Long-term Variability Research Articles

Variability of Dry Days and Sequences of Dry Days in the Polish Carpathians in the Period 1986–2020

This study provides a climatological analysis of annual and long-term variability of dry days and sequences of dry days in the Polish Carpathians between 1986 and 2020. The input data for the research was compiled from the daily precipitation totals from 17 meteorological stations and the T. Niedźwiedź catalogue of circulation types over southern Poland. The frequency of sequences of dry days of different duration has been presented. The incidence of long-term periods has been related to the atmospheric circulation. The number of dry days and the averages of both the number and of the duration of sequences of dry days were analysed for the study period. This yielded an average annual number of dry days ranging from 142 to 195 (39–53% of days in a year), depending on the altitude above sea level and longitude. A general pattern emerged in which the number of dry days increased from west to east. At most stations, there were no statistically significant trends with respect to the dry day characteristics analysed. This is an obvious result of high year-to-year variability, which means that only large changes can achieve statistical significance. Dry days have been evidenced to relate to circulation types. The vast majority of dry days are related to anticyclonic systems, particularly the anticyclonic wedge (Ka) and western anticyclonic (Wa) situations. On the other hand, no clear-cut relationship was established between an increase in air temperature and the occurrence of dry days.

Generating Long-term GRACE-like Total Water Storage Change Products using Conditional Generative Adversarial Networks

Abstract. Since 2002, the Gravity Recovery And Climate Experiment (GRACE) and its Follow-On (GRACE-FO, hereafter GRACE) missions have offered global observations of total water storage (TWS). However, the relatively short record of GRACE data poses a significant challenge for researchers to investigate the full range and long-term variability in TWS. In this study, we present RecGAN, a novel Conditional Generative Adversarial Network (CGAN) comprising a RecNet generator and pixel discriminator. Our approach aims to generate long-term GRACE-like TWS observations by calibrating the WaterGAP Global Hydrology Model (WGHM). The generator is trained to produce observations conforming to the distribution of GRACE data, while the discriminator is trained to assess whether each generated pixel resembles GRACE data. Our results show that RecGAN effectively enhances the consistency between GRACE observations and WGHM-derived TWS changes, achieving improved correlation coefficients, Nash-Sutcliffe Efficiency, and Normalized Root-Mean-Square Error. In addition, RecGAN is robust to different GRACE mascon data, crop sizes used during the training period, and hydrological models targeted for calibration. This study illustrates a promising application of employing CGANs to fine-tune the WGHM output to match GRACE observations. This approach enables the generation of longterm TWS change datasets, which are invaluable for evaluating long-term water storage fluctuations, allocating water resources, and forecasting future hydrological extremes.

Long-term variability of the Kuroshio since 1788 based on coral records

The Kuroshio transports warm water poleward from low- to mid-high latitude regions and strongly affects ocean-atmosphere-land interactions. Previous studies have shown that the Kuroshio has strengthened at its origin during recent decades. However, changes in the Kuroshio on a centennial timescale are unclear due to the lack of observations before the Industrial Revolution. In this study, a precisely dated and monthly resolved Porites coral Sr/Ca record from south of Taiwan island, where coral growth is influenced by the Kuroshio, was used to generate a continuous reconstruction of Kuroshio transport (KT) during the period from 1788 to 2013. The data show a consistent decline in KT since 1788, with the rate of decline increasing since the 1950s, probably due to rapid oceanic warming. The southward shift of the bifurcation latitude of the North Equatorial Current, which is related to accelerated global oceanic warming, might have led to the decrease in KT. Natural variability in the phase transition of the Pacific Decadal Oscillation and El Niño-Southern Oscillation might also influence the long-term changes in KT, particularly before the 1950s.

Post-Lunch Napping as a Strategy to Enhance Physiological Performance and Cognitive Function in Elite Volleyball Players

Background and Objectives: Volleyball demands high levels of anaerobic strength, flexibility, agility, and mental focus. Adequate sleep has been shown to enhance athletic performance and cognitive function. This study investigates the impact of post-lunch naps of varying durations (25 and 45 min) on the physiological performance and cognitive focus of elite volleyball players. Materials and Methods: Sixteen elite volleyball players (8 male, 8 female) with at least 7 years of competitive experience participated in a randomized crossover study. They underwent three experimental conditions: no nap (No-Nap), a 25-min nap (N25), and a 45-min nap (N45). Physical performance was measured through counter-movement jumps (CMJ) and volleyball agility tests, while cognitive function was assessed using the D2 attention test. Statistical analysis included repeated measures ANOVA to examine the differences between nap conditions and gender-specific responses. Results: Significant improvements in both physical performance and cognitive focus were observed in the N25 and N45 conditions compared to the No-Nap condition (indicating the effectiveness of short naps in enhancing both physical and mental performance). Males outperformed females in most physical metrics, while females scored higher on the D2 attention test (suggesting possible gender-specific responses to napping). The 25-min nap showed slightly better results in terms of sleep quality and subsequent performance (confirming that shorter naps may be more beneficial). Conclusions: Post-lunch naps, especially of 25 or 45 min, enhance both physiological and cognitive performance in elite volleyball players. These findings suggest that integrating short naps into athletes’ training regimens can improve performance and focus, with potential gender-specific benefits. Further research is needed to explore long-term effects and variations across other sports.

Long-term variation of the eddy kinetic energy in the Northeastern South China sea

The seasonal to interannual variability of eddy kinetic energy (EKE) in the Northeastern South China Sea (NE-SCS) has been widely studied and it is recognized that they are strongly related to the state of the Kuroshio pathway in the Luzon Strait. While, due to the lack of long-term observations and high-resolution simulations, the decadal change of EKE in NE-SCS remains unexplored. In this study, we show the EKE trend in the past ∼ 30 years in the NE-SCS by using satellite observation and global HYbrid Coordinate Ocean Model reanalysis with the Navy Coupled Ocean Data Assimilation. It is found that due to the weakening of the Kuroshio in the Luzon Strait since 1990 s, the Kuroshio shows an enhanced looping path in the NE-SCS, inducing stronger EKE in this region. Further analysis confirms that the energy transfer by baroclinic instability is dominant for the increasing of EKE, when the Kuroshio intrudes into the NE-SCS and brings more potential energy inside the circulation. The Kuroshio state along the Luzon Strait is the key for modulating the EKE in the NE-SCS. Furthermore, the long-term weakening of Kuroshio current along the Luzon strait during 1993–2020 is determined by the decreasing of subtropical mode water, corresponding to the positive phase of the Atlantic Multidecadal Oscillation. This study provides insight into the interaction between marginal sea (i.e., the SCS) and the open ocean (i.e., the western Pacific Ocean), finally linking to the global climate change.

Evolution of a buried moat-drift system within the Ewing Terrace uncovering highly dynamic bottom currents at the Argentine Margin during Early Oligocene to Middle Miocene

The Ewing Terrace is a relatively flat surface formed by the action of bottom currents and part of a Contourite Depositional System (CDS) at the Argentine continental slope. It is situated in a highly complex oceanographic setting at the Brazil-Malvinas Confluence Zone. Located in water depths of approx. 1000 – 1200 m and incised by the Mar del Plata Canyon, the Ewing Terrace is separated into the Northern Ewing Terrace (NET) and the Southern Ewing Terrace (SET). The long-term variations in ocean circulation led to a complex internal architecture of the terrace. As a result, this region represents a unique archive for studying sedimentary features that were eroded, transported, and deposited by along- and down-slope processes. An in-depth data analysis of high-resolution multichannel seismic profiles exhibits a complex sequence of erosional and depositional contouritic features, namely buried moat-drift systems identified in depths of approx. 370-750 m below the seafloor. They are arranged in migrating sequences and clustered in the Early Oligocene to Middle Miocene. This pattern is probably attributable to the vertical shift of water masses and to a highly dynamic oceanographic setting with spatial changes influenced by the Brazil-Malvinas Confluence Zone over this particular geological time. The moat-drift systems reveal significant lateral changes from north to south. In the southern area of the SET the moats are constructional and the associated separated mounded drifts are well developed. In contrast, the northern area exhibits two types of moats, reminiscent of cut-and-fill structures that mirror the significant and rapid changes in bottom current dynamics. With these new insights, this study contributes to a better understanding of moat-drift systems and improves the knowledge about past oceanographic dynamics and sediment deposition at the northern Argentine margin.

Analyses of sea surface chlorophyll a trends and variability from 1998 to 2020 in the German Bight (North Sea)

Abstract. Satellite remote sensing of ocean colour properties allows observation of the ocean with high temporal and spatial coverage, facilitating the better assessment of changes in marine primary production. Ocean productivity is often assessed using satellite-derived chlorophyll a concentrations, a commonly used proxy for phytoplankton concentration. We used the Copernicus GlobColour remote sensing chlorophyll a surface concentration to investigate seasonal and non-seasonal variability, temporal trends, and changes in spring bloom chlorophyll a magnitude. Complementary, we analysed the chlorophyll a relationship with sea surface temperature and mixed-layer depth in the German Bight from 1998 to 2020. Empirical orthogonal functions were employed in order to investigate dominant spatial and temporal patterns (modes) related to the main processes of chlorophyll a variability. Multi covariance analysis was used to extract the dominant structures that maximize the covariance between chlorophyll a and sea surface temperature mixed-layer depth fields. High levels of chlorophyll a were found near the coast, showing a decreasing gradient towards offshore waters. A significant chlorophyll a positive trend was observed close to the Elbe estuary and adjacent area, while 55 % of the German Bight was characterized by a significant chlorophyll a negative trend. The chlorophyll a non-seasonal variability showed that the first four modes explained around 45 %, with the first and second modes related to inter- and intra-annual variability, respectively, observed in the temporal principal components spectral analyses. Monthly chlorophyll a concentration anomalies co-varied by 45 % with sea surface temperature anomalies and 23 % with mixed-layer depth anomalies. The monthly averages of chlorophyll a anomaly fields were suitable to investigate long-term trends and variability. The rising water temperature, combined with its indirect effects on other variables, can partially explain the observed trends in chlorophyll a.

Long-Term Halocarbon Observations in an Urban Area of the YRD Region, China: Characteristic, Sources Apportionment and Health Risk Assessment

To observe the long-term variations in halocarbons in the Yangtze River Delta (YRD) region, this study analyzes halocarbon concentrations and composition characteristics in Shanxi from 2018 to 2020, exploring their origins and the health effects. The total concentration of halocarbons has shown an overall increasing trend, which is driven by both regulated substances (CFC-11 and CFC-113) and unregulated substances, such as dichloromethane, chloromethane and chloroform. The results of the study also reveal that dichloromethane (1.194 ± 1.003 to 1.424 ± 1.004 ppbv) and chloromethane (0.205 ± 0.185 to 0.666 ± 0.323 ppbv) are the predominant halocarbons in Shanxi, influenced by local and northwestern emissions. Next, this study identifies that neighboring cities in Zhejiang Province and other YRD areas are potentially affected by backward trajectory models. Notably, chloroform and 1,2-dichloroethane have consistently surpassed acceptable thresholds, indicating a significant carcinogenic risk associated with solvent usage. This research sheds light on the evolution of halocarbons in the YRD region, offering valuable data for the control and reduction in halocarbon emissions.

Multiple-Win Effects and Beneficial Implications from Analyzing Long-Term Variations of Carbon Exchange in a Subtropical Coniferous Plantation in China

To improve our understanding of the carbon balance, it is significant to study long-term variations of all components of carbon exchange and their driving factors. Gross primary production (GPP), respiration (Re), and net ecosystem productivity (NEP) from the hourly to the annual sums in a subtropical coniferous forest in China during 2003–2017 were calculated using empirical models developed previously in terms of PAR (photosynthetically active radiation), and meteorological parameters, GPP, Re, and NEP were calculated. The calculated GPP, Re, and NEP were in reasonable agreement with the observations, and their seasonal and interannual variations were well reproduced. The model-estimated annual sums of GPP and Re over 2003–2017 were larger than the observations of 11.38% and 5.52%, respectively, and the model-simulated NEP was lower by 34.99%. The GPP, Re, and NEP showed clear interannual variations, and both the calculated and the observed annual sums of GPPs increased on average by 1.04% and 0.93%, respectively, while the Re values increased by 4.57% and 1.06% between 2003 and 2017. The calculated and the observed annual sums of NEPs/NEEs (net ecosystem exchange) decreased/increased by 1.04%/0.93%, respectively, which exhibited an increase of the carbon sink at the experimental site. During the period 2003–2017, the annual averages of PAR and the air temperature decreased by 0.28% and 0.02%, respectively, while the annual average water vapor pressure increased by 0.87%. The increase in water vapor contributed to the increases of GPP, Re, and NEE in 2003–2017. Good linear and non-linear relationships were found between the monthly calculated GPP and the satellite solar-induced fluorescence (SIF) and then applied to compute GPP with relative biases of annual sums of GPP of 5.20% and 4.88%, respectively. Large amounts of CO2 were produced in a clean atmosphere, indicating a clean atmospheric environment will enhance CO2 storage in plants, i.e., clean atmosphere is beneficial to human health and carbon sink, as well as slowing down climate warming.

Embracing market dynamics in the post-COVID era: A data-driven analysis of investor sentiment and behavioral characteristics in stock index futures returns

This paper aims to enhance the understanding and prediction of stock market behavior during unexpected events like the COVID-19 pandemic, with a specific focus on the role of market attention, social media sentiment indicators, and the development and evolution of unexpected events. We highlight that the common trading and technical indicators used in forecasting the stock index futures prices often overlook investor sentiment and pandemic-related data, which can be instrumental in predicting stock market behavior during significant emergencies. In response, we propose a multi-faceted approach that incorporates these overlooked factors. First, we enhance the predictive index system by integrating investor sentiment, derived from stock message board commentary, and investor behavior influenced by the development and evolution of the pandemic. This innovative approach refines our model's predictive capabilities and is validated through comparative analysis. Second, we introduce a hybrid framework for predicting stock index futures closing prices. By decomposing the closing price series into long-term trends, cyclical variations, and random fluctuations, we create a more nuanced forecast. Each component is predicted separately using appropriate time-series algorithms, improving the overall predictive accuracy and offering generalizability and scalability. Third, we devise a dynamic trading strategy that recognizes pandemic-related data, evolving over time, as a pivotal factor. This strategy is adaptable to evolving market conditions, and our experimental evidence demonstrates its effectiveness in yielding higher returns and reducing associated risks. Our findings underline the importance of incorporating investor sentiment and pandemic-related data into stock market predictions, thus offering a more comprehensive and accurate approach to market forecasting and risk management.

MeerKAT Observations of Procyon at 815.5 MHz

We have conducted observations of the nearby (11.46 ly) star system Procyon, using MeerKAT’s UHF (544–1087 MHz) receivers. We produce full-Stokes time and frequency integrated continuum images, as well as total intensity time series imaging at 8 s cadence, and full-Stokes vector-averaged dynamic spectra from the visibilities in order to search for transient activity such as flaring events. We detect no significant radio emission from the system, and estimate an upper limit on the circular polarization fraction of 65% (3σ confidence level). A comparison with previous Very Large Array observations places a 3σ lower limit on the spectral index between 815.5 and 8400 MHz of 0.26, however long-term significant variability over the last 33 yr cannot be ruled out without further, regular radio monitoring of the system.

Dust resuspension rates in Kuwait: insights from 7Be and 137Cs radionuclides.

Dust resuspension rates in four different landscapes in Kuwait were estimated over a 2-year period using 7Be and 137Cs radionuclides. The average rates of resuspension of particles labeled with 7Be (2 × 10-3 ± 3.9 × 10-4 s-1) were much higher than those of particles labeled with 137Cs (1.6 × 10-6 ± 2.15 × 10-7 s-1), which indicates increased short-term fluctuations in recently deposited dust. Conversely, the resuspension rates for particles labeled with 137Cs were considerably lower, which better reflects long-term variations in dust resuspension. This evaluation approach may provide a foundation for future studies assessing the impact of suspended dust particulates on the performance of solar power systems, in conjunction with other influencing factors like vertical mass flux.

Fragments of harmony amid apparent chaos: A closer look at the X-ray quasi-periodic eruptions of the galaxy RX J1301.9+2747

Quasi-periodic eruptions (QPEs) are an extreme X-ray variability phenomenon associated with low-mass ($M_ BH < 10^7 M_ odot $) supermassive black holes (SMBHs). First discovered in the nucleus of the galaxy GSN 069, they have been so far securely detected in five other galaxies, including RX J1301.9+2747. When detected, the out-of-QPE emission (quiescence) is consistent with the high-energy tail of thermal emission from an accretion disk. In this article we present the X-ray properties of RX J1301.9+2747, both in quiescence and during QPEs, and complement this information with radio observations. We analyze X-ray data taken during five XMM-Newton observations between 2000 and 2022. The last three observations were taken in coordination with radio observations with the Karl G. Jansky Very Large Array. We also made use of EXOSAT, ROSAT, and Chandra archival observations taken between 1983 and 2009. XMM-Newton detected 34 QPEs of which eight have significantly lower amplitudes than the others. No correlated radio/X-ray variability was observed during QPEs. In terms of timing properties, the QPEs in RX J1301.9+2747 do not exhibit the striking regularity observed in the discovery source GSN 069. In fact there is no clear repetition pattern between QPEs: the average time separation between their peaks is about four hours, but it can be as short as one, and as long as six hours. The QPE spectral properties of RX J1301.9+2747 as a function of energy are, however, very similar to those of GSN 069 and of other QPE sources. During their evolution, X-ray QPEs follow a hysteresis pattern in the temperature-luminosity plane, with a hotter rise than decay. The quiescent emission of RX J1301.9+2747 is more complex than that of GSN 069, as it requires a soft X-ray excess-like component in addition to the thermal emission from the accretion disk. Its long-term X-ray quiescent flux variations are of a low amplitude and not strictly monotonic, with a general decay over the course of $ years. We discuss our observational results in terms of some of the ideas and models that have been proposed so far for the physical origin of QPEs.

Holocene paleoenvironmental and paleoclimatic variability in a high mountain lake in Sierra Nevada (Spain): Insights from diatom analysis

This study examines the Holocene history of Río Seco Lake (3040 m a.s.l; Sierra Nevada, Southern Spain) by analysing diatom remains and other paleoenvironmental data. The aim is to understand the impact of long-term environmental and climatic variability on the aquatic ecosystem over the past 21,000 years. Our results suggest that shifts in diatom assemblages were mainly climate-driven in terms of temperature and water availability. The absence of diatom remains during the Late Pleistocene indicated low temperatures and prolonged lake snow cover. Five distinct periods were identified during the Holocene. The high abundance of epiphytic and bog-inhabiting taxa and tychoplanktonic Tabellaria flocculosa in the period 11,000–6700 cal yr BP were indicative of a humid climate. The onset of the tychoplanktonic Aulacoseira alpigena between 6700 and 5100 cal yr BP indicated a drop in temperature. These changes intensified during the period 5100–3300 cal yr BP, when the most significant changes in diatom assemblages took place with the dominance of A. alpigena and an abrupt increase in the abundance of the epiphytic Fragilaria radians. During the subsequent period (3300–1500 cal yr BP), the significant declines in A. alpigena and in epiphytic taxa were indicative of increased aridity and higher alkalinity values due to increased aridity and Saharan dust input during this period. The last period (1500–256 cal yr BP) was characterized by a rise in the abundance of Staurosirella pinnata, indicative of warmer temperatures and higher alkalinity values coincident with a marked increase in proxies of temperature and aridity. The increase in aridity and temperature during the last period, which has led to changes in diatom assemblages, is a matter of great concern in an ecosystem that is particularly susceptible to global warming.

Spatial-temporal seasonal and annual rainfall trends and variability assessment in the Pangani Basin, East Africa

Although in situ rainfall data remains the most accurate, the gauge network density in East Africa is sparse. It lacks continuity, thus making it inadequate to assess the spatial and long-term rainfall trend and variability accurately. As such, rainfall remote sensing data are normally used instead of ground station data. This study evaluates the capabilities and limitations of remote sensing data compared with ground-based observations in Tanzania's Pangani Basin in assessing the seasonal and annual rainfall trends and variability. Data from the Climate Hazards Group Infrared Precipitation with Stations (CHIRPS) and twenty-three ground stations were analyzed, comprising a time series from 1990 to 2022. Trend analysis was conducted using the Mann-Kendall test, while the spatial distribution of precipitation was determined using Sen's slope method. CHIRPS annual rainfall showed good agreement with station rainfall data, with NSE, R2, slope, Pbias, MAE, and RMSE values of 0.84, 0.92, 0.92, 7.55%, 297.4, and 397.1, respectively. The coefficient of variation from station data indicated extreme variability, exceeding 30% for annual rainfall, while CHIRPS data showed moderate variability, ranging from 20% to 30%. Both station data and remote sensing data showed an increasing trend for annual and seasonal rainfall at least 10 stations. However, stations like Maji Moshi, Kiungu Primary School, Segera C. Tank, and Kibong'oto exhibited an increasing trend for vuli rainfall with CHIRPS data, while station data indicated a significant decreasing trend.The study highlights the necessity for calibration and validation to avert misinterpretations in climate trend analyses, especially at the basin level.

Long-term Glycemic Variability Predicts Adverse Outcomes in Diabetic Heart Failure with Preserved Ejection Fraction.

Previous studies have shown associations between glycemic variability (GV) and cardiovascular outcomes in patients with type 2 diabetes. However, the impact of GV on outcomes in patients with heart failure with preserved ejection fraction (HFpEF) has not been investigated. Between 2014 and 2019, we conducted a retrospective cohort analysis using the electronic medical records of a tertiary medical center in Taiwan. Diabetic patients with HFpEF were enrolled. Each individual's coefficient of variability of fasting glucose (FGCV) was determined and the FGCVs were categorized into tertiles. Multivariable Cox regression models and the Kaplan-Meier with log-rank test were used to assess the association between the FGCV and the risk of hospitalization for heart failure (HHF), atrial fibrillation (AF), cardiovascular mortality, and overall mortality. In a cohort comprising 74,835 individuals diagnosed with diabetes, a subset of 753 patients was identified with HFpEF and measurement of FGCV. The median follow-up duration 38.1 months. In the model of full adjustment, the third FGCV tertile was significantly associated with an increased risk of HHF compared to the first tertile (hazard ratio [HR] = 1.32, 95% confidence interval [CI] 1.04-1.69, p = 0.025). Likewise, the highest FGCV tertille was associated with an increased risk of death (HR 1.65, 95% CI: 1.16-2.35, p = 0.005) while it was not associated with increased of AF and cardiovascular mortality. Kaplan-Meier analyses revealed a significant association between FGCV and both HHF and overall mortality (log-rank p = 0.022 and <0.001, respectively). Our study highlights a significant association between increased GV and a higher incidence of HHF as well as an elevated overall mortality rate in individuals with diabetes and HFpEF.

A frequency-dependent model for bone remodeling using a micromorphic porous medium subjected to harmonic mechanical loading

In this paper, the bone tissue was modeled as a linear viscoelastic material saturated with interstitial fluid. We considered a specific case of harmonic loading and related the mechanical stimuli to the loading frequency. In this way, we could include the inertial effect in the model while not having to deal with the perturbation during each loading period. Two types of mechanical signals were considered: strain energy and dissipation energy. A parametric study revealed the dependency of the two signals on loading frequency and material property. The evolution of the apparent mass density supported the parametric study’s findings. Under the three different frequency loadings, the strain energy-stimulated samples experienced identical remodeling scenarios. The samples stimulated with dissipation energy, on the other hand, exhibited a strong frequency dependence. An additional study was performed to investigate the effect of long-term variations in the loading frequency on the remodeling process. This demonstrated the model’s capabilities in designing and evaluating load regimes for rehabilitation following a bone injury or bone reconstruction.

Productivity experienced a more rapid enhancement trend than greenness across the Tibetan Plateau

Satellite-derived products and field measurements verify that Tibetan Plateau (TP) has been experiencing continuous vegetation greening and productivity increase; however, it remains unclear how this greening translates into productivity and how long-term productivity variations depend on greenness across the TP. Moreover, ignoring the accuracy evaluation of satellite-derived greenness and productivity products may mislead the understanding of TP vegetation changes. Thus, we initially assessed the accuracy of three widely used leaf area index (LAI, proxy of greenness) products (i.e., MODIS, GLASS and GEOV2 LAI) and three gross primary productivity (GPP, proxy of productivity) products (i.e., MODIS, GLASS and PML-V2 GPP) to selected robust products to represent greenness and productivity respectively. Then, we explored the dependence of spatiotemporal GPP dynamics on greenness variations during 2000–2020. Results indicated that PML-V2 GPP and MODIS LAI were more robust and reliable than other satellite-derived products when compared to the reference values. They revealed a prevailing increase in GPP over the past two decades, with a regional average of 71 % higher than that of LAI. Notably, the area proportion of significant productivity enhancement was 31.6 % higher than that of significant greening. About 24.7 % of the TP displayed significantly inconsistent trends. The dependency of GPP on LAI gradually decreased with the increasing water availability, the complexity of vegetation structures, and dense canopy community. By calculating leaf photosynthetic capacity, we found that this indicator greatly regulated the velocity discrepancy between GPP and LAI, and the contribution of only greening to productivity is limited, only occupying 11.9 % of the TP, which was helpful in understanding the inter-annual changes of vegetation dynamics under varying environment conditions. We therefore reveal an unexpected rapid increase in productivity than greening during 2000–2020 on the TP, as well as highlight the caution of only using satellite-derived greenness indicators for assessing long-term changes in vegetation productivity dynamics, especially over mesic ecosystems with complex vegetation structures and dense canopies of TP.

Long-term performance monitoring of a-Si 1200 electronic portal imaging device for dosimetric applications.

Recently, dosimetri applications of the electronic portal imaging device (EPID) in radiotherapy have gained popularity. Confidence in the robust and reliable dosimetric performance of EPID detectors is essential for their clinical use. This study aimed to evaluate the dosimetric performance of the a-Si 1200 EPID and assess the long-term stability of its response. Weekly measurements were performed on two clinically used TrueBeam linear accelerators (linacs) equipped with a-Si 1200 EPID detectors over a 2-year period. They included dark and flood calibration fields, and EPID response to an open field corrected for the long-term machine output drift measured with the secondary absolute dosimeters: an ion chamber and an ion chamber array. All measurements were performed using five photon beam energies and two imaging modes: continuous and dosimetry. The measurements were analyzed for constancy and the presence of long-term trends. Comparisons were made between the two linacs for each beam energy. Pixel sensitivity matrices (PSM) were determined semi-annually and analyzed for long-term constancy for both treatment machines. The long-term variation of the dark and flood field signals, integrated across the EPID plane, over the entire observation period did not exceed 0.17% and 0.79%, respectively. The output-corrected EPID response showed long-term variation from 0.28% to 0.36%, depending on beam energy, while the short-term variation was 0.04%-0.07% for EPID and 0.02%-0.06% for secondary dosimeters. The long-term variation of secondary dosimeters was 0.2%-0.3%. PSMs were found to be stable to within 1% for 97.8% of pixels and 2% for 100% of pixels. Techniques to monitor and assess the long-term performance of the a-Si 1200 EPID as a dosimeter were developed and implemented using two TrueBeam linacs. The long-term variation of the EPID response was within clinical tolerance indicated in AAPM TG-142 report, and the detector was shown to be stable and reproducible for routine clinical dosimetry.

Integrating hydrological parameters in wildfire risk assessment: a machine learning approach for mapping wildfire probability

Abstract The increasing occurrence of catastrophic wildfire across the globe threatens public health, community safety, ecosystem functioning, and biodiversity resilience. Wildfire risk is closely connected to shifting climatic trends and their impacts on fuel availability and flammability. Although previous research has explored the connection between meteorological conditions and wildfire probabilities, there remains a substantial gap in understanding the influence of hydrologic drivers, such as groundwater recharge, on wildfire dynamics. Both short- and long-term variations in these variables are crucial in shaping fuel conditions, and significant changes can create environments more prone to severe wildfires. This study focuses on Santa Barbara County to examine the connection between wildfire probability and various environmental factors, including meteorological and hydrological data from 1994 to 2021, topography, vegetation, and proximity to road. Using a random forest (RF) machine learning model and fine-scale data (270 m resolution) we achieved high predictive accuracy in identifying wildfire probability. Our findings confirm the important roles of short-term meteorological conditions, such as mean precipitation 12 months and relative humidity 1 month before a wildfire event, in predicting wildfire occurrence. In addition, our results emphasize the critical contribution of long-term hydrological components, such as mean deviation from the historical normal in actual evapotranspiration and recharge in the years preceding the fire, in influencing wildfire probability. Partial dependence plots from our RF model revealed that both positive and negative deviations of these hydrological variables can increase the likelihood of wildfire by controlling fuel water availability and productivity. These findings are particularly relevant given the increasing extreme weather patterns in southern California, significantly affecting water availability and fuel conditions. This study provides valuable insights into the complex interactions between wildfire occurrence and hydrometeorological conditions. Additionally, the resulting wildfire probability map, can aid in identifying high-risk areas, contributing to enhanced mitigation planning and prevention strategies.