Statistical description of UV climate and climatological maps Second EDUCE Meeting, Bordeaux 2001 H. Slaper and P.N. den Outer.

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Presentation transcript:

Statistical description of UV climate and climatological maps Second EDUCE Meeting, Bordeaux 2001 H. Slaper and P.N. den Outer

UV climatology: u Retrieve and analyse large amounts of data, spectral and pyranometer data. Sets requirements on format (data format, cosine correction,….) u Construction of integrated properties: daily, monthly, annual dosesV-dat How to deal with data gaps? u Models required since UV-data exist for limited periods only Validation of models (ground-based and satellite-based) u QA/QC-tools on irradiance scale errors

DATA SUPPLEMENTATION Data gaps supplemented with: RB-measurements fractional: Test: 35 days interchanged 1. randomly 2. in a row Data used: 1998, skin cancer weighted RIVM, Bilthoven, The Netherlands RB cal.:  RB =  spectroradiometer

MonthsRandom Average: UV supp /UV meas s.d. RB-supp Fractional

UV-transfer model UV-reduction algorithm 1. Global Solar Irradiation, pyranometers, WRDC 2. TOMS Reflection 3. ISCCP (ρ, τ CLD ) Ozone SZA Standard atmosphere Cloudless sky UV Cloudy sky UV Extra terrestrial UV

UV v.s. Global Solar Irradiation:

Trends: 5±1%/decade, cloudless 6±2%/decade, cloudy sky Standard deviations in yearly sums 1.00 ± 0.01, cloudless 0.98 ± 0.03, cloudy sky Monthly doses Yearly doses

CORRELEATION WITH GROUND-BASED DATA ISCCP, and TOMS versus GDF Belgium + Southern Netherlands correlation

Cloudless sky Cloudy sky Percent change

Cloudless skyCloudy sky

UV v.s. Global Solar Irradiation:

UVB nm UVA nm Individual measurements Dialy sums Global Irradiation UVB nm, summer data Clear sky model Direct related SZA-dependent

Results QA/QC-absolute irradiance Gaussian fit95% conf.sd All UVA summer UVA All UVB summer UVB Check threshold UVA: 20% UVB:35% Thresholds apply to all weather conditions

Conclusions 1) data gaps can be eliminated without introducing much uncertainty: 10% loss of data adds 0.5% uncertainty 2) Use of pyranometer and ozone data is good approach to model UV. The approach yields good correlation with satellite data based models next step: validation at other locations using DB 3) Agreement of model with measurements allows for irradiance checks on the 20% level