PUBLICATIONS & TALKS

Atmospheric effects are not spectrally neutral

Aerosols and clouds do not affect all parts of the solar spectrum in the same way. Long-term observations at a Mediterranean site showed that aerosol effects on PAR can represent a substantial fraction of the total solar radiative effect, while changes detectable within PAR were not necessarily reproduced in broadband total irradiance. Subsequent analyses of cloud and ultraviolet effects reinforce the same broader message: spectrally resolved observations can reveal atmospheric behaviour that broadband radiation alone may obscure.

Further reading:

Lozano et al. (2021), Atmospheric Research 255, 105538

Lozano et al. (2022), Atmospheric Research 268, 106010

Lozano et al. (2023), Atmospheric Research 296, 107072

Lozano et al. (2026), Physics and Chemistry of the Earth 144, 104518

Clouds redistribute radiation — they do not simply dim it

Clouds reduce the global solar radiation reaching the surface while simultaneously modifying its diffuse component. In PAR, this produces distinct responses of global and diffuse radiation and changes the direct–diffuse partitioning experienced by ecosystems. This distinction matters because the same amount of total incoming radiation can have different environmental consequences depending on how that energy is partitioned between direct and diffuse components.

Further reading:

Lozano et al. (2022), Atmospheric Research 268, 106010

Lozano et al. (2023), Atmospheric Research 296, 107072

Radiative forcing depends on more than atmospheric loading

The magnitude and evolution of aerosol radiative effects cannot be interpreted from aerosol amount alone. Long-term analyses showed changes in aerosol forcing efficiency and, more recently, a strong dependence of erythemal-UV aerosol forcing on solar geometry and aerosol optical properties. In the UV, aerosol optical depth declined markedly without a corresponding surface brightening, while coarse and absorbing particles exerted an important control on forcing. Together, these findings show that atmospheric loading, particle properties, spectral range and Sun–Earth geometry must be considered jointly when interpreting radiative forcing.

The cloud analysis provides a complementary long-term result: at the analysed Mediterranean site, cloud radiative forcing evolved consistently with a weakening of the surface cooling effect of clouds over the study period, illustrating that atmospheric radiative effects need not remain stationary through time.

Further reading:

Lozano et al. (2021), Atmospheric Research 255, 105538

Lozano et al. (2023), Atmospheric Research 296, 107072

Lozano et al. (2026), Physics and Chemistry of the Earth 144, 104518

Aquatic ecosystem responses emerge from interacting environmental and trophic controls

Aquatic ecosystems respond to combinations of environmental and biological controls rather than to individual drivers in isolation. Work in Mediterranean and high-mountain aquatic systems showed that algal–bacterial relationships can shift over time alongside changes in temperature, nutrient stoichiometry and atmospheric inputs, while the strength and direction of phytoplankton–bacteria coupling can also depend on trophic-web interactions. Experimental work further showed that increased nutrient availability can expose responses to UV radiation or elevated CO₂ that are not apparent when those factors are considered independently.

The broader implication is that ecosystem responses to future environmental conditions cannot always be inferred by adding together responses measured for individual drivers; interactions among physical forcing, nutrient availability and biological processes can alter the resulting metabolic balance.

Further reading:

González-Olalla et al. (2018), Scientific Reports 8, 10278

Lozano et al. (2023), Microbial Ecology 86, 810–824

Lozano (2024), Marine and Freshwater Research 75(9), MF23137

Complex forest structure can emerge from the data instead of being imposed beforehand

In uneven-aged forests, predefined size classes can discard structural information before an ecosystem model is even run. Comparing traditional classifications with unsupervised approaches showed that data-derived groupings generally represented key structural variables such as diameter, height and basal area more accurately. The result suggests that allowing groups to emerge from the multivariate structure of the stand can provide a more faithful representation than imposing fixed classes a priori.

More broadly, this shows that the way environmental complexity is represented can itself become an important source of model performance and uncertainty: improving representation does not necessarily require increasing the number of groups or the complexity of the underlying ecosystem model.

Further reading:

Lozano et al. (2026), Ecological Modelling 521, 111733

Physically informed simplicity can compete with more complex models

Greater model complexity does not automatically produce a better environmental representation. Across different radiation problems, relatively simple formulations built around physically meaningful predictors have achieved performance comparable to, and in some cases better than, approaches requiring additional variables or greater statistical flexibility. In diffuse PAR estimation, physically motivated relationships were able to reproduce much of the observed variability despite comparison with highly flexible machine-learning approaches; related work showed that aerosol forcing on PAR can be estimated from widely available global irradiance and solar geometry.

The same principle emerged independently in net-radiation modelling: adding further predictors did not necessarily improve performance, and the simplest formulations remained competitive across contrasting sites and conditions. The broader lesson is not that models should always be simple, but that additional complexity should provide additional physical information rather than complexity for its own sake.

Further reading:

Foyo-Moreno et al. (2023), Atmospheric Research 291, 106819

Lozano et al. (2023), Journal of Geophysical Research: Atmospheres 128, e2023JD039256

Foyo-Moreno et al. (2025), Atmospheric Research 315, 107886