Maximum Warming Research Articles

Eocene maar sediments record warming of up to 3.5 °C during a hyperthermal event 47.2 million years ago

Eocene hyperthermal events reflect profound perturbations of the global carbon cycle. Most of our knowledge about their onset, timing, and rates originates from marine records. Hence, the pacing and magnitude of hyperthermal continental warming remains largely unaccounted for due to a lack of high-resolution climate records. Here we use terrestrial biomarkers and carbon isotopes retrieved from varved lake deposits of the UNESCO World Heritage site ‘Messel Fossil Pit’ (Germany) to quantify sub-millennial to millennial-scale temperature and carbon isotope changes across hyperthermal event C21n-H1 (47.2 million years ago). Our results show maximum warming of ca. 3.5 °C during C21n-H1. We propose that two components are responsible for the warming pattern across the hyperthermal: (1) the massive release of greenhouse gases into the atmosphere-ocean system and (2) half-precession orbital forcing indicated by ~12.000-year temperature cycles. The carbon isotope record of bulk organic matter indicates a sharp, 7‰ decrease at the peak of the hyperthermal, corresponding to increased organic carbon content and a shift in the lake algal community. Collectively, our proxy data reveal the structure of continental temperature response during the hyperthermal event that is characterized by overall warming with a superimposed pattern of sub-orbital scale temperature fluctuations.

Aerosol effects during heat waves in summer 2022 and responses to emission change over China

This study explores aerosol direct, indirect, and feedback effects on meteorology and fine particulate matter during heat waves of August 2022 over eastern China by using an online coupled regional climate–chemistry–aerosol model. In this period, aerosols exerted mean direct (DRE) and indirect (IRE) radiative effects of −3.9 Wm−2 and −2.4 Wm−2 at TOA, which totally caused a decrease in average surface air temperature by 0.3 °C over east China, accompanied by decreases in PBLH (planetary boundary layer height) and precipitation and an increase in PM2.5 concentration. With the anthropogenic emission reduction from 2013 to 2022, DRE apparently decreased while IRE changed little, leading to a decrease in total aerosol radiative effect (TRE) by 27% at TOA. The weakened TRE resulted in increases in surface air temperature and precipitation by 0.14 °C and 2.7 mm, respectively, on average over east China, with the maximum warming exceeding 0.5 °C in BTH (Beijing–Tianjin–Hebei province). This study highlights a warming trend due to weakened TRE, which may exacerbate heat wave, and an increasing importance of aerosol IRE relative to DRE due to weak sensitivity of cloud properties to aerosol change during the emission reduction.

Asian monsoonal temperature and environmental changes since the penultimate deglaciation as revealed by alkenones and alkanes in sediments from the northern South China Sea

A new alkenone sea surface temperature (SST) record from the South China Sea (SCS) over the last 170 ka has been reported here. Our analysis of magnetic susceptibility and AMS 14C dating on the top portion of the core suggests that this record dates to the Marine Isotope Stage (MIS) 6. As indicated in Termination I and II, SST changes are correlated with clear glacial/interglacial cycles and likely dominated by atmospheric CO2 and Western Pacific Warm Pool temperature changes. But the two Terminations were different in magnitude. In Termination I, the minimum and maximum SSTs are 24.5 °C and 27.5 °C, respectively, showing a smaller rise (3 °C) than in Termination II (24–28.3 °C). The n-alkane indices, such as average chain length (ACL) and carbon preference index (CPI), exhibited high/low values during glacial/interglacial periods, and possible more arid climate during MIS 6 than MIS 2. During Termination II, the maximum surface warming in the SCS is accompanied by a progressive lag of approximately 7000 years in relation to maximum summer insolation until Termination I, when they are nearly synchronous. According to the study, SSTs are continuously changing and are influenced by solar insolation, global ice volume changes, and ocean–atmosphere interactions across hemispheres.

Investigating the microclimate impacts of blue–green space development in the urban–rural fringe using the WRF-UCM model

Blue–green spaces in the urban–rural fringe (URF) can help restrain endless urban sprawl and urban warming; however, the climate impact of these spaces has not been examined. Based on spatial transformation characteristics within the identified URF areas in Wuhan from 2000 to 2020, this study used the WRF-UCM model to observe microclimate impacts of different development modes and lake reduction in URF blue–green spaces. 1) Urban sprawl increased the average air temperature at 2 m (T2) by 0.82 °C and increased the 10-m wind speed (WS10) by 0.16 m/s in the city centre area. 2) The non-built-up areas (GW_CT) development mode reduced T2, with a maximum hourly cooling effect of 0.13 °C, and the open high-rise (GW_HR) and large low-rise (GW_LL) development modes increased the average nighttime T2 (with maximum hourly warming of 0.22 °C and 0.12 °C, respectively) as well as the WS10. 3) When built-up land expanded outwards and encroached on more than 25.89% of the lake area, the T2 and WS10 at the city centre significantly changed (0.17 °C and 0.1 m/s increased). This paper demonstrates the importance of conducting climate impact assessments for peri-urban blue-green space development.

Ichthyoplankton in the northern part of the Black Sea under prolongation of summer hydrological season in 2020

The species diversity and spatial distribution of ichthyoplankton in the shelf and deep-sea waters of the northern half of the Black Sea near the Crimean Peninsula and the shores of the Caucasus under the conditions of prolongation of the summer hydrological season 2020 for September–October are presented. The high temperatures of the upper layer of the sea, peculiar of the summer spawning season, caused a continuation of productive spawning of warm-water fish. Eggs and larvae of 19 species from 12 families were identified in the ichthyoplankton. The maximum number of eggs was 302 ind./m2, and larvae — 58 ind./m2. Eggs and larvae of the mass commercial species Engraulis encrasicolus (L., 1758) dominated, whose share in the total population was 92.9 and 84.2% respectively. The highest abundance of ichthyoplankton corresponded to areas with minimal dynamic activity and maximum warming within the limits of coastal-shelf quasi-stationary anticyclonic vortices characteristic of the summer hydrological season.

Distinct Impacts of the Central and Eastern Atlantic Niño on the European Climate

AbstractThe Atlantic Niño is the primary interannual variability mode in the tropical Atlantic, with far‐reaching impacts on global climate. A recent study identified two types of the Atlantic Niño, each with its maximum warming centered in the central and eastern equatorial Atlantic, respectively. Through analysis of observational data and numerical model experiments, we find that the two Atlantic Niño types have distinct climatic impacts on Europe. This is because the central Atlantic Niño is associated with a pronounced increase in precipitation in the western tropical Atlantic, while the positive precipitation anomalies during the eastern type are mainly located in the eastern basin with weaker amplitudes. Consequently, compared to the eastern Atlantic Niño, the extra‐tropical atmospheric waves and the associated precipitation and temperature anomalies in Europe during the central type are stronger and shifted westward. Therefore, distinguishing between the two Atlantic Niño types may help improve seasonal climate predictions in Europe.

Spatiotemporal dynamics of Pinus densiflora in the south of the Russian Far East during the Late Pleistocene and the Holocene by pollen records

The aim of the present work is to reconstruct the distribution of Pinus densiflora Siebold & Zucc. in the south of the Russian Far East (SRFE) during the Late Pleistocene (MIS 2) and the Holocene based by pollen records and chronological data. We found that P. densiflora did not grow in SRFE under cold and dry climate of the MIS 2. Warming in the Early Holocene caused the expansion of P. densiflora to the region. Under maximum warming during the Middle Holocene, P. densiflora range reached the Central Subregion of the SRFE. The cooling at the beginning of the Late Holocene caused the decrease of P. densiflora distribution in the SRFE. Under subsequent warming during the second half of the Late Holocene, Pinus densiflora has taken again a dominant position in the Southern and the Central subregions in the SRFE. During the last two centuries, P. densiflora range in the region began to degrade, due to the anthropogenic influence.

Mapping spatial microclimate patterns in mountain forests from LiDAR

Forests create unique microclimates that have the potential to serve as microrefugia for species under climate change. Yet, our understanding of the heterogenous thermal patterns at the forest floor of complex landscapes (e.g., in mountain forests) remains incomplete. We here used Light Detection and Ranging (LiDAR) for predicting summer temperature offsets in a mountain forest landscape in the European Alps. We calibrated models on a network of 150 microclimate loggers that were combined with data from 15 meteorological stations to estimate the maximum, mean, and minimum temperature offsets, using LiDAR-derived metrics of forest structure and topography as predictors. Models predicted summer temperature offsets with an R²/RMSE of 0.50/3.15 °C for maximum temperature, 0.51/0.41 °C for mean temperature and 0.55/0.57 °C for minimum temperature. Forest canopy openness and elevation were most important for predicting temperature offsets. The mean offset ranged from – 1.9 °C to 2.7 °C (mean of - 0.3 °C), but both minimum and maximum offsets varied considerably, with some forests even having warmer maximum and colder minimum temperatures than open areas. This was particularly prominent in forests of the subalpine zone, which are characterized by open canopies and a considerable presence of coniferous shrubs. In contrast, submontane forests with largely closed canopies had mostly colder maximum and warmer minimum temperatures within forests compared to open areas. Analysing the development of temperature offsets with time since disturbance, we found that recently disturbed forests had higher maximum temperatures compared to open areas, but they recovered to closed forest conditions within two decades. We conclude that mountain forests exhibit complex microclimate patterns that vary strongly with forest type and canopy openness. We further highlight that disturbances are an important driver of spatiotemporal dynamics in forest microclimate. Finally, temperature offset maps such as the ones generated here have strong potential to improve the robustness of species distribution models and to assess climate risks for biodiversity.

Interannual variability of sea surface temperature at the polar latitudes of the Atlantic Ocean

The general regularities and regional differences in the interannual variability of the sea surface temperature in the polar latitudes of the Atlantic Ocean are revealed according to the OI SST reanalysis data for period 1982—2017. The reanalysis contains daily average sea surface temperature values at the nodes of a regular grid 0,25°×0,25°. In this work, areas where the ice concentration did not exceed
 90 % were analyzed. In both polar basins, the position of areas with a high level of sea surface temperature
 interannual variability qualitatively coincides with the position of intense currents. The maximum values of
 linear sea surface temperature trends are observed in areas of the maximum level of interannual variability,
 while the trends in long-term sea surface temperature variability in the Arctic and Antarctic are noticeably
 different. Significant positive sea surface temperature trends prevail in the Atlantic sector of the Arctic.
 Significant negative trends have been identified only off the northeastern coast of Greenland and north of the Arctic Current. The sea surface temperature decrease on a long-term scale in this area is associated with an increase of cold water transport by the East Greenland and Arctic currents, which are formed as a result
 of the intensive melting of Arctic ice observed in recent decades. In the Atlantic sector of the Antarctic, on the contrary, significant negative sea surface temperature trends prevail. In the Arctic, the maximum values of positive sea surface temperature trends are observed in August—September during the period of maximum warming of surface waters and minimum concentration of drifting ice. In the Antarctic, the maximum negative sea surface temperature trends in absolute value are observed from August to October, during the period of surface water cooling and maximum ice concentration.

Sea Coast of the Western Part of the Russian Arctic under Climate Change: Dynamics, Technogenic Influence and Potential Economic Damage

The Arctic coast dynamics has been an urgent problem over the last years, from both a practical and a fundamental point of view. In this research, for the first time for the Russian Arctic coast, we assessed the damage from the loss of territories in the western part of the Russian Arctic, where the active production and transportation of hydrocarbon material are carried out. Most of the studied coastline is composed of frozen unlithified soils with inclusions of underground ice. In this regard, the coastal zone is highly sensitive to climate change and its economic consequences. According to our investigation and literature data, the erosion rates could rich up to 2–3 m/year in some part of the coastline. Having estimated the cadastral cost of land and the area of the possible loss of territory, as well as the cost of transport infrastructure in the risk zone, we tried to predict the damage from changes in the total structure of the area under consideration. In particular, the economic damages from coastal permafrost processes were estimated. The assessment was conducted for the middle of the 21st century, taking into account the current climatic trend, erosion rate and probable maximum warming in this region.

Integrated techno-economic and life cycle assessment of shared circular business model based blockchain-enabled dynamic grapevoltaic farm for major grape growing states in India

Grape farms face many climate risks during cultivation, and regulatory and sustainability-related challenges after the harvest. To support the farmers, Government of India (GoI) aims to promote adaptive capacity throughout the grape value chain by improving resilient infrastructure. This paper proposes a novel Grapevoltaics farm design based on shared circular business model principles where resources like energy, water, and land are shared between grape farmer and solar plant operator. The resilience (in the near term) and sustainability (in the long term) of such multifunctional systems may be influenced by the decisions taken by the involved stakeholders in terms of resource sharing and support extension when facing climate risk events. To address stakeholder engagement, the proposed Grapevoltaic farms leverage blockchain smart contract, making them Blockchain-enabled Grapevoltaics (BCeDGVs). To understand the feasibility, 1-ha Grapevoltaic farm is modeled for 12 grape growing regions accross India and analysed using Resilience Performance, Life Cycle Analysis, and Techno-Economic (RePLiCATE) approach. The results show that the solar panels provide resilience support based on the rules of engagement written on blockchain smart contracts. The BCeDGVs has 1295.28–2908.08 kWh/kWp/day electricity generation potential across India with a lifetime average of 15,380.65 MWh even after considering the national average photovoltaic degradation rate of 1.9%. The observed grape yields vary between 2 and 31.25 Mt/ha with an average yield of 45 Mt/ha (table grape) and 40 Mt/ha (wine grape), and the rainwater harvest varies between 1.23 to 7.32 Ml. The economic assessment revealed that grape farmers and photovoltaic plant operators across India under BCeDGVs could have revenues ranging between INR 56.25 to 225 million and INR 29.48–66.19 million, respectively, suggesting to relook into the feed-in tariffs and crop selling prices. The environmental sustainability results suggest that 1.984 ha/MW land-use mitigation and 12–100% reduction in groundwater dependency are possible while maintaining the minimum and maximum national average global warming potentials as 0.074 and 0.088 kg CO2-eq./kg grape, respectively. Overall, the integrated assessments find that the BCeDGVs may promote low carbon, climate resilient grape cultivation in India and has possible integration with GoI's GrapeNet platform. This study highlights a new research direction symbiotic grape farms and energy networks.

МОДЕЛИРОВАНИЕ ЦВЕТЕНИЯ ВОДЫ В КУЙБЫШЕВСКОМ ВОДОХРАНИЛИЩЕ В ГОДЫ С РАЗЛИЧНЫМ РЕЖИМОМ РЕГУЛИРОВАНИЯ СТОКА

The article studies the influence that the dynamics of currents have on algal blooms in the Kuibyshev Reservoir in the conditions of an unsteady flow regime. One of the ways to improve the ecological condition of the reservoir is to reduce cyanobacteria blooms by increasing the flow rate during the maximum warming of the water. The hydrodynamics of the aquatic environment is considered as a regulatory factor that reduces the negative effects of eutrophication and improves the quality of water in the reservoir. The author performed full-scale hydroecological observations in the summer periods of 2016 and 2017 and made model calculations of the dynamics of currents and spatial distribution of phytoplankton in the water area of the Kuibyshev Reservoir. As a result, the dependence of the chlorophyll a index (Chl a) on the flow regulation regime was established. The proposed model is based on the equations of long-wave hydrodynamics, known as the shallow-water equations, the equations of convective transport and development of the components of the ecosystem, which is implemented in the author’s software environment VOLNA. The model is constructed for the near-dam water area on a regular rectangular grid with a step of 200 m. The model was verified on the basis of data from field observations, and the quality of the calculations performed was evaluated. It has been found that the phytoplankton biomass index (Chl a) is related to the water flow velocity non-linearly and varies according to a power law. The conducted studies give reason to believe that the intensity of cyanobacteria blooms largely depends not on the water content of the year, but on the intra-annual redistribution of runoff.

Lateglacial paleoglacier and paleoclimate reconstructions in the north-western Italian Alps

Lateglacial (19.0–11.7 ka ago) paleo-temperature records in the Western European Alps document several short-term cooling episodes within the general post-Last Glacial Maximum warming trend, in phase with North Hemisphere climatic oscillations. Alpine paleo-precipitation reconstructions are instead rare, and further constraints are needed in order to assess whether Lateglacial cold periods were associated with a modified atmospheric circulation pattern over the European Alps. The Alpine paleoglacial record offers a quantitative framework to investigate Lateglacial paleoclimatic conditions and glacier sensitivity in response to both temperature and precipitation changes. Through the combination of 10Be surface-exposure dating of glacial landforms and deposits constraining ice front and surface, together with numerical glacier simulations (iSOSIA), our study aims to reconstruct in space and time the main Lateglacial ice stages and associated paleo-climatic conditions in three tributary valleys (Valpelline, Valsavarenche and Val di Cogne) located within the Dora Baltea catchment (north-western Italian Alps). Our dating-modelling approach reveals in all the three investigated sectors two distinct paleoglacier stages at ca. 13 and 11 ka, documenting respectively the ice configurations at the transition between the Oldest Dryas cold period and the Bølling-Allerød interstadial, and between the Younger Dryas cold period and the early Holocene warming. Numerical ice-simulation outcomes suggest a similar-to-today precipitation pattern during the two ice stages, with either same absolute or homogeneously decreased precipitation values over the Dora Baltea catchment, although a unique quantitative solution of paleo-precipitation magnitudes could not be constrained from our dataset. Using present-day precipitation pattern and magnitude, our results provide paleo-temperature offsets from present-day between −3.3 and −3.8 °C for the older glacial stage, and −2.7 to −3.2 °C for the younger glacial stage, coinciding with the upper range of paleo-temperature reconstructions from other paleoclimatic proxies. Finally, Alpine glaciers’ sensitivity to climate fluctuations differ significantly between the investigated catchments, with a much higher glacier sensitivity to changes in the Equilibrium Line Altitude in the northern (Valpelline) compared to the southern (Valsavarenche and Val di Cogne) tributaries, reflecting different topographic and/or climatic conditions between the three valleys.

Spatial Homogenization Adjustment and Application of Weather Station Networks in Xinjiang, China

In this study, we define the S0 value (buffer zone area centred on a meteorological station) and two inhomogeneity measurement parameters, the station domain area and station network density, for 89 weather stations in the Xinjiang region, and we construct the weight coefficient of the station network according to the station domain area. Applying the weight coefficient, we calculate the mean temperature, maximum temperature, and minimum temperature in January, April, July, October, and annually in the Xinjiang region from 1961 to 2021. The results show that the S0 value of 200,000 km2 is suitable for determining the weight coefficient of the station network in the Xinjiang region. The two measurement parameters can quantitatively reflect the inhomogeneity of the distribution of 89 weather stations in the Xinjiang region. The spatial distribution density of the station network is positively proportional to the station network density and inversely proportional to the station domain area and weight coefficient of the stations. The equal-weighted average is lower than the spatially homogenized revised average, which underestimates the mean temperature in the Xinjiang region, and the spatially homogenized revised average better reflects the real temperature in the Xinjiang region. The annual and monthly mean temperatures, maximum and minimum temperatures calculated by the spatially homogenized revised average, and the equal-weighted average have the same upwards trend, and the mean temperature warming trend calculated by the two methods have differences, but the differences are not significant. The annual, January, April, July, and October minimum temperature warming trends according to the spatial homogenization revised average are greater than the maximum temperature warming trend and the mean temperature warming trend, and the annual minimum temperature warming trend is 3.3 times the annual maximum warming trend and two times the annual mean temperature.

The Paris Climate Agreement as Benchmark for Buildings and Companies

The real estate market has a high obligation, but also many opportunities, to tackle climate change. The real estate sector is responsible for 40% of energy consumption and 36% of CO2 emissions in the EU. The global temperature must not rise by more than 1.5° Celsius compared to pre-industrial times in order to avert serious consequences of climate change. 195 countries agreed on this target by signing the Paris Climate Agreement in 2015 and thus also set the legislative framework and the desired direction of development for societies, companies and buildings. The Paris Climate Agreement can be used to establish a benchmark by showing which development routes are necessary to be compliant with the Agreement. It can be examined which adjustments are necessary to limit maximum global warming to 1.5° Celsius. By matching specific properties against such a benchmark, it can be worked out which properties are at risk of no longer being usable/rentable because they cannot meet the expected increases in environmental regulations, CO2 pricing, building standards and market expectations. This can be used to address transitory climate change risks.

Can Norway become a net-zero economy under scenarios of tourism growth?

The Paris Agreement suggests that all countries engage in significant emission reductions. To stay within safe guardrails, usually defined as a maximum warming of 1.5 °C compared to pre-industrial times, this will mean decarbonisation within less than 30 years. This significant challenge is complicated because of growth in some sectors, such as tourism. This paper analyses emissions and economic output in Norway, considering national Tourism Satellite Accounts. Novel aspects of this paper include a longitudinal perspective covering 12 years through which critical developments and progress on emission reduction pathways can be assessed. Findings suggest that the carbon intensity of tourism (emissions per NOK) is more than twice the Norwegian economy average. Aviation in particular is a major barrier to emission reductions, as it generates 17% of national tourism revenue and 75% of direct tourism emissions. Trend extrapolation shows that tourism will be the largest emission sub-sector of the Norwegian economy by 2030. The Norwegian economy will have to decarbonise at a rate more than 30 times faster than its current rate, if it is to decarbonise to mid-century, while continuing on its observed economic growth trajectory.

Estimating the impact of the 1991 Pinatubo eruption on mesospheric temperature by analyzing HALOE (UARS) temperature data

Abstract. The Mt. Pinatubo eruption in 1991 had a severe impact on the Earth system, with a well-documented warming of the tropical lower stratosphere and a general cooling of the surface. This study focuses on the impact of this event on the mesosphere by analyzing solar occultation temperature data from the Halogen Occultation Experiment (HALOE) instrument on the Upper Atmosphere Research Satellite (UARS). Previous analyses of lidar temperature data found positive temperature anomalies of up to 12.9 K in the upper mesosphere that peaked in 1993 and were attributed to the Pinatubo eruption. Fitting the HALOE data according to a previously published method indicates a maximum warming of the mesosphere region of 4.1 ± 1.4 K and does not confirm significantly higher values reported for that lidar time series. An alternative fit is proposed that assumes a more rapid response of the mesosphere to the volcanic event and approximates the signature of the Pinatubo with an exponential decay function having an e-folding time of 6 months. It suggests a maximum warming of 5.4 ± 3.0 K, if the mesospheric perturbation is assumed to reach its peak 4 months after the eruption. We conclude that the HALOE time series probably captures the decay of a Pinatubo-induced mesospheric warming at the beginning of its measurement period.

Exceptional warming over the Barents area

In recent decades, surface air temperature (SAT) data from Global reanalyses points to maximum warming over the northern Barents area. However, a scarcity of observations hampers the confidence of reanalyses in this Arctic hotspot region. Here, we study the warming over the past 20–40 years based on new available SAT observations and a quality controlled comprehensive SAT dataset from the northern archipelagos in the Barents Sea. We identify a statistically significant record-high annual warming of up to 2.7 °C per decade, with a maximum in autumn of up to 4.0 °C per decade. Our results are compared with the most recent global and Arctic regional reanalysis data sets, as well as remote sensing data records of sea ice concentration (SIC), sea surface temperature (SST) and high-resolution ice charts. The warming pattern is primarily consistent with reductions in sea ice cover and confirms the general spatial and temporal patterns represented by reanalyses. However, our findings suggest even a stronger rate of warming and SIC-SAT relation than was known in this region until now.

Application of remote sensing data for monitoring eutrophication of floodplain water bodies

The aim of this article was to investigate the influence of structural features of the floodplain water network on the spatial and temporal dynamics of chlorophyll-a concentration as an indicator of eutrophication. The research was conducted in the waters of the “Dnipro-Orilskiy” Nature Reserve. The geographic information base with polygonal objects which represented water bodies of the reserve was created on the basis of detailed geographical maps and the high resolution space images. The water bodies were characterized using such parameters as the distance of the water body centroid from the nearest shore of the Dnipro River, the area of the water body, the order of the water body and the connectivity of the water body. Chlorophyll-а concentration was estimated based on the surface algal bloom index. The information was obtained about 148 water bodies, 141 of which are water bodies in the floodplain of the Dnipro River. The area of floodplain water bodies within the reserve was 3.28 million m2. The area of floodplain water bodies ranged from 300–232,500 m2. Trophic State Index allows us to estimate the trophic level of Dnipro River waters as mesotrophic, water bodies of first and second order as eutrophic, and water bodies of third and fourth order as hypereutrophic. The dynamics of chlorophyll-a content in water followed the seasonal course of temperatures. The concentration was lowest in the cold period of the year and reached its maximum in the second half of summer. The autumn decrease occurred at the end of September. The seasonal course of air temperature was superimposed on the peculiarities of the temperature regime of a particular water body, which depended on its depth and flow rate. The time, water body area, distance from the Dnipro River channel, connectivity and order of water bodies were the statistically significant predictors of chlorophyll concentration in water and were able to explain 85% of the variation of this indicator. The increase in chlorophyll-a concentration with increasing order of a water body is due to a decrease in the intensity of water exchange and a decrease in the depth of water bodies of higher order. An increase in the order of a water body is accompanied by a branching network of water bodies, the ability of water bodies to clear sediments decreases. Sediment accumulation leads to a decrease in their depth. Warming of shallow ponds and accumulation of organic matter in them are factors of intensive growth of blue-green algae. The evacuation of surplus organic matter, which results from mass vegetation development with excessive nutrient inputs, is a key driver of the eutrophic regime of water bodies. The increasing importance of regulatory processes develops in agreement with an increase in chlorophyll-a concentration in a water body. The importance of the considered factors reaches the highest level in summer time, when simultaneous maximum warming of water bodies and minimum water level in them take place. Accordingly, the differences between deep and relatively cool water bodies and shallow water bodies that warm up quickly, which significantly stimulates the growth of organic mass, reach the greatest contrast. The spatial patterns of variation in chlorophyll-a concentration have a complex multiscale structure, indicating the multiple nature of the acting factors. The spatial variability was represented as a composition of broad-scale and medium-scale spatial processes. The broad-scale process is most dependent on connectivity, whereas for the medium-scale process the leading one is the effect of water body order.

Seasonality in Arctic Warming Driven by Sea Ice Effective Heat Capacity

Abstract Arctic surface warming under greenhouse gas forcing peaks in winter and reaches its minimum during summer in both observations and model projections. Many mechanisms have been proposed to explain this seasonal asymmetry, but disentangling these processes remains a challenge in the interpretation of general circulation model (GCM) experiments. To isolate these mechanisms, we use an idealized single-column sea ice model (SCM) that captures the seasonal pattern of Arctic warming. SCM experiments demonstrate that as sea ice melts and exposes open ocean, the accompanying increase in effective surface heat capacity alone can produce the observed pattern of peak warming in early winter (shifting to late winter under increased forcing) by slowing the seasonal heating rate, thus delaying the phase and reducing the amplitude of the seasonal cycle of surface temperature. To investigate warming seasonality in more complex models, we perform GCM experiments that individually isolate sea ice albedo and thermodynamic effects under CO2 forcing. These also show a key role for the effective heat capacity of sea ice in promoting seasonal asymmetry through suppressing summer warming, in addition to precluding summer climatological inversions and a positive summer lapse-rate feedback. Peak winter warming in GCM experiments is further supported by a positive winter lapse-rate feedback, due to cold initial surface temperatures and strong surface-trapped warming that are enabled by the albedo effects of sea ice alone. While many factors contribute to the seasonal pattern of Arctic warming, these results highlight changes in effective surface heat capacity as a central mechanism supporting this seasonality. Significance Statement Under increasing concentrations of atmospheric greenhouse gases, the strongest Arctic warming has occurred during early winter, but the reasons for this seasonal pattern of warming are not well understood. We use experiments in both simple and complex models with certain sea ice processes turned on and off to disentangle potential drivers of seasonality in Arctic warming. When sea ice melts and open ocean is exposed, surface temperatures are slower to reach the warm-season maximum and slower to cool back down below freezing in early winter. We find that this process alone can produce the observed pattern of maximum Arctic warming in early winter, highlighting a fundamental mechanism for the seasonality of Arctic warming.