scholarly journals Quality Scoring of the Fengyun 4A Clear Sky Radiance Product

2021 ◽  
Vol 13 (18) ◽  
pp. 3658
Author(s):  
Tianlei Yu ◽  
Gang Ma ◽  
Feng Lu ◽  
Xiaohu Zhang ◽  
Peng Zhang
Keyword(s):  
Scoring System ◽  
Cloud Cover ◽  
Weather Prediction ◽  
Field Of View ◽  
Surface Type ◽  
Clear Sky ◽  
L1 Data ◽  
Level 1 ◽  
Sky Radiance ◽  
Percentile Point

The Clear Sky Radiance (CSR) product has been widely used instead of Level 1 (L1) geostationary imager data in data assimilation for numerical weather prediction due to its many advantages concerning superobservation methodology. In this study, CSR was produced in two water vapor channels (channels 9 and channel 10, with wavelengths at 5.8–6.7 μm and 6.9–7.3 μm) of the Advanced Geostationary Radiation Imager aboard Fengyun 4A. The root mean square error (RMSE) between CSR observations and backgrounds was used as a quality flag and was predicted by cloud cover, standard deviation (STD), surface type, and elevation of a CSR field of view (FOV). Then, a centesimal scoring system based on the predicted RMSE was set to a CSR FOV that indicates its percentile point in the quality distribution of the whole FOV. Validations of the scoring system demonstrated that the biases of the predicted RMSE were small for all FOVs and that the score was consistent with the predicted RMSE, especially for FOVs with high scores. We suggest using this score for quality control (QC) to replace the QC of cloud cover, STD, and elevation of CSR, and we propose 40 points as the QC threshold for the two channels, above which the predicted RMSE of a CSR is superior to the RMSE of averaged clear-sky L1 data.

A Clear Sky Model of Diffuse Sky Radiance

1987 ◽  
Vol 109 (1) ◽  
pp. 9-14 ◽  
Author(s):  
F. C. Hooper ◽  
A. P. Brunger ◽  
C. S. Chan
Keyword(s):  
Direct Determination ◽  
Field Of View ◽  
Mean Bias Error ◽  
Bias Error ◽  
Mean Square ◽  
Clear Sky ◽  
Expected Values ◽  
Sky Radiance ◽  
Made In

A model, previously proposed, describing the sky radiance as a continuous function, has been calibrated from 11,000 individual measurements made in scans taken across springtime skies in Toronto using a narrow field of view radiometer. The model reproduces the measured sky radiance with a mean bias error under five percent and a root mean square error only slightly larger than the standard deviation of the measurements. The model is applied to the calculation of the ratio of the clear sky diffuse irradiance on a slope to that on a horizontal surface. Charts are presented for the direct determination of the expected values of these ratios for surfaces at three tilts and at any azimuth.

scholarly journals 3D-VAR Data Assimilation of SEVIRI Radiances for the Prediction of Solar Irradiance in Italy Using WRF Solar Mesoscale Model—Preliminary Results

2020 ◽  
Vol 12 (6) ◽  
pp. 920 ◽  
Author(s):  
Sabrina Gentile ◽  
Francesco Di Paola ◽  
Domenico Cimini ◽  
Donatello Gallucci ◽  
Edoardo Geraldi ◽  
...  
Keyword(s):  
Data Assimilation ◽  
Solar Irradiance ◽  
Cloud Cover ◽  
Weather Prediction ◽  
National Research Council ◽  
Mean Bias Error ◽  
Bias Error ◽  
Clear Sky ◽  
Sky Conditions ◽  
The Impact

Solar power generation is highly fluctuating due to its dependence on atmospheric conditions. The integration of this variable resource into the energy supply system requires reliable predictions of the expected power production as a basis for management and operation strategies. This is one of the goals of the Solar Cloud project, funded by the Italian Ministry of Economic Development (MISE)—to provide detailed forecasts of solar irradiance variables to operators and organizations operating in the solar energy industry. The Institute of Methodologies for Environmental Analysis of the National Research Council (IMAA-CNR), participating to the project, implemented an operational chain that provides forecasts of all the solar irradiance variables at high temporal and horizontal resolution using the numerical weather prediction Advanced Research Weather Research and Forecasting (WRF-ARW) Solar version 3.8.1 released by the National Center for Atmospheric Research (NCAR) in August 2016. With the aim of improving the forecast of solar irradiance, the three-dimensional (3D-Var) data assimilation was tested to assimilate radiances from the Spinning Enhanced Visible and Infrared Imager (SEVIRI) aboard the Meteosat Second Generation (MSG) geostationary satellite into WRF Solar. To quantify the impact, the model output is compared against observational data. Hourly Global Horizontal Irradiance (GHI) is compared with ground-based observations from Regional Agency for the Protection of the Environment (ARPA) and with MSG Shortwave Solar Irradiance estimations, while WRF Solar cloud coverage is compared with Cloud Mask by MSG. A preliminary test has been performed in clear sky conditions to assess the capability of the model to reproduce the diurnal cycle of the solar irradiance. The statistical scores for clear sky conditions show a positive performance of the model with values comparable to the instrument uncertainty and a correlation of 0.995. For cloudy sky, the solar irradiance and the cloud cover are better simulated when the SEVIRI radiances are assimilated, especially in the short range of the simulation. For the cloud cover, the Mean Bias Error one hour after the assimilation time is reduced from 41.62 to 20.29 W/m2 when the assimilation is activated. Although only two case studies are considered here, the results indicate that the assimilation of SEVIRI radiance improves the performance of WRF Solar especially in the first 3 hour forecast.

scholarly journals Use of a Clear Sky Index to Evaluate Solar and Cloud NWP Forecasts

2021 ◽  
Author(s):  
Emily Gleeson ◽  
Kristian Pagh Nielsen
Keyword(s):  
Cloud Cover ◽  
Weather Prediction ◽  
Global Radiation ◽  
Energy Resource ◽  
Quantitative Measure ◽  
Qualitative Evaluation ◽  
Resource Assessment ◽  
Shortwave Radiation ◽  
Diffuse Fraction ◽  
Clear Sky

<p>Forecasting cloud accurately is still a challenge in numerical weather prediction (NWP) models. Detailed qualitative evaluation of such forecasts is needed in order to improve the forecasts. Cloud cover is often used for the evaluation but it is not a good metric due to inconsistency in methods for assessing the cloud cover. Global horizontal irradiance (GHI), also referred to as “global radiation”, provides an objective and quantitative measure for evaluating cloud forecasts during daytime.</p><p>Non-dimensional indices for solar energy resource assessment have been developed in recent years and decades that are very useful. One such index<br>is the clear sky index (CSI), which is the GHI divided by the theoretical GHI during clear sky conditions (e.g. [1,2]). We use the theoretical GHI clear sky model of [3,4], which includes coefficients that account for variable integrated atmospheric water vapour, aerosols and ozone. We have used binned CSI data computed using HARMONIE-AROME NWP forecast data and observations to identify model deficiencies in cloud and to evaluate new model physics options and settings. Sample results include the identification of consistent negative GHI biases under the thickest clouds and positive biases under Stratocumulus clouds. Such results help to pin-point deficiencies in the HARMONIE-AROME NWP model.</p><p><br>[1] Perez, R.; Ineichen, P.; Seals, R.; Zelenka, A. Making full use of the clearness index for parameterizing hourly insolation conditions. Sol. Energy 1990, 45, 111–114.</p><p>[2] Skartveit, A.; Olseth, J.A.; Tuft, M.E. An hourly diffuse fraction model with correction for variability and surface albedo. Sol. Energy 1998, 63, 173–183.</p><p>[3] Savijärvi, H. Fast radiation parameterization schemes for mesoscale and short-range forecast models. J. Appl. Meteorol. 1990, 437–447.</p><p>[4] Gleeson, E.; Nielsen, K.P.; Toll, V.; Rontu, L.; Whelan, E. Shortwave Radiation Experiments in HARMONIE. Tests of the cloud inhomogeneity factor and a new cloud liquid optical property scheme compared to observations. ALADIN-HIRLAM Newsl. 2015, 5, 92–106.</p>

ZABOLOTSKA T.M., SHPYG V.M., TSILA A.YU. CIRCULATION INDEXES AND THE CLOUD COVER DURING OF THE GLOBAL WARMING PERIOD

2021 ◽  
pp. 76-91
Author(s):  
T.M. Zabolotska ◽  
V.M. Shpyg ◽  
A.Yu. Tsila
Keyword(s):  
Global Warming ◽  
North Atlantic ◽  
Relative Frequency ◽  
Cloud Cover ◽  
Annual Data ◽  
East Atlantic ◽  
Clear Sky ◽  
The Difference ◽  
Monthly Variations ◽  
Overcast Sky

The investigations of connection between the different meteorological processes, for example, the circulation indexes with the quantity of the total and lower cloudiness during 1961-2018 over Ukraine were made. The spatial distributions of the total and lower cloudiness were received for 73 years (1946-2018) at first. The quantity of cloudiness is diminished from west to east and with north to south. The declinations of the annual data of total and lower cloudiness from the historical (1961-1990) and the present (1981-2010) norms were calculated. The great variations were characterized for the lower cloudiness. The linear trends showed that the diminish of the lower cloudiness was on 90 % of the all territory, this changes were important on 70 % of the territory. The trends of the monthly variations were showed on the diminish of the lower cloudiness in during all year only on north, on other territory was the increasing in the separate months, frequently in January and September. The variations of the total cloudiness were insignificant, the increase or decrease were nearly in equal parts. North Atlantic Oscillation (NAO), Arctic Oscillation (AO), East-Atlantic Oscillation (EA), Scandinavian Oscillation (SCAND), Greenlandic Oscillation (GBI) and South Oscillation (El-Niño) were used for the investigation of relationship between the circulation indexes and cloud cover. It was shown that different circulation indexes have influence on climate of Northern Hemisphere and on Ukraine too. The relation with each other and their variations in period of global warming were showed. The quantity estimation of the total and lower cloudiness variations was made by the frequencies of clear, semi clear and overcast sky in the successive decades and by the relative variations of frequencies between decades (1961-1970 and 1971-1980; 1971-1980 and 1981-1990; 1981-1990 and 1991-2000; 1991-2000 and 2001-2010; 2001-2010 and 2011-2018). The parallel analyze of the variations of circulation was estimated in that time. The difference between the circulating processes during 1961-1970 and 1971-1980 contributed to a decrease in the relative frequency of the clear sky (on 5.4%) and a slight increase of the overcast sky (on 1.6%) by total cloud cover and a slight increase of the clear sky (on 0.8 %) and a decrease of the overcast sky (on 5.2%) by lower cloudiness. At the same time, the relative frequency of the semi-clear sky by lower cloudiness almost in three times increased in comparison to total cloudiness (on 10.2% and 3.8%, respectively). In the third decade of 1981-1990 the relative frequency of clear sky by lower cloudiness increased on 5.1% and did not change by total cloudiness (0%). During this decade the relative frequency of overcast sky decreased the most in the whole period under study: by total cloudiness on 6.4% and by lower cloudiness on 13.3%. At the same time, the relative frequency of semi-clear sky had largest increasing: on 22.4% for total cloudiness and 13% for lower cloudiness. Then, during 1991-2000, the frequency of clear sky decreased significantly both for total cloudiness (on 6.5%) and for lower cloudiness (on 3.1%). The frequency of overcast sky decreased also, but less significantly (on 1.3% and 2.3%, respectively), thereby the number of clouds of the middle and upper levels increased. From 2001 to 2010, the frequency of clear sky by total cloudiness and by lower cloudiness continued to decrease (on 5.3 and 3.2%, respectively), but the frequency of overcast sky increased (on 0.9 and 1.7%, respectively), thereby the number of clouds for all levels increased. During 2011-2018 the frequency of clear sky by total cloudiness increased (on 0.9%) and by lower cloudiness did not change. The frequency of overcast sky decreased on 3.6% (by total cloudiness) and on 0.7% (by lower cloudiness). The variations of the relative frequencies of the different state sky between the successive decades are agreed with the changes of the circulation indexes.

scholarly journals Evaluation of SCIAMACHY Level-1 data versions using nadir ozone profile retrievals in the period 2003–2011

2018 ◽  
Vol 11 (4) ◽  
pp. 2345-2360 ◽  
Author(s):  
Sweta Shah ◽  
Olaf N. E. Tuinder ◽  
Jacob C. A. van Peet ◽  
Adrianus T. J. de Laat ◽  
Piet Stammes
Keyword(s):  
Pressure Range ◽  
Stratospheric Ozone ◽  
Spectral Shift ◽  
Retrieval Algorithm ◽  
Visible Range ◽  
L1 Data ◽  
Ozone Profile ◽  
Level 1 ◽  
Scanning Imaging ◽  
Radiance Data

Abstract. Ozone profile retrieval from nadir-viewing satellite instruments operating in the ultraviolet–visible range requires accurate calibration of Level-1 (L1) radiance data. Here we study the effects of calibration on the derived Level-2 (L2) ozone profiles for three versions of SCanning Imaging Absorption spectroMeter for Atmospheric ChartograpHY (SCIAMACHY) L1 data: version 7 (v7), version 7 with m-factors (v7mfac) and version 8 (v8). We retrieve nadir ozone profiles from the SCIAMACHY instrument that flew on board Envisat using the Ozone ProfilE Retrieval Algorithm (OPERA) developed at KNMI with a focus on stratospheric ozone. We study and assess the quality of these profiles and compare retrieved L2 products from L1 SCIAMACHY data versions from the years 2003 to 2011 without further radiometric correction. From validation of the profiles against ozone sonde measurements, we find that the v8 performs better than v7 and v7mfac due to correction for the scan-angle dependency of the instrument's optical degradation. Validation for the years 2003 and 2009 with ozone sondes shows deviations of SCIAMACHY ozone profiles of 0.8–15 % in the stratosphere (corresponding to pressure range ∼ 100–10 hPa) and 2.5–100 % in the troposphere (corresponding to pressure range ∼ 1000–100 hPa), depending on the latitude and the L1 version used. Using L1 v8 for the years 2003–2011 leads to deviations of ∼ 1–11 % in stratospheric ozone and ∼ 1–45 % in tropospheric ozone. The SCIAMACHY L1 v8 data can still be improved upon in the 265–330 nm range used for ozone profile retrieval. The slit function can be improved with a spectral shift and squeeze, which leads to a few percent residue reduction compared to reference solar irradiance spectra. Furthermore, studies of the ratio of measured to simulated reflectance spectra show that a bias correction in the reflectance for wavelengths below 300 nm appears to be necessary.

scholarly journals ARPEGE cloud cover forecast post-processing with convolutional neural network

2020 ◽  
Author(s):  
Florian Dupuy ◽  
Olivier Mestre ◽  
Léo Pfitzner
Keyword(s):  
Neural Network ◽  
Machine Learning ◽  
Convolutional Neural Network ◽  
Random Forests ◽  
Cloud Cover ◽  
Spatial Information ◽  
Weather Prediction ◽  
Excellent Result ◽  
Machine Learning Algorithms ◽  
Post Processing

<p>Cloud cover is a crucial information for many applications such as planning land observation missions from space. However, cloud cover remains a challenging variable to forecast, and Numerical Weather Prediction (NWP) models suffer from significant biases, hence justifying the use of statistical post-processing techniques. In our application, the ground truth is a gridded cloud cover product derived from satellite observations over Europe, and predictors are spatial fields of various variables produced by ARPEGE (Météo-France global NWP) at the corresponding lead time.</p><p>In this study, ARPEGE cloud cover is post-processed using a convolutional neural network (CNN). CNN is the most popular machine learning tool to deal with images. In our case, CNN allows to integrate spatial information contained in NWP outputs. We show that a simple U-Net architecture produces significant improvements over Europe. Compared to the raw ARPEGE forecasts, MAE drops from 25.1 % to 17.8 % and RMSE decreases from 37.0 % to 31.6 %. Considering specific needs for earth observation, special interest was put on forecasts with low cloud cover conditions (< 10 %). For this particular nebulosity class, we show that hit rate jumps from 40.6 to 70.7 (which is the order of magnitude of what can be achieved using classical machine learning algorithms such as random forests) while false alarm decreases from 38.2 to 29.9. This is an excellent result, since improving hit rates by means of random forests usually also results in a slight increase of false alarms.</p>

scholarly journals Water vapour foreign-continuum absorption in near-infrared windows from laboratory measurements

2012 ◽  
Vol 370 (1968) ◽  
pp. 2557-2577 ◽  
Author(s):  
Igor V. Ptashnik ◽  
Robert A. McPheat ◽  
Keith P. Shine ◽  
Kevin M. Smith ◽  
R. Gary Williams
Keyword(s):  
Water Vapour ◽  
Near Infrared ◽  
Prediction Models ◽  
Weather Prediction ◽  
Pair Interaction ◽  
Atmospheric Conditions ◽  
Laboratory Measurements ◽  
Atmospheric Absorption ◽  
Clear Sky ◽  
Long Time

For a long time, it has been believed that atmospheric absorption of radiation within wavelength regions of relatively high infrared transmittance (so-called ‘windows’) was dominated by the water vapour self-continuum, that is, spectrally smooth absorption caused by H 2 O−H 2 O pair interaction. Absorption due to the foreign continuum (i.e. caused mostly by H 2 O−N 2 bimolecular absorption in the Earth's atmosphere) was considered to be negligible in the windows. We report new retrievals of the water vapour foreign continuum from high-resolution laboratory measurements at temperatures between 350 and 430 K in four near-infrared windows between 1.1 and 5 μm (9000–2000 cm −1 ). Our results indicate that the foreign continuum in these windows has a very weak temperature dependence and is typically between one and two orders of magnitude stronger than that given in representations of the continuum currently used in many climate and weather prediction models. This indicates that absorption owing to the foreign continuum may be comparable to the self-continuum under atmospheric conditions in the investigated windows. The calculated global-average clear-sky atmospheric absorption of solar radiation is increased by approximately 0.46 W m −2 (or 0.6% of the total clear-sky absorption) by using these new measurements when compared with calculations applying the widely used MTCKD (Mlawer–Tobin–Clough–Kneizys–Davies) foreign-continuum model.

scholarly journals Climatological Features of the Weakly and Very Stably Stratified Nocturnal Boundary Layers. Part II: Regime Occupation and Transition Statistics and the Influence of External Drivers

2019 ◽  
Vol 76 (11) ◽  
pp. 3485-3504 ◽  
Author(s):  
Carsten Abraham ◽  
Adam H. Monahan
Keyword(s):  
Complex Terrain ◽  
Cloud Cover ◽  
Companion Paper ◽  
Statistical Features ◽  
Clear Sky ◽  
Cloud Coverage ◽  
Weakly Stable ◽  
Sky Conditions ◽  
Regime Transitions

Abstract In a companion paper hidden Markov model (HMM) analyses have been conducted to classify the nocturnal stably stratified boundary layer (SBL) into weakly stable (wSBL) and very stable (vSBL) conditions at different tower sites on the basis of long-term Reynolds-averaged mean data. The resulting HMM regime sequences allow analysis of long-term (climatological) SBL regime statistics. In particular, statistical features of very persistent wSBL and vSBL nights, in which a single regime lasts for the entire night, are contrasted with those of nights with SBL regime transitions. The occurrence of very persistent nights is seasonally dependent and more likely in homogeneous surroundings than in regions with complex terrain. When transitions occur, their timing is not seasonally dependent, but transitions are enhanced close to sunset (for land-based sites). The regime event durations depict remarkably similar distributions across all stations with peaks in transition likelihood approximately 1–2 h after a preceding transition. At Cabauw in the Netherlands, very persistent wSBL and vSBL nights are usually accompanied by overcast conditions with strong geostrophic winds Ugeo or clear-sky conditions with weak Ugeo, respectively. In contrast, SBL regime transitions can neither be linked to magnitudes in Ugeo and cloud coverage nor to specific tendencies in Ugeo. However, regime transitions can be initiated by changes in low-level cloud cover.

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