERES approach is not easily extended to new ERB spectral channels that lack previous sampling, such as the “split-shortwave” planned to be part of the next-generation ERB mission Libera. As an alternative approach, the capability of a monochromatic, wide-field-of-view camera to provide dense angular sampling in a much shorter time frame is assessed. We present a general concept for how this can be achieved and quantify the proficiency of a camera to provide rapid angular distribution model (ADM) generation for the new Libera ultraviolet and visible (VIS) sub-band. A single mid-visible camera wavelength (555 nm) is shown to be ideal for representing the VIS sub-band, requiring only basic scene stratification for 555 nm to VIS conversion. Synthetic camera sampling with realistic operating constraints also demonstrates that the angular radiance field of various scenes can be well populated within a single day of sampling, a notable advance over existing approaches. These results provide a path for generating observationally based VIS ADMs with minimal lag time following Libera's launch. Coupled with efforts to utilize a camera for scene identification, this may also pave the way for future ERB satellite systems to develop stand-alone irradiance products for arbitrary sets of spectral channels, opening up new measurement and science possibilities.

Breast cancer prevention only requires local exposure of the breast to active drug. However, oral preventive agents entail systemic exposure, causing adverse effects that limit acceptance by high-risk women. Drug-delivery through the breast skin is an attractive option, but requires demonstration of dermal safety and drug distribution throughout the breast. We formulated the tamoxifen metabolite (E/Z)-endoxifen for transdermal delivery and tested it in a placebo-controlled, double-blinded Phase I trial with dose escalation from 10 to 20 mg daily. The primary endpoint was dermal toxicity. Thirty-two women planning mastectomy were randomized (2:1) to endoxifen-gel or placebo-gel applied to both breasts for 3–5 weeks. Both doses of endoxifen-gel incurred no dermal or systemic toxicity compared to placebo. All endoxifen-treated breasts contained the drug at each of five sampling locations; the median per-person tissue concentration in the treated participants was 0.6 ng/g (IQR 0.4–1.6), significantly higher (p

The first implementation of NASA’s Total and Spectral Solar Irradiance Sensor (TSIS-1) launched on December 15th, 2017, and was integrated into the International Space Station (ISS) to measure both the total solar irradiance (TSI) and the solar spectral irradiance (SSI). The direct measurement of the SSI is made by the LASP Spectral Irradiance Monitor (SIM) and provides data essential to interpreting how the Earth system responds to solar spectral variability. Extensive advances in TSIS-1 SIM instrument design and new SI-traceable spectral irradiance calibration techniques have resulted in improved absolute accuracy with uncertainties of less than 0.5% over the continuous 200–2400 nm spectral range. Furthermore, improvements in the long-term spectral stability corrections provide lower trend uncertainties in SSI variability measurements. Here we present the early results of the TSIS-1 SIM measurements covering the first 5 years of operations. This time period includes the descending phase of solar cycle 24, the last solar minimum, and the ascending phase of solar cycle 25. The TSIS-1 SIM SSI results are compared to previous measurements both in the absolute scale of the solar spectrum and the time dependence of the SSI variability. The TSIS-1 SIM SSI spectrum shows lower IR irradiance (up to 6% at 2400 nm) and small visible increases (~0.5%) from some previous reference solar spectra. Finally, initial comparisons are made to current NRLSSI2 and SATIRE-S SSI model results and offer opportunities to validate model details both for short-term (solar rotation) spectral variability and, for the first time, the longer-term (near half solar cycle) spectral variability across the solar spectrum from the UV to the IR.

Abstract This work describes two achievements to a key data set. First, we present version 2 of the Total and Spectral Solar Irradiance Sensor‐1 Hybrid Solar Reference Spectrum (TSIS‐1 HSRS), which has recently been recognized as a new solar irradiance reference standard (https://calvalportal.ceos.org/). Second, we present a new “full spectrum extension” of the TSIS‐1 HSRS. The TSIS‐1 HSRS observational composite solar irradiance reference spectrum spans 0.202–2.730 μm and encompasses more than 97% of the energy in the total solar irradiance (TSI). Version 2 is an incremental update that corrects the radiometric baseline between 0.202 and 0.210 μm and updates the solar lines at wavelengths longward of 0.743 μm to those listed in the most recent database. The full spectrum extension builds off version 2 of the TSIS‐1 HSRS and supports applications that require a solar spectrum encompassing nearly 100% of the energy in the TSI. It spans 0.115–200 μm and was developed by incorporating additional observations and theoretical knowledge where no direct observations currently exist.

Aerosol heating due to shortwave absorption has implications for local atmospheric stability and regional dynamics. The derivation of heating rate profiles from space-based observations is challenging because it requires the vertical profile of relevant properties such as the aerosol extinction coefficient and single-scattering albedo (SSA). In the southeastern Atlantic, this challenge is amplified by the presence of stratocumulus clouds below the biomass burning plume advected from Africa, since the cloud properties affect the magnitude of the aerosol heating aloft, which may in turn lead to changes in the cloud properties and life cycle. The combination of spaceborne lidar data with passive imagers shows promise for future derivations of heating rate profiles and curtains, but new algorithms require careful testing with data from aircraft experiments where measurements of radiation, aerosol, and cloud parameters are better colocated and readily available. In this study, we derive heating rate profiles and vertical cross sections (curtains) from aircraft measurements during the NASA ObseRvations of Aerosols above CLouds and their intEractionS (ORACLES) project in the southeastern Atlantic. Spectrally resolved irradiance measurements and the derived column absorption allow for the separation of total heating rates into aerosol and gas (primarily water vapor) absorption. The nine cases we analyzed capture some of the co-variability of heating rate profiles and their primary drivers, leading to the development of a new concept: the heating rate efficiency (HRE; the heating rate per unit aerosol extinction). HRE, which accounts for the overall aerosol loading as well as vertical distribution of the aerosol layer, varies little with altitude as opposed to the standard heating rate. The large case-to-case variability for ORACLES is significantly reduced after converting from heating rate to HRE, allowing us to quantify its dependence on SSA, cloud albedo, and solar zenith angle.

Abstract This study evaluated the comparative entropy represented in shortwave (300–1,750 nm) passive remote sensing measurements from conceptual instruments with varying systematic measurement uncertainties and spectral resolutions. The focus was on spectral and broadband reflectance averaged over large spatial scales typically relevant for climate change studies. Information theory was applied to quantify how the normalized Shannon entropy changed for different conceptual instruments and over different spatial scales. Reflectance measurements from the Scanning Imaging Absorption Spectrometer for Atmospheric Cartography (SCIAMACHY) were used to represent the observed reflectance, and simulated reflectance from climate Observing System Simulations Experiments (OSSEs) were used to represent decadal‐ and centennial‐length data sets free from instrument artifacts. Similar to previous studies, the simulated OSSE spectra were shown to be a sufficient proxy for the observed reflectance. As hypothesized, the normalized entropy decreased with increasing measurement uncertainty and increasing spectral bandwidth. Additionally, the entropy decreased for increasingly large spatial scales, particularly for measurement uncertainties larger than 2%. When applied to OSSE reflectance simulated from a forced CMIP3 climate model simulation, the change in entropy with measurement uncertainty and spectral resolution provided insight into measurement attributes needed to monitor a changing climate system and highlighted the importance of sufficiently high accuracy and spectral resolution for detecting and attributing climate trends. These preliminary studies illustrate the value of this information theory‐based framework in instrument design by calculating the entropy, used to represent information in measurements from different conceptual instruments.

Cloud optical properties such as optical thickness along with surface albedo are important inputs for deriving the shortwave radiative effects of clouds from spaceborne remote sensing. Owing to insufficient knowledge about the snow or ice surface in the Arctic, cloud detection and the retrieval products derived from passive remote sensing, such as from the Moderate Resolution Imaging Spectroradiometer (MODIS), are difficult to obtain with adequate accuracy – especially for low-level thin clouds, which are ubiquitous in the Arctic. This study aims at evaluating the spectral and broadband irradiance calculated from MODIS-derived cloud properties in the Arctic using aircraft measurements collected during the Arctic Radiation-IceBridge Sea and Ice Experiment (ARISE), specifically using the upwelling and downwelling shortwave spectral and broadband irradiance measured by the Solar Spectral Flux Radiometer (SSFR) and the BroadBand Radiometer system (BBR). This starts with the derivation of surface albedo from SSFR and BBR, accounting for the heterogeneous surface in the marginal ice zone (MIZ) with aircraft camera imagery, followed by subsequent intercomparisons of irradiance measurements and radiative transfer calculations in the presence of thin clouds. It ends with an attribution of any biases we found to causes, based on the spectral dependence and the variations in the measured and calculated irradiance along the flight track. The spectral surface albedo derived from the airborne radiometers is consistent with prior ground-based and airborne measurements and adequately represents the surface variability for the study region and time period. Somewhat surprisingly, the primary error in MODIS-derived irradiance fields for this study stems from undetected clouds, rather than from the retrieved cloud properties. In our case study, about 27 % of clouds remained undetected, which is attributable to clouds with an optical thickness of less than 0.5. We conclude that passive imagery has the potential to accurately predict shortwave irradiances in the region if the detection of thin clouds is improved. Of at least equal importance, however, is the need for an operational imagery-based surface albedo product for the polar regions that adequately captures its temporal, spatial, and spectral variability to estimate cloud radiative effects from spaceborne remote sensing.

As the proportion of women diagnosed with invasive breast cancer increases, the role of imaging for staging and surveillance purposes should be determined based on evidence-based guidelines. It is important to understand the indications for extent of disease evaluation and staging, as unnecessary imaging can delay care and even result in adverse outcomes. In asymptomatic patients that received treatment for curative intent, there is no role for imaging to screen for distant recurrence. Routine surveillance with an annual 2-D mammogram and/or tomosynthesis is recommended to detect an in-breast recurrence or a new primary breast cancer in women with a history of breast cancer, and MRI is increasingly used as an additional screening tool in this population, especially in women with dense breasts. The American College of Radiology Appropriateness Criteria are evidence-based guidelines for specific clinical conditions that are reviewed annually by a multidisciplinary expert panel. The guideline development and revision process support the systematic analysis of the medical literature from peer reviewed journals. Established methodology principles such as Grading of Recommendations Assessment, Development, and Evaluation or GRADE are adapted to evaluate the evidence. The RAND/UCLA Appropriateness Method User Manual provides the methodology to determine the appropriateness of imaging and treatment procedures for specific clinical scenarios. In those instances where peer reviewed literature is lacking or equivocal, experts may be the primary evidentiary source available to formulate a recommendation. [ABSTRACT FROM AUTHOR]

Southern Africa produces almost a third of the Earth's biomass burning (BB) aerosol particles, yet the fate of these particles and their influence on regional and global climate is poorly understood. ORACLES (ObseRvations of Aerosols above CLouds and their intEractionS) is a 5-year NASA EVS-2 (Earth Venture Suborbital-2) investigation with three intensive observation periods designed to study key atmospheric processes that determine the climate impacts of these aerosols. During the Southern Hemisphere winter and spring (June–October), aerosol particles reaching 3–5 km in altitude are transported westward over the southeast Atlantic, where they interact with one of the largest subtropical stratocumulus (Sc) cloud decks in the world. The representation of these interactions in climate models remains highly uncertain in part due to a scarcity of observational constraints on aerosol and cloud properties, as well as due to the parameterized treatment of physical processes. Three ORACLES deployments by the NASA P-3 aircraft in September 2016, August 2017, and October 2018 (totaling ∼350 science flight hours), augmented by the deployment of the NASA ER-2 aircraft for remote sensing in September 2016 (totaling ∼100 science flight hours), were intended to help fill this observational gap. ORACLES focuses on three fundamental science themes centered on the climate effects of African BB aerosols: (a) direct aerosol radiative effects, (b) effects of aerosol absorption on atmospheric circulation and clouds, and (c) aerosol–cloud microphysical interactions. This paper summarizes the ORACLES science objectives, describes the project implementation, provides an overview of the flights and measurements in each deployment, and highlights the integrative modeling efforts from cloud to global scales to address science objectives. Significant new findings on the vertical structure of BB aerosol physical and chemical properties, chemical aging, cloud condensation nuclei, rain and precipitation statistics, and aerosol indirect effects are emphasized, but their detailed descriptions are the subject of separate publications. The main purpose of this paper is to familiarize the broader scientific community with the ORACLES project and the dataset it produced.

In this paper, we use observations from the NASA ORACLES (ObseRvations of CLouds above Aerosols and their intEractionS) aircraft campaign to develop a framework by way of two parameterizations that establishes regionally representative relationships between aerosol-cloud properties and their radiative effects. These relationships rely on new spectral aerosol property retrievals of the single scattering albedo (SSA) and asymmetry parameter (ASY). The retrievals capture the natural variability of the study region as sampled, and both were found to be fairly narrowly constrained (SSA: 0.83 ± 0.03 in the mid-visible, 532 nm; ASY: 0.54 ± 0.06 at 532 nm). The spectral retrievals are well suited for calculating the direct aerosol radiative effect (DARE) since SSA and ASY are tied directly to the irradiance measured in the presence of aerosols – one of the inputs to the spectral DARE. The framework allows for entire campaigns to be generalized into a set of parameterizations. For a range of solar zenith angles, it links the broadband DARE to the mid-visible aerosol optical depth (AOD) and the albedo (α) of the underlying scene (either clouds or clear sky) by way of the first parameterization: P(AOD, α). For ORACLES, the majority of the case-to-case variability of the broadband DARE is attributable to the dependence on the two driving parameters of P(AOD, α). A second, extended, parameterization PX(AOD, α, SSA) explains even more of the case-to-case variability by introducing the mid-visible SSA as a third parameter. These parameterizations establish a direct link from two or three mid-visible (narrowband) parameters to the broadband DARE, implicitly accounting for the underlying spectral dependencies of its drivers. They circumvent some of the assumptions when calculating DARE from satellite products or in a modeling context. For example, the DARE dependence on aerosol microphysical properties is not explicit in P or PX because the asymmetry parameter varies too little from case to case to translate into appreciable DARE variability. While these particular DARE parameterizations only represent the ORACLES data, they raise the prospect of generalizing the framework to other regions.

Abstract Background Racial disparities in breast cancer survival between Black and White women persist across all stages of breast cancer. The metabolic syndrome (MetS) of insulin resistance disproportionately affects more Black than White women. It has not been discerned if insulin resistance mediates the link between race and poor prognosis in breast cancer. We aimed to determine whether insulin resistance mediates in part the association between race and breast cancer prognosis, and if insulin receptor (IR) and insulin-like growth factor receptor (IGF-1R) expression differs between tumors from Black and White women. Methods We conducted a cross-sectional, multi-center study across ten hospitals. Self-identified Black women and White women with newly diagnosed invasive breast cancer were recruited. The primary outcome was to determine if insulin resistance, which was calculated using the homeostatic model assessment of insulin resistance (HOMA-IR), mediated the effect of race on prognosis using the multivariate linear mediation model. Demographic data, anthropometric measurements, and fasting blood were collected. Poor prognosis was defined as a Nottingham Prognostic Index (NPI) > 4.4. Breast cancer pathology specimens were evaluated for IR and IGF-1R expression by immunohistochemistry (IHC). Results Five hundred fifteen women were recruited (83% White, 17% Black). The MetS was more prevalent in Black women than in White women (40% vs 20%, p 1: 4.2 ± 0.8 vs IR/IGF-1R = 1: 3.9 ± 0.8 vs IR/IGF-1R

The stability and longevity of the Ozone Monitoring Instrument (OMI), flying on board the (active) Aura Earth‐observing satellite since July 2004, facilitates creation of accurate, long‐term record of relative (normalized to a solar minimum) solar spectral irradiances (SSIs). Here we discuss technical details of the most recent version (V3) of the SSI product that provides approximately daily measurements for the period July 2006 to April 2018 in the 265‐ to 500‐nm domain with average 0.5‐nm resolution. We compare OMI SSIs with concurrent independent observations and model estimates. The short‐term (solar rotational cycle) observations and model predictions mostly agree to ∼0.1–0.2% in the ultraviolet domain, with an excellent, down to ∼0.01% agreement in the visible range. The long‐term (solar cycle) comparisons pose more challenges in the ultraviolet domain, where the differences between observations and models frequently exceed the rather conservative ∼0.1% (both point‐to‐point and long‐term) OMI uncertainties. In the visible range, these differences gradually diminish to

Determining the direct aerosol radiative effect (DARE) of absorbing aerosols above clouds from satellite observations alone is a challenging task, in part because the radiative signal of the aerosol layer is not easily untangled from that of the clouds below. In this study, we use aircraft measurements from the NASA ObseRvations of CLouds above Aerosols and their intEractionS (ORACLES) project in the southeastern Atlantic to derive it with as few assumptions as possible. This is accomplished by using spectral irradiance measurements (Solar Spectral Flux Radiometer, SSFR) and aerosol optical depth (AOD) retrievals (Spectrometer for Sky-Scanning, Sun-Tracking Atmospheric Research, 4STAR) during vertical profiles (spirals) that minimize the albedo variability of the underlying cloud field – thus isolating aerosol radiative effects from those of the cloud field below. For two representative cases, we retrieve spectral aerosol single scattering albedo (SSA) and the asymmetry parameter (g) from these profile measurements and calculate DARE given the albedo range measured by SSFR on horizontal legs above clouds. For mid-visible wavelengths, we find SSA values from 0.80 to 0.85 and a significant spectral dependence of g. As the cloud albedo increases, the aerosol increasingly warms the column. The transition from a cooling to a warming top-of-aerosol radiative effect occurs at an albedo value (critical albedo) just above 0.2 in the mid-visible wavelength range. In a companion paper, we use the techniques introduced here to generalize our findings to all 2016 and 2017 measurements and parameterize aerosol radiative effects.

Abstract The Earth system responds to solar variability on a wide range of timescales. Knowledge of total solar irradiance (TSI) and solar spectral irradiance (SSI) spanning minutes to centuries is needed by scientists studying a broad array of research applications. For these purposes, the NOAA National Centers for Environmental Information (NCEI) Climate Data Record Program established the Solar Irradiance Climate Data Record. Version 2 of the Naval Research Laboratory's solar variability models that are derived from and demonstrate consistency with irradiance observations specifies TSI and SSI for the Solar Irradiance Climate Data Record. We establish the veracity of the Naval Research Laboratory models on the timescales and over the wavelength range for which the Sun is known to vary and, thereby, specify the utility of these models. Through comparisons with irradiance observations and independent models, we validate NRLTSI2 estimates of TSI on solar rotational (~27‐day), solar cycle (~11‐year), and multidecadal (spacecraft era) variability timescales. Similarly, we validate NRLSSI2 estimates of SSI rotational variability in the ultraviolet through the mid‐visible spectrum. Validation of NRLSSI2 estimates at longer wavelengths, particularly in the near‐infrared, and for the full spectrum at solar cycle timescales and longer is not possible with the current observational record due to instrumental noise and instrument instability. We identify where key new data sets, such as observations from the Total and Spectral Solar Irradiance Sensor‐1, are expected to provide a fuller understanding of total and spectral solar irradiance variability on multiple timescales.

We retrieve aerosol optical thickness (AOT) independently for brown carbon, dust and sulfate from hyperspectral image data. The model, a neural network, is trained on atmospheric radiative transfer calculations from MODTRAN 6.0 with varying aerosol concentration and type, surface albedo, water vapor, and viewing geometries. From a set of test radiative transfer calculations, we are able to retrieve AOT with a standard error of better than ±0.05. No a priori information on the surface albedo or atmospheric state is necessary for our model. We apply the model to AVIRIS-NG imagery from a recent campaign over India and demonstrate its performance under high and low aerosol loadings and different aerosol types.

Abstract We compare solar spectral irradiance (SSI) measurements obtained from the Spectral Irradiance Monitor (SIM) on board the Solar Radiation and Climate Experiment (SORCE), corrected for instrument degradation using three different methods; SIM Version 25, Multiple Same‐Irradiance‐Level and SIM constrained Version 2 (SIMc V2), to quantify their differences and gain understanding about the relative performance of each method. Furthermore, we compare the three data sets to independent SSI observations that include the SORCE SIM successor Total and Spectral Solar Irradiance Sensor SIM and solar irradiance models. While we find agreement between the SSI for the three correction methods for wavelengths in the visible, differences persist for shorter and longer wavelengths, on time scales on the order of the 11‐year solar cycle. The comparisons to independent SSI observations reveal remaining instrument trends in some of the corrected SORCE SIM data.

Sensors on satellites provide unprecedented understanding of the Earth's climate system by measuring incoming solar radiation, as well as both passive and active observations of the entire Earth with outstanding spatial and temporal coverage. A common challenge with satellite observations is to quantify their ability to provide well-calibrated, long-term, stable records of the parameters they measure. Ground-based intercomparisons offer some insight, while reference observations and internal calibrations give further assistance for understanding long-term stability. A valuable tool for evaluating and developing long-term records from satellites is the examination of data from overlapping satellite missions. This paper addresses how the length of overlap affects the ability to identify an offset or a drift in the overlap of data between two sensors. Ozone and temperature data sets are used as examples showing that overlap data can differ by latitude and can change over time. New results are presented for the general case of sensor overlap by using Solar Radiation and Climate Experiment (SORCE) Spectral Irradiance Monitor (SIM) and Solar Stellar Irradiance Comparison Experiment (SOLSTICE) solar irradiance data as an example. To achieve a 1 % uncertainty in estimating the offset for these two instruments' measurement of the Mg II core (280 nm) requires approximately 5 months of overlap. For relative drift to be identified within 0.1 % yr−1 uncertainty (0.00008 W m−2 nm−1 yr−1), the overlap for these two satellites would need to be 2.5 years. Additional overlap of satellite measurements is needed if, as is the case for solar monitoring, unexpected jumps occur adding uncertainty to both offsets and drifts; the additional length of time needed to account for a single jump in the overlap data may be as large as 50 % of the original overlap period in order to achieve the same desired confidence in the stability of the merged data set. Results presented here are directly applicable to satellite Earth observations. Approaches for Earth observations offer additional challenges due to the complexity of the observations, but Earth observations may also benefit from ancillary observations taken from ground-based and in situ sources. Difficult choices need to be made when monitoring approaches are considered; we outline some attempts at optimizing networks based on economic principles. The careful evaluation of monitoring overlap is important to the appropriate application of observational resources and to the usefulness of current and future observations.