Because atmospheric aerosols scatter sunlight back to space, reflectance measurements from spaceborne radiometers can be used to estimate the aerosol load and its optical properties. Several aerosol ...products have been generated in a systematic way, and are available for further studies. In this paper, we evaluate the accuracy of such aerosol products derived from the measurements of POLDER, MODIS, MERIS, SEVIRI and CALIOP, through a statistical comparison with Aerosol Optical Depth (AOD) measurements from the AERONET sunphotometer network. Although this method is commonly used, this study is, to our knowledge, among the most extensive of its type since it compares the performance of the products from 5 different sensors using up to five years of data for each of them at global scale. The choice of these satellite aerosol datasets was based on their availability at the ICARE Data and Service Centre (
www.icare.univ-lille1.fr).
We distinguish between retrievals over land and ocean and between estimates of total and fine mode AOD. Over the oceans, POLDER and MODIS retrievals are of similar quality, with RMS difference lower than 0.1 and a correlation with AERONET of around 0.9. The POLDER estimates suffer from a small positive bias for clean atmospheres, which weakens its statistics. The other aerosol products are of lesser quality, although the SEVIRI products may be of interest for some applications that require a high temporal resolution. The MERIS product shows a very high bias. Over land, only the MODIS product offers a reliable estimate of the total AOD. On the other hand, the polarization-based retrieval using POLDER data allows a better fine mode estimate than that from MODIS. These results suggest the need for a product combining POLDER and MODIS products over land.
The paper also analyses how the statistics change with the spatial and temporal thresholds that are used. Spatio-temporal averaging improves the statistics only slightly, which indicates that random errors are not dominant in the error budget. The paper includes various statistical indicators at global scale, and detailed results at individual ground stations can be obtained on request from the authors.
► POLDER, MODIS, MERIS, SEVIRI and CALIOP aerosol products are evaluated. ► Some satellite aerosol products are better than others. ► The users must use the quality indices, when provided. ► Statistics vary with the spatio-temporal thresholds of the coincidences.
Land surface reflectance is not isotropic. It varies with the observation geometry that is defined by the sun, view zenith angles, and the relative azimuth. In addition, the reflectance is linearly ...polarized. The reflectance anisotropy is quantified by the bidirectional reflectance distribution function (BRDF), while its polarization properties are defined by the bidirectional polarization distribution function (BPDF). The POLDER radiometer that flew onboard the PARASOL microsatellite remains the only space instrument that measured numerous samples of the BRDF and BPDF of Earth targets. Here, we describe a database of representative BRDFs and BPDFs derived from the POLDER measurements. From the huge number of data acquired by the spaceborne instrument over a period of 7 years, we selected a set of targets with high-quality observations. The selection aimed for a large number of observations, free of significant cloud or aerosol contamination, acquired in diverse observation geometries with a focus on the backscatter direction that shows the specific hot spot signature. The targets are sorted according to the 16-class International Geosphere-Biosphere Programme (IGBP) land cover classification system, and the target selection aims at a spatial representativeness within the class. The database thus provides a set of high-quality BRDF and BPDF samples that can be used to assess the typical variability of natural surface reflectances or to evaluate models. It is available freely from the PANGAEA website (doi:10.1594/PANGAEA.864090). In addition to the database, we provide a visualization and analysis tool based on the Interactive Data Language (IDL). It allows an interactive analysis of the measurements and a comparison against various BRDF and BPDF analytical models. The present paper describes the input data, the selection principles, the database format, and the analysis tool
Aerosol concentration and cloud droplet radii derived from space-borne measurements are used to explore the effect of aerosols on cloud microphysics. Cloud droplet size is found to be largest (14 ...micrometers) over remote tropical oceans and smallest (6 micrometers) over highly polluted continental areas. Small droplets are also present in clouds downwind of continents. By using estimates of droplet radii coupled with aerosol load, a statistical mean relationship is derived. The cloud droplet size appears to be better correlated with an aerosol index that is representative of the aerosol column number under some assumptions than with the aerosol optical thickness. This study reveals that the effect of aerosols on cloud microphysics is significant and occurs on a global scale.
The linear kernel-driven RossThick-LiSparseReciprocal (RTLSR) bidirectional reflectance distribution function (BRDF) model was originally developed from the simplified scenarios of continuous and ...discrete vegetation canopies, and has been widely used to fit multiangle observations of vegetation-soil systems of the land surface in many fields. Although this model was not developed explicitly for snow surfaces, it can capture the geometric-optical effect caused by the shadowing of rugged or undulating snow surfaces. However, in this study, this model has been further developed to better characterize the scattering properties of snow surface, which can also exhibit strongly forward-scattering behavior. This study proposes a new snow kernel to characterize the reflectance anisotropy of pure snow based on the asymptotic radiative transfer (ART) model that assumes snow can be modeled as a semi-infinite, plane-parallel, weakly absorbing light scattering layer. This new snow kernel adopts a correction term with a free parameter α to correct the analytic form of the ART model that has been reported to underestimate observed snow reflectance in the forward-scattering direction in the principal plane (PP), particularly in cases of a large viewing zenith angle (>60°). This snow kernel has now been implemented in the kernel-driven RTLSR BRDF model framework in conjunction with two additional kernels (i.e., the volumetric scattering kernel and geometric-optical scattering kernel) and is validated using observed and simulated multiangle data from three data sources. Pure snow targets were selected from the extensive archive of the Polarization and Directionality of the Earth's Reflectance (POLDER) BRDF data. Antarctic snow field measurements, which were taken from the top of a 32-m-tall tower at Dome C Station and include 6336 spectral bidirectional reflectance factors (BRFs), were also utilized. Finally, a set of simulated BRFs, generated by a hybrid scattering snow model that combines the geometric optics with vector radiative transfer theory, were used to further assess the proposed method. We first retrieve the value of the free parameter α for a comprehensive analysis using single multiangle snow data with a sufficient BRDF sampling. Then, we determine the optimally fixed value of the α parameter as prior information for potential users. The new snow kernel method is shown to be quite accurate, presenting a high correlation coefficient (R2 = ~0.9) and a negligible bias between the modeled BRFs and the various snow BRDF validation data. The finding demonstrates that this snow kernel provides an improved potential compared to that of the original kernel-driven model framework for a pure snow surface in many applications, particularly those involving the global water cycle and radiation budget, where snow cover plays an important role.
•The kernel-driven RTLSR model is extended to model snow reflectance anisotropy.•We develop a snow kernel to better characterize the scattering properties of snow.•The kernel derived from the ART model improves the forward scattering of snow.•Validation tests show a high accuracy in the fitting available pure snow BRDF data.
Urban heat island is among the most evident aspects of human impacts on the earth system. Here we assess the diurnal and seasonal variation of surface urban heat island intensity (SUHII) defined as ...the surface temperature difference between urban area and suburban area measured from the MODIS. Differences in SUHII are analyzed across 419 global big cities, and we assess several potential biophysical and socio-economic driving factors. Across the big cities, we show that the average annual daytime SUHII (1.5 ± 1.2 °C) is higher than the annual nighttime SUHII (1.1 ± 0.5 °C) (P < 0.001). But no correlation is found between daytime and nighttime SUHII across big cities (P = 0.84), suggesting different driving mechanisms between day and night. The distribution of nighttime SUHII correlates positively with the difference in albedo and nighttime light between urban area and suburban area, while the distribution of daytime SUHII correlates negatively across cities with the difference of vegetation cover and activity between urban and suburban areas. Our results emphasize the key role of vegetation feedbacks in attenuating SUHII of big cities during the day, in particular during the growing season, further highlighting that increasing urban vegetation cover could be one effective way to mitigate the urban heat island effect.
The CALIOP (Cloud‐Aerosol Lidar with Orthogonal Polarization) layer product is used for a multimodel evaluation of the vertical distribution of aerosols. Annual and seasonal aerosol extinction ...profiles are analyzed over 13 sub‐continental regions representative of industrial, dust, and biomass burning pollution, from CALIOP 2007–2009 observations and from AeroCom (Aerosol Comparisons between Observations and Models) 2000 simulations. An extinction mean height diagnostic (Zα) is defined to quantitatively assess the models' performance. It is calculated over the 0–6 km and 0–10 km altitude ranges by weighting the altitude of each 100 m altitude layer by its aerosol extinction coefficient. The mean extinction profiles derived from CALIOP layer products provide consistent regional and seasonal specificities and a low inter‐annual variability. While the outputs from most models are significantly correlated with the observed Zα climatologies, some do better than others, and 2 of the 12 models perform particularly well in all seasons. Over industrial and maritime regions, most models show higher Zα than observed by CALIOP, whereas over the African and Chinese dust source regions, Zα is underestimated during Northern Hemisphere Spring and Summer. The positive model bias in Zα is mainly due to an overestimate of the extinction above 6 km. Potential CALIOP and model limitations, and methodological factors that might contribute to the differences are discussed.
Key Points
Mean regional tropospheric aerosol extinction profiles are calculated from CALIOP data.
An extinction mean height diagnostic is defined.
The performance of 12 global models in simulating the aerosol profiles is evaluated.
The semi-empirical, kernel-driven, linear RossThick-LiSparseReciprocal (RTLSR) Bidirectional Reflectance Distribution Function (BRDF) model is used to generate the routine MODIS BRDF/Albedo product ...due to its global applicability and the underlying physics. A challenge of this model in regard to surface reflectance anisotropy effects comes from its underestimation of the directional reflectance signatures near the Sun illumination direction; also known as the hotspot effect. In this study, a method has been developed for improving the ability of the RTLSR model to simulate the magnitude and width of the hotspot effect. The method corrects the volumetric scattering component of the RTLSR model using an exponential approximation of a physical hotspot kernel, which recreates the hotspot magnitude and width using two free parameters (C1 and C2, respectively). The approach allows one to reconstruct, with reasonable accuracy, the hotspot effect by adjusting or using the prior values of these two hotspot variables. Our results demonstrate that: (1) significant improvements in capturing hotspot effect can be made to this method by using the inverted hotspot parameters; (2) the reciprocal nature allow this method to be more adaptive for simulating the hotspot height and width with high accuracy, especially in cases where hotspot signatures are available; and (3) while the new approach is consistent with the heritage RTLSR model inversion used to estimate intrinsic narrowband and broadband albedos, it presents some differences for vegetation clumping index (CI) retrievals. With the hotspot-related model parameters determined a priori, this method offers improved performance for various ecological remote sensing applications; including the estimation of canopy structure parameters.
•We have developed a new method to refine the hotspot obtained from the MODIS BRDF retrieval.•The method uses an exponential function to correct the Ross kernel.•The method was evaluated using multi-resolution BRDF data sets.•We examined the sensitivity of the hotspot parameters in characterizing hotspot effect.•We examined this method in retrieving intrinsic albedo and clumping index values.
Multiangle remote sensing plays a central role in the development of algorithms for the retrieval of various surface biophysical parameters that are influenced by the reflectance anisotropy. Surface ...reflectance anisotropy is characterized by the Bidirectional Reflectance Distribution Function (BRDF). Within the past decade, space-borne multiangle observations acquired by the MODerate resolution Imaging Spectroradiometer (MODIS) sensor (which has a gridded spatial resolution of 500 m) and by the POLarization and Directionality of Earth Reflectances (POLDER) sensor (which has a spatial resolution of 6 × 7 km) have been used for a wide variety of global applications. However, it is necessary to fully understand the variability inherent in the surface BRDF information as retrieved from MODIS and POLDER at these two spatial resolutions to optimize their use. In this study, we make use of extensive POLDER Bidirectional Reflectance Factors (BRFs) selected from the entire archive of the POLDER BRDF database and standard MODIS BRDF parameter products (MCD43A1, Collection V005) that were geolocated within the same spatial extents as the POLDER data. The variability in surface BRDF is characterized by investigation of three BRDF model parameters as retrieved from MODIS and POLDER and a comprehensive index indicating the variations in the primary dome-bowl BRDF patterns (the anisotropic flat index (AFX)). The principal information content contained in these BRDF data is characterized by the general BRDF shapes (the BRDF archetypes) that account for >90% of the total variance in these BRDF data. A hotspot-revised BRDF model is used directly on top of the retrieved model BRDF parameters to capture the hotspot effect associated with these BRDF parameters. The main findings of this study show that the variability in surface BRDF, as extracted from the MODIS and POLDER datasets, shares six reciprocal BRDF archetypes. However, the 500-m MODIS BRDF data can uniquely capture some additional extreme BRDF shapes mainly due to the data's finer pixel scales. These original findings are very important, because subsequent albedo retrievals can be significantly impacted by the use of BRDFs of different resolutions. This study provides evidence concerning the influence of spatial resolution on angular variation patterns of optical reflectance as retrieved from the MODIS and POLDER BRDF products.
•Variability in surface BRDF retrieved from MODIS and POLDER data is investigated.•The MODIS data captures more variations in surface BRDF than the POLDER data.•Subsequent albedo retrievals can be impacted by using BRDFs of different resolutions.•Results offer insights into the variability of multi-resolution BRDF data.
Surface reflectance time series measured from space borne instruments, such as the MODIS sensor, show an apparent high-frequency noise that limits their information content. A major contributor to ...this noise is the directional effect as the target reflectance varies with the observation geometry. The operational MODIS processing inverts the parameters of a BRDF model which are provided in the so-called MCD43C2 product with a frequency of (8days)−1. Recently, Vermote et al. (2009) suggested an alternative BRDF inversion method. A major assumption is that the BRDF model shape (i.e. the BRDF normalized by its overall amplitude) varies little throughout the year so that the two model parameters are linear functions of the NDVI. Consequently, a given target BRDF shape is described by four parameters (slope and intercept for the two NDVI-dependent parameters) rather than 2 parameters that change for each 8days period. This method imposes additional constrain for the surface BRDF inversion.
In this paper, we evaluate the performance of these two approaches for the correction of surface reflectance time series. We work at the 0.05° (≈5km) resolution of the CMG grid and analyze a representative set of +100 targets selected on the basis of the location of AERONET sites. The performance is quantified by the high-frequency noise in the corrected time series. We demonstrate that the performances of the two approaches are very similar. This result demonstrates that a simple four-parameter NDVI-scaled model performs as well as a more complex model with many more degrees of freedom. Besides, the four-parameter model, which is inverted on a given year, can be applied to the measurements of other years with a similar level of performance. Finally, a single “averaged” model can be applied to any target with a performance that is only slightly reduced compared to what is achieved with a model derived through a full inversion of the multi-temporal data.
The proposed four-parameter BRDF model permits the reduction of noise in the reflectance time series by a factor of the order of three in the red and four in the near infrared. After correction, the reflectance time series are very clean, with an apparent noise that is ≈0.005 in the red band and 0.01 in the near infrared. The quality of the BRDF correction makes it possible to use the individual reflectance time-series at high temporal resolution, rather than indices based on their ratio, and thus retain more information about the vegetation dynamics.
► Quantitative evaluation of BRDF modelling for reflectance time series correction. ► Uses a representative set of Earth targets ► Compares operational MODIS product and other approaches ► Describes a method for a very easy BRDF correction of reflectance measurements
•ERA5 reanalysis and multi-ensemble EURO-CORDEX models are used for simulating onshore and offshore wind power output.•All wind speed models show significant bias that imposes a method for ...bias-correction.•Wind turbine improvements are evaluated.•Wind power intermittency and spatial-decorrelation effects are analyzed and quantified.•Climate change has little impact on the wind power output and even the sign of the change varies among climate models.
Wind power is developing rapidly because of its potential to provide renewable electricity and the large reduction in installation costs during the past decade. However, the high temporal variability of the wind power source is an obstacle to a high penetration in the electricity mix as it makes difficult to balance electricity supply and demand. There is therefore a need to quantify the variability of wind power and also to analyze how this variability decreases through spatial aggregation. In the context of climate change, it is also necessary to analyze how the wind power potential and its variability may change in the future. One difficulty for such objective is the large biases in the modeled winds, and the difficulty to derive a reliable power curve. In this paper, we propose an Empirical Parametric Power Curve Function (EPPCF) model to calibrate a power curve function for a realistic estimate of wind power from weather and climate model data at the regional or national scale. We use this model to analyze the wind power potential, with France as an example, considering the future wind turbine evolution, both onshore and offshore, with a focus on the production intermittency and the impact of spatial de-correlations. We also analyze the impact of climate change.
We show that the biases in the modeled wind vary from region to region, and must be corrected for a valid evaluation of the wind power potential. For onshore wind, we quantify the potential increase of the load factor linked to the wind turbine evolution (from a current 23% to 30% under optimistic hypothesis). For offshore, our estimate of the load factor is smaller for the French coast than is currently observed for installed wind farms that are further north (around 35% versus 39%). However, the estimates vary significantly with the atmospheric model used, with a large spatial gradient with the distance from the coast. The improvement potential appears smaller than over land. The temporal variability of wind power is large, with variations of 100% of the average within 3–10 h at the regional scale and 14 h at the national scale. A better spatial distribution of the wind farms could further reduce the temporal variability by around 20% at the national scale, although it would remain high with respect to that of the demand. The impact of climate change on the wind power resource is insignificant (from +2.7% to −8.4% for national annual mean load factor) and even its direction varies among models.
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