A framework was established for remote sensing of sea ice albedo that integrates sea ice physics with high computational efficiency and that can be ap…A framework was established for remote sensing of sea ice albedo that integrates sea ice physics with high computational efficiency and that can be applied to optical sensors that measure appropriate radiance data. A scientific machine learning (SciML) approach was developed and trained on a large synthetic dataset (SD) constructed using a coupled atmosphere-surface radiative transfer model (RTM). The resulting RTM-SciML framework combines the RTM with a multi-layer artificial neural network SciML model. In contrast to the Moderate Resolution Imaging Spectroradiometer (MODIS) MCD43 albedo product, this framework does not depend on observations from multiple days and can be applied to single angular observations obtained under clear-sky conditions. Compared to the existing melt pond detection (MPD)-based approach for albedo retrieval, the RTM-SciML framework has the advantage of being applicable to a wide variety of cryosphere surfaces, both heterogeneous and homogeneous. Excellent agreement was found between the RTM-SciML albedo retrieval results and measurements collected from airplane campaigns. Assessment against pyranometer data (N=4144) yields RMSE = 0.094 for the shortwave albedo retrieval, while evaluation against albedometer data (N=1225) yields RMSE = 0.069, 0.143, and 0.085 for the broadband albedo in the visible, near-infrared, and shortwave spectral ranges, respectively.more
An estimate of solar irradiation potential over large regions requires the knowledge of the long-term spatio-temporal distribution of the solar radiat…An estimate of solar irradiation potential over large regions requires the knowledge of the long-term spatio-temporal distribution of the solar radiation as well as the identification of the suitable surfaces where the photovoltaic (PV) installations can be built. These main components can be modelled in different ways and are thus affected by different sources of uncertainty. Thus, when estimating the exploitable potential over large regions, it is important to measure the accuracy of the entire process. In this work, we provide a generic method to estimate the solar irradiation potential of rooftops over large regions and an estimate of the corresponding uncertainties when calculating the long-term electricity generation of PV plants. This method uses satellite based solar radiation data covering a period of 22 years, with a temporal resolution of 30 min and a spatial resolution of 3.8–5.6 km. Suitable surfaces on rooftops are identified using Digital Surface Models combined with building footprints. This allows to determine the geometry of rooftops, such as slope, and orientation with a spatial resolution of 0.5 m. Finally, we calculated the electricity generation based on models which take into account all characteristics of PV system components. In order to estimate the accuracy of the model for electricity production, we compared the monthly generation of 500 PV plants in Switzerland consisting of different PV technologies (mono-crystalline, poly-crystalline and thin film) with the estimates. The validation results show a correlation coefficient (R2) of 0.9 and a median monthly relative error between 0.28% (August) and 28.08% (December). The monthly estimates are more accurate during summer time, while spatially and technology-wise no significant differences are found.more
The Ocean and Sea-Ice Satellite Application Facility (OSI-SAF) of the EUropean Organisation for the Exploitation of METeorological Satellites (EUMETSA…The Ocean and Sea-Ice Satellite Application Facility (OSI-SAF) of the EUropean Organisation for the Exploitation of METeorological Satellites (EUMETSAT) has performed a reprocessing of Sea Surface Temperature (SST) from the Spinning Enhanced Visible and Infrared Imager (SEVIRI) onboard Meteosat Second Generation (MSG) archive (2004–2012).
The retrieval method consists of a non-linear split-window algorithm and an algorithm correction relying on simulations of infrared brightness temperatures performed using atmospheric profiles of water vapour and temperature from a Numerical Weather Prediction model, and a radiative transfer model. The cloud mask used is the Climate SAF reprocessing of the MSG/SEVIRI archive which is consistent over the period considered. Atmospheric Saharan dust has a strong impact on the retrieved SST in the Atlantic and Mediterranean regions, they are taken into consideration through the computation of the Saharan Dust Index (SDI) which is then used to determine an empirical correction applied to SST.
The reprocessing has benefited from the experience of the OSI SAF team in operational near real time processing of MSG/SEVIRI data, and the methods have been improved to provide a higher quality SST. The MSG/SEVIRI SST reprocessing dataset consists of hourly level 3 composites of sub-skin temperature projected onto a regular 0.05° grid over the region delimited by 60N,60S and 60W,60E. It has been thoroughly validated against drifting buoys and moored buoys measurements.
Results of this validation have shown that the reprocessed data record is of significantly better quality than the OSI SAF operational processing (for instance the day-time robust standard deviation is 0.45 K for the operational processing and 0.35 K for the reprocessed dataset). The data record has been used to characterize the diurnal variability of SST over large temporal and spatial scales.more
This study uses aerosol optical depth (AOD) and cloud properties data to investigate the influence of aerosol on the cloud properties over the Tibetan…This study uses aerosol optical depth (AOD) and cloud properties data to investigate the influence of aerosol on the cloud properties over the Tibetan Plateau and its adjacent regions. The study regions are divided as the western part of the Tibetan Plateau (WTP), the Indo-Gangetic Plain (IGP), and the Sichuan Basin (SCB). All three regions show significant cloud effects under low aerosol loading conditions. In WTP, under low aerosol loading conditions, the effective radius of liquid cloud particles (LREF) decreases with the increase of aerosol loading, while the effective radius of ice cloud particles (IREF) and cloud top height (CTH) increase during the cold season. Increased aerosol loading might inhibit the development of warm rain processes, transporting more cloud droplets above the freezing level and promoting ice cloud development. During the warm season, under low aerosol loading conditions, both the cloud microphysical (LREF and IREF) and macrophysical (cloud top height and cloud fraction) properties increase with the increase of aerosol loading, likely due to higher dust aerosol concentration in this region. In IGP, both LREF and IREF increase with the increase in aerosol loading during the cold season. In SCB, LREF increases with the increase in aerosol loading, while IREF decreases, possibly due to the higher hygroscopic aerosol concentration in the SCB during the cold season. Meteorological conditions also modulate the aerosol-cloud interaction. Under different convective available potential energy (CAPE) and relative humidity (RH) conditions, the influence of aerosol on clouds varies in the three regions. Under low CAPE and RH conditions, the relationship between LREF and aerosol in both the cold and warm seasons is opposite in the WTP: LREF decreases with the increase of aerosol in the cold season, while it increases in the warm season. This discrepancy may be attributed to a difference in the moisture condition between the cold and warm seasons in this region. In general, the influence of aerosols on cloud properties in TP and its adjacent regions is characterized by significant nonlinearity and spatial variability, which is likely related to the differences in aerosol types and meteorological conditions between different regions.more