Radiative effect of different aerosol types in clear sky conditions according to COSMO-Ru model

2018 ◽  
Author(s):  
Marina Shatunova ◽  
Gdaliy Rivin ◽  
Aleksander Makshtas ◽  
Aleksei Poliukhov ◽  
Natalia Chubarova ◽  
...  
Keyword(s):  
Radiative Effect ◽  
Clear Sky ◽  
Sky Conditions ◽  
Aerosol Types

scholarly journals Variability and trend of diurnal temperature range in China and their relationship to total cloud cover and sunshine duration

2013 ◽  
Vol 31 (5) ◽  
pp. 795-804 ◽  
Author(s):  
X. Xia
Keyword(s):  
Diurnal Temperature Range ◽  
Cloud Cover ◽  
Sunshine Duration ◽  
Radiative Effect ◽  
Total Cloud Cover ◽  
Diurnal Temperature ◽  
Temperature Range ◽  
Clear Sky ◽  
Sky Conditions

Abstract. This study aims to investigate the effect of total cloud cover (TCC) and sunshine duration (SSD) in the variation of diurnal temperature range (DTR) in China during 1954–2009. As expected, the inter-annual variation of DTR was mainly determined by TCC. Analysis of trends of 30-year moving windows of DTR and TCC time series showed that TCC changes could account for that of DTR in some cases. However, TCC decreased during 1954–2009, which did not support DTR reduction across China. DTRs under sky conditions such as clear, cloudy and overcast showed nearly the same decreasing rate that completely accounted for the overall DTR reduction. Nevertheless, correlation between SSD and DTR was weak and not significant under clear sky conditions in which aerosol direct radiative effect should be dominant. Furthermore, 30–60% of DTR reduction was associated with DTR decrease under overcast conditions in south China. This implies that aerosol direct radiative effect appears not to be one of the main factors determining long-term changes in DTR in China.

scholarly journals Global Clear-Sky Aerosol Speciated Direct Radiative Effects over 40 Years (1980–2019)

Atmosphere ◽  
2021 ◽  
Vol 12 (10) ◽  
pp. 1254
Author(s):  
Marios-Bruno Korras-Carraca ◽  
Antonis Gkikas ◽  
Christos Matsoukas ◽  
Nikolaos Hatzianastassiou
Keyword(s):  
Global Climate ◽  
Regional Scale ◽  
Radiative Transfer Model ◽  
Transfer Model ◽  
Radiative Effect ◽  
Clear Sky ◽  
Order Of Magnitude ◽  
Carbon Aerosols ◽  
Aerosol Types

We assess the 40-year climatological clear-sky global direct radiative effect (DRE) of five main aerosol types using the MERRA-2 reanalysis and a spectral radiative transfer model (FORTH). The study takes advantage of aerosol-speciated, spectrally and vertically resolved optical properties over the period 1980–2019, to accurately determine the aerosol DREs, emphasizing the attribution of the total DREs to each aerosol type. The results show that aerosols radiatively cool the Earth’s surface and heat its atmosphere by 7.56 and 2.35 Wm−2, respectively, overall cooling the planet by 5.21 Wm−2, partly counterbalancing the anthropogenic greenhouse global warming during 1980–2019. These DRE values differ significantly in terms of magnitude, and even sign, among the aerosol types (sulfate and black carbon aerosols cool and heat the planet by 1.88 and 0.19 Wm−2, respectively), the hemispheres (larger NH than SH values), the surface cover type (larger land than ocean values) or the seasons (larger values in local spring and summer), while considerable inter-decadal changes are evident. These DRE differences are even larger by up to an order of magnitude on a regional scale, highlighting the important role of the aerosol direct radiative effect for local and global climate.

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

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.

Efficient downscaling of satellite oceanographic data with convolutional neural networks

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.

Intra-Day DNI Forecasting Under Clear Sky Conditions Using ANFIS

2014 ◽  
Vol 47 (3) ◽  
pp. 10361-10366 ◽  
Author(s):  
Rémi Chauvin ◽  
Julien Nou ◽  
Stéphane Thil ◽  
Stéphane Grieu
Keyword(s):  
Clear Sky ◽  
Sky Conditions

scholarly journals A Blended Sea Ice Concentration Product from AMSR2 and VIIRS

2021 ◽  
Vol 13 (15) ◽  
pp. 2982
Author(s):  
Richard Dworak ◽  
Yinghui Liu ◽  
Jeffrey Key ◽  
Walter N. Meier
Keyword(s):  
Sea Ice ◽  
Spatial Resolution ◽  
Infrared Imaging ◽  
High Spatial Resolution ◽  
Sea Ice Concentration ◽  
Clear Sky ◽  
Ice Concentration ◽  
Best Linear Unbiased ◽  
The Individual ◽  
Sky Conditions

An effective blended Sea-Ice Concentration (SIC) product has been developed that utilizes ice concentrations from passive microwave and visible/infrared satellite instruments, specifically the Advanced Microwave Scanning Radiometer-2 (AMSR2) and the Visible Infrared Imaging Radiometer Suite (VIIRS). The blending takes advantage of the all-sky capability of the AMSR2 sensor and the high spatial resolution of VIIRS, though it utilizes only the clear sky characteristics of VIIRS. After both VIIRS and AMSR2 images are remapped to a 1 km EASE-Grid version 2, a Best Linear Unbiased Estimator (BLUE) method is used to combine the AMSR2 and VIIRS SIC for a blended product at 1 km resolution under clear-sky conditions. Under cloudy-sky conditions the AMSR2 SIC with bias correction is used. For validation, high spatial resolution Landsat data are collocated with VIIRS and AMSR2 from 1 February 2017 to 31 October 2019. Bias, standard deviation, and root mean squared errors are calculated for the SICs of VIIRS, AMSR2, and the blended field. The blended SIC outperforms the individual VIIRS and AMSR2 SICs. The higher spatial resolution VIIRS data provide beneficial information to improve upon AMSR2 SIC under clear-sky conditions, especially during the summer melt season, as the AMSR2 SIC has a consistent negative bias near and above the melting point.

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

2021 ◽  
Vol 13 (10) ◽  
pp. 1897
Author(s):  
Jerzy Cierniewski ◽  
Jean-Louis Roujean ◽  
Jarosław Jasiewicz ◽  
Sławomir Królewicz
Keyword(s):  
Arable Land ◽  
Soil Tillage ◽  
Shortwave Radiation ◽  
Landsat 8 ◽  
Clear Sky ◽  
Spatial Coverage ◽  
Arable Fields ◽  
Model Equations ◽  
Earth’S Climate ◽  
Sky Conditions

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.

Aerosol Effects on Temperature Forecast in the COSMO-Ru Model

2021 ◽  
pp. 29-39
Author(s):  
A. A. Poliukhov ◽  
◽  
D. V. Blinov ◽  
◽  
Keyword(s):  
Air Temperature ◽  
Numerical Experiments ◽  
Surface Air Temperature ◽  
European Part ◽  
Clear Sky ◽  
Temperature Forecast ◽  
European Part Of Russia ◽  
Simulated Surface ◽  
Aerosol Effects ◽  
Sky Conditions

Aerosol effects on the forecast of surface temperature, as well as temperature at the levels of 850 and 500 hPa over Europe and the European part of Russia are studied using various aerosol climatologies: Tanre, Tegen, and MACv2. The numerical experiments with the COSMO-Ru model are performed for the central months of the seasons (January, April, July, and October) in 2017. It is found that a change in the simulated surface air temperature over land can reach 1C when using Tegen and MACv2 data as compared to Tanre. At 850 and 500 hPa levels, the changes do not exceed 0.4C. At the same time, it is shown that a decrease in the root-mean-square error of 2-m air temperature forecast at individual stations reaches 0.5C when using Tegen and MACv2 data and 1C for clear-sky conditions in Moscow.

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