Variability class dependent evaluation of the CAMS Solar Radiation Service

2021 ◽  
Author(s):  
Faiza Azam ◽  
Jethro Betcke ◽  
Marion Schroedter-Homscheidt ◽  
Mireille Lefevre ◽  
Yves-Marie Saint-Drenan ◽  
...  

<p>The Copernicus Atmospheric Monitoring Service (CAMS) offers Solar radiation services (CRS) providing information on surface solar irradiance (SSI). The service is currently derived from Meteosat Second Generation (MSG) and the service evolution includes its extension to other parts of the globe. CRS provides clear and all sky time series combining satellite data products with numerical model output from CAMS on aerosols, water vapour and ozone. These products are available from 2004 until yesterday. A regular quality control of input parameters, quarterly benchmarking against ground measurements and automatic consistency checks ensure the service quality.</p> <p>Variability of solar surface irradiances in the 1-minute range is of interest especially for solar energy applications. The variability classes can be defined based on ground as well as satellite-based measurements. This study will present the evaluation of the CAMS CRS based on the eight variability classes derived from ground observations of direct normal irradiation (DNI) (Schroedter-Homscheidt et al., 2018). Such an analysis will help assess the impact of recent improvements in the derivation of all sky irradiance under different cloudy conditions.</p> <p>References:</p> <p>Schroedter-Homscheidt, M., S. Jung, M. Kosmale, 2018: Classifying ground-measured 1 minute temporal variability within hourly intervals for direct normal irradiances. – Meteorol. Z. 27, 2, 160–179. DOI:10.1127/metz/2018/0875.</p>

2021 ◽  
Author(s):  
Marion Schroedter-Homscheidt ◽  
Faiza Azam ◽  
Jethro Betcke ◽  
Hartwig Deneke ◽  
Mireille Lefèvre ◽  
...  

<p>The Copernicus Atmospheric Monitoring Service (CAMS) provides a surface solar irradiance service which is currently derived from Meteosat Second Generation (MSG). The service combines satellite data products with numerical model output from CAMS on aerosols, water vapour and ozone in order to provide both clear-sky and all-sky radiation time series with availability from 2004 until yesterday. A regular quality control of input parameters, quarterly benchmarking against ground measurements and automatic consistency checks ensures the data quality. To anticipate the increase in resolution that will occur with the commissioning of MTG, it is necessary to enhance methods currently used in CAMS.</p><p>The recent development focuses on the assessment and improvement of cloud retrieval products from APOLLO_NG in irradiance retrieval schemes. Such a validation against ground-based surface solar irradiances provides insight into the use of probabilistic cloud masking, specific results for pixels with small COD values below 5, as well as in partly cloudy pixel conditions. Such conditions are often neglected in existing cloud retrieval validation studies due to the expected large uncertainties of cloud properties. But they cannot be omitted in irradiance retrieval schemes for solar energy sector users as complete temporal coverage is required.</p><p>Such cloud situations may additionally be better characterized in future with the help of spatially higher resolved channels. Using e.g. SEVIRI’s HRV channel is known to be beneficial in cloud index based irradiance retrieval schemes, but has not been evaluated yet for cloud physical retrieval based irradiance schemes. Results from such a method development for the HRV channel in preparation for MTG, Himawari-8, and GOES-R channels will be presented.</p>


2009 ◽  
Vol 26 (2) ◽  
pp. 395-402 ◽  
Author(s):  
Stephanie Guinehut ◽  
Christine Coatanoan ◽  
Anne-Lise Dhomps ◽  
Pierre-Yves Le Traon ◽  
Gilles Larnicol

Abstract Satellite altimeter measurements are used to check the quality of the Argo profiling floats time series. The method compares collocated sea level anomalies from altimeter measurements and dynamic height anomalies calculated from Argo temperature and salinity profiles for each Argo float time series. Different kinds of anomalies (sensor drift, bias, spikes, etc.) have been identified on some real-time but also delayed-mode Argo floats. About 4% of the floats should probably not be used until they are carefully checked and reprocessed by the principal investigators (PIs). The method appears to be very complementary to the existing quality control checks performed in real time or delayed mode. It could also be used to quantify the impact of the adjustments made in delayed mode on the pressure, temperature, and salinity fields.


2014 ◽  
Author(s):  
Νικόλαος Μπενάς

A deterministic spectral shortwave radiative transfer model was used forthe computation of the Earth's atmospheric radiation budget, based on hightemporal and spatial resolution satellite data of aerosols and atmospheric climaticparameters from the Moderate Resolution Imaging Spectroradiometer(MODIS) sensor.The study focused on the evaluation of the aerosol direct radiative effect(DRE) on the radiation budget components. Due to the high spatialand temporal variability of aerosols, the DRE, which constitutes a crucialcomponent of the overall eect of aerosols on climate, is thus also highlyvariable.The aerosol direct eect on the tropospheric ozone photolysis rate, J(O1D),was also examined, being a dominant sink of tropospheric ozone. We notethat tropospheric ozone contributes to the global greenhouse eect. Thus,J(O1D) is an important climatic parameter, which needs to be studied usingmodelling approaches, due to the scarcity of measuring stations, andbecause it takes place primarily below 330 nm, a spectral region where theaerosol eect is a key operating factor.The aerosol direct eect on potential evaporation was also assessed. Potentialevaporation equals actual evaporation in shallow lakes, and constitutesa crucial parameter of the hydrological cycle. The aerosol DRE decreasespotential evaporation by decreasing the solar radiation reaching the Earth'ssurface.The model runs were performed for the period 2000{2010 over severalsites in Greece, which are characterised by high aerosol loads, with uniquecharacteristics in terms of seasonal variation and origin. Two research stationsin Crete (HCMR/AERONET and Finokalia), were selected due to theappropriateness of the island for studying Saharan dust episodes, which arefrequent in the wider Eastern Mediterranean, and the availability of ground{based data for both model supplementary input and validation. The modelwas also run over four lakes in Central Greece, which constitute the mainwater supply reservoirs of the city of Athens, for the evaluation of the aerosol eect on potential evaporation.MODIS Level 2 data of aerosols, clouds and atmospheric parameters wereanalysed and processed, and used as input to the model. These data areavailable since 2000, on a daily basis and at 10km10km and 5km5kmspatial resolution. The model takes into account all physical parameters andprocesses that aect signicantly the solar radiation transfer. The aerosolDRE is determined at the Earth's surface, within the atmosphere and at thetop of the atmosphere.The model output downwelling shortwave radiation was successfully validatedagainst ground{based measurements at the HCMR and Finokalia stationsand at the four lakes in Central Greece. The model output J(O1D) wassuccessfully validated against Finokalia station measurements. The analysisof the aerosol DRE on the model radiation budget, J(O1D) and potentialevaporation was performed on an instantaneous/daily mean, seasonal andinter{annual basis. Dust event eects were also quantied, and trends duringthe period examined were assessed and evaluated in terms of correspondingtrends and eects of operating factors, including aerosols, clouds and totalozone.Results show a decreasing trend in aerosols and the corresponding DREover all sites examined. Changes in the radiation budget components, however,are also controlled by other factors; an increase in cloud fraction overHCMR station counterbalanced the eect that the DRE reduction wouldhave caused. Similarly, although the DRE on J(O1D) has decreased, J(O1D)has not increased as was expected, due to an increase in total atmosphericozone. The presence of aerosols reduces potential evaporation by about 0.5mm on a mean daily basis, reaching up to 2 mm in summer. However, adecreasing trend in the aerosol load and DRE was found over all lakes duringthe period 2001{2010.Depending on the availability of model input data, the methodology developedin this study is applicable to any region of specic interest over theglobe.


2021 ◽  
Vol 10 (3) ◽  
pp. 401-414
Author(s):  
Omaima El Alani ◽  
Hicham Ghennioui ◽  
Abdellatif Ghennioui ◽  
Yves-Marie Saint-Drenan ◽  
Philippe Blanc ◽  
...  

Solar irradiance data from high-quality ground-based measurements are primordial for different solar energy applications. In order to achieve the required accuracy, quality control procedures are of great benefit. A variety of approaches   have been proposed. In this sense, some approaches propose a visual representation of the routine, while others only provide a time series of binary flag values, and do not propose any specific visualization of the flagged data as opposed to non-flagged ones. In this regard, the present paper puts forward a complete routine including several quality control procedures for solar irradiance measurements by providing visual support for these different approaches. The visual tool in question was validated using five years research data with 10 minutes resolution of the global, diffuse and direct components of solar irradiation collected from three ground-based weather stations in Morocco. This visual tool puts forth a more precise idea of the measurement quality by detecting various errors, such as time shifts, outliers identification; either with one or two components, or consistency tests between the three components of solar radiation when available. The proposed tool can be regarded as a means of improving the detection rate of abnormal data as a first step in diagnosing the prominent causes of error.


Author(s):  
Manajit Sengupta

Clouds, aerosols, water vapor and other atmospheric constituents influence solar energy reaching the earth’s surface. Each of these atmospheric constituents has it’s own inherent scale of temporal and spatial variability and they in turn influence the variability in the amount of solar radiation reaching the earth’s surface. This combined influence of the atmospheric constituents and their separate variability characteristics makes solar variability modeling a complicated task. Output from photovoltaic (PV) power plants is dependent on the amount of solar energy reaching the surface. Therefore variability in solar radiation results in variability in PV plant output. The issue of variability in PV plant output has become important in the last couple of years as utility scale PV plants go online and increase in size. Understanding variability in PV plant output requires an understanding of (a) the spatial and temporal variability of solar radiation; (b) the influence of this solar variability on PV plant output. The goal of this paper is to understand what temporal and spatial scales of variability in Global Horizontal Radiation (GHI) are important to a PV plants and what measurements are needed to be able to characterize them. As solar radiation measuring instruments are point receivers it is important to understand how those measurements translate to energy received over a larger spatial extent. Also of importance is the temporal nature of variability characterized not at a single point on the ground but over large spatial areas. In this research we use high temporal and spatial resolution measurements from multiple time synchronized solar radiation sensors to create solar radiation fields at various spatial and temporal scales using a wide range of interpolation techniques. These solar fields are then used to create plant power output for various size PV plants. As various interpolation schemes can produce different distributions we investigate the impact of interpolation schemes on GHI and power output distribution. While power output from PV plants is an important quantity the temporal variability of power is a matter of concern to utilities. In this paper we show how PV plant output varies across different time scales.


1982 ◽  
Vol 14 (4-5) ◽  
pp. 245-252 ◽  
Author(s):  
C S Sinnott ◽  
D G Jamieson

The combination of increasing nitrate concentrations in the River Thames and the recent EEC Directive on the acceptable level in potable water is posing a potential problem. In assessing the impact of nitrates on water-resource systems, extensive use has been made of time-series analysis and simulation. These techniques are being used to define the optimal mix of alternatives for overcoming the problem on a regional basis.


GEOgraphia ◽  
2018 ◽  
Vol 20 (43) ◽  
pp. 124
Author(s):  
Amaury De Souza ◽  
Priscilla V Ikefuti ◽  
Ana Paula Garcia ◽  
Debora A.S Santos ◽  
Soetania Oliveira

Análise e previsão de parâmetros de qualidade do ar são tópicos importantes da pesquisa atmosférica e ambiental atual, devido ao impacto causado pela poluição do ar na saúde humana. Este estudo examina a transformação do dióxido de nitrogênio (NO2) em ozônio (O3) no ambiente urbano, usando o diagrama de séries temporais. Foram utilizados dados de concentração de poluentes ambientais e variáveis meteorológicas para prever a concentração de O3 na atmosfera. Foi testado o emprego de modelos de regressão linear múltipla como ferramenta para a predição da concentração de O3. Os resultados indicam que o valor da temperatura e a presença de NO2 influenciam na concentração de O3 em Campo Grande, capital do Estado do Mato Grosso do Sul. Palavras-chave: Ozônio. Dióxido de nitrogênio. Séries cronológicas. Regressões. ANALYSIS OF THE RELATIONSHIP BETWEEN O3, NO AND NO2 USING MULTIPLE LINEAR REGRESSION TECHNIQUES.Abstract: Analysis and prediction of air quality parameters are important topics of current atmospheric and environmental research due to the impact caused by air pollution on human health. This study examines the transformation of nitrogen dioxide (NO2) into ozone (O3) in the urban environment, using the time series diagram. Environmental pollutant concentration and meteorological variables were used to predict the O3 concentration in the atmosphere. The use of multiple linear regression models was tested as a tool to predict O3 concentration. The results indicate that the temperature value and the presence of NO2 influence the O3 concentration in Campo Grande, capital of the State of Mato Grosso do Sul.Keywords: Ozone. Nitrogen dioxide. Time series. Regressions. ANÁLISIS DE LA RELACIÓN ENTRE O3, NO Y NO2 UTILIZANDO MÚLTIPLES TÉCNICAS DE REGRESIÓN LINEAL.Resumen: Análisis y previsión de los parámetros de calidad del aire son temas importantes de la actual investigación de la atmósfera y el medio ambiente, debido al impacto de la contaminación atmosférica sobre la salud humana. Este estudio examina la transformación del dióxido de nitrógeno (NO2) en ozono (O3) en el entorno urbano, utilizando el diagrama de series de tiempo. Las concentraciones de los contaminantes ambientales de datos y variables climáticas fueron utilizadas para predecir la concentración de O3 en la atmósfera. El uso de múltiples modelos de regresión lineal como herramienta para predecir la concentración de O3 se puso a prueba. Los resultados indican que el valor de la temperatura y la presencia de NO2 influyen en la concentración de O3 en Campo Grande, capital del Estado de Mato Grosso do Sul.Palabras clave: Ozono. Dióxido de nitrógeno. Series de tiempo. Regresiones.


Author(s):  
Richard McCleary ◽  
David McDowall ◽  
Bradley J. Bartos

The general AutoRegressive Integrated Moving Average (ARIMA) model can be written as the sum of noise and exogenous components. If an exogenous impact is trivially small, the noise component can be identified with the conventional modeling strategy. If the impact is nontrivial or unknown, the sample AutoCorrelation Function (ACF) will be distorted in unknown ways. Although this problem can be solved most simply when the outcome of interest time series is long and well-behaved, these time series are unfortunately uncommon. The preferred alternative requires that the structure of the intervention is known, allowing the noise function to be identified from the residualized time series. Although few substantive theories specify the “true” structure of the intervention, most specify the dichotomous onset and duration of an impact. Chapter 5 describes this strategy for building an ARIMA intervention model and demonstrates its application to example interventions with abrupt and permanent, gradually accruing, gradually decaying, and complex impacts.


2008 ◽  
Vol 18 (12) ◽  
pp. 3679-3687 ◽  
Author(s):  
AYDIN A. CECEN ◽  
CAHIT ERKAL

We present a critical remark on the pitfalls of calculating the correlation dimension and the largest Lyapunov exponent from time series data when trend and periodicity exist. We consider a special case where a time series Zi can be expressed as the sum of two subsystems so that Zi = Xi + Yi and at least one of the subsystems is deterministic. We show that if the trend and periodicity are not properly removed, correlation dimension and Lyapunov exponent estimations yield misleading results, which can severely compromise the results of diagnostic tests and model identification. We also establish an analytic relationship between the largest Lyapunov exponents of the subsystems and that of the whole system. In addition, the impact of a periodic parameter perturbation on the Lyapunov exponent for the logistic map and the Lorenz system is discussed.


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