Optimizing UV index determination from broadband irradiances

Abstract. Amidst mounting concerns about the depletion of stratospheric ozone (O3), and for subsequent increases in the surface irradiances of ultraviolet (UV) light and its effects on human health, a daily UV forecast program was launched by Environment Canada in 1993. The program serves to monitor harmful surface UV radiation and provide this information to the Canadian public through the UV index, a scale which reports the relative intensity of the Sun's UV radiation at the Earth's surface, and the corresponding protection actions to be taken. The UV index was accepted as a standard method of reporting surface UV irradiances by the World Meteorological Organization (WMO) and World Health Organization (WHO) in 1994. A study was undertaken to improve upon the prognosticative capability of Environment and Climate Change Canada's (ECCC) UV index forecast model. An aspect of that work, and the topic of this communication, was to investigate the use of the four UV broadband surface irradiance fields generated by ECCC's Global Environmental Multi-scale (GEM) numerical prediction model to determine the UV index. The basis of the investigation involves the creation of a suite of routines which employ high spectral resolution radiative transfer code developed to calculate UV index fields from GEM forecasts. These routines employ a modified version of the Cloud-J v7.4 radiative transfer model, which integrates GEM output to produce high spectral resolution surface irradiance fields. The output generated using the high-resolution radiative transfer code served to verify and calibrate GEM broadband surface irradiances under clear-sky conditions and their use in providing the UV index. A subsequent comparison of irradiances and UV index under cloudy conditions was also performed. Linear correlation agreement of surface irradiances from the two models for each of the two higher UV bands covering 310–330 nm and 330–400 nm is typically greater than 95 % for clear-sky conditions with associated root mean square relative errors of 5.5 % and 3.8 %. On the other hand, underestimations of clear-sky GEM irradiances were found on the order of ~30–50 % for the 294–310 nm band and by a factor of ~30 for the 280–294 nm band. This underestimation can be significant for UV index determination but would not impact weather forecasting. Corresponding empirical adjustments were applied to the broadband irradiances now giving a correlation coefficient of unity. From these, a least-squares fitting was derived for the calculation of the UV index. The resultant differences in UV indices from the high spectral resolution irradiances and the resultant GEM broadband irradiances are typically within 0.2 with a root mean square relative error in the scatter of ~5.5 % for clear-sky conditions. Similar results are reproduced under cloudy conditions with light to moderate clouds, having a relative error comparable to the clear-sky counterpart; under strong attenuation due to clouds, a substantial increase in the root mean square relative error of up to 30 % is observed due to differing cloud radiative transfer models.

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Optimizing UV Index determination from broadband irradiances

Geoscientific Model Development ◽

10.5194/gmd-11-1093-2018 ◽

2018 ◽

Vol 11 (3) ◽

pp. 1093-1113 ◽

Cited By ~ 2

Author(s):

Keith A. Tereszchuk ◽

Yves J. Rochon ◽

Chris A. McLinden ◽

Paul A. Vaillancourt

Keyword(s):

Radiative Transfer ◽

Root Mean Square ◽

Relative Error ◽

Spectral Resolution ◽

High Spectral Resolution ◽

Mean Square ◽

Uv Index ◽

Clear Sky ◽

Surface Irradiance ◽

Sky Conditions

Abstract. A study was undertaken to improve upon the prognosticative capability of Environment and Climate Change Canada's (ECCC) UV Index forecast model. An aspect of that work, and the topic of this communication, was to investigate the use of the four UV broadband surface irradiance fields generated by ECCC's Global Environmental Multiscale (GEM) numerical prediction model to determine the UV Index. The basis of the investigation involves the creation of a suite of routines which employ high-spectral-resolution radiative transfer code developed to calculate UV Index fields from GEM forecasts. These routines employ a modified version of the Cloud-J v7.4 radiative transfer model, which integrates GEM output to produce high-spectral-resolution surface irradiance fields. The output generated using the high-resolution radiative transfer code served to verify and calibrate GEM broadband surface irradiances under clear-sky conditions and their use in providing the UV Index. A subsequent comparison of irradiances and UV Index under cloudy conditions was also performed. Linear correlation agreement of surface irradiances from the two models for each of the two higher UV bands covering 310.70–330.0 and 330.03–400.00 nm is typically greater than 95 % for clear-sky conditions with associated root-mean-square relative errors of 6.4 and 4.0 %. However, underestimations of clear-sky GEM irradiances were found on the order of ∼ 30–50 % for the 294.12–310.70 nm band and by a factor of ∼ 30 for the 280.11–294.12 nm band. This underestimation can be significant for UV Index determination but would not impact weather forecasting. Corresponding empirical adjustments were applied to the broadband irradiances now giving a correlation coefficient of unity. From these, a least-squares fitting was derived for the calculation of the UV Index. The resultant differences in UV indices from the high-spectral-resolution irradiances and the resultant GEM broadband irradiances are typically within 0.2–0.3 with a root-mean-square relative error in the scatter of ∼ 6.6 % for clear-sky conditions. Similar results are reproduced under cloudy conditions with light to moderate clouds, with a relative error comparable to the clear-sky counterpart; under strong attenuation due to clouds, a substantial increase in the root-mean-square relative error of up to 35 % is observed due to differing cloud radiative transfer models.

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Estimation of Daylight Downward Longwave Atmospheric Irradiance under Clear-Sky and All-Sky Conditions

Journal of Applied Meteorology and Climatology ◽

10.1175/jam2503.1 ◽

2007 ◽

Vol 46 (6) ◽

pp. 878-889 ◽

Cited By ~ 30

Author(s):

Julia Bilbao ◽

Argimiro H. de Miguel

Keyword(s):

Linear Regression ◽

Root Mean Square ◽

Mean Square ◽

Clear Sky ◽

Parameterization Schemes ◽

Irradiance Data ◽

Sky Conditions ◽

Mean Square Errors

Abstract Daylight downward longwave irradiance data recorded over a flat place for the period between April 2001 and December 2004 in Valladolid, Spain, have been compared with estimates generated using four different schemes. The parameterization schemes of Brutsaert, Swinbank, Idso, and Brunt have been considered and calibrated for the comparison. Root-mean-square errors (rmse), mean bias errors, and linear regression correlations have been used to compare measured and estimated values. The results of this comparison show that, for clear-sky conditions, rmse values range between 19.57 and 8.85 W m−2 for calibrated schemes and between 39.78 and 11.13 W m−2 for original ones. The Idso and Brunt schemes give the best results with calibrated coefficients, and the Brunt scheme performs the best with original coefficients. A new scheme for estimating daylight downward longwave irradiance under “all-sky” conditions has been developed based on clear-sky schemes and solar global shortwave irradiance, and, after comparing measured and estimated values by calibrated schemes, it has been found that the Idso and Brunt schemes give the best results.

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Minimum Local Emissivity Variance Retrieval of Cloud Altitude and Effective Spectral Emissivity—Simulation and Initial Verification

Journal of Applied Meteorology ◽

10.1175/2090.1 ◽

2004 ◽

Vol 43 (5) ◽

pp. 795-809 ◽

Cited By ~ 23

Author(s):

Hung-Lung Huang ◽

William L. Smith ◽

Jun Li ◽

Paolo Antonelli ◽

Xiangqian Wu ◽

...

Keyword(s):

Root Mean Square ◽

Spectral Resolution ◽

Single Layer ◽

Spectral Emissivity ◽

Pressure Level ◽

High Spectral Resolution ◽

Mean Square ◽

Atmospheric Conditions ◽

Wide Range ◽

Mean Square Errors

Abstract This paper describes the theory and application of the minimum local emissivity variance (MLEV) technique for simultaneous retrieval of cloud pressure level and effective spectral emissivity from high-spectral-resolution radiances, for the case of single-layer clouds. This technique, which has become feasible only with the recent development of high-spectral-resolution satellite and airborne instruments, is shown to provide reliable cloud spectral emissivity and pressure level under a wide range of atmospheric conditions. The MLEV algorithm uses a physical approach in which the local variances of spectral cloud emissivity are calculated for a number of assumed or first-guess cloud pressure levels. The optimal solution for the single-layer cloud emissivity spectrum is that having the “minimum local emissivity variance” among the retrieved emissivity spectra associated with different first-guess cloud pressure levels. This is due to the fact that the absorption, reflection, and scattering processes of clouds exhibit relatively limited localized spectral emissivity structure in the infrared 10–15-μm longwave region. In this simulation study it is shown that the MLEV cloud pressure root-mean-square errors for a single level with effective cloud emissivity greater than 0.1 are ∼30, ∼10, and ∼50 hPa, for high (200– 300 hPa), middle (500 hPa), and low (850 hPa) clouds, respectively. The associated cloud emissivity root-mean-square errors in the 900 cm−1 spectral channel are less than 0.05, 0.04, and 0.25 for high, middle, and low clouds, respectively.

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Aerosol Layering in the Free Troposphere over the Industrial City of Raciborz in Southwest Poland and Its Influence on Surface UV Radiation

Atmosphere ◽

10.3390/atmos12070812 ◽

2021 ◽

Vol 12 (7) ◽

pp. 812

Author(s):

Alnilam Fernandes ◽

Aleksander Pietruczuk ◽

Artur Szkop ◽

Janusz Krzyścin

Keyword(s):

Radiative Transfer ◽

Uv Radiation ◽

Hybrid Model ◽

Radiative Transfer Model ◽

Asymmetry Factor ◽

Transfer Model ◽

Free Troposphere ◽

Clear Sky ◽

Sky Conditions ◽

The Impact

Atmospheric aerosol and ultraviolet index (UVI) measurements performed in Racibórz (50.08° N, 18.19° E) were analyzed for the period June–September 2019. Results of the following observations were taken into account: columnar characteristics of the aerosols (aerosol thickness, Angstrom exponent, single scattering albedo, asymmetry factor) obtained from standard CIMEL sun-photometer observations and parameters of aerosol layers (ALs) in the free troposphere (the number of layers and altitudes of the base and top) derived from continuous monitoring by a CHM-15k ceilometer. Three categories of ALs were defined: residues from the daily evolution of the planetary boundary layer (PBL) aerosols, from the PBL-adjacent layer, and from the elevated layer above the PBL. Total column ozone measurements taken by the Ozone-Monitoring Instrument on board NASA’s Aura satellite completed the list of variables used to model UVI variability under clear-sky conditions. The aim was to present a hybrid model (radiative transfer model combined with a regression model) for determining ALs’ impact on the observed UVI series. First, a radiative transfer model, the Tropospheric Ultraviolet–Visible (TUV) model, which uses typical columnar characteristics to describe UV attenuation in the atmosphere, was applied to calculate hypothetical surface UVI values under clear-sky conditions. These modeled values were used to normalize the measured UVI data obtained during cloudless conditions. Next, a regression of the normalized UVI values was made using the AL characteristics. Random forest (RF) regression was chosen to search for an AL signal in the measured data. This explained about 55% of the variance in the normalized UVI series under clear-sky conditions. Finally, the UVI values were calculated as the product of the RF regression and the relevant UVIs by the columnar TUV model. The root mean square error and mean absolute error of the hybrid model were 1.86% and 1.25%, respectively, about 1 percentage point lower than corresponding values derived from the columnar TUV model. The 5th–95th percentile ranges of the observation/model differences were [−2.5%, 2.8%] and [−3.0%, 5.3%] for the hybrid model and columnar TUV model, respectively. Therefore, the impact of ALs on measured surface UV radiation could be demonstrated using the proposed AL characteristics. The statistical analysis of the UVI differences between the models allowed us to identify specific AL configuration responsible for these differences.

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A fractional order epidemic model for the simulation of outbreaks of Ebola

Advances in Difference Equations ◽

10.1186/s13662-021-03272-5 ◽

2021 ◽

Vol 2021 (1) ◽

Author(s):

Weiqiu Pan ◽

Tianzeng Li ◽

Safdar Ali

Keyword(s):

Numerical Solution ◽

Root Mean Square ◽

Fractional Order ◽

Relative Error ◽

Numerical Solutions ◽

Real Data ◽

Mean Square ◽

Order Model ◽

The Real ◽

Fractional Orders

AbstractThe Ebola outbreak in 2014 caused many infections and deaths. Some literature works have proposed some models to study Ebola virus, such as SIR, SIS, SEIR, etc. It is proved that the fractional order model can describe epidemic dynamics better than the integer order model. In this paper, we propose a fractional order Ebola system and analyze the nonnegative solution, the basic reproduction number $R_{0}$ R 0 , and the stabilities of equilibrium points for the system firstly. In many studies, the numerical solutions of some models cannot fit very well with the real data. Thus, to show the dynamics of the Ebola epidemic, the Gorenflo–Mainardi–Moretti–Paradisi scheme (GMMP) is taken to get the numerical solution of the SEIR fractional order Ebola system and the modified grid approximation method (MGAM) is used to acquire the parameters of the SEIR fractional order Ebola system. We consider that the GMMP method may lead to absurd numerical solutions, so its stability and convergence are given. Then, the new fractional orders, parameters, and the root-mean-square relative error $g(U^{*})=0.4146$ g ( U ∗ ) = 0.4146 are obtained. With the new fractional orders and parameters, the numerical solution of the SEIR fractional order Ebola system is closer to the real data than those models in other literature works. Meanwhile, we find that most of the fractional order Ebola systems have the same order. Hence, the fractional order Ebola system with different orders using the Caputo derivatives is also studied. We also adopt the MGAM algorithm to obtain the new orders, parameters, and the root-mean-square relative error which is $g(U^{*})=0.2744$ g ( U ∗ ) = 0.2744 . With the new parameters and orders, the fractional order Ebola systems with different orders fit very well with the real data.

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Possible values of UV index in Serbia

Srpski arhiv za celokupno lekarstvo ◽

10.2298/sarh0812640l ◽

2008 ◽

Vol 136 (11-12) ◽

pp. 640-643 ◽

Cited By ~ 1

Author(s):

Milorad Letic

Keyword(s):

Uv Radiation ◽

The Sun ◽

Total Column Ozone ◽

Uv Index ◽

Clear Sky ◽

Expected Values ◽

June July ◽

Column Ozone ◽

Ozone Column

INTRODUCTION UV Index is an indicator of human exposure to solar ultraviolet (UV) rays. The numerical values of the UV Index range from 1-11 and above. There are three levels of protection against UV radiation; low values of the UV Index - protection is not required, medium values of the UV Index - protection is recommended and high values of the UV Index - protection is obligatory. The value of the UV Index primarily depends on the elevation of the sun and total ozone column. OBJECTIVE The aim of the study is to determine the intervals of possible maximal annual values of the UV Index in Serbia in order to determine the necessary level of protection in a simple manner. METHOD For maximal and minimal expected values of total column ozone and for maximal elevation of the sun, the value of the UV Index was determined for each month in the Northern and Southern parts of Serbia. These values were compared with the forecast of the UV Index. RESULTS Maximal clear sky values of the UV Index in Serbia for altitudes up to 500m in May, June, July and August can be 9 or even 10, and not less than 5 or 6. During November, December, January and February the UV Index can be 4 at most. During March, April, September and October the expected values of the UV Index are maximally 7 and not less than 3. The forecast of the UV Index is within these limits in 98% of comparisons. CONCLUSION The described method of determination of possible UV Index values showed a high agreement with forecasts. The obtained results can be used for general recommendations in the protection against UV radiation.

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UV Index Forecasting under the Influence of Desert Dust: Evaluation against Surface and Satellite-Retrieved Data

Atmosphere ◽

10.3390/atmos11010096 ◽

2020 ◽

Vol 11 (1) ◽

pp. 96 ◽

Cited By ~ 1

Author(s):

Dillan Raymond Roshan ◽

Muammer Koc ◽

Amir Abdallah ◽

Luis Martin-Pomares ◽

Rima Isaifan ◽

...

Keyword(s):

Uv Radiation ◽

Mesoscale Model ◽

Dust Storms ◽

Average Error ◽

Accurate Estimation ◽

Strong Impact ◽

Uv Index ◽

Desert Dust ◽

Clear Sky ◽

Uv Irradiance

Human exposure to healthy doses of UV radiation is required for vitamin D synthesis, but exposure to excessive UV irradiance leads to several harmful impacts ranging from premature wrinkles to dangerous skin cancer. However, for countries located in the global dust belt, accurate estimation of the UV irradiance is challenging due to a strong impact of desert dust on incoming solar radiation. In this work, a UV Index forecasting capability is presented, specifically developed for dust-rich environments, that combines the use of ground-based measurements of broadband irradiances UVA (320–400 nm) and UVB (280–315 nm), NASA OMI Aura satellite-retrieved data and the meteorology-chemistry mesoscale model WRF-Chem. The forecasting ability of the model is evaluated for clear sky days as well as during the influence of dust storms in Doha, Qatar. The contribution of UV radiation to the total incoming global horizontal irradiance (GHI) ranges between 5% and 7% for UVA and 0.1% and 0.22% for UVB. The UVI forecasting performance of the model is quite encouraging with an absolute average error of less than 6% and a correlation coefficient of 0.93. In agreement with observations, the model predicts that the UV Index at local noontime can drop from 10–11 on clear sky days to approximately 6–7 during typical dusty conditions in the Arabian Peninsula—an effect similar to the presence of extensive cloud cover.

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High-resolution satellite-based cloud-coupled estimates of total downwelling surface radiation for hydrologic modelling applications

Hydrology and Earth System Sciences ◽

10.5194/hess-13-969-2009 ◽

2009 ◽

Vol 13 (7) ◽

pp. 969-986 ◽

Cited By ~ 25

Author(s):

B. A. Forman ◽

S. A. Margulis

Keyword(s):

High Resolution ◽

Root Mean Square ◽

Mean Difference ◽

Lookup Table ◽

Root Mean Square Difference ◽

Mean Square ◽

Radiation Model ◽

Radiative Fluxes ◽

Mean Square Difference ◽

Sky Conditions

Abstract. A relatively simple satellite-based radiation model yielding high-resolution (in space and time) downwelling longwave and shortwave radiative fluxes at the Earth's surface is presented. The primary aim of the approach is to provide a basis for deriving physically consistent forcing fields for distributed hydrologic models using satellite-based remote sensing data. The physically-based downwelling radiation model utilises satellite inputs from both geostationary and polar-orbiting platforms and requires only satellite-based inputs except that of a climatological lookup table derived from a regional climate model. Comparison against ground-based measurements over a 14-month simulation period in the Southern Great Plains of the United States demonstrates the ability to reproduce radiative fluxes at a spatial resolution of 4 km and a temporal resolution of 1 h with good accuracy during all-sky conditions. For hourly fluxes, a mean difference of −2 W m−2 with a root mean square difference of 21 W m−2 was found for the longwave fluxes whereas a mean difference of −7 W m−2 with a root mean square difference of 29 W m−2 was found for the shortwave fluxes. Additionally, comparison against advanced downwelling longwave and solar insolation products during all-sky conditions showed comparable uncertainty in the longwave estimates and reduced uncertainty in the shortwave estimates. The relatively simple form of the model enables future usage in ensemble-based applications including data assimilation frameworks in order to explicitly account for input uncertainties while providing the potential for conditioning estimates from other readily available products derived from more sophisticated retrieval algorithms.

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Measurements of UV irradiance within the area of one satellite pixel

Atmospheric Chemistry and Physics ◽

10.5194/acp-8-5615-2008 ◽

2008 ◽

Vol 8 (18) ◽

pp. 5615-5626 ◽

Cited By ~ 40

Author(s):

P. Weihs ◽

M. Blumthaler ◽

H. E. Rieder ◽

A. Kreuter ◽

S. Simic ◽

...

Keyword(s):

Ozone Monitoring Instrument ◽

Short Term ◽

Uv Index ◽

Clear Sky ◽

Uv Irradiance ◽

Instantaneous Values ◽

The Mean ◽

The Difference ◽

Sky Conditions ◽

Better Than

Abstract. A measurement campaign was performed in the region of Vienna and its surroundings from May to July 2007. Within the scope of this campaign erythemal UV was measured at six ground stations within a radius of 30 km. First, the homogeneity of the UV levels within the area of one satellite pixel was studied. Second, the ground UV was compared to ground UV retrieved by the ozone monitoring instrument (OMI) onboard the NASA EOS Aura Spacecraft. During clear-sky conditions the mean bias between erythemal UV measured by the different stations was within the measurement uncertainty of ±5%. Short term fluctuations of UV between the stations were below 3% within a radius of 20 km. For partly cloudy conditions and overcast conditions the discrepancy of instantaneous values between the stations is up to 200% or even higher. If averages of the UV index over longer time periods are compared the difference between the stations decreases strongly. The agreement is better than 20% within a distance of 10 km between the stations for 3 h averages. The comparison with OMI UV showed for clear-sky conditions higher satellite retrieved UV values by, on the average, approximately 15%. The ratio of OMI to ground measured UV lies between 0.9 and 1.5. and strongly depends on the aerosol optical depth. For partly cloudy and overcast conditions the OMI derived surface UV estimates show larger deviation from the ground-based reference data, and even bigger systematic positive bias. Here the ratio OMI to ground data lies between 0.5 and 4.5. The average difference between OMI and ground measurements is +24 to +37% for partly cloudy conditions and more than +50% for overcast conditions.

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Retrieval of Ice Cloud Properties from AIRS and MODIS Observations Based on a Fast High-Spectral-Resolution Radiative Transfer Model

Journal of Applied Meteorology and Climatology ◽

10.1175/jamc-d-12-020.1 ◽

2013 ◽

Vol 52 (3) ◽

pp. 710-726 ◽

Cited By ~ 23

Author(s):

Chenxi Wang ◽

Ping Yang ◽

Steven Platnick ◽

Andrew K. Heidinger ◽

Bryan A. Baum ◽

...

Keyword(s):

Radiative Transfer ◽

Spectral Resolution ◽

Spectral Response ◽

Thermal Infrared ◽

High Spectral Resolution ◽

Radiative Transfer Model ◽

Transfer Model ◽

Retrieval Method ◽

Ice Cloud ◽

Cloud Properties

AbstractA computationally efficient high-spectral-resolution cloudy-sky radiative transfer model (HRTM) in the thermal infrared region (700–1300 cm−1, 0.1 cm−1 spectral resolution) is advanced for simulating the upwelling radiance at the top of atmosphere and for retrieving cloud properties. A precomputed transmittance database is generated for simulating the absorption contributed by up to seven major atmospheric absorptive gases (H2O, CO2, O3, O2, CH4, CO, and N2O) by using a rigorous line-by-line radiative transfer model (LBLRTM). Both the line absorption of individual gases and continuum absorption are included in the database. A high-spectral-resolution ice particle bulk scattering properties database is employed to simulate the radiation transfer within a vertically nonisothermal ice cloud layer. Inherent to HRTM are sensor spectral response functions that couple with high-spectral-resolution measurements in the thermal infrared regions from instruments such as the Atmospheric Infrared Sounder (AIRS) and Infrared Atmospheric Sounding Interferometer. When compared with the LBLRTM and the discrete ordinates radiative transfer model (DISORT), the root-mean-square error of HRTM-simulated single-layer cloud brightness temperatures in the thermal infrared window region is generally smaller than 0.2 K. An ice cloud optical property retrieval scheme is developed using collocated AIRS and Moderate Resolution Imaging Spectroradiometer (MODIS) data. A retrieval method is proposed to take advantage of the high-spectral-resolution instrument. On the basis of the forward model and retrieval method, a case study is presented for the simultaneous retrieval of ice cloud optical thickness τ and effective particle size Deff that includes a cloud-top-altitude self-adjustment approach to improve consistency with simulations.

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