Validation of the TROPOspheric Monitoring Instrument (TROPOMI) surface UV radiation product

The TROPOspheric Monitoring Instrument (TROPOMI) onboard the Sentinel-5 Precursor (S5P) satellite was launched on 13 October 2017 to provide the atmospheric composition for atmosphere and climate research. The S5P is a Sun-synchronous polar-orbiting satellite providing global daily coverage. The TROPOMI swath is 2600 km wide, and the ground resolution for most data products is 7:23:5 km2 (5:63:5 km2 since 6 August 2019) at nadir. The Finnish Meteorological Institute (FMI) is responsible for the development of the TROPOMI UV algorithm and the processing of the TROPOMI surface ultraviolet (UV) radiation product which includes 36 UV parameters in total. Ground-based data from 25 sites located in arctic, subarctic, temperate, equatorial and Antarctic areas were used for validation of the TROPOMI overpass irradiance at 305, 310, 324 and 380 nm, overpass erythemally weighted dose rate/UV index, and erythemally weighted daily dose for the period from 1 January 2018 to 31 August 2019. The validation results showed that for most sites 60 % 80% of TROPOMI data was within 20% of ground-based data for snow-free surface conditions. The median relative differences to ground-based measurements of TROPOMI snow-free surface daily doses were within 10% and 5% at two-Thirds and at half of the sites, respectively. At several sites more than 90% of cloud-free TROPOMI data was within 20% of groundbased measurements. Generally median relative differences between TROPOMI data and ground-based measurements were a little biased towards negative values (i.e. satellite data ground-based measurement), but at high latitudes where non-homogeneous topography and albedo or snow conditions occurred, the negative bias was exceptionally high: from 30% to 65 %. Positive biases of 10 % 15% were also found for mountainous sites due to challenging topography. The TROPOMI surface UV radiation product includes quality flags to detect increased uncertainties in the data due to heterogeneous surface albedo and rough terrain, which can be used to filter the data retrieved under challenging conditions

Validation of ozone measurements from the Atmospheric Chemistry Experiment (ACE)

This paper presents extensive bias determination analyses of ozone observations from the Atmospheric Chemistry Experiment (ACE) satellite instruments: the ACE Fourier Transform Spectrometer (ACE-FTS) and the Measurement of Aerosol Extinction in the Stratosphere and Troposphere Retrieved by Occultation (ACE-MAESTRO) instrument. Here we compare the latest ozone data products from ACE-FTS and ACE-MAESTRO with coincident observations from nearly 20 satellite-borne, airborne, balloon-borne and ground-based instruments, by analysing volume mixing ratio profiles and partial column densities. The ACE-FTS version 2.2 Ozone Update product reports more ozone than most correlative measurements from the upper troposphere to the lower mesosphere. At altitude levels from 16 to 44 km, the average values of the mean relative differences are nearly all within +1 to +8%. At higher altitudes (45 60 km), the ACE-FTS ozone amounts are significantly larger than those of the comparison instruments, with mean relative differences of up to +40% (about + 20% on average). For the ACE-MAESTRO version 1.2 ozone data product, mean relative differences are within +/- 10% (average values within +/- 6%) between 18 and 40 km for both the sunrise and sunset measurements. At higher altitudes (similar to 35-55 km), systematic biases of opposite sign are found between the ACE-MAESTRO sunrise and sunset observations. While ozone amounts derived from the ACE-MAESTRO sunrise occultation data are often smaller than the coincident observations (with mean relative differences down to -10%), the sunset occultation profiles for ACE-MAESTRO show results that are qualitatively similar to ACE-FTS, indicating a large positive bias (mean relative differences within +10 to +30%) in the 45-55 km altitude range. In contrast, there is no significant systematic difference in bias found for the ACE-FTS sunrise and sunset measurements

A map of the top-soil organic carbon content of Europe generated by a generalized additive model

There is an increasing demand for up-to-date soil organic carbon (OC) data for global environmental and climatic modelling. The aim of this study was to create a map of topsoil OC content at the European scale AQ4 by applying digital soil mapping techniques to the first European harmonized geo-referenced topsoil (0–20 cm) database, which arises from the Land use/Cover Area Frame statistical Survey (LUCAS). A map of the associated uncertainty was also produced to support careful use of the predicted OC contents. A generalized additive model (GAM) was fitted on 85% of the dataset (R2 =0.29), using OC content as dependent variable; a backward stepwise approach selected slope, land cover, temperature, net primary productivity, latitude and longitude as suitable covariates. The validation of the model (performed on 15% of the data-set) gave an overall R2 of 0.27 and an R2 of 0.21 for mineral soils and 0.06 for organic soils. Organic C content in most organic soils was under-predicted, probably because of the imposed unimodal distribution of our model, whose mean is tilted towards the prevalent mineral soils. This was also confirmed by the poor prediction in Scandinavia (where organic soils are more frequent), which gave an R2 of 0.09, whilst the prediction performance (R2) in non-Scandinavian countries was 0.28. The map of predicted OC content had the smallest values in Mediterranean countries and in croplands across Europe, whereas largest OC contents were predicted in wetlands, woodlands and mountainous areas. The map of the predictions’ standard error had large uncertainty in northern latitudes, wetlands, moors and heathlands, whereas small uncertainty was mostly found in croplands. The map produced gives the most updated general picture of topsoil OC content at the European Union scale.JRC.H.5-Land Resources Managemen

A map of the topsoil organic carbon content of Europe generated by a generalized additive model

There is an increasing demand for up-to-date soil organic carbon (OC) data for global environmental and climatic modelling. The aim of this study was to create a map of topsoil OC content at the European scale by applying digital soil mapping techniques to the first European harmonized geo-referenced topsoil (0–20 cm) database, which arises from the Land use/Cover Area frame statistical Survey (LUCAS). A map of the associated uncertainty was also produced to support careful use of the predicted OC contents. A generalized additive model (GAM)was fitted on 85% of the dataset (R2 =0.29), using OC content as dependent variable; a backward stepwise approach selected slope, land cover, temperature, net primary productivity, latitude and longitude as suitable covariates. The validation of the model (performed on 15% of the data-set) gave an overall R2 of 0.27 and an R2 of 0.21 for mineral soils and 0.06 for organic soils. Organic C content in most organic soils was under-predicted, probably because of the imposed unimodal distribution of our model, whose mean is tilted towards the prevalent mineral soils. This was also confirmed by the poor prediction in Scandinavia (where organic soils are more frequent), which gave an R2 of 0.09, whilst the prediction performance (R2) in non-Scandinavian countries was 0.28. Themap of predicted OC content had the smallest values in Mediterranean countries and in croplands across Europe, whereas largest OC contents were predicted in wetlands, woodlands and mountainous areas. The map of the predictions’ standard error had large uncertainty in northern latitudes, wetlands, moors and heathlands, whereas small uncertainty was mostly found in croplands. The map produced gives the most updated general picture of topsoil OC content at the European Union scale

From model intercomparison toward benchmark UV spectra for six real atmospheric cases

The validity of a radiative transfer model can be checked either by comparing its results with measurements or with solutions for artificial cases. Unfortunately, neither type of comparison can guarantee that the spectral UV surface irradiance is accurately calculated for real atmospheric cases. There is a need therefore for benchmarks, i.e., standard results that can be used as a validation tool for UV radiation models. In this paper we give such benchmarks for six cloud-free situations. The chosen cases are characterized by different values of solar zenith angle, ozone column, aerosol loading, and surface albedo. Observations are also available for these cases to allow a further comparison between model results and measurements. An intercomparison of 12 numerical models is used to construct the benchmarks. Each model is supplied with identical input data, and a distinction is made between models that assume a planeparallel geometry and those that use a pseudospherical approximation. Differences remain between the model results, because of different treatments of the input data set. Calculations of direct and global transmission and direct and global irradiance are within 3% for wavelengths longer than 320 nm. For the low-Sun cases the calculations are within 10% for wavelengths longer than 300 nm. On the basis of these calculations, six benchmark UV spectra (295–400 nm) are established with a standard deviation of 2%. Relative standard deviations are higher for the lowest absolute intensities at low Sun (5% at 300 nm). The variation between models is typically less than the variation seen between model and measurement. Differences between the benchmarks and the observed spectra are mainly due to the uncertainty in the input parameters. In four of the six cases the benchmarks agree with the observed spectra within 13% over the whole UV spectral region