Interannual Temperature Variability Research Articles

Влияние погодных условий на процесс массового развития цианобактерий в Куйбышевском водохранилище

According to observation data in the summer period 2016-2021. The interannual variability of weather conditions, water temperature and chlorophyll (Chl) content in the Kuibyshev Reservoir was considered. Regular observations were carried out at the outlet section of the reservoir (Zhigulevsky hydroelectric complex) under conditions of complete mixing of water masses. It has been established that the main factors influencing the process of mass development of cyanobacteria (MDC) are thermal regime and weather conditions. With increasing water temperature, the interval and degree of favorable activity of cyanobacteria increases. Over a 6-year period, the average interval was 44 days, the largest was 72 days, and the smallest was 11 days. The degree of favorability varied widely: from low (23 °С ˃ t ˃ 22 °С) to extreme high (t ˃ 26 °С). The most favorable years for the MRC process were 2016 and 2021, when the Chl content during the summer period was 6.2 and 7.2 μg/dm3, respectively. The least favorable years were 2017 and 2019, when the Chl content during the summer period was 0.6 and 1.4 μg/dm3, respectively. Seasonally, the temperature optimum was observed annually in July. The Chl content in July 2021 was 12.6 μg/dm3, and in the cold July 2017 – 0.7 μg/dm3. Significant variability of the MRC process is due to synoptic cyclicity and changing weather conditions. The established influence of thermal regime and weather conditions on the content of chlorophyll suggests that in conditions of global warming, the process of mass development of cyanobacteria is expected to intensify, which will negatively affect the ecological state and water quality of the Kuibyshev Reservoir.

Yield and nutritional quality of intercropped forages for organic production in a hot-summer Mediterranean oak grassland ecosystem

Context Forage cultivation plays a pivotal role in sustaining ruminants in resource-limited ecosystems such as the hot-summer Mediterranean agroforestry systems of the Iberian Peninsula comprising oak trees (Quercus spp.) and grassland species. Intercropping techniques can enhance forage yields and nutritional quality. Aims This study assessed the yield and nutritional quality of organic forage mixtures in an Iberian oak grassland ecosystem. Methods Six forage associations were assessed over two growing seasons: vetch (Vicia sativa L.)–triticale (Triticum × Secale), vetch–rye (Secale cereale), vetch–oat (Avena sativa), pea (Pisum sativum L.)–triticale, pea–rye, and pea–oat. The data were analysed using a multivariate procedure. Key results Differences in forage composition influenced nutritional quality but not yield. Vetch-based associations exhibited higher crude protein, calcium, phosphorus, potassium, zinc, magnesium, manganese and sulfur contents, along with lower proportions of neutral-detergent fibre and ether extract. The vetch–oat mixture emerged as the highest quality association. Interannual variations in precipitation and temperature caused differences in forage yield, with greater values observed in 2020 than in 2019. Forage associations also had significantly higher nutritional quality in 2020 (increased protein and mineral content, and decreased neutral detergent fibre and lignin). Conclusions All forages demonstrated satisfactory performance and quality, even in the drier conditions of 2019, suggesting high resilience and adaptability to hot-summer Mediterranean oak grassland ecosystems. Implications The findings of this study are relevant for organic farmers in resource-limited ecosystems. This information empowers them to select the most suitable forage species based on the specific agroclimatic conditions of each growing season.

Interannual variability of ice cover across Davis Strait and the Labrador Sea for the period from 1979 to 2023

In conditions of rapid development of trade and transport communications, the issue of navigation through ice regime zones became of greater importance. In particular, reduction of the area of ice cover in the Canadian Arctic because of global warming opens up favourable prospects for further development of maritime shipping in this zone. Considering that the routes through the Northwest Passage are the shortest ones of all the routes connecting the Atlantic and Pacific oceans, it is clear that all aspects of this topic are of great importance and relevance. This especially applies to the aspects dedicated to studying the characteristics of appearance, formation, concentration, physical characteristics, trajectory of ice movement and forecasting the area of the ice cover in a given zone, i.e. the characteristics affecting the conditions of ice navigation and serving as determining factors in terms of navigation safety.
 The research examines some of these issues, namely the spread of the ice cover during the period of its maximum formation across Davis Strait and the Labrador Sea (where the routes through the Northwest Passage start) and the establishment of statistical relations between the ice spread and the temperatures of surface water and surface air. The research method to be used: synoptic-climatic and statistical analysis of numerical series of ice cover deviations from its average limit as of April 15 over the period of 1979-2023 within the zone in study.
 Based on the set goal, the study processed raw data on distribution of ice cover across Davis Strait and the Labrador Sea for the period of 1979-2023 and completed its statistical analysis. The results of the analysis showed presence of a statistically significant negative trend and cyclical fluctuations with periods of 3-6, 9, 10 and 13 years in relation to the interannual variability of ice cover distribution for the studied period. Positive trends are also observed in the interannual variability of surface water temperature and surface air temperature. After bringing the original series to a quasi-stationary form, a correlation analysis of the relationships between the ice cover distribution and the temperature of water and air was carried out. The results of the analysis determined zones and points with statistically significant correlation coefficients between them during the year. It turned out that the highest values of coefficients are observed from December to March, and the maximum one occurs in March.
 Systematization and analysis of the ice field across Davis Strait and the Labrador Sea during the period of maximum development made it possible to establish that the spread of ice between 60° and 55° north parallels was the most stable during the studied period, and the least stable was observed in the area below 55° north parallel.
 The results of the conducted research open up prospects for development of methods for forecasting the distribution of ice cover across Davis Strait and the Labrador Sea. This will make ice navigation in this area safer.

Linking Climate Change Information with Crop Growing Seasons in the Northwest Ethiopian Highlands

In Ethiopia, the impacts of climate change are expected to have significant consequences for agriculture and food security. This study investigates both past (1981–2010) and future (2041–2070) climate trends and their influence on the length of the growing season (LGS) in the North-Western Ethiopian highlands. Climate observations were obtained from the National Meteorological Agency of Ethiopia, while the best performing and highest resolution models from the CMIP5 experiment and RCP6 (Coupled Models Intercomparison Project and representative concentration pathway 6) were used for the analysis. Standard statistical methods were applied to compute soil water content, evaluate climate variability and trends, and assess their impact on the length of the growing season. Maximum temperature (tasmax) and minimum temperature (tasmin) inter-annual variability anomalies show that the region has experienced cooler years than hotter years in the past. However, in the future, the coolest years are expected to decrease by −1.2 °C, while the hottest years will increase by +1.3 °C. During the major rainfall season (JJAS), the area has received an adequate amount of rainfall in the past and is very likely to receive similar rainfall in the future. On the other hand, the rainfall amount in the season February to May (FMAM) is expected to assist only with early planting. For the season October to January (ONDJ), the rainfall amount may help lengthen the growing season of JJAS if properly utilized; otherwise, the season has the potential to destroy crops before and during the harvesting time. The soil water content changes in the future remain close to those of the past period. The length of growing seasons has less variable onset and cessation dates, while in the future, the length of the growing period (LGP) of 174 to 177 days will be suitable for short- and long-cycle crops, as well as double cropping, benefiting crop production yield in the North-Western Ethiopian highlands in the future.

Weak interannual variability of sea–air carbon flux in the Tropical Pacific Ocean simulated by CMIP6 models

Air–sea carbon fluxes (FCO2) simulated by 20 CMIP6 models in the pre-industrial control experiments are analyzed. 13 models can simulate the dominant role of the equatorial Pacific (EP) in the interannual variation of global FCO2, which is related to ENSO. Compared with CMIP5, CMIP6 has improved the simulation performance of interannual variation of global FCO2, while for the simulation of FCO2 in the tropical Pacific, most CMIP6 models inherit some biases of their CMIP5 versions. For example, the simulated interannual fluctuation of precipitation leads to excessive interannual variations of the dissolved inorganic carbon (DIC) concentration and then of the partial pressure of CO2 at the sea surface (pCO2sea) in the western tropical Pacific, especially in the warm pool. Another inherited disadvantage is the underestimated interannual fluctuation of FCO2 in the central tropical Pacific from 120ºW to 180ºW. The underestimation includes two aspects: the simulated intensity of the fluctuation is weak, and the negative response region of CO2 outgassing to the ENSO index is narrow. There are two main reasons for the weak interannual fluctuation strength of FCO2 in the models. One is that most models cannot represent the strong interannual variation of 10 m wind speed (vm10) in the central tropical Pacific, and the other is that the interannual fluctuation of pCO2sea in the central tropical Pacific in most models is too weak, which is related to the overestimated interannual variation of sea surface temperature (SST) here. The underestimated spatial range of negative response of CO2 outgassing to the ENSO index is mainly induced by the simulated interannual variations of the vm10 and of the vertical transport of DIC which is related to the vertical upwelling rate. According to the simulation results of CMIP6, the improvement of the simulation performance of the interannual variations of the global and tropical Pacific FCO2 is still dependent on the improvement of the simulation performance of physical climate, such as wind fields, SST, and the entrainment velocity at the bottom of the mixed layer.

Mechanistic simulations of kelp populations in a dynamic landscape of light, temperature, and winter storms

Kelp forests are widely distributed across the coastal ocean, support high levels of biodiversity and primary productivity, and underpin a range of ecosystem services. Laminaria hyperborea is a forest-forming kelp species in the Northeast Atlantic that alters the local environment, providing biogenic structure for a diversity of associated organisms. Populations are strongly affected by light availability, temperature, and storm-related disturbance. We constructed a stage-based, two-season model of L. hyperborea populations along the coast of Great Britain and Ireland to predict biomass across a range of depths, drawing on extensive surveys and data from the literature. Population dynamics were driven by wave exposure, historic winter storm intensity, and simulated interannual variation in temperature and depth-attenuated light intensity, with density-dependent competition for light and space. High biomass was predicted in shallow depths across the domain on suitable substrate, with populations extending deeper in the north and west where light penetration was greater. Detritus production was heavily skewed across years, particularly at greater depths, with 10 % of years comprising more than 50 % of detritus on average below 10 m depth. Annual fluctuations in light and storm intensity produced opposing population oscillations with a ∼6-year period persisting for up to a decade but diminishing sharply with depth. Interannual variation in temperature had minimal impact. Biomass was most sensitive to survival and settlement rates, with negligible sensitivity to individual growth rates. This model highlights the need for an improved understanding of canopy and subcanopy mortality, particularly regarding increasingly frequent heatwaves. Estimations of kelp forest contributions to carbon sequestration should consider the high variability among years or risk underestimating the potential value of kelp forests. Process-based simulations of populations with realistic spatiotemporal environmental variability are a valuable approach to forecasting biotic responses to an increasingly extreme climate.

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.

Future weakening of southeastern tropical Atlantic Ocean interannual sea surface temperature variability in a global climate model

AbstractFuture changes in the southeastern tropical Atlantic interannual sea surface temperature (SST) variability in response to increasing greenhouse gas concentrations are investigated utilizing the global climate model FOCI. In that model, the Coastal Angola Benguela Area (CABA) is among the regions of the tropical Atlantic that exhibits the largest surface warming. Under the worst-case scenario of the Shared Socioeconomic Pathway 5-8.5 (SSP5-8.5), the SST variability in the CABA decreases by about 19% in 2070–2099 relative to 1981–2010 during the model’s peak interannual variability season May–June–July (MJJ). The weakening of the MJJ interannual temperature variability spans the upper 40 m of the ocean along the Angolan and Namibian coasts. The reduction in variability appears to be related to a diminished surface-layer temperature response to thermocline-depth variations, i.e., a weaker thermocline feedback, which is linked to changes in the mean vertical temperature gradient. Despite improvements made by embedding a high-resolution nest in the ocean a significant SST bias remains, which might have implications for the results.

Spatial and Temporal Variation in Water Use Efficiency and Ecosystem Photosynthetic Efficiency in Central Asia

Ecosystem water use efficiency (WUE) and ecosystem photosynthetic efficiency (EPE) are key indicators in studies of the carbon–water cycle in terrestrial ecosystems. Analyses of WUE and EPE can enhance our understanding of the relationship between ecosystem light use efficiency and WUE. Although several studies of individual indexes (i.e., either WUE or EPE) have been conducted, analyses of variation in both WUE and EPE, as well as their relationships, have rarely been conducted. Here, we analyzed spatial and temporal variation in WUE and EPE in Central Asia. Specifically, time trend analysis was conducted to characterize temporal and spatial changes in WUE and EPE in Central Asia from 2001 to 2020 at different altitudes and latitudes. Pearson correlation analysis was used to characterize the effects of precipitation and temperature on WUE and EPE. WUE decreased and EPE increased in Central Asia over the 20-year study period; this might have been due to interannual variations in precipitation and temperature. WUE was highest in August, and EPE was highest in June and July. Substantial spatial heterogeneity in WUE and EPE was observed; WUE was highly variable in Central Asia as well as in western and southern Central Asia. Major changes in EPE were observed in northern, eastern, and southern Central Asia. We also found that both WUE and EPE decreased with the increase in altitude. WUE was positively correlated with temperature and negatively correlated with precipitation, whereas EPE was positively correlated with both temperature and precipitation. The increase in photosynthetic efficiency might be one of the main factors contributing to increases in ecosystem productivity in arid environments. The temporal and spatial variation in WUE and EPE observed in our study will aid ecosystem research, providing a reliable theoretical basis for ecosystem research in areas with scarce large-scale data, integrated water resources management, and ecosystem restoration efforts. Our findings also enhance our understanding of the terrestrial carbon–water cycle and have implications for predicting ecosystem responses to climate change. The results of this study provide insights that will aid studies of the terrestrial carbon–water cycle under the background of climate change. It is of great significance to further study the carbon water cycle in the future.

Peculiarities of interannual variability of near-surface air temperature in the Northern and Southern Hemispheres according to HadCRUT5 archive data

Peculiarities of interannual variability of near-surface air temperature in the Northern and Southern Hemispheres according to HadCRUT5 archive data

Intraseasonal and interannual variability of sea temperature in the Arabian Sea Warm Pool

Abstract. The Arabian Sea Warm Pool (ASWP) is a part of the Indian Ocean Warm Pool, formed in the Arabian Sea before the onset of the Indian summer monsoon. The ASWP has a significant impact on climate change in the Indian Peninsula and globally. In this study, we examined the intraseasonal and interannual variability of sea temperature in the ASWP using the latest Simple Ocean Data Assimilation (SODA) reanalysis dataset. We quantified the contributions of sea surface heat flux forcing, horizontal advection, and vertical entrainment to the sea temperature using the mixed-layer heat budget analysis method. We also used a lead–lag correlation method to examine the relationship between the interannual variability of the ASWP and various large-scale modes in the Indo-Pacific Ocean. We found that the ASWP formed in April and decayed in June; its formation and decay processes were asymmetrical, with the decay rate being twice as fast as the formation rate. During the ASWP development phase, the sea surface heat flux forcing had the largest impact on the mixed-layer temperature with a contribution of up to 85 %. Its impact was divided into the net surface heat flux (0.41–0.50 ∘C per 5 d) and the shortwave radiation loss penetrating the mixed layer (from −0.08 ∘C per 5 d to −0.17 ∘C per 5 d). During the decay phase, the cooling effect of the vertical entrainment on the temperature variation increased (from −0.05 ∘C per 5 d to −0.18 ∘C per 5 d) and dominated the temperature variation jointly with the sea surface heat flux forcing. We also found that the ASWP has strong interannual variability related to the basin warming of the Indian Ocean. The lead–lag correlation indicated that the ASWP had a good synchronous correlation with the Indian Ocean Dipole. The ASWP had the largest correlation coefficient at a lag of 5–7 months of the Niño3.4 index, showing the characteristics of modulation by the El Niño–Southern Oscillation (ENSO). When the El Niño (La Niña) event peaked in the winter of the previous year, the ASWP that occurred before the summer monsoon was more significant (insignificant) in the following year.

Evapotranspiration of advanced perennial bioenergy grasses produced on marginal land in the U.S. Midwest

The production of dedicated energy crops for biofuel and co-products can help develop a sustainable and viable bioeconomy under a changing climate. The co-production of perennial bioenergy and commodity crops in an agricultural landscape has the potential to reduce greenhouse gas emissions and provide numerous ecosystem services. However, as production of advanced, higher-yielding cultivars occurs, their impact on water resources needs to be considered. Estimates of evapotranspiration (ET) of perennial grasses compared to commodity crops are not always consistent in the literature. In this study, ET was estimated using an energy-balance model with Landsat satellite imagery and ground-based weather data to compare the large-scale production of advanced switchgrass cultivars (‘Independence’, ‘Liberty’, and ‘Carthage’), predecessor cultivars (‘Shawnee’ and ‘Sunburst’), and other perennial grasses (big bluestem and a low-diversity mixture) to corn grown continuously on marginal soils in the U.S. Midwest. Results showed significant differences in ET between corn and perennial grass treatments at four of the five field sites. However, differences between crop treatments were not consistent across sites, nor were the differences between advanced and predecessor switchgrass varieties. Production year played a large role in daily and cumulative ET across all sites. Differences in crop biomass yield between establishment and post-establishment years may contribute to these interannual differences. Site and interannual variations in precipitation and temperature may also be major contributing factors. Overall, the results of this study indicate that differences in ET between perennial bioenergy grasses and corn are likely dependent upon location of production and weather conditions.

Decoupling of Arctic variability from the North Pacific in a warmer climate

The sea level pressure variability in the North Pacific modulates the climate of the Arctic and surrounding continents, substantially impacting ecosystems and indigenous communities. Our analysis based on data from the CESM2 Large Ensemble and different Model Intercomparison Project datasets reveals that the interannual variability of Arctic surface air temperature (SAT) gradually decouples from the contemporaneous atmospheric conditions over the North Pacific as external forcing increases in intensity in the future. Future projections show that the North Pacific-Arctic relationship during the fall season consistently weakens in magnitude until the end of this century, and in the 22nd and 23rd centuries, the relationship is negligible throughout the year. We show that under increased greenhouse gas emissions, the regional heat fluxes extensively control the Arctic temperature variability, and the strength of the projected North Pacific-Arctic relationship is strongly dependent on the Arctic sea ice extent. Our results suggest that under future warming, a strong coupling of Arctic SAT with the underlying ocean and a weakening of the meridional pressure gradient driven by an enhanced rate of sea ice retreat will weaken the interannual footprint of North Pacific variability on Arctic SAT. Therefore, we propose that the alarming rate of sea-ice decline over recent decades and projected in the near future could accelerate the rate of decoupling. Further, we suggest that mitigation strategies for the Arctic should focus on regional mechanisms operating on interannual and seasonal timescales.

Human heat health index (H3I) for holistic assessment of heat hazard and mitigation strategies beyond urban heat islands

Certain urban neighborhoods are more susceptible to heat than others, primarily because of the unequal distribution of imperviousness, building and vegetation morphology, social vulnerability, and anthropogenic heat release. Here, we demonstrate that using the surface urban heat island intensity obtained through remote sensing approaches to evaluate urban heat vulnerability (UHV) can be misleading due to the interannual and seasonal variability of rural land surface temperature (LST). We present the disparity in the heat vulnerability index (HVI) when LST and air temperature are used as hazards and show that the LST-based approach overestimates the HVI during daytime. Thus, we contend that while HVI may be appropriate for comparing the relative UHV of different neighborhoods, it should not be used to assess absolute daytime heat vulnerability. To address this limitation, we propose a new metric: human heat health index (H3I) that can be utilized to (i) assess and compare heat hazard in different neighborhoods and (ii) evaluate the effectiveness of environmental interventions for heat mitigation. H3I was applied to demonstrate the reduction in heat hazard due to 3-D urban structures using street-level modeling in Austin, Texas. Our findings emphasize the need for combining 3-D urban data, modeling, and community feedbacks efforts to assess daytime UHV for prioritizing the implementation of heat mitigation strategies.

Snow cover duration in northern Finland and the influence of key variables through a conceptual framework based on observed variations in snow depth

Seasonal snow cover duration is the net result from many processes acting on snow fallen on the Earth's surface. Several of these processes feed back into the atmosphere-cryosphere system causing non-linear interactions. The timing of snow retreat is of essential importance, but the duration of snow cover has large spatiotemporal variabilities. However, from a large data set of observed snow depth changes in northern Finland, systematic similar evolutions are identified that allow for a considerable simplification and reduction of the complexity in snow depth changes. Here, a novel conceptual framework is designed based on dividing the season into two main periods (dark and bright period, based on solar irradiance), for which snow depth decrease is parameterized based on three variables, average temperature, incoming shortwave radiation, and light-absorbing particles (LAP) in the snow. The processes are simplified into two linear relations, and a new formulation for concentration enhancement of LAP, which is dependent on snow depth decrease, is given. The results show that the seasonal snow cover duration is shifted by about one day for every 10 mm snow water equivalent of precipitation. This effect is comparable in scale to that of doubling of the amount of LAP concentration in snow. We also found that the combined shift in snow cover duration from interannual variability in ambient temperature and shortwave radiation (warm and bright vs. cold and dark season) is large enough to explain the variability of a couple of weeks for a given precipitation amount in Northern Finland.

Dryland sensitivity to climate change and variability using nonlinear dynamics

Primary productivity response to climatic drivers varies temporally, indicating state-dependent interactions between climate and productivity. Previous studies primarily employed equation-based approaches to clarify this relationship, ignoring the state-dependent nature of ecological dynamics. Here, using 40 y of climate and productivity data from 48 grassland sites across Mongolia, we applied an equation-free, nonlinear time-series analysis to reveal sensitivity patterns of productivity to climate change and variability and clarify underlying mechanisms. We showed that productivity responded positively to annual precipitation in mesic regions but negatively in arid regions, with the opposite pattern observed for annual mean temperature. Furthermore, productivity responded negatively to decreasing annual aridity that integrated precipitation and temperature across Mongolia. Productivity responded negatively to interannual variability in precipitation and aridity in mesic regions but positively in arid regions. Overall, interannual temperature variability enhanced productivity. These response patterns are largely unrecognized; however, two mechanisms are inferable. First, time-delayed climate effects modify annual productivity responses to annual climate conditions. Notably, our results suggest that the sensitivity of annual productivity to increasing annual precipitation and decreasing annual aridity can even be negative when the negative time-delayed effects of annual precipitation and aridity on productivity prevail across time. Second, the proportion of plant species resistant to water and temperature stresses at a site determines the sensitivity of productivity to climate variability. Thus, we highlight the importance of nonlinear, state-dependent sensitivity of productivity to climate change and variability, accurately forecasting potential biosphere feedback to the climate system.

Projected changes in the interannual variability of surface air temperature using CMIP6 simulations

Projected changes in the interannual variability of surface air temperature using CMIP6 simulations

Estimation of long-term changes in thermal conditions and distribution of Atlantic and Subarctic water in the XXI Century in the Norwegian Sea on area surveys data

Purpose of the work: assessing the spatial and temporal variability of thermal conditions in waters of various origins in the Norwegian Sea in the first decades of the 21st century. Materials: oceanographic data collected during the International Ecosystem Surveys in the Norwegian Sea in 2000–2021. Methods used: comparative data analysis, descriptive statistics methods, correlation analysis. Results: the “boxes”, temperature in which most fully describes the change in the temperature of the Atlantic and Subarctic waters of the Norwegian Sea, were identified. This is confirmed by the high correlation coefficients of temperature in the “boxes” with the water temperature over a wide area of distribution of waters of various origins. The interannual temperature variability in the “boxes” was studied with the separation of warm and cold periods. An assessment of the interannual variability of the distribution boundaries of the Atlantic and subarctic waters is made by the position of isotherms at different horizons. A statistically significant relationship is shown between changes in the temperature of Atlantic and Subarctic waters according to the “boxes” data and changes in the boundaries of the distribution of water masses and the position of the frontal zone between them. Practical significance: the results of the analysis of in situ data from annual areal surveys make it possible to estimate the interannual variability of the thermal state of waters of various origins in the Norwegian Sea in the absence of standard sections and can be used to predict the distribution of pelagic fish in the sea area depending on oceanographic conditions.

The influence of inter-annual temperature variability on the Greenland Ice Sheet volume

Abstract The Greenland Ice Sheet has become an increasingly larger contributor to sea level rise in the past two decades and is projected to continue to lose mass. Climate variability is expected to increase under future warming, but the effect of climate variability on the Greenland Ice Sheet volume is poorly understood and is adding to the uncertainty of the projected mass loss. Here we quantify the influence of inter-annual temperature variability on mass loss from the Greenland Ice Sheet using the PISM model. We construct an ensemble of temperature-forcing fields that accounts for inter-annual variability in temperature using reanalysis data from NOAA-CIRES over the period 1851–2014. We investigate the steady-state and transient response of the Greenland Ice Sheet. We find that the simulated steady-state ice-sheet volume decreases by 1.9 ± 0.4 cm of sea level equivalent when forced with a varying temperature forcing compared to a constant temperature forcing, and by 11.5 ± 1.4 cm when the variability is doubled. The northern basins are particularly sensitive with a change in volume of 0.9–1.1%. Our results emphasize the importance of including temperature variability in projections of future mass loss.

Intensive and extensive margins of the peak load: Measuring adaptation with mixed frequency panel data

In this work we investigate the response of daily electricity peak load to daily maximum temperatures across states in Europe and India. We propose a method that decomposes short- from medium/long-run effects, retains the high frequency nature of the load-weather covariation and treats economic growth as a modulating factor. By simultaneously exploiting variation in unexpected daily weather anomalies and decade-long climatic changes in each location we decompose transitory - intensive margin - adjustments from permanent - extensive margin - adjustments. We find that the shocks over the long-run differ substantially from the short-run dynamics. Furthermore, we find evidence that per capita income modulates the adjustments over the short- and long-run. We project that in response to climate change around 2050 the peak load may increase by up to 20%-30% in Southern Europe and in several states in India, depending on the degree of warming and the evolution of socio-economic conditions. Even with a limited scope to two world regions, we identify that the structure of the economy and differences in future income growth matter in shaping the adaptation to climate change. Our decomposition allows to identify how future weather anomalies can further amplify the relative increase associated to the shift in the climate norm. Assuming that the interannual variability of maximum temperatures follows the distribution observed in the past, we find a doubling of the impacts of climate change during the summer in Europe. Uncertainty around the distribution of future weather anomalies may lead to further unexpected peak load amplifications. Our results have important policy implications for power systems’ generation capacity, transmission and storage, as we show that the challenges to accommodate the peak load in days with extreme temperatures may substantially increase already around mid-century.