Abstract
In June–July 2020, the middle and lower reaches of the Yangtze River (MLYR) were hit by a Meiyu event characterized by a long duration, abundant precipitation, and frequent heavy rainfall, resulting in destructive flooding. We found that the extreme cumulative precipitation in 2020 was mainly contributed by more moderate to heavy daily precipitation rather than extreme daily events. Although some previous studies have been conducted to attribute the 2020 Meiyu event in the MLYR, most of them focused on the cumulative precipitation amount. This attribution case study complements previous attribution analyses and reveals many new features. Our results show that anthropogenic climate change—primarily driven by greenhouse gas (GHG) forcing, anthropogenic aerosol (AA) forcing, and land-use—has led to a decrease in the number of light to heavy precipitation days, while concurrently increasing the number of extreme precipitation days in the MLYR. Specifically, GHG and AA forcings decreased the frequency of light and moderate precipitation, but only GHG increased the frequency of extreme precipitation. An increasing trend in very heavy precipitation days has been observed. The competitive effects of GHG and AA forcings make it challenging to detect the signal of human activities, which could be intermingled with effects from natural variability. Under the SSP5-8.5 scenario, the probability of experiencing both light and extreme precipitation events will significantly increase in the MLYR. By 2050–2100, these events are projected to be nearly 4 times more frequent compared to the current climate, which poses significant challenges to water security and economic development decision makers.
Abstract
The interactions of clouds with radiation influence climate. Many of these impacts appear to be related to the radiative heating and cooling from high-level clouds, but few studies have explicitly tested this. Here, we use simulations with the ICON-ESM model to understand how high-level clouds, through their radiative heating and cooling, influence the large-scale atmospheric circulation and precipitation in the present-day climate. We introduce a new method to diagnose the radiative heating of high-level clouds: instead of defining high-level clouds as all clouds at temperatures colder than −35°C, we define them as all clouds with a cloud top at temperatures colder than −35°C. The inclusion of the lower cloud parts at temperatures warmer than −35°C circumvents the creation of artificial cloud boundaries and strong artificial radiative heating at the temperature threshold. To isolate the impact of high-level clouds, we analyze simulations with active cloud-radiative heating, with the radiative heating from high-level clouds set to zero, and with the radiative heating from all clouds set to zero. We show that the radiative interactions of high-level clouds warm the troposphere and strengthen the eddy-driven jet streams, but have no impact on the Hadley circulation strength and the latitude of the Intertropical Convergence Zone. Consistent with their positive radiative heating and energetic arguments, high-level clouds reduce precipitation throughout the tropics and lower midlatitudes. Overall, our results confirm that the radiative interactions of high-level clouds have important impacts on climate and highlight the need for better representing their radiative interactions in models.
Unveiling transboundary challenges in river flood risk management: learning from the Ciliwung River basin
Harkunti Pertiwi Rahayu, Khonsa Indana Zulfa, Dewi Nurhasanah, Richard Haigh, Dilanthi Amaratunga, and In In Wahdiny
Nat. Hazards Earth Syst. Sci., 24, 2045–2064, https://doi.org/10.5194/nhess-24-2045-2024, 2024
Transboundary flood risk management in the Ciliwung River basin is placed in a broader context of disaster management, environmental science, and governance. This is particularly relevant for areas of research involving the management of shared water resources, the impact of regional development on flood risk, and strategies to reduce economic losses from flooding.
Estimation of future rainfall extreme values by temperature-dependent disaggregation of climate model data
Niklas Ebers, Kai Schröter, and Hannes Müller-Thomy
Nat. Hazards Earth Syst. Sci., 24, 2025–2043, https://doi.org/10.5194/nhess-24-2025-2024, 2024
Future changes in sub-daily rainfall extreme values are essential in various hydrological fields, but climate scenarios typically offer only daily resolution. One solution is rainfall generation. With a temperature-dependent rainfall generator climate scenario data were disaggregated to 5 min rainfall time series for 45 locations across Germany. The analysis of the future 5 min rainfall time series showed an increase in the rainfall extremes values for rainfall durations of 5 min and 1 h.
Brief communication: Implications of outstanding solitons for the occurrence of rogue waves at two additional sites in the North Sea
Ina Teutsch, Ralf Weisse, and Sander Wahls
Nat. Hazards Earth Syst. Sci., 24, 2065–2069, https://doi.org/10.5194/nhess-24-2065-2024, 2024
We investigate buoy and radar measurement data from shallow depths in the southern North Sea. We analyze the role of solitons for the occurrence of rogue waves. This is done by computing the nonlinear soliton spectrum of each time series. In a previous study that considered a single measurement site, we found a connection between the shape of the soliton spectrum and the occurrence of rogue waves. In this study, results for two additional sites are reported.
Abstract
Ionospheric heavy ions in the distant tail of the Earth's magnetosphere at lunar distances are observed using the ARTEMIS mission. These heavy ions are originally produced in the terrestrial ionosphere. Using the ElectroStatic Analyzers (ESA) onboard the two probes orbiting the Moon, these heavy ions are observed as cold populations with distinct energies higher than the baseline energy of protons, with the energy-per-charge values for the heavy populations highly correlated with the proton energies. We conducted a full solar cycle survey of these heavy ion observations, including the flux, location, and drift energy, as well as the correlations with the solar wind and geomagnetic indices. The likelihood of finding these heavy ions in the preferred regions of observation called “loaded” quadrants of the terrestrial magnetotail is ∼90%, regardless of the z orientation of the IMF. We characterize the ratio of the heavy ion energy to the proton energy, as well as the velocity ratio of these two populations, for events from 2010 to mid-2023. This study shows that the “common velocity” assumption for the proton and heavy ion particles, as suggested in previous work through the velocity filter effect, is not necessarily valid in this case. Challenges in the identification of the mass of the heavy ions due to the ESA's lack of ion composition discrimination are addressed. It is proposed that at the lunar distances the heavy ion population mainly consists of atomic oxygen ions (O+) with velocities ∼25% more than the velocity of the co-located proton population.
Abstract
Calculating the magnetic flux transfer across the open-closed boundary (OCB) per unit time and distance—the reconnection electric field—is an important means of remotely monitoring magnetospheric dynamics. Ground-based measurements of plasma convection velocities together with velocities of the OCB are commonly used to infer reconnection rates. However, this approach is limited by spatial coverage and often lacks robust uncertainty quantification. In this paper, we assimilate Super Dual Auroral Radar Network convection measurements, ground magnetometer data, and estimates of the conductance derived from the Imager for Magnetopause-to-Aurora Global Exploration satellite imagers, using the Local mapping of polar ionospheric electrodynamics (Lompe) framework over a region in North America. We present a new method to assess various contributions to uncertainties in the derived reconnection electric fields, including a novel approach to estimate uncertainties in conductance from global auroral imaging. Our method is demonstrated on a substorm event with an associated pseudobreakup during a period of favorable observational coverage. In this case study, the uncertainties in the reconnection electric field are ∼5–10 mV/m at the peak of substorm expansion, roughly 15% of the peak reconnection electric field. We find that the main contributor to the reconnection electric field estimates after substorm onset is the OCB motion, whereas during the pseudobreakup the main contributor is ionospheric plasma convection.
Abstract
Over the past century, rapid urbanization has greatly altered landscapes and affected atmospheric conditions causing impacts across a wide range of sectors including human welfare, infrastructure, and ecosystems. As a result, there is a growing imperative to improve understanding of urbanization impacts on local and regional weather events and hydroclimates. This study investigates how urbanization affects precipitation and cloud fraction (CF) in the vicinity of Indianapolis. We employ multi-month simulations using the Weather Research and Forecasting model to: (a) assess the impact of an urban area on precipitation and CF, (b) quantify how this impact varies with urban growth, and (c) examine the main mechanisms through which the city alters the local hydroclimate. Specifically, two perturbed simulations, where the urban land cover is either replaced by croplands or is increased in size, are also performed for the two rainiest months. Comparisons of the control run with no city against the perturbed runs indicate statistically significant impacts of the urban area in enhancing precipitation amounts, frequency and low-level CF, particularly within the first 100 km radius downwind of the city boarder. The urban environment is found to increase precipitation efficiency over the city and in downwind regions. Temperature at 2 m height, planetary boundary layer height, turbulent kinetic energy, and convective available potential energy, are also enhanced in the perturbed runs and drive changes in vertical mixing, downwind precipitation amounts, frequency and low-level height CF. All these changes appear to be a non-linear function of the city size.
Abstract
While the Department of Defense (DoD) infrastructure is no stranger to extremes, recent events have been unprecedented, with climate change acting as a growing risk multiplier. To assess the level of exposure of DoD installations to extreme weather and climate events, site-specific climate information is needed. One way to bridge the scale gap between outputs from existing global climate models (GCMs) and sites is climate downscaling. This makes the information more relevant for impact assessment at the DoD installation and facility scale. However, downscaling GCMs is beset by a myriad of challenges and sources of uncertainty, and downscaling methods were not designed with specific infrastructure planning and design needs in mind. Here, we evaluate state-of-the-science dynamical downscaling and statistical downscaling and bias correction for climate variables (i.e., temperature and precipitation) at the daily scale. We also combine downscaling approaches in novel ways to optimize computational efficiency and reduce uncertainty. Furthermore, we examine the sensitivity of the downscaled outputs to the choice of reference data and quantify the relative uncertainty related to downscaling approach, reference data, and other factors across the climate variables and aggregation scales. Results show that empirical quantile mapping (EQM), a statistical downscaling, consistently performs well and has less sensitivity to the choice of reference data. Moreover, the hybrid downscaling that leverages EQM improves the performance of dynamical downscaling. Our findings highlight that the choice of reference data dominates uncertainties in temperature downscaling, while their role is more muted for precipitation but still non-negligible.
Abstract
Despite the importance of understanding the urban emission characteristics of greenhouse gases (GHGs) and air pollutants, few studies have conducted integrated assessments across diverse urban environments. Herein, we conducted a comprehensive evaluation of the emission characteristics of GHGs and air pollutants in seven cities in the Northern Hemisphere using ground-based Fourier transform spectrometers. Our analysis primarily focused on emission ratios of excess column-averaged dry-air mole fractions of carbon monoxide (CO) to carbon dioxide (CO2) (∆XCO:∆XCO2) and those of methane (CH4) to CO2 (∆XCH4:∆XCO2). We found that the emission ratios varied significantly across cities. Xianghe (China) and Pasadena (USA), known for severe air pollution, showed the highest emission ratios. Notably, Seoul (South Korea) showed lower ∆XCO:∆XCO2 (3.32 ± 0.10 ppb/ppm) but relatively higher ∆XCH4:∆XCO2 (4.85 ± 0.04 ppb/ppm), which was comparable to the ∆XCH4:∆XCO2 value of Xianghe (5.15 ± 0.10 ppb/ppm), suggesting that targeted CH4 reduction strategies may be required for climate change mitigation in Seoul.
Abstract
Dr. Jennifer Gannon passed away suddenly on 2024 May 2 in Greenbelt, MD. Dr. Gannon had served as an editor for the Space Weather journal since April 2019, and she was the longest-serving editor on the current board, having started under the previous editor-in-chief, Dr. Delores Knipp.
Comparison of the LEO and CPMA-SP2 techniques for black-carbon mixing-state measurements
Arash Naseri, Joel C. Corbin, and Jason S. Olfert
Atmos. Meas. Tech., 17, 3719–3738, https://doi.org/10.5194/amt-17-3719-2024, 2024
It is crucial to accurately measure the mixing states of light-absorbing carbon particles from emission sources like wildfires and biomass combustion to decrease climate forcing uncertainties. This study compares methods that measure light-absorbing carbon in the atmosphere. The CPMA-SP2 method offers more accurate results than traditional light-scattering methods, such as the leading-edge-only (LEO) method, thereby enhancing the accuracy of measuring the mixing states of light-absorbing carbon.
Cost-effective off-grid automatic precipitation samplers for pollutant and biogeochemical atmospheric deposition
Alessia A. Colussi, Daniel Persaud, Melodie Lao, Bryan K. Place, Rachel F. Hems, Susan E. Ziegler, Kate A. Edwards, Cora J. Young, and Trevor C. VandenBoer
Atmos. Meas. Tech., 17, 3697–3718, https://doi.org/10.5194/amt-17-3697-2024, 2024
A new modular and affordable instrument was developed to automatically collect wet deposition continuously with an off-grid solar top-up power package. Monthly collections were performed across the Newfoundland and Labrador Boreal Ecosystem Latitudinal Transect of experimental forest sites from 2015 to 2016. The proof-of-concept systems were validated with baseline measurements of pH and conductivity and then applied to dissolved organic carbon as an analyte of emerging biogeochemical interest.
Modeling biochar effects on soil organic carbon on croplands in a microbial decomposition model (MIMICS-BC_v1.0)
Mengjie Han, Qing Zhao, Xili Wang, Ying-Ping Wang, Philippe Ciais, Haicheng Zhang, Daniel S. Goll, Lei Zhu, Zhe Zhao, Zhixuan Guo, Chen Wang, Wei Zhuang, Fengchang Wu, and Wei Li
Geosci. Model Dev., 17, 4871–4890, https://doi.org/10.5194/gmd-17-4871-2024, 2024
The impact of biochar (BC) on soil organic carbon (SOC) dynamics is not represented in most land carbon models used for assessing land-based climate change mitigation. Our study develops a BC model that incorporates our current understanding of BC effects on SOC based on a soil carbon model (MIMICS). The BC model can reproduce the SOC changes after adding BC, providing a useful tool to couple dynamic land models to evaluate the effectiveness of BC application for CO2 removal from the atmosphere.
Hector V3.2.0: functionality and performance of a reduced-complexity climate model
Kalyn Dorheim, Skylar Gering, Robert Gieseke, Corinne Hartin, Leeya Pressburger, Alexey N. Shiklomanov, Steven J. Smith, Claudia Tebaldi, Dawn L. Woodard, and Ben Bond-Lamberty
Geosci. Model Dev., 17, 4855–4869, https://doi.org/10.5194/gmd-17-4855-2024, 2024
Hector is an easy-to-use, global climate–carbon cycle model. With its quick run time, Hector can provide climate information from a run in a fraction of a second. Hector models on a global and annual basis. Here, we present an updated version of the model, Hector V3. In this paper, we document Hector’s new features. Hector V3 is capable of reproducing historical observations, and its future temperature projections are consistent with those of more complex models.
RoadSurf 1.1: open-source road weather model library
Virve Eveliina Karsisto
Geosci. Model Dev., 17, 4837–4853, https://doi.org/10.5194/gmd-17-4837-2024, 2024
RoadSurf is an open-source library that contains functions from the Finnish Meteorological Institute’s road weather model. The evaluation of the library shows that it is well suited for making road surface temperature forecasts. The evaluation was done by making forecasts for about 400 road weather stations in Finland with the library. Accurate forecasts help road authorities perform salting and plowing operations at the right time and keep roads safe for drivers.
