Shortwave Flux Research Articles

A Numerical Study of Effects of Radiation on Deep Convective Warm Based Cumulus Cloud Development with a 3-D Radiative Transfer Model

The effects of radiation heating and cooling on cumulus cloud development have been the focus of considerable attention for many years. However, it is still not clear how radiation impacts cloud droplet growth. Since cloud inhomogeneity has a great influence on radiation transmission, we coupled the 3D atmospheric radiative transfer model using the spherical harmonic discrete ordinate method with WRF-LES, which can improve the simulation accuracy of the inhomogeneous effect of clouds on radiation compared with that of the 1D radiation method. The shortwave and longwave radiation fluxes for upward and downward directions were simulated with different solar zenith angles. The comparison of 1D and 3D radiative solvers for deep convective cloud cases shows that the 3D radiative solver provides an accurate structure of solar and thermal radiation characteristics and the spatial distribution field. The solar radiation heating is likely to increase perpendicular to the solar incidence direction. For longwave radiation, the cooling effect on the cloud top and the heating effect on the cloud base are both more intense in the 3D radiation model. This study focuses on 3D cloud-radiative interactions in an inhomogeneous cloud field in a large eddy simulation, and the results suggest that compared with the widely used 1D radiative solver in WRF, the 3D radiation model can provide a precise description of the radiation field in an inhomogeneous atmosphere.

Satellite-observed changes of surface spectral reflectances due to solar farming and the implication for radiation budget

Increased deployment of solar farms in the last decade is coincident with continued monitoring of surface spectral reflectances by the moderate resolution imaging spectroradiometers (MODIS) aboard NASA Aqua satellite. By analyzing the surface spectral reflectances retrieved at seven MODIS shortwave bands, this study quantifies the changes of surface spectral reflectances caused by solar farms commissioned in the southwestern US. Our case study using one solar farm indicates a 20%–25% reduction of surface reflectance over the seven MODIS bands due to the solar panel installation. Radiative transfer calculation shows that such a reduction in surface spectral reflectance leads to a ∼23% decrease in the upward shortwave broadband flux at the surface and a ∼14%–18% decrease in the clear-sky reflected shortwave flux at the top of atmosphere (TOA). Though the MODIS surface reflectance retrievals can be affected by other factors such as aerosol or thin-cirrus contaminations, five out of six solar farm sites analyzed here show unambiguously detectable changes of surface reflectances due to solar panel installations. The brighter the surface is at a given MODIS band before the solar-farm construction, the larger the spectral reflectance reduction tends to be. If all the bright deserts, which occupies about 4% of the global surface, were covered with the solar panels similar to what has been studied here, the estimated instantaneous TOA shortwave radiative forcing would be no more than 1.1 W m−2.

Estimation of the distribution of the total net radiative flux from satellite and automatic weather station data in the Upper Blue Nile basin, Ethiopia

Net radiation is an important factor in studies of land–atmosphere processes, water resource management, and global climate change. This is particularly true for the Upper Blue Nile (UBN) basin, where significant parts of the basin are dry and evapotranspiration (ET) is a major mechanism for water loss. However, net radiation has not yet been appropriately parameterized in the basin. In this study, we estimated the instantaneous distribution of the net radiation flux in the basin using data from the Moderate Resolution Imaging Spectroradiometer (MODIS) sensor onboard the Terra satellite and Automatic Weather Station (AWS) data. Downward shortwave radiation and air temperature usually vary with topography, so we applied residual kriging spatial interpolation techniques to convert AWS data for point locations into gridded surface data. Simulated net radiation outputs were validated through comparison with independent field measurements. Validation results show that our method successfully reproduced the downward shortwave, upward shortwave, and net radiation fluxes. Using AWS data and residual kriging spatial interpolation techniques makes our results robust and comparable to previous works that used satellite data at a finer spatial resolution than MODIS. The estimated net shortwave, longwave, and total radiation fluxes were in close agreement with ground truth measurements, with mean bias (MB) values of − 14.84, 5.7, and 20.53 W m−2 and root mean square error (RMSE) values 83.43, 32.54, and 78.07 W m−2, respectively. The method presented here has potential applications in research focused on energy balance, ET estimation, and weather prediction for regions with similar physiographic features to those of the Nile basin.

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.

Field Assessment of Neighboring Building and Tree Shading Effects on the 3D Radiant Environment and Human Thermal Comfort in Summer within Urban Settlements in Northeast China

Shading is one of the most effective strategies to mitigate urban local-scale heat stress during summer. Therefore, this study investigates the effects of shading caused by buildings and trees via exhaustive field measurement research on urban outdoor 3D radiant environment and human thermal comfort. We analyzed the characteristics of micrometeorology and human thermal comfort at shaded areas, and compared the difference between building and tree shading effects as well as that between shaded and sunlit sites. The results demonstrate that mean radiant temperature Tmrt (mean reduction values of 28.1°C for tree shading and 28.8°C for building shading) decreased considerably more than air temperature Ta (mean reduction values of 1.9°C for tree shading and 1.2°C for building shading) owing to shading; furthermore, the reduction effect of shading on UTCI synthesized the variation in the above two parameters. Within the shaded areas, short-wave radiant components (mean standardized values of 0.104 for tree shading and 0.087 for building shading) decreased considerably more than long-wave radiant components (mean standardized values of 0.848 for tree shading and 0.851 for building shading) owing to shading; the proportion of long-wave radiant flux densities absorbed by the reference standing person was high, leading to a relatively high long-wave mean radiant temperature, and R2 between long-wave mean radiant temperature and air temperature exceeded 0.8. Moreover, the directional sky view factor (SVF) was utilized in this study, and it showed significant positive correlation with short-wave radiant flux densities, but no statistically evident correlation with long-wave radiant flux densities. Meanwhile, Tmrt was most relevant with SVFS⟶ with R2 of 0.9756. Furthermore, UTCI rose two categories at the sunlit areas compared with that at the shaded areas. In contrast, Ta and Tmrt played the first positive role in UTCI at shaded and sunlit areas, respectively.

Changes in the surface broadband shortwave radiation budget during the 2017 eclipse

Abstract. While solar eclipses are known to greatly diminish the visible radiation reaching the surface of the Earth, less is known about the magnitude of the impact. We explore both the observed and modeled levels of change in surface radiation during the eclipse of 2017. We deployed a pyranometer and Pandora spectrometer instrument to Casper, Wyoming, and Columbia, Missouri, to measure surface broadband shortwave (SW) flux and atmospheric properties during the 21 August 2017 solar eclipse event. We performed detailed radiative transfer simulations to understand the role of clouds in spectral and broadband solar radiation transfer in the Earth's atmosphere for the normal (non-eclipse) spectrum and red-shift solar spectra for eclipse conditions. The theoretical calculations showed that the non-eclipse-to-eclipse surface flux ratio depends strongly on the obscuration of the solar disk and slightly on the cloud optical depth. These findings allowed us to estimate what the surface broadband SW flux would be for hypothetical non-eclipse conditions from observations during the eclipse and further to quantify the impact of the eclipse on the surface broadband SW radiation budget. We found that the eclipse caused local reductions of time-averaged surface flux of about 379 W m−2 (50 %) and 329 W m−2 (46 %) during the ∼3 h course of the eclipse at the Casper and Columbia sites, respectively. We estimated that the Moon's shadow caused a reduction of approximately 7 %–8 % in global average surface broadband SW radiation. The eclipse has a smaller impact on the absolute value of surface flux reduction for cloudy conditions than a clear atmosphere; the impact decreases with the increase in cloud optical depth. However, the relative time-averaged reduction of local surface SW flux during a solar eclipse is approximately 45 %, and it is not sensitive to cloud optical depth. The reduction of global average SW flux relative to climatology is proportional to the non-eclipse and eclipse flux difference in the penumbra area and depends on cloud optical depth in the Moon's shadow and geolocation due to the change in solar zenith angle. We also discuss the influence of cloud inhomogeneity on the observed SW flux. Our results not only quantify the reduction of the surface solar radiation budget, but also advance the understanding of broadband SW radiative transfer under solar eclipse conditions.

Cloud<i>_</i>cci ATSR-2 and AATSR data set version 3: a 17-year climatology of global cloud and radiation properties

Abstract. We present version 3 (V3) of the Cloud_cci Along-Track Scanning Radiometer (ATSR) and Advanced ATSR (AATSR) data set. The data set was created for the European Space Agency (ESA) Cloud_cci (Climate Change Initiative) programme. The cloud properties were retrieved from the second ATSR (ATSR-2) on board the second European Remote Sensing Satellite (ERS-2) spanning 1995–2003 and the AATSR on board Envisat, which spanned 2002–2012. The data are comprised of a comprehensive set of cloud properties: cloud top height, temperature, pressure, spectral albedo, cloud effective emissivity, effective radius, and optical thickness, alongside derived liquid and ice water path. Each retrieval is provided with its associated uncertainty. The cloud property retrievals are accompanied by high-resolution top- and bottom-of-atmosphere shortwave and longwave fluxes that have been derived from the retrieved cloud properties using a radiative transfer model. The fluxes were generated for all-sky and clear-sky conditions. V3 differs from the previous version 2 (V2) through development of the retrieval algorithm and attention to the consistency between the ATSR-2 and AATSR instruments. The cloud properties show improved accuracy in validation and better consistency between the two instruments, as demonstrated by a comparison of cloud mask and cloud height with co-located CALIPSO data. The cloud masking has improved significantly, particularly in its ability to detect clear pixels. The Kuiper Skill score has increased from 0.49 to 0.66. The cloud top height accuracy is relatively unchanged. The AATSR liquid water path was compared with the Multisensor Advanced Climatology of Liquid Water Path (MAC-LWP) in regions of stratocumulus cloud and shown to have very good agreement and improved consistency between ATSR-2 and AATSR instruments. The correlation with MAC-LWP increased from 0.4 to over 0.8 for these cloud regions. The flux products are compared with NASA Clouds and the Earth's Radiant Energy System (CERES) data, showing good agreement within the uncertainty. The new data set is well suited to a wide range of climate applications, such as comparison with climate models, investigation of trends in cloud properties, understanding aerosol–cloud interactions, and providing contextual information for co-located ATSR-2/AATSR surface temperature and aerosol products. The following new digital identifier has been issued for the Cloud_cci ATSR-2/AATSRv3 data set: https://doi.org/10.5676/DWD/ESA_Cloud_cci/ATSR2-AATSR/V003 (Poulsen et al., 2019).

Evaluation of CERES and CloudSat Surface Radiative Fluxes Over Macquarie Island, the Southern Ocean

AbstractMany studies involving surface radiative fluxes rely on surface fluxes retrieved by the Clouds and the Earth's Radiant Energy System (CERES) project or derived from spaceborne cloud radar and lidar observations (CloudSat‐CALIPSO). In particular, most climate models that participated in the Coupled Model Intercomparison Project Phase 5 (CMIP5) were found to have too little shortwave (SW) radiation being reflected back to space and excessive SW radiation reaching the surface over the Southern Ocean—an error with significant consequences for predicting both regional and global climate. There have been few evaluations of CERES or CloudSat retrievals over the Southern Ocean. In this article, CERES and CloudSat retrieved surface SW and longwave (LW) downwelling fluxes are evaluated using surface observations collected over the Southern Ocean during the Macquarie Island Cloud and Radiation Experiment (MICRE). Overall, biases (CERES—surface observations) in the CERES‐surface fluxes are found to be slightly larger over Macquarie Island than most other regions, approximately +10 W m−2 for the SW and −10 W m−2 for the LW in the annual mean, but with significant seasonal and diurnal variations. If the Macquarie observations are representative of the larger SO, these results imply that CMIP5 model errors in SW surface fluxes are (if anything) somewhat larger than previous evaluation studies suggest. The bias in LW surface flux shows a marked increase at night, which explains most of the total LW bias. The nighttime bias is due to poor representation of cloud base associated with low clouds.

Quantifying the spatial scale mismatch between satellite-derived solar irradiance and in situ measurements: A case study using CERES synoptic surface shortwave flux and the Oklahoma Mesonet

The spatial scale mismatch between gridded irradiance products and in situ measurements is perhaps the least understood topic in solar resource assessment. However, it has a profound impact on virtually all solar applications that involve satellite-derived or reanalysis irradiance data. This paper investigates spatial scale mismatch through a kriging-based upscaling method. Point-location measurements from a monitoring network are upscaled to the size of a satellite-derived irradiance footprint. Subsequently, satellite-derived irradiance is validated against both the nearest point-location measurements and the upscaled areal averages, and the error reduction can, thus, be used to quantify the amount of spatial scale mismatch. In that, a new measure is proposed. The empirical part of the paper considers a synoptic scale satellite-derived irradiance product, namely, National Aeronautics and Space Administration's Clouds and the Earth's Radiant Energy System synoptic surface shortwave flux, and a mesoscale monitoring network, namely, the Oklahoma Mesonet. Based on two years of hourly data and the proposed measure, the spatial scale mismatch is found to be 45% for the U.S. state of Oklahoma.

Dust induced radiative perturbations during an episode of long-range dust transport over Delhi, India: a high-resolution regional NWP model study

Dust-induced modifications to the radiative fluxes/heating during a light-blocking haze episode over Delhi, India, 7–9th Nov 2017—triggered by long range transport from a severe Saudi Arabian dust storm—have been investigated with a regional NWP model, NCUM-R with prognostic dust-radiation feedbacks. The study employs ‘Double Radiation Calls’, wherein parallel runs of the radiation scheme ‘with’ (prognostic) and ‘without’ (diagnostic) dust radiative effects—while prognostic fields drive the forecast—isolate the dust-induced perturbations. The forecasted dust optical depth agreed spatially with the AOD from MODIS with Angstrom Exponent > 0.5, indicating that the dust was well mixed with the fine mode anthropogenic aerosols upwind. The ‘downward shortwave (SW) flux’ was diminished (upto − 12.9 Wm−2) in layers sampling (i) near-surface (L1Avg), (ii) well-mixed layer within the planetary boundary layer (PBL, L2Avg) and (iii) free-troposphere (FT, L3Avg). Dust-induced ‘Solar heating’ dominated in FT (upto 9.5 × 10–7 Ks−1) and the patches below (in L2Avg) exhibited a cooling, leading to thermal dipoles. The ‘upward longwave (LW) flux’ in FT was reduced and ‘LW heating’ prevailed in all levels—peak (2.5 × 10–6 Ks−1) in L2Avg—along with well-defined cooling zones in L1Avg. The dust–radiation interaction in turn influenced the boundary layer meteorology, manifested as (i) shallow PBLs that spatially correlate with dust-induced cooling of the boundary layer column, (ii) enhanced surface humidity and (iii) reduced visibility. The study is an instance of prognostic dust-radiation feedbacks improving the skill of NWP models in dust-laden regions.

The impact of moderately absorbing aerosol on surface sensible, latent, and net radiative fluxes during the summer of 2015 in Central Europe

The impact of moderately absorbing aerosols on the energy budget over Central Europe is discussed, based on experimental observations and numerical simulations obtained for the summer of 2015. Aerosol events, defined as aerosol optical depth (AOD) at 500 nm greater than 0.15, especially in August, are mostly attributed to transport of biomass burning (BB) from Eastern Europe. Shortwave (SW) aerosol radiative forcings (ARF) at the surface and the top of the atmosphere (TOA) are estimated from ensembles of ten and eight observational and model-based approaches, respectively. Different measuring methods, including unmanned aviation system (UAS) and ground-based measurements, radiative transfer models, including MOTRAN and Fu-Liou, and parameterisations of aerosol optical properties regarding full vertical profiles, columnar and surface properties, are used in these approaches. The mean ARF is −15.9 ± 2.1 W/m2, -9.1 ± 1.4 W/m2, and 7.0 ± 1.0 W/m2, respectively, for the Earth's surface, TOA, and atmosphere under clear conditions for June–August 2015. During an aerosol event with AOD peak of about 0.6 at 500 nm, the daily mean surface, TOA, and atmosphere ARF are around −30, −18, and 13 W/m2, respectively. The mean ARF differences between all methods are about 4.0 W/m2 for the surface and about 2.3 W/m2 for the TOA, which correspond to 23% of ensemble means. Aerosols are also shown to have a significant impact on observed surface sensible and latent heat fluxes for the study period. Flux sensitivity to AOD for a solar zenith angle of 45° is −70 ± 41 W/m2/τ500, -112 ± 56 W/m2/τ500, and -119 ± 19 W/m2/τ500, respectively, for sensible, latent, and net SW and longwave (LW) radiation flux. When averaged over day time, sensitivities of sensible heat, latent heat fluxes, and net radiation fluxes to AOD are reduced by about 50%, 20%, and 70%, respectively.

Variability and role of long-wave radiation fluxes in the formation of net radiation and thermal features of grassy and bare soil active surfaces in Wrocław

The paper examines the variability of long-wave radiation fluxes in two contrasting types of urban active surfaces – grassy surface and surface without plants (bare soil) in Wrocław (Poland) within a 12-year period (August 2007–July 2019). The study used net radiation and heat balance formulas to calculate the share of individual radiation fluxes in these balances, and then utilized the Stefan-Boltzmann formula to calculate the effective temperatures of researched surfaces. The analysis showed the temporal variability of these fluxes against the background of weather and climatic conditions and in relation to the variability of short-wave radiation fluxes. The role of long-wave radiation fluxes in forming net radiation was examined in detail to show the buffering role of vegetation surfaces regarding the variability of solar radiation fluxes and their heat effects. The mean monthly values of outgoing long-wave radiation fluxes change from 309.0 W·m−2 for bare soil, 309.8 W·m−2 for grassy surface, and 288.8 W·m−2 for downward atmospheric radiation to respectively 435.8, 425.0 and 369.4 W·m−2 in July. The coefficient of variability for long-wave radiation daily fluxes are approximately one order of magnitude lower than for the short-wave radiation. The differences between values of long-wave radiation fluxes for bare soil and grassy surfaces vary from slight negative values in winter to relatively sizable positive values during the vegetation period (March–October). The weakening of the buffering effect for grassy surface and how air temperature then changes considerably compared to the effective temperature of the active surfaces were explained using the dry summer period of August 2015 as example. The obtained results are important, as they provide empirical arguments for urban planning to extend plant areas' share in big cities as well as to introduce there a friendly environmental system of irrigation in these areas using renewable solar energy.

Using two-stream theory to capture fluctuations of satellite-perceived TOA SW radiances reflected from clouds over ocean

Abstract. Shortwave (SW) fluxes estimated from broadband radiometry rely on empirically gathered and hemispherically resolved fields of outgoing top-of-atmosphere (TOA) radiances. This study aims to provide more accurate and precise fields of TOA SW radiances reflected from clouds over ocean by introducing a novel semiphysical model predicting radiances per narrow sun-observer geometry. This model was statistically trained using CERES-measured radiances paired with MODIS-retrieved cloud parameters as well as reanalysis-based geophysical parameters. By using radiative transfer approximations as a framework to ingest the above parameters, the new approach incorporates cloud-top effective radius and above-cloud water vapor in addition to traditionally used cloud optical depth, cloud fraction, cloud phase, and surface wind speed. A two-stream cloud albedo – serving to statistically incorporate cloud optical thickness and cloud-top effective radius – and Cox–Munk ocean reflectance were used to describe an albedo over each CERES footprint. Effective-radius-dependent asymmetry parameters were obtained empirically and separately for each viewing-illumination geometry. A simple equation of radiative transfer, with this albedo and attenuating above-cloud water vapor as inputs, was used in its log-linear form to allow for statistical optimization. We identified the two-stream functional form that minimized radiance residuals calculated against CERES observations and outperformed the state-of-the-art approach for most observer geometries outside the sun-glint and solar zenith angles between 20 and 70∘, reducing the median SD of radiance residuals per solar geometry by up to 13.2 % for liquid clouds, 1.9 % for ice clouds, and 35.8 % for footprints containing both cloud phases. Geometries affected by sun glint (constituting between 10 % and 1 % of the discretized upward hemisphere for solar zenith angles of 20 and 70∘, respectively), however, often showed weaker performance when handled with the new approach and had increased residuals by as much as 60 % compared to the state-of-the-art approach. Overall, uncertainties were reduced for liquid-phase and mixed-phase footprints by 5.76 % and 10.81 %, respectively, while uncertainties for ice-phase footprints increased by 0.34 %. Tested for a variety of scenes, we further demonstrated the plausibility of scene-wise predicted radiance fields. This new approach may prove useful when employed in angular distribution models and may result in improved flux estimates, in particular dealing with clouds characterized by small or large droplet/crystal sizes.

Uncertainties in CERES Top-of-Atmosphere Fluxes Caused by Changes in Accompanying Imager

The Clouds and the Earth’s Radiant Energy System (CERES) project provides observations of Earth’s radiation budget using measurements from CERES instruments on board the Terra, Aqua, Suomi National Polar-orbiting Partnership (S-NPP), and NOAA-20 satellites. The CERES top-of-atmosphere (TOA) fluxes are produced by converting radiance measurements using empirical angular distribution models, which are functions of cloud properties that are retrieved from imagers flying with the CERES instruments. As the objective is to create a long-term climate data record, not only calibration consistency of the six CERES instruments needs to be maintained for the entire time period, it is also important to maintain the consistency of other input data sets used to produce this climate data record. In this paper, we address aspects that could potentially affect the CERES TOA flux data quality. Discontinuities in imager calibration can affect cloud retrieval which can lead to erroneous flux trends. When imposing an artificial 0.6 per decade decreasing trend to cloud optical depth, which is similar to the trend difference between CERES Edition 2 and Edition 4 cloud retrievals, the decadal SW flux trend changed from − 0.3 5 ± 0.18 Wm − 2 to 0.61 ± 0.18 Wm − 2 . This indicates that a 13% change in cloud optical depth results in about 1% change in the SW flux. Furthermore, different CERES instruments provide valid fluxes at different viewing zenith angle ranges, and including fluxes derived at the most oblique angels unique to S-NPP (>66 ∘ ) can lead to differences of 0.8 Wm − 2 and 0.3 Wm − 2 in global monthly mean instantaneous SW flux and LW flux. To ensure continuity, the viewing zenith angle ranges common to all CERES instruments (<66 ∘ ) are used to produce the long-term Earth’s radiation budget climate data record. The consistency of cloud properties retrieved from different imagers also needs to be maintained to ensure the TOA flux consistency.

Reconstruction of daytime land surface temperatures under cloud-covered conditions using integrated MODIS/Terra land products and MSG geostationary satellite data

There is considerable demand for satellite observations that can support spatiotemporally continuous mapping of land surface temperature (LST) because of its strong relationships with many surface processes. However, the frequent occurrence of cloud cover induces a large blank area in current thermal infrared-based LST products. To effectively fill this blank area, a new method for reconstructing the cloud-covered LSTs of Terra Moderate Resolution Imaging Spectroradiometer (MODIS) daytime observations is described using random forest (RF) regression approach. The high temporal resolution of the Meteosat Second Generation (MSG) LST product assisted in identifying the temporal variations in cloud cover. The cumulative downward shortwave radiation flux (DSSF) was estimated as the solar radiation factor for each MODIS pixel based on the MSG DSSF product to represent the impact from cloud cover on incident solar radiation. The RF approach was used to fit an LST linking model based on the datasets collected from clear-sky pixels that depicted the complicated relationship between LST and the predictor variables, including the surface vegetation index (the normalized difference vegetation index and the enhanced vegetation index), normalized difference water index, solar radiation factor, surface albedo, surface elevation, surface slope, and latitude. The fitted model was then used to reconstruct the LSTs of cloud-covered pixels. The proposed method was applied to the Terra/MODIS daytime LST product for four days in 2015, spanning different seasons in southwestern Europe. A visual inspection indicated that the reconstructed LSTs thoroughly captured the distribution of surface temperature associated with surface vegetation cover, solar radiation, and topography. The reconstructed LSTs showed similar spatial pattern according to the comparison with clear-sky LSTs from temporally adjacent days. In addition, evaluations against Global Land Data Assimilation System (GLDAS) NOAH 0.25° 3-h LST data and reference LST data derived based on in-situ air temperature measurements showed that the reconstructed LSTs presented a stable and reliable performance. The coefficients of determination derived with the GLDAS LST data were all above 0.59 on the four examined days. These results indicate that the proposed method has a strong potential for reconstructing LSTs under cloud-covered conditions and can also accurately depict the spatial patterns of LST.

Ensemble daily simulations for elucidating cloud–aerosol interactions under a large spread of realistic environmental conditions

Abstract. Aerosol effects on cloud properties and the atmospheric energy and radiation budgets are studied through ensemble simulations over two month-long periods during the NARVAL campaigns (Next-generation Aircraft Remote-Sensing for Validation Studies, December 2013 and August 2016). For each day, two simulations are conducted with low and high cloud droplet number concentrations (CDNCs), representing low and high aerosol concentrations, respectively. This large data set, which is based on a large spread of co-varying realistic initial conditions, enables robust identification of the effect of CDNC changes on cloud properties. We show that increases in CDNC drive a reduction in the top-of-atmosphere (TOA) net shortwave flux (more reflection) and a decrease in the lower-tropospheric stability for all cases examined, while the TOA longwave flux and the liquid and ice water path changes are generally positive. However, changes in cloud fraction or precipitation, that could appear significant for a given day, are not as robustly affected, and, at least for the summer month, are not statistically distinguishable from zero. These results highlight the need for using a large sample of initial conditions for cloud–aerosol studies for identifying the significance of the response. In addition, we demonstrate the dependence of the aerosol effects on the season, as it is shown that the TOA net radiative effect is doubled during the winter month as compared to the summer month. By separating the simulations into different dominant cloud regimes, we show that the difference between the different months emerges due to the compensation of the longwave effect induced by an increase in ice content as compared to the shortwave effect of the liquid clouds. The CDNC effect on the longwave flux is stronger in the summer as the clouds are deeper and the atmosphere is more unstable.

Long term variability of carbonaceous aerosols over Southeast Asia via reanalysis: Association with changes in vegetation cover and biomass burning

In this study, we examine the seasonal variability and long–term trends in aerosol distribution over peninsular Southeast Asia (SEA: 90°–105°E, 15°–28°N) based on MERRA–2 reanalysis datasets for a period of 30 years (1985–2015). Special emphasis has been given on the loading and distribution of carbonaceous aerosols, in response to changes in vegetation cover and biomass burning over SEA. MERRA–2 reanalysis reveals a distinct seasonality in columnar AOD distribution, that peaks (0.3–0.45) in the pre-monsoon (March–May) season, with a maximum contribution from carbonaceous aerosols (~60%). The ratio of organic carbon (OC) to black carbon (BC) column mass density indicates a dominant contribution from biomass burning along with biogenic emissions (OC/BC > 10), while the OC (BC) aerosols during pre-monsoon vertically vary between ~6 and 12 μgm−3 (~0.6–1.6 μgm−3) in the lower troposphere (surface to 700 hPa) during pre-monsoon. Interestingly, linear regression in monthly variability of the enhanced vegetation index (EVI) over SEA shows a slightly increasing tendency during the recent decade (2004–2015), while the number of fire counts decreased during the same time period. In addition, a slightly positive trend in OC–AOD is likely associated with the increase in vegetation cover that contributes to the rising trend of biogenic OC emissions, while the reduction in biomass burning is linked with the declining trend of BC–AOD. The pre-monsoon average shortwave flux at the top of the atmosphere (TOA) obtained from MERRA–2 over SEA varies from −12 to −6 Wm−2 and presents a decreasing tendency during the last 30 years due to a decrease in absorbing BC fraction. The temperature anomalies are well related to changes in BC–AOD, and OC–AOD at 850 hPa level, revealing important atmospheric heating.

Retrospective Analysis of Micrometeorological Observations Above an Australian Wheat Crop

We apply well-established flux–gradient relationships to deduce the aerodynamic and radiative properties of a winter wheat crop, using a neglected 1971 dataset (hourly averages), only recently resurrected as part of a historical review of precision CO2 measurements in Australia (Pearman et al. in Hist Rec Aust Sci 28:111–125, 2017). The aerodynamic roughness length (seasonal variation between 0.07 and 0.14 of the mean crop height) and broadband albedo (seasonal variation between 0.13 and 0.23) are consistent with values published in the literature over the past 50 years. Net radiation at night is found to agree with the net longwave flux only when the dry-bulb temperature exceeds 10 °C, probably the result of dewfall on one or both of the two instruments. During the day, the sum of the four individual radiative flux components (upwards and downwards shortwave and longwave)—the composite net radiation—exceeds the directly measured net radiation, from near zero at sunrise to approximately 100 W m−2 at maximum net radiation ≈ 600 W m−2, viz. an underestimate in the directly measured net radiation of close to 15%. Again, this is in line with instrument comparisons made in the USA and Europe 15–25 years ago. A novel approach is used in the analysis of terms in the surface energy budget, viz., normalization of all terms by the downwelling shortwave flux. Normalization reveals, (1) near-normal frequency distributions of both the total turbulent heat flux (sensible plus latent) and the implied total storage (the residual); (2) significant diurnal variations in the total turbulent heat flux, whose standard deviations of individual values about any hourly mean during daytime are reduced significantly on those for either the sensible or latent heat flux; (3) an implied storage term with a well-defined diurnal variation, but with an overall mean value of 1% of the shortwave input. Overall, with the above results in mind, the computed momentum and heat fluxes (and also the CO2 flux) during the daytime, at small to moderate gradient Richardson numbers, provide support for the profile approach when eddy-correlation fluxes are unavailable. Even so, possible errors due to, (1) uncertainties in the zero-plane displacement, and (2) influences of the roughness sublayer, must be borne in mind.

The April 2010 North African heatwave: when the water vapor greenhouse effect drives nighttime temperatures

North Africa experienced a severe heatwave in April 2010 with daily maximum temperatures ( $$T_{max}$$ ) frequently exceeding $$40\,^{\circ }\mathrm{C}$$ and daily minimum temperatures ( $$T_{min}$$ ) over $$27\,^{\circ }\mathrm{C}$$ for more than five consecutive days in extended Saharan and Sahelian areas. Observations show that areas and periods affected by the heatwave correspond to strong positive anomalies of surface incoming longwave fluxes ( $$LW_{in}$$ ) and negative anomalies of incoming shortwave fluxes ( $$SW_{in}$$ ). The latter are explained by clouds in the Sahara, and by both clouds and dust loadings in the Sahel. However, the strong positive anomalies of $$LW_{in}$$ are hardly related to cloud or aerosol radiative effects. An analysis based on climate-model simulations (CNRM-AM) complemented by a specially-designed conceptual soil-atmospheric surface layer model (SARAWI) shows that this positive anomaly of $$LW_{in}$$ is mainly due to a water vapor greenhouse effect. SARAWI, which represents the two processes driving temperatures, namely turbulence and longwave radiative transfer between the soil and the atmospheric surface layer, points to the crucial impact of synoptic low-level advection of water vapor on $$T_{min}$$ . By increasing the atmospheric infrared emissivity, the advected water vapor dramatically increases the nocturnal radiative warming of the soil surface, then in turn reducing the nocturnal cooling of the atmospheric surface layer, which remains warm throughout the night. Over Western Sahel, this advection is related to an early northward incursion of the monsoon flow. Over Sahara, the anomalously high precipitable water is due to a tropical plume event. Both observations and simulations support this major influence of the low-level water vapor radiative effect on $$T_{min}$$ during this spring heatwave.

A Model‐Based Investigation of Terrestrial Plant Carbon Uptake Response to Four Radiation Modification Approaches

AbstractA number of radiation modification approaches have been proposed to counteract anthropogenic warming by intentionally altering Earth's shortwave or longwave fluxes. While several previous studies have examined the climate effect of different radiation modification approaches, only a few have investigated the carbon cycle response. Our study examines the response of plant carbon uptake to four radiation modification approaches that are used to offset the global mean warming caused by a doubling of atmospheric CO2. Using the National Center for Atmospheric Research Community Earth System Model, we performed simulations that represent four idealized radiation modification options: solar constant reduction, sulfate aerosol increase (SAI), marine cloud brightening, and cirrus cloud thinning (CCT). Relative to the high CO2 state, all these approaches reduce gross primary production (GPP) and net primary production (NPP). In high latitudes, decrease in GPP is mainly due to the reduced plant growing season length, and in low latitudes, decrease in GPP is mainly caused by the enhanced nitrogen limitation due to surface cooling. The simulated GPP for sunlit leaves decreases for all approaches. Decrease in sunlit GPP is the largest for SAI which substantially decreases direct sunlight, and the smallest for CCT, which increases direct sunlight that reaches the land surface. GPP for shaded leaves increases in SAI associated with a substantial increase in surface diffuse sunlight, and decreases in all other cases. The combined effects of CO2 increase and radiation modification result in increases in primary production, indicating the dominant role of the CO2 fertilization effect on plant carbon uptake.