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A comprehensive examination of uplifted mid-late Pleistocene marine terraces along the eastern coast of Korea offers valuable insights into the temporal and spatial variability of uplift rates spanning ∼200 ka. Focusing on the Gangneung–Samcheok region of the Korean peninsula’s east coast, the study area is delineated into three distinct areas (i.e., Anin, Jeongdongjin–Donghae, and Samcheok) by two NNE-SSW to NE-SE-striking faults. Three flights of marine terraces are developed in each area, with terraces typically observed at elevations of 10 to 20 m and 20 to 35 m across all three areas. Conversely, upper terraces exceeding these elevations are mainly observed at 50 to 60 m or 60 to 80 m, with regional variations noted. Quartz optically stimulated luminescence dating (OSL) was used for dating marine terrace deposits. However, it could not be applied to older deposits beyond the upper limit of quartz OSL. Therefore, IRSL and post IR-IRSL dating using K-rich feldspar, which has a higher upper limit than quartz OSL, were applied in this study. The results indicate that marine terraces at elevations of 10 to 20 m and 20 to 35 m formed during MIS 5a and MIS 5e. Depositional ages of MIS 7 were obtained from terraces ranging from 50 to 60 m or 60 to 80 m, exhibiting elevation differences across regions. Consequently, the estimated temporal variation in uplift rates revealed an average uplift rate of 0.52–0.79 m/ka from MIS 7 to MIS 5e, followed by 0.2–0.3 m/ka after MIS 5e. Spatial variation in uplift rates was observed from MIS 7 to MIS 5e. Specifically, the uplift rate in the Jeongdongjin–Donghae area, located in the middle part of the study area, was 0.79 m/ka (Min. 0.68 m/ka, Max. 0.90 m/ka), whereas the uplift rate in the other study areas was 0.52 m/ka (Min. 0.41 m/ka, Max. 0.62 m/ka). This discrepancy is probably attributed to the influence of the two faults that subdivide the study area.

The increasing national healthcare expenditure (NHE) with the aging rate is a significant social problem in Japan, and efficient distribution and use of NHE is an urgent issue. It is assumed that comparisons in subregions would be important to explore the regional variation in NHE and health system performance in targeted municipalities of the metropolitan area of Tokyo (central cities) and the neighboring municipalities of Chiba Prefecture (suburbs). This study aimed to clarify the differences of the socioeconomic factors affecting NHE and the health system performances between subregions. A multiple regression analysis was performed to extract the factors affecting the total medical expenses of NHE (Total), comprising the medical expenses of inpatients (MEI), medical expenses of outpatients (MEO), and consultation rates of inpatients (CRI) and outpatients (CRO). Using the stepwise method, dependent variables were selected from three categories: health service, socioeconomic, and lifestyle. Then, health system performance analysis was performed, and the differences between regions were clarified using the Mann–Whitney U test. The test was applied to 18 indicators, classified into five dimensions referred to in the OECD indicators: health status, risk factors for health, access to care, quality of care, and health system capacity and resources. In the central cities, the number of persons per household was the primary factor affecting Total, MEI, MEO, and CRO, and the number of persons per household and the percentage of the entirely unemployed persons primarily affected CRI. In the suburbs, the ratio of the population aged 65–74 and the number of hospital beds were significantly positively related to Total, MEI, and CRI, but the number of workers employed in primary industries was negatively related to Total and MEI. The ratio of the population aged 65–74 was significantly positively related to MEO and CRO. Regarding health system performance, while risk factors for health was high in the central cities, the others, including access to care, quality of care, and health system capacity and resources, were superior in the suburbs, suggesting that the health system might be well developed to compensate for the risks. In the suburbs, while risk factors for health were lower than those in the central cities, access to care, quality of care, and health system capacity and resources were also lower, suggesting that the healthcare system might be poorer. These results indicate a need to prioritize mitigating healthcare disparities in the central cities and promoting the health of the elderly in the suburbs by expanding the suburbs’ healthcare systems and resources. This study clarified that the determinants of NHE and health system performance are drastically varied among subregional levels and suggested the importance of precise regional moderation of the healthcare system.

This paper exploits rich SOEP microdata to analyze state-level variation in health care utilization in Germany. Unlike most studies in the field of the Small Area Variation (SAV) literature, our approach allows us to net out a large array of individual-level and state-level factors that may contribute to the geographic variation in health care utilization. The raw data suggest that state-level hospitalization rates vary from 65 to 165 percent of the national mean. Ambulatory doctor visits range from 90 to 120 percent of the national mean. Interestingly, in the former GDR states, doctor visit rates are significantly below the national mean, while hospitalization rates lie above the national mean. The significant state-level differences vanish once we control for individual-level socio-economic characteristics, the respondents¿ health status, their health behavior as well as supply-side state-level factors.

This study presents an analysis of daily temperature and precipitation extremes with return periods ranging from 2 to 50 years in phase 6 of the Coupled Model Intercomparison Project (CMIP6) multimodel ensemble of simulations. Judged by similarity with reanalyses, the new-generation models simulate the present-day temperature and precipitation extremes reasonably well. In line with previous CMIP simulations, the new simulations continue to project a large-scale picture of more frequent and more intense hot temperature extremes and precipitation extremes and vanishing cold extremes under continued global warming. Changes in temperature extremes outpace changes in global annual mean surface air temperature (GSAT) over most landmasses, while changes in precipitation extremes follow changes in GSAT globally at roughly the Clausius–Clapeyron rate of ∼7% °C−1. Changes in temperature and precipitation extremes normalized with respect to GSAT do not depend strongly on the choice of forcing scenario or model climate sensitivity, and do not vary strongly over time, but with notable regional variations. Over the majority of land regions, the projected intensity increases and relative frequency increases tend to be larger for more extreme hot temperature and precipitation events than for weaker events. To obtain robust estimates of these changes at local scales, large initial-condition ensemble simulations are needed. Appropriate spatial pooling of data from neighboring grid cells within individual simulations can, to some extent, reduce the needed ensemble size.

With frequent air pollution episodes in China, growing research emphasis has been put on quantifying meteorological influences on PM2.5 concentrations. However, these studies mainly focus on isolated cities, whilst meteorological influences on PM2.5 concentrations at the national scale have not yet been examined comprehensively. This research employs the CCM (convergent cross-mapping) method to understand the influence of individual meteorological factors on local PM2.5 concentrations in 188 monitoring cities across China. Results indicate that meteorological influences on PM2.5 concentrations have notable seasonal and regional variations. For the heavily polluted North China region, when PM2.5 concentrations are high, meteorological influences on PM2.5 concentrations are strong. The dominant meteorological influence for PM2.5 concentrations varies across locations and demonstrates regional similarities. For the most polluted winter, the dominant meteorological driver for local PM2.5 concentrations is mainly the wind within the North China region, whilst precipitation is the dominant meteorological influence for most coastal regions. At the national scale, the influence of temperature, humidity and wind on PM2.5 concentrations is much larger than that of other meteorological factors. Amongst eight factors, temperature exerts the strongest and most stable influence on national PM2.5 concentrations in all seasons. Due to notable temporal and spatial differences in meteorological influences on local PM2.5 concentrations, this research suggests pertinent environmental projects for air quality improvement should be designed accordingly for specific regions.

Vertical land movements can cause regional relative sea-level changes to differ substantially from climate-driven absolute sea-level changes. Whereas absolute sea level has been accurately monitored by satellite altimetry since 1992, there are limited observations of vertical land motion. Vertical land motion is generally modelled as a linear process, despite some evidence of nonlinear motion associated with tectonic activity, changes in surface loading or groundwater extraction. As a result, the temporal evolution of vertical land motion, and its contribution to projected sea-level rise and its uncertainty, remains unresolved. Here we generate a probabilistic vertical land motion reconstruction from 1995 to 2020 to determine the impact of regional-scale and nonlinear vertical land motion on relative sea-level projections up to 2150. We show that regional variations in projected coastal sea-level changes are equally influenced by vertical land motion and climate-driven processes, with vertical land motion driving relative sea-level changes of up to 50 cm by 2150. Accounting for nonlinear vertical land motion increases the uncertainty in projections by up to 1 m on a regional scale. Our results highlight the uncertainty in future coastal impacts and demonstrate the importance of including nonlinear vertical land motions in sea-level change projections. A probabilistic reconstruction of vertical land motion reveals regional variations in relative sea-level changes and large uncertainties in sea-level projections due to nonlinear effects.

The North China Plain (NCP) has been suffering from groundwater storage (GWS) depletion and land subsidence for a long period. This paper collects data on GWS changes and land subsidence from in situ groundwater-level measurements, literature, and satellite observations to provide an overview of the evolution of the aquifer system during 1971–2015 with a focus on the sub-regional variations. It is found that the GWS showed a prolonged declining rate of −17.8 ± 0.1 mm/yr during 1971–2015, with a negative correlation to groundwater abstraction before year ~2000 and a positive correlation after ~2000. Statistical correlations between subsidence rate and the GWS anomaly (GWSA), groundwater abstraction, and annual precipitation show that the land subsidence in three sub-regions (Beijing, Tianjin, and Hebei) represents different temporal variations due to varying driver factors. Continuous drought caused intensive GWS depletion (−76.1 ± 6.5 mm/yr) and land subsidence in Beijing during 1999–2012. Negative correlations between total groundwater abstraction and land subsidence exhibited after the 1980s indicate that it may be questionable to infer subsidence from regional abstraction data. Instead, the GWSA generally provides a reliable correlation with subsidence. This study highlights the spatio-temporal variabilities of GWS depletion and land subsidence in the NCP under natural and anthropogenic impacts, and the importance of GWS changes for understanding land subsidence development.

We introduce the first catchment dataset for large sample studies in Chile. This dataset includes 516 catchments; it covers particularly wide latitude (17.8 to 55.0∘ S) and elevation (0 to 6993 m a.s.l.) ranges, and it relies on multiple data sources (including ground data, remote-sensed products and reanalyses) to characterise the hydroclimatic conditions and landscape of a region where in situ measurements are scarce. For each catchment, the dataset provides boundaries, daily streamflow records and basin-averaged daily time series of precipitation (from one national and three global datasets), maximum, minimum and mean temperatures, potential evapotranspiration (PET; from two datasets), and snow water equivalent. We calculated hydro-climatological indices using these time series, and leveraged diverse data sources to extract topographic, geological and land cover features. Relying on publicly available reservoirs and water rights data for the country, we estimated the degree of anthropic intervention within the catchments. To facilitate the use of this dataset and promote common standards in large sample studies, we computed most catchment attributes introduced by Addor et al. (2017) in their Catchment Attributes and MEteorology for Large-sample Studies (CAMELS) dataset, and added several others. We used the dataset presented here (named CAMELS-CL) to characterise regional variations in hydroclimatic conditions over Chile and to explore how basin behaviour is influenced by catchment attributes and water extractions. Further, CAMELS-CL enabled us to analyse biases and uncertainties in basin-wide precipitation and PET. The characterisation of catchment water balances revealed large discrepancies between precipitation products in arid regions and a systematic precipitation underestimation in headwater mountain catchments (high elevations and steep slopes) over humid regions. We evaluated PET products based on ground data and found a fairly good performance of both products in humid regions (r>0.91) and lower correlation (r<0.76) in hyper-arid regions. Further, the satellite-based PET showed a consistent overestimation of observation-based PET. Finally, we explored local anomalies in catchment response by analysing the relationship between hydrological signatures and an attribute characterising the level of anthropic interventions. We showed that larger anthropic interventions are correlated with lower than normal annual flows, runoff ratios, elasticity of runoff with respect to precipitation, and flashiness of runoff, especially in arid catchments. CAMELS-CL provides unprecedented information on catchments in a region largely underrepresented in large sample studies. This effort is part of an international initiative to create multi-national large sample datasets freely available for the community. CAMELS-CL can be visualised from http://camels.cr2.cl and downloaded from https://doi.pangaea.de/10.1594/PANGAEA.894885.

Long-term changes in upper-tropospheric jet latitude, altitude, and strength are assessed for 1980–2014 using five modern reanalyses: MERRA, MERRA-2, ERA-Interim, JRA-55, and NCEP CFSR. Changes are computed from jet locations evaluated daily at each longitude to analyze regional and seasonal variations. The changes in subtropical and polar (eddy driven) jets are evaluated separately. Good agreement among the reanalyses in many regions and seasons provides confidence in the robustness of the diagnosed trends. Jet shifts show strong regional and seasonal variations, resulting in changes that are not robust in zonal or annual means. Robust changes in the subtropical jet indicate tropical widening over Africa except during Northern Hemisphere (NH) spring, and tropical narrowing over the eastern Pacific in NH winter. The Southern Hemisphere (SH) polar jet shows a robust poleward shift, while the NH polar jet shifts equatorward in most regions/seasons. Both subtropical and polar jet altitudes typically increase; these changes are more robust in the NH than in the SH. Subtropical jet wind speeds have generally increased in winter and decreased in summer, whereas polar jet wind speeds have weakened (strengthened) over Africa and eastern Asia (elsewhere) during winter in both hemispheres. The Asian monsoon has increased in area and appears to have shifted slightly westward toward Africa. The results herein highlight the importance of understanding regional and seasonal variations when quantifying long-term changes in jet locations, the mechanisms for those changes, and their potential human impacts. Comparison of multiple reanalyses is a valuable tool for assessing the robustness of jet changes.

By extending the record of Alaskan divisional temperature and precipitation back in time, regional variations and trends of temperature and precipitation over 1920–2012 are documented. The use of the divisional framework highlights the greater spatial coherence of temperature variations relative to precipitation variations. The divisional time series of temperature are characterized by large interannual variability superimposed upon low-frequency variability, as well as by an underlying trend. Low-frequency variability corresponding to the Pacific decadal oscillation (PDO) includes Alaska’s generally warm period of the 1920s and 1930s, a cold period from the late 1940s through the mid-1970s, a warm period from the late 1970s through the early 2000s, and a cooler period in the most recent decade. An exception to the cooling of the past decade is the North Slope climate division, which has continued to warm. There has been a gradual upward trend of Alaskan temperatures relative to the PDO since 1920, resulting in a statewide average warming of about 1°C. In contrast to temperature, variations of precipitation are less consistent across climate divisions and have much less multidecadal character. Thirty-year trends of both variables are highly sensitive to the choice of the subperiod within the overall 93-yr period. The trends also vary seasonally, with winter and spring contributing the most to the annual trends.