To limit global warming below 2°C, a drastic overall reduction from current CO2 emissions is needed. We argue that scientists should also participate in this effort in their professional activity and especially Earth scientists, on the grounds of maintaining credibility and leading by example. The strategies and measures to reach a low-carbon scientific activity require detailed estimates of the current footprint of laboratories. Here, we present the footprint of six laboratories in Earth, environmental and space sciences, representative of the AGU community, with a comprehensive scope also including international research infrastructures. We propose a novel method to attribute the footprint of any research infrastructure to any given research laboratory. Our results highlight that most laboratories have annual footprints reaching 10-20 tonnes CO2 equivalent per person (tCO2e.p-1), dominated by infrastructures and specifically satellites in three cases (with footprints up to 11 tCO2e.p-1 or 60%), while air-travels and purchases remain within the top three sources in all cases (2-4 tCO2e p-1 or 10-30% each). Consequently, footprints related to commuting and laboratory functioning, about 2 tCO2e.p-1 (20%) or less, are relatively modest compared to infrastructures, purchases and air-travels. Thus, reduction measures ignoring infrastructures may not be able to achieve reductions larger than 20 to 35% even with flight quotas and a substantial reduction of purchases. Finally, we also discuss how a deeper transformation of scientific practices, away from a fast science ideal, could make Earth and environmental sciences more sustainable and at the forefront of a rapid and drastic social bifurcation.

The study of river dynamics has long relied on the analysis of traditional in situ hydrographs. This graphical representation of temporal variability at a given location is so ubiquitous that the mere term “hydrograph” is widely recognized as a time series. While such a “temporal hydrograph” is well suited for in situ data analysis, it fails to represent hydrologic variability across space at a given time; a perspective that characterizes satellite-based hydrologic observations. Here we argue that the concept of “spatial hydrograph” should be the focus of its own dedicated scrutiny. We build “space series” of river discharge and present their analysis in the context of peak flow event detection. We propose the use of peak event spatial coverage, referred to as “length”, as an analog to event duration. Our analysis is performed in the Mississippi basin using a dense in situ network. We reveal that peak flow events range in length from around 75 to 1,800 km with a median (mean) value of 330 (520) km along the basin’s largest rivers. Our analysis also suggests that spatial sampling needs to be a factor of 4 (2) finer in resolution than peak flow lengths to detect 81±13% (70±20%) of events and to estimate their length within 84±3% (67±12%) median accuracy. We evaluate the connection between temporal and spatial scales of peak flows and show that events with longer durations also affect larger extents. We finally discuss the implications for the design of satellite missions concerned with capturing floods across space.

Lakes are the most prevalent and predominant water repositories on land surface. A primary objective of the Surface Water and Ocean Topography (SWOT) satellite mission is to monitor the surface water elevation, area, and storage change in Earth’s lakes. To meet this objective, prior information of global lakes, such as locations and benchmark extents, is required to organize SWOT’s KaRIn observations over time for computing lake storage variation. Here, we present the SWOT mission Prior Lake Database (PLD) to fulfill this requirement. This paper emphasizes the development of the “operational PLD”, which consists of (1) a high-resolution mask of ~6 million lakes and reservoirs with a minimum area of 1 ha, and (2) multiple operational auxiliaries to assist the lake mask in generating SWOT’s standard vector lake products. We built the prior lake mask by harmonizing the UCLA Circa-2015 Global Lake Dataset and several state-of-the-art reservoir databases. Operational auxiliaries were produced from multi-theme geospatial data to provide information necessary to embody the PLD function, including lake catchments and influence areas, ice phenology, relationship with SWOT-visible rivers, and spatiotemporal coverage by SWOT overpasses. Globally, over three quarters of the prior lakes are smaller than 10 ha. Nearly 96% of the lakes, constituting over half of the global lake area, are fully observed at least once per orbit cycle. The PLD will be recursively improved during the mission period and serves as a critical framework for organizing, processing, and interpreting SWOT observations over lacustrine environments with fundamental significance to lake system science.