Engineering topics

Markus Reichstein

Publications and source records attributed to Markus Reichstein.

3 records

NASA NTRS2022

Exploring the Relationship Between Temperature Forecast Errors and Earth System Variables

Accurate subseasonal weather forecasts, from two weeks up to a season, can help reduce costs and impacts related to weather and corresponding extremes. The quality of weather forecasts has improved considerably in recent decades as models represent more details of physical processes, and they benefit from assimilating comprehensive Earth observation data as well as increasing computing power. However, with ever–growing model complexity, it becomes increasingly difficult to pinpoint weaknesses in the forecast models’ process representations which is key to improving forecast accuracy. In this study, we use a comprehensive set of observation–based ecological, hydrological and meteorological variables to study their potential for explaining temperature forecast errors at the weekly time scale. For this purpose, we compute Spearman correlations between each considered variable and the forecast error obtained from the ECMWF subseasonal–to–seasonal (S2S) reforecasts at lead times of 1–6 weeks. This is done across the globe for the time period 2001–2017. The results show that temperature forecast errors globally are most strongly related with climate–related variables such as surface solar radiation and precipitation, which highlights the model’s difficulties in accurately capturing the evolution of the climate–related variables during the forecasting period. At the same time, we find particular regions in which other variables are more strongly related to forecast errors. For instance, in central Europe, eastern North America and southeastern Asia, vegetation greenness and soil moisture are relevant, while in western South America and central North America, circulation–related variables such as surface pressure relate more strongly with forecast errors. Overall, the identified relationships between forecast errors and independent Earth observations reveal promising variables on which future forecasting system development could focus by specifically considering related process representations and data assimilation.

Temperature↗

NASA NTRS2021

Soil Moisture–Atmosphere Feedbacks Dominate Land Carbon Uptake Variability

Year-to-year changes in carbon uptake by terrestrial ecosystems play an essential role in determining atmospheric carbon dioxide concentrations. It remains uncertain to what extent temperature and water availability can explain these variations at the global scale. Here we use factorial climate model simulations and show that variability in soil moisture drives 90% of the inter-annual variability in global land carbon uptake, mainly through its impact on photosynthesis. We find that most of this ecosystem response occurs indirectly as soil moisture–atmosphere feedbacks amplify temperature and humidity anomalies, and enhance the direct effects of soil water stress. The strength of this feedback mechanism explains why coupled climate models indicate a dominant role of soil moisture which is not readily apparent in land surface model simulations and observational analyses. These findings highlight the need to account for feedbacks between soil and atmospheric dryness when estimating the carbon cycle’s response to climatic change globally, as well as when conducting field-scale investigations of the ecosystem response to droughts. Our results show that most of the global variability in modelled land carbon uptake is driven by temperature and vapour pressure deficit effects which are controlled by soil moisture.

Atmospheric dynamics↗

NASA NTRSDate not supplied

Systemic Risk From the Perspective of Climate, Environmental and Disaster Risk Science and Practice

Understanding and managing systemic risk is more important than ever due to our immense global connectivity (e.g., between sectors, such as food-health-water-energy, countries and continents, down to individuals). Despite the fact that the notion of systemic risk is several decades old, the term is used in diverse ways across different disciplines (e.g., financial systems, medicine, earth system sciences, disaster risk research and climate science). Triggered by the repercussions of the global financial crisis of the late 2000s, and more recently the COVID-19 pandemic, which are clear realization of systemic risk, the perception of systemic risk has often been focused on global and catastrophic or even existential risks. Systemic risk, however, can be seen as a feature of systems at all possible scales (e.g., global, national, regional, local) with system boundaries varying depending on the context. Addressing current societal challenges, such as climate change, in terms of systemic risk requires integrating different systems perspectives and fostering system thinking, while implementing key intergovernmental agendas, such as the Paris Agreement, the Sendai Framework for Disaster Risk Reduction and the Sustainable Development Goals. Based on insights gained and knowledge collected from an expert workshop, literature review and expert elicitation, we give an integrated perspective of climate, environmental and disaster risk science and practice on systemic risk as summarized in a Briefing Note to the International Science Council. We provide an overview of concepts of systemic risk that have evolved over time and identify commonalities across terminologies and perspectives associated with systemic risk used in different contexts. Key attributes of systemic risk are outlined without prescribing a single definition, and information and data requirements are discussed that are essential for a better and more actionable understanding of the systemic nature of risk. Finally, the opportunities to connect research and policy for addressing systemic risk are highlighted.

systemic risk↗