Intra-annual Variability Research Articles

Modeling streamflow response under changing environment using a modified SWAT model with enhanced representation of CO2 effects

Study regionHaihe River Basin (HRB) in North China Plain. Study focusChanges in streamflow due to climate change and human activities are highly uncertain. An improved Soil and Water Assessment Tool (SWAT) model equipped with a dynamic CO2 input method was used to quantify the environmental change impacts on streamflow in the HRB. Streamflow changes were analyzed based on 22 bias-corrected CMIP6 GCMs under SSP1-2.6, SSP2-4.5, SSP3-7.0, and SSP5-8.5 during two 30-year periods of the middle (2041–2070) and end (2071–2100) of the 21st century relative to the historical period (1971–2000). New hydrological insights for the regionLong-term simulations of annual streamflow in the HRB demonstrated substantial discrepancies between the dynamic and constant CO2 input methods under the SSP1-2.6 and SSP5-8.5 scenarios, which highlighted the importance of using the dynamic CO2 input method for streamflow simulations. Spatio-temporal analysis using the improved SWAT model revealed that streamflow generally increased under four emission scenarios compared to the historical period. In the HRB, annual streamflow in the downstream plains was higher than in the upstream mountains, and this was more evident under the highest emission scenario of SSP5-8.5. Monthly streamflow showed considerable intra-annual variability that was generally greater from July to November. The strongest increment in streamflow was projected in the SSP3-7.0 and SSP5-8.5 scenarios, indicating that flood risk would possibly increase in the late 21st century.

Mapping future offshore wind resources in the South China Sea under climate change by regional climate modeling

Cost-effective deployment of wind energy systems benefits from a thorough understanding of wind resources. Therefore, it is imperative to figure out how the spatiotemporal patterns of wind resources will evolve in a warmer future world. Based on a regional climate model system named RegCM4.7, this study investigates the future offshore wind resources under climate change in a tropical ocean, namely the South China Sea (SCS). First, 25-km-resolution wind field information over the SCS is retrieved from a regional climate model driven by 22 global climate models. Then, the simulated wind fields are validated against the reanalysis dataset ERA5 and the Cross-Calibrated Multi-Platform satellite dataset. Subsequently, the spatial distribution and temporal variation of wind resources under climate change are comprehensively assessed, and the inter-annual and intra-annual wind resource variability is quantified by the robust coefficient of determination. Last, the significance, robustness, and uncertainty of climate change signals are evaluated. It is projected that the wind power density will increase by 10–20 % in the northern SCS but decrease by 10–30 % in the southern SCS in 2081–2100 (compared to 1985–2004) under the Representative Concentration Pathway 8.5.

El Niño-Southern Oscillation forcing on carbon and water cycling in a Bornean tropical rainforest

Carbon dioxide and water vapor exchanges between tropical forest canopies and the atmosphere through photosynthesis, respiration, and evapotranspiration (ET) influence carbon and water cycling at the regional and global scales. Their inter- and intra-annual variations are sensitive to seasonal rhythms and longer-timescale tropical climatic events. In the present study, we assessed the El Niño-Southern Oscillation (ENSO) influence on ET and on the net ecosystem exchange (NEE), using eddy-covariance flux observations in a Bornean rainforest over a 10-y period (2010-2019) that included several El Niño and La Niña events. From flux model inversions, we inferred ecophysiological properties, notably the canopy stomatal conductance and "big-leaf" maximum carboxylation rate (Vcmax25_BL). Mean ET values were similar between ENSO phases (El Niño, La Niña, and neutral conditions). Conversely, the mean net ecosystem productivity was highest during La Niña events and lowest during El Niño events. Combining Shapley additive explanation calculations for nine controlling factors with a machine-learning algorithm, we determined that the primary factors for ET and NEE in the La Niña and neutral phases were incoming shortwave solar radiation and Vcmax25_BL, respectively, but that canopy stomatal conductance was the most significant factor for both ET and NEE in the El Niño phase. A combined stomatal-photosynthesis model approach further indicated that Vcmax25_BL differences between ENSO phases were the most significant controlling factor for canopy photosynthesis, emphasizing the strong need to account for ENSO-induced ecophysiological factor variations in model projections of the long-term carbon balance in Southeast Asian tropical rainforests.

Can offshore wind energy help to attain carbon neutrality amid climate change? A GIS-MCDM based analysis to unravel the facts using CORDEX-SA

Harnessing offshore wind energy helps to achieve carbon neutrality. However, the availability of wind resources is sensitive to climate change and also depends on the available foundation technologies of wind turbines. Investigating annual energy production (AEP) and CO2 equivalent emission avoidance using offshore wind farms helps to make appropriate energy strategies. This study uses an ensemble developed using CORDEX-South Asia regional climate models by assigning weights derived from the CRITIC multi-criteria technique to estimate AEP under two representative concentration pathways (RCP), i.e., RCP4.5 and RCP8.5 scenarios in the North Indian Ocean. To account for the impact of climate change, inter and intra-annual variations in the wind power density (WPD), capacity factor (CF), and AEP are estimated. Estimates based on the feasibility of foundation technology show that the cumulative AEP obtained from the 240 MW wind farm in historic, near- and far-future scenarios are 357.91 TWh, 808.6 TWh, and 4888.78 TWh, respectively. In the near future, harnessing offshore wind energy can reduce CO2 emissions by 4500 million tons annually. The findings of this study suggest that harnessing offshore wind energy by installing farms within the study area could help in the massive reduction of CO2 emissions leading to carbon neutrality.

Belowground growth strategies of native and invasive rhizomatous perennial grasses in response to precipitation variability, clipping, and competition

Invasive clonal species may exhibit different growth strategies than their native clonal competitors. In this study, we examined the spatial distribution of tiller outgrowth and the bud bank by comparing the investment in phalanx versus guerilla growth of a native and invasive perennial grass in North America. We also examined the effect of altered precipitation frequency, clipping, and competition on their clonal growth strategies. Investment in phalanx and guerilla growth was assessed by examining live propagule and tiller production from the plant crown versus its rhizomes. Although invasive Bromus inermis and native Pascopyrum smithii exhibited similar clonal growth strategies as young seedlings, their clonal growth strategies significantly differed by the end of their first growing season. Pascopyrum smithii invested in dual phalanx and guerilla tiller outgrowth and bud placement, and B. inermis primarily invested in phalanx tiller outgrowth and bud placement. Competition rather than intra-annual precipitation variability and clipping altered the clonal growth strategy of these species. Intra- and inter- specific competition did not alter tiller outgrowth for either species. However, inter-specific competition caused both species to alter their bud placement. Bromus inermis shifted more buds from phalanx to guerilla positions while P. smithii shifted in the opposite direction. This may enable invasive B. inermis to expand while confining native P. smithii to more localized areas in the future. Clonal growth strategies appear to be species specific and responsive to inter-specific competition. Investigating the belowground bud aspect of clonal growth can reveal the mechanism driving the future aboveground clonal growth strategy of native and invasive rhizomatous grasses and help inform the patterns of invasion within a plant community.

Flowering variabilities in subtropical intertidal Zostera muelleri meadows of Australia

Flowering is an integral feature of the life history of seagrasses, and it contributes to the genetic diversity and resilience of meadows. There is some evidence that seagrass flowering is influenced by tidal depth; however, the effects of tidal exposure on the flowering variabilities in patchy intertidal meadows are largely unknown. In the present study, inter and intra-annual variability of flowering was examined using a line transect sampling method across two subtropical intertidal meadows (i.e., Lilley’s Beach and Pelican Banks) of Zostera muelleri on Australia’s east coast. Along each transect, the depth was measured using Leica Geosystems AGS14 RTK, and the plant cover was estimated using a standard scale. The duration of exposure at each depth was computed based on the tidal data and categorised exposure duration by hours. The abundance (i.e., the density of flowering shoots and density of spathes) and the ratio of flowering (i.e., flowering frequency) and morphology of flowering (i.e., the number of spathes per flowering shoot) were estimated at every 10 m along three 100 m fixed transects established perpendicular to the tide monthly in 2020 and 2021. Flowering started in July and extended for approximately six months, with peak flowering observed in September-October at both sites. Generalised linear mixed-effect models showed that approximately 39% of the density of flowering shoots, 36% of the density of spathes and 28% of flowering frequency were explained by plant cover and exposure duration. Similar variation in the spathes per flowering shoot was explained by plant cover only (40%). The density of spathes during peak flowering months was significantly different among exposure categories (3-4 hrs and 5-6 hrs in Lilley’s Beach and 5-6 hrs and 6-7 hrs in Pelican Banks in 2021), where significantly different interannual variability was observed only between the same exposure categories in Pelican Banks. The study offers valuable insights into seed-based restoration projects, including optimal seed harvesting times and the average quantity of harvestable flowers, although some inter-annual variations should be anticipated.

Monitoring intra-annual and interannual variability in spatial distribution of plastic-mulched citrus in cloudy and rainy areas using multisource remote sensing data

The technology of canopy plastic mulching has been widely used in citrus orchards for protecting fruit trees from cold damage. Understanding the spatio-temporal dynamics of plastic-mulched citrus (PMC) is of great importance for precision management of citrus orchards. However, monitoring the long-term and large-area PMC dynamics is challenging because the PMC is typically distributed in cloudy and rainy areas with rapid spatial variability, leading to the limited availability of high-quality remotely sensed data. Moreover, it is difficult to collect sufficient field samples in rugged mountainous regions for extracting PMC. To address these limitations, we proposed a new plastic-mulched citrus index (PMCI) based on spectral separability analysis of PMC and other land cover types. The images from Landsat-5/7/8, Sentinel-2, and Gaofen-1 satellites were employed to extract the intra-annual PMC distribution from 2019 to 2020 and interannual PMC distribution from 2008 to 2020 in Yangshuo county, Guangxi Zhuang Autonomous Region, China. Results showed that the PMCI outperformed other widely used indices in PMC extraction with overall accuracy (OA) increased by 0.09–0.3. Besides, the PMCI exhibited good performances in extracting PMC over different observation dates with OA ranging 0.92–0.98 and 0.91–0.98 in the intra-annual and annual PMC maps, respectively. According to the derived PMC time series maps, PMC displayed significant intra-annual spatial variations in the start date and length of plastic mulching period, whereas the interannual variation of PMC revealed long-term technology adoption patterns in the study area. Furthermore, we found that temperature mainly affected intra-annual PMC variability, and that agricultural policy, market factor, neighborhood effect and variety replacement can explain the interannual PMC variability. These results indicate that the developed PMCI can effectively identify PMC over different agricultural regions and observation dates, and the resultant spatio-temporal dynamic PMC maps based on multi-source satellite data provide an important basis for the promotion of PMC at larger scales and the sustainable development of the citrus industry.

Consistency of Intra-Centennial Oscillations in Length of Day and Oceanic Characteristics

The paper presents analysis of intra-centennial (inter-decadal and multidecadal) variations of the length of day (LOD) and some oceanic parameters such as sea surface temperature (SST) and sea level (SL). Methods of multivariate regression analysis and correlation analysis are used. Results of the regression analysis show a spatially coherent response of SST to LOD variations on the multidecadal time scale. The earlier response is peculiar to the north and tropical Atlantic where the multidecadal SST variations are approximately opposite to the LOD variations. In the most remaining parts of the oceans, except especially in the Nino 3.4 region of the equatorial east Pacific, the multidecadal SST variations are generally lagged relative to the antiphase variations of the LOD. Smoothing of SST averaged over different areas and of the global mean SL shows that the intra-annual variations include inter-decadal, 20–30-year, multidecadal, 60–70-year, components that correspond to similar oscillation components in the LOD. The most striking correspondence of the two components is observed between the LOD and SST averaged over the Nino 3.4 region. Generally, there are significant correlations of the intra-centennial variations on the averaged and smoothed SST series and global mean SL with the LOD variations. We propose that angular momentum exchange processes involving oceanic circulation and interactions between the Earth’s core and the mantle play probably a part in the observed relationships of intra-centennial variations in oceanic parameters with variations in the LOD.

Improving RUSLE predictions through UAV-based soil cover management factor (C) assessments: A novel approach for enhanced erosion analysis in sugarcane fields

The Universal Soil Loss Equation (USLE) and its derivatives express the combined effects of crop cover and rainfall patterns by the cover and management factor (C). Thus, the C-factor links the combined effect of soil surface roughness, vegetation, biomass cover, and rainfall patterns on soil erosion. This evaluation should be at each phenological stage. Due to the significant time and effort needed to access this factor for a crop, simplified methods are often used, disregarding the expected intra-annual variability and consequently increasing the uncertainty for soil loss modeling. In this scenario, we proposed a framework to collect input data at a fine-scale to estimate the C-factor by the original approach. For this, we collected data with a low-cost UAV at the middle of each phenological stage of sugarcane: sprouting, tillering, elongation, and maturation. We used orthomosaics, three vegetation indices (ExRmG, MGRVI, ViGREEN), digital surface models (DSM), and digital terrain model (DTM) to determine the canopy cover (CC), surface cover (SC), and soil roughness (SR), accessing the soil loss ratio (SLR) per phenological stage. Late on, we estimate the C-factor weighting the SLR by the rainfall erosivity. Our annual C-factor aligns with the most values applied to sugarcane studies and ranged from 0.0241 to 0.2938. Our results pointed out that using the proposed methods can access suitable annual C-factor for sugarcane areas. Furthermore, we highlighted the ViGREEN because it presented a significant performance in orthomosaics classification and has a potential already reported in other studies on C-factor at different scales.

The relationship between salmon (Salmo salar) farming and cell abundance of harmful algal taxa

The effects of nutrient effluents from fish cage aquaculture are an important eutrophication concern. It has been proposed that marine fish farm derived nutrients have the potential to increase phytoplankton abundance and lead to intensification of Harmful Algal Blooms (HABs), and that these blooms may negatively impact both the finfish and the shellfish industry. This study addressed this hypothesis using farmed salmon biomass in Scottish marine waters (as a proxy for nutrient load added to the water column as a consequence of fish farming) cell abundance of HAB taxa that most frequently impact shellfish farms and human health in the region (Dinophysis spp., Alexandrium spp. and Pseudo-nitzschia spp.), and cell abundance of one phytoplankton species of particular concern to the salmon farming industry (Karenia mikimotoi). Data from a 15-year weekly HAB monitoring programme and parallel national monitoring data relating to salmon farm stocking biomass were summarised in 5 km per 5 km aggregation boxes. Linear regression models were used to assess (i) inter-annual variation in cell abundance and total annual farmed salmon biomass; (ii) intra-annual (monthly) variation in harmful phytoplankton cell abundance and salmon biomass; (iii) a further analysis included seasonal effects within the intra-annual analysis. Farmed salmon biomass alone had a non-significant effect on cell abundance of any of the studied phytoplankton taxa. In contrast, a significant effect on cell abundance was found when using location, month or season as the predictive variable. Despite the non-significant impact of fish biomass on phytoplankton counts, the relationship varied seasonally, with a different response of Dinophysis spp. indicating a taxa specific interaction. A possible explanation for the lack of a significant relationship between farmed salmon and harmful phytoplankton cell abundance is that aquaculture farms are generally located in hydrodynamically energetic locations where recurrent flushing likely allows efficient dilution of nutrients. Overall, the analyses suggest that current levels of salmon farming activities do not markedly impact the abundance of routinely monitored biotoxin producing or fish killing phytoplankton taxa in Scottish waters.

Detection and attribution of intra-annual mass component of sea-level variations along the Norwegian coast

Reliable sea-level observations in coastal regions are needed to assess the impact of sea level on coastal communities and ecosystems. This paper evaluates the ability of in-situ and remote sensing instruments to monitor and help explain the mass component of sea level along the coast of Norway. The general agreement between three different GRACE/GRACE-FO mascon solutions and a combination of satellite altimetry and hydrography gives us confidence to explore the mass component of sea level in coastal areas on intra-annual timescales. At first, the estimates reveal a large spatial-scale coherence of the sea-level mass component on the shelf, which agrees with Ekman theory. Then, they suggest a link between the mass component of sea level and the along-slope wind stress integrated along the eastern boundary of the North Atlantic, which agrees with the theory of poleward propagating coastal trapped waves. These results highlight the potential of the sea-level mass component from GRACE and GRACE-FO, satellite altimetry and the hydrographic stations over the Norwegian shelf. Moreover, they indicate that GRACE and GRACE-FO can be used to monitor and understand the intra-annual variability of the mass component of sea level in the coastal ocean, especially where in-situ measurements are sparse or absent.

Collections of small urban parks consistently support higher species richness but not higher phylogenetic or functional diversity.

When prioritizing regions for conservation protection, decisions are often based on the principle that a single large reserve should support more species than several small reserves of the same total area (SLOSS). This principle remains a central paradigm in conservation planning despite conflicting empirical evidence and methodological concerns. In urban areas where small parks tend to dominate and policies to promote biodiversity are becoming increasingly popular, determining the most appropriate prioritization method is critical. Here, we document the role of SLOSS in defining the seasonal diversity of birds in 475 parks in 21 US cities. Collections of small parks were consistently associated with higher species richness, spatial turnover and rarity. Collections of both small and large parks were associated with higher phylogenetic and functional diversity whose patterns varied across seasons and cities. Thus, collections of small parks are a reliable source of species richness driven by higher spatial turnover and rarity, whereas collections of both small and large parks contain the potential to support higher phylogenetic and functional diversity. The presence of strong intra-annual and geographical variation emphasizes the need for regional prioritization strategies, where multiple diversity metrics are examined across parks and seasons.

Techno-economic analysis of marine hybrid clusters in two potential Latin American markets

Contemporary communities require innovative solutions to cope with projected increases in demand for natural resources. Diversification and modernization of the energy matrix through the affordable and efficient harnessing of marine renewable energies (MRE) are possible means to mitigate the vulnerability of coastal communities and climate change. While the offshore wind sector has reached sufficient maturity to compete in the energy market, other MRE, such as wave energy, are still in the development phase, which limits their financing and commercial deployment. This study aims to evaluate the techno-economic feasibility of maritime hybrid clusters (MHC) powered by wave energy converters (WEC) and offshore wind turbines (OWT) to electrify households and the marine aquaculture sector, where electricity surpluses can be stored in lithium-ion batteries or for green hydrogen production. Different scenarios for WaveDragon (WD) and Pelamis (PEL) WEC farms were studied in two coastal communities, Coquimbo (Chile) and Ensenada (Mexico). The mean annual wave power availability at Coquimbo is high (26.05 kW/m) and of Ensenada, moderate (13.8 kW/m). The wave energy shows less inter- and intra-annual variability in Coquimbo than in Ensenada. The hybridization between WECs and OWT covers the total electricity consumption, where the PEL-OWT system is the cost-effective option in Ensenada and WD-OWT in Coquimbo. Ensenada demonstrated a higher electricity surplus than Coquimbo, profitable result of storing it to sale in the electricity market or for hydrogen production. For both selected WECs, the seaweed aquaculture integration in a blue economy framework generates higher returns than households, higher in Coquimbo than Ensenada.

Environmental Drivers of Immature Ixodes scapularis in Minnesota's Metro Area.

Research on the public health significance of Ixodes scapularis ticks in the Midwest seldom focuses on extreme weather conditions that can modulate their population dynamics and ability to transmit pathogenic organisms. In this study, we assessed whether the distributional abundance of I. scapularis immatures is associated with current and time-lagged climatic determinants either directly or indirectly. We analyzed a 20-year longitudinal small mammal live-trapping dataset within a seven-county metropolitan area in Minnesota (1998-2016) using yearly tick counts at each site to assess whether inter- and intra-annual variation in immature I. scapularis counts is associated with climate and land-use conditions. We found that (1) immature I. scapularis ticks infesting mammals expanded southwesterly over the study period, (2) eastern chipmunks, Tamias striatus, supplied a substantial proportion of nymphal blood meals, (3) a suite of climatological variables are demonstrably associated with I. scapularis presence, and abundance across sites, most notably summer vapor pressure deficit, and (4) immature I. scapularis display an affinity for deciduous forests in metro areas. Our results suggest that climatic and land-type conditions may impact host-seeking I. scapularis ticks through numerous mechanistic avenues. These findings extend our understanding of the abiotic factors supporting I. scapularis populations in metro areas of the upper Midwest with strong implications for discerning future tick-borne pathogen risk.

Atmospheric CO2 inversion reveals the Amazon as a minor carbon source caused by fire emissions, with forest uptake offsetting about half of these emissions

Abstract. Tropical forests such as the Amazonian rainforests play an important role for climate, are large carbon stores and are a treasure of biodiversity. Amazonian forests have been exposed to large-scale deforestation and degradation for many decades. Deforestation declined between 2005 and 2012 but more recently has again increased with similar rates as in 2007–2008. The resulting forest fragments are exposed to substantially elevated temperatures in an already warming world. These temperature and land cover changes are expected to affect the forests, and an important diagnostic of their health and sensitivity to climate variation is their carbon balance. In a recent study based on CO2 atmospheric vertical profile observations between 2010 and 2018, and an air column budgeting technique used to estimate fluxes, we reported the Amazon region as a carbon source to the atmosphere, mainly due to fire emissions. Instead of an air column budgeting technique, we use an inverse of the global atmospheric transport model, TOMCAT, to assimilate CO2 observations from Amazon vertical profiles and global flask measurements. We thus estimate inter- and intra-annual variability in the carbon fluxes, trends over time and controls for the period of 2010–2018. This is the longest period covered by a Bayesian inversion of these atmospheric CO2 profile observations to date. Our analyses indicate that the Amazon is a small net source of carbon to the atmosphere (mean 2010–2018 = 0.13 ± 0.17 Pg C yr−1, where 0.17 is the 1σ uncertainty), with the majority of the emissions coming from the eastern region (77 % of total Amazon emissions). Fire is the primary driver of the Amazonian source (0.26 ± 0.13 Pg C yr−1), while forest carbon uptake removes around half of the fire emissions to the atmosphere (−0.13 ± 0.20 Pg C yr−1). The largest net carbon sink was observed in the western-central Amazon region (72 % of the fire emissions). We find larger carbon emissions during the extreme drought years (such as 2010, 2015 and 2016), correlated with increases in temperature, cumulative water deficit and burned area. Despite the increase in total carbon emissions during drought years, we do not observe a significant trend over time in our carbon total, fire and net biome exchange estimates between 2010 and 2018. Our analysis thus cannot provide clear evidence for a weakening of the carbon uptake by Amazonian tropical forests.

Anthropogenic activities significantly increase annual greenhouse gas (GHG) fluxes from temperate headwater streams in Germany

Abstract. Anthropogenic activities increase the contributions of inland waters to global greenhouse gas (GHG; CO2, CH4, and N2O) budgets, yet the mechanisms driving these increases are still not well constrained. In this study, we quantified year-long GHG concentrations, fluxes, and water physico-chemical variables from 28 sites contrasted by land use across five headwater catchments in Germany. Based on linear mixed-effects models, we showed that land use was more significant than seasonality in controlling the intra-annual variability of the GHGs. Streams in agriculture-dominated catchments or with wastewater inflows had up to 10 times higher daily CO2, CH4, and N2O emissions and were also more temporally variable (CV > 55 %) than forested streams. Our findings also suggested that nutrient, labile carbon, and dissolved GHG inputs from the agricultural and settlement areas may have supported these hotspots and hot-moments of fluvial GHG emissions. Overall, the annual emission from anthropogenic-influenced streams in CO2 equivalents was up to 20 times higher (∼ 71 kg CO2 m−2 yr−1) than from natural streams (∼ 3 kg CO2 m−2 yr−1), with CO2 accounting for up to 81 % of these annual emissions, while N2O and CH4 accounted for up to 18 % and 7 %, respectively. The positive influence of anthropogenic activities on fluvial GHG emissions also resulted in a breakdown of the expected declining trends of fluvial GHG emissions with stream size. Therefore, future studies should focus on anthropogenically perturbed streams, as their GHG emissions are much more variable in space and time and can potentially introduce the largest uncertainties to fluvial GHG estimates.

Snow Cover on the Tibetan Plateau and Topographic Controls

Snow cover plays a critical role in global energy and water cycles. Snow cover on the Tibetan Plateau (TP) provides vital water sources in western China and Himalayan regions, in addition to its weather and climate significance. The massive high mountain topography of the TP is the main condition for the presence and persistence of snow cover on the plateau at the mid-low latitudes of the Northern Hemisphere (NH). However, how the mountain topography controls snow-cover distribution on the TP remains largely unclear, and the relationship is not well quantified. Here, the spatial distribution and the topographic controls of snow cover on the TP are examined based on snow cover frequency (SCF) derived from MODIS snow cover product (MOD10A2 v005) and digital elevation model (DEM) data. The results show that snow cover on the TP is spatially unevenly distributed, and that it is characterized by rich snow and high SCF on the interior and the surrounding high mountain ranges, with less snow and low SCF in inland basins and river valleys. Snow cover on the TP presents elevation dependence: the higher the altitude, the higher the SCF, the longer the snow cover duration, and the more stable the intra-annual variation. The annual mean SCF below 3000 m above sea level (m a.s.l) is less than 4%, and it reaches 77% above 6000 m a.s.l. The intra-annual snow cover variation below 4000 m a.s.l features a unimodal distribution, while above 4000 m a.s.l it presents a bimodal distribution. The mean minimum SCF below 6000 m a.s.l occurs in summer, while above 6000 m a.s.l it occurs in winter. Due to differences in solar radiation and moisture condition caused by the mountain slope and aspect, the mean SCF generally increases with mountain slopes, and it is the highest on the north-facing aspect and the lowest on the south-facing aspect.

Analysis of the impact of the Xiaolangdi Reservoir on the runoff of the Yellow River downstream based on CEEMDAN-multiscale information entropy.

Water resources are vital to the development of human society, and mastering the law of runoff changes is the basis for achieving sustainable use of water resources. To study the impact of reservoir construction on the changes of downstream river runoff, this paper decomposes the runoff before and after reservoir construction using the CEEMDAN method based on the runoff data from the Huayuankou hydrological station. The fluctuation characteristics of each decomposition series of runoff before and after reservoir construction and the intra-annual variation pattern of runoff are also analyzed by combining multi-time information entropy and coefficient of variation. The results show that after the operation of the Xiaolangdi Reservoir, the annual runoff variation cycle tends to be flat, and the monthly runoff cycle is significantly reduced. After reservoir construction, the entropy values of each IMF and Res of runoff become larger, the complexity and randomness of runoff changes increase, and predictability decreases. Before and after the operation of the Xiaolangdi Reservoir, the coefficient of variation of runoff were 0.28-1 and 0.38-0.83, the distribution of runoff was more uniform, and the percentage of runoff in the flood season was reduced from 51.51 to 39.89%.

Intra-Annual Variability of the Immune System Organs and Lysozyme Levels in the Male Pike Esox lucius L.

Intra-Annual Variability of the Immune System Organs and Lysozyme Levels in the Male Pike Esox lucius L.

The Spatio-Temporal Cloud Frequency Distribution in the Galapagos Archipelago as Seen from MODIS Cloud Mask Data

Clouds play an important role in the climate system; nonetheless, the relationship between climate change in general and regional cloud occurrence is not yet well understood. This particularly holds for remote areas such as the iconic Galapagos archipelago in Ecuador. As a first step towards a better understanding, we analyzed the spatio-temporal patterns of cloud cover over Galapagos. We found that cloud frequency and distribution exhibit large inter- and intra-annual variability due to the changing influence of climatic drivers (trade winds, sea surface temperature, El Niño/La Niña events) and spatial variations due to terrain characteristics and location within the archipelago. The highest cloud frequencies occur in mid-elevations on the slopes exposed to the southerly trade winds (south-east slopes). Towards the highlands ( >900 m a.s.l), cloud frequency decreases, with a sharp leap towards high-level crater areas mainly on Isabela Island that frequently immerse into the trade inversion layer. With respect to the diurnal cycle, we found a lower cloud frequency over the islands in the evening than in the morning. Seasonally, cloud frequency is higher during the hot season (January–May) than in the cool season (June–December). However, spatial differences in cloudiness were more pronounced during the cool season months. We further analyzed two periods beyond average atmospheric forcing. During El Niño 2015, the cloud frequency was higher than usual, and differences between altitudes and aspects were less pronounced. La Niña 2007 led to negative anomalies in cloud frequency over the islands, with intensified differences between altitude and aspect.