Surface Incoming Solar Radiation Research Articles

The impact of aerosols on stratiform clouds over southern West Africa: a large-eddy-simulation study

Abstract. Low-level stratiform clouds (LLSCs) covering a large area appear frequently during the wet monsoon season in southern West Africa. This region is also a place where different types of aerosols coexist, including biomass burning aerosols coming from central and southern Africa and aerosols emitted by local anthropogenic activities. We investigate the indirect and semi-direct effects of these aerosols on the life cycle of LLSCs by conducting a case study based on airborne and ground-based observations from the field campaign of Dynamic-Aerosol-Chemistry-Cloud-Interaction in West Africa (DACCIWA). This case is modeled using a large-eddy-simulation (LES) model with fine resolution and in situ aerosol measurements, including size distribution and chemical composition. The model has successfully reproduced the observed life cycle of the LLSC, from stratus formation to stabilization during the night and to upward development after sunrise until break-up of the cloud deck in the late afternoon. Additional sensitivity simulations using different measured aerosol profiles also suggest that aerosols can affect the cloud life cycle through both the indirect and semi-direct effects. As expected, modeled cloud microphysical features, including cloud droplet number concentration, mean radius, and thus cloud reflectivity, are all controlled by aerosol concentration. However, it is found that the variation in cloud reflectivity induced by different aerosol profiles is not always the only factor in determining the incoming solar radiation at the ground and thus for the cloud life cycle after sunrise. Instead, the difference in cloud fraction brought by dry-air entrainment from above and thus the speed of consequent evaporation – also influenced by aerosol concentration – is another important factor to consider. Clouds influenced by higher aerosol concentrations and thus with a higher number concentration and smaller sizes of cloud droplets are found to evaporate more easily and thus impose a lower cloud fraction. In addition, our sensitivity runs including versus excluding aerosol direct radiative effects have also demonstrated the impacts specifically of solar absorption by black carbon on the cloud life cycle. The semi-direct effect resulting from an excessive atmospheric heating of up to 12 K d−1 by black carbon in our modeled cases is found to lower the cloud top as well as the liquid water path, reducing surface incoming solar radiation and dry entrainment and increasing the cloud fraction.

Regional assessment of daily reference evapotranspiration: Can ground observations be replaced by blending ERA5-Land meteorological reanalysis and CM-SAF satellite-based radiation data?

This study evaluates the accuracy of daily reference evapotranspiration (ETo), computed according to the FAO Penman-Monteith equation by using a set of input weather variables obtained by blending ERA5-Land (ERA5L) reanalysis data with surface incoming solar radiation (Rs) provided by the instruments on board the Meteosat geostationary satellites, operationally delivered by the Satellite Applications Facility on Climate Monitoring (CM-SAF). Performance assessment was carried out in Sicily (southern Italy) by using data from 38 automatic ground weather stations (AWSs) for years 2003–2020. ERA5L and CM-SAF data were first downscaled and bias-corrected with a calibration dataset; ERA5L air temperature data were also downscaled by lapse-rate correction. ETo estimates obtained with the blended ERA5L and CM-SAF validation dataset (ERA5L+CM-SAF) were compared with two other ETo estimates respectively obtained by using ERA5L and interpolated ground weather data (IGD). Performance indicators of the IGD dataset were evaluated by recursively applying universal kriging or ordinary kriging to the observed weather data, according to a cross-validation procedure. Rs provided by CM-SAF outperformed Rs obtained by ground interpolation, thus confirming the convenience of using bias-corrected CM-SAF data even when ground observations are available in the study area. ETo estimates with ERA5L+CM-SAF showed a normalized RMSE of 12%, outperforming ERA5L ETo estimates while performing comparably to ETo estimates obtained with the IGD dataset. The results suggested that the proposed blended dataset is a good proxy for interpolated ground weather observations in the assessment of ETo at regional scale when weather measurements cannot be easily gathered or in data-sparse regions.

The importance of inter‐basin atmospheric teleconnection in the SST footprint of Atlantic multidecadal oscillation over western Pacific

Western Pacific sea surface temperature (SST) multidecadal fluctuations are synchronized to the Atlantic multidecadal oscillation (AMO) phenomenon during the instrumental period. The possible mechanism of the inter-basin synchronization of multidecadal SST variability still remains a matter of discussion regarding the roles of external radiative forcing and internal inter-basin interaction. Here we address this issue using simulations of CMIP5 coupled models and a partially coupled model experiment with prescribed SSTs over the North Atlantic. Observational analysis suggests that in association with the warm AMO phase, prominent SST warming occurs over the western Pacific, accompanied by anomalous low pressures and ascending motion that maintain the warm SST anomalies through positive feedback of local air–sea interaction. The upward motion in the western Pacific corresponds to a significant intensification of Pacific zonal Walker circulation, which is coupled with an increase in the zonal gradient of atmospheric temperature aloft. The CMIP5 model simulated externally forced component of AMO-related changes in western Pacific SST is weak, associated with little change in Pacific zonal circulation showing an absence of anomalous upward motion over the western Pacific, and this is primarily resultant from the negligible changes in the zonal gradient of atmospheric temperature as a direct thermal response to the external radiative forcing. By contrast, the partially coupled model simulation forced by the Atlantic SST variations reasonably reproduces the observed AMO-related changes in western Pacific SST and pan-tropical atmospheric circulation. A surface radiation budget analysis for the western Pacific shows contrasting roles of AMO-related surface incoming solar radiation between the reanalysis/partially coupled model simulation and the forced signal in CMIP5, further confirming the key role of dynamically induced inter-basin atmospheric teleconnection in the multidecadal SST footprint of AMO over the western Pacific.

Comparison of Three Different Satellite-Based Approaches for Aboveground Biomass Estimation

Effective estimation of crop yield on a regional scale in a short time with low cost would only be possible utilizing remote sensing. Several approaches have been proposed based on remotely sensed data for estimating Aboveground Biomass (AGB). In this study, three satellite-based approaches, including Radiation Use Efficiency (RUE). The soil water atmosphere plant (SWAP) model, and FAO33, were evaluated in the irrigated wheat and barley fields in the Qazvin irrigation network, Iran. To this end, the leaf area index (LAI) and relative evapotranspiration (ETrel) were extracted from the Landsat data and incorporated into the methods. A comparative analysis was undertaken to evaluate the performance of the satellite-based approaches using percent absolute error (PAE). By updating SWAP with satellite-derived LAI and surface incoming solar radiation, the PAE decreased significantly. Results of different Spectral Indices (SIs) in the RUE method showed that NDVI performed best with PAE of 1.52 percent and RMSE of 664.6 kg ha−1. Also, the RUE method with RMSE of 664.6 kg ha−1 had 4.7 and 23.8 lower PAE compared to the SWAP (RMSE = 2221.4 kg ha−1) and FAO33 (RMSE = 4394.2 kg ha−1), respectively. However, this was not the only criteria for a well-performed method, because earlier AGB forecast was only feasible by making use of SWAP since the satellite-derived parameters were only incorporated into the model about one month before the harvest.

On the spatiotemporal variability and potential of complementarity of wind and solar resources

The anticipated greater penetration of the variable renewable energies wind and solar in the future energy mix could be facilitated by exploiting their complementarity, thereby improving the balance between energy supply and demand. Based on the hypothesis that a complementary use of wind and solar is possible, this investigation provides information about the spatiotemporal scales on which there is potential for the synergistic use of wind and solar in Germany. The results show that the wind-solar complementarity depends very much on the time scale under consideration. Regardless of the spatial scale, potential for complementarity is greatest on the seasonal scale, where the annual cycles of surface incoming solar radiation and surface wind speed show the strongest anti-correlation. On all other scales studied, including daily and inter-annual scales, the potential for wind-solar complementarity is significantly lower with wind and solar being usually very weakly anti-correlated or being uncorrelated. On these scales, there is hardly any compensation of times with low solar resource by the wind resource and vice versa. There is also hardly any solar-solar or wind-wind complementarity in different regions because their regional inter-regime dynamics are similar and do not show any significant differences. From the results, it is therefore concluded that there is little potential for the complementary use of wind and solar in Germany, except on the seasonal scale. Germany’s low complementarity potential reinforces the need to systematically advance other options for mitigating the individual volatilities of wind and solar such as energy storage systems and transboundary exchange of renewable power in a pan-European electricity grid. Although the results are limited to a single country, the proposed novel data-driven approach can be readily transferred to study wind-solar complementarity in other parts of the world. It enables for the first time the consistent small-scale assessment of wind-solar complementarity in large, transnational areas and has the potential for being established as an essential tool to improve electrical grid operability.

Performance of Different Surface Incoming Solar Radiation Models and Their Impacts on Reference Evapotranspiration

Reference evapotranspiration (ET0) from FAO-Penman-Monteith equation is highly sensitive to the surface incoming solar radiation (SISR) and therefore accurate estimate of this parameter would result in more accurate estimation of ET0. In this study, the accuracy of three main approaches for SISR estimation including empirical models (Angstrom and Hargreaves-Samani), physically-based data assimilation models (Global Land Data Assimilation System-Noah, GLDAS/Noah, and National Centers of Environmental Predictions/National Center for Atmospheric Research, NCEP/NCAR), and a satellite observation model (Satellite Application Facility on Climate Monitoring, CM-SAF) were evaluated using ground-based measurements from 2012 to 2015. Then SISR outputs from introduced approaches were implemented in FAO-Penman-Monteith equation for ET0 estimation on daily and monthly basis. The Angstrom calibrated model was the most accurate model with a coefficient of determination (R2) of 0.9 and standard error of estimate (SEE) of 2.58 MJ. m−2. d−1, and GLDAS/Noah, Hargreaves-Samani, NCEP/NCAR, and CM-SAF, had lower accuracy, respectively. However, the lack of the meteorological data and required empirical coefficients are the main limitations of applying the empirical models, however, satellite-based approaches are more practical for operational purposes. The results indicated that, in spite of slight overestimation in warm months, GLDAS/Noah model had better performance with R2=0.87 and SEE = 3.5 MJ. m−2. d−1 in case of lack of meteorological data. The accuracy of ET0 derived from FAO-Penman-Monteith equation was directly depended on the accuracy of SISR estimation. The ET0 estimation error was related to SISR estimation error with a fourth-degree function and had a linear relationship with SISR error at daily and monthly scales, respectively.

Improving crop yield estimation by assimilating LAI and inputting satellite-based surface incoming solar radiation into SWAP model

Precise crop yield forecast at regional scales would increase global food security, especially in strategic crops such as wheat and barley. Soil Water Atmosphere Plant (SWAP) is an agro-hydrological model based on a crop growth detailed module that could properly estimate crop yield using satellite observations as input data. In this study, in order to reduce crop yield estimation errors in wheat and barley, MODIS-based leaf area index (LAI) was assimilated using a sequential update algorithm into SWAP, and GLDAS/Noah-derived surface incoming solar radiation (SISR) was used as an alternative to measured SISR. The assimilation of remotely sensed LAI and using SISR as input was examined in nine different cases. Results showed that soil adjusted vegetation index (SAVI) was the best VI for LAI estimation with coefficient of determination (R2) of 0.72 and root mean square error (RMSE) of 0.87 m2 m−2. Also noise equivalent variations indicated an appropriate sensitivity of SAVI along the entire range of LAI variability. GLDAS/Noah-derived SISR showed good agreement with measured SISR; therefore LAI and SISR were jointly used in the model. Simulation results showed that the lowest percent absolute error (PAE) for aboveground dry biomass and grain yield was obtained in case 7 (the assimilation of the peak LAI in addition to ten days after and before the peak LAI is reached) with 1.59% and case 5 (the daily assimilation of LAI until twenty days after the peak LAI is reached) with 6.06%, respectively. Crop yield estimates were improved by 26.25 and 14.4% compared with no LAI assimilation case. Overall, LAI assimilation into SWAP associated with the most efficient cases in this study would result in an accurate crop yield forecast in wheat and barley.

The reliance of insolation pattern on surface aspect

The Sun's radiated energy is an important source in realizing the green technology concept construction. When interacting with the atmosphere and objects on the Earth's surface incoming solar radiation (insolation) will create insolation patterns that are ambiguous and as a result need to be investigated further. This paper explores the insolation pattern and ambiguities against topographic surfaces in the context of direct, diffuse, and reflectance irradiance. The topography is modeled from LiDAR data as Digital Surface Model (DSM) and Digital Terrain Model (DTM). The generated DSM and DTM were converted to Triangular Irregular Network (TIN) format within the Arc GIS environment before the insolation pattern could be visualized. The slope and aspect of the topography has an impact on the insolation which is the emphasis of this paper. The main outcome from the study is the insolation map and plots of relationship between the insolation and surface aspect. The findings from this study should contribute to the sustainable practices of green building technology.

Spatiotemporal variation of surface shortwave forcing from fire-induced albedo change in interior Alaska

The albedo change caused by fires and the subsequent succession is spatially heterogeneous, leading to the need to assess the spatiotemporal variation of surface shortwave forcing (SSF) as a component to quantify the climate impacts of high-latitude fires. We used an image reconstruction approach to compare postfire albedo with the albedo assuming that no fires had occurred. Combining the fire-caused albedo change from the 2001–2010 fires in interior Alaska and the monthly surface incoming solar radiation, we examined the spatiotemporal variation of SSF in the early successional stage of approximately 10 years. Our results showed that although postfire albedo generally increased in fall, winter, and spring, some burned areas could show an albedo decrease during these seasons. In summer, the albedo increased for several years and then declined again. The spring SSF distribution did not show a latitudinal decrease from south to north as previously reported. The results also indicated that although the SSF is usually largely negative in the early successional years, it may not be significant during the first postfire year. The annual 2005–2010 SSF for the 2004 fire scars was –1.30, –4.40, –3.31, –4.00, –3.42, and –2.47 W·m−2, respectively. The integrated annual SSF map showed significant spatial variation, with a mean of –3.15 W·m−2, a standard deviation of 3.26 watts per square metre (W·m−2), and 16% of burned areas having positive SSF. Our results suggest that boreal deciduous fires would be less positive for climate change than boreal evergreen fires. Future research is needed to comprehensively investigate the spatiotemporal radiative and nonradiative forcings to determine the effect of boreal fires on the climate.

Solar resource assessment in the Benelux by merging Meteosat-derived climate data and ground measurements

To characterize the solar radiation in the Benelux countries, a dataset of daily global horizontal solar radiation resulting from both on-site observations time series and long-term satellite-derived data has been generated and analysed at the Royal Meteorological Institute of Belgium (RMI). The developed procedures take advantage of a recently released 23years long (1983–2005) surface incoming solar radiation (SIS) climate data records derived from the first generation of Meteosat satellites imageries and the radiometric measurements networks operated by the Koninklijk Nederlands Meteorologisch Instituut (KNMI) and RMI, respectively. In addition to the computation of various statistics to quantify the amount and the variability of the solar resources in the Benelux, solar radiation climate zones within the Benelux were defined and the recent trend in solar radiation was characterized.

Comparison of Gene Expression Programming with neuro-fuzzy and neural network computing techniques in estimating daily incoming solar radiation in the Basque Country (Northern Spain)

Surface incoming solar radiation is a key variable for many agricultural, meteorological and solar energy conversion related applications. In absence of the required meteorological sensors for the detection of global solar radiation it is necessary to estimate this variable. Temperature based modeling procedures are reported in this study for estimating daily incoming solar radiation by using Gene Expression Programming (GEP) for the first time, and other artificial intelligence models such as Artificial Neural Networks (ANNs), and Adaptive Neuro-Fuzzy Inference System (ANFIS). A comparison was also made among these techniques and traditional temperature based global solar radiation estimation equations. Root mean square error (RMSE), mean absolute error (MAE) RMSE-based skill score (SSRMSE), MAE-based skill score (SSMAE) and r2 criterion of Nash and Sutcliffe criteria were used to assess the models’ performances. An ANN (a four-input multilayer perceptron with 10 neurons in the hidden layer) presented the best performance among the studied models (2.93MJm−2d−1 of RMSE). The ability of GEP approach to model global solar radiation based on daily atmospheric variables was found to be satisfactory.

Evaluation of the Surface Radiation Budget in the Atmospheric Component of the Hadley Centre Global Environmental Model (HadGEM1)

Abstract The partitioning of the earth radiation budget (ERB) between its atmosphere and surface components is of crucial interest in climate studies as it has a significant role in the oceanic and atmospheric general circulation. An analysis of the present-day climate simulation of the surface radiation budget in the atmospheric component of the new Hadley Centre Global Environmental Model version 1 (HadGEM1) is presented, and the simulations are assessed by comparing the results with fluxes derived from satellite data from the International Satellite Cloud Climatology Project (ISCCP) and ground measurements from the Baseline Surface Radiation Network (BSRN). Comparisons against radiative fluxes from satellite and ground observations show that the model tends to overestimate the surface incoming solar radiation (Ss,d). The model simulates Ss,d very well over the polar regions. Consistency in the comparisons against BSRN and ISCCP-FD suggests that the ISCCP-FD database is a good test for the performance of the surface downwelling solar radiation in climate model simulations. Overall, the simulation of downward longwave radiation is closer to observations than its shortwave counterpart. The model underestimates the downward longwave radiation with respect to BSRN measurements by 6.0 W m−2. Comparisons of land surface albedo from the model and estimates from the Moderate Resolution Imaging Spectroradiometer (MODIS) show that HadGEM1 overestimates the land surface albedo over deserts and over midlatitude landmasses in the Northern Hemisphere in January. Analysis of the seasonal cycle of the land surface albedo in different regions shows that the amplitude and phase of the seasonal cycle are not well represented in the model, although a more extensive validation needs to be carried out. Two decades of coupled model simulations of the twentieth-century climate are used to look into the model’s simulation of global dimming/brightening. The model results are in line with the conclusions of the studies that suggest that global dimming is far from being a uniform phenomenon across the globe.

Comparison of empirical daily surface incoming solar radiation models

Most environmental and agronomic models use climatic inputs such as temperature, solar radiation and rainfall. In Canada, few automatic weather stations can monitor incoming solar radiation. Hence, surface incoming solar radiation must be estimated from other meteorological data. The aim of the present research was to conduct a comparative study of three empirical models for the estimation of surface incoming solar radiation on a horizontal surface. The first two methodologies use the traditional and long-utilized linear approach based on latitude and daily temperature range. A more recent methodology uses neural networks (NN) to build a similar regression based on latitude and temperature range, but providing more flexibility in the formulation as well as a non-linear activation function. Global daily solar radiation data from 11 stations located in northeastern America was used to optimize and test the different models. Even though coefficients of the classical models were locally optimized using a standard unconstrained non-linear scheme, NNs markedly improved the estimation of incoming surface solar radiation.

Influences of urbanization on surface characteristics as derived from the Moderate‐Resolution Imaging Spectroradiometer: A case study for the Beijing metropolitan area

Moderate‐Resolution Imaging Spectroradiometer (MODIS) global land surface temperature/emissivity (LST), vegetation indices, BRDF/Albedo and land cover products collected for the period of March 2000 to March 2006 are combined with the surface heat fluxes retrieved from MODIS as well as meteorological data to investigate the influence of urbanization associated with the surface characteristics of the city of Beijing. The results show that the use of different rural areas in the urban heat island (UHI) calculation influences the value of UHI and its seasonal variation. Daytime UHI shows a distinct seasonal variation, the maximum during summer being larger than 10°C, while conspicuous negative UHI occurs in winter and spring. Seasonal variation of nighttime UHI is much less. The contrast in thermal inertia between rural and urban areas, anthropogenic heat from the urban area and less latent heat flux over urban areas are the main factors influencing daytime UHI, whereas anthropogenic heat controls the nighttime UHI. Surface broadband emissivity derived from MODIS LST/emissivity for the urban area is nearly equal to the rural areas. Surface albedo over the urban area is 0.03–0.08 less than that of rural areas, but aerosols substantially reduce surface incoming solar radiation over the urban area, which results in the surface absorbed solar radiation being nearly equal for urban and rural areas during autumn. Diurnal variation of UHI demonstrates a distinctively seasonal variation. The accuracy of MODIS LST is investigated and it was found that the influence of satellite view angle on the calculated UHI is small enough to be ignored.