Top Of The Atmosphere Research Articles

Radiative Energy Budget for East Asia Based on GK-2A/AMI Observation Data

The incident and emitted radiative energy data for the top of the atmosphere (TOA) are essential in climate research. Since East Asia (11–61°N, 80–175°E) is complexly composed of land and ocean, real-time satellite data are used importantly for analyzing the detailed energy budget or climate characteristics of this region. Therefore, in this study, the radiative energy budget for East Asia, during the year 2021, was analyzed using GEO-KOMPSAT-2A/Advanced Metrological Imager (GK-2A/AMI) and the European Centre for Medium-range Weather Forecasts reanalysis (ERA5) data. The results showed that the net fluxes for the TOA and surface were −4.09 W·m−2 and −8.24 W·m−2, respectively. Thus, the net flux difference of 4.15 W·m−2 between TOA and surface implied atmospheric warming. These results, produced by GK-2A/AMI, were well-matched with the ERA5 data. However, they varied with surface characteristics; the atmosphere over ocean areas warmed because of the large amounts of longwave radiation emitted from surfaces, while the atmosphere over the plain area was relatively balanced and the atmosphere over the mountain area was cooled because large amount of longwave radiation was emitted to space. Although the GK2A/AMI radiative products used for this study have not yet been sufficiently compared with surface observation data, and the period of data used was only one year, they were highly correlated with the CERES (Clouds and the Earth’s Radiant Energy System of USA), HIMAWARI/AHI (Geostationary Satellite of Japan), and ERA5 data. Therefore, if more GK-2A/AMI data are accumulated and analyzed, it could be used for the analysis of radiant energy budget and climate research for East Asia, and it will be an opportunity to greatly increase the utilization of total meteorological products of 52 types, including radiative products.

The influence of dust aerosols on solar radiation and near-surface temperature during a severe duststorm transport episode

In the west of China, a rarely seen black storm, with a high intensity of dust aerosols and a large area of influence, occurred from April 26–29, 2015, for the first time, after more than 30 years. Based on the regional climate model (RegCM version 4.6), combined with Moderate Resolution Imaging Spectroradiometer (MODIS) satellite retrieval, meteorological, and environmental data, this work presents the pollution situation, weather background, and backward trajectory during the black storm process. In addition, we analyzed the temporal–spatial distribution of aerosol optical depth (AOD) and the impacts of dust aerosols on solar radiation and near-surface temperature under this extreme weather condition. We discovered that this black storm process was caused by the surface cold high pressure and frontal transit under the background of the upper-air circulation of “two troughs and two ridges.” The pollutants primarily from Xinjiang and the Central Asia region, along with the airflow, entered northern Xinjiang almost simultaneously with the southwest airflow, piled up along the Tianshan Mountains, and then crossed the mountains into southern Xinjiang. In addition, the areas with high AOD were mostly in the desert regions and basins, whereas the low-value areas were mountainous areas with relatively high altitudes due to the effect of geographical and climatic conditions. The AOD from RegCM 4.6 was generally lower, unlike the MODIS AOD. Moreover, the dust aerosols from this black storm caused a significant decline in net short-wave radiation (NSR) both at the top of the atmosphere (TOA) and surface. The cooling effect was more significant in the region with high AOD. For the areas where the AOD was higher than 0.7, the net short-wave radiative forcing of dust aerosols (ADRF) at the surface was above −70 W•m−2; on the other hand, the cooling effect at the TOA was not as significant as that at the surface, with the ADRFTOA being only about a quarter of the ADRFSUR. The ADRFSUR could reduce the near-surface temperature, and the region with a large temperature drop corresponded to the high-value areas of ADRFSUR/AOD. During this black storm, the near-surface temperature response to dust aerosols reached 0.40°C–2.9°C with a significant temperature drop because of cold air.

On the use of Infrared Atmospheric Sounding Interferometer (IASI) spectrally resolved radiances to test the EC-Earth climate model (v3.3.3) in clear-sky conditions

Abstract. The long-term comparison between simulated and observed spectrally resolved outgoing longwave radiation (OLR) can represent a stringent test for the direct verification and improvement of general circulation models (GCMs), which are regularly tuned by adjusting parameters related to subgrid processes not explicitly represented in the model to constrain the integrated OLR energy fluxes to observed values. However, a good agreement between simulated and observed integrated OLR fluxes may be obtained from the cancellation of opposite-in-sign systematic errors localized in specific spectral ranges. Since the mid-2000s, stable hyperspectral observations of the mid-infrared region (667 to 2750 cm−1) of the Earth emission spectrum have been provided by different sensors (e.g. AIRS, IASI and CrIS). Furthermore, the FORUM (Far-infrared Outgoing Radiation Understanding and Monitoring) mission, selected to be the ninth ESA Earth Explorer, will measure, starting from 2027, the terrestrial radiation emitted to space at the top of the atmosphere (TOA) from 100 to 1600 cm−1, filling the observational gap in the far-infrared (FIR) region, from 100 to 667 cm−1. In this work, in anticipation of FORUM measurements, we compare Infrared Atmospheric Sounding Interferometer (IASI) Metop-A observations to radiances simulated on the basis of the atmospheric fields predicted by the EC-Earth Global Climate Model (version 3.3.3) in clear-sky conditions. To simulate spectra based on the atmospheric and surface state provided by the climate model, the radiative transfer model σ-IASI has been integrated in the Cloud Feedback Model Intercomparison Project (COSP) package. Therefore, online simulations, provided by the EC-Earth model equipped with the new COSP–σ-IASI module, have been performed in clear-sky conditions with prescribed sea surface temperature and sea ice concentration, every 6 h, over a time frame consistent with the availability of IASI data. Systematic comparisons between observed and simulated brightness temperature (BT) have been performed in 10 cm−1 spectral intervals, on a global scale over the ocean, with a specific focus on the latitudinal belt between 30∘ S and 30∘ N. The analysis has shown a warm BT bias of about 3.5 K in the core of the CO2 absorption band and a cold BT bias of approximately 1 K in the wing of the CO2 band, due to a positive temperature bias in the stratosphere and a negative temperature bias in the middle troposphere of the climate model, respectively. Finally, considering a warm BT bias in the rotational–vibrational water vapour band, we have highlighted a dry bias of the water vapour concentration in the upper troposphere of the model.

Observations on the decadal variability of aerosol in eastern Himalayan foothills: Evidence of an anthropologically induced positive shift

The decadal variability of direct radiative effects of aerosols is investigated at Dibrugarh, a site in northeast India (NEI) at the eastern Himalayan foothills, primarily using multi-wavelength solar radiometer measurements spanning from October 2001 to February 2020. The ground-based aerosol observations are combined with satellite remote sensing, reanalysis data, and model simulations to study the change in atmospheric particle loading over the region. Observations indicate a statistically significant increase (∼0.015 yr−1) in Aerosol Optical Depth (AOD) during the last two decades in line with an increase in human activity. As compared to 2001–2007 (we call it as Stage I), the aerosol burden has grown rapidly during 2008 until 2020 (Stage II). AOD at 500 nm is found to increase by ∼40% from Stage I to Stage II, resulting in an increase in the aerosol direct radiative forcing (DRF) at the top of the atmosphere (TOA) by ∼43% during stage II (∼−16.0 W m-2), from the base value of −11.2 W m−2 in Stage I. Decreasing biomass burning activities, black carbon aerosol mass concentration, and high sulfate and organic aerosols are the primary factors responsible for the trend in TOA cooling by −0.46 W m−2 yr−1. This is further aided by the decrease in rainfall over NEI. MERRA-2 data analysis shows a similar enhancements in aerosol load over the entire NEI and the adjacent highly polluted Indo-Gangetic Plains (IGP). A similar feature is seen over the IGP, primarily driven by anthropogenic emissions, but precedes that in NEI by about a year. A simulation of the regional climate model (RegCM) over the south Asian domain quantifies the contribution of aerosol loading over NEI due to the aerosols carried from the IGP. In the highest aerosol loading period, about 12–30% of the aerosols, equivalent to 15–30% of atmospheric warming, are transported from the IGP to the NEI.

Reconstructing volcanic radiative forcing since 1990, using a comprehensive emission inventory and spatially resolved sulfur injections from satellite data in a chemistry-climate model

Abstract. This paper presents model simulations of stratospheric aerosols with a focus on explosive volcanic eruptions. Using various (occultation and limb-based) satellite instruments, providing vertical profiles of sulfur dioxide (SO2) and aerosol extinction, we characterized the chemical and radiative influence of volcanic aerosols for the period between 1990 and 2019. We established an improved and extended volcanic SO2 emission inventory that includes more than 500 explosive volcanic eruptions reaching the upper troposphere and the stratosphere. Each perturbation identified was derived from the satellite data and incorporated as a three-dimensional SO2 plume into a chemistry-climate model without the need for additional assumptions about altitude distribution and eruption duration as needed for a “point source” approach. The simultaneous measurements of SO2 and aerosol extinction by up to four satellite instruments enabled a reliable conversion of extinction measurements into injected SO2. In the chemistry-climate model, the SO2 from each individual plume was converted into aerosol particles and their optical properties were determined. Furthermore, the aerosol optical depth (AOD) and the instantaneous radiative forcing on climate were calculated online. Combined with model improvements, the results of the simulations are consistent with the observations of the various satellites. Slight deviations between the observations and model simulations were found for the large volcanic eruption of Pinatubo in 1991 and cases where simultaneous satellite observations were not unique or too sparse. Weak- and medium-strength volcanic eruptions captured in satellite data and the Smithsonian database typically inject about 10 to 50 kt SO2 directly into the upper troposphere/lower stratosphere (UTLS) region or the sulfur species are transported via convection and advection. Our results confirm that these relatively minor eruptions, which occur quite frequently, can nevertheless contribute to the stratospheric aerosol layer and are relevant for the Earth's radiation budget. These minor eruptions cause a total global instantaneous radiative forcing of the order of −0.1 W m−2 at the top of the atmosphere (TOA) compared to a background stratospheric aerosol forcing of about −0.04 W m−2. Medium-strength eruptions injecting about 400 kt SO2 into the stratosphere or accumulation of consecutive smaller eruptions can lead to a total instantaneous forcing of about −0.3 W m−2. We show that it is critical to include the contribution of the extratropical lowermost stratospheric aerosol in the forcing calculations.

Investigating the radiative effect of Arctic cirrus measured in situ during the winter 2015–2016

Abstract. The radiative energy budget in the Arctic undergoes a rapid transformation compared with global mean changes. Understanding the role of cirrus clouds in this system is vital, as they interact with short- and long-wave radiation, and the presence of cirrus can be decisive as to a net gain or loss of radiative energy in the polar atmosphere. In an effort to derive the radiative properties of cirrus in a real scenario in this sensitive region, we use in situ measurements of the ice water content (IWC) performed during the Polar Stratosphere in a Changing Climate (POLSTRACC) aircraft campaign in the boreal winter and spring 2015–2016 employing the German High Altitude and Long Range Research Aircraft (HALO). A large dataset of IWC measurements of mostly thin cirrus at high northern latitudes was collected in the upper troposphere and also frequently in the lowermost stratosphere. From this dataset, we select vertical profiles that sampled the complete vertical extent of cirrus cloud layers. These profiles exhibit a vertical IWC structure that will be shown to control the instantaneous radiative effect in both the long and short wavelength regimes in the polar winter. We perform radiative transfer calculations with the uvspec model from the libRadtran software package in a one-dimensional column between the surface and the top of the atmosphere (TOA), using the IWC profiles as well as the state of the atmospheric column at the time of measurement, as given by weather forecast products, as input. In parameter studies, we vary the surface albedo and solar zenith angle in ranges typical of the Arctic region. We find the strongest (positive) radiative forcing up to about 48 W m−2 for cirrus over bright snow, whereas the forcing is mostly weaker and even ambiguous, with a rather symmetric range of values down to -35Wm-2, over the open ocean in winter and spring. The IWC structure over several kilometres in the vertical affects the irradiance at the TOA via the distribution of optical thickness. We show the extent to which IWC profiles with a coarser vertical resolution can reflect this effect. Further, a highly variable heating rate profile within the cloud is found which drives dynamical processes and contributes to the thermal stratification at the tropopause. Our case studies highlight the importance of a detailed resolution of cirrus clouds and the consideration of surface albedo for estimations of the radiative energy budget in the Arctic.

Impact of Rain Effects on L-Band Passive Microwave Satellite Observations Over the Ocean

L-band passive microwave remote sensing of ocean surfaces is hampered by uncertainties due to the contribution of precipitation. However, modeling and correcting rain effect are complicated because all the precipitation contributions from the atmosphere and sea surface, including the rain effect in the atmosphere, water refreshing, rain-perturbed sea surface, and rain-induced local wind, are coupled. These rain effects significantly alter L-band microwave satellite measurements. This study investigates the impact of precipitation on the satellite measured brightness temperature (TB) and proposes a correction method. The results show that the rain-induced TB increase is approximately 0.5–1.4 K in the atmosphere, depending on the incidence angle and polarization. Moreover, the rain effect on sea surface emissions is more significant than that in the atmosphere. The result shows that rain effects on sea surface emissions are higher than 3 K for both polarizations when the rain rate is higher than 20 mm/h. We validate the rain effect correction model based on Soil Moisture Active Passive (SMAP) observations. The results show that the TBs at the top of the atmosphere (TOA) simulated by the model are in a good agreement with the SMAP observations, with root-mean-square errors (RMSEs) of 1.137 and 1.519 K for the horizontal and vertical polarizations, respectively, indicating a relatively high accuracy of the established model. Then, a correction model is applied to sea surface salinity (SSS) retrieval for analysis, and the results show that the developed model corrects the underestimation in SSS retrieval. Finally, the rain effect correction model is validated with Aquarius observations in three regions, and it is found that the RMSEs of the corrected TOA TBs range from 1.013 to 1.608 K, which is higher than those without rain effect correction (RMSEs range from 2.078 to 3.894 K). Overall, the model developed in this study provides relatively a good accuracy for rain effect correction.

A Physical-Based Method for Pixel-by-Pixel Quantifying Uncertainty of Land Surface Temperature Retrieval From Satellite Thermal Infrared Data Using the Generalized Split-Window Algorithm

Land surface temperature (LST) is an important physical parameter at the interface between the Earth’s surface and the atmosphere. Accurately quantifying LST uncertainty is essential for the generation of a long-term and consistent LST Climate Data Record (CDR) or Earth System Data Record (ESDR) from either multiple sensors or algorithms. In this study, a physical-based method was proposed to quantify the uncertainty of LST retrieval from satellite thermal infrared data using the generalized split-window (GSW) algorithm. LST uncertainties were parameterized as a function of brightness temperature at the top of the atmosphere (TOA) and surface emissivity in two split-window channels, which are two key input parameters in the GSW algorithm, as well as their uncertainties. The performance of the parameterized uncertainty model was evaluated according to simulation dataset at six prescribed viewing zenith angles (VZAs) of 0°, 33.56°, 44.42°, 51.32°, 56.25°, and 60°, with a root mean squared error (RMSE) of 0.001 K. The coefficients of the parameterized uncertainty model at arbitrary VZA within a sensor’ field of view (FOV) can be obtained by linear interpolation of the coefficients at the six prescribed VZAs. Once the coefficients of the parameterized uncertainty model for each pixel are available, total LST uncertainties can be quantified on a pixel-by-pixel basis. As an example, the parameterized uncertainty model was applied to actual MODIS data for displaying the spatial distribution of LST uncertainties. The results indicate that the parameterized uncertainty model can well characterize the spatial variation in LST uncertainties over various land cover types.

Nutritional monitoring of boron in Eucalyptus spp. in the Brazilian cerrado by multispectral bands of the MSI sensor (Sentinel-2)

B deficiency is one of the most limiting factors for the growth of Eucalyptus spp. in Brazil, especially in the cerrado region, where there is the greatest expansion of forest production of the species. Based on multi or hyperspectral sensors and digital image processing techniques, the application in diagnosis is fast, nondestructive and local in applications with plants. Our hypothesis is that the use of orbital sensors through the spectral bands is sensitive in the diagnosis of B deficiency or toxicity in adult Eucalyptus spp. in the Brazilian Cerrado region. The main objective of this study was to discriminate the adequate levels and boron deficiency from the supervised classification with the SAM algorithm in an area with Eucalyptus spp plantation. and to verify the performance of vegetation indices in distinguishing micronutrient. The experiment was carried out at Brejo Seco Farm in the rural zone of Baixa Grande do Ribeiro municipality (Cerrado biome) in Piauí State, Brazil. Eucalyptus clones MA-2000 (from controlled pollination between Eucalyptus urophylla x Eucalyptus tereticornis) trees that were ten years old were considered. This clone is adapted to the edaphic conditions of the region. The planting occurred without amendments or fertilizers, according to a 3 m × 3 m spacing with a density of approximately 1111 plants hectare−1. The orbital images used were those of the MSI/Sentinel-2 System/sensor with Level-1C, processed with values of reflectance at the top of the atmosphere (TOA). Deficiency classifications were then performed using the spectral angle mapping (SAM) algorithm and the vegetation indices NDVI, NDRE, EVI, CI, PRSI, CCCI, MTCI and HMSSI. Subsequently, a multivariate analysis of canonical variables was performed to verify the interrelationship between boron levels and each group of variables evaluated in the experiment. From these results, it is possible to discriminate levels of deficient and adequate boron in juvenile Eucalyptus spp. based on the wavelengths of the MSI/Sentinel-2 sensor system. Vegetation indices can be used to monitor boron levels, with the normalized difference vegetation index (NDVI) being the most efficient in discriminating adequate boron levels in Eucalyptus spp. plants.

Predicting the Forest Canopy Height from LiDAR and Multi-Sensor Data Using Machine Learning over India

Forest canopy height estimates, at a regional scale, help understand the forest carbon storage, ecosystem processes, the development of forest management and the restoration policies to mitigate global climate change, etc. The recent availability of the NASA’s Global Ecosystem Dynamics Investigation (GEDI) LiDAR data has opened up new avenues to assess the plant canopy height at a footprint level. Here, we present a novel approach using the random forest (RF) for the wall-to-wall canopy height estimation over India’s forests (i.e., evergreen forest, deciduous forest, mixed forest, plantation, and shrubland) by employing the high-resolution top-of-the-atmosphere (TOA) reflectance and vegetation indices, the synthetic aperture radar (SAR) backscatters, the topography and tree canopy density, as the proxy variables. The variable importance plot indicated that the SAR backscatters, tree canopy density and the topography are the most influential height predictors. 33.15% of India’s forest cover demonstrated the canopy height <10 m, while 44.51% accounted for 10–20 m and 22.34% of forests demonstrated a higher canopy height (>20 m). This study advocates the importance and use of GEDI data for estimating the canopy height, preferably in data-deficit mountainous regions, where most of India’s natural forest vegetation exists.

The simulation of mineral dust in the United Kingdom Earth System Model UKESM1

Abstract. Mineral dust plays an important role in Earth system models and is linked to many components, including atmospheric wind speed, precipitation and radiation, surface vegetation cover and soil properties and oceanic biogeochemical systems. In this paper, the dust scheme in the first configuration of the United Kingdom Earth System Model UKESM1 is described, and simulations of dust and its radiative effects are presented and compared with results from the parallel coupled atmosphere–ocean general circulation model (GCM) HadGEM3-GC3.1. Not only changes in the driving model fields but also changes in the dust size distribution are shown to lead to considerable differences to the present-day dust simulations and to projected future changes. UKESM1 simulations produce a present-day, top-of-the-atmosphere (ToA) dust direct radiative effect (DRE – defined as the change in downward net flux directly due to the presence of dust) of 0.086 W m−2 from a dust load of 19.5 Tg. Under climate change pathways these values decrease considerably. In the 2081–2100 mean of the Shared Socioeconomic Pathway SSP5–8.45 ToA DRE reaches 0.048 W m−2 from a load of 15.1 Tg. In contrast, in HadGEM3-GC3.1 the present-day values of −0.296 W m−2 and 15.0 Tg are almost unchanged at −0.289 W m−2 and 14.5 Tg in the 2081–2100 mean. The primary mechanism causing the differences in future dust projections is shown to be the vegetation response, which dominates over the direct effects of warming in our models. Though there are considerable uncertainties associated with any such estimates, the results presented demonstrate both the importance of the size distribution for dust modelling and also the necessity of including Earth system processes such as interactive vegetation in dust simulations for climate change studies.

3D cloud envelope and cloud development velocity from simulated CLOUD (C3IEL) stereo images

Abstract. A method to derive the 3D cloud envelope and the cloud development velocity from high spatial and temporal resolution satellite imagery is presented. The CLOUD instrument of the recently proposed C3IEL mission lends itself well to observing at high spatial and temporal resolutions the development of convective cells. Space-borne visible cameras simultaneously image, under multiple view angles, the same surface domain every 20 s over a time interval of 200 s. In this paper, we present a method for retrieving cloud development velocity from simulated multi-angular, high-resolution top of the atmosphere (TOA) radiance cloud fields. The latter are obtained via the image renderer Mitsuba for a cumulus case generated via the atmospheric research model SAM and via the radiative transfer model 3DMCPOL, coupled with the outputs of an orbit, attitude, and camera simulator for a deep convective cloud case generated via the atmospheric research model Meso-NH. Matching cloud features are found between simulations via block matching. Image coordinates of tie points are mapped to spatial coordinates via 3D stereo reconstruction of the external cloud envelope for each acquisition. The accuracy of the retrieval of cloud topography is quantified in terms of RMSE and bias that are, respectively, less than 25 and 5 m for the horizontal components and less than 40 and 25 m for the vertical components. The inter-acquisition 3D velocity is then derived for each pair of tie points separated by 20 s. An independent method based on minimising the RMSE for a continuous horizontal shift of the cloud top, issued from the atmospheric research model, allows for the obtainment of a ground estimate of the velocity from two consecutive acquisitions. The mean values of the distributions of the stereo and ground velocities exhibit small biases. The width of the distributions is significantly different, with higher a distribution width for the stereo-retrieved velocity. An alternative way to derive an average velocity over 200 s, which relies on tracking clusters of points via image feature matching over several acquisitions, was also implemented and tested. For each cluster of points, mean stereo and ground positions were derived every 20 s over 200 s. The mean stereo and ground velocities, obtained as the slope of the line of best fit to the mean positions, are in good agreement.

Review of the Observed Energy Flow in the Earth System

The energy budget imbalance at the top of the atmosphere (TOA) and the energy flow in the Earth’s system plays an essential role in climate change over the global and regional scales. Under the constraint of observations, the radiative fluxes at TOA have been reconstructed prior to CERES (Clouds and the Earth’s Radiant Energy System) between 1985 and 2000. The total atmospheric energy divergence has been mass corrected based on ERA5 (the fifth generation ECMWF ReAnalysis) atmospheric reanalysis by a newly developed method considering the enthalpy removing of the atmospheric water vapor, which avoids inconsistencies due to the residual lateral total mass flux divergence in the atmosphere, ensuring the balances of the freshwater fluxes at the surface. The net surface energy flux (Fs) has been estimated using the residual method based on energy conservation, which is the difference between the net TOA radiative flux and the atmospheric energy tendency and divergence. The Fs is then verified directly and indirectly with observations, and results show that the estimated Fs in North Atlantic is superior to those from model simulations. This paper gives a brief review of the progress in the estimation of the observed energy flow in the Earth system, discusses some caveats of the existing method, and provides some suggestions for the improvements of the aforementioned data sets.

Size-resolved dust direct radiative effect efficiency derived from satellite observations

Abstract. The role of mineral dust aerosol in the global radiative energy budget is often quantified by the dust direct radiative effect (DRE). The dust DRE strongly depends on dust aerosol optical depth (DAOD), therefore, DRE efficiency (DREE = DRE / DAOD) is widely compared across different studies to eliminate differences due to the various dust loads. Nevertheless, DREE is still influenced by the uncertainties associated with dust particle size distribution (PSD) and optical properties. In this study, we derive a global clear-sky size-resolved DREE dataset in both shortwave (SW) and longwave (LW) at top of the atmosphere (TOA) and surface based on satellite observations (i.e., satellite-retrieved dust extinction spatial and vertical distributions). In the DREE dataset, dust geometric diameter from 0.1 to 100 µm is divided into 10 bins and the corresponding monthly mean DREE (with respect to DAOD at 532 nm) for each size bin is derived by using the Rapid Radiative Transfer Model (RRTM). Three sets of state of the art dust refractive indices (RI) and two sets of dust shape models (sphere vs. spheroid) are adopted to investigate the sensitivity of dust DREE to dust absorption and shape. As a result, the size-resolved dust DREE dataset contains globally distributed monthly mean dust DREE at TOA and surface for each of 10 size bins with 5∘ (longitude) ×2∘ (latitude) resolution as well as for each dust RI and shape combination. The size-resolved dust DREE dataset can be used to readily calculate global dust DRE for any DAOD and dust PSD, including the uncertainty in the DRE induced by dust microphysical properties, (e.g., dust PSD, RI and shape). By calculating dust DRE based on DAOD climatology retrieved from different satellite sensors and based on different dust PSD, we find that uncertainty in the spatial pattern of DAOD induces more than 10 % of the uncertainty in SW dust DRE at TOA. The observation-based dust PSD induces around 15–20 % uncertainty in dust DRE at TOA and in the atmosphere. The sensitivity assessments of dust DRE to dust RI and shape further suggest that dust nonsphericity induces a negligible effect on dust DRE estimations, while dust RI turns out to be the most important factor in determining dust DRE, particularly in SW.

Significant Effective Radiative Forcing of Stratospheric Wildfire Smoke

AbstractThe radiative forcing (RF) of volcanic sulfate is well quantified. However, the RF of pyrocumulonimbus (pyroCb) smoke with absorbing carbonaceous aerosols has not been considered in climate assessment reports. With the Community Earth System Model, we studied two record‐breaking wildfire events, the 2017 Pacific Northwest Event (PNE) and the 2019–2020 Australian New Year event (ANY), that perturbed stratospheric chemistry and the earth's radiation budget. We calculated a global annual‐mean effective RF (ERF) of −0.04 ± 0.02 and −0.17 ± 0.02 W/m2 at the top of the atmosphere (TOA) for PNE and ANY, respectively. The complexity of longwave RF led to an uncertainty of about 50% in the ERF at the TOA among climate models. We found that modeled ERF from wildfire smoke was 70%–270% more negative than the ERF of mass‐equivalent sulfate aerosol, highlighting its important role in the climate radiative budget.

Top-of-the-atmosphere reflected shortwave radiative fluxes from GOES-R

Abstract. Under the GOES-R activity, new algorithms are being developed at the National Oceanic and Atmospheric Administration (NOAA)/Center for Satellite Applications and Research (STAR) to derive surface and top-of-the-atmosphere (TOA) shortwave (SW) radiative fluxes from the Advanced Baseline Imager (ABI), the primary instrument on GOES-R. This paper describes a support effort in the development and evaluation of the ABI instrument capabilities to derive such fluxes. Specifically, scene-dependent narrow-to-broadband (NTB) transformations are developed to facilitate the use of observations from ABI at the TOA. Simulations of NTB transformations have been performed with MODTRAN 4.3 using an updated selection of atmospheric profiles and implemented with the final ABI specifications. These are combined with angular distribution models (ADMs), which are a synergy of ADMs from the Clouds and the Earth's Radiant Energy System (CERES) and from simulations. Surface conditions at the scale of the ABI products as needed to compute the TOA radiative fluxes come from the International Geosphere–Biosphere Programme (IGBP). Land classifications at 1/6∘ resolution for 18 surface types are converted to the ABI 2 km grid over the contiguous United States (CONUS) and subsequently re-grouped to 12 IGBP types to match the classification of the CERES ADMs. In the simulations, default information on aerosols and clouds is based on that used in MODTRAN. Comparison of derived fluxes at the TOA is made with those from CERES, and the level of agreement for both clear and cloudy conditions is documented. Possible reasons for differences are discussed. The product is archived and can be downloaded from the NOAA Comprehensive Large Array-data Stewardship System (CLASS).

GOES ABI Detection of Thin Cirrus over Land

Abstract This study develops a new thin cirrus detection algorithm applicable to overland scenes. The methodology builds from a previously developed overwater algorithm, which makes use of the Geostationary Operational Environmental Satellite 16 (GOES-16) Advanced Baseline Imager (ABI) channel 4 radiance (1.378-μm “cirrus” band). Calibration of this algorithm is based on coincident Cloud–Aerosol Lidar with Orthogonal Polarization (CALIOP) cloud profiles. Emphasis is placed on rejection of false detections that are more common in overland scenes. Clear-sky false alarm rates over land are examined as a function of precipitable water vapor (PWV), showing that nearly all pixels having a PWV of <0.4 cm produce false alarms. Enforcing an above-cloud PWV minimum threshold of ∼1 cm ensures that most low-/midlevel clouds are not misclassified as cirrus by the algorithm. Pixel-filtering based on the total column PWV and the PWV for a layer between the top of the atmosphere (TOA) and a predetermined altitude H removes significant land surface and low-/midlevel cloud false alarms from the overall sample while preserving over 80% of valid cirrus pixels. Additionally, the use of an aggressive PWV layer threshold preferentially removes noncirrus pixels such that the remaining sample is composed of nearly 70% cirrus pixels, at the cost of a much-reduced overall sample size. This study shows that lower-tropospheric clouds are a much more significant source of uncertainty in cirrus detection than the land surface.

Retrieving aerosols single scattering albedo from MODIS reflectances

Single scattering albedo (SSA) is a key parameter to estimate aerosol direct radiative forcing. However, retrieving SSA from satellite observations is still challenging. In this study, a new method optimizing the aerosol optical model based on four basic aerosol components is developed for retrieving SSA from Moderate Resolution Imaging Spectroradiometer (MODIS) data. The new method takes advantage of the relationship between aerosol composition and reflectance at multiple wavelengths to derive SSA, which considers the variation of aerosol species with time and location. A sensitivity study considering the uncertainties from the top of the atmosphere (TOA) apparent reflectance, aerosol optical depth (AOD) at 550 nm and land surface bidirectional reflectance distribution function (BRDF) parameters is performed to test the stability of the proposed method. The results demonstrate the high accuracy and robustness of the new method. The root mean square error (RMSE) is within 0.03 at 470 and 550 nm based on the sensitivity study. The aerosol components used in our method show better representativeness of real aerosol components than that used in the Second Simulation of a Satellite Signal in the Solar Spectrum - Vector (6SV) model. The aerosols SSA values are retrieved from real MODIS observations with the new method and compared with the AERONET SSA product at two polluted AERONET sites in Asia. A better consistency with the correlation coefficient (R) of 0.27– 0.55 and the RMSE within 0.04 at 470 and 550 nm wavelengths between MODIS SSA retrievals and the AERONET SSA product is obtained with the new method compared with that of deep blue (DB) SSA. The new method can help to better understand aerosol radiative forcing regionally and globally.

Long-Term Variations in Global Solar Radiation and Its Interaction with Atmospheric Substances at Qomolangma.

An empirical model to estimate global solar radiation was developed at Qomolangma Station using observed solar radiation and meteorological parameters. The predicted hourly global solar radiation agrees well with observations at the ground in 2008–2011. This model was used to calculate global solar radiation at the ground and its loss in the atmosphere due to absorbing and scattering substances in 2007–2020. A sensitivity analysis shows that the responses of global solar radiation to changes in water vapor and scattering factors (expressed as water-vapor pressure and the attenuation factor, AF, respectively) are nonlinear, and global solar radiation is more sensitive to changes in scattering than to changes in absorption. Further applying this empirical model, the albedos at the top of the atmosphere (TOA) and the surface in 2007–2020 were computed and are in line with satellite-based retrievals. During 2007–2020, the mean estimated annual global solar radiation increased by 0.22% per year, which was associated with a decrease in AF of 1.46% and an increase in water-vapor pressure of 0.37% per year. The annual mean air temperature increased by about 0.16 °C over the 14 years. Annual mean losses of solar radiation caused by absorbing and scattering substances and total loss were 2.55, 0.64, and 3.19 MJ m−2, respectively. The annual average absorbing loss was much larger than the scattering loss; their contributions to the total loss were 77.23% and 22.77%, indicating that absorbing substances play significant roles. The annual absorbing loss increased by 0.42% per year, and scattering and total losses decreased by 2.00% and 0.14% per year, respectively. The estimated and satellite-derived annual albedos increased at the TOA and decreased at the surface. This study shows that solar radiation and its interactions with atmospheric absorbing and scattering substances have played key but different roles in regional climate and climate change at the three poles.

An Investigation of the Ice Cloud Detection Sensitivity of Cloud Radars Using the Raman Lidar at the ARM SGP Site

The ice cloud detection sensitivity of the millimeter cloud radar (MMCR) and the Ka-band Zenith radar (KAZR) is investigated using a collocated Raman lidar (RL) at the Atmospheric Radiation Measurement Program Southern Great Plains site. Only profiles that are transparent to the RL with ice clouds only are considered in this study. The MMCR underestimates the RL ice cloud optical depth (COD) by 20%. The MMCR detects no ice clouds in 37% of the profiles. These profiles where ice cloud goes undetected by the MMCR typically contain very optically thin clouds, with a mean RL ice COD of 0.03. Higher ice cloud detection sensitivity is found for the KAZR, which underestimates the RL ice COD by 15%. The decrease in the ice COD bias for the KAZR compared to the MMCR is largely due to a decrease in the ice COD bias for the situation where the transparent profiles with ice clouds are detected by both the RL and cloud radar. The climatic net ice cloud radiative effects (CREs) from the RL at the top of the atmosphere (TOA) and the surface are 3.2 W m−2 and −0.6 W m−2, respectively. The ice CREs at the TOA and surface are underestimated for the MMCR by 0.7 W m−2 and 0.16 W m−2 (21% and 29%) and underestimated for the KAZR by 0.6 W m−2 and 0.14 W m−2 (17% and 24%). The ice clouds undetected by the cloud radars led to underestimating the climatic net cloud heating rates below 150 hPa by about 0–0.04 K day−1.