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The 2023 global warming spike was driven by the El Niño–Southern Oscillation

The rapid global warming of 2023 has led to concerns that it could be externally driven. Here we show that climate models subject only to internal variability predict such warming spikes but rarely (p~1.6 %). However, when a prolonged La Niña immediately precedes an El Niño, as occurred leading up to 2023, such spikes are not uncommon (p~10.3 %). Virtually all of the spikes occur during an El Niño, strongly suggesting that internal variability drove the 2023 warming.

Stable and unstable fall motions of plate-like ice crystal analogues

This study uses 3D-printed ice crystal analogues falling in a water–glycerine mix and observed with multi-view cameras, simulating atmospheric conditions. Four types of motion are observed: stable, zigzag, transitional, and spiralling. Particle shape strongly influences motion; complex shapes have a wider range of conditions where they fall steadily compared to simple plates. The most common orientation of unstable particles is non-horizontal, contrary to prior assumptions of always horizontal.

Characterizing nonlinear, nonstationary, and heterogeneous hydrologic behavior using ensemble rainfall–runoff analysis (ERRA): proof of concept

Here, I present a new way to quantify how streamflow responds to rainfall across a range of timescales. This approach can estimate how different rainfall intensities affect streamflow. It can also quantify how runoff response to rainfall varies, depending on how wet the landscape already is before the rain falls. This may help us to understand processes and landscape properties that regulate streamflow and to assess the susceptibility of different landscapes to flooding

Global-scale gravity wave analysis methodology for the ESA Earth Explorer 11 candidate CAIRT

We investigate the capabilities of a proposed satellite mission, CAIRT, for observing gravity waves throughout the middle atmosphere and present the necessary methodology for in-depth wave analysis. Our findings suggest that such a satellite mission is highly capable of resolving individual wave parameters and could give new insights into the role of gravity waves in general atmospheric circulation and atmospheric processes.

The effects of land use on soil carbon stocks in the UK

We collated a large data set (15 790 soil cores) on soil carbon stock in different land uses. Soil carbon stocks were highest in woodlands and lowest in croplands. The variability in the effects was large. This has important implications for agri-environment schemes seeking to sequester carbon in the soil by altering land use because the effect of a given intervention is very hard to verify.

Calibrating estimates of ionospheric long-term change

Long-term change in the ionosphere are expected due to increases in greenhouse gases in the lower atmosphere. Empirical formulae are used to estimate height. Through comparison with independent data we show that there are seasonal and long-term biases introduced by the empirical model. We conclude that estimates of long-term changes in ionospheric height need to account for these biases.

Review article: Drought as a continuum – memory effects in interlinked hydrological, ecological, and social systems

Natural Hazards and Earth System Sciences
DOI 10.5194/nhess-24-3173-2024
23 September 2024

Drought is a creeping phenomenon but is often still analysed and managed like an isolated event, without taking into account what happened before and after. Here, we review the literature and analyse five cases to discuss how droughts and their impacts develop over time. We find that the responses of hydrological, ecological, and social systems can be classified into four types and that the systems interact. We provide suggestions for further research and monitoring, modelling, and management.

Increasing aerosol optical depth spatial and temporal availability by merging datasets from geostationary and sun-synchronous satellites

In this study, for the first time, we combined aerosol data from six satellites using a unified algorithm. The global datasets are generated at a high spatial resolution of about 25 km with an interval of 30 min. The new datasets are compared against ground truth and verified. They will be useful for various applications such as air quality monitoring, climate research, pollution diurnal variability, long-range smoke and dust transport, and evaluation of regional and global models.

Methane retrieval from MethaneAIR using the CO2 proxy approach: a demonstration for the upcoming MethaneSAT mission

MethaneSAT is an upcoming satellite mission designed to monitor methane emissions from the oil and gas (O&G) industry globally. Here, we present observations from the first flight campaign of MethaneAIR, a MethaneSAT-like instrument mounted on an aircraft. MethaneAIR can map methane with high precision and accuracy over a typically sized oil and gas basin (~200 km2) in a single flight. This paper demonstrates the capability of the upcoming satellite to routinely track global O&G emissions.

Volcano tsunamis and their effects on moored vessel safety: the 2022 Tonga event

Natural Hazards and Earth System Sciences
DOI 10.5194/nhess-24-3095-2024
20 September 2024

The eruption of the Hunga Tonga–Hunga Ha’apai volcano in January 2022 triggered a global phenomenon, including an atmospheric wave and a volcano-meteorological tsunami (VMT). The tsunami, reaching as far as Callao, Peru, 10 000 km away, caused significant coastal impacts. This study delves into understanding these effects, particularly on vessel mooring safety. The findings underscore the importance of enhancing early warning systems and preparing port authorities for managing such rare events.

The 2020 European Seismic Hazard Model: overview and results

Natural Hazards and Earth System Sciences
DOI 10.5194/nhess-24-3049-2024
20 September 2024

The 2020 European Seismic Hazard Model (ESHM20) is the latest seismic hazard assessment update for the Euro-Mediterranean region. This state-of-the-art model delivers a broad range of hazard results, including hazard curves, maps, and uniform hazard spectra. ESHM20 provides two hazard maps as informative references in the next update of the European Seismic Design Code (CEN EC8), and it also provides a key input to the first earthquake risk model for Europe.

Large-sample hydrology – a few camels or a whole caravan?

We show that the differences between the forcing data included in three CAMELS datasets (US, BR, GB) and the forcing data included for the same catchments in the Caravan dataset affect model calibration considerably. The model performance dropped when the data from the Caravan dataset were used instead of the original data. Most of the model performance drop could be attributed to the differences in precipitation data. However, differences were largest for the potential evapotranspiration data.

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.