Transition Dates Research Articles

Subsurface Temperature Anomalies Off Central Oregon During 2014–2021

AbstractWe use moored observations in 80 m water depth at the NH‐10 site along the historic Newport Hydrographic Line from 1999 to 2021 to calculate water temperature anomalies at the surface, near surface, and bottom. Analysis is focused on the subsurface temporal and spatial characteristics of marine heatwaves (MHWs) during 2014–2016 and 2019–2020 on the continental shelf and slope. Warm anomalies extend throughout the water column in fall/winter 2014–2016 when winds are predominantly downwelling‐favorable, while the 2019–2020 period is characterized by shallower summer and fall anomalies on the shelf. Sustained temperature anomalies during the bottom MHW in late 2016 are the largest in the NH‐10 time series. Analysis of temporal patterns in wind stress during MHW and non‐MHW periods shows the onset of upwelling‐favorable winds interrupts warm events. Indices of cumulative upwelling and annual spring transition dates reveal the spring transition was unusually late in 2014, with only five years with later spring transitions since the upwelling index record began in 1967. In 2015 and 2019, in contrast, spring transition is close to the climatological mean of April 15. In 2016 and 2020, anomalous warming is observed when cumulative upwelling decreases after an early spring transition.

Агроклиматическая оценка периода перезимовки озимой пшеницы в Центрально-Черноземном экономическом районе

This study was conducted in order to identify the most significant, in terms of influence, agroclimatic indicators of the overwintering period for winter wheat in the territories of the regions that are part of the Central Black Earth Economic Region. For this purpose, meteorological data on average, minimum and maximum air temperature, precipitation and snow cover height for the period from 1993 to 2022 were used, and a correlation and regression analysis of the dependence of the yield of this crop on the calculated indicators was carried out. During the analysis, statistically significant dependences of winter wheat yield on a number of agroclimatic indicators of the overwintering period were considered, revealed when using the Fisher criterion and estimating the P-values of the coefficients of the regression equation. According to the results of the analysis, the most significant indicators of the overwintering period are: the average air temperature for the coldest month and the coldest five-day period, the duration of the period between the dates of a steady transition of air temperature through 0℃ in autumn and spring, as well as the sum of negative air temperatures between these dates. The results obtained can potentially be more visible when using a larger amount of data, as well as when performing multiple regression.

Factors determining the timing of ice appearance on the Kama Reservoir

The analysis and assessment of the correlations of the ice dates vice the zero-isotherm dates, dates of water temperatures transition through 2 and 3 °C were carried out. The initial data were long-term series of observations of air temperature at weather stations, water temperature and ice dates at the gauge stations of Roshydromet for the whole period of the reservoir existence (1956–2021). As the characteristic under study, the dates of ice formation in autumn were used. Main results: verification of previously obtained correlations on independent data (1996–2021) showed that the accuracy of issued forecasts (P) was decreased by 20% compared with the accuracy on dependent data (1956–1995); an analysis of the whole period applicability (1956–2021) for constructing predictive correlations with an assessment of their justification showed that there was no noticeable refinement. The accuracy of the forecasts based on the dates of water temperatures transition through 3 °C has not changed, while forecasts based on the zero-isotherm dates and the dates of water temperatures transition through 2 °C, has noticeably decreased at all stations; the use of data only for the period of modern climate changes (1996–2021) led to the following: correlations of the ice dates vice the zero-isotherm dates and water temperature through 2 °C did not pass the criteria S and P. This period is characterized by a decrease in the frequency of small forecast errors ( 4–5 days) and an increase in large errors ( 6–11 days) by 2–3 times; a forecast technique is proposed based on the separation of the studied correlations for years with different meteorological conditions in autumn (years with stable cooling and with heat returns). The criterion for using this or that dependence in a particular year is the weather forecast. Forecasts issued according to such dependencies have a higher accuracy.

Quantifying City- and Street-Scale Urban Tree Phenology from Landsat-8, Sentinel-2, and PlanetScope Images: A Case Study in Downtown Beijing

Understanding the phenology of urban trees can help mitigate the heat island effect by strategically planting and managing trees to provide shade, reduce energy consumption, and improve urban microclimates. In this study, we carried out the first evaluation of high spatial resolution satellite images from Landsat-8, Sentinel-2, and PlanetScope images to quantify urban street tree phenology in downtown Beijing. The major research goals are to evaluate the consistency in pixel-level spring–summer growth period phenology and to investigate the capacity of high-resolution satellite observations to distinguish phenological transition dates of urban street trees. At the city scale, Landsat-8, Sentinel-2, and PlanetScope show similar temporal NDVI trends in general. The pixel-level analysis reveals that green-up date consistency is higher in areas with medium (NDVI > 0.5) to high (NDVI > 0.7) vegetation cover when the impacts of urban surfaces on vegetation reflectance are excluded. Similarly, maturity date consistency significantly increases in densely vegetated pixels with NDVI greater than 0.7. At the street scale, this study emphasizes the efficacy of NDVI time series derived from PlanetScope in quantifying the phenology of common street tree genera, including Poplars (Populus), Ginkgos (Ginkgo), Chinese Scholars (Styphnolobium), and Willows (Salix), in downtown Beijing to improve urban vegetation planning. Based on PlanetScope observations, we found that the four street tree genera have unique phenological patterns. Interestingly, we found that the trees along many major streets, where Chinese Scholars are the major tree genus, have later green-up dates than other areas in downtown Beijing. In conclusion, the three satellite observation datasets prove to be effective in monitoring street tree phenology during the spring–summer growth period in Beijing. PlanetScope is effective in monitoring tree phenology at the street scale; however, Landsat-8 may be affected by the mixture of land covers due to its relatively coarse spatial resolution.

Using Geostationary Satellite Observations to Improve the Monitoring of Vegetation Phenology

Geostationary satellite data enable frequent observations of the Earth’s surface, facilitating the rapid monitoring of land covers and changes. However, optical signals over vegetation, represented by the vegetation index (VI), exhibit an anisotropic effect due to the diurnal variation in the solar angle during data acquisition by geostationary satellites. This effect, typically characterized by the bi-directional reflectance distribution function (BRDF), can introduce uncertainties in vegetation monitoring and the estimation of phenological transition dates (PTDs). To address this, we investigated the diurnal variation in the normalized difference vegetation index (NDVI) with solar angles obtained from geostationary satellites since the image had fixed observation angles. By establishing a temporal conversion relationship between instantaneous NDVI and daily NDVI at the local solar noon (LSNVI), we successfully converted NDVIs obtained at any time during the day to LSNVI, increasing cloud-free observations of NDVI by 34%. Using different statistics of the time series vegetation index, including LSNVI, daily averaged NDVI (DAVI), and angular corrected NDVI (ACVI), we extracted PTD at five typical sites in China. The results showed a difference of up to 41.5 days in PTD estimation, with the highest accuracy achieved using LSNVI. The use of the proposed conversion approach, utilizing time series LSNVI, reduced the root mean square error (RMSE) of PTD estimation by 9 days compared with the use of actual LSNVI. In conclusion, this study highlights the importance of eliminating BRDF effects in geostationary satellite observations and demonstrates that the proposed angular normalization method can enhance the accuracy of time series NDVI in vegetation monitoring.

Comparison of change-based and shape-based data fusion methods in fine-resolution land surface phenology monitoring with Landsat and Sentinel-2 data

Fine-resolution land surface phenology (LSP) is urgently required for applications on agriculture management and vegetation-climate interaction, especially over heterogeneous areas, such as agricultural lands and fragmented forests. The critical challenge of fine-resolution LSP monitoring is how to reconstruct the spatiotemporal continuous vegetation index time series. To solve this problem, various data fusion methods have been devised; however, the comprehensive inter-comparison is lacking across different spatial heterogeneity, data quality, and vegetation types. We divide these methods into two main categories: the change-based methods fusing satellite observations with different spatiotemporal resolutions, and the shape-based methods fusing prior knowledge of shape models and satellite observations. We selected four methods to rebuilt two-band enhanced vegetation index (EVI2) series based on the harmonized Landsat and Sentinel-2 (HLS) data, including two change-based methods, namely the Spatial and temporal Adaptive Reflectance Fusion Model (STARFM), the Flexible Spatiotemporal DAta Fusion (FSDAF), and two shape-based methods, namely the Multiple-year Weighting Shape-Matching (MWSM), and the Spatiotemporal Shape-Matching Model (SSMM). Four phenological transition dates were extracted, evaluated with PhenoCam observations and the 500 m Visible Infrared Imaging Radiometer Suite (VIIRS) phenology product. The 30 m transition dates show more spatial details and reveal more apparent intra-class and inter-class phenology variation compared with 500 m product. The four transition dates of SSMM and FSDAF (R2>0.74, MAD<15 days) show better agreement with PhenoCam-derived dates. The performance difference between fusion methods over various application scenarios are then analyzed. Fusion results are more robust when temporal frequency is higher than 15 observations per year. The shape-based methods are less sensitive to temporal sampling irregularity than change-based methods. Both change-based methods and shape-based methods cannot perform well when the region is heterogeneous. Among different vegetation types, SSMM-like methods have the highest overall accuracy. The findings in this paper can provide references for regional and global fine-resolution phenology monitoring.

The phenology of the spring phytoplankton bloom in the North Atlantic does not trend with temperature

Climate change is anticipated to alter the phenology of phytoplankton blooms in the ocean, making their recent dynamics of interest to inform models of future ocean states. We characterized temperature change in the North Atlantic using metrics that track the patterns of sea surface water temperature (SST) defined by quantiles. To complement these thermal indicators, we estimated a thermal phenology index in the form of the date of the spring transition, taken as the date that temperature achieved the long-term mean at a specific location. We then used ocean color data (1998–2022) and characterized spring bloom phenology using change point methods to derive bloom initiation, duration, magnitude, and intensity. The North Atlantic has warmed over recent decades, averaging a rate of increase of 0.27°C decade−1, yet throughout most of the basin, spring transition timing has remained constant, with the exception of small areas with either delayed or advanced transitions. There were no clear trends in bloom start or duration in the North Atlantic, indicating that spring bloom phenology was independent of climate-driven temperature change. Bloom magnitude and intensity trended downward in some North Atlantic continental shelf seas, indicating that increased temperatures may have had negative effects on overall bloom productivity. However, exclusive of the areas where the bloom parameters were trending, there was a decrease in magnitude and intensity with warmer winter temperatures, suggesting that the inter-annual variability of these parameters may be affected by thermal conditions at the onset of the bloom. While temperature has increased in the North Atlantic, vernal light availability has remained unchanged, which may explain why spring bloom phenology has remained resistant to climate change. Consequently, it seems plausible that future climate change may have limited effects on spring bloom phenology, but could have substantial effects on overall phytoplankton production.

Measurement of Energy and Power Quality in the Spanish Des-regulated Market

The spanish electrical sector is, since 1997, becoming opened to a free deregulated market, in a progressive way, step by step, finishing the process the next 2007. One of the keys of this deregulation has been the reform of the Spanish regulation for the electrical metering points, necessary for adapt the energy meter fleet to the new needs of the market. This changes in the regulation have arrived later than the transition date for the different steps. Despite this, the different steps have been accelerated, and, since 1st of January of 2003, any electrical consumer can compete for being in the deregulated market. In this article it is tried to give a practical point of view and summarize, the different types of energy meters, depending of the level of consumer.

Temperature Dependence of the Breeding Parametres of the Collared Flycatcher (Passeriformes, Muscicapidae) in the National Park Homilshanski Lisy (NE Ukraine)

The breeding phenology of Collared Flycatchers was studied over an 11-year period (2006‒2011 and 2013‒2017) in oak-maple-lime stands located in the Northern-East of Ukraine (in the National Park Homilshanski Lisy). In most years, egg laying began in the first and second ten-day periods of May. The earliest recorded first-egg date (368 broods) was 23 April, while the latest was 5 May. These dates varied from year to year. The relationship between the first-egg date and the date of daily average temperature transition through + 10 °C suggests that birds bred earlier due to warmer local temperatures. The clutch size was negatively correlated with the date of the average air temperature transition through + 5 °C. The earliest hatching date was 15 May, and the latest was 25 May. Fledging typically began in the first half of June. The breeding season’s length ranged from 30 to 42 days, and the breeding cycle was positively correlated with the transition of the average daily temperature through +5 °C. To determine which factors explained the first egg date and clutch size, Generalized Linear Models (GLMs) were conducted. GLMs suggest a correlation between the first-egg date and the sum of effective temperatures (∑T150), arrival date temperature, migration route temperature, and average temperature of the third decade of April. Clutch size is determined by the sum of effective temperature accumulation (∑130) and migration route temperature. Reproductive success is negatively correlated with the average of 30 daily temperatures until the median date.

ОСОБЛИВОСТІ РОЗКРИТТЯ ІНФОРМАЦІЇ У ФІНАНСОВІЙ ЗВІТНОСТІ ЗА МІЖНАРОДНИМИ СТАНДАРТАМИ

In Ukraine, quite a few enterprises prepare reports in accordance with international standards: large enterprises, public joint stock companies, insurance companies, private pension funds, and others. The article provides statistical data on the number of enterprises that are required to prepare reports in accordance with international standards by type and year. The main motivation for the decision to switch to international financial reporting is the need to attract foreign investment in the company's operations. The most expensive assets of such enterprises are usually fixed assets, which are available at each enterprise and, accordingly, depreciated. The start date of depreciation under national and international standards is different. The proposed sequence of actions in recalculating the amount of accrued depreciation of fixed assets as of the date of transition to international standards will allow to reliably assess their carrying amount. The paper describes the peculiarities of preparing notes to the financial statements in accordance with international standards. It is established that the financial statements prepared in accordance with international standards are significantly expanded in relation to the financial statements of Ukrainian enterprises prepared in accordance with NAR(S). The main indicators in the notes to the financial statements prepared in accordance with IFRS of many companies are similar. However, some companies highlight specific features related to their core business. Each analysed company, in addition to the accounting policy, discloses in detail in the notes those accounting items that best characterise its business activities. It was found that some of the analysed companies in their accounting policies for fixed assets do not comply with the minimum terms of their use provided for by the Tax Code of Ukraine, which leads to misstatement of financial statements. From year to year, the number of Ukrainian companies preparing financial statements in accordance with international standards is increasing due to legal requirements or business motives: entering the foreign market, searching for and attracting foreign investors, establishing joint ventures, etc. Financial statements prepared in accordance with IFRS allow for a broader presentation of information about the company's activities, in particular, by using a taxonomy and expanded presentation of information about the company's activities in the notes.

Drivers of contemporary and future changes in Arctic seasonal transition dates for a tundra site in coastal Greenland.

Climate change has had a significant impact on the seasonal transition dates of Arctic tundra ecosystems, causing diverse variations between distinct land surface classes. However, the combined effect of multiple controls as well as their individual effects on these dates remains unclear at various scales and across diverse land surface classes. Here we quantified spatiotemporal variations of three seasonal transition dates (start of spring, maximum normalized difference vegetation index (NDVImax ) day, end of fall) for five dominating land surface classes in the ice-free Greenland. Using a distributed snow model, structural equation modeling, and a random forest model, based on ground observations and remote sensing data, we assessed the indirect and direct effects of climate, snow, and terrain on seasonal transition dates. We then presented new projections of likely changes in seasonal transition dates under six future climate scenarios. The coupled climate, snow cover, and terrain conditions explained up to 61% of seasonal transition dates across different land surface classes. Snow ending day played a crucial role in the start of spring and timing of NDVImax . A warmer June and a decline in wind could advance the NDVImax day. Increased precipitation and temperature during July-August are the most important for delaying the end of fall. We projected that a 1-4.5°C increase in temperature and a 5%-20% increase in precipitation would lengthen the spring-to-fall period for all five land surface classes by 2050, thus the current order of spring-to-fall lengths for the five land surface classes could undergo notable changes. Tall shrubs and fens would have a longer spring-to-fall period under the warmest and wettest scenario, suggesting a competitive advantage for these vegetation communities. This study's results illustrate controls on seasonal transition dates and portend potential changes in vegetation composition in the Arctic under climate change.

Patterns of runoff fluctuations of the Dniester River (Ukraine) under conditions of climate change at the beginning of the 21st century

The relevance of the chosen topic is associated with the impact of climate change on fluctuations of water content in Ukrainian rivers. The consequences of warming depend on physical and geographical conditions and vary significantly across different natural zones. The behaviour of catchment areas affected by climate change varies depending on landscape (mountainous or flat terrain) and latitude. This results in instability of boundaries of catchment areas with annual runoff synchronous and out-of-phase fluctuations. The study aims at establishing the patterns of annual runoff fluctuations in the Dniester basin with relation to fluctuations in the maximum runoff of rainfalls and spring floods. The spring floods are the ones that determine a significant part of annual runoff and depend on the impact of warming during the winter season. The study's main method is the method of constructing difference integral curves of annual and maximum rainfalls and maximum spring runoff and their analysis. There are 7 groups (zones) within the Dniester River catchment area identified by the type of difference integral curves of annual runoff. Fluctuations in annual, maximum rain and spring runoff were compared using the curves averaged within each group. The degree of synchronicity of fluctuations was estimated via correlation coefficients between the ordinates of difference integral curves. It was found that the main river oscillations retain their cyclicity along its entire length, even below the Dniester HPP. The last transition to a low-water phase occurred in 2010-2011. It was discovered that the main river's cyclical nature mostly results from fluctuations in the runoff of mountainous Carpathian tributaries that form the Dniester's runoff formation zone. This part of the catchment area is characterized by a high amount of snow and rainfalls feeding the river with the role of rainfalls having a predominant character. In the upper reaches of Carpathian rivers, where the impact of warming is not yet sufficiently pronounced at high altitudes, spring floods play a significant role in runoff formation. In the upper reaches of Carpathian rivers there is an additional zone where fluctuations in annual runoff are caused by both rainfalls and spring floods. The boundaries of this zone (2nd district) may change as the effects of warming increase high in the mountains. On the left-bank tributaries, the runoff fluctuations in Verkhnepodilskyi and Serednepodilskyi districts are similar to those of the main river, however, there is a shift in the dates of the last transition to a low-water phase. The study indicates the likelihood of karst and artificial reservoirs influence. It also indicates a significant difference in the nature of runoff fluctuations of the upper left-bank tributaries (Strvyazh, Vereshchytsia, Shcherek) and lower left-bank tributaries. They are affected by other atmospheric processes and climatic factors associated with such processes.

Spring to summer transition timing influences zooplankton phenology and temporal niche partitioning in the coastal zone of the White Sea

Climatic changes are manifested through temporal shifts of seasonal events in environment, which may be critical for planktonic organisms. Temporal shift of seasonal warming curve in high latitudes affects phenology of aquatic organisms. Significant correlation between timing of phenological events in the life cycles of planktonic copepods and spring-summer temperature transition dates was revealed by canonical correlation analysis. We analyzed the long-term zooplankton and temperature time series (1961–2018) from the White Sea (66°19'50"N; 33°40'06"E, near the White Sea Biological Station of the Zoological Institute of the Russian Academy of Sciences). Two types of seasonal abundance dynamics of copepod juveniles and four types of the spring to summer transition were revealed. Each species demonstrated specific dynamics in response to each type of spring to summer transition. Species with similar ecological traits differed in their phenological response to the changes in the temperature dynamics. This phenomenon was explained, at least partly, by niche partitioning, when temporal niches of ecologically similar species were separated as a result of shifting the phenological events in time. The latter, in turn, was the result of organisms’ response to changes of spring to summer transition dynamics from year to year. We hypothesize that such separation may be one of the solutions of the “Paradox of the plankton”, favouring success of species-rich planktonic communities in high-latitude ecosystems, characterized by relative paucity of food resources and short productive season.

ESTIMATION OF WORKING LIFE EXPECTANCY: APPLICATION OF A MULTISTATE MARKOV MODEL

Abstract Longer life expectancy in Western countries has led to concerns about sustainable workforces amid the rising costs of securing aging populations. Retirement age is no more a good indicator of the end of the working life, because many older workers move in-and-out of workforce. A more useful measure is working life expectancy (WLE), which is the expected number of remaining years from a given age that a person will work. This measure considers transitions across different employment states. The method adopted for estimation of WLE is along the same line to estimate health expectancy (HE) based on cross-sectional data without considering transitions in different states of work over time. A better approach is based on multi-state survival models considering transitions among states over time using longitudinal data. These models assume a Markov Process to estimate transition probabilities. WLE is the weighted sum of duration of stay in a state weighted by the transition probabilities. The method adopted in IDEAR consortium is a multistate survival model assuming a first-order Markov process in continuous time to estimate transition probabilities. Transition probabilities are estimated by the msm package. This model takes care of interval censoring where the exact dates of transitions from one state to another is not known. WLEs are estimated by using the package elect (van den Hout, 2019) incorporating age as a time dependent variable by using a Gompertz model instead of the exponential model. The method is demonstrated to estimate WLE using Swedish Longitudinal Occupational Survey of Health (SLOSH).

Multiscale phenology of seasonally dry tropical forests in an aridity gradient

The leaf phenology of seasonally dry tropical forests (SDTFs) is highly seasonal, marked by synchronized flushing of new leaves triggered by the first rains of the wet season. Such phenological transitions may not be accurately detected by remote sensing vegetation indices and derived transition dates (TDs) due to the coarse spatial and temporal resolutions of satellite data. The aim of this study was to compared TDs from PhenoCams and satellite remote sensing (RS) and used the TDs calculated from PhenoCams to select the best thresholds for RS time series and calculate TDs. For this purpose, we assembled cameras in seven sites along an aridity gradient in the Brazilian Caatinga, a region dominated by SDTFs. The leafing patterns were registered during one to three growing seasons from 2017 to 2020. We drew a region of interest (ROI) in the images to calculate the normalized green chromatic coordinate index. We compared the camera data with the NDVI time series (2000–2019) derived from near-infrared (NIR) and red bands from MODIS product data. Using calibrated PhenoCam thresholds reduced the mean absolute error by 5 days for SOS and 34 days for EOS, compared to common thresholds in land surface phenology studies. On average, growing season length (LOS) did not differ significantly among vegetation types, but the driest sites showed the highest interannual variation. This pattern was applied to leaf flushing (SOS) and leaf fall (EOS) as well. We found a positive relationship between the accumulated precipitation and the LOS and between the accumulated precipitation and maximum and minimum temperatures and the vegetation productivity (peak and accumulated NDVI). Our results demonstrated that (A) the fine temporal resolution of phenocamera phenology time series improved the definitions of TDs and thresholds for RS landscape phenology; (b) long-term RS greening responded to the variability in rainfall, adjusting their timing of green-up and green-down, and (C) the amount of rainfall, although not determinant for the length of the growing season, is related to the estimates of vegetation productivity.

The influence of climatic factors on the vegetative development of introduced Pinus pumila (Pall.) Regel at the Polar-Alpine Botanical Garden-Institute

The article describes the vegetative development of introduced Pinus pumila (Pall.) Regel that grow in the experimental area of the Polar-Alpine Botanical Garden and Institute (the surroundings of the town Apatity). It gives the generalized over several years dates of the beginning of the main vegetative phenophases, the duration of the lateral shoot linear growth and needles, the sum of active and effective temperatures above 5 and 10 °C. To identify interrelations between phenodates and climatic factors, a correlation analysis was carried out (Spearman’s rank correlation coefficient was used). The sum of effective temperatures above 10 °C and the sum of precipitation varies greatly from year to year. Medium, strong and very strong correlations were found between: the dates of the beginning of various phenophases and the dates of a stable transition through 0, 5, 10 °C; sums of active and effective temperatures; average temperature and air humidity for 5, 10 and 30 days before the beginning of the phenophase; the date of isolation of а wintering apical bud in the last growing season and the environmental conditions preceding its isolation. The length of shoots and needles was measured for 2016-2021. Significant correlations between the length of shoots and needles and phenodates and selected climatic factors were not found.

Seasonal and Inter-Annual Variability of Water Temperature in Petrozavodsk Bay of Lake Onega

Abstract—Based on year-round measurements of water temperature at an autonomous station (an anchored chain equipped with temperature sensors), the features of the temperature and ice regimes of the Petrozavodsk Bay of Onega Lake in modern climatic conditions were studied; the dates and duration of the main hydrological phenomena in the water area of the bay were specified. In the abnormally warm winter of 2019–2020, the water area of the Petrozavodsk Bay was not completely covered with ice for the first time in a long period of observations; in the area of the measurement station, ice fields were observed from late January to mid-March. The duration of ice-covered period in the next two winters was 3.5 and 5 months. Data were obtained on the timing of the onset and duration of the spring under-ice convection, a phenomenon that plays an important role in the thermal regime of the lake at the end of winter. It is shown that 2016, 2021 and 2022 spring under-ice convective mixing lasted 4–6.5 weeks, covering the entire water column by the end of ice period. Mixing of the water column after breaking the ice (spring homothermy) continued for another 3–4 weeks. In the spring of 2020, under-ice convection was not observed; spring overturn continued for two months from mid-March to mid-May. The dates of the upward transition of water temperature through 4°C in the years of measurements (5–19 May) were ahead of the long-term average by 2–3 weeks (end of May). Thermal stratification was established from 12 to 27 May and existed for 3–3.5 months. Complete mixing of the water mass of the bay took place in late August–early September, and then, until ice settling, the water column cooled in a state of homothermy. Immediately before ice formation, the water temperature dropped to very low values and did not exceed 0.1°С in the water column. The period with an average daily water temperature of the surface layer of the Petrozavodsk Bay above 10°C lasted from 121 to 144 days during the years of measurements.

Division of the tropical savanna fire season into early and late dry season burning using MODIS active fires

Tropical savannas and grasslands are the most frequently burned biome in the world, and fire has an important role in sustaining ecosystem processes. Modern management of fires in savannas has roots in traditions stretching back centuries, and nowadays earth observation data is incorporated extensively in fire management practices. In tropical savannas in particular strongly seasonal monsoonal climates allow relatively low severity prescribed burning in the early part of the dry season (EDS) with the goal of preventing more destructive late dry season (LDS) fires. In many regional contexts it is common that a specific, fixed date is used officially to indicate when the window of safe burning has expired and the EDS transitions to the LDS, based on the experience of local or regional fire management authorities. This approach, while practical, neglects inter-annual variability in meteorological conditions and timing of onset of more dangerous fire weather. In this study, we pro-pose a remote sensing-based method for determining when this EDS window expires for five savanna-dominated continental-scale regions. By taking ad- vantage of the fact that conditions allowing night-time burning occur later in the dry season, we use day and night-time active fire detections from the MODerate Resolution Imaging Spectroradiometer (MODIS) instruments to set a flexible date of transition between the EDS and LDS. The vast majority of tropical savannas have very variable (std. dev. ≈ 20–40 days) transition dates, though this is somewhat modulated by fire frequency. Fuel connectivity rather than fuel condition appears to be a strong driving factor behind this variability. We find that especially national parks and protected areas have a high proportion of potentially more severe burning in the LDS, though areas with well-established EDS burning programmes are reducing this impact.

Prediction of South China Sea summer monsoon onset in the CAMS‐CSM climate forecast system

AbstractBased on a set of hindcast experiments from 2011 to 2020, the prediction skills of the Chinese Academy of Meteorological Science Climate System Model (CAMS‐CSM) climate forecast system (CFS) on the abrupt changes and characteristic processes associated with the South China Sea summer monsoon (SCSSM) establishment are evaluated. We studied predictions for three different lead times, that is, LT1‐30, LT31‐60 and LT61‐90. The CAMS‐CSM CFS captures the climatological SCSSM onset date at all lead times, while the prediction skill of the SCSSM onset index decreases with the increasing lead times. The features of abrupt changes and characteristic processes related to the SCSSM establishment can be generally reproduced in the predictions, but different biases exist at three lead times. Besides, the CAMS‐CSM CFS provides higher skill on the transition of the zonal wind shear (ZWS) than that of meridional temperature difference (MTG). The transition date of MTG can only be accurately predicted at LT1‐30, indicating the limited ability of predicting temperature. Further results confirm that the CFS cannot well capture the eastward withdrawal of the western North Pacific subtropical high on late onset years, thereby leading a poorer prediction skill than early onset years. In addition, skillful prediction on the eastward extension of westerlies from the equatorial Indian Ocean to SCS also contributes to increase predictability of SCSSM onset.

Drier August and colder September slow down the delaying trend of leaf senescence in herbaceous plants on the Qinghai–Tibetan Plateau

Plant phenological shifts on the Qinghai–Tibetan Plateau (QTP) have gained considerable attention over the last few decades. However, temporal changes in plant autumn phenology and the main driving factors remain uncertain. Most previous studies used satellite-derived phenological transition dates and climatic statistics during the preseason, which have relatively large uncertainties and may mask some important climate change characteristics at the intra-annual scale, thus affecting exploration of the underlying phenological change causes. This study collected 1685 phenological records at 27 ground stations on the QTP during 1983–2017. Temporal change trends and break points in leaf senescence date (LSD) of 23 herbaceous species were assessed using least squares regression, a meta-analysis procedure, and the Pettitt test. The main drivers and causes were investigated through correlation analysis and contribution calculation based on LSD observations and monthly climatic data. Results showed that, LSD of QTP herbaceous plants was significantly delayed at a rate of 4.45 days/decade during 1983–2017. Break points were concentrated during 1999–2003, with an overall mean in 2001. After 2001, the delay trend in LSD decreased, falling from 5.26 days/decade to 2.54 days/decade. Air temperature and precipitation were the most important climatic factors that showed closer and more extensive correlations with LSD and greater contributions to the inter-annual variations in LSD. August and September were the most critical period during which climatic factors had higher contributions to the LSD shifts. However, August was drier, with precipitation significantly decreasing and temperature increasing, and September was colder after 2001. Therefore, the declining trend in LSD may be attributed to the drier August and colder September. This study has not only provided reliable field evidence on temporal changes in autumn phenology on the QTP, but has also provided valuable insights into autumn phenological modelling and regional carbon cycling in alpine regions.