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Seasonality in photosynthetic activity is a critical component of seasonal carbon, water and energy cycles in the Earth system. This characteristic is a consequence of plant's adaptive evolutionary processes to a given set of environmental conditions. Changing climate in northern lands (>30°N) alters the state of climatic constraints on plant growth, and therefore, changes in the seasonality and carbon accumulation are anticipated. However, how photosynthetic seasonality evolved to its current state, and what role climatic constraints and their variability played in this process and ultimately in carbon cycle is still poorly understood due to its complexity. Here, we take the 'laws of minimum' as a basis and introduce a new framework where the timing (Day of Year) of peak photosynthetic activity (DOYP max ) acts as a proxy for plant's adaptive state to climatic constraints on its growth. Our analyses confirm that spatial variations in DOYP max reflect spatial gradients in climatic constraints as well as seasonal maximum and total productivity. We find a widespread warming-induced advance in DOYP max (-1.66 ± 0.30 days decade-1 , P < 0.001) across northern lands, indicating a spatio-temporal dynamism of climatic constraints to plant growth. We show that the observed changes in DOYP max are associated with an increase in total gross primary productivity through enhanced carbon assimilation early in the growing season, which leads to an earlier phase shift in land-atmosphere carbon fluxes and an increase in their amplitude. Such changes are expected to continue in the future based on our analysis of Earth System Model (ESM) projections. Our study provides a simplified, yet realistic framework based on first principles for the complex mechanisms by which various climatic factors constrain plant growth in northern ecosystems.

Climate change impacts the electric power system by affecting both the load and generation. It is paramount to understand this impact in the context of renewable energy as their market share has increased and will continue to grow. This study investigates the impact of climate change on the supply of renewable energy through applying novel metrics of intermittency, power production and storage required by the renewable energy plants as a function of historical climate data variability. Here we focus on and compare two disparate locations, Palma de Mallorca in the Balearic Islands and Cordova, Alaska. The main results of this analysis of wind, solar radiation and precipitation over the 1950–2020 period show that climate change impacts both the total supply available and its variability. Importantly, this impact is found to vary significantly with location. This analysis demonstrates the feasibility of a process to evaluate the local optimal mix of renewables, the changing needs for energy storage as well as the ability to evaluate the impact on grid reliability regarding both penetration of the increasing renewable resources and changes in the variability of the resource. This framework can be used to quantify the impact on both transmission grids and microgrids and can guide possible mitigation paths., P.C. and D.G. acknowledge financial support from Ministerio de Ciencia e Innovación (Spain), the Agencia Estatal de Investigación (AEI, Spain), and the Fondo Europeo de Desarrollo Regional (FEDER, EU) under grant PACSS (RTI2018-093732-B-C22) and the Maria de Maeztu program for Units of Excellence in R&D (MDM-2017-0711). D.N. gratefully acknowledges support from DOE Project GMLC 1.5.02—Resilient Alaskan Distribution system Improvements using Automation, Network analysis, Control, and Energy storage (RADIANCE). U.S.B. acknowledges support from the National Science Foundation under award #OIA-1753748 and by the State of Alaska for material which this work is based upon.

The late-season extreme fire activity in Southcentral Alaska during 2019 was highly unusual and consequential. Firefighting operations had to be extended by a month in 2019 due to the extreme conditions of hot summer temperature and prolonged drought. The ongoing fires created poor air quality in the region containing most of Alaska&rsquo, s population, leading to substantial impacts to public health. Suppression costs totaled over $70 million for Southcentral Alaska. This study&rsquo, s main goals are to place the 2019 season into historical context, provide an attribution analysis, and assess future changes in wildfire risk in the region. The primary tools are meteorological observations and climate model simulations from the NCAR CESM Large Ensemble (LENS). The 2019 fire season in Southcentral Alaska included the hottest and driest June&ndash, August season over the 1979&ndash, 2019 period. The LENS simulation analysis suggests that the anthropogenic signal of increased fire risk had not yet emerged in 2019 because of the CESM&rsquo, s internal variability, but that the anthropogenic signal will emerge by the 2040&ndash, 80 period. The effect of warming temperatures dominates the effect of enhanced precipitation in the trend towards increased fire risk.

Questions How do plant communities on zonal loamy vs. sandy soils vary across the full maritime Arctic bioclimate gradient? How are plant communities of these areas related to existing vegetation units of the European Vegetation Classification? What are the main environmental factors controlling the transitions of vegetation along the bioclimate gradient? Location 1700‐km Eurasia Arctic Transect (EAT), Yamal Peninsula and Franz Josef Land (FJL), Russia. Methods The Braun‐Blanquet approach was used to sample mesic loamy and sandy plots at 14 total study sites at six locations, one in each of the five Arctic bioclimate subzones and the forest‐tundra transition. Trends in soil factors, cover of plant growth forms (PGFs), and species diversity were examined along the summer‐warmth‐index (SWI) gradient and on loamy and sandy soils. Classification and ordination were used to group the plots and to test relationships between vegetation and environmental factors. Results Clear, mostly nonlinear, trends occurred for soil factors, vegetation‐structure, and species diversity along the climate gradient. Cluster analysis revealed seven groups with clear relationships to subzone and soil texture. Clusters at the ends of the bioclimate gradient (forest‐tundra and polar desert) had many highly diagnostic taxa, whereas clusters from the Yamal Peninsula had only a few. Axis 1 of a Detrended Correspondence Analysis was strongly correlated with latitude and summer warmth; Axis 2 was strongly correlated with soil moisture, percentage sand, and landscape age. Conclusions Summer temperature and soil texture have clear effects on tundra canopy structure and species composition, with consequences to ecosystem properties. Each layer of the plant canopy has a distinct region of peak abundance along the bioclimate gradient. The major vegetation types are weakly aligned with described classes of the European Vegetation Checklist indicating a continuous floristic gradient rather than distinct subzone regions. The study provides ground‐based vegetation data for satellite‐based interpretations of the western maritime Eurasian Arctic, and the first vegetation data from Hayes Island, Franz Josef Land, which is strongly separated geographically and floristically from the rest of the gradient and most susceptible to ongoing climate change. This article is protected by copyright. All rights reserved.

This synthesis study assesses recent changes of Arctic Ocean physical parameters using a unique collection of observations from the 2000s and places them in the context of long-term climate trends and variability. Our analysis demonstrates that the 2000s were an exceptional decade with extraordinary upper Arctic Ocean freshening and intermediate Atlantic water warming. We note that the Arctic Ocean is characterized by large amplitude multi-decadal variability in addition to a long-term trend, making the link of observed changes to climate drivers problematic. However, the exceptional magnitude of recent high-latitude changes (not only oceanic, but also ice and atmospheric) strongly suggests that these recent changes signify a potentially irreversible shift of the Arctic Ocean to a new climate state. These changes have important implications for the Arctic Ocean’s marine ecosystem, especially those components that are dependent on sea ice or that have temperature-dependent sensitivities or thresholds. Addressing these and other questions requires a carefully orchestrated combination of sustained multidisciplinary observations and advanced modeling.

The causes of a greening trend detected in the Arctic using the normalized difference vegetation index (NDVI) are still poorly understood. Changes in NDVI are a result of multiple ecological and social factors that affect tundra net primary productivity. Here we use a 25 year time series of AVHRR-derived NDVI data (AVHRR: advanced very high resolution radiometer), climate analysis, a global geographic information database and ground-based studies to examine the spatial and temporal patterns of vegetation greenness on the Yamal Peninsula, Russia. We assess the effects of climate change, gas-field development, reindeer grazing and permafrost degradation. In contrast to the case for Arctic North America, there has not been a significant trend in summer temperature or NDVI, and much of the pattern of NDVI in this region is due to disturbances. There has been a 37% change in early-summer coastal sea-ice concentration, a 4% increase in summer land temperatures and a 7% change in the average time-integrated NDVI over the length of the satellite observations. Gas-field infrastructure is not currently extensive enough to affect regional NDVI patterns. The effect of reindeer is difficult to quantitatively assess because of the lack of control areas where reindeer are excluded. Many of the greenest landscapes on the Yamal are associated with landslides and drainage networks that have resulted from ongoing rapid permafrost degradation. A warming climate and enhanced winter snow are likely to exacerbate positive feedbacks between climate and permafrost thawing. We present a diagram that summarizes the social and ecological factors that influence Arctic NDVI. The NDVI should be viewed as a powerful monitoring tool that integrates the cumulative effect of a multitude of factors affecting Arctic land-cover change.

[1] El Nino–Southern Oscillation (ENSO) variability was found to be sensitive to the land surface energy budget from a comparison of two integrations of the coupled general circulation model of Center for Ocean-Land-Atmosphere Studies, a control simulation in which global soil wetness in the three layers is predicted, and a sensitivity experiment in which deep soil moisture is specified. In contrast to the control experiment, in which the net land surface energy flux is zero, the sensitivity experiment leads to land becoming a unphysical and unexpected net energy sink. However, the comparison points toward a physically realizable mechanism by which ENSO can be influenced by changes in land surface properties. The net energy sink causes cooling tropical land surface. The cooling over tropical land is connected with the mean state changes of the coupled system, including a shift in the land/sea partitioning of precipitation toward the oceans, a more westerly wind stress over the tropical Pacific, and a more El Nino-like mean state of the tropical Pacific with a weaker east-west temperature contrast. Meanwhile, sea surface temperature (SST) variance decreases in the central and eastern tropical Pacific, and the ENSO becomes less energetic. A series of diagnostic simulations using an intermediate coupled model tests the impact of the simulated mean state and atmospheric noise changes on the ENSO variability. It is demonstrated that the mean state change plays a key role in determining the ENSO variance change. The mean state change in the sensitivity experiment causes a reduction in the sensitivity of ENSO SST variability to surface wind stress, and is consistent with a decrease in ENSO SST variance.

Numerous studies have evaluated the dynamics of Arctic tundra vegetation throughout the past few decades, using remotely sensed proxies of vegetation, such as the normalized difference vegetation index (NDVI). While extremely useful, these coarse-scale satellite-derived measurements give us minimal information with regard to how these changes are being expressed on the ground, in terms of tundra structure and function. In this analysis, we used a strong regression model between NDVI and aboveground tundra phytomass, developed from extensive field-harvested measurements of vegetation biomass, to estimate the biomass dynamics of the circumpolar Arctic tundra over the period of continuous satellite records (1982-2010). We found that the southernmost tundra subzones (C-E) dominate the increases in biomass, ranging from 20 to 26%, although there was a high degree of heterogeneity across regions, floristic provinces, and vegetation types. The estimated increase in carbon of the aboveground live vegetation of 0.40 Pg C over the past three decades is substantial, although quite small relative to anthropogenic C emissions. However, a 19.8% average increase in aboveground biomass has major implications for nearly all aspects of tundra ecosystems including hydrology, active layer depths, permafrost regimes, wildlife and human use of Arctic landscapes. While spatially extensive on-the-ground measurements of tundra biomass were conducted in the development of this analysis, validation is still impossible without more repeated, long-term monitoring of Arctic tundra biomass in the field.