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Annual VIIRS global night-time lights traditionally report mean radiance levels after filtering to remove moonlit and cloudy data followed by outlier removal. The mean is the first statistical moment, but there are three other statistical moments (variance, skew and kurtosis) that are currently not produced globally. In this study, we generated VIIRS day/night band multiyear and annual statistical moments for a widely dispersed set of test areas. The moments were calculated from 15 arc second nightly temporal profiles spanning 2012–2020, filtered to exclude cloudy and sunlit data, with radiance adjustments to reduce view angle and lunar illuminance effects. The moment data were examined in two ways: (1) Geospatial grids-which reveal zonation and temporal changes present in urban areas and (2) Scattergrams of moment pairs. The variance versus mean scattergram exhibits several distinct data clusters used to define five zones: core lighting, dark-erratics, mid-erratics, bright-erratics and bright and seteady. The results indicate that the information content of VIIRS night-time lights can be augmented if all four statistical moments are calculated. [ABSTRACT FROM AUTHOR]

Alternating current can result in flickering—or pulsing—in the brightness of light emitted by luminaires. Lighting flicker typically occurs in the range of 100 to 140 cycles per second (Hz), which is too fast for visual perception by most organisms. However, evidence indicates that many organisms perceive flicker with non-visual photoreceptors present on the retinas. Exposure to flickering lights at night disrupts the circadian rhythm of organisms, leading to symptoms similar to blue light exposure at night. The traditional method for detecting flickering is with a flickermeter held near a single light. In this paper, we explore the use of high-speed camera data in the collection of temporal profiles for groups of luminaires simultaneously at distances ranging from several meters to several kilometers. Temporal profiles are extracted for individual lighting features and the full scene. The identification of luminaire types is based on their spectral signatures. With the camera data, it is possible to identify flickering and non-flickering lights, to determine the flicker frequency, to calculate percent flicker and the flicker index, and to identify groups of lights whose flickers are synchronized. Both flickering and non-flickering luminaires can be found for LED, metal halide, fluorescent, and compact fluorescent lights. To date, flickering has been detected in all of the incandescent, high-pressure sodium, and low-pressure sodium luminaires that we measured. We found that flicker synchronization is often present for lights installed within a single facility and also for strings of streetlights. We also found that flicker exposure can come from the light reflected off of the earth's surface. Luminaires designed to illuminate large areas often saturate high-speed camera data collection. This saturation can be reduced or eliminated using neutral density filters on the camera. Published experimental data on the impacts of flicker on organisms remains sparse. Many studies have drawn inferences on the impacts of spectral and lighting brightness on organisms without controlling for flicker. Our conclusion is that lighting flicker is a type of light pollution. The use of high-speed camera data makes it easier to include flicker as a variable in studies regarding the impacts of lighting on organisms. [ABSTRACT FROM AUTHOR]

This paper reports on the first daily global monitoring program for natural gas flaring and industrial sites producing waste heat based on satellite observed infrared emissions. The Visible Infrared Imaging Radiometer Suite (VIIRS) collects nightly global infrared data in spectral bands ranging from near infrared (NIR) to longwave infrared (LWIR), providing a unique capability to detect and characterize infrared emitters at night. The VIIRS nightfire (VNF) algorithm identifies infrared (IR) emitters with multiple spectral bands and calculates the temperature, source area, and radiant heat via Planck curve fitting and physical laws. VNF data are produced nightly and extend from 2012 to the present. The most common infrared emitter is biomass burning, which must be filtered out. Industrial IR emitters can be distinguished from biomass burning based on temperature and persistence. The initial filtering to remove biomass burning was performed with 15 arc second grids formed from eleven years of VIIRS data, spanning 2012–2022. The locations and shapes of the remaining features were used to guide the generation of super-resolution pixel center clouds. These data clouds were then analyzed to define bounding vectors for single emitters and to split larger clusters into multiple emitters. A total of nearly 20,000 IR emitters were identified; each was assigned an identification number, and the type of emitter was recorded. Nightly temporal profiles were produced for each site, revealing activity patterns back to 2012. Nightly temporal profiles were kept current with weekly updates. Temporal profiles from individual sites were aggregated by country to form monthly profiles extending back to 2012. The nightly and monthly temporal profiles were suitable for analyzing industrial production, identifying disruption events, and tracking recovery. The data could also be used in tracking progress in energy conservation and greenhouse gas emission inventories. [ABSTRACT FROM AUTHOR]

In wintertime over the subpolar North Atlantic Ocean (SPNA), the strongest surface sensible and latent heat fluxes typically occur just downstream of the sea‐ice edge. The recent retreat in Arctic wintertime sea ice is changing the distribution of these turbulent heat fluxes, with consequences for the formation of the dense waters that feed into the Atlantic Meridional Overturning Circulation. Projections of turbulent heat flux over the SPNA are investigated using output from the HadGEM3‐GC3.1 climate model, produced as part of the sixth phase of the Coupled Model Inter‐Comparison Project. Comparison of two model resolutions (MM: 60 km atmosphere—1/4° ocean and HH: 25 km–1/12°) shows that the HH configuration more accurately simulates historic sea ice and turbulent heat flux distributions. The MM configuration tends to produce too much sea ice in the SPNA, affecting the turbulent heat flux distribution; however, it displays improved performance during winters with less sea ice, increasing confidence in future projections when less sea ice is predicted. Future projections are presented for low (SSP1‐2.6) and high (SSP5‐8.5) emissions pathways. The simulations agree in predicting that, with climate change, the SPNA will see reductions in wintertime sea ice and air‐sea turbulent fluxes later in the 21st century, particularly in the Labrador and Irminger Seas and the interior of the Nordic Seas, and a notable reduction in their decadal variability. These effects are more severe under the SSP5‐8.5 pathway. The implications for SPNA ocean circulation are discussed. Plain Language Summary: In winter over the subpolar North Atlantic Ocean a large amount of heat is transferred from the ocean to the air just off the sea ice. This heat loss drives water mass changes in the ocean, which, in turn, helps drive global ocean circulation. The subpolar North Atlantic is rapidly warming due to fossil fuel emissions, resulting in a large reduction of sea ice that may further impact global climate. We look at predictions of future sea ice loss and its effects on air‐sea heat exchange using some of the latest climate simulations that represent the atmosphere and the ocean at high spatial resolution. These simulations do reasonably well at reproducing the historic climate of the region, so we have some confidence that they are suitable for making predictions of future conditions. We investigate future projections for low and high emissions scenarios, finding that ocean heat loss to the atmosphere will reduce, particularly in the Labrador, Irminger and interior of the Nordic Seas, and by a greater amount under the high emissions scenario. How this could affect the ocean is discussed. Key Points: The climate model HadGEM3‐GC3.1 simulates historic sea ice and turbulent heat fluxes reasonably well, with improvements at higher resolutionUpward turbulent heat fluxes are predicted to reduce, particularly in the Labrador and Irminger Seas and the interior of the Nordic SeasChanges in local heat flux maxima are largely governed by ice edge retreat, while overall a reduction in ocean heat loss is projected [ABSTRACT FROM AUTHOR]

A new, simple parameterization scheme for scalar (heat and moisture) exchange over sea ice and the marginal ice zone is tested in a numerical weather and climate prediction model. This new "Blended A87" scheme accounts for the influence of aerodynamic roughness on the relationship between momentum and scalar exchange over consolidated sea ice, in line with long‐standing theory and recent field observations, and in contrast to the crude schemes currently operational in most models. Using aircraft observations and Met Office Unified Model simulations of cold‐air outbreak (CAO) conditions over aerodynamically rough sea ice, we demonstrate striking improvements in model performance when the Blended A87 scheme replaces the model's operational treatment for surface scalar exchange, provided that the aerodynamic roughness over consolidated ice is appropriately prescribed. The mean biases in surface sensible heat flux, surface latent heat flux, near‐surface air temperature, and surface temperature reduce from 25 to 11 W m−2, 22 to 12 W m−2, 0.8 to 0.0 K, and 1.4 to 0.8 K, respectively. We demonstrate that such impacts on surface exchange over sea ice can have a marked impact on the evolution of the atmospheric boundary layer across hundreds of kilometres downwind of the sea ice during CAO conditions in the model. Our results highlight the importance of spatiotemporal variability in the topography of consolidated sea ice for both momentum and scalar exchange over sea ice; accounting for which remains a key challenge for modeling polar weather and climate. Plain Language Summary: A new algorithm for the turbulent exchange of heat and moisture between the atmosphere and the ice‐covered oceans of the polar regions is tested in a state‐of‐the‐art weather and climate model. The algorithm is applicable both over consolidated sea ice and in regions characterized by a mixture of open seawater and ice. It accounts for the influence of aerodynamic roughness (a function of wind speed and the fine‐scale topographic roughness of the surface), in line with long‐standing theory and recent field observations, and in contrast to the crude schemes currently operational in most models. Using low‐altitude aircraft observations from over the Arctic Ocean and Nordic Seas, we demonstrate striking improvements in model performance when the new algorithm replaces the model's operational treatment for surface scalar exchange, provided that the aerodynamic roughness over consolidated ice is appropriately prescribed. The mean biases in surface sensible heat flux, surface latent heat flux, near‐surface air temperature and surface temperature reduce from 25 to 11 W m−2, 22 to 12 W m−2, 0.8 to 0.0 K, and 1.4 to 0.8 K, respectively. We demonstrate that such impacts on surface exchange over sea ice can have a significant impact on model prediction of high‐latitude weather. Key Points: The model reproduction of scalar fluxes over sea ice is improved with a new parameterization that accounts for aerodynamic roughnessThe properties and structure of the polar atmospheric boundary layer are sensitive to the implementation of this new parameterizationThe benefit of the parameterization accounting for aerodynamic roughness hinges on the appropriate prescription of sea‐ice topography [ABSTRACT FROM AUTHOR]

Marine cold‐air outbreaks (CAOs) are vigorous equatorward excursions of cold air over the ocean, responsible for the majority of wintertime oceanic heat loss from the subpolar seas of the North Atlantic. However, the impact of individual CAO events on the ocean is poorly understood. Here we present the first coupled observations of the atmosphere and ocean during a wintertime CAO event, between 28 February and 13 March 2018, in the subpolar North Atlantic region. Comprehensive observations are presented from five aircraft flights, a research vessel, a meteorological buoy, a subsurface mooring, an ocean glider, and an Argo float. The CAO event starts abruptly with substantial changes in temperature, humidity and wind throughout the atmospheric boundary layer. The CAO is well mixed vertically and, away from the sea‐ice edge, relatively homogeneous spatially. During the CAO peak, higher sensible heat fluxes occupy at least the lowest 200 m of the atmospheric boundary layer, while higher latent heat fluxes are confined to the surface layer. The response of the ocean to the CAO is spatially dependent. In the interior of the Iceland Sea the mixed layer cools, while in the boundary current region it warms. In both locations, the mixed layer deepens and becomes more saline. Combining our observations with one‐dimensional mixed‐layer modelling, we show that in the interior of the Iceland Sea, atmospheric forcing dominates the ocean response. In contrast, in the boundary current region lateral advection and mixing counteract the short‐term impact of the atmospheric forcing. Time series observations of the late‐winter period illustrate a highly variable ocean mixed layer, with lateral advection and mixing often masking the ocean's general cooling and deepening response to individual CAO events. [ABSTRACT FROM AUTHOR]

Abstract--Novel data on the spatial and temporal distribution of fishing effort and population abundance are presented for the market squid fishery (Loligo opalescens) in the Southern California Bight, 1992-2000. Fishing [...]

A major source of uncertainty in both climate projections and seasonal forecasting of sea ice is inadequate representation of surface–atmosphere exchange processes. The observations needed to improve understanding and reduce uncertainty in surface exchange parameterizations are challenging to make and rare. Here we present a large dataset of ship-based measurements of surface momentum exchange (surface drag) in the vicinity of sea ice from the Arctic Clouds in Summer Experiment (ACSE) in July–October 2014, and the Arctic Ocean 2016 experiment (AO2016) in August–September 2016. The combined dataset provides an extensive record of momentum flux over a wide range of surface conditions spanning the late summer melt and early autumn freeze-up periods, and a wide range of atmospheric stabilities. Surface exchange coefficients are estimated from in situ eddy covariance measurements. The local sea-ice fraction is determined via automated processing of imagery from ship-mounted cameras. The surface drag coefficient, CD10n , peaks at local ice fractions of 0.6–0.8, consistent with both recent aircraft-based observations and theory. Two state-of-the-art parameterizations have been tuned to our observations, with both providing excellent fits to the measurements. [ABSTRACT FROM AUTHOR]

The VIIRS day/night band (DNB) high gain stage (HGS) pixel effective dwell time is in the range of 2–3 milliseconds (ms), which is about one third of the flicker cycle present in lighting powered by alternating current. Thus, if flicker is present, it induces random fluctuations in nightly DNB radiances. This results in increased variance in DNB temporal profiles. A survey of flicker characteristics conducted with high-speed camera data collected on a wide range of individual luminaires found that the flicker is most pronounced in high-intensity discharge (HID) lamps, such as high- and low-pressure sodium and metal halides. Flicker is muted, but detectable, in incandescent luminaires. Modern light-emitting diodes (LEDs) and fluorescent lights are often nearly flicker-free, thanks to high-quality voltage smoothing. DNB pixel footprints are about half a square kilometer and can contain vast numbers of individual luminaires, some of which flicker, while others do not. If many of the flickering lights are drawing from a common AC supplier, the flicker can be synchronized and leave an imprint on the DNB temporal profile. In contrast, multiple power supplies will throw the flickering out of synchronization, resulting in a cacophony with less radiance fluctuation. The examination of DNB temporal profiles for locations before and after the conversion of high-intensity discharge (HID) to LED streetlight conversions shows a reduction in the index of dispersion, calculated by dividing the annual variance by the mean. There are a number of variables that contribute to radiance variations in the VIIRS DNB, including the view angle, cloud optical thickness, atmospheric variability, snow cover, lunar illuminance, and the compilation of temporal profiles using pixels whose footprints are not perfectly aligned. It makes sense to adjust the DNB radiance for as many of these extraneous effects as possible. However, none of these adjustments will reduce the radiance instability introduced by flicker. Because flicker is known to affect organisms, including humans, the development of methods to detect and rate the strength of flickering from space will open up new areas of research on the biologic impacts of artificial lighting. Over time, there is a trend towards the reduction of flicker in outdoor lighting through the replacement of HID with low-flicker LED sources. This study indicates that the effects of LED conversions on the brightness and steadiness of outdoor lighting can be analyzed with VIIRS DNB temporal profiles. [ABSTRACT FROM AUTHOR]

Biomass burning is a coupled exothermic/endothermic system that transfers carbon in several forms to the atmosphere, ultimately leaving mineral ash. The exothermic phases include flaming and smoldering, which produce the heat that drives the endothermic processes. The endothermic components include pre-heating and pyrolysis, which produce the fuel consumed by flaming and smoldering. These components can be broadly distinguished from each other based on temperature. For several years, we have researched the subpixel analysis of two temperature phases present in fire pixels detected in nighttime VIIRS data. Here, we present the flaming subtractive method, with which we have successfully derived temperatures and source areas for two infrared (IR) emitters and a cooler background. This is developed as an add-on to the existing VIIRS nightfire algorithm version 3 (VNF v.3) which uses Planck curve fitting to calculate temperatures and source areas for a single IR emitter and background. The flaming subtractive method works with data collected in four spectral ranges: near-infrared (NIR), short-wave infrared (SWIR), mid-wave infrared (MWIR) and long-wave infrared (LWIR). With sunlight eliminated, the NIR and SWIR radiances can be fully attributed to the primary IR emitter. The analysis begins with Planck curve modeling for the primary emitter based on the NIR and SWIR radiances, yielding temperature, source area and primary emitter radiances in all spectral bands. The primary emitter radiances are subtracted from each spectral band and then the residual radiance is analyzed for a secondary IR emitter and the background. Spurious results are obtained in pixels lacking a discernable secondary emitter. These misfit pixels revert back to the single IR emitter analysis of VNF v.3. In tests run for two California megafires, we found that the primary emitters straddle the temperature ranges for flaming and smoldering, the exothermic portions of biomass burning, which are apparently commingled on the ground. The secondary emitter temperatures span 350-750 K, corresponding to pre-heating and slow pyrolysis. The natural gas flare test case had few numbers of successful secondary emitter retrievals and a wide range of secondary emitter temperatures. The flaming subtractive analysis is the key addition to VNF version 4, which will commence production later in 2021. In 2022, we will seek validation of the VNF v.4 from nighttime Landsat and other data sources. [ABSTRACT FROM AUTHOR]

A major source of uncertainty in both climate projections and seasonal forecasting of sea ice is inadequate representation of surface-atmosphere exchange processes. The observations needed to improve understanding and reduce uncertainty in surface exchange parameterizations are challenging to make and rare. Here we present a large dataset of ship-based measurements of surface momentum exchange (surface drag) in the vicinity of sea ice from the Arctic Clouds in Summer Experiment (ACSE) in July-October 2014, and the Arctic Ocean 2016 experiment (AO2016) in August-September 2016. The combined dataset provides an extensive record of momentum flux over a wide range of surface conditions spanning the late summer melt and early autumn freeze-up periods, and a wide range of atmospheric stabilities. Surface exchange coefficients are estimated from in situ eddy covariance measurements. The local sea-ice fraction is determined via automated processing of imagery from ship-mounted cameras. The surface drag coefficient, CD10n, peaks at local ice fractions of 0.6-0.8, consistent with both recent aircraft-based observations and theory. Two state-of-the-art parameterizations have been tuned to our observations with both providing excellent fits to the measurements. [ABSTRACT FROM AUTHOR]

Aircraft observations from two Arctic field campaigns are used to characterize and model surface heat and moisture exchange over the marginal ice zone (MIZ). We show that the surface roughness lengths for heat and moisture over uninterrupted sea ice vary with roughness Reynolds number (R∗; itself a function of the roughness length for momentum, z0, and surface wind stress), with a peak at the transition between aerodynamically smooth (R∗<0.135) and aerodynamically rough (R∗>2.5) regimes. A pre‐existing theoretical model based on surface‐renewal theory accurately reproduces this peak, in contrast to the simple parameterizations currently employed in two state‐of‐the‐art numerical weather prediction models, which are insensitive to R∗. We propose a new, simple parameterization for surface exchange over the MIZ that blends this theoretical model for sea ice with surface exchange over water as a function of sea ice concentration. In offline tests, this new scheme performs much better than the existing schemes for the rough conditions observed during the 'Iceland Greenland Seas Project' field campaign. The bias in total turbulent heat flux across the MIZ is reduced to only 13 W m−2 for the new scheme, from 48 and 80 W m−2 for the Met Office Unified Model and ECMWF Integrated Forecast System schemes, respectively. It also performs marginally better for the comparatively smooth conditions observed during the 'Aerosol‐Cloud Coupling and Climate Interactions in the Arctic' field campaign. The new surface exchange scheme has the benefit of being physically‐motivated, comparatively accurate and straightforward to implement, although to reap the full benefits an improvement to the representation of sea ice topography via z0 is required. Key Points: Observations over the marginal ice zone show that surface scalar exchange is a function of the aerodynamic roughness of the surfaceExisting scalar exchange parameterization schemes do not represent this sensitivity; we propose a new scheme that doesThe new scheme is more accurate in offline calculations of surface heat fluxes, especially for aerodynamically rough conditions [ABSTRACT FROM AUTHOR]