Monthly Time Scales Research Articles

Assessing the Suitability of Probability Distribution Models for Streamflow Analysis in Peninsular Malaysia

Streamflow analysis is indeed a need for Malaysia which always threaten by extreme streamflow events including flooding. However, the determination of the most suitable probability distribution for streamflow analysis has been the major concern and received considerable critical attention recently. The purpose of this study is to analyse the performances of several distributions in fitting the streamflow data collected form 11 streamflow stations in Peninsular Malaysia. and select the best performed distribution eventually. Normal, Generalized Extreme Value (GEV), three-parameter Gamma (G3), two-parameter Gamma (G2), three-parameter Weibull (W3), two-parameter Weibull (W2), three-parameter Log-Normal (LN3) and two-parameter Log-Normal (LN2) were used in this study to fit the maximum, minimum, and mean streamflow with monthly and seasonal time scales by using Easyfit software. The performances of distributions were evaluated through constructing Probability-Probability (P-P) Plot, Cumulative Distribution Function (CDF) and conducting goodness-of-fit tests including Chi-square () Test, Anderson-Darling (AD) Test and Kolmogorov-Smirnov (KS) Test. All the results were tabulated for comparison and the most suitable probability distribution was selected. Overall, the results indicated that the GEV distribution was the best fit distribution for most of the stations and most of the data series or time scales, while the LN3 distribution appeared to be the second-best distribution. These findings add to a growing body of literature on the selection of probability distribution especially for the streamflow analysis in Peninsular Malaysia. Besides, these findings provide significant information and practical knowledge in supporting the future development of streamflow-related plans or management including the flood and drought mitigation plans.

Sea level variations in shelf waters off the coast of British Columbia: from sub-synoptic to interannual time scales

Abstract Sea level variations beyond monthly time scales in the northeast Pacific are analyzed using simulation results of a high-resolution regional model, tide gauge and altimeter observations, and surface winds. Along a zonal section extending westward from the Tofino tide gauge on Vancouver Island, sea level variations are mostly accounted for by steric height. On the shelf, the sea level variations are dominated by salinity in the lower half of the water column, with the seasonal maxima occurring in winter caused by the wind-driven downwelling. In the deep ocean the variations are dominated by temperature in the upper layer up to 50–60 m depth, with a maximum in the summer. In between, the sea levels show a minimum seasonal amplitude over the continental slope because this is the inflection point between the out-of-the-phase variations on the shelf and in the deep ocean. The de-seasonalized anomalies of the halosteric and thermosteric heights at Tofino are coherent at time scales of less than 20 months. At time scales less than 5 months, both are correlated with winds over a mid-latitude zone extending from coast to offshore, and at time scale of 5–20 months both are correlated with the winds in the same mid latitude band and with winds in the equatorial Pacific Ocean.

Extreme drought shapes the gut microbiota composition and function of common cranes (Grus grus) wintering in Poyang Lake.

Extreme weather events driven by climate change profoundly affect migratory birds by altering their habitats, food sources, and migration routes. While gut microbiota is believed to play a role in helping birds adapt to environmental changes, research on how extreme weather impacts their gut microbiota and how these microbial communities respond to such conditions has been limited. 16S rRNA gene sequencing was utilized to investigate the gut microbiota of common cranes (Grus grus) wintering at Poyang Lake from 2020 to 2023, with a particular focus on their response to extreme drought conditions on both inter-annual and monthly timescales. The results revealed that extreme drought conditions substantially impact gut microbiota, with inter-annual water-level fluctuations exerting a more pronounced impact on microbial community structure than that of inter-monthly fluctuations. Notably, a significant decline in bacterial diversity within the gut microbiota of common cranes was observed in the extreme drought year of 2022 compared with other years. Monthly observations indicated a gradual increase in gut microbial diversity, coinciding with relatively minor water-level changes. Key taxa that responded to drought included the Enterobacteriaceae family and Bifidobacterium and Lactobacillus species. Additionally, functional genes related to carbohydrate metabolism, the phosphotransferase system, and the two-component systems were significantly enriched during the extreme drought year. These functions may represent adaptive mechanisms by which the gut microbiota of common cranes respond to drought stress. This research provides novel insights into the temporal variability of gut microbiota in wintering waterbirds, underscoring the significant impact of climatic fluctuations on microbial communities. The findings highlight the importance of understanding the ecological and functional responses of gut microbiota to extreme weather events, which is crucial for the conservation and management of migratory bird populations in the face of climate change.

Identifying time patterns of highland and lowland air temperature trends in Italy and the UK across monthly and annual scales

Abstract. This paper presents a statistical analysis of air temperature data from 32 stations in Italy and the UK up to 2000 m above sea level from 2002 to 2021. The data came from both highland and lowland areas in order to evaluate the differences due to both location and elevation. The analysis focused on detecting trends at annual and monthly timescales, employing ordinary least-squares (OLS), robust S-estimator regression, and Mann–Kendall (MK) and Sen's slope methods. Hierarchical clustering (HCA) using dynamic time warping (DTW) was then applied to the monthly data to analyze the intra-annual pattern similarity of trends within and across the groups. Two different regions of Europe were chosen because of the different climate and temperature trends – namely, the northern UK (smaller trends) and the northwest Italian Alps (larger trends). The main novelty of the work is to show that stations with similar locations and altitudes have similar monthly slopes by quantifying them using DTW and clustering. These results reveal the nonrandomness of different trends throughout the year and between different parts of Europe, with a modest influence of altitude in wintertime. The findings revealed that group average trends were close to the National Oceanic and Atmospheric Administration (NOAA) values for the areas in Italy and the UK, confirming the validity of analyzing a small number of stations. More interestingly, intra-annual patterns were detected commonly at the stations of each of the groups and are clearly different between them. Confirming the different climates, most highland and lowland stations in Italy exhibit statistically significant positive trends, while in the UK, both highland and lowland stations show statistically nonsignificant negative trends. Hierarchical clustering in combination with DTW showed consistent similarity between monthly patterns of means and trends within the group of stations and inconsistent similarity between patterns across groups. The use of the 12 distance correlation matrices (dcor) (one for each month) also contributes to what is the main result of the paper, which is to clearly show the different temporal patterns in relation to location and (in some months) altitude. The anomalous behaviors detected at 3 of the 32 stations, namely Valpelline, Fossano, and Aonoch Mòr, can be attributed, respectively, to the facts that Valpelline is the lowest-elevation station in its group; Fossano is the southernmost of the Italian stations, with some sublittoral influence; and Aonoch Mòr has a large number of missing values. In conclusion, these results improve our understanding of temperature spatio-temporal dynamics in two very different regions of Europe and emphasize the importance of consistent analysis of data to assess the ongoing effects of climate change. The intra-annual time patterns of temperature trends could also be compared with climate model results.

The Discovery and Evolution of a Radio Continuum and Excited-OH Spectral-line Outburst in the Nearby Galaxy NGC 660

Arecibo 305 m Telescope observations between 2008 and 2018 detected a radio continuum and spectral-line outburst in the nearby galaxy, NGC 660. Excited-OH maser emission/absorption lines near 4.7 GHz, and H2CO absorption at 4.83 GHz varied on timescales of months. Simultaneously, a continuum outburst occurred in which a new compact component appeared, with a GHz-peaked spectrum and a 5 GHz flux density that rose to a peak value of about 500 mJy from 2008.0 to 2012.0. Follow-up interferometric continuum images from the Very Large Array at 10 GHz of this new continuum component determined it to be located at the nucleus of NGC 660. Subsequent High Sensitivity Array line and continuum very long baseline interferometry observations of the NGC 660 nucleus revealed a morphology that appears to be consistent with rapidly precessing, mildly relativistic jets from the central black hole. While requiring detailed modeling, this strongly suggests that the outburst is due to nuclear activity. From its timescale, the shape of the continuum light curve, and the milliarcsec radio structure, the most likely cause of the outburst is active galactic nuclei-type activity of accretion of a gas cloud onto the central black hole.

SPIRou observations of the young planet-hosting star PDS 70

Abstract This paper presents near-infrared spectropolarimetric and velocimetric observations of the young planet-hosting T Tauri star PDS 70, collected with SPIRou at the 3.6-m Canada-France-Hawaii Telescope from 2020 to 2024. Clear Zeeman signatures from magnetic fields at the surface of PDS 70 are detected in our data set of 40 circularly polarized spectra. Longitudinal fields inferred from Zeeman signatures, ranging from −116 to 176 G, are modulated on a timescale of 3.008 ± 0.006 d, confirming that this is the rotation period of PDS 70. Applying Zeeman-Doppler imaging to subsets of unpolarized and circularly polarised line profiles, we show that PDS 70 hosts low-contrast brightness spots and a large-scale magnetic field in its photosphere, featuring in particular a dipole component of strength 200–420 G that evolves on a timescale of months. From the broadening of spectral lines, we also infer that PDS 70 hosts a small-scale field of 2.51 ± 0.12 kG. Radial velocities derived from unpolarized line profiles are rotationally modulated as well, and exhibit additional longer-term chromatic variability, most likely attributable to magnetic activity rather than to a close-in giant planet (with a 3-σ upper limit on its minimum mass of ≃4 at a distance of ≃0.2 au). We finally confirm that accretion occurs at the surface of PDS 70, generating modulated red-shifted absorption in the 1083.3-nm He i triplet, and show that the large-scale magnetic field, often strong enough to disrupt the inner accretion disc up to the corotation radius, weakens as the star gets fainter and redder (as in 2022), suggesting that dust from the disc more easily penetrates the stellar magnetosphere in such phases.

Prominent Increase in Air Temperatures on Two Small Mediterranean Islands, Lastovo and Lošinj, Since 1998 and Its Effect on the Frequency of Extreme Droughts

The article analyzes the development of air temperatures and precipitation on two remote islands in the Adriatic Sea from 1961 to 2023, examining annual and monthly time scales. Lastovo Island is located in the southern Adriatic, and Lošinj Island is situated 277 km north, and both exhibit a sharp rise in air temperatures since 1998, though precipitation series show no significant trends of an increase or decrease. Using the New Drought Index (NDI) method, this study calculated drought intensities for the period 1961–2023. The analyses conducted in this study undoubtedly indicate a rising frequency and intensity of droughts, with severe droughts doubling and extreme droughts increasing fourfold in the recent period (1998–2023) compared to the previous one (1961–1997). The most pronounced increase in severe and extreme droughts occurs specifically from June to August. This trend is likely applicable to many small Mediterranean Islands, which number over 10,000 and have a permanent population of more than 1.6 million people, with numbers significantly rising during the tourist season. The increased water demand for agriculture and daily use, combined with increased drought risk, not only exacerbates the potential for forest fires but also threatens social structures and ecological conditions. This is particularly critical as the combination of drier conditions and increased fire risk poses a significant challenge, endangering natural landscapes and valuable historical sites that are integral to the islands’ identity and heritage. This study’s findings indicate a dangerous trend likely to persist and worsen with continued increases in air temperatures in the Mediterranean region.

The Variability Structure Function of the Highest-Luminosity Quasars on Short Timescales

Abstract The stochastic photometric variability of quasars is known to follow a random-walk phenomenology on emission timescales of months to years. Some high-cadence restframe optical monitoring in the past has hinted at a suppression of variability amplitudes on shorter timescales of a few days or weeks, opening the question of what drives the suppression and how it might scale with quasar properties. Here, we study a few thousand of the highest-luminosity quasars in the sky, mostly in the luminosity range of Lbol=[46.4, 47.3] and redshift range of z = [0.7, 2.4]. We use a dataset from the NASA/ATLAS facility with nightly cadence, weather permitting, which has been used before to quantify strong regularity in longer-term restframe-UV variability. As we focus on a careful treatment of short timescales across the sample, we find that a linear function is sufficient to describe the UV variability structure function. Although the result can not rule out the existence of breaks in some groups completely, a simpler model is usually favoured under this circumstance. In conclusion, the data is consistent with a single-slope random walk across restframe timescales of Δt = [10, 250] days.

Monthly Prediction on Summer Extreme Precipitation With a Deep Learning Approach: Experiments Over the Mid‐To‐Lower Reaches of the Yangtze River

AbstractAccurate predictions of monthly extremes assume paramount importance in enabling proactive decision‐making, which however are lacked in skills even for state‐of‐the‐art dynamical models. Taking the extreme precipitation prediction over the mid‐to‐lower reaches of the Yangtze River, China, as an instance, a multi‐predictor U‐Net deep learning approach is designed to enhance the prediction over the European Center for Medium‐Range Weather Forecasts (ECMWF) model, with the single‐predictor U‐Net parallelly examined as the benchmark. Focusing on the precipitation extremes, an extreme associated component is incorporated into the model loss function for optimization. Besides, predictions composed by daily outputs with multiple lead times are imported as a comprehensive set in the training phase to augment the deep learning sample size and to emphasize enhancements in predictions at the monthly timescale as a whole. Results indicate that the multi‐predictor U‐Net effectively improves predictions of extreme summer precipitation frequency, showing distinct superiority to the raw ECMWF and the single‐predictor U‐Net. Multiple evaluation metrics indicate that the model shows a significant positive improvement ratio ranging from 65.1% to 80.0% across all grids compared to the raw ECMWF prediction, which has also been validated through applications in the two extreme summer precipitation cases in 2016 and 2020. Besides, a ranking analysis of feature importance reveals that factors such as humidity and temperature play even more crucial roles than precipitation itself in the multi‐predictor extreme precipitation prediction model at the monthly timescale. That is, in such a deep learning approach, the monthly prediction on extreme precipitation benefits significantly from the inclusion of multiple associated predictors.

Hydrological controls of a riparian wetland based on stable isotope data and model simulations.

Isotopic evidence of groundwater and stream water is frequently used to investigate water exchanges with groundwater. Monthly sampling of rain, stream water, and groundwater was conducted at Tims Branch watershed in South Carolina for the oxygen and hydrogen stable isotope (δ2H and δ18O) measurement, as well as pH and oxidation-reduction potential (ORP). Together with a mass balance perspective, it was determined that it takes a few weeks to one month for groundwater in the hyporheic zone to fully exchange with stream water. From hydrodynamic modelling, we show that substantial (up to 70 %) groundwater exchange occurs at gaining and losing sites. Groundwater exfiltration, i.e. inflow into stream water, contributes up to 4 % to stream water, with the remainder from upstream exfiltration. A 2-4 % per day renewal rate of adjacent groundwater would indirectly indicate a groundwater residence time in the order of half a month to a full month (assuming either a well-mixed case or large dispersion rate in pulse flow case), in agreement with a greatly reduced variability of δ2H and δ18O of groundwater compared to stream water and rain. This reduced variability of stable isotope signal from groundwater confirms our hypothesis that riparian groundwater mixing at Tims Branch is more of a mixed type rather than a pulse flow type. A monthly time scale is sufficient for groundwater to become anoxic at exit points into stream water resulting in the episodic production of natural organic matter- and iron-rich flocs upon oxidation.

Evaluation of gridded precipitation datasets in mountainous terrains of Northwestern Mexico

Study regionThe complex mountainous terrains of the Sierra Madre Occidental in northwestern Mexico. Study focusAcquiring high-resolution precipitation data in regions with limited conventional rain gauge coverage poses significant challenges. Gridded precipitation (GP) datasets, including gauge-based, satellite, and reanalysis products, provide a potential solution, but their reliability in areas with complex terrain and intricate precipitation patterns remains uncertain. This study comprehensively evaluates the performance of four GP datasets—AORC, CHIRPS, Daymet, and ERA5—in estimating precipitation. The evaluation was conducted at a daily, monthly, and seasonal timescale, further analyzing extreme precipitation, the influence of elevation, and spatial averaging across hydrologic basins, using as reference the NERN rain gauge data from 2002 to 2004. New hydrological insights for the regionResults indicate that Daymet and AORC are the most accurate GP datasets for daily and monthly timescales, respectively. All datasets improve in accuracy over longer timescales but face challenges during the wet summer monsoon months and extreme events, with Daymet performing relatively better. Terrain elevation had a minimal impact on overall dataset accuracy, though a slight improvement in precipitation detection was noted as elevation increased. This work provides valuable insights into the strengths and limitations of GP datasets in regions with complex terrain and orographically-forced convective precipitation, offering practical outcomes for climate and hydrologic studies in similar regions.

Dust aerosol from the Aralkum Desert influences the radiation budget and atmospheric dynamics of Central Asia

Abstract. The Aralkum is a new desert created by the desiccation of the Aral Sea and is an efficient source of dust aerosol which perturbs the regional Central Asian radiation balance. COSMO–MUSCAT model simulations are used to quantify the direct radiative effects (DREs) of Aralkum dust, and investigate the associated perturbations to the atmospheric environment. Considering scenarios of “Past” (end of 20th century) and “Present” (beginning of 21st century) defined by differences in surface water coverage, it is found that in the Present scenario the simulated yearly mean net surface DRE across the Aralkum is −1.34 W m−2 with a standard deviation (±) of 6.19 W m−2, of which −0.15 ± 1.19 W m−2 comes from dust emitted by the Aralkum. In the atmosphere the yearly mean DRE is −0.62 ± 2.91 W m−2, of which −0.05 ± 0.51 W m−2 is from Aralkum dust: on the yearly timescale, Aralkum dust is cooling both at the surface and in the atmosphere, due to its optically scattering properties. The daytime surface cooling effect (solar zenith angle ≲ 70–80°) outweighs the nighttime heating effect and the atmospheric daytime (solar zenith angle ≲ 60–70°) heating and nighttime cooling effects. Instantaneous Aralkum dust DREs contribute up to −116 W m−2 of surface cooling and +54 W m−2 of atmospheric heating. Aralkum dust perturbs the surface pressure in the vicinity of the Aralkum by up to +0.76 Pa on the monthly timescale, implying a strengthening of the Siberian High in winter and a weakening of the Central Asian heat low in summer. These results highlight the impacts of anthropogenic lakebed dust on regional atmospheric environments.

JWST/NIRCam 4–5 μm Imaging of the Giant Planet AF Lep b

With a dynamical mass of 3 M Jup, the recently discovered giant planet AF Lep b is the lowest-mass imaged planet with a direct mass measurement. Its youth and spectral type near the L/T transition make it a promising target to study the impact of clouds and atmospheric chemistry at low surface gravities. In this work, we present JWST/NIRCam imaging of AF Lep b. Across two epochs, we detect AF Lep b in F444W (4.4 μm) with signal-to-noise ratios of 9.6 and 8.7, respectively. At the planet’s separation of 320 mas during the observations, the coronagraphic throughput is ≈7%, demonstrating that NIRCam’s excellent sensitivity persists down to small separations. The F444W photometry of AF Lep b affirms the presence of disequilibrium carbon chemistry and enhanced atmospheric metallicity. These observations also place deep limits on wider-separation planets in the system, ruling out 1.1 M Jup planets beyond 15.6 au (0.″58), 1.1 M Sat planets beyond 27 au (1″), and 2.8 M Nep planets beyond 67 au (2.″5). We also present new Keck/NIRC2 L′ imaging of AF Lep b; combining this with the two epochs of F444W photometry and previous Keck L′ photometry provides limits on the long-term 3–5 μm variability of AF Lep b on timescales of months to years. AF Lep b is the closest-separation planet imaged with JWST to date, demonstrating that planets can be recovered well inside the nominal (50% throughput) NIRCam coronagraph inner working angle.

Local Weather and Global Climate Data-Driven Long-Term Runoff Forecasting Based on Local–Global–Temporal Attention Mechanisms and Graph Attention Networks

The accuracy of long-term runoff models can be increased through the input of local weather variables and global climate indices. However, existing methods do not effectively extract important information from complex input factors across various temporal and spatial dimensions, thereby contributing to inaccurate predictions of long-term runoff. In this study, local–global–temporal attention mechanisms (LGTA) were proposed for capturing crucial information on global climate indices on monthly, annual, and interannual time scales. The graph attention network (GAT) was employed to extract geographical topological information of meteorological stations, based on remotely sensed elevation data. A long-term runoff prediction model was established based on long-short-term memory (LSTM) integrated with GAT and LGTA, referred to as GAT–LGTA–LSTM. The proposed model was compared to five comparative models (LGTA–LSTM, GAT–GTA–LSTM, GTA–LSTM, GAT–GA–LSTM, GA–LSTM). The models were applied to forecast the long-term runoff at Luning and Pingshan stations in China. The results indicated that the GAT–LGTA–LSTM model demonstrated the best forecasting performance among the comparative models. The Nash–Sutcliffe Efficiency (NSE) of GAT–LGTA–LSTM at the Luning and Pingshan stations reached 0.87 and 0.89, respectively. Compared to the GA–LSTM benchmark model, the GAT–LGTA–LSTM model demonstrated an average increase in NSE of 0.07, an average increase in Kling–Gupta Efficiency (KGE) of 0.08, and an average reduction in mean absolute percent error (MAPE) of 0.12. The excellent performance of the proposed model is attributed to the following: (1) local attention mechanism assigns a higher weight to key global climate indices at a monthly scale, enhancing the ability of global and temporal attention mechanisms to capture the critical information at annual and interannual scales and (2) the global attention mechanism integrated with GAT effectively extracts crucial temporal and spatial information from precipitation and remotely-sensed elevation data. Furthermore, attention visualization reveals that various global climate indices contribute differently to runoff predictions across distinct months. The global climate indices corresponding to specific seasons or months should be selected to forecast the respective monthly runoff.

Seasonal euxinia in a coastal basin: Impact on sedimentary molybdenum enrichments and isotope signatures

Eutrophication and global warming are leading to increased deoxygenation of coastal waters worldwide. To predict future trajectories of oxygen loss, insight into the intensity and temporal dynamics of past coastal deoxygenation is essential. Here, we assess the use of sedimentary molybdenum (Mo) enrichments and isotopic signatures (δ98Mo) as redox proxies in sediments of a seasonally euxinic coastal basin (Scharendijke, Lake Grevelingen, the Netherlands). Strong drawdown of dissolved Mo (from ∼100 to ∼60 nmol L−1) was observed in the euxinic bottom waters from July to September in 2021, coinciding with sedimentary enrichment of Mo (with peak values up to 19 ppm). A mass balance for Mo indicates that both deposition of Mo in the form of particles and diffusion of dissolved Mo into the sediment account for this Mo enrichment. The δ98Mo composition of suspended matter in the euxinic waters (0.30 to −1.95 ‰) is in line with isotopic fractionation during formation of thiomolybdates, and removal of Mo by sulfur- and/or iron-rich particles. The δ98Mo composition of the bottom water increases from 2.42 to 3.16 ‰ throughout the euxinic period, thereby further supporting preferential uptake of light Mo isotopes during sulfidation in the water column and near the sediment-water interface. The exceptionally high sedimentation rate at this site (>13 cm yr−1) allows seasonal variations in sedimentary enrichments to be preserved in the sedimentary record. Notably, sediment δ98Mo values peak during the summer euxinic period, reaching 1.28 ‰ in 2021 and as high as 2.15 ‰ in 2020. The 2020 value is close to the mean ocean value of 2.3 ‰, implying that sediments overlain by seasonally and permanently euxinic bottom waters can record the same isotopic signatures for Mo. Further work is needed to determine the potential role of diagenesis in altering δ98Mo records on time scales of months to several years.

Evaluating potential evapotranspiration methods in a rapidly warming Arctic region, SW Spitsbergen (1983–2023)

Study regionsHornsund, SW Spitsbergen, Svalbard – area representing atlantic sector of High Arctic Study focusSvalbard's warming climate significantly alters its hydrological conditions. Evapotranspiration, a crucial hydrological component, is understudied in this High Arctic environment. In this study, daily potential evapotranspiration (PET) estimates for the period 1983–2023 were calculated using meteorological data from the Polish Polar Station Hornsund (SW Spitsbergen). 11 different PET methods were applied, those include radiation-based, temperature-based, radiation-temperature-based, and combined methods. New hydrological insights for the regionThe results show a large spread in the annual sum of PET ranging from ∼20 mm/y (Kharrufa) through ∼300 mm/y (Penman-Monteith) up to ∼450 mm/y (Abtew). Trends analysis shows different outcomes depending on the length of the averaging period. Using a daily timescale, PET methods tend to show more similar patterns of changes than using monthly timescales. The changes in PET estimates differ between the models, hence classifying PET methods should consider their sensitivity to meteorological changes. PET estimates were compared with pan measurements at a daily time scale in 2022–2023. The Penman method produced the best results in relation to pan measurements. In other cases, despite a relatively high linear correlation, calibration to local conditions is needed to scale the outcomes and limit biases. This study improves understanding of how PET models perform in the rapidly changing High Arctic climate.

Spatiotemporal variation and teleconnections of extreme precipitation in the Upper Indus Basin: insights for natural hazard assessment

ABSTRACT The study investigates trends and teleconnections of extreme precipitation events in the Upper Indus Basin (UIB) within the Indian region, part of the crucial geo-ecological Hindu Kush Himalayan Mountain system. Utilizing high-resolution (10km) HAR data from 2002 to 2013, we analyzed 11 indices established by the Expert Team on Climate Change Detection and Indices (ETCCDI) to observe variations in extreme precipitation at the monthly, seasonal, and annual scales. Results show an increase in dry and wet extreme precipitation frequency and intensity, increased monsoon precipitation, and a shift of winter precipitation, increasing continuous dry days. Using APHRODITE daily (0.25°) data from 1952 to 2014, continuous wavelet transform and wavelet coherence analysis indicate significant periodicities and correlations with large-scale climate anomalies such as El Niño-Southern Oscillation (ENSO) and North Atlantic Oscillation (NAO). Wavelet coherence analysis reveals that monthly extreme precipitation events significantly correlate with ENSO at 3-5 years periodicity, while annual extremes show significant coherence with NAO at 8-10 years and over 16 years periodicities. The study highlights the impact of global climate change on regional precipitation and the need for adaptive water management policies to mitigate flood risks during the rainy season and address water scarcity in the dry season.

Aggregation and transport of microplastics by a cold-core ring in the southern recirculation of the Kuroshio Extension: the role of mesoscale eddies on plastic debris distribution

Mesoscale eddies – ocean vortices with spatial scales of tens to hundreds of kilometers and time scales of months to years – are among the most energetic forms of flow in the ocean, and may act as significant transporters of floating microplastics. Yet, shipboard observation has thus far not clarified the abundance and transport of microplastics in mesoscale eddies. We conducted floating microplastic surveys in an intense cyclonic mesoscale eddy with a large sea surface height depression (approximately 0.8 m), a so-called cold-core ring, in the Kuroshio Extension recirculation gyre (KERG) southeast of Japan. The concentration of microplastics within the eddy (460 × 104 pieces/km2) was one or two orders of magnitude higher than in the adjacent oceanic waters, likely due to the acquisition of microplastics from the microplastic-rich Kuroshio Extension (KE) when detaching, as well as the horizontal entrainment of particles by the eddy. Our examination by using an assimilation product showed that most particles captured by the eddy remained within for several months while the eddy moved clockwise in the KERG. These results suggest that mesoscale eddies are of importance in the transportation and redistribution of microplastics on the ocean surface.

Discovery of Very High Energy Gamma-Ray Emissions from the Low-luminosity AGN NGC 4278 by LHAASO

Abstract The first source catalog of the Large High Altitude Air Shower Observatory (LHAASO) reported the detection of a very high energy gamma-ray source, 1LHAASO J1219+2915. This Letter presents a further detailed study of the spectral and temporal behavior of this pointlike source. The best-fit position of the TeV source (R.A. = 185.°05 ± 0.°04, decl. = 29.°25 ± 0.°03) is compatible with NGC 4278 within ∼0.°03. Variation analysis shows an indication of variability on a timescale of a few months in the TeV band, which is consistent with low-frequency observations. Based on these observations, we report the detection of TeV γ-ray emissions from this low-luminosity active galactic nucleus. The observation by LHAASO's Water Cherenkov Detector Array during the active period has a significance level of 8.8σ with a best-fit photon spectral index Γ = 2.56 ± 0.14 and a flux f 1–10 TeV = (7.0 ± 1.1sta ± 0.35syst) × 10−13 photons cm−2 s−1, or approximately 5% of the Crab Nebula. The discovery of VHE gamma-ray emission from NGC 4278 indicates that compact, weak radio jets can efficiently accelerate particles and emit TeV photons.

Exploring the Transport Path of Oceanic Microplastics in the Atmosphere.

Microplastics (MP) have been recognized as an emerging atmospheric pollutant, yet uncertainties persist in their emissions and concentrations. With a bottom-up approach, we estimate 6-hourly MP fluxes at the ocean-atmosphere interface, using as an input the monthly ocean surface MP concentrations simulated by the global oceanic model (NEMO/PISCES-PLASTIC, Nucleus for European Modeling of the Ocean, Pelagic Interaction Scheme for Carbon and Ecosystem Studies), a size distribution estimate for the MP in the micrometer range, and a sea salt emission scheme. The atmospheric dispersion is then simulated with the Lagrangian model FLEXPART. We identify hotspot sources in the tropical regions and highlight the seasonal variability of emissions, atmospheric concentrations, and deposition fluxes both on land and ocean surfaces. Due to the variability of MP concentration during the year, the MP flux from the sea surface appears to follow a seasonality opposite to that of sea salt aerosol emissions. The comparison with existing observations of MP in the marine atmosphere suggests an underestimation of one to 2 orders of magnitude in our current knowledge of the MP in the oceans' surface. In addition, we show that the MP in the micrometer range is transported efficiently around the globe and can penetrate and linger in the stratosphere over time scales of months. The interaction of these particles with the chemistry and physics of the atmosphere is still mostly unknown and deserves to be further investigated.