An Efficient Method of Estimating Downward Solar Radiation Based on the MODIS Observations for the Use of Land Surface Modeling

Solar radiation is a critical variable in global change sciences. While most of the current global datasets provide only the total downward solar radiation, we aim to develop a method to estimate the downward global land surface solar radiation and its partitioned direct and diffuse components, which provide the necessary key meteorological inputs for most land surface models. We developed a simple satellite-based computing scheme to enable fast and reliable estimation of these variables. The global Moderate Resolution Imaging Spectroradiometer (MODIS) products at 1° spatial resolution for the period 2003–2011 were used as the forcing data. Evaluations at Baseline Surface Radiation Network (BSRN) sites show good agreement between the estimated radiation and ground-based observations. At all the 48 BSRN sites, the RMSE between the observations and estimations are 34.59, 41.98 and 28.06 W∙m−2 for total, direct and diffuse solar radiation, respectively. Our estimations tend to slightly overestimate the total and diffuse but underestimate the direct solar radiation. The errors may be related to the simple model structure and error of the input data. Our estimation is also comparable to the Clouds and Earth’s Radiant Energy System (CERES) data while shows notable improvement over the widely used National Centers for Environmental Prediction and National Center for Atmospheric Research (NCEP/NCAR) Reanalysis data. Using our MODIS-based datasets of total solar radiation and its partitioned components to drive land surface models should improve simulations of global dynamics of water, carbon and climate

Estimation of Incident Photosynthetically Active Radiation From Moderate Resolution Imaging Spectrometer Data

Incident photosynthetically active radiation (PAR) is a key variable needed by almost all terrestrial ecosystem models. Unfortunately, the current incident PAR products estimated from remotely sensed data at spatial and temporal resolutions are not sufficient for carbon cycle modeling and various applications. In this study, the authors develop a new method based on the look-up table approach for estimating instantaneous incident PAR from the polar-orbiting Moderate Resolution Imaging Spectrometer (MODIS) data. Since the top-of-atmosphere (TOA) radiance depends on both surface reflectance and atmospheric properties that largely determine the incident PAR, our first step is to estimate surface reflectance. The approach assumes known aerosol properties for the observations with minimum blue reflectance from a temporal window of each pixel. Their inverted surface reflectance is then interpolated to determine the surface reflectance of other observations. The second step is to calculate PAR by matching the computed TOA reflectance from the look-up table with the TOA values of the satellite observations. Both the direct and diffuse PAR components, as well as the total shortwave radiation, are determined in exactly the same fashion. The calculation of a daily average PAR value from one or two instantaneous PAR values is also explored. Ground measurements from seven FLUXNET sites are used for validating the algorithm. The results indicate that this approach can produce reasonable PAR product at 1 km resolution and is suitable for global applications, although more quantitative validation activities are still needed

An assessment of the quality of aerosol retrievals over the Red Sea and evaluation of the climatological cloud-free dust direct radiative effect in the region

Ground-based and satellite observations are used in conjunction with the Rapid Radiative Transfer Model (RRTM) to assess climatological aerosol loading and the associated cloud-free aerosol direct radiative effect (DRE) over the Red Sea. Aerosol optical depth (AOD) retrievals from the Moderate Resolution Imaging Spectroradiometer and Spinning Enhanced Visible and InfraRed Imager (SEVIRI) instruments are first evaluated via comparison with ship-based observations. Correlations are typically better than 0.9 with very small root-mean-square and bias differences. Calculations of the DRE along the ship cruises using RRTM also show good agreement with colocated estimates from the Geostationary Earth Radiation Budget instrument if the aerosol asymmetry parameter is adjusted to account for the presence of large particles. A monthly climatology of AOD over the Red Sea is then created from 5 years of SEVIRI retrievals. This shows enhanced aerosol loading and a distinct north to south gradient across the basin in the summer relative to the winter months. The climatology is used with RRTM to estimate the DRE at the top and bottom of the atmosphere and the atmospheric absorption due to dust aerosol. These climatological estimates indicate that although longwave effects can reach tens of W m−2, shortwave cooling typically dominates the net radiative effect over the Sea, being particularly pronounced in the summer, reaching 60 W m−2 at the surface. The spatial gradient in summertime AOD is reflected in the radiative effect at the surface and in associated differential heating by aerosol within the atmosphere above the Sea. This asymmetric effect is expected to exert a significant influence on the regional atmospheric and oceanic circulation

mapping photosynthetically active radiation (PAR) using multiple remote sensing data

Incident Photosynthetically Active Radiation (PAR) is an important parameter for terrestrial ecosystem models. Presently, deriving PAR using remotely sensed data is the only practical approach to meet the needs for large scale ecosystem modeling. The usefulness of the currently available PAR products is constricted by their limited spatial and temporal resolution. In addition, the applicability of the existing algorithms for deriving PAR using remotely sensed data are limited by their requirements for external atmospheric information. This study develops new algorithms to estimate incident PAR using remotely sensed data from MODIS (Moderate Resolution Imaging Spectroradiometer), GOES (Geostationary Operational Environmental Satellite), and AVHRR (Advanced Very High Resolution Radiometer). The new PAR algorithms differ from existing algorithms in that the new algorithms derive surface properties and atmospheric optical properties using time-series of at-sensor radiance without external atmospheric information. First, a new PAR algorithm is developed for MODIS visible band data. The validity of the algorithm's underpinning theoretical basis is examined and associated errors are analyzed in light of their impact on PAR estimation accuracy. Second, the MODIS PAR algorithm is adapted to AVHRR in order to take advantage of the long data acquisition record of AVHRR. In addition, the scaling of remote sensing derived instantaneous PAR to daily PAR is addressed. Last, the new algorithm is extended to GOES visible band data. Two major improvements of GOES PAR algorithm over that of MODIS and AVHRR are the inclusion of the bi-directional reflectance distribution function for deriving surface reflectance, and the procedure for excluding cloud-shadowed pixels in searching for observations made under clear skies. Furthermore, the topographic impact on PAR is accessed and corrected. To assess the effectiveness of the newly developed PAR algorithms, validation efforts have been made using ground measurements made at FLUXNET sites. The validations indicate that the new PAR algorithms for MODIS, GOES, and AVHRR are capable of reaching reasonably high accuracy with no need for external atmospheric information. This work is the first attempt to develop a unified PAR estimation algorithm for both polar-orbiting and geostationary satellite data. The new algorithms developed in this study have been used to produce incident PAR over North America routinely to support the North America Carbon Program

The HelioMont method for assessing solar irradiance over complex terrain: Validation and improvements

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Remote sensing of cloud properties and their effects on shortwave radiation

As nuvens são os principais reguladores da quantidade de radiação solar que atinge a superfície terrestre, e esta quantidade de radiação depende das suas propriedades tais como o raio efetivo e a espessura ótica. Por outro lado, as propriedades das nuvens podem sofrer alterações devido a variações nas quantidades de aerossóis levando a alterações dos efeitos radiativos das nuvens. Deste modo, o trabalho desenvolvido nesta tese visa o estudo dos efeitos radiativos das nuvens na radiação solar à superfície, e a determinação das propriedades das nuvens e das interações aerossol-nuvem utilizando diferentes métodos de deteção remota. A variabilidade sazonal dos valores médios diários dos efeitos radiativos das nuvens na radiação solar foi analisada para sete anos (2003 – 2010) de dados medidos em Évora, tendo sido encontrada uma maior variabilidade durante a primavera quando a variabilidade dos períodos de nuvens é também maior. Para o mesmo período (2003 – 2010), a espessura ótica das nuvens de água líquida foi determinada a partir de medições feitas à superfície, e foi relacionada com os efeitos radiativos correspondentes. Posteriormente, estabeleceu-se um método para determinar a espessura ótica e o raio efetivo das nuvens, baseado em reflectâncias medidas pelo SEVIRI no visível e no infravermelho próximo. As propriedades das nuvens obtidas a partir do SEVIRI sobre a região de Évora foram também relacionadas com os efeitos radiativos das nuvens à superfície para o ano 2015, e para um caso de estudo de eventos de efeitos radiativos positivos das nuvens na radiação solar. Finalmente, foi aplicado um método baseado em medições de Lidar para determinar a espessura ótica das nuvens, a qual foi utilizada para estimar a concentração de gotículas de nuvem e o raio efetivo. Estas propriedades das nuvens foram usadas para avaliar as interações aerossol-nuvem de nuvens de água líquida não precipitantes nos Açores; SUMMARY: Clouds are the main controllers of the amount of solar radiation that reaches the Earth’s surface, and this amount of radiation depends on cloud properties such as the cloud effective radius and the cloud optical thickness. On the other hand, cloud properties may change due to changes in aerosol amounts leading to changes in cloud radiative effects. Thus, the work developed in this thesis aims to study the shortwave cloud radiative effects at the surface, and to determine the cloud properties and the aerosol-cloud interactions using different remote sensing methods. The seasonal variability of the daily-mean shortwave cloud radiative effects was analysed for seven years (2003 – 2010) of measured data in Évora, and a greater variability of the radiative effects was found for springtime when the variability of cloud periods is larger. For the same period (2003 – 2010), the cloud optical thickness was retrieved from ground-based measurements and it was related to the corresponding cloud radiative effects. After, a method to retrieve the cloud thickness depth and the effective radius was established using SEVIRI measured reflectances at visible and near infrared wavelengths. The satellite retrievals over Évora region were also related to the shortwave cloud radiative effects for year 2015, and for a case study with events of positive shortwave cloud radiative effects. Finally, a method based on Lidar signals was applied to retrieve the cloud optical thickness, which was used to estimate the cloud droplet number concentration and the effective radius. These cloud properties were used to evaluate the aerosol-cloud interactions of non-precipitating water clouds over Azores

Satellite remote sensing of aerosols using geostationary observations from MSG-SEVIRI

Aerosols play a fundamental role in physical and chemical processes affecting regional and global climate, and have adverse effects on human health. Although much progress has been made over the past decade in understanding aerosol-climate interactions, their impact still remains one of the largest sources of uncertainty in climate change assessment. The wide variety of aerosol sources and the short lifetime of aerosol particles cause highly variable aerosol fields in both space and time. Groundbased measurements can provide continuous data with high accuracy, but often they are valid for a limited area and are not available for remote areas. Satellite remote sensing appears therefore to be the most appropriate tool for monitoring the high variability of aerosol properties over large scales. Passive remote sensing of aerosol properties is based on the ability of aerosols to scatter and absorb solar radiation. Algorithms for aerosol retrieval from satellites are used to derive the aerosol optical depth (AOD), which is the aerosol extinction integrated over the entire atmospheric column. The aim of the work described in this thesis was to develop and validate a new algorithm for the retrieval of aerosol optical properties from geostationary observations with the SEVIRI (Spinning Enhanced Visible and Infra-Red Imager) instrument onboard the MSG (Meteorological Second Generation) satellite. Every 15 minutes, MSG-SEVIRI captures a full scan of an Earth disk covering Europe and the whole African continent with a high spatial resolution. With such features MSG-SEVIRI offers the unique opportunity to explore transport of aerosols, and to study their impact on both air quality and climate. The SEVIRI Aerosol Retrieval Algorithm (SARA) presented in this thesis, estimates the AOD over sea and land surfaces using the three visible channels and one near-infrared channel of the instrument. Because only clear sky radiances can be used to derive aerosol information, a stand-alone cloud detection algorithm was developed to remove cloud contaminated pixels. The cloud mask was generated over Europe for different seasons, and it compared favorably with the results from other cloud detection algorithms - namely the cloud mask algorithm of Meteo-France for MSG-SEVIRI, and the MODIS (Moderate Resolution Imaging Spectroradiometer) algorithm. The aerosol information is extracted from cloud-free scenes using a method that minimizes the error between the measured and the simulated radiance. The signal observed at the satellite level results from the complex combination of the surface and the atmosphere contributions. The surface contribution is either parameterized (over sea), or based on a priori values (over land). The effects of atmospheric gases and aerosols on the radiance are simulated with the radiative transfer model DAK (Doubling-Adding-KNMI) for different atmospheric scenarios. The algorithm was applied for various case studies (i.e. forest fires, dust storm, anthropogenic pollution) over Europe, and the results were validated against groundbased measurements from the AERONET database, and evaluated by comparison with aerosol products derived from other space-borne instruments such as the Terra/- Aqua-MODIS sensors. In general, for retrievals over the ocean, AOD values as well as their diurnal variations are in good agreement with the observations made at AERONET coastal sites, and the spatial variations of the AOD obtained with the SARA algorithm are well correlated with the results derived from MODIS. Over land, the results presented should be considered as preliminary. They show reasonable agreement with AERONET and MODIS, however extra work is required to improve the accuracy of the retrievals based on the proposed metho