Earth's Energy Budget Research Articles

Estimating Surface BRDF/Albedo Over Rugged Terrain Using an Extended Multisensor Combined BRDF Inversion (EMCBI) Model

Land surface albedo is a crucial variable of earth energy budget and global climate change. Rugged terrain significantly impacts surface bidirectional reflectance distribution function (BRDF) and the subsequent albedo retrieval using satellite remote sensing. Existing studies of estimating surface BRDF/albedo from satellite observations are limited to neglecting topographic impacts, resulting in large uncertainty in satellite albedo product, especially for low spatial resolution satellite sensors that are primarily regulated by subpixel-scale topographic effects. To fill this knowledge gap, we proposed an extended multisensor combined BRDF inversion (EMCBI) model to characterize subpixel-scale topographic effects, and applied this model to estimate BRDF/albedo from the Himawari-8 Advanced Himawari Imager (AHI) and Terra/Aqua moderate resolution imaging spectroradiometer (MODIS) data and finally validated the satellite-derived albedo with ground measurements of two stations located in Tibet plateau. Our results show that: 1) EMCBI can generate a daily BRDF/albedo dataset with more than 90% spatial coverage and 2) EMCBI-derived albedo agrees well with the referenced albedo corrected from ground measurement, with a root-mean-square-error (RMSE) of 0.0537 and 0.0608 for black-sky albedo (BSA) and white-sky albedo (WSA), and a mean absolute percentage error (MAPE) of 21.93% and 25.13% for BSA and WSA, respectively. These results demonstrate EMCBI has great potential for mapping large-scale high temporal resolution BRDF/albedo product over rugged terrain.

Top-of-Atmosphere Clear-Sky Albedo Estimation Over Ocean: Preliminary Framework for MODIS

Top-of-atmosphere (TOA) albedo is a significant factor of earth energy budget, climate change, and environmental change. As tremendous regional and global changes are happening over ocean, more details are needed to monitor the ocean environment. However, there were still no high-spatial resolution TOA albedo products over ocean. In this study, a new algorithm for clear-sky TOA albedo estimation over ocean was proposed, based on Moderate Resolution Imaging Spectroradiometer (MODIS) data. Instead of building angular distribution models, direct retrieval models between TOA reflectance and TOA albedo were developed based on extensive radiative transfer (RT) simulations, covering thousands of ocean and atmosphere types. Three-component ocean water albedo model was involved to take account for the ocean surface anisotropy at different wind speed, wind direction, and chlorophyll concentration, while Modtran 5 was utilized to simulate different atmospheric conditions. Our results showed good agreement with the Clouds and the Earth’s Radiant Energy System (CERES) based on a global comparison on August 4, 2011, with RMSE = 0.015 and bias = 0.002. And our MODIS-based products provide more spatial details due to higher spatial resolution (1 km), which will be a good data source for regional environmental and climatic research and will also enhance the understanding of Earth’s radiation budget.

Evaluating the large-scale hydrological cycle response within the Pliocene Model Intercomparison Project Phase 2 (PlioMIP2) ensemble

Abstract. The mid-Pliocene (∼3 Ma) is one of the most recent warm periods with high CO2 concentrations in the atmosphere and resulting high temperatures, and it is often cited as an analog for near-term future climate change. Here, we apply a moisture budget analysis to investigate the response of the large-scale hydrological cycle at low latitudes within a 13-model ensemble from the Pliocene Model Intercomparison Project Phase 2 (PlioMIP2). The results show that increased atmospheric moisture content within the mid-Pliocene ensemble (due to the thermodynamic effect) results in wetter conditions over the deep tropics, i.e., the Pacific intertropical convergence zone (ITCZ) and the Maritime Continent, and drier conditions over the subtropics. Note that the dynamic effect plays a more important role than the thermodynamic effect in regional precipitation minus evaporation (PmE) changes (i.e., northward ITCZ shift and wetter northern Indian Ocean). The thermodynamic effect is offset to some extent by a dynamic effect involving a northward shift of the Hadley circulation that dries the deep tropics and moistens the subtropics in the Northern Hemisphere (i.e., the subtropical Pacific). From the perspective of Earth's energy budget, the enhanced southward cross-equatorial atmospheric transport (0.22 PW), induced by the hemispheric asymmetries of the atmospheric energy, favors an approximately 1∘ northward shift of the ITCZ. The shift of the ITCZ reorganizes atmospheric circulation, favoring a northward shift of the Hadley circulation. In addition, the Walker circulation consistently shifts westward within PlioMIP2 models, leading to wetter conditions over the northern Indian Ocean. The PlioMIP2 ensemble highlights that an imbalance of interhemispheric atmospheric energy during the mid-Pliocene could have led to changes in the dynamic effect, offsetting the thermodynamic effect and, hence, altering mid-Pliocene hydroclimate.

Reconstruction of Historical Land Surface Albedo Changes in China From 850 to 2015 Using Land Use Harmonization Data and Albedo Look‐Up Maps

AbstractLand surface albedo is a critical parameter of the Earth's energy budget and has been greatly altered by climate change and human activities. To improve our understanding of historical land surface albedo changes and their climatic effects before the satellite remote sensing era, we reconstructed land surface albedo in China from 850 to 2015 using the historical land use harmonization version 2 (LUH2) data set and albedo look‐up maps, and estimated the radiative forcing induced by land surface albedo changes using atmospheric radiative kernels. The reconstruction results showed that the annual‐mean land surface albedo in China increased by 0.00110 during 850–2015, and the rate of increase was accelerated by the expansion of croplands during recent centuries. The most significant increases in land surface albedo were found in the Huang‐Huai‐Hai (HHH; +0.00646) and Northeast China (NE; +0.00501), which were primarily driven by anthropogenic land cover transformations (e.g., land reclamation, deforestation, and urbanization) and can be enhanced by the vegetation masking effect on snow cover. The radiative forcing induced by land surface albedo changes in China during 850–2015 and 1750–2015 was −0.09 ± 0.04 and −0.06 ± 0.02 W m−2, respectively, which indicated that the land surface albedo changes produced a slight climate cooling effect, helping to offset the warming effect caused by greenhouse gas emissions.

20th century cooling of the deep ocean contributed to delayed acceleration of Earth\u2019s energy imbalance

The historical evolution of Earth’s energy imbalance can be quantified by changes in the global ocean heat content. However, historical reconstructions of ocean heat content often neglect a large volume of the deep ocean, due to sparse observations of ocean temperatures below 2000 m. Here, we provide a global reconstruction of historical changes in full-depth ocean heat content based on interpolated subsurface temperature data using an autoregressive artificial neural network, providing estimates of total ocean warming for the period 1946-2019. We find that cooling of the deep ocean and a small heat gain in the upper ocean led to no robust trend in global ocean heat content from 1960-1990, implying a roughly balanced Earth energy budget within −0.16 to 0.06 W m−2 over most of the latter half of the 20th century. However, the past three decades have seen a rapid acceleration in ocean warming, with the entire ocean warming from top to bottom at a rate of 0.63 ± 0.13 W m−2. These results suggest a delayed onset of a positive Earth energy imbalance relative to previous estimates, although large uncertainties remain.

Water-soluble brown carbon in atmospheric aerosols along the transport pathway of Asian dust: Optical properties, chemical compositions, and potential sources

As an important type of light-absorbing aerosol, brown carbon (BrC) has the potential to affect the atmospheric photochemistry and Earth's energy budget. A comprehensive field campaign was carried out along the transport pathway of Asian dust during the spring of 2016, including a desert site (Erenhot), a rural site (Zhangbei), and an urban site (Jinan), in northern China. Optical properties, bulk chemical compositions, and potential sources of water-soluble brown carbon (WS-BrC) were investigated in atmospheric total suspended particulate (TSP) samples. Samples from Zhangbei had higher mass absorption efficiency at 365 nm (MAE365, 1.32 ± 0.34 m2 g−1) than those from Jinan (1.00 ± 0.23 m2 g−1) and Erenhot (0.84 ± 0.30 m2 g−1). Compere to the non-dust samples, elevated water-soluble organic carbon (WSOC) concentrations and MAE365 values of dust samples from Erenhot are related to the input of high molecular weight organic compounds and biogenic matter from the Gobi Desert, while lower values from Zhangbei and Jinan are attributed to the dilution effect caused by strong northwesterly winds. Based on fluorescence excitation–emission matrix spectra and parallel factor analysis, two humic-like (C1 and C2) and two protein-like (C3 and C4) substances were identified. Together, C1 and C2 accounted for ~64% of total fluorescence intensity at the highly polluted urban Jinan site; C3 represented ~45% at the rural Zhangbei site where local biomass burning affects; and C4 contributed ~24% in the desert region (Erenhot) due to dust-sourced biogenic substances. The relative absorptive forcing of WS-BrC compared to black carbon at 300–400 nm was about 31.3%, 13.9%, and 9.2% during non-dust periods at Erenhot, Zhangbei, and Jinan, respectively, highlighting that WS-BrC may significantly affect the radiative balance of Earth's climate system and should be included in radiative forcing models.

Assessment of the EUMETSAT Multi Decadal Land Surface Albedo Data Record from Meteosat Observations

Surface albedo, defined as the ratio of the surface-reflected irradiance to the incident irradiance, is one of the parameters driving the Earth energy budget and it is for this reason an essential variable in climate studies. Instruments on geostationary satellites provide suitable observations allowing long-term monitoring of surface albedo from space. In 2012, EUMETSAT published Release 1 of the Meteosat Surface Albedo (MSA) data record. The main limitation effecting the quality of this release was non-removed clouds by the incorporated cloud screening procedure that caused too high albedo values, in particular for regions with permanent cloud coverage. For the generation of Release 2, the MSA algorithm has been replaced with the Geostationary Surface Albedo (GSA) one, able to process imagery from any geostationary imager. The GSA algorithm exploits a new, improved, cloud mask allowing better cloud screening, and thus fixing the major limitation of Release 1. Furthermore, the data record has an extended temporal and spatial coverage compared to the previous release. Both Black-Sky Albedo (BSA) and White-Sky Albedo (WSA) are estimated, together with their associated uncertainties. A direct comparison between Release 1 and Release 2 clearly shows that the quality of the retrieval improved significantly with the new cloud mask. For Release 2 the decadal trend is less than 1% over stable desert sites. The validation against Moderate Resolution Imaging Spectroradiometer (MODIS) and the Southern African Regional Science Initiative (SAFARI) surface albedo shows a good agreement for bright desert sites and a slightly worse agreement for urban and rain forest locations. In conclusion, compared with MSA Release 1, GSA Release 2 provides the users with a significantly more longer time range, reliable and robust surface albedo data record.

Controlling factors of seasonal and spatial variation of riverine CO2 partial pressure and its implication for riverine carbon flux

Global carbon cycle is closely related to the earth's energy budget, because CO2 plays an active role in the global climate change. The higher CO2 partial pressure (pCO2) in inland water in comparison with atmosphere, causing a CO2 evasion from water to the air. However, the relationship between CO2 evasion, riverine carbon export, and hydrochemistry in watershed has remained largely unknown. This study collected 84 river water samples in Jiulongjiang River, to further address this subject on a small watershed scale. Water temperature fluctuation, riverine photosynthesis, and acidic matter input could not account for the seasonal variation of pCO2 in Jiulongjiang River. The spatial shifts of pCO2 were derived from the mixing process between headwater and soil influx. The soil influx with high pCO2 compensated the CO2 lost from evasion and caused pCO2 in Jiulongjiang River higher than the atmospheric level. The seasonal variation of pCO2 was caused by the precipitation difference between the wet season and dry season. The addition of rainwater significantly decreased the riverine pCO2 and HCO3− concentration in the wet season. The CO2 evasion rate in Jiulongjiang River was clearly higher than that in most worldwide large rivers. The annual CO2 evasion flux in Jiulongjiang River Basin was estimated about 2.48 × 105 T C/year, which was higher than the riverine total carbon export. The CO2 evasion rate exhibited significantly positive relationship with water surface area, indicating that the global CO2 evasion flux may be roughly estimated based on the observed regression relationship. Overall, our study indicated that it still requires collaborative effects to investigate the carbon dynamics in river water, more estimations of CO2 outgassing flux from river water under different hydrologic and geologic conditions are necessary.

First palaeointensity data from the cryogenian and their potential implications for inner core nucleation age

SUMMARY The timing of inner core nucleation is a hugely significant event in Earth's evolution and has been the subject of intense debate. Some of the most recent theoretical estimates for the age of nucleation fall throughout the Neoproterozoic era; much younger than previously thought. A young inner core requires faster recent core cooling rates and a likely hotter early core; knowledge of its age would be invaluable in understanding Earth's thermal history and total energy budget. Predictions generated by numerical dynamo models need to be tested against such data, but records are currently much too sparse to constrain the event to a precise period of time. Here, we present results from 720 Ma dolerite dykes (and one sill) from the Franklin Large Igneous Province, which fall within a crucial 300 Myr gap in palaeointensity records. This study uses three independent techniques on whole rocks from 11 sites spread across High Arctic Canada and Greenland to produce virtual dipole moments ranging from 5 to 20 ZAm2 (mean 11 ZAm2); almost one order of magnitude lower than the present-day field. These weak-field results agree with recent ultralow palaeointensity data obtained from Ediacaran rocks formed ∼150 Myr later and may support that the dynamo was on the brink of collapse in the Neoproterozoic prior to a young inner core formation date.

Global Daytime Variability of Clouds From DSCOVR/EPIC Observations

AbstractKnowledge of the daytime variability of cloud fraction is pivotal for the accurate determination of the atmosphere's energy balance. Yet, polar orbiting satellites are unable to fully capture daytime variability and individual geostationary satellites only provide measurements for portions of the Earth. In addition, diurnal cloud fraction variations analyzed with General Circulation Models provide results that cannot be reconciled with observations in many situations. Here, we show that the Earth Polychromatic Imaging Camera (EPIC) aboard the Deep Space Climate Observatory (DSCOVR) satellite presents a unique opportunity to examine changes in daytime global cloud fraction resolved at one‐hour frequency. For the first time, we characterize the global daytime variability of clouds with a single sensor, presenting evidence that the fraction of liquid clouds reaches its maximum over continental areas and its minimum over ocean around noon. We compare our results with previous global and regional studies and examine implications for the Earth's energy budget.

Increasing Resolution and Resolving Convection Improve the Simulation of Cloud‐Radiative Effects Over the North Atlantic

AbstractClouds interact with atmospheric radiation and substantially modify the Earth's energy budget. Cloud formation processes occur over a vast range of spatial and temporal scales, which make their thorough numerical representation challenging. Therefore, the impact of parameter choices for simulations of cloud‐radiative effects is assessed in the current study. Numerical experiments are carried out using the ICOsahedral Nonhydrostatic (ICON) model with varying grid spacings between 2.5 and 80 km and with different subgrid‐scale parameterization approaches. Simulations are performed over the North Atlantic with either one‐moment or two‐moment microphysics and with convection being parameterized or explicitly resolved by grid‐scale dynamics. Simulated cloud‐radiative effects are compared to products derived from Meteosat measurements. Furthermore, a sophisticated cloud classification algorithm is applied to understand the differences and dependencies of simulated and observed cloud‐radiative effects. The cloud classification algorithm developed for the satellite observations is also applied to the simulation output based on synthetic infrared brightness temperatures, a novel approach that is not impacted by changing insolation and guarantees a consistent and fair comparison. It is found that flux biases originate equally from clear‐sky and cloudy parts of the radiation field. Simulated cloud amounts and cloud‐radiative effects are dominated by marine, shallow clouds, and their behavior is highly resolution dependent. Bias compensation between shortwave and longwave flux biases, seen in the coarser simulations, is significantly diminished for higher resolutions. Based on the analysis results, it is argued that cloud‐microphysical and cloud‐radiative properties have to be adjusted to further improve agreement with observed cloud‐radiative effects.

Robust Acceleration of Stratospheric Moistening and Its Radiative Feedback Under Greenhouse Warming

AbstractStratospheric water vapor (SWV) changes, in response to increasing CO2, as a feedback component may play an important role in the Earth's energy budget. It has drawn extensive studies in the past decade. Here, we calculate the SWV climate feedback using the 150‐year CO2 forcing (1pctCO2) simulations in the CMIP6 ensemble of models. All models robustly show a moistening of the stratosphere, causing a positive radiative feedback to surface warming. We find that the stratospheric moistening rate and the SWV feedback both increase with surface warming. The moistening occurs at a rate of 0.9 ± 0.1 ppmv K−1 and its radiative feedback measured by the fixed dynamical heating method is 0.11 ± 0.02 W m−2 K−1 in the first 50 model years; the moistening rate increases to 1.2 ± 0.2 ppmv K−1 and the feedback increases to 0.16 ± 0.03 W m−2 K−1 in the last 50 model years when the global‐mean surface temperature is 3.3 K warmer. These increases are found to be caused by an amplified rate of tropical tropopause warming with respect to surface warming, which is 0.6 and 1.1 K K−1 for the two 50‐year periods, respectively. We conclude that the SWV feedback is strengthening with surface warming, which can contribute to increasing climate sensitivity in the future under global warming.

An Effective Method for Detecting Clouds in GaoFen-4 Images of Coastal Zones

Cloud-cover information is important for a wide range of scientific studies, such as the studies on water supply, climate change, earth energy budget, etc. In remote sensing, correct detection of clouds plays a crucial role in deriving the physical properties associated with clouds that exert a significant impact on the radiation budget of planet earth. Although the traditional cloud detection methods have generally performed well, these methods were usually developed specifically for particular sensors in a particular region with a particular underlying surface (e.g., land, water, vegetation, and man-made objects). Coastal regions are known to have a variety of underlying surfaces, which represent a major challenge in cloud detection. Therefore, there is an urgent requirement for developing a cloud detection method that could be applied to a variety of sensors, situations, and underlying surfaces. In the present study, a cloud detection method based on spatial and spectral uniformity of clouds was developed. In addition to having a spatially uniform texture, a spectrally approximate value was also present between the blue and green bands of the cloud region. The blue and green channel data appeared more uniform over the cloudy region, i.e., the entropy of the cloudy region was lower than that of the cloud-free region. On the basis of this difference in entropy, it would be possible to categorize the satellite images into cloud region images and cloud-free region images. Furthermore, the performance of the proposed method was validated by applying it to the data from various sensors across the coastal zone of the South China Sea. The experimental results demonstrated that compared to the existing operational algorithms, EN-clustering exhibited higher accuracy and scalability, and also performed robustly regardless of the spatial resolution of the different satellite images. It is concluded that the EN-clustering algorithm proposed in the present study is applicable to different sensors, different underlying surfaces, and different regions, with the support of NDSI and NDBI indices to remove the interference information from snow, ice, and man-made objects.

Diurnal Black-Sky Surface Albedo Parameterization of Snow

AbstractSurface albedo, the fraction of incoming solar radiation reflected hemispherically by the surface, is an essential climate variable (ECV) directly related to the energy budget of Earth. The presence and properties of snow cover alter surface albedo significantly, with variability in temporal scales reaching from seasonal to diurnal. The diurnal variation of snow albedo is typically parameterized with the solar zenith angle, but it cannot take into account asymmetry with respect to midday. Using the solar azimuth angle instead is suggested, since especially in the melting season the snow albedo varies highly asymmetrically during the day. To derive a general time- and latitude-independent formula, the azimuth angle values are normalized. Baseline Surface Radiation Network data are used to derive an empirical formula for the diurnal variation of snow black-sky surface albedo. The overall accuracy is on the order of 0.02, and the relative accuracy is about 3%.

Abundances and Microphysical Properties of Light‐Absorbing Iron Oxide and Black Carbon Aerosols Over East Asia and the Arctic

AbstractBlack carbon (BC), brown carbon, and light‐absorbing iron oxides (FeOx) aerosols affect Earth's energy budget through their strong absorption of solar radiation. FeOx aerosols can also affect global biogeochemical cycles through their role as a nutrient for oceanic phytoplankton. However, observational data for these aerosols required for evaluating their effects using global models are scarce, especially for FeOx. Here, we summarize and compare the data sets of BC and FeOx from five ground‐based and three aircraft observation campaigns conducted in the East Asian and Arctic regions during the 2009–2018 period acquired using a modified single‐particle soot photometer. In these campaigns, >80% of FeOx‐containing aerosols in the 170–270 nm FeOx core size range had microphysical features indicating an anthropogenic origin. The particle size distribution for each of the BC and FeOx was similar in all of the data sets except for those dominated by fresh urban pollution or pristine Arctic air. The campaign‐averaged mass concentrations of FeOx and BC were ~60–360 ng/m3 and ~240–1,300 ng/m3, respectively, in East Asia, and ~6 ng/m3 and ~20–30 ng/m3, respectively, in the Arctic. The campaign‐averaged FeOx/BC mass concentration ratio varied within a narrow range of 0.2–0.6 in both East Asian and Arctic regions. In every campaign, FeOx, BC, and carbon monoxide were tightly correlated with each other with similar slope to the urban campaigns (around Tokyo), implying the spatiotemporal variation of anthropogenic FeOx emission around northern middle‐to‐high latitudes is similar to those of anthropogenic BC and CO emissions.

Comparison of Cloud‐Top Property Retrievals From Advanced Himawari Imager, MODIS, CloudSat/CPR, CALIPSO/CALIOP, and Radiosonde

AbstractThe information on cloud properties and microphysical characteristics is critical for environmental research and application, such as that on weather, climate, hydrology, and green energy and Earth energy budget. The launch of the new‐generation geostationary satellite, for example, the Japanese Himawari‐8, enables retrieval of cloud information through multichannel observation. To confirm the retrievals from the Advanced Himawari Imager (AHI) onboard Himawari‐8 (Himawari‐8/AHI), this study accessed the cloud retrievals from AHI and compare them against those obtained from spaceborne passive and active sensors on the low Earth orbit satellites, such as NASA's CloudSat, Cloud‐Aerosol Lidar and Infrared Pathfinder Satellite Observations (CALIPSO). The atmospheric thermodynamic state from in situ radiosonde provides another dimension for evaluating the retrieved cloud‐top temperature and height, which were obtained and analyzed during two research cruises over the South China Sea during monsoon onset season with large cloud variability to ensure the comprehensive intercomparisons. The findings show that the cloud‐top altitude, cloud optical thickness, and cloud effective particle radius retrieved from AHI are consistent with passive Moderate Resolution Imaging Spectroradiometer (MODIS) data. Furthermore, both spaceborne active Cloud Priofiling Radar (CPR) and Cloud‐Aerosol Lidar with Orthogonal Polarization (CALIOP) data confirm the low uncertainty of cloud‐top altitude, particularly when the cloud is optically thick. Large cloud‐top altitude discrepancy among these data in the optically thin cloud might be due to the limited AHI spectral channels or instrumental spatial resolutions. The cloud‐top temperature and altitudes in either liquid or ice phase cloud agree well with collocated sounding profiles, with low difference of 1 K and 170 m, respectively.

Response of surface shortwave cloud radiative effect to greenhouse gases and aerosols and its impact on summer maximum temperature

Abstract. Shortwave cloud radiative effects (SWCREs), defined as the difference of the shortwave radiative flux between all-sky and clear-sky conditions at the surface, have been reported to play an important role in influencing the Earth's energy budget and temperature extremes. In this study, we employed a set of global climate models to examine the SWCRE responses to CO2, black carbon (BC) aerosols, and sulfate aerosols in boreal summer over the Northern Hemisphere. We found that CO2 causes positive SWCRE changes over most of the NH, and BC causes similar positive responses over North America, Europe, and eastern China but negative SWCRE over India and tropical Africa. When normalized by effective radiative forcing, the SWCRE from BC is roughly 3–5 times larger than that from CO2. SWCRE change is mainly due to cloud cover changes resulting from changes in relative humidity (RH) and, to a lesser extent, changes in cloud liquid water, circulation, dynamics, and stability. The SWCRE response to sulfate aerosols, however, is negligible compared to that for CO2 and BC because part of the radiation scattered by clouds under all-sky conditions will also be scattered by aerosols under clear-sky conditions. Using a multilinear regression model, it is found that mean daily maximum temperature (Tmax) increases by 0.15 and 0.13 K per watt per square meter (W m−2) increase in local SWCRE under the CO2 and BC experiment, respectively. When domain-averaged, the contribution of SWCRE change to summer mean Tmax changes was 10 %–30 % under CO2 forcing and 30 %–50 % under BC forcing, varying by region, which can have important implications for extreme climatic events and socioeconomic activities.

A fast visible-wavelength 3D radiative transfer model for numerical weather prediction visualization and forward modeling

Abstract. Solar radiation is the ultimate source of energy flowing through the atmosphere; it fuels all atmospheric motions. The visible-wavelength range of solar radiation represents a significant contribution to the earth's energy budget, and visible light is a vital indicator for the composition and thermodynamic processes of the atmosphere from the smallest weather scales to the largest climate scales. The accurate and fast description of light propagation in the atmosphere and its lower-boundary environment is therefore of critical importance for the simulation and prediction of weather and climate. Simulated Weather Imagery (SWIm) is a new, fast, and physically based visible-wavelength three-dimensional radiative transfer model. Given the location and intensity of the sources of light (natural or artificial) and the composition (e.g., clear or turbid air with aerosols, liquid or ice clouds, precipitating rain, snow, and ice hydrometeors) of the atmosphere, it describes the propagation of light and produces visually and physically realistic hemispheric or 360∘ spherical panoramic color images of the atmosphere and the underlying terrain from any specified vantage point either on or above the earth's surface. Applications of SWIm include the visualization of atmospheric and land surface conditions simulated or forecast by numerical weather or climate analysis and prediction systems for either scientific or lay audiences. Simulated SWIm imagery can also be generated for and compared with observed camera images to (i) assess the fidelity and (ii) improve the performance of numerical atmospheric and land surface models. Through the use of the latter in a data assimilation scheme, it can also (iii) improve the estimate of the state of atmospheric and land surface initial conditions for situational awareness and numerical weather prediction forecast initialization purposes.

Atmospheric observations of the water vapour continuum in the near-infrared windows between 2500 and 6600 cm−1

Abstract. Water vapour continuum absorption is potentially important for both closure of the Earth's energy budget and remote sensing applications. Currently, there are significant uncertainties in its characteristics in the near-infrared atmospheric windows at 2.1 and 1.6 µm. There have been several attempts to measure the continuum in the laboratory; not only are there significant differences amongst these measurements, but there are also difficulties in extrapolating the laboratory data taken at room temperature and above to temperatures more widely relevant to the atmosphere. Validation is therefore required using field observations of the real atmosphere. There are currently no published observations in atmospheric conditions with enough water vapour to detect a continuum signal within these windows or where the self-continuum component is significant. We present observations of the near-infrared water vapour continuum from Camborne, UK, at sea level using a Sun-pointing, radiometrically calibrated Fourier transform spectrometer in the window regions between 2000 and 10 000 cm−1. Analysis of these data is challenging, particularly because of the need to remove aerosol extinction and the large uncertainties associated with such field measurements. Nevertheless, we present data that are consistent with recent laboratory datasets in the 4 and 2.1 µm windows (when extrapolated to atmospheric temperatures). These results indicate that the most recent revision (3.2) of the MT_CKD foreign continuum, versions of which are widely used in atmospheric radiation models, requires strengthening by a factor of ∼5 in the centre of the 2.1 µm window. In the higher-wavenumber window at 1.6 µm, our estimated self- and foreign-continua are significantly stronger than MT_CKD. The possible contribution of the self- and foreign-continua to our derived total continuum optical depth is estimated by using laboratory or MT_CKD values of one, to estimate the other. The obtained self-continuum shows some consistency with temperature-extrapolated laboratory data in the centres of the 4 and 2.1 µm windows. The 1.6 µm region is more sensitive to atmospheric aerosol and continuum retrievals and therefore more uncertain than the more robust results at 2.1 and 4 µm. We highlight the difficulties in observing the atmospheric continuum and make the case for additional measurements in both the laboratory and field and discuss the requirements for any future field campaign.

Spectral albedo measurements over snow-covered slopes: theory and slope effect corrections

Abstract. Surface albedo is an essential variable to determine the Earth's surface energy budget, in particular for snow-covered areas where it is involved in one of the most powerful positive feedback loops of the climate system. In situ measurements of broadband and spectral albedo are therefore common. However they are subject to several artefacts. Here we investigate the sensitivity of spectral albedo measurements to surface slope, and we propose simple correction algorithms to retrieve the intrinsic albedo of a slope from measurements, as if it were flat. For this, we first derive the analytical equations relating albedo measured on a slope to intrinsic direct and diffuse albedo, the apportionment between diffuse and direct incoming radiation, and slope inclination and aspect. The theory accounts for two main slope effects. First, the slope affects the proportion of solar radiation intercepted by the surface relative to that intercepted by the upward-looking, horizontal, sensor. Second, the upward- and downward-looking sensors receive reduced radiation from the sky and the surface respectively and increased radiation from neighbouring terrain. Using this theory, we show that (i) slope has a significant effect on albedo (over 0.01) from as little as a ≈1∘ inclination, causing distortions of the albedo spectral shape; (ii) the first-order slope effect is sufficient to fully explain measured albedo up to ≈15∘, which we designate “small-slope approximation”; and (iii) for larger slopes, the theory depends on the neighbouring slope geometry and land cover, leading to much more complex equations. Next, we derive four correction methods from the small-slope approximation, to be used depending on whether (1) the slope inclination and orientation are known or not, (2) the snow surface is free of impurities or dirty, and (3) a single or a time series of albedo measurements is available. The methods applied to observations taken in the Alps on terrain with up to nearly 20∘ slopes prove the ability to recover intrinsic albedo with a typical accuracy of 0.03 or better. From this study, we derive two main recommendations for future field campaigns: first, sloping terrain requires more attention because it reduces the measurement accuracy of albedo even for almost invisible slopes (1–2∘). Second, while the correction of the slope effect is possible, it requires additional information such as the spectral diffuse and direction partitioning and if possible the actual slope inclination and aspect, especially when the absence of impurities can not be assumed.