Improvement of radiation modelling during cloudy sky days using in-situ and satellite measurements. 

2021 ◽  
Author(s):  
Lea Al Asmar ◽  
Luc Musson-Genon ◽  
Eric Dupont ◽  
Karine Sartelet
Keyword(s):  
Solar Radiation ◽  
Wrf Model ◽  
Cloud Fraction ◽  
Satellite Measurements ◽  
Radiation Model ◽  
Radiometric Measurements ◽  
Observational Site ◽  
Radiation Modelling ◽  
The Impact

<p>Solar radiation modelling is important for the evaluation and deployment of solar renewable energy systems. The amount of solar radiation reaching the ground is influenced by geographical parameters (seasons, latitude and local characteristics of the site) and meteorological and atmospheric parameters (like humidity, clouds or particles). Those parameters have important spatio-temporal variations that make solar radiation hard to model. </p><p>Various radiation models exist in literature. Among them, the 1D radiation model part of the computational fluid dynamics software “Code_Saturne” estimates the global and direct solar irradiances at the ground. It takes into account the impact of meteorology, atmospheric gas, particles and clouds whose influence is represented using the two-stream approximation. </p><p>The model showed satisfactory results during clear-sky days  but not during cloudy-sky days. It is a common problem in solar radiation modelling, because of the complexity to accurately represent  clouds, which are extremely variable in space and time and have a strong influence on the depletion of solar irradiance.  </p><p>In the current study, the estimation of radiation during cloudy-sky days is improved by coupling the 1D radiation model of Code_Saturne with on-site and satellite measurements of the cloud optical properties. Meteorological data are obtained from the Weather Research and Forecasting (WRF) model, aerosol’s concentrations from the air-quality modelling platform Polyphemus, and on-site measurements from the SIRTA observational site (close to Paris). Two periods are simulated: 'august 2009' and 'year 2014'. It is shown that the introduction of the measured cloud properties in the computation of the surface radiation fluxes leads to a strong reduction of the simulated errors, compared to the case where these properties are derived from the WRF model.                    </p><p>A sensitivity analysis on the parameters representing clouds in the model is conducted. It enabled us to identify the most influencing parameters - cloud optical thickness (COD) and cloud fraction - and instruments that are sufficient and mandatory for a good description of solar radiation during cloudy-sky days. A fitted model is developed to deduce the COD from liquid water path measurements. Satellite and radiometric measurements could both be used, although satellite measurements are not always available.  For the estimation of cloud fraction, the best results are obtained from shortwave radiometric measurements or from a sky imager. Moreover, large error cases in hourly values of solar fluxes are examined to understand their origin. For a large part of these error cases, there is a high variation within the hour of satellite or in situ measurements, or the presence of low clouds (in more than 50% of these cases in august 2009). </p><p> </p>

scholarly journals A new Snow-SVAT to simulate the accumulation and ablation of seasonal snow cover beneath a forest canopy

2004 ◽  
Vol 50 (169) ◽  
pp. 171-182 ◽  
Author(s):  
Melody J. Tribbeck ◽  
Robert J. Gurney ◽  
Elizabeth M. Morris ◽  
David W. C. Pearson
Keyword(s):  
Solar Radiation ◽  
Snow Cover ◽  
Forest Canopy ◽  
Correlation Coefficients ◽  
Field Measurements ◽  
Radiation Model ◽  
Physically Based ◽  
Boreal Ecosystem ◽  
Snow Model

AbstractA new snow—soil—vegetation—atmosphere transfer (Snow-SVAT) scheme, which simulates the accumulation and ablation of the snow cover beneath a forest canopy, is presented. The model was formulated by coupling a canopy optical and thermal radiation model to a physically based multi-layer snow model. This canopy radiation model is physically based yet requires few parameters, so can be used when extensive in situ field measurements are not available. Other forest effects such as the reduction of wind speed, interception of snow on the canopy and the deposition of litter were incorporated within this combined model, SNOWCAN, which was tested with data taken as part of the Boreal Ecosystem—Atmosphere Study (BOREAS) international collaborative experiment. Snow depths beneath four different canopy types and at an open site were simulated. Agreement between observed and simulated snow depths was generally good, with correlation coefficients ranging between r2 = 0.94 and r2 = 0.98 for all sites where automatic measurements were available. However, the simulated date of total snowpack ablation generally occurred later than the observed date. A comparison between simulated solar radiation and limited measurements of sub-canopy radiation at one site indicates that the model simulates the sub-canopy downwelling solar radiation early in the season to within measurement uncertainty.

scholarly journals The influence of cloud structure and droplet concentration on the reflectance of shortwave radiation

1996 ◽  
Vol 14 (8) ◽  
pp. 845-852 ◽  
Author(s):  
P. F. Coley ◽  
P. R. Jonas
Keyword(s):  
Solar Radiation ◽  
Monte Carlo Model ◽  
Liquid Water Content ◽  
Cloud Fraction ◽  
Cloud Layer ◽  
Shortwave Radiation ◽  
Transmission Properties ◽  
Droplet Concentration ◽  
The Impact ◽  
Side Illumination

Abstract. The effects of cloud shadowing, channelling, cloud side illumination and droplet concentration are investigated with regard to the reflection of shortwave solar radiation. Using simple geometric clouds, coupled with a Monte Carlo model the transmission properties of idealized cloud layers are found. The clouds are illuminated with direct solar radiation from above. The main conclusion reached is that the distribution of the cloud has a very large influence on the reflectivity of a cloud layer. In particular, if the cloud contains vertical gaps through the cloud layer in which the liquid water content is zero, then, smaller more numerous gaps are more influential on the radiation than fewer, larger gaps with equal cloud fraction. At very low solar zenith angles channelling of the radiation reduces the reflection expected on the basis of the percentage cloud cover. At high solar zenith angles the illumination of the cloud edges significantly increases the reflection despite the shadowing of one cloud by another when the width of the gaps is small. The impact of droplet concentration upon the reflection of cloud layers is also investigated. It is found that at low solar zenith angles where channelling is important, the lower concentrations increase the transmission. Conversely, when cloud edge illumination is dominant the cloud distribution is found to be more important for the higher concentrations.

scholarly journals Merging ground-based sunshine duration observations with satellite cloud and aerosol retrievals to produce high-resolution long-term surface solar radiation over China

2021 ◽  
Vol 13 (3) ◽  
pp. 907-922
Author(s):  
Fei Feng ◽  
Kaicun Wang
Keyword(s):  
Standard Deviation ◽  
High Resolution ◽  
Solar Radiation ◽  
Spatial Resolution ◽  
Sunshine Duration ◽  
Ordinary Least Squares ◽  
Cloud Fraction ◽  
Surface Solar Radiation ◽  
The Impact

Abstract. Although great progress has been made in estimating surface solar radiation (Rs) from meteorological observations, satellite retrieval, and reanalysis, getting best-estimated long-term variations in Rs are sorely needed for climate studies. It has been shown that Rs data derived from sunshine duration (SunDu) can provide reliable long-term variability, but such data are available at sparsely distributed weather stations. Here, we merge SunDu-derived Rs with satellite-derived cloud fraction and aerosol optical depth (AOD) to generate high-spatial-resolution (0.1∘) Rs over China from 2000 to 2017. The geographically weighted regression (GWR) and ordinary least-squares regression (OLS) merging methods are compared, and GWR is found to perform better. Based on the SunDu-derived Rs from 97 meteorological observation stations, which are co-located with those that direct Rs measurement sites, the GWR incorporated with satellite cloud fraction and AOD data produces monthly Rs with R2=0.97 and standard deviation =11.14 W m−2, while GWR driven by only cloud fraction produces similar results with R2=0.97 and standard deviation =11.41 W m−2. This similarity is because SunDu-derived Rs has included the impact of aerosols. This finding can help to build long-term Rs variations based on cloud data, such as Advanced Very High Resolution Radiometer (AVHRR) cloud retrievals, especially before 2000, when satellite AOD retrievals are not unavailable. The merged Rs product at a spatial resolution of 0.1∘ in this study can be downloaded at https://doi.org/10.1594/PANGAEA.921847 (Feng and Wang, 2020).

scholarly journals Neural Networks Technique for Filling Gaps in Satellite Measurements: Application to Ocean Color Observations

2016 ◽  
Vol 2016 ◽  
pp. 1-9 ◽  
Author(s):  
Vladimir Krasnopolsky ◽  
Sudhir Nadiga ◽  
Avichal Mehra ◽  
Eric Bayler ◽  
David Behringer
Keyword(s):  
Ocean Color ◽  
Ocean Dynamics ◽  
Upper Ocean ◽  
Satellite Measurements ◽  
Cheap Method ◽  
Sensitivity Studies ◽  
The Impact ◽  
Ocean Observations ◽  
Satellite Ocean Color

A neural network (NN) technique to fill gaps in satellite data is introduced, linking satellite-derived fields of interest with other satellites andin situphysical observations. Satellite-derived “ocean color” (OC) data are used in this study because OC variability is primarily driven by biological processes related and correlated in complex, nonlinear relationships with the physical processes of the upper ocean. Specifically, ocean color chlorophyll-a fields from NOAA’s operational Visible Imaging Infrared Radiometer Suite (VIIRS) are used, as well as NOAA and NASA ocean surface and upper-ocean observations employed—signatures of upper-ocean dynamics. An NN transfer function is trained, using global data for two years (2012 and 2013), and tested on independent data for 2014. To reduce the impact of noise in the data and to calculate a stable NN Jacobian for sensitivity studies, an ensemble of NNs with different weights is constructed and compared with a single NN. The impact of the NN training period on the NN’s generalization ability is evaluated. The NN technique provides an accurate and computationally cheap method for filling in gaps in satellite ocean color observation fields and time series.

Analysis of solar radiation on the surface estimated from GWNU solar radiation model with temporal resolution of satellite cloud fraction

2016 ◽  
Vol 52 (4) ◽  
pp. 405-412 ◽  
Author(s):  
Il-Sung Zo ◽  
Joon-Bum Jee ◽  
Kyu-Tae Lee ◽  
Bu-Yo Kim
Keyword(s):  
Solar Radiation ◽  
Temporal Resolution ◽  
Cloud Fraction ◽  
Radiation Model ◽  
Solar Radiation Model

scholarly journals The impact of horizontal heterogeneities, cloud fraction, and liquid water path on warm cloud effective radii from CERES-like Aqua MODIS retrievals

2013 ◽  
Vol 13 (19) ◽  
pp. 9997-10003 ◽  
Author(s):  
D. Painemal ◽  
P. Minnis ◽  
S. Sun-Mack
Keyword(s):  
Liquid Water ◽  
Vertical Structure ◽  
Cloud Fraction ◽  
Effective Radius ◽  
Liquid Water Path ◽  
Water Path ◽  
Warm Cloud ◽  
Southeast Pacific ◽  
The Impact

Abstract. The impact of horizontal heterogeneities, liquid water path (LWP from AMSR-E), and cloud fraction (CF) on MODIS cloud effective radius (re), retrieved from the 2.1 μm (re2.1) and 3.8 μm (re3.8) channels, is investigated for warm clouds over the southeast Pacific. Values of re retrieved using the CERES algorithms are averaged at the CERES footprint resolution (∼20 km), while heterogeneities (Hσ) are calculated as the ratio between the standard deviation and mean 0.64 μm reflectance. The value of re2.1 strongly depends on CF, with magnitudes up to 5 μm larger than those for overcast scenes, whereas re3.8 remains insensitive to CF. For cloudy scenes, both re2.1 and re3.8 increase with Hσ for any given AMSR-E LWP, but re2.1 changes more than for re3.8. Additionally, re3.8–re2.1 differences are positive (<1 μm) for homogeneous scenes (Hσ < 0.2) and LWP > 45 gm−2, and negative (up to −4 μm) for larger Hσ. While re3.8–re2.1 differences in homogeneous scenes are qualitatively consistent with in situ microphysical observations over the region of study, negative differences – particularly evinced in mean regional maps – are more likely to reflect the dominant bias associated with cloud heterogeneities rather than information about the cloud vertical structure. The consequences for MODIS LWP are also discussed.

scholarly journals Merging ground-based sunshine duration with satellite cloud and aerosol data to produce high resolution long-term surface solar radiation over China

2020 ◽  
Author(s):  
Fei Feng ◽  
Kaicun Wang
Keyword(s):  
Standard Deviation ◽  
High Resolution ◽  
Solar Radiation ◽  
Spatial Resolution ◽  
Sunshine Duration ◽  
Ordinary Least Squares ◽  
Cloud Fraction ◽  
Surface Solar Radiation ◽  
The Impact

Abstract. Although great progress has been made in estimating surface solar radiation (Rs) from meteorological observations, satellite retrieval and reanalysis, getting best estimated of long-term variations in Rs are sorely needed for climate studies. It has been shown that sunshine duration (SunDu)-derived Rs data can provide reliable long-term Rs variation. Here, we merge SunDu-derived Rs data with satellite-derived cloud fraction and aerosol optical depth (AOD) data to generate high spatial resolution (0.1°) Rs over China from 2000 to 2017. The geographically weighted regression (GWR) and ordinary least squares regression (OLS) merging methods are compared, and GWR is found to perform better. Whether or not AOD is taken as input data makes little difference for the GWR merging results. Based on the SunDu-derived Rs from 97 meteorological observation stations, the GWR incorporated with satellite cloud fraction and AOD data produces monthly Rs with R2 = 0.97 and standard deviation = 11.14 W/m2, while GWR driven by only cloud fraction produces similar results with R2 = 0.97 and standard deviation = 11.41 w/m2. This similarity is because SunDu-derived Rs has included the impact of aerosols. This finding can help to build long-term Rs variations based on cloud data, such as Advanced Very High Resolution Radiometer (AVHRR) cloud retrievals, especially before 2000, when satellite AOD retrievals are not unavailable. The merged Rs product at a spatial resolution of 0.1° in this study can be downloaded at https://doi.pangaea.de/10.1594/PANGAEA.921847 (Feng and Wang, 2020).

scholarly journals Uncertainties in modeling heterogeneous chemistry and Arctic ozone depletion in the winter 2009/2010

2012 ◽  
Vol 12 (10) ◽  
pp. 26245-26295 ◽  
Author(s):  
I. Wohltmann ◽  
T. Wegner ◽  
R. Müller ◽  
R. Lehmann ◽  
M. Rex ◽  
...  
Keyword(s):  
Transport Model ◽  
Particle Number Density ◽  
Rate Coefficients ◽  
The Arctic ◽  
Satellite Measurements ◽  
Mixing Ratios ◽  
Different Types ◽  
Stratospheric Clouds ◽  
The Impact

Abstract. Stratospheric chemistry and denitrification are simulated for the Arctic winter 2009/2010 with the Lagrangian Chemistry and Transport Model ATLAS. A number of sensitivity runs is used to explore the impact of uncertainties in chlorine activation and denitrification on the model results. In particular, the efficiency of chlorine activation on different types of liquid aerosol versus activation on nitric acid trihydrate clouds is examined. Additionally, the impact of changes in reaction rate coefficients, in the particle number density of polar stratospheric clouds, in supersaturation, temperature or the extent of denitrification is investigated. Results are compared to satellite measurements of MLS and ACE-FTS and to in-situ measurements onboard the Geophysica aircraft during the RECONCILE measurement campaign. It is shown that even large changes in the underlying assumptions have only a small impact on the modeled ozone loss, even though they can cause considerable differences in chemical evolution and denitrification. In addition, it is shown that chlorine activation on liquid aerosols alone is able to explain the observed magnitude and morphology of the mixing ratios of active chlorine, reservoir gases and ozone.

scholarly journals On the Potential of Improving WRF Model Forecasts by Assimilation of High-Resolution GPS-Derived Water-Vapor Maps Augmented with METEOSAT-11 Data

2020 ◽  
Vol 13 (1) ◽  
pp. 96
Author(s):  
Anton Leontiev ◽  
Dorita Rostkier-Edelstein ◽  
Yuval Reuveni
Keyword(s):  
Water Vapor ◽  
High Resolution ◽  
Mediterranean Sea ◽  
Numerical Models ◽  
Wrf Model ◽  
In Situ Measurements ◽  
Positioning Systems ◽  
The Mediterranean ◽  
The Impact

Improving the accuracy of numerical weather predictions remains a challenging task. The absence of sufficiently detailed temporal and spatial real-time in-situ measurements poses a critical gap regarding the proper representation of atmospheric moisture fields, such as water vapor distribution, which are highly imperative for improving weather predictions accuracy. The estimated amount of the total vertically integrated water vapor (IWV), which can be derived from the attenuation of global positioning systems (GPS) signals, can support various atmospheric models at global, regional, and local scales. Currently, several existing atmospheric numerical models can estimate the IWV amount. However, they do not provide accurate results compared with in-situ measurements such as radiosondes. Here, we present a new strategy for assimilating 2D IWV regional maps estimations, derived from combined GPS and METEOSAT satellite imagery data, to improve Weather Research and Forecast (WRF) model predictions accuracy in Israel and surrounding areas. As opposed to previous studies, which used point measurements of IWV in the assimilation procedure, in the current study, we assimilate quasi-continuous 2D GPS IWV maps, combined with METEOSAT-11 data. Using the suggested methodology, our results indicate an improvement of more than 30% in the root mean square error (RMSE) of WRF forecasts after assimilation relative standalone WRF, when both are compared to the radiosonde measured data near the Mediterranean coast. Moreover, significant improvements along the Jordan Rift Valley and Dead Sea Valley areas are obtained when compared to 2D IWV regional maps estimations. Improvements in these areas suggest the impact of the assimilated high resolution IWV maps, with initialization times which coincide with the Mediterranean Sea Breeze propagation from the coastline to highland stations, as the distance to the Mediterranean Sea shore, along with other features, dictates its arrival times.

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