bluuebunny/crossref_metadata_2025 huggingface dataset:
Lessons learned from 15 years of TERENO: the integrated TERrestrial ENvironmental Observatories in Germany
Authors: Zacharias Steffen , Blume Theresa , Bogena Heye , Kiese Ralf , Borg Erik , Dietrich Peter , Liebner Susanne , Schmid Hans Peter , Schrön Martin , Vereecken Harry
Published: March 2024

The need to develop and provide integrated observation systems to better understand and manage global and regional environmental change is one of the major challenges facing Earth system science today. In 2008, the German Helmholtz Association took up this challenge and launched the German research infrastructure TERrestrial ENvironmental Observatories (TERENO). The aim of TERENO is to establish and to maintain a network of observatories as a basis for an interdisciplinary and long-term research programme to investigate the effects of global environmental change on terrestrial ecosystems and their socio-economic consequences. State-of-the-art methods from the field of environmental monitoring, geophysics, and remote sensing are used to record and analyze states and fluxes in different environmental compartments from groundwater through the vadose zone, surface water, and biosphere, up to the lower atmosphere. To date, four observatories are part of the network, and over the past 15 years we have gained collective experience in running a long-term observing network, thereby overcoming unexpected operational and institutional challenges, exceeding expectations and facilitating new research. Today, the TERENO network is a key pillar for environmental modelling and prediction in Germany, an information hub for regional stakeholders, a nucleus for international collaboration, an important anchor for large-scale experiments, and a trigger for methodological innovation and technological progress. We will present the main lessons learned from this 15-year endeavour, and illustrate the need to continue long-term integrated environmental monitoring programmes in the future.
Evaluation of inter-calibration approaches for the GEMS Level 1B product
Authors: Lee Yeeun , Ahn Myoung-Hwan , Kang Mina , Eo Mijin , Moon Kyung-jung , Kim Jhoon
Published: March 2024

To meet the growing demand for diurnal information on trace gases and aerosols in the atmosphere, a series of satellite programs consisting of the GEO-ring (GEO-constellation) has been initiated. The series started off with the launch of the Geostationary Korean Multi-Purpose Satellite-2B (GK-2B) in 2020, followed by the Tropospheric Emissions: Monitoring of Pollution (TEMPO) in 2023 and the expected launch of Sentinel-4 in 2024. Onboard GK-2B, the Geostationary Environment Monitoring Spectrometer (GEMS) is dedicated to observing the Asia-Pacific region, providing spectral radiance in the 300-500 nm range to obtain specific spectral information on absorption and scattering lines. To evaluate the post-launch data quality of GEMS, especially for Level 1B products, this study utilizes inter-calibration approaches with the measurements from geostationary as well as polar orbit satellite sensors. The evaluation comprises two parts to address current and potential calibration issues of GEMS: 1) applying the ray-matching approach with the Advanced Meteorological Imager (AMI) onboard the twin satellite, GK-2A; and 2) employing vicarious calibration with polar orbit satellite sensors, Tropospheric Monitoring Instrument (TROPOMI) and Ozone Mapping and Profiler Suite (OMPS), targeting stable scenes on Earth. In the first approach, AMI and GEMS demonstrate a strong agreement, showing a high correlation coefficient exceeding 0.9 regardless of measurement time and season. However, the GEMS Level 1B product reveals a positive bias when compared to AMI, 10% and 5% for radiance and reflectance, respectively. The GEMS measurements also display distinct seasonal and diurnal variations compared to AMI, which needs further investigation considering that the variations could influence the Level 2 retrieval products of GEMS. In the second approach, GEMS shows residual stray light effect especially at the shorter wavelengths (below 320 nm) and quantitatively, GEMS shows a consistent bias with the first approach, when compared to TROPOMI and OMPS. The paper aims to provide valuable insights for the efficient monitoring of sensors under comparable conditions with GEMS, along with remaining challenges emphasizing the need for refined approaches to address the radiometric calibration accuracy of the GEMS Level 1B product.
Bacterial necromass is more responsive to global change than fungal necromass
Authors: Wu Wenao , Zhu Biao
Published: March 2024

As an important component of soil organic matter (SOM), soil microbial necromass largely determines the dynamics of SOM under global change. However, the response of soil microbial necromass to global change is not well understood. Hence, this study conducted a meta-analysis to assess the global response of soil microbial necromass to warming, altered precipitation, nutrient addition, and elevated CO2. Results showed that global change had no significant effects on total necromass carbon (TNC) and fungal necromass carbon (FNC). However, we found that bacterial necromass carbon (BNC) was significantly responsive to warming (+9.70%), increased precipitation (+10.15%), and nitrogen (N) addition (+8.62%). Furthermore, the response of BNC could be regulated by ecosystem types, climate factors, soil properties, and experimental conditions, but the influencing factors under different global change factors could be different. Correlation analysis suggested that the response of BNC was associated with the change of soil pH under warming, while it had a positive correlation with the response of soil microbial biomass carbon under N addition. Overall, this study contributes to the understanding of how soil microbial necromass responds to global change on a global scale, and emphasizes the important role of BNC in SOC dynamics under global change.
Mid Holocene relative sea-level changes from coral microatolls of Pulau Biola, Singapore 
Authors: Quye-Sawyer Jennifer , Yeo Jing Ying , Neo Wan Lin , Aw Zihan , Aung Lin Thu , Tan Nurul Syafiqah , Komori Junki , Lin Ke , Wang Xianfeng , Meltzner Aron J.
Published: March 2024

Coral microatolls are precise proxies of relative sea-level (RSL) change in low-latitude coastal regions. These coral colonies live in the intertidal zone where partial mortality due to low-water events produces a characteristic planform ring structure. Since ring elevations reflect changes in local RSL during a coral’s lifetime, we can use the surface profiles of microatolls to quantify short-term (decadal) rates of RSL change. Therefore, Holocene fossil microatolls can produce sea-level index points (SLIPs) with relatively high spatial and temporal resolution. In this study, we present preliminary sea-level reconstructions from Pulau Biola (Violin Island), Singapore, based upon several Porites sp. and Diploastrea heliopora fossil microatolls. We calculated the difference in elevation between the fossils and local living microatolls of the same genus to quantify the magnitude of past water level. We also combined U-Th ages, structure-from-motion photogrammetry and LiDAR 3D models, and survey data to generate a RSL history spanning more than two centuries in the mid Holocene. The highest-elevation fossil microatolls at Pulau Biola are consistent with an overall rise in sea level, from 0.2 to 0.7 m above present, between 7.7 and 7.4 kyr BP. In addition, decimetre-scale sea-level fluctuations during this period are inferred from decreasing and increasing ring elevations within corals. These fluctuations indicate a more complex sea-level history than resolved by other proxies or glacial isostatic adjustment models, and ongoing work aims to reconcile conflicting Holocene sea-level models and datasets in the Singapore region.
Upper Mantle Heterogeneity Recorded by Microstructures and Fluid Inclusions from Peridotite Xenoliths Beneath the Rio Grande Rift, USA
Authors: Park Munjae
Published: March 2024

Mantle heterogeneity is closely related to the distribution and circulation of volatile components in the Earth’s interior, and the behavior of volatiles in the mantle strongly influences the rheological properties of silicate rocks. In mantle xenoliths, these physicochemical properties of the upper mantle can be recorded in the form of microstructures and fluid inclusions. In this paper, I summarized and reviewed the results of previous studies related to the characteristics of microstructures and fluid inclusions from peridotite xenoliths beneath the Rio Grande Rift (RGR) in order to understand the evolution and heterogeneity of upper mantle. In the RGR, the mantle peridotites are mainly reported in the rift axis (EB: Elephant Butte, KB: Kilbourne Hole) and rift flank (AD: Adam’s Diggings) regions. In the case of the former (EB and KB peridotites), the type-A lattice preferred orientation (LPO), formed under low-stress and low-water content, was reported. In the case of the latter (AD peridotites), the type-C LPO, formed under low-stress and high-water content, was reported. In particular, in the case of AD peridotites, at least two fluid infiltration events, such as early (type-1: CO2-N2) and late (type-2: CO2-H2O), have been recorded in orthopyroxene. The upper mantle heterogeneity recorded by these microstructures and fluid inclusions is considered to be due to the interaction between the North American plate and the Farallon plate.
Predictability of Metabolic index and its application to fish catch prediction
Authors: Choi Hwa-Jin , Park Jong-Yeon , Stock Charles
Published: March 2024

Climate change has caused shifts in the abundance, geographic distribution, and phenology of marine species. Spatial shifts of species due to global warming will cause a high local extinction rate and decrease fisheries catch and species richness at tropical latitudes. Predicting the migration of marine organisms in response to climate change holds significance not just from an ecological perspective, but also from an economic standpoint in terms of effectively managing marine living resources. This study investigates the predictability of metabolically viable habitats by utilizing an Earth system model (ESM) that incorporates a coupled physical-biogeochemical prediction system. The metabolic index, previously defined with dissolved oxygen and temperature, has a higher predictability compared to temperature, particularly in the subsurface tropics. The primary factor contributing to the high predictability of the metabolic index is the longer persistency of lateral oxygen advection at the boundary of the tropical oxygen minimum zone. Further investigations indicate that the interannual fluctuations in the catch of bigeye tuna within the exclusive economic zones (EEZs) in tropical regions can be predicted based on the metabolic index forecasted one year ahead, implying the potential application of ESM-based physiological prediction to dynamic management of marine living resources.
Time Varying Copula based formulations for Flood Risk Assessment of two Tropical basins of Kerala, India
Authors: Sankaran Adarsh , Mohan Meera G , Raj Ananya , Shaji Anagha
Published: March 2024

Flood frequency analysis is a challenging but essential hydrologic problem for design of control structures and water resources management. The design flood estimates based on traditional stationary assumption may lead to inaccurate estimation of flood risk because of non-stationarity and the compounding impacts of several drivers in a dynamic environment. Copulas are a useful and adaptable technique for determining the multivariate joint dependency amongst flood variables. This study employed time-varying copula models to investigate the nonstationary dependence structures between two highly correlated flood variables, such as flood peak and flood volume, in order to determine the joint and conditional return periods of the flood events revealed by the 2018 Great Kerala floods. The proposed approach is executed for two potential locations of high flood risk namely, Periyar river basin and Greater Pamba river basin of Kerala, India. The Archimedean copula (Clayton, Frank and Gumbel) parameters were estimated using Maximum likelihood estimation and the optimal copula selection was made using Akaike Information Criterion. The non-stationary joint return time was found to be shorter than the stationary joint return period, suggesting that the extreme flood occurrences happened more frequently in the non-stationary bivariate study. Thus, it can be demonstrated that the extreme flood episodes are underestimated by stationary bivariate flood frequency analysis. The validation of results by comparing the flood magnitude of Neeleswaram station for 2018 flood quantile ascertained the necessity of non-stationary flood risk estimation. The study advocates the conduct of multivariate frequency analysis over the univariate analysis for the risk assessment of hydrological extremes. The results demonstrate that the long-term decision-making methods need to be updated to account for the oddities of the nonstationary climate. This study rendered flood risk assessment indicators as well as a risk-based design approach for hydraulic infrastructures in a non-stationary environment, which is crucial for climate change adaption and water security management.
Transfer learning for reservoir operation based on regional model and large-scale dataset
Authors: Zheng Yalian , Liu Pan , Cheng Qian , Liu Weibo , Xu Huan , Lei Hongxuan , Luo Xinran
Published: March 2024

A regional spatial transfer learning method is proposed to map the attributes of reservoirs and their operating decisions, addressing the issue of poor transfer-ability of reservoir operating models. Firstly, a dataset of reservoir attributes and operating data is constructed, including a total of 503 reservoirs in China and the United States. The 503 reservoirs are divided into source reservoirs (rich data reservoirs) and target reservoirs (data-scarce reservoirs) based on a five-fold cross-validation method. A regional spatial transfer learning method is established to map the attributes of reservoirs and their operating strategies. After training the model network parameters, a generalized reservoir operating model is formed. The information of data-scarce reservoirs is input into the generalized reservoir operating model to achieve adaptive dynamic transfer of reservoir operating strategies. Deep learning interpretability techniques are used to analyze the relationship between static attribute features of reservoirs and the performance of transfer learning. Results show: (1) The generalized reservoir operating model, which maps the static attribute features of reservoirs to reservoir operating decisions, can achieve spatial transfer of operating decisions. After five-fold cross-validation, the average Nash-Sutcliffe Efficiency (NSE) for reconstructing operating decisions of data-scarce reservoirs is 0.69. By evaluating the deviation between the transferred operating decisions and real-world operating decisions of the 503 reservoirs, it is found that 337 reservoirs, accounting for 67.0% of all reservoirs, have an NSE higher than 0.6. (2) Reservoir attribute features can enable the model to explore the relationship between operating decisions of reservoirs with similar features. Among the 503 reservoirs, 288 reservoirs show better transfer learning performance considering static attribute features. (3) Deep learning interpretability techniques are used to analyze the relationship between the transfer learning performance and the static attribute features of reservoirs. The most important factors affecting the transfer learning performance are long-term average discharge at dam location, longitude of point location of dam, area of upstream catchment draining into the reservoir, and maximum storage capacity of reservoir, which explain 31.1%, 11.3%, 10.0%, and 7.2% of the transfer learning model's performance, respectively.
Projecting Changes in the Drivers of Compound Flooding in Europe Using CMIP6 Models
Authors: Hermans Tim , Busecke Julius , Wahl Thomas , Malagón-Santos Víctor , Tadesse Michael , Jane Robert , van de Wal Roderik
Published: March 2024

When different flooding drivers co-occur, they can cause compound floods. Despite the potential impact of compound flooding, few studies have projected how the joint probability of flooding drivers may change. Furthermore, existing projections are based on only 5 to 6 climate model simulations because flooding drivers such as storm surges and river run-off need to be simulated offline using computationally expensive hydrodynamic and hydrological models. Here, we use a large ensemble of simulations from the Coupled Model Intercomparison Project 6 to project changes in the joint probability of extreme storm surges and precipitation in Europe under a medium and high emissions scenario. To compute storm surges for so many simulations, we apply a statistical storm surge model trained with tide gauge observations and atmospheric forcing from the ERA5 reanalysis. We find that the joint probability of extreme storm surges and precipitation will increase in the northwest and decrease in most of the southwest of Europe. On average, the absolute magnitude of these changes is 36% to 49% by 2080, depending on the scenario. We show that due to internal climate variability and inter-model differences, projections based on small climate model ensembles can differ qualitatively depending on the specific simulations included. Therefore, our results provide a more robust and less uncertain representation of changes in the potential for compound flooding in Europe than previous projections.
Chinese nationwide earthquake early warning system and its performance during several M6.0+ earthquakes occurred in 2022-2023
Authors: Peng Chaoyong , Jiang Peng , Ma Qiang
Published: March 2024

As one of the most earthquake-prone regions in the world, China faces extremely serious earthquake hazards, especially for those heavily populated urban areas located near major fault zones. In order to improve the ability to prevent and minimize the risk of earthquake disasters, and to reduce the losses caused by earthquakes, China is currently building a nationwide earthquake early warning system (EEWS) with more than 18,000 seismic stations. Here, we present the recent progress of this project by describing the overall architecture of the national EEWS and evaluating the system performance during four M6.0+ earthquakes that occurred within the seismic network between 2022 and 2023. The accuracy of the source characterization for these earthquakes is discussed by comparing the continuously estimated location and magnitude with the catalogs obtained from the China Earthquake Networks Center. For each earthquake, the EEWS usually generated more than one alert, and the initial alert was created about 5~8 s after its occurrence, with excellent estimates of epicentral location and origin time. In terms of magnitude estimation, the deviation for each event was relatively large at the first alert, but gradually decreased until it approached the catalog value. However, from the point view of alerting performance, the radius of the real blind zone without warning time was about 30 km and much larger than the theoretical result, mainly caused by the releasing system not considering the epicenter distance of each terminal when issuing the alerts. Although these earthquakes revealed some limitations that need to be addressed in future upgrades, the results showed that most aspects of the EEWS demonstrated robust performance, with continuous, reliable event detection and early-warning information releasing.
Importance of biophysical forcing of global land cover to local precipitation and water vapor budget on the Loess Plateau of China
Authors: Qiu Linjing
Published: March 2024

Land use and cover change (LULCC) is an important climatic forcing. However, it is challenging to quantify the responses of local precipitation to LULCC forcing due to the complex interaction between the land surface and atmosphere. The ecologically fragile Loess Plateau (LP) of China has experienced evident changes in precipitation patterns, but the underlying mechanism remains unclear. The biophysical effects of LULCC on precipitation and the water vapor balance in the LP region were quantified based on the LULCC forcing experiments from the sixth phase of the Coupled Model Intercomparison Project (CMIP6). We found that the selected 11 Earth system models (ESMs) reproduced the general spatial pattern of annual precipitation on the LP region, with slight overestimation in the southern LP. The multimodel ensemble (MME) average showed that global LULCC forcing exerted a negative effect on long-term mean precipitation in this region during the period of 1850-2014. In particular, it decreased evidently during the period from 1850 to 1960, with a reduction of approximately 14.1 mm. However, a positive effect was detected for the period of 1961-2014, with an increase of 6.4 mm in annual precipitation. This is largely related to the intensified water vapor transport in the southern boundary and westerly belt of the LP region resulting from global LULCC forcing. Furthermore, water vapor balance analysis showed that global LULCC forcing resulted in a divergence in water vapor transport within the LP region, leading to a net water vapor output to the surrounding regions. These findings highlight the importance of considering global LULCC, in addition to regional LULCC, in studying regional climate change and associated impacts on the water cycle.
Micro-windows to deep COH-rich planetary fluids and associated mantle processes
Authors: Weiss Yaakov
Published: March 2024

Metasomatism, a process whereby infiltrating fluids and melts rich in trace elements and volatiles interact and alter mantle rocks is a common mantle process, as reflected by the mineralogy and chemical composition of mantle-derived samples from all continents. However, the metasomatic agent itself is only rarely available as fluid/melt inclusions for direct analyses; and thus, in many cases, the nature of metasomatism remains elusive.High-density fluid (HDF) microinclusions in diamonds provide a unique record of the compositions and nature of deep mantle carbon- and water-bearing (COH) fluids. Their high volatile content: 8-20 wt.% H2O and 4-32 wt.% CO2, and their enrichment in incompatible elements make them a key player in mantle metasomatism. The most common HDFs vary in compositions between four major types: silicic, rich in Si, Al, K and water; low- and high-Mg carbonatitic, rich in Ca, Mg, Fe, K and carbonate; and saline, rich in Cl, K, Na and water. Few lines of evidence indicate the relation of saline HDFs and subducted surface material: their K/Cl ratio overlaps the range of altered oceanic crust; pronounced positive Eu and Sr anomalies reflect the involvement of plagioclase during low-pressure crustal processes of protolith formation; and, low 3He/4He isotope ratios (2.7–4.4 Ra) further strengthen a connection with recycled surface material. In addition, recent radiogenic isotope data points to the involvement of distinct mantle sources and subducted components in the formation of varying HDF types. For example, the isotopic composition of silicic to low-Mg carbonatitic HDFs in a suite of diamonds from Canada indicate the contribution of two distinct sources within the continental lithosphere: one with relatively primitive isotopic compositions characterized by εNd of −0.2, 87Sr/86Sr of 0.7044 and 206Pb/204Pb of 17.52, and another with more unradiogenic εNd < −16 and radiogenic 87Sr/86Sr and 206Pb/204Pb > 0.713 and 18.3, respectively. The latter reflects an old metasomatic event in the continental lithosphere involving fluid addition from a subducting slab, most probably in the Paleoproterozoic. In comparison, isotopic compositions of HDFs in South African diamonds suggest that saline HDFs record the involvement of metasomatized Archaean lithosphere and subducting surface material that includes recent sediments.HDFs are the deepest mantle fluids we have at hand. Due to their high mobility, they can migrate and react with different mantle lithologies over a range of depths. Such HDFs-rock interaction leads to the formation of new metasomatic phases and enriches depleted mantle rocks in volatile and incompatible elements, thereby impacting their density, rheology and melting behavior. Indeed, the mineralogy and chemical composition of xenoliths/xenocrysts and some alkaline magmas suggest a prevalent role of HDFs in mantle metasomatism and deep Earth processes.
Insights into Subsurface Stormflow Dynamics using multitracer approaches
Authors: Pyschik Jonas , Kuleshov Alexey , Fasching Christina , Chifflard Peter , Blume Theresa , Hopp Luisa , Weiler Markus
Published: March 2024

Subsurface stromflow (SSF) is an important runoff generation mechanism in hillslope catchments. However, since the process occurs below ground, it is difficult to observe and measure. So far, the dynamics and thresholds of SSF occurrence remain elusive.To gain insights into the mechanisms and to determine SSF quantities and their dynamics, we installed three SSF trenches in a first-order catchment in the Black Forest, Germany. We selected hillslopes with different landuse and topography and excavated slope-perpendicular trenches to bedrock (approx. 15 m wide, 2.5 m deep). The trenches are split by soil depth to collect subsurface flow from a top and from a bottom layer. The flow is channeled to tipping buckets for measuring discharge, and autosamplers for semi-continuous water sampling. The water samples are then used to measure multi tracers like stable water isotopes, dissolved organic carbon as well as major anions and cations.In November and December 2023, the catchment experienced three extreme, multi-day rainfall events. The generated subsurface discharge showed distinct differences in volume among the trenches (up to 100% of upslope-area-corrected flow volume). Most flow (70-90%) occurred in the lower trench sections. Top layer flow was only activated during peak discharge in the bottom layer. Using the multitracer approach, we can gain first insights into the dynamics of the different natural tracers and relate them to the observed subsurface flow variations, possible flow pathways and transit times. Ultimately, we aim to compare these findings to data from three other trenched research catchments to gain a more general understanding of the underlying subsurface stormflow generation mechanisms.
Under threat from climate change Türkiye's alkaline lakes are alarming
Authors: Balci Nurgul
Published: March 2024

Under threat from climate change Türkiye's alkaline lakes are alarmingLakes district of Turkey, located in the southwest, host the majority of the Turkish lakes. These lakes (Acıgol, Yarisli, Burdur and Salda) are not only valuable for their unique water chemistry but also for their role in supporting biodiversity and serving as important habitats for various species, especially birds. The impact of climate change, alongside human activities like uncontrolled land use and agriculture, is visibly altering these crucial ecosystems. The decrease in annual precipitation in the Aegean and Mediterranean regions, coupled with overall global climate changes, is directly affecting the water levels of the lakes. The drying out of approximately 1.5 million hectares of Turkish wetlands over the last century highlights the severity of the situation. Preserving these lakes is crucial not only for their ecological significance but also for their potential analogs, like Lake Salda, which offer invaluable insights into understanding geological landscapes similar to those found on other planets, such as Mars. Addressing these challenges requires urgent action. Strategies to mitigate the impact of climate change and implementing sustainable land use practices, are essential. Additionally, regulate and manage anthropogenic activities (e.g., agriculture and land use) around the lakes can help alleviate the pressure on these fragile ecosystems. Conservation efforts, combined with public awareness and policy changes, can play a vital role in protecting these lakes and preventing further deterioration. 
The GOME-type Tropical Tropospheric Ozone Essential Climate Variable (GTTO-ECV) satellite data record between 1995 and 2023
Authors: Heue Klaus-Peter , Loyola Diego , Coldewey-Egbers Melanie , van Gent Jeroen , van Roozendael Michel , Hubert Daan
Published: March 2024

A tropospheric ozone Climate Data Record from 1995 until end 2023 has been generated within ESA’s Climate Change Initiative programme. The GOME-type Tropical Tropospheric Ozone Essential Climate Variable (GTTO-ECV) satellite data record combines data from GOME, SCIAMACHY, OMI, the three GOME-2 missions and TROPOMI. The retrieval is based on the Convective Cloud Differential technique, which limits the coverage to the tropical belt (20°S to 20°N). We generated two monthly mean data sets at 1° x 1° resolution: one corresponds to a tropospheric column up to 200 hPa as in the previous CCI data release (Heue et al., 2016), while the other is limited to 270 hPa this pressure level is used in the operational S5P data set. Besides a consistent reprocessing of the CCD data for individual sensors, we also updated the harmonising scheme. The mean bias as well as the mean annual cycle relative to the reference instrument (OMI) are used to correct for the differences between the sensors.Heue et al (2016) inferred a mean tropospheric ozone trend of +0.7±0.1 DU/decade (1995-2015) from the previous GTTO-ECV version. Did the trend change with the extended and improved data set? The GTTO-ECV data record will be used to investigate the tropical mean trend as well as temporal and local changes in the trends or extreme events.
The development of the Koreans’ climatic index for tourism (KCIT)
Authors: Park Sookuk , Jo Sangman , Choi Yuri , Moon Jeonghyeon
Published: March 2024

To develop the Koreans’ climatic index for tourism (KCIT) in the four tourism and recreation types (cultural tourism, beach walking, Oreum/light climbing, and Olle/tracking), this study conducted comprehensive microclimatic data collection and surveys throughout the four seasons of 2022-2023 in Jeju, Republic of Korea. The research involved expert opinions and insights from 26 experts and 1,860 tourists in cultural tourism, 15 and 511 in beach walking, 28 and 603 in Oreum, and 14 and 234 in Olle. The collected microclimatic data included air temperature, relative humidity, wind speed, and shortwave and longwave radiation, concurrently gathered with tourist surveys. The KCIT comprises 7 scales, ranging from very poor to ideal, and is composed of three critical aspects: thermal, aesthetic, and physical. The thermal aspect analyzed human thermal sensation across 9 ASHRAE scales, from very hot to very cold, utilizing physiological equivalent temperature. It revealed that a consistent optimal range was from neutral to slightly cool across the four tourism and recreation types. The possible range of all tourism and recreation was from hot to cold, and the difficult range was very hot and very cold. The aesthetic aspect evaluated cloud cover, establishing an optimal range of clear or less cloudy conditions (30-50%) for all tourism and recreation types, while beach walking displayed a preference for clearer skies. Wind speed, a physical aspect, indicated an optimal range of a gentle breeze, 1.4-3.4 ms-1, with variations observed across tourism and recreation types. The possible range was from 0 to 7.5 ms-1 in cultural tourism and from 0 to 5.5 ms-1 in the others. The difficult range was from 7.5 ms-1 in cultural tourism and 5.6 ms-1 in the others. Precipitation, another physical aspect, revealed optimal, possible, and difficult ranges of 0 mmhr-1, 0.1-5.0 mmhr-1, and more than 5.1 mmhr-1, respectively. The study highlights the versatility of the KCIT scale, offering a user-friendly tool for tourists and tour companies. Additionally, it presents valuable insights for local governments in shaping future tourism plans. This ongoing research is set to continue exploring other tourism and recreation aspects in 2024.
Which type of WNPSH indices can be better applied, defined by the geopotential height, the eddy geopotential height, or the stream function?
Authors: Li Deqian , Hu Shujuan
Published: March 2024

The western North Pacific subtropical high (WNPSH) is a crucial circulation system affecting weather and climate over China. To quantitatively measure its strength and spatial pattern, the geopotential height was firstly used to define WNSPH indices (H indices). However, due to global warming, the H indices have shown significant increasing trends in recent decades, causing some disturbance to reveal the interdecadal variation of WNPSH. Then, the eddy geopotential height (He indices) and stream function (R indices) have been successively used to redefine WNPSH indices to reflect the WNPSH’s actual interdecadal variation. Here, for further understanding the performances of these three types of WNPSH indices in the interannual variability, some comparisons have been made by using various statistical methods and machine learning models. The results show that, in the statistical characteristics, the He and R indices have normal distributions and are stationary time series with no systematic changes over time, while the H indices do not. Regarding the indication for summer precipitation in eastern China, the R indices perform well generally, but the other two types of indices are better in indicating regional precipitation. Also for predictability, the temporal correlation coefficients between the prediction results and the R indices are above 0.80, the same as the H indices which are used in operational applications until now. Overall, the R indices have obvious advantages whatever statistical characteristics or indication for precipitation. Using R indices as a benchmark to further improve indication of regional precipitation can provide more references for future operational applications. 
Response of the northward heat transport depends on regional anthropogenic aerosol effects in CMIP
Authors: Varma Vidya , Fiedler Stephanie
Published: March 2024

Past decades witnessed strong spatial changes in the emissions of anthropogenic aerosols and their precursors resulting in a global redistribution of maxima in the anthropogenic aerosol optical depth. This study investigates the response of the circulation to the different anthropogenic aerosol patterns around the 1970s and 2000s with focus on the meridional heat transport. Our analysis uses 309 historical model experiments of the Coupled Model Intercomparison Project Phase 6 and 94 single-forcing experiments for anthropogenic aerosols from the Detection and Attribution Model Intercomparison Project (DAMIP). We substantially reduce the influence of internal variability by computing multi-model multi-realization means and additional averaging over time periods of 15 years. The results highlight the influence of anthropogenic aerosol radiative effects on the total northward heat transport. Around the 1970s, most anthropogenic aerosols were located over Europe, North America and the North Atlantic. At that time, the anthropogenic aerosol increase explains almost half of the total change in the summertime northward heat transport in the tropics compared to pre-industrial times. In polar regions, the anthropogenic aerosols around the 1970s counteracted the induced response of the northward heat transport to greenhouse gas forcing. It suggests that changes induced by the aerosol pattern until the 1970s delayed the increase in Arctic warming in CMIP6, later known as Arctic amplification. The later change in the anthropogenic aerosol pattern between the 1970s and the 2000s led to different hemispheric asymmetries in the anthropogenic aerosol optical depth and hence the reflected shortwave radiation. Due to the associated different regional radiative effect, the change in the summertime northward heat transport in the polar region is now qualitatively similar for anthropogenic aerosols and greenhouse gas forcings for the 2000s against the 1970s. Specifically, the heat transport to the Arctic during summer increases for the 2000s compared to the 1970s consistent with emergence of Arctic amplification in the late 1970s.   
Impacts of Interannual Climate Variability on Direct and Virtual Water Shortage Risks in China
Authors: Wang Yaoping , Cao Tao , Zhang Shuo , He Xiaogang
Published: March 2024

Water scarcity can have far-reaching sectoral impacts beyond where it physically occurred through the propagation of virtual water flows. Both fast (e.g., interannual meteorological variability) and slow physical processes (e.g., phase changes in sea surface temperature [SST] modes) can affect water availability and use, leading to changes in both direct and virtual water scarcity. In this study, we use a two-stage regression to investigate how interannual meteorological variability and SST-phase changes contribute to variations in water shortage in China, both locally (through the Local Water Scarcity Risk index, LWSR) and remotely (through the Virtual Water Scarcity Risk index, VWSR). More specifically, LWSR and VWSR are estimated using the regression-based water stress indices and agricultural water uses under varying meteorological forcings and SST phases, holding the region-by-sector input-output relationships constant. Our findings indicate that interannual meteorological variability affects LWSR on the order of 10–1000% and VWSR on the order of 10% in most sectors and provinces, with a limited portion of impacts attributable to SST-phase changes. In particular, the positive phase of the second investigated SST mode results in significantly higher (on the order of 5%) LWSR and VWSR for nearly all sectors and provinces compared to the negative phase. These results highlight the importance of using longer time series to accurately assess local and virtual water scarcity situations. Decision makers in susceptible provinces and sectors should consider interannual variabilities in LWSR and VWSR and plan for potential occurrences of extreme conditions.
Intensive photochemical oxidation in the marine atmosphere: Evidence from direct radical measurements
Authors: Hu Renzhi , Zhang Guoxian , Xie Pinhua , Liu Wenqing
Published: March 2024

Measurement of OH and HO2 radicals was conducted at a coastal site in the Pearl River Delta in October 2019. The mixing of air masses of continental and marine origins can lead to more variability in radical concentrations. In the ocean-atmosphere period (OCM), the observed OH and HO2 radicals could be reflected by the RACM2-LIM1 chemical mechanism. However, the heterogeneous uptake process has a certain effect on the HOx radical chemistry, but the influence of the halogen mechanism is limited due to the NOx level. Land mass (LAM) was associated with a higher net ozone generation rate (5.52 ppb/h), and the daily maximum OH and HO2 concentrations were 7.1 × 106 cm−3 and 5.2 × 108 cm−3, respectively. Rapid oxidation process was accompanied by a higher diurnal nitrous acid (HONO) concentration (> 400 ppt). The particularity of HONO chemistry increases the ozone generation rate of the coastal atmosphere by ~40%. Without HONO constraint, simulated ozone concentration drops from ~75 ppb to a global background (~35 ppb). Therefore, the promotion of oxidation by elevated precursors deserves a lot of attention when aiding pollution mitigation policies.
pyBL: an open source Python package for fine-scale rainfall modelling with short records based upon a Bartlett Lewis model
Authors: Wang Li-Pen , Wei Chi-Ling , Chen Pei-Chun , Tseng Chien-Yu , Dai Ting-Yu , Ho Yun-Ting , Chou Ching-Chun , Onof Christian
Published: March 2024

Bartlett-Lewis (BL) model is a stochastic model that represents rainfall based upon the theory of Poisson cluster point process. It had been used for daily and hourly stochastic rainfall time series modelling for over 30 years. It was however known to underestimate sub-hourly rainfall extremes until some recent advances, where this shortcoming has been overcome. It could therefore serve as an alternative to the existing rainfall frequency analysis methods based upon, for example, annual maxima time series.The implementation of the BL model is however a non-trivial task. The formulation of the BL model is of high complexity, and the calibration of the model parameters constitutes a nonlinear optimisation process with high numerical instability. This hinders the widespread use of the BL model. Another computational challenge of BL modelling lies in sampling. In particular, when using this type of rainfall generators, it often requires sampling a large number of long-term realisations.In this work, with the purpose of promoting BL model and of demonstrating its capacity in modelling sub-hourly rainfall (both standard and extreme statistics), we have initiated an open source Python library for the BL model: pyBL, where a set of data structures and algorithms are designed specifically for the BL model, making the fitting and sampling processes more efficient and lightweight in terms of memory. In particular, one of our designs is a lossless time series compression method that perfectly suits BL model and a set of algorithms and can calculate statistical properties without any decompression. Additionally, we have implemented user interfaces and packaging at various levels, making experimental adjustments and optimisation methods more flexible and concise.Finally, two scientific experiments resembling real-world scenarios were conducted here to demonstrate pyBL's capacity of modelling sub-hourly rainfall extremes with short records, as well as flexibility of utilising records at various resolutions and with various data lengths. We show that, with the help from the BL model, we can well model hourly and sub-hourly rainfall extremes with merely half data length required by the widely-used Annual Maxima method.
Reservoir lakes in the Upper Harz Mountains (Germany): GIS Implementation and hydrochemical development
Authors: Schäfer Tanja , Bozau Elke , Hutwalker Alexander
Published: March 2024

Dam reservoirs were used for the continuous water supply to the ore mines in the Upper Harz Mountains. The first reservoirs were built in the 16th century. The dam heights reach up to 15 m and the stored water volumes are between 10,000 and 600,000 m3. There are about 70 of such lakes around Clausthal-Zellerfeld now. Hydrogeochemical data of the lakes have been investigated for about ten years (Bozau et al., 2015). A data management system combining GIS and hydrochemical data is prepared to facilitate data collection and interpretation.The specific electrical conductivity (SEC) of the lake water ranges between approx. 30 and 280 µS/cm and can be used for the classification of these lakes. SEC lower than 50 µS/cm are typical for lakes mainly filled by rain water. SEC higher than 200 µS/cm are found in lakes near urban and anthropogenic influences. Due to the long dry periods of the last years an increase of the SEC is seen in the majority of lakes especially between spring 2015 and 2023. Because of extraordinary high precipitation in autumn 2023 this trend stagnates or even decreases in some lakes, but is still observable in the comparison between autumn 2015 and autumn 2023.Especially those lakes with catchment areas strongly changed by forest decline are expected to show higher values of the SEC. In order to investigate this, spatial comparison with forest damage maps is planned. Furthermore, the concentrations of main ions will be investigated in addition to SEC values. Nitrate and potassium concentrations of the lake water should be the most sensitive indicators for forest decline and anthropogenic influences. A first evaluation of organic trace components (Bozau et al., 2022) did not confirm the classification based on the SEC. Bozau, E., Licha, T., Stärk, H.-J., Strauch, G., Voss, I., Wiegand, B. (2015): Hydrogeochemische Studien im Harzer Einzugsgebiet der Innerste. Clausthaler Geowissenschaften, 10, 35-46.Bozau, E., Licha, T., Warner, W. (2022): Natürliche und anthropogene hydrochemische Parameter der Oberharzer Bergbauteiche. FH-DGGV-Tagung, Jena, März 2022.
Seismic interpretation of the Messinian salt of the Levant basin offshore Lebanon: new insight into the geology and tectonics of the eastern Mediterranean region
Authors: Nemer Tony , Sarieddine Karam , Faysal Reenal
Published: March 2024

Little is known about the relationship between the Messinian salt layer in the eastern Mediterranean region and the formation of the offshore tectonic structures. The objective of this study is to leverage 3D seismic reflection data from the northern Levant basin offshore Lebanon in order to map the Messinian salt layer and understand its effect on the structures around it. For that, we used current 3D time seismic reflection data to map the seafloor and the top and base of the salt layer, and we generated their corresponding bathymetric and structural maps. In addition, we generated isochron maps of the salt layer and the post-salt sedimentary section in an attempt to detect the variations in the lateral thicknesses of these layers. The presented maps helped to understand the impact of the Messinian salt deformation on the geological structures both in the pre-salt and post-salt sections. In addition, we assess the distribution and geometries of the salt structures, and discuss the thick and thin salt deposits. We also relate the movement of the Messinian salt in the subsurface to the formation of bathymetric features along the seafloor. The results enable geoscientists to have solid knowledge about the salt tectonics of the Messinian salt layer in the Levant basin, and allow hydrocarbon explorers to build on this knowledge and pursue further investigations on the hydrocarbon potential in relation to the Messinian salt deformation.
Spontaneous Dansgaard–Oeschger type oscillations in three models: the impact of CO2
Authors: Malmierca Vallet Irene , Sime Louise C. , Valdes Paul J. , Klockmann Marlene , Vettoretti Guido , Slattery John
Published: March 2024

Greenland ice core records feature Dansgaard–Oeschger (D-O) events, which are abrupt warming episodes followed by gradual cooling during ice age climate. The three climate models used in this study (CCSM4, MPI-ESM, and HadCM3) show spontaneous self-sustained D-O-like oscillations (albeit with differences in amplitude, duration and shape) in a remarkably similar, narrow window of carbon dioxide (CO2) concentration, roughly 185-230 ppm. This range matches atmospheric CO2 during Marine Isotopic Stage 3 (MIS 3: between 27.8 – 59.4 thousand of years BP, hereafter ka), a period when D-O events were most frequent. Insights from the three climate models point to NA sea-ice coverage as a key ingredient behind D-O type oscillations, which acts as a tipping point. No other climate property (NA salinity, Atlantic Meridional Overturning Circulation, Global mean Ocean temperature and Global mean temperature) is found to directly determine whether D-O type behaviour can occur in all three models.
Reconstructing Historical Climate Fields With Deep Learning
Authors: Bochow Nils , Poltronieri Anna , Rypdal Martin , Boers Niklas
Published: March 2024

Historical records of climate fields are often sparse due to missing measurements, especially before the introduction of large-scale satellite missions. Several statistical and model-based methods have been introduced to fill gaps and reconstruct historical records. Here, we employ a recently introduced deep-learning approach based on Fourier convolutions, trained on numerical climate model output, to reconstruct historical climate fields. Using this approach we are able to realistically reconstruct large and irregular areas of missing data, as well as reconstruct known historical events such as strong El Niño and La Niña with very little given information. Our method outperforms the widely used statistical kriging method as well as other recent machine learning approaches. The model generalizes to higher resolutions than the ones it was trained on and can be used on a variety of climate fields. Moreover, it allows inpainting of masks never seen before during the model training.