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The EarthCARE lidar cloud and aerosol profile processor (A-PRO): the A-AER, A-EBD, A-TC, and A-ICE products

ATLID (atmospheric lidar) is the lidar to be flown on the Earth Clouds and Radiation Explorer satellite (EarthCARE). EarthCARE is a joint European–Japanese satellite mission that was launched in May 2024. ATLID is an advanced lidar optimized for cloud and aerosol property profile measurements. This paper describes some of the key novel algorithms being applied to this lidar to retrieve cloud and aerosol properties. Example results based on simulated data are presented and discussed.

Can we reliably reconstruct the mid-Pliocene Warm Period with sparse data and uncertain models?

We have created a new global surface temperature reconstruction of the climate of the mid-Pliocene Warm Period, representing the period roughly 3.2 million years before the present day. We estimate that the globally averaged mean temperature was around 3.9 °C warmer than it was in pre-industrial times, but there is significant uncertainty in this value.

Biological and dust aerosols as sources of ice-nucleating particles in the eastern Mediterranean: source apportionment, atmospheric processing and parameterization

Ice nucleating particle (INP) concentrations are required for correct predictions of clouds and precipitation in a changing climate, but they are poorly constrained in climate models. We unravel source contributions to INPs in the eastern Mediterranean and find that biological particles are important, regardless of their origin. The parameterizations developed exhibit superior performance and enable models to consider biological-particle effects on INPs.

CO2 emissions of drained coastal peatlands in the Netherlands and potential emission reduction by water infiltration systems

Biogeosciences
DOI 10.5194/bg-21-4099-2024
20 September 2024

Drained peatlands cause high CO2 emissions. We assessed the effectiveness of subsurface water infiltration systems (WISs) in reducing CO2 emissions related to increases in water table depth (WTD) on 12 sites for up to 4 years. Results show WISs markedly reduced emissions by 2.1 t CO2-C ha-1 yr-1. The relationship between the amount of carbon above the WTD and CO2 emission was stronger than the relationship between WTD and emission. Long-term monitoring is crucial for accurate emission estimates.

Young and new water fractions in soil and hillslope waters

We use a 3-year time series of tracer data of streamflow and soils to show how water moves through the subsurface to become streamflow. Less than 50% of soil water consists of rainfall from the last 3 weeks. Most annual streamflow is older than 3 months, and waters in deep subsurface layers are even older; thus deep layers are not the only source of streamflow. After wet periods more rainfall was found in the subsurface and the stream, suggesting that water moves quicker through wet landscapes.

Representation learning with unconditional denoising diffusion models for dynamical systems

We train neural networks as denoising diffusion models for state generation in the Lorenz 1963 system and demonstrate that they learn an internal representation of the system. We make use of this learned representation and the pre-trained model in two downstream tasks: surrogate modelling and ensemble generation. For both tasks, the diffusion model can outperform other more common approaches. Thus, we see a potential of representation learning with diffusion models for dynamical systems.

Mesoscale permeability variations estimated from natural airflows in the decorated Cosquer Cave (southeastern France)

Conservation of decorated caves is highly dependent on airflows and is correlated with rock formation permeability. We present the first conceptual model of flows around the Paleolithic decorated Cosquer coastal cave (southeastern France), quantify air permeability, and show how its variation affects water levels inside the cave. This study highlights that airflows may change in karst unsaturated zones in response to changes in the water cycle and may thus be affected by climate change.

Precursors and pathways: dynamically informed extreme event forecasting demonstrated on the historic Emilia-Romagna 2023 flood

Natural Hazards and Earth System Sciences
DOI 10.5194/nhess-24-2995-2024
6 September 2024

Extreme rainfall is the leading weather-related source of damages in Europe, but it is still difficult to predict on long timescales. A recent example of this was the devastating floods in the Italian region of Emiglia Romagna in May 2023. We present perspectives based on large-scale dynamical information that allows us to better understand and predict such events.

Ice viscosity governs hydraulic fracture that causes rapid drainage of supraglacial lakes

Due to surface melting, meltwater lakes seasonally form on the surface of glaciers. These lakes drive hydrofractures that rapidly transfer water to the base of ice sheets. This paper presents a computational method to capture the complicated hydrofracturing process. Our work reveals that viscous ice rheology has a great influence on the short-term propagation of fractures, enabling fast lake drainage, whereas thermal effects (frictional heating, conduction, and freezing) have little influence.

Optimizing the iodide-adduct chemical ionization mass spectrometry (CIMS) quantitative method for toluene oxidation intermediates: experimental insights into functional-group differences

We introduce detailed and improved quantitation and semi-quantitation methods of iodide-adduct time-of-flight chemical ionization mass spectrometry (I-CIMS) to measure toluene oxidation intermediates. We assess the experimental sensitivity of various functional group species and their binding energy with iodide ions in I-CIMS. A novel classification approach was introduced to significantly enhance the accuracy of semi-quantitative methods (improving R2 values from 0.52 to beyond 0.88).

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