Seasonal Net Shortwave Radiation of Bare Arable Land in Poland and Israel According to Roughness and Atmospheric Irradiance

Tillage of arable fields, using for instance a smoothing harrow, may increase the magnitude of albedo of such soil surfaces depending on the location, the sun’s illumination and atmospheric components. As these soil surfaces absorb less shortwave radiation compared to plowed soils, the result is an atmospheric cooling and a positive effect on the Earth’s climate. This paper is the follow-on of a previous study aimed at quantifying the seasonal dynamics of net shortwave radiation reflected by bare air-dried arable land areas located in contrasting environments, i.e. Poland and Israel. Soil tillage includes a plow, a disk harrow, and a smoothing harrow. Previous work concentrated on the estimate of net shortwave radiation under clear-sky theoretical scenarios, whereas the present study deals with a realistic atmosphere throughout the year 2014. This latter is characterized by the observations of the Spinning Enhanced Visible and Infrared Imager (SEVIRI) instrument on board the Meteosat Second Generation (MSG). The variations of the net shortwave radiation for the selected bare arable land areas were assessed in combining observations from Landsat 8 images and digital maps of land use and soil, plus model equations that calculate the diurnal variations of the broadband blue-sky albedo with roughness inclusive. The daily amount of net shortwave radiation for air-dried bare arable land in Poland and Israel for the time their spatial coverage is the largest was found to be about 40–50% and 10% lower, respectively, in cloudy-sky conditions compared to clear-sky conditions.

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Evaluation of net shortwave radiation over China with a regional climate model

Climate Research ◽

10.3354/cr01598 ◽

2020 ◽

Vol 80 (2) ◽

pp. 147-163

Author(s):

X Liu ◽

Y Kang ◽

Q Liu ◽

Z Guo ◽

Y Chen ◽

...

Keyword(s):

Regional Climate Model ◽

Climate Model ◽

Regional Climate ◽

Radiant Energy ◽

Energy System ◽

Radiation Budget ◽

Shortwave Radiation ◽

Monsoon Region ◽

Clear Sky ◽

Sky Conditions

The regional climate model RegCM version 4.6, developed by the European Centre for Medium-Range Weather Forecasts Reanalysis, was used to simulate the radiation budget over China. Clouds and the Earth’s Radiant Energy System (CERES) satellite data were utilized to evaluate the simulation results based on 4 radiative components: net shortwave (NSW) radiation at the surface of the earth and top of the atmosphere (TOA) under all-sky and clear-sky conditions. The performance of the model for low-value areas of NSW was superior to that for high-value areas. NSW at the surface and TOA under all-sky conditions was significantly underestimated; the spatial distribution of the bias was negative in the north and positive in the south, bounded by 25°N for the annual and seasonal averaged difference maps. Compared with the all-sky condition, the simulation effect under clear-sky conditions was significantly better, which indicates that the cloud fraction is the key factor affecting the accuracy of the simulation. In particular, the bias of the TOA NSW under the clear-sky condition was <±10 W m-2 in the eastern areas. The performance of the model was better over the eastern monsoon region in winter and autumn for surface NSW under clear-sky conditions, which may be related to different levels of air pollution during each season. Among the 3 areas, the regional average biases overall were largest (negative) over the Qinghai-Tibet alpine region and smallest over the eastern monsoon region.

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Cloudiness Information Services for Solar Energy Management in West Africa

Atmosphere ◽

10.3390/atmos11080857 ◽

2020 ◽

Vol 11 (8) ◽

pp. 857

Author(s):

Derrick Kwadwo Danso ◽

Sandrine Anquetin ◽

Arona Diedhiou ◽

Rabani Adamou

Keyword(s):

Solar Radiation ◽

Solar Energy ◽

West Africa ◽

Cloud Cover ◽

Shortwave Radiation ◽

Surface Solar Radiation ◽

Clear Sky ◽

Incoming Solar Radiation ◽

Sahel Region ◽

Sky Conditions

In West Africa (WA), interest in solar energy development has risen in recent years with many planned and ongoing projects currently in the region. However, a major drawback to this development in the region is the intense cloud cover that reduces the incoming solar radiation when present and causes fluctuations in solar power production. Therefore, understanding the occurrence of clouds and their link to the surface solar radiation in the region is important for making plans to manage future solar energy production. In this study, we use the state-of-the-art European Centre for Medium-range Weather Forecasts ReAnalysis (ERA5) dataset to examine the occurrence and persistence of cloudy and clear-sky conditions in the region. Then, we investigate the effects of cloud cover on the quantity and variability of the incoming solar radiation. The cloud shortwave radiation attenuation (CRASW↓) is used to quantify the amount of incoming solar radiation that is lost due to clouds. The results showed that the attenuation of incoming solar radiation is stronger in all months over the southern part of WA near the Guinea Coast. Across the whole region, the maximum attenuation occurs in August, with a mean CRASW↓ of about 55% over southern WA and between 20% and 35% in the Sahelian region. Southern WA is characterized by a higher occurrence of persistent cloudy conditions, while the Sahel region and northern WA are associated with frequent clear-sky conditions. Nonetheless, continuous periods with extremely low surface solar radiation were found to be few over the whole region. The analysis also showed that the surface solar radiation received from November to April only varies marginally from one year to the other. However, there is a higher uncertainty during the core of the monsoon season (June to October) with regard to the quantity of incoming solar radiation. The results obtained show the need for robust management plans to ensure the long-term success of solar energy projects in the region.

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Evaluation of Himawari-8 surface downwelling solar radiation by ground-based measurements

Atmospheric Measurement Techniques ◽

10.5194/amt-11-2501-2018 ◽

2018 ◽

Vol 11 (4) ◽

pp. 2501-2521 ◽

Cited By ~ 20

Author(s):

Alessandro Damiani ◽

Hitoshi Irie ◽

Takashi Horio ◽

Tamio Takamura ◽

Pradeep Khatri ◽

...

Keyword(s):

Global Radiation ◽

Time Estimation ◽

Spatial Domain ◽

Surface Radiation ◽

Spatiotemporal Variability ◽

Shortwave Radiation ◽

Time Step ◽

Clear Sky ◽

Aerosol Forcing ◽

Sky Conditions

Abstract. Observations from the new Japanese geostationary satellite Himawari-8 permit quasi-real-time estimation of global shortwave radiation at an unprecedented temporal resolution. However, accurate comparisons with ground-truthing observations are essential to assess their uncertainty. In this study, we evaluated the Himawari-8 global radiation product AMATERASS using observations recorded at four SKYNET stations in Japan and, for certain analyses, from the surface network of the Japanese Meteorological Agency in 2016. We found that the spatiotemporal variability of the satellite estimates was smaller than that of the ground observations; variability decreased with increases in the time step and spatial domain. Cloud variability was the main source of uncertainty in the satellite radiation estimates, followed by direct effects caused by aerosols and bright albedo. Under all-sky conditions, good agreement was found between satellite and ground-based data, with a mean bias in the range of 20–30 W m−2 (i.e., AMATERASS overestimated ground observations) and a root mean square error (RMSE) of approximately 70–80 W m−2. However, results depended on the time step used in the validation exercise, on the spatial domain, and on the different climatological regions. In particular, the validation performed at 2.5 min showed largest deviations and RMSE values ranging from about 110 W m−2 for the mainland to a maximum of 150 W m−2 in the subtropical region. We also detected a limited overestimation in the number of clear-sky episodes, particularly at the pixel level. Overall, satellite-based estimates were higher under overcast conditions, whereas frequent episodes of cloud-induced enhanced surface radiation (i.e., measured radiation was greater than expected clear-sky radiation) tended to reduce this difference. Finally, the total mean bias was approximately 10–15 W m−2 under clear-sky conditions, mainly because of overall instantaneous direct aerosol forcing efficiency in the range of 120–150 W m−2 per unit of aerosol optical depth (AOD). A seasonal anticorrelation between AOD and global radiation differences was evident at all stations and was also observed within the diurnal cycle.

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Radiation Exchange at Greenhouse Tilted Surfaces under All-Sky Conditions

10.5772/intechopen.95595 ◽

2021 ◽

Author(s):

Erick K. Ronoh

Keyword(s):

Thermal Radiation ◽

Thermal Environment ◽

Shortwave Radiation ◽

Material Surface ◽

Climate Control ◽

Surface Design ◽

Clear Sky ◽

Radiation Exchange ◽

Surface Inclination ◽

Sky Conditions

Greenhouses generally exhibit a greater degree of thermal radiation interaction with the surroundings than other buildings. A number of greenhouse thermal environment analyses have handled the thermal radiation exchange in different ways. Thermal radiation exchange at greenhouse surfaces is of great interest for energy balance. It dominates the heat transfer mechanisms especially between the cover material surface and the surrounding atmosphere. At these surfaces, the usual factors of interest are local temperatures and energy fluxes. The greenhouse surfaces are inclined and oriented in various ways and thus can influence the radiation exchange. The scope of this work is determination of the thermal radiation exchange models as well as effects of surface inclination and orientation on the radiation exchange between greenhouse surfaces and sky. Apart from the surface design and the thermal properties of the cover, the key meteorological parameters influencing longwave and shortwave radiation models were considered in detail. For the purpose of evaluating surface inclination and orientation effects, four identical thermal boxes were developed to simulate the roof and wall greenhouse surfaces. The surface temperatures and atmospheric parameters were noted under all-sky conditions (clear-sky and overcast). Differences in terms of surface-to-air temperature differences at the exposed roof and wall surfaces as influenced by surface inclination and orientation are discussed in this work. Overall, the findings of this work form a basis for decisions on greenhouse design improvements and climate control interventions in the horticultural industry.

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Evaluation of Himawari-8 surface downwelling solar radiation by SKYNET observations

10.5194/amt-2017-440 ◽

2018 ◽

Cited By ~ 2

Author(s):

Alessandro Damiani ◽

Hitoshi Irie ◽

Takashi Horio ◽

Tamio Takamura ◽

Pradeep Khatri ◽

...

Keyword(s):

Global Radiation ◽

Time Estimation ◽

Spatial Domain ◽

Surface Radiation ◽

Spatiotemporal Variability ◽

Shortwave Radiation ◽

Time Step ◽

Clear Sky ◽

Aerosol Forcing ◽

Sky Conditions

Abstract. Observations from the new Japanese geostationary satellite Himawari-8 permit quasi-real-time estimation of global shortwave radiation at an unprecedented temporal resolution. However, accurate comparisons with ground truthing observations are essential to assess their uncertainty. In this study, we evaluated the Himawari-8 global radiation product AMATERASS using observations recorded at four SKYNET stations in Japan and, for certain analyses, from the surface network of the Japanese Meteorological Agency in 2016. We found that the spatiotemporal variability of the satellite estimates was smaller than that of the ground observations; variability decreased with increases in the time step and spatial domain. Cloud variability was the main source of uncertainty in the satellite radiation estimates, followed by direct effects caused by aerosols and bright albedo. Under all-sky conditions, good agreement was found between satellite and ground-based data, with a mean bias in the range of 20–30 W/m2 (i.e., AMATERASS overestimated ground observations) and a root mean square error of approximately 80 W/m2. However, results depended on the time step used in the validation exercise and on the spatial domain. We also detected a limited overestimation in the number of clear-sky episodes, particularly at the pixel level. Overall, satellite-based estimates were higher under overcast conditions, whereas frequent episodes of cloud-induced enhanced surface radiation (i.e., measured radiation was greater than expected clear-sky radiation) tended to reduce this difference. Finally, the total mean bias was reduced to approximately 10–15 W/m2 under clear-sky conditions, mainly because of overall instantaneous direct aerosol forcing efficiency in the range of 120–150 W/m2 per unit of aerosol optical depth (AOD). A seasonal anti-correlation between AOD and global radiation differences was evident at all stations and was also observed within the diurnal cycle.

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Efficient downscaling of satellite oceanographic data with convolutional neural networks

SIGSPATIAL Special ◽

10.1145/3447994.3448011 ◽

2021 ◽

Vol 12 (3) ◽

pp. 46-47

Author(s):

Nikita Saxena

Keyword(s):

Neural Networks ◽

Deep Learning ◽

Convolutional Neural Networks ◽

Super Resolution ◽

Sea Surface ◽

Clear Sky ◽

Oceanographic Data ◽

Computationally Expensive ◽

Sky Conditions ◽

Data Inference

Space-borne satellite radiometers measure Sea Surface Temperature (SST), which is pivotal to studies of air-sea interactions and ocean features. Under clear sky conditions, high resolution measurements are obtainable. But under cloudy conditions, data analysis is constrained to the available low resolution measurements. We assess the efficiency of Deep Learning (DL) architectures, particularly Convolutional Neural Networks (CNN) to downscale oceanographic data from low spatial resolution (SR) to high SR. With a focus on SST Fields of Bay of Bengal, this study proves that Very Deep Super Resolution CNN can successfully reconstruct SST observations from 15 km SR to 5km SR, and 5km SR to 1km SR. This outcome calls attention to the significance of DL models explicitly trained for the reconstruction of high SR SST fields by using low SR data. Inference on DL models can act as a substitute to the existing computationally expensive downscaling technique: Dynamical Downsampling. The complete code is available on this Github Repository.

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Application of an improved surface energy balance model to two large valley glaciers in the St. Elias Mountains, Yukon

Journal of Glaciology ◽

10.1017/jog.2020.106 ◽

2020 ◽

pp. 1-16

Author(s):

Tim Hill ◽

Christine F. Dow ◽

Eleanor A. Bash ◽

Luke Copland

Keyword(s):

Energy Balance ◽

Surface Energy ◽

Surface Energy Balance ◽

Shortwave Radiation ◽

Balance Model ◽

Landsat 8 ◽

Glacier Surface ◽

Ice Dynamics ◽

Surface Melt

Abstract Glacier surficial melt rates are commonly modelled using surface energy balance (SEB) models, with outputs applied to extend point-based mass-balance measurements to regional scales, assess water resource availability, examine supraglacial hydrology and to investigate the relationship between surface melt and ice dynamics. We present an improved SEB model that addresses the primary limitations of existing models by: (1) deriving high-resolution (30 m) surface albedo from Landsat 8 imagery, (2) calculating shadows cast onto the glacier surface by high-relief topography to model incident shortwave radiation, (3) developing an algorithm to map debris sufficiently thick to insulate the glacier surface and (4) presenting a formulation of the SEB model coupled to a subsurface heat conduction model. We drive the model with 6 years of in situ meteorological data from Kaskawulsh Glacier and Nàłùdäy (Lowell) Glacier in the St. Elias Mountains, Yukon, Canada, and validate outputs against in situ measurements. Modelled seasonal melt agrees with observations within 9% across a range of elevations on both glaciers in years with high-quality in situ observations. We recommend applying the model to investigate the impacts of surface melt for individual glaciers when sufficient input data are available.

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A Simple Method for Converting 1-km Resolution Daily Clear-Sky LST into Real LST

Remote Sensing ◽

10.3390/rs12101641 ◽

2020 ◽

Vol 12 (10) ◽

pp. 1641

Author(s):

Yunfei Zhang ◽

Yunhao Chen ◽

Jing Li ◽

Xi Chen

Keyword(s):

Land Surface ◽

Missing Values ◽

Vegetation Index ◽

Normalized Difference Vegetation Index ◽

Shortwave Radiation ◽

Simple Method ◽

The Real ◽

Independent Variables ◽

Clear Sky ◽

Reconstruction Methods

Land-surface temperature (LST) plays a key role in the physical processes of surface energy and water balance from local through global scales. The widely used one kilometre resolution daily Moderate Resolution Imaging Spectroradiometer (MODIS) LST product has missing values due to the influence of clouds. Therefore, a large number of clear-sky LST reconstruction methods have been developed to obtain spatially continuous LST datasets. However, the clear-sky LST is a theoretical value that is often an overestimate of the real value. In fact, the real LST (also known as cloudy-sky LST) is more necessary and more widely used. The existing cloudy-sky LST algorithms are usually somewhat complicated, and the accuracy needs to be improved. It is necessary to convert the clear-sky LST obtained by the currently better-developed methods into cloudy-sky LST. We took the clear-sky LST, cloud-cover duration, downward shortwave radiation, albedo and normalized difference vegetation index (NDVI) as five independent variables and the real LST at the ground stations as the dependent variable to perform multiple linear regression. The mean absolute error (MAE) of the cloudy-sky LST retrieved by this method ranged from 3.5–3.9 K. We further analyzed different cases of the method, and the results suggested that this method has good flexibility. When we chose fewer independent variables, different clear-sky algorithms, or different regression tools, we also achieved good results. In addition, the method calculation process was relatively simple and can be applied to other research areas. This study preliminarily explored the influencing factors of the real LST and can provide a possible option for researchers who want to obtain cloudy-sky LST through clear-sky LST, that is, a convenient conversion method. This article lays the foundation for subsequent research in various fields that require real LST.

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