Distinguishing short‐term versus long‐term responses in cover‐class structured community dynamics: a test with grassland drought response

Ecology Letters Wiley 28:8 (2025) e70182

Authors:

Aryaman Gupta, Samuel Gascoigne, György Barabás, Benjamin Wong Blonder, Man Qi, Erola Fenollosa Romani, Rachael Thornley, Christina Hernandez, Andrew Hector, Roberto Salguero-Gómez

Abstract:

Climate change is increasing the magnitude and frequency of precipitation extremes. Consequently, grassland community dynamics are destabilising and becoming harder to predict since models typically simulate long-term (asymptotic) behaviour, potentially neglecting short-term (transient) behaviour. Here, we use cover data from an experiment performed over 8 years to model short- and long-term responses of three functional groups (grasses, legumes, and non-leguminous forbs) to precipitation extremes. We use Integral Projection Models (IPMs) and pseudospectral theory to track transient grassland community dynamics driven by response lags and interannual shifts. We show that the cover-class structure and inter-cover-class interactions of functional groups make them transiently unstable but asymptotically stable, that is, disturbances are initially amplified before eventually dissipating. We also show that grasses dominate under irrigation, while legumes and forbs dominate under drought. We demonstrate that the pseudospectra of IPMs enable computationally and data-wise inexpensive assessment of whether transient dynamics drive community responses to disturbances.

Fewer but More Intense: Changes in Extreme Precipitation Cells from Global Kilometer-Scale Climate Modeling

Copernicus Publications (2025)

Authors:

Fabian Senf, Leonie Hartog, William Jones

Abstract:

Earth system modeling is currently undergoing an exciting transformation, thanks to new technical capabilities that allow for significant spatial refinement. For the first time, these capabilities allow us to explicitly simulate extreme precipitation and its effects on climate-relevant timescales on a global scale. Thus, new Earth system data from high-resolution modeling approaches offer an exciting foundation for new analyses and research. In our study, we examine the distribution and changes in extreme precipitation from global simulations. We obtained this data from the ICON Earth system model simulations conducted within the nextGEMS project, which aims to create future projections up to the year 2050 with a grid spacing of approximately 5 km. Our analysis focuses on the portion of precipitation contributing to the top ten percent of globally accumulated precipitation. Using the open-source tool tobac we identify and track the resulting precipitation cells over time. Our analysis reveals that warming causes the most extreme precipitation cells to become more intense. At the same time, the data shows a significant decrease in the total number of cells, resulting in fewer, more intense extremes. Finally, we discuss these findings in relation to changes in the spatial distribution of the cells and changed environmental conditions.

Studying aerosol, clouds, and air quality in the coastal urban environment of Southeastern Texas

Bulletin of the American Meteorological Society American Meteorological Society (2025)

Authors:

Michael P Jensen, James H Flynn, Jorge E Gonzalez-Cruz, Laura M Judd, Pavlos Kollias, Chongai Kuang, Greg M McFarquhar, Heath Powers, Prathap Ramamurthy, John Sullivan, Allison C Aiken, Sergio L Alvarez, Peter Argay, Brian Argrow, Tyler M Bell, Doug Boyer, Sarah D Brooks, Eric C Bruning, Kelcy Brunner, Brian Butterworth, Radiance Calmer, Christopher D Cappa, Rajan K Chakrabarty, V Chandrasekar, Chun-Ying Chao, Bo Chen, Swarup China, Don R Collins, Scott M Collis, Sean Crowell, Rachael Dal Porto, Gijs de Boer, Min Deng, Darielle Dexheimer, Aryeh J Drager, Xuanlin Du, Manvendra K Dubey, Andrew M Dzambo, Montana Etten-Bohm, Jiwen Fan, Ryan Farley, Ya-Chien Feng, Yan Feng, Marta Fenn, Richard E Ferrare, Samuel Flusche, Ann M Fridlind, Joseph Galewsky, Harold Gamarro, Samuel Gardner

Abstract:

A multi-agency succession of field campaigns was conducted in southeastern Texas during July 2021 through October 2022 to study the complex interactions of aerosols, clouds and air pollution in the coastal urban environment. As part of the Tracking Aerosol Convection interactions Experiment (TRACER), the TRACER- Air Quality (TAQ) campaign the Experiment of Sea Breeze Convection, Aerosols, Precipitation and Environment (ESCAPE) and the Convective Cloud Urban Boundary Layer Experiment (CUBE), a combination of ground-based supersites and mobile laboratories, shipborne measurements and aircraft-based instrumentation were deployed. These diverse platforms collected high-resolution data to characterize the aerosol microphysics and chemistry, cloud and precipitation micro- and macro-physical properties, environmental thermodynamics and air quality-relevant constituents that are being used in follow-on analysis and modeling activities. We present the overall deployment setups, a summary of the campaign conditions and a sampling of early research results related to: (a) aerosol precursors in the urban environment, (b) influences of local meteorology on air pollution, (c) detailed observations of the sea breeze circulation, (d) retrieved supersaturation in convective updrafts, (e) characterizing the convective updraft lifecycle, (f) variability in lightning characteristics of convective storms and (g) urban influences on surface energy fluxes. The work concludes with discussion of future research activities highlighted by the TRACER model-intercomparison project to explore the representation of aerosol-convective interactions in high-resolution simulations.

Multispectral to Hyperspectral Using Pretrained Foundational Model

IGARSS 2025 - 2025 IEEE International Geoscience and Remote Sensing Symposium IEEE (2025) 785-789

Authors:

Ruben Gonzalez, Conrad M Albrecht, Nassim Ait Ali Braham, Devyani Lambhate, Joao Lucas De Sousa Almeida, Paolo Fraccaro, Benedikt Blumenstiel, Thomas Brunschwiler, Ranjini Bangalore

Multimodal GNSS-R self-supervised learning as a generalist Earth surface monitor

International Journal of Applied Earth Observation and Geoinformation Elsevier BV 142 (2025) 104658

Authors:

Daixin Zhao, Konrad Heidler, Milad Asgarimehr, Conrad M Albrecht, Jens Wickert, Xiao Xiang Zhu, Lichao Mou