Biavati, G.; Feist, D. G.; Gerbig, C.; Kretschmer, R.: Error estimation for localized signal properties: application to atmospheric mixing height retrievals. Atmospheric Measurement Techniques 8, pp. 4215 - 4230 (2015)
Vogel, F. R.; Tiruchittampalam, B.; Theloke, J.; Kretschmer, R.; Gerbig, C.; Hammer, S.; Levin, I.: Can we evaluate a fine-grained emission model using high-resolution atmospheric transport modelling and regional fossil fuel CO2 observations? Tellus, Series B - Chemical and Physical Meteorology 65, 18681 (2013)
Pillai, D.; Gerbig, C.; Kretschmer, R.; Beck, V.; Karstens, U.; Neininger, B.; Heimann, M.: Comparing Lagrangian and Eulerian models for CO2 transport - a step towards Bayesian inverse modeling using WRF/STILT-VPRM. Atmospheric Chemistry and Physics 12, pp. 8979 - 8991 (2012)
Kretschmer, R.; Gerbig, C.; Karstens, U.; Koch, F. T.: Error characterization of CO2 vertical mixing in the atmospheric transport model WRF-VPRM. Atmospheric Chemistry and Physics 12, pp. 2441 - 2458 (2011)
Ahmadov, R.; Gerbig, C.; Kretschmer, R.; Körner, S.; Neininger, B.; Dolman, A. J.; Sarrat, C.: Mesoscale covariance of transport and CO2 fluxes: Evidence from observations and simulations using the WRF-VPRM coupled atmosphere-biosphere model. Journal of Geophysical Research: Atmospheres 112 (22), p. D22107 (2007)
Kretschmer, R.: On the use of observation based mixing heights to constrain atmospheric CO2 transport models. Dissertation, XX, 123 pp., Friedrich Schiller University Jena, Jena (2014)
Kretschmer, R.: Development of a software system for integration, automation, management & [and] presentation of WRF-VPRM computer model runs. Diploma, 89 pp., Friedrich-Schiller-Universität, Jena (2008)
The new research project "PollenNet" aims to use artificial intelligence to accurately predict the spread of pollen. In order to improve allergy prevention, experts are bringing together the latest interdisciplinary findings from a wide range of fields.
If rivers overflow their banks, the consequences can be devastating. Using methods of explainable machine learning, researchers at the Helmholtz Centre for Environmental Research (UFZ) have shown that floods are more extreme when several factors are involved in their development.
Europe is the fastest warming continent in the world. According to the European Environment Agency’s assessment, many of these risks have already reached critical levels and could become catastrophic without urgent and decisive action.
Plant observations collected with plant identification apps such as Flora Incognita allow statements about the developmental stages of plants - both on a small scale and across Europe.
Global experts have unveiled the annual 10 New Insights in Climate Science report. The report equips policymakers with the latest and most pivotal climate science research from the previous 18 months, synthesised to help inform negotiations at COP28 and policy implementation through 2024 and beyond.
Vegetation can respond to drought through different mechanisms, including changes in the plants’ structure and physiology. By analyzing state-of-the-art satellite-derived datasets with explainable machine learning methods, an international team around Wantong Li and René Orth showed that the vegetation’s physiology in many ecosystems has deviated from its structure under drought on a global scale.
Carbon sinks on the land surface mitigate the greenhouse effect. An international team of scientists has now determined that the vast majority of Europe’s total above-ground carbon storage is provided by the forests of Eastern Europe. However, this carbon sink has declined, mainly due to changes in land use.
The world’s forests, grasslands, and other terrestrial ecosystems have played a substantial role in offsetting human carbon emissions—a capability that researchers say would be threatened by continued global change.
A new study shows that the efficiency of microbial carbon use is at least four times more influential than other biological factors or environmental conditions on the global storage and distribution of carbon in soil.
Germany's most popular plant identification app "Flora Incognita" has been further upgraded by a new artificial intelligence. This triples the number of plant species that can be identified up to 16,000. In addition, the app is now available in 20 different languages and also in offline mode.
Dr. Ana Bastos, group leader at Max Planck Institute for Biogeochemistry in Jena, was awarded the Beutenberg Campus science award in the category „outstanding junior research scientist”.